flaredetector: util: remove double sine fit
it nnever fits better than a polynomial, and often takes a lot longer to compute
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@@ -86,30 +86,11 @@ def convertStarndardIndexToFoldedIndex(foldedLc, standardIndex):
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def singleSine(t, A, w, p, c):
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def singleSine(t, A, w, p, c):
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return A * np.sin(w*t + p) + c
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return A * np.sin(w*t + p) + c
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def doubleSine(t, A1, w1, p1, c1, A2, w2, p2, c2, split1, split2):
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y = np.zeros_like(t)
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m1 = t < split1
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m2 = (t >= split1) & (t < split2)
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m3 = t >= split2
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y[m1] = A1 * np.sin(w1 * t[m1] + p1) + c1
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y[m2] = A2 * np.sin(w2 * t[m2] + p2) + (A1 * np.sin(w1 * split1 + p1) + c1 - A2 * np.sin(w2 * split1 + p2))
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y[m3] = A1 * np.sin(w1 * t[m3] + p1) + (A2 * np.sin(w2 * split2 + p2) + (A1 * np.sin(w1 * split1 + p1) + c1 - A2 * np.sin(w2 * split1 + p2)) - A1 * np.sin(w1 * split2 + p1))
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return y
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def fitSingleSine(phase, flux):
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def fitSingleSine(phase, flux):
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initGuess = [np.ptp(flux)/2, 2 * np.pi / (np.max(phase) - np.min(phase)), 0, np.mean(flux)]
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initGuess = [np.ptp(flux)/2, 2 * np.pi / (np.max(phase) - np.min(phase)), 0, np.mean(flux)]
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popt, _ = curve_fit(singleSine, phase, flux, p0=initGuess, maxfev=100000)
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popt, _ = curve_fit(singleSine, phase, flux, p0=initGuess, maxfev=100000)
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return singleSine(phase, *popt)
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return singleSine(phase, *popt)
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def fitDoubleSine(phase, flux):
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initSplit1 = abs(phase[0]) * 2 / 3 + phase[0]
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initSplit2 = abs(phase[0]) * 4 / 3 + phase[0]
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initGuess = [np.ptp(flux) / 2, 2 * np.pi / (np.max(phase) - np.min(phase)), 0, np.mean(flux),
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np.ptp(flux) / 2, 2 * np.pi / (np.max(phase) - np.min(phase)), 0, np.mean(flux),
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initSplit1, initSplit2]
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popt, _ = curve_fit(doubleSine, phase, flux, p0=initGuess, maxfev=100000)
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return doubleSine(phase, *popt)
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def fitPolynomial(phase, flux, degree):
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def fitPolynomial(phase, flux, degree):
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return sum(p * phase**i for i, p in enumerate(Polynomial.fit(phase, flux, degree).convert().coef))
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return sum(p * phase**i for i, p in enumerate(Polynomial.fit(phase, flux, degree).convert().coef))
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@@ -133,41 +114,24 @@ def getFoldedBestFit(foldedLc):
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phase = foldedLc.phase[filt].value
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phase = foldedLc.phase[filt].value
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flux = flux[filt]
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flux = flux[filt]
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#popt, pcov = curve_fit(sine, phase, flux[filt], maxfev=100000)
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#popt, pcov = curve_fit(sine, phase, flux[filt], maxfev=100000)
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import time
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start = time.time()
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singleFit = fitSingleSine(phase, flux)
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singleFit = fitSingleSine(phase, flux)
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singleTime = time.time() - start
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start = time.time()
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doubleFit = fitDoubleSine(phase, flux)
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doubleTime = time.time() - start
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start = time.time()
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polyFit = fitPolynomial(phase, flux, 10)
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polyFit = fitPolynomial(phase, flux, 10)
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polyTime = time.time() - start
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singleRSS = compureRSS(singleFit, flux)
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singleRSS = compureRSS(singleFit, flux)
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doubleRSS = compureRSS(doubleFit, flux)
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polyRSS = compureRSS(polyFit, flux)
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polyRSS = compureRSS(polyFit, flux)
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singleAIC = computeAIC(singleRSS, 4, len(flux))
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singleAIC = computeAIC(singleRSS, 4, len(flux))
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singleBIC = computeBIC(singleRSS, 4, len(flux))
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singleBIC = computeBIC(singleRSS, 4, len(flux))
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doubleAIC = computeAIC(doubleRSS, 10, len(flux))
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doubleBIC = computeBIC(doubleRSS, 10, len(flux))
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polyAIC = computeAIC(polyRSS, 10, len(flux))
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polyAIC = computeAIC(polyRSS, 10, len(flux))
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polyBIC = computeBIC(polyRSS, 10, len(flux))
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polyBIC = computeBIC(polyRSS, 10, len(flux))
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if (singleAIC < doubleAIC and singleAIC < polyAIC and singleBIC < doubleBIC and singleBIC < polyBIC):
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if (singleAIC < polyAIC and singleBIC < polyBIC):
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print("Single sine preferred")
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print("Single sine preferred")
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sineFit = singleFit
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sineFit = singleFit
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elif (doubleAIC < singleAIC and doubleAIC < polyAIC and doubleBIC < singleBIC and doubleBIC < polyBIC):
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print("Double sine preferred")
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sineFit = doubleFit
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else:
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else:
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print("Polynomial preferred")
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print("Polynomial preferred")
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sineFit = polyFit
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sineFit = polyFit
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print("Single sine time: ", singleTime)
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print("Double sine time: ", doubleTime)
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print("Polynomial time: ", polyTime)
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sineFit *= multi
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sineFit *= multi
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return phase, sineFit
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return phase, sineFit
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