index out of bounds because numel(y)=1.
%#####Optimal Experimental Design based on the Fisher Information Matrix####%#####The NF-kB model with 24 states and 64 parameters######################
clc;
close all;
clear all;
format long;
parameters_hoff; % parametrization of ODE's and simulation times
IKK_normal=0.9;%the initial concentration of IKK
para=;%the id of parameters analysed
for k=1:100
Y01(1)=IKK_normal*k/10;
IKK(k)=Y01(1);
tspan=;
=ode15s(@model_hoff,tspan,Y01,[],par,Source);
%%The local sensitivity analysis method is used to gain the absolute sensitivity matrix
error=10;%input gain value
disp('please wait......')
abso_s=[];%the absolute sensitivity matrix
%%the local sensitivity analysis using the infite difference method%%%%%%%%
for j=1:length(para)
i=para(j);
%parameter i is decreased with error%
par(i,1)=par(i,1)*(1-error/100);
%############ IKK on ####################################
=ode15s(@model_hoff,tspan,Y01,[],par,Source);
%parameter i is returned to its original value
par(i,1)=par(i,1)/(1-error/100);
%parameter i is increased with 1error%
par(i,1)=par(i,1)*(1+error/100);
%############ IKK on ####################################
=ode15s(@model_hoff,tspan,Y01,[],par,Source);
%parameter i is returned to its original value
par(i,1)=par(i,1)/(1+error/100);
%the absolute sensitivity S(i,j)=/(2*error%*p)
S=(Y2-Y1)/(2*par(i,1)*error/100);
abso_s=; %the absolute sensitivity matrix of the system output states x9 w.r.t the i-th parameter
end
relative_error=0.05;%the relative error of the measure value
absolute_error=0.001; %the absolute error of the measure value
cova_v=[]; %the error covariance matrix
v=[]; %the diagnoal elements of the error covariance matrix
for j=9
for i=1:max(size(Y))
sigma(:,i)=relative_error*Y(i,j)+absolute_error;
end
v=;
end
cova_v=diag(v.^2);
%the Fisher information matrix FIM
FIM=abso_s'*inv(cova_v)*abso_s;
=eig(FIM); %to calculate the eigenvalue of FIM
for j=1:length(para)
lambda(j)=lam(j,j); %the eigenvalue lamda of FIM
end
%Optimal experimental design w.r.t initial value of IKK
oed_a(k)=trace(inv(FIM)); %A-optimal criterion
oed_d(k)=det(FIM); %D-optimal criterion
oed_e(k)=min(lambda); %E-optimal criterion
oed_me(k)=max(lambda)/min(lambda);%Modified E-optimal criterion
end
%################# PLOTTING ###############################
figure
plot(IKK,oed_a,'r-');
hold on;
=min(oed_a);
IKK1=b/10*IKK_normal*ones(size(oed_a));
plot(IKK1,oed_a,'b--');
text(0.1,2e-3,['IKK=' num2str(b/10*IKK_normal) '\muM']);
xlabel('Initial concentration of IKK (\muM)');
ylabel('Trace(FIM^-^1)');
legend('A-optimal criterion');
figure
plot(IKK,oed_d,'r-');
hold on;
=max(oed_d);
IKK1=b/10*IKK_normal*ones(size(oed_d));
plot(IKK1,oed_d,'b--');
text(0.1,10e25,['IKK=' num2str(b/10*IKK_normal) '\muM']);
xlabel('Initial concentration of IKK (\muM)');
ylabel('Det(FIM)');
legend('D-optimal criterion');
figure
plot(IKK,oed_e,'r-');
hold on;
=max(oed_e);
IKK1=b/10*IKK_normal*ones(size(oed_e));
plot(IKK1,oed_e,'b--');
text(0.1,5e6,['IKK=' num2str(b/10*IKK_normal) '\muM']);
xlabel('Initial concentration of IKK (\muM)');
ylabel('\lambda_m_i_n(FIM)');
legend('E-optimal criterion');
figure
plot(IKK,oed_me,'r-');
hold on;
=min(oed_me);
IKK1=b/10*IKK_normal*ones(size(oed_me));
plot(IKK1,oed_me,'b--');
text(0.1,8e5,['IKK=' num2str(b/10*IKK_normal) '\muM']);
xlabel('Initial concentration of IKK (\muM)');
ylabel('\lambda_m_a_x(FIM)/\lambda_m_i_n(FIM)');
legend('modified E-optimal criterion');
%######################################################################################################
%######################################################################################################
另外
parameter_hoff
%######################################################################################################
%######################################################################################################
num=600; %the number of sampling
%############## Simulation time points ##################################
t0=0; %time when IKK is being introduced into the system
tw=6000; %length of IKK stimulation
tau=(tw-t0)/num; %defines the period (in seconds) in between to successive data points
%############### Initial condition for total NF-kB ######################
y0=zeros(1,10); %Initial condition set to zero for each reaction participant
NF=0.9;
EF=1.5e-5;
SF=0.8;
y0(8)=NF; %NF-kB is given in cytoplasm
y0(1)=1.5e-5;
y0(6)=0.8;
Source=1;
%############### Parametrization for system of ODE's ####################
par=zeros(11,1);
par(1,1)=100000;
par(2,1)=1000;
par(3,1)=100;
par(4,1)=10000;
par(5,1)=50000;
par(6,1)=200;
par(7,1)=1000;
par(8,1)=20000;
par(9,1)=5000;
par(10,1)=100;
par(11,1)=500;
%######################################################################################################
%######################################################################################################
model_hoff
%######################################################################################################
function dy=model_hoff(t,y,par,Source)
dy=zeros(10,1);
par(1,1) = 100000;
par(2,1)= 1000;
par(3,1) = 100;
par(4,1)= 10000;
par(5,1) = 50000;
par(6,1)= 200;
par(7,1) = 1000;
par(8,1)= 20000;
par(9,1)= 5000;
par(10,1)= 100;
par(11,1) = 500;
dy(1)=-par(1,1)*y(1)*y(6)+par(2,1)*y(2)+par(7,1)*y(4)-par(8,1)*y(1)*y(9)+par(11,1)*y(5);
dy(2)=par(1,1)*y(1)*y(6) - par(2,1)*y(2) - par(3,1)*y(2) + par(4,1)*y(3)*y(7);
dy(3)=par(3,1)*y(2) - par(4,1)*y(3)*y(7) - par(5,1)*y(3)*y(8) + par(6,1)*y(4) - par(9,1)*y(3) + par(10,1)*y(5);
dy(4)=par(5,1)*y(3)*y(8) - par(6,1)*y(4) - par(7,1)*y(4) + par(8,1)*y(1)*y(9);
dy(5)=par(9,1)*y(3) - par(10,1)*y(5) - par(11,1)*y(5);
dy(6)=-par(1,1)*y(1)*y(6) + par(2,1)*y(2);
dy(7)=par(3,1)*y(2) - par(4,1)*y(3)*y(7);
dy(8)=-par(5,1)*y(3)*y(8) + par(6,1)*y(4);
dy(9)=par(7,1)*y(4) - par(8,1)*y(1)*y(9);
dy(10)=par(11,1)*y(5);
%######################################################################################################
%######################################################################################################
怎么错了？希望帮下忙
谢谢！！！ 回复 1 # lphtoby 的帖子
出现的错误是这样的
??? Attempted to access y(6); index out of bounds because numel(y)=1.
Error in ==> model_hoff at 17
dy(1)=-par(1,1)*y(1)*y(6)+par(2,1)*y(2)+par(7,1)*y(4)-par(8,1)*y(1)*y(9)+par(11,1)*y(5);
Error in ==> funfun\private\odearguments at 110
f0 = feval(ode,t0,y0,args{:}); % ODE15I sets args{1} to yp0.
Error in ==> ode15s at 227
[neq, tspan, ntspan, next, t0, tfinal, tdir, y0, f0, odeArgs, ...
Error in ==> IKK_optimal at 22
=ode15s(@model_hoff,tspan,Y01,[],par,Source);
衷心感谢帮忙！！！ 本帖最后由 john152 于 2011-3-20 20:21 编辑
这问题提的
直接上来就是一大段程序
就算是让别人帮你改程序，你也得告知这是什么样的程序，是干嘛的吧？ 你可以试试这样：
function dy=model_hoff(t,y,par,Source)
dy=zeros(10,1)
y = zeros(10 , 1) ; % 加上去的！
我没试，你试试！ 回复 3 # john152 的帖子
这是优化设计的程序
回复 3 # john152 的帖子
一共10个状态 11个参数 初始值已经知道谢谢！！ 回复 4 # zhouyang664 的帖子
首先谢谢你的帮助！！
我加上
y=zero(10,1)
y(1)=1.5e-5;
y(2)=0;
y(3)=0;
y(4)=0;
y(5)=0;
y(6)=0.8;
y(7)=0;
y(8)=0.9;
y(9)=0;
y(10)=0; %赋予初始值
结果运行提示为
??? Error using ==> funfun\private\odearguments
Solving MODEL_HOFF requires an initial condition vector of length 10.
Error in ==> ode15s at 227
[neq, tspan, ntspan, next, t0, tfinal, tdir, y0, f0, odeArgs, ...
Error in ==> IKK_optimal at 22
=ode15s(@model_hoff,tspan,Y01,[],par,Source);
希望你有时间看看 行吗？
在此感谢您的帮忙！！！ 试了试，没整出来，没有太多时间，还是楼主自己好好整整吧！ 楼主现在整明白了吗？问题解决了没？ ??? Attempted to access y(6); index out of bounds because numel(y)=1.
报错都已经告知y仅为纯量, 那来的y(6), y(5) ... 你好我跟你的问题机会一样请问你的解决了吗
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