diff options
Diffstat (limited to 'gn3/api/correlation.py')
| -rw-r--r-- | gn3/api/correlation.py | 39 |
1 files changed, 30 insertions, 9 deletions
diff --git a/gn3/api/correlation.py b/gn3/api/correlation.py index e023cbe..f28e1f5 100644 --- a/gn3/api/correlation.py +++ b/gn3/api/correlation.py @@ -1,6 +1,4 @@ """Endpoints for running correlations""" -from unittest import mock - from flask import jsonify from flask import Blueprint from flask import request @@ -8,11 +6,31 @@ from flask import request from gn3.computations.correlations import compute_all_sample_correlation from gn3.computations.correlations import compute_all_lit_correlation from gn3.computations.correlations import compute_all_tissue_correlation - +from gn3.computations.correlations import map_shared_keys_to_values +from gn3.db_utils import database_connector 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\ @@ -23,11 +41,11 @@ def compute_sample_r(corr_method="pearson"): # xtodo move code below to compute_all_sampl correlation this_trait_data = correlation_input.get("this_trait") - target_datasets = correlation_input.get("target_dataset") + 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_datasets) + target_dataset=target_dataset_data) return jsonify({ "corr_results": correlation_results @@ -41,13 +59,16 @@ def compute_lit_corr(species=None, gene_id=None): might be needed for actual computing of the correlation results """ - database_instance = mock.Mock() + conn, _cursor_object = database_connector() target_traits_gene_ids = request.get_json() + target_trait_gene_list = list(target_traits_gene_ids.items()) lit_corr_results = compute_all_lit_correlation( - database_instance=database_instance, trait_lists=target_traits_gene_ids, + conn=conn, trait_lists=target_trait_gene_list, species=species, gene_id=gene_id) + conn.close() + return jsonify(lit_corr_results) @@ -56,10 +77,10 @@ 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_list = tissue_input_data["target_tissues"] + target_tissues_dict = tissue_input_data["target_tissues_dict"] results = compute_all_tissue_correlation(primary_tissue_dict=primary_tissue_dict, - target_tissues_dict_list=target_tissues_dict_list, + target_tissues_data=target_tissues_dict, corr_method=corr_method) return jsonify(results) |