pylake
Project description
PyLake
This work present methods used to compute meaningful physical properties in aquatic sciences.
Multi-dimensional array (time and depth) are compatible.
Algorithms and documentation are inspired by LakeAnalyzer in R (https://github.com/GLEON/rLakeAnalyzer)
Implemented methods:
- Thermocline
- Mixed layer
- Metalimnion extent (top metalimnion and bottom metalimnion)
- Wedderburn Number
- Schmidt stability
- internal energy
- Seiche periode
- Lake Number
- Brunt-Vaisala frequency
- Average layer temperature
Future updates:
- Data check and comparison with other sources
- Xarray based algorithms for spatial data compatibility
- Thermocline uses a smoothing algorithm (savgol filter) to correct the variability in vertical resolution. This method is temporary and need to be replaced.
- Mixed layer interpolation need to be optimized, set as parameter for now
Installation
pip install pylake
Usage
import pylake
import numpy as np
temp = np.array([14.3,14,12.1,10,9.7,9.5])
depth = np.array([1,2,3,4,5,6])
meta_depth = pylake.meta_depths(temp, depth, thermocline_output=True)
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