Back to Multiple platform build/check report for BioC 3.16: simplified long |
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This page was generated on 2023-04-12 11:05:27 -0400 (Wed, 12 Apr 2023).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo2 | Linux (Ubuntu 20.04.5 LTS) | x86_64 | 4.2.3 (2023-03-15) -- "Shortstop Beagle" | 4502 |
palomino4 | Windows Server 2022 Datacenter | x64 | 4.2.3 (2023-03-15 ucrt) -- "Shortstop Beagle" | 4282 |
lconway | macOS 12.5.1 Monterey | x86_64 | 4.2.3 (2023-03-15) -- "Shortstop Beagle" | 4310 |
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 |
To the developers/maintainers of the BufferedMatrix package: - Please 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 How and When does the builder pull? When will my changes propagate? for more information. - Make sure to use the following settings in order to reproduce any error or warning you see on this page. |
Package 232/2183 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
BufferedMatrix 1.62.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 20.04.5 LTS) / x86_64 | OK | OK | OK | |||||||||
palomino4 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | |||||||||
lconway | macOS 12.5.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | |||||||||
Package: BufferedMatrix |
Version: 1.62.0 |
Command: F:\biocbuild\bbs-3.16-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=F:\biocbuild\bbs-3.16-bioc\R\library --no-vignettes --timings BufferedMatrix_1.62.0.tar.gz |
StartedAt: 2023-04-10 23:33:20 -0400 (Mon, 10 Apr 2023) |
EndedAt: 2023-04-10 23:35:02 -0400 (Mon, 10 Apr 2023) |
EllapsedTime: 101.5 seconds |
RetCode: 0 |
Status: OK |
CheckDir: BufferedMatrix.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.16-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=F:\biocbuild\bbs-3.16-bioc\R\library --no-vignettes --timings BufferedMatrix_1.62.0.tar.gz ### ############################################################################## ############################################################################## * using log directory 'F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck' * using R version 4.2.3 (2023-03-15 ucrt) * using platform: x86_64-w64-mingw32 (64-bit) * using session charset: UTF-8 * using option '--no-vignettes' * checking for file 'BufferedMatrix/DESCRIPTION' ... OK * this is package 'BufferedMatrix' version '1.62.0' * 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 whether package 'BufferedMatrix' can be installed ... OK * 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 for x64 is not available File 'F:/biocbuild/bbs-3.16-bioc/R/library/BufferedMatrix/libs/x64/BufferedMatrix.dll': Found 'abort', possibly from 'abort' (C), 'runtime' (Fortran) Compiled code should not call entry points which might terminate R nor write to stdout/stderr instead of to the console, nor use Fortran I/O nor system RNGs. The detected symbols are linked into the code but might come from libraries and not actually be called. See 'Writing portable packages' in the 'Writing R Extensions' manual. * 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: 2 NOTEs See 'F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/00check.log' for details.
BufferedMatrix.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.16-bioc\R\bin\R.exe CMD INSTALL BufferedMatrix ### ############################################################################## ############################################################################## * installing to library 'F:/biocbuild/bbs-3.16-bioc/R/library' * installing *source* package 'BufferedMatrix' ... ** using staged installation ** libs gcc -I"F:/biocbuild/bbs-3.16-bioc/R/include" -DNDEBUG -I"C:/rtools42/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -std=gnu99 -mfpmath=sse -msse2 -mstackrealign -c RBufferedMatrix.c -o RBufferedMatrix.o gcc -I"F:/biocbuild/bbs-3.16-bioc/R/include" -DNDEBUG -I"C:/rtools42/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -std=gnu99 -mfpmath=sse -msse2 -mstackrealign -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o doubleBufferedMatrix.c: In function 'dbm_ReadOnlyMode': doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of '!' or change '&' to '&&' or '!' to '~' [-Wparentheses] 1580 | if (!(Matrix->readonly) & setting){ | ^~~~~~~~~~~~~~~~~~~ At top level: doubleBufferedMatrix.c:3327:12: warning: 'sort_double' defined but not used [-Wunused-function] 3327 | static int sort_double(const double *a1,const double *a2){ | ^~~~~~~~~~~ gcc -I"F:/biocbuild/bbs-3.16-bioc/R/include" -DNDEBUG -I"C:/rtools42/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -std=gnu99 -mfpmath=sse -msse2 -mstackrealign -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o gcc -I"F:/biocbuild/bbs-3.16-bioc/R/include" -DNDEBUG -I"C:/rtools42/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -std=gnu99 -mfpmath=sse -msse2 -mstackrealign -c init_package.c -o init_package.o gcc -shared -s -static-libgcc -o BufferedMatrix.dll tmp.def RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -LC:/rtools42/x86_64-w64-mingw32.static.posix/lib/x64 -LC:/rtools42/x86_64-w64-mingw32.static.posix/lib -LF:/biocbuild/bbs-3.16-bioc/R/bin/x64 -lR installing to F:/biocbuild/bbs-3.16-bioc/R/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs/x64 ** 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 ** 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 4.2.3 (2023-03-15 ucrt) -- "Shortstop Beagle" Copyright (C) 2023 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 (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 0.28 0.26 0.70
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.2.3 (2023-03-15 ucrt) -- "Shortstop Beagle" Copyright (C) 2023 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 (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] "F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests" > prefix(tmp3) [1] "BM" > > ## testing if we can remove these objects > rm(tmp, tmp2, tmp3) > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 440029 23.6 946741 50.6 620968 33.2 Vcells 764301 5.9 8388608 64.0 1694585 13.0 > > > > > ## > ## 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] "Mon Apr 10 23:33:47 2023" > 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] "Mon Apr 10 23:33:47 2023" > > > 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: 0x000002b65e719250> > > > > 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] "Mon Apr 10 23:33:59 2023" > 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] "Mon Apr 10 23:34:04 2023" > > ColMode(tmp2) <pointer: 0x000002b65e719250> > > > > ### 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,] 100.65277985 1.24865038 0.1478467 -0.4722071 [2,] 1.05146562 -1.37148942 1.0854372 -1.5186906 [3,] -0.04246878 -1.25095917 3.0546731 -0.4622302 [4,] 1.42703936 0.09114619 -1.4196224 0.1061665 > ewApply(tmp5,abs) BufferedMatrix object Matrix size: 10 20 Buffer size: 1 1 Directory: F:/biocbuild/bbs-3.16-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,] 100.65277985 1.24865038 0.1478467 0.4722071 [2,] 1.05146562 1.37148942 1.0854372 1.5186906 [3,] 0.04246878 1.25095917 3.0546731 0.4622302 [4,] 1.42703936 0.09114619 1.4196224 0.1061665 > ewApply(tmp5,sqrt) BufferedMatrix object Matrix size: 10 20 Buffer size: 1 1 Directory: F:/biocbuild/bbs-3.16-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,] 10.0325859 1.1174303 0.3845084 0.6871732 [2,] 1.0254100 1.1711061 1.0418432 1.2323516 [3,] 0.2060796 1.1184629 1.7477623 0.6798752 [4,] 1.1945875 0.3019043 1.1914791 0.3258321 > > 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: F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 1.9 Kilobytes. Disk usage : 1.6 Kilobytes. > tmp5[1:4,1:4] [,1] [,2] [,3] [,4] [1,] 225.97864 37.42295 28.99293 32.34394 [2,] 36.30557 38.08255 36.50387 38.84221 [3,] 27.10326 37.43559 45.53230 32.26098 [4,] 38.37291 28.11019 38.33441 28.36449 > > > > ## testing functions that elementwise transform the matrix > sqrt(tmp5) <pointer: 0x000002b65e719090> > exp(tmp5) <pointer: 0x000002b65e719090> > log(tmp5,2) <pointer: 0x000002b65e719090> > pow(tmp5,2) > > > > > > ## testing functions that apply to entire matrix > Max(tmp5) [1] 470.3449 > Min(tmp5) [1] 53.29476 > mean(tmp5) [1] 73.42829 > Sum(tmp5) [1] 14685.66 > Var(tmp5) [1] 875.8294 > > > ## testing functions applied to rows or columns > > rowMeans(tmp5) [1] 90.67320 72.70923 72.39501 69.03914 71.26570 69.57655 70.45355 73.55934 [9] 74.35543 70.25576 > rowSums(tmp5) [1] 1813.464 1454.185 1447.900 1380.783 1425.314 1391.531 1409.071 1471.187 [9] 1487.109 1405.115 > rowVars(tmp5) [1] 8044.19353 63.54388 127.11628 98.96742 83.08290 83.28446 [7] 99.89692 51.92702 76.49225 68.29810 > rowSd(tmp5) [1] 89.689428 7.971442 11.274586 9.948237 9.114982 9.126032 9.994845 [8] 7.206041 8.745985 8.264267 > rowMax(tmp5) [1] 470.34493 91.71127 94.76951 88.78223 89.25954 87.67579 88.92632 [8] 84.37564 89.91336 84.26712 > rowMin(tmp5) [1] 60.34499 59.86397 56.41189 55.66048 54.26619 56.11643 53.29476 54.55008 [9] 62.24729 54.76839 > > colMeans(tmp5) [1] 115.96080 73.48210 71.78915 67.95831 70.15903 73.06293 69.88076 [8] 73.94270 68.28434 70.62668 70.90487 72.07293 77.58314 63.74720 [15] 69.93366 71.46046 72.07728 71.40009 70.04136 74.19802 > colSums(tmp5) [1] 1159.6080 734.8210 717.8915 679.5831 701.5903 730.6293 698.8076 [8] 739.4270 682.8434 706.2668 709.0487 720.7293 775.8314 637.4720 [15] 699.3366 714.6046 720.7728 714.0009 700.4136 741.9802 > colVars(tmp5) [1] 15583.47086 61.87640 135.33836 86.04088 46.74019 53.05444 [7] 51.11996 101.98119 120.81014 112.25854 93.96615 41.56701 [13] 82.58741 29.50827 85.68902 88.09516 84.19554 109.48181 [19] 65.94836 50.85019 > colSd(tmp5) [1] 124.833773 7.866155 11.633501 9.275822 6.836680 7.283848 [7] 7.149822 10.098574 10.991367 10.595213 9.693614 6.447248 [13] 9.087762 5.432152 9.256836 9.385902 9.175813 10.463355 [19] 8.120859 7.130932 > colMax(tmp5) [1] 470.34493 84.26712 94.76951 83.32864 81.72277 84.37564 80.86726 [8] 83.61714 89.02490 89.91336 88.56322 81.55844 91.71127 73.43190 [15] 83.17360 91.04287 88.78223 93.55331 86.31289 85.40859 > colMin(tmp5) [1] 56.41189 58.50768 53.29476 54.33123 60.13108 62.14335 59.16625 54.76839 [9] 54.55008 55.82751 57.35981 59.86430 62.24729 54.26619 56.11643 62.50222 [17] 61.49149 62.88553 61.35417 59.14908 > > > ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default) > > > which.row <- sample(1:10,1,replace=TRUE) > which.col <- sample(1:20,1,replace=TRUE) > > tmp5[which.row,which.col] <- NA > > Max(tmp5) [1] NA > Min(tmp5) [1] NA > mean(tmp5) [1] NA > Sum(tmp5) [1] NA > Var(tmp5) [1] NA > > rowMeans(tmp5) [1] 90.67320 72.70923 72.39501 69.03914 71.26570 69.57655 70.45355 NA [9] 74.35543 70.25576 > rowSums(tmp5) [1] 1813.464 1454.185 1447.900 1380.783 1425.314 1391.531 1409.071 NA [9] 1487.109 1405.115 > rowVars(tmp5) [1] 8044.19353 63.54388 127.11628 98.96742 83.08290 83.28446 [7] 99.89692 49.40636 76.49225 68.29810 > rowSd(tmp5) [1] 89.689428 7.971442 11.274586 9.948237 9.114982 9.126032 9.994845 [8] 7.028966 8.745985 8.264267 > rowMax(tmp5) [1] 470.34493 91.71127 94.76951 88.78223 89.25954 87.67579 88.92632 [8] NA 89.91336 84.26712 > rowMin(tmp5) [1] 60.34499 59.86397 56.41189 55.66048 54.26619 56.11643 53.29476 NA [9] 62.24729 54.76839 > > colMeans(tmp5) [1] 115.96080 73.48210 71.78915 67.95831 70.15903 73.06293 69.88076 [8] 73.94270 68.28434 70.62668 70.90487 72.07293 77.58314 63.74720 [15] NA 71.46046 72.07728 71.40009 70.04136 74.19802 > colSums(tmp5) [1] 1159.6080 734.8210 717.8915 679.5831 701.5903 730.6293 698.8076 [8] 739.4270 682.8434 706.2668 709.0487 720.7293 775.8314 637.4720 [15] NA 714.6046 720.7728 714.0009 700.4136 741.9802 > colVars(tmp5) [1] 15583.47086 61.87640 135.33836 86.04088 46.74019 53.05444 [7] 51.11996 101.98119 120.81014 112.25854 93.96615 41.56701 [13] 82.58741 29.50827 NA 88.09516 84.19554 109.48181 [19] 65.94836 50.85019 > colSd(tmp5) [1] 124.833773 7.866155 11.633501 9.275822 6.836680 7.283848 [7] 7.149822 10.098574 10.991367 10.595213 9.693614 6.447248 [13] 9.087762 5.432152 NA 9.385902 9.175813 10.463355 [19] 8.120859 7.130932 > colMax(tmp5) [1] 470.34493 84.26712 94.76951 83.32864 81.72277 84.37564 80.86726 [8] 83.61714 89.02490 89.91336 88.56322 81.55844 91.71127 73.43190 [15] NA 91.04287 88.78223 93.55331 86.31289 85.40859 > colMin(tmp5) [1] 56.41189 58.50768 53.29476 54.33123 60.13108 62.14335 59.16625 54.76839 [9] 54.55008 55.82751 57.35981 59.86430 62.24729 54.26619 NA 62.50222 [17] 61.49149 62.88553 61.35417 59.14908 > > Max(tmp5,na.rm=TRUE) [1] 470.3449 > Min(tmp5,na.rm=TRUE) [1] 53.29476 > mean(tmp5,na.rm=TRUE) [1] 73.37932 > Sum(tmp5,na.rm=TRUE) [1] 14602.48 > Var(tmp5,na.rm=TRUE) [1] 879.7707 > > rowMeans(tmp5,na.rm=TRUE) [1] 90.67320 72.70923 72.39501 69.03914 71.26570 69.57655 70.45355 73.05333 [9] 74.35543 70.25576 > rowSums(tmp5,na.rm=TRUE) [1] 1813.464 1454.185 1447.900 1380.783 1425.314 1391.531 1409.071 1388.013 [9] 1487.109 1405.115 > rowVars(tmp5,na.rm=TRUE) [1] 8044.19353 63.54388 127.11628 98.96742 83.08290 83.28446 [7] 99.89692 49.40636 76.49225 68.29810 > rowSd(tmp5,na.rm=TRUE) [1] 89.689428 7.971442 11.274586 9.948237 9.114982 9.126032 9.994845 [8] 7.028966 8.745985 8.264267 > rowMax(tmp5,na.rm=TRUE) [1] 470.34493 91.71127 94.76951 88.78223 89.25954 87.67579 88.92632 [8] 84.37564 89.91336 84.26712 > rowMin(tmp5,na.rm=TRUE) [1] 60.34499 59.86397 56.41189 55.66048 54.26619 56.11643 53.29476 54.55008 [9] 62.24729 54.76839 > > colMeans(tmp5,na.rm=TRUE) [1] 115.96080 73.48210 71.78915 67.95831 70.15903 73.06293 69.88076 [8] 73.94270 68.28434 70.62668 70.90487 72.07293 77.58314 63.74720 [15] 68.46256 71.46046 72.07728 71.40009 70.04136 74.19802 > colSums(tmp5,na.rm=TRUE) [1] 1159.6080 734.8210 717.8915 679.5831 701.5903 730.6293 698.8076 [8] 739.4270 682.8434 706.2668 709.0487 720.7293 775.8314 637.4720 [15] 616.1630 714.6046 720.7728 714.0009 700.4136 741.9802 > colVars(tmp5,na.rm=TRUE) [1] 15583.47086 61.87640 135.33836 86.04088 46.74019 53.05444 [7] 51.11996 101.98119 120.81014 112.25854 93.96615 41.56701 [13] 82.58741 29.50827 72.05349 88.09516 84.19554 109.48181 [19] 65.94836 50.85019 > colSd(tmp5,na.rm=TRUE) [1] 124.833773 7.866155 11.633501 9.275822 6.836680 7.283848 [7] 7.149822 10.098574 10.991367 10.595213 9.693614 6.447248 [13] 9.087762 5.432152 8.488433 9.385902 9.175813 10.463355 [19] 8.120859 7.130932 > colMax(tmp5,na.rm=TRUE) [1] 470.34493 84.26712 94.76951 83.32864 81.72277 84.37564 80.86726 [8] 83.61714 89.02490 89.91336 88.56322 81.55844 91.71127 73.43190 [15] 78.11853 91.04287 88.78223 93.55331 86.31289 85.40859 > colMin(tmp5,na.rm=TRUE) [1] 56.41189 58.50768 53.29476 54.33123 60.13108 62.14335 59.16625 54.76839 [9] 54.55008 55.82751 57.35981 59.86430 62.24729 54.26619 56.11643 62.50222 [17] 61.49149 62.88553 61.35417 59.14908 > > # now set an entire row to NA > > tmp5[which.row,] <- NA > rowMeans(tmp5,na.rm=TRUE) [1] 90.67320 72.70923 72.39501 69.03914 71.26570 69.57655 70.45355 NaN [9] 74.35543 70.25576 > rowSums(tmp5,na.rm=TRUE) [1] 1813.464 1454.185 1447.900 1380.783 1425.314 1391.531 1409.071 0.000 [9] 1487.109 1405.115 > rowVars(tmp5,na.rm=TRUE) [1] 8044.19353 63.54388 127.11628 98.96742 83.08290 83.28446 [7] 99.89692 NA 76.49225 68.29810 > rowSd(tmp5,na.rm=TRUE) [1] 89.689428 7.971442 11.274586 9.948237 9.114982 9.126032 9.994845 [8] NA 8.745985 8.264267 > rowMax(tmp5,na.rm=TRUE) [1] 470.34493 91.71127 94.76951 88.78223 89.25954 87.67579 88.92632 [8] NA 89.91336 84.26712 > rowMin(tmp5,na.rm=TRUE) [1] 60.34499 59.86397 56.41189 55.66048 54.26619 56.11643 53.29476 NA [9] 62.24729 54.76839 > > > # now set an entire col to NA > > > tmp5[,which.col] <- NA > colMeans(tmp5,na.rm=TRUE) [1] 120.12983 73.38032 71.16786 66.25049 70.10994 71.80596 69.50847 [8] 73.85017 69.81037 70.81803 71.26465 71.01898 78.64269 62.67113 [15] NaN 71.68330 72.00874 72.23314 69.48481 73.97315 > colSums(tmp5,na.rm=TRUE) [1] 1081.1685 660.4229 640.5108 596.2544 630.9894 646.2537 625.5762 [8] 664.6515 628.2933 637.3622 641.3818 639.1709 707.7842 564.0401 [15] 0.0000 645.1497 648.0787 650.0983 625.3633 665.7583 > colVars(tmp5,na.rm=TRUE) [1] 17335.87004 69.49442 147.91315 63.98389 52.55560 41.91162 [7] 55.95068 114.63251 109.71280 125.87896 104.25570 34.26636 [13] 80.28112 20.16996 NA 98.54842 94.66715 115.35972 [19] 70.70721 56.63755 > colSd(tmp5,na.rm=TRUE) [1] 131.665751 8.336331 12.161955 7.998993 7.249524 6.473918 [7] 7.480019 10.706657 10.474388 11.219579 10.210568 5.853747 [13] 8.959973 4.491098 NA 9.927155 9.729704 10.740564 [19] 8.408758 7.525793 > colMax(tmp5,na.rm=TRUE) [1] 470.34493 84.26712 94.76951 80.84496 81.72277 79.74856 80.86726 [8] 83.61714 89.02490 89.91336 88.56322 77.58731 91.71127 67.39480 [15] -Inf 91.04287 88.78223 93.55331 86.31289 85.40859 > colMin(tmp5,na.rm=TRUE) [1] 56.41189 58.50768 53.29476 54.33123 60.13108 62.14335 59.16625 54.76839 [9] 55.66048 55.82751 57.35981 59.86430 62.24729 54.26619 Inf 62.50222 [17] 61.49149 62.88553 61.35417 59.14908 > > > > > 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] 112.6841 233.1177 173.8788 212.5892 130.2877 332.6040 200.3115 189.9965 [9] 206.4064 292.1363 > apply(copymatrix,1,var,na.rm=TRUE) [1] 112.6841 233.1177 173.8788 212.5892 130.2877 332.6040 200.3115 189.9965 [9] 206.4064 292.1363 > > > > 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-13 5.684342e-14 -1.136868e-13 5.684342e-14 2.842171e-14 [6] 8.526513e-14 1.136868e-13 1.136868e-13 -8.526513e-14 8.526513e-14 [11] -2.273737e-13 5.684342e-14 1.136868e-13 -1.421085e-13 0.000000e+00 [16] -2.842171e-14 1.136868e-13 2.842171e-14 2.842171e-14 -1.136868e-13 > > > > > > > > > > > ## making sure these things agree > ## > ## first when there is no NA > > > > agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){ + + if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){ + stop("No agreement in Max") + } + + + if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){ + stop("No agreement in Min") + } + + + if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){ + + cat(Sum(buff.matrix,na.rm=TRUE),"\n") + cat(sum(r.matrix,na.rm=TRUE),"\n") + cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n") + + stop("No agreement in Sum") + } + + if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){ + stop("No agreement in mean") + } + + + if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){ + stop("No agreement in Var") + } + + + + if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in rowMeans") + } + + + if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){ + stop("No agreement in colMeans") + } + + + if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){ + stop("No agreement in rowSums") + } + + + if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){ + stop("No agreement in colSums") + } + + ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when + ### computing variance + my.Var <- function(x,na.rm=FALSE){ + if (all(is.na(x))){ + return(NA) + } else { + var(x,na.rm=na.rm) + } + + } + + if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in rowVars") + } + + + if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in rowVars") + } + + + if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colMax") + } + + + if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colMax") + } + + + + if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colMin") + } + + + if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colMin") + } + + if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colMedian") + } + + if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){ + stop("No agreement in colRanges") + } + + + + } > > > > > > > > > > for (rep in 1:20){ + copymatrix <- matrix(rnorm(200,150,15),10,20) + + tmp5[1:10,1:20] <- copymatrix + + + agree.checks(tmp5,copymatrix) + + ## now lets assign some NA values and check agreement + + which.row <- sample(1:10,1,replace=TRUE) + which.col <- sample(1:20,1,replace=TRUE) + + cat(which.row," ",which.col,"\n") + + tmp5[which.row,which.col] <- NA + copymatrix[which.row,which.col] <- NA + + agree.checks(tmp5,copymatrix) + + ## make an entire row NA + tmp5[which.row,] <- NA + copymatrix[which.row,] <- NA + + + agree.checks(tmp5,copymatrix) + + ### also make an entire col NA + tmp5[,which.col] <- NA + copymatrix[,which.col] <- NA + + agree.checks(tmp5,copymatrix) + + ### now make 1 element non NA with NA in the rest of row and column + + tmp5[which.row,which.col] <- rnorm(1,150,15) + copymatrix[which.row,which.col] <- tmp5[which.row,which.col] + + agree.checks(tmp5,copymatrix) + } 3 19 10 18 4 10 6 1 7 16 1 7 9 7 1 7 5 20 2 8 1 19 7 5 9 7 6 18 1 14 6 13 8 8 3 9 9 7 9 15 There were 50 or more warnings (use warnings() to see the first 50) > > > ### now test 1 by n and n by 1 matrix > > > err.tol <- 1e-12 > > rm(tmp5) > > dataset1 <- rnorm(100) > dataset2 <- rnorm(100) > > tmp <- createBufferedMatrix(1,100) > tmp[1,] <- dataset1 > > tmp2 <- createBufferedMatrix(100,1) > tmp2[,1] <- dataset2 > > > > > > Max(tmp) [1] 1.553101 > Min(tmp) [1] -2.519899 > mean(tmp) [1] -0.1256883 > Sum(tmp) [1] -12.56883 > Var(tmp) [1] 0.8747437 > > rowMeans(tmp) [1] -0.1256883 > rowSums(tmp) [1] -12.56883 > rowVars(tmp) [1] 0.8747437 > rowSd(tmp) [1] 0.9352773 > rowMax(tmp) [1] 1.553101 > rowMin(tmp) [1] -2.519899 > > colMeans(tmp) [1] 0.36533150 0.09606835 -1.19993481 0.54513445 1.24953868 -2.22884576 [7] 0.79047025 -1.54151841 0.74727111 0.23628532 -0.86196602 -0.40401031 [13] 0.27912996 0.97853767 1.29510530 -1.78367727 0.79566387 -0.33215396 [19] 0.97252922 1.03916799 -0.42127592 1.00393160 -0.07120814 -1.28999178 [25] -1.36659710 0.18841876 -1.77962347 1.31339534 -0.62239333 -0.90372563 [31] 0.22028903 -0.68336023 -1.49808783 0.33951757 0.44506656 0.65517220 [37] 0.34927434 -0.41294299 -0.26716591 0.08566548 0.14210109 0.25300704 [43] -1.01690564 0.77798010 0.21705722 -0.90197572 0.67393295 -1.38564720 [49] 0.22524204 -1.05939230 -0.13462977 1.02731836 0.04855145 0.92250508 [55] -0.57306508 0.34611075 0.35014905 -1.68645498 -0.38688556 -0.74500720 [61] -0.71234984 0.22796665 -1.49991918 0.53308607 -0.51864912 -2.51989903 [67] -1.07809246 0.22172624 -0.41862776 0.13502938 -0.45570094 -1.79707442 [73] -0.11319502 -0.85161210 -0.27032443 1.21511559 0.16459494 0.30499720 [79] 0.71130715 1.51775855 1.55310091 1.23614932 -1.26378623 -0.80090286 [85] 1.07808403 -0.17562388 -0.66158462 0.38675000 0.42638025 0.39801360 [91] -0.09446267 0.07192228 -1.72140737 -1.47318111 1.04320456 0.64196210 [97] 0.98558490 -0.30211098 -0.14000652 -1.96952875 > colSums(tmp) [1] 0.36533150 0.09606835 -1.19993481 0.54513445 1.24953868 -2.22884576 [7] 0.79047025 -1.54151841 0.74727111 0.23628532 -0.86196602 -0.40401031 [13] 0.27912996 0.97853767 1.29510530 -1.78367727 0.79566387 -0.33215396 [19] 0.97252922 1.03916799 -0.42127592 1.00393160 -0.07120814 -1.28999178 [25] -1.36659710 0.18841876 -1.77962347 1.31339534 -0.62239333 -0.90372563 [31] 0.22028903 -0.68336023 -1.49808783 0.33951757 0.44506656 0.65517220 [37] 0.34927434 -0.41294299 -0.26716591 0.08566548 0.14210109 0.25300704 [43] -1.01690564 0.77798010 0.21705722 -0.90197572 0.67393295 -1.38564720 [49] 0.22524204 -1.05939230 -0.13462977 1.02731836 0.04855145 0.92250508 [55] -0.57306508 0.34611075 0.35014905 -1.68645498 -0.38688556 -0.74500720 [61] -0.71234984 0.22796665 -1.49991918 0.53308607 -0.51864912 -2.51989903 [67] -1.07809246 0.22172624 -0.41862776 0.13502938 -0.45570094 -1.79707442 [73] -0.11319502 -0.85161210 -0.27032443 1.21511559 0.16459494 0.30499720 [79] 0.71130715 1.51775855 1.55310091 1.23614932 -1.26378623 -0.80090286 [85] 1.07808403 -0.17562388 -0.66158462 0.38675000 0.42638025 0.39801360 [91] -0.09446267 0.07192228 -1.72140737 -1.47318111 1.04320456 0.64196210 [97] 0.98558490 -0.30211098 -0.14000652 -1.96952875 > 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] 0.36533150 0.09606835 -1.19993481 0.54513445 1.24953868 -2.22884576 [7] 0.79047025 -1.54151841 0.74727111 0.23628532 -0.86196602 -0.40401031 [13] 0.27912996 0.97853767 1.29510530 -1.78367727 0.79566387 -0.33215396 [19] 0.97252922 1.03916799 -0.42127592 1.00393160 -0.07120814 -1.28999178 [25] -1.36659710 0.18841876 -1.77962347 1.31339534 -0.62239333 -0.90372563 [31] 0.22028903 -0.68336023 -1.49808783 0.33951757 0.44506656 0.65517220 [37] 0.34927434 -0.41294299 -0.26716591 0.08566548 0.14210109 0.25300704 [43] -1.01690564 0.77798010 0.21705722 -0.90197572 0.67393295 -1.38564720 [49] 0.22524204 -1.05939230 -0.13462977 1.02731836 0.04855145 0.92250508 [55] -0.57306508 0.34611075 0.35014905 -1.68645498 -0.38688556 -0.74500720 [61] -0.71234984 0.22796665 -1.49991918 0.53308607 -0.51864912 -2.51989903 [67] -1.07809246 0.22172624 -0.41862776 0.13502938 -0.45570094 -1.79707442 [73] -0.11319502 -0.85161210 -0.27032443 1.21511559 0.16459494 0.30499720 [79] 0.71130715 1.51775855 1.55310091 1.23614932 -1.26378623 -0.80090286 [85] 1.07808403 -0.17562388 -0.66158462 0.38675000 0.42638025 0.39801360 [91] -0.09446267 0.07192228 -1.72140737 -1.47318111 1.04320456 0.64196210 [97] 0.98558490 -0.30211098 -0.14000652 -1.96952875 > colMin(tmp) [1] 0.36533150 0.09606835 -1.19993481 0.54513445 1.24953868 -2.22884576 [7] 0.79047025 -1.54151841 0.74727111 0.23628532 -0.86196602 -0.40401031 [13] 0.27912996 0.97853767 1.29510530 -1.78367727 0.79566387 -0.33215396 [19] 0.97252922 1.03916799 -0.42127592 1.00393160 -0.07120814 -1.28999178 [25] -1.36659710 0.18841876 -1.77962347 1.31339534 -0.62239333 -0.90372563 [31] 0.22028903 -0.68336023 -1.49808783 0.33951757 0.44506656 0.65517220 [37] 0.34927434 -0.41294299 -0.26716591 0.08566548 0.14210109 0.25300704 [43] -1.01690564 0.77798010 0.21705722 -0.90197572 0.67393295 -1.38564720 [49] 0.22524204 -1.05939230 -0.13462977 1.02731836 0.04855145 0.92250508 [55] -0.57306508 0.34611075 0.35014905 -1.68645498 -0.38688556 -0.74500720 [61] -0.71234984 0.22796665 -1.49991918 0.53308607 -0.51864912 -2.51989903 [67] -1.07809246 0.22172624 -0.41862776 0.13502938 -0.45570094 -1.79707442 [73] -0.11319502 -0.85161210 -0.27032443 1.21511559 0.16459494 0.30499720 [79] 0.71130715 1.51775855 1.55310091 1.23614932 -1.26378623 -0.80090286 [85] 1.07808403 -0.17562388 -0.66158462 0.38675000 0.42638025 0.39801360 [91] -0.09446267 0.07192228 -1.72140737 -1.47318111 1.04320456 0.64196210 [97] 0.98558490 -0.30211098 -0.14000652 -1.96952875 > colMedians(tmp) [1] 0.36533150 0.09606835 -1.19993481 0.54513445 1.24953868 -2.22884576 [7] 0.79047025 -1.54151841 0.74727111 0.23628532 -0.86196602 -0.40401031 [13] 0.27912996 0.97853767 1.29510530 -1.78367727 0.79566387 -0.33215396 [19] 0.97252922 1.03916799 -0.42127592 1.00393160 -0.07120814 -1.28999178 [25] -1.36659710 0.18841876 -1.77962347 1.31339534 -0.62239333 -0.90372563 [31] 0.22028903 -0.68336023 -1.49808783 0.33951757 0.44506656 0.65517220 [37] 0.34927434 -0.41294299 -0.26716591 0.08566548 0.14210109 0.25300704 [43] -1.01690564 0.77798010 0.21705722 -0.90197572 0.67393295 -1.38564720 [49] 0.22524204 -1.05939230 -0.13462977 1.02731836 0.04855145 0.92250508 [55] -0.57306508 0.34611075 0.35014905 -1.68645498 -0.38688556 -0.74500720 [61] -0.71234984 0.22796665 -1.49991918 0.53308607 -0.51864912 -2.51989903 [67] -1.07809246 0.22172624 -0.41862776 0.13502938 -0.45570094 -1.79707442 [73] -0.11319502 -0.85161210 -0.27032443 1.21511559 0.16459494 0.30499720 [79] 0.71130715 1.51775855 1.55310091 1.23614932 -1.26378623 -0.80090286 [85] 1.07808403 -0.17562388 -0.66158462 0.38675000 0.42638025 0.39801360 [91] -0.09446267 0.07192228 -1.72140737 -1.47318111 1.04320456 0.64196210 [97] 0.98558490 -0.30211098 -0.14000652 -1.96952875 > colRanges(tmp) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [1,] 0.3653315 0.09606835 -1.199935 0.5451344 1.249539 -2.228846 0.7904702 [2,] 0.3653315 0.09606835 -1.199935 0.5451344 1.249539 -2.228846 0.7904702 [,8] [,9] [,10] [,11] [,12] [,13] [,14] [1,] -1.541518 0.7472711 0.2362853 -0.861966 -0.4040103 0.27913 0.9785377 [2,] -1.541518 0.7472711 0.2362853 -0.861966 -0.4040103 0.27913 0.9785377 [,15] [,16] [,17] [,18] [,19] [,20] [,21] [1,] 1.295105 -1.783677 0.7956639 -0.332154 0.9725292 1.039168 -0.4212759 [2,] 1.295105 -1.783677 0.7956639 -0.332154 0.9725292 1.039168 -0.4212759 [,22] [,23] [,24] [,25] [,26] [,27] [,28] [1,] 1.003932 -0.07120814 -1.289992 -1.366597 0.1884188 -1.779623 1.313395 [2,] 1.003932 -0.07120814 -1.289992 -1.366597 0.1884188 -1.779623 1.313395 [,29] [,30] [,31] [,32] [,33] [,34] [,35] [1,] -0.6223933 -0.9037256 0.220289 -0.6833602 -1.498088 0.3395176 0.4450666 [2,] -0.6223933 -0.9037256 0.220289 -0.6833602 -1.498088 0.3395176 0.4450666 [,36] [,37] [,38] [,39] [,40] [,41] [,42] [1,] 0.6551722 0.3492743 -0.412943 -0.2671659 0.08566548 0.1421011 0.253007 [2,] 0.6551722 0.3492743 -0.412943 -0.2671659 0.08566548 0.1421011 0.253007 [,43] [,44] [,45] [,46] [,47] [,48] [,49] [1,] -1.016906 0.7779801 0.2170572 -0.9019757 0.6739329 -1.385647 0.225242 [2,] -1.016906 0.7779801 0.2170572 -0.9019757 0.6739329 -1.385647 0.225242 [,50] [,51] [,52] [,53] [,54] [,55] [,56] [1,] -1.059392 -0.1346298 1.027318 0.04855145 0.9225051 -0.5730651 0.3461107 [2,] -1.059392 -0.1346298 1.027318 0.04855145 0.9225051 -0.5730651 0.3461107 [,57] [,58] [,59] [,60] [,61] [,62] [,63] [1,] 0.3501491 -1.686455 -0.3868856 -0.7450072 -0.7123498 0.2279666 -1.499919 [2,] 0.3501491 -1.686455 -0.3868856 -0.7450072 -0.7123498 0.2279666 -1.499919 [,64] [,65] [,66] [,67] [,68] [,69] [,70] [1,] 0.5330861 -0.5186491 -2.519899 -1.078092 0.2217262 -0.4186278 0.1350294 [2,] 0.5330861 -0.5186491 -2.519899 -1.078092 0.2217262 -0.4186278 0.1350294 [,71] [,72] [,73] [,74] [,75] [,76] [,77] [1,] -0.4557009 -1.797074 -0.113195 -0.8516121 -0.2703244 1.215116 0.1645949 [2,] -0.4557009 -1.797074 -0.113195 -0.8516121 -0.2703244 1.215116 0.1645949 [,78] [,79] [,80] [,81] [,82] [,83] [,84] [1,] 0.3049972 0.7113072 1.517759 1.553101 1.236149 -1.263786 -0.8009029 [2,] 0.3049972 0.7113072 1.517759 1.553101 1.236149 -1.263786 -0.8009029 [,85] [,86] [,87] [,88] [,89] [,90] [,91] [1,] 1.078084 -0.1756239 -0.6615846 0.38675 0.4263803 0.3980136 -0.09446267 [2,] 1.078084 -0.1756239 -0.6615846 0.38675 0.4263803 0.3980136 -0.09446267 [,92] [,93] [,94] [,95] [,96] [,97] [,98] [1,] 0.07192228 -1.721407 -1.473181 1.043205 0.6419621 0.9855849 -0.302111 [2,] 0.07192228 -1.721407 -1.473181 1.043205 0.6419621 0.9855849 -0.302111 [,99] [,100] [1,] -0.1400065 -1.969529 [2,] -0.1400065 -1.969529 > > > Max(tmp2) [1] 2.802377 > Min(tmp2) [1] -2.34141 > mean(tmp2) [1] -0.04032177 > Sum(tmp2) [1] -4.032177 > Var(tmp2) [1] 0.830513 > > rowMeans(tmp2) [1] -0.17952836 -1.11640238 -0.49174094 1.23540712 0.08210073 -0.57180443 [7] 0.10793968 -0.44909324 -2.34141009 0.98270492 1.54170008 -0.90823731 [13] 1.48900470 -0.95233636 0.54243649 -0.05222727 -0.83141267 -0.51385131 [19] -0.78699581 -1.80112234 1.08591961 0.04362514 0.14298916 -0.73108558 [25] 0.13508237 -0.65379002 -0.63476886 0.84941816 0.46507428 -0.85265514 [31] -1.28007680 -0.42721784 -0.03500034 -1.84994350 0.14330394 0.67374839 [37] 1.74889007 -1.28940755 -1.02446348 0.38267277 1.19116710 -0.44050986 [43] 0.45742452 1.07801708 0.11552473 0.43077419 0.94588309 -0.40014336 [49] -0.36349241 0.43092343 0.21234116 -0.33732163 -0.24699842 -0.20087869 [55] 1.57923805 -0.84623970 -1.28592407 -1.15147864 0.09227707 -0.80490045 [61] 1.19487847 -0.73526526 0.21121826 -0.76803311 -0.42121188 0.83947706 [67] -2.01656551 0.23677205 -0.19508889 -0.31913718 0.78815756 0.44979993 [73] 0.59336965 1.41936550 -0.32040991 0.40988062 0.37484837 1.50122430 [79] -0.23569424 -0.45991669 0.77242896 -1.22750919 -0.24071634 0.47277550 [85] -0.99803708 0.02496479 -0.80165237 -0.62277937 -0.63189713 -0.32735045 [91] -1.14730583 2.80237679 0.74340228 -0.38868047 0.24387587 -0.01721434 [97] -0.72825204 1.17950446 0.37665765 1.60243333 > rowSums(tmp2) [1] -0.17952836 -1.11640238 -0.49174094 1.23540712 0.08210073 -0.57180443 [7] 0.10793968 -0.44909324 -2.34141009 0.98270492 1.54170008 -0.90823731 [13] 1.48900470 -0.95233636 0.54243649 -0.05222727 -0.83141267 -0.51385131 [19] -0.78699581 -1.80112234 1.08591961 0.04362514 0.14298916 -0.73108558 [25] 0.13508237 -0.65379002 -0.63476886 0.84941816 0.46507428 -0.85265514 [31] -1.28007680 -0.42721784 -0.03500034 -1.84994350 0.14330394 0.67374839 [37] 1.74889007 -1.28940755 -1.02446348 0.38267277 1.19116710 -0.44050986 [43] 0.45742452 1.07801708 0.11552473 0.43077419 0.94588309 -0.40014336 [49] -0.36349241 0.43092343 0.21234116 -0.33732163 -0.24699842 -0.20087869 [55] 1.57923805 -0.84623970 -1.28592407 -1.15147864 0.09227707 -0.80490045 [61] 1.19487847 -0.73526526 0.21121826 -0.76803311 -0.42121188 0.83947706 [67] -2.01656551 0.23677205 -0.19508889 -0.31913718 0.78815756 0.44979993 [73] 0.59336965 1.41936550 -0.32040991 0.40988062 0.37484837 1.50122430 [79] -0.23569424 -0.45991669 0.77242896 -1.22750919 -0.24071634 0.47277550 [85] -0.99803708 0.02496479 -0.80165237 -0.62277937 -0.63189713 -0.32735045 [91] -1.14730583 2.80237679 0.74340228 -0.38868047 0.24387587 -0.01721434 [97] -0.72825204 1.17950446 0.37665765 1.60243333 > 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] -0.17952836 -1.11640238 -0.49174094 1.23540712 0.08210073 -0.57180443 [7] 0.10793968 -0.44909324 -2.34141009 0.98270492 1.54170008 -0.90823731 [13] 1.48900470 -0.95233636 0.54243649 -0.05222727 -0.83141267 -0.51385131 [19] -0.78699581 -1.80112234 1.08591961 0.04362514 0.14298916 -0.73108558 [25] 0.13508237 -0.65379002 -0.63476886 0.84941816 0.46507428 -0.85265514 [31] -1.28007680 -0.42721784 -0.03500034 -1.84994350 0.14330394 0.67374839 [37] 1.74889007 -1.28940755 -1.02446348 0.38267277 1.19116710 -0.44050986 [43] 0.45742452 1.07801708 0.11552473 0.43077419 0.94588309 -0.40014336 [49] -0.36349241 0.43092343 0.21234116 -0.33732163 -0.24699842 -0.20087869 [55] 1.57923805 -0.84623970 -1.28592407 -1.15147864 0.09227707 -0.80490045 [61] 1.19487847 -0.73526526 0.21121826 -0.76803311 -0.42121188 0.83947706 [67] -2.01656551 0.23677205 -0.19508889 -0.31913718 0.78815756 0.44979993 [73] 0.59336965 1.41936550 -0.32040991 0.40988062 0.37484837 1.50122430 [79] -0.23569424 -0.45991669 0.77242896 -1.22750919 -0.24071634 0.47277550 [85] -0.99803708 0.02496479 -0.80165237 -0.62277937 -0.63189713 -0.32735045 [91] -1.14730583 2.80237679 0.74340228 -0.38868047 0.24387587 -0.01721434 [97] -0.72825204 1.17950446 0.37665765 1.60243333 > rowMin(tmp2) [1] -0.17952836 -1.11640238 -0.49174094 1.23540712 0.08210073 -0.57180443 [7] 0.10793968 -0.44909324 -2.34141009 0.98270492 1.54170008 -0.90823731 [13] 1.48900470 -0.95233636 0.54243649 -0.05222727 -0.83141267 -0.51385131 [19] -0.78699581 -1.80112234 1.08591961 0.04362514 0.14298916 -0.73108558 [25] 0.13508237 -0.65379002 -0.63476886 0.84941816 0.46507428 -0.85265514 [31] -1.28007680 -0.42721784 -0.03500034 -1.84994350 0.14330394 0.67374839 [37] 1.74889007 -1.28940755 -1.02446348 0.38267277 1.19116710 -0.44050986 [43] 0.45742452 1.07801708 0.11552473 0.43077419 0.94588309 -0.40014336 [49] -0.36349241 0.43092343 0.21234116 -0.33732163 -0.24699842 -0.20087869 [55] 1.57923805 -0.84623970 -1.28592407 -1.15147864 0.09227707 -0.80490045 [61] 1.19487847 -0.73526526 0.21121826 -0.76803311 -0.42121188 0.83947706 [67] -2.01656551 0.23677205 -0.19508889 -0.31913718 0.78815756 0.44979993 [73] 0.59336965 1.41936550 -0.32040991 0.40988062 0.37484837 1.50122430 [79] -0.23569424 -0.45991669 0.77242896 -1.22750919 -0.24071634 0.47277550 [85] -0.99803708 0.02496479 -0.80165237 -0.62277937 -0.63189713 -0.32735045 [91] -1.14730583 2.80237679 0.74340228 -0.38868047 0.24387587 -0.01721434 [97] -0.72825204 1.17950446 0.37665765 1.60243333 > > colMeans(tmp2) [1] -0.04032177 > colSums(tmp2) [1] -4.032177 > colVars(tmp2) [1] 0.830513 > colSd(tmp2) [1] 0.9113249 > colMax(tmp2) [1] 2.802377 > colMin(tmp2) [1] -2.34141 > colMedians(tmp2) [1] -0.1158778 > colRanges(tmp2) [,1] [1,] -2.341410 [2,] 2.802377 > > 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] 6.2233052 0.6924593 3.2140393 2.7365518 -4.2118723 0.7584869 [7] -2.4862670 2.9756189 4.4254597 3.0620522 > colApply(tmp,quantile)[,1] [,1] [1,] -0.3748969 [2,] 0.1624247 [3,] 0.6904306 [4,] 0.9905044 [5,] 1.6185002 > > rowApply(tmp,sum) [1] 3.2706946 1.6351021 -1.1303807 -0.6847062 -0.1523820 5.8778075 [7] 1.7881120 2.7133940 0.6513800 3.4208127 > rowApply(tmp,rank)[1:10,] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 7 3 10 8 10 8 7 4 2 5 [2,] 10 7 4 1 1 10 10 9 3 3 [3,] 4 10 7 4 2 9 2 6 7 7 [4,] 5 9 2 5 6 1 6 7 9 9 [5,] 9 2 1 2 5 2 1 10 5 1 [6,] 3 1 3 10 8 4 8 1 6 10 [7,] 1 4 6 3 4 5 3 5 1 4 [8,] 8 6 8 7 7 3 5 3 10 6 [9,] 6 8 9 6 9 6 9 2 4 2 [10,] 2 5 5 9 3 7 4 8 8 8 > > tmp <- createBufferedMatrix(5,20) > > tmp[1:5,1:20] <- rnorm(100) > colApply(tmp,sum) [1] 0.63180879 -1.84697236 -1.28303479 -1.48304722 -1.93399476 2.66555268 [7] -3.08286949 1.67982499 -1.25976535 0.94208841 -0.03645901 2.17585671 [13] 2.23685101 1.90237654 -1.14449917 -0.38718526 -2.16645561 2.20321527 [19] -2.32291570 0.34638815 > colApply(tmp,quantile)[,1] [,1] [1,] -1.0718775 [2,] -0.7119119 [3,] -0.3746352 [4,] 0.7456229 [5,] 2.0446105 > > rowApply(tmp,sum) [1] -1.5439476 4.5969309 0.7411168 -14.2235137 8.2661774 > rowApply(tmp,rank)[1:5,] [,1] [,2] [,3] [,4] [,5] [1,] 9 20 1 18 5 [2,] 13 13 3 9 1 [3,] 1 8 8 16 12 [4,] 10 3 6 20 2 [5,] 6 1 4 12 20 > > > as.matrix(tmp) [,1] [,2] [,3] [,4] [,5] [,6] [1,] -0.3746352 0.2877083 -1.7725449 -0.3661541 -0.5367827 1.0469119 [2,] 2.0446105 0.7142365 0.1249577 -0.9567729 -2.4255057 -0.9830097 [3,] -1.0718775 -1.0052734 -0.6046657 -0.8128535 -0.9588739 0.4345780 [4,] 0.7456229 -0.9826272 0.1843827 1.4228877 -0.3170122 1.1030958 [5,] -0.7119119 -0.8610166 0.7848354 -0.7701544 2.3041797 1.0639767 [,7] [,8] [,9] [,10] [,11] [,12] [1,] -0.6406222 -0.5116615 0.5665528 -0.009824738 0.8884656 1.8282089 [2,] 0.7184213 1.9824527 0.2298012 0.852336079 -0.4064371 1.0555312 [3,] -0.6581728 1.4974867 -0.8142007 0.293296354 -1.0422627 -0.2038767 [4,] -2.3467381 -2.4234881 -2.3786981 -0.294789008 -0.8953275 -1.6332303 [5,] -0.1557576 1.1350352 1.1367795 0.101069720 1.4191027 1.1292237 [,13] [,14] [,15] [,16] [,17] [,18] [1,] 1.1788615 -1.4413007 -0.3786644 0.39548506 -1.39060672 0.8453897 [2,] -0.2587568 0.2647278 0.8834458 0.93481746 0.24980049 -0.5232002 [3,] 1.4856483 1.1653577 -0.2443056 -0.34851523 0.03358266 2.4007826 [4,] -1.1119932 0.2557160 -1.6584398 -1.39926288 -1.59345722 -0.3032949 [5,] 0.9430912 1.6578756 0.2534648 0.03029033 0.53422518 -0.2164620 [,19] [,20] [1,] -1.4076290 0.2488946 [2,] -0.1980597 0.2935343 [3,] 0.7851842 0.4100782 [4,] -0.7527170 0.1558567 [5,] -0.7496942 -0.7619756 > > > is.BufferedMatrix(tmp) [1] TRUE > > as.BufferedMatrix(as.matrix(tmp)) BufferedMatrix object Matrix size: 5 20 Buffer size: 1 1 Directory: F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 1.8 Kilobytes. Disk usage : 800 bytes. > > > > subBufferedMatrix(tmp,1:5,1:5) BufferedMatrix object Matrix size: 5 5 Buffer size: 1 1 Directory: F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 623 bytes. Disk usage : 200 bytes. > subBufferedMatrix(tmp,,5:8) BufferedMatrix object Matrix size: 5 4 Buffer size: 1 1 Directory: F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 542 bytes. Disk usage : 160 bytes. > subBufferedMatrix(tmp,1:3,) BufferedMatrix object Matrix size: 3 20 Buffer size: 1 1 Directory: F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests Prefix: BM Mode: Col mode Read Only: FALSE Memory usage : 1.8 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 -0.8577084 -1.149068 -0.4016308 1.183488 -1.565828 -0.7680995 -0.4042412 col8 col9 col10 col11 col12 col13 col14 row1 0.7674258 1.247638 0.1345481 -1.771707 0.117229 0.8575099 1.604652 col15 col16 col17 col18 col19 col20 row1 -1.230808 0.9077947 -0.4636223 -0.3561376 -0.4649234 0.08783763 > tmp[,"col10"] col10 row1 0.1345481 row2 1.3247105 row3 -0.5869439 row4 -0.3432638 row5 0.9686535 > tmp[c("row1","row5"),] col1 col2 col3 col4 col5 col6 row1 -0.8577084 -1.1490679 -0.4016308 1.183488 -1.5658283 -0.7680995 row5 0.3183139 0.4351196 -0.6824127 -0.675012 -0.7421802 0.7468039 col7 col8 col9 col10 col11 col12 col13 row1 -0.4042412 0.7674258 1.24763830 0.1345481 -1.7717070 0.1172290 0.8575099 row5 1.9316427 0.1712366 -0.07134408 0.9686535 0.9696099 -0.1904305 0.7000987 col14 col15 col16 col17 col18 col19 col20 row1 1.6046524 -1.2308084 0.9077947 -0.4636223 -0.3561376 -0.4649234 0.08783763 row5 0.2285823 0.1435318 0.2857757 1.6916764 0.6591104 -0.6193645 1.67405286 > tmp[,c("col6","col20")] col6 col20 row1 -0.7680995 0.08783763 row2 0.2897231 1.97627938 row3 -0.1023447 0.98784831 row4 1.1818909 2.32463072 row5 0.7468039 1.67405286 > tmp[c("row1","row5"),c("col6","col20")] col6 col20 row1 -0.7680995 0.08783763 row5 0.7468039 1.67405286 > > > > > 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 51.55693 49.8973 49.94787 48.86999 47.783 103.6053 49.52253 50.45138 col9 col10 col11 col12 col13 col14 col15 col16 row1 48.64127 50.46423 49.82884 48.86844 47.80997 50.59108 48.87138 49.59049 col17 col18 col19 col20 row1 50.47687 49.71016 50.48129 103.4626 > tmp[,"col10"] col10 row1 50.46423 row2 29.67006 row3 29.42473 row4 30.22538 row5 50.56818 > tmp[c("row1","row5"),] col1 col2 col3 col4 col5 col6 col7 col8 row1 51.55693 49.89730 49.94787 48.86999 47.78300 103.6053 49.52253 50.45138 row5 49.60910 49.65688 49.49166 48.35377 47.72557 104.0715 48.98448 49.26316 col9 col10 col11 col12 col13 col14 col15 col16 row1 48.64127 50.46423 49.82884 48.86844 47.80997 50.59108 48.87138 49.59049 row5 49.58831 50.56818 49.24809 48.71537 49.59482 49.62060 50.71303 50.34759 col17 col18 col19 col20 row1 50.47687 49.71016 50.48129 103.4626 row5 50.62977 50.03281 50.39010 102.6673 > tmp[,c("col6","col20")] col6 col20 row1 103.60530 103.46256 row2 75.87705 74.89093 row3 75.71444 75.23555 row4 74.30908 74.64224 row5 104.07147 102.66733 > tmp[c("row1","row5"),c("col6","col20")] col6 col20 row1 103.6053 103.4626 row5 104.0715 102.6673 > > > subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2] col6 col20 row1 103.6053 103.4626 row5 104.0715 102.6673 > > > > > > tmp <- createBufferedMatrix(5,20) > tmp[1:5,1:20] <- rnorm(100) > colnames(tmp) <- colnames(tmp,do.NULL=FALSE) > > tmp[,"col13"] col13 [1,] -1.5795412 [2,] -0.4257341 [3,] 0.9820994 [4,] 1.4454660 [5,] 0.8963624 > tmp[,c("col17","col7")] col17 col7 [1,] 1.0076463 -1.34101461 [2,] 0.9168269 1.33918650 [3,] 0.5211252 -1.09654745 [4,] 0.1992567 -0.09918181 [5,] -0.3510156 -1.74182478 > > subBufferedMatrix(tmp,,c("col6","col20"))[,1:2] col6 col20 [1,] -1.3529159 -0.97337150 [2,] -0.3634385 -0.07385865 [3,] -0.1562904 1.24370758 [4,] 0.3283764 -0.64141574 [5,] 0.9716667 0.72101996 > subBufferedMatrix(tmp,1,c("col6"))[,1] col1 [1,] -1.352916 > subBufferedMatrix(tmp,1:2,c("col6"))[,1] col6 [1,] -1.3529159 [2,] -0.3634385 > > > > tmp <- createBufferedMatrix(5,20) > tmp[1:5,1:20] <- rnorm(100) > rownames(tmp) <- rownames(tmp,do.NULL=FALSE) > > > > > subBufferedMatrix(tmp,c("row3","row1"),)[,1:20] [,1] [,2] [,3] [,4] [,5] [,6] row3 -1.6006115 0.9469616 -0.02553887 0.49919328 -0.91513512 1.210094 row1 -0.5620362 -0.1906575 0.85066405 -0.03200967 0.08872176 2.533810 [,7] [,8] [,9] [,10] [,11] [,12] [,13] row3 0.110946 1.2416720 -1.164792 -0.8914024 1.584141 0.4255152 -0.7532941 row1 2.556557 0.1732662 1.222233 -1.2582894 -1.470887 0.5639462 0.6969583 [,14] [,15] [,16] [,17] [,18] [,19] row3 -0.2162315 -0.9725242 -1.0690340 -0.1130944 -1.447551 -0.09644627 row1 -0.7155467 1.1246003 -0.0235932 2.1517228 -1.448148 -0.36227822 [,20] row3 -0.7575704 row1 -0.9981915 > subBufferedMatrix(tmp,c("row2"),1:10)[,1:10] [,1] [,2] [,3] [,4] [,5] [,6] [,7] row2 0.3321148 -0.8934874 -0.2407638 -0.6837726 0.725233 -1.035444 1.129034 [,8] [,9] [,10] row2 -0.0228975 -0.4370907 -1.330279 > subBufferedMatrix(tmp,c("row5"),1:20)[,1:20] [,1] [,2] [,3] [,4] [,5] [,6] [,7] row5 0.4738306 -0.6389424 -0.7689216 -1.03222 1.242364 1.556523 -0.03316153 [,8] [,9] [,10] [,11] [,12] [,13] [,14] row5 0.6824613 0.322185 0.414015 -1.201154 1.058479 0.9349919 0.537581 [,15] [,16] [,17] [,18] [,19] [,20] row5 -1.090297 -0.1506841 0.1828073 1.222024 0.8268671 -2.083496 > > > 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: 0x000002b65e718d10> > is.ReadOnlyMode(tmp) [1] TRUE > > filenames(tmp) [1] "F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests\\BM45885b476c0" [2] "F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests\\BM45883922660c" [3] "F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests\\BM458859285e" [4] "F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests\\BM458865cb337f" [5] "F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests\\BM458819cd7ca5" [6] "F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests\\BM458848e81c62" [7] "F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests\\BM45885ea91f34" [8] "F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4588d29176d" [9] "F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests\\BM458872897b8d" [10] "F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests\\BM458873607449" [11] "F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests\\BM458839787fc7" [12] "F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests\\BM45881893be7" [13] "F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests\\BM458877df7784" [14] "F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests\\BM458823086b16" [15] "F:/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests\\BM458814f13b23" > > > ### 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: 0x000002b65f0b8610> > MoveStorageDirectory(tmp,getwd(),full.path=TRUE) <pointer: 0x000002b65f0b8610> Warning message: In dir.create(new.directory) : 'F:\biocbuild\bbs-3.16-bioc\meat\BufferedMatrix.Rcheck\tests' already exists > > > RowMode(tmp) <pointer: 0x000002b65f0b8610> > rowMedians(tmp) [1] 0.186716633 -0.432662072 0.082111710 -0.393633811 0.719972932 [6] -0.152614882 0.118027768 0.394687333 -0.095698638 -0.027300620 [11] 0.346425325 0.491187680 -0.208843702 0.289144557 0.294939562 [16] 0.061315642 0.067180982 0.227359773 0.364067627 -0.161834133 [21] 0.249769519 -0.340081321 0.465756673 0.344807164 0.206001963 [26] 0.164947791 0.427474522 0.458699097 -0.181099342 -0.011131533 [31] 0.408813835 -0.173440080 0.024681164 -0.017263127 -0.174213415 [36] 0.175629537 -0.204610684 -0.488786290 -0.075785172 -0.239100126 [41] 0.134430095 -0.067400966 0.225964006 -0.216801573 0.026502536 [46] -0.237884857 0.023154905 -0.159878610 0.202655516 -0.947300146 [51] 0.299061374 0.093769698 0.431847684 0.049607782 -0.185387663 [56] 0.444721230 -0.683572877 -0.382966772 0.066384630 -0.011365977 [61] -0.221128361 -0.551714278 -0.338184745 0.244622583 -0.138862735 [66] 0.251971620 0.317321110 0.009706375 0.338764523 -0.308766329 [71] -0.032427566 0.156985235 0.166901965 0.100616955 -0.134019443 [76] 0.384091799 0.372037558 -0.240965012 -0.598092871 -0.116886414 [81] 0.105116434 -0.263504690 -0.280218957 -0.416384157 -0.214351888 [86] -0.232129532 -0.203623342 -0.356711133 -0.026813355 -0.606547664 [91] 0.572352930 0.610197139 0.591024842 -0.356608885 -0.217926605 [96] -0.275897901 -0.331707918 -0.028147837 -0.129162289 -0.539138794 [101] 0.360850637 -0.136550171 -0.541739186 0.118086773 -0.055127473 [106] -0.123562046 -0.292617560 -0.324432120 -0.315322737 0.312492497 [111] -0.302436492 0.182358180 0.001814461 -0.114710200 0.574223654 [116] 0.559376226 0.606195641 -0.172582494 -0.230917938 -0.284310075 [121] -0.187140428 -0.067772706 -0.235608046 0.052995165 0.084951947 [126] -0.652381907 0.344648117 -0.492152594 -0.042671802 -0.002457292 [131] 0.568122326 0.651211290 -0.622482356 0.244052667 -0.574007297 [136] -0.610982398 0.171799025 0.606986840 -0.285826791 0.247209064 [141] 0.314357124 -0.294517328 -0.115172369 -0.168032755 0.070259866 [146] 0.001788988 -0.069731717 -0.095868460 -0.275947823 0.510737088 [151] 0.112369917 0.012878542 -0.021303415 -0.583096932 0.107827536 [156] 0.331725556 -0.414795827 -0.206440081 0.379167639 -0.029451439 [161] 0.969925814 -0.011975397 -0.095682497 0.033284950 0.351075717 [166] 0.081107876 0.330432303 0.067535157 0.631980241 0.052530057 [171] -0.445960700 -0.233436452 0.308609359 -0.008515433 0.303303506 [176] -0.495443135 -0.394095706 -0.250719165 0.061251595 0.056109864 [181] 0.215613758 0.102872417 -0.191692394 0.223866935 0.343586976 [186] -0.236896158 0.270532688 -0.349167792 0.353917109 -0.452107047 [191] -0.515463820 0.270868339 0.068296922 -0.418318871 -0.419437018 [196] 0.541877331 0.317448117 0.332600665 0.109783590 -0.157714894 [201] 0.573094463 -0.046020350 0.111865752 -0.603203209 -0.315847112 [206] -0.013799459 0.198894015 -0.062309920 -0.356660514 0.266594770 [211] 0.159953603 -0.197660493 -0.257822211 0.392052145 0.388811028 [216] 0.242017139 0.291424425 0.027125624 -0.079231387 0.101303826 [221] 0.275272751 0.072792220 0.177014378 -0.009645201 -0.188494042 [226] 0.276762400 0.327097006 0.349772710 0.171684298 -0.527685808 > > proc.time() user system elapsed 3.78 18.43 66.54
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.2.3 (2023-03-15 ucrt) -- "Shortstop Beagle" Copyright (C) 2023 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 (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: 0x0000024f55a5b360> > .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: 0x0000024f55a5b360> > .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: 0x0000024f55a5b360> > .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: 0x0000024f55a5b360> > 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: 0x0000024f55a5b3d0> > .Call("R_bm_AddColumn",P) <pointer: 0x0000024f55a5b3d0> > .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: 0x0000024f55a5b3d0> > .Call("R_bm_AddColumn",P) <pointer: 0x0000024f55a5b3d0> > .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: 0x0000024f55a5b3d0> > 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: 0x0000024f55a5b4b0> > .Call("R_bm_AddColumn",P) <pointer: 0x0000024f55a5b4b0> > .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: 0x0000024f55a5b4b0> > > .Call("R_bm_ResizeBuffer",P,5,5) <pointer: 0x0000024f55a5b4b0> > .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: 0x0000024f55a5b4b0> > > .Call("R_bm_RowMode",P) <pointer: 0x0000024f55a5b4b0> > .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: 0x0000024f55a5b4b0> > > .Call("R_bm_ColMode",P) <pointer: 0x0000024f55a5b4b0> > .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: 0x0000024f55a5b4b0> > 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: 0x0000024f55a5b520> > .Call("R_bm_SetPrefix",P,"BufferedMatrixFile") <pointer: 0x0000024f55a5b520> > .Call("R_bm_AddColumn",P) <pointer: 0x0000024f55a5b520> > .Call("R_bm_AddColumn",P) <pointer: 0x0000024f55a5b520> > dir(pattern="BufferedMatrixFile") [1] "BufferedMatrixFile3f943db37c4" "BufferedMatrixFile3f943e99c88" > rm(P) > dir(pattern="BufferedMatrixFile") [1] "BufferedMatrixFile3f943db37c4" "BufferedMatrixFile3f943e99c88" > > > P <- .Call("R_bm_Create",prefix,directory,1,1) > .Call("R_bm_setRows",P,10) [1] TRUE > .Call("R_bm_AddColumn",P) <pointer: 0x0000024f55a5af70> > .Call("R_bm_AddColumn",P) <pointer: 0x0000024f55a5af70> > .Call("R_bm_ReadOnlyModeToggle",P) <pointer: 0x0000024f55a5af70> > .Call("R_bm_isReadOnlyMode",P) [1] TRUE > .Call("R_bm_ReadOnlyModeToggle",P) <pointer: 0x0000024f55a5af70> > .Call("R_bm_isReadOnlyMode",P) [1] FALSE > .Call("R_bm_isRowMode",P) [1] FALSE > .Call("R_bm_RowMode",P) <pointer: 0x0000024f55a5af70> > .Call("R_bm_isRowMode",P) [1] TRUE > .Call("R_bm_ColMode",P) <pointer: 0x0000024f55a5af70> > .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: 0x0000024f55a5aa30> > .Call("R_bm_AddColumn",P) <pointer: 0x0000024f55a5aa30> > > .Call("R_bm_getSize",P) [1] 10 2 > .Call("R_bm_getBufferSize",P) [1] 1 1 > .Call("R_bm_ResizeBuffer",P,5,5) <pointer: 0x0000024f55a5aa30> > > .Call("R_bm_getBufferSize",P) [1] 5 5 > .Call("R_bm_ResizeBuffer",P,-1,5) <pointer: 0x0000024f55a5aa30> > 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: 0x0000024f55a5b600> > .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: 0x0000024f55a5b600> > rm(P) > > proc.time() user system elapsed 0.25 0.35 0.76
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.2.3 (2023-03-15 ucrt) -- "Shortstop Beagle" Copyright (C) 2023 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 (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 0.37 0.03 0.39