Source code for reproject.adaptive.high_level
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from ..utils import parse_input_data, parse_output_projection
from .core import _reproject_adaptive_2d
__all__ = ['reproject_adaptive']
ORDER = {}
ORDER['nearest-neighbor'] = 0
ORDER['bilinear'] = 1
[docs]def reproject_adaptive(input_data, output_projection, shape_out=None, hdu_in=0,
order='bilinear', return_footprint=True):
"""
Reproject celestial slices from an 2d array from one WCS to another using
the DeForest (2004) adaptive resampling algorithm.
Parameters
----------
input_data : str or `~astropy.io.fits.HDUList` or `~astropy.io.fits.PrimaryHDU` or `~astropy.io.fits.ImageHDU` or tuple
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
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.
order : int or str, optional
The order of the interpolation. This can be any of the
following strings:
* 'nearest-neighbor'
* 'bilinear'
or an integer. A value of ``0`` indicates nearest neighbor
interpolation.
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.
"""
# TODO: add support for output_array
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 isinstance(order, str):
order = ORDER[order]
return _reproject_adaptive_2d(array_in, wcs_in, wcs_out, shape_out,
order=order, return_footprint=return_footprint)