Method take

numpy/ma/core.py:6066–6090

(self, indices, axis=None, out=None, mode='raise')

        return super().argpartition(*args, **kwargs)

    def take(self, indices, axis=None, out=None, mode='raise'):
        """
        """
        (_data, _mask) = (self._data, self._mask)
        cls = type(self)
        # Make sure the indices are not masked
        maskindices = getmask(indices)
        if maskindices is not nomask:
            indices = indices.filled(0)
        # Get the data, promoting scalars to 0d arrays with [...] so that
        # .view works correctly
        if out is None:
            out = _data.take(indices, axis=axis, mode=mode)[...].view(cls)
        else:
            np.take(_data, indices, axis=axis, mode=mode, out=out)
        # Get the mask
        if isinstance(out, MaskedArray):
            if _mask is nomask:
                outmask = maskindices
            else:
                outmask = _mask.take(indices, axis=axis, mode=mode)
                outmask |= maskindices
            out.__setmask__(outmask)
        # demote 0d arrays back to scalars, for consistency with ndarray.take
        return out[()]

    # Array methods
    copy = _arraymethod('copy')