pygp | A Gaussian process toolbox in python

by PMBio Python Version: 1.1.10 License: GPL-2.0

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

kandi X-RAY | pygp Summary

pygp is a Python library. pygp has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. However pygp has 6 bugs. You can install using 'pip install pygp' or download it from GitHub, PyPI.

Gaussian process toolbox for python. For documentation see the doctree generated by Sphinx. Currently licensed under GPLV2, see LICENSE.txt. Authors: Oliver Stegle, Nicolo Fusi, Max Zwiessele Email: oliver.stegle@gmail.com.

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Quality

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pygp has a low active ecosystem.

It has 38 star(s) with 8 fork(s). There are 5 watchers for this library.

It had no major release in the last 12 months.

pygp has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of pygp is 1.1.10

Quality

pygp has 6 bugs (0 blocker, 0 critical, 5 major, 1 minor) and 535 code smells.

Security

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

pygp code analysis shows 0 unresolved vulnerabilities.

There are 9 security hotspots that need review.

License

pygp is licensed under the GPL-2.0 License. This license is Strong Copyleft.

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

Reuse

pygp 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.

pygp saves you 1613 person hours of effort in developing the same functionality from scratch.

It has 3584 lines of code, 323 functions and 51 files.

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

Top functions reviewed by kandi - BETA

kandi has reviewed pygp and discovered the below as its top functions. This is intended to give you an instant insight into pygp implemented functionality, and help decide if they suit your requirements.

Run toy - data
Predictive Gaussian distribution
Creates toy data
Compute the covariance matrix
Updates the ephemeral polynomials at a given covariance matrix
Compute the model parameters
Compute the covariance matrix
R Calculate the covariance matrix
Logarithm of Gamma
Calculate lnng
Calculate the derivative of the covariance matrix
Predict the Gaussian distribution
Gradient of the gradient of the covariance function
Plot prior
Compute the diagonal of the diagonal matrix
Calculate the gradient of the covariance function
Diagonalization function
Gradient of the kernel function
Calculate the gradient of the gradient of the gradients
Set the logarithm
Calculate the covariance matrix
Gradient of kernel gradients
Calculates the expected expectations
Calculate the expected expectations
Calculate the expectations for the mixture of covariance
R Calculate the gradient of the gradients of the gradients

Get all kandi verified functions for this library.

pygp Key Features

No Key Features are available at this moment for pygp.

pygp Examples and Code Snippets

No Code Snippets are available at this moment for pygp.

Community Discussions

Trending Discussions on pygp

Wrapping C++ class in Python with SWIG

QUESTION

Wrapping C++ class in Python with SWIG

Asked 2017-May-14 at 21:23

I have the following C++ class that I wish to wrap in Python with SWIG.

...

ANSWER

Answered 2017-May-14 at 12:41

If look into the examples in the numpy.i header, you will see examples of how to apply the NumPy typemaps.

In your case, you should change

Source https://stackoverflow.com/questions/43954870

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

Vulnerabilities

No vulnerabilities reported

Install pygp

You can install using 'pip install pygp' or download it from GitHub, PyPI.
You can use pygp 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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