Max-Flow Optimization Project

Overview

The Max-Flow Project is an implementation of the max flow algorithm, utilizing both Python and C++ languages. This project showcases the integration of the two languages, compiled with CMake, and includes a Jupyter notebook example for demonstration purposes.

Table of Contents

• Max-Flow Optimization Project
  • Overview
  • Table of Contents
  • Introduction
  • Features
  • Installation
    • Prerequisites
    • Steps
  • Usage
  • Example
    • Usage

Introduction

The max flow algorithm is used to find the maximum flow in a directed flow network. This project implements the algorithm using C++ for the core computations and Python for the interface and additional functionalities. The Jupyter notebook included in this project provides an interactive example to demonstrate how to use this project.

Features

• Implementation of the max flow algorithm in C++
• Python interface for easier interaction
• Jupyter notebook example to demonstrate usage
• CMake build system for compiling the C++ code

Installation

Prerequisites

• Python 3.x
• C++ compiler (e.g., g++)
• CMake

Steps

1. Clone the repository:

   git clone https://github.com/thenchoz/MaxFlow.git
   cd MaxFlow

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate

3. Install Python dependencies:

   pip install -r python/requirements.txt

4. Compile the C++ code using CMake:

   mkdir build
   cd build
   cmake ..
   make

Usage

1. Ensure the virtual environment is activated:

   source venv/bin/activate

2. Go in the python folder:

   cd python

3. Run graph_analysis:

   python graph_analysis.py --help

Example

The Jupyter notebook MaxFlow_example.ipynb contains an example of how to use the max flow algorithm implemented in this project. It provides a step-by-step guide to demonstrate the setup, execution, and visualization of the algorithm.

Usage

1. Ensure the virtual environment is activated:

   source venv/bin/activate

2. Run the Jupyter notebook:

   jupyter notebook

3. Open the MaxFlow_example.ipynb notebook and run the cells to see the max flow algorithm in action.