From ec1d2180d99e0cde1dc181ee9ed79e86cf1a5675 Mon Sep 17 00:00:00 2001
From: Arun Isaac
Date: Thu, 11 Nov 2021 16:10:35 +0530
Subject: Reimplement correlations2.compute_correlation using pearsonr.

correlations2.compute_correlation computes the Pearson correlation
coefficient. Outsource this computation to scipy.stats.pearsonr. When the
inputs are constant, the Pearson correlation coefficient does not exist and is
represented by NaN. Update the tests to reflect this.

* gn3/computations/correlations2.py: Remove import of sqrt from math.
(compute_correlation): Reimplement using scipy.stats.pearsonr.
* tests/unit/computations/test_correlation.py: Import math.
(TestCorrelation.test_compute_correlation): When inputs are constant, set
expected correlation coefficient to NaN.
---
 tests/unit/computations/test_correlation.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

(limited to 'tests/unit')

diff --git a/tests/unit/computations/test_correlation.py b/tests/unit/computations/test_correlation.py
index e6cf198..d60dd62 100644
--- a/tests/unit/computations/test_correlation.py
+++ b/tests/unit/computations/test_correlation.py
@@ -4,6 +4,7 @@ from unittest import mock
 import unittest
 
 from collections import namedtuple
+import math
 from numpy.testing import assert_almost_equal
 
 from gn3.computations.correlations import normalize_values
@@ -471,10 +472,10 @@ class TestCorrelation(TestCase):
                  [None, None, None, None, None, None, None, None, None, 0],
                  (0.0, 1)],
                 [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
-                 (0, 10)],
+                 (math.nan, 10)],
                 [[9.87, 9.87, 9.87, 9.87, 9.87, 9.87, 9.87, 9.87, 9.87, 9.87],
                  [9.87, 9.87, 9.87, 9.87, 9.87, 9.87, 9.87, 9.87, 9.87, 9.87],
-                 (0.9999999999999998, 10)],
+                 (math.nan, 10)],
                 [[9.3, 2.2, 5.4, 7.2, 6.4, 7.6, 3.8, 1.8, 8.4, 0.2],
                  [0.6, 3.97, 5.82, 8.21, 1.65, 4.55, 6.72, 9.5, 7.33, 2.34],
                  (-0.12720361919462056, 10)],
-- 
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