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"""
Fit comparing leastsq and basin hopping, or other methods
============================================================
This example compares the ``leastsq`` and ``basinhopping`` algorithms
on a decaying sine wave. Note that this can be used to compare other
fitting algorithms too.
"""
import sys
import matplotlib.pyplot as plt
import numpy as np
import lmfit
VALID_METHODS = ['least_squares', 'differential_evolution', 'brute',
'basinhopping', 'ampgo', 'nelder', 'lbfgsb', 'powell', 'cg',
'newton', 'cobyla', 'bfgs', 'tnc', 'trust-ncg', 'trust-exact',
'trust-krylov', 'trust-constr', 'dogleg', 'slsqp', 'emcee',
'shgo', 'dual_annealing']
def sine_decay(x, amplitude, frequency, decay, offset):
return offset + amplitude * np.sin(x*frequency) * np.exp(-x/decay)
x = np.linspace(0, 20, 201)
np.random.seed(2)
ydat = sine_decay(x, 12.5, 2.0, 4.5, 1.25) + np.random.normal(size=len(x), scale=0.40)
model = lmfit.Model(sine_decay)
params = model.make_params(amplitude={'value': 10, 'min': 0, 'max': 1000},
frequency={'value': 2.0, 'min': 0, 'max': 6.0},
decay={'value': 2.0, 'min': 0.001, 'max': 12},
offset=1.0)
# fit with leastsq
result0 = model.fit(ydat, params, x=x, method='leastsq')
print("# Fit using leastsq:")
print(result0.fit_report())
method2 = 'basinhopping'
if len(sys.argv) > 1 and sys.argv[1] in VALID_METHODS:
method2 = sys.argv[1]
# fit with other method
result = model.fit(ydat, params, x=x, method=method2)
print(f"\n#####################\n# Fit using {method2}:")
print(result.fit_report())
# plot comparison
plt.plot(x, ydat, 'o', label='data')
plt.plot(x, result0.best_fit, '+', label='leastsq')
plt.plot(x, result.best_fit, '-', label=method2)
plt.legend()
plt.show()
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