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EntropyHub-0.2


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توضیحات

An open-source toolkit for entropic time series analysis.
ویژگی مقدار
سیستم عامل -
نام فایل EntropyHub-0.2
نام EntropyHub
نسخه کتابخانه 0.2
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Matthew W. Flood
ایمیل نویسنده info@entropyhub.xyz, help@entropyhub.xyz
آدرس صفحه اصلی https://www.EntropyHub.xyz
آدرس اینترنتی https://pypi.org/project/EntropyHub/
مجوز Apache 2.0
# EntropyHub: An open-source toolkit for entropic time series analysis __*Python Edition*__ ___ _ _ _____ _____ ____ ____ _ _ | _|| \ | ||_ _|| \| || || \ / | ___________ | \_ | \| | | | | __/| || __| \ \_/ / / _______ \ | _|| \ \ | | | | \ | || | \ / | / ___ \ | | \_ | |\ | | | | |\ \ | || | | | | | / \ | | |___||_| \_| |_| |_| \_||____||_| |_| _|_|__\___/ | | _ _ _ _ ____ / |__\______\/ | | | | || | | || \ An open-source | /\______\__|_/ | |_| || | | || | toolkit for | | / \ | | | _ || | | || \ entropic time- | | \___/ | | | | | || |_| || \ series analysis | \_______/ | |_| |_|\_____/|_____/ \___________/ ## About Information and uncertainty can be regarded as two sides of the same coin: the more uncertainty there is, the more information we gain by removing that uncertainty. In the context of information and probability theory, ***Entropy*** quantifies that uncertainty. The concept of entropy has its origins in [classical physics](http://www.scholarpedia.org/article/Entropy "Scholarpedia") under the second law of thermodynamics, a law [considered to underpin our fundamental understanding](https://www.penguin.co.uk/books/301539/the-order-of-time/9780141984964.html "Rovelli") of [time in physics](https://en.wikipedia.org/wiki/Time_in_physics "Wiki Time"). Attempting to analyse the analog world around us requires that we measure time in discrete steps, but doing so compromises our ability to measure entropy accurately. Various measures have been derived to estimate entropy (uncertainty) from discrete time series, each seeking to best capture the uncertainty of the system under examination. This has resulted in many entropy statistics from approximate entropy and sample entropy, to multiscale sample entropy and refined-composite multiscale cross-sample entropy. As the number of statisitcal entropy measures grows, it becomes more difficult to identify, contrast and compare the performance of each measure. To overcome this, we have developed EntropyHub - an open-source toolkit designed to integrate the many established entropy methods into one package. The goal of EntropyHub is to provide a comprehensive set of functions with a simple and consistent syntax that allows the user to augment parameters at the command line, enabling a range from basic to advanced entropy methods to be implemented with ease. ***It is important to clarify that the entropy functions herein described estimate entropy in the context of probability theory and information theory as defined by Shannon, and not thermodynamic or other entropies from classical physics.*** ## Installation There are two ways to install EntropyHub for Python. Method 1 is strongly recommended. #### Method 1: 1. Using `pip` in your python IDE, type: `pip install EntropyHub` #### Method 2: 1. Download the folder above (EntropyHub.*x.x.x*.tar.gz) and unzip it. 2. Open a command terminal (__*cmd*__ on Windows, __*terminal*__ on Mac) or __use the Anaconda prompt if you use Anaconda as your python package distribution__. 3. In the command prompt/terminal, navigate to the directory where you saved and extracted the .tar.gz folder. 4. Enter the following in the command line: `python setup.py install` ### System Requirements & Dependencies There are several package dependencies which will be installed alongside EntropyHub: Numpy, Scipy, Matplotlib, PyEMD EntropyHub was designed using Python 3 and thus is not intended for use with Python 2. Python versions > 3.6 are required for using EntropyHub. ## Documentation & Help A key advantage of EntropyHub is the comprehensive documentation available to help users to make the most of the toolkit. One can simply access the docstrings of a function (like any Python function) by typing `help FunctionName` in the command line, which will print the docstrings. All information on the EntropyHub package is detailed in the *EntropyHub Guide*, a .pdf document available [here](https://github.com/MattWillFlood/EntropyHub/blob/main/EntropyHub%20Guide.pdf). ## Functions EntropyHub functions fall into 5 categories: * Base functions for estimating the entropy of a single univariate time series. * Cross functions for estimating the entropy between two univariate time series. * Bidimensional functions for estimating the entropy of a two-dimensional univariate matrix. * Multiscale functions for estimating the multiscale entropy of a single univariate time series using any of the Base entropy functions. * Multiscale Cross functions for estimating the multiscale entropy between two univariate time series using any of the Cross-entropy functions. #### The following tables outline the functions available in the EntropyHub package. *When new entropies are published in the scientific literature, efforts will be made to incorporate them in future releases.* ### Base Entropies: Entropy Type | Function Name ---|--- Approximate Entropy | ApEn Sample Entropy | SampEn Fuzzy Entropy | FuzzEn Kolmogorov Entropy | K2En Permutation Entropy | PermEn Conditional Entropy | CondEn Distribution Entropy | DistEn Spectral Entropy | SpecEn Dispersion Entropy | DispEn Symbolic Dynamic Entropy | SyDyEn Increment Entropy | IncrEn Cosine Similarity Entropy | CoSiEn Phase Entropy | PhasEn Slope Entropy | SlopEn Bubble Entropy | BubbEn Gridded Distribution Entropy | GridEn Entropy of Entropy | EnofEn Attention Entropy | AttnEn _______________________________________________________________________ ### Cross Entropies: Entropy Type | Function Name ---|--- Cross Sample Entropy | XSampEn Cross Approximate Entropy | XApEn Cross Fuzzy Entropy | XFuzzEn Cross Permutation Entropy | XPermEn Cross Conditional Entropy | XCondEn Cross Distribution Entropy | XDistEn Cross Spectral Entropy | XSpecEn Cross Kolmogorov Entropy | XK2En _______________________________________________________________________ ### Bidimensional Entropies Entropy Type | Function Name ---|--- Bidimensional Sample Entropy | SampEn2D Bidimensional Fuzzy Entropy | FuzzEn2D Bidimensional Distribution Entropy | DistEn2D Bidimensional Dispersion Entropy | DispEn2D Bidimensional Permutation Entropy | PermEn2D Bidimensional Espinosa Entropy | EspEn2D _________________________________________________________________________ ### Multiscale Entropy Functions Entropy Type | Function Name ---|--- Multiscale Entropy | MSEn Composite/Refined-Composite Multiscale Entropy | cMSEn Refined Multiscale Entropy | rMSEn Hierarchical Multiscale Entropy | hMSEn _________________________________________________________________________ ### Multiscale Cross-Entropy Functions Entropy Type | Function Name ---|--- Multiscale Cross-Entropy | XMSEn Composite/Refined-Composite Multiscale Cross-Entropy | cXMSEn Refined Multiscale Cross-Entropy | rXMSEn Hierarchical Multiscale Cross-Entropy | hXMSEn ## License and Terms of Use EntropyHub is licensed under the Apache License (Version 2.0) and is free to use by all on condition that the following reference be included on any outputs realized using the software: Matthew W. Flood and Bernd Grimm (2021), EntropyHub: An Open-Source Toolkit for Entropic Time Series Analysis, PLoS ONE 16(11):e0259448 DOI: 10.1371/journal.pone.0259448 www.EntropyHub.xyz __________________________________________________________________ © Copyright 2021 Matthew W. Flood, EntropyHub Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. For Terms of Use see https://www.EntropyHub.xyz ## Contact If you find this package useful, please consider starring it on GitHub, MatLab File Exchange, PyPI or Julia Packages as this helps us to gauge user satisfaction. For general queries and information about EntropyHub, contact: info@entropyhub.xyz If you have any questions or need help using the package, please contact us at: help@entropyhub.xyz If you notice or identify any issues, please do not hesitate to contact us at: fix@entropyhub.xyz __Thank you__ for using EntropyHub. Yours in research, Matt


نیازمندی

مقدار نام
- numpy
- matplotlib
- scipy
- EMD-signal
- requests


زبان مورد نیاز

مقدار نام
>=3.6, <4 Python


نحوه نصب


نصب پکیج whl EntropyHub-0.2:

    pip install EntropyHub-0.2.whl


نصب پکیج tar.gz EntropyHub-0.2:

    pip install EntropyHub-0.2.tar.gz