Ben Bolstad
| Snapshot Date: 2025-11-05 13:45 -0500 (Wed, 05 Nov 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_22 |
| git_last_commit: d2ce144 |
| git_last_commit_date: 2025-10-29 09:58:55 -0500 (Wed, 29 Oct 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-11-06 12:00 -0500 (Thu, 06 Nov 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" | 4902 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4638 |
| 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 257/2361 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.74.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | 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: 1.74.0 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.74.0.tar.gz |
| StartedAt: 2025-11-05 19:17:52 -0500 (Wed, 05 Nov 2025) |
| EndedAt: 2025-11-05 19:18:08 -0500 (Wed, 05 Nov 2025) |
| EllapsedTime: 16.2 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
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###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.74.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.1 Patched (2025-09-10 r88807)
* using platform: aarch64-apple-darwin20
* R was compiled by
Apple clang version 16.0.0 (clang-1600.0.26.6)
GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.7
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.74.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... WARNING
Found the following significant warnings:
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
* used SDK: ‘MacOSX11.3.1.sdk’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 WARNING, 2 NOTEs
See
‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
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###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.74.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
using SDK: ‘MacOSX11.3.1.sdk’
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch arm64 -std=gnu2x -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/arm64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R
installing to /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.112 0.035 0.144
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
Ncells 480828 25.7 1056614 56.5 NA 634360 33.9
Vcells 891019 6.8 8388608 64.0 196608 2109493 16.1
>
>
>
>
> ##
> ## 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] "Wed Nov 5 19:18:01 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] "Wed Nov 5 19:18:01 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: 0x600000fdc000>
>
>
>
> 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] "Wed Nov 5 19:18:02 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] "Wed Nov 5 19:18:02 2025"
>
> ColMode(tmp2)
<pointer: 0x600000fdc000>
>
>
>
> ### 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,] 100.4718672 -0.6019741 -0.01793912 -0.7734290
[2,] -0.5234133 -1.0264783 -0.35195642 0.1382367
[3,] 0.3199994 1.3645927 -1.72791096 -1.3536986
[4,] -0.8324462 -0.6275955 -1.41537990 -0.4910269
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-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,] 100.4718672 0.6019741 0.01793912 0.7734290
[2,] 0.5234133 1.0264783 0.35195642 0.1382367
[3,] 0.3199994 1.3645927 1.72791096 1.3536986
[4,] 0.8324462 0.6275955 1.41537990 0.4910269
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-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,] 10.0235656 0.7758699 0.1339370 0.8794481
[2,] 0.7234731 1.0131526 0.5932591 0.3718019
[3,] 0.5656849 1.1681578 1.3145003 1.1634855
[4,] 0.9123849 0.7922093 1.1896974 0.7007331
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.70752 33.36067 26.35731 34.56791
[2,] 32.75814 36.15800 31.28455 28.85626
[3,] 30.97685 38.04617 39.87291 37.98855
[4,] 34.95630 33.54969 38.31235 32.49836
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600000fd8000>
> exp(tmp5)
<pointer: 0x600000fd8000>
> log(tmp5,2)
<pointer: 0x600000fd8000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.7806
> Min(tmp5)
[1] 54.85929
> mean(tmp5)
[1] 74.21304
> Sum(tmp5)
[1] 14842.61
> Var(tmp5)
[1] 858.4568
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.76510 71.56585 71.67629 74.11728 71.14527 73.57907 72.54774 72.72255
[9] 71.89323 70.11803
> rowSums(tmp5)
[1] 1855.302 1431.317 1433.526 1482.346 1422.905 1471.581 1450.955 1454.451
[9] 1437.865 1402.361
> rowVars(tmp5)
[1] 7941.21136 70.33679 67.43882 60.76445 57.85575 57.62481
[7] 40.06712 85.83665 137.60185 57.11135
> rowSd(tmp5)
[1] 89.113475 8.386703 8.212114 7.795156 7.606297 7.591101 6.329860
[8] 9.264807 11.730381 7.557205
> rowMax(tmp5)
[1] 469.78064 87.35904 82.99025 87.08279 86.23738 89.70033 85.15006
[8] 89.53153 90.13691 86.62836
> rowMin(tmp5)
[1] 54.85929 60.06052 55.56397 56.34743 55.10292 62.63048 57.72704 58.56214
[9] 56.93634 57.46084
>
> colMeans(tmp5)
[1] 111.40360 72.51180 72.75938 71.41940 68.86884 70.71955 70.96685
[8] 74.50129 75.54674 78.27394 69.53799 75.00985 71.09031 78.58942
[15] 67.83366 70.94214 71.45624 69.52305 72.57102 70.73574
> colSums(tmp5)
[1] 1114.0360 725.1180 727.5938 714.1940 688.6884 707.1955 709.6685
[8] 745.0129 755.4674 782.7394 695.3799 750.0985 710.9031 785.8942
[15] 678.3366 709.4214 714.5624 695.2305 725.7102 707.3574
> colVars(tmp5)
[1] 15884.09645 72.51611 133.73301 86.20474 164.20015 65.00562
[7] 53.70516 55.28738 64.53541 22.46906 75.23314 80.74425
[13] 44.50975 51.17680 66.45693 71.55733 55.84765 27.30004
[19] 55.11596 59.76306
> colSd(tmp5)
[1] 126.032125 8.515639 11.564299 9.284651 12.814060 8.062606
[7] 7.328381 7.435548 8.033394 4.740154 8.673704 8.985781
[13] 6.671563 7.153796 8.152112 8.459157 7.473128 5.224944
[19] 7.424012 7.730657
> colMax(tmp5)
[1] 469.78064 85.77289 88.61891 86.73694 89.53153 83.72466 80.18685
[8] 84.06439 87.35904 86.62836 82.41449 90.13691 80.26459 87.08279
[15] 83.76715 81.30341 80.41260 77.13092 83.55619 82.06843
> colMin(tmp5)
[1] 64.47425 61.18512 54.85929 60.06052 55.10292 57.75162 58.14315 62.57399
[9] 61.20628 70.38255 57.72866 61.66823 58.10124 66.30342 57.72704 56.93634
[17] 57.46084 60.98719 56.34743 61.02306
>
>
> ### 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] 92.76510 71.56585 71.67629 NA 71.14527 73.57907 72.54774 72.72255
[9] 71.89323 70.11803
> rowSums(tmp5)
[1] 1855.302 1431.317 1433.526 NA 1422.905 1471.581 1450.955 1454.451
[9] 1437.865 1402.361
> rowVars(tmp5)
[1] 7941.21136 70.33679 67.43882 64.13854 57.85575 57.62481
[7] 40.06712 85.83665 137.60185 57.11135
> rowSd(tmp5)
[1] 89.113475 8.386703 8.212114 8.008654 7.606297 7.591101 6.329860
[8] 9.264807 11.730381 7.557205
> rowMax(tmp5)
[1] 469.78064 87.35904 82.99025 NA 86.23738 89.70033 85.15006
[8] 89.53153 90.13691 86.62836
> rowMin(tmp5)
[1] 54.85929 60.06052 55.56397 NA 55.10292 62.63048 57.72704 58.56214
[9] 56.93634 57.46084
>
> colMeans(tmp5)
[1] 111.40360 72.51180 72.75938 71.41940 68.86884 NA 70.96685
[8] 74.50129 75.54674 78.27394 69.53799 75.00985 71.09031 78.58942
[15] 67.83366 70.94214 71.45624 69.52305 72.57102 70.73574
> colSums(tmp5)
[1] 1114.0360 725.1180 727.5938 714.1940 688.6884 NA 709.6685
[8] 745.0129 755.4674 782.7394 695.3799 750.0985 710.9031 785.8942
[15] 678.3366 709.4214 714.5624 695.2305 725.7102 707.3574
> colVars(tmp5)
[1] 15884.09645 72.51611 133.73301 86.20474 164.20015 NA
[7] 53.70516 55.28738 64.53541 22.46906 75.23314 80.74425
[13] 44.50975 51.17680 66.45693 71.55733 55.84765 27.30004
[19] 55.11596 59.76306
> colSd(tmp5)
[1] 126.032125 8.515639 11.564299 9.284651 12.814060 NA
[7] 7.328381 7.435548 8.033394 4.740154 8.673704 8.985781
[13] 6.671563 7.153796 8.152112 8.459157 7.473128 5.224944
[19] 7.424012 7.730657
> colMax(tmp5)
[1] 469.78064 85.77289 88.61891 86.73694 89.53153 NA 80.18685
[8] 84.06439 87.35904 86.62836 82.41449 90.13691 80.26459 87.08279
[15] 83.76715 81.30341 80.41260 77.13092 83.55619 82.06843
> colMin(tmp5)
[1] 64.47425 61.18512 54.85929 60.06052 55.10292 NA 58.14315 62.57399
[9] 61.20628 70.38255 57.72866 61.66823 58.10124 66.30342 57.72704 56.93634
[17] 57.46084 60.98719 56.34743 61.02306
>
> Max(tmp5,na.rm=TRUE)
[1] 469.7806
> Min(tmp5,na.rm=TRUE)
[1] 54.85929
> mean(tmp5,na.rm=TRUE)
[1] 74.21266
> Sum(tmp5,na.rm=TRUE)
[1] 14768.32
> Var(tmp5,na.rm=TRUE)
[1] 862.7925
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.76510 71.56585 71.67629 74.10825 71.14527 73.57907 72.54774 72.72255
[9] 71.89323 70.11803
> rowSums(tmp5,na.rm=TRUE)
[1] 1855.302 1431.317 1433.526 1408.057 1422.905 1471.581 1450.955 1454.451
[9] 1437.865 1402.361
> rowVars(tmp5,na.rm=TRUE)
[1] 7941.21136 70.33679 67.43882 64.13854 57.85575 57.62481
[7] 40.06712 85.83665 137.60185 57.11135
> rowSd(tmp5,na.rm=TRUE)
[1] 89.113475 8.386703 8.212114 8.008654 7.606297 7.591101 6.329860
[8] 9.264807 11.730381 7.557205
> rowMax(tmp5,na.rm=TRUE)
[1] 469.78064 87.35904 82.99025 87.08279 86.23738 89.70033 85.15006
[8] 89.53153 90.13691 86.62836
> rowMin(tmp5,na.rm=TRUE)
[1] 54.85929 60.06052 55.56397 56.34743 55.10292 62.63048 57.72704 58.56214
[9] 56.93634 57.46084
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.40360 72.51180 72.75938 71.41940 68.86884 70.32297 70.96685
[8] 74.50129 75.54674 78.27394 69.53799 75.00985 71.09031 78.58942
[15] 67.83366 70.94214 71.45624 69.52305 72.57102 70.73574
> colSums(tmp5,na.rm=TRUE)
[1] 1114.0360 725.1180 727.5938 714.1940 688.6884 632.9068 709.6685
[8] 745.0129 755.4674 782.7394 695.3799 750.0985 710.9031 785.8942
[15] 678.3366 709.4214 714.5624 695.2305 725.7102 707.3574
> colVars(tmp5,na.rm=TRUE)
[1] 15884.09645 72.51611 133.73301 86.20474 164.20015 71.36201
[7] 53.70516 55.28738 64.53541 22.46906 75.23314 80.74425
[13] 44.50975 51.17680 66.45693 71.55733 55.84765 27.30004
[19] 55.11596 59.76306
> colSd(tmp5,na.rm=TRUE)
[1] 126.032125 8.515639 11.564299 9.284651 12.814060 8.447604
[7] 7.328381 7.435548 8.033394 4.740154 8.673704 8.985781
[13] 6.671563 7.153796 8.152112 8.459157 7.473128 5.224944
[19] 7.424012 7.730657
> colMax(tmp5,na.rm=TRUE)
[1] 469.78064 85.77289 88.61891 86.73694 89.53153 83.72466 80.18685
[8] 84.06439 87.35904 86.62836 82.41449 90.13691 80.26459 87.08279
[15] 83.76715 81.30341 80.41260 77.13092 83.55619 82.06843
> colMin(tmp5,na.rm=TRUE)
[1] 64.47425 61.18512 54.85929 60.06052 55.10292 57.75162 58.14315 62.57399
[9] 61.20628 70.38255 57.72866 61.66823 58.10124 66.30342 57.72704 56.93634
[17] 57.46084 60.98719 56.34743 61.02306
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.76510 71.56585 71.67629 NaN 71.14527 73.57907 72.54774 72.72255
[9] 71.89323 70.11803
> rowSums(tmp5,na.rm=TRUE)
[1] 1855.302 1431.317 1433.526 0.000 1422.905 1471.581 1450.955 1454.451
[9] 1437.865 1402.361
> rowVars(tmp5,na.rm=TRUE)
[1] 7941.21136 70.33679 67.43882 NA 57.85575 57.62481
[7] 40.06712 85.83665 137.60185 57.11135
> rowSd(tmp5,na.rm=TRUE)
[1] 89.113475 8.386703 8.212114 NA 7.606297 7.591101 6.329860
[8] 9.264807 11.730381 7.557205
> rowMax(tmp5,na.rm=TRUE)
[1] 469.78064 87.35904 82.99025 NA 86.23738 89.70033 85.15006
[8] 89.53153 90.13691 86.62836
> rowMin(tmp5,na.rm=TRUE)
[1] 54.85929 60.06052 55.56397 NA 55.10292 62.63048 57.72704 58.56214
[9] 56.93634 57.46084
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.69767 72.80985 71.98352 71.83922 69.89535 NaN 70.70568
[8] 73.54520 75.78177 77.76895 69.05205 75.68058 70.30627 77.64572
[15] 66.06328 70.65471 71.44898 69.36984 74.37364 69.52837
> colSums(tmp5,na.rm=TRUE)
[1] 1041.2790 655.2887 647.8516 646.5529 629.0582 0.0000 636.3511
[8] 661.9068 682.0359 699.9206 621.4684 681.1252 632.7564 698.8115
[15] 594.5695 635.8924 643.0408 624.3286 669.3628 625.7553
> colVars(tmp5,na.rm=TRUE)
[1] 17662.16912 80.58120 143.67755 94.99759 172.87064 NA
[7] 59.65090 51.91459 71.98087 22.40882 81.98069 85.77606
[13] 43.15791 47.55483 39.50351 79.57257 62.82801 30.44846
[19] 25.44923 50.83375
> colSd(tmp5,na.rm=TRUE)
[1] 132.899094 8.976703 11.986557 9.746671 13.148028 NA
[7] 7.723399 7.205178 8.484154 4.733795 9.054319 9.261537
[13] 6.569468 6.896001 6.285182 8.920346 7.926412 5.518013
[19] 5.044723 7.129779
> colMax(tmp5,na.rm=TRUE)
[1] 469.78064 85.77289 88.61891 86.73694 89.53153 -Inf 80.18685
[8] 84.06439 87.35904 86.62836 82.41449 90.13691 80.26459 85.86898
[15] 80.48251 81.30341 80.41260 77.13092 83.55619 82.06843
> colMin(tmp5,na.rm=TRUE)
[1] 64.47425 61.18512 54.85929 60.06052 55.10292 Inf 58.14315 62.57399
[9] 61.20628 70.38255 57.72866 61.66823 58.10124 66.30342 57.72704 56.93634
[17] 57.46084 60.98719 66.68558 61.02306
>
>
>
>
> 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] 96.69549 206.35516 217.14906 193.16472 439.96283 160.70848 213.36194
[8] 255.08124 232.90656 195.48988
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 96.69549 206.35516 217.14906 193.16472 439.96283 160.70848 213.36194
[8] 255.08124 232.90656 195.48988
>
>
>
> 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] -2.842171e-14 1.705303e-13 2.273737e-13 1.136868e-13 -7.105427e-14
[6] 5.684342e-14 0.000000e+00 -1.705303e-13 1.136868e-13 -2.842171e-14
[11] -1.421085e-14 4.263256e-14 5.684342e-14 7.105427e-14 2.842171e-14
[16] -8.526513e-14 5.684342e-14 -2.842171e-14 0.000000e+00 2.273737e-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)
+ }
1 16
1 2
9 10
6 19
4 20
7 18
3 7
9 5
6 14
7 11
6 20
4 5
4 12
3 8
7 12
7 9
5 17
1 20
1 7
3 8
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] 2.189567
> Min(tmp)
[1] -1.931805
> mean(tmp)
[1] 0.03765071
> Sum(tmp)
[1] 3.765071
> Var(tmp)
[1] 0.7920128
>
> rowMeans(tmp)
[1] 0.03765071
> rowSums(tmp)
[1] 3.765071
> rowVars(tmp)
[1] 0.7920128
> rowSd(tmp)
[1] 0.889951
> rowMax(tmp)
[1] 2.189567
> rowMin(tmp)
[1] -1.931805
>
> colMeans(tmp)
[1] 0.69053284 -0.17119183 1.04287539 -1.01479212 0.72017633 -0.10075269
[7] 0.88350510 -0.73345641 -0.45147653 0.71933615 -0.91345418 -0.54609105
[13] 1.32991220 -0.27373616 -0.56036615 -0.36024882 0.49662021 -0.44378908
[19] -1.41996160 0.35119557 0.88908029 0.47906957 -0.59928026 0.67683987
[25] 1.31124587 -0.52533709 0.17969846 0.28392176 -0.01708678 -0.98884324
[31] -0.06461722 0.40233306 0.08374876 -0.07350861 0.77204831 0.18099664
[37] -1.05203250 1.09231270 -1.22549706 -1.09255254 -0.39344033 -0.04276942
[43] 0.71152413 1.07333224 -1.50182987 0.77689355 0.67955015 0.57519293
[49] 1.21501089 -0.90764330 -1.12541102 1.80614825 0.43195699 0.11763089
[55] 0.75665352 0.17581601 -1.50906872 -1.23324051 -1.93180534 0.91524235
[61] -0.86869777 -0.01464323 -1.24313649 1.87135923 -0.44262693 1.26196308
[67] 0.27427574 0.30389662 -1.37945049 1.45035941 -1.13730919 2.18956661
[73] -0.88899863 -0.16966225 -0.25044961 0.36246426 1.32217560 -0.22541273
[79] -0.25030135 -1.02577443 -0.39737768 0.41706715 1.70319046 1.29834688
[85] -0.30386741 -0.48203427 1.67414986 0.18470212 -0.06923301 -0.59373382
[91] -1.06782146 -0.06724166 1.13350881 -0.52744308 0.79057387 0.40438948
[97] -0.95160521 -0.21378581 -0.68546246 -0.16797011
> colSums(tmp)
[1] 0.69053284 -0.17119183 1.04287539 -1.01479212 0.72017633 -0.10075269
[7] 0.88350510 -0.73345641 -0.45147653 0.71933615 -0.91345418 -0.54609105
[13] 1.32991220 -0.27373616 -0.56036615 -0.36024882 0.49662021 -0.44378908
[19] -1.41996160 0.35119557 0.88908029 0.47906957 -0.59928026 0.67683987
[25] 1.31124587 -0.52533709 0.17969846 0.28392176 -0.01708678 -0.98884324
[31] -0.06461722 0.40233306 0.08374876 -0.07350861 0.77204831 0.18099664
[37] -1.05203250 1.09231270 -1.22549706 -1.09255254 -0.39344033 -0.04276942
[43] 0.71152413 1.07333224 -1.50182987 0.77689355 0.67955015 0.57519293
[49] 1.21501089 -0.90764330 -1.12541102 1.80614825 0.43195699 0.11763089
[55] 0.75665352 0.17581601 -1.50906872 -1.23324051 -1.93180534 0.91524235
[61] -0.86869777 -0.01464323 -1.24313649 1.87135923 -0.44262693 1.26196308
[67] 0.27427574 0.30389662 -1.37945049 1.45035941 -1.13730919 2.18956661
[73] -0.88899863 -0.16966225 -0.25044961 0.36246426 1.32217560 -0.22541273
[79] -0.25030135 -1.02577443 -0.39737768 0.41706715 1.70319046 1.29834688
[85] -0.30386741 -0.48203427 1.67414986 0.18470212 -0.06923301 -0.59373382
[91] -1.06782146 -0.06724166 1.13350881 -0.52744308 0.79057387 0.40438948
[97] -0.95160521 -0.21378581 -0.68546246 -0.16797011
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] 0.69053284 -0.17119183 1.04287539 -1.01479212 0.72017633 -0.10075269
[7] 0.88350510 -0.73345641 -0.45147653 0.71933615 -0.91345418 -0.54609105
[13] 1.32991220 -0.27373616 -0.56036615 -0.36024882 0.49662021 -0.44378908
[19] -1.41996160 0.35119557 0.88908029 0.47906957 -0.59928026 0.67683987
[25] 1.31124587 -0.52533709 0.17969846 0.28392176 -0.01708678 -0.98884324
[31] -0.06461722 0.40233306 0.08374876 -0.07350861 0.77204831 0.18099664
[37] -1.05203250 1.09231270 -1.22549706 -1.09255254 -0.39344033 -0.04276942
[43] 0.71152413 1.07333224 -1.50182987 0.77689355 0.67955015 0.57519293
[49] 1.21501089 -0.90764330 -1.12541102 1.80614825 0.43195699 0.11763089
[55] 0.75665352 0.17581601 -1.50906872 -1.23324051 -1.93180534 0.91524235
[61] -0.86869777 -0.01464323 -1.24313649 1.87135923 -0.44262693 1.26196308
[67] 0.27427574 0.30389662 -1.37945049 1.45035941 -1.13730919 2.18956661
[73] -0.88899863 -0.16966225 -0.25044961 0.36246426 1.32217560 -0.22541273
[79] -0.25030135 -1.02577443 -0.39737768 0.41706715 1.70319046 1.29834688
[85] -0.30386741 -0.48203427 1.67414986 0.18470212 -0.06923301 -0.59373382
[91] -1.06782146 -0.06724166 1.13350881 -0.52744308 0.79057387 0.40438948
[97] -0.95160521 -0.21378581 -0.68546246 -0.16797011
> colMin(tmp)
[1] 0.69053284 -0.17119183 1.04287539 -1.01479212 0.72017633 -0.10075269
[7] 0.88350510 -0.73345641 -0.45147653 0.71933615 -0.91345418 -0.54609105
[13] 1.32991220 -0.27373616 -0.56036615 -0.36024882 0.49662021 -0.44378908
[19] -1.41996160 0.35119557 0.88908029 0.47906957 -0.59928026 0.67683987
[25] 1.31124587 -0.52533709 0.17969846 0.28392176 -0.01708678 -0.98884324
[31] -0.06461722 0.40233306 0.08374876 -0.07350861 0.77204831 0.18099664
[37] -1.05203250 1.09231270 -1.22549706 -1.09255254 -0.39344033 -0.04276942
[43] 0.71152413 1.07333224 -1.50182987 0.77689355 0.67955015 0.57519293
[49] 1.21501089 -0.90764330 -1.12541102 1.80614825 0.43195699 0.11763089
[55] 0.75665352 0.17581601 -1.50906872 -1.23324051 -1.93180534 0.91524235
[61] -0.86869777 -0.01464323 -1.24313649 1.87135923 -0.44262693 1.26196308
[67] 0.27427574 0.30389662 -1.37945049 1.45035941 -1.13730919 2.18956661
[73] -0.88899863 -0.16966225 -0.25044961 0.36246426 1.32217560 -0.22541273
[79] -0.25030135 -1.02577443 -0.39737768 0.41706715 1.70319046 1.29834688
[85] -0.30386741 -0.48203427 1.67414986 0.18470212 -0.06923301 -0.59373382
[91] -1.06782146 -0.06724166 1.13350881 -0.52744308 0.79057387 0.40438948
[97] -0.95160521 -0.21378581 -0.68546246 -0.16797011
> colMedians(tmp)
[1] 0.69053284 -0.17119183 1.04287539 -1.01479212 0.72017633 -0.10075269
[7] 0.88350510 -0.73345641 -0.45147653 0.71933615 -0.91345418 -0.54609105
[13] 1.32991220 -0.27373616 -0.56036615 -0.36024882 0.49662021 -0.44378908
[19] -1.41996160 0.35119557 0.88908029 0.47906957 -0.59928026 0.67683987
[25] 1.31124587 -0.52533709 0.17969846 0.28392176 -0.01708678 -0.98884324
[31] -0.06461722 0.40233306 0.08374876 -0.07350861 0.77204831 0.18099664
[37] -1.05203250 1.09231270 -1.22549706 -1.09255254 -0.39344033 -0.04276942
[43] 0.71152413 1.07333224 -1.50182987 0.77689355 0.67955015 0.57519293
[49] 1.21501089 -0.90764330 -1.12541102 1.80614825 0.43195699 0.11763089
[55] 0.75665352 0.17581601 -1.50906872 -1.23324051 -1.93180534 0.91524235
[61] -0.86869777 -0.01464323 -1.24313649 1.87135923 -0.44262693 1.26196308
[67] 0.27427574 0.30389662 -1.37945049 1.45035941 -1.13730919 2.18956661
[73] -0.88899863 -0.16966225 -0.25044961 0.36246426 1.32217560 -0.22541273
[79] -0.25030135 -1.02577443 -0.39737768 0.41706715 1.70319046 1.29834688
[85] -0.30386741 -0.48203427 1.67414986 0.18470212 -0.06923301 -0.59373382
[91] -1.06782146 -0.06724166 1.13350881 -0.52744308 0.79057387 0.40438948
[97] -0.95160521 -0.21378581 -0.68546246 -0.16797011
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.6905328 -0.1711918 1.042875 -1.014792 0.7201763 -0.1007527 0.8835051
[2,] 0.6905328 -0.1711918 1.042875 -1.014792 0.7201763 -0.1007527 0.8835051
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.7334564 -0.4514765 0.7193362 -0.9134542 -0.5460911 1.329912 -0.2737362
[2,] -0.7334564 -0.4514765 0.7193362 -0.9134542 -0.5460911 1.329912 -0.2737362
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.5603662 -0.3602488 0.4966202 -0.4437891 -1.419962 0.3511956 0.8890803
[2,] -0.5603662 -0.3602488 0.4966202 -0.4437891 -1.419962 0.3511956 0.8890803
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.4790696 -0.5992803 0.6768399 1.311246 -0.5253371 0.1796985 0.2839218
[2,] 0.4790696 -0.5992803 0.6768399 1.311246 -0.5253371 0.1796985 0.2839218
[,29] [,30] [,31] [,32] [,33] [,34]
[1,] -0.01708678 -0.9888432 -0.06461722 0.4023331 0.08374876 -0.07350861
[2,] -0.01708678 -0.9888432 -0.06461722 0.4023331 0.08374876 -0.07350861
[,35] [,36] [,37] [,38] [,39] [,40] [,41]
[1,] 0.7720483 0.1809966 -1.052033 1.092313 -1.225497 -1.092553 -0.3934403
[2,] 0.7720483 0.1809966 -1.052033 1.092313 -1.225497 -1.092553 -0.3934403
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] -0.04276942 0.7115241 1.073332 -1.50183 0.7768935 0.6795502 0.5751929
[2,] -0.04276942 0.7115241 1.073332 -1.50183 0.7768935 0.6795502 0.5751929
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] 1.215011 -0.9076433 -1.125411 1.806148 0.431957 0.1176309 0.7566535
[2,] 1.215011 -0.9076433 -1.125411 1.806148 0.431957 0.1176309 0.7566535
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] 0.175816 -1.509069 -1.233241 -1.931805 0.9152424 -0.8686978 -0.01464323
[2,] 0.175816 -1.509069 -1.233241 -1.931805 0.9152424 -0.8686978 -0.01464323
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] -1.243136 1.871359 -0.4426269 1.261963 0.2742757 0.3038966 -1.37945
[2,] -1.243136 1.871359 -0.4426269 1.261963 0.2742757 0.3038966 -1.37945
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 1.450359 -1.137309 2.189567 -0.8889986 -0.1696623 -0.2504496 0.3624643
[2,] 1.450359 -1.137309 2.189567 -0.8889986 -0.1696623 -0.2504496 0.3624643
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] 1.322176 -0.2254127 -0.2503013 -1.025774 -0.3973777 0.4170671 1.70319
[2,] 1.322176 -0.2254127 -0.2503013 -1.025774 -0.3973777 0.4170671 1.70319
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 1.298347 -0.3038674 -0.4820343 1.67415 0.1847021 -0.06923301 -0.5937338
[2,] 1.298347 -0.3038674 -0.4820343 1.67415 0.1847021 -0.06923301 -0.5937338
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -1.067821 -0.06724166 1.133509 -0.5274431 0.7905739 0.4043895 -0.9516052
[2,] -1.067821 -0.06724166 1.133509 -0.5274431 0.7905739 0.4043895 -0.9516052
[,98] [,99] [,100]
[1,] -0.2137858 -0.6854625 -0.1679701
[2,] -0.2137858 -0.6854625 -0.1679701
>
>
> Max(tmp2)
[1] 3.472937
> Min(tmp2)
[1] -2.583782
> mean(tmp2)
[1] -0.07579829
> Sum(tmp2)
[1] -7.579829
> Var(tmp2)
[1] 1.416211
>
> rowMeans(tmp2)
[1] 0.685558566 -1.138095408 -0.377037078 -0.954970889 -1.531287263
[6] 0.049853683 -0.969357680 3.009624285 0.060686033 1.110903254
[11] -1.118961419 0.277657179 0.218081401 0.057038915 -2.051587284
[16] 0.142806585 0.256767352 0.309308498 1.839329564 2.811094904
[21] -0.480078376 1.167331429 1.645771615 -1.430358150 -1.793272624
[26] -1.565301794 -1.695540707 -1.373292341 -1.144696096 -0.866864754
[31] -0.455197685 -0.331123051 2.197622560 -2.583782008 -0.056076928
[36] 1.104471564 -0.025095234 -0.386208025 -0.234917670 -0.292712560
[41] 0.099027182 -0.471911130 -0.249521750 -0.865717412 0.215641177
[46] 1.137220307 -0.640629190 -0.542419329 -0.736293949 -0.395978836
[51] 0.155470211 0.153884331 -0.107558441 0.165664482 0.163263403
[56] -1.431974373 0.240137292 -0.897470555 1.041186824 -0.381219506
[61] -0.322273877 1.635552361 -0.136659665 -0.240147043 0.752073572
[66] -2.549867845 0.238369523 0.099446707 3.089410193 -0.784223814
[71] 0.675448349 1.031156939 0.422418795 -0.222942610 -2.024901968
[76] -0.535773467 -1.444013637 3.472937424 1.824175642 2.004788532
[81] 1.106066964 0.395499980 -1.071801621 -1.071412404 0.383164671
[86] -0.288890290 1.036628931 0.644157518 0.643259775 -1.089595317
[91] 0.320229337 -0.965674568 0.748565793 0.280791543 -0.317368662
[96] -2.123422050 -0.006956855 -1.305603437 -1.983769870 -0.637565986
> rowSums(tmp2)
[1] 0.685558566 -1.138095408 -0.377037078 -0.954970889 -1.531287263
[6] 0.049853683 -0.969357680 3.009624285 0.060686033 1.110903254
[11] -1.118961419 0.277657179 0.218081401 0.057038915 -2.051587284
[16] 0.142806585 0.256767352 0.309308498 1.839329564 2.811094904
[21] -0.480078376 1.167331429 1.645771615 -1.430358150 -1.793272624
[26] -1.565301794 -1.695540707 -1.373292341 -1.144696096 -0.866864754
[31] -0.455197685 -0.331123051 2.197622560 -2.583782008 -0.056076928
[36] 1.104471564 -0.025095234 -0.386208025 -0.234917670 -0.292712560
[41] 0.099027182 -0.471911130 -0.249521750 -0.865717412 0.215641177
[46] 1.137220307 -0.640629190 -0.542419329 -0.736293949 -0.395978836
[51] 0.155470211 0.153884331 -0.107558441 0.165664482 0.163263403
[56] -1.431974373 0.240137292 -0.897470555 1.041186824 -0.381219506
[61] -0.322273877 1.635552361 -0.136659665 -0.240147043 0.752073572
[66] -2.549867845 0.238369523 0.099446707 3.089410193 -0.784223814
[71] 0.675448349 1.031156939 0.422418795 -0.222942610 -2.024901968
[76] -0.535773467 -1.444013637 3.472937424 1.824175642 2.004788532
[81] 1.106066964 0.395499980 -1.071801621 -1.071412404 0.383164671
[86] -0.288890290 1.036628931 0.644157518 0.643259775 -1.089595317
[91] 0.320229337 -0.965674568 0.748565793 0.280791543 -0.317368662
[96] -2.123422050 -0.006956855 -1.305603437 -1.983769870 -0.637565986
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 0.685558566 -1.138095408 -0.377037078 -0.954970889 -1.531287263
[6] 0.049853683 -0.969357680 3.009624285 0.060686033 1.110903254
[11] -1.118961419 0.277657179 0.218081401 0.057038915 -2.051587284
[16] 0.142806585 0.256767352 0.309308498 1.839329564 2.811094904
[21] -0.480078376 1.167331429 1.645771615 -1.430358150 -1.793272624
[26] -1.565301794 -1.695540707 -1.373292341 -1.144696096 -0.866864754
[31] -0.455197685 -0.331123051 2.197622560 -2.583782008 -0.056076928
[36] 1.104471564 -0.025095234 -0.386208025 -0.234917670 -0.292712560
[41] 0.099027182 -0.471911130 -0.249521750 -0.865717412 0.215641177
[46] 1.137220307 -0.640629190 -0.542419329 -0.736293949 -0.395978836
[51] 0.155470211 0.153884331 -0.107558441 0.165664482 0.163263403
[56] -1.431974373 0.240137292 -0.897470555 1.041186824 -0.381219506
[61] -0.322273877 1.635552361 -0.136659665 -0.240147043 0.752073572
[66] -2.549867845 0.238369523 0.099446707 3.089410193 -0.784223814
[71] 0.675448349 1.031156939 0.422418795 -0.222942610 -2.024901968
[76] -0.535773467 -1.444013637 3.472937424 1.824175642 2.004788532
[81] 1.106066964 0.395499980 -1.071801621 -1.071412404 0.383164671
[86] -0.288890290 1.036628931 0.644157518 0.643259775 -1.089595317
[91] 0.320229337 -0.965674568 0.748565793 0.280791543 -0.317368662
[96] -2.123422050 -0.006956855 -1.305603437 -1.983769870 -0.637565986
> rowMin(tmp2)
[1] 0.685558566 -1.138095408 -0.377037078 -0.954970889 -1.531287263
[6] 0.049853683 -0.969357680 3.009624285 0.060686033 1.110903254
[11] -1.118961419 0.277657179 0.218081401 0.057038915 -2.051587284
[16] 0.142806585 0.256767352 0.309308498 1.839329564 2.811094904
[21] -0.480078376 1.167331429 1.645771615 -1.430358150 -1.793272624
[26] -1.565301794 -1.695540707 -1.373292341 -1.144696096 -0.866864754
[31] -0.455197685 -0.331123051 2.197622560 -2.583782008 -0.056076928
[36] 1.104471564 -0.025095234 -0.386208025 -0.234917670 -0.292712560
[41] 0.099027182 -0.471911130 -0.249521750 -0.865717412 0.215641177
[46] 1.137220307 -0.640629190 -0.542419329 -0.736293949 -0.395978836
[51] 0.155470211 0.153884331 -0.107558441 0.165664482 0.163263403
[56] -1.431974373 0.240137292 -0.897470555 1.041186824 -0.381219506
[61] -0.322273877 1.635552361 -0.136659665 -0.240147043 0.752073572
[66] -2.549867845 0.238369523 0.099446707 3.089410193 -0.784223814
[71] 0.675448349 1.031156939 0.422418795 -0.222942610 -2.024901968
[76] -0.535773467 -1.444013637 3.472937424 1.824175642 2.004788532
[81] 1.106066964 0.395499980 -1.071801621 -1.071412404 0.383164671
[86] -0.288890290 1.036628931 0.644157518 0.643259775 -1.089595317
[91] 0.320229337 -0.965674568 0.748565793 0.280791543 -0.317368662
[96] -2.123422050 -0.006956855 -1.305603437 -1.983769870 -0.637565986
>
> colMeans(tmp2)
[1] -0.07579829
> colSums(tmp2)
[1] -7.579829
> colVars(tmp2)
[1] 1.416211
> colSd(tmp2)
[1] 1.190047
> colMax(tmp2)
[1] 3.472937
> colMin(tmp2)
[1] -2.583782
> colMedians(tmp2)
[1] -0.1221091
> colRanges(tmp2)
[,1]
[1,] -2.583782
[2,] 3.472937
>
> 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] -4.3252947 2.6323608 2.5956883 -1.6594482 1.6904475 -0.3556309
[7] -1.8547489 0.5595453 -7.8264181 2.7970655
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.7449016
[2,] -0.9044817
[3,] -0.5763603
[4,] 0.1171303
[5,] 1.0753210
>
> rowApply(tmp,sum)
[1] -2.3510025 1.7623340 0.6777831 -1.8021218 -1.8313029 2.5310928
[7] -7.1130965 7.3843155 -4.1824893 -0.8219458
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 3 2 6 8 2 1 1 3 5
[2,] 3 7 8 7 5 5 3 9 10 7
[3,] 9 9 10 4 2 9 4 2 8 9
[4,] 4 10 9 5 1 4 2 8 2 2
[5,] 7 2 1 8 4 10 9 10 6 4
[6,] 10 4 4 2 10 8 6 4 7 1
[7,] 6 5 5 3 7 6 8 3 4 3
[8,] 5 1 6 10 3 3 10 5 9 6
[9,] 1 6 3 1 9 1 5 6 1 8
[10,] 2 8 7 9 6 7 7 7 5 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.7957455 2.4673682 2.6251956 -3.6085309 2.3083332 -2.8123994
[7] 2.3606788 0.4183479 3.2173881 1.2912742 -3.1724171 -2.8339074
[13] -0.2855081 2.6989897 3.2207749 0.2708216 -0.6395654 1.1711371
[19] 1.8259490 -4.9564397
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.6931705
[2,] -0.4034768
[3,] 1.0386839
[4,] 1.3604191
[5,] 1.4932898
>
> rowApply(tmp,sum)
[1] -1.6103128 -0.9258757 4.2272396 2.2100544 4.4621301
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 18 7 3 18 17
[2,] 12 20 8 11 6
[3,] 11 15 2 12 20
[4,] 6 13 6 3 3
[5,] 17 19 16 5 7
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.3604191 0.4318703 0.4134061 -1.0978194 1.0083118 -2.0206669
[2,] -0.4034768 2.3727568 0.4630404 0.3264483 0.7682435 -1.6060147
[3,] -0.6931705 -0.1640937 -1.2388850 -0.2360940 1.0267362 0.2598382
[4,] 1.0386839 0.4968509 0.5113328 -1.3526722 -0.2006548 0.1253499
[5,] 1.4932898 -0.6700161 2.4763013 -1.2483936 -0.2943034 0.4290941
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.93322762 1.654808779 -0.6465928 -0.84403592 -1.5774455 -1.1296875
[2,] 0.41055717 -0.005573284 0.7359956 0.75405650 -0.7819549 -1.1884714
[3,] 1.77787902 -2.094994075 1.7685497 -0.08794761 -0.2212843 0.3131247
[4,] -0.68998430 0.188639125 0.5596896 0.40376447 0.5159501 0.6860215
[5,] -0.07100075 0.675467316 0.7997460 1.06543676 -1.1076825 -1.5148947
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.9087596 -1.3899785 0.21278513 0.9511833 -2.7202845 0.755311424
[2,] 0.1856503 0.6043807 -0.05504541 -2.1792019 -0.7452245 -0.220768982
[3,] -0.5862912 0.8216247 0.16819035 1.7888771 0.4770036 0.347953497
[4,] -1.6608438 0.6969668 1.39797549 0.5475059 1.0905966 0.002975825
[5,] -0.1327831 1.9659959 1.49686934 -0.8375428 1.2583434 0.285665363
[,19] [,20]
[1,] 0.99655521 -0.8104403
[2,] -0.63579042 0.2745173
[3,] 1.14902264 -0.3487997
[4,] 0.35876789 -2.5068612
[5,] -0.04260627 -1.5648558
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 649 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 563 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.5476443 1.518238 0.530815 -0.8871832 0.02243727 0.9049274 0.9706193
col8 col9 col10 col11 col12 col13 col14
row1 -0.8109851 -2.225974 -0.3983951 0.6059107 0.9164927 1.205642 0.5163676
col15 col16 col17 col18 col19 col20
row1 -0.5576148 1.193733 0.9555205 1.357898 -0.8289282 0.7321257
> tmp[,"col10"]
col10
row1 -0.39839511
row2 1.83916682
row3 -0.06700367
row4 -0.04284080
row5 0.76057365
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.5476443 1.518238 0.5308150 -0.8871832 0.02243727 0.9049274 0.9706193
row5 0.2449821 -0.590831 -0.2412826 -0.3763929 1.27727136 1.4189519 -1.3319241
col8 col9 col10 col11 col12 col13 col14
row1 -0.8109851 -2.225974 -0.3983951 0.6059107 0.9164927 1.205642 0.5163676
row5 -1.0238030 1.340087 0.7605736 0.8162708 1.2247699 -0.823305 1.0677486
col15 col16 col17 col18 col19 col20
row1 -0.5576148 1.193733 0.9555205 1.357898 -0.8289282 0.7321257
row5 -1.3297889 2.860662 -0.2584667 0.466749 -0.7703075 1.2575562
> tmp[,c("col6","col20")]
col6 col20
row1 0.90492739 0.7321257
row2 0.66977915 0.2749593
row3 0.07438745 0.5758043
row4 0.72727281 0.1772235
row5 1.41895187 1.2575562
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.9049274 0.7321257
row5 1.4189519 1.2575562
>
>
>
>
> 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 50.14825 51.20177 50.52867 50.58805 49.3605 104.7558 51.1851 48.09625
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.38839 50.37603 50.48154 50.50222 48.54403 48.67613 49.68101 48.42374
col17 col18 col19 col20
row1 50.86761 49.97587 49.83418 104.8013
> tmp[,"col10"]
col10
row1 50.37603
row2 28.90090
row3 30.02105
row4 29.16968
row5 50.26565
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.14825 51.20177 50.52867 50.58805 49.36050 104.7558 51.18510 48.09625
row5 50.13256 49.31569 48.65309 49.48477 50.01361 106.5627 51.04073 51.31068
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.38839 50.37603 50.48154 50.50222 48.54403 48.67613 49.68101 48.42374
row5 49.16211 50.26565 52.16682 50.87148 50.22975 50.79787 51.33915 50.48943
col17 col18 col19 col20
row1 50.86761 49.97587 49.83418 104.8013
row5 50.03477 52.04607 50.05983 104.6507
> tmp[,c("col6","col20")]
col6 col20
row1 104.75581 104.80134
row2 74.73195 74.92693
row3 75.07879 73.50168
row4 73.88669 74.25161
row5 106.56265 104.65067
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.7558 104.8013
row5 106.5627 104.6507
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.7558 104.8013
row5 106.5627 104.6507
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.4452910
[2,] -0.7849850
[3,] -1.5366858
[4,] -0.9460220
[5,] -0.9761248
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.62427880 -0.3947984
[2,] 0.09683601 0.6435237
[3,] 0.73308419 0.5549155
[4,] -0.33110930 -1.5344880
[5,] 0.05611783 0.2440893
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.6972355 -0.8132594
[2,] 1.7301232 0.1493617
[3,] -0.4765070 0.5705732
[4,] -0.4203382 0.6011255
[5,] -1.5620409 -0.5095216
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.6972355
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.6972355
[2,] 1.7301232
>
>
>
> 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 1.562903 -3.0260047 -2.174628 0.1592416 -0.4218745 -0.1705655 -2.474987
row1 1.234496 -0.4359931 1.748970 0.6133131 0.6594640 -1.8660730 -1.063101
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.2483908 2.1817178 -0.2754898 -1.3683711 3.1981208 0.1410344 -0.3528597
row1 0.6669102 -0.6307231 0.9381127 -0.2934984 -0.4322758 0.4165976 -0.1995179
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.6896241 -0.6944956 0.6626686 0.2486224 0.1647150 0.1584905
row1 0.4035628 1.0297540 -1.3002949 1.0463823 -0.3276632 -0.5616310
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.1468342 -0.1050592 -0.3897745 0.3000088 1.1147 0.6266695 0.3599607
[,8] [,9] [,10]
row2 0.04023461 -0.6616446 0.2098229
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.9452105 -1.587278 1.884831 0.6825896 -1.519613 0.2864291 0.4394347
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.162828 -0.2324418 1.330578 -0.9737788 -0.246733 0.5879418 0.7540551
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.8652259 1.054741 1.352414 -1.282339 -1.003027 -1.118322
>
>
> 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: 0x600000fdc300>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMcc9b738031f2"
[2] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMcc9b654f421b"
[3] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMcc9b367d2e93"
[4] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMcc9b547cd0d7"
[5] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMcc9b4e72fe96"
[6] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMcc9b5fa85216"
[7] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMcc9b23a5536a"
[8] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMcc9b3b07666e"
[9] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMcc9b62d5de08"
[10] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMcc9b46e411e9"
[11] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMcc9b2753fc5b"
[12] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMcc9b7adcce88"
[13] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMcc9b367b81bc"
[14] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMcc9b66827995"
[15] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMcc9b7ffc59c6"
>
>
> ### 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: 0x600000fd0360>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600000fd0360>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600000fd0360>
> rowMedians(tmp)
[1] -0.190212763 -0.146680187 0.161658158 0.137404560 -0.515290316
[6] 0.030391362 0.367987679 -0.128563878 -0.270466746 -0.152890776
[11] -0.261173126 -0.005853771 0.285488783 0.163198628 0.461849137
[16] -0.060182480 -0.313794761 -0.023791564 -0.290807262 -0.007820578
[21] 0.402290279 0.362969419 -0.315363285 -0.310147485 0.613791821
[26] -0.007398571 -0.241842656 -0.210881598 -0.124461189 -0.241816349
[31] -0.475468034 0.184466556 0.059835023 -0.086595476 0.425865624
[36] -0.194382462 -0.580853136 -0.222171002 -0.179515980 -0.298736754
[41] -0.396410328 0.031795092 0.442771462 0.036036652 0.205274382
[46] -0.351824027 0.103959559 -0.295362249 -0.085820900 0.084680016
[51] 0.120790515 -0.861694431 0.501032589 0.351972598 -0.322605820
[56] -0.405263808 -0.101113846 0.168334794 0.359029403 -0.002074535
[61] -0.117088602 0.005435027 -0.377091275 0.005408091 0.357840221
[66] -0.047487733 0.147746585 0.170881794 -0.211599363 -0.262940038
[71] 0.104987718 0.049870472 -0.203951019 -0.207202280 0.261740450
[76] -0.357849301 0.216013790 -0.419015140 -0.171342044 -0.361502428
[81] -0.029386193 -0.718654654 -0.301480351 -0.072363463 -0.339458948
[86] 0.163587448 -0.092869846 -0.402423775 0.117541409 -0.364128027
[91] -0.341428193 0.131746248 -0.026504499 -0.223202262 0.237317886
[96] 0.287414393 -0.189011975 -0.023279135 -0.065095924 -0.124647573
[101] 0.128782127 -0.527799761 0.457376757 -0.111208454 0.358965289
[106] -0.178866504 -0.084992686 -0.114698884 0.330573340 -0.134265763
[111] 0.102821155 0.064109914 0.059872114 0.174211176 -0.157069997
[116] -0.405895916 0.234868603 0.600405550 0.192351215 0.202836935
[121] -0.242230155 -0.249794193 0.054663647 0.052766661 0.008960274
[126] -0.378174612 0.174699394 0.350942356 0.086148936 -0.074300331
[131] 0.543611402 -0.790428285 0.361687107 0.083773859 -0.417265143
[136] 0.162922144 -0.129747975 0.330098286 0.193190166 -0.171692731
[141] 0.280162241 0.307189277 0.262356708 0.337069046 -0.005561325
[146] 0.094637500 0.305422896 -0.137560632 -0.228727642 0.091973908
[151] 0.287869384 -0.247406708 -0.218640281 -0.046540299 -0.038933235
[156] 0.166943248 -0.266221452 0.285060268 -0.135963447 0.439372473
[161] 0.239613755 0.040636668 0.433154667 0.253542873 -0.277163005
[166] 0.188546388 -0.387691441 0.031951401 0.313422059 -0.646269922
[171] 0.133381522 0.120401843 -0.207145906 0.262912356 -0.227775778
[176] 0.043916945 -0.579405303 0.361066979 -0.042521578 -0.353924507
[181] 0.278194231 -0.038243540 -0.173780258 -0.277094952 -0.421215385
[186] 0.533859773 0.203006992 -0.149609028 -0.428114407 -0.118739204
[191] -0.360871223 0.494831410 0.090956127 -0.644109300 -0.184400563
[196] -0.045257503 0.177282531 0.145104284 -0.173043734 -0.062664774
[201] -0.224609496 -0.330057012 -0.299811247 -0.055949287 -0.661960532
[206] -0.088156231 -0.493665126 -0.126142923 0.037945210 -0.425945654
[211] -0.180102041 -0.140281553 0.194463086 0.214681210 0.292082294
[216] 0.187922891 0.153430586 0.160885976 0.090398121 0.078570586
[221] 0.033566378 -0.684662717 0.532654785 -0.411279021 -0.720816783
[226] 0.371616479 -0.501880781 -0.513738833 0.015580086 0.104847505
>
> proc.time()
user system elapsed
0.647 3.219 4.140
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x6000033f44e0>
> .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: 0x6000033f44e0>
> .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: 0x6000033f44e0>
> .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: 0x6000033f44e0>
> 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: 0x6000033e82a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033e82a0>
> .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: 0x6000033e82a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033e82a0>
> .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: 0x6000033e82a0>
> 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: 0x6000033e8480>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033e8480>
> .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: 0x6000033e8480>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000033e8480>
> .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: 0x6000033e8480>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000033e8480>
> .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: 0x6000033e8480>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000033e8480>
> .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: 0x6000033e8480>
> 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: 0x6000033e8660>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000033e8660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033e8660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033e8660>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilecfd71f0264c4" "BufferedMatrixFilecfd756258fc3"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilecfd71f0264c4" "BufferedMatrixFilecfd756258fc3"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033e8900>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033e8900>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000033e8900>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000033e8900>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000033e8900>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000033e8900>
> .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: 0x6000033e8ae0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033e8ae0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000033e8ae0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000033e8ae0>
> 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: 0x6000033e8cc0>
> .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: 0x6000033e8cc0>
> rm(P)
>
> proc.time()
user system elapsed
0.111 0.039 0.147
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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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.
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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
0.111 0.025 0.132