improve findSamplersOnNodes performance (#1614)

Refactor node matching in findSamplersOnNodes to flatten sampler target nodes once and map matches back to sampler indices.
This preserves the return value and can reduce overhead for repeated matching.

Author: hoxo-m

packages/nimble/R/MCMC_configuration.R

@@ -1081,7 +1081,15 @@ ind: A numeric vector or character vector.  A numeric vector may be used to spec
             if(length(samplerConfs) == 0) return(integer())
             nodes <- model$expandNodeNames(nodes, returnScalarComponents = TRUE, sort = TRUE)
             samplerConfNodesList <- lapply(samplerConfs, function(sc) sc$targetAsScalar)
-            return(unique(unlist(lapply(nodes, function(n) which(unlist(lapply(samplerConfNodesList, function(scn) n %in% scn)))))))
+
+            # Match requested nodes in the flattened node list and map matches back to sampler indices.
+            samplerIndices <- 1:length(samplerConfs)
+            samplerConfNodesLengths <- unlist(lapply(samplerConfNodesList, length))
+            flatSamplerConfNodes <- unlist(samplerConfNodesList)
+            flatSamplerIndices <- rep.int(samplerIndices, times = samplerConfNodesLengths)
+            flatNodePositions <- unlist(lapply(nodes, function(n) which(n == flatSamplerConfNodes)))
+            matchedSamplerIndices <- flatSamplerIndices[flatNodePositions]
+            unique(matchedSamplerIndices)
         },
 
         getSamplerDefinition = function(ind, print = FALSE) {