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

See also

nest2ring, ring2nest

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 = -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)