Hi. Has anybody here any experience with SciPy? I'm trying to get SciPy to adjust a gaussian function to some data. For more details its the photopeak of Co60. This is what I do: Code (Text): import numpy as np from scipy.optimize import curve_fit # counts is a numpy array which holds the number of counts for each channel # start is the position in the count array where the peak starts, and # end is the position where the peak ends, both guesstimated by eye # define the gaussian function gauss = lambda x, u, v: (1 / (v*np.sqrt(2*np.pi)) * np.exp(-(x-u)**2/(2*v**2))) # create the space over which the gaussian should be fitted x = np.linspace(start, end, end - start) # the initial parameters, estimated from the start and end positions a0 =[ (start + end)/2, (end - start)/(4*np.log(2))] # fit the gaussian function over the interval x to the datapoints counts[data:end] fit = curve_fit(f, x, counts[start:end], a0) mean = fit var = fit The result is not what I would expect, though, though: The green line is my fit, the blue one the original data. The gaussian should b much wider! What am I doing wrong? Thank you for your time.