def test_matrix_mul_matrix_invalid(self):
m1_data = [[1, 2, 3], [4, 5, 6]]
m2_data = [[6, 5, 4], [3, 2, 1]]
m1 = Matrix(data=m1_data, dtype=np.int32)
m2 = Matrix(data=m2_data, dtype=np.int32)
with self.assertRaises(ValueError):
m_prod = m1 * m2
def test_matrix_mul_matrix(self):
m1_data = [[1, 2, 3], [4, 5, 6]]
m2_data = [[10, 11], [20, 21], [30, 31]]
expected_data = [[140, 146], [320, 335]]
m1 = Matrix(data=m1_data, dtype=np.int32)
m2 = Matrix(data=m2_data, dtype=np.int32)
m_prod = m1 * m2
self.assertIsInstance(m_prod, Matrix)
self.assertEqual(m_prod.dtype, 'int32')
self.assertEqual(m_prod.shape, (2, 2))
self.assertTrue(np.array_equal(m_prod.data, np.array(expected_data)))
def test_matrix_sub(self):
data1 = [[3, 2], [4, -3], [2, 0]]
data2 = [[-4, 5], [1, -6], [0, 1]]
expected_data = [[7, -3], [3, 3], [2, -1]]
m1 = Matrix(data=data1)
m2 = Matrix(data=data2, dtype=np.int32)
matrix_sub = m1 - m2
self.assertIsInstance(matrix_sub, Matrix)
self.assertEqual(matrix_sub.shape, (3, 2))
self.assertEqual(matrix_sub.dtype, 'float32')
self.assertTrue(
np.array_equal(matrix_sub.data, np.array(expected_data)))
def test_matrix_add(self):
data1 = [[3, 2], [4, -3], [2, 0]]
data2 = [[-4, 5], [1, -6], [0, 1]]
expected_data = [[-1, 7], [5, -9], [2, 1]]
m1 = Matrix(data=data1, dtype=np.int32)
m2 = Matrix(data=data2)
matrix_add = m1 + m2
self.assertIsInstance(matrix_add, Matrix)
self.assertEqual(matrix_add.shape, (3, 2))
self.assertEqual(matrix_add.dtype, 'int32')
self.assertTrue(
np.array_equal(matrix_add.data, np.array(expected_data)))
def test_matrix_len(self):
m_data = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
m = Matrix(data=m_data, dtype=np.int32)
m_len = len(m)
self.assertEqual(m_len, len(m_data))
def test_matrix_initialize_dtype(self):
matrix = Matrix(dtype=np.int32)
self.assertIsInstance(matrix, Matrix)
self.assertEqual(matrix.shape, (2, 2))
self.assertEqual(matrix.dtype, 'int32')
self.assertTrue(np.array_equal(matrix.data, np.array([[0, 0], [0,
0]])))
def test_matrix_initialize_default(self):
matrix = Matrix()
self.assertIsInstance(matrix, Matrix)
self.assertEqual(matrix.shape, (2, 2))
self.assertEqual(matrix.dtype, 'float32')
self.assertTrue(
np.array_equal(matrix.data, np.array([[0.0, 0.0], [0.0, 0.0]])))
def test_matrix_mul_vector_invalid(self):
m_data = [[1, 2, 3], [4, 5, 6]]
v_data = [1, 2]
m = Matrix(data=m_data, dtype=np.int32)
v = Vector(data=v_data, dtype=np.int32)
with self.assertRaises(ValueError):
mv_prod = m * v
def test_matrix_index_column(self):
m_data = [[1, 2, 3], [4, 5, 6]]
expected_data = [2, 5]
m = Matrix(data=m_data, dtype=np.int32)
indexed_value = m[:, 1]
self.assertIsInstance(indexed_value, np.ndarray)
self.assertTrue(np.array_equal(indexed_value, np.array(expected_data)))
def test_matrix_mul_scalar(self):
scalar = 3
m_data = [[3, 4, 2], [2, -3, 0]]
expected_data = [[9, 12, 6], [6, -9, 0]]
matrix = Matrix(data=m_data, dtype=np.int32)
s_matrix = matrix * scalar
self.assertIsInstance(s_matrix, Matrix)
self.assertEqual(s_matrix.dtype, 'int32')
self.assertEqual(s_matrix.shape, (2, 3))
self.assertTrue(np.array_equal(s_matrix.data, np.array(expected_data)))
def test_matrix_mul_vector_2(self):
m_data = [[0.8, 0.6, 0.4], [0.2, 0.4, 0.6]]
v_data = [60, 50, 30]
expected_data = [90, 50]
matrix = Matrix(data=m_data)
vector = Vector(data=v_data, dtype=np.int32)
mv_prod = matrix * vector
self.assertIsInstance(mv_prod, Vector)
self.assertEqual(mv_prod.dtype, 'float32')
self.assertEqual(mv_prod.size, 2)
self.assertTrue(np.array_equal(mv_prod.data, np.array(expected_data)))
def test_matrix_mul_vector_1(self):
m_data = [[1, 2], [3, 4], [5, 6]]
v_data = [7, 8]
expected_data = [23, 53, 83]
matrix = Matrix(data=m_data, dtype=np.int32)
vector = Vector(data=v_data, dtype=np.int32)
mv_prod = matrix * vector
self.assertIsInstance(mv_prod, Vector)
self.assertEqual(mv_prod.dtype, 'int32')
self.assertEqual(mv_prod.size, 3)
self.assertTrue(np.array_equal(mv_prod.data, np.array(expected_data)))
self.assertTrue(np.array_equal(matrix.data, np.array(m_data)))
self.assertTrue(np.array_equal(vector.data, np.array(v_data)))
def test_matrix_sub_invalid(self):
m1 = Matrix(data=[[1, 2], [3, 4]])
m2 = Matrix(data=[[1, 2], [3, 4], [5, 6]])
with self.assertRaises(ValueError):
matrix_sub = m1 - m2
def test_matrix_minimum_cols(self):
with self.assertRaises(ValueError):
matrix = Matrix(rows=2, cols=1)
def test_matrix_iter(self):
m_data = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
m = Matrix(data=m_data, dtype=np.int32)
for i, item in enumerate(m):
self.assertTrue(np.array_equal(item, np.array(m_data[i])))
