fix

map_tab/map_logic.py

@@ -6,7 +6,7 @@ import pandas as pd
 import rasterio
 import pyproj
 import matplotlib.pyplot as plt
-from matplotlib import cm, colors
+from matplotlib import colors
 from geopy.geocoders import Nominatim
 from config import OUTPUT_DIR
 import plotly.graph_objects as go
@@ -14,6 +14,7 @@ from PIL import Image
 
 CELL_SIZE_M = 100  # meters
 
+
 def make_map(city, show_grid=True, show_georef=True):
     city = city.strip()
     if not city:
@@ -97,7 +98,7 @@ def make_map(city, show_grid=True, show_georef=True):
 
     # --- Optional grid overlay ---
     if show_grid:
-        _add_grid_overlay_plotly(fig, transformer)
+        _add_grid_overlay_plotly(fig, transformer, crs)
 
     # --- Layout ---
     fig.update_layout(
@@ -110,37 +111,43 @@ def make_map(city, show_grid=True, show_georef=True):
     return fig
 
 
-def _add_grid_overlay_plotly(fig, transformer):
+def _add_grid_overlay_plotly(fig, transformer, raster_crs):
+    """Add grid overlay as colored cells, works for any CRS."""
     grid_values = []
 
+    # Adapt grid size if CRS uses degrees instead of meters
+    if raster_crs.is_geographic:
+        cell_size = 0.001  # roughly 100m at equator
+    else:
+        cell_size = CELL_SIZE_M
+
     for fname in os.listdir(OUTPUT_DIR):
         if fname.startswith("street_matches_tile") and fname.endswith(".csv"):
             df = pd.read_csv(os.path.join(OUTPUT_DIR, fname))
-            if df.empty:
+            if df.empty or "x" not in df.columns or "y" not in df.columns:
                 continue
 
             tile_xmin, tile_xmax = df['x'].min(), df['x'].max()
             tile_ymin, tile_ymax = df['y'].min(), df['y'].max()
-            n_cols = int(np.ceil((tile_xmax - tile_xmin) / CELL_SIZE_M))
-            n_rows = int(np.ceil((tile_ymax - tile_ymin) / CELL_SIZE_M))
+            n_cols = int(np.ceil((tile_xmax - tile_xmin) / cell_size))
+            n_rows = int(np.ceil((tile_ymax - tile_ymin) / cell_size))
 
             grid = np.zeros((n_rows, n_cols))
             counts = np.zeros((n_rows, n_cols))
 
             for _, row in df.iterrows():
-                col = int((row['x'] - tile_xmin) // CELL_SIZE_M)
-                row_idx = int((row['y'] - tile_ymin) // CELL_SIZE_M)
+                col = int((row['x'] - tile_xmin) // cell_size)
+                row_idx = int((tile_ymax - row['y']) // cell_size)  # origin top-left
                 if 0 <= col < n_cols and 0 <= row_idx < n_rows:
                     grid[row_idx, col] += row['osm_match_score']
                     counts[row_idx, col] += 1
 
             mask = counts > 0
             grid[mask] /= counts[mask]
-
-            grid_values.append((grid, tile_xmin, tile_ymin, n_rows, n_cols))
+            grid_values.append((grid, tile_xmin, tile_ymax, n_rows, n_cols, cell_size))
 
     if not grid_values:
-        print("No grid values found")
+        print("No valid CSV grids found.")
         return
 
     all_scores = np.concatenate([g[0].flatten() for g in grid_values])
@@ -150,7 +157,7 @@ def _add_grid_overlay_plotly(fig, transformer):
 
     cmap = plt.get_cmap("Reds")
 
-    for grid, tile_xmin, tile_ymin, n_rows, n_cols in grid_values:
+    for grid, tile_xmin, tile_ymax, n_rows, n_cols, cell_size in grid_values:
         for r in range(n_rows):
             for c in range(n_cols):
                 val = grid[r, c]
@@ -159,20 +166,22 @@ def _add_grid_overlay_plotly(fig, transformer):
                 norm_val = (val - min_val) / (max_val - min_val)
                 color = colors.to_hex(cmap(norm_val))
 
-                # Rectangle in projected CRS
-                x0 = tile_xmin + c * CELL_SIZE_M
-                x1 = x0 + CELL_SIZE_M
-                y0 = tile_ymin + r * CELL_SIZE_M
-                y1 = y0 + CELL_SIZE_M
+                # Compute rectangle in projected CRS
+                x0 = tile_xmin + c * cell_size
+                x1 = x0 + cell_size
+                y1 = tile_ymax - r * cell_size
+                y0 = y1 - cell_size
 
                 # Convert to lon/lat
-                lon0, lat0 = transformer.transform(x0, y0)
-                lon1, lat1 = transformer.transform(x1, y1)
-
-                # Add rectangle to Plotly
-                lons = [lon0, lon1, lon1, lon0, lon0]
-                lats = [lat0, lat0, lat1, lat1, lat0]
-
+                lons, lats = zip(*[
+                    transformer.transform(x0, y0),
+                    transformer.transform(x1, y0),
+                    transformer.transform(x1, y1),
+                    transformer.transform(x0, y1),
+                    transformer.transform(x0, y0),
+                ])
+
+                # Add to Plotly map
                 fig.add_trace(go.Scattermapbox(
                     lon=lons,
                     lat=lats,
@@ -183,4 +192,3 @@ def _add_grid_overlay_plotly(fig, transformer):
                     hoverinfo="text",
                     text=f"{val:.2f}"
                 ))
-