diff options
| -rw-r--r-- | gn3/api/correlation.py | 4 | ||||
| -rw-r--r-- | gn3/computations/correlations.py | 26 | ||||
| -rw-r--r-- | tests/integration/test_correlation.py | 2 | ||||
| -rw-r--r-- | tests/unit/computations/test_correlation.py | 14 |
4 files changed, 25 insertions, 21 deletions
diff --git a/gn3/api/correlation.py b/gn3/api/correlation.py index e7e89cf..a3e366e 100644 --- a/gn3/api/correlation.py +++ b/gn3/api/correlation.py @@ -5,7 +5,7 @@ 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 compute_tissue_correlation from gn3.computations.correlations import map_shared_keys_to_values from gn3.db_utils import database_connector @@ -78,7 +78,7 @@ def compute_tissue_corr(corr_method="pearson"): primary_tissue_dict = tissue_input_data["primary_tissue"] target_tissues_dict = tissue_input_data["target_tissues_dict"] - results = compute_all_tissue_correlation(primary_tissue_dict=primary_tissue_dict, + results = compute_tissue_correlation(primary_tissue_dict=primary_tissue_dict, target_tissues_data=target_tissues_dict, corr_method=corr_method) diff --git a/gn3/computations/correlations.py b/gn3/computations/correlations.py index 56f483c..1fd3213 100644 --- a/gn3/computations/correlations.py +++ b/gn3/computations/correlations.py @@ -124,11 +124,12 @@ def filter_shared_sample_keys(this_samplelist, return (this_vals, target_vals) -def compute_all_sample_correlation(this_trait, - target_dataset, - corr_method="pearson") -> List: +def speed_compute_all_sample_correlation(this_trait, + target_dataset, + corr_method="pearson") -> List: """Given a trait data sample-list and target__datasets compute all sample correlation + this functions uses multiprocessing if not use the normal fun """ # xtodo fix trait_name currently returning single one @@ -160,9 +161,9 @@ def compute_all_sample_correlation(this_trait, key=lambda trait_name: -abs(list(trait_name.values())[0]["corr_coefficient"])) -def benchmark_compute_all_sample(this_trait, - target_dataset, - corr_method="pearson") -> List: +def compute_all_sample_correlation(this_trait, + target_dataset, + corr_method="pearson") -> List: """Temp function to benchmark with compute_all_sample_r alternative to compute_all_sample_r where we use multiprocessing @@ -174,6 +175,7 @@ def benchmark_compute_all_sample(this_trait, target_trait_data = target_trait["trait_sample_data"] this_vals, target_vals = filter_shared_sample_keys( this_trait_samples, target_trait_data) + sample_correlation = compute_sample_r_correlation( trait_name=trait_name, corr_method=corr_method, @@ -190,7 +192,9 @@ def benchmark_compute_all_sample(this_trait, "num_overlap": num_overlap } corr_results.append({trait_name: corr_result}) - return corr_results + return sorted( + corr_results, + key=lambda trait_name: -abs(list(trait_name.values())[0]["corr_coefficient"])) def tissue_correlation_for_trait( @@ -336,7 +340,7 @@ def compute_all_lit_correlation(conn, trait_lists: List, return sorted_lit_results -def compute_all_tissue_correlation(primary_tissue_dict: dict, +def compute_tissue_correlation(primary_tissue_dict: dict, target_tissues_data: dict, corr_method: str): """Function acts as an abstraction for tissue_correlation_for_trait\ @@ -382,9 +386,9 @@ def process_trait_symbol_dict(trait_symbol_dict, symbol_tissue_vals_dict) -> Lis return traits_tissue_vals -def compute_tissue_correlation(primary_tissue_dict: dict, - target_tissues_data: dict, - corr_method: str): +def speed_compute_tissue_correlation(primary_tissue_dict: dict, + target_tissues_data: dict, + corr_method: str): """Experimental function that uses multiprocessing for computing tissue correlation diff --git a/tests/integration/test_correlation.py b/tests/integration/test_correlation.py index e67f58d..bdd9bce 100644 --- a/tests/integration/test_correlation.py +++ b/tests/integration/test_correlation.py @@ -80,7 +80,7 @@ class CorrelationIntegrationTest(TestCase): self.assertEqual(mock_compute_corr.call_count, 1) self.assertEqual(response.status_code, 200) - @mock.patch("gn3.api.correlation.compute_all_tissue_correlation") + @mock.patch("gn3.api.correlation.compute_tissue_correlation") def test_tissue_correlation(self, mock_tissue_corr): """Test api/correlation/tissue_corr/{corr_method}""" mock_tissue_corr.return_value = {} diff --git a/tests/unit/computations/test_correlation.py b/tests/unit/computations/test_correlation.py index 9450094..f2d65bd 100644 --- a/tests/unit/computations/test_correlation.py +++ b/tests/unit/computations/test_correlation.py @@ -1,5 +1,4 @@ """Module contains the tests for correlation""" -import unittest from unittest import TestCase from unittest import mock @@ -16,7 +15,7 @@ from gn3.computations.correlations import fetch_lit_correlation_data from gn3.computations.correlations import query_formatter from gn3.computations.correlations import map_to_mouse_gene_id from gn3.computations.correlations import compute_all_lit_correlation -from gn3.computations.correlations import compute_all_tissue_correlation +from gn3.computations.correlations import compute_tissue_correlation from gn3.computations.correlations import map_shared_keys_to_values from gn3.computations.correlations import process_trait_symbol_dict from gn3.computations.correlations2 import compute_correlation @@ -173,7 +172,6 @@ class TestCorrelation(TestCase): self.assertEqual(results, (filtered_this_samplelist, filtered_target_samplelist)) - @unittest.skip("Test needs to be refactored ") @mock.patch("gn3.computations.correlations.compute_sample_r_correlation") @mock.patch("gn3.computations.correlations.filter_shared_sample_keys") def test_compute_all_sample(self, filter_shared_samples, sample_r_corr): @@ -181,7 +179,7 @@ class TestCorrelation(TestCase): filter_shared_samples.return_value = (["1.23", "6.565", "6.456"], [ "6.266", "6.565", "6.456"]) - sample_r_corr.return_value = ([-1.0, 0.9, 6]) + sample_r_corr.return_value = (["1419792_at", -1.0, 0.9, 6]) this_trait_data = { "trait_id": "1455376_at", @@ -204,13 +202,14 @@ class TestCorrelation(TestCase): } ] - sample_all_results = [{"1419792_at": {"corr_coeffient": -1.0, + sample_all_results = [{"1419792_at": {"corr_coefficient": -1.0, "p_value": 0.9, "num_overlap": 6}}] self.assertEqual(compute_all_sample_correlation( this_trait=this_trait_data, target_dataset=traits_dataset), sample_all_results) sample_r_corr.assert_called_once_with( + trait_name='1419792_at', corr_method="pearson", trait_vals=['1.23', '6.565', '6.456'], target_samples_vals=['6.266', '6.565', '6.456']) filter_shared_samples.assert_called_once_with( @@ -417,7 +416,7 @@ class TestCorrelation(TestCase): {"1418702_a_at": {"tissue_corr": -0.5, "tissue_p_val": 0.9, "tissue_number": 3}}] - results = compute_all_tissue_correlation( + results = compute_tissue_correlation( primary_tissue_dict=primary_tissue_dict, target_tissues_data=target_tissue_data, corr_method="pearson") @@ -491,4 +490,5 @@ class TestCorrelation(TestCase): [None, None, None, None, 2, None, None, 3, None, None], (0.0, 2)]]: with self.subTest(dbdata=dbdata, userdata=userdata): - self.assertEqual(compute_correlation(dbdata, userdata), expected) + self.assertEqual(compute_correlation( + dbdata, userdata), expected) |