Ben Bolstad
| Snapshot Date: 2025-12-10 13:40 -0500 (Wed, 10 Dec 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 2025-12-11 11:35 -0500 (Thu, 11 Dec 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" | 4872 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" | 4580 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 253/2331 | 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: 2025-12-10 19:03:18 -0500 (Wed, 10 Dec 2025) |
| EndedAt: 2025-12-10 19:03:39 -0500 (Wed, 10 Dec 2025) |
| EllapsedTime: 21.3 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
0.131 0.047 0.178
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] "Wed Dec 10 19:03:30 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed Dec 10 19:03:30 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: 0x6000012c8000>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Wed Dec 10 19:03:32 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed Dec 10 19:03:32 2025"
>
> ColMode(tmp2)
<pointer: 0x6000012c8000>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.8185700 -0.0727743 -0.05708602 0.8933339
[2,] 0.1603520 0.4517772 1.29965636 0.5072287
[3,] 0.8652339 -1.8037324 -0.98904791 -0.4761152
[4,] 1.0785185 -0.5302684 -1.16177162 0.7266936
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.8185700 0.0727743 0.05708602 0.8933339
[2,] 0.1603520 0.4517772 1.29965636 0.5072287
[3,] 0.8652339 1.8037324 0.98904791 0.4761152
[4,] 1.0785185 0.5302684 1.16177162 0.7266936
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0408451 0.2697671 0.2389268 0.9451634
[2,] 0.4004397 0.6721437 1.1400247 0.7121999
[3,] 0.9301795 1.3430311 0.9945089 0.6900110
[4,] 1.0385174 0.7281953 1.0778551 0.8524633
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 226.22702 27.77045 27.44635 35.34497
[2,] 29.16475 32.17321 37.69990 32.62923
[3,] 35.16703 40.23404 35.93414 32.37623
[4,] 36.46369 32.81222 36.94032 34.25133
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000012c8060>
> exp(tmp5)
<pointer: 0x6000012c8060>
> log(tmp5,2)
<pointer: 0x6000012c8060>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.8619
> Min(tmp5)
[1] 52.514
> mean(tmp5)
[1] 71.71923
> Sum(tmp5)
[1] 14343.85
> Var(tmp5)
[1] 877.8199
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.48594 66.89651 73.54740 71.61687 70.91084 65.40736 66.78255 67.90211
[9] 74.07636 67.56638
> rowSums(tmp5)
[1] 1849.719 1337.930 1470.948 1432.337 1418.217 1308.147 1335.651 1358.042
[9] 1481.527 1351.328
> rowVars(tmp5)
[1] 8054.98896 42.60644 52.96787 78.75690 87.75881 74.08852
[7] 39.76310 67.03135 63.21084 43.25231
> rowSd(tmp5)
[1] 89.749590 6.527361 7.277903 8.874509 9.367967 8.607469 6.305799
[8] 8.187267 7.950524 6.576649
> rowMax(tmp5)
[1] 470.86190 79.49944 89.92112 88.19035 82.30466 80.19044 77.14591
[8] 86.64750 86.69794 79.40339
> rowMin(tmp5)
[1] 56.37672 57.91141 62.28510 54.55573 55.92553 53.85824 52.51400 57.41018
[9] 57.76989 57.94010
>
> colMeans(tmp5)
[1] 108.89389 67.02507 74.24967 69.26592 69.54369 67.33350 69.11647
[8] 72.73955 69.19876 70.02981 68.85469 70.68238 66.89460 71.52492
[15] 70.58678 70.97640 65.69654 71.74613 72.16008 67.86580
> colSums(tmp5)
[1] 1088.9389 670.2507 742.4967 692.6592 695.4369 673.3350 691.1647
[8] 727.3955 691.9876 700.2981 688.5469 706.8238 668.9460 715.2492
[15] 705.8678 709.7640 656.9654 717.4613 721.6008 678.6580
> colVars(tmp5)
[1] 16237.48939 89.21341 54.73976 17.92113 20.62740 114.84216
[7] 45.25744 122.87789 95.52859 56.88500 112.62160 65.79964
[13] 121.98529 59.44846 121.32935 41.99117 103.25154 57.42703
[19] 50.46397 105.26304
> colSd(tmp5)
[1] 127.426408 9.445285 7.398632 4.233335 4.541740 10.716443
[7] 6.727365 11.085030 9.773873 7.542215 10.612333 8.111698
[13] 11.044695 7.710283 11.014960 6.480060 10.161277 7.578063
[19] 7.103800 10.259778
> colMax(tmp5)
[1] 470.86190 83.74189 83.14833 77.14591 79.28481 89.92112 82.07164
[8] 94.06866 86.69794 82.30466 86.64750 80.19044 93.72018 83.85682
[15] 85.04740 83.67828 80.09987 82.66117 82.45901 88.19035
> colMin(tmp5)
[1] 57.21993 55.81298 57.12599 62.09338 63.54003 54.28911 61.90566 58.86806
[9] 55.92553 59.62639 54.55573 56.97269 57.51751 57.76989 53.85824 61.67087
[17] 52.51400 56.37672 60.16098 56.81998
>
>
> ### 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] 92.48594 66.89651 73.54740 71.61687 70.91084 65.40736 66.78255 67.90211
[9] NA 67.56638
> rowSums(tmp5)
[1] 1849.719 1337.930 1470.948 1432.337 1418.217 1308.147 1335.651 1358.042
[9] NA 1351.328
> rowVars(tmp5)
[1] 8054.98896 42.60644 52.96787 78.75690 87.75881 74.08852
[7] 39.76310 67.03135 66.33302 43.25231
> rowSd(tmp5)
[1] 89.749590 6.527361 7.277903 8.874509 9.367967 8.607469 6.305799
[8] 8.187267 8.144508 6.576649
> rowMax(tmp5)
[1] 470.86190 79.49944 89.92112 88.19035 82.30466 80.19044 77.14591
[8] 86.64750 NA 79.40339
> rowMin(tmp5)
[1] 56.37672 57.91141 62.28510 54.55573 55.92553 53.85824 52.51400 57.41018
[9] NA 57.94010
>
> colMeans(tmp5)
[1] 108.89389 67.02507 74.24967 69.26592 69.54369 NA 69.11647
[8] 72.73955 69.19876 70.02981 68.85469 70.68238 66.89460 71.52492
[15] 70.58678 70.97640 65.69654 71.74613 72.16008 67.86580
> colSums(tmp5)
[1] 1088.9389 670.2507 742.4967 692.6592 695.4369 NA 691.1647
[8] 727.3955 691.9876 700.2981 688.5469 706.8238 668.9460 715.2492
[15] 705.8678 709.7640 656.9654 717.4613 721.6008 678.6580
> colVars(tmp5)
[1] 16237.48939 89.21341 54.73976 17.92113 20.62740 NA
[7] 45.25744 122.87789 95.52859 56.88500 112.62160 65.79964
[13] 121.98529 59.44846 121.32935 41.99117 103.25154 57.42703
[19] 50.46397 105.26304
> colSd(tmp5)
[1] 127.426408 9.445285 7.398632 4.233335 4.541740 NA
[7] 6.727365 11.085030 9.773873 7.542215 10.612333 8.111698
[13] 11.044695 7.710283 11.014960 6.480060 10.161277 7.578063
[19] 7.103800 10.259778
> colMax(tmp5)
[1] 470.86190 83.74189 83.14833 77.14591 79.28481 NA 82.07164
[8] 94.06866 86.69794 82.30466 86.64750 80.19044 93.72018 83.85682
[15] 85.04740 83.67828 80.09987 82.66117 82.45901 88.19035
> colMin(tmp5)
[1] 57.21993 55.81298 57.12599 62.09338 63.54003 NA 61.90566 58.86806
[9] 55.92553 59.62639 54.55573 56.97269 57.51751 57.76989 53.85824 61.67087
[17] 52.51400 56.37672 60.16098 56.81998
>
> Max(tmp5,na.rm=TRUE)
[1] 470.8619
> Min(tmp5,na.rm=TRUE)
[1] 52.514
> mean(tmp5,na.rm=TRUE)
[1] 71.69442
> Sum(tmp5,na.rm=TRUE)
[1] 14267.19
> Var(tmp5,na.rm=TRUE)
[1] 882.1296
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.48594 66.89651 73.54740 71.61687 70.91084 65.40736 66.78255 67.90211
[9] 73.94053 67.56638
> rowSums(tmp5,na.rm=TRUE)
[1] 1849.719 1337.930 1470.948 1432.337 1418.217 1308.147 1335.651 1358.042
[9] 1404.870 1351.328
> rowVars(tmp5,na.rm=TRUE)
[1] 8054.98896 42.60644 52.96787 78.75690 87.75881 74.08852
[7] 39.76310 67.03135 66.33302 43.25231
> rowSd(tmp5,na.rm=TRUE)
[1] 89.749590 6.527361 7.277903 8.874509 9.367967 8.607469 6.305799
[8] 8.187267 8.144508 6.576649
> rowMax(tmp5,na.rm=TRUE)
[1] 470.86190 79.49944 89.92112 88.19035 82.30466 80.19044 77.14591
[8] 86.64750 86.69794 79.40339
> rowMin(tmp5,na.rm=TRUE)
[1] 56.37672 57.91141 62.28510 54.55573 55.92553 53.85824 52.51400 57.41018
[9] 57.76989 57.94010
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.89389 67.02507 74.24967 69.26592 69.54369 66.29753 69.11647
[8] 72.73955 69.19876 70.02981 68.85469 70.68238 66.89460 71.52492
[15] 70.58678 70.97640 65.69654 71.74613 72.16008 67.86580
> colSums(tmp5,na.rm=TRUE)
[1] 1088.9389 670.2507 742.4967 692.6592 695.4369 596.6778 691.1647
[8] 727.3955 691.9876 700.2981 688.5469 706.8238 668.9460 715.2492
[15] 705.8678 709.7640 656.9654 717.4613 721.6008 678.6580
> colVars(tmp5,na.rm=TRUE)
[1] 16237.48939 89.21341 54.73976 17.92113 20.62740 117.12346
[7] 45.25744 122.87789 95.52859 56.88500 112.62160 65.79964
[13] 121.98529 59.44846 121.32935 41.99117 103.25154 57.42703
[19] 50.46397 105.26304
> colSd(tmp5,na.rm=TRUE)
[1] 127.426408 9.445285 7.398632 4.233335 4.541740 10.822359
[7] 6.727365 11.085030 9.773873 7.542215 10.612333 8.111698
[13] 11.044695 7.710283 11.014960 6.480060 10.161277 7.578063
[19] 7.103800 10.259778
> colMax(tmp5,na.rm=TRUE)
[1] 470.86190 83.74189 83.14833 77.14591 79.28481 89.92112 82.07164
[8] 94.06866 86.69794 82.30466 86.64750 80.19044 93.72018 83.85682
[15] 85.04740 83.67828 80.09987 82.66117 82.45901 88.19035
> colMin(tmp5,na.rm=TRUE)
[1] 57.21993 55.81298 57.12599 62.09338 63.54003 54.28911 61.90566 58.86806
[9] 55.92553 59.62639 54.55573 56.97269 57.51751 57.76989 53.85824 61.67087
[17] 52.51400 56.37672 60.16098 56.81998
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.48594 66.89651 73.54740 71.61687 70.91084 65.40736 66.78255 67.90211
[9] NaN 67.56638
> rowSums(tmp5,na.rm=TRUE)
[1] 1849.719 1337.930 1470.948 1432.337 1418.217 1308.147 1335.651 1358.042
[9] 0.000 1351.328
> rowVars(tmp5,na.rm=TRUE)
[1] 8054.98896 42.60644 52.96787 78.75690 87.75881 74.08852
[7] 39.76310 67.03135 NA 43.25231
> rowSd(tmp5,na.rm=TRUE)
[1] 89.749590 6.527361 7.277903 8.874509 9.367967 8.607469 6.305799
[8] 8.187267 NA 6.576649
> rowMax(tmp5,na.rm=TRUE)
[1] 470.86190 79.49944 89.92112 88.19035 82.30466 80.19044 77.14591
[8] 86.64750 NA 79.40339
> rowMin(tmp5,na.rm=TRUE)
[1] 56.37672 57.91141 62.28510 54.55573 55.92553 53.85824 52.51400 57.41018
[9] NA 57.94010
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.28592 66.54956 73.26093 70.06287 69.51180 NaN 69.43518
[8] 71.48227 67.25441 69.69876 67.36639 70.78144 66.94624 73.05325
[15] 69.12543 70.83684 64.32348 70.53335 72.15258 67.18835
> colSums(tmp5,na.rm=TRUE)
[1] 1019.5733 598.9460 659.3483 630.5659 625.6062 0.0000 624.9167
[8] 643.3405 605.2897 627.2888 606.2975 637.0330 602.5161 657.4793
[15] 622.1288 637.5315 578.9113 634.8001 649.3733 604.6952
> colVars(tmp5,na.rm=TRUE)
[1] 18050.16401 97.82130 50.58415 13.01607 23.19439 NA
[7] 49.77187 120.45414 64.93895 62.76269 101.78017 73.91419
[13] 137.20346 40.60161 112.47040 47.02095 94.94847 48.05845
[19] 56.77133 113.25788
> colSd(tmp5,na.rm=TRUE)
[1] 134.350899 9.890465 7.112253 3.607780 4.816056 NA
[7] 7.054918 10.975160 8.058471 7.922291 10.088616 8.597336
[13] 11.713388 6.371940 10.605206 6.857183 9.744151 6.932420
[19] 7.534675 10.642269
> colMax(tmp5,na.rm=TRUE)
[1] 470.86190 83.74189 79.40339 77.14591 79.28481 -Inf 82.07164
[8] 94.06866 78.61033 82.30466 86.64750 80.19044 93.72018 83.85682
[15] 85.04740 83.67828 80.09987 81.44229 82.45901 88.19035
> colMin(tmp5,na.rm=TRUE)
[1] 57.21993 55.81298 57.12599 65.51019 63.54003 Inf 61.90566 58.86806
[9] 55.92553 59.62639 54.55573 56.97269 57.51751 63.33873 53.85824 61.67087
[17] 52.51400 56.37672 60.16098 56.81998
>
>
>
>
> 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] 185.1173 189.3582 288.9459 305.3949 250.6351 176.0725 176.1396 125.7088
[9] 337.0212 196.3884
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 185.1173 189.3582 288.9459 305.3949 250.6351 176.0725 176.1396 125.7088
[9] 337.0212 196.3884
>
>
>
> 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 1.705303e-13 0.000000e+00 -2.842171e-13 -8.526513e-14
[6] 0.000000e+00 -1.136868e-13 2.842171e-13 -2.273737e-13 -4.547474e-13
[11] -2.842171e-14 5.684342e-14 -5.684342e-14 1.136868e-13 0.000000e+00
[16] -1.136868e-13 2.842171e-14 1.705303e-13 0.000000e+00 -2.842171e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
6 19
3 16
2 16
8 8
10 16
3 10
1 9
2 20
4 14
3 10
3 7
7 10
10 17
10 13
6 7
1 18
10 16
7 11
3 13
5 12
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] 2.709649
> Min(tmp)
[1] -3.001734
> mean(tmp)
[1] -0.01804431
> Sum(tmp)
[1] -1.804431
> Var(tmp)
[1] 0.8952866
>
> rowMeans(tmp)
[1] -0.01804431
> rowSums(tmp)
[1] -1.804431
> rowVars(tmp)
[1] 0.8952866
> rowSd(tmp)
[1] 0.9461959
> rowMax(tmp)
[1] 2.709649
> rowMin(tmp)
[1] -3.001734
>
> colMeans(tmp)
[1] -1.07833023 0.60225431 0.84016311 -0.84114717 1.23340641 -0.77813648
[7] -0.38081020 -0.12667482 -1.45470913 -0.59846846 0.86278333 1.31591468
[13] -0.13065838 0.55653953 -1.56692096 0.35079680 -0.09151312 -0.06998115
[19] 0.13994883 0.59980574 -0.48331109 -0.35360263 -0.20004488 -0.83400555
[25] 0.18194234 1.30326300 -1.58645448 -0.34926438 -0.35973591 -0.95821805
[31] -0.41969490 -0.63813690 0.63352484 -1.54140006 0.54640699 0.87335288
[37] -0.77865369 -1.22683544 -1.37884139 -0.32178670 -1.07440292 0.66300319
[43] -0.25620907 2.70964855 -0.85875384 -0.74998224 -0.49109686 0.64650816
[49] 0.72121342 -0.98473373 -1.18562195 0.40267341 -0.77945570 0.37257090
[55] 1.66294901 0.51624484 0.80068746 1.41426823 0.47225962 -1.12788777
[61] -0.50143853 1.30075456 -0.20046987 -0.16183472 -0.49393522 -0.86153348
[67] 1.21794123 0.29460923 1.10986789 -0.45252433 0.09435502 -1.19048056
[73] 0.31976928 -3.00173381 -1.32058700 0.77866205 0.62683133 2.46843986
[79] -0.30974777 -0.66427070 -0.03234638 1.06779115 -1.87279775 -0.26124367
[85] -0.36630117 0.03001056 0.66590675 0.70989057 -0.51665479 0.47280989
[91] -0.31513742 0.41976081 1.19121607 0.33647972 0.44275316 0.39734170
[97] 1.15801324 -0.72857674 1.07304197 0.90428803
> colSums(tmp)
[1] -1.07833023 0.60225431 0.84016311 -0.84114717 1.23340641 -0.77813648
[7] -0.38081020 -0.12667482 -1.45470913 -0.59846846 0.86278333 1.31591468
[13] -0.13065838 0.55653953 -1.56692096 0.35079680 -0.09151312 -0.06998115
[19] 0.13994883 0.59980574 -0.48331109 -0.35360263 -0.20004488 -0.83400555
[25] 0.18194234 1.30326300 -1.58645448 -0.34926438 -0.35973591 -0.95821805
[31] -0.41969490 -0.63813690 0.63352484 -1.54140006 0.54640699 0.87335288
[37] -0.77865369 -1.22683544 -1.37884139 -0.32178670 -1.07440292 0.66300319
[43] -0.25620907 2.70964855 -0.85875384 -0.74998224 -0.49109686 0.64650816
[49] 0.72121342 -0.98473373 -1.18562195 0.40267341 -0.77945570 0.37257090
[55] 1.66294901 0.51624484 0.80068746 1.41426823 0.47225962 -1.12788777
[61] -0.50143853 1.30075456 -0.20046987 -0.16183472 -0.49393522 -0.86153348
[67] 1.21794123 0.29460923 1.10986789 -0.45252433 0.09435502 -1.19048056
[73] 0.31976928 -3.00173381 -1.32058700 0.77866205 0.62683133 2.46843986
[79] -0.30974777 -0.66427070 -0.03234638 1.06779115 -1.87279775 -0.26124367
[85] -0.36630117 0.03001056 0.66590675 0.70989057 -0.51665479 0.47280989
[91] -0.31513742 0.41976081 1.19121607 0.33647972 0.44275316 0.39734170
[97] 1.15801324 -0.72857674 1.07304197 0.90428803
> 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] -1.07833023 0.60225431 0.84016311 -0.84114717 1.23340641 -0.77813648
[7] -0.38081020 -0.12667482 -1.45470913 -0.59846846 0.86278333 1.31591468
[13] -0.13065838 0.55653953 -1.56692096 0.35079680 -0.09151312 -0.06998115
[19] 0.13994883 0.59980574 -0.48331109 -0.35360263 -0.20004488 -0.83400555
[25] 0.18194234 1.30326300 -1.58645448 -0.34926438 -0.35973591 -0.95821805
[31] -0.41969490 -0.63813690 0.63352484 -1.54140006 0.54640699 0.87335288
[37] -0.77865369 -1.22683544 -1.37884139 -0.32178670 -1.07440292 0.66300319
[43] -0.25620907 2.70964855 -0.85875384 -0.74998224 -0.49109686 0.64650816
[49] 0.72121342 -0.98473373 -1.18562195 0.40267341 -0.77945570 0.37257090
[55] 1.66294901 0.51624484 0.80068746 1.41426823 0.47225962 -1.12788777
[61] -0.50143853 1.30075456 -0.20046987 -0.16183472 -0.49393522 -0.86153348
[67] 1.21794123 0.29460923 1.10986789 -0.45252433 0.09435502 -1.19048056
[73] 0.31976928 -3.00173381 -1.32058700 0.77866205 0.62683133 2.46843986
[79] -0.30974777 -0.66427070 -0.03234638 1.06779115 -1.87279775 -0.26124367
[85] -0.36630117 0.03001056 0.66590675 0.70989057 -0.51665479 0.47280989
[91] -0.31513742 0.41976081 1.19121607 0.33647972 0.44275316 0.39734170
[97] 1.15801324 -0.72857674 1.07304197 0.90428803
> colMin(tmp)
[1] -1.07833023 0.60225431 0.84016311 -0.84114717 1.23340641 -0.77813648
[7] -0.38081020 -0.12667482 -1.45470913 -0.59846846 0.86278333 1.31591468
[13] -0.13065838 0.55653953 -1.56692096 0.35079680 -0.09151312 -0.06998115
[19] 0.13994883 0.59980574 -0.48331109 -0.35360263 -0.20004488 -0.83400555
[25] 0.18194234 1.30326300 -1.58645448 -0.34926438 -0.35973591 -0.95821805
[31] -0.41969490 -0.63813690 0.63352484 -1.54140006 0.54640699 0.87335288
[37] -0.77865369 -1.22683544 -1.37884139 -0.32178670 -1.07440292 0.66300319
[43] -0.25620907 2.70964855 -0.85875384 -0.74998224 -0.49109686 0.64650816
[49] 0.72121342 -0.98473373 -1.18562195 0.40267341 -0.77945570 0.37257090
[55] 1.66294901 0.51624484 0.80068746 1.41426823 0.47225962 -1.12788777
[61] -0.50143853 1.30075456 -0.20046987 -0.16183472 -0.49393522 -0.86153348
[67] 1.21794123 0.29460923 1.10986789 -0.45252433 0.09435502 -1.19048056
[73] 0.31976928 -3.00173381 -1.32058700 0.77866205 0.62683133 2.46843986
[79] -0.30974777 -0.66427070 -0.03234638 1.06779115 -1.87279775 -0.26124367
[85] -0.36630117 0.03001056 0.66590675 0.70989057 -0.51665479 0.47280989
[91] -0.31513742 0.41976081 1.19121607 0.33647972 0.44275316 0.39734170
[97] 1.15801324 -0.72857674 1.07304197 0.90428803
> colMedians(tmp)
[1] -1.07833023 0.60225431 0.84016311 -0.84114717 1.23340641 -0.77813648
[7] -0.38081020 -0.12667482 -1.45470913 -0.59846846 0.86278333 1.31591468
[13] -0.13065838 0.55653953 -1.56692096 0.35079680 -0.09151312 -0.06998115
[19] 0.13994883 0.59980574 -0.48331109 -0.35360263 -0.20004488 -0.83400555
[25] 0.18194234 1.30326300 -1.58645448 -0.34926438 -0.35973591 -0.95821805
[31] -0.41969490 -0.63813690 0.63352484 -1.54140006 0.54640699 0.87335288
[37] -0.77865369 -1.22683544 -1.37884139 -0.32178670 -1.07440292 0.66300319
[43] -0.25620907 2.70964855 -0.85875384 -0.74998224 -0.49109686 0.64650816
[49] 0.72121342 -0.98473373 -1.18562195 0.40267341 -0.77945570 0.37257090
[55] 1.66294901 0.51624484 0.80068746 1.41426823 0.47225962 -1.12788777
[61] -0.50143853 1.30075456 -0.20046987 -0.16183472 -0.49393522 -0.86153348
[67] 1.21794123 0.29460923 1.10986789 -0.45252433 0.09435502 -1.19048056
[73] 0.31976928 -3.00173381 -1.32058700 0.77866205 0.62683133 2.46843986
[79] -0.30974777 -0.66427070 -0.03234638 1.06779115 -1.87279775 -0.26124367
[85] -0.36630117 0.03001056 0.66590675 0.70989057 -0.51665479 0.47280989
[91] -0.31513742 0.41976081 1.19121607 0.33647972 0.44275316 0.39734170
[97] 1.15801324 -0.72857674 1.07304197 0.90428803
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.07833 0.6022543 0.8401631 -0.8411472 1.233406 -0.7781365 -0.3808102
[2,] -1.07833 0.6022543 0.8401631 -0.8411472 1.233406 -0.7781365 -0.3808102
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.1266748 -1.454709 -0.5984685 0.8627833 1.315915 -0.1306584 0.5565395
[2,] -0.1266748 -1.454709 -0.5984685 0.8627833 1.315915 -0.1306584 0.5565395
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.566921 0.3507968 -0.09151312 -0.06998115 0.1399488 0.5998057 -0.4833111
[2,] -1.566921 0.3507968 -0.09151312 -0.06998115 0.1399488 0.5998057 -0.4833111
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.3536026 -0.2000449 -0.8340056 0.1819423 1.303263 -1.586454 -0.3492644
[2,] -0.3536026 -0.2000449 -0.8340056 0.1819423 1.303263 -1.586454 -0.3492644
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.3597359 -0.9582181 -0.4196949 -0.6381369 0.6335248 -1.5414 0.546407
[2,] -0.3597359 -0.9582181 -0.4196949 -0.6381369 0.6335248 -1.5414 0.546407
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.8733529 -0.7786537 -1.226835 -1.378841 -0.3217867 -1.074403 0.6630032
[2,] 0.8733529 -0.7786537 -1.226835 -1.378841 -0.3217867 -1.074403 0.6630032
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.2562091 2.709649 -0.8587538 -0.7499822 -0.4910969 0.6465082 0.7212134
[2,] -0.2562091 2.709649 -0.8587538 -0.7499822 -0.4910969 0.6465082 0.7212134
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.9847337 -1.185622 0.4026734 -0.7794557 0.3725709 1.662949 0.5162448
[2,] -0.9847337 -1.185622 0.4026734 -0.7794557 0.3725709 1.662949 0.5162448
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.8006875 1.414268 0.4722596 -1.127888 -0.5014385 1.300755 -0.2004699
[2,] 0.8006875 1.414268 0.4722596 -1.127888 -0.5014385 1.300755 -0.2004699
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.1618347 -0.4939352 -0.8615335 1.217941 0.2946092 1.109868 -0.4525243
[2,] -0.1618347 -0.4939352 -0.8615335 1.217941 0.2946092 1.109868 -0.4525243
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.09435502 -1.190481 0.3197693 -3.001734 -1.320587 0.778662 0.6268313
[2,] 0.09435502 -1.190481 0.3197693 -3.001734 -1.320587 0.778662 0.6268313
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 2.46844 -0.3097478 -0.6642707 -0.03234638 1.067791 -1.872798 -0.2612437
[2,] 2.46844 -0.3097478 -0.6642707 -0.03234638 1.067791 -1.872798 -0.2612437
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.3663012 0.03001056 0.6659067 0.7098906 -0.5166548 0.4728099 -0.3151374
[2,] -0.3663012 0.03001056 0.6659067 0.7098906 -0.5166548 0.4728099 -0.3151374
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.4197608 1.191216 0.3364797 0.4427532 0.3973417 1.158013 -0.7285767
[2,] 0.4197608 1.191216 0.3364797 0.4427532 0.3973417 1.158013 -0.7285767
[,99] [,100]
[1,] 1.073042 0.904288
[2,] 1.073042 0.904288
>
>
> Max(tmp2)
[1] 2.195168
> Min(tmp2)
[1] -2.307761
> mean(tmp2)
[1] 0.0817442
> Sum(tmp2)
[1] 8.17442
> Var(tmp2)
[1] 0.9534447
>
> rowMeans(tmp2)
[1] 0.55140833 0.87209791 -0.53123476 -0.90306815 1.04421397 -1.03286901
[7] -0.23805494 1.51005111 -0.66268522 -2.30776068 -1.02571183 0.21146974
[13] 0.64314837 0.75024471 0.85916340 0.17670617 0.69217769 1.18996063
[19] -1.02740947 0.02835172 1.37418453 -1.00953238 -0.30342478 1.84564842
[25] -1.20508257 0.35742925 0.81549113 1.41912923 1.68850571 -0.70007256
[31] -0.27025662 0.49422766 0.02708544 1.32593740 1.05517013 -0.45285779
[37] -0.12525551 1.19515756 -0.77633560 -0.36096928 -0.37295861 -0.91535758
[43] -0.52013096 1.13653434 -0.14587883 -0.89794522 0.95060766 0.49551357
[49] 0.20779864 0.60925800 0.31392910 -0.37413514 0.39745741 -1.38437528
[55] -2.22375092 0.61360397 -0.78556535 1.10559833 0.73407845 -1.09464041
[61] 1.49009925 -0.25860011 0.15977534 1.16864927 0.19738005 -0.69692099
[67] -1.62739521 -1.37410263 -1.93897341 -0.29054152 1.91847397 0.50937365
[73] -1.04155261 -0.48980460 1.02308581 -0.09228498 1.06141394 0.32082293
[79] 1.69017059 -0.83385282 0.19156115 -0.18165421 0.10847611 -1.30857554
[85] 0.18271383 -0.90584610 0.36191436 -0.26600490 1.43413494 -0.67220810
[91] -0.22906204 2.19516792 0.75979212 0.35217009 1.04160266 0.17036373
[97] -2.14777583 0.17477558 0.85895158 0.11468614
> rowSums(tmp2)
[1] 0.55140833 0.87209791 -0.53123476 -0.90306815 1.04421397 -1.03286901
[7] -0.23805494 1.51005111 -0.66268522 -2.30776068 -1.02571183 0.21146974
[13] 0.64314837 0.75024471 0.85916340 0.17670617 0.69217769 1.18996063
[19] -1.02740947 0.02835172 1.37418453 -1.00953238 -0.30342478 1.84564842
[25] -1.20508257 0.35742925 0.81549113 1.41912923 1.68850571 -0.70007256
[31] -0.27025662 0.49422766 0.02708544 1.32593740 1.05517013 -0.45285779
[37] -0.12525551 1.19515756 -0.77633560 -0.36096928 -0.37295861 -0.91535758
[43] -0.52013096 1.13653434 -0.14587883 -0.89794522 0.95060766 0.49551357
[49] 0.20779864 0.60925800 0.31392910 -0.37413514 0.39745741 -1.38437528
[55] -2.22375092 0.61360397 -0.78556535 1.10559833 0.73407845 -1.09464041
[61] 1.49009925 -0.25860011 0.15977534 1.16864927 0.19738005 -0.69692099
[67] -1.62739521 -1.37410263 -1.93897341 -0.29054152 1.91847397 0.50937365
[73] -1.04155261 -0.48980460 1.02308581 -0.09228498 1.06141394 0.32082293
[79] 1.69017059 -0.83385282 0.19156115 -0.18165421 0.10847611 -1.30857554
[85] 0.18271383 -0.90584610 0.36191436 -0.26600490 1.43413494 -0.67220810
[91] -0.22906204 2.19516792 0.75979212 0.35217009 1.04160266 0.17036373
[97] -2.14777583 0.17477558 0.85895158 0.11468614
> 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] 0.55140833 0.87209791 -0.53123476 -0.90306815 1.04421397 -1.03286901
[7] -0.23805494 1.51005111 -0.66268522 -2.30776068 -1.02571183 0.21146974
[13] 0.64314837 0.75024471 0.85916340 0.17670617 0.69217769 1.18996063
[19] -1.02740947 0.02835172 1.37418453 -1.00953238 -0.30342478 1.84564842
[25] -1.20508257 0.35742925 0.81549113 1.41912923 1.68850571 -0.70007256
[31] -0.27025662 0.49422766 0.02708544 1.32593740 1.05517013 -0.45285779
[37] -0.12525551 1.19515756 -0.77633560 -0.36096928 -0.37295861 -0.91535758
[43] -0.52013096 1.13653434 -0.14587883 -0.89794522 0.95060766 0.49551357
[49] 0.20779864 0.60925800 0.31392910 -0.37413514 0.39745741 -1.38437528
[55] -2.22375092 0.61360397 -0.78556535 1.10559833 0.73407845 -1.09464041
[61] 1.49009925 -0.25860011 0.15977534 1.16864927 0.19738005 -0.69692099
[67] -1.62739521 -1.37410263 -1.93897341 -0.29054152 1.91847397 0.50937365
[73] -1.04155261 -0.48980460 1.02308581 -0.09228498 1.06141394 0.32082293
[79] 1.69017059 -0.83385282 0.19156115 -0.18165421 0.10847611 -1.30857554
[85] 0.18271383 -0.90584610 0.36191436 -0.26600490 1.43413494 -0.67220810
[91] -0.22906204 2.19516792 0.75979212 0.35217009 1.04160266 0.17036373
[97] -2.14777583 0.17477558 0.85895158 0.11468614
> rowMin(tmp2)
[1] 0.55140833 0.87209791 -0.53123476 -0.90306815 1.04421397 -1.03286901
[7] -0.23805494 1.51005111 -0.66268522 -2.30776068 -1.02571183 0.21146974
[13] 0.64314837 0.75024471 0.85916340 0.17670617 0.69217769 1.18996063
[19] -1.02740947 0.02835172 1.37418453 -1.00953238 -0.30342478 1.84564842
[25] -1.20508257 0.35742925 0.81549113 1.41912923 1.68850571 -0.70007256
[31] -0.27025662 0.49422766 0.02708544 1.32593740 1.05517013 -0.45285779
[37] -0.12525551 1.19515756 -0.77633560 -0.36096928 -0.37295861 -0.91535758
[43] -0.52013096 1.13653434 -0.14587883 -0.89794522 0.95060766 0.49551357
[49] 0.20779864 0.60925800 0.31392910 -0.37413514 0.39745741 -1.38437528
[55] -2.22375092 0.61360397 -0.78556535 1.10559833 0.73407845 -1.09464041
[61] 1.49009925 -0.25860011 0.15977534 1.16864927 0.19738005 -0.69692099
[67] -1.62739521 -1.37410263 -1.93897341 -0.29054152 1.91847397 0.50937365
[73] -1.04155261 -0.48980460 1.02308581 -0.09228498 1.06141394 0.32082293
[79] 1.69017059 -0.83385282 0.19156115 -0.18165421 0.10847611 -1.30857554
[85] 0.18271383 -0.90584610 0.36191436 -0.26600490 1.43413494 -0.67220810
[91] -0.22906204 2.19516792 0.75979212 0.35217009 1.04160266 0.17036373
[97] -2.14777583 0.17477558 0.85895158 0.11468614
>
> colMeans(tmp2)
[1] 0.0817442
> colSums(tmp2)
[1] 8.17442
> colVars(tmp2)
[1] 0.9534447
> colSd(tmp2)
[1] 0.9764449
> colMax(tmp2)
[1] 2.195168
> colMin(tmp2)
[1] -2.307761
> colMedians(tmp2)
[1] 0.1725697
> colRanges(tmp2)
[,1]
[1,] -2.307761
[2,] 2.195168
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.8231014 -1.0316292 2.9556553 3.3080057 5.7695714 -0.2309887
[7] 1.2673110 1.2145381 -2.7889016 -0.4585090
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.2357950
[2,] -0.4811119
[3,] -0.4046884
[4,] 0.1056459
[5,] 0.5070947
>
> rowApply(tmp,sum)
[1] -2.53359673 2.21984055 -0.90288135 3.53496247 4.44368975 -0.30063803
[7] 1.13294649 1.15063623 -1.51307753 -0.04993017
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 4 1 4 3 3 8 6 3 2 8
[2,] 7 8 3 5 5 4 7 1 3 7
[3,] 5 7 8 8 6 7 9 5 5 4
[4,] 2 2 7 9 9 10 4 4 9 6
[5,] 10 5 9 7 7 9 3 6 4 10
[6,] 6 4 6 4 4 3 1 10 8 2
[7,] 1 10 10 1 8 5 5 9 1 5
[8,] 8 9 2 2 10 1 8 7 6 9
[9,] 9 6 5 10 1 2 2 2 7 3
[10,] 3 3 1 6 2 6 10 8 10 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -3.73614609 6.72157215 0.14152018 2.26138406 -2.71004836 -2.16707291
[7] -0.31253078 0.59437965 0.73802368 -0.06441043 -2.03925390 -1.57072434
[13] 0.33941521 -1.79256775 0.67572347 -0.69709419 1.90372600 -3.03411355
[19] -1.00809718 1.21920329
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.4286327
[2,] -1.5106619
[3,] -0.5707742
[4,] 0.1770228
[5,] 0.5969000
>
> rowApply(tmp,sum)
[1] 3.512421 -13.961941 1.028797 6.322350 -1.438739
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 3 1 10 1 13
[2,] 17 20 12 15 20
[3,] 12 18 6 13 11
[4,] 8 19 7 18 18
[5,] 4 17 4 3 8
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.5707742 0.8096095 0.4164798 -0.07542714 -0.40521212 -0.2480829
[2,] -2.4286327 1.5435400 0.1378255 0.39141231 -0.01282759 -0.5351670
[3,] 0.1770228 0.3589544 -0.8335134 -0.74102828 -0.84369523 -0.5412347
[4,] -1.5106619 1.1056822 0.6621125 1.54866939 -0.97347886 0.3065129
[5,] 0.5969000 2.9037860 -0.2413843 1.13775778 -0.47483456 -1.1491012
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.3563977 -0.2413978 1.22392137 0.7158442 -0.07195554 -0.3590763
[2,] -0.5668268 -0.9952177 -1.03648043 -0.6116559 -1.61535710 -0.1490139
[3,] 1.4532315 0.2372519 1.01928268 1.0047179 0.40465096 -0.9498809
[4,] -1.2630958 0.4400828 -0.03043032 0.4493694 0.49492846 1.1725250
[5,] -1.2922375 1.1536604 -0.43826962 -1.6226860 -1.25152068 -1.2852782
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.02677266 0.6699939 0.5440395 -0.02559684 0.8423268 -0.58558808
[2,] -0.99828245 -1.2226457 -2.2922526 -1.13207252 -1.4464778 -0.09437329
[3,] -1.14523190 0.6987685 0.7916889 1.15006785 -0.1724928 -0.86362535
[4,] 1.75376109 -0.1012566 0.9658437 -0.56001569 1.5911356 -0.90327169
[5,] 0.75594114 -1.8374279 0.6664040 -0.12947700 1.0892342 -0.58725513
[,19] [,20]
[1,] -0.94589705 0.4895887
[2,] -0.03518116 -0.8622537
[3,] 0.66107352 -0.8372115
[4,] -0.34448786 1.5184259
[5,] -0.34360463 0.9106539
>
>
> 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 : 648 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 563 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.4763468 -0.3001275 0.961219 0.05590927 -0.4471184 0.003398786 -0.356828
col8 col9 col10 col11 col12 col13 col14
row1 0.03739334 0.2668823 0.0795118 0.7425063 0.7445444 -1.047003 -0.2191993
col15 col16 col17 col18 col19 col20
row1 0.9162043 0.02641743 -0.1959491 -0.3068549 2.002695 1.363038
> tmp[,"col10"]
col10
row1 0.0795118
row2 -2.7515800
row3 1.0045762
row4 -0.2313138
row5 0.5643649
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.4763468 -0.3001275 0.961219 0.05590927 -0.4471184 0.003398786
row5 -0.5016285 0.4913076 1.726050 1.21915120 0.3739865 -0.191468920
col7 col8 col9 col10 col11 col12 col13
row1 -0.3568280 0.03739334 0.2668823 0.0795118 0.7425063 0.7445444 -1.04700310
row5 -0.8407669 0.77147002 0.9593082 0.5643649 1.2214275 0.8972680 0.06640444
col14 col15 col16 col17 col18 col19
row1 -0.21919925 0.9162043 0.02641743 -0.1959491 -0.3068549 2.0026946
row5 -0.01833129 -0.1953124 -0.94110855 0.3783674 1.2240817 0.8911867
col20
row1 1.3630383
row5 0.6983241
> tmp[,c("col6","col20")]
col6 col20
row1 0.003398786 1.3630383
row2 -1.213873263 0.2579104
row3 0.230366107 0.9822931
row4 1.167192317 -1.4846687
row5 -0.191468920 0.6983241
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.003398786 1.3630383
row5 -0.191468920 0.6983241
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.16553 49.9831 49.75459 49.65029 51.01675 105.2299 50.28563 49.74611
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.0475 50.88851 51.60849 49.19841 49.41814 48.18127 50.57384 48.37296
col17 col18 col19 col20
row1 50.90603 49.24613 49.28881 103.8471
> tmp[,"col10"]
col10
row1 50.88851
row2 30.26237
row3 30.35812
row4 30.05587
row5 49.99578
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.16553 49.98310 49.75459 49.65029 51.01675 105.2299 50.28563 49.74611
row5 50.23841 49.43621 50.44946 50.28940 49.59817 103.3307 51.01076 50.03185
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.04750 50.88851 51.60849 49.19841 49.41814 48.18127 50.57384 48.37296
row5 50.96084 49.99578 52.16353 50.29154 50.35153 50.87948 50.29898 50.65113
col17 col18 col19 col20
row1 50.90603 49.24613 49.28881 103.8471
row5 51.14746 49.38631 50.09672 103.6019
> tmp[,c("col6","col20")]
col6 col20
row1 105.22990 103.84713
row2 74.39156 75.26261
row3 76.08466 74.74210
row4 76.39441 75.77828
row5 103.33066 103.60191
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.2299 103.8471
row5 103.3307 103.6019
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.2299 103.8471
row5 103.3307 103.6019
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.6080832
[2,] -0.8856191
[3,] -1.2456253
[4,] -0.9319761
[5,] -0.8317835
> tmp[,c("col17","col7")]
col17 col7
[1,] 2.0333632 0.8059374
[2,] -0.7090319 0.2382866
[3,] 0.8077538 0.0286677
[4,] 1.1487619 -0.9199910
[5,] 1.2468648 0.3596234
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.9851349 0.1930849
[2,] -1.7948429 -0.1539100
[3,] -0.3214063 -0.7842242
[4,] 0.5156554 0.3286578
[5,] 0.3217517 1.1640398
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.9851349
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.9851349
[2,] -1.7948429
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 0.9646254 0.4531242 2.0721490 0.8346934 0.5550051 -1.0375777 0.4578686
row1 -1.0205199 -2.1104088 0.2127466 -1.2316318 -1.4265492 -0.3113624 0.4902303
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 1.237767 0.3118641 -1.0777583 0.03592992 0.4490677 0.2869205 1.069205
row1 -1.425827 -0.3152203 0.7504032 0.97609262 0.6146766 0.6451460 -1.370311
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.06007157 -1.0011589 0.1381385 -0.3245696 0.05416476 0.7378202
row1 -0.41761146 -0.1590562 -0.6509354 -0.6064905 -0.31843714 -2.0468534
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.02010938 -0.4478126 -0.8474555 1.796239 0.7989674 0.1224228 1.982816
[,8] [,9] [,10]
row2 -1.250571 -1.244363 -0.5455811
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.6157231 -1.008088 0.07241521 0.5052566 -0.2161431 -0.6295961 -0.1903785
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.0195183 1.02568 0.56748 -0.4037421 1.347524 0.4139577 -0.1630531
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.1080317 -1.767635 0.8530905 -1.866291 -1.157696 0.8658259
>
>
> 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: 0x6000012f0360>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMb2d8369387ab"
[2] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMb2d8fb0078b"
[3] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMb2d86dbf3eb8"
[4] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMb2d826aeda52"
[5] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMb2d8217f5155"
[6] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMb2d82db4b4a1"
[7] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMb2d832becd78"
[8] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMb2d8ca39b4f"
[9] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMb2d849296604"
[10] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMb2d83ce8b622"
[11] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMb2d8520d916b"
[12] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMb2d878c631e2"
[13] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMb2d81bf52a60"
[14] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMb2d87cb112f6"
[15] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BMb2d84d54146e"
>
>
> ### 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: 0x6000012c81e0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000012c81e0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6000012c81e0>
> rowMedians(tmp)
[1] 0.002199837 0.503267790 0.336804602 0.246172373 -0.045212704
[6] 0.355713827 0.095281146 0.095647257 -0.201256784 -0.488367904
[11] -0.311417995 -0.099970701 0.055324460 -0.111379216 0.096418472
[16] 0.124482594 -0.595442620 -0.116996896 0.098496165 0.213360158
[21] 0.148101966 0.102375138 0.190099767 -0.023039606 -0.249400306
[26] -0.281703806 -0.416331312 0.130081044 0.139028507 0.022823663
[31] 0.178263272 0.661142715 0.044510596 0.141187434 -0.225426155
[36] -0.242569121 0.064568161 -0.396265878 -0.248190555 0.002177743
[41] 0.196172678 0.021073615 0.257886032 -0.015527674 -0.152618742
[46] 0.397035957 0.564376291 0.255877262 0.011809587 0.224365368
[51] 0.258261929 0.022663637 0.102827306 0.011860878 -0.269437905
[56] -0.060562189 0.169565908 -0.188537333 0.281040136 -0.163671135
[61] 0.339786864 0.138600243 0.336222779 -0.111857321 -0.334020991
[66] -0.557003481 0.047689729 0.002859483 0.079801661 0.353326792
[71] -0.222839830 0.285950988 0.242273133 0.041106122 -0.243147022
[76] -0.441562301 -0.063990850 0.883361478 0.198929822 -0.110574496
[81] 0.231146987 0.024961747 0.313814433 0.056883747 -0.548829429
[86] -0.193201221 0.154759577 -0.341063314 -0.418056318 -0.175215519
[91] 0.710966521 0.169367336 0.357442462 0.246101193 -0.536680953
[96] 0.013827555 0.216556365 0.007408599 -0.012701050 -0.621769246
[101] 0.198678124 0.214224300 -0.412070247 -0.367636125 -0.054787920
[106] -0.061603892 0.205182416 0.467106661 -0.053692769 -0.065975187
[111] 0.538778354 0.375438117 -0.586572062 0.024199914 -0.205477471
[116] 0.413095603 0.285844330 -0.657865824 0.271791494 -0.520861035
[121] -0.618883530 -0.036071505 -0.128173722 -0.127619076 0.063822680
[126] -0.060519532 0.417369672 0.131424837 -0.150114846 -0.254684273
[131] -0.355997819 0.097097663 0.041646776 -0.013704033 -0.258987017
[136] -0.032539898 0.602711785 0.112972664 -0.053517230 -0.135193240
[141] -0.497243485 -0.152718605 -0.321444252 0.106900771 0.178871820
[146] 0.186272688 -0.018172513 0.272603830 0.669844294 -0.303928889
[151] -0.491583920 0.129046249 0.263056044 -0.371539589 0.234149133
[156] 0.121831501 0.074147656 0.066703610 0.185490447 -0.495042794
[161] 0.089486438 0.108189431 -0.015083729 0.160482266 -0.198482186
[166] 0.210448725 -0.044257145 -0.264952526 0.116789382 0.335074064
[171] 0.016736249 0.391842003 -0.018381322 0.505819221 0.407235450
[176] 0.576470605 0.100367636 0.307601834 0.162934778 -0.053404942
[181] -0.120498100 -0.144865848 -0.286306540 0.104174157 -0.567818700
[186] 0.182802941 0.146477317 -0.285838923 -0.142913861 -0.175957926
[191] 0.048647248 0.073601810 -0.107618284 -0.391790693 0.532170158
[196] -0.062077676 -0.392605044 -0.210421827 -0.254346818 0.043656134
[201] 0.599880908 -0.302497342 0.071265847 0.507916452 0.173484740
[206] 0.023287505 -0.069925205 -0.288295002 -0.054933436 -0.454987228
[211] -0.393106051 -0.139788697 0.315955011 0.568198367 0.376430957
[216] 0.030057844 -0.369457422 -0.226893263 -0.073429370 -0.266537884
[221] -0.412752079 0.157597416 0.059278231 0.103383629 -0.050373255
[226] 0.472529475 -0.544730137 0.115232896 0.005362764 -0.244270304
>
> proc.time()
user system elapsed
0.772 3.808 5.066
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: 0x6000016740c0>
> .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: 0x6000016740c0>
> .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: 0x6000016740c0>
> .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: 0x6000016740c0>
> 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: 0x600001674840>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001674840>
> .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: 0x600001674840>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001674840>
> .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: 0x600001674840>
> 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: 0x600001674a20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001674a20>
> .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: 0x600001674a20>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600001674a20>
> .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: 0x600001674a20>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600001674a20>
> .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: 0x600001674a20>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600001674a20>
> .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: 0x600001674a20>
> 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: 0x600001674c00>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600001674c00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001674c00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001674c00>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFileb83251bb2503" "BufferedMatrixFileb832557b11e0"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFileb83251bb2503" "BufferedMatrixFileb832557b11e0"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001674ea0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001674ea0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600001674ea0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600001674ea0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600001674ea0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600001674ea0>
> .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: 0x600001675080>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001675080>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600001675080>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600001675080>
> 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: 0x600001675260>
> .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: 0x600001675260>
> rm(P)
>
> proc.time()
user system elapsed
0.151 0.055 0.199
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences"
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Platform: aarch64-apple-darwin20
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Type 'license()' or 'licence()' for distribution details.
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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
0.143 0.041 0.175