Fix minor bugs on training data page

src/entropice/dashboard/plots/source_data.py

@@ -173,7 +173,7 @@ def render_alphaearth_plots(ds: xr.Dataset):
         hovermode="x unified",
     )
 
-    st.plotly_chart(fig, use_container_width=True)
+    st.plotly_chart(fig, width="stretch")
 
     # Band statistics
     with st.expander("📈 Statistics by Embedding Band", expanded=False):
@@ -194,7 +194,7 @@ def render_alphaearth_plots(ds: xr.Dataset):
             )
 
         band_df = pd.DataFrame(band_stats)
-        st.dataframe(band_df, use_container_width=True, hide_index=True)
+        st.dataframe(band_df, width="stretch", hide_index=True)
 
         if len(ds["band"]) > 10:
             st.info(f"Showing first 10 of {len(ds['band'])} embedding dimensions")
@@ -250,7 +250,7 @@ def render_arcticdem_overview(ds: xr.Dataset):
         )
 
     stats_df = pd.DataFrame(var_stats)
-    st.dataframe(stats_df, use_container_width=True, hide_index=True)
+    st.dataframe(stats_df, width="stretch", hide_index=True)
 
 
 @st.fragment
@@ -296,7 +296,7 @@ def render_arcticdem_plots(ds: xr.Dataset):
             height=400,
         )
 
-        st.plotly_chart(fig, use_container_width=True)
+        st.plotly_chart(fig, width="stretch")
 
 
 def render_era5_overview(ds: xr.Dataset, temporal_type: str):
@@ -362,7 +362,7 @@ def render_era5_overview(ds: xr.Dataset, temporal_type: str):
         )
 
     stats_df = pd.DataFrame(var_stats)
-    st.dataframe(stats_df, use_container_width=True, hide_index=True)
+    st.dataframe(stats_df, width="stretch", hide_index=True)
 
 
 @st.fragment
@@ -416,7 +416,7 @@ def render_era5_plots(ds: xr.Dataset, temporal_type: str):
             hovermode="x unified",
         )
 
-        st.plotly_chart(fig, use_container_width=True)
+        st.plotly_chart(fig, width="stretch")
 
 
 @st.fragment

src/entropice/dashboard/training_data_page.py

@@ -163,8 +163,6 @@ def render_training_data_page():
 
             render_spatial_map(train_data_dict)
 
-            st.balloons()
-
         # AlphaEarth tab
         tab_idx = 1
         if "AlphaEarth" in ensemble.members:
@@ -181,10 +179,15 @@ def render_training_data_page():
 
                 st.markdown("---")
 
+                if (ensemble.grid == "hex" and ensemble.level == 6) or (
+                    ensemble.grid == "healpix" and ensemble.level == 10
+                ):
+                    st.warning(
+                        "🗺️ Spatial map rendering is disabled for this grid configuration (hex-6 or healpix-10) due to performance considerations."
+                    )
+                else:
                     render_alphaearth_map(alphaearth_ds, targets, ensemble.grid)
 
-                st.balloons()
-
             tab_idx += 1
 
         # ArcticDEM tab
@@ -202,10 +205,15 @@ def render_training_data_page():
 
                 st.markdown("---")
 
+                if (ensemble.grid == "hex" and ensemble.level == 6) or (
+                    ensemble.grid == "healpix" and ensemble.level == 10
+                ):
+                    st.warning(
+                        "🗺️ Spatial map rendering is disabled for this grid configuration (hex-6 or healpix-10) due to performance considerations."
+                    )
+                else:
                     render_arcticdem_map(arcticdem_ds, targets, ensemble.grid)
 
-                st.balloons()
-
             tab_idx += 1
 
         # ERA5 tab (combining all temporal variants)
@@ -243,8 +251,16 @@ def render_training_data_page():
 
                     st.markdown("---")
 
+                    if (ensemble.grid == "hex" and ensemble.level == 6) or (
+                        ensemble.grid == "healpix" and ensemble.level == 10
+                    ):
+                        st.warning(
+                            "🗺️ Spatial map rendering is disabled for this grid configuration (hex-6 or healpix-10) due to performance considerations."
+                        )
+                    else:
                         render_era5_map(era5_ds, targets, ensemble.grid, temporal_type)
 
+        # Show balloons once after all tabs are rendered
         st.balloons()
 
     else:

src/entropice/dataset.py

@@ -90,7 +90,16 @@ def bin_values(
     non_none_values = values[~none_mask]
 
     assert len(non_none_values) > 5, "Not enough non-none values to create bins."
-    binned_non_none = pd.qcut(non_none_values, q=5, labels=labels[1:]).cat.set_categories(labels, ordered=True)
+
+    # Create bins without labels first to handle duplicates
+    binned_non_none = pd.qcut(non_none_values, q=5, labels=False, duplicates="drop")
+
+    # Map the bin indices to labels, using only as many labels as bins created
+    n_bins = binned_non_none.max() + 1  # bins are 0-indexed
+    active_labels = labels[1 : 1 + n_bins]  # Skip "None" and take n_bins labels
+    binned_non_none = binned_non_none.map(dict(enumerate(active_labels))).astype("category")
+    binned_non_none = binned_non_none.cat.set_categories(labels, ordered=True)
+
     binned = pd.Series(index=values.index, dtype="category")
     binned = binned.cat.set_categories(labels, ordered=True)
     binned.update(binned_non_none)