How to Plot for multiple values of a variable

I am new to MATLAB and need to plot for three different numerical values of G and plot the result on a single plot. Is there an easy way to do it by putting a loop, if yes, can you please let me know how should I write it. Thanks in advance!

The code is given below

clc; clf
clear all;
format short; 
syms M;
syms G;

G = input('Enter the value of Gamma of the gas used (for monoatomic=1.66, for diatomic=1.4) : ' );
%Need to plot for different values of G (1.4,1.66, 1.8);  
Molecular_Weight=input('Enter the molecular weight of the gas used in grams/mole (for air=28.97): ' );
%Molecular_Weight=28.97;
R=8314.46261815324/Molecular_Weight;

Throat_Diameter=2.8; 
Throat_Area=3.14159265.*(10.^(-6)).*((Throat_Diameter).^2)/4;
Exit_Diameter=5.76; 
Exit_Area_inMeter=3.14159265.*(10.^(-6)).*((Exit_Diameter).^2)/4;

Diverging_Length= input('Enter the length of diverging section in mm: ' );

DFT=[1:1:Diverging_Length];

M_Local=zeros([1 numel(DFT)]);
for d=1:numel(DFT)
	Distance_from_throat=DFT(d);
	Section_Diameter=Throat_Diameter+((Exit_Diameter-Throat_Diameter).*Distance_from_throat)/Diverging_Length;
	Section_Area=3.14159265.*(10.^(-6)).*((Section_Diameter).^2)/4;
	ARatio=Section_Area/Throat_Area;
	problem.objective = @(M) (1/M.^2).*(((2+(G-1).*M.^2)/(G+1)).^((G+1)/(G-1)))-ARatio.^2;    % Objective function
	problem.solver    = 'fzero';                                                % Find the zero
	problem.options   = optimset(@fzero);                                       % Default options
	% Solve supersonic root
	problem.x0 = [1+1e-6 50];                                                   % Supersonic solver bounds
	M_Local(d) = fzero(problem);    % Solve for supersonic M
end

plot(DFT,M_Local);
title('Distance from Throat vs Mach Number');
xlabel('Distance from Throat (in mm)');
ylabel('Mach Number');

hold on

Answer 1

[Star Strider]

It would likely be easiest to define ‘G’ as a vector:

Gv = [1.4,1.66, 1.8];

and then add an additional loop for it:

for k = 1:numel(Gv)
    G = Gv(k);
    for d=1:numel(DFT)
        Distance_from_throat=DFT(d);
        Section_Diameter=Throat_Diameter+((Exit_Diameter-Throat_Diameter).*Distance_from_throat)/Diverging_Length;
        Section_Area=3.14159265.*(10.^(-6)).*((Section_Diameter).^2)/4;
        ARatio=Section_Area/Throat_Area;
        problem.objective = @(M) (1/M.^2).*(((2+(G-1).*M.^2)/(G+1)).^((G+1)/(G-1)))-ARatio.^2;    % Objective function
        problem.solver    = 'fzero';                                                % Find the zero
        problem.options   = optimset(@fzero);                                       % Default options
        % Solve supersonic root
        problem.x0 = [1+1e-6 50];                                                   % Supersonic solver bounds
        M_Local(d,k) = fzero(problem);    % Solve for supersonic M
    end
end
plot(DFT,M_Local);
title('Distance from Throat vs Mach Number');
xlabel('Distance from Throat (in mm)');
ylabel('Mach Number');
legend(compose('G = %.2f',Gv), 'Location','best')for k = 1:numel(Gv)
    G = Gv(k);
    for d=1:numel(DFT)
        Distance_from_throat=DFT(d);
        Section_Diameter=Throat_Diameter+((Exit_Diameter-Throat_Diameter).*Distance_from_throat)/Diverging_Length;
        Section_Area=3.14159265.*(10.^(-6)).*((Section_Diameter).^2)/4;
        ARatio=Section_Area/Throat_Area;
        problem.objective = @(M) (1/M.^2).*(((2+(G-1).*M.^2)/(G+1)).^((G+1)/(G-1)))-ARatio.^2;    % Objective function
        problem.solver    = 'fzero';                                                % Find the zero
        problem.options   = optimset(@fzero);                                       % Default options
        % Solve supersonic root
        problem.x0 = [1+1e-6 50];                                                   % Supersonic solver bounds
        M_Local(d,k) = fzero(problem);    % Solve for supersonic M
    end
end
plot(DFT,M_Local);
title('Distance from Throat vs Mach Number');
xlabel('Distance from Throat (in mm)');
ylabel('Mach Number');
legend(compose('G = %.2f',Gv), 'Location','best')

.