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:

• Thermocline
• Mixed layer
• Metalimnion extent (epilimnion and hypolimnion depth)
• Wedderburn Number
• Schmidt stability
• Heat content
• Seiche periode
• Lake Number
• Brunt-Vaisala frequency
• Average layer temperature
• Monin-Obhukov

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.