Ben Bolstad
| Snapshot Date: 2025-11-10 13:45 -0500 (Mon, 10 Nov 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_22 |
| git_last_commit: d2ce144 |
| git_last_commit_date: 2025-10-29 09:58:55 -0500 (Wed, 29 Oct 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-11-11 12:03 -0500 (Tue, 11 Nov 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" | 4902 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4638 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 257/2361 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.74.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.74.0 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.74.0.tar.gz |
| StartedAt: 2025-11-10 19:03:35 -0500 (Mon, 10 Nov 2025) |
| EndedAt: 2025-11-10 19:03:52 -0500 (Mon, 10 Nov 2025) |
| EllapsedTime: 16.2 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
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###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.74.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.1 Patched (2025-09-10 r88807)
* using platform: aarch64-apple-darwin20
* R was compiled by
Apple clang version 16.0.0 (clang-1600.0.26.6)
GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.7
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.74.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... WARNING
Found the following significant warnings:
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
* used SDK: ‘MacOSX11.3.1.sdk’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 WARNING, 2 NOTEs
See
‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
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###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.74.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
using SDK: ‘MacOSX11.3.1.sdk’
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch arm64 -std=gnu2x -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/arm64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R
installing to /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.109 0.036 0.148
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
Ncells 480828 25.7 1056614 56.5 NA 634360 33.9
Vcells 891019 6.8 8388608 64.0 196608 2109493 16.1
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Mon Nov 10 19:03:44 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Mon Nov 10 19:03:44 2025"
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
>
>
> RowMode(tmp2)
<pointer: 0x6000035c80c0>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Mon Nov 10 19:03:45 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Mon Nov 10 19:03:46 2025"
>
> ColMode(tmp2)
<pointer: 0x6000035c80c0>
>
>
>
> ### 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,] 101.1246879 1.7654056 0.6811077 -1.382787
[2,] -0.5870358 -0.9765529 0.4172592 -2.451051
[3,] -0.5475985 -2.8218285 1.9728476 -1.395394
[4,] 2.1113646 -0.5230369 -0.6449881 1.018216
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 101.1246879 1.7654056 0.6811077 1.382787
[2,] 0.5870358 0.9765529 0.4172592 2.451051
[3,] 0.5475985 2.8218285 1.9728476 1.395394
[4,] 2.1113646 0.5230369 0.6449881 1.018216
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0560772 1.3286857 0.8252925 1.175920
[2,] 0.7661826 0.9882069 0.6459560 1.565583
[3,] 0.7399990 1.6798299 1.4045809 1.181268
[4,] 1.4530535 0.7232129 0.8031115 1.009067
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 226.68546 40.05226 33.93403 38.14199
[2,] 33.24886 35.85862 31.87682 43.10688
[3,] 32.94759 44.62013 41.01866 38.20807
[4,] 41.64190 32.75517 33.67610 36.10888
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000035c8120>
> exp(tmp5)
<pointer: 0x6000035c8120>
> log(tmp5,2)
<pointer: 0x6000035c8120>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.8161
> Min(tmp5)
[1] 52.61702
> mean(tmp5)
[1] 73.07037
> Sum(tmp5)
[1] 14614.07
> Var(tmp5)
[1] 883.1421
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.57201 70.77566 71.52533 73.52774 71.56524 72.90456 71.02088 71.03092
[9] 69.13247 68.64891
> rowSums(tmp5)
[1] 1811.440 1415.513 1430.507 1470.555 1431.305 1458.091 1420.418 1420.618
[9] 1382.649 1372.978
> rowVars(tmp5)
[1] 8103.01072 85.33108 131.68136 106.69430 97.92078 91.98493
[7] 55.03607 78.53602 76.83772 43.89876
> rowSd(tmp5)
[1] 90.016725 9.237482 11.475250 10.329293 9.895493 9.590877 7.418630
[8] 8.862055 8.765712 6.625614
> rowMax(tmp5)
[1] 471.81608 89.72133 92.87095 98.92148 93.97369 93.39609 81.21436
[8] 81.26180 94.07936 81.68429
> rowMin(tmp5)
[1] 56.71894 53.29524 54.51449 56.21309 55.54392 56.38443 56.64053 52.61702
[9] 54.88519 53.77206
>
> colMeans(tmp5)
[1] 115.37987 70.31566 70.93180 75.75157 75.24997 67.94856 73.15363
[8] 67.98271 68.25672 70.19027 74.83669 72.22095 68.78712 72.83889
[15] 67.56159 64.15615 70.54599 68.63093 75.73083 70.93756
> colSums(tmp5)
[1] 1153.7987 703.1566 709.3180 757.5157 752.4997 679.4856 731.5363
[8] 679.8271 682.5672 701.9027 748.3669 722.2095 687.8712 728.3889
[15] 675.6159 641.5615 705.4599 686.3093 757.3083 709.3756
> colVars(tmp5)
[1] 15778.27054 143.36036 46.96803 74.50411 117.99538 93.94187
[7] 62.67761 47.89460 74.22249 49.95735 61.80124 43.65371
[13] 54.11620 103.12546 73.35226 33.62314 153.02764 28.73086
[19] 126.27893 62.47853
> colSd(tmp5)
[1] 125.611586 11.973319 6.853323 8.631576 10.862568 9.692362
[7] 7.916919 6.920592 8.615248 7.068051 7.861377 6.607095
[13] 7.356371 10.155071 8.564593 5.798547 12.370434 5.360117
[19] 11.237390 7.904336
> colMax(tmp5)
[1] 471.81608 92.87095 85.37496 89.72133 98.92148 81.68429 83.11981
[8] 74.82624 78.62130 79.57895 83.27176 81.74788 79.57124 85.78910
[15] 80.51745 73.92047 94.07936 79.98577 93.97369 83.60731
> colMin(tmp5)
[1] 58.45079 56.64053 62.48977 61.07421 62.12343 53.29524 54.88519 56.21309
[9] 54.51449 60.14389 60.90584 62.58420 58.09118 52.61702 53.77206 55.54392
[17] 56.38443 59.62313 59.75442 58.89463
>
>
> ### 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] 90.57201 NA 71.52533 73.52774 71.56524 72.90456 71.02088 71.03092
[9] 69.13247 68.64891
> rowSums(tmp5)
[1] 1811.440 NA 1430.507 1470.555 1431.305 1458.091 1420.418 1420.618
[9] 1382.649 1372.978
> rowVars(tmp5)
[1] 8103.01072 83.74971 131.68136 106.69430 97.92078 91.98493
[7] 55.03607 78.53602 76.83772 43.89876
> rowSd(tmp5)
[1] 90.016725 9.151487 11.475250 10.329293 9.895493 9.590877 7.418630
[8] 8.862055 8.765712 6.625614
> rowMax(tmp5)
[1] 471.81608 NA 92.87095 98.92148 93.97369 93.39609 81.21436
[8] 81.26180 94.07936 81.68429
> rowMin(tmp5)
[1] 56.71894 NA 54.51449 56.21309 55.54392 56.38443 56.64053 52.61702
[9] 54.88519 53.77206
>
> colMeans(tmp5)
[1] 115.37987 70.31566 70.93180 75.75157 75.24997 67.94856 73.15363
[8] 67.98271 68.25672 70.19027 74.83669 72.22095 68.78712 72.83889
[15] 67.56159 64.15615 NA 68.63093 75.73083 70.93756
> colSums(tmp5)
[1] 1153.7987 703.1566 709.3180 757.5157 752.4997 679.4856 731.5363
[8] 679.8271 682.5672 701.9027 748.3669 722.2095 687.8712 728.3889
[15] 675.6159 641.5615 NA 686.3093 757.3083 709.3756
> colVars(tmp5)
[1] 15778.27054 143.36036 46.96803 74.50411 117.99538 93.94187
[7] 62.67761 47.89460 74.22249 49.95735 61.80124 43.65371
[13] 54.11620 103.12546 73.35226 33.62314 NA 28.73086
[19] 126.27893 62.47853
> colSd(tmp5)
[1] 125.611586 11.973319 6.853323 8.631576 10.862568 9.692362
[7] 7.916919 6.920592 8.615248 7.068051 7.861377 6.607095
[13] 7.356371 10.155071 8.564593 5.798547 NA 5.360117
[19] 11.237390 7.904336
> colMax(tmp5)
[1] 471.81608 92.87095 85.37496 89.72133 98.92148 81.68429 83.11981
[8] 74.82624 78.62130 79.57895 83.27176 81.74788 79.57124 85.78910
[15] 80.51745 73.92047 NA 79.98577 93.97369 83.60731
> colMin(tmp5)
[1] 58.45079 56.64053 62.48977 61.07421 62.12343 53.29524 54.88519 56.21309
[9] 54.51449 60.14389 60.90584 62.58420 58.09118 52.61702 53.77206 55.54392
[17] NA 59.62313 59.75442 58.89463
>
> Max(tmp5,na.rm=TRUE)
[1] 471.8161
> Min(tmp5,na.rm=TRUE)
[1] 52.61702
> mean(tmp5,na.rm=TRUE)
[1] 73.13415
> Sum(tmp5,na.rm=TRUE)
[1] 14553.7
> Var(tmp5,na.rm=TRUE)
[1] 886.7847
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.57201 71.32289 71.52533 73.52774 71.56524 72.90456 71.02088 71.03092
[9] 69.13247 68.64891
> rowSums(tmp5,na.rm=TRUE)
[1] 1811.440 1355.135 1430.507 1470.555 1431.305 1458.091 1420.418 1420.618
[9] 1382.649 1372.978
> rowVars(tmp5,na.rm=TRUE)
[1] 8103.01072 83.74971 131.68136 106.69430 97.92078 91.98493
[7] 55.03607 78.53602 76.83772 43.89876
> rowSd(tmp5,na.rm=TRUE)
[1] 90.016725 9.151487 11.475250 10.329293 9.895493 9.590877 7.418630
[8] 8.862055 8.765712 6.625614
> rowMax(tmp5,na.rm=TRUE)
[1] 471.81608 89.72133 92.87095 98.92148 93.97369 93.39609 81.21436
[8] 81.26180 94.07936 81.68429
> rowMin(tmp5,na.rm=TRUE)
[1] 56.71894 53.29524 54.51449 56.21309 55.54392 56.38443 56.64053 52.61702
[9] 54.88519 53.77206
>
> colMeans(tmp5,na.rm=TRUE)
[1] 115.37987 70.31566 70.93180 75.75157 75.24997 67.94856 73.15363
[8] 67.98271 68.25672 70.19027 74.83669 72.22095 68.78712 72.83889
[15] 67.56159 64.15615 71.67574 68.63093 75.73083 70.93756
> colSums(tmp5,na.rm=TRUE)
[1] 1153.7987 703.1566 709.3180 757.5157 752.4997 679.4856 731.5363
[8] 679.8271 682.5672 701.9027 748.3669 722.2095 687.8712 728.3889
[15] 675.6159 641.5615 645.0817 686.3093 757.3083 709.3756
> colVars(tmp5,na.rm=TRUE)
[1] 15778.27054 143.36036 46.96803 74.50411 117.99538 93.94187
[7] 62.67761 47.89460 74.22249 49.95735 61.80124 43.65371
[13] 54.11620 103.12546 73.35226 33.62314 157.79737 28.73086
[19] 126.27893 62.47853
> colSd(tmp5,na.rm=TRUE)
[1] 125.611586 11.973319 6.853323 8.631576 10.862568 9.692362
[7] 7.916919 6.920592 8.615248 7.068051 7.861377 6.607095
[13] 7.356371 10.155071 8.564593 5.798547 12.561742 5.360117
[19] 11.237390 7.904336
> colMax(tmp5,na.rm=TRUE)
[1] 471.81608 92.87095 85.37496 89.72133 98.92148 81.68429 83.11981
[8] 74.82624 78.62130 79.57895 83.27176 81.74788 79.57124 85.78910
[15] 80.51745 73.92047 94.07936 79.98577 93.97369 83.60731
> colMin(tmp5,na.rm=TRUE)
[1] 58.45079 56.64053 62.48977 61.07421 62.12343 53.29524 54.88519 56.21309
[9] 54.51449 60.14389 60.90584 62.58420 58.09118 52.61702 53.77206 55.54392
[17] 56.38443 59.62313 59.75442 58.89463
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.57201 NaN 71.52533 73.52774 71.56524 72.90456 71.02088 71.03092
[9] 69.13247 68.64891
> rowSums(tmp5,na.rm=TRUE)
[1] 1811.440 0.000 1430.507 1470.555 1431.305 1458.091 1420.418 1420.618
[9] 1382.649 1372.978
> rowVars(tmp5,na.rm=TRUE)
[1] 8103.01072 NA 131.68136 106.69430 97.92078 91.98493
[7] 55.03607 78.53602 76.83772 43.89876
> rowSd(tmp5,na.rm=TRUE)
[1] 90.016725 NA 11.475250 10.329293 9.895493 9.590877 7.418630
[8] 8.862055 8.765712 6.625614
> rowMax(tmp5,na.rm=TRUE)
[1] 471.81608 NA 92.87095 98.92148 93.97369 93.39609 81.21436
[8] 81.26180 94.07936 81.68429
> rowMin(tmp5,na.rm=TRUE)
[1] 56.71894 NA 54.51449 56.21309 55.54392 56.38443 56.64053 52.61702
[9] 54.88519 53.77206
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 120.51061 69.83573 71.44117 74.19938 75.95465 69.57671 72.04628
[8] 67.45082 69.42300 69.79162 74.49815 71.16240 68.73231 72.03688
[15] 67.42300 64.75164 NaN 68.94326 76.69190 70.36153
> colSums(tmp5,na.rm=TRUE)
[1] 1084.5955 628.5216 642.9706 667.7944 683.5919 626.1904 648.4165
[8] 607.0574 624.8070 628.1246 670.4834 640.4616 618.5908 648.3319
[15] 606.8070 582.7648 0.0000 620.4893 690.2271 633.2538
> colVars(tmp5,na.rm=TRUE)
[1] 17454.40306 158.68917 49.92008 56.71239 127.15838 75.86240
[7] 56.71722 50.69871 68.19775 54.41418 68.23709 36.50453
[13] 60.84693 108.77993 82.30522 33.83664 NA 31.22477
[19] 131.67255 66.55555
> colSd(tmp5,na.rm=TRUE)
[1] 132.115113 12.597189 7.065414 7.530763 11.276452 8.709902
[7] 7.531084 7.120302 8.258193 7.376597 8.260574 6.041898
[13] 7.800444 10.429762 9.072222 5.816927 NA 5.587913
[19] 11.474866 8.158159
> colMax(tmp5,na.rm=TRUE)
[1] 471.81608 92.87095 85.37496 81.26180 98.92148 81.68429 81.21436
[8] 74.82624 78.62130 79.57895 83.27176 78.83859 79.57124 85.78910
[15] 80.51745 73.92047 -Inf 79.98577 93.97369 83.60731
> colMin(tmp5,na.rm=TRUE)
[1] 58.45079 56.64053 62.48977 61.07421 62.12343 56.71894 54.88519 56.21309
[9] 54.51449 60.14389 60.90584 62.58420 58.09118 52.61702 53.77206 55.54392
[17] Inf 59.62313 59.75442 58.89463
>
>
>
>
> 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] 170.04940 158.49410 95.22355 172.92414 306.19065 218.71173 324.25531
[8] 301.93691 284.74435 169.74065
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 170.04940 158.49410 95.22355 172.92414 306.19065 218.71173 324.25531
[8] 301.93691 284.74435 169.74065
>
>
>
> 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] 0.000000e+00 1.136868e-13 0.000000e+00 -1.705303e-13 -2.842171e-14
[6] 5.684342e-14 1.705303e-13 5.684342e-14 -2.842171e-14 8.526513e-14
[11] 2.842171e-14 5.684342e-14 3.979039e-13 -2.842171e-13 0.000000e+00
[16] 0.000000e+00 -1.136868e-13 -1.136868e-13 0.000000e+00 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## 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 1
3 1
10 4
4 5
8 3
9 15
9 17
1 20
2 8
4 14
8 10
6 17
10 20
7 4
7 11
7 7
1 4
1 7
10 8
3 1
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] 2.169247
> Min(tmp)
[1] -3.86989
> mean(tmp)
[1] -0.1116466
> Sum(tmp)
[1] -11.16466
> Var(tmp)
[1] 1.133965
>
> rowMeans(tmp)
[1] -0.1116466
> rowSums(tmp)
[1] -11.16466
> rowVars(tmp)
[1] 1.133965
> rowSd(tmp)
[1] 1.064878
> rowMax(tmp)
[1] 2.169247
> rowMin(tmp)
[1] -3.86989
>
> colMeans(tmp)
[1] 0.84676046 0.13137870 1.25130005 -0.47105213 -0.35854531 -2.11047551
[7] 0.03467971 0.60051296 -0.72334861 0.01236006 -1.24522015 0.06673188
[13] 0.09652768 -0.15472099 -2.48497763 0.51536862 -3.86989004 0.51560900
[19] -1.63677831 0.27029064 -0.64559561 -0.24776701 -1.11037262 -1.26340962
[25] -1.31299310 1.20700168 1.88314417 -0.63214735 0.15960421 1.22028702
[31] 0.38505511 0.42972264 0.57090060 0.92870607 0.41315835 -0.29415152
[37] 0.23516790 -0.35799340 0.20188218 0.10755018 0.72909407 0.92970698
[43] -0.34726411 -0.84844902 2.16924676 -1.75737517 0.32677707 -2.58773641
[49] -0.57405874 -1.30073204 0.89043375 1.02415691 -0.06040200 0.04391361
[55] -0.30782054 -0.93849481 0.13932967 -0.19231555 0.93750875 0.28005698
[61] -0.79651413 1.61274350 0.86949882 -2.06394326 -1.86700323 0.16246534
[67] 1.39448271 0.77889958 -0.17278844 -0.68976989 -1.06693668 -0.16069711
[73] 0.38696701 1.21882582 0.53119999 1.22740443 -0.24234921 -0.51887960
[79] -1.08936311 0.95643591 0.55565194 -0.54247791 1.39701733 0.16533767
[85] -0.02614734 -1.14390983 1.18703527 0.10267792 -0.87617934 -1.66101361
[91] 0.09542626 0.32306472 -1.31011490 -0.18352245 -0.87606774 -2.38471684
[97] 0.32321500 1.90984090 -0.28371192 -0.12657827
> colSums(tmp)
[1] 0.84676046 0.13137870 1.25130005 -0.47105213 -0.35854531 -2.11047551
[7] 0.03467971 0.60051296 -0.72334861 0.01236006 -1.24522015 0.06673188
[13] 0.09652768 -0.15472099 -2.48497763 0.51536862 -3.86989004 0.51560900
[19] -1.63677831 0.27029064 -0.64559561 -0.24776701 -1.11037262 -1.26340962
[25] -1.31299310 1.20700168 1.88314417 -0.63214735 0.15960421 1.22028702
[31] 0.38505511 0.42972264 0.57090060 0.92870607 0.41315835 -0.29415152
[37] 0.23516790 -0.35799340 0.20188218 0.10755018 0.72909407 0.92970698
[43] -0.34726411 -0.84844902 2.16924676 -1.75737517 0.32677707 -2.58773641
[49] -0.57405874 -1.30073204 0.89043375 1.02415691 -0.06040200 0.04391361
[55] -0.30782054 -0.93849481 0.13932967 -0.19231555 0.93750875 0.28005698
[61] -0.79651413 1.61274350 0.86949882 -2.06394326 -1.86700323 0.16246534
[67] 1.39448271 0.77889958 -0.17278844 -0.68976989 -1.06693668 -0.16069711
[73] 0.38696701 1.21882582 0.53119999 1.22740443 -0.24234921 -0.51887960
[79] -1.08936311 0.95643591 0.55565194 -0.54247791 1.39701733 0.16533767
[85] -0.02614734 -1.14390983 1.18703527 0.10267792 -0.87617934 -1.66101361
[91] 0.09542626 0.32306472 -1.31011490 -0.18352245 -0.87606774 -2.38471684
[97] 0.32321500 1.90984090 -0.28371192 -0.12657827
> 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] 0.84676046 0.13137870 1.25130005 -0.47105213 -0.35854531 -2.11047551
[7] 0.03467971 0.60051296 -0.72334861 0.01236006 -1.24522015 0.06673188
[13] 0.09652768 -0.15472099 -2.48497763 0.51536862 -3.86989004 0.51560900
[19] -1.63677831 0.27029064 -0.64559561 -0.24776701 -1.11037262 -1.26340962
[25] -1.31299310 1.20700168 1.88314417 -0.63214735 0.15960421 1.22028702
[31] 0.38505511 0.42972264 0.57090060 0.92870607 0.41315835 -0.29415152
[37] 0.23516790 -0.35799340 0.20188218 0.10755018 0.72909407 0.92970698
[43] -0.34726411 -0.84844902 2.16924676 -1.75737517 0.32677707 -2.58773641
[49] -0.57405874 -1.30073204 0.89043375 1.02415691 -0.06040200 0.04391361
[55] -0.30782054 -0.93849481 0.13932967 -0.19231555 0.93750875 0.28005698
[61] -0.79651413 1.61274350 0.86949882 -2.06394326 -1.86700323 0.16246534
[67] 1.39448271 0.77889958 -0.17278844 -0.68976989 -1.06693668 -0.16069711
[73] 0.38696701 1.21882582 0.53119999 1.22740443 -0.24234921 -0.51887960
[79] -1.08936311 0.95643591 0.55565194 -0.54247791 1.39701733 0.16533767
[85] -0.02614734 -1.14390983 1.18703527 0.10267792 -0.87617934 -1.66101361
[91] 0.09542626 0.32306472 -1.31011490 -0.18352245 -0.87606774 -2.38471684
[97] 0.32321500 1.90984090 -0.28371192 -0.12657827
> colMin(tmp)
[1] 0.84676046 0.13137870 1.25130005 -0.47105213 -0.35854531 -2.11047551
[7] 0.03467971 0.60051296 -0.72334861 0.01236006 -1.24522015 0.06673188
[13] 0.09652768 -0.15472099 -2.48497763 0.51536862 -3.86989004 0.51560900
[19] -1.63677831 0.27029064 -0.64559561 -0.24776701 -1.11037262 -1.26340962
[25] -1.31299310 1.20700168 1.88314417 -0.63214735 0.15960421 1.22028702
[31] 0.38505511 0.42972264 0.57090060 0.92870607 0.41315835 -0.29415152
[37] 0.23516790 -0.35799340 0.20188218 0.10755018 0.72909407 0.92970698
[43] -0.34726411 -0.84844902 2.16924676 -1.75737517 0.32677707 -2.58773641
[49] -0.57405874 -1.30073204 0.89043375 1.02415691 -0.06040200 0.04391361
[55] -0.30782054 -0.93849481 0.13932967 -0.19231555 0.93750875 0.28005698
[61] -0.79651413 1.61274350 0.86949882 -2.06394326 -1.86700323 0.16246534
[67] 1.39448271 0.77889958 -0.17278844 -0.68976989 -1.06693668 -0.16069711
[73] 0.38696701 1.21882582 0.53119999 1.22740443 -0.24234921 -0.51887960
[79] -1.08936311 0.95643591 0.55565194 -0.54247791 1.39701733 0.16533767
[85] -0.02614734 -1.14390983 1.18703527 0.10267792 -0.87617934 -1.66101361
[91] 0.09542626 0.32306472 -1.31011490 -0.18352245 -0.87606774 -2.38471684
[97] 0.32321500 1.90984090 -0.28371192 -0.12657827
> colMedians(tmp)
[1] 0.84676046 0.13137870 1.25130005 -0.47105213 -0.35854531 -2.11047551
[7] 0.03467971 0.60051296 -0.72334861 0.01236006 -1.24522015 0.06673188
[13] 0.09652768 -0.15472099 -2.48497763 0.51536862 -3.86989004 0.51560900
[19] -1.63677831 0.27029064 -0.64559561 -0.24776701 -1.11037262 -1.26340962
[25] -1.31299310 1.20700168 1.88314417 -0.63214735 0.15960421 1.22028702
[31] 0.38505511 0.42972264 0.57090060 0.92870607 0.41315835 -0.29415152
[37] 0.23516790 -0.35799340 0.20188218 0.10755018 0.72909407 0.92970698
[43] -0.34726411 -0.84844902 2.16924676 -1.75737517 0.32677707 -2.58773641
[49] -0.57405874 -1.30073204 0.89043375 1.02415691 -0.06040200 0.04391361
[55] -0.30782054 -0.93849481 0.13932967 -0.19231555 0.93750875 0.28005698
[61] -0.79651413 1.61274350 0.86949882 -2.06394326 -1.86700323 0.16246534
[67] 1.39448271 0.77889958 -0.17278844 -0.68976989 -1.06693668 -0.16069711
[73] 0.38696701 1.21882582 0.53119999 1.22740443 -0.24234921 -0.51887960
[79] -1.08936311 0.95643591 0.55565194 -0.54247791 1.39701733 0.16533767
[85] -0.02614734 -1.14390983 1.18703527 0.10267792 -0.87617934 -1.66101361
[91] 0.09542626 0.32306472 -1.31011490 -0.18352245 -0.87606774 -2.38471684
[97] 0.32321500 1.90984090 -0.28371192 -0.12657827
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.8467605 0.1313787 1.2513 -0.4710521 -0.3585453 -2.110476 0.03467971
[2,] 0.8467605 0.1313787 1.2513 -0.4710521 -0.3585453 -2.110476 0.03467971
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.600513 -0.7233486 0.01236006 -1.24522 0.06673188 0.09652768 -0.154721
[2,] 0.600513 -0.7233486 0.01236006 -1.24522 0.06673188 0.09652768 -0.154721
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -2.484978 0.5153686 -3.86989 0.515609 -1.636778 0.2702906 -0.6455956
[2,] -2.484978 0.5153686 -3.86989 0.515609 -1.636778 0.2702906 -0.6455956
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.247767 -1.110373 -1.26341 -1.312993 1.207002 1.883144 -0.6321473
[2,] -0.247767 -1.110373 -1.26341 -1.312993 1.207002 1.883144 -0.6321473
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.1596042 1.220287 0.3850551 0.4297226 0.5709006 0.9287061 0.4131583
[2,] 0.1596042 1.220287 0.3850551 0.4297226 0.5709006 0.9287061 0.4131583
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.2941515 0.2351679 -0.3579934 0.2018822 0.1075502 0.7290941 0.929707
[2,] -0.2941515 0.2351679 -0.3579934 0.2018822 0.1075502 0.7290941 0.929707
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.3472641 -0.848449 2.169247 -1.757375 0.3267771 -2.587736 -0.5740587
[2,] -0.3472641 -0.848449 2.169247 -1.757375 0.3267771 -2.587736 -0.5740587
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -1.300732 0.8904338 1.024157 -0.060402 0.04391361 -0.3078205 -0.9384948
[2,] -1.300732 0.8904338 1.024157 -0.060402 0.04391361 -0.3078205 -0.9384948
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.1393297 -0.1923156 0.9375088 0.280057 -0.7965141 1.612744 0.8694988
[2,] 0.1393297 -0.1923156 0.9375088 0.280057 -0.7965141 1.612744 0.8694988
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -2.063943 -1.867003 0.1624653 1.394483 0.7788996 -0.1727884 -0.6897699
[2,] -2.063943 -1.867003 0.1624653 1.394483 0.7788996 -0.1727884 -0.6897699
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -1.066937 -0.1606971 0.386967 1.218826 0.5312 1.227404 -0.2423492
[2,] -1.066937 -0.1606971 0.386967 1.218826 0.5312 1.227404 -0.2423492
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.5188796 -1.089363 0.9564359 0.5556519 -0.5424779 1.397017 0.1653377
[2,] -0.5188796 -1.089363 0.9564359 0.5556519 -0.5424779 1.397017 0.1653377
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.02614734 -1.14391 1.187035 0.1026779 -0.8761793 -1.661014 0.09542626
[2,] -0.02614734 -1.14391 1.187035 0.1026779 -0.8761793 -1.661014 0.09542626
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.3230647 -1.310115 -0.1835224 -0.8760677 -2.384717 0.323215 1.909841
[2,] 0.3230647 -1.310115 -0.1835224 -0.8760677 -2.384717 0.323215 1.909841
[,99] [,100]
[1,] -0.2837119 -0.1265783
[2,] -0.2837119 -0.1265783
>
>
> Max(tmp2)
[1] 2.549296
> Min(tmp2)
[1] -1.928099
> mean(tmp2)
[1] 0.1420893
> Sum(tmp2)
[1] 14.20893
> Var(tmp2)
[1] 0.889906
>
> rowMeans(tmp2)
[1] -1.219333348 -0.294084326 -0.635530984 0.221130008 -0.776175541
[6] 0.029652001 0.782665777 0.942963746 0.135536293 0.026550698
[11] 0.855782068 0.006188576 0.515807404 -0.409054381 0.633201529
[16] 0.912724572 1.760458669 -0.288677882 2.426158060 -0.157546981
[21] -0.199825161 -0.954161855 -0.233106462 -1.336235693 0.671323704
[26] -0.578891632 -0.209157034 0.672403696 0.890346975 0.745442906
[31] 1.109709560 -1.015712652 0.708656011 0.992373033 0.428698403
[36] -1.011755586 -0.354878357 -0.708406051 -0.125063935 0.097463748
[41] -0.361281187 -0.823202037 0.211204111 0.536691173 0.917784997
[46] -1.409437874 0.888844846 -0.308522033 0.860741727 0.487415879
[51] 1.716180747 -0.869185962 1.616420778 -0.851072480 -0.960408844
[56] -0.088477089 0.795376052 1.140891787 0.592846284 1.309327278
[61] 0.892704774 1.020270857 -0.729935202 -1.651260625 -0.702054426
[66] 0.970643305 -1.261474996 -0.440275622 0.980234926 1.814482354
[71] 0.884928230 -0.430338384 0.884777203 1.174165841 0.678703920
[76] 0.599565141 -1.237316579 0.039002979 -0.280575118 0.579565923
[81] 2.549296394 -0.086067268 0.736512778 -1.595912254 -0.630300316
[86] 0.995287052 1.774960251 0.730586564 -1.928099271 -1.418999349
[91] -0.242236887 -0.296909248 0.619130267 -1.392461838 -1.391749343
[96] 1.143061835 0.096321834 -0.081017465 0.889394235 -0.507460883
> rowSums(tmp2)
[1] -1.219333348 -0.294084326 -0.635530984 0.221130008 -0.776175541
[6] 0.029652001 0.782665777 0.942963746 0.135536293 0.026550698
[11] 0.855782068 0.006188576 0.515807404 -0.409054381 0.633201529
[16] 0.912724572 1.760458669 -0.288677882 2.426158060 -0.157546981
[21] -0.199825161 -0.954161855 -0.233106462 -1.336235693 0.671323704
[26] -0.578891632 -0.209157034 0.672403696 0.890346975 0.745442906
[31] 1.109709560 -1.015712652 0.708656011 0.992373033 0.428698403
[36] -1.011755586 -0.354878357 -0.708406051 -0.125063935 0.097463748
[41] -0.361281187 -0.823202037 0.211204111 0.536691173 0.917784997
[46] -1.409437874 0.888844846 -0.308522033 0.860741727 0.487415879
[51] 1.716180747 -0.869185962 1.616420778 -0.851072480 -0.960408844
[56] -0.088477089 0.795376052 1.140891787 0.592846284 1.309327278
[61] 0.892704774 1.020270857 -0.729935202 -1.651260625 -0.702054426
[66] 0.970643305 -1.261474996 -0.440275622 0.980234926 1.814482354
[71] 0.884928230 -0.430338384 0.884777203 1.174165841 0.678703920
[76] 0.599565141 -1.237316579 0.039002979 -0.280575118 0.579565923
[81] 2.549296394 -0.086067268 0.736512778 -1.595912254 -0.630300316
[86] 0.995287052 1.774960251 0.730586564 -1.928099271 -1.418999349
[91] -0.242236887 -0.296909248 0.619130267 -1.392461838 -1.391749343
[96] 1.143061835 0.096321834 -0.081017465 0.889394235 -0.507460883
> 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] -1.219333348 -0.294084326 -0.635530984 0.221130008 -0.776175541
[6] 0.029652001 0.782665777 0.942963746 0.135536293 0.026550698
[11] 0.855782068 0.006188576 0.515807404 -0.409054381 0.633201529
[16] 0.912724572 1.760458669 -0.288677882 2.426158060 -0.157546981
[21] -0.199825161 -0.954161855 -0.233106462 -1.336235693 0.671323704
[26] -0.578891632 -0.209157034 0.672403696 0.890346975 0.745442906
[31] 1.109709560 -1.015712652 0.708656011 0.992373033 0.428698403
[36] -1.011755586 -0.354878357 -0.708406051 -0.125063935 0.097463748
[41] -0.361281187 -0.823202037 0.211204111 0.536691173 0.917784997
[46] -1.409437874 0.888844846 -0.308522033 0.860741727 0.487415879
[51] 1.716180747 -0.869185962 1.616420778 -0.851072480 -0.960408844
[56] -0.088477089 0.795376052 1.140891787 0.592846284 1.309327278
[61] 0.892704774 1.020270857 -0.729935202 -1.651260625 -0.702054426
[66] 0.970643305 -1.261474996 -0.440275622 0.980234926 1.814482354
[71] 0.884928230 -0.430338384 0.884777203 1.174165841 0.678703920
[76] 0.599565141 -1.237316579 0.039002979 -0.280575118 0.579565923
[81] 2.549296394 -0.086067268 0.736512778 -1.595912254 -0.630300316
[86] 0.995287052 1.774960251 0.730586564 -1.928099271 -1.418999349
[91] -0.242236887 -0.296909248 0.619130267 -1.392461838 -1.391749343
[96] 1.143061835 0.096321834 -0.081017465 0.889394235 -0.507460883
> rowMin(tmp2)
[1] -1.219333348 -0.294084326 -0.635530984 0.221130008 -0.776175541
[6] 0.029652001 0.782665777 0.942963746 0.135536293 0.026550698
[11] 0.855782068 0.006188576 0.515807404 -0.409054381 0.633201529
[16] 0.912724572 1.760458669 -0.288677882 2.426158060 -0.157546981
[21] -0.199825161 -0.954161855 -0.233106462 -1.336235693 0.671323704
[26] -0.578891632 -0.209157034 0.672403696 0.890346975 0.745442906
[31] 1.109709560 -1.015712652 0.708656011 0.992373033 0.428698403
[36] -1.011755586 -0.354878357 -0.708406051 -0.125063935 0.097463748
[41] -0.361281187 -0.823202037 0.211204111 0.536691173 0.917784997
[46] -1.409437874 0.888844846 -0.308522033 0.860741727 0.487415879
[51] 1.716180747 -0.869185962 1.616420778 -0.851072480 -0.960408844
[56] -0.088477089 0.795376052 1.140891787 0.592846284 1.309327278
[61] 0.892704774 1.020270857 -0.729935202 -1.651260625 -0.702054426
[66] 0.970643305 -1.261474996 -0.440275622 0.980234926 1.814482354
[71] 0.884928230 -0.430338384 0.884777203 1.174165841 0.678703920
[76] 0.599565141 -1.237316579 0.039002979 -0.280575118 0.579565923
[81] 2.549296394 -0.086067268 0.736512778 -1.595912254 -0.630300316
[86] 0.995287052 1.774960251 0.730586564 -1.928099271 -1.418999349
[91] -0.242236887 -0.296909248 0.619130267 -1.392461838 -1.391749343
[96] 1.143061835 0.096321834 -0.081017465 0.889394235 -0.507460883
>
> colMeans(tmp2)
[1] 0.1420893
> colSums(tmp2)
[1] 14.20893
> colVars(tmp2)
[1] 0.889906
> colSd(tmp2)
[1] 0.9433483
> colMax(tmp2)
[1] 2.549296
> colMin(tmp2)
[1] -1.928099
> colMedians(tmp2)
[1] 0.09689279
> colRanges(tmp2)
[,1]
[1,] -1.928099
[2,] 2.549296
>
> 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] 0.04607292 -1.78252602 -0.75345772 -2.05338759 0.53569871 -4.67407365
[7] -3.81913397 -4.76703006 1.49132201 0.07830072
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.7890105
[2,] -0.6116031
[3,] 0.2914195
[4,] 0.7992452
[5,] 0.8942250
>
> rowApply(tmp,sum)
[1] 1.4134640 -2.0483966 -0.1148353 1.2149557 1.1829853 -1.3307399
[7] -7.0887005 -0.5902829 -5.7396100 -2.5970544
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 4 9 4 1 7 8 10 7 10 2
[2,] 6 5 3 10 6 7 3 6 4 3
[3,] 7 6 2 3 10 10 2 9 5 5
[4,] 10 8 1 4 1 3 5 5 6 9
[5,] 2 4 6 9 9 4 8 8 8 7
[6,] 5 10 7 6 2 2 1 1 3 4
[7,] 3 7 5 2 4 1 7 3 9 6
[8,] 8 3 9 7 3 5 4 4 2 1
[9,] 9 1 10 5 5 6 9 10 1 8
[10,] 1 2 8 8 8 9 6 2 7 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.1785807 -1.4768953 -2.7709209 -2.1415283 0.9576668 -1.5173179
[7] -1.7677182 1.3964431 -5.3173588 1.9483216 0.5268502 -2.8133563
[13] -1.1793457 0.6593510 -0.4333770 -2.7397006 3.1246015 1.5734554
[19] 1.2347070 2.3742062
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.5126781
[2,] -0.4657569
[3,] 0.2496798
[4,] 0.2560238
[5,] 2.6513120
>
> rowApply(tmp,sum)
[1] 2.1760580 -1.2015875 0.1861713 -5.3885324 -1.9554450
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 5 15 6 14 20
[2,] 18 5 8 3 8
[3,] 10 7 17 1 11
[4,] 8 11 14 6 2
[5,] 20 6 4 19 3
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.4657569 1.4846433 0.03070905 -0.243644217 1.7204508 0.21424079
[2,] 0.2560238 -0.5760828 -0.42293358 -0.005195646 -0.5453499 -0.87136389
[3,] -0.5126781 -0.1956704 0.73484721 0.462125177 -0.7886030 -0.73110594
[4,] 0.2496798 -1.5424614 -2.65028296 -1.121992800 1.6473070 -0.03517167
[5,] 2.6513120 -0.6473240 -0.46326061 -1.232820853 -1.0761382 -0.09391715
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.8606382 1.1624678 -1.5487025 -0.57206558 -0.3942321896 0.6835375
[2,] 0.6135052 -1.4158211 -1.5348070 0.08231467 0.0007850616 -1.5896559
[3,] 0.7869578 2.0270948 -1.7606898 -0.29482361 -0.1705578666 -0.1534530
[4,] -1.7154772 -0.8081456 -0.9316812 0.60099396 1.5932185419 -0.7165291
[5,] -0.5920657 0.4308472 0.4585217 2.13190214 -0.5023633898 -1.0372558
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.07221996 0.66386657 0.9732722 -2.1470003 1.6388726 0.2903842
[2,] 0.18482294 -0.37915622 -0.3884227 0.8988872 1.3330445 2.2050345
[3,] -0.81408198 0.62328156 1.5205928 -1.5794915 0.2236997 0.2660388
[4,] 0.25193369 -0.29297256 -1.2645017 -1.2482314 0.7511188 -0.2602725
[5,] -0.87424030 0.04433167 -1.2743176 1.3361353 -0.8221342 -0.9277297
[,19] [,20]
[1,] -0.1808298 -0.34573717
[2,] 1.0373298 -0.08454643
[3,] 0.6390429 -0.09635438
[4,] -0.4827500 2.58768595
[5,] 0.2219142 0.31315823
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 650 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 563 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -1.264373 -0.5189842 -0.00168826 0.2569057 -0.1788404 -2.509836 0.3999698
col8 col9 col10 col11 col12 col13 col14
row1 -0.654355 0.6726718 1.273783 -0.1464114 0.6650413 1.494759 1.316584
col15 col16 col17 col18 col19 col20
row1 -1.140946 0.2519541 0.8845736 0.9343517 0.2569452 -0.3320857
> tmp[,"col10"]
col10
row1 1.2737825
row2 1.1142719
row3 -0.3797311
row4 0.8892922
row5 1.2626216
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -1.264373 -0.5189842 -0.00168826 0.2569057 -0.1788404 -2.50983647
row5 1.162720 -0.1395602 -0.77327733 -0.4757552 -0.4947129 0.08174774
col7 col8 col9 col10 col11 col12 col13
row1 0.39996979 -0.654355 0.6726718 1.273783 -0.1464114 0.6650413 1.4947589
row5 -0.08916341 -1.251058 1.1226578 1.262622 -0.9680836 0.8288071 -0.8450447
col14 col15 col16 col17 col18 col19 col20
row1 1.3165842 -1.140946 0.2519541 0.8845736 0.9343517 0.25694524 -0.33208573
row5 0.7368892 -0.623664 1.1285996 -0.4203758 -1.5740866 0.02447708 0.04764689
> tmp[,c("col6","col20")]
col6 col20
row1 -2.50983647 -0.33208573
row2 -0.30910799 1.02660085
row3 -0.93750527 1.15763807
row4 0.49231512 -0.61458986
row5 0.08174774 0.04764689
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -2.50983647 -0.33208573
row5 0.08174774 0.04764689
>
>
>
>
> 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 49.8026 48.18714 50.68023 47.22832 48.84437 105.4288 49.67311 48.73891
col9 col10 col11 col12 col13 col14 col15 col16
row1 52.74825 49.61087 50.04368 49.94785 48.09711 49.721 49.32241 51.91923
col17 col18 col19 col20
row1 51.45407 50.64063 48.97761 105.1569
> tmp[,"col10"]
col10
row1 49.61087
row2 30.42518
row3 30.14141
row4 28.74831
row5 51.41883
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.80260 48.18714 50.68023 47.22832 48.84437 105.4288 49.67311 48.73891
row5 50.73331 49.57632 51.05891 49.42179 46.83667 104.2178 51.32149 50.12517
col9 col10 col11 col12 col13 col14 col15 col16
row1 52.74825 49.61087 50.04368 49.94785 48.09711 49.72100 49.32241 51.91923
row5 50.39976 51.41883 49.17580 49.84655 49.33335 52.98018 49.58464 49.14106
col17 col18 col19 col20
row1 51.45407 50.64063 48.97761 105.1569
row5 49.21071 48.45692 49.90267 104.1564
> tmp[,c("col6","col20")]
col6 col20
row1 105.42881 105.15693
row2 75.80546 74.91436
row3 76.08312 76.23310
row4 75.40023 76.28622
row5 104.21778 104.15635
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.4288 105.1569
row5 104.2178 104.1564
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.4288 105.1569
row5 104.2178 104.1564
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.4043868
[2,] 0.1961642
[3,] 0.1923619
[4,] -0.7572309
[5,] -0.2336112
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.5981759 0.6513170
[2,] 1.0938906 0.5186040
[3,] 0.9982399 -1.2755816
[4,] 0.6950558 1.3238816
[5,] -0.1346714 -0.4070168
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.9790528 0.8553644
[2,] 0.2133747 1.6554913
[3,] -0.2300068 -0.2261395
[4,] 0.9950747 1.9128838
[5,] -2.2422203 0.4825575
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.9790528
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.9790528
[2,] 0.2133747
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 1.3067153 1.250433 1.4554684 1.890054 0.2570693 0.1320479 1.0602603
row1 -0.4021398 -2.033527 -0.7269317 -1.746713 -0.8057071 -1.3490400 -0.3245223
[,8] [,9] [,10] [,11] [,12] [,13]
row3 0.08159471 -1.739123 -1.049666 1.6481679 -0.07675043 -1.6392841
row1 -0.19726078 -1.690531 0.413526 -0.7653467 -0.99305681 -0.3124184
[,14] [,15] [,16] [,17] [,18] [,19]
row3 1.249669 -0.9700610 -1.1571141 -0.4207461 0.5369174 -0.3964348
row1 -1.762475 -0.5710982 -0.1596003 -0.6652783 0.4740999 -0.1460026
[,20]
row3 -0.49806423
row1 0.07523605
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.9688516 0.7985302 -0.3719894 0.219361 -0.8369268 -0.9791569 1.733644
[,8] [,9] [,10]
row2 0.1331207 1.316314 -0.9065885
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.4215442 -0.5012261 -0.3346844 -0.7277047 1.334019 0.6935168 1.555156
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.4639821 -0.5092689 -0.007528815 0.391028 -1.619498 -0.4846688 -1.644831
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.841159 -0.2814004 -1.135292 0.3077892 -0.1100386 -0.4653698
>
>
> 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: 0x6000035f8180>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7baa6dbb9dff"
[2] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7baa388208a1"
[3] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7baa61049f02"
[4] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7baa76636e10"
[5] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7baa79cf1928"
[6] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7baab7ccf92"
[7] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7baa2f1f8022"
[8] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7baa3d155059"
[9] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7baa424e2263"
[10] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7baa17b3b397"
[11] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7baa16d38aa9"
[12] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7baa1a3468f4"
[13] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7baa66d6789c"
[14] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7baaa887e83"
[15] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7baa729cfdc"
>
>
> ### 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: 0x6000035d4360>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000035d4360>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6000035d4360>
> rowMedians(tmp)
[1] -0.0058862170 0.0547877998 0.0611455583 0.3403786144 0.1025790325
[6] 0.2562183208 -0.0745210558 -0.2918856165 0.1931394599 0.0160163519
[11] 0.1690498453 -0.3423917432 -0.2036594165 0.1443738324 0.3472953576
[16] -0.0078278829 0.3737887583 0.6760818030 0.1302971103 0.3664305471
[21] -0.5773778459 0.1909543849 -0.3568931618 0.4692452786 0.4427792747
[26] 0.2391908385 0.3411644910 0.6273960167 0.1960378570 0.1818176621
[31] -0.8995414405 0.6718720618 0.0998332462 -1.1032097678 0.3590460721
[36] 0.2208443746 -0.2051925094 0.1883105661 -0.3052554704 0.0961982597
[41] -0.5231478122 -0.3191437838 -0.2833392568 0.2047556837 -0.5785788379
[46] -0.0579573221 -0.2649812056 -0.3024521710 0.2079684137 0.1775758604
[51] 0.1460612086 -0.1826162946 -0.0937232101 0.5577784400 -0.0662118784
[56] 0.3757437117 0.0409842114 0.5174207497 0.5388687657 0.0658465807
[61] -0.0257117511 0.1879027988 0.0452713468 -0.0615167253 0.4547415442
[66] 0.0846752109 0.4627819992 0.2304195645 0.2226352993 -0.1276833885
[71] 0.3409297555 -0.1597379204 0.3901241841 -0.5121243922 -0.0999226833
[76] -0.0784626918 0.3162290045 -0.2725181274 0.2873136823 -0.1178276223
[81] -0.1045421728 0.1191138958 0.3442531098 0.0788314646 -0.3545579805
[86] 0.5158863660 -0.1962055014 0.2076019046 -0.4054662211 0.0758145499
[91] 0.4458397720 -0.0421003837 -0.1491252916 -0.1259777085 -0.0745888866
[96] 0.1560271721 0.1036509514 0.3475706339 -0.2037958265 -0.0986527183
[101] 0.5638238938 0.0951908723 0.4212695480 -0.0149572307 -0.1225540327
[106] 0.1816936332 -0.3208725067 0.4443237270 -0.1667621190 0.1591374609
[111] 0.0478482062 -0.2029009952 0.2292386050 -0.0421103775 0.1047603689
[116] 0.2220194638 0.1330649070 0.4069333306 0.6846993473 0.1263341717
[121] 0.3200312312 -0.2071691230 0.0286527041 0.5017851462 -0.0211248339
[126] 0.0860981511 0.0904549988 -0.2172287128 -0.2573098722 -0.3490884673
[131] -0.6583024520 -0.4536305943 0.5670267106 -0.2612984166 0.4618034330
[136] -0.3324895984 0.0168981915 -0.5233750613 0.2954066156 0.1811755068
[141] -0.4542855108 0.2855838435 -0.0654989802 0.0639445513 0.1846223505
[146] -0.1591908188 0.4713368727 -0.9620745156 -0.3964305540 -0.5152806008
[151] -0.0121716842 -0.1135799269 -0.6540789593 0.6028842678 -0.7909685747
[156] -0.4608255198 -0.0196395542 0.2075796941 0.1706765546 0.4919769457
[161] 0.1359884237 -0.3176398693 0.0054939433 0.3796695643 0.3499180037
[166] -0.0441270882 -0.3321668472 -0.1609808041 0.7543933701 -0.1316545186
[171] -0.2441716658 0.1279116128 0.4271130118 -0.3971460207 0.3301855314
[176] 0.0090505136 -0.2759014091 -0.1120751741 -0.1462042368 0.1187643315
[181] -0.5613689309 -0.0110703912 0.0850700175 0.0098602304 -0.1789375428
[186] 0.2392705836 0.2048851610 0.1250132432 -0.2747489941 -0.0565210971
[191] 0.3960100952 0.2460848396 -0.2370207842 -0.0401025748 0.0548450023
[196] -0.3531264735 -0.1184700658 -0.4928869135 -0.0392746083 0.0726158638
[201] 0.0432742735 0.3082867091 -0.2485967759 0.1399598161 0.2888053494
[206] -0.0138538528 0.0004370849 -0.4545891767 -0.4377123328 0.3747689538
[211] 0.4339395529 0.3410137022 0.0448559883 0.3192297578 -0.1515078265
[216] -0.2281825425 0.0953483775 -0.1990550962 -0.6151922218 0.0362499700
[221] 0.0144981194 0.0549588122 -0.0015449215 -0.1619731792 0.3387900181
[226] -0.5229995293 0.3640553552 -0.4398230056 -0.2966861761 -0.5683501623
>
> proc.time()
user system elapsed
0.649 3.040 4.090
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x6000026e0000>
> .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: 0x6000026e0000>
> .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: 0x6000026e0000>
> .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: 0x6000026e0000>
> 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: 0x6000026fc000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000026fc000>
> .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: 0x6000026fc000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000026fc000>
> .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: 0x6000026fc000>
> 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: 0x6000026fc180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000026fc180>
> .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: 0x6000026fc180>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000026fc180>
> .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: 0x6000026fc180>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000026fc180>
> .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: 0x6000026fc180>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000026fc180>
> .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: 0x6000026fc180>
> 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: 0x6000026f82a0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000026f82a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000026f82a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000026f82a0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile7e522c218665" "BufferedMatrixFile7e524cfe6785"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile7e522c218665" "BufferedMatrixFile7e524cfe6785"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000026f8540>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000026f8540>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000026f8540>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000026f8540>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000026f8540>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000026f8540>
> .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: 0x6000026f8720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000026f8720>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000026f8720>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000026f8720>
> 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: 0x6000026f8900>
> .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: 0x6000026f8900>
> rm(P)
>
> proc.time()
user system elapsed
0.111 0.038 0.145
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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
0.110 0.029 0.134