crogan / phsx815_week1

PHSX815 Spring 2021 Week 1

Random number generation and data visualization

This repository contains three examples (coded in three different ways) that illustrates random number generation and simple data visualization (plotting). Three different plotting libraries are used (which requires users to independently download and setup/install these libraries - instructions at the links below)

• matplotlib (Python)
• matplotlib (C++)
• ROOT (C++)

Example usage

matplotlib (Python)

The python file python/Random_python.py can be run from the command line by typing:

<> python python/Random_python.py

This requires a working Python distribution (so that the python executable exists) with the Python package numpy also installed.

matplotlib (C++)

The C++ source file src/Random_matplotlib.C can be compiled into an executable by changing directories to the main folder of this repository (the folder containing the file Makefile) and typing:

<> make

In order for this to be successful, users need to edit the Makefile in order to include the correct paths to

• the matplotlib-cpp GitHub package
• the header files (in the include folder) for Python
• the header files for numpy
• the shared library for python Users can see the matplotlib (C++) documentaion for more information about where to find these folders on their machine.

This will create the Random_matplotlib.x, executable which can be run from the command line by typing:

<> ./Random_matplotlib.x

ROOT (C++)

The C++ macro macros/Random_ROOT.Cis set up to run in the ROOT command line interpreter environment. To use this functionality, users must first download and install ROOT on their machine (this will create shared libraries and header files that can be used in compiled C++ code, like the previous example, and the root executable).

To enter the ROOT command line environment users can type:

<> root

From the ROOT command line users can then run the macros/Random_ROOT.C macro by typing:

<> .x macros/Random_ROOT.C+