Is NaN ok here?

Question

Vadim Potorocha 2020-11-20

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/654593-is-nan-ok-here

评论： Vadim Potorocha 2020-11-20

采纳的回答： John D'Errico

在 MATLAB Online 中打开

%coin txt

5.00000000e-01 5.00000000e-01

%crime txt

1.66000000e-01 6.60000000e-02 1.40000000e-02 3.90000000e-02 1.40000000e-02 2.70000000e-02 7.20000000e-02 1.00000000e-03 9.00000000e-03 1.30000000e-02 5.50000000e-02 9.00000000e-03 2.80000000e-02 3.80000000e-02 2.60000000e-02 5.50000000e-02 9.60000000e-02 2.30000000e-02 3.50000000e-02 4.50000000e-02 5.40000000e-02 2.40000000e-02 1.00000000e-03 7.00000000e-03 2.00000000e-03 1.50000000e-02 7.00000000e-03 3.00000000e-03 0.00000000e+00 1.40000000e-02 1.80000000e-02 3.00000000e-03 5.00000000e-03 1.80000000e-02

%unfair.txt

9.99000000e-01 1.00000000e-03

%ventsel.txt

1.45000000e-01 6.40000000e-02 1.50000000e-02 3.90000000e-02 1.40000000e-02 2.60000000e-02 7.40000000e-02 8.00000000e-03 1.50000000e-02 6.40000000e-02 1.00000000e-02 2.90000000e-02 3.60000000e-02 2.60000000e-02 5.60000000e-02 9.50000000e-02 2.40000000e-02 4.10000000e-02 4.70000000e-02 5.60000000e-02 2.10000000e-02 2.00000000e-03 9.00000000e-03 4.00000000e-03 1.30000000e-02 6.00000000e-03 3.00000000e-03 1.50000000e-02 1.60000000e-02 3.00000000e-03 7.00000000e-03 1.90000000e-02

%ralph.txt

3.36184163e-02 1.43227594e-01 1.64970470e-01 1.34046838e-01 7.52792246e-02 6.54570283e-02 5.34771727e-03 9.39337045e-02 1.06252105e-01 1.77866902e-01

%ALPH_ENTROPY FUNCTION
function h = alph_entropy(P)
h = sum(-P .* log2(P));
end
%APLH_REDUNDANCY FUNCTION
function r = alph_redundancy(P)
r = sum(1 - (alph_entropy(P)./log2(P)));
end

%main.m

A = load("coin.txt",'-ascii') 
B = load("crime.txt",'-ascii') 
C = load("unfair.txt",'-ascii') 
D = load("ventsel.txt",'-ascii') 
E = load("ralph.txt",'-ascii') 
Z = [alph_entropy(A) alph_redundancy(A); alph_entropy(B) alph_redundancy(B) ; alph_entropy(C) alph_redundancy(C); alph_entropy(D) alph_redundancy(D); alph_entropy(E) alph_redundancy(E)];
save results.txt Z -ascii;

MATRIX RESULT

%results.txt

1.00000000e+00 4.00000000e+00

NaN NaN

1.14077577e-02 9.90444552e+00

4.41966505e+00 5.87982853e+01

3.06961940e+00 1.90521746e+01

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Answer 1

John D'Errico 2020-11-20

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/654593-is-nan-ok-here#answer_550938

编辑：John D'Errico 2020-11-20

在 MATLAB Online 中打开

Sure. It does not bother me. Why does it bother you?

B = [1.66000000e-01 6.60000000e-02 1.40000000e-02 3.90000000e-02 1.40000000e-02 2.70000000e-02 7.20000000e-02 1.00000000e-03 9.00000000e-03 1.30000000e-02 5.50000000e-02 9.00000000e-03 2.80000000e-02 3.80000000e-02 2.60000000e-02 5.50000000e-02 9.60000000e-02 2.30000000e-02 3.50000000e-02 4.50000000e-02 5.40000000e-02 2.40000000e-02 1.00000000e-03 7.00000000e-03 2.00000000e-03 1.50000000e-02 7.00000000e-03 3.00000000e-03 0.00000000e+00 1.40000000e-02 1.80000000e-02 3.00000000e-03 5.00000000e-03 1.80000000e-02];
alph_entropy = @(P) sum(-P .* log2(P));
alph_entropy(B)
ans =
   NaN

Why is that?

B(29)
ans =
     0

In fact, B(29) was 0.00000000e+00.

Your entropy formula will generate NaN when any element is exactly zero. And since the redundancy code uses the entropy computation, it too results in NaN.

So what do you expect? Looks fine.

When you see a problem, LOOK AT YOUR DATA. THINK ABOUT WHAT YOUR CODE IS DOING.

You might decide if you can just drop any zero elements of the vector. Does that make sense?

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John D'Errico 2020-11-20

If it is homework, then you might look at the formulas for entropy, and decide how zero impacts the result you would expect. Would deleting zero elements be a problem? You were given this as homework, so you are the one who is supposed to think.

Vadim Potorocha 2020-11-20

yep deleting zero elements coulda be the answer. But i have another formula with limit in it, but in GNU Octave i have no idea how to code it lim(inf to 0) = -p/ln(2)

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