Pipeline for testing impact of survey conditions on tomographic redshift distribution

[hangqianjun]

I have put together a draft pipeline in this Jupyter notebook that uses rail modules to generate a test sample of galaxies (rail.creation), apply survey conditions (rail.creation.degradation), and test the impact of different i-band depth on tomographic redshift distributions in terms of the mean and scatter (rail.evaluation?) of the tomographic bin (rail.summarization/tomo-challenge/TXPipe). I will work on turining this into a pipeline class. Suggestions and comments on the pipeline would be most welcome.

One open question in the pipeline is how the tomographic bins are defined. In the pipeline I wrote a dummy function to assign tomographic bins according to SRD, but there are also methods existing in TXPipe that directly takes the output of metadetect. Feedback on this would be helpful.

[hangqianjun]

Currently waiting for the following steps to complete:

• Tomographer PR in rail_base
• Moving obs_cond from rail_attic to rail_astro_tools (?) (depending on the PhotErr package)