def setHdus(self, p): self.hdus = p self.table = fits_table(self.hdus[1].data)[0] T = self.table self.aa = T.aa.astype(float) self.kk = T.kk.astype(float) self.airmass = T.airmass
def readPhotoObj(self, run, camcol, field, filename=None):
obj = PhotoObj(run, camcol, field)
if filename is None:
fn = self.getPath('photoObj', run, camcol, field)
else:
fn = filename
obj.table = fits_table(fn)
return obj
def getMaskPlane(self, name):
# Mask planes are described in HDU 11 (the last HDU)
if self.maskmap is None:
self.maskmap = {}
T = fits_table(self.hdus[-1].data)
#print 'Got mask definition table'
#T.about()
T.cut(T.defname == 'S_MASKTYPE')
for k,v in zip(T.attributename, T.value):
k = k.replace('S_MASK_', '')
if k == 'S_NMASK_TYPES':
continue
#print ' Mask', k, '=', v
self.maskmap[k] = v
if not name in self.maskmap:
raise RuntimeError('Unknown mask plane \"%s\"' % name)
return fits_table(self.hdus[1 + self.maskmap[name]].data)
def getPsfAtPoints(self, bandnum, x, y):
'''
Reconstruct the SDSS model PSF from KL basis functions.
x,y can be scalars or 1-d numpy arrays.
Return value:
if x,y are scalars: a PSF image
if x,y are arrays: a list of PSF images
'''
rtnscalar = np.isscalar(x) and np.isscalar(y)
x = np.atleast_1d(x)
y = np.atleast_1d(y)
psf = fits_table(self.hdus[bandnum+1].data)
psfimgs = None
(outh, outw) = (None,None)
# From the IDL docs:
# http://photo.astro.princeton.edu/photoop_doc.html#SDSS_PSF_RECON
# acoeff_k = SUM_i{ SUM_j{ (0.001*ROWC)^i * (0.001*COLC)^j * C_k_ij } }
# psfimage = SUM_k{ acoeff_k * RROWS_k }
for k in range(len(psf)):
nrb = psf.nrow_b[k]
ncb = psf.ncol_b[k]
c = psf.c[k].reshape(5, 5)
c = c[:nrb,:ncb]
(gridi,gridj) = np.meshgrid(range(nrb), range(ncb))
if psfimgs is None:
psfimgs = [np.zeros_like(psf.rrows[k]) for xy
in np.broadcast(x,y)]
(outh,outw) = (psf.rnrow[k], psf.rncol[k])
else:
assert(psf.rnrow[k] == outh)
assert(psf.rncol[k] == outw)
for i,(xi,yi) in enumerate(np.broadcast(x,y)):
#print 'xi,yi', xi,yi
acoeff_k = np.sum(((0.001 * xi)**gridi * (0.001 * yi)**gridj * c))
if False: # DEBUG
print 'coeffs:', (0.001 * xi)**gridi * (0.001 * yi)**gridj
print 'c:', c
for (coi,ci) in zip(((0.001 * xi)**gridi * (0.001 * yi)**gridj).ravel(), c.ravel()):
print 'co %g, c %g' % (coi,ci)
print 'acoeff_k', acoeff_k
#print 'acoeff_k', acoeff_k.shape, acoeff_k
#print 'rrows[k]', psf.rrows[k].shape, psf.rrows[k]
psfimgs[i] += acoeff_k * psf.rrows[k]
psfimgs = [img.reshape((outh,outw)) for img in psfimgs]
if rtnscalar:
return psfimgs[0]
return psfimgs
def setHdus(self, p): self.hdus = p t = fits_table(p[6].data) # the table has only one row... assert(len(t) == 1) t = t[0] #self.table = t self.gain = t.gain self.dark_variance = t.dark_variance self.sky = t.sky self.skyerr = t.skyerr self.psp_status = t.status # Double-Gaussian PSF params self.dgpsf_s1 = t.psf_sigma1_2g self.dgpsf_s2 = t.psf_sigma2_2g self.dgpsf_b = t.psf_b_2g # summary PSF width (sigmas) self.psf_fwhm = t.psf_width * (2.*np.sqrt(2.*np.log(2.)))
def readFrame(self, run, camcol, field, band, filename=None):
'''
http://data.sdss3.org/datamodel/files/BOSS_PHOTOOBJ/frames/RERUN/RUN/CAMCOL/frame.html
'''
f = Frame(run, camcol, field, band)
# ...
if filename is None:
fn = self.getPath('frame', run, camcol, field, band)
else:
fn = filename
#print 'reading file', fn
p = pyfits.open(fn)
#print 'got', len(p), 'HDUs'
# in nanomaggies
f.image = p[0].data
# converts counts -> nanomaggies
f.calib = p[1].data
# table with val,x,y -- binned; use bilinear interpolation to expand
sky = p[2].data
f.sky = sky.field('allsky')[0]
#print 'sky shape', f.sky.shape
if len(f.sky.shape) != 2:
f.sky = f.sky.reshape((-1, 256))
f.skyxi = sky.field('xinterp')[0]
f.skyyi = sky.field('yinterp')[0]
#print 'p3:', p[3]
# table -- asTrans structure
tab = fits_table(p[3].data)
assert(len(tab) == 1)
tab = tab[0]
# DR7 has NODE, INCL in radians...
f.astrans = AsTrans(run, camcol, field, band,
node=np.deg2rad(tab.node), incl=np.deg2rad(tab.incl),
astrans=tab, cut_to_band=False)
return f
