import unittest
import numpy as np
from decoders import proximal


class CheckParityTestCase(unittest.TestCase):
    """Test case for the check_parity function."""
    def test_check_parity(self):
        # Hamming(7,4) code
        G = np.array([[1, 1, 1, 0, 0, 0, 0],
                      [1, 0, 0, 1, 1, 0, 0],
                      [0, 1, 0, 1, 0, 1, 0],
                      [1, 1, 0, 1, 0, 0, 1]])
        H = np.array([[1, 0, 1, 0, 1, 0, 1],
                      [0, 1, 1, 0, 0, 1, 1],
                      [0, 0, 0, 1, 1, 1, 1]])
        R = np.array([[0, 0, 1, 0, 0, 0, 0],
                      [0, 0, 0, 0, 1, 0, 0],
                      [0, 0, 0, 0, 0, 1, 0],
                      [0, 0, 0, 0, 0, 0, 1]])

        decoder = proximal.ProximalDecoder(H, R)

        d1 = np.array([0, 1, 0, 1])
        c1 = np.dot(np.transpose(G), d1) % 2

        d2 = np.array([0, 0, 0, 0])
        c2 = np.dot(np.transpose(G), d2) % 2

        d3 = np.array([1, 1, 1, 1])
        c3 = np.dot(np.transpose(G), d3) % 2

        invalid_codeword = np.array([0, 1, 1, 0, 1, 1, 1])

        self.assertEqual(decoder._check_parity(c1), True)
        self.assertEqual(decoder._check_parity(c2), True)
        self.assertEqual(decoder._check_parity(c3), True)
        self.assertEqual(decoder._check_parity(invalid_codeword), False)


class GradientTestCase(unittest.TestCase):
    """Test case for the calculation of the gradient of the code-constraint-polynomial."""
    def test_grad_h(self):
        """Test the gradient of the code-constraint polynomial."""
        H = np.array([[1, 0, 0],
                      [0, 1, 0]])
        x = np.array([1, 2, 2])
        R = np.array([0])

        decoder = proximal.ProximalDecoder(H, R)
        grad = decoder._grad_h(x)

        expected = 4 * (x**2 - 1)*x + 2 / x * np.array([0, 2, 0])

        self.assertEqual(np.array_equal(grad, expected), True)

    def test_gen_A_B(self):
        """Test the generation of the A and B sets used for the gradient calculation."""
        # Hamming(7,4) code
        G = np.array([[1, 1, 1, 0, 0, 0, 0],
                      [1, 0, 0, 1, 1, 0, 0],
                      [0, 1, 0, 1, 0, 1, 0],
                      [1, 1, 0, 1, 0, 0, 1]])
        H = np.array([[1, 0, 1, 0, 1, 0, 1],
                      [0, 1, 1, 0, 0, 1, 1],
                      [0, 0, 0, 1, 1, 1, 1]])
        R = np.array([[0, 0, 1, 0, 0, 0, 0],
                      [0, 0, 0, 0, 1, 0, 0],
                      [0, 0, 0, 0, 0, 1, 0],
                      [0, 0, 0, 0, 0, 0, 1]])

        decoder = proximal.ProximalDecoder(H, R)

        expected_A = [np.array([0, 2, 4, 6]),
                      np.array([1, 2, 5, 6]),
                      np.array([3, 4, 5, 6])]
        expected_B = [np.array([0]),
                      np.array([1]),
                      np.array([0, 1]),
                      np.array([2]),
                      np.array([0, 2]),
                      np.array([1, 2]),
                      np.array([0, 1, 2])]

        for A_i, expected_A_i in zip(decoder._A, expected_A):
            self.assertEqual(np.array_equal(A_i, expected_A_i), True)

        for B_k, expected_B_k in zip(decoder._B, expected_B):
            self.assertEqual(np.array_equal(B_k, expected_B_k), True)


if __name__ == "__main__":
    unittest.main()