healpy.pixelfunc.ma(m, badval=-1.6375e+30, rtol=1e-05, atol=1e-08, copy=True)

Return map as a masked array, with badval pixels masked.


m : a map (may be a sequence of maps)

badval : float, optional

The value of the pixel considered as bad (UNSEEN by default)

rtol : float, optional

The relative tolerance

atol : float, optional

The absolute tolerance

copy : bool, optional

If True, a copy of the input map is made.


a masked array with the same shape as the input map,

masked where input map is close to badval.

See also

mask_good, mask_bad, numpy.ma.masked_values


>>> import healpy as hp
>>> m = np.arange(12.)
>>> m[3] = hp.UNSEEN
>>> hp.ma(m)
masked_array(data = [0.0 1.0 2.0 -- 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0],
             mask = [False False False  True False False False False False False False False],
       fill_value = -1.6375e+30)