Difference between revisions of "Fft.R"
(FFT of sin waves in R) |
(like matlab example) |
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| − | # {{R}} | + | Fs <- 1000 # {{R}} Sampling frequency [Hz] |
| − | + | Ts <- 1/Fs # Sample time | |
| − | Ts <- | + | L <- 10 # Length of signal [s] |
| + | |||
f1 <- 2 # Frequency of signal [Hz] | f1 <- 2 # Frequency of signal [Hz] | ||
f2 <- 2.7 | f2 <- 2.7 | ||
| − | A1 <- | + | A1 <- 2.7 # Amplitude of sine functions |
A2 <- 0.5 | A2 <- 0.5 | ||
| − | Time <- seq(0, | + | Time <- seq(0, L, length=Fs*L) |
| − | |||
y <- A1*sin(2*pi*f1*Time) + A2*sin(2*pi*f2*Time+20*pi/180) + 0.01 * rnorm(length(Time)) | y <- A1*sin(2*pi*f1*Time) + A2*sin(2*pi*f2*Time+20*pi/180) + 0.01 * rnorm(length(Time)) | ||
Latest revision as of 21:59, 2 August 2009
Fs <- 1000 #
Code snipits and programs written in R, S or S-PLUS Sampling frequency [Hz] Ts <- 1/Fs # Sample time L <- 10 # Length of signal [s]
f1 <- 2 # Frequency of signal [Hz] f2 <- 2.7
A1 <- 2.7 # Amplitude of sine functions A2 <- 0.5 Time <- seq(0, L, length=Fs*L)
y <- A1*sin(2*pi*f1*Time) + A2*sin(2*pi*f2*Time+20*pi/180) + 0.01 * rnorm(length(Time)) par(mfrow=c(1,1)) plot(Time, y, type="l")
fty <- fft(y)/length(y)*2
Frequency <- Fs/2*seq(0,2, length=length(fty))
par(mfrow=c(2,1))
xmin <- 1.9 xmax <- 2.8
tolerance <- 0.005
- Phasors with an amplitude of zero make it hard to determine phase
ok <- (Mod(fty) >= tolerance) Colours <- ifelse(ok, "black","red")
plot(Frequency, Mod(fty), type="b", xlim=c(xmin, xmax)) # Close up of peaks
grid(NULL, NULL, lwd = 2)
points(Frequency, Mod(fty), col=Colours)
plot(Frequency, Arg(fty), type="b", xlim=c(xmin, xmax)) # Close up of peaks
grid(NULL, NULL, lwd = 2)
points(Frequency, Arg(fty), col=Colours)
- See also Nyquist frequency http://en.wikipedia.org/wiki/Nyquist_frequency
plot(Frequency, Mod(fty), type="l")
plot(Frequency, Arg(fty), type="l")
X11() par(mfrow=c(2,1)) angles <- Arg(fty) angles[!ok] <- 0 plot(Frequency, Mod(fty), type="l") plot(Frequency, angles, type="l")
graphics.off()
