Gaussian fit, based on http://stackoverflow.com/a/11507723/323100

gaussianfit.py

import numpy
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt

# Define model function to be used to fit to the data above:
def gauss(x, *p):
    A, mu, sigma = p
    return A*numpy.exp(-(x-mu)**2/(2.*sigma**2))

xdata = numpy.linspace(-5,5,100)
y = gauss(xdata,2,2,0.9)
ydata = y + 0.1 * numpy.random.normal(size=len(xdata))

# Fit
# p0 is the initial guess for the fitting coefficients (A, mu and sigma above)
p0 = [1, 0, 1]
coeff, var_matrix = curve_fit(gauss, xdata, ydata, p0=p0)

plt.plot(ydata, label='Test data')
plt.plot(gauss(xdata, *coeff), label='Gaussian fit')
plt.legend(loc='best')
plt.show()