numba-stats | Numba-accelerated statistical functions | Analytics library

by HDembinski Jupyter Notebook Version: v1.1.1 License: MIT

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

kandi X-RAY | numba-stats Summary

numba-stats is a Jupyter Notebook library typically used in Analytics, Numpy, Pandas applications. numba-stats has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Numba-accelerated statistical functions

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Quality

Security

License

Reuse

Support

numba-stats has a low active ecosystem.

It has 29 star(s) with 10 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

There are 3 open issues and 9 have been closed. On average issues are closed in 74 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of numba-stats is v1.1.1

Quality

numba-stats has 0 bugs and 0 code smells.

Security

numba-stats has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

numba-stats code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

numba-stats is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

numba-stats releases are available to install and integrate.

Installation instructions are not available. Examples and code snippets are available.

It has 1142 lines of code, 139 functions and 36 files.

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

Top functions reviewed by kandi - BETA

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

Log PDF function
Calculate the log of the power law
Compute the log PDF for a given distribution
Log density function
Evaluate density function
De Casteljau algorithm
Translates x
Compute log - likelihood function
Log likelihood function
Helper function for njit
Create a readonly array
Generate wrappers
Create a function object with the specified signature
Integral distribution
Convert a beta array into an integer
Create a wrapper function with the specified signature

Get all kandi verified functions for this library.

numba-stats Key Features

No Key Features are available at this moment for numba-stats.

numba-stats Examples and Code Snippets

No Code Snippets are available at this moment for numba-stats.

Community Discussions

Trending Discussions on numba-stats

Numba/CUDA - Calling vectorized library function

QUESTION

Numba/CUDA - Calling vectorized library function

Asked 2022-Jan-18 at 03:06

I would like to use Numba to get the GPU to run the following function defined here, which has the signature:

...

ANSWER

Answered 2022-Jan-18 at 03:06

I'm not sure if this is relevant, but I noticed that because this function is defined in a separate package, I can't specify in the decorator target='cuda'.

The problem isn’t that the function is defined in another module, it is that the function is already decorated. You can’t replace the decorator after import because the function is already defined (and by replaced by the decorated implementation).

When you see something like this:

Source https://stackoverflow.com/questions/70725765

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

Vulnerabilities

No vulnerabilities reported

Install numba-stats

You can download it from GitHub.

Support

Because of a technical limitation of Numba, this project is poorly documented. Functions with equivalents in scipy.stats follow the Scipy calling conventions exactly. These conventions are sometimes a bit unusual, for example, in case of the exponential, the log-normal or the uniform distribution. See the SciPy docs for details. Please look into the source code for documentation of the other functions. Technical note: pydoc numba_stats does not show anything useful, because numba.vectorize creates instances of a class DUFunc. The wrapped functions show up as objects of that class and help() shows the generic documentation of that class instead of the documentation for the instances.

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