def save_graph(G, filepath):
data = json_graph.node_link_data(G)
# dump json to a file
save_results = check_savepath(filepath)
if save_results:
with open(filepath, 'w') as outfile:
json.dump(data, fp=outfile, cls=MyEncoder)
def results_to_geojson(results_f, geojson_inf, geojson_outf):
'''
Results file is merged with the network geojson file based on the init and term ids
of each link. Saves geojson with merged results.
- results_f = string, path to results text file from solver
- geojson_inf = string, path to network geojson
- geojson_outf = string, path save location for results geojson
'''
geodf = create_results_df(results_f, geojson_inf)
save_results = check_savepath(geojson_outf)
if save_results:
with open(geojson_outf, 'w') as f:
f.write(geodf.to_json())
def save_plot(df, save_path):
save_results = check_savepath(save_path)
if save_results:
matplotlib.style.use('ggplot')
pp = PdfPages(save_path)
plt.figure(figsize=(20, 20), dpi=400)
df.ix[:,'vmt'].plot.bar()
plt.title('vmt')
pp.savefig()
plt.figure(figsize=(20, 20), dpi=400)
df.ix[:,'vht'].plot.bar()
plt.title('vht')
pp.savefig()
plt.figure(figsize=(20, 20), dpi=400)
df.ix[:,'delay'].plot.bar()
plt.title('delay')
pp.savefig()
pp.close()
def df_vmt_vht_delay(df, output_summary, totalODflow = 0, min_speed = 0):
'''
df = results dataframe
totalODflow = total demand (total number of passengers)
min_speed = force speed to min_speed if link speed < minspeed
'''
#TODO updated names?
df['vmt'] = df['flow'].astype(float)*df['length'].astype(float)/1609.34
# tt/fftt represents how many times longer the result takes compared to the free flowing time
# multiply this by the free flowing time to calculate time traveled from results
df['travel time'] = df['fftt'].astype(float)*df['tt/fftt'].astype(float)/3600
if float(min_speed) == 0:
df['vht'] = df['flow'].astype(float)*df['travel time'].astype(float)
df['delay'] = df['flow'].astype(float)*(df['travel time'].astype(float)-df['fftt'].astype(float)/3600)
df['speed'] = (df['length'].astype(float)/1609.34)/df['travel time'].astype(float)
else:
df['speed'] = (df['length'].astype(float)/1609.34)/df['travel time'].astype(float)
df['travel time'] = np.where([df['speed'] > float(min_speed)], df['travel time'], df['length'].astype(float)/(1609.34*float(speed_limit)))[0]
df['vht'] = df['flow'].astype(float)*df['travel time'].astype(float)
df['delay'] = df['flow'].astype(float)*(df['travel time'].astype(float)-df['fftt'].astype(float)/3600)
df['speed_new'] = (df['length'].astype(float)/1609.34)/df['travel time'].astype(float)
totalvmt = np.sum(df['vmt'])
totalvht = np.sum(df['vht'])
totaldelay = np.sum(df['delay'])
#print("VMT: ", totalvmt, "VHT: ", totalvht, "Total Delay: ", totaldelay)
if totalODflow != 0:
d = {'vmt': [totalvmt, float(totalvmt/totalODflow)],
'vht': [totalvht, float(totalvht/totalODflow)],
'delay': [totaldelay, float(totaldelay/totalODflow)]}
totaldf = pd.DataFrame(d, index = ['total','per passenger'])
save_results = check_savepath(output_summary)
if save_results:
with open(output_summary,'w') as f:
f.write(totaldf.to_csv())
print('totalvmt: ' + str(totalvmt))
print('totalvht: ' + str(totalvht))
print('totaldelay: ' + str(totaldelay))
print('vmt per traveler: ' + str(totalvmt/totalODflow))
print('vht per traveler: ' + str(totalvht/totalODflow))
print('delay per traveler: ' + str(totaldelay/totalODflow))
return df
def update_capacity(attr_dict, percent_cap, geojson_inf,
geojson_outf, graph_f=None):
'''
update a network file by changing the capacity according to the fields in attr_dict
- attr_dict = {key: [list of values that will be changed]}
example: {'county': ['Alameda', 'Berkeley', 'Emeryville']}
- precent_cap = type decimal, percent of existing capacity roads will now have
- geojson_in = type str, filepath network geojson file
- geojson_out = type str, filepath save locations of modified network geojson file
- graph_f = path of updated networkx or None if don't want to save networkx graph
'''
links = gpd.read_file(geojson_inf)
roads_to_update = 1
for k,v in attr_dict.items():
# if k == 'type':
# v = [r+';' for r in v]
roads_to_update = roads_to_update & links[k].isin(v)
# Change capacity of city Arterials and save to dataframe
links['capacity'] = np.where(roads_to_update,
links['capacity']*percent_cap,
links['capacity'])
save_results = check_savepath(geojson_outf)
if save_results:
with open(geojson_outf, 'w') as f:
f.write(links.to_json())
if graph_f != None:
geojson_to_networkx(geojson_outf, graph_f)
def label_road_network(input_shp, road_network_geojson, attributes, geojson_outf, rename_attributes = None):
#####################append_city_names#####################
# read links geojson
'''
Generalized function of append_city_names:
Allows user to specify which attributes to keep from the input shape file.
Spatial join shape file with network, so that network file now has identifying labels
- input_shp: type str, filepath for generalized shapefile for cities, neighborhoods, from any state
- road_network_geojson: type str, filepath for input geoJSON network file
- attributes: type str OR str array, selected attributes that will be joined
- geojson_outf: type str, filepath for output file with identifying labels
- rename_attributes: type str OR str array, either string or array of strings (should match attributes), can be used if user
would like to rename the attributes to more user-friendly names
Example:
label_road_network('maryland_counties.shp','network.geojson','countyname00','new_network.geojson', 'CountyName')
'''
links = gpd.GeoDataFrame.from_file(road_network_geojson)
# read input shapefile
shape = gpd.GeoDataFrame.from_file(input_shp)
# if only one attribute
if type(attributes) == str:
attributes = [attributes]
# check if column name in input_shp
for x in attributes:
if x not in shape.columns:
raise ValueError("Column name {} is not in input_shp".format(x))
if len(attributes) != (len(rename_attributes)):
raise ValueError("Number of attributes different from number of rename attributes.")
rename_columns = {}
for i in range(len(attributes)):
rename_columns.update({attributes[i]:rename_attributes[i]})
shape = shape.rename(columns = rename_columns)
# chedk if each attribute is already a property in the road network
for x in rename_attributes:
if x in links.columns:
rejoin = input("Attribute '{}' already in the network geojson, do you want to redo join? (y/n)".format(x))
if rejoin:
links = links.drop(x, 1)
else:
rename_attributes.remove(x)
# if there are any files left to join
if len(rename_attributes) == 0:
print ("There are no new attributes to join")
return None
rename_attributes.append('geometry')
shape = shape[rename_attributes]
# spatial join
links_w_city = sjoin(links, shape, 'left')
links_w_city = links_w_city.reset_index().drop_duplicates(subset='index').set_index('index')
links_w_city = links_w_city.drop('index_right',1)
save_results = check_savepath(geojson_outf)
if save_results:
with open(geojson_outf, 'w') as f:
f.write(links_w_city.to_json())