def mosaicDistortionErrors(rootDir, ep, mosaicRoot, mosaicStarlist,
addResid=True, distResid=0.11):
"""
Read in a maser mosaic and it's associated *.shifts file and
calculate the distortion error contribution to each pixel in the
maser mosaic. This is done by using the NIRC2 single frame distortion
error maps (X and Y) located here:
/u/ghezgroup/code/python/gcreduce/nirc2dist_xerr.fits
/u/ghezgroup/code/python/gcreduce/nirc2dist_yerr.fits
For each independent dither position (where independent excludes any
frame within 30 pixels of another frame), the distortion error map
is shifted to the appropriate location in the final moasic and
added in quadrature as sqrt( err1^2 + err2^2 + ... + errN^2 ) / sqrt(N).
The resulting distortion error maps for the mosaics are saved to FITS
files with the name:
<mosaicRoot>_xdisterr.fits
<mosaicRoot>_ydisterr.fits
Finally, <mosaicStarlist> is the existing positional errors are
added in quadrature to the distortion error at the nearest pixel for
each star. The final starlist is saved off to the following file in
the same directory as the input list:
<mosaicStarlist_root>_rms_dist.lis
Inputs:
mosaicRoot - The root name of the maser mosaic fits file
(e.g. 'mag08maylgs1_msr_kp')
mosaicStarlist - The full name of a maser starlist with positional
errors (e.g. 'starfinder/mag08maylgs1_msr_kp_0.8_rms.lis')
addResid - Set to True to add residual distortion error (0.11 pix) in
quadrature to the centroiding and distortion errors
distResid - Value of residual distortion in pixels, to be added to centroid
and distortion errors in quadrature (def=0.11 pix).
"""
# Read in the shifts file
shiftsFile = mosaicRoot + '.shifts'
print(shiftsFile)
shiftsTable = asciidata.open(shiftsFile)
singleFiles = shiftsTable[0]._data
xshifts = shiftsTable[1].tonumpy()
yshifts = shiftsTable[2].tonumpy()
# Read in the mosaic fits file to get the size of the mosaic.
# Then define coordinates for the mosaic.
fitsFile = mosaicRoot + '.fits'
fitsImg, fitsHdr = pyfits.getdata(fitsFile, header=True)
mosaicSize = fitsImg.shape
# Make the final distortion error map.
# Also keep the number of frames that contributes to each pixel.
xdistErrMap = np.zeros((mosaicSize[0], mosaicSize[1]), dtype=float)
ydistErrMap = np.zeros((mosaicSize[0], mosaicSize[1]), dtype=float)
distErrCnt = np.zeros((mosaicSize[0], mosaicSize[1]), dtype=int)
# Read in the distortion errors map
errorRoot = '/u/ghezgroup/code/python/gcreduce/nirc2dist'
xerrOrig = pyfits.getdata(errorRoot + '_xerr.fits')
yerrOrig = pyfits.getdata(errorRoot + '_yerr.fits')
# Get the half-way points for both the mosaic and the single frame.
# For zero-shift, the center of the single frame lies at the center of
# the mosaic.
mosaicHalfX = mosaicSize[1] / 2.0
mosaicHalfY = mosaicSize[0] / 2.0
singleHalfX = xerrOrig.shape[1] / 2.0
singleHalfY = xerrOrig.shape[0] / 2.0
print('Mosaic Size: ', mosaicSize)
print('Mosaic Half: ', mosaicHalfX, mosaicHalfY)
print('Single Half: ', singleHalfX, singleHalfY)
# Loop through the individual frames and add them in
# quadrature to the final distortion error map. Remember that we
# can only do this for independent dither positions. We will
# consider independent dither positions to be those that are
# more than 30 pixel distant from any other ones.
xshiftsUsed = np.array([])
yshiftsUsed = np.array([])
allowedSep = 30.0 # pixels
for ii in range(len(singleFiles)):
# Check to see if we should count this single file as
# a new "independent" position by comparing to all
# shifts used so far.
sep = np.hypot(xshifts[ii] - xshiftsUsed, yshifts[ii] - yshiftsUsed)
idx = np.where(sep < allowedSep)[0]
# If used before, skip
if (len(idx) > 0):
continue
# This is a new independent dither position
xshiftsUsed = np.append(xshiftsUsed, xshifts[ii])
yshiftsUsed = np.append(yshiftsUsed, yshifts[ii])
# Calculate the stop and start indices in the maser mosaic
xlo = round(mosaicHalfX + xshifts[ii] - singleHalfX)
xhi = round(mosaicHalfX + xshifts[ii] + singleHalfX)
ylo = round(mosaicHalfY + yshifts[ii] - singleHalfY)
yhi = round(mosaicHalfY + yshifts[ii] + singleHalfY)
print(singleFiles[ii], xshifts[ii], yshifts[ii])
print(' xrange = [%4d:%4d] yrange = [%4d:%4d]' % (xlo, xhi, ylo, yhi))
xdistErrMap[ylo:yhi,xlo:xhi] += xerrOrig**2
ydistErrMap[ylo:yhi,xlo:xhi] += yerrOrig**2
distErrCnt[ylo:yhi,xlo:xhi] += 1.0
idx = np.where(distErrCnt != 0)
xdistErrMap[idx] = np.sqrt(xdistErrMap[idx] / distErrCnt[idx])
ydistErrMap[idx] = np.sqrt(ydistErrMap[idx] / distErrCnt[idx])
# Save these to a FITS file
xfits = pyfits.PrimaryHDU(xdistErrMap)
gcutil.rmall([mosaicRoot + '_xdisterr.fits', mosaicRoot + '_ydisterr.fits'])
pyfits.writeto(mosaicRoot + '_xdisterr.fits', xdistErrMap)
pyfits.writeto(mosaicRoot + '_ydisterr.fits', ydistErrMap)
##########
#
# Read in starlist and apply distortion errors.
#
##########
starlist = asciidata.open(mosaicStarlist)
# Check that this starlist properly has error columns
if starlist.nrows < 11:
print('Starlist does not have error columns: %s' % mosaicStarlist)
# Now for each star, add the distortion errors in quadrature
for rr in range(starlist.nrows):
xpix = round(starlist[3][rr])
ypix = round(starlist[4][rr])
if addResid:
xerr = math.sqrt(starlist[5][rr]**2 + xdistErrMap[ypix,xpix]**2 + \
distResid**2)
yerr = math.sqrt(starlist[6][rr]**2 + ydistErrMap[ypix,xpix]**2 + \
distResid**2)
else:
xerr = math.sqrt(starlist[5][rr]**2 + xdistErrMap[ypix,xpix]**2)
yerr = math.sqrt(starlist[6][rr]**2 + ydistErrMap[ypix,xpix]**2)
starlist[5][rr] = xerr
starlist[6][rr] = yerr
# Reformat the columns so they get printed out nicely
starlist[0].reformat('%-13s ')
starlist[1].reformat('%6.3f ')
starlist[2].reformat('%8.3f')
starlist[3].reformat('%9.3f ')
starlist[4].reformat('%9.3f ')
starlist[5].reformat('%6.3f')
starlist[6].reformat('%6.3f')
starlist[7].reformat('%11.4f')
starlist[8].reformat('%5.2f')
starlist[9].reformat('%5d')
starlist[10].reformat('%8.4f')
# Write out the new starlist
outroot = mosaicStarlist.replace('rms', 'rms_dist')
starlist.writeto(outroot)
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 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)
