def GeoTran():
filters = ['J', '1113', '1184']
for filt in filters:
s = 'mfm*' + filt + '*.fits'
files = glob.glob(s)
flist = 'flist' + str(filt)
glist = 'glist' + str(filt)
fout = open(flist, 'w')
gout = open(glist, 'w')
for file in files:
ffile = str(file) #+'\n'
gfile = 'g' + str(file) #+'\n'
fout.write(ffile + '\n')
gout.write(gfile + '\n')
iraf.geotran(input=ffile,
output=gfile,
database='PiscesBok',
transforms=filt,
fluxconserve='no')
iraf.rotate(input=gfile, output=gfile, rotation=90)
gfilein = 'g' + str(file) + '[-*,*]'
gfileout = 'g' + str(file)
iraf.imcopy(gfilein, gfileout)
infiles = '@' + str(flist)
outfiles = '@' + str(glist)
#infiles=str(flist)
#outfiles=str(glist)
fout.close()
gout.close()
def deimos_preproc(image):
'''Take a MEF DEIMOS image, extract the relevant extensions, trim the
LVM slit masks appropriately, and rename.'''
# Needing grating
graname = get_head(image, "GRATENAM", extn=0)
# "Blue" chip
iraf.imcopy("%s[%i]" % (image, BEXT), "d%s_B.fits" % image[6:10])
iraf.ccdproc("d%s_B.fits" % image[6:10], overscan=yes, trim=yes,
fixpix=yes, biassec=BBIASSEC, trimsec=BTRIMSEC,
fixfile="%s_%i.fits" % (MASK, BEXT))
iraf.imcopy("d%s_B.fits%s" % (image[6:10], DGRATINGS[graname]["blvmreg"]),
"td%s_B.fits" % image[6:10])
iraf.imtranspose("td%s_B.fits" % image[6:10], "rtd%s_B.fits" % image[6:10])
# "Red" chip
iraf.imcopy("%s[%i]" % (image, REXT), "d%s_R.fits" % image[6:10])
iraf.ccdproc("d%s_R.fits" % image[6:10], overscan=yes, trim=yes,
fixpix=yes, biassec=RBIASSEC, trimsec=RTRIMSEC,
fixfile="%s_%i.fits" % (MASK, BEXT))
iraf.imcopy("d%s_R.fits%s" % (image[6:10], DGRATINGS[graname]["rlvmreg"]),
"td%s_R.fits" % image[6:10])
iraf.imtranspose("td%s_R.fits" % image[6:10], "rtd%s_R.fits" % image[6:10])
iraf.rotate("rtd%s_R.fits" % image[6:10], "rtd%s_R.fits" % image[6:10], 180.0)
return
def rotate_2005_lgsao():
# Need to rotate an image.
ir.unlearn('rotate')
ir.rotate.boundary = 'constant'
ir.rotate.constant = 0
ir.rotate.interpolant = 'spline3'
ir.rotate.ncols = 1040
ir.rotate.nlines = 1040
ir.rotate.xin = 528
ir.rotate.xout = 540
ir.rotate.yin = 645
ir.rotate.yout = 410
ir.rotate(workdir + 'mag05jullgs_kp.fits',
workdir + 'mag05jullgs_kp_rot.fits', 190)
ir.rotate.xin = 535
ir.rotate.xout = 540
ir.rotate.yin = 655
ir.rotate.yout = 410
ir.rotate(workdir + 'mag05jullgs_h.fits',
workdir + 'mag05jullgs_h_rot.fits', 190)
ir.rotate.xin = 572
ir.rotate.xout = 540
ir.rotate.yin = 694
ir.rotate.yout = 410
ir.rotate(workdir + 'mag05jullgs_lp.fits',
workdir + 'mag05jullgs_lp_rot.fits', 190)
ir.rotate.xin = 483
ir.rotate.xout = 483
ir.rotate.yin = 612
ir.rotate.yout = 612
ir.rotate(workdir + 'mag04jul.fits', workdir + 'mag04jul_rot.fits', 1)
def rotate_2005_lgsao():
# Need to rotate an image.
ir.unlearn('rotate')
ir.rotate.boundary = 'constant'
ir.rotate.constant = 0
ir.rotate.interpolant = 'spline3'
ir.rotate.ncols = 1040
ir.rotate.nlines = 1040
ir.rotate.xin = 528
ir.rotate.xout = 540
ir.rotate.yin = 645
ir.rotate.yout = 410
ir.rotate(workdir + 'mag05jullgs_kp.fits', workdir + 'mag05jullgs_kp_rot.fits', 190)
ir.rotate.xin = 535
ir.rotate.xout = 540
ir.rotate.yin = 655
ir.rotate.yout = 410
ir.rotate(workdir + 'mag05jullgs_h.fits', workdir + 'mag05jullgs_h_rot.fits', 190)
ir.rotate.xin = 572
ir.rotate.xout = 540
ir.rotate.yin = 694
ir.rotate.yout = 410
ir.rotate(workdir + 'mag05jullgs_lp.fits', workdir + 'mag05jullgs_lp_rot.fits', 190)
ir.rotate.xin = 483
ir.rotate.xout = 483
ir.rotate.yin = 612
ir.rotate.yout = 612
ir.rotate(workdir + 'mag04jul.fits', workdir + 'mag04jul_rot.fits', 1)
def rotate24():
for i in range(len(images24)):
#for i in range(1):
iraf.imgets(
image=images24[i],
param='CROTA2') #[deg] Orientation of axis 2 (W of N, +=CW)
print iraf.imgets.value
rot24 = float(iraf.imgets.value)
iraf.imgets(
image=images[i],
param='ORIENTAT') #position angle of image y axis (deg. e of n)
print iraf.imgets.value
rotacs = float(iraf.imgets.value)
angle = -1 * rot24 - rotacs
outimage = rimages24[i]
iraf.rotate(input=images24[i], output=outimage, rotation=angle)
def rotate(imlist_name, rotation):
"""
rotate and shift a list of images
Rotate input output rotation
Angle of rotation of the image in degrees. Positive angles will rotate the image counter-clockwise from the x axis.
In the case of SAO 1-m longslit data, 180 degree rotation is required for easy wavelength calibration.
"""
import glob
import os, sys
from pyraf import iraf
iraf.images()
iraf.imgeom()
imlist = glob.glob(imlist_name)
imlist.sort()
for i in range(len(imlist)):
inim = imlist[i]
print('Rotate ' + inim + ' with angle of ' + str(round(rotation, 3)))
iraf.rotate(input=inim, output='r' + inim, rotation=rotation)
print('r' + inim + ' is created.')
def deimos_preproc(image):
'''Take a MEF DEIMOS image, extract the relevant extensions, trim the
LVM slit masks appropriately, and rename.'''
# Needing grating
graname = get_head(image, "GRATENAM", extn=0)
# "Blue" chip
iraf.imcopy("%s[%i]" % (image, BEXT), "d%s_B.fits" % image[6:10])
iraf.ccdproc("d%s_B.fits" % image[6:10],
overscan=yes,
trim=yes,
fixpix=yes,
biassec=BBIASSEC,
trimsec=BTRIMSEC,
fixfile="%s_%i.fits" % (MASK, BEXT))
iraf.imcopy("d%s_B.fits%s" % (image[6:10], DGRATINGS[graname]["blvmreg"]),
"td%s_B.fits" % image[6:10])
iraf.imtranspose("td%s_B.fits" % image[6:10], "rtd%s_B.fits" % image[6:10])
# "Red" chip
iraf.imcopy("%s[%i]" % (image, REXT), "d%s_R.fits" % image[6:10])
iraf.ccdproc("d%s_R.fits" % image[6:10],
overscan=yes,
trim=yes,
fixpix=yes,
biassec=RBIASSEC,
trimsec=RTRIMSEC,
fixfile="%s_%i.fits" % (MASK, BEXT))
iraf.imcopy("d%s_R.fits%s" % (image[6:10], DGRATINGS[graname]["rlvmreg"]),
"td%s_R.fits" % image[6:10])
iraf.imtranspose("td%s_R.fits" % image[6:10], "rtd%s_R.fits" % image[6:10])
iraf.rotate("rtd%s_R.fits" % image[6:10], "rtd%s_R.fits" % image[6:10],
180.0)
return
def lgsAnimate(redoImages=False):
dataRoot = "/u/ghezgroup/data/gc/"
imgRoots = ["05jullgs", "06maylgs1", "06junlgs", "06jullgs", "07maylgs", "07auglgs", "08maylgs1"]
workRoot = "/u/ghezgroup/public_html/gc/images/media/image_anim/"
alignRoot = workRoot + "align/align"
s = starset.StarSet(alignRoot)
names = s.getArray("name")
idx = names.index("SgrA")
sgraxOrig = s.stars[idx].getArrayAllEpochs("xorig")
sgrayOrig = s.stars[idx].getArrayAllEpochs("yorig")
sgrax = s.stars[idx].getArrayAllEpochs("xpix")
sgray = s.stars[idx].getArrayAllEpochs("ypix")
print sgraxOrig
print sgrax
print sgrayOrig
print sgray
sgrax = array([602.831, 600.688, 600.9547, 601.239, 601.118, 601.5432, 600.7679])
sgray = array([689.024, 686.918, 687.0692, 686.7293, 686.971, 686.8857, 687.4686])
# Color Ranges for Images - Log Scale
vmin = array([2.55, 2.52, 2.45, 2.48, 2.5, 2.55, 2.5])
vmax = array([3.4, 3.33, 3.38, 3.35, 3.4, 3.25, 3.25])
# Image plate scale
scale = 0.00996
if len(imgRoots) != len(sgrax):
print "Problem... images and align do not match. Compare to align.list"
print imgRoots
import gcutil, nirc2
if redoImages:
# Need to rotate images
from pyraf import iraf as ir
ir.unlearn("rotate")
ir.rotate.boundary = "constant"
ir.rotate.constant = 0
ir.rotate.interpolant = "spline3"
# Need to plot images
pylab.clf()
for i in range(len(imgRoots)):
imgIn = dataRoot + imgRoots[i] + "/combo/mag" + imgRoots[i] + "_kp.fits"
imgOut = "images/mag" + imgRoots[i] + "_rot.fits"
trans = objects.Transform()
trans.loadFromAbsolute(root=workRoot, align="align/align.trans", idx=i)
trans.linearToSpherical(override=False)
hdr = pyfits.getheader(imgIn)
# phi = nirc2.getPA(hdr)
phi = math.degrees(trans.angle)
if phi != 0:
phi *= -1
if redoImages:
gcutil.rmall([imgOut])
ir.rotate.xin = sgraxOrig[i]
ir.rotate.yin = sgrayOrig[i]
ir.rotate.xout = sgrax[i]
ir.rotate.yout = sgray[i]
ir.rotate(imgIn, imgOut, phi)
img = pyfits.getdata(imgOut)
xax = arange(0, img.shape[0])
yax = arange(0, img.shape[1])
xax = (xax - sgrax[1]) * -scale
yax = (yax - sgray[1]) * scale
pylab.imshow(log10(img), extent=[xax[0], xax[-1], yax[0], yax[-1]], vmin=vmin[i], vmax=vmax[i])
pylab.plot([0], [0], "k+")
# pylab.axis([0.5, -0.5, -0.5, 0.5])
pylab.axis([0.8, -0.8, -0.8, 0.8])
# pylab.axis([3, -3, -3, 3])
pylab.xlabel("RA Offset from Sgr A* (arcsec)")
pylab.ylabel("RA Offset from Sgr A* (arcsec)")
pylab.title(imgRoots[i])
pylab.savefig("frame%d.png" % i)
def ASYM(cutimage, maskimage, ini_xcntr, ini_ycntr, pa, one_minus_eg_sq, r50, background, extraction_radius, angle, flag_image, ABS_ZSUM):
iraf.images(_doprint=0)
iraf.images.imgeom(_doprint=0)
iraf.images.imutil(_doprint=0)
co = n.cos(pa * n.pi / 180.0)
si = n.sin(pa * n.pi / 180.0)
Aabs = n.zeros([9])
Aabs = Aabs.astype(n.float32)
rot_sum = n.zeros([9])
rot_sum = rot_sum.astype(n.float32)
abs_zsum = n.zeros([9])
abs_zsum = abs_zsum.astype(n.float32)
sh_sum = n.zeros([9])
sh_sum = sh_sum.astype(n.float32)
absres_sum = n.zeros([9])
absres_sum = absres_sum.astype(n.float32)
f=pyfits.open(cutimage)
z = f[0].data
z = z - background
f.close()
z = n.swapaxes(z, 0, 1)
iraf.rotate("".join(maskimage), output="MRotated.fits",\
rotation=180, xin = ini_xcntr + 1.0,\
yin = ini_ycntr + 1.0, \
xout = ini_xcntr + 1.0, yout = ini_ycntr + 1.0, \
ncols= "INDEF",\
nlines = "INDEF", interpo= "linear", \
boundar="nearest", verbose="no")
# iraf.imarith("".join(maskimage), op="*", operand2="MRotated.fits", \
# result="AMask.fits")
# f=pyfits.open("AMask.fits")
# mask = f[0].data
# f.close()
f=pyfits.open("MRotated.fits")
mask1 = f[0].data
f.close()
mask1 = n.swapaxes(mask1, 0, 1)
f=pyfits.open(maskimage)
mask2 = f[0].data
f.close()
mask2 = n.swapaxes(mask2, 0, 1)
mask = mask1 + mask2
maskedgalaxy = ma.masked_array(z, mask)
z = ma.filled(maskedgalaxy, value = background)
hdu = pyfits.PrimaryHDU(n.swapaxes(z, 0, 1).astype(n.float32))
hdu.writeto('MaskedGalaxy.fits')
NXPTS = z.shape[0]
NYPTS = z.shape[1]
#r50=c.r50
center_rad = 0.01 * r50
# print 'center_rad', center_rad
# center_rad = 0.5#0.01*r50 The centering correction has to be done by calculating asymmetric parameters at different points 0.1% of r50 away around the center
flag_center = 0 #flag_center=1 if the program finds the exact center else center=0
#extraction_radius=total_rad ie. 1.5 times the radius at eta=0.2
x = n.reshape(n.arange(NXPTS * NYPTS), (NXPTS, NYPTS)) / NYPTS
x = x.astype(n.float32)
y = n.reshape(n.arange(NXPTS * NYPTS), (NXPTS, NYPTS)) % NYPTS
y = y.astype(n.float32)
nn = 0 #This nn is given here and the following loop run either it finds the minimum asymmetry or n=20
while flag_center == 0:
flag_out = 0
#x and y coordinates of different center points in 1-d array
xcntr = n.reshape(n.array([[ini_xcntr] * 3, [ini_xcntr - center_rad] *\
3, [ini_xcntr + center_rad] * 3]), (9, ))
xcntr = xcntr.astype(n.float32)
ycntr = n.array([ini_ycntr, ini_ycntr - center_rad, ini_ycntr + \
center_rad]*3)
ycntr = ycntr.astype(n.float32)
for iter in range(9):#The below is done in order to keep the extraction radius inside the image. If the extraction radius goes outside the image then flag_out=1
if(flag_image):#flag_image will tell whether the input is image (flag_image=1) or background (flag_image=0)
if(xcntr[iter] - 2 - extraction_radius < 0):
extraction_radius = xcntr[iter] - 2
flag_out = 1
if(ycntr[iter] - 2 - extraction_radius < 0):
extraction_radius = ycntr[iter] - 2
flag_out = 1
if(xcntr[iter] + 2 + extraction_radius > NXPTS):
extraction_radius = NXPTS - xcntr[iter] - 2
flag_out = 1
if(ycntr[iter] + 2 + extraction_radius > NYPTS):
extraction_radius = NYPTS - ycntr[iter] - 2
flag_out = 1
tx = (x - xcntr[iter]) * co + (y - ycntr[iter]) * si
ty = (xcntr[iter] - x) * si + (y - ycntr[iter]) * co
R = n.sqrt(tx**2.0 + ty**2.0 / one_minus_eg_sq)
iraf.rotate("".join("MaskedGalaxy.fits"), output="Rotated.fits",\
rotation = 180, xin = xcntr[iter] + 1.0, \
yin = ycntr[iter] + 1.0, \
xout = xcntr[iter] + 1.0, yout = ycntr[iter] + 1.0, \
ncols = "INDEF",\
nlines = "INDEF", interpo = "linear", \
boundar = "nearest", verbose = "no")
f = pyfits.open("Rotated.fits")
rz = f[0].data
f.close()
rz = n.swapaxes(rz, 0, 1)
res = z - rz
for myfile in ['Rotated.fits', 'Residual.fits', 'AResidual.fits']:
if os.access(myfile, os.F_OK):
os.remove(myfile)
sh_sum[iter] = z[n.where(R <= extraction_radius)].sum()
rot_sum[iter] = rz[n.where(R <= extraction_radius)].sum()
abs_zsum[iter] = abs(z[n.where(R <= extraction_radius)]).sum()
absres_sum[iter] = abs(res[n.where(R <= extraction_radius)]).sum()
if(flag_image):
Aabs[iter] = absres_sum[iter] / (abs_zsum[iter])
else:
Aabs[iter] = absres_sum[iter] / (ABS_ZSUM)
Aabso = Aabs.min()
index = Aabs.argmin()
if(nn > 20):
xcntr[index] = ini_xcntr
ycntr[index] = ini_ycntr
if(xcntr[index] == ini_xcntr and ycntr[index] == ini_ycntr):
iraf.rotate("".join("MaskedGalaxy.fits"), output = "Rotated.fits",\
rotation = 180, xin = xcntr[iter] + 1.0, \
yin = ycntr[iter] + 1.0, \
xout = xcntr[iter] + 1.0, yout = ycntr[iter] + 1.0, \
ncols = "INDEF",\
nlines = "INDEF", interpo = "linear", \
boundar = "nearest", verbose = "no")
f = pyfits.open("Rotated.fits")
rz = f[0].data
f.close()
rz = n.swapaxes(rz, 0, 1)
res = z - rz
hdu = pyfits.PrimaryHDU(n.swapaxes(res, 0, 1).astype(n.float32))
hdu.writeto('AResidual.fits')
flag_center = 1
rot_sum = rot_sum[index]
abs_zsum = abs_zsum[index]
if(flag_image == 0):
abs_zsum = ABS_ZSUM
sh_sum = sh_sum[index]
absres_sum = absres_sum[index]
if(flag_image):
error_asym = n.sqrt( Aabso**2*( ((sh_sum + rot_sum + 4 * \
background * \
R[n.where(R <= n.floor(extraction_radius))].size) \
/ absres_sum**2.0) + ((sh_sum + 2.0 * background *\
R[n.where(R <= n.floor(extraction_radius))].size) \
/ abs_zsum**2) ) )
else:
error_asym = n.sqrt( Aabso**2 * (((sh_sum+rot_sum + 2 * \
background * \
R[n.where(R <= n.floor(extraction_radius))].size) \
/ absres_sum**2.0) + ((sh_sum + 2.0 * background \
* R[n.where(R <= n.floor(extraction_radius))].size) \
/ abs_zsum**2) ) )
else:
ini_xcntr = xcntr[index]
ini_ycntr = ycntr[index]
nn += 1
for myfile in ['MaskedGalaxy.fits', 'MRotated.fits']:
if os.access(myfile, os.F_OK):
os.remove(myfile)
return Aabso, error_asym, ini_xcntr, ini_ycntr, nn, flag_out,\
abs_zsum, sh_sum, extraction_radius
def psf_rotate(psf, psf_rot, angle):
file_remove(psf_rot)
iraf.rotate(psf + '[0]', psf_rot, -angle, interpolant='nearest')
iraf.rotate.unlearn()
def rotate(params, params_gal, dark_perform):
"""This function rotates the image
Args:
key: (str) key value for galaxy. e.g. jcmc11ctq_flt.fits has key ==
rw: (str) name of FLT file
x_filter: (str)filter name . e.g. F165LP
params: (dict) Dictionary of 'basic' section of config file (common for all ULIRGs)
params_gal: (dict) Dictionary of galaxy parameters from config file
Returns:
str : (xreg_out) shifted image with a reference image
"""
flt_files = params['flt_files']
tab = Table.read(flt_files, format='csv')
rw = list(tab["filename"])
gal_name = params_gal['name']
dark = params_gal['dark_frames']
dark = (dark.split(','))
bad = params_gal['bad_frames']
bad = (bad.split(','))
primary_dir = params['data_dir'] + gal_name + '/'
t = 0
for i in range(len(tab)):
c = []
for letter in rw[i]:
c.append(letter)
gal_key = c[4] + c[5] + c[6] + c[7] + c[8]
x_filter = tab["filtername"][i]
if t == 0:
ref_angle = float(tab["orientation"][i])
rotate_ang = float(tab["orientation"][i]) - ref_angle
if gal_key not in bad \
and gal_key not in dark \
and tab["galaxy"][i] == gal_name \
and tab["detector"][i] == "SBC":
t = t + 1
sky_dark_iraf, rotate_out, sky_dark_err, rotate_out_err, sky_dark_DQ, rotate_out_DQ = \
iraf_rotate_command("sky", rw[i], x_filter, primary_dir)
iraf.rotate(sky_dark_iraf,
rotate_out,
rotate_ang,
interpolant='nearest')
iraf.rotate.unlearn()
iraf.rotate(sky_dark_err,
rotate_out_err,
rotate_ang,
interpolant='nearest')
iraf.rotate.unlearn()
iraf.rotate(sky_dark_DQ,
rotate_out_DQ,
rotate_ang,
interpolant='nearest')
iraf.rotate.unlearn()
if gal_key in dark \
and tab["galaxy"][i] == gal_name \
and tab["detector"][i] == "SBC" and dark_perform:
sky_dark_iraf, rotate_out, sky_dark_err, rotate_out_err, sky_dark_DQ, rotate_out_DQ = \
iraf_rotate_command("drk", rw[i], x_filter, primary_dir)
iraf.rotate(sky_dark_iraf,
rotate_out,
rotate_ang,
interpolant='nearest')
iraf.rotate.unlearn()
iraf.rotate(sky_dark_err,
rotate_out_err,
rotate_ang,
interpolant='nearest')
iraf.rotate.unlearn()
iraf.rotate(sky_dark_DQ,
rotate_out_DQ,
rotate_ang,
interpolant='nearest')
iraf.rotate.unlearn()
return tab, bad, dark, primary_dir
def lgsAnimate(redoImages=False):
dataRoot = '/u/ghezgroup/data/gc/'
imgRoots = [
'05jullgs', '06maylgs1', '06junlgs', '06jullgs', '07maylgs',
'07auglgs', '08maylgs1'
]
workRoot = '/u/ghezgroup/public_html/gc/images/media/image_anim/'
alignRoot = workRoot + 'align/align'
s = starset.StarSet(alignRoot)
names = s.getArray('name')
idx = names.index('SgrA')
sgraxOrig = s.stars[idx].getArrayAllEpochs('xorig')
sgrayOrig = s.stars[idx].getArrayAllEpochs('yorig')
sgrax = s.stars[idx].getArrayAllEpochs('xpix')
sgray = s.stars[idx].getArrayAllEpochs('ypix')
print sgraxOrig
print sgrax
print sgrayOrig
print sgray
sgrax = array(
[602.831, 600.688, 600.9547, 601.239, 601.118, 601.5432, 600.7679])
sgray = array(
[689.024, 686.918, 687.0692, 686.7293, 686.971, 686.8857, 687.4686])
# Color Ranges for Images - Log Scale
vmin = array([2.55, 2.52, 2.45, 2.48, 2.5, 2.55, 2.5])
vmax = array([3.4, 3.33, 3.38, 3.35, 3.4, 3.25, 3.25])
# Image plate scale
scale = 0.00996
if (len(imgRoots) != len(sgrax)):
print 'Problem... images and align do not match. Compare to align.list'
print imgRoots
import gcutil, nirc2
if (redoImages):
# Need to rotate images
from pyraf import iraf as ir
ir.unlearn('rotate')
ir.rotate.boundary = 'constant'
ir.rotate.constant = 0
ir.rotate.interpolant = 'spline3'
# Need to plot images
pylab.clf()
for i in range(len(imgRoots)):
imgIn = dataRoot + imgRoots[i] + '/combo/mag' + imgRoots[i] + '_kp.fits'
imgOut = 'images/mag' + imgRoots[i] + '_rot.fits'
trans = objects.Transform()
trans.loadFromAbsolute(root=workRoot, align='align/align.trans', idx=i)
trans.linearToSpherical(override=False)
hdr = pyfits.getheader(imgIn)
#phi = nirc2.getPA(hdr)
phi = math.degrees(trans.angle)
if (phi != 0):
phi *= -1
if (redoImages):
gcutil.rmall([imgOut])
ir.rotate.xin = sgraxOrig[i]
ir.rotate.yin = sgrayOrig[i]
ir.rotate.xout = sgrax[i]
ir.rotate.yout = sgray[i]
ir.rotate(imgIn, imgOut, phi)
img = pyfits.getdata(imgOut)
xax = arange(0, img.shape[0])
yax = arange(0, img.shape[1])
xax = (xax - sgrax[1]) * -scale
yax = (yax - sgray[1]) * scale
pylab.imshow(log10(img),
extent=[xax[0], xax[-1], yax[0], yax[-1]],
vmin=vmin[i],
vmax=vmax[i])
pylab.plot([0], [0], 'k+')
#pylab.axis([0.5, -0.5, -0.5, 0.5])
pylab.axis([0.8, -0.8, -0.8, 0.8])
#pylab.axis([3, -3, -3, 3])
pylab.xlabel('RA Offset from Sgr A* (arcsec)')
pylab.ylabel('RA Offset from Sgr A* (arcsec)')
pylab.title(imgRoots[i])
pylab.savefig('frame%d.png' % i)
def psf_rotate(psf, psf_rot, angle):
iraf.rotate(psf + '[0]', psf_rot, -angle, interpolant='nearest')
def lgsAnimate(redoAlign=False, redoImages=False):
dataRoot = '/u/ghezgroup/data/gc/'
imgRoots = ['05jullgs', '06maylgs1', '06junlgs', '06jullgs',
'07maylgs', '07auglgs', '08maylgs1', '08jullgs',
'09maylgs', '10maylgs', '10jullgs1', '10auglgs1',
'11maylgs', '11auglgs']
refEpoch = '08maylgs'
workRoot = '/u/ghezgroup/public_html/gc/images/media/image_anim/'
alignRoot = workRoot + 'align/align'
if (redoAlign):
# Copy over the starlists
for epoch in imgRoots:
lisFile = 'mag' + epoch + '_kp_rms.lis'
copyFrom = dataRoot + epoch + '/combo/starfinder/' + lisFile
copyTo = workRoot + 'lis/'
shutil.copy(copyFrom, copyTo)
lisFile = 'mag' + epoch + '_kp_rms_named.lis'
copyFrom = dataRoot + epoch + '/combo/starfinder/' + lisFile
copyTo = workRoot + 'lis/'
shutil.copy(copyFrom, copyTo)
# Align
os.chdir(workRoot + 'align/')
alignList = open(alignRoot + '.list', 'w')
for epoch in imgRoots:
lisFile = 'mag' + epoch + '_kp_rms.lis'
alignList.write('../lis/' + lisFile + ' 9')
if (epoch == refEpoch):
alignList.write(' ref')
alignList.write('\n')
alignList.close()
alignCmd = 'java align -a 2 -p '
alignCmd += '-N /u/ghezgroup/data/gc/source_list/label.dat '
#alignCmd += '-N /u/ghezgroup/data/gc/source_list/label_new.dat '
alignCmd += '-o /u/ghezgroup/data/gc/source_list/orbits.dat '
alignCmd += 'align.list'
os.system(alignCmd)
absCmd = 'java align_absolute '
absCmd += '-abs /u/ghezgroup/data/gc/source_list/absolute_refs.dat '
absCmd += 'align align_abs'
os.system(absCmd)
os.chdir(workRoot)
s = starset.StarSet(alignRoot+'_abs')
names = s.getArray('name')
idx = names.index('SgrA')
sgraxOrig = s.stars[idx].getArrayAllEpochs('xorig')
sgrayOrig = s.stars[idx].getArrayAllEpochs('yorig')
sgrax = s.stars[idx].getArrayAllEpochs('xpix')
sgray = s.stars[idx].getArrayAllEpochs('ypix')
print 'sgraxOrig = ', sgraxOrig
print 'sgrax = ', sgrax
print 'sgrayOrig = ', sgrayOrig
print 'sgray = ', sgray
# Tweak 05jullgs Sgr A* position, since it was not detected
print
print 'Tweaking 05jullgs Sgr A* position, since it was not named in the starlist'
sgraxOrig[0] = 525.9
sgrayOrig[0] = 643.9
sgrax[0] = 0.0
sgray[0] = 0.0
print 'Update code with positions of Sgr A*'
foo = raw_input('Continue? ')
if (foo == 'q' or foo == 'Q'):
return
# Tweaks to Sgr A*'s positions (in arcseconds)
# more negative goes to the right
dx = array([-0.017, -0.002, -0.003, -0.005, 0.001, 0.00, 0.002, 0.001, 0.002, 0.001,
0.00, 0.00, 0.001, 0.00])
dy = array([ 0.005, 0.00, 0.00, 0.00, 0.001, 0.00, 0.00, -0.003, 0.00, 0.00,
0.000, 0.00, 0.000, 0.00])
# Color Ranges for Images - Log Scale
vmin = array([2.48, 2.51, 2.45, 2.48, 2.50, 2.55, 2.50, 2.50, 2.50, 2.55,
2.53, 2.53, 2.53, 2.45])
vmax = array([3.45, 3.32, 3.38, 3.35, 3.40, 3.25, 3.3, 3.35, 3.3, 3.30,
3.30, 3.30, 3.30, 3.45])
# Image plate scale
scale = 0.00995
if (len(imgRoots) != len(sgrax)):
print 'Problem... images and align do not match. Compare to align.list'
print imgRoots
from gcreduce import gcutil
import nirc2
if (redoImages):
# Need to rotate images
from pyraf import iraf as ir
ir.unlearn('rotate')
ir.rotate.boundary = 'constant'
ir.rotate.constant = 0
ir.rotate.interpolant = 'spline3'
# Need to plot images
pylab.clf()
for i in range(len(imgRoots)):
imgIn = dataRoot + imgRoots[i] + '/combo/mag' + imgRoots[i] + '_kp.fits'
imgOut = 'images/mag' + imgRoots[i] + '_rot.fits'
hdr = pyfits.getheader(imgIn)
phi = nirc2.getPA(hdr)
if (redoImages):
gcutil.rmall([imgOut])
ir.rotate.xin = sgraxOrig[i]+1
ir.rotate.yin = sgrayOrig[i]+1
ir.rotate.xout = (sgrax[i]/scale)+512+1
ir.rotate.yout = (sgray[i]/scale)+512+1
ir.rotate(imgIn, imgOut, phi)
img = pyfits.getdata(imgOut)
xax = arange(0, img.shape[1])
yax = arange(0, img.shape[0])
xax = (xax - 512.) * -scale + dx[i]
yax = (yax - 512.) * scale + dy[i]
# With labels and borders
pylab.figure(1)
pylab.clf()
pylab.figure(figsize=(7,7))
pylab.imshow(log10(img), extent=[xax[0], xax[-1], yax[0], yax[-1]],
vmin=vmin[i], vmax=vmax[i],origin='lowerleft')
pylab.plot([0], [0], 'k+')
#pylab.axis([0.5, -0.5, -0.5, 0.5])
#pylab.axis([0.8, -0.8, -0.8, 0.8])
#pylab.axis([3, -3, -3, 3])
pylab.axis([1, -1, -1, 1])
pylab.xlabel('RA Offset from Sgr A* (arcsec)')
pylab.ylabel('Dec Offset from Sgr A* (arcsec)')
pylab.title(imgRoots[i])
pylab.savefig('frame%d.png' % i)
pylab.close(1)
# No labels and borders
pylab.figure(2)
pylab.clf()
pylab.figure(figsize=(6,6))
pylab.subplots_adjust(left=0, right=1, bottom=0, top=1)
pylab.imshow(log10(img), extent=[xax[0], xax[-1], yax[0], yax[-1]],
vmin=vmin[i], vmax=vmax[i],origin='lowerleft')
pylab.plot([0], [0], 'k+')
pylab.axis([0.5, -0.5, -0.5, 0.5])
pylab.axis('off')
pylab.title(imgRoots[i])
pylab.savefig('frame%d_noborder.png' % i)
pylab.close(2)