healpy.pixelfunc.reorder¶
- healpy.pixelfunc.reorder(map_in, inp=None, out=None, r2n=None, n2r=None)¶
Reorder a healpix map from RING/NESTED ordering to NESTED/RING
- Parameters:
- map_inarray-like
the input map to reorder, accepts masked arrays
- inp, out
'RING'
or'NESTED'
define the input and output ordering
- r2nbool
if True, reorder from RING to NESTED
- n2rbool
if True, reorder from NESTED to RING
- Returns:
- map_outarray-like
the reordered map, as masked array if the input was a masked array
Notes
if
r2n
orn2r
is defined, overrideinp
andout
.Examples
>>> import healpy as hp >>> hp.reorder(np.arange(48), r2n = True) array([13, 5, 4, 0, 15, 7, 6, 1, 17, 9, 8, 2, 19, 11, 10, 3, 28, 20, 27, 12, 30, 22, 21, 14, 32, 24, 23, 16, 34, 26, 25, 18, 44, 37, 36, 29, 45, 39, 38, 31, 46, 41, 40, 33, 47, 43, 42, 35]) >>> hp.reorder(np.arange(12), n2r = True) array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]) >>> hp.reorder(hp.ma(np.arange(12.)), n2r = True) masked_array(data = [ 0. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.], mask = False, fill_value = -1.6375e+30) >>> m = [np.arange(12.), np.arange(12.), np.arange(12.)] >>> m[0][2] = hp.UNSEEN >>> m[1][2] = hp.UNSEEN >>> m[2][2] = hp.UNSEEN >>> m = hp.ma(m) >>> hp.reorder(m, n2r = True) masked_array(data = [[0.0 1.0 -- 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0] [0.0 1.0 -- 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0] [0.0 1.0 -- 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0]], mask = [[False False True False False False False False False False False False] [False False True False False False False False False False False False] [False False True False False False False False False False False False]], fill_value = -1.6375e+30)