def test_passing_incorrect_custom_filter(test_pbf):
from pyrosm import OSM
osm = OSM(filepath=test_pbf)
try:
osm.get_pois(custom_filter="wrong")
except ValueError as e:
if "dictionary" in str(e):
pass
except Exception as e:
raise e
def test_adding_extra_attribute(helsinki_pbf):
from pyrosm import OSM
from geopandas import GeoDataFrame
osm = OSM(filepath=helsinki_pbf)
gdf = osm.get_pois()
extra_col = "wikidata"
extra = osm.get_pois(extra_attributes=[extra_col])
# The extra should have one additional column compared to the original one
assert extra.shape[1] == gdf.shape[1] + 1
# Should have same number of rows
assert extra.shape[0] == gdf.shape[0]
assert extra_col in extra.columns
assert len(extra[extra_col].dropna().unique()) > 0
assert isinstance(gdf, GeoDataFrame)
def test_using_rare_tag(helsinki_pbf):
from pyrosm import OSM
from geopandas import GeoDataFrame
osm = OSM(filepath=helsinki_pbf)
# There aren't any but should not raise an error still (#47)
gdf = osm.get_pois({"park_ride": ["yes"]})
assert gdf is None
def test_pdgraph_connectivity():
from pyrosm.graphs import to_pandana
import pandas as pd
from pyrosm import OSM
osm = OSM(get_data("helsinki_pbf"))
nodes, edges = osm.get_network(nodes=True)
# Prerare some test data for aggregations
restaurants = osm.get_pois(custom_filter={"amenity": ["restaurant"]})
restaurants = restaurants.loc[restaurants["osm_type"] == "node"]
restaurants["employee_cnt"] = 1
x = restaurants["lon"]
y = restaurants["lat"]
g = to_pandana(nodes, edges, retain_all=False)
# Nodes and edges should be in DataFrames
assert isinstance(g.nodes_df, pd.DataFrame)
assert isinstance(g.edges_df, pd.DataFrame)
# Precompute up to 1000 meters
g.precompute(1000)
# Link restaurants to graph
g.set_pois("restaurants", 1000, 5, x, y)
# Find the distance to nearest 5 restaurants from each node
nearest_restaurants = g.nearest_pois(1000, "restaurants", num_pois=5)
assert isinstance(nearest_restaurants, pd.DataFrame)
assert nearest_restaurants.shape == (5750, 5)
# Get closest node_ids for each restaurant
node_ids = g.get_node_ids(x, y)
assert isinstance(node_ids, pd.Series)
assert node_ids.min() > 0
restaurants["node_id"] = node_ids
# Attach employee counts to the graph
g.set(node_ids, variable=restaurants.employee_cnt, name="employee_cnt")
# Aggregate the number of employees within 500 meters from each node
access = g.aggregate(500, type="sum", decay="linear", name="employee_cnt")
assert isinstance(access, pd.Series)
assert len(access) == 5750
# Test shortest path calculations
shortest_distances = g.shortest_path_lengths(node_ids[0:100],
node_ids[100:200],
imp_name="length")
assert isinstance(shortest_distances, list)
assert len(shortest_distances) == 100
shortest_distances = pd.Series(shortest_distances)
assert shortest_distances.min().round(0) == 22
assert shortest_distances.max().round(0) == 2453
assert shortest_distances.mean().round(0) == 856
def test_reading_pois_from_area_having_none(helsinki_pbf):
from pyrosm import OSM
from geopandas import GeoDataFrame
# Bounding box for area that does not have any data
bbox = [24.940514, 60.173849, 24.942, 60.175892]
osm = OSM(filepath=helsinki_pbf, bounding_box=bbox)
# The tool should warn if no buildings were found
with pytest.warns(UserWarning) as w:
gdf = osm.get_pois()
# Check the warning text
if "could not find any buildings" in str(w):
pass
# Result should be None
assert gdf is None
def test_using_multiple_filters(helsinki_pbf):
from pyrosm import OSM
from geopandas import GeoDataFrame
osm = OSM(filepath=helsinki_pbf)
gdf = osm.get_pois({"shop": ["alcohol"], "amenity": ["pub"]})
# shop and amenity columns should only contain alcohol and pub as requested
# (in addition to None values)
shop = gdf["shop"].unique().tolist()
shop = [item for item in shop if isinstance(item, str)]
amenity = gdf["amenity"].unique().tolist()
amenity = [item for item in amenity if isinstance(item, str)]
assert isinstance(gdf, GeoDataFrame)
assert shop == ["alcohol"]
assert amenity == ["pub"]
assert gdf.shape == (59, 32)
def test_pois(test_pbf):
from pyrosm import OSM
from geopandas import GeoDataFrame
osm = OSM(test_pbf)
gdf = osm.get_pois()
assert isinstance(gdf, GeoDataFrame)