Support downloading grid and its info

app.py

@@ -1,10 +1,11 @@
 import os
+import zipfile
 import gradio as gr
 import plotly.graph_objects as go
 
 from geo_tools import (
     shapefile_to_latlong,
-    shapefile_to_grid_indices,
+    mask_shapefile_to_grid_indices,
     points_to_shapefile,
     get_cached_grid_indices,
 )
@@ -19,7 +20,6 @@ OUT_DIR = "out/"
 def gr_generate_map(
     token: str,
     side_len: str,
-    show_grid: bool,
     show_mask: bool,
     show_hospitals: bool = True,
     show_police: bool = True,
@@ -28,21 +28,33 @@ def gr_generate_map(
     side_len = float(side_len)
 
     scattermaps = []
-    if show_grid:
-        grid_path = MASK_PATH[: -len(".shp")] + f"-len={side_len}.shp"
-        if not os.path.exists(grid_path):
-            indices = shapefile_to_grid_indices(MASK_PATH, side_len)
-            points_to_shapefile(indices, grid_path)
-        else:
-            indices, _ = get_cached_grid_indices(grid_path)
-        box = go.Scattermapbox(
-            lat=indices[:, 1],
-            lon=indices[:, 0],
-            mode="markers",
-            marker=go.scattermapbox.Marker(size=6),
-        )
-        box.name = "Grids"
-        scattermaps.append(box)
+    grid_path = MASK_PATH[: -len(".shp")] + f"-gap={side_len}.shp"
+    prefix = ".".join(grid_path.split(".")[:-1])
+    if not os.path.exists(grid_path):
+        indices, labels = mask_shapefile_to_grid_indices(MASK_PATH, side_len)
+        points_to_shapefile(indices, labels, grid_path)
+
+        file_list = [prefix + ext for ext in (".shp", ".shx", ".prj", ".dbf", ".cpg")]
+        with zipfile.ZipFile(prefix + ".zip", "w") as fp:
+            for file in file_list:
+                fp.write(file, compress_type=zipfile.ZIP_DEFLATED)
+
+        with open(prefix + ".csv", "w") as fp:
+            fp.write("Label, Latitude, Longitude\n")
+            for lbl, idx in zip(labels, indices):
+                fp.write(f"{lbl}, {idx[1]}, {idx[0]}\n")
+    else:
+        indices, labels = get_cached_grid_indices(grid_path)
+    box = go.Scattermapbox(
+        lat=indices[:, 1],
+        lon=indices[:, 0],
+        mode="markers+text",
+        text=labels,
+        marker=go.scattermapbox.Marker(size=6),
+    )
+    box.name = "Grids"
+    scattermaps.append(box)
+
     if show_mask:
         contours = shapefile_to_latlong(MASK_PATH)
         for contour in contours:
@@ -129,7 +141,7 @@ def gr_generate_map(
             ),
         )
 
-    return fig
+    return fig, prefix + ".zip", prefix + ".csv"
 
 
 with gr.Blocks() as demo:
@@ -141,7 +153,6 @@ with gr.Blocks() as demo:
         )
         grid_side_len = gr.Textbox(value="100", label="Sampling Gap (m)")
 
-        grid_show_grid = gr.Checkbox(True, label="Show Grid")
         grid_show_mask = gr.Checkbox(False, label="Show Mask")
         grid_show_hosp = gr.Checkbox(True, label="Show Hospitals")
         grid_show_police = gr.Checkbox(True, label="Show Police Stations")
@@ -161,11 +172,13 @@ with gr.Blocks() as demo:
                 "Seruwila",
             ],
         )
+        grid_shapefile = gr.File(label="Grid Shapefile")
+        grid_point_info = gr.File(label="Sample Point Info")
 
     grid_button.click(
         gr_generate_map,
-        inputs=[grid_token, grid_side_len, grid_show_grid, grid_show_mask],
-        outputs=grid_map,
+        inputs=[grid_token, grid_side_len, grid_show_mask],
+        outputs=[grid_map, grid_shapefile, grid_point_info],
     )
 
     grid_region.change(
@@ -173,13 +186,12 @@ with gr.Blocks() as demo:
         inputs=[
             grid_token,
             grid_side_len,
-            grid_show_grid,
             grid_show_mask,
             grid_show_hosp,
             grid_show_police,
             grid_region,
         ],
-        outputs=grid_map,
+        outputs=[grid_map, grid_shapefile, grid_point_info],
     )
 
 demo.queue(concurrency_count=10).launch(debug=True)

geo_tools.py

@@ -30,15 +30,20 @@ def shapefile_to_latlong(file_path: str):
     return contours
 
 
-def shapefile_to_grid_indices(
+def mask_shapefile_to_grid_indices(
     file_path: str, side_len_m: float = 100, meters_per_px: float = 10
 ):
     c = fiona.open(file_path, "r")
     all_indices = []
+    all_labels = []
+    city_counts = {}
     side_len = side_len_m / meters_per_px
 
     for poly in c:
         coords = poly["geometry"].coordinates
+        city = poly["properties"]["City"]
+        if city not in city_counts:
+            city_counts[city] = 0
         for coord_set in tqdm(coords):
             contour = np.array(coord_set[0] if len(coord_set) == 1 else coord_set)
 
@@ -62,16 +67,20 @@ def shapefile_to_grid_indices(
             indices = np.array(get_optimal_grid(mask, side_len=side_len)[0])
             indices = indices * meters_per_px + cmin
 
-            all_indices += indices.tolist()
+            all_indices += sorted(indices.tolist(), key=lambda x: x[1])
+            all_labels += [
+                f"{city}-{city_counts[city] + i}" for i in range(len(indices))
+            ]
+            city_counts[city] += len(indices)
 
     transformer = Transformer.from_crs(c.crs, 4326, always_xy=True)
     all_indices = list(transformer.itransform(all_indices))
 
-    return np.array(all_indices)
+    return np.array(all_indices), all_labels
 
 
-def points_to_shapefile(points: np.ndarray, file_path: str):
-    schema = {"geometry": "Point", "properties": [("ID", "int")]}
+def points_to_shapefile(points: np.ndarray, labels: list, file_path: str):
+    schema = {"geometry": "Point", "properties": [("ID", "int"), ("Name", "str")]}
 
     # open a fiona object
     pointShp = fiona.open(
@@ -85,7 +94,7 @@ def points_to_shapefile(points: np.ndarray, file_path: str):
     for i, (x, y) in enumerate(points):
         rowDict = {
             "geometry": {"type": "Point", "coordinates": (x, y)},
-            "properties": {"ID": i},
+            "properties": {"ID": i, "Name": labels[i]},
         }
         pointShp.write(rowDict)
     # close fiona object