WebApp#

JADE V&V environment includes a WebApp that allows to visualize JADE results without the need to install any software. The WebApp is hosted on GitHub here.

For a benchmark to be supported by the web app a .json file must be added in the resources folder. The name of the file should be the same as the one used in the raw data repository. In such file, a structure like the following should be added for each of the tallies that are to be supported:

{
    ...
"Reaction Rates - S32 (n,p) P32": {
    "result": "ASPIS-PCA-Replica_S Reaction Rate S",
    "substitutions": {
            "Cells": "Shielding thickness [cm]",
            "Value": "C/E (Reaction rate)"
        },
        "plot_type": "scatter",
        "plot_args": {
            "x": "Shielding thickness [cm]",
            "y": "C/E (Reaction rate)",
            "log_x": false,
            "log_y": false
        },
        "y_axis_format": {
            "tickformat": ".2e"
        },
        "only_ratio": true
    },
    ...
}

where the key of the tally dictionary is the name that will appear on the web app tally selection. If a “-” is contained, it will consider it a couple category - option and will split the selection into two parts (or more). This is particularly useful for benchmarks with a huge list of available tallies which more often than not are just combination of different configuration of the same benchmark (i.e. a change in geometry or materials) and actual available tallies.

At the same tally level, a "general" tally can be optionally specified. This contains parameters that are not related to the rendering of the single tally result, but are applicable to the benchmark itself. The only options available for the moment are:

tally_options_labels

This accepts a list of labels that will be used to give additional information in case the tally selection was to be split into subcategories

generic_tallies

This allows to define generic tallies instead of specific ones. more details can be found below in the tally_name option

If generic_tallies has been set to true, it is also possible to define “generic” tallies, like for the Sphere SDDR benchmark. This is to be used when different versions of the same benchmarks are run (for instance, different isotopes in the sphere) but they all have the same tallies. It is not useful to individually include all the tallies for each isotope (they can be hundreds) in the .json file, hence, a generic tally is defined. As an example, if all .csv results are provided as “benchmark_option1-option2 tallyname.csv”, then a generic tally should be provided with key = “{} - {} - quantity name”. Internally, the code, during the initialization of the Processor class will substitute each “{}” for one of the options and add a tally config for each combination of option1 and option2 found across the .csv.

The following, instead, are the available options for each tally configuration.

Mandatory configuration options#

result

it can either be a string of a list of strings. If it’s a single string, it is interpreted as the name of the .csv file in the raw data repository that contains the data to plot. If it’s a list of strings, it corresponds to the group of .csv files in the raw data repository whose data will be plotted together. If a generic tally is being defined and the corresponding .csv files follow the naming convention “benchmark_option1-option2 tallyname.csv”, only the tallyname should be specified for this configuration option. The same .csv file can be used across different tally dictionaries.

plot_type

at the moment the available plot types are step, scatter and grouped_bar. You can check the webapp directly to have a feeling of how these plots look like.

plot_args

this is the dictionary of options that will be passed directly to the plotly native functions. The minimum requirement is to specify at least the x and y column name to be used for the plot. For a full reference of the available additional options you can check:

Optional configuration options#

y_axis_format and x_axis_format

these parameters allow you to customize the axis properties such as ticks number, labels, labels format, etc. You can see a complete list of the parameters that can be controlled at this page of the plotly API reference.

subset

a list [column_name, value] is expected. The effect is that from the total raw data table, only the rows that contain value in the specified column will be retained for plotting.

only_ratio

forces the plot always to be C/E (ratio). This is sometimes useful for some of the experimental benchmarks where absolute values are not that important.