def test_attribute_error_from_data_frame():
df = DataFrame(
data=[
[39.984094, 116.319236, Timestamp('2008-10-23 05:53:05'), 1],
[39.984198, 116.319322, Timestamp('2008-10-23 05:53:06'), 1],
[39.984224, 116.319402, Timestamp('2008-10-23 05:53:11'), 2],
[39.984224, 116.319402, Timestamp('2008-10-23 05:53:11'), 2],
],
columns=['laterr', 'lon', 'datetime', 'id'],
index=[0, 1, 2, 3],
)
try:
MoveDataFrame(
data=df, latitude=LATITUDE, longitude=LONGITUDE, datetime=DATETIME
)
raise AssertionError(
'AttributeError error not raised by MoveDataFrame'
)
except KeyError:
pass
df = DataFrame(
data=[
[39.984094, 116.319236, Timestamp('2008-10-23 05:53:05'), 1],
[39.984198, 116.319322, Timestamp('2008-10-23 05:53:06'), 1],
[39.984224, 116.319402, Timestamp('2008-10-23 05:53:11'), 2],
[39.984224, 116.319402, Timestamp('2008-10-23 05:53:11'), 2],
],
columns=['lat', 'lonerr', 'datetime', 'id'],
index=[0, 1, 2, 3],
)
try:
MoveDataFrame(
data=df, latitude=LATITUDE, longitude=LONGITUDE, datetime=DATETIME
)
raise AssertionError(
'AttributeError error not raised by MoveDataFrame'
)
except KeyError:
pass
df = DataFrame(
data=[
[39.984094, 116.319236, Timestamp('2008-10-23 05:53:05'), 1],
[39.984198, 116.319322, Timestamp('2008-10-23 05:53:06'), 1],
[39.984224, 116.319402, Timestamp('2008-10-23 05:53:11'), 2],
[39.984224, 116.319402, Timestamp('2008-10-23 05:53:11'), 2],
],
columns=['lat', 'lon', 'datetimerr', 'id'],
index=[0, 1, 2, 3],
)
try:
MoveDataFrame(
data=df, latitude=LATITUDE, longitude=LONGITUDE, datetime=DATETIME
)
raise AssertionError(
'AttributeError error not raised by MoveDataFrame'
)
except KeyError:
pass
def test_move_data_frame_from_list():
move_df = _default_move_df()
assert MoveDataFrame.has_columns(move_df)
try:
MoveDataFrame.validate_move_data_frame(move_df)
except Exception:
assert False
assert isinstance(move_df, PandasMoveDataFrame)
def test_MEDP():
expected = 241.91923668814994
move_df1 = MoveDataFrame(data=traj_example1)
move_df2 = MoveDataFrame(data=traj_example2)
medp = distances.MEDP(move_df1, move_df2)
assert_almost_equal(medp, expected)
def test_MEDT():
expected = 619.9417037397966
move_df1 = MoveDataFrame(data=traj_example1)
move_df2 = MoveDataFrame(data=traj_example3)
medt = distances.MEDT(move_df1, move_df2)
assert_almost_equal(medt, expected)
def test_to_grid():
move_df = MoveDataFrame(
data=list_data,
latitude=LATITUDE,
longitude=LONGITUDE,
datetime=DATETIME,
traj_id=TRAJ_ID,
)
assert isinstance(move_df.to_grid(8), pymove.core.grid.Grid)
def test_to_data_frame():
move_df = MoveDataFrame(
data=list_data,
latitude=LATITUDE,
longitude=LONGITUDE,
datetime=DATETIME,
traj_id=TRAJ_ID,
)
assert isinstance(move_df.to_data_frame(), DataFrame)
def test_move_data_frame_from_data_frame():
df = _default_pandas_df()
move_df = MoveDataFrame(
data=df, latitude=LATITUDE, longitude=LONGITUDE, datetime=DATETIME
)
assert MoveDataFrame.has_columns(move_df)
try:
MoveDataFrame.validate_move_data_frame(move_df)
except Exception:
assert False
assert isinstance(move_df, PandasMoveDataFrame)
def test_number_users():
move_df = MoveDataFrame(
data=list_data,
latitude=LATITUDE,
longitude=LONGITUDE,
datetime=DATETIME,
traj_id=TRAJ_ID,
)
assert move_df.get_users_number() == 1
move_df[UID] = [1, 1, 2, 3]
assert move_df.get_users_number() == 3
def test_join_colletive_areas():
move_df = MoveDataFrame(data=list_move, )
move_df['geometry'] = move_df.apply(lambda x: Point(x['lon'], x['lat']),
axis=1)
expected = move_df.copy()
indexes_ac = np.linspace(0, move_df.shape[0], 5, dtype=int)
area_c = move_df[move_df.index.isin(indexes_ac)].copy()
integration.join_collective_areas(move_df, area_c, inplace=True)
expected[VIOLATING] = [
True, False, True, False, True, False, True, False, False
]
assert_frame_equal(move_df, expected)
def test_append():
move_df = _default_move_df()
df = DataFrame(
data=[[39.984094, 116.319236,
Timestamp('2008-10-23 05:53:05'), 1]],
columns=['lat', 'lon', 'datetime', 'id'],
index=[0],
)
mdf = MoveDataFrame(df)
expected = DataFrame(
data=[
[39.984094, 116.319236,
Timestamp('2008-10-23 05:53:05'), 1],
[39.984198, 116.319322,
Timestamp('2008-10-23 05:53:06'), 1],
[39.984224, 116.319402,
Timestamp('2008-10-23 05:53:11'), 2],
[39.984224, 116.319402,
Timestamp('2008-10-23 05:53:11'), 2],
[39.984094, 116.319236,
Timestamp('2008-10-23 05:53:05'), 1],
],
columns=['lat', 'lon', 'datetime', 'id'],
index=[0, 1, 2, 3, 0],
)
assert_frame_equal(move_df.append(df), expected)
assert_frame_equal(move_df.append(mdf), expected)
def test_move_data_frame_from_data_frame():
df = DataFrame(
data=[
[39.984094, 116.319236,
Timestamp('2008-10-23 05:53:05'), 1],
[39.984198, 116.319322,
Timestamp('2008-10-23 05:53:06'), 1],
[39.984224, 116.319402,
Timestamp('2008-10-23 05:53:11'), 2],
[39.984224, 116.319402,
Timestamp('2008-10-23 05:53:11'), 2],
],
columns=['lat', 'lon', 'datetime', 'id'],
index=[0, 1, 2, 3],
)
move_df = MoveDataFrame(
data=df,
latitude=LATITUDE,
longitude=LONGITUDE,
datetime=DATETIME,
type_=TYPE_DASK,
)
assert _has_columns(move_df)
assert _validate_move_data_frame_data(move_df)
assert isinstance(move_df, DaskMoveDataFrame)
def _prepare_df_with_dist_time_speed():
move_df = MoveDataFrame(
data=list_data_2,
latitude=LATITUDE,
longitude=LONGITUDE,
datetime=DATETIME,
)
move_df[DIST_TO_PREV] = [
nan,
13.884481484192932,
140454.64510608764,
140460.97747220137,
1.3208180727070074,
]
move_df[TIME_TO_PREV] = [nan, 1.0, 5.0, 5.0, 5.0]
move_df[SPEED_TO_PREV] = [
nan,
13.884481484192932,
28090.92902121753,
28092.195494440275,
0.26416361454140147,
]
cols = [
'id',
'lat',
'lon',
'datetime',
'dist_to_prev',
'time_to_prev',
'speed_to_prev',
]
return move_df[cols], cols
def test_join_with_pois():
move_df = MoveDataFrame(list_move)
pois = DataFrame(
data=list_pois,
columns=[LATITUDE, LONGITUDE, TRAJ_ID, TYPE_POI, NAME_POI],
index=[0, 1, 2, 3, 4, 5, 6])
expected = DataFrame(data=[[
39.984094, 116.319236,
Timestamp('2008-10-23 05:53:05'), 1, 1, 0.0, 'distrito_pol_1'
],
[
39.984559000000004, 116.326696,
Timestamp('2008-10-23 10:37:26'), 1, 6,
128.24869775642176, 'adocao_de_animais'
],
[
40.002899, 116.32151999999999,
Timestamp('2008-10-23 10:50:16'), 1, 5,
663.0104596559174, 'rinha_de_galo_world_cup'
],
[
40.016238, 116.30769099999999,
Timestamp('2008-10-23 11:03:06'), 1, 4,
286.3387434682031, 'forro_tropykalia'
],
[
40.013814, 116.306525,
Timestamp('2008-10-23 11:58:33'), 2, 4,
0.9311014399622559, 'forro_tropykalia'
],
[
40.009735, 116.315069,
Timestamp('2008-10-23 23:50:45'), 2, 3,
211.06912863495492, 'supermercado_aroldo'
],
[
39.993527, 116.32648300000001,
Timestamp('2008-10-24 00:02:14'), 2, 2,
279.6712398549538, 'policia_federal'
],
[
39.978575, 116.326975,
Timestamp('2008-10-24 00:22:01'), 3, 6,
792.7526066105717, 'adocao_de_animais'
],
[
39.981668, 116.310769,
Timestamp('2008-10-24 01:57:57'), 3, 7,
270.7018856738821, 'dia_do_municipio'
]],
columns=[
LATITUDE, LONGITUDE, DATETIME, TRAJ_ID, ID_POI,
DIST_POI, NAME_POI
],
index=[0, 1, 2, 3, 4, 5, 6, 7, 8])
integration.join_with_pois(move_df, pois, inplace=True)
assert_frame_equal(move_df, expected, check_dtype=False)
def _prepare_df_with_long_trajectory():
move_df = MoveDataFrame(
data=list_data_3,
latitude=LATITUDE,
longitude=LONGITUDE,
datetime=DATETIME,
)
move_df[DIST_TO_PREV] = [
nan,
13.884481484192932,
7.563335999941849,
1.3208180727070074,
nan,
2039.4197149375298,
]
move_df[TIME_TO_PREV] = [nan, 61.00000000000001, 70.0, 65.0, nan, 5.0]
move_df[SPEED_TO_PREV] = [
nan,
0.22761445056053983,
0.10804765714202641,
0.020320278041646267,
nan,
407.883942987506,
]
cols = [
'id',
'lat',
'lon',
'datetime',
'dist_to_prev',
'time_to_prev',
'speed_to_prev',
]
return move_df[cols], cols
def test_move_data_frame_from_file(tmpdir):
d = tmpdir.mkdir('core')
file_default_columns = d.join('test_read_default.csv')
file_default_columns.write(str_data_default)
filename_default = os.path.join(
file_default_columns.dirname, file_default_columns.basename
)
move_df = read_csv(filename_default)
assert MoveDataFrame.has_columns(move_df)
try:
MoveDataFrame.validate_move_data_frame(move_df)
except Exception:
assert False
assert isinstance(move_df, PandasMoveDataFrame)
file_different_columns = d.join('test_read_different.csv')
file_different_columns.write(str_data_different)
filename_diferent = os.path.join(
file_different_columns.dirname, file_different_columns.basename
)
move_df = read_csv(
filename_diferent,
latitude='latitude',
longitude='longitude',
datetime='time',
traj_id='traj_id',
)
assert MoveDataFrame.has_columns(move_df)
try:
MoveDataFrame.validate_move_data_frame(move_df)
except Exception:
assert False
assert isinstance(move_df, PandasMoveDataFrame)
file_missing_columns = d.join('test_read_missing.csv')
file_missing_columns.write(str_data_missing)
filename_missing = os.path.join(
file_missing_columns.dirname, file_missing_columns.basename
)
move_df = read_csv(
filename_missing, names=[LATITUDE, LONGITUDE, DATETIME, TRAJ_ID]
)
assert MoveDataFrame.has_columns(move_df)
try:
MoveDataFrame.validate_move_data_frame(move_df)
except Exception:
assert False
assert isinstance(move_df, PandasMoveDataFrame)
def test_move_data_frame_from_data_frame():
df = _default_pandas_df()
move_df = MoveDataFrame(
data=df, latitude=LATITUDE, longitude=LONGITUDE, datetime=DATETIME
)
assert _has_columns(move_df)
assert _validate_move_data_frame_data(move_df)
assert isinstance(move_df, PandasMoveDataFrame)
def _default_move_df():
return MoveDataFrame(
data=list_data,
latitude=LATITUDE,
longitude=LONGITUDE,
datetime=DATETIME,
traj_id=TRAJ_ID,
)
def test_merge_home_with_poi():
list_move4merge = [
[39.984094, 116.319236, Timestamp('2008-10-23 05:53:05'), 1],
[39.984559000000004, 116.326696, Timestamp('2008-10-23 10:37:26'), 1],
[40.002899, 116.32151999999999, Timestamp('2008-10-23 10:50:16'), 1],
[40.016238, 116.30769099999999, Timestamp('2008-10-23 11:03:06'), 1],
[40.013814, 116.306525, Timestamp('2008-10-23 11:58:33'), 2],
[40.009735, 116.315069, Timestamp('2008-10-23 23:50:45'), 2],
[39.993527, 116.32648300000001, Timestamp('2008-10-24 00:02:14'), 2],
]
move_df = MoveDataFrame(list_move4merge)
pois = DataFrame(
data=list_pois,
columns=[LATITUDE, LONGITUDE, TRAJ_ID, TYPE_POI, NAME_POI],
index=[0, 1, 2, 3, 4, 5, 6]
)
integration.join_with_pois(move_df, pois)
list_home = [
[39.984094, 116.319236, 1, 'rua da mae', 'quixiling'],
[40.013821, 116.306531, 2, 'rua da familia', 'quixeramoling']
]
home_df = DataFrame(
data=list_home,
columns=[LATITUDE, LONGITUDE, TRAJ_ID, ADDRESS, CITY],
index=[0, 1]
)
integration.join_with_home_by_id(move_df, home_df)
expected = DataFrame(
data=[
[1, 39.984094, 116.319236, Timestamp('2008-10-23 05:53:05'),
'rua da mae', 0.0, 'home', 'quixiling'],
[1, 39.984559000000004, 116.326696,
Timestamp('2008-10-23 10:37:26'), 6, 128.24869775642176,
'adocao_de_animais', 'quixiling'],
[1, 40.002899, 116.32151999999999,
Timestamp('2008-10-23 10:50:16'), 5, 663.0104596559174,
'rinha_de_galo_world_cup', 'quixiling'],
[1, 40.016238, 116.30769099999999,
Timestamp('2008-10-23 11:03:06'), 4, 286.3387434682031,
'forro_tropykalia', 'quixiling'],
[2, 40.013814, 116.306525, Timestamp('2008-10-23 11:58:33'),
'rua da familia', 0.9311014399622559, 'home', 'quixeramoling'],
[2, 40.009735, 116.315069, Timestamp('2008-10-23 23:50:45'), 3,
211.06912863495492, 'supermercado_aroldo', 'quixeramoling'],
[2, 39.993527, 116.32648300000001,
Timestamp('2008-10-24 00:02:14'), 2, 279.6712398549538,
'policia_federal', 'quixeramoling']
],
columns=[
TRAJ_ID, LATITUDE, LONGITUDE, DATETIME, ID_POI, DIST_POI, NAME_POI, CITY
],
index=[0, 1, 2, 3, 4, 5, 6]
)
integration.merge_home_with_poi(move_df)
assert_frame_equal(move_df, expected, check_dtype=False)
def read_postgres(
query,
in_memory=True,
type_=TYPE_PANDAS,
dbname='postgres',
user='******',
psswrd='',
host='localhost',
port=5432,
):
"""
Builds a dataframe from a query to a postgres database.
Parameters
----------
query : string
Sql query
in_memory : bool, default True
Whether te operation will be executed in memory
type_ : 'pandas', 'dask' or None, defaults 'pandas'
It will try to convert the dataframe into a MoveDataFrame
dbname : string, default 'postgres'
Name of the database
user : string, default 'postgres'
The user connecting to the database
psswrd : string, default ''
The password of the database
host : string, default 'localhost'
The address of the database
port : int, default 5432
The port of the database in the host
Returns
-------
PandasMoveDataFrame, DaskMoveDataFrame or PandasDataFrame
a dataframe object containing the result from the query
"""
conn = None
try:
conn = connect_postgres(dbname, user, psswrd, host, port)
if in_memory:
dataframe = read_sql_inmem_uncompressed(query, conn)
else:
dataframe = read_sql_tmpfile(query, conn)
except Exception as e:
if conn is not None:
conn.close()
raise e
finally:
if conn is not None:
conn.close()
try:
return MoveDataFrame(dataframe, type_=type_)
except Exception:
return dataframe
def _prepare_df_default(list_data):
move_df = MoveDataFrame(
data=list_data,
latitude=LATITUDE,
longitude=LONGITUDE,
datetime=DATETIME,
traj_id=TRAJ_ID,
)
cols = ['lat', 'lon', 'datetime', 'id']
return move_df, cols
def _default_traj_df(data=None):
if data is None:
data = traj_example
return MoveDataFrame(
data=data,
latitude=LATITUDE,
longitude=LONGITUDE,
datetime=DATETIME,
traj_id=TRAJ_ID,
)
def test__reset_set_window__and_creates_event_id_type():
list_events = [[
39.984094, 116.319236, 1,
Timestamp('2008-10-24 01:57:57'), 'show do tropykalia'
],
[
39.991013, 116.326384, 2,
Timestamp('2008-10-24 00:22:01'), 'evento da prefeitura'
],
[
40.01, 116.312615, 3,
Timestamp('2008-10-25 00:21:01'), 'show do seu joao'
],
[
40.013821, 116.306531, 4,
Timestamp('2008-10-26 00:22:01'), 'missa'
]]
move_df = MoveDataFrame(list_move)
pois = DataFrame(
data=list_events,
columns=[LATITUDE, LONGITUDE, EVENT_ID, DATETIME, EVENT_TYPE],
index=[0, 1, 2, 3])
list_win_start = [
'2008-10-22T17:23:05.000000000', '2008-10-22T22:07:26.000000000',
'2008-10-22T22:20:16.000000000', '2008-10-22T22:33:06.000000000',
'2008-10-22T23:28:33.000000000', '2008-10-23T11:20:45.000000000',
'2008-10-23T11:32:14.000000000', '2008-10-23T11:52:01.000000000',
'2008-10-23T13:27:57.000000000'
]
win_start_expected = Series(pd.to_datetime(list_win_start), name=DATETIME)
list_win_end = [
'2008-10-23T18:23:05.000000000', '2008-10-23T23:07:26.000000000',
'2008-10-23T23:20:16.000000000', '2008-10-23T23:33:06.000000000',
'2008-10-24T00:28:33.000000000', '2008-10-24T12:20:45.000000000',
'2008-10-24T12:32:14.000000000', '2008-10-24T12:52:01.000000000',
'2008-10-24T14:27:57.000000000'
]
win_end_expected = Series(pd.to_datetime(list_win_end), name=DATETIME)
dist_expected = np.full(9, np.Infinity, dtype=np.float64)
type_expected = np.full(9, '', dtype='object_')
id_expected = np.full(9, '', dtype='object_')
window_starts, window_ends, current_distances, event_id, event_type = (
integration._reset_set_window__and_creates_event_id_type(
move_df, pois, 45000, DATETIME))
assert_series_equal(window_starts, win_start_expected)
assert_series_equal(window_ends, win_end_expected)
assert_array_almost_equal(current_distances, dist_expected)
assert_array_equal(event_id, id_expected)
assert_array_equal(event_type, type_expected)
def test_move_data_frame_from_dict():
dict_data = {
LATITUDE: [39.984198, 39.984224, 39.984094],
LONGITUDE: [116.319402, 116.319322, 116.319402],
DATETIME: [
'2008-10-23 05:53:11',
'2008-10-23 05:53:06',
'2008-10-23 05:53:06',
],
}
move_df = MoveDataFrame(
data=dict_data,
latitude=LATITUDE,
longitude=LONGITUDE,
datetime=DATETIME,
traj_id=TRAJ_ID,
)
assert MoveDataFrame.has_columns(move_df)
try:
MoveDataFrame.validate_move_data_frame(move_df)
except Exception:
assert False
assert isinstance(move_df, PandasMoveDataFrame)
def test__reset_and_creates_id_and_lat_lon():
move_df = MoveDataFrame(list_move)
pois = DataFrame(
data=list_pois,
columns=[LATITUDE, LONGITUDE, TRAJ_ID, TYPE_POI, NAME_POI],
index=[0, 1, 2, 3, 4, 5, 6])
dists, ids, tags, lats, lons = (
integration._reset_and_creates_id_and_lat_lon(move_df, pois, True,
True))
id_expected = np.full(9, '', dtype='object_')
tag_expected = np.full(9, '', dtype='object_')
dist_expected = np.full(9, np.Infinity, dtype=np.float64)
lat_expected = np.full(7, np.Infinity, dtype=np.float64)
lon_expected = np.full(7, np.Infinity, dtype=np.float64)
assert_array_almost_equal(dists, dist_expected)
assert_array_equal(ids, id_expected)
assert_array_equal(tags, tag_expected)
assert_array_almost_equal(lats, lat_expected)
assert_array_almost_equal(lons, lon_expected)
dists, ids, tags, lats, lons = (
integration._reset_and_creates_id_and_lat_lon(move_df, pois, True,
False))
assert_array_almost_equal(dists, dist_expected)
assert_array_equal(ids, id_expected)
assert_array_equal(tags, tag_expected)
assert_array_almost_equal(lats, lat_expected)
assert_array_almost_equal(lons, lon_expected)
dists, ids, tags, lats, lons = (
integration._reset_and_creates_id_and_lat_lon(move_df, pois, False,
True))
lat_expected = np.full(9, np.Infinity, dtype=np.float64)
lon_expected = np.full(9, np.Infinity, dtype=np.float64)
assert_array_almost_equal(dists, dist_expected)
assert_array_equal(ids, id_expected)
assert_array_equal(tags, tag_expected)
assert_array_almost_equal(lats, lat_expected)
assert_array_almost_equal(lons, lon_expected)
dists, ids, tags, lats, lons = (
integration._reset_and_creates_id_and_lat_lon(move_df, pois, False,
False))
assert_array_almost_equal(dists, dist_expected)
assert_array_equal(ids, id_expected)
assert_array_equal(tags, tag_expected)
assert_array_almost_equal(lats, lat_expected)
assert_array_almost_equal(lons, lon_expected)
def test_join_with_pois_by_category():
move_df = MoveDataFrame(list_move)
pois = DataFrame(
data=list_pois,
columns=[LATITUDE, LONGITUDE, TRAJ_ID, TYPE_POI, NAME_POI],
index=[0, 1, 2, 3, 4, 5, 6]
)
expected = DataFrame(
data=[
[39.984094, 116.319236, Timestamp('2008-10-23 05:53:05'), 1, 1,
0.0, 3, 2935.3102772960456, 7, 814.8193850933852, 5,
2672.393533820207, 6, 675.1730686007362],
[39.984559000000004, 116.326696, Timestamp('2008-10-23 10:37:26'),
1, 1, 637.6902157810676, 3, 3072.6963790707114, 7,
1385.3649632111096, 5, 2727.1360691122813, 6, 128.24869775642176],
[40.002899, 116.32151999999999, Timestamp('2008-10-23 10:50:16'),
1, 2, 1385.0871812075436, 3, 1094.8606633486436, 4,
1762.0085654338782, 5, 663.0104596559174, 6, 1965.702358742657],
[40.016238, 116.30769099999999, Timestamp('2008-10-23 11:03:06'),
1, 2, 3225.288830967221, 3, 810.5429984051405, 4,
286.3387434682031, 5, 1243.8915481769327, 6, 3768.0652637796675],
[40.013814, 116.306525, Timestamp('2008-10-23 11:58:33'), 2, 2,
3047.8382223981853, 3, 669.9731550451877, 4, 0.9311014399622559,
5, 1145.172578151837, 6, 3574.252994707609],
[40.009735, 116.315069, Timestamp('2008-10-23 23:50:45'), 2, 2,
2294.0758201547073, 3, 211.06912863495492, 4, 857.4175399672413,
5, 289.35378153627966, 6, 2855.1657930463994],
[39.993527, 116.32648300000001, Timestamp('2008-10-24 00:02:14'),
2, 2, 279.6712398549538, 3, 2179.5701631051966, 7,
2003.4096341742952, 5, 1784.3132149978549, 6, 870.5252810680124],
[39.978575, 116.326975, Timestamp('2008-10-24 00:22:01'), 3, 1,
900.7798955139455, 3, 3702.2394204188754, 7, 1287.7039084016499,
5, 3376.4438614084356, 6, 792.7526066105717],
[39.981668, 116.310769, Timestamp('2008-10-24 01:57:57'), 3, 1,
770.188754517813, 3, 3154.296880053552, 7, 270.7018856738821, 5,
2997.898227057909, 6, 1443.9247752786023]
],
columns=[
LATITUDE, LONGITUDE, DATETIME, TRAJ_ID, 'id_policia', 'dist_policia',
'id_comercio', 'dist_comercio', 'id_show', 'dist_show', 'id_risca-faca',
'dist_risca-faca', 'id_evento', 'dist_evento'
],
index=[0, 1, 2, 3, 4, 5, 6, 7, 8]
)
integration.join_with_pois_by_category(move_df, pois)
assert_frame_equal(move_df, expected, check_dtype=False)
def test_join_with_poi_datetime():
list_events = [
[39.984094, 116.319236, 1,
Timestamp('2008-10-24 01:57:57'), 'show do tropykalia'],
[39.991013, 116.326384, 2,
Timestamp('2008-10-24 00:22:01'), 'evento da prefeitura'],
[40.01, 116.312615, 3,
Timestamp('2008-10-25 00:21:01'), 'show do seu joao'],
[40.013821, 116.306531, 4,
Timestamp('2008-10-26 00:22:01'), 'missa']
]
move_df = MoveDataFrame(list_move)
pois = DataFrame(
data=list_events,
columns=[LATITUDE, LONGITUDE, EVENT_ID, DATETIME, EVENT_TYPE],
index=[0, 1, 2, 3]
)
expected = DataFrame(
data=[
[39.984094, 116.319236, Timestamp('2008-10-23 05:53:05'), 1,
'', inf, ''],
[39.984559000000004, 116.326696, Timestamp('2008-10-23 10:37:26'),
1, '', inf, ''],
[40.002899, 116.32151999999999, Timestamp('2008-10-23 10:50:16'),
1, '', inf, ''],
[40.016238, 116.30769099999999, Timestamp('2008-10-23 11:03:06'),
1, '', inf, ''],
[40.013814, 116.306525, Timestamp('2008-10-23 11:58:33'), 2, 2,
3047.8382223981853, 'evento da prefeitura'],
[40.009735, 116.315069, Timestamp('2008-10-23 23:50:45'), 2, 2,
2294.0758201547073, 'evento da prefeitura'],
[39.993527, 116.32648300000001, Timestamp('2008-10-24 00:02:14'),
2, 2, 279.6712398549538, 'evento da prefeitura'],
[39.978575, 116.326975, Timestamp('2008-10-24 00:22:01'), 3, 1,
900.7798955139455, 'show do tropykalia'],
[39.981668, 116.310769, Timestamp('2008-10-24 01:57:57'), 3, 1,
770.188754517813, 'show do tropykalia']
],
columns=[
LATITUDE, LONGITUDE, DATETIME, TRAJ_ID, EVENT_ID, DIST_EVENT, EVENT_TYPE
],
index=[0, 1, 2, 3, 4, 5, 6, 7, 8]
)
integration.join_with_poi_datetime(move_df, pois, time_window=45000)
assert_frame_equal(move_df, expected, check_dtype=False)
def test_join_with_poi_datetime_optimizer():
list_events = [
[39.984094, 116.319236, 1,
Timestamp('2008-10-24 01:57:57'), 'show do tropykalia'],
[39.991013, 116.326384, 2,
Timestamp('2008-10-24 00:22:01'), 'evento da prefeitura'],
[40.01, 116.312615, 3,
Timestamp('2008-10-25 00:21:01'), 'show do seu joao'],
[40.013821, 116.306531, 4,
Timestamp('2008-10-26 00:22:01'), 'missa']
]
move_df = MoveDataFrame(list_move)
pois = DataFrame(
data=list_events,
columns=[LATITUDE, LONGITUDE, EVENT_ID, DATETIME, EVENT_TYPE],
index=[0, 1, 2, 3]
)
expected = DataFrame(
data=[
[39.984094, 116.319236, Timestamp('2008-10-23 05:53:05'), 1, 1,
0.0, 'show do tropykalia'],
[39.984559000000004, 116.326696, Timestamp('2008-10-23 10:37:26'),
1, 1, 637.6902157810676, 'show do tropykalia'],
[40.002899, 116.32151999999999, Timestamp('2008-10-23 10:50:16'),
1, 1, 1094.8606633486436, 'show do tropykalia'],
[40.016238, 116.30769099999999, Timestamp('2008-10-23 11:03:06'),
1, 1, 286.3387434682031, 'show do tropykalia'],
[40.013814, 116.306525, Timestamp('2008-10-23 11:58:33'), 2, 1,
0.9311014399622559, 'show do tropykalia'],
[40.009735, 116.315069, Timestamp('2008-10-23 23:50:45'), 2,
'', inf, ''],
[39.993527, 116.32648300000001, Timestamp('2008-10-24 00:02:14'),
2, '', inf, ''],
[39.978575, 116.326975, Timestamp('2008-10-24 00:22:01'), 3,
'', inf, ''],
[39.981668, 116.310769, Timestamp('2008-10-24 01:57:57'), 3,
'', inf, '']
],
columns=[
LATITUDE, LONGITUDE, DATETIME, TRAJ_ID, EVENT_ID, DIST_EVENT, EVENT_TYPE
],
index=[0, 1, 2, 3, 4, 5, 6, 7, 8]
)
integration.join_with_poi_datetime_optimizer(move_df, pois, time_window=45000)
assert_frame_equal(move_df, expected, check_dtype=False)
def test_get_bbox_by_radius():
list_data = [
[39.984092712402344, 116.31923675537101, '2008-10-23 05:53:05', 1],
[39.984199952392578, 116.31932067871094, '2008-10-23 05:53:06', 1],
[39.984222412109375, 116.31940460205078, '2008-10-23 05:53:11', 2],
[39.984222412109375, 116.31940460205078, '2008-10-23 05:53:11', 2],
]
move_df = MoveDataFrame(list_data)
bbox = filters.get_bbox_by_radius((move_df[LATITUDE], move_df[LONGITUDE]))
bbox_expected = [[39.9750995, 39.97520674, 39.9752292, 39.9752292],
[116.30749968, 116.30758358, 116.3076675, 116.3076675],
[39.99308593, 39.99319317, 39.99321563, 39.99321563],
[116.33097383, 116.33105777, 116.3311417, 116.3311417]]
assert_array_almost_equal(bbox, bbox_expected)
def _prepare_df_with_distances():
move_df = MoveDataFrame(
data=[
[39.984093, 116.319237, '2008-10-23 05:53:05', 1],
[39.984200, 116.319321, '2008-10-23 05:53:06', 1],
[38.984211, 115.319389, '2008-10-23 05:53:11', 1],
[39.984222, 116.319405, '2008-10-23 05:53:16', 1],
[39.984219, 116.319420, '2008-10-23 05:53:21', 1],
],
latitude=LATITUDE,
longitude=LONGITUDE,
datetime=DATETIME,
)
move_df[DIST_TO_PREV] = [
nan,
13.884481484192932,
140454.64510608764,
140460.97747220137,
1.3208180727070074,
]
move_df[DIST_TO_NEXT] = [
13.884481484192932,
140454.64510608764,
140460.97747220137,
1.3208180727070074,
nan,
]
move_df[DIST_PREV_TO_NEXT] = [
nan,
140440.86267282354,
7.563335999941849,
140461.50100279532,
nan,
]
cols = [
'id',
'lat',
'lon',
'datetime',
'dist_to_prev',
'dist_to_next',
'dist_prev_to_next',
]
return move_df[cols], cols
def _prepare_df_tid(tid):
move_df = MoveDataFrame(
data=list_data,
latitude=LATITUDE,
longitude=LONGITUDE,
datetime=DATETIME,
traj_id=TRAJ_ID,
)
cols = [
'id',
'lat',
'lon',
'datetime',
'dist_to_prev',
'time_to_prev',
'speed_to_prev',
tid,
]
return move_df, cols
