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Helper functions for NSE as LPV with Neural Networks

Project description

Neural Networks for NSE as low-dimensional LPV

Active workflow


# package for sparse cholesky factorizations 
# not needed but speed up with FEM norms and POD
apt install libsuitesparse-dev
pip install scikit-sparse==0.4.5

# fenics -- for the FEM part
apt install fenics  # see

# install this module and helper modules
pip install .

Generate the data

cd ../simulations-training-data
mkdir simu-data
mkdir train-data
# python3
cd -

Check the NN


Python Machine-Learning Resources

  • an overview
    1. Tensorflow -- see below
    2. Pytorch -- see below
    3. NeuroLab
    4. ffnet
    5. Scikit-Neural Network
    6. Lasagne
    7. pyrenn




  • website
  • looks well maintained
  • many routines for data processing
  • a few on neural network


# not needed anymore
# pip install -e .  # Python3 needed here! install the module (and one dependency)

pip install -e installs the module nse_nn_lpv to be used in the tests/... but keeps track of all changes made in nse_nn_lpv.

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