def from_hdu(cls, hdu, hdu_bands=None):
"""Make a WcsNDMap object from a FITS HDU.
Parameters
----------
hdu : `~astropy.io.fits.BinTableHDU` or `~astropy.io.fits.ImageHDU`
The map FITS HDU.
hdu_bands : `~astropy.io.fits.BinTableHDU`
The BANDS table HDU.
"""
geom = WcsGeom.from_header(hdu.header, hdu_bands)
shape = tuple([ax.nbin for ax in geom.axes])
shape_wcs = tuple([np.max(geom.npix[0]), np.max(geom.npix[1])])
meta = cls._get_meta_from_header(hdu.header)
unit = unit_from_fits_image_hdu(hdu.header)
map_out = cls(geom, meta=meta, unit=unit)
# TODO: Should we support extracting slices?
if isinstance(hdu, fits.BinTableHDU):
pix = hdu.data.field("PIX")
pix = np.unravel_index(pix, shape_wcs[::-1])
vals = hdu.data.field("VALUE")
if "CHANNEL" in hdu.data.columns.names and shape:
chan = hdu.data.field("CHANNEL")
chan = np.unravel_index(chan, shape[::-1])
idx = chan + pix
else:
idx = pix
map_out.set_by_idx(idx[::-1], vals)
else:
map_out.data = hdu.data
return map_out
def from_hdu(cls, hdu, hdu_bands=None):
"""Make a HpxNDMap object from a FITS HDU.
Parameters
----------
hdu : `~astropy.io.fits.BinTableHDU`
The FITS HDU
hdu_bands : `~astropy.io.fits.BinTableHDU`
The BANDS table HDU
"""
hpx = HpxGeom.from_header(hdu.header, hdu_bands)
convname = HpxGeom.identify_hpx_convention(hdu.header)
hpx_conv = HPX_FITS_CONVENTIONS[convname]
shape = tuple([ax.nbin for ax in hpx.axes[::-1]])
# shape_data = shape + tuple([np.max(hpx.npix)])
# TODO: Should we support extracting slices?
meta = cls._get_meta_from_header(hdu.header)
unit = unit_from_fits_image_hdu(hdu.header)
map_out = cls(hpx, None, meta=meta, unit=unit)
colnames = hdu.columns.names
cnames = []
if hdu.header.get("INDXSCHM", None) == "SPARSE":
pix = hdu.data.field("PIX")
vals = hdu.data.field("VALUE")
if "CHANNEL" in hdu.data.columns.names:
chan = hdu.data.field("CHANNEL")
chan = np.unravel_index(chan, shape)
idx = chan + (pix, )
else:
idx = (pix, )
map_out.set_by_idx(idx[::-1], vals)
else:
for c in colnames:
if c.find(hpx_conv.colstring) == 0:
cnames.append(c)
nbin = len(cnames)
if nbin == 1:
map_out.data = hdu.data.field(cnames[0])
else:
for i, cname in enumerate(cnames):
idx = np.unravel_index(i, shape)
map_out.data[idx + (slice(None), )] = hdu.data.field(cname)
return map_out
def from_hdu(cls, hdu, hdu_bands=None, format=None):
"""Make a WcsNDMap object from a FITS HDU.
Parameters
----------
hdu : `~astropy.io.fits.BinTableHDU` or `~astropy.io.fits.ImageHDU`
The map FITS HDU.
hdu_bands : `~astropy.io.fits.BinTableHDU`
The BANDS table HDU.
format : {'gadf', 'fgst-ccube','fgst-template'}
FITS format convention.
Returns
-------
map : `WcsNDMap`
Wcs map
"""
geom = WcsGeom.from_header(hdu.header, hdu_bands, format=format)
shape = geom.axes.shape
shape_wcs = tuple([np.max(geom.npix[0]), np.max(geom.npix[1])])
meta = cls._get_meta_from_header(hdu.header)
unit = unit_from_fits_image_hdu(hdu.header)
# TODO: Should we support extracting slices?
if isinstance(hdu, fits.BinTableHDU):
map_out = cls(geom, meta=meta, unit=unit)
pix = hdu.data.field("PIX")
pix = np.unravel_index(pix, shape_wcs[::-1])
vals = hdu.data.field("VALUE")
if "CHANNEL" in hdu.data.columns.names and shape:
chan = hdu.data.field("CHANNEL")
chan = np.unravel_index(chan, shape[::-1])
idx = chan + pix
else:
idx = pix
map_out.set_by_idx(idx[::-1], vals)
else:
if any(x in hdu.name.lower()
for x in ["mask", "is_ul", "success"]):
data = hdu.data.astype(bool)
else:
data = hdu.data
map_out = cls(geom=geom, meta=meta, data=data, unit=unit)
return map_out
def from_hdu(cls, hdu, hdu_bands=None, format=None, colname=None):
"""Make a HpxNDMap object from a FITS HDU.
Parameters
----------
hdu : `~astropy.io.fits.BinTableHDU`
The FITS HDU
hdu_bands : `~astropy.io.fits.BinTableHDU`
The BANDS table HDU
format : str, optional
FITS convention. If None the format is guessed. The following
formats are supported:
- "gadf"
- "fgst-ccube"
- "fgst-ltcube"
- "fgst-bexpcube"
- "fgst-srcmap"
- "fgst-template"
- "fgst-srcmap-sparse"
- "galprop"
- "galprop2"
colname : str, optional
Data column name to be used for the HEALPix map.
Returns
-------
map : `HpxMap`
HEALPix map
"""
if format is None:
format = HpxConv.identify_hpx_format(hdu.header)
geom = HpxGeom.from_header(hdu.header, hdu_bands, format=format)
hpx_conv = HPX_FITS_CONVENTIONS[format]
shape = geom.axes.shape[::-1]
# TODO: Should we support extracting slices?
meta = cls._get_meta_from_header(hdu.header)
unit = unit_from_fits_image_hdu(hdu.header)
map_out = cls(geom, None, meta=meta, unit=unit)
colnames = hdu.columns.names
cnames = []
if hdu.header.get("INDXSCHM", None) == "SPARSE":
pix = hdu.data.field("PIX")
vals = hdu.data.field("VALUE")
if "CHANNEL" in hdu.data.columns.names:
chan = hdu.data.field("CHANNEL")
chan = np.unravel_index(chan, shape)
idx = chan + (pix, )
else:
idx = (pix, )
map_out.set_by_idx(idx[::-1], vals)
else:
if colname is not None:
cnames.append(colname)
else:
for c in colnames:
if c.find(hpx_conv.colstring) == 0:
cnames.append(c)
nbin = len(cnames)
if nbin == 1:
map_out.data = hdu.data.field(cnames[0])
else:
for idx, cname in enumerate(cnames):
idx = np.unravel_index(idx, shape)
map_out.data[idx + (slice(None), )] = hdu.data.field(cname)
return map_out
