kombine | A kernel-density-based , embarrassingly parallel ensemble | GPU library
kandi X-RAY | kombine Summary
kandi X-RAY | kombine Summary
kombine is a Python library typically used in Hardware, GPU applications. kombine 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 kombine' or download it from GitHub, PyPI.
kombine is an ensemble sampler that uses a clustered kernel-density-estimate proposal density, allowing for massive parallelization and efficient sampling.
kombine is an ensemble sampler that uses a clustered kernel-density-estimate proposal density, allowing for massive parallelization and efficient sampling.
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kombine has a low active ecosystem.
It has 30 star(s) with 26 fork(s). There are 7 watchers for this library.
It had no major release in the last 12 months.
There are 1 open issues and 7 have been closed. On average issues are closed in 452 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of kombine is 0.8.4
Quality
kombine has 0 bugs and 0 code smells.
Security
kombine has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
kombine code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
kombine 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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kombine 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.
Installation instructions are not available. Examples and code snippets are available.
kombine saves you 509 person hours of effort in developing the same functionality from scratch.
It has 1195 lines of code, 116 functions and 16 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed kombine and discovered the below as its top functions. This is intended to give you an instant insight into kombine implemented functionality, and help decide if they suit your requirements.
- Generate the model
- Generate the covariance matrix
- Generate noise
- R Compute the RBF model
- Filter times
- Generate Poisson distribution
- Generate a list of tobs
- Draw a random prior distribution
Get all kandi verified functions for this library.
kombine Key Features
No Key Features are available at this moment for kombine.
kombine Examples and Code Snippets
No Code Snippets are available at this moment for kombine.
Community Discussions
Trending Discussions on kombine
QUESTION
Python peewee / fastapi get User without loading Items
Asked 2020-Jul-18 at 21:31
So I followed this tutorial to kombine fastapi & peewee: link
And due to this tutorial i got those models (peewee):
...ANSWER
Answered 2020-Jul-18 at 21:31There is a simple way to do that, response_model_exclude
is exactly what you are looking for.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install kombine
You can install using 'pip install kombine' or download it from GitHub, PyPI.
You can use kombine 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 kombine 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.
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