def test_get_circle():
ar = np.ones((10, 10), dtype=int)
aarc(
get_circle(ar, radius=4),
np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0,
0], [0, 0, 0, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0,
0], [0, 1, 1, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 1,
0], [0, 1, 1, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 1,
0], [0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]))
aarc(
get_circle(PRETTY_ODD, radius=4, mode="val"),
np.array([
1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 2, 3, 2, 1, 1, 2, 2, 2, 1, 1, 1,
1, 1, 1
]))
aarc(
get_circle(PRETTY_EVEN, radius=4, mode="val"),
np.array([
1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 2, 3, 3, 2, 1, 1, 2, 3, 3,
2, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1
]))
def test_matrix_scaling():
"""
The "truth" values were verified by hand.
"""
m = np.array([[6, 12, 18], [0, 0, 12]], dtype=float)
res = matrix_scaling(m, None)
truth = m
aarc(res, truth)
res = matrix_scaling(m, "temp-mean")
truth = np.array([[ 3, 6, 3],
[-3, -6, -3]])
aarc(res, truth)
res = matrix_scaling(m, "spat-mean")
truth = np.array([[-6, 0, 6],
[-4, -4, 8]])
aarc(res, truth)
res = matrix_scaling(m, "temp-standard")
truth = np.array([[ 1, 1, 1],
[-1, -1, -1]])
aarc(res, truth)
res = matrix_scaling(m, "spat-standard")
truth = np.array([[-np.sqrt(3/2), 0, np.sqrt(3/2)],
[-np.sqrt(1/2), -np.sqrt(1/2), np.sqrt(2)]])
aarc(res, truth)
def test_matrix_scaling():
"""
The "truth" values were verified by hand.
"""
m = np.array([[6, 12, 18], [0, 0, 12]], dtype=float)
res = matrix_scaling(m, None)
truth = m
aarc(res, truth)
res = matrix_scaling(m, "temp-mean")
truth = np.array([[3, 6, 3], [-3, -6, -3]])
aarc(res, truth)
res = matrix_scaling(m, "spat-mean")
truth = np.array([[-6, 0, 6], [-4, -4, 8]])
aarc(res, truth)
res = matrix_scaling(m, "temp-standard")
truth = np.array([[1, 1, 1], [-1, -1, -1]])
aarc(res, truth)
res = matrix_scaling(m, "spat-standard")
truth = np.array([[-np.sqrt(3 / 2), 0, np.sqrt(3 / 2)],
[-np.sqrt(1 / 2), -np.sqrt(1 / 2),
np.sqrt(2)]])
aarc(res, truth)
def test_reshape_matrix():
vectorized_frames = np.array([[1, 1, 1, 2, 2, 2], [1, 2, 3, 4, 5, 6]])
cube = reshape_matrix(vectorized_frames, 2, 3)
assert cube.shape == (2, 2, 3) # 2 frames of 2x3
cube_truth = np.array([[[1, 1, 1], [2, 2, 2]], [[1, 2, 3], [4, 5, 6]]])
aarc(cube, cube_truth)
def test_reshape_matrix():
vectorized_frames = np.array([[1, 1, 1, 2, 2, 2], [1, 2, 3, 4, 5, 6]])
cube = reshape_matrix(vectorized_frames, 2, 3)
assert cube.shape == (2, 2, 3) # 2 frames of 2x3
cube_truth = np.array([[[1, 1, 1],
[2, 2, 2]],
[[1, 2, 3],
[4, 5, 6]]])
aarc(cube, cube_truth)
def test_check_scal_vector():
scal_vec = np.array([2, 8, 4])
# === basic function ===
res = check_scal_vector(scal_vec)
truth = np.array([4, 1, 2])
aarc(res, truth)
# === do nothing if min factor is already 1 ===
res2 = check_scal_vector(res)
aarc(res2, res)
# === wrong input value ===
with raises(TypeError):
check_scal_vector(42)
def test_check_scal_vector():
scal_vec = np.array([2, 8, 4])
# === basic function ===
res = check_scal_vector(scal_vec)
truth = np.array([4, 1, 2])
aarc(res, truth)
# === do nothing if min factor is already 1 ===
res2 = check_scal_vector(res)
aarc(res2, res)
# === wrong input value ===
with raises(TypeError):
check_scal_vector(42)
def test_get_square():
aarc(get_square(PRETTY_ODD, size=3, x=2, y=2),
np.array([[2, 2, 2],
[2, 3, 2],
[2, 2, 2]]))
aarc(get_square(PRETTY_ODD, size=2, x=2, y=2),
np.array([[2, 2, 2],
[2, 3, 2],
[2, 2, 2]]))
# -> prints warning
aarc(get_square(PRETTY_ODD, size=2, x=2, y=2, force=True),
np.array([[2, 2],
[2, 3]]))
aarc(get_square(PRETTY_EVEN, size=2, x=3, y=3),
np.array([[3, 3],
[3, 3]]))
aarc(get_square(PRETTY_EVEN, size=3, x=3, y=3),
np.array([[2, 2, 2, 2],
[2, 3, 3, 2],
[2, 3, 3, 2],
[2, 2, 2, 2]]))
# -> prints warning
aarc(get_square(PRETTY_EVEN, size=2, x=4, y=2, force=True),
np.array([[2, 2],
[3, 2]]))
def test_get_circle():
ar = np.ones((10, 10), dtype=int)
aarc(get_circle(ar, radius=4),
np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]))
aarc(get_circle(PRETTY_ODD, radius=4, mode="val"),
np.array([1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 2, 3, 2, 1, 1, 2, 2,
2, 1, 1, 1, 1, 1, 1]))
aarc(get_circle(PRETTY_EVEN, radius=4, mode="val"),
np.array([1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 2, 3, 3, 2, 1,
1, 2, 3, 3, 2, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1]))
def dataset(request):
"""
Create 3D and 4D datasets for use with ``test_cube_inject_companions``.
"""
if request.param == "3D":
cube = np.zeros((3, 5, 5))
psf = np.ones((1, 1))
elif request.param == "4D":
cube = np.zeros((2, 3, 5, 5)) # lambda, frames, width, height
psf = np.ones((2, 1, 1))
angles = np.array([0, 90, 180])
return cube, psf, angles
def dataset(request):
"""
Create 3D and 4D datasets for use with ``test_cube_inject_companions``.
"""
if request.param == "3D":
cube = np.zeros((3, 5, 5))
psf = np.ones((1, 1))
elif request.param == "4D":
cube = np.zeros((2, 3, 5, 5)) # lambda, frames, width, height
psf = np.ones((2, 1, 1))
angles = np.array([0, 90, 180])
return cube, psf, angles
def test_get_square():
aarc(get_square(PRETTY_ODD, size=3, x=2, y=2),
np.array([[2, 2, 2], [2, 3, 2], [2, 2, 2]]))
aarc(get_square(PRETTY_ODD, size=2, x=2, y=2),
np.array([[2, 2, 2], [2, 3, 2], [2, 2, 2]]))
# -> prints warning
aarc(get_square(PRETTY_ODD, size=2, x=2, y=2, force=True),
np.array([[2, 2], [2, 3]]))
aarc(get_square(PRETTY_EVEN, size=2, x=3, y=3), np.array([[3, 3], [3, 3]]))
aarc(get_square(PRETTY_EVEN, size=3, x=3, y=3),
np.array([[2, 2, 2, 2], [2, 3, 3, 2], [2, 3, 3, 2], [2, 2, 2, 2]]))
# -> prints warning
aarc(get_square(PRETTY_EVEN, size=2, x=4, y=2, force=True),
np.array([[2, 2], [3, 2]]))
def test_get_annulus_segments():
arr = np.ones((10, 10))
# single segment, like the old get_annulus. Note the ``[0]``.
res = get_annulus_segments(arr, 2, 3)[0]
truth = (np.array([0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3,
3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6,
6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 8, 8, 8, 9, 9,
9, 9]),
np.array([3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 0, 1,
2, 3, 6, 7, 8, 9, 0, 1, 2, 7, 8, 9, 0, 1, 2, 7, 8, 9, 0, 1, 2, 3,
6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 3, 4,
5, 6]))
aarc(res, truth)
res = get_annulus_segments(arr, 2, 3, mode="val")[0]
truth = np.array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.])
aarc(res, truth)
# multiple segments:
res = get_annulus_segments(PRETTY_EVEN, 2, 3, nsegm=2)
truth = [(np.array([0, 0, 0, 1, 1, 2, 3, 4, 4, 5, 5, 5]),
np.array([3, 4, 5, 4, 5, 5, 5, 4, 5, 3, 4, 5])),
(np.array([0, 0, 0, 1, 1, 2, 3, 4, 4, 5, 5, 5]),
np.array([0, 1, 2, 0, 1, 0, 0, 0, 1, 0, 1, 2]))]
aarc(res, truth)
res = get_annulus_segments(PRETTY_EVEN, 2, 3, nsegm=3)
truth = [(np.array([2, 3, 4, 4, 5, 5, 5]),
np.array([5, 5, 4, 5, 3, 4, 5])),
(np.array([0, 0, 0, 0, 0, 0, 1, 1, 1, 1]),
np.array([0, 1, 2, 3, 4, 5, 0, 1, 4, 5])),
(np.array([2, 3, 4, 4, 5, 5, 5]),
np.array([0, 0, 0, 1, 0, 1, 2]))]
assert repr(res) == repr(truth)
# TODO: cannot compare using `allclose`, as elements have variable length!
# tuple as input:
res = get_annulus_segments((6, 6), 2, 3, nsegm=3)
assert repr(res) == repr(truth)
# masked arr:
res = get_annulus_segments(arr, 2, 3, mode="mask")[0]
truth = np.array([[0., 0., 0., 1., 1., 1., 1., 0., 0., 0.],
[0., 1., 1., 1., 1., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 1., 1., 1., 1., 0.],
[1., 1., 1., 1., 0., 0., 1., 1., 1., 1.],
[1., 1., 1., 0., 0., 0., 0., 1., 1., 1.],
[1., 1., 1., 0., 0., 0., 0., 1., 1., 1.],
[1., 1., 1., 1., 0., 0., 1., 1., 1., 1.],
[0., 1., 1., 1., 1., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 1., 1., 1., 1., 0.],
[0., 0., 0., 1., 1., 1., 1., 0., 0., 0.]])
aarc(res, truth)
# tuple as input:
res = get_annulus_segments((10, 10), 2, 3, mode="mask")[0]
# masking a zeros array -> only zeros left!
assert res.sum() == 0
from __future__ import division, print_function, absolute_import
__author__ = "Ralf Farkas"
from helpers import aarc, np
from vip_hci.var.shapes import (frame_center, mask_circle, get_square,
get_circle, get_annulus_segments, dist,
matrix_scaling, reshape_matrix, get_ell_annulus,
get_ellipse)
PRETTY_ODD = np.array([
[1, 1, 1, 1, 1],
[1, 2, 2, 2, 1],
[1, 2, 3, 2, 1],
[1, 2, 2, 2, 1],
[1, 1, 1, 1, 1]
])
PRETTY_EVEN = np.array([
[1, 1, 1, 1, 1, 1],
[1, 2, 2, 2, 2, 1],
[1, 2, 3, 3, 2, 1],
[1, 2, 3, 3, 2, 1],
[1, 2, 2, 2, 2, 1],
[1, 1, 1, 1, 1, 1]
])
def test_frame_center():
def test_get_annulus_segments():
arr = np.ones((10, 10))
# single segment, like the old get_annulus. Note the ``[0]``.
res = get_annulus_segments(arr, 2, 3)[0]
truth = (np.array([
0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3,
3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6,
7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 8, 8, 8, 9, 9, 9, 9
]),
np.array([
3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 0,
1, 2, 3, 6, 7, 8, 9, 0, 1, 2, 7, 8, 9, 0, 1, 2, 7, 8, 9, 0, 1,
2, 3, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7,
8, 3, 4, 5, 6
]))
aarc(res, truth)
res = get_annulus_segments(arr, 2, 3, mode="val")[0]
truth = np.array([
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.
])
aarc(res, truth)
# multiple segments:
res = get_annulus_segments(PRETTY_EVEN, 2, 3, nsegm=2)
truth = [(np.array([0, 0, 0, 1, 1, 2, 3, 4, 4, 5, 5,
5]), np.array([3, 4, 5, 4, 5, 5, 5, 4, 5, 3, 4, 5])),
(np.array([0, 0, 0, 1, 1, 2, 3, 4, 4, 5, 5,
5]), np.array([0, 1, 2, 0, 1, 0, 0, 0, 1, 0, 1, 2]))]
aarc(res, truth)
res = get_annulus_segments(PRETTY_EVEN, 2, 3, nsegm=3)
truth = [(np.array([2, 3, 4, 4, 5, 5, 5]), np.array([5, 5, 4, 5, 3, 4,
5])),
(np.array([0, 0, 0, 0, 0, 0, 1, 1, 1,
1]), np.array([0, 1, 2, 3, 4, 5, 0, 1, 4, 5])),
(np.array([2, 3, 4, 4, 5, 5, 5]), np.array([0, 0, 0, 1, 0, 1,
2]))]
assert repr(res) == repr(truth)
# TODO: cannot compare using `allclose`, as elements have variable length!
# tuple as input:
res = get_annulus_segments((6, 6), 2, 3, nsegm=3)
assert repr(res) == repr(truth)
# masked arr:
res = get_annulus_segments(arr, 2, 3, mode="mask")[0]
truth = np.array([[0., 0., 0., 1., 1., 1., 1., 0., 0., 0.],
[0., 1., 1., 1., 1., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 1., 1., 1., 1., 0.],
[1., 1., 1., 1., 0., 0., 1., 1., 1., 1.],
[1., 1., 1., 0., 0., 0., 0., 1., 1., 1.],
[1., 1., 1., 0., 0., 0., 0., 1., 1., 1.],
[1., 1., 1., 1., 0., 0., 1., 1., 1., 1.],
[0., 1., 1., 1., 1., 1., 1., 1., 1., 0.],
[0., 1., 1., 1., 1., 1., 1., 1., 1., 0.],
[0., 0., 0., 1., 1., 1., 1., 0., 0., 0.]])
aarc(res, truth)
# tuple as input:
res = get_annulus_segments((10, 10), 2, 3, mode="mask")[0]
# masking a zeros array -> only zeros left!
assert res.sum() == 0
"""
Tests for var/shapes.py
"""
from __future__ import division, print_function, absolute_import
__author__ = "Ralf Farkas"
from helpers import aarc, np
from vip_hci.var.shapes import (frame_center, mask_circle, get_square,
get_circle, get_annulus_segments, dist,
matrix_scaling, reshape_matrix,
get_ell_annulus, get_ellipse)
PRETTY_ODD = np.array([[1, 1, 1, 1, 1], [1, 2, 2, 2, 1], [1, 2, 3, 2, 1],
[1, 2, 2, 2, 1], [1, 1, 1, 1, 1]])
PRETTY_EVEN = np.array([[1, 1, 1, 1, 1, 1], [1, 2, 2, 2, 2, 1],
[1, 2, 3, 3, 2, 1], [1, 2, 3, 3, 2, 1],
[1, 2, 2, 2, 2, 1], [1, 1, 1, 1, 1, 1]])
def test_frame_center():
frames = 39
nlambda = 2
res44 = (1.5, 1.5)
res55 = (2.0, 2.0)
# 2D
assert frame_center(np.zeros((4, 4))) == res44