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_saveable_dataset():
"""
Test the HCIDataset.save() and .load() methods
"""
# build HCIDataset
cube = np.zeros((5, 10, 10))
angles = np.linspace(1, 2, 5)
fwhm = 4 # test non-numpy type saving/loading
ds = HCIDataset(cube=cube, angles=angles, fwhm=fwhm)
# save
fd, fn = tempfile.mkstemp(prefix="vip_")
ds.save(fn)
# restore
ds2 = HCIDataset.load(fn)
# compare
aarc(ds2.cube, cube)
aarc(ds2.angles, angles)
assert ds2.fwhm == fwhm
# cleanup
os.remove(fn)
def test_fit2d(psf_model, fit_fkt, y, x, framesize, psfsize):
frame = np.zeros((framesize, framesize))
psf = create_synth_psf(psf_model, shape=(psfsize, psfsize))
inj_frame = put_center(frame, psf, y, x)
y_out, x_out = fit_fkt(inj_frame)
# correct "half-pixel centering", to make output of fit_2d* comparable
# with `put`.
if (
(framesize % 2 == 0 and psfsize % 2 == 0) or
(framesize % 2 == 1 and psfsize % 2 == 0)
):
y_exp = y - 0.5
x_exp = x - 0.5
else:
y_exp = y
x_exp = x
yx_real = np.unravel_index(inj_frame.argmax(), inj_frame.shape)
print("demanded injection: {}".format((y, x)))
print("brightes pixel: {}".format(yx_real))
print("fit should return: {}".format((y_exp, x_exp)))
print("fitted injection: {}".format((y_out, x_out)))
aarc((y_out, x_out), (y_exp, x_exp), atol=0.05)
def test_fit2d(psf_model, fit_fkt, y, x, framesize, psfsize):
frame = np.zeros((framesize, framesize))
psf = create_synth_psf(psf_model, shape=(psfsize, psfsize))
inj_frame = put_center(frame, psf, y, x)
y_out, x_out = fit_fkt(inj_frame)
# correct "half-pixel centering", to make output of fit_2d* comparable
# with `put`.
if ((framesize % 2 == 0 and psfsize % 2 == 0)
or (framesize % 2 == 1 and psfsize % 2 == 0)):
y_exp = y - 0.5
x_exp = x - 0.5
else:
y_exp = y
x_exp = x
yx_real = np.unravel_index(inj_frame.argmax(), inj_frame.shape)
print("demanded injection: {}".format((y, x)))
print("brightes pixel: {}".format(yx_real))
print("fit should return: {}".format((y_exp, x_exp)))
print("fitted injection: {}".format((y_out, x_out)))
aarc((y_out, x_out), (y_exp, x_exp), atol=0.05)
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
assert frame_center(np.zeros((5, 5))) == res55
# 3D
assert frame_center(np.zeros((frames, 4, 4))) == res44
assert frame_center(np.zeros((frames, 5, 5))) == res55
# 4D
assert frame_center(np.zeros((nlambda, frames, 4, 4))) == res44
assert frame_center(np.zeros((nlambda, frames, 5, 5))) == res55
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
assert frame_center(np.zeros((5, 5))) == res55
# 3D
assert frame_center(np.zeros((frames, 4, 4))) == res44
assert frame_center(np.zeros((frames, 5, 5))) == res55
# 4D
assert frame_center(np.zeros((nlambda, frames, 4, 4))) == res44
assert frame_center(np.zeros((nlambda, frames, 5, 5))) == res55
"""
Tests for preproc/rescaling.py
"""
from __future__ import division, print_function
__author__ = "Ralf Farkas"
from helpers import np, aarc, raises, parametrize
from vip_hci.preproc.rescaling import (cube_px_resampling, frame_px_resampling,
cube_rescaling_wavelengths,
check_scal_vector, _find_indices_sdi)
CUBE = np.ones((10, 100, 100))
FRAME = np.zeros((100, 100))
@parametrize("imlib", ["ndimage", "opencv"])
def test_cube_px_resampling(imlib):
# === enlargen ===
res = cube_px_resampling(CUBE, scale=2, imlib=imlib)
assert res.shape == (10, 200, 200)
# === shrink ===
res = cube_px_resampling(CUBE, scale=0.5, imlib=imlib)
assert res.shape == (10, 50, 50)
"""
from __future__ import division, print_function
__author__ = "Ralf Farkas"
from helpers import np, aarc, raises, parametrize
from vip_hci.preproc.rescaling import (cube_px_resampling,
frame_px_resampling,
cube_rescaling_wavelengths,
check_scal_vector,
_find_indices_sdi)
CUBE = np.ones((10, 100, 100))
FRAME = np.zeros((100, 100))
@parametrize("imlib", ["ndimage", "opencv"])
def test_cube_px_resampling(imlib):
# === enlargen ===
res = cube_px_resampling(CUBE, scale=2, imlib=imlib)
assert res.shape == (10, 200, 200)
# === shrink ===
res = cube_px_resampling(CUBE, scale=0.5, imlib=imlib)
assert res.shape == (10, 50, 50)