A clustering redshift estimation code for us folks. For information on the method see Schmidt et al. 2013, Menard et al. 2013, and Rahman et al. 2015, 2016b. Details on this implementation can be found in Morrison et al. 2017
In order to combine the clustering-zs of a set of sub bins into a large bin we need to know how many objects were used in the clustering-z and or what the sum of their weights were.
This issue adds this data to the region pickle file that is an option output of pdf_maker.py.
Store the actual distance of the pairs with pair_maker.py/_compute_bin_values, this should not make any difference in the disk space required. Weights can be determined in pdf_maker, which is handy if I later change my mind about the weight_power.