def test_equal_distance_between_points(self): #Distance should be the same, no matter the order the points are inputted distance1 = gu.calculate_distance_between_points(self.reference1[0], self.reference1[1], self.reference2[0],self.reference2[1]) distance2 = gu.calculate_distance_between_points(self.reference2[0], self.reference2[1], self.reference1[0],self.reference1[1]) self.assertEqual(distance2, distance1)
def __init__(self, address = None):
if address:
if not self._is_in_chicago(address):
raise ValueError('Address not in Chicago')
else:
self.get_address()
self.formatted_address = self.address_info['formatted_address']
self.lat,self.lon = self._get_address_lat_lon()
self.district = get_district_from_lat_lon((self.lat,self.lon))
self.street_address = self._get_street_address()
police_station_lat, police_station_lon = get_police_station_coordinates(self.district)
self.distance_to_police_station = calculate_distance_between_points(self.lat,self.lon, police_station_lat, police_station_lon)
self.summary = None
def _get_data_crime_circle(self,fullDataCrime):
""" Receives a non-filtered DF
Computes the database of the points inside the circle by filtering them by distance
:param fullDataCrime
"""
#Getting boundaries
boundaries = self._get_circle_boundaries()
districts = fullDataCrime['District'].unique()
if len(districts)== 0:
raise ValueError("There are no districts in data")
district_polygons = {dist: du.get_polygon(dist) for dist in districts}
districts_to_search = []
#Filtering districts where the circle has values, to optimize time
for bound in boundaries:
for dist in district_polygons.keys():
if dist not in districts_to_search:
if gu.return_points_in_polygon([bound],district_polygons[dist]):
districts_to_search.append(dist)
dataframe = fullDataCrime[fullDataCrime['District'].isin(districts_to_search)]
#Getting the points inside of circle by distance (less equal than 1 mile)
index_of_entries_in_circle = []
for entry in dataframe.index:
lat, lon = dataframe.ix[entry].Latitude, dataframe.ix[entry].Longitude
if gu.calculate_distance_between_points(self.address.lat, self.address.lon, lat, lon) <= 1:
index_of_entries_in_circle.append(entry)
return dataframe.ix[index_of_entries_in_circle]
