Ben Bolstad
| Snapshot Date: 2026-01-08 13:40 -0500 (Thu, 08 Jan 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 -0500 (Wed, 29 Oct 2025) |
| Back to Build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-01-09 12:02 -0500 (Fri, 09 Jan 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" | 4593 |
| 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 253/2332 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.75.0 (landing page) Ben Bolstad
| 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: 1.75.0 |
| 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: 2026-01-08 18:48:37 -0500 (Thu, 08 Jan 2026) |
| EndedAt: 2026-01-08 18:48:56 -0500 (Thu, 08 Jan 2026) |
| EllapsedTime: 19.3 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 Under development (unstable) (2025-11-04 r88984)
* 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 13.7.8
* using session charset: UTF-8
* 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 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 ... 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-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.75.0’
** 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/4.6-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 Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences"
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
0.130 0.049 0.177
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences"
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-3.23-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 481248 25.8 1058085 56.6 NA 633817 33.9
Vcells 891449 6.9 8388608 64.0 196608 2110969 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] "Thu Jan 8 18:48:47 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] "Thu Jan 8 18:48:47 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: 0x600001420000>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu Jan 8 18:48:48 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] "Thu Jan 8 18:48:49 2026"
>
> ColMode(tmp2)
<pointer: 0x600001420000>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.7865338 0.4636347 -0.26237848 2.09279995
[2,] 0.1322546 2.5493282 -1.62171414 0.34192722
[3,] 0.5672522 -1.1363760 -0.05732304 -0.62114685
[4,] 0.7737923 1.0767872 1.51997427 -0.05681744
> 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,] 99.7865338 0.4636347 0.26237848 2.09279995
[2,] 0.1322546 2.5493282 1.62171414 0.34192722
[3,] 0.5672522 1.1363760 0.05732304 0.62114685
[4,] 0.7737923 1.0767872 1.51997427 0.05681744
> 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,] 9.9893210 0.6809073 0.5122289 1.4466513
[2,] 0.3636682 1.5966616 1.2734654 0.5847454
[3,] 0.7531615 1.0660094 0.2394223 0.7881287
[4,] 0.8796547 1.0376836 1.2328724 0.2383641
>
> 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,] 224.67974 32.27271 30.38467 41.55931
[2,] 28.76894 43.51594 39.35637 31.18938
[3,] 33.09887 36.79647 27.45155 33.50243
[4,] 34.57034 36.45362 38.84870 27.44046
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x60000142c000>
> exp(tmp5)
<pointer: 0x60000142c000>
> log(tmp5,2)
<pointer: 0x60000142c000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.6414
> Min(tmp5)
[1] 52.72522
> mean(tmp5)
[1] 72.1597
> Sum(tmp5)
[1] 14431.94
> Var(tmp5)
[1] 856.8392
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 93.42911 69.60526 71.71329 70.78299 67.45149 68.10801 69.76931 69.20279
[9] 70.60957 70.92517
> rowSums(tmp5)
[1] 1868.582 1392.105 1434.266 1415.660 1349.030 1362.160 1395.386 1384.056
[9] 1412.191 1418.503
> rowVars(tmp5)
[1] 7814.19687 83.60543 76.04233 60.53277 74.15797 53.01257
[7] 56.69376 64.92367 90.74495 55.11560
> rowSd(tmp5)
[1] 88.397946 9.143601 8.720225 7.780281 8.611502 7.280973 7.529526
[8] 8.057522 9.526014 7.423988
> rowMax(tmp5)
[1] 467.64145 90.57274 91.38636 82.54650 87.73226 84.47920 85.07249
[8] 85.45825 88.12474 80.78173
> rowMin(tmp5)
[1] 61.67184 57.45664 57.13680 57.11372 52.72522 55.73744 55.29277 55.46226
[9] 55.29548 57.33567
>
> colMeans(tmp5)
[1] 109.30961 73.82200 70.95636 67.86219 71.58325 72.41776 69.01825
[8] 68.19558 68.75129 70.40221 68.82914 67.89228 69.32281 74.84425
[15] 70.59692 70.38150 69.05907 68.75549 71.33450 69.85956
> colSums(tmp5)
[1] 1093.0961 738.2200 709.5636 678.6219 715.8325 724.1776 690.1825
[8] 681.9558 687.5129 704.0221 688.2914 678.9228 693.2281 748.4425
[15] 705.9692 703.8150 690.5907 687.5549 713.3450 698.5956
> colVars(tmp5)
[1] 15911.22010 67.10685 126.68968 137.26812 86.53906 45.85839
[7] 95.25941 37.84245 63.85725 52.18062 61.71303 32.02100
[13] 39.96240 70.05180 52.73059 48.99956 49.10463 100.04599
[19] 137.45022 39.96516
> colSd(tmp5)
[1] 126.139685 8.191877 11.255651 11.716148 9.302637 6.771882
[7] 9.760093 6.151622 7.991073 7.223616 7.855764 5.658710
[13] 6.321582 8.369695 7.261583 6.999968 7.007470 10.002299
[19] 11.723917 6.321800
> colMax(tmp5)
[1] 467.64145 90.57274 84.33424 86.50026 90.32856 84.47920 88.12474
[8] 77.61732 80.09057 79.26888 79.15902 77.82579 77.16504 88.23931
[15] 78.62333 79.19195 79.97012 87.73226 91.38636 83.55152
> colMin(tmp5)
[1] 59.87877 62.78105 57.13680 52.72522 57.33567 62.38858 55.29277 57.95813
[9] 58.72289 62.20944 55.73744 61.19584 57.45664 64.62003 59.64909 55.46226
[17] 56.64096 55.29548 56.75564 61.67184
>
>
> ### 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] 93.42911 69.60526 71.71329 70.78299 NA 68.10801 69.76931 69.20279
[9] 70.60957 70.92517
> rowSums(tmp5)
[1] 1868.582 1392.105 1434.266 1415.660 NA 1362.160 1395.386 1384.056
[9] 1412.191 1418.503
> rowVars(tmp5)
[1] 7814.19687 83.60543 76.04233 60.53277 75.91869 53.01257
[7] 56.69376 64.92367 90.74495 55.11560
> rowSd(tmp5)
[1] 88.397946 9.143601 8.720225 7.780281 8.713133 7.280973 7.529526
[8] 8.057522 9.526014 7.423988
> rowMax(tmp5)
[1] 467.64145 90.57274 91.38636 82.54650 NA 84.47920 85.07249
[8] 85.45825 88.12474 80.78173
> rowMin(tmp5)
[1] 61.67184 57.45664 57.13680 57.11372 NA 55.73744 55.29277 55.46226
[9] 55.29548 57.33567
>
> colMeans(tmp5)
[1] 109.30961 73.82200 70.95636 67.86219 71.58325 72.41776 69.01825
[8] 68.19558 68.75129 70.40221 NA 67.89228 69.32281 74.84425
[15] 70.59692 70.38150 69.05907 68.75549 71.33450 69.85956
> colSums(tmp5)
[1] 1093.0961 738.2200 709.5636 678.6219 715.8325 724.1776 690.1825
[8] 681.9558 687.5129 704.0221 NA 678.9228 693.2281 748.4425
[15] 705.9692 703.8150 690.5907 687.5549 713.3450 698.5956
> colVars(tmp5)
[1] 15911.22010 67.10685 126.68968 137.26812 86.53906 45.85839
[7] 95.25941 37.84245 63.85725 52.18062 NA 32.02100
[13] 39.96240 70.05180 52.73059 48.99956 49.10463 100.04599
[19] 137.45022 39.96516
> colSd(tmp5)
[1] 126.139685 8.191877 11.255651 11.716148 9.302637 6.771882
[7] 9.760093 6.151622 7.991073 7.223616 NA 5.658710
[13] 6.321582 8.369695 7.261583 6.999968 7.007470 10.002299
[19] 11.723917 6.321800
> colMax(tmp5)
[1] 467.64145 90.57274 84.33424 86.50026 90.32856 84.47920 88.12474
[8] 77.61732 80.09057 79.26888 NA 77.82579 77.16504 88.23931
[15] 78.62333 79.19195 79.97012 87.73226 91.38636 83.55152
> colMin(tmp5)
[1] 59.87877 62.78105 57.13680 52.72522 57.33567 62.38858 55.29277 57.95813
[9] 58.72289 62.20944 NA 61.19584 57.45664 64.62003 59.64909 55.46226
[17] 56.64096 55.29548 56.75564 61.67184
>
> Max(tmp5,na.rm=TRUE)
[1] 467.6414
> Min(tmp5,na.rm=TRUE)
[1] 52.72522
> mean(tmp5,na.rm=TRUE)
[1] 72.21528
> Sum(tmp5,na.rm=TRUE)
[1] 14370.84
> Var(tmp5,na.rm=TRUE)
[1] 860.5458
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.42911 69.60526 71.71329 70.78299 67.78578 68.10801 69.76931 69.20279
[9] 70.60957 70.92517
> rowSums(tmp5,na.rm=TRUE)
[1] 1868.582 1392.105 1434.266 1415.660 1287.930 1362.160 1395.386 1384.056
[9] 1412.191 1418.503
> rowVars(tmp5,na.rm=TRUE)
[1] 7814.19687 83.60543 76.04233 60.53277 75.91869 53.01257
[7] 56.69376 64.92367 90.74495 55.11560
> rowSd(tmp5,na.rm=TRUE)
[1] 88.397946 9.143601 8.720225 7.780281 8.713133 7.280973 7.529526
[8] 8.057522 9.526014 7.423988
> rowMax(tmp5,na.rm=TRUE)
[1] 467.64145 90.57274 91.38636 82.54650 87.73226 84.47920 85.07249
[8] 85.45825 88.12474 80.78173
> rowMin(tmp5,na.rm=TRUE)
[1] 61.67184 57.45664 57.13680 57.11372 52.72522 55.73744 55.29277 55.46226
[9] 55.29548 57.33567
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.30961 73.82200 70.95636 67.86219 71.58325 72.41776 69.01825
[8] 68.19558 68.75129 70.40221 69.68793 67.89228 69.32281 74.84425
[15] 70.59692 70.38150 69.05907 68.75549 71.33450 69.85956
> colSums(tmp5,na.rm=TRUE)
[1] 1093.0961 738.2200 709.5636 678.6219 715.8325 724.1776 690.1825
[8] 681.9558 687.5129 704.0221 627.1914 678.9228 693.2281 748.4425
[15] 705.9692 703.8150 690.5907 687.5549 713.3450 698.5956
> colVars(tmp5,na.rm=TRUE)
[1] 15911.22010 67.10685 126.68968 137.26812 86.53906 45.85839
[7] 95.25941 37.84245 63.85725 52.18062 61.12998 32.02100
[13] 39.96240 70.05180 52.73059 48.99956 49.10463 100.04599
[19] 137.45022 39.96516
> colSd(tmp5,na.rm=TRUE)
[1] 126.139685 8.191877 11.255651 11.716148 9.302637 6.771882
[7] 9.760093 6.151622 7.991073 7.223616 7.818566 5.658710
[13] 6.321582 8.369695 7.261583 6.999968 7.007470 10.002299
[19] 11.723917 6.321800
> colMax(tmp5,na.rm=TRUE)
[1] 467.64145 90.57274 84.33424 86.50026 90.32856 84.47920 88.12474
[8] 77.61732 80.09057 79.26888 79.15902 77.82579 77.16504 88.23931
[15] 78.62333 79.19195 79.97012 87.73226 91.38636 83.55152
> colMin(tmp5,na.rm=TRUE)
[1] 59.87877 62.78105 57.13680 52.72522 57.33567 62.38858 55.29277 57.95813
[9] 58.72289 62.20944 55.73744 61.19584 57.45664 64.62003 59.64909 55.46226
[17] 56.64096 55.29548 56.75564 61.67184
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.42911 69.60526 71.71329 70.78299 NaN 68.10801 69.76931 69.20279
[9] 70.60957 70.92517
> rowSums(tmp5,na.rm=TRUE)
[1] 1868.582 1392.105 1434.266 1415.660 0.000 1362.160 1395.386 1384.056
[9] 1412.191 1418.503
> rowVars(tmp5,na.rm=TRUE)
[1] 7814.19687 83.60543 76.04233 60.53277 NA 53.01257
[7] 56.69376 64.92367 90.74495 55.11560
> rowSd(tmp5,na.rm=TRUE)
[1] 88.397946 9.143601 8.720225 7.780281 NA 7.280973 7.529526
[8] 8.057522 9.526014 7.423988
> rowMax(tmp5,na.rm=TRUE)
[1] 467.64145 90.57274 91.38636 82.54650 NA 84.47920 85.07249
[8] 85.45825 88.12474 80.78173
> rowMin(tmp5,na.rm=TRUE)
[1] 61.67184 57.45664 57.13680 57.11372 NA 55.73744 55.29277 55.46226
[9] 55.29548 57.33567
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.56974 74.71802 72.29954 69.54407 70.83360 72.22807 69.81989
[8] 68.47250 69.86555 71.07491 NaN 68.63633 69.72570 75.06466
[15] 69.78015 70.58486 67.84673 66.64696 72.12854 70.12892
> colSums(tmp5,na.rm=TRUE)
[1] 1031.1276 672.4622 650.6959 625.8966 637.5024 650.0526 628.3790
[8] 616.2525 628.7900 639.6742 0.0000 617.7270 627.5313 675.5819
[15] 628.0214 635.2637 610.6206 599.8227 649.1569 631.1603
> colVars(tmp5,na.rm=TRUE)
[1] 17588.84699 66.46296 122.22926 122.60335 91.03426 51.18588
[7] 99.93732 41.71004 57.87151 53.61234 NA 29.79552
[13] 43.13164 78.26173 51.81696 54.65924 38.70785 62.53540
[19] 147.53828 44.14458
> colSd(tmp5,na.rm=TRUE)
[1] 132.622950 8.152482 11.055734 11.072640 9.541188 7.154431
[7] 9.996865 6.458331 7.607333 7.322045 NA 5.458527
[13] 6.567469 8.846566 7.198400 7.393189 6.221563 7.907933
[19] 12.146534 6.644139
> colMax(tmp5,na.rm=TRUE)
[1] 467.64145 90.57274 84.33424 86.50026 90.32856 84.47920 88.12474
[8] 77.61732 80.09057 79.26888 -Inf 77.82579 77.16504 88.23931
[15] 78.62333 79.19195 74.42544 78.99298 91.38636 83.55152
> colMin(tmp5,na.rm=TRUE)
[1] 59.87877 62.78105 57.13680 55.98027 57.33567 62.38858 55.29277 57.95813
[9] 60.12560 62.20944 Inf 62.62680 57.45664 64.62003 59.64909 55.46226
[17] 56.64096 55.29548 56.75564 61.67184
>
>
>
>
> 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] 201.6440 310.5522 140.9476 219.1618 285.8434 273.5082 337.5901 147.2076
[9] 177.2262 331.4028
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 201.6440 310.5522 140.9476 219.1618 285.8434 273.5082 337.5901 147.2076
[9] 177.2262 331.4028
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -1.421085e-13 -5.684342e-14 -2.842171e-14 5.684342e-14 2.842171e-14
[6] -4.263256e-14 5.684342e-14 -1.421085e-14 5.684342e-14 0.000000e+00
[11] -1.136868e-13 -1.136868e-13 2.842171e-14 0.000000e+00 1.136868e-13
[16] -2.842171e-14 -2.842171e-14 -5.684342e-14 -3.126388e-13 -8.526513e-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)
+ }
1 9
8 10
1 12
6 10
4 3
5 10
3 2
6 11
4 15
5 14
4 10
4 16
7 10
9 11
2 11
1 3
6 11
6 20
5 8
2 7
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.334767
> Min(tmp)
[1] -2.241751
> mean(tmp)
[1] -0.02453594
> Sum(tmp)
[1] -2.453594
> Var(tmp)
[1] 0.7657904
>
> rowMeans(tmp)
[1] -0.02453594
> rowSums(tmp)
[1] -2.453594
> rowVars(tmp)
[1] 0.7657904
> rowSd(tmp)
[1] 0.8750945
> rowMax(tmp)
[1] 2.334767
> rowMin(tmp)
[1] -2.241751
>
> colMeans(tmp)
[1] 1.355584322 -0.687157002 -0.439291925 0.733711515 -0.362729621
[6] 0.003476405 0.984249803 -0.775368182 1.225154654 0.158794441
[11] 0.372577344 -0.721746123 -0.593343106 1.045962160 1.111896793
[16] -0.673302273 0.024528144 0.566142636 0.273315946 0.180803864
[21] 1.528649134 2.189619570 -1.211085679 0.374718950 -0.431297788
[26] -1.084301565 -0.226034792 0.563695421 -0.890778914 0.028884976
[31] 0.977223400 -0.956517254 1.386443703 0.393836661 0.493034575
[36] 1.175107973 1.014151441 -0.378362085 -0.980420708 0.598467654
[41] 0.753669973 1.049721125 1.182355027 0.595929918 -0.419333527
[46] -1.819612465 -0.205961453 -1.053828766 1.031925212 -0.202071598
[51] 0.943289683 -0.368085480 -0.576801493 -0.158972489 -0.804631134
[56] -0.902137212 -0.976506482 -0.181792351 0.756200397 -0.199798306
[61] 2.334766917 -0.345411193 0.856056571 -0.691653293 -0.813035749
[66] -0.146657869 -1.097578796 -1.579186675 0.200426089 1.476629284
[71] -0.691417587 0.054230289 0.175331206 -0.456417864 -0.378618640
[76] 1.033835000 -2.241750711 0.356722502 0.861557983 -0.170878787
[81] -0.621401333 -0.638807061 -1.189381770 -0.225821124 0.607196296
[86] 0.176788944 -1.056552682 -0.757999454 -0.234526835 0.931796761
[91] -0.227975119 -1.687506725 -0.794058901 -0.383682163 -0.170736049
[96] -0.900915874 -0.045463126 -1.035548798 0.523666736 -0.251467735
> colSums(tmp)
[1] 1.355584322 -0.687157002 -0.439291925 0.733711515 -0.362729621
[6] 0.003476405 0.984249803 -0.775368182 1.225154654 0.158794441
[11] 0.372577344 -0.721746123 -0.593343106 1.045962160 1.111896793
[16] -0.673302273 0.024528144 0.566142636 0.273315946 0.180803864
[21] 1.528649134 2.189619570 -1.211085679 0.374718950 -0.431297788
[26] -1.084301565 -0.226034792 0.563695421 -0.890778914 0.028884976
[31] 0.977223400 -0.956517254 1.386443703 0.393836661 0.493034575
[36] 1.175107973 1.014151441 -0.378362085 -0.980420708 0.598467654
[41] 0.753669973 1.049721125 1.182355027 0.595929918 -0.419333527
[46] -1.819612465 -0.205961453 -1.053828766 1.031925212 -0.202071598
[51] 0.943289683 -0.368085480 -0.576801493 -0.158972489 -0.804631134
[56] -0.902137212 -0.976506482 -0.181792351 0.756200397 -0.199798306
[61] 2.334766917 -0.345411193 0.856056571 -0.691653293 -0.813035749
[66] -0.146657869 -1.097578796 -1.579186675 0.200426089 1.476629284
[71] -0.691417587 0.054230289 0.175331206 -0.456417864 -0.378618640
[76] 1.033835000 -2.241750711 0.356722502 0.861557983 -0.170878787
[81] -0.621401333 -0.638807061 -1.189381770 -0.225821124 0.607196296
[86] 0.176788944 -1.056552682 -0.757999454 -0.234526835 0.931796761
[91] -0.227975119 -1.687506725 -0.794058901 -0.383682163 -0.170736049
[96] -0.900915874 -0.045463126 -1.035548798 0.523666736 -0.251467735
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] 1.355584322 -0.687157002 -0.439291925 0.733711515 -0.362729621
[6] 0.003476405 0.984249803 -0.775368182 1.225154654 0.158794441
[11] 0.372577344 -0.721746123 -0.593343106 1.045962160 1.111896793
[16] -0.673302273 0.024528144 0.566142636 0.273315946 0.180803864
[21] 1.528649134 2.189619570 -1.211085679 0.374718950 -0.431297788
[26] -1.084301565 -0.226034792 0.563695421 -0.890778914 0.028884976
[31] 0.977223400 -0.956517254 1.386443703 0.393836661 0.493034575
[36] 1.175107973 1.014151441 -0.378362085 -0.980420708 0.598467654
[41] 0.753669973 1.049721125 1.182355027 0.595929918 -0.419333527
[46] -1.819612465 -0.205961453 -1.053828766 1.031925212 -0.202071598
[51] 0.943289683 -0.368085480 -0.576801493 -0.158972489 -0.804631134
[56] -0.902137212 -0.976506482 -0.181792351 0.756200397 -0.199798306
[61] 2.334766917 -0.345411193 0.856056571 -0.691653293 -0.813035749
[66] -0.146657869 -1.097578796 -1.579186675 0.200426089 1.476629284
[71] -0.691417587 0.054230289 0.175331206 -0.456417864 -0.378618640
[76] 1.033835000 -2.241750711 0.356722502 0.861557983 -0.170878787
[81] -0.621401333 -0.638807061 -1.189381770 -0.225821124 0.607196296
[86] 0.176788944 -1.056552682 -0.757999454 -0.234526835 0.931796761
[91] -0.227975119 -1.687506725 -0.794058901 -0.383682163 -0.170736049
[96] -0.900915874 -0.045463126 -1.035548798 0.523666736 -0.251467735
> colMin(tmp)
[1] 1.355584322 -0.687157002 -0.439291925 0.733711515 -0.362729621
[6] 0.003476405 0.984249803 -0.775368182 1.225154654 0.158794441
[11] 0.372577344 -0.721746123 -0.593343106 1.045962160 1.111896793
[16] -0.673302273 0.024528144 0.566142636 0.273315946 0.180803864
[21] 1.528649134 2.189619570 -1.211085679 0.374718950 -0.431297788
[26] -1.084301565 -0.226034792 0.563695421 -0.890778914 0.028884976
[31] 0.977223400 -0.956517254 1.386443703 0.393836661 0.493034575
[36] 1.175107973 1.014151441 -0.378362085 -0.980420708 0.598467654
[41] 0.753669973 1.049721125 1.182355027 0.595929918 -0.419333527
[46] -1.819612465 -0.205961453 -1.053828766 1.031925212 -0.202071598
[51] 0.943289683 -0.368085480 -0.576801493 -0.158972489 -0.804631134
[56] -0.902137212 -0.976506482 -0.181792351 0.756200397 -0.199798306
[61] 2.334766917 -0.345411193 0.856056571 -0.691653293 -0.813035749
[66] -0.146657869 -1.097578796 -1.579186675 0.200426089 1.476629284
[71] -0.691417587 0.054230289 0.175331206 -0.456417864 -0.378618640
[76] 1.033835000 -2.241750711 0.356722502 0.861557983 -0.170878787
[81] -0.621401333 -0.638807061 -1.189381770 -0.225821124 0.607196296
[86] 0.176788944 -1.056552682 -0.757999454 -0.234526835 0.931796761
[91] -0.227975119 -1.687506725 -0.794058901 -0.383682163 -0.170736049
[96] -0.900915874 -0.045463126 -1.035548798 0.523666736 -0.251467735
> colMedians(tmp)
[1] 1.355584322 -0.687157002 -0.439291925 0.733711515 -0.362729621
[6] 0.003476405 0.984249803 -0.775368182 1.225154654 0.158794441
[11] 0.372577344 -0.721746123 -0.593343106 1.045962160 1.111896793
[16] -0.673302273 0.024528144 0.566142636 0.273315946 0.180803864
[21] 1.528649134 2.189619570 -1.211085679 0.374718950 -0.431297788
[26] -1.084301565 -0.226034792 0.563695421 -0.890778914 0.028884976
[31] 0.977223400 -0.956517254 1.386443703 0.393836661 0.493034575
[36] 1.175107973 1.014151441 -0.378362085 -0.980420708 0.598467654
[41] 0.753669973 1.049721125 1.182355027 0.595929918 -0.419333527
[46] -1.819612465 -0.205961453 -1.053828766 1.031925212 -0.202071598
[51] 0.943289683 -0.368085480 -0.576801493 -0.158972489 -0.804631134
[56] -0.902137212 -0.976506482 -0.181792351 0.756200397 -0.199798306
[61] 2.334766917 -0.345411193 0.856056571 -0.691653293 -0.813035749
[66] -0.146657869 -1.097578796 -1.579186675 0.200426089 1.476629284
[71] -0.691417587 0.054230289 0.175331206 -0.456417864 -0.378618640
[76] 1.033835000 -2.241750711 0.356722502 0.861557983 -0.170878787
[81] -0.621401333 -0.638807061 -1.189381770 -0.225821124 0.607196296
[86] 0.176788944 -1.056552682 -0.757999454 -0.234526835 0.931796761
[91] -0.227975119 -1.687506725 -0.794058901 -0.383682163 -0.170736049
[96] -0.900915874 -0.045463126 -1.035548798 0.523666736 -0.251467735
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.355584 -0.687157 -0.4392919 0.7337115 -0.3627296 0.003476405 0.9842498
[2,] 1.355584 -0.687157 -0.4392919 0.7337115 -0.3627296 0.003476405 0.9842498
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.7753682 1.225155 0.1587944 0.3725773 -0.7217461 -0.5933431 1.045962
[2,] -0.7753682 1.225155 0.1587944 0.3725773 -0.7217461 -0.5933431 1.045962
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.111897 -0.6733023 0.02452814 0.5661426 0.2733159 0.1808039 1.528649
[2,] 1.111897 -0.6733023 0.02452814 0.5661426 0.2733159 0.1808039 1.528649
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 2.18962 -1.211086 0.374719 -0.4312978 -1.084302 -0.2260348 0.5636954
[2,] 2.18962 -1.211086 0.374719 -0.4312978 -1.084302 -0.2260348 0.5636954
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.8907789 0.02888498 0.9772234 -0.9565173 1.386444 0.3938367 0.4930346
[2,] -0.8907789 0.02888498 0.9772234 -0.9565173 1.386444 0.3938367 0.4930346
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.175108 1.014151 -0.3783621 -0.9804207 0.5984677 0.75367 1.049721
[2,] 1.175108 1.014151 -0.3783621 -0.9804207 0.5984677 0.75367 1.049721
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 1.182355 0.5959299 -0.4193335 -1.819612 -0.2059615 -1.053829 1.031925
[2,] 1.182355 0.5959299 -0.4193335 -1.819612 -0.2059615 -1.053829 1.031925
[,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.2020716 0.9432897 -0.3680855 -0.5768015 -0.1589725 -0.8046311
[2,] -0.2020716 0.9432897 -0.3680855 -0.5768015 -0.1589725 -0.8046311
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.9021372 -0.9765065 -0.1817924 0.7562004 -0.1997983 2.334767 -0.3454112
[2,] -0.9021372 -0.9765065 -0.1817924 0.7562004 -0.1997983 2.334767 -0.3454112
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 0.8560566 -0.6916533 -0.8130357 -0.1466579 -1.097579 -1.579187 0.2004261
[2,] 0.8560566 -0.6916533 -0.8130357 -0.1466579 -1.097579 -1.579187 0.2004261
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 1.476629 -0.6914176 0.05423029 0.1753312 -0.4564179 -0.3786186 1.033835
[2,] 1.476629 -0.6914176 0.05423029 0.1753312 -0.4564179 -0.3786186 1.033835
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -2.241751 0.3567225 0.861558 -0.1708788 -0.6214013 -0.6388071 -1.189382
[2,] -2.241751 0.3567225 0.861558 -0.1708788 -0.6214013 -0.6388071 -1.189382
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.2258211 0.6071963 0.1767889 -1.056553 -0.7579995 -0.2345268 0.9317968
[2,] -0.2258211 0.6071963 0.1767889 -1.056553 -0.7579995 -0.2345268 0.9317968
[,91] [,92] [,93] [,94] [,95] [,96]
[1,] -0.2279751 -1.687507 -0.7940589 -0.3836822 -0.170736 -0.9009159
[2,] -0.2279751 -1.687507 -0.7940589 -0.3836822 -0.170736 -0.9009159
[,97] [,98] [,99] [,100]
[1,] -0.04546313 -1.035549 0.5236667 -0.2514677
[2,] -0.04546313 -1.035549 0.5236667 -0.2514677
>
>
> Max(tmp2)
[1] 1.99001
> Min(tmp2)
[1] -2.370812
> mean(tmp2)
[1] -0.1360568
> Sum(tmp2)
[1] -13.60568
> Var(tmp2)
[1] 0.813039
>
> rowMeans(tmp2)
[1] -1.323370050 1.321358513 -0.256741741 -0.487569265 -0.515470360
[6] -0.174660501 -1.834973351 -0.132276110 -1.368018961 -0.253200743
[11] -0.422150272 -0.685563874 1.061546893 -0.857315844 -0.146936992
[16] 0.122878218 1.123013794 1.211500566 -0.782977211 -0.377287063
[21] 0.422093296 -0.426380599 -1.029033157 -0.689449545 0.496626069
[26] -0.599643658 -1.108060192 1.480830424 1.023250032 -2.370812200
[31] 0.716250555 -0.350456116 -1.298459290 -0.250672256 0.543372618
[36] 1.177304845 -0.171980418 0.417142025 -2.103008307 0.124288799
[41] 0.599411164 0.791480901 1.255277861 -1.464418507 -0.477662613
[46] -0.838964859 -0.013108667 -0.580155383 -0.492246614 0.039517716
[51] -0.048232557 0.321426515 0.317517941 -0.875107977 1.531174770
[56] -1.786918215 -0.649511147 0.823538589 0.416013645 -0.560548484
[61] -0.527363410 0.033659117 0.634097574 0.017885676 1.990010461
[66] -0.092782576 -0.892830012 0.267263503 -0.191833476 -1.042607263
[71] 1.361137974 -2.031120059 1.518775934 -0.162385360 -0.457318239
[76] 0.979559676 -0.363406371 -0.291510919 -0.131205530 -0.078509634
[81] 1.173200628 0.226910036 -1.836295195 -0.806145902 -0.022904294
[86] -0.005267981 -0.170522518 0.460952276 0.555532353 -0.658879990
[91] -2.103485777 -0.517702224 -1.129207833 0.749663525 0.173390646
[96] 0.823575483 0.468340229 -0.896009638 -0.405823785 0.242014247
> rowSums(tmp2)
[1] -1.323370050 1.321358513 -0.256741741 -0.487569265 -0.515470360
[6] -0.174660501 -1.834973351 -0.132276110 -1.368018961 -0.253200743
[11] -0.422150272 -0.685563874 1.061546893 -0.857315844 -0.146936992
[16] 0.122878218 1.123013794 1.211500566 -0.782977211 -0.377287063
[21] 0.422093296 -0.426380599 -1.029033157 -0.689449545 0.496626069
[26] -0.599643658 -1.108060192 1.480830424 1.023250032 -2.370812200
[31] 0.716250555 -0.350456116 -1.298459290 -0.250672256 0.543372618
[36] 1.177304845 -0.171980418 0.417142025 -2.103008307 0.124288799
[41] 0.599411164 0.791480901 1.255277861 -1.464418507 -0.477662613
[46] -0.838964859 -0.013108667 -0.580155383 -0.492246614 0.039517716
[51] -0.048232557 0.321426515 0.317517941 -0.875107977 1.531174770
[56] -1.786918215 -0.649511147 0.823538589 0.416013645 -0.560548484
[61] -0.527363410 0.033659117 0.634097574 0.017885676 1.990010461
[66] -0.092782576 -0.892830012 0.267263503 -0.191833476 -1.042607263
[71] 1.361137974 -2.031120059 1.518775934 -0.162385360 -0.457318239
[76] 0.979559676 -0.363406371 -0.291510919 -0.131205530 -0.078509634
[81] 1.173200628 0.226910036 -1.836295195 -0.806145902 -0.022904294
[86] -0.005267981 -0.170522518 0.460952276 0.555532353 -0.658879990
[91] -2.103485777 -0.517702224 -1.129207833 0.749663525 0.173390646
[96] 0.823575483 0.468340229 -0.896009638 -0.405823785 0.242014247
> 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] -1.323370050 1.321358513 -0.256741741 -0.487569265 -0.515470360
[6] -0.174660501 -1.834973351 -0.132276110 -1.368018961 -0.253200743
[11] -0.422150272 -0.685563874 1.061546893 -0.857315844 -0.146936992
[16] 0.122878218 1.123013794 1.211500566 -0.782977211 -0.377287063
[21] 0.422093296 -0.426380599 -1.029033157 -0.689449545 0.496626069
[26] -0.599643658 -1.108060192 1.480830424 1.023250032 -2.370812200
[31] 0.716250555 -0.350456116 -1.298459290 -0.250672256 0.543372618
[36] 1.177304845 -0.171980418 0.417142025 -2.103008307 0.124288799
[41] 0.599411164 0.791480901 1.255277861 -1.464418507 -0.477662613
[46] -0.838964859 -0.013108667 -0.580155383 -0.492246614 0.039517716
[51] -0.048232557 0.321426515 0.317517941 -0.875107977 1.531174770
[56] -1.786918215 -0.649511147 0.823538589 0.416013645 -0.560548484
[61] -0.527363410 0.033659117 0.634097574 0.017885676 1.990010461
[66] -0.092782576 -0.892830012 0.267263503 -0.191833476 -1.042607263
[71] 1.361137974 -2.031120059 1.518775934 -0.162385360 -0.457318239
[76] 0.979559676 -0.363406371 -0.291510919 -0.131205530 -0.078509634
[81] 1.173200628 0.226910036 -1.836295195 -0.806145902 -0.022904294
[86] -0.005267981 -0.170522518 0.460952276 0.555532353 -0.658879990
[91] -2.103485777 -0.517702224 -1.129207833 0.749663525 0.173390646
[96] 0.823575483 0.468340229 -0.896009638 -0.405823785 0.242014247
> rowMin(tmp2)
[1] -1.323370050 1.321358513 -0.256741741 -0.487569265 -0.515470360
[6] -0.174660501 -1.834973351 -0.132276110 -1.368018961 -0.253200743
[11] -0.422150272 -0.685563874 1.061546893 -0.857315844 -0.146936992
[16] 0.122878218 1.123013794 1.211500566 -0.782977211 -0.377287063
[21] 0.422093296 -0.426380599 -1.029033157 -0.689449545 0.496626069
[26] -0.599643658 -1.108060192 1.480830424 1.023250032 -2.370812200
[31] 0.716250555 -0.350456116 -1.298459290 -0.250672256 0.543372618
[36] 1.177304845 -0.171980418 0.417142025 -2.103008307 0.124288799
[41] 0.599411164 0.791480901 1.255277861 -1.464418507 -0.477662613
[46] -0.838964859 -0.013108667 -0.580155383 -0.492246614 0.039517716
[51] -0.048232557 0.321426515 0.317517941 -0.875107977 1.531174770
[56] -1.786918215 -0.649511147 0.823538589 0.416013645 -0.560548484
[61] -0.527363410 0.033659117 0.634097574 0.017885676 1.990010461
[66] -0.092782576 -0.892830012 0.267263503 -0.191833476 -1.042607263
[71] 1.361137974 -2.031120059 1.518775934 -0.162385360 -0.457318239
[76] 0.979559676 -0.363406371 -0.291510919 -0.131205530 -0.078509634
[81] 1.173200628 0.226910036 -1.836295195 -0.806145902 -0.022904294
[86] -0.005267981 -0.170522518 0.460952276 0.555532353 -0.658879990
[91] -2.103485777 -0.517702224 -1.129207833 0.749663525 0.173390646
[96] 0.823575483 0.468340229 -0.896009638 -0.405823785 0.242014247
>
> colMeans(tmp2)
[1] -0.1360568
> colSums(tmp2)
[1] -13.60568
> colVars(tmp2)
[1] 0.813039
> colSd(tmp2)
[1] 0.9016868
> colMax(tmp2)
[1] 1.99001
> colMin(tmp2)
[1] -2.370812
> colMedians(tmp2)
[1] -0.1664539
> colRanges(tmp2)
[,1]
[1,] -2.370812
[2,] 1.990010
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.4824907 0.9564132 -2.3398187 -3.9497853 4.4501987 7.5872425
[7] -4.4627843 -0.5844514 2.1459182 -4.0201930
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5081416
[2,] -0.2569502
[3,] 0.3547767
[4,] 1.0068761
[5,] 1.6146158
>
> rowApply(tmp,sum)
[1] 0.94294934 4.77873123 6.26779431 -4.63302623 0.02549026 -3.37423671
[7] -4.49400529 -0.63370037 1.20053238 2.18470170
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 8 1 9 10 6 10 3 6 3
[2,] 5 10 3 8 8 1 3 7 2 9
[3,] 7 4 2 2 4 2 5 6 1 10
[4,] 9 3 8 3 1 4 2 4 5 4
[5,] 4 5 9 6 5 7 4 9 8 8
[6,] 6 7 5 10 2 9 9 10 10 5
[7,] 8 2 4 7 6 5 1 1 7 1
[8,] 2 9 7 4 7 10 8 2 3 2
[9,] 1 6 10 5 3 8 7 5 9 6
[10,] 3 1 6 1 9 3 6 8 4 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.9498288 3.2653678 -0.3272908 0.8061995 -0.4296121 -1.3278218
[7] 1.6144639 -1.7125389 0.7361433 1.5575935 -0.4297111 -2.9141237
[13] -1.5662703 -1.6002953 3.2406383 2.5724151 -0.3522928 1.9048037
[19] -1.3246691 0.8619650
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.6632912
[2,] -1.2373013
[3,] 0.0967000
[4,] 0.6416265
[5,] 1.2124372
>
> rowApply(tmp,sum)
[1] -0.6202974 -3.4433802 2.2475427 4.5039168 0.9373535
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 2 2 17 8 18
[2,] 12 17 19 20 3
[3,] 19 4 7 10 1
[4,] 14 15 3 18 11
[5,] 5 6 2 6 20
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.6632912 -0.1787507 1.3576957 0.08814136 -0.5147992 -0.25883951
[2,] -1.2373013 0.6452158 -0.8417083 0.26033760 -0.4704354 0.06072604
[3,] 0.6416265 1.5646149 -0.1722607 -1.02128105 -1.2354348 -0.16450387
[4,] 0.0967000 2.0181721 0.3458409 1.49671079 -0.1717608 -1.55312272
[5,] 1.2124372 -0.7838844 -1.0168584 -0.01770923 1.9628180 0.58791831
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.8141512 -0.7499019 2.6388874 -0.3184624 0.7169244 -0.5473461
[2,] 0.4031453 -0.9332348 -2.0290133 0.9306631 -0.3514036 -0.2891275
[3,] 0.1803742 -0.1261986 0.2295348 -0.2291163 0.4717651 -0.0532254
[4,] -1.4665320 -0.7463328 0.5785415 0.4190588 -0.6080847 -1.5257922
[5,] 1.6833251 0.8431292 -0.6818072 0.7554503 -0.6589122 -0.4986325
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.3157553 -1.7207392 0.8348293 0.39884007 -0.008991318 -0.41174518
[2,] 0.1509755 1.0397358 -0.4401422 0.93628255 -0.508277272 -0.30275120
[3,] -1.6894165 -0.4476811 2.3396960 0.53886642 0.443978485 1.01658606
[4,] 0.5446181 0.4036806 0.8519946 0.61516431 0.308299702 1.58793907
[5,] -0.2566921 -0.8752913 -0.3457394 0.08326179 -0.587302439 0.01477495
[,19] [,20]
[1,] -0.396313542 -0.38483138
[2,] -0.375876510 -0.09119054
[3,] 0.176819628 -0.21720098
[4,] -0.003555998 1.31237740
[5,] -0.725742728 0.24281054
>
>
> 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 : 650 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 : 563 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-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 0.8229786 -0.8866901 -0.04987604 -1.048025 -0.6938521 0.8543555 1.141337
col8 col9 col10 col11 col12 col13 col14
row1 -0.2609733 -0.1870449 0.08910216 -0.6122559 -0.8074954 0.4388133 0.8763381
col15 col16 col17 col18 col19 col20
row1 -0.7640392 -0.4533146 -1.527159 -0.2533631 -0.0673086 -1.058936
> tmp[,"col10"]
col10
row1 0.08910216
row2 -2.62957321
row3 0.47525506
row4 -0.52483979
row5 0.04774129
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.8229786 -0.8866901 -0.04987604 -1.0480250 -0.6938521 0.8543555
row5 0.8856914 0.5958636 -0.36325991 -0.4471436 0.3553685 0.5190596
col7 col8 col9 col10 col11 col12
row1 1.14133707 -0.2609733 -0.1870449 0.08910216 -0.6122559 -0.8074954
row5 -0.02641452 -1.2222916 0.9670378 0.04774129 0.9235597 -1.1987215
col13 col14 col15 col16 col17 col18
row1 0.4388133 0.8763381 -0.76403923 -0.4533146 -1.5271585 -0.25336307
row5 -1.2644492 -0.2177114 0.07093184 -0.8642855 -0.7648874 -0.02112335
col19 col20
row1 -0.0673086 -1.0589359
row5 0.6841544 -0.3949849
> tmp[,c("col6","col20")]
col6 col20
row1 0.85435552 -1.0589359
row2 -0.04208889 0.6230288
row3 0.57834075 -0.5924426
row4 3.21537111 0.3707809
row5 0.51905961 -0.3949849
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.8543555 -1.0589359
row5 0.5190596 -0.3949849
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.38534 49.14269 50.85595 49.34338 51.30834 104.9942 50.82585 50.01968
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.93172 48.54384 49.922 50.84156 48.24319 49.65106 47.57998 50.84393
col17 col18 col19 col20
row1 49.26622 51.48802 49.92749 104.0463
> tmp[,"col10"]
col10
row1 48.54384
row2 30.50610
row3 28.86308
row4 32.50258
row5 50.57616
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.38534 49.14269 50.85595 49.34338 51.30834 104.9942 50.82585 50.01968
row5 48.64267 50.22978 49.88195 50.49354 50.00609 104.8258 50.65969 49.62850
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.93172 48.54384 49.92200 50.84156 48.24319 49.65106 47.57998 50.84393
row5 49.18654 50.57616 50.59949 48.92824 51.20428 48.83891 49.58199 49.10645
col17 col18 col19 col20
row1 49.26622 51.48802 49.92749 104.0463
row5 50.01811 51.22296 49.72932 105.0106
> tmp[,c("col6","col20")]
col6 col20
row1 104.99421 104.04629
row2 74.11762 75.74948
row3 74.72406 74.78713
row4 76.07575 76.49499
row5 104.82580 105.01064
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.9942 104.0463
row5 104.8258 105.0106
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.9942 104.0463
row5 104.8258 105.0106
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.8597041
[2,] 0.7915926
[3,] -1.0986565
[4,] -0.7253784
[5,] -0.3603486
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.68033992 -0.01635449
[2,] -0.16312465 -0.64088142
[3,] 0.53906723 0.92942057
[4,] -0.07782248 -0.84520339
[5,] -0.18375374 -0.81734495
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 2.2025419 1.0392848
[2,] -1.2699121 0.1009948
[3,] 0.5814413 -2.5828272
[4,] -0.5159423 -0.1742154
[5,] -0.9921232 1.1396406
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 2.202542
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 2.202542
[2,] -1.269912
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 0.7767862 1.335366 0.4509999 0.407399831 -0.07538404 -0.7554368
row1 -0.9804347 -1.088959 -1.3415672 0.003738836 -0.15997826 -0.9366665
[,7] [,8] [,9] [,10] [,11] [,12]
row3 1.1919538 0.1567355 0.68525077 1.5963505 0.6796882 -0.1657728
row1 -0.4073118 0.5579092 -0.04513128 -0.4869133 -0.9849840 -0.6586839
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.3660121 0.2219888 1.6188392 0.6204355 -0.2769323 -1.42983 -1.111905
row1 0.3975595 -0.3108849 -0.8594769 0.3453945 -0.7831019 1.25018 1.096715
[,20]
row3 1.3248760
row1 0.1433351
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.8079009 0.6703028 0.6149054 -1.246044 0.06034215 -1.158875 1.191001
[,8] [,9] [,10]
row2 0.2309748 0.8886136 1.388592
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.5114283 -0.7360155 0.6524234 0.3344001 -0.9757098 -0.2190772 1.226969
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.6699799 0.749316 0.02944932 0.1777917 -0.4375 -0.2718026 0.6757674
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.007112609 0.3304929 -2.163362 -1.1827 1.391986 1.3628
>
>
> 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: 0x60000140c660>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM80132d2bccb2"
[2] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM8013168bd149"
[3] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM801335591b2f"
[4] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM80136d07c605"
[5] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM80131959aa2f"
[6] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM80134db400a9"
[7] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM801364977f19"
[8] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM8013161975e7"
[9] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM8013618b9c06"
[10] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM801314b07ff2"
[11] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM80134f9ff37a"
[12] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM8013e29f76d"
[13] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM801365331c5e"
[14] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM80137e8b9339"
[15] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM80137d6ec416"
>
>
> ### 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: 0x60000140c960>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x60000140c960>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x60000140c960>
> rowMedians(tmp)
[1] -2.018462e-01 1.153339e-01 -2.693358e-01 -4.941953e-01 -3.975085e-01
[6] -8.109103e-03 -2.752711e-01 -2.592829e-01 6.918379e-02 3.160913e-01
[11] -9.649463e-02 7.286765e-02 1.363905e-01 6.505602e-02 -3.725754e-01
[16] -1.938094e-01 3.113677e-01 -6.079768e-01 -3.193614e-03 -5.510757e-01
[21] 5.742280e-01 5.747343e-01 -1.006989e-02 -2.222286e-01 -3.440971e-02
[26] 6.479844e-01 -3.217029e-01 -4.804824e-02 2.485914e-01 7.847697e-02
[31] -3.452659e-01 -2.679197e-01 3.737382e-01 4.616285e-01 4.798990e-03
[36] 1.802947e-01 2.473394e-01 -2.324985e-01 6.234420e-02 1.044626e+00
[41] 6.361273e-01 -2.896541e-01 -1.819348e-01 3.564079e-01 -3.451564e-01
[46] 2.863807e-01 -2.402918e-01 4.659111e-01 1.159004e-01 -3.453526e-01
[51] -2.372923e-01 5.181750e-01 1.212958e-01 1.406948e-01 -1.989632e-01
[56] 3.842651e-02 3.987800e-01 9.100393e-02 1.973023e-01 -1.826186e-01
[61] 8.612637e-02 2.003403e-01 5.681557e-01 6.764668e-02 7.039183e-01
[66] -4.112277e-02 -2.512260e-01 -6.043665e-02 -3.781124e-01 3.832823e-02
[71] -2.577540e-01 -3.933477e-01 2.996209e-01 -1.446766e-01 -4.148516e-01
[76] -1.431351e-01 1.821387e-01 2.262335e-01 1.924835e-01 1.207794e-01
[81] -2.079169e-01 2.755083e-01 -2.908944e-02 2.111650e-01 3.453770e-01
[86] -9.557067e-02 6.358757e-02 4.569530e-01 -5.460087e-01 -5.086650e-01
[91] -2.722651e-01 -5.216636e-01 1.016369e-01 -1.124385e-01 5.863497e-02
[96] 2.412146e-01 -3.700488e-01 -6.975139e-01 3.688826e-01 -4.830497e-02
[101] 2.079522e-01 -1.786045e-01 -3.779011e-01 5.309570e-01 -4.793872e-01
[106] 1.978003e-01 1.757004e-02 1.822947e-01 2.742092e-01 -5.122400e-01
[111] -1.548413e-01 -8.693874e-02 8.904034e-03 -1.916609e-01 8.566481e-01
[116] 1.054120e-01 -4.724903e-01 -3.199360e-01 4.248885e-01 4.240182e-01
[121] 4.595794e-01 1.212746e-01 -5.960202e-01 2.160907e-01 -2.965880e-01
[126] 3.614766e-01 -5.222715e-01 -2.314885e-01 -9.539561e-02 3.421251e-01
[131] -2.190387e-01 -1.389741e-01 6.153036e-02 -1.379141e-01 -2.212421e-01
[136] 3.603823e-01 2.174493e-01 -3.501723e-01 1.092888e-01 -4.193615e-01
[141] -7.456687e-02 -5.343890e-01 -2.870735e-01 2.551771e-01 1.402326e-01
[146] 4.637365e-01 5.158824e-01 -2.179792e-01 -4.728759e-01 4.503693e-01
[151] -1.782427e-02 1.164520e-01 -4.020458e-01 2.434408e-01 -9.213236e-02
[156] 2.160335e-01 2.731813e-02 3.965133e-01 5.963053e-02 -2.357750e-02
[161] 1.049615e-01 -5.356114e-01 6.302669e-02 3.336586e-03 1.913572e-01
[166] 3.910654e-02 -4.331567e-01 4.466500e-01 1.499167e-01 -4.951389e-02
[171] -2.910365e-02 6.021461e-02 2.484180e-01 1.314520e-06 4.373288e-01
[176] 5.864788e-01 -2.014012e-02 -4.177752e-01 2.043729e-01 -2.741584e-02
[181] -4.886284e-02 2.929728e-02 -1.955283e-01 -5.588678e-01 8.688758e-02
[186] 2.768313e-01 9.561019e-01 1.162185e-01 -3.770608e-01 -8.953778e-02
[191] 4.058194e-02 -3.032566e-01 2.288409e-01 -1.186218e-01 2.068740e-02
[196] -3.909113e-01 2.850051e-01 1.884397e-01 -2.258096e-01 9.153115e-02
[201] 2.758271e-01 -3.966702e-01 -2.744646e-02 -3.183134e-01 -3.908257e-02
[206] 6.079316e-02 -1.456129e-01 -5.817476e-02 -4.076823e-01 -1.408561e-01
[211] 1.683495e-01 -2.593528e-02 2.702917e-01 -1.144591e-01 1.831099e-01
[216] -2.636088e-01 -5.257268e-03 9.044117e-02 1.287629e-01 7.649954e-02
[221] -4.314959e-01 -7.770875e-02 1.000796e-02 8.280113e-02 -2.358723e-01
[226] -4.481553e-01 -3.277097e-01 -1.602415e-01 -3.525591e-01 6.188587e-01
>
> proc.time()
user system elapsed
0.715 3.657 4.832
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences"
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: 0x600001404000>
> .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: 0x600001404000>
> .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: 0x600001404000>
> .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: 0x600001404000>
> 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: 0x60000143c000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000143c000>
> .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: 0x60000143c000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000143c000>
> .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: 0x60000143c000>
> 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: 0x600001430000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001430000>
> .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: 0x600001430000>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600001430000>
> .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: 0x600001430000>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600001430000>
> .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: 0x600001430000>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600001430000>
> .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: 0x600001430000>
> 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: 0x600001428000>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600001428000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001428000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001428000>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile85c0120082b3" "BufferedMatrixFile85c05f84bf00"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile85c0120082b3" "BufferedMatrixFile85c05f84bf00"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001428240>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001428240>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600001428240>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600001428240>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600001428240>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600001428240>
> .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: 0x600001428420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001428420>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600001428420>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600001428420>
> 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: 0x600001428600>
> .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: 0x600001428600>
> rm(P)
>
> proc.time()
user system elapsed
0.124 0.047 0.172
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences"
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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.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.131 0.033 0.162