for file in files:
fitsTable = fits.open(file, memmap=True)
objName = fitsTable[0].header['OBJECT']
print("\nReading in " + objName + " Filename: " + file)
try:
curveTable = Table(fitsTable[1].data).to_pandas()
except:
print('*************** ERROR ***************')
f = open('errors.txt', 'a')
f.write(file + '\n')
f.close()
else:
curveData = curveTable.loc[curveTable['QUALITY'] == 0].dropna(
subset=['TIME']).dropna(subset=['PDCSAP_FLUX']).copy()
curveData = curveTable.filter(
['TIME', 'PDCSAP_FLUX', 'PDCSAP_FLUX_ERR'])
idx = np.where(
(curveData['TIME'][1:] - curveData['TIME'][:-1]).isnull())[0]
idxL = idx[np.where(idx[1:] - idx[:-1] > 1)]
idxR = idx[np.where(idx[1:] - idx[:-1] > 1)[0] + 1]
for badDataPoint in idxL:
# Set data points to the right to null
r = range(badDataPoint + 1, badDataPoint + 501)
try:
curveData.loc[r, 'PDCSAP_FLUX'] = None
curveData.loc[r, 'TIME'] = None
except:
pass
