lmfitparabola.py

import numpy as np

from lmfit import Minimizer, Parameters, report_fit

# create data to be fitted
x = np.linspace(0, 15, 301)
data = 2*x*x+ 3*x+4


# define objective function: returns the array to be minimized
def fcn2min(params, x, data):
    """Model a parabola."""
    a = params['a']
    b = params['b']
    c = params['c']
    model = a*x*x + b*x +c 
    return model - data

# create a set of Parameters
params = Parameters()
params.add('a', value=0.0, min=0, max=5)
params.add('b', value=0.0, min=0, max=5)
params.add('c', value=0.0, min=0, max=5)

# do fit, here with leastsq model
minner = Minimizer(fcn2min, params, fcn_args=(x, data))
result = minner.minimize()

# calculate final result
final = data + result.residual

# write error report
report_fit(result)

# try to plot results
try:
    import matplotlib.pyplot as plt
    plt.plot(x, data, 'k+')
    plt.plot(x, final, 'r')
    plt.show()
except ImportError:
    pass