This work present methods used to compute meaningful physical properties in aquatic sciences.
The methods are based on Xarray. Multi-dimensional large time-series array are compatible if an xarray is passed as input.
Algorithms and documentation are sometimes inspired by LakeAnalyzer in R (https://github.com/GLEON/rLakeAnalyzer)
Implemented methods:
Pylake use Dask which require a python version >=3.8
pip install pylake
Have a look in the notebooks, an example is provided
import pylake
import numpy as np
Temp = np.array([14.3,14,12.1,10,9.7,9.5,6,5])
depth = np.array([1,2,3,4,5,6,7,8])
epilimnion, hypolimnion = pylake.metalimnion(temp, depth)
Warning messages Lake metabolizer is being implemented.