Leavitt's Footsteps #21
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View / edit / reply to this conversation on ReviewNB ttdu commented on 2023-08-28T14:32:41Z It might be worth mentioning that we only get back FFIs, since this impacts our later data analysis (no background subtraction)
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View / edit / reply to this conversation on ReviewNB ttdu commented on 2023-08-28T14:32:42Z "Header data unit" |
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View / edit / reply to this conversation on ReviewNB ttdu commented on 2023-08-28T14:32:43Z Good to have this function, we should add something above about "to avoid repetitive code, let's create a function to plot cutouts". We should also maybe explain that without vmax/vmin, we're not going to see very much |
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View / edit / reply to this conversation on ReviewNB ttdu commented on 2023-08-28T14:32:43Z Line #6. plt.xlabel('Image Column',fontsize = 14)
As a thought, do we want to add labeling to our function? We could do something like
Given that this is a beginner Notebook, I wonder if this would be more or less complicated for the student |
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View / edit / reply to this conversation on ReviewNB ttdu commented on 2023-08-28T14:32:44Z citation: https://tess.mit.edu/science/tess-input-catalogue/ (note that as of 28 Aug, the TESS MIT site is down for maintenance) |
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View / edit / reply to this conversation on ReviewNB ttdu commented on 2023-08-28T14:32:45Z I had expressed concern about the weird "striations" in the periodograms we generate below
Looking at this plot, it is obvious to me now that those "striations" are due to the "hockey stick" curve of stray light. If we background subtracted (which is likely out-of-scope for this NB), they would go away. Perhaps we should mention this at some point, or create an exercise |
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View / edit / reply to this conversation on ReviewNB ttdu commented on 2023-08-28T14:32:46Z Maybe here is the place to discuss striation and stray light? In theory, if we background subtracted these points would line up perfectly jrka commented on 2023-08-30T04:04:31Z In addition to the two times this was referenced in the review, I also added reference to it when tpf.interact() is called - very easy to see every pixel getting brighter. |
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View / edit / reply to this conversation on ReviewNB ttdu commented on 2023-08-28T14:32:47Z Strange that some of these are normalized and others are not. Did I miss something obvious in the code?
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View / edit / reply to this conversation on ReviewNB ttdu commented on 2023-08-28T14:32:49Z [link to typical HR diagram] |
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In addition to the two times this was referenced in the review, I also added reference to it when tpf.interact() is called - very easy to see every pixel getting brighter. View entire conversation on ReviewNB |
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Line #1. # Being slow, commented out for now.
I think this was a temporary issue on the MAST side. Seems to be back up to speed now
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aha. the reason why some of these are normalized and others are not is that the "authors" are different. the QLP (quick-look pipeline) generates normalized light curves; there is no "raw flux" to fall back on.
Ideally, for consistency of data reduction techniques, we would pick one TESS pipeline for all of these light curves. Unfortunately, there are only two "authors" in common for this set of TIC IDs: 'GSFC-ELEANOR-LITE' and 'TGLC'. TGLC isn't supported by lightkurve, and the GSFC curves are pretty "raw", in the sense that they have nonsense values like negative flux
potential solutions
- leave it "as-is" and add a disclaimer about the different pipelines
- use GSFC and do a "quick and dirty" sigma clip (it produces decent results with
.remove_outliers(5)) - other solutions at your discretion
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This just in! Lightkurve 2.4.1 now supports TGLC, so we could actually use this
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Great, I changed the instructions to use TGLC
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Line #3. for i in range(len(ticlist)):
do we need "i"? we could do something like
for tic in ticlist:# Get the obs, keep only the first matching
obs = lk.search_lightcurve(tic)
tesslc = obs[0].download()
# Create the periodogram, find period
pgrm = tesslc.to_periodogram()
p_max = pgrm.period_at_max_power
periods.append(p_max.value)
# Plot lc
tesslc.fold(p_max).scatter(label = f"TIC={tic}, Period = {p_max.value:.3f}d");
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Commented back in the query for Gaia data, fixed errors referencing 14 vs 13 length TIC list, fixed errors only saving 7 instead of 8 stars from TIC list.
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