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