Fitting a histogram with python

Question

I have a histogram

H=hist(my_data,bins=my_bin,histtype=\'step\',color=\'r\')

I can see that the shape is almost gaussian but I would like t

Answer 1

Here is another solution using only matplotlib.pyplot and numpy packages. It works only for Gaussian fitting. It is based on maximum likelihood estimation and have already been mentioned in this topic. Here is the corresponding code :

# Python version : 2.7.9
from __future__ import division
import numpy as np
from matplotlib import pyplot as plt

# For the explanation, I simulate the data :
N=1000
data = np.random.randn(N)
# But in reality, you would read data from file, for example with :
#data = np.loadtxt("data.txt")

# Empirical average and variance are computed
avg = np.mean(data)
var = np.var(data)
# From that, we know the shape of the fitted Gaussian.
pdf_x = np.linspace(np.min(data),np.max(data),100)
pdf_y = 1.0/np.sqrt(2*np.pi*var)*np.exp(-0.5*(pdf_x-avg)**2/var)

# Then we plot :
plt.figure()
plt.hist(data,30,normed=True)
plt.plot(pdf_x,pdf_y,'k--')
plt.legend(("Fit","Data"),"best")
plt.show()

and here is the output.