testing added.

vbi/tests/all_tests.py

@@ -0,0 +1,35 @@
+import os
+import vbi
+import glob
+import unittest
+from os.path import join
+from unittest import TestLoader, TextTestRunner, TestSuite
+
+
+
+def get_module_path():
+    '''
+    Returns the location of the tests folder
+    '''
+    tests_folder = "tests"
+    location = vbi.__file__
+    location = location.replace('__init__.py', '')
+    location = join(location, tests_folder)
+
+    return location
+
+
+def tests():
+    """
+    Find all test_*.py files in the tests folder and run them
+
+    """
+
+    path = get_module_path()
+    test_suite = unittest.TestLoader().discover(path, pattern='test_*.py')
+    test_runner = TextTestRunner().run(test_suite)
+
+
+
+if __name__ == '__main__':
+    tests()

vbi/tests/test_features.py

@@ -0,0 +1,213 @@
+import unittest
+import numpy as np
+from vbi.feature_extraction.features import *
+
+class TestAbsEnergy(unittest.TestCase):
+
+    def test_positive_values(self):
+        ts = [1, 2, 3, 4, 5]
+        expected_values = [55]
+        expected_labels = ['abs_energy_0']
+
+        values, labels = abs_energy(ts)
+
+        self.assertEqual(values, expected_values)
+        self.assertEqual(labels, expected_labels)
+
+    def test_negative_values(self):
+        ts = [-1, -2, -3, -4, -5]
+        expected_values = [55]
+        expected_labels = ['abs_energy_0']
+
+        values, labels = abs_energy(ts)
+
+        self.assertEqual(values, expected_values)
+        self.assertEqual(labels, expected_labels)
+
+    def test_mixed_values(self):
+        ts = [-1, 2, -3, 4, -5]
+        expected_values = [55]
+        expected_labels = ['abs_energy_0']
+
+        values, labels = abs_energy(ts)
+
+        self.assertEqual(values, expected_values)
+        self.assertEqual(labels, expected_labels)
+
+    def test_empty_ts(self):
+        ts = []
+        expected_values = [np.nan]
+        expected_labels = ["abs_energy_0"]
+
+        values, labels = abs_energy(ts)
+
+        self.assertEqual(values, expected_values)
+        self.assertEqual(labels, expected_labels)
+
+    def test_nan_values(self):
+        ts = [1, np.nan, 3, 4, 5]
+        expected_values = [np.nan]
+        expected_labels = ['abs_energy_0']
+
+        values, labels = abs_energy(ts)
+
+        self.assertTrue(np.isnan(values[0]))
+        self.assertEqual(labels, expected_labels)
+
+    def test_infinite_values(self):
+        ts = [1, np.inf, 3, 4, 5]
+        expected_values = [np.nan]
+        expected_labels = ['abs_energy_0']
+
+        values, labels = abs_energy(ts)
+
+        self.assertTrue(np.isnan(values[0]))
+        self.assertEqual(labels, expected_labels)
+
+    def test_positive_values_fixed(self):
+        ts = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
+        expected_values = [30, 174]
+        expected_labels = ['abs_energy_0', 'abs_energy_1']
+
+        values, labels = abs_energy(ts)
+
+        self.assertEqual(list(values), expected_values)
+        self.assertEqual(list(labels), expected_labels)
+
+class TestAuc(unittest.TestCase):
+
+    def test_computes_area_under_curve(self):
+        ts = np.array([[1, 2, 3], [4, 5, 6]])
+        fs = 2
+        expected_values = np.array([2.0, 5.0])
+        expected_labels = ["auc_0", "auc_1"]
+
+        values, labels = auc(ts, fs)
+
+        self.assertTrue(np.allclose(values, expected_values))
+        self.assertEqual(labels, expected_labels)
+
+    def test_accepts_ndarrays_input(self):
+        ts = np.array([[1, 2, 3], [4, 5, 6]])
+        fs = 2
+        expected_values = np.array([2.0, 5.0])
+        expected_labels = ["auc_0", "auc_1"]
+
+        values, labels = auc(ts, fs)
+
+        self.assertTrue(np.allclose(values, expected_values))
+        self.assertEqual(labels, expected_labels)
+
+    def test_handles_nan_values(self):
+        ts = np.array([[1, np.nan, 3], [4, 5, np.nan]])
+        fs = 2
+        expected_values = np.array([np.nan, np.nan])
+        expected_labels = ["auc_0", "auc_1"]
+
+        values, labels = auc(ts, fs)
+
+        self.assertTrue(np.isnan(values).all())
+        self.assertEqual(labels, expected_labels)
+
+class TestCalcVar(unittest.TestCase):
+
+    def test_one_region_one_sample(self):
+        ts = np.array([1])
+        expected_values = [0]
+        expected_labels = ["variance_0"]
+        values, labels = calc_var(ts)
+        self.assertEqual(values, expected_values)
+        self.assertEqual(labels, expected_labels)
+
+    def test_multiple_regions_one_sample(self):
+        ts = np.array([[1], [2], [3]])
+        expected_values = [0, 0, 0]
+        expected_labels = ["variance_0", "variance_1", "variance_2"]
+        values, labels = calc_var(ts)
+        np.testing.assert_array_equal(values, expected_values)
+        np.testing.assert_array_equal(labels, expected_labels)
+
+    def test_one_region_multiple_samples(self):
+        ts = np.array([[1, 2, 3]])
+        expected_values = [0.66666667]
+        expected_labels = ["variance_0"]
+        values, labels = calc_var(ts)
+        self.assertEqual(np.allclose(values, expected_values), True)
+        self.assertEqual(labels, expected_labels)
+
+    def test_empty_list_input(self):
+        ts = []
+        expected_values = [np.nan]
+        expected_labels = ["variance_0"]
+        values, labels = calc_var(ts)
+        self.assertEqual(values, expected_values)
+        self.assertEqual(labels, expected_labels)
+
+        # Returns empty list when input is a list of empty numpy arrays.
+    def test_list_of_empty_numpy_arrays_input(self):
+        ts = [np.array([]), np.array([]), np.array([])]
+        expected_values = [np.nan]
+        expected_labels = ["variance_0"]
+        values, labels = calc_var(ts)
+        self.assertEqual(values, expected_values)
+        self.assertEqual(labels, expected_labels)
+
+class TestCalcStd(unittest.TestCase):
+
+    def test_handles_empty_input(self):
+        ts = []
+        expected_values = [np.nan]
+        expected_labels = ["std_0"]
+
+        values, labels = calc_std(ts)
+
+        self.assertEqual(values, expected_values)
+        self.assertEqual(labels, expected_labels)
+
+    def test_handles_nan_values(self):
+        ts = np.array([[1, 2, np.nan], [4, np.nan, 6]])
+        expected_values = [np.nan, np.nan]
+        expected_labels = ["std_0", "std_1"]
+
+        values, labels = calc_std(ts)
+
+        self.assertTrue(np.isnan(values).all())
+        self.assertEqual(labels, expected_labels)
+
+    def test_multiple_regions_and_samples(self):
+        ts = np.array([[1, 2, 3], [4, 5, 6]])
+        expected_values = [0.816497, 0.816497]
+        expected_labels = ["std_0", "std_1"]
+
+        values, labels = calc_std(ts)
+        self.assertTrue(np.allclose(values, expected_values))
+        self.assertEqual(labels, expected_labels)
+
+    def test_handles_infinite_values(self):
+        ts = np.array([[1, 2, np.inf], [4, -np.inf, 6]])
+        expected_values = [np.nan, np.nan]
+        expected_labels = ["std_0", "std_1"]
+
+        values, labels = calc_std(ts)
+
+        self.assertTrue(np.isnan(values).all())
+        self.assertEqual(labels, expected_labels)
+
+class TestFcSum(unittest.TestCase):
+
+    def test_calculate_sum_of_fc(self):
+        x = np.array([[1, 2, 3], [4, 5, 6]])
+        value, label = fc_sum(x)
+        self.assertAlmostEqual(value, 2.0)
+        self.assertEqual(label, "fc_sum")
+
+    def test_return_zero_for_single_sample_input(self):
+        x = np.array([[1], [2]])
+        value, label = fc_sum(x)
+        self.assertAlmostEqual(value, 0.0)
+
+
+if __name__ == '__main__':
+    unittest.main()
+    # obj = TestModules()
+    # obj.test_HH_Solution()