Ben Bolstad
| Snapshot Date: 2025-11-11 13:45 -0500 (Tue, 11 Nov 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_22 |
| git_last_commit: d2ce144 |
| git_last_commit_date: 2025-10-29 09:58:55 -0500 (Wed, 29 Oct 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-11-12 11:58 -0500 (Wed, 12 Nov 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" | 4902 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4668 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 257/2361 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.74.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | 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. - See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host. |
| Package: BufferedMatrix |
| Version: 1.74.0 |
| Command: /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.74.0.tar.gz |
| StartedAt: 2025-11-11 07:43:55 -0000 (Tue, 11 Nov 2025) |
| EndedAt: 2025-11-11 07:44:18 -0000 (Tue, 11 Nov 2025) |
| EllapsedTime: 23.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
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###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.74.0.tar.gz
###
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* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.0 (2025-04-11)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.74.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0’
* 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 loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking 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: 2 NOTEs
See
‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
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###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/R/R-4.5.0/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.74.0’
** using staged installation
** libs
using C compiler: ‘aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0’
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c init_package.c -o init_package.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -shared -L/home/biocbuild/R/R-4.5.0/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/R/R-4.5.0/lib -lR
installing to /home/biocbuild/R/R-4.5.0/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
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
0.304 0.069 0.357
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
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] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 478398 25.6 1047041 56 639620 34.2
Vcells 885166 6.8 8388608 64 2080985 15.9
>
>
>
>
> ##
> ## 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] "Tue Nov 11 07:44:13 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] "Tue Nov 11 07:44:13 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: 0x2e3e8ff0>
>
>
>
> 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] "Tue Nov 11 07:44:13 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] "Tue Nov 11 07:44:13 2025"
>
> ColMode(tmp2)
<pointer: 0x2e3e8ff0>
>
>
>
> ### 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,] 97.9341658 0.7357290 0.6604947 -1.4202283
[2,] -0.1099645 -0.3472249 0.3400510 -1.0241125
[3,] -0.5773988 1.0659786 -1.3896402 1.3468535
[4,] 2.5061612 1.9878151 -0.2100075 -0.4134135
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-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,] 97.9341658 0.7357290 0.6604947 1.4202283
[2,] 0.1099645 0.3472249 0.3400510 1.0241125
[3,] 0.5773988 1.0659786 1.3896402 1.3468535
[4,] 2.5061612 1.9878151 0.2100075 0.4134135
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-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,] 9.8961692 0.8577465 0.8127082 1.1917333
[2,] 0.3316090 0.5892579 0.5831389 1.0119844
[3,] 0.7598676 1.0324624 1.1788300 1.1605402
[4,] 1.5830860 1.4098990 0.4582657 0.6429724
>
> 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: /home/biocbuild/bbs-3.22-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,] 221.89586 34.31319 33.78758 38.33756
[2,] 28.42605 31.23980 31.17144 36.14396
[3,] 33.17608 36.39060 38.17794 37.95226
[4,] 43.33702 41.08680 29.79266 31.84314
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x2d0cb6c0>
> exp(tmp5)
<pointer: 0x2d0cb6c0>
> log(tmp5,2)
<pointer: 0x2d0cb6c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 461.8472
> Min(tmp5)
[1] 53.90864
> mean(tmp5)
[1] 72.79336
> Sum(tmp5)
[1] 14558.67
> Var(tmp5)
[1] 833.9864
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.82732 68.56688 71.83287 70.85601 71.76803 68.35275 70.33809 73.38328
[9] 68.29806 72.71029
> rowSums(tmp5)
[1] 1836.546 1371.338 1436.657 1417.120 1435.361 1367.055 1406.762 1467.666
[9] 1365.961 1454.206
> rowVars(tmp5)
[1] 7651.44055 30.44858 71.00069 90.40302 69.01895 73.73381
[7] 45.61938 98.20428 55.34472 94.75740
> rowSd(tmp5)
[1] 87.472513 5.518024 8.426190 9.508051 8.307764 8.586840 6.754212
[8] 9.909807 7.439403 9.734341
> rowMax(tmp5)
[1] 461.84716 77.87741 86.11454 90.20033 90.64650 85.95312 87.24925
[8] 87.03460 81.40322 94.25024
> rowMin(tmp5)
[1] 58.59916 58.21689 57.38774 54.55436 55.26292 55.99499 58.63176 58.69072
[9] 53.90864 57.91493
>
> colMeans(tmp5)
[1] 111.45537 71.43881 71.40273 74.00919 68.20595 70.56293 68.51213
[8] 66.02802 71.38653 71.75622 70.63410 74.26216 71.88111 71.05822
[15] 72.67192 74.25330 67.60411 72.37217 69.10636 67.26582
> colSums(tmp5)
[1] 1114.5537 714.3881 714.0273 740.0919 682.0595 705.6293 685.1213
[8] 660.2802 713.8653 717.5622 706.3410 742.6216 718.8111 710.5822
[15] 726.7192 742.5330 676.0411 723.7217 691.0636 672.6582
> colVars(tmp5)
[1] 15243.63075 76.44940 42.22940 87.63880 64.61296 88.99633
[7] 42.00669 76.04536 69.01893 86.52064 60.89313 150.53359
[13] 44.78934 60.78708 65.77058 53.40198 37.09116 113.06228
[19] 92.50703 20.78868
> colSd(tmp5)
[1] 123.465099 8.743535 6.498416 9.361560 8.038218 9.433787
[7] 6.481257 8.720399 8.307763 9.301647 7.803405 12.269213
[13] 6.692484 7.796607 8.109906 7.307665 6.090251 10.633075
[19] 9.618057 4.559460
> colMax(tmp5)
[1] 461.84716 85.51680 81.46932 82.91846 84.29575 90.64650 79.05086
[8] 80.78709 85.39300 85.95018 87.24925 94.25024 85.95312 82.19368
[15] 85.90629 87.31173 75.42287 91.80790 87.03460 75.46127
> colMin(tmp5)
[1] 59.16511 60.82103 62.00953 55.26292 57.90644 58.21689 58.63176 54.55436
[9] 59.48954 55.99499 59.94198 58.38196 63.56039 58.92710 63.19176 66.45926
[17] 59.45311 57.38774 53.90864 57.91493
>
>
> ### 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] 91.82732 68.56688 71.83287 70.85601 71.76803 68.35275 70.33809 73.38328
[9] NA 72.71029
> rowSums(tmp5)
[1] 1836.546 1371.338 1436.657 1417.120 1435.361 1367.055 1406.762 1467.666
[9] NA 1454.206
> rowVars(tmp5)
[1] 7651.44055 30.44858 71.00069 90.40302 69.01895 73.73381
[7] 45.61938 98.20428 56.17977 94.75740
> rowSd(tmp5)
[1] 87.472513 5.518024 8.426190 9.508051 8.307764 8.586840 6.754212
[8] 9.909807 7.495317 9.734341
> rowMax(tmp5)
[1] 461.84716 77.87741 86.11454 90.20033 90.64650 85.95312 87.24925
[8] 87.03460 NA 94.25024
> rowMin(tmp5)
[1] 58.59916 58.21689 57.38774 54.55436 55.26292 55.99499 58.63176 58.69072
[9] NA 57.91493
>
> colMeans(tmp5)
[1] 111.45537 71.43881 71.40273 74.00919 68.20595 70.56293 68.51213
[8] NA 71.38653 71.75622 70.63410 74.26216 71.88111 71.05822
[15] 72.67192 74.25330 67.60411 72.37217 69.10636 67.26582
> colSums(tmp5)
[1] 1114.5537 714.3881 714.0273 740.0919 682.0595 705.6293 685.1213
[8] NA 713.8653 717.5622 706.3410 742.6216 718.8111 710.5822
[15] 726.7192 742.5330 676.0411 723.7217 691.0636 672.6582
> colVars(tmp5)
[1] 15243.63075 76.44940 42.22940 87.63880 64.61296 88.99633
[7] 42.00669 NA 69.01893 86.52064 60.89313 150.53359
[13] 44.78934 60.78708 65.77058 53.40198 37.09116 113.06228
[19] 92.50703 20.78868
> colSd(tmp5)
[1] 123.465099 8.743535 6.498416 9.361560 8.038218 9.433787
[7] 6.481257 NA 8.307763 9.301647 7.803405 12.269213
[13] 6.692484 7.796607 8.109906 7.307665 6.090251 10.633075
[19] 9.618057 4.559460
> colMax(tmp5)
[1] 461.84716 85.51680 81.46932 82.91846 84.29575 90.64650 79.05086
[8] NA 85.39300 85.95018 87.24925 94.25024 85.95312 82.19368
[15] 85.90629 87.31173 75.42287 91.80790 87.03460 75.46127
> colMin(tmp5)
[1] 59.16511 60.82103 62.00953 55.26292 57.90644 58.21689 58.63176 NA
[9] 59.48954 55.99499 59.94198 58.38196 63.56039 58.92710 63.19176 66.45926
[17] 59.45311 57.38774 53.90864 57.91493
>
> Max(tmp5,na.rm=TRUE)
[1] 461.8472
> Min(tmp5,na.rm=TRUE)
[1] 53.90864
> mean(tmp5,na.rm=TRUE)
[1] 72.84705
> Sum(tmp5,na.rm=TRUE)
[1] 14496.56
> Var(tmp5,na.rm=TRUE)
[1] 837.6191
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.82732 68.56688 71.83287 70.85601 71.76803 68.35275 70.33809 73.38328
[9] 68.62378 72.71029
> rowSums(tmp5,na.rm=TRUE)
[1] 1836.546 1371.338 1436.657 1417.120 1435.361 1367.055 1406.762 1467.666
[9] 1303.852 1454.206
> rowVars(tmp5,na.rm=TRUE)
[1] 7651.44055 30.44858 71.00069 90.40302 69.01895 73.73381
[7] 45.61938 98.20428 56.17977 94.75740
> rowSd(tmp5,na.rm=TRUE)
[1] 87.472513 5.518024 8.426190 9.508051 8.307764 8.586840 6.754212
[8] 9.909807 7.495317 9.734341
> rowMax(tmp5,na.rm=TRUE)
[1] 461.84716 77.87741 86.11454 90.20033 90.64650 85.95312 87.24925
[8] 87.03460 81.40322 94.25024
> rowMin(tmp5,na.rm=TRUE)
[1] 58.59916 58.21689 57.38774 54.55436 55.26292 55.99499 58.63176 58.69072
[9] 53.90864 57.91493
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.45537 71.43881 71.40273 74.00919 68.20595 70.56293 68.51213
[8] 66.46341 71.38653 71.75622 70.63410 74.26216 71.88111 71.05822
[15] 72.67192 74.25330 67.60411 72.37217 69.10636 67.26582
> colSums(tmp5,na.rm=TRUE)
[1] 1114.5537 714.3881 714.0273 740.0919 682.0595 705.6293 685.1213
[8] 598.1707 713.8653 717.5622 706.3410 742.6216 718.8111 710.5822
[15] 726.7192 742.5330 676.0411 723.7217 691.0636 672.6582
> colVars(tmp5,na.rm=TRUE)
[1] 15243.63075 76.44940 42.22940 87.63880 64.61296 88.99633
[7] 42.00669 83.41844 69.01893 86.52064 60.89313 150.53359
[13] 44.78934 60.78708 65.77058 53.40198 37.09116 113.06228
[19] 92.50703 20.78868
> colSd(tmp5,na.rm=TRUE)
[1] 123.465099 8.743535 6.498416 9.361560 8.038218 9.433787
[7] 6.481257 9.133369 8.307763 9.301647 7.803405 12.269213
[13] 6.692484 7.796607 8.109906 7.307665 6.090251 10.633075
[19] 9.618057 4.559460
> colMax(tmp5,na.rm=TRUE)
[1] 461.84716 85.51680 81.46932 82.91846 84.29575 90.64650 79.05086
[8] 80.78709 85.39300 85.95018 87.24925 94.25024 85.95312 82.19368
[15] 85.90629 87.31173 75.42287 91.80790 87.03460 75.46127
> colMin(tmp5,na.rm=TRUE)
[1] 59.16511 60.82103 62.00953 55.26292 57.90644 58.21689 58.63176 54.55436
[9] 59.48954 55.99499 59.94198 58.38196 63.56039 58.92710 63.19176 66.45926
[17] 59.45311 57.38774 53.90864 57.91493
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.82732 68.56688 71.83287 70.85601 71.76803 68.35275 70.33809 73.38328
[9] NaN 72.71029
> rowSums(tmp5,na.rm=TRUE)
[1] 1836.546 1371.338 1436.657 1417.120 1435.361 1367.055 1406.762 1467.666
[9] 0.000 1454.206
> rowVars(tmp5,na.rm=TRUE)
[1] 7651.44055 30.44858 71.00069 90.40302 69.01895 73.73381
[7] 45.61938 98.20428 NA 94.75740
> rowSd(tmp5,na.rm=TRUE)
[1] 87.472513 5.518024 8.426190 9.508051 8.307764 8.586840 6.754212
[8] 9.909807 NA 9.734341
> rowMax(tmp5,na.rm=TRUE)
[1] 461.84716 77.87741 86.11454 90.20033 90.64650 85.95312 87.24925
[8] 87.03460 NA 94.25024
> rowMin(tmp5,na.rm=TRUE)
[1] 58.59916 58.21689 57.38774 54.55436 55.26292 55.99499 58.63176 58.69072
[9] NA 57.91493
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.10123 71.57092 71.01032 73.27161 68.41854 71.35023 68.74662
[8] NaN 72.56773 72.88821 69.84135 75.96919 71.44062 71.51289
[15] 71.70178 75.11931 67.82594 72.90659 70.79500 66.35521
> colSums(tmp5,na.rm=TRUE)
[1] 1044.9111 644.1383 639.0929 659.4445 615.7668 642.1520 618.7196
[8] 0.0000 653.1096 655.9939 628.5722 683.7227 642.9656 643.6160
[15] 645.3160 676.0738 610.4335 656.1593 637.1550 597.1969
> colVars(tmp5,na.rm=TRUE)
[1] 16906.26433 85.80924 45.77580 92.47327 72.18116 93.14768
[7] 46.63894 NA 61.94975 82.92004 61.43468 136.56832
[13] 48.20519 66.05976 63.40363 51.64012 41.17395 123.98202
[19] 71.99113 14.05873
> colSd(tmp5,na.rm=TRUE)
[1] 130.024091 9.263328 6.765781 9.616302 8.495950 9.651305
[7] 6.829271 NA 7.870817 9.106044 7.838028 11.686245
[13] 6.942996 8.127715 7.962640 7.186106 6.416693 11.134721
[19] 8.484759 3.749497
> colMax(tmp5,na.rm=TRUE)
[1] 461.84716 85.51680 81.46932 82.91846 84.29575 90.64650 79.05086
[8] -Inf 85.39300 85.95018 87.24925 94.25024 85.95312 82.19368
[15] 85.90629 87.31173 75.42287 91.80790 87.03460 70.92180
> colMin(tmp5,na.rm=TRUE)
[1] 59.16511 60.82103 62.00953 55.26292 57.90644 58.21689 58.63176 Inf
[9] 59.48954 55.99499 59.94198 58.38196 63.56039 58.92710 63.19176 69.06762
[17] 59.45311 57.38774 56.53063 57.91493
>
>
>
>
> 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] 210.7794 223.3877 216.6114 231.1309 254.4857 206.6923 260.2668 235.1892
[9] 276.2247 300.7858
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 210.7794 223.3877 216.6114 231.1309 254.4857 206.6923 260.2668 235.1892
[9] 276.2247 300.7858
>
>
>
> 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 1.563194e-13 -1.705303e-13 -3.410605e-13 -1.136868e-13
[6] 0.000000e+00 -1.136868e-13 0.000000e+00 5.684342e-14 0.000000e+00
[11] 5.684342e-14 5.684342e-14 0.000000e+00 2.842171e-14 4.263256e-14
[16] -8.526513e-14 -7.105427e-14 -5.684342e-14 5.684342e-14 1.421085e-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)
+ }
3 16
3 18
2 17
4 1
2 7
9 16
5 1
10 10
3 11
1 3
8 14
8 9
5 18
7 19
9 5
9 3
7 5
5 14
4 2
2 4
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] 2.949475
> Min(tmp)
[1] -2.634398
> mean(tmp)
[1] -0.07528536
> Sum(tmp)
[1] -7.528536
> Var(tmp)
[1] 1.00842
>
> rowMeans(tmp)
[1] -0.07528536
> rowSums(tmp)
[1] -7.528536
> rowVars(tmp)
[1] 1.00842
> rowSd(tmp)
[1] 1.004201
> rowMax(tmp)
[1] 2.949475
> rowMin(tmp)
[1] -2.634398
>
> colMeans(tmp)
[1] -0.54766421 0.83137016 -0.73763805 0.08490261 0.48570490 1.05049291
[7] 2.65358680 -0.09919624 -0.31063605 0.40023011 -0.93253221 2.94947516
[13] -0.26158794 -0.63785572 -0.70985084 -1.53086312 -0.61259020 0.85843509
[19] -1.45369842 -0.99585260 0.01441412 0.84344811 -0.06769866 1.06498162
[25] 0.76253976 0.65758416 0.73223791 -0.06311575 0.03394751 0.06113435
[31] -0.63503555 2.46013896 -2.63439758 -0.98796452 0.86195488 -1.68657342
[37] 0.81480962 -0.16253649 -1.55826472 0.69811026 0.18202107 -0.74574805
[43] -0.47365845 0.86994128 -0.68066782 0.97149487 0.92852196 -0.39452160
[49] -0.75628374 -0.10822601 -2.55795939 -0.22310300 -0.78332693 1.31241750
[55] -0.17716600 0.79607423 -2.37297509 0.28940231 -1.13591589 -1.08100351
[61] -0.18943668 0.24460771 0.08545279 -0.89475400 -0.52225305 0.99870118
[67] 0.48099777 -0.24674806 0.85763414 0.09344192 -0.53942430 0.15373438
[73] 0.80951616 1.94232723 0.89984386 -0.33912939 -0.80528499 0.60056087
[79] 0.20769506 -1.62850573 -0.52794791 -0.42748182 -0.83487388 -1.37141482
[85] 0.10445430 0.21841351 -0.88834469 -0.16439059 -0.38735263 0.16772263
[91] -0.16745962 0.19911992 0.98977522 1.24802876 0.31016128 -0.80982065
[97] -2.01287563 -1.21004131 0.44990164 -0.17635101
> colSums(tmp)
[1] -0.54766421 0.83137016 -0.73763805 0.08490261 0.48570490 1.05049291
[7] 2.65358680 -0.09919624 -0.31063605 0.40023011 -0.93253221 2.94947516
[13] -0.26158794 -0.63785572 -0.70985084 -1.53086312 -0.61259020 0.85843509
[19] -1.45369842 -0.99585260 0.01441412 0.84344811 -0.06769866 1.06498162
[25] 0.76253976 0.65758416 0.73223791 -0.06311575 0.03394751 0.06113435
[31] -0.63503555 2.46013896 -2.63439758 -0.98796452 0.86195488 -1.68657342
[37] 0.81480962 -0.16253649 -1.55826472 0.69811026 0.18202107 -0.74574805
[43] -0.47365845 0.86994128 -0.68066782 0.97149487 0.92852196 -0.39452160
[49] -0.75628374 -0.10822601 -2.55795939 -0.22310300 -0.78332693 1.31241750
[55] -0.17716600 0.79607423 -2.37297509 0.28940231 -1.13591589 -1.08100351
[61] -0.18943668 0.24460771 0.08545279 -0.89475400 -0.52225305 0.99870118
[67] 0.48099777 -0.24674806 0.85763414 0.09344192 -0.53942430 0.15373438
[73] 0.80951616 1.94232723 0.89984386 -0.33912939 -0.80528499 0.60056087
[79] 0.20769506 -1.62850573 -0.52794791 -0.42748182 -0.83487388 -1.37141482
[85] 0.10445430 0.21841351 -0.88834469 -0.16439059 -0.38735263 0.16772263
[91] -0.16745962 0.19911992 0.98977522 1.24802876 0.31016128 -0.80982065
[97] -2.01287563 -1.21004131 0.44990164 -0.17635101
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] -0.54766421 0.83137016 -0.73763805 0.08490261 0.48570490 1.05049291
[7] 2.65358680 -0.09919624 -0.31063605 0.40023011 -0.93253221 2.94947516
[13] -0.26158794 -0.63785572 -0.70985084 -1.53086312 -0.61259020 0.85843509
[19] -1.45369842 -0.99585260 0.01441412 0.84344811 -0.06769866 1.06498162
[25] 0.76253976 0.65758416 0.73223791 -0.06311575 0.03394751 0.06113435
[31] -0.63503555 2.46013896 -2.63439758 -0.98796452 0.86195488 -1.68657342
[37] 0.81480962 -0.16253649 -1.55826472 0.69811026 0.18202107 -0.74574805
[43] -0.47365845 0.86994128 -0.68066782 0.97149487 0.92852196 -0.39452160
[49] -0.75628374 -0.10822601 -2.55795939 -0.22310300 -0.78332693 1.31241750
[55] -0.17716600 0.79607423 -2.37297509 0.28940231 -1.13591589 -1.08100351
[61] -0.18943668 0.24460771 0.08545279 -0.89475400 -0.52225305 0.99870118
[67] 0.48099777 -0.24674806 0.85763414 0.09344192 -0.53942430 0.15373438
[73] 0.80951616 1.94232723 0.89984386 -0.33912939 -0.80528499 0.60056087
[79] 0.20769506 -1.62850573 -0.52794791 -0.42748182 -0.83487388 -1.37141482
[85] 0.10445430 0.21841351 -0.88834469 -0.16439059 -0.38735263 0.16772263
[91] -0.16745962 0.19911992 0.98977522 1.24802876 0.31016128 -0.80982065
[97] -2.01287563 -1.21004131 0.44990164 -0.17635101
> colMin(tmp)
[1] -0.54766421 0.83137016 -0.73763805 0.08490261 0.48570490 1.05049291
[7] 2.65358680 -0.09919624 -0.31063605 0.40023011 -0.93253221 2.94947516
[13] -0.26158794 -0.63785572 -0.70985084 -1.53086312 -0.61259020 0.85843509
[19] -1.45369842 -0.99585260 0.01441412 0.84344811 -0.06769866 1.06498162
[25] 0.76253976 0.65758416 0.73223791 -0.06311575 0.03394751 0.06113435
[31] -0.63503555 2.46013896 -2.63439758 -0.98796452 0.86195488 -1.68657342
[37] 0.81480962 -0.16253649 -1.55826472 0.69811026 0.18202107 -0.74574805
[43] -0.47365845 0.86994128 -0.68066782 0.97149487 0.92852196 -0.39452160
[49] -0.75628374 -0.10822601 -2.55795939 -0.22310300 -0.78332693 1.31241750
[55] -0.17716600 0.79607423 -2.37297509 0.28940231 -1.13591589 -1.08100351
[61] -0.18943668 0.24460771 0.08545279 -0.89475400 -0.52225305 0.99870118
[67] 0.48099777 -0.24674806 0.85763414 0.09344192 -0.53942430 0.15373438
[73] 0.80951616 1.94232723 0.89984386 -0.33912939 -0.80528499 0.60056087
[79] 0.20769506 -1.62850573 -0.52794791 -0.42748182 -0.83487388 -1.37141482
[85] 0.10445430 0.21841351 -0.88834469 -0.16439059 -0.38735263 0.16772263
[91] -0.16745962 0.19911992 0.98977522 1.24802876 0.31016128 -0.80982065
[97] -2.01287563 -1.21004131 0.44990164 -0.17635101
> colMedians(tmp)
[1] -0.54766421 0.83137016 -0.73763805 0.08490261 0.48570490 1.05049291
[7] 2.65358680 -0.09919624 -0.31063605 0.40023011 -0.93253221 2.94947516
[13] -0.26158794 -0.63785572 -0.70985084 -1.53086312 -0.61259020 0.85843509
[19] -1.45369842 -0.99585260 0.01441412 0.84344811 -0.06769866 1.06498162
[25] 0.76253976 0.65758416 0.73223791 -0.06311575 0.03394751 0.06113435
[31] -0.63503555 2.46013896 -2.63439758 -0.98796452 0.86195488 -1.68657342
[37] 0.81480962 -0.16253649 -1.55826472 0.69811026 0.18202107 -0.74574805
[43] -0.47365845 0.86994128 -0.68066782 0.97149487 0.92852196 -0.39452160
[49] -0.75628374 -0.10822601 -2.55795939 -0.22310300 -0.78332693 1.31241750
[55] -0.17716600 0.79607423 -2.37297509 0.28940231 -1.13591589 -1.08100351
[61] -0.18943668 0.24460771 0.08545279 -0.89475400 -0.52225305 0.99870118
[67] 0.48099777 -0.24674806 0.85763414 0.09344192 -0.53942430 0.15373438
[73] 0.80951616 1.94232723 0.89984386 -0.33912939 -0.80528499 0.60056087
[79] 0.20769506 -1.62850573 -0.52794791 -0.42748182 -0.83487388 -1.37141482
[85] 0.10445430 0.21841351 -0.88834469 -0.16439059 -0.38735263 0.16772263
[91] -0.16745962 0.19911992 0.98977522 1.24802876 0.31016128 -0.80982065
[97] -2.01287563 -1.21004131 0.44990164 -0.17635101
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.5476642 0.8313702 -0.7376381 0.08490261 0.4857049 1.050493 2.653587
[2,] -0.5476642 0.8313702 -0.7376381 0.08490261 0.4857049 1.050493 2.653587
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.09919624 -0.310636 0.4002301 -0.9325322 2.949475 -0.2615879 -0.6378557
[2,] -0.09919624 -0.310636 0.4002301 -0.9325322 2.949475 -0.2615879 -0.6378557
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.7098508 -1.530863 -0.6125902 0.8584351 -1.453698 -0.9958526 0.01441412
[2,] -0.7098508 -1.530863 -0.6125902 0.8584351 -1.453698 -0.9958526 0.01441412
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.8434481 -0.06769866 1.064982 0.7625398 0.6575842 0.7322379 -0.06311575
[2,] 0.8434481 -0.06769866 1.064982 0.7625398 0.6575842 0.7322379 -0.06311575
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.03394751 0.06113435 -0.6350356 2.460139 -2.634398 -0.9879645 0.8619549
[2,] 0.03394751 0.06113435 -0.6350356 2.460139 -2.634398 -0.9879645 0.8619549
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.686573 0.8148096 -0.1625365 -1.558265 0.6981103 0.1820211 -0.7457481
[2,] -1.686573 0.8148096 -0.1625365 -1.558265 0.6981103 0.1820211 -0.7457481
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.4736584 0.8699413 -0.6806678 0.9714949 0.928522 -0.3945216 -0.7562837
[2,] -0.4736584 0.8699413 -0.6806678 0.9714949 0.928522 -0.3945216 -0.7562837
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.108226 -2.557959 -0.223103 -0.7833269 1.312418 -0.177166 0.7960742
[2,] -0.108226 -2.557959 -0.223103 -0.7833269 1.312418 -0.177166 0.7960742
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -2.372975 0.2894023 -1.135916 -1.081004 -0.1894367 0.2446077 0.08545279
[2,] -2.372975 0.2894023 -1.135916 -1.081004 -0.1894367 0.2446077 0.08545279
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.894754 -0.522253 0.9987012 0.4809978 -0.2467481 0.8576341 0.09344192
[2,] -0.894754 -0.522253 0.9987012 0.4809978 -0.2467481 0.8576341 0.09344192
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.5394243 0.1537344 0.8095162 1.942327 0.8998439 -0.3391294 -0.805285
[2,] -0.5394243 0.1537344 0.8095162 1.942327 0.8998439 -0.3391294 -0.805285
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.6005609 0.2076951 -1.628506 -0.5279479 -0.4274818 -0.8348739 -1.371415
[2,] 0.6005609 0.2076951 -1.628506 -0.5279479 -0.4274818 -0.8348739 -1.371415
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.1044543 0.2184135 -0.8883447 -0.1643906 -0.3873526 0.1677226 -0.1674596
[2,] 0.1044543 0.2184135 -0.8883447 -0.1643906 -0.3873526 0.1677226 -0.1674596
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.1991199 0.9897752 1.248029 0.3101613 -0.8098206 -2.012876 -1.210041
[2,] 0.1991199 0.9897752 1.248029 0.3101613 -0.8098206 -2.012876 -1.210041
[,99] [,100]
[1,] 0.4499016 -0.176351
[2,] 0.4499016 -0.176351
>
>
> Max(tmp2)
[1] 3.506565
> Min(tmp2)
[1] -2.054367
> mean(tmp2)
[1] 0.04719301
> Sum(tmp2)
[1] 4.719301
> Var(tmp2)
[1] 0.8679658
>
> rowMeans(tmp2)
[1] -0.029225940 -0.236040936 0.806035894 -0.489103741 -1.191678397
[6] -0.280075442 -0.299853400 1.295738844 -1.293259195 -0.282703069
[11] 1.389578337 0.711734193 -0.031091997 -0.644394228 -0.192572206
[16] 0.615766022 0.486770223 0.195129743 0.851619242 0.763210284
[21] 0.356321734 -0.935491285 -0.372827578 0.645847763 -0.848528901
[26] -0.736363322 -0.015210339 -0.339872218 -1.236018194 -0.405250110
[31] 0.213584931 0.360406568 0.245586828 -0.415616780 -0.038707339
[36] 1.100776124 -0.917845823 0.905780326 -0.222794042 -0.688014089
[41] 0.482033301 -0.067070583 0.702484137 -1.297408808 -0.845192243
[46] -0.524284859 0.598460739 0.520009550 0.329569477 0.741309639
[51] 0.300024989 -0.101102802 1.045247761 0.006985369 -2.054367436
[56] -0.628967784 -0.027093991 -1.000515429 0.708662479 0.146891001
[61] -0.209840898 -0.211957162 0.221635486 -0.810245804 2.534195070
[66] -0.984191618 0.514985631 -1.748930860 -0.714582758 -0.095946045
[71] 1.326765994 -1.296640398 0.636665881 -0.774672639 -0.258005716
[76] -1.705386123 2.345276056 -0.096261388 0.500488853 0.730753308
[81] 0.203534094 1.731247023 1.183255725 -1.150353311 3.506565085
[86] -0.262948525 -1.035770982 0.971262483 -0.306967849 -0.541680591
[91] 0.655918068 -1.195001026 -0.564807610 1.591753375 0.066899250
[96] 0.047395754 -0.497196323 0.643863684 1.788133468 0.143071440
> rowSums(tmp2)
[1] -0.029225940 -0.236040936 0.806035894 -0.489103741 -1.191678397
[6] -0.280075442 -0.299853400 1.295738844 -1.293259195 -0.282703069
[11] 1.389578337 0.711734193 -0.031091997 -0.644394228 -0.192572206
[16] 0.615766022 0.486770223 0.195129743 0.851619242 0.763210284
[21] 0.356321734 -0.935491285 -0.372827578 0.645847763 -0.848528901
[26] -0.736363322 -0.015210339 -0.339872218 -1.236018194 -0.405250110
[31] 0.213584931 0.360406568 0.245586828 -0.415616780 -0.038707339
[36] 1.100776124 -0.917845823 0.905780326 -0.222794042 -0.688014089
[41] 0.482033301 -0.067070583 0.702484137 -1.297408808 -0.845192243
[46] -0.524284859 0.598460739 0.520009550 0.329569477 0.741309639
[51] 0.300024989 -0.101102802 1.045247761 0.006985369 -2.054367436
[56] -0.628967784 -0.027093991 -1.000515429 0.708662479 0.146891001
[61] -0.209840898 -0.211957162 0.221635486 -0.810245804 2.534195070
[66] -0.984191618 0.514985631 -1.748930860 -0.714582758 -0.095946045
[71] 1.326765994 -1.296640398 0.636665881 -0.774672639 -0.258005716
[76] -1.705386123 2.345276056 -0.096261388 0.500488853 0.730753308
[81] 0.203534094 1.731247023 1.183255725 -1.150353311 3.506565085
[86] -0.262948525 -1.035770982 0.971262483 -0.306967849 -0.541680591
[91] 0.655918068 -1.195001026 -0.564807610 1.591753375 0.066899250
[96] 0.047395754 -0.497196323 0.643863684 1.788133468 0.143071440
> 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] -0.029225940 -0.236040936 0.806035894 -0.489103741 -1.191678397
[6] -0.280075442 -0.299853400 1.295738844 -1.293259195 -0.282703069
[11] 1.389578337 0.711734193 -0.031091997 -0.644394228 -0.192572206
[16] 0.615766022 0.486770223 0.195129743 0.851619242 0.763210284
[21] 0.356321734 -0.935491285 -0.372827578 0.645847763 -0.848528901
[26] -0.736363322 -0.015210339 -0.339872218 -1.236018194 -0.405250110
[31] 0.213584931 0.360406568 0.245586828 -0.415616780 -0.038707339
[36] 1.100776124 -0.917845823 0.905780326 -0.222794042 -0.688014089
[41] 0.482033301 -0.067070583 0.702484137 -1.297408808 -0.845192243
[46] -0.524284859 0.598460739 0.520009550 0.329569477 0.741309639
[51] 0.300024989 -0.101102802 1.045247761 0.006985369 -2.054367436
[56] -0.628967784 -0.027093991 -1.000515429 0.708662479 0.146891001
[61] -0.209840898 -0.211957162 0.221635486 -0.810245804 2.534195070
[66] -0.984191618 0.514985631 -1.748930860 -0.714582758 -0.095946045
[71] 1.326765994 -1.296640398 0.636665881 -0.774672639 -0.258005716
[76] -1.705386123 2.345276056 -0.096261388 0.500488853 0.730753308
[81] 0.203534094 1.731247023 1.183255725 -1.150353311 3.506565085
[86] -0.262948525 -1.035770982 0.971262483 -0.306967849 -0.541680591
[91] 0.655918068 -1.195001026 -0.564807610 1.591753375 0.066899250
[96] 0.047395754 -0.497196323 0.643863684 1.788133468 0.143071440
> rowMin(tmp2)
[1] -0.029225940 -0.236040936 0.806035894 -0.489103741 -1.191678397
[6] -0.280075442 -0.299853400 1.295738844 -1.293259195 -0.282703069
[11] 1.389578337 0.711734193 -0.031091997 -0.644394228 -0.192572206
[16] 0.615766022 0.486770223 0.195129743 0.851619242 0.763210284
[21] 0.356321734 -0.935491285 -0.372827578 0.645847763 -0.848528901
[26] -0.736363322 -0.015210339 -0.339872218 -1.236018194 -0.405250110
[31] 0.213584931 0.360406568 0.245586828 -0.415616780 -0.038707339
[36] 1.100776124 -0.917845823 0.905780326 -0.222794042 -0.688014089
[41] 0.482033301 -0.067070583 0.702484137 -1.297408808 -0.845192243
[46] -0.524284859 0.598460739 0.520009550 0.329569477 0.741309639
[51] 0.300024989 -0.101102802 1.045247761 0.006985369 -2.054367436
[56] -0.628967784 -0.027093991 -1.000515429 0.708662479 0.146891001
[61] -0.209840898 -0.211957162 0.221635486 -0.810245804 2.534195070
[66] -0.984191618 0.514985631 -1.748930860 -0.714582758 -0.095946045
[71] 1.326765994 -1.296640398 0.636665881 -0.774672639 -0.258005716
[76] -1.705386123 2.345276056 -0.096261388 0.500488853 0.730753308
[81] 0.203534094 1.731247023 1.183255725 -1.150353311 3.506565085
[86] -0.262948525 -1.035770982 0.971262483 -0.306967849 -0.541680591
[91] 0.655918068 -1.195001026 -0.564807610 1.591753375 0.066899250
[96] 0.047395754 -0.497196323 0.643863684 1.788133468 0.143071440
>
> colMeans(tmp2)
[1] 0.04719301
> colSums(tmp2)
[1] 4.719301
> colVars(tmp2)
[1] 0.8679658
> colSd(tmp2)
[1] 0.9316468
> colMax(tmp2)
[1] 3.506565
> colMin(tmp2)
[1] -2.054367
> colMedians(tmp2)
[1] -0.03015897
> colRanges(tmp2)
[,1]
[1,] -2.054367
[2,] 3.506565
>
> 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] -2.6852221 -3.5123413 4.5101162 2.8841053 -0.5055319 0.2984685
[7] 0.6263562 -6.2773569 -4.1308423 2.4285314
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.6331093
[2,] -1.3256364
[3,] -0.2887796
[4,] 0.6820880
[5,] 1.4732753
>
> rowApply(tmp,sum)
[1] -1.5207979 -2.6685012 0.5923065 -8.5555078 4.3616686 2.9000000
[7] 1.6855165 -4.3314877 2.2976021 -1.1245159
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 2 10 1 4 3 6 6 10 7 1
[2,] 4 8 5 2 5 1 7 8 4 3
[3,] 3 3 9 9 10 9 5 9 6 5
[4,] 1 7 7 6 7 10 10 7 8 4
[5,] 5 6 4 5 8 8 3 4 5 8
[6,] 7 1 8 8 6 5 2 6 3 10
[7,] 6 5 6 10 4 7 9 2 10 2
[8,] 8 9 2 1 1 3 1 5 2 7
[9,] 9 4 3 3 2 4 8 3 1 6
[10,] 10 2 10 7 9 2 4 1 9 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.6162107 -0.7067806 -2.2254591 4.4667423 -2.7439955 -1.5719335
[7] 1.9919966 -3.9288521 5.6087685 -3.5358852 3.5096332 2.1860799
[13] 0.9932990 -1.8588254 -1.7956197 0.7952642 -0.5590971 2.4081313
[19] 4.3325053 1.4998166
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.33339805
[2,] -0.73522067
[3,] -0.05153047
[4,] 0.18206862
[5,] 0.32186984
>
> rowApply(tmp,sum)
[1] 3.4706385 7.0217894 0.9436081 -0.5708596 -3.6155986
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 2 13 12 12
[2,] 10 6 9 17 4
[3,] 9 14 1 10 11
[4,] 17 18 7 19 16
[5,] 4 5 10 2 13
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.73522067 0.16808697 -0.03037946 1.02547781 -0.92622355 -1.2550700
[2,] -1.33339805 -0.37041109 0.79568077 1.54761656 -0.43135638 0.9006842
[3,] 0.32186984 0.05280659 -2.85033474 -0.07426961 0.08683344 0.6103176
[4,] 0.18206862 0.62532487 0.06986169 1.27251837 -1.66037381 0.2966201
[5,] -0.05153047 -1.18258799 -0.21028734 0.69539914 0.18712479 -2.1244854
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.4669702 -1.2155125 2.353068 0.5735320 1.1448882 0.7163146
[2,] 1.5423226 -1.9198575 1.485614 -1.1424824 2.1335896 0.4800735
[3,] -0.4647771 0.7044298 1.701724 -0.1554495 -0.4876131 0.8263038
[4,] 0.1626113 0.1937743 1.421978 -2.1616250 -0.3863084 -0.1302845
[5,] -0.7151304 -1.6916863 -1.353616 -0.6498603 1.1050769 0.2936724
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.05509216 -1.2697675 -0.82913950 0.2392993 0.6011503 -0.11556065
[2,] -0.25365364 0.6922967 -0.03231966 0.7452751 0.5790151 0.03456514
[3,] 0.26573741 0.2488751 -1.56053302 0.3623995 -1.1297576 1.23183174
[4,] 0.26259743 -1.1203934 -0.22933195 -0.3141322 -0.3454367 0.02506032
[5,] 0.77370992 -0.4098363 0.85570447 -0.2375775 -0.2640682 1.23223476
[,19] [,20]
[1,] 0.79427921 0.8195378
[2,] 2.06645522 -0.4979207
[3,] -0.00328829 1.2565024
[4,] 0.88344447 0.3811666
[5,] 0.59161465 -0.4594696
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 1.657201 -0.4852663 0.5928942 -0.3479973 -0.4498446 1.209066 -0.2744235
col8 col9 col10 col11 col12 col13 col14
row1 0.8793397 -0.6465412 0.3395428 -0.9503208 0.9974307 -0.7740555 0.8153249
col15 col16 col17 col18 col19 col20
row1 -0.4974729 -0.2969137 -0.7534366 -1.348207 -0.34719 -0.2457591
> tmp[,"col10"]
col10
row1 0.3395428
row2 0.6271461
row3 1.5153614
row4 0.1682191
row5 -0.2854076
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 1.6572012 -0.4852663 0.5928942 -0.3479973 -0.4498446 1.2090661
row5 -0.2949942 -2.2119814 -0.8161395 -0.4948439 0.1573544 0.3866217
col7 col8 col9 col10 col11 col12
row1 -0.2744235 0.8793397 -0.6465412 0.3395428 -0.9503208 0.99743069
row5 -0.2788412 1.5807783 0.4562956 -0.2854076 0.4239054 0.02466946
col13 col14 col15 col16 col17 col18
row1 -0.7740555 0.8153249 -0.4974729 -0.2969137 -0.7534366 -1.3482066
row5 0.4273826 -0.8370304 -1.6269612 -0.1295914 -1.5869197 0.7518598
col19 col20
row1 -0.3471900 -0.24575908
row5 -0.2666134 0.06178087
> tmp[,c("col6","col20")]
col6 col20
row1 1.20906605 -0.24575908
row2 -0.85376597 -0.22535793
row3 0.08157172 1.57650003
row4 -0.37092315 0.56553278
row5 0.38662167 0.06178087
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.2090661 -0.24575908
row5 0.3866217 0.06178087
>
>
>
>
> 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 50.19641 50.07147 49.73319 50.86 48.52089 104.4266 47.43453 50.102
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.33024 50.54556 49.45093 48.25714 50.02011 49.79185 51.10961 49.04337
col17 col18 col19 col20
row1 49.33396 48.3033 50.45623 105.5024
> tmp[,"col10"]
col10
row1 50.54556
row2 30.05612
row3 30.52828
row4 30.33382
row5 50.45649
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.19641 50.07147 49.73319 50.86000 48.52089 104.4266 47.43453 50.10200
row5 51.98181 49.81700 49.77157 52.15725 50.42558 103.9127 49.74033 50.92579
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.33024 50.54556 49.45093 48.25714 50.02011 49.79185 51.10961 49.04337
row5 48.87669 50.45649 51.88381 49.92246 50.78227 48.56496 49.70673 48.04322
col17 col18 col19 col20
row1 49.33396 48.30330 50.45623 105.5024
row5 49.34549 49.98154 50.12873 103.1057
> tmp[,c("col6","col20")]
col6 col20
row1 104.42658 105.50244
row2 74.82737 74.89943
row3 74.52620 76.02124
row4 75.24535 76.55143
row5 103.91272 103.10567
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.4266 105.5024
row5 103.9127 103.1057
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.4266 105.5024
row5 103.9127 103.1057
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.35155449
[2,] -0.70801114
[3,] 0.85242147
[4,] -0.46364535
[5,] 0.07335349
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.1209475 0.04706898
[2,] 1.1438021 -2.31377958
[3,] 0.4595337 1.63403086
[4,] -0.6334983 0.67939944
[5,] 0.6373118 -0.22699262
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.76912495 0.9413168
[2,] 1.69723506 1.3065980
[3,] 0.02424555 -0.4933154
[4,] -0.85730109 -0.7574883
[5,] 1.25546400 -0.1423217
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.769125
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.769125
[2,] 1.697235
>
>
>
> 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 0.4206648 0.09074227 -1.0026471 -0.6731617 -0.02900406 0.9491517
row1 -0.1069188 1.51820159 -0.9540459 -0.1579290 -1.18050104 0.2299676
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 0.2004055 -0.187907 -0.427251 0.48945049 0.8301043 -0.922640 -0.9080199
row1 -0.6417455 -1.556132 -1.636011 -0.09565804 -1.1523215 1.639589 1.9658160
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.79900176 -0.1009259 -1.1327208 0.7077924 -0.6833599 -0.2085422
row1 0.03620607 0.5700573 -0.6720269 0.8963566 0.6111853 0.6008651
[,20]
row3 -1.2226934
row1 0.9378874
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.633253 1.049936 -0.5094249 -0.04592207 -0.2104276 0.6309547 0.1113828
[,8] [,9] [,10]
row2 1.805978 -1.583401 1.15981
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.5894288 0.7650777 -0.3087594 -1.073463 -0.6817247 -0.854294 1.792186
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.5117747 0.6539438 -1.414691 0.8926792 -0.5136855 0.2803762 2.94752
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.4754738 0.1985501 -0.8238967 -0.2105768 0.4299898 1.884089
>
>
> 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: 0x2df6dbd0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd6d628e1af"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd6d6abd86d7"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd6d73f2a42e"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd6d8783853"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd6d696a6fa4"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd6d18de087d"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd6d46eb32f9"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd6d2683dc9"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd6d3547dfe4"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd6d323ac614"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd6d391806e6"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd6d7b9f13ba"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd6d7e83c00b"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd6d53386c61"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM12fd6d24f12e8b"
>
>
> ### 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: 0x2d293a30>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x2d293a30>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x2d293a30>
> rowMedians(tmp)
[1] 0.045716137 -0.145922842 -0.086219435 0.500703399 0.260619210
[6] 0.018815345 -0.279521758 0.410970012 0.630055114 -0.098532860
[11] 1.081060182 -0.126214265 0.190806259 0.193171982 -0.103760819
[16] -0.196291004 0.117008722 -0.265425059 -0.368366552 0.142961850
[21] -0.041704733 -0.127231548 -0.161305127 0.251385441 0.161854905
[26] -0.449743489 -0.404033269 -0.048985065 0.225948963 0.308329272
[31] 0.414594331 0.223526289 -0.220562608 -0.342445890 -0.124215547
[36] -0.050432339 0.420922936 0.036980670 -0.101011989 0.375877118
[41] -0.072232353 0.273993021 -0.226517802 0.034528934 -0.305308090
[46] 0.152877054 0.593199107 0.257853246 0.194969991 0.265894796
[51] -0.022425186 -0.766103265 0.843934842 -0.110538359 -0.191653513
[56] -0.166865973 -0.230210098 0.404196851 -0.006416793 -0.052917890
[61] 0.393429383 -0.073103637 0.324771865 0.356941669 0.066214417
[66] -0.168161760 -0.583583273 -0.041461700 0.093134542 0.113563316
[71] 0.419840928 -0.620769860 -0.237576195 0.393004863 -0.375108515
[76] -0.065165022 0.194999001 -0.330565551 0.049579498 0.754087865
[81] 0.320486700 0.164990879 -0.475620880 0.114321359 -0.177806153
[86] -0.248182872 -0.167544065 0.220186708 0.156998130 -0.162738727
[91] -0.053273179 0.385080349 0.147657256 0.504227592 0.289692147
[96] 0.098636079 0.400944282 0.174247351 0.453176422 -0.009342419
[101] 0.275661661 -0.244252550 0.153526954 -0.389183833 0.426690601
[106] -0.471477209 -0.332690693 -0.394315086 -0.428094176 -0.079936051
[111] -0.053957725 0.152894537 0.062954523 -0.377045159 0.255644737
[116] -0.463583764 -0.007019993 -0.273880403 0.296860267 -0.196254370
[121] 0.112076157 0.242057882 -1.462318167 0.381263428 0.281463576
[126] 0.542879452 -0.129101701 -0.013905109 0.473473435 0.363668434
[131] 0.420202331 0.231509053 0.019116774 -0.635695553 0.174669182
[136] -0.352801737 -0.471055914 -0.121186408 0.314017755 0.176657111
[141] -0.391027251 0.108354759 0.308266157 -0.353002574 0.291570162
[146] 0.069222112 0.035725178 0.425271827 -0.081163785 0.022039502
[151] -0.056393754 0.106334129 0.009785904 -0.183235061 0.342888981
[156] 0.412732250 0.117971257 0.070618714 0.113306370 0.323271986
[161] -0.151345807 -0.024857363 -0.675815419 -0.355751809 0.136208953
[166] 0.058524602 -0.389671308 0.508327375 0.133795909 -0.128719475
[171] -0.322794095 0.097283919 0.324814746 0.656171253 0.280235746
[176] 0.304963370 0.126688022 -0.256150680 -0.047812407 -0.084630338
[181] -0.236263049 0.450197638 -0.085073901 0.408396564 -0.384247270
[186] 0.272516044 0.558106295 0.110589498 -0.187335490 0.055268802
[191] -0.293047000 -0.021939178 -0.240938083 0.181984391 0.149630845
[196] 0.353270353 0.347244465 -0.508119103 0.148384459 0.011307253
[201] -0.232392549 -0.016231715 0.267344369 -0.634615370 -0.014839985
[206] -0.012545604 -0.243423183 0.249356722 0.131702085 0.430013731
[211] -0.113429183 0.421752560 -0.248880407 -0.316263652 -0.197633981
[216] 0.044353696 -0.260657167 0.127063813 -0.186821911 0.364556676
[221] -0.409062154 -0.434397239 -0.049246791 -0.668043422 0.288741254
[226] 0.075519804 -0.055583336 0.029735349 0.424879800 -0.038110502
>
> proc.time()
user system elapsed
1.953 0.817 2.796
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
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: 0xe143ff0>
> .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: 0xe143ff0>
> .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: 0xe143ff0>
> .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: 0xe143ff0>
> 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: 0xe0290e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xe0290e0>
> .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: 0xe0290e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xe0290e0>
> .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: 0xe0290e0>
> 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: 0xcfb0520>
> .Call("R_bm_AddColumn",P)
<pointer: 0xcfb0520>
> .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: 0xcfb0520>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0xcfb0520>
> .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: 0xcfb0520>
>
> .Call("R_bm_RowMode",P)
<pointer: 0xcfb0520>
> .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: 0xcfb0520>
>
> .Call("R_bm_ColMode",P)
<pointer: 0xcfb0520>
> .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: 0xcfb0520>
> 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: 0xc9b4720>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0xc9b4720>
> .Call("R_bm_AddColumn",P)
<pointer: 0xc9b4720>
> .Call("R_bm_AddColumn",P)
<pointer: 0xc9b4720>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile12fda7641ff4a5" "BufferedMatrixFile12fda79bce04a"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile12fda7641ff4a5" "BufferedMatrixFile12fda79bce04a"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0xd8a47d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xd8a47d0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0xd8a47d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0xd8a47d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0xd8a47d0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0xd8a47d0>
> .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: 0xd9abc90>
> .Call("R_bm_AddColumn",P)
<pointer: 0xd9abc90>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0xd9abc90>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0xd9abc90>
> 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: 0xec54110>
> .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: 0xec54110>
> rm(P)
>
> proc.time()
user system elapsed
0.328 0.038 0.352
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
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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
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Type 'demo()' for some demos, 'help()' for on-line help, or
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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
0.367 0.021 0.374