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It did went into bright outburst mode. I’ve been only able to collect 58 measurements this night due to clouds.
Max
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Hi All,
Strange things going on… The timing of minima keeps sliding. I’ve plotted the minimum a few days ago and it was right on the observed minimum. Tonight it is about 0.2 phase off. There is very little data, as it was shot through the hole in the clouds, but the eclipse was captured. Either this is a bug in my code or the period keeps changing. But the code here is rather straightforward – I get the epoch time and simply add periods to it to plot lines. How can a period drift by 0.2 phase in such a short period of time?
Code:
if self.plot_epoch > 0 and self.plot_period > 0:
extrema = []
current_extrema = self.plot_epoch
light_curve_start = light_curve[“DATE”].min()
light_curve_end = light_curve[“DATE”].max()
while current_extrema < light_curve_end:
if light_curve_end > current_extrema > light_curve_start:
extrema.append(current_extrema)
print(“Ephemeris extrema:”, current_extrema)
ax0.axvline(current_extrema – 2400000.50, color=”green”, linestyle=’–‘)
current_extrema = current_extrema + self.plot_periodMax
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Hmmm…that is very odd Max. Could it be the recent dip is a random fluctuation rather than an eclipse?
Eclipses No(s): 94
State: QuiescenceThe eclipse minima definitely has shifted or there is an error in how I am calculating minima. I am puzzled. Can O-C analysis be done in Peranso or some other software?
Max
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Period analysis can be performed using one of Peranso spectrum analysis tools. But these analyse the data globally, resulting in significant periods being identified, rather than calculating the ToMin that would be required for O-C analysis.
Just double-checked my minima calculation: MetroPSF provides the same ephemeris as Peranso, so looks like there is something going on with periods here. I just wonder if there’s an automated way to identify observed minima of all ~ 90 eclipses we have, or is manual the only way? Anyone brave enough to do O-C analysis? 🙂
Max
Eclipses No(s): 95
State: QuiescenceTypical U/N/A eclipse for this state.
Max
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Thinking how to automate ToM detection for the data collected so far, I have tried fitting a Gaussian function and finding its minimum – see screenshots attached for the last eclipse recorded. Unfortunately, this method is very sensitive to the data boundaries if the data is noisy. If I include more points to the left or right, I get a different curve fit. Even the Kwee-van Woerden method displays the same sensitivity in Peranso. Attached are a few examples. I was thinking to try to find ToM automatically using some predefined phase shift, say, delta phi = 0.2, from calculated minima to set search boundaries, but the choice of delta phi produces different ToM results with both Gaussian fits and the KvW.
Max
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OK, I have managed to do Gaussian fits. First, I define a delta phi search region, then identify the faintest magnitude within the search region, smooth out the noise, determine eclipse well and then fit a Gaussian curve to the well. Presenting the first O-C table. Looks like it’s linear. ANOVA period determined incorrectly?
Max
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Eclipses No(s): 96
State: Quiescence
U/H?/PEHAttachments:
Eclipses No(s): 97
State: Rising
U/N/A-type eclipse.Attachments:
Flat O-C (ignore a few outliers) with P=0.188644 d.
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Eclipses No(s): 98
State: Quiescent.
U/N/A-type eclipse.Attachments:
These are exactly the cases where the algorithm has failed to fit a Gaussian due to noise or partial data. I also need to resample the data to a finer grid, as described by KvW, to refine the result.
Eclipses No(s): 100 (didn’t show a pic for 99th, partial data)
State: Outburst
U/L/S-type eclipse.Attachments:
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