🧠 cvx-optimization-to-ml

C++ Convex Optimization and Polynomial System Solver with Dockerized Symbolic Computation via msolve

This project is a modular C++ pipeline designed for convex optimization and algebraic computation, integrating symbolic solvers like msolve to compute real roots of polynomial systems within Docker. It uses Eigen for linear algebra operations and supports clean reproducible builds via CMake and Make.

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📦 Features

• 🧮 Symbolic solution of multivariate polynomial systems via msolve (Docker-integrated).
• 🌀 Modular structure with Eigen-powered vector/matrix manipulation.
• 🐳 Full Docker environment for reproducible builds and isolated math toolchain (FLINT, GMP, MPFR).
• 🛠️ Developer-friendly Makefile with helper targets for running, testing, and Docker workflows.

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🚀 Quick Start Guide

✅ Requirements

Make sure the following tools are installed on your host machine:

• Docker Desktop
• Git
• Optionally: make and cmake (if you want to build outside Docker)

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📥 Clone the Repository

git clone https://github.com/evya1/cvx-optimization-to-ml.git
cd cvx-optimization-to-ml

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🐳 Build and Run via Docker (Recommended)

1. Build the Docker Image

make docker

This builds a two-stage image:

• Stage 1 compiles FLINT and msolve from source.
• Stage 2 produces a minimal runtime image with your binary and tools installed.

2. Run the Main Program (Binary)

make docker-run

This runs /cvx-optimization-to-ml inside the container.

3. Run msolve on an Example

make msolve-test-real-roots-sec4p1
make show-msolve-output-sec4p1

This will:

• Run msolve on ms_test_inputs/real_roots_sec4p1.ms
• Output the result to ms_outputs/real_roots_sec4p1.out
• Print the content to your terminal

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🛠️ Developer Workflow (Local Build)

1. Build Locally

make build

2. Run the Program

make run

3. Run Tests (optional)

make test

⚠️ Currently a placeholder – you'll need to implement test cases under /tests.

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🧪 Directory Structure

.
├── CMakeLists.txt                # CMake project definition
├── Dockerfile                    # Multi-stage Dockerfile
├── Makefile                      # All build + docker logic
├── include/                      # Header files (rotate.hpp)
├── src/                          # Main source code
│   ├── main.cpp
│   └── rotate.cpp
├── ms\_test\_inputs/              # Sample .ms file for msolve
│   └── real\_roots\_sec4p1.ms
├── ms\_outputs/                  # Output of msolve runs
│   └── real\_roots\_sec4p1.out
├── build/ (or cmake-build-debug/) # Local CMake build artifacts
└── tests/                       # (Placeholder) test files

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📚 Technologies Used

• C++17, Eigen – Linear Algebra
• FLINT, GMP, MPFR – Number theory / multiprecision
• msolve – Real root solver (symbolic polynomial systems)
• CMake – Build configuration
• Docker – Isolated build + runtime
• Makefile – Workflow automation

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🧠 Example Problem Solved

The provided real_roots_sec4p1.ms solves the following polynomial system:

x + 2y + 2z = 1
x^2 + 2y^2 + 2z^2 = x
2xy + 2yz = y

Run make msolve-test-real-roots-sec4p1 to compute its real solutions.

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🤝 Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you'd like to change or add.

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🙌 Acknowledgments

• msolve authors
• Eigen
• FLINT