WeightedRandom | Unity library for evaluating generic biased randomized

by merpheus-dev C# Version: Current License: No License

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

kandi X-RAY | WeightedRandom Summary

WeightedRandom is a C# library typically used in Testing, Unity applications. WeightedRandom has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Unity library for evaluating generic biased randomized results.

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Support

WeightedRandom has a low active ecosystem.

It has 18 star(s) with 4 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

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

It has a neutral sentiment in the developer community.

The latest version of WeightedRandom is current.

Quality

WeightedRandom has 0 bugs and 0 code smells.

Security

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

WeightedRandom code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

WeightedRandom does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

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

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

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WeightedRandom Key Features

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WeightedRandom Examples and Code Snippets

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Community Discussions

Trending Discussions on WeightedRandom

Why are the mean values not much closer to the original weightings?

template class implementation errors

QUESTION

Why are the mean values not much closer to the original weightings?

Asked 2017-Sep-25 at 16:53

I run the following program and a typical console output is as follows.

Mean percentage points for weighting 0 is: 57.935590153643616
Mean percentage points for weighting 1 is: 42.06440984635654

Why are these printed means not much closer to 60 and 40?

...

ANSWER

Answered 2017-Sep-25 at 16:53

You are estimating 100*E(X/(X+Y)] and 100*E(Y/(X+Y)] where X = 60*U(1,10) and Y = 40*U(1,10) (where U(1,10) is the discrete uniform distribution on 1,..,10). Since there are only 10*10 = 100 possible ways to generate two such uniform variables, you can compute the expressions for each such pair and then compute these expectations directly. In Python define:

Source https://stackoverflow.com/questions/46406542

QUESTION

template class implementation errors

Asked 2017-Aug-10 at 04:45

Below are my codes to generate random numbers based on user-defined weighting values. It all works, until I tried to make the type of data become any types, e.g. double, float. I have little experience implement them in practice, only read about them on textbooks. Can anyone helps me fix it?

Thanks,

...

ANSWER

Answered 2017-Aug-10 at 04:45

you simply need to template the class, allowing total to be the templated type.

Source https://stackoverflow.com/questions/45603471

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

Vulnerabilities

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