General-Review-(post-GW190814).md

@@ -96,6 +96,59 @@ verbosity arguments:
   -v, --verbose
 ```
 
+### Other Executables
+
+**weigh-mass-samples**
+
+`weigh-mass-samples` records the probability that each mass samples from a single-event posterior is below Mmax (marginalizing over Mmax). Weights are added to a CSV file as a new column. This is what was used Fig. 3 of [arXiv:2007.01372.pdf](https://arxiv.org/pdf/2007.01372.pdf).
+    * *Note*, this includes the prior normalization (Occam factor) associated with simultaneous inference over both Mmax and the object's mass. This is essentially the same factor that appears in [Landry+(2020)](https://arxiv.org/abs/2003.04880) for massive PSR observations.
+    * This calucation still ignores selection effects, though, which could be important as this calculation de facto assumes that the extent of the mass distribution is limited by Mmax and therfore different values of Mmax will lead to different "expected numbers of events".
+
+The full help-string is reproduced below
+
+```
+$ weigh-mass-samples -h
+usage: weigh-mass-samples [-h] [--mass-column MASS_COLUMN]
+                          [--mass-range MASS_RANGE MASS_RANGE]
+                          [--mmax-column MMAX_COLUMN]
+                          [--mmax-weight-column MMAX_WEIGHT_COLUMN]
+                          [--mmax-weight-is-log]
+                          [--mmax-range MMAX_RANGE MMAX_RANGE] [-v]
+                          [--output-weight-column OUTPUT_WEIGHT_COLUMN]
+                          [--outpath OUTPATH]
+                          event_samples mmax_samples
+
+a script that will add weights to a CSV based on the probability that each
+sample is below Mmax. NOTE! This includes the prior normalization associated
+with simulataneous inference over both the EOS and the mass. We assume a flat-
+in-mass prior within the range specified by --mass-range
+
+optional arguments:
+  -h, --help            show this help message and exit
+
+event posterior arguments:
+  event_samples
+  --mass-column MASS_COLUMN
+  --mass-range MASS_RANGE MASS_RANGE
+                        this specifies the prior range used to construct a
+                        simultaneous over the EOS and --mass-column. We assume
+                        a flat prior in --mass-column and update
+                        p(mass_column|Mmax) appropriate. This introduces a
+                        prior normalization within the weight for each EOS.
+
+Mmax posterior arguments:
+  mmax_samples
+  --mmax-column MMAX_COLUMN
+  --mmax-weight-column MMAX_WEIGHT_COLUMN
+  --mmax-weight-is-log
+  --mmax-range MMAX_RANGE MMAX_RANGE
+
+ouptut arguments:
+  -v, --verbose
+  --output-weight-column OUTPUT_WEIGHT_COLUMN
+  --outpath OUTPATH
+```
+
 ## Comparison to Previous Results
 
 **WRITE ME**
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