Update app.py

app.py

@@ -93,7 +93,7 @@ div[data-testid="stExpander"] div[data-baseweb="tab-list"] {
 </style>
 """, unsafe_allow_html=True)
 
-# Center text in all pandas Styler tables (headers + cells)
+# Center text in pandas tables
 TABLE_CENTER_CSS = [
     dict(selector="th", props=[("text-align", "center")]),
     dict(selector="td", props=[("text-align", "center")]),
@@ -162,7 +162,7 @@ def rmse(y_true, y_pred) -> float:
 def pearson_r(y_true, y_pred) -> float:
     a = np.asarray(y_true, dtype=float)
     p = np.asarray(y_pred, dtype=float)
-    if a.size < 2: 
+    if a.size < 2:
         return float("nan")
     return float(np.corrcoef(a, p)[0, 1])
 
@@ -230,7 +230,7 @@ def _excel_safe_name(name: str) -> str:
     safe = ''.join('_' if ch in bad else ch for ch in str(name))
     return safe[:31]
 
-def _round_numeric(df: pd.DataFrame, ndigits: int = 2) -> pd.DataFrame:
+def _round_numeric(df: pd.DataFrame, ndigits: int = 3) -> pd.DataFrame:
     out = df.copy()
     for c in out.columns:
         if pd.api.types.is_float_dtype(out[c]) or pd.api.types.is_integer_dtype(out[c]):
@@ -267,7 +267,7 @@ def _excel_autofit(writer, sheet_name: str, df: pd.DataFrame, min_w: int = 8, ma
         ws.set_column(i, i, max(min_w, min(max_len + 2, max_w)))
     ws.freeze_panes(1, 0)
 
-def _add_sheet(sheets: dict, order: list, name: str, df: pd.DataFrame, ndigits: int):
+def _add_sheet(sheets: dict, order: list, name: str, df: pd.DataFrame, ndigits: int = 3):
     if isinstance(df, pd.DataFrame) and not df.empty:
         sheets[name] = _round_numeric(df, ndigits)
         order.append(name)
@@ -283,7 +283,8 @@ def _available_sections():
     sections += ["Info"]
     return sections
 
-def build_export_workbook(selected: list[str], ndigits: int = 2) -> tuple[bytes|None, str|None, list[str]]:
+def build_export_workbook(selected: list[str], ndigits: int = 3) -> tuple[bytes|None, str|None, list[str]]:
+    """Builds an in-memory Excel workbook for selected sheets; fixed rounding to 3 decimals."""
     res = st.session_state.get("results", {})
     if not res:
         return None, None, []
@@ -358,11 +359,11 @@ def build_export_workbook(selected: list[str], ndigits: int = 2) -> tuple[bytes|
     fname = f"YM_Export_{datetime.now().strftime('%Y%m%d_%H%M%S')}.xlsx"
     return bio.getvalue(), fname, order
 
-def render_export_button(key: str = "export_main") -> None:
+def render_export_button(phase_key: str, default_sections: list[str]) -> None:
+    """Export UI — dropdown checklist, fixed rounding=3, appears inside each phase after results."""
     st.divider()
     st.markdown("### Export to Excel")
 
-    default_sections = _available_sections()
     all_sections = [
         "Training","Training_Metrics","Training_Summary",
         "Testing","Testing_Metrics","Testing_Summary",
@@ -370,14 +371,17 @@ def render_export_button(key: str = "export_main") -> None:
         "Prediction","Prediction_Summary",
         "Training_Ranges","Info"
     ]
-    selected = st.multiselect("Sheets to include", options=all_sections, default=default_sections)
-    c1, c2 = st.columns([1,2])
-    with c1:
-        ndigits = st.number_input("Rounding (decimals)", 0, 6, 2, 1)
-    with c2:
-        base_name = st.text_input("Base filename", value="YM_Export")
-
-    data, _, names = build_export_workbook(selected=selected, ndigits=int(ndigits))
+    # Dropdown checklist
+    selected = st.multiselect(
+        "Sheets to include",
+        options=all_sections,
+        default=default_sections,
+        help="Choose which sheets to include in the Excel export.",
+    )
+
+    base_name = st.text_input("Base filename", value="YM_Export", key=f"basename_{phase_key}")
+
+    data, _, names = build_export_workbook(selected=selected, ndigits=3)  # fixed 3 decimals
     if names:
         st.caption("Will include: " + ", ".join(names))
 
@@ -387,7 +391,7 @@ def render_export_button(key: str = "export_main") -> None:
         file_name=((base_name or "YM_Export") + "_" + datetime.now().strftime("%Y%m%d_%H%M%S") + ".xlsx") if data else "YM_Export.xlsx",
         mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
         disabled=(data is None),
-        key=key,
+        key=f"download_{phase_key}",
     )
 
 # =========================
@@ -510,7 +514,7 @@ def preview_tracks(df: pd.DataFrame, cols: list[str]):
         ax.text(0.5,0.5,"No selected columns",ha="center",va="center"); ax.axis("off")
         return fig
     fig, axes = plt.subplots(1, n, figsize=(2.2*n, 7.0), sharey=True, dpi=100)
-    if n == 1: 
+    if n == 1:
         axes = [axes]
     idx = np.arange(1, len(df) + 1)
     for ax, col in zip(axes, cols):
@@ -744,6 +748,10 @@ if st.session_state.app_step == "dev":
         st.session_state.train_ranges = {f:(float(tr_min[f]), float(tr_max[f])) for f in FEATURES}
         st.markdown('<div class="st-message-box st-success">Case has been built and results are displayed below.</div>', unsafe_allow_html=True)
 
+        # --- Export (DEV phase) ---
+        default_sections = [s for s in _available_sections() if s.startswith("Training") or s.startswith("Testing")] + ["Training_Ranges","Info"]
+        render_export_button(phase_key="dev", default_sections=default_sections)
+
     def _dev_block(df, m):
         c1,c2,c3 = st.columns(3)
         c1.metric("R", f"{m['R']:.2f}")
@@ -826,6 +834,13 @@ if st.session_state.app_step == "validate":
         st.session_state.results["sv_val"]={"n":len(df), "pred_min":float(df[PRED_COL].min()), "pred_max":float(df[PRED_COL].max()), "oor":oor_pct}
         st.session_state.results["oor_tbl"]=tbl
 
+        # --- Export (VALIDATE phase) ---
+        default_sections = ["Validation","Validation_Metrics","Validation_Summary"]
+        if st.session_state.results.get("oor_tbl") is not None and not st.session_state.results["oor_tbl"].empty:
+            default_sections.append("Validation_OOR")
+        default_sections += ["Training_Ranges","Info"]
+        render_export_button(phase_key="validate", default_sections=default_sections)
+
     if "Validate" in st.session_state.results:
         m = st.session_state.results["m_val"]
         c1,c2,c3 = st.columns(3)
@@ -902,6 +917,10 @@ if st.session_state.app_step == "predict":
             "oor":oor_pct
         }
 
+        # --- Export (PREDICT phase) ---
+        default_sections = ["Prediction","Prediction_Summary","Training_Ranges","Info"]
+        render_export_button(phase_key="predict", default_sections=default_sections)
+
     if "PredictOnly" in st.session_state.results:
         df = st.session_state.results["PredictOnly"]; sv = st.session_state.results["sv_pred"]
 
@@ -962,11 +981,7 @@ if st.session_state.show_preview_modal:
                             df_centered_rounded(tbl)
     st.session_state.show_preview_modal = False
 
-# === Bottom-of-page Export (per step) =========================================
-if st.session_state.app_step in ("dev", "validate", "predict"):
-    has_results = any(k in st.session_state.results for k in ("Train", "Test", "Validate", "PredictOnly"))
-    if has_results:
-        render_export_button(key=f"export_{st.session_state.app_step}")
+# (Removed the old global bottom-of-page export — now shown per phase)
 
 # =========================
 # Footer
@@ -978,4 +993,4 @@ st.markdown("""
     © 2025 Smart Thinking AI-Solutions Team. All rights reserved.<br>
     Website: <a href="https://smartthinking.com.sa" target="_blank" rel="noopener noreferrer">smartthinking.com.sa</a>
 </div>
-""", unsafe_allow_html=True)
+""", unsafe_allow_html=True)