Update app.py

app.py

@@ -1,5 +1,6 @@
 import os
 import gradio as gr
+import numpy as np
 import pandas as pd
 import datetime
 import plotly.express as px
@@ -54,10 +55,12 @@ def _pick_col(df, candidates):
             return norm[cand]
     return None
 
-def _kblocks_to_tib(kblocks):
-    # KiB blocks -> TiB (so 104149210112 -> ~97.0)
+def _kblocks_to_tib(kblocks):  # shown as "TB" per your convention
     return kblocks / (1024**3)
 
+def _kblocks_to_gib(kblocks):  # shown as "GB"
+    return kblocks / (1024**2)
+
 def plot_disks(alert_threshold_pct=99.0):
     df = datasets.load_dataset(
         "pluslab/PLUS_Lab_GPUs_Data",
@@ -88,61 +91,54 @@ def plot_disks(alert_threshold_pct=99.0):
     else:
         df["Label"] = df[server_col].astype(str) + " • " + df[fs_col].astype(str)
 
-    # Totals & pct (compute ourselves)
+    # Totals & pct
     df["Total_kb"] = df[used_col] + df[avail_col]
     df["Used_pct"] = (df[used_col] / df["Total_kb"]) * 100.0
     df["Used_pct"] = df["Used_pct"].clip(0, 100)
     df["Avail_pct"] = (100.0 - df["Used_pct"]).clip(0, 100)
 
-    # Sizes in TiB (shown as "TB")
+    # Sizes
     df["Used_TB"]  = _kblocks_to_tib(df[used_col])
-    df["Avail_TB"] = _kblocks_to_tib(df[avail_col])
     df["Total_TB"] = _kblocks_to_tib(df["Total_kb"])
+    df["Avail_GB"] = _kblocks_to_gib(df[avail_col])  # <-- GB for hovers
 
-    # Alert rows
+    # Alerts
     df["ALERT"] = df["Used_pct"] > alert_threshold_pct
 
-    # Sort by total desc
+    # Sort
     df = df.sort_values("Total_kb", ascending=False).reset_index(drop=True)
 
-    # Display text
-    used_text  = [f"{u:.1f} TB ({p:.0f}%)" for u, p in zip(df["Used_TB"], df["Used_pct"])]
-    total_text = [f"{t:.1f} TB" for t in df["Total_TB"]]
-    avail_text = [f"{a:.1f} TB" for a in df["Avail_TB"]]
+    y_labels = np.where(df["ALERT"].to_numpy(), "⚠ " + df["Label"], df["Label"])
 
-    # Pro palette + alert accent
-    COLOR_TOTAL = "#CBD5E1"  # slate-300
-    COLOR_USED  = "#2563EB"  # blue-600
-    COLOR_FREE  = "#94A3B8"  # slate-400
-    COLOR_ALERT = "#F59E0B"  # amber-500 (dashboard alert)
-    COLOR_OKTXT = "#0F172A"  # slate-900
-    COLOR_ALTXT = "#B45309"  # amber-700
+    used_text   = [f"{u:.2f} TB ({p:.0f}%)" for u, p in zip(df["Used_TB"], df["Used_pct"])]
+    total_annot = [f"{t:.2f} TB" for t in df["Total_TB"]]
+    avail_gb_0  = [f"{g:.0f} GB" for g in df["Avail_GB"]]
 
-    # Used color per row (highlight alerts)
+    # Colors
+    COLOR_TOTAL = "#CBD5E1"
+    COLOR_USED  = "#2563EB"
+    COLOR_FREE  = "#94A3B8"
+    COLOR_ALERT = "#F59E0B"
     used_colors = np.where(df["ALERT"].to_numpy(), COLOR_ALERT, COLOR_USED)
 
-    # Add an icon to the y label for alerts
-    y_labels = np.where(df["ALERT"].to_numpy(), "⚠ " + df["Label"], df["Label"])
-
     fig = go.Figure()
 
-    # Gray background (hover shows AVAILABLE)
+    # Gray background hover: Available in GB (0dp)
     fig.add_trace(
         go.Bar(
             y=y_labels,
             x=[100] * len(df),
             base=0,
-            name="(hover) Available",
             orientation="h",
             marker=dict(color=COLOR_TOTAL),
             opacity=0.40,
             hovertemplate="<b>%{y}</b><br>Available: %{customdata}<br><extra></extra>",
-            customdata=avail_text,
+            customdata=avail_gb_0,
             showlegend=False,
         )
     )
 
-    # Used (colored per-row; alert if >99%)
+    # Used hover: Available in GB (0dp) too
     fig.add_trace(
         go.Bar(
             y=y_labels,
@@ -163,9 +159,9 @@ def plot_disks(alert_threshold_pct=99.0):
             ),
             customdata=np.stack(
                 [
-                    df["Used_TB"].to_numpy(),
-                    df["Avail_TB"].to_numpy(),
-                    df["Total_TB"].to_numpy(),
+                    df["Used_TB"].map(lambda v: f"{v:.2f} TB").to_numpy(),
+                    df["Avail_GB"].map(lambda v: f"{v:.0f} GB").to_numpy(),  # <-- changed
+                    df["Total_TB"].map(lambda v: f"{v:.2f} TB").to_numpy(),
                     df["Used_pct"].to_numpy(),
                 ],
                 axis=1,
@@ -173,7 +169,7 @@ def plot_disks(alert_threshold_pct=99.0):
         )
     )
 
-    # Available
+    # Available hover: Available in GB (0dp)
     fig.add_trace(
         go.Bar(
             y=y_labels,
@@ -191,7 +187,7 @@ def plot_disks(alert_threshold_pct=99.0):
             ),
             customdata=np.stack(
                 [
-                    df["Avail_TB"].map(lambda v: f"{v:.2f} TB").to_numpy(),
+                    df["Avail_GB"].map(lambda v: f"{v:.0f} GB").to_numpy(),  # <-- changed
                     df["Used_TB"].map(lambda v: f"{v:.2f} TB").to_numpy(),
                     df["Total_TB"].map(lambda v: f"{v:.2f} TB").to_numpy(),
                 ],
@@ -200,17 +196,17 @@ def plot_disks(alert_threshold_pct=99.0):
         )
     )
 
-    # Total annotation at far right (color it if alert)
-    for lbl, ttxt, is_alert in zip(y_labels, total_text, df["ALERT"].to_numpy()):
+    # Total annotation (TB, 2dp)
+    for y, ttxt, is_alert in zip(y_labels, total_annot, df["ALERT"].to_numpy()):
         fig.add_annotation(
             x=100,
-            y=lbl,
+            y=y,
             text=ttxt,
             showarrow=False,
             xanchor="left",
             yanchor="middle",
             xshift=6,
-            font=dict(color=(COLOR_ALTXT if is_alert else "#334155")),
+            font=dict(color=("#B45309" if is_alert else "#334155")),
         )
 
     fig.update_layout(