Teresa Vogl, Martin Radenz, Heike Kalesse-Los 2022
PEAKO is a supervised radar Doppler spectrum peak finding algorithm. It finds the optimal parameters for detecting peaks in cloud radar Doppler spectra using user-generated training data.
PEAKO is used to:
- create labeled data (peaks marked by a user in cloud radar Doppler spectra), which can be used for training and testing the learned function
- train the algorithm using the labeled data to obtain the optimal parameter combination for peak detection. Optimization is done using a similarity measure based on the area below the peaks.
- test the performance of the learned function
- detect peaks in cloud radar Doppler spectra using the learned function
Reference for PEAKO: Kalesse et al. (2019), AMT
Documentation is available at: https://pypeako.readthedocs.io/en/latest/
pypeako is available via pip, so that one can simply do :
$ pip install pyPEAKO
The current release is tailored to use cloud radar Doppler spectra netcdf files. The files are in the same format as the netcdf output files returned by the rpgpy reader ([https://github.com/actris-cloudnet/rpgpy]).
If you find a bug or have ideas for improvements, or want to help develop peako, please contact one of the authors. Your input will for sure be appreciated!