This collection belongs to the doctoral thesis _"Nonlinear Parameter Estimation of Experimental Cake Filtration Data"_.  Most of the content are Jupyter notebooks which contain the Python code which reproduces graphs found in the thesis from the original experimental data.

The lab practice dataset that contains 500 filtration experiments is contained in the folder for section 3.5.

The notebooks are not strictly sorted by section. At any rate, the Readme will guide you to the notebook which produces a certain graph, if it is not part of the main notebook of that specific section.

The original Python environment was set up with Anaconda. Please use the provided `.yml` file to create a Python environment which contains all the necessary packages. Some notebooks may not work with the most current versions of the packages, so updating is not necessarily a good idea.

This collection is published under a Creative Commons license **Attribution 4.0 International (CC BY 4.0)**. Please feel free to use the methods and data provided to further filtration research or anything you want with it as long as you mention the source or the corresponding written work.

Have fun!

Thomas