Combine analyses in Studyset (#810)

* combine analyses

* Update nimads.py

* Update .gitignore

* Return copy of Studyset

.gitignore

@@ -8,6 +8,7 @@ docs/auto_examples/
 nimare/resources/data/neurovault-data/
 nimare/tests/data/downloaded/
 nimare/tests/resources/data/neurovault-data/
+_readthedocs/
 .pytest_cache
 
 #

nimare/nimads.py

@@ -79,6 +79,28 @@ def from_nimads(cls, filename):
 
         return cls(nimads)
 
+    def combine_analyses(self):
+        """Combine analyses in Studyset."""
+        studyset = self.copy()
+        for study in studyset.studies:
+            if len(study.analyses) > 1:
+                source_lst = [analysis.to_dict() for analysis in study.analyses]
+                ids, names, conditions, images, points, weights = [
+                    [source[key] for source in source_lst] for key in source_lst[0]
+                ]
+
+                new_source = {
+                    "id": "_".join(ids),
+                    "name": "; ".join(names),
+                    "conditions": [cond for c_list in conditions for cond in c_list],
+                    "images": [image for i_list in images for image in i_list],
+                    "points": [point for p_list in points for point in p_list],
+                    "weights": [weight for w_list in weights for weight in w_list],
+                }
+                study.analyses = [Analysis(new_source)]
+
+        return studyset
+
     def to_nimads(self, filename):
         """Write the Studyset to a NIMADS JSON file."""
         with open(filename, "w+") as fn:

nimare/tests/test_nimads.py

@@ -10,8 +10,11 @@ def test_load_nimads(example_nimads_studyset, example_nimads_annotation):
     # filter the studyset to only include analyses with include=True
     annotation = studyset.annotations[0]
     analysis_ids = [n.analysis.id for n in annotation.notes if n.note["include"]]
-    analysis_ids = analysis_ids[0:5]
+    analysis_ids = analysis_ids[:5]
     filtered_studyset = studyset.slice(analyses=analysis_ids)
+    # Combine analyses after filtering
+    filtered_studyset = filtered_studyset.combine_analyses()
+
     assert isinstance(filtered_studyset, nimads.Studyset)
     dataset = filtered_studyset.to_dataset()
     assert isinstance(dataset, Dataset)