# -*- coding: utf-8 -*- # A simple benchmark script for DP3 and wsclean # they need to be in "./mss/" import sys, os, glob, re, argparse import numpy as np import time import lsmtool import multiprocessing as mp ######################################################## from LiLF import lib_ms, lib_img, lib_util, lib_log logger_obj = lib_log.Logger('script-benchmark.logger') logger = lib_log.logger s = lib_util.Scheduler(log_dir=logger_obj.log_dir, dry=False) w = lib_util.Walker('script-benchmark.walker') parset = lib_util.getParset() parset_dir = parset.get('LOFAR_self', 'parset_dir') parser = argparse.ArgumentParser(description="Benchmark LOFAR software.") parser.add_argument("msfiles", type=str, help="Input ms files, glob-like string") parser.add_argument("--sourcedb", default='', help="If you want to provide a certain skymodel.") args = parser.parse_args() ############################################################################# # Clear with w.if_todo('cleaning'):
#!/usr/bin/env python # -*- coding: utf-8 -*- # Pipeline to run on the calibrator observation. # It isolates various systematic effects and # prepare them for the transfer to the target field. import sys, os, glob, re import numpy as np ######################################################## from LiLF import lib_ms, lib_img, lib_util, lib_log lib_log.Logger('pipeline-cal.logger') logger = lib_log.logger s = lib_util.Scheduler(dry=False) # parse parset parset = lib_util.getParset() parset_dir = parset.get('cal', 'parset_dir') data_dir = parset.get('cal', 'data_dir') skymodel = parset.get('cal', 'skymodel') imaging = parset.getboolean('cal', 'imaging') bl2flag = parset.get('flag', 'stations') if 'LBAsurvey' in os.getcwd(): obs = os.getcwd().split('/')[-2] # assumes .../c??-o??/3c196 calname = os.getcwd().split('/')[-1] # assumes .../c??-o??/3c196 data_dir = '../../download/%s/%s' % (obs, calname) ############################################################# MSs = lib_ms.AllMSs(glob.glob(data_dir + '/*MS'), s)
#!/usr/bin/env python # -*- coding: utf-8 -*- # Data preparation for selfcal, apply cal solutions # and split SB in time and concatenate in frequency. import sys, os, glob, re import numpy as np from astropy.time import Time import casacore.tables as pt ######################################################## from LiLF import lib_ms, lib_util, lib_log logger_obj = lib_log.Logger('pipeline-timesplit.logger') logger = lib_log.logger s = lib_util.Scheduler(log_dir=logger_obj.log_dir, dry=False) w = lib_util.Walker('pipeline-timesplit.walker') # parse parset parset = lib_util.getParset() parset_dir = parset.get('LOFAR_timesplit', 'parset_dir') data_dir = parset.get('LOFAR_timesplit', 'data_dir') cal_dir = parset.get('LOFAR_timesplit', 'cal_dir') ngroups = parset.getint('LOFAR_timesplit', 'ngroups') initc = parset.getint( 'LOFAR_timesplit', 'initc') # initial tc num (useful for multiple observation of same target) bl2flag = parset.get('flag', 'stations') ################################################# # Clean
# Pipeline for single facet self calibration import sys, os, glob, re import numpy as np import pyrap.tables as pt import lsmtool #TODO, to extract from regionfile: lastcycle = 0 # get from somewhere target_reg = 'target.reg' ####################################################### from LiLF import lib_ms, lib_img, lib_util, lib_log, lib_dd logger_obj = lib_log.Logger('pipeline-facet_self.logger') logger = lib_log.logger s = lib_util.Scheduler(log_dir=logger_obj.log_dir, dry=False) #, maxThreads = 4) w = lib_util.Walker('pipeline-facet-self.walker') # parse parset parset = lib_util.getParset() parset_dir = parset.get('LOFAR_facet_self', 'parset_dir') maxniter = parset.getint('LOFAR_facet_self', 'maxniter') userReg = parset.get('model', 'userReg') mosaic_image = lib_img.Image('ddcal/images/c%02i/mos-MFS-image.fits' % lastcycle) ############################ if w.todo('cleaning'): logger.info('Cleaning...') lib_util.check_rm('plot*')