Fix missing protobuf messages for BetaGG hierarchy

src/proto/algorithm_state.proto

@@ -26,7 +26,7 @@ message AlgorithmState {
       LinRegUniLSState lin_reg_uni_ls_state = 4; // State of a linear regression univariate location-scale family
       Vector general_state = 5; // Just a vector of doubles
       FAState fa_state = 6; // State of a Mixture of Factor Analysers
-
+      SRState sr_state = 7; // State of a Mixture of Beta distributions
     }
     int32 cardinality = 3; // How many observations are in this cluster
   }
@@ -45,6 +45,7 @@ message AlgorithmState {
       MultiNormalIGDistribution lin_reg_uni_state = 4;
       NxIGDistribution nnxig_state = 5;
       FAPriorDistribution fa_state = 7;
+      GamGamDistribution gg_state = 8;
     }
   }
   HierarchyHypers hierarchy_hypers = 5; // The current values of the hyperparameters of the hierarchy

src/proto/distribution.proto

@@ -95,3 +95,10 @@ message MultiNormalIGDistribution {
   double shape = 3;
   double scale = 4;
 }
+
+message GamGamDistribution {
+  double a_shape = 1;
+  double a_rate = 2;
+  double b_shape = 3;
+  double b_rate = 4;
+}

src/proto/hierarchy_id.proto

@@ -14,4 +14,5 @@ enum HierarchyId {
     FA = 5; // Factor Analysers
     NNxIG = 6; // Normal - Normal x Inverse Gamma
     PythonHier = 7; // Generic python hierarchy
+    BetaGG = 8; // Beta - GammaGamma hierarchy
 }

src/proto/hierarchy_prior.proto

@@ -123,3 +123,12 @@ message PythonHierPrior{
     Vector values = 1; // values are modified from python
   }
 }
+
+/*
+ * Prior for the parameters of the base measure in a Beta - GammaGamma hierarchy
+ */
+message GGPrior {
+  oneof prior {
+    GamGamDistribution fixed_values = 1;
+  }
+}

src/proto/ls_state.proto

@@ -37,3 +37,8 @@ message FAState {
   Matrix eta = 3;
   Matrix lambda = 4;
 }
+
+message SRState {
+  double shape = 1;
+  double rate = 2;
+}