How to have a 2D surface plot from the two columns of data?

Hi. I have a data where the first two columns are the x and y coordinates, while the third column is the color. How can I plot such that it give me a 2D surface plot with colorbar as well. The data is attached here. Thank you.

Answer 1

[Cameron]

%x = your x data
%y = your y data
%c = your color data
scatter3(x,y,c,[],c,'filled')
colorbar
colormap turbo %you can omit this line if you want or change turbo to something else
a = gca;
a.View = [0 90];

[Bacha Munir]

Thank you so much. Your answer is correct.

Answer 2

[Image Analyst]

If you have a list of 2-D (x,y) locations and you want to get a surface, you will have to interpolate a surface value for the missing points. The function to do that is scatteredInterpolant.

help scatteredInterpolant

 scatteredInterpolant   Scattered data interpolation
    scatteredInterpolant performs interpolation on scattered data that
    resides in 2-D or 3-D space. A scattered data set is defined by sample
    points X and corresponding values v. A scatteredInterpolant object F
    represents a surface of the form v = F(X). Interpolated values vq at
    query points Xq are obtained by evaluating the interpolant, vq = F(Xq).
 
    F = scatteredInterpolant creates an empty scattered data interpolant.
 
    F = scatteredInterpolant(X,v) creates an interpolant that fits a
    surface of the form v = F(X) to the sample data set (X,v). The sample
    points X must have size NPTS-by-2 in 2-D or NPTS-by-3 in 3-D, where
    NPTS is the number of points. Each row of X contains the coordinates of
    one sample point. The values v must be a column vector of length NPTS.
 
    F = scatteredInterpolant(x,y,v) and F = scatteredInterpolant(x,y,z,v)
    also allow the sample point locations to be specified in alternative
    column vector format when working in 2-D and 3-D.
 
    F = scatteredInterpolant(...,METHOD) specifies the method used to
    interpolate the data. METHOD must be one of the following:
        'linear'  - (default) Linear interpolation
        'nearest' - Nearest neighbor interpolation
        'natural' - Natural neighbor interpolation
    The 'natural' method is C1 continuous except at the sample points. The
    'linear' method is C0 continuous. The 'nearest' method is discontinuous.
 
    F = scatteredInterpolant(...,METHOD,EXTRAPOLATIONMETHOD) also specifies
    the extrapolation method used for query points outside the convex hull.
    EXTRAPOLATIONMETHOD must be one of the following:
        'linear'  - (default if METHOD is 'linear' or 'natural')
                    Linear extrapolation based on boundary gradients
        'nearest' - (default if METHOD is 'nearest') Evaluates to the value
                    of the nearest neighbor on the convex hull boundary
        'none'    - Queries outside the convex hull return NaN
 
    Example:
      % Construct a scatteredInterpolant F from locations x,y and values v
        t = linspace(3/4*pi,2*pi,50)';
        x = [3*cos(t); 2*cos(t); 0.7*cos(t)];
        y = [3*sin(t); 2*sin(t); 0.7*sin(t)];
        v = repelem([-0.5; 1.5; 2],length(t));
        F = scatteredInterpolant(x,y,v)
      % Evaluate F at query locations xq,yq to obtain interpolated values vq
        tq = linspace(3/4*pi+0.2,2*pi-0.2,40)';
        xq = [2.8*cos(tq); 1.7*cos(tq); cos(tq)];
        yq = [2.8*sin(tq); 1.7*sin(tq); sin(tq)];
        vq = F(xq,yq);
      % Plot the sample data (x,y,v) and interpolated query data (xq,yq,vq)
        plot3(x,y,v,'.',xq,yq,vq,'.'), grid on
        title('Linear Interpolation')
        xlabel('x'), ylabel('y'), zlabel('Values')
        legend('sample data','interpolated query data','Location','best')
      % Change the interpolation method from 'linear' to 'nearest'
        F.Method = 'nearest'
      % Perform nearest neighbor interpolation and plot the result
        vq = F(xq,yq);
        figure
        plot3(x,y,v,'.',xq,yq,vq,'.'), grid on
        title('Nearest Interpolation')
        xlabel('x'), ylabel('y'), zlabel('Values')
        legend('sample data','interpolated query data','Location','best')
 
    scatteredInterpolant properties:
        Points              - Locations of the scattered sample points
        Values              - Values associated with each sample point
        Method              - Method used to interpolate at query points
        ExtrapolationMethod - Extrapolation method used outside the convex hull
 
    scatteredInterpolant methods:
        vq = F(Xq) evaluates the scatteredInterpolant F at scattered query
        points Xq and returns a column vector of interpolated values vq.
        Each row of Xq contains the coordinates of one query point.
 
        vq = F(xq,yq) and vq = F(xq,yq,zq) also allow the scattered query
        points to be specified as column vectors of coordinates.
 
        Vq = F(Xq,Yq) and Vq = F(Xq,Yq,Zq) evaluates F at gridded query
        points specified in full grid format as 2-D and 3-D arrays created
        from grid vectors using [Xq,Yq,Zq] = NDGRID(xqg,yqg,zqg).
 
        Vq = F({xqg,yqg}) and Vq = F({xqg,yqg,zqg}) also allow a grid of
        query points to be specified in compact form as grid vectors. Use
        this syntax to conserve memory when the query points form a large
        grid. Vq has the same size as the grid: LENGTH(xqg)-by-LENGTH(yqg)
        or LENGTH(xqg)-by-LENGTH(yqg)-by-LENGTH(zqg).
 
    See also griddedInterpolant, griddata, delaunayTriangulation

    Documentation for scatteredInterpolant
       doc scatteredInterpolant

See my attached demo where I let you click a bunch of arbitrary points of your choice and it then interpolates the surface.

In the above demo I clicked on 9 points and for the "z" values at those locations I used the gray level of the image. You can see the points I clicked on and the values of the interpolated image in between those points. While I displayed it as an image you could just as well use surf() to display/render it as a surface in a 3-D axes.

[Bacha Munir]

Thank you so much. Correct.