def test_apply_to_timeseries(self):
rolling_mean = RollingMean(mock_dataset.fields.wins, 3)
result = rolling_mean.apply(dimx1_date_df, None)
expected = pd.Series([nan, nan, 2.0, 2.0, 2.0, 2.0],
name='$wins',
index=dimx1_date_df.index)
pandas.testing.assert_series_equal(expected, result)
def test_apply_to_timeseries_with_uni_dim_and_ref(self):
rolling_mean = RollingMean(mock_dataset.fields.wins, 3)
result = rolling_mean.apply(dimx2_date_str_ref_df, ElectionOverElection(mock_dataset.fields.timestamp))
expected = pd.Series([nan, nan, nan, nan, 4 / 3, 0., 4 / 3, 2 / 3, 4 / 3, 4 / 3, 2 / 3],
name='$wins_eoe',
index=dimx2_date_str_ref_df.index)
pandas.testing.assert_series_equal(expected, result)
def test_apply_to_timeseries_with_uni_dim_and_ref(self):
rolling_mean = RollingMean(slicer.metrics.wins, 3)
result = rolling_mean.apply(cont_uni_dim_ref_df, ElectionOverElection(slicer.dimensions.timestamp))
expected = pd.Series([np.nan, np.nan, np.nan, np.nan, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
name='$m$wins_eoe',
index=cont_uni_dim_ref_df.index)
pandas.testing.assert_series_equal(expected, result)
def test_apply_to_timeseries_with_uni_dim(self):
rolling_mean = RollingMean(slicer.metrics.wins, 3)
result = rolling_mean.apply(cont_uni_dim_df, None)
expected = pd.Series([np.nan, np.nan, np.nan, np.nan, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
name='$m$wins',
index=cont_uni_dim_df.index)
pandas.testing.assert_series_equal(expected, result)
def test_apply_to_timeseries(self):
rolling_mean = RollingMean(slicer.metrics.wins, 3)
result = rolling_mean.apply(cont_dim_df, None)
expected = pd.Series([np.nan, np.nan, 2.0, 2.0, 2.0, 2.0],
name='$m$wins',
index=cont_dim_df.index)
pandas.testing.assert_series_equal(expected, result)
def test_apply_to_timeseries_with_uni_dim_and_ref(self):
rolling_mean = RollingMean(slicer.metrics.wins, 3)
result = rolling_mean.apply(
cont_uni_dim_ref_df,
ElectionOverElection(slicer.dimensions.timestamp))
expected = pd.Series(
[np.nan, np.nan, np.nan, np.nan, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
name='$m$wins_eoe',
index=cont_uni_dim_ref_df.index)
pandas.testing.assert_series_equal(expected, result)
def test_apply_to_timeseries_with_uni_dim(self):
rolling_mean = RollingMean(mock_dataset.fields.wins, 3)
result = rolling_mean.apply(dimx2_date_str_df, None)
expected = pd.Series(
[
nan, nan, nan, nan, nan, 2 / 3, 4 / 3, 2 / 3, 4 / 3, 4 / 3,
2 / 3, 4 / 3, 2 / 3
],
name='$wins',
index=dimx2_date_str_df.index,
)
pandas.testing.assert_series_equal(expected, result)