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CC BY NC SA 4.0

This work is licensed under a Creative Commons Attribution 4.0 International License.

CADET Tutorials

This is a repository for introductory examples and tutorials of the CADET-Process software for modelling and simulating chromatographic processes.

For more information, see also:

Download the tutorials

To run the tutorials locally, we recommend installing Anaconda. Anaconda is a high-performance scientific distribution of Python that includes many common packages needed for scientific and engineering work. Download the installer from their website and run it for the local (!) user. Optionally, use mamba which uses a faster dependency solver than conda. To use mamba, replace conda commands with mamba.

The easiest way to download the tutorials is to clone this repository. For this purpuse, make sure, git is installed.

From a git bash navigate to to where you want to store the tutorials and run

git clone https://github.com/modsim/CADET-Process_Tutorial

Then, from an Anaconda Prompt, cd into the directory and install all the requirements by running

mamba env create -f ./environment.yml

This will create a new conda environment called cadet. Activate it using the following command

conda activate cadet

Getting started

Fire up a jupyter-lab and get started with the Tutorials.

In case you are new to Python and jupyter, we also included a small tutorial (00_Introduction_Python) which covers the necessary basics for the tutorials.

Fixing potential problems.

  • If you get the following error The code execution cannot proceed because VCRUNTIME140_1.dll was not found. Reinstalling the program may fix this problem., please visit https://support.microsoft.com/en-us/help/2977003/the-latest-supported-visual-c-downloads and install the latest Microsoft Visual C++ Redistributable.
  • Some of the notebooks include interactive graphs. To enable them, please open an Anaconda prompt and run:
    • For JupyterLab 2.0+
      jupyter labextension install @jupyter-widgets/jupyterlab-manager
      jupyter lab clean
      jupyter lab build
      
    • For JupyterLab 3.0+: install ipympl

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  • Jupyter Notebook 94.4%
  • Python 5.6%