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Can graphs in Matlab provide a more detailed scale?

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cindyawati cindyawati
cindyawati cindyawati 2023 年 7 月 19 日
回答済み: Steven Lord 2023 年 7 月 19 日
I have 2 different function and I want to combine the plot. In Matlab cannot show the difference plot of 2 function but in excel can show the difference. How to solve that?
This is the function that has been combined
clc;clear;
%input parameter
delta=50;
gamma=75;
K1=10^-4;
K2=5*10^-4;
K3=10^-3;
K4=5*10^-3;
K5=10^-2;
K6=5*10^-2;
Ko=0.1;
n=6;
Oa=10;
Pa=100;
mu_1=10^-3;
mu_2=10^-3;
mu_3=10^-3;
mu_4=10^-3;
mu_5=10^-3;
mu_6=10^-3;
mu_o=10^-4;
mu_p= 10^-5;
%komponen paper 1
Mg = 0.047;
lambdaMf = 2*10^-1;
Fo = 3.36*10^-5;
KFo = 2.58*10^-5;
lambdaMa = 2.3*10^-1;
Ao = 0.14;
KAo = 10^-2;
beta = 10;
epsilon1 = 0.3333;
epsilon2 = 0.8;
lambdaM1Tb = 6*10^-1;
Tb=10^-2;
KTb = 2.5*10^-3;
makro1 = 0.02;
makro2 = 0.02;
dM1= 0.015;
dM2= 0.015;
dtmakro1 = (Mg*(lambdaMf*(Fo/(Fo+KFo))+lambdaMa*(Ao/(Ao+KAo)))*(epsilon1*beta/(beta*(epsilon1+epsilon2)))*makro1)+(lambdaM1Tb*(Tb/(Tb+KTb))*makro1)-dM1*makro1;
dtmakro2 = (Mg*(lambdaMf*(Fo/(Fo+KFo))+lambdaMa*(Ao/(Ao+KAo)))*(epsilon2/(beta*(epsilon1+epsilon2)))*makro2)+(lambdaM1Tb*(Tb/(Tb+KTb))*makro1)-dM2*makro2;
%input initial condition
M1(1)=10;
M2(1)=0;
M3(1)=0;
M4(1)=0;
M5(1)=0;
M6(1)=0;
O(1)=0;
P(1)=0;
M12(1)=10;
M22(1)=0;
M32(1)=0;
M42(1)=0;
M52(1)=0;
M62(1)=0;
O2(1)=0;
P2(1)=0;
%input for time
t(1)=0;
dt=0.01; %time interval
t=0:dt:100; %time span
%input empty array
T=zeros(length(t)+1,1); %empty array for t
M1=zeros(length(t)+1,1); %empty array for M1
M2=zeros(length(t)+1,1); %empty array for M2
M3=zeros(length(t)+1,1); %empty array for M3
M4=zeros(length(t)+1,1); %empty array for M4
M5=zeros(length(t)+1,1); %empty array for M5
M6=zeros(length(t)+1,1); %empty array for M6
O=zeros(length(t)+1,1);
P=zeros(length(t)+1,1);
M12=zeros(length(t)+1,1); %empty array for M1
M22=zeros(length(t)+1,1); %empty array for M2
M32=zeros(length(t)+1,1); %empty array for M3
M42=zeros(length(t)+1,1); %empty array for M4
M52=zeros(length(t)+1,1); %empty array for M5
M62=zeros(length(t)+1,1); %empty array for M6
O2=zeros(length(t)+1,1);
P2=zeros(length(t)+1,1);
sumter=K2*M2+K3*M3+K4*M4+K5*M5;
for j = 1:length(t)
T(j+1)=T(j)+dt;
M1(j+1)=M1(j)+1./(1+exp(-T(j)));
M1(j+1) = M1(j)+(dt*(delta*M1(j+1)*(1-(M1(j+1)/gamma))-2*K1*M1(j+1)*M1(j+1)-M1(j+1)*sumter(j+1))-((Oa-n)*K6*M1(j+1)*M6(j+1))-((Pa-Oa)*Ko*M1(j+1)*O(j+1))-(mu_1*M1(j+1)));
M2(j+1) = M2(j)+(dt*(K1*M1(j)*M1(j)-K2*M1(j)*M2(j))-(mu_2*M2(j+1))-dtmakro1+dtmakro2);
M3(j+1) = M3(j)+(dt*(K2*M1(j)*M2(j)-K3*M1(j)*M3(j))-mu_3*M3(j));
M4(j+1) = M4(j)+(dt*(K3*M1(j)*M3(j)-K4*M1(j)*M4(j))-mu_4*M4(j));
M5(j+1) = M5(j)+(dt*(K4*M1(j)*M4(j)-K5*M1(j)*M5(j))-mu_5*M5(j));
M6(j+1) = M6(j)+(dt*(K5*M1(j)*M5(j)-K6*M1(j)*M6(j))-mu_6*M6(j));
O(j+1) = O(j)+(dt*(K6*M1(j)*M6(j)-Ko*M1(j)*O(j)-mu_o*O(j)));
P(j+1) = P(j)+(dt*(Ko*M1(j)*O(j)-mu_p*P(j)));
M12(j+1) = M12(j)+(dt*(delta*M12(j+1)*(1-(M12(j+1)/gamma))-2*K1*M12(j+1)*M12(j+1)-M12(j+1)*sumter(j+1))-((Oa-n)*K6*M12(j+1)*M62(j+1))-((Pa-Oa)*Ko*M12(j+1)*O2(j+1))-(mu_1*M12(j+1)));
M22(j+1) = M22(j)+(dt*(K1*M12(j)*M12(j)-K2*M12(j)*M22(j))-(mu_2*M22(j+1)));
M32(j+1) = M32(j)+(dt*(K2*M12(j)*M22(j)-K3*M12(j)*M32(j))-mu_3*M32(j));
M42(j+1) = M42(j)+(dt*(K3*M12(j)*M32(j)-K4*M12(j)*M42(j))-mu_4*M42(j));
M52(j+1) = M52(j)+(dt*(K4*M12(j)*M42(j)-K5*M12(j)*M52(j))-mu_5*M52(j));
M62(j+1) = M62(j)+(dt*(K5*M12(j)*M52(j)-K6*M12(j)*M62(j))-mu_6*M62(j));
O2(j+1) = O2(j)+(dt*(K6*M12(j)*M62(j)-Ko*M12(j)*O2(j)-mu_o*O2(j)));
P2(j+1) = P2(j)+(dt*(Ko*M12(j)*O2(j)-mu_p*P2(j)));
end
%figure
%subplot (3,1,1)
figure
%hold on
plot(T,M1,'r', T,M12,'b','Linewidth',2)
legend ('M1', 'M12');
xlabel('time (days)')
ylabel('M1 (gr/ml)')
%subplot (3,1,2)
figure
%hold on
plot(T,M2,'b',T,M22,'r','Linewidth',2)
legend ('M2', 'M22');
xlabel('time (days)')
ylabel('M2 (gr/ml)')
%subplot (3,1,3)
figure
%hold on
plot(T,M3,'g',T,M32,'b','Linewidth',2)
legend ('M3', 'M32');
xlabel('time (days)')
ylabel('M3 (gr/ml)')
%subplot (2,1,2)
figure
%hold on
plot(T,M4,'m',T,M42,'g','Linewidth',2)
legend ('M4', 'M42');
xlabel('time (days)')
ylabel('M4 (gr/ml)')
%subplot (2,1,1)
figure
%hold on
plot(T,M5,'k',T,M52,'g','Linewidth',2)
legend ('M5', 'M52');
xlabel('time (days)')
ylabel('M5 (gr/ml)')
figure
%hold on
plot(T,M6,'m',T,M62,'g','Linewidth',2)
legend ('M6', 'M62');
xlabel('time (days)')
ylabel('M6 (gr/ml)')
%subplot (2,1,1)
figure
%hold on
plot(T,O,'k',T,O2,'g','Linewidth',2)
legend ('O', 'O2');
xlabel('time (days)')
ylabel('O (gr/ml)')
figure
%hold on
plot(T,P,'m',T,P2,'g','Linewidth',2)
legend ('P', 'P2');
xlabel('time (days)')
ylabel('P (gr/ml)')

採用された回答

Steven Lord
Steven Lord 2023 年 7 月 19 日
Let's look at the data you used to create your first graph as I suspect the insights we gain from that will apply to the others as well.
clc;clear;
%input parameter
delta=50;
gamma=75;
K1=10^-4;
K2=5*10^-4;
K3=10^-3;
K4=5*10^-3;
K5=10^-2;
K6=5*10^-2;
Ko=0.1;
n=6;
Oa=10;
Pa=100;
mu_1=10^-3;
mu_2=10^-3;
mu_3=10^-3;
mu_4=10^-3;
mu_5=10^-3;
mu_6=10^-3;
mu_o=10^-4;
mu_p= 10^-5;
%komponen paper 1
Mg = 0.047;
lambdaMf = 2*10^-1;
Fo = 3.36*10^-5;
KFo = 2.58*10^-5;
lambdaMa = 2.3*10^-1;
Ao = 0.14;
KAo = 10^-2;
beta = 10;
epsilon1 = 0.3333;
epsilon2 = 0.8;
lambdaM1Tb = 6*10^-1;
Tb=10^-2;
KTb = 2.5*10^-3;
makro1 = 0.02;
makro2 = 0.02;
dM1= 0.015;
dM2= 0.015;
dtmakro1 = (Mg*(lambdaMf*(Fo/(Fo+KFo))+lambdaMa*(Ao/(Ao+KAo)))*(epsilon1*beta/(beta*(epsilon1+epsilon2)))*makro1)+(lambdaM1Tb*(Tb/(Tb+KTb))*makro1)-dM1*makro1;
dtmakro2 = (Mg*(lambdaMf*(Fo/(Fo+KFo))+lambdaMa*(Ao/(Ao+KAo)))*(epsilon2/(beta*(epsilon1+epsilon2)))*makro2)+(lambdaM1Tb*(Tb/(Tb+KTb))*makro1)-dM2*makro2;
%input initial condition
M1(1)=10;
M2(1)=0;
M3(1)=0;
M4(1)=0;
M5(1)=0;
M6(1)=0;
O(1)=0;
P(1)=0;
M12(1)=10;
M22(1)=0;
M32(1)=0;
M42(1)=0;
M52(1)=0;
M62(1)=0;
O2(1)=0;
P2(1)=0;
%input for time
t(1)=0;
dt=0.01; %time interval
t=0:dt:100; %time span
%input empty array
T=zeros(length(t)+1,1); %empty array for t
M1=zeros(length(t)+1,1); %empty array for M1
M2=zeros(length(t)+1,1); %empty array for M2
M3=zeros(length(t)+1,1); %empty array for M3
M4=zeros(length(t)+1,1); %empty array for M4
M5=zeros(length(t)+1,1); %empty array for M5
M6=zeros(length(t)+1,1); %empty array for M6
O=zeros(length(t)+1,1);
P=zeros(length(t)+1,1);
M12=zeros(length(t)+1,1); %empty array for M1
M22=zeros(length(t)+1,1); %empty array for M2
M32=zeros(length(t)+1,1); %empty array for M3
M42=zeros(length(t)+1,1); %empty array for M4
M52=zeros(length(t)+1,1); %empty array for M5
M62=zeros(length(t)+1,1); %empty array for M6
O2=zeros(length(t)+1,1);
P2=zeros(length(t)+1,1);
sumter=K2*M2+K3*M3+K4*M4+K5*M5;
for j = 1:length(t)
T(j+1)=T(j)+dt;
M1(j+1)=M1(j)+1./(1+exp(-T(j)));
M1(j+1) = M1(j)+(dt*(delta*M1(j+1)*(1-(M1(j+1)/gamma))-2*K1*M1(j+1)*M1(j+1)-M1(j+1)*sumter(j+1))-((Oa-n)*K6*M1(j+1)*M6(j+1))-((Pa-Oa)*Ko*M1(j+1)*O(j+1))-(mu_1*M1(j+1)));
M2(j+1) = M2(j)+(dt*(K1*M1(j)*M1(j)-K2*M1(j)*M2(j))-(mu_2*M2(j+1))-dtmakro1+dtmakro2);
M3(j+1) = M3(j)+(dt*(K2*M1(j)*M2(j)-K3*M1(j)*M3(j))-mu_3*M3(j));
M4(j+1) = M4(j)+(dt*(K3*M1(j)*M3(j)-K4*M1(j)*M4(j))-mu_4*M4(j));
M5(j+1) = M5(j)+(dt*(K4*M1(j)*M4(j)-K5*M1(j)*M5(j))-mu_5*M5(j));
M6(j+1) = M6(j)+(dt*(K5*M1(j)*M5(j)-K6*M1(j)*M6(j))-mu_6*M6(j));
O(j+1) = O(j)+(dt*(K6*M1(j)*M6(j)-Ko*M1(j)*O(j)-mu_o*O(j)));
P(j+1) = P(j)+(dt*(Ko*M1(j)*O(j)-mu_p*P(j)));
M12(j+1) = M12(j)+(dt*(delta*M12(j+1)*(1-(M12(j+1)/gamma))-2*K1*M12(j+1)*M12(j+1)-M12(j+1)*sumter(j+1))-((Oa-n)*K6*M12(j+1)*M62(j+1))-((Pa-Oa)*Ko*M12(j+1)*O2(j+1))-(mu_1*M12(j+1)));
M22(j+1) = M22(j)+(dt*(K1*M12(j)*M12(j)-K2*M12(j)*M22(j))-(mu_2*M22(j+1)));
M32(j+1) = M32(j)+(dt*(K2*M12(j)*M22(j)-K3*M12(j)*M32(j))-mu_3*M32(j));
M42(j+1) = M42(j)+(dt*(K3*M12(j)*M32(j)-K4*M12(j)*M42(j))-mu_4*M42(j));
M52(j+1) = M52(j)+(dt*(K4*M12(j)*M42(j)-K5*M12(j)*M52(j))-mu_5*M52(j));
M62(j+1) = M62(j)+(dt*(K5*M12(j)*M52(j)-K6*M12(j)*M62(j))-mu_6*M62(j));
O2(j+1) = O2(j)+(dt*(K6*M12(j)*M62(j)-Ko*M12(j)*O2(j)-mu_o*O2(j)));
P2(j+1) = P2(j)+(dt*(Ko*M12(j)*O2(j)-mu_p*P2(j)));
end
Let's plot M1 and M12 separately.
figure
plot(T, M1)
figure
plot(T, M12)
Are the values in M12 actually exactly 0?
[minvalue, maxvalue] = bounds(M12)
minvalue = 0
maxvalue = 0
So that looks correct. How about the other variables whose names end with 2?
[minvalue, maxvalue] = bounds(M22)
minvalue = 0
maxvalue = 0
[minvalue, maxvalue] = bounds(M32)
minvalue = 0
maxvalue = 0
[minvalue, maxvalue] = bounds(M42)
minvalue = 0
maxvalue = 0
[minvalue, maxvalue] = bounds(M52)
minvalue = 0
maxvalue = 0
[minvalue, maxvalue] = bounds(M62)
minvalue = 0
maxvalue = 0
[minvalue, maxvalue] = bounds(O2)
minvalue = 0
maxvalue = 0
[minvalue, maxvalue] = bounds(P2)
minvalue = 0
maxvalue = 0
Given the data, all those plots you showed look correct to me. Could you say more about what you believe MATLAB is doing / plotting incorrectly?

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