Source code for reproject.healpix.high_level

from ..utils import parse_input_data, parse_output_projection
from ..wcs_utils import has_celestial
from .core import healpix_to_image, image_to_healpix
from .utils import parse_coord_system, parse_input_healpix_data

__all__ = ['reproject_from_healpix', 'reproject_to_healpix']


[docs]def reproject_from_healpix(input_data, output_projection, shape_out=None, hdu_in=1, order='bilinear', nested=None, field=0): """ Reproject data from a HEALPIX projection to a standard projection. Parameters ---------- input_data The input data to reproject. This can be: * The name of a HEALPIX FITS file * A `~astropy.io.fits.TableHDU` or `~astropy.io.fits.BinTableHDU` instance * A tuple where the first element is a `~numpy.ndarray` and the second element is a `~astropy.coordinates.BaseCoordinateFrame` instance or a string alias for a coordinate frame. 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, specifies the HDU to use. (the default HDU for HEALPIX data is 1, unlike with image files where it is generally 0) order : int or str, optional The order of the interpolation (if ``mode`` is set to ``'interpolation'``). This can be either one of the following strings: * 'nearest-neighbor' * 'bilinear' or an integer. A value of ``0`` indicates nearest neighbor interpolation. nested : bool, optional The order of the healpix_data, either nested (True) or ring (False). If a FITS file is passed in, this is determined from the header. field : int, optional The column to read from the HEALPIX FITS file. If the fits file is a partial-sky file, field=0 corresponds to the first column after the pixel index column. 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. """ array_in, coord_system_in, nested = parse_input_healpix_data(input_data, hdu_in=hdu_in, field=field, nested=nested) wcs_out, shape_out = parse_output_projection(output_projection, shape_out=shape_out) if nested is None: raise ValueError("Could not determine whether the data follows the " "'ring' or 'nested' ordering, so you should set " "nested=True or nested=False explicitly.") return healpix_to_image(array_in, coord_system_in, wcs_out, shape_out, order=order, nested=nested)
[docs]def reproject_to_healpix(input_data, coord_system_out, hdu_in=0, order='bilinear', nested=False, nside=128): """ Reproject data from a standard projection to a HEALPIX projection. 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` or `~astropy.io.fits.ImageHDU` 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 coord_system_out : `~astropy.coordinates.BaseCoordinateFrame` or str The output coordinate system for the HEALPIX projection 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 (if ``mode`` is set to ``'interpolation'``). This can be either one of the following strings: * 'nearest-neighbor' * 'bilinear' * 'biquadratic' * 'bicubic' or an integer. A value of ``0`` indicates nearest neighbor interpolation. nested : bool The order of the healpix_data, either nested (True) or ring (False) nside : int, optional The resolution of the HEALPIX projection. 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. """ array_in, wcs_in = parse_input_data(input_data, hdu_in=hdu_in) coord_system_out = parse_coord_system(coord_system_out) if (has_celestial(wcs_in) and wcs_in.low_level_wcs.pixel_n_dim == 2 and wcs_in.low_level_wcs.world_n_dim == 2): return image_to_healpix(array_in, wcs_in, coord_system_out, nside=nside, order=order, nested=nested) else: raise NotImplementedError("Only data with a 2-d celestial WCS can be " "reprojected to a HEALPIX projection")