fix: change voronoi example notebook (#159)

* fix: added wgs84 const
kraina-ai · Jan 13, 2023 · 0882609 · 0882609
1 parent f94a37c
commit 0882609
Showing 1 changed file with 42 additions and 34 deletions.
diff --git a/examples/regionizers/voronoi_regionizer.ipynb b/examples/regionizers/voronoi_regionizer.ipynb
@@ -12,7 +12,8 @@
     "import plotly.express as px\n",
     "from shapely.geometry import MultiPolygon, Point, Polygon\n",
     "\n",
-    "from srai.regionizers import VoronoiRegionizer"
+    "from srai.regionizers import VoronoiRegionizer\n",
+    "from srai.utils.constants import WGS84_CRS"
    ]
   },
   {
@@ -43,7 +44,7 @@
     "        ]\n",
     "    },\n",
     "    index=[1, 2, 3, 4, 5, 6],\n",
-    "    crs=\"EPSG:4326\",\n",
+    "    crs=WGS84_CRS,\n",
     ")"
    ]
   },
@@ -102,7 +103,10 @@
     "fig.update_traces(marker_color=\"white\", marker_size=10, selector=dict(type=\"scattergeo\"))\n",
     "fig.update_layout(coloraxis_showscale=False)\n",
     "fig.update_geos(\n",
-    "    projection_type=\"orthographic\", projection_rotation_lon=20, projection_rotation_lat=30\n",
+    "    projection_type=\"orthographic\",\n",
+    "    projection_rotation_lon=20,\n",
+    "    projection_rotation_lat=30,\n",
+    "    showlakes=False,\n",
     ")\n",
     "fig.update_layout(height=800, width=800, margin={\"r\": 0, \"t\": 0, \"l\": 0, \"b\": 0})\n",
     "fig.show(renderer=\"png\")  # replace with fig.show() to allow interactivity"
@@ -144,25 +148,36 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "N_POINTS = 100\n",
-    "# generate some random points within the bounds\n",
-    "minx, miny, maxx, maxy = uk_gdf_shape.bounds\n",
+    "def generate_random_points(shape, n_points=100):\n",
+    "    minx, miny, maxx, maxy = shape.bounds\n",
+    "    pts = []\n",
+    "\n",
+    "    while len(pts) < 4:\n",
+    "        randx = np.random.uniform(minx, maxx, n_points)\n",
+    "        randy = np.random.uniform(miny, maxy, n_points)\n",
+    "        coords = np.vstack((randx, randy)).T\n",
     "\n",
-    "randx = np.random.uniform(minx, maxx, N_POINTS)\n",
-    "randy = np.random.uniform(miny, maxy, N_POINTS)\n",
-    "coords = np.vstack((randx, randy)).T\n",
+    "        # use only the points inside the geographic area\n",
+    "        pts = [p for p in list(map(Point, coords)) if p.within(shape)]\n",
     "\n",
-    "# use only the points inside the geographic area\n",
+    "    del coords  # not used any more\n",
     "\n",
-    "pts = [p for p in list(map(Point, coords)) if p.within(uk_gdf_shape)]\n",
+    "    return pts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pts = generate_random_points(uk_gdf_shape)\n",
     "\n",
     "uk_seeds_gdf = gpd.GeoDataFrame(\n",
     "    {\"geometry\": pts},\n",
     "    index=list(range(len(pts))),\n",
-    "    crs=\"EPSG:4326\",\n",
-    ")\n",
-    "\n",
-    "del coords  # not used any more"
+    "    crs=WGS84_CRS,\n",
+    ")"
    ]
   },
   {
@@ -219,6 +234,7 @@
     "fig.add_trace(fig2.data[0])\n",
     "fig.update_traces(marker_color=\"black\", marker_size=6, selector=dict(type=\"scattergeo\"))\n",
     "fig.update_layout(coloraxis_showscale=False)\n",
+    "minx, miny, maxx, maxy = uk_gdf_shape.bounds\n",
     "fig.update_geos(\n",
     "    projection_type=\"natural earth\",\n",
     "    lataxis_range=[miny - 1, maxy + 1],\n",
@@ -271,7 +287,7 @@
     "        stations.append({\"id\": idx, \"geometry\": Point(*pos)})\n",
     "        positions.add(pos)\n",
     "\n",
-    "stations_gdf = gpd.GeoDataFrame(data=stations, crs=\"EPSG:4326\").set_index(\"id\")\n",
+    "stations_gdf = gpd.GeoDataFrame(data=stations, crs=WGS84_CRS).set_index(\"id\")\n",
     "\n",
     "del stations_csv\n",
     "del stations\n",
@@ -405,25 +421,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "N_POINTS = 100\n",
-    "# generate some random points within the bounds\n",
-    "minx, miny, maxx, maxy = pl_gdf_shape.bounds\n",
-    "\n",
-    "randx = np.random.uniform(minx, maxx, N_POINTS)\n",
-    "randy = np.random.uniform(miny, maxy, N_POINTS)\n",
-    "coords = np.vstack((randx, randy)).T\n",
-    "\n",
-    "# use only the points inside the geographic area\n",
-    "\n",
-    "pts = [p for p in list(map(Point, coords)) if p.within(pl_gdf_shape)]\n",
+    "pts = generate_random_points(pl_gdf_shape)\n",
     "\n",
     "pl_seeds_gdf = gpd.GeoDataFrame(\n",
     "    {\"geometry\": pts},\n",
     "    index=list(range(len(pts))),\n",
-    "    crs=\"EPSG:4326\",\n",
-    ")\n",
-    "\n",
-    "del coords"
+    "    crs=WGS84_CRS,\n",
+    ")"
    ]
   },
   {
@@ -453,7 +457,7 @@
     "pl_regions_2d_gdf = gpd.GeoDataFrame(\n",
     "    {\"geometry\": [orient_geom(geom) for geom in region_polys.values()]},\n",
     "    index=list(range(len(region_polys))),\n",
-    "    crs=\"EPSG:4326\",\n",
+    "    crs=WGS84_CRS,\n",
     ")"
    ]
   },
@@ -536,6 +540,8 @@
     "    for c in [1, 2]:\n",
     "        fig.add_trace(points_plot.data[0], row=r, col=c)\n",
     "\n",
+    "minx, miny, maxx, maxy = pl_gdf_shape.bounds\n",
+    "\n",
     "fig.update_traces(marker_color=\"black\", marker_size=6, selector=dict(type=\"scattergeo\"))\n",
     "fig.update_layout(coloraxis_showscale=False)\n",
     "fig.update_geos(\n",
@@ -544,6 +550,7 @@
     "    lonaxis_range=[minx - 1, maxx + 1],\n",
     "    resolution=50,\n",
     "    row=1,\n",
+    "    showlakes=False,\n",
     ")\n",
     "\n",
     "fig.update_geos(\n",
@@ -552,6 +559,7 @@
     "    lonaxis_range=[minx + 2, maxx - 2],\n",
     "    resolution=50,\n",
     "    row=2,\n",
+    "    showlakes=False,\n",
     ")\n",
     "\n",
     "fig.update_traces(marker={\"opacity\": 0.6}, selector=dict(type=\"choropleth\"), row=1)\n",
@@ -569,7 +577,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.8.10 ('.venv': venv)",
+   "display_name": ".venv",
    "language": "python",
    "name": "python3"
   },
@@ -587,7 +595,7 @@
   },
   "vscode": {
    "interpreter": {
-    "hash": "27588098aedc4e0690c9f009d86804b277352852ed19dd471efc5e9817d4b199"
+    "hash": "4153976b658cb8b76d04b10dc7a0c871c2dac1d3dcfe690ad61d83a61969a12e"
    }
   }
  },