def do_pedsub( pedparname, Trl, pedtrlname, file_1, file_2, kwpars, saapername):
""" Call pedsub
@param pedparname: parameter file name
@type pedparname: string
@param Trl: trailer file name
@type Trl: string
@param pedtrlname: pedsub's trailer file name
@type pedtrlname: string
@param file_1: name of input cal file
@type file_1: string
@param file_2: name of output ped file
@type file_2: string
@param kwpars: keyword params for pedsub
@type kwpars: dict
@param saapername: name of file for SAA persistence image
@type saapername: string
"""
pedsub_complete='=== PEDSUB finished'
# Timestamp the trailer file
Trl.write(_timestamp('PEDSUB starting with paramas from %s'%pedparname))
# Run pedsub with output directed to special file
iraf.flprcache()
iraf.pedsub.unlearn()
iraf.pedsub(input = file_1, output = file_2, Stdout = pedtrlname, **kwpars)
# Examine task output & append to trailer file
pedout = open( pedtrlname )
for line in pedout:
Trl.write( line )
pedout.close()
os.remove(pedtrlname)
if not line.startswith(pedsub_complete):
raise PedsubError
def imgets(img, field):
iraf.flprcache()
iraf.flprcache()
iraf.imgets(img, field)
return iraf.imgets.value
def imgets(img,field): iraf.flprcache() iraf.flprcache() iraf.imgets(img,field) return iraf.imgets.value
def coaddImages(workdir, coaddfile=None, method='median'):
'''
Combine aligned images, masking out bad pixels using transformed
masks
@parameter coaddfile path to output coadded file to be produced by
this method. None defaults to the workdir.
@parameter method Method for combining images. See IRAF's imcombine
for additional options
'''
print "Reading database..."
db = readpickle(os.path.join(workdir, "db.pkl"))
rejectimages = []
for image in db:
## reject images with unphysical transformations.
## e.g., those rotated too much
if image['geomapangle'] > 15. and image['geomapangle'] < 345:
image['okforalignment'] = False
rejectimages.append(image['rawimgname'])
db = [image for image in db if image['okforalignment'] == True]
if len(db) == 0:
print "Cannot continue, no matching images!"
return
print "Ok, we have %i images to combine." % len(db)
curdir = os.getcwd()
os.chdir(workdir)
if coaddfile is None:
coaddfile = 'coadd.fits'
starttime = datetime.now()
iraf.images()
iraf.immatch()
inputimages = []
outnames = []
## sub-grouping the files
numberofGroups = int(len(db) / 30.) + 1
for i in range(numberofGroups - 1):
inputimages.append(','.join(
[image['aliimgname'] for image in db[i * 30:(i + 1) * 30]]))
outnames.append(coaddfile + '_{0}.fits'.format(i))
if len(db) % 30 != 0:
## handling the remaining not-grouped files
inputimages.append(','.join(
[image['aliimgname'] for image in db[(numberofGroups - 1) * 30:]]))
outnames.append(coaddfile + '_{0}.fits'.format(numberofGroups - 1))
print "divied the images in {} groups".format(numberofGroups)
for i in range(len(inputimages)):
iraf.flprcache()
iraf.imcombine(input=inputimages[i],
output=outnames[i],
combine=method,
masktype='goodvalue')
iraf.flprcache()
iraf.imcombine(input=outnames[i],
output=coaddfile,
combine=method,
masktype='goodvalue')
print "- " * 40
endtime = datetime.now()
timetaken = nicetimediff(endtime - starttime)
os.chdir(curdir)
print "Dear user, I'm done with the alignment. I did it in %s." % timetaken
print "The following are rejected: \n{0}".format(rejectimages)
## Update the db :
writepickle(db, os.path.join(workdir, "db.pkl"))
print "Central reference pixel is: ", central_pixel
shift = peak_pos - central_pixel
print "Shift between two images is: ",shift
if shift != 0: #this should always be the case bc we know it's tilted but I ran into this when the sample size was small
slope = (line2y2 - line1y2) / shift
#this is where I will be copying the image over row-by-row; the iterator is moving up in rows
#now I can't actually 'slide' a row, since the image section I have to put it into needs to be the same size. I'll have to select only the part of the image I need (not-selecting the amount determined from the tilt) and copy that over to the full sized row <-- hopefully this will automatically pad it with 0's, otherwise I may have to make it up some how? Otherwise, when the skyline is straight the slit as a whole will be tilted, and I don't think I can go past the already existing boundaries of the slit I'm copying into.
#The y_expansion factor is here because the slit_width doesn't reflect the iraf.blkrep change
for row in range(2,int(mod_slit_width)+2): #that range bc IRAF starts at 1 and need to reach slit end
iraf.flprcache()
new_y1 = row-1
new_y2 = row
try:
#If there is a negative slope, I correct the tilt by altering the x1 from image2. In this case, as I increase in y, the correction needs to push the rows to the right. To do that I can copy the full row from image1 to start at the corrected position in image2.
#the correction is just inverting the slope-intercept form of y = mx + b to solve for x (which is (y-b)/m = x)
if slope < 0:
correction = row / -slope
corrected_x1 = round(secx1 + correction) #coordinate x1 position of where row goes to in image2
#corrected_x2 = secx2 - corrected_x1 #so the image end fits just to the end of image2
image1 = '%s[%d][%d:%d,%d:%d]' % (filename,ext_num,secx1,mod_secx2,new_y1,new_y2)
image2 = '%s[%d][%d:%d,%d:%d]' % (corrected_file,ext_num,corrected_x1,mod_secx2,new_y1,new_y2)
imcopy_output = iraf.imcopy(image1,image2, Stdout=1)
imcopy_log.write('%s\n' % imcopy_output)
#does this make the x-dimension of the corrected slit less than 6218?