continue refactor. Much worse than I thought

fix some typos

fix order

spectral_cube/cube_utils.py

@@ -157,51 +157,61 @@ def _orient(array, wcs):
  dimension.
  wcs : `~astropy.wcs.WCS`
  The input 3-d WCS with two position dimensions and one spectral
- dimension.
+ dimension. Any LowLevelWCS will be accepted, but only FITS WCSes
+ presently implement the reordering scheme used here.
  """
 
+ if isinstance(wcs, WCS):
+ if wcs.naxis != 3:
+ raise ValueError("Input WCS must be 3-dimensional")
+ wcs = wcs_utils.diagonal_wcs_to_cdelt(_fix_spectral(wcs))
+
+ from astropy.wcs.wcsapi import HighLevelWCSWrapper
+ wcs = HighLevelWCSWrapper(wcs)
+
  if array.ndim != 3:
  raise ValueError("Input array must be 3-dimensional")
 
- if wcs.wcs.naxis != 3:
+ if wcs.pixel_n_dim != 3:
  raise ValueError("Input WCS must be 3-dimensional")
 
- wcs = wcs_utils.diagonal_wcs_to_cdelt(_fix_spectral(wcs))
+ lowlev = wcs.low_level_wcs
 
- # reverse from wcs -> numpy convention
- axtypes = wcs.get_axis_types()[::-1]
-
- types = [a['coordinate_type'] for a in axtypes]
-
- n_celestial = types.count('celestial')
+ n_celestial = sum('celestial' == comp[0] for comp in lowlev.world_axis_object_components)
 
  if n_celestial == 0:
  raise ValueError('No celestial axes found in WCS')
  elif n_celestial != 2:
  raise ValueError('WCS should contain 2 celestial dimensions but '
  'contains {0}'.format(n_celestial))
 
- n_spectral = types.count('spectral')
+ n_spectral = sum('spectral' == comp[0] for comp in lowlev.world_axis_object_components)
 
  if n_spectral == 0:
  raise ValueError('No spectral axes found in WCS')
  elif n_spectral != 1:
  raise ValueError('WCS should contain one spectral dimension but '
  'contains {0}'.format(n_spectral))
 
- nums = [None if a['coordinate_type'] != 'celestial' else a['number']
- for a in axtypes]
-
- if 'stokes' in types:
+ subcomps = [comps[:2] for comps in lowlev.world_axis_object_components]
+ # WCS target order (celestial first, then spectral)
+ # This is the _reverse_ of numpy order
+ target_order = [
+ subcomps.index(('celestial', 0)),
+ subcomps.index(('celestial', 1)),
+ subcomps.index(('spectral', 0)),
+ ]
+ target_order_numpy = target_order[::-1]
+
+ if any('stokes' in tp for tp in lowlev.world_axis_object_components):
  raise ValueError("Input WCS should not contain stokes")
 
- t = [types.index('spectral'), nums.index(1), nums.index(0)]
- if t == [0, 1, 2]:
+ if target_order == [0, 1, 2]:
  result_array = array
  else:
- result_array = array.transpose(t)
+ result_array = array.transpose(target_order_numpy)
 
- result_wcs = wcs.sub([WCSSUB_LONGITUDE, WCSSUB_LATITUDE, WCSSUB_SPECTRAL])
+ result_wcs = lowlev.sub([WCSSUB_LONGITUDE, WCSSUB_LATITUDE, WCSSUB_SPECTRAL])
 
  return result_array, result_wcs
 

spectral_cube/spectral_cube.py

@@ -2670,16 +2670,16 @@ def reproject(self, header, order='bilinear', use_memmap=False,
  reproj_kwargs['independent_celestial_slices'] = True
 
  from reproject import reproject_interp
- from astropy.wcs.wcsapi import HighLevelWCS
+ from astropy.wcs.wcsapi import HighLevelWCSWrapper
 
  # TODO: Find the minimal subcube that contains the header and only reproject that
  # (see FITS_tools.regrid_cube for a guide on how to do this)
 
- if isinstance(header, HighLevelWCS):
+ if isinstance(header, HighLevelWCSWrapper):
  newwcs = header
  else:
  # try this; if it fails, the user should get the error
- newwcs = HighLevelWCS(wcs.WCS(header))
+ newwcs = HighLevelWCSWrapper(wcs.WCS(header))
 
  shape_out = newwcs.array_shape
  if shape_out is None: