def get_multiharmonic_periodogram(x, y, err, nh, hfac=3, ofac=10):
model = LombScargle(Nterms=nh)
model.fit(x, y, err)
pers, p = model.periodogram_auto(nyquist_factor=hfac, oversampling=ofac)
return np.power(pers, -1), p
def periodogram():
x = np.array(df['#time'].values.tolist())
y1 = params1[0] * np.sin(params1[1] * x - params1[2]) + params1[3]
y2 = params2[0] * np.sin(params2[1] * x - params2[2]) + params2[3]
model1 = LombScargle().fit(x, y1)
model2 = LombScargle().fit(x, y2)
periods1, power1 = model1.periodogram_auto()
periods2, power2 = model2.periodogram_auto()
plt.title("Periodogram")
plt.plot(periods1, power1, color='red', label='Star 1')
plt.scatter(periods2, power2, label='Star 2')
plt.legend(loc="lower right")
plt.ylabel("Lomb-Scargle Power")
plt.xlabel("Period (Years)")
plt.xlim(2, 5)
plt.show()
return
