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memPyGUTS is a python package for fitting GUTS models to survival data, from ecotoxicology experiments, developed at the Osnabrück University, Germany

Project description

memPyGUTS

memPyGUTS is a python package for fitting GUTS models to survival data, from ecotoxicology experiments, developed at the Osnabrück University, Germany

Description

The small package is currently capable of calibrating various General Unified Threshold model of Survival (GUTS,[1]) models to exposure-survival datasets using a frequentist Nelder-Mead approach. Uncertainties can be additionally assessed using a Bayesian Monte-Carlo-Marrcov-Chain method (MCMC). It is based on the epytox package by Raymond Nepstad (github.com/nepstad/epytox). Additional models for GUTS mixture toxicity [2] and BufferGUTS models [3] for above-ground invertebrates are also implemented.

Installation

Prerequisites

Clone the repository and change into the directory:

git clone https://gitlab.uni-osnabrueck.de/memuos/mempyguts.git
cd mempyguts

Create a conda environment with Python 3.11 and activate:

conda create -n mempyguts -c conda-forge python=3.11 pandoc
conda activate mempyguts

Install the package into the activated environment with the package installer for python (pip) as an editable installation

pip install -e .[pymob]

Usage

For usage of mempyguts, see the Jupyter notebook: notebooks/demo.ipynb

References

[1] Jager, T., Albert, C., Preuss, T. G., & Ashauer, R. (2011). General unified threshold model of survival - A toxicokinetic-toxicodynamic framework for ecotoxicology. Environmental Science and Technology, 45(7), 2529–2540.

[2] Bart, S., Jager, T., Robinson, A., Lahive, E., Spurgeon, D. J., & Ashauer, R. (2021). Predicting Mixture Effects over Time with Toxicokinetic–Toxicodynamic Models (GUTS): Assumptions, Experimental Testing, and Predictive Power. Environmental Science & Technology, 55(4), 2430–2439. https://doi.org/10.1021/acs.est.0c05282

[3] Bürger, L. U., & Focks, A. (2025). From water to land—Usage of Generalized Unified Threshold models of Survival (GUTS) in an above-ground terrestrial context exemplified by honeybee survival data. Environmental Toxicology and Chemistry, 44(2), 589–598. https://doi.org/10.1093/etojnl/vgae058

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