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"""Endpoints for running correlations"""
import sys
from functools import reduce
import redis
from flask import jsonify
from flask import Blueprint
from flask import request
from flask import current_app
from gn3.settings import SQL_URI
from gn3.commands import run_async_cmd, compose_pcorrs_command
from gn3.db_utils import database_connector
from gn3.responses.pcorrs_responses import build_response
from gn3.computations.correlations import map_shared_keys_to_values
from gn3.computations.correlations import compute_tissue_correlation
from gn3.computations.correlations import compute_all_lit_correlation
from gn3.computations.correlations import compute_all_sample_correlation
correlation = Blueprint("correlation", __name__)
@correlation.route("/sample_x/<string:corr_method>", methods=["POST"])
def compute_sample_integration(corr_method="pearson"):
"""temporary api to help integrate genenetwork2 to genenetwork3 """
correlation_input = request.get_json()
target_samplelist = correlation_input.get("target_samplelist")
target_data_values = correlation_input.get("target_dataset")
this_trait_data = correlation_input.get("trait_data")
results = map_shared_keys_to_values(target_samplelist, target_data_values)
correlation_results = compute_all_sample_correlation(corr_method=corr_method,
this_trait=this_trait_data,
target_dataset=results)
return jsonify(correlation_results)
@correlation.route("/sample_r/<string:corr_method>", methods=["POST"])
def compute_sample_r(corr_method="pearson"):
"""Correlation endpoint for computing sample r correlations\
api expects the trait data with has the trait and also the\
target_dataset data
"""
correlation_input = request.get_json()
# xtodo move code below to compute_all_sampl correlation
this_trait_data = correlation_input.get("this_trait")
target_dataset_data = correlation_input.get("target_dataset")
correlation_results = compute_all_sample_correlation(corr_method=corr_method,
this_trait=this_trait_data,
target_dataset=target_dataset_data)
return jsonify({
"corr_results": correlation_results
})
@correlation.route("/lit_corr/<string:species>/<int:gene_id>", methods=["POST"])
def compute_lit_corr(species=None, gene_id=None):
"""Api endpoint for doing lit correlation.results for lit correlation\
are fetched from the database this is the only case where the db\
might be needed for actual computing of the correlation results
"""
with database_connector() as conn:
target_traits_gene_ids = request.get_json()
target_trait_gene_list = list(target_traits_gene_ids.items())
lit_corr_results = compute_all_lit_correlation(
conn=conn, trait_lists=target_trait_gene_list,
species=species, gene_id=gene_id)
return jsonify(lit_corr_results)
@correlation.route("/tissue_corr/<string:corr_method>", methods=["POST"])
def compute_tissue_corr(corr_method="pearson"):
"""Api endpoint fr doing tissue correlation"""
tissue_input_data = request.get_json()
primary_tissue_dict = tissue_input_data["primary_tissue"]
target_tissues_dict = tissue_input_data["target_tissues_dict"]
results = compute_tissue_correlation(primary_tissue_dict=primary_tissue_dict,
target_tissues_data=target_tissues_dict,
corr_method=corr_method)
return jsonify(results)
@correlation.route("/partial", methods=["POST"])
def partial_correlation():
"""API endpoint for partial correlations."""
def trait_fullname(trait):
return f"{trait['dataset']}::{trait['trait_name']}"
def __field_errors__(args):
def __check__(acc, field):
if args.get(field) is None:
return acc + (f"Field '{field}' missing",)
return acc
return __check__
def __errors__(request_data, fields):
errors = tuple()
if request_data is None:
return ("No request data",)
return reduce(__field_errors__(request_data), fields, errors)
args = request.get_json()
with_target_db = args.get("with_target_db", True)
request_errors = __errors__(
args, ("primary_trait", "control_traits",
("target_db" if with_target_db else "target_traits"),
"method"))
if request_errors:
return build_response({
"status": "error",
"messages": request_errors,
"error_type": "Client Error"})
with redis.Redis() as conn:
if with_target_db:
command = compose_pcorrs_command(
trait_fullname(args["primary_trait"]),
tuple(
trait_fullname(trait) for trait in args["control_traits"]),
args["method"], target_database=args["target_db"],
criteria = int(args.get("criteria", 500)))
else:
command = compose_pcorrs_command(
trait_fullname(args["primary_trait"]),
tuple(
trait_fullname(trait) for trait in args["control_traits"]),
args["method"], target_traits=tuple(
trait_fullname(trait) for trait in args["target_traits"]))
queueing_results = run_async_cmd(
conn=conn,
cmd=command,
job_queue=current_app.config.get("REDIS_JOB_QUEUE"),
env = {"PYTHONPATH": ":".join(sys.path), "SQL_URI": SQL_URI})
return build_response({
"status": "success",
"results": queueing_results,
"queued": True
})
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