reflect the WDL model update in Stockfish (#184)

Readme.md

@@ -169,7 +169,8 @@ together with plots of `win_rate(x)`, `draw_rate(x)` and `loss_rate(x)`
 for the fitted `a=p_a(58)` and `b=p_b(58)`. 
 Finally, the bottom left plot shows the collection of
 all the values of `a(mom)` and `b(mom)`, together with plots of the two
-polynomials `p_a` and `p_b`.
+polynomials `p_a` and `p_b`. For comparison it also includes a plot of
+the polynomial `p_a` that was used in the WDL model of the input data.
 
 ---
 [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

scoreWDL.py

@@ -710,7 +710,7 @@ def save(self):
 
     if args.NormalizeToPawnValue is None:
         if args.NormalizeData is None:
-            args.NormalizeData = '{"momType": "material", "momMin": 10, "momMax": 78, "momTarget": 58, "as": [-185.71965483,504.85014385,-438.58295743,474.04604627]}'
+            args.NormalizeData = '{"momType": "material", "momMin": 10, "momMax": 78, "momTarget": 58, "as": [-150.77043883,394.96159472,-321.73403766,406.15850091]}'
     else:
         assert (
             args.NormalizeData is None

updateWDL.sh

@@ -5,7 +5,7 @@ set -e
 
 # set range of commits to be considered for the WDL fitting, and other options
 # by default we start from the most recent WDL model change and go to master
-default_firstrev=9b92ada935ddf920491156be22f609afaca4d840
+default_firstrev=6fc7da44ad9c7e2ba6062d5c79daafd29a4dcd6f
 default_lastrev=HEAD
 default_materialMin=10
 firstrev=$default_firstrev