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import unittest

import numpy as np
from systemds.context import SystemDSContext

np.random.seed(7)
shape = np.random.randint(1, 100)
A = np.random.rand(shape, shape)
# set A = MM^T and A is a positive definite matrix
A = np.matmul(A, A.transpose())

class TestCholesky(unittest.TestCase):

    sds: SystemDSContext = None

    @classmethod
    def setUpClass(cls):
        cls.sds = SystemDSContext(11412)

    @classmethod
    def tearDownClass(cls):
        cls.sds.close()


class TestCholesky_0(TestCholesky):

    def test_basic1(self):
        L = self.sds.from_numpy(A).cholesky().compute()
        self.assertTrue(np.allclose(L, np.linalg.cholesky(A)))

    def test_basic2(self):
        L = self.sds.from_numpy(A).cholesky().compute()
        # L * L.H = A
        self.assertTrue(np.allclose(A, np.dot(L, L.T.conj())))

class TestCholesky_1(TestCholesky):
    def test_pos_def(self):
        m1 = -np.random.rand(shape, shape)
        with self.assertRaises(RuntimeError) as context:
            self.sds.from_numpy(m1).cholesky().compute()
            
class TestCholesky_2(TestCholesky):

    def test_symmetric_matrix(self):
        m2 = np.asarray([[4, 9], [1, 4]])
        np.linalg.cholesky(m2)
        with self.assertRaises(RuntimeError) as context:
            self.sds.from_numpy(m2).cholesky().compute()

class TestCholesky_3(TestCholesky):
    def test_asymetric_dim(self):
        m3 = np.random.rand(shape, shape + 1)
        with self.assertRaises(RuntimeError) as context:
            self.sds.from_numpy(m3).cholesky().compute()


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