class TestDetection:
def setup_method(self):
latitude = constants.LATITUDE
longitude = constants.LONGITUDE
date_time = constants.DATETIME
user_id = constants.UID
lat_lons = np.array(
[[43.8430139, 10.5079940], [43.5442700, 10.3261500],
[43.7085300, 10.4036000], [43.7792500, 11.2462600],
[43.8430139, 10.5079940], [43.7085300, 10.4036000],
[43.8430139, 10.5079940], [43.5442700, 10.3261500],
[43.5442700, 10.3261500], [43.7085300, 10.4036000],
[43.8430139, 10.5079940], [43.7792500, 11.2462600],
[43.7085300, 10.4036000], [43.5442700, 10.3261500],
[43.7792500, 11.2462600], [43.7085300, 10.4036000],
[43.7792500, 11.2462600], [43.8430139, 10.5079940],
[43.8430139, 10.5079940], [43.5442700, 10.3261500]])
traj = pd.DataFrame(lat_lons, columns=[latitude, longitude])
traj[date_time] = pd.to_datetime([
'20110203 8:34:04', '20110203 9:34:04', '20110203 10:34:04',
'20110204 10:34:04', '20110203 8:34:04', '20110203 9:34:04',
'20110204 10:34:04', '20110204 11:34:04', '20110203 8:34:04',
'20110203 9:34:04', '20110204 10:34:04', '20110204 11:34:04',
'20110204 10:34:04', '20110204 11:34:04', '20110204 12:34:04',
'20110204 10:34:04', '20110204 11:34:04', '20110205 12:34:04',
'20110204 10:34:04', '20110204 11:34:04'
])
traj[user_id] = [1 for _ in range(4)] + [2 for _ in range(4)] + \
[3 for _ in range(4)] + [4 for _ in range(3)] + \
[5 for _ in range(3)] + [6 for _ in range(2)]
self.unique_points = [(43.544270, 10.326150), (43.708530, 10.403600),
(43.779250, 11.246260), (43.843014, 10.507994)]
self.traj = traj.sort_values([user_id, date_time])
self.trjdat = TrajDataFrame(traj, user_id=user_id)
def test_stops(self):
output = detection.stops(self.trjdat)
expected = self.trjdat.drop([3, 7, 11, 14, 17, 19])
stamps = [
pd.Timestamp('2011-02-03 09:34:04'),
pd.Timestamp('2011-02-03 10:34:04'),
pd.Timestamp('2011-02-04 10:34:04'),
pd.Timestamp('2011-02-03 09:34:04'),
pd.Timestamp('2011-02-04 10:34:04'),
pd.Timestamp('2011-02-04 11:34:04'),
pd.Timestamp('2011-02-03 09:34:04'),
pd.Timestamp('2011-02-04 10:34:04'),
pd.Timestamp('2011-02-04 11:34:04'),
pd.Timestamp('2011-02-04 11:34:04'),
pd.Timestamp('2011-02-04 12:34:04'),
pd.Timestamp('2011-02-04 11:34:04'),
pd.Timestamp('2011-02-05 12:34:04'),
pd.Timestamp('2011-02-04 11:34:04')
]
expected['leaving_datetime'] = stamps
output.reset_index(inplace=True)
output.drop(columns=['index'], inplace=True)
expected.reset_index(inplace=True)
expected.drop(columns=['index'], inplace=True)
# assert
pd.testing.assert_frame_equal(output, expected, check_dtype=False)
output = detection.stops(self.trjdat,
minutes_for_a_stop=60.0,
leaving_time=False)
expected = self.trjdat.drop(
[0, 1, 3, 4, 6, 7, 8, 10, 11, 12, 13, 14, 15, 17, 18, 19])
output.reset_index(inplace=True)
output.drop(columns=['index'], inplace=True)
expected.reset_index(inplace=True)
expected.drop(columns=['index'], inplace=True)
# assert
pd.testing.assert_frame_equal(output, expected, check_dtype=False)
def test_compress(self):
output = compression.compress(self.trjdat)
expected = self.trjdat.copy()
output.reset_index(inplace=True)
output.drop(columns=['index'], inplace=True)
expected.reset_index(inplace=True)
expected.drop(columns=['index'], inplace=True)
# assert
pd.testing.assert_frame_equal(output, expected)
output = compression.compress(self.trjdat, spatial_radius_km=20)
expected = TrajDataFrame(
{
"lat": {
"0": 43.8430139,
"1": 43.6264,
"2": 43.77925,
"3": 43.8430139,
"4": 43.54427,
"5": 43.6264,
"6": 43.8430139,
"7": 43.77925,
"8": 43.6264,
"9": 43.77925,
"10": 43.70853,
"11": 43.77925,
"12": 43.8430139,
"13": 43.8430139,
"14": 43.54427
},
"lng": {
"0": 10.507994,
"1": 10.364875,
"2": 11.24626,
"3": 10.507994,
"4": 10.32615,
"5": 10.364875,
"6": 10.507994,
"7": 11.24626,
"8": 10.364875,
"9": 11.24626,
"10": 10.4036,
"11": 11.24626,
"12": 10.507994,
"13": 10.507994,
"14": 10.32615
},
"datetime": {
"0": 1296722044,
"1": 1296725644,
"2": 1296815644,
"3": 1296722044,
"4": 1296819244,
"5": 1296722044,
"6": 1296815644,
"7": 1296819244,
"8": 1296815644,
"9": 1296822844,
"10": 1296815644,
"11": 1296819244,
"12": 1296909244,
"13": 1296815644,
"14": 1296819244
},
"uid": {
"0": 1,
"1": 1,
"2": 1,
"3": 2,
"4": 2,
"5": 3,
"6": 3,
"7": 3,
"8": 4,
"9": 4,
"10": 5,
"11": 5,
"12": 5,
"13": 6,
"14": 6
}
},
timestamp=True)
output.reset_index(inplace=True)
output.drop(columns=['index'], inplace=True)
expected.reset_index(inplace=True)
expected.drop(columns=['index'], inplace=True)
# assert
pd.testing.assert_frame_equal(output, expected, check_dtype=False)
class TestFiltering:
def setup_method(self):
latitude = constants.LATITUDE
longitude = constants.LONGITUDE
date_time = constants.DATETIME
user_id = constants.UID
lat_lons = np.array(
[[43.8430139, 10.5079940], [43.5442700, 10.3261500],
[43.7085300, 10.4036000], [43.7792500, 11.2462600],
[43.8430139, 10.5079940], [43.7085300, 10.4036000],
[43.8430139, 10.5079940], [43.5442700, 10.3261500],
[43.5442700, 10.3261500], [43.7085300, 10.4036000],
[43.8430139, 10.5079940], [43.7792500, 11.2462600],
[43.7085300, 10.4036000], [43.5442700, 10.3261500],
[43.7792500, 11.2462600], [43.7085300, 10.4036000],
[43.7792500, 11.2462600], [43.8430139, 10.5079940],
[43.8430139, 10.5079940], [43.5442700, 10.3261500]])
traj = pd.DataFrame(lat_lons, columns=[latitude, longitude])
traj[date_time] = pd.to_datetime([
'20110203 8:34:04', '20110203 9:34:04', '20110203 10:34:04',
'20110204 10:34:04', '20110203 8:34:04', '20110203 9:34:04',
'20110204 10:34:04', '20110204 11:34:04', '20110203 8:34:04',
'20110203 9:34:04', '20110204 10:34:04', '20110204 11:34:04',
'20110204 10:34:04', '20110204 11:34:04', '20110204 12:34:04',
'20110204 10:34:04', '20110204 11:34:04', '20110205 12:34:04',
'20110204 10:34:04', '20110204 11:34:04'
])
traj[user_id] = [1 for _ in range(4)] + [2 for _ in range(4)] + \
[3 for _ in range(4)] + [4 for _ in range(3)] + \
[5 for _ in range(3)] + [6 for _ in range(2)]
self.unique_points = [(43.544270, 10.326150), (43.708530, 10.403600),
(43.779250, 11.246260), (43.843014, 10.507994)]
self.traj = traj.sort_values([user_id, date_time])
self.trjdat = TrajDataFrame(traj, user_id=user_id)
def test_filter(self):
output = filtering.filter(self.trjdat, max_speed_kmh=10.)
expected = self.trjdat.drop([1, 5, 9, 13, 16])
output.reset_index(inplace=True)
output.drop(columns=['index'], inplace=True)
expected.reset_index(inplace=True)
expected.drop(columns=['index'], inplace=True)
# assert
pd.testing.assert_frame_equal(output, expected)
output = filtering.filter(self.trjdat, max_speed_kmh=120.)
expected = self.trjdat
# assert
pd.testing.assert_frame_equal(output, expected)
output = filtering.filter(self.trjdat, max_speed_kmh=10., max_loop=1)
expected = self.trjdat.drop([1, 5, 9, 13, 16])
output.reset_index(inplace=True)
output.drop(columns=['index'], inplace=True)
expected.reset_index(inplace=True)
expected.drop(columns=['index'], inplace=True)
# assert
pd.testing.assert_frame_equal(output, expected)
output = filtering.filter(self.trjdat,
max_speed_kmh=10.,
ratio_max=0.9)
expected = self.trjdat.drop([1, 5, 9, 13, 16])
output.reset_index(inplace=True)
output.drop(columns=['index'], inplace=True)
expected.reset_index(inplace=True)
expected.drop(columns=['index'], inplace=True)
# assert
pd.testing.assert_frame_equal(output, expected)