def createFromHDU(hdu):
header = hdu.header
wcs = pywcs.WCS(header,relax=True)
axes = copy.deepcopy(FITSAxis.create_axes(header))
return SkyImage(wcs,axes,copy.deepcopy(hdu.data.astype(float).T))
def createFromHDU(hdu):
header = pyfits.Header.fromstring(hdu.header.tostring())
# header = hdu.header
wcs = pywcs.WCS(header,naxis=[1,2])#,relax=True)
# wcs1 = pywcs.WCS(header,naxis=[3])
axes = copy.deepcopy(FITSAxis.create_axes(header))
return SkyCube(wcs,axes,copy.deepcopy(hdu.data.astype(float).T))
def createWCS(ra,dec,roi_radius_deg,bin_size_deg=0.2,coordsys='cel'):
nbin = np.ceil(2.0*roi_radius_deg/bin_size_deg)
deg_to_pix = bin_size_deg
wcs = pywcs.WCS(naxis=2)
wcs.wcs.crpix = [nbin/2.+0.5, nbin/2.+0.5]
wcs.wcs.cdelt = np.array([-deg_to_pix,deg_to_pix])
wcs.wcs.crval = [ra, dec]
if coordsys == 'cel': wcs.wcs.ctype = ["RA---AIT", "DEC--AIT"]
else: wcs.wcs.ctype = ["GLON-AIT", "GLAT-AIT"]
wcs.wcs.equinox = 2000.0
return wcs
def createFromFITS(fitsfile,ihdu=0):
hdulist = pyfits.open(fitsfile)
header = hdulist[ihdu].header
wcs = pywcs.WCS(header,naxis=[1,2],relax=True)
if hdulist[1].name == 'ENERGIES':
v = bintable_to_array(hdulist[1].data)
v = np.log10(v)
energy_axis = Axis.createFromArray(v)
axes = copy.deepcopy(FITSAxis.create_axes(header))
axes[2]._crval = energy_axis.edges[0]
axes[2]._delta = energy_axis.width[0]
axes[2]._crpix = 0.0
else:
axes = copy.deepcopy(FITSAxis.create_axes(header))
return SkyCube(wcs,axes,
copy.deepcopy(hdulist[ihdu].data.astype(float).T))
def get_projected_map(self, header):
map_shape = (header["naxis2"], header["naxis1"])
iy, ix = np.indices(map_shape)
wcs = pywcs.WCS(header)
phi, theta = wcs.wcs_pix2sky(ix, iy, 0)
if self._coord is not None:
from pywcsgrid2.wcs_helper import coord_system_guess, sky2sky
map_coord = coord_system_guess(header["ctype1"],
header["ctype2"],
equinox=header["equinox"])
if (map_coord is not None) and (map_coord != self._coord):
warnings.warn(" doing the conversion " + map_coord)
phi, theta = sky2sky(map_coord, self._coord)(phi, theta)
if self._flipy:
theta -= 90
theta *= -np.pi / 180.
else:
theta += 90
theta *= np.pi / 180.
phi *= np.pi / 180
if self._nested:
ang2pix = healpy._healpy_pixel_lib._ang2pix_nest
else:
ang2pix = healpy._healpy_pixel_lib._ang2pix_ring
# some values could be NaNs. Maske those out before calling
# ang2pix and recover them.
mask = np.isfinite(theta) & np.isfinite(theta)
ipix = ang2pix(self._nside, theta[mask], phi[mask])
map_data_ = self._data[ipix]
map_data = np.empty(map_shape, dtype=map_data_.dtype)
map_data.fill(np.nan)
map_data.flat[mask] = map_data_
return map_data
def __getnewargs__(self):
self._wcs = pywcs.WCS(self._header)
return ()