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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,100 @@ | ||
| #!/usr/bin/env python | ||
|
|
||
| """ | ||
| Make a map containing model objects using the info in a nemo output catalog | ||
| """ | ||
|
|
||
| import os | ||
| import sys | ||
| import numpy as np | ||
| import astropy.table as atpy | ||
| from astLib import * | ||
| from nemo import startUp | ||
| from nemo import maps | ||
| import argparse | ||
| import astropy.io.fits as pyfits | ||
|
|
||
| #------------------------------------------------------------------------------------------------------------ | ||
| if __name__ == '__main__': | ||
|
|
||
| parser=argparse.ArgumentParser("nemoModel") | ||
| parser.add_argument("catalogFileName", help = """A catalog (FITS table format) as produced by nemo.""") | ||
| parser.add_argument("templateFileName", help = """A FITS image file. The output sky model image will | ||
| have the same pixelization.""") | ||
| parser.add_argument("beamFileName", help = """A file containing the beam profile, in the standard format | ||
| used by ACT.""") | ||
| parser.add_argument("outputFileName", help = """The name of the output file that will contain the sky | ||
| model image.""") | ||
| parser.add_argument("-f", "--frequency-GHz", dest = "obsFreqGHz", type = float, default = 150.0, | ||
| help = """If the nemo catalog contains SZ-selected clusters, the SZ signal will be | ||
| evaluted at the given frequency, ignoring relativistic effects | ||
| (default: 150.0).""") | ||
| parser.add_argument("-M", "--mpi", dest="MPIEnabled", action="store_true", help="""Enable MPI. If used, | ||
| the image will be broken into a number of tiles, with one tile per process. If you | ||
| want to use this, run with e.g., mpiexec -np 4 nemoMass configFile.yml -M""", | ||
| default = False) | ||
| parser.add_argument("-n", "--no-strict-errors", dest="noStrictMPIExceptions", action="store_true", | ||
| help="""Disable strict exception handling (applies under MPI only, i.e., must be | ||
| used with the -M switch). If you use this option, you will get the full traceback | ||
| when a Python Exception is triggered, but the code may not terminate. This is due | ||
| to the Exception handling in mpi4py.""", | ||
| default = False) | ||
| args = parser.parse_args() | ||
|
|
||
| if args.noStrictMPIExceptions == True: | ||
| strictMPIExceptions=False | ||
| else: | ||
| strictMPIExceptions=True | ||
|
|
||
| # Create a stub config (then we can use existing start-up stuff to dish out the tiles) | ||
| parDict={} | ||
| mapDict={} | ||
| mapDict['mapFileName']=args.templateFileName | ||
| mapDict['obsFreqGHz']=args.obsFreqGHz | ||
| mapDict['beamFileName']=args.beamFileName | ||
| parDict['unfilteredMaps']=[mapDict] | ||
| parDict['mapFilters']=[] | ||
| if args.MPIEnabled == True: | ||
| parDict['makeTileDir']=True | ||
| parDict['tileOverlapDeg']=1.0 | ||
| parDict['tileDefLabel']='auto' | ||
| parDict['tileDefinitions']={'targetTileWidthDeg': 10.0, 'targetTileHeightDeg': 5.0} | ||
|
|
||
| config=startUp.NemoConfig(parDict, MPIEnabled = args.MPIEnabled, divideTilesByProcesses = True, | ||
| makeOutputDirs = False, setUpMaps = True, writeTileDir = False, | ||
| verbose = False, strictMPIExceptions = strictMPIExceptions) | ||
|
|
||
| tab=atpy.Table().read(args.catalogFileName) | ||
|
|
||
| # Build a dictionary containing the model images which we'll stich together at the end | ||
| modelsDict={} | ||
| for tileName in config.tileNames: | ||
| shape=(config.tileCoordsDict[tileName]['clippedSection'][3], | ||
| config.tileCoordsDict[tileName]['clippedSection'][1]) | ||
| wcs=astWCS.WCS(config.tileCoordsDict[tileName]['header'], mode = 'pyfits') | ||
| try: | ||
| modelsDict[tileName]=maps.makeModelImage(shape, wcs, tab, args.beamFileName, | ||
| obsFreqGHz = args.obsFreqGHz) | ||
| except: | ||
| raise Exception("makeModelImage failed on tile '%s'" % (tileName)) | ||
|
|
||
| # Gathering | ||
| if config.MPIEnabled == True: | ||
| config.comm.barrier() | ||
| gathered_modelsDicts=config.comm.gather(modelsDict, root = 0) | ||
| if config.rank == 0: | ||
| print("... gathered sky model tiles ...") | ||
| for tileModelDict in gathered_modelsDicts: | ||
| for tileName in tileModelDict.keys(): | ||
| modelsDict[tileName]=tileModelDict[tileName] | ||
|
|
||
| # Stitching | ||
| if config.rank == 0: | ||
| d=np.zeros([config.origWCS.header['NAXIS2'], config.origWCS.header['NAXIS1']]) | ||
| wcs=config.origWCS | ||
| for tileName in modelsDict.keys(): | ||
| minX, maxX, minY, maxY=config.tileCoordsDict[tileName]['clippedSection'] | ||
| d[minY:maxY, minX:maxX]=modelsDict[tileName] | ||
| astImages.saveFITS(args.outputFileName, d, wcs) |
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