Source code for reproject.spherical_intersect.high_level
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from ..utils import parse_input_data, parse_output_projection
from ..wcs_utils import has_celestial
from .core import _reproject_celestial
__all__ = ['reproject_exact']
[docs]
def reproject_exact(input_data, output_projection, shape_out=None, hdu_in=0,
parallel=False, return_footprint=True):
"""
Reproject data to a new projection using flux-conserving spherical
polygon intersection (this is the slowest algorithm).
Parameters
----------
input_data
The input data to reproject. This can be:
* The name of a FITS file
* An `~astropy.io.fits.HDUList` object
* An image HDU object such as a `~astropy.io.fits.PrimaryHDU`,
`~astropy.io.fits.ImageHDU`, or `~astropy.io.fits.CompImageHDU`
instance
* A tuple where the first element is a `~numpy.ndarray` and the
second element is either a `~astropy.wcs.WCS` or a
`~astropy.io.fits.Header` object
* An `~astropy.nddata.NDData` object from which the ``.data`` and
``.wcs`` attributes will be used as the input data.
output_projection : `~astropy.wcs.WCS` or `~astropy.io.fits.Header`
The output projection, which can be either a `~astropy.wcs.WCS`
or a `~astropy.io.fits.Header` instance.
shape_out : tuple, optional
If ``output_projection`` is a `~astropy.wcs.WCS` instance, the
shape of the output data should be specified separately.
hdu_in : int or str, optional
If ``input_data`` is a FITS file or an `~astropy.io.fits.HDUList`
instance, specifies the HDU to use.
parallel : bool or int
Flag for parallel implementation. If ``True``, a parallel implementation
is chosen, the number of processes selected automatically to be equal to
the number of logical CPUs detected on the machine. If ``False``, a
serial implementation is chosen. If the flag is a positive integer ``n``
greater than one, a parallel implementation using ``n`` processes is chosen.
return_footprint : bool
Whether to return the footprint in addition to the output array.
Returns
-------
array_new : `~numpy.ndarray`
The reprojected array
footprint : `~numpy.ndarray`
Footprint of the input array in the output array. Values of 0 indicate
no coverage or valid values in the input image, while values of 1
indicate valid values. Intermediate values indicate partial coverage.
"""
array_in, wcs_in = parse_input_data(input_data, hdu_in=hdu_in)
wcs_out, shape_out = parse_output_projection(output_projection, shape_out=shape_out)
if has_celestial(wcs_in) and wcs_in.pixel_n_dim == 2 and wcs_in.world_n_dim == 2:
return _reproject_celestial(array_in, wcs_in, wcs_out, shape_out=shape_out,
parallel=parallel, return_footprint=return_footprint)
else:
raise NotImplementedError("Currently only data with a 2-d celestial "
"WCS can be reprojected using flux-conserving algorithm")