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Plotting 3 matrix vs range curves

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s d
s d 2016-1-14
关闭： MATLAB Answer Bot 2021-8-20
Hi everyone,
I have 3 sets of parameter data that I'm attempting to plot against a range of thickness values from 1nm-1um. I have attempted multiple ways of doing this but I believe this way is the closest to retrieving the answer:
clc;clf;
a = [1e-10 7e-10 8e-10];
b = [10e-6 10e-6 10e-6];
for t = 1e-9:1e-9:1000e-9,
Rf = pcu./(w.*t);
end
figure
plot(t,Rf),title('Rf vs. t'),xlabel('t'),ylabel('Rf')
If anyone could give any suggestions or let me know if I'm close to the answer then I'd appreciate it!
Thanks

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回答（1 个）

Kirby Fears
Kirby Fears 2016-1-14
编辑：Kirby Fears 2016-1-14
I don't know what the values of pcu or w are, but here's a simplification that works fine.
t = 1e-9:1e-9:1000e-9;
Rf = (2.*t);
figure();
plot(t,Rf),title('Rf vs. t'),xlabel('t'),ylabel('Rf');
I don't see a need for the for loop in your code. The dot operations will take care of element-wise multiplication and division.
If you have three separate calculations for t and Rf, you can plot each one separately.
  2 个评论
s d
s d 2016-1-14
Thanks for the reply.
Plotting your code is fine. It's when I have the matrix values implemented where the problem lies. Values pcu and w are meant to be a and b (my bad).
I'm basically trying to get 3 separate curves on the same graph for Rf vs. t. It's as though I'm trying to plot this but with 3 sets of values for a and b, as defined in the original post:
clc;clf;
a = 1e-10;
b = 10e-6;
t = 1e-9:1e-9:1000e-9;
Rf = a./(b.*t);
figure
plot(t,Rf),title('Rf vs. t'),xlabel('t'),ylabel('Rf')
Kirby Fears
Kirby Fears 2016-1-14
编辑：Kirby Fears 2016-1-14
Thanks for the clarification. This should do it:
t = (1e-9:1e-9:1000e-9)';
a = repmat([1e-10, 7e-10, 8e-10],size(t,1),1);
b = repmat([10e-6, 10e-6, 10e-6],size(t,1),1);
t = repmat(t,1,size(a,2));
Rf = a./(b.*t);
plot(t,Rf);
title('Rf vs. t');
xlabel('t');
ylabel('Rf');
Both arrays involved in a dot operation need to have the same dimensions. It won't automatically do all combinations for you. Matrix multiplication could be used here, but replicating the rows and columns is more straightforward.

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