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Return amplitude list to allow photometric comparison #12

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merged 2 commits into from
May 13, 2023
Merged

Return amplitude list to allow photometric comparison #12

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ac0caaf
return amplist
May 12, 2023
5b6f901
return amplist, test functions correction
May 12, 2023
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204 changes: 183 additions & 21 deletions notebooks/JWST_PSF_reconstruction.ipynb
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307 changes: 107 additions & 200 deletions notebooks/testing.ipynb
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6 changes: 3 additions & 3 deletions psfr/psfr.py
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Original file line number Diff line number Diff line change
Expand Up @@ -110,7 +110,7 @@ def stack_psf(star_list, oversampling=1, mask_list=None, error_map_list=None, sa
else:
mask_list_one_step = None
for j in range(num_iteration):
psf_guess = one_step_psf_estimate(star_list, psf_guess, center_list, mask_list_one_step,
psf_guess, amplitude_list = one_step_psf_estimate(star_list, psf_guess, center_list, mask_list_one_step,
error_map_list=error_map_list, oversampling=oversampling,
**kwargs_psf_stacking, **kwargs_one_step)
if j % n_recenter == 0 and j != 0:
Expand Down Expand Up @@ -145,7 +145,7 @@ def _updatefig(i):
anim.save(animation_options['output_dir'])
plt.close()

return psf_guess, center_list, mask_list
return psf_guess, center_list, mask_list, amplitude_list


def one_step_psf_estimate(star_list, psf_guess, center_list, mask_list=None, error_map_list=None, oversampling=1,
Expand Down Expand Up @@ -297,7 +297,7 @@ def one_step_psf_estimate(star_list, psf_guess, center_list, mask_list=None, err
amplitude_list=amplitude_list, error_map_list=error_map_list_psf,
**psf_stacking_options)
kernel_new = kernel_util.cut_psf(kernel_new, psf_size=len(psf_guess))
return kernel_new
return kernel_new, amplitude_list


def psf_error_map(star_list, psf_kernel, center_list, mask_list=None, error_map_list=None, oversampling=1):
Expand Down
2 changes: 1 addition & 1 deletion tests/test_Examples/test_JWST.py
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Expand Up @@ -25,7 +25,7 @@ def test_reconstruct_psf():
star = psfr.shift_psf(psf_center=kernel, oversampling=5, shift=[x_shift, y_shift], degrade=True, n_pix_star=kernel.shape[0]/oversampling)
star_list_webb.append(star)

psf_psfr_super, center_list_psfr_super, mask_list = psfr.stack_psf(star_list_webb, oversampling=oversampling,
psf_psfr_super, center_list_psfr_super, mask_list, amplitude_list = psfr.stack_psf(star_list_webb, oversampling=oversampling,
saturation_limit=None, num_iteration=10,
n_recenter=20)

Expand Down
2 changes: 1 addition & 1 deletion tests/test_Examples/test_gaussian.py
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Expand Up @@ -50,7 +50,7 @@ def stack_psf_guassian_high_res(oversampling, num_stars, kwargs_one_step, num_it
star = oversampled2regular(star, oversampling=oversampling_compute)
star_list.append(star)

psf_after, center_list_after, mask_list = stack_psf(star_list, oversampling=oversampling,
psf_after, center_list_after, mask_list,amplitude_list = stack_psf(star_list, oversampling=oversampling,
saturation_limit=None, num_iteration=num_iteration,
n_recenter=n_recenter, verbose=False, kwargs_one_step=kwargs_one_step)

Expand Down
14 changes: 7 additions & 7 deletions tests/test_psfr.py
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Original file line number Diff line number Diff line change
Expand Up @@ -163,7 +163,7 @@ def test_one_step_psf_estimation():
star = util.array2image(flux_model)
star_list.append(star)

psf_after = psfr.one_step_psf_estimate(star_list, psf_guess, center_list, mask_list=None, error_map_list=None,
psf_after, amplitude_list= psfr.one_step_psf_estimate(star_list, psf_guess, center_list, mask_list=None, error_map_list=None,
step_factor=0.2)
# psf_after should be a better guess of psf_true than psf_guess
diff_after = np.sum((psf_after - psf_true) ** 2)
Expand All @@ -184,14 +184,14 @@ def test_one_step_psf_estimation():
psf_true_super = util.array2image(flux_true_super)
psf_true_super /= np.sum(psf_true_super)

psf_after_super = psfr.one_step_psf_estimate(star_list, psf_guess_super, center_list, mask_list=None,
psf_after_super, amplitude_list = psfr.one_step_psf_estimate(star_list, psf_guess_super, center_list, mask_list=None,
error_map_list=None, step_factor=0.2, oversampling=oversampling)
diff_after = np.sum((psf_after_super - psf_true_super) ** 2)
diff_before = np.sum((psf_guess_super - psf_true_super) ** 2)
assert diff_after < diff_before

# de-shifting in oversampled space (should be a bit lower quality but still better than initial guess)
psf_after_super = psfr.one_step_psf_estimate(star_list, psf_guess_super, center_list, mask_list=None,
psf_after_super, amplitude_list = psfr.one_step_psf_estimate(star_list, psf_guess_super, center_list, mask_list=None,
error_map_list=None, step_factor=0.2, oversampling=oversampling,
oversampled_residual_deshifting=True)
diff_after = np.sum((psf_after_super - psf_true_super) ** 2)
Expand Down Expand Up @@ -226,14 +226,14 @@ def test_saturation_limit():
star_list_webb.append(star)

# psf reconstructed with a saturation limit
psf_psfr_super_sat, center_list_psfr_super_sat, mask_list_sat = psfr.stack_psf(star_list_webb,
psf_psfr_super_sat, center_list_psfr_super_sat, mask_list_sat, amplitude_list_sat = psfr.stack_psf(star_list_webb,
oversampling=oversampling,
saturation_limit=saturation_limit,
num_iteration=10,
n_recenter=20,
centroid_optimizer='Nelder-Mead')
# psf reconstructed without a saturation limit
psf_psfr_super, center_list_psfr_super, mask_list = psfr.stack_psf(star_list_webb, oversampling=oversampling,
psf_psfr_super, center_list_psfr_super, mask_list, amplitude_list_super = psfr.stack_psf(star_list_webb, oversampling=oversampling,
saturation_limit=None, num_iteration=10,
n_recenter=20)

Expand Down Expand Up @@ -269,12 +269,12 @@ def test_noisy_psf():
star_noisy = star + star_n1 + star_n2
star_list_webb_noisy.append(star_noisy)

psf_psfr_super_noisy, center_list_psfr_super_sat, mask_list_sat = psfr.stack_psf(star_list_webb_noisy,
psf_psfr_super_noisy, center_list_psfr_super_sat, mask_list_sat, amplitude_list_noisy = psfr.stack_psf(star_list_webb_noisy,
oversampling=oversampling,
saturation_limit=None,
num_iteration=10,
n_recenter=5)
psf_psfr_super, center_list_psfr_super_sat, mask_list_sat = psfr.stack_psf(star_list_webb,
psf_psfr_super, center_list_psfr_super_sat, mask_list_sat, amplitude_list = psfr.stack_psf(star_list_webb,
oversampling=oversampling,
saturation_limit=None, num_iteration=10,
n_recenter=20)
Expand Down