IGVF-2342-calc-mux-samp-class

src/igvfd/mappings/multiplexed_sample.json

@@ -1,6 +1,6 @@
 {
-    "hash": "21e8f10a20a106a41987067591c7a652",
-    "index_name": "multiplexed_sample_21e8f10a",
+    "hash": "a93dd9b7b3a5f012161d0fb62b9269bb",
+    "index_name": "multiplexed_sample_a93dd9b7",
     "item_type": "multiplexed_sample",
     "mapping": {
         "dynamic_templates": [

src/igvfd/tests/test_types_sample.py

@@ -119,8 +119,9 @@ def test_classifications(testapp, primary_cell, technical_sample, whole_organism
     assert res.json.get('classifications') == ['tissue']
     res = testapp.get(in_vitro_cell_line['@id'])
     assert res.json.get('classifications') == ['cell line']
+    # This fixutre has one cell line and one tissue
     res = testapp.get(multiplexed_sample['@id'])
-    assert res.json.get('classifications') == ['multiplexed sample']
+    assert res.json.get('classifications') == ['cell line', 'tissue', 'multiplexed sample']
 
 
 def test_sorted_fractions(testapp, primary_cell, tissue, in_vitro_cell_line):

src/igvfd/types/sample.py

@@ -11,10 +11,15 @@
 )
 
 
-def collect_multiplexed_samples_prop(request, multiplexed_samples, property_name):
+def collect_multiplexed_samples_prop(request, multiplexed_samples, property_name, skip_calculated=True):
     property_set = set()
     for sample in multiplexed_samples:
-        sample_props = request.embed(sample, '@@object?skip_calculated=true')
+        # If to get a specific calculated property
+        if skip_calculated is False:
+            sample_props = request.embed(sample, f'@@object_with_select_calculated_properties?field={property_name}')
+        # If to get non-calculated properties
+        else:
+            sample_props = request.embed(sample, '@@object?skip_calculated=true')
         property_contents = sample_props.get(property_name, None)
         if property_contents:
             if type(property_contents) == list:
@@ -1059,5 +1064,9 @@ def institutional_certificates(self, request, multiplexed_samples):
             'notSubmittable': True,
         }
     )
-    def classifications(self):
-        return [self.item_type.replace('_', ' ')]
+    def classifications(self, request, multiplexed_samples):
+        # Get unique properties of individual samples' item types
+        sample_classfications = collect_multiplexed_samples_prop(
+            request, multiplexed_samples, 'classifications', skip_calculated=False)
+        self_classification = [self.item_type.replace('_', ' ')]
+        return sample_classfications + self_classification