uratools 1.0.0

Tools to simplify the use of URANIE with python

uratools

This Python module provides tools to simplify the use of URANIE with Python

uratools aims to provide a multitude of utilities designed to enhance the user experience, particularly by facilitating ports to NumPy, interfacing Uranie with Python machine learning libraries (PyTorch, TensorFlow, and scikit-learn), and providing tools for fitting empirical distributions and generating plots easily. It will be updated regularly.

URANIE

• Website: https://uranie.cea.fr/
• Python documentation: https://uranie.cea.fr/documentation/userManual_Py/index
• Installation: https://gitlab.com/uranie-cea/publication/-/wikis/home
• Uratools documentation https://uratools-508bc1.gitlab.io/

Installation

pip install uratools

How to use it

Before using the package, ensure that URANIE is installed and properly sourced.

The python command to use the package is the following

from uratools import converter

Documentation is available on this page https://uratools-508bc1.gitlab.io/

Example

import numpy as np
import ROOT
from ROOT.URANIE import DataServer, Sampler
from uratools import converter

## == np.array to DataServer
mA = np.random.randn(10,2)
tds = converter.np2ds(mA, "x1:x2") ## a DataServer.TDataServer is created from np.array

## == DataServer to np.array 
tds = DataServer.TDataServer()
tds.addAttribute(DataServer.TUniformDistribution("x1",0.0, 5.0))
tds.addAttribute(DataServer.TNormalDistribution("x2",-2.0, 0.5))
sam = Sampler.TSampling(tds,"lhs",20)
sam.generateSample()

npA = converter.ds2np(tds) ## a np.array is created from a DataServer.TDataServer

Support

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