Ben Bolstad
| Snapshot Date: 2026-04-07 13:45 -0400 (Tue, 07 Apr 2026) |
| 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 -0400 (Wed, 29 Oct 2025) |
| Back to Build/check report for BioC 3.22: simplified long |
|
This page was generated on 2026-04-08 11:57 -0400 (Wed, 08 Apr 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" | 4897 |
| 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 | | ||||||||
| See other builds for BufferedMatrix in R Universe. | ||||||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.74.0 |
| Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.74.0.tar.gz |
| StartedAt: 2026-04-07 21:37:38 -0400 (Tue, 07 Apr 2026) |
| EndedAt: 2026-04-07 21:38:02 -0400 (Tue, 07 Apr 2026) |
| EllapsedTime: 24.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.74.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.2 (2025-10-31)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* 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: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0’
* 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 re-building of vignette outputs ... OK
* 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
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.74.0’
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0’
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/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){
| ^~~~~~~~~~~
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -Werror=format-security -c init_package.c -o init_package.o
gcc -std=gnu2x -shared -L/home/biocbuild/bbs-3.22-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.22-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.22-bioc/R/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 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-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
0.243 0.045 0.276
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-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 478284 25.6 1046725 56 639600 34.2
Vcells 884773 6.8 8388608 64 2081613 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 Apr 7 21:37:53 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Apr 7 21:37:53 2026"
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
>
>
> RowMode(tmp2)
<pointer: 0x5911248d0370>
>
>
>
> 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 Apr 7 21:37:53 2026"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Apr 7 21:37:53 2026"
>
> ColMode(tmp2)
<pointer: 0x5911248d0370>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.1937534 0.1596135 1.2422009 0.2094122
[2,] 0.2380192 0.1268732 0.6302830 1.1429957
[3,] -0.5924355 -0.6870356 -0.2868990 1.1211290
[4,] 1.1920842 -0.4328613 0.3191514 0.9973111
> 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,] 99.1937534 0.1596135 1.2422009 0.2094122
[2,] 0.2380192 0.1268732 0.6302830 1.1429957
[3,] 0.5924355 0.6870356 0.2868990 1.1211290
[4,] 1.1920842 0.4328613 0.3191514 0.9973111
> 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,] 9.9596061 0.3995165 1.1145407 0.4576157
[2,] 0.4878721 0.3561926 0.7939037 1.0691097
[3,] 0.7696983 0.8288761 0.5356295 1.0588338
[4,] 1.0918261 0.6579219 0.5649349 0.9986546
>
> 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,] 223.78981 29.15478 37.38761 29.78557
[2,] 30.11674 28.68880 33.56932 36.83409
[3,] 33.28942 33.97580 30.64319 36.70947
[4,] 37.11035 32.01208 30.96850 35.98386
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5911258cc9b0>
> exp(tmp5)
<pointer: 0x5911258cc9b0>
> log(tmp5,2)
<pointer: 0x5911258cc9b0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 465.7892
> Min(tmp5)
[1] 54.98731
> mean(tmp5)
[1] 73.20542
> Sum(tmp5)
[1] 14641.08
> Var(tmp5)
[1] 849.4358
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.39059 71.38911 68.79448 72.53682 71.69307 72.22303 71.11665 69.17238
[9] 72.37862 70.35948
> rowSums(tmp5)
[1] 1847.812 1427.782 1375.890 1450.736 1433.861 1444.461 1422.333 1383.448
[9] 1447.572 1407.190
> rowVars(tmp5)
[1] 7787.39134 50.92230 43.86160 48.35991 61.54196 90.93094
[7] 120.32028 56.32599 102.22766 88.59080
> rowSd(tmp5)
[1] 88.246197 7.135986 6.622809 6.954129 7.844869 9.535771 10.969060
[8] 7.505064 10.110769 9.412269
> rowMax(tmp5)
[1] 465.78918 81.82476 82.76272 83.04267 88.35673 85.64555 97.31745
[8] 86.42570 86.82865 88.57349
> rowMin(tmp5)
[1] 60.68185 59.18354 56.78903 58.80797 58.80887 57.03094 55.50261 58.01365
[9] 54.98731 56.91367
>
> colMeans(tmp5)
[1] 106.79394 68.67170 70.52705 72.06412 66.80508 74.76427 73.11822
[8] 66.34071 70.89217 69.59510 73.75262 72.47469 70.14805 69.94532
[15] 77.36388 72.91432 74.86643 72.01428 66.65549 74.40098
> colSums(tmp5)
[1] 1067.9394 686.7170 705.2705 720.6412 668.0508 747.6427 731.1822
[8] 663.4071 708.9217 695.9510 737.5262 724.7469 701.4805 699.4532
[15] 773.6388 729.1432 748.6643 720.1428 666.5549 744.0098
> colVars(tmp5)
[1] 15957.59531 85.03618 87.04053 148.36773 69.64694 87.01834
[7] 117.68584 34.60196 68.49477 47.54514 40.03437 37.40906
[13] 66.72749 79.34996 56.76588 49.49185 89.48952 44.10595
[19] 58.50106 53.92044
> colSd(tmp5)
[1] 126.323376 9.221506 9.329552 12.180629 8.345474 9.328362
[7] 10.848311 5.882343 8.276157 6.895298 6.327272 6.116295
[13] 8.168690 8.907859 7.534314 7.035044 9.459890 6.641231
[19] 7.648598 7.343054
> colMax(tmp5)
[1] 465.78918 82.42406 88.23674 97.31745 79.06903 86.42570 95.06115
[8] 77.77272 85.55386 79.22215 85.99725 85.13246 85.52828 83.04267
[15] 88.57349 86.82865 85.64555 82.48284 79.34010 88.35673
> colMin(tmp5)
[1] 57.11270 55.60942 61.21258 57.03094 54.98731 55.50261 58.67437 58.80797
[9] 58.06214 59.87610 65.28013 64.20795 61.71448 55.33676 66.50704 63.18096
[17] 56.91367 56.78903 56.61157 64.95550
>
>
> ### 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] 92.39059 NA 68.79448 72.53682 71.69307 72.22303 71.11665 69.17238
[9] 72.37862 70.35948
> rowSums(tmp5)
[1] 1847.812 NA 1375.890 1450.736 1433.861 1444.461 1422.333 1383.448
[9] 1447.572 1407.190
> rowVars(tmp5)
[1] 7787.39134 52.64155 43.86160 48.35991 61.54196 90.93094
[7] 120.32028 56.32599 102.22766 88.59080
> rowSd(tmp5)
[1] 88.246197 7.255450 6.622809 6.954129 7.844869 9.535771 10.969060
[8] 7.505064 10.110769 9.412269
> rowMax(tmp5)
[1] 465.78918 NA 82.76272 83.04267 88.35673 85.64555 97.31745
[8] 86.42570 86.82865 88.57349
> rowMin(tmp5)
[1] 60.68185 NA 56.78903 58.80797 58.80887 57.03094 55.50261 58.01365
[9] 54.98731 56.91367
>
> colMeans(tmp5)
[1] 106.79394 68.67170 70.52705 72.06412 66.80508 74.76427 73.11822
[8] 66.34071 70.89217 NA 73.75262 72.47469 70.14805 69.94532
[15] 77.36388 72.91432 74.86643 72.01428 66.65549 74.40098
> colSums(tmp5)
[1] 1067.9394 686.7170 705.2705 720.6412 668.0508 747.6427 731.1822
[8] 663.4071 708.9217 NA 737.5262 724.7469 701.4805 699.4532
[15] 773.6388 729.1432 748.6643 720.1428 666.5549 744.0098
> colVars(tmp5)
[1] 15957.59531 85.03618 87.04053 148.36773 69.64694 87.01834
[7] 117.68584 34.60196 68.49477 NA 40.03437 37.40906
[13] 66.72749 79.34996 56.76588 49.49185 89.48952 44.10595
[19] 58.50106 53.92044
> colSd(tmp5)
[1] 126.323376 9.221506 9.329552 12.180629 8.345474 9.328362
[7] 10.848311 5.882343 8.276157 NA 6.327272 6.116295
[13] 8.168690 8.907859 7.534314 7.035044 9.459890 6.641231
[19] 7.648598 7.343054
> colMax(tmp5)
[1] 465.78918 82.42406 88.23674 97.31745 79.06903 86.42570 95.06115
[8] 77.77272 85.55386 NA 85.99725 85.13246 85.52828 83.04267
[15] 88.57349 86.82865 85.64555 82.48284 79.34010 88.35673
> colMin(tmp5)
[1] 57.11270 55.60942 61.21258 57.03094 54.98731 55.50261 58.67437 58.80797
[9] 58.06214 NA 65.28013 64.20795 61.71448 55.33676 66.50704 63.18096
[17] 56.91367 56.78903 56.61157 64.95550
>
> Max(tmp5,na.rm=TRUE)
[1] 465.7892
> Min(tmp5,na.rm=TRUE)
[1] 54.98731
> mean(tmp5,na.rm=TRUE)
[1] 73.19266
> Sum(tmp5,na.rm=TRUE)
[1] 14565.34
> Var(tmp5,na.rm=TRUE)
[1] 853.6931
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.39059 71.15983 68.79448 72.53682 71.69307 72.22303 71.11665 69.17238
[9] 72.37862 70.35948
> rowSums(tmp5,na.rm=TRUE)
[1] 1847.812 1352.037 1375.890 1450.736 1433.861 1444.461 1422.333 1383.448
[9] 1447.572 1407.190
> rowVars(tmp5,na.rm=TRUE)
[1] 7787.39134 52.64155 43.86160 48.35991 61.54196 90.93094
[7] 120.32028 56.32599 102.22766 88.59080
> rowSd(tmp5,na.rm=TRUE)
[1] 88.246197 7.255450 6.622809 6.954129 7.844869 9.535771 10.969060
[8] 7.505064 10.110769 9.412269
> rowMax(tmp5,na.rm=TRUE)
[1] 465.78918 81.82476 82.76272 83.04267 88.35673 85.64555 97.31745
[8] 86.42570 86.82865 88.57349
> rowMin(tmp5,na.rm=TRUE)
[1] 60.68185 59.18354 56.78903 58.80797 58.80887 57.03094 55.50261 58.01365
[9] 54.98731 56.91367
>
> colMeans(tmp5,na.rm=TRUE)
[1] 106.79394 68.67170 70.52705 72.06412 66.80508 74.76427 73.11822
[8] 66.34071 70.89217 68.91174 73.75262 72.47469 70.14805 69.94532
[15] 77.36388 72.91432 74.86643 72.01428 66.65549 74.40098
> colSums(tmp5,na.rm=TRUE)
[1] 1067.9394 686.7170 705.2705 720.6412 668.0508 747.6427 731.1822
[8] 663.4071 708.9217 620.2057 737.5262 724.7469 701.4805 699.4532
[15] 773.6388 729.1432 748.6643 720.1428 666.5549 744.0098
> colVars(tmp5,na.rm=TRUE)
[1] 15957.59531 85.03618 87.04053 148.36773 69.64694 87.01834
[7] 117.68584 34.60196 68.49477 48.23472 40.03437 37.40906
[13] 66.72749 79.34996 56.76588 49.49185 89.48952 44.10595
[19] 58.50106 53.92044
> colSd(tmp5,na.rm=TRUE)
[1] 126.323376 9.221506 9.329552 12.180629 8.345474 9.328362
[7] 10.848311 5.882343 8.276157 6.945122 6.327272 6.116295
[13] 8.168690 8.907859 7.534314 7.035044 9.459890 6.641231
[19] 7.648598 7.343054
> colMax(tmp5,na.rm=TRUE)
[1] 465.78918 82.42406 88.23674 97.31745 79.06903 86.42570 95.06115
[8] 77.77272 85.55386 79.22215 85.99725 85.13246 85.52828 83.04267
[15] 88.57349 86.82865 85.64555 82.48284 79.34010 88.35673
> colMin(tmp5,na.rm=TRUE)
[1] 57.11270 55.60942 61.21258 57.03094 54.98731 55.50261 58.67437 58.80797
[9] 58.06214 59.87610 65.28013 64.20795 61.71448 55.33676 66.50704 63.18096
[17] 56.91367 56.78903 56.61157 64.95550
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.39059 NaN 68.79448 72.53682 71.69307 72.22303 71.11665 69.17238
[9] 72.37862 70.35948
> rowSums(tmp5,na.rm=TRUE)
[1] 1847.812 0.000 1375.890 1450.736 1433.861 1444.461 1422.333 1383.448
[9] 1447.572 1407.190
> rowVars(tmp5,na.rm=TRUE)
[1] 7787.39134 NA 43.86160 48.35991 61.54196 90.93094
[7] 120.32028 56.32599 102.22766 88.59080
> rowSd(tmp5,na.rm=TRUE)
[1] 88.246197 NA 6.622809 6.954129 7.844869 9.535771 10.969060
[8] 7.505064 10.110769 9.412269
> rowMax(tmp5,na.rm=TRUE)
[1] 465.78918 NA 82.76272 83.04267 88.35673 85.64555 97.31745
[8] 86.42570 86.82865 88.57349
> rowMin(tmp5,na.rm=TRUE)
[1] 60.68185 NA 56.78903 58.80797 58.80887 57.03094 55.50261 58.01365
[9] 54.98731 56.91367
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 111.69504 69.66723 70.60004 71.55287 66.79732 74.04721 72.46686
[8] 66.20137 72.19313 NaN 73.79496 72.41393 68.85064 68.67189
[15] 78.41842 73.62178 74.70126 72.08748 67.11691 74.33462
> colSums(tmp5,na.rm=TRUE)
[1] 1005.2554 627.0051 635.4003 643.9759 601.1759 666.4249 652.2017
[8] 595.8123 649.7382 0.0000 664.1546 651.7254 619.6558 618.0470
[15] 705.7658 662.5961 672.3113 648.7873 604.0522 669.0116
> colVars(tmp5,na.rm=TRUE)
[1] 17682.06103 84.51616 97.86067 163.97325 78.35213 92.11107
[7] 127.62346 38.70878 58.01605 NA 45.01851 42.04367
[13] 56.13155 71.02537 51.35112 50.04767 100.36878 49.55892
[19] 63.41845 60.61096
> colSd(tmp5,na.rm=TRUE)
[1] 132.973911 9.193267 9.892455 12.805204 8.851674 9.597451
[7] 11.297055 6.221638 7.616827 NA 6.709583 6.484109
[13] 7.492099 8.427655 7.165970 7.074438 10.018422 7.039809
[19] 7.963570 7.785304
> colMax(tmp5,na.rm=TRUE)
[1] 465.78918 82.42406 88.23674 97.31745 79.06903 86.42570 95.06115
[8] 77.77272 85.55386 -Inf 85.99725 85.13246 85.52828 83.04267
[15] 88.57349 86.82865 85.64555 82.48284 79.34010 88.35673
> colMin(tmp5,na.rm=TRUE)
[1] 57.11270 55.60942 61.21258 57.03094 54.98731 55.50261 58.67437 58.80797
[9] 58.06214 Inf 65.28013 64.20795 61.71448 55.33676 66.50704 63.18096
[17] 56.91367 56.78903 56.61157 64.95550
>
>
>
>
> 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] 293.01694 348.71899 174.37053 275.76829 98.35385 319.13552 151.51694
[8] 159.66123 245.18576 245.29879
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 293.01694 348.71899 174.37053 275.76829 98.35385 319.13552 151.51694
[8] 159.66123 245.18576 245.29879
>
>
>
> 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] 2.273737e-13 -5.684342e-14 7.105427e-14 -5.684342e-14 5.684342e-14
[6] -1.421085e-14 8.526513e-14 -2.842171e-14 -5.684342e-14 1.989520e-13
[11] -1.421085e-14 5.684342e-14 1.136868e-13 -4.263256e-14 -5.684342e-14
[16] 1.705303e-13 -2.842171e-14 0.000000e+00 -1.136868e-13 1.136868e-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)
+ }
7 14
4 17
10 10
5 10
10 3
3 19
10 16
9 20
3 12
6 12
4 16
8 10
9 3
8 7
2 7
3 14
10 1
9 6
7 17
2 6
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] 2.567051
> Min(tmp)
[1] -2.430594
> mean(tmp)
[1] 0.106332
> Sum(tmp)
[1] 10.6332
> Var(tmp)
[1] 1.084412
>
> rowMeans(tmp)
[1] 0.106332
> rowSums(tmp)
[1] 10.6332
> rowVars(tmp)
[1] 1.084412
> rowSd(tmp)
[1] 1.041351
> rowMax(tmp)
[1] 2.567051
> rowMin(tmp)
[1] -2.430594
>
> colMeans(tmp)
[1] 0.458674154 -1.132775951 -0.845154340 -0.374856258 -0.047592387
[6] 1.588737268 -1.248024836 -0.584647787 0.514865401 1.086564821
[11] 0.377570519 0.286306399 -0.574697834 0.259600644 -1.898575696
[16] -2.430594202 -0.389360013 0.101292256 -1.237291478 0.768112087
[21] -1.199651400 0.194394525 1.537795835 1.958486986 -1.240264509
[26] -0.156362233 -0.555439409 -0.305994716 0.756986828 -1.061270206
[31] 1.503988169 -0.020979642 -2.003057669 -0.165197722 -0.136834839
[36] 0.102215905 -0.172050479 1.090108155 -0.349144867 -0.584921720
[41] -0.776076423 -0.459068345 2.081194615 -1.615106425 0.678312705
[46] 1.449010318 -0.235378197 1.556121289 0.815387942 0.033842113
[51] 1.887617718 1.775340248 1.875875754 2.123222210 -0.028784606
[56] -0.627061118 -0.444964120 1.288749480 -0.690061415 -0.706852632
[61] 1.071168994 -0.746687316 -0.864674602 -0.875964490 -1.612307305
[66] 0.432843584 -0.822715551 0.850283399 0.001403197 -1.483994279
[71] 0.273111368 2.463554015 0.376427678 0.406142366 0.573469545
[76] 0.194726791 0.520110012 -0.689292119 0.060272688 0.503741445
[81] 0.640080739 1.002497559 1.208161935 -0.601496549 0.607453244
[86] 0.625452444 -0.565326189 0.090664057 -1.186631776 1.552545014
[91] -0.817254202 -0.330499870 0.176259616 -0.487195227 1.291502759
[96] 2.567050893 0.690168351 0.854761892 -0.194438400 -0.974459425
> colSums(tmp)
[1] 0.458674154 -1.132775951 -0.845154340 -0.374856258 -0.047592387
[6] 1.588737268 -1.248024836 -0.584647787 0.514865401 1.086564821
[11] 0.377570519 0.286306399 -0.574697834 0.259600644 -1.898575696
[16] -2.430594202 -0.389360013 0.101292256 -1.237291478 0.768112087
[21] -1.199651400 0.194394525 1.537795835 1.958486986 -1.240264509
[26] -0.156362233 -0.555439409 -0.305994716 0.756986828 -1.061270206
[31] 1.503988169 -0.020979642 -2.003057669 -0.165197722 -0.136834839
[36] 0.102215905 -0.172050479 1.090108155 -0.349144867 -0.584921720
[41] -0.776076423 -0.459068345 2.081194615 -1.615106425 0.678312705
[46] 1.449010318 -0.235378197 1.556121289 0.815387942 0.033842113
[51] 1.887617718 1.775340248 1.875875754 2.123222210 -0.028784606
[56] -0.627061118 -0.444964120 1.288749480 -0.690061415 -0.706852632
[61] 1.071168994 -0.746687316 -0.864674602 -0.875964490 -1.612307305
[66] 0.432843584 -0.822715551 0.850283399 0.001403197 -1.483994279
[71] 0.273111368 2.463554015 0.376427678 0.406142366 0.573469545
[76] 0.194726791 0.520110012 -0.689292119 0.060272688 0.503741445
[81] 0.640080739 1.002497559 1.208161935 -0.601496549 0.607453244
[86] 0.625452444 -0.565326189 0.090664057 -1.186631776 1.552545014
[91] -0.817254202 -0.330499870 0.176259616 -0.487195227 1.291502759
[96] 2.567050893 0.690168351 0.854761892 -0.194438400 -0.974459425
> 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] 0.458674154 -1.132775951 -0.845154340 -0.374856258 -0.047592387
[6] 1.588737268 -1.248024836 -0.584647787 0.514865401 1.086564821
[11] 0.377570519 0.286306399 -0.574697834 0.259600644 -1.898575696
[16] -2.430594202 -0.389360013 0.101292256 -1.237291478 0.768112087
[21] -1.199651400 0.194394525 1.537795835 1.958486986 -1.240264509
[26] -0.156362233 -0.555439409 -0.305994716 0.756986828 -1.061270206
[31] 1.503988169 -0.020979642 -2.003057669 -0.165197722 -0.136834839
[36] 0.102215905 -0.172050479 1.090108155 -0.349144867 -0.584921720
[41] -0.776076423 -0.459068345 2.081194615 -1.615106425 0.678312705
[46] 1.449010318 -0.235378197 1.556121289 0.815387942 0.033842113
[51] 1.887617718 1.775340248 1.875875754 2.123222210 -0.028784606
[56] -0.627061118 -0.444964120 1.288749480 -0.690061415 -0.706852632
[61] 1.071168994 -0.746687316 -0.864674602 -0.875964490 -1.612307305
[66] 0.432843584 -0.822715551 0.850283399 0.001403197 -1.483994279
[71] 0.273111368 2.463554015 0.376427678 0.406142366 0.573469545
[76] 0.194726791 0.520110012 -0.689292119 0.060272688 0.503741445
[81] 0.640080739 1.002497559 1.208161935 -0.601496549 0.607453244
[86] 0.625452444 -0.565326189 0.090664057 -1.186631776 1.552545014
[91] -0.817254202 -0.330499870 0.176259616 -0.487195227 1.291502759
[96] 2.567050893 0.690168351 0.854761892 -0.194438400 -0.974459425
> colMin(tmp)
[1] 0.458674154 -1.132775951 -0.845154340 -0.374856258 -0.047592387
[6] 1.588737268 -1.248024836 -0.584647787 0.514865401 1.086564821
[11] 0.377570519 0.286306399 -0.574697834 0.259600644 -1.898575696
[16] -2.430594202 -0.389360013 0.101292256 -1.237291478 0.768112087
[21] -1.199651400 0.194394525 1.537795835 1.958486986 -1.240264509
[26] -0.156362233 -0.555439409 -0.305994716 0.756986828 -1.061270206
[31] 1.503988169 -0.020979642 -2.003057669 -0.165197722 -0.136834839
[36] 0.102215905 -0.172050479 1.090108155 -0.349144867 -0.584921720
[41] -0.776076423 -0.459068345 2.081194615 -1.615106425 0.678312705
[46] 1.449010318 -0.235378197 1.556121289 0.815387942 0.033842113
[51] 1.887617718 1.775340248 1.875875754 2.123222210 -0.028784606
[56] -0.627061118 -0.444964120 1.288749480 -0.690061415 -0.706852632
[61] 1.071168994 -0.746687316 -0.864674602 -0.875964490 -1.612307305
[66] 0.432843584 -0.822715551 0.850283399 0.001403197 -1.483994279
[71] 0.273111368 2.463554015 0.376427678 0.406142366 0.573469545
[76] 0.194726791 0.520110012 -0.689292119 0.060272688 0.503741445
[81] 0.640080739 1.002497559 1.208161935 -0.601496549 0.607453244
[86] 0.625452444 -0.565326189 0.090664057 -1.186631776 1.552545014
[91] -0.817254202 -0.330499870 0.176259616 -0.487195227 1.291502759
[96] 2.567050893 0.690168351 0.854761892 -0.194438400 -0.974459425
> colMedians(tmp)
[1] 0.458674154 -1.132775951 -0.845154340 -0.374856258 -0.047592387
[6] 1.588737268 -1.248024836 -0.584647787 0.514865401 1.086564821
[11] 0.377570519 0.286306399 -0.574697834 0.259600644 -1.898575696
[16] -2.430594202 -0.389360013 0.101292256 -1.237291478 0.768112087
[21] -1.199651400 0.194394525 1.537795835 1.958486986 -1.240264509
[26] -0.156362233 -0.555439409 -0.305994716 0.756986828 -1.061270206
[31] 1.503988169 -0.020979642 -2.003057669 -0.165197722 -0.136834839
[36] 0.102215905 -0.172050479 1.090108155 -0.349144867 -0.584921720
[41] -0.776076423 -0.459068345 2.081194615 -1.615106425 0.678312705
[46] 1.449010318 -0.235378197 1.556121289 0.815387942 0.033842113
[51] 1.887617718 1.775340248 1.875875754 2.123222210 -0.028784606
[56] -0.627061118 -0.444964120 1.288749480 -0.690061415 -0.706852632
[61] 1.071168994 -0.746687316 -0.864674602 -0.875964490 -1.612307305
[66] 0.432843584 -0.822715551 0.850283399 0.001403197 -1.483994279
[71] 0.273111368 2.463554015 0.376427678 0.406142366 0.573469545
[76] 0.194726791 0.520110012 -0.689292119 0.060272688 0.503741445
[81] 0.640080739 1.002497559 1.208161935 -0.601496549 0.607453244
[86] 0.625452444 -0.565326189 0.090664057 -1.186631776 1.552545014
[91] -0.817254202 -0.330499870 0.176259616 -0.487195227 1.291502759
[96] 2.567050893 0.690168351 0.854761892 -0.194438400 -0.974459425
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.4586742 -1.132776 -0.8451543 -0.3748563 -0.04759239 1.588737 -1.248025
[2,] 0.4586742 -1.132776 -0.8451543 -0.3748563 -0.04759239 1.588737 -1.248025
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.5846478 0.5148654 1.086565 0.3775705 0.2863064 -0.5746978 0.2596006
[2,] -0.5846478 0.5148654 1.086565 0.3775705 0.2863064 -0.5746978 0.2596006
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.898576 -2.430594 -0.38936 0.1012923 -1.237291 0.7681121 -1.199651
[2,] -1.898576 -2.430594 -0.38936 0.1012923 -1.237291 0.7681121 -1.199651
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.1943945 1.537796 1.958487 -1.240265 -0.1563622 -0.5554394 -0.3059947
[2,] 0.1943945 1.537796 1.958487 -1.240265 -0.1563622 -0.5554394 -0.3059947
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.7569868 -1.06127 1.503988 -0.02097964 -2.003058 -0.1651977 -0.1368348
[2,] 0.7569868 -1.06127 1.503988 -0.02097964 -2.003058 -0.1651977 -0.1368348
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.1022159 -0.1720505 1.090108 -0.3491449 -0.5849217 -0.7760764 -0.4590683
[2,] 0.1022159 -0.1720505 1.090108 -0.3491449 -0.5849217 -0.7760764 -0.4590683
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 2.081195 -1.615106 0.6783127 1.44901 -0.2353782 1.556121 0.8153879
[2,] 2.081195 -1.615106 0.6783127 1.44901 -0.2353782 1.556121 0.8153879
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.03384211 1.887618 1.77534 1.875876 2.123222 -0.02878461 -0.6270611
[2,] 0.03384211 1.887618 1.77534 1.875876 2.123222 -0.02878461 -0.6270611
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.4449641 1.288749 -0.6900614 -0.7068526 1.071169 -0.7466873 -0.8646746
[2,] -0.4449641 1.288749 -0.6900614 -0.7068526 1.071169 -0.7466873 -0.8646746
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.8759645 -1.612307 0.4328436 -0.8227156 0.8502834 0.001403197 -1.483994
[2,] -0.8759645 -1.612307 0.4328436 -0.8227156 0.8502834 0.001403197 -1.483994
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.2731114 2.463554 0.3764277 0.4061424 0.5734695 0.1947268 0.52011
[2,] 0.2731114 2.463554 0.3764277 0.4061424 0.5734695 0.1947268 0.52011
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.6892921 0.06027269 0.5037414 0.6400807 1.002498 1.208162 -0.6014965
[2,] -0.6892921 0.06027269 0.5037414 0.6400807 1.002498 1.208162 -0.6014965
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.6074532 0.6254524 -0.5653262 0.09066406 -1.186632 1.552545 -0.8172542
[2,] 0.6074532 0.6254524 -0.5653262 0.09066406 -1.186632 1.552545 -0.8172542
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.3304999 0.1762596 -0.4871952 1.291503 2.567051 0.6901684 0.8547619
[2,] -0.3304999 0.1762596 -0.4871952 1.291503 2.567051 0.6901684 0.8547619
[,99] [,100]
[1,] -0.1944384 -0.9744594
[2,] -0.1944384 -0.9744594
>
>
> Max(tmp2)
[1] 2.360678
> Min(tmp2)
[1] -1.692943
> mean(tmp2)
[1] 0.09537901
> Sum(tmp2)
[1] 9.537901
> Var(tmp2)
[1] 0.6644554
>
> rowMeans(tmp2)
[1] 0.43469381 -0.36529738 0.50974456 1.83955864 0.83225661 -0.59898806
[7] -0.06909783 -1.17828983 0.27340168 -0.84525795 0.95627990 -1.69294335
[13] 0.31755604 0.36540235 0.30318899 -0.42005551 1.14808674 -0.04221476
[19] -1.13728783 0.24986501 0.10865604 -0.41155369 -0.06991561 -0.25149866
[25] 0.05458015 -1.08851836 -0.22914522 0.99211798 -0.18047313 1.28851821
[31] 2.36067816 -0.06566256 1.09554507 -0.49137363 0.19923054 -0.13919416
[37] -0.63807564 -0.30849388 -0.30472876 0.30561659 -0.04222356 0.42885255
[43] -0.92460057 0.33341146 1.71510211 -1.01562398 0.75326952 -0.49184370
[49] 0.45690852 -0.32696908 0.51416859 1.47729961 0.84153546 1.95219409
[55] -0.42550605 1.28170145 -0.08898323 0.44894489 0.89259056 -0.70168324
[61] -1.20445820 -0.78620406 1.13244182 1.42045084 -1.11998689 -0.90870320
[67] -0.04244772 0.58274365 -1.11119981 -1.17232993 -0.10067594 -0.57903174
[73] 0.89594074 0.13354431 -0.72976738 -0.64378139 -0.84850803 0.26274638
[79] -0.14060272 1.00332624 0.53610997 0.47391428 0.31996809 0.38667949
[85] 1.21609690 0.49086124 -0.31289662 -1.08951798 1.31843551 0.93130293
[91] -0.91339205 -0.35923514 1.02765194 -0.52364954 -0.20095865 -0.48763234
[97] -0.41279189 0.57237571 0.50837448 -0.17274872
> rowSums(tmp2)
[1] 0.43469381 -0.36529738 0.50974456 1.83955864 0.83225661 -0.59898806
[7] -0.06909783 -1.17828983 0.27340168 -0.84525795 0.95627990 -1.69294335
[13] 0.31755604 0.36540235 0.30318899 -0.42005551 1.14808674 -0.04221476
[19] -1.13728783 0.24986501 0.10865604 -0.41155369 -0.06991561 -0.25149866
[25] 0.05458015 -1.08851836 -0.22914522 0.99211798 -0.18047313 1.28851821
[31] 2.36067816 -0.06566256 1.09554507 -0.49137363 0.19923054 -0.13919416
[37] -0.63807564 -0.30849388 -0.30472876 0.30561659 -0.04222356 0.42885255
[43] -0.92460057 0.33341146 1.71510211 -1.01562398 0.75326952 -0.49184370
[49] 0.45690852 -0.32696908 0.51416859 1.47729961 0.84153546 1.95219409
[55] -0.42550605 1.28170145 -0.08898323 0.44894489 0.89259056 -0.70168324
[61] -1.20445820 -0.78620406 1.13244182 1.42045084 -1.11998689 -0.90870320
[67] -0.04244772 0.58274365 -1.11119981 -1.17232993 -0.10067594 -0.57903174
[73] 0.89594074 0.13354431 -0.72976738 -0.64378139 -0.84850803 0.26274638
[79] -0.14060272 1.00332624 0.53610997 0.47391428 0.31996809 0.38667949
[85] 1.21609690 0.49086124 -0.31289662 -1.08951798 1.31843551 0.93130293
[91] -0.91339205 -0.35923514 1.02765194 -0.52364954 -0.20095865 -0.48763234
[97] -0.41279189 0.57237571 0.50837448 -0.17274872
> 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] 0.43469381 -0.36529738 0.50974456 1.83955864 0.83225661 -0.59898806
[7] -0.06909783 -1.17828983 0.27340168 -0.84525795 0.95627990 -1.69294335
[13] 0.31755604 0.36540235 0.30318899 -0.42005551 1.14808674 -0.04221476
[19] -1.13728783 0.24986501 0.10865604 -0.41155369 -0.06991561 -0.25149866
[25] 0.05458015 -1.08851836 -0.22914522 0.99211798 -0.18047313 1.28851821
[31] 2.36067816 -0.06566256 1.09554507 -0.49137363 0.19923054 -0.13919416
[37] -0.63807564 -0.30849388 -0.30472876 0.30561659 -0.04222356 0.42885255
[43] -0.92460057 0.33341146 1.71510211 -1.01562398 0.75326952 -0.49184370
[49] 0.45690852 -0.32696908 0.51416859 1.47729961 0.84153546 1.95219409
[55] -0.42550605 1.28170145 -0.08898323 0.44894489 0.89259056 -0.70168324
[61] -1.20445820 -0.78620406 1.13244182 1.42045084 -1.11998689 -0.90870320
[67] -0.04244772 0.58274365 -1.11119981 -1.17232993 -0.10067594 -0.57903174
[73] 0.89594074 0.13354431 -0.72976738 -0.64378139 -0.84850803 0.26274638
[79] -0.14060272 1.00332624 0.53610997 0.47391428 0.31996809 0.38667949
[85] 1.21609690 0.49086124 -0.31289662 -1.08951798 1.31843551 0.93130293
[91] -0.91339205 -0.35923514 1.02765194 -0.52364954 -0.20095865 -0.48763234
[97] -0.41279189 0.57237571 0.50837448 -0.17274872
> rowMin(tmp2)
[1] 0.43469381 -0.36529738 0.50974456 1.83955864 0.83225661 -0.59898806
[7] -0.06909783 -1.17828983 0.27340168 -0.84525795 0.95627990 -1.69294335
[13] 0.31755604 0.36540235 0.30318899 -0.42005551 1.14808674 -0.04221476
[19] -1.13728783 0.24986501 0.10865604 -0.41155369 -0.06991561 -0.25149866
[25] 0.05458015 -1.08851836 -0.22914522 0.99211798 -0.18047313 1.28851821
[31] 2.36067816 -0.06566256 1.09554507 -0.49137363 0.19923054 -0.13919416
[37] -0.63807564 -0.30849388 -0.30472876 0.30561659 -0.04222356 0.42885255
[43] -0.92460057 0.33341146 1.71510211 -1.01562398 0.75326952 -0.49184370
[49] 0.45690852 -0.32696908 0.51416859 1.47729961 0.84153546 1.95219409
[55] -0.42550605 1.28170145 -0.08898323 0.44894489 0.89259056 -0.70168324
[61] -1.20445820 -0.78620406 1.13244182 1.42045084 -1.11998689 -0.90870320
[67] -0.04244772 0.58274365 -1.11119981 -1.17232993 -0.10067594 -0.57903174
[73] 0.89594074 0.13354431 -0.72976738 -0.64378139 -0.84850803 0.26274638
[79] -0.14060272 1.00332624 0.53610997 0.47391428 0.31996809 0.38667949
[85] 1.21609690 0.49086124 -0.31289662 -1.08951798 1.31843551 0.93130293
[91] -0.91339205 -0.35923514 1.02765194 -0.52364954 -0.20095865 -0.48763234
[97] -0.41279189 0.57237571 0.50837448 -0.17274872
>
> colMeans(tmp2)
[1] 0.09537901
> colSums(tmp2)
[1] 9.537901
> colVars(tmp2)
[1] 0.6644554
> colSd(tmp2)
[1] 0.8151414
> colMax(tmp2)
[1] 2.360678
> colMin(tmp2)
[1] -1.692943
> colMedians(tmp2)
[1] -0.04221916
> colRanges(tmp2)
[,1]
[1,] -1.692943
[2,] 2.360678
>
> 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] -1.9344968 -1.6289298 1.9552546 1.1326770 -2.3173274 -0.7281024
[7] -0.6641598 2.6680107 2.1475650 3.2870098
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.7150938
[2,] -1.0802778
[3,] 0.1503225
[4,] 0.6728800
[5,] 0.8198679
>
> rowApply(tmp,sum)
[1] 0.2371970 4.0899080 0.3621434 2.3849090 5.3732490 -0.8907642
[7] 0.6997502 0.3752579 -1.8406824 -6.8734671
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 7 1 2 6 1 8 10 5 9
[2,] 7 8 2 6 1 6 9 2 9 2
[3,] 8 9 4 4 9 7 2 1 7 7
[4,] 3 4 9 7 7 10 6 4 6 1
[5,] 1 1 5 9 5 9 4 5 3 5
[6,] 2 5 3 8 2 8 1 9 8 4
[7,] 10 3 8 1 10 2 5 3 2 6
[8,] 4 6 6 3 8 3 3 7 10 10
[9,] 9 2 10 5 3 5 10 8 4 3
[10,] 6 10 7 10 4 4 7 6 1 8
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.5989174 0.6792160 1.3703250 2.3558056 2.5617340 -0.8833315
[7] 1.8798646 0.2699844 0.2805283 2.4170616 2.5451441 1.6571860
[13] -1.2889272 -0.3657910 -4.0925423 0.1549380 1.4881557 -0.1301445
[19] -2.0325613 2.9849573
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.69322913
[2,] -0.59837146
[3,] -0.25779497
[4,] -0.03189422
[5,] -0.01762760
>
> rowApply(tmp,sum)
[1] 1.064393 11.351699 1.366571 -1.945726 -2.584252
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 7 9 9 1
[2,] 7 10 18 14 4
[3,] 17 13 8 15 12
[4,] 19 9 11 18 13
[5,] 8 15 20 13 14
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.59837146 -0.5844211 0.76748824 1.47376261 -0.4214917 -0.09683519
[2,] -0.03189422 0.3619705 0.57101997 0.20860036 1.1704566 0.56062541
[3,] -0.01762760 1.2851952 -0.13087970 0.07496757 1.4668842 -0.64626985
[4,] -0.25779497 0.1947089 0.25157546 0.67835771 0.1851008 -0.19245161
[5,] -1.69322913 -0.5782375 -0.08887897 -0.07988268 0.1607841 -0.50840021
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.4365818 0.07544416 -0.6981663 -0.6116101 0.4531726 1.159051602
[2,] 2.7019690 -0.05963803 0.5552715 2.1294869 -0.2181903 -0.100320164
[3,] -0.1800782 1.11293195 0.6664709 0.5544296 1.4039591 -0.006119072
[4,] -0.5944755 -1.13985119 -1.1190698 0.6346787 1.3638677 -0.344844800
[5,] -0.4841324 0.28109756 0.8760221 -0.2899236 -0.4576651 0.949418468
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.3476934 -0.6936023 -0.62565679 1.7657647 0.575812896 -1.52801136
[2,] 1.1913186 -0.7841152 -1.17752809 0.9181472 1.870157257 0.03287901
[3,] -0.9813867 0.8374061 -1.04370718 -1.7350386 -1.394414497 0.57847349
[4,] -0.6632592 -0.4689932 -1.14831341 0.4196045 0.003582383 -0.62480068
[5,] -1.1832933 0.7435136 -0.09733683 -1.2135398 0.433017704 1.41131505
[,19] [,20]
[1,] -0.42077496 0.2885623
[2,] -0.12366373 1.5751466
[3,] -1.31808558 0.8394597
[4,] 0.02992869 0.8467236
[5,] -0.19996574 -0.5649349
>
>
> 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 : 654 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 : 566 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 -0.9955244 0.9154652 -0.5151361 -0.7033465 0.4267502 0.4332064 -0.4846466
col8 col9 col10 col11 col12 col13 col14
row1 -1.16218 -0.2480263 -0.9284055 0.4313165 0.4575826 1.629859 0.1018476
col15 col16 col17 col18 col19 col20
row1 -0.04137902 -0.03612626 -1.508042 -1.415019 -1.180768 0.6863771
> tmp[,"col10"]
col10
row1 -0.9284055
row2 -0.5212638
row3 -0.3562202
row4 -0.9081648
row5 0.3483274
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.9955244 0.9154652 -0.5151361 -0.7033465 0.4267502 0.4332064 -0.4846466
row5 -1.1820688 0.3643678 -0.1871721 1.3822214 0.4582701 0.2033449 0.3126792
col8 col9 col10 col11 col12 col13
row1 -1.1621800 -0.2480263 -0.9284055 0.4313165 0.4575826 1.62985950
row5 0.7519855 -1.7683467 0.3483274 1.0089327 -0.6184695 -0.07073753
col14 col15 col16 col17 col18 col19
row1 0.1018476 -0.04137902 -0.03612626 -1.5080416 -1.415019 -1.180768
row5 -0.8307824 -0.35824631 -0.59550642 0.7084514 -1.217361 -1.419363
col20
row1 0.6863771
row5 -1.1957439
> tmp[,c("col6","col20")]
col6 col20
row1 0.4332064 0.6863771
row2 0.3187115 -0.5823254
row3 0.3302318 0.2110232
row4 2.4193150 1.2443844
row5 0.2033449 -1.1957439
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.4332064 0.6863771
row5 0.2033449 -1.1957439
>
>
>
>
> 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 50.58572 49.33054 51.06598 47.83038 50.44691 105.6766 48.54695 51.00713
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.96889 48.9624 50.69126 51.40243 49.3754 51.51088 50.34961 50.80026
col17 col18 col19 col20
row1 49.87635 50.10027 50.33636 104.4595
> tmp[,"col10"]
col10
row1 48.96240
row2 29.11058
row3 31.77453
row4 28.76457
row5 49.94365
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.58572 49.33054 51.06598 47.83038 50.44691 105.6766 48.54695 51.00713
row5 49.42566 49.56049 50.14553 49.39725 49.58587 106.3239 52.11919 49.94051
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.96889 48.96240 50.69126 51.40243 49.37540 51.51088 50.34961 50.80026
row5 50.12540 49.94365 51.12016 49.74727 48.93435 49.91886 50.18665 51.14281
col17 col18 col19 col20
row1 49.87635 50.10027 50.33636 104.4595
row5 50.32430 50.79322 50.71472 103.3980
> tmp[,c("col6","col20")]
col6 col20
row1 105.67656 104.45946
row2 76.06351 74.09054
row3 75.47818 74.28969
row4 75.20916 78.23092
row5 106.32394 103.39799
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.6766 104.4595
row5 106.3239 103.3980
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.6766 104.4595
row5 106.3239 103.3980
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.4330077
[2,] -0.7414498
[3,] -1.8249934
[4,] -0.6201957
[5,] 0.9279415
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.63046250 0.2437814
[2,] -0.18089515 -0.1764092
[3,] 0.74354317 -1.2821146
[4,] -0.09699009 -0.6774235
[5,] -0.33440897 -1.5741684
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.7504417 1.1914648
[2,] -0.1926970 0.2577367
[3,] -0.4672061 -1.5554994
[4,] 0.2188679 2.6674699
[5,] 0.1275807 -1.4597684
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.7504417
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.7504417
[2,] -0.1926970
>
>
>
> 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 -2.130260 -0.2227947 0.8817319 1.307437 0.3353132 -1.5525528 -1.1888666
row1 1.131153 -0.4580828 -0.3497765 1.444399 2.2787940 0.3503115 0.1445794
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.08885574 -0.82018545 -1.1794471 1.924631 -0.03755218 1.5919740
row1 -0.62106705 0.08684494 -0.1460751 -0.264592 0.95942665 -0.5589079
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.5036625 1.4815077 0.6082057 0.5643466 0.6359972 0.4964859 -0.5791059
row1 0.9153783 0.2436125 -0.6204338 1.4677489 0.4502528 -0.3431849 -0.1333919
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.2695429 0.8532791 -1.045445 -0.439278 1.097577 1.054197 -0.3453857
[,8] [,9] [,10]
row2 0.1124593 -0.1498866 0.3120085
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.102091 -1.360903 0.725158 1.213831 -1.621751 1.548096 -1.226399
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.1525835 1.254306 -0.5414986 -1.859333 0.1321102 1.266042 -0.3822958
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.3044311 -2.392306 -0.3191457 0.4874215 0.823017 1.066246
>
>
> 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: 0x5911254ce220>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM32e94a12746eb1"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM32e94a5e8da39f"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM32e94a59646862"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM32e94a691e9108"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM32e94a1b103667"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM32e94a304bec3a"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM32e94a6f2da748"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM32e94a57cc2d4f"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM32e94a7169feb4"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM32e94a331a1ce9"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM32e94a7cf6c773"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM32e94a497c2130"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM32e94a701f514e"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM32e94ab69cd6d"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM32e94a1b132967"
>
>
> ### 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: 0x591123aab560>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x591123aab560>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x591123aab560>
> rowMedians(tmp)
[1] -0.068132643 -0.125273171 -0.237546746 0.187140360 0.081816327
[6] -0.338234350 -0.644712057 0.093952447 -0.635652282 -0.271842163
[11] 0.714337652 0.272293286 -0.297355899 0.056591479 0.202014180
[16] -0.037390543 0.048000497 0.066678744 0.002932348 0.148743706
[21] 0.497973760 -0.611029794 0.103946440 0.098008492 -0.078256451
[26] -0.288942357 0.195701311 0.429334282 0.446991770 0.810222299
[31] 0.194043818 0.209222077 -0.514835720 0.004129277 0.536680523
[36] 0.157322261 -0.333564705 -0.052414030 -0.146972215 -0.403028176
[41] -0.221833367 0.309886872 -0.653899591 0.220556557 -0.229074651
[46] -0.125371522 -0.010537193 0.227358795 -0.319131054 0.194186835
[51] -0.289134671 -0.367231815 -0.136392483 0.462428842 -0.576190066
[56] 0.239795856 -0.044759197 0.202125114 0.083991207 -0.223652455
[61] 0.056030810 -0.358713495 0.414154829 -0.134264630 -0.435132134
[66] -0.183639048 0.150842500 0.652603018 0.181705276 -0.853355058
[71] 0.178838517 0.022623465 -0.082976941 0.371429665 0.172403440
[76] -0.051930669 0.054622085 0.103701916 -0.017580891 0.351886230
[81] 0.095293442 -0.047336593 0.004139437 -0.049835985 -0.354490321
[86] -0.316559025 -0.027843392 -0.013237434 -0.074069288 -0.379263950
[91] 0.391214818 -0.129926000 -0.257853290 0.467320910 0.573959736
[96] 0.322160898 -0.227961663 -0.380434820 0.281349363 -0.176755115
[101] 0.346049137 -0.042512341 -0.168233709 0.355169650 -0.197878043
[106] -0.588558420 -0.308902485 -0.014093455 -0.288715891 -0.350417263
[111] -0.781799441 0.106039296 -0.033039866 -0.404613990 -0.358164322
[116] 0.299213965 -0.078933276 -0.059109133 0.183274777 -0.191598035
[121] -0.204551168 0.040997506 -0.002343634 0.273711377 -0.323369468
[126] -0.120913159 0.009742324 -0.132610722 0.178276094 0.411454693
[131] -0.156084461 0.531495072 -0.505002842 0.340014247 -0.287897377
[136] 0.469342633 0.051926632 0.294295680 -0.591527514 -0.222532274
[141] 0.098779969 -0.334771129 -0.489501407 -0.075852804 0.578836010
[146] 0.035279617 -0.378583754 0.001458521 -0.442982021 -0.370108643
[151] 0.036127251 0.232473214 -0.435523918 0.431857649 -0.190394756
[156] -0.367969270 0.509201470 -0.195369250 0.091477638 -0.077005161
[161] 0.118639980 -0.344369633 0.326728991 0.239666292 -0.154807606
[166] 0.003031966 0.190150613 0.216625563 -0.019254559 0.354939349
[171] -0.491053166 0.067114562 0.509021203 -0.467364417 -0.649503335
[176] -0.328139961 0.475419635 0.147868793 0.191044293 0.059183534
[181] 0.307491548 -0.015991214 0.501204130 0.382757199 0.175177943
[186] 0.201608713 0.218898758 -0.077355727 0.664128816 -0.345542468
[191] -0.360900131 0.340521323 0.506847852 -0.303973901 0.114850559
[196] -0.463533720 0.231538497 -0.101791029 -0.363841233 -0.546451259
[201] -0.263574871 0.431523584 -0.507746570 -0.467325122 0.329626733
[206] 0.091160360 0.482567802 0.181773417 -0.064294199 0.065342759
[211] -0.035698767 -0.087840783 -0.106349534 0.208300691 -0.574376603
[216] 0.010804774 -0.772378312 -0.167621627 0.262291037 -0.568840170
[221] -0.058806800 0.363278668 0.523171843 0.134039896 0.582476697
[226] -0.237051762 0.130556762 -0.091395162 0.265964009 -0.363554871
>
> proc.time()
user system elapsed
1.231 0.660 1.882
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-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: 0x5a887bc59370>
> .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: 0x5a887bc59370>
> .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: 0x5a887bc59370>
> .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: 0x5a887bc59370>
> 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: 0x5a887bc411c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5a887bc411c0>
> .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: 0x5a887bc411c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5a887bc411c0>
> .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: 0x5a887bc411c0>
> 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: 0x5a887bf24120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5a887bf24120>
> .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: 0x5a887bf24120>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5a887bf24120>
> .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: 0x5a887bf24120>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5a887bf24120>
> .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: 0x5a887bf24120>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5a887bf24120>
> .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: 0x5a887bf24120>
> 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: 0x5a887ac74390>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5a887ac74390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5a887ac74390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5a887ac74390>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile32ea63236f084e" "BufferedMatrixFile32ea63524d4612"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile32ea63236f084e" "BufferedMatrixFile32ea63524d4612"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5a887ab6b3d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5a887ab6b3d0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5a887ab6b3d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5a887ab6b3d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5a887ab6b3d0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5a887ab6b3d0>
> .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: 0x5a887c6a0fa0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5a887c6a0fa0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5a887c6a0fa0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5a887c6a0fa0>
> 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: 0x5a887ae78ff0>
> .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: 0x5a887ae78ff0>
> rm(P)
>
> proc.time()
user system elapsed
0.256 0.037 0.282
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-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
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.247 0.052 0.286