Ben Bolstad
| Snapshot Date: 2025-03-17 13:00 -0400 (Mon, 17 Mar 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_20 |
| git_last_commit: 32b6f6a |
| git_last_commit_date: 2024-10-29 09:27:20 -0400 (Tue, 29 Oct 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2025-03-20 12:06 -0400 (Thu, 20 Mar 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4756 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.3 (2025-02-28 ucrt) -- "Trophy Case" | 4487 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4514 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4441 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4406 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 251/2289 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.70.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.70.0 |
| Command: F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings BufferedMatrix_1.70.0.tar.gz |
| StartedAt: 2025-03-17 23:28:46 -0400 (Mon, 17 Mar 2025) |
| EndedAt: 2025-03-17 23:31:24 -0400 (Mon, 17 Mar 2025) |
| EllapsedTime: 157.9 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings BufferedMatrix_1.70.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck'
* using R version 4.4.3 (2025-02-28 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
gcc.exe (GCC) 13.3.0
GNU Fortran (GCC) 13.3.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* using option '--no-vignettes'
* checking for file 'BufferedMatrix/DESCRIPTION' ... OK
* this is package 'BufferedMatrix' version '1.70.0'
* 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
* used C compiler: 'gcc.exe (GCC) 13.3.0'
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files for x64 is not available
File 'F:/biocbuild/bbs-3.20-bioc/R/library/BufferedMatrix/libs/x64/BufferedMatrix.dll':
Found '_exit', possibly from '_exit' (C)
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 nor [v]sprintf. 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 ... 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-3.20-bioc/meat/BufferedMatrix.Rcheck/00check.log'
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library 'F:/biocbuild/bbs-3.20-bioc/R/library'
* installing *source* package 'BufferedMatrix' ...
** using staged installation
** libs
using C compiler: 'gcc.exe (GCC) 13.3.0'
gcc -I"F:/biocbuild/bbs-3.20-bioc/R/include" -DNDEBUG -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -mfpmath=sse -msse2 -mstackrealign -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"F:/biocbuild/bbs-3.20-bioc/R/include" -DNDEBUG -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -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){
| ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: 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-3.20-bioc/R/include" -DNDEBUG -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -mfpmath=sse -msse2 -mstackrealign -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"F:/biocbuild/bbs-3.20-bioc/R/include" -DNDEBUG -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -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:/rtools44/x86_64-w64-mingw32.static.posix/lib/x64 -LC:/rtools44/x86_64-w64-mingw32.static.posix/lib -LF:/biocbuild/bbs-3.20-bioc/R/bin/x64 -lR
installing to F:/biocbuild/bbs-3.20-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 4.4.3 (2025-02-28 ucrt) -- "Trophy Case"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
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 0.20 0.98
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.3 (2025-02-28 ucrt) -- "Trophy Case"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
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-3.20-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 467958 25.0 1020317 54.5 633411 33.9
Vcells 853502 6.6 8388608 64.0 2003112 15.3
>
>
>
>
> ##
> ## 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 Mar 17 23:29:18 2025"
> 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 Mar 17 23:29:19 2025"
>
>
> 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: 0x0000022b4ecff650>
>
>
>
> 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 Mar 17 23:29:45 2025"
> 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 Mar 17 23:29:53 2025"
>
> ColMode(tmp2)
<pointer: 0x0000022b4ecff650>
>
>
>
> ### 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,] 99.8907285 -0.6527934 0.1403837 0.18265539
[2,] 0.5715286 -0.7499837 -1.1364350 0.71462639
[3,] -0.2874517 -2.0015868 -1.1547443 1.71566880
[4,] 2.0847808 -0.7040841 -0.2492610 0.06733288
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.20-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,] 99.8907285 0.6527934 0.1403837 0.18265539
[2,] 0.5715286 0.7499837 1.1364350 0.71462639
[3,] 0.2874517 2.0015868 1.1547443 1.71566880
[4,] 2.0847808 0.7040841 0.2492610 0.06733288
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9945349 0.8079563 0.3746782 0.4273820
[2,] 0.7559951 0.8660160 1.0660370 0.8453558
[3,] 0.5361452 1.4147745 1.0745903 1.3098354
[4,] 1.4438770 0.8390972 0.4992604 0.2594858
>
> 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-3.20-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,] 224.83608 33.73236 28.88717 29.45648
[2,] 33.13148 34.41014 36.79681 34.16818
[3,] 30.64890 41.14933 36.90065 39.81402
[4,] 41.52355 34.09506 30.24187 27.66219
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x0000022b4ecff950>
> exp(tmp5)
<pointer: 0x0000022b4ecff950>
> log(tmp5,2)
<pointer: 0x0000022b4ecff950>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.9668
> Min(tmp5)
[1] 54.20329
> mean(tmp5)
[1] 73.2088
> Sum(tmp5)
[1] 14641.76
> Var(tmp5)
[1] 860.9564
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.81604 72.56589 70.66426 69.87782 71.92764 68.13594 72.12188 72.45184
[9] 71.84653 71.68018
> rowSums(tmp5)
[1] 1816.321 1451.318 1413.285 1397.556 1438.553 1362.719 1442.438 1449.037
[9] 1436.931 1433.604
> rowVars(tmp5)
[1] 7959.88080 62.21160 69.60202 93.51094 117.00485 76.30474
[7] 32.19247 84.75474 77.28878 64.29678
> rowSd(tmp5)
[1] 89.218164 7.887433 8.342783 9.670105 10.816878 8.735258 5.673841
[8] 9.206234 8.791404 8.018528
> rowMax(tmp5)
[1] 467.96684 85.51534 85.64694 89.67290 95.71571 84.17051 82.39542
[8] 96.41368 93.76040 84.39151
> rowMin(tmp5)
[1] 55.64423 55.70372 55.05072 56.30307 56.25948 54.20329 62.22769 56.32907
[9] 58.78897 56.30942
>
> colMeans(tmp5)
[1] 108.39386 72.58416 71.77707 69.24347 69.97089 73.52019 73.01035
[8] 72.84366 71.74134 74.15003 74.87753 69.50909 67.36146 67.79306
[15] 68.61677 70.15437 71.74038 72.01222 74.90660 69.96953
> colSums(tmp5)
[1] 1083.9386 725.8416 717.7707 692.4347 699.7089 735.2019 730.1035
[8] 728.4366 717.4134 741.5003 748.7753 695.0909 673.6146 677.9306
[15] 686.1677 701.5437 717.4038 720.1222 749.0660 699.6953
> colVars(tmp5)
[1] 16035.33523 56.24696 39.94540 56.63224 21.62176 62.69613
[7] 55.32426 25.45773 89.83799 67.65427 124.54390 89.41580
[13] 95.06740 150.45595 85.51533 129.01398 67.41123 83.41237
[19] 71.22639 77.31051
> colSd(tmp5)
[1] 126.630704 7.499797 6.320237 7.525439 4.649921 7.918089
[7] 7.438028 5.045566 9.478290 8.225221 11.159924 9.455993
[13] 9.750251 12.266049 9.247450 11.358432 8.210434 9.133038
[19] 8.439573 8.792640
> colMax(tmp5)
[1] 467.96684 85.64694 80.10272 82.86767 76.99673 84.96179 83.03134
[8] 79.58308 84.17051 85.78225 93.76040 84.99049 83.39441 96.41368
[15] 84.13985 95.71571 85.51534 90.26297 83.81734 81.65806
> colMin(tmp5)
[1] 56.30942 57.86496 60.12485 57.57523 63.28187 61.18678 59.56564 63.25878
[9] 55.05072 61.98304 56.32907 54.20329 55.21211 55.64423 57.43408 57.67611
[17] 61.61017 58.68131 56.30307 56.87305
>
>
> ### 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 72.56589 70.66426 69.87782 71.92764 68.13594 72.12188 72.45184
[9] 71.84653 71.68018
> rowSums(tmp5)
[1] NA 1451.318 1413.285 1397.556 1438.553 1362.719 1442.438 1449.037
[9] 1436.931 1433.604
> rowVars(tmp5)
[1] 8398.23330 62.21160 69.60202 93.51094 117.00485 76.30474
[7] 32.19247 84.75474 77.28878 64.29678
> rowSd(tmp5)
[1] 91.641875 7.887433 8.342783 9.670105 10.816878 8.735258 5.673841
[8] 9.206234 8.791404 8.018528
> rowMax(tmp5)
[1] NA 85.51534 85.64694 89.67290 95.71571 84.17051 82.39542 96.41368
[9] 93.76040 84.39151
> rowMin(tmp5)
[1] NA 55.70372 55.05072 56.30307 56.25948 54.20329 62.22769 56.32907
[9] 58.78897 56.30942
>
> colMeans(tmp5)
[1] 108.39386 72.58416 71.77707 69.24347 69.97089 73.52019 73.01035
[8] 72.84366 NA 74.15003 74.87753 69.50909 67.36146 67.79306
[15] 68.61677 70.15437 71.74038 72.01222 74.90660 69.96953
> colSums(tmp5)
[1] 1083.9386 725.8416 717.7707 692.4347 699.7089 735.2019 730.1035
[8] 728.4366 NA 741.5003 748.7753 695.0909 673.6146 677.9306
[15] 686.1677 701.5437 717.4038 720.1222 749.0660 699.6953
> colVars(tmp5)
[1] 16035.33523 56.24696 39.94540 56.63224 21.62176 62.69613
[7] 55.32426 25.45773 NA 67.65427 124.54390 89.41580
[13] 95.06740 150.45595 85.51533 129.01398 67.41123 83.41237
[19] 71.22639 77.31051
> colSd(tmp5)
[1] 126.630704 7.499797 6.320237 7.525439 4.649921 7.918089
[7] 7.438028 5.045566 NA 8.225221 11.159924 9.455993
[13] 9.750251 12.266049 9.247450 11.358432 8.210434 9.133038
[19] 8.439573 8.792640
> colMax(tmp5)
[1] 467.96684 85.64694 80.10272 82.86767 76.99673 84.96179 83.03134
[8] 79.58308 NA 85.78225 93.76040 84.99049 83.39441 96.41368
[15] 84.13985 95.71571 85.51534 90.26297 83.81734 81.65806
> colMin(tmp5)
[1] 56.30942 57.86496 60.12485 57.57523 63.28187 61.18678 59.56564 63.25878
[9] NA 61.98304 56.32907 54.20329 55.21211 55.64423 57.43408 57.67611
[17] 61.61017 58.68131 56.30307 56.87305
>
> Max(tmp5,na.rm=TRUE)
[1] 467.9668
> Min(tmp5,na.rm=TRUE)
[1] 54.20329
> mean(tmp5,na.rm=TRUE)
[1] 73.16116
> Sum(tmp5,na.rm=TRUE)
[1] 14559.07
> Var(tmp5,na.rm=TRUE)
[1] 864.8485
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.24381 72.56589 70.66426 69.87782 71.92764 68.13594 72.12188 72.45184
[9] 71.84653 71.68018
> rowSums(tmp5,na.rm=TRUE)
[1] 1733.632 1451.318 1413.285 1397.556 1438.553 1362.719 1442.438 1449.037
[9] 1436.931 1433.604
> rowVars(tmp5,na.rm=TRUE)
[1] 8398.23330 62.21160 69.60202 93.51094 117.00485 76.30474
[7] 32.19247 84.75474 77.28878 64.29678
> rowSd(tmp5,na.rm=TRUE)
[1] 91.641875 7.887433 8.342783 9.670105 10.816878 8.735258 5.673841
[8] 9.206234 8.791404 8.018528
> rowMax(tmp5,na.rm=TRUE)
[1] 467.96684 85.51534 85.64694 89.67290 95.71571 84.17051 82.39542
[8] 96.41368 93.76040 84.39151
> rowMin(tmp5,na.rm=TRUE)
[1] 55.64423 55.70372 55.05072 56.30307 56.25948 54.20329 62.22769 56.32907
[9] 58.78897 56.30942
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.39386 72.58416 71.77707 69.24347 69.97089 73.52019 73.01035
[8] 72.84366 70.52500 74.15003 74.87753 69.50909 67.36146 67.79306
[15] 68.61677 70.15437 71.74038 72.01222 74.90660 69.96953
> colSums(tmp5,na.rm=TRUE)
[1] 1083.9386 725.8416 717.7707 692.4347 699.7089 735.2019 730.1035
[8] 728.4366 634.7250 741.5003 748.7753 695.0909 673.6146 677.9306
[15] 686.1677 701.5437 717.4038 720.1222 749.0660 699.6953
> colVars(tmp5,na.rm=TRUE)
[1] 16035.33523 56.24696 39.94540 56.63224 21.62176 62.69613
[7] 55.32426 25.45773 84.42365 67.65427 124.54390 89.41580
[13] 95.06740 150.45595 85.51533 129.01398 67.41123 83.41237
[19] 71.22639 77.31051
> colSd(tmp5,na.rm=TRUE)
[1] 126.630704 7.499797 6.320237 7.525439 4.649921 7.918089
[7] 7.438028 5.045566 9.188235 8.225221 11.159924 9.455993
[13] 9.750251 12.266049 9.247450 11.358432 8.210434 9.133038
[19] 8.439573 8.792640
> colMax(tmp5,na.rm=TRUE)
[1] 467.96684 85.64694 80.10272 82.86767 76.99673 84.96179 83.03134
[8] 79.58308 84.17051 85.78225 93.76040 84.99049 83.39441 96.41368
[15] 84.13985 95.71571 85.51534 90.26297 83.81734 81.65806
> colMin(tmp5,na.rm=TRUE)
[1] 56.30942 57.86496 60.12485 57.57523 63.28187 61.18678 59.56564 63.25878
[9] 55.05072 61.98304 56.32907 54.20329 55.21211 55.64423 57.43408 57.67611
[17] 61.61017 58.68131 56.30307 56.87305
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 72.56589 70.66426 69.87782 71.92764 68.13594 72.12188 72.45184
[9] 71.84653 71.68018
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1451.318 1413.285 1397.556 1438.553 1362.719 1442.438 1449.037
[9] 1436.931 1433.604
> rowVars(tmp5,na.rm=TRUE)
[1] NA 62.21160 69.60202 93.51094 117.00485 76.30474 32.19247
[8] 84.75474 77.28878 64.29678
> rowSd(tmp5,na.rm=TRUE)
[1] NA 7.887433 8.342783 9.670105 10.816878 8.735258 5.673841
[8] 9.206234 8.791404 8.018528
> rowMax(tmp5,na.rm=TRUE)
[1] NA 85.51534 85.64694 89.67290 95.71571 84.17051 82.39542 96.41368
[9] 93.76040 84.39151
> rowMin(tmp5,na.rm=TRUE)
[1] NA 55.70372 55.05072 56.30307 56.25948 54.20329 62.22769 56.32907
[9] 58.78897 56.30942
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 68.44130 72.84802 73.07176 70.12499 70.71411 73.68223 72.56899 72.09484
[9] NaN 72.85756 75.14295 67.78893 66.53746 69.14293 69.02407 71.54084
[17] 72.67781 72.05542 75.08783 69.12178
> colSums(tmp5,na.rm=TRUE)
[1] 615.9717 655.6321 657.6459 631.1249 636.4270 663.1401 653.1209 648.8536
[9] 0.0000 655.7180 676.2866 610.1004 598.8372 622.2863 621.2166 643.8676
[17] 654.1003 648.4988 675.7905 622.0960
> colVars(tmp5,na.rm=TRUE)
[1] 82.42866 62.49462 26.08103 54.96916 18.11019 70.23776 60.04830
[8] 22.33164 NA 57.31817 139.31936 67.30473 99.31250 148.76376
[15] 94.33843 123.51477 65.95138 93.81793 79.76020 78.88913
> colSd(tmp5,na.rm=TRUE)
[1] 9.079023 7.905354 5.106959 7.414119 4.255607 8.380797 7.749084
[8] 4.725637 NA 7.570876 11.803362 8.203946 9.965566 12.196875
[15] 9.712797 11.113720 8.121045 9.685965 8.930857 8.881955
> colMax(tmp5,na.rm=TRUE)
[1] 86.42583 85.64694 80.10272 82.86767 76.99673 84.96179 83.03134 78.12480
[9] -Inf 84.39151 93.76040 83.74769 83.39441 96.41368 84.13985 95.71571
[17] 85.51534 90.26297 83.81734 81.65806
> colMin(tmp5,na.rm=TRUE)
[1] 56.30942 57.86496 62.94448 57.57523 63.32772 61.18678 59.56564 63.25878
[9] Inf 61.98304 56.32907 54.20329 55.21211 55.70372 57.43408 60.21632
[17] 61.61017 58.68131 56.30307 56.87305
>
>
>
>
> 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] 220.0455 275.9516 244.0008 170.7105 216.2905 277.2186 194.4417 330.3305
[9] 222.5068 358.9149
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 220.0455 275.9516 244.0008 170.7105 216.2905 277.2186 194.4417 330.3305
[9] 222.5068 358.9149
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 1.421085e-14 5.684342e-14 2.131628e-13 -1.989520e-13 1.136868e-13
[6] 0.000000e+00 2.842171e-14 5.684342e-14 2.842171e-14 1.705303e-13
[11] -2.273737e-13 8.526513e-14 2.273737e-13 -1.421085e-13 0.000000e+00
[16] 5.684342e-14 -5.684342e-14 -5.684342e-14 -1.705303e-13 2.557954e-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)
+ }
8 10
1 16
10 15
3 1
1 8
1 6
8 20
8 9
5 8
7 8
2 5
6 1
8 20
10 2
10 14
5 6
2 20
7 7
2 8
8 20
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] 2.022981
> Min(tmp)
[1] -2.211624
> mean(tmp)
[1] 0.004939772
> Sum(tmp)
[1] 0.4939772
> Var(tmp)
[1] 0.7948357
>
> rowMeans(tmp)
[1] 0.004939772
> rowSums(tmp)
[1] 0.4939772
> rowVars(tmp)
[1] 0.7948357
> rowSd(tmp)
[1] 0.8915356
> rowMax(tmp)
[1] 2.022981
> rowMin(tmp)
[1] -2.211624
>
> colMeans(tmp)
[1] -1.22990684 0.32184229 0.04874561 0.13244773 0.48187821 0.33882586
[7] -0.72572102 0.65921472 0.50059447 -2.21162352 0.81393807 1.50601160
[13] -1.08443785 -0.79028969 -0.88728479 -2.19665911 1.28536573 -0.19809914
[19] 0.01092636 -0.69347784 -0.08154314 -0.87922821 -1.50979902 -0.24913115
[25] -1.15614934 -0.18354392 0.58974460 0.53481342 -0.74924560 0.18588513
[31] 0.75455621 -0.09680240 -1.30796352 0.02739043 -0.83682381 0.50477567
[37] 1.95000826 1.40770897 1.56305271 0.40517907 0.19314535 -1.85341505
[43] 0.18281184 0.96315064 0.96956257 0.05997712 0.06602166 -0.16523378
[49] -0.54879408 1.25624388 0.41571295 2.02298086 0.26240675 0.02414519
[55] 0.91433452 1.44500057 -0.19366689 -0.61745467 0.10662338 0.75205060
[61] 1.02305556 1.11856526 -1.15292361 -1.82288782 0.52722472 0.91873925
[67] -0.15341340 0.33648645 0.16444246 0.35610183 -0.56144365 0.44030725
[73] -0.30584943 -0.71755896 -1.04383219 1.88176423 -0.59996406 0.83831801
[79] 0.20533670 -1.82899656 -0.91048658 -0.84331197 0.10564420 -0.63314849
[85] 0.46699982 -0.64712587 -1.17030464 -0.24958826 0.43396725 -0.29373558
[91] 0.23864974 0.44588884 -1.09631679 0.22347485 0.05476344 0.31991828
[97] 0.58487350 0.42887605 0.39389844 -0.19320969
> colSums(tmp)
[1] -1.22990684 0.32184229 0.04874561 0.13244773 0.48187821 0.33882586
[7] -0.72572102 0.65921472 0.50059447 -2.21162352 0.81393807 1.50601160
[13] -1.08443785 -0.79028969 -0.88728479 -2.19665911 1.28536573 -0.19809914
[19] 0.01092636 -0.69347784 -0.08154314 -0.87922821 -1.50979902 -0.24913115
[25] -1.15614934 -0.18354392 0.58974460 0.53481342 -0.74924560 0.18588513
[31] 0.75455621 -0.09680240 -1.30796352 0.02739043 -0.83682381 0.50477567
[37] 1.95000826 1.40770897 1.56305271 0.40517907 0.19314535 -1.85341505
[43] 0.18281184 0.96315064 0.96956257 0.05997712 0.06602166 -0.16523378
[49] -0.54879408 1.25624388 0.41571295 2.02298086 0.26240675 0.02414519
[55] 0.91433452 1.44500057 -0.19366689 -0.61745467 0.10662338 0.75205060
[61] 1.02305556 1.11856526 -1.15292361 -1.82288782 0.52722472 0.91873925
[67] -0.15341340 0.33648645 0.16444246 0.35610183 -0.56144365 0.44030725
[73] -0.30584943 -0.71755896 -1.04383219 1.88176423 -0.59996406 0.83831801
[79] 0.20533670 -1.82899656 -0.91048658 -0.84331197 0.10564420 -0.63314849
[85] 0.46699982 -0.64712587 -1.17030464 -0.24958826 0.43396725 -0.29373558
[91] 0.23864974 0.44588884 -1.09631679 0.22347485 0.05476344 0.31991828
[97] 0.58487350 0.42887605 0.39389844 -0.19320969
> 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] -1.22990684 0.32184229 0.04874561 0.13244773 0.48187821 0.33882586
[7] -0.72572102 0.65921472 0.50059447 -2.21162352 0.81393807 1.50601160
[13] -1.08443785 -0.79028969 -0.88728479 -2.19665911 1.28536573 -0.19809914
[19] 0.01092636 -0.69347784 -0.08154314 -0.87922821 -1.50979902 -0.24913115
[25] -1.15614934 -0.18354392 0.58974460 0.53481342 -0.74924560 0.18588513
[31] 0.75455621 -0.09680240 -1.30796352 0.02739043 -0.83682381 0.50477567
[37] 1.95000826 1.40770897 1.56305271 0.40517907 0.19314535 -1.85341505
[43] 0.18281184 0.96315064 0.96956257 0.05997712 0.06602166 -0.16523378
[49] -0.54879408 1.25624388 0.41571295 2.02298086 0.26240675 0.02414519
[55] 0.91433452 1.44500057 -0.19366689 -0.61745467 0.10662338 0.75205060
[61] 1.02305556 1.11856526 -1.15292361 -1.82288782 0.52722472 0.91873925
[67] -0.15341340 0.33648645 0.16444246 0.35610183 -0.56144365 0.44030725
[73] -0.30584943 -0.71755896 -1.04383219 1.88176423 -0.59996406 0.83831801
[79] 0.20533670 -1.82899656 -0.91048658 -0.84331197 0.10564420 -0.63314849
[85] 0.46699982 -0.64712587 -1.17030464 -0.24958826 0.43396725 -0.29373558
[91] 0.23864974 0.44588884 -1.09631679 0.22347485 0.05476344 0.31991828
[97] 0.58487350 0.42887605 0.39389844 -0.19320969
> colMin(tmp)
[1] -1.22990684 0.32184229 0.04874561 0.13244773 0.48187821 0.33882586
[7] -0.72572102 0.65921472 0.50059447 -2.21162352 0.81393807 1.50601160
[13] -1.08443785 -0.79028969 -0.88728479 -2.19665911 1.28536573 -0.19809914
[19] 0.01092636 -0.69347784 -0.08154314 -0.87922821 -1.50979902 -0.24913115
[25] -1.15614934 -0.18354392 0.58974460 0.53481342 -0.74924560 0.18588513
[31] 0.75455621 -0.09680240 -1.30796352 0.02739043 -0.83682381 0.50477567
[37] 1.95000826 1.40770897 1.56305271 0.40517907 0.19314535 -1.85341505
[43] 0.18281184 0.96315064 0.96956257 0.05997712 0.06602166 -0.16523378
[49] -0.54879408 1.25624388 0.41571295 2.02298086 0.26240675 0.02414519
[55] 0.91433452 1.44500057 -0.19366689 -0.61745467 0.10662338 0.75205060
[61] 1.02305556 1.11856526 -1.15292361 -1.82288782 0.52722472 0.91873925
[67] -0.15341340 0.33648645 0.16444246 0.35610183 -0.56144365 0.44030725
[73] -0.30584943 -0.71755896 -1.04383219 1.88176423 -0.59996406 0.83831801
[79] 0.20533670 -1.82899656 -0.91048658 -0.84331197 0.10564420 -0.63314849
[85] 0.46699982 -0.64712587 -1.17030464 -0.24958826 0.43396725 -0.29373558
[91] 0.23864974 0.44588884 -1.09631679 0.22347485 0.05476344 0.31991828
[97] 0.58487350 0.42887605 0.39389844 -0.19320969
> colMedians(tmp)
[1] -1.22990684 0.32184229 0.04874561 0.13244773 0.48187821 0.33882586
[7] -0.72572102 0.65921472 0.50059447 -2.21162352 0.81393807 1.50601160
[13] -1.08443785 -0.79028969 -0.88728479 -2.19665911 1.28536573 -0.19809914
[19] 0.01092636 -0.69347784 -0.08154314 -0.87922821 -1.50979902 -0.24913115
[25] -1.15614934 -0.18354392 0.58974460 0.53481342 -0.74924560 0.18588513
[31] 0.75455621 -0.09680240 -1.30796352 0.02739043 -0.83682381 0.50477567
[37] 1.95000826 1.40770897 1.56305271 0.40517907 0.19314535 -1.85341505
[43] 0.18281184 0.96315064 0.96956257 0.05997712 0.06602166 -0.16523378
[49] -0.54879408 1.25624388 0.41571295 2.02298086 0.26240675 0.02414519
[55] 0.91433452 1.44500057 -0.19366689 -0.61745467 0.10662338 0.75205060
[61] 1.02305556 1.11856526 -1.15292361 -1.82288782 0.52722472 0.91873925
[67] -0.15341340 0.33648645 0.16444246 0.35610183 -0.56144365 0.44030725
[73] -0.30584943 -0.71755896 -1.04383219 1.88176423 -0.59996406 0.83831801
[79] 0.20533670 -1.82899656 -0.91048658 -0.84331197 0.10564420 -0.63314849
[85] 0.46699982 -0.64712587 -1.17030464 -0.24958826 0.43396725 -0.29373558
[91] 0.23864974 0.44588884 -1.09631679 0.22347485 0.05476344 0.31991828
[97] 0.58487350 0.42887605 0.39389844 -0.19320969
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.229907 0.3218423 0.04874561 0.1324477 0.4818782 0.3388259 -0.725721
[2,] -1.229907 0.3218423 0.04874561 0.1324477 0.4818782 0.3388259 -0.725721
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.6592147 0.5005945 -2.211624 0.8139381 1.506012 -1.084438 -0.7902897
[2,] 0.6592147 0.5005945 -2.211624 0.8139381 1.506012 -1.084438 -0.7902897
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.8872848 -2.196659 1.285366 -0.1980991 0.01092636 -0.6934778 -0.08154314
[2,] -0.8872848 -2.196659 1.285366 -0.1980991 0.01092636 -0.6934778 -0.08154314
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.8792282 -1.509799 -0.2491311 -1.156149 -0.1835439 0.5897446 0.5348134
[2,] -0.8792282 -1.509799 -0.2491311 -1.156149 -0.1835439 0.5897446 0.5348134
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.7492456 0.1858851 0.7545562 -0.0968024 -1.307964 0.02739043 -0.8368238
[2,] -0.7492456 0.1858851 0.7545562 -0.0968024 -1.307964 0.02739043 -0.8368238
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.5047757 1.950008 1.407709 1.563053 0.4051791 0.1931454 -1.853415
[2,] 0.5047757 1.950008 1.407709 1.563053 0.4051791 0.1931454 -1.853415
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.1828118 0.9631506 0.9695626 0.05997712 0.06602166 -0.1652338 -0.5487941
[2,] 0.1828118 0.9631506 0.9695626 0.05997712 0.06602166 -0.1652338 -0.5487941
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 1.256244 0.4157129 2.022981 0.2624068 0.02414519 0.9143345 1.445001
[2,] 1.256244 0.4157129 2.022981 0.2624068 0.02414519 0.9143345 1.445001
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.1936669 -0.6174547 0.1066234 0.7520506 1.023056 1.118565 -1.152924
[2,] -0.1936669 -0.6174547 0.1066234 0.7520506 1.023056 1.118565 -1.152924
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.822888 0.5272247 0.9187393 -0.1534134 0.3364865 0.1644425 0.3561018
[2,] -1.822888 0.5272247 0.9187393 -0.1534134 0.3364865 0.1644425 0.3561018
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.5614437 0.4403072 -0.3058494 -0.717559 -1.043832 1.881764 -0.5999641
[2,] -0.5614437 0.4403072 -0.3058494 -0.717559 -1.043832 1.881764 -0.5999641
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.838318 0.2053367 -1.828997 -0.9104866 -0.843312 0.1056442 -0.6331485
[2,] 0.838318 0.2053367 -1.828997 -0.9104866 -0.843312 0.1056442 -0.6331485
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.4669998 -0.6471259 -1.170305 -0.2495883 0.4339673 -0.2937356 0.2386497
[2,] 0.4669998 -0.6471259 -1.170305 -0.2495883 0.4339673 -0.2937356 0.2386497
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.4458888 -1.096317 0.2234748 0.05476344 0.3199183 0.5848735 0.428876
[2,] 0.4458888 -1.096317 0.2234748 0.05476344 0.3199183 0.5848735 0.428876
[,99] [,100]
[1,] 0.3938984 -0.1932097
[2,] 0.3938984 -0.1932097
>
>
> Max(tmp2)
[1] 2.774464
> Min(tmp2)
[1] -2.368664
> mean(tmp2)
[1] 0.06396754
> Sum(tmp2)
[1] 6.396754
> Var(tmp2)
[1] 1.067269
>
> rowMeans(tmp2)
[1] 1.01080236 -0.41032605 0.24565920 -2.11588882 0.85357512 0.29789425
[7] 0.50997005 -0.66365136 1.59572591 -1.40009079 -0.40930127 -1.13418159
[13] 1.19479561 -1.00208312 1.23205724 0.48796975 -0.15228989 -0.38220023
[19] 0.31859675 -0.11070990 -0.07959859 1.02722366 1.95109787 1.80014628
[25] -0.05305813 -0.19373430 -1.55263356 -2.19076308 0.93848398 -0.53545146
[31] 0.23632791 0.95952083 0.20580549 -0.31648008 -0.91197612 1.70245954
[37] 0.64723568 0.96181639 0.41481020 -0.24308565 -0.77520744 -1.43224143
[43] 0.80102653 -2.36866397 0.84543541 0.45411315 -0.07932439 2.36224126
[49] -0.40158559 -1.36306163 -0.27677657 -0.70674165 -0.19731109 -0.81209808
[55] -1.63543075 -1.00448987 0.83868949 0.75412133 -0.20177665 1.56955844
[61] -0.57407434 -0.10984080 -0.76113791 -0.27730466 -0.45123341 1.35140408
[67] -0.94727522 -1.04842564 -0.04667484 -0.58697406 1.67058724 0.53346829
[73] 1.05186984 -0.17284198 0.16921809 1.96468522 0.79190828 2.77446439
[79] 0.29014559 -1.05490386 -0.36000601 -0.96210669 -1.13428470 -0.65418107
[85] -0.67867813 -0.11978114 0.45013335 -0.74546522 -0.24453473 1.38701248
[91] 1.37188095 0.14306615 -0.36195099 -0.33487674 -0.16928265 -0.81456880
[97] -0.57803467 1.58964356 1.10111349 1.83964432
> rowSums(tmp2)
[1] 1.01080236 -0.41032605 0.24565920 -2.11588882 0.85357512 0.29789425
[7] 0.50997005 -0.66365136 1.59572591 -1.40009079 -0.40930127 -1.13418159
[13] 1.19479561 -1.00208312 1.23205724 0.48796975 -0.15228989 -0.38220023
[19] 0.31859675 -0.11070990 -0.07959859 1.02722366 1.95109787 1.80014628
[25] -0.05305813 -0.19373430 -1.55263356 -2.19076308 0.93848398 -0.53545146
[31] 0.23632791 0.95952083 0.20580549 -0.31648008 -0.91197612 1.70245954
[37] 0.64723568 0.96181639 0.41481020 -0.24308565 -0.77520744 -1.43224143
[43] 0.80102653 -2.36866397 0.84543541 0.45411315 -0.07932439 2.36224126
[49] -0.40158559 -1.36306163 -0.27677657 -0.70674165 -0.19731109 -0.81209808
[55] -1.63543075 -1.00448987 0.83868949 0.75412133 -0.20177665 1.56955844
[61] -0.57407434 -0.10984080 -0.76113791 -0.27730466 -0.45123341 1.35140408
[67] -0.94727522 -1.04842564 -0.04667484 -0.58697406 1.67058724 0.53346829
[73] 1.05186984 -0.17284198 0.16921809 1.96468522 0.79190828 2.77446439
[79] 0.29014559 -1.05490386 -0.36000601 -0.96210669 -1.13428470 -0.65418107
[85] -0.67867813 -0.11978114 0.45013335 -0.74546522 -0.24453473 1.38701248
[91] 1.37188095 0.14306615 -0.36195099 -0.33487674 -0.16928265 -0.81456880
[97] -0.57803467 1.58964356 1.10111349 1.83964432
> 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] 1.01080236 -0.41032605 0.24565920 -2.11588882 0.85357512 0.29789425
[7] 0.50997005 -0.66365136 1.59572591 -1.40009079 -0.40930127 -1.13418159
[13] 1.19479561 -1.00208312 1.23205724 0.48796975 -0.15228989 -0.38220023
[19] 0.31859675 -0.11070990 -0.07959859 1.02722366 1.95109787 1.80014628
[25] -0.05305813 -0.19373430 -1.55263356 -2.19076308 0.93848398 -0.53545146
[31] 0.23632791 0.95952083 0.20580549 -0.31648008 -0.91197612 1.70245954
[37] 0.64723568 0.96181639 0.41481020 -0.24308565 -0.77520744 -1.43224143
[43] 0.80102653 -2.36866397 0.84543541 0.45411315 -0.07932439 2.36224126
[49] -0.40158559 -1.36306163 -0.27677657 -0.70674165 -0.19731109 -0.81209808
[55] -1.63543075 -1.00448987 0.83868949 0.75412133 -0.20177665 1.56955844
[61] -0.57407434 -0.10984080 -0.76113791 -0.27730466 -0.45123341 1.35140408
[67] -0.94727522 -1.04842564 -0.04667484 -0.58697406 1.67058724 0.53346829
[73] 1.05186984 -0.17284198 0.16921809 1.96468522 0.79190828 2.77446439
[79] 0.29014559 -1.05490386 -0.36000601 -0.96210669 -1.13428470 -0.65418107
[85] -0.67867813 -0.11978114 0.45013335 -0.74546522 -0.24453473 1.38701248
[91] 1.37188095 0.14306615 -0.36195099 -0.33487674 -0.16928265 -0.81456880
[97] -0.57803467 1.58964356 1.10111349 1.83964432
> rowMin(tmp2)
[1] 1.01080236 -0.41032605 0.24565920 -2.11588882 0.85357512 0.29789425
[7] 0.50997005 -0.66365136 1.59572591 -1.40009079 -0.40930127 -1.13418159
[13] 1.19479561 -1.00208312 1.23205724 0.48796975 -0.15228989 -0.38220023
[19] 0.31859675 -0.11070990 -0.07959859 1.02722366 1.95109787 1.80014628
[25] -0.05305813 -0.19373430 -1.55263356 -2.19076308 0.93848398 -0.53545146
[31] 0.23632791 0.95952083 0.20580549 -0.31648008 -0.91197612 1.70245954
[37] 0.64723568 0.96181639 0.41481020 -0.24308565 -0.77520744 -1.43224143
[43] 0.80102653 -2.36866397 0.84543541 0.45411315 -0.07932439 2.36224126
[49] -0.40158559 -1.36306163 -0.27677657 -0.70674165 -0.19731109 -0.81209808
[55] -1.63543075 -1.00448987 0.83868949 0.75412133 -0.20177665 1.56955844
[61] -0.57407434 -0.10984080 -0.76113791 -0.27730466 -0.45123341 1.35140408
[67] -0.94727522 -1.04842564 -0.04667484 -0.58697406 1.67058724 0.53346829
[73] 1.05186984 -0.17284198 0.16921809 1.96468522 0.79190828 2.77446439
[79] 0.29014559 -1.05490386 -0.36000601 -0.96210669 -1.13428470 -0.65418107
[85] -0.67867813 -0.11978114 0.45013335 -0.74546522 -0.24453473 1.38701248
[91] 1.37188095 0.14306615 -0.36195099 -0.33487674 -0.16928265 -0.81456880
[97] -0.57803467 1.58964356 1.10111349 1.83964432
>
> colMeans(tmp2)
[1] 0.06396754
> colSums(tmp2)
[1] 6.396754
> colVars(tmp2)
[1] 1.067269
> colSd(tmp2)
[1] 1.033087
> colMax(tmp2)
[1] 2.774464
> colMin(tmp2)
[1] -2.368664
> colMedians(tmp2)
[1] -0.1152455
> colRanges(tmp2)
[,1]
[1,] -2.368664
[2,] 2.774464
>
> 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] 2.63901767 -0.47903819 -0.05179399 -0.59687441 -2.15878261 -0.69744227
[7] 3.75750267 4.32989858 -1.66658931 2.37453771
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.7627420
[2,] 0.1539340
[3,] 0.2689862
[4,] 0.3323716
[5,] 1.3560173
>
> rowApply(tmp,sum)
[1] -3.59901027 -3.86225154 -2.82043679 5.41524753 0.53403521 2.57590033
[7] 7.57120228 1.67936643 0.07109602 -0.11471333
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 7 9 6 7 6 4 1 6 6
[2,] 3 9 10 8 3 3 8 5 1 3
[3,] 9 4 8 9 2 5 1 7 4 2
[4,] 1 1 7 4 6 9 7 10 10 1
[5,] 2 2 5 2 4 4 6 4 9 7
[6,] 5 6 1 3 8 2 2 8 7 5
[7,] 8 8 3 7 9 8 9 2 2 9
[8,] 7 5 6 10 5 7 5 6 5 8
[9,] 4 3 4 1 1 10 3 9 3 10
[10,] 6 10 2 5 10 1 10 3 8 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 3.5209550 3.8498985 -0.7550638 -3.1427547 -2.2639518 1.9241446
[7] -1.3733170 -1.6892375 -1.1618627 -0.5770062 1.6225897 -0.2837028
[13] 0.8471928 -1.8134807 -1.6314199 2.0239630 -0.4004178 0.1878120
[19] -2.1382860 0.8391243
> colApply(tmp,quantile)[,1]
[,1]
[1,] 0.08666931
[2,] 0.16703029
[3,] 0.24225912
[4,] 0.85700962
[5,] 2.16798666
>
> rowApply(tmp,sum)
[1] -1.6700108 -0.2525999 3.7950635 -8.5893693 4.3020956
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 14 20 9 18 10
[2,] 19 14 19 13 14
[3,] 16 9 2 11 5
[4,] 15 3 8 1 13
[5,] 4 7 3 2 20
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.16703029 1.87502618 0.46922036 0.2667653 -0.6912800 -0.5588938
[2,] 2.16798666 0.42764445 -0.14136323 -1.1137015 -0.4342562 0.4163073
[3,] 0.24225912 1.06714345 -0.87505605 -0.1127005 -0.6668887 0.2985166
[4,] 0.85700962 0.08560314 -0.07746965 -2.5064728 -1.9165038 0.9459103
[5,] 0.08666931 0.39448131 -0.13039527 0.3233549 1.4449769 0.8223042
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.10437035 -2.1117930 -0.5673266 -0.42753891 1.9762362 0.5375732
[2,] -0.58098796 -0.2483289 -0.1082101 -0.83988374 0.6051361 1.1132254
[3,] 0.55341416 -0.1638298 1.7014349 0.30684298 -0.1455597 -1.9817257
[4,] -1.36854345 -0.3120472 -1.4913993 0.32220300 -1.7081427 1.0232390
[5,] -0.08157006 1.1467615 -0.6963616 0.06137042 0.8949198 -0.9760147
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.1414629 -0.02988716 -0.5686160 0.7004085 -1.2956190573 -0.10709401
[2,] 0.6227040 -2.43582799 -0.9939034 1.6735394 0.3207306756 -0.06028104
[3,] 0.3647550 0.96199205 -0.2766400 0.7815801 0.6711721101 0.67961760
[4,] 0.7244372 -1.63686817 -0.3446613 -1.4205922 -0.0003924669 0.47971660
[5,] 0.2767596 1.32711053 0.5524008 0.2890272 -0.0963090280 -0.80414712
[,19] [,20]
[1,] -0.0119922 -0.2551374
[2,] -1.4110864 0.7679566
[3,] -0.4449405 0.8336763
[4,] 0.1343510 -0.3787461
[5,] -0.4046179 -0.1286251
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.20-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-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 624 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 543 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.20-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 -1.253024 1.418194 -0.4075236 -0.6282293 0.2892247 -0.4198881 -0.3488831
col8 col9 col10 col11 col12 col13 col14
row1 -0.5464649 0.5375226 -0.6466035 0.6188515 -1.53032 0.5058242 0.9118756
col15 col16 col17 col18 col19 col20
row1 -0.2218198 -1.168553 -0.4332726 -0.305744 0.4277713 -0.8882289
> tmp[,"col10"]
col10
row1 -0.6466035
row2 -1.2212874
row3 0.8645748
row4 1.0918351
row5 -0.9356186
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -1.2530242 1.4181939 -0.4075236 -0.6282293 0.2892247 -0.4198881
row5 0.4046264 0.5053739 -1.5165073 1.1763525 -1.3276048 -2.3089886
col7 col8 col9 col10 col11 col12
row1 -0.3488831 -0.5464649 0.5375226 -0.6466035 0.6188515 -1.5303197
row5 0.3775228 -0.9683924 -1.6878396 -0.9356186 -1.4309899 -0.8482916
col13 col14 col15 col16 col17 col18 col19
row1 0.5058242 0.9118756 -0.2218198 -1.168553 -0.4332726 -0.305744 0.4277713
row5 0.2462284 0.9298600 0.6399488 -0.133876 -1.7701452 -1.476197 2.0483454
col20
row1 -0.8882289
row5 0.7854573
> tmp[,c("col6","col20")]
col6 col20
row1 -0.4198881 -0.8882289
row2 0.4782907 1.6527106
row3 -0.2443908 0.5556142
row4 -1.0172939 -0.6658775
row5 -2.3089886 0.7854573
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.4198881 -0.8882289
row5 -2.3089886 0.7854573
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.00301 48.98618 50.50871 50.59653 50.47164 104.9253 51.71781 51.08052
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.36587 50.21084 49.44021 50.56989 49.45936 50.03278 50.25743 52.61406
col17 col18 col19 col20
row1 49.47824 49.32134 49.88519 104.0836
> tmp[,"col10"]
col10
row1 50.21084
row2 28.77418
row3 29.93920
row4 30.26424
row5 48.10562
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.00301 48.98618 50.50871 50.59653 50.47164 104.9253 51.71781 51.08052
row5 49.38224 50.23645 48.54386 49.76814 48.73125 104.9813 50.79596 47.29089
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.36587 50.21084 49.44021 50.56989 49.45936 50.03278 50.25743 52.61406
row5 51.26457 48.10562 51.18646 51.20876 48.28473 49.71434 48.23801 49.47723
col17 col18 col19 col20
row1 49.47824 49.32134 49.88519 104.0836
row5 50.34969 50.00195 51.08385 104.4704
> tmp[,c("col6","col20")]
col6 col20
row1 104.92535 104.08359
row2 74.83612 75.09525
row3 75.05781 73.11380
row4 74.36490 75.35956
row5 104.98132 104.47039
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.9253 104.0836
row5 104.9813 104.4704
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.9253 104.0836
row5 104.9813 104.4704
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.1883847
[2,] -0.1263336
[3,] -0.7706378
[4,] -1.2336005
[5,] 0.6507129
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.9010845 1.03701845
[2,] -0.4610593 0.08240138
[3,] -1.4742090 -0.45118875
[4,] -1.0979475 -0.55129222
[5,] 0.3618676 -1.08562934
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.07895303 0.6691777
[2,] -0.68340631 -0.2027773
[3,] -0.17715014 1.1193665
[4,] 0.70087300 0.6846733
[5,] 1.37582295 -1.0370321
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.07895303
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.07895303
[2,] -0.68340631
>
>
>
> 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] [,7]
row3 0.1359133 0.04635998 0.1475972 0.2316958 -0.4659225 0.7285582 0.1046148
row1 1.1059872 -1.69887884 -1.0172404 0.2458775 0.4833946 0.3914286 0.2154607
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.2327733 0.5488523 -0.3373787 1.0026079 -0.3460430 0.7297278
row1 2.0090320 0.6551231 1.9071822 -0.6850707 0.1107456 -1.4901299
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.4410264 0.07715707 1.9458505 0.5709489 1.0211712 0.2183191
row1 0.2852247 -1.51553458 -0.7088304 -0.7945699 -0.3851788 0.8884050
[,20]
row3 -0.8768032
row1 -0.4735271
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.5797738 -0.6241154 -2.187322 -0.6012924 0.3424588 -0.5504791 -0.7911927
[,8] [,9] [,10]
row2 0.001342987 1.301145 -0.4080702
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.1576833 -0.116376 0.88605 0.3342184 0.05318161 -0.9178579 -0.862117
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.6116162 -0.03466132 0.8577471 -1.396121 0.6654242 0.321244 -0.9949921
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.02146095 0.00598205 0.09228725 -0.2746237 -1.060093 -0.02940521
>
>
> 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: 0x0000022b4ecff0b0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM6af013f94cab"
[2] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM6af06867a51"
[3] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM6af0134c21f2"
[4] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM6af052c1a27"
[5] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM6af01ab0285e"
[6] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM6af02868683a"
[7] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM6af0776172c5"
[8] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM6af08016c43"
[9] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM6af0650c15b2"
[10] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM6af04fa9273b"
[11] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM6af014922316"
[12] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM6af01bdfcb6"
[13] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM6af0100ae3a"
[14] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM6af01e142672"
[15] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM6af02005bf8"
>
>
> ### 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: 0x0000022b526dd7d0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x0000022b526dd7d0>
Warning message:
In dir.create(new.directory) :
'F:\biocbuild\bbs-3.20-bioc\meat\BufferedMatrix.Rcheck\tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x0000022b526dd7d0>
> rowMedians(tmp)
[1] 0.049834633 0.361496502 -0.155219380 -0.177383691 -0.680067764
[6] 0.054182193 0.167288513 0.371299198 0.155293072 -0.336603502
[11] -0.275292470 -0.065189360 0.172167961 -0.165738691 0.148750044
[16] -0.133656974 0.422109318 -0.442106205 0.908959721 0.213275857
[21] 0.297353571 -0.076731962 0.018581675 -0.112382580 0.102846540
[26] 0.372706663 -0.009299296 0.180213014 0.173524935 -0.342549638
[31] 0.168765063 -0.474022937 0.199862327 -0.212249266 -0.034226573
[36] -0.141511035 -0.339581451 0.138614554 0.229571358 -0.078476072
[41] -0.107864155 -0.099769837 -0.029417679 -0.224480908 0.099198537
[46] 0.381091559 -0.216750625 0.040519656 -0.146407680 0.070715638
[51] 0.258723072 -0.012599431 0.521527577 -0.050343877 0.115065405
[56] -0.247056850 -0.094396889 0.392634925 0.011658952 -0.380343440
[61] 0.135373458 -0.028177816 0.070537978 -0.005645459 -0.133148245
[66] 0.005643708 -0.208318222 0.230427299 -0.383430874 0.191586019
[71] -0.655077812 0.132212203 0.467262279 0.400669903 0.068740028
[76] 0.169657895 0.187367802 -0.098632346 0.312180178 -0.194643577
[81] 0.607765876 -0.259144576 0.201502573 -0.018409216 0.428785001
[86] 0.228561174 0.054746337 0.030928374 -0.415615925 -0.175326719
[91] 0.192449399 -0.128085121 -0.256204788 -0.008107396 0.018628593
[96] 0.235959349 -0.301284978 -0.538569965 -0.160663248 -0.253320282
[101] 0.064131040 -0.334188817 -0.219447105 0.088729119 0.325432971
[106] 0.128198809 0.282784633 0.099873116 0.426858091 0.092876781
[111] 0.264091809 -0.446658568 0.041105849 -0.105217763 -0.151158796
[116] 0.454235078 -0.098951143 0.135748940 0.190090566 0.192676607
[121] -0.068509445 -0.107782811 -0.281324631 0.341065391 0.037413233
[126] -1.099993505 0.645362925 0.266693507 0.248223683 -0.601547267
[131] -0.149477174 0.257444354 -0.372497596 -0.104331215 -0.358912039
[136] -0.006859167 0.180565033 -0.288432338 0.058702685 -0.234109687
[141] -0.360531795 0.073401056 -0.127130800 0.570748938 -0.418927808
[146] -0.150209644 -0.174673321 -0.091592220 0.060522554 0.151422926
[151] -0.287994760 0.140591833 -0.329587783 0.905295186 0.296141240
[156] 0.034087079 0.019027919 0.529843113 -0.123343856 0.746779779
[161] -0.413820271 -0.307222162 -0.279434933 -0.180023226 -0.351673031
[166] -0.693137880 0.156669602 -0.043774883 -0.098103174 0.401832615
[171] -0.124642039 0.485749455 0.371298300 -0.130445585 0.192231328
[176] 0.098405341 0.061298073 -0.286152055 -0.145519839 0.164320006
[181] 0.074189558 0.022683980 -0.292769522 0.070492729 0.155696515
[186] -0.259479263 0.144271959 -0.058568317 -0.039818451 0.622418316
[191] 0.667557781 0.146099048 -0.255138255 -0.336879921 -0.489098237
[196] 0.250801531 -0.175438048 -0.768975870 0.142110857 -0.021737583
[201] 0.283006279 -0.071017721 0.410362658 0.106291310 -0.468855914
[206] 0.353076916 -0.143829794 0.008150682 -0.236680955 0.027555427
[211] 0.310562208 -0.267330901 0.379091542 -0.286244108 0.301320518
[216] 0.037691702 -0.258123690 0.298836662 0.496633237 0.067775504
[221] -0.302834396 0.178931204 -0.568239099 0.178238326 0.169783502
[226] -1.039551290 -0.007181211 -0.479005875 -0.117506325 -0.218819467
>
> proc.time()
user system elapsed
4.00 14.92 120.84
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.3 (2025-02-28 ucrt) -- "Trophy Case"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
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: 0x0000017d74eff4d0>
> .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: 0x0000017d74eff4d0>
> .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: 0x0000017d74eff4d0>
> .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: 0x0000017d74eff4d0>
> 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: 0x0000017d74effb30>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000017d74effb30>
> .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: 0x0000017d74effb30>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000017d74effb30>
> .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: 0x0000017d74effb30>
> 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: 0x0000017d74eff770>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000017d74eff770>
> .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: 0x0000017d74eff770>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x0000017d74eff770>
> .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: 0x0000017d74eff770>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x0000017d74eff770>
> .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: 0x0000017d74eff770>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x0000017d74eff770>
> .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: 0x0000017d74eff770>
> 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: 0x0000017d74effcb0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x0000017d74effcb0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000017d74effcb0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000017d74effcb0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1f5e423b07e28" "BufferedMatrixFile1f5e440b74e18"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1f5e423b07e28" "BufferedMatrixFile1f5e440b74e18"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000017d76cff350>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000017d76cff350>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x0000017d76cff350>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x0000017d76cff350>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x0000017d76cff350>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x0000017d76cff350>
> .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: 0x0000017d76cff1d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000017d76cff1d0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x0000017d76cff1d0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x0000017d76cff1d0>
> 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: 0x0000017d76cffb90>
> .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: 0x0000017d76cffb90>
> rm(P)
>
> proc.time()
user system elapsed
0.35 0.10 0.71
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.3 (2025-02-28 ucrt) -- "Trophy Case"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
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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
'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.
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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
0.28 0.14 0.59