Control-Core C++ Implementation

About

Control Core is a platform for control systems to treat conditions affecting internal organs. This repository is the C++ translation of Control Core framework which is initially written in Python. C++ inherently being faster than Python offers a much higher speed of code execution.

Table of Contents

• Quick Start 💥
• Installation 🐣
• Starting the app
• Supoorted OS ✒
• Repository Structure

Quick Start

This is the offical repository of C++ Implemention of Control Core Framework.

Installation

Follow these steps to install this project directory:

# clone the repo
$ git clone https://github.com/NISYSLAB/concore-cpp.git

# go into app's directory:
$ cd concore-cpp

Starting the app

Follow these steps to run the app on your local machine:

# go into app's directory:
$ cd concore-cpp

# in a terminal, create a sub project in the format
$ python mkconcore.py <graphml-file> <source-directory> <subproject-name> <operating-system>
  
# example for windows
$ python mkconcore.py testZ.graphml testsou t2 windows

Supported Operating Systems

1. Windows
2. Linux/Ubuntu
3. MacOS

Repository structure guidelines

1. The repo contains the original python files (pmpymat.py, cpymat.py and powermeter.py) as well as their c++ translations (pmpymat.cpp, cpymat.cpp and powermeter.cpp) in testsou directory. concore.py and concore.hpp are present in the root directory.

2. The source directory has files involving the neuromodultation which is outside the current scope.

3. The graphml files which have a 'C' in their name work with C++ translated files. Others work with the python files.
   Some highlights -
   testZ.graphml - Basic Single Port Python functionality.
   testZC.graphml - Basic Single Port Python and C++ integration functionality.
   testCC.graphml - Basic Single Port pure C++ functionality.
   test3.graphml - Python with multiple port functionality.
   testC3.graphml - C++ with multiple port functionality.
   

   
   To view these graphml files, yEd can be used.