afeinstein20 / eleanor

A tool for light curve extraction from the TESS FFIs.
MIT License
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IndexError for Sector 60 TICs #275

Open zessack opened 5 months ago

zessack commented 5 months ago

Hello! I am running eleanor on a long list of TICs from Sector 60. I have updated eleanor to the most recent main branch.

I am encountering an IndexError on a lot of TICs. An example to reproduce the issue:

import eleanor
star = eleanor.Source(tic=str(197185325), sector=int(60), tc=False, post_dir='.')
data = eleanor.TargetData(source=star, height=15, width=15, bkg_size=31, do_psf=False, do_pca=True)

This produces the following error:

---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-3-36db9dcfd1a9> in <module>
----> 1 data = eleanor.TargetData(source=star, height=15, width=15, bkg_size=31, do_psf=False, do_pca=True)

~/anaconda3/envs/search_env/lib/python3.7/site-packages/eleanor/targetdata.py in __init__(self, source, height, width, save_postcard, do_pca, do_psf, bkg_size, aperture_mode, cal_cadences, try_load, regressors, language)
    229 
    230                 self.get_tpf_from_postcard(source.coords, source.postcard, height, width, bkg_size, save_postcard, source)
--> 231                 self.set_quality()
    232                 self.get_cbvs()
    233 

~/anaconda3/envs/search_env/lib/python3.7/site-packages/eleanor/targetdata.py in set_quality(self)
    856         self.quality = np.array(self.post_obj.quality)
    857 
--> 858         self.quality[np.nansum(self.tpf, axis=(1,2)) == 0] = 128
    859 
    860         bkgvar = np.nanstd(self.bkg_tpf, axis=(1,2))/(np.nansum(self.bkg_tpf, axis=(1,2)))

IndexError: boolean index did not match indexed array along dimension 0; dimension is 8643 but corresponding boolean dimension is 8642

This may be similar to Issue #267. Any ideas on how to go about fixing this issue would be appreciated!

Bucket-Bear commented 3 months ago

I am having this exact issue. Did you happen to figure out a solution to it? Thank you