Back to Multiple platform build/check report for BioC 3.19: simplified long |
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This page was generated on 2024-06-11 14:42 -0400 (Tue, 11 Jun 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4757 |
palomino3 | Windows Server 2022 Datacenter | x64 | 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup" | 4491 |
lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4522 |
kjohnson3 | macOS 13.6.5 Ventura | arm64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4468 |
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 | |||||||||
kjohnson3 | macOS 13.6.5 Ventura / arm64 | OK | OK | WARNINGS | 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: 1.68.0 |
Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.68.0.tar.gz |
StartedAt: 2024-06-09 19:10:55 -0400 (Sun, 09 Jun 2024) |
EndedAt: 2024-06-09 19:11:42 -0400 (Sun, 09 Jun 2024) |
EllapsedTime: 47.6 seconds |
RetCode: 0 |
Status: WARNINGS |
CheckDir: BufferedMatrix.Rcheck |
Warnings: 1 |
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.68.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck’ * using R version 4.4.0 (2024-04-24) * using platform: x86_64-apple-darwin20 * R was compiled by Apple clang version 14.0.0 (clang-1400.0.29.202) GNU Fortran (GCC) 12.2.0 * running under: macOS Monterey 12.7.1 * using session charset: UTF-8 * using option ‘--no-vignettes’ * 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 ... WARNING Found the following significant warnings: doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses] See ‘/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details. * used C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’ * used SDK: ‘MacOSX11.3.sdk’ * 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 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 sizes of PDF files under ‘inst/doc’ ... OK * 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 running R code from vignettes ... SKIPPED * checking re-building of vignette outputs ... SKIPPED * checking PDF version of manual ... OK * DONE Status: 1 WARNING, 2 NOTEs See ‘/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/00check.log’ for details.
BufferedMatrix.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix ### ############################################################################## ############################################################################## * installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library’ * installing *source* package ‘BufferedMatrix’ ... ** using staged installation ** libs using C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’ using SDK: ‘MacOSX11.3.sdk’ clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses] if (!(Matrix->readonly) & setting){ ^ ~ doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first if (!(Matrix->readonly) & setting){ ^ ( ) doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning if (!(Matrix->readonly) & setting){ ^ ( ) doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function] static int sort_double(const double *a1,const double *a2){ ^ 2 warnings generated. clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o clang -arch x86_64 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/x86_64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation installing to /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/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 (2024-04-24) -- "Puppy Cup" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-apple-darwin20 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 0.343 0.132 0.479
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-apple-darwin20 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] "/Users/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) limit (Mb) max used (Mb) Ncells 474174 25.4 1035464 55.3 NA 638637 34.2 Vcells 877658 6.7 8388608 64.0 98304 2071778 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] "Sun Jun 9 19:11:18 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] "Sun Jun 9 19:11:19 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: 0x60000078c000> > > > > 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] "Sun Jun 9 19:11:23 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] "Sun Jun 9 19:11:24 2024" > > ColMode(tmp2) <pointer: 0x60000078c000> > > > > ### 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,] 98.3478856 -0.7682341 -0.1660270 -0.8134644 [2,] 0.2903112 -1.6345638 0.4656637 0.8381190 [3,] -0.5988870 -1.7591914 -0.6677717 0.9324065 [4,] -2.2153285 -0.5529421 -0.3997165 -0.6346685 > ewApply(tmp5,abs) BufferedMatrix object Matrix size: 10 20 Buffer size: 1 1 Directory: /Users/biocbuild/bbs-3.19-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,] 98.3478856 0.7682341 0.1660270 0.8134644 [2,] 0.2903112 1.6345638 0.4656637 0.8381190 [3,] 0.5988870 1.7591914 0.6677717 0.9324065 [4,] 2.2153285 0.5529421 0.3997165 0.6346685 > ewApply(tmp5,sqrt) BufferedMatrix object Matrix size: 10 20 Buffer size: 1 1 Directory: /Users/biocbuild/bbs-3.19-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,] 9.9170502 0.8764897 0.4074641 0.9019226 [2,] 0.5388053 1.2785006 0.6823956 0.9154884 [3,] 0.7738779 1.3263451 0.8171730 0.9656120 [4,] 1.4883980 0.7436008 0.6322314 0.7966609 > > 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: /Users/biocbuild/bbs-3.19-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,] 222.51839 34.53313 29.24067 34.83269 [2,] 30.67836 39.41957 32.28962 34.99300 [3,] 33.33767 40.02264 33.83950 35.58853 [4,] 42.09931 32.98895 31.72203 33.60128 > > > > ## testing functions that elementwise transform the matrix > sqrt(tmp5) <pointer: 0x600000788000> > exp(tmp5) <pointer: 0x600000788000> > log(tmp5,2) <pointer: 0x600000788000> > pow(tmp5,2) > > > > > > ## testing functions that apply to entire matrix > Max(tmp5) [1] 463.1429 > Min(tmp5) [1] 54.26333 > mean(tmp5) [1] 72.73544 > Sum(tmp5) [1] 14547.09 > Var(tmp5) [1] 843.7 > > > ## testing functions applied to rows or columns > > rowMeans(tmp5) [1] 92.05861 69.99514 68.06333 71.78676 69.94874 72.54794 73.63904 69.47345 [9] 70.87504 68.96636 > rowSums(tmp5) [1] 1841.172 1399.903 1361.267 1435.735 1398.975 1450.959 1472.781 1389.469 [9] 1417.501 1379.327 > rowVars(tmp5) [1] 7698.09794 82.51241 61.60521 71.79267 88.02969 78.05434 [7] 84.86018 85.09170 56.06039 66.80859 > rowSd(tmp5) [1] 87.738805 9.083634 7.848899 8.473055 9.382414 8.834837 9.211958 [8] 9.224516 7.487349 8.173652 > rowMax(tmp5) [1] 463.14287 83.87520 83.30189 89.04542 86.13879 83.16919 94.87865 [8] 89.48070 86.86769 88.29878 > rowMin(tmp5) [1] 60.86062 54.26333 57.22369 59.84883 55.23655 56.25964 56.99211 58.53390 [9] 60.32769 55.82601 > > colMeans(tmp5) [1] 113.85677 74.27374 69.71159 68.70404 65.58042 67.89923 76.97307 [8] 73.05050 67.48320 68.11601 72.05316 74.99460 73.04413 72.97603 [15] 69.12249 68.72514 67.86924 69.07643 70.68468 70.51434 > colSums(tmp5) [1] 1138.5677 742.7374 697.1159 687.0404 655.8042 678.9923 769.7307 [8] 730.5050 674.8320 681.1601 720.5316 749.9460 730.4413 729.7603 [15] 691.2249 687.2514 678.6924 690.7643 706.8468 705.1434 > colVars(tmp5) [1] 15114.66786 100.49645 81.01142 37.16487 71.71497 51.51909 [7] 73.83212 112.45357 26.58364 79.33167 38.15005 97.96677 [13] 66.09044 103.11247 64.75210 118.12075 61.37206 71.15988 [19] 76.27303 52.30840 > colSd(tmp5) [1] 122.941725 10.024792 9.000634 6.096300 8.468469 7.177680 [7] 8.592562 10.604413 5.155933 8.906833 6.176573 9.897817 [13] 8.129603 10.154431 8.046869 10.868337 7.834032 8.435632 [19] 8.733443 7.232455 > colMax(tmp5) [1] 463.14287 94.87865 86.86769 75.63373 82.32366 80.43357 89.17752 [8] 89.48070 79.29750 85.05806 81.43647 88.29878 83.87520 89.04542 [15] 82.69844 84.20272 84.24761 83.16698 82.60904 86.13879 > colMin(tmp5) [1] 63.85300 58.98017 57.29835 56.99211 54.26333 57.57065 59.49377 55.82601 [9] 62.19406 55.64515 61.86306 58.64904 57.22369 60.50085 58.51805 56.25964 [17] 60.38407 55.23655 57.24552 63.90652 > > > ### 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] NA 69.99514 68.06333 71.78676 69.94874 72.54794 73.63904 69.47345 [9] 70.87504 68.96636 > rowSums(tmp5) [1] NA 1399.903 1361.267 1435.735 1398.975 1450.959 1472.781 1389.469 [9] 1417.501 1379.327 > rowVars(tmp5) [1] 8098.86328 82.51241 61.60521 71.79267 88.02969 78.05434 [7] 84.86018 85.09170 56.06039 66.80859 > rowSd(tmp5) [1] 89.993685 9.083634 7.848899 8.473055 9.382414 8.834837 9.211958 [8] 9.224516 7.487349 8.173652 > rowMax(tmp5) [1] NA 83.87520 83.30189 89.04542 86.13879 83.16919 94.87865 89.48070 [9] 86.86769 88.29878 > rowMin(tmp5) [1] NA 54.26333 57.22369 59.84883 55.23655 56.25964 56.99211 58.53390 [9] 60.32769 55.82601 > > colMeans(tmp5) [1] 113.85677 74.27374 69.71159 68.70404 65.58042 67.89923 76.97307 [8] 73.05050 67.48320 NA 72.05316 74.99460 73.04413 72.97603 [15] 69.12249 68.72514 67.86924 69.07643 70.68468 70.51434 > colSums(tmp5) [1] 1138.5677 742.7374 697.1159 687.0404 655.8042 678.9923 769.7307 [8] 730.5050 674.8320 NA 720.5316 749.9460 730.4413 729.7603 [15] 691.2249 687.2514 678.6924 690.7643 706.8468 705.1434 > colVars(tmp5) [1] 15114.66786 100.49645 81.01142 37.16487 71.71497 51.51909 [7] 73.83212 112.45357 26.58364 NA 38.15005 97.96677 [13] 66.09044 103.11247 64.75210 118.12075 61.37206 71.15988 [19] 76.27303 52.30840 > colSd(tmp5) [1] 122.941725 10.024792 9.000634 6.096300 8.468469 7.177680 [7] 8.592562 10.604413 5.155933 NA 6.176573 9.897817 [13] 8.129603 10.154431 8.046869 10.868337 7.834032 8.435632 [19] 8.733443 7.232455 > colMax(tmp5) [1] 463.14287 94.87865 86.86769 75.63373 82.32366 80.43357 89.17752 [8] 89.48070 79.29750 NA 81.43647 88.29878 83.87520 89.04542 [15] 82.69844 84.20272 84.24761 83.16698 82.60904 86.13879 > colMin(tmp5) [1] 63.85300 58.98017 57.29835 56.99211 54.26333 57.57065 59.49377 55.82601 [9] 62.19406 NA 61.86306 58.64904 57.22369 60.50085 58.51805 56.25964 [17] 60.38407 55.23655 57.24552 63.90652 > > Max(tmp5,na.rm=TRUE) [1] 463.1429 > Min(tmp5,na.rm=TRUE) [1] 54.26333 > mean(tmp5,na.rm=TRUE) [1] 72.74613 > Sum(tmp5,na.rm=TRUE) [1] 14476.48 > Var(tmp5,na.rm=TRUE) [1] 847.9381 > > rowMeans(tmp5,na.rm=TRUE) [1] 93.18756 69.99514 68.06333 71.78676 69.94874 72.54794 73.63904 69.47345 [9] 70.87504 68.96636 > rowSums(tmp5,na.rm=TRUE) [1] 1770.564 1399.903 1361.267 1435.735 1398.975 1450.959 1472.781 1389.469 [9] 1417.501 1379.327 > rowVars(tmp5,na.rm=TRUE) [1] 8098.86328 82.51241 61.60521 71.79267 88.02969 78.05434 [7] 84.86018 85.09170 56.06039 66.80859 > rowSd(tmp5,na.rm=TRUE) [1] 89.993685 9.083634 7.848899 8.473055 9.382414 8.834837 9.211958 [8] 9.224516 7.487349 8.173652 > rowMax(tmp5,na.rm=TRUE) [1] 463.14287 83.87520 83.30189 89.04542 86.13879 83.16919 94.87865 [8] 89.48070 86.86769 88.29878 > rowMin(tmp5,na.rm=TRUE) [1] 60.86062 54.26333 57.22369 59.84883 55.23655 56.25964 56.99211 58.53390 [9] 60.32769 55.82601 > > colMeans(tmp5,na.rm=TRUE) [1] 113.85677 74.27374 69.71159 68.70404 65.58042 67.89923 76.97307 [8] 73.05050 67.48320 67.83906 72.05316 74.99460 73.04413 72.97603 [15] 69.12249 68.72514 67.86924 69.07643 70.68468 70.51434 > colSums(tmp5,na.rm=TRUE) [1] 1138.5677 742.7374 697.1159 687.0404 655.8042 678.9923 769.7307 [8] 730.5050 674.8320 610.5515 720.5316 749.9460 730.4413 729.7603 [15] 691.2249 687.2514 678.6924 690.7643 706.8468 705.1434 > colVars(tmp5,na.rm=TRUE) [1] 15114.66786 100.49645 81.01142 37.16487 71.71497 51.51909 [7] 73.83212 112.45357 26.58364 88.38525 38.15005 97.96677 [13] 66.09044 103.11247 64.75210 118.12075 61.37206 71.15988 [19] 76.27303 52.30840 > colSd(tmp5,na.rm=TRUE) [1] 122.941725 10.024792 9.000634 6.096300 8.468469 7.177680 [7] 8.592562 10.604413 5.155933 9.401343 6.176573 9.897817 [13] 8.129603 10.154431 8.046869 10.868337 7.834032 8.435632 [19] 8.733443 7.232455 > colMax(tmp5,na.rm=TRUE) [1] 463.14287 94.87865 86.86769 75.63373 82.32366 80.43357 89.17752 [8] 89.48070 79.29750 85.05806 81.43647 88.29878 83.87520 89.04542 [15] 82.69844 84.20272 84.24761 83.16698 82.60904 86.13879 > colMin(tmp5,na.rm=TRUE) [1] 63.85300 58.98017 57.29835 56.99211 54.26333 57.57065 59.49377 55.82601 [9] 62.19406 55.64515 61.86306 58.64904 57.22369 60.50085 58.51805 56.25964 [17] 60.38407 55.23655 57.24552 63.90652 > > # now set an entire row to NA > > tmp5[which.row,] <- NA > rowMeans(tmp5,na.rm=TRUE) [1] NaN 69.99514 68.06333 71.78676 69.94874 72.54794 73.63904 69.47345 [9] 70.87504 68.96636 > rowSums(tmp5,na.rm=TRUE) [1] 0.000 1399.903 1361.267 1435.735 1398.975 1450.959 1472.781 1389.469 [9] 1417.501 1379.327 > rowVars(tmp5,na.rm=TRUE) [1] NA 82.51241 61.60521 71.79267 88.02969 78.05434 84.86018 85.09170 [9] 56.06039 66.80859 > rowSd(tmp5,na.rm=TRUE) [1] NA 9.083634 7.848899 8.473055 9.382414 8.834837 9.211958 9.224516 [9] 7.487349 8.173652 > rowMax(tmp5,na.rm=TRUE) [1] NA 83.87520 83.30189 89.04542 86.13879 83.16919 94.87865 89.48070 [9] 86.86769 88.29878 > rowMin(tmp5,na.rm=TRUE) [1] NA 54.26333 57.22369 59.84883 55.23655 56.25964 56.99211 58.53390 [9] 60.32769 55.82601 > > > # now set an entire col to NA > > > tmp5[,which.col] <- NA > colMeans(tmp5,na.rm=TRUE) [1] 75.04720 74.54013 70.69503 68.28230 64.51287 66.50653 75.61703 71.85138 [9] 68.03984 NaN 72.47249 76.38925 72.17185 73.57369 68.63373 67.27536 [17] 68.48688 69.41372 69.35975 71.06039 > colSums(tmp5,na.rm=TRUE) [1] 675.4248 670.8612 636.2553 614.5407 580.6158 598.5588 680.5532 646.6625 [9] 612.3585 0.0000 652.2524 687.5032 649.5467 662.1632 617.7036 605.4782 [17] 616.3819 624.7235 624.2377 639.5435 > colVars(tmp5,na.rm=TRUE) [1] 59.44849 112.26014 80.25733 39.80952 67.85811 36.13820 62.37385 [8] 110.33416 26.42092 NA 40.94068 88.33089 65.79193 111.98311 [15] 70.15862 109.23979 64.75197 78.77504 66.05849 55.49263 > colSd(tmp5,na.rm=TRUE) [1] 7.710285 10.595289 8.958645 6.309478 8.237603 6.011505 7.897712 [8] 10.504007 5.140128 NA 6.398490 9.398452 8.111222 10.582207 [15] 8.376074 10.451784 8.046861 8.875530 8.127638 7.449337 > colMax(tmp5,na.rm=TRUE) [1] 87.62419 94.87865 86.86769 75.63373 82.32366 76.80798 86.86284 89.48070 [9] 79.29750 -Inf 81.43647 88.29878 83.87520 89.04542 82.69844 84.20272 [17] 84.24761 83.16698 82.39076 86.13879 > colMin(tmp5,na.rm=TRUE) [1] 63.85300 58.98017 57.29835 56.99211 54.26333 57.57065 59.49377 55.82601 [9] 62.19406 Inf 61.86306 58.64904 57.22369 60.50085 58.51805 56.25964 [17] 60.38407 55.23655 57.24552 63.90652 > > > > > 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] 216.1239 372.1812 214.1715 217.1701 208.1594 392.3281 110.5723 211.3967 [9] 151.5563 201.7589 > apply(copymatrix,1,var,na.rm=TRUE) [1] 216.1239 372.1812 214.1715 217.1701 208.1594 392.3281 110.5723 211.3967 [9] 151.5563 201.7589 > > > > 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] 2.842171e-14 -2.842171e-14 -2.842171e-13 2.842171e-14 8.526513e-14 [6] -8.526513e-14 1.136868e-13 0.000000e+00 2.842171e-14 5.684342e-14 [11] 2.842171e-14 -1.136868e-13 -5.684342e-14 -8.526513e-14 -2.842171e-13 [16] 5.684342e-14 -1.421085e-13 2.842171e-14 -2.842171e-14 0.000000e+00 > > > > > > > > > > > ## 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 3 3 17 10 5 4 11 6 10 8 12 10 11 4 18 10 7 9 20 4 16 8 13 8 12 7 14 2 19 8 11 4 19 1 13 2 15 6 4 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] 1.95317 > Min(tmp) [1] -2.777506 > mean(tmp) [1] 0.1350977 > Sum(tmp) [1] 13.50977 > Var(tmp) [1] 0.9051181 > > rowMeans(tmp) [1] 0.1350977 > rowSums(tmp) [1] 13.50977 > rowVars(tmp) [1] 0.9051181 > rowSd(tmp) [1] 0.9513769 > rowMax(tmp) [1] 1.95317 > rowMin(tmp) [1] -2.777506 > > colMeans(tmp) [1] 0.51896428 0.39035851 1.02428843 0.98295693 1.21981599 -0.01949250 [7] -1.53717543 0.15634453 0.06358518 -1.77164451 -0.74460918 0.96709833 [13] 0.74358407 -1.03095117 1.35674389 0.90408797 0.53716604 0.91305957 [19] 0.06594654 0.28189414 0.16634447 0.07255518 0.33264454 1.95317047 [25] 0.09731804 1.23917423 1.06247678 -1.69420682 1.43083346 -0.46043551 [31] -0.43641675 1.50752919 -1.69169295 -1.57609966 -1.05786098 0.07342189 [37] -0.69233750 -2.77750636 0.83154201 1.89891807 -0.38605253 1.50159368 [43] -0.66034141 1.57124232 0.24420551 -0.78107246 -0.23783076 -0.33970261 [49] -0.65321697 -0.02483335 1.10632602 -1.06468706 -0.75990867 -0.47653489 [55] 0.29146034 -0.29979533 -1.00137709 1.90322098 0.41795019 0.98608278 [61] -0.74076631 -1.06209358 -0.36705699 -0.75112370 -0.14863840 -0.16094742 [67] 0.45826868 1.08204745 -0.19447266 0.95398803 1.04295096 0.86333871 [73] 1.46495009 0.76771275 0.71871992 1.17756404 1.07303022 1.02167239 [79] 0.50293457 0.24920757 -0.94918807 0.65356237 -0.02427790 0.46865232 [85] 0.21016021 1.28201882 -0.02722187 -0.63574315 -1.00287129 -0.19702155 [91] 0.61457873 -0.51299762 0.31541983 -1.23426222 0.15004873 -0.05615311 [97] -0.90315157 1.02672102 -1.45576127 1.19784885 > colSums(tmp) [1] 0.51896428 0.39035851 1.02428843 0.98295693 1.21981599 -0.01949250 [7] -1.53717543 0.15634453 0.06358518 -1.77164451 -0.74460918 0.96709833 [13] 0.74358407 -1.03095117 1.35674389 0.90408797 0.53716604 0.91305957 [19] 0.06594654 0.28189414 0.16634447 0.07255518 0.33264454 1.95317047 [25] 0.09731804 1.23917423 1.06247678 -1.69420682 1.43083346 -0.46043551 [31] -0.43641675 1.50752919 -1.69169295 -1.57609966 -1.05786098 0.07342189 [37] -0.69233750 -2.77750636 0.83154201 1.89891807 -0.38605253 1.50159368 [43] -0.66034141 1.57124232 0.24420551 -0.78107246 -0.23783076 -0.33970261 [49] -0.65321697 -0.02483335 1.10632602 -1.06468706 -0.75990867 -0.47653489 [55] 0.29146034 -0.29979533 -1.00137709 1.90322098 0.41795019 0.98608278 [61] -0.74076631 -1.06209358 -0.36705699 -0.75112370 -0.14863840 -0.16094742 [67] 0.45826868 1.08204745 -0.19447266 0.95398803 1.04295096 0.86333871 [73] 1.46495009 0.76771275 0.71871992 1.17756404 1.07303022 1.02167239 [79] 0.50293457 0.24920757 -0.94918807 0.65356237 -0.02427790 0.46865232 [85] 0.21016021 1.28201882 -0.02722187 -0.63574315 -1.00287129 -0.19702155 [91] 0.61457873 -0.51299762 0.31541983 -1.23426222 0.15004873 -0.05615311 [97] -0.90315157 1.02672102 -1.45576127 1.19784885 > 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] 0.51896428 0.39035851 1.02428843 0.98295693 1.21981599 -0.01949250 [7] -1.53717543 0.15634453 0.06358518 -1.77164451 -0.74460918 0.96709833 [13] 0.74358407 -1.03095117 1.35674389 0.90408797 0.53716604 0.91305957 [19] 0.06594654 0.28189414 0.16634447 0.07255518 0.33264454 1.95317047 [25] 0.09731804 1.23917423 1.06247678 -1.69420682 1.43083346 -0.46043551 [31] -0.43641675 1.50752919 -1.69169295 -1.57609966 -1.05786098 0.07342189 [37] -0.69233750 -2.77750636 0.83154201 1.89891807 -0.38605253 1.50159368 [43] -0.66034141 1.57124232 0.24420551 -0.78107246 -0.23783076 -0.33970261 [49] -0.65321697 -0.02483335 1.10632602 -1.06468706 -0.75990867 -0.47653489 [55] 0.29146034 -0.29979533 -1.00137709 1.90322098 0.41795019 0.98608278 [61] -0.74076631 -1.06209358 -0.36705699 -0.75112370 -0.14863840 -0.16094742 [67] 0.45826868 1.08204745 -0.19447266 0.95398803 1.04295096 0.86333871 [73] 1.46495009 0.76771275 0.71871992 1.17756404 1.07303022 1.02167239 [79] 0.50293457 0.24920757 -0.94918807 0.65356237 -0.02427790 0.46865232 [85] 0.21016021 1.28201882 -0.02722187 -0.63574315 -1.00287129 -0.19702155 [91] 0.61457873 -0.51299762 0.31541983 -1.23426222 0.15004873 -0.05615311 [97] -0.90315157 1.02672102 -1.45576127 1.19784885 > colMin(tmp) [1] 0.51896428 0.39035851 1.02428843 0.98295693 1.21981599 -0.01949250 [7] -1.53717543 0.15634453 0.06358518 -1.77164451 -0.74460918 0.96709833 [13] 0.74358407 -1.03095117 1.35674389 0.90408797 0.53716604 0.91305957 [19] 0.06594654 0.28189414 0.16634447 0.07255518 0.33264454 1.95317047 [25] 0.09731804 1.23917423 1.06247678 -1.69420682 1.43083346 -0.46043551 [31] -0.43641675 1.50752919 -1.69169295 -1.57609966 -1.05786098 0.07342189 [37] -0.69233750 -2.77750636 0.83154201 1.89891807 -0.38605253 1.50159368 [43] -0.66034141 1.57124232 0.24420551 -0.78107246 -0.23783076 -0.33970261 [49] -0.65321697 -0.02483335 1.10632602 -1.06468706 -0.75990867 -0.47653489 [55] 0.29146034 -0.29979533 -1.00137709 1.90322098 0.41795019 0.98608278 [61] -0.74076631 -1.06209358 -0.36705699 -0.75112370 -0.14863840 -0.16094742 [67] 0.45826868 1.08204745 -0.19447266 0.95398803 1.04295096 0.86333871 [73] 1.46495009 0.76771275 0.71871992 1.17756404 1.07303022 1.02167239 [79] 0.50293457 0.24920757 -0.94918807 0.65356237 -0.02427790 0.46865232 [85] 0.21016021 1.28201882 -0.02722187 -0.63574315 -1.00287129 -0.19702155 [91] 0.61457873 -0.51299762 0.31541983 -1.23426222 0.15004873 -0.05615311 [97] -0.90315157 1.02672102 -1.45576127 1.19784885 > colMedians(tmp) [1] 0.51896428 0.39035851 1.02428843 0.98295693 1.21981599 -0.01949250 [7] -1.53717543 0.15634453 0.06358518 -1.77164451 -0.74460918 0.96709833 [13] 0.74358407 -1.03095117 1.35674389 0.90408797 0.53716604 0.91305957 [19] 0.06594654 0.28189414 0.16634447 0.07255518 0.33264454 1.95317047 [25] 0.09731804 1.23917423 1.06247678 -1.69420682 1.43083346 -0.46043551 [31] -0.43641675 1.50752919 -1.69169295 -1.57609966 -1.05786098 0.07342189 [37] -0.69233750 -2.77750636 0.83154201 1.89891807 -0.38605253 1.50159368 [43] -0.66034141 1.57124232 0.24420551 -0.78107246 -0.23783076 -0.33970261 [49] -0.65321697 -0.02483335 1.10632602 -1.06468706 -0.75990867 -0.47653489 [55] 0.29146034 -0.29979533 -1.00137709 1.90322098 0.41795019 0.98608278 [61] -0.74076631 -1.06209358 -0.36705699 -0.75112370 -0.14863840 -0.16094742 [67] 0.45826868 1.08204745 -0.19447266 0.95398803 1.04295096 0.86333871 [73] 1.46495009 0.76771275 0.71871992 1.17756404 1.07303022 1.02167239 [79] 0.50293457 0.24920757 -0.94918807 0.65356237 -0.02427790 0.46865232 [85] 0.21016021 1.28201882 -0.02722187 -0.63574315 -1.00287129 -0.19702155 [91] 0.61457873 -0.51299762 0.31541983 -1.23426222 0.15004873 -0.05615311 [97] -0.90315157 1.02672102 -1.45576127 1.19784885 > colRanges(tmp) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [1,] 0.5189643 0.3903585 1.024288 0.9829569 1.219816 -0.0194925 -1.537175 [2,] 0.5189643 0.3903585 1.024288 0.9829569 1.219816 -0.0194925 -1.537175 [,8] [,9] [,10] [,11] [,12] [,13] [,14] [1,] 0.1563445 0.06358518 -1.771645 -0.7446092 0.9670983 0.7435841 -1.030951 [2,] 0.1563445 0.06358518 -1.771645 -0.7446092 0.9670983 0.7435841 -1.030951 [,15] [,16] [,17] [,18] [,19] [,20] [,21] [1,] 1.356744 0.904088 0.537166 0.9130596 0.06594654 0.2818941 0.1663445 [2,] 1.356744 0.904088 0.537166 0.9130596 0.06594654 0.2818941 0.1663445 [,22] [,23] [,24] [,25] [,26] [,27] [,28] [1,] 0.07255518 0.3326445 1.95317 0.09731804 1.239174 1.062477 -1.694207 [2,] 0.07255518 0.3326445 1.95317 0.09731804 1.239174 1.062477 -1.694207 [,29] [,30] [,31] [,32] [,33] [,34] [,35] [1,] 1.430833 -0.4604355 -0.4364167 1.507529 -1.691693 -1.5761 -1.057861 [2,] 1.430833 -0.4604355 -0.4364167 1.507529 -1.691693 -1.5761 -1.057861 [,36] [,37] [,38] [,39] [,40] [,41] [,42] [1,] 0.07342189 -0.6923375 -2.777506 0.831542 1.898918 -0.3860525 1.501594 [2,] 0.07342189 -0.6923375 -2.777506 0.831542 1.898918 -0.3860525 1.501594 [,43] [,44] [,45] [,46] [,47] [,48] [,49] [1,] -0.6603414 1.571242 0.2442055 -0.7810725 -0.2378308 -0.3397026 -0.653217 [2,] -0.6603414 1.571242 0.2442055 -0.7810725 -0.2378308 -0.3397026 -0.653217 [,50] [,51] [,52] [,53] [,54] [,55] [,56] [1,] -0.02483335 1.106326 -1.064687 -0.7599087 -0.4765349 0.2914603 -0.2997953 [2,] -0.02483335 1.106326 -1.064687 -0.7599087 -0.4765349 0.2914603 -0.2997953 [,57] [,58] [,59] [,60] [,61] [,62] [,63] [1,] -1.001377 1.903221 0.4179502 0.9860828 -0.7407663 -1.062094 -0.367057 [2,] -1.001377 1.903221 0.4179502 0.9860828 -0.7407663 -1.062094 -0.367057 [,64] [,65] [,66] [,67] [,68] [,69] [,70] [1,] -0.7511237 -0.1486384 -0.1609474 0.4582687 1.082047 -0.1944727 0.953988 [2,] -0.7511237 -0.1486384 -0.1609474 0.4582687 1.082047 -0.1944727 0.953988 [,71] [,72] [,73] [,74] [,75] [,76] [,77] [,78] [1,] 1.042951 0.8633387 1.46495 0.7677127 0.7187199 1.177564 1.07303 1.021672 [2,] 1.042951 0.8633387 1.46495 0.7677127 0.7187199 1.177564 1.07303 1.021672 [,79] [,80] [,81] [,82] [,83] [,84] [,85] [1,] 0.5029346 0.2492076 -0.9491881 0.6535624 -0.0242779 0.4686523 0.2101602 [2,] 0.5029346 0.2492076 -0.9491881 0.6535624 -0.0242779 0.4686523 0.2101602 [,86] [,87] [,88] [,89] [,90] [,91] [,92] [1,] 1.282019 -0.02722187 -0.6357431 -1.002871 -0.1970216 0.6145787 -0.5129976 [2,] 1.282019 -0.02722187 -0.6357431 -1.002871 -0.1970216 0.6145787 -0.5129976 [,93] [,94] [,95] [,96] [,97] [,98] [,99] [1,] 0.3154198 -1.234262 0.1500487 -0.05615311 -0.9031516 1.026721 -1.455761 [2,] 0.3154198 -1.234262 0.1500487 -0.05615311 -0.9031516 1.026721 -1.455761 [,100] [1,] 1.197849 [2,] 1.197849 > > > Max(tmp2) [1] 2.045537 > Min(tmp2) [1] -2.587331 > mean(tmp2) [1] -0.002098384 > Sum(tmp2) [1] -0.2098384 > Var(tmp2) [1] 0.9080044 > > rowMeans(tmp2) [1] -1.198498692 -0.128133395 -1.212193648 -0.382166512 0.129951283 [6] -0.119888289 -0.459957492 -0.079818560 1.547119632 -0.279927516 [11] -0.246090556 0.701518659 0.351323465 0.686111893 1.368337339 [16] 0.828721532 -0.375800461 0.309448903 -0.977278457 1.545451608 [21] -0.745618726 0.828317336 1.246715504 -0.555568628 1.550327234 [26] 0.507794774 -0.151846210 -0.949495718 -0.646837288 -0.243955181 [31] 0.808211111 -1.010753502 -0.076647490 -0.474547972 -0.608937895 [36] -0.799393524 -0.315605183 -0.167065782 -0.269578475 -0.494158938 [41] 1.314292194 -1.913035379 -0.155057632 -2.014716595 -2.587331444 [46] -1.393558914 0.284224979 -0.417955357 -1.071245042 2.005339262 [51] -1.077226872 0.106850865 -0.393672154 -1.599932214 1.035851668 [56] -0.080045632 0.650709870 -0.532851090 -0.841329136 -0.483727858 [61] 0.316486588 -1.242665030 0.046957932 1.791634677 -1.161908966 [66] 1.638966746 -0.180634602 0.314193474 0.733360337 1.403441831 [71] 1.933637105 -0.176624148 0.171891783 0.400484046 0.919193359 [76] -0.302095273 -1.296431710 -0.828014422 -0.506821959 0.082661044 [81] -0.135460459 2.009161592 -0.006724618 -0.811168573 -0.573617907 [86] 0.353396275 -0.836576307 1.498101374 1.629282963 -0.395394529 [91] -0.455723055 0.579239822 -0.149389946 0.208822709 -0.130749776 [96] -0.322332556 2.045536692 -0.308526076 0.205842274 1.053559165 > rowSums(tmp2) [1] -1.198498692 -0.128133395 -1.212193648 -0.382166512 0.129951283 [6] -0.119888289 -0.459957492 -0.079818560 1.547119632 -0.279927516 [11] -0.246090556 0.701518659 0.351323465 0.686111893 1.368337339 [16] 0.828721532 -0.375800461 0.309448903 -0.977278457 1.545451608 [21] -0.745618726 0.828317336 1.246715504 -0.555568628 1.550327234 [26] 0.507794774 -0.151846210 -0.949495718 -0.646837288 -0.243955181 [31] 0.808211111 -1.010753502 -0.076647490 -0.474547972 -0.608937895 [36] -0.799393524 -0.315605183 -0.167065782 -0.269578475 -0.494158938 [41] 1.314292194 -1.913035379 -0.155057632 -2.014716595 -2.587331444 [46] -1.393558914 0.284224979 -0.417955357 -1.071245042 2.005339262 [51] -1.077226872 0.106850865 -0.393672154 -1.599932214 1.035851668 [56] -0.080045632 0.650709870 -0.532851090 -0.841329136 -0.483727858 [61] 0.316486588 -1.242665030 0.046957932 1.791634677 -1.161908966 [66] 1.638966746 -0.180634602 0.314193474 0.733360337 1.403441831 [71] 1.933637105 -0.176624148 0.171891783 0.400484046 0.919193359 [76] -0.302095273 -1.296431710 -0.828014422 -0.506821959 0.082661044 [81] -0.135460459 2.009161592 -0.006724618 -0.811168573 -0.573617907 [86] 0.353396275 -0.836576307 1.498101374 1.629282963 -0.395394529 [91] -0.455723055 0.579239822 -0.149389946 0.208822709 -0.130749776 [96] -0.322332556 2.045536692 -0.308526076 0.205842274 1.053559165 > 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] -1.198498692 -0.128133395 -1.212193648 -0.382166512 0.129951283 [6] -0.119888289 -0.459957492 -0.079818560 1.547119632 -0.279927516 [11] -0.246090556 0.701518659 0.351323465 0.686111893 1.368337339 [16] 0.828721532 -0.375800461 0.309448903 -0.977278457 1.545451608 [21] -0.745618726 0.828317336 1.246715504 -0.555568628 1.550327234 [26] 0.507794774 -0.151846210 -0.949495718 -0.646837288 -0.243955181 [31] 0.808211111 -1.010753502 -0.076647490 -0.474547972 -0.608937895 [36] -0.799393524 -0.315605183 -0.167065782 -0.269578475 -0.494158938 [41] 1.314292194 -1.913035379 -0.155057632 -2.014716595 -2.587331444 [46] -1.393558914 0.284224979 -0.417955357 -1.071245042 2.005339262 [51] -1.077226872 0.106850865 -0.393672154 -1.599932214 1.035851668 [56] -0.080045632 0.650709870 -0.532851090 -0.841329136 -0.483727858 [61] 0.316486588 -1.242665030 0.046957932 1.791634677 -1.161908966 [66] 1.638966746 -0.180634602 0.314193474 0.733360337 1.403441831 [71] 1.933637105 -0.176624148 0.171891783 0.400484046 0.919193359 [76] -0.302095273 -1.296431710 -0.828014422 -0.506821959 0.082661044 [81] -0.135460459 2.009161592 -0.006724618 -0.811168573 -0.573617907 [86] 0.353396275 -0.836576307 1.498101374 1.629282963 -0.395394529 [91] -0.455723055 0.579239822 -0.149389946 0.208822709 -0.130749776 [96] -0.322332556 2.045536692 -0.308526076 0.205842274 1.053559165 > rowMin(tmp2) [1] -1.198498692 -0.128133395 -1.212193648 -0.382166512 0.129951283 [6] -0.119888289 -0.459957492 -0.079818560 1.547119632 -0.279927516 [11] -0.246090556 0.701518659 0.351323465 0.686111893 1.368337339 [16] 0.828721532 -0.375800461 0.309448903 -0.977278457 1.545451608 [21] -0.745618726 0.828317336 1.246715504 -0.555568628 1.550327234 [26] 0.507794774 -0.151846210 -0.949495718 -0.646837288 -0.243955181 [31] 0.808211111 -1.010753502 -0.076647490 -0.474547972 -0.608937895 [36] -0.799393524 -0.315605183 -0.167065782 -0.269578475 -0.494158938 [41] 1.314292194 -1.913035379 -0.155057632 -2.014716595 -2.587331444 [46] -1.393558914 0.284224979 -0.417955357 -1.071245042 2.005339262 [51] -1.077226872 0.106850865 -0.393672154 -1.599932214 1.035851668 [56] -0.080045632 0.650709870 -0.532851090 -0.841329136 -0.483727858 [61] 0.316486588 -1.242665030 0.046957932 1.791634677 -1.161908966 [66] 1.638966746 -0.180634602 0.314193474 0.733360337 1.403441831 [71] 1.933637105 -0.176624148 0.171891783 0.400484046 0.919193359 [76] -0.302095273 -1.296431710 -0.828014422 -0.506821959 0.082661044 [81] -0.135460459 2.009161592 -0.006724618 -0.811168573 -0.573617907 [86] 0.353396275 -0.836576307 1.498101374 1.629282963 -0.395394529 [91] -0.455723055 0.579239822 -0.149389946 0.208822709 -0.130749776 [96] -0.322332556 2.045536692 -0.308526076 0.205842274 1.053559165 > > colMeans(tmp2) [1] -0.002098384 > colSums(tmp2) [1] -0.2098384 > colVars(tmp2) [1] 0.9080044 > colSd(tmp2) [1] 0.9528927 > colMax(tmp2) [1] 2.045537 > colMin(tmp2) [1] -2.587331 > colMedians(tmp2) [1] -0.1506181 > colRanges(tmp2) [,1] [1,] -2.587331 [2,] 2.045537 > > 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] -1.4216929 -6.7048730 -2.8546863 -1.6920565 0.5196224 -4.0349690 [7] -1.0183047 -2.2167364 4.5448657 -1.1762396 > colApply(tmp,quantile)[,1] [,1] [1,] -1.6514227 [2,] -0.7120891 [3,] -0.0650135 [4,] 0.4785591 [5,] 1.3631186 > > rowApply(tmp,sum) [1] 3.1433385 0.5091482 1.7641945 -3.1488840 0.9282629 -2.6127611 [7] -7.3498681 -1.8353138 -3.0284010 -4.4247864 > rowApply(tmp,rank)[1:10,] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 8 5 5 4 3 1 10 10 3 3 [2,] 3 8 3 3 1 3 5 3 8 4 [3,] 6 3 9 6 5 7 3 8 2 1 [4,] 4 6 2 9 8 2 7 1 5 10 [5,] 9 10 6 1 10 9 9 7 1 7 [6,] 2 4 4 2 6 5 1 4 10 5 [7,] 5 7 1 5 4 10 2 9 7 8 [8,] 1 2 8 7 9 4 6 2 9 2 [9,] 10 9 10 10 7 8 4 5 6 6 [10,] 7 1 7 8 2 6 8 6 4 9 > > tmp <- createBufferedMatrix(5,20) > > tmp[1:5,1:20] <- rnorm(100) > colApply(tmp,sum) [1] 0.67524342 1.76680073 0.68142410 1.70867088 0.52517887 -2.63243696 [7] -0.17419240 0.09333224 -2.41521211 -1.88046543 1.23252934 1.79644507 [13] 1.63196774 -1.01757329 -2.05410311 1.17721654 -5.87761367 0.43378710 [19] -1.62221901 -2.38691982 > colApply(tmp,quantile)[,1] [,1] [1,] -0.58286488 [2,] -0.19792021 [3,] -0.02758779 [4,] 0.06137490 [5,] 1.42224139 > > rowApply(tmp,sum) [1] -0.3374608 -0.9247585 -10.4717927 1.9297848 1.4660874 > rowApply(tmp,rank)[1:5,] [,1] [,2] [,3] [,4] [,5] [1,] 8 20 13 9 12 [2,] 9 10 14 20 17 [3,] 17 11 11 13 3 [4,] 20 13 6 12 11 [5,] 19 18 8 1 4 > > > as.matrix(tmp) [,1] [,2] [,3] [,4] [,5] [,6] [1,] -0.58286488 -0.23375366 1.19184209 2.19083198 2.1509503 0.1877347 [2,] 1.42224139 0.03436946 0.08136072 0.37907895 1.1341696 -1.2815357 [3,] -0.19792021 -0.09529449 -0.53935899 -0.95107717 -0.7273047 -2.3789627 [4,] -0.02758779 1.49060399 0.28891017 0.16030903 -1.7255882 0.9609049 [5,] 0.06137490 0.57087544 -0.34132989 -0.07047192 -0.3070481 -0.1205781 [,7] [,8] [,9] [,10] [,11] [,12] [1,] -1.4021361 0.4892929 0.09149770 1.8016116 -1.19847828 0.2856735 [2,] 1.1165439 0.4963795 -0.99809663 -1.1995739 0.15314194 -0.2967518 [3,] 1.1848166 -0.8262131 -1.29438368 -2.2901612 -0.02420784 0.9913182 [4,] -1.3222699 -0.2908342 -0.09306222 -0.4142598 0.10041202 0.9552825 [5,] 0.2488531 0.2247071 -0.12116729 0.2219179 2.20166150 -0.1390774 [,13] [,14] [,15] [,16] [,17] [,18] [1,] 0.6668973 -1.2745923 -1.6217635 0.91327451 -2.6334547 -1.10925391 [2,] 0.4600301 -1.6165739 1.1327110 -0.30765710 -0.6751202 1.27527901 [3,] -0.2021660 0.4517993 0.3280774 -0.59607324 -1.3383660 0.51275953 [4,] -0.2958800 0.9550105 -1.1200544 1.26003316 0.6089142 -0.05542325 [5,] 1.0030863 0.4667831 -0.7730737 -0.09236079 -1.8395870 -0.18957428 [,19] [,20] [1,] 0.3510366 -0.6018067 [2,] -1.2003252 -1.0344294 [3,] -0.6904828 -1.7885917 [4,] 0.1186729 0.3756911 [5,] -0.2011205 0.6622170 > > > is.BufferedMatrix(tmp) [1] TRUE > > as.BufferedMatrix(as.matrix(tmp)) BufferedMatrix object Matrix size: 5 20 Buffer size: 1 1 Directory: /Users/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: /Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 650 bytes. Disk usage : 200 bytes. > subBufferedMatrix(tmp,,5:8) BufferedMatrix object Matrix size: 5 4 Buffer size: 1 1 Directory: /Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 560 bytes. Disk usage : 160 bytes. > subBufferedMatrix(tmp,1:3,) BufferedMatrix object Matrix size: 3 20 Buffer size: 1 1 Directory: /Users/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 -0.4898211 -0.9334199 0.7668728 -0.7647493 -0.6077149 -0.3858124 -1.022161 col8 col9 col10 col11 col12 col13 col14 row1 1.206621 1.901784 0.2827919 -0.9666164 0.3023208 -0.3407686 0.9903775 col15 col16 col17 col18 col19 col20 row1 -0.1562928 -0.5031999 -1.422378 0.08527366 -0.0393021 0.1898256 > tmp[,"col10"] col10 row1 0.28279191 row2 0.68495612 row3 0.05840786 row4 -0.80348342 row5 -1.69007395 > tmp[c("row1","row5"),] col1 col2 col3 col4 col5 col6 row1 -0.4898211 -0.9334199 0.7668728 -0.7647493 -0.6077149 -0.3858124 row5 -0.1199860 0.6635241 -1.1564120 -1.2561090 -0.1518657 -0.6178475 col7 col8 col9 col10 col11 col12 col13 row1 -1.022161 1.206621 1.901784 0.2827919 -0.9666164 0.3023208 -0.3407686 row5 -1.924346 -1.270206 -2.188250 -1.6900739 -1.0590844 0.4446938 -0.5879917 col14 col15 col16 col17 col18 col19 row1 0.9903775 -0.1562928 -0.5031999 -1.4223775 0.08527366 -0.0393021 row5 -1.4142550 -0.3482787 0.9880981 0.3291674 0.25500007 -1.1052671 col20 row1 0.1898256 row5 -2.0282016 > tmp[,c("col6","col20")] col6 col20 row1 -0.3858124 0.1898256 row2 1.6293936 0.7696292 row3 0.7345343 0.8626758 row4 0.6457178 1.1142574 row5 -0.6178475 -2.0282016 > tmp[c("row1","row5"),c("col6","col20")] col6 col20 row1 -0.3858124 0.1898256 row5 -0.6178475 -2.0282016 > > > > > 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 50.19706 49.25834 48.60942 51.8077 48.76303 105.7818 48.87521 51.17152 col9 col10 col11 col12 col13 col14 col15 col16 row1 50.17224 49.56682 50.7267 50.92534 49.80026 49.9324 50.11197 48.78007 col17 col18 col19 col20 row1 49.42998 53.1429 50.12038 105.0346 > tmp[,"col10"] col10 row1 49.56682 row2 30.96276 row3 30.61961 row4 29.29922 row5 52.02018 > tmp[c("row1","row5"),] col1 col2 col3 col4 col5 col6 col7 col8 row1 50.19706 49.25834 48.60942 51.80770 48.76303 105.7818 48.87521 51.17152 row5 49.09352 50.36723 49.65264 50.26219 50.50764 103.9434 49.60144 49.39715 col9 col10 col11 col12 col13 col14 col15 col16 row1 50.17224 49.56682 50.72670 50.92534 49.80026 49.93240 50.11197 48.78007 row5 50.82149 52.02018 49.38654 50.44457 49.74534 50.40614 48.23768 50.03084 col17 col18 col19 col20 row1 49.42998 53.14290 50.12038 105.0346 row5 48.39887 51.41905 49.17438 105.1751 > tmp[,c("col6","col20")] col6 col20 row1 105.78183 105.03463 row2 76.91982 75.43510 row3 75.81751 73.22273 row4 75.33845 73.41968 row5 103.94343 105.17509 > tmp[c("row1","row5"),c("col6","col20")] col6 col20 row1 105.7818 105.0346 row5 103.9434 105.1751 > > > subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2] col6 col20 row1 105.7818 105.0346 row5 103.9434 105.1751 > > > > > > tmp <- createBufferedMatrix(5,20) > tmp[1:5,1:20] <- rnorm(100) > colnames(tmp) <- colnames(tmp,do.NULL=FALSE) > > tmp[,"col13"] col13 [1,] -0.6324869 [2,] 0.2915381 [3,] -0.6295189 [4,] 0.1031953 [5,] -1.3182676 > tmp[,c("col17","col7")] col17 col7 [1,] -0.5248789 0.8560957 [2,] 1.3143129 -1.8310592 [3,] -0.6356923 -0.4928847 [4,] -0.4920192 -0.0418367 [5,] 0.5900039 -1.6140537 > > subBufferedMatrix(tmp,,c("col6","col20"))[,1:2] col6 col20 [1,] 0.2862556 -0.63150649 [2,] -1.5719790 1.03650540 [3,] 1.3182668 -1.96276700 [4,] 0.2756864 0.04320893 [5,] 1.4708747 -0.27087492 > subBufferedMatrix(tmp,1,c("col6"))[,1] col1 [1,] 0.2862556 > subBufferedMatrix(tmp,1:2,c("col6"))[,1] col6 [1,] 0.2862556 [2,] -1.5719790 > > > > 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] row3 1.5023607 -0.9975333 -0.8194817 0.16256963 -0.259844 -0.8749656 row1 -0.1887539 0.1189371 0.9599051 -0.07952056 -1.657001 0.6230001 [,7] [,8] [,9] [,10] [,11] [,12] [,13] row3 0.2462092 0.3482236 0.9331237 0.3439456 1.644769 -0.7470784 -0.8846016 row1 -0.7296085 2.2959129 -0.8377199 -2.4868972 1.033478 1.0613103 1.0960723 [,14] [,15] [,16] [,17] [,18] [,19] [,20] row3 0.4213018 0.3725719 0.9412265 -0.4805140 0.5161631 -1.7154804 0.7621447 row1 -0.8061479 1.7787776 1.1725693 0.8662498 0.6656628 -0.8811302 -0.5399899 > subBufferedMatrix(tmp,c("row2"),1:10)[,1:10] [,1] [,2] [,3] [,4] [,5] [,6] [,7] row2 -0.7993033 1.588299 0.2766986 0.1540345 0.6210038 0.8018639 1.246123 [,8] [,9] [,10] row2 -0.5564572 -0.1108364 -0.2895429 > subBufferedMatrix(tmp,c("row5"),1:20)[,1:20] [,1] [,2] [,3] [,4] [,5] [,6] [,7] row5 -0.4727777 -0.8149673 0.04859722 -0.684344 0.5846122 -1.148441 -2.193083 [,8] [,9] [,10] [,11] [,12] [,13] [,14] row5 -0.7125778 0.3781063 1.316808 -0.1797972 -0.09183357 0.07130808 1.493469 [,15] [,16] [,17] [,18] [,19] [,20] row5 -1.794429 -1.251427 -0.8756898 1.204281 0.2321822 1.518951 > > > 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: 0x600000790120> > is.ReadOnlyMode(tmp) [1] TRUE > > filenames(tmp) [1] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMdb752c1f991" [2] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMdb75ce7a001" [3] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMdb753ab9a845" [4] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMdb7572d66821" [5] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMdb755a4e896d" [6] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMdb755a20816c" [7] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMdb75c1107ae" [8] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMdb75320f36b2" [9] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMdb754cff9cb" [10] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMdb75721880e4" [11] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMdb7526b63341" [12] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMdb753df0442" [13] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMdb7526908b0a" [14] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMdb755b98514d" [15] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMdb756d01c535" > > > ### 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: 0x6000007fc180> > MoveStorageDirectory(tmp,getwd(),full.path=TRUE) <pointer: 0x6000007fc180> Warning message: In dir.create(new.directory) : '/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests' already exists > > > RowMode(tmp) <pointer: 0x6000007fc180> > rowMedians(tmp) [1] 0.0094883467 -0.3010110932 0.4152842232 -0.0314187955 0.4346338358 [6] -0.1907183844 -0.2796023408 0.0362574110 -0.1727095884 -0.6101736393 [11] 0.1041349064 -0.0865118613 0.4488923478 0.2326786647 -0.3345328461 [16] -0.4168608252 -0.3895963977 0.1057590658 -0.0148053399 0.0777372909 [21] -0.0484217882 0.5577741438 0.1247999934 0.2203815531 0.2779064568 [26] -0.2557188513 -0.2456423305 -0.3580185939 -0.4745155268 0.5192425824 [31] 0.5959517527 -0.5036593686 0.2511094801 0.1130826726 0.3496372693 [36] -0.2260703660 0.5413339838 0.1692530655 -0.4612550796 0.3900383629 [41] -0.0215600815 -0.7779160574 0.3606704633 -0.2080320042 -0.4917128198 [46] 0.3746649985 0.3946739033 0.1805742354 -0.4466524306 0.3203148176 [51] -0.2841762880 -0.1011546055 -0.0025353634 0.6337679284 -0.0652529025 [56] 0.1627268229 -0.1432110627 -0.0224609699 -0.0237578396 -0.1140326779 [61] -0.5649825007 -0.0378154619 -0.3072829080 0.0038935976 -0.0100556775 [66] 0.2345401286 0.4247952248 0.1810606947 -0.5924524445 0.0455286123 [71] 0.2843896641 -0.2173914984 -0.0740090728 0.3718698051 0.0874905387 [76] 0.0860815503 -0.0574328061 0.4968754741 0.1840056686 -0.0848513112 [81] -0.0237030048 -0.0017716449 -0.0846487694 -0.2213604893 0.0430989566 [86] -0.1636911452 -0.3013022737 -0.1015649108 0.1537812953 0.3706773893 [91] 0.1453152086 0.1253674038 0.3414264596 -0.4249534234 -0.0680389181 [96] -0.2735464633 0.2385589016 0.1727090617 0.4276214939 -0.1697390630 [101] -0.1360204521 0.2378399168 -0.4097669407 -0.2242658575 0.2070457489 [106] -0.2357905964 0.0227190564 0.1498776535 0.1791381327 -0.2174855539 [111] 0.2190690920 0.0617066303 0.0800844100 -0.4091674465 -0.1263274658 [116] 0.1191414954 -0.5971653289 -0.3394114087 -0.2649981375 -0.6211977385 [121] 0.3292574963 0.3027991290 -0.5348832851 -0.2185697826 -0.1145034856 [126] 0.2852225062 0.4232803034 -0.2410159447 0.1905970175 0.0785189573 [131] -0.5549669995 -0.0174871267 -0.0386787541 0.3230658539 0.1886827365 [136] 0.0786315951 0.1693724649 0.0827397654 0.1617373398 -0.2955011504 [141] 0.1869140101 0.1897725852 0.6083976193 -0.5636591049 0.4614624028 [146] 0.2579601290 -0.1771749279 0.0025784818 0.1461638067 -0.7215722174 [151] 0.3358481756 0.2868644670 0.2760195166 -0.1017204910 -0.1173551290 [156] 0.2017737688 0.1613099731 0.0605429837 -0.2178224851 -0.2160102486 [161] -1.0064428358 -0.6258087909 -0.3570398340 -0.6362010304 0.4049661938 [166] -0.3002976277 -0.7048030583 -0.1155103738 0.1282158102 0.1178913247 [171] -0.6009782952 0.2143570075 -0.3113015148 -0.5927049341 0.1178004332 [176] 0.4351494268 0.2203228141 0.5210608580 0.1623697213 0.0431406043 [181] 0.2405176718 0.0235735418 0.0900549361 -0.0900031225 0.1474849504 [186] -0.2973710711 0.5225087064 -0.6718525005 0.4970436029 -0.0638125485 [191] -0.3728815883 -0.3386295455 -0.2139191741 -0.0910867957 0.2570209984 [196] -0.0536108883 0.0447190536 -0.2155668228 0.4206048361 -0.1032530977 [201] -0.6388584313 0.2782679531 0.0644546391 -0.1718204571 0.2071171421 [206] 0.7943925950 -0.1064918380 -0.5565589442 -0.1000139701 0.3714941115 [211] -0.0008317804 -0.3060559991 -0.3258232141 0.3217833451 -0.3870506775 [216] 0.3612597675 0.0516789411 -0.1583246823 0.3811475446 0.0516637757 [221] -0.1052611196 -0.4739206720 0.3047369155 0.1684757633 0.0249040408 [226] 0.1265822814 0.0393354225 -0.1092384163 -0.0648828025 -0.4874866175 > > proc.time() user system elapsed 2.449 12.755 15.740
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-apple-darwin20 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: 0x600002c24240> > .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: 0x600002c24240> > .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: 0x600002c24240> > .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: 0x600002c24240> > 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: 0x600002c10000> > .Call("R_bm_AddColumn",P) <pointer: 0x600002c10000> > .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: 0x600002c10000> > .Call("R_bm_AddColumn",P) <pointer: 0x600002c10000> > .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: 0x600002c10000> > 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: 0x600002c10180> > .Call("R_bm_AddColumn",P) <pointer: 0x600002c10180> > .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: 0x600002c10180> > > .Call("R_bm_ResizeBuffer",P,5,5) <pointer: 0x600002c10180> > .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: 0x600002c10180> > > .Call("R_bm_RowMode",P) <pointer: 0x600002c10180> > .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: 0x600002c10180> > > .Call("R_bm_ColMode",P) <pointer: 0x600002c10180> > .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: 0x600002c10180> > 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: 0x600002c1c000> > .Call("R_bm_SetPrefix",P,"BufferedMatrixFile") <pointer: 0x600002c1c000> > .Call("R_bm_AddColumn",P) <pointer: 0x600002c1c000> > .Call("R_bm_AddColumn",P) <pointer: 0x600002c1c000> > dir(pattern="BufferedMatrixFile") [1] "BufferedMatrixFilee0a13709df21" "BufferedMatrixFilee0a1dfe5eec" > rm(P) > dir(pattern="BufferedMatrixFile") [1] "BufferedMatrixFilee0a13709df21" "BufferedMatrixFilee0a1dfe5eec" > > > P <- .Call("R_bm_Create",prefix,directory,1,1) > .Call("R_bm_setRows",P,10) [1] TRUE > .Call("R_bm_AddColumn",P) <pointer: 0x600002c18060> > .Call("R_bm_AddColumn",P) <pointer: 0x600002c18060> > .Call("R_bm_ReadOnlyModeToggle",P) <pointer: 0x600002c18060> > .Call("R_bm_isReadOnlyMode",P) [1] TRUE > .Call("R_bm_ReadOnlyModeToggle",P) <pointer: 0x600002c18060> > .Call("R_bm_isReadOnlyMode",P) [1] FALSE > .Call("R_bm_isRowMode",P) [1] FALSE > .Call("R_bm_RowMode",P) <pointer: 0x600002c18060> > .Call("R_bm_isRowMode",P) [1] TRUE > .Call("R_bm_ColMode",P) <pointer: 0x600002c18060> > .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: 0x600002c18120> > .Call("R_bm_AddColumn",P) <pointer: 0x600002c18120> > > .Call("R_bm_getSize",P) [1] 10 2 > .Call("R_bm_getBufferSize",P) [1] 1 1 > .Call("R_bm_ResizeBuffer",P,5,5) <pointer: 0x600002c18120> > > .Call("R_bm_getBufferSize",P) [1] 5 5 > .Call("R_bm_ResizeBuffer",P,-1,5) <pointer: 0x600002c18120> > 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: 0x600002c34120> > .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: 0x600002c34120> > rm(P) > > proc.time() user system elapsed 0.327 0.133 0.451
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-apple-darwin20 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 0.312 0.086 0.383