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#2391 adding graceful handling if PloverDB is down
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@kvnthomas98
kvnthomas98 committed Oct 2, 2024
1 parent 71e405a commit 5b609be
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Showing 2 changed files with 76 additions and 64 deletions.
8 changes: 4 additions & 4 deletions code/ARAX/ARAXQuery/ARAX_infer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -857,8 +857,8 @@ def __chemical_gene_regulation_graph_expansion(self, describe=False):
self.response.warning(f"Could not get predicted genes for chemical {preferred_subject_curie}. Likely the model was not trained with this chemical.")
return self.response
if top_paths is None or len(top_paths) == 0:
self.response.warning(f"Could not get any predicted paths for chemical {preferred_subject_curie}. Likely the model considers there is no reasonable path for this chemical.")

self.response.warning(f"Could not get any predicted paths for chemical {preferred_subject_curie}. Either Plover is not reachable or no paths found")
return self.response
iu = InferUtilities()
qedge_id = self.parameters.get('qedge_id')
self.response, self.kedge_global_iter, self.qedge_global_iter, self.qnode_global_iter, self.option_global_iter = iu.genrete_regulate_subgraphs(self.response, normalized_subject_curie, None, top_predictions, top_paths, qedge_id, self.parameters['regulation_type'], self.kedge_global_iter, self.qedge_global_iter, self.qnode_global_iter, self.option_global_iter)
Expand All @@ -875,8 +875,8 @@ def __chemical_gene_regulation_graph_expansion(self, describe=False):
self.response.warning(f"Could not get predicted chemicals for gene {preferred_object_curie}. Likely the model was not trained with this gene.")
return self.response
if top_paths is None or len(top_paths) == 0:
self.response.warning(f"Could not get any predicted paths for gene {preferred_object_curie}. Likely the model considers there is no reasonable path for this gene.")

self.response.warning(f"Could not get any predicted paths for gene {preferred_object_curie}. Either Plover is not reachable or no paths found")
return self.response
iu = InferUtilities()
qedge_id = self.parameters.get('qedge_id')

Expand Down
132 changes: 72 additions & 60 deletions code/ARAX/ARAXQuery/Infer/scripts/creativeCRG.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,6 +28,7 @@ def eprint(*args, **kwargs): print(*args, file=sys.stderr, **kwargs)
def call_plover(curies: List, respect_predicate_symmetry: bool=False):
json = {}
plover_url = RTXConfig.plover_url
status_code = 500
endpoint = "/query"
body = {
"edges": {
Expand All @@ -49,33 +50,12 @@ def call_plover(curies: List, respect_predicate_symmetry: bool=False):
}
try:
response = requests.post(plover_url + endpoint, headers={'accept': 'application/json'}, json=body)
status_code = response.status_code
json = response.json()
except Exception as e:
pass
return json

# class TFDatabase:
# def __init__(self):
# database = '/Users/kevin/Documents/GitHub/RTX/code/ARAX/ARAXQuery/Infer/data/xCRG_data/tf_db_kg2.10.0.db'
# self.connection = sqlite3.connect(database)
# self.connection.row_factory = sqlite3.Row

# def _query_database(self, query):
# cursor = self.connection.cursor()
# cursor.execute(query)
# res = cursor.fetchall()
# return res

# # def get_tf_neighbors(self):
# # query = "select * from edges ;"
# # return self._query_database(query)

# def __del__(self):
# try:
# self.connection.commit()
# self.connection.close()
# except:
# pass
return status_code, json


def load_ML_CRGmodel(response: ARAXResponse, model_path: str, model_type: str):

Expand Down Expand Up @@ -216,7 +196,7 @@ def __init__(self, response: ARAXResponse, data_path: str):
self.tf_list = json.loads(fp.read())['tf']

def get_tf_neighbors(self):
response = call_plover(self.tf_list,respect_predicate_symmetry=False)
status_code, response = call_plover(self.tf_list,respect_predicate_symmetry=False)
edges = response.get("edges",{}).get("e00",{})
query_tf_neighbor_data = []
answer_tf_neigbor_data = []
Expand All @@ -236,7 +216,7 @@ def get_tf_neighbors(self):
curie = c1
tf = c2
query_tf_neighbor_data.append({"edge_id": edge, "transcription_factor":tf, "neighbour": curie, "depth": depth})
return query_tf_neighbor_data,answer_tf_neigbor_data, edges
return status_code, query_tf_neighbor_data,answer_tf_neigbor_data, edges

def add_node_ids_to_path(self, paths, tf_edges,chemical_edges, gene_edges):
kg2_querier = KG2Querier(self.response, RTXConfig.plover_url)
Expand All @@ -255,6 +235,8 @@ def add_node_ids_to_path(self, paths, tf_edges,chemical_edges, gene_edges):
_path_to_add.append({edge:trapi_edge})
_path_to_add.append(plover_edge[1])
final_paths[(query,answer)].append(_path_to_add)
if len(final_paths[(query,answer)]) == 0:
del final_paths[(query,answer)]
return final_paths


Expand Down Expand Up @@ -493,12 +475,21 @@ def _check_params(query_chemical: Optional[str], query_gene: Optional[str], mode
self.response.warning(f"There is no chemical-gene pair satisfying the requirement of top {N} with threshold >={threshold}. Perhaps try using more loose threshold.")
return None
top_paths = dict()
chemical_neighbors = call_plover([query_chemical])
status_code, chemical_neighbors = call_plover([query_chemical])
if status_code != 200:
self.response.warning(f"Could not get answers from Plover. Plover responded with status code: {status_code}")
return None
answers = res['gene_id'].tolist()
self.preferred_curies = self.get_preferred_curies(answers)
valid_genes = [item for item in self.preferred_curies.values() if item]
gene_neighbors = call_plover(valid_genes)
query_tf_neighbors, answer_tf_neigbors, tf_edges = self.get_tf_neighbors()
status_code, gene_neighbors = call_plover(valid_genes)
if status_code != 200:
self.response.warning(f"Could not get answers from Plover. Plover responded with status code: {status_code}")
return None
status_code, query_tf_neighbors, answer_tf_neigbors, tf_edges = self.get_tf_neighbors()
if status_code != 200:
self.response.warning(f"Could not get answers from Plover. Plover responded with status code: {status_code}")
return None


paths = self.get_paths(preferred_query_chemical, res['gene_id'].tolist(), chemical_neighbors, gene_neighbors, query_tf_neighbors, answer_tf_neigbors, self.tf_list, M)
Expand All @@ -520,12 +511,21 @@ def _check_params(query_chemical: Optional[str], query_gene: Optional[str], mode

top_paths = dict()

gene_neighbors = call_plover([preferred_query_gene])
status_code, gene_neighbors = call_plover([preferred_query_gene])
if status_code != 200:
self.response.warning(f"Could not get answers from Plover. Plover responded with status code: {status_code}")
return None
answers = res['chemical_id'].tolist()
self.preferred_curies = self.get_preferred_curies(answers)
valid_chemicals = [item for item in self.preferred_curies.values() if item]
chemical_neighbors = call_plover(valid_chemicals)
query_tf_neighbors, answer_tf_neigbors, tf_edges = self.get_tf_neighbors()
status_code, chemical_neighbors = call_plover(valid_chemicals)
if status_code != 200:
self.response.warning(f"Could not get answers from Plover. Plover responded with status code: {status_code}")
return None
status_code, query_tf_neighbors, answer_tf_neigbors, tf_edges = self.get_tf_neighbors()
if status_code != 200:
self.response.warning(f"Could not get answers from Plover. Plover responded with status code: {status_code}")
return None
paths = self.get_paths(preferred_query_gene, res['chemical_id'].tolist(), gene_neighbors, chemical_neighbors, query_tf_neighbors, answer_tf_neigbors,self.tf_list, M)
final_paths = self.add_node_ids_to_path(paths, tf_edges, chemical_neighbors, gene_neighbors)
return final_paths
Expand All @@ -542,12 +542,52 @@ def get_paths(self, query_curie, answer_curies, query_neighbors, answer_neighbor
for answer in answer_curies:
valid_answer_tf_list[answer] = []

edges_to_ignore = set()
for edge_id, edge in answer_neighbors['edges']['e00'].items():
if edge[1] not in self.preferred_curies.values():
continue
relevant_node = False
answer = edge[1]
neighbor = edge[0]
# ignoring lookup edges
if neighbor == query_curie:
edges_to_ignore.add(edge_id)
continue
neighbor_category = answer_neighbors['nodes']['n01'][neighbor][1]
if neighbor_category in self.relevant_node_categories:
relevant_node = True
# one hop from answer
if answer not in answer_path:
answer_path[answer] = dict()
if neighbor in tf_list and neighbor not in answer_path[answer]:
valid_answer_tf_list[answer].append(neighbor)
answer_path[answer][neighbor] = [edge_id, self.predicate_depth_map[edge[2]]]
elif neighbor in tf_list and neighbor in answer_path[answer]:
if answer_path[answer][neighbor][-1] < self.predicate_depth_map[edge[2]]:
answer_path[answer][neighbor] = [edge_id, self.predicate_depth_map[edge[2]]]

# two hop from answer
for item in answer_tf_neighbors_dict.get(neighbor,[]):
neighbor_category = answer_neighbors['nodes']['n01'][neighbor][1]
if relevant_node and item[1] not in valid_answer_tf_list[answer]:
valid_answer_tf_list[answer].append(item[1])
if item[1] not in answer_path[answer]:
answer_path[answer][item[1]] = [item[0],edge_id, item[2]]
elif answer_path[answer][item[1]][-1] < item[2] and ((item[1] not in valid_answer_tf_list[answer]) or relevant_node):
answer_path[answer][item[1]] = [item[0], edge_id, min(item[2],self.predicate_depth_map[edge[2]])]

for record in query_tf_neighbors:
if record['edge_id'] in edges_to_ignore:
continue
query_tf_neighbors_dict[record['neighbour']] = query_tf_neighbors_dict.get(record['neighbour'],[]) + [(record['edge_id'],record['transcription_factor'], record['depth'])]
for record in answer_tf_neighbors:
if record['edge_id'] in edges_to_ignore:
continue
answer_tf_neighbors_dict[record['neighbour']] = answer_tf_neighbors_dict.get(record['neighbour'],[]) + [(record['edge_id'],record['transcription_factor'], record['depth'])]
# one hop from query
for edge_id, edge in query_neighbors['edges']['e00'].items():
if edge_id in edges_to_ignore:
continue
if edge[1] in tf_list and edge[1] not in query_path:
valid_query_tf_list.append(edge[1])
query_path[edge[1]] = [edge_id,self.predicate_depth_map[edge[2]]]
Expand Down Expand Up @@ -575,34 +615,6 @@ def get_paths(self, query_curie, answer_curies, query_neighbors, answer_neighbor



for edge_id, edge in answer_neighbors['edges']['e00'].items():
if edge[1] not in self.preferred_curies.values():
continue
relevant_node = False
answer = edge[1]
neighbor = edge[0]
neighbor_category = answer_neighbors['nodes']['n01'][neighbor][1]
if neighbor_category in self.relevant_node_categories:
relevant_node = True
# one hop from answer
if answer not in answer_path:
answer_path[answer] = dict()
if neighbor in tf_list and neighbor not in answer_path[answer]:
valid_answer_tf_list[answer].append(neighbor)
answer_path[answer][neighbor] = [edge_id, self.predicate_depth_map[edge[2]]]
elif neighbor in tf_list and neighbor in answer_path[answer]:
if answer_path[answer][neighbor][-1] < self.predicate_depth_map[edge[2]]:
answer_path[answer][neighbor] = [edge_id, self.predicate_depth_map[edge[2]]]

# two hop from answer
for item in answer_tf_neighbors_dict.get(neighbor,[]):
neighbor_category = answer_neighbors['nodes']['n01'][neighbor][1]
if relevant_node and item[1] not in valid_answer_tf_list[answer]:
valid_answer_tf_list[answer].append(item[1])
if item[1] not in answer_path[answer]:
answer_path[answer][item[1]] = [item[0],edge_id, item[2]]
elif answer_path[answer][item[1]][-1] < item[2] and ((item[1] not in valid_answer_tf_list[answer]) or relevant_node):
answer_path[answer][item[1]] = [item[0], edge_id, min(item[2],self.predicate_depth_map[edge[2]])]
# joining paths
for answer in answer_curies:
combined_path[(query_curie,answer)] = list()
Expand Down

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