https://github.com/kul-optec/panoc-gauss-newton-ifac-experiments

https://github.com/kul-optec/panoc-gauss-newton-ifac-experiments

Science Score: 13.0%

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Last synced: 4 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: kul-optec
  • Language: Python
  • Default Branch: main
  • Size: 40.5 MB
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  • Stars: 4
  • Watchers: 4
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Created over 3 years ago · Last pushed over 3 years ago
Metadata Files
Readme

README.md

Gauss–Newton meets PANOC: A fast and globally convergent algorithm for nonlinear optimal control

To reproduce (Linux, requires Python 3, CMake, Ninja, a modern C/C++ toolchain):

```sh

Create a Python virtual environment

python3 -m venv py-venv . py-venv/bin/activate

Set compiler flags for optimal performance

export CFLAGS=-march=native export CXXFLAGS=-march=native

Install alpaqa dependencies into virtual environment

wget https://raw.githubusercontent.com/kul-optec/alpaqa/50ea3edaa6f3c79cb10f3f7816ef475606cd11c8/scripts/install-casadi-static.sh -O- | bash wget https://raw.githubusercontent.com/kul-optec/alpaqa/50ea3edaa6f3c79cb10f3f7816ef475606cd11c8/scripts/install-eigen.sh -O- | bash

Install Python dependencies, build alpaqa from source

pip install -r requirements.txt # takes a couple of minutes

Run the experiments and generate the figures

make # takes some more minutes, close the figures to start next experiment ```

If you wish to use a pre-built version of alpaqa rather than building from source, Wheel packages are available in the dist folder.

Owner

  • Name: OPTEC
  • Login: kul-optec
  • Kind: organization

KU Leuven Center of Excellence: Optimization in Engineering

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