API Documentation¶

Modules¶

`obiwan.fetch`	Download and unpack tarballs
`obiwan.db_tools`	Query our PostgreSQL Databases at NERSC
`obiwan.draw_radec_color_z`	Draw random location and galaxy properties from Gaussian Mixtures
`obiwan.common`	Commonly used functions
`obiwan.kenobi`	The Monte Carlo code that adds fake galaxiesto images from the Legacy Survey

Tests¶

tests.end_to_end.test_datasets Continuous integration ‘end-to-end’ tests of the Obiwan pipeline

Compute Jobs¶

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`obiwan.qa.visual`	Functions for visualizing the imaging data
`obiwan.qa.number_finished_by_slurm`	Reports the number of completed jobs (tractor.fits files) for a SLURM stdout file
`obiwan.qa.plots_randomsprops_fluxdiff`
`obiwan.qa.cpu_hours`	Computes the number of CPU hours burned using SLURM sacct
`obiwan.qa.heatmaps`
`obiwan.qa.plots_footprint`
`obiwan.qa.plots_common`
`obiwan.qa.unique_ccds_dr3`	Using obiwan outputs, make a table of ‘official’ randoms per-brick - uniform randoms: random ra,dec + geometry cut - obiwan randoms: uniform randoms + recovered by tractor

Deep Learning¶

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`obiwan.dplearn.cnn`
`obiwan.dplearn.create_training`
`obiwan.dplearn.split_testtrain`
`obiwan.dplearn.cnn_working_version`	Trains a CNN on fake and real galaxy images using TensorFlow.