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):