Ben Bolstad
| Snapshot Date: 2022-03-17 13:55:23 -0400 (Thu, 17 Mar 2022) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: master |
| git_last_commit: 50f93ab |
| git_last_commit_date: 2021-10-26 11:50:47 -0400 (Tue, 26 Oct 2021) |
| Back to Multiple platform build/check report for BioC 3.15 |
|
This page was generated on 2022-03-18 11:07:05 -0400 (Fri, 18 Mar 2022).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 20.04.4 LTS) | x86_64 | R Under development (unstable) (2022-02-17 r81757) -- "Unsuffered Consequences" | 4334 |
| riesling1 | Windows Server 2019 Standard | x64 | R Under development (unstable) (2021-11-21 r81221) -- "Unsuffered Consequences" | 4097 |
| palomino3 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2022-02-17 r81757 ucrt) -- "Unsuffered Consequences" | 4083 |
| merida1 | macOS 10.14.6 Mojave | x86_64 | R Under development (unstable) (2022-03-02 r81842) -- "Unsuffered Consequences" | 4134 |
| 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? here for more information. - Make sure to use the following settings in order to reproduce any error or warning you see on this page. |
| Package 221/2090 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.59.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 20.04.4 LTS) / x86_64 | OK | OK | OK | | ||||||||
| riesling1 | Windows Server 2019 Standard / x64 | OK | OK | OK | OK | |||||||||
| palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 10.14.6 Mojave / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| Package: BufferedMatrix |
| Version: 1.59.0 |
| Command: D:\biocbuild\bbs-3.15-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=D:\biocbuild\bbs-3.15-bioc\R\library --no-vignettes --timings BufferedMatrix_1.59.0.tar.gz |
| StartedAt: 2022-03-17 18:37:08 -0400 (Thu, 17 Mar 2022) |
| EndedAt: 2022-03-17 18:39:17 -0400 (Thu, 17 Mar 2022) |
| EllapsedTime: 129.3 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### D:\biocbuild\bbs-3.15-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=D:\biocbuild\bbs-3.15-bioc\R\library --no-vignettes --timings BufferedMatrix_1.59.0.tar.gz ### ############################################################################## ############################################################################## * using log directory 'D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck' * using R Under development (unstable) (2021-11-21 r81221) * using platform: x86_64-w64-mingw32 (64-bit) * using session charset: ISO8859-1 * using option '--no-vignettes' * checking for file 'BufferedMatrix/DESCRIPTION' ... OK * this is package 'BufferedMatrix' version '1.59.0' * 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 'D:/biocbuild/bbs-3.15-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 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 'D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/00check.log' for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### D:\biocbuild\bbs-3.15-bioc\R\bin\R.exe CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library 'D:/biocbuild/bbs-3.15-bioc/R/library'
* installing *source* package 'BufferedMatrix' ...
** using staged installation
** libs
"C:/rtools40/mingw64/bin/"gcc -I"D:/biocbuild/bbs-3.15-bioc/R/include" -DNDEBUG -I"C:/extsoft/include" -O2 -Wall -std=gnu99 -mfpmath=sse -msse2 -mstackrealign -fno-reorder-blocks-and-partition -c RBufferedMatrix.c -o RBufferedMatrix.o
"C:/rtools40/mingw64/bin/"gcc -I"D:/biocbuild/bbs-3.15-bioc/R/include" -DNDEBUG -I"C:/extsoft/include" -O2 -Wall -std=gnu99 -mfpmath=sse -msse2 -mstackrealign -fno-reorder-blocks-and-partition -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]
if (!(Matrix->readonly) & setting){
^~~~~~~~~~~~~~~~~~~
At top level:
doubleBufferedMatrix.c:3327:12: warning: 'sort_double' defined but not used [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^~~~~~~~~~~
"C:/rtools40/mingw64/bin/"gcc -I"D:/biocbuild/bbs-3.15-bioc/R/include" -DNDEBUG -I"C:/extsoft/include" -O2 -Wall -std=gnu99 -mfpmath=sse -msse2 -mstackrealign -fno-reorder-blocks-and-partition -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
"C:/rtools40/mingw64/bin/"gcc -I"D:/biocbuild/bbs-3.15-bioc/R/include" -DNDEBUG -I"C:/extsoft/include" -O2 -Wall -std=gnu99 -mfpmath=sse -msse2 -mstackrealign -fno-reorder-blocks-and-partition -c init_package.c -o init_package.o
C:/rtools40/mingw64/bin/gcc -shared -s -static-libgcc -o BufferedMatrix.dll tmp.def RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -LC:/extsoft/lib/x64 -LC:/extsoft/lib -LD:/biocbuild/bbs-3.15-bioc/R/bin/x64 -lR
installing to D:/biocbuild/bbs-3.15-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
converting help for package 'BufferedMatrix'
finding HTML links ... done
BufferedMatrix-class html
as.BufferedMatrix html
createBufferedMatrix html
** 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)
Making 'packages.html' ... done
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R Under development (unstable) (2021-11-21 r81221) -- "Unsuffered Consequences"
Copyright (C) 2021 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
0.25 0.09 0.62
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2021-11-21 r81221) -- "Unsuffered Consequences"
Copyright (C) 2021 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] "D:/biocbuild/bbs-3.15-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 438496 23.5 940730 50.3 624231 33.4
Vcells 761370 5.9 8388608 64.0 1691090 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] "Thu Mar 17 18:37:32 2022"
> 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] "Thu Mar 17 18:37:34 2022"
>
>
> 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: 0x0000000012b13d70>
>
>
>
> 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] "Thu Mar 17 18:37:58 2022"
> 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] "Thu Mar 17 18:38:11 2022"
>
> ColMode(tmp2)
<pointer: 0x0000000012b13d70>
>
>
>
> ### 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,] 100.6691731 -1.1306467 0.4733143 0.6298952
[2,] 1.2592110 0.5202191 -0.1696558 -0.3847474
[3,] -0.1556034 1.0821276 -1.4765426 0.7465664
[4,] -0.3904053 -0.1745694 1.5583277 -1.2079907
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: D:/biocbuild/bbs-3.15-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,] 100.6691731 1.1306467 0.4733143 0.6298952
[2,] 1.2592110 0.5202191 0.1696558 0.3847474
[3,] 0.1556034 1.0821276 1.4765426 0.7465664
[4,] 0.3904053 0.1745694 1.5583277 1.2079907
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: D:/biocbuild/bbs-3.15-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,] 10.0334029 1.0633187 0.6879784 0.7936594
[2,] 1.1221457 0.7212622 0.4118930 0.6202801
[3,] 0.3944660 1.0402536 1.2151307 0.8640407
[4,] 0.6248242 0.4178151 1.2483300 1.0990863
>
> 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: D:/biocbuild/bbs-3.15-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,] 226.00320 36.76383 32.35310 33.56649
[2,] 37.48067 32.73284 29.28859 31.58755
[3,] 29.10026 36.48466 38.62785 34.38697
[4,] 31.63865 29.35272 39.04163 37.19885
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x0000000012b13fa0>
> exp(tmp5)
<pointer: 0x0000000012b13fa0>
> log(tmp5,2)
<pointer: 0x0000000012b13fa0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.3961
> Min(tmp5)
[1] 53.25222
> mean(tmp5)
[1] 71.92847
> Sum(tmp5)
[1] 14385.69
> Var(tmp5)
[1] 865.567
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.63288 71.55738 68.50224 70.50881 73.30794 69.00561 64.28981 72.92598
[9] 69.29362 69.26047
> rowSums(tmp5)
[1] 1812.658 1431.148 1370.045 1410.176 1466.159 1380.112 1285.796 1458.520
[9] 1385.872 1385.209
> rowVars(tmp5)
[1] 8050.46162 70.14301 37.12951 74.61755 104.84397 52.08184
[7] 31.42116 66.06344 74.91317 32.84491
> rowSd(tmp5)
[1] 89.724365 8.375142 6.093399 8.638145 10.239334 7.216775 5.605458
[8] 8.127942 8.655239 5.731048
> rowMax(tmp5)
[1] 470.39605 87.34529 80.39881 87.82241 91.49006 83.88966 76.11562
[8] 88.70234 88.76774 81.92239
> rowMin(tmp5)
[1] 57.50304 58.22348 60.09848 56.47239 56.76351 59.13137 56.71454 59.03376
[9] 53.25222 56.88164
>
> colMeans(tmp5)
[1] 109.66663 67.78225 71.18107 71.40971 73.62411 69.49007 73.02292
[8] 70.76947 72.10529 68.28008 69.90230 69.71299 68.70271 69.63548
[15] 72.53319 65.77108 70.56185 69.25481 67.68061 67.48283
> colSums(tmp5)
[1] 1096.6663 677.8225 711.8107 714.0971 736.2411 694.9007 730.2292
[8] 707.6947 721.0529 682.8008 699.0230 697.1299 687.0271 696.3548
[15] 725.3319 657.7108 705.6185 692.5481 676.8061 674.8283
> colVars(tmp5)
[1] 16101.93666 39.63322 71.90421 67.55207 116.12511 76.14224
[7] 77.12015 142.61848 38.27944 71.41900 28.40731 77.61618
[13] 60.98798 39.38716 87.98137 40.07783 77.01560 45.91227
[19] 76.54711 50.12810
> colSd(tmp5)
[1] 126.893407 6.295492 8.479635 8.219006 10.776136 8.725952
[7] 8.781808 11.942298 6.187038 8.450976 5.329851 8.810005
[13] 7.809480 6.275919 9.379838 6.330706 8.775853 6.775859
[19] 8.749120 7.080120
> colMax(tmp5)
[1] 470.39605 76.51910 81.66158 88.61652 91.49006 88.70234 83.91243
[8] 87.82241 80.49762 81.11227 77.68399 84.22635 87.34529 83.20010
[15] 84.42140 75.04424 88.76774 82.76305 82.96480 81.92239
> colMin(tmp5)
[1] 60.56839 59.54740 57.65415 59.26358 61.71428 60.21637 58.99567 56.88164
[9] 62.32557 58.22348 58.93115 56.71454 59.03376 62.89867 58.48332 57.50304
[17] 56.76351 58.95329 53.25222 56.47239
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] NA 71.55738 68.50224 70.50881 73.30794 69.00561 64.28981 72.92598
[9] 69.29362 69.26047
> rowSums(tmp5)
[1] NA 1431.148 1370.045 1410.176 1466.159 1380.112 1285.796 1458.520
[9] 1385.872 1385.209
> rowVars(tmp5)
[1] 8469.17264 70.14301 37.12951 74.61755 104.84397 52.08184
[7] 31.42116 66.06344 74.91317 32.84491
> rowSd(tmp5)
[1] 92.028108 8.375142 6.093399 8.638145 10.239334 7.216775 5.605458
[8] 8.127942 8.655239 5.731048
> rowMax(tmp5)
[1] NA 87.34529 80.39881 87.82241 91.49006 83.88966 76.11562 88.70234
[9] 88.76774 81.92239
> rowMin(tmp5)
[1] NA 58.22348 60.09848 56.47239 56.76351 59.13137 56.71454 59.03376
[9] 53.25222 56.88164
>
> colMeans(tmp5)
[1] 109.66663 67.78225 71.18107 71.40971 73.62411 69.49007 73.02292
[8] 70.76947 72.10529 68.28008 69.90230 NA 68.70271 69.63548
[15] 72.53319 65.77108 70.56185 69.25481 67.68061 67.48283
> colSums(tmp5)
[1] 1096.6663 677.8225 711.8107 714.0971 736.2411 694.9007 730.2292
[8] 707.6947 721.0529 682.8008 699.0230 NA 687.0271 696.3548
[15] 725.3319 657.7108 705.6185 692.5481 676.8061 674.8283
> colVars(tmp5)
[1] 16101.93666 39.63322 71.90421 67.55207 116.12511 76.14224
[7] 77.12015 142.61848 38.27944 71.41900 28.40731 NA
[13] 60.98798 39.38716 87.98137 40.07783 77.01560 45.91227
[19] 76.54711 50.12810
> colSd(tmp5)
[1] 126.893407 6.295492 8.479635 8.219006 10.776136 8.725952
[7] 8.781808 11.942298 6.187038 8.450976 5.329851 NA
[13] 7.809480 6.275919 9.379838 6.330706 8.775853 6.775859
[19] 8.749120 7.080120
> colMax(tmp5)
[1] 470.39605 76.51910 81.66158 88.61652 91.49006 88.70234 83.91243
[8] 87.82241 80.49762 81.11227 77.68399 NA 87.34529 83.20010
[15] 84.42140 75.04424 88.76774 82.76305 82.96480 81.92239
> colMin(tmp5)
[1] 60.56839 59.54740 57.65415 59.26358 61.71428 60.21637 58.99567 56.88164
[9] 62.32557 58.22348 58.93115 NA 59.03376 62.89867 58.48332 57.50304
[17] 56.76351 58.95329 53.25222 56.47239
>
> Max(tmp5,na.rm=TRUE)
[1] 470.3961
> Min(tmp5,na.rm=TRUE)
[1] 53.25222
> mean(tmp5,na.rm=TRUE)
[1] 71.94549
> Sum(tmp5,na.rm=TRUE)
[1] 14317.15
> Var(tmp5,na.rm=TRUE)
[1] 869.8804
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.79552 71.55738 68.50224 70.50881 73.30794 69.00561 64.28981 72.92598
[9] 69.29362 69.26047
> rowSums(tmp5,na.rm=TRUE)
[1] 1744.115 1431.148 1370.045 1410.176 1466.159 1380.112 1285.796 1458.520
[9] 1385.872 1385.209
> rowVars(tmp5,na.rm=TRUE)
[1] 8469.17264 70.14301 37.12951 74.61755 104.84397 52.08184
[7] 31.42116 66.06344 74.91317 32.84491
> rowSd(tmp5,na.rm=TRUE)
[1] 92.028108 8.375142 6.093399 8.638145 10.239334 7.216775 5.605458
[8] 8.127942 8.655239 5.731048
> rowMax(tmp5,na.rm=TRUE)
[1] 470.39605 87.34529 80.39881 87.82241 91.49006 83.88966 76.11562
[8] 88.70234 88.76774 81.92239
> rowMin(tmp5,na.rm=TRUE)
[1] 57.50304 58.22348 60.09848 56.47239 56.76351 59.13137 56.71454 59.03376
[9] 53.25222 56.88164
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.66663 67.78225 71.18107 71.40971 73.62411 69.49007 73.02292
[8] 70.76947 72.10529 68.28008 69.90230 69.84303 68.70271 69.63548
[15] 72.53319 65.77108 70.56185 69.25481 67.68061 67.48283
> colSums(tmp5,na.rm=TRUE)
[1] 1096.6663 677.8225 711.8107 714.0971 736.2411 694.9007 730.2292
[8] 707.6947 721.0529 682.8008 699.0230 628.5873 687.0271 696.3548
[15] 725.3319 657.7108 705.6185 692.5481 676.8061 674.8283
> colVars(tmp5,na.rm=TRUE)
[1] 16101.93666 39.63322 71.90421 67.55207 116.12511 76.14224
[7] 77.12015 142.61848 38.27944 71.41900 28.40731 87.12796
[13] 60.98798 39.38716 87.98137 40.07783 77.01560 45.91227
[19] 76.54711 50.12810
> colSd(tmp5,na.rm=TRUE)
[1] 126.893407 6.295492 8.479635 8.219006 10.776136 8.725952
[7] 8.781808 11.942298 6.187038 8.450976 5.329851 9.334236
[13] 7.809480 6.275919 9.379838 6.330706 8.775853 6.775859
[19] 8.749120 7.080120
> colMax(tmp5,na.rm=TRUE)
[1] 470.39605 76.51910 81.66158 88.61652 91.49006 88.70234 83.91243
[8] 87.82241 80.49762 81.11227 77.68399 84.22635 87.34529 83.20010
[15] 84.42140 75.04424 88.76774 82.76305 82.96480 81.92239
> colMin(tmp5,na.rm=TRUE)
[1] 60.56839 59.54740 57.65415 59.26358 61.71428 60.21637 58.99567 56.88164
[9] 62.32557 58.22348 58.93115 56.71454 59.03376 62.89867 58.48332 57.50304
[17] 56.76351 58.95329 53.25222 56.47239
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 71.55738 68.50224 70.50881 73.30794 69.00561 64.28981 72.92598
[9] 69.29362 69.26047
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1431.148 1370.045 1410.176 1466.159 1380.112 1285.796 1458.520
[9] 1385.872 1385.209
> rowVars(tmp5,na.rm=TRUE)
[1] NA 70.14301 37.12951 74.61755 104.84397 52.08184 31.42116
[8] 66.06344 74.91317 32.84491
> rowSd(tmp5,na.rm=TRUE)
[1] NA 8.375142 6.093399 8.638145 10.239334 7.216775 5.605458
[8] 8.127942 8.655239 5.731048
> rowMax(tmp5,na.rm=TRUE)
[1] NA 87.34529 80.39881 87.82241 91.49006 83.88966 76.11562 88.70234
[9] 88.76774 81.92239
> rowMin(tmp5,na.rm=TRUE)
[1] NA 58.22348 60.09848 56.47239 56.76351 59.13137 56.71454 59.03376
[9] 53.25222 56.88164
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 69.58558 66.81149 71.60800 71.58143 73.43648 69.14278 74.58150 68.93681
[9] 72.14852 67.25171 69.10936 NaN 68.67694 68.95562 71.48051 66.68975
[17] 70.74107 70.39942 68.27931 67.74479
> colSums(tmp5,na.rm=TRUE)
[1] 626.2702 601.3034 644.4720 644.2329 660.9284 622.2850 671.2335 620.4313
[9] 649.3367 605.2654 621.9842 0.0000 618.0925 620.6006 643.3246 600.2078
[17] 636.6697 633.5948 614.5138 609.7031
> colVars(tmp5,na.rm=TRUE)
[1] 41.66237 33.98562 78.84174 75.66434 130.24471 84.30313 59.43187
[8] 122.66132 43.04334 68.44893 24.88462 NA 68.60401 39.11068
[15] 86.51259 35.59303 86.28120 36.91224 82.08305 55.62212
> colSd(tmp5,na.rm=TRUE)
[1] 6.454639 5.829719 8.879287 8.698525 11.412480 9.181673 7.709207
[8] 11.075257 6.560743 8.273387 4.988449 NA 8.282754 6.253853
[15] 9.301214 5.965990 9.288767 6.075544 9.059970 7.458024
> colMax(tmp5,na.rm=TRUE)
[1] 78.47259 75.93805 81.66158 88.61652 91.49006 88.70234 83.91243 87.82241
[9] 80.49762 81.11227 77.68399 -Inf 87.34529 83.20010 84.42140 75.04424
[17] 88.76774 82.76305 82.96480 81.92239
> colMin(tmp5,na.rm=TRUE)
[1] 60.56839 59.54740 57.65415 59.26358 61.71428 60.21637 62.28710 56.88164
[9] 62.32557 58.22348 58.93115 Inf 59.03376 62.89867 58.48332 60.11944
[17] 56.76351 63.51545 53.25222 56.47239
>
>
>
>
> 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] 231.10536 152.29742 285.42492 181.63888 176.71813 291.28685 73.11808
[8] 251.20194 268.07301 158.86312
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 231.10536 152.29742 285.42492 181.63888 176.71813 291.28685 73.11808
[8] 251.20194 268.07301 158.86312
>
>
>
> 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] -8.526513e-14 5.684342e-14 0.000000e+00 -5.684342e-14 5.684342e-14
[6] -2.842171e-14 -5.684342e-14 0.000000e+00 0.000000e+00 2.842171e-14
[11] -7.105427e-15 0.000000e+00 3.552714e-14 2.842171e-14 -8.526513e-14
[16] -5.684342e-14 1.136868e-13 -1.705303e-13 -2.273737e-13 1.705303e-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)
+ }
9 8
5 10
6 20
7 14
6 3
7 14
10 18
6 2
7 7
1 19
7 18
2 5
4 14
10 3
7 4
5 5
8 3
6 13
9 12
7 7
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] 2.84617
> Min(tmp)
[1] -2.815914
> mean(tmp)
[1] 0.1235956
> Sum(tmp)
[1] 12.35956
> Var(tmp)
[1] 1.288231
>
> rowMeans(tmp)
[1] 0.1235956
> rowSums(tmp)
[1] 12.35956
> rowVars(tmp)
[1] 1.288231
> rowSd(tmp)
[1] 1.135003
> rowMax(tmp)
[1] 2.84617
> rowMin(tmp)
[1] -2.815914
>
> colMeans(tmp)
[1] 2.21658943 -0.38014650 0.65936277 1.94735994 -0.65701840 0.84079820
[7] 0.84681022 0.89806301 -0.01057574 0.56246029 0.90066940 0.32749599
[13] 2.51338341 -0.44747257 2.11121385 -1.15960973 0.16237497 -0.04769838
[19] -2.03242038 -0.73445533 0.96990621 -0.19882485 -0.08695896 2.84617034
[25] -0.83251916 -1.92926699 1.11812431 0.83192010 1.71672629 1.67871287
[31] 0.33636350 -1.51563760 -1.19173931 -0.17430639 1.62461004 0.70311018
[37] 0.82699328 -0.02612684 2.00776158 1.12951380 -1.02806445 -0.48528351
[43] -0.57701653 -1.63281254 -0.33859600 0.09798236 -0.31099029 -0.86524419
[49] -0.25999732 0.35579779 -0.13915738 -1.16039602 0.04523951 -0.25930360
[55] 0.93399369 0.53013512 1.66200546 -0.57238416 -0.22135679 1.62396259
[61] -1.08726303 -0.34436323 -0.37085568 -0.81624494 -0.67094049 0.15084321
[67] 0.87309873 -1.02213936 -1.50754846 2.12161015 1.43575792 -1.65613373
[73] 0.77943146 -1.09939599 -0.77369886 -0.57101181 0.67500159 -1.26714185
[79] -0.39871913 -1.42415269 1.32692456 0.36956931 0.99013802 -2.81591444
[85] -1.58902415 1.88237463 -0.26052822 -0.41973205 1.01989879 0.96114613
[91] 0.36357140 -1.07263969 -0.86032390 0.64972770 -0.12193091 0.92569506
[97] -0.05455358 -0.81309153 1.64617617 1.45571355
> colSums(tmp)
[1] 2.21658943 -0.38014650 0.65936277 1.94735994 -0.65701840 0.84079820
[7] 0.84681022 0.89806301 -0.01057574 0.56246029 0.90066940 0.32749599
[13] 2.51338341 -0.44747257 2.11121385 -1.15960973 0.16237497 -0.04769838
[19] -2.03242038 -0.73445533 0.96990621 -0.19882485 -0.08695896 2.84617034
[25] -0.83251916 -1.92926699 1.11812431 0.83192010 1.71672629 1.67871287
[31] 0.33636350 -1.51563760 -1.19173931 -0.17430639 1.62461004 0.70311018
[37] 0.82699328 -0.02612684 2.00776158 1.12951380 -1.02806445 -0.48528351
[43] -0.57701653 -1.63281254 -0.33859600 0.09798236 -0.31099029 -0.86524419
[49] -0.25999732 0.35579779 -0.13915738 -1.16039602 0.04523951 -0.25930360
[55] 0.93399369 0.53013512 1.66200546 -0.57238416 -0.22135679 1.62396259
[61] -1.08726303 -0.34436323 -0.37085568 -0.81624494 -0.67094049 0.15084321
[67] 0.87309873 -1.02213936 -1.50754846 2.12161015 1.43575792 -1.65613373
[73] 0.77943146 -1.09939599 -0.77369886 -0.57101181 0.67500159 -1.26714185
[79] -0.39871913 -1.42415269 1.32692456 0.36956931 0.99013802 -2.81591444
[85] -1.58902415 1.88237463 -0.26052822 -0.41973205 1.01989879 0.96114613
[91] 0.36357140 -1.07263969 -0.86032390 0.64972770 -0.12193091 0.92569506
[97] -0.05455358 -0.81309153 1.64617617 1.45571355
> 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] 2.21658943 -0.38014650 0.65936277 1.94735994 -0.65701840 0.84079820
[7] 0.84681022 0.89806301 -0.01057574 0.56246029 0.90066940 0.32749599
[13] 2.51338341 -0.44747257 2.11121385 -1.15960973 0.16237497 -0.04769838
[19] -2.03242038 -0.73445533 0.96990621 -0.19882485 -0.08695896 2.84617034
[25] -0.83251916 -1.92926699 1.11812431 0.83192010 1.71672629 1.67871287
[31] 0.33636350 -1.51563760 -1.19173931 -0.17430639 1.62461004 0.70311018
[37] 0.82699328 -0.02612684 2.00776158 1.12951380 -1.02806445 -0.48528351
[43] -0.57701653 -1.63281254 -0.33859600 0.09798236 -0.31099029 -0.86524419
[49] -0.25999732 0.35579779 -0.13915738 -1.16039602 0.04523951 -0.25930360
[55] 0.93399369 0.53013512 1.66200546 -0.57238416 -0.22135679 1.62396259
[61] -1.08726303 -0.34436323 -0.37085568 -0.81624494 -0.67094049 0.15084321
[67] 0.87309873 -1.02213936 -1.50754846 2.12161015 1.43575792 -1.65613373
[73] 0.77943146 -1.09939599 -0.77369886 -0.57101181 0.67500159 -1.26714185
[79] -0.39871913 -1.42415269 1.32692456 0.36956931 0.99013802 -2.81591444
[85] -1.58902415 1.88237463 -0.26052822 -0.41973205 1.01989879 0.96114613
[91] 0.36357140 -1.07263969 -0.86032390 0.64972770 -0.12193091 0.92569506
[97] -0.05455358 -0.81309153 1.64617617 1.45571355
> colMin(tmp)
[1] 2.21658943 -0.38014650 0.65936277 1.94735994 -0.65701840 0.84079820
[7] 0.84681022 0.89806301 -0.01057574 0.56246029 0.90066940 0.32749599
[13] 2.51338341 -0.44747257 2.11121385 -1.15960973 0.16237497 -0.04769838
[19] -2.03242038 -0.73445533 0.96990621 -0.19882485 -0.08695896 2.84617034
[25] -0.83251916 -1.92926699 1.11812431 0.83192010 1.71672629 1.67871287
[31] 0.33636350 -1.51563760 -1.19173931 -0.17430639 1.62461004 0.70311018
[37] 0.82699328 -0.02612684 2.00776158 1.12951380 -1.02806445 -0.48528351
[43] -0.57701653 -1.63281254 -0.33859600 0.09798236 -0.31099029 -0.86524419
[49] -0.25999732 0.35579779 -0.13915738 -1.16039602 0.04523951 -0.25930360
[55] 0.93399369 0.53013512 1.66200546 -0.57238416 -0.22135679 1.62396259
[61] -1.08726303 -0.34436323 -0.37085568 -0.81624494 -0.67094049 0.15084321
[67] 0.87309873 -1.02213936 -1.50754846 2.12161015 1.43575792 -1.65613373
[73] 0.77943146 -1.09939599 -0.77369886 -0.57101181 0.67500159 -1.26714185
[79] -0.39871913 -1.42415269 1.32692456 0.36956931 0.99013802 -2.81591444
[85] -1.58902415 1.88237463 -0.26052822 -0.41973205 1.01989879 0.96114613
[91] 0.36357140 -1.07263969 -0.86032390 0.64972770 -0.12193091 0.92569506
[97] -0.05455358 -0.81309153 1.64617617 1.45571355
> colMedians(tmp)
[1] 2.21658943 -0.38014650 0.65936277 1.94735994 -0.65701840 0.84079820
[7] 0.84681022 0.89806301 -0.01057574 0.56246029 0.90066940 0.32749599
[13] 2.51338341 -0.44747257 2.11121385 -1.15960973 0.16237497 -0.04769838
[19] -2.03242038 -0.73445533 0.96990621 -0.19882485 -0.08695896 2.84617034
[25] -0.83251916 -1.92926699 1.11812431 0.83192010 1.71672629 1.67871287
[31] 0.33636350 -1.51563760 -1.19173931 -0.17430639 1.62461004 0.70311018
[37] 0.82699328 -0.02612684 2.00776158 1.12951380 -1.02806445 -0.48528351
[43] -0.57701653 -1.63281254 -0.33859600 0.09798236 -0.31099029 -0.86524419
[49] -0.25999732 0.35579779 -0.13915738 -1.16039602 0.04523951 -0.25930360
[55] 0.93399369 0.53013512 1.66200546 -0.57238416 -0.22135679 1.62396259
[61] -1.08726303 -0.34436323 -0.37085568 -0.81624494 -0.67094049 0.15084321
[67] 0.87309873 -1.02213936 -1.50754846 2.12161015 1.43575792 -1.65613373
[73] 0.77943146 -1.09939599 -0.77369886 -0.57101181 0.67500159 -1.26714185
[79] -0.39871913 -1.42415269 1.32692456 0.36956931 0.99013802 -2.81591444
[85] -1.58902415 1.88237463 -0.26052822 -0.41973205 1.01989879 0.96114613
[91] 0.36357140 -1.07263969 -0.86032390 0.64972770 -0.12193091 0.92569506
[97] -0.05455358 -0.81309153 1.64617617 1.45571355
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 2.216589 -0.3801465 0.6593628 1.94736 -0.6570184 0.8407982 0.8468102
[2,] 2.216589 -0.3801465 0.6593628 1.94736 -0.6570184 0.8407982 0.8468102
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.898063 -0.01057574 0.5624603 0.9006694 0.327496 2.513383 -0.4474726
[2,] 0.898063 -0.01057574 0.5624603 0.9006694 0.327496 2.513383 -0.4474726
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 2.111214 -1.15961 0.162375 -0.04769838 -2.03242 -0.7344553 0.9699062
[2,] 2.111214 -1.15961 0.162375 -0.04769838 -2.03242 -0.7344553 0.9699062
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.1988248 -0.08695896 2.84617 -0.8325192 -1.929267 1.118124 0.8319201
[2,] -0.1988248 -0.08695896 2.84617 -0.8325192 -1.929267 1.118124 0.8319201
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.716726 1.678713 0.3363635 -1.515638 -1.191739 -0.1743064 1.62461
[2,] 1.716726 1.678713 0.3363635 -1.515638 -1.191739 -0.1743064 1.62461
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.7031102 0.8269933 -0.02612684 2.007762 1.129514 -1.028064 -0.4852835
[2,] 0.7031102 0.8269933 -0.02612684 2.007762 1.129514 -1.028064 -0.4852835
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.5770165 -1.632813 -0.338596 0.09798236 -0.3109903 -0.8652442 -0.2599973
[2,] -0.5770165 -1.632813 -0.338596 0.09798236 -0.3109903 -0.8652442 -0.2599973
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.3557978 -0.1391574 -1.160396 0.04523951 -0.2593036 0.9339937 0.5301351
[2,] 0.3557978 -0.1391574 -1.160396 0.04523951 -0.2593036 0.9339937 0.5301351
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 1.662005 -0.5723842 -0.2213568 1.623963 -1.087263 -0.3443632 -0.3708557
[2,] 1.662005 -0.5723842 -0.2213568 1.623963 -1.087263 -0.3443632 -0.3708557
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.8162449 -0.6709405 0.1508432 0.8730987 -1.022139 -1.507548 2.12161
[2,] -0.8162449 -0.6709405 0.1508432 0.8730987 -1.022139 -1.507548 2.12161
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.435758 -1.656134 0.7794315 -1.099396 -0.7736989 -0.5710118 0.6750016
[2,] 1.435758 -1.656134 0.7794315 -1.099396 -0.7736989 -0.5710118 0.6750016
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -1.267142 -0.3987191 -1.424153 1.326925 0.3695693 0.990138 -2.815914
[2,] -1.267142 -0.3987191 -1.424153 1.326925 0.3695693 0.990138 -2.815914
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -1.589024 1.882375 -0.2605282 -0.419732 1.019899 0.9611461 0.3635714
[2,] -1.589024 1.882375 -0.2605282 -0.419732 1.019899 0.9611461 0.3635714
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.07264 -0.8603239 0.6497277 -0.1219309 0.9256951 -0.05455358 -0.8130915
[2,] -1.07264 -0.8603239 0.6497277 -0.1219309 0.9256951 -0.05455358 -0.8130915
[,99] [,100]
[1,] 1.646176 1.455714
[2,] 1.646176 1.455714
>
>
> Max(tmp2)
[1] 2.647745
> Min(tmp2)
[1] -1.807209
> mean(tmp2)
[1] 0.1695933
> Sum(tmp2)
[1] 16.95933
> Var(tmp2)
[1] 0.8120367
>
> rowMeans(tmp2)
[1] 1.12752617 0.98858120 -0.04567743 2.47227327 -0.52660070 -1.76833967
[7] -0.81799165 -0.27149594 -0.27216132 -0.86276453 0.50169232 0.62193013
[13] -0.73231832 -0.27457115 -0.58327803 -0.21756310 0.54423448 0.91698892
[19] 1.23341021 0.19988571 0.54653556 -1.74594708 1.22518106 0.26774367
[25] 1.02559582 0.57465474 2.64774518 -0.88166775 -0.06331309 -0.74015893
[31] -0.75283292 -0.45905353 0.97109156 0.71563312 0.12336973 0.38147524
[37] -1.27555991 -0.71385033 0.62436528 -1.28479250 0.08725524 1.01339743
[43] 0.24897831 1.51173974 0.31005996 -0.16615160 0.71113129 -0.43506071
[49] 1.79157272 -0.58313695 0.33978043 0.10039173 -0.13855298 0.89417963
[55] -0.36132451 0.27311216 0.21008639 -1.20396149 0.30850357 0.71897875
[61] 1.48876139 0.66246491 0.40152976 0.37360987 0.64399409 0.15542483
[67] 2.06413032 -0.27170933 -1.60072962 0.86036835 1.16805902 0.66228805
[73] 0.13942309 0.74318954 0.37619075 -0.68970087 -0.16503717 0.58220773
[79] -0.41672551 -1.14899786 -1.13883889 0.31023603 1.27727698 0.77309041
[85] -0.18753643 0.08609547 0.79810980 0.42536781 0.23691721 2.18712774
[91] 0.02924124 -0.31741091 -0.80729123 -1.80720874 0.60042989 0.69340627
[97] -0.15438712 0.78793832 -0.30680518 -1.60612786
> rowSums(tmp2)
[1] 1.12752617 0.98858120 -0.04567743 2.47227327 -0.52660070 -1.76833967
[7] -0.81799165 -0.27149594 -0.27216132 -0.86276453 0.50169232 0.62193013
[13] -0.73231832 -0.27457115 -0.58327803 -0.21756310 0.54423448 0.91698892
[19] 1.23341021 0.19988571 0.54653556 -1.74594708 1.22518106 0.26774367
[25] 1.02559582 0.57465474 2.64774518 -0.88166775 -0.06331309 -0.74015893
[31] -0.75283292 -0.45905353 0.97109156 0.71563312 0.12336973 0.38147524
[37] -1.27555991 -0.71385033 0.62436528 -1.28479250 0.08725524 1.01339743
[43] 0.24897831 1.51173974 0.31005996 -0.16615160 0.71113129 -0.43506071
[49] 1.79157272 -0.58313695 0.33978043 0.10039173 -0.13855298 0.89417963
[55] -0.36132451 0.27311216 0.21008639 -1.20396149 0.30850357 0.71897875
[61] 1.48876139 0.66246491 0.40152976 0.37360987 0.64399409 0.15542483
[67] 2.06413032 -0.27170933 -1.60072962 0.86036835 1.16805902 0.66228805
[73] 0.13942309 0.74318954 0.37619075 -0.68970087 -0.16503717 0.58220773
[79] -0.41672551 -1.14899786 -1.13883889 0.31023603 1.27727698 0.77309041
[85] -0.18753643 0.08609547 0.79810980 0.42536781 0.23691721 2.18712774
[91] 0.02924124 -0.31741091 -0.80729123 -1.80720874 0.60042989 0.69340627
[97] -0.15438712 0.78793832 -0.30680518 -1.60612786
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 1.12752617 0.98858120 -0.04567743 2.47227327 -0.52660070 -1.76833967
[7] -0.81799165 -0.27149594 -0.27216132 -0.86276453 0.50169232 0.62193013
[13] -0.73231832 -0.27457115 -0.58327803 -0.21756310 0.54423448 0.91698892
[19] 1.23341021 0.19988571 0.54653556 -1.74594708 1.22518106 0.26774367
[25] 1.02559582 0.57465474 2.64774518 -0.88166775 -0.06331309 -0.74015893
[31] -0.75283292 -0.45905353 0.97109156 0.71563312 0.12336973 0.38147524
[37] -1.27555991 -0.71385033 0.62436528 -1.28479250 0.08725524 1.01339743
[43] 0.24897831 1.51173974 0.31005996 -0.16615160 0.71113129 -0.43506071
[49] 1.79157272 -0.58313695 0.33978043 0.10039173 -0.13855298 0.89417963
[55] -0.36132451 0.27311216 0.21008639 -1.20396149 0.30850357 0.71897875
[61] 1.48876139 0.66246491 0.40152976 0.37360987 0.64399409 0.15542483
[67] 2.06413032 -0.27170933 -1.60072962 0.86036835 1.16805902 0.66228805
[73] 0.13942309 0.74318954 0.37619075 -0.68970087 -0.16503717 0.58220773
[79] -0.41672551 -1.14899786 -1.13883889 0.31023603 1.27727698 0.77309041
[85] -0.18753643 0.08609547 0.79810980 0.42536781 0.23691721 2.18712774
[91] 0.02924124 -0.31741091 -0.80729123 -1.80720874 0.60042989 0.69340627
[97] -0.15438712 0.78793832 -0.30680518 -1.60612786
> rowMin(tmp2)
[1] 1.12752617 0.98858120 -0.04567743 2.47227327 -0.52660070 -1.76833967
[7] -0.81799165 -0.27149594 -0.27216132 -0.86276453 0.50169232 0.62193013
[13] -0.73231832 -0.27457115 -0.58327803 -0.21756310 0.54423448 0.91698892
[19] 1.23341021 0.19988571 0.54653556 -1.74594708 1.22518106 0.26774367
[25] 1.02559582 0.57465474 2.64774518 -0.88166775 -0.06331309 -0.74015893
[31] -0.75283292 -0.45905353 0.97109156 0.71563312 0.12336973 0.38147524
[37] -1.27555991 -0.71385033 0.62436528 -1.28479250 0.08725524 1.01339743
[43] 0.24897831 1.51173974 0.31005996 -0.16615160 0.71113129 -0.43506071
[49] 1.79157272 -0.58313695 0.33978043 0.10039173 -0.13855298 0.89417963
[55] -0.36132451 0.27311216 0.21008639 -1.20396149 0.30850357 0.71897875
[61] 1.48876139 0.66246491 0.40152976 0.37360987 0.64399409 0.15542483
[67] 2.06413032 -0.27170933 -1.60072962 0.86036835 1.16805902 0.66228805
[73] 0.13942309 0.74318954 0.37619075 -0.68970087 -0.16503717 0.58220773
[79] -0.41672551 -1.14899786 -1.13883889 0.31023603 1.27727698 0.77309041
[85] -0.18753643 0.08609547 0.79810980 0.42536781 0.23691721 2.18712774
[91] 0.02924124 -0.31741091 -0.80729123 -1.80720874 0.60042989 0.69340627
[97] -0.15438712 0.78793832 -0.30680518 -1.60612786
>
> colMeans(tmp2)
[1] 0.1695933
> colSums(tmp2)
[1] 16.95933
> colVars(tmp2)
[1] 0.8120367
> colSd(tmp2)
[1] 0.9011308
> colMax(tmp2)
[1] 2.647745
> colMin(tmp2)
[1] -1.807209
> colMedians(tmp2)
[1] 0.2429478
> colRanges(tmp2)
[,1]
[1,] -1.807209
[2,] 2.647745
>
> 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] -5.0317220 3.1580967 2.4346790 -0.7570421 5.4676038 -6.8458253
[7] 2.6331037 -0.6655002 1.6916356 -0.1097654
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.0570381
[2,] -1.1247320
[3,] -0.7216922
[4,] 0.3963738
[5,] 1.1227061
>
> rowApply(tmp,sum)
[1] 2.4175551 0.2631596 -4.0657641 -0.8276748 -2.9281186 -4.2440887
[7] 6.2334101 -0.5424796 0.4190771 5.2501879
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 2 8 4 2 1 1 3 1 7 8
[2,] 6 3 10 1 10 10 9 6 2 4
[3,] 4 9 7 4 6 7 1 5 8 6
[4,] 1 1 3 3 8 3 8 9 4 10
[5,] 10 10 8 8 4 9 5 7 3 7
[6,] 8 4 1 5 2 2 6 3 1 2
[7,] 9 7 2 6 9 4 2 8 6 5
[8,] 5 6 5 7 5 6 7 4 10 3
[9,] 3 2 6 9 7 5 4 10 5 9
[10,] 7 5 9 10 3 8 10 2 9 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.4600323 2.4663538 1.3697748 -0.9595846 -0.9673806 -4.8521120
[7] 1.6295622 1.0962785 2.0680884 0.5300168 -1.1320929 -2.0505313
[13] 2.0569906 4.1347015 -0.8202427 -2.0519927 -3.4536186 2.2118497
[19] -1.2610089 0.6787488
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8017646
[2,] -0.8066387
[3,] -0.2879127
[4,] 0.3566421
[5,] 1.0796416
>
> rowApply(tmp,sum)
[1] 5.635813 10.325620 -7.999197 -6.944182 -1.784285
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 15 9 8 2 8
[2,] 11 15 16 17 16
[3,] 5 7 19 10 17
[4,] 7 16 2 8 11
[5,] 8 8 4 3 19
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.0796416 0.5051310 -0.5808385 -0.3469027 -0.3309926 -0.27809258
[2,] 0.3566421 0.8901701 0.2121977 1.0061733 0.2862399 -2.41897118
[3,] -0.8066387 0.2829809 0.7882036 -1.5360233 -1.1293271 -1.13736526
[4,] -1.8017646 0.3324771 -0.1295017 -0.2839407 -1.2793207 -0.05686045
[5,] -0.2879127 0.4555946 1.0797138 0.2011087 1.4860197 -0.96082257
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.4865739 1.06626297 0.1316634 -0.6349612 1.3598556 0.50646319
[2,] 0.5139769 -0.50466549 1.5698300 2.8739216 0.3839194 0.46889827
[3,] 0.1220279 0.12462333 -0.9535305 0.3422517 -0.1382910 -2.07698843
[4,] -0.6050410 0.09275766 1.1058975 0.5786149 -0.6392347 -0.07575525
[5,] 0.1120245 0.31730005 0.2142281 -2.6298103 -2.0983423 -0.87314913
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 2.0364649 1.53364368 -0.71862315 1.0984449 -1.50287095 0.763851495
[2,] 2.4043778 0.79849949 -0.05609195 -0.1615740 -0.23122895 1.665009393
[3,] -0.2604021 0.37770444 0.88884649 -0.6776804 -0.01211996 -0.461479630
[4,] -0.9061986 -0.04296582 -0.18654756 -2.6436832 -1.12356055 -0.006098258
[5,] -1.2172514 1.46781975 -0.74782649 0.3325000 -0.58383816 0.250566673
[,19] [,20]
[1,] -0.47511357 -1.0637886
[2,] -0.15415432 0.4224499
[3,] -0.81155129 -0.9244376
[4,] 0.22748942 0.4990541
[5,] -0.04767916 1.7454711
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: D:/biocbuild/bbs-3.15-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: D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 625 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 541 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: D:/biocbuild/bbs-3.15-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 0.4947207 0.04316574 -0.2819572 1.958815 -0.4398544 -0.2351394 -1.272162
col8 col9 col10 col11 col12 col13 col14
row1 -0.1076782 -0.2860703 -1.820158 1.731387 -0.7907413 0.1354337 0.1130867
col15 col16 col17 col18 col19 col20
row1 -0.2117903 -1.184511 0.1025714 0.5485622 0.03966733 -1.308569
> tmp[,"col10"]
col10
row1 -1.8201576
row2 0.3567272
row3 0.3737915
row4 1.7630948
row5 -1.0324699
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.4947207 0.04316574 -0.2819572 1.958815 -0.4398544 -0.2351394 -1.272162
row5 -1.4799538 0.89929536 2.0985136 1.299611 0.9070696 -0.6098972 1.127743
col8 col9 col10 col11 col12 col13 col14
row1 -0.1076782 -0.2860703 -1.820158 1.731387 -0.7907413 0.1354337 0.1130867
row5 -1.0555360 0.1659845 -1.032470 0.883581 1.7403813 0.3927091 -0.3827372
col15 col16 col17 col18 col19 col20
row1 -0.2117903 -1.184511 0.1025714 0.5485622 0.03966733 -1.30856905
row5 -0.6150400 -1.311861 -2.1718941 -0.8100961 -1.41410842 -0.06161777
> tmp[,c("col6","col20")]
col6 col20
row1 -0.23513940 -1.30856905
row2 0.15624625 -0.21955511
row3 -0.03573304 1.08507425
row4 0.07496862 1.19332113
row5 -0.60989717 -0.06161777
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.2351394 -1.30856905
row5 -0.6098972 -0.06161777
>
>
>
>
> 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 49.26254 51.17273 49.96143 50.40119 48.45413 105.5144 49.36239 49.68774
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.20465 50.85809 49.97592 49.11962 50.16274 51.01744 50.13977 47.059
col17 col18 col19 col20
row1 51.43065 50.63636 49.22438 107.4871
> tmp[,"col10"]
col10
row1 50.85809
row2 29.97348
row3 31.47610
row4 26.77449
row5 51.12169
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.26254 51.17273 49.96143 50.40119 48.45413 105.5144 49.36239 49.68774
row5 50.96597 50.85880 51.21188 51.19597 48.73329 105.4535 51.05947 49.01849
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.20465 50.85809 49.97592 49.11962 50.16274 51.01744 50.13977 47.05900
row5 49.57873 51.12169 49.53912 49.30576 48.98315 52.57845 49.34569 48.78341
col17 col18 col19 col20
row1 51.43065 50.63636 49.22438 107.4871
row5 50.13738 48.58880 49.67205 104.3652
> tmp[,c("col6","col20")]
col6 col20
row1 105.51444 107.48711
row2 75.85350 73.78491
row3 74.64635 75.34750
row4 75.54827 73.76860
row5 105.45351 104.36521
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.5144 107.4871
row5 105.4535 104.3652
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.5144 107.4871
row5 105.4535 104.3652
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.5991067
[2,] -0.9785731
[3,] 1.6847711
[4,] -0.2004462
[5,] 0.3425437
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.01886655 0.26182388
[2,] -0.59373528 1.08155686
[3,] 0.72826607 2.13989215
[4,] -0.70156715 -0.05741053
[5,] 0.57346976 -0.90287122
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.6101559 0.2798359
[2,] -0.7428576 -0.6140226
[3,] 1.6314283 0.2232119
[4,] -1.8614145 1.2395687
[5,] -0.5832894 0.5972215
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.6101559
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.6101559
[2,] -0.7428576
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 0.3131581 -0.6336840 -0.59381954 0.6954229 -2.0594492 -1.1183447
row1 0.2871895 -0.6359172 -0.05629187 -0.1689773 -0.3274236 0.7868146
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.5389636 0.8968366 0.2177535 -1.030955 1.6133332 1.9517952 -0.2024538
row1 1.1716372 0.3276901 0.2887027 -2.522054 -0.4632697 0.7088077 0.9030173
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -1.8855047 0.1508317 0.7271687 0.1287335 0.2748852 -0.1843989 1.9947255
row1 -0.4203289 1.1543539 -0.1848063 1.0738206 0.8528249 -0.3573189 0.9467383
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.4496616 -2.180222 -1.246854 -0.3812193 -0.9365439 -0.8511277 -0.1734624
[,8] [,9] [,10]
row2 2.702563 -0.0301289 0.4100796
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.47799 0.8222993 -0.01452085 0.474704 1.141839 0.2188046 -0.6666679
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.016145 -0.5881898 2.283815 0.4680483 -0.5025604 -0.3373342 0.7972743
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.8636696 1.449899 0.2219062 0.1480137 1.02318 -0.0310854
>
>
> 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: 0x0000000012b13de0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3fbc3af602e"
[2] "D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3fbc1903408d"
[3] "D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3fbc4a4b12dd"
[4] "D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3fbc622468fe"
[5] "D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3fbc5c2d4a67"
[6] "D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3fbc6db1361e"
[7] "D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3fbc58ae5d32"
[8] "D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3fbc3f52231"
[9] "D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3fbc697bd36"
[10] "D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3fbc341a2182"
[11] "D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3fbc704628bc"
[12] "D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3fbcf87694a"
[13] "D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3fbc3cbb2865"
[14] "D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3fbc2f6c1dd4"
[15] "D:/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3fbc5eb66e6f"
>
>
> ### 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: 0x00000000119a2a10>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x00000000119a2a10>
Warning message:
In dir.create(new.directory) :
'D:\biocbuild\bbs-3.15-bioc\meat\BufferedMatrix.Rcheck\tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x00000000119a2a10>
> rowMedians(tmp)
[1] 0.132700818 0.572594667 -0.042576533 0.253091080 0.265346498
[6] -0.733737856 0.242557424 0.042958159 -0.244369266 0.096670512
[11] 0.026324610 0.830737493 0.422050256 -0.129373988 0.416024790
[16] 0.101185007 -0.054410485 0.141102797 -0.360775574 0.531709958
[21] -0.062370116 -0.069218505 -0.119935435 -0.177109721 0.019401529
[26] 0.092662007 -0.445851084 -0.206966151 -0.012402334 -0.074116492
[31] -0.236966444 -0.186666115 0.412081979 -0.180992417 -0.294268305
[36] -0.214967122 0.044842405 0.636983495 0.262163567 -0.030299929
[41] 0.225732231 0.356293979 -0.163753213 -0.088614633 0.225142170
[46] -0.301177300 -0.196043106 0.383195894 0.346148396 -0.042735511
[51] -0.264222339 -0.028056017 -0.309048111 -0.265965490 0.256955165
[56] -0.030890121 -0.051592535 0.260673109 -0.518256836 -0.402697258
[61] -0.173075545 0.033277943 -0.123147022 -0.310725216 0.031341131
[66] -0.059656372 0.587031814 -0.308353489 0.096495184 0.263358855
[71] 0.605466265 0.090204393 0.240963875 0.046394224 -0.423732803
[76] -0.070153453 -0.304031429 -0.062512347 -0.193882992 0.094010422
[81] 0.089405031 0.009526241 0.158423421 0.151443611 0.142850203
[86] 0.144675096 0.171891616 -0.115029642 0.389394007 -0.345564848
[91] 0.248933862 0.009456617 0.327777475 0.178196312 -0.353172411
[96] -0.105036413 -0.289705538 0.188356650 0.430754815 0.523287549
[101] 0.351290536 0.283864993 -0.503087010 -0.311870961 0.122321199
[106] 0.020860774 0.150952821 0.025391335 0.136638852 -0.065650409
[111] -0.374058629 -0.122692001 -0.182137088 0.081340197 0.098665000
[116] 0.190009091 -0.161066341 0.061530363 -0.084550949 0.120144148
[121] -0.111182795 0.193086692 -0.255235053 0.233336117 -0.019803432
[126] 0.441975831 -0.729580721 0.555866926 -0.022175377 -0.117291938
[131] 0.323806790 -0.103580917 0.618758425 -0.448690159 -0.212027720
[136] 0.087640333 -0.773377604 -0.081898362 0.706170690 -0.064500807
[141] 0.004519884 0.079150834 -0.195486993 -0.109665479 0.059832964
[146] 0.039885869 0.272863454 0.027948168 -0.347162631 -0.116110059
[151] 0.156057388 -0.078870236 0.227539670 0.453098334 -0.237697589
[156] -0.376980178 -0.165438153 -0.207105397 -0.443638206 -0.148045184
[161] 0.220059089 -0.698741048 0.108623974 0.047270389 0.522408681
[166] -0.153740141 -0.140248443 -0.007304342 -0.061842310 0.024795842
[171] -0.280571098 -0.030147422 0.135498628 -0.412717431 0.177596598
[176] -0.422211841 -0.429070438 -0.195283255 -0.665581185 0.308089892
[181] 0.110988275 -0.049858871 -0.135070787 -0.063730450 0.166294487
[186] 0.332414531 -0.037459031 0.524228701 0.360848318 0.112971318
[191] -0.283123788 0.241036318 -0.415846958 0.525576375 0.092958291
[196] 0.273676361 -0.156006608 0.292760770 0.444147813 -0.005783859
[201] -0.377035594 -0.562076814 0.253522890 0.267978032 -0.208201083
[206] -0.300788069 0.148964703 0.420886554 -0.035515208 -0.351340457
[211] 0.128730766 0.199689531 0.336742829 0.148515152 0.295847474
[216] -0.301486712 0.031706398 -0.159136728 0.650771329 -0.328626677
[221] -0.011920882 -0.096341654 0.772765255 -0.211456348 0.032583495
[226] 0.037910554 -0.397324916 -0.035283298 0.045024568 -0.070352092
>
> proc.time()
user system elapsed
2.79 9.75 94.89
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2021-11-21 r81221) -- "Unsuffered Consequences"
Copyright (C) 2021 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: 0x0000000012ae4010>
> .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: 0x0000000012ae4010>
> .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: 0x0000000012ae4010>
> .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: 0x0000000012ae4010>
> 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: 0x0000000012ae40f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000012ae40f0>
> .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: 0x0000000012ae40f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000012ae40f0>
> .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: 0x0000000012ae40f0>
> 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: 0x0000000012ae3ec0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000012ae3ec0>
> .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: 0x0000000012ae3ec0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x0000000012ae3ec0>
> .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: 0x0000000012ae3ec0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x0000000012ae3ec0>
> .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: 0x0000000012ae3ec0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x0000000012ae3ec0>
> .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: 0x0000000012ae3ec0>
> 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: 0x0000000012ae4160>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x0000000012ae4160>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000012ae4160>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000012ae4160>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile175428f36ea" "BufferedMatrixFile175455ba15d1"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile175428f36ea" "BufferedMatrixFile175455ba15d1"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000012ae44e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000012ae44e0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x0000000012ae44e0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x0000000012ae44e0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x0000000012ae44e0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x0000000012ae44e0>
> .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: 0x0000000012ae42b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000012ae42b0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x0000000012ae42b0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x0000000012ae42b0>
> 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: 0x0000000012ae41d0>
> .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: 0x0000000012ae41d0>
> rm(P)
>
> proc.time()
user system elapsed
0.43 0.04 0.82
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2021-11-21 r81221) -- "Unsuffered Consequences"
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Platform: x86_64-w64-mingw32/x64 (64-bit)
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
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Type 'demo()' for some demos, 'help()' for on-line help, or
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> 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
0.23 0.10 0.31