How to find (x,y) for peaks of a plot?

I am using findpeaks() to get the (x,y) coordinates of the peaks of my plot, but it is giving me the x value in weird numbers. Some research has me thinking that it's giving me the x's in an index(?) but I do not know what that means and how to get it into a usable form. Thanks.

UPDATE:

I think I may understand. When I run the code, it is telling my that my locations of peaks are [180,301]. This number should be closer to 1. Is this telling me that my locations are the 180th and 301st term of the r vector? Is that what indexing means?

Code:

clear
clc
close all

%Constants:
M = 3.98*10^7; %[kg]
m = 6.6*10^5; %[kg]
k_f = 35*10^6; %[N/m]
k_d1 = 580.4*10^3; %[N/m]
k_d2 = 546.1*10^3; %[N/m]
c_d = 37.135*10^3; %[N*s/m]
F_0 = 50*10^3; %[N]

omega = 0.7:0.001:1.2; %[rad/s]
omega_1 = sqrt(k_f/M); %[rad/s]
omega_2_1 = sqrt(k_d1/m); %[rad/s]
omega_2_2 = sqrt(k_d2/m); %[rad/s]
r = omega/omega_1;
alpha1 = omega_2_1/omega_1;
alpha2 = omega_2_2/omega_1;
mu = m/M;
delta_st = F_0/k_f; %[m]
zeta = c_d/(2*m*omega_1);

%Case 1:
for i = 1:length(omega)
    X_M1(i) = F_0/(sqrt((k_f-(M*omega(i)^2))^2));
end

X_m1 = 0;

%Case 2:
for i = 1:length(omega)
    X_M2(i) = abs((alpha1^2-r(i)^2)/(((1-r(i)^2)*(alpha1^2-r(i)^2))-(mu*alpha1^2*r(i)^2)))*delta_st;
end

for i = 1:length(omega)
    X_m2(i) = abs((alpha1^2)/((1-r(i)^2)*(alpha1^2-r(i)^2)-(mu*alpha1^2*r(i)^2)))*delta_st;
end

%Case 3:
for i = 1:length(omega)
    X_M3(i) = sqrt(((alpha2^2-r(i)^2)^2+(2*zeta*r(i))^2)/((((1-r(i)^2)*(alpha2^2-r(i)^2))-(mu*alpha2^2*r(i)^2))^2+((2*zeta*r(i))*(1-r(i)^2-mu*r(i)^2))^2))*delta_st;
end

for i = 1:length(omega)
    X_m3(i) = sqrt(((alpha2^2)^2+(2*zeta*r(i))^2)/(((1-r(i)^2)*(alpha2^2-r(i)^2)-(mu*alpha2^2*r(i)^2))^2+((2*zeta*r(i))*(1-r(i)^2-mu*r(i)^2))^2))*delta_st;
end

%Case 4:
zeta_optimal = sqrt((mu*(3-(sqrt(mu/(mu+2)))))/(8*(1+mu)^3));
tuned_alpha = 1/(1+mu);

for i = 1:length(omega)
    X_M4(i) = sqrt(((tuned_alpha^2-r(i)^2)^2+(2*zeta_optimal*r(i))^2)/((((1-r(i)^2)*(tuned_alpha^2-r(i)^2))-(mu*tuned_alpha^2*r(i)^2))^2+((2*zeta_optimal*r(i))*(1-r(i)^2-mu*r(i)^2))^2))*delta_st;
end

for i = 1:length(omega)
    X_m4(i) = sqrt(((tuned_alpha^2)^2+(2*zeta_optimal*r(i))^2)/(((1-r(i)^2)*(tuned_alpha^2-r(i)^2)-(mu*tuned_alpha^2*r(i)^2))^2+((2*zeta_optimal*r(i))*(1-r(i)^2-mu*r(i)^2))^2))*delta_st;
end

subplot(2,1,1)
plot(r,X_M1,'LineWidth',2)
hold on
plot(r,X_M2,'-.r','LineWidth',2)
hold on
plot(r,X_M3,'.g','LineWidth',1)
hold on
plot(r,X_M4,'--b','LineWidth',1)
axis([0.5 1.5 0 0.05])
ylabel('X_M')
xlabel('r')
legend('Skyscraper w/ no mass damper','Skyscraper w/ undamped mass','Skyscraper w/ damped mass','Optimally Tuned')
subplot(2,1,2)
plot(r,X_m1,'LineWidth',2)
hold on
plot(r,X_m2,'-.r','LineWidth',2)
hold on
plot(r,X_m3,'.g','LineWidth',2)
hold on
plot(r,X_m4,'--b','LineWidth',1)
axis([0.5 1.5 0 0.25])
ylabel('X_m')
xlabel('r')

[pksM1,locsM1] = findpeaks(X_M1);
[pksM2,locsM2] = findpeaks(X_M2);
[pksM3,locsM3] = findpeaks(X_M3);
[pksM4,locsM4] = findpeaks(X_M4);

Answer 1

[Star Strider]

The second output are the vector indices corresponding to the identified peaks. If you want to find the ‘r’ coordinate corresponding the ‘pksM1’, for example in this findpeaks call:

[pksM1,locsM1] = findpeaks(X_M1);

it would be:

rM1 = r(locsM1);

You could then plot the peaks with a marker, for example as:

plot(rM1, pksM1, 'p')

to plot a star at each peak.