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EntropyHub-0.2
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مشاهده بیشترتوضیحات
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