linear de-trend using curve_fit and sigma

gistfile1.py

from scipy.optimize import curve_fit

def linear(x, m, b):
    return m*x + b

x = np.arange(0,400,1)
y = linear(x, -0.2, 3)
yn = y + np.random.normal(size=len(x))*2
yn[50:350] *= np.random.normal(size=300)

weights = np.zeros_like(yn) + 0.001
weights[50:350] = 1.0

popt, pconv = curve_fit(linear, x, yn, sigma=weights)
y_fit = linear(x,*popt)

plt.figure(figsize=(12,6))
plt.subplot(1,2,1)
plt.plot(x,yn)
plt.plot(y_fit)

plt.subplot(1,2,2)
plt.plot(yn-y_fit)