Back to Multiple platform build/check report for BioC 3.19: simplified long |
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This page was generated on 2024-05-04 11:36:21 -0400 (Sat, 04 May 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" | 4753 |
palomino3 | Windows Server 2022 Datacenter | x64 | 4.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup" | 4486 |
lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.0 beta (2024-04-14 r86421) -- "Puppy Cup" | 4519 |
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" | 4479 |
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 249/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
BufferedMatrix 1.68.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | ![]() | ||||||||
palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | ![]() | ||||||||
lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | ![]() | ||||||||
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) / aarch64 | OK | OK | OK | ||||||||||
kjohnson3 | macOS 13.6.5 Ventura / arm64 | see weekly results here | ||||||||||||
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: 1.68.0 |
Command: /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings BufferedMatrix_1.68.0.tar.gz |
StartedAt: 2024-05-03 21:21:13 -0400 (Fri, 03 May 2024) |
EndedAt: 2024-05-03 21:21:37 -0400 (Fri, 03 May 2024) |
EllapsedTime: 24.0 seconds |
RetCode: 0 |
Status: OK |
CheckDir: BufferedMatrix.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings BufferedMatrix_1.68.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck’ * using R version 4.4.0 beta (2024-04-15 r86425) * using platform: x86_64-pc-linux-gnu * R was compiled by gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 * running under: Ubuntu 22.04.4 LTS * using session charset: UTF-8 * checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK * this is package ‘BufferedMatrix’ version ‘1.68.0’ * 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 11.4.0-1ubuntu1~22.04) 11.4.0’ * 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-3.19-bioc/meat/BufferedMatrix.Rcheck/00check.log’ for details.
BufferedMatrix.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD INSTALL BufferedMatrix ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.19-bioc/R/site-library’ * installing *source* package ‘BufferedMatrix’ ... ** using staged installation ** libs using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’ gcc -I"/home/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o gcc -I"/home/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -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){ | ^~~~~~~~~~~~~~~~~~~ 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 -I"/home/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o gcc -I"/home/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c init_package.c -o init_package.o gcc -shared -L/home/biocbuild/bbs-3.19-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-3.19-bioc/R/lib -lR installing to /home/biocbuild/bbs-3.19-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 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" Copyright (C) 2024 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 0.281 0.038 0.308
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" Copyright (C) 2024 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-3.19-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 471777 25.2 1026217 54.9 643434 34.4 Vcells 871902 6.7 8388608 64.0 2046581 15.7 > > > > > ## > ## 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] "Fri May 3 21:21:28 2024" > 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] "Fri May 3 21:21:28 2024" > > > 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: 0x55fe4aee92a0> > > > > 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] "Fri May 3 21:21:29 2024" > 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] "Fri May 3 21:21:29 2024" > > ColMode(tmp2) <pointer: 0x55fe4aee92a0> > > > > ### 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,] 98.8421728 0.4872693 0.5414392 -0.35686089 [2,] -1.5279343 0.6968304 0.3983223 0.11836833 [3,] 0.2126679 1.1056122 1.8955265 -0.37216630 [4,] 0.8962157 0.6506706 0.2362745 -0.04585253 > ewApply(tmp5,abs) BufferedMatrix object Matrix size: 10 20 Buffer size: 1 1 Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 2 Kilobytes. Disk usage : 1.6 Kilobytes. > tmp5[1:4,1:4] [,1] [,2] [,3] [,4] [1,] 98.8421728 0.4872693 0.5414392 0.35686089 [2,] 1.5279343 0.6968304 0.3983223 0.11836833 [3,] 0.2126679 1.1056122 1.8955265 0.37216630 [4,] 0.8962157 0.6506706 0.2362745 0.04585253 > ewApply(tmp5,sqrt) BufferedMatrix object Matrix size: 10 20 Buffer size: 1 1 Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 2 Kilobytes. Disk usage : 1.6 Kilobytes. > tmp5[1:4,1:4] [,1] [,2] [,3] [,4] [1,] 9.9419401 0.6980468 0.7358255 0.5973783 [2,] 1.2360964 0.8347637 0.6311278 0.3440470 [3,] 0.4611593 1.0514809 1.3767812 0.6100543 [4,] 0.9466867 0.8066415 0.4860807 0.2141320 > > 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-3.19-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 2 Kilobytes. Disk usage : 1.6 Kilobytes. > tmp5[1:4,1:4] [,1] [,2] [,3] [,4] [1,] 223.26157 32.46774 32.89969 31.33064 [2,] 38.88890 34.04447 31.70960 28.55884 [3,] 29.82426 36.62042 40.66334 31.47271 [4,] 35.36308 33.71709 30.09708 27.18717 > > > > ## testing functions that elementwise transform the matrix > sqrt(tmp5) <pointer: 0x55fe48f872e0> > exp(tmp5) <pointer: 0x55fe48f872e0> > log(tmp5,2) <pointer: 0x55fe48f872e0> > pow(tmp5,2) > > > > > > ## testing functions that apply to entire matrix > Max(tmp5) [1] 464.6897 > Min(tmp5) [1] 52.79016 > mean(tmp5) [1] 72.34281 > Sum(tmp5) [1] 14468.56 > Var(tmp5) [1] 849.4823 > > > ## testing functions applied to rows or columns > > rowMeans(tmp5) [1] 90.86478 66.87405 71.32028 70.70285 71.66208 69.02567 69.31842 70.67843 [9] 70.52010 72.46145 > rowSums(tmp5) [1] 1817.296 1337.481 1426.406 1414.057 1433.242 1380.513 1386.368 1413.569 [9] 1410.402 1449.229 > rowVars(tmp5) [1] 7813.25077 60.47167 58.07917 91.58911 90.35516 86.95925 [7] 72.29875 58.17484 83.13143 58.24056 > rowSd(tmp5) [1] 88.392595 7.776353 7.620969 9.570220 9.505533 9.325195 8.502867 [8] 7.627243 9.117644 7.631550 > rowMax(tmp5) [1] 464.68971 85.02099 84.63541 87.47614 85.68622 83.24550 92.57765 [8] 82.60464 87.87064 90.76675 > rowMin(tmp5) [1] 60.75715 53.85529 55.34450 56.38939 52.88663 52.79016 58.65729 55.19133 [9] 55.01195 59.72374 > > colMeans(tmp5) [1] 112.66121 68.98974 71.10865 65.11166 67.63725 69.96435 70.22171 [8] 73.98890 68.31267 69.99551 76.54433 69.08322 69.70027 74.79689 [15] 66.88996 72.50400 73.84711 68.72964 68.54225 68.22692 > colSums(tmp5) [1] 1126.6121 689.8974 711.0865 651.1166 676.3725 699.6435 702.2171 [8] 739.8890 683.1267 699.9551 765.4433 690.8322 697.0027 747.9689 [15] 668.8996 725.0400 738.4711 687.2964 685.4225 682.2692 > colVars(tmp5) [1] 15352.68180 27.27347 52.26325 83.58534 65.24664 91.69186 [7] 57.64010 36.15537 143.40076 184.12878 52.71289 58.28100 [13] 61.33893 115.84796 50.50600 62.65909 41.60661 31.17492 [19] 56.29665 86.13498 > colSd(tmp5) [1] 123.905939 5.222400 7.229332 9.142502 8.077539 9.575586 [7] 7.592108 6.012933 11.975006 13.569406 7.260365 7.634200 [13] 7.831918 10.763269 7.106758 7.915749 6.450318 5.583450 [19] 7.503109 9.280893 > colMax(tmp5) [1] 464.68971 76.22061 84.63541 82.29336 80.54037 85.02099 84.12316 [8] 85.04636 86.18476 92.57765 87.87064 79.63435 83.79247 90.76675 [15] 78.55615 79.20389 81.87084 76.28635 80.54206 87.47614 > colMin(tmp5) [1] 62.07529 57.13958 62.64313 55.19133 58.65729 58.43377 57.20285 67.07542 [9] 52.88663 53.85529 65.92205 52.79016 58.14837 58.26550 57.17349 56.37599 [17] 59.56304 61.49414 59.52262 59.15499 > > > ### 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] 90.86478 66.87405 71.32028 70.70285 71.66208 69.02567 69.31842 70.67843 [9] 70.52010 NA > rowSums(tmp5) [1] 1817.296 1337.481 1426.406 1414.057 1433.242 1380.513 1386.368 1413.569 [9] 1410.402 NA > rowVars(tmp5) [1] 7813.25077 60.47167 58.07917 91.58911 90.35516 86.95925 [7] 72.29875 58.17484 83.13143 61.14780 > rowSd(tmp5) [1] 88.392595 7.776353 7.620969 9.570220 9.505533 9.325195 8.502867 [8] 7.627243 9.117644 7.819706 > rowMax(tmp5) [1] 464.68971 85.02099 84.63541 87.47614 85.68622 83.24550 92.57765 [8] 82.60464 87.87064 NA > rowMin(tmp5) [1] 60.75715 53.85529 55.34450 56.38939 52.88663 52.79016 58.65729 55.19133 [9] 55.01195 NA > > colMeans(tmp5) [1] 112.66121 68.98974 71.10865 65.11166 67.63725 69.96435 70.22171 [8] 73.98890 68.31267 69.99551 76.54433 NA 69.70027 74.79689 [15] 66.88996 72.50400 73.84711 68.72964 68.54225 68.22692 > colSums(tmp5) [1] 1126.6121 689.8974 711.0865 651.1166 676.3725 699.6435 702.2171 [8] 739.8890 683.1267 699.9551 765.4433 NA 697.0027 747.9689 [15] 668.8996 725.0400 738.4711 687.2964 685.4225 682.2692 > colVars(tmp5) [1] 15352.68180 27.27347 52.26325 83.58534 65.24664 91.69186 [7] 57.64010 36.15537 143.40076 184.12878 52.71289 NA [13] 61.33893 115.84796 50.50600 62.65909 41.60661 31.17492 [19] 56.29665 86.13498 > colSd(tmp5) [1] 123.905939 5.222400 7.229332 9.142502 8.077539 9.575586 [7] 7.592108 6.012933 11.975006 13.569406 7.260365 NA [13] 7.831918 10.763269 7.106758 7.915749 6.450318 5.583450 [19] 7.503109 9.280893 > colMax(tmp5) [1] 464.68971 76.22061 84.63541 82.29336 80.54037 85.02099 84.12316 [8] 85.04636 86.18476 92.57765 87.87064 NA 83.79247 90.76675 [15] 78.55615 79.20389 81.87084 76.28635 80.54206 87.47614 > colMin(tmp5) [1] 62.07529 57.13958 62.64313 55.19133 58.65729 58.43377 57.20285 67.07542 [9] 52.88663 53.85529 65.92205 NA 58.14837 58.26550 57.17349 56.37599 [17] 59.56304 61.49414 59.52262 59.15499 > > Max(tmp5,na.rm=TRUE) [1] 464.6897 > Min(tmp5,na.rm=TRUE) [1] 52.79016 > mean(tmp5,na.rm=TRUE) [1] 72.35412 > Sum(tmp5,na.rm=TRUE) [1] 14398.47 > Var(tmp5,na.rm=TRUE) [1] 853.7469 > > rowMeans(tmp5,na.rm=TRUE) [1] 90.86478 66.87405 71.32028 70.70285 71.66208 69.02567 69.31842 70.67843 [9] 70.52010 72.58616 > rowSums(tmp5,na.rm=TRUE) [1] 1817.296 1337.481 1426.406 1414.057 1433.242 1380.513 1386.368 1413.569 [9] 1410.402 1379.137 > rowVars(tmp5,na.rm=TRUE) [1] 7813.25077 60.47167 58.07917 91.58911 90.35516 86.95925 [7] 72.29875 58.17484 83.13143 61.14780 > rowSd(tmp5,na.rm=TRUE) [1] 88.392595 7.776353 7.620969 9.570220 9.505533 9.325195 8.502867 [8] 7.627243 9.117644 7.819706 > rowMax(tmp5,na.rm=TRUE) [1] 464.68971 85.02099 84.63541 87.47614 85.68622 83.24550 92.57765 [8] 82.60464 87.87064 90.76675 > rowMin(tmp5,na.rm=TRUE) [1] 60.75715 53.85529 55.34450 56.38939 52.88663 52.79016 58.65729 55.19133 [9] 55.01195 59.72374 > > colMeans(tmp5,na.rm=TRUE) [1] 112.66121 68.98974 71.10865 65.11166 67.63725 69.96435 70.22171 [8] 73.98890 68.31267 69.99551 76.54433 68.97115 69.70027 74.79689 [15] 66.88996 72.50400 73.84711 68.72964 68.54225 68.22692 > colSums(tmp5,na.rm=TRUE) [1] 1126.6121 689.8974 711.0865 651.1166 676.3725 699.6435 702.2171 [8] 739.8890 683.1267 699.9551 765.4433 620.7403 697.0027 747.9689 [15] 668.8996 725.0400 738.4711 687.2964 685.4225 682.2692 > colVars(tmp5,na.rm=TRUE) [1] 15352.68180 27.27347 52.26325 83.58534 65.24664 91.69186 [7] 57.64010 36.15537 143.40076 184.12878 52.71289 65.42481 [13] 61.33893 115.84796 50.50600 62.65909 41.60661 31.17492 [19] 56.29665 86.13498 > colSd(tmp5,na.rm=TRUE) [1] 123.905939 5.222400 7.229332 9.142502 8.077539 9.575586 [7] 7.592108 6.012933 11.975006 13.569406 7.260365 8.088560 [13] 7.831918 10.763269 7.106758 7.915749 6.450318 5.583450 [19] 7.503109 9.280893 > colMax(tmp5,na.rm=TRUE) [1] 464.68971 76.22061 84.63541 82.29336 80.54037 85.02099 84.12316 [8] 85.04636 86.18476 92.57765 87.87064 79.63435 83.79247 90.76675 [15] 78.55615 79.20389 81.87084 76.28635 80.54206 87.47614 > colMin(tmp5,na.rm=TRUE) [1] 62.07529 57.13958 62.64313 55.19133 58.65729 58.43377 57.20285 67.07542 [9] 52.88663 53.85529 65.92205 52.79016 58.14837 58.26550 57.17349 56.37599 [17] 59.56304 61.49414 59.52262 59.15499 > > # now set an entire row to NA > > tmp5[which.row,] <- NA > rowMeans(tmp5,na.rm=TRUE) [1] 90.86478 66.87405 71.32028 70.70285 71.66208 69.02567 69.31842 70.67843 [9] 70.52010 NaN > rowSums(tmp5,na.rm=TRUE) [1] 1817.296 1337.481 1426.406 1414.057 1433.242 1380.513 1386.368 1413.569 [9] 1410.402 0.000 > rowVars(tmp5,na.rm=TRUE) [1] 7813.25077 60.47167 58.07917 91.58911 90.35516 86.95925 [7] 72.29875 58.17484 83.13143 NA > rowSd(tmp5,na.rm=TRUE) [1] 88.392595 7.776353 7.620969 9.570220 9.505533 9.325195 8.502867 [8] 7.627243 9.117644 NA > rowMax(tmp5,na.rm=TRUE) [1] 464.68971 85.02099 84.63541 87.47614 85.68622 83.24550 92.57765 [8] 82.60464 87.87064 NA > rowMin(tmp5,na.rm=TRUE) [1] 60.75715 53.85529 55.34450 56.38939 52.88663 52.79016 58.65729 55.19133 [9] 55.01195 NA > > > # now set an entire col to NA > > > tmp5[,which.col] <- NA > colMeans(tmp5,na.rm=TRUE) [1] 116.74057 69.28101 70.85042 63.49087 67.25518 70.66673 71.38815 [8] 73.47932 68.52011 70.75530 76.32435 NaN 69.90813 73.02246 [15] 65.72102 71.94374 73.74313 67.89001 67.67866 68.96229 > colSums(tmp5,na.rm=TRUE) [1] 1050.6651 623.5291 637.6538 571.4178 605.2966 636.0006 642.4934 [8] 661.3139 616.6810 636.7977 686.9191 0.0000 629.1732 657.2021 [15] 591.4892 647.4937 663.6882 611.0100 609.1080 620.6606 > colVars(tmp5,na.rm=TRUE) [1] 17084.55408 29.72820 58.04601 64.48001 71.76018 97.60333 [7] 49.53852 37.75357 160.84178 200.65045 58.75762 NA [13] 68.52024 94.90721 41.44704 66.96024 46.68581 27.14069 [19] 54.94361 90.81821 > colSd(tmp5,na.rm=TRUE) [1] 130.707896 5.452358 7.618793 8.029944 8.471138 9.879440 [7] 7.038361 6.144393 12.682341 14.165114 7.665352 NA [13] 8.277695 9.742033 6.437937 8.182924 6.832702 5.209672 [19] 7.412396 9.529859 > colMax(tmp5,na.rm=TRUE) [1] 464.68971 76.22061 84.63541 82.29336 80.54037 85.02099 84.12316 [8] 85.04636 86.18476 92.57765 87.87064 -Inf 83.79247 85.68622 [15] 78.55615 79.20389 81.87084 76.05781 80.54206 87.47614 > colMin(tmp5,na.rm=TRUE) [1] 62.07529 57.13958 62.64313 55.19133 58.65729 58.43377 57.20285 67.07542 [9] 52.88663 53.85529 65.92205 Inf 58.14837 58.26550 57.17349 56.37599 [17] 59.56304 61.49414 59.52262 59.15499 > > > > > 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] 233.1367 265.0658 186.4606 165.3668 213.8066 154.8842 127.5700 160.9807 [9] 125.3742 228.6781 > apply(copymatrix,1,var,na.rm=TRUE) [1] 233.1367 265.0658 186.4606 165.3668 213.8066 154.8842 127.5700 160.9807 [9] 125.3742 228.6781 > > > > 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] -5.684342e-14 -2.842171e-14 1.421085e-14 -5.684342e-14 0.000000e+00 [6] 5.684342e-14 -1.421085e-13 -5.684342e-14 -8.526513e-14 5.684342e-14 [11] 5.684342e-14 -8.526513e-14 1.989520e-13 -2.842171e-14 -8.526513e-14 [16] 2.842171e-14 -1.705303e-13 1.705303e-13 2.842171e-14 -7.105427e-14 > > > > > > > > > > > ## 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) + } 10 13 8 13 9 9 6 18 9 7 9 1 6 8 8 15 3 1 10 19 1 16 7 5 9 7 1 17 4 14 4 5 1 1 5 3 4 15 8 13 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] 2.419556 > Min(tmp) [1] -2.177475 > mean(tmp) [1] -0.0545071 > Sum(tmp) [1] -5.45071 > Var(tmp) [1] 0.7882957 > > rowMeans(tmp) [1] -0.0545071 > rowSums(tmp) [1] -5.45071 > rowVars(tmp) [1] 0.7882957 > rowSd(tmp) [1] 0.8878602 > rowMax(tmp) [1] 2.419556 > rowMin(tmp) [1] -2.177475 > > colMeans(tmp) [1] 0.39581988 -0.58802873 1.33372235 1.52216449 2.33469211 0.83412436 [7] -0.69257961 -0.84673589 0.54366696 -0.98114840 1.33329331 -0.27192644 [13] 2.41955597 -0.74671133 0.20332392 0.03138877 -0.45134603 1.17890427 [19] -1.12004276 -0.40065429 -0.93675173 0.30694825 0.35930069 1.28833288 [25] -0.53506194 -0.20415145 1.16962021 -0.69141465 -1.00702349 -0.26888882 [31] 0.36736622 -0.69471962 -1.10398334 -0.72934699 0.87778534 -0.90587413 [37] -0.04519204 -0.43239248 -0.93674630 -0.65107496 -1.19218568 1.24054823 [43] 0.88367495 -0.19358544 1.25147119 -0.90967378 -1.31953353 0.15319004 [49] -0.10045601 -0.83191616 -2.17747451 -0.72725638 -0.13257479 0.84731778 [55] 0.78198063 0.14421063 0.33957840 0.81461790 -0.31349594 0.71998269 [61] -0.70176268 -0.81853304 -0.11368793 0.22397182 -0.87994966 0.01966952 [67] -1.36807499 0.46667207 -0.06312468 0.85953374 -0.38488489 -1.55399800 [73] -0.72658876 -1.33833137 0.01520236 0.90442043 0.13168172 1.00099134 [79] -1.24427180 -1.33357542 0.69095771 0.32627770 0.07608671 -0.53822166 [85] 0.58512409 0.97802103 -0.85879132 0.07574278 -0.33477754 0.09391974 [91] 1.20349535 -0.41791123 0.77257823 -0.26389293 1.13701321 -0.53474747 [97] -1.68300387 0.09741134 0.43799381 -0.92598040 > colSums(tmp) [1] 0.39581988 -0.58802873 1.33372235 1.52216449 2.33469211 0.83412436 [7] -0.69257961 -0.84673589 0.54366696 -0.98114840 1.33329331 -0.27192644 [13] 2.41955597 -0.74671133 0.20332392 0.03138877 -0.45134603 1.17890427 [19] -1.12004276 -0.40065429 -0.93675173 0.30694825 0.35930069 1.28833288 [25] -0.53506194 -0.20415145 1.16962021 -0.69141465 -1.00702349 -0.26888882 [31] 0.36736622 -0.69471962 -1.10398334 -0.72934699 0.87778534 -0.90587413 [37] -0.04519204 -0.43239248 -0.93674630 -0.65107496 -1.19218568 1.24054823 [43] 0.88367495 -0.19358544 1.25147119 -0.90967378 -1.31953353 0.15319004 [49] -0.10045601 -0.83191616 -2.17747451 -0.72725638 -0.13257479 0.84731778 [55] 0.78198063 0.14421063 0.33957840 0.81461790 -0.31349594 0.71998269 [61] -0.70176268 -0.81853304 -0.11368793 0.22397182 -0.87994966 0.01966952 [67] -1.36807499 0.46667207 -0.06312468 0.85953374 -0.38488489 -1.55399800 [73] -0.72658876 -1.33833137 0.01520236 0.90442043 0.13168172 1.00099134 [79] -1.24427180 -1.33357542 0.69095771 0.32627770 0.07608671 -0.53822166 [85] 0.58512409 0.97802103 -0.85879132 0.07574278 -0.33477754 0.09391974 [91] 1.20349535 -0.41791123 0.77257823 -0.26389293 1.13701321 -0.53474747 [97] -1.68300387 0.09741134 0.43799381 -0.92598040 > 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] 0.39581988 -0.58802873 1.33372235 1.52216449 2.33469211 0.83412436 [7] -0.69257961 -0.84673589 0.54366696 -0.98114840 1.33329331 -0.27192644 [13] 2.41955597 -0.74671133 0.20332392 0.03138877 -0.45134603 1.17890427 [19] -1.12004276 -0.40065429 -0.93675173 0.30694825 0.35930069 1.28833288 [25] -0.53506194 -0.20415145 1.16962021 -0.69141465 -1.00702349 -0.26888882 [31] 0.36736622 -0.69471962 -1.10398334 -0.72934699 0.87778534 -0.90587413 [37] -0.04519204 -0.43239248 -0.93674630 -0.65107496 -1.19218568 1.24054823 [43] 0.88367495 -0.19358544 1.25147119 -0.90967378 -1.31953353 0.15319004 [49] -0.10045601 -0.83191616 -2.17747451 -0.72725638 -0.13257479 0.84731778 [55] 0.78198063 0.14421063 0.33957840 0.81461790 -0.31349594 0.71998269 [61] -0.70176268 -0.81853304 -0.11368793 0.22397182 -0.87994966 0.01966952 [67] -1.36807499 0.46667207 -0.06312468 0.85953374 -0.38488489 -1.55399800 [73] -0.72658876 -1.33833137 0.01520236 0.90442043 0.13168172 1.00099134 [79] -1.24427180 -1.33357542 0.69095771 0.32627770 0.07608671 -0.53822166 [85] 0.58512409 0.97802103 -0.85879132 0.07574278 -0.33477754 0.09391974 [91] 1.20349535 -0.41791123 0.77257823 -0.26389293 1.13701321 -0.53474747 [97] -1.68300387 0.09741134 0.43799381 -0.92598040 > colMin(tmp) [1] 0.39581988 -0.58802873 1.33372235 1.52216449 2.33469211 0.83412436 [7] -0.69257961 -0.84673589 0.54366696 -0.98114840 1.33329331 -0.27192644 [13] 2.41955597 -0.74671133 0.20332392 0.03138877 -0.45134603 1.17890427 [19] -1.12004276 -0.40065429 -0.93675173 0.30694825 0.35930069 1.28833288 [25] -0.53506194 -0.20415145 1.16962021 -0.69141465 -1.00702349 -0.26888882 [31] 0.36736622 -0.69471962 -1.10398334 -0.72934699 0.87778534 -0.90587413 [37] -0.04519204 -0.43239248 -0.93674630 -0.65107496 -1.19218568 1.24054823 [43] 0.88367495 -0.19358544 1.25147119 -0.90967378 -1.31953353 0.15319004 [49] -0.10045601 -0.83191616 -2.17747451 -0.72725638 -0.13257479 0.84731778 [55] 0.78198063 0.14421063 0.33957840 0.81461790 -0.31349594 0.71998269 [61] -0.70176268 -0.81853304 -0.11368793 0.22397182 -0.87994966 0.01966952 [67] -1.36807499 0.46667207 -0.06312468 0.85953374 -0.38488489 -1.55399800 [73] -0.72658876 -1.33833137 0.01520236 0.90442043 0.13168172 1.00099134 [79] -1.24427180 -1.33357542 0.69095771 0.32627770 0.07608671 -0.53822166 [85] 0.58512409 0.97802103 -0.85879132 0.07574278 -0.33477754 0.09391974 [91] 1.20349535 -0.41791123 0.77257823 -0.26389293 1.13701321 -0.53474747 [97] -1.68300387 0.09741134 0.43799381 -0.92598040 > colMedians(tmp) [1] 0.39581988 -0.58802873 1.33372235 1.52216449 2.33469211 0.83412436 [7] -0.69257961 -0.84673589 0.54366696 -0.98114840 1.33329331 -0.27192644 [13] 2.41955597 -0.74671133 0.20332392 0.03138877 -0.45134603 1.17890427 [19] -1.12004276 -0.40065429 -0.93675173 0.30694825 0.35930069 1.28833288 [25] -0.53506194 -0.20415145 1.16962021 -0.69141465 -1.00702349 -0.26888882 [31] 0.36736622 -0.69471962 -1.10398334 -0.72934699 0.87778534 -0.90587413 [37] -0.04519204 -0.43239248 -0.93674630 -0.65107496 -1.19218568 1.24054823 [43] 0.88367495 -0.19358544 1.25147119 -0.90967378 -1.31953353 0.15319004 [49] -0.10045601 -0.83191616 -2.17747451 -0.72725638 -0.13257479 0.84731778 [55] 0.78198063 0.14421063 0.33957840 0.81461790 -0.31349594 0.71998269 [61] -0.70176268 -0.81853304 -0.11368793 0.22397182 -0.87994966 0.01966952 [67] -1.36807499 0.46667207 -0.06312468 0.85953374 -0.38488489 -1.55399800 [73] -0.72658876 -1.33833137 0.01520236 0.90442043 0.13168172 1.00099134 [79] -1.24427180 -1.33357542 0.69095771 0.32627770 0.07608671 -0.53822166 [85] 0.58512409 0.97802103 -0.85879132 0.07574278 -0.33477754 0.09391974 [91] 1.20349535 -0.41791123 0.77257823 -0.26389293 1.13701321 -0.53474747 [97] -1.68300387 0.09741134 0.43799381 -0.92598040 > colRanges(tmp) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [1,] 0.3958199 -0.5880287 1.333722 1.522164 2.334692 0.8341244 -0.6925796 [2,] 0.3958199 -0.5880287 1.333722 1.522164 2.334692 0.8341244 -0.6925796 [,8] [,9] [,10] [,11] [,12] [,13] [,14] [1,] -0.8467359 0.543667 -0.9811484 1.333293 -0.2719264 2.419556 -0.7467113 [2,] -0.8467359 0.543667 -0.9811484 1.333293 -0.2719264 2.419556 -0.7467113 [,15] [,16] [,17] [,18] [,19] [,20] [,21] [1,] 0.2033239 0.03138877 -0.451346 1.178904 -1.120043 -0.4006543 -0.9367517 [2,] 0.2033239 0.03138877 -0.451346 1.178904 -1.120043 -0.4006543 -0.9367517 [,22] [,23] [,24] [,25] [,26] [,27] [,28] [1,] 0.3069483 0.3593007 1.288333 -0.5350619 -0.2041515 1.16962 -0.6914147 [2,] 0.3069483 0.3593007 1.288333 -0.5350619 -0.2041515 1.16962 -0.6914147 [,29] [,30] [,31] [,32] [,33] [,34] [,35] [1,] -1.007023 -0.2688888 0.3673662 -0.6947196 -1.103983 -0.729347 0.8777853 [2,] -1.007023 -0.2688888 0.3673662 -0.6947196 -1.103983 -0.729347 0.8777853 [,36] [,37] [,38] [,39] [,40] [,41] [,42] [1,] -0.9058741 -0.04519204 -0.4323925 -0.9367463 -0.651075 -1.192186 1.240548 [2,] -0.9058741 -0.04519204 -0.4323925 -0.9367463 -0.651075 -1.192186 1.240548 [,43] [,44] [,45] [,46] [,47] [,48] [,49] [1,] 0.883675 -0.1935854 1.251471 -0.9096738 -1.319534 0.15319 -0.100456 [2,] 0.883675 -0.1935854 1.251471 -0.9096738 -1.319534 0.15319 -0.100456 [,50] [,51] [,52] [,53] [,54] [,55] [,56] [1,] -0.8319162 -2.177475 -0.7272564 -0.1325748 0.8473178 0.7819806 0.1442106 [2,] -0.8319162 -2.177475 -0.7272564 -0.1325748 0.8473178 0.7819806 0.1442106 [,57] [,58] [,59] [,60] [,61] [,62] [,63] [1,] 0.3395784 0.8146179 -0.3134959 0.7199827 -0.7017627 -0.818533 -0.1136879 [2,] 0.3395784 0.8146179 -0.3134959 0.7199827 -0.7017627 -0.818533 -0.1136879 [,64] [,65] [,66] [,67] [,68] [,69] [,70] [1,] 0.2239718 -0.8799497 0.01966952 -1.368075 0.4666721 -0.06312468 0.8595337 [2,] 0.2239718 -0.8799497 0.01966952 -1.368075 0.4666721 -0.06312468 0.8595337 [,71] [,72] [,73] [,74] [,75] [,76] [,77] [1,] -0.3848849 -1.553998 -0.7265888 -1.338331 0.01520236 0.9044204 0.1316817 [2,] -0.3848849 -1.553998 -0.7265888 -1.338331 0.01520236 0.9044204 0.1316817 [,78] [,79] [,80] [,81] [,82] [,83] [,84] [1,] 1.000991 -1.244272 -1.333575 0.6909577 0.3262777 0.07608671 -0.5382217 [2,] 1.000991 -1.244272 -1.333575 0.6909577 0.3262777 0.07608671 -0.5382217 [,85] [,86] [,87] [,88] [,89] [,90] [,91] [1,] 0.5851241 0.978021 -0.8587913 0.07574278 -0.3347775 0.09391974 1.203495 [2,] 0.5851241 0.978021 -0.8587913 0.07574278 -0.3347775 0.09391974 1.203495 [,92] [,93] [,94] [,95] [,96] [,97] [,98] [1,] -0.4179112 0.7725782 -0.2638929 1.137013 -0.5347475 -1.683004 0.09741134 [2,] -0.4179112 0.7725782 -0.2638929 1.137013 -0.5347475 -1.683004 0.09741134 [,99] [,100] [1,] 0.4379938 -0.9259804 [2,] 0.4379938 -0.9259804 > > > Max(tmp2) [1] 3.027798 > Min(tmp2) [1] -2.957567 > mean(tmp2) [1] -0.04864743 > Sum(tmp2) [1] -4.864743 > Var(tmp2) [1] 1.320538 > > rowMeans(tmp2) [1] 0.547685710 -0.101734537 0.983813060 0.422990735 1.499264883 [6] -1.543239712 -0.701105659 0.206766073 1.538675997 1.087742924 [11] -0.100075579 -0.413937728 -1.508560787 0.643411953 0.110047640 [16] 0.625694954 -0.318276768 0.817918946 0.624330202 0.575309518 [21] -1.481472641 -1.828003218 0.250052028 0.767400973 1.496164508 [26] 0.287854278 1.858105464 -0.444601356 -0.205841173 -0.326073071 [31] 0.583739057 -1.892858629 0.634904394 -2.957566820 0.339083084 [36] -2.850813227 2.129859553 0.707617118 0.196012373 0.950425827 [41] 1.148154208 -0.631106434 -0.991053189 -0.865163035 -0.930604737 [46] -0.679533038 -1.041162860 -1.174341382 -0.100855274 0.685170698 [51] -0.552084862 -2.407375551 -1.154647602 3.027797531 -0.147921038 [56] -1.200696900 1.681796319 -0.703073425 0.386568371 -1.907006498 [61] -0.287473168 1.617335907 -0.931405501 -0.437738361 0.765795870 [66] 1.233448616 -1.560224105 -0.566722135 -0.532279210 0.876905520 [71] 1.913899406 -0.131183136 -0.552690883 0.251394821 0.300952415 [76] 1.141232375 0.667704947 -1.405953541 -1.501744537 -1.337309244 [81] -1.301229465 0.009643464 -1.559707784 0.503514813 -1.035313449 [86] -0.252626868 0.794632868 0.517716389 0.420575550 1.121321048 [91] -1.296733587 0.012697951 1.295425854 1.650338864 0.178721455 [96] 1.689970953 -1.676752845 0.757316714 -0.946744262 -0.925028280 > rowSums(tmp2) [1] 0.547685710 -0.101734537 0.983813060 0.422990735 1.499264883 [6] -1.543239712 -0.701105659 0.206766073 1.538675997 1.087742924 [11] -0.100075579 -0.413937728 -1.508560787 0.643411953 0.110047640 [16] 0.625694954 -0.318276768 0.817918946 0.624330202 0.575309518 [21] -1.481472641 -1.828003218 0.250052028 0.767400973 1.496164508 [26] 0.287854278 1.858105464 -0.444601356 -0.205841173 -0.326073071 [31] 0.583739057 -1.892858629 0.634904394 -2.957566820 0.339083084 [36] -2.850813227 2.129859553 0.707617118 0.196012373 0.950425827 [41] 1.148154208 -0.631106434 -0.991053189 -0.865163035 -0.930604737 [46] -0.679533038 -1.041162860 -1.174341382 -0.100855274 0.685170698 [51] -0.552084862 -2.407375551 -1.154647602 3.027797531 -0.147921038 [56] -1.200696900 1.681796319 -0.703073425 0.386568371 -1.907006498 [61] -0.287473168 1.617335907 -0.931405501 -0.437738361 0.765795870 [66] 1.233448616 -1.560224105 -0.566722135 -0.532279210 0.876905520 [71] 1.913899406 -0.131183136 -0.552690883 0.251394821 0.300952415 [76] 1.141232375 0.667704947 -1.405953541 -1.501744537 -1.337309244 [81] -1.301229465 0.009643464 -1.559707784 0.503514813 -1.035313449 [86] -0.252626868 0.794632868 0.517716389 0.420575550 1.121321048 [91] -1.296733587 0.012697951 1.295425854 1.650338864 0.178721455 [96] 1.689970953 -1.676752845 0.757316714 -0.946744262 -0.925028280 > 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] 0.547685710 -0.101734537 0.983813060 0.422990735 1.499264883 [6] -1.543239712 -0.701105659 0.206766073 1.538675997 1.087742924 [11] -0.100075579 -0.413937728 -1.508560787 0.643411953 0.110047640 [16] 0.625694954 -0.318276768 0.817918946 0.624330202 0.575309518 [21] -1.481472641 -1.828003218 0.250052028 0.767400973 1.496164508 [26] 0.287854278 1.858105464 -0.444601356 -0.205841173 -0.326073071 [31] 0.583739057 -1.892858629 0.634904394 -2.957566820 0.339083084 [36] -2.850813227 2.129859553 0.707617118 0.196012373 0.950425827 [41] 1.148154208 -0.631106434 -0.991053189 -0.865163035 -0.930604737 [46] -0.679533038 -1.041162860 -1.174341382 -0.100855274 0.685170698 [51] -0.552084862 -2.407375551 -1.154647602 3.027797531 -0.147921038 [56] -1.200696900 1.681796319 -0.703073425 0.386568371 -1.907006498 [61] -0.287473168 1.617335907 -0.931405501 -0.437738361 0.765795870 [66] 1.233448616 -1.560224105 -0.566722135 -0.532279210 0.876905520 [71] 1.913899406 -0.131183136 -0.552690883 0.251394821 0.300952415 [76] 1.141232375 0.667704947 -1.405953541 -1.501744537 -1.337309244 [81] -1.301229465 0.009643464 -1.559707784 0.503514813 -1.035313449 [86] -0.252626868 0.794632868 0.517716389 0.420575550 1.121321048 [91] -1.296733587 0.012697951 1.295425854 1.650338864 0.178721455 [96] 1.689970953 -1.676752845 0.757316714 -0.946744262 -0.925028280 > rowMin(tmp2) [1] 0.547685710 -0.101734537 0.983813060 0.422990735 1.499264883 [6] -1.543239712 -0.701105659 0.206766073 1.538675997 1.087742924 [11] -0.100075579 -0.413937728 -1.508560787 0.643411953 0.110047640 [16] 0.625694954 -0.318276768 0.817918946 0.624330202 0.575309518 [21] -1.481472641 -1.828003218 0.250052028 0.767400973 1.496164508 [26] 0.287854278 1.858105464 -0.444601356 -0.205841173 -0.326073071 [31] 0.583739057 -1.892858629 0.634904394 -2.957566820 0.339083084 [36] -2.850813227 2.129859553 0.707617118 0.196012373 0.950425827 [41] 1.148154208 -0.631106434 -0.991053189 -0.865163035 -0.930604737 [46] -0.679533038 -1.041162860 -1.174341382 -0.100855274 0.685170698 [51] -0.552084862 -2.407375551 -1.154647602 3.027797531 -0.147921038 [56] -1.200696900 1.681796319 -0.703073425 0.386568371 -1.907006498 [61] -0.287473168 1.617335907 -0.931405501 -0.437738361 0.765795870 [66] 1.233448616 -1.560224105 -0.566722135 -0.532279210 0.876905520 [71] 1.913899406 -0.131183136 -0.552690883 0.251394821 0.300952415 [76] 1.141232375 0.667704947 -1.405953541 -1.501744537 -1.337309244 [81] -1.301229465 0.009643464 -1.559707784 0.503514813 -1.035313449 [86] -0.252626868 0.794632868 0.517716389 0.420575550 1.121321048 [91] -1.296733587 0.012697951 1.295425854 1.650338864 0.178721455 [96] 1.689970953 -1.676752845 0.757316714 -0.946744262 -0.925028280 > > colMeans(tmp2) [1] -0.04864743 > colSums(tmp2) [1] -4.864743 > colVars(tmp2) [1] 1.320538 > colSd(tmp2) [1] 1.149147 > colMax(tmp2) [1] 3.027798 > colMin(tmp2) [1] -2.957567 > colMedians(tmp2) [1] 0.01117071 > colRanges(tmp2) [,1] [1,] -2.957567 [2,] 3.027798 > > 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] 4.8988703 -1.2008952 0.3981593 -6.6597366 -1.4151087 10.1640286 [7] -1.3577388 0.1187381 0.3498071 4.5146099 > colApply(tmp,quantile)[,1] [,1] [1,] -1.3523686 [2,] -0.3576861 [3,] 0.8578152 [4,] 1.0287236 [5,] 1.9919462 > > rowApply(tmp,sum) [1] -1.9229380 -0.7302314 -5.5198843 0.9505373 2.3593929 0.9663822 [7] 0.9600448 7.6850350 5.6266318 -0.5642362 > rowApply(tmp,rank)[1:10,] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 5 8 10 2 7 9 1 7 7 8 [2,] 8 3 5 7 9 5 4 4 2 5 [3,] 6 2 3 4 3 7 9 9 9 4 [4,] 1 1 1 5 6 1 5 3 1 2 [5,] 3 7 2 6 8 6 8 1 6 1 [6,] 7 6 8 9 10 10 10 8 4 9 [7,] 2 10 7 1 4 3 2 2 5 7 [8,] 9 5 4 3 1 4 3 10 10 10 [9,] 10 4 6 8 5 2 6 6 3 3 [10,] 4 9 9 10 2 8 7 5 8 6 > > tmp <- createBufferedMatrix(5,20) > > tmp[1:5,1:20] <- rnorm(100) > colApply(tmp,sum) [1] -0.12377047 0.66452395 -3.07360052 -2.89784705 0.04294543 6.42841858 [7] 2.55147868 -3.09786141 -5.67806202 3.17301169 -0.20408322 -4.74718994 [13] -3.01742030 1.56769700 2.57723329 -0.58168998 -1.14634663 0.53584617 [19] -1.62304327 -4.48184275 > colApply(tmp,quantile)[,1] [,1] [1,] -1.85258629 [2,] -0.14907609 [3,] -0.07098375 [4,] 0.73480120 [5,] 1.21407446 > > rowApply(tmp,sum) [1] -2.072386 -6.230981 3.827111 -9.736112 1.080766 > rowApply(tmp,rank)[1:5,] [,1] [,2] [,3] [,4] [,5] [1,] 16 4 10 15 17 [2,] 18 5 17 12 11 [3,] 15 7 7 9 1 [4,] 6 15 3 5 9 [5,] 8 17 4 13 12 > > > as.matrix(tmp) [,1] [,2] [,3] [,4] [,5] [,6] [1,] 0.73480120 1.3305003 0.6667560 -0.5075306 -0.3431442 1.5929108 [2,] -1.85258629 -1.4710547 -0.8449294 0.5068580 0.9423874 2.9028532 [3,] -0.07098375 1.1573110 -0.4006166 -1.2854413 -0.7045785 0.7965058 [4,] -0.14907609 -0.6214142 -0.7907093 -1.3784407 -0.2962209 1.2470278 [5,] 1.21407446 0.2691815 -1.7041013 -0.2332925 0.4445016 -0.1108790 [,7] [,8] [,9] [,10] [,11] [,12] [1,] 1.8392020 -1.0902176 -0.1522700 0.2136329 -0.4545699 0.3745353 [2,] 1.2211549 -2.7286482 -0.9441463 0.8121684 -0.6245593 -2.9628484 [3,] 0.5877801 0.7007646 -0.2481839 1.0444859 -0.5445528 -0.2161291 [4,] -0.7387211 1.5337836 -2.9021284 1.8940790 0.5027777 -1.0838277 [5,] -0.3579371 -1.5135439 -1.4313334 -0.7913545 0.9168210 -0.8589200 [,13] [,14] [,15] [,16] [,17] [,18] [1,] -2.2818012 -2.3921826 0.4258453 -1.7236419 -1.51760296 0.08937378 [2,] -0.3032026 -0.1498015 0.9696356 -0.1430431 -0.02984325 0.26913168 [3,] 1.5276166 2.4710039 -1.6396745 0.6516128 1.45183924 0.29113925 [4,] -1.0747837 -0.2865996 1.6956111 -0.7502493 -1.97497736 -1.64539882 [5,] -0.8852493 1.9252767 1.1258158 1.3836314 0.92423770 1.53160028 [,19] [,20] [1,] -0.005768929 1.1287860 [2,] 0.218486141 -2.0189932 [3,] -0.414566609 -1.3282216 [4,] -1.946006431 -0.9708379 [5,] 0.524812560 -1.2925761 > > > is.BufferedMatrix(tmp) [1] TRUE > > as.BufferedMatrix(as.matrix(tmp)) BufferedMatrix object Matrix size: 5 20 Buffer size: 1 1 Directory: /home/biocbuild/bbs-3.19-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-3.19-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 654 bytes. Disk usage : 200 bytes. > subBufferedMatrix(tmp,,5:8) BufferedMatrix object Matrix size: 5 4 Buffer size: 1 1 Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 566 bytes. Disk usage : 160 bytes. > subBufferedMatrix(tmp,1:3,) BufferedMatrix object Matrix size: 3 20 Buffer size: 1 1 Directory: /home/biocbuild/bbs-3.19-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 col7 row1 1.854898 0.9754459 -1.478383 0.884351 -1.683536 0.0230431 -2.867646 col8 col9 col10 col11 col12 col13 col14 row1 -0.923078 2.272056 0.9678272 2.181075 1.045384 -0.4385748 -0.9526382 col15 col16 col17 col18 col19 col20 row1 -0.779617 -0.2339619 -0.09823418 -0.7476343 -0.06489575 -0.2830363 > tmp[,"col10"] col10 row1 0.96782719 row2 0.06179989 row3 0.75497361 row4 1.01820777 row5 0.95306405 > tmp[c("row1","row5"),] col1 col2 col3 col4 col5 col6 col7 row1 1.8548983 0.9754459 -1.47838292 0.884351 -1.6835355 0.0230431 -2.867646 row5 0.2166501 0.4224217 0.01723733 -1.777695 0.6619821 -0.7431580 1.181908 col8 col9 col10 col11 col12 col13 col14 row1 -0.9230780 2.272056 0.9678272 2.1810753 1.045384 -0.4385748 -0.9526382 row5 -0.7201973 -1.258208 0.9530641 -0.8455358 -2.126681 -1.9866702 0.7416062 col15 col16 col17 col18 col19 col20 row1 -0.779617 -0.2339619 -0.09823418 -0.7476343 -0.06489575 -0.2830363 row5 -1.046003 -0.3845266 -0.01949927 -1.1537003 2.12068087 0.5889516 > tmp[,c("col6","col20")] col6 col20 row1 0.0230431 -0.2830363 row2 -1.0031281 -0.9075479 row3 -0.1574544 1.3311940 row4 1.3188096 -0.5868342 row5 -0.7431580 0.5889516 > tmp[c("row1","row5"),c("col6","col20")] col6 col20 row1 0.0230431 -0.2830363 row5 -0.7431580 0.5889516 > > > > > 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 50.04047 48.8525 48.91537 49.87559 48.50139 105.3983 50.02974 49.76008 col9 col10 col11 col12 col13 col14 col15 col16 row1 50.27365 49.11248 51.64005 50.50205 50.10658 49.25076 51.10062 46.9316 col17 col18 col19 col20 row1 48.29278 50.01709 50.01941 105.2475 > tmp[,"col10"] col10 row1 49.11248 row2 30.19833 row3 30.13529 row4 30.00833 row5 51.38601 > tmp[c("row1","row5"),] col1 col2 col3 col4 col5 col6 col7 col8 row1 50.04047 48.85250 48.91537 49.87559 48.50139 105.3983 50.02974 49.76008 row5 51.24119 51.00532 50.56537 49.55354 50.37157 104.6359 48.75273 50.62755 col9 col10 col11 col12 col13 col14 col15 col16 row1 50.27365 49.11248 51.64005 50.50205 50.10658 49.25076 51.10062 46.93160 row5 50.31450 51.38601 50.32100 49.40341 50.88642 49.18475 50.79908 49.14522 col17 col18 col19 col20 row1 48.29278 50.01709 50.01941 105.2475 row5 49.76227 49.44760 50.62101 104.5513 > tmp[,c("col6","col20")] col6 col20 row1 105.39828 105.24745 row2 73.71100 73.61676 row3 75.26537 74.42987 row4 74.41969 75.40286 row5 104.63587 104.55131 > tmp[c("row1","row5"),c("col6","col20")] col6 col20 row1 105.3983 105.2475 row5 104.6359 104.5513 > > > subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2] col6 col20 row1 105.3983 105.2475 row5 104.6359 104.5513 > > > > > > tmp <- createBufferedMatrix(5,20) > tmp[1:5,1:20] <- rnorm(100) > colnames(tmp) <- colnames(tmp,do.NULL=FALSE) > > tmp[,"col13"] col13 [1,] 0.75973733 [2,] -0.65178937 [3,] 0.04856532 [4,] -1.11583871 [5,] 1.98513992 > tmp[,c("col17","col7")] col17 col7 [1,] 1.7564508 0.97495806 [2,] -0.7626684 -0.38501012 [3,] -1.3545337 0.08878102 [4,] 0.8867298 -1.50945788 [5,] -0.3130282 -0.62644818 > > subBufferedMatrix(tmp,,c("col6","col20"))[,1:2] col6 col20 [1,] 0.01937701 1.36535643 [2,] 0.94817598 -0.66221575 [3,] 0.22481594 0.05567491 [4,] -0.50112895 -0.11551487 [5,] -0.61389549 1.02549445 > subBufferedMatrix(tmp,1,c("col6"))[,1] col1 [1,] 0.01937701 > subBufferedMatrix(tmp,1:2,c("col6"))[,1] col6 [1,] 0.01937701 [2,] 0.94817598 > > > > 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 0.1744096 1.535646 -0.03276707 0.1803503 1.139275 -1.8338084 0.341901 row1 -0.1413368 2.088203 -0.63834888 0.6152854 2.178245 -0.7650048 1.010197 [,8] [,9] [,10] [,11] [,12] [,13] row3 -1.2031596 0.3864236 -0.8277044 1.0730216 -0.5097399 -1.48617998 row1 0.3531779 -2.0815875 -0.1384659 -0.4375639 0.4964463 -0.09900803 [,14] [,15] [,16] [,17] [,18] [,19] row3 -1.0666705 0.3126795 1.5661706 0.1804110 0.9055581 0.001717239 row1 -0.8677452 -1.0896631 0.0807609 0.7585054 -0.8007040 1.282590158 [,20] row3 -1.0017361 row1 0.3456969 > subBufferedMatrix(tmp,c("row2"),1:10)[,1:10] [,1] [,2] [,3] [,4] [,5] [,6] [,7] row2 -0.2403108 0.09487479 -0.09991576 -2.264129 -2.535004 -1.910064 -0.1409716 [,8] [,9] [,10] row2 -0.6443069 0.800235 -0.9562909 > subBufferedMatrix(tmp,c("row5"),1:20)[,1:20] [,1] [,2] [,3] [,4] [,5] [,6] [,7] row5 -0.2758859 -0.8097635 0.6251316 2.19939 0.1925933 -1.758483 0.01973626 [,8] [,9] [,10] [,11] [,12] [,13] [,14] row5 1.359705 -0.0328878 -0.974449 1.17158 0.1715051 0.4162136 -1.115815 [,15] [,16] [,17] [,18] [,19] [,20] row5 -0.2474891 1.250419 1.732424 0.6266758 1.255233 -0.9528359 > > > 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: 0x55fe4adb1020> > is.ReadOnlyMode(tmp) [1] TRUE > > filenames(tmp) [1] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM392c415d17173c" [2] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM392c414f8e43e2" [3] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM392c413093b197" [4] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM392c4149608b08" [5] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM392c412700deba" [6] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM392c413a984773" [7] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM392c4158c2945" [8] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM392c41663ac59d" [9] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM392c41549c02c6" [10] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM392c415ec6d157" [11] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM392c4133e5a37d" [12] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM392c41534498fa" [13] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM392c416e6009eb" [14] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM392c411fcb5fb3" [15] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM392c41c454ec5" > > > ### 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: 0x55fe49ce1ca0> > MoveStorageDirectory(tmp,getwd(),full.path=TRUE) <pointer: 0x55fe49ce1ca0> Warning message: In dir.create(new.directory) : '/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests' already exists > > > RowMode(tmp) <pointer: 0x55fe49ce1ca0> > rowMedians(tmp) [1] 0.431649036 -0.042020562 -0.418753697 0.127744939 0.417295206 [6] 0.117814198 0.105882277 -0.228207344 -0.160387872 0.581019264 [11] -0.612163547 0.248137473 0.087267993 0.017976586 0.648455378 [16] -0.425846449 0.747691949 0.140317407 0.174051715 0.009119733 [21] -0.409256097 0.165565657 0.100039693 -0.448474572 -0.217907991 [26] -0.602829508 0.295787868 -0.086485288 0.467170511 -0.507950637 [31] 0.244197768 -0.070095319 0.039522479 0.395282336 0.337308570 [36] -0.684406630 0.214438887 -0.035934974 0.236355201 0.274118559 [41] -0.414575476 -0.117423068 0.242565504 -0.072203570 -0.490618537 [46] 0.115148393 -0.379546726 0.036400033 0.667074497 -0.128519644 [51] 0.055280751 0.328932116 0.140557852 0.232742827 -0.232596543 [56] -0.317585709 0.080644884 0.054899652 -0.268082352 -0.098101102 [61] -0.123757962 -0.406313435 -0.188994177 -0.157288875 -0.106357089 [66] -0.167937042 0.235590759 -0.118961224 0.396170531 -0.308480090 [71] -0.272684722 -0.576202998 -0.631270924 -0.178958431 0.338651427 [76] 0.259626616 0.366954025 0.242955106 0.034017482 -0.023989360 [81] 0.065590232 0.294306341 -0.396058713 -0.228413519 0.229055612 [86] -0.540836557 0.556811582 0.190517036 0.181354213 -0.179548840 [91] -0.307618628 -0.198859323 -0.078654242 -0.096796663 0.227582284 [96] -0.194353381 0.217846931 0.056808037 -0.049804981 -0.416379355 [101] -0.041043205 0.011713733 -0.605426655 0.459768562 -0.213405985 [106] 0.002305022 -0.458499111 0.050747276 0.082393836 -0.793739777 [111] 0.779211878 -0.372000981 0.169140309 -0.356913776 0.624638182 [116] 0.161586786 -0.107287751 -0.086470095 0.208477625 -0.194221114 [121] 0.570849178 -0.228010672 0.279010621 -0.005592513 -0.455240964 [126] -0.109948838 -0.396198993 0.192507368 0.039681473 0.119925133 [131] 0.308203639 0.395754620 -0.715368546 0.229467322 -0.201176227 [136] 0.070465873 -0.009393212 -0.078890017 0.200044580 -0.594605342 [141] -0.705723791 0.020934129 -0.102977930 -0.155527188 -0.304885526 [146] 0.410118673 -0.739019784 0.307839446 0.474129341 0.168647973 [151] 0.222050894 0.167906889 -0.107525301 -0.180597835 0.329003513 [156] 0.218520000 0.114819170 0.026601118 -0.068327797 -0.356452644 [161] -0.386866293 0.076847751 -0.047232794 -0.282029528 0.080839664 [166] 0.356935064 -0.461263458 0.405438172 -0.158492347 0.320853636 [171] 0.235840694 0.243796457 0.346147139 -0.619401302 -0.190867173 [176] -0.841753789 -0.172075254 0.148540109 0.234862779 0.109545930 [181] -0.403640324 0.136740589 0.003091633 0.017151430 -0.432347054 [186] -0.450635391 0.160018677 -0.232381649 -0.176890776 0.164912190 [191] 0.187512875 -0.101716491 -0.197519748 0.152934068 -0.146859601 [196] -0.072147264 0.133568764 0.018070707 0.281567091 0.341737662 [201] -0.370839787 -0.191849106 0.189106830 -0.095445321 -0.352381468 [206] -0.453290861 0.260521569 0.253982020 0.080027006 -0.220788594 [211] 0.029272183 0.659160484 -0.019842566 0.056431895 0.002858771 [216] 0.414834019 0.207176618 -0.373953522 0.172640164 -0.241137661 [221] 0.628365054 0.077057501 -0.192954608 0.151359317 0.009872430 [226] -0.278931652 -0.303963454 0.090690921 0.180184193 0.066505279 > > proc.time() user system elapsed 1.340 1.522 2.880
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" Copyright (C) 2024 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: 0x55bfc64bab20> > .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: 0x55bfc64bab20> > .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: 0x55bfc64bab20> > .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: 0x55bfc64bab20> > 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: 0x55bfc44e4430> > .Call("R_bm_AddColumn",P) <pointer: 0x55bfc44e4430> > .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: 0x55bfc44e4430> > .Call("R_bm_AddColumn",P) <pointer: 0x55bfc44e4430> > .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: 0x55bfc44e4430> > 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: 0x55bfc44cfc60> > .Call("R_bm_AddColumn",P) <pointer: 0x55bfc44cfc60> > .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: 0x55bfc44cfc60> > > .Call("R_bm_ResizeBuffer",P,5,5) <pointer: 0x55bfc44cfc60> > .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: 0x55bfc44cfc60> > > .Call("R_bm_RowMode",P) <pointer: 0x55bfc44cfc60> > .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: 0x55bfc44cfc60> > > .Call("R_bm_ColMode",P) <pointer: 0x55bfc44cfc60> > .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: 0x55bfc44cfc60> > 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: 0x55bfc432a030> > .Call("R_bm_SetPrefix",P,"BufferedMatrixFile") <pointer: 0x55bfc432a030> > .Call("R_bm_AddColumn",P) <pointer: 0x55bfc432a030> > .Call("R_bm_AddColumn",P) <pointer: 0x55bfc432a030> > dir(pattern="BufferedMatrixFile") [1] "BufferedMatrixFile3931833781d41c" "BufferedMatrixFile393183638ad6c8" > rm(P) > dir(pattern="BufferedMatrixFile") [1] "BufferedMatrixFile3931833781d41c" "BufferedMatrixFile393183638ad6c8" > > > P <- .Call("R_bm_Create",prefix,directory,1,1) > .Call("R_bm_setRows",P,10) [1] TRUE > .Call("R_bm_AddColumn",P) <pointer: 0x55bfc545aac0> > .Call("R_bm_AddColumn",P) <pointer: 0x55bfc545aac0> > .Call("R_bm_ReadOnlyModeToggle",P) <pointer: 0x55bfc545aac0> > .Call("R_bm_isReadOnlyMode",P) [1] TRUE > .Call("R_bm_ReadOnlyModeToggle",P) <pointer: 0x55bfc545aac0> > .Call("R_bm_isReadOnlyMode",P) [1] FALSE > .Call("R_bm_isRowMode",P) [1] FALSE > .Call("R_bm_RowMode",P) <pointer: 0x55bfc545aac0> > .Call("R_bm_isRowMode",P) [1] TRUE > .Call("R_bm_ColMode",P) <pointer: 0x55bfc545aac0> > .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: 0x55bfc4f61b90> > .Call("R_bm_AddColumn",P) <pointer: 0x55bfc4f61b90> > > .Call("R_bm_getSize",P) [1] 10 2 > .Call("R_bm_getBufferSize",P) [1] 1 1 > .Call("R_bm_ResizeBuffer",P,5,5) <pointer: 0x55bfc4f61b90> > > .Call("R_bm_getBufferSize",P) [1] 5 5 > .Call("R_bm_ResizeBuffer",P,-1,5) <pointer: 0x55bfc4f61b90> > 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: 0x55bfc5121430> > .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: 0x55bfc5121430> > rm(P) > > proc.time() user system elapsed 0.256 0.055 0.300
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" Copyright (C) 2024 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 0.258 0.042 0.287