Back to Multiple platform build/check report for BioC 3.22: simplified long |
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This page was generated on 2025-08-20 12:03 -0400 (Wed, 20 Aug 2025).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4818 |
lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4596 |
kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4538 |
taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4536 |
Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X |
Package 251/2317 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
BufferedMatrix 1.73.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | ![]() | ||||||||
lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | ![]() | ||||||||
kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | ![]() | ||||||||
taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
Package: BufferedMatrix |
Version: 1.73.0 |
Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.73.0.tar.gz |
StartedAt: 2025-08-19 20:39:44 -0400 (Tue, 19 Aug 2025) |
EndedAt: 2025-08-19 20:40:08 -0400 (Tue, 19 Aug 2025) |
EllapsedTime: 24.0 seconds |
RetCode: 0 |
Status: OK |
CheckDir: BufferedMatrix.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.73.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’ * using R version 4.5.1 (2025-06-13) * using platform: x86_64-pc-linux-gnu * R was compiled by gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0 GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0 * running under: Ubuntu 24.04.3 LTS * using session charset: UTF-8 * checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK * this is package ‘BufferedMatrix’ version ‘1.73.0’ * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking whether package ‘BufferedMatrix’ can be installed ... OK * used C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’ * checking installed package size ... OK * checking package directory ... OK * checking ‘build’ directory ... OK * checking DESCRIPTION meta-information ... OK * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking code files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... OK * checking whether the package can be loaded with stated dependencies ... OK * checking whether the package can be unloaded cleanly ... OK * checking whether the namespace can be loaded with stated dependencies ... OK * checking whether the namespace can be unloaded cleanly ... OK * checking loading without being on the library search path ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... OK * checking Rd files ... NOTE checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup? 209 | $x^{power}$ elementwise of the matrix | ^ prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples * checking Rd metadata ... OK * checking Rd cross-references ... OK * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking line endings in C/C++/Fortran sources/headers ... OK * checking compiled code ... NOTE Note: information on .o files is not available * checking files in ‘vignettes’ ... OK * checking examples ... NONE * checking for unstated dependencies in ‘tests’ ... OK * checking tests ... Running ‘Rcodetesting.R’ Running ‘c_code_level_tests.R’ Running ‘objectTesting.R’ Running ‘rawCalltesting.R’ OK * checking for unstated dependencies in vignettes ... OK * checking package vignettes ... OK * checking re-building of vignette outputs ... OK * checking PDF version of manual ... OK * DONE Status: 2 NOTEs See ‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’ for details.
BufferedMatrix.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL BufferedMatrix ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’ * installing *source* package ‘BufferedMatrix’ ... ** this is package ‘BufferedMatrix’ version ‘1.73.0’ ** using staged installation ** libs using C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’ gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’: doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses] 1580 | if (!(Matrix->readonly) & setting){ | ^~~~~~~~~~~~~~~~~~~ doubleBufferedMatrix.c: At top level: doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function] 3327 | static int sort_double(const double *a1,const double *a2){ | ^~~~~~~~~~~ gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c init_package.c -o init_package.o gcc -std=gnu2x -shared -L/home/biocbuild/bbs-3.22-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.22-bioc/R/lib -lR installing to /home/biocbuild/bbs-3.22-bioc/R/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs ** R ** inst ** byte-compile and prepare package for lazy loading Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’ Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’ Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’ Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’ Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’ Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’ ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** checking absolute paths in shared objects and dynamic libraries ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.5.1 (2025-06-13) -- "Great Square Root" Copyright (C) 2025 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1)) Attaching package: 'BufferedMatrix' The following objects are masked from 'package:base': colMeans, colSums, rowMeans, rowSums Checking dimensions Rows: 5 Cols: 5 Buffer Rows: 1 Buffer Cols: 1 Assigning Values 0.000000 1.000000 2.000000 3.000000 4.000000 1.000000 2.000000 3.000000 4.000000 5.000000 2.000000 3.000000 4.000000 5.000000 6.000000 3.000000 4.000000 5.000000 6.000000 7.000000 4.000000 5.000000 6.000000 7.000000 8.000000 Adding Additional Column Checking dimensions Rows: 5 Cols: 6 Buffer Rows: 1 Buffer Cols: 1 0.000000 1.000000 2.000000 3.000000 4.000000 0.000000 1.000000 2.000000 3.000000 4.000000 5.000000 0.000000 2.000000 3.000000 4.000000 5.000000 6.000000 0.000000 3.000000 4.000000 5.000000 6.000000 7.000000 0.000000 4.000000 5.000000 6.000000 7.000000 8.000000 0.000000 Reassigning values 1.000000 6.000000 11.000000 16.000000 21.000000 26.000000 2.000000 7.000000 12.000000 17.000000 22.000000 27.000000 3.000000 8.000000 13.000000 18.000000 23.000000 28.000000 4.000000 9.000000 14.000000 19.000000 24.000000 29.000000 5.000000 10.000000 15.000000 20.000000 25.000000 30.000000 Resizing Buffers Checking dimensions Rows: 5 Cols: 6 Buffer Rows: 3 Buffer Cols: 3 1.000000 6.000000 11.000000 16.000000 21.000000 26.000000 2.000000 7.000000 12.000000 17.000000 22.000000 27.000000 3.000000 8.000000 13.000000 18.000000 23.000000 28.000000 4.000000 9.000000 14.000000 19.000000 24.000000 29.000000 5.000000 10.000000 15.000000 20.000000 25.000000 30.000000 Activating Row Buffer In row mode: 1 1.000000 6.000000 11.000000 16.000000 21.000000 26.000000 2.000000 7.000000 12.000000 17.000000 22.000000 27.000000 3.000000 8.000000 13.000000 18.000000 23.000000 28.000000 4.000000 9.000000 14.000000 19.000000 24.000000 29.000000 5.000000 10.000000 15.000000 20.000000 25.000000 30.000000 Squaring Last Column 1.000000 6.000000 11.000000 16.000000 21.000000 676.000000 2.000000 7.000000 12.000000 17.000000 22.000000 729.000000 3.000000 8.000000 13.000000 18.000000 23.000000 784.000000 4.000000 9.000000 14.000000 19.000000 24.000000 841.000000 5.000000 10.000000 15.000000 20.000000 25.000000 900.000000 Square rooting Last Row, then turing off Row Buffer In row mode: 0 Checking on value that should be not be in column buffer2.236068 1.000000 6.000000 11.000000 16.000000 21.000000 676.000000 2.000000 7.000000 12.000000 17.000000 22.000000 729.000000 3.000000 8.000000 13.000000 18.000000 23.000000 784.000000 4.000000 9.000000 14.000000 19.000000 24.000000 841.000000 2.236068 3.162278 3.872983 4.472136 5.000000 30.000000 Single Indexing. Assign each value its square 1.000000 36.000000 121.000000 256.000000 441.000000 676.000000 4.000000 49.000000 144.000000 289.000000 484.000000 729.000000 9.000000 64.000000 169.000000 324.000000 529.000000 784.000000 16.000000 81.000000 196.000000 361.000000 576.000000 841.000000 25.000000 100.000000 225.000000 400.000000 625.000000 900.000000 Resizing Buffers Smaller Checking dimensions Rows: 5 Cols: 6 Buffer Rows: 1 Buffer Cols: 1 1.000000 36.000000 121.000000 256.000000 441.000000 676.000000 4.000000 49.000000 144.000000 289.000000 484.000000 729.000000 9.000000 64.000000 169.000000 324.000000 529.000000 784.000000 16.000000 81.000000 196.000000 361.000000 576.000000 841.000000 25.000000 100.000000 225.000000 400.000000 625.000000 900.000000 Activating Row Mode. Resizing Buffers Checking dimensions Rows: 5 Cols: 6 Buffer Rows: 1 Buffer Cols: 1 Activating ReadOnly Mode. The results of assignment is: 0 Printing matrix reversed. 900.000000 625.000000 400.000000 225.000000 100.000000 25.000000 841.000000 576.000000 361.000000 196.000000 81.000000 16.000000 784.000000 529.000000 324.000000 169.000000 64.000000 9.000000 729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000 676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000 [[1]] [1] 0 > > proc.time() user system elapsed 0.283 0.054 0.319
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 (2025-06-13) -- "Great Square Root" Copyright (C) 2025 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths()); Attaching package: 'BufferedMatrix' The following objects are masked from 'package:base': colMeans, colSums, rowMeans, rowSums > > > ### this is used to control how many repetitions in something below > ### higher values result in more checks. > nreps <-100 ##20000 > > > ## test creation and some simple assignments and subsetting operations > > ## first on single elements > tmp <- createBufferedMatrix(1000,10) > > tmp[10,5] [1] 0 > tmp[10,5] <- 10 > tmp[10,5] [1] 10 > tmp[10,5] <- 12.445 > tmp[10,5] [1] 12.445 > > > > ## now testing accessing multiple elements > tmp2 <- createBufferedMatrix(10,20) > > > tmp2[3,1] <- 51.34 > tmp2[9,2] <- 9.87654 > tmp2[,1:2] [,1] [,2] [1,] 0.00 0.00000 [2,] 0.00 0.00000 [3,] 51.34 0.00000 [4,] 0.00 0.00000 [5,] 0.00 0.00000 [6,] 0.00 0.00000 [7,] 0.00 0.00000 [8,] 0.00 0.00000 [9,] 0.00 9.87654 [10,] 0.00 0.00000 > tmp2[,-(3:20)] [,1] [,2] [1,] 0.00 0.00000 [2,] 0.00 0.00000 [3,] 51.34 0.00000 [4,] 0.00 0.00000 [5,] 0.00 0.00000 [6,] 0.00 0.00000 [7,] 0.00 0.00000 [8,] 0.00 0.00000 [9,] 0.00 9.87654 [10,] 0.00 0.00000 > tmp2[3,] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0 [,14] [,15] [,16] [,17] [,18] [,19] [,20] [1,] 0 0 0 0 0 0 0 > tmp2[-3,] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0 [2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0 [3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0 [4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0 [5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0 [6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0 [7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0 [8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0 [9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0 [,14] [,15] [,16] [,17] [,18] [,19] [,20] [1,] 0 0 0 0 0 0 0 [2,] 0 0 0 0 0 0 0 [3,] 0 0 0 0 0 0 0 [4,] 0 0 0 0 0 0 0 [5,] 0 0 0 0 0 0 0 [6,] 0 0 0 0 0 0 0 [7,] 0 0 0 0 0 0 0 [8,] 0 0 0 0 0 0 0 [9,] 0 0 0 0 0 0 0 > tmp2[2,1:3] [,1] [,2] [,3] [1,] 0 0 0 > tmp2[3:9,1:3] [,1] [,2] [,3] [1,] 51.34 0.00000 0 [2,] 0.00 0.00000 0 [3,] 0.00 0.00000 0 [4,] 0.00 0.00000 0 [5,] 0.00 0.00000 0 [6,] 0.00 0.00000 0 [7,] 0.00 9.87654 0 > tmp2[-4,-4] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0 [2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0 [3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0 [4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0 [5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0 [6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0 [7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0 [8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0 [9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0 [,14] [,15] [,16] [,17] [,18] [,19] [1,] 0 0 0 0 0 0 [2,] 0 0 0 0 0 0 [3,] 0 0 0 0 0 0 [4,] 0 0 0 0 0 0 [5,] 0 0 0 0 0 0 [6,] 0 0 0 0 0 0 [7,] 0 0 0 0 0 0 [8,] 0 0 0 0 0 0 [9,] 0 0 0 0 0 0 > > ## now testing accessing/assigning multiple elements > tmp3 <- createBufferedMatrix(10,10) > > for (i in 1:10){ + for (j in 1:10){ + tmp3[i,j] <- (j-1)*10 + i + } + } > > tmp3[2:4,2:4] [,1] [,2] [,3] [1,] 12 22 32 [2,] 13 23 33 [3,] 14 24 34 > tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [1,] 11 21 31 11 21 31 91 1 11 1 11 21 31 [2,] 12 22 32 12 22 32 92 2 12 2 12 22 32 [3,] 13 23 33 13 23 33 93 3 13 3 13 23 33 [4,] 14 24 34 14 24 34 94 4 14 4 14 24 34 [5,] 15 25 35 15 25 35 95 5 15 5 15 25 35 [6,] 16 26 36 16 26 36 96 6 16 6 16 26 36 [7,] 17 27 37 17 27 37 97 7 17 7 17 27 37 [8,] 18 28 38 18 28 38 98 8 18 8 18 28 38 [9,] 19 29 39 19 29 39 99 9 19 9 19 29 39 [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25] [1,] 41 51 61 71 81 91 91 81 71 61 51 41 [2,] 42 52 62 72 82 92 92 82 72 62 52 42 [3,] 43 53 63 73 83 93 93 83 73 63 53 43 [4,] 44 54 64 74 84 94 94 84 74 64 54 44 [5,] 45 55 65 75 85 95 95 85 75 65 55 45 [6,] 46 56 66 76 86 96 96 86 76 66 56 46 [7,] 47 57 67 77 87 97 97 87 77 67 57 47 [8,] 48 58 68 78 88 98 98 88 78 68 58 48 [9,] 49 59 69 79 89 99 99 89 79 69 59 49 [,26] [,27] [,28] [,29] [1,] 31 21 11 1 [2,] 32 22 12 2 [3,] 33 23 13 3 [4,] 34 24 14 4 [5,] 35 25 15 5 [6,] 36 26 16 6 [7,] 37 27 17 7 [8,] 38 28 18 8 [9,] 39 29 19 9 > tmp3[-c(1:5),-c(6:10)] [,1] [,2] [,3] [,4] [,5] [1,] 6 16 26 36 46 [2,] 7 17 27 37 47 [3,] 8 18 28 38 48 [4,] 9 19 29 39 49 [5,] 10 20 30 40 50 > > ## assignment of whole columns > tmp3[,1] <- c(1:10*100.0) > tmp3[,1:2] <- tmp3[,1:2]*100 > tmp3[,1:2] <- tmp3[,2:1] > tmp3[,1:2] [,1] [,2] [1,] 1100 1e+04 [2,] 1200 2e+04 [3,] 1300 3e+04 [4,] 1400 4e+04 [5,] 1500 5e+04 [6,] 1600 6e+04 [7,] 1700 7e+04 [8,] 1800 8e+04 [9,] 1900 9e+04 [10,] 2000 1e+05 > > > tmp3[,-1] <- tmp3[,1:9] > tmp3[,1:10] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 1100 1100 1e+04 21 31 41 51 61 71 81 [2,] 1200 1200 2e+04 22 32 42 52 62 72 82 [3,] 1300 1300 3e+04 23 33 43 53 63 73 83 [4,] 1400 1400 4e+04 24 34 44 54 64 74 84 [5,] 1500 1500 5e+04 25 35 45 55 65 75 85 [6,] 1600 1600 6e+04 26 36 46 56 66 76 86 [7,] 1700 1700 7e+04 27 37 47 57 67 77 87 [8,] 1800 1800 8e+04 28 38 48 58 68 78 88 [9,] 1900 1900 9e+04 29 39 49 59 69 79 89 [10,] 2000 2000 1e+05 30 40 50 60 70 80 90 > > tmp3[,1:2] <- rep(1,10) > tmp3[,1:2] <- rep(1,20) > tmp3[,1:2] <- matrix(c(1:5),1,5) > > tmp3[,-c(1:8)] <- matrix(c(1:5),1,5) > > tmp3[1,] <- 1:10 > tmp3[1,] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 1 2 3 4 5 6 7 8 9 10 > tmp3[-1,] <- c(1,2) > tmp3[1:10,] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 1 2 3 4 5 6 7 8 9 10 [2,] 1 2 1 2 1 2 1 2 1 2 [3,] 2 1 2 1 2 1 2 1 2 1 [4,] 1 2 1 2 1 2 1 2 1 2 [5,] 2 1 2 1 2 1 2 1 2 1 [6,] 1 2 1 2 1 2 1 2 1 2 [7,] 2 1 2 1 2 1 2 1 2 1 [8,] 1 2 1 2 1 2 1 2 1 2 [9,] 2 1 2 1 2 1 2 1 2 1 [10,] 1 2 1 2 1 2 1 2 1 2 > tmp3[-c(1:8),] <- matrix(c(1:5),1,5) > tmp3[1:10,] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 1 2 3 4 5 6 7 8 9 10 [2,] 1 2 1 2 1 2 1 2 1 2 [3,] 2 1 2 1 2 1 2 1 2 1 [4,] 1 2 1 2 1 2 1 2 1 2 [5,] 2 1 2 1 2 1 2 1 2 1 [6,] 1 2 1 2 1 2 1 2 1 2 [7,] 2 1 2 1 2 1 2 1 2 1 [8,] 1 2 1 2 1 2 1 2 1 2 [9,] 1 3 5 2 4 1 3 5 2 4 [10,] 2 4 1 3 5 2 4 1 3 5 > > > tmp3[1:2,1:2] <- 5555.04 > tmp3[-(1:2),1:2] <- 1234.56789 > > > > ## testing accessors for the directory and prefix > directory(tmp3) [1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests" > prefix(tmp3) [1] "BM" > > ## testing if we can remove these objects > rm(tmp, tmp2, tmp3) > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 478417 25.6 1047105 56 639600 34.2 Vcells 885231 6.8 8388608 64 2081598 15.9 > > > > > ## > ## checking reads > ## > > tmp2 <- createBufferedMatrix(10,20) > > test.sample <- rnorm(10*20) > > tmp2[1:10,1:20] <- test.sample > > test.matrix <- matrix(test.sample,10,20) > > ## testing reads > for (rep in 1:nreps){ + which.row <- sample(1:10,1) + which.col <- sample(1:20,1) + if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){ + cat("incorrect agreement") + break; + } + } > > > for (rep in 1:nreps){ + which.row <- sample(1:10,1) + if (!all(tmp2[which.row,] == test.matrix[which.row,])){ + cat("incorrect agreement") + break; + } + } > > > for (rep in 1:nreps){ + which.col <- sample(1:20,1) + if (!all(tmp2[,which.col] == test.matrix[,which.col])){ + cat("incorrect agreement") + break; + } + } > > > > for (rep in 1:nreps){ + which.col <- sample(1:10,5,replace=TRUE) + if (!all(tmp2[,which.col] == test.matrix[,which.col])){ + cat("incorrect agreement") + break; + } + } > > > date() [1] "Tue Aug 19 20:40:00 2025" > for (rep in 1:nreps){ + which.row <- sample(1:10,5,replace=TRUE) + if (!all(tmp2[which.row,] == test.matrix[which.row,])){ + cat("incorrect agreement") + break; + } + } > date() [1] "Tue Aug 19 20:40:00 2025" > > > for (rep in 1:nreps){ + which.row <- sample(1:10,5,replace=TRUE) + which.col <- sample(1:10,5,replace=TRUE) + if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){ + cat("incorrect agreement") + break; + } + } > > > > > > RowMode(tmp2) <pointer: 0x5fe076cd0b80> > > > > for (rep in 1:nreps){ + which.row <- sample(1:10,1) + which.col <- sample(1:20,1) + if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){ + cat("incorrect agreement") + break; + } + } > > > for (rep in 1:nreps){ + which.row <- sample(1:10,1) + if (!all(tmp2[which.row,] == test.matrix[which.row,])){ + cat("incorrect agreement") + break; + } + } > > > for (rep in 1:nreps){ + which.col <- sample(1:20,1) + if (!all(tmp2[,which.col] == test.matrix[,which.col])){ + cat("incorrect agreement") + break; + } + } > > > > for (rep in 1:nreps){ + which.col <- sample(1:20,5,replace=TRUE) + if (!all(tmp2[,which.col] == test.matrix[,which.col])){ + cat("incorrect agreement") + break; + } + } > > > > for (rep in 1:nreps){ + which.row <- sample(1:10,5,replace=TRUE) + if (!all(tmp2[which.row,] == test.matrix[which.row,])){ + cat("incorrect agreement") + break; + } + } > > > date() [1] "Tue Aug 19 20:40:00 2025" > for (rep in 1:nreps){ + which.row <- sample(1:10,5,replace=TRUE) + which.col <- sample(1:20,5,replace=TRUE) + if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){ + cat("incorrect agreement") + break; + } + } > date() [1] "Tue Aug 19 20:40:00 2025" > > ColMode(tmp2) <pointer: 0x5fe076cd0b80> > > > > ### Now testing assignments > > for (rep in 1:nreps){ + which.row <- sample(1:10,1) + + new.data <- rnorm(20) + tmp2[which.row,] <- new.data + test.matrix[which.row,] <- new.data + if (rep > 1){ + if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){ + cat("incorrect agreement") + break; + } + } + prev.row <- which.row + + } > > > > > > for (rep in 1:nreps){ + which.col <- sample(1:20,1) + new.data <- rnorm(10) + tmp2[,which.col] <- new.data + test.matrix[,which.col]<- new.data + + if (rep > 1){ + if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){ + cat("incorrect agreement") + break; + } + } + prev.col <- which.col + } > > > > > > for (rep in 1:nreps){ + which.col <- sample(1:20,5,replace=TRUE) + new.data <- matrix(rnorm(50),5,10) + tmp2[,which.col] <- new.data + test.matrix[,which.col]<- new.data + + if (rep > 1){ + if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){ + cat("incorrect agreement") + break; + } + } + prev.col <- which.col + } > > > > for (rep in 1:nreps){ + which.row <- sample(1:10,5,replace=TRUE) + new.data <- matrix(rnorm(50),5,10) + tmp2[which.row,] <- new.data + test.matrix[which.row,]<- new.data + + if (rep > 1){ + if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){ + cat("incorrect agreement") + break; + } + } + prev.row <- which.row + } > > > > > > for (rep in 1:nreps){ + which.row <- sample(1:10,5,replace=TRUE) + which.col <- sample(1:20,5,replace=TRUE) + new.data <- matrix(rnorm(25),5,5) + tmp2[which.row,which.col] <- new.data + test.matrix[which.row,which.col]<- new.data + + if (rep > 1){ + if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){ + cat("incorrect agreement") + break; + } + } + prev.row <- which.row + prev.col <- which.col + } > > > > > ### > ### > ### testing some more functions > ### > > > > ## duplication function > tmp5 <- duplicate(tmp2) > > # making sure really did copy everything. > tmp5[1,1] <- tmp5[1,1] +100.00 > > if (tmp5[1,1] == tmp2[1,1]){ + stop("Problem with duplication") + } > > > > > ### testing elementwise applying of functions > > tmp5[1:4,1:4] [,1] [,2] [,3] [,4] [1,] 100.5199742 1.4952456 -1.0460748 1.1177256 [2,] -0.7610715 0.1165287 -0.3821007 -1.2595265 [3,] 0.8278580 0.5153239 -0.6253844 -1.0792470 [4,] 0.9258106 -0.3495005 -1.0021999 0.5044785 > ewApply(tmp5,abs) BufferedMatrix object Matrix size: 10 20 Buffer size: 1 1 Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 1.9 Kilobytes. Disk usage : 1.6 Kilobytes. > tmp5[1:4,1:4] [,1] [,2] [,3] [,4] [1,] 100.5199742 1.4952456 1.0460748 1.1177256 [2,] 0.7610715 0.1165287 0.3821007 1.2595265 [3,] 0.8278580 0.5153239 0.6253844 1.0792470 [4,] 0.9258106 0.3495005 1.0021999 0.5044785 > ewApply(tmp5,sqrt) BufferedMatrix object Matrix size: 10 20 Buffer size: 1 1 Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 1.9 Kilobytes. Disk usage : 1.6 Kilobytes. > tmp5[1:4,1:4] [,1] [,2] [,3] [,4] [1,] 10.0259650 1.2228024 1.0227780 1.0572254 [2,] 0.8723941 0.3413630 0.6181430 1.1222863 [3,] 0.9098671 0.7178606 0.7908125 1.0388682 [4,] 0.9621905 0.5911857 1.0010993 0.7102665 > > my.function <- function(x,power){ + (x+5)^power + } > > ewApply(tmp5,my.function,power=2) BufferedMatrix object Matrix size: 10 20 Buffer size: 1 1 Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 1.9 Kilobytes. Disk usage : 1.6 Kilobytes. > tmp5[1:4,1:4] [,1] [,2] [,3] [,4] [1,] 225.77962 38.72327 36.27385 36.68998 [2,] 34.48501 28.53016 31.56353 37.48239 [3,] 34.92653 32.69393 33.53351 36.46793 [4,] 35.54772 31.26136 36.01319 32.60714 > > > > ## testing functions that elementwise transform the matrix > sqrt(tmp5) <pointer: 0x5fe0757294b0> > exp(tmp5) <pointer: 0x5fe0757294b0> > log(tmp5,2) <pointer: 0x5fe0757294b0> > pow(tmp5,2) > > > > > > ## testing functions that apply to entire matrix > Max(tmp5) [1] 469.9307 > Min(tmp5) [1] 55.94516 > mean(tmp5) [1] 73.05823 > Sum(tmp5) [1] 14611.65 > Var(tmp5) [1] 869.6112 > > > ## testing functions applied to rows or columns > > rowMeans(tmp5) [1] 89.73490 72.04368 72.13165 72.67427 68.84563 73.81169 68.98814 70.04252 [9] 73.48455 68.82523 > rowSums(tmp5) [1] 1794.698 1440.874 1442.633 1453.485 1376.913 1476.234 1379.763 1400.850 [9] 1469.691 1376.505 > rowVars(tmp5) [1] 8071.54527 78.61535 79.51761 81.07068 54.51892 69.38894 [7] 62.41784 92.90863 74.90473 82.91272 > rowSd(tmp5) [1] 89.841779 8.866530 8.917265 9.003926 7.383693 8.330003 7.900496 [8] 9.638913 8.654752 9.105642 > rowMax(tmp5) [1] 469.93071 92.47315 95.13657 91.72367 84.49990 91.54227 86.58375 [8] 93.46933 88.40202 87.71275 > rowMin(tmp5) [1] 57.48243 59.38179 58.89368 55.94516 56.26046 58.46407 57.18948 57.08163 [9] 59.73449 56.12275 > > colMeans(tmp5) [1] 111.35589 69.51262 70.84354 71.19665 70.60437 72.60337 69.28772 [8] 71.69201 64.20738 71.01872 67.56539 70.92646 76.00639 75.80163 [15] 72.94451 71.07680 68.67273 71.58254 69.78212 74.48369 > colSums(tmp5) [1] 1113.5589 695.1262 708.4354 711.9665 706.0437 726.0337 692.8772 [8] 716.9201 642.0738 710.1872 675.6539 709.2646 760.0639 758.0163 [15] 729.4451 710.7680 686.7273 715.8254 697.8212 744.8369 > colVars(tmp5) [1] 15933.76845 77.85935 42.39237 77.22459 62.39602 63.19479 [7] 110.33166 47.77381 77.75489 74.96083 71.24767 83.90415 [13] 104.03143 149.70356 106.58172 68.74294 55.02734 76.33344 [19] 33.59307 42.90378 > colSd(tmp5) [1] 126.229032 8.823795 6.510942 8.787752 7.899115 7.949515 [7] 10.503888 6.911860 8.817873 8.657992 8.440834 9.159921 [13] 10.199580 12.235341 10.323842 8.291136 7.418041 8.736901 [19] 5.795953 6.550098 > colMax(tmp5) [1] 469.93071 82.90083 79.75539 81.45866 82.05287 86.58375 87.71275 [8] 82.77503 82.40530 83.18682 82.13048 93.46933 89.31545 95.13657 [15] 92.47315 84.49251 84.49990 89.28492 80.39795 91.54227 > colMin(tmp5) [1] 56.12275 57.08163 60.54191 57.23422 57.46222 58.29863 57.48243 61.19074 [9] 55.94516 59.30802 56.75152 59.93647 57.18948 61.33797 57.63558 58.89368 [17] 61.29953 60.77173 59.50582 66.15420 > > > ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default) > > > which.row <- sample(1:10,1,replace=TRUE) > which.col <- sample(1:20,1,replace=TRUE) > > tmp5[which.row,which.col] <- NA > > Max(tmp5) [1] NA > Min(tmp5) [1] NA > mean(tmp5) [1] NA > Sum(tmp5) [1] NA > Var(tmp5) [1] NA > > rowMeans(tmp5) [1] 89.73490 72.04368 72.13165 72.67427 68.84563 73.81169 68.98814 70.04252 [9] NA 68.82523 > rowSums(tmp5) [1] 1794.698 1440.874 1442.633 1453.485 1376.913 1476.234 1379.763 1400.850 [9] NA 1376.505 > rowVars(tmp5) [1] 8071.54527 78.61535 79.51761 81.07068 54.51892 69.38894 [7] 62.41784 92.90863 76.35568 82.91272 > rowSd(tmp5) [1] 89.841779 8.866530 8.917265 9.003926 7.383693 8.330003 7.900496 [8] 9.638913 8.738174 9.105642 > rowMax(tmp5) [1] 469.93071 92.47315 95.13657 91.72367 84.49990 91.54227 86.58375 [8] 93.46933 NA 87.71275 > rowMin(tmp5) [1] 57.48243 59.38179 58.89368 55.94516 56.26046 58.46407 57.18948 57.08163 [9] NA 56.12275 > > colMeans(tmp5) [1] 111.35589 69.51262 70.84354 NA 70.60437 72.60337 69.28772 [8] 71.69201 64.20738 71.01872 67.56539 70.92646 76.00639 75.80163 [15] 72.94451 71.07680 68.67273 71.58254 69.78212 74.48369 > colSums(tmp5) [1] 1113.5589 695.1262 708.4354 NA 706.0437 726.0337 692.8772 [8] 716.9201 642.0738 710.1872 675.6539 709.2646 760.0639 758.0163 [15] 729.4451 710.7680 686.7273 715.8254 697.8212 744.8369 > colVars(tmp5) [1] 15933.76845 77.85935 42.39237 NA 62.39602 63.19479 [7] 110.33166 47.77381 77.75489 74.96083 71.24767 83.90415 [13] 104.03143 149.70356 106.58172 68.74294 55.02734 76.33344 [19] 33.59307 42.90378 > colSd(tmp5) [1] 126.229032 8.823795 6.510942 NA 7.899115 7.949515 [7] 10.503888 6.911860 8.817873 8.657992 8.440834 9.159921 [13] 10.199580 12.235341 10.323842 8.291136 7.418041 8.736901 [19] 5.795953 6.550098 > colMax(tmp5) [1] 469.93071 82.90083 79.75539 NA 82.05287 86.58375 87.71275 [8] 82.77503 82.40530 83.18682 82.13048 93.46933 89.31545 95.13657 [15] 92.47315 84.49251 84.49990 89.28492 80.39795 91.54227 > colMin(tmp5) [1] 56.12275 57.08163 60.54191 NA 57.46222 58.29863 57.48243 61.19074 [9] 55.94516 59.30802 56.75152 59.93647 57.18948 61.33797 57.63558 58.89368 [17] 61.29953 60.77173 59.50582 66.15420 > > Max(tmp5,na.rm=TRUE) [1] 469.9307 > Min(tmp5,na.rm=TRUE) [1] 55.94516 > mean(tmp5,na.rm=TRUE) [1] 73.02187 > Sum(tmp5,na.rm=TRUE) [1] 14531.35 > Var(tmp5,na.rm=TRUE) [1] 873.7375 > > rowMeans(tmp5,na.rm=TRUE) [1] 89.73490 72.04368 72.13165 72.67427 68.84563 73.81169 68.98814 70.04252 [9] 73.12623 68.82523 > rowSums(tmp5,na.rm=TRUE) [1] 1794.698 1440.874 1442.633 1453.485 1376.913 1476.234 1379.763 1400.850 [9] 1389.398 1376.505 > rowVars(tmp5,na.rm=TRUE) [1] 8071.54527 78.61535 79.51761 81.07068 54.51892 69.38894 [7] 62.41784 92.90863 76.35568 82.91272 > rowSd(tmp5,na.rm=TRUE) [1] 89.841779 8.866530 8.917265 9.003926 7.383693 8.330003 7.900496 [8] 9.638913 8.738174 9.105642 > rowMax(tmp5,na.rm=TRUE) [1] 469.93071 92.47315 95.13657 91.72367 84.49990 91.54227 86.58375 [8] 93.46933 88.40202 87.71275 > rowMin(tmp5,na.rm=TRUE) [1] 57.48243 59.38179 58.89368 55.94516 56.26046 58.46407 57.18948 57.08163 [9] 59.73449 56.12275 > > colMeans(tmp5,na.rm=TRUE) [1] 111.35589 69.51262 70.84354 70.18600 70.60437 72.60337 69.28772 [8] 71.69201 64.20738 71.01872 67.56539 70.92646 76.00639 75.80163 [15] 72.94451 71.07680 68.67273 71.58254 69.78212 74.48369 > colSums(tmp5,na.rm=TRUE) [1] 1113.5589 695.1262 708.4354 631.6740 706.0437 726.0337 692.8772 [8] 716.9201 642.0738 710.1872 675.6539 709.2646 760.0639 758.0163 [15] 729.4451 710.7680 686.7273 715.8254 697.8212 744.8369 > colVars(tmp5,na.rm=TRUE) [1] 15933.76845 77.85935 42.39237 75.38675 62.39602 63.19479 [7] 110.33166 47.77381 77.75489 74.96083 71.24767 83.90415 [13] 104.03143 149.70356 106.58172 68.74294 55.02734 76.33344 [19] 33.59307 42.90378 > colSd(tmp5,na.rm=TRUE) [1] 126.229032 8.823795 6.510942 8.682554 7.899115 7.949515 [7] 10.503888 6.911860 8.817873 8.657992 8.440834 9.159921 [13] 10.199580 12.235341 10.323842 8.291136 7.418041 8.736901 [19] 5.795953 6.550098 > colMax(tmp5,na.rm=TRUE) [1] 469.93071 82.90083 79.75539 81.45866 82.05287 86.58375 87.71275 [8] 82.77503 82.40530 83.18682 82.13048 93.46933 89.31545 95.13657 [15] 92.47315 84.49251 84.49990 89.28492 80.39795 91.54227 > colMin(tmp5,na.rm=TRUE) [1] 56.12275 57.08163 60.54191 57.23422 57.46222 58.29863 57.48243 61.19074 [9] 55.94516 59.30802 56.75152 59.93647 57.18948 61.33797 57.63558 58.89368 [17] 61.29953 60.77173 59.50582 66.15420 > > # now set an entire row to NA > > tmp5[which.row,] <- NA > rowMeans(tmp5,na.rm=TRUE) [1] 89.73490 72.04368 72.13165 72.67427 68.84563 73.81169 68.98814 70.04252 [9] NaN 68.82523 > rowSums(tmp5,na.rm=TRUE) [1] 1794.698 1440.874 1442.633 1453.485 1376.913 1476.234 1379.763 1400.850 [9] 0.000 1376.505 > rowVars(tmp5,na.rm=TRUE) [1] 8071.54527 78.61535 79.51761 81.07068 54.51892 69.38894 [7] 62.41784 92.90863 NA 82.91272 > rowSd(tmp5,na.rm=TRUE) [1] 89.841779 8.866530 8.917265 9.003926 7.383693 8.330003 7.900496 [8] 9.638913 NA 9.105642 > rowMax(tmp5,na.rm=TRUE) [1] 469.93071 92.47315 95.13657 91.72367 84.49990 91.54227 86.58375 [8] 93.46933 NA 87.71275 > rowMin(tmp5,na.rm=TRUE) [1] 57.48243 59.38179 58.89368 55.94516 56.26046 58.46407 57.18948 57.08163 [9] NA 56.12275 > > > # now set an entire col to NA > > > tmp5[,which.col] <- NA > colMeans(tmp5,na.rm=TRUE) [1] 114.62889 68.02504 70.66822 NaN 71.12035 72.40545 69.60878 [8] 70.87557 62.18539 70.16522 68.43549 71.22051 74.98051 75.55374 [15] 71.22700 71.66816 69.40717 72.49340 69.95306 75.40919 > colSums(tmp5,na.rm=TRUE) [1] 1031.6600 612.2254 636.0140 0.0000 640.0831 651.6491 626.4790 [8] 637.8801 559.6685 631.4870 615.9194 640.9846 674.8246 679.9837 [15] 641.0430 645.0134 624.6645 652.4406 629.5775 678.6827 > colVars(tmp5,na.rm=TRUE) [1] 17804.97413 62.69676 47.34564 NA 67.20038 70.65346 [7] 122.96347 46.24654 41.47922 76.13581 71.63654 93.41940 [13] 105.19545 167.72519 86.71906 73.40162 55.83743 76.54133 [19] 37.46349 38.63059 > colSd(tmp5,na.rm=TRUE) [1] 133.435281 7.918129 6.880817 NA 8.197584 8.405561 [7] 11.088889 6.800481 6.440436 8.725584 8.463837 9.665371 [13] 10.256483 12.950876 9.312307 8.567475 7.472445 8.748790 [19] 6.120742 6.215351 > colMax(tmp5,na.rm=TRUE) [1] 469.93071 80.59741 79.75539 -Inf 82.05287 86.58375 87.71275 [8] 82.77503 73.99097 83.18682 82.13048 93.46933 89.31545 95.13657 [15] 92.47315 84.49251 84.49990 89.28492 80.39795 91.54227 > colMin(tmp5,na.rm=TRUE) [1] 56.12275 57.08163 60.54191 Inf 57.46222 58.29863 57.48243 61.19074 [9] 55.94516 59.30802 56.75152 59.93647 57.18948 61.33797 57.63558 58.89368 [17] 61.29953 60.77173 59.50582 71.30854 > > > > > copymatrix <- matrix(rnorm(200,150,15),10,20) > > tmp5[1:10,1:20] <- copymatrix > which.row <- 3 > which.col <- 1 > cat(which.row," ",which.col,"\n") 3 1 > tmp5[which.row,which.col] <- NA > copymatrix[which.row,which.col] <- NA > > rowVars(tmp5,na.rm=TRUE) [1] 234.3964 276.4532 181.3605 128.9958 171.3233 119.0143 191.5303 168.0296 [9] 278.4588 307.6096 > apply(copymatrix,1,var,na.rm=TRUE) [1] 234.3964 276.4532 181.3605 128.9958 171.3233 119.0143 191.5303 168.0296 [9] 278.4588 307.6096 > > > > copymatrix <- matrix(rnorm(200,150,15),10,20) > > tmp5[1:10,1:20] <- copymatrix > which.row <- 1 > which.col <- 3 > cat(which.row," ",which.col,"\n") 1 3 > tmp5[which.row,which.col] <- NA > copymatrix[which.row,which.col] <- NA > > colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE) [1] -3.410605e-13 2.842171e-14 -3.552714e-14 5.684342e-14 1.136868e-13 [6] 0.000000e+00 -1.136868e-13 5.684342e-14 5.684342e-14 2.842171e-14 [11] -2.842171e-14 -5.684342e-14 2.842171e-14 -2.273737e-13 0.000000e+00 [16] -5.684342e-14 2.842171e-14 -2.557954e-13 -5.684342e-14 -1.136868e-13 > > > > > > > > > > > ## making sure these things agree > ## > ## first when there is no NA > > > > agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){ + + if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){ + stop("No agreement in Max") + } + + + if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){ + stop("No agreement in Min") + } + + + if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){ + + cat(Sum(buff.matrix,na.rm=TRUE),"\n") + cat(sum(r.matrix,na.rm=TRUE),"\n") + cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n") + + stop("No agreement in Sum") + } + + if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){ + stop("No agreement in mean") + } + + + if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){ + stop("No agreement in Var") + } + + + + if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in rowMeans") + } + + + if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){ + stop("No agreement in colMeans") + } + + + if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){ + stop("No agreement in rowSums") + } + + + if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){ + stop("No agreement in colSums") + } + + ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when + ### computing variance + my.Var <- function(x,na.rm=FALSE){ + if (all(is.na(x))){ + return(NA) + } else { + var(x,na.rm=na.rm) + } + + } + + if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in rowVars") + } + + + if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in rowVars") + } + + + if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colMax") + } + + + if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colMax") + } + + + + if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colMin") + } + + + if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colMin") + } + + if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colMedian") + } + + if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colRanges") + } + + + + } > > > > > > > > > > for (rep in 1:20){ + copymatrix <- matrix(rnorm(200,150,15),10,20) + + tmp5[1:10,1:20] <- copymatrix + + + agree.checks(tmp5,copymatrix) + + ## now lets assign some NA values and check agreement + + which.row <- sample(1:10,1,replace=TRUE) + which.col <- sample(1:20,1,replace=TRUE) + + cat(which.row," ",which.col,"\n") + + tmp5[which.row,which.col] <- NA + copymatrix[which.row,which.col] <- NA + + agree.checks(tmp5,copymatrix) + + ## make an entire row NA + tmp5[which.row,] <- NA + copymatrix[which.row,] <- NA + + + agree.checks(tmp5,copymatrix) + + ### also make an entire col NA + tmp5[,which.col] <- NA + copymatrix[,which.col] <- NA + + agree.checks(tmp5,copymatrix) + + ### now make 1 element non NA with NA in the rest of row and column + + tmp5[which.row,which.col] <- rnorm(1,150,15) + copymatrix[which.row,which.col] <- tmp5[which.row,which.col] + + agree.checks(tmp5,copymatrix) + } 6 12 4 10 1 8 7 12 7 19 4 3 9 14 9 10 10 6 4 14 9 1 2 15 3 15 3 4 3 14 10 14 4 18 5 11 9 10 8 2 There were 50 or more warnings (use warnings() to see the first 50) > > > ### now test 1 by n and n by 1 matrix > > > err.tol <- 1e-12 > > rm(tmp5) > > dataset1 <- rnorm(100) > dataset2 <- rnorm(100) > > tmp <- createBufferedMatrix(1,100) > tmp[1,] <- dataset1 > > tmp2 <- createBufferedMatrix(100,1) > tmp2[,1] <- dataset2 > > > > > > Max(tmp) [1] 3.867424 > Min(tmp) [1] -1.721176 > mean(tmp) [1] 0.0622083 > Sum(tmp) [1] 6.22083 > Var(tmp) [1] 0.905356 > > rowMeans(tmp) [1] 0.0622083 > rowSums(tmp) [1] 6.22083 > rowVars(tmp) [1] 0.905356 > rowSd(tmp) [1] 0.951502 > rowMax(tmp) [1] 3.867424 > rowMin(tmp) [1] -1.721176 > > colMeans(tmp) [1] 0.749984532 0.903581436 -1.086165024 0.330568750 0.609928461 [6] -0.069469236 1.224365939 -0.471066135 -0.372025415 -0.274870500 [11] 0.580713938 -0.301345308 0.532893085 0.003992507 -0.496071213 [16] 1.380533786 1.574076036 1.755105999 -0.992663088 -1.185402474 [21] 0.038432279 -1.560321630 -0.141523270 0.856113247 0.676420078 [26] -0.164169435 3.867423946 1.138330544 0.051226351 0.726946694 [31] -0.530201991 1.039680860 -0.248471569 -0.889728897 0.901437076 [36] -1.648162770 0.438320522 -0.211609090 1.160269680 2.673691223 [41] -0.588266084 -0.496176979 1.050404024 1.001266535 0.108447516 [46] -1.721176313 -0.425761898 1.214396577 -0.351977432 -0.230879901 [51] 0.686391418 -0.877122481 0.948277864 1.055828970 -0.030754321 [56] -0.693905220 0.278215727 0.048902486 -1.067146455 -1.049033659 [61] 0.838429614 0.321847170 -0.227322735 0.594265130 -0.977145728 [66] -1.594120039 -1.130060612 0.665101387 -0.601715688 0.680177638 [71] -0.613514535 0.299200269 -0.360392364 -1.116151444 0.674175643 [76] -0.604265565 -0.897462015 1.449572660 0.568765662 0.499181629 [81] -1.131838050 0.471917381 -0.422822233 1.389691725 0.268443297 [86] -0.875859740 0.932557990 -0.611121533 -0.686834443 -1.097874579 [91] -0.461305047 -0.190654944 1.569959915 -0.811701452 0.300263859 [96] -0.085653673 -0.714689872 -0.510752432 -0.179317109 -0.830845405 > colSums(tmp) [1] 0.749984532 0.903581436 -1.086165024 0.330568750 0.609928461 [6] -0.069469236 1.224365939 -0.471066135 -0.372025415 -0.274870500 [11] 0.580713938 -0.301345308 0.532893085 0.003992507 -0.496071213 [16] 1.380533786 1.574076036 1.755105999 -0.992663088 -1.185402474 [21] 0.038432279 -1.560321630 -0.141523270 0.856113247 0.676420078 [26] -0.164169435 3.867423946 1.138330544 0.051226351 0.726946694 [31] -0.530201991 1.039680860 -0.248471569 -0.889728897 0.901437076 [36] -1.648162770 0.438320522 -0.211609090 1.160269680 2.673691223 [41] -0.588266084 -0.496176979 1.050404024 1.001266535 0.108447516 [46] -1.721176313 -0.425761898 1.214396577 -0.351977432 -0.230879901 [51] 0.686391418 -0.877122481 0.948277864 1.055828970 -0.030754321 [56] -0.693905220 0.278215727 0.048902486 -1.067146455 -1.049033659 [61] 0.838429614 0.321847170 -0.227322735 0.594265130 -0.977145728 [66] -1.594120039 -1.130060612 0.665101387 -0.601715688 0.680177638 [71] -0.613514535 0.299200269 -0.360392364 -1.116151444 0.674175643 [76] -0.604265565 -0.897462015 1.449572660 0.568765662 0.499181629 [81] -1.131838050 0.471917381 -0.422822233 1.389691725 0.268443297 [86] -0.875859740 0.932557990 -0.611121533 -0.686834443 -1.097874579 [91] -0.461305047 -0.190654944 1.569959915 -0.811701452 0.300263859 [96] -0.085653673 -0.714689872 -0.510752432 -0.179317109 -0.830845405 > colVars(tmp) [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA > colSd(tmp) [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA > colMax(tmp) [1] 0.749984532 0.903581436 -1.086165024 0.330568750 0.609928461 [6] -0.069469236 1.224365939 -0.471066135 -0.372025415 -0.274870500 [11] 0.580713938 -0.301345308 0.532893085 0.003992507 -0.496071213 [16] 1.380533786 1.574076036 1.755105999 -0.992663088 -1.185402474 [21] 0.038432279 -1.560321630 -0.141523270 0.856113247 0.676420078 [26] -0.164169435 3.867423946 1.138330544 0.051226351 0.726946694 [31] -0.530201991 1.039680860 -0.248471569 -0.889728897 0.901437076 [36] -1.648162770 0.438320522 -0.211609090 1.160269680 2.673691223 [41] -0.588266084 -0.496176979 1.050404024 1.001266535 0.108447516 [46] -1.721176313 -0.425761898 1.214396577 -0.351977432 -0.230879901 [51] 0.686391418 -0.877122481 0.948277864 1.055828970 -0.030754321 [56] -0.693905220 0.278215727 0.048902486 -1.067146455 -1.049033659 [61] 0.838429614 0.321847170 -0.227322735 0.594265130 -0.977145728 [66] -1.594120039 -1.130060612 0.665101387 -0.601715688 0.680177638 [71] -0.613514535 0.299200269 -0.360392364 -1.116151444 0.674175643 [76] -0.604265565 -0.897462015 1.449572660 0.568765662 0.499181629 [81] -1.131838050 0.471917381 -0.422822233 1.389691725 0.268443297 [86] -0.875859740 0.932557990 -0.611121533 -0.686834443 -1.097874579 [91] -0.461305047 -0.190654944 1.569959915 -0.811701452 0.300263859 [96] -0.085653673 -0.714689872 -0.510752432 -0.179317109 -0.830845405 > colMin(tmp) [1] 0.749984532 0.903581436 -1.086165024 0.330568750 0.609928461 [6] -0.069469236 1.224365939 -0.471066135 -0.372025415 -0.274870500 [11] 0.580713938 -0.301345308 0.532893085 0.003992507 -0.496071213 [16] 1.380533786 1.574076036 1.755105999 -0.992663088 -1.185402474 [21] 0.038432279 -1.560321630 -0.141523270 0.856113247 0.676420078 [26] -0.164169435 3.867423946 1.138330544 0.051226351 0.726946694 [31] -0.530201991 1.039680860 -0.248471569 -0.889728897 0.901437076 [36] -1.648162770 0.438320522 -0.211609090 1.160269680 2.673691223 [41] -0.588266084 -0.496176979 1.050404024 1.001266535 0.108447516 [46] -1.721176313 -0.425761898 1.214396577 -0.351977432 -0.230879901 [51] 0.686391418 -0.877122481 0.948277864 1.055828970 -0.030754321 [56] -0.693905220 0.278215727 0.048902486 -1.067146455 -1.049033659 [61] 0.838429614 0.321847170 -0.227322735 0.594265130 -0.977145728 [66] -1.594120039 -1.130060612 0.665101387 -0.601715688 0.680177638 [71] -0.613514535 0.299200269 -0.360392364 -1.116151444 0.674175643 [76] -0.604265565 -0.897462015 1.449572660 0.568765662 0.499181629 [81] -1.131838050 0.471917381 -0.422822233 1.389691725 0.268443297 [86] -0.875859740 0.932557990 -0.611121533 -0.686834443 -1.097874579 [91] -0.461305047 -0.190654944 1.569959915 -0.811701452 0.300263859 [96] -0.085653673 -0.714689872 -0.510752432 -0.179317109 -0.830845405 > colMedians(tmp) [1] 0.749984532 0.903581436 -1.086165024 0.330568750 0.609928461 [6] -0.069469236 1.224365939 -0.471066135 -0.372025415 -0.274870500 [11] 0.580713938 -0.301345308 0.532893085 0.003992507 -0.496071213 [16] 1.380533786 1.574076036 1.755105999 -0.992663088 -1.185402474 [21] 0.038432279 -1.560321630 -0.141523270 0.856113247 0.676420078 [26] -0.164169435 3.867423946 1.138330544 0.051226351 0.726946694 [31] -0.530201991 1.039680860 -0.248471569 -0.889728897 0.901437076 [36] -1.648162770 0.438320522 -0.211609090 1.160269680 2.673691223 [41] -0.588266084 -0.496176979 1.050404024 1.001266535 0.108447516 [46] -1.721176313 -0.425761898 1.214396577 -0.351977432 -0.230879901 [51] 0.686391418 -0.877122481 0.948277864 1.055828970 -0.030754321 [56] -0.693905220 0.278215727 0.048902486 -1.067146455 -1.049033659 [61] 0.838429614 0.321847170 -0.227322735 0.594265130 -0.977145728 [66] -1.594120039 -1.130060612 0.665101387 -0.601715688 0.680177638 [71] -0.613514535 0.299200269 -0.360392364 -1.116151444 0.674175643 [76] -0.604265565 -0.897462015 1.449572660 0.568765662 0.499181629 [81] -1.131838050 0.471917381 -0.422822233 1.389691725 0.268443297 [86] -0.875859740 0.932557990 -0.611121533 -0.686834443 -1.097874579 [91] -0.461305047 -0.190654944 1.569959915 -0.811701452 0.300263859 [96] -0.085653673 -0.714689872 -0.510752432 -0.179317109 -0.830845405 > colRanges(tmp) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [1,] 0.7499845 0.9035814 -1.086165 0.3305688 0.6099285 -0.06946924 1.224366 [2,] 0.7499845 0.9035814 -1.086165 0.3305688 0.6099285 -0.06946924 1.224366 [,8] [,9] [,10] [,11] [,12] [,13] [1,] -0.4710661 -0.3720254 -0.2748705 0.5807139 -0.3013453 0.5328931 [2,] -0.4710661 -0.3720254 -0.2748705 0.5807139 -0.3013453 0.5328931 [,14] [,15] [,16] [,17] [,18] [,19] [,20] [1,] 0.003992507 -0.4960712 1.380534 1.574076 1.755106 -0.9926631 -1.185402 [2,] 0.003992507 -0.4960712 1.380534 1.574076 1.755106 -0.9926631 -1.185402 [,21] [,22] [,23] [,24] [,25] [,26] [,27] [1,] 0.03843228 -1.560322 -0.1415233 0.8561132 0.6764201 -0.1641694 3.867424 [2,] 0.03843228 -1.560322 -0.1415233 0.8561132 0.6764201 -0.1641694 3.867424 [,28] [,29] [,30] [,31] [,32] [,33] [,34] [1,] 1.138331 0.05122635 0.7269467 -0.530202 1.039681 -0.2484716 -0.8897289 [2,] 1.138331 0.05122635 0.7269467 -0.530202 1.039681 -0.2484716 -0.8897289 [,35] [,36] [,37] [,38] [,39] [,40] [,41] [1,] 0.9014371 -1.648163 0.4383205 -0.2116091 1.16027 2.673691 -0.5882661 [2,] 0.9014371 -1.648163 0.4383205 -0.2116091 1.16027 2.673691 -0.5882661 [,42] [,43] [,44] [,45] [,46] [,47] [,48] [1,] -0.496177 1.050404 1.001267 0.1084475 -1.721176 -0.4257619 1.214397 [2,] -0.496177 1.050404 1.001267 0.1084475 -1.721176 -0.4257619 1.214397 [,49] [,50] [,51] [,52] [,53] [,54] [,55] [1,] -0.3519774 -0.2308799 0.6863914 -0.8771225 0.9482779 1.055829 -0.03075432 [2,] -0.3519774 -0.2308799 0.6863914 -0.8771225 0.9482779 1.055829 -0.03075432 [,56] [,57] [,58] [,59] [,60] [,61] [,62] [1,] -0.6939052 0.2782157 0.04890249 -1.067146 -1.049034 0.8384296 0.3218472 [2,] -0.6939052 0.2782157 0.04890249 -1.067146 -1.049034 0.8384296 0.3218472 [,63] [,64] [,65] [,66] [,67] [,68] [,69] [1,] -0.2273227 0.5942651 -0.9771457 -1.59412 -1.130061 0.6651014 -0.6017157 [2,] -0.2273227 0.5942651 -0.9771457 -1.59412 -1.130061 0.6651014 -0.6017157 [,70] [,71] [,72] [,73] [,74] [,75] [,76] [1,] 0.6801776 -0.6135145 0.2992003 -0.3603924 -1.116151 0.6741756 -0.6042656 [2,] 0.6801776 -0.6135145 0.2992003 -0.3603924 -1.116151 0.6741756 -0.6042656 [,77] [,78] [,79] [,80] [,81] [,82] [,83] [1,] -0.897462 1.449573 0.5687657 0.4991816 -1.131838 0.4719174 -0.4228222 [2,] -0.897462 1.449573 0.5687657 0.4991816 -1.131838 0.4719174 -0.4228222 [,84] [,85] [,86] [,87] [,88] [,89] [,90] [1,] 1.389692 0.2684433 -0.8758597 0.932558 -0.6111215 -0.6868344 -1.097875 [2,] 1.389692 0.2684433 -0.8758597 0.932558 -0.6111215 -0.6868344 -1.097875 [,91] [,92] [,93] [,94] [,95] [,96] [,97] [1,] -0.461305 -0.1906549 1.56996 -0.8117015 0.3002639 -0.08565367 -0.7146899 [2,] -0.461305 -0.1906549 1.56996 -0.8117015 0.3002639 -0.08565367 -0.7146899 [,98] [,99] [,100] [1,] -0.5107524 -0.1793171 -0.8308454 [2,] -0.5107524 -0.1793171 -0.8308454 > > > Max(tmp2) [1] 2.276088 > Min(tmp2) [1] -1.874163 > mean(tmp2) [1] 0.1121943 > Sum(tmp2) [1] 11.21943 > Var(tmp2) [1] 0.8534469 > > rowMeans(tmp2) [1] 1.16871426 0.29088905 -0.28764169 -1.34607302 1.17690968 1.32861337 [7] -0.39192455 0.37645875 0.33207075 0.23640374 -0.61813240 2.27608800 [13] -0.75644382 1.67409599 -0.27064620 0.07680682 0.89137391 -0.89490773 [19] -0.37294620 -0.05030148 -1.25065302 0.46779617 0.46107982 0.51889415 [25] -1.33553781 -0.40346476 -1.06767525 1.33430064 0.65113253 -0.69106959 [31] 0.72578680 2.11274796 -1.40187787 -0.77434016 0.52954060 1.54200505 [37] 1.84568118 1.51277987 -0.44939275 0.91449721 0.51555884 0.43116484 [43] -0.59836999 1.56724577 0.23730924 -1.56431070 -1.11622091 0.28549073 [49] -1.54069617 -0.48635253 -0.19614977 -0.21937561 -1.63713752 -0.42537081 [55] -1.87416266 1.22278433 0.93941402 0.20069034 -1.20534317 -0.27068236 [61] 2.06573116 1.25796408 0.73161839 0.69740549 0.06169100 -1.16733658 [67] 0.06384200 0.38461299 0.67429156 -0.22846795 -0.04513310 0.10624410 [73] -0.31157307 -0.52128989 -1.61666527 0.23031345 0.57515691 -0.07237459 [79] 0.67220199 -0.87403582 1.01921341 0.48194654 0.93124399 -0.11391046 [85] 0.97990792 0.59863298 -0.05080045 0.27382911 1.57004811 0.87701506 [91] -0.52031277 0.33440311 -0.01393692 -0.56201649 -0.21371922 0.03994205 [97] -0.44095999 0.11868751 0.17639632 -1.29749857 > rowSums(tmp2) [1] 1.16871426 0.29088905 -0.28764169 -1.34607302 1.17690968 1.32861337 [7] -0.39192455 0.37645875 0.33207075 0.23640374 -0.61813240 2.27608800 [13] -0.75644382 1.67409599 -0.27064620 0.07680682 0.89137391 -0.89490773 [19] -0.37294620 -0.05030148 -1.25065302 0.46779617 0.46107982 0.51889415 [25] -1.33553781 -0.40346476 -1.06767525 1.33430064 0.65113253 -0.69106959 [31] 0.72578680 2.11274796 -1.40187787 -0.77434016 0.52954060 1.54200505 [37] 1.84568118 1.51277987 -0.44939275 0.91449721 0.51555884 0.43116484 [43] -0.59836999 1.56724577 0.23730924 -1.56431070 -1.11622091 0.28549073 [49] -1.54069617 -0.48635253 -0.19614977 -0.21937561 -1.63713752 -0.42537081 [55] -1.87416266 1.22278433 0.93941402 0.20069034 -1.20534317 -0.27068236 [61] 2.06573116 1.25796408 0.73161839 0.69740549 0.06169100 -1.16733658 [67] 0.06384200 0.38461299 0.67429156 -0.22846795 -0.04513310 0.10624410 [73] -0.31157307 -0.52128989 -1.61666527 0.23031345 0.57515691 -0.07237459 [79] 0.67220199 -0.87403582 1.01921341 0.48194654 0.93124399 -0.11391046 [85] 0.97990792 0.59863298 -0.05080045 0.27382911 1.57004811 0.87701506 [91] -0.52031277 0.33440311 -0.01393692 -0.56201649 -0.21371922 0.03994205 [97] -0.44095999 0.11868751 0.17639632 -1.29749857 > rowVars(tmp2) [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA > rowSd(tmp2) [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA > rowMax(tmp2) [1] 1.16871426 0.29088905 -0.28764169 -1.34607302 1.17690968 1.32861337 [7] -0.39192455 0.37645875 0.33207075 0.23640374 -0.61813240 2.27608800 [13] -0.75644382 1.67409599 -0.27064620 0.07680682 0.89137391 -0.89490773 [19] -0.37294620 -0.05030148 -1.25065302 0.46779617 0.46107982 0.51889415 [25] -1.33553781 -0.40346476 -1.06767525 1.33430064 0.65113253 -0.69106959 [31] 0.72578680 2.11274796 -1.40187787 -0.77434016 0.52954060 1.54200505 [37] 1.84568118 1.51277987 -0.44939275 0.91449721 0.51555884 0.43116484 [43] -0.59836999 1.56724577 0.23730924 -1.56431070 -1.11622091 0.28549073 [49] -1.54069617 -0.48635253 -0.19614977 -0.21937561 -1.63713752 -0.42537081 [55] -1.87416266 1.22278433 0.93941402 0.20069034 -1.20534317 -0.27068236 [61] 2.06573116 1.25796408 0.73161839 0.69740549 0.06169100 -1.16733658 [67] 0.06384200 0.38461299 0.67429156 -0.22846795 -0.04513310 0.10624410 [73] -0.31157307 -0.52128989 -1.61666527 0.23031345 0.57515691 -0.07237459 [79] 0.67220199 -0.87403582 1.01921341 0.48194654 0.93124399 -0.11391046 [85] 0.97990792 0.59863298 -0.05080045 0.27382911 1.57004811 0.87701506 [91] -0.52031277 0.33440311 -0.01393692 -0.56201649 -0.21371922 0.03994205 [97] -0.44095999 0.11868751 0.17639632 -1.29749857 > rowMin(tmp2) [1] 1.16871426 0.29088905 -0.28764169 -1.34607302 1.17690968 1.32861337 [7] -0.39192455 0.37645875 0.33207075 0.23640374 -0.61813240 2.27608800 [13] -0.75644382 1.67409599 -0.27064620 0.07680682 0.89137391 -0.89490773 [19] -0.37294620 -0.05030148 -1.25065302 0.46779617 0.46107982 0.51889415 [25] -1.33553781 -0.40346476 -1.06767525 1.33430064 0.65113253 -0.69106959 [31] 0.72578680 2.11274796 -1.40187787 -0.77434016 0.52954060 1.54200505 [37] 1.84568118 1.51277987 -0.44939275 0.91449721 0.51555884 0.43116484 [43] -0.59836999 1.56724577 0.23730924 -1.56431070 -1.11622091 0.28549073 [49] -1.54069617 -0.48635253 -0.19614977 -0.21937561 -1.63713752 -0.42537081 [55] -1.87416266 1.22278433 0.93941402 0.20069034 -1.20534317 -0.27068236 [61] 2.06573116 1.25796408 0.73161839 0.69740549 0.06169100 -1.16733658 [67] 0.06384200 0.38461299 0.67429156 -0.22846795 -0.04513310 0.10624410 [73] -0.31157307 -0.52128989 -1.61666527 0.23031345 0.57515691 -0.07237459 [79] 0.67220199 -0.87403582 1.01921341 0.48194654 0.93124399 -0.11391046 [85] 0.97990792 0.59863298 -0.05080045 0.27382911 1.57004811 0.87701506 [91] -0.52031277 0.33440311 -0.01393692 -0.56201649 -0.21371922 0.03994205 [97] -0.44095999 0.11868751 0.17639632 -1.29749857 > > colMeans(tmp2) [1] 0.1121943 > colSums(tmp2) [1] 11.21943 > colVars(tmp2) [1] 0.8534469 > colSd(tmp2) [1] 0.9238219 > colMax(tmp2) [1] 2.276088 > colMin(tmp2) [1] -1.874163 > colMedians(tmp2) [1] 0.1124658 > colRanges(tmp2) [,1] [1,] -1.874163 [2,] 2.276088 > > dataset1 <- matrix(dataset1,1,100) > > agree.checks(tmp,dataset1) > > dataset2 <- matrix(dataset2,100,1) > agree.checks(tmp2,dataset2) > > > tmp <- createBufferedMatrix(10,10) > > tmp[1:10,1:10] <- rnorm(100) > colApply(tmp,sum) [1] 3.7648811 2.2513263 0.6913985 3.3294526 3.4701917 0.8930821 [7] -3.2378683 1.5525471 -1.7686455 -0.5589726 > colApply(tmp,quantile)[,1] [,1] [1,] -0.49781876 [2,] -0.02937338 [3,] 0.22340865 [4,] 0.74544763 [5,] 1.81687765 > > rowApply(tmp,sum) [1] 0.7797138 6.0522035 4.7711359 0.0315975 -6.2575593 1.9714547 [7] 2.1755684 0.4966939 0.6308201 -0.2642355 > rowApply(tmp,rank)[1:10,] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 10 9 4 3 9 5 5 8 6 8 [2,] 3 10 2 1 8 8 6 1 9 6 [3,] 8 2 7 8 2 4 10 4 8 4 [4,] 1 5 8 9 5 10 2 7 5 9 [5,] 6 6 10 4 7 9 9 2 7 1 [6,] 5 3 5 10 6 3 7 5 10 2 [7,] 9 7 3 2 3 1 8 3 1 5 [8,] 7 4 9 5 10 6 1 9 2 3 [9,] 4 8 1 6 1 2 3 10 3 10 [10,] 2 1 6 7 4 7 4 6 4 7 > > tmp <- createBufferedMatrix(5,20) > > tmp[1:5,1:20] <- rnorm(100) > colApply(tmp,sum) [1] -1.85355815 -1.08764035 3.29711107 -0.10416260 -0.34400078 1.08729212 [7] 1.07713168 -1.39948929 -0.67747601 2.38579242 0.01997558 -2.28853175 [13] -2.14077301 2.22446454 0.79412077 -1.35308081 0.37842842 1.51959094 [19] -1.00798117 -0.56381311 > colApply(tmp,quantile)[,1] [,1] [1,] -1.3850150 [2,] -0.7730625 [3,] -0.3791950 [4,] 0.1046511 [5,] 0.5790633 > > rowApply(tmp,sum) [1] -0.5239173 2.2236526 -0.8004806 2.1259203 -3.0617744 > rowApply(tmp,rank)[1:5,] [,1] [,2] [,3] [,4] [,5] [1,] 14 5 3 7 13 [2,] 5 7 6 12 17 [3,] 19 3 20 8 19 [4,] 16 13 18 2 8 [5,] 15 11 10 11 4 > > > as.matrix(tmp) [,1] [,2] [,3] [,4] [,5] [,6] [1,] 0.5790633 -0.79634050 1.0544060 0.6609056 0.622828825 1.08908601 [2,] -0.7730625 -0.31568140 -0.9307932 0.2512934 0.047166639 0.02704342 [3,] -1.3850150 -0.61231180 2.7912870 0.6083754 0.034304748 -0.08078917 [4,] -0.3791950 0.05575989 -0.3418704 -1.0307746 0.008103675 -0.03568972 [5,] 0.1046511 0.58093347 0.7240817 -0.5939624 -1.056404666 0.08764158 [,7] [,8] [,9] [,10] [,11] [,12] [1,] 0.3540252 -1.5439875 -1.2047397 -0.6297766 -0.3302821 0.09510571 [2,] -1.2241721 0.5234052 -1.8605095 1.8262971 0.3941487 -0.25956405 [3,] 0.3007449 -0.1711307 -0.2190618 0.4675044 0.2554321 -1.16756203 [4,] 0.3103500 0.5742513 2.1954150 1.0532107 -0.7997745 -0.69800861 [5,] 1.3361837 -0.7820276 0.4114200 -0.3314432 0.5004513 -0.25850276 [,13] [,14] [,15] [,16] [,17] [,18] [1,] 0.153428477 -0.025896044 0.8339344 -1.1173030 0.7206844 -0.8554074 [2,] -0.040986678 0.894087398 3.4013650 -0.3709422 -0.8460320 0.1210602 [3,] -1.635081087 0.772007516 -1.4439968 0.5146215 0.2573339 0.4267782 [4,] 0.005189369 0.576477362 -0.5977323 -0.8718158 1.3214827 1.2198668 [5,] -0.623323094 0.007788306 -1.3994496 0.4923586 -1.0750407 0.6072932 [,19] [,20] [1,] 0.03610495 -0.2197574 [2,] 0.32796566 1.0315634 [3,] 0.41047710 -0.9243989 [4,] -1.14998869 0.7106631 [5,] -0.63254019 -1.1618832 > > > is.BufferedMatrix(tmp) [1] TRUE > > as.BufferedMatrix(as.matrix(tmp)) BufferedMatrix object Matrix size: 5 20 Buffer size: 1 1 Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 1.9 Kilobytes. Disk usage : 800 bytes. > > > > subBufferedMatrix(tmp,1:5,1:5) BufferedMatrix object Matrix size: 5 5 Buffer size: 1 1 Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 649 bytes. Disk usage : 200 bytes. > subBufferedMatrix(tmp,,5:8) BufferedMatrix object Matrix size: 5 4 Buffer size: 1 1 Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 562 bytes. Disk usage : 160 bytes. > subBufferedMatrix(tmp,1:3,) BufferedMatrix object Matrix size: 3 20 Buffer size: 1 1 Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 1.9 Kilobytes. Disk usage : 480 bytes. > > > rm(tmp) > > > ### > ### Testing colnames and rownames > ### > > tmp <- createBufferedMatrix(5,20) > tmp[1:5,1:20] <- rnorm(100) > > > colnames(tmp) NULL > rownames(tmp) NULL > > > colnames(tmp) <- colnames(tmp,do.NULL=FALSE) > rownames(tmp) <- rownames(tmp,do.NULL=FALSE) > > colnames(tmp) [1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9" [10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18" [19] "col19" "col20" > rownames(tmp) [1] "row1" "row2" "row3" "row4" "row5" > > > tmp["row1",] col1 col2 col3 col4 col5 col6 row1 -0.09008613 -0.6583055 -0.2975523 1.712413 -0.5936177 -0.06800104 col7 col8 col9 col10 col11 col12 col13 row1 0.2741112 -0.06714724 0.1111396 -0.1353129 0.3217064 0.448687 0.4554948 col14 col15 col16 col17 col18 col19 col20 row1 -0.7164531 1.065116 1.510043 -0.5186808 0.4722992 0.7960186 -1.723255 > tmp[,"col10"] col10 row1 -0.1353129 row2 1.6338609 row3 -1.4968442 row4 -1.5783391 row5 -0.6482539 > tmp[c("row1","row5"),] col1 col2 col3 col4 col5 col6 row1 -0.09008613 -0.6583055 -0.2975523 1.7124125 -0.5936177 -0.06800104 row5 -0.89186486 0.2483889 1.2511248 0.3912231 -0.5747523 -0.86015797 col7 col8 col9 col10 col11 col12 row1 0.2741112 -0.06714724 0.1111396 -0.1353129 0.3217064 0.44868695 row5 1.1496182 -0.34687711 -0.8834484 -0.6482539 0.1810761 -0.08940511 col13 col14 col15 col16 col17 col18 col19 row1 0.4554948 -0.7164531 1.065116 1.5100431 -0.5186808 0.4722992 0.7960186 row5 -0.5155415 1.3823107 -1.249117 0.7804666 1.1336114 0.5286087 -0.9942748 col20 row1 -1.7232546 row5 -0.1643404 > tmp[,c("col6","col20")] col6 col20 row1 -0.06800104 -1.7232546 row2 0.90636970 2.5010046 row3 -1.33843948 0.8642555 row4 -1.46671255 1.1735149 row5 -0.86015797 -0.1643404 > tmp[c("row1","row5"),c("col6","col20")] col6 col20 row1 -0.06800104 -1.7232546 row5 -0.86015797 -0.1643404 > > > > > tmp["row1",] <- rnorm(20,mean=10) > tmp[,"col10"] <- rnorm(5,mean=30) > tmp[c("row1","row5"),] <- rnorm(40,mean=50) > tmp[,c("col6","col20")] <- rnorm(10,mean=75) > tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105) > > tmp["row1",] col1 col2 col3 col4 col5 col6 col7 col8 row1 51.46256 49.74118 48.66781 50.03691 51.06789 107.3014 50.54686 49.96696 col9 col10 col11 col12 col13 col14 col15 col16 row1 49.16701 50.83036 50.29005 50.26208 49.26571 50.99464 50.4199 50.10335 col17 col18 col19 col20 row1 50.68159 51.12784 49.5481 106.1038 > tmp[,"col10"] col10 row1 50.83036 row2 30.83001 row3 31.53244 row4 29.23299 row5 49.26855 > tmp[c("row1","row5"),] col1 col2 col3 col4 col5 col6 col7 col8 row1 51.46256 49.74118 48.66781 50.03691 51.06789 107.3014 50.54686 49.96696 row5 50.24615 50.37021 49.27077 49.19440 49.92247 104.2770 50.49783 49.54729 col9 col10 col11 col12 col13 col14 col15 col16 row1 49.16701 50.83036 50.29005 50.26208 49.26571 50.99464 50.41990 50.10335 row5 50.17073 49.26855 48.82500 50.09862 49.37191 48.29162 51.07235 51.57694 col17 col18 col19 col20 row1 50.68159 51.12784 49.54810 106.1038 row5 49.90605 49.31487 49.04784 105.9902 > tmp[,c("col6","col20")] col6 col20 row1 107.30142 106.10377 row2 74.21874 73.53416 row3 73.17938 73.97554 row4 74.82096 72.94093 row5 104.27699 105.99021 > tmp[c("row1","row5"),c("col6","col20")] col6 col20 row1 107.3014 106.1038 row5 104.2770 105.9902 > > > subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2] col6 col20 row1 107.3014 106.1038 row5 104.2770 105.9902 > > > > > > tmp <- createBufferedMatrix(5,20) > tmp[1:5,1:20] <- rnorm(100) > colnames(tmp) <- colnames(tmp,do.NULL=FALSE) > > tmp[,"col13"] col13 [1,] -1.2846237 [2,] -1.7904308 [3,] 0.4347555 [4,] -1.6438929 [5,] 0.8151159 > tmp[,c("col17","col7")] col17 col7 [1,] 0.2103682 -0.2866729 [2,] -1.1242956 1.6085209 [3,] 0.5023224 -1.2022984 [4,] -0.4831921 -1.7339628 [5,] -1.2630033 0.2426007 > > subBufferedMatrix(tmp,,c("col6","col20"))[,1:2] col6 col20 [1,] 0.63057214 -0.8232505 [2,] -0.44256193 -0.6129987 [3,] 0.03542096 1.0506268 [4,] 1.08111652 -1.2580217 [5,] -0.29922254 0.4175879 > subBufferedMatrix(tmp,1,c("col6"))[,1] col1 [1,] 0.6305721 > subBufferedMatrix(tmp,1:2,c("col6"))[,1] col6 [1,] 0.6305721 [2,] -0.4425619 > > > > tmp <- createBufferedMatrix(5,20) > tmp[1:5,1:20] <- rnorm(100) > rownames(tmp) <- rownames(tmp,do.NULL=FALSE) > > > > > subBufferedMatrix(tmp,c("row3","row1"),)[,1:20] [,1] [,2] [,3] [,4] [,5] [,6] [,7] row3 -0.3022928 0.2321295 -0.4623202 1.1801405 0.08376790 0.9433444 0.5923313 row1 -0.4593055 0.5663966 0.5749758 -0.7113325 0.05445166 0.6268230 1.8620721 [,8] [,9] [,10] [,11] [,12] [,13] row3 -0.4571623 1.3951433 -0.3832574 0.3984189 -0.2524718 -0.2271486 row1 -1.7520332 0.2689581 -0.6356322 -0.7025212 0.7981365 0.9436400 [,14] [,15] [,16] [,17] [,18] [,19] row3 -0.6718755 0.82942875 0.4214367 -0.09872043 0.4568485 -1.729376 row1 -0.3647429 0.07797192 1.3354195 -0.39062686 -1.0842828 -1.081836 [,20] row3 -0.7342797 row1 -1.5916632 > subBufferedMatrix(tmp,c("row2"),1:10)[,1:10] [,1] [,2] [,3] [,4] [,5] [,6] [,7] row2 -0.7499726 1.621194 0.9237476 -0.02562761 0.3784411 -2.541733 -0.5266657 [,8] [,9] [,10] row2 0.5215261 0.7031744 0.9303148 > subBufferedMatrix(tmp,c("row5"),1:20)[,1:20] [,1] [,2] [,3] [,4] [,5] [,6] [,7] row5 -0.4813004 -1.823853 0.1228595 -1.59793 1.934316 -0.8961515 0.7820463 [,8] [,9] [,10] [,11] [,12] [,13] [,14] row5 1.649858 0.9393479 2.509722 -1.904663 -1.259225 -0.8071342 -0.5723122 [,15] [,16] [,17] [,18] [,19] [,20] row5 0.7274225 1.979644 0.4263924 0.3791746 -0.4143611 0.1597182 > > > colnames(tmp) <- colnames(tmp,do.NULL=FALSE) > rownames(tmp) <- rownames(tmp,do.NULL=FALSE) > > colnames(tmp) [1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9" [10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18" [19] "col19" "col20" > rownames(tmp) [1] "row1" "row2" "row3" "row4" "row5" > > > colnames(tmp) <- NULL > rownames(tmp) <- NULL > > colnames(tmp) NULL > rownames(tmp) NULL > > > colnames(tmp) <- colnames(tmp,do.NULL=FALSE) > rownames(tmp) <- rownames(tmp,do.NULL=FALSE) > > dimnames(tmp) [[1]] [1] "row1" "row2" "row3" "row4" "row5" [[2]] [1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9" [10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18" [19] "col19" "col20" > > dimnames(tmp) <- NULL > > colnames(tmp) <- colnames(tmp,do.NULL=FALSE) > dimnames(tmp) [[1]] NULL [[2]] [1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9" [10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18" [19] "col19" "col20" > > > dimnames(tmp) <- NULL > rownames(tmp) <- rownames(tmp,do.NULL=FALSE) > dimnames(tmp) [[1]] [1] "row1" "row2" "row3" "row4" "row5" [[2]] NULL > > dimnames(tmp) <- list(NULL,c(colnames(tmp,do.NULL=FALSE))) > dimnames(tmp) [[1]] NULL [[2]] [1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9" [10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18" [19] "col19" "col20" > > > > ### > ### Testing logical indexing > ### > ### > > tmp <- createBufferedMatrix(230,15) > tmp[1:230,1:15] <- rnorm(230*15) > x <-tmp[1:230,1:15] > > for (rep in 1:10){ + which.cols <- sample(c(TRUE,FALSE),15,replace=T) + which.rows <- sample(c(TRUE,FALSE),230,replace=T) + + if (!all(tmp[which.rows,which.cols] == x[which.rows,which.cols])){ + stop("No agreement when logical indexing\n") + } + + if (!all(subBufferedMatrix(tmp,,which.cols)[,1:sum(which.cols)] == x[,which.cols])){ + stop("No agreement when logical indexing in subBufferedMatrix cols\n") + } + if (!all(subBufferedMatrix(tmp,which.rows,)[1:sum(which.rows),] == x[which.rows,])){ + stop("No agreement when logical indexing in subBufferedMatrix rows\n") + } + + + if (!all(subBufferedMatrix(tmp,which.rows,which.cols)[1:sum(which.rows),1:sum(which.cols)]== x[which.rows,which.cols])){ + stop("No agreement when logical indexing in subBufferedMatrix rows and columns\n") + } + } > > > ## > ## Test the ReadOnlyMode > ## > > ReadOnlyMode(tmp) <pointer: 0x5fe07649e2e0> > is.ReadOnlyMode(tmp) [1] TRUE > > filenames(tmp) [1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25a72288156d5" [2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25a725039c2c1" [3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25a723b1c77b8" [4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25a724446019" [5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25a7237d323c0" [6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25a724a4fb419" [7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25a727d1a4b4c" [8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25a7215c2d4c8" [9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25a72335afce1" [10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25a7249dd15b7" [11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25a725497403b" [12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25a725ad0a410" [13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25a723700db64" [14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25a726f09e6f4" [15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM25a727d4dbc39" > > > ### testing coercion functions > ### > > tmp <- as(tmp,"matrix") > tmp <- as(tmp,"BufferedMatrix") > > > > ### testing whether can move storage from one location to another > > MoveStorageDirectory(tmp,"NewDirectory",full.path=FALSE) <pointer: 0x5fe0781868c0> > MoveStorageDirectory(tmp,getwd(),full.path=TRUE) <pointer: 0x5fe0781868c0> Warning message: In dir.create(new.directory) : '/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists > > > RowMode(tmp) <pointer: 0x5fe0781868c0> > rowMedians(tmp) [1] 7.711504e-02 3.779416e-01 6.642818e-02 -3.948778e-01 -3.075622e-01 [6] -2.284353e-01 4.777341e-01 7.894444e-02 -1.349530e-03 2.917426e-01 [11] -1.500694e-02 -3.696485e-01 2.406682e-01 -1.341256e-01 -1.966992e-01 [16] 2.067972e-01 -2.404804e-01 1.898546e-01 4.691738e-01 -3.744545e-01 [21] 2.755337e-01 3.478336e-01 2.822042e-01 4.491829e-02 -2.660128e-01 [26] -3.762905e-02 8.656136e-02 4.425637e-01 -3.699445e-01 -2.657649e-01 [31] 2.546520e-01 2.015550e-01 5.167775e-01 -1.999966e-02 2.834181e-01 [36] 1.255557e-01 -6.999279e-02 3.895859e-01 -3.087110e-01 -2.289461e-01 [41] 2.666815e-01 3.192059e-01 4.939461e-01 1.008861e-01 1.976961e-01 [46] 4.073866e-01 -1.599372e-01 -1.687882e-01 -3.547156e-01 2.716866e-01 [51] -6.197086e-01 -5.849626e-02 2.784998e-01 -1.996391e-02 3.802948e-01 [56] 4.091972e-01 -4.123781e-01 5.217064e-01 -2.499998e-01 1.083070e+00 [61] 3.722290e-01 4.388187e-02 1.975262e-01 1.666404e-01 1.999047e-01 [66] 7.874333e-01 2.527521e-01 1.067242e-01 -2.590381e-01 -4.976045e-02 [71] 1.050004e-01 -1.774079e-01 -9.595853e-02 5.636426e-03 -3.818667e-01 [76] 2.137079e-01 -3.557082e-01 -1.475715e-01 2.929464e-02 5.799448e-02 [81] -1.507212e-01 2.373615e-01 -4.810372e-01 3.609449e-01 5.327134e-01 [86] -2.826045e-01 8.244572e-02 1.444711e-01 -9.166325e-01 -1.856990e-01 [91] -3.139314e-02 -7.249139e-01 -3.347834e-01 5.746509e-01 -3.033065e-01 [96] -5.251749e-02 4.566494e-01 -7.439374e-02 1.064754e-01 -4.438029e-02 [101] -2.658853e-02 3.616621e-01 -5.377340e-02 2.372715e-02 1.605965e-01 [106] 4.968406e-02 -9.862925e-01 4.225638e-01 7.002954e-05 9.856767e-03 [111] -3.172215e-01 3.848255e-02 -4.240645e-01 3.796667e-01 -2.887236e-01 [116] 5.855714e-02 -2.169715e-01 5.673068e-03 9.128996e-02 8.199338e-02 [121] -2.452925e-01 2.508746e-01 -1.933573e-01 -4.515372e-02 -6.153585e-01 [126] -2.733859e-01 2.675336e-01 1.219201e-01 -1.375613e-01 4.255883e-01 [131] -5.762498e-02 9.352870e-03 2.060638e-01 -1.200127e-01 -1.723955e-01 [136] -3.392709e-02 -1.669394e-01 -1.032361e-01 -2.510180e-01 -4.728668e-01 [141] -4.039729e-02 -3.203263e-02 3.690154e-01 1.601909e-01 2.926348e-01 [146] -4.132960e-01 -4.720283e-01 2.516719e-01 2.352697e-01 2.495498e-01 [151] -1.830058e-01 -5.066929e-02 -4.030604e-01 -3.457690e-01 -9.797287e-02 [156] 4.981857e-02 2.113003e-01 -4.154614e-01 -3.578961e-01 5.219803e-01 [161] -3.611283e-02 4.174255e-02 9.573245e-02 4.318459e-01 4.457286e-01 [166] -2.208276e-01 -3.634272e-02 1.712617e-01 2.402863e-02 -6.053042e-01 [171] -1.002124e-01 -1.699827e-01 4.215727e-01 -1.523101e-01 2.360504e-02 [176] -4.310839e-02 -4.055538e-01 1.857842e-01 8.568533e-02 1.893452e-01 [181] -2.822621e-01 -2.857224e-01 1.863481e-01 -5.213481e-01 -3.290967e-01 [186] -2.718387e-01 4.102173e-01 1.323728e-01 -1.115401e-01 -1.291002e-01 [191] -2.393267e-01 2.794959e-01 -2.005728e-01 -2.824565e-01 2.329379e-01 [196] 3.286613e-01 4.251093e-02 4.598937e-01 -7.458812e-01 -2.514446e-01 [201] 9.982292e-02 -6.902628e-02 7.800165e-02 5.702329e-01 1.147514e-01 [206] -7.946782e-02 -3.941777e-01 2.509778e-01 -3.369255e-01 7.569897e-02 [211] -2.043725e-01 1.506702e-01 2.891912e-01 4.480748e-01 -3.026370e-01 [216] 5.685044e-03 3.983373e-01 2.834738e-01 -6.713362e-01 -3.183321e-01 [221] 3.041182e-01 1.354049e-01 2.828178e-01 2.225728e-01 -6.103246e-01 [226] -3.319312e-01 -2.031488e-01 6.488583e-01 -8.054676e-02 -9.720864e-02 > > proc.time() user system elapsed 1.263 0.671 1.921
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.1 (2025-06-13) -- "Great Square Root" Copyright (C) 2025 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths()); Attaching package: 'BufferedMatrix' The following objects are masked from 'package:base': colMeans, colSums, rowMeans, rowSums > > prefix <- "dbmtest" > directory <- getwd() > > > P <- .Call("R_bm_Create",prefix,directory,1,1) > .Call("R_bm_Test_C",P) RBufferedMatrix Checking dimensions Rows: 5 Cols: 5 Buffer Rows: 1 Buffer Cols: 1 Assigning Values 0.000000 1.000000 2.000000 3.000000 4.000000 1.000000 2.000000 3.000000 4.000000 5.000000 2.000000 3.000000 4.000000 5.000000 6.000000 3.000000 4.000000 5.000000 6.000000 7.000000 4.000000 5.000000 6.000000 7.000000 8.000000 <pointer: 0x599ca85f4b80> > .Call("R_bm_Test_C2",P) Checking dimensions Rows: 5 Cols: 5 Buffer Rows: 1 Buffer Cols: 1 Printing Values 0.000000 1.000000 2.000000 3.000000 4.000000 1.000000 2.000000 3.000000 4.000000 5.000000 2.000000 3.000000 4.000000 5.000000 6.000000 3.000000 4.000000 5.000000 6.000000 7.000000 4.000000 5.000000 6.000000 7.000000 8.000000 <pointer: 0x599ca85f4b80> > .Call("R_bm_Test_C",P) RBufferedMatrix Checking dimensions Rows: 5 Cols: 10 Buffer Rows: 1 Buffer Cols: 1 Assigning Values 0.000000 1.000000 2.000000 3.000000 4.000000 1.000000 2.000000 3.000000 4.000000 5.000000 2.000000 3.000000 4.000000 5.000000 6.000000 3.000000 4.000000 5.000000 6.000000 7.000000 4.000000 5.000000 6.000000 7.000000 8.000000 <pointer: 0x599ca85f4b80> > .Call("R_bm_Test_C2",P) Checking dimensions Rows: 5 Cols: 10 Buffer Rows: 1 Buffer Cols: 1 Printing Values 0.000000 1.000000 2.000000 3.000000 4.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000 2.000000 3.000000 4.000000 5.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2.000000 3.000000 4.000000 5.000000 6.000000 0.000000 0.000000 0.000000 0.000000 0.000000 3.000000 4.000000 5.000000 6.000000 7.000000 0.000000 0.000000 0.000000 0.000000 0.000000 4.000000 5.000000 6.000000 7.000000 8.000000 0.000000 0.000000 0.000000 0.000000 0.000000 <pointer: 0x599ca85f4b80> > rm(P) > > #P <- .Call("R_bm_Destroy",P) > #.Call("R_bm_Destroy",P) > #.Call("R_bm_Test_C",P) > > > P <- .Call("R_bm_Create",prefix,directory,1,1) > .Call("R_bm_setRows",P,5) [1] TRUE > .Call("R_bm_Test_C2",P) Checking dimensions Rows: 5 Cols: 0 Buffer Rows: 1 Buffer Cols: 1 Printing Values <pointer: 0x599ca85d7390> > .Call("R_bm_AddColumn",P) <pointer: 0x599ca85d7390> > .Call("R_bm_Test_C2",P) Checking dimensions Rows: 5 Cols: 1 Buffer Rows: 1 Buffer Cols: 1 Printing Values 0.000000 0.000000 0.000000 0.000000 0.000000 <pointer: 0x599ca85d7390> > .Call("R_bm_AddColumn",P) <pointer: 0x599ca85d7390> > .Call("R_bm_Test_C2",P) Checking dimensions Rows: 5 Cols: 2 Buffer Rows: 1 Buffer Cols: 1 Printing Values 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 <pointer: 0x599ca85d7390> > rm(P) > > > > P <- .Call("R_bm_Create",prefix,directory,1,1) > .Call("R_bm_setRows",P,5) [1] TRUE > .Call("R_bm_AddColumn",P) <pointer: 0x599ca85bf1e0> > .Call("R_bm_AddColumn",P) <pointer: 0x599ca85bf1e0> > .Call("R_bm_Test_C2",P) Checking dimensions Rows: 5 Cols: 2 Buffer Rows: 1 Buffer Cols: 1 Printing Values 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 <pointer: 0x599ca85bf1e0> > > .Call("R_bm_ResizeBuffer",P,5,5) <pointer: 0x599ca85bf1e0> > .Call("R_bm_Test_C2",P) Checking dimensions Rows: 5 Cols: 2 Buffer Rows: 5 Buffer Cols: 5 Printing Values 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 <pointer: 0x599ca85bf1e0> > > .Call("R_bm_RowMode",P) <pointer: 0x599ca85bf1e0> > .Call("R_bm_Test_C2",P) Checking dimensions Rows: 5 Cols: 2 Buffer Rows: 5 Buffer Cols: 5 Printing Values 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 <pointer: 0x599ca85bf1e0> > > .Call("R_bm_ColMode",P) <pointer: 0x599ca85bf1e0> > .Call("R_bm_Test_C2",P) Checking dimensions Rows: 5 Cols: 2 Buffer Rows: 5 Buffer Cols: 5 Printing Values 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 <pointer: 0x599ca85bf1e0> > rm(P) > > > P <- .Call("R_bm_Create",prefix,directory,1,1) > .Call("R_bm_setRows",P,10) [1] TRUE > .Call("R_bm_AddColumn",P) <pointer: 0x599ca7e442a0> > .Call("R_bm_SetPrefix",P,"BufferedMatrixFile") <pointer: 0x599ca7e442a0> > .Call("R_bm_AddColumn",P) <pointer: 0x599ca7e442a0> > .Call("R_bm_AddColumn",P) <pointer: 0x599ca7e442a0> > dir(pattern="BufferedMatrixFile") [1] "BufferedMatrixFile25b981c575d49" "BufferedMatrixFile25b9879ee5cb6" > rm(P) > dir(pattern="BufferedMatrixFile") [1] "BufferedMatrixFile25b981c575d49" "BufferedMatrixFile25b9879ee5cb6" > > > P <- .Call("R_bm_Create",prefix,directory,1,1) > .Call("R_bm_setRows",P,10) [1] TRUE > .Call("R_bm_AddColumn",P) <pointer: 0x599ca9047da0> > .Call("R_bm_AddColumn",P) <pointer: 0x599ca9047da0> > .Call("R_bm_ReadOnlyModeToggle",P) <pointer: 0x599ca9047da0> > .Call("R_bm_isReadOnlyMode",P) [1] TRUE > .Call("R_bm_ReadOnlyModeToggle",P) <pointer: 0x599ca9047da0> > .Call("R_bm_isReadOnlyMode",P) [1] FALSE > .Call("R_bm_isRowMode",P) [1] FALSE > .Call("R_bm_RowMode",P) <pointer: 0x599ca9047da0> > .Call("R_bm_isRowMode",P) [1] TRUE > .Call("R_bm_ColMode",P) <pointer: 0x599ca9047da0> > .Call("R_bm_isRowMode",P) [1] FALSE > rm(P) > > > P <- .Call("R_bm_Create",prefix,directory,1,1) > .Call("R_bm_setRows",P,10) [1] TRUE > .Call("R_bm_AddColumn",P) <pointer: 0x599ca92dc470> > .Call("R_bm_AddColumn",P) <pointer: 0x599ca92dc470> > > .Call("R_bm_getSize",P) [1] 10 2 > .Call("R_bm_getBufferSize",P) [1] 1 1 > .Call("R_bm_ResizeBuffer",P,5,5) <pointer: 0x599ca92dc470> > > .Call("R_bm_getBufferSize",P) [1] 5 5 > .Call("R_bm_ResizeBuffer",P,-1,5) <pointer: 0x599ca92dc470> > rm(P) > > > P <- .Call("R_bm_Create",prefix,directory,1,1) > .Call("R_bm_Test_C",P) RBufferedMatrix Checking dimensions Rows: 5 Cols: 5 Buffer Rows: 1 Buffer Cols: 1 Assigning Values 0.000000 1.000000 2.000000 3.000000 4.000000 1.000000 2.000000 3.000000 4.000000 5.000000 2.000000 3.000000 4.000000 5.000000 6.000000 3.000000 4.000000 5.000000 6.000000 7.000000 4.000000 5.000000 6.000000 7.000000 8.000000 <pointer: 0x599ca84bd410> > .Call("R_bm_getValue",P,3,3) [1] 6 > > .Call("R_bm_getValue",P,100000,10000) [1] NA > .Call("R_bm_setValue",P,3,3,12345.0) [1] TRUE > .Call("R_bm_Test_C2",P) Checking dimensions Rows: 5 Cols: 5 Buffer Rows: 1 Buffer Cols: 1 Printing Values 0.000000 1.000000 2.000000 3.000000 4.000000 1.000000 2.000000 3.000000 4.000000 5.000000 2.000000 3.000000 4.000000 5.000000 6.000000 3.000000 4.000000 5.000000 12345.000000 7.000000 4.000000 5.000000 6.000000 7.000000 8.000000 <pointer: 0x599ca84bd410> > rm(P) > > proc.time() user system elapsed 0.271 0.046 0.306
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.1 (2025-06-13) -- "Great Square Root" Copyright (C) 2025 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths()); Attaching package: 'BufferedMatrix' The following objects are masked from 'package:base': colMeans, colSums, rowMeans, rowSums > > Temp <- createBufferedMatrix(100) > dim(Temp) [1] 100 0 > buffer.dim(Temp) [1] 1 1 > > > proc.time() user system elapsed 0.274 0.059 0.315