def test_reversability_categorical(self): class F(Classifier): inputs = () window_length = 0 dtype = categorical_dtype missing_value = '<missing>' f = F() column_data = LabelArray( np.array( [['a', f.missing_value], ['b', f.missing_value], ['c', 'd']], ), missing_value=f.missing_value, ) assert_equal( f.postprocess(column_data.ravel()), pd.Categorical( ['a', f.missing_value, 'b', f.missing_value, 'c', 'd'], ), ) # only include the non-missing data pipeline_output = pd.Series( data=['a', 'b', 'c', 'd'], index=pd.MultiIndex.from_arrays([ [pd.Timestamp('2014-01-01'), pd.Timestamp('2014-01-02'), pd.Timestamp('2014-01-03'), pd.Timestamp('2014-01-03')], [0, 0, 0, 1], ]), dtype='category', ) assert_equal( f.to_workspace_value(pipeline_output, pd.Index([0, 1])), column_data, )
def test_reversability_categorical(self): class F(Classifier): inputs = () window_length = 0 dtype = categorical_dtype missing_value = "<missing>" f = F() column_data = LabelArray( np.array([["a", f.missing_value], ["b", f.missing_value], ["c", "d"]], ), missing_value=f.missing_value, ) assert_equal( f.postprocess(column_data.ravel()), pd.Categorical( ["a", f.missing_value, "b", f.missing_value, "c", "d"], ), ) # only include the non-missing data pipeline_output = pd.Series( data=["a", "b", "c", "d"], index=pd.MultiIndex.from_arrays([ [ pd.Timestamp("2014-01-01"), pd.Timestamp("2014-01-02"), pd.Timestamp("2014-01-03"), pd.Timestamp("2014-01-03"), ], [0, 0, 0, 1], ]), dtype="category", ) assert_equal( f.to_workspace_value(pipeline_output, pd.Index([0, 1])), column_data, )