def test_spearman_one_target_one_feature(self, idadf): data = idadf._table_def() columns = list(data.loc[data['VALTYPE'] == "NUMERIC"].index) if len(columns) > 1: result = spearman(idadf, target=columns[0], features=[columns[1]]) assert (isinstance(result, float)) result2 = spearman(idadf, target=columns[1], features=[columns[0]]) assert (round(result, 3) == round(result2, 3)) # symmetry
def test_spearman_one_target_one_feature(self, idadf): data = idadf._table_def() columns = list(data.loc[data['VALTYPE'] == "NUMERIC"].index) if len(columns) > 1: result = spearman(idadf, target = columns[0], features=[columns[1]]) assert(isinstance(result, float)) result2 = spearman(idadf, target = columns[1], features=[columns[0]]) assert(round(result,3) == round(result2,3)) # symmetry
def test_spearman_valueError(self, idadf): if len(idadf.columns) > 0: with pytest.raises(ValueError): spearman(idadf, features=idadf.columns[0]) with pytest.raises(ValueError): spearman(idadf, target=idadf.columns[0], features=idadf.columns[0])
def test_spearman_default(self, idadf): data = idadf._table_def() columns = list(data.loc[data['VALTYPE'] == "NUMERIC"].index) if len(columns) > 1: result = spearman(idadf, features = columns) assert(isinstance(result, pandas.core.frame.DataFrame)) assert(len(result.columns) == len(columns)) assert(len(result.index) == len(columns)) result2 = spearman(idadf) assert(all(result == result2)) result = result.fillna(0) # np.nan values are not equal when compared assert(all(result == result.T)) # symmetry
def test_spearman_default(self, idadf): data = idadf._table_def() columns = list(data.loc[data['VALTYPE'] == "NUMERIC"].index) if len(columns) > 1: result = spearman(idadf, features=columns) assert (isinstance(result, pandas.core.frame.DataFrame)) assert (len(result.columns) == len(columns)) assert (len(result.index) == len(columns)) result2 = spearman(idadf) assert (all(result == result2)) result = result.fillna( 0) # np.nan values are not equal when compared assert (all(result == result.T)) # symmetry
def test_spearman_one_target(self, idadf): data = idadf._table_def() columns = list(data.loc[data['VALTYPE'] == "NUMERIC"].index) if len(columns) > 1: result = spearman(idadf, target = columns[0]) assert(isinstance(result, pandas.core.series.Series)) assert(len(result) == (len(columns)-1))
def test_spearman_one_target(self, idadf): data = idadf._table_def() columns = list(data.loc[data['VALTYPE'] == "NUMERIC"].index) if len(columns) > 1: result = spearman(idadf, target=columns[0]) assert (isinstance(result, pandas.core.series.Series)) assert (len(result) == (len(columns) - 1))
def test_spearman_multiple_target(self, idadf): data = idadf._table_def() columns = list(data.loc[data['VALTYPE'] == "NUMERIC"].index) if len(columns) > 1: result = spearman(idadf, target = [columns[0],columns[1]]) assert(isinstance(result, pandas.core.frame.DataFrame)) assert(len(result.columns) == 2) assert(len(result.index) == len(columns))
def test_spearman_multiple_target(self, idadf): data = idadf._table_def() columns = list(data.loc[data['VALTYPE'] == "NUMERIC"].index) if len(columns) > 1: result = spearman(idadf, target=[columns[0], columns[1]]) assert (isinstance(result, pandas.core.frame.DataFrame)) assert (len(result.columns) == 2) assert (len(result.index) == len(columns))
def test_spearman_TypeError(self, idadf): data = idadf._table_def() columns = list(data.loc[data['VALTYPE'] != "NUMERIC"].index) if len(columns) > 1: with pytest.raises(TypeError): spearman(idadf, features = columns)
def test_spearman_valueError(self, idadf): if len(idadf.columns) > 0: with pytest.raises(ValueError): spearman(idadf, features = idadf.columns[0]) with pytest.raises(ValueError): spearman(idadf, target= idadf.columns[0], features = idadf.columns[0])
def test_spearman_TypeError(self, idadf): data = idadf._table_def() columns = list(data.loc[data['VALTYPE'] != "NUMERIC"].index) if len(columns) > 1: with pytest.raises(TypeError): spearman(idadf, features=columns)