The dimension of the input vector in the imagesc function

I used the sample data in the attachment and got the result of Figure 1 when using the imagesc function, but I expected the result to be Figure 2.

(Note: XData, YData, and C in the imagesc () function correspond to the first, second, and third columns in the sample data, respectively.)

I want to ask how the dimensions of the matrix should be adjusted to be similar to the result in Figure 2. Thank you.

figure1

figure 2

[Geoff Hayes]

sun - do you have enough data so that you can get the second image? Your sample data file only has 22 rows...

[sun]

Yes, sir, my data is probably more than 10,000, how can I improve it?

In my data, the first and second columns are coordinates, and the third column is an attribute, representing the speed of movement at that point.

Even with more than 10,000 data, the result is similar to Figure 1.

[Geoff Hayes]

So the colours we see in the second image represent the speed at that coordinate?

[sun]

We can call it a similar name like velocity field.

Answer 1

[Bjorn Gustavsson]

For this type of scattered data you can use scatter, something like this:

scatter(data(:,1),data(:,2),23,data(:,3),'filled')

or if you want to reinterpolate to a regular grid you can use any of griddata, TriScatteredInterp, or scatteredInterpolant.

HTH

[sun]

@Bjorn Gustavsson

The figure below is the result based on the code you said. I have a question whether I can adjust the color, because it seems to have only one color.

[Bjorn Gustavsson]

You can adjust the intensity-levels for scatterplots with

caxis([min_level max_level])

where you chose your intensity-range to display.

Sometimes it is also preferable to plot the data in log-scale, you can do that with scatter too - provided your data is positive, just change

scatter(data(:,1),data(:,2),23,data(:,3),'filled')

to

scatter(data(:,1),data(:,2),23,log10(data(:,3)),'filled')

further you might want to dots with smaller (or larger) radius, just change 23 to whatever gives the best display. Sometimes it is worthwhile to sort the points in increasing order. This makes the dots with largest value of data(:,3) to be plotted last which reduces how much they are shaded by other points. To do that use the second out-argument from sort to generate index-vectors.