Lab2 Group (2021-22) :rocket:

This repo is made to hold all the code and data generated by lab experiments.

There are two branches: main and active.

Latex files Current status of latex files.

Usage

This repo should be maintained up-to-date with the latest experiments and data.

There is a ./esperienza_#__<title> folder for each one lab. experience. Those are then divided as described in README for each sub-directory.

The setup.py file is meant to be used to create the base project for a lab. experience. To run setup.py use python3 setup.py <OPTIONAL: expNumber_title>

Requirements

Software needed to use this repo is listed below:

• root, An open-source data analysis framework used by high energy physics and others, developed by CERN (currently using v6.24/02 or v6.22/06 to run code);
• stat custom library (Currently v1.0). Run as g++ -o <exe_name> <program.cpp> stat.cpp.
• LabTools.h is a C++ library only used for general purpouse C++ classes and namespaces for easier graph manipulation and statistical computation (see LabTools installation and usage).
• ErrorAnalysis/ErrorAnalysis.h class function used to compute error propagationa and analysis.
• various python libraries are used: numpy, matplotlib, scipy, pandas, mainly for data analisys on-the-go, alongside with jupiter-notebook.
• LTSpice is a software used for schematics simulation, needed to read .asc files.
• PyLTSpice v1.5(also on Github) and ltspice 1.0.4 are used for LTSpice simulation automation in Python and for data visualization. <!-- - numpy Python library is only needed in order for the setup.py program to work. -->

Future code might need other libraries, that will be eventually be written here.

Stat Library

stat is a C++ library made exclusively to compute the statistical average and standard error. It is located in stat/stat.h.

Library Usage

This library is just a piece of code written to facilitate some computing, eventually it needs to be implemented in the code.

• stat::read_values() takes a stdin::vector as input, whereas the vector contain all data needed in calculation.

• stat::avg() return average of elements in the vector.

• stat::std_err() return standard error computed from RMS (Root Minimum Square).

• stat::clear() is needed to clean up the data vector, in order to compute other data.

LabTools

Inside LabTools there is the full definition and implementation for the LabTools c++ library. It needs to be compiled and if used in ROOT needs to be included in the rootlogon.C root file.

How to install

inside LabTools folder go to build/ (cd build). Then do the following bash $ cmake .. $ make $ sudo make install Then go to $HOME and create (if non existing!) the .rootrc file by doing bash $ touch .rootrc and add the following line to .rootrc: Rint.Logon: ~/rootlogon.C

Finally, in your $HOME directory create a file named rootlogon.C by doing bash $ touch rootlogon.C and modify this file adding the following lines cpp { gInterpreter->AddIncludePath("/usr/local/include"); gSystem->Load("/usr/local/lib/libLabTools"); }

Now to load the Library in any program you'll need to ```cpp

include

```

If using ROOT macros, no other compiler instruction is needed. To use this library in compiled c/c++ programs you'll need to do the following: bash $ g++ file_name.cpp -o exe_name -I/usr/local/include -L/usr/local/lib/ -lLabTools `root-config --glibs --cflags` where `root-config --glibs --cflags` is only needed if the code calls for other ROOT specific functions.

Changelog