add a test for dataset-level model spec retrieval

bids/analysis/tests/test_analysis.py

@@ -12,165 +12,185 @@
 
 @pytest.fixture
 def analysis():
-    layout_path = join(get_test_data_path(), 'ds005')
+    layout_path = join(get_test_data_path(), "ds005")
     layout = BIDSLayout(layout_path)
-    json_file = join(layout_path, 'models', 'ds-005_type-test_model.json')
+    json_file = join(layout_path, "models", "ds-005_type-test_model.json")
     analysis = Analysis(layout, json_file)
-    analysis.setup(scan_length=480, subject=['01', '02'])
+    analysis.setup(scan_length=480, subject=["01", "02"])
     return analysis
 
 
 def test_first_level_sparse_design_matrix(analysis):
-    collections = analysis['run'].get_collections(subject=['01'])
+    collections = analysis["run"].get_collections(subject=["01"])
     assert len(collections) == 3
-    df = collections[0].to_df(format='long')
+    df = collections[0].to_df(format="long")
     assert df.shape == (172, 9)
-    assert df['condition'].nunique() == 2
-    assert set(df.columns) == {'amplitude', 'onset', 'duration',
-                               'condition', 'subject', 'run',
-                               'task', 'datatype', 'suffix'}
+    assert df["condition"].nunique() == 2
+    assert set(df.columns) == {
+        "amplitude",
+        "onset",
+        "duration",
+        "condition",
+        "subject",
+        "run",
+        "task",
+        "datatype",
+        "suffix",
+    }
 
 
 def test_incremental_data_loading():
-    layout_path = join(get_test_data_path(), 'ds005')
+    layout_path = join(get_test_data_path(), "ds005")
     layout = BIDSLayout(layout_path)
-    json_file = join(layout_path, 'models', 'ds-005_type-test_model.json')
+    json_file = join(layout_path, "models", "ds-005_type-test_model.json")
     analysis = Analysis(layout, json_file)
-    analysis.setup(scan_length=480, subject=['01'], run=[1], finalize=False)
-    analysis.setup(scan_length=480, subject=['02'], run=[2], finalize=False)
+    analysis.setup(scan_length=480, subject=["01"], run=[1], finalize=False)
+    analysis.setup(scan_length=480, subject=["02"], run=[2], finalize=False)
     analysis.finalize()
-    assert len(analysis['run'].get_collections()) == 2
+    assert len(analysis["run"].get_collections()) == 2
 
 
 def test_post_first_level_sparse_design_matrix(analysis):
 
-    collections = analysis['session'].get_collections()
+    collections = analysis["session"].get_collections()
     assert len(collections) == 2
-    result = collections[0].to_df(format='long')
+    result = collections[0].to_df(format="long")
     assert result.shape == (9, 11)
-    result = collections[0].to_df(format='long', entities=False)
+    result = collections[0].to_df(format="long", entities=False)
     assert result.shape == (9, 2)
     entities = {
         # 'subject': '01',  # PY35
-        'task': 'mixedgamblestask',
-        'datatype': 'func',
-        'suffix': 'bold'}
+        "task": "mixedgamblestask",
+        "datatype": "func",
+        "suffix": "bold",
+    }
     assert not set(entities.keys()) - set(collections[0].entities.keys())
     assert not set(entities.values()) - set(collections[0].entities.values())
     # PY35
-    assert 'subject' in collections[0].entities
-    assert collections[0].entities['subject'] in ('01', '02')
+    assert "subject" in collections[0].entities
+    assert collections[0].entities["subject"] in ("01", "02")
 
     # Participant level and also check integer-based indexing
-    collections = analysis['participant'].get_collections()
+    collections = analysis["participant"].get_collections()
     assert len(collections) == 2
-    assert analysis[2].name == 'participant'
+    assert analysis[2].name == "participant"
 
     # Dataset level
-    collections = analysis['group'].get_collections()
+    collections = analysis["group"].get_collections()
     assert len(collections) == 1
-    data = collections[0].to_df(format='long')
+    data = collections[0].to_df(format="long")
     assert len(data) == 10
-    assert data['subject'].nunique() == 2
+    assert data["subject"].nunique() == 2
 
     # # Make sure columns from different levels exist
-    varset = {'sex', 'age', 'RT-trial_type'}
-    assert not (varset - set(data['condition'].unique()))
+    varset = {"sex", "age", "RT-trial_type"}
+    assert not (varset - set(data["condition"].unique()))
 
     # Calling an invalid level name should raise an exception
     with pytest.raises(KeyError):
-        result = analysis['nonexistent_name'].to_df()
+        result = analysis["nonexistent_name"].to_df()
 
 
 def test_step_get_collections(analysis):
-    collections = analysis['run'].get_collections(subject='01')
+    collections = analysis["run"].get_collections(subject="01")
     assert len(collections) == 3
     assert isinstance(collections[0], BIDSVariableCollection)
 
 
 def test_contrast_info(analysis):
-    colls = analysis['run'].get_collections(subject='01')
-    contrast_lists = [analysis['run'].get_contrasts(c) for c in colls]
+    colls = analysis["run"].get_collections(subject="01")
+    contrast_lists = [analysis["run"].get_contrasts(c) for c in colls]
     assert len(contrast_lists) == 3
     for cl in contrast_lists:
         assert len(cl) == 3
-        cl = [c for c in cl if c.type == 't']
-        assert set([c.name for c in cl]) == {'RT', 'RT-trial_type'}
-        assert set([c.type for c in cl]) == {'t'}
-        assert cl[0].weights.columns.tolist() == ['RT', 'trial_type']
-        assert cl[1].weights.columns.tolist() == ['RT']
+        cl = [c for c in cl if c.type == "t"]
+        assert set([c.name for c in cl]) == {"RT", "RT-trial_type"}
+        assert set([c.type for c in cl]) == {"t"}
+        assert cl[0].weights.columns.tolist() == ["RT", "trial_type"]
+        assert cl[1].weights.columns.tolist() == ["RT"]
         assert np.array_equal(cl[0].weights.values, np.array([[1, -1]]))
         assert np.array_equal(cl[1].weights.values, np.array([[1]]))
         assert isinstance(cl[0], ContrastInfo)
-        assert cl[0]._fields == ('name', 'weights', 'type', 'entities')
+        assert cl[0]._fields == ("name", "weights", "type", "entities")
 
 
 def test_contrast_info_with_specified_variables(analysis):
-    varlist = ['RT', 'dummy']
-    colls = analysis['run'].get_collections(subject='01')
-    contrast_lists = [analysis['run'].get_contrasts(c, variables=varlist)
-                      for c in colls]
+    varlist = ["RT", "dummy"]
+    colls = analysis["run"].get_collections(subject="01")
+    contrast_lists = [
+        analysis["run"].get_contrasts(c, variables=varlist) for c in colls
+    ]
     assert len(contrast_lists) == 3
     for cl in contrast_lists:
         assert len(cl) == 3
-        cl = [c for c in cl if c.type == 't']
-        assert set([c.name for c in cl]) == {'RT', 'RT-trial_type'}
-        assert set([c.type for c in cl]) == {'t'}
+        cl = [c for c in cl if c.type == "t"]
+        assert set([c.name for c in cl]) == {"RT", "RT-trial_type"}
+        assert set([c.type for c in cl]) == {"t"}
         for c in cl:
-            assert c.weights.columns.tolist() == ['RT', 'dummy']
+            assert c.weights.columns.tolist() == ["RT", "dummy"]
             assert np.array_equal(c.weights.values, np.array([[1, 0]]))
         assert isinstance(cl[0], ContrastInfo)
-        assert cl[0]._fields == ('name', 'weights', 'type', 'entities')
+        assert cl[0]._fields == ("name", "weights", "type", "entities")
 
 
 def test_contrast_info_F_contrast(analysis):
-    colls = analysis['run'].get_collections(subject='01')
-    contrast_lists = [analysis['run'].get_contrasts(c, names=["crummy-F"])
-                      for c in colls]
+    colls = analysis["run"].get_collections(subject="01")
+    contrast_lists = [
+        analysis["run"].get_contrasts(c, names=["crummy-F"]) for c in colls
+    ]
     assert len(contrast_lists) == 3
     for cl in contrast_lists:
         assert len(cl) == 1
         c = cl[0]
         assert c.name == "crummy-F"
-        assert c.type == 'F'
-        assert c.weights.columns.tolist() == ['RT', 'trial_type']
+        assert c.type == "F"
+        assert c.weights.columns.tolist() == ["RT", "trial_type"]
         assert np.array_equal(c.weights.values, np.array([[1, 0], [0, 1]]))
         assert isinstance(c, ContrastInfo)
-        assert c._fields == ('name', 'weights', 'type', 'entities')
+        assert c._fields == ("name", "weights", "type", "entities")
 
 
 def test_dummy_contrasts(analysis):
-    collection = analysis['run'].get_collections(subject='01')[0]
-    names = [c.name for c in analysis['run'].get_contrasts(collection)]
+    collection = analysis["run"].get_collections(subject="01")[0]
+    names = [c.name for c in analysis["run"].get_contrasts(collection)]
 
-    collections = analysis['session'].get_collections()
-    collection = analysis['session'].get_collections(subject='01')[0]
-    session = analysis['session'].get_contrasts(collection)
+    collections = analysis["session"].get_collections()
+    collection = analysis["session"].get_collections(subject="01")[0]
+    session = analysis["session"].get_contrasts(collection)
     for cl in session:
-        assert cl.type == 'FEMA'
+        assert cl.type == "FEMA"
         assert cl.name in names
 
-    collection = analysis['participant'].get_collections(subject='01')[0]
-    participant = analysis['participant'].get_contrasts(collection)
+    collection = analysis["participant"].get_collections(subject="01")[0]
+    participant = analysis["participant"].get_contrasts(collection)
     assert len(participant) == 3
     for cl in participant:
-        assert cl.type == 'FEMA'
+        assert cl.type == "FEMA"
         assert cl.name in names
 
-    collection = analysis['group'].get_collections()[0]
-    group = analysis['group'].get_contrasts(collection)
+    collection = analysis["group"].get_collections()[0]
+    group = analysis["group"].get_contrasts(collection)
     group_names = []
     for cl in group:
-        assert cl.type == 't'
+        assert cl.type == "t"
         group_names.append(cl.name)
 
     assert set(names) < set(group_names)
 
 
-def test_get_model_spec(analysis):
-    collection = analysis['run'].get_collections(subject='01', run=1)[0]
-    model_spec = analysis['run'].get_model_spec(collection, 'TR')
-    assert model_spec.__class__.__name__ == 'GLMMSpec'
+def test_get_run_level_model_spec(analysis):
+    collection = analysis["run"].get_collections(subject="01", run=1)[0]
+    model_spec = analysis["run"].get_model_spec(collection, "TR")
+    assert model_spec.__class__.__name__ == "GLMMSpec"
     assert model_spec.X.shape == (240, 1)
     assert model_spec.Z is None
-    assert {'RT'} == set(model_spec.terms.keys())
+    assert {"RT"} == set(model_spec.terms.keys())
+
+
+def test_get_dataset_level_model_spec(analysis):
+    collection = analysis["group"].get_collections()[0]
+    model_spec = analysis["group"].get_model_spec(collection)
+    assert model_spec.__class__.__name__ == "GLMMSpec"
+    assert model_spec.X.shape == (2, 1)
+    assert model_spec.Z is None
+    assert {"age"} == set(model_spec.terms.keys())

bids/tests/data/ds005/models/ds-005_type-test_model.json

@@ -6,7 +6,10 @@
       "Name": "run",
       "Level": "Run",
       "Model": {
-        "X": ["RT", "trial_type"]
+        "X": [
+          "RT",
+          "trial_type"
+        ]
       },
       "Transformations": [
         {
@@ -15,17 +18,22 @@
         }
       ],
       "DummyContrasts": {
-        "Conditions": ["RT"],
+        "Conditions": [
+          "RT"
+        ],
         "Type": "t"
-        },
+      },
       "Contrasts": [
         {
           "Name": "RT-trial_type",
           "ConditionList": [
             "RT",
             "trial_type"
           ],
-          "Weights": [1, -1]
+          "Weights": [
+            1,
+            -1
+          ]
         },
         {
           "Name": "crummy-F",
@@ -34,8 +42,14 @@
             "trial_type"
           ],
           "Weights": [
-            [1, 0],
-            [0, 1]
+            [
+              1,
+              0
+            ],
+            [
+              0,
+              1
+            ]
           ]
         }
       ]
@@ -57,15 +71,19 @@
             "RT"
           ],
           "Type": "FEMA",
-          "Weights": [1]
+          "Weights": [
+            1
+          ]
         },
         {
           "Name": "RT-trial_type",
           "ConditionList": [
             "RT-trial_type"
           ],
           "Type": "FEMA",
-          "Weights": [1]
+          "Weights": [
+            1
+          ]
         },
         {
           "Name": "crummy-F",
@@ -74,17 +92,24 @@
           ],
           "Type": "FEMA",
           "Weights": [
-            [1]
+            [
+              1
+            ]
           ]
         }
       ]
     },
     {
       "Name": "group",
       "Level": "Dataset",
+      "Model": {
+        "X": [
+          "age"
+        ]
+      },
       "DummyContrasts": {
         "Type": "t"
       }
     }
   ]
-}
+}