blpd

Lagrangian (stochastic) particle dispersion with Python+Numba to model bees finding floral scents

pdoc API documentation: https://zmoon.github.io/blpd/blpd.html

Installing

Latest:

pip install https://github.com/zmoon/blpd/archive/master.zip

For development

1. Clone the repo

   git clone https://github.com/zmoon/blpd
   
2. Register the package as an editable install, by navigating into the the repo and executing

   pip install -e .
   

Notes

❗ 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.

References

• 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