CODEWITHSUNDEEP
r
Harpal
Harpal

Reputation: 12587

R: Fitting Gaussian peaks to density plot data using nls

I'm trying to fit two gaussian peaks to my density plot data, using the following code:

model <- function(coeffs,x)
{
    (coeffs[1] * exp( - ((x-coeffs[2])/coeffs[3])**2 ))

}

y_axis <- data.matrix(den.PA$y)
x_axis <- data.matrix(den.PA$x)
peak1 <- c(1.12e-2,1075,2) # guess for peak 1
peak2 <- c(1.15e-2,1110,2) # guess for peak 2

peak1_fit <- model(peak1,den.PA$x)
peak2_fit <- model(peak2,den.PA$x)

total_peaks <- peak1_fit + peak2_fit
err <- den.PA$y - total_peaks

fit <- nls(y_axis~coeffs2 * exp( - ((x_axis-coeffs3)/coeffs4)**2 ),start=list(coeffs2=1.12e-2, coeffs3=1075, coeffs4=2))
fit2<- nls(y_axis~coeffs2 * exp( - ((x_axis-coeffs3)/coeffs4)**2 ),start=list(coeffs2=1.15e-2, coeffs3=1110, coeffs4=2))


fit_coeffs = coef(fit)
fit2_coeffs = coef(fit2)

a <- model(fit_coeffs,den.PA$x)
b <- model(fit2_coeffs,den.PA$x)



plot(den.PA, main="Cytochome C PA", xlab= expression(paste("Collision Cross-Section (", Å^2, ")")))
lines(results2,a, col="red")
lines(results2,b, col="blue")

This gives me the following plot:

enter image description here

This is where I have my problem. I calculate the fits independently of each other and gaussian peaks are overlaid on on top of each other. I need to feed the err variable into nls which should return 6 coeffs from which I can then re-model the gaussian peaks to fit to the plot.

Upvotes: 1

Views: 3353

Answers (1)

Harpal
Harpal

Reputation: 12587

The answer came to me as soon as i Posted the question. Changing fit to this:

fit <- nls(y_axis~(coeffs2 * exp( - ((x_axis-coeffs3)/coeffs4)**2)) + (coeffs5 * exp( - ((x_axis-coeffs6)/coeffs7)**2)), start=list(coeffs2=1.12e-2, coeffs3=1075, coeffs4=2,coeffs5=1.15e-2, coeffs6=1110, coeffs7=2))

Gives:

enter image description here

An inelegant soloution but it does the job.

Upvotes: 2

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