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#! /usr/bin/octave -q
%
% General test cases for Octave
%
%
% Tests for Information Theory Library.
%
p=[ 0 0.75;
0.125 0.125 ];
jointentropy(p)
x=marginalc(p);
entropy(x)
y=marginalr(p);
entropy(y)
% Test on Mutual Information
XY=[ 1/8 1/16 1/32 1/32;
1/16 1/8 1/32 1/32;
1/16 1/16 1/16 1/16;
1/4 0 0 0 ];
mutualinformation(XY)
entropy(marginalc(XY)) - conditionalentropy_XY(XY)
entropy(marginalr(XY)) - conditionalentropy_YX(XY)
jointentropy(XY)
% Test on Relative Entropy
X=[0.5 0.2 0.2 0.1];
Y=[0.2 0.2 0.2 0.4];
relativeentropy(X,Y)
relativeentropy(Y,X)
% Test on Conditional Entropy
XY=[ 1/8 1/16 1/32 1/32;
1/16 1/8 1/32 1/32;
1/16 1/16 1/16 1/16;
1/4 0 0 0 ];
% x=marginalr(XY)
% y=marginalc(XY)
c1=conditionalentropy_XY(XY);
c2=conditionalentropy_YX(XY);
j=jointentropy(XY);
marx=entropy(marginalc(XY));
mary=entropy(marginalr(XY));
j # H(x,y)
marx + c2 # H(x,y)
mary + c1 # H(x,y)
% Test on Joint Entropy
XY=[ 1/8 1/16 1/32 1/32;
1/16 1/8 1/32 1/32;
1/16 1/16 1/16 1/16;
1/4 0 0 0 ];
jointentropy(XY)
% Test on Conditional Entropy
% Test on Entropy function
for N=2:20
prob=ones(1,N)*(1/N);
x=entropy(prob);
printf("Entropy of %g is %g\n",prob(1),x);
end
prob=[1/2,1/4,1/8,1/8]
val=0
for i=1:length(prob)
val=val+prob(i)*log2(prob(i))
end
entropy(prob)

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