mdxp = irsa_mdsp (md, rd, N, [rfunc])
Generate N sampling points with a minimum distance md and an additional random distance rd with random distribution rfunc
Input:
md : Scalar – minimum distance
rd : Scalar – mean of the random distance
N : Scalar – number of sampling points to generate
rfunc: String – random distribution function for the random part. Has to take the number of rows as the first and the number of columns as the second argument. Default is 'rand'.
Output:
mdxp : Columnvector – sampling points with a minimum distance
Note:
The first sampling point is 0 and the last
(N-1)*(md + rd).
The following code
N = 25;
eqxp = irsa_mdsp( 1 , 0 , N ); # Should be the same as [0:1:N-1].'
mdxp = irsa_mdsp( .2 , .8, N, "randn" );
o = ones(N,1);
## Plot
figure();
subplot( 211 );
plot( eqxp, o, '^b', eqxp, o, '*b' ); text(); title("");
title( "Irregular Minimum Distance Sampling versus regular (equidistant) sampling" );
legend('off');
axis ([-0.5,19.5,0,1.5]);
text( 5,1.25, 'regular sampling with distance = 1' );
subplot( 212 );
plot( mdxp, o, '^r', mdxp, o, 'xr' ); text;
xlabel( "Time" );
text( 5,1.25, 'minimum distance sampling with md = 0.2 and rd = 0.8' );
legend('off');
axis ([-0.5,19.5,0,1.5]);
Produces the following figure
| Figure 1 |
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