Surface Interpolation for Scilab

use plot3d() and contour() with scattered data



Presentation

Here is a new toolbox for Scilab. This toolbox enables the use of plot3d() and contour() functions even if your data are not located on a regular grid.
Indeed, a new function interpolates your data and generates automatically a regular grid. This is well suited for load-pull analysis (this example).
This toolbox includes 2 functions :
  • plotsmith(color) : display the smithchart, even for 3D applications.

  • interpolate_grid(data,scale_factor) : generate a 3 elements list. The fist element is the X vector, the second one is the Y vector and the third one is the Z matrix of the interpolated data. Data is a matrix : each column has to contain X,Y and Z data points (real only).The scaling factor is the ratio beetween the interpolated grid and the smallest vector in your data.

Example

// This exemple displays the picture below
M=fscanfMat("C:\exemple.txt");
M(:,3)=M(:,3)./1000 // Unit change from mW to W
clf() ;
plotsmith(12);
plot2d(M(:,1),M(:,2),-8);
new_data=interpolate_grid(M,10);
contour(new_data(1),new_data(2),new_data(3),20);
plot3d(new_data(1),new_data(2),new_data(3),alpha=28,theta=236);

plot3d() and contour() with load-pull measured data
This new function generates a regular grid from scattered input data




Download and installation

1. Download the archive file here
2. Unzip the file in your Scilab contrib directory (SCI+\contrib)
3. Launch Scilab and write the following command : exec(SCI+'/contrib/surface/builder.sce');

Now the toolbox is installed. For future scilab session, you just have to call once the surface library either by the toolbox menu or the command line :

SURFACE=lib(SCI+'/contrib/surface/macros/');