mentionJsonFiles in release notes

SModelS · Jul 31, 2024 · f6856ed · f6856ed
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diff --git a/ReleaseNotes b/ReleaseNotes
@@ -1,4 +1,4 @@
-Release v3.0.0, Wed 24 Jul 2024
+Release v3.0.0, Thu 1 Aug 2024
 =======================================================
 
   * Extension to general SMS topologies using graphs
@@ -8,6 +8,7 @@ Release v3.0.0, Wed 24 Jul 2024
   * We now report negative log likelihoods, instead of likelihoods
   * Added outputFormat option to parameters.ini to allow for writing the output using the old format
   * model.updateParticles and crossSection.getXsecFromSLHAFile can now also supply SLHA strings instead of SLHA filenames as argument
+  * jsonFiles entries in database now allow to specify also pyhf name, and analysis region type
   * Z2parity attribute of particles is not longer needed
   * Introduced centralized database dictionary to decrease redundancies in SMS matching (SMS Dictionary)
   * Clustering of SMS for UL results replaced by a (simple) K-means clustering algorithm (see Clustering)

diff --git a/docs/manual/source/ReleaseUpdate.rst b/docs/manual/source/ReleaseUpdate.rst
@@ -44,6 +44,7 @@ New in Version 3.0.0:
   * Changes in missing topologies (coverage): the grouping of topologies is now done only by final states and ignores the topology structure (see :ref:`missing topologies <finalStateSMS>`)
   * We now report negative log likelihoods, instead of likelihoods 
   * `model.updateParticles <base.html#base.model.Model.updateParticles>`_ and `crossSection.getXsecFromSLHAFile <base.html#base.crossSection.getXsecFromSLHAFile>`_ can now also supply SLHA strings instead of SLHA filenames as argument
+  * `jsonFiles <DatabaseStructure.html#experimental-result-folder>`_ entries in database now allow to specify also pyhf name, and analysis region type 
   * Z2parity attribute of particles is not longer needed
   * Introduced centralized database dictionary to decrease redundancies in SMS matching (see :ref:`SMS Dictionary <smsDictionary>`)
   * Clustering of SMS for UL results replaced by a (simple) K-means clustering algorithm (see :ref:`Clustering <cluster>`)

diff --git a/docs/manual/source/conf.py b/docs/manual/source/conf.py
@@ -286,7 +286,7 @@
 numfig = True
 numfig_format = {'figure' : "Figure %s:"}
 
-nitpicky = True
+nitpicky = False
 
 nitpick_ignore = [('py:class', 'type')]
 nitpick_ignore_regex = [('py:class', 'logging.StreamHandler'),('py:class', 'collections.OrderedDict')]