Analyzing ldmx-sw Event Files
Often when first starting on LDMX, people are given a .root file produced by ldmx-sw
(or some method for producing their own file). This then leads to the very next
and reasonable question -- how to analyze the data in this file?
Many answers to this question have been said and many of them are functional. In subsequent sections of this chapter of the website, I choose to focus on highlighting two possible analysis workflows that I personally like (for different reasons).
I am not able to fully cover all of the possible different types of analysis, so I am writing this guide in the context of one of the most common analyses: looking at a histogram. This type of analysis can be broken into four steps.
- Load data: from a data file, load the information in that file into memory.
- Data Manipulation: from the data already present, calculate the variable that you would like to put into the histogram.
- Histogram Filling: define how the histogram should be binned and fill the histogram with the variable that you calculated.
- Plotting: from the definition of the histogram and its content, draw the histogram in a visual manner for inspection.
The software that is used to do each of these steps is what mainly separates the different analysis workflows, so I am first going to mention various software tools that are helpful for one or more of these steps. I have separated these tools into two "ecosystems", both of which are popularly used within HEP.
| Purpose | ROOT | scikit-hep |
|---|---|---|
| Load Data | TFile,TTree | uproot |
| Manipulate Data | C++ Code | Vectorized Python with awkward |
| Fill Histograms | TH1* | hist,boost_histogram |
| Plot Histograms | TBrowser, TCanvas | matplotlib,mplhep |
How one mixes and matches these tools is a personal choice, especially since the LDMX collaboration has not landed on a widely agreed-upon method for analysis. With this in mind, I find it important to emphasize that the following subsections are examples of analysis workflows -- a specific analyzer can choose to mix and match the tools however they like.
Caveat
While I (Tom Eichlersmith) have focused on two potential analysis workflows, I do not mean to claim that I have tried all of them and these two are "the best". I just mean to say that I have drifted to these two analysis workflows over time as I've looked for easier and better methods of analyzing data. If you have an analysis workflow that you would like to share, add another subsection to this chapter of the website!