Merge pull request #570 from VChristiaens/master

Bug fix for bad pixel correction by interpolation in 2D input frames + minor additions

README.rst

@@ -22,6 +22,12 @@ VIP - Vortex Image Processing package
 
 .. image:: https://codecov.io/gh/vortex-exoplanet/VIP/branch/master/graph/badge.svg?token=HydCFQqLRf
     :target: https://codecov.io/gh/vortex-exoplanet/VIP
+
+.. image:: https://joss.theoj.org/papers/10.21105/joss.04774/status.svg
+   :target: https://doi.org/10.21105/joss.04774
+
+.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.7499314.svg
+   :target: https://doi.org/10.5281/zenodo.7499314
 
 
 ::

tests/test_preproc_badpix.py

@@ -179,12 +179,14 @@ def test_badpix_ann():
 
     # test kernel correction
     cy, cx = frame_center(cube)
+    frame_c_gau = cube_fix_badpix_interp(cube[0], bpm[0], mode='gauss', fwhm=1)
     cube_c_gau = cube_fix_badpix_interp(cube, bpm, mode='gauss', fwhm=1)
     cube_c_fft = cube_fix_badpix_interp(cube, bpm, mode='fft', nit=50)
 
     r0 = dist(cy, cx, idx0, idx0)
     ann = get_annulus_segments(cube_c[0], r0-1, 3, mode='val')
     med_val_ann = np.median(ann)
+    assert (frame_c_gau[idx0, idx0]-med_val_ann) < 4*s0
     assert (cube_c_gau[0, idx0, idx0]-med_val_ann) < 4*s0
     assert (cube_c_fft[0, idx0, idx0]-med_val_ann) < 4*s0
 

vip_hci/preproc/badpixremoval.py

@@ -1170,11 +1170,13 @@ def squash_v(array):
         # first replace all bad pixels with NaNs - they will be interpolated
         array_corr[np.where(bpm_mask)] = np.nan
         if ndims == 2:
-            array_corr = frame_filter_lowpass(array_corr, mode=mode,
-                                                fwhm_size=fwhm, conv_mode='conv',
-                                                kernel_sz=kernel_sz, psf=psf,
-                                                iterate=True,
-                                                half_res_y=half_res_y, **kwargs)
+            array_corr_filt = frame_filter_lowpass(array_corr, mode=mode,
+                                                   fwhm_size=fwhm,
+                                                   conv_mode='conv',
+                                                   kernel_sz=kernel_sz, psf=psf,
+                                                   iterate=True,
+                                                   half_res_y=half_res_y,
+                                                   **kwargs)
         else:
             array_corr_filt = array_corr.copy()
             if np.isscalar(fwhm):
@@ -1188,14 +1190,15 @@ def squash_v(array):
             elif psf.shape[0] != nz:
                 raise ValueError("input psf must have same z dimension as array")
             for z in range(nz):
-                array_corr_filt[z] = frame_filter_lowpass(array_corr[z], mode=mode,
-                                                        fwhm_size=fwhm[z],
-                                                        conv_mode='conv',
-                                                        kernel_sz=kernel_sz,
-                                                        psf=psf[z],
-                                                        iterate=True,
-                                                        half_res_y=half_res_y,
-                                                        **kwargs)
+                array_corr_filt[z] = frame_filter_lowpass(array_corr[z],
+                                                          mode=mode,
+                                                          fwhm_size=fwhm[z],
+                                                          conv_mode='conv',
+                                                          kernel_sz=kernel_sz,
+                                                          psf=psf[z],
+                                                          iterate=True,
+                                                          half_res_y=half_res_y,
+                                                          **kwargs)
 
         # replace only the bad pixels (array_corr is low-pass filtered)
         array_corr[np.where(bpm_mask)] = array_corr_filt[np.where(bpm_mask)]
@@ -1214,8 +1217,8 @@ def squash_v(array):
             if nproc is None:
                 nproc = cpu_count()//2
             res = pool_map(nproc, frame_fix_badpix_fft, iterable(array_corr),
-                           iterable(bpm_mask), nit, tol, 2, False,
-                           full_output, msg="Correcting bad pixels")
+                           iterable(bpm_mask), nit, tol, 2, False, full_output,
+                           msg="Correcting bad pixels")
             if full_output and isinstance(nit, int):
                 array_corr = np.array(res[:, 0], dtype=np.float64)
                 recon_cube = np.array(res[:, 1], dtype=np.float64)