pypolyagamma | Fast C code for sampling Polya | Machine Learning library

by slinderman C++ Version: 1.2.3 License: GPL-3.0

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | pypolyagamma Summary

pypolyagamma is a C++ library typically used in Artificial Intelligence, Machine Learning, Bitcoin, Deep Learning, Unity, Numpy applications. pypolyagamma has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.

Support

Quality

Security

License

Reuse

Support

pypolyagamma has a low active ecosystem.

It has 74 star(s) with 22 fork(s). There are 8 watchers for this library.

It had no major release in the last 12 months.

There are 3 open issues and 33 have been closed. On average issues are closed in 148 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of pypolyagamma is 1.2.3

Quality

pypolyagamma has 0 bugs and 0 code smells.

Security

pypolyagamma has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

pypolyagamma code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pypolyagamma is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

pypolyagamma releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

It has 1386 lines of code, 97 functions and 11 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

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pypolyagamma Key Features

No Key Features are available at this moment for pypolyagamma.

pypolyagamma Examples and Code Snippets

Demo

C++

Lines of Code : 42

License : Strong Copyleft (GPL-3.0)

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from pypolyagamma import BernoulliRegression
D_out = 1     # Output dimension
D_in = 2      # Input dimension
reg = BernoulliRegression(D_out, D_in)

# Given X, an NxD_in array of real-valued inputs,
# and Y, and NxD_out array of binary observations.

Manual Installation,Parallel sampling with OpenMP

C++

Lines of Code : 13

License : Strong Copyleft (GPL-3.0)

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USE_OPENMP=True pip install -e .

n = 10             # Number of variates to sample
b = np.ones(n)     # Vector of shape parameters
c = np.zeros(n)    # Vector of tilting parameters
out = np.empty(n)  # Outputs

# Construct a set of PolyaGamma object

Manual Installation

C++

Lines of Code : 6

License : Strong Copyleft (GPL-3.0)

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pip install cython    
git clone git@github.com:slinderman/pypolyagamma.git
cd pypolyagamma
pip install -e .

pip install nose
nosetests

Community Discussions

Trending Discussions on pypolyagamma

Pickle module that imports code with C bindings

QUESTION

Pickle module that imports code with C bindings

Asked 2020-Mar-23 at 18:41

I have a class I want to pickle using this function:

...

ANSWER

Answered 2020-Mar-23 at 18:41

Unfortunately it looks like that pypolyagamma library you use doesn't currently support pickling/unpickling those objects, so in a word: you can't pickle them without modifying the library.

Furthermore, since it wraps a C++ class, the pickler/unpickler isn't trivial; it'd need to know what state from that wrapped class is necessary for the object to be in the same state after unpickling.

Source https://stackoverflow.com/questions/60819096

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install pypolyagamma

You can also install from source, but you'll need cython.

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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