Update docstrings

TCT/TCT_neighborhood_finder.py

@@ -195,41 +195,39 @@ def neighborhood_finder(input_node, node2_categories, APInames, metaKG, API_pred
 
     Parameters
     ----------
-    input_node (str)
+    input_node : str
         The input node - should be a CURIE id.
-    node2_categories (list)
+    node2_categories : list
         A list of intermediate categories to be used in the neighborhood finding process.
-    APInames (dict)
+    APInames : dict
         A dictionary containing the names of the APIs to be used.
-    metaKG (DataFrame)
+    metaKG : DataFrame
         The metadata knowledge graph containing information about the APIs and their predicates.
-    API_predicates (dict)
+    API_predicates : dict
         A dictionary containing the predicates for each API.
-    input_node_category (list)
+    input_node_category : list
         Optional. A list of categories for the input node. If empty, it will be derived from the input node's types.
-    attribute_constraints (list)
+    attribute_constraints : list
         Optional. List of outputs of translator_query.build_attribute_constraint
 
     Returns
-    --------------
-    input_node_id (str)
+    -------
+    input_node_id : str
         The curie id of the input node.
-    result (dict)
+    result : dict
         The result of the query for the input node.
-    result_parsed (DataFrame)
+    result_parsed : DataFrame
         The parsed results for the input node.
-    result_ranked_by_primary_infores (DataFrame)
+    result_ranked_by_primary_infores : DataFrame
         The ranked results based on primary infores.
 
-    --------------
-    Example:
+    Examples
+    --------
     >>> input_node_id, result, result_parsed, result_ranked_by_primary_infores1 = neighborhood_finder('MONDO:0008170', #Ovarian Cancer
                                                                                             node2_categories = ['biolink:SmallMolecule', 'biolink:Drug', 'biolink:ChemicalEntity'],
                                                                                             APInames = APInames,
                                                                                             metaKG = metaKG,
                                                                                             API_predicates = API_predicates)
-    --------------
-
     """
     from . import node_normalizer
     from . import translator_query
@@ -291,23 +289,23 @@ def neighborhood_finder_multiple_inputs(input_nodes:list[str], node2_categories:
 
     Parameters
     ----------
-    input_nodes (list[str])
+    input_nodes : list[str]
         The input nodes - should be a list of CURIE ids.
-    node2_categories (list)
+    node2_categories : list
         A list of intermediate categories to be used in the neighborhood finding process.
-    APInames (dict)
+    APInames : dict
         A dictionary containing the names of the APIs to be used.
-    metaKG (DataFrame)
+    metaKG : DataFrame
         The metadata knowledge graph containing information about the APIs and their predicates.
-    API_predicates (dict)
+    API_predicates : dict
         A dictionary containing the predicates for each API.
-    input_node_category (list)
+    input_node_category : list
         Optional. A list of categories for the input node. If empty, it will be derived from the input node's types.
-    attribute_constraints (list)
+    attribute_constraints : list
         Optional. List of outputs of translator_query.build_attribute_constraint
 
     Returns
-    --------------
+    -------
     input_node_id (str)
         The curie id of the input node.
     result (dict)
@@ -317,15 +315,14 @@ def neighborhood_finder_multiple_inputs(input_nodes:list[str], node2_categories:
     result_ranked_by_primary_infores (DataFrame)
         The ranked results based on primary infores.
 
-    --------------
-    Example:
-    >>> input_node_id, result, result_parsed, result_ranked_by_primary_infores1 = neighborhood_finder('MONDO:0008170', #Ovarian Cancer
-                                                                                            node2_categories = ['biolink:SmallMolecule', 'biolink:Drug', 'biolink:ChemicalEntity'],
-                                                                                            APInames = APInames,
-                                                                                            metaKG = metaKG,
-                                                                                            API_predicates = API_predicates)
-    --------------
 
+    Examples
+    --------
+    >>> result, result_parsed = neighborhood_finder_multiple_inputs(['NCBIGene:6774', 'NCBIGene:4170', 'NCBIGene:4792'],
+                                                                    node2_categories = ['biolink:SmallMolecule', 'biolink:Drug', 'biolink:ChemicalEntity'],
+                                                                    APInames = APInames,
+                                                                    metaKG = metaKG,
+                                                                    API_predicates = API_predicates)
     """
     from . import node_normalizer
     from . import translator_query

TCT/TCT_network_annotator.py

@@ -175,36 +175,31 @@ def get_connected_graph(result_parsed, input_identifiers):
 
     Parameters
     ----------
-    result_parsed (dict)
+    result_parsed : dict
         The parsed results for results from TCT_neighborhood_finder.neighborhood_finder_multiple_inputs().
-    input_identifiers (list)
+    input_identifiers : list
         A list of input node identifiers, which are also input for TCT_neighborhood_finder.neighborhood_finder_multiple_inputs().
 
     Returns
-    --------------
-    result_parsed (dict)
+    -------
+    result_parsed : dict
         The connected graph extracted from the parsed results.
 
-    --------------
-    Example:
-    >>>
-    input_identifiers = ['NCBIGene:6774', 'NCBIGene:4170','NCBIGene:4792','NCBIGene:4288','NCBIGene:596','NCBIGene:581','NCBIGene:836','NCBIGene:6777','NCBIGene:4790','NCBIGene:545']
-
-    result, result_parsed = TCT_neighborhood_finder.neighborhood_finder_multiple_inputs(input_identifiers,
+    Examples
+    --------
+    >>> input_identifiers = ['NCBIGene:6774', 'NCBIGene:4170','NCBIGene:4792','NCBIGene:4288','NCBIGene:596','NCBIGene:581','NCBIGene:836','NCBIGene:6777','NCBIGene:4790','NCBIGene:545']
+    >>> result, result_parsed = TCT_neighborhood_finder.neighborhood_finder_multiple_inputs(input_identifiers,
                                                                                             node2_categories = ['biolink:Gene','biolink:Protein'],
                                                                                             APInames = APInames,
                                                                                             metaKG = metaKG,
                                                                                             API_predicates = API_predicates)   
-
-    result = TCT_network_annotator.get_connected_graph(result_parsed, input_identifiers)
-    import datetime
-    import json
-    timestamp = datetime.datetime.now().strftime('%Y%m%d_%H%M%S')
-    with open('./PathFinder_testing_results/'+'TCT_neighborhood_finder_result_'+'_'+timestamp+'.json', 'w') as f:
-        json.dump(result, f)
-    # visualize the result using the TCT visualization tool (https://github.com/NCATSTranslator/Translator_component_toolkit/blob/main/notebooks/visulize_path_finder_results.html). 
-    --------------
-
+    >>> result = TCT_network_annotator.get_connected_graph(result_parsed, input_identifiers)
+    >>> import datetime
+    >>> import json
+    >>> timestamp = datetime.datetime.now().strftime('%Y%m%d_%H%M%S')
+    >>> with open('./PathFinder_testing_results/'+'TCT_neighborhood_finder_result_'+'_'+timestamp+'.json', 'w') as f:
+    >>>     json.dump(result, f)
+    >>> # visualize the result using the TCT visualization tool (https://github.com/NCATSTranslator/Translator_component_toolkit/blob/main/notebooks/visulize_path_finder_results.html). 
     """
 
     result_parsed_copy = result_parsed.copy()

TCT/TCT_pathfinder.py

@@ -31,20 +31,21 @@ def format_query_json_for_pathfinder_with_constraints(subject_ids,
         a list of predicates for the edge between subject and object nodes
     constraints : list
         a list of intermediate categories for the pathfinder pipeline, currently only one intermediate category is allowed in the constraints list. 
+
     Returns
     -------
     query_json_temp : dict
         a query json for pathfinder pipeline
 
-        Example
-        -------
-        query_json_temp = format_query_json_for_pathfinder_with_constraints(
-            subject_ids='NCBIGene:6774',
-            object_ids='NCBIGene:4170',
-            subject_categories=['biolink:Gene'],
-            object_categories=['biolink:Gene'],
-            predicates=['biolink:related_to'],
-            constraints=['biolink:Protein']
+    Examples
+    --------
+    >>> query_json_temp = format_query_json_for_pathfinder_with_constraints(
+        subject_ids='NCBIGene:6774',
+        object_ids='NCBIGene:4170',
+        subject_categories=['biolink:Gene'],
+        object_categories=['biolink:Gene'],
+        predicates=['biolink:related_to'],
+        constraints=['biolink:Protein'])
     """
     if constraints is None or len(constraints) == 0:
         constraints_intermediate_category = None