def test_exceptions_return_points_in_polygon(self): #If the input s correct it must create a list for i in range(len(self.valid_input)): assert isinstance(gu.return_points_in_polygon(zip(self.reference1, self.reference2),self.valid_input[i]), list) #If it is incorrect(type1)it must raise an exception for i in range(len(self.invalid_input)): self.assertRaises(TypeError, gu.return_points_in_polygon, self.reference1, self.invalid_input[i]) #Similarly for type 2 for i in range(len(self.invalid_input2)): self.assertRaises(TypeError, gu.return_points_in_polygon, self.reference1, self.invalid_input2[i])
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]
def text_output_return_points_in_polygon(self): #Validates that it retunrs a list assert isinstance(gu.return_points_in_polygon(self.reference1,valid_input[0]), list)
