View or download correlationTest.frink in plain text format
/** This file tests the routines in correlation.frink. */
use correlation.frink
list = [1,2,1,4,1,8,1,2,1,4,1,8,1,2,1,4,1,8]
/** Calculate the autocorrelation in a repeating list with sub-patterns.
This should obtain an offset of 6 being the highest correlation. */
println[autocorrelation[list]]
println[]
// The previous list with a bit of noise. Hopefully the period will still be 6
println[autocorrelation[[1,2,1,4,1,8,1,2,3,4,1,8,1,2,1,5,1,8]]]
println[]
// The list made very noisy because each point is perturbed by Gaussian noise
// centered around the true value with standard deviation = 1
// (Note that results will vary between runs.)
// Hopefully the strongest period will still be detected at 6.
b = new array
for a = list
b.push[randomGaussian[a, 1]]
println["Noisy list is $b"]
println["Results:"]
println[autocorrelation[b]]
println[]
// Find when the digits in a number repeat themselves. The precision may have
// to be increased for larger denominators, as 1/n may repeat after as many as
// n-1 digits.
for b = 1 to 200
{
setPrecision[b*2+10]
r = autocorrelation[array[chars[toString[1./b]]]]
// println[r]
println["1/$b appears to repeat most strongly after " + r@0@0 + " terms."]
}
println[]
// Calculate the autocorrelation of a sinewave. The period should be close
// to the number divided by in the "step" below, although if the step is
// small, then the offsets near 1 will be the strongest (as the sine wave is
// shifted very slightly relative to itself.)
setPrecision[15]
c = new array
for i = 0 to 10 pi step (2 pi / 17.1)
c.push[sin[i]]
println[autocorrelation[c]]
View or download correlationTest.frink in plain text format
This is a program written in the programming language Frink.
For more information, view the Frink
Documentation or see More Sample Frink Programs.
Alan Eliasen was born 18492 days, 22 hours, 11 minutes ago.