add unit tests

Signed-off-by: Oliver Schacht <[email protected]>

tests/TestCIT_FastKCI.py

@@ -0,0 +1,33 @@
+import unittest
+
+import numpy as np
+
+import causallearn.utils.cit as cit
+
+
+class TestCIT_FastKCI(unittest.TestCase):
+    def test_Gaussian_dist(self):
+        np.random.seed(10)
+        X = np.random.randn(1200, 1)
+        X_prime = np.random.randn(1200, 1)
+        Y = X + 0.5 * np.random.randn(1200, 1)
+        Z = Y + 0.5 * np.random.randn(1200, 1)
+        data = np.hstack((X, X_prime, Y, Z))
+
+        pvalue01 = []
+        pvalue03 = []
+        pvalue032 = []
+        for K in [3, 10]:
+            for J in [8, 16]:
+                for use_gp in [True, False]:
+                    cit_CIT = cit.CIT(data, 'fastkci', K=K, J=J, use_gp=use_gp)
+                    pvalue01.append(round(cit_CIT(0, 1), 4))
+                    pvalue03.append(round(cit_CIT(0, 3), 4))
+                    pvalue032.append(round(cit_CIT(0, 3, {2}), 4))
+
+        self.assertTrue(np.all((0.0 <= pvalue01) & (pvalue01 <= 1.0)),
+                        "pvalue01 contains invalid values")
+        self.assertTrue(np.all((0.0 <= pvalue03) & (pvalue03 <= 1.0)),
+                        "pvalue03 contains invalid values")
+        self.assertTrue(np.all((0.0 <= pvalue032) & (pvalue032 <= 1.0)),
+                        "pvalue032 contains invalid values")

tests/TestCIT_RCIT.py

@@ -0,0 +1,35 @@
+import unittest
+
+import numpy as np
+
+import causallearn.utils.cit as cit
+
+
+class TestCIT_RCIT(unittest.TestCase):
+    def test_Gaussian_dist(self):
+        np.random.seed(10)
+        X = np.random.randn(300, 1)
+        X_prime = np.random.randn(300, 1)
+        Y = X + 0.5 * np.random.randn(300, 1)
+        Z = Y + 0.5 * np.random.randn(300, 1)
+        data = np.hstack((X, X_prime, Y, Z))
+
+        pvalue01 = []
+        pvalue03 = []
+        pvalue032 = []
+        for approx in ["lpd4", "hbe", "gamma", "chi2", "perm"]:
+            for num_f in [50, 100]:
+                for num_f2 in [5, 10]:
+                    for rcit in [True, False]:
+                        cit_CIT = cit.CIT(data, 'rcit', approx=approx, num_f=num_f,
+                                          num_f2=num_f2, rcit=rcit)
+                        pvalue01.append(round(cit_CIT(0, 1), 4))
+                        pvalue03.append(round(cit_CIT(0, 3), 4))
+                        pvalue032.append(round(cit_CIT(0, 3, {2}), 4))
+
+        self.assertTrue(np.all((0.0 <= pvalue01) & (pvalue01 <= 1.0)),
+                        "pvalue01 contains invalid values")
+        self.assertTrue(np.all((0.0 <= pvalue03) & (pvalue03 <= 1.0)),
+                        "pvalue03 contains invalid values")
+        self.assertTrue(np.all((0.0 <= pvalue032) & (pvalue032 <= 1.0)),
+                        "pvalue032 contains invalid values")