How can I match two vectors using the discrete inverse transform method?

iV=reshape(pr,1,[]);% pr represents the pobability matrix
V=cumsum(V)/sum(V);
figure, cdfplot(prc)
U=rand(1,100)

I have a probability map (V) containing 4096 elements (see figure). I've also generated a vector U containing 100 random uniform probabilities. Now i want to match each elment of U to the correseponding probalility on the figure, using the discrete inverse transform method (Vj-1=<Ui<Vj). I'll apprecaite your help.

Answer 1

[darova]

Give each element of U and compare with every element of V

ind = zeros(size(U));
for i = 1:length(U(:))
    [~, ind(i)] = min( abs(U(i)-V) );
end

I think ismember() can be faster solution, but don't know how to apply it here

[darova]

U and V can be rounded to desired tolerance and ismember() can be used

[Tchilabalo]

Thanks Darova! It is what i was looking for. I have one follow up question. To get "V", i reshaped the probability matrix to a vector. Now how do I determine where the index are on the probability matrix.

[darova]

tol = 1000;    % tolerance: 3 position after decimal point
[~, ind] = ismember( round(U(:)*tol),round(V(:)*tol) );
%    V(:) - reshape matrix to vector
%    U(i) == V(ind(i)) - (if ind(i) is not zero)

If you have linear index and want to convert it to [rows,columns]:

matrix_size = [m,n];
[I,J] = ind2sub(matrix_size,IND);

[Tchilabalo]

Thanks for your help.