Chaotic datasets on pyFTS.data: logistic_map, mackey_glass, henon, lorentz and rossler
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# Sphinx build info version 1
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# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
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config: 23a83af8fc84956f406e435cfed523f9
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tags: 645f666f9bcd5a90fca523b33c5a78b7
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# Minimal makefile for Sphinx documentation
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#
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# You can set these variables from the command line.
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SPHINXOPTS =
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SPHINXBUILD = sphinx-build
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SPHINXPROJ = pyFTS
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SOURCEDIR = source
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BUILDDIR = build
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# Put it first so that "make" without argument is like "make help".
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help:
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@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
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.PHONY: help Makefile
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# Catch-all target: route all unknown targets to Sphinx using the new
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# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
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%: Makefile
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@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
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@ECHO OFF
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pushd %~dp0
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REM Command file for Sphinx documentation
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if "%SPHINXBUILD%" == "" (
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set SPHINXBUILD=sphinx-build
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)
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set SOURCEDIR=source
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set BUILDDIR=build
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set SPHINXPROJ=pyFTS
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if "%1" == "" goto help
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%SPHINXBUILD% >NUL 2>NUL
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if errorlevel 9009 (
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echo.
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echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
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echo.installed, then set the SPHINXBUILD environment variable to point
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echo.to the full path of the 'sphinx-build' executable. Alternatively you
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echo.may add the Sphinx directory to PATH.
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echo.
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exit /b 1
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)
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goto end
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:help
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%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS%
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:end
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popd
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pyFTS/.directory
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pyFTS/.directory
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[Dolphin]
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Timestamp=2018,2,27,12,11,58
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Version=4
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ViewMode=1
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pyFTS/conf.py
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pyFTS/conf.py
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# -*- coding: utf-8 -*-
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#
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# Configuration file for the Sphinx documentation builder.
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#
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# This file does only contain a selection of the most common options. For a
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# full list see the documentation:
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# http://www.sphinx-doc.org/en/stable/config
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# -- Path setup --------------------------------------------------------------
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# If extensions (or modules to document with autodoc) are in another directory,
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# add these directories to sys.path here. If the directory is relative to the
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# documentation root, use os.path.abspath to make it absolute, like shown here.
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#
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# import os
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# import sys
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# sys.path.insert(0, os.path.abspath('.'))
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# -- Project information -----------------------------------------------------
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project = 'pyFTS'
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copyright = '2018, Petrônio Cândido de Lima e Silva'
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author = 'Petrônio Cândido de Lima e Silva'
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# The short X.Y version
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version = ''
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# The full version, including alpha/beta/rc tags
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release = '1.2.2'
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# -- General configuration ---------------------------------------------------
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# If your documentation needs a minimal Sphinx version, state it here.
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#
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# needs_sphinx = '1.0'
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# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
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# ones.
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extensions = [
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'sphinx.ext.autodoc',
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'sphinx.ext.intersphinx',
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'sphinx.ext.todo',
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# The master toctree document.
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master_doc = 'index'
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# This is also used if you do content translation via gettext catalogs.
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language = None
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# directories to ignore when looking for source files.
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exclude_patterns = []
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pygments_style = 'sphinx'
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html_theme = 'alabaster'
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# further. For a list of options available for each theme, see the
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#
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# html_theme_options = {}
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# relative to this directory. They are copied after the builtin static files,
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# so a file named "default.css" will overwrite the builtin "default.css".
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html_static_path = ['.static']
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# to template names.
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# The default sidebars (for documents that don't match any pattern) are
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# default: ``['localtoc.html', 'relations.html', 'sourcelink.html',
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# 'searchbox.html']``.
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#
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# html_sidebars = {}
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# -- Options for HTMLHelp output ---------------------------------------------
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# Output file base name for HTML help builder.
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htmlhelp_basename = 'pyFTSdoc'
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# -- Options for LaTeX output ------------------------------------------------
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latex_elements = {
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#
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# 'papersize': 'letterpaper',
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# author, documentclass [howto, manual, or own class]).
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latex_documents = [
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(master_doc, 'pyFTS.tex', 'pyFTS Documentation',
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'Petrônio Cândido de Lima e Silva', 'manual'),
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# -- Options for manual page output ------------------------------------------
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# One entry per manual page. List of tuples
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man_pages = [
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(master_doc, 'pyfts', 'pyFTS Documentation',
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[author], 1)
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# (source start file, target name, title, author,
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# dir menu entry, description, category)
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texinfo_documents = [
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(master_doc, 'pyFTS', 'pyFTS Documentation',
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author, 'pyFTS', 'One line description of project.',
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'Miscellaneous'),
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]
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# -- Extension configuration -------------------------------------------------
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# -- Options for intersphinx extension ---------------------------------------
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# Example configuration for intersphinx: refer to the Python standard library.
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intersphinx_mapping = {'https://docs.python.org/': None}
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# If true, `todo` and `todoList` produce output, else they produce nothing.
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todo_include_todos = True
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[Dolphin]
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SortOrder=1
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Timestamp=2018,3,2,14,0,24
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Version=4
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pyFTS/data/henon.py
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import numpy as np
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import pandas as pd
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def get_data(var, a=1.4, b=0.3, initial_values = [1, 1], iterations=1000):
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return get_dataframe(a,b, initial_values, iterations)[var].values
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def get_dataframe(a=1.4, b=0.3, initial_values = [1, 1], iterations=1000):
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'''
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M. Hénon. "A two-dimensional mapping with a strange attractor". Commun. Math. Phys. 50, 69-77 (1976)
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dx/dt = a + by(t-1) - x(t-1)^2
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dy/dt = x
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:param a: Equation coefficient
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:param b: Equation coefficient
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:param initial_values: numpy array with the initial values of x and y. Default: [1, 1]
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:param iterations: number of iterations. Default: 1000
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:return: Panda dataframe with the x and y values
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'''
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x = [initial_values[0]]
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y = [initial_values[1]]
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for t in np.arange(0, iterations):
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xx = a + b * y[t] - x[t] ** 2
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y.append(x[t])
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x.append(xx)
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return pd.DataFrame({'x': x, 'y':y})
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pyFTS/data/logistic_map.py
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#
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import numpy as np
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def get_data(r = 4, initial_value = 0.3, iterations=100):
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'''
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May, Robert M. (1976). "Simple mathematical models with very complicated dynamics".
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Nature. 261 (5560): 459–467. doi:10.1038/261459a0.
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x(t) = r * x(t-1) * (1 - x(t -1) )
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:param r: Equation coefficient
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:param initial_value: Initial value of x. Default: 0.3
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:param iterations: number of iterations. Default: 100
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:return:
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'''
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x = [initial_value]
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for t in np.arange(0,iterations):
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x.append(r * x[t]*(1 - x[t]))
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return x
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pyFTS/data/lorentz.py
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pyFTS/data/lorentz.py
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import numpy as np
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import pandas as pd
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def get_data(var, a = 10.0, b = 28.0, c = 8.0 / 3.0, dt = 0.01,
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initial_values = [0.1, 0, 0], iterations=1000):
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return get_dataframe(a, b, c, dt, initial_values, iterations)[var].values
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def get_dataframe(a = 10.0, b = 28.0, c = 8.0 / 3.0, dt = 0.01,
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initial_values = [0.1, 0, 0], iterations=1000):
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'''
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Lorenz, Edward Norton (1963). "Deterministic nonperiodic flow". Journal of the Atmospheric Sciences. 20 (2): 130–141.
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https://doi.org/10.1175/1520-0469(1963)020<0130:DNF>2.0.CO;2
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dx/dt = a(y -x)
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dy/dt = x(b - z) - y
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dz/dt = xy - cz
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:param a: Equation coefficient. Default value: 10
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:param b: Equation coefficient. Default value: 28
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:param c: Equation coefficient. Default value: 8.0/3.0
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:param dt: Time differential for continuous time integration. Default value: 0.01
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:param initial_values: numpy array with the initial values of x,y and z. Default: [0.1, 0, 0]
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:param iterations: number of iterations. Default: 1000
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:return: Panda dataframe with the x, y and z values
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'''
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x = [initial_values[0]]
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y = [initial_values[1]]
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z = [initial_values[2]]
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for t in np.arange(0, iterations):
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dxdt = a * (y[t] - x[t])
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dydt = x[t] * (b - z[t]) - y[t]
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dzdt = x[t] * y[t] - c * z[t]
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x.append(x[t] + dt * dxdt)
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y.append(y[t] + dt * dydt)
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z.append(z[t] + dt * dzdt)
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return pd.DataFrame({'x': x, 'y':y, 'z': z})
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pyFTS/data/mackey_glass.py
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import numpy as np
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def get_data(b=0.1, c=0.2, tau=17, initial_values = np.linspace(0.5,1.5,18), iterations=1000):
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'''
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Mackey, M. C. and Glass, L. (1977). Oscillation and chaos in physiological control systems.
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Science, 197(4300):287-289.
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dy/dt = -by(t)+ cy(t - tau) / 1+y(t-tau)^10
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:param b: Equation coefficient
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:param c: Equation coefficient
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:param tau: Lag parameter, default: 17
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:param initial_values: numpy array with the initial values of y. Default: np.linspace(0.5,1.5,18)
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:param iterations: number of iterations. Default: 1000
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:return:
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'''
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y = initial_values.tolist()
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for n in np.arange(len(y), iterations+100):
|
||||||
|
y.append(y[n] - b * y[n] + c * y[n - tau] / (1 + y[n - tau] ** 10))
|
||||||
|
|
||||||
|
return y[100:]
|
40
pyFTS/data/rossler.py
Normal file
40
pyFTS/data/rossler.py
Normal file
@ -0,0 +1,40 @@
|
|||||||
|
import numpy as np
|
||||||
|
import pandas as pd
|
||||||
|
|
||||||
|
|
||||||
|
def get_data(var, a = 0.2, b = 0.2, c = 5.7, dt = 0.01,
|
||||||
|
initial_values = [0.001, 0.001, 0.001], iterations=5000):
|
||||||
|
return get_dataframe(a, b, c, dt, initial_values, iterations)[var].values
|
||||||
|
|
||||||
|
|
||||||
|
def get_dataframe(a = 0.2, b = 0.2, c = 5.7, dt = 0.01,
|
||||||
|
initial_values = [0.001, 0.001, 0.001], iterations=5000):
|
||||||
|
'''
|
||||||
|
O. E. Rössler, Phys. Lett. 57A, 397 (1976).
|
||||||
|
|
||||||
|
dx/dt = -z - y
|
||||||
|
dy/dt = x + ay
|
||||||
|
dz/dt = b + z( x - c )
|
||||||
|
|
||||||
|
:param a: Equation coefficient. Default value: 0.2
|
||||||
|
:param b: Equation coefficient. Default value: 0.2
|
||||||
|
:param c: Equation coefficient. Default value: 5.7
|
||||||
|
:param dt: Time differential for continuous time integration. Default value: 0.01
|
||||||
|
:param initial_values: numpy array with the initial values of x,y and z. Default: [0.001, 0.001, 0.001]
|
||||||
|
:param iterations: number of iterations. Default: 5000
|
||||||
|
:return: Panda dataframe with the x, y and z values
|
||||||
|
'''
|
||||||
|
|
||||||
|
x = [initial_values[0]]
|
||||||
|
y = [initial_values[1]]
|
||||||
|
z = [initial_values[2]]
|
||||||
|
|
||||||
|
for t in np.arange(0, iterations):
|
||||||
|
dxdt = - (y[t] + z[t])
|
||||||
|
dydt = x[t] + a * y[t]
|
||||||
|
dzdt = b + z[t] * x[t] - z[t] * c
|
||||||
|
x.append(x[t] + dt * dxdt)
|
||||||
|
y.append(y[t] + dt * dydt)
|
||||||
|
z.append(z[t] + dt * dzdt)
|
||||||
|
|
||||||
|
return pd.DataFrame({'x': x, 'y':y, 'z': z})
|
20
pyFTS/index.rst
Normal file
20
pyFTS/index.rst
Normal file
@ -0,0 +1,20 @@
|
|||||||
|
.. pyFTS documentation master file, created by
|
||||||
|
sphinx-quickstart on Thu Apr 12 17:13:04 2018.
|
||||||
|
You can adapt this file completely to your liking, but it should at least
|
||||||
|
contain the root `toctree` directive.
|
||||||
|
|
||||||
|
Welcome to pyFTS's documentation!
|
||||||
|
=================================
|
||||||
|
|
||||||
|
.. toctree::
|
||||||
|
:maxdepth: 2
|
||||||
|
:caption: Contents:
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
Indices and tables
|
||||||
|
==================
|
||||||
|
|
||||||
|
* :ref:`genindex`
|
||||||
|
* :ref:`modindex`
|
||||||
|
* :ref:`search`
|
@ -53,6 +53,7 @@ partitions = {'CMIV': {'BoxCox(0)': 36, 'Differential(1)': 11, 'None': 8},
|
|||||||
|
|
||||||
|
|
||||||
tag = 'benchmarks'
|
tag = 'benchmarks'
|
||||||
|
|
||||||
'''
|
'''
|
||||||
for ds in datasets.keys():
|
for ds in datasets.keys():
|
||||||
dataset = datasets[ds]
|
dataset = datasets[ds]
|
||||||
@ -62,11 +63,11 @@ for ds in datasets.keys():
|
|||||||
|
|
||||||
partitioning = partitions[ds][tf]
|
partitioning = partitions[ds][tf]
|
||||||
|
|
||||||
bchmk.sliding_window_benchmarks(dataset, 2000, train=0.2, inc=0.2,
|
bchmk.sliding_window_benchmarks(dataset, 3000, train=0.1, inc=0.1,
|
||||||
methods=[
|
#methods=[
|
||||||
hwang.HighOrderFTS,
|
# hwang.HighOrderFTS,
|
||||||
hofts.HighOrderFTS,
|
# hofts.HighOrderFTS,
|
||||||
pwfts.ProbabilisticWeightedFTS],
|
# pwfts.ProbabilisticWeightedFTS],
|
||||||
#orders = [3],
|
#orders = [3],
|
||||||
benchmark_models=False,
|
benchmark_models=False,
|
||||||
transformations=[transformation],
|
transformations=[transformation],
|
||||||
@ -86,7 +87,9 @@ for ds in datasets.keys():
|
|||||||
train = dataset[:train_split]
|
train = dataset[:train_split]
|
||||||
test = dataset[train_split:test_split]
|
test = dataset[train_split:test_split]
|
||||||
|
|
||||||
fs = nspart.simplenonstationary_gridpartitioner_builder(data=train, npart=partitions[ds][tf], transformation=transformation)
|
fs = nspart.simplenonstationary_gridpartitioner_builder(data=train,
|
||||||
|
npart=partitions[ds][tf],
|
||||||
|
transformation=transformation)
|
||||||
print(fs)
|
print(fs)
|
||||||
#cvfts1 = cvfts.ConditionalVarianceFTS(partitioner=fs)
|
#cvfts1 = cvfts.ConditionalVarianceFTS(partitioner=fs)
|
||||||
model = nsfts.NonStationaryFTS(partitioner=fs)
|
model = nsfts.NonStationaryFTS(partitioner=fs)
|
||||||
@ -94,9 +97,9 @@ for ds in datasets.keys():
|
|||||||
print(model)
|
print(model)
|
||||||
|
|
||||||
forecasts = model.predict(test)
|
forecasts = model.predict(test)
|
||||||
'''
|
|
||||||
#print(forecasts)
|
#print(forecasts)
|
||||||
|
'''
|
||||||
partitioning = partitions[ds][tf]
|
partitioning = partitions[ds][tf]
|
||||||
|
|
||||||
bchmk.sliding_window_benchmarks(dataset, 2000, train=0.2, inc=0.2,
|
bchmk.sliding_window_benchmarks(dataset, 2000, train=0.2, inc=0.2,
|
||||||
|
Loading…
Reference in New Issue
Block a user