refactor: disable docstring linting for tests and __init__

medmodels/medrecord/_overview.py

@@ -18,19 +18,19 @@
 )
 
 
 def extract_attribute_summary(
     attribute_dictionary: Union[
         Dict[EdgeIndex, Attributes], Dict[NodeIndex, Attributes]
     ],
     schema: Optional[AttributesSchema] = None,
 ) -> Dict[
     MedRecordAttribute,
     Union[TemporalAttributeInfo, NumericAttributeInfo, StringAttributeInfo],
 ]:
     """Extracts a summary from a node or edge attribute dictionary.
 
     Args:
         attribute_dict (Union[Dict[EdgeIndex, Attributes], Dict[NodeIndex, Attributes]]):
             Edges or Nodes and their attributes and values.
         schema (Optional[AttributesSchema], optional): Attribute Schema for the group
             nodes or edges. Defaults to None.
@@ -210,7 +210,7 @@
                 row[2] = str(attribute) if first_line else ""
 
                 # displaying info based on the type
                 if "values" in info.keys():
                     row[3] = info[key]
                 else:
                     if isinstance(info[key], float):
@@ -232,10 +232,12 @@
         "-" * (sum(lengths) + len(lengths)),
     ]
 
-    table.extend([
-        "".join(f"{row[x]: <{lengths[x]}} " for x in range(len(lengths)))
-        for row in rows
-    ])
+    table.extend(
+        [
+            "".join(f"{row[x]: <{lengths[x]}} " for x in range(len(lengths)))
+            for row in rows
+        ]
+    )
 
     table.append("-" * (sum(lengths) + len(lengths)))
 

medmodels/medrecord/schema.py

@@ -328,10 +328,12 @@ def _convert_node(
                 else None,
             )
 
-        return AttributesSchema({
-            x: _convert_node(self._group_schema.nodes[x])
-            for x in self._group_schema.nodes
-        })
+        return AttributesSchema(
+            {
+                x: _convert_node(self._group_schema.nodes[x])
+                for x in self._group_schema.nodes
+            }
+        )
 
     @property
     def edges(self) -> AttributesSchema:
@@ -352,10 +354,12 @@ def _convert_edge(
                 else None,
             )
 
-        return AttributesSchema({
-            x: _convert_edge(self._group_schema.edges[x])
-            for x in self._group_schema.edges
-        })
+        return AttributesSchema(
+            {
+                x: _convert_edge(self._group_schema.edges[x])
+                for x in self._group_schema.edges
+            }
+        )
 
     @property
     def strict(self) -> Optional[bool]:

medmodels/medrecord/tests/test_medrecord.py

@@ -31,33 +31,41 @@ def create_edges() -> List[Tuple[NodeIndex, NodeIndex, Attributes]]:
 
 
 def create_pandas_nodes_dataframe() -> pd.DataFrame:
-    return pd.DataFrame({
-        "index": ["0", "1"],
-        "attribute": [1, 2],
-    })
+    return pd.DataFrame(
+        {
+            "index": ["0", "1"],
+            "attribute": [1, 2],
+        }
+    )
 
 
 def create_second_pandas_nodes_dataframe() -> pd.DataFrame:
-    return pd.DataFrame({
-        "index": ["2", "3"],
-        "attribute": [2, 3],
-    })
+    return pd.DataFrame(
+        {
+            "index": ["2", "3"],
+            "attribute": [2, 3],
+        }
+    )
 
 
 def create_pandas_edges_dataframe() -> pd.DataFrame:
-    return pd.DataFrame({
-        "source": ["0", "1"],
-        "target": ["1", "0"],
-        "attribute": [1, 2],
-    })
+    return pd.DataFrame(
+        {
+            "source": ["0", "1"],
+            "target": ["1", "0"],
+            "attribute": [1, 2],
+        }
+    )
 
 
 def create_second_pandas_edges_dataframe() -> pd.DataFrame:
-    return pd.DataFrame({
-        "source": ["0", "1"],
-        "target": ["1", "0"],
-        "attribute": [2, 3],
-    })
+    return pd.DataFrame(
+        {
+            "source": ["0", "1"],
+            "target": ["1", "0"],
+            "attribute": [2, 3],
+        }
+    )
 
 
 def create_medrecord() -> MedRecord:
@@ -277,11 +285,13 @@ def test_schema(self) -> None:
 
         medrecord.add_edges_to_group("group", edge_index)
 
-        edge_index = medrecord.add_edges((
-            "0",
-            "1",
-            {"attribute": 1, "attribute2": "1"},
-        ))
+        edge_index = medrecord.add_edges(
+            (
+                "0",
+                "1",
+                {"attribute": 1, "attribute2": "1"},
+            )
+        )
 
         with self.assertRaises(ValueError):
             medrecord.add_edges_to_group("group", edge_index)
@@ -602,10 +612,12 @@ def test_add_nodes(self) -> None:
 
         assert medrecord.node_count() == 0
 
-        medrecord.add_nodes([
-            (create_pandas_nodes_dataframe(), "index"),
-            (create_second_pandas_nodes_dataframe(), "index"),
-        ])
+        medrecord.add_nodes(
+            [
+                (create_pandas_nodes_dataframe(), "index"),
+                (create_second_pandas_nodes_dataframe(), "index"),
+            ]
+        )
 
         assert medrecord.node_count() == 4
 
@@ -649,10 +661,12 @@ def test_add_nodes(self) -> None:
 
         assert medrecord.node_count() == 0
 
-        medrecord.add_nodes([
-            (nodes, "index"),
-            (second_nodes, "index"),
-        ])
+        medrecord.add_nodes(
+            [
+                (nodes, "index"),
+                (second_nodes, "index"),
+            ]
+        )
 
         assert medrecord.node_count() == 4
 
@@ -908,10 +922,12 @@ def test_add_edges(self) -> None:
 
         assert medrecord.edge_count() == 0
 
-        medrecord.add_edges([
-            (create_pandas_edges_dataframe(), "source", "target"),
-            (create_second_pandas_edges_dataframe(), "source", "target"),
-        ])
+        medrecord.add_edges(
+            [
+                (create_pandas_edges_dataframe(), "source", "target"),
+                (create_second_pandas_edges_dataframe(), "source", "target"),
+            ]
+        )
 
         assert medrecord.edge_count() == 4
 
@@ -942,10 +958,12 @@ def test_add_edges(self) -> None:
 
         second_edges = pl.from_pandas(create_second_pandas_edges_dataframe())
 
-        medrecord.add_edges([
-            (edges, "source", "target"),
-            (second_edges, "source", "target"),
-        ])
+        medrecord.add_edges(
+            [
+                (edges, "source", "target"),
+                (second_edges, "source", "target"),
+            ]
+        )
 
         assert medrecord.edge_count() == 4
 

medmodels/medrecord/tests/test_overview.py

@@ -11,25 +11,31 @@
 
 
 def create_medrecord():
-    patients = pd.DataFrame({
-        "index": ["P1", "P2", "P3"],
-        "age": [20, 30, 70],
-    })
+    patients = pd.DataFrame(
+        {
+            "index": ["P1", "P2", "P3"],
+            "age": [20, 30, 70],
+        }
+    )
 
     diagnosis = pd.DataFrame({"index": ["D1", "D2"]})
 
-    prescriptions = pd.DataFrame({
-        "index": ["M1", "M2", "M3"],
-        "ATC": ["B01AF01", "B01AA03", np.nan],
-    })
+    prescriptions = pd.DataFrame(
+        {
+            "index": ["M1", "M2", "M3"],
+            "ATC": ["B01AF01", "B01AA03", np.nan],
+        }
+    )
 
     nodes = [patients, diagnosis, prescriptions]
 
-    edges = pd.DataFrame({
-        "source": ["D1", "M1", "D1"],
-        "target": ["P1", "P2", "P3"],
-        "time": ["2000-01-01", "1999-10-15", "1999-12-15"],
-    })
+    edges = pd.DataFrame(
+        {
+            "source": ["D1", "M1", "D1"],
+            "target": ["P1", "P2", "P3"],
+            "time": ["2000-01-01", "1999-10-15", "1999-12-15"],
+        }
+    )
 
     edges.time = pd.to_datetime(edges.time)
 

medmodels/medrecord/tests/test_schema.py

@@ -16,15 +16,17 @@ def setUp(self) -> None:
         self.schema = create_medrecord().schema
 
     def test_groups(self) -> None:
-        assert sorted([
-            "diagnosis",
-            "drug",
-            "patient_diagnosis",
-            "patient_drug",
-            "patient_procedure",
-            "patient",
-            "procedure",
-        ]) == sorted(self.schema.groups)
+        assert sorted(
+            [
+                "diagnosis",
+                "drug",
+                "patient_diagnosis",
+                "patient_drug",
+                "patient_procedure",
+                "patient",
+                "procedure",
+            ]
+        ) == sorted(self.schema.groups)
 
     def test_group(self) -> None:
         assert isinstance(self.schema.group("patient"), mr.GroupSchema)  # pyright: ignore[reportUnnecessaryIsInstance]

medmodels/treatment_effect/continuous_estimators.py

@@ -59,34 +59,38 @@ def average_treatment_effect(
     Raises:
         ValueError: If the outcome variable is not numeric.
     """
-    treated_outcomes = np.array([
-        medrecord.edge[
-            find_reference_edge(
-                medrecord,
-                node_index,
-                outcome_group,
-                time_attribute=time_attribute,
-                reference=reference,
-            )
-        ][outcome_variable]
-        for node_index in treatment_outcome_true_set
-    ])
+    treated_outcomes = np.array(
+        [
+            medrecord.edge[
+                find_reference_edge(
+                    medrecord,
+                    node_index,
+                    outcome_group,
+                    time_attribute=time_attribute,
+                    reference=reference,
+                )
+            ][outcome_variable]
+            for node_index in treatment_outcome_true_set
+        ]
+    )
     if not all(isinstance(i, (int, float)) for i in treated_outcomes):
         msg = "Outcome variable must be numeric"
         raise ValueError(msg)
 
-    control_outcomes = np.array([
-        medrecord.edge[
-            find_reference_edge(
-                medrecord,
-                node_index,
-                outcome_group,
-                time_attribute="time",
-                reference=reference,
-            )
-        ][outcome_variable]
-        for node_index in control_outcome_true_set
-    ])
+    control_outcomes = np.array(
+        [
+            medrecord.edge[
+                find_reference_edge(
+                    medrecord,
+                    node_index,
+                    outcome_group,
+                    time_attribute="time",
+                    reference=reference,
+                )
+            ][outcome_variable]
+            for node_index in control_outcome_true_set
+        ]
+    )
     if not all(isinstance(i, (int, float)) for i in control_outcomes):
         msg = "Outcome variable must be numeric"
         raise ValueError(msg)
@@ -151,34 +155,38 @@ def cohens_d(
     Raises:
         ValueError: If the outcome variable is not numeric.
     """
-    treated_outcomes = np.array([
-        medrecord.edge[
-            find_reference_edge(
-                medrecord,
-                node_index,
-                outcome_group,
-                time_attribute=time_attribute,
-                reference=reference,
-            )
-        ][outcome_variable]
-        for node_index in treatment_outcome_true_set
-    ])
+    treated_outcomes = np.array(
+        [
+            medrecord.edge[
+                find_reference_edge(
+                    medrecord,
+                    node_index,
+                    outcome_group,
+                    time_attribute=time_attribute,
+                    reference=reference,
+                )
+            ][outcome_variable]
+            for node_index in treatment_outcome_true_set
+        ]
+    )
     if not all(isinstance(i, (int, float)) for i in treated_outcomes):
         msg = "Outcome variable must be numeric"
         raise ValueError(msg)
 
-    control_outcomes = np.array([
-        medrecord.edge[
-            find_reference_edge(
-                medrecord,
-                node_index,
-                outcome_group,
-                time_attribute="time",
-                reference=reference,
-            )
-        ][outcome_variable]
-        for node_index in control_outcome_true_set
-    ])
+    control_outcomes = np.array(
+        [
+            medrecord.edge[
+                find_reference_edge(
+                    medrecord,
+                    node_index,
+                    outcome_group,
+                    time_attribute="time",
+                    reference=reference,
+                )
+            ][outcome_variable]
+            for node_index in control_outcome_true_set
+        ]
+    )
     if not all(isinstance(i, (int, float)) for i in control_outcomes):
         msg = "Outcome variable must be numeric"
         raise ValueError(msg)