A Python package for Monte Carlo based lidar uncertainty modeling.
mocalum is a python package for Monte Carlo based lidar uncertainty modeling. It has following features:
- Slick and super fast Monte Carlo uncertainty modeling
- Simulation of single or multi lidar configuration
- Configuration of arbitrary trajectories for single and multi lidars
- Configuration of
IVAP(sector-scan) trajectory for single lidar - 3D or 4D / uniform or turbulent flow field generation
- Sampling of correlated or uncorrelated uncertainty terms
- Built-in 2nd order kinematic model for calculation of trajectory timing
- 3D or 4D interpolation/projection of flow on lidar(s) line-of-sight(s)
- xarray datasets enriched with metadata
A presentation summarizing mocalum features is available on Zenodo.
The package documentation is available online.
Ideally, you should have conda or anaconda installed on your computer so you can build an isolated python environment in which you will install mocalum.
Make a new conda environment:
conda create -n mc_test python=3.7
Be sure that you are in the previously made conda environment:
conda activate mc_test
Install mocalum in the new environment and you are ready to go:
pip install git+https://github.com/niva83/mocalum.git
In the folder examples you will find jupyter notebook tutorials on how to use mocalum. The purpose of the tutorials is to familiarize users with mocalum and enable them to quickly build there own workflows with this package. The tutorials cover various usage of mocalum. The tutorials are described in a dedicated README.
- Python - Languange
- xarray - Package
- numpy - Package
- pandas - Package
- netCDF4 - Package
- scipy - Package
- pyconturb - Package
- Nikola Vasiljevic - design, development and testing (DevOps) of
mocalum
- Andrea Vignaroli - initial wrapper around PyConTurb, method for conversion of 3D to 4D turbulence box
- Bjarke Tobias Olsen - hints on how to speed up advance interpolation using xarray
- Anders Tegtmeier Pedersen -
matlabscript to sample correlated uncertainties
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If you want to take an active part in the further development of mocalum make a pull request or post an issue in this repository.