This repository contains code for measuring the ionization electron diffusion coefficients,
- C++ source code for extracting waveform information from calibration ntuples
- Python modules for extracting the
$D_L$ and$D_T$ measurements and making plots -
project.pyconfiguration xml files for job submission to Fermigrid
The project.py configuration files are provided for reference, and should not be expected to run for a generic user without modification. We include them here to document icaruscode versions, fcl file configurations, tar balls used, etc.
To-do. Include link to technical note.
The C++ (waveform analyzer) and Python (measurement and plotting) portions of this code can be installed and used independently. An easy place to do so is on the ICARUS gpvms, but installation should work in any environment that has access to ROOT (for the C++ code) and/or Python v3.6 or greater. The steps listed below have been tested with icaruscode v09_56_00_01, which includes ROOT and Python v3.9.2. From an ICARUS gpvm, this can be setup as follows:
source /cvmfs/icarus.opensciencegrid.org/products/icarus/setup_icarus.sh
# Setup any version of icaruscode with python version >= 3.6
setup icaruscode v09_56_00_01 -q e20:prof
Assuming you have access to ROOT and have setup the appropriate environment variables, the C++ code is simple to build. From the top directory, run the following commands:
cd cpp/src/
make
If you encounter build errors, there is likely an issue with your ROOT installation.
The Python code includes some external dependencies which by default cannot be installed by users on the gpvms (and other servers with similar security measures). The easiest way to manage these installations without causing conflicts is to create a virtual environment using Python's built-in venv module. Virtual environments are stored in a directory where you have write access (e.g., in your /app space) and can be activated when necessary.
cd /path/to/virtual/environments # e.g., in your /app space
python3 -m venv my_environment
where my_environment can be named whatever you want. To activate the virtual environment and install the packages necessary for the diffusion measurement code,
source /path/to/virtual/environments/my_environment/bin/activate
cd /path/to/lardiff/python/
python3 -m pip install .
This will install the lardiff package and its dependencies in your virtual environment. To test your installation, open up an interactive Python session and attempt to import this package:
$ python3
>>> import lardiff
If there are no errors, you should then be able to run the Python scripts using the output files from the waveform analyzer as input.
The diffusion analysis code can be run through a command-line interface. The executable located in /path/to/lardiff/python/bin/ can be run as:
python run_diffusion_analysis.py --input_filename <input_file> --config <config.yaml>
where input_file should be a ROOT-format file output from the C++ WaveformStudy.cpp module and config.yaml is a config file containing the necessary configuration parameters described below.
Due to the large number of configurable parameters, and the possibility of adding more parameters in the future, the diffusion analysis code called from run_diffusion_analysis.py is configured through a yaml file. You can find example configuration files in /path/to/lardiff/python/config. The config file should contain the following parameters:
- DL_min: minimum
$D_L$ value in$cm^2/s$ in the grid scan - DL_max: maximum
$D_L$ value in$cm^2/s$ in in the grid scan - DL_step:
$D_L$ step size in the$\chi^2$ grid scan - DT_min: minimum
$D_T$ value in in$cm^2/s$ in the grid scan - DT_max: maximum
$D_T$ value in in$cm^2/s$ in the grid scan - DT_step:
$D_T$ step size in the grid scan - angle_min: minimum angular bin value in degrees
- angle_max: maximum angular bin value in degrees
- angle_step: angular bin step size. This should be set to 2.
- test_statistic: which test statistic to use in the grid scan
- interpolation: interpolation method to use when interpolating signal waveforms, e.g.
'scipy'or'numpy' - isdata: boolean flag stating whether the input file was processed from simulation or data
- save_waveform_data: boolean flag that controls whether a sample set of wire waveforms is saved to a
.pklfile for offline use
To-do
To-do
Distributed under the MIT License. See LICENSE for more information.