import gpxpy
from getgpx import get_points
file = open('09_27_20.gpx', 'r')
parseado = gpxpy.parse(file)
position = get_points(
parseado
) #array of objects that hold information like lat, long, elev, time.
with open("improved_results.txt") as f:
content = f.readlines()
# you may also want to remove whitespace characters like `\n` at the end of each line
content = [x.strip() for x in content]
list = []
for i in content:
if i != "":
temp = (i.replace(']', ''))
temp1 = (temp.replace('[', ''))
temp2 = (temp1.replace(',', ''))
# parte = (temp1.replace(',', ''))
# print(parte)
numero = temp2.split(" ")
list.append(numero[0].strip())
for i in list:
print("{},".format(i), end="")
# for i in list:
# print("{0},{1}\n".format(position[i].get_lat(), position[i].get_long())
#
from getgpx import get_points
import gpxpy
from math import cos, sin, asin, radians, sqrt
file = open('09_27_20.gpx',
'r') #just for testing, it won't be here in final version
parseado = gpxpy.parse(file)
list = get_points(
parseado
) #array of objects that hold information like lat, long, elev, time. It holds all the info from the gpx file, every point (Look up in getgpx.py to see how the class is defined)
#start and end points in the gpx file. This function will roll over each point and calculate the distance of a segment(from one point to another) and add up to give the total distance.
#The way I have organized everything is that the function that detects changes in street will return the index value where this happens and return the index (among the name of the street) For instance, the route starts in NW Sprouce Ave (index 0,44.587662, -123.256691) and goes to Higland dr (index 88, 44.587414, -123.2624050 and turns right. Now, if we put start = 0 and end = 88), it returns the distance of all the points between that range.
#calculates distance between two points using the harvestein formula for spheric shapes.
def distance(ini_lat, ini_lon, fin_lat, fin_lon):
dif_lat = radians(ini_lat) - radians(fin_lat)
dif_lon = radians(ini_lon) - radians(fin_lon)
earth_radio = 6371 #radius in km
distance = (sin(dif_lat / 2))**2 + cos(radians(ini_lat)) * cos(
radians(fin_lat)) * (sin(dif_lon / 2))**2
distancia = earth_radio * asin(
sqrt(distance)
) * 2 * 1000 # multiply by 1000 to convert to distance in meters
return distancia
def route_distance(start, end):
segment = 0
import gpxpy
import time
# import threading
from searcher import *
from getgpx import get_points
from calculations import Mathematica
# from multiprocessing import Process#to run concurrently.
start_time = time.time() #record time
# #get the points from the gpx file
file = open('09_27_20.gpx',
'r') #for testing, it won't be here for final version
gpx_list = gpxpy.parse(file)
list_coordinates = get_points(
gpx_list
) #array of objects that hold information like lat, long, elev, time.
ruta = Route(list_coordinates)
resultado = ruta.result(0, 100)
print(resultado)
# o = 0
# for i in list_coordinates:
# o +=1
# print(o)
# # print(i.get_lat())
# points = Route(list)
# print(len(list))
# calc = Mathematica()