Merge pull request #100 from NERDSITU/99-osmnx-project_gdf-api-change

Fix and version bump `1.0.1`

.github/workflows/lint.yml

@@ -53,9 +53,9 @@ jobs:
         run: pip install pylint
 
       - name: Lint Source Code
-        run: pylint -d E0401 superblockify/
+        run: pylint -d E0401,R0917 superblockify/
         # ignore import-errors first, analyze later with tests in anaconda environment
 
       - name: Lint Tests
-        run: pylint -d E0401 -d R0801 tests/
+        run: pylint -d E0401,R0801,R0917 tests/
         # also ignore code repetition in tests

.github/workflows/test.yml

@@ -69,6 +69,7 @@ jobs:
 
     name: ${{ matrix.submodule.name }} (${{ matrix.python-version }} on ${{ matrix.os }})
     runs-on: ${{ matrix.os }}
+    timeout-minutes: 60
     defaults:
       run:
         shell: bash -el {0}

docs/changelog.rst

@@ -2,6 +2,15 @@
 Changelog
 *********
 
+Version 1.0.1 (2024-12-04)
+**************************
+
+* 🧹 Lint: Reconfigured linting settings.
+* 🐛 Fixes: Removed unused Haversine distance function and adapted to `osmnx` API changes.
+* 🛠️ Update: Updated `test.yml` for artifacts v4.4.0 breaking change.
+* 📝 Documentation: Various updates including changelog, badge links,
+  mobile optimization, GitHub handles, installation instructions, `CITATION.cff`, and `paper.md`.
+
 Version 1.0.0 (2024-08-12)
 **************************
 

docs/conf.py

@@ -11,6 +11,7 @@
 #
 import os
 import sys
+from datetime import datetime
 
 sys.path.insert(0, os.path.abspath(".."))
 
@@ -22,9 +23,9 @@
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information
 
 project = "superblockify"
-copyright = "2023-2024, superblockify developers"
+copyright = f"2023-{datetime.now().year}, superblockify developers"
 author = "superblockify developers"
-release = "1.0.0"
+release = "1.0.1"
 
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration

docs/guide/30_population_density.myst

@@ -48,9 +48,9 @@ from rasterstats import zonal_stats
 ## 1. Area Boundary
 
 ```{code-cell} ipython3
-bogota_gdf = ox.geocode_to_gdf('Bogotá, Colombia')
+bogota_gdf = ox.geocode_to_gdf('Bogotá, Capital District, RAP (Especial) Central, Colombia')
 # Project to UTM, so we can treat it as flat Cartesian coordinates (meters)
-bogota_gdf = ox.project_gdf(bogota_gdf)
+bogota_gdf = ox.projection.project_gdf(bogota_gdf)
 print(f"The area of Bogotá is {round(bogota_gdf.area[0] / 10 ** 6, 2)} km²")
 bogota_gdf.explore()
 ```
@@ -405,7 +405,9 @@ One such example is the city of Jönköping in Sweden, it falls on two tiles.
 
 ```{code-cell} ipython3
 :tags: [hide-input]
-def get_population(place_gdf, pop_raster_files, resample_factor=1, place_name=None):
+def get_population(
+        place_gdf, pop_raster_files, resample_factor=1, place_name=None, low_cutoff=0
+):
     """Get the population for a place.
 
     Parameters
@@ -419,6 +421,8 @@ def get_population(place_gdf, pop_raster_files, resample_factor=1, place_name=No
         up-scaling.
     place_name : str, optional
         Name of the place. The default is None.
+    low_cutoff : float, optional
+        The least considered value for the population. The default is 0.
 
     Returns
     -------
@@ -427,7 +431,8 @@ def get_population(place_gdf, pop_raster_files, resample_factor=1, place_name=No
     """
     fig, axe = plt.subplots(figsize=(6, 6))
     pop_sum = 0
-    for pop_raster_file in pop_raster_files if isinstance(pop_raster_files, list) else [pop_raster_files]:
+    for pop_raster_file in pop_raster_files if isinstance(pop_raster_files, list) else [
+        pop_raster_files]:
         # Window of place, buffered by 100m
         with rasterio.open(pop_raster_file) as src:
             window = src.window(*place_gdf.buffer(100).total_bounds)
@@ -442,6 +447,9 @@ def get_population(place_gdf, pop_raster_files, resample_factor=1, place_name=No
         pop_raster = pop_raster / resample_factor ** 2  # Correct for resampling
         # Set masked values to 0
         pop_raster = pop_raster.filled(0)
+        # Cut off low values
+        pop_raster[pop_raster < low_cutoff] = 0
+
         # Get population
         zs_place = zonal_stats(place_gdf_raster_crs, pop_raster, affine=affine,
                                stats="sum", nodata=0)

docs/guide/31_tessellation.myst

@@ -70,7 +70,7 @@ that might come to one's mind is the convex hull of the linestrings.
 
 ```{code-cell} ipython3
 # From subgraph_edges we want to get a hull that encloses all edges
-convex_hull = subgraph_edges.unary_union.convex_hull
+convex_hull = subgraph_edges.union_all().convex_hull
 # Make gdf from convex hull with the same crs as the subgraph
 convex_hull_gdf = gpd.GeoDataFrame(
     geometry=[convex_hull], crs=subgraph_edges.crs
@@ -102,7 +102,7 @@ from numpy import linspace
 def plot_concave_hull(ax, subgraph_edges, ratio=0.4, allow_holes=False,
                       color="crimson"):
     concave_hull = shp.concave_hull(
-        subgraph_edges.unary_union,
+        subgraph_edges.union_all(),
         ratio=ratio,
         allow_holes=allow_holes,
     )
@@ -186,7 +186,7 @@ each other, we'll buffer using a flat cap style.
     Does work well with small buffer values."""
     edges = ox.graph_to_gdfs(subgraph, nodes=False, edges=True)
     # First buffer with flat cap style to avoid self-intersections
-    polygon = shp.Polygon(edges.unary_union.buffer(2 * buffer, cap_style='flat')
+    polygon = shp.Polygon(edges.union_all().buffer(2 * buffer, cap_style='flat')
                           .exterior)
     # Simplify the polygon to remove small artifacts of flat cap style at curved edges
     # polygon = polygon.simplify(buffer*2, preserve_topology=True)
@@ -335,7 +335,7 @@ geometries. Then we can also split up the hull into points and add them to the p
 array.
 
 ```{code-cell} ipython3
-hull = shp.Polygon(edges.unary_union.buffer(100).exterior)
+hull = shp.Polygon(edges.union_all().buffer(100).exterior)
 # interpolate points along the hull - double the distance
 hull_points = shp.line_interpolate_point(
     hull.boundary,

docs/guide/32_edge_population.myst

@@ -124,11 +124,11 @@ For that, we take the union of all road cells and get the bounding box of it. Wh
 looking at the union, the _skewness_ of our projection is visible.
 
 ```{code-cell} ipython3
-lc_road_cells.unary_union
+lc_road_cells.union_all()
 ```
 
 ```{code-cell} ipython3
-lc_bbox = lc_road_cells.unary_union.bounds
+lc_bbox = lc_road_cells.union_all().bounds
 lc_ghsl = get_ghsl(lc_bbox)
 ```
 

examples/06-population-density.ipynb

@@ -81,9 +81,9 @@
    },
    "outputs": [],
    "source": [
-    "bogota_gdf = ox.geocode_to_gdf('Bogotá, Colombia')\n",
+    "bogota_gdf = ox.geocode_to_gdf('Bogotá, Capital District, RAP (Especial) Central, Colombia')\n",
     "# Project to UTM, so we can treat it as flat Cartesian coordinates (meters)\n",
-    "bogota_gdf = ox.project_gdf(bogota_gdf)\n",
+    "bogota_gdf = ox.projection.project_gdf(bogota_gdf)\n",
     "print(f\"The area of Bogotá is {round(bogota_gdf.area[0] / 10 ** 6, 2)} km²\")\n",
     "bogota_gdf.explore()"
    ]
@@ -681,7 +681,9 @@
    },
    "outputs": [],
    "source": [
-    "def get_population(place_gdf, pop_raster_files, resample_factor=1, place_name=None):\n",
+    "def get_population(\n",
+    "        place_gdf, pop_raster_files, resample_factor=1, place_name=None, low_cutoff=0\n",
+    "):\n",
     "    \"\"\"Get the population for a place.\n",
     "\n",
     "    Parameters\n",
@@ -695,6 +697,8 @@
     "        up-scaling.\n",
     "    place_name : str, optional\n",
     "        Name of the place. The default is None.\n",
+    "    low_cutoff : float, optional\n",
+    "        The least considered value for the population. The default is 0.\n",
     "\n",
     "    Returns\n",
     "    -------\n",
@@ -703,7 +707,8 @@
     "    \"\"\"\n",
     "    fig, axe = plt.subplots(figsize=(6, 6))\n",
     "    pop_sum = 0\n",
-    "    for pop_raster_file in pop_raster_files if isinstance(pop_raster_files, list) else [pop_raster_files]:\n",
+    "    for pop_raster_file in pop_raster_files if isinstance(pop_raster_files, list) else [\n",
+    "        pop_raster_files]:\n",
     "        # Window of place, buffered by 100m\n",
     "        with rasterio.open(pop_raster_file) as src:\n",
     "            window = src.window(*place_gdf.buffer(100).total_bounds)\n",
@@ -718,6 +723,9 @@
     "        pop_raster = pop_raster / resample_factor ** 2  # Correct for resampling\n",
     "        # Set masked values to 0\n",
     "        pop_raster = pop_raster.filled(0)\n",
+    "        # Cut off low values\n",
+    "        pop_raster[pop_raster < low_cutoff] = 0\n",
+    "\n",
     "        # Get population\n",
     "        zs_place = zonal_stats(place_gdf_raster_crs, pop_raster, affine=affine,\n",
     "                               stats=\"sum\", nodata=0)\n",

examples/07-superblock-boundary.ipynb

@@ -125,7 +125,7 @@
    "outputs": [],
    "source": [
     "# From subgraph_edges we want to get a hull that encloses all edges\n",
-    "convex_hull = subgraph_edges.unary_union.convex_hull\n",
+    "convex_hull = subgraph_edges.union_all().convex_hull\n",
     "# Make gdf from convex hull with the same crs as the subgraph\n",
     "convex_hull_gdf = gpd.GeoDataFrame(\n",
     "    geometry=[convex_hull], crs=subgraph_edges.crs\n",
@@ -163,7 +163,7 @@
    "outputs": [],
    "source": [
     "# Shapely MultiLineString geometry\n",
-    "subgraph_edges.explode().unary_union.boundary\n"
+    "subgraph_edges.explode().union_all().boundary\n"
    ]
   },
   {
@@ -179,7 +179,7 @@
    "source": [
     "# Concave hull of the edges\n",
     "shp.concave_hull(\n",
-    "    subgraph_edges.unary_union,\n",
+    "    subgraph_edges.union_all(),\n",
     "    ratio=0.4,\n",
     "    allow_holes=True,\n",
     ")"
@@ -199,7 +199,7 @@
     "def plot_concave_hull(ax, subgraph_edges, ratio=0.4, allow_holes=False,\n",
     "                      color=\"crimson\"):\n",
     "    concave_hull = shp.concave_hull(\n",
-    "        subgraph_edges.unary_union,\n",
+    "        subgraph_edges.union_all(),\n",
     "        ratio=ratio,\n",
     "        allow_holes=allow_holes,\n",
     "    )\n",
@@ -281,7 +281,7 @@
    "source": [
     "def border_from_subgraph(subgraph, buffer=2):\n",
     "    edges = ox.graph_to_gdfs(subgraph, nodes=False, edges=True)\n",
-    "    return edges.unary_union.buffer(buffer, cap_style='flat').buffer(-buffer / 2)"
+    "    return edges.union_all().buffer(buffer, cap_style='flat').buffer(-buffer / 2)"
    ]
   },
   {
@@ -341,7 +341,7 @@
     "    Does work well with small buffer values.\"\"\"\n",
     "    edges = ox.graph_to_gdfs(subgraph, nodes=False, edges=True)\n",
     "    # First buffer with flat cap style to avoid self-intersections\n",
-    "    polygon = shp.Polygon(edges.unary_union.buffer(2 * buffer, cap_style='flat')\n",
+    "    polygon = shp.Polygon(edges.union_all().buffer(2 * buffer, cap_style='flat')\n",
     "                          .exterior)\n",
     "    # Simplify the polygon to remove small artifacts of flat cap style at curved edges\n",
     "    # polygon = polygon.simplify(buffer*2, preserve_topology=True)\n",
@@ -378,7 +378,7 @@
     "    Works better with larger buffer values.\"\"\"\n",
     "    edges = ox.graph_to_gdfs(subgraph, nodes=False, edges=True)\n",
     "    # First buffer with flat cap style to avoid self-intersections\n",
-    "    lin_ring = edges.unary_union.buffer(buffer, cap_style='flat').exterior\n",
+    "    lin_ring = edges.union_all().buffer(buffer, cap_style='flat').exterior\n",
     "    # Smoothen the linear ring, taking the midpoints of the edges\n",
     "    lin_ring = shp.LinearRing(\n",
     "        [shp.Point((x1 + x2) / 2, (y1 + y2) / 2) for (x1, y1), (x2, y2) in zip(\n",
@@ -543,7 +543,7 @@
     "    primary_barriers=gpd.GeoDataFrame(\n",
     "        geometry=part.graph.graph[\"boundary\"].difference(\n",
     "            gpd.GeoSeries(edges_sparsified.buffer(5)\n",
-    "                          .unary_union)),\n",
+    "                          .union_all())),\n",
     "        crs=part.graph.graph[\"boundary_crs\"]\n",
     "    ),\n",
     "    limit=  #mm.buffered_limit(borders, 1).convex_hull,\n",
@@ -818,7 +818,7 @@
     "    part.graph.nodes[node][\"cell\"] = node_poly_gdf.loc[node, \"geometry\"]\n",
     "# For each partition create boundary as union of cells\n",
     "for p, p_order in zip(part.partitions, part.get_partition_nodes()):\n",
-    "    p[\"boundary\"] = shp.unary_union(\n",
+    "    p[\"boundary\"] = shp.union_all()(\n",
     "        [part.graph.nodes[node][\"cell\"] for node in p_order[\"nodes\"]])"
    ]
   },
@@ -990,7 +990,7 @@
    "source": [
     "# get hull from the graph boundary\n",
     "# hull = part.graph.graph[\"boundary\"]\n",
-    "hull = shp.Polygon(edges.unary_union.buffer(100).exterior)\n",
+    "hull = shp.Polygon(edges.union_all().buffer(100).exterior)\n",
     "hull"
    ]
   },

superblockify/_version.py

@@ -1,3 +1,3 @@
 """superblockify package version."""
 
-__version__ = "1.0.0"
+__version__ = "1.0.1"

superblockify/cities.yml

@@ -120,11 +120,11 @@ place_lists:
         - 1572779
         pop_GHSL2023: 328740.3926395578
       Liechtenstein:
-        query: Liechtenstein, Europe
+        query: Liechtenstein
         country: LI
         region: EU
         nominatim link:
-        - https://nominatim.openstreetmap.org/ui/search.html?q=Liechtenstein,+Europe
+        - https://nominatim.openstreetmap.org/ui/search.html?q=Liechtenstein
         OSM relation:
         - https://www.openstreetmap.org/relation/1155955
         osm_id: