General-Review-(post-GW190814).md

@@ -29,7 +29,50 @@ This review wiki covers the changes to the code based in order to incorporate po
   * [X] population priors are correctly implemented within calls to [utils.population_weights](https://git.ligo.org/reed.essick/mmax-model-selection/-/blob/master/mmax_model_selection/utils.py#L107)
   * [X] reweighting of single-event posterior samples is by population priors is correctly done within the [mmax-model-selection executable](https://git.ligo.org/reed.essick/mmax-model-selection/-/blob/master/bin/mmax-model-selection#L153)
   * [X] code can be run with minimal adjustments by cloning the repo 
-  * [ ] results in [LIGO-P2000216](https://dcc.ligo.org/LIGO-P2000216) / [arXiv:2007.01372](https://arxiv.org/abs/2007.01372) are reproducible
+    - Review statement: The `README` is slightly outdated in the repo, but error messages are informative and getting a working command is straightforward - see "Quantitative Results" section below for commands run and output gotten.
+ ## Quantitative Results
+using `master` at [1f035f47](https://git.ligo.org/reed.essick/mmax-model-selection/-/commit/1f035f47c04ddd4c7f69947b96ff0c759479b68d) I get:
+```
+$ python bin/mmax-model-selection -v etc\combined_PHM.csv etc/mmax_spec.csv --m1-column mass_1 --m2-column mass_2 --mmax-column Mmax --mass-column mass_2_source --d-column luminosity_distance --d-range 0 500 --q-range 0.02 0.25 --mc-range 6.0 7.0 --m-range 1.0 54.5 --population-parameter dmin 0.0 -P dmax 500
+loading mmax samples from: etc/mmax_spec.csv
+pruning mmax samples to fit within
+    mmax in [0.100000, 5.000000)
+Mmax SAMPLES:
+    num=2396
+    mean=2.174838e+00
+    median=2.124839e+00
+    std=1.748310e-01
+    min=1.970043e+00
+    max=2.882590e+00
+loading mass samples from: etc\combined_PHM.csv
+pruning mass samples to fit within prior
+    m1 in [1.000000, 54.500000)
+    m2 in [1.000000, 54.500000)
+    mc in [6.000000, 7.000000)
+    q in [0.020000, 0.250000)
+    d in [0.000000, 500.000000)
+computing prior weights
+    population=LALINF
+    dmax=5.000000e+02
+    dmin=0.000000e+00
+Mass SAMPLES:
+    num=27736
+    mean=2.587310e+00
+    median=2.588220e+00
+    std=5.302449e-02
+    min=2.300970e+00
+    max=2.838526e+00
+marginalizing to compute posteriors and odds ratio
+    Probability: P(m<=Mmax) = 3.464760e-02 +/- 3.212052e-03
+    Odds Ratio : O^{m<Mmax)_{m>Mmax} = 3.589114e-02 +/- 3.446759e-03
+```
+  * [X] this version of the code reproduces the results for GW190814 (housed [here](https://git.ligo.org/reed.essick/mmax-model-selection/-/wikis/GW190814-Review)) reasonably well
+    - Review statement: The results obtained from 1f035f47c04ddd4c7f69947b96ff0c759479b68d are identical to those found in the review of the code used for GW190814.
+| Mmax posterior | previous result | current result |
+| ------ | ------ | ------ |
+| `etc/mmax_spec.csv` | `posterior probability: P(m<=Mmax\|data) = 3.464760e-02 +/- 1.147533e-05 +/- 3.210484e-03` | `P(m<=Mmax) = 3.464760e-02 +/- 3.212052e-03`|
+| `etc/mmax_obs.csv` | `posterior probability: P(m<=Mmax\|data) = 1.037933e-01 +/- 4.245073e-06 +/- 2.037448e-03` | `P(m<=Mmax) = 1.037933e-01 +/- 2.040315e-03`|
+| `etc/just-Mmax\=2.3.csv` | `posterior probability: P(m<=Mmax\|data) = 7.210845e-05 +/- 5.098654e-05 +/- 0.000000e+00` | `P(m<=Mmax) = 7.210845e-05 +/- 5.098654e-05`|
 
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