def test_stack_time_periods_by_ddmm_unique_dates():
test_data_invalid = pd.DataFrame(create_test_data())
test_data_invalid['end_date'] = pd.to_datetime(
test_data_invalid['end_date'])
test_data_invalid['date'] = pd.to_datetime(test_data_invalid['end_date'])
test_data_invalid['period'] = [
'2019-01-01 to 2019-12-31', '2005-01-01 to 2005-12-31',
'2000-01-01 to 2000-12-31', '2005-01-01 to 2005-12-31'
]
test_data_invalid['mm-dd'] = test_data_invalid['date'].dt.strftime("%m-%d")
test_data = test_data_invalid.drop(test_data_invalid.index[-1])
expected = pd.DataFrame({'mm-dd': ['03-01', '07-31', '08-28'],
'2000-01-01 to 2000-12-31': [2.39664378851418,
2.39664378851418,
2.39664378851418],
'2005-01-01 to 2005-12-31': [1.17640700229636,
1.17640700229636,
1.17640700229636],
'2019-01-01 to 2019-12-31': [0.13002748115958,
0.13002748115958,
0.13002748115958]}). \
set_index('mm-dd')
expected.columns.name = 'period'
assert_frame_equal(
get_transform_data.stack_time_periods_by_ddmm(test_data), expected)
def ay_dtw(timeseries):
pivot_time_series = get_transform_data.stack_time_periods_by_ddmm(timeseries)
return distance_matrix.dtw_dist_matrix(pivot_time_series)
def ay_euclidean(timeseries):
transposed_pivot_time_series = get_transform_data.stack_time_periods_by_ddmm(
timeseries).transpose()
return distance_matrix.euclidean_dist_matrix(transposed_pivot_time_series)
def test_stack_time_periods_by_ddmm_nonunique_dates():
test_data_invalid = pd.DataFrame(create_test_data())
test_data_invalid.loc[:, 'end_date'] = pd.to_datetime(test_data_invalid['end_date'])
with pytest.raises(KeyError):
get_transform_data.stack_time_periods_by_ddmm(test_data_invalid)
