finding Frequency of Sinewave data using Fourier

Question

CONTEXT

I read 5 different related posts but I do not understand how to interpret mathematica's output for my situation.

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I have 300 measurements (taken every 1 second);

I am told that the data is in the form $$y = A \sin{2\pi f t}$$

I want to find the frequency $f$ using a fourier transform

ListLinePlot[data]

plotting the data it seems (using my fallible human perception) that the period is not far of 18 seconds

Show[
     ListLinePlot[data, AxesLabel -> {"s"}], 
     Plot[.03 Sin[2 \[Pi] (1/18) t] + Mean[data], {t, 0, 300},    
          PlotStyle -> Directive[Orange, Dashed]
     ]
]

note this code could be incorrect perhaps I need to include FourierParameters

powerSpectrum = Abs[Fourier[data[[All, 2]]]]^2;
ListLinePlot[powerSpectrum[[1 ;; 100]], PlotStyle -> Red, PlotRange -> {All, {0, .012}}]

QUESTION

Ignoring the outliers on the extreme left it appears that the highest spike is near x = 18

How does one convert this into a frequency (number of oscillations in 1 second)?

Given that my sample length is 300 seconds?

Answer 1

Have a look at my post on using Fourier here you will see that the frequency axis has an increment of the sample rate divided by the number of points and goes from zero to one less than the sample rate.

I also note that your data has a large mean value. It is worth removing this as it dominates the first point of the fourier transform. You tell us that the sample rate is 1 sample per second.

a = data[[All, 2]];
b = a - Mean[a];
sr = 1;  (* sample rate*)
nn = Length@data;
ff = Table[(n - 1) sr/nn, {n, nn}] // N;
ft = Fourier[b, FourierParameters -> {-1, -1}];
ListLinePlot[Transpose[{ff, Abs[ft]}][[1 ;; 40]], PlotRange -> All]

There is a peak at point 18 corresponding to a frequency of 0.056666 Hz or a period of 17.6 sec. However, the data is very noisy and nothing like a sine wave. I would recommend trying to get better data. Trying to estimate an exact sine wave from Fourier is difficult even if the data is good. Look here for an extensive discussion on this topic.

Hope that helps.