src/seismic_hazard_forecasting.py

@@ -70,6 +70,8 @@ def main(catalog_file, mc_file, pdf_file, m_file, m_select, mag_label, mc, m_max
     import matplotlib.pyplot as plt
     from matplotlib.ticker import MultipleLocator
     from matplotlib.contour import ContourSet
+    import xml.etree.ElementTree as ET
+    import json
 
     logger = getDefaultLogger('igfash')
 
@@ -239,6 +241,9 @@ verbose: {verbose}")
         grid_y_max = int(ceil(y_max / grid_dim) * grid_dim)
         grid_y_min = int(floor(y_min / grid_dim) * grid_dim)
 
+        grid_lat_max, grid_lon_max = utm.to_latlon(grid_x_max, grid_y_max, utm_zone_number, utm_zone_letter)
+        grid_lat_min, grid_lon_min = utm.to_latlon(grid_x_min, grid_y_min, utm_zone_number, utm_zone_letter)
+
         # rectangular grid
         nx = int((grid_x_max - grid_x_min) / grid_dim) + 1
         ny = int((grid_y_max - grid_y_min) / grid_dim) + 1
@@ -495,9 +500,18 @@ verbose: {verbose}")
 
             # Save the figure
             fig.canvas.draw()
-            plt.savefig("overlay_" + str(j) + ".svg", bbox_inches="tight", pad_inches=0, transparent=True)
+            overlay_filename = f"overlay_{j}.svg"
+            plt.savefig(overlay_filename, bbox_inches="tight", pad_inches=0, transparent=True)
             plt.close(fig)
 
+            # Embed geographic bounding box into the SVG
+            map_bounds = dict(zip(("south", "west", "north", "east"),
+                            map(float, (grid_lat_min, grid_lon_min, grid_lat_max, grid_lon_max))))
+            tree = ET.parse(overlay_filename)
+            tree.getroot().set("data-map-bounds", json.dumps(map_bounds))
+            tree.write(overlay_filename, encoding="utf-8", xml_declaration=True)
+            logger.info(f"Saved geographic bounds to SVG metadata (data-map-bounds): {overlay_filename} → {map_bounds}")
+
             # Make the color bar
             cmap_name = 'viridis'
             width = 50