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LArSoft Basics for DUNE

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Introduction to art and LArSoft

Overview

Teaching: 50 min
Exercises: 0 min
Questions

  • Why do we need a complicated software framework? Can’t I just write standalone code?

Objectives

  • Learn what services the art framework provides.

  • Learn how the LArSoft toolkit is organized and how to run its command-line tools.

Introduction to art

Art is the framework used for the offline software used to process LArTPC data from the far detector and the ProtoDUNEs. It was chosen not only because of the features it provides, but also because it allows DUNE to use and share algorithms developed for other LArTPC experiments, such as ArgoNeuT, LArIAT, MicroBooNE and ICARUS. The section below describes LArSoft, a shared software toolkit. Art is also used by the NOvA and mu2e experiments. The primary language for art and experiment-specific plug-ins is C++.

The art wiki page is here: https://cdcvs.fnal.gov/redmine/projects/art/wiki. It contains important information on command-line utilities, how to configure an art job, how to define, read in and write out data products, how and when to use art modules, services, and tools.

Art features:

  1. Defines the event loop
  2. Manages event data storage memory and prevents unintended overwrites
  3. Input file interface – allows ganging together input files
  4. Schedules module execution
  5. Defines a standard way to store data products in art-formatted ROOT files
  6. Defines a format for associations between data products (for example, tracks have hits, and associations between tracks and hits can be made via art’s association mechanism).
  7. Provides a uniform job configuration interface
  8. Stores job configuration information in art-formatted root files.
  9. Output file control – lets you define output filenames based on parts of the input filename.
  10. Message handling
  11. Random number control
  12. Exception handling

The configuration storage is particularly useful if you receive a data file from a colleague, or find one in a data repository and you want to know more about how it was produced, with what settings.

Getting set up to try the tools

Log in to a dunegpvmXX.fnal.gov machine, which runs Alma Linux 9 with no container needed, or to lxplus.cern.ch. Set up your environment as in the setup episode.

This episode only runs existing LArSoft and dunesw tools on existing files. It does not build or modify code, so the AL9 Spack environment is all you need. Checking out and modifying code (Episodes 05.5 and 06) still needs the SL7 container; see the fallback at the end of this section.

Do not mix environments

Source either the AL9/Spack setup or the SL7 container in a given shell, not both. Start a fresh shell when you switch.

AL9 / Spack setup (default)

Start from a clean shell with no other experiment’s setup sourced.

source /cvmfs/dune.opensciencegrid.org/spack/setup-env.sh
spack env activate dune-prototype

Activating the environment puts lar, root, and the rest of dunesw on your path. No separate spack load is needed. For Spack and MPD documentation and issue tracking, see the DUNE Spack project.

Instructor check: environment

Verified 2026-09-07 on dunegpvm13: spack instance v1.2.2, environment dune-prototype, dunesw@10.22.00d01, root@6.28.12. setup-env.sh selects the current instance automatically (v1.0 and v1.1 are deprecated). Spack and MPD docs, config reference, and issues: https://dune.github.io/dune-spack-project/.

In a live session, confirm spack env list includes dune-prototype, and that which lar and root --version both resolve after the activate.

What you should see

$ which lar && root --version
/cvmfs/dune.opensciencegrid.org/spack/environments/dune-prototype/.spack-env/view/bin/lar
ROOT Version: 6.28/12

Define the sample file used through this episode. This is an xrootd URL; file access works the same way in either environment.

export SAMPLE_FILE=root://fndca1.fnal.gov:1094//pnfs/fnal.gov/usr/dune/persistent/users/schellma/tutorial_2025/NNBarAtm_hA_BR_dune10kt_1x2x6_54053565_607_20220331T192335Z_gen_g4_detsim_reco_65751406_0_20230125T150414Z_reReco.root

Instructor check: sample file

Verified present 2026-09-07 with xrdfs fndca1.fnal.gov stat /pnfs/fnal.gov/usr/dune/persistent/users/schellma/tutorial_2025/NNBarAtm_hA_BR_dune10kt_1x2x6_54053565_607_20220331T192335Z_gen_g4_detsim_reco_65751406_0_20230125T150414Z_reReco.root. It sits in a user persistent area from an earlier tutorial. Re-check near the session date; if it has been cleaned up, stage a fresh copy under this year’s tutorial area.

Get a token for streaming access (htgettoken -a htvaultprod.fnal.gov -i dune, see the setup episode), then check that the tools are on your path:

which lar
lar --help
which root
root --version

If lar --help fails with “command not found” or a missing-library error, dunesw is not set up in your session. Stop and flag it rather than continuing into the exercises below. The Spack environment may have changed since this page was last checked; ask in #computing-training-basics on DUNE Slack.

The examples below refer to files in dCache at Fermilab, which are best accessed with xrootd.

No Fermilab access but a CERN account

Copies of the tutorial files are in /afs/cern.ch/work/t/tjunk/public/jan2023tutorialfiles/.

The follow-up of this tutorial provides help on how to find data and MC files in storage.

SL7 container fallback

You need this only if a command in this episode fails under Spack, or if you are continuing to Episodes 05.5 and 06. mrb and UPS-based development do not yet work under Spack on AL9.

Start the SL7 container from a shell where the Spack environment is not active. A fresh login shell is the safe choice. Apptainer copies the parent shell’s environment into the container, so a leftover LD_LIBRARY_PATH from spack env activate makes the container’s root and lar load the AL9 ROOT libraries and fail with GLIBC_2.33 not found. setup dunesw does not undo that.

Use the alias for your machine (defined in the setup episode): dunesl7 on a gpvm, dunesl7build on a build node, dunesl7CERN at CERN. Starting a container gives you a very bare environment. It does not source your .profile, so do that yourself. I always set the prompt variable PS1 in my profile so I can tell that I have sourced it:

PS1="<`hostname`> "; export PS1

Then set up dunesw:

dunesl7
source .profile
source /cvmfs/dune.opensciencegrid.org/products/dune/setup_dune.sh

export DUNELAR_VERSION=v10_22_00d01
export DUNELAR_QUALIFIER=e26:prof
setup dunesw $DUNELAR_VERSION -q $DUNELAR_QUALIFIER

<get a token>

Instructor check: dunesw version

dune-prototype on AL9 carries dunesw@10.22.00d01 (verified 2026-09-07), so v10_22_00d01 is correct. Inside the SL7 container, confirm the UPS tag and qualifier with ups list -aK+ dunesw near the session date, and update every DUNELAR_VERSION in this lesson (including the scripts in Episode 06) if it has moved.

Once dunesw is set up this way, every command in the rest of this episode (config_dumper, fhicl-dump, count_events, product_sizes_dumper, lar, root) runs the same as on the AL9 path. This is the previously verified route; use it to get a session unblocked while any AL9 gaps are sorted out.

You can list available versions of dunesw in CVMFS with:

ups list -aK+ dunesw

The output is not sorted, although portions of it may look sorted. Do not depend on it being sorted. The version tag looks like v10_22_00d01. The qualifiers here are e26 and prof. Qualifiers can be entered in any order and are separated by colons. “e26” corresponds to a specific version of the GNU compiler. We also compile with clang; the compiler qualifier for that is “c7”. “prof” means compiled with optimizations turned on, “debug” means turned off. More information on qualifiers is here.

UPS products also have “flavors”, meaning the operating system type and version. Currently only SL7 and the compatible CentOS 7 are supported. The flavor is selected automatically to match your OS when you set up a product. Products that do not depend on OS libraries are “unflavored” and listed with a flavor of “NULL”.

The operating system provides its own setup command, which you usually do not want. If you have not sourced setup_dune.sh but type setup xyz anyway, you get the system setup, which asks for the root password. Type control-C, source setup_dune.sh, and try again. On AL9 and inside the SL7 container there is no system setup command, so you get “command not found” instead.

UPS’s own setup command (find where it lives with type setup) sets up the product you name and all dependent products at consistent versions. List everything that is set up with ups active, and pipe through grep to find one product, for example ups active | grep geant4 to see the Geant4 version.

To learn more about ups see more documentation here. For how the AL9 Spack environment replaces this UPS setup, and how the two compare, see the DUNE Spack project.

Art command-line tools

All of these command-line tools have online help. Invoke the help feature with the --help command-line option. Example:

config_dumper --help

Docmentation on art command-line tools is available on the art wiki page.

config_dumper

Configuration information for a file can be printed with config_dumper.

config_dumper -P <artrootfile>

Try it out:

config_dumper -P $SAMPLE_FILE

The output is an executable fcl file, sent to stdout. We recommend redirecting the output to a file that you can look at in a text editor:

Try it out:

config_dumper -P $SAMPLE_FILE > tmp.fcl

Your shell may be configured with noclobber, meaning that if you already have a file called tmp.fcl, the shell will refuse to overwrite it. Just rm tmp.fcl and try again.

The -P option to config_dumper is needed to tell config_dumper to print out all processing configuration fcl parameters. The default behavior of config_dumper prints out only a subset of the configuration parameters, and is most notably missing art services configuration.

Quiz

Quiz questions from the output of the above run of config_dumper:

  1. What generators were used? What physics processes are simulated in this file?
  2. What geometry is used? (hint: look for “GDML” or “gdml”)
  3. What electron lifetime was assumed?
  4. What is the readout window size?

fhicl-dump

You can parse a FCL file with fhicl-dump.

Try it out:

fhicl-dump protoDUNE_refactored_g4_stage2.fcl

See the section below on FCL files for more information on what you’re looking at.

count_events

Try it out:

count_events $SAMPLE_FILE

product_sizes_dumper

You can get a peek at what’s inside an artROOT file with product_sizes_dumper.

Try it out:

product_sizes_dumper -f 0 $SAMPLE_FILE

It is also useful to redirect the output of this command to a file so you can look at it with a text editor and search for items of interest. This command lists the sizes of the TBranches in the Events TTree in the artROOT file. There is one TBranch per data product, and the name of the TBranch is the data product name, an “s” is appended (even if the plural of the data product name doesn’t make sense with just an “s” on the end), an underscore, then the module label that made the data product, an underscore, the instance name, an underscore, and the process name and a period.

Quiz questions, looking at the output from above.

Quiz

Questions:

  1. What is the name of the data product that takes up the most space in the file?
  2. What the module label for this data product?
  3. What is the module instance name for this data product? (This question is tricky. You have to count underscores here).
  4. How many different modules produced simb::MCTruth data products? What are their module labels?
  5. How many different modules produced recob::Hit data products? What are their module labels?

You can open up an artROOT file with ROOT and browse the TTrees in it with a TBrowser. Not all TBranches and leaves can be inspected easily this way, but enough can that it can save a lot of time programming if you just want to know something simple about a file such as whether it contains a particular data product and how many there are.

Try it out

root $SAMPLE_FILE

then at the root prompt, type:

new TBrowser

This will be faster with VNC. Navigate to the Events TTree in the file that is automatically opened, navigate to the TBranch with the Argon 39 MCTruths (it’s near the bottom), click on the branch icon simb::MCTruths_ar39__SinglesGen.obj, and click on the NParticles() leaf (It’s near the bottom. Yes, it has a red exclamation point on it, but go ahead and click on it). How many events are there? How many 39Ar decays are there per event on average?

A stale ~/.rootrc breaks the TBrowser icons

The TBrowser works under dune-prototype (verified 2026-09-07, ROOT 6.28/12). If it opens with a burst of *.xpm not found errors instead, move an old ~/.rootrc aside and start root again:

mv ~/.rootrc ~/.rootrc.old

Why: an old ROOT config file

A ~/.rootrc left over from the SL7 and UPS days overrides Gui.IconPath with a path that does not exist in the Spack ROOT layout, so the GUI cannot find its button and scrollbar pixmaps. The giveaway is errors like

Error in <TGVSplitter::TGVSplitter>: splitterv.xpm not found
Error in <TGComboBox::TGComboBox>: arrow_down.xpm not found

together with messages mentioning $SRT_PRIVATE_CONTEXT or $SRT_PUBLIC_CONTEXT, variables from a build system retired years ago.

Header files for many data products are in lardataobj and some are in nusimdata.

Art is not constrained to using ROOT files – we use HDF5-formatted files for some purposes. ROOT has nice browsing features for inspecting ROOT-formatted files; Some HDF5 data visualiztion tools exist, but they assume that data are in particular formats. ROOT has the ability to display more general kinds of data (C++ classes), but it needs dictionaries for some of the more complicated ones.

The art main executable program is a very short stub that interprets command-line options, reads in the configuration document (a FHiCL file which usually includes other FHiCL files), and loads shared libraries, initializes software components, and schedules execution of modules. Most code we are interested in is in the form of art plug-ins – modules, services, and tools. The generic executable for invoking art is called art, but a LArSoft-customized one is called lar. No additional customization has yet been applied so in fact, the lar executable has identical functionality to the art executable.

There is online help:

 lar --help

All programs in the art suite have a --help command-line option.

Most art job invocations take the form

lar -n <nevents> -c fclfile.fcl artrootfile.root

where the input file specification is just on the command line without a command-line option. Explicit examples follow below. The -n <nevents> is optional – it specifies the number of events to process. If omitted, or if <nevents> is bigger than the number of events in the input file, the job processes all of the events in the input file. -n <nevents> is important for the generator stage. There’s also a handy --nskip <nevents_to_skip> argument if you’d like the job to start processing partway through the input file. You can steer the output with

lar -c fclfile.fcl artrootfile.root -o outputartrootfile.root -T outputhistofile.root

The outputhistofile.root file contains ROOT objects that have been declared with the TFileService service in user-supplied art plug-in code (i.e. your code).

Job configuration with FHiCL

The Fermilab Hierarchical Configuration Language, FHiCL is described here https://cdcvs.fnal.gov/redmine/documents/327.

FHiCL is not a Turing-complete language: you cannot write an executable program in it. It is meant to declare values for named parameters to steer job execution and adjust algorithm parameters (such as the electron lifetime in the simulation and reconstruction). Look at .fcl files in installed job directories, like $DUNESW_DIR/fcl for examples. Fcl files are sought in the directory seach path FHICL_FILE_PATH when art starts up and when #include statements are processed. A fully-expanded fcl file with all the #include statements executed is referred to as a fhicl “document”.

Parameters may be defined more than once. The last instance of a parameter definition wins out over previous ones. This makes for a common idiom in changing one or two parameters in a fhicl document. The generic pattern for making a short fcl file that modifies a parameter is:

#include "fcl_file_that_does_almost_what_I_want.fcl"
block.subblock.parameter: new_value

To see what block and subblock a parameter is in, use fhcl-dump on the parent fcl file and look for the curly brackets. You can also use

lar -c fclfile.fcl --debug-config tmp.txt --annotate

which is equivalent to fhicl-dump with the –annotate option and piping the output to tmp.txt.

Entire blocks of parameters can be substituted in using @local and @table idioms. See the examples and documentation for guidance on how to use these. Generally they are defined in the PROLOG sections of fcl files. PROLOGs must precede all non-PROLOG definitions and if their symbols are not subsequently used they do not get put in the final job configuration document (that gets stored with the data and thus may bloat it). This is useful if there are many alternate configurations for some module and only one is chosen at a time.

Try it out:

fhicl-dump protoDUNE_refactored_g4_stage2.fcl > tmp.txt

Look for the parameter ModBoxA. It is one of the Modified Box Model ionization parameters. See what block it is in. Here are the contents of a modified g4 stage 2 fcl file that modifies just that parameter:

#include "protoDUNE_refactored_g4_stage2.fcl"
services.LArG4Parameters.ModBoxA: 7.7E-1

Exercise

Do a similar thing – modify the stage 2 g4 fcl configuration to change the drift field from 486.7 V/cm to 500 V/cm. Hint – you will find the drift field in an array of fields which also has the fields between wire planes listed.

Types of Plug-Ins

Plug-ins each have their own .so library which gets dynamically loaded by art when referenced by name in the fcl configuration.

Producer Modules
A producer module is a software component that writes data products to the event memory. It is characterized by produces<> and consumes<> statements in the class constructor, and art::Event::put() calls in the produces() method. A producer must produce the data product collection it says it produces, even if it is empty, or art will throw an exception at runtime. art::Event::put() transfers ownership of memory (use std::move so as not to copy the data) from the module to the art event memory. Data in the art event memory will be written to the output file unless output commands in the fcl file tell art not to do that. Documentation on output commands can be found in the LArSoft wiki here. Producer modules have methods that are called on begin job, begin run, begin subrun, and on each event, as well as at the end of processing, so you can initialize counters or histograms, and finish up summaries at the end. Source code must be in files of the form: modulename_module.cc, where modulename does not have any underscores in it.

Analyzer Modules
Analyzer modules read data products from the event memory and produce histograms or TTrees, or other output. They are typically scheduled after the producer modules have been run. Producer modules have methods that are called on begin job, begin run, begin subrun, and on each event, as well as at the end of processing, so you can initialize counters or histograms, and finish up summaries at the end. Source code must be in files of the form: modulename_module.cc, where modulename does not have any underscores in it.

Source Modules
Source modules read data from input files and reformat it as need be, in order to put the data in art event data store. Most jobs use the art-provided RootInput source module which reads in art-formatted ROOT files. RootInput interacts well with the rest of the framework in that it provides lazy reading of TTree branches. When using the RootInput source, data are not actually fetched from the file into memory when the source executes, but only when GetHandle or GetValidHandle or other product get methods are called. This is useful for art jobs that only read a subset of the TBranches in an input file. Code for sources must be in files of the form: modulename_source.cc, where modulename does not have any underscores in it. Monte Carlo generator jobs use the input source called EmptyEvent.

Services
These are singleton classes that are globally visible within an art job. They can be FHiCL configured like modules, and they can schedule methods to be called on begin job, begin run, begin event, etc. They are meant to help supply configuration parameters like the drift velocity, or more complicated things like geometry functions, to modules that need them. Please do not use services as a back door for storing event data outside of the art event store. Source code must be in files of the form: servicename_service.cc, where servicename does not have any underscores in it.

Tools
Tools are FHiCL-configurable software components that are not singletons, like services. They are meant to be swappable by FHiCL parameters which tell art which .so libraries to load up, configure, and call from user code. See the Art Wiki Page for more information on tools and other plug-ins.

You can use cetskelgen to make empty skeletons of art plug-ins. See the art wiki for documentation, or use

cetskelgen --help

for instructions on how to invoke it.

Ordering of Plug-in Execution

The constructors for each plug-in are called at job-start time, after the shared object libraries are loaded by the image activater after their names have been discovered from the fcl configuration. Producer, analyzer and service plug-ins have BeginJob, BeginRun, BeginSubRun, EndSubRun, EndRun, EndJob methods where they can do things like book histograms, write out summary information, or clean up memory.

When processing data, the input source always gets executed first, and it defines the run, subrun and event number of the trigger record being processed. The producers and filters in trigger_paths then get executed for each event. The analyzers and filters in end_paths then get executed. Analyzers cannot be added to trigger_paths, and producers cannot be added to end_paths. This ordering ensures that data products are all produced by the time they are needed to be analyzed. But it also forces high memory usage for the same reason.

Services and tools are visible to other plug-ins at any stage of processing. They are loaded dynamically from names in the fcl configurations, so a common error is to use in code a service that hasn’t been mentioned in the job configuration. You will get an error asking you to configure the service, even if it is just an empty configuration with the service name and no parameters set.

Non-Plug-In Code

You are welcome to write standard C++ code – classes and C-style functions are no problem. In fact, to enhance the portability of code, the art team encourages the separation of algorithm code into non-framework-specific source files, and to call these functions or class methods from the art plug-ins. Typically, source files for standalone algorithm code have the extension .cxx while art plug-ins have .cc extensions. Most directories have a CMakeLists.txt file which has instructions for building the plug-ins, each of which is built into a .so library, and all other code gets built and put in a separate .so library.

Retrieving Data Products

In a producer or analyzer module, data products can be retrieved from the art event store with getHandle() or getValidHandle() calls, or more rarely getManyByType or other calls. The arguments to these calls specify the module label and the instance of the data product. A typical TBranch name in the Events tree in an artROOT file is

simb::MCParticles_largeant__G4Stage1.

here, simb::MCParticle is the name of the class that defines the data product. The “s” after the data product name is added by art – you have no choice in this even if the plural of your noun ought not to just add an “s”. The underscore separates the data product name from the module name, “largeant”. Another underscore separates the module name and the instance name, which in this example is the empty string – there are two underscores together there. The last string is the process name and usually is not needed to be specified in data product retrieval. You can find the TBranch names by browsing an artroot file with ROOT and using a TBrowser, or by using product_sizes_dumper -f 0.

Art documentation

There is a mailing list – art-users@fnal.gov where users can ask questions and get help.

There is a workbook for art available at https://art.fnal.gov/art-workbook/ Look for the “versions” link in the menu on the left for the actual document. It is a few years old and is missing some pieces like how to write a producer module, but it does answer some questions. I recommend keeping a copy of it on your computer and using it to search for answers.

There was an art/LArSoft course in 2015. While it, too is a few years old, the examples are quite good and it serves as a useful reference.

Gallery is a lightweight tool that lets users read art-formatted root files and make plots without having to write and build art modules. It works well with interpreted and compiled ROOT macros, and is thus ideally suited for data exploration and fast turnaround of making plots. It lacks the ability to use art services, however, though some LArSoft services have been split into services and service providers. The service provider code is intended to be able to run outside of the art framework and linked into separate programs.

Gallery also lacks the ability to write data products to an output file. You are of course free to open and write files of your own devising in your gallery programs. There are example gallery ROOT scripts in duneexamples/duneexamples/GalleryScripts. They are only in the git repository but do not get installed in the UPS product.

More documentation: https://art.fnal.gov/gallery/

LArSoft

Introductory Documentation

LArSoft’s home page: larsoft.org

The LArSoft wiki is here: larsoft-wiki.

Software structure

The LArSoft toolkit is a set of software components that simulate and reconstruct LArTPC data, and also it provides tools for accessing raw data from the experiments. LArSoft contains an interface to GEANT4 (art does not list GEANT4 as a dependency) and the GENIE generator. It contains geometry tools that are adapted for wire-based LArTPC detectors.

LArSoft provides a collection of shared simulation, reconstruction, and analysis tools, with art interfaces. Often, a useful algorithm will be developed by an experimental collaboration, and desire to share it with other LArTPC collaborations, which is how much of the software in LArSoft came to be. Interfaces and services have to be standardized for shared use. Things like the detector geometry and the dead channel list, for example, are detector-specific, but shared simulation and reconstruction algorithms need to be able to access information from these services, which are not defined until an experiment’s software stack is set up and the lar program is invoked. LArSoft therefore uses plug-ins and class inheritance extensively to deal with these situations.

A recent graph (v10_00) of the UPS products in a full stack starting with dunesw is available here (dunesw). You can see the LArSoft pieces under dunesw, as well as GEANT4, GENIE, ROOT, and a few others.

LArSoft Data Products

A very good introduction to data products such as raw digits, calibrated waveforms, hits and tracks, that are created and used by LArSoft modules and usable by analyzers was given by Tingjun Yang at the 2019 ProtoDUNE analysis workshop (larsoft-data-products).

There are a number of data product dumper fcl files. A non-exhaustive list of useful examples is given below:

 dump_mctruth.fcl
 dump_mcparticles.fcl
 dump_simenergydeposits.fcl
 dump_simchannels.fcl
 dump_simphotons.fcl
 dump_rawdigits.fcl
 dump_wires.fcl
 dump_hits.fcl
 dump_clusters.fcl
 dump_tracks.fcl
 dump_pfparticles.fcl
 eventdump.fcl
 dump_lartpcdetector_channelmap.fcl
 dump_lartpcdetector_geometry.fcl

Some of these may require some configuration of input module labels so they can find the data products of interest. Try one of these yourself:

lar -n 1 -c dump_mctruth.fcl $SAMPLE_FILE

This command will make a file called DumpMCTruth.log which you can open in a text editor. Reminder: MCTruth are particles made by the generator(s), and MCParticles are those made by GEANT4, except for those owned by the MCTruth data products. Due to the showering nature of LArTPCs, there are usually many more MCParticles than MCTruths.

Examples and current workflows

The page with instructions on how to find and look at ProtoDUNE data has links to standard fcl configurations for simulating and reconstructing ProtoDUNE data: https://wiki.dunescience.org/wiki/Look_at_ProtoDUNE_SP_data.

Try it yourself! The workflow for ProtoDUNE-SP MC is given in the Simulation Task Force web page.

Running on a dunegpvm machine at Fermilab

Warning: this takes time and has high peak memory use, and the environment does not change that. On dunegpvm13 (2026-09-07) the gen stage took about 90 seconds for one event and reco stage 1 took about 5 minutes for one event with a peak resident set size near 3.8 GB (WireCell signal processing, Pandora, and the Michel-ID module dominate). Run a single event unless you have a reason not to.

Set up as in the setup episode. On AL9:

 export USER=`whoami`
 mkdir -p /exp/dune/data/users/$USER/tutorialtest
 cd /exp/dune/data/users/$USER/tutorialtest

 source /cvmfs/dune.opensciencegrid.org/spack/setup-env.sh
 spack env activate dune-prototype

 TMPDIR=/tmp lar -n 1 -c mcc12_gen_protoDune_beam_cosmics_p1GeV.fcl -o gen.root
 lar -n 1 -c protoDUNE_refactored_g4_stage1.fcl gen.root -o g4_stage1.root
 lar -n 1 -c protoDUNE_refactored_g4_stage2_sce_datadriven.fcl g4_stage1.root -o g4_stage2.root
 lar -n 1 -c protoDUNE_refactored_detsim_stage1.fcl g4_stage2.root -o detsim_stage1.root
 lar -n 1 -c protoDUNE_refactored_detsim_stage2.fcl detsim_stage1.root -o detsim_stage2.root
 lar -n 1 -c protoDUNE_refactored_reco_35ms_sce_datadriven_stage1.fcl detsim_stage2.root -o reco_stage1.root
 lar -c eventdump.fcl reco_stage1.root >& eventdump_output.txt
 config_dumper -P reco_stage1.root >& config_output.txt
 product_sizes_dumper -f 0 reco_stage1.root >& productsizes.txt

What each stage does

Each lar command reads the previous stage’s art/ROOT file and writes the next one. This is the ProtoDUNE-SP chain, so it produces a different detector’s file from the Far Detector $SAMPLE_FILE used earlier in the episode.

  • gen (mcc12_gen_protoDune_beam_cosmics_p1GeV.fcl): event generation. Builds the primary particles: a 1 GeV beam particle from the H4 beamline simulation, a CORSIKA cosmic-ray overlay, and radiological backgrounds (39Ar, 42Ar, 85Kr, 222Rn). Output is truth-level only (simb::MCTruth, simb::MCParticle), no detector response yet.
  • g4 stage 1 (protoDUNE_refactored_g4_stage1.fcl): Geant4 transport of those particles through the detector geometry, producing energy deposits in the liquid argon (sim::SimEnergyDeposit).
  • g4 stage 2 (protoDUNE_refactored_g4_stage2_sce_datadriven.fcl): drift of the ionization electrons to the anode with the data-driven space-charge map applied, and propagation of scintillation light to the photon detectors. Produces sim::SimChannel.
  • detsim stage 1 (protoDUNE_refactored_detsim_stage1.fcl): TPC electronics response. Converts sim::SimChannel into digitized ADC waveforms (raw::RawDigit) with noise and cold-electronics shaping.
  • detsim stage 2 (protoDUNE_refactored_detsim_stage2.fcl): the rest of the readout simulation (photon-detector electronics and trigger-primitive level).
  • reco stage 1 (protoDUNE_refactored_reco_35ms_sce_datadriven_stage1.fcl): signal processing (deconvolution to recob::Wire), hit finding (recob::Hit), and Pandora pattern recognition (recob::PFParticle, recob::Track, recob::Shower, recob::SpacePoint) with calorimetry. “35ms” is the assumed electron lifetime. This is the file the dump and event-display commands below use.

There is no CAF step in this chain. CAFs, the flat Common Analysis Format ntuples, come from a separate CAFMaker job run on a reconstructed Far Detector file such as $SAMPLE_FILE; ProtoDUNE analyses instead use pduneana analyzer trees.

Instructor note: the descriptions above are a summary. Check the data products each stage actually writes with product_sizes_dumper -f 0 on its output file, and correct this list against the current dunesw if the refactored chain has changed.

Prefixing TMPDIR=/tmp on the same line defines that variable only for that one command. The generator stage copies a 2.9 GB beam file, plus several CORSIKA cosmic-ray databases, through ifdh’s temporary area, which defaults to /var/tmp. Some dunegpvm machines are short on free space in /var/tmp, so pointing TMPDIR at /tmp heads off a mid-job copy failure. The prod4 fcl files can stream the beam file with XRootD instead, but streaming is off by default in the prod4 fcl for the dunesw version used here, so setting TMPDIR is the smaller change. The prod4 fcl files are here.

Instructor check: ifdh and TMPDIR

Verified 2026-09-07 on dunegpvm13 under dune-prototype (ifdhc@2.8.0): the generator stage runs to completion (exit status 0, about 90 seconds) both with and without TMPDIR=/tmp. ifdh stages into /var/tmp/ifdh_* by default and into /tmp/ifdh_* with the override. Free space in /var/tmp varies by machine, so keep the TMPDIR=/tmp line as a safeguard rather than dropping it.

Run the event display on your new Monte Carlo event

 lar -c evd_protoDUNE_data.fcl reco_stage1.root

and push the “Reconstructed” radio button at the bottom of the display.

The event display currently needs the SL7 container

Tried 2026-09-07 on dunegpvm13 under dune-prototype with a clean ~/.rootrc. evd_protoDUNE_data.fcl reads the file, then fails during beginJob with a fatal ROOT error before any window opens:

Fatal Root Error: TGPictureButton::TGPictureButton
pixmap not found or the file format is not supported for button -1
ROOT severity: 3000
Art has completed and will exit with status 1

The event display toolbar loads button pixmaps that are not on the Spack ROOT icon path, and it treats a missing one as fatal (unlike the TBrowser, which only warns). Until this is fixed in the Spack build, run the event-display exercises in the SL7 container. Issue to track: DUNE Spack project.

Display decoded raw digits

This also uses the event display, so the same SL7 requirement applies for now (see the callout above).

To look at some raw digits in the event display, you need to decode a DAQ file or find one that’s already been decoded. The decoder fcl for ProtoDUNE-HD data taken in 2024 is run_pdhd_wibeth3_tpc_decoder.fcl. An event display of an example decoded file is

 lar -c evd_protoDUNE_data.fcl /exp/dune/data/users/trj/nov2024tutorial/np04hd_raw_run028707_0075_dataflow5_datawriter_0_20240815T154544_decode.root

which is a file taken in August 2024.

Running on HDF5 raw data

One has to load (on the same line) a special library to stream HDF5 formatted data from vd-protodune and hd-protodune. LD_PRELOAD=$XROOTD_LIB/libXrdPosixPreload.so has to be on the same line as your lar command:

export DATA=root://ccxrootdegee.in2p3.fr:1094/pnfs/in2p3.fr/data/dune/disk/hd-protodune/d1/a6/np04hd_raw_run029147_0032_dataflow4_datawriter_0_20240912T110618.hdf5
LD_PRELOAD=$XROOTD_LIB/libXrdPosixPreload.so lar -c standard_reco_protodunehd_keepup.fcl $DATA -n 1

HDF5 raw-data reading: not working yet, fix coming soon

As of September 2026 the recipe above does not run on either path, so the tutorial does not exercise it. It is kept here as a record of how it is meant to work.

  • AL9 / dune-prototype Spack: $XROOTD_LIB is not set in the Spack environment, so LD_PRELOAD expands to /libXrdPosixPreload.so and the loader rejects it (ld.so: object '/libXrdPosixPreload.so' from LD_PRELOAD cannot be preloaded).
  • SL7 container: the preload line is fine, but opening the CC-IN2P3 URL above fails with HDF5RawDataFile ... File open failure ... (File accessibility) Unable to open file.

A working AL9 recipe (the real libXrdPosixPreload.so path plus a reachable input file) will be added here once it is sorted out.

Running at CERN

This example puts all files in a subdirectory of your home directory. There is an input file for the ProtoDUNE-SP beamline simulation that is copied over and you need to point the generation job at it. The above sequence of commands will work at CERN if you have a Fermilab grid proxy, but not everyone signed up for the tutorial can get one of these yet, so we copied the necessary file over and adjusted a fcl file to point at it. It also runs faster with the local copy of the input file than the above workflow which copies it.

This assumes you are logged into an lxplus node running Alma 9 and using the dune-prototype Spack environment, set up as in the setup episode. If you need the SL7 container at CERN instead, use the dunesl7CERN alias from that episode.

Make a fcl file and call it tmpgen.fcl

#include "mcc12_gen_protoDune_beam_cosmics_p1GeV.fcl"
physics.producers.generator.FileName: "/afs/cern.ch/work/t/tjunk/public/may2023tutorialfiles/H4_v34b_1GeV_-27.7_10M_1.root"

if you have difficulties opening an editor

echo '#include "mcc12_gen_protoDune_beam_cosmics_p1GeV.fcl"' > tmpgen.fcl
echo 'physics.producers.generator.FileName: "/afs/cern.ch/work/t/tjunk/public/may2023tutorialfiles/H4_v34b_1GeV_-27.7_10M_1.root"' >> tmpgen.fcl

then do some setup. On an lxplus node running Alma 9, use the Spack environment:

 cd ~
 mkdir 2024Tutorial
 cd 2024Tutorial

 source /cvmfs/dune.opensciencegrid.org/spack/setup-env.sh
 spack env activate dune-prototype

Now you can run a sequence of lar steps to generate and reconstruct a file.

 lar -n 1 -c tmpgen.fcl -o gen.root
 lar -n 1 -c protoDUNE_refactored_g4_stage1.fcl gen.root -o g4_stage1.root
 lar -n 1 -c protoDUNE_refactored_g4_stage2_sce_datadriven.fcl g4_stage1.root -o g4_stage2.root
 lar -n 1 -c protoDUNE_refactored_detsim_stage1.fcl g4_stage2.root -o detsim_stage1.root
 lar -n 1 -c protoDUNE_refactored_detsim_stage2.fcl detsim_stage1.root -o detsim_stage2.root
 lar -n 1 -c protoDUNE_refactored_reco_35ms_sce_datadriven_stage1.fcl detsim_stage2.root -o reco_stage1.root
 lar -c eventdump.fcl reco_stage1.root >& eventdump_output.txt
 config_dumper -P reco_stage1.root >& config_output.txt
 product_sizes_dumper -f 0 reco_stage1.root >& productsizes.txt

You can also browse the root files with a TBrowser or run other dumper fcl files on them. The dump example commands above redirect their outputs to text files which you can edit with a text editor or run grep on to look for things.

You can run the event display with the command below, from the SL7 container for now (see the event-display callout earlier in this episode).

lar -c evd_protoDUNE.fcl reco_stage1.root

but it will run very slowly over a tunneled X connection. A VNC session will be much faster. Tips: select the “Reconstructed” radio button at the bottom and click on “Unzoom Interest” on the left to see the reconstructed objects in the three views.

DUNE software documentation and how-to’s

The following legacy wiki page provides information on how to check out, build, and contribute to dune-specific larsoft plug-in code.

https://cdcvs.fnal.gov/redmine/projects/dunetpc/wiki

The follow-up part of this tutorial gives hands-on exercises for doing these things.

Contributing to LArSoft

The LArSoft git repositories are hosted on GitHub and use a pull-request model. LArSoft’s github link is https://github.com/larsoft. DUNE repositories, such as the dunesw stack, protoduneana and garsoft are also on GitHub but at the moment (not for long however), allow users to push code.

To work with pull requests, see the documentation at this link: https://larsoft.github.io/LArSoftWiki/Developing_With_LArSoft

There are bi-weekly LArSoft coordination meetings https://indico.fnal.gov/category/405/ at which stakeholders, managers, and users discuss upcoming releases, plans, and new features to be added to LArSoft.

Useful tip: check out an inspection copy of larsoft

A good old-fashioned grep -r or a find command can be effective if you are looking for an example of how to call something but I do not know where such an example might live. The copies of LArSoft source in CVMFS lack the CMakeLists.txt files and if that’s what you’re looking for to find examples, it’s good to have a copy checked out. Here’s a script that checks out all the LArSoft source and DUNE LArSoft code but does not compile it. Warning: it deletes a directory called “inspect” in your app area. Make sure /exp/dune/app/users/<yourusername> exists first:

SL7 container needed here

This checks out source with mrb, which does not work under Spack on AL9 yet. Use the dunesl7 alias from the setup episode.

 #!/bin/bash
 USERNAME=`whoami`
 export DUNELAR_VERSION=v10_22_00d01
 export DUNELAR_QUALIFIER=e26:prof
 source /cvmfs/dune.opensciencegrid.org/products/dune/setup_dune.sh
 cd /exp/dune/app/users/${USERNAME}
 rm -rf inspect
 mkdir inspect
 cd inspect
 setup dunesw ${DUNELAR_VERSION} -q ${DUNELAR_QUALIFIER}
 mrb newDev
 source /exp/dune/app/users/${USERNAME}/inspect/localProducts*/setup
 cd srcs
 mrb g larsoft_suite
 mrb g larsoftobj_suite
 mrb g larutils
 mrb g larbatch
 mrb g dune_suite
 mrb g -d dune_raw_data dune-raw-data

Putting it to use: A very common workflow in developing software is to look for an example of how to do something similar to what you want to do. Let’s say you want to find some examples of how to use FindManyP – it’s an art method for retrieving associations between data products, and the art documentation isn’t as good as the examples for learning how to use it. You can use a recursive grep through your checked-out version, or you can even look through the installed source in CVMFS. This example looks through the duneprototype product’s source files for FindManyP:

 cd $DUNEPROTOTYPES_DIR/source/duneprototypes
 grep -r -i findmanyp *

It is good to use the -i option to grep which tells it to ignore the difference between uppercase and lowercase string matches, in case you misremembered the case of what you are looking for. The list of matches is quite long – you may want to pipe the output of that grep into another grep

 grep -r -i findmanyp * | grep recob::Hit

The checked-out versions of the software have the advantage of providing some files that don’t get installed in CVMFS, notably CMakeLists.txt files and the UPS product_deps files, which you may want to examine when looking for examples of how to do things.

GArSoft

GArSoft is another art-based software package, designed to simulate the ND-GAr near detector. Many components were copied from LArSoft and modified for the pixel-based TPC with an ECAL. You can find installed versions in CVMFS with the following command:

ups list -aK+ garsoft

and you can check out the source and build it by following the instructions on the GArSoft wiki.

Key Points

  • Art provides the tools physicists in a large collaboration need in order to contribute software to a large, shared effort without getting in each others’ way.

  • Art helps us keep track of our data and job configuration, reducing the chances of producing mystery data that no one knows where it came from.

  • LArSoft is a set of simulation and reconstruction tools shared among the liquid-argon TPC collaborations.

  • Running these tools on existing files works under AL9 and the dune-prototype Spack environment; building or modifying them still needs the SL7 container.

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