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-rw-r--r--tests/unit/computations/test_pca.py101
1 files changed, 101 insertions, 0 deletions
diff --git a/tests/unit/computations/test_pca.py b/tests/unit/computations/test_pca.py
new file mode 100644
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+++ b/tests/unit/computations/test_pca.py
@@ -0,0 +1,101 @@
+"""module contains unittests for pca"""
+import unittest
+from unittest.mock import patch
+from unittest.mock import Mock
+
+import numpy as np
+import pytest
+
+from gn3.computations.pca import cache_pca_dataset
+from gn3.computations.pca import generate_pca_temp_traits
+from gn3.computations.pca import generate_scree_plot_data
+from gn3.computations.pca import process_factor_loadings_tdata
+
+
+class TestPCA(unittest.TestCase):
+ """pca testcase class"""
+
+ @pytest.mark.unit_test
+ def test_process_factor_loadings(self):
+ """test for processing factor loadings"""
+
+ test_array = np.array([
+ [-0.23511749, -0.61483617, -0.26872797, 0.70319381],
+ [-0.71057342, 0.4623377, -0.52921008, -0.0355803],
+ [-0.60977093, -0.02877103, 0.78874096, 0.07238328],
+ [0.26073856, 0.63827311, 0.16003023, 0.70640864]
+ ])
+
+ expected_results = [[-0.23511749, -0.71057342, -0.60977093],
+ [-0.61483617, 0.4623377, -0.02877103],
+ [-0.26872797, -0.52921008, 0.78874096],
+ [0.70319381, -0.0355803, 0.07238328]]
+
+ self.assertEqual(process_factor_loadings_tdata(
+ test_array, 3), expected_results)
+
+ @pytest.mark.unit_test
+ @patch("gn3.computations.pca.generate_pca_traits_vals")
+ def test_generate_pca_datasets(self, mock_pca_data):
+ """test for generating temp pca dataset"""
+
+ mock_pca_data.return_value = np.array([[21, 10, 17, 15, 13],
+ [21, 11, 18,
+ 9, 1],
+ [22, 16, 0,
+ 0.22667229, -1],
+ [31, 12, 10, 17, 11]])
+
+ shared_samples = ["BXD1", "BXD2", "BXD", "BXD4", "Unkown"]
+
+ dataset_samples = ["BXD1", "BXD5", "BXD4", "BXD"]
+ expected_results = {
+ "PCA1_mouse_G1_now": ["21.0", "x", "10.0", "17.0"],
+ "PCA2_mouse_G1_now": ["21.0", "x", "11.0", "18.0"],
+ "PCA3_mouse_G1_now": ["22.0", "x", "16.0", "0.0"],
+ "PCA4_mouse_G1_now": ["31.0", "x", "12.0", "10.0"]
+ }
+
+ results = generate_pca_temp_traits(species="mouse", group="G1",
+ traits_data=[],
+ dataset_samples=dataset_samples,
+ corr_array=[],
+ shared_samples=shared_samples,
+ create_time="now")
+
+ self.assertEqual(results, expected_results)
+
+ @pytest.mark.unit_test
+ def test_generate_scree_plot(self):
+ """test scree plot data is generated"""
+
+ variance = [0.9271, 0.06232, 0.031]
+
+ self.assertEqual(generate_scree_plot_data(variance),
+ (['PC1', 'PC2', 'PC3'], [92.7, 6.2, 3.1]))
+
+ @pytest.mark.unit_test
+ def test_cache_pca_datasets(self):
+ """test for caching pca datasets"""
+
+ pca_traits = {
+ "PCA_1": ["11.0", "x", "9.0", "7.0"],
+ "PCA_2": ["x", "x", "1.2", "3.1"]
+ }
+
+ self.assertEqual(cache_pca_dataset(redis_conn={}, exp_days=30,
+ pca_trait_dict=pca_traits), False)
+
+ mock_redis = Mock()
+ mock_redis.set.return_value = True
+
+ test_data = [({}, 30, pca_traits, False),
+ (mock_redis, 30, pca_traits, True)]
+
+ for (test_redis, exp_day, test_traits, expected) in test_data:
+
+ with self.subTest(redis_conn=test_redis,
+ exp_days=exp_day, pca_trait_dict=test_traits):
+
+ self.assertEqual(cache_pca_dataset(
+ test_redis, exp_day, test_traits), expected)