fixed VIP installation problems related to scikit-image, general improvements for recenter functions and docstrings , PEP8 imports

[IainHammond]

• VIP was facing installation difficulties with Python 3.9, 3.10 and 3.11 due to requiring a very old version of scikit-image (0.18.3). The limitation was due to a new parameter normalization being added to phase_cross_correlation, being set to true by default, which changed the resulting shifts. We now provide normalization=None to retain the original behaviour. _shift_dft also catches the case where the latest version of phase_cross_correlation (0.22) from scikit-image returns all three variables always rather than just the shifts (which the VIP code was originally designed around), and keeps the original behaviour of the _shift_dft function. The code is now compatible with versions 0.19-> of scikit-image , however I recommend 0.22 (latest release) due to the performance improvements
• in cube_recenter_speckles, the cube is only high pass filtered if the user requests it (by default it is), and I've moved each call of .copy() to numpy.copy() as it's safer and faster
• avoided a photutils import deprecation
• PEP8 a bunch of imports and removed some unused ones
• docstring fix in cube_recenter_dft_upsampling related to the center_fr1 parameter
• changed print statements to be consistent with "FITS"
• general typo fixes

[codecov-commenter]

Codecov Report

Merging #622 (fefd9cd) into master (12e61f3) will increase coverage by 1.57%.
The diff coverage is 76.09%.

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@@            Coverage Diff             @@
##           master     #622      +/-   ##
==========================================
+ Coverage   55.80%   57.37%   +1.57%     
==========================================
  Files          67       67              
  Lines       13549    13541       -8     
==========================================
+ Hits         7560     7768     +208     
+ Misses       5989     5773     -216     

Files	Coverage Δ
vip_hci/fits/fits.py	45.57% <ø> (ø)
vip_hci/fits/headers.py	35.71% <ø> (ø)
vip_hci/metrics/detection.py	63.56% <100.00%> (-0.32%)	⬇️
vip_hci/metrics/roc.py	9.01% <100.00%> (ø)
vip_hci/preproc/parangles.py	23.88% <ø> (ø)
vip_hci/var/shapes.py	70.00% <100.00%> (-0.11%)	⬇️
vip_hci/metrics/completeness.py	73.09% <88.89%> (ø)
vip_hci/stats/distances.py	28.95% <85.71%> (-0.11%)	⬇️
vip_hci/preproc/recentering.py	66.33% <60.87%> (-0.10%)	⬇️

... and 9 files with indirect coverage changes

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[VChristiaens]

Thanks @IainHammond !