def passed_test(dtype, as_matrix, x_is_row, stride):
    """
    Run 2-norm computation 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
        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 vector to test
    x = random_vector(length, x_is_row, dtype, as_matrix)

    # create view of x that can be used to calculate the expected result
    x_2 = x.T if x_is_row else x

    # compute the expected result
    if stride == 1:
        expected = norm(x)
    else:
        expected = 0
        for i in range(0, length, stride):
            expected += abs(x_2[i, 0]) ** 2
        expected **= 0.5

    # get the actual result
    actual = nrm2(x, stride)

    # compare the actual result to the expected result and return result of the test
    return abs(actual - expected) / expected < EPSILON
 def test_float64_dtype(self):
     x = array([[1., 2., 3., 3., 1., 1.]], dtype='float64')
     self.assertEqual(x.dtype, 'float64')
     self.assertEqual(nrm2(x), 5)
 def test_stride_greater_than_length(self):
     x = array([[1., -2., 3., 3., -1., 1.]])
     self.assertEqual(nrm2(x, inc_x=6), 1)
 def test_stride_less_than_length(self):
     x = array([[1., 2., 2., 3., 2., 1.]])
     self.assertEqual(nrm2(x, inc_x=2), 3)
 def test_vector_as_matrix(self):
     x = asmatrix(array([[1.], [2.], [3.], [3.], [1.], [1.]]))
     self.assertEqual(nrm2(x), 5)
 def test_column_vector_as_ndarray(self):
     x = array([[1.], [2.], [3.], [3.], [1.], [1.]])
     self.assertEqual(nrm2(x), 5)
 def test_negative_element(self):
     x = array([[1., -2., 3., 3., -1., 1.]])
     self.assertEqual(nrm2(x), 5)
 def test_row_vector_as_ndarray(self):
     x = array([[1., 2., 3., 3., 1., 1.]])
     self.assertEqual(nrm2(x), 5)
 def test_scalar_as_ndarray(self):
     x = array([[1.]])
     self.assertEqual(nrm2(x), 1)