Software Platform for solving and manipulating multiparametric programs in Python

Overview

PPOPT

Python package Documentation Status PyPI

Python Parametric OPtimization Toolbox (PPOPT) is a software platform for solving and manipulating multiparametric programs in Python. This package is still in development but the following features are complete and are in full working order.

Installation

Currently PPOPT requires Python 3.7 or higher and can be installed with the following commands.

pip install -e git+https://github.com/mmihaltz/pysettrie.git#egg=pysettrie
pip install ppopt

Quick Overview

To give a fast primer of what we are doing, we are solving multiparametric programming problems (fast) by writting parallel algorithms efficently. Here is a quick sclaing analysis on a large multiparametric program.

image image

Here is a benchmark against the state of the art multiparametric programming solvers. All tests run on the Terra Supercomputer at Texas A&M University. Matlab 2021b was used for solvers written in matlab and Python 3.8 was used for PPOPT.

image

Completed Features

  • Solver interface for mpLPs and mpQP with the following algorithms
    1. Serial and Parallel Combinatorial Algorithm
    2. Serial and Parallel Geometrical Algorithm
    3. Serial and Parallel Graph based Algorithm
  • Multiparametric solution export to C++, Javacript, Matlab, and Python
  • Plotting utilities
  • Presolver and Conditioning for Multiparametric Programs

Key Applications

  • Explicit Model Predictive Control
  • Multilevel Optimization
  • Integrated Design, Control, and Scheduling
  • Robust Optimization

For more information about Multiparametric programming and it's applications, this paper is a good jumping point.

You might also like...
A module for solving and visualizing Schrödinger equation.
A module for solving and visualizing Schrödinger equation.

qmsolve This is an attempt at making a solid, easy to use solver, capable of solving and visualize the Schrödinger equation for multiple particles, an

Deep learning library for solving differential equations and more

DeepXDE Voting on whether we should have a Slack channel for discussion. DeepXDE is a library for scientific machine learning. Use DeepXDE if you need

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

JAX: Autograd and XLA Quickstart | Transformations | Install guide | Neural net libraries | Change logs | Reference docs | Code search News: JAX tops

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

JAX: Autograd and XLA Quickstart | Transformations | Install guide | Neural net libraries | Change logs | Reference docs | Code search News: JAX tops

Prototypical python implementation of the trust-region algorithm presented in Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints by Larson, Leyffer, Kirches, and Manns.

Prototypical python implementation of the trust-region algorithm presented in Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints by Larson, Leyffer, Kirches, and Manns.

Some simple programs built in Python: webcam with cv2 that detects eyes and face, with grayscale filter
Some simple programs built in Python: webcam with cv2 that detects eyes and face, with grayscale filter

Programas en Python Algunos programas simples creados en Python: 📹 Webcam con c

Code for Graph-to-Tree Learning for Solving Math Word Problems (ACL 2020)

Graph-to-Tree Learning for Solving Math Word Problems PyTorch implementation of Graph based Math Word Problem solver described in our ACL 2020 paper G

 Exploration-Exploitation Dilemma Solving Methods
Exploration-Exploitation Dilemma Solving Methods

Exploration-Exploitation Dilemma Solving Methods Medium article for this repo - HERE In ths repo I implemented two techniques for tackling mentioned t

Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary Differential Equations
Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary Differential Equations

ODE GAN (Prototype) in PyTorch Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary

Comments
  • Bitset debug

    Bitset debug

    I've been trying to use autogenerated c++ code to do control allocation on an aircraft. I've discovered that the original code finds incorrect critical regions. Root cause is that bitsets order bits from right to left, but code referenced bitsets from left to right.

    opened by AeroTH310 1
  • Control allocation example

    Control allocation example

    I've out together a basic octocopter example in a .rst file in a style similar to the existing tutorial. I've attempted to get it to display properly on a Read the Docs page, but have not yet been successful. Anyway, I felt it shouldn't delay the PR.

    opened by AeroTH310 0
  • Adds the mixed integer problem type and export code

    Adds the mixed integer problem type and export code

    1. Added enumeration algorithm for the mixed-integer case of mpMILP and mpMIQP
    2. Fixed plotting export file name not to include a timestamp
    3. Removed output on constraint processing
    opened by DKenefake 0
  • No module named 'settrie' when calling the method of solve_mpqp

    No module named 'settrie' when calling the method of solve_mpqp

    In the source code of ppopt.mp_solvers.solve_mpqp, there is From settrie import SetTrie at the top, but there is no such a package in the network, surly 'pip install' fails to work.

    I know the author want to create a trie, but there is a package missing. Pls fix this bug, thanks a lot!

    opened by TimberJ99 1
Releases(Release)
  • Release(Sep 25, 2021)

    This is the initial public release. Please feel free to use this to solve your parametric programming problems.

    If you run into any errors or bugs, please feel free to let us know!

    Source code(tar.gz)
    Source code(zip)
[RSS 2021] An End-to-End Differentiable Framework for Contact-Aware Robot Design

DiffHand This repository contains the implementation for the paper An End-to-End Differentiable Framework for Contact-Aware Robot Design (RSS 2021). I

Jie Xu 60 Jan 04, 2023
An open-source Kazakh named entity recognition dataset (KazNERD), annotation guidelines, and baseline NER models.

Kazakh Named Entity Recognition This repository contains an open-source Kazakh named entity recognition dataset (KazNERD), named entity annotation gui

ISSAI 9 Dec 23, 2022
Multi-View Radar Semantic Segmentation

Multi-View Radar Semantic Segmentation Paper Multi-View Radar Semantic Segmentation, ICCV 2021. Arthur Ouaknine, Alasdair Newson, Patrick Pérez, Flore

valeo.ai 37 Oct 25, 2022
A Jupyter notebook to play with NVIDIA's StyleGAN3 and OpenAI's CLIP for a text-based guided image generation.

A Jupyter notebook to play with NVIDIA's StyleGAN3 and OpenAI's CLIP for a text-based guided image generation.

Eugenio Herrera 175 Dec 29, 2022
Reference implementation for Structured Prediction with Deep Value Networks

Deep Value Network (DVN) This code is a python reference implementation of DVNs introduced in Deep Value Networks Learn to Evaluate and Iteratively Re

Michael Gygli 55 Feb 02, 2022
Versatile Generative Language Model

Versatile Generative Language Model This is the implementation of the paper: Exploring Versatile Generative Language Model Via Parameter-Efficient Tra

Zhaojiang Lin 17 Dec 02, 2022
Two-stage CenterNet

Probabilistic two-stage detection Two-stage object detectors that use class-agnostic one-stage detectors as the proposal network. Probabilistic two-st

Xingyi Zhou 1.1k Jan 03, 2023
Quickly and easily create / train a custom DeepDream model

Dream-Creator This project aims to simplify the process of creating a custom DeepDream model by using pretrained GoogleNet models and custom image dat

55 Dec 27, 2022
SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs

SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs SMORE is a a versatile framework that scales multi-hop query emb

Google Research 135 Dec 27, 2022
Python based framework for Automatic AI for Regression and Classification over numerical data.

Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.

BlobCity, Inc 141 Dec 21, 2022
A High-Performance Distributed Library for Large-Scale Bundle Adjustment

MegBA: A High-Performance and Distributed Library for Large-Scale Bundle Adjustment This repo contains an official implementation of MegBA. MegBA is a

旷视研究院 3D 组 336 Dec 27, 2022
NuPIC Studio is an all­-in-­one tool that allows users create a HTM neural network from scratch

NuPIC Studio is an all­-in-­one tool that allows users create a HTM neural network from scratch, train it, collect statistics, and share it among the members of the community. It is not just a visual

HTM Community 93 Sep 30, 2022
BLEND: A Fast, Memory-Efficient, and Accurate Mechanism to Find Fuzzy Seed Matches

BLEND is a mechanism that can efficiently find fuzzy seed matches between sequences to significantly improve the performance and accuracy while reducing the memory space usage of two important applic

SAFARI Research Group at ETH Zurich and Carnegie Mellon University 19 Dec 26, 2022
PyTorch implementation of MuseMorphose, a Transformer-based model for music style transfer.

MuseMorphose This repository contains the official implementation of the following paper: Shih-Lun Wu, Yi-Hsuan Yang MuseMorphose: Full-Song and Fine-

Yating Music, Taiwan AI Labs 142 Jan 08, 2023
Fuzzing the Kernel Using Unicornafl and AFL++

Unicorefuzz Fuzzing the Kernel using UnicornAFL and AFL++. For details, skim through the WOOT paper or watch this talk at CCCamp19. Is it any good? ye

Security in Telecommunications 283 Dec 26, 2022
implementation of the paper "MarginGAN: Adversarial Training in Semi-Supervised Learning"

MarginGAN This repository is the implementation of the paper "MarginGAN: Adversarial Training in Semi-Supervised Learning". 1."preliminary" is the imp

Van 7 Dec 23, 2022
Spectral Temporal Graph Neural Network (StemGNN in short) for Multivariate Time-series Forecasting

Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting This repository is the official implementation of Spectral Temporal Gr

Microsoft 306 Dec 29, 2022
The pure and clear PyTorch Distributed Training Framework.

The pure and clear PyTorch Distributed Training Framework. Introduction Requirements and Usage Dependency Dataset Basic Usage Slurm Cluster Usage Base

WILL LEE 208 Dec 20, 2022
DeepSTD: Mining Spatio-temporal Disturbances of Multiple Context Factors for Citywide Traffic Flow Prediction

DeepSTD: Mining Spatio-temporal Disturbances of Multiple Context Factors for Citywide Traffic Flow Prediction This is the implementation of DeepSTD in

5 Sep 26, 2022
A pytorch implementation of Pytorch-Sketch-RNN

Pytorch-Sketch-RNN A pytorch implementation of https://arxiv.org/abs/1704.03477 In order to draw other things than cats, you will find more drawing da

Alexis David Jacq 172 Dec 12, 2022