Das deutsche Python-Forum

Code: Alles auswählen

# -*- coding: utf-8 -*-
"""
Created on Fri Apr 26 10:45:34 2019

@author: Karl Kraft
"""
from __future__ import print_function, division
import numpy as np
from distances_airports_worldwide import get_airport_positions

def haversine(lat1, lat2, lon1, lon2):
    """ calculates the distance in meters between geographical points
    """
    # Haversine formula
    lat1 = np.radians(lat1)
    lat2 = np.radians(lat2)
    lon1 = np.radians(lon1)
    lon2 = np.radians(lon2)
    leftParenthesis = ((lat2 - lat1)/2)
    rightParenthesis = ((lon2 - lon1)/2)
    allUnderSquareRoot = ((np.sin(leftParenthesis))**2) + np.cos(lat1)*np.cos(lat2)*(np.sin(rightParenthesis))**2
    squareRootResult = np.sqrt(allUnderSquareRoot)
    arcSin = np.arcsin(squareRootResult)
    middleEarthRadiusKm = 6371.009
    middleEarthRadiusM = middleEarthRadiusKm * 1000
    distanceMeters = 2 * middleEarthRadiusM * arcSin
    
    return distanceMeters

def haversine_vectorized(coord0, coords):
    """ prepares data vor vectorized use of haversine-function
    """
    lat0, lon0 = coord0
    lats = coords[:,0] # 1. Spalte von coords (= array von latitudes)
    lons = coords[:,1] # 2. Spalte von coords (= array von longitudes)
    result_vectorized = haversine(lat0, lats, lon0, lons)
    
    return result_vectorized

if __name__ == "__main__":
    coords = get_airport_positions("data\\airports.dat", "Germany")
    coord0 = coords[0]
    coords = np.array(coords)
    coord0 = np.array(coord0)
    result_vectorized = haversine_vectorized(coord0, coords) / 1000
    np.set_printoptions(formatter={'float': '{: 0.1f}'.format})
    print(result_vectorized)

Code: Alles auswählen

print(len(coords))
for i in range(7184):
    coord0 = coords[i]

Code: Alles auswählen

coords = get_airport_positions("data\\airports.dat", "All")
counter = 0
# print(len(coords))
for i in range(7184):
    coord0 = coords[i]
    coords = np.array(coords[i+1:]) # slicing von i+1 bis Ende Array

Code: Alles auswählen

coords = get_airport_positions("data\\airports.dat", "All")
coords = np.array(coords)
counter = 0
# print(len(coords))
print(coords.shape)
for i in range(10):
    coord0 = coords[i]
    coords = coords[i+1:] # slicing von i+1 bis Ende Array
    print(len(coords))

Code: Alles auswählen

# -*- coding: utf-8 -*-
"""
Created on Fri Apr 26 10:45:34 2019

@author: Karl Kraft
"""
from __future__ import print_function, division
import numpy as np
from distances_airports_worldwide import get_airport_positions
import time

def haversine(lat1, lat2, lon1, lon2):
    """ calculates the distance in meters between geographical points
    """
    # in: 2 pairs of coordinates
    # out: distance in meters of them
    
    # Haversine formula
    lat1 = np.radians(lat1)
    lat2 = np.radians(lat2)
    lon1 = np.radians(lon1)
    lon2 = np.radians(lon2)
    leftParenthesis = ((lat2 - lat1)/2)
    rightParenthesis = ((lon2 - lon1)/2)
    allUnderSquareRoot = ((np.sin(leftParenthesis))**2) + np.cos(lat1)*np.cos(lat2)*(np.sin(rightParenthesis))**2
    squareRootResult = np.sqrt(allUnderSquareRoot)
    arcSin = np.arcsin(squareRootResult)
    middleEarthRadiusKm = 6371.009
    middleEarthRadiusM = middleEarthRadiusKm * 1000
    distancesMeters = 2 * middleEarthRadiusM * arcSin
    
    return distancesMeters

def haversine_vectorized(coord0, coords):
    """ prepares data vor vectorized use of haversine-function
    """
    # in: one tupel of first 2 coordinates, list of all remainung coordinates
    # out: vectorized result, which is list of kilometers
    lat0, lon0 = coord0
    lats = coords[:,0] # 1. Spalte von coords (= array von latitudes)
    lons = coords[:,1] # 2. Spalte von coords (= array von longitudes)
    result_vectorized = haversine(lat0, lats, lon0, lons)
    
    return result_vectorized

def calc_dist_all2all_airports(airport_file, country):
    """ calculates the distances of each airport to each and adds them
    """
    # in: the file where the airport data are stored, the desired country
    # out: added kilometers of all the distances, number of calculations done
    coords = get_airport_positions(airport_file, country)
    coords = np.array(coords)
    coordsOneValue = coords
    multipleKilometers = []
    counter = 0
    for i in range(len(coords)):
        coord0 = coordsOneValue[i]
        coords = coords[i+1:] # slicing from i+1 until end array
        result_vectorized = haversine_vectorized(coord0, coords) / 1000
        multipleKilometers.extend(result_vectorized)
        counter += 1
    sumKilometers = sum(multipleKilometers)
    nCalculations = counter
    
    return sumKilometers, nCalculations

# number of airports: 7184
if __name__ == "__main__":
    t0 = time.clock()
    sumKilometers, nCalculations = calc_dist_all2all_airports("data\\airports.dat", country="All")
    print("sum kilometers: %10.1f" % (sumKilometers))
    print("number of calculations done: %10.f" % (nCalculations))
    print("Computation of distances took %6.2f secs" % (time.clock()-t0))

Code: Alles auswählen

EARTH_RADIUS_IN_M = 63710090

def haversine(lat1, lat2, lon1, lon2):
    """ calculates the distance in meters between geographical points
    in: 2 pairs of coordinates in radians
    out: distance in meters of them
    """
    mean_lat = (lat2 - lat1) * 0.5
    mean_lon = (lon2 - lon1) * 0.5
    a = np.sin(mean_lat)**2 + np.cos(lat1)*np.cos(lat2)* np.sin(mean_lon)**2
    return 2 * EARTH_RADIUS_IN_M * np.arcsin(a**0.5)

def calc_dist_all2all_airports(airport_file, country):
    """ calculates the distances of each airport to each and adds them
    in: the file where the airport data are stored, the desired country
    out: added kilometers of all the distances, number of calculations done
    """
    coords = get_airport_positions(airport_file, country)
    lat, lon = np.radians(coords).T
    distances = haversine(lat[:, None], lon[:, None], lat[None, :], lon[None, :])
    return distances.sum()/2, len(coords)

# number of airports: 7184
if __name__ == "__main__":
    t0 = time.clock()
    total_distance, number_of_airports = calc_dist_all2all_airports("data\\airports.dat", country="All")
    print("sum of kilometers: %10.1f" % total_distance)
    print("number of airports: %10d" % number_of_airports)
    print("Computation of distances took %6.2f secs" % (time.clock()-t0))