Lagrangian (stochastic) particle dispersion with Python+Numba to model bees finding floral scents
pdoc API documentation: https://zmoon.github.io/blpd/blpd.html
Latest:
pip install https://github.com/zmoon/blpd/archive/master.zip
- Clone the repo
git clone https://github.com/zmoon/blpd
- Register the package as an editable install, by navigating into the the repo and executing
pip install -e .
❗ An updated version of pip
(>= 19.0) should be used for the install to ensure that the build backend specified in pyproject.toml
will be read and used (installed if necessary). Otherwise, the blpd
package version may not be correctly read into the package metadata.
- K. Pratt's thesis: https://etda.libraries.psu.edu/catalog/14063. The version described there included a simpler treatment of the in-canopy statistics. Marcelo Chamecki added the Massman & Weil (1999) model to enhance the canopy treatment. The LPD code (module
blpd.lpd
) is based on a version of Pratt's model written in Matlab. - Massman & Weil (1999): https://doi.org/10.1023/A:1001810204560
- Fuentes et al. (2016): https://doi.org/10.1016/j.atmosenv.2016.07.002