├── src
├── __init__.py
├── utils
│ ├── __init__.py
│ ├── calculator.py
│ ├── parser.py
│ └── drawer.py
├── attractors
│ ├── __init__.py
│ ├── wang.py
│ ├── nose_hoover.py
│ ├── rikitake.py
│ ├── lotka_volterra.py
│ ├── lorenz.py
│ ├── chua.py
│ ├── rossler.py
│ ├── attractor.py
│ └── duffing.py
└── dynamic_system.py
├── img
├── Wang_3D.png
├── Chua1_3D.png
├── Chua2_3D.png
├── Duffing_3D.png
├── Lorenz_3D.png
├── Lorenz_3d.gif
├── Lotka_3D.png
├── Rossler_3D.png
├── Rikitake_3D.png
├── Lorenz_Spectrum.png
└── Nose_Hoover_3D.png
├── requirements.txt
├── Dockerfile
├── run.py
├── tests
├── test_drawer.py
├── test_attractor.py
├── test_chua.py
└── conftest.py
├── pyproject.toml
├── .pre-commit-config.yaml
├── .gitignore
├── README.rst
└── LICENSE
/src/__init__.py:
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1 |
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/src/utils/__init__.py:
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1 |
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/src/attractors/__init__.py:
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1 |
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/img/Wang_3D.png:
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https://raw.githubusercontent.com/hukenovs/chaospy/HEAD/img/Wang_3D.png
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/img/Chua1_3D.png:
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https://raw.githubusercontent.com/hukenovs/chaospy/HEAD/img/Chua1_3D.png
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/img/Chua2_3D.png:
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https://raw.githubusercontent.com/hukenovs/chaospy/HEAD/img/Chua2_3D.png
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/img/Duffing_3D.png:
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https://raw.githubusercontent.com/hukenovs/chaospy/HEAD/img/Duffing_3D.png
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/img/Lorenz_3D.png:
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https://raw.githubusercontent.com/hukenovs/chaospy/HEAD/img/Lorenz_3D.png
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/img/Lorenz_3d.gif:
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https://raw.githubusercontent.com/hukenovs/chaospy/HEAD/img/Lorenz_3d.gif
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/img/Lotka_3D.png:
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https://raw.githubusercontent.com/hukenovs/chaospy/HEAD/img/Lotka_3D.png
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/img/Rossler_3D.png:
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https://raw.githubusercontent.com/hukenovs/chaospy/HEAD/img/Rossler_3D.png
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/img/Rikitake_3D.png:
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https://raw.githubusercontent.com/hukenovs/chaospy/HEAD/img/Rikitake_3D.png
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/img/Lorenz_Spectrum.png:
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https://raw.githubusercontent.com/hukenovs/chaospy/HEAD/img/Lorenz_Spectrum.png
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/img/Nose_Hoover_3D.png:
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https://raw.githubusercontent.com/hukenovs/chaospy/HEAD/img/Nose_Hoover_3D.png
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/requirements.txt:
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1 | matplotlib==3.5.1
2 | numpy==1.22.0
3 | pandas==1.3.4
4 | pre-commit==2.16.0
5 | pytest==6.2.5
6 | scipy==1.10.0
7 |
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/Dockerfile:
--------------------------------------------------------------------------------
1 | FROM python:3
2 | WORKDIR /app
3 | COPY . /app
4 |
5 | RUN pip install --upgrade pip && \
6 | pip install --no-cache-dir -r requirements.txt
7 |
8 | CMD python -m src.dynamic_system
9 |
--------------------------------------------------------------------------------
/run.py:
--------------------------------------------------------------------------------
1 | r"""Main function to run chaotic model
2 |
3 | """
4 |
5 | from src.dynamic_system import DynamicSystem
6 |
7 |
8 | if __name__ == '__main__':
9 | chaotic_system = DynamicSystem(input_args=None, show_log=True)
10 | chaotic_system.run()
11 |
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/tests/test_drawer.py:
--------------------------------------------------------------------------------
1 | """Testing for Drawer
2 | """
3 |
4 | import matplotlib.pyplot as plt
5 | import numpy as np
6 | import pytest
7 | from src.utils.drawer import PlotDrawer
8 |
9 |
10 | @pytest.fixture(name="drawer")
11 | def drawer():
12 | """Return PlotDrawer object with default parameters."""
13 | return PlotDrawer(save_plots=False, show_plots=False)
14 |
15 |
16 | @pytest.mark.parametrize(
17 | "coordinates",
18 | [
19 | np.random.randn(10, 3),
20 | np.zeros(15).reshape(5, 3),
21 | np.ones((3, 7)).T,
22 | np.array([[0, 1, 2], [3, 4, 5], [0, 0, 0], [7, 7, 7]]),
23 | np.array([ii for ii in range(30)]).reshape(-1, 3),
24 | np.array([[0, 1, 2]] * 10),
25 | ],
26 | )
27 | def test_shapes_of_coordinates(drawer, coordinates):
28 | """Test input coordinates from iterable sources. Shape[1] shoud be 3"""
29 | drawer.show_time_plots(coordinates)
30 | plt.close() # disable matplotlib warnings
31 | drawer.show_3d_plots(coordinates)
32 | plt.close() # disable matplotlib warnings
33 | assert coordinates.shape[1] == 3, f"[FAIL]: Expected shape of vector coordinates is 3!"
34 |
--------------------------------------------------------------------------------
/pyproject.toml:
--------------------------------------------------------------------------------
1 | # Example configuration for Black.
2 |
3 | # NOTE: you have to use single-quoted strings in TOML for regular expressions.
4 | # It's the equivalent of r-strings in Python. Multiline strings are treated as
5 | # verbose regular expressions by Black. Use [ ] to denote a significant space
6 | # character.
7 |
8 | # TODO 2020/06/02: Check Flake8
9 | [tool.flake8]
10 | ignore = ['E203', 'E266', 'E501', 'W503', 'F403', 'F401']
11 | max-line-length = 120
12 | max-complexity = 12
13 | select = ['B','C','E','F','W','T4','B9']
14 |
15 | [tool.isort]
16 | known_third_party = ["matplotlib", "mpl_toolkits", "numpy", "pandas", "pytest", "scipy", "src"]
17 | multi_line_output = 3
18 | include_trailing_comma = true
19 | force_grid_wrap = 0
20 | use_parentheses = true
21 | line_length = 120
22 |
23 | [tool.black]
24 | line-length = 120
25 | target-version = ['py39']
26 | exclude = '''
27 | /(
28 | \.eggs
29 | | \.git
30 | | \.hg
31 | | \.mypy_cache
32 | | \.tox
33 | | \.venv
34 | | _build
35 | | buck-out
36 | | build
37 | | dist
38 | # The following are specific to Black, you probably don't want those.
39 | | blib2to3
40 | | tests/data
41 | | profiling
42 | )/
43 | '''
44 |
--------------------------------------------------------------------------------
/tests/test_attractor.py:
--------------------------------------------------------------------------------
1 | """Testing for Chua system.
2 | """
3 |
4 | import pytest
5 | from src.attractors.attractor import BaseAttractor
6 |
7 |
8 | @pytest.fixture
9 | def chaotic_system():
10 | return BaseAttractor
11 |
12 |
13 | @pytest.mark.parametrize("num_points, length", [(-10, 0), (0, 0), (10, 10)])
14 | def test_initialized_coordinates(num_points, length):
15 | model = BaseAttractor(num_points=num_points)
16 | assert len(model) == length, f"[FAIL]: Expected len is {length} for positive integers only!"
17 |
18 |
19 | def test_check_reset_coordinates():
20 | model = BaseAttractor(num_points=100)
21 | assert model._coordinates is None, f"[FAIL]: Coordinates should be None!"
22 | assert len(model) == 100, f"[FAIL]: Expected len is {model.num_points} for positive integers only!"
23 | del model.coordinates
24 | assert model._coordinates is None, f"[FAIL]: Coordinates should be None!"
25 |
26 |
27 | @pytest.mark.parametrize(
28 | "num_points, initial_points, result", [(1, (0, 0, 0), None), (1, (0, 0, 0), None),],
29 | )
30 | def test_math_moments(num_points, initial_points, result, assert_moments):
31 | assert_moments(num_points, initial_points, result)
32 |
--------------------------------------------------------------------------------
/.pre-commit-config.yaml:
--------------------------------------------------------------------------------
1 | exclude: '^$'
2 | fail_fast: false
3 | default_language_version:
4 | python: python3.9
5 | repos:
6 | - repo: https://github.com/pre-commit/pre-commit-hooks
7 | rev: v2.5.0
8 | hooks:
9 | - id: check-docstring-first
10 | - id: check-merge-conflict
11 | - id: check-yaml
12 | - id: trailing-whitespace
13 | - id: end-of-file-fixer
14 | - id: requirements-txt-fixer
15 |
16 | - repo: https://github.com/humitos/mirrors-autoflake.git
17 | rev: v1.3
18 | hooks:
19 | - id: autoflake
20 | args: ['-r', '--in-place',
21 | '--remove-all-unused-imports',
22 | '--ignore-init-module-imports',
23 | '--remove-unused-variables',
24 | '--remove-duplicate-keys'
25 | ]
26 |
27 | - repo: https://github.com/asottile/seed-isort-config
28 | rev: v2.1.0
29 | hooks:
30 | - id: seed-isort-config
31 | args: ['--application-directories=src']
32 |
33 | - repo: https://github.com/pre-commit/mirrors-isort
34 | rev: v4.3.21
35 | hooks:
36 | - id: isort
37 | args: ['-y']
38 |
39 | - repo: https://github.com/ambv/black
40 | rev: stable
41 | hooks:
42 | - id: black
43 |
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/.gitignore:
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1 | # User added
2 | .idea/
3 | .pytest_cache/
4 |
5 | # Byte-compiled / optimized / DLL files
6 | __pycache__/
7 | *.py[cod]
8 | *$py.class
9 |
10 | # C extensions
11 | *.so
12 |
13 | # Distribution / packaging
14 | .Python
15 | build/
16 | develop-eggs/
17 | dist/
18 | downloads/
19 | eggs/
20 | .eggs/
21 | lib/
22 | lib64/
23 | parts/
24 | sdist/
25 | var/
26 | wheels/
27 | *.egg-info/
28 | .installed.cfg
29 | *.egg
30 | MANIFEST
31 |
32 | # PyInstaller
33 | # Usually these files are written by a python script from a template
34 | # before PyInstaller builds the exe, so as to inject date/other infos into it.
35 | *.manifest
36 | *.spec
37 |
38 | # Installer logs
39 | pip-log.txt
40 | pip-delete-this-directory.txt
41 |
42 | # Unit test / coverage reports
43 | htmlcov/
44 | .tox/
45 | .coverage
46 | .coverage.*
47 | .cache
48 | nosetests.xml
49 | coverage.xml
50 | *.cover
51 | .hypothesis/
52 | .pytest_cache/
53 |
54 | # Translations
55 | *.mo
56 | *.pot
57 |
58 | # Django stuff:
59 | *.log
60 | local_settings.py
61 | db.sqlite3
62 |
63 | # Flask stuff:
64 | instance/
65 | .webassets-cache
66 |
67 | # Scrapy stuff:
68 | .scrapy
69 |
70 | # Sphinx documentation
71 | docs/_build/
72 |
73 | # PyBuilder
74 | target/
75 |
76 | # Jupyter Notebook
77 | .ipynb_checkpoints
78 |
79 | # pyenv
80 | .python-version
81 |
82 | # celery beat schedule file
83 | celerybeat-schedule
84 |
85 | # SageMath parsed files
86 | *.sage.py
87 |
88 | # Environments
89 | .env
90 | .venv
91 | env/
92 | venv/
93 | ENV/
94 | env.bak/
95 | venv.bak/
96 |
97 | # Spyder project settings
98 | .spyderproject
99 | .spyproject
100 |
101 | # Rope project settings
102 | .ropeproject
103 |
104 | # mkdocs documentation
105 | /site
106 |
107 | # mypy
108 | .mypy_cache/
109 |
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/tests/test_chua.py:
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1 | """Testing for Chua system."""
2 |
3 | import pytest
4 | from src.attractors.chua import Chua
5 |
6 |
7 | @pytest.fixture
8 | def chaotic_system():
9 | return Chua
10 |
11 |
12 | @pytest.fixture(scope="module")
13 | def model():
14 | chua = Chua(num_points=100)
15 | return chua.attractor
16 |
17 |
18 | @pytest.mark.parametrize(
19 | "inputs, outputs",
20 | [
21 | ((0, 0, 0), (0, 0, 0)),
22 | ((0, 0, 1), (0, 1, 0)),
23 | ((0, 1, 0), (15.6, -1, -28)),
24 | ((1, 0, 0), (2.2308, 1, 0)),
25 | ((1e-3, 1e-4, 1e-5), (3.7908e-03, 9.1e-04, -2.8e-03)),
26 | ((1.0, 2.0, 3.0), (33.4308, 2.0, -56.0)),
27 | ((-1000, 2000, -3000), (35654.9076, -6000, -56000)),
28 | ((1000000, 2000000, 3000000), (26738406.6924, 2000000, -56000000)),
29 | ],
30 | )
31 | def test_chua_with_default_kwargs(model, inputs, outputs, assert_threshold):
32 | xi, yi, zi = inputs
33 | xo, yo, zo = model(xi, yi, zi)
34 |
35 | assert_threshold((xo, yo, zo), outputs)
36 |
37 |
38 | @pytest.mark.parametrize(
39 | "inputs, outputs, kwargs",
40 | [
41 | ((1, 2, 3), (25.3, 2, -86), {"alpha": 11, "beta": 43, "mu0": -1.3, "mu1": -0.9}),
42 | ((1, 2, 3), (12.0, 2, -34), {"alpha": 4, "beta": 17, "mu0": -2, "mu1": -3}),
43 | ((1, 2, 3), (0.0, 2.00001, 0), {"alpha": 0, "beta": 0, "mu0": 0, "mu1": 0}),
44 | ((-0.01, 0.2, 100), (2.167, 99.79, -8.6), {"alpha": 11, "beta": 43, "mu0": -1.3, "mu1": -0.9}),
45 | ],
46 | )
47 | def test_chua_with_kwargs(model, inputs, outputs, kwargs, assert_threshold):
48 | xi, yi, zi = inputs
49 | xo, yo, zo = model(xi, yi, zi, **kwargs)
50 |
51 | assert_threshold((xo, yo, zo), outputs)
52 |
53 |
54 | def test_output_length(model):
55 | outputs = model(0, 0, 0)
56 | assert len(outputs) == 3, "Should return 3 values as a tuple"
57 |
--------------------------------------------------------------------------------
/tests/conftest.py:
--------------------------------------------------------------------------------
1 | import pytest
2 |
3 |
4 | @pytest.fixture
5 | def error_threshold():
6 | return 10e-8
7 |
8 |
9 | @pytest.fixture
10 | def assert_threshold(error_threshold, calc_absolute_error):
11 | def wrapper(inputs, outputs):
12 | err_sum = calc_absolute_error(inputs, outputs)
13 | assert err_sum < error_threshold, f"Outputs: {outputs}, Error: {err_sum :.5f}"
14 |
15 | return wrapper
16 |
17 |
18 | @pytest.fixture
19 | def calc_absolute_error():
20 | def wrapper(test: tuple = None, pred: tuple = None) -> float:
21 | """Calculate absolute error for test checking.
22 |
23 | Parameters
24 | ----------
25 | test : tuple
26 | coordinates array of theoretical values.
27 | pred : tuple
28 | coordinates array of calculated values.
29 |
30 | Returns
31 | -------
32 | err: float
33 | Absolute error: sum[(Xi - Yi) / Xi] / 3.
34 |
35 | """
36 | err_sum = 0
37 | for e1, e2 in zip(test, pred):
38 | div = e2 if e1 == 0 else e1
39 | try:
40 | err_sum += (e1 - e2) ** 2 / div ** 2
41 | except ZeroDivisionError:
42 | pass
43 | return err_sum / 3
44 |
45 | return wrapper
46 |
47 |
48 | # TODO: 2020/07/23: Fix this
49 | # @pytest.mark.parametrize(
50 | # "num_points, initial_points, result",
51 | # [
52 | # (1, (0, 0, 0), None),
53 | # (1, (0, 0, 0), None),
54 | # ],
55 | # )
56 | # def assert_moments(num_points, initial_points, result):
57 | # def wrapper(chaotic_system):
58 | # chaos = chaotic_system(num_points, initial_points)
59 | # moments = chaos.check_moments()
60 | # assert result == moments, f"Outputs: {moments :5f}, Golden data: {result :.5f}"
61 | # return wrapper
62 |
63 |
64 | @pytest.fixture
65 | def assert_moments(chaotic_system):
66 | def wrapper(num_points, initial_points, result):
67 | chaos = chaotic_system(num_points, initial_points)
68 | moments = chaos.check_moments()
69 | assert result == moments, f"Outputs: {moments}, Golden data: {result}"
70 |
71 | return wrapper
72 |
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/src/attractors/wang.py:
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1 | r"""Wang 3D attractor system. It also has 4D realization.
2 |
3 | Description :
4 | Wang system (improved Lorenz model) as classic chaotic attractor
5 |
6 | Wang equations are:
7 | dx/dt = x - y*z
8 | dy/dt = x - y + x*z
9 | dz/dt = -3*z + x*y
10 |
11 | ------------------------------------------------------------------------
12 |
13 | GNU GENERAL PUBLIC LICENSE
14 | Version 3, 29 June 2007
15 |
16 | Copyright (c) 2019 Kapitanov Alexander
17 |
18 | This program is free software: you can redistribute it and/or modify
19 | it under the terms of the GNU General Public License as published by
20 | the Free Software Foundation, either version 3 of the License, or
21 | (at your option) any later version.
22 |
23 | You should have received a copy of the GNU General Public License
24 | along with this program. If not, see .
25 |
26 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
27 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
28 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT
29 | WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT
30 | NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
31 | FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND
32 | PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE
33 | DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR
34 | OR CORRECTION.
35 |
36 | ------------------------------------------------------------------------
37 | """
38 |
39 | # Authors : Alexander Kapitanov
40 | # ...
41 | # Contacts :
42 | # ...
43 | # Release Date : 2019/05/31
44 | # License : GNU GENERAL PUBLIC LICENSE
45 |
46 | from typing import Tuple
47 |
48 | from src.attractors.attractor import BaseAttractor
49 |
50 |
51 | class Wang(BaseAttractor):
52 | """Wang attractor (it is improved version of Lorenz model)."""
53 |
54 | def attractor(self, x: float, y: float, z: float, **kwargs) -> Tuple[float, float, float]:
55 | r"""Calculate the next coordinate X, Y, Z for 3rd-order Wang system
56 |
57 | Parameters
58 | ----------
59 | x, y, z : float
60 | Input coordinates X, Y, Z respectively.
61 |
62 | Examples
63 | --------
64 | >>> from src.attractors.wang import Wang
65 | >>> coordinates = (0, 1, -1)
66 | >>> model = Wang(num_points=1)
67 | >>> output = model.attractor(*coordinates)
68 | >>> print(output)
69 | (1, -1, 3)
70 | >>> model = Wang(num_points=10, init_point=(0.1, 0, -0.1), step=100)
71 | >>> print(model.get_coordinates())
72 | [[ 0.1 0. -0.1 ]
73 | [ 0.101 0.0009 -0.097 ]
74 | [ 0.10201087 0.00180303 -0.09408909]
75 | [ 0.10303268 0.00270913 -0.09126458]
76 | [ 0.10406548 0.00361833 -0.08852385]
77 | [ 0.10510934 0.00453068 -0.08586437]
78 | [ 0.10616432 0.00544621 -0.08328368]
79 | [ 0.1072305 0.00636498 -0.08077938]
80 | [ 0.10830794 0.00728701 -0.07834918]
81 | [ 0.10939673 0.00821236 -0.07599081]]
82 |
83 | See Also
84 | -----
85 | No links.
86 | """
87 | x_out = x - y * z
88 | y_out = x - y + x * z
89 | z_out = -3 * z + x * y
90 | return x_out, y_out, z_out
91 |
92 |
93 | if __name__ == "__main__":
94 | import doctest
95 |
96 | doctest.testmod(verbose=True)
97 |
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/src/attractors/nose_hoover.py:
--------------------------------------------------------------------------------
1 | r"""Nose-Hoover attractor system.
2 |
3 | Description:
4 | The Nose–Hoover thermostat is a deterministic algorithm for
5 | constant-temperature molecular dynamics simulations. It was originally
6 | developed by Nose and was improved further by Hoover.
7 |
8 | Nose–Hoover oscillator is ordinary differential equation (ODE) of
9 | 3rd order system.
10 | Nose–Hoover system has only five terms and two quadratic
11 | nonlinearities.
12 |
13 | Nose–Hoover equations are:
14 | dx/dt = y
15 | dy/dt = y * z - x
16 | dz/dt = 1 - y * y
17 |
18 | Nose–Hoover system doesn't have any system parameters.
19 |
20 | ------------------------------------------------------------------------
21 |
22 | GNU GENERAL PUBLIC LICENSE
23 | Version 3, 29 June 2007
24 |
25 | Copyright (c) 2019 Kapitanov Alexander
26 |
27 | This program is free software: you can redistribute it and/or modify
28 | it under the terms of the GNU General Public License as published by
29 | the Free Software Foundation, either version 3 of the License, or
30 | (at your option) any later version.
31 |
32 | You should have received a copy of the GNU General Public License
33 | along with this program. If not, see .
34 |
35 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
36 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
37 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT
38 | WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT
39 | NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
40 | FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND
41 | PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE
42 | DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR
43 | OR CORRECTION.
44 |
45 | ------------------------------------------------------------------------
46 | """
47 |
48 | # Authors : Alexander Kapitanov
49 | # ...
50 | # Contacts :
51 | # ...
52 | # Release Date : 2020/07/29
53 | # License : GNU GENERAL PUBLIC LICENSE
54 |
55 | from typing import Tuple
56 |
57 | from src.attractors.attractor import BaseAttractor
58 |
59 |
60 | class NoseHoover(BaseAttractor):
61 | """Nose Hoover attractor."""
62 |
63 | def attractor(self, x: float, y: float, z: float, **kwargs) -> Tuple[float, float, float]:
64 | r"""Calculate the next coordinate X, Y, Z for 3rd-order Nose Hoover system
65 |
66 | Parameters
67 | ----------
68 | x, y, z : float
69 | Input coordinates X, Y, Z respectively.
70 |
71 | Examples
72 | --------
73 | >>> from src.attractors.nose_hoover import NoseHoover
74 | >>> coordinates = (0, 1, -1)
75 | >>> model = NoseHoover(num_points=1)
76 | >>> output = model.attractor(*coordinates)
77 | >>> print(output)
78 | (1, -1, 0)
79 | >>> model = NoseHoover(num_points=10, init_point=(0.1, 0, -0.1), step=100)
80 | >>> print(model.get_coordinates())
81 | [[ 0.1 0. -0.1 ]
82 | [ 0.1 -0.001 -0.09 ]
83 | [ 0.09999 -0.0019991 -0.08000001]
84 | [ 0.09997001 -0.0029974 -0.07000005]
85 | [ 0.09994003 -0.003995 -0.06000014]
86 | [ 0.09990008 -0.00499201 -0.0500003 ]
87 | [ 0.09985016 -0.00598851 -0.04000055]
88 | [ 0.09979028 -0.00698462 -0.03000091]
89 | [ 0.09972043 -0.00798042 -0.0200014 ]
90 | [ 0.09964063 -0.00897603 -0.01000203]]
91 |
92 | See Also
93 | -----
94 | https://en.wikipedia.org/wiki/Nos%C3%A9%E2%80%93Hoover_thermostat
95 |
96 | """
97 | x_out = y
98 | y_out = y * z - x
99 | z_out = 1 - y * y
100 | return x_out, y_out, z_out
101 |
102 |
103 | if __name__ == "__main__":
104 | import doctest
105 |
106 | doctest.testmod(verbose=True)
107 |
--------------------------------------------------------------------------------
/src/attractors/rikitake.py:
--------------------------------------------------------------------------------
1 | r"""Rikitake chaotic system.
2 |
3 | Description :
4 | Rikitake system is ordinary differential equation (ODE) of
5 | 3rd order system.
6 | Rikitake system attempts to explain the reversal of the Earth’s
7 | magnetic field.
8 |
9 | Rikitake equations are:
10 | dx/dt = -mu * x + z * y
11 | dy/dt = -mu * y + x * (z - a)
12 | dz/dt = 1 - x * y
13 |
14 | where a, mu - are Rikitake system parameters.
15 | Default values are
16 | - a = 5,
17 | - mu = 2
18 | or
19 |
20 | - a = mu = 1.
21 |
22 | ------------------------------------------------------------------------
23 |
24 | GNU GENERAL PUBLIC LICENSE
25 | Version 3, 29 June 2007
26 |
27 | Copyright (c) 2019 Kapitanov Alexander
28 |
29 | This program is free software: you can redistribute it and/or modify
30 | it under the terms of the GNU General Public License as published by
31 | the Free Software Foundation, either version 3 of the License, or
32 | (at your option) any later version.
33 |
34 | You should have received a copy of the GNU General Public License
35 | along with this program. If not, see .
36 |
37 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
38 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
39 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT
40 | WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT
41 | NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
42 | FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND
43 | PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE
44 | DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR
45 | OR CORRECTION.
46 |
47 | ------------------------------------------------------------------------
48 | """
49 |
50 | # Authors : Alexander Kapitanov
51 | # ...
52 | # Contacts :
53 | # ...
54 | # Release Date : 2019/05/30
55 | # License : GNU GENERAL PUBLIC LICENSE
56 |
57 | from typing import Tuple
58 |
59 | from src.attractors.attractor import BaseAttractor
60 |
61 |
62 | class Rikitake(BaseAttractor):
63 | """Rikitake attractor."""
64 |
65 | def attractor(self, x: float, y: float, z: float, a: float = 5, mu: float = 2) -> Tuple[float, float, float]:
66 | r"""Calculate the next coordinate X, Y, Z for 3rd-order Rikitake system
67 |
68 | Parameters
69 | ----------
70 | x, y, z : float
71 | Input coordinates X, Y, Z respectively.
72 | a, mu : float
73 | Rikitake system parameters. Default:
74 | - a = 5,
75 | - mu = 2
76 | or
77 | - a = mu = 1.
78 |
79 | Examples
80 | --------
81 | >>> from src.attractors.rikitake import Rikitake
82 | >>> coordinates = (0, 1, -1)
83 | >>> model = Rikitake(num_points=1)
84 | >>> output = model.attractor(*coordinates)
85 | >>> print(output)
86 | (-1, -2, 1)
87 | >>> model = Rikitake(num_points=10, init_point=(0.1, 0, -0.1), step=100)
88 | >>> print(model.get_coordinates())
89 | [[ 0.1 0. -0.1 ]
90 | [ 0.098 -0.0051 -0.09 ]
91 | [ 0.09604459 -0.0099862 -0.079995 ]
92 | [ 0.09413169 -0.01466554 -0.06998541]
93 | [ 0.09225932 -0.01914469 -0.05997161]
94 | [ 0.09042561 -0.02343009 -0.04995394]
95 | [ 0.0886288 -0.02752794 -0.03993276]
96 | [ 0.08686722 -0.03144421 -0.02990836]
97 | [ 0.08513928 -0.03518467 -0.01988104]
98 | [ 0.08344349 -0.03875487 -0.00985109]]
99 |
100 | See Also
101 | -----
102 | Cannot add wiki link ;(
103 | """
104 | x_out = -mu * x + z * y
105 | y_out = -mu * y + x * (z - a)
106 | z_out = 1 - x * y
107 |
108 | return x_out, y_out, z_out
109 |
110 |
111 | if __name__ == "__main__":
112 | import doctest
113 |
114 | doctest.testmod(verbose=True)
115 |
--------------------------------------------------------------------------------
/src/attractors/lotka_volterra.py:
--------------------------------------------------------------------------------
1 | r"""Lotka Volterra attractor.
2 |
3 | Description :
4 | The Lotka–Volterra equations, also known as the predator–prey equations,
5 | are a pair of first-order nonlinear differential equations,
6 | frequently used to describe the dynamics of biological systems in
7 | which two species interact, one as a predator and the other as prey.
8 |
9 | Chaotic Lotka-Volterra model require a careful tuning of
10 | parameters and are even less likely to exhibit chaos as the number
11 | of species increases.
12 |
13 | Lotka–Volterra equations are:
14 | Eq. 1:
15 | dx/dt = x * (1 - x - 9*y)
16 | dy/dt = -y * (1 - 6*x - y + 9*z)
17 | dz/dt = z * (1 - 3*x - z)
18 |
19 | Be careful! Init parameters of x, y, z should be set right!
20 |
21 | For example, [x, y, z] = [0.6, 0.2, 0.01]
22 |
23 | ------------------------------------------------------------------------
24 |
25 | GNU GENERAL PUBLIC LICENSE
26 | Version 3, 29 June 2007
27 |
28 | Copyright (c) 2019 Kapitanov Alexander
29 |
30 | This program is free software: you can redistribute it and/or modify
31 | it under the terms of the GNU General Public License as published by
32 | the Free Software Foundation, either version 3 of the License, or
33 | (at your option) any later version.
34 |
35 | You should have received a copy of the GNU General Public License
36 | along with this program. If not, see .
37 |
38 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
39 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
40 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT
41 | WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT
42 | NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
43 | FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND
44 | PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE
45 | DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR
46 | OR CORRECTION.
47 |
48 | ------------------------------------------------------------------------
49 | """
50 |
51 | # Authors : Alexander Kapitanov
52 | # ...
53 | # Contacts :
54 | # ...
55 | # Release Date : 2019/05/31
56 | # License : GNU GENERAL PUBLIC LICENSE
57 |
58 | from typing import Tuple
59 |
60 | from src.attractors.attractor import BaseAttractor
61 |
62 |
63 | class LotkaVolterra(BaseAttractor):
64 | """Lotka-Volterra attractor."""
65 |
66 | def attractor(self, x: float, y: float, z: float, **kwargs) -> Tuple[float, float, float]:
67 | r"""Calculate the next coordinate X, Y, Z for 3rd-order Lotka-Volterra system
68 |
69 | Parameters
70 | ----------
71 | x, y, z : float
72 | Input coordinates X, Y, Z respectively.
73 |
74 | Lotka-Volterra does not have initial parameters.
75 |
76 | Examples
77 | --------
78 | >>> from src.attractors.lotka_volterra import LotkaVolterra
79 | >>> coordinates = (0, 1, -1)
80 | >>> model = LotkaVolterra(num_points=1)
81 | >>> output = model.attractor(*coordinates)
82 | >>> print(output)
83 | (0, 9, -2)
84 | >>> model = LotkaVolterra(num_points=10, init_point=(0.1, 0.5, -0.1), step=100)
85 | >>> print(model.get_coordinates())
86 | [[ 0.1 0.5 -0.1 ]
87 | [ 0.0964 0.505 -0.1008 ]
88 | [ 0.09288969 0.51000253 -0.10161809]
89 | [ 0.08946864 0.51501026 -0.10245436]
90 | [ 0.08613633 0.52002601 -0.10330888]
91 | [ 0.08289212 0.5250527 -0.10418173]
92 | [ 0.07973528 0.53009342 -0.10507301]
93 | [ 0.07666501 0.53515137 -0.10598281]
94 | [ 0.07368042 0.54022989 -0.1069112 ]
95 | [ 0.07078055 0.54533243 -0.1078583 ]]
96 |
97 | See Also
98 | -----
99 | https://en.wikipedia.org/wiki/Lotka%E2%80%93Volterra_equations
100 | """
101 | x_out = x * (1 - x - 9 * y)
102 | y_out = -y * (1 - 6 * x - y + 9 * z)
103 | z_out = z * (1 - 3 * x - z)
104 | return x_out, y_out, z_out
105 |
106 |
107 | if __name__ == "__main__":
108 | import doctest
109 |
110 | doctest.testmod(verbose=True)
111 |
--------------------------------------------------------------------------------
/src/attractors/lorenz.py:
--------------------------------------------------------------------------------
1 | r"""Lorenz Attractor
2 |
3 | Description:
4 | Lorenz attractor is ordinary differential equation (ODE) of 3rd order system.
5 | In 1963, E. Lorenz developed a simplified mathematical model for
6 | atmospheric convection.
7 |
8 | Lorenz equations are:
9 | dx/dt = sigma * (y - x)
10 | dy/dt = rho * x - y - x * z
11 | dz/dt = x * y - beta * z
12 |
13 | where:
14 | beta, rho and sigma - are Lorenz system parameters. Default
15 | default values for parameters are:
16 | beta = 8/3,
17 | rho = 28,
18 | sigma = 10.
19 |
20 | If rho < 1 then there is only one equilibrium point,
21 | which is at the origin. This point corresponds to no convection.
22 |
23 | ------------------------------------------------------------------------
24 |
25 | GNU GENERAL PUBLIC LICENSE
26 | Version 3, 29 June 2007
27 |
28 | Copyright (c) 2019 Kapitanov Alexander
29 |
30 | This program is free software: you can redistribute it and/or modify
31 | it under the terms of the GNU General Public License as published by
32 | the Free Software Foundation, either version 3 of the License, or
33 | (at your option) any later version.
34 |
35 | You should have received a copy of the GNU General Public License
36 | along with this program. If not, see .
37 |
38 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
39 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
40 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT
41 | WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT
42 | NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
43 | FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND
44 | PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE
45 | DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR
46 | OR CORRECTION.
47 |
48 | ------------------------------------------------------------------------
49 | """
50 |
51 | # Authors : Alexander Kapitanov
52 | # ...
53 | # Contacts :
54 | # ...
55 | # Release Date : 2019/05/31
56 | # License : GNU GENERAL PUBLIC LICENSE
57 |
58 | from typing import Tuple
59 |
60 | from src.attractors.attractor import BaseAttractor
61 |
62 |
63 | class Lorenz(BaseAttractor):
64 | """Lorenz attractor."""
65 |
66 | def attractor(
67 | self, x: float, y: float, z: float, sigma: float = 10, beta: float = 8 / 3, rho: float = 28,
68 | ) -> Tuple[float, float, float]:
69 | r"""Calculate the next coordinate X, Y, Z for 3rd-order Lorenz system
70 |
71 | Parameters
72 | ----------
73 | x, y, z : float
74 | Input coordinates X, Y, Z respectively.
75 | sigma, beta, rho : float
76 | Lorenz system parameters. Default:
77 | - sigma = 10,
78 | - beta = 8/3,
79 | - rho = 28,
80 |
81 | Examples
82 | --------
83 | >>> from src.attractors.lorenz import Lorenz
84 | >>> coordinates = (0, 1, -1)
85 | >>> model = Lorenz(num_points=1)
86 | >>> output = model.attractor(*coordinates)
87 | >>> print(output)
88 | (10, -1, 2.6666666666666665)
89 | >>> model = Lorenz(num_points=10, init_point=(0.1, 0, -0.1), step=100)
90 | >>> print(model.get_coordinates())
91 | [[ 0.1 0. -0.1 ]
92 | [ 0.09 0.0281 -0.09733333]
93 | [ 0.08381 0.0531066 -0.09471249]
94 | [ 0.08073966 0.07612171 -0.09214231]
95 | [ 0.08027787 0.098042 -0.08962372]
96 | [ 0.08205428 0.11961133 -0.08715505]
97 | [ 0.08580998 0.14146193 -0.08473277]
98 | [ 0.09137518 0.16414681 -0.08235184]
99 | [ 0.09865234 0.18816564 -0.0800058 ]
100 | [ 0.10760367 0.21398557 -0.07768669]]
101 |
102 | See Also
103 | -----
104 | https://en.wikipedia.org/wiki/Lorenz_system
105 | """
106 | x_out = sigma * (y - x)
107 | y_out = rho * x - y - x * z
108 | z_out = x * y - beta * z
109 | return x_out, y_out, z_out
110 |
111 |
112 | if __name__ == "__main__":
113 | import doctest
114 |
115 | doctest.testmod(verbose=True)
116 |
--------------------------------------------------------------------------------
/src/attractors/chua.py:
--------------------------------------------------------------------------------
1 | r"""Chua attractor
2 |
3 | Description:
4 | Chua circuit. This is a simple electronic circuit that exhibits
5 | classic chaotic behavior. This means roughly that it is a
6 | "nonperiodic oscillator".
7 |
8 | Chua equations are:
9 |
10 | Eq. 1:
11 | dx/dt = alpha * (y - x - ht)
12 | dy/dt = x - y + z
13 | dz/dt = -beta * y
14 |
15 | where ht = mu1*x + 0.5*(mu0 - mu1)*(np.abs(x + 1) - np.abs(x - 1))
16 | and alpha, beta, mu0 and mu1 - are Chua system parameters.
17 |
18 | Default values are:
19 | alpha = 15.6
20 | beta = 28
21 | mu0 = -1.143
22 | mu1 = -0.714
23 |
24 | Eq. 2:
25 | dx/dt = 0.3*y + x - x**3
26 | dy/dt = x + z
27 | dz/dt = y
28 |
29 | without default values.
30 |
31 | ------------------------------------------------------------------------
32 |
33 | GNU GENERAL PUBLIC LICENSE
34 | Version 3, 29 June 2007
35 |
36 | Copyright (c) 2019 Kapitanov Alexander
37 |
38 | This program is free software: you can redistribute it and/or modify
39 | it under the terms of the GNU General Public License as published by
40 | the Free Software Foundation, either version 3 of the License, or
41 | (at your option) any later version.
42 |
43 | You should have received a copy of the GNU General Public License
44 | along with this program. If not, see .
45 |
46 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
47 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
48 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT
49 | WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT
50 | NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
51 | FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND
52 | PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE
53 | DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR
54 | OR CORRECTION.
55 |
56 | ------------------------------------------------------------------------
57 | """
58 |
59 | # Authors : Alexander Kapitanov
60 | # ...
61 | # Contacts :
62 | # ...
63 | # Release Date : 2019/05/31
64 | # License : GNU GENERAL PUBLIC LICENSE
65 |
66 | from math import fabs
67 | from typing import Tuple
68 |
69 | from src.attractors.attractor import BaseAttractor
70 |
71 |
72 | class Chua(BaseAttractor):
73 | """Chua attractor."""
74 |
75 | def attractor(
76 | self,
77 | x: float,
78 | y: float,
79 | z: float,
80 | alpha: float = 15.6,
81 | beta: float = 28,
82 | mu0: float = -1.143,
83 | mu1: float = -0.714,
84 | ) -> Tuple[float, float, float]:
85 | r"""Calculate the next coordinate X, Y, Z for Chua system.
86 |
87 | Parameters
88 | ----------
89 | x, y, z : float
90 | Input coordinates X, Y, Z respectively.
91 |
92 | alpha, beta, mu0, mu1 : float
93 | Chua system parameters. Default:
94 | - alpha = 15.6,
95 | - beta = 28,
96 | - mu0 = -1.143,
97 | - mu1 = -0.714,
98 |
99 | Examples
100 | --------
101 | >>> from src.attractors.chua import Chua
102 | >>> coordinates = (0, 1, -1)
103 | >>> model = Chua(num_points=1)
104 | >>> output = model.attractor(*coordinates)
105 | >>> print(output)
106 | (15.6, -2, -28)
107 | >>> model = Chua(num_points=10, init_point=(0.1, 0, -0.1), step=100)
108 | >>> print(model.get_coordinates())
109 | [[ 1.00000000e-01 0.00000000e+00 -1.00000000e-01]
110 | [ 1.02230800e-01 0.00000000e+00 -1.00000000e-01]
111 | [ 1.04511365e-01 2.23080000e-05 -1.00000000e-01]
112 | [ 1.06846284e-01 6.71985669e-05 -1.00006246e-01]
113 | [ 1.09240294e-01 1.34926961e-04 -1.00025062e-01]
114 | [ 1.11698275e-01 2.25730015e-04 -1.00062841e-01]
115 | [ 1.14225254e-01 3.39827053e-04 -1.00126046e-01]
116 | [ 1.16826404e-01 4.77420867e-04 -1.00221197e-01]
117 | [ 1.19507045e-01 6.38698727e-04 -1.00354875e-01]
118 | [ 1.22272645e-01 8.23833441e-04 -1.00533711e-01]]
119 |
120 | See Also
121 | -----
122 | https://en.wikipedia.org/wiki/Chua%27s_circuit
123 | """
124 |
125 | ht = mu1 * x + 0.5 * (mu0 - mu1) * (fabs(x + 1) - fabs(x - 1))
126 | # Next step coordinates:
127 | x_out = alpha * (y - x - ht)
128 | y_out = x - y + z
129 | z_out = -beta * y
130 | return x_out, y_out, z_out
131 |
132 |
133 | if __name__ == "__main__":
134 | import doctest
135 |
136 | doctest.testmod(verbose=True)
137 |
--------------------------------------------------------------------------------
/src/dynamic_system.py:
--------------------------------------------------------------------------------
1 | """Dynamic system class.
2 |
3 | Description:
4 | Combine attractor, calculator and drawer.
5 |
6 | ------------------------------------------------------------------------
7 |
8 | GNU GENERAL PUBLIC LICENSE
9 | Version 3, 29 June 2007
10 |
11 | Copyright (c) 2019 Kapitanov Alexander
12 |
13 | This program is free software: you can redistribute it and/or modify
14 | it under the terms of the GNU General Public License as published by
15 | the Free Software Foundation, either version 3 of the License, or
16 | (at your option) any later version.
17 |
18 | You should have received a copy of the GNU General Public License
19 | along with this program. If not, see .
20 |
21 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
22 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
23 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT
24 | WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT
25 | NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
26 | FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND
27 | PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE
28 | DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR
29 | OR CORRECTION.
30 |
31 | ------------------------------------------------------------------------
32 | """
33 |
34 | # Authors : Alexander Kapitanov
35 | # ...
36 | # Contacts :
37 | # ...
38 | # Release Date : 2020/07/25
39 | # License : GNU GENERAL PUBLIC LICENSE
40 |
41 | from typing import Optional
42 |
43 | import pandas as pd
44 | from src.utils.calculator import Calculator
45 | from src.utils.drawer import PlotDrawer
46 | from src.utils.parser import AttractorType, Settings
47 |
48 |
49 | class DynamicSystem:
50 | """Main class for computing chaotic system.
51 |
52 | Parameters
53 | ----------
54 | # TODO: add parameters
55 |
56 | Attributes
57 | ----------
58 | model: ChaoticAttractor()
59 | drawer: PlotDrawer()
60 | calculator: Calculator()
61 | settings: Settings()
62 |
63 | Examples
64 | --------
65 | # TODO: Add examples
66 |
67 | See Also:
68 | -----
69 |
70 | Dynamic systems:
71 | https://en.wikipedia.org/wiki/Dynamical_system
72 | https://en.wikipedia.org/wiki/Dynamical_systems_theory
73 |
74 | Differential equations:
75 | https://en.wikipedia.org/wiki/Differential_equation
76 |
77 | """
78 |
79 | def __init__(self, input_args: Optional[tuple] = None, show_log: bool = False):
80 | # Main modules
81 | self.settings = Settings(show_logs=show_log)
82 | self.settings.update_params(input_args)
83 |
84 | self.model: AttractorType = self.settings.model
85 | self.drawer: PlotDrawer = PlotDrawer(
86 | self.settings.save_plots,
87 | self.settings.show_plots,
88 | self.settings.add_2d_gif
89 | )
90 | self.drawer.model_name = self.settings.attractor.capitalize()
91 | self.calculator = Calculator()
92 |
93 | def collect_statistics(self):
94 | math_dict = {}
95 | _min_max = self.calculator.check_min_max()
96 | _moments = self.calculator.check_moments()
97 | math_dict.update({"Min": _min_max[0]})
98 | math_dict.update({"Max": _min_max[1]})
99 | math_dict.update(_moments)
100 | math_df = pd.DataFrame.from_dict(math_dict, columns=["X", "Y", "Z"], orient="index")
101 | return math_df
102 |
103 | def run(self):
104 | # Get vector of coordinates
105 | coordinates = self.model.get_coordinates()
106 | self.calculator.coordinates = coordinates
107 |
108 | # Calculate
109 | stats = self.collect_statistics()
110 | if self.settings.show_logs:
111 | print(f"[INFO]: Show statistics:\n{stats}\n")
112 |
113 | self.calculator.check_probability()
114 | spectrums = self.calculator.calculate_spectrum()
115 | correlations = self.calculator.calculate_correlation()
116 |
117 | # Draw results
118 |
119 | if self.settings.show_all:
120 | self.drawer.show_all_plots(coordinates, spectrums, correlations)
121 | else:
122 | if self.settings.show_spectrum:
123 | self.drawer.show_spectrum_and_correlation(coordinates, spectrums, correlations)
124 | if self.settings.show_timeplot:
125 | self.drawer.show_time_plots(coordinates)
126 | if self.settings.show_3d_plots:
127 | self.drawer.show_3d_plots(coordinates)
128 | # self.drawer.make_3d_plot_gif(50)
129 |
130 |
131 | if __name__ == "__main__":
132 | command_line = (
133 | "--init_point",
134 | "1 -1 2",
135 | "--points",
136 | "3000",
137 | "--step",
138 | "50",
139 | "--save_plots",
140 | # "--show_plots",
141 | "--add_2d_gif",
142 | "lorenz",
143 | )
144 |
145 | dynamic_system = DynamicSystem(input_args=command_line, show_log=True)
146 | dynamic_system.run()
147 |
--------------------------------------------------------------------------------
/src/attractors/rossler.py:
--------------------------------------------------------------------------------
1 | r"""Rossler attractor (see 'Strange attractors' book).
2 |
3 | Description :
4 | Rossler attractor is the attractor for the Rössler system. Rossler
5 | attractor is a system of three non-linear ordinary differential
6 | equations.
7 |
8 | Rossler equations are:
9 | dx/dt = -(y + z)
10 | dy/dt = x + a * y
11 | dz/dt = b + z * (x - c)
12 |
13 | where a, b and sigma - are Rossler system parameters. Default
14 | values are: a = 0.2, b = 0.2 and c = 5.7.
15 |
16 | 1) a = 0.2, b = 0.2 and c = 5.7 (Standard model)
17 | 2) a = 0.1, b = 0.1 and c = 14 (another useful parameters)
18 | 3) a = 0.5, b = 1.0 and c = 3 (J. C. Sprott)
19 |
20 | Wiki (Varying parameters);
21 |
22 | Varying a:
23 | b = 0.2 and c = 5.7 are fixed. Change a:
24 |
25 | a <= 0 : Converges to the centrally located fixed point
26 | a = 0.1 : Unit cycle of period 1
27 | a = 0.2 : Standard parameter value selected by Rössler, chaotic
28 | a = 0.3 : Chaotic attractor, significantly more Möbius strip-like
29 | (folding over itself).
30 | a = 0.35 : Similar to .3, but increasingly chaotic
31 | a = 0.38 : Similar to .35, but increasingly chaotic
32 |
33 | Varying b:
34 | a = 0.2 and c = 5.7 are fixed. Change b:
35 |
36 | If b approaches 0 the attractor approaches infinity, but if b would
37 | be more than a and c, system becomes not a chaotic.
38 |
39 | Varying c:
40 | a = b = 0.1 are fixed. Change c:
41 |
42 | c = 4 : period-1 orbit,
43 | c = 6 : period-2 orbit,
44 | c = 8.5 : period-4 orbit,
45 | c = 8.7 : period-8 orbit,
46 | c = 9 : sparse chaotic attractor,
47 | c = 12 : period-3 orbit,
48 | c = 12.6 : period-6 orbit,
49 | c = 13 : sparse chaotic attractor,
50 | c = 18 : filled-in chaotic attractor.
51 |
52 | ------------------------------------------------------------------------
53 |
54 | GNU GENERAL PUBLIC LICENSE
55 | Version 3, 29 June 2007
56 |
57 | Copyright (c) 2019 Kapitanov Alexander
58 |
59 | This program is free software: you can redistribute it and/or modify
60 | it under the terms of the GNU General Public License as published by
61 | the Free Software Foundation, either version 3 of the License, or
62 | (at your option) any later version.
63 |
64 | You should have received a copy of the GNU General Public License
65 | along with this program. If not, see .
66 |
67 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
68 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
69 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT
70 | WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT
71 | NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
72 | FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND
73 | PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE
74 | DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR
75 | OR CORRECTION.
76 |
77 | ------------------------------------------------------------------------
78 | """
79 |
80 | # Authors : Alexander Kapitanov
81 | # ...
82 | # Contacts :
83 | # ...
84 | # Release Date : 2019/05/31
85 | # License : GNU GENERAL PUBLIC LICENSE
86 |
87 | from typing import Tuple
88 |
89 | from src.attractors.attractor import BaseAttractor
90 |
91 |
92 | class Rossler(BaseAttractor):
93 | """Rossler attractor."""
94 |
95 | def attractor(
96 | self, x: float, y: float, z: float, a: float = 0.2, b: float = 0.2, c: float = 5.7,
97 | ) -> Tuple[float, float, float]:
98 | r"""Calculate the next coordinate X, Y, Z for 3rd-order Rossler system
99 |
100 | Parameters
101 | ----------
102 | x, y, z : float
103 | Input coordinates X, Y, Z respectively.
104 | a, b, c : float
105 | Rossler system parameters. Default:
106 | 1) a = 0.2, b = 0.2 and c = 5.7 (Standard model)
107 | 2) a = 0.1, b = 0.1 and c = 14 (another useful parameters)
108 | 3) a = 0.5, b = 1.0 and c = 3 (J. C. Sprott)
109 |
110 | Examples
111 | --------
112 | >>> from src.attractors.rossler import Rossler
113 | >>> coordinates = (0, 1, -1)
114 | >>> model = Rossler(num_points=1)
115 | >>> output = model.attractor(*coordinates)
116 | >>> print(output)
117 | (0, 0.2, 5.9)
118 | >>> model = Rossler(num_points=10, init_point=(0.1, 0, -0.1), step=100)
119 | >>> print(model.get_coordinates())
120 | [[ 0.1 0. -0.1 ]
121 | [ 0.101 0.001 -0.0924 ]
122 | [ 0.101914 0.002012 -0.08522652]
123 | [ 0.10274615 0.00303516 -0.07845547]
124 | [ 0.10350035 0.0040687 -0.07206412]
125 | [ 0.1041803 0.00511184 -0.06603105]
126 | [ 0.10478949 0.00616386 -0.06033607]
127 | [ 0.10533122 0.00722409 -0.05496014]
128 | [ 0.10580858 0.00829185 -0.0498853 ]
129 | [ 0.10622451 0.00936652 -0.04509462]]
130 |
131 | See Also
132 | -----
133 | https://en.wikipedia.org/wiki/R%C3%B6ssler_attractor
134 | """
135 | x_out = -(y + z)
136 | y_out = x + a * y
137 | z_out = b + z * (x - c)
138 |
139 | return x_out, y_out, z_out
140 |
141 |
142 | if __name__ == "__main__":
143 | import doctest
144 |
145 | doctest.testmod(verbose=True)
146 |
--------------------------------------------------------------------------------
/src/utils/calculator.py:
--------------------------------------------------------------------------------
1 | """Chaotic system calculator.
2 |
3 | Description:
4 | Useful component for calculate some parameters:
5 | math moments, FFTs, min and max values etc.
6 |
7 | ------------------------------------------------------------------------
8 |
9 | GNU GENERAL PUBLIC LICENSE
10 | Version 3, 29 June 2007
11 |
12 | Copyright (c) 2019 Kapitanov Alexander
13 |
14 | This program is free software: you can redistribute it and/or modify
15 | it under the terms of the GNU General Public License as published by
16 | the Free Software Foundation, either version 3 of the License, or
17 | (at your option) any later version.
18 |
19 | You should have received a copy of the GNU General Public License
20 | along with this program. If not, see .
21 |
22 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
23 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
24 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT
25 | WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT
26 | NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
27 | FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND
28 | PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE
29 | DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR
30 | OR CORRECTION.
31 |
32 | ------------------------------------------------------------------------
33 | """
34 |
35 | # Authors : Alexander Kapitanov
36 | # ...
37 | # Contacts :
38 | # ...
39 | # Release Date : 2020/07/25
40 | # License : GNU GENERAL PUBLIC LICENSE
41 |
42 | from typing import Tuple
43 |
44 | import numpy as np
45 | from scipy.fftpack import fft, fftshift
46 | from scipy.stats import gaussian_kde, kurtosis, skew
47 |
48 |
49 | class Calculator:
50 | """Main class for calculate math parameters: FFTs, Auto-Correlation, KDE (Prob) etc.
51 |
52 | See Also:
53 | -----
54 |
55 | """
56 |
57 | def __init__(self, kde_dots: int = 1000, fft_dots: int = 4096):
58 | self.kde_dots = kde_dots
59 | self.fft_dots = fft_dots
60 | self._coordinates = None
61 |
62 | def __len__(self):
63 | return len(self.coordinates)
64 |
65 | @property
66 | def coordinates(self) -> np.ndarray:
67 | return self._coordinates
68 |
69 | @coordinates.setter
70 | def coordinates(self, value: np.ndarray):
71 | """3D coordinates.
72 |
73 | Parameters
74 | ----------
75 | value : np.ndarray
76 | Numpy 3D array of dynamic system coordinates.
77 |
78 | """
79 | self._coordinates = value
80 |
81 | def check_min_max(self) -> Tuple[np.ndarray, np.ndarray]:
82 | """Calculate minimum and maximum for X, Y, Z coordinates.
83 | """
84 | return np.min(self.coordinates, axis=0), np.max(self.coordinates, axis=0)
85 |
86 | def check_moments(self, is_common: bool = False) -> dict:
87 | """Calculate stochastic parameters: mean, variance, skewness, kurtosis etc.
88 |
89 | Parameters
90 | ----------
91 | is_common : bool
92 | If False - method returns moments for each coordinate. Otherwise
93 | returns moments over all ndarray. Similar for axis or axes along
94 | which the moments are computed.
95 | The default is to compute the moments for each coordinate.
96 | """
97 | axis = None if is_common else 0
98 | return {
99 | "Mean": np.mean(self.coordinates, axis=axis),
100 | "Variance": np.var(self.coordinates, axis=axis),
101 | "Skewness": skew(self.coordinates, axis=axis),
102 | "Kurtosis": kurtosis(self.coordinates, axis=axis),
103 | "Median": np.median(self.coordinates, axis=axis),
104 | }
105 |
106 | def check_probability(self):
107 | """Check probability for each chaotic coordinates.
108 |
109 | """
110 | p_axi = np.zeros([3, self.kde_dots])
111 | d_kde = np.zeros([3, self.kde_dots])
112 | for ii in range(3):
113 | p_axi[ii] = np.linspace(self.coordinates[ii, :].min(), self.coordinates[ii, :].max(), self.kde_dots)
114 | d_kde[ii] = gaussian_kde(self.coordinates[ii, :]).evaluate(p_axi[ii, :])
115 | d_kde[ii] /= d_kde[ii].max()
116 | return d_kde
117 |
118 | def calculate_spectrum(self):
119 | """Calculate FFT (in dB) for input 3D coordinates. You can set number of FFT points into the object instance.
120 |
121 | """
122 | spectrum = fft(self.coordinates, self.fft_dots, axis=0)
123 | spectrum = np.abs(fftshift(spectrum, axes=0))
124 | # spectrum = np.abs(spectrum)
125 | spectrum /= np.max(spectrum)
126 | spec_log = 20 * np.log10(spectrum + np.finfo(np.float32).eps)
127 | return spec_log
128 |
129 | def calculate_correlation(self):
130 | """Calculate auto correlation function for chaotic coordinates.
131 |
132 | """
133 | nn, mm = 3, len(self.coordinates)
134 | auto_corr = np.zeros([mm, nn])
135 | for ii in range(nn):
136 | auto_corr[:, ii] = np.correlate(self.coordinates[:, ii], self.coordinates[:, ii], "same")
137 | return auto_corr
138 |
139 |
140 | if __name__ == "__main__":
141 | calc = Calculator()
142 |
143 | num_dots = 10000
144 | np.random.seed(42)
145 | calc.coordinates = np.random.randn(num_dots, 3)
146 |
147 | dd_kde = calc.check_probability()
148 | import matplotlib.pyplot as plt
149 |
150 | print(dd_kde.shape)
151 | plt.figure("Probability density function")
152 | for idx in range(dd_kde.shape[0]):
153 | plt.plot(dd_kde[idx], ".")
154 | # plt.xlim([0, dd_kde.shape[1] - 1])
155 | plt.grid()
156 | plt.tight_layout()
157 | plt.show()
158 |
--------------------------------------------------------------------------------
/README.rst:
--------------------------------------------------------------------------------
1 | .. -*- mode: rst -*-
2 |
3 | Python scripts for some 3rd-order chaotic systems (Lorenz attractor,
4 | Nose-Hoover oscillator, Rossler attractor, Riktake model, Duffing map etc.)
5 |
6 | Chaotic attractors
7 | ==================
8 |
9 | .. image:: https://raw.githubusercontent.com/capitanov/chaospy/master/img/Lorenz_3d.gif?sanitize=true
10 |
11 | Math model::
12 |
13 | dx/dt = sigma * (y - x)
14 | dy/dt = rho * x - y - x * z
15 | dz/dt = x * y - beta * z
16 |
17 | where sigma = 10, rho = 28 and beta = 8/3.
18 |
19 | Main info
20 | ~~~~~~~~~
21 |
22 | +---------------------+-----------------------------------------+
23 | | **Title** | Analysis and modeling chaotic systems |
24 | +=====================+=========================================+
25 | | **Author** | Alexander Kapitanov |
26 | +---------------------+-----------------------------------------+
27 | | **Contact** | |
28 | +---------------------+-----------------------------------------+
29 | | **Project lang** | Python 3 |
30 | +---------------------+-----------------------------------------+
31 | | **First Release** | 30 May 2019 |
32 | +---------------------+-----------------------------------------+
33 | | **License** | GNU GPL 3.0. |
34 | +---------------------+-----------------------------------------+
35 |
36 | Chaotic system
37 | ~~~~~~~~~~~~~~~~~~~~~~~~
38 |
39 | Rossler attractor::
40 |
41 | dx/dt = -(y + z)
42 | dy/dt = x + a * y
43 | dz/dt = b + z * (x - c)
44 |
45 | where a = 0.2, b = 0.2 and c = 5.7.
46 |
47 | .. image:: https://raw.githubusercontent.com/capitanov/chaospy/master/img/Rossler_3D.png?sanitize=true
48 |
49 | Spectrum and auto correlation
50 | ****************
51 | .. image:: https://raw.githubusercontent.com/capitanov/chaospy/master/img/Lorenz_Spectrum.png?sanitize=true
52 |
53 | Source code
54 | ~~~~~~~~~~~
55 |
56 | You can check the latest sources with the command::
57 |
58 | $ git clone
59 | $ cd chaospy
60 | $
61 | $ conda create -y -n venv python==3.9
62 | $ conda activate venv
63 | $ pip install -r requirements.txt
64 |
65 | Example run::
66 |
67 | $ python run.py --show_plots --show_all lorenz
68 |
69 |
70 | Dependencies
71 | ~~~~~~~~~~~~
72 |
73 | Project requirements: ``requirements.txt``
74 |
75 | Chaotic models
76 | ~~~~~~~~~~~~~~~~~~~~~~~~
77 |
78 | - Lorenz
79 | - Rossler
80 | - Rikitake
81 | - Duffing
82 | - Nose-Hoover
83 | - Lotka-Volterra
84 | - Wang
85 | - Chua
86 |
87 | Help
88 | ~~~~
89 |
90 | ::
91 |
92 | usage: parser.py [-h] [-p POINTS] [-s STEP]
93 | [--init_point INIT_POINT [INIT_POINT ...]] [--show_plots]
94 | [--save_plots] [--add_2d_gif]
95 | {lorenz,rossler,rikitake,chua,duffing,wang,nose-hoover,lotka-volterra}
96 | ...
97 |
98 | Specify command line arguments for dynamic system.Calculate some math
99 | parameters and plot some graphs of a given chaotic system.
100 |
101 | optional arguments:
102 | -h, --help show this help message and exit
103 | -p POINTS, --points POINTS
104 | Number of points for dymanic system. Default: 1024.
105 | -s STEP, --step STEP Step size for calculating the next coordinates of
106 | chaotic system. Default: 100.
107 | --init_point INIT_POINT [INIT_POINT ...]
108 | Initial point as string of three floats: "X, Y, Z".
109 | --show_plots Show plots of a model. Default: False.
110 | --save_plots Save plots to PNG files. Default: False.
111 | --add_2d_gif Add 2D coordinates to 3D model into GIF. Default:
112 | False.
113 |
114 | Chaotic models:
115 | You can select one of the chaotic models:
116 |
117 | {lorenz,rossler,rikitake,chua,duffing,wang,nose-hoover,lotka-volterra}
118 | lorenz Lorenz chaotic model
119 | rossler Rossler chaotic model
120 | rikitake Rikitake chaotic model
121 | chua Chua chaotic model
122 | duffing Duffing chaotic model
123 | wang Wang chaotic model
124 | nose-hoover Nose-hoover chaotic model
125 | lotka-volterra Lotka-volterra chaotic model
126 |
127 | Chaotic attractors are used as subparse command. Example:
128 |
129 | Lorenz attractor
130 | ****************
131 | ::
132 |
133 | usage: parser.py lorenz [-h] [--sigma SIGMA] [--beta BETA] [--rho RHO]
134 |
135 | optional arguments:
136 | -h, --help show this help message and exit
137 |
138 | Lorenz model arguments:
139 | --sigma SIGMA Lorenz system parameter. Default: 10
140 | --beta BETA Lorenz system parameter. Default: 2.6666
141 | --rho RHO Lorenz system parameter. Default: 28
142 |
143 | Chua circuit
144 | ************
145 | ::
146 |
147 | usage: parser.py chua [-h] [--alpha ALPHA] [--beta BETA] [--mu0 MU0]
148 | [--mu1 MU1]
149 |
150 | optional arguments:
151 | -h, --help show this help message and exit
152 |
153 | Chua model arguments:
154 | --alpha ALPHA Chua system parameter. Default: 0.1
155 | --beta BETA Chua system parameter. Default: 28
156 | --mu0 MU0 Chua system parameter. Default: -1.143
157 | --mu1 MU1 Chua system parameter. Default: -0.714
158 |
159 | See Also
160 | ~~~~~~~~
161 |
162 | - `Wiki `__
163 | - `Habr `__
164 |
--------------------------------------------------------------------------------
/src/attractors/attractor.py:
--------------------------------------------------------------------------------
1 | """Main attractor
2 |
3 | Description :
4 | Attractor base class.
5 | It implements abstract method (Chua, Lorenz, Duffing system).
6 | Can check some parameters for each chaotic system.
7 |
8 | ------------------------------------------------------------------------
9 |
10 | GNU GENERAL PUBLIC LICENSE
11 | Version 3, 29 June 2007
12 |
13 | Copyright (c) 2019 Kapitanov Alexander
14 |
15 | This program is free software: you can redistribute it and/or modify
16 | it under the terms of the GNU General Public License as published by
17 | the Free Software Foundation, either version 3 of the License, or
18 | (at your option) any later version.
19 |
20 | You should have received a copy of the GNU General Public License
21 | along with this program. If not, see .
22 |
23 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
24 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
25 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT
26 | WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT
27 | NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
28 | FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND
29 | PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE
30 | DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR
31 | OR CORRECTION.
32 |
33 | ------------------------------------------------------------------------
34 | """
35 |
36 | # Authors : Alexander Kapitanov
37 | # ...
38 | # Contacts :
39 | # ...
40 | # Release Date : 2020/07/16
41 | # License : GNU GENERAL PUBLIC LICENSE
42 |
43 | from abc import abstractmethod
44 | from typing import Tuple
45 |
46 | import numpy as np
47 |
48 |
49 | class BaseAttractor:
50 | """Base class for 3D chaotic system.
51 |
52 | Warning: Do not use this class directly. Use derived classes instead.
53 |
54 | Parameters
55 | ----------
56 | num_points: int
57 | Number of points for X, Y, Z coordinates.
58 |
59 | init_point: tuple
60 | Initial point [x0, y0, z0] for chaotic attractor system.
61 | Do not use zeros or very big values because of unstable behavior of dynamic system.
62 | Default: x, y, z == 1e-4.
63 |
64 | step: float / int
65 | Step for the next coordinate of dynamic system. Default: 1.0.
66 |
67 | Examples
68 | --------
69 | >>> from src.attractors.attractor import BaseAttractor
70 | >>> coordinates = (0, 1, -1)
71 | >>> model = BaseAttractor(num_points=10, init_point=(0.1, 2, -0.5), step=10)
72 | >>> print(model.get_coordinates())
73 | [[ 0.1 2. -0.5 ]
74 | [ 0.11 2.2 -0.55 ]
75 | [ 0.121 2.42 -0.605 ]
76 | [ 0.1331 2.662 -0.6655 ]
77 | [ 0.14641 2.9282 -0.73205 ]
78 | [ 0.161051 3.22102 -0.805255 ]
79 | [ 0.1771561 3.543122 -0.8857805 ]
80 | [ 0.19487171 3.8974342 -0.97435855]
81 | [ 0.21435888 4.28717762 -1.07179441]
82 | [ 0.23579477 4.71589538 -1.17897385]]
83 | >>> print(len(model))
84 | 10
85 | >>> model.update_attributes(num_points=1, init_point=(0, 1, 2), nfft=8)
86 | >>> model.__dict__
87 | {'num_points': 1, 'init_point': (0, 1, 2), 'step': 10, 'nfft': 8, '_coordinates': None}
88 | >>> len(model)
89 | 1
90 |
91 | See Also:
92 | -----
93 | Chaotic theory:
94 | https://en.wikipedia.org/wiki/Chaos_theory
95 | Attractors (dynamical systems):
96 | https://en.wikipedia.org/wiki/Attractor
97 | """
98 |
99 | def __init__(
100 | self,
101 | num_points: int,
102 | init_point: Tuple[float, float, float] = (1e-4, 1e-4, 1e-4),
103 | step: float = 1.0,
104 | show_log: bool = False,
105 | **kwargs: dict,
106 | ):
107 | if show_log:
108 | print(f"[INFO]: Initialize chaotic system: {self.__class__.__name__}\n")
109 | self.num_points = num_points
110 | self.init_point = init_point
111 | self.step = step
112 | self.kwargs = kwargs
113 |
114 | def get_coordinates(self):
115 | return np.array(list(next(self)))
116 |
117 | def __len__(self):
118 | return self.num_points
119 |
120 | def __iter__(self):
121 | return self
122 |
123 | def __next__(self):
124 | points = self.init_point
125 | for i in range(self.num_points):
126 | try:
127 | yield points
128 | next_points = self.attractor(*points, **self.kwargs)
129 | points = tuple(prev + curr / self.step for prev, curr in zip(points, next_points))
130 | except OverflowError:
131 | print(f"[FAIL]: Cannot do the next step because of floating point overflow. Step: {i}")
132 | break
133 |
134 | @abstractmethod
135 | def attractor(self, x: float, y: float, z: float, **kwargs) -> Tuple[float, float, float]:
136 | """Calculate the next coordinate X, Y, Z for chaotic system.
137 | Do not use this method for parent BaseAttractor class.
138 |
139 | Parameters
140 | ----------
141 | x, y, z : float
142 | Input coordinates: X, Y, Z respectively
143 |
144 | Returns
145 | -------
146 | result: tuple
147 | The next coordinates: X, Y, Z respectively
148 | """
149 | # raise NotImplementedError
150 | return x + y + z, y - z, x ** 2 - z ** 2
151 |
152 | def update_attributes(self, **kwargs):
153 | """Update chaotic system parameters."""
154 | for key in kwargs:
155 | if key in self.__dict__ and not key.startswith("_"):
156 | self.__dict__[key] = kwargs.get(key)
157 |
158 |
159 | if __name__ == "__main__":
160 |
161 | base_model = BaseAttractor(num_points=10, init_point=(-0.01, 0.5, 2), step=100)
162 | print(f"Model attributes: {base_model.__dict__}")
163 | print(f"Model length: {len(base_model)}")
164 | xyz = base_model.get_coordinates()
165 | print(xyz)
166 |
--------------------------------------------------------------------------------
/src/attractors/duffing.py:
--------------------------------------------------------------------------------
1 | r"""Duffing map.
2 |
3 | Description:
4 | Duffing map. It is a discrete-time dynamical system (2nd order)
5 | The map depends on the two constants: a and b.
6 | Z coordinate is a linear function.
7 |
8 | Duffing equations are:
9 | Eq. 1:
10 | dx/dt = y
11 | dy/dt = -a*y - x**3 + b * cos(z)
12 | dz/dt = 1
13 | where a = 0.1 and b = 11 (default parameters)
14 |
15 | Eq. 2:
16 | dx/dt = y
17 | dy/dt = a*y - y**3 - b*x
18 | dz/dt = 1
19 | where a = 2.75 and b = 0.2 (default parameters)
20 |
21 | ------------------------------------------------------------------------
22 |
23 | GNU GENERAL PUBLIC LICENSE
24 | Version 3, 29 June 2007
25 |
26 | Copyright (c) 2019 Kapitanov Alexander
27 |
28 | This program is free software: you can redistribute it and/or modify
29 | it under the terms of the GNU General Public License as published by
30 | the Free Software Foundation, either version 3 of the License, or
31 | (at your option) any later version.
32 |
33 | You should have received a copy of the GNU General Public License
34 | along with this program. If not, see .
35 |
36 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
37 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
38 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT
39 | WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT
40 | NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
41 | FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND
42 | PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE
43 | DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR
44 | OR CORRECTION.
45 |
46 | ------------------------------------------------------------------------
47 | """
48 |
49 | # Authors : Alexander Kapitanov
50 | # ...
51 | # Contacts :
52 | # ...
53 | # Release Date : 2019/05/31
54 | # License : GNU GENERAL PUBLIC LICENSE
55 |
56 | from math import cos
57 | from typing import Tuple
58 |
59 | from src.attractors.attractor import BaseAttractor
60 |
61 |
62 | class Duffing(BaseAttractor):
63 | """Duffing attractor."""
64 |
65 | def attractor(
66 | self, x: float, y: float, z: float, alpha: float = 0.1, beta: float = 11
67 | ) -> Tuple[float, float, float]:
68 | r"""Calculate the next coordinate X, Y, Z for 3rd-order Duffing map.
69 | It is 2nd order attractor (Z coordinate = 1)
70 |
71 | Parameters
72 | ----------
73 | x, y, z : float
74 | Input coordinates X, Y, Z respectively
75 | alpha, beta: float
76 | Duffing map parameters. Default:
77 | - alpha = 0.1,
78 | - beta = 11,
79 |
80 | Examples
81 | --------
82 | >>> from src.attractors.duffing import Duffing
83 | >>> coordinates = (0, 1, -1)
84 | >>> model = Duffing(num_points=1)
85 | >>> output = model.attractor(*coordinates)
86 | >>> print(output)
87 | (1, 5.843325364549537, 1)
88 | >>> model = Duffing(num_points=10, init_point=(0.1, 0, -0.1), step=100)
89 | >>> print(model.get_coordinates())
90 | [[ 0.1 0. -0.1 ]
91 | [ 0.1 0.10944046 -0.09 ]
92 | [ 0.1010944 0.21887582 -0.08 ]
93 | [ 0.10328316 0.3282948 -0.07 ]
94 | [ 0.10656611 0.4376861 -0.06 ]
95 | [ 0.11094297 0.54703837 -0.05 ]
96 | [ 0.11641336 0.6563402 -0.04 ]
97 | [ 0.12297676 0.7655801 -0.03 ]
98 | [ 0.13063256 0.87474642 -0.02 ]
99 | [ 0.13938002 0.98382738 -0.01 ]]
100 |
101 | See Also
102 | -----
103 | Duffing map (attractor):
104 | https://en.wikipedia.org/wiki/Duffing_map
105 | Duffing equation:
106 | https://en.wikipedia.org/wiki/Duffing_equation
107 |
108 | """
109 | x_out = y
110 | y_out = -alpha * y - x ** 3 + beta * cos(z)
111 | z_out = 1
112 | return x_out, y_out, z_out
113 |
114 |
115 | class DuffingMap(BaseAttractor):
116 | """Duffing attractor."""
117 |
118 | def attractor(
119 | self, x: float, y: float, z: float, alpha: float = 2.75, beta: float = 0.2
120 | ) -> Tuple[float, float, float]:
121 | """Calculate the next coordinate X, Y, Z for 3rd-order Duffing map.
122 | It is 2nd order attractor (Z coordinate = 1)
123 |
124 | Parameters
125 | ----------
126 | x, y, z : float
127 | Input coordinates X, Y, Z respectively
128 | alpha, beta: float
129 | Duffing map parameters. Default:
130 | - alpha = 2.75,
131 | - beta = 0.2,
132 |
133 | Examples
134 | --------
135 | >>> from src.attractors.duffing import Duffing
136 | >>> coordinates = (0, 0.5, -1)
137 | >>> model = Duffing(num_points=1)
138 | >>> output = model.attractor(*coordinates)
139 | >>> print(output)
140 | (0.5, 5.893325364549537, 1)
141 | >>> model = Duffing(num_points=10, init_point=(0, 4, -0.1), step=100)
142 | >>> print(model.get_coordinates())
143 | [[ 0. 4. -0.1 ]
144 | [ 0.04 4.10545046 -0.09 ]
145 | [ 0.0810545 4.21089917 -0.08 ]
146 | [ 0.1231635 4.31633113 -0.07 ]
147 | [ 0.16632681 4.42172673 -0.06 ]
148 | [ 0.21054407 4.52706105 -0.05 ]
149 | [ 0.25581469 4.63230318 -0.04 ]
150 | [ 0.30213772 4.73741548 -0.03 ]
151 | [ 0.34951187 4.84235276 -0.02 ]
152 | [ 0.3979354 4.94706145 -0.01 ]]
153 |
154 | See Also
155 | -----
156 | Duffing map (attractor):
157 | https://en.wikipedia.org/wiki/Duffing_map
158 | Duffing equation:
159 | https://en.wikipedia.org/wiki/Duffing_equation
160 |
161 | """
162 | x_out = y
163 | y_out = alpha * y - y ** 3 - beta * x
164 | z_out = 1
165 | return x_out, y_out, z_out
166 |
167 |
168 | if __name__ == "__main__":
169 | import doctest
170 |
171 | doctest.testmod(verbose=True)
172 |
--------------------------------------------------------------------------------
/src/utils/parser.py:
--------------------------------------------------------------------------------
1 | r"""Argument parser for testing chaotic attractor.
2 |
3 | ------------------------------------------------------------------------
4 |
5 | GNU GENERAL PUBLIC LICENSE
6 | Version 3, 29 June 2007
7 |
8 | Copyright (c) 2019 Kapitanov Alexander
9 |
10 | This program is free software: you can redistribute it and/or modify
11 | it under the terms of the GNU General Public License as published by
12 | the Free Software Foundation, either version 3 of the License, or
13 | (at your option) any later version.
14 |
15 | You should have received a copy of the GNU General Public License
16 | along with this program. If not, see .
17 |
18 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
19 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
20 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT
21 | WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT
22 | NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
23 | FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND
24 | PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE
25 | DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR
26 | OR CORRECTION.
27 |
28 | ------------------------------------------------------------------------
29 | """
30 |
31 | # Authors : Alexander Kapitanov
32 | # ...
33 | # Contacts :
34 | # ...
35 | # Release Date : 2020/07/30
36 | # License : GNU GENERAL PUBLIC LICENSE
37 |
38 | import argparse
39 | from typing import Optional, Sequence, Tuple, Union
40 |
41 | from src.attractors.chua import Chua
42 | from src.attractors.duffing import Duffing
43 | from src.attractors.lorenz import Lorenz
44 | from src.attractors.lotka_volterra import LotkaVolterra
45 | from src.attractors.nose_hoover import NoseHoover
46 | from src.attractors.rikitake import Rikitake
47 | from src.attractors.rossler import Rossler
48 | from src.attractors.wang import Wang
49 |
50 | AttractorType = Union[Chua, Duffing, Rossler, Lorenz, Wang, NoseHoover, Rikitake, Wang, LotkaVolterra]
51 |
52 | DEFAULT_PARAMETERS = {
53 | "lorenz": {"sigma": 10, "beta": 8 / 3, "rho": 28},
54 | "rikitake": {"a": 1, "mu": 1},
55 | "duffing": {"alpha": 0.1, "beta": 11},
56 | "rossler": {"a": 0.2, "b": 0.2, "c": 5.7},
57 | "chua": {"alpha": 0.1, "beta": 28, "mu0": -1.143, "mu1": -0.714},
58 | }
59 |
60 |
61 | class Settings:
62 | r"""Attributes collection for chaotic system.
63 |
64 | Attributes
65 | ----------
66 |
67 | attractor : Optional[AttractorType]
68 | Chaotic model.
69 |
70 | points : step
71 | Number of points for 3D system.
72 |
73 | step : float
74 | Step for diff. equations.
75 |
76 | show_timeplot : bool
77 | Show time plots
78 |
79 | show_spectrum : bool
80 | Show spectrum plots
81 |
82 | show_3d_plots : bool
83 | Show 3D plots
84 |
85 | show_all : bool
86 | Show all plots
87 |
88 | show_plots : bool
89 | Show plots after calculations: True / False.
90 |
91 | save_plots : bool
92 | Save plots after calculations: True / False.
93 |
94 | """
95 | __model_map = {
96 | "lorenz": Lorenz,
97 | "rossler": Rossler,
98 | "rikitake": Rikitake,
99 | "chua": Chua,
100 | "duffing": Duffing,
101 | "wang": Wang,
102 | "nose-hoover": NoseHoover,
103 | "lotka-volterra": LotkaVolterra,
104 | }
105 |
106 | def __init__(self, show_logs: bool = False, show_help: bool = False):
107 | self.show_logs = show_logs
108 | self.show_help = show_help
109 | # Settings
110 | self.attractor: str = "lorenz"
111 | self.init_point: Tuple[float, float, float] = (0.1, -0.1, 0.1)
112 | self.points: int = 1024
113 | self.step: float = 10
114 | self.add_2d_gif: bool = False
115 | self.show_all: bool = False
116 | self.show_timeplot: bool = False
117 | self.show_spectrum: bool = False
118 | self.show_3d_plots: bool = False
119 | self.show_plots: bool = False
120 | self.save_plots: bool = False
121 | self.kwargs: dict = {}
122 | # Model
123 | self._model: Optional[AttractorType] = None
124 |
125 | @property
126 | def model(self) -> Optional[AttractorType]:
127 | r"""Return model from dict of attractors.
128 | Set initial parameters.
129 |
130 | """
131 | if self._model is None:
132 | self._model = self.__model_map.get(self.attractor)(
133 | num_points=self.points,
134 | init_point=self.init_point,
135 | step=self.step,
136 | show_log=self.show_logs,
137 | **self.kwargs,
138 | )
139 | return self._model
140 |
141 | def update_params(self, input_args: Optional[Sequence[str]] = None):
142 | r"""Update class attributes from command line parser.
143 | Kwargs is a dictionary, and it can have some parameters for chaotic model.
144 |
145 | Parameters
146 | ----------
147 | input_args : tuple
148 | Tuple of strings for input arguments. Example: ("--show_plots", "--step", "1000", "lorenz")
149 |
150 | """
151 | args_dict = self.parse_arguments(input_args=input_args, show_args=self.show_logs, show_help=self.show_help)
152 | for item in args_dict:
153 | if hasattr(self, item) and item is not None:
154 | setattr(self, item, args_dict[item])
155 | else:
156 | self.kwargs[item] = args_dict[item]
157 |
158 | self.init_point = args_dict["init_point"]
159 |
160 | @staticmethod
161 | def _three_floats(value) -> Tuple:
162 | values = value.split()
163 | if len(values) != 3:
164 | print(f"[FAIL]: Please enter initial points as X, Y, Z list. Example: --init_point 1 2 3")
165 | raise argparse.ArgumentError
166 | return tuple(map(float, values))
167 |
168 | def parse_arguments(
169 | self, input_args: Optional[Sequence[str]] = None, show_help: bool = False, show_args: bool = False
170 | ) -> dict:
171 | """This method is the useful command line helper. You can use it with command line arguments.
172 |
173 | Parameters
174 | ----------
175 | input_args : tuple
176 |
177 | show_help : bool
178 | Show help of argument parser.
179 |
180 | show_args : bool
181 | Display arguments and their values as {key : item}
182 |
183 | Returns
184 | -------
185 | arguments : dict
186 | Parsed arguments from command line. Note: some arguments are positional.
187 |
188 | Examples
189 | --------
190 | >>> from src.utils.parser import Settings
191 | >>> settings = Settings()
192 | >>> command_line_str = "lorenz",
193 | >>> test_args = settings.parse_arguments(command_line_str, show_args=True)
194 | [INFO]: Cmmaind line arguments:
195 | points = 1024
196 | step = 100
197 | init_point = (0.1, -0.1, 0.1)
198 | show_plots = False
199 | save_plots = False
200 | add_2d_gif = False
201 | attractor = lorenz
202 | sigma = 10
203 | beta = 2.6666666666666665
204 | rho = 28
205 |
206 | >>> command_line_str = "--show_plots rossler --a 2 --b 4".split()
207 | >>> test_args = settings.parse_arguments(command_line_str, show_args=True)
208 | [INFO]: Cmmaind line arguments:
209 | points = 1024
210 | step = 100
211 | init_point = (0.1, -0.1, 0.1)
212 | show_plots = True
213 | save_plots = False
214 | add_2d_gif = False
215 | attractor = rossler
216 | a = 2.0
217 | b = 4.0
218 | c = 5.7
219 |
220 | """
221 | parser = argparse.ArgumentParser(
222 | description="Specify command line arguments for dynamic system."
223 | "Calculate some math parameters and plot some graphs of a given chaotic system."
224 | )
225 |
226 | parser.add_argument(
227 | "-p",
228 | "--points",
229 | type=int,
230 | default=1024,
231 | action="store",
232 | help=f"Number of points for dymanic system. Default: 1024.",
233 | )
234 |
235 | parser.add_argument(
236 | "-s",
237 | "--step",
238 | type=int,
239 | default=100,
240 | action="store",
241 | help=f"Step size for calculating the next coordinates of chaotic system. Default: 100.",
242 | )
243 |
244 | parser.add_argument(
245 | "--init_point",
246 | action="store",
247 | type=self._three_floats,
248 | default=(0.1, -0.1, 0.1),
249 | help='Initial point as string of three floats: "X, Y, Z".',
250 | )
251 | parser.add_argument("--show_plots", action="store_true", help="Show plots of a model. Default: False.")
252 | parser.add_argument("--save_plots", action="store_true", help="Save plots to PNG files. Default: False.")
253 | parser.add_argument("--show_spectrum", action="store_true", help="Show spectrum plots")
254 | parser.add_argument("--show_timeplot", action="store_true", help="Save time plots.")
255 | parser.add_argument("--show_3d_plots", action="store_true", help="Save 3d plots.")
256 | parser.add_argument("--show_all", action="store_true", help="Save all plots.")
257 | parser.add_argument(
258 | "--add_2d_gif", action="store_true", help="Add 2D coordinates to 3D model into GIF. Default: False."
259 | )
260 |
261 | subparsers = parser.add_subparsers(
262 | title="Chaotic models", description="You can select one of the chaotic models:", dest="attractor"
263 | )
264 |
265 | sub_list = []
266 | for attractor in [*self.__model_map]:
267 | chosen_items = DEFAULT_PARAMETERS.get(attractor)
268 | chosen_model = f"{attractor}".capitalize()
269 | subparser = subparsers.add_parser(f"{attractor}", help=f"{chosen_model} chaotic model")
270 | if chosen_items is not None:
271 | group = subparser.add_argument_group(title=f"{chosen_model} model arguments")
272 | for key in chosen_items:
273 | group.add_argument(
274 | f"--{key}",
275 | type=float,
276 | default=chosen_items[key],
277 | action="store",
278 | help=f"{chosen_model} system parameter. Default: {chosen_items[key]}",
279 | )
280 | sub_list.append(subparser)
281 |
282 | if show_help:
283 | parser.print_help()
284 | for item in sub_list:
285 | item.print_help()
286 |
287 | args = vars(parser.parse_args(input_args))
288 | if args["attractor"] is None:
289 | raise AssertionError(f"[FAIL]: Please select a chaotic model from the next set: {[*self.__model_map]}")
290 | if show_args:
291 | print(f"[INFO]: Cmmaind line arguments:")
292 | for arg in args:
293 | print(f"{arg :<14} = {args[arg]}")
294 |
295 | if args["init_point"] is not None and len(args["init_point"]) != 3:
296 | raise AssertionError(f"[FAIL]: Please enter initial points as X, Y, Z list. Example: --init_point 1 2 3")
297 | return args
298 |
299 |
300 | if __name__ == "__main__":
301 | import doctest
302 |
303 | doctest.testmod(verbose=True)
304 | # command_line = "--init_point", '0 -1 2', "lorenz"
305 | # params = Settings(show_logs=True, show_help=True)
306 | # params.update_params(input_args=command_line)
307 |
--------------------------------------------------------------------------------
/src/utils/drawer.py:
--------------------------------------------------------------------------------
1 | """Plot drawer
2 |
3 | Description :
4 | Useful component for plotting results
5 |
6 | ------------------------------------------------------------------------
7 |
8 | GNU GENERAL PUBLIC LICENSE
9 | Version 3, 29 June 2007
10 |
11 | Copyright (c) 2019 Kapitanov Alexander
12 |
13 | This program is free software: you can redistribute it and/or modify
14 | it under the terms of the GNU General Public License as published by
15 | the Free Software Foundation, either version 3 of the License, or
16 | (at your option) any later version.
17 |
18 | You should have received a copy of the GNU General Public License
19 | along with this program. If not, see .
20 |
21 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
22 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
23 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT
24 | WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT
25 | NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
26 | FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND
27 | PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE
28 | DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR
29 | OR CORRECTION.
30 |
31 | ------------------------------------------------------------------------
32 | """
33 |
34 | # Authors : Alexander Kapitanov
35 | # ...
36 | # Contacts :
37 | # ...
38 | # Release Date : 2020/07/25
39 | # License : GNU GENERAL PUBLIC LICENSE
40 |
41 | import matplotlib.animation as animation
42 | import matplotlib.pyplot as plt
43 | import mpl_toolkits.mplot3d.axes3d as p3 # noqa # pylint: disable=unused-import
44 | import numpy as np
45 |
46 |
47 | class PlotDrawer:
48 | """Main class for drawing plots.
49 |
50 | See Also:
51 | -----
52 | Matplotlib: Visualization with Python:
53 | https://matplotlib.org/
54 |
55 | """
56 |
57 | _plot_axis = ((0, 1), (2, 1), (0, 2))
58 | _plot_labels = {0: "X", 1: "Y", 2: "Z"}
59 |
60 | def __init__(
61 | self, save_plots: bool = False, show_plots: bool = False, add_2d_gif: bool = False, model_name: str = None,
62 | ):
63 | self.save_plots = save_plots
64 | self.show_plots = show_plots
65 | self.add_2d_gif = add_2d_gif
66 | self.time_or_dot = False
67 |
68 | self._model_name = model_name
69 | self._coordinates = None
70 | # Internal parameters
71 | self._color_map = None
72 | self._plot_list = None
73 | self._min_max_axis = None
74 | self.coordinates = None
75 |
76 | @property
77 | def model_name(self):
78 | return self._model_name
79 |
80 | @model_name.setter
81 | def model_name(self, value: str):
82 | self._model_name = value
83 |
84 | @staticmethod
85 | def __min_max_axis(coordinates: np.ndarray):
86 | return np.vstack([np.min(coordinates, axis=0), np.max(coordinates, axis=0)]).T
87 |
88 | def plot_kde(self, kde: np.ndarray, pdf: np.ndarray):
89 | """Plot Probability density function"""
90 | _ = plt.figure("Probability density function", figsize=(8, 6), dpi=100)
91 | for ii, axis in enumerate(self._plot_labels.values()):
92 | plt.subplot(3, 3, ii + 1)
93 | plt.title("KDE plots", y=1.0) if ii % 2 == 1 else None
94 | plt.plot(kde[ii], ".")
95 | plt.xlim([0, pdf - 1])
96 | plt.grid()
97 | plt.tight_layout()
98 |
99 | def show_spectrum_and_correlation(self, coordinates: np.ndarray, spectrums: np.ndarray, correlations: np.ndarray):
100 | """Plot 3D coordinates as time series."""
101 | _ = plt.figure("Autocorrelation and Spectrum", figsize=(8, 6), dpi=100)
102 |
103 | x_corr = np.linspace(-len(coordinates) // 2, len(coordinates) // 2, len(coordinates))
104 | x_ffts = np.linspace(-0.5, 0.5, len(spectrums))
105 |
106 | plt.suptitle(f"{self.model_name} attractor", x=0.1)
107 | for ii, axis in enumerate(self._plot_labels.values()):
108 | plt.subplot(3, 3, ii + 1)
109 | plt.title("Time plots", y=1.0) if ii % 2 == 1 else None
110 | plt.plot(coordinates[:, ii], linewidth=0.75)
111 | plt.grid(True)
112 | plt.ylabel(axis)
113 | plt.xlim([0, len(coordinates) - 1])
114 | plt.subplot(3, 3, ii + 4)
115 | plt.title("Spectrum plots", y=1.0) if ii % 2 == 1 else None
116 | plt.plot(x_ffts, spectrums[:, ii], linewidth=0.75)
117 | plt.grid(True)
118 | plt.ylabel(axis)
119 | plt.xlim([np.min(x_ffts), np.max(x_ffts)])
120 | plt.subplot(3, 3, ii + 7)
121 | plt.title("Correlation plots", y=1.0) if ii % 2 == 1 else None
122 | plt.plot(x_corr, correlations[:, ii], linewidth=0.75)
123 | plt.grid(True)
124 | plt.ylabel(axis)
125 | plt.xlim([np.min(x_corr), np.max(x_corr)])
126 | plt.tight_layout()
127 |
128 | if self.save_plots:
129 | plt.savefig(f"{self.model_name}_spectrum_correlations.png")
130 | if self.show_plots:
131 | plt.show()
132 |
133 | def show_time_plots(self, coordinates: np.ndarray):
134 | """Plot 3D coordinates as time series."""
135 | _ = plt.figure("Coordinates evolution in time", figsize=(8, 6), dpi=100)
136 | for ii, axis in enumerate(self._plot_labels.values()):
137 | plt.subplot(3, 1, ii + 1)
138 | plt.plot(coordinates[:, ii], linewidth=0.75)
139 | plt.grid(True)
140 | if axis == "Z":
141 | plt.xlabel("Time (t)")
142 | plt.ylabel(axis)
143 | plt.xlim([0, len(coordinates) - 1])
144 | plt.tight_layout()
145 | if self.save_plots:
146 | plt.savefig(f"{self.model_name}_coordinates_in_time.png")
147 | if self.show_plots:
148 | plt.show()
149 |
150 | def __axis_defaults_3d(self, plots, coordinates: np.ndarray):
151 | min_max = self.__min_max_axis(coordinates)
152 | plots.set_title(f"{self.model_name} model")
153 | plots.set_xlabel("X")
154 | plots.set_ylabel("Y")
155 | plots.set_zlabel("Z")
156 | plots.set_xlim3d(min_max[0])
157 | plots.set_ylim3d(min_max[1])
158 | plots.set_zlim3d(min_max[2])
159 | plots.xaxis.pane.fill = False
160 | plots.yaxis.pane.fill = False
161 | plots.zaxis.pane.fill = False
162 |
163 | def __axis_defaults_2d(self, plots, coordinates: np.ndarray):
164 | min_max = self.__min_max_axis(coordinates)
165 | for idx, (xx, yy) in enumerate(self._plot_axis):
166 | plots[idx].set_xlim(min_max[xx])
167 | plots[idx].set_ylim(min_max[yy])
168 | plots[idx].set_xlabel(self._plot_labels[xx])
169 | plots[idx].set_ylabel(self._plot_labels[yy])
170 | plots[idx].grid(True)
171 | # ax.set_axis_off()
172 | # ax.xaxis.pane.set_edgecolor('w')
173 | # ax.yaxis.pane.set_edgecolor('w')
174 | # ax.zaxis.pane.set_edgecolor('w')
175 | # ax.grid(False)
176 | # ax.tight_layout()
177 |
178 | def show_3d_plots(self, coordinates: np.ndarray):
179 | """Plot 3D coordinates as time series."""
180 | min_max = self.__min_max_axis(coordinates)
181 |
182 | fig = plt.figure(f"3D model of {self.model_name} system", figsize=(8, 6), dpi=100)
183 | for ii, (xx, yy) in enumerate(self._plot_axis):
184 | plt.subplot(2, 2, 1 + ii)
185 | plt.plot(coordinates[:, xx], coordinates[:, yy], linewidth=0.75)
186 | plt.grid()
187 | plt.xlabel(self._plot_labels[xx])
188 | plt.ylabel(self._plot_labels[yy])
189 | plt.xlim(min_max[xx])
190 | plt.ylim(min_max[yy])
191 |
192 | ax = fig.add_subplot(2, 2, 4, projection="3d")
193 | ax.plot(coordinates[:, 0], coordinates[:, 1], coordinates[:, 2], linewidth=0.75)
194 | self.__axis_defaults_3d(ax, coordinates)
195 | plt.tight_layout()
196 |
197 | if self.save_plots:
198 | plt.savefig(f"{self.model_name}_3d_coordinates.png")
199 | if self.show_plots:
200 | plt.show()
201 |
202 | def _add_2d_to_plots(self, figure, coordinates: np.ndarray):
203 | self._plot_list += [figure.add_subplot(2, 2, 1 + ii) for ii in range(3)]
204 | self.__axis_defaults_2d(self._plot_list[1:], coordinates)
205 | plt.tight_layout()
206 |
207 | def make_3d_plot_gif(self, coordinates: np.ndarray, step_size: int = 10):
208 | """Make git for 3D coordinates as time series."""
209 | nodes = 2 if self.add_2d_gif else 1
210 | posit = 4 if self.add_2d_gif else 1
211 | fig = plt.figure(f"3D model of {self.model_name} system", figsize=(8, 6), dpi=100)
212 |
213 | self._plot_list = [fig.add_subplot(nodes, nodes, posit, projection="3d")]
214 | self.__axis_defaults_3d(self._plot_list[0], coordinates)
215 |
216 | if self.add_2d_gif:
217 | self._add_2d_to_plots(fig, coordinates)
218 |
219 | # Convert ax to plot
220 | self._plot_list = [item.plot([], [], ".--", lw=0.75)[0] for item in self._plot_list]
221 |
222 | step_dots = len(coordinates) // step_size
223 | self._color_map = plt.cm.get_cmap("hsv", step_dots)
224 |
225 | self.coordinates = coordinates
226 | ani = animation.FuncAnimation(
227 | fig, self._update_coordinates, step_dots, fargs=(step_size,), interval=100, blit=False, repeat=True
228 | )
229 |
230 | if self.save_plots:
231 | ani.save(f"{self.model_name}_3d.gif", writer="imagemagick")
232 | if self.show_plots:
233 | plt.show()
234 |
235 | def _update_coordinates(self, num, step):
236 | """Update plots for making gif"""
237 | self._plot_list[0].set_data(self.coordinates[0 : 1 + num * step, 0], self.coordinates[0 : 1 + num * step, 1])
238 | self._plot_list[0].set_3d_properties(self.coordinates[0 : 1 + num * step, 2])
239 | self._plot_list[0].set_color(self._color_map(num))
240 | if self.add_2d_gif:
241 | for ii, (x, y) in enumerate(self._plot_axis):
242 | self._plot_list[ii + 1].set_data(
243 | self.coordinates[0 : 1 + num * step, x], self.coordinates[0 : 1 + num * step, y]
244 | )
245 | self._plot_list[ii + 1].set_color(self._color_map(num))
246 |
247 | def show_all_plots(self, coordinates: np.ndarray, spectrums: np.ndarray, correlations: np.ndarray):
248 | """Cannot show all plots while 'show_plots' is True.
249 |
250 | Note: After closing plots you cannot reopen them!
251 | """
252 | show_plots, self.show_plots = self.show_plots, False
253 | self.show_time_plots(coordinates)
254 | self.show_3d_plots(coordinates)
255 | self.show_spectrum_and_correlation(coordinates, spectrums, correlations)
256 | plt.show()
257 | self.show_plots = show_plots
258 |
259 |
260 | def random_circle(num_points: int = 100, sigma: float = 0.01, angle: float = 2.) -> np.ndarray:
261 | r"""Create random circle for 3D plots.
262 |
263 | Parameters
264 | ----------
265 | num_points : int
266 | Number of points to draw
267 |
268 | sigma : int
269 | Random shift
270 |
271 | angle : int
272 | Rotate angle
273 |
274 | Returns
275 | -------
276 |
277 | arr: np.ndarray
278 | Numpy 3D array with shapes [3, num_points]
279 | """
280 |
281 | theta = np.linspace(0, angle * np.pi, num_points)
282 | xyz = np.vstack([np.cos(theta), np.sin(theta), np.sin(np.linspace(0, 2.05 * np.pi, num_points))]).T
283 | xyz += sigma * np.cumsum(np.random.randn(num_points, 3), axis=1)
284 | return xyz
285 |
286 |
287 | if __name__ == "__main__":
288 | np.random.seed(42)
289 | circle_points = random_circle(num_points=400, sigma=0.01)
290 |
291 | drawer = PlotDrawer(show_plots=True, add_2d_gif=True)
292 | drawer.model_name = "Chaotic"
293 |
294 | # print(drawer.min_max_axis)
295 | drawer.make_3d_plot_gif(step_size=10, coordinates=circle_points)
296 | # drawer.show_time_plots()
297 | # drawer.show_3d_plots()
298 | # drawer.show_all_plots()
299 |
--------------------------------------------------------------------------------
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497 | patent against the party.
498 |
499 | If you convey a covered work, knowingly relying on a patent license,
500 | and the Corresponding Source of the work is not available for anyone
501 | to copy, free of charge and under the terms of this License, through a
502 | publicly available network server or other readily accessible means,
503 | then you must either (1) cause the Corresponding Source to be so
504 | available, or (2) arrange to deprive yourself of the benefit of the
505 | patent license for this particular work, or (3) arrange, in a manner
506 | consistent with the requirements of this License, to extend the patent
507 | license to downstream recipients. "Knowingly relying" means you have
508 | actual knowledge that, but for the patent license, your conveying the
509 | covered work in a country, or your recipient's use of the covered work
510 | in a country, would infringe one or more identifiable patents in that
511 | country that you have reason to believe are valid.
512 |
513 | If, pursuant to or in connection with a single transaction or
514 | arrangement, you convey, or propagate by procuring conveyance of, a
515 | covered work, and grant a patent license to some of the parties
516 | receiving the covered work authorizing them to use, propagate, modify
517 | or convey a specific copy of the covered work, then the patent license
518 | you grant is automatically extended to all recipients of the covered
519 | work and works based on it.
520 |
521 | A patent license is "discriminatory" if it does not include within
522 | the scope of its coverage, prohibits the exercise of, or is
523 | conditioned on the non-exercise of one or more of the rights that are
524 | specifically granted under this License. You may not convey a covered
525 | work if you are a party to an arrangement with a third party that is
526 | in the business of distributing software, under which you make payment
527 | to the third party based on the extent of your activity of conveying
528 | the work, and under which the third party grants, to any of the
529 | parties who would receive the covered work from you, a discriminatory
530 | patent license (a) in connection with copies of the covered work
531 | conveyed by you (or copies made from those copies), or (b) primarily
532 | for and in connection with specific products or compilations that
533 | contain the covered work, unless you entered into that arrangement,
534 | or that patent license was granted, prior to 28 March 2007.
535 |
536 | Nothing in this License shall be construed as excluding or limiting
537 | any implied license or other defenses to infringement that may
538 | otherwise be available to you under applicable patent law.
539 |
540 | 12. No Surrender of Others' Freedom.
541 |
542 | If conditions are imposed on you (whether by court order, agreement or
543 | otherwise) that contradict the conditions of this License, they do not
544 | excuse you from the conditions of this License. If you cannot convey a
545 | covered work so as to satisfy simultaneously your obligations under this
546 | License and any other pertinent obligations, then as a consequence you may
547 | not convey it at all. For example, if you agree to terms that obligate you
548 | to collect a royalty for further conveying from those to whom you convey
549 | the Program, the only way you could satisfy both those terms and this
550 | License would be to refrain entirely from conveying the Program.
551 |
552 | 13. Use with the GNU Affero General Public License.
553 |
554 | Notwithstanding any other provision of this License, you have
555 | permission to link or combine any covered work with a work licensed
556 | under version 3 of the GNU Affero General Public License into a single
557 | combined work, and to convey the resulting work. The terms of this
558 | License will continue to apply to the part which is the covered work,
559 | but the special requirements of the GNU Affero General Public License,
560 | section 13, concerning interaction through a network will apply to the
561 | combination as such.
562 |
563 | 14. Revised Versions of this License.
564 |
565 | The Free Software Foundation may publish revised and/or new versions of
566 | the GNU General Public License from time to time. Such new versions will
567 | be similar in spirit to the present version, but may differ in detail to
568 | address new problems or concerns.
569 |
570 | Each version is given a distinguishing version number. If the
571 | Program specifies that a certain numbered version of the GNU General
572 | Public License "or any later version" applies to it, you have the
573 | option of following the terms and conditions either of that numbered
574 | version or of any later version published by the Free Software
575 | Foundation. If the Program does not specify a version number of the
576 | GNU General Public License, you may choose any version ever published
577 | by the Free Software Foundation.
578 |
579 | If the Program specifies that a proxy can decide which future
580 | versions of the GNU General Public License can be used, that proxy's
581 | public statement of acceptance of a version permanently authorizes you
582 | to choose that version for the Program.
583 |
584 | Later license versions may give you additional or different
585 | permissions. However, no additional obligations are imposed on any
586 | author or copyright holder as a result of your choosing to follow a
587 | later version.
588 |
589 | 15. Disclaimer of Warranty.
590 |
591 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
592 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
593 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
594 | OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
595 | THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
596 | PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
597 | IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
598 | ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
599 |
600 | 16. Limitation of Liability.
601 |
602 | IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
603 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
604 | THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
605 | GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
606 | USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
607 | DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
608 | PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
609 | EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
610 | SUCH DAMAGES.
611 |
612 | 17. Interpretation of Sections 15 and 16.
613 |
614 | If the disclaimer of warranty and limitation of liability provided
615 | above cannot be given local legal effect according to their terms,
616 | reviewing courts shall apply local law that most closely approximates
617 | an absolute waiver of all civil liability in connection with the
618 | Program, unless a warranty or assumption of liability accompanies a
619 | copy of the Program in return for a fee.
620 |
621 | END OF TERMS AND CONDITIONS
622 |
623 | How to Apply These Terms to Your New Programs
624 |
625 | If you develop a new program, and you want it to be of the greatest
626 | possible use to the public, the best way to achieve this is to make it
627 | free software which everyone can redistribute and change under these terms.
628 |
629 | To do so, attach the following notices to the program. It is safest
630 | to attach them to the start of each source file to most effectively
631 | state the exclusion of warranty; and each file should have at least
632 | the "copyright" line and a pointer to where the full notice is found.
633 |
634 |
635 | Copyright (C)
636 |
637 | This program is free software: you can redistribute it and/or modify
638 | it under the terms of the GNU General Public License as published by
639 | the Free Software Foundation, either version 3 of the License, or
640 | (at your option) any later version.
641 |
642 | This program is distributed in the hope that it will be useful,
643 | but WITHOUT ANY WARRANTY; without even the implied warranty of
644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
645 | GNU General Public License for more details.
646 |
647 | You should have received a copy of the GNU General Public License
648 | along with this program. If not, see .
649 |
650 | Also add information on how to contact you by electronic and paper mail.
651 |
652 | If the program does terminal interaction, make it output a short
653 | notice like this when it starts in an interactive mode:
654 |
655 | Copyright (C)
656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
657 | This is free software, and you are welcome to redistribute it
658 | under certain conditions; type `show c' for details.
659 |
660 | The hypothetical commands `show w' and `show c' should show the appropriate
661 | parts of the General Public License. Of course, your program's commands
662 | might be different; for a GUI interface, you would use an "about box".
663 |
664 | You should also get your employer (if you work as a programmer) or school,
665 | if any, to sign a "copyright disclaimer" for the program, if necessary.
666 | For more information on this, and how to apply and follow the GNU GPL, see
667 | .
668 |
669 | The GNU General Public License does not permit incorporating your program
670 | into proprietary programs. If your program is a subroutine library, you
671 | may consider it more useful to permit linking proprietary applications with
672 | the library. If this is what you want to do, use the GNU Lesser General
673 | Public License instead of this License. But first, please read
674 | .
675 |
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