updated unification

decomverse · Nov 11, 2020 · 7f271cb · 7f271cb
1 parent 8964a73
commit 7f271cb
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Showing 2 changed files with 4 additions and 4 deletions.
diff --git a/R/main.R b/R/main.R
@@ -97,7 +97,7 @@ run.ACTIONet <- function(ace, k_max = 30, min.cells.per.arch = 2, min_specificit
 
 
     # Identiy equivalent classes of archetypes and group them together
-	unification.out = unify_archetypes_with_ACTIONet(G = G, S_r = S_r, C_stacked = pruning.out$C_stacked, H_stacked = pruning.out$H_stacked, sensitivity = unification_sensitivity, alpha = unification_alpha, thread_no = thread_no)    
+	unification.out = unify_archetypes(S_r = S_r, C_stacked = pruning.out$C_stacked, H_stacked = pruning.out$H_stacked, sensitivity = unification_sensitivity)    
 
 
 	Ht_unified = as(Matrix::t(unification.out$H_unified), "sparseMatrix")
@@ -279,7 +279,7 @@ rerun.archetype.aggregation <- function(ace, data_slot = "logcounts",
     H_stacked = Matrix::t(as.matrix(colMaps(ace)[["H_stacked"]]))
     G = colNets(ace)[["ACTIONet"]]
 
-	unification.out = unify_archetypes_with_ACTIONet(G = G, S_r = S_r, C_stacked = C_stacked, H_stacked = H_stacked, sensitivity = unification_sensitivity, alpha = unification_alpha, thread_no = thread_no)    
+	unification.out = unify_archetypes(S_r = S_r, C_stacked = C_stacked, H_stacked = H_stacked, sensitivity = unification_sensitivity)    
 
 
     R.utils::printf("%d states\n", length(unique(unification.out$assigned_archetype)))

diff --git a/src/ACTIONet/archetype_unification/unification.cc b/src/ACTIONet/archetype_unification/unification.cc
@@ -121,7 +121,7 @@ namespace ACTIONet {
 		mat Wg = cor(arch_S_r);
 		mat Hg = computeFullSim(arch_H_stacked, 1);
 
-		mat G0 = Wg % Hg;				
+		mat G0 = arma::pow(Wg, 9); // % Hg;				
 		sp_mat G = sp_mat(G0);
 
 		uvec initial_clusters_uvec(G.n_rows);
@@ -137,7 +137,7 @@ namespace ACTIONet {
 			v(idx) = ones(idx.n_elem);
 			C_arch.col(i) = v;
 		}
-		uvec selected_clusters = find(1 < sum(C_arch));
+		uvec selected_clusters = find(2 < sum(C_arch));
 		C_arch = C_arch.cols(selected_clusters);
 
 		mat C_unified = C_norm * C_arch;