Create a 2-D grid from the vectors [1 3 5 7 9 11 13 15 17 19] and [2 4 6 8 10 12].

[X,Y] = ndgrid(1:2:19,2:2:12)

X = 10×6

     1     1     1     1     1     1
     3     3     3     3     3     3
     5     5     5     5     5     5
     7     7     7     7     7     7
     9     9     9     9     9     9
    11    11    11    11    11    11
    13    13    13    13    13    13
    15    15    15    15    15    15
    17    17    17    17    17    17
    19    19    19    19    19    19

Y = 10×6

     2     4     6     8    10    12
     2     4     6     8    10    12
     2     4     6     8    10    12
     2     4     6     8    10    12
     2     4     6     8    10    12
     2     4     6     8    10    12
     2     4     6     8    10    12
     2     4     6     8    10    12
     2     4     6     8    10    12
     2     4     6     8    10    12

Evaluate and plot the function

over the gridded domain

$$-2<x_1<2$$ and $$-2<x_2<2$$.

Create a grid of values for the domain.

[X1,X2] = ndgrid(-2:.2:2);

Evaluate the function over the domain.

Z = X1 .* exp(-X1.^2 - X2.^2);

Generate a mesh plot of the function.

mesh(X1,X2,Z)

In R2016b and later releases, this task does not require the use of ndgrid. Instead, you can construct the grid using implicit expansion with these commands:

x = -2:.2:2;

Z1 = x.' .* exp(-(x.').^2 - x.^2);

Create a 2-D grid and calculate some function values on the grid. Interpolate between the assigned values to refine the grid.

Create a coarse grid for $$(x,y)$$ in the range $$[-5,5]$$.

[X,Y] = ndgrid(-5:0.5:5);

Calculate some function values on the grid and plot the function.

f = sin(X.^2) * cos(Y.^2);
surf(X,Y,f)

Interpolate between the points using a more refined grid and plot the result.

[X1,Y1] = ndgrid(-5:0.125:5);
F = interpn(X,Y,f,X1,Y1,'spline');

surf(X1,Y1,F)