corrected docstrings
@@ -29,8 +29,7 @@ from scipy.ndimage import median_filter
from astropy.stats import sigma_clipped_stats
from multiprocessing import cpu_count
from ..stats import clip_array, sigma_filter
-from ..var import (frame_center, get_annulus_segments, frame_filter_lowpass,
- frame_filter_highpass)
+from ..var import frame_center, get_annulus_segments, frame_filter_lowpass
from ..config import timing, time_ini, Progressbar
from ..config.utils_conf import pool_map, iterable
from .rescaling import find_scal_vector, frame_rescaling
@@ -230,7 +229,6 @@ def cube_fix_badpix_isolated(array, bpm_mask=None, correct_only=False,
if bpm_mask is not None:
bpm_mask = bpm_mask.astype('bool')
-
if verbose:
start = time_ini()
@@ -607,8 +605,8 @@ def cube_fix_badpix_clump(array, bpm_mask=None, correct_only=False, cy=None,
----------
array : 3D or 2D array
Input 3d cube or 2d image.
- bpix_map: 3D or 2D array, opt
- Input bad pixel array. Should have same dimenstions as array. If not
+ bpm_mask: 3D or 2D array, opt
+ Input bad pixel array. Should have same dimensions as array. If not
provided, the algorithm will attempt to identify bad pixel clumps
automatically.
correct_only : bool, opt
@@ -679,7 +677,6 @@ def cube_fix_badpix_clump(array, bpm_mask=None, correct_only=False, cy=None,
msg = "Bad pixel map should be provided if correct_only is True."
raise ValueError(msg)
-
def bp_removal_2d(obj_tmp, cy, cx, fwhm, sig, protect_mask, bpm_mask_ori,
min_thr, half_res_y, mad, verbose):
n_x = obj_tmp.shape[1]
@@ -1071,8 +1068,8 @@ def cube_fix_badpix_interp(array, bpm_mask, mode='fft', fwhm=4., kernel_sz=None,
----------
array : 3D or 2D array
Input 3d cube or 2d image.
- bpix_map: 3D or 2D array
- Input bad pixel array. Should have same x,y dimenstions as array.
+ bpm_mask: 3D or 2D array
+ Input bad pixel array. Should have same x,y dimensions as array.
If 2D, but input array is 3D, the same bpix_map will be assumed for all
frames.
mode: str, optional {'fft', 'gauss', 'psf'}
@@ -1160,7 +1157,6 @@ def cube_fix_badpix_interp(array, bpm_mask, mode='fft', fwhm=4., kernel_sz=None,
obj_tmp = np.array(new_obj_tmp)
bpm_mask = np.array(new_bpm_mask)
-
if mode != 'fft':
# first replace all bad pixels with NaN values - they will be interpolated
obj_tmp[np.where(bpm_mask)] = np.nan
@@ -1751,7 +1747,6 @@ def get_err_spec(F_i, W, ind, npix, G_i, dims):
return G_i - conv/float(npix)
-
if not no_numba:
_err_spec_numba = njit(_err_spec)
return _err_spec_numba(F_i, W, ind, npix, G_i, dims)
