lstmcpipe.scripts package

lstmcpipe.scripts package#

Subpackages#

Submodules#

lstmcpipe.scripts.generate_nsb_levels_configs module#

lstmcpipe.scripts.generate_nsb_levels_configs.build_argparser()#

Build the argument parser for the script.

Returns:

The argument parser object.

Return type:

argparse.ArgumentParser

lstmcpipe.scripts.generate_nsb_levels_configs.dump_lstchain_nsb_config(nsb_tuning, outdir='.')#

Dump the lstchain configuration file with the given nsb_tuning_rate_GHz.

Parameters:

nsb_tuning_rate_GHz (float) – The nsb tuning rate in GHz.

lstmcpipe.scripts.generate_nsb_levels_configs.lstchain_config_name(nsb_tuning)#

Generate the name of the lstchain configuration file based on the given nsb_tuning_rate_GHz.

Parameters:

nsb_tuning_rate_GHz (float) – The nsb tuning rate in GHz.

Returns:

The name of the lstchain configuration file.

Return type:

str

lstmcpipe.scripts.generate_nsb_levels_configs.lstmcpipe_config_filename(nsb_tuning, outdir='.')#

Generate the name of the lstmcpipe configuration file based on the given nsb_tuning_rate_GHz.

Parameters:

nsb_tuning_rate_GHz (float) – The nsb tuning rate in GHz.

Returns:

The name of the lstmcpipe configuration file.

Return type:

str

lstmcpipe.scripts.generate_nsb_levels_configs.main()#

Dump the lstchain and lstmcpipe configuration files for the given nsb_tuning_rate_GHz.

lstmcpipe.scripts.generate_nsb_levels_configs.prod_id(nsb_tuning, prefix=None)#

Generate the prod ID based on the given nsb_tuning_rate_GHz.

Parameters:

  • nsb_tuning_rate_GHz (float) – The nsb tuning rate in GHz.

  • prefix (str) – The prefix of the prod ID. Example: “20240918_v0.10.12”

Returns:

The prod ID.

Return type:

str

lstmcpipe.scripts.generate_test_lapalma module#

Script to generate a mini production tree with symlinks to a few simtel files and the corresponding path config. This is used to test lstmcpipe on a small prod

lstmcpipe.scripts.generate_test_lapalma.generate_test_allsky(working_dir, nfiles=5, path_to_config_file='.', decs=['dec_4822', 'dec_931'], overwrite=True)#
lstmcpipe.scripts.generate_test_lapalma.generate_test_prod5trans80(working_dir, nfiles=5, path_to_config_file='.', overwrite=True)#
lstmcpipe.scripts.generate_test_lapalma.generate_tree(base_dir, working_dir, nfiles)#

Walk the base dir looking for simtels files When a directory contains simtels files, it’s tree structure is duplicated into the working dir and nfiles are symlinked there

lstmcpipe.scripts.lstmcpipe_generate_config module#

class lstmcpipe.scripts.lstmcpipe_generate_config.ParseKwargs(option_strings, dest, nargs=None, const=None, default=None, type=None, choices=None, required=False, help=None, metavar=None)#

Bases: Action

Parse a string formatted as option1=foo into a dict {option1: foo}

lstmcpipe.scripts.lstmcpipe_generate_config.build_argparser()#
lstmcpipe.scripts.lstmcpipe_generate_config.list_config_classes()#

List the classes in lstmcpipe.config.paths_config that inherit from lstmcpipe.config.paths_config.PathConfig

Returns:

[object]

Return type:

list of classes

lstmcpipe.scripts.lstmcpipe_generate_config.main()#

lstmcpipe.scripts.script_batch_filelist_cta module#

lstmcpipe.scripts.script_batch_filelist_cta.main()#

lstmcpipe.scripts.script_batch_filelist_lst module#

lstmcpipe.scripts.script_batch_filelist_lst.main()#

lstmcpipe.scripts.script_batch_filelist_lst_dl1ab module#

lstmcpipe.scripts.script_batch_filelist_lst_dl1ab.main()#

lstmcpipe.scripts.script_batch_filelist_rta module#

lstmcpipe.scripts.script_batch_filelist_rta.main()#

lstmcpipe.scripts.script_compare_irfs module#

lstmcpipe.scripts.script_compare_irfs.main()#
lstmcpipe.scripts.script_compare_irfs.plot_comparison(filelist, outfile=None, cta_north=False)#

Create a 2x2 plot comparing different sensitivity curves

Parameters:

  • filelist (list) – File list with sensitivity curves to be compared.

  • outfile (str or Path or None) – path to the output file to be saved. if None, the figure is not saved

  • cta_north (Bool) – Flag to superpose/add (True) or not (False - Default) the CTA North. Imported from ctaplot

lstmcpipe.scripts.script_dl2_to_sensitivity module#

Procedure adapted from pyirf v0.4 example one (used with eventdisplay)

lstmcpipe.scripts.script_dl2_to_sensitivity.determine_source_position(gamma_events)#
lstmcpipe.scripts.script_dl2_to_sensitivity.main()#

lstmcpipe.scripts.script_lstmcpipe_validate_config module#

lstmcpipe.scripts.script_lstmcpipe_validate_config.build_argparser()#
lstmcpipe.scripts.script_lstmcpipe_validate_config.main()#
lstmcpipe.scripts.script_lstmcpipe_validate_config.mc_r0_path()#
lstmcpipe.scripts.script_lstmcpipe_validate_config.mc_requirements(config)#
lstmcpipe.scripts.script_lstmcpipe_validate_config.run_lstchain_mc_r0_dl1(simtel_file, outdir, config_file)#
lstmcpipe.scripts.script_lstmcpipe_validate_config.test_dl1ab(config_file)#
lstmcpipe.scripts.script_lstmcpipe_validate_config.test_r0_dl1(config_file)#
lstmcpipe.scripts.script_lstmcpipe_validate_config.validate_lstchain(config_file, stage)#

lstmcpipe.scripts.script_train_test_splitting module#

lstmcpipe.scripts.script_train_test_splitting.main()#
lstmcpipe.scripts.script_train_test_splitting.move_files(filelist, outdir)#

Move all files within filelist to outdir

Parameters:

  • filelist (list) – list of files to be written

  • outdir (Path) – Output directory Path

lstmcpipe.scripts.script_train_test_splitting.write_filelist(filelist, outdir, dataset='')#

Write all files within filelist in {dataset}.list file at outdir

Parameters:

  • filelist (list) – list of files to be written

  • outdir (Path) – Output directory Path

  • dataset (str) – ‘training’ or ‘testing’ dataset list

Module contents#