zmoon/blpd

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

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

blpd's Issues

xarray accessor

Since all of the plotting functions in .plots now take a ds as the first arg, it would be nice to create lpd accessor with a .plot _PlotMethods for convenience. .chem functions also take the ds.

Examples upgrade

Jupytext nbs; be more organized with the figures and such, add some comments

also can use normal imports now

progress bar

for the LPD run. Would be nice.

Name of project and Python package

I sometimes mistype "blpdm" as "bldpm", so maybe just "blpd" would be better since it is shorter. Or something different. Especially with the coming inclusion of the Eulerian model.

module `lpd` needs cleanup

MW params

The MW input params are kind of opaque. I want to create a convenience function that takes more standard wind variables (sigmas and such) and generates the MW input params. Some of these would include params that are output from calc_MW_derived_params, like U(h), displacement height, roughness length.

Examples to `.ipynb`

• incorporate some interactivity
• add nbstripout to pre-commit config

Basic docs build

Probably won't initially include examples but eventually would. Just want to have docs built for the basic intended public API (Model, plotting routines, main chem stuff, ...).