dataservices-api/server/lib/python/cartodb_services/test/test_mapzenisolines.py
2016-07-06 16:05:51 +02:00

77 lines
2.3 KiB
Python

import unittest
from cartodb_services.mapzen import MapzenIsolines
from math import radians, cos, sin, asin, sqrt
"""
This file is basically a sanity test on the algorithm.
It uses a mocked client, which returns the cost based on a very simple model:
just proportional to the distance from origin to the target point.
"""
class MatrixClientMock():
def __init__(self, speed):
"""
Sets up the mock with a speed in km/h
"""
self._speed = speed
def one_to_many(self, locations, costing):
origin = locations[0]
distances = [self._distance(origin, l) for l in locations]
response = {
'one_to_many': [
[
{
'distance': distances[i] * self._speed,
'time': distances[i] / self._speed * 3600,
'to_index': i,
'from_index': 0
}
for i in xrange(0, len(distances))
]
],
'units': 'km',
'locations': [
locations
]
}
return response
def _distance(self, a, b):
"""
Calculate the great circle distance between two points
on the earth (specified in decimal degrees)
http://stackoverflow.com/questions/4913349/haversine-formula-in-python-bearing-and-distance-between-two-gps-points
Returns:
distance in meters
"""
# convert decimal degrees to radians
lon1, lat1, lon2, lat2 = map(radians, [a['lon'], a['lat'], b['lon'], b['lat']])
# 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))
r = 6371 # Radius of earth in kilometers. Use 3956 for miles
return c * r
class MapzenIsolinesTestCase(unittest.TestCase):
def setUp(self):
speed = 4 # in km/h
matrix_client = MatrixClientMock(speed)
self.mapzen_isolines = MapzenIsolines(matrix_client)
def test_calculate_isochrone(self):
origin = {"lat":40.744014,"lon":-73.990508}
transport_mode = 'walk'
isorange = 10 * 60 # 10 minutes
solution = self.mapzen_isolines.calculate_isochrone(origin, transport_mode, isorange)