How to split data matrix conditionally?

2 vues (au cours des 30 derniers jours)
Andi
Andi le 14 Avr 2022
Commenté : Andi le 14 Avr 2022
I have a data matrix of 59 columns and variabale number of rows, Required to extract a new matrix such that it include only those values that are in a specific bound.
As a result, we left with variable number of observations in each coloumn. How can i get new matrix, in such a condition:
An examplry random data set with my approach as below, but did not get required results.
p = rand(10, 10)
for i=1:10
q = p((p(:,ii) > .2) & (p(:,ii) < .4) , :)
end

Réponse acceptée

Chunru
Chunru le 14 Avr 2022
Modifié(e) : Chunru le 14 Avr 2022
You will not get an matrix for the output since the number of entries satisfying the condition for each column will be different.
Your output can be combined as a cell array instead.
n = 50;
p = rand(n, n);
for i=1:n
pi = p(:, i);
q{i} = pi(pi > .2 & pi < .4);
end
q
q = 1×50 cell array
{13×1 double} {13×1 double} {9×1 double} {12×1 double} {11×1 double} {6×1 double} {9×1 double} {14×1 double} {8×1 double} {13×1 double} {10×1 double} {9×1 double} {9×1 double} {10×1 double} {8×1 double} {10×1 double} {17×1 double} {10×1 double} {14×1 double} {11×1 double} {9×1 double} {7×1 double} {5×1 double} {9×1 double} {8×1 double} {12×1 double} {12×1 double} {14×1 double} {9×1 double} {7×1 double} {5×1 double} {13×1 double} {9×1 double} {10×1 double} {10×1 double} {15×1 double} {9×1 double} {13×1 double} {12×1 double} {9×1 double} {11×1 double} {13×1 double} {10×1 double} {6×1 double} {12×1 double} {11×1 double} {12×1 double} {10×1 double} {11×1 double} {10×1 double}
%% counting base on q (actually you can do that on p instead)
count = cellfun(@numel, q)
count = 1×50
13 13 9 12 11 6 9 14 8 13 10 9 9 10 8 10 17 10 14 11 9 7 5 9 8 12 12 14 9 7
% number of cells with >=10 elements
nc = sum(count>=10)
nc = 31
  12 commentaires
Andi
Andi le 14 Avr 2022
For each point in data set, I have an upper and lower limit, then by using that upper and lower limits i need to search for observations in ecah coloumn of dataset 2. So technically each column should have some value or just no value. There is no other choice to give answer like NaN or etc.
Andi
Andi le 14 Avr 2022
we did mistake here that why we get NaN
e{ii, kk}=a(a(:, ii)>L_lim(:,kk) & a(:,ii)<U_lim(:, kk), ii);
Thank you for help.

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