Ben Bolstad
| Snapshot Date: 2026-04-12 13:40 -0400 (Sun, 12 Apr 2026) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: ecdbf23 |
| git_last_commit_date: 2025-10-29 09:58:55 -0400 (Wed, 29 Oct 2025) |
| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-04-13 11:35 -0400 (Mon, 13 Apr 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) | x86_64 | 4.6.0 alpha (2026-04-05 r89794) | 4919 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.6.0 alpha (2026-04-08 r89818) | 4632 |
| 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 259/2390 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.75.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) / x86_64 | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| See other builds for BufferedMatrix in R Universe. | ||||||||||||||
|
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: 1.75.0 |
| 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_1.75.0.tar.gz |
| StartedAt: 2026-04-12 18:42:17 -0400 (Sun, 12 Apr 2026) |
| EndedAt: 2026-04-12 18:42:37 -0400 (Sun, 12 Apr 2026) |
| EllapsedTime: 20.3 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_1.75.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.6.0 alpha (2026-04-08 r89818)
* using platform: aarch64-apple-darwin23
* R was compiled by
Apple clang version 17.0.0 (clang-1700.3.19.1)
GNU Fortran (GCC) 14.2.0
* running under: macOS Tahoe 26.3.1
* using session charset: UTF-8
* current time: 2026-04-12 22:42:17 UTC
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.75.0’
* 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-3.23-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 17.0.0 (clang-1700.6.4.2)’
* used SDK: ‘MacOSX26.2.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 ... INFO
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, 1 NOTE
See
‘/Users/biocbuild/bbs-3.23-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/4.6/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.75.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 17.0.0 (clang-1700.6.4.2)’
using SDK: ‘MacOSX26.2.sdk’
clang -arch arm64 -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 -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]
1580 | if (!(Matrix->readonly) & setting){
| ^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
1580 | if (!(Matrix->readonly) & setting){
| ^
| ( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
1580 | if (!(Matrix->readonly) & setting){
| ^
| ( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
2 warnings generated.
clang -arch arm64 -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 -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 -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/4.6/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 4.6.0 alpha (2026-04-08 r89818)
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23
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
0.121 0.047 0.164
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.6.0 alpha (2026-04-08 r89818)
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23
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-3.23-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 484141 25.9 1067250 57 NA 632020 33.8
Vcells 896965 6.9 8388608 64 196608 2112095 16.2
>
>
>
>
> ##
> ## 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] "Sun Apr 12 18:42:28 2026"
> 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] "Sun Apr 12 18:42:28 2026"
>
>
> 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: 0xc9dd78000>
>
>
>
> 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] "Sun Apr 12 18:42:30 2026"
> 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] "Sun Apr 12 18:42:30 2026"
>
> ColMode(tmp2)
<pointer: 0xc9dd78000>
>
>
>
> ### 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,] 101.957679 0.2978303 0.4992326 0.4190492
[2,] 0.364888 0.9912730 1.3066266 -2.1827509
[3,] 1.873354 0.6392277 1.4726742 0.3620634
[4,] -1.620116 0.7762525 0.4016415 1.9014396
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-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,] 101.957679 0.2978303 0.4992326 0.4190492
[2,] 0.364888 0.9912730 1.3066266 2.1827509
[3,] 1.873354 0.6392277 1.4726742 0.3620634
[4,] 1.620116 0.7762525 0.4016415 1.9014396
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-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,] 10.0974095 0.5457383 0.7065639 0.6473401
[2,] 0.6040596 0.9956269 1.1430777 1.4774136
[3,] 1.3687052 0.7995171 1.2135379 0.6017170
[4,] 1.2728377 0.8810520 0.6337520 1.3789270
>
> 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-3.23-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,] 227.93177 30.75521 32.56487 31.89245
[2,] 31.40548 35.94754 37.73740 41.95689
[3,] 40.56041 33.63440 38.60805 31.37923
[4,] 39.34849 34.58677 31.73916 40.69071
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0xc9dd780c0>
> exp(tmp5)
<pointer: 0xc9dd780c0>
> log(tmp5,2)
<pointer: 0xc9dd780c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 474.4101
> Min(tmp5)
[1] 54.11813
> mean(tmp5)
[1] 72.67174
> Sum(tmp5)
[1] 14534.35
> Var(tmp5)
[1] 889.4426
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 88.45385 69.30078 73.74790 71.25625 70.84478 70.77589 72.98800 68.69344
[9] 70.75072 69.90580
> rowSums(tmp5)
[1] 1769.077 1386.016 1474.958 1425.125 1416.896 1415.518 1459.760 1373.869
[9] 1415.014 1398.116
> rowVars(tmp5)
[1] 8313.11817 95.36361 75.36246 82.76703 71.03002 72.92374
[7] 82.38753 104.45490 78.79767 26.06265
> rowSd(tmp5)
[1] 91.176303 9.765429 8.681156 9.097639 8.427931 8.539540 9.076758
[8] 10.220318 8.876805 5.105159
> rowMax(tmp5)
[1] 474.41013 87.49987 90.84212 84.69238 85.97262 85.27842 91.16523
[8] 87.14106 88.21507 82.73976
> rowMin(tmp5)
[1] 57.10173 54.11813 57.35178 54.37042 56.59783 55.58116 59.69890 56.49868
[9] 56.98406 60.84098
>
> colMeans(tmp5)
[1] 108.99286 72.45483 67.00035 70.20948 71.77200 71.78935 67.43788
[8] 71.18347 74.82047 68.02873 69.84049 67.15603 71.40145 72.84895
[15] 69.41729 74.97688 74.40999 65.12435 73.08981 71.48016
> colSums(tmp5)
[1] 1089.9286 724.5483 670.0035 702.0948 717.7200 717.8935 674.3788
[8] 711.8347 748.2047 680.2873 698.4049 671.5603 714.0145 728.4895
[15] 694.1729 749.7688 744.0999 651.2435 730.8981 714.8016
> colVars(tmp5)
[1] 16560.72506 73.28829 67.79928 111.97650 43.44853 42.20818
[7] 57.71847 185.42542 28.09315 16.79472 77.15629 56.18892
[13] 72.60156 111.79961 112.80121 73.00653 57.99402 92.89601
[19] 60.53112 61.40346
> colSd(tmp5)
[1] 128.688481 8.560858 8.234032 10.581895 6.591550 6.496783
[7] 7.597267 13.617100 5.300297 4.098137 8.783865 7.495927
[13] 8.520655 10.573533 10.620791 8.544386 7.615381 9.638258
[19] 7.780175 7.836036
> colMax(tmp5)
[1] 474.41013 83.01620 80.35760 87.32776 85.97262 80.02954 80.66494
[8] 90.01830 81.31754 75.63409 87.49987 77.70211 81.08689 90.84212
[15] 91.16523 85.54764 85.89159 88.21507 83.79856 85.27549
> colMin(tmp5)
[1] 57.86415 57.31926 55.58116 56.59783 60.74233 64.17055 56.86700 54.11813
[9] 65.99277 61.26558 60.18368 55.75622 57.10173 57.97734 56.49868 59.84206
[17] 64.20205 54.37042 58.26661 57.35178
>
>
> ### 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] 88.45385 69.30078 73.74790 71.25625 70.84478 70.77589 NA 68.69344
[9] 70.75072 69.90580
> rowSums(tmp5)
[1] 1769.077 1386.016 1474.958 1425.125 1416.896 1415.518 NA 1373.869
[9] 1415.014 1398.116
> rowVars(tmp5)
[1] 8313.11817 95.36361 75.36246 82.76703 71.03002 72.92374
[7] 81.44092 104.45490 78.79767 26.06265
> rowSd(tmp5)
[1] 91.176303 9.765429 8.681156 9.097639 8.427931 8.539540 9.024462
[8] 10.220318 8.876805 5.105159
> rowMax(tmp5)
[1] 474.41013 87.49987 90.84212 84.69238 85.97262 85.27842 NA
[8] 87.14106 88.21507 82.73976
> rowMin(tmp5)
[1] 57.10173 54.11813 57.35178 54.37042 56.59783 55.58116 NA 56.49868
[9] 56.98406 60.84098
>
> colMeans(tmp5)
[1] NA 72.45483 67.00035 70.20948 71.77200 71.78935 67.43788 71.18347
[9] 74.82047 68.02873 69.84049 67.15603 71.40145 72.84895 69.41729 74.97688
[17] 74.40999 65.12435 73.08981 71.48016
> colSums(tmp5)
[1] NA 724.5483 670.0035 702.0948 717.7200 717.8935 674.3788 711.8347
[9] 748.2047 680.2873 698.4049 671.5603 714.0145 728.4895 694.1729 749.7688
[17] 744.0999 651.2435 730.8981 714.8016
> colVars(tmp5)
[1] NA 73.28829 67.79928 111.97650 43.44853 42.20818 57.71847
[8] 185.42542 28.09315 16.79472 77.15629 56.18892 72.60156 111.79961
[15] 112.80121 73.00653 57.99402 92.89601 60.53112 61.40346
> colSd(tmp5)
[1] NA 8.560858 8.234032 10.581895 6.591550 6.496783 7.597267
[8] 13.617100 5.300297 4.098137 8.783865 7.495927 8.520655 10.573533
[15] 10.620791 8.544386 7.615381 9.638258 7.780175 7.836036
> colMax(tmp5)
[1] NA 83.01620 80.35760 87.32776 85.97262 80.02954 80.66494 90.01830
[9] 81.31754 75.63409 87.49987 77.70211 81.08689 90.84212 91.16523 85.54764
[17] 85.89159 88.21507 83.79856 85.27549
> colMin(tmp5)
[1] NA 57.31926 55.58116 56.59783 60.74233 64.17055 56.86700 54.11813
[9] 65.99277 61.26558 60.18368 55.75622 57.10173 57.97734 56.49868 59.84206
[17] 64.20205 54.37042 58.26661 57.35178
>
> Max(tmp5,na.rm=TRUE)
[1] 474.4101
> Min(tmp5,na.rm=TRUE)
[1] 54.11813
> mean(tmp5,na.rm=TRUE)
[1] 72.71899
> Sum(tmp5,na.rm=TRUE)
[1] 14471.08
> Var(tmp5,na.rm=TRUE)
[1] 893.486
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.45385 69.30078 73.74790 71.25625 70.84478 70.77589 73.49952 68.69344
[9] 70.75072 69.90580
> rowSums(tmp5,na.rm=TRUE)
[1] 1769.077 1386.016 1474.958 1425.125 1416.896 1415.518 1396.491 1373.869
[9] 1415.014 1398.116
> rowVars(tmp5,na.rm=TRUE)
[1] 8313.11817 95.36361 75.36246 82.76703 71.03002 72.92374
[7] 81.44092 104.45490 78.79767 26.06265
> rowSd(tmp5,na.rm=TRUE)
[1] 91.176303 9.765429 8.681156 9.097639 8.427931 8.539540 9.024462
[8] 10.220318 8.876805 5.105159
> rowMax(tmp5,na.rm=TRUE)
[1] 474.41013 87.49987 90.84212 84.69238 85.97262 85.27842 91.16523
[8] 87.14106 88.21507 82.73976
> rowMin(tmp5,na.rm=TRUE)
[1] 57.10173 54.11813 57.35178 54.37042 56.59783 55.58116 59.69890 56.49868
[9] 56.98406 60.84098
>
> colMeans(tmp5,na.rm=TRUE)
[1] 114.07326 72.45483 67.00035 70.20948 71.77200 71.78935 67.43788
[8] 71.18347 74.82047 68.02873 69.84049 67.15603 71.40145 72.84895
[15] 69.41729 74.97688 74.40999 65.12435 73.08981 71.48016
> colSums(tmp5,na.rm=TRUE)
[1] 1026.6594 724.5483 670.0035 702.0948 717.7200 717.8935 674.3788
[8] 711.8347 748.2047 680.2873 698.4049 671.5603 714.0145 728.4895
[15] 694.1729 749.7688 744.0999 651.2435 730.8981 714.8016
> colVars(tmp5,na.rm=TRUE)
[1] 18340.44723 73.28829 67.79928 111.97650 43.44853 42.20818
[7] 57.71847 185.42542 28.09315 16.79472 77.15629 56.18892
[13] 72.60156 111.79961 112.80121 73.00653 57.99402 92.89601
[19] 60.53112 61.40346
> colSd(tmp5,na.rm=TRUE)
[1] 135.426907 8.560858 8.234032 10.581895 6.591550 6.496783
[7] 7.597267 13.617100 5.300297 4.098137 8.783865 7.495927
[13] 8.520655 10.573533 10.620791 8.544386 7.615381 9.638258
[19] 7.780175 7.836036
> colMax(tmp5,na.rm=TRUE)
[1] 474.41013 83.01620 80.35760 87.32776 85.97262 80.02954 80.66494
[8] 90.01830 81.31754 75.63409 87.49987 77.70211 81.08689 90.84212
[15] 91.16523 85.54764 85.89159 88.21507 83.79856 85.27549
> colMin(tmp5,na.rm=TRUE)
[1] 57.86415 57.31926 55.58116 56.59783 60.74233 64.17055 56.86700 54.11813
[9] 65.99277 61.26558 60.18368 55.75622 57.10173 57.97734 56.49868 59.84206
[17] 64.20205 54.37042 58.26661 57.35178
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.45385 69.30078 73.74790 71.25625 70.84478 70.77589 NaN 68.69344
[9] 70.75072 69.90580
> rowSums(tmp5,na.rm=TRUE)
[1] 1769.077 1386.016 1474.958 1425.125 1416.896 1415.518 0.000 1373.869
[9] 1415.014 1398.116
> rowVars(tmp5,na.rm=TRUE)
[1] 8313.11817 95.36361 75.36246 82.76703 71.03002 72.92374
[7] NA 104.45490 78.79767 26.06265
> rowSd(tmp5,na.rm=TRUE)
[1] 91.176303 9.765429 8.681156 9.097639 8.427931 8.539540 NA
[8] 10.220318 8.876805 5.105159
> rowMax(tmp5,na.rm=TRUE)
[1] 474.41013 87.49987 90.84212 84.69238 85.97262 85.27842 NA
[8] 87.14106 88.21507 82.73976
> rowMin(tmp5,na.rm=TRUE)
[1] 57.10173 54.11813 57.35178 54.37042 56.59783 55.58116 NA 56.49868
[9] 56.98406 60.84098
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] NaN 71.31126 67.81162 70.78107 71.97709 70.87377 67.42565 70.14573
[9] 74.29754 68.28778 69.05202 65.98424 70.35972 73.86601 67.00085 74.53496
[17] 75.38576 65.62960 71.97692 71.95716
> colSums(tmp5,na.rm=TRUE)
[1] 0.0000 641.8013 610.3046 637.0296 647.7938 637.8640 606.8308 631.3116
[9] 668.6779 614.5900 621.4682 593.8582 633.2375 664.7941 603.0077 670.8147
[17] 678.4718 590.6664 647.7923 647.6144
> colVars(tmp5,na.rm=TRUE)
[1] NA 67.73711 68.86985 122.29805 48.40640 38.05355 64.93159
[8] 196.48848 28.52841 18.13911 79.80691 47.76531 69.46828 114.13748
[15] 61.21070 79.93531 54.53191 101.63620 54.16414 66.51920
> colSd(tmp5,na.rm=TRUE)
[1] NA 8.230256 8.298786 11.058845 6.957471 6.168756 8.058014
[8] 14.017435 5.341199 4.259004 8.933471 6.911245 8.334764 10.683515
[15] 7.823727 8.940655 7.384573 10.081478 7.359629 8.155930
> colMax(tmp5,na.rm=TRUE)
[1] -Inf 83.01620 80.35760 87.32776 85.97262 80.00531 80.66494 90.01830
[9] 81.31754 75.63409 87.49987 76.76670 81.08689 90.84212 80.23620 85.54764
[17] 85.89159 88.21507 83.79856 85.27549
> colMin(tmp5,na.rm=TRUE)
[1] Inf 57.31926 55.58116 56.59783 60.74233 64.17055 56.86700 54.11813
[9] 65.99277 61.26558 60.18368 55.75622 57.10173 57.97734 56.49868 59.84206
[17] 64.20205 54.37042 58.26661 57.35178
>
>
>
>
> 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] 199.0901 246.9150 164.1214 295.5654 253.5277 275.1509 224.4637 186.2546
[9] 173.7295 104.7634
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 199.0901 246.9150 164.1214 295.5654 253.5277 275.1509 224.4637 186.2546
[9] 173.7295 104.7634
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -8.526513e-14 5.684342e-14 0.000000e+00 -2.842171e-14 -5.684342e-14
[6] -2.557954e-13 -1.989520e-13 -1.989520e-13 5.684342e-14 -5.684342e-14
[11] 2.842171e-14 0.000000e+00 -1.421085e-13 5.684342e-14 -2.842171e-14
[16] 5.684342e-14 -5.684342e-14 0.000000e+00 2.842171e-14 -7.105427e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
9 10
3 8
8 11
8 20
1 10
2 19
4 10
1 20
6 2
7 1
9 6
3 11
3 18
5 4
2 5
4 13
2 15
8 4
6 8
10 15
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 3.094928
> Min(tmp)
[1] -2.364937
> mean(tmp)
[1] 0.05226091
> Sum(tmp)
[1] 5.226091
> Var(tmp)
[1] 1.083935
>
> rowMeans(tmp)
[1] 0.05226091
> rowSums(tmp)
[1] 5.226091
> rowVars(tmp)
[1] 1.083935
> rowSd(tmp)
[1] 1.041122
> rowMax(tmp)
[1] 3.094928
> rowMin(tmp)
[1] -2.364937
>
> colMeans(tmp)
[1] -0.04764571 0.42369991 1.21366898 -1.66518071 -1.62787577 0.69847342
[7] 0.32388550 -1.99977070 -1.06047699 0.69479107 -0.19532168 -0.48400326
[13] -0.09488060 0.29223023 0.23153379 0.50043390 0.19590072 0.19107194
[19] -0.86754982 -1.91206373 1.57917630 1.11883713 -0.89400424 -0.28718493
[25] -0.98897922 1.55262898 0.98053551 0.02016811 0.52954351 0.08922870
[31] 2.08673070 0.08490351 1.23597268 1.43997381 -0.37043120 0.36847147
[37] 0.64232676 -0.14143705 -0.67553335 0.48743755 -1.24261831 0.33190692
[43] 0.05830338 -1.42265806 1.34714220 -0.71175918 0.34540791 -0.81316254
[49] -0.53502929 -0.69744354 -1.43657165 3.09492764 0.63751763 1.88338619
[55] 0.46702717 0.47185877 0.18578224 0.32354559 -1.10768832 0.18481690
[61] -0.86919961 -0.49297725 -0.58681317 -0.27730039 0.93753535 0.42145860
[67] -0.05529485 0.26416509 -1.03036573 0.36598562 -0.51458713 1.20774857
[73] -1.63838017 -0.00703014 -1.99560859 -0.22213649 0.15348650 0.07330461
[79] -0.47619157 1.26786270 1.09931814 0.92840668 -0.15945611 -0.48329825
[85] -1.84661974 1.37793958 0.89887947 2.05246481 1.09777845 0.23401319
[91] -0.33083486 -0.17228271 -0.36056516 1.07416009 1.08611743 -1.53482045
[97] -2.36493721 0.93207706 -1.68222906 1.82034083
> colSums(tmp)
[1] -0.04764571 0.42369991 1.21366898 -1.66518071 -1.62787577 0.69847342
[7] 0.32388550 -1.99977070 -1.06047699 0.69479107 -0.19532168 -0.48400326
[13] -0.09488060 0.29223023 0.23153379 0.50043390 0.19590072 0.19107194
[19] -0.86754982 -1.91206373 1.57917630 1.11883713 -0.89400424 -0.28718493
[25] -0.98897922 1.55262898 0.98053551 0.02016811 0.52954351 0.08922870
[31] 2.08673070 0.08490351 1.23597268 1.43997381 -0.37043120 0.36847147
[37] 0.64232676 -0.14143705 -0.67553335 0.48743755 -1.24261831 0.33190692
[43] 0.05830338 -1.42265806 1.34714220 -0.71175918 0.34540791 -0.81316254
[49] -0.53502929 -0.69744354 -1.43657165 3.09492764 0.63751763 1.88338619
[55] 0.46702717 0.47185877 0.18578224 0.32354559 -1.10768832 0.18481690
[61] -0.86919961 -0.49297725 -0.58681317 -0.27730039 0.93753535 0.42145860
[67] -0.05529485 0.26416509 -1.03036573 0.36598562 -0.51458713 1.20774857
[73] -1.63838017 -0.00703014 -1.99560859 -0.22213649 0.15348650 0.07330461
[79] -0.47619157 1.26786270 1.09931814 0.92840668 -0.15945611 -0.48329825
[85] -1.84661974 1.37793958 0.89887947 2.05246481 1.09777845 0.23401319
[91] -0.33083486 -0.17228271 -0.36056516 1.07416009 1.08611743 -1.53482045
[97] -2.36493721 0.93207706 -1.68222906 1.82034083
> 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] -0.04764571 0.42369991 1.21366898 -1.66518071 -1.62787577 0.69847342
[7] 0.32388550 -1.99977070 -1.06047699 0.69479107 -0.19532168 -0.48400326
[13] -0.09488060 0.29223023 0.23153379 0.50043390 0.19590072 0.19107194
[19] -0.86754982 -1.91206373 1.57917630 1.11883713 -0.89400424 -0.28718493
[25] -0.98897922 1.55262898 0.98053551 0.02016811 0.52954351 0.08922870
[31] 2.08673070 0.08490351 1.23597268 1.43997381 -0.37043120 0.36847147
[37] 0.64232676 -0.14143705 -0.67553335 0.48743755 -1.24261831 0.33190692
[43] 0.05830338 -1.42265806 1.34714220 -0.71175918 0.34540791 -0.81316254
[49] -0.53502929 -0.69744354 -1.43657165 3.09492764 0.63751763 1.88338619
[55] 0.46702717 0.47185877 0.18578224 0.32354559 -1.10768832 0.18481690
[61] -0.86919961 -0.49297725 -0.58681317 -0.27730039 0.93753535 0.42145860
[67] -0.05529485 0.26416509 -1.03036573 0.36598562 -0.51458713 1.20774857
[73] -1.63838017 -0.00703014 -1.99560859 -0.22213649 0.15348650 0.07330461
[79] -0.47619157 1.26786270 1.09931814 0.92840668 -0.15945611 -0.48329825
[85] -1.84661974 1.37793958 0.89887947 2.05246481 1.09777845 0.23401319
[91] -0.33083486 -0.17228271 -0.36056516 1.07416009 1.08611743 -1.53482045
[97] -2.36493721 0.93207706 -1.68222906 1.82034083
> colMin(tmp)
[1] -0.04764571 0.42369991 1.21366898 -1.66518071 -1.62787577 0.69847342
[7] 0.32388550 -1.99977070 -1.06047699 0.69479107 -0.19532168 -0.48400326
[13] -0.09488060 0.29223023 0.23153379 0.50043390 0.19590072 0.19107194
[19] -0.86754982 -1.91206373 1.57917630 1.11883713 -0.89400424 -0.28718493
[25] -0.98897922 1.55262898 0.98053551 0.02016811 0.52954351 0.08922870
[31] 2.08673070 0.08490351 1.23597268 1.43997381 -0.37043120 0.36847147
[37] 0.64232676 -0.14143705 -0.67553335 0.48743755 -1.24261831 0.33190692
[43] 0.05830338 -1.42265806 1.34714220 -0.71175918 0.34540791 -0.81316254
[49] -0.53502929 -0.69744354 -1.43657165 3.09492764 0.63751763 1.88338619
[55] 0.46702717 0.47185877 0.18578224 0.32354559 -1.10768832 0.18481690
[61] -0.86919961 -0.49297725 -0.58681317 -0.27730039 0.93753535 0.42145860
[67] -0.05529485 0.26416509 -1.03036573 0.36598562 -0.51458713 1.20774857
[73] -1.63838017 -0.00703014 -1.99560859 -0.22213649 0.15348650 0.07330461
[79] -0.47619157 1.26786270 1.09931814 0.92840668 -0.15945611 -0.48329825
[85] -1.84661974 1.37793958 0.89887947 2.05246481 1.09777845 0.23401319
[91] -0.33083486 -0.17228271 -0.36056516 1.07416009 1.08611743 -1.53482045
[97] -2.36493721 0.93207706 -1.68222906 1.82034083
> colMedians(tmp)
[1] -0.04764571 0.42369991 1.21366898 -1.66518071 -1.62787577 0.69847342
[7] 0.32388550 -1.99977070 -1.06047699 0.69479107 -0.19532168 -0.48400326
[13] -0.09488060 0.29223023 0.23153379 0.50043390 0.19590072 0.19107194
[19] -0.86754982 -1.91206373 1.57917630 1.11883713 -0.89400424 -0.28718493
[25] -0.98897922 1.55262898 0.98053551 0.02016811 0.52954351 0.08922870
[31] 2.08673070 0.08490351 1.23597268 1.43997381 -0.37043120 0.36847147
[37] 0.64232676 -0.14143705 -0.67553335 0.48743755 -1.24261831 0.33190692
[43] 0.05830338 -1.42265806 1.34714220 -0.71175918 0.34540791 -0.81316254
[49] -0.53502929 -0.69744354 -1.43657165 3.09492764 0.63751763 1.88338619
[55] 0.46702717 0.47185877 0.18578224 0.32354559 -1.10768832 0.18481690
[61] -0.86919961 -0.49297725 -0.58681317 -0.27730039 0.93753535 0.42145860
[67] -0.05529485 0.26416509 -1.03036573 0.36598562 -0.51458713 1.20774857
[73] -1.63838017 -0.00703014 -1.99560859 -0.22213649 0.15348650 0.07330461
[79] -0.47619157 1.26786270 1.09931814 0.92840668 -0.15945611 -0.48329825
[85] -1.84661974 1.37793958 0.89887947 2.05246481 1.09777845 0.23401319
[91] -0.33083486 -0.17228271 -0.36056516 1.07416009 1.08611743 -1.53482045
[97] -2.36493721 0.93207706 -1.68222906 1.82034083
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.04764571 0.4236999 1.213669 -1.665181 -1.627876 0.6984734 0.3238855
[2,] -0.04764571 0.4236999 1.213669 -1.665181 -1.627876 0.6984734 0.3238855
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.999771 -1.060477 0.6947911 -0.1953217 -0.4840033 -0.0948806 0.2922302
[2,] -1.999771 -1.060477 0.6947911 -0.1953217 -0.4840033 -0.0948806 0.2922302
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.2315338 0.5004339 0.1959007 0.1910719 -0.8675498 -1.912064 1.579176
[2,] 0.2315338 0.5004339 0.1959007 0.1910719 -0.8675498 -1.912064 1.579176
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.118837 -0.8940042 -0.2871849 -0.9889792 1.552629 0.9805355 0.02016811
[2,] 1.118837 -0.8940042 -0.2871849 -0.9889792 1.552629 0.9805355 0.02016811
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.5295435 0.0892287 2.086731 0.08490351 1.235973 1.439974 -0.3704312
[2,] 0.5295435 0.0892287 2.086731 0.08490351 1.235973 1.439974 -0.3704312
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.3684715 0.6423268 -0.141437 -0.6755334 0.4874375 -1.242618 0.3319069
[2,] 0.3684715 0.6423268 -0.141437 -0.6755334 0.4874375 -1.242618 0.3319069
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.05830338 -1.422658 1.347142 -0.7117592 0.3454079 -0.8131625 -0.5350293
[2,] 0.05830338 -1.422658 1.347142 -0.7117592 0.3454079 -0.8131625 -0.5350293
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.6974435 -1.436572 3.094928 0.6375176 1.883386 0.4670272 0.4718588
[2,] -0.6974435 -1.436572 3.094928 0.6375176 1.883386 0.4670272 0.4718588
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.1857822 0.3235456 -1.107688 0.1848169 -0.8691996 -0.4929772 -0.5868132
[2,] 0.1857822 0.3235456 -1.107688 0.1848169 -0.8691996 -0.4929772 -0.5868132
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.2773004 0.9375353 0.4214586 -0.05529485 0.2641651 -1.030366 0.3659856
[2,] -0.2773004 0.9375353 0.4214586 -0.05529485 0.2641651 -1.030366 0.3659856
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.5145871 1.207749 -1.63838 -0.00703014 -1.995609 -0.2221365 0.1534865
[2,] -0.5145871 1.207749 -1.63838 -0.00703014 -1.995609 -0.2221365 0.1534865
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.07330461 -0.4761916 1.267863 1.099318 0.9284067 -0.1594561 -0.4832982
[2,] 0.07330461 -0.4761916 1.267863 1.099318 0.9284067 -0.1594561 -0.4832982
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -1.84662 1.37794 0.8988795 2.052465 1.097778 0.2340132 -0.3308349
[2,] -1.84662 1.37794 0.8988795 2.052465 1.097778 0.2340132 -0.3308349
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.1722827 -0.3605652 1.07416 1.086117 -1.53482 -2.364937 0.9320771
[2,] -0.1722827 -0.3605652 1.07416 1.086117 -1.53482 -2.364937 0.9320771
[,99] [,100]
[1,] -1.682229 1.820341
[2,] -1.682229 1.820341
>
>
> Max(tmp2)
[1] 1.86159
> Min(tmp2)
[1] -1.849252
> mean(tmp2)
[1] -0.04543387
> Sum(tmp2)
[1] -4.543387
> Var(tmp2)
[1] 0.7137603
>
> rowMeans(tmp2)
[1] 1.3553215869 0.5165942912 0.4933780300 -0.4288942730 -1.3275325428
[6] 1.0102690065 0.6704068240 -1.4768391984 -0.0357733694 -0.1491428668
[11] -0.6261669075 -0.8177415470 -0.4377280389 -0.8592072501 -0.8400311874
[16] 0.4376424152 0.7859940972 -0.1324732259 -0.2312337070 -0.7792035013
[21] -1.4867777282 -1.0714441363 0.7016955017 -0.6235126975 -0.2791327570
[26] 1.0441354188 -0.6895971316 0.4275700920 -0.7257593253 -0.0822191816
[31] -1.0461669279 0.5914295825 0.8323999197 0.0217841756 0.2328719617
[36] -0.5090058699 1.2119402580 0.9972199246 0.3570501165 -0.6493198293
[41] -0.1613807808 1.5613191429 -1.0192846522 0.5979846843 1.0224328453
[46] 0.5709403436 0.5528472163 -0.0468597748 -0.5146629924 0.6654996737
[51] 0.0008815718 0.1938498269 0.4231342264 0.2246394433 1.0935372234
[56] 0.2754529125 1.0436051422 -0.4142529423 -1.0679337452 -0.0307097775
[61] -0.4276623653 0.1047945144 0.9267415032 -0.8799488661 -0.8066413232
[66] -0.3847122438 1.5594758673 -0.0945754731 -0.3533683841 0.9804855227
[71] -0.2898093323 1.7444604467 0.3427328616 -0.1024969529 -1.3161404798
[76] -1.4974152984 -1.4453274556 -0.7456323574 1.0998174901 -0.0972207469
[81] -0.4964196104 -0.5605643682 -1.3946575635 -0.6543056651 -0.8140252649
[86] 0.1497263408 -0.0477739739 1.8615898748 0.4014980011 1.7874782609
[91] 0.3161226632 -0.1647050633 1.0339559781 -0.6587475472 -1.6815590121
[96] -1.8492517376 -0.5306251435 -0.7143064995 -0.3081724728 0.1099590758
> rowSums(tmp2)
[1] 1.3553215869 0.5165942912 0.4933780300 -0.4288942730 -1.3275325428
[6] 1.0102690065 0.6704068240 -1.4768391984 -0.0357733694 -0.1491428668
[11] -0.6261669075 -0.8177415470 -0.4377280389 -0.8592072501 -0.8400311874
[16] 0.4376424152 0.7859940972 -0.1324732259 -0.2312337070 -0.7792035013
[21] -1.4867777282 -1.0714441363 0.7016955017 -0.6235126975 -0.2791327570
[26] 1.0441354188 -0.6895971316 0.4275700920 -0.7257593253 -0.0822191816
[31] -1.0461669279 0.5914295825 0.8323999197 0.0217841756 0.2328719617
[36] -0.5090058699 1.2119402580 0.9972199246 0.3570501165 -0.6493198293
[41] -0.1613807808 1.5613191429 -1.0192846522 0.5979846843 1.0224328453
[46] 0.5709403436 0.5528472163 -0.0468597748 -0.5146629924 0.6654996737
[51] 0.0008815718 0.1938498269 0.4231342264 0.2246394433 1.0935372234
[56] 0.2754529125 1.0436051422 -0.4142529423 -1.0679337452 -0.0307097775
[61] -0.4276623653 0.1047945144 0.9267415032 -0.8799488661 -0.8066413232
[66] -0.3847122438 1.5594758673 -0.0945754731 -0.3533683841 0.9804855227
[71] -0.2898093323 1.7444604467 0.3427328616 -0.1024969529 -1.3161404798
[76] -1.4974152984 -1.4453274556 -0.7456323574 1.0998174901 -0.0972207469
[81] -0.4964196104 -0.5605643682 -1.3946575635 -0.6543056651 -0.8140252649
[86] 0.1497263408 -0.0477739739 1.8615898748 0.4014980011 1.7874782609
[91] 0.3161226632 -0.1647050633 1.0339559781 -0.6587475472 -1.6815590121
[96] -1.8492517376 -0.5306251435 -0.7143064995 -0.3081724728 0.1099590758
> 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] 1.3553215869 0.5165942912 0.4933780300 -0.4288942730 -1.3275325428
[6] 1.0102690065 0.6704068240 -1.4768391984 -0.0357733694 -0.1491428668
[11] -0.6261669075 -0.8177415470 -0.4377280389 -0.8592072501 -0.8400311874
[16] 0.4376424152 0.7859940972 -0.1324732259 -0.2312337070 -0.7792035013
[21] -1.4867777282 -1.0714441363 0.7016955017 -0.6235126975 -0.2791327570
[26] 1.0441354188 -0.6895971316 0.4275700920 -0.7257593253 -0.0822191816
[31] -1.0461669279 0.5914295825 0.8323999197 0.0217841756 0.2328719617
[36] -0.5090058699 1.2119402580 0.9972199246 0.3570501165 -0.6493198293
[41] -0.1613807808 1.5613191429 -1.0192846522 0.5979846843 1.0224328453
[46] 0.5709403436 0.5528472163 -0.0468597748 -0.5146629924 0.6654996737
[51] 0.0008815718 0.1938498269 0.4231342264 0.2246394433 1.0935372234
[56] 0.2754529125 1.0436051422 -0.4142529423 -1.0679337452 -0.0307097775
[61] -0.4276623653 0.1047945144 0.9267415032 -0.8799488661 -0.8066413232
[66] -0.3847122438 1.5594758673 -0.0945754731 -0.3533683841 0.9804855227
[71] -0.2898093323 1.7444604467 0.3427328616 -0.1024969529 -1.3161404798
[76] -1.4974152984 -1.4453274556 -0.7456323574 1.0998174901 -0.0972207469
[81] -0.4964196104 -0.5605643682 -1.3946575635 -0.6543056651 -0.8140252649
[86] 0.1497263408 -0.0477739739 1.8615898748 0.4014980011 1.7874782609
[91] 0.3161226632 -0.1647050633 1.0339559781 -0.6587475472 -1.6815590121
[96] -1.8492517376 -0.5306251435 -0.7143064995 -0.3081724728 0.1099590758
> rowMin(tmp2)
[1] 1.3553215869 0.5165942912 0.4933780300 -0.4288942730 -1.3275325428
[6] 1.0102690065 0.6704068240 -1.4768391984 -0.0357733694 -0.1491428668
[11] -0.6261669075 -0.8177415470 -0.4377280389 -0.8592072501 -0.8400311874
[16] 0.4376424152 0.7859940972 -0.1324732259 -0.2312337070 -0.7792035013
[21] -1.4867777282 -1.0714441363 0.7016955017 -0.6235126975 -0.2791327570
[26] 1.0441354188 -0.6895971316 0.4275700920 -0.7257593253 -0.0822191816
[31] -1.0461669279 0.5914295825 0.8323999197 0.0217841756 0.2328719617
[36] -0.5090058699 1.2119402580 0.9972199246 0.3570501165 -0.6493198293
[41] -0.1613807808 1.5613191429 -1.0192846522 0.5979846843 1.0224328453
[46] 0.5709403436 0.5528472163 -0.0468597748 -0.5146629924 0.6654996737
[51] 0.0008815718 0.1938498269 0.4231342264 0.2246394433 1.0935372234
[56] 0.2754529125 1.0436051422 -0.4142529423 -1.0679337452 -0.0307097775
[61] -0.4276623653 0.1047945144 0.9267415032 -0.8799488661 -0.8066413232
[66] -0.3847122438 1.5594758673 -0.0945754731 -0.3533683841 0.9804855227
[71] -0.2898093323 1.7444604467 0.3427328616 -0.1024969529 -1.3161404798
[76] -1.4974152984 -1.4453274556 -0.7456323574 1.0998174901 -0.0972207469
[81] -0.4964196104 -0.5605643682 -1.3946575635 -0.6543056651 -0.8140252649
[86] 0.1497263408 -0.0477739739 1.8615898748 0.4014980011 1.7874782609
[91] 0.3161226632 -0.1647050633 1.0339559781 -0.6587475472 -1.6815590121
[96] -1.8492517376 -0.5306251435 -0.7143064995 -0.3081724728 0.1099590758
>
> colMeans(tmp2)
[1] -0.04543387
> colSums(tmp2)
[1] -4.543387
> colVars(tmp2)
[1] 0.7137603
> colSd(tmp2)
[1] 0.8448433
> colMax(tmp2)
[1] 1.86159
> colMin(tmp2)
[1] -1.849252
> colMedians(tmp2)
[1] -0.09589811
> colRanges(tmp2)
[,1]
[1,] -1.849252
[2,] 1.861590
>
> 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] 0.8410623 -2.9915744 -0.9758651 0.8505082 0.6217855 0.5502328
[7] -0.5723942 2.1694380 4.8480636 -2.1717648
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5336714
[2,] -0.5158610
[3,] -0.3403378
[4,] 0.9648380
[5,] 1.8101380
>
> rowApply(tmp,sum)
[1] 1.18848994 -3.37321711 3.53517451 -1.96710961 2.77698674 -1.00116283
[7] -0.01265218 1.08788258 0.70224866 0.23285126
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 4 5 10 9 3 2 4 5 2
[2,] 10 2 9 5 2 7 5 6 1 1
[3,] 2 3 7 3 4 2 8 3 7 4
[4,] 5 6 8 7 10 6 3 8 3 8
[5,] 6 10 6 9 3 8 7 5 4 5
[6,] 7 9 2 8 7 4 1 9 2 10
[7,] 3 1 3 1 8 10 6 1 9 3
[8,] 4 7 4 6 5 1 10 10 6 6
[9,] 8 5 1 2 6 9 9 7 10 9
[10,] 1 8 10 4 1 5 4 2 8 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.2433403 1.6167624 1.2902952 -0.1617286 5.1529367 -0.4545207
[7] 2.0909262 -2.6051265 -0.8903206 1.0948163 -0.4160645 2.5979256
[13] -2.7106449 -2.7754178 1.8350931 1.2284905 -0.3014075 2.5854042
[19] 1.5722766 3.9234574
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.0271896
[2,] -0.7939910
[3,] -0.5494153
[4,] 0.6509934
[5,] 1.4762622
>
> rowApply(tmp,sum)
[1] 5.385987 7.788901 3.060699 3.508965 -5.314738
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 13 3 6 17 4
[2,] 11 11 18 2 15
[3,] 16 10 4 5 19
[4,] 14 7 7 12 7
[5,] 5 18 11 20 20
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.6509934 0.2952786 1.1493449 0.6739745 -0.4329897 -0.5476622
[2,] -0.7939910 0.3977886 0.3964099 0.1372806 1.2779508 0.8904971
[3,] -0.5494153 1.5615060 -0.9465873 -0.3682573 0.2342893 -1.4412285
[4,] 1.4762622 -1.0507526 -0.5955685 0.1051105 2.5714197 -0.4929743
[5,] -1.0271896 0.4129418 1.2866961 -0.7098369 1.5022666 1.1368473
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.07555772 -1.7683617 0.2546979 0.3761531 1.32044470 -0.48022339
[2,] 1.63566461 0.5386587 0.4288513 -0.2114270 -0.13057095 1.24881259
[3,] 2.23016590 1.1327616 0.3514466 0.0751897 -0.76176669 2.24625524
[4,] 0.37209078 -0.5293134 -0.7353329 1.6958665 -0.83369783 -0.02779518
[5,] -2.22255283 -1.9788717 -1.1899835 -0.8409661 -0.01047375 -0.38912368
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -2.3715147 0.007271716 1.2356238 0.2371778 -0.2987448 2.3778584
[2,] 0.3302294 -1.304913009 1.2733967 1.8268247 0.3002784 0.5700834
[3,] 0.2563808 1.172148851 -2.0153071 -0.1257112 -1.0961057 0.2691873
[4,] -0.4744132 -1.906579677 0.9268771 -0.2271472 0.9579250 -0.0990776
[5,] -0.4513272 -0.743345680 0.4145026 -0.4826536 -0.1647604 -0.5326474
[,19] [,20]
[1,] 0.8663882 1.76471828
[2,] -1.1031178 0.08019398
[3,] 0.7040027 0.13174344
[4,] 0.3218547 2.05421062
[5,] 0.7831488 -0.10740890
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-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-3.23-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-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 562 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-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 -0.7401616 -0.5874095 -0.1438969 -1.06994 -0.8715083 -0.9254001 0.4272944
col8 col9 col10 col11 col12 col13 col14
row1 0.0244524 2.154605 0.4141418 -0.7289562 0.2294296 0.3819205 -0.5944203
col15 col16 col17 col18 col19 col20
row1 0.253426 -0.701349 1.21457 -2.560244 0.8434416 -0.8462005
> tmp[,"col10"]
col10
row1 0.4141418
row2 0.6604377
row3 -0.8371744
row4 -0.5436415
row5 -0.4100300
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.7401616 -0.5874095 -0.1438969 -1.0699399 -0.8715083 -0.9254001
row5 1.6409686 1.2683068 0.6641412 -0.5796682 1.4467724 -0.7069563
col7 col8 col9 col10 col11 col12 col13
row1 0.4272944 0.0244524 2.1546047 0.4141418 -0.7289562 0.2294296 0.3819205
row5 -0.3276793 0.8888086 -0.9515867 -0.4100300 -1.7429764 0.0256444 0.7325767
col14 col15 col16 col17 col18 col19 col20
row1 -0.5944203 0.2534260 -0.701349 1.21457021 -2.5602435 0.8434416 -0.8462005
row5 -0.5335327 0.4235039 1.899293 0.09026396 -0.8749482 -2.1661669 1.0294120
> tmp[,c("col6","col20")]
col6 col20
row1 -0.9254001 -0.8462005
row2 -0.6890943 2.5980301
row3 0.2131983 1.8747287
row4 0.5651600 -0.6207736
row5 -0.7069563 1.0294120
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.9254001 -0.8462005
row5 -0.7069563 1.0294120
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.57473 49.54615 49.64705 50.43388 50.98757 103.9326 48.82927 49.52994
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.26642 48.36573 51.76759 50.30139 49.56621 49.84843 51.39449 49.77583
col17 col18 col19 col20
row1 50.23878 49.57823 49.16568 101.8904
> tmp[,"col10"]
col10
row1 48.36573
row2 31.13415
row3 32.29492
row4 30.33303
row5 50.29288
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.57473 49.54615 49.64705 50.43388 50.98757 103.9326 48.82927 49.52994
row5 50.67734 48.29103 50.50547 50.56011 50.89606 104.1095 49.23392 50.74667
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.26642 48.36573 51.76759 50.30139 49.56621 49.84843 51.39449 49.77583
row5 48.97644 50.29288 49.94650 49.19401 49.51162 50.02394 48.95789 50.63880
col17 col18 col19 col20
row1 50.23878 49.57823 49.16568 101.8904
row5 49.97162 49.99593 49.97864 104.8237
> tmp[,c("col6","col20")]
col6 col20
row1 103.93263 101.89035
row2 75.31604 76.64545
row3 75.39096 75.93981
row4 74.27764 74.92286
row5 104.10946 104.82374
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 103.9326 101.8904
row5 104.1095 104.8237
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 103.9326 101.8904
row5 104.1095 104.8237
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.7433850
[2,] -0.1902363
[3,] -1.3816473
[4,] -0.2670351
[5,] 0.7891613
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.726932406 0.5635134
[2,] -1.231683787 1.4316758
[3,] -0.483798186 0.7130561
[4,] -0.933828771 1.5762865
[5,] 0.004428764 -1.5973958
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.2920597 -1.1119522
[2,] -1.4017867 -0.3639717
[3,] 0.6961889 0.3314851
[4,] -1.1066367 0.9147008
[5,] -0.4152902 1.1618630
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.2920597
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.2920597
[2,] -1.4017867
>
>
>
> 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 0.597746 -1.1631222 -0.7868561 0.7768415 -2.125649 0.4657129 0.8455369
row1 2.030242 0.5218745 -1.1624411 0.2933306 1.251656 -0.1118006 -0.6164078
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.4645391 1.3382248 0.10601032 -0.2617539 -2.351351 1.094008 0.1440177
row1 -2.8636706 -0.5398261 0.06241422 2.0618644 -2.095297 1.647240 -0.3408358
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -1.1508330 0.4176617 0.2483707 -0.9586383 2.6988618 -0.7443758
row1 -0.7002277 -0.4408351 0.0649593 0.2191479 0.3519081 0.4999523
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.7599736 -0.05420045 0.8584207 0.27014 0.5188521 1.961042 0.1139909
[,8] [,9] [,10]
row2 -0.6066908 -0.6934539 -0.5900433
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.4802051 1.949861 1.907583 -0.2711089 0.374061 0.03550773 -1.191956
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.772662 1.686802 0.00361559 -0.3316702 0.04551935 -0.9193993 1.630391
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.4234438 1.580103 0.8727558 1.030376 -2.181484 1.716032
>
>
> 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: 0xc9dd786c0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM42545166cc72"
[2] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM425433f87a1e"
[3] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM42547e196239"
[4] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM4254347fccdc"
[5] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM425432629a71"
[6] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM425467898a8e"
[7] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM425476e7a5bc"
[8] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM4254623216a0"
[9] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM4254466b94bd"
[10] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM425440f22869"
[11] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM42545a3b26ce"
[12] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM42546170cca9"
[13] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM4254348c9d39"
[14] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM42547ba62422"
[15] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM4254588e7399"
>
>
> ### 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: 0xc9dd79260>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0xc9dd79260>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0xc9dd79260>
> rowMedians(tmp)
[1] 0.562914800 -0.523635770 -0.271990087 -0.496941754 0.099412984
[6] 0.257678141 -0.186631407 0.341572782 0.456883973 0.207866486
[11] -0.092267806 -0.037505261 -0.004541341 -0.782712962 -0.173602255
[16] 0.177394934 0.335087577 0.700349142 0.129584070 0.430268390
[21] -0.126226609 0.455726341 -0.222446429 -0.315364873 -0.449976742
[26] 0.149739108 0.074740558 0.312959529 -0.231307317 0.230017697
[31] 0.143433233 0.084302482 0.212069348 -0.191558141 -0.206887755
[36] -0.111776914 0.581573319 -0.367168631 0.167257381 0.102498502
[41] -0.142564601 0.285094345 -0.123998134 0.261597310 0.598386896
[46] 0.184094876 0.133903781 -0.144011803 -0.124319736 0.056488670
[51] -0.097976412 0.673357109 -0.141212615 0.463576305 0.162695752
[56] -0.200743544 -0.022198975 -0.488023681 -0.140167622 -0.141085918
[61] -0.627627208 0.405468262 0.432335075 0.197446468 0.686827370
[66] -0.214868930 -0.615416008 -0.651831935 -0.540044118 -0.435708491
[71] 0.470700304 -0.426654095 0.434311324 0.138830318 -0.061510190
[76] 0.747865014 0.645183725 -0.375565445 0.046190436 -0.133998267
[81] -0.017169665 -0.306096646 0.084253790 -0.000267398 0.358964265
[86] 0.495919812 0.701622420 -0.035341074 0.157787982 -0.138934643
[91] 0.265661761 -0.225436903 0.292539078 0.113369944 -0.046811052
[96] 0.036946207 -0.183755368 0.688327505 -0.338458890 0.172711164
[101] 0.119800950 0.314421490 0.125373933 -0.144418753 0.064795486
[106] -0.123834659 -0.512077513 -0.309230527 -0.524411942 -0.391978874
[111] 0.328315623 0.230847110 0.466015761 0.103560035 0.046963368
[116] -0.229589823 0.507063105 0.096237842 -0.187748332 -0.354196134
[121] -0.160161801 0.195830787 0.083097330 -0.173955845 -0.614093131
[126] -0.054702302 -0.302934449 -0.125755029 0.267778193 -0.349132632
[131] 0.029518516 0.683283964 -0.169275713 0.303748688 0.304162295
[136] 0.094189357 0.101099843 -0.148398440 -0.523340996 -0.176594225
[141] -0.570155411 0.785239178 -0.062467608 0.107062680 0.060568845
[146] -0.248378973 -0.237605215 -0.562167956 0.091540453 0.169209349
[151] -0.079656703 0.089754759 -0.060928837 -0.439472192 -0.252381110
[156] -0.011380045 -0.082469870 0.016781743 0.188437539 0.086531219
[161] -0.202845377 -0.138877135 0.699616176 0.064046918 0.442888488
[166] 0.267054386 0.134475473 0.256099072 0.068600641 0.014768851
[171] -0.088928780 0.084238904 0.481913164 0.339633788 -0.287041015
[176] 0.010065862 -0.298434101 -0.175145757 -0.082578522 0.126564363
[181] -0.104526455 0.225453141 -0.190956663 0.172110575 0.175535839
[186] -0.226375046 -0.469830601 0.337390013 0.234137777 0.238655500
[191] 0.420871002 0.046490803 -0.299125861 0.158828420 0.344540631
[196] -0.271440412 0.379499628 -0.458751911 -0.311197878 0.063170248
[201] -0.065384108 0.143506632 0.049558001 -0.391902862 -0.440337875
[206] 0.285632192 -0.328262959 -0.594283280 0.911329411 0.286229296
[211] 0.736814089 0.098536630 -0.033931638 -0.896960210 0.114157335
[216] 0.277407990 -0.125080963 0.213132781 0.195153301 0.385835133
[221] 0.431666768 -0.121005963 -0.062968232 -0.233335505 0.379006203
[226] -0.717300626 -0.237796023 -0.612611546 -0.272747959 0.111396428
>
> proc.time()
user system elapsed
0.763 5.081 5.960
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.6.0 alpha (2026-04-08 r89818)
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23
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: 0x101a90510>
> .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: 0x101a90510>
> .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: 0x101a90510>
> .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: 0x101a90510>
> 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: 0xace4a4000>
> .Call("R_bm_AddColumn",P)
<pointer: 0xace4a4000>
> .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: 0xace4a4000>
> .Call("R_bm_AddColumn",P)
<pointer: 0xace4a4000>
> .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: 0xace4a4000>
> 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: 0xace4a4060>
> .Call("R_bm_AddColumn",P)
<pointer: 0xace4a4060>
> .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: 0xace4a4060>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0xace4a4060>
> .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: 0xace4a4060>
>
> .Call("R_bm_RowMode",P)
<pointer: 0xace4a4060>
> .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: 0xace4a4060>
>
> .Call("R_bm_ColMode",P)
<pointer: 0xace4a4060>
> .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: 0xace4a4060>
> 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: 0xace4a4180>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0xace4a4180>
> .Call("R_bm_AddColumn",P)
<pointer: 0xace4a4180>
> .Call("R_bm_AddColumn",P)
<pointer: 0xace4a4180>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile44f0494c1c15" "BufferedMatrixFile44f057e822e9"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile44f0494c1c15" "BufferedMatrixFile44f057e822e9"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0xace4a42a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xace4a42a0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0xace4a42a0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0xace4a42a0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0xace4a42a0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0xace4a42a0>
> .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: 0xace4a4420>
> .Call("R_bm_AddColumn",P)
<pointer: 0xace4a4420>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0xace4a4420>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0xace4a4420>
> 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: 0xace4a4540>
> .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: 0xace4a4540>
> rm(P)
>
> proc.time()
user system elapsed
0.133 0.054 0.184
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.6.0 alpha (2026-04-08 r89818)
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23
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.
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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
0.127 0.033 0.154