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reduceIfuObj.py
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reduceIfuObj.py
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import os
import pyfu
import time
import utils
from pyraf import iraf
from iraf import proto
from iraf import dataio
from iraf import system
from iraf import fitsutil
from iraf import gemini, gmos
from iraf import images, imutil, immatch
from iraf import stsdas, analysis, gasp
from astropy.io import fits
class ReduceIfuObj():
def __init__(self, imList, target="", steps={}, rawPath="./", calPath="", \
mdf="", biasIm="", flatList="", arcDir="", arcList="", sFunc="", \
logRoot=""):
self.target = target
self.steps = steps
self.rawPath = rawPath
self.calPath = calPath
self.bias = self.calPath + biasIm
self.mdf = mdf
self.imList = imList
self.arcDir = arcDir
self.arcList = arcList
if len(flatList) > 0:
self.flats = utils.getImPaths(flatList)
self.sFunc = self.calPath + sFunc
self.logRoot = logRoot
return
# function to mask cosmetics in exposures
def adjustDQ(self, inIm, ext, txtMask):
print "\nADJUSTING MASK FOR " + inIm + ext.upper()
# grab dimensions of mask from header of image
# TODO: will expression for num work in one-slit case?
hdu = fits.open(inIm)
num = 3 * (int(ext[-2]) - 1) + 2
xDim = hdu[num].header["NAXIS1"]
yDim = hdu[num].header["NAXIS2"]
hdu.close()
# display input image
print "Displaying 2D spectra"
iraf.display(inIm + ext)
if ext[-2] == "1":
iraf.imdelete("x" + inIm, verify="yes")
# allow user to adjust mask iteratively
while True:
# ask user to input coordinate ranges to mask
fixDQ = bool(input("\nDoes mask need improvement? (True/False): "))
if fixDQ:
os.system("rm -iv " + txtMask)
ranges = raw_input("Coord ranges to be masked (space-separated): ")
cmd = "echo '" + ranges + "' >> " + txtMask
os.system(cmd)
else:
break
# transform text mask to pixel list format
plMask = txtMask[:txtMask.find(".")] + ".pl"
iraf.delete(plMask)
iraf.text2mask(txtMask, plMask, xDim, yDim)
# interpolate over bad pixels and mark them in DQ plane
tmp = "tmp_" + inIm[:inIm.find(".")] + "_" + ext[-2] + ".fits"
tmpdq = "tmpdq_" + inIm[:inIm.find(".")] + "_" + ext[-2] + ".fits"
images = tmp + "," + tmpdq
iraf.imdelete(images)
if ext[-2] == "1": iraf.copy(inIm, "x" + inIm)
iraf.imcopy(inIm + ext, tmp)
iraf.fixpix(tmp, plMask, linterp="1,2,3,4")
iraf.imcopy(tmp + "[*,*]", "x" + inIm + ext + "[*,*]")
iraf.imarith(plMask, "+", "x" + inIm + "[DQ," + ext[-2:], tmpdq)
iraf.imcopy(tmpdq + "[*,*]", "x" + inIm + "[DQ," + ext[-2:] + \
"[*,*]")
# display result
iraf.display("x" + inIm + ext)
# delete temporary files
iraf.imdelete(images)
return
# function to flux calibrate extracted object spectra
def calibFlux(self, inIm, **kwargs):
print "\nCALIBRATING FLUX IN " + inIm
# determine which extinction file to use
hdu = fits.open(inIm)
if hdu[0].header["OBSERVAT"] == "Gemini-North":
self.extDat = "gmos$calib/mkoextinct.dat"
else:
self.extDat = "onedstds$ctioextinct.dat"
# determine which sensitivity function to use
centWave = str(int(hdu[0].header["CENTWAVE"]))
sFunc = self.sFunc.replace("X", centWave)
hdu.close()
# delete previous flux calibrated spectra and generate new one
iraf.imdelete("c" + inIm)
iraf.gscalibrate(inIm, sfunction=sFunc, extinction=self.extDat, **kwargs)
# view the result
print "Displaying calibrated data cube"
self.viewCube("c" + inIm, version="1")
return
# function to clean cosmic ray hits from exposures
def cleanCosRays(self, inIm, pref="x", **kwargs):
print "\nCLEANING COSMIC RAYS FROM " + inIm
iraf.imdelete(pref + inIm)
iraf.gemcrspec(inIm, pref + inIm, **kwargs)
return
# function to compute sensitivity function b/o observed flux standard
def compSensFunc(self, inIm, **kwargs):
print "\nCOMPUTING SENSITIVITY FUNCTION FROM " + inIm
suffStart = inIm.find(".")
date = inIm[suffStart - 13:suffStart - 5]
hdu = fits.open(inIm)
tgtName = hdu[0].header["OBJECT"]
centWave = str(int(hdu[0].header["CENTWAVE"]))
hdu.close()
outFlux = tgtName + "_" + centWave + "_" + date + "_flux.txt"
sFunc = tgtName + "_" + centWave + "_" + date + "_sFunc"
iraf.gsstandard(inIm, sfile=outFlux, sfunction=sFunc, **kwargs)
return
# function to correct exposures for QE changes between CCD chips
def correctQE(self, inIm, **kwargs):
print "\nCORRECTING QE IN " + inIm
# delete previous correction data and QE-corrected exposure
iraf.imdelete("q" + inIm)
iraf.imdelete("qecorr" + kwargs["refimages"])
iraf.gqecorr(inIm, **kwargs)
return
# function to extract spectra from the fibers and build a datacube
def extractSpec(self, inIm, **kwargs):
print "\nEXTRACTING SPECTRA FROM", inIm
# destroy previous extracted spectra
iraf.imdelete("e" + inIm)
# extract the spectra and view the result
iraf.gfextract(inIm, **kwargs)
self.viewCube("e" + inIm, frame=1, z1=0., z2=0., extname="SCI", \
version="*")
return
# function to rectify IFU spectra using established wavelength calibration
def rectifySpec(self, inIm, **kwargs):
# remove previous rectified spectra
iraf.imdelete("t" + inIm)
# transform the spectra and view the result
iraf.gftransform(inIm, **kwargs)
print "\nDisplaying 2D spectra"
iraf.display("t" + inIm + "[SCI]")
return
# function to perform a tailored set of reductions on an IFU exposure
def reduceIm(self, inIm, **kwargs):
print "\nREDUCING", inIm
# remove previously reduced exposures
inPref = inIm[:inIm.find(".") - 14]
if inPref == "":
outPref = "g"
images = outPref + inIm
outPref = "r" + outPref
images += "," + outPref + inIm
else:
outPref = ""
images = ""
if "fl_gscrrej" in kwargs.keys() and kwargs["fl_gscrrej"] == "yes":
outPref = "x" + outPref
images += "," + outPref + inIm
else:
pass
if "fl_scatsub" in kwargs.keys() and kwargs["fl_scatsub"] == "yes":
outPref = "b" + outPref
images += "," + outPref + inIm
else:
pass
if "fl_qecorr" in kwargs.keys() and kwargs["fl_qecorr"] == "yes":
outPref = "q" + outPref
images += "," + outPref + inIm
else:
pass
if "fl_extract" in kwargs.keys() and kwargs["fl_extract"] == "no":
pass
else:
outPref = "e" + outPref
images += "," + outPref + inIm
iraf.imdelete(images)
# reduce the image
iraf.gfreduce(inIm, **kwargs)
return
# function to resample a data cube onto a regular 3D grid
def resampCube(self, inIm, **kwargs):
print "\nRESAMPLING DATA CUBE IN " + inIm
# determine name of output and delete previous version (if present)
if "outimage" in kwargs.keys():
outIm = kwargs["outimage"]
elif "outprefix" in kwargs.keys():
outIm = kwargs["outprefix"] + inIm
else:
outIm = "d" + inIm
iraf.imdelete(outIm)
# resample the data cube
iraf.gfcube(inIm, **kwargs)
# view white-light image
self.viewWhiteIm(outIm, **kwargs)
# view cube as movie in wavelength
self.viewCubeMov(outIm)
return
# function to run the pipeline following the steps in K Labrie's tutorial
def run(self):
imPaths = utils.getImPaths(self.imList)
for i, im in enumerate(imPaths):
# attach MDF, subtract the bias+overscan, and trim the overscan
if self.steps["reduceIm"]:
logFile = self.logRoot + "_reduceIm.log"
# TODO: remove hard-coding of slits and mdfdir parms
self.reduceIm(im, rawpath=self.rawPath, slits="both", \
fl_over="yes", fl_trim="yes", fl_gscrrej="no", \
fl_wavtran="no", fl_skysub="no", fl_extract="no", \
fl_fluxcal="no", fl_inter="no", fl_vardq="yes", \
bias=self.bias, mdffile=self.mdf, mdfdir="./", \
logfile=logFile, verbose="no")
# model and subtract the scattered light
if self.steps["subScatLgt"]:
self.subScatLgt("rg" + im, self.calPath + "blkMask_" + \
self.flats[i], prefix = "b", fl_inter="yes", cross="yes")
# clean the cosmic rays
if self.steps["cleanCosRays"]:
logFile = self.logRoot + "_cleanCosRays.log"
self.cleanCosRays("brg" + im, fl_vardq="yes", xorder=9, \
yorder=-1, sigclip=4.5, sigfrac=0.5, objlim=1.0, niter=4, \
key_ron="RDNOISE", key_gain="GAIN", logfile=logFile, \
verbose="no")
# correct for QE changes
if self.steps["correctQE"]:
logFile = self.logRoot + "_correctQE.log"
# retrieve arc of matching central wavelength
arc = utils.matchCentWave(im, self.rawPath, self.arcList, "arc/")
refIm = "erg" + arc
os.system("mv " + self.calPath + refIm + " ./")
self.correctQE("xbrg" + im, refimages=refIm, fl_correct="yes", \
fl_vardq="yes", logfile=logFile, verbose="no")
# return arc from whence it came
os.system("mv " + refIm + " " + self.calPath)
# extract the spectra
if self.steps["extractSpec"]:
logFile = self.logRoot + "_extractSpec.log"
# retrieve flat of matching central wavelength
# TODO: set flat through call to matchCentWave?
flat = self.flats[i]
refIm = "eqbrg" + flat
os.system("mv " + self.calPath + refIm + " ./")
respIm = self.calPath + flat[:flat.find(".")] + "_resp.fits"
self.extractSpec("qxbrg" + im, reference=refIm, \
response=respIm, fl_inter="no", fl_vardq="yes", \
recenter="no", trace="no", weights="none", logfile=logFile, \
verbose="no")
# return flat from whence it came
os.system("mv " + refIm + " " + self.calPath)
# TODO: place this in extractSpec
# view extracted spectra in detector plane
#for j in range(1, 3):
# print "\nDISPLAYING eqxbrg" + im + "[SCI," + str(j) + "]"
# iraf.display("eqxbrg" + im + "[SCI," + str(j) + "]")
# continue
# adjust the mask to cover cosmetics
if self.steps["maskSpec"]:
hdu = fits.open("eqxbrg" + im)
# create a separate mask for each science extension
for j in range(1, hdu[-1].header["EXTVER"] + 1):
txtMask = "mask_" + im[:im.find(".")] + "_" + str(j) + ".txt"
ext = "[SCI," + str(j) + "]"
self.adjustDQ("eqxbrg" + im, ext, txtMask)
# rectify the extracted spectra
if self.steps["rectifySpec"]:
logFile = self.logRoot + "_rectifySpec.log"
# retrieve arc of matching central wavelength
arc = utils.matchCentWave(im, self.rawPath, self.arcList, "arc/")
refIm = "erg" + arc
os.system("mv " + self.calPath + refIm + " ./")
# use first spectra to inform choice of final wavelength sampling
print "\nRECTIFYING SPECTRA IN", "xeqxbrg" + im
if i == 0:
self.rectifySpec("xeqxbrg" + im, wavtraname=refIm, \
fl_vardq="no", dw="INDEF", logfile=logFile, verbose="no")
dw = input("\nDesired wavelength sampling: ")
self.rectifySpec("xeqxbrg" + im, wavtraname=refIm, \
fl_vardq="yes", dw=dw, logfile=logFile, verbose="no")
# return arc from whence it came
os.system("mv " + refIm + " " + self.calPath)
# subtract the sky from the object fibers
if self.steps["subSky"]:
logFile = self.logRoot + "_subSky.log"
self.subSky("txeqxbrg" + im, fl_inter="no", logfile=logFile, \
verbose="no")
# flux calibrate the spectra
if self.steps["calibFlux"]:
logFile = self.logRoot + "_calibFlux.log"
self.calibFlux("stxeqxbrg" + im, fl_vardq="yes", fl_ext="yes", \
logfile=logFile, verbose="no")
# resample the data cube
if self.steps["resampCube"]:
logFile = self.logRoot + "_resampCube.log"
self.resampCube("cstxeqxbrg" + im, fl_atmdisp="yes", \
fl_var="yes", fl_dq="yes", logfile=logFile)
continue
# stack data cubes
if self.steps["stackCubes"]:
logFile = self.logRoot + "_stackCubes.log"
# make list of data cubes
cubeList = "cubeFiles.txt"
cmd = "ls dcstxeqxbrg* > " + cubeList
os.system(cmd)
# combine data cubes
self.stackCubes(cubeList)
# remove list
cmd = "rm -v " + cubeList
os.system(cmd)
return
# function to stack several data cubes into single one
def stackCubes(self, cubeList, **kwargs):
outCube = self.target + "_finalCube.fits"
# extract filenames of individual data cubes
cubePaths = utils.getImPaths(cubeList)
cubes = ", ".join(cubePaths)
print "\nCOMBINING DATA CUBES: " + cubes
# make work directory and copy images there
cmd = "mkdir -v scratch/"
os.system(cmd)
for i, cube in enumerate(cubePaths):
cmd = "cp -v " + cube + " scratch/"
os.system(cmd)
cubePaths[i] = "scratch/" + cube
# update the WCS header cards of the cubes to their centroids
# TODO: allow for lower pixel limit?
# TODO: put calls to pyfalign and pyfmosaic into iterative loop?
pyfu.pyfalign(cubePaths, method="centroid", llimit=0)
# resample and align the cubes without stacking them
# TODO: add line below to view alignment
iraf.imdelete("scratch/separatedCubes.fits")
pyfu.pyfmosaic(cubePaths, "scratch/separatedCubes.fits", separate="yes")
# stack the aligned cubes and view the result
# (both as white-light image and slow-paced movie)
iraf.imdelete(outCube)
pyfu.pyfmosaic(cubePaths, outCube, propvar="yes")
self.viewWhiteIm(outCube)
time.sleep(30)
self.viewCubeMov(outCube)
# remove work directory and its contents
cmd = "rm scratch/*.fits"
os.system(cmd)
cmd = "rmdir scratch/"
os.system(cmd)
return
# function to subtract scattered light b/o bundle gaps identified from flats
def subScatLgt(self, inIm, mask, **kwargs):
print "\nSUBTRACTING SCATTERED LIGHT FROM", inIm
pref = kwargs["prefix"]
# allow user to iterate over orders used to model scattered light
while True:
fixScat = bool(input("\nDoes subtraction of scattered light need improvement? (True/False): "))
if fixScat:
# request orders from user
xOrders = raw_input("X orders (csv): ")
yOrders = raw_input("Y orders (csv): ")
# model and subtract the light, and view the result
iraf.imdelete(pref + inIm)
iraf.gfscatsub(inIm, mask, xorder=xOrders, yorder=yOrders, \
**kwargs)
utils.examIm(pref + inIm + "[SCI]", frame=1)
else:
break
return
# function to subtract the sky component from the object fibers
def subSky(self, inIm, **kwargs):
print "\nSUBTRACTING SKY FROM " + inIm
# delete previous sky-subtracted spectra
iraf.imdelete("s" + inIm)
# subtract the sky and view the result (as image and datacube)
iraf.gfskysub(inIm, **kwargs)
print "\nDisplaying 2D spectra"
iraf.display("s" + inIm + "[SCI]")
print "\nDisplaying data cube"
self.viewCube("s" + inIm, extname="SCI", version="1")
return
# function to sum all the spectra from a datacube into one
def sumFibers(self, inIm, **kwargs):
print "\nSUMMING FIBERS FROM " + inIm
# delete previous summed spectra
# TODO: add attribute to class to turn imdelete verifications on/off
iraf.imdelete("a" + inIm)
# sum the fibers and view the final spectrum
iraf.gfapsum(inIm, **kwargs)
iraf.splot("a" + inIm + "[SCI,1]")
return
# function to view a cube and its individual spectra
def viewCube(self, cube, **kwargs):
print "\nDISPLAYING DATA CUBE"
iraf.gfdisplay(cube, **kwargs)
return
# function to step through a cube along the wavelength axis
def viewCubeMov(self, inCube, step=10, **kwargs):
print "\nSTEPPING THROUGH " + inCube
# obtain number of wavelength samples in cube
hdul = fits.open(inCube)
nWave = hdul["SCI"].data.shape[0]
# step through cube, summing images within each chunk
cubeChunk = "chunk.fits"
for i in range(0, nWave, step):
iraf.imdelete(cubeChunk)
if i + 9 > nWave - 1:
lastFrame = str(nWave - 1)
else:
lastFrame = str(i + 9)
iraf.imcombine(inCube + "[SCI][*,*," + str(i) + ":" + lastFrame + \
"]", cubeChunk, project="yes", combine="sum", logfile="")
print "Displaying chunk [" + str(i) + ":" + lastFrame + "]"
iraf.display(cubeChunk, frame="1", contrast=0.)
time.sleep(2)
# delete the last wavelength chunk and close the cube
iraf.imdelete(cubeChunk)
hdul.close()
return
# function to make and display a white-light image from the cube
def viewWhiteIm(self, inIm, **kwargs):
print "\nDISPLAYING WHITE-LIGHT IMAGE"
idx = inIm.find(".")
#whiteIm = inIm[:idx] + "_2d.fits"
whiteIm = "whiteIm_" + inIm
iraf.imdelete(whiteIm)
iraf.imcombine(inIm + "[SCI]", whiteIm, project="yes", combine="sum", \
logfile="")
iraf.display(whiteIm)
return
if __name__ == "__main__":
# set root filename of logs
target = "v1895"
logRoot = target + "_sci"
# declare which steps of pipeline to execute
pipeSteps = {}
pipeSteps["reduceIm"] = False
pipeSteps["subScatLgt"] = False
pipeSteps["cleanCosRays"] = False
pipeSteps["correctQE"] = False
pipeSteps["extractSpec"] = False
pipeSteps["maskSpec"] = False
pipeSteps["rectifySpec"] = False
pipeSteps["subSky"] = False
pipeSteps["calibFlux"] = False
pipeSteps["resampCube"] = False
pipeSteps["stackCubes"] = True
# setup object for VCC1895 and run pipeline
v1895_sci = ReduceIfuObj("targetFiles.txt", target=target, steps=pipeSteps, \
rawPath="target/", calPath="calibrations/", mdf="gsifu_slits_mdf.fits", \
biasIm=target + "_masterBias.fits", flatList="flatFiles.txt", \
arcDir="arc/", arcList="arcFiles.txt", \
sFunc="LTT7379_X_20080607_sFunc.fits", logRoot=logRoot)
v1895_sci.run()