def test_negative_alpha_with_vectors(self):
x = array([[-1., -2., 3.]])
y = array([[3., 2., 1.]])
expected = [[4.5, 5., -3.5]]
self.assertListEqual(axpy(-1.5, x, y).tolist(), expected)
self.assertListEqual(y.tolist(), expected)
def test_vectors_as_matrices(self):
x = asmatrix(array([[1., 2., 3.]]))
y = asmatrix(array([[3., 2., 1.]]))
expected = [[5., 6., 7.]]
self.assertListEqual(axpy(2, x, y).tolist(), expected)
self.assertListEqual(y.tolist(), expected)
def test_vectors_with_negatives_in_values(self):
x = array([[-1., -2., 3.]])
y = array([[3., 2., 1.]])
expected = [[1., -2., 7.]]
self.assertListEqual(axpy(2, x, y).tolist(), expected)
self.assertListEqual(y.tolist(), expected)
def test_alpha_equal_to_zero_with_vectors(self):
x = array([[-1., -2., 3.]])
y = array([[3., 2., 1.]])
expected = [[3., 2., 1.]]
self.assertListEqual(axpy(0, x, y).tolist(), expected)
self.assertListEqual(y.tolist(), expected)
def test_two_row_vectors_as_ndarrays(self):
x = array([[1., 2., 3.]])
y = array([[3., 2., 1.]])
expected = [[5., 6., 7.]]
self.assertListEqual(axpy(2, x, y).tolist(), expected)
self.assertListEqual(y.tolist(), expected)
def test_row_and_col_vectors_as_ndarrays(self):
x = array([[1., 2., 3.]])
y = array([[3.], [2.], [1.]])
expected = [[5.], [6.], [7.]]
self.assertListEqual(axpy(2, x, y).tolist(), expected)
self.assertListEqual(y.tolist(), expected)
def test_alpha_equal_to_zero_with_scalar(self):
x = array([[1.]])
y = array([[2.]])
expected = [[2.]]
self.assertListEqual(axpy(0, x, y).tolist(), expected)
self.assertListEqual(y.tolist(), expected)
def test_negative_alpha_with_scalar(self):
x = array([[1.]])
y = array([[2.]])
expected = [[1.]]
self.assertListEqual(axpy(-1, x, y).tolist(), expected)
self.assertListEqual(y.tolist(), expected)
def test_scalar_as_ndarray(self):
x = array([[1.]])
y = array([[2.]])
expected = [[3.]]
self.assertListEqual(axpy(1, x, y).tolist(), expected)
self.assertListEqual(y.tolist(), expected)
def test_unequal_strides(self):
x = array([[1., 2., 3., 4., 5., 6.]])
y = array([[3., 2., 1.]])
expected = [[5., 8., 11.]]
self.assertListEqual(axpy(2, x, y, inc_x=2, inc_y=1).tolist(), expected)
self.assertListEqual(y.tolist(), expected)
def test_strides_greater_than_length(self):
x = array([[1., 2., 3.]])
y = array([[3., 2., 1.]])
expected = [[5., 2., 1.]]
self.assertListEqual(axpy(2, x, y, inc_x=3, inc_y=3).tolist(), expected)
self.assertListEqual(y.tolist(), expected)
def passed_test(dtype, as_matrix, x_is_row, y_is_row, stride):
"""
Run one axpy operation test.
Arguments:
dtype: either 'float64' or 'float32', the NumPy dtype to test
as_matrix: True to test a NumPy matrix, False to test a NumPy ndarray
x_is_row: True to test a row vector as parameter x, False to test a column vector
y_is_row: True to test a row vector as parameter y, False to test a column vector
stride: stride of x and y to test; if None, a random stride is assigned
Returns:
True if the expected result is within the margin of error of the actual result,
False otherwise.
"""
# generate random sizes for vector dimensions and vector stride (if necessary)
length = randint(N_MIN, N_MAX)
stride = randint(N_MIN, STRIDE_MAX) if stride is None else stride
# create random scalar and vectors to test
alpha = uniform(SCAL_MIN, SCAL_MAX)
x = random_vector(length, x_is_row, dtype, as_matrix)
y = random_vector(length, y_is_row, dtype, as_matrix)
# create views of x and y that can be used to calculate the expected result
x_2 = x.T if x_is_row else x
y_2 = y.T if y_is_row else y
# compute the expected result
if stride == 1:
y_2 += alpha * x_2
else:
for i in range(0, length, stride):
y_2[i, 0] += alpha * x_2[i, 0]
# get the actual result
axpy(alpha, x, y, stride, stride)
# if y is a row vector, make y_2 a row vector as well
if y.shape[0] == 1:
y_2 = y_2.T
# compare the actual result to the expected result and return result of the test
return allclose(y, y_2, RTOL, ATOL)
def test_float64_dtype(self):
x = array([[1., 2., 3.]], dtype='float64')
y = array([[3., 2., 1.]], dtype='float64')
self.assertEqual(x.dtype, 'float64')
self.assertEqual(y.dtype, 'float64')
expected = [[5., 6., 7.]]
self.assertListEqual(axpy(2, x, y).tolist(), expected)
self.assertListEqual(y.tolist(), expected)
