Source code for drizzlepac.sky

#!/usr/bin/env python
"""
This step measures, subtracts and/or equalizes the sky from each
input image while recording the subtracted value in the image header.

:Authors:
    Christopher Hanley, Megan Sosey, Mihai Cara

:License: :doc:`LICENSE`

"""
import os, sys

import numpy as np
from astropy.nddata import interpret_bit_flags

from stsci.tools import fileutil, teal, logutil
import stsci.imagestats as imagestats

from stsci.skypac.skymatch import skymatch
from stsci.skypac.utils import MultiFileLog, ResourceRefCount, ext2str, \
     file_name_components, in_memory_mask, temp_mask_file, openImageEx
from stsci.skypac.parseat import FileExtMaskInfo, parse_at_file

from . import processInput
from .imageObject import imageObject

from . import util
from .version import *


__taskname__= "drizzlepac.sky" #looks in drizzlepac for sky.cfg
_step_num_ = 2  #this relates directly to the syntax in the cfg file


log = logutil.create_logger(__name__, level=logutil.logging.NOTSET)


#this is the user access function
[docs]def sky(input=None,outExt=None,configObj=None, group=None, editpars=False, **inputDict): """ Perform sky subtraction on input list of images Parameters ---------- input : str or list of str a python list of image filenames, or just a single filename configObj : configObject an instance of configObject inputDict : dict, optional an optional list of parameters specified by the user outExt : str The extension of the output image. If the output already exists then the input image is overwritten Notes ----- These are parameters that the configObj should contain by default, they can be altered on the fly using the inputDict Parameters that should be in configobj: ========== =================================================================== Name Definition ========== =================================================================== skymethod 'Sky computation method' skysub 'Perform sky subtraction?' skywidth 'Bin width of histogram for sampling sky statistics (in sigma)' skystat 'Sky correction statistics parameter' skylower 'Lower limit of usable data for sky (always in electrons)' skyupper 'Upper limit of usable data for sky (always in electrons)' skyclip 'Number of clipping iterations' skylsigma 'Lower side clipping factor (in sigma)' skyusigma 'Upper side clipping factor (in sigma)' skymask_cat 'Catalog file listing image masks' use_static 'Use static mask for skymatch computations?' sky_bits 'Integer mask bit values considered good pixels in DQ array' skyfile 'Name of file with user-computed sky values' skyuser 'KEYWORD indicating a sky subtraction value if done by user' in_memory 'Optimize for speed or for memory use' ========== =================================================================== The output from sky subtraction is a copy of the original input file where all the science data extensions have been sky subtracted. """ if input is not None: inputDict['input']=input inputDict['output']=None inputDict['updatewcs']=False inputDict['group']=group else: print("Please supply an input image", file=sys.stderr) raise ValueError configObj = util.getDefaultConfigObj(__taskname__,configObj,inputDict,loadOnly=(not editpars)) if configObj is None: return if not editpars: run(configObj,outExt=outExt)
#this is the function that will be called from TEAL def run(configObj,outExt=None): #now we really just need the imageObject list created for the dataset filelist,output,ivmlist,oldasndict=processInput.processFilenames(configObj['input'],None) imageObjList=processInput.createImageObjectList(filelist,instrpars={},group=configObj['group']) #set up the output names, if no extension given the default will be used #otherwise, the user extension is used and if the file already exists it's overwritten saveFile = False if(outExt not in [None,'','None']): saveFile = True for image in imageObjList: outsky = image.outputNames['outSky'] if outExt not in outsky: outsky = outsky.replace("sky",outExt) image.outputNames['outSky']=outsky log.info(outsky) subtractSky(imageObjList,configObj,saveFile=saveFile) #this is the workhorse looping function def subtractSky(imageObjList,configObj,saveFile=False,procSteps=None): # if neither 'skyfile' nor 'skyuser' are specified, subtractSky will # call _skymatch to perform "sky background matching". When 'skyuser' # is specified, subtractSky will call the old _skysub. if procSteps is not None: procSteps.addStep('Subtract Sky') #General values to use step_name=util.getSectionName(configObj,_step_num_) paramDict = configObj[step_name] if not util.getConfigObjPar(configObj, 'skysub'): log.info('Sky Subtraction step not performed.') _addDefaultSkyKW(imageObjList) if 'skyuser' in paramDict and not util.is_blank(paramDict['skyuser']): kwd = paramDict['skyuser'].lstrip() if kwd[0] == '@': # user's sky values are in a file: log.info("Retrieving user computed sky values from file '{}'" .format(kwd[1:])) _skyUserFromFile(imageObjList, kwd[1:],apply_sky=False) else: # user's sky values are stored in a header keyword: log.info("Retrieving user computed sky values from image " "headers ") log.info("recorded in the '{:s}' header keywords." .format(paramDict['skyuser'])) for image in imageObjList: log.info('Working on sky for: %s' % image._filename) _skyUserFromHeaderKwd(image, paramDict) else: # reset "computedSky" chip's attribute: for image in imageObjList: numchips = image._numchips extname = image.scienceExt for extver in range(1, numchips + 1, 1): chip = image[extname, extver] if not chip.group_member: continue chip.computedSky = None if procSteps is not None: procSteps.endStep('Subtract Sky') return #get the sub-dictionary of values for this step alone and print them out log.info('USER INPUT PARAMETERS for Sky Subtraction Step:') util.printParams(paramDict, log=log) if 'skyfile' in paramDict and not util.is_blank(paramDict['skyfile']): _skyUserFromFile(imageObjList,paramDict['skyfile']) else: # in_memory: if 'in_memory' in configObj: inmemory = configObj['in_memory'] elif len(imageObjList) > 0 and imageObjList[0].inmemory is not None: inmemory = imageObjList[0].inmemory else: inmemory = False # clean: if 'STATE OF INPUT FILES' in configObj and \ 'clean' in configObj['STATE OF INPUT FILES']: clean = configObj['STATE OF INPUT FILES']['clean'] else: clean = True _skymatch(imageObjList, paramDict, inmemory, clean, log) if procSteps is not None: procSteps.endStep('Subtract Sky') def _skymatch(imageList, paramDict, in_memory, clean, logfile): # '_skymatch' converts input imageList and other parameters to # data structures accepted by the "skymatch" package. # It also creates a temporary mask by combining 'static' mask, # DQ image, and user-supplied mask. The combined mask is then # passed to 'skymatch' to be used for excluding "bad" pixels. #header keyword that contains the sky that's been subtracted skyKW = "MDRIZSKY" nimg = len(imageList) if nimg == 0: ml.logentry("Skymatch needs at least one images to perform{0}" \ "sky matching. Nothing to be done.",os.linesep) return # create a list of input file names as provided by the user: user_fnames = [] loaded_fnames = [] filemaskinfos = nimg * [ None ] for img in imageList: user_fnames.append(img._original_file_name) loaded_fnames.append(img._filename) # parse sky mask catalog file (if any): catfile = paramDict['skymask_cat'] if catfile: #extname = imageList[0].scienceExt #assert(extname is not None and extname != '') catfile = catfile.strip() mfindx = parse_at_file(fname = catfile, default_ext = ('SCI','*'), default_mask_ext = 0, clobber = False, fnamesOnly = True, doNotOpenDQ = True, match2Images = user_fnames, im_fmode = 'update', dq_fmode = 'readonly', msk_fmode = 'readonly', logfile = MultiFileLog(console=True), verbose = True) for p in mfindx: filemaskinfos[p[1]] = p[0] # step through the list of input images and create # combined (static + DQ + user supplied, if any) mask, and # create a list of FileExtMaskInfo objects to be passed # to 'skymatch' function. # # This needs to be done in several steps, mostly due to the fact that # the mask catalogs use "original" (e.g., GEIS, WAIVER FITS) file names # while ultimately we want to open the version converted to MEF. Second # reason is that we want to combine user supplied masks with DQ+static # masks provided by astrodrizzle. new_fi = [] sky_bits = interpret_bit_flags(paramDict['sky_bits']) for i in range(nimg): # extract extension information: extname = imageList[i].scienceExt extver = imageList[i].group if extver is None: extver = imageList[i].getExtensions() assert(extname is not None and extname != '') assert(extver) # create a new FileExtMaskInfo object fi = FileExtMaskInfo(default_ext=(extname,'*'), default_mask_ext=0, clobber=False, doNotOpenDQ=True, fnamesOnly=False, im_fmode='update', dq_fmode='readonly', msk_fmode='readonly') # set image file and extensions: fi.image = loaded_fnames[i] extlist = [ (extname,ev) for ev in extver ] fi.append_ext(extlist) # set user masks if any (this will open the files for a later use): fi0 = filemaskinfos[i] if fi0 is not None: nmask = len(fi0.mask_images) for m in range(nmask): mask = fi0.mask_images[m] ext = fi0.maskext[m] fi.append_mask(mask, ext) fi.finalize() # combine user masks with static masks: assert(len(extlist) == fi.count) #TODO: <-- remove after thorough testing masklist = [] mextlist = [] for k in range(fi.count): if fi.mask_images[k].closed: umask = None else: umask = fi.mask_images[k].hdu[fi.maskext[k]].data (mask, mext) = _buildStaticDQUserMask(imageList[i], extlist[k], sky_bits, paramDict['use_static'], fi.mask_images[k], fi.maskext[k], in_memory) masklist.append(mask) mextlist.append(mext) # replace the original user-supplied masks with the # newly computed combined static+DQ+user masks: fi.clear_masks() for k in range(fi.count): if in_memory and mask is not None: # os.stat() on the "original_fname" of the mask will fail # since this is a "virtual" mask. Therefore we need to compute # mask_stat ourselves. We will simply use id(data) for this: mstat = os.stat_result((0,id(mask.hdu)) + 8*(0,)) fi.append_mask(masklist[k], mextlist[k], mask_stat=mstat) else: fi.append_mask(masklist[k], mextlist[k]) if masklist[k]: masklist[k].release() fi.finalize() new_fi.append(fi) # Run skymatch algorithm: skymatch(new_fi, skymethod = paramDict['skymethod'], skystat = paramDict['skystat'], lower = paramDict['skylower'], upper = paramDict['skyupper'], nclip = paramDict['skyclip'], lsigma = paramDict['skylsigma'], usigma = paramDict['skyusigma'], binwidth = paramDict['skywidth'], skyuser_kwd = skyKW, units_kwd = 'BUNIT', readonly = not paramDict['skysub'], dq_bits = None, optimize = 'inmemory' if in_memory else 'balanced', clobber = True, clean = clean, verbose = True, flog = MultiFileLog(console = True, enableBold = False), _taskname4history = 'AstroDrizzle') # Populate 'subtractedSky' and 'computedSky' of input image objects: for i in range(nimg): assert(not new_fi[i].fnamesOnly and not new_fi[i].image.closed) image = imageList[i] skysubimage = new_fi[i].image.hdu numchips = image._numchips extname = image.scienceExt assert(os.path.samefile(image._filename, skysubimage.filename())) for extver in range(1, numchips + 1, 1): chip = image[extname, extver] if not chip.group_member: continue subtracted_sky = skysubimage[extname, extver].header.get(skyKW, 0.) chip.subtractedSky = subtracted_sky chip.computedSky = subtracted_sky # clean-up: for fi in new_fi: fi.release_all_images() def _buildStaticDQUserMask(img, ext, sky_bits, use_static, umask, umaskext, in_memory): # creates a temporary mask by combining 'static' mask, # DQ image, and user-supplied mask. def merge_masks(m1, m2): if m1 is None: return m2 if m2 is None: return m1 return np.logical_and(m1, m2).astype(np.uint8) mask = None # build DQ mask if sky_bits is not None: mask = img.buildMask(img[ext]._chip,bits=sky_bits) # get correct static mask mask filenames/objects staticMaskName = img[ext].outputNames['staticMask'] smask = None if use_static: if img.inmemory: if staticMaskName in img.virtualOutputs: smask = img.virtualOutputs[staticMaskName].data else: if staticMaskName is not None and os.path.isfile(staticMaskName): sm, dq = openImageEx( staticMaskName, mode='readonly', memmap=False, saveAsMEF=False, clobber=False, imageOnly=True, openImageHDU=True, openDQHDU=False, preferMEF=False, verbose=False ) if sm.hdu is not None: smask = sm.hdu[0].data sm.release() else: log.warning("Static mask for file \'{}\', ext={} NOT FOUND." \ .format(img._filename, ext)) # combine DQ and static masks: mask = merge_masks(mask, smask) # combine user mask with the previously computed mask: if umask is not None and not umask.closed: if mask is None: # return user-supplied mask: umask.hold() return (umask, umaskext) else: # combine user mask with the previously computed mask: dtm = umask.hdu[umaskext].data mask = merge_masks(mask, dtm) if mask is None: return (None, None) elif mask.sum() == 0: log.warning("All pixels masked out when applying DQ, " \ "static, and user masks!") # save mask to a temporary file: (root,suffix,fext) = file_name_components(img._filename) if in_memory: tmpmask = in_memory_mask(mask) strext = ext2str(ext, compact=True, default_extver=None) tmpmask.original_fname = "{1:s}{0:s}{2:s}{0:s}{3:s}" \ .format('_', root, suffix, 'in-memory_skymatch_mask') else: (tmpfname, tmpmask) = temp_mask_file(mask, root, prefix='', suffix='skymatch_mask', ext=ext, randomize_prefix=False) img[ext].outputNames['skyMatchMask'] = tmpfname return (tmpmask, 0) # this function applies user supplied sky values from an input file def _skyUserFromFile(imageObjList, skyFile, apply_sky=None): """ Apply sky value as read in from a user-supplied input file. """ skyKW="MDRIZSKY" #header keyword that contains the sky that's been subtracted # create dict of fname=sky pairs skyvals = {} if apply_sky is None: skyapplied = False # flag whether sky has already been applied to images else: skyapplied = apply_sky for line in open(skyFile): if apply_sky is None and line[0] == '#' and 'applied' in line: if '=' in line: linesep = '=' if ':' in line: linesep = ':' appliedstr = line.split(linesep)[1].strip() if appliedstr.lower() in ['yes','true','y','t']: skyapplied = True print('...Sky values already applied by user...') if not util.is_blank(line) and line[0] != '#': lspl = line.split() svals = [] for lvals in lspl[1:]: svals.append(float(lvals)) skyvals[lspl[0]] = svals # Apply user values to appropriate input images for imageSet in imageObjList: fname = imageSet._filename numchips=imageSet._numchips sciExt=imageSet.scienceExt if fname in skyvals: print(" ...updating MDRIZSKY with user-supplied value.") for chip in range(1,numchips+1,1): if len(skyvals[fname]) == 1: _skyValue = skyvals[fname][0] else: _skyValue = skyvals[fname][chip-1] chipext = '%s,%d'%(sciExt,chip) _updateKW(imageSet[chipext],fname,(sciExt,chip),skyKW,_skyValue) # Update internal record with subtracted sky value # # .computedSky: value to be applied by the # adrizzle/ablot steps. # .subtractedSky: value already (or will be by adrizzle/ablot) # subtracted from the image if skyapplied: imageSet[chipext].computedSky = None # used by adrizzle/ablot else: imageSet[chipext].computedSky = _skyValue imageSet[chipext].subtractedSky = _skyValue print("Setting ",skyKW,"=",_skyValue) else: print("*"*40) print("*") print("WARNING:") print(" .... NO user-supplied sky value found for ",fname) print(" .... Setting sky to a value of 0.0! ") print("*") print("*"*40) def _skyUserFromHeaderKwd(imageSet,paramDict): """ subtract the sky from all the chips in the imagefile that imageSet represents imageSet is a single imageObject reference paramDict should be the subset from an actual config object """ _skyValue=0.0 #this will be the sky value computed for the exposure skyKW="MDRIZSKY" #header keyword that contains the sky that's been subtracted #just making sure, tricky users and all, these are things that will be used #by the sky function so we want them defined at least try: assert imageSet._numchips > 0, "invalid value for number of chips" assert imageSet._filename != '', "image object filename is empty!, doh!" assert imageSet._rootname != '', "image rootname is empty!, doh!" assert imageSet.scienceExt !='', "image object science extension is empty!" except AssertionError: raise AssertionError numchips=imageSet._numchips sciExt=imageSet.scienceExt # User Subtraction Case, User has done own sky subtraction, # so use the image header value for subtractedsky value skyuser=paramDict["skyuser"] if skyuser != '': print("User has computed their own sky values...") if skyuser != skyKW: print(" ...updating MDRIZSKY with supplied value.") for chip in range(1,numchips+1,1): chipext = '%s,%d'%(sciExt,chip) if not imageSet[chipext].group_member: # skip extensions/chips that will not be processed continue try: _skyValue = imageSet[chipext].header[skyuser] except: print("**************************************************************") print("*") print("* Cannot find keyword ",skyuser," in ",imageSet._filename) print("*") print("**************************************************************\n\n\n") raise KeyError _updateKW(imageSet[sciExt+','+str(chip)], imageSet._filename,(sciExt,chip),skyKW,_skyValue) # Update internal record with subtracted sky value imageSet[chipext].subtractedSky = _skyValue imageSet[chipext].computedSky = None print("Setting ",skyKW,"=",_skyValue) #this is the main function that does all the real work in computing the # statistical sky value for each image (set of chips) # mcara: '_skySub' is obsolete now: # was replaced with '_skyUserFromHeaderKwd' and '_skymatch' def _skySub(imageSet,paramDict,saveFile=False): """ subtract the sky from all the chips in the imagefile that imageSet represents imageSet is a single imageObject reference paramDict should be the subset from an actual config object if saveFile=True, then images that have been sky subtracted are saved to a predetermined output name else, overwrite the input images with the sky-subtracted results the output from sky subtraction is a copy of the original input file where all the science data extensions have been sky subtracted """ _skyValue=0.0 #this will be the sky value computed for the exposure skyKW="MDRIZSKY" #header keyword that contains the sky that's been subtracted #just making sure, tricky users and all, these are things that will be used #by the sky function so we want them defined at least try: assert imageSet._numchips > 0, "invalid value for number of chips" assert imageSet._filename != '', "image object filename is empty!, doh!" assert imageSet._rootname != '', "image rootname is empty!, doh!" assert imageSet.scienceExt !='', "image object science extension is empty!" except AssertionError: raise AssertionError numchips=imageSet._numchips sciExt=imageSet.scienceExt # User Subtraction Case, User has done own sky subtraction, # so use the image header value for subtractedsky value skyuser=paramDict["skyuser"] if skyuser != '': print("User has computed their own sky values...") if skyuser != skyKW: print(" ...updating MDRIZSKY with supplied value.") for chip in range(1,numchips+1,1): try: chipext = '%s,%d'%(sciExt,chip) _skyValue = imageSet[chipext].header[skyuser] except: print("**************************************************************") print("*") print("* Cannot find keyword ",skyuser," in ",imageSet._filename) print("*") print("**************************************************************\n\n\n") raise KeyError _updateKW(imageSet[sciExt+','+str(chip)],imageSet._filename,(sciExt,chip),skyKW,_skyValue) # Update internal record with subtracted sky value imageSet[chipext].subtractedSky = _skyValue imageSet[chipext].computedSky = None print("Setting ",skyKW,"=",_skyValue) else: # Compute our own sky values and record the values for use later. # The minimum sky value from all the science chips in the exposure # is used as the reference sky for each chip log.info("Computing minimum sky ...") minSky=[] #store the sky for each chip minpscale = [] for chip in range(1,numchips+1,1): myext=sciExt+","+str(chip) #add the data back into the chip, leave it there til the end of this function imageSet[myext].data=imageSet.getData(myext) image=imageSet[myext] _skyValue= _computeSky(image, paramDict, memmap=False) #scale the sky value by the area on sky # account for the case where no IDCSCALE has been set, due to a # lack of IDCTAB or to 'coeffs=False'. pscale=imageSet[myext].wcs.idcscale if pscale is None: log.warning("No Distortion coefficients available...using " "default plate scale.") pscale = imageSet[myext].wcs.pscale _scaledSky=_skyValue / (pscale**2) #_skyValue=_scaledSky minSky.append(_scaledSky) minpscale.append(pscale) _skyValue = min(minSky) _reportedSky = _skyValue*(minpscale[minSky.index(_skyValue)]**2) log.info("Minimum sky value for all chips %s" % _reportedSky) #now subtract that value from all the chips in the exposure #and update the chips header keyword with the sub for chip in range(1,numchips+1,1): image=imageSet[sciExt,chip] myext = sciExt+","+str(chip) # account for the case where no IDCSCALE has been set, due to a # lack of IDCTAB or to 'coeffs=False'. idcscale = image.wcs.idcscale if idcscale is None: idcscale = image.wcs.pscale _scaledSky=_skyValue * (idcscale**2) image.subtractedSky = _scaledSky image.computedSky = _scaledSky log.info("Using sky from chip %d: %f\n" % (chip,_scaledSky)) ###_subtractSky(image,(_scaledSky)) # Update the header so that the keyword in the image is #the sky value which should be subtracted from the image _updateKW(image,imageSet._filename,(sciExt,chip),skyKW,_scaledSky) ############################### ## Helper functions follow ## ############################### def _computeSky(image, skypars, memmap=False): """ Compute the sky value for the data array passed to the function image is a fits object which contains the data and the header for one image extension skypars is passed in as paramDict """ #this object contains the returned values from the image stats routine _tmp = imagestats.ImageStats(image.data, fields = skypars['skystat'], lower = skypars['skylower'], upper = skypars['skyupper'], nclip = skypars['skyclip'], lsig = skypars['skylsigma'], usig = skypars['skyusigma'], binwidth = skypars['skywidth'] ) _skyValue = _extractSkyValue(_tmp,skypars['skystat'].lower()) log.info(" Computed sky value/pixel for %s: %s "% (image.rootname, _skyValue)) del _tmp return _skyValue def _extractSkyValue(imstatObject,skystat): if (skystat =="mode"): return imstatObject.mode elif (skystat == "mean"): return imstatObject.mean else: return imstatObject.median def _subtractSky(image,skyValue,memmap=False): """ subtract the given sky value from each the data array that has been passed. image is a fits object that contains the data and header for one image extension """ try: np.subtract(image.data,skyValue,image.data) except IOError: print("Unable to perform sky subtraction on data array") raise IOError def _updateKW(image, filename, exten, skyKW, Value): """update the header with the kw,value""" # Update the value in memory image.header[skyKW] = Value # Now update the value on disk if isinstance(exten,tuple): strexten = '[%s,%s]'%(exten[0],str(exten[1])) else: strexten = '[%s]'%(exten) log.info('Updating keyword %s in %s' % (skyKW, filename + strexten)) fobj = fileutil.openImage(filename, mode='update', memmap=False) fobj[exten].header[skyKW] = (Value, 'Sky value computed by AstroDrizzle') fobj.close() def _addDefaultSkyKW(imageObjList): """Add MDRIZSKY keyword to "commanded" SCI headers of all input images, if that keyword does not already exist. """ skyKW = "MDRIZSKY" Value = 0.0 for imageSet in imageObjList: fname = imageSet._filename numchips=imageSet._numchips sciExt=imageSet.scienceExt fobj = fileutil.openImage(fname, mode='update', memmap=False) for chip in range(1,numchips+1,1): ext = (sciExt,chip) if not imageSet[ext].group_member: # skip over extensions not used in processing continue if skyKW not in fobj[ext].header: fobj[ext].header[skyKW] = (Value, 'Sky value computed by AstroDrizzle') log.info("MDRIZSKY keyword not found in the %s[%s,%d] header."%( fname,sciExt,chip)) log.info(" Adding MDRIZSKY to header with default value of 0.") fobj.close() #this is really related to each individual chip #so pass in the image for that chip, image contains header and data def getreferencesky(image,keyval): _subtractedSky=image.header[keyval] _refplatescale=image.header["REFPLTSCL"] _platescale=image.header["PLATESCL"] return (_subtractedsky * (_refplatescale / _platescale)**2 )
[docs]def help(file=None): """ Print out syntax help for running astrodrizzle Parameters ---------- file : str (Default = None) If given, write out help to the filename specified by this parameter Any previously existing file with this name will be deleted before writing out the help. """ helpstr = getHelpAsString(docstring=True, show_ver = True) if file is None: print(helpstr) else: if os.path.exists(file): os.remove(file) f = open(file, mode = 'w') f.write(helpstr) f.close()
def getHelpAsString(docstring = False, show_ver = True): """ return useful help from a file in the script directory called __taskname__.help """ install_dir = os.path.dirname(__file__) taskname = util.base_taskname(__taskname__, __package__) htmlfile = os.path.join(install_dir, 'htmlhelp', taskname + '.html') helpfile = os.path.join(install_dir, taskname + '.help') if docstring or (not docstring and not os.path.exists(htmlfile)): if show_ver: helpString = os.linesep + \ ' '.join([__taskname__, 'Version', __version__, ' updated on ', __version_date__]) + 2*os.linesep else: helpString = '' if os.path.exists(helpfile): helpString += teal.getHelpFileAsString(taskname, __file__) else: if __doc__ is not None: helpString += __doc__ + os.linesep else: helpString = 'file://' + htmlfile return helpString sky.__doc__ = getHelpAsString(docstring = True, show_ver = False)