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Drop TESS rows with negative or NaN flux #213

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Jan 18, 2024
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Drop TESS rows with negative or NaN flux #213

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11 changes: 8 additions & 3 deletions light_curves/code_src/TESS_Kepler_functions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -76,6 +76,14 @@ def TESS_Kepler_get_lightcurves(sample_table, radius):
# convert to Pandas
lcdf = lightcurve.to_pandas().reset_index()

# record band name
filtername = clean_filternames(lightcurve)

# filter out TESS negative fluxes (non-detections) and NaNs
# https://tess.mit.edu/public/tesstransients/pages/readme.html
if filtername == "TESS":
lcdf = lcdf.loc[lcdf.flux > 0]

# these light curves are too highly sampled for our AGN use case, so reduce their size
# by choosing only to keep every nth sample
nsample = 30
Expand All @@ -92,9 +100,6 @@ def TESS_Kepler_get_lightcurves(sample_table, radius):
flux_lc = lcdf_small.flux #in electron/s
fluxerr_lc = lcdf_small.flux_err #in electron/s

# record band name
filtername = clean_filternames(lightcurve)

# put this single object light curves into a pandas multiindex dataframe
# fluxes are in units of electrons/s and will be scaled to fit the other fluxes when plotting
dfsingle = pd.DataFrame(dict(flux=flux_lc, err=fluxerr_lc, time=time_lc, objectid=row["objectid"], band=filtername,label=row["label"])).set_index(["objectid", "label", "band", "time"])
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