for testing only: full exclude self nodes in getParents

README.md

@@ -78,7 +78,7 @@ NIMBLE. Journal of Computational and Graphical Statistics 26:403-413. [https://d
 
 In published work that uses NIMBLE, please also cite the package version:
 
-de Valpine, P., C. Paciorek, D. Turek, N. Michaud, C. Anderson-Bergman, F. Obermeyer, C. Wehrhahn Cortes, A. Rodriguez, D. Temple Lang, W. Zhang, S. Paganin, and P. van Dam-Bates. 2024. NIMBLE: MCMC, Particle Filtering, and Programmable Hierarchical Modeling.  doi: 10.5281/zenodo.1211190. R package version 1.4.1, https://cran.r-project.org/package=nimble.
+de Valpine, P., C. Paciorek, D. Turek, N. Michaud, C. Anderson-Bergman, F. Obermeyer, C. Wehrhahn Cortes, A. Rodriguez, D. Temple Lang, W. Zhang, S. Paganin, and P. van Dam-Bates. 2024. NIMBLE: MCMC, Particle Filtering, and Programmable Hierarchical Modeling.  doi: 10.5281/zenodo.1211190. R package version 1.4.2, https://cran.r-project.org/package=nimble.
 
 To help us track usage to justify funding support for NIMBLE, please include the DOI in the citation.
 

packages/nimble/DESCRIPTION

@@ -15,8 +15,8 @@ Description: A system for writing hierarchical statistical models largely
     of MCMC as the main goal of the 'BUGS'/'JAGS' language for writing models,
     one can use 'NIMBLE' for writing arbitrary other kinds of model-generic
     algorithms as well. A full User Manual is available at <https://r-nimble.org>.
-Version: 1.4.2
-Date: 2026-04-01
+Version: 1.4.3
+Date: 2026-05-01
 Maintainer: Christopher Paciorek <paciorek@stat.berkeley.edu>
 Authors@R: c(
     person("Perry", "de Valpine", role = "aut"),

packages/nimble/R/BUGS_model.R

@@ -959,7 +959,9 @@ Details: The upward search for dependent nodes propagates through deterministic
   if(self)	{ # The C++ call does *not* return self nodes
     nodeFunIDs <- unique(modelDef$maps$vertexID_2_nodeID[ nodeIDs ])
     parentIDs <- sort(c(parentIDs, nodeFunIDs))
-  }
+  } else parentIDs <- setdiff(parentIDs, nodeIDs)
+
+
   if(!includeRHSonly) parentIDs <- parentIDs[modelDef$maps$types[parentIDs] != 'RHSonly']
   if(determOnly)      parentIDs <- parentIDs[modelDef$maps$types[parentIDs] == 'determ']
   if(stochOnly)	      parentIDs <- parentIDs[modelDef$maps$types[parentIDs] == 'stoch']

packages/nimble/R/BUGS_nimbleGraph.R

@@ -194,7 +194,7 @@ getConditionallyIndependentSets <- function(model,
 
   if(!missing(nodes)) {
     if(missing(givenNodes))
-      givenNodesIDs <- setdiff(givenNodeIDs, nodeIDs)
+      givenNodeIDs <- setdiff(givenNodeIDs, nodeIDs)
   }
   if(!missing(givenNodes)) {
     nodeIDs <- setdiff(nodeIDs, givenNodeIDs)

packages/nimble/R/MCMC_WAIC.R

@@ -288,7 +288,7 @@ buildWAIC <- nimbleFunction(
             if(mcmcIter > 1) {
                 badpWAIC <- length(which( sspWAICmat[lengthConvCheck, ] / (mcmcIter-1) > 0.4 ))
                 if(badpWAIC) {  
-                    cat("  [Warning] There are ", badpWAIC, " individual pWAIC values that are greater than 0.4. This may indicate that the WAIC estimate is unstable (Vehtari et al., 2017), at least in cases without grouping of data nodes or multivariate data nodes.\n" )
+                    cat("  [Warning] There are ", badpWAIC, " individual pWAIC values that are greater than 0.4. This may indicate that the WAIC estimate is unstable (Vehtari et al., 2017), at least in cases without grouping of data nodes or multivariate data nodes. To see the individual pWAIC values, use the `getWAICdetails` method of the compiled MCMC object, with argument `returnElements = TRUE`.\n" )
                 }
             }
             output <- waicNimbleList$new()

packages/nimble/R/setupMargNodes.R

@@ -283,7 +283,7 @@ setupMargNodes <- function(model, paramNodes, randomEffectsNodes, calcNodes,
         tempDataNodesDefault <- model$getNodeNames(dataOnly = TRUE)
       if(paramsHandled)
         tempDataNodesDefault <- setdiff(tempDataNodesDefault, paramNodes)
-      tempDataNodesDefaultParents <- model$getParents(tempDataNodesDefault, upstream = TRUE, stochOnly = TRUE)
+      tempDataNodesDefaultParents <- model$getParents(tempDataNodesDefault, upstream = TRUE, stochOnly = TRUE, self = TRUE)
       # See comment above about why this is necessary:
       tempDataNodesDefaultParents <- setdiff(tempDataNodesDefaultParents, tempDataNodesDefault)
       reNodesDefault <- intersect(reNodesDefault, tempDataNodesDefaultParents)
@@ -292,12 +292,12 @@ setupMargNodes <- function(model, paramNodes, randomEffectsNodes, calcNodes,
       if(paramsHandled) { # This means reProvided OR paramsProvided. Including parents allows checking
         # of potentially missing REs.
         reNodesDefault <- intersect(reNodesDefault,
-                                    model$getParents(calcNodes, upstream=TRUE, stochOnly = TRUE))
+                                    model$getParents(calcNodes, upstream=TRUE, stochOnly = TRUE, self = TRUE))
       } else { # This means !paramsHandled and hence !reProvided AND !paramsProvided
         reNodesDefault <- intersect(reNodesDefault,
                                     calcNodes)
         reNodesDefault <- intersect(reNodesDefault,
-                                    model$getParents(calcNodes, upstream=TRUE, stochOnly = TRUE))
+                                    model$getParents(calcNodes, upstream=TRUE, stochOnly = TRUE, self = TRUE))
       }
     }
   }

packages/nimble/tests/testthat/test-getDependencies.R

@@ -154,12 +154,12 @@ test_that("getParents works in model with no criss-crossing dependencies", {
 
   expect_identical(m1$getParents("f1"), c("a1", "a2", "c2", "c4", "c3"))
   expect_identical(m1$getParents("f1", immediateOnly = TRUE), c("c4", "c3"))
-  expect_identical(m1$getParents(c("f1", "g1"), stochOnly = TRUE), c("a1", "a2", "f1"))
-  expect_identical(m1$getParents(c("f1", "g1"), immediateOnly = TRUE), c("c4", "c3", "f1"))
-  expect_identical(m1$getParents(c("g1", "f1"), stochOnly = TRUE), c("a1", "a2", "f1"))
+  expect_identical(m1$getParents(c("f1", "g1"), stochOnly = TRUE), c("a1", "a2"))
+  expect_identical(m1$getParents(c("f1", "g1"), immediateOnly = TRUE), c("c4", "c3"))
+  expect_identical(m1$getParents(c("g1", "f1"), stochOnly = TRUE), c("a1", "a2"))
   expect_identical(m1$getParents(c("f1", "g1"), stochOnly = TRUE, self = TRUE), c("a1", "a2", "f1", "g1"))
-  expect_identical(m1$getParents(c("c3", "c2", "e1"), stochOnly = FALSE), c("a1", "c2", "c3"))
-  expect_identical(m1$getParents(c("c3", "c2", "e1"), immediateOnly = TRUE, stochOnly = FALSE), c("a1", "c2", "c3"))
+  expect_identical(m1$getParents(c("c3", "c2", "e1"), stochOnly = FALSE), c("a1"))
+  expect_identical(m1$getParents(c("c3", "c2", "e1"), immediateOnly = TRUE, stochOnly = FALSE), c("a1"))
   expect_identical(m1$getParents("h1", includeRHSonly = TRUE, stochOnly = FALSE), c("lho"))
 })