Back to Multiple platform build/check report for BioC 3.19: simplified long |
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This page was generated on 2024-05-04 11:38:56 -0400 (Sat, 04 May 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" | 4753 |
palomino3 | Windows Server 2022 Datacenter | x64 | 4.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup" | 4486 |
lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.0 beta (2024-04-14 r86421) -- "Puppy Cup" | 4519 |
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" | 4479 |
Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X |
Package 249/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
BufferedMatrix 1.68.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | ![]() | ||||||||
palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | ![]() | ||||||||
lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | ![]() | ||||||||
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) / aarch64 | OK | OK | OK | ||||||||||
kjohnson3 | macOS 13.6.5 Ventura / arm64 | see weekly results here | ||||||||||||
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
Package: BufferedMatrix |
Version: 1.68.0 |
Command: /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: 2024-05-03 20:34:56 -0400 (Fri, 03 May 2024) |
EndedAt: 2024-05-03 20:35:49 -0400 (Fri, 03 May 2024) |
EllapsedTime: 52.4 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 beta (2024-04-14 r86421) * 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 beta (2024-04-14 r86421) -- "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 0.338 0.144 0.472
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.0 beta (2024-04-14 r86421) -- "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 474173 25.4 1035458 55.3 NA 638642 34.2 Vcells 877661 6.7 8388608 64.0 98304 2071729 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] "Fri May 3 20:35:21 2024" > for (rep in 1:nreps){ + which.row <- sample(1:10,5,replace=TRUE) + if (!all(tmp2[which.row,] == test.matrix[which.row,])){ + cat("incorrect agreement") + break; + } + } > date() [1] "Fri May 3 20:35:22 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: 0x6000001d02a0> > > > > for (rep in 1:nreps){ + which.row <- sample(1:10,1) + which.col <- sample(1:20,1) + if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){ + cat("incorrect agreement") + break; + } + } > > > for (rep in 1:nreps){ + which.row <- sample(1:10,1) + if (!all(tmp2[which.row,] == test.matrix[which.row,])){ + cat("incorrect agreement") + break; + } + } > > > for (rep in 1:nreps){ + which.col <- sample(1:20,1) + if (!all(tmp2[,which.col] == test.matrix[,which.col])){ + cat("incorrect agreement") + break; + } + } > > > > for (rep in 1:nreps){ + which.col <- sample(1:20,5,replace=TRUE) + if (!all(tmp2[,which.col] == test.matrix[,which.col])){ + cat("incorrect agreement") + break; + } + } > > > > for (rep in 1:nreps){ + which.row <- sample(1:10,5,replace=TRUE) + if (!all(tmp2[which.row,] == test.matrix[which.row,])){ + cat("incorrect agreement") + break; + } + } > > > date() [1] "Fri May 3 20:35:26 2024" > for (rep in 1:nreps){ + which.row <- sample(1:10,5,replace=TRUE) + which.col <- sample(1:20,5,replace=TRUE) + if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){ + cat("incorrect agreement") + break; + } + } > date() [1] "Fri May 3 20:35:28 2024" > > ColMode(tmp2) <pointer: 0x6000001d02a0> > > > > ### 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,] 100.9590785 0.1867910 1.479031 0.59228576 [2,] 0.1871133 -1.2040866 -1.173718 -1.32900103 [3,] 0.5716709 -0.1482378 2.643692 -2.56537747 [4,] 0.2718265 0.9227729 -3.004420 -0.05585091 > 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,] 100.9590785 0.1867910 1.479031 0.59228576 [2,] 0.1871133 1.2040866 1.173718 1.32900103 [3,] 0.5716709 0.1482378 2.643692 2.56537747 [4,] 0.2718265 0.9227729 3.004420 0.05585091 > 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,] 10.0478395 0.4321932 1.216154 0.769601 [2,] 0.4325660 1.0973088 1.083383 1.152823 [3,] 0.7560892 0.3850167 1.625943 1.601680 [4,] 0.5213699 0.9606107 1.733326 0.236328 > > 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,] 226.43747 29.50872 38.64057 33.28830 [2,] 29.51277 37.17717 37.00755 37.85723 [3,] 33.13256 28.99840 43.90313 43.58217 [4,] 30.48553 35.52888 45.33768 27.41913 > > > > ## testing functions that elementwise transform the matrix > sqrt(tmp5) <pointer: 0x6000001cc000> > exp(tmp5) <pointer: 0x6000001cc000> > log(tmp5,2) <pointer: 0x6000001cc000> > pow(tmp5,2) > > > > > > ## testing functions that apply to entire matrix > Max(tmp5) [1] 471.2999 > Min(tmp5) [1] 54.54207 > mean(tmp5) [1] 72.04402 > Sum(tmp5) [1] 14408.8 > Var(tmp5) [1] 872.1017 > > > ## testing functions applied to rows or columns > > rowMeans(tmp5) [1] 91.24169 73.32032 71.26387 67.93538 67.34855 68.29962 67.55084 70.50533 [9] 71.81459 71.16003 > rowSums(tmp5) [1] 1824.834 1466.406 1425.277 1358.708 1346.971 1365.992 1351.017 1410.107 [9] 1436.292 1423.201 > rowVars(tmp5) [1] 8079.70748 87.65823 93.02684 88.61946 40.97285 60.76168 [7] 34.62432 47.49086 67.30507 63.29055 > rowSd(tmp5) [1] 89.887193 9.362598 9.645042 9.413791 6.401004 7.794978 5.884243 [8] 6.891361 8.203967 7.955536 > rowMax(tmp5) [1] 471.29993 90.05485 91.37860 94.36445 78.68353 83.20190 79.54097 [8] 83.02938 83.46748 85.22067 > rowMin(tmp5) [1] 56.64761 57.06295 55.87758 57.06933 57.31033 55.43169 54.54207 56.90429 [9] 57.71160 57.14470 > > colMeans(tmp5) [1] 106.27555 71.85428 77.90180 69.69742 68.98379 69.97023 70.00369 [8] 65.46465 73.74200 70.49371 71.30400 64.64278 68.57281 70.30649 [15] 71.60040 70.80576 71.14548 71.06131 68.96506 68.08925 > colSums(tmp5) [1] 1062.7555 718.5428 779.0180 696.9742 689.8379 699.7023 700.0369 [8] 654.6465 737.4200 704.9371 713.0400 646.4278 685.7281 703.0649 [15] 716.0040 708.0576 711.4548 710.6131 689.6506 680.8925 > colVars(tmp5) [1] 16477.78911 48.66136 86.12349 103.28093 83.76023 62.27263 [7] 63.59198 26.38398 111.03022 70.23649 56.99354 73.18945 [13] 90.91053 107.98373 36.91807 32.78281 95.43997 43.06991 [19] 35.64283 46.99282 > colSd(tmp5) [1] 128.365841 6.975769 9.280274 10.162723 9.152062 7.891301 [7] 7.974458 5.136534 10.537088 8.380722 7.549406 8.555083 [13] 9.534701 10.391522 6.076025 5.725628 9.769338 6.562767 [19] 5.970161 6.855131 > colMax(tmp5) [1] 471.29993 78.62506 94.36445 90.71058 85.40261 79.35218 83.06007 [8] 74.45218 86.51071 85.22067 79.54097 84.79290 84.57687 83.46748 [15] 80.97950 79.31763 90.05485 79.72693 81.22031 77.99782 > colMin(tmp5) [1] 54.54207 60.35638 64.41060 57.06933 55.87758 57.34215 60.90572 59.20716 [9] 57.27936 59.70496 58.45653 57.06295 55.43169 57.31033 58.94893 62.32359 [17] 56.64761 56.90429 62.18405 60.44856 > > > ### 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] 91.24169 73.32032 71.26387 NA 67.34855 68.29962 67.55084 70.50533 [9] 71.81459 71.16003 > rowSums(tmp5) [1] 1824.834 1466.406 1425.277 NA 1346.971 1365.992 1351.017 1410.107 [9] 1436.292 1423.201 > rowVars(tmp5) [1] 8079.70748 87.65823 93.02684 52.69507 40.97285 60.76168 [7] 34.62432 47.49086 67.30507 63.29055 > rowSd(tmp5) [1] 89.887193 9.362598 9.645042 7.259137 6.401004 7.794978 5.884243 [8] 6.891361 8.203967 7.955536 > rowMax(tmp5) [1] 471.29993 90.05485 91.37860 NA 78.68353 83.20190 79.54097 [8] 83.02938 83.46748 85.22067 > rowMin(tmp5) [1] 56.64761 57.06295 55.87758 NA 57.31033 55.43169 54.54207 56.90429 [9] 57.71160 57.14470 > > colMeans(tmp5) [1] 106.27555 71.85428 NA 69.69742 68.98379 69.97023 70.00369 [8] 65.46465 73.74200 70.49371 71.30400 64.64278 68.57281 70.30649 [15] 71.60040 70.80576 71.14548 71.06131 68.96506 68.08925 > colSums(tmp5) [1] 1062.7555 718.5428 NA 696.9742 689.8379 699.7023 700.0369 [8] 654.6465 737.4200 704.9371 713.0400 646.4278 685.7281 703.0649 [15] 716.0040 708.0576 711.4548 710.6131 689.6506 680.8925 > colVars(tmp5) [1] 16477.78911 48.66136 NA 103.28093 83.76023 62.27263 [7] 63.59198 26.38398 111.03022 70.23649 56.99354 73.18945 [13] 90.91053 107.98373 36.91807 32.78281 95.43997 43.06991 [19] 35.64283 46.99282 > colSd(tmp5) [1] 128.365841 6.975769 NA 10.162723 9.152062 7.891301 [7] 7.974458 5.136534 10.537088 8.380722 7.549406 8.555083 [13] 9.534701 10.391522 6.076025 5.725628 9.769338 6.562767 [19] 5.970161 6.855131 > colMax(tmp5) [1] 471.29993 78.62506 NA 90.71058 85.40261 79.35218 83.06007 [8] 74.45218 86.51071 85.22067 79.54097 84.79290 84.57687 83.46748 [15] 80.97950 79.31763 90.05485 79.72693 81.22031 77.99782 > colMin(tmp5) [1] 54.54207 60.35638 NA 57.06933 55.87758 57.34215 60.90572 59.20716 [9] 57.27936 59.70496 58.45653 57.06295 55.43169 57.31033 58.94893 62.32359 [17] 56.64761 56.90429 62.18405 60.44856 > > Max(tmp5,na.rm=TRUE) [1] 471.2999 > Min(tmp5,na.rm=TRUE) [1] 54.54207 > mean(tmp5,na.rm=TRUE) [1] 71.93186 > Sum(tmp5,na.rm=TRUE) [1] 14314.44 > Var(tmp5,na.rm=TRUE) [1] 873.9774 > > rowMeans(tmp5,na.rm=TRUE) [1] 91.24169 73.32032 71.26387 66.54438 67.34855 68.29962 67.55084 70.50533 [9] 71.81459 71.16003 > rowSums(tmp5,na.rm=TRUE) [1] 1824.834 1466.406 1425.277 1264.343 1346.971 1365.992 1351.017 1410.107 [9] 1436.292 1423.201 > rowVars(tmp5,na.rm=TRUE) [1] 8079.70748 87.65823 93.02684 52.69507 40.97285 60.76168 [7] 34.62432 47.49086 67.30507 63.29055 > rowSd(tmp5,na.rm=TRUE) [1] 89.887193 9.362598 9.645042 7.259137 6.401004 7.794978 5.884243 [8] 6.891361 8.203967 7.955536 > rowMax(tmp5,na.rm=TRUE) [1] 471.29993 90.05485 91.37860 80.62881 78.68353 83.20190 79.54097 [8] 83.02938 83.46748 85.22067 > rowMin(tmp5,na.rm=TRUE) [1] 56.64761 57.06295 55.87758 57.06933 57.31033 55.43169 54.54207 56.90429 [9] 57.71160 57.14470 > > colMeans(tmp5,na.rm=TRUE) [1] 106.27555 71.85428 76.07262 69.69742 68.98379 69.97023 70.00369 [8] 65.46465 73.74200 70.49371 71.30400 64.64278 68.57281 70.30649 [15] 71.60040 70.80576 71.14548 71.06131 68.96506 68.08925 > colSums(tmp5,na.rm=TRUE) [1] 1062.7555 718.5428 684.6536 696.9742 689.8379 699.7023 700.0369 [8] 654.6465 737.4200 704.9371 713.0400 646.4278 685.7281 703.0649 [15] 716.0040 708.0576 711.4548 710.6131 689.6506 680.8925 > colVars(tmp5,na.rm=TRUE) [1] 16477.78911 48.66136 59.24744 103.28093 83.76023 62.27263 [7] 63.59198 26.38398 111.03022 70.23649 56.99354 73.18945 [13] 90.91053 107.98373 36.91807 32.78281 95.43997 43.06991 [19] 35.64283 46.99282 > colSd(tmp5,na.rm=TRUE) [1] 128.365841 6.975769 7.697236 10.162723 9.152062 7.891301 [7] 7.974458 5.136534 10.537088 8.380722 7.549406 8.555083 [13] 9.534701 10.391522 6.076025 5.725628 9.769338 6.562767 [19] 5.970161 6.855131 > colMax(tmp5,na.rm=TRUE) [1] 471.29993 78.62506 91.37860 90.71058 85.40261 79.35218 83.06007 [8] 74.45218 86.51071 85.22067 79.54097 84.79290 84.57687 83.46748 [15] 80.97950 79.31763 90.05485 79.72693 81.22031 77.99782 > colMin(tmp5,na.rm=TRUE) [1] 54.54207 60.35638 64.41060 57.06933 55.87758 57.34215 60.90572 59.20716 [9] 57.27936 59.70496 58.45653 57.06295 55.43169 57.31033 58.94893 62.32359 [17] 56.64761 56.90429 62.18405 60.44856 > > # now set an entire row to NA > > tmp5[which.row,] <- NA > rowMeans(tmp5,na.rm=TRUE) [1] 91.24169 73.32032 71.26387 NaN 67.34855 68.29962 67.55084 70.50533 [9] 71.81459 71.16003 > rowSums(tmp5,na.rm=TRUE) [1] 1824.834 1466.406 1425.277 0.000 1346.971 1365.992 1351.017 1410.107 [9] 1436.292 1423.201 > rowVars(tmp5,na.rm=TRUE) [1] 8079.70748 87.65823 93.02684 NA 40.97285 60.76168 [7] 34.62432 47.49086 67.30507 63.29055 > rowSd(tmp5,na.rm=TRUE) [1] 89.887193 9.362598 9.645042 NA 6.401004 7.794978 5.884243 [8] 6.891361 8.203967 7.955536 > rowMax(tmp5,na.rm=TRUE) [1] 471.29993 90.05485 91.37860 NA 78.68353 83.20190 79.54097 [8] 83.02938 83.46748 85.22067 > rowMin(tmp5,na.rm=TRUE) [1] 56.64761 57.06295 55.87758 NA 57.31033 55.43169 54.54207 56.90429 [9] 57.71160 57.14470 > > > # now set an entire col to NA > > > tmp5[,which.col] <- NA > colMeans(tmp5,na.rm=TRUE) [1] 111.03376 71.62157 NaN 71.10054 68.73304 71.37335 70.83600 [8] 64.46604 74.93137 71.69246 72.73149 65.13778 68.69879 71.27812 [15] 71.14986 70.50911 70.09178 71.28072 68.41820 68.85417 > colSums(tmp5,na.rm=TRUE) [1] 999.3038 644.5941 0.0000 639.9048 618.5973 642.3601 637.5240 580.1943 [9] 674.3823 645.2321 654.5834 586.2400 618.2891 641.5031 640.3487 634.5820 [17] 630.8260 641.5265 615.7638 619.6876 > colVars(tmp5,na.rm=TRUE) [1] 18282.80605 54.13478 NA 94.04263 93.52288 47.90831 [7] 63.74772 18.46314 108.99489 62.84981 41.19311 79.58159 [13] 102.09580 110.86099 39.24924 35.89070 94.87919 47.91206 [19] 36.73381 46.28440 > colSd(tmp5,na.rm=TRUE) [1] 135.213927 7.357634 NA 9.697558 9.670723 6.921583 [7] 7.984217 4.296875 10.440062 7.927787 6.418186 8.920851 [13] 10.104247 10.529054 6.264922 5.990885 9.740595 6.921854 [19] 6.060843 6.803264 > colMax(tmp5,na.rm=TRUE) [1] 471.29993 78.62506 -Inf 90.71058 85.40261 79.35218 83.06007 [8] 70.98935 86.51071 85.22067 79.54097 84.79290 84.57687 83.46748 [15] 80.97950 79.31763 90.05485 79.72693 81.22031 77.99782 > colMin(tmp5,na.rm=TRUE) [1] 54.54207 60.35638 Inf 58.26893 55.87758 61.95545 60.90572 59.20716 [9] 57.27936 62.91750 65.13848 57.06295 55.43169 57.31033 58.94893 62.32359 [17] 56.64761 56.90429 62.18405 60.44856 > > > > > 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] 310.1014 250.9681 106.1345 211.9857 273.7624 232.6974 193.0684 127.1902 [9] 157.9522 374.8329 > apply(copymatrix,1,var,na.rm=TRUE) [1] 310.1014 250.9681 106.1345 211.9857 273.7624 232.6974 193.0684 127.1902 [9] 157.9522 374.8329 > > > > 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] 1.421085e-14 0.000000e+00 -1.421085e-14 -1.136868e-13 -1.705303e-13 [6] -5.684342e-14 -5.684342e-14 1.136868e-13 0.000000e+00 5.684342e-14 [11] 8.526513e-14 1.421085e-13 0.000000e+00 5.684342e-14 -2.842171e-14 [16] -1.136868e-13 -1.705303e-13 -2.273737e-13 1.136868e-13 -7.105427e-14 > > > > > > > > > > > ## making sure these things agree > ## > ## first when there is no NA > > > > agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){ + + if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){ + stop("No agreement in Max") + } + + + if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){ + stop("No agreement in Min") + } + + + if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){ + + cat(Sum(buff.matrix,na.rm=TRUE),"\n") + cat(sum(r.matrix,na.rm=TRUE),"\n") + cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n") + + stop("No agreement in Sum") + } + + if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){ + stop("No agreement in mean") + } + + + if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){ + stop("No agreement in Var") + } + + + + if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in rowMeans") + } + + + if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){ + stop("No agreement in colMeans") + } + + + if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){ + stop("No agreement in rowSums") + } + + + if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){ + stop("No agreement in colSums") + } + + ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when + ### computing variance + my.Var <- function(x,na.rm=FALSE){ + if (all(is.na(x))){ + return(NA) + } else { + var(x,na.rm=na.rm) + } + + } + + if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in rowVars") + } + + + if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in rowVars") + } + + + if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colMax") + } + + + if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colMax") + } + + + + if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colMin") + } + + + if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colMin") + } + + if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colMedian") + } + + if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colRanges") + } + + + + } > > > > > > > > > > for (rep in 1:20){ + copymatrix <- matrix(rnorm(200,150,15),10,20) + + tmp5[1:10,1:20] <- copymatrix + + + agree.checks(tmp5,copymatrix) + + ## now lets assign some NA values and check agreement + + which.row <- sample(1:10,1,replace=TRUE) + which.col <- sample(1:20,1,replace=TRUE) + + cat(which.row," ",which.col,"\n") + + tmp5[which.row,which.col] <- NA + copymatrix[which.row,which.col] <- NA + + agree.checks(tmp5,copymatrix) + + ## make an entire row NA + tmp5[which.row,] <- NA + copymatrix[which.row,] <- NA + + + agree.checks(tmp5,copymatrix) + + ### also make an entire col NA + tmp5[,which.col] <- NA + copymatrix[,which.col] <- NA + + agree.checks(tmp5,copymatrix) + + ### now make 1 element non NA with NA in the rest of row and column + + tmp5[which.row,which.col] <- rnorm(1,150,15) + copymatrix[which.row,which.col] <- tmp5[which.row,which.col] + + agree.checks(tmp5,copymatrix) + } 7 20 5 7 1 15 1 19 10 4 6 7 2 11 9 10 3 13 10 2 8 10 6 11 2 18 7 2 7 10 7 6 6 12 8 5 7 15 3 9 There were 50 or more warnings (use warnings() to see the first 50) > > > ### now test 1 by n and n by 1 matrix > > > err.tol <- 1e-12 > > rm(tmp5) > > dataset1 <- rnorm(100) > dataset2 <- rnorm(100) > > tmp <- createBufferedMatrix(1,100) > tmp[1,] <- dataset1 > > tmp2 <- createBufferedMatrix(100,1) > tmp2[,1] <- dataset2 > > > > > > Max(tmp) [1] 2.732554 > Min(tmp) [1] -1.989105 > mean(tmp) [1] 0.1813369 > Sum(tmp) [1] 18.13369 > Var(tmp) [1] 0.7879686 > > rowMeans(tmp) [1] 0.1813369 > rowSums(tmp) [1] 18.13369 > rowVars(tmp) [1] 0.7879686 > rowSd(tmp) [1] 0.8876759 > rowMax(tmp) [1] 2.732554 > rowMin(tmp) [1] -1.989105 > > colMeans(tmp) [1] -0.02657093 1.55555674 0.12850381 1.30395093 0.47776796 -1.23987683 [7] 1.60425437 0.02483447 1.56120441 0.31861704 1.50370183 -0.10878168 [13] 0.31334518 1.33129752 -0.95455184 0.72324671 0.20611906 -0.85676674 [19] -1.23238561 -0.29083268 -0.63256991 0.34704862 -0.35952506 0.58030099 [25] -1.30213154 -0.63812953 -0.14796808 0.66268267 0.92317382 -1.98910521 [31] -0.56964027 0.54167428 -0.72972320 -0.17148355 0.16783619 -0.77331165 [37] 1.88295696 0.07608046 0.75718199 1.08671306 0.15458518 -0.93456110 [43] 0.40671179 1.04184907 2.73255401 -0.68990260 1.13653684 0.70252710 [49] 0.35495900 0.04715374 0.60813777 0.31772422 -0.68119422 -0.95803937 [55] 1.28490298 1.56344205 1.30937989 -0.93542646 1.04289550 -0.06530823 [61] 1.83487949 -1.84931567 -0.38167866 -0.78672547 0.21476423 -1.68149068 [67] 0.36834889 -0.09916172 0.76842096 -0.67399057 0.13577703 -0.33160834 [73] 0.14932210 0.06184652 0.58375125 0.91051574 0.85984328 0.99472325 [79] -0.46775551 1.06385401 1.06019392 0.09018427 -0.10837531 0.37125477 [85] -0.80332283 -0.07581864 -0.96334634 -0.38562462 -0.89472600 1.03357700 [91] -0.10345076 -0.32411757 -0.21413860 1.53581823 0.02585157 -0.53845375 [97] 0.97200227 0.36149873 0.51801716 0.40872605 > colSums(tmp) [1] -0.02657093 1.55555674 0.12850381 1.30395093 0.47776796 -1.23987683 [7] 1.60425437 0.02483447 1.56120441 0.31861704 1.50370183 -0.10878168 [13] 0.31334518 1.33129752 -0.95455184 0.72324671 0.20611906 -0.85676674 [19] -1.23238561 -0.29083268 -0.63256991 0.34704862 -0.35952506 0.58030099 [25] -1.30213154 -0.63812953 -0.14796808 0.66268267 0.92317382 -1.98910521 [31] -0.56964027 0.54167428 -0.72972320 -0.17148355 0.16783619 -0.77331165 [37] 1.88295696 0.07608046 0.75718199 1.08671306 0.15458518 -0.93456110 [43] 0.40671179 1.04184907 2.73255401 -0.68990260 1.13653684 0.70252710 [49] 0.35495900 0.04715374 0.60813777 0.31772422 -0.68119422 -0.95803937 [55] 1.28490298 1.56344205 1.30937989 -0.93542646 1.04289550 -0.06530823 [61] 1.83487949 -1.84931567 -0.38167866 -0.78672547 0.21476423 -1.68149068 [67] 0.36834889 -0.09916172 0.76842096 -0.67399057 0.13577703 -0.33160834 [73] 0.14932210 0.06184652 0.58375125 0.91051574 0.85984328 0.99472325 [79] -0.46775551 1.06385401 1.06019392 0.09018427 -0.10837531 0.37125477 [85] -0.80332283 -0.07581864 -0.96334634 -0.38562462 -0.89472600 1.03357700 [91] -0.10345076 -0.32411757 -0.21413860 1.53581823 0.02585157 -0.53845375 [97] 0.97200227 0.36149873 0.51801716 0.40872605 > 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] -0.02657093 1.55555674 0.12850381 1.30395093 0.47776796 -1.23987683 [7] 1.60425437 0.02483447 1.56120441 0.31861704 1.50370183 -0.10878168 [13] 0.31334518 1.33129752 -0.95455184 0.72324671 0.20611906 -0.85676674 [19] -1.23238561 -0.29083268 -0.63256991 0.34704862 -0.35952506 0.58030099 [25] -1.30213154 -0.63812953 -0.14796808 0.66268267 0.92317382 -1.98910521 [31] -0.56964027 0.54167428 -0.72972320 -0.17148355 0.16783619 -0.77331165 [37] 1.88295696 0.07608046 0.75718199 1.08671306 0.15458518 -0.93456110 [43] 0.40671179 1.04184907 2.73255401 -0.68990260 1.13653684 0.70252710 [49] 0.35495900 0.04715374 0.60813777 0.31772422 -0.68119422 -0.95803937 [55] 1.28490298 1.56344205 1.30937989 -0.93542646 1.04289550 -0.06530823 [61] 1.83487949 -1.84931567 -0.38167866 -0.78672547 0.21476423 -1.68149068 [67] 0.36834889 -0.09916172 0.76842096 -0.67399057 0.13577703 -0.33160834 [73] 0.14932210 0.06184652 0.58375125 0.91051574 0.85984328 0.99472325 [79] -0.46775551 1.06385401 1.06019392 0.09018427 -0.10837531 0.37125477 [85] -0.80332283 -0.07581864 -0.96334634 -0.38562462 -0.89472600 1.03357700 [91] -0.10345076 -0.32411757 -0.21413860 1.53581823 0.02585157 -0.53845375 [97] 0.97200227 0.36149873 0.51801716 0.40872605 > colMin(tmp) [1] -0.02657093 1.55555674 0.12850381 1.30395093 0.47776796 -1.23987683 [7] 1.60425437 0.02483447 1.56120441 0.31861704 1.50370183 -0.10878168 [13] 0.31334518 1.33129752 -0.95455184 0.72324671 0.20611906 -0.85676674 [19] -1.23238561 -0.29083268 -0.63256991 0.34704862 -0.35952506 0.58030099 [25] -1.30213154 -0.63812953 -0.14796808 0.66268267 0.92317382 -1.98910521 [31] -0.56964027 0.54167428 -0.72972320 -0.17148355 0.16783619 -0.77331165 [37] 1.88295696 0.07608046 0.75718199 1.08671306 0.15458518 -0.93456110 [43] 0.40671179 1.04184907 2.73255401 -0.68990260 1.13653684 0.70252710 [49] 0.35495900 0.04715374 0.60813777 0.31772422 -0.68119422 -0.95803937 [55] 1.28490298 1.56344205 1.30937989 -0.93542646 1.04289550 -0.06530823 [61] 1.83487949 -1.84931567 -0.38167866 -0.78672547 0.21476423 -1.68149068 [67] 0.36834889 -0.09916172 0.76842096 -0.67399057 0.13577703 -0.33160834 [73] 0.14932210 0.06184652 0.58375125 0.91051574 0.85984328 0.99472325 [79] -0.46775551 1.06385401 1.06019392 0.09018427 -0.10837531 0.37125477 [85] -0.80332283 -0.07581864 -0.96334634 -0.38562462 -0.89472600 1.03357700 [91] -0.10345076 -0.32411757 -0.21413860 1.53581823 0.02585157 -0.53845375 [97] 0.97200227 0.36149873 0.51801716 0.40872605 > colMedians(tmp) [1] -0.02657093 1.55555674 0.12850381 1.30395093 0.47776796 -1.23987683 [7] 1.60425437 0.02483447 1.56120441 0.31861704 1.50370183 -0.10878168 [13] 0.31334518 1.33129752 -0.95455184 0.72324671 0.20611906 -0.85676674 [19] -1.23238561 -0.29083268 -0.63256991 0.34704862 -0.35952506 0.58030099 [25] -1.30213154 -0.63812953 -0.14796808 0.66268267 0.92317382 -1.98910521 [31] -0.56964027 0.54167428 -0.72972320 -0.17148355 0.16783619 -0.77331165 [37] 1.88295696 0.07608046 0.75718199 1.08671306 0.15458518 -0.93456110 [43] 0.40671179 1.04184907 2.73255401 -0.68990260 1.13653684 0.70252710 [49] 0.35495900 0.04715374 0.60813777 0.31772422 -0.68119422 -0.95803937 [55] 1.28490298 1.56344205 1.30937989 -0.93542646 1.04289550 -0.06530823 [61] 1.83487949 -1.84931567 -0.38167866 -0.78672547 0.21476423 -1.68149068 [67] 0.36834889 -0.09916172 0.76842096 -0.67399057 0.13577703 -0.33160834 [73] 0.14932210 0.06184652 0.58375125 0.91051574 0.85984328 0.99472325 [79] -0.46775551 1.06385401 1.06019392 0.09018427 -0.10837531 0.37125477 [85] -0.80332283 -0.07581864 -0.96334634 -0.38562462 -0.89472600 1.03357700 [91] -0.10345076 -0.32411757 -0.21413860 1.53581823 0.02585157 -0.53845375 [97] 0.97200227 0.36149873 0.51801716 0.40872605 > colRanges(tmp) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [1,] -0.02657093 1.555557 0.1285038 1.303951 0.477768 -1.239877 1.604254 [2,] -0.02657093 1.555557 0.1285038 1.303951 0.477768 -1.239877 1.604254 [,8] [,9] [,10] [,11] [,12] [,13] [,14] [1,] 0.02483447 1.561204 0.318617 1.503702 -0.1087817 0.3133452 1.331298 [2,] 0.02483447 1.561204 0.318617 1.503702 -0.1087817 0.3133452 1.331298 [,15] [,16] [,17] [,18] [,19] [,20] [,21] [1,] -0.9545518 0.7232467 0.2061191 -0.8567667 -1.232386 -0.2908327 -0.6325699 [2,] -0.9545518 0.7232467 0.2061191 -0.8567667 -1.232386 -0.2908327 -0.6325699 [,22] [,23] [,24] [,25] [,26] [,27] [,28] [1,] 0.3470486 -0.3595251 0.580301 -1.302132 -0.6381295 -0.1479681 0.6626827 [2,] 0.3470486 -0.3595251 0.580301 -1.302132 -0.6381295 -0.1479681 0.6626827 [,29] [,30] [,31] [,32] [,33] [,34] [,35] [1,] 0.9231738 -1.989105 -0.5696403 0.5416743 -0.7297232 -0.1714836 0.1678362 [2,] 0.9231738 -1.989105 -0.5696403 0.5416743 -0.7297232 -0.1714836 0.1678362 [,36] [,37] [,38] [,39] [,40] [,41] [,42] [1,] -0.7733117 1.882957 0.07608046 0.757182 1.086713 0.1545852 -0.9345611 [2,] -0.7733117 1.882957 0.07608046 0.757182 1.086713 0.1545852 -0.9345611 [,43] [,44] [,45] [,46] [,47] [,48] [,49] [1,] 0.4067118 1.041849 2.732554 -0.6899026 1.136537 0.7025271 0.354959 [2,] 0.4067118 1.041849 2.732554 -0.6899026 1.136537 0.7025271 0.354959 [,50] [,51] [,52] [,53] [,54] [,55] [,56] [1,] 0.04715374 0.6081378 0.3177242 -0.6811942 -0.9580394 1.284903 1.563442 [2,] 0.04715374 0.6081378 0.3177242 -0.6811942 -0.9580394 1.284903 1.563442 [,57] [,58] [,59] [,60] [,61] [,62] [,63] [1,] 1.30938 -0.9354265 1.042896 -0.06530823 1.834879 -1.849316 -0.3816787 [2,] 1.30938 -0.9354265 1.042896 -0.06530823 1.834879 -1.849316 -0.3816787 [,64] [,65] [,66] [,67] [,68] [,69] [,70] [1,] -0.7867255 0.2147642 -1.681491 0.3683489 -0.09916172 0.768421 -0.6739906 [2,] -0.7867255 0.2147642 -1.681491 0.3683489 -0.09916172 0.768421 -0.6739906 [,71] [,72] [,73] [,74] [,75] [,76] [,77] [1,] 0.135777 -0.3316083 0.1493221 0.06184652 0.5837512 0.9105157 0.8598433 [2,] 0.135777 -0.3316083 0.1493221 0.06184652 0.5837512 0.9105157 0.8598433 [,78] [,79] [,80] [,81] [,82] [,83] [,84] [1,] 0.9947233 -0.4677555 1.063854 1.060194 0.09018427 -0.1083753 0.3712548 [2,] 0.9947233 -0.4677555 1.063854 1.060194 0.09018427 -0.1083753 0.3712548 [,85] [,86] [,87] [,88] [,89] [,90] [,91] [1,] -0.8033228 -0.07581864 -0.9633463 -0.3856246 -0.894726 1.033577 -0.1034508 [2,] -0.8033228 -0.07581864 -0.9633463 -0.3856246 -0.894726 1.033577 -0.1034508 [,92] [,93] [,94] [,95] [,96] [,97] [,98] [1,] -0.3241176 -0.2141386 1.535818 0.02585157 -0.5384538 0.9720023 0.3614987 [2,] -0.3241176 -0.2141386 1.535818 0.02585157 -0.5384538 0.9720023 0.3614987 [,99] [,100] [1,] 0.5180172 0.4087261 [2,] 0.5180172 0.4087261 > > > Max(tmp2) [1] 2.723487 > Min(tmp2) [1] -1.59213 > mean(tmp2) [1] 0.09899404 > Sum(tmp2) [1] 9.899404 > Var(tmp2) [1] 0.7356191 > > rowMeans(tmp2) [1] 0.0794929569 -0.4088028325 0.9747055215 -0.1095893141 -1.3872221613 [6] -0.7428908367 -0.1862495060 1.0969150132 -0.0388715134 0.6302137347 [11] -0.7678417657 0.4581981210 1.4681452432 -0.1552142867 0.9506891473 [16] 0.3038045843 0.3042760098 2.0710251257 -0.1821246816 -0.4359639089 [21] -0.5605905724 -0.6574242057 -1.2163302374 1.1474291447 0.8938628779 [26] 0.7158990920 0.6450898938 0.1256090796 1.5691707939 0.1815136243 [31] 0.4058879350 -0.9341232975 0.7840191967 0.0001294059 0.8109299212 [36] 0.5219802174 0.6911935603 0.0938196494 0.0069232786 0.1388331755 [41] -1.5921303410 -0.2184268516 0.6779862224 0.1378590238 1.2672390187 [46] -0.7280978890 0.0999763556 0.4010308492 -0.2618884823 -0.7784045003 [51] 1.5037007458 -0.2807001848 -0.2420018088 0.8559180564 -0.4196011874 [56] -0.0395039337 0.1122046723 2.7234872115 -0.2538506411 -0.3454625701 [61] 0.9438606685 2.0190309710 -0.0282254627 1.6281879310 -0.1440050512 [66] 1.3279708634 0.2401838796 -0.2281015028 -0.2072203612 -1.4403830419 [71] -0.1931715258 -0.9671143752 -1.0560160864 0.1046998772 1.2372046479 [76] -0.9474614517 -0.2531940896 -0.0404861520 0.4898051864 -0.5716729480 [81] 0.0161397856 -1.0820416616 -0.6366704247 0.2094466179 0.2934562051 [86] -0.2062450718 -0.0376583087 1.0154925564 1.1444409791 -1.3172536012 [91] -0.3933724362 0.2401682180 0.0485576635 -0.8652310672 -1.2428143964 [96] -1.0070868867 -1.1678713041 1.9582896223 0.0074938443 -0.8975789320 > rowSums(tmp2) [1] 0.0794929569 -0.4088028325 0.9747055215 -0.1095893141 -1.3872221613 [6] -0.7428908367 -0.1862495060 1.0969150132 -0.0388715134 0.6302137347 [11] -0.7678417657 0.4581981210 1.4681452432 -0.1552142867 0.9506891473 [16] 0.3038045843 0.3042760098 2.0710251257 -0.1821246816 -0.4359639089 [21] -0.5605905724 -0.6574242057 -1.2163302374 1.1474291447 0.8938628779 [26] 0.7158990920 0.6450898938 0.1256090796 1.5691707939 0.1815136243 [31] 0.4058879350 -0.9341232975 0.7840191967 0.0001294059 0.8109299212 [36] 0.5219802174 0.6911935603 0.0938196494 0.0069232786 0.1388331755 [41] -1.5921303410 -0.2184268516 0.6779862224 0.1378590238 1.2672390187 [46] -0.7280978890 0.0999763556 0.4010308492 -0.2618884823 -0.7784045003 [51] 1.5037007458 -0.2807001848 -0.2420018088 0.8559180564 -0.4196011874 [56] -0.0395039337 0.1122046723 2.7234872115 -0.2538506411 -0.3454625701 [61] 0.9438606685 2.0190309710 -0.0282254627 1.6281879310 -0.1440050512 [66] 1.3279708634 0.2401838796 -0.2281015028 -0.2072203612 -1.4403830419 [71] -0.1931715258 -0.9671143752 -1.0560160864 0.1046998772 1.2372046479 [76] -0.9474614517 -0.2531940896 -0.0404861520 0.4898051864 -0.5716729480 [81] 0.0161397856 -1.0820416616 -0.6366704247 0.2094466179 0.2934562051 [86] -0.2062450718 -0.0376583087 1.0154925564 1.1444409791 -1.3172536012 [91] -0.3933724362 0.2401682180 0.0485576635 -0.8652310672 -1.2428143964 [96] -1.0070868867 -1.1678713041 1.9582896223 0.0074938443 -0.8975789320 > 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] 0.0794929569 -0.4088028325 0.9747055215 -0.1095893141 -1.3872221613 [6] -0.7428908367 -0.1862495060 1.0969150132 -0.0388715134 0.6302137347 [11] -0.7678417657 0.4581981210 1.4681452432 -0.1552142867 0.9506891473 [16] 0.3038045843 0.3042760098 2.0710251257 -0.1821246816 -0.4359639089 [21] -0.5605905724 -0.6574242057 -1.2163302374 1.1474291447 0.8938628779 [26] 0.7158990920 0.6450898938 0.1256090796 1.5691707939 0.1815136243 [31] 0.4058879350 -0.9341232975 0.7840191967 0.0001294059 0.8109299212 [36] 0.5219802174 0.6911935603 0.0938196494 0.0069232786 0.1388331755 [41] -1.5921303410 -0.2184268516 0.6779862224 0.1378590238 1.2672390187 [46] -0.7280978890 0.0999763556 0.4010308492 -0.2618884823 -0.7784045003 [51] 1.5037007458 -0.2807001848 -0.2420018088 0.8559180564 -0.4196011874 [56] -0.0395039337 0.1122046723 2.7234872115 -0.2538506411 -0.3454625701 [61] 0.9438606685 2.0190309710 -0.0282254627 1.6281879310 -0.1440050512 [66] 1.3279708634 0.2401838796 -0.2281015028 -0.2072203612 -1.4403830419 [71] -0.1931715258 -0.9671143752 -1.0560160864 0.1046998772 1.2372046479 [76] -0.9474614517 -0.2531940896 -0.0404861520 0.4898051864 -0.5716729480 [81] 0.0161397856 -1.0820416616 -0.6366704247 0.2094466179 0.2934562051 [86] -0.2062450718 -0.0376583087 1.0154925564 1.1444409791 -1.3172536012 [91] -0.3933724362 0.2401682180 0.0485576635 -0.8652310672 -1.2428143964 [96] -1.0070868867 -1.1678713041 1.9582896223 0.0074938443 -0.8975789320 > rowMin(tmp2) [1] 0.0794929569 -0.4088028325 0.9747055215 -0.1095893141 -1.3872221613 [6] -0.7428908367 -0.1862495060 1.0969150132 -0.0388715134 0.6302137347 [11] -0.7678417657 0.4581981210 1.4681452432 -0.1552142867 0.9506891473 [16] 0.3038045843 0.3042760098 2.0710251257 -0.1821246816 -0.4359639089 [21] -0.5605905724 -0.6574242057 -1.2163302374 1.1474291447 0.8938628779 [26] 0.7158990920 0.6450898938 0.1256090796 1.5691707939 0.1815136243 [31] 0.4058879350 -0.9341232975 0.7840191967 0.0001294059 0.8109299212 [36] 0.5219802174 0.6911935603 0.0938196494 0.0069232786 0.1388331755 [41] -1.5921303410 -0.2184268516 0.6779862224 0.1378590238 1.2672390187 [46] -0.7280978890 0.0999763556 0.4010308492 -0.2618884823 -0.7784045003 [51] 1.5037007458 -0.2807001848 -0.2420018088 0.8559180564 -0.4196011874 [56] -0.0395039337 0.1122046723 2.7234872115 -0.2538506411 -0.3454625701 [61] 0.9438606685 2.0190309710 -0.0282254627 1.6281879310 -0.1440050512 [66] 1.3279708634 0.2401838796 -0.2281015028 -0.2072203612 -1.4403830419 [71] -0.1931715258 -0.9671143752 -1.0560160864 0.1046998772 1.2372046479 [76] -0.9474614517 -0.2531940896 -0.0404861520 0.4898051864 -0.5716729480 [81] 0.0161397856 -1.0820416616 -0.6366704247 0.2094466179 0.2934562051 [86] -0.2062450718 -0.0376583087 1.0154925564 1.1444409791 -1.3172536012 [91] -0.3933724362 0.2401682180 0.0485576635 -0.8652310672 -1.2428143964 [96] -1.0070868867 -1.1678713041 1.9582896223 0.0074938443 -0.8975789320 > > colMeans(tmp2) [1] 0.09899404 > colSums(tmp2) [1] 9.899404 > colVars(tmp2) [1] 0.7356191 > colSd(tmp2) [1] 0.8576824 > colMax(tmp2) [1] 2.723487 > colMin(tmp2) [1] -1.59213 > colMedians(tmp2) [1] 0.007208561 > colRanges(tmp2) [,1] [1,] -1.592130 [2,] 2.723487 > > 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] -1.4561397 -0.2043599 -2.8670574 0.2756587 -0.1362538 4.4133901 [7] 2.6918190 4.9545906 -1.0960473 1.6684701 > colApply(tmp,quantile)[,1] [,1] [1,] -1.8036923 [2,] -0.3852921 [3,] 0.1140224 [4,] 0.2601340 [5,] 0.4213439 > > rowApply(tmp,sum) [1] -2.1460360 -4.3808990 1.5369824 3.1116398 4.1422539 1.6012183 [7] -0.5334267 5.5931724 -3.0730774 2.3922428 > rowApply(tmp,rank)[1:10,] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 1 8 1 7 4 6 7 4 9 3 [2,] 7 3 3 10 2 1 4 2 4 10 [3,] 6 2 4 8 6 2 2 1 5 6 [4,] 3 10 9 4 7 7 5 6 2 1 [5,] 8 4 6 2 5 4 3 3 8 9 [6,] 2 7 7 5 9 3 9 9 10 8 [7,] 4 6 2 3 8 9 10 7 1 7 [8,] 9 9 8 1 10 5 6 10 7 4 [9,] 5 1 10 6 3 8 1 8 6 2 [10,] 10 5 5 9 1 10 8 5 3 5 > > tmp <- createBufferedMatrix(5,20) > > tmp[1:5,1:20] <- rnorm(100) > colApply(tmp,sum) [1] 5.46965099 0.01502295 -0.02932651 0.13920538 1.81131247 2.72954629 [7] 1.94381269 5.12957347 -0.59572750 -4.45709993 0.11344907 -0.03377761 [13] -1.44970635 6.16226956 -3.08120961 -2.21000758 -0.46879720 -0.61768153 [19] -3.40606177 7.18084317 > colApply(tmp,quantile)[,1] [,1] [1,] -0.01676233 [2,] 0.64155916 [3,] 1.21740359 [4,] 1.59443494 [5,] 2.03301564 > > rowApply(tmp,sum) [1] 5.5357469 2.3553674 6.8040450 -1.0206345 0.6707657 > rowApply(tmp,rank)[1:5,] [,1] [,2] [,3] [,4] [,5] [1,] 12 20 18 10 20 [2,] 17 5 3 16 6 [3,] 11 12 12 8 4 [4,] 19 7 1 13 15 [5,] 7 16 13 18 7 > > > as.matrix(tmp) [,1] [,2] [,3] [,4] [,5] [,6] [1,] 0.64155916 1.0980801 0.6380456 1.513576637 -0.06265223 -0.4063675 [2,] 1.59443494 -0.5535624 0.4407567 0.009929921 0.92480479 1.5880208 [3,] 1.21740359 -0.5937683 0.3548772 -2.579151024 0.39156600 1.1888648 [4,] -0.01676233 0.8185616 -0.4710450 0.304921920 1.14863062 0.6047050 [5,] 2.03301564 -0.7542881 -0.9919610 0.889927925 -0.59103671 -0.2456768 [,7] [,8] [,9] [,10] [,11] [,12] [1,] -0.5680542 0.9971834 0.8507448 -0.40556392 1.4362089 -2.1460231 [2,] 1.4397133 -0.2927167 0.6765391 -2.52737303 0.3430879 0.7032591 [3,] 0.2381884 1.9313137 -1.3367113 -0.18311474 -0.3747148 2.8641297 [4,] 0.3729985 1.2850987 -0.9847330 -1.24453529 -1.6638660 -0.1117766 [5,] 0.4609667 1.2086944 0.1984330 -0.09651296 0.3727331 -1.3433667 [,13] [,14] [,15] [,16] [,17] [,18] [1,] 0.4697256 0.8094144 -0.05113554 0.33037152 -1.0715742 0.6971499 [2,] -2.0459939 0.5720948 -0.56762754 0.32260208 0.2839021 -1.8379542 [3,] -0.1355467 0.9132640 0.25709521 0.07451302 0.1897684 0.2055893 [4,] -0.4877278 2.9025873 0.05845935 -1.63763337 -0.7926438 0.1132231 [5,] 0.7498365 0.9649089 -2.77800109 -1.29986083 0.9217502 0.2043103 [,19] [,20] [1,] -1.7217391 2.4867966 [2,] 0.2861644 0.9952853 [3,] 1.1725022 1.0079762 [4,] -2.2684206 1.0493231 [5,] -0.8745687 1.6414620 > > > 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 : 649 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 : 562 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 0.91566 1.013621 0.5135399 -1.332424 -0.4071551 0.4395599 0.4867319 col8 col9 col10 col11 col12 col13 col14 col15 row1 0.739054 1.074391 -1.79334 0.7835629 -1.196733 1.104377 0.2159109 0.199053 col16 col17 col18 col19 col20 row1 -0.2463785 0.6276322 -1.011726 0.2147811 1.208543 > tmp[,"col10"] col10 row1 -1.79333953 row2 0.44942757 row3 -2.60412401 row4 0.38270370 row5 -0.04902704 > tmp[c("row1","row5"),] col1 col2 col3 col4 col5 col6 col7 row1 0.91566 1.013621 0.5135399 -1.33242433 -0.4071551 0.4395599 0.4867319 row5 1.04224 -1.660834 -0.1820872 0.02550398 -0.1503976 1.3314217 0.9964382 col8 col9 col10 col11 col12 col13 col14 row1 0.7390540 1.074391 -1.79333953 0.78356289 -1.1967330 1.1043769 0.2159109 row5 -0.8525137 1.056364 -0.04902704 0.06152541 0.1148486 -0.4734162 0.9170472 col15 col16 col17 col18 col19 col20 row1 0.1990530 -0.2463785 0.6276322 -1.011726 0.21478112 1.2085431 row5 0.6236217 0.3014254 -0.8029784 1.572599 0.02670133 -0.3409649 > tmp[,c("col6","col20")] col6 col20 row1 0.4395599 1.2085431 row2 0.8277872 -1.3011647 row3 0.1059612 -1.1388523 row4 -1.7362829 1.0895433 row5 1.3314217 -0.3409649 > tmp[c("row1","row5"),c("col6","col20")] col6 col20 row1 0.4395599 1.2085431 row5 1.3314217 -0.3409649 > > > > > 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 50.30283 50.5519 49.04392 49.48171 49.64808 106.1864 50.2553 49.25074 col9 col10 col11 col12 col13 col14 col15 col16 row1 50.81809 51.18926 50.13836 50.62369 49.04589 51.09575 51.08122 48.50987 col17 col18 col19 col20 row1 49.33146 50.77564 50.74741 104.9008 > tmp[,"col10"] col10 row1 51.18926 row2 32.23526 row3 28.45156 row4 29.02954 row5 50.10340 > tmp[c("row1","row5"),] col1 col2 col3 col4 col5 col6 col7 col8 row1 50.30283 50.55190 49.04392 49.48171 49.64808 106.1864 50.25530 49.25074 row5 50.79610 51.24888 51.93404 49.13215 48.17067 104.7817 49.92245 49.46823 col9 col10 col11 col12 col13 col14 col15 col16 row1 50.81809 51.18926 50.13836 50.62369 49.04589 51.09575 51.08122 48.50987 row5 50.55542 50.10340 50.58627 49.70687 50.30865 49.65813 50.37193 49.07809 col17 col18 col19 col20 row1 49.33146 50.77564 50.74741 104.9008 row5 49.16014 51.08631 52.63202 104.3723 > tmp[,c("col6","col20")] col6 col20 row1 106.18642 104.90085 row2 75.43566 75.26388 row3 75.44504 75.89741 row4 73.44241 76.91975 row5 104.78168 104.37228 > tmp[c("row1","row5"),c("col6","col20")] col6 col20 row1 106.1864 104.9008 row5 104.7817 104.3723 > > > subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2] col6 col20 row1 106.1864 104.9008 row5 104.7817 104.3723 > > > > > > tmp <- createBufferedMatrix(5,20) > tmp[1:5,1:20] <- rnorm(100) > colnames(tmp) <- colnames(tmp,do.NULL=FALSE) > > tmp[,"col13"] col13 [1,] 0.5341798 [2,] -1.1677172 [3,] -1.5009553 [4,] -0.5825968 [5,] -1.3954927 > tmp[,c("col17","col7")] col17 col7 [1,] -0.1284007 -0.06256351 [2,] -0.9829497 1.28489554 [3,] -0.6559544 1.28848044 [4,] -1.4902259 -1.02826082 [5,] 0.1091370 1.57684701 > > subBufferedMatrix(tmp,,c("col6","col20"))[,1:2] col6 col20 [1,] 1.7285476 -0.2196226 [2,] -0.1618673 0.5986470 [3,] 0.4863856 -1.4820659 [4,] -0.8646549 -0.3920117 [5,] -0.6052125 1.7176704 > subBufferedMatrix(tmp,1,c("col6"))[,1] col1 [1,] 1.728548 > subBufferedMatrix(tmp,1:2,c("col6"))[,1] col6 [1,] 1.7285476 [2,] -0.1618673 > > > > 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 -2.0514004 0.05376466 2.062462 -0.8229917 -0.2981480 1.0758773 row1 0.2433421 -1.61659460 -0.209417 0.8964720 0.0992871 0.9699916 [,7] [,8] [,9] [,10] [,11] [,12] row3 -0.6769519 0.3573422 0.1085776 -0.5568579 0.3164510 -1.2252551 row1 0.9459126 0.3783012 -0.3914545 0.4979803 -0.1831103 -0.4669484 [,13] [,14] [,15] [,16] [,17] [,18] [,19] row3 0.3530496 0.0378194 0.8352967 0.8789777 1.0622514 -1.235228 0.55226610 row1 -1.1524904 -0.4957508 0.8945188 -1.4284720 0.2207051 0.908102 0.03993803 [,20] row3 1.229295 row1 -1.335531 > subBufferedMatrix(tmp,c("row2"),1:10)[,1:10] [,1] [,2] [,3] [,4] [,5] [,6] [,7] row2 0.6015092 1.133285 0.7686293 -0.6226516 -0.4283825 0.5807063 1.743709 [,8] [,9] [,10] row2 -0.2857724 0.0825321 0.9460803 > subBufferedMatrix(tmp,c("row5"),1:20)[,1:20] [,1] [,2] [,3] [,4] [,5] [,6] row5 0.1119487 -0.3917991 0.05542568 0.01996883 -0.3771538 -0.2020396 [,7] [,8] [,9] [,10] [,11] [,12] [,13] row5 -0.6900567 0.6955126 1.076893 0.4277873 0.7116813 1.325107 0.03134145 [,14] [,15] [,16] [,17] [,18] [,19] [,20] row5 0.9395104 -1.291135 0.1476977 0.3917666 -2.355038 -0.05631661 -0.2686731 > > > 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: 0x600000154000> > is.ReadOnlyMode(tmp) [1] TRUE > > filenames(tmp) [1] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbdc23b8a348d" [2] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbdc26e803384" [3] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbdc222b657c9" [4] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbdc2713d5eec" [5] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbdc274231208" [6] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbdc22a7506c9" [7] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbdc269108be5" [8] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbdc23d509d46" [9] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbdc277857e1c" [10] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbdc25d1a9d91" [11] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbdc27e5eca57" [12] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbdc21365692" [13] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbdc2166d8bdd" [14] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbdc271f965ab" [15] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbdc22c81f802" > > > ### 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: 0x60000017c000> > MoveStorageDirectory(tmp,getwd(),full.path=TRUE) <pointer: 0x60000017c000> Warning message: In dir.create(new.directory) : '/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests' already exists > > > RowMode(tmp) <pointer: 0x60000017c000> > rowMedians(tmp) [1] -0.1055908175 -0.4154212418 0.5931443707 -0.2466680119 -0.0387579391 [6] 0.3879090660 0.0299291821 -0.3960864444 0.4311232609 0.0985969965 [11] -0.2504400541 0.0429395155 -0.3145279649 0.2463741326 0.0180543696 [16] -0.5970083314 0.4944163960 -0.3661340224 -0.0423870614 0.0177932399 [21] 0.3602245771 -0.3246847668 0.0196422618 -0.2463661567 -0.1236427028 [26] 0.3407784441 0.0947190485 0.3116990702 -0.5927287230 -0.0006112559 [31] -0.2189931804 0.1148096692 0.6424845716 -0.6146129750 -0.1587858556 [36] -0.1246848335 -0.0129641470 -0.3484873129 -0.0515924893 -0.2686319182 [41] -0.1049042428 0.2976777873 0.1688795208 -0.4243927327 -0.0203904928 [46] -0.2213973996 -0.2994589156 -0.1389479495 0.0969455456 0.4633770365 [51] 0.1139895778 0.0834955714 0.1283541213 -0.1251598367 -0.2275869073 [56] 0.0388492588 0.0436586359 0.2338647354 -0.3318766440 -0.2809179293 [61] 0.2775175705 -0.3031208962 0.3270878809 -0.2010515762 -0.0429253509 [66] -0.2591848203 -0.1553357866 0.1246158691 -0.1111908277 0.1215996848 [71] 0.5471166479 0.2159895372 0.0260657218 -0.4221850866 0.3575873855 [76] -0.1295289735 -0.3548376942 -0.5378648115 -0.1841538870 0.3214884611 [81] -0.1618255061 0.0497267842 -0.0047742523 0.2899003874 -0.0241533698 [86] -0.3514163200 0.1119130633 0.0042361108 0.3341392374 0.2199123439 [91] -0.0176535313 0.4113090172 -0.6057085099 -0.5650255059 0.4087750888 [96] 0.1580506078 0.2102242912 -0.0718500204 -0.0998198234 -0.6719037460 [101] -0.3052858274 -0.1864267608 -0.2384129284 -0.2309630681 0.1347753863 [106] 0.3829732781 0.0993322943 0.2205522135 0.1061923890 -0.4556228293 [111] -0.5097077386 -0.0125428461 0.0504428407 -0.0919977707 -0.2433769563 [116] -0.0508530355 0.3401995109 0.4598356585 -0.1076353450 0.0376926507 [121] -0.4627328713 0.5690097508 -0.2602629524 -0.2769205970 -0.4531680589 [126] -0.8340889404 -0.2160439723 -0.2598477544 -0.3873493562 -0.1066950240 [131] 0.1908035937 0.0439272514 0.0933020583 -0.1005556759 0.3824444381 [136] 0.0155873860 0.1593386880 -0.3875974274 0.1470698015 0.1026431059 [141] -0.0035904753 0.3473228083 0.1312900102 0.2001159851 0.2231100603 [146] 0.1700891755 -0.2256661898 0.4260655648 0.0157284753 -0.2324513921 [151] -0.0054950964 0.1509355333 -0.3754762428 -0.3515248297 -0.2829816417 [156] 0.1001613405 -0.2214998926 0.0063891811 0.0809534984 0.0956450210 [161] 0.2328839336 0.4681097529 -0.2252238946 -0.5177995343 -0.2847023362 [166] -0.3822727979 0.0861689988 -0.0140121758 0.3989839511 0.5486136796 [171] 0.1132198141 0.4836082026 -0.2103148461 -0.1675731912 0.5517872254 [176] 0.4616208530 0.2151713905 -0.0627269843 0.3937353104 -0.1529619381 [181] 0.1685643344 0.0156660566 0.2343890791 0.1618586032 0.0787521560 [186] 0.1709218372 0.6307586175 0.5642588057 0.2743988904 -0.3963082221 [191] 0.2743521650 0.3769282528 0.1634739302 0.2804845106 -0.7573354295 [196] -0.4637147567 0.1173409927 -0.1568298710 -0.2383746021 0.5625545338 [201] -0.1588095998 0.0582323428 0.2046563767 0.0673051687 -0.1034177190 [206] -0.1928302266 -0.1589639669 -0.3615527285 0.0578040721 0.3420877090 [211] 0.6231964169 0.0551733809 -0.4577202940 0.5699317663 0.0631349486 [216] -0.2682227797 -0.3426374781 0.4248462000 -0.1320238487 -0.1765232571 [221] 0.2806274995 -0.0554639930 -0.0072810722 -0.1822201954 0.0199052223 [226] -0.1918233272 0.4049253951 -1.1480835657 -0.6220699964 0.3024462826 > > proc.time() user system elapsed 2.617 14.784 18.341
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.0 beta (2024-04-14 r86421) -- "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: 0x600001a98000> > .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: 0x600001a98000> > .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: 0x600001a98000> > .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: 0x600001a98000> > 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: 0x600001ad8180> > .Call("R_bm_AddColumn",P) <pointer: 0x600001ad8180> > .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: 0x600001ad8180> > .Call("R_bm_AddColumn",P) <pointer: 0x600001ad8180> > .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: 0x600001ad8180> > 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: 0x600001ad40c0> > .Call("R_bm_AddColumn",P) <pointer: 0x600001ad40c0> > .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: 0x600001ad40c0> > > .Call("R_bm_ResizeBuffer",P,5,5) <pointer: 0x600001ad40c0> > .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: 0x600001ad40c0> > > .Call("R_bm_RowMode",P) <pointer: 0x600001ad40c0> > .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: 0x600001ad40c0> > > .Call("R_bm_ColMode",P) <pointer: 0x600001ad40c0> > .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: 0x600001ad40c0> > 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: 0x600001a90000> > .Call("R_bm_SetPrefix",P,"BufferedMatrixFile") <pointer: 0x600001a90000> > .Call("R_bm_AddColumn",P) <pointer: 0x600001a90000> > .Call("R_bm_AddColumn",P) <pointer: 0x600001a90000> > dir(pattern="BufferedMatrixFile") [1] "BufferedMatrixFilec3ec23e5cc1b" "BufferedMatrixFilec3ec43bb1306" > rm(P) > dir(pattern="BufferedMatrixFile") [1] "BufferedMatrixFilec3ec23e5cc1b" "BufferedMatrixFilec3ec43bb1306" > > > P <- .Call("R_bm_Create",prefix,directory,1,1) > .Call("R_bm_setRows",P,10) [1] TRUE > .Call("R_bm_AddColumn",P) <pointer: 0x600001a90240> > .Call("R_bm_AddColumn",P) <pointer: 0x600001a90240> > .Call("R_bm_ReadOnlyModeToggle",P) <pointer: 0x600001a90240> > .Call("R_bm_isReadOnlyMode",P) [1] TRUE > .Call("R_bm_ReadOnlyModeToggle",P) <pointer: 0x600001a90240> > .Call("R_bm_isReadOnlyMode",P) [1] FALSE > .Call("R_bm_isRowMode",P) [1] FALSE > .Call("R_bm_RowMode",P) <pointer: 0x600001a90240> > .Call("R_bm_isRowMode",P) [1] TRUE > .Call("R_bm_ColMode",P) <pointer: 0x600001a90240> > .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: 0x600001a88240> > .Call("R_bm_AddColumn",P) <pointer: 0x600001a88240> > > .Call("R_bm_getSize",P) [1] 10 2 > .Call("R_bm_getBufferSize",P) [1] 1 1 > .Call("R_bm_ResizeBuffer",P,5,5) <pointer: 0x600001a88240> > > .Call("R_bm_getBufferSize",P) [1] 5 5 > .Call("R_bm_ResizeBuffer",P,-1,5) <pointer: 0x600001a88240> > 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: 0x600001aac000> > .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: 0x600001aac000> > rm(P) > > proc.time() user system elapsed 0.352 0.159 0.502
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.0 beta (2024-04-14 r86421) -- "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 0.347 0.095 0.433