Update app.py

app.py

@@ -12,7 +12,7 @@ matplotlib.use("Agg")
 import matplotlib.pyplot as plt
 
 import plotly.graph_objects as go
-from sklearn.metrics import r2_score, mean_squared_error, mean_absolute_error
+from sklearn.metrics import mean_squared_error, mean_absolute_error
 from scipy.stats import pearsonr
 
 # =========================
@@ -52,7 +52,26 @@ st.markdown(
       .st-hero .tagline { margin:2px 0 0 2px; color:#6b7280; font-size:1.05rem; font-style:italic; }
       [data-testid="stBlock"]{ margin-top:0 !important; }
       /* Center align text in table cells */
-      .st-emotion-cache-1wq06yv { text-align: center; }
+      .st-emotion-cache-1wq06yv, .st-emotion-cache-1e71x4x table tr td { text-align: center !important; }
+
+      /* Hide the drag-and-drop helper text */
+      .stFileUploader>label+div { display: none; }
+      .stFileUploader>label { width: 100%; }
+      .stFileUploader > label:first-child + div { display: block; }
+      .stFileUploader > label:first-child { display: none; }
+
+      /* Pinned Titles */
+      .pinned-title {
+        position: fixed;
+        top: 0;
+        left: 0;
+        right: 0;
+        background: #fff;
+        z-index: 999;
+        padding: 1rem;
+        box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+        font-weight: bold;
+      }
     </style>
     """,
     unsafe_allow_html=True
@@ -177,12 +196,8 @@ def _nice_tick0(xmin: float, step: int = 100) -> float:
 def cross_plot(actual, pred):
     a = pd.Series(actual).astype(float)
     p = pd.Series(pred).astype(float)
-    lo = float(np.nanmin([a.min(), p.min()]))
-    hi = float(np.nanmax([a.max(), p.max()]))
-    pad = 0.03 * (hi - lo if hi > lo else 1.0)
-    x0, x1 = lo - pad, hi + pad
     
-    # Get the global min and max of all data points for consistent scaling
+    # Calculate the global min and max of all data points for consistent scaling
     all_values = pd.concat([a, p]).dropna()
     global_min = all_values.min()
     global_max = all_values.max()