pyitlib | theoretic methods for data analysis | Machine Learning library
kandi X-RAY | pyitlib Summary
kandi X-RAY | pyitlib Summary
pyitlib is a Python library typically used in Artificial Intelligence, Machine Learning, Numpy applications. pyitlib has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install pyitlib' or download it from GitHub, PyPI.
A library of information-theoretic methods for data analysis and machine learning, implemented in Python and NumPy.
A library of information-theoretic methods for data analysis and machine learning, implemented in Python and NumPy.
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pyitlib has a low active ecosystem.
It has 78 star(s) with 16 fork(s). There are 4 watchers for this library.
It had no major release in the last 12 months.
There are 7 open issues and 4 have been closed. On average issues are closed in 148 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of pyitlib is 0.2.3
Quality
pyitlib has 0 bugs and 384 code smells.
Security
pyitlib has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
pyitlib code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
pyitlib is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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pyitlib releases are not available. You will need to build from source code and install.
Deployable package is available in PyPI.
Build file is available. You can build the component from source.
pyitlib saves you 1719 person hours of effort in developing the same functionality from scratch.
It has 3807 lines of code, 73 functions and 8 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed pyitlib and discovered the below as its top functions. This is intended to give you an instant insight into pyitlib implemented functionality, and help decide if they suit your requirements.
- Calculate the Information Multivariate Normalised Information Criterion
- Helper function for cartesian product
- Automatically generate the alphabet for each column
- Check if X is NaN
- Calculate the Information Coefficient
- Increment a binary vector
- Estimate the information interaction interaction
- Kullback - Leibler divergence
- Computes the entropy cross product of the input data
- Computes the divergence of the KL - bundled divergence
- Append empty bins using given alphabet
- Compute the information variance
- Residual entropy residual
- Construct an Information Binding
- Computes the information for the given set of information
- Compute the information of the information
- Calculate the weights for a given estimator
- R Derivative divergence of the divergence of a symmetrised PMF
- Computes the divergence of the divergence function
- Reads the python version
Get all kandi verified functions for this library.
pyitlib Key Features
No Key Features are available at this moment for pyitlib.
pyitlib Examples and Code Snippets
No Code Snippets are available at this moment for pyitlib.
Community Discussions
Trending Discussions on pyitlib
QUESTION
How to perform on global dataframe in the target function of multiprocessing in python?
Asked 2020-Dec-15 at 16:59
I have the following code. I want to calculate values of all pairs using calculate_mi function on global dataframe df with python multiprocess.
...ANSWER
Answered 2020-Dec-15 at 16:59First, a couple of things:
- It should be:
from multiprocessing import Pool(notfrom multiprocess) - It appears you have left out the import of the
pandaslibrary.
Moving on ...
The problem is that under Windows the creation of new processes is not done using a fork call and consequently the sub-processes do not automatically inherit global variables such as df. Therefore, you must initialize each sub-process to have global variable df properly initialized by using an initializer when you create the Pool:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install pyitlib
You can install using 'pip install pyitlib' or download it from GitHub, PyPI.
You can use pyitlib like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use pyitlib like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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