def make_cube(filelist, outfilename, clobber=True, brgfile=None,
stellarfile=True, h2file=True, brdfile=True, brefile=True,
reference_image=None, reference_radec=None, reference_pix=None,
pabfile=True, rot90=False, cd1=0.5, cd2=0.5,):
"""
Create a data cube from a list of reduced TripleSpec spectra
Parameters
----------
filelist : list
A list of the files to include. Generate by, e.g.,
filelist = glob.glob("*JHK_cal.fits")
outfilename : string
The output FITS file name
clobber : bool
Overwrite the output file if it exists?
brgfile : string
Create a Brackett Gamma integrated image if this is set to a FITS file
name
stellarfile : string
Create a stellar continuum image from a relatively clean part of the
spectrum if this is set to a FITS file name
h2file : string
Create an H2 2.12um integrated image if this is set to a FITS file name
reference_image : string
A FITS file to use as the pointing standard for cross-correlation based
pointing correction. Makes use of agpy's cross_correlation_shift tool
reference_radec : (float,float)
The RA/Dec (CRVAL1/CRVAL2) of the image reference position. If not
specified, will be extracted from one of the input spectra (likely
incorrectly)
reference_pix : (float,float)
The X,Y pixel (CRPIX1/CRPIX2) reference in the image. If not
specified, will default to the center.
rot90 : bool
Should the spectra be rotated by 90 degrees before stacking?
cd1 : float
cd2 : float
The CD1_1 and CD2_2 / CDELT1 & CDELT2 parameters for the FITS header
"""
f0 = pyfits.open(filelist[0])
cubeJHK = np.zeros([f0[0].header['NAXIS2']+20,f0[0].header['NAXIS1'],len(filelist)+20])
print 'cubeshape (no adds): ',[f0[0].header['NAXIS2'],f0[0].header['NAXIS1'],len(filelist)]
print 'cubeshape (with adds): ',[f0[0].header['NAXIS2']+20,f0[0].header['NAXIS1'],len(filelist)+20]
fout = pyfits.open(filelist[0])
print "cube shape: ",cubeJHK.shape
fout[0].data = cubeJHK = cubeJHK.swapaxes(0,1)
if rot90:
fout[0].data = cubeJHK = fout[0].data.swapaxes(1,2)[:,::-1,:]
fout[0].header.update('NAXIS3',cubeJHK.shape[0])
fout[0].header.update('NAXIS',3)
print "fout.data shape: ",fout[0].data.shape
if reference_radec is not None:
ra,dec = reference_radec
else:
fcen = pyfits.open(filelist[len(filelist)/2])
ra = fcen[0].header.get('RA')
dec = fcen[0].header.get('DEC')
#ra,dec = coords.Position(ra+" "+dec).j2000()
C = coordinates.ICRS(ra,dec,unit=('deg','deg'))
ra,dec = C.ra.deg,C.dec.deg
if reference_pix is not None:
xpix,ypix = reference_pix
else:
xpix = fout[0].data.shape[2]/2.+1
ypix = fout[0].data.shape[1]
fout[0].header.update('CRVAL3', fout[0].header['CRVAL1'])
fout[0].header.update('CRPIX3', fout[0].header['CRPIX1'])
fout[0].header.update('CD3_3', fout[0].header['CDELT1'])
fout[0].header.update('CRVAL1', ra)
fout[0].header.update('CRVAL2', dec)
fout[0].header.update('CRPIX1', xpix)
fout[0].header.update('CRPIX2', ypix)
fout[0].header.update('CD1_1', -cd1/3600.)
fout[0].header.update('CD2_2', cd2/3600.)
fout[0].header.update('CTYPE1', 'RA---TAN')
fout[0].header.update('CTYPE2', 'DEC--TAN')
fout[0].header.update('CTYPE3', 'LINEAR')
del fout[0].header['CDELT1']
del fout[0].header['CDELT2']
outhd = fout[0].header
flathead = agpy.cubes.flatten_header(outhd)
outwcs = pywcs.WCS(flathead)
wtcube = cubeJHK*0
for ii,fn in enumerate(filelist):
d = pyfits.getdata(fn)
h = pyfits.getheader(fn)
findername = h.get('FINDER')
if findername is None or findername == '':
raise IOError("No finder found!")
slitcoords = get_slit_coordinates(findername,d.shape[0])
pixcoords = outwcs.wcs_world2pix(np.array(zip(*slitcoords)),0)
print ii,fn,len(slitcoords),len(pixcoords),len(pixcoords[0])
for x,y,di in zip(pixcoords[:,0],pixcoords[:,1],d):
xrd = round(x)
yrd = round(y)
xrem = x-xrd
yrem = y-yrd
weights = ((0.5+(abs(xrem)-0.5)*np.sign(xrem)) * (0.5+(abs(yrem)-0.5)*np.sign(yrem)),
(0.5+(abs(xrem)-0.5)*np.sign(xrem)) * (0.5-(abs(yrem)-0.5)*np.sign(yrem)),
(0.5-(abs(xrem)-0.5)*np.sign(xrem)) * (0.5-(abs(yrem)-0.5)*np.sign(yrem)),
(0.5-(abs(xrem)-0.5)*np.sign(xrem)) * (0.5+(abs(yrem)-0.5)*np.sign(yrem)))
if np.any(np.array(weights) < 0):
print weights
raise ValueError('negative weight')
wtsum = sum(weights)
if (wtsum - 1) > 1e-5:
raise ValueError("wtsum = 1+%g" % (wtsum-1))
cubeJHK[:,xrd,yrd] += di * weights[0]
cubeJHK[:,xrd,yrd-1] += di * weights[1]
cubeJHK[:,xrd-1,yrd-1] += di * weights[3]
cubeJHK[:,xrd-1,yrd] += di * weights[2]
wtcube[:,xrd,yrd] += weights[0]
wtcube[:,xrd,yrd-1] += weights[1]
wtcube[:,xrd-1,yrd-1] += weights[3]
wtcube[:,xrd-1,yrd] += weights[2]
#wtcube[:,x,y] += (1-xrem) * (1-yrem)
print "wtcube shape: ",wtcube.shape," wtcube.sum(): ",wtcube.sum()," single plane: ",wtcube[0,:,:].sum()
print "max wt: ",wtcube[0,:,:].max()
print "min wt: ",wtcube[0,:,:].min()
fout[0].data = cubeJHK/wtcube
fout.writeto(outfilename,clobber=clobber,output_verify='fix')
#fout[0].data = wtcube
#fout.writeto(outfilename.replace('cube','weightcube'),clobber=clobber,output_verify='fix')
cubeJHK = cubeJHK/wtcube
if brgfile is not None:
if brgfile is True:
if 'cube.fits' in outfilename:
brgfile = outfilename.replace("cube.fits","brg.fits")
else:
raise
brg = cubeJHK[3582:3590,:,:].sum(axis=0) #- np.median(cubeJHK[3592:3605,:,:],axis=0)*8
fout[0].data=brg
del fout[0].header['CTYPE3']
del fout[0].header['CRVAL3']
del fout[0].header['CRPIX3']
del fout[0].header['CD3_3']
fout.writeto(brgfile,clobber=clobber,output_verify='fix')
if reference_image is not None:
offsets = AG_image_tools.cross_correlation_shifts_FITS(brgfile, reference_image)
fout[0].header['CRPIX1'] -= offsets[0][0]
fout[0].header['CRPIX2'] -= offsets[1][0]
fout.writeto(brgfile,clobber=clobber,output_verify='fix')
foutcube = pyfits.open(outfilename)
foutcube[0].header['CRPIX1'] -= offsets[0][0]
foutcube[0].header['CRPIX2'] -= offsets[1][0]
foutcube.writeto(outfilename,clobber=clobber,output_verify='fix')
if stellarfile is not None:
if stellarfile is True:
if 'cube.fits' in outfilename:
stellarfile = outfilename.replace("cube.fits","brg_cont.fits")
else:
raise
stellar = (np.sum(cubeJHK[3570:3575,:,:],axis=0) + np.sum(cubeJHK[3592:3594,:,:],axis=0) + np.sum(cubeJHK[3598:3601,:,:],axis=0)) * 8./10.
fout[0].data=stellar
fout.writeto(stellarfile,clobber=clobber,output_verify='fix')
if h2file is not None:
if h2file is True:
if 'cube.fits' in outfilename:
h2file = outfilename.replace("cube.fits","h2.fits")
else:
raise
h2 = np.sum(cubeJHK[3431:3435,:,:],axis=0)# - np.median(cubeJHK[3435:3445,:,:],axis=0)*4
fout[0].data=h2
fout.writeto(h2file,clobber=clobber,output_verify='fix')
if h2file is True:
if 'cube.fits' in outfilename:
h2cfile = outfilename.replace("cube.fits","h2_cont.fits")
else:
raise
else:
if 'h2' in h2file:
h2cfile = h2file.replace("h2","h2_cont")
else:
raise
h2c = (np.sum(cubeJHK[3446:3452,:,:],axis=0))*4./6.
fout[0].data=h2c
fout.writeto(h2cfile,clobber=clobber,output_verify='fix')
if brdfile is not None:
if brdfile is True:
if 'cube.fits' in outfilename:
brdfile = outfilename.replace("cube.fits","brd.fits")
else:
raise
brd = np.sum(cubeJHK[2819:2824,:,:],axis=0) #- np.median(cubeJHK[2825:2835,:,:],axis=0)*5
fout[0].data=brd
fout.writeto(brdfile,clobber=clobber,output_verify='fix')
if brdfile is True:
if 'cube.fits' in outfilename:
brdcfile = outfilename.replace("cube.fits","brd_cont.fits")
else:
raise
else:
if 'brd' in brdfile:
brdcfile = brdfile.replace("brd","brd_cont")
else:
raise
brdc = (np.sum(cubeJHK[2810:2815,:,:],axis=0) + np.sum(cubeJHK[2824:2829,:,:],axis=0))/2.
fout[0].data=brdc
fout.writeto(brdcfile,clobber=clobber,output_verify='fix')
if brefile is not None:
if brefile is True:
if 'cube.fits' in outfilename:
brefile = outfilename.replace("cube.fits","bre.fits")
else:
raise
bre = np.sum(cubeJHK[2377:2382,:,:],axis=0) # - np.median(cubeJHK[2347:2353,:,:],axis=0)*5
fout[0].data=bre
fout.writeto(brefile,clobber=clobber,output_verify='fix')
if brefile is True:
if 'cube.fits' in outfilename:
brecfile = outfilename.replace("cube.fits","bre_cont.fits")
else:
raise
else:
if 'bre' in brefile:
brecfile = brefile.replace("bre","bre_cont")
else:
raise
brec = (np.sum(cubeJHK[2370:2375,:,:],axis=0) + np.sum(cubeJHK[2382:2387,:,:],axis=0))/2.
fout[0].data=brec
fout.writeto(brecfile,clobber=clobber,output_verify='fix')
if pabfile is not None:
if pabfile is True:
if 'cube.fits' in outfilename:
pabfile = outfilename.replace("cube.fits","pab.fits")
else:
raise
pab = np.sum(cubeJHK[519:523,:,:],axis=0) # - np.median(cubeJHK[2347:2353,:,:],axis=0)*5
fout[0].data=pab
fout.writeto(pabfile,clobber=clobber,output_verify='fix')
if pabfile is True:
if 'cube.fits' in outfilename:
pabcfile = outfilename.replace("cube.fits","pab_cont.fits")
else:
raise
else:
if 'pab' in pabfile:
pabcfile = pabfile.replace("pab","pab_cont")
else:
raise
pabc = (cubeJHK[519,:,:]+cubeJHK[523,:,:])*2.
fout[0].data=pabc
fout.writeto(pabcfile,clobber=clobber,output_verify='fix')
for line in line_ranges:
make_integral(cubeJHK, filename=True, outfilename=outfilename, line=line, fout=fout, clobber=clobber)
kcont = np.sum([cubeJHK[a:b,:,:].sum(axis=0) for (a,b) in Kcont],axis=0)
fout[0].data=kcont
fout.writeto(outfilename.replace('cube','kcont'),clobber=clobber,output_verify='fix')
len("blasdgasdfasdfa")
206265/400.
206265/415.
206265/18500.
400./206265.
206265/5e4.
206265/5e4
400./206265. * 33
400./206265. * 120
im1
im1 = np.zeros([10,10])
im1[4,4] = 1
im2 = np.zeros([10,10])
im2[5,5] = 1
import AG_image_tools
AG_image_tools.cross_correlation_shifts(im1,im2)
roll
help(roll)
help(rollaxis)
roll(roll(im1,1,0),1,1)
(roll(roll(im1,1,0),1,1) - im2).sum()
im1[4,4]=0
im1[4,3] = 1
AG_image_tools.cross_correlation_shifts(im1,im2)
(roll(roll(im1,2,0),1,1) - im2).sum()
get_ipython().magic(u"history ")
yoff,xoff = AG_image_tools.cross_correlation_shifts(im1,im2)
im1_aligned_to_im2 = roll(roll(im1,yoff,0),xoff,1)
im1_aligned_to_im2 = roll(roll(im1,yoff,0),xoff,1)
yoff
reload(AG_image_tools)
