Expose positivity threshold in the runcard

Created by: scarlehoff

This is the maximum value that the replica's positivity loss can have to get a POS_PASS tag in .fitinfo. By default it has the conservative 1e-6 value, but now it can be changed directly from the runcard as sometimes might not a good idea to be too strict. A comparison below:

I used as baseline the 130920-nnpdf40_jcm_iterated fit from Cameron, for which 66% of the replica passed. This was with a threshold of 1e-6.

I've launched a fit with 1e-4 and another one with 1e-3, the results are below:

For 1e-4, 74% of the replicas passed positivity

https://vp.nnpdf.science/VLGnw8h8SPOVI4HxJ0YaXA==/

For 1e-3, 90% of the replicas passed positivity.

https://vp.nnpdf.science/A1WNzi7oQNewiGzRDF3isA==/

doc/sphinx/source/n3fit/runcard_detailed.rst

@@ -154,6 +154,7 @@ the Neural Network as:
     fitting:
         parameters:
             positivity:
+              threshold: 1e-6
               multiplier: 1.05
               initial: 14.5
               
@@ -164,7 +165,11 @@ In this case ``n3fit`` will set the initial Lagrange multiplier as ``initial`` (
 while the ``multiplier`` will be such that after the last epoch the final Lagrange multiplier 
 equals the ``poslambda`` defined for the dataset.
 
-Note that the effect of the positivity constraints on the fit are still being studied and so this cannot be considered final.
+Finally we have the positivity threshold, which is set to ``1e-6`` by default.
+During the fit, the positivity loss will be compared to this value. If it is above it,
+the positivity won't be considered good (and thus the fit won't stop).
+If the replica reaches the maximum number of epochs with the positivity loss above
+this value, it will be tagged as ``POS_VETO`` and the replica removed from postfit.
      
               
 .. _otheroptions-label: