Getting started with validphys
validphys you must provide a YAML input runcard which includes
The resources you need (PDFs, fits, etc.)
The actions (functions) you would like to be carried out
Additional flags and parameters for fine-tuning
Metadata describing the author, title and keywords
To get an idea of the layout, Examples details the example runcards that can be found in this folder. The Tutorials section also takes you through how to make runcards for various tasks.
A simple example is:
pdf: NNPDF40_nlo_as_01180 theoryid: 208 use_cuts: "internal" dataset_input: dataset: ATLASWZRAP36PB cfac: [EWK] actions_: - plot_fancy - plot_chi2dist
We are specifying one PDF (by the LHAPDF id),
one dataset and one
theory. Note that the dataset specification is identical to that of
n3fit configuration files.
We are saying that we do not want to use any cuts on the data (so we do not have to specify a fit containing the cut data, for example).
actions_ key is used to declare the actions we want to
have executed. The syntax is the same as for the targets inside the
report (see How to generate a report). We want a data-theory comparison (
see How to do a data theory comparison) and to
plot the distribution of the chi² for each replica (
Once you have created a runcard (e.g.
runcard.yaml), simply run
to set the ball rolling. For information on writing more complex runcards see here.
Another useful command to be aware of is
vp-comparefits - i, which launches an interactive
session to compare two fits. See the tutorial How to compare two fits for more information.
For more tailored analysis, the API provides a high level interface to the code, allowing you to extract objects and play around with them. See Using the validphys API.
validphys --help command can give you information on modules and specific actions, e.g.
$ validphys --help plots
will list all the actions defined in the plots module together with a brief description of each of them. Asking for the help of one of the actions will list all the inputs required for this action. For example:
$ validphys --help fits_chi2_table fits_chi2_table Defined in: validphys.results Generates: table fits_chi2_table(fits_total_chi2_data, fits_datasets_chi2_table, fits_groups_chi2_table, show_total: bool = False) Show the chi² of each and number of points of each dataset and experiment of each fit, where experiment is a group of datasets according to the ``experiment`` key in the PLOTTING info file, computed with the theory corresponding to the fit. Dataset that are not included in some fit appear as ``NaN`` The following additionl arguments can be used to control the behaviour. They are set by default to sensible values: show_total(bool) = False per_point_data(bool) = True [Used by fits_groups_chi2_table]
We can see which keys have a special meaning in the configuration file with
$ validphys --help config
All other keys are interpreted literally (although they could be further processed by specific actions).