loop for different columns

Hi every one

i want to write a loop but i get confused

i have a data with 103 rows and 811 columns. i want calculate 6 parameters for all the columns. at last i should have a matrix with 811 rows and 6 parameters. please help me. i know that i cant find the right position of the counter n trough the loop.

 Y1='Y1.xlsx'
Y1=xlsread(Y1);
 z2_real=Y1(:,1);
threshold = 4;
 N=size(Y1,2);
 n=1
 
for i=1:N
  Y1_new(:,n)=Y1;
  [r_z2_real,c_z2_real]=size(z2_real);
[rows_rl, columns_rl] = find(z2_real > threshold);%number of real active cmpds [rows_tn, columns_tn] = find(Y1 > threshold);%number of predicted as active cmpds [rows_rl_tp, columns_rl_tp] = find(z2_real < threshold);%number of real inactive cmpds [rows_tp, columns_tp] = find(Y1 < threshold);%number of predicted as inactive cmpds NTN = nnz(ismember(rows_tn,rows_rl));%NTN:number of correct active cmpd NTP = nnz(ismember(rows_tp,rows_rl_tp));%NTP:number of correct inactive cmpd FC=((NTN+NTP)/r_z2_real)*280; [rr_rows_rl_tp,cc_rows_rl_tp]=size(rows_rl_tp); [rr_rows_tp,cc_rows_tp]=size(rows_tp); NFP=abs(rr_rows_tp-NTP);%NFP:number of cmpds that model determined as actice cmpd incorrectly FAR=((NFP/(NTN+NTP))*280); [rr_rows_rl,cc_rows_rl]=size(rows_rl); [rr_rows_tn,cc_rows_tn]=size(rows_tn); NFN=abs(rr_rows_rl-NTN);%NFP:number of cmpds that model determined as inactice cmpd incorrectly POD=(NTP/(NFN+NTP))*280;
[rows_tn, columns_tn] = find(Y1_new > threshold);%number of predicted as active cmpds
[rows_rl_tp, columns_rl_tp] = find(z2_real < threshold);%number of real inactive cmpds
[rows_tp, columns_tp] = find(Y1_new < threshold);%number of predicted as inactive cmpds
NTN = nnz(ismember(rows_tn,rows_rl));%NTN:number of correct active cmpd
NTP = nnz(ismember(rows_tp,rows_rl_tp));%NTP:number of correct inactive cmpd
FC=((NTN+NTP)/r_z2_real)*100;
[rr_rows_rl_tp,cc_rows_rl_tp]=size(rows_rl_tp);
[rr_rows_tp,cc_rows_tp]=size(rows_tp);
NFP=abs(rr_rows_rl_tp-rr_rows_tp);%NFP:number of cmpds that model determined as actice cmpd incorrectly
FAR=((NFP/(NTN+NTP))*100);
[rr_rows_rl,cc_rows_rl]=size(rows_rl);
[rr_rows_tn,cc_rows_tn]=size(rows_tn);
NFN=abs(rr_rows_rl-NTN);%NFP:number of cmpds that model determined as inactice cmpd incorrectly
POD=(NTP/(NFN+NTP))*100;
             ss(n,:)=[NTN,NTP,NFP,NFN,FC,FAR,POD];
ss(isnan(ss))=0;
%  i=i+1

xlswrite('classification_results.xlsx',ss,'results'); 
end
 %    

Answer 1

[Walter Roberson]

xlswrite('classification_results.xlsx',ss,'results'); 

You are always writing the ss vector of results to the same location in the file.

Change

%  i=i+1
xlswrite('classification_results.xlsx',ss,'results');
end

to

all_ss(i, :) = ss;
end
xlswrite('classification_results.xlsx', all_ss, 'results');

[Stephen23]

mary moz's incorrectly posted and accepted "Answer" moved here:

Dear Walter Roberson

Thanks for the reply. but the problem is still exist. i get the following error.

Subscripted assignment dimension mismatch.

Error in parameters (line 9)

Y1_new(i, :) = Y1

[mary moz]

Dear Walter

it works by your guidance using following code. thanks

clc

clear all

Y1='Y1.xlsx'

Y1=xlsread(Y1);

z2_real=Y1(:,1);

threshold = 4;

N=size(Y1,2);

n=1

for i=1:N

Y1_new = Y1(:,i)

[r_z2_real,c_z2_real]=size(z2_real);

[rows_rl, columns_rl] = find(z2_real > threshold);%number of real active cmpds [rows_tn, columns_tn] = find(Y1 > threshold);%number of predicted as active cmpds [rows_rl_tp, columns_rl_tp] = find(z2_real < threshold);%number of real inactive cmpds [rows_tp, columns_tp] = find(Y1 < threshold);%number of predicted as inactive cmpds NTN = nnz(ismember(rows_tn,rows_rl));%NTN:number of correct active cmpd NTP = nnz(ismember(rows_tp,rows_rl_tp));%NTP:number of correct inactive cmpd FC=((NTN+NTP)/r_z2_real)*280; [rr_rows_rl_tp,cc_rows_rl_tp]=size(rows_rl_tp); [rr_rows_tp,cc_rows_tp]=size(rows_tp); NFP=abs(rr_rows_tp-NTP);%NFP:number of cmpds that model determined as actice cmpd incorrectly FAR=((NFP/(NTN+NTP))*280); [rr_rows_rl,cc_rows_rl]=size(rows_rl); [rr_rows_tn,cc_rows_tn]=size(rows_tn); NFN=abs(rr_rows_rl-NTN);%NFP:number of cmpds that model determined as inactice cmpd incorrectly POD=(NTP/(NFN+NTP))*280;

[rows_tn, columns_tn] = find(Y1_new > threshold);%number of predicted as active cmpds

[rows_rl_tp, columns_rl_tp] = find(z2_real < threshold);%number of real inactive cmpds

[rows_tp, columns_tp] = find(Y1_new < threshold);%number of predicted as inactive cmpds

NTN = nnz(ismember(rows_tn,rows_rl));%NTN:number of correct active cmpd

NTP = nnz(ismember(rows_tp,rows_rl_tp));%NTP:number of correct inactive cmpd

FC=((NTN+NTP)/r_z2_real)*100;

[rr_rows_rl_tp,cc_rows_rl_tp]=size(rows_rl_tp);

[rr_rows_tp,cc_rows_tp]=size(rows_tp);

NFP=abs(rr_rows_rl_tp-rr_rows_tp);%NFP:number of cmpds that model determined as actice cmpd incorrectly

FAR=((NFP/(NTN+NTP))*100);

[rr_rows_rl,cc_rows_rl]=size(rows_rl);

[rr_rows_tn,cc_rows_tn]=size(rows_tn);

NFN=abs(rr_rows_rl-NTN);%NFP:number of cmpds that model determined as inactice cmpd incorrectly

POD=(NTP/(NFN+NTP))*100;

ss(:,i)=[NTN,NTP,NFP,NFN,FC,FAR,POD];

ss(isnan(ss))=0;

% all_ss(i) = ss;

end

xlswrite('classification_results.xlsx', ss', 'results');