Auto mcp w/o MC

magicctapipe/scripts/lst1_magic/semi_automatic_scripts/__init__.py

@@ -8,41 +8,34 @@
 from .coincident_events import configfile_coincidence, linking_bash_lst
 from .dl1_production import (
     config_file_gen,
-    directories_generator_MC,
     directories_generator_real,
     lists_and_bash_gen_MAGIC,
-    lists_and_bash_generator,
 )
 from .job_accounting import run_shell
 from .list_from_h5 import clear_files, list_run, magic_date, split_lst_date
 from .merge_stereo import MergeStereo
-from .merging_runs import merge, mergeMC, split_train_test
-from .stereo_events import bash_stereo, bash_stereoMC, configfile_stereo
+from .merging_runs import merge
+from .stereo_events import bash_stereo, configfile_stereo
 
 __all__ = [
     "bash_stereo",
-    "bash_stereoMC",
     "clear_files",
     "configfile_coincidence",
     "configfile_stereo",
     "config_file_gen",
     "directories_generator_real",
-    "directories_generator_MC",
     "existing_files",
     "fix_lists_and_convert",
     "linking_bash_lst",
-    "lists_and_bash_generator",
     "lists_and_bash_gen_MAGIC",
     "list_run",
     "magic_date",
     "merge",
-    "mergeMC",
     "MergeStereo",
     "missing_files",
     "rc_lines",
     "run_shell",
     "slurm_lines",
     "split_lst_date",
-    "split_train_test",
     "table_magic_runs",
 ]

magicctapipe/scripts/lst1_magic/semi_automatic_scripts/config_auto_MCP.yaml

@@ -8,12 +8,7 @@ mc_tel_ids:
 
 directories:
     workspace_dir : "/fefs/aswg/workspace/elisa.visentin/auto_MCP_PR/"  # Output directory where all the data products will be saved.
-    # MC paths below are ignored if you set NSB_matching = true.
-    MC_gammas     : "/fefs/aswg/data/mc/DL0/LSTProd2/TestDataset/sim_telarray"  # set to "" if you don't want to process these Monte Carlo simulations.
-    MC_electrons  : "" 
-    MC_helium     : "" 
-    MC_protons    : "/fefs/aswg/data/mc/DL0/LSTProd2/TrainingDataset/Protons/dec_2276/sim_telarray" 
-    MC_gammadiff  : "/fefs/aswg/data/mc/DL0/LSTProd2/TrainingDataset/GammaDiffuse/dec_2276/sim_telarray/"
+
 
 data_selection:
     source_name_database: "CrabNebula"  # MUST BE THE SAME AS IN THE DATABASE; Set to null to process all sources in the given time range.
@@ -29,12 +24,9 @@ general:
     base_config_file: ''    # path + name to a custom MCP config file. If not provided, the default config.yaml file will be used 
     LST_version   : "v0.10" # check the `processed_lstchain_file` version in the LST database!
     LST_tailcut   : "tailcut84"
-    focal_length  : "effective"
     simtel_nsb    : "/fefs/aswg/data/mc/DL0/LSTProd2/TestDataset/sim_telarray/node_theta_14.984_az_355.158_/output_v1.4/simtel_corsika_theta_14.984_az_355.158_run10.simtel.gz" # simtel file (DL0) to evaluate NSB
-    lstchain_modified_config : true # use_flatfield_heuristic = True to evaluate NSB
-    proton_train_fraction  : 0.8  # 0.8 means that 80% of the DL1 protons will be used for training the Random Forest.
+    lstchain_modified_config : true # use_flatfield_heuristic = True to evaluate NSB    
     nsb           : [0.5, 1.0, 1.5, 2.0, 2.5, 3.0]
     env_name      : magic-lst  # name of the conda environment to be used to process data.
     cluster       : "SLURM"  # cluster management system on which data are processed. At the moment we have only SLURM available, in the future maybe also condor (PIC, CNAF).
-    NSB_matching  : true  # Set to false to process also the MCs. Set to true if adequate MC productions (DLx) are already available on the IT Container.
-    NSB_MC        : 0.5  # extra noise in dim pixels used to process MCs; e.g., you could put here the average NSB value of the processed LST runs. Ignored if NSB_matching=true.
+