sierras is a tool for empirical Arrhenius equation fitting for thermally-induced physicochemical processes.
You need Python 3.8+ to run sierras.
You can install the most recent stable release of sierras with pip
python -m pip install -U pip
python -m pip install -U sierras
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.
You can contact me at ffernandev@gmail.com