This issue can be closed when there is a Jupyter notebook that isolates the estimated photo-zs from the mock catalog and calculates the canonical statistics (bias, intrinsic scatter, cutoff in scatter by which each galaxy would be considered an outlier) on a per-galaxy basis. EDIT: We can also use the magnitude error estimates from the catalog as another dimension for selection criteria.
Once this is done we can make selection cuts on these statistics to focus on galaxies whose photo-zs are the worst without CASTOR data and then quantify the improvement in their photo-zs with CASTOR data..
This issue can be closed when there is a Jupyter notebook that isolates the estimated photo-zs from the mock catalog and calculates the canonical statistics (bias, intrinsic scatter, cutoff in scatter by which each galaxy would be considered an outlier) on a per-galaxy basis. EDIT: We can also use the magnitude error estimates from the catalog as another dimension for selection criteria.
Once this is done we can make selection cuts on these statistics to focus on galaxies whose photo-zs are the worst without CASTOR data and then quantify the improvement in their photo-zs with CASTOR data..