Source code for drizzlepac.adrizzle

Interfaces to main drizzle functions.

:Authors: Warren Hack

:License: :doc:`LICENSE`

import os
import copy
import time
import platform
from . import util
import numpy as np
from import fits
from import fileutil, logutil, mputil, teal
from . import outputimage, wcs_functions
import stwcs
from stwcs import distortion

from .version import *

    from . import cdriz
except ImportError:
    cdriz = None
    print('\n Coordinate transformation and image resampling library, cdriz, NOT found!')
    print('\n Please check the installation of this package to insure C code was built successfully.')
    raise ImportError

if util.can_parallel:
    import multiprocessing

__all__ = ['drizzle', 'run', 'drizSeparate', 'drizFinal', 'mergeDQarray',
           'updateInputDQArray', 'buildDrizParamDict', 'interpret_maskval',
           'run_driz', 'run_driz_img', 'run_driz_chip', 'do_driz',
           'get_data', 'create_output', 'help', 'getHelpAsString']

__taskname__ = "drizzlepac.adrizzle"
_single_step_num_ = 3
_final_step_num_ = 7

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

time_pre_all = []
time_driz_all = []
time_post_all = []
time_write_all = []

# ### Interactive interface for running drizzle tasks separately

[docs]def drizzle(input, outdata, wcsmap=None, editpars=False, configObj=None, **input_dict): # Pass along values of input and outdata as members of input_dict if input_dict is None: input_dict = {} input_dict['input'] = input input_dict['outdata'] = outdata # If called from interactive user-interface, configObj will not be # defined yet, so get defaults using EPAR/TEAL. # # Also insure that the input_dict (user-specified values) are folded in # with a fully populated configObj instance. configObj = util.getDefaultConfigObj(__taskname__,configObj,input_dict,loadOnly=(not editpars)) if configObj is None: return if not editpars: run(configObj,wcsmap=wcsmap)
# #### User level interface to run drizzle tasks from TEAL #
[docs]def run(configObj, wcsmap=None): """ Interface for running `wdrizzle` from TEAL or Python command-line. This code performs all file ``I/O`` to set up the use of the drizzle code for a single exposure to replicate the functionality of the original `wdrizzle`. """ # Insure all output filenames specified have .fits extensions if configObj['outdata'][-5:] != '.fits': configObj['outdata'] += '.fits' if not util.is_blank(configObj['outweight']) and configObj['outweight'][-5:] != '.fits': configObj['outweight'] += '.fits' if not util.is_blank(configObj['outcontext']) and configObj['outcontext'][-5:] != '.fits': configObj['outcontext'] += '.fits' # Keep track of any files we need to open in_sci_handle = None in_wht_handle = None out_sci_handle = None out_wht_handle = None out_con_handle = None _wcskey = configObj['wcskey'] if util.is_blank(_wcskey): _wcskey = ' ' scale_pars = configObj['Data Scaling Parameters'] user_wcs_pars = configObj['User WCS Parameters'] # Open the SCI (and WHT?) image # read file to get science array insci = get_data(configObj['input']) expin = fileutil.getKeyword(configObj['input'],scale_pars['expkey']) in_sci_phdr = fits.getheader(fileutil.parseFilename(configObj['input'])[0], memmap=False) # we need to read in the input WCS input_wcs = stwcs.wcsutil.HSTWCS(configObj['input'],wcskey=_wcskey) if not util.is_blank(configObj['inweight']): inwht = get_data(configObj['inweight']).astype(np.float32) else: # Generate a default weight map of all good pixels inwht = np.ones(insci.shape,dtype=insci.dtype) output_exists = False outname = fileutil.osfn(fileutil.parseFilename(configObj['outdata'])[0]) if os.path.exists(outname): output_exists = True # Output was specified as a filename, so open it in 'update' mode outsci = get_data(configObj['outdata']) if output_exists: # we also need to read in the output WCS from pre-existing output output_wcs = stwcs.wcsutil.HSTWCS(configObj['outdata']) out_sci_hdr = fits.getheader(outname, memmap=False) outexptime = out_sci_hdr['DRIZEXPT'] if 'ndrizim' in out_sci_hdr: uniqid = out_sci_hdr['ndrizim']+1 else: uniqid = 1 else: # otherwise, define the output WCS either from user pars or refimage if util.is_blank(configObj['User WCS Parameters']['refimage']): # Define a WCS based on user provided WCS values # NOTE: # All parameters must be specified, not just one or a few if not util.is_blank(user_wcs_pars['outscale']): output_wcs = wcs_functions.build_hstwcs( user_wcs_pars['raref'], user_wcs_pars['decref'], user_wcs_pars['xrefpix'], user_wcs_pars['yrefpix'], int(user_wcs_pars['outnx']), int(user_wcs_pars['outny']), user_wcs_pars['outscale'], user_wcs_pars['orient'] ) else: # Define default WCS based on input image applydist = True if input_wcs.sip is None or input_wcs.instrument=='DEFAULT': applydist = False output_wcs = stwcs.distortion.utils.output_wcs([input_wcs],undistort=applydist) else: refimage = configObj['User WCS Parameters']['refimage'] refroot,extroot = fileutil.parseFilename(refimage) if extroot is None: fimg =, memmap=False) for i,extn in enumerate(fimg): if 'CRVAL1' in extn.header: # Key on CRVAL1 for valid WCS refwcs = stwcs.wcsutil.HSTWCS('{}[{}]'.format(refroot,i)) if refwcs.wcs.has_cd(): extroot = i break fimg.close() # try to find extension with valid WCS refimage = "{}[{}]".format(refroot,extroot) # Define the output WCS based on a user specified reference image WCS output_wcs = stwcs.wcsutil.HSTWCS(refimage) # Initialize values used for combining results outexptime = 0.0 uniqid = 1 # Set up the output data array and insure that the units for that array is 'cps' if outsci is None: # Define a default blank array based on definition of output_wcs outsci = np.empty(output_wcs.array_shape, dtype=np.float32) outsci.fill(np.nan) else: # Convert array to units of 'cps', if needed if outexptime != 0.0: np.divide(outsci, outexptime, outsci) outsci = outsci.astype(np.float32) # Now update output exposure time for additional input file outexptime += expin outwht = None if not util.is_blank(configObj['outweight']): outwht = get_data(configObj['outweight']) if outwht is None: outwht = np.zeros(output_wcs.array_shape, dtype=np.float32) else: outwht = outwht.astype(np.float32) outcon = None keep_con = False if not util.is_blank(configObj['outcontext']): outcon = get_data(configObj['outcontext']) keep_con = True if outcon is None: outcon = np.zeros((1,) + output_wcs.array_shape, dtype=np.int32) else: outcon = outcon.astype(np.int32) planeid = int((uniqid - 1)/ 32) # Add a new plane to the context image if planeid overflows while outcon.shape[0] <= planeid: plane = np.zeros_like(outcon[0]) outcon = np.append(outcon, plane, axis=0) # Interpret wt_scl parameter if configObj['wt_scl'] == 'exptime': wt_scl = expin elif configObj['wt_scl'] == 'expsq': wt_scl = expin*expin else: wt_scl = float(configObj['wt_scl']) # Interpret coeffs parameter to determine whether to apply coeffs or not undistort = True if not configObj['coeffs'] or input_wcs.sip is None or input_wcs.instrument == 'DEFAULT': undistort = False # turn off use of coefficients if undistort is False (coeffs == False) if not undistort: input_wcs.sip = None input_wcs.cpdis1 = None input_wcs.cpdis2 = None input_wcs.det2im = None wcslin = distortion.utils.output_wcs([input_wcs],undistort=undistort) # Perform actual drizzling now... _vers = do_driz(insci, input_wcs, inwht, output_wcs, outsci, outwht, outcon, expin, scale_pars['in_units'], wt_scl, wcslin_pscale=wcslin.pscale ,uniqid=uniqid, pixfrac=configObj['pixfrac'], kernel=configObj['kernel'], fillval=scale_pars['fillval'], stepsize=configObj['stepsize'], wcsmap=None) out_sci_handle,outextn = create_output(configObj['outdata']) if not output_exists: # Also, define default header based on input image Primary header out_sci_handle[outextn].header = in_sci_phdr.copy() # Update header of output image with exptime used to scale the output data # if out_units is not counts, this will simply be a value of 1.0 # the keyword 'exptime' will always contain the total exposure time # of all input image regardless of the output units out_sci_handle[outextn].header['EXPTIME'] = outexptime # create CTYPE strings ctype1 = input_wcs.wcs.ctype[0] ctype2 = input_wcs.wcs.ctype[1] if ctype1.find('-SIP'): ctype1 = ctype1.replace('-SIP','') if ctype2.find('-SIP'): ctype2 = ctype2.replace('-SIP','') # Update header with WCS keywords out_sci_handle[outextn].header['ORIENTAT'] = output_wcs.orientat out_sci_handle[outextn].header['CD1_1'] =[0][0] out_sci_handle[outextn].header['CD1_2'] =[0][1] out_sci_handle[outextn].header['CD2_1'] =[1][0] out_sci_handle[outextn].header['CD2_2'] =[1][1] out_sci_handle[outextn].header['CRVAL1'] = output_wcs.wcs.crval[0] out_sci_handle[outextn].header['CRVAL2'] = output_wcs.wcs.crval[1] out_sci_handle[outextn].header['CRPIX1'] = output_wcs.wcs.crpix[0] out_sci_handle[outextn].header['CRPIX2'] = output_wcs.wcs.crpix[1] out_sci_handle[outextn].header['CTYPE1'] = ctype1 out_sci_handle[outextn].header['CTYPE2'] = ctype2 out_sci_handle[outextn].header['VAFACTOR'] = 1.0 if scale_pars['out_units'] == 'counts': np.multiply(outsci, outexptime, outsci) out_sci_handle[outextn].header['DRIZEXPT'] = outexptime else: out_sci_handle[outextn].header['DRIZEXPT'] = 1.0 # Update header keyword NDRIZIM to keep track of how many images have # been combined in this product so far out_sci_handle[outextn].header['NDRIZIM'] = uniqid #define keywords to be written out to product header drizdict = outputimage.DRIZ_KEYWORDS.copy() # Update drizdict with current values drizdict['VER']['value'] = _vers[:44] drizdict['DATA']['value'] = configObj['input'][:64] drizdict['DEXP']['value'] = expin drizdict['OUDA']['value'] = configObj['outdata'][:64] drizdict['OUWE']['value'] = configObj['outweight'][:64] drizdict['OUCO']['value'] = configObj['outcontext'][:64] drizdict['MASK']['value'] = configObj['inweight'][:64] drizdict['WTSC']['value'] = wt_scl drizdict['KERN']['value'] = configObj['kernel'] drizdict['PIXF']['value'] = configObj['pixfrac'] drizdict['OUUN']['value'] = scale_pars['out_units'] drizdict['FVAL']['value'] = scale_pars['fillval'] drizdict['WKEY']['value'] = configObj['wcskey'] outputimage.writeDrizKeywords(out_sci_handle[outextn].header,uniqid,drizdict) # add output array to output file out_sci_handle[outextn].data = outsci out_sci_handle.close() if not util.is_blank(configObj['outweight']): out_wht_handle,outwhtext = create_output(configObj['outweight']) out_wht_handle[outwhtext].header = out_sci_handle[outextn].header.copy() out_wht_handle[outwhtext].data = outwht out_wht_handle.close() if keep_con: out_con_handle,outconext = create_output(configObj['outcontext']) out_con_handle[outconext].data = outcon out_con_handle.close()
# # drizzlepac based interfaces: relying on imageObject instances and drizzlepac internals # # #### Top-level interface from inside MultiDrizzle #
[docs]def drizSeparate(imageObjectList,output_wcs,configObj,wcsmap=None,procSteps=None): if procSteps is not None: procSteps.addStep('Separate Drizzle') # ConfigObj needs to be parsed specifically for driz_separate set of parameters single_step = util.getSectionName(configObj,_single_step_num_) # This can be called directly from MultiDrizle, so only execute if # switch has been turned on (no guarantee MD will check before calling). if configObj[single_step]['driz_separate']: paramDict = buildDrizParamDict(configObj) paramDict['crbit'] = None paramDict['proc_unit'] = 'electrons' paramDict['wht_type'] = None # Force 'build' to always be False, so that this step always generates # simple FITS files as output for compatibility with 'createMedian' paramDict['build'] = False # Record whether or not intermediate files should be deleted when finished paramDict['clean'] = configObj['STATE OF INPUT FILES']['clean'] paramDict['num_cores'] = configObj.get('num_cores') paramDict['rules_file'] = configObj['rules_file'] if configObj['rules_file'] != "" else None'USER INPUT PARAMETERS for Separate Drizzle Step:') util.printParams(paramDict, log=log) # override configObj[build] value with the value of the build parameter # this is necessary in order for AstroDrizzle to always have build=False # for single-drizzle step when called from the top-level. run_driz(imageObjectList, output_wcs.single_wcs, paramDict, single=True, build=False, wcsmap=wcsmap) else:'Single drizzle step not performed.') if procSteps is not None: procSteps.endStep('Separate Drizzle')
[docs]def drizFinal(imageObjectList, output_wcs, configObj,build=None,wcsmap=None,procSteps=None): if procSteps is not None: procSteps.addStep('Final Drizzle') # ConfigObj needs to be parsed specifically for driz_final set of parameters final_step = util.getSectionName(configObj,_final_step_num_) # This can be called directly from MultiDrizle, so only execute if # switch has been turned on (no guarantee MD will check before calling). if configObj[final_step]['driz_combine']: paramDict = buildDrizParamDict(configObj,single=False) paramDict['crbit'] = configObj['crbit'] paramDict['proc_unit'] = configObj['proc_unit'] paramDict['wht_type'] = configObj[final_step]['final_wht_type'] paramDict['rules_file'] = configObj['rules_file'] if configObj['rules_file'] != "" else None # override configObj[build] value with the value of the build parameter # this is necessary in order for MultiDrizzle to always have build=False # for single-drizzle step when called from the top-level. if build is None: build = paramDict['build'] # Record whether or not intermediate files should be deleted when finished paramDict['clean'] = configObj['STATE OF INPUT FILES']['clean']'USER INPUT PARAMETERS for Final Drizzle Step:') util.printParams(paramDict, log=log) run_driz(imageObjectList, output_wcs.final_wcs, paramDict, single=False, build=build, wcsmap=wcsmap) else:'Final drizzle step not performed.') if procSteps is not None: procSteps.endStep('Final Drizzle')
# Run 'drizzle' here... #
[docs]def mergeDQarray(maskname,dqarr): """ Merge static or CR mask with mask created from DQ array on-the-fly here. """ maskarr = None if maskname is not None: if isinstance(maskname, str): # working with file on disk (default case) if os.path.exists(maskname): mask = fileutil.openImage(maskname, memmap=False) maskarr = mask[0].data.astype(np.bool) mask.close() else: if isinstance(maskname, fits.HDUList): # working with a virtual input file maskarr = maskname[0].data.astype(np.bool) else: maskarr = if maskarr is not None: # merge array with dqarr now np.bitwise_and(dqarr,maskarr,dqarr)
[docs]def updateInputDQArray(dqfile,dq_extn,chip, crmaskname,cr_bits_value): if not isinstance(crmaskname, fits.HDUList) and not os.path.exists(crmaskname): log.warning('No CR mask file found! Input DQ array not updated.') return if cr_bits_value is None: log.warning('Input DQ array not updated!') return if isinstance(crmaskname, fits.HDUList): # in_memory case crmask = crmaskname else: crmask = fileutil.openImage(crmaskname, memmap=False) if os.path.exists(dqfile): fullext=dqfile+"["+dq_extn+str(chip)+"]" infile = fileutil.openImage(fullext, mode='update', memmap=False) __bitarray = np.logical_not(crmask[0].data).astype(np.int16) * cr_bits_value np.bitwise_or(infile[dq_extn,chip].data,__bitarray,infile[dq_extn,chip].data) infile.close() crmask.close()
[docs]def buildDrizParamDict(configObj,single=True): chip_pars = ['units','wt_scl','pixfrac','kernel','fillval','bits','maskval'] cfunc_pars = {'pixfrac':float} # Initialize paramDict with global parameter(s) paramDict = {'build':configObj['build'],'stepsize':configObj['stepsize'], 'coeffs':configObj['coeffs'],'wcskey':configObj['wcskey']} # build appro if single: driz_prefix = 'driz_sep_' stepnum = 3 else: driz_prefix = 'final_' stepnum = 7 section_name = util.getSectionName(configObj,stepnum) # Copy values from configObj for the appropriate step to paramDict for p in list(configObj[section_name].keys())+[driz_prefix+'units']: if p.startswith(driz_prefix): par = p[len(driz_prefix):] if par == 'units': if single: # Hard-code single-drizzle to always returns 'cps' paramDict[par] = 'cps' else: paramDict[par] = configObj[section_name][driz_prefix+par] else: val = configObj[section_name][driz_prefix+par] if par in cfunc_pars: val = cfunc_pars[par](val) paramDict[par] = val"Interpreted paramDict with single={} as:\n{}".format(single,paramDict)) return paramDict
def _setDefaults(configObj={}): """set up the default parameters to run drizzle build,single,units,wt_scl,pixfrac,kernel,fillval, rot,scale,xsh,ysh,blotnx,blotny,outnx,outny,data Used exclusively for unit-testing, if any are defined. """ paramDict={"build":True, "single":True, "stepsize":10, "in_units":"cps", "wt_scl":1., "pixfrac":1., "kernel":"square", "fillval":999., "maskval": None, "rot":0., "scale":1., "xsh":0., "ysh":0., "blotnx":2048, "blotny":2048, "outnx":4096, "outny":4096, "data":None, "driz_separate":True, "driz_combine":False} if(len(configObj) !=0): for key in configObj.keys(): paramDict[key]=configObj[key] return paramDict
[docs]def interpret_maskval(paramDict): """ Apply logic for interpreting final_maskval value... """ # interpret user specified final_maskval value to use for initializing # output SCI array... if 'maskval' not in paramDict: return 0 maskval = paramDict['maskval'] if maskval is None: maskval = np.nan else: maskval = float(maskval) # just to be clear and absolutely sure... return maskval
[docs]def run_driz(imageObjectList,output_wcs,paramDict,single,build,wcsmap=None): """ Perform drizzle operation on input to create output. The input parameters originally was a list of dictionaries, one for each input, that matches the primary parameters for an ``IRAF`` `drizzle` task. This method would then loop over all the entries in the list and run `drizzle` for each entry. Parameters required for input in paramDict: build,single,units,wt_scl,pixfrac,kernel,fillval, rot,scale,xsh,ysh,blotnx,blotny,outnx,outny,data """ # Insure that input imageObject is a list if not isinstance(imageObjectList, list): imageObjectList = [imageObjectList] # # Setup the versions info dictionary for output to PRIMARY header # The keys will be used as the name reported in the header, as-is # _versions = {'AstroDrizzle':__version__, 'PyFITS':util.__fits_version__, 'Numpy':util.__numpy_version__} # Set sub-sampling rate for drizzling #stepsize = 2.0' **Using sub-sampling value of %s for kernel %s' % (paramDict['stepsize'], paramDict['kernel'])) maskval = interpret_maskval(paramDict) outwcs = copy.deepcopy(output_wcs) # Check for existance of output file. if (not single and build and fileutil.findFile(imageObjectList[0].outputNames['outFinal'])):'Removing previous output product...') os.remove(imageObjectList[0].outputNames['outFinal']) # print out parameters being used for drizzling"Running Drizzle to create output frame with WCS of: ") output_wcs.printwcs() # Will we be running in parallel? pool_size = util.get_pool_size(paramDict.get('num_cores'), len(imageObjectList)) will_parallel = single and pool_size > 1 and platform.system() != "Windows" if will_parallel:'Executing %d parallel workers' % pool_size) else: if single: # not yet an option for final drizzle, msg would confuse'Executing serially') # Set parameters for each input and run drizzle on it here. # # Perform drizzling... numctx = 0 for img in imageObjectList: numctx += img._nmembers _numctx = {'all':numctx} # if single: # Determine how many chips make up each single image for img in imageObjectList: for chip in img.returnAllChips(extname=img.scienceExt): plsingle = chip.outputNames['outSingle'] if plsingle in _numctx: _numctx[plsingle] += 1 else: _numctx[plsingle] = 1 # Compute how many planes will be needed for the context image. _nplanes = int((_numctx['all']-1) / 32) + 1 # For single drizzling or when context is turned off, # minimize to 1 plane only... if single or imageObjectList[0][1].outputNames['outContext'] in [None,'',' ']: _nplanes = 1 # # An image buffer needs to be setup for converting the input # arrays (sci and wht) from FITS format to native format # with respect to byteorder and byteswapping. # This buffer should be reused for each input if possible. # _outsci = _outwht = _outctx = _hdrlist = None if (not single) or \ (single and (not will_parallel) and (not imageObjectList[0].inmemory)): # Note there are four cases/combinations for single drizzle alone here: # (not-inmem, serial), (not-inmem, parallel), (inmem, serial), (inmem, parallel) _outsci=np.empty(output_wcs.array_shape, dtype=np.float32) _outsci.fill(maskval) _outwht=np.zeros(output_wcs.array_shape, dtype=np.float32) # initialize context to 3-D array but only pass appropriate plane to drizzle as needed _outctx=np.zeros((_nplanes,) + output_wcs.array_shape, dtype=np.int32) _hdrlist = [] # Keep track of how many chips have been processed # For single case, this will determine when to close # one product and open the next. _chipIdx = 0 # Remember the name of the 1st image that goes into this particular product # Insure that the header reports the proper values for the start of the # exposure time used to make this; in particular, TIME-OBS and DATE-OBS. template = None # # Work on each image # subprocs = [] for img in imageObjectList: chiplist = img.returnAllChips(extname=img.scienceExt) # How many inputs should go into this product? num_in_prod = _numctx['all'] if single: num_in_prod = _numctx[chiplist[0].outputNames['outSingle']] # The name of the 1st image fnames = [] for chip in chiplist: fnames.append(chip.outputNames['data']) if _chipIdx == 0: template = fnames else: template.extend(fnames) # Work each image, possibly in parallel if will_parallel: # use multiprocessing.Manager only if in parallel and in memory if img.inmemory: manager = multiprocessing.Manager() dproxy = manager.dict(img.virtualOutputs) # copy & wrap it in proxy img.virtualOutputs = dproxy # parallelize run_driz_img (currently for separate drizzle only) p = multiprocessing.Process(target=run_driz_img, name='adrizzle.run_driz_img()', # for err msgs args=(img,chiplist,output_wcs,outwcs,template,paramDict, single,num_in_prod,build,_versions,_numctx,_nplanes, _chipIdx,None,None,None,None,wcsmap)) subprocs.append(p) else: # serial run_driz_img run (either separate drizzle or final drizzle) run_driz_img(img,chiplist,output_wcs,outwcs,template,paramDict, single,num_in_prod,build,_versions,_numctx,_nplanes, _chipIdx,_outsci,_outwht,_outctx,_hdrlist,wcsmap) # Increment/reset master chip counter _chipIdx += len(chiplist) if _chipIdx == num_in_prod: _chipIdx = 0 # do the join if we spawned tasks if will_parallel: mputil.launch_and_wait(subprocs, pool_size) # blocks till all done del _outsci,_outwht,_outctx,_hdrlist
# have looped over each img/chip # # Still to check: # - why have both output_wcs and outwcs?
[docs]def run_driz_img(img,chiplist,output_wcs,outwcs,template,paramDict,single, num_in_prod,build,_versions,_numctx,_nplanes,chipIdxCopy, _outsci,_outwht,_outctx,_hdrlist,wcsmap): """ Perform the drizzle operation on a single image. This is separated out from :py:func:`run_driz` so as to keep together the entirety of the code which is inside the loop over images. See the :py:func:`run_driz` code for more documentation. """ maskval = interpret_maskval(paramDict) # Check for unintialized inputs here = _outsci is None and _outwht is None and _outctx is None if _outsci is None: _outsci=np.empty(output_wcs.array_shape, dtype=np.float32) if single: _outsci.fill(0) else: _outsci.fill(maskval) if _outwht is None: _outwht=np.zeros(output_wcs.array_shape, dtype=np.float32) if _outctx is None: _outctx = np.zeros((_nplanes,) + output_wcs.array_shape, dtype=np.int32) if _hdrlist is None: _hdrlist = [] # Work on each chip - note that they share access to the arrays above for chip in chiplist: # See if we will be writing out data doWrite = chipIdxCopy == num_in_prod-1 # debuglog('#chips='+str(chipIdxCopy)+', num_in_prod='+\ # str(num_in_prod)+', single='+str(single)+', write='+\ # str(doWrite)+', here='+str(here)) # run_driz_chip run_driz_chip(img,chip,output_wcs,outwcs,template,paramDict, single,doWrite,build,_versions,_numctx,_nplanes, chipIdxCopy,_outsci,_outwht,_outctx,_hdrlist,wcsmap) # Increment chip counter (also done outside of this function) chipIdxCopy += 1 # # Reset for next output image... # if here: del _outsci,_outwht,_outctx,_hdrlist elif single: np.multiply(_outsci,0.,_outsci) np.multiply(_outwht,0.,_outwht) np.multiply(_outctx,0,_outctx) # this was "_hdrlist=[]", but we need to preserve the var ptr itself while len(_hdrlist)>0: _hdrlist.pop()
# else, these were intended to live and be used beyond this function call # img.saveVirtualOutputs() has already been done in run_driz_chip (but # only if single and doWrite)
[docs]def run_driz_chip(img,chip,output_wcs,outwcs,template,paramDict,single, doWrite,build,_versions,_numctx,_nplanes,_numchips, _outsci,_outwht,_outctx,_hdrlist,wcsmap): """ Perform the drizzle operation on a single chip. This is separated out from `run_driz_img` so as to keep together the entirety of the code which is inside the loop over chips. See the `run_driz` code for more documentation. """ global time_pre_all, time_driz_all, time_post_all, time_write_all epoch = time.time() # Look for sky-subtracted product if os.path.exists(chip.outputNames['outSky']): chipextn = '['+chip.header['extname']+','+str(chip.header['extver'])+']' _expname = chip.outputNames['outSky']+chipextn else: # If sky-subtracted product does not exist, use regular input _expname = chip.outputNames['data']'-Drizzle input: %s' % _expname) # Open the SCI image _handle = fileutil.openImage(_expname, mode='readonly', memmap=False) _sciext = _handle[chip.header['extname'],chip.header['extver']] # Apply sky subtraction and unit conversion to input array if chip.computedSky is None: _insci = else:"Applying sky value of %0.6f to %s"%(chip.computedSky,_expname)) _insci = - chip.computedSky # If input SCI image is still integer format (RAW files) # transform it to float32 for all subsequent operations # needed for numpy >=1.12.x if np.issubdtype(_insci[0,0],np.int16): _insci = _insci.astype(np.float32) _insci *= chip._effGain # Set additional parameters needed by 'drizzle' _in_units = chip.in_units.lower() if _in_units == 'cps': _expin = 1.0 else: _expin = chip._exptime #### # # Put the units keyword handling in the imageObject class # #### # Determine output value of BUNITS # and make sure it is not specified as 'ergs/cm...' _bunit = chip._bunit _bindx = _bunit.find('/') if paramDict['units'] == 'cps': # If BUNIT value does not specify count rate already... if _bindx < 1: # ... append '/SEC' to value _bunit += '/S' else: # reset _bunit here to None so it does not # overwrite what is already in header _bunit = None else: if _bindx > 0: # remove '/S' _bunit = _bunit[:_bindx] else: # reset _bunit here to None so it does not # overwrite what is already in header _bunit = None _uniqid = _numchips + 1 if _nplanes == 1: # We need to reset what gets passed to TDRIZ # when only 1 context image plane gets generated # to prevent overflow problems with trying to access # planes that weren't created for large numbers of inputs. _uniqid = ((_uniqid-1) % 32) + 1 # Select which mask needs to be read in for drizzling #### # # Actually need to generate mask file here 'on-demand' # and combine it with the static_mask for single_drizzle case... # #### # Build basic DQMask from DQ array and bits value dqarr = img.buildMask(chip._chip,bits=paramDict['bits']) # get correct mask filenames/objects staticMaskName = chip.outputNames['staticMask'] crMaskName = chip.outputNames['crmaskImage'] if img.inmemory: if staticMaskName in img.virtualOutputs: staticMaskName = img.virtualOutputs[staticMaskName] if crMaskName in img.virtualOutputs: crMaskName = img.virtualOutputs[crMaskName] # Merge appropriate additional mask(s) with DQ mask if single: mergeDQarray(staticMaskName,dqarr) if dqarr.sum() == 0: log.warning('All pixels masked out when applying static mask!') else: mergeDQarray(staticMaskName,dqarr) if dqarr.sum() == 0: log.warning('All pixels masked out when applying static mask!') else: # Only apply cosmic-ray mask when some good pixels remain after # applying the static mask mergeDQarray(crMaskName,dqarr) if dqarr.sum() == 0: log.warning('WARNING: All pixels masked out when applying ' 'cosmic ray mask to %s' % _expname) updateInputDQArray(chip.dqfile,chip.dq_extn,chip._chip, crMaskName, paramDict['crbit']) img.set_wtscl(chip._chip,paramDict['wt_scl']) pix_ratio = outwcs.pscale / chip.wcslin_pscale # Convert mask to a datatype expected by 'tdriz' # Also, base weight mask on ERR or IVM file as requested by user wht_type = paramDict['wht_type'] if wht_type == 'ERR': _inwht = img.buildERRmask(chip._chip,dqarr,pix_ratio) elif wht_type == 'IVM': _inwht = img.buildIVMmask(chip._chip,dqarr,pix_ratio) elif wht_type == 'EXP': _inwht = img.buildEXPmask(chip._chip,dqarr) else: # wht_type == None, used for single drizzle images _inwht = chip._exptime * dqarr.astype(np.float32) if not(paramDict['clean']): # Write out mask file if 'clean' has been turned off if single: step_mask = 'singleDrizMask' else: step_mask = 'finalMask' _outmaskname = chip.outputNames[step_mask] if os.path.exists(_outmaskname): os.remove(_outmaskname) pimg = fits.PrimaryHDU(data=_inwht) img.saveVirtualOutputs({step_mask:pimg}) # Only write out mask files if in_memory=False if not img.inmemory: pimg.writeto(_outmaskname) del pimg'Writing out mask file: %s' % _outmaskname) time_pre = time.time() - epoch; epoch = time.time() # New interface to performing the drizzle operation on a single chip/image _vers = do_driz(_insci, chip.wcs, _inwht, outwcs, _outsci, _outwht, _outctx, _expin, _in_units, chip._wtscl, wcslin_pscale=chip.wcslin_pscale, uniqid=_uniqid, pixfrac=paramDict['pixfrac'], kernel=paramDict['kernel'], fillval=paramDict['fillval'], stepsize=paramDict['stepsize'], wcsmap=wcsmap) time_driz = time.time() - epoch; epoch = time.time() # Set up information for generating output FITS image #### Check to see what names need to be included here for use in _hdrlist chip.outputNames['driz_version'] = _vers chip.outputNames['driz_wcskey'] = paramDict['wcskey'] outputvals = chip.outputNames.copy() # Update entries for names/values based on final output outputvals.update(img.outputValues) for kw in img.outputNames: if kw[:3] == 'out': outputvals[kw] = img.outputNames[kw] outputvals['exptime'] = chip._exptime outputvals['expstart'] = chip._expstart outputvals['expend'] = chip._expend outputvals['wt_scl_val'] = chip._wtscl _hdrlist.append(outputvals) time_post = time.time() - epoch; epoch = time.time() if doWrite: ########################### # # IMPLEMENTATION REQUIREMENT: # # Need to implement scaling of the output image # from 'cps' to 'counts' in the case where 'units' # was set to 'counts'... 21-Mar-2005 # ########################### # Convert output data from electrons/sec to counts/sec as specified native_units = img.native_units if paramDict['proc_unit'].lower() == 'native' and native_units.lower()[:6] == 'counts': np.divide(_outsci, chip._gain, _outsci) _bunit = native_units.lower() if paramDict['units'] == 'counts': indx = _bunit.find('/') if indx > 0: _bunit = _bunit[:indx] # record IDCSCALE for output to product header paramDict['idcscale'] = chip.wcs.idcscale #If output units were set to 'counts', rescale the array in-place if paramDict['units'] == 'counts': #determine what exposure time needs to be used # to rescale the product. if single: _expscale = chip._exptime else: _expscale = img.outputValues['texptime'] np.multiply(_outsci, _expscale, _outsci) # # Write output arrays to FITS file(s) # if not single: img.inmemory = False _outimg = outputimage.OutputImage(_hdrlist, paramDict, build=build, wcs=output_wcs, single=single) _outimg.set_bunit(_bunit) _outimg.set_units(paramDict['units']) outimgs = _outimg.writeFITS(template,_outsci,_outwht,ctxarr=_outctx, versions=_versions,virtual=img.inmemory, rules_file=paramDict['rules_file']) del _outimg # update imageObject with product in memory if single: img.saveVirtualOutputs(outimgs) # this is after the doWrite time_write = time.time() - epoch; epoch = time.time() if False and not single: # turn off all this perf reporting for now time_pre_all.append(time_pre) time_driz_all.append(time_driz) time_post_all.append(time_post) time_write_all.append(time_write)'chip time pre-drizzling: %6.3f' % time_pre)'chip time drizzling: %6.3f' % time_driz)'chip time post-drizzling: %6.3f' % time_post)'chip time writing output: %6.3f' % time_write) if doWrite: tot_pre = sum(time_pre_all) tot_driz = sum(time_driz_all) tot_post = sum(time_post_all) tot_write = sum(time_write_all) tot = tot_pre+tot_driz+tot_post+tot_write'chip total pre-drizzling: %6.3f (%4.1f%%)' % (tot_pre, (100.*tot_pre/tot)))'chip total drizzling: %6.3f (%4.1f%%)' % (tot_driz, (100.*tot_driz/tot)))'chip total post-drizzling: %6.3f (%4.1f%%)' % (tot_post, (100.*tot_post/tot)))'chip total writing output: %6.3f (%4.1f%%)' % (tot_write, (100.*tot_write/tot)))
[docs]def do_driz(insci, input_wcs, inwht, output_wcs, outsci, outwht, outcon, expin, in_units, wt_scl, wcslin_pscale=1.0,uniqid=1, pixfrac=1.0, kernel='square', fillval="INDEF", stepsize=10,wcsmap=None): """ Core routine for performing 'drizzle' operation on a single input image All input values will be Python objects such as ndarrays, instead of filenames. File handling (input and output) will be performed by calling routine. """ # Insure that the fillval parameter gets properly interpreted for use with tdriz if util.is_blank(fillval): fillval = 'INDEF' else: fillval = str(fillval) if in_units == 'cps': expscale = 1.0 else: expscale = expin # Compute what plane of the context image this input would # correspond to: planeid = int((uniqid-1) / 32) # Check if the context image has this many planes if outcon.ndim == 3: nplanes = outcon.shape[0] elif outcon.ndim == 2: nplanes = 1 else: nplanes = 0 if nplanes <= planeid: raise IndexError("Not enough planes in drizzle context image") # Alias context image to the requested plane if 3d if outcon.ndim == 2: outctx = outcon else: outctx = outcon[planeid] pix_ratio = output_wcs.pscale/wcslin_pscale if wcsmap is None and cdriz is not None:'Using WCSLIB-based coordinate transformation...')'stepsize = %s' % stepsize) mapping = cdriz.DefaultWCSMapping( input_wcs, output_wcs, input_wcs.pixel_shape[0], input_wcs.pixel_shape[1], stepsize ) else: # ##Using the Python class for the WCS-based transformation # # Use user provided mapping function'Using coordinate transformation defined by user...') if wcsmap is None: wcsmap = wcs_functions.WCSMap wmap = wcsmap(input_wcs,output_wcs) mapping = wmap.forward _shift_fr = 'output' _shift_un = 'output' ystart = 0 nmiss = 0 nskip = 0 # # This call to 'cdriz.tdriz' uses the new C syntax # _dny = insci.shape[0] # Call 'drizzle' to perform image combination if insci.dtype > np.float32: #WARNING: Input array recast as a float32 array insci = insci.astype(np.float32) _vers,nmiss,nskip = cdriz.tdriz(insci, inwht, outsci, outwht, outctx, uniqid, ystart, 1, 1, _dny, pix_ratio, 1.0, 1.0, 'center', pixfrac, kernel, in_units, expscale, wt_scl, fillval, nmiss, nskip, 1, mapping) if nmiss > 0: log.warning('! %s points were outside the output image.' % nmiss) if nskip > 0: log.debug('! Note, %s input lines were skipped completely.' % nskip) return _vers
[docs]def get_data(filename): fileroot,extn = fileutil.parseFilename(filename) extname = fileutil.parseExtn(extn) if extname[0] == '': extname = "PRIMARY" if os.path.exists(fileroot): handle = fileutil.openImage(filename, memmap=False) data = handle[extname].data handle.close() else: data = None return data
[docs]def create_output(filename): fileroot,extn = fileutil.parseFilename(filename) extname = fileutil.parseExtn(extn) if extname[0] == '': extname = "PRIMARY" if not os.path.exists(fileroot): # We need to create the new file pimg = fits.HDUList() phdu = fits.PrimaryHDU() phdu.header['NDRIZIM'] = 1 pimg.append(phdu) if extn is not None: # Create a MEF file with the specified extname ehdu = fits.ImageHDU(data=arr) ehdu.header['EXTNAME'] = extname[0] ehdu.header['EXTVER'] = extname[1] pimg.append(ehdu)'Creating new output file: %s' % fileroot) pimg.writeto(fileroot) del pimg else:'Updating existing output file: %s' % fileroot) handle =, mode='update', memmap=False) return handle,extname
[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()
[docs]def getHelpAsString(docstring = False, show_ver = True): """ return useful help from a file in the script directory called ```` """ 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
drizzle.__doc__ = getHelpAsString(docstring = True, show_ver = False)