def passed_test(dtype, as_matrix, x_is_row, stride):
"""
Run one amax 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 = argmax(absolute(x))
else:
expected = -1
current_max = -1
for i in range(0, length, stride):
if abs(x_2[i, 0]) > current_max:
current_max = abs(x_2[i, 0])
expected = i / stride
# get the actual result
actual = amax(x, stride)
# compare the actual result to the expected result and return result of the test
return actual == expected
def test_stride_greater_than_length(self):
x = array([[1., 2., 3., 4.]])
self.assertEqual(amax(x, 5), 0) # 1 is at index 0
def test_float64_dtype(self):
x = array([[1., 2., 3.]], dtype='float64')
self.assertEqual(x.dtype, 'float64')
self.assertEqual(amax(x), 2)
def test_vector_as_matrix(self):
x = asmatrix(array([[1., 2., 3.]]))
self.assertEqual(amax(x), 2)
def test_stride_less_than_length(self):
x = array([[1., 2., 3., 4.]])
self.assertEqual(amax(x, 2), 1) # 3. is at index 1
def test_negative_element(self):
x = x = array([[5., -6.5, 3.]])
self.assertEqual(amax(x), 1)
def test_column_vector_as_ndarray(self):
x = array([[1.], [2.], [3.]])
self.assertEqual(amax(x), 2)
def test_last_element(self):
x = x = array([[5., 2., 10.]])
self.assertEqual(amax(x), 2)
def test_middle_element(self):
x = x = array([[5., 8., 3.]])
self.assertEqual(amax(x), 1)
def test_first_element(self):
x = x = array([[5., 2., 3.]])
self.assertEqual(amax(x), 0)
def test_row_vector_as_ndarray(self):
x = array([[1., 2., 3.]])
self.assertEqual(amax(x), 2)
def test_scalar_as_ndarray(self):
x = array([[1.]])
self.assertEqual(amax(x), 0)
