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raw2extract.py
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executable file
·354 lines (307 loc) · 16.4 KB
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#!/usr/bin/env python
#!/user/covey/iraf/mypython
import os
import numpy as np
from pyraf import iraf
from pyraf.iraf import noao
from pyraf.iraf import imutil, imred, crutil, ccdred, echelle, images, tv
from pyraf.iraf import system, twodspec, longslit, apextract, onedspec, astutil
from list_utils import read_reduction_list
import pdb
def raw2extract(instrument, imagelist='to_reduce.lis', apall_interactive='yes'):
'''
This function performs the following tasks:
* combines the biases into masterbias.fits (for Modspec only)
* runs CCD proc on all images to apply overscan correction (Modspec only), master bias correction (Modspec only), and trim images
* clean science images with cosmicrays
* combine flats into masterflat.fits
IMPORTANT: If instrument is OSMOS, then the bias correction steps should be done with OSMOS_bias.py before running this function.
Once the masterflat has been normalized by the response, the function will use normflat.fits to flat-divide each (2-D) spectrum with ccdproc.
The function then asks the user to help extract the science targets and flux standards. This is done with standard apall tasks -- for more on this, see "A User's Guide to Reducing Slit Spectra with IRAF" by Phil Massey.
instrument - String; it can be Modspec, OSMOS4k, or OSMOSr4k (not case sensitive).
imagelist - String; filename (produced by list_utils.prep()) with list of spectra to process .
apall_interactive - String; it can be yes or no. Whether to interactively select and fit traces and apertures for each image.
Kevin Covey
version 1.0 (Last Modified 3-12-12; segment of former MODpipeline.py code)
Stephanie Douglas
version 2.0 (Last Modified 4-23-15)
Alejandro Nunez
version: 2.1 (Last modified on 2017-11)
'''
image_dict = read_reduction_list(imagelist)
# Split out the relevant lists
# and make them arrays for marginally faster readout
flat_list = np.array(image_dict["flat"])
lamp_list = np.array(image_dict["lamp"])
if instrument.upper() == 'MODSPEC':
bias_list = np.array(image_dict["bias"])
science_list = np.array(image_dict["science_list"])
science_names = np.array(image_dict["science_names"])
std_list = np.array(image_dict["std"])
std_names = np.array(image_dict["std_names"])
# Find the number of objects in each list
numflats = len(flat_list)
numlamps = len(lamp_list)
numscience = len(science_list)
if instrument.upper() == 'MODSPEC':
numbiases = len(bias_list)
numstds = len(std_list)
overscanregion = image_dict["overscan_region"]
gooddata = image_dict["good_region"]
print "{} Science images".format(numscience)
# Define gain and read noise
if instrument.upper() == 'MODSPEC':
gain = '2.7' # taken from header in Dec. 2010, but matches 1997 docs.
elif instrument.upper() == 'OSMOS4K':
gain = '2.7'
elif instrument.upper() == 'OSMOSR4K':
gain = '1.0' # Unknown as of Nov 2017
readnoise = '7.9' # taken from web documentation dated 1997
# Combine biases into master biases of each color
if instrument.upper() == 'MODSPEC':
biasestocombine = ''
for bias_file in bias_list:
biasestocombine = biasestocombine + ", {}".format(bias_file)
# Remove that first comma
biasestocombine = biasestocombine[2:]
iraf.noao.imred.ccdred.zerocombine.combine = 'median'
iraf.noao.imred.ccdred.zerocombine.reject = 'minmax'
iraf.noao.imred.ccdred.zerocombine.ccdtype = ''
iraf.noao.imred.ccdred.zerocombine.process = 'no'
iraf.noao.imred.ccdred.zerocombine.delete = 'no'
iraf.noao.imred.ccdred.zerocombine.clobber = 'no'
iraf.noao.imred.ccdred.zerocombine.scale = 'no'
iraf.noao.imred.ccdred.zerocombine.statsec = ''
iraf.noao.imred.ccdred.zerocombine.nlow = '0'
iraf.noao.imred.ccdred.zerocombine.nhigh = '1'
iraf.noao.imred.ccdred.zerocombine.nkeep = '1'
iraf.noao.imred.ccdred.zerocombine.mclip = 'yes'
iraf.noao.imred.ccdred.zerocombine.lsigma = '3.0'
iraf.noao.imred.ccdred.zerocombine.hsigma = '3.0'
iraf.noao.imred.ccdred.zerocombine.rdnoise = readnoise
iraf.noao.imred.ccdred.zerocombine.gain = gain
iraf.noao.imred.ccdred.zerocombine.snoise = '0.' #last thing that should change
iraf.noao.imred.ccdred.zerocombine.pclip = '-0.5'
iraf.noao.imred.ccdred.zerocombine.blank = '0.0'
iraf.noao.imred.ccdred.zerocombine(input = biasestocombine, output = 'masterbias')
# Trim all the images and store them in a trimmed, overscan region
iraf.noao.imred.ccdred.ccdproc.ccdtype = ''
iraf.noao.imred.ccdred.ccdproc.noproc = 'no'
iraf.noao.imred.ccdred.ccdproc.fixpix = 'no'
if 'OSMOS' in instrument.upper():
iraf.noao.imred.ccdred.ccdproc.overscan = 'no'
iraf.noao.imred.ccdred.ccdproc.zerocor = 'no'
else:
iraf.noao.imred.ccdred.ccdproc.overscan = 'yes'
iraf.noao.imred.ccdred.ccdproc.zerocor = 'yes'
iraf.noao.imred.ccdred.ccdproc.trim = 'yes'
iraf.noao.imred.ccdred.ccdproc.darkcor = 'no'
iraf.noao.imred.ccdred.ccdproc.flatcor = 'no'
iraf.noao.imred.ccdred.ccdproc.illumcor = 'no'
iraf.noao.imred.ccdred.ccdproc.fringecor = 'no'
iraf.noao.imred.ccdred.ccdproc.readcor = 'no'
iraf.noao.imred.ccdred.ccdproc.scancor = 'no'
iraf.noao.imred.ccdred.ccdproc.readaxis = 'line'
iraf.noao.imred.ccdred.ccdproc.interactive = 'no'
iraf.noao.imred.ccdred.ccdproc.function = 'legendre'
iraf.noao.imred.ccdred.ccdproc.order = '1'
iraf.noao.imred.ccdred.ccdproc.sample = '*'
iraf.noao.imred.ccdred.ccdproc.naverage = '1'
iraf.noao.imred.ccdred.ccdproc.niterate = '1'
iraf.noao.imred.ccdred.ccdproc.low_reject = '3.0'
iraf.noao.imred.ccdred.ccdproc.high_reject = '3.0'
os.mkdir('trimmed')
if 'OSMOS' in instrument.upper():
iraf.noao.imred.ccdred.ccdproc.biassec = ''
else:
iraf.noao.imred.ccdred.ccdproc.biassec = overscanregion
iraf.noao.imred.ccdred.ccdproc.trimsec = gooddata
iraf.noao.imred.ccdred.ccdproc.zero = 'masterbias'
for science_file in science_list:
iraf.noao.imred.ccdred.ccdproc(images = science_file,
output = 'trimmed/tr.' + science_file)
for flat_file in flat_list:
iraf.noao.imred.ccdred.ccdproc(images = flat_file,
output = 'trimmed/tr.' + flat_file)
for lamp_file in lamp_list:
iraf.noao.imred.ccdred.ccdproc(images = lamp_file,
output = 'trimmed/tr.' + lamp_file)
# Clean out the cosmic rays (just from the science images)
os.mkdir('cleaned')
iraf.unlearn(iraf.imred.crutil.cosmicrays)
iraf.imred.crutil.cosmicrays.threshold = '25'
iraf.imred.crutil.cosmicrays.fluxratio = '2'
iraf.imred.crutil.cosmicrays.npasses = '5'
iraf.imred.crutil.cosmicrays.window = '5'
iraf.imred.crutil.cosmicrays.interactive = 'no'
for science_file in science_list:
print "cleaning " + science_file
iraf.imred.crutil.cosmicrays(input = 'trimmed/tr.' + science_file,
output = 'cleaned/cr.' + science_file)
# Combine the flats and use response on the master flats
flatstocombine = ''
for flat_file in flat_list:
flatstocombine = flatstocombine + ", {}".format(flat_file)
# Remove that first comma
flatstocombine = flatstocombine[2:]
iraf.noao.imred.ccdred.flatcombine.combine = 'average'
iraf.noao.imred.ccdred.flatcombine.reject = 'avsigclip'
iraf.noao.imred.ccdred.flatcombine.ccdtype = ''
iraf.noao.imred.ccdred.flatcombine.process = 'no'
iraf.noao.imred.ccdred.flatcombine.subsets = 'no'
iraf.noao.imred.ccdred.flatcombine.delete = 'no'
iraf.noao.imred.ccdred.flatcombine.clobber = 'no'
iraf.noao.imred.ccdred.flatcombine.scale = 'mode'
iraf.noao.imred.ccdred.flatcombine.nlow = '0'
iraf.noao.imred.ccdred.flatcombine.nhigh = '1'
iraf.noao.imred.ccdred.flatcombine.nkeep = '1'
iraf.noao.imred.ccdred.flatcombine.mclip = 'yes'
iraf.noao.imred.ccdred.flatcombine.lsigma = '3.0'
iraf.noao.imred.ccdred.flatcombine.hsigma = '3.0'
iraf.noao.imred.ccdred.flatcombine.rdnoise = readnoise
iraf.noao.imred.ccdred.flatcombine.gain = gain
iraf.noao.imred.ccdred.flatcombine.snoise = '0.' #last thing that should change
iraf.noao.imred.ccdred.flatcombine.pclip = '-0.5'
iraf.noao.imred.ccdred.flatcombine.blank = '0.0'
iraf.noao.imred.ccdred.flatcombine(input = flatstocombine, output = 'masterflat')
if 'OSMOS' in instrument.upper():
iraf.noao.twodspec.longslit.dispaxis = '1' # horizontal dispersion
else:
iraf.noao.twodspec.longslit.dispaxis = '2' # vertical dispersion
iraf.noao.twodspec.longslit.response.interactive = 'yes'
iraf.noao.twodspec.longslit.response.threshold = 'INDEF'
iraf.noao.twodspec.longslit.response.sample = '*'
iraf.noao.twodspec.longslit.response.naverage = '1'
iraf.noao.twodspec.longslit.response.function = 'spline3'
iraf.noao.twodspec.longslit.response.order = '11'
iraf.noao.twodspec.longslit.response.low_reject = '3.'
iraf.noao.twodspec.longslit.response.high_reject = '3.'
iraf.noao.twodspec.longslit.response.niterate = '1'
iraf.noao.twodspec.longslit.response.grow = '0'
iraf.noao.twodspec.longslit.response(calibration = 'masterflat', normalization = 'masterflat', response = 'normflat')
# Do the flat division
iraf.noao.imred.ccdred.ccdproc.ccdtype = ''
iraf.noao.imred.ccdred.ccdproc.noproc = 'no'
iraf.noao.imred.ccdred.ccdproc.fixpix = 'no'
iraf.noao.imred.ccdred.ccdproc.overscan = 'no'
iraf.noao.imred.ccdred.ccdproc.trim = 'no'
iraf.noao.imred.ccdred.ccdproc.zerocor = 'no'
iraf.noao.imred.ccdred.ccdproc.darkcor = 'no'
iraf.noao.imred.ccdred.ccdproc.flatcor = 'yes'
iraf.noao.imred.ccdred.ccdproc.illumcor = 'no'
iraf.noao.imred.ccdred.ccdproc.fringecor = 'no'
iraf.noao.imred.ccdred.ccdproc.readcor = 'no'
iraf.noao.imred.ccdred.ccdproc.scancor = 'no'
if 'OSMOS' in instrument.upper():
iraf.noao.imred.ccdred.ccdproc.readaxis = 'column'
else:
iraf.noao.imred.ccdred.ccdproc.readaxis = 'line'
iraf.noao.imred.ccdred.ccdproc.interactive = 'no'
iraf.noao.imred.ccdred.ccdproc.function = 'legendre'
iraf.noao.imred.ccdred.ccdproc.order = '1'
iraf.noao.imred.ccdred.ccdproc.sample = '*'
iraf.noao.imred.ccdred.ccdproc.naverage = '1'
iraf.noao.imred.ccdred.ccdproc.niterate = '1'
iraf.noao.imred.ccdred.ccdproc.low_reject = '3.0'
iraf.noao.imred.ccdred.ccdproc.high_reject = '3.0'
os.mkdir('flattened')
iraf.noao.imred.ccdred.ccdproc.flat = 'normflat'
for science_file in science_list:
iraf.noao.imred.ccdred.ccdproc(images = 'cleaned/cr.' + science_file,
output = 'flattened/fl.' + science_file)
#iraf.imcopy('cleaned/cr.' + science_file,'flattened/fl.' + science_file)
iraf.unlearn(iraf.noao.twodspec.apextract.apall)
if 'OSMOS' in instrument.upper():
iraf.noao.twodspec.apextract.dispaxis = '1' # horizontal dispersion
else:
iraf.noao.twodspec.apextract.dispaxis = '2' # vertical dispersion
iraf.noao.twodspec.apextract.apall.apertures = '1'
iraf.noao.twodspec.apextract.apall.format = 'multispec'
iraf.noao.twodspec.apextract.apall.references = ''
iraf.noao.twodspec.apextract.apall.profiles = ''
iraf.noao.twodspec.apextract.apall.interactive = apall_interactive
iraf.noao.twodspec.apextract.apall.find = 'yes'
iraf.noao.twodspec.apextract.apall.recenter = 'yes'
iraf.noao.twodspec.apextract.apall.resize = 'yes'
iraf.noao.twodspec.apextract.apall.edit = 'yes'
iraf.noao.twodspec.apextract.apall.trace = 'yes'
iraf.noao.twodspec.apextract.apall.fittrace = 'yes'
iraf.noao.twodspec.apextract.apall.extract = 'yes'
iraf.noao.twodspec.apextract.apall.extras = 'yes'
iraf.noao.twodspec.apextract.apall.review = 'no'
iraf.noao.twodspec.apextract.apall.line = 'INDEF'
iraf.noao.twodspec.apextract.apall.nsum = '10'
iraf.noao.twodspec.apextract.apall.lower = '-5'
iraf.noao.twodspec.apextract.apall.upper = '5'
iraf.noao.twodspec.apextract.apall.b_function = 'chebyshev'
iraf.noao.twodspec.apextract.apall.b_order = '2'
iraf.noao.twodspec.apextract.apall.b_sample = '-30:-18,18:30'
iraf.noao.twodspec.apextract.apall.b_naverage = '-100'
iraf.noao.twodspec.apextract.apall.b_niterate = '3'
iraf.noao.twodspec.apextract.apall.b_low_reject = '3'
iraf.noao.twodspec.apextract.apall.b_high_reject = '3'
iraf.noao.twodspec.apextract.apall.b_grow = '0'
iraf.noao.twodspec.apextract.apall.width = '10'
iraf.noao.twodspec.apextract.apall.radius = '10'
iraf.noao.twodspec.apextract.apall.threshold = '0'
iraf.noao.twodspec.apextract.apall.nfind = '1'
iraf.noao.twodspec.apextract.apall.minsep = '5'
iraf.noao.twodspec.apextract.apall.maxsep = '1000'
iraf.noao.twodspec.apextract.apall.order = 'increasing'
iraf.noao.twodspec.apextract.apall.aprecenter = ''
iraf.noao.twodspec.apextract.apall.npeaks = 'INDEF'
iraf.noao.twodspec.apextract.apall.shift = 'no'
iraf.noao.twodspec.apextract.apall.llimit = 'INDEF'
iraf.noao.twodspec.apextract.apall.ulimit = 'INDEF'
iraf.noao.twodspec.apextract.apall.ylevel = '.2'
iraf.noao.twodspec.apextract.apall.peak = 'yes'
iraf.noao.twodspec.apextract.apall.bkg = 'yes'
iraf.noao.twodspec.apextract.apall.r_grow = '0.'
iraf.noao.twodspec.apextract.apall.avglimits = 'no'
iraf.noao.twodspec.apextract.apall.t_nsum = '10'
iraf.noao.twodspec.apextract.apall.t_step = '10'
iraf.noao.twodspec.apextract.apall.t_nlost = '5'
iraf.noao.twodspec.apextract.apall.t_function = 'legendre'
iraf.noao.twodspec.apextract.apall.t_order = '5'
iraf.noao.twodspec.apextract.apall.t_sample = '*'
iraf.noao.twodspec.apextract.apall.t_naverage = '1'
iraf.noao.twodspec.apextract.apall.t_niterate = '3'
iraf.noao.twodspec.apextract.apall.t_low_reject = '3'
iraf.noao.twodspec.apextract.apall.t_high_reject = '3'
iraf.noao.twodspec.apextract.apall.t_grow = '0'
iraf.noao.twodspec.apextract.apall.background = 'fit'
iraf.noao.twodspec.apextract.apall.skybox = '1'
iraf.noao.twodspec.apextract.apall.weights = 'variance'
iraf.noao.twodspec.apextract.apall.pfit = 'fit1d'
iraf.noao.twodspec.apextract.apall.clean = 'yes'
iraf.noao.twodspec.apextract.apall.saturation = 'INDEF' #needs to be confirmed
iraf.noao.twodspec.apextract.apall.readnoise = readnoise
iraf.noao.twodspec.apextract.apall.gain = gain
iraf.noao.twodspec.apextract.apall.lsigma = 4
iraf.noao.twodspec.apextract.apall.usigma = 4
iraf.noao.twodspec.apextract.apall.nsubaps = '1'
os.mkdir('extract')
for science_file in science_list:
iraf.noao.twodspec.apextract.apall(input = 'flattened/fl.' + science_file,
output = 'extract/ex.' + science_file)
# Extract a blue and red lamp using the first science object as our trace.
if len(std_list)>0:
trace_ref_image = std_list[0]
else:
trace_ref_image = science_list[0]
iraf.noao.twodspec.apextract.apall.references = 'flattened/fl.' + trace_ref_image
iraf.noao.twodspec.apextract.apall.interactive = 'no'
iraf.noao.twodspec.apextract.apall.find = 'no'
iraf.noao.twodspec.apextract.apall.recenter = 'no'
iraf.noao.twodspec.apextract.apall.resize = 'no'
iraf.noao.twodspec.apextract.apall.edit = 'no'
iraf.noao.twodspec.apextract.apall.trace = 'no'
iraf.noao.twodspec.apextract.apall.fittrace = 'no'
iraf.noao.twodspec.apextract.apall.extract = 'yes'
iraf.noao.twodspec.apextract.apall.background = 'none'
iraf.noao.twodspec.apextract.apall.clean = 'no'
iraf.noao.twodspec.apextract.apall.weights = 'none'
for lamp_file in lamp_list:
iraf.noao.twodspec.apextract.apall(input = 'trimmed/tr.' + lamp_file,
output = 'lamp.'+lamp_file)
iraf.flprcache()