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)
Denoising Diffusion Probabilistic Models

Denoising Diffusion Probabilistic Models Jonathan Ho, Ajay Jain, Pieter Abbeel Paper: https://arxiv.org/abs/2006.11239 Website: https://hojonathanho.g

Jonathan Ho 1.5k Jan 08, 2023
Deep Unsupervised 3D SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment.

(ACMMM 2021 Oral) SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment This repository shows two tasks: Face landmark detection and Fac

BoomStar 51 Dec 13, 2022
You can draw the corresponding bounding box into the image and save it according to the result file (txt format) run by the tracker.

You can draw the corresponding bounding box into the image and save it according to the result file (txt format) run by the tracker.

Huiyiqianli 42 Dec 06, 2022
Code for the Shortformer model, from the paper by Ofir Press, Noah A. Smith and Mike Lewis.

Shortformer This repository contains the code and the final checkpoint of the Shortformer model. This file explains how to run our experiments on the

Ofir Press 138 Apr 15, 2022
Code for paper "Multi-level Disentanglement Graph Neural Network"

Multi-level Disentanglement Graph Neural Network (MD-GNN) This is a PyTorch implementation of the MD-GNN, and the code includes the following modules:

Lirong Wu 6 Dec 29, 2022
The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information".

The HIST framework for stock trend forecasting The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining C

Wentao Xu 110 Dec 27, 2022
LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation

LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation by Junjue Wang, Zhuo Zheng, Ailong Ma, Xiaoyan Lu, and Yanfei Zh

Payphone 8 Nov 21, 2022
(ICCV 2021 Oral) Re-distributing Biased Pseudo Labels for Semi-supervised Semantic Segmentation: A Baseline Investigation.

DARS Code release for the paper "Re-distributing Biased Pseudo Labels for Semi-supervised Semantic Segmentation: A Baseline Investigation", ICCV 2021

CVMI Lab 58 Jan 01, 2023
GRF: Learning a General Radiance Field for 3D Representation and Rendering

GRF: Learning a General Radiance Field for 3D Representation and Rendering [Paper] [Video] GRF: Learning a General Radiance Field for 3D Representatio

Alex Trevithick 243 Dec 29, 2022
3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans.

3DMV 3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans. This work is based on our ECCV'18 p

Владислав Молодцов 0 Feb 06, 2022
Efficient and intelligent interactive segmentation annotation software

Efficient and intelligent interactive segmentation annotation software

294 Dec 30, 2022
A PyTorch implementation of the architecture of Mask RCNN

EDIT (AS OF 4th NOVEMBER 2019): This implementation has multiple errors and as of the date 4th, November 2019 is insufficient to be utilized as a reso

Sai Himal Allu 975 Dec 30, 2022
3D ResNets for Action Recognition (CVPR 2018)

3D ResNets for Action Recognition Update (2020/4/13) We published a paper on arXiv. Hirokatsu Kataoka, Tenga Wakamiya, Kensho Hara, and Yutaka Satoh,

Kensho Hara 3.5k Jan 06, 2023
Pytorch implemenation of Stochastic Multi-Label Image-to-image Translation (SMIT)

SMIT: Stochastic Multi-Label Image-to-image Translation This repository provides a PyTorch implementation of SMIT. SMIT can stochastically translate a

Biomedical Computer Vision Group @ Uniandes 37 Mar 01, 2022
Distributed Asynchronous Hyperparameter Optimization better than HyperOpt.

UltraOpt : Distributed Asynchronous Hyperparameter Optimization better than HyperOpt. UltraOpt is a simple and efficient library to minimize expensive

98 Aug 16, 2022
Bayesian Image Reconstruction using Deep Generative Models

Bayesian Image Reconstruction using Deep Generative Models R. Marinescu, D. Moyer, P. Golland For technical inquiries, please create a Github issue. F

Razvan Valentin Marinescu 51 Nov 23, 2022
[IJCAI'21] Deep Automatic Natural Image Matting

Deep Automatic Natural Image Matting [IJCAI-21] This is the official repository of the paper Deep Automatic Natural Image Matting. Introduction | Netw

Jizhizi_Li 316 Jan 06, 2023
Code for EMNLP'21 paper "Types of Out-of-Distribution Texts and How to Detect Them"

ood-text-emnlp Code for EMNLP'21 paper "Types of Out-of-Distribution Texts and How to Detect Them" Files fine_tune.py is used to finetune the GPT-2 mo

Udit Arora 19 Oct 28, 2022
On the model-based stochastic value gradient for continuous reinforcement learning

On the model-based stochastic value gradient for continuous reinforcement learning This repository is by Brandon Amos, Samuel Stanton, Denis Yarats, a

Facebook Research 46 Dec 15, 2022
PyTorch implementation of Constrained Policy Optimization

PyTorch implementation of Constrained Policy Optimization (CPO) This repository has a simple to understand and use implementation of CPO in PyTorch. A

Sapana Chaudhary 25 Dec 08, 2022