pyBarSim is a Python package to simulate wave-dominated shallow-marine environments using Storms (2003)'s BarSim.
You can directly install pyBarSim from pip:
pip install pybarsim
Or from GitHub using pip:
pip install git+https://github.com/grongier/pybarsim.git
Basic use:
import numpy as np
from pybarsim import BarSim2D
import matplotlib.pyplot as plt
# Set the parameters
run_time = 10000.
barsim = BarSim2D(np.linspace(1000., 900., 200),
np.array([(0., 950.), (run_time, 998.)]),
np.array([(0., 25.), (run_time, 5.)]),
spacing=100.)
# Run the simulation
barsim.run(run_time=10000., dt_fair_weather=15., dt_storm=1.)
# Interpolate the outputs into a regular grid
barsim.regrid(900., 1000., 0.5)
# Compute the mean grain size
barsim.finalize(on='record')
# Plot the median grid size in the regular grid
barsim.record_['Mean grain size'].plot(figsize=(12, 4))
plt.show()
For a more complete example, see the Jupyter notebook using_pybarsim.ipynb or the Binder link above.
If you use pyBarSim in your research, please cite the original article:
Storms, J.E.A. (2003). Event-based stratigraphic simulation of wave-dominated shallow-marine environments. Marine Geology, 199(1), 83-100. doi:10.1016/S0025-3227(03)00144-0
Here is the corresponding BibTex entry if you use LaTex:
@Article{Storms2003,
author="Storms, Joep E.A.",
title="Event-based stratigraphic simulation of wave-dominated shallow-marine environments",
journal="Marine Geology",
year="2003",
volume="199",
number="1",
pages="83--100",
issn="0025-3227",
doi="https://doi.org/10.1016/S0025-3227(03)00144-0",
}
This software was written by:
Guillaume Rongier  |
Joep Storms |
Andrea Cuesta Cano |
|---|
Copyright notice: Technische Universiteit Delft hereby disclaims all copyright interest in the program pyBarSim written by the Author(s). Prof. Dr. Ir. J.D. Jansen, Dean of the Faculty of Civil Engineering and Geosciences
© 2023, G. Rongier, J.E.A. Storms, A. Cuesta Cano
This work is licensed under a MIT OSS licence.
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