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
import astropy.units as u
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 metadata. 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`, optional HEALPix NSIDE parameter. This parameter sets the size of the spatial pixels in the map. Default is None. binsz : float or `~numpy.ndarray`, optional 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 This option is superseded by ``nside``. Default is None. nest : bool, optional Indexing scheme. If True, "NESTED" scheme. If False, "RING" scheme. Default is True. map_type : {'hpx', 'hpx-sparse'}, optional Map type. Selects the class that will be used to instantiate the map. Default is "hpx". frame : {"icrs", "galactic"} Coordinate system, either Galactic ("galactic") or Equatorial ("icrs"). Default is "icrs". data : `~numpy.ndarray`, optional Data array. Default is None. skydir : tuple or `~astropy.coordinates.SkyCoord`, optional 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. Default is None. width : float, optional Diameter of the map in degrees. If None then an all-sky geometry will be created. Default is None. dtype : str, optional Data type. Default is "float32". region : str, optional HEALPix region string. Default is None. axes : list, optional List of `~MapAxis` objects for each non-spatial dimension. Default is None. meta : `dict`, optional Dictionary to store the metadata. Default is None. unit : str or `~astropy.units.Unit`, optional The map unit. Default is "". Returns ------- map : `~HpxMap` A HEALPix 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, optional 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. Default is None. hdu_bands : str, optional Name or index of the HDU with the BANDS table. Default is None. 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 = u.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, optional The HDU extension name. Default is "SKYMAP". hdu_bands : str, optional The HDU extension name for BANDS table. Default is None. sparse : bool, optional Set INDXSCHM to SPARSE and sparsify the map by only writing pixels with non-zero amplitude. Default is False. 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` The 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, optional Sum over non-spatial axes before reprojecting. If False then the WCS map will have the same dimensionality as the HEALPix one. Default is False. normalize : bool, optional Preserve integral by splitting HEALPix values between bins. Default is True. proj : str, optional WCS-projection. Default is "AIT". oversample : float, optional Oversampling factor for WCS map. This will be the approximate ratio of the width of a HEALPix pixel to a WCS pixel. If this parameter is None then the width will be set from ``width_pix``. Default is 2. width_pix : int, optional 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``. Default is None. hpx2wcs : `~HpxToWcsMapping`, optional Set the HEALPix 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. Default is None. 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, optional The HDU extension name. Default is None. hdu_bands : str, optional The HDU extension name for BANDS table. Default is None. sparse : bool, optional Set INDXSCHM to SPARSE and sparsify the map by only writing pixels with non-zero amplitude. Default is False. format : {None, 'fgst-ccube', 'fgst-template', 'gadf'} FITS format convention. If None this will be set to the default convention of the map. Default is None. 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)