version 1.2-17

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: Matrix
-Version: 1.2-16
-Date: 2019-03-04
+Version: 1.2-17
+Date: 2019-03-11
 Priority: recommended
 Title: Sparse and Dense Matrix Classes and Methods
 Contact: Doug and Martin <Matrix-authors@R-project.org>
@@ -34,6 +34,8 @@ BuildResaveData: no
 License: GPL (>= 2) | file LICENCE
 URL: http://Matrix.R-forge.R-project.org/
 BugReports: https://r-forge.r-project.org/tracker/?group_id=61
+NeedsCompilation: yes
+Packaged: 2019-03-20 21:37:04 UTC; maechler
 Author: Douglas Bates [aut],
   Martin Maechler [aut, cre] (<https://orcid.org/0000-0002-8685-9910>),
   Timothy A. Davis [ctb] (SuiteSparse and 'cs' C libraries, notably
@@ -45,9 +47,4 @@ Author: Douglas Bates [aut],
     Regents of the University of California),
   R Core Team [ctb] (base R matrix implementation)
 Repository: CRAN
-Repository/R-Forge/Project: matrix
-Repository/R-Forge/Revision: 3291
-Repository/R-Forge/DateTimeStamp: 2019-03-04 11:00:53
-Date/Publication: 2019-03-08 15:33:45 UTC
-NeedsCompilation: yes
-Packaged: 2019-03-04 11:32:46 UTC; rforge
+Date/Publication: 2019-03-22 22:56:52 UTC

MD5

@@ -1,18 +1,18 @@
 675a3a48a357cb2ee05ed285387b3e85 *ChangeLog
-1a6f6fa0b7de869ebb6b603fb2cc077d *DESCRIPTION
+5e59faf86756d7dcf42826b8d318c0ec *DESCRIPTION
 49c7113b5e0e4fbf269132f6a5ff5b06 *LICENCE
 c64f1d9e5087f242f8a60c4f135fbf10 *NAMESPACE
 7e494fcaf80175fe73944c4d8732eb90 *R/AllClass.R
 b8ddeb8ff877f40a12519c3e965debb2 *R/AllGeneric.R
-6b4d466dfdba769a0c6aeeb57b7c8e3f *R/Auxiliaries.R
+f46239d6b3b7f1d7af26980777bacbe6 *R/Auxiliaries.R
 e184b3cf64c092b6ed0a0d22eb332a44 *R/CHMfactor.R
 3d80552f2d6bbaef906bd95dc4b734f6 *R/Csparse.R
 d7497671f04e08d0d703b650fd3eacff *R/HBMM.R
 3f37d43942f54523314df6f5406cf488 *R/Hilbert.R
 4d794b4715d6efa432fd7cf86f69da7a *R/KhatriRao.R
 7cd5d5938844fa73c1a2b50fae7fdd19 *R/LU.R
 639a65f83a4dccc663aad5299708071b *R/Math.R
-9eb05df834157e3129ed758df50d879b *R/Matrix.R
+8090100a5f06f969fc92a686e555800a *R/Matrix.R
 e19ed36934229e22f41552d4d40c5d5a *R/MatrixFactorization.R
 6e6e090d031ce8f02c8b4a6cd5b6ab08 *R/Ops.R
 a738e970d3c972b9ce5bc9492024a724 *R/Rsparse.R
@@ -76,30 +76,30 @@ b3d2c13789b1cc7ad4b38d1ee14a07bd *R/sparseMatrix.R
 7fcad2d91e94cfac03a4276a6acb211c *R/sparseVector.R
 97e508e9e124aac0fb3dc3d046de347f *R/symmetricMatrix.R
 a3265f0761ef916f610e9849c6677600 *R/triangularMatrix.R
-97734dbeedf076622f5a20e8cd6c0937 *R/zzz.R
-8531259eb72b7318c9028de5c7584cb5 *TODO
-53cea45c7db3841b03c8aecb778ad256 *build/partial.rdb
+7bb8f3b96f0cd3fc41bf5e4d75d085d9 *R/zzz.R
+f3b1b137d928891510363a3a18f9cfa6 *TODO
+77fc9f3d733ea9855b5b5026431a4eea *build/partial.rdb
 f6a48395281382c8210c31d00fb9d7a7 *build/vignette.rds
 f2ad5375e270deeb7b041272dd095032 *cleanup
 53de12cc7d1449cb2fa136f09333286b *data/CAex.R
 9b3cfbb2041e5aba139c715280208c30 *data/KNex.R
 3ed2e24d0f9b1af73f0b432f99644d64 *data/USCounties.R
 8734f0b040c6292983d273d4251d250a *inst/Copyrights
 ac3697580885d17a062ce39df01338ad *inst/Doxyfile
-e53099d1529073886025d47d1b81dd0e *inst/NEWS.Rd
+76ebc2b80bf1698523d3c104a0f096ff *inst/NEWS.Rd
 ea747a35318c564002a7144ebd510e28 *inst/doc/Announce.txt
 0eeea40a3fb6da7157d2862bba10713a *inst/doc/Comparisons.R
 09e13507b9832a30aa92e8aff0dc96a0 *inst/doc/Comparisons.Rnw
-7a81c839f873c82768bb567a9fdb71d2 *inst/doc/Comparisons.pdf
+42d1e2ebceb4386a7e81b12d60ee5b6b *inst/doc/Comparisons.pdf
 f5541439d0f08315e57f86d026a1c40d *inst/doc/Design-issues.R
 5a9e99ce004c325e01fb2773e58052f5 *inst/doc/Design-issues.Rnw
-c209eeefbc76b7286a53031634725995 *inst/doc/Design-issues.pdf
+e6e6f6671bf9b0075f6b688a6deec860 *inst/doc/Design-issues.pdf
 6f66bd95aab28d7bf06a019e7fbc14b5 *inst/doc/Intro2Matrix.R
 a6d6903590a8f5ac036fdeb74b48bb89 *inst/doc/Intro2Matrix.Rnw
-a4a3a928d25bee227577e54e8985c62c *inst/doc/Intro2Matrix.pdf
+ea6a658bb1c0874563f623eabd3a0e38 *inst/doc/Intro2Matrix.pdf
 188b839523ce6ec32e1f00ec4e2bc18e *inst/doc/Introduction.R
 c39a26dfe7ccaafd044e88468155b153 *inst/doc/Introduction.Rnw
-bd180d3d5a75876b6201a8458d119316 *inst/doc/Introduction.pdf
+7a0268bde26480ecdbbb0ffa47dbcbeb *inst/doc/Introduction.pdf
 7d60c8defc517d361513bac03d04f13b *inst/doc/SuiteSparse/AMD.txt
 e4f8cd28fc8be8ab14106630610b9c5f *inst/doc/SuiteSparse/CHOLMOD.txt
 0a80fb0db9cefb02e290ffd2f3431e6c *inst/doc/SuiteSparse/COLAMD.txt
@@ -108,7 +108,7 @@ d75882d4bb768ba0ea352291652daaee *inst/doc/SuiteSparse/SPQR.txt
 6d217288f5da4fe419afaa34988bf42d *inst/doc/SuiteSparse/UserGuides.txt
 2ab394c4daa5c94c2498ba3fa0578462 *inst/doc/sparseModels.R
 491d961ca64f8da569c817b82daa9c58 *inst/doc/sparseModels.Rnw
-62882f881b274478bd63ea10085b763f *inst/doc/sparseModels.pdf
+2e592e2bec481ff8fe86d04499bea367 *inst/doc/sparseModels.pdf
 dcd11f6947f910f743254824e930b2c7 *inst/external/CAex_slots.rda
 be886d6bb832210bb654b9ad064fe0ff *inst/external/KNex_slots.rda
 90f019ec81e67d7f3542f7ca39bf3f2d *inst/external/USCounties_slots.rda
@@ -220,7 +220,7 @@ f5127ffbf702e88219a61c8385c53de2 *man/lu.Rd
 4a897749bfc1ee9afd46bb58f8fa8c05 *man/matrix-products.Rd
 4a449d40a733322c55cf7146d8ddb43e *man/nMatrix-class.Rd
 3e94bd26a125e628e83c7b6d4d8a045c *man/ndenseMatrix-class.Rd
-46dc1c9089fefb669bf1b8137edd2d12 *man/nearPD.Rd
+115b74fe54e0b5ada18182d9bde630b7 *man/nearPD.Rd
 07c563eefd115c5f74e5ba28231ffb46 *man/ngeMatrix-class.Rd
 ffb57c3063559175113661c71b6f130d *man/nnzero.Rd
 001c81a2b8215c310e817aa60ea2095b *man/norm.Rd
@@ -383,31 +383,31 @@ e14e53d0b36e1d0647348a326e8b3b54 *src/COLAMD/Include/colamd.h
 b56b67fa4e3e8bc168f5ad98d27f207a *src/COLAMD/Source/Makefile
 561ff6512783cc2af5b343ff3630267d *src/COLAMD/Source/colamd.c
 8f9d70daa9adafe39e555573d974d17e *src/COLAMD/Source/colamd_global.c
-e52babc8b8e37bd088058bc96f39d73e *src/Csparse.c
+60251cd94325ee15b1502f9ea8bf1184 *src/Csparse.c
 684b703246b23a66b77fce3dc0e5d73a *src/Csparse.h
 e879c68d033040e33a588710797323b5 *src/Makevars
 739a9b145f3e90adf5b58f743e4d3e77 *src/Mutils.c
-5ea701c24ba16afb99f5164e7f1f4907 *src/Mutils.h
+6b01b5ee807043e6cf42191f68306af9 *src/Mutils.h
 34a94c6db1f395da28ca4e94dd9cf9ca *src/SuiteSparse_config/Makefile
 e9b2be5ad0056f588187cf504cf60764 *src/SuiteSparse_config/SuiteSparse_config.c
 ff586155b86948cc5b4eec822b8670e2 *src/SuiteSparse_config/SuiteSparse_config.h
 d41d8cd98f00b204e9800998ecf8427e *src/SuiteSparse_config/SuiteSparse_config.mk
-b08d523906ab962f8e0729cb4d3d2f15 *src/Syms.h
+1cf7c17bb7f79d7d22577cf4770cfc37 *src/Syms.h
 5dfee1d8667f9553469dea08cec731e6 *src/TMatrix_as.c
 0ef00bab2b7ffb79f64b25311decd236 *src/TMatrix_as.h
 6551aecedc2b54c2c1f4c8a0973861f2 *src/Tsparse.c
 20c550b57138bf22290ea759dfcb1c3e *src/Tsparse.h
 3714d37c755fbf0b5b2a88362b651390 *src/abIndex.c
 ea6bdd1b33f38c8c2913eeef6eb21be3 *src/abIndex.h
-f6f9e84779e01f8dbc4272539b7b6e43 *src/chm_common.c
+32f9854050f40537e61497a181be2f80 *src/chm_common.c
 b6ea652eed1988974dec16b9cb9a35c1 *src/chm_common.h
 4893273047274b21bfa8542880de3fa6 *src/cs.c
 2d48f8b8f4e1eb4598302396f70e8c89 *src/cs.h
-0a56e3408129fe35387a17bfd35e29a6 *src/cs_utils.c
+749274eb9cfbbb5cf0db83c0ae4300cd *src/cs_utils.c
 0b6112e86dab4fcececbadd2e84582ea *src/cs_utils.h
-0f9ca4d63c86b9ae9299a9bdf4fad9c2 *src/dense.c
+e1b9bfdf21d644dffd2b3764c6514cd6 *src/dense.c
 f14d4d8cd3b94ab5e95c8c9bff9630f1 *src/dense.h
-c51ca6433a1a0361c3d95064a6b1690d *src/dgCMatrix.c
+ad83ec224514ddc5304264281ea43450 *src/dgCMatrix.c
 2392fd374cf7d259fedbef27f0a13e7f *src/dgCMatrix.h
 62db9316297b07b1a82897e558b8e81a *src/dgTMatrix.c
 341e051982a88f9c4d9a02c1376978fc *src/dgTMatrix.h
@@ -433,7 +433,7 @@ ca00a8f2c785b0b4e3ead5cb888dc330 *src/dtpMatrix.h
 feba4a84f226246a992cc103f3da8874 *src/dtrMatrix.h
 cc1dca4dce1c8f68cf41f991ad349236 *src/factorizations.c
 37fd937251ae9f1c68d974bd6169ade3 *src/factorizations.h
-1e240fe50368743af3baa91f8ec289bb *src/init.c
+069b9c048677ed614b7bb99a97609740 *src/init.c
 5258096040c5fc0b0374fe510dc46c7d *src/ldense.c
 d8522bb27a18eea16d17c411d8da9e38 *src/ldense.h
 0b0a474b5b19cb09637063134a0ba203 *src/lgCMatrix.c
@@ -443,7 +443,7 @@ f3b6b0ff9a8088a21a1c46c9d7797f4d *src/scripts/DEPS.mkf
 0aba26556ef5ddd3adc0031d41ef0d4c *src/scripts/DEPS.mkf_make.sh
 15eb76d731d373a415312098f6f707e5 *src/scripts/SOURCES_C.mkf
 f1d325ea608f75622777bef1fbe55611 *src/scripts/fixup-fn.R
-c4f73d8e14e8268b7ec4e7ce548e109e *src/sparseQR.c
+80235a6bc16762bcd571ff7a9f553d14 *src/sparseQR.c
 68c429cbb92387ef9ce70dac75a6e934 *src/sparseQR.h
 2e623510d32213208f40240fc50a0c57 *src/t_Csparse_subassign.c
 2394f5def013c7e571231935320fa6c3 *src/t_Csparse_validate.c
@@ -452,7 +452,7 @@ c55fe12890cabcf61d562a4969825c02 *src/t_Matrix_rle.c
 edb93b23eb7e6db1f454970b4c663f3a *src/t_matrix_to_Csp.c
 e6de21ff3bf0908eaca620d9b868b4f1 *src/t_sparseVector.c
 3dcc9418cfcbd6ec989b16a91b2b945a *tests/Class+Meth.R
-25d02c4cc55e2d072606224fe229af9b *tests/Simple.R
+b7de3c2add7cf86ac1e651697cd5f25b *tests/Simple.R
 4966b9ac5a23de46814439a84174973b *tests/abIndex-tsts.R
 ce85ee2aba7d78e88fef738a0d1c7118 *tests/base-matrix-fun.R
 78d7038fa6dfd7401a6a20efae58ab1e *tests/bind.R

R/Auxiliaries.R

@@ -69,7 +69,7 @@ is.null.DN <- function(dn) {
 ##' return 'x' unless it is NULL where you'd use 'orElse'
 `%||%` <- function(x, orElse) if(!is.null(x)) x else orElse
 
-##  not %in%  :
+##'  not %in%  :
 `%nin%` <- function (x, table) is.na(match(x, table))
 
 nonTRUEoption <- function(ch) is.null(v <- getOption(ch)) || !isTRUE(v)

R/Matrix.R

@@ -218,8 +218,7 @@ Matrix <- function (data = NA, nrow = 1, ncol = 1, byrow = FALSE,
     }
     if(is.null(sparse1 <- sparse) && (i.M || is(data, "matrix")))
 	sparse <- sparseDefault(data)
-    doDN <- TRUE
-    i.m <- is.matrix(data)
+    doDN <- TRUE # by default
     if (i.M) {
 	if (!sV) {
 	    if(!missing(nrow) || !missing(ncol)|| !missing(byrow))
@@ -230,7 +229,7 @@ Matrix <- function (data = NA, nrow = 1, ncol = 1, byrow = FALSE,
 	    ## else : convert  dense <-> sparse -> at end
 	}
     }
-    else if (!i.m) { ## cut & paste from "base::matrix" :
+    else if(!is.matrix(data)) { ## cut & paste from "base::matrix" :
 	## avoid copying to strip attributes in simple cases
 	if (is.object(data) || !is.atomic(data)) data <- as.vector(data)
 	if(length(data) == 1 && is0(data) && !identical(sparse, FALSE)) {

R/zzz.R

@@ -59,6 +59,11 @@ if(getRversion() >= "3.2.0") {
     lengths <- function (x, use.names = TRUE) vapply(x, length, 1L, USE.NAMES = use.names)
 }
 
+if(getRversion() < "3.5.0") {
+    isFALSE <- function (x) is.logical(x) && length(x) == 1L && !is.na(x) && !x
+    isTRUE  <- function (x) is.logical(x) && length(x) == 1L && !is.na(x) && x
+}
+
 .onUnload <- function(libpath)
 {
     library.dynam.unload("Matrix", libpath)

TODO

@@ -9,6 +9,8 @@
 * *Urgent* in some sense ---------------------------------------------------
 ** TODO (partly DONE via workaround "round up" to 100): print() / show() for small options(max.print=<n>):
     --> tests/Simple.R {'max.print'}
+** TODO API change: Should  Matrix(diag(2), sparse=TRUE, doDiag=TRUE)  not rather give "ddiMatrix" ??
+      Why change? Originally "ddiMatrix" etc extended denseMatrix but now sparseMatrix
 ** DONE qr.coef() has *wrong* (column)names, even in full-rank case: see man/qr-methods.Rd ("FIXME"); maybe related to
 ** DONE qr.R(), qrR() etc have *wrong* currently *lose* column/row names {compared to base R's qr.R}, see,
    	drop0(R. <- qr.R(qx), tol=1e-15) # columns are int b1 c1 c2 b2 c3 {in man/qr-methods.Rd}

inst/NEWS.Rd

@@ -14,6 +14,22 @@
 %% \item \code{as(<large-matrix>, "sparseMatrix")} no longer fails
 %%  when \code{prod(dim(.))} is larger than \eqn{2^{31} - 1}.
 %
+\section{Changes in version 1.2-17 (2019-03-.., svn r....)}{
+  \subsection{New Features}{
+    \itemize{
+      \item (none)
+    }
+  }
+  \subsection{Bug Fixes}{
+    \itemize{
+      \item Fix new \code{PROTECT()} warnings (bugs?) found by \command{rchk}.
+
+      \item Provide \code{isFALSE()} for \R < 3.5.0 as now need it for
+      sparseMatrix printing.
+    }
+  }
+}
+
 \section{Changes in version 1.2-16 (2019-03-04, svn r3291)}{
   \subsection{New Features}{
     \itemize{

man/nearPD.Rd

@@ -32,14 +32,14 @@ nearPD(x, corr = FALSE, keepDiag = FALSE, do2eigen = TRUE,
     direct fixpoint iteration
     \eqn{Y_k = P_U(P_S(Y_{k-1}))}{Y(k) = P_U(P_S(Y(k-1)))}.}
   \item{only.values}{logical; if \code{TRUE}, the result is just the
-    vector of eigen values of the approximating matrix.}
+    vector of eigenvalues of the approximating matrix.}
   \item{ensureSymmetry}{logical; by default, \code{\link{symmpart}(x)}
     is used whenever \code{\link{isSymmetric}(x)} is not true.  The user
     can explicitly set this to \code{TRUE} or \code{FALSE}, saving the
     symmetry test. \emph{Beware} however that setting it \code{FALSE}
     for an \bold{a}symmetric input \code{x}, is typically nonsense!}
   \item{eig.tol}{defines relative positiveness of eigenvalues compared
-    to largest one, \eqn{\lambda_1}. Eigen values \eqn{\lambda_k} are
+    to largest one, \eqn{\lambda_1}. Eigenvalues \eqn{\lambda_k} are
     treated as if zero when \eqn{\lambda_k / \lambda_1 \le eig.tol}.}
   \item{conv.tol}{convergence tolerance for Higham algorithm.}
   \item{posd.tol}{tolerance for enforcing positive definiteness (in the
@@ -55,27 +55,28 @@ nearPD(x, corr = FALSE, keepDiag = FALSE, do2eigen = TRUE,
 \details{
   This implements the algorithm of Higham (2002), and then (if
   \code{do2eigen} is true) forces positive definiteness using code from
-  \code{\link[sfsmisc]{posdefify}}.  The algorithm of Knol DL and ten
-  Berge (1989) (not implemented here) is more general in (1) that it
-  allows constraints to fix some rows (and columns) of the matrix and (2)
-  to force the smallest eigenvalue to have a certain value.
+  \code{\link[sfsmisc]{posdefify}}.  The algorithm of Knol and ten
+  Berge (1989) (not implemented here) is more general in that it
+  allows constraints to (1) fix some rows (and columns) of the matrix and
+  (2) force the smallest eigenvalue to have a certain value.
 
   Note that setting \code{corr = TRUE} just sets \code{diag(.) <- 1}
   within the algorithm.
 
   Higham (2002) uses Dykstra's correction, but the version by Jens
-  Oehlschlaegel did not use it (accidentally), and has still lead to
-  good results; this simplification, now only via \code{doDykstra = FALSE},
-  was active in \code{nearPD()} upto Matrix version 0.999375-40.
+  Oehlschlaegel did not use it (accidentally), and still gave
+  reasonable results; this simplification, now only
+  used if \code{doDykstra = FALSE},
+  was active in \code{nearPD()} up to Matrix version 0.999375-40.
 }
 \value{
-  If \code{only.values = TRUE}, a numeric vector of eigen values of the
+  If \code{only.values = TRUE}, a numeric vector of eigenvalues of the
   approximating matrix;
   Otherwise, as by default, an S3 object of \code{\link{class}}
   \code{"nearPD"}, basically a list with components
   \item{mat}{a matrix of class \code{\linkS4class{dpoMatrix}}, the
   computed positive-definite matrix.}
-  \item{eigenvalues}{numeric vector of eigen values of \code{mat}.}
+  \item{eigenvalues}{numeric vector of eigenvalues of \code{mat}.}
   \item{corr}{logical, just the argument \code{corr}.}
   \item{normF}{the Frobenius norm (\code{\link{norm}(x-X, "F")}) of the
   difference between the original and the resulting matrix.}

src/Csparse.c

@@ -163,8 +163,8 @@ SEXP Csparse_to_dense(SEXP x, SEXP symm_or_tri)
 				 /* transp: */ FALSE);
     // -> a [dln]geMatrix
     if(is_sym) { // ==> want  [dln]syMatrix
-	const char cl1 = class_P(ans)[0];
 	PROTECT(ans);
+	const char cl1 = class_P(ans)[0];
 	SEXP aa = PROTECT(NEW_OBJECT_OF_CLASS((cl1 == 'd') ? "dsyMatrix" :
 					      ((cl1 == 'l') ? "lsyMatrix" : "nsyMatrix")));
 	// No need to duplicate() as slots of ans are freshly allocated and ans will not be used
@@ -176,8 +176,8 @@ SEXP Csparse_to_dense(SEXP x, SEXP symm_or_tri)
 	return aa;
     }
     else if(is_tri) { // ==> want  [dln]trMatrix
-	const char cl1 = class_P(ans)[0];
 	PROTECT(ans);
+	const char cl1 = class_P(ans)[0];
 	SEXP aa = PROTECT(NEW_OBJECT_OF_CLASS((cl1 == 'd') ? "dtrMatrix" :
 					      ((cl1 == 'l') ? "ltrMatrix" : "ntrMatrix")));
 	// No need to duplicate() as slots of ans are freshly allocated and ans will not be used

src/Mutils.h

@@ -300,10 +300,10 @@ Rboolean any_NA_in_x(SEXP obj)
 static R_INLINE
 SEXP inv_permutation(SEXP p_, SEXP zero_p, SEXP zero_res)
 {
-    int np = 0;
+    int np = 1;
     if(!isInteger(p_)) {p_ = PROTECT(coerceVector(p_, INTSXP)); np++; }
     int *p = INTEGER(p_), n = LENGTH(p_);
-    SEXP val = allocVector(INTSXP, n);// (not PROTECT()ing: no alloc from here on)
+    SEXP val = PROTECT(allocVector(INTSXP, n));
     int *v = INTEGER(val), p_0 = asLogical(zero_p), r_0 = asLogical(zero_res);
     if(!p_0) v--; // ==> use 1-based indices
     // shorter (but not 100% sure if ok: is LHS always eval'ed *before* RHS ?) :

src/Syms.h

@@ -7,6 +7,7 @@ SEXP
     Matrix_iSym,
     Matrix_jSym,
     Matrix_lengthSym,
+    Matrix_LSym, Matrix_RSym, Matrix_USym,
     Matrix_pSym,
     Matrix_permSym,
     Matrix_uploSym,

src/chm_common.c

@@ -48,27 +48,33 @@ void CHM_store_common() {
 }
 
 void CHM_restore_common() {
-    SEXP rho = chm_common_env;
-    c.dbound = asReal(findVarInFrame(rho, dboundSym));
-    c.grow0 = asReal(findVarInFrame(rho, grow0Sym));
-    c.grow1 = asReal(findVarInFrame(rho, grow1Sym));
-    c.grow2 = asInteger(findVarInFrame(rho, grow2Sym));
-    c.maxrank = asInteger(findVarInFrame(rho, maxrankSym));
-    c.supernodal_switch = asReal(findVarInFrame(rho, supernodal_switchSym));
-    c.supernodal = asLogical(findVarInFrame(rho, supernodalSym));
-    c.final_asis = asLogical(findVarInFrame(rho, final_asisSym));
-    c.final_super = asLogical(findVarInFrame(rho, final_superSym));
-    c.final_ll = asLogical(findVarInFrame(rho, final_llSym));
-    c.final_pack = asLogical(findVarInFrame(rho, final_packSym));
-    c.final_monotonic = asLogical(findVarInFrame(rho, final_monotonicSym));
-    c.final_resymbol = asLogical(findVarInFrame(rho, final_resymbolSym));
-    c.prefer_zomplex = asLogical(findVarInFrame(rho, prefer_zomplexSym));
-    c.prefer_upper = asLogical(findVarInFrame(rho, prefer_upperSym));
-    c.quick_return_if_not_posdef =
-	asLogical(findVarInFrame(rho, quick_return_if_not_posdefSym));
-    c.nmethods = asInteger(findVarInFrame(rho, nmethodsSym));
-    c.method[0].ordering = asInteger(findVarInFrame(rho, m0_ordSym));
-    c.postorder = asLogical(findVarInFrame(rho, postorderSym));
+    SEXP rho = chm_common_env, var;
+
+#define SET_AS_FROM_FRAME(_V_, _KIND_, _SYM_)	\
+    var = PROTECT(findVarInFrame(rho, _SYM_));	\
+    _V_ = _KIND_(var);				\
+    UNPROTECT(1)
+
+    SET_AS_FROM_FRAME(c.dbound, asReal,    dboundSym);
+    SET_AS_FROM_FRAME(c.grow0,  asReal,    grow0Sym);
+    SET_AS_FROM_FRAME(c.grow1,  asReal,    grow1Sym);
+    SET_AS_FROM_FRAME(c.grow2,  asInteger, grow2Sym);
+    SET_AS_FROM_FRAME(c.maxrank,asInteger, maxrankSym);
+    SET_AS_FROM_FRAME(c.supernodal_switch, asReal, supernodal_switchSym);
+    SET_AS_FROM_FRAME(c.supernodal,     asLogical, supernodalSym);
+    SET_AS_FROM_FRAME(c.final_asis,     asLogical, final_asisSym);
+    SET_AS_FROM_FRAME(c.final_super,    asLogical, final_superSym);
+    SET_AS_FROM_FRAME(c.final_ll,       asLogical, final_llSym);
+    SET_AS_FROM_FRAME(c.final_pack,     asLogical, final_packSym);
+    SET_AS_FROM_FRAME(c.final_monotonic,asLogical, final_monotonicSym);
+    SET_AS_FROM_FRAME(c.final_resymbol, asLogical, final_resymbolSym);
+    SET_AS_FROM_FRAME(c.prefer_zomplex, asLogical, prefer_zomplexSym);
+    SET_AS_FROM_FRAME(c.prefer_upper,   asLogical, prefer_upperSym);
+    SET_AS_FROM_FRAME(c.quick_return_if_not_posdef,
+					asLogical, quick_return_if_not_posdefSym);
+    SET_AS_FROM_FRAME(c.nmethods,           asInteger, nmethodsSym);
+    SET_AS_FROM_FRAME(c.method[0].ordering, asInteger, m0_ordSym);
+    SET_AS_FROM_FRAME(c.postorder,          asLogical, postorderSym);
 }
 
 SEXP CHM_set_common_env(SEXP rho) {