qNoise is a non-gaussian colored random noise generator. It is a handy source of self-correlated noise for a great variety of applications. It depends on two parameters only: tau for controlling the autocorrelation, and q for controlling the statistics. This noise tends smoothly for q = 1 to an Ornstein-Uhlenbeck (colored gaussian) noise with autocorrelation tau. for q < 1 it is bounded noise and it is supra-Gaussian for q > 1.
The noise is generated via a stochastic differential equation using the Heun method (a second order Runge-Kutta type integration scheme) and it is implemented as a stand-alone library in c++.
It is useful as input for numerical simulations, as a source of noise for controlling experiments using synthetic noise via micro-controllers and for a wide variety of applications.
It is stand-alone with no dependencies other than the standard libraries. Due to it's use of some functions from the <random> library, it currently works on c++11 or higher only.
This should be OK for most Macs and new Linux/Unix systems. On Windows please ensure you upgrade to a c++11 compatible compiler, for example GNU g++ 4.7 or higher.
In some older systems it is possible that you need to add -std=gnu++11 to your compilation flags.
Type the following commands on a terminal. The explanations come below.
git clone https://github.com/ignaciodeza/qNoise.git
cd qNoise/test
make test
./runTest.sh
If you see
All tests OK.
at the end of the process then qNoise is installed and works in your system, if you don't want to know more about the installation, you can go directly to Usage.
If you haven't done this yet, clone the repository by typing on a terminal window
git clone https://github.com/ignaciodeza/qNoise.git
To compile the test, from the terminal go to the folder test inside the cloned directory by typing:
cd qNoise/test
Compile the test, using the qNoise library
make test
and run the battery of tests.
./runTest.sh
In less than a second, examples of several types of noise will be shown in the terminal. The files will be saved on disk. You should see several sets of parameters and in the last line:
All tests OK.
This means the software is installed and works in your system.
For cleaning the files and the executables from the test folder, simply type
make clean
Just move both qNoise.h and qNoise.cpp to the folder where your code is. No other installation is necessary.
Include as #include"qNoise.h"in your projects.
In some older systems is possible that you need to add -std=gnu++11 to your compilation flags.
The library provides four methods.
A generator of Gaussian white noise (for convenience).
double gaussWN();
A generator of Gaussian Colored noise (Orstein-Uhlenbeck)
double orsUhl(double x, double tau, double H);
A generator of qNoise, valid in the whole range, where tau and the variance of the noise diverge for q = 5/3
double qNoise(double x, double tau, double q, double H, double sqrt_H);
A normalized version of the former, where tau and the variance are independent of q, valid sufficiently far away from q = 5/3
double qNoiseNorm(double x, double tau, double q, double H, double sqrt_H);
Additionally it provides two methods for seeding the random number generator, manually and using the timer:
void seedManual(unsigned Seed);
void seedTimer();
The timer is used by default.
The executable test_qNoise can be also used as a standalone noise generator.
It accepts four commands
./test_qNoise tau H q N
- tau is the autocorrelation
- H is the integration step
- q controls the statistics
- N is the number of points to calculate
For example (try it!):
./test_qNoise 1 0.01 1.2 1000
will generate 1000 points of supra-Gaussian noise (q=1.2) of tau=1 (relative to H=0.01 ) and put them into the file
qNoise_1_0.01_1.2_1000.txt
which explicitly contains all the parameters.
This file together with the runTest.sh can be edited to better suit your needs and compiled using the same scheme provided above.
A set of unit tests is provided. It is a rather stern test which compares the histograms to the theoretical PDFs. It calculates the square root of sum the square of the difference between both functions as a percentage of the maximum height of the distribution. This allows to have a metric of the "goodness" of the histogram of the generated noise. Note that it may take time (N) for the histogram to take the shape of the PDF, and this time may be considerably higher for highly correlated noise.
In order to access to this unit test first uncomment the following line in qNoise.cpp:
// #define UNIT_TEST
#ifdef UNIT_TEST
#include "unit_tests.cpp"
#endif
And then compile and run, with a command similar to this (it may change in your system):
c++ -std=gnu++11 qNoise.cpp -o qNoise; qNoise
The limit of 10% of difference for passing the test is arbitrary. But I found it to be a good guideline for most applications.
Please read the preprint included in the repository for further information. This manuscript is being prepared for its submission to a Scientific Journal.
If you wish to collaborate with this project please contact me to my email address below.
Have fun!
Copyright (c) 2021, Juan Ignacio Deza email: ignacio.deza@uwe.ac.uk