Update app.py

app.py

@@ -16,6 +16,13 @@ MODELS_DIR = Path("models")
 DEFAULT_MODEL = MODELS_DIR / "ucs_rf.joblib"
 MODEL_FALLBACKS = [MODELS_DIR / "model.joblib", MODELS_DIR / "model.pkl"]
 
+# Colors for plots
+COLORS = {
+    "pred": "#1f77b4",   # blue (predicted)
+    "actual": "#f2b702", # yellow (actual)
+    "ref": "#5a5a5a"     # grey 1:1 line
+}
+
 # =========================
 # Page / Theme
 # =========================
@@ -79,13 +86,15 @@ def find_sheet(book, names):
         if nm.lower() in low2orig: return low2orig[nm.lower()]
     return None
 
-def cross_plot(actual, pred, title, size=(4.6, 4.6)):
+def cross_plot(actual, pred, title, size=(3.9, 3.9)):
+    """Compact, square cross-plot with a 1:1 reference line."""
     fig, ax = plt.subplots(figsize=size, dpi=100)
-    ax.scatter(actual, pred, s=14, alpha=0.8)
+    ax.scatter(actual, pred, s=14, alpha=0.85, color=COLORS["pred"])
     lo = float(np.nanmin([actual.min(), pred.min()]))
     hi = float(np.nanmax([actual.max(), pred.max()]))
     pad = 0.03 * (hi - lo if hi > lo else 1.0)
-    ax.plot([lo - pad, hi + pad], [lo - pad, hi + pad], '--', lw=1.2, color=(0.35, 0.35, 0.35))
+    ax.plot([lo - pad, hi + pad], [lo - pad, hi + pad],
+            '--', lw=1.2, color=COLORS["ref"])
     ax.set_xlim(lo - pad, hi + pad)
     ax.set_ylim(lo - pad, hi + pad)
     ax.set_aspect('equal', 'box')  # perfect 1:1
@@ -94,31 +103,38 @@ def cross_plot(actual, pred, title, size=(4.6, 4.6)):
     return fig
 
 def depth_or_index_track(df, title=None, include_actual=True):
+    """
+    Narrow, tall track: predicted solid blue; actual dotted yellow.
+    Works for either Depth on Y or Index on Y.
+    """
     # Find depth-like column if available
-    depth_col = None
-    for c in df.columns:
-        if 'depth' in str(c).lower():
-            depth_col = c; break
+    depth_col = next((c for c in df.columns if 'depth' in str(c).lower()), None)
 
-    fig_h = 7.4 if depth_col is not None else 7.0  # taller track; still fits most screens
-    fig, ax = plt.subplots(figsize=(6.0, fig_h), dpi=100)
+    # Narrow width, tall height for logging look
+    fig_w = 3.1
+    fig_h = 7.6 if depth_col is not None else 7.2
+    fig, ax = plt.subplots(figsize=(fig_w, fig_h), dpi=100)
 
     if depth_col is not None:
-        ax.plot(df["UCS_Pred"], df[depth_col], '--', lw=1.6, label="UCS_Pred")
+        ax.plot(df["UCS_Pred"], df[depth_col],
+                '-', lw=1.8, color=COLORS["pred"], label="UCS_Pred")
         if include_actual and TARGET in df.columns:
-            ax.plot(df[TARGET], df[depth_col], '-', lw=2.0, alpha=0.85, label="UCS (actual)")
+            ax.plot(df[TARGET], df[depth_col],
+                    ':', lw=2.0, color=COLORS["actual"], alpha=0.95, label="UCS (actual)")
         ax.set_ylabel(depth_col); ax.set_xlabel("UCS")
         ax.xaxis.set_label_position('top'); ax.xaxis.tick_top(); ax.invert_yaxis()
     else:
         idx = np.arange(1, len(df) + 1)
-        ax.plot(df["UCS_Pred"], idx, '--', lw=1.6, label="UCS_Pred")
+        ax.plot(df["UCS_Pred"], idx,
+                '-', lw=1.8, color=COLORS["pred"], label="UCS_Pred")
         if include_actual and TARGET in df.columns:
-            ax.plot(df[TARGET], idx, '-', lw=2.0, alpha=0.85, label="UCS (actual)")
+            ax.plot(df[TARGET], idx,
+                    ':', lw=2.0, color=COLORS["actual"], alpha=0.95, label="UCS (actual)")
         ax.set_ylabel("Point Index"); ax.set_xlabel("UCS")
         ax.xaxis.set_label_position('top'); ax.xaxis.tick_top(); ax.invert_yaxis()
 
     ax.grid(True, linestyle=":", alpha=0.4)
-    if title: ax.set_title(title, pad=8)  # no title if None/empty
+    if title: ax.set_title(title, pad=8)  # keep no title by passing None
     ax.legend(loc="best")
     return fig
 
@@ -272,7 +288,7 @@ if st.session_state.app_step == "dev":
         on_click=(lambda: st.session_state.update(app_step="predict")) if st.session_state.dev_ready else None,
     )
 
-    # ---- Header + helper sentence positioned under the header (your request) ----
+    # Header + helper sentence under the header
     st.subheader("Model Development")
     st.write("Upload your data to train the model and review the development performance.")
 
@@ -323,11 +339,11 @@ if st.session_state.app_step == "dev":
                 df = st.session_state.results["Train"]; m = st.session_state.results["metrics_train"]
                 c1,c2,c3 = st.columns(3)
                 c1.metric("R²", f"{m['R2']:.4f}"); c2.metric("RMSE", f"{m['RMSE']:.4f}"); c3.metric("MAE", f"{m['MAE']:.4f}")
-                left,right = st.columns([1,1])
+                # Narrow track column for log-look
+                left, right = st.columns([0.9, 0.55])
                 with left:
                     st.pyplot(cross_plot(df[TARGET], df["UCS_Pred"], "Training: Actual vs Predicted"), use_container_width=True)
                 with right:
-                    # no title on the track (cleaner)
                     st.pyplot(depth_or_index_track(df, title=None, include_actual=True), use_container_width=True)
 
         if "Test" in st.session_state.results:
@@ -335,7 +351,7 @@ if st.session_state.app_step == "dev":
                 df = st.session_state.results["Test"]; m = st.session_state.results["metrics_test"]
                 c1,c2,c3 = st.columns(3)
                 c1.metric("R²", f"{m['R2']:.4f}"); c2.metric("RMSE", f"{m['RMSE']:.4f}"); c3.metric("MAE", f"{m['MAE']:.4f}")
-                left,right = st.columns([1,1])
+                left, right = st.columns([0.9, 0.55])
                 with left:
                     st.pyplot(cross_plot(df[TARGET], df["UCS_Pred"], "Testing: Actual vs Predicted"), use_container_width=True)
                 with right:
@@ -412,21 +428,36 @@ if st.session_state.app_step == "predict":
         st.subheader("Validation Results")
         sv = st.session_state.results["summary_val"]; oor_table = st.session_state.results.get("oor_table")
 
-        # ---- NEW: show OOR warning above the plots when applicable ----
+        # Show OOR warning above the plots when applicable
         if sv["oor_pct"] > 0:
             st.warning("Some validation inputs fall outside the **training min–max** ranges. Interpret predictions with caution.")
 
         c1,c2,c3,c4 = st.columns(4)
         c1.metric("points", f"{sv['n_points']}"); c2.metric("Pred min", f"{sv['pred_min']:.2f}")
         c3.metric("Pred max", f"{sv['pred_max']:.2f}"); c4.metric("OOR %", f"{sv['oor_pct']:.1f}%")
-        left,right = st.columns([1,1])
+
+        left, right = st.columns([0.9, 0.55])  # slim log-look track
         with left:
             if TARGET in st.session_state.results["Validate"].columns:
-                st.pyplot(cross_plot(st.session_state.results["Validate"][TARGET], st.session_state.results["Validate"]["UCS_Pred"], "Validation: Actual vs Predicted"), use_container_width=True)
+                st.pyplot(
+                    cross_plot(
+                        st.session_state.results["Validate"][TARGET],
+                        st.session_state.results["Validate"]["UCS_Pred"],
+                        "Validation: Actual vs Predicted"
+                    ),
+                    use_container_width=True
+                )
             else:
                 st.info("Actual UCS values are not available in the validation data. Cross-plot cannot be generated.")
         with right:
-            st.pyplot(depth_or_index_track(st.session_state.results["Validate"], title=None, include_actual=(TARGET in st.session_state.results["Validate"].columns)), use_container_width=True)
+            st.pyplot(
+                depth_or_index_track(
+                    st.session_state.results["Validate"],
+                    title=None,
+                    include_actual=(TARGET in st.session_state.results["Validate"].columns)
+                ),
+                use_container_width=True
+            )
 
         if oor_table is not None:
             st.write("*Out-of-range rows (vs. Training min–max):*")
@@ -451,4 +482,4 @@ if st.session_state.app_step == "predict":
 # Footer
 # =========================
 st.markdown("---")
-st.markdown("<div style='text-align:center; color:#6b7280;'>ST_GeoMech_UCS • © Smart Thinking</div>", unsafe_allow_html=True)
+st.markdown("<div style='text-align:center; color:#6b7280;'>ST_GeoMech_UCS • © Smart Thinking</div>", unsafe_allow_html=True)