import unittest

import numpy as np

from inmoose.edgepy.makeCompressedMatrix import makeCompressedMatrix

class Test(unittest.TestCase):

    def test_makeCompressedMatrix(self):

        self.assertTrue(

            np.array_equal(

                makeCompressedMatrix(42, dims=(2, 3), byrow=True), np.full((2, 3), 42)

            )

        )

        self.assertTrue(

            np.array_equal(

                makeCompressedMatrix(42, dims=(2, 3), byrow=False), np.full((2, 3), 42)

            )

        )

        ref = np.array([[1, 2, 3] for i in range(2)])

        self.assertTrue(

            np.array_equal(

                makeCompressedMatrix([1, 2, 3], dims=(2, 3), byrow=True), ref

            )

        )

        self.assertTrue(

            np.array_equal(

                makeCompressedMatrix([1, 2, 3], dims=(3, 2), byrow=False), ref.T

            )

        )

        with self.assertRaisesRegex(

            ValueError, expected_regex="dims\[.\] should be equal to length of x"

        ):

            makeCompressedMatrix([1, 2, 3], dims=(3, 2), byrow=True)

        with self.assertRaisesRegex(

            ValueError, expected_regex="dims\[.\] should be equal to length of x"

        ):

            makeCompressedMatrix([1, 2, 3], dims=(2, 3), byrow=False)

        with self.assertRaisesRegex(

            ValueError, expected_regex="dims does not represent the shape of a matrix"

        ):

            makeCompressedMatrix(42, dims=(5,))

        with self.assertRaisesRegex(

            ValueError, expected_regex="dims does not represent the shape of a matrix"

        ):

            makeCompressedMatrix(42, dims=(1, 2, 3))

        with self.assertRaisesRegex(

            ValueError,

            expected_regex="input has too many dimensions to be interpreted as a matrix",

        ):

            makeCompressedMatrix(np.ones(shape=(1, 2, 3)), dims=(2, 3))

if __name__ == "__main__":

    unittest.main()