def test_symmetry_function():
# Check the consistency of abel.benchmark.is_symmetric
# checking all combination of odd and even images
for n, m in [(11, 11), (10, 10), (10, 12), (11, 12), (10, 13), (11, 13)]:
x = np.linspace(-np.pi, np.pi, n)
y = np.linspace(-np.pi, np.pi, m)
XX, YY = np.meshgrid(x, y)
f1 = np.cos(XX) * np.cos(YY)
assert_equal(
is_symmetric(f1, i_sym=True, j_sym=True), True,
'Checking f1 function for polar symmetry n={},m={}'.format(n, m))
f2 = np.cos(XX) * np.sin(YY)
assert_equal(
is_symmetric(f2, i_sym=True, j_sym=False), True,
'Checking f2 function for i symmetry n={},m={}'.format(n, m))
f3 = np.sin(XX) * np.cos(YY)
assert_equal(
is_symmetric(f3, i_sym=False, j_sym=True), True,
'Checking f3 function for j symmetry n={},m={}'.format(n, m))
assert_equal(
is_symmetric(f3, i_sym=True, j_sym=False), False,
'Checking that f3 function does not have i symmetry n={},m={}'.
format(n, m))
for n in [10, 11]:
x = np.linspace(-np.pi, np.pi, n)
f1 = np.cos(x)
assert_equal( is_symmetric(f1, i_sym=True, j_sym=False), True,\
'Checking f1 function for symmetry in 1D n={},m={}'.format(n,m))
def test_centering_function():
# ni -> original shape of the data is (ni, ni)
# n_c -> the image center is (n_c, n_c)
# n -> after the centering function, the array has a shape (n, n)
for (ni, n_c, n) in [
(9, 5, 3),
(9, 5, 4),
]:
arr = np.zeros((ni, ni))
if n % 2 == 1:
arr[n_c - 1:n_c + 2, n_c - 1:n_c + 2] = 1
else:
arr[n_c - 1:n_c + 1, n_c - 1:n_c + 1] = 1
res = center_image(arr, (n_c, n_c), n)
# The print statements below can be commented after we fix the centering issue
# print('Original array')
# print(arr)
# print('Centered array')
# print(res)
assert_equal( is_symmetric(res), True,\
'Validating the centering function for ni={}, n_c={}, n={}'.format(ni, n_c, n))
def test_symmetry_function():
# Check the consistency of abel.benchmark.is_symmetric
# checking all combination of odd and even images
for n, m in [(11, 11),
(10, 10),
(10, 12),
(11, 12),
(10, 13),
(11, 13)
]:
x = np.linspace(-np.pi, np.pi, n)
y = np.linspace(-np.pi, np.pi, m)
XX, YY = np.meshgrid(x, y)
f1 = np.cos(XX)*np.cos(YY)
assert_equal( is_symmetric(f1, i_sym=True, j_sym=True), True,
'Checking f1 function for polar symmetry n={},m={}'.format(n,m))
f2 = np.cos(XX)*np.sin(YY)
assert_equal( is_symmetric(f2, i_sym=True, j_sym=False), True,
'Checking f2 function for i symmetry n={},m={}'.format(n,m))
f3 = np.sin(XX)*np.cos(YY)
assert_equal( is_symmetric(f3, i_sym=False, j_sym=True), True,
'Checking f3 function for j symmetry n={},m={}'.format(n,m))
assert_equal( is_symmetric(f3, i_sym=True, j_sym=False), False,
'Checking that f3 function does not have i symmetry n={},m={}'.format(n,m))
for n in [10, 11]:
x = np.linspace(-np.pi, np.pi, n)
f1 = np.cos(x)
assert_equal( is_symmetric(f1, i_sym=True, j_sym=False), True,\
'Checking f1 function for symmetry in 1D n={},m={}'.format(n,m))
def test_centering_function():
# ni -> original shape of the data is (ni, ni)
# n_c -> the image origin is (n_c, n_c)
for (ni, n_c) in [(10, 5), (10, 5)]:
arr = np.zeros((ni, ni))
# arr[n_c-1:n_c+2,n_c-1:n_c+2] = 1
# # else:
arr[n_c - 1:n_c + 1, n_c - 1:n_c + 1] = 1.0
res = abel.tools.center.center_image(arr, (n_c, n_c), odd_size=False)
# The print statements below can be commented after we fix the centering issue
# print('Original array')
# print(arr)
# print('Centered array')
# print(res)
assert_equal( is_symmetric(res), True,\
'Validating the centering function for ni={}, n_c={}'.format(ni, n_c))
def test_centering_function():
# ni -> original shape of the data is (ni, ni)
# n_c -> the image center is (n_c, n_c)
for (ni, n_c) in [(10, 5),
(10, 5),
]:
arr = np.zeros((ni, ni))
# arr[n_c-1:n_c+2,n_c-1:n_c+2] = 1
# # else:
arr[n_c-1:n_c+1,n_c-1:n_c+1] = 1.0
res = abel.tools.center.center_image(arr, (n_c, n_c), odd_size=False)
# The print statements below can be commented after we fix the centering issue
# print('Original array')
# print(arr)
# print('Centered array')
# print(res)
assert_equal( is_symmetric(res), True,\
'Validating the centering function for ni={}, n_c={}'.format(ni, n_c))
def test_centering_function():
# ni -> original shape of the data is (ni, ni)
# n_c -> the image center is (n_c, n_c)
# n -> after the centering function, the array has a shape (n, n)
for (ni, n_c, n) in [(9, 5, 3),
(9, 5, 4),
]:
arr = np.zeros((ni, ni))
if n % 2 == 1:
arr[n_c-1:n_c+2,n_c-1:n_c+2] = 1
else:
arr[n_c-1:n_c+1,n_c-1:n_c+1] = 1
res = center_image(arr, (n_c, n_c), n)
# The print statements below can be commented after we fix the centering issue
# print('Original array')
# print(arr)
# print('Centered array')
# print(res)
assert_equal( is_symmetric(res), True,\
'Validating the centering function for ni={}, n_c={}, n={}'.format(ni, n_c, n))
