healpy.pixelfunc.reorder¶
- healpy.pixelfunc.reorder(*args, **kwds)¶
Reorder an healpix map from RING/NESTED ordering to NESTED/RING
Parameters: map_in : array-like
the input map to reorder, accepts masked arrays
inp, out : 'RING' or 'NESTED'
define the input and output ordering
r2n : bool
if True, reorder from RING to NESTED
n2r : bool
if True, reorder from NESTED to RING
Returns: map_out : array-like
the reordered map, as masked array if the input was a masked array
Notes
if r2n or n2r is defined, override inp and out.
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 = 999999) >>> m = [range(12), range(12), range(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], mask = [False False True False False False False False False False False False], fill_value = -1.6375e+30) , 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], mask = [False False True False False False False False False False False False], fill_value = -1.6375e+30) , 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], mask = [False False True False False False False False False False False False], fill_value = -1.6375e+30) )