Adapted pca_local function to be compatible with contrast curve function
@@ -150,7 +150,7 @@ def pca_annular(cube, angle_list, cube_ref=None, scale_list=None, radius_int=0,
``spat-mean``: spatial mean is subtracted.
``temp-standard``: temporal mean centering plus scaling pixel values
- to unit variance.
+ to unit variance. HIGHLY RECOMMENDED FOR ASDI AND RDI CASES.
``spat-standard``: spatial mean centering plus scaling pixel values
to unit variance.
@@ -376,11 +376,11 @@ def _pca_adi_rdi(cube, angle_list, radius_int=0, fwhm=4, asize=2, n_segments=1,
delta_rot = [delta_rot] * n_annuli
# forcing the 'temp-standard' scaling
- if cube_ref is not None:
- if not scaling == 'temp-standard':
- scaling = 'temp-standard'
- if verbose:
- print("Pixel-wise scaling set to `temp-standard`")
+# if cube_ref is not None:
+# if not scaling == 'temp-standard':
+# scaling = 'temp-standard'
+# if verbose:
+# print("Pixel-wise scaling set to `temp-standard`")
if isinstance(n_segments, int):
n_segments = [n_segments for _ in range(n_annuli)]
