Ben Bolstad
| Snapshot Date: 2025-11-13 13:40 -0500 (Thu, 13 Nov 2025) |
| 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 Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2025-11-14 11:36 -0500 (Fri, 14 Nov 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences" | 4825 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" | 4547 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 251/2325 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.75.0 (landing page) Ben Bolstad
| nebbiolo1 | 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: 1.75.0 |
| 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: 2025-11-13 18:51:24 -0500 (Thu, 13 Nov 2025) |
| EndedAt: 2025-11-13 18:51:45 -0500 (Thu, 13 Nov 2025) |
| EllapsedTime: 20.3 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
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###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.75.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck’
* using R 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
0.142 0.059 0.202
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 Nov 13 18:51:35 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] "Thu Nov 13 18:51:36 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: 0x600000da0180>
>
>
>
> 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 Nov 13 18:51:37 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] "Thu Nov 13 18:51:37 2025"
>
> ColMode(tmp2)
<pointer: 0x600000da0180>
>
>
>
> ### 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,] 98.713766 2.6399684 0.5039362 0.9255521
[2,] -1.174345 0.1905830 0.1337386 -1.6296635
[3,] -1.386819 -0.3234447 -0.9971620 -0.3935116
[4,] -1.785917 -0.3465023 1.0308631 0.6429409
> 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 : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 98.713766 2.6399684 0.5039362 0.9255521
[2,] 1.174345 0.1905830 0.1337386 1.6296635
[3,] 1.386819 0.3234447 0.9971620 0.3935116
[4,] 1.785917 0.3465023 1.0308631 0.6429409
> 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 : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.935480 1.6247979 0.7098846 0.9620562
[2,] 1.083672 0.4365581 0.3657029 1.2765827
[3,] 1.177633 0.5687220 0.9985800 0.6273050
[4,] 1.336382 0.5886444 1.0153143 0.8018360
>
> 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 : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 223.06857 43.88795 32.60278 35.54611
[2,] 37.01107 29.55616 28.79077 39.39549
[3,] 38.16315 31.01066 35.98296 31.66656
[4,] 40.14974 31.23295 36.18401 33.66130
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600000db8780>
> exp(tmp5)
<pointer: 0x600000db8780>
> log(tmp5,2)
<pointer: 0x600000db8780>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 464.288
> Min(tmp5)
[1] 53.40964
> mean(tmp5)
[1] 73.14818
> Sum(tmp5)
[1] 14629.64
> Var(tmp5)
[1] 843.8265
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.93374 72.02381 69.49500 72.41790 68.91677 70.74099 71.63231 68.99323
[9] 73.10223 71.22579
> rowSums(tmp5)
[1] 1858.675 1440.476 1389.900 1448.358 1378.335 1414.820 1432.646 1379.865
[9] 1462.045 1424.516
> rowVars(tmp5)
[1] 7716.01816 60.22279 63.84165 75.22499 60.63529 70.30827
[7] 114.96344 38.95884 112.38209 47.97445
> rowSd(tmp5)
[1] 87.840868 7.760334 7.990097 8.673234 7.786867 8.385003 10.722100
[8] 6.241702 10.601042 6.926359
> rowMax(tmp5)
[1] 464.28800 82.64567 82.40055 86.42690 81.92242 84.82300 91.89781
[8] 78.74148 92.69273 90.15739
> rowMin(tmp5)
[1] 59.13631 59.92421 55.61137 56.50433 55.10624 57.69543 53.40964 56.46941
[9] 56.14957 62.21208
>
> colMeans(tmp5)
[1] 112.04763 70.32606 68.43183 68.83891 68.44855 72.13337 71.15025
[8] 72.33332 66.91114 74.75670 73.74673 70.78371 68.22939 76.85385
[15] 68.34848 68.49234 73.53157 72.35586 72.74175 72.50209
> colSums(tmp5)
[1] 1120.4763 703.2606 684.3183 688.3891 684.4855 721.3337 711.5025
[8] 723.3332 669.1114 747.5670 737.4673 707.8371 682.2939 768.5385
[15] 683.4848 684.9234 735.3157 723.5586 727.4175 725.0209
> colVars(tmp5)
[1] 15412.36781 99.23666 41.17149 40.93732 67.87174 58.77752
[7] 53.12682 23.47295 91.41459 96.44426 71.96361 58.77412
[13] 71.99627 57.08474 74.59977 115.12047 94.42969 117.03090
[19] 65.37464 34.35432
> colSd(tmp5)
[1] 124.146558 9.961760 6.416501 6.398228 8.238431 7.666650
[7] 7.288815 4.844889 9.561098 9.820604 8.483137 7.666428
[13] 8.485061 7.555445 8.637116 10.729421 9.717494 10.818082
[19] 8.085458 5.861256
> colMax(tmp5)
[1] 464.28800 91.34701 78.62930 81.99655 82.64567 79.67991 82.40055
[8] 78.23419 85.22574 92.69273 89.18682 82.93176 81.54990 91.89781
[15] 81.99522 86.42690 90.91789 90.15739 89.16739 83.43490
> colMin(tmp5)
[1] 53.40964 60.33605 59.92421 58.56953 56.50433 59.45859 62.08035 64.08883
[9] 56.14957 57.69543 58.14664 56.46941 54.93540 64.64010 55.61137 55.10624
[17] 60.22103 58.09511 63.52972 64.13809
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 92.93374 72.02381 69.49500 72.41790 NA 70.74099 71.63231 68.99323
[9] 73.10223 71.22579
> rowSums(tmp5)
[1] 1858.675 1440.476 1389.900 1448.358 NA 1414.820 1432.646 1379.865
[9] 1462.045 1424.516
> rowVars(tmp5)
[1] 7716.01816 60.22279 63.84165 75.22499 58.63088 70.30827
[7] 114.96344 38.95884 112.38209 47.97445
> rowSd(tmp5)
[1] 87.840868 7.760334 7.990097 8.673234 7.657080 8.385003 10.722100
[8] 6.241702 10.601042 6.926359
> rowMax(tmp5)
[1] 464.28800 82.64567 82.40055 86.42690 NA 84.82300 91.89781
[8] 78.74148 92.69273 90.15739
> rowMin(tmp5)
[1] 59.13631 59.92421 55.61137 56.50433 NA 57.69543 53.40964 56.46941
[9] 56.14957 62.21208
>
> colMeans(tmp5)
[1] 112.04763 70.32606 68.43183 68.83891 68.44855 72.13337 71.15025
[8] 72.33332 66.91114 74.75670 73.74673 70.78371 68.22939 76.85385
[15] 68.34848 68.49234 73.53157 NA 72.74175 72.50209
> colSums(tmp5)
[1] 1120.4763 703.2606 684.3183 688.3891 684.4855 721.3337 711.5025
[8] 723.3332 669.1114 747.5670 737.4673 707.8371 682.2939 768.5385
[15] 683.4848 684.9234 735.3157 NA 727.4175 725.0209
> colVars(tmp5)
[1] 15412.36781 99.23666 41.17149 40.93732 67.87174 58.77752
[7] 53.12682 23.47295 91.41459 96.44426 71.96361 58.77412
[13] 71.99627 57.08474 74.59977 115.12047 94.42969 NA
[19] 65.37464 34.35432
> colSd(tmp5)
[1] 124.146558 9.961760 6.416501 6.398228 8.238431 7.666650
[7] 7.288815 4.844889 9.561098 9.820604 8.483137 7.666428
[13] 8.485061 7.555445 8.637116 10.729421 9.717494 NA
[19] 8.085458 5.861256
> colMax(tmp5)
[1] 464.28800 91.34701 78.62930 81.99655 82.64567 79.67991 82.40055
[8] 78.23419 85.22574 92.69273 89.18682 82.93176 81.54990 91.89781
[15] 81.99522 86.42690 90.91789 NA 89.16739 83.43490
> colMin(tmp5)
[1] 53.40964 60.33605 59.92421 58.56953 56.50433 59.45859 62.08035 64.08883
[9] 56.14957 57.69543 58.14664 56.46941 54.93540 64.64010 55.61137 55.10624
[17] 60.22103 NA 63.52972 64.13809
>
> Max(tmp5,na.rm=TRUE)
[1] 464.288
> Min(tmp5,na.rm=TRUE)
[1] 53.40964
> mean(tmp5,na.rm=TRUE)
[1] 73.12127
> Sum(tmp5,na.rm=TRUE)
[1] 14551.13
> Var(tmp5,na.rm=TRUE)
[1] 847.9427
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.93374 72.02381 69.49500 72.41790 68.41228 70.74099 71.63231 68.99323
[9] 73.10223 71.22579
> rowSums(tmp5,na.rm=TRUE)
[1] 1858.675 1440.476 1389.900 1448.358 1299.833 1414.820 1432.646 1379.865
[9] 1462.045 1424.516
> rowVars(tmp5,na.rm=TRUE)
[1] 7716.01816 60.22279 63.84165 75.22499 58.63088 70.30827
[7] 114.96344 38.95884 112.38209 47.97445
> rowSd(tmp5,na.rm=TRUE)
[1] 87.840868 7.760334 7.990097 8.673234 7.657080 8.385003 10.722100
[8] 6.241702 10.601042 6.926359
> rowMax(tmp5,na.rm=TRUE)
[1] 464.28800 82.64567 82.40055 86.42690 81.92242 84.82300 91.89781
[8] 78.74148 92.69273 90.15739
> rowMin(tmp5,na.rm=TRUE)
[1] 59.13631 59.92421 55.61137 56.50433 55.10624 57.69543 53.40964 56.46941
[9] 56.14957 62.21208
>
> colMeans(tmp5,na.rm=TRUE)
[1] 112.04763 70.32606 68.43183 68.83891 68.44855 72.13337 71.15025
[8] 72.33332 66.91114 74.75670 73.74673 70.78371 68.22939 76.85385
[15] 68.34848 68.49234 73.53157 71.67294 72.74175 72.50209
> colSums(tmp5,na.rm=TRUE)
[1] 1120.4763 703.2606 684.3183 688.3891 684.4855 721.3337 711.5025
[8] 723.3332 669.1114 747.5670 737.4673 707.8371 682.2939 768.5385
[15] 683.4848 684.9234 735.3157 645.0565 727.4175 725.0209
> colVars(tmp5,na.rm=TRUE)
[1] 15412.36781 99.23666 41.17149 40.93732 67.87174 58.77752
[7] 53.12682 23.47295 91.41459 96.44426 71.96361 58.77412
[13] 71.99627 57.08474 74.59977 115.12047 94.42969 126.41301
[19] 65.37464 34.35432
> colSd(tmp5,na.rm=TRUE)
[1] 124.146558 9.961760 6.416501 6.398228 8.238431 7.666650
[7] 7.288815 4.844889 9.561098 9.820604 8.483137 7.666428
[13] 8.485061 7.555445 8.637116 10.729421 9.717494 11.243354
[19] 8.085458 5.861256
> colMax(tmp5,na.rm=TRUE)
[1] 464.28800 91.34701 78.62930 81.99655 82.64567 79.67991 82.40055
[8] 78.23419 85.22574 92.69273 89.18682 82.93176 81.54990 91.89781
[15] 81.99522 86.42690 90.91789 90.15739 89.16739 83.43490
> colMin(tmp5,na.rm=TRUE)
[1] 53.40964 60.33605 59.92421 58.56953 56.50433 59.45859 62.08035 64.08883
[9] 56.14957 57.69543 58.14664 56.46941 54.93540 64.64010 55.61137 55.10624
[17] 60.22103 58.09511 63.52972 64.13809
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.93374 72.02381 69.49500 72.41790 NaN 70.74099 71.63231 68.99323
[9] 73.10223 71.22579
> rowSums(tmp5,na.rm=TRUE)
[1] 1858.675 1440.476 1389.900 1448.358 0.000 1414.820 1432.646 1379.865
[9] 1462.045 1424.516
> rowVars(tmp5,na.rm=TRUE)
[1] 7716.01816 60.22279 63.84165 75.22499 NA 70.30827
[7] 114.96344 38.95884 112.38209 47.97445
> rowSd(tmp5,na.rm=TRUE)
[1] 87.840868 7.760334 7.990097 8.673234 NA 8.385003 10.722100
[8] 6.241702 10.601042 6.926359
> rowMax(tmp5,na.rm=TRUE)
[1] 464.28800 82.64567 82.40055 86.42690 NA 84.82300 91.89781
[8] 78.74148 92.69273 90.15739
> rowMin(tmp5,na.rm=TRUE)
[1] 59.13631 59.92421 55.61137 56.50433 NA 57.69543 53.40964 56.46941
[9] 56.14957 62.21208
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.39488 71.43606 69.15748 69.59205 68.75741 72.54725 72.15802
[8] 72.88687 67.68195 74.95382 73.23742 70.47098 66.74934 76.82008
[15] 68.92560 69.97969 73.86600 NaN 73.14508 72.93375
> colSums(tmp5,na.rm=TRUE)
[1] 1038.5539 642.9245 622.4173 626.3285 618.8167 652.9253 649.4222
[8] 655.9818 609.1376 674.5844 659.1367 634.2388 600.7440 691.3807
[15] 620.3304 629.8172 664.7940 0.0000 658.3057 656.4038
> colVars(tmp5,na.rm=TRUE)
[1] 17212.86817 97.78011 40.39405 39.67325 75.28248 64.19762
[7] 48.34224 22.95990 96.15717 108.06266 78.04085 65.02064
[13] 56.35193 64.20750 80.17781 104.62334 104.97515 NA
[19] 71.71634 36.55235
> colSd(tmp5,na.rm=TRUE)
[1] 131.197821 9.888382 6.355631 6.298671 8.676548 8.012342
[7] 6.952858 4.791649 9.805976 10.395319 8.834073 8.063538
[13] 7.506792 8.012958 8.954206 10.228555 10.245738 NA
[19] 8.468550 6.045854
> colMax(tmp5,na.rm=TRUE)
[1] 464.28800 91.34701 78.62930 81.99655 82.64567 79.67991 82.40055
[8] 78.23419 85.22574 92.69273 89.18682 82.93176 78.66653 91.89781
[15] 81.99522 86.42690 90.91789 -Inf 89.16739 83.43490
> colMin(tmp5,na.rm=TRUE)
[1] 53.40964 61.51728 59.92421 58.56953 56.50433 59.45859 63.39287 64.08883
[9] 56.14957 57.69543 58.14664 56.46941 54.93540 64.64010 55.61137 57.70874
[17] 60.22103 Inf 63.52972 64.13809
>
>
>
>
> 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] 131.6971 103.2874 277.2510 222.8581 305.7897 328.4383 196.7087 267.9488
[9] 268.6139 157.4896
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 131.6971 103.2874 277.2510 222.8581 305.7897 328.4383 196.7087 267.9488
[9] 268.6139 157.4896
>
>
>
> 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] 7.105427e-14 -1.136868e-13 -5.684342e-14 -4.263256e-14 -8.526513e-14
[6] 5.684342e-14 5.684342e-14 7.105427e-15 -5.684342e-14 -5.684342e-14
[11] -1.136868e-13 2.842171e-14 -1.705303e-13 -2.842171e-14 5.684342e-14
[16] 2.842171e-14 5.684342e-14 -1.136868e-13 -8.526513e-14 -2.842171e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
5 11
4 15
1 16
10 5
3 4
8 1
5 9
1 20
10 7
4 3
8 17
10 17
4 6
4 10
3 18
4 17
8 10
8 15
8 20
8 9
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] 2.893013
> Min(tmp)
[1] -1.991093
> mean(tmp)
[1] -0.115648
> Sum(tmp)
[1] -11.5648
> Var(tmp)
[1] 1.00235
>
> rowMeans(tmp)
[1] -0.115648
> rowSums(tmp)
[1] -11.5648
> rowVars(tmp)
[1] 1.00235
> rowSd(tmp)
[1] 1.001174
> rowMax(tmp)
[1] 2.893013
> rowMin(tmp)
[1] -1.991093
>
> colMeans(tmp)
[1] 1.078207328 -0.630260689 -1.950184563 1.065653823 1.171066943
[6] 0.681080602 -0.529592228 1.250197452 -1.680749583 -0.601439134
[11] 2.893013420 -0.136352327 -0.019028293 0.395658305 -1.407363356
[16] -1.924716628 0.961838349 -1.555457511 -0.660995445 -0.394182694
[21] -0.294874310 -0.963038363 0.362713793 -1.406924191 0.892740428
[26] -0.613260776 -1.926949549 -0.516457743 0.298186912 0.007236885
[31] 1.183140433 1.039047696 1.896146837 1.570295124 1.499697070
[36] -0.791467023 0.499737756 -0.300013682 0.501421852 1.257707234
[41] -0.692790866 -1.169999851 -1.090752707 -1.318389026 0.072663686
[46] 1.063128426 -0.230358000 -1.267606572 -0.423459503 -1.991092957
[51] 0.276769052 -0.671475671 -0.705584935 0.918979050 -1.248254445
[56] 1.964460476 -1.302640294 -1.119645978 0.766828196 -0.174628399
[61] 0.889285380 -0.187769209 -0.511543995 0.254722460 0.729817051
[66] -0.751564911 -0.755484857 0.919262399 -0.150821209 -0.646451553
[71] -0.540024522 0.138886990 -0.372313683 -0.399010768 -1.733008222
[76] -1.207522151 -0.027196680 0.657633092 -0.113640009 0.193528794
[81] 0.289079071 0.433493728 1.882436216 0.420930637 1.213704322
[86] 0.159133535 0.318869725 -1.421063132 -0.184622990 -0.283859229
[91] 0.620045527 -1.051868320 -0.450021214 -0.066689914 -0.308965459
[96] -0.728722123 -0.643281762 -1.082122734 0.717450790 -1.643139683
> colSums(tmp)
[1] 1.078207328 -0.630260689 -1.950184563 1.065653823 1.171066943
[6] 0.681080602 -0.529592228 1.250197452 -1.680749583 -0.601439134
[11] 2.893013420 -0.136352327 -0.019028293 0.395658305 -1.407363356
[16] -1.924716628 0.961838349 -1.555457511 -0.660995445 -0.394182694
[21] -0.294874310 -0.963038363 0.362713793 -1.406924191 0.892740428
[26] -0.613260776 -1.926949549 -0.516457743 0.298186912 0.007236885
[31] 1.183140433 1.039047696 1.896146837 1.570295124 1.499697070
[36] -0.791467023 0.499737756 -0.300013682 0.501421852 1.257707234
[41] -0.692790866 -1.169999851 -1.090752707 -1.318389026 0.072663686
[46] 1.063128426 -0.230358000 -1.267606572 -0.423459503 -1.991092957
[51] 0.276769052 -0.671475671 -0.705584935 0.918979050 -1.248254445
[56] 1.964460476 -1.302640294 -1.119645978 0.766828196 -0.174628399
[61] 0.889285380 -0.187769209 -0.511543995 0.254722460 0.729817051
[66] -0.751564911 -0.755484857 0.919262399 -0.150821209 -0.646451553
[71] -0.540024522 0.138886990 -0.372313683 -0.399010768 -1.733008222
[76] -1.207522151 -0.027196680 0.657633092 -0.113640009 0.193528794
[81] 0.289079071 0.433493728 1.882436216 0.420930637 1.213704322
[86] 0.159133535 0.318869725 -1.421063132 -0.184622990 -0.283859229
[91] 0.620045527 -1.051868320 -0.450021214 -0.066689914 -0.308965459
[96] -0.728722123 -0.643281762 -1.082122734 0.717450790 -1.643139683
> 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] 1.078207328 -0.630260689 -1.950184563 1.065653823 1.171066943
[6] 0.681080602 -0.529592228 1.250197452 -1.680749583 -0.601439134
[11] 2.893013420 -0.136352327 -0.019028293 0.395658305 -1.407363356
[16] -1.924716628 0.961838349 -1.555457511 -0.660995445 -0.394182694
[21] -0.294874310 -0.963038363 0.362713793 -1.406924191 0.892740428
[26] -0.613260776 -1.926949549 -0.516457743 0.298186912 0.007236885
[31] 1.183140433 1.039047696 1.896146837 1.570295124 1.499697070
[36] -0.791467023 0.499737756 -0.300013682 0.501421852 1.257707234
[41] -0.692790866 -1.169999851 -1.090752707 -1.318389026 0.072663686
[46] 1.063128426 -0.230358000 -1.267606572 -0.423459503 -1.991092957
[51] 0.276769052 -0.671475671 -0.705584935 0.918979050 -1.248254445
[56] 1.964460476 -1.302640294 -1.119645978 0.766828196 -0.174628399
[61] 0.889285380 -0.187769209 -0.511543995 0.254722460 0.729817051
[66] -0.751564911 -0.755484857 0.919262399 -0.150821209 -0.646451553
[71] -0.540024522 0.138886990 -0.372313683 -0.399010768 -1.733008222
[76] -1.207522151 -0.027196680 0.657633092 -0.113640009 0.193528794
[81] 0.289079071 0.433493728 1.882436216 0.420930637 1.213704322
[86] 0.159133535 0.318869725 -1.421063132 -0.184622990 -0.283859229
[91] 0.620045527 -1.051868320 -0.450021214 -0.066689914 -0.308965459
[96] -0.728722123 -0.643281762 -1.082122734 0.717450790 -1.643139683
> colMin(tmp)
[1] 1.078207328 -0.630260689 -1.950184563 1.065653823 1.171066943
[6] 0.681080602 -0.529592228 1.250197452 -1.680749583 -0.601439134
[11] 2.893013420 -0.136352327 -0.019028293 0.395658305 -1.407363356
[16] -1.924716628 0.961838349 -1.555457511 -0.660995445 -0.394182694
[21] -0.294874310 -0.963038363 0.362713793 -1.406924191 0.892740428
[26] -0.613260776 -1.926949549 -0.516457743 0.298186912 0.007236885
[31] 1.183140433 1.039047696 1.896146837 1.570295124 1.499697070
[36] -0.791467023 0.499737756 -0.300013682 0.501421852 1.257707234
[41] -0.692790866 -1.169999851 -1.090752707 -1.318389026 0.072663686
[46] 1.063128426 -0.230358000 -1.267606572 -0.423459503 -1.991092957
[51] 0.276769052 -0.671475671 -0.705584935 0.918979050 -1.248254445
[56] 1.964460476 -1.302640294 -1.119645978 0.766828196 -0.174628399
[61] 0.889285380 -0.187769209 -0.511543995 0.254722460 0.729817051
[66] -0.751564911 -0.755484857 0.919262399 -0.150821209 -0.646451553
[71] -0.540024522 0.138886990 -0.372313683 -0.399010768 -1.733008222
[76] -1.207522151 -0.027196680 0.657633092 -0.113640009 0.193528794
[81] 0.289079071 0.433493728 1.882436216 0.420930637 1.213704322
[86] 0.159133535 0.318869725 -1.421063132 -0.184622990 -0.283859229
[91] 0.620045527 -1.051868320 -0.450021214 -0.066689914 -0.308965459
[96] -0.728722123 -0.643281762 -1.082122734 0.717450790 -1.643139683
> colMedians(tmp)
[1] 1.078207328 -0.630260689 -1.950184563 1.065653823 1.171066943
[6] 0.681080602 -0.529592228 1.250197452 -1.680749583 -0.601439134
[11] 2.893013420 -0.136352327 -0.019028293 0.395658305 -1.407363356
[16] -1.924716628 0.961838349 -1.555457511 -0.660995445 -0.394182694
[21] -0.294874310 -0.963038363 0.362713793 -1.406924191 0.892740428
[26] -0.613260776 -1.926949549 -0.516457743 0.298186912 0.007236885
[31] 1.183140433 1.039047696 1.896146837 1.570295124 1.499697070
[36] -0.791467023 0.499737756 -0.300013682 0.501421852 1.257707234
[41] -0.692790866 -1.169999851 -1.090752707 -1.318389026 0.072663686
[46] 1.063128426 -0.230358000 -1.267606572 -0.423459503 -1.991092957
[51] 0.276769052 -0.671475671 -0.705584935 0.918979050 -1.248254445
[56] 1.964460476 -1.302640294 -1.119645978 0.766828196 -0.174628399
[61] 0.889285380 -0.187769209 -0.511543995 0.254722460 0.729817051
[66] -0.751564911 -0.755484857 0.919262399 -0.150821209 -0.646451553
[71] -0.540024522 0.138886990 -0.372313683 -0.399010768 -1.733008222
[76] -1.207522151 -0.027196680 0.657633092 -0.113640009 0.193528794
[81] 0.289079071 0.433493728 1.882436216 0.420930637 1.213704322
[86] 0.159133535 0.318869725 -1.421063132 -0.184622990 -0.283859229
[91] 0.620045527 -1.051868320 -0.450021214 -0.066689914 -0.308965459
[96] -0.728722123 -0.643281762 -1.082122734 0.717450790 -1.643139683
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.078207 -0.6302607 -1.950185 1.065654 1.171067 0.6810806 -0.5295922
[2,] 1.078207 -0.6302607 -1.950185 1.065654 1.171067 0.6810806 -0.5295922
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.250197 -1.68075 -0.6014391 2.893013 -0.1363523 -0.01902829 0.3956583
[2,] 1.250197 -1.68075 -0.6014391 2.893013 -0.1363523 -0.01902829 0.3956583
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.407363 -1.924717 0.9618383 -1.555458 -0.6609954 -0.3941827 -0.2948743
[2,] -1.407363 -1.924717 0.9618383 -1.555458 -0.6609954 -0.3941827 -0.2948743
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.9630384 0.3627138 -1.406924 0.8927404 -0.6132608 -1.92695 -0.5164577
[2,] -0.9630384 0.3627138 -1.406924 0.8927404 -0.6132608 -1.92695 -0.5164577
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.2981869 0.007236885 1.18314 1.039048 1.896147 1.570295 1.499697
[2,] 0.2981869 0.007236885 1.18314 1.039048 1.896147 1.570295 1.499697
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.791467 0.4997378 -0.3000137 0.5014219 1.257707 -0.6927909 -1.17
[2,] -0.791467 0.4997378 -0.3000137 0.5014219 1.257707 -0.6927909 -1.17
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.090753 -1.318389 0.07266369 1.063128 -0.230358 -1.267607 -0.4234595
[2,] -1.090753 -1.318389 0.07266369 1.063128 -0.230358 -1.267607 -0.4234595
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -1.991093 0.2767691 -0.6714757 -0.7055849 0.9189791 -1.248254 1.96446
[2,] -1.991093 0.2767691 -0.6714757 -0.7055849 0.9189791 -1.248254 1.96446
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -1.30264 -1.119646 0.7668282 -0.1746284 0.8892854 -0.1877692 -0.511544
[2,] -1.30264 -1.119646 0.7668282 -0.1746284 0.8892854 -0.1877692 -0.511544
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.2547225 0.7298171 -0.7515649 -0.7554849 0.9192624 -0.1508212 -0.6464516
[2,] 0.2547225 0.7298171 -0.7515649 -0.7554849 0.9192624 -0.1508212 -0.6464516
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.5400245 0.138887 -0.3723137 -0.3990108 -1.733008 -1.207522 -0.02719668
[2,] -0.5400245 0.138887 -0.3723137 -0.3990108 -1.733008 -1.207522 -0.02719668
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.6576331 -0.11364 0.1935288 0.2890791 0.4334937 1.882436 0.4209306
[2,] 0.6576331 -0.11364 0.1935288 0.2890791 0.4334937 1.882436 0.4209306
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 1.213704 0.1591335 0.3188697 -1.421063 -0.184623 -0.2838592 0.6200455
[2,] 1.213704 0.1591335 0.3188697 -1.421063 -0.184623 -0.2838592 0.6200455
[,92] [,93] [,94] [,95] [,96] [,97]
[1,] -1.051868 -0.4500212 -0.06668991 -0.3089655 -0.7287221 -0.6432818
[2,] -1.051868 -0.4500212 -0.06668991 -0.3089655 -0.7287221 -0.6432818
[,98] [,99] [,100]
[1,] -1.082123 0.7174508 -1.64314
[2,] -1.082123 0.7174508 -1.64314
>
>
> Max(tmp2)
[1] 3.164713
> Min(tmp2)
[1] -2.924198
> mean(tmp2)
[1] -0.1276014
> Sum(tmp2)
[1] -12.76014
> Var(tmp2)
[1] 1.078182
>
> rowMeans(tmp2)
[1] 0.12413669 -2.05025054 -0.38921000 1.73509565 -0.55232827 -1.19957335
[7] 0.05326495 1.61802781 -0.13117760 0.28466700 -0.45580077 -2.20572318
[13] 0.62145510 0.48892141 -0.89872970 -0.39248487 0.40013355 0.06553669
[19] 1.64130074 0.68114248 -0.69443347 1.07476570 -1.11902450 0.55260831
[25] -0.15696080 0.18679066 0.36863883 -0.56757770 1.51095792 0.38650200
[31] -1.56304349 -0.49917833 -0.64032596 -0.93802742 -1.78653175 -0.13672156
[37] 1.05474737 1.39193659 0.67358560 0.48685785 0.46130801 -0.54563233
[43] 0.09566866 0.03067410 0.17512883 -1.33612744 -0.01641884 0.55346842
[49] 0.28536411 -0.55604486 0.79949560 -0.93839893 0.43152541 -0.59855051
[55] -0.49409185 -1.01111216 1.07846344 -1.52077491 -0.97202223 -1.01996654
[61] -0.67451509 0.27026281 1.07591606 -0.29766782 0.74731714 0.43134606
[67] 2.10214305 -2.23890124 -0.09956157 -1.17046247 -1.12271195 -1.47310574
[73] 0.11098585 -0.23891665 0.66492733 -0.44300607 0.02286479 3.16471326
[79] 0.17532655 -0.05619969 0.08181325 -0.01035402 -1.92569633 -2.92419795
[85] 0.84647029 -0.45779465 0.17962964 -0.50145682 -0.38362264 0.82481453
[91] -0.55022864 1.52971795 -0.94309421 -1.25438397 -0.40159330 0.71175932
[97] -0.53601226 -0.64499570 -2.70318984 1.42559496
> rowSums(tmp2)
[1] 0.12413669 -2.05025054 -0.38921000 1.73509565 -0.55232827 -1.19957335
[7] 0.05326495 1.61802781 -0.13117760 0.28466700 -0.45580077 -2.20572318
[13] 0.62145510 0.48892141 -0.89872970 -0.39248487 0.40013355 0.06553669
[19] 1.64130074 0.68114248 -0.69443347 1.07476570 -1.11902450 0.55260831
[25] -0.15696080 0.18679066 0.36863883 -0.56757770 1.51095792 0.38650200
[31] -1.56304349 -0.49917833 -0.64032596 -0.93802742 -1.78653175 -0.13672156
[37] 1.05474737 1.39193659 0.67358560 0.48685785 0.46130801 -0.54563233
[43] 0.09566866 0.03067410 0.17512883 -1.33612744 -0.01641884 0.55346842
[49] 0.28536411 -0.55604486 0.79949560 -0.93839893 0.43152541 -0.59855051
[55] -0.49409185 -1.01111216 1.07846344 -1.52077491 -0.97202223 -1.01996654
[61] -0.67451509 0.27026281 1.07591606 -0.29766782 0.74731714 0.43134606
[67] 2.10214305 -2.23890124 -0.09956157 -1.17046247 -1.12271195 -1.47310574
[73] 0.11098585 -0.23891665 0.66492733 -0.44300607 0.02286479 3.16471326
[79] 0.17532655 -0.05619969 0.08181325 -0.01035402 -1.92569633 -2.92419795
[85] 0.84647029 -0.45779465 0.17962964 -0.50145682 -0.38362264 0.82481453
[91] -0.55022864 1.52971795 -0.94309421 -1.25438397 -0.40159330 0.71175932
[97] -0.53601226 -0.64499570 -2.70318984 1.42559496
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 0.12413669 -2.05025054 -0.38921000 1.73509565 -0.55232827 -1.19957335
[7] 0.05326495 1.61802781 -0.13117760 0.28466700 -0.45580077 -2.20572318
[13] 0.62145510 0.48892141 -0.89872970 -0.39248487 0.40013355 0.06553669
[19] 1.64130074 0.68114248 -0.69443347 1.07476570 -1.11902450 0.55260831
[25] -0.15696080 0.18679066 0.36863883 -0.56757770 1.51095792 0.38650200
[31] -1.56304349 -0.49917833 -0.64032596 -0.93802742 -1.78653175 -0.13672156
[37] 1.05474737 1.39193659 0.67358560 0.48685785 0.46130801 -0.54563233
[43] 0.09566866 0.03067410 0.17512883 -1.33612744 -0.01641884 0.55346842
[49] 0.28536411 -0.55604486 0.79949560 -0.93839893 0.43152541 -0.59855051
[55] -0.49409185 -1.01111216 1.07846344 -1.52077491 -0.97202223 -1.01996654
[61] -0.67451509 0.27026281 1.07591606 -0.29766782 0.74731714 0.43134606
[67] 2.10214305 -2.23890124 -0.09956157 -1.17046247 -1.12271195 -1.47310574
[73] 0.11098585 -0.23891665 0.66492733 -0.44300607 0.02286479 3.16471326
[79] 0.17532655 -0.05619969 0.08181325 -0.01035402 -1.92569633 -2.92419795
[85] 0.84647029 -0.45779465 0.17962964 -0.50145682 -0.38362264 0.82481453
[91] -0.55022864 1.52971795 -0.94309421 -1.25438397 -0.40159330 0.71175932
[97] -0.53601226 -0.64499570 -2.70318984 1.42559496
> rowMin(tmp2)
[1] 0.12413669 -2.05025054 -0.38921000 1.73509565 -0.55232827 -1.19957335
[7] 0.05326495 1.61802781 -0.13117760 0.28466700 -0.45580077 -2.20572318
[13] 0.62145510 0.48892141 -0.89872970 -0.39248487 0.40013355 0.06553669
[19] 1.64130074 0.68114248 -0.69443347 1.07476570 -1.11902450 0.55260831
[25] -0.15696080 0.18679066 0.36863883 -0.56757770 1.51095792 0.38650200
[31] -1.56304349 -0.49917833 -0.64032596 -0.93802742 -1.78653175 -0.13672156
[37] 1.05474737 1.39193659 0.67358560 0.48685785 0.46130801 -0.54563233
[43] 0.09566866 0.03067410 0.17512883 -1.33612744 -0.01641884 0.55346842
[49] 0.28536411 -0.55604486 0.79949560 -0.93839893 0.43152541 -0.59855051
[55] -0.49409185 -1.01111216 1.07846344 -1.52077491 -0.97202223 -1.01996654
[61] -0.67451509 0.27026281 1.07591606 -0.29766782 0.74731714 0.43134606
[67] 2.10214305 -2.23890124 -0.09956157 -1.17046247 -1.12271195 -1.47310574
[73] 0.11098585 -0.23891665 0.66492733 -0.44300607 0.02286479 3.16471326
[79] 0.17532655 -0.05619969 0.08181325 -0.01035402 -1.92569633 -2.92419795
[85] 0.84647029 -0.45779465 0.17962964 -0.50145682 -0.38362264 0.82481453
[91] -0.55022864 1.52971795 -0.94309421 -1.25438397 -0.40159330 0.71175932
[97] -0.53601226 -0.64499570 -2.70318984 1.42559496
>
> colMeans(tmp2)
[1] -0.1276014
> colSums(tmp2)
[1] -12.76014
> colVars(tmp2)
[1] 1.078182
> colSd(tmp2)
[1] 1.038356
> colMax(tmp2)
[1] 3.164713
> colMin(tmp2)
[1] -2.924198
> colMedians(tmp2)
[1] -0.07788063
> colRanges(tmp2)
[,1]
[1,] -2.924198
[2,] 3.164713
>
> 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] 0.38670530 3.52418692 -0.86357457 -2.01837546 4.08808949 -1.33955769
[7] -0.67339139 0.07765003 -1.38764281 4.86989612
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.9027992
[2,] -0.6914731
[3,] -0.2286618
[4,] 0.5432520
[5,] 1.6726767
>
> rowApply(tmp,sum)
[1] -2.2070115 5.2800652 6.0566888 -3.0059726 0.5035777 2.5192190
[7] -0.6958152 4.3977441 -5.1257758 -1.0587338
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 9 3 3 6 2 6 9 7 3
[2,] 5 2 10 5 10 9 10 4 9 4
[3,] 4 7 6 10 8 7 2 1 2 2
[4,] 2 3 7 4 4 6 1 2 6 6
[5,] 1 10 1 8 9 8 8 10 8 5
[6,] 6 5 4 1 2 10 5 8 1 8
[7,] 3 1 9 2 1 1 3 6 10 10
[8,] 9 4 2 9 5 3 9 3 3 7
[9,] 7 8 5 6 3 5 7 5 5 1
[10,] 10 6 8 7 7 4 4 7 4 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.41114148 -3.06404705 -1.80993475 -0.55188842 3.49340619 0.49533453
[7] -1.12045594 -1.56290741 -1.05204444 0.79321210 -0.99279362 -0.09274441
[13] -0.61720298 -2.60410229 -1.98211435 0.81679106 2.61671926 -2.05668418
[19] 1.56025450 -0.06516042
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.7425915
[2,] -0.5369033
[3,] 0.1882358
[4,] 1.1237109
[5,] 1.3786896
>
> rowApply(tmp,sum)
[1] -3.945579 -2.005129 2.721141 -4.919149 1.763494
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 18 7 12 7 18
[2,] 4 19 4 15 1
[3,] 5 1 19 16 11
[4,] 2 18 17 1 13
[5,] 19 20 9 5 7
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.1237109 -1.06109171 -0.9258995 -1.3627312 1.157404875 2.0381006
[2,] -0.5369033 0.97924866 -2.7195165 0.8456194 3.307807910 -0.6757624
[3,] 0.1882358 -0.79875133 1.2980857 1.2026494 -0.002631938 -0.8290848
[4,] -0.7425915 -0.02233563 0.4163917 -1.5563166 -0.958229215 -0.2743530
[5,] 1.3786896 -2.16111705 0.1210038 0.3188906 -0.010945443 0.2364341
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.03052561 -0.4389117 0.6322377 -0.360332051 -0.49976863 -0.10476905
[2,] -1.38448531 0.1458824 0.8037622 0.005768972 -0.20138228 0.32143795
[3,] -0.57981375 -1.1867125 -1.4697803 0.462726198 -0.18060294 0.12866201
[4,] 0.83713846 -0.7537814 -0.4181995 -0.209411403 -0.14802381 -0.52228224
[5,] 0.03723027 0.6706158 -0.6000645 0.894460388 0.03698405 0.08420693
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.66396866 -0.4981477 -0.91520557 -1.3466376 -0.67454612 1.0413669
[2,] -0.54986119 -0.1440836 -1.63045477 0.2518567 -0.00402658 -1.7595845
[3,] 0.08900427 1.0759195 0.23240618 0.4778192 1.21530018 -0.6865856
[4,] -1.38682885 -1.4311778 -0.03529531 2.2864475 1.43090717 0.4306873
[5,] 1.89445144 -1.6066127 0.36643513 -0.8526946 0.64908461 -1.0825682
[,19] [,20]
[1,] 0.3819637 -1.43782841
[2,] 0.7708551 0.16869229
[3,] 2.0978731 -0.01357698
[4,] -1.2824984 -0.57939626
[5,] -0.4079390 1.79694893
>
>
> 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 : 655 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 : 566 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 0.08472585 -0.9841503 -1.504415 -1.029001 0.9340939 1.562199 -0.7178045
col8 col9 col10 col11 col12 col13 col14
row1 -0.2251703 -0.1869429 -0.7115046 0.786088 0.2032674 -1.068355 0.5505386
col15 col16 col17 col18 col19 col20
row1 -0.6631468 1.258739 0.6193277 0.2988527 1.210167 1.112359
> tmp[,"col10"]
col10
row1 -0.7115046257
row2 -0.0004315644
row3 0.7533951849
row4 0.8220400852
row5 -0.2111474805
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.08472585 -0.9841503 -1.504415 -1.029001 0.9340939 1.562199 -0.7178045
row5 -1.11202838 1.4806257 2.963702 -1.785997 1.3028600 1.864545 -0.7786395
col8 col9 col10 col11 col12 col13
row1 -0.2251703 -0.18694287 -0.7115046 0.786088 0.2032674 -1.0683550
row5 -1.3970581 -0.09392061 -0.2111475 1.183043 -1.0975554 -0.6964716
col14 col15 col16 col17 col18 col19 col20
row1 0.5505386 -0.6631468 1.2587387 0.6193277 0.29885268 1.210167 1.112359
row5 -0.8885736 -0.5393655 0.7833511 0.3884182 -0.03028885 -1.635662 -1.721961
> tmp[,c("col6","col20")]
col6 col20
row1 1.5621989 1.1123594
row2 -1.4595341 -0.5558539
row3 0.5470549 1.0700090
row4 -0.7201932 0.5538764
row5 1.8645453 -1.7219615
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.562199 1.112359
row5 1.864545 -1.721961
>
>
>
>
> 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 49.20279 50.69512 51.67207 51.07771 49.72242 104.4115 51.68267 51.76676
col9 col10 col11 col12 col13 col14 col15 col16
row1 47.33004 51.10961 50.46636 49.47986 51.3911 49.66891 51.70994 49.69919
col17 col18 col19 col20
row1 49.51151 49.2668 50.17834 104.3741
> tmp[,"col10"]
col10
row1 51.10961
row2 30.62787
row3 29.24746
row4 30.73298
row5 50.31326
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.20279 50.69512 51.67207 51.07771 49.72242 104.4115 51.68267 51.76676
row5 49.68571 48.07824 49.44917 51.24885 52.72061 105.7890 49.03206 49.12056
col9 col10 col11 col12 col13 col14 col15 col16
row1 47.33004 51.10961 50.46636 49.47986 51.39110 49.66891 51.70994 49.69919
row5 50.71317 50.31326 51.49101 51.46988 49.83242 49.96572 51.36954 49.41591
col17 col18 col19 col20
row1 49.51151 49.26680 50.17834 104.3741
row5 49.44342 48.87738 49.77700 105.3339
> tmp[,c("col6","col20")]
col6 col20
row1 104.41154 104.37410
row2 75.73677 73.20988
row3 74.81121 74.18613
row4 74.81210 77.29396
row5 105.78901 105.33393
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.4115 104.3741
row5 105.7890 105.3339
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.4115 104.3741
row5 105.7890 105.3339
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.6743645
[2,] -1.7345367
[3,] 1.5286511
[4,] 0.6456544
[5,] -1.1526778
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.5626230 1.3458716
[2,] 1.9425510 -0.2502187
[3,] -1.6381752 0.6573197
[4,] 0.5558132 0.4154200
[5,] 1.2114660 0.5912430
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.68847068 -1.1936608
[2,] 1.01651479 0.6315449
[3,] -0.18185969 0.9740370
[4,] -0.04809527 0.1747494
[5,] -1.44863200 -0.3220067
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.6884707
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.6884707
[2,] 1.0165148
>
>
>
> 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 -0.1783040 -0.2625812 0.7627951 -1.0695191 -0.6914069 0.9883828
row1 0.6503477 -0.3665178 -1.7711980 0.1213588 0.2597710 0.1794134
[,7] [,8] [,9] [,10] [,11] [,12]
row3 0.9865609 1.350390 0.009710896 -0.7926899 -2.23792811 -1.669768
row1 -0.8709514 1.710807 -0.743503898 1.0493599 0.02838053 -1.326827
[,13] [,14] [,15] [,16] [,17] [,18]
row3 -0.3530042 -2.203963036 1.9241576 0.8378474 0.5480256 -0.4155626
row1 -0.8526980 -0.001581037 -0.4712535 0.6901003 0.3935789 -0.9878960
[,19] [,20]
row3 -1.7122292 -0.2711664
row1 0.1127299 -1.7735237
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.5408908 -0.7134443 -0.5698528 -0.669811 1.184405 0.6174538 -0.2231836
[,8] [,9] [,10]
row2 -0.3117513 -1.038727 -1.368205
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.1538988 -0.1023422 -2.252637 2.778366 0.4730941 0.1019107 1.919318
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.175455 0.3888448 0.0867518 0.93885 -2.301292 -1.787957 -0.9838374
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.4179254 2.124832 -0.4257094 0.4291806 0.1458852 -1.295367
>
>
> 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: 0x600000dac5a0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1030c3560ac56"
[2] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1030c5dd25d7a"
[3] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1030c1df724b5"
[4] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1030c4c8af671"
[5] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1030c37399bf9"
[6] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1030c272f14c2"
[7] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1030c3fbe0a7"
[8] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1030cd59f5fc"
[9] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1030cd247a3d"
[10] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1030c55d54188"
[11] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1030c23c173be"
[12] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1030c7195d148"
[13] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1030c22df083a"
[14] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1030c609529b8"
[15] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM1030c60e62091"
>
>
> ### 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: 0x600000da09c0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600000da09c0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600000da09c0>
> rowMedians(tmp)
[1] -0.803538069 -0.120688284 0.172551784 -0.196833496 0.437952501
[6] -0.310339857 -0.116086740 0.182035459 0.075348935 -0.176373330
[11] 0.128392439 -0.125412401 0.014124413 -0.199402613 0.084938444
[16] 0.361784695 -0.417770879 0.090653129 0.301413120 -0.539469204
[21] 0.336007466 0.386408093 -0.361696069 -0.024853185 0.014778628
[26] 0.104933793 -0.004070706 -0.195013768 -0.102118314 0.359143732
[31] 0.637307406 -0.101355043 -0.296579454 0.304579450 -0.542734161
[36] 0.370488424 0.067827946 0.349445010 0.316384907 0.891185968
[41] 0.509928510 -0.083038906 0.128443641 -0.134285576 -0.378296605
[46] 0.277584385 0.256608197 0.304236186 0.280562660 0.410304316
[51] -0.311788204 0.374065552 -0.503067501 0.595783685 -0.338122302
[56] 0.596896954 0.114639343 -0.395648059 -0.045103195 -0.588302317
[61] 0.357762054 -0.186691628 -0.503230204 -0.028032666 -0.200188180
[66] -0.652762152 -0.269189138 -0.019480678 -0.326716863 0.138934813
[71] -0.334234404 0.155611107 -0.353177681 -0.559001535 -0.345086678
[76] -0.329692063 -0.567219734 0.200132321 -0.252093383 -0.486279046
[81] -0.182044819 -0.278747314 -0.042146252 0.434444145 -0.639835272
[86] -0.261573640 -0.143118589 -0.196296386 0.037588850 0.095206762
[91] -0.254239994 0.139657890 -0.193968410 0.219471655 -0.201442220
[96] 0.066976587 0.235903904 -0.249900082 -0.052895122 0.289624659
[101] -0.145879342 0.226369748 0.177618130 0.043423310 0.184289256
[106] -0.182928227 0.023295081 -0.083902858 -0.441950058 -0.922996659
[111] 0.506014895 -0.066061824 0.316523869 0.306723999 -0.011175247
[116] 0.117020291 -0.473358674 -0.518496950 -0.204119812 0.234530839
[121] 0.266807018 0.313306113 -0.221595825 0.010847691 0.098679372
[126] 0.007876814 -0.250801408 -0.370554573 -0.318455631 -0.128217324
[131] 0.200417644 -0.700064618 -0.099025899 0.330587809 0.057242918
[136] 0.162504824 -0.352463456 0.385890445 -0.154219700 0.236125940
[141] -0.083059118 0.155055661 -0.186807035 -0.195663753 -0.176519239
[146] 0.483581313 0.136770270 0.041509171 0.075241446 0.038868675
[151] 0.048952782 -0.248214388 -0.171831559 0.415240237 -0.182201397
[156] -0.208321360 -0.854614613 -0.741005009 -0.112603468 -0.076569178
[161] -0.266520130 0.162308222 -0.129094654 0.315093558 0.086217258
[166] -0.416127489 0.143921103 0.392598404 -0.157801872 -0.071915208
[171] -0.256206429 0.082472016 0.023225329 0.770791690 0.515589959
[176] 0.450073623 0.057911230 0.601506544 -0.371390295 0.332182660
[181] -0.446264162 -0.387548042 -0.011372588 0.330655372 -0.004041705
[186] -0.524192404 0.211157829 0.500376668 0.168967602 -0.251966283
[191] -0.342770819 -0.134698864 0.264389051 -0.415450824 0.216589470
[196] 0.006631445 0.242597532 -0.030331464 0.312547534 -0.627355201
[201] -0.102134641 -0.393074901 0.257438106 0.240830413 -0.040368201
[206] -0.526008374 -0.179251811 0.288816600 0.111850332 -0.045641524
[211] -0.097196609 0.222983720 -0.515736623 0.079991338 -0.310804816
[216] -0.296295936 0.313037276 -0.287244905 0.158215802 0.631847757
[221] -0.347738413 0.425687259 0.072434548 0.440871615 -0.560452900
[226] 0.280844476 0.268908004 0.233004334 0.232499844 0.325655333
>
> proc.time()
user system elapsed
0.697 3.661 4.981
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: 0x6000035801e0>
> .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: 0x6000035801e0>
> .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: 0x6000035801e0>
> .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: 0x6000035801e0>
> 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: 0x600003590060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003590060>
> .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: 0x600003590060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003590060>
> .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: 0x600003590060>
> 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: 0x600003590240>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003590240>
> .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: 0x600003590240>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003590240>
> .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: 0x600003590240>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600003590240>
> .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: 0x600003590240>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600003590240>
> .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: 0x600003590240>
> 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: 0x600003590420>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600003590420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003590420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003590420>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile108325dc81432" "BufferedMatrixFile108327aa60eb7"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile108325dc81432" "BufferedMatrixFile108327aa60eb7"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000035906c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000035906c0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000035906c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000035906c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000035906c0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000035906c0>
> .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: 0x6000035908a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000035908a0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000035908a0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000035908a0>
> 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: 0x600003590a80>
> .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: 0x600003590a80>
> rm(P)
>
> proc.time()
user system elapsed
0.129 0.056 0.183
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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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
0.134 0.039 0.175