healpy.pixelfunc.reorder¶

healpy.pixelfunc.reorder(map_in, *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

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],
             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)
)