pydeb is a Python package for building and analyzing Dynamic Energy Budget models. It supports phylogenetic inference of DEB models for new species, simulation of growth, reproduction and survival, and Bayesian inference with the Adaptive Metropolis algorithm. It is designed for high performance and can analyze 100,000 parameter sets in under 2 minutes on most workstations.
To get an impression of the capabilities of pydeb, check out the Debber webservice. Debber builds and simulates DEB models for any species of interest and uses pydeb underneath for all computations.
To use pydeb, you need a Python distribution with NumPy. To run the examples, you additionally need jupyter and plotly.
If you are starting from scratch, we recommend you use a Python distribution such as Anaconda or Miniconda.
If you have Anaconda or Miniconda, you install pydeb and its dependencies with:
conda install -c conda-forge pydeb plotly jupyterlab
Alternatively, you can install pydeb from source with
python -m pip install <PYDEB_DIR> --user
Notes:
pythonis the name of the your Python interpreter. Replace it if necessary. For instance, some systems have Python 3 installed aspython3. If you want to install pydeb for this distribution, usepython3 -m pip install <PYDEB_DIR> --user.- If you run the above from the pydeb top-level directory (the one that contains this README file),
<PYDEB_DIR>would be. - Installation from source requires a C compiler, which may need to be installed separately on Windows as described here.
- The above installs in your user-specific site packages directory. To install system-wide, omit
--user. But this may require administrator/sudo permissions.
pydeb comes with a number of Jupyter Notebook examples.
To use these, run jupyter notebook from the examples subdirectory.