Code for data: validphys
validphys 2is a Python code that implements the data model of NNPDF resources.
It provides an executable, called
validphyswhich is used to analyze NNPDF specific data, which takes runcards written in YAML as an input and can produce plots, tables or entire reports as an output.
The code also provides a Python library (also called validphys) which is used to implement executables providing interfaces to more specific analyses such as the
vp-comparefits, and to serve as basis to other NNPDF codes such as
validphys 2is implemented on top of the reportengine framework.
reportengineprovides the logic to process the runcards by building task execution graphs based on individual actions (which are Python functions). The runcards can execute complex analysis and parameter scans with the appropriate use of namespaces. More information on
reportengineand its interface with
validphyscan be found in the Design section.
The ideas behind the design of the code are explained in the Design section.
Some things that validphys does
Download resources (
vp-get) - see Downloading resources
Upload resources (
--uploadflag) - see Uploading results to the validphys repository
Prepare fits for running with
vp_setupfit) - see Validphys scripts
Postprocess a fit (
postfit) - see Validphys scripts
Rename a fit or PDF (
vp-pdfrename) - see Validphys scripts
Sample a PDF (
vp-pdffromreplicas) - see Validphys scripts
Generate a report with information about possible inefficiencies in fitting methodology (
vp-deltachi2) - see Validphys scripts
Allow analysis via a high level interface - see Using the validphys API
Analyse results - see Tutorials
- Getting started with validphys
- Downloading resources
- Uploading results to the
- Writing validphys runcards
- Specifying data cuts
- Comparing data and theory
- Generating reports
- Validphys scripts
- Using the validphys API
- Developing validphys
- Producing tables and figures
validphysplots and other functionality