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caospy-0.0.1


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توضیحات

Dynamic systems analysis
ویژگی مقدار
سیستم عامل -
نام فایل caospy-0.0.1
نام caospy
نسخه کتابخانه 0.0.1
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Juan Colman, Sebastián Bertolo
ایمیل نویسنده juancolmanot@gmail.com
آدرس صفحه اصلی https://github.com/Colman-Bertolo/Caospy
آدرس اینترنتی https://pypi.org/project/caospy/
مجوز The MIT License
# Caospy ![logo](https://raw.githubusercontent.com/Colman-Bertolo/Caospy/main/res/logo.png) [![Documentation Status](https://readthedocs.org/projects/caospy/badge/?version=latest)](https://caospy.readthedocs.io/en/latest/?badge=latest) [![Caospy](https://github.com/Colman-Bertolo/Caospy/actions/workflows/caospy_ci.yml/badge.svg)](https://github.com/Colman-Bertolo/Caospy/actions/workflows/caospy_ci.yml) [![MIT License](https://img.shields.io/npm/l/caos)](https://caospy.readthedocs.io/en/latest/license.html) [![Coverage Status](https://coveralls.io/repos/github/Colman-Bertolo/Caospy/badge.svg?branch=main)](https://coveralls.io/github/Colman-Bertolo/Caospy?branch=main) [![https://github.com/leliel12/diseno_sci_sfw](https://img.shields.io/badge/DiSoftCompCi-FAMAF-ffda00)](https://github.com/leliel12/diseno_sci_sfw) Caospy is a Python package to analyze continuous dynamical systems and chaos. Its utilities are: - Solve systems of ODEs. - Eigenvalues, eigenvectors and roots of equations. - Classification of fixed points in 1D and 2D. - Poincare maps. - Plots. Some well studied systems are available in the library, like Lorenz’s system, the Logistic equation, Duffing’s system and the Rosslers-Chaos systems. ## Motivation Dynamic sisytems are one of the most researched niches of knowledge, their understanding is crucial in order to interact more effectively with our environment. In order to study any dynamical systems to an acceptable level of detail, the classical qualitative analysis fall short and different heuristic methods along with numerical approaches where born to better understand their behavior. Properties like fixed points stability or chaotic behavior, and phenomena like bifurcations are commonly obtained by means of using these so called heuristic methods. Caospy attempts to bring this different tools of analysis together in one Python package, and achieve the unification and regularization of their use in a common developing context, hoping it will provide an easier and more comprehensive analysis of the subject in question. ## Requirements You will need Python 3.9 or later to run Caospy. ## Installation Caospy is available at PyPI. You can install it via the pip command: ```bash $ pip install Caospy ``` If you'd like to bleeding edge of the code or you want to run the latest version, you can clone this repo and then inside the local directory execute: ```bash $ pip install -e . ``` ## Usage Let's study the [damped harmonic oscillator](https://en.wikipedia.org/wiki/Harmonic_oscillator) without driving force. It's a second order one dimensional ODE, but we'll reduce it to a system of first-order odes. ```Python import caospy as cp import matplotlib.pyplot as plt var = ["x", "y"] # Variables par = ["k", "c"] # Parameters fun = ["y", "-c*y-k*x"] # Functions name = "Damped harmonic oscillator" # System's name Ode_2d = cp.TwoDim(var, fun, par, name) t0 = 0 # Initial time tf = 8 # End time x0 = [0, 1] # Initial Conditions par_value = [100, 1] # Parameter values N = 500 # Number of time steps sol = Ode_2d.time_evolution(x0, par_value, t0, tf, N) fig, ax = plt.subplots() ax = sol.plot_trajectory("t-x") # Plot the solution ax.set_xlabel("t [s]") ax.set_ylabel("x [cm]") ``` You'll get the next figure. ![harmonic](https://raw.githubusercontent.com/Colman-Bertolo/Caospy/main/res/harmonic_oscillator.jpg) For more examples, please refer to the tutorial in [Documentation](https://caospy.readthedocs.io/en/latest/?badge=latest). ## Contributing Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are **greatly appreciated**. If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again! 1. Fork the Project 2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`) 3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`) 4. Push to the Branch (`git push origin feature/AmazingFeature`) 5. Open a Pull Request ## License Distributed under the MIT License. See [LICENSE](https://github.com/Colman-Bertolo/Caospy/blob/main/LICENSE) for more information. ## Authors Juan Colman(E-mail: juancolmanot@gmail.com), Sebastián Nicolás Bertolo.


نیازمندی

مقدار نام
- numpy
- pandas
- scipy
- sympy
- matplotlib


نحوه نصب


نصب پکیج whl caospy-0.0.1:

    pip install caospy-0.0.1.whl


نصب پکیج tar.gz caospy-0.0.1:

    pip install caospy-0.0.1.tar.gz