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#!/usr/bin/env python
from matplotlib import pyplot as plt
import numpy as np
import lmfit
# construct data
x = np.linspace(-4, 4)
y = np.exp(-x**2)
noise = np.random.randn(x.size) * 0.1
y += noise
# define model and fit
model_gaussian = lmfit.models.GaussianModel()
model_gaussian.guess(y, x=x)
fit_gaussian = model_gaussian.fit(y, x=x, weights=1/noise**2)
# plot the with with customization
fig, gridspec = fit_gaussian.plot(fig_kws=dict(figsize=[8, 7]),
ax_fit_kws=dict(title='The gaussian fit'),
initfmt='k:', datafmt='ks',
fit_kws=dict(lw=2, color='red'),
data_kws=dict(ms=8, markerfacecolor='white'))
fig.set_tight_layout(True)
plt.show()
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