This repository is a fork of https://github.com/tensorflow/models, using the astronet
part of the Tensorflow model library for training on light curves from the Kepler space telescope.
astronet README - contains instructions on replicating Shallue et al. (2018)
If using the current (2018-04-23) python DEV docker container.
Packages installed with pip:
pip install tensorflow==1.5
pip install numpy --upgrade
pip install pydl
Packages installed with conda:
conda install pandas bazel astropy
When downloading the TCE file, be sure to specifically select the following. By default, the av_training_set column is not selected. You can select it using the select columns
button on the top left of the webpage.
rowid
: Integer ID of the row in the TCE table.kepid
: Kepler ID of the target star.tce_plnt_num
: TCE number within the target star.tce_period
: Period of the detected event, in days.tce_time0bk
: The time corresponding to the center of the first detected event in Barycentric Julian Day (BJD) minus a constant offset of 2,454,833.0 days.tce_duration
: Duration of the detected event, in hours.av_training_set
: Autovetter training set label; one of PC (planet candidate), AFP (astrophysical false positive), NTP (non-transiting phenomenon), UNK (unknown).
NOTE: the column rowid
is actually called loc_rowid
in the .csv file. So either change that to rowid
or change the code to use loc_rowid
in generate_input_records.py