.. -- mode: rst --

Python scripts for some 3rd-order chaotic systems (Lorenz attractor, Nose-Hoover oscillator, Rossler attractor, Riktake model, Duffing map etc.)

Chaotic attractors

.. image:: https://raw.githubusercontent.com/capitanov/chaospy/master/img/Lorenz_3d.gif?sanitize=true

Math model::

dx/dt = sigma * (y - x)
dy/dt = rho * x - y - x * z
dz/dt = x * y - beta * z

where sigma = 10, rho = 28 and beta = 8/3.

Main info

+---------------------+-----------------------------------------+
| **Title**           | Analysis and modeling chaotic systems   |
+=====================+=========================================+
| **Author**          | Alexander Kapitanov                     |
+---------------------+-----------------------------------------+
| **Contact**         | <email_hidden>                          |
+---------------------+-----------------------------------------+
| **Project lang**    | Python 3                                |
+---------------------+-----------------------------------------+
| **First Release**   | 30 May 2019                             |
+---------------------+-----------------------------------------+
| **License**         | GNU GPL 3.0.                            |
+---------------------+-----------------------------------------+

Chaotic system

Rossler attractor::

dx/dt = -(y + z)
dy/dt = x + a * y
dz/dt = b + z * (x - c)

where a = 0.2, b = 0.2 and c = 5.7.

.. image:: https://raw.githubusercontent.com/capitanov/chaospy/master/img/Rossler_3D.png?sanitize=true

Spectrum and auto correlation

---

.. image:: https://raw.githubusercontent.com/capitanov/chaospy/master/img/Lorenz_Spectrum.png?sanitize=true

Source code

You can check the latest sources with the command::

    $ git clone <chaospy.git>
    $ cd chaospy
    $ <install miniconda for your operation system>
    $ conda create -y -n venv python==3.9
    $ conda activate venv
    $ pip install -r requirements.txt

Example run::

    $ python run.py --show_plots --show_all lorenz


Dependencies

Project requirements: requirements.txt

Chaotic models

- Lorenz
- Rossler
- Rikitake
- Duffing
- Nose-Hoover
- Lotka-Volterra
- Wang
- Chua

Help
~~~~

::

    usage: parser.py [-h] [-p POINTS] [-s STEP]
                     [--init_point INIT_POINT [INIT_POINT ...]] [--show_plots]
                     [--save_plots] [--add_2d_gif]
                     {lorenz,rossler,rikitake,chua,duffing,wang,nose-hoover,lotka-volterra}
                     ...

        Specify command line arguments for dynamic system.Calculate some math
        parameters and plot some graphs of a given chaotic system.

        optional arguments:
          -h, --help            show this help message and exit
          -p POINTS, --points POINTS
                                Number of points for dymanic system. Default: 1024.
          -s STEP, --step STEP  Step size for calculating the next coordinates of
                                chaotic system. Default: 100.
          --init_point INIT_POINT [INIT_POINT ...]
                                Initial point as string of three floats: "X, Y, Z".
          --show_plots          Show plots of a model. Default: False.
          --save_plots          Save plots to PNG files. Default: False.
          --add_2d_gif          Add 2D coordinates to 3D model into GIF. Default:
                                False.

        Chaotic models:
          You can select one of the chaotic models:

          {lorenz,rossler,rikitake,chua,duffing,wang,nose-hoover,lotka-volterra}
            lorenz              Lorenz chaotic model
            rossler             Rossler chaotic model
            rikitake            Rikitake chaotic model
            chua                Chua chaotic model
            duffing             Duffing chaotic model
            wang                Wang chaotic model
            nose-hoover         Nose-hoover chaotic model
            lotka-volterra      Lotka-volterra chaotic model

Chaotic attractors are used as subparse command. Example:

Lorenz attractor
****************
::

    usage: parser.py lorenz [-h] [--sigma SIGMA] [--beta BETA] [--rho RHO]

    optional arguments:
      -h, --help     show this help message and exit

    Lorenz model arguments:
      --sigma SIGMA  Lorenz system parameter. Default: 10
      --beta BETA    Lorenz system parameter. Default: 2.6666
      --rho RHO      Lorenz system parameter. Default: 28

Chua circuit
************
::

    usage: parser.py chua [-h] [--alpha ALPHA] [--beta BETA] [--mu0 MU0]
                          [--mu1 MU1]

    optional arguments:
      -h, --help     show this help message and exit

    Chua model arguments:
      --alpha ALPHA  Chua system parameter. Default: 0.1
      --beta BETA    Chua system parameter. Default: 28
      --mu0 MU0      Chua system parameter. Default: -1.143
      --mu1 MU1      Chua system parameter. Default: -0.714

See Also
~~~~~~~~

- `Wiki <https://en.wikipedia.org/wiki/Attractor>`__
- `Habr <https://habr.com/users/hukenovs>`__