From ef55d9769c50e12af6252f9fae78f5aa3bf42670 Mon Sep 17 00:00:00 2001
From: Alexander Kabui
Date: Mon, 3 May 2021 10:43:07 +0300
Subject: minor fixes for tiss correlation tests and naming

---
 gn3/computations/correlations.py            | 28 ++++++++++------------------
 tests/unit/computations/test_correlation.py |  8 ++++----
 2 files changed, 14 insertions(+), 22 deletions(-)

diff --git a/gn3/computations/correlations.py b/gn3/computations/correlations.py
index 3563530..065a1ed 100644
--- a/gn3/computations/correlations.py
+++ b/gn3/computations/correlations.py
@@ -226,6 +226,7 @@ def tissue_correlation_for_trait_list(
         primary_tissue_vals: List,
         target_tissues_values: List,
         corr_method: str,
+        trait_id: str,
         compute_corr_p_value: Callable = compute_corr_coeff_p_value) -> dict:
     """Given a primary tissue values for a trait and the target tissues values
     compute the correlation_cooeff and p value the input required are arrays
@@ -241,13 +242,12 @@ def tissue_correlation_for_trait_list(
                                      target_values=target_tissues_values,
                                      corr_method=corr_method)
 
-    lit_corr_result = {
+    tiss_corr_result = {trait_id: {
         "tissue_corr": tissue_corr_coeffient,
         "tissue_number": len(primary_tissue_vals),
-        "p_value": p_value
-    }
+        "p_value": p_value}}
 
-    return lit_corr_result
+    return tiss_corr_result
 
 
 def fetch_lit_correlation_data(
@@ -432,9 +432,9 @@ def process_trait_symbol_dict(trait_symbol_dict, symbol_tissue_vals_dict) -> Lis
     return traits_tissue_vals
 
 
-def experimental_compute_all_tissue_correlation(primary_tissue_dict: dict,
-                                                target_tissues_data: dict,
-                                                corr_method: str):
+def compute_tissue_correlation(primary_tissue_dict: dict,
+                               target_tissues_data: dict,
+                               corr_method: str):
     """Experimental function that uses multiprocessing\
     for computing tissue correlation
     """
@@ -450,25 +450,17 @@ def experimental_compute_all_tissue_correlation(primary_tissue_dict: dict,
     processed_values = []
 
     for target_tissue_obj in target_tissues_list:
+        trait_id = target_tissue_obj.get("trait_id")
 
         target_tissue_vals = target_tissue_obj.get("tissue_values")
         processed_values.append(
-            (primary_tissue_vals, target_tissue_vals, corr_method))
+            (primary_tissue_vals, target_tissue_vals, corr_method, trait_id))
 
     with multiprocessing.Pool() as pool:
         results = pool.starmap(
             tissue_correlation_for_trait_list, processed_values)
         for result in results:
-            tissue_result_dict = {"trait_name": result}
-            tissues_results.append(tissue_result_dict)
-
-        # tissue_result = tissue_correlation_for_trait_list(
-        #     primary_tissue_vals=primary_tissue_vals,
-        #     target_tissues_values=target_tissue_vals,
-        #     corr_method=corr_method)
-
-        # tissue_result_dict = {trait_id: tissue_result}
-        # tissues_results.append(tissue_result_dict)
+            tissues_results.append(result)
 
     return sorted(
         tissues_results,
diff --git a/tests/unit/computations/test_correlation.py b/tests/unit/computations/test_correlation.py
index c6fa35e..6414c3b 100644
--- a/tests/unit/computations/test_correlation.py
+++ b/tests/unit/computations/test_correlation.py
@@ -235,12 +235,12 @@ class TestCorrelation(TestCase):
         primary_tissue_values = [1.1, 1.5, 2.3]
         target_tissues_values = [1, 2, 3]
         mock_compute_corr_coeff.side_effect = [(0.4, 0.9), (-0.2, 0.91)]
-        expected_tissue_results = {
-            'tissue_corr': 0.4, 'p_value': 0.9, "tissue_number": 3}
-
+        expected_tissue_results = {"1456_at": {"tissue_corr": 0.4,
+                                               "p_value": 0.9, "tissue_number": 3}}
         tissue_results = tissue_correlation_for_trait_list(
             primary_tissue_values, target_tissues_values,
-            corr_method="pearson", compute_corr_p_value=mock_compute_corr_coeff)
+            corr_method="pearson", trait_id="1456_at",
+            compute_corr_p_value=mock_compute_corr_coeff)
 
         self.assertEqual(tissue_results, expected_tissue_results)
 
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