Merge branch 'main' of...

Merge branch 'main' of https://gitlab.lis-lab.fr/laurie.boffelli/modelisation-statistique-coeur into main

training/A/prepare_models_part1modifie.m

+% build dynamics model (part 1)
+%modele A
+Y=load('ListeDesVolumes.txt');
+y_training=zeros(192,1)%zeros(210,1);
+C=xlsread('points courbes.xls')
+
+% on normalise les patients
+J=1;
+I=1;
+ymax_training=Y;
+ymax_training=zeros(18,1);
+while (I<=18);
+    % on cherche le max du patient
+    J=1;
+    while (J<=25);
+        if Y(J,I) > ymax_training(I,1)
+            ymax_training(I,1)=Y(J,I);
+        end
+        J=J+1;
+    end
+    
+    % on normalise le patient
+    J=1;
+    while (J<=25);
+        Y(J,I) = Y(J,I) / ymax_training(I,1);
+        J=J+1;
+    end
+    
+    I=I+1;
+end
+
+% on récupère les frames qui nous intéressent
+J=1;
+I=1;
+i=1;
+while (I<=18);
+    J=1;
+    while (J<C(I,1));
+        y_training(i,1)=Y(J,I);
+        i=i+1;
+        J=J+1;
+    end
+    I=I+1;
+end
+Y_training = y_training;
+
+%creation de X_training
+k=1;
+X_training=[];
+while k<=18
+    X=[0:1/(C(k,1)-1):1];
+    X_training = [X_training, X];
+    k=k+1;
+end
+X_training=X_training';
+%X_training=repmat(X_training,18,1);
+
+
+save('training.mat','X_training','Y_training')
\ No newline at end of file

training/B1/prepare_models_part1modifie.m

+% build dynamics model (part 1)
+%modele B1
+Y=load('ListeDesVolumes.txt');
+y_training=zeros(127,1)%zeros(145,1);
+C=xlsread('points courbes.xls')
+
+% on normalise les patients
+J=1;
+I=1;
+ymax_training=Y;
+ymax_training=zeros(18,1);
+while (I<=18);
+    % on cherche le max du patient
+    J=1;
+    while (J<=25);
+        if Y(J,I) > ymax_training(I,1)
+            ymax_training(I,1)=Y(J,I);
+        end
+        J=J+1;
+    end
+    
+    % on normalise le patient
+    J=1;
+    while (J<=25);
+        Y(J,I) = Y(J,I) / ymax_training(I,1);
+        J=J+1;
+    end
+    
+    I=I+1;
+end
+
+% on récupère les frames qui nous intéressent
+J=1;
+I=1;
+i=1;
+while (I<=18); %on parcourt tout les patients
+    J=C(I,1); %on prend que la premiere colonne du .xls
+    if C(I,3)>0 %si le patient a un plateau
+        while (J<C(I,3)); %on parcourt tout les éléments de la 3ieme colonnes J in 1:element troisieme col
+            y_training(i,1)=Y(J,I); %exp patient 1: y_training=une col 
+            i=i+1;
+            J=J+1;
+        end
+    else
+        while (J<C(I,2));
+            y_training(i,1)=Y(J,I);
+            i=i+1;
+            J=J+1;
+        end
+    end
+    I=I+1;
+end
+Y_training = y_training;
+
+%creation de X_training
+k=1;
+X_training=[];
+while k<=18
+    if C(k,3)>0
+        X=[0:1/(C(k,3)-C(k,1)):1];
+        X_training = [X_training, X];
+    else
+        X=[0:1/(C(k,2)-C(k,1)):1];
+        X_training = [X_training, X];
+    end
+    k=k+1;
+end
+X_training=X_training';
+%X_training=repmat(X_training,18,1);
+
+
+save('training.mat','X_training','Y_training')
\ No newline at end of file

training/B2/prepare_models_part1modifie.m

+% build dynamics model (part 1)
+%modele B2 %le vrai
+Y=load('ListeDesVolumes.txt');
+y_training=zeros(73,1)%zeros(88,1);
+C=xlsread('points courbes.xls')
+
+% on normalise les patients
+J=1;
+I=1;
+ymax_training=Y;
+ymax_training=zeros(18,1);
+while (I<=18);
+    % on cherche le max du patient
+    J=1;
+    while (J<=25);
+        if Y(J,I) > ymax_training(I,1)
+            ymax_training(I,1)=Y(J,I);
+        end
+        J=J+1;
+    end
+    
+    % on normalise le patient
+    J=1;
+    while (J<=25);
+        Y(J,I) = Y(J,I) / ymax_training(I,1);
+        J=J+1;
+    end
+    
+    I=I+1;
+end
+
+% on récupère les frames qui nous intéressent
+J=1;
+I=1;
+i=1;
+while (I<=18);
+    J=C(I,3);
+    if C(I,3)>0
+        while (J<C(I,2));
+            y_training(i,1)=Y(J,I);
+            i=i+1;
+            J=J+1;
+        end
+    end
+    I=I+1;
+end
+Y_training = y_training;
+
+%creation de X_training
+k=1;
+X_training=[];
+while k<=18
+    if C(k,3)>0
+        X=[0:1/(C(k,2)-C(k,3)):1];
+        X_training = [X_training, X];
+    end
+    k=k+1;
+end
+X_training=X_training';
+%X_training=repmat(X_training,18,1);
+
+
+save('training.mat','X_training','Y_training')

training/C/prepare_models_part1modifie.m

+% build dynamics model (part 1)
+%modele C
+Y=load('ListeDesVolumes.txt');
+y_training=zeros(58,1);
+C=xlsread('points courbes.xls')
+
+% on normalise les patients
+J=1;
+I=1;
+ymax_training=Y;
+ymax_training=zeros(18,1);
+while (I<=18);
+    % on cherche le max du patient
+    J=1;
+    while (J<=25);
+        if Y(J,I) > ymax_training(I,1)
+            ymax_training(I,1)=Y(J,I);
+        end
+        J=J+1;
+    end
+    
+    % on normalise le patient
+    J=1;
+    while (J<=25);
+        Y(J,I) = Y(J,I) / ymax_training(I,1);
+        J=J+1;
+    end
+    
+    I=I+1;
+end
+
+% on récupère les frames qui nous intéressent
+J=1;
+I=1;
+i=1;
+while (I<=18);
+    J=C(I,2);
+    while (J<=25);
+        y_training(i,1)=Y(J,I);
+        i=i+1;
+        J=J+1;
+    end
+    I=I+1;
+end
+Y_training = y_training;
+
+%creation de X_training
+k=1;
+X_training=[];
+while k<=18
+    X=[0:1/(25-C(k,2)):1];
+    X_training = [X_training, X];
+    k=k+1;
+end
+X_training=X_training';
+%X_training=repmat(X_training,18,1);
+
+
+save('training.mat','X_training','Y_training')
\ No newline at end of file