def test_network(bbox=bb_athens,
path=path_data,
osm_filter=adj_filter,
save_shp=False,
save_pickle=True,
reload=False):
tic = time.time()
print('Start: …load network ')
if reload:
network_df = cn.CreateNetwork(bounding_box=bbox,
custom_filter=osm_filter)
_ = network_df.network_dfs()
if save_pickle:
write_pickle(network_df, 'network', path)
else:
try:
network_df = read_pickle('network', path)
except FileNotFoundError:
network_df = cn.CreateNetwork(bounding_box=bbox,
custom_filter=osm_filter)
_ = network_df.network_dfs()
if save_pickle:
write_pickle(network_df, 'network', path)
if save_shp:
network_df.save_graph_to_shp()
print('Shapefiles stored')
toc = time.time()
print(f'Network loaded, took {toc - tic} sec')
return network_df
def get_path_dict(path=path_data, reset=False):
name = 'path_dict'
if not reset:
try:
path_dict = read_pickle(name, path=path)
return path_dict
except FileNotFoundError:
path_dict = {'hdf_path': init_hdf(), 'groups': {}, 'current_resample_step': {}, 'extra': 'all_data'}
write_pickle(path_dict, name, path=path_data)
return path_dict
else:
path_dict = {'hdf_path': init_hdf(), 'groups': {}, 'current_resample_step': {}, 'extra': 'all_data'}
write_pickle(path_dict, name, path=path_data)
return path_dict
def test_detectors(network_df,
path,
number_detectors=n_det,
detector_length=len_det,
distance_from_intersection=dfi,
double_loops=None,
lonlat=False,
save_shp=False):
double_l = False
dl_tmp = 0
if double_loops is not None:
if type(double_loops) in (int, float):
if double_loops > 0:
double_l = double_loops
else:
print(
f'unrealistic length: {double_loops}, default of 1 m is used'
)
double_l = 1
dl_tmp = double_l
else:
raise TypeError(
'"double_loops" parameter not of the right type, should be integer or float'
)
name = f'{number_detectors}_{distance_from_intersection}_{detector_length}_{dl_tmp}'
try:
det = read_pickle(f'detectors_{name}', path=path)
except FileNotFoundError:
det = md.Detectors(network_df.network_edges,
length_detector=detector_length,
dfi=distance_from_intersection,
n_det=number_detectors,
double_loops=double_l,
lonlat=lonlat,
gdf_special=network_df.node_tags)
det.detector_projected()
det.features_projected()
write_pickle(det, f'detectors_{name}', path=path)
print('Virtual detectors created for edges')
if save_shp:
det.detector_to_shapefile()
print('Shapefiles stored')
return det