def get_selection(file_name):
"""
Get selection from an XML file. Returns a dictionary with the data from the file
or None if unable to read/parse the file.
:param file_name: string
:return: selection data dictionary
"""
selection = get_data_from_file(file_name)
if selection is None:
return None
selection_data = {
'name':
file_name,
'raw_data':
selection,
'from_file':
'yes',
'paths': [p for p in selection[0]['elements'] if p['type'] == 'way'],
'nodes':
get_nodes_dict(selection, nodes_dict={}),
'relations':
[p for p in selection[0]['elements'] if p['type'] == 'relation']
}
add_missing_highway_tag(selection_data['paths'],
get_streets(selection_data))
return insert_street_names(selection_data)
def crop_selection(selection, x0, y0, nodes_dict=None, radius=150.0):
"""
Crop the selection to a smaller radius
:param selection: list of intersection data in the osmnx format
:param x0: float: center coordinate
:param y0: float: center coordinate
:param nodes_dict: dictionary
:param radius: float in meters: cropping radius
:return: cropped list of intersection data in the osmnx format
"""
if nodes_dict is None:
nodes_dict = get_nodes_dict(selection, nodes_dict={})
cropped_selection = []
for s in selection:
s_cropped = {
'version': s['version'],
'osm3s': s['osm3s'],
'generator': s['generator'],
'elements': s['elements']
}
s_cropped['element'] = remove_elements_beyond_radius(
s_cropped['elements'], nodes_dict, x0, y0, radius)
cropped_selection.append(s_cropped)
return cropped_selection
def get_city(city_name):
"""
Get city data as a dictionary.
:param city_name: city name like 'Campbell, California, USA'
:return: city data dictionary
"""
city_paths_nodes = get_city_from_osm(city_name)
if city_paths_nodes is None:
return None
city_data = {
'name':
city_name,
'raw_data':
None,
'from_file':
'no',
'paths':
[p for p in city_paths_nodes[0]['elements'] if p['type'] == 'way'],
'nodes':
get_nodes_dict(city_paths_nodes, nodes_dict={}),
'relations': [
p for p in city_paths_nodes[0]['elements']
if p['type'] == 'relation'
]
}
add_missing_highway_tag(city_data['paths'], get_streets(city_data))
return insert_street_names(city_data)
def get_street_structure(city_name):
"""
Get street structure of a city
:param city_name: city name like 'Campbell, California, USA'
:return: a tuple of list of paths and a nodes dictionary
"""
city_boundaries = ox.gdf_from_place(city_name)
city_paths_nodes = ox.osm_net_download(
city_boundaries['geometry'].unary_union, network_type="drive")
nodes_dict = get_nodes_dict(city_paths_nodes)
paths = [p for p in city_paths_nodes[0]['elements'] if p['type'] != 'node']
return paths, nodes_dict