desolver | Genetic function optimization via differential evolution | Machine Learning library

by compmem Python Version: Current License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | desolver Summary

desolver is a Python library typically used in Artificial Intelligence, Machine Learning applications. desolver has no bugs, it has no vulnerabilities, it has build file available and it has low support. However desolver has a Non-SPDX License. You can download it from GitHub.

Genetic function optimization via differential evolution in Python.

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Quality

Security

License

Reuse

Support

desolver has a low active ecosystem.

It has 5 star(s) with 1 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

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

It has a neutral sentiment in the developer community.

The latest version of desolver is current.

Quality

desolver has no bugs reported.

Security

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

License

desolver has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

desolver releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Top functions reviewed by kandi - BETA

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

Initialize the population .
Evaluate the population .
Evaluate the population .
Evaluate a population .
Prints out the best evolution .
Inverse function .

Get all kandi verified functions for this library.

desolver Key Features

No Key Features are available at this moment for desolver.

desolver Examples and Code Snippets

No Code Snippets are available at this moment for desolver.

Community Discussions

Trending Discussions on desolver

Error occuring when including Boost headers into .h files but not in .cpp files

speed problems with odesolver in R

QUESTION

Error occuring when including Boost headers into .h files but not in .cpp files

Asked 2018-Dec-28 at 22:56

I'm dealing with a strange problem. I have a code, where I need to implement several macros using Boost typeindex framework. As my macros are only included in the header file, I'd like #include to be included in the header file only like this:

...

ANSWER

Answered 2018-Dec-28 at 22:56

Eventually it was helpful to read the whole error message more carefully:

Source https://stackoverflow.com/questions/53964811

QUESTION

speed problems with odesolver in R

Asked 2018-Mar-07 at 12:56

I have a differential equation model in R that uses the odesolver from the deSolve package. However, at the moment the model is running very slowly. I think this might be something to do with the function that I feed to odesolver being poorly written, but can't figure out what exactly is slowing it down and how I might speed it up. Does anyone have any ideas?

I've made an example that works in a similar way to mine:

...

ANSWER

Answered 2018-Mar-07 at 12:56

A good way to identify the bottle neck is with a profiler and the profvis package provides a good way of drilling down into the results. Wrapping your code in p <- profvis({YourCodeInHere}) and then viewing the results with print(p) gives the following insights:

The lines that are taking the most time are (in descending order of time taken):

Source https://stackoverflow.com/questions/49106797

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

Vulnerabilities

No vulnerabilities reported

Install desolver

You can download it from GitHub.
You can use desolver 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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