gtfs_plus.py

import csv
import transitfeed
import pandas as pd

def routesft_assume_mode(schedule, default_mode):
    routeid_to_mode_dict = dict(zip(schedule.routes.keys(),[default_mode]*len(schedule.routes.keys())))
    return routeid_to_mode_dict


def get_transfer_dist(schedule):
    for k,v in schedule._transfers.iteritems():
        from_stop_id,to_stop_id = k
        
        from_lat = schedule.stops[from_stop_id].stop_lat
        from_lon = schedule.stops[from_stop_id].stop_lon
        to_lat   = schedule.stops[to_stop_id].stop_lat
        to_lon   = schedule.stops[to_stop_id].stop_lon
        

def haversine((lat1, lon1), (lat2, lon2)):
    """
    Calculate the great circle distance between two points 
    on the earth (specified in decimal degrees)
    returns miles
    """
    from math import radians, cos, sin, asin, sqrt
    # convert decimal degrees to radians 
    lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])
    # haversine formula 
    dlon = lon2 - lon1 
    dlat = lat2 - lat1 
    a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
    c = 2 * asin(sqrt(a)) 
    km = 6367 * c
    miles = 0.621371 * km
    return miles 

def create_tranfers(schedule,max_xfer_dist = 0.5):
    from itertools import combinations
    5 #miles
    
    #create pairwise iterator
    stops = {}
    for key,val in schedule.stops.iteritems():
        stops[key]=(val.stop_lat, val.stop_lon)
    
    pair = list(set(list(combinations(stops, r=2))))
    #print "PAIR",pair
    
    #get xfer distance between each combination
    #potential_xfer_dict = {(pair[0][0],pair[1][0]): haversine(pair[0][1],pair[1][1]) }
    
    potential_xfer_dict = {p:haversine(stops[p[0]],stops[p[1]]) for p in pair }
    
    #delete pairs that are greater than maximum xfer distance
    del_keys = []
    for k,v in potential_xfer_dict.iteritems():
        if v > max_xfer_dist:
            del_keys.append(k)
    for k in del_keys:
        del potential_xfer_dict[k]
        
    #return dictionary with valid values
    return potential_xfer_dict