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")