#!/usr/bin/env python
# coding: utf-8

# # Short demo of interactive fit

# In[ ]:


import numpy as np
from scipy.stats import norm
from iminuit import Minuit, cost

truth = 100.0, 200.0, 0.3, 0.1, 0.7, 0.2


def scaled_cdf(xe, n1, n2, mu1, sigma1, mu2, sigma2):
    return n1 * norm.cdf(xe, mu1, sigma1) + n2 * norm.cdf(xe, mu2, sigma2)


xe = np.linspace(0, 1)
m = np.diff(scaled_cdf(xe, *truth))
n = np.random.default_rng(1).poisson(m)  # generate random histogram

c = cost.ExtendedBinnedNLL(n, xe, scaled_cdf)
m = Minuit(c, *truth)

m.interactive()