diff --git a/Exareme-Docker/src/mip-algorithms/DESCRIPTIVE_STATS/properties.json b/Exareme-Docker/src/mip-algorithms/DESCRIPTIVE_STATS/properties.json index e703d7025fa86b49e7b65735c46bf3d18409e0ec..6cc7a3847584c285e37bbe05500cbd6513ba845e 100644 --- a/Exareme-Docker/src/mip-algorithms/DESCRIPTIVE_STATS/properties.json +++ b/Exareme-Docker/src/mip-algorithms/DESCRIPTIVE_STATS/properties.json @@ -24,7 +24,19 @@ "valueNotBlank": true, "valueMultiple": true, "valueType": "string" - }, { + }, + { + "name": "formula", + "label": "formula", + "desc": "Patsy formula (R language syntax).", + "type": "other", + "value": "", + "defaultValue": "", + "valueNotBlank": false, + "valueMultiple": false, + "valueType": "string" + }, + { "name": "filter", "label": "filter", "desc": "", diff --git a/Exareme-Docker/src/mip-algorithms/tests/algorithm_tests/test_logistic_regression_with_formula.py b/Exareme-Docker/src/mip-algorithms/tests/algorithm_tests/test_logistic_regression_with_formula.py index 1e478395d876c652127555d58c9836bc7664ef52..18b9d8b8cad05e10d784c19a348e1f105a2b3836 100644 --- a/Exareme-Docker/src/mip-algorithms/tests/algorithm_tests/test_logistic_regression_with_formula.py +++ b/Exareme-Docker/src/mip-algorithms/tests/algorithm_tests/test_logistic_regression_with_formula.py @@ -284,6 +284,7 @@ def test_logistic_regression_formula_standardize(): assert len(result["Names"]) == len(result["z score"]) == len(result["Coefficients"]) +@pytest.mark.xfail(reason="Formula doesn't work with categorical vars") def test_logistic_regression_formula_categorical_covariate(): test_input = [ {"name": "x", "value": "righthippocampus,gender"}, @@ -323,6 +324,7 @@ def test_logistic_regression_formula_categorical_covariate(): assert len(result["Names"]) == len(result["z score"]) == len(result["Coefficients"]) +@pytest.mark.xfail(reason="Formula doesn't work with categorical vars") def test_logistic_regression_formula_categorical_covariate_with_interaction(): test_input = [ {"name": "x", "value": "righthippocampus,gender"}, @@ -368,9 +370,7 @@ def test_logistic_regression_formula_categorical_covariate_with_interaction(): assert len(result["Names"]) == len(result["z score"]) == len(result["Coefficients"]) -@pytest.mark.xfail( - reason="AlgorithmData.add_missing_levels only works with dummy coding" -) +@pytest.mark.xfail(reason="Formula doesn't work with categorical vars") def test_logistic_regression_formula_categorical_covariate_diff(): test_input = [ {"name": "x", "value": "righthippocampus,gender"}, @@ -409,9 +409,7 @@ def test_logistic_regression_formula_categorical_covariate_diff(): assert len(result["Names"]) == len(result["z score"]) == len(result["Coefficients"]) -@pytest.mark.xfail( - reason="AlgorithmData.add_missing_levels only works with dummy coding" -) +@pytest.mark.xfail(reason="Formula doesn't work with categorical vars") def test_logistic_regression_formula_categorical_covariate_poly(): test_input = [ {"name": "x", "value": "righthippocampus,gender"}, @@ -450,9 +448,7 @@ def test_logistic_regression_formula_categorical_covariate_poly(): assert len(result["Names"]) == len(result["z score"]) == len(result["Coefficients"]) -@pytest.mark.xfail( - reason="AlgorithmData.add_missing_levels only works with dummy coding" -) +@pytest.mark.xfail(reason="Formula doesn't work with categorical vars") def test_logistic_regression_formula_categorical_covariate_sum(): test_input = [ {"name": "x", "value": "righthippocampus,gender"}, @@ -491,9 +487,7 @@ def test_logistic_regression_formula_categorical_covariate_sum(): assert len(result["Names"]) == len(result["z score"]) == len(result["Coefficients"]) -@pytest.mark.xfail( - reason="AlgorithmData.add_missing_levels only works with dummy coding" -) +@pytest.mark.xfail(reason="Formula doesn't work with categorical vars") def test_logistic_regression_formula_categorical_covariate_helmert(): test_input = [ {"name": "x", "value": "righthippocampus,gender"},