Back to Multiple platform build/check report for BioC 3.18: simplified long |
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This page was generated on 2024-03-27 11:37:26 -0400 (Wed, 27 Mar 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.3.3 (2024-02-29) -- "Angel Food Cake" | 4667 |
palomino4 | Windows Server 2022 Datacenter | x64 | 4.3.3 (2024-02-29 ucrt) -- "Angel Food Cake" | 4403 |
merida1 | macOS 12.7.1 Monterey | x86_64 | 4.3.3 (2024-02-29) -- "Angel Food Cake" | 4426 |
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 246/2266 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
BufferedMatrix 1.66.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | |||||||||
palomino4 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | |||||||||
merida1 | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | |||||||||
kjohnson1 | macOS 13.6.1 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: 1.66.0 |
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_1.66.0.tar.gz |
StartedAt: 2024-03-26 00:01:21 -0400 (Tue, 26 Mar 2024) |
EndedAt: 2024-03-26 00:02:29 -0400 (Tue, 26 Mar 2024) |
EllapsedTime: 68.2 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_1.66.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck’ * using R version 4.3.3 (2024-02-29) * using platform: x86_64-apple-darwin20 (64-bit) * 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 ‘1.66.0’ * 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-3.18-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 R 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 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 in ‘inst/doc’ ... 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-3.18-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/4.3-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/4.3-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 4.3.3 (2024-02-29) -- "Angel Food Cake" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-apple-darwin20 (64-bit) 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 0.576 0.203 0.742
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.3.3 (2024-02-29) -- "Angel Food Cake" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-apple-darwin20 (64-bit) 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-3.18-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 460384 24.6 992698 53.1 NA 645368 34.5 Vcells 848931 6.5 8388608 64.0 65536 2019930 15.5 > > > > > ## > ## checking reads > ## > > tmp2 <- createBufferedMatrix(10,20) > > test.sample <- rnorm(10*20) > > tmp2[1:10,1:20] <- test.sample > > test.matrix <- matrix(test.sample,10,20) > > ## testing reads > for (rep in 1:nreps){ + which.row <- sample(1:10,1) + which.col <- sample(1:20,1) + if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){ + cat("incorrect agreement") + break; + } + } > > > for (rep in 1:nreps){ + which.row <- sample(1:10,1) + if (!all(tmp2[which.row,] == test.matrix[which.row,])){ + cat("incorrect agreement") + break; + } + } > > > for (rep in 1:nreps){ + which.col <- sample(1:20,1) + if (!all(tmp2[,which.col] == test.matrix[,which.col])){ + cat("incorrect agreement") + break; + } + } > > > > for (rep in 1:nreps){ + which.col <- sample(1:10,5,replace=TRUE) + if (!all(tmp2[,which.col] == test.matrix[,which.col])){ + cat("incorrect agreement") + break; + } + } > > > date() [1] "Tue Mar 26 00:01:52 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] "Tue Mar 26 00:01:53 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: 0x6000016e4060> > > > > for (rep in 1:nreps){ + which.row <- sample(1:10,1) + which.col <- sample(1:20,1) + if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){ + cat("incorrect agreement") + break; + } + } > > > for (rep in 1:nreps){ + which.row <- sample(1:10,1) + if (!all(tmp2[which.row,] == test.matrix[which.row,])){ + cat("incorrect agreement") + break; + } + } > > > for (rep in 1:nreps){ + which.col <- sample(1:20,1) + if (!all(tmp2[,which.col] == test.matrix[,which.col])){ + cat("incorrect agreement") + break; + } + } > > > > for (rep in 1:nreps){ + which.col <- sample(1:20,5,replace=TRUE) + if (!all(tmp2[,which.col] == test.matrix[,which.col])){ + cat("incorrect agreement") + break; + } + } > > > > for (rep in 1:nreps){ + which.row <- sample(1:10,5,replace=TRUE) + if (!all(tmp2[which.row,] == test.matrix[which.row,])){ + cat("incorrect agreement") + break; + } + } > > > date() [1] "Tue Mar 26 00:01:59 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] "Tue Mar 26 00:02:01 2024" > > ColMode(tmp2) <pointer: 0x6000016e4060> > > > > ### Now testing assignments > > for (rep in 1:nreps){ + which.row <- sample(1:10,1) + + new.data <- rnorm(20) + tmp2[which.row,] <- new.data + test.matrix[which.row,] <- new.data + if (rep > 1){ + if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){ + cat("incorrect agreement") + break; + } + } + prev.row <- which.row + + } > > > > > > for (rep in 1:nreps){ + which.col <- sample(1:20,1) + new.data <- rnorm(10) + tmp2[,which.col] <- new.data + test.matrix[,which.col]<- new.data + + if (rep > 1){ + if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){ + cat("incorrect agreement") + break; + } + } + prev.col <- which.col + } > > > > > > for (rep in 1:nreps){ + which.col <- sample(1:20,5,replace=TRUE) + new.data <- matrix(rnorm(50),5,10) + tmp2[,which.col] <- new.data + test.matrix[,which.col]<- new.data + + if (rep > 1){ + if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){ + cat("incorrect agreement") + break; + } + } + prev.col <- which.col + } > > > > for (rep in 1:nreps){ + which.row <- sample(1:10,5,replace=TRUE) + new.data <- matrix(rnorm(50),5,10) + tmp2[which.row,] <- new.data + test.matrix[which.row,]<- new.data + + if (rep > 1){ + if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){ + cat("incorrect agreement") + break; + } + } + prev.row <- which.row + } > > > > > > for (rep in 1:nreps){ + which.row <- sample(1:10,5,replace=TRUE) + which.col <- sample(1:20,5,replace=TRUE) + new.data <- matrix(rnorm(25),5,5) + tmp2[which.row,which.col] <- new.data + test.matrix[which.row,which.col]<- new.data + + if (rep > 1){ + if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){ + cat("incorrect agreement") + break; + } + } + prev.row <- which.row + prev.col <- which.col + } > > > > > ### > ### > ### testing some more functions > ### > > > > ## duplication function > tmp5 <- duplicate(tmp2) > > # making sure really did copy everything. > tmp5[1,1] <- tmp5[1,1] +100.00 > > if (tmp5[1,1] == tmp2[1,1]){ + stop("Problem with duplication") + } > > > > > ### testing elementwise applying of functions > > tmp5[1:4,1:4] [,1] [,2] [,3] [,4] [1,] 100.0174450 -0.5431656 0.0406617 1.0945323 [2,] -0.4137801 1.4444943 0.4162762 -0.4039193 [3,] 1.1643481 0.6752384 -0.1552309 1.3254312 [4,] -0.9264180 -0.6963723 -0.4487477 -0.8277042 > ewApply(tmp5,abs) BufferedMatrix object Matrix size: 10 20 Buffer size: 1 1 Directory: /Users/biocbuild/bbs-3.18-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,] 100.0174450 0.5431656 0.0406617 1.0945323 [2,] 0.4137801 1.4444943 0.4162762 0.4039193 [3,] 1.1643481 0.6752384 0.1552309 1.3254312 [4,] 0.9264180 0.6963723 0.4487477 0.8277042 > ewApply(tmp5,sqrt) BufferedMatrix object Matrix size: 10 20 Buffer size: 1 1 Directory: /Users/biocbuild/bbs-3.18-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,] 10.0008722 0.7369977 0.2016475 1.0461990 [2,] 0.6432574 1.2018712 0.6451947 0.6355465 [3,] 1.0790496 0.8217289 0.3939936 1.1512737 [4,] 0.9625061 0.8344893 0.6698863 0.9097825 > > 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-3.18-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,] 225.02617 32.91314 27.05714 36.55652 [2,] 31.84635 38.46321 31.86822 31.75938 [3,] 36.95484 33.89253 29.09517 37.83817 [4,] 35.55148 34.04126 32.14761 34.92553 > > > > ## testing functions that elementwise transform the matrix > sqrt(tmp5) <pointer: 0x6000016dc000> > exp(tmp5) <pointer: 0x6000016dc000> > log(tmp5,2) <pointer: 0x6000016dc000> > pow(tmp5,2) > > > > > > ## testing functions that apply to entire matrix > Max(tmp5) [1] 468.3625 > Min(tmp5) [1] 53.73938 > mean(tmp5) [1] 72.52415 > Sum(tmp5) [1] 14504.83 > Var(tmp5) [1] 854.7663 > > > ## testing functions applied to rows or columns > > rowMeans(tmp5) [1] 91.05208 71.12366 69.88143 70.55629 71.97074 69.63803 72.08858 69.69292 [9] 66.68017 72.55765 > rowSums(tmp5) [1] 1821.042 1422.473 1397.629 1411.126 1439.415 1392.761 1441.772 1393.858 [9] 1333.603 1451.153 > rowVars(tmp5) [1] 7957.16759 60.26324 57.65744 36.25322 46.78498 87.90281 [7] 61.69199 42.38903 57.77083 116.14851 > rowSd(tmp5) [1] 89.202957 7.762940 7.593250 6.021065 6.839954 9.375650 7.854425 [8] 6.510686 7.600713 10.777222 > rowMax(tmp5) [1] 468.36248 83.61704 79.97881 87.29525 82.22996 85.05383 86.28524 [8] 82.30783 80.61361 92.70935 > rowMin(tmp5) [1] 54.31929 57.76450 57.06232 62.26828 57.35537 54.99151 55.75788 61.97966 [9] 55.05964 53.73938 > > colMeans(tmp5) [1] 112.98271 73.28591 66.30122 69.83501 66.17339 70.90315 65.06329 [8] 68.61149 74.83686 72.34925 71.18332 66.52455 69.43289 74.92968 [15] 72.20884 69.20186 72.12593 72.93241 71.93359 69.66773 > colSums(tmp5) [1] 1129.8271 732.8591 663.0122 698.3501 661.7339 709.0315 650.6329 [8] 686.1149 748.3686 723.4925 711.8332 665.2455 694.3289 749.2968 [15] 722.0884 692.0186 721.2593 729.3241 719.3359 696.6773 > colVars(tmp5) [1] 15669.62925 20.88948 26.97941 38.74387 72.97355 39.28042 [7] 56.53988 78.03332 75.64308 100.58072 58.85072 51.94516 [13] 80.54724 48.70484 75.32426 88.05434 37.94983 88.67273 [19] 42.24739 63.96604 > colSd(tmp5) [1] 125.178390 4.570501 5.194171 6.224457 8.542456 6.267409 [7] 7.519301 8.833647 8.697303 10.028994 7.671423 7.207299 [13] 8.974812 6.978885 8.678955 9.383727 6.160344 9.416620 [19] 6.499799 7.997878 > colMax(tmp5) [1] 468.36248 82.15349 73.77844 78.75519 78.20405 80.98730 80.52019 [8] 80.23642 87.29525 92.70935 82.23233 77.57462 82.30783 85.00175 [15] 83.61704 86.24176 81.77472 89.88932 84.10177 79.60418 > colMin(tmp5) [1] 55.95729 68.50439 56.31588 56.91612 54.99151 63.38688 55.45678 53.73938 [9] 58.51548 57.35537 57.98956 55.05964 56.95408 61.13560 56.31440 57.76450 [17] 63.44922 61.18560 61.97966 54.31929 > > > ### 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] 91.05208 71.12366 NA 70.55629 71.97074 69.63803 72.08858 69.69292 [9] 66.68017 72.55765 > rowSums(tmp5) [1] 1821.042 1422.473 NA 1411.126 1439.415 1392.761 1441.772 1393.858 [9] 1333.603 1451.153 > rowVars(tmp5) [1] 7957.16759 60.26324 56.65205 36.25322 46.78498 87.90281 [7] 61.69199 42.38903 57.77083 116.14851 > rowSd(tmp5) [1] 89.202957 7.762940 7.526755 6.021065 6.839954 9.375650 7.854425 [8] 6.510686 7.600713 10.777222 > rowMax(tmp5) [1] 468.36248 83.61704 NA 87.29525 82.22996 85.05383 86.28524 [8] 82.30783 80.61361 92.70935 > rowMin(tmp5) [1] 54.31929 57.76450 NA 62.26828 57.35537 54.99151 55.75788 61.97966 [9] 55.05964 53.73938 > > colMeans(tmp5) [1] 112.98271 73.28591 66.30122 69.83501 66.17339 70.90315 65.06329 [8] 68.61149 74.83686 72.34925 71.18332 66.52455 69.43289 74.92968 [15] NA 69.20186 72.12593 72.93241 71.93359 69.66773 > colSums(tmp5) [1] 1129.8271 732.8591 663.0122 698.3501 661.7339 709.0315 650.6329 [8] 686.1149 748.3686 723.4925 711.8332 665.2455 694.3289 749.2968 [15] NA 692.0186 721.2593 729.3241 719.3359 696.6773 > colVars(tmp5) [1] 15669.62925 20.88948 26.97941 38.74387 72.97355 39.28042 [7] 56.53988 78.03332 75.64308 100.58072 58.85072 51.94516 [13] 80.54724 48.70484 NA 88.05434 37.94983 88.67273 [19] 42.24739 63.96604 > colSd(tmp5) [1] 125.178390 4.570501 5.194171 6.224457 8.542456 6.267409 [7] 7.519301 8.833647 8.697303 10.028994 7.671423 7.207299 [13] 8.974812 6.978885 NA 9.383727 6.160344 9.416620 [19] 6.499799 7.997878 > colMax(tmp5) [1] 468.36248 82.15349 73.77844 78.75519 78.20405 80.98730 80.52019 [8] 80.23642 87.29525 92.70935 82.23233 77.57462 82.30783 85.00175 [15] NA 86.24176 81.77472 89.88932 84.10177 79.60418 > colMin(tmp5) [1] 55.95729 68.50439 56.31588 56.91612 54.99151 63.38688 55.45678 53.73938 [9] 58.51548 57.35537 57.98956 55.05964 56.95408 61.13560 NA 57.76450 [17] 63.44922 61.18560 61.97966 54.31929 > > Max(tmp5,na.rm=TRUE) [1] 468.3625 > Min(tmp5,na.rm=TRUE) [1] 53.73938 > mean(tmp5,na.rm=TRUE) [1] 72.4948 > Sum(tmp5,na.rm=TRUE) [1] 14426.47 > Var(tmp5,na.rm=TRUE) [1] 858.9102 > > rowMeans(tmp5,na.rm=TRUE) [1] 91.05208 71.12366 69.43493 70.55629 71.97074 69.63803 72.08858 69.69292 [9] 66.68017 72.55765 > rowSums(tmp5,na.rm=TRUE) [1] 1821.042 1422.473 1319.264 1411.126 1439.415 1392.761 1441.772 1393.858 [9] 1333.603 1451.153 > rowVars(tmp5,na.rm=TRUE) [1] 7957.16759 60.26324 56.65205 36.25322 46.78498 87.90281 [7] 61.69199 42.38903 57.77083 116.14851 > rowSd(tmp5,na.rm=TRUE) [1] 89.202957 7.762940 7.526755 6.021065 6.839954 9.375650 7.854425 [8] 6.510686 7.600713 10.777222 > rowMax(tmp5,na.rm=TRUE) [1] 468.36248 83.61704 79.97881 87.29525 82.22996 85.05383 86.28524 [8] 82.30783 80.61361 92.70935 > rowMin(tmp5,na.rm=TRUE) [1] 54.31929 57.76450 57.06232 62.26828 57.35537 54.99151 55.75788 61.97966 [9] 55.05964 53.73938 > > colMeans(tmp5,na.rm=TRUE) [1] 112.98271 73.28591 66.30122 69.83501 66.17339 70.90315 65.06329 [8] 68.61149 74.83686 72.34925 71.18332 66.52455 69.43289 74.92968 [15] 71.52485 69.20186 72.12593 72.93241 71.93359 69.66773 > colSums(tmp5,na.rm=TRUE) [1] 1129.8271 732.8591 663.0122 698.3501 661.7339 709.0315 650.6329 [8] 686.1149 748.3686 723.4925 711.8332 665.2455 694.3289 749.2968 [15] 643.7237 692.0186 721.2593 729.3241 719.3359 696.6773 > colVars(tmp5,na.rm=TRUE) [1] 15669.62925 20.88948 26.97941 38.74387 72.97355 39.28042 [7] 56.53988 78.03332 75.64308 100.58072 58.85072 51.94516 [13] 80.54724 48.70484 79.47656 88.05434 37.94983 88.67273 [19] 42.24739 63.96604 > colSd(tmp5,na.rm=TRUE) [1] 125.178390 4.570501 5.194171 6.224457 8.542456 6.267409 [7] 7.519301 8.833647 8.697303 10.028994 7.671423 7.207299 [13] 8.974812 6.978885 8.914963 9.383727 6.160344 9.416620 [19] 6.499799 7.997878 > colMax(tmp5,na.rm=TRUE) [1] 468.36248 82.15349 73.77844 78.75519 78.20405 80.98730 80.52019 [8] 80.23642 87.29525 92.70935 82.23233 77.57462 82.30783 85.00175 [15] 83.61704 86.24176 81.77472 89.88932 84.10177 79.60418 > colMin(tmp5,na.rm=TRUE) [1] 55.95729 68.50439 56.31588 56.91612 54.99151 63.38688 55.45678 53.73938 [9] 58.51548 57.35537 57.98956 55.05964 56.95408 61.13560 56.31440 57.76450 [17] 63.44922 61.18560 61.97966 54.31929 > > # now set an entire row to NA > > tmp5[which.row,] <- NA > rowMeans(tmp5,na.rm=TRUE) [1] 91.05208 71.12366 NaN 70.55629 71.97074 69.63803 72.08858 69.69292 [9] 66.68017 72.55765 > rowSums(tmp5,na.rm=TRUE) [1] 1821.042 1422.473 0.000 1411.126 1439.415 1392.761 1441.772 1393.858 [9] 1333.603 1451.153 > rowVars(tmp5,na.rm=TRUE) [1] 7957.16759 60.26324 NA 36.25322 46.78498 87.90281 [7] 61.69199 42.38903 57.77083 116.14851 > rowSd(tmp5,na.rm=TRUE) [1] 89.202957 7.762940 NA 6.021065 6.839954 9.375650 7.854425 [8] 6.510686 7.600713 10.777222 > rowMax(tmp5,na.rm=TRUE) [1] 468.36248 83.61704 NA 87.29525 82.22996 85.05383 86.28524 [8] 82.30783 80.61361 92.70935 > rowMin(tmp5,na.rm=TRUE) [1] 54.31929 57.76450 NA 62.26828 57.35537 54.99151 55.75788 61.97966 [9] 55.05964 53.73938 > > > # now set an entire col to NA > > > tmp5[,which.col] <- NA > colMeans(tmp5,na.rm=TRUE) [1] 116.99005 73.59069 66.93938 68.84388 66.78858 71.43079 65.95229 [8] 68.42442 75.35050 72.57409 70.24418 67.01279 70.39081 74.36866 [15] NaN 70.05482 72.73662 73.05433 71.27985 68.80423 > colSums(tmp5,na.rm=TRUE) [1] 1052.9105 662.3162 602.4544 619.5949 601.0972 642.8771 593.5706 [8] 615.8197 678.1545 653.1668 632.1976 603.1151 633.5173 669.3179 [15] 0.0000 630.4934 654.6296 657.4890 641.5186 619.2380 > colVars(tmp5,na.rm=TRUE) [1] 17447.67183 22.45562 25.77029 32.53552 77.83762 41.05844 [7] 54.71631 87.39378 82.13036 112.58460 56.28486 55.75665 [13] 80.29251 51.25213 NA 90.87626 38.49797 99.58957 [19] 42.72032 63.57333 > colSd(tmp5,na.rm=TRUE) [1] 132.089636 4.738736 5.076445 5.703992 8.822563 6.407686 [7] 7.397048 9.348464 9.062580 10.610589 7.502324 7.467038 [13] 8.960609 7.159060 NA 9.532904 6.204673 9.979458 [19] 6.536078 7.973289 > colMax(tmp5,na.rm=TRUE) [1] 468.36248 82.15349 73.77844 76.08761 78.20405 80.98730 80.52019 [8] 80.23642 87.29525 92.70935 82.23233 77.57462 82.30783 85.00175 [15] -Inf 86.24176 81.77472 89.88932 84.10177 79.60418 > colMin(tmp5,na.rm=TRUE) [1] 55.95729 68.50439 56.31588 56.91612 54.99151 63.38688 55.45678 53.73938 [9] 58.51548 57.35537 57.98956 55.05964 56.95408 61.13560 Inf 57.76450 [17] 63.44922 61.18560 61.97966 54.31929 > > > > > 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] 145.1777 265.6719 307.1407 147.2226 196.1074 301.4243 131.7739 248.9258 [9] 254.9522 191.5930 > apply(copymatrix,1,var,na.rm=TRUE) [1] 145.1777 265.6719 307.1407 147.2226 196.1074 301.4243 131.7739 248.9258 [9] 254.9522 191.5930 > > > > 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] 0.000000e+00 2.842171e-14 -5.684342e-14 0.000000e+00 2.842171e-14 [6] -1.136868e-13 -1.136868e-13 -5.684342e-14 -2.273737e-13 -8.526513e-14 [11] 0.000000e+00 1.136868e-13 5.684342e-14 -1.705303e-13 -1.989520e-13 [16] 1.136868e-13 -1.136868e-13 2.273737e-13 0.000000e+00 -1.421085e-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) + } 5 8 8 4 2 11 3 3 10 19 8 15 2 10 6 1 8 13 10 6 5 18 7 5 5 15 10 18 10 8 8 2 1 18 2 18 2 5 7 17 There were 50 or more warnings (use warnings() to see the first 50) > > > ### now test 1 by n and n by 1 matrix > > > err.tol <- 1e-12 > > rm(tmp5) > > dataset1 <- rnorm(100) > dataset2 <- rnorm(100) > > tmp <- createBufferedMatrix(1,100) > tmp[1,] <- dataset1 > > tmp2 <- createBufferedMatrix(100,1) > tmp2[,1] <- dataset2 > > > > > > Max(tmp) [1] 3.096452 > Min(tmp) [1] -2.102984 > mean(tmp) [1] 0.01939373 > Sum(tmp) [1] 1.939373 > Var(tmp) [1] 0.821262 > > rowMeans(tmp) [1] 0.01939373 > rowSums(tmp) [1] 1.939373 > rowVars(tmp) [1] 0.821262 > rowSd(tmp) [1] 0.9062351 > rowMax(tmp) [1] 3.096452 > rowMin(tmp) [1] -2.102984 > > colMeans(tmp) [1] -0.85421973 0.36522054 -1.52492747 -0.50229119 0.06133893 -0.87444161 [7] -0.08418636 1.28042547 -0.38915450 -0.32213216 0.69378742 0.40156351 [13] -0.59410992 1.45231252 -0.06700397 0.80327094 0.27320670 0.69780549 [19] 0.30817888 -0.08475854 1.24235363 -0.82624344 0.46284594 -0.16119732 [25] -1.30524238 -0.58831893 0.84063367 1.50797682 0.47589888 -0.71493641 [31] -1.22700800 -0.31055006 0.32703876 0.79588313 -1.13684480 -1.25344599 [37] -1.46613641 0.10454536 -2.10298401 1.35143019 -0.38506747 -0.48799343 [43] 0.19983286 0.42926673 -1.47582202 0.52797302 -0.31508124 -1.31517165 [49] 0.81585355 0.38049323 0.39521122 -1.07862727 0.15701753 -0.05116317 [55] -1.28150099 -0.23271904 0.10574782 -0.24511438 -0.79777264 -0.15979081 [61] -0.05390469 -0.58053050 1.08387946 -0.16433127 0.08730571 -0.65998950 [67] -0.38038846 -1.83346007 0.69072308 0.72520756 0.36145104 3.09645178 [73] -1.73027498 -0.29465292 0.72876635 0.23261552 -0.31723349 1.30304174 [79] 1.13602889 -0.17002453 2.16161809 -0.23201721 -0.02477048 0.62124110 [85] 1.20612448 -0.31296971 -0.40282430 -0.19220113 1.85224940 0.13011594 [91] -0.74402777 -0.70103237 0.70742701 -1.05521131 1.12988783 0.88316072 [97] -0.08426407 0.55715201 1.05970922 -0.12183071 > colSums(tmp) [1] -0.85421973 0.36522054 -1.52492747 -0.50229119 0.06133893 -0.87444161 [7] -0.08418636 1.28042547 -0.38915450 -0.32213216 0.69378742 0.40156351 [13] -0.59410992 1.45231252 -0.06700397 0.80327094 0.27320670 0.69780549 [19] 0.30817888 -0.08475854 1.24235363 -0.82624344 0.46284594 -0.16119732 [25] -1.30524238 -0.58831893 0.84063367 1.50797682 0.47589888 -0.71493641 [31] -1.22700800 -0.31055006 0.32703876 0.79588313 -1.13684480 -1.25344599 [37] -1.46613641 0.10454536 -2.10298401 1.35143019 -0.38506747 -0.48799343 [43] 0.19983286 0.42926673 -1.47582202 0.52797302 -0.31508124 -1.31517165 [49] 0.81585355 0.38049323 0.39521122 -1.07862727 0.15701753 -0.05116317 [55] -1.28150099 -0.23271904 0.10574782 -0.24511438 -0.79777264 -0.15979081 [61] -0.05390469 -0.58053050 1.08387946 -0.16433127 0.08730571 -0.65998950 [67] -0.38038846 -1.83346007 0.69072308 0.72520756 0.36145104 3.09645178 [73] -1.73027498 -0.29465292 0.72876635 0.23261552 -0.31723349 1.30304174 [79] 1.13602889 -0.17002453 2.16161809 -0.23201721 -0.02477048 0.62124110 [85] 1.20612448 -0.31296971 -0.40282430 -0.19220113 1.85224940 0.13011594 [91] -0.74402777 -0.70103237 0.70742701 -1.05521131 1.12988783 0.88316072 [97] -0.08426407 0.55715201 1.05970922 -0.12183071 > 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] -0.85421973 0.36522054 -1.52492747 -0.50229119 0.06133893 -0.87444161 [7] -0.08418636 1.28042547 -0.38915450 -0.32213216 0.69378742 0.40156351 [13] -0.59410992 1.45231252 -0.06700397 0.80327094 0.27320670 0.69780549 [19] 0.30817888 -0.08475854 1.24235363 -0.82624344 0.46284594 -0.16119732 [25] -1.30524238 -0.58831893 0.84063367 1.50797682 0.47589888 -0.71493641 [31] -1.22700800 -0.31055006 0.32703876 0.79588313 -1.13684480 -1.25344599 [37] -1.46613641 0.10454536 -2.10298401 1.35143019 -0.38506747 -0.48799343 [43] 0.19983286 0.42926673 -1.47582202 0.52797302 -0.31508124 -1.31517165 [49] 0.81585355 0.38049323 0.39521122 -1.07862727 0.15701753 -0.05116317 [55] -1.28150099 -0.23271904 0.10574782 -0.24511438 -0.79777264 -0.15979081 [61] -0.05390469 -0.58053050 1.08387946 -0.16433127 0.08730571 -0.65998950 [67] -0.38038846 -1.83346007 0.69072308 0.72520756 0.36145104 3.09645178 [73] -1.73027498 -0.29465292 0.72876635 0.23261552 -0.31723349 1.30304174 [79] 1.13602889 -0.17002453 2.16161809 -0.23201721 -0.02477048 0.62124110 [85] 1.20612448 -0.31296971 -0.40282430 -0.19220113 1.85224940 0.13011594 [91] -0.74402777 -0.70103237 0.70742701 -1.05521131 1.12988783 0.88316072 [97] -0.08426407 0.55715201 1.05970922 -0.12183071 > colMin(tmp) [1] -0.85421973 0.36522054 -1.52492747 -0.50229119 0.06133893 -0.87444161 [7] -0.08418636 1.28042547 -0.38915450 -0.32213216 0.69378742 0.40156351 [13] -0.59410992 1.45231252 -0.06700397 0.80327094 0.27320670 0.69780549 [19] 0.30817888 -0.08475854 1.24235363 -0.82624344 0.46284594 -0.16119732 [25] -1.30524238 -0.58831893 0.84063367 1.50797682 0.47589888 -0.71493641 [31] -1.22700800 -0.31055006 0.32703876 0.79588313 -1.13684480 -1.25344599 [37] -1.46613641 0.10454536 -2.10298401 1.35143019 -0.38506747 -0.48799343 [43] 0.19983286 0.42926673 -1.47582202 0.52797302 -0.31508124 -1.31517165 [49] 0.81585355 0.38049323 0.39521122 -1.07862727 0.15701753 -0.05116317 [55] -1.28150099 -0.23271904 0.10574782 -0.24511438 -0.79777264 -0.15979081 [61] -0.05390469 -0.58053050 1.08387946 -0.16433127 0.08730571 -0.65998950 [67] -0.38038846 -1.83346007 0.69072308 0.72520756 0.36145104 3.09645178 [73] -1.73027498 -0.29465292 0.72876635 0.23261552 -0.31723349 1.30304174 [79] 1.13602889 -0.17002453 2.16161809 -0.23201721 -0.02477048 0.62124110 [85] 1.20612448 -0.31296971 -0.40282430 -0.19220113 1.85224940 0.13011594 [91] -0.74402777 -0.70103237 0.70742701 -1.05521131 1.12988783 0.88316072 [97] -0.08426407 0.55715201 1.05970922 -0.12183071 > colMedians(tmp) [1] -0.85421973 0.36522054 -1.52492747 -0.50229119 0.06133893 -0.87444161 [7] -0.08418636 1.28042547 -0.38915450 -0.32213216 0.69378742 0.40156351 [13] -0.59410992 1.45231252 -0.06700397 0.80327094 0.27320670 0.69780549 [19] 0.30817888 -0.08475854 1.24235363 -0.82624344 0.46284594 -0.16119732 [25] -1.30524238 -0.58831893 0.84063367 1.50797682 0.47589888 -0.71493641 [31] -1.22700800 -0.31055006 0.32703876 0.79588313 -1.13684480 -1.25344599 [37] -1.46613641 0.10454536 -2.10298401 1.35143019 -0.38506747 -0.48799343 [43] 0.19983286 0.42926673 -1.47582202 0.52797302 -0.31508124 -1.31517165 [49] 0.81585355 0.38049323 0.39521122 -1.07862727 0.15701753 -0.05116317 [55] -1.28150099 -0.23271904 0.10574782 -0.24511438 -0.79777264 -0.15979081 [61] -0.05390469 -0.58053050 1.08387946 -0.16433127 0.08730571 -0.65998950 [67] -0.38038846 -1.83346007 0.69072308 0.72520756 0.36145104 3.09645178 [73] -1.73027498 -0.29465292 0.72876635 0.23261552 -0.31723349 1.30304174 [79] 1.13602889 -0.17002453 2.16161809 -0.23201721 -0.02477048 0.62124110 [85] 1.20612448 -0.31296971 -0.40282430 -0.19220113 1.85224940 0.13011594 [91] -0.74402777 -0.70103237 0.70742701 -1.05521131 1.12988783 0.88316072 [97] -0.08426407 0.55715201 1.05970922 -0.12183071 > colRanges(tmp) [,1] [,2] [,3] [,4] [,5] [,6] [1,] -0.8542197 0.3652205 -1.524927 -0.5022912 0.06133893 -0.8744416 [2,] -0.8542197 0.3652205 -1.524927 -0.5022912 0.06133893 -0.8744416 [,7] [,8] [,9] [,10] [,11] [,12] [,13] [1,] -0.08418636 1.280425 -0.3891545 -0.3221322 0.6937874 0.4015635 -0.5941099 [2,] -0.08418636 1.280425 -0.3891545 -0.3221322 0.6937874 0.4015635 -0.5941099 [,14] [,15] [,16] [,17] [,18] [,19] [,20] [1,] 1.452313 -0.06700397 0.8032709 0.2732067 0.6978055 0.3081789 -0.08475854 [2,] 1.452313 -0.06700397 0.8032709 0.2732067 0.6978055 0.3081789 -0.08475854 [,21] [,22] [,23] [,24] [,25] [,26] [,27] [1,] 1.242354 -0.8262434 0.4628459 -0.1611973 -1.305242 -0.5883189 0.8406337 [2,] 1.242354 -0.8262434 0.4628459 -0.1611973 -1.305242 -0.5883189 0.8406337 [,28] [,29] [,30] [,31] [,32] [,33] [,34] [1,] 1.507977 0.4758989 -0.7149364 -1.227008 -0.3105501 0.3270388 0.7958831 [2,] 1.507977 0.4758989 -0.7149364 -1.227008 -0.3105501 0.3270388 0.7958831 [,35] [,36] [,37] [,38] [,39] [,40] [,41] [1,] -1.136845 -1.253446 -1.466136 0.1045454 -2.102984 1.35143 -0.3850675 [2,] -1.136845 -1.253446 -1.466136 0.1045454 -2.102984 1.35143 -0.3850675 [,42] [,43] [,44] [,45] [,46] [,47] [,48] [1,] -0.4879934 0.1998329 0.4292667 -1.475822 0.527973 -0.3150812 -1.315172 [2,] -0.4879934 0.1998329 0.4292667 -1.475822 0.527973 -0.3150812 -1.315172 [,49] [,50] [,51] [,52] [,53] [,54] [,55] [1,] 0.8158536 0.3804932 0.3952112 -1.078627 0.1570175 -0.05116317 -1.281501 [2,] 0.8158536 0.3804932 0.3952112 -1.078627 0.1570175 -0.05116317 -1.281501 [,56] [,57] [,58] [,59] [,60] [,61] [1,] -0.232719 0.1057478 -0.2451144 -0.7977726 -0.1597908 -0.05390469 [2,] -0.232719 0.1057478 -0.2451144 -0.7977726 -0.1597908 -0.05390469 [,62] [,63] [,64] [,65] [,66] [,67] [,68] [1,] -0.5805305 1.083879 -0.1643313 0.08730571 -0.6599895 -0.3803885 -1.83346 [2,] -0.5805305 1.083879 -0.1643313 0.08730571 -0.6599895 -0.3803885 -1.83346 [,69] [,70] [,71] [,72] [,73] [,74] [,75] [1,] 0.6907231 0.7252076 0.361451 3.096452 -1.730275 -0.2946529 0.7287663 [2,] 0.6907231 0.7252076 0.361451 3.096452 -1.730275 -0.2946529 0.7287663 [,76] [,77] [,78] [,79] [,80] [,81] [,82] [1,] 0.2326155 -0.3172335 1.303042 1.136029 -0.1700245 2.161618 -0.2320172 [2,] 0.2326155 -0.3172335 1.303042 1.136029 -0.1700245 2.161618 -0.2320172 [,83] [,84] [,85] [,86] [,87] [,88] [,89] [1,] -0.02477048 0.6212411 1.206124 -0.3129697 -0.4028243 -0.1922011 1.852249 [2,] -0.02477048 0.6212411 1.206124 -0.3129697 -0.4028243 -0.1922011 1.852249 [,90] [,91] [,92] [,93] [,94] [,95] [,96] [1,] 0.1301159 -0.7440278 -0.7010324 0.707427 -1.055211 1.129888 0.8831607 [2,] 0.1301159 -0.7440278 -0.7010324 0.707427 -1.055211 1.129888 0.8831607 [,97] [,98] [,99] [,100] [1,] -0.08426407 0.557152 1.059709 -0.1218307 [2,] -0.08426407 0.557152 1.059709 -0.1218307 > > > Max(tmp2) [1] 3.373632 > Min(tmp2) [1] -2.543692 > mean(tmp2) [1] -0.02427928 > Sum(tmp2) [1] -2.427928 > Var(tmp2) [1] 1.140093 > > rowMeans(tmp2) [1] 0.90361693 -0.94031865 1.28934719 -0.65552550 0.59607614 -0.58522074 [7] -2.00673118 1.10803962 -0.03525143 0.77204494 -0.73672396 2.02016208 [13] 0.24444284 -0.70287234 1.41395347 0.02826654 0.23084137 -0.86784446 [19] 0.51226678 0.21900663 0.24145210 1.33752656 0.33277251 -0.41143641 [25] -0.94100462 0.43758445 -0.58104862 -0.34206579 -1.61093478 -1.07156700 [31] 0.85967564 -2.54369168 -0.15165089 2.14743478 1.11102867 1.04277834 [37] -1.45899640 -1.38986115 -0.24655295 -1.17291747 -0.13930663 0.42399602 [43] -0.13043419 2.17484679 1.25946545 -0.38831434 0.57992199 0.73875764 [49] 0.42104980 -0.76630187 -0.66628586 0.11298271 -1.41056728 -0.34106464 [55] -0.08160545 -1.53337985 -2.00427662 -0.60926620 -0.53813004 -1.51108836 [61] 1.30241797 -0.98451318 1.70143080 -1.75664200 -0.86930297 0.12305004 [67] -0.92256067 -0.11568154 3.37363232 0.69467237 0.91488799 -0.25626547 [73] 0.37242114 -0.86950029 -0.04654069 0.43821952 -0.17477877 -1.23120613 [79] 0.74887399 -0.93829424 0.52834455 -0.68710467 0.10855239 0.72743170 [85] 0.29298161 -0.34580392 -0.20919224 1.14073300 1.06342262 0.52348403 [91] 1.26539023 -0.61370563 -1.33971571 0.33973546 -0.19346977 0.29496723 [97] -0.02902975 -1.34555515 2.47753408 -1.91834898 > rowSums(tmp2) [1] 0.90361693 -0.94031865 1.28934719 -0.65552550 0.59607614 -0.58522074 [7] -2.00673118 1.10803962 -0.03525143 0.77204494 -0.73672396 2.02016208 [13] 0.24444284 -0.70287234 1.41395347 0.02826654 0.23084137 -0.86784446 [19] 0.51226678 0.21900663 0.24145210 1.33752656 0.33277251 -0.41143641 [25] -0.94100462 0.43758445 -0.58104862 -0.34206579 -1.61093478 -1.07156700 [31] 0.85967564 -2.54369168 -0.15165089 2.14743478 1.11102867 1.04277834 [37] -1.45899640 -1.38986115 -0.24655295 -1.17291747 -0.13930663 0.42399602 [43] -0.13043419 2.17484679 1.25946545 -0.38831434 0.57992199 0.73875764 [49] 0.42104980 -0.76630187 -0.66628586 0.11298271 -1.41056728 -0.34106464 [55] -0.08160545 -1.53337985 -2.00427662 -0.60926620 -0.53813004 -1.51108836 [61] 1.30241797 -0.98451318 1.70143080 -1.75664200 -0.86930297 0.12305004 [67] -0.92256067 -0.11568154 3.37363232 0.69467237 0.91488799 -0.25626547 [73] 0.37242114 -0.86950029 -0.04654069 0.43821952 -0.17477877 -1.23120613 [79] 0.74887399 -0.93829424 0.52834455 -0.68710467 0.10855239 0.72743170 [85] 0.29298161 -0.34580392 -0.20919224 1.14073300 1.06342262 0.52348403 [91] 1.26539023 -0.61370563 -1.33971571 0.33973546 -0.19346977 0.29496723 [97] -0.02902975 -1.34555515 2.47753408 -1.91834898 > 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] 0.90361693 -0.94031865 1.28934719 -0.65552550 0.59607614 -0.58522074 [7] -2.00673118 1.10803962 -0.03525143 0.77204494 -0.73672396 2.02016208 [13] 0.24444284 -0.70287234 1.41395347 0.02826654 0.23084137 -0.86784446 [19] 0.51226678 0.21900663 0.24145210 1.33752656 0.33277251 -0.41143641 [25] -0.94100462 0.43758445 -0.58104862 -0.34206579 -1.61093478 -1.07156700 [31] 0.85967564 -2.54369168 -0.15165089 2.14743478 1.11102867 1.04277834 [37] -1.45899640 -1.38986115 -0.24655295 -1.17291747 -0.13930663 0.42399602 [43] -0.13043419 2.17484679 1.25946545 -0.38831434 0.57992199 0.73875764 [49] 0.42104980 -0.76630187 -0.66628586 0.11298271 -1.41056728 -0.34106464 [55] -0.08160545 -1.53337985 -2.00427662 -0.60926620 -0.53813004 -1.51108836 [61] 1.30241797 -0.98451318 1.70143080 -1.75664200 -0.86930297 0.12305004 [67] -0.92256067 -0.11568154 3.37363232 0.69467237 0.91488799 -0.25626547 [73] 0.37242114 -0.86950029 -0.04654069 0.43821952 -0.17477877 -1.23120613 [79] 0.74887399 -0.93829424 0.52834455 -0.68710467 0.10855239 0.72743170 [85] 0.29298161 -0.34580392 -0.20919224 1.14073300 1.06342262 0.52348403 [91] 1.26539023 -0.61370563 -1.33971571 0.33973546 -0.19346977 0.29496723 [97] -0.02902975 -1.34555515 2.47753408 -1.91834898 > rowMin(tmp2) [1] 0.90361693 -0.94031865 1.28934719 -0.65552550 0.59607614 -0.58522074 [7] -2.00673118 1.10803962 -0.03525143 0.77204494 -0.73672396 2.02016208 [13] 0.24444284 -0.70287234 1.41395347 0.02826654 0.23084137 -0.86784446 [19] 0.51226678 0.21900663 0.24145210 1.33752656 0.33277251 -0.41143641 [25] -0.94100462 0.43758445 -0.58104862 -0.34206579 -1.61093478 -1.07156700 [31] 0.85967564 -2.54369168 -0.15165089 2.14743478 1.11102867 1.04277834 [37] -1.45899640 -1.38986115 -0.24655295 -1.17291747 -0.13930663 0.42399602 [43] -0.13043419 2.17484679 1.25946545 -0.38831434 0.57992199 0.73875764 [49] 0.42104980 -0.76630187 -0.66628586 0.11298271 -1.41056728 -0.34106464 [55] -0.08160545 -1.53337985 -2.00427662 -0.60926620 -0.53813004 -1.51108836 [61] 1.30241797 -0.98451318 1.70143080 -1.75664200 -0.86930297 0.12305004 [67] -0.92256067 -0.11568154 3.37363232 0.69467237 0.91488799 -0.25626547 [73] 0.37242114 -0.86950029 -0.04654069 0.43821952 -0.17477877 -1.23120613 [79] 0.74887399 -0.93829424 0.52834455 -0.68710467 0.10855239 0.72743170 [85] 0.29298161 -0.34580392 -0.20919224 1.14073300 1.06342262 0.52348403 [91] 1.26539023 -0.61370563 -1.33971571 0.33973546 -0.19346977 0.29496723 [97] -0.02902975 -1.34555515 2.47753408 -1.91834898 > > colMeans(tmp2) [1] -0.02427928 > colSums(tmp2) [1] -2.427928 > colVars(tmp2) [1] 1.140093 > colSd(tmp2) [1] 1.067751 > colMax(tmp2) [1] 3.373632 > colMin(tmp2) [1] -2.543692 > colMedians(tmp2) [1] -0.06407307 > colRanges(tmp2) [,1] [1,] -2.543692 [2,] 3.373632 > > 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] 6.1777632 0.7213149 1.0620458 -1.0342003 4.2436063 1.4132281 [7] 1.1303146 4.7241747 -1.2672746 -1.4103628 > colApply(tmp,quantile)[,1] [,1] [1,] -1.0104294 [2,] 0.1078455 [3,] 0.7991580 [4,] 1.2116947 [5,] 1.7547156 > > rowApply(tmp,sum) [1] 1.374504343 1.745521368 0.130773935 -0.104802704 -1.899479163 [6] 3.591345778 2.855841751 5.317370445 2.745398093 0.004136172 > rowApply(tmp,rank)[1:10,] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 3 6 7 1 10 10 9 3 10 8 [2,] 9 8 8 3 1 8 4 9 2 3 [3,] 5 9 3 7 6 4 3 4 4 7 [4,] 2 7 5 8 8 3 2 5 5 5 [5,] 4 10 10 6 2 6 1 10 7 9 [6,] 10 3 2 9 4 1 10 7 3 4 [7,] 7 5 9 10 7 5 5 2 1 2 [8,] 1 2 6 4 9 9 8 6 9 10 [9,] 6 1 4 5 3 2 7 1 8 6 [10,] 8 4 1 2 5 7 6 8 6 1 > > tmp <- createBufferedMatrix(5,20) > > tmp[1:5,1:20] <- rnorm(100) > colApply(tmp,sum) [1] 2.9807964 3.0909795 2.3017125 -2.7796055 -1.3063045 2.4282981 [7] -4.0084504 -1.2149918 0.8364889 -1.7503201 2.5229790 4.1653814 [13] -1.0792550 -0.2149982 -1.6906986 2.4075780 2.3059446 -0.1714387 [19] 0.5754640 -0.6644785 > colApply(tmp,quantile)[,1] [,1] [1,] -0.1917557 [2,] 0.3338775 [3,] 0.8258910 [4,] 0.9314750 [5,] 1.0813086 > > rowApply(tmp,sum) [1] -2.8503597 3.5896504 3.1256982 -0.7639232 5.6340152 > rowApply(tmp,rank)[1:5,] [,1] [,2] [,3] [,4] [,5] [1,] 15 16 14 9 15 [2,] 17 20 13 13 8 [3,] 11 10 17 12 11 [4,] 1 9 1 17 6 [5,] 12 3 10 16 2 > > > as.matrix(tmp) [,1] [,2] [,3] [,4] [,5] [,6] [1,] 0.3338775 0.61347072 0.23732257 -1.4534233 0.2395411 0.6412864 [2,] 1.0813086 1.80720956 -0.03571029 -0.1043553 -0.7529338 -0.3573700 [3,] 0.8258910 0.36026796 1.25137315 -1.5770392 0.1111754 -0.3614497 [4,] -0.1917557 0.37837917 0.32854563 0.5568912 0.5335211 0.5111231 [5,] 0.9314750 -0.06834787 0.52018146 -0.2016789 -1.4376082 1.9947082 [,7] [,8] [,9] [,10] [,11] [,12] [1,] -1.407131 -1.1873420 0.07906745 -0.62737057 0.3626520 -0.2550850 [2,] 1.390067 0.7161435 -0.60814321 0.26695527 1.6683035 0.7187620 [3,] -1.391115 -0.1072897 2.29320601 -0.07074016 0.1755360 0.9463557 [4,] -1.468537 -1.1134201 0.09883868 -2.31756545 0.5171821 1.0496073 [5,] -1.131734 0.4769165 -1.02648004 0.99840078 -0.2006947 1.7057414 [,13] [,14] [,15] [,16] [,17] [,18] [1,] -0.6436934 0.3133564 -0.9180046 0.6380907 0.8329243 0.2193645 [2,] 1.5464469 -1.6549362 0.8357894 -0.4036764 0.3159518 -1.8725564 [3,] -1.0836122 -0.6741090 1.5156881 -0.7330536 0.8623270 0.1800568 [4,] -0.6077434 -0.3070661 -0.4322526 1.5482855 -0.5557631 0.9919197 [5,] -0.2906529 2.1077567 -2.6919188 1.3579318 0.8505047 0.3097767 [,19] [,20] [1,] -1.17948024 0.3102169 [2,] -0.54576544 -0.4218402 [3,] 1.64015355 -1.0379240 [4,] 0.08707992 -0.3711927 [5,] 0.57347622 0.8562615 > > > is.BufferedMatrix(tmp) [1] TRUE > > as.BufferedMatrix(as.matrix(tmp)) BufferedMatrix object Matrix size: 5 20 Buffer size: 1 1 Directory: /Users/biocbuild/bbs-3.18-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-3.18-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: /Users/biocbuild/bbs-3.18-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: /Users/biocbuild/bbs-3.18-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 0.4033225 1.736494 -0.4019365 0.9077819 -0.4951689 0.5238839 -1.562842 col8 col9 col10 col11 col12 col13 col14 row1 0.514131 -0.4204542 -2.292729 -0.2094491 -1.150387 -1.370941 -0.4274217 col15 col16 col17 col18 col19 col20 row1 0.08193184 0.1531184 -0.7910402 -1.407082 -0.8896586 -0.01918951 > tmp[,"col10"] col10 row1 -2.2927291 row2 0.9199343 row3 0.3365962 row4 -2.2071601 row5 -0.3228011 > tmp[c("row1","row5"),] col1 col2 col3 col4 col5 col6 row1 0.4033225 1.736494 -0.4019365 0.90778192 -0.49516888 0.52388389 row5 -0.7947292 -1.838317 -1.4995056 0.04630742 -0.04322583 0.02329288 col7 col8 col9 col10 col11 col12 col13 row1 -1.562842 0.5141310 -0.4204542 -2.2927291 -0.2094491 -1.1503871 -1.3709409 row5 1.185359 0.3317832 0.9870281 -0.3228011 0.1308485 -0.8154852 0.3633091 col14 col15 col16 col17 col18 col19 row1 -0.4274217 0.08193184 0.1531184 -0.7910402 -1.407082 -0.8896586 row5 -0.3944775 2.18371155 0.2126991 -0.5040801 -2.208552 2.0417662 col20 row1 -0.01918951 row5 -0.79742690 > tmp[,c("col6","col20")] col6 col20 row1 0.52388389 -0.019189510 row2 -0.06447036 1.203081794 row3 0.22521507 -0.172565805 row4 0.32557542 0.005166983 row5 0.02329288 -0.797426898 > tmp[c("row1","row5"),c("col6","col20")] col6 col20 row1 0.52388389 -0.01918951 row5 0.02329288 -0.79742690 > > > > > tmp["row1",] <- rnorm(20,mean=10) > tmp[,"col10"] <- rnorm(5,mean=30) > tmp[c("row1","row5"),] <- rnorm(40,mean=50) > tmp[,c("col6","col20")] <- rnorm(10,mean=75) > tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105) > > tmp["row1",] col1 col2 col3 col4 col5 col6 col7 col8 row1 51.70347 50.522 50.27129 49.08038 50.47984 105.7431 49.98465 50.46011 col9 col10 col11 col12 col13 col14 col15 col16 row1 49.95302 48.2491 50.10168 51.7932 50.05383 49.41851 49.59301 51.10669 col17 col18 col19 col20 row1 49.7225 50.86255 50.7326 104.1454 > tmp[,"col10"] col10 row1 48.24910 row2 30.79688 row3 30.18750 row4 30.47006 row5 49.42307 > tmp[c("row1","row5"),] col1 col2 col3 col4 col5 col6 col7 col8 row1 51.70347 50.52200 50.27129 49.08038 50.47984 105.7431 49.98465 50.46011 row5 50.58724 50.47957 49.03096 51.56512 48.48817 105.5446 48.81511 49.88393 col9 col10 col11 col12 col13 col14 col15 col16 row1 49.95302 48.24910 50.10168 51.79320 50.05383 49.41851 49.59301 51.10669 row5 48.37762 49.42307 50.06533 49.84169 50.26653 48.32781 50.73222 49.06894 col17 col18 col19 col20 row1 49.72250 50.86255 50.7326 104.1454 row5 50.44561 49.44952 50.5181 105.9071 > tmp[,c("col6","col20")] col6 col20 row1 105.74309 104.14538 row2 76.05660 75.29369 row3 74.76755 76.36400 row4 76.99522 74.66082 row5 105.54462 105.90707 > tmp[c("row1","row5"),c("col6","col20")] col6 col20 row1 105.7431 104.1454 row5 105.5446 105.9071 > > > subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2] col6 col20 row1 105.7431 104.1454 row5 105.5446 105.9071 > > > > > > tmp <- createBufferedMatrix(5,20) > tmp[1:5,1:20] <- rnorm(100) > colnames(tmp) <- colnames(tmp,do.NULL=FALSE) > > tmp[,"col13"] col13 [1,] 0.1108036 [2,] -1.7380158 [3,] 0.3194498 [4,] 1.8595008 [5,] 0.8383725 > tmp[,c("col17","col7")] col17 col7 [1,] -1.5240127 0.23439146 [2,] 0.4718798 1.30998391 [3,] 0.6067363 -2.90624391 [4,] 0.7629807 0.09685809 [5,] -0.6202579 1.16870739 > > subBufferedMatrix(tmp,,c("col6","col20"))[,1:2] col6 col20 [1,] 0.3680952 1.254286 [2,] -1.6366982 1.132361 [3,] 0.3277133 0.470995 [4,] 0.9315995 0.457594 [5,] -0.9768817 -1.598874 > subBufferedMatrix(tmp,1,c("col6"))[,1] col1 [1,] 0.3680952 > subBufferedMatrix(tmp,1:2,c("col6"))[,1] col6 [1,] 0.3680952 [2,] -1.6366982 > > > > 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 0.7116737 0.50573855 -1.61153524 -2.143724 0.43344432 -1.022793401 row1 0.3317735 0.01661216 0.04064711 -1.043341 -0.07132512 0.008542646 [,7] [,8] [,9] [,10] [,11] [,12] [,13] row3 2.4203849 -0.9186861 0.6228760 0.2531129 -0.7022523 -0.2831981 0.7568639 row1 -0.3468788 0.4563313 0.1041852 -0.7936064 0.6062158 0.4360973 0.4814806 [,14] [,15] [,16] [,17] [,18] [,19] [,20] row3 0.05510485 0.6044902 0.6297065 0.6828201 -0.505626 -0.5187817 0.4632439 row1 0.57417062 -0.3385167 0.4063684 -0.4225820 -1.334465 -0.1571516 -0.7943582 > subBufferedMatrix(tmp,c("row2"),1:10)[,1:10] [,1] [,2] [,3] [,4] [,5] [,6] [,7] row2 -0.4034425 -1.625817 0.2489369 -0.6598043 -2.742588 -0.1799558 -0.7620393 [,8] [,9] [,10] row2 -1.465429 0.8489269 0.5588245 > subBufferedMatrix(tmp,c("row5"),1:20)[,1:20] [,1] [,2] [,3] [,4] [,5] [,6] [,7] row5 1.885864 -0.2824627 0.1106045 -0.03163801 0.3031949 -1.238234 0.4134134 [,8] [,9] [,10] [,11] [,12] [,13] [,14] row5 -0.8365897 -0.4347729 1.268601 0.8645812 -0.5954516 0.4983945 -1.265304 [,15] [,16] [,17] [,18] [,19] [,20] row5 -0.6554071 -0.5882185 0.7209856 -0.49173 -0.2249814 -0.6379432 > > > 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: 0x6000016c0120> > is.ReadOnlyMode(tmp) [1] TRUE > > filenames(tmp) [1] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM1815d533c0dce" [2] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM1815dbae7a13" [3] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM1815d6bd07b62" [4] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM1815d4454963a" [5] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM1815dd52dce2" [6] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM1815d3b238043" [7] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM1815d17b9cd0a" [8] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM1815d274457b1" [9] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM1815d77d9399a" [10] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM1815d5654eaee" [11] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM1815d610bdb89" [12] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM1815d517a3125" [13] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM1815d2d309ded" [14] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM1815d52d049c8" [15] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM1815d689c13f1" > > > ### 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: 0x6000016d0240> > MoveStorageDirectory(tmp,getwd(),full.path=TRUE) <pointer: 0x6000016d0240> Warning message: In dir.create(new.directory) : '/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests' already exists > > > RowMode(tmp) <pointer: 0x6000016d0240> > rowMedians(tmp) [1] 0.004401113 0.456634912 -0.456567978 0.006616411 -0.314247396 [6] -0.450830167 -0.047568515 0.296432212 -0.495373808 0.386696612 [11] 0.319633641 0.422497705 -0.270501059 0.073600107 0.329867533 [16] 0.146148184 0.207671685 0.135799246 -0.341282966 0.286259378 [21] 0.329580982 -0.077991731 0.330222276 -0.092821281 0.187609211 [26] -0.096056198 -0.037988976 -0.175484598 -0.220367060 0.332514559 [31] -0.261130065 0.367416975 0.291157621 0.111141145 0.624168115 [36] 0.272352313 -0.080269665 0.490784836 0.718698564 -0.413526608 [41] -0.071280312 -0.405640571 -0.169548145 0.072719792 -0.298071155 [46] 0.749691547 -0.278133450 0.071883447 -0.408415230 -0.482139596 [51] -0.109649941 -0.251779483 0.026539045 -0.350181982 0.131709948 [56] 0.077441577 -0.340821751 0.127715324 -0.160453321 -0.418894075 [61] 0.404446562 0.262722557 0.377843552 -0.209021993 0.271600670 [66] -0.033413472 -0.416330886 -0.126805317 -0.075498878 -0.072747328 [71] 0.040846826 -0.018359554 -0.079983806 0.386887585 0.358555006 [76] -0.499360117 0.270228463 0.029350307 0.146629096 -0.304384794 [81] 0.454240088 0.173854625 -0.389083611 -0.284568983 0.094832129 [86] 0.123535032 -0.017802495 0.368159354 -0.289505918 0.380848759 [91] -0.075138113 -0.011184862 -0.026081122 0.412994516 0.270030610 [96] -0.174039442 -0.222952447 -0.193096867 0.502735613 -0.222433897 [101] 0.271621224 0.348007780 -0.049273403 -0.052911757 -0.146924631 [106] -0.001925874 -0.201352327 -0.060732187 -0.076348503 -0.125040080 [111] -0.598455225 0.292837747 -0.123245317 -0.349778258 0.440916818 [116] -0.154060830 -0.144293303 -0.070462546 0.518422142 -0.214558200 [121] 0.058539708 -0.174647881 -0.553659095 -0.232706104 -0.002946229 [126] -0.214647500 0.018289579 -0.452235648 -0.405570702 -0.336098455 [131] -0.475003538 -0.380711706 0.250165838 0.105958315 -0.243172801 [136] -0.153815967 -0.498866379 0.445938056 0.145658221 -0.154672184 [141] -0.038309071 0.334325647 -0.603919152 -0.190509203 0.372210420 [146] 0.175310396 0.136116474 -0.010388893 -0.162410207 0.168209057 [151] -0.570484939 -0.074033152 0.007478233 -0.202264444 0.202695918 [156] -0.001236111 0.155113776 -0.074346947 -0.299573402 0.048658217 [161] 0.231832646 -0.471665221 0.041554395 0.054526477 0.567387015 [166] 0.248106795 -0.030628388 -0.008242254 0.071912344 0.060304367 [171] 0.042439221 0.036591654 -0.134456210 0.483541787 -0.074372099 [176] -0.314025869 -0.425898197 0.298466072 -0.099003260 -0.101162660 [181] 0.296879241 -0.431143047 0.757864291 -0.001468068 -0.197983817 [186] -0.381131806 0.315003508 -0.042365767 0.500715508 0.001327743 [191] 0.306711670 0.037210708 -0.014967270 0.242178033 0.333778589 [196] -0.102134452 -0.108953490 0.001541144 -0.015636321 0.094951406 [201] 0.407592360 -0.368633158 -0.107143576 0.903873509 -0.184586004 [206] 0.002585057 0.428371859 -0.370654132 0.382600094 0.010817102 [211] 0.613855486 0.723822261 0.688565273 0.632930884 -0.635289218 [216] 0.248366314 -0.714476177 -0.026011092 0.133765701 -0.028039496 [221] 0.425519628 0.190782314 -0.381098218 -0.043158170 -0.486863535 [226] 0.024463412 -0.572413589 0.211945670 -0.606652238 -0.684176917 > > proc.time() user system elapsed 4.938 17.855 24.498
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.3.3 (2024-02-29) -- "Angel Food Cake" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-apple-darwin20 (64-bit) 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: 0x600000c60120> > .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: 0x600000c60120> > .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: 0x600000c60120> > .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: 0x600000c60120> > 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: 0x600000c50000> > .Call("R_bm_AddColumn",P) <pointer: 0x600000c50000> > .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: 0x600000c50000> > .Call("R_bm_AddColumn",P) <pointer: 0x600000c50000> > .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: 0x600000c50000> > 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: 0x600000c604e0> > .Call("R_bm_AddColumn",P) <pointer: 0x600000c604e0> > .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: 0x600000c604e0> > > .Call("R_bm_ResizeBuffer",P,5,5) <pointer: 0x600000c604e0> > .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: 0x600000c604e0> > > .Call("R_bm_RowMode",P) <pointer: 0x600000c604e0> > .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: 0x600000c604e0> > > .Call("R_bm_ColMode",P) <pointer: 0x600000c604e0> > .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: 0x600000c604e0> > 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: 0x600000c54000> > .Call("R_bm_SetPrefix",P,"BufferedMatrixFile") <pointer: 0x600000c54000> > .Call("R_bm_AddColumn",P) <pointer: 0x600000c54000> > .Call("R_bm_AddColumn",P) <pointer: 0x600000c54000> > dir(pattern="BufferedMatrixFile") [1] "BufferedMatrixFilee14215b7e64" "BufferedMatrixFilee147dc6e857" > rm(P) > dir(pattern="BufferedMatrixFile") [1] "BufferedMatrixFilee14215b7e64" "BufferedMatrixFilee147dc6e857" > > > P <- .Call("R_bm_Create",prefix,directory,1,1) > .Call("R_bm_setRows",P,10) [1] TRUE > .Call("R_bm_AddColumn",P) <pointer: 0x600000c54240> > .Call("R_bm_AddColumn",P) <pointer: 0x600000c54240> > .Call("R_bm_ReadOnlyModeToggle",P) <pointer: 0x600000c54240> > .Call("R_bm_isReadOnlyMode",P) [1] TRUE > .Call("R_bm_ReadOnlyModeToggle",P) <pointer: 0x600000c54240> > .Call("R_bm_isReadOnlyMode",P) [1] FALSE > .Call("R_bm_isRowMode",P) [1] FALSE > .Call("R_bm_RowMode",P) <pointer: 0x600000c54240> > .Call("R_bm_isRowMode",P) [1] TRUE > .Call("R_bm_ColMode",P) <pointer: 0x600000c54240> > .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: 0x600000c70180> > .Call("R_bm_AddColumn",P) <pointer: 0x600000c70180> > > .Call("R_bm_getSize",P) [1] 10 2 > .Call("R_bm_getBufferSize",P) [1] 1 1 > .Call("R_bm_ResizeBuffer",P,5,5) <pointer: 0x600000c70180> > > .Call("R_bm_getBufferSize",P) [1] 5 5 > .Call("R_bm_ResizeBuffer",P,-1,5) <pointer: 0x600000c70180> > 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: 0x600000c70300> > .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: 0x600000c70300> > rm(P) > > proc.time() user system elapsed 0.590 0.209 0.783
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.3.3 (2024-02-29) -- "Angel Food Cake" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-apple-darwin20 (64-bit) 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 0.577 0.134 0.675