quickstats 0.8.5.4

A tool for quick statistical analysis for HEP experiments

Setup

Clone the repository:

git clone ssh://[e-mail]:7999/clcheng/quickstats.git

1. CERN User

To set up from lxplus, just do

source setup.sh

2. Genearl User

To set up locally, make sure you have pyROOT 6.24+ installed (using conda is recommended), and do

pip install quickstats

Installing pyROOT

Simplest way to install pyROOT is via conda

conda install -c conda-forge ROOT

Important: First-time compilation

To compile c++ dependencies, do this for first time use

quickstats compile

Command Line Tools

Run Nuisance Parameter Pulls and Ranking

quickstats run_pulls -i <input_ws_path> -d <dataset_name> -p <np_name/pattern> --poi <poi_name> --parallel -1 -o <output_dir>

The following options are available

Option	Description	Default
-i/--input_file	Path to the input workspace file	-
-w/--workspace	Name of workspace. Auto-detect by default.	None
-m/--model_config	Name of model config. Auto-detect by default.	None
-d/--data	Name of dataset	"combData"
-p/--parameter	Nuisance parameter(s) to run pulls on. Multiple parameters are separated by commas. Wildcards are accepted. All NPs will be run over by default	""
-x/--poi	POIs to measure. If empty, impact on POI will not be calculated.	""
-r/--profile	Parameters to profile	""
-f/--fix	Parameters to fix	""
-s/--snapshot	Name of initial snapshot	"nominalNuis"
-o/--outdir	Output directory	"pulls"
-t/--minimizer_type	Minimizer type	"Minuit2"
-a/--minimizer_algo	Minimizer algorithm	"Migrad"
-c/--num_cpu	Number of CPUs to use per parameter	1
--binned/--unbinned	Whether to use binned likelihood	True
-q/--precision	Precision for scan	0.001
-e/--eps	Tolerance	1.0
-l/--log_level	Log level	"INFO"
--eigen/--no-eigen	Compute eigenvalues and vectors	False
--strategy	Default fit strategy	0
--fix-cache/--no-fix-cache	Fix StarMomentMorph cache	True
--fix-multi/--no-fix-multi	Fix MultiPdf level 2	True
--offset/--no-offset	Offset likelihood	True
--optimize/--no-optimize	Optimize constant terms	True
--max_calls	Maximum number of function calls	-1
--max_iters	Maximum number of Minuit iterations	-1
--parallel	Parallelize job across different nuisanceparameters using N workers. Use -1 for N_CPU workers.	0
--cache/--no-cache	Cache existing result	True
--exclude	Exclude NPs (wildcard is accepted)	""

Plot Nuisance Parameter Pulls and Ranking

quickstats plot_pulls --help

Likelihood Fit (Best-fit)

quickstats likelihood_fit --help

Run Likelihood Scan

quickstats likelihood_scan --help

Asymptotic CLs Limit

quickstats cls_limit --help

CLs Limit Scan

quickstats limit_scan --help

Generate Asimov dataset

quickstats generate_standard_asimov --help

Inspect Workspace

quickstats inspect_workspace --help

Create Workspace from XML Cards

quickstats build_xml_ws --help

Modify Workspace from XML Cards or Json Config

quickstats modify_ws --help

Combine Workspace from XML Cards or Json Config

quickstats combine_ws --help

Compare Workspaces

quickstats compare_ws --help

Run Event Loop from Custom Config File

quickstats process_rfile --help

Syntax for setting parameter values

One may modify the values and/or range of variables in a ROOT workspace via a so-called parameter expression. This is used in the class AnalysisBase (or ExtendedModel) via the method set_parameters, or through the CLIs likelihood_fit, likelihood_scan, significance_scan, cls_limit, limit_scan via the arguments --fix and --profile.

A parameter expression is a comma-separated string with the general syntax "<parameter_name>=<value_expression>,...". Here, <parameter_name> can be a string that matches the name of a given variable in the workspace, or a wildcard pattern that matches a collection of variables. There are also special magic keywords that allows matching a specific type of variables via the use of angular brackets. Currently, the following special keywords are supported:

• <poi>: matches all Parameters of Interests (POIs)
• <global_observable>: matches all Global Observables (GOs)
• <nuisance_parameter>: matches all Nuisance Parameters (NPs)
• <constrained_nuisance_parameter>: matches all NPs with associated constraint pdfs
• <unconstrained_nuisance_parameter>: matches all NPs without associated constraint pdfs
• <gaussian_constraint_np>: matches all NPs with Gaussian constraint pdfs
• <poisson_constraint_np>: matches all NPs with Poisson constraint pdfs

The <value_expression> supports the following syntax:

• Set only the nominal value: "<parameter_name>=<nominal_value>"
• Set only the range: "<parameter_name>=<min_value>_<max_value>"
• Set both nominal value and range: "<parameter_name>=<nominal_value>_<min_value>_<max_value>"
• Set nominal value, range, and error: "<parameter_name>=<nominal_value>_<min_value>_<max_value>_<error_value>"

Note that one can ommit values if you do not want to modify a particular data, i.e.:

• Set only the nominal value and the minimal range: "<parameter_name>=<nominal_value>_<min_value>_"
• Set only the error value: "<parameter_name>=___<error_value>"

Additional, if you want to change only the state of the variable(s), you may completely ommit the value expression. The state can be controlled via the mode argument in set_parameters if you are using the API. Or through the use of --fix (variables marked as constant) or --profile (variables marked as floating) if you are using the CLI.

Some CLI examples:

• Fixing the values of all NPs starting with the substring "ATLAS_" to 0 and those with substring "CMS_" to 1: --fix "ATLAS_*=0",CMS_*=1"
• Fixing (Floating) the values of all constrained (unconstrained) NPs: --fix "<constrained_nuisance_parameter>" --profile "<unconstrained_nuisance_parameter>"
• Float all POIs and setting their range to be [-10, 10] with value 1: --profile "<poi>=1_-10_10"

Some API examples:

• Fixing the values of all NPs starting with the substring "ATLAS_" to 0 and those with substring "CMS_" to 1: analysis.set_parameters("ATLAS_*=0,CMS_*=1", mode="fix")
• Floating all constrained NPs: analysis.set_parameters("<constrained_nuisance_parameters>", mode="float")
• Set all POIs' range to be [-10, 10] with value 1: analysis.set_parameters("<poi>=1_-10_10", mode="unchanged")