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

I was a bit puzzled that norm.fit apparently only worked with the expanded list of sampled values. I tried giving it two lists of numbers, or lists of tuples, but it only appeared to flatten everything and threat the input as individual samples. Since I already have a histogram based on millions of samples, I didn't want to expand this if I didn't have to. Thankfully, the normal distribution is trivial to calculate, so...

# histogram is [(val,count)]
from math import sqrt

def normfit(hist):
    n,s,ss = univar(hist)
    mu = s/n
    var = ss/n-mu*mu
    return (mu, sqrt(var))

def univar(hist):
    n = 0
    s = 0
    ss = 0
    for v,c in hist:
        n += c
        s += c*v
        ss += c*v*v
    return n, s, ss

I'm sure this must be provided by the libraries, but as I couldn't find it anywhere, I'm posting this here instead. Feel free to point to the correct way to do it and downvote me :-)