Added CircularGridDistribution

Author: FlorianPfaff

pyrecest/tests/distributions/test_circular_grid_distribution.py

@@ -0,0 +1,43 @@
+import unittest
+import numpy as np
+from pyrecest.distributions.circle.circular_grid_distribution import CircularGridDistribution
+from pyrecest.distributions import VonMisesDistribution, WrappedNormalDistribution
+
+class CircularGridDistributionTest(unittest.TestCase):
+
+    @staticmethod
+    def _test_grid_conversion(dist, coeffs, enforceNonnegative, tolerance):
+        figd = CircularGridDistribution.from_distribution(dist, coeffs, enforce_pdf_nonnegative=enforceNonnegative)
+        # Test grid values
+        xvals = np.linspace(0, 2*np.pi, coeffs, endpoint=False)
+        np.testing.assert_allclose(figd.pdf(xvals), dist.pdf(xvals), atol=tolerance)
+        # Test approximation of pdf
+        xvals = np.arange(-2 * np.pi, 3 * np.pi, 0.01)
+        np.testing.assert_allclose(figd.pdf(xvals), dist.pdf(xvals), atol=tolerance)
+
+    def test_VMToGridId(self):
+        mu = 0.4
+        for kappa in np.arange(.1, 2.1, .1):
+            dist = VonMisesDistribution(mu, kappa)
+            self._test_grid_conversion(dist, 101, False, 1E-8)
+
+    def test_VMToGridSqrt(self):
+        mu = 0.5
+        for kappa in np.arange(.1, 2.1, .1):
+            dist = VonMisesDistribution(mu, kappa)
+            self._test_grid_conversion(dist, 101, True, 1E-8)
+
+    def test_WNToGridId(self):
+        mu = 0.8
+        for sigma in np.arange(.2, 2.1, .1):
+            dist = WrappedNormalDistribution(mu, sigma)
+            self._test_grid_conversion(dist, 101, False, 1E-8)
+
+    def test_WNToGridSqrt(self):
+        mu = 0.9
+        for sigma in np.arange(.2, 2.1, .1):
+            dist = WrappedNormalDistribution(mu, sigma)
+            self._test_grid_conversion(dist, 101, True, 1E-8)
+
+if __name__ == "__main__":
+    unittest.main()