add tests

geosnap/analyze/network.py

@@ -20,7 +20,9 @@ def _geom_to_hull(geom, ratio, allow_holes):
 
 def _geom_to_alpha(geom):
     if isinstance(geom, list):
-        return alpha_shape_auto(gpd.GeoSeries(geom).get_coordinates()[["x", "y"]].values)
+        return alpha_shape_auto(
+            gpd.GeoSeries(geom).get_coordinates()[["x", "y"]].values
+        )
 
     return alpha_shape_auto(geom.get_coordinates()[["x", "y"]].values)
 
@@ -85,7 +87,14 @@ def pdna_to_adj(origins, network, threshold, reindex=True, drop_nonorigins=True)
 
 
 def isochrones_from_id(
-    origin, network, threshold, hull="shapely", ratio=0.2, allow_holes=False, use_edges=True
+    origin,
+    network,
+    threshold,
+    hull="shapely",
+    ratio=0.2,
+    allow_holes=False,
+    use_edges=True,
+    network_crs=4326
 ):
     """Create travel isochrone(s) from a single origin using a pandana network.
 
@@ -95,11 +104,12 @@ def isochrones_from_id(
         A single or list of node id(s) from a `pandana.Network.nodes_df`
         to serve as isochrone origins
     network : pandana.Network
-        A pandana network object
+        A pandana network object (preferably created with
+        geosnap.io.get_network_from_gdf)
     threshold : int or list
         A single or list of threshold distances for which isochrones will be
-        computed. These are in the
-        same units as edges from the pandana.Network.edge_df
+        computed. These are in the same impedance units as edges from the 
+        pandana.Network.edge_df
     hull : str, {'libpysal', 'shapely'}
         Which method to generate container polygons (concave hulls) for destination
         points. If 'libpysal', use `libpysal.cg.alpha_shape_auto` to create the
@@ -112,6 +122,9 @@ def isochrones_from_id(
         keyword passed to `shapely.concave_hull` governing  whether holes are
         allowed in the resulting polygon. Only used if `algorithm='hull'`.
         Default is False.
+    network_crs : int or pyproj.CRS
+        which coordinate system the pandana.Network node coordinates are stored in.
+        Default is 4326
 
     Returns
     -------
@@ -126,7 +139,7 @@ def isochrones_from_id(
     node_df = gpd.GeoDataFrame(
         network.nodes_df,
         geometry=gpd.points_from_xy(network.nodes_df.x, network.nodes_df.y),
-        crs=4326,
+        crs=network_crs,
     )
 
     maxdist = max(threshold) if isinstance(threshold, list) else threshold
@@ -166,7 +179,7 @@ def isochrones_from_id(
                 f"`algorithm must be either 'alpha' or 'hull' but {hull} was passed"
             )
 
-        alpha = gpd.GeoDataFrame(geometry=pd.Series(alpha), crs=4326)
+        alpha = gpd.GeoDataFrame(geometry=pd.Series(alpha), crs=network_crs)
         alpha["distance"] = distance
 
         dfs.append(alpha)
@@ -194,10 +207,8 @@ def isochrones_from_gdf(
     origins : geopandas.GeoDataFrame
         a geodataframe containing the locations of origin point features
     threshold: float
-        maximum travel distance to define the isochrone, measured in the same
-        units as edges_df in the pandana.Network object. If the network was
-        created with pandana this is usually meters; if it was created with
-        urbanaccess this is usually travel time in minutes.
+        maximum travel cost to define the isochrone, measured in the same
+        impedance units as edges_df in the pandana.Network object.
     network : pandana.Network
         pandana Network instance for calculating the shortest path isochrone
         for each origin feature
@@ -288,5 +299,5 @@ def isochrones_from_gdf(
     df = pd.concat(alphas, ignore_index=True)
     df = df.set_index("origin")
     if reindex:
-        df = df.rename(index=mapper, errors='raise')
+        df = df.rename(index=mapper, errors="raise")
     return gpd.GeoDataFrame(df, crs=network_crs)

geosnap/io/networkio.py

@@ -24,21 +24,22 @@ def get_network_from_gdf(
     Parameters
     ----------
     gdf : geopandas.GeoDataFrame
-        dataframe covering the study area of interest; this should be stored in lat/long
-        (epsg 4326). Note the first step is to take the unary union of this dataframe,
-        which is expensive, so large dataframes may be time-consuming
+        dataframe covering the study area of interest; Note the first step is to take
+        the unary union of this dataframe, which is expensive, so large dataframes may
+        be time-consuming. The network will inherit the CRS from this dataframe
     network_type : str, {"all_private", "all", "bike", "drive", "drive_service", "walk"}
         the type of network to collect from OSM (passed to `osmnx.graph_from_polygon`)
         by default "walk"
     twoway : bool, optional
         Whether to treat the pandana.Network as directed or undirected. For a directed network,
         use `twoway=False` (which is the default). For an undirected network (e.g. a
         walk network) where travel can flow in both directions, the network is more
-        efficient when twoway=True. This has implications for drive networks or multimodal
-        networks where impedance is different depending on travel direction.
+        efficient when twoway=True but forces the impedance to be equal in both
+        directions. This has implications for auto or multimodal
+        networks where impedance is generally different depending on travel direction.
     add_travel_times : bool, default=False
         whether to use posted travel times from OSM as the impedance measure (rather
-        than network-distance). Speeds are based on max drive speeds, see
+        than network-distance). Speeds are based on max posted drive speeds, see
         <https://osmnx.readthedocs.io/en/stable/internals-reference.html#osmnx-speed-module>
         for more information.
     default_speeds : dict, optional
@@ -50,7 +51,9 @@ def get_network_from_gdf(
     -------
     pandana.Network
         a pandana.Network object with node coordinates stored in the same system as the
-        input geodataframe
+        input geodataframe. If add_travel_times is True, the network impedance
+        is travel time measured in seconds (assuming automobile travel speeds); else 
+        the impedance is travel distance measured in meters
 
     Raises
     ------
@@ -92,7 +95,7 @@ def get_network_from_gdf(
         e = e.to_crs(output_crs)
     e = e.reset_index()
 
-    net= pdna.Network(
+    net = pdna.Network(
         edge_from=e["u"],
         edge_to=e["v"],
         edge_weights=e[[impedance]],
@@ -133,16 +136,16 @@ def project_network(network, output_crs=None, input_crs=4326):
     #  take original x,y coordinates and convert into geopandas.Series, then reproject
     nodes = _reproject_osm_nodes(network.nodes_df, input_crs, output_crs)
     edges = network.edges_df.copy()
-    if 'geometry' in edges:
+    if "geometry" in edges.columns:
         edges = edges.to_crs(output_crs)
 
     #  reinstantiate the network (needs to rebuild the tree)
     net = pdna.Network(
         node_x=nodes["x"],
         node_y=nodes["y"],
         edge_from=edges["from"],
-        edge_to=network.edges["to"],
-        edge_weights=network.edges[network.impedance_names],
+        edge_to=edges["to"],
+        edge_weights=edges[[network.impedance_names[0]]],
         twoway=network._twoway,
     )
     return net

geosnap/tests/test_isochrones.py

@@ -3,14 +3,14 @@
     isochrones_from_gdf,
 )
 from geosnap import DataStore
-from geosnap.io import get_acs, get_network_from_gdf
+from geosnap.io import get_acs, get_network_from_gdf, project_network
 import pandana as pdna
 import geopandas as gpd
 import os
 import pytest
 import sys
 from numpy.testing import assert_almost_equal
-
+import osmnx as ox
 
 def get_data():
     if not os.path.exists("./41740.h5"):
@@ -83,4 +83,29 @@ def test_network_constructor():
     tracts = get_acs(DataStore(), county_fips='48301', level='tract', years=2015)
     walk_net = get_network_from_gdf(tracts)
     # this will grow depending on the size of the OSM network when tested...
-    assert walk_net.edges_df.shape[0] > 6000
+    assert walk_net.edges_df.shape[0] > 6000
+
+def test_isos_with_edges():
+    tracts = get_acs(DataStore(), county_fips='48301', level='tract', years=2015)
+    walk_net = get_network_from_gdf(tracts)
+    type(walk_net)
+    facilities = ox.features.features_from_polygon(
+    tracts.unary_union, {"amenity": "fuel"}
+)
+    #facilities = facilities[facilities.geometry.type == "Point"]
+    alpha = isochrones_from_gdf(
+    facilities, network=walk_net, threshold=2000, use_edges=True
+)
+    print(alpha.area.round(8))
+    # this will grow depending on the size of the OSM network when tested...
+    assert alpha.area.round(8).iloc[0] == 0.00026001
+
+def test_project_network():   
+    tracts = get_acs(DataStore(), county_fips='48301', level='tract', years=2015)
+    walk_net = get_network_from_gdf(tracts)
+    # this will grow depending on the size of the OSM network when tested...
+    tracts = tracts.to_crs(tracts.estimate_utm_crs())
+    walk_net = project_network(walk_net, output_crs=tracts.crs)
+    nodes = walk_net.get_node_ids(tracts.centroid.x, tracts.centroid.y)
+    print(nodes)
+    assert nodes[0] == 7876436325