One key goal of pyhf is to provide seamless translations between other statistical frameworks and pyhf. This page details the various ways to translate from a tool you might already be using as part of an existing analysis to pyhf. Many of these solutions involve extracting out the HistFactory workspace and then running pyhf xml2json which provides a single JSON workspace that can be loaded directly into pyhf.


In order to go from HistFitter to pyhf, the first step is to extract out the HistFactory workspaces. Assuming you have an existing configuration file,, you likely run an exclusion fit like so: -f -D "before,after,corrMatrix" -F excl

The name of output workspace files depends on four parameters you define in your

  • analysisName is from configMgr.analysisName

  • prefix is defined in configMgr.addFitConfig({prefix})

  • measurementName is the first measurement you define via fitConfig.addMeasurement(name={measurementName},...)

  • channelName are the names of channels you define via fitConfig.addChannel("cuts", [{channelName}], ...)

  • cachePath is where HistFitter stores the cached histograms, defined by configMgr.histCacheFile which defaults to data/{analysisName}.root

To dump the HistFactory workspace, you will modify the above to skip the fit -f and plotting -D so you end up with -wx -F excl

The -w flag tells HistFitter to (re)create the HistFactory workspace stored in results/{analysisName}/{prefix}_combined_{measurementName}.root. The -x flag tells HistFitter to dump the XML files into config/{analysisName}/, with the top-level file being {prefix}.xml and all other files being {prefix}_{channelName}_cuts.xml.

Typically, prefix = 'FitConfig' and measurementName = 'NormalMeasurement'. For example, if the following exists in your

from configManager import configMgr

# ...
configMgr.analysisName = "3b_tag21.2.27-1_RW_ExpSyst_36100_multibin_bkg"
configMgr.histCacheFile = f"cache/{configMgr.analysisName:s}.root"
# ...
fitConfig = configMgr.addFitConfig("Excl")
# ...
channel = fitConfig.addChannel("cuts", ["SR_0L"], 1, 0.5, 1.5)
# ...
meas1 = fitConfig.addMeasurement(name="DefaultMeasurement", lumi=1.0, lumiErr=0.029)
# ...
meas2 = fitConfig.addMeasurement(name="DefaultMeasurement", lumi=1.0, lumiErr=0.029)

Then, you expect the following files to be made:

  • config/3b_tag21.2.27-1_RW_ExpSyst_36100_multibin_bkg/Excl.xml

  • config/3b_tag21.2.27-1_RW_ExpSyst_36100_multibin_bkg/Excl_SR_0L_cuts.xml

  • cache/3b_tag21.2.27-1_RW_ExpSyst_36100_multibin_bkg.root

  • results/3b_tag21.2.27-1_RW_ExpSyst_36100_multibin_bkg/Excl_combined_DefaultMeasurement.root

These are all the files you need in order to use pyhf xml2json. At this point, you could run

pyhf xml2json config/3b_tag21.2.27-1_RW_ExpSyst_36100_multibin_bkg/Excl.xml

which will read all of the XML files and load the histogram data from the histogram cache.

The HistFactory workspace in results/ contains all of the information necessary to rebuild the XML files again. For debugging purposes, the pyhf developers will often ask for your workspace file, which means results/3b_tag21.2.27-1_RW_ExpSyst_36100_multibin_bkg/Excl_combined_DefaultMeasurement.root. If you want to generate the XML, you can open this file in ROOT and run DefaultMeasurement->PrintXML() which puts all of the XML files into the current directory you are in.



For more details on this section, please refer to the ATLAS-internal TRExFitter documentation.

In order to go from TRExFitter to pyhf, the good news is that the RooWorkspace files (XML and ROOT) are already made for you. For a given configuration which looks like

Job: "pyhf_example"
Label: "..."

You can expect some files to be made after the n/h and w steps:

  • pyhf_example/RooStats/pyhf_example.xml

  • pyhf_example/RooStats/pyhf_example_Signal_region.xml

  • pyhf_example/Histograms/pyhf_example_Signal_region_histos.root

These are all the files you need in order to use pyhf xml2json. At this point, you could run

pyhf xml2json pyhf_example/RooStats/pyhf_example.xml

which will read all of the XML files and load the histogram data from the histogram cache.


There are a few caveats one needs to be aware of with this conversion:

  • Uncorrelated shape systematics cannot be pruned, see Issue #662.

  • Custom expressions for normalization factors cannot be used, see Issue #850.