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from csst_cpic_sim.target import star_photlam
from csst_cpic_sim.optics import make_focus_image, focal_mask, filter_throughput, ideal_focus_image
from csst_cpic_sim.config import which_focalplane, S
from astropy.io import fits
def gaussian_psf(band, spectrum, shape, error=0.1):
psf_shape = [shape, shape]
xx, yy = np.mgrid[0:psf_shape[0], 0:psf_shape[1]]
center = np.array([(psf_shape[0]-1)/2, (psf_shape[1]-1)/2])
sigma = 10
psf = np.exp(-((xx-center[0])**2 +
(yy-center[1])**2) / (2*sigma**2))
psf = psf / psf.sum()
filter = filter_throughput(band)
return psf * (spectrum * filter).integrate()
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class TestOptics(unittest.TestCase):
def test_filter_throughtput(self):
bandpass = filter_throughput('f661')
self.assertIsInstance(bandpass, S.spectrum.SpectralElement)
bandpass = filter_throughput('F1265')
self.assertIsInstance(bandpass, S.spectrum.SpectralElement)
bandpass = filter_throughput('deFault')
self.assertIsInstance(bandpass, S.spectrum.SpectralElement)
bandpass = filter_throughput('none')
self.assertIsInstance(bandpass, S.spectrum.SpectralElement)
def test_which_focalpalne(self):
self.assertEqual(which_focalplane('f565'), 'vis')
self.assertEqual(which_focalplane('F661'), 'vis')
self.assertEqual(which_focalplane('f743'), 'vis')
self.assertEqual(which_focalplane('f883'), 'vis')
self.assertEqual(which_focalplane('F940'), 'nir')
self.assertEqual(which_focalplane('f1265'), 'nir')
self.assertEqual(which_focalplane('F1425'), 'nir')
self.assertEqual(which_focalplane('f1542'), 'nir')
self.assertEqual(which_focalplane('wfs'), 'wfs')
self.assertRaises(ValueError, which_focalplane, 'what')
def test_make_focus_image(self):
# test fuction to generate psf
# test targets
cstar = star_photlam(0, 'F2V', is_blackbody=True)
targets = [
[0, 0, cstar],
[1, 1, star_photlam(10-5, 'B2V', is_blackbody=True)],
[-2, 2, star_photlam(11-5, 'A2V', is_blackbody=True)],
[3, -3, star_photlam(12-5, 'G2V', is_blackbody=True)],
[100, 100, star_photlam(12, 'K2V', is_blackbody=True)],
[100, 100, star_photlam(12, 'K2V', is_blackbody=True)],
]
focus_image = make_focus_image(
'f661',
targets,
gaussian_psf,
init_shifts=[1, 1],
rotation=45,
platesize=[1024, 1024]
)
self.assertIsNotNone(focus_image)
focus_image = make_focus_image(
'f661',
[],
gaussian_psf,
init_shifts=[1, 1],
rotation=45,
platesize=[1024, 1024]
)
self.assertIsNotNone(focus_image)
def test_focal_mask(self):
image = np.zeros((100, 100)) + 1
image_out = focal_mask(image, 1, 0.1, throughtput=0)
self.assertEqual((image - image_out).sum(), 2000+2000-400)
if __name__ == '__main__':
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# unittest.main()
import time
from CpicImgSim.target import star_photlam
def make_test_sub_image(size, shape):
shape = np.array([shape, shape])
sub_image = np.zeros(shape)
center = (shape-1)/2
xx, yy = np.meshgrid(np.arange(shape[0]), np.arange(shape[1]))
xx = xx - center[1]
yy = yy - center[0]
sub_image[np.abs(xx) < 0.6] = 1
sub_image[np.abs(yy) < 0.6] = 1
sub_image[(np.abs(xx) < 0.6) & (np.abs(yy) < 0.6)] = 0
sub_image[yy > 7] = 0
sub_image[yy < -3] = 0
sub_image[np.abs(xx) > 3] = 0
sub_image2 = (np.sqrt(xx**2*2 + yy**2) < size).astype(int)
sub_image = sub_image2 * (1 - sub_image)
return sub_image
def test_ideal_focus_image():
targets = [
[0, 0, star_photlam(2, 'G2'), None],
[5, 3, star_photlam(0, 'G2'), make_test_sub_image(4, 20)],
[8, 0, star_photlam(-5, 'G2'), make_test_sub_image(10, 100)],
]
bandpass = S.Box(6000, 500)
start_time = time.time()
foc = ideal_focus_image(
bandpass,
targets,
0.0165,
[1024, 1024],
)
end_time = time.time()
execution_time = end_time - start_time
fits.writeto('foc.fits', foc, overwrite=True)
start_time = time.time()
foc = ideal_focus_image(
bandpass,
targets,
0.0165,
[1024, 1024],
rotation=30,
)
end_time = time.time()
execution_time = end_time - start_time
fits.writeto('foc_rot30.fits', foc, overwrite=True)
def test_convolve_psf():
targets = [
[0, 0, star_photlam(2, 'G2'), None],
[5, 3, star_photlam(0, 'G2'), make_test_sub_image(4, 20)],
[8, 0, star_photlam(-5, 'G2'), make_test_sub_image(10, 100)],
]
def cov_psf_func(wave, error=0.1):
psf_shape = [1024, 1024]
xx, yy = np.mgrid[0:psf_shape[0], 0:psf_shape[1]]
center = np.array([(psf_shape[0]-1)/2, (psf_shape[1]-1)/2])
sigma = 10
psf = np.exp(-((xx-center[0])**2 +
(yy-center[1])**2) / (2*sigma**2))
psf = psf / psf.sum()
return psf
from CpicImgSim.optics import focal_convolve
img_final = focal_convolve('f661', targets, cov_psf_func)