def _iraf_pset_init():
"""Initialize common IRAF tasks for pset tests
"""
if not HAS_IRAF:
return
# imports & package loading
iraf.stsdas(_doprint=0)
iraf.imgtools(_doprint=0)
iraf.mstools(_doprint=0)
# reset PSET egstp's values
_unlearn_egstp(iraf.egstp)
def _iraf_dqbits_init(_data):
"""Initialize common IRAF tasks for dqbits tests
"""
if not HAS_IRAF:
return
# imports & package loading
iraf.stsdas(_doprint=0)
iraf.imgtools(_doprint=0)
iraf.artdata(_doprint=0)
iraf.mstools(_doprint=0)
# create two data files as input (dont care if appropriate to mscombine)
iraf.imcopy('dev$pix', _data['dqbits']['input1'])
iraf.imcopy('dev$pix', _data['dqbits']['input2'])
from scipy.optimize import curve_fit
import os
os.environ[
'oref'] = '/Users/cmccully/Documents/sne/sn2013dh/cti_corrected/ref/references/hst/oref/'
os.environ[
'ctirefs'] = '/Users/cmccully/Documents/sne/sn2013dh/cti_corrected/ref'
from astroscrappy import detect_cosmics
from pyraf import iraf
iraf.stsdas()
iraf.hst_calib()
iraf.stis()
iraf.mstools()
iraf.fitting()
iraf.longslit()
import stistools
iraf.twodspec()
iraf.apextract()
iraf.onedspec()
iraf.set(ctirefs='/Users/cmccully/Documents/sne/sn2013dh/cti_corrected/ref/')
iraf.set(clobber='YES')
def gauss(x, a, x0, sigma, sky):
return a * exp(-(x - x0)**2 / (2 * sigma**2) + sky)
from astropy.io import fits
from numpy import isnan,min,logical_and,bitwise_and,linspace,median,arange,correlate, average, exp
from scipy.interpolate import interp1d
from scipy.integrate import trapz
from scipy.optimize import curve_fit
import os
os.environ['oref'] = '/Users/cmccully/Documents/sne/sn2013dh/cti_corrected/ref/references/hst/oref/'
os.environ['ctirefs'] = '/Users/cmccully/Documents/sne/sn2013dh/cti_corrected/ref'
from astroscrappy import detect_cosmics
from pyraf import iraf
iraf.stsdas()
iraf.hst_calib()
iraf.stis()
iraf.mstools()
iraf.fitting()
iraf.longslit()
import stistools
iraf.twodspec()
iraf.apextract()
iraf.onedspec()
iraf.set(ctirefs='/Users/cmccully/Documents/sne/sn2013dh/cti_corrected/ref/')
iraf.set(clobber='YES')
def gauss(x, a, x0, sigma, sky):
return a * exp(-(x - x0) ** 2 / (2 * sigma ** 2) + sky)
def tofits(filename, data, hdr=None,clobber=False):