Source code for gammapy.maps.hpx.core

# Licensed under a 3-clause BSD style license - see LICENSE.rst
import abc
import json
import numpy as np
from astropy.io import fits
from ..core import Map
from ..io import find_bands_hdu, find_bintable_hdu
from .geom import HpxGeom
from .io import HpxConv

__all__ = ["HpxMap"]


[docs]class HpxMap(Map): """Base class for HEALPIX map classes. Parameters ---------- geom : `~gammapy.maps.HpxGeom` HEALPix geometry object. data : `~numpy.ndarray` Data array. meta : `dict` Dictionary to store meta data. unit : `~astropy.units.Unit` The map unit """
[docs] @classmethod def create( cls, nside=None, binsz=None, nest=True, map_type="hpx", frame="icrs", data=None, skydir=None, width=None, dtype="float32", region=None, axes=None, meta=None, unit="", ): """Factory method to create an empty HEALPix map. Parameters ---------- nside : int or `~numpy.ndarray` HEALPix NSIDE parameter. This parameter sets the size of the spatial pixels in the map. binsz : float or `~numpy.ndarray` Approximate pixel size in degrees. An NSIDE will be chosen that corresponds to a pixel size closest to this value. This option is superseded by nside. nest : bool True for HEALPix "NESTED" indexing scheme, False for "RING" scheme. frame : {"icrs", "galactic"}, optional Coordinate system, either Galactic ("galactic") or Equatorial ("icrs"). skydir : tuple or `~astropy.coordinates.SkyCoord` Sky position of map center. Can be either a SkyCoord object or a tuple of longitude and latitude in deg in the coordinate system of the map. map_type : {'hpx', 'hpx-sparse'} Map type. Selects the class that will be used to instantiate the map. width : float Diameter of the map in degrees. If None then an all-sky geometry will be created. axes : list List of `~MapAxis` objects for each non-spatial dimension. meta : `dict` Dictionary to store meta data. unit : str or `~astropy.units.Unit` The map unit Returns ------- map : `~HpxMap` A HPX map object. """ from .ndmap import HpxNDMap hpx = HpxGeom.create( nside=nside, binsz=binsz, nest=nest, frame=frame, region=region, axes=axes, skydir=skydir, width=width, ) if cls.__name__ == "HpxNDMap": return HpxNDMap(hpx, dtype=dtype, meta=meta, unit=unit) elif map_type == "hpx": return HpxNDMap(hpx, dtype=dtype, meta=meta, unit=unit) else: raise ValueError(f"Unrecognized map type: {map_type!r}")
[docs] @classmethod def from_hdulist( cls, hdu_list, hdu=None, hdu_bands=None, format=None, colname=None ): """Make a HpxMap object from a FITS HDUList. Parameters ---------- hdu_list : `~astropy.io.fits.HDUList` HDU list containing HDUs for map data and bands. hdu : str Name or index of the HDU with the map data. If None then the method will try to load map data from the first BinTableHDU in the file. hdu_bands : str Name or index of the HDU with the BANDS table. format : str, optional FITS format convention. By default files will be written to the gamma-astro-data-formats (GADF) format. This option can be used to write files that are compliant with format conventions required by specific software (e.g. the Fermi Science Tools). The following formats are supported: - "gadf" (default) - "fgst-ccube" - "fgst-ltcube" - "fgst-bexpcube" - "fgst-srcmap" - "fgst-template" - "fgst-srcmap-sparse" - "galprop" - "galprop2" Returns ------- hpx_map : `HpxMap` Map object """ if hdu is None: hdu_out = find_bintable_hdu(hdu_list) else: hdu_out = hdu_list[hdu] if hdu_bands is None: hdu_bands = find_bands_hdu(hdu_list, hdu_out) hdu_bands_out = None if hdu_bands is not None: hdu_bands_out = hdu_list[hdu_bands] if format is None: format = HpxConv.identify_hpx_format(hdu_out.header) hpx_map = cls.from_hdu(hdu_out, hdu_bands_out, format=format, colname=colname) # exposure maps have an additional GTI hdu if format == "fgst-bexpcube" and "GTI" in hdu_list: hpx_map.unit = "cm2 s" return hpx_map
[docs] def to_hdulist(self, hdu="SKYMAP", hdu_bands=None, sparse=False, format="gadf"): """Convert to `~astropy.io.fits.HDUList`. Parameters ---------- hdu : str The HDU extension name. hdu_bands : str The HDU extension name for BANDS table. sparse : bool Set INDXSCHM to SPARSE and sparsify the map by only writing pixels with non-zero amplitude. format : str, optional FITS format convention. By default files will be written to the gamma-astro-data-formats (GADF) format. This option can be used to write files that are compliant with format conventions required by specific software (e.g. the Fermi Science Tools). The following formats are supported: - "gadf" (default) - "fgst-ccube" - "fgst-ltcube" - "fgst-bexpcube" - "fgst-srcmap" - "fgst-template" - "fgst-srcmap-sparse" - "galprop" - "galprop2" Returns ------- hdu_list : `~astropy.io.fits.HDUList` """ if hdu_bands is None: hdu_bands = f"{hdu.upper()}_BANDS" if self.geom.axes: hdu_bands_out = self.geom.to_bands_hdu(hdu_bands=hdu_bands, format=format) hdu_bands = hdu_bands_out.name else: hdu_bands_out = None hdu_bands = None hdu_out = self.to_hdu( hdu=hdu, hdu_bands=hdu_bands, sparse=sparse, format=format ) hdu_out.header["META"] = json.dumps(self.meta) hdu_out.header["BUNIT"] = self.unit.to_string("fits") hdu_list = fits.HDUList([fits.PrimaryHDU(), hdu_out]) if self.geom.axes: hdu_list.append(hdu_bands_out) return hdu_list
[docs] @abc.abstractmethod def to_wcs( self, sum_bands=False, normalize=True, proj="AIT", oversample=2, width_pix=None, hpx2wcs=None, ): """Make a WCS object and convert HEALPIX data into WCS projection. Parameters ---------- sum_bands : bool Sum over non-spatial axes before reprojecting. If False then the WCS map will have the same dimensionality as the HEALPix one. normalize : bool Preserve integral by splitting HEALPIX values between bins? proj : str WCS-projection oversample : float Oversampling factor for WCS map. This will be the approximate ratio of the width of a HPX pixel to a WCS pixel. If this parameter is None then the width will be set from ``width_pix``. width_pix : int Width of the WCS geometry in pixels. The pixel size will be set to the number of pixels satisfying ``oversample`` or ``width_pix`` whichever is smaller. If this parameter is None then the width will be set from ``oversample``. hpx2wcs : `~HpxToWcsMapping` Set the HPX to WCS mapping object that will be used to generate the WCS map. If none then a new mapping will be generated based on ``proj`` and ``oversample`` arguments. Returns ------- map_out : `~gammapy.maps.WcsMap` WCS map object. """ pass
[docs] @abc.abstractmethod def to_swapped(self): """Return a new map with the opposite scheme (ring or nested). Returns ------- map : `~HpxMap` Map object. """ pass
[docs] def to_hdu(self, hdu=None, hdu_bands=None, sparse=False, format=None): """Make a FITS HDU with input data. Parameters ---------- hdu : str The HDU extension name. hdu_bands : str The HDU extension name for BANDS table. sparse : bool Set INDXSCHM to SPARSE and sparsify the map by only writing pixels with non-zero amplitude. format : {'fgst-ccube', 'fgst-template', 'gadf', None}, optional FITS format convention. If None this will be set to the default convention of the map. Returns ------- hdu_out : `~astropy.io.fits.BinTableHDU` or `~astropy.io.fits.ImageHDU` Output HDU containing map data. """ hpxconv = HpxConv.create(format) hduname = hpxconv.hduname if hdu is None else hdu hduname_bands = hpxconv.bands_hdu if hdu_bands is None else hdu_bands header = self.geom.to_header(format=format) if self.geom.axes: header["BANDSHDU"] = hduname_bands if sparse: header["INDXSCHM"] = "SPARSE" cols = [] if header["INDXSCHM"] == "EXPLICIT": array = self.geom._ipix cols.append(fits.Column("PIX", "J", array=array)) elif header["INDXSCHM"] == "LOCAL": array = np.arange(self.data.shape[-1]) cols.append(fits.Column("PIX", "J", array=array)) cols += self._make_cols(header, hpxconv) return fits.BinTableHDU.from_columns(cols, header=header, name=hduname)