Create an array containing pseudorandom numbers drawn from a Rayleigh distribution.
JavaScript
1
0
Apache License 2.0
This project provides a function to create arrays containing pseudorandom numbers drawn from a Rayleigh distribution, which is commonly used in physics and signal processing. It's designed for developers working on numerical computing tasks in JavaScript who need to generate Rayleigh-distributed random values for simulations, statistical analysis, or other scientific applications.
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Support the dependencies of stdlib-js/random-array-rayleigh
Default array settings.
List of array data types.
Create a factory function for generating pseudorandom values drawn from a unary PRNG.
Rayleigh distributed pseudorandom numbers.
stdlib TypeScript type declarations.
Define a non-enumerable read-only property.
Float32Array.
Float64Array.
Create an array filled with NaNs and having a specified length.
Uint32Array.
Create a zero-filled array having a specified length.
Test if a value is a Uint32Array.
Insert array element values into a format string and print the result.
Maximum unsigned 32-bit integer.
Test if a double-precision floating-point numeric value is NaN.
Test if a single-precision floating-point numeric value is NaN.
Exponential function.
A linear congruential pseudorandom number generator (LCG) based on Park and Miller.
tap-producing test harness for node and browsers
Yet another JS code coverage tool that computes statement, line, function and branch coverage with module loader hooks to transparently add coverage when running tests. Supports all JS coverage use cases including unit tests, server side functional tests and browser tests. Built for scale
Minimal TAP output formatter.
Benchmark harness.
Support the repos that depend on stdlib-js/random-array-rayleigh
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stdlib-bot
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