sierras 0.2.5

A tool for empirical Arrhenius equation fitting for thermally-induced physicochemical processes.

sierras

sierras is a tool for empirical Arrhenius equation fitting for thermally-induced physicochemical processes.

Requirements

You need Python 3.8+ to run sierras.

Installation

You can install the most recent stable release of sierras with pip

python -m pip install -U pip
python -m pip install -U sierras

Usage

A simple example of use:

from sierras import ArrheniusRegressor

# default constant is Boltzmann in eV/K
areg = ArrheniusRegressor()

# temperatures and target_process arrays-like as usually used in scikit-learn 
areg.fit(Temperatures, target_process)

# print the activation energy ([eV] in the default case) and the extrapolated 
# process at room temperatures values (in the same units as target_process is)
print(areg.activation_energy_, areg.extrapolated_process_)

# plot the fitting
fig, ax = plt.subplots()
areg.plot(ax=ax)

For a more detailed explanation you can read the tutorial and the API.

License

MIT License

Contact info

You can contact me at [e-mail]