import myFitter as mf
import matplotlib.pyplot as plt
import scipy.stats as stats
import sys
import numpy as np
import random

# Import our example model.
from mymodel import MyModel

# Set random seed to get reproducable results
random.seed(1234)
np.random.seed(1234)

# To find the global minimum of the chi-square function we first randomly
# sample the model's parameter space. The points with the smallest chi-square
# values are then used for local (gradient search) minimisations.

# Create an instance of MyModel.
model = MyModel()

# Create a Fitter object to fit the model.
fitter = mf.Fitter(model)

# Sample 100 points. 
fitter.sample(100)

# Try 5 minimisations to (hopefully) find the global minimum.
globalmin = fitter.fit(tries=5)
print globalmin