Plot 3D FFT over time with Surf - How to set the Axis?

Hi there,

I'm sampling data from an EEG in a C++ program that writes the FFT of a sample to a csv file. After the experiment I read all the csv's into matlab and end up with a matrix in which each column represents a sampled FFT: [InputHistory]

TIME__________(Columns)_____________>
R1_C1_S1 | R1_C2_S1 | R1_C3_S1
R2_C1_S2 | R2_C2_S2 | R2_C3_S2
R3_C1_S3 | R3_C2_S3 | R3_C3_S3
R4_C1_S4 | R4_C2_S4 | R4_C3_S4
R5_C1_S5 | R5_C2_S5 | R5_C3_S5

Where R=row,C= column and S = sample. I hope you understand my data structure? Each column is an FFT.

Below is result of the command:

surf( InputHisotry)

How can I set the values of the Highlighted X-axis? I know I can call surf(x,y,Z), but I don't have an x,y, and Z. I just have a Z and an x? I'm not trying to plot a surface function with 3 variables like they use in the examples.

Thank you for your time,

Rudolf

EDIT: set(gca,'XTick'_,myrange_) changes the ticks on the "y" axis so obviously I have my axis mixed around. regardless, set(gca,'YTick', 0:0.25:63.5) sets the ticks from 0 - 63.5, I need 0 - 63.5 to span the 0 - 100 shown in the plot.

Answer 1

[Star Strider]

I am guessing here because I am not certain that I completely understand your question. (I do not understand the reason your set(gca, 'YTick',... command does not work in your application.)

To start, I suggest you use meshgrid to create your x and y axes for your figure. For example:

x = 0:0.25:63.5;
y = 1:30;
[X, Y] = meshgrid(x, y);
surf(X, Y, InputHisotry)

You may have to experiment a bit to be sure that the dimensions of ‘X’, ‘Y’, and ‘InputHisotry’ all match, but if I understand your question correctly, this approach may solve your problem.

If you only have 100 elements to your x-axis vector, it may be appropriate to use:

x = linspace(0, 63.5, 100);

because the x-axis you specified has 255 elements, but the x-axis in the plot you posted seems to have 100 elements.

I also suggest you consider ribbon for your plot. It may make it easier for you to see the frequency components of your EEG signals.