def test_extract_graph_links_with_flat_condition_and_list_value_specifying_to_ignore_mixed_types(
):
n = Network('epsg:27700')
n.add_link('0',
1,
2,
attribs={
'attributes': {
'osm:way:highway': {
'name': 'osm:way:highway',
'class': 'java.lang.String',
'text': 'primary'
}
}
})
n.add_link('1',
2,
3,
attribs={
'attributes': {
'osm:way:highway': {
'name': 'osm:way:highway',
'class': 'java.lang.String',
'text': 'primary'
}
}
})
n.add_link('2', 3, 4, attribs={'attributes': ['yes', 'no', 'bobby']})
links = graph_operations.extract_links_on_edge_attributes(
n, conditions={'attributes': 'yes'}, mixed_dtypes=False)
assert links == []
def test_extract_graph_links_with_flat_condition():
n = Network('epsg:27700')
n.add_link('0',
1,
2,
attribs={
'attributes': {
'osm:way:highway': {
'name': 'osm:way:highway',
'class': 'java.lang.String',
'text': 'primary'
}
}
})
n.add_link('1',
2,
3,
attribs={
'attributes': {
'osm:way:highway': {
'name': 'osm:way:highway',
'class': 'java.lang.String',
'text': 'primary'
}
}
})
n.add_link('2', 3, 4, attribs={'attributes': 'yes'})
links = graph_operations.extract_links_on_edge_attributes(
n,
conditions={'attributes': 'yes'},
)
assert links == ['2']
def generate_standard_outputs(n, output_dir, gtfs_day='19700101'):
logging.info(
f'Generating geojson outputs for the entire network in {output_dir}')
save_network_to_geojson(n, output_dir)
graph_nodes, graph_links = generate_geodataframes(n.graph)
logging.info('Generating geojson outputs for car/driving modal subgraph')
graph_output_dir = os.path.join(output_dir, 'graph')
gdf_car = graph_links[graph_links.apply(lambda x: modal_subset(x, {'car'}),
axis=1)]
for attribute in ['freespeed', 'capacity', 'permlanes']:
try:
save_geodataframe(gdf_car[[attribute, 'geometry', 'id']],
filename=f'car_{attribute}_subgraph',
output_dir=graph_output_dir)
except KeyError:
logging.warning(
f'Your network is missing a vital attribute {attribute}')
logging.info(
'Generating geojson outputs for different highway tags in car modal subgraph'
)
highway_tags = n.link_attribute_data_under_key(
{'attributes': {
'osm:way:highway': 'text'
}})
highway_tags = set(
chain.from_iterable(highway_tags.apply(lambda x: setify(x))))
for tag in highway_tags:
tag_links = graph_operations.extract_links_on_edge_attributes(
network=n,
conditions={'attributes': {
'osm:way:highway': {
'text': tag
}
}},
mixed_dtypes=True)
save_geodataframe(graph_links[graph_links['id'].isin(tag_links)],
filename=f'car_osm_highway_{tag}',
output_dir=graph_output_dir)
for mode in n.modes():
logging.info(
f'Generating geometry-only geojson outputs for {mode} modal subgraph'
)
gdf = graph_links[graph_links.apply(lambda x: modal_subset(x, {mode}),
axis=1)]
save_geodataframe(gdf[['geometry', 'id']],
filename=f'subgraph_geometry_{mode}',
output_dir=os.path.join(graph_output_dir,
'geometry_only_subgraphs'))
# schedule outputs
if n.schedule:
generate_standard_outputs_for_schedule(n.schedule,
output_dir=os.path.join(
output_dir, 'schedule'),
gtfs_day=gtfs_day)
def extract_network_id_from_osm_csv(network, attribute_name, osm_csv_path,
outpath):
"""
Parse a Network() object and find edges whose
['attributes'][attribute_name]['text'] is present in a list of OSM way ids
:param network: a Network() object with attribute_name tags
:param attribute_name: a string corresponding to the name of the link attribute of interest
:param osm_csv_path: path to a .csv config file where OSM way ids are stored in column `osm_ids`
:param outpath: path to a folder
:return: None, but will write .csv and .json files to `outpath` location
"""
osm_df = pd.read_csv(osm_csv_path, dtype=str)
osm_df['network_id'] = pd.Series(dtype=str)
target_osm_ids = set(osm_df['osm_ids'].values)
osm_to_network_dict = {}
with tqdm(total=len(target_osm_ids)) as pbar:
for target_id in target_osm_ids:
links = graph_operations.extract_links_on_edge_attributes(
network,
conditions={
'attributes': {
attribute_name: {
'text': target_id
}
}
},
)
# links is now a list of strings
if len(links) > 0:
# store list of links in dictionary
osm_to_network_dict[target_id] = links
# mark the OSM id as "matched" in the dataframe
osm_df.loc[osm_df['osm_ids'] == target_id, 'network_id'] = True
else:
# mark the OSM id as "ummatched" in the dataframe
osm_df.loc[osm_df['osm_ids'] == target_id,
'network_id'] = False
pbar.update(1)
# check whether some of our OSM ids were not found
unmatched_osm_df = osm_df[osm_df['network_id'] == 'no']
if unmatched_osm_df.shape[0] > 0:
# print unmatched ids
logging.info(
'these OSM way ids did not find a match in the network.xml')
logging.info(unmatched_osm_df['osm_ids'].values)
# write dataframe as .csv and dictionary as .json
osm_df.to_csv(os.path.join(outpath, 'osm_tolls_with_network_ids.csv'),
index=False)
with open(os.path.join(outpath, 'osm_to_network_ids.json'),
'w') as write_file:
json.dump(osm_to_network_dict, write_file)
def test_extract_graph_links_with_callable_condition_and_list_value_specifying_to_ignore_mixed_types(
):
n = Network('epsg:27700')
n.add_link('0',
1,
2,
attribs={
'attributes': {
'osm:way:highway': {
'name': 'osm:way:highway',
'class': 'java.lang.String',
'text': {9, 10}
}
}
})
n.add_link('1',
2,
3,
attribs={
'attributes': {
'osm:way:highway': {
'name': 'osm:way:highway',
'class': 'java.lang.String',
'text': [1, 2]
}
}
})
n.add_link('2', 3, 4, attribs={'attributes': 'yes'})
def condition(val):
return val == 9
links = graph_operations.extract_links_on_edge_attributes(
n,
conditions={'attributes': {
'osm:way:highway': {
'text': condition
}
}},
mixed_dtypes=False)
assert links == []
def test_extract_graph_links_with_callable_condition():
n = Network('epsg:27700')
n.add_link('0',
1,
2,
attribs={
'attributes': {
'osm:way:highway': {
'name': 'osm:way:highway',
'class': 'java.lang.String',
'text': 9
}
}
})
n.add_link('1',
2,
3,
attribs={
'attributes': {
'osm:way:highway': {
'name': 'osm:way:highway',
'class': 'java.lang.String',
'text': 1
}
}
})
n.add_link('2', 3, 4, attribs={'attributes': 'yes'})
def condition(val):
return val == 9
links = graph_operations.extract_links_on_edge_attributes(
n, conditions={'attributes': {
'osm:way:highway': {
'text': condition
}
}})
assert links == ['0']
def test_extract_graph_links_with_list_condition_and_list_value():
n = Network('epsg:27700')
n.add_link('0',
1,
2,
attribs={
'attributes': {
'osm:way:highway': {
'name': 'osm:way:highway',
'class': 'java.lang.String',
'text': ['primary', 'secondary']
}
}
})
n.add_link('1',
2,
3,
attribs={
'attributes': {
'osm:way:highway': {
'name': 'osm:way:highway',
'class': 'java.lang.String',
'text': {'primary', 'other'}
}
}
})
n.add_link('2', 3, 4, attribs={'attributes': 'yes'})
links = graph_operations.extract_links_on_edge_attributes(
n,
conditions={
'attributes': {
'osm:way:highway': {
'text': ['primary', 'some_other_highway']
}
}
})
assert links == ['0', '1']
def test_extract_graph_links_with_bound_condition_and_list_value():
n = Network('epsg:27700')
n.add_link('0',
1,
2,
attribs={
'attributes': {
'osm:way:highway': {
'name': 'osm:way:highway',
'class': 'java.lang.String',
'text': [9, 1]
}
}
})
n.add_link('1',
2,
3,
attribs={
'attributes': {
'osm:way:highway': {
'name': 'osm:way:highway',
'class': 'java.lang.String',
'text': [0, 1]
}
}
})
n.add_link('2', 3, 4, attribs={'attributes': 'yes'})
links = graph_operations.extract_links_on_edge_attributes(
n, conditions={'attributes': {
'osm:way:highway': {
'text': (2, 10)
}
}})
assert links == ['0']
