def test_fits_wcs(ra, dec, pa):
input_image = AstroImage(ra=ra, dec=dec, pa=pa, psf=False)
input_image.toFits('test_wcs.fits')
pc_11 = np.cos(np.radians(pa))
pc_12 = -np.sin(np.radians(pa))
pc_21 = np.sin(np.radians(pa))
pc_22 = np.cos(np.radians(pa))
pc_matrix = [[pc_11, pc_12], [pc_21, pc_22]]
with fits.open("test_wcs.fits") as input_file:
img_wcs = WCS(input_file[0].header)
assert np.isclose(img_wcs.wcs.crval[0], ra)
assert np.isclose(img_wcs.wcs.crval[1], dec)
assert np.isclose(img_wcs.wcs.pc[0][0], pc_matrix[0][0])
assert np.isclose(img_wcs.wcs.pc[0][1], pc_matrix[0][1])
assert np.isclose(img_wcs.wcs.pc[1][0], pc_matrix[1][0])
assert np.isclose(img_wcs.wcs.pc[1][1], pc_matrix[1][1])
assert np.isclose(input_file[0].header["CRVAL1"], ra)
assert np.isclose(input_file[0].header["CRVAL2"], dec)
assert np.isclose(input_file[0].header["PC1_1"], pc_matrix[0][0])
assert np.isclose(input_file[0].header["PC1_2"], pc_matrix[0][1])
assert np.isclose(input_file[0].header["PC2_1"], pc_matrix[1][0])
assert np.isclose(input_file[0].header["PC2_2"], pc_matrix[1][1])
os.remove("test_wcs.fits")
def test_DEC(coords, coord_types, ra, dec, new_dec, out_dec):
my_wcs = makeWCS(coords=coords, coord_types=coord_types)
image = AstroImage(wcs=my_wcs, psf=False)
assert image.ra == ra
assert image.dec == dec
image.dec = new_dec
assert image.dec == out_dec
def test_addHistory(history):
image = AstroImage(psf=False)
for item in history:
image.addHistory(item)
for item in history:
assert item in image.history
for item in image.history:
assert item in history
def test_PA(pa_in, pa, scale, new_pa, pa_out):
image = AstroImage(pa=pa_in, scale=scale, psf=False)
assert abs(image.pa - pa) < 1.e-4
assert abs(image.xscale - scale[0] * 3600) < 1.e-4
assert abs(image.yscale - scale[1] * 3600) < 1.e-4
image.pa = new_pa
assert abs(image.pa - pa_out) < 1.e-4
assert abs(image.xscale - scale[0] * 3600) < 1.e-4
assert abs(image.yscale - scale[1] * 3600) < 1.e-4
def test_bin(input, bin, result):
# If psf=True, then the image will create a default PSF, and pad its
# borders (and thus increase its size) sufficiently to include off-image
# regions of half the PSF width on each side. That will, in turn, result
# in the image sizes not matching the pre-made output arrays. Because this
# test is not related to PSFs in any way, no PSF is created.
im1 = AstroImage(data=input, psf=False)
im1.bin(bin[0], bin[1])
verifyData(im1.hdu.data, result)
def test_astro_image_rotation_full(data_base):
fits_path = os.path.join(data_base, "test", "wcs_test.fits")
# Test 90 degree rotation
ai = AstroImage.initFromFits(fits_path, psf=False)
default_wcs = ai._getWcs() # WCS(ai.hdu)
default_data = ai.hdu.data[:]
ai.rotate(90)
rotated_wcs = ai._getWcs() # WCS(ai.hdu)
rotated_data = ai.hdu.data[:]
arr_size_x = ai.hdu.shape[0]
arr_size_y = ai.hdu.shape[1]
for x in range(arr_size_x):
print("Starting Iteration {} of {}".format(x, arr_size_x))
for y in range(arr_size_y):
wcs_location = default_wcs.all_pix2world([[y, x]], 0)
default_value = default_data[y][x]
y, x = np.round(rotated_wcs.all_world2pix(wcs_location,
0)).astype(int)[0]
assert (0 <= x < arr_size_x)
assert (0 <= y < arr_size_y)
rotated_value = rotated_data[y][x]
if not np.isclose(default_value, rotated_value):
print("Failed Values: ", default_value, rotated_value)
assert np.isclose(default_value, rotated_value)
def test_astro_image_rotation_sample(data_base):
fits_path = os.path.join(data_base, "test", "wcs_test.fits")
# Test 90 degree rotation
ai = AstroImage.initFromFits(fits_path, psf=False)
default_wcs = ai._getWcs() # WCS(ai.hdu)
default_data = ai.hdu.data[:]
ai.rotate(90)
rotated_wcs = ai._getWcs() # WCS(ai.hdu)
rotated_data = ai.hdu.data[:]
arr_size_x = ai.hdu.shape[0]
arr_size_y = ai.hdu.shape[1]
random.seed()
coords = []
for x in range(1000):
coords.append(
(random.randrange(arr_size_x), random.randrange(arr_size_y)))
for x, y in coords:
wcs_location = default_wcs.all_pix2world([[y, x]], 0)
default_value = default_data[y][x]
y, x = np.round(rotated_wcs.all_world2pix(wcs_location,
0)).astype(int)[0]
assert (0 <= x < arr_size_x)
assert (0 <= y < arr_size_y)
rotated_value = rotated_data[y][x]
if not np.isclose(default_value, rotated_value):
print("Failed Values: ", default_value, rotated_value)
assert np.isclose(default_value, rotated_value)
def test_updateHeader(header_in, header_out):
image = AstroImage(psf=False)
for k, v in header_in:
image.updateHeader(k, v)
for k, v in header_out:
assert image.header[k] == v
def test_convolve(input, kernel, result):
input_image = AstroImage(data=input, psf=False)
kernel_image = AstroImage(data=kernel, psf=False)
input_image.convolve(kernel_image)
verifyData(input_image.hdu.data, result)
def new_empty_astro_image(data_base):
fits_path = os.path.join(data_base, "astro_image", "zero_image.fits")
print(fits_path)
return AstroImage.initFromFits(fits_path, psf=False)