Ben Bolstad
| Snapshot Date: 2025-11-04 13:40 -0500 (Tue, 04 Nov 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: ecdbf23 |
| git_last_commit_date: 2025-10-29 09:58:55 -0500 (Wed, 29 Oct 2025) |
| Back to Build/check report for BioC 3.23: simplified long |
|
This page was generated on 2025-11-05 11:32 -0500 (Wed, 05 Nov 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences" | 4818 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 251/2323 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.75.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.75.0 |
| Command: /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings BufferedMatrix_1.75.0.tar.gz |
| StartedAt: 2025-11-04 21:30:42 -0500 (Tue, 04 Nov 2025) |
| EndedAt: 2025-11-04 21:31:07 -0500 (Tue, 04 Nov 2025) |
| EllapsedTime: 25.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
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###
### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings BufferedMatrix_1.75.0.tar.gz
###
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* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2025-10-20 r88955)
* 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 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.75.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 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 ... INFO
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ...* 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: 1 NOTE
See
‘/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
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###
### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.75.0’
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.23-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-3.23-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-3.23-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-3.23-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-3.23-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-3.23-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.23-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 Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences"
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
0.234 0.062 0.284
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences"
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-3.23-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 478818 25.6 1048392 56 639317 34.2
Vcells 885623 6.8 8388608 64 2082728 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 4 21:30:57 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 4 21:30:57 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: 0x60e5f07aa5e0>
>
>
>
> 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 4 21:30:57 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 4 21:30:57 2025"
>
> ColMode(tmp2)
<pointer: 0x60e5f07aa5e0>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 101.5697031 -0.27925338 0.7487034 0.004619994
[2,] -0.9659375 -0.03374995 0.5310231 -1.339036636
[3,] -1.0008332 -0.67963490 -1.0749717 0.705514448
[4,] -0.7723975 -0.07815578 0.4376353 0.685691531
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 101.5697031 0.27925338 0.7487034 0.004619994
[2,] 0.9659375 0.03374995 0.5310231 1.339036636
[3,] 1.0008332 0.67963490 1.0749717 0.705514448
[4,] 0.7723975 0.07815578 0.4376353 0.685691531
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0781796 0.5284443 0.8652765 0.06797054
[2,] 0.9828212 0.1837116 0.7287133 1.15716751
[3,] 1.0004165 0.8243997 1.0368084 0.83994907
[4,] 0.8788615 0.2795635 0.6615401 0.82806493
>
> 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-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 227.35150 30.56370 34.40147 25.68433
[2,] 35.79415 26.87087 32.81816 37.91071
[3,] 36.00500 33.92363 36.44306 34.10501
[4,] 34.56101 27.87379 32.05304 33.96634
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x60e5f0335840>
> exp(tmp5)
<pointer: 0x60e5f0335840>
> log(tmp5,2)
<pointer: 0x60e5f0335840>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 473.2024
> Min(tmp5)
[1] 53.45856
> mean(tmp5)
[1] 72.89204
> Sum(tmp5)
[1] 14578.41
> Var(tmp5)
[1] 877.5618
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.09681 72.31393 73.51080 69.18281 70.75161 66.98049 72.76468 69.15089
[9] 70.63979 73.52859
> rowSums(tmp5)
[1] 1801.936 1446.279 1470.216 1383.656 1415.032 1339.610 1455.294 1383.018
[9] 1412.796 1470.572
> rowVars(tmp5)
[1] 8216.18353 63.88780 46.96335 47.97194 79.83648 45.53856
[7] 69.32509 52.18725 82.55358 97.91300
> rowSd(tmp5)
[1] 90.643166 7.992984 6.852981 6.926178 8.935126 6.748226 8.326169
[8] 7.224074 9.085900 9.895100
> rowMax(tmp5)
[1] 473.20236 88.08769 87.55190 86.27881 86.18483 79.73367 91.90788
[8] 83.69894 85.92803 89.10411
> rowMin(tmp5)
[1] 53.45856 55.92819 60.06682 58.01564 54.22065 54.12369 59.45410 56.07065
[9] 57.24069 55.68069
>
> colMeans(tmp5)
[1] 111.01263 66.44613 70.18830 71.14174 73.73923 66.55385 74.90438
[8] 71.67798 72.95696 70.69108 73.82782 69.17786 70.70923 67.09845
[15] 74.46309 71.80197 69.22819 72.19874 68.56200 71.46118
> colSums(tmp5)
[1] 1110.1263 664.4613 701.8830 711.4174 737.3923 665.5385 749.0438
[8] 716.7798 729.5696 706.9108 738.2782 691.7786 707.0923 670.9845
[15] 744.6309 718.0197 692.2819 721.9874 685.6200 714.6118
> colVars(tmp5)
[1] 16239.19941 73.83904 52.15426 60.58488 62.77332 80.12492
[7] 67.59979 69.03701 27.62606 71.91250 70.43789 52.99065
[13] 127.18236 71.84280 48.78537 154.67514 79.86964 84.08043
[19] 55.57392 22.77280
> colSd(tmp5)
[1] 127.433117 8.592965 7.221791 7.783629 7.922962 8.951252
[7] 8.221909 8.308852 5.256050 8.480124 8.392728 7.279467
[13] 11.277516 8.476013 6.984653 12.436846 8.936982 9.169538
[19] 7.454792 4.772085
> colMax(tmp5)
[1] 473.20236 83.17569 84.52247 78.90618 86.27881 82.80536 86.02888
[8] 85.92803 79.55103 85.28419 89.10411 79.30732 91.90788 79.55607
[15] 86.18483 88.25922 87.55190 88.08769 80.25295 79.73367
> colMin(tmp5)
[1] 61.40838 55.92819 61.37929 53.45856 64.55185 57.16349 61.27865 57.51223
[9] 62.93912 57.20714 63.96980 57.39923 56.66763 54.12369 66.03902 54.22065
[17] 56.07065 59.64151 55.68069 65.97676
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 90.09681 72.31393 73.51080 69.18281 70.75161 66.98049 72.76468 69.15089
[9] 70.63979 NA
> rowSums(tmp5)
[1] 1801.936 1446.279 1470.216 1383.656 1415.032 1339.610 1455.294 1383.018
[9] 1412.796 NA
> rowVars(tmp5)
[1] 8216.18353 63.88780 46.96335 47.97194 79.83648 45.53856
[7] 69.32509 52.18725 82.55358 103.23936
> rowSd(tmp5)
[1] 90.643166 7.992984 6.852981 6.926178 8.935126 6.748226 8.326169
[8] 7.224074 9.085900 10.160677
> rowMax(tmp5)
[1] 473.20236 88.08769 87.55190 86.27881 86.18483 79.73367 91.90788
[8] 83.69894 85.92803 NA
> rowMin(tmp5)
[1] 53.45856 55.92819 60.06682 58.01564 54.22065 54.12369 59.45410 56.07065
[9] 57.24069 NA
>
> colMeans(tmp5)
[1] 111.01263 66.44613 70.18830 NA 73.73923 66.55385 74.90438
[8] 71.67798 72.95696 70.69108 73.82782 69.17786 70.70923 67.09845
[15] 74.46309 71.80197 69.22819 72.19874 68.56200 71.46118
> colSums(tmp5)
[1] 1110.1263 664.4613 701.8830 NA 737.3923 665.5385 749.0438
[8] 716.7798 729.5696 706.9108 738.2782 691.7786 707.0923 670.9845
[15] 744.6309 718.0197 692.2819 721.9874 685.6200 714.6118
> colVars(tmp5)
[1] 16239.19941 73.83904 52.15426 NA 62.77332 80.12492
[7] 67.59979 69.03701 27.62606 71.91250 70.43789 52.99065
[13] 127.18236 71.84280 48.78537 154.67514 79.86964 84.08043
[19] 55.57392 22.77280
> colSd(tmp5)
[1] 127.433117 8.592965 7.221791 NA 7.922962 8.951252
[7] 8.221909 8.308852 5.256050 8.480124 8.392728 7.279467
[13] 11.277516 8.476013 6.984653 12.436846 8.936982 9.169538
[19] 7.454792 4.772085
> colMax(tmp5)
[1] 473.20236 83.17569 84.52247 NA 86.27881 82.80536 86.02888
[8] 85.92803 79.55103 85.28419 89.10411 79.30732 91.90788 79.55607
[15] 86.18483 88.25922 87.55190 88.08769 80.25295 79.73367
> colMin(tmp5)
[1] 61.40838 55.92819 61.37929 NA 64.55185 57.16349 61.27865 57.51223
[9] 62.93912 57.20714 63.96980 57.39923 56.66763 54.12369 66.03902 54.22065
[17] 56.07065 59.64151 55.68069 65.97676
>
> Max(tmp5,na.rm=TRUE)
[1] 473.2024
> Min(tmp5,na.rm=TRUE)
[1] 53.45856
> mean(tmp5,na.rm=TRUE)
[1] 72.89583
> Sum(tmp5,na.rm=TRUE)
[1] 14506.27
> Var(tmp5,na.rm=TRUE)
[1] 881.9911
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.09681 72.31393 73.51080 69.18281 70.75161 66.98049 72.76468 69.15089
[9] 70.63979 73.60183
> rowSums(tmp5,na.rm=TRUE)
[1] 1801.936 1446.279 1470.216 1383.656 1415.032 1339.610 1455.294 1383.018
[9] 1412.796 1398.435
> rowVars(tmp5,na.rm=TRUE)
[1] 8216.18353 63.88780 46.96335 47.97194 79.83648 45.53856
[7] 69.32509 52.18725 82.55358 103.23936
> rowSd(tmp5,na.rm=TRUE)
[1] 90.643166 7.992984 6.852981 6.926178 8.935126 6.748226 8.326169
[8] 7.224074 9.085900 10.160677
> rowMax(tmp5,na.rm=TRUE)
[1] 473.20236 88.08769 87.55190 86.27881 86.18483 79.73367 91.90788
[8] 83.69894 85.92803 89.10411
> rowMin(tmp5,na.rm=TRUE)
[1] 53.45856 55.92819 60.06682 58.01564 54.22065 54.12369 59.45410 56.07065
[9] 57.24069 55.68069
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.01263 66.44613 70.18830 71.03116 73.73923 66.55385 74.90438
[8] 71.67798 72.95696 70.69108 73.82782 69.17786 70.70923 67.09845
[15] 74.46309 71.80197 69.22819 72.19874 68.56200 71.46118
> colSums(tmp5,na.rm=TRUE)
[1] 1110.1263 664.4613 701.8830 639.2804 737.3923 665.5385 749.0438
[8] 716.7798 729.5696 706.9108 738.2782 691.7786 707.0923 670.9845
[15] 744.6309 718.0197 692.2819 721.9874 685.6200 714.6118
> colVars(tmp5,na.rm=TRUE)
[1] 16239.19941 73.83904 52.15426 68.02042 62.77332 80.12492
[7] 67.59979 69.03701 27.62606 71.91250 70.43789 52.99065
[13] 127.18236 71.84280 48.78537 154.67514 79.86964 84.08043
[19] 55.57392 22.77280
> colSd(tmp5,na.rm=TRUE)
[1] 127.433117 8.592965 7.221791 8.247449 7.922962 8.951252
[7] 8.221909 8.308852 5.256050 8.480124 8.392728 7.279467
[13] 11.277516 8.476013 6.984653 12.436846 8.936982 9.169538
[19] 7.454792 4.772085
> colMax(tmp5,na.rm=TRUE)
[1] 473.20236 83.17569 84.52247 78.90618 86.27881 82.80536 86.02888
[8] 85.92803 79.55103 85.28419 89.10411 79.30732 91.90788 79.55607
[15] 86.18483 88.25922 87.55190 88.08769 80.25295 79.73367
> colMin(tmp5,na.rm=TRUE)
[1] 61.40838 55.92819 61.37929 53.45856 64.55185 57.16349 61.27865 57.51223
[9] 62.93912 57.20714 63.96980 57.39923 56.66763 54.12369 66.03902 54.22065
[17] 56.07065 59.64151 55.68069 65.97676
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.09681 72.31393 73.51080 69.18281 70.75161 66.98049 72.76468 69.15089
[9] 70.63979 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1801.936 1446.279 1470.216 1383.656 1415.032 1339.610 1455.294 1383.018
[9] 1412.796 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 8216.18353 63.88780 46.96335 47.97194 79.83648 45.53856
[7] 69.32509 52.18725 82.55358 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 90.643166 7.992984 6.852981 6.926178 8.935126 6.748226 8.326169
[8] 7.224074 9.085900 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 473.20236 88.08769 87.55190 86.27881 86.18483 79.73367 91.90788
[8] 83.69894 85.92803 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 53.45856 55.92819 60.06682 58.01564 54.22065 54.12369 59.45410 56.07065
[9] 57.24069 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.97122 65.32029 68.59561 NaN 72.54099 65.46098 73.81705
[8] 73.25196 72.22428 70.71328 72.13045 69.65460 71.05079 67.95359
[15] 73.51370 71.11042 69.02793 71.03534 69.99326 72.02934
> colSums(tmp5,na.rm=TRUE)
[1] 1043.7410 587.8826 617.3605 0.0000 652.8689 589.1488 664.3535
[8] 659.2676 650.0185 636.4195 649.1741 626.8914 639.4571 611.5823
[15] 661.6233 639.9938 621.2514 639.3181 629.9394 648.2641
> colVars(tmp5,na.rm=TRUE)
[1] 17992.48863 68.80946 30.13624 NA 54.46762 76.70393
[7] 62.74918 49.79600 25.04018 80.89602 46.83080 57.05754
[13] 141.76767 72.59637 44.74342 168.62931 89.40216 79.36365
[19] 39.47506 21.98781
> colSd(tmp5,na.rm=TRUE)
[1] 134.136082 8.295147 5.489649 NA 7.380218 8.758078
[7] 7.921438 7.056628 5.004016 8.994221 6.843303 7.553644
[13] 11.906623 8.520350 6.689052 12.985735 9.455272 8.908628
[19] 6.282918 4.689116
> colMax(tmp5,na.rm=TRUE)
[1] 473.20236 83.17569 77.23431 -Inf 86.27881 82.80536 86.02888
[8] 85.92803 78.50144 85.28419 84.14640 79.30732 91.90788 79.55607
[15] 86.18483 88.25922 87.55190 88.08769 80.25295 79.73367
> colMin(tmp5,na.rm=TRUE)
[1] 61.40838 55.92819 61.37929 Inf 64.55185 57.16349 61.27865 65.39473
[9] 62.93912 57.20714 63.96980 57.39923 56.66763 54.12369 66.03902 54.22065
[17] 56.07065 59.64151 62.73472 65.97676
>
>
>
>
> 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] 297.6847 230.8865 267.2199 214.3626 217.8943 112.8482 272.8238 221.9689
[9] 305.5582 199.5476
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 297.6847 230.8865 267.2199 214.3626 217.8943 112.8482 272.8238 221.9689
[9] 305.5582 199.5476
>
>
>
> 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] 1.136868e-13 1.705303e-13 1.705303e-13 5.684342e-14 1.705303e-13
[6] 0.000000e+00 9.947598e-14 -1.136868e-13 -2.842171e-13 5.684342e-14
[11] 0.000000e+00 -2.842171e-14 -5.684342e-14 2.842171e-13 1.136868e-13
[16] 2.273737e-13 1.136868e-13 -2.842171e-13 -8.526513e-14 1.705303e-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)
+ }
6 15
9 7
3 17
3 10
10 2
3 19
9 12
5 5
6 6
3 12
8 12
7 16
4 10
9 16
3 4
2 6
7 12
2 8
2 15
6 13
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] 2.315987
> Min(tmp)
[1] -2.489089
> mean(tmp)
[1] -0.03177517
> Sum(tmp)
[1] -3.177517
> Var(tmp)
[1] 0.9091817
>
> rowMeans(tmp)
[1] -0.03177517
> rowSums(tmp)
[1] -3.177517
> rowVars(tmp)
[1] 0.9091817
> rowSd(tmp)
[1] 0.9535102
> rowMax(tmp)
[1] 2.315987
> rowMin(tmp)
[1] -2.489089
>
> colMeans(tmp)
[1] 0.567427475 0.237790569 -0.396422011 -0.387405120 -0.323672391
[6] -0.649054242 1.560157651 -0.002063835 -1.622641299 0.556162958
[11] -1.963009154 0.989208207 1.046529603 0.231532418 0.701760156
[16] -0.209413324 -1.833177583 0.203414531 -0.909724436 0.008487737
[21] -0.295412039 -0.209957981 -0.445948543 -0.549860555 0.263837336
[26] -0.686624267 0.655193131 -1.192218628 0.318606280 -1.148653402
[31] 1.440322321 -1.901891982 0.009296838 0.407527984 -0.986006047
[36] 0.200503199 -0.302091700 -0.040494923 -0.692309987 -0.365991278
[41] 1.285948583 -0.135165003 -2.489088661 -1.050595075 2.149148601
[46] 0.965330637 -1.475317584 0.109002509 -1.154132000 0.622923346
[51] -0.460756015 0.828078079 -0.592147755 0.092848575 -0.967738462
[56] 1.041357483 -0.390103232 -0.774029640 0.066736524 0.334718303
[61] 0.617484769 1.657325191 -0.355564441 -0.558103987 -0.690023883
[66] -0.113978648 -0.781240808 -0.637632671 0.030768038 1.065235087
[71] 1.115749391 -1.040803391 1.703195355 -0.768071394 -0.567494471
[76] -0.847993079 0.167645515 0.313848165 0.845721170 -0.792089902
[81] 0.179828018 -0.747131753 0.987059720 -1.422700652 -1.104625906
[86] 1.426316601 -0.293148173 0.205516441 1.351184062 0.537349526
[91] 2.115957463 -1.256798882 2.315986768 0.606306533 1.275720451
[96] -0.587368706 0.229442542 0.748356165 -0.424185578 0.024709853
> colSums(tmp)
[1] 0.567427475 0.237790569 -0.396422011 -0.387405120 -0.323672391
[6] -0.649054242 1.560157651 -0.002063835 -1.622641299 0.556162958
[11] -1.963009154 0.989208207 1.046529603 0.231532418 0.701760156
[16] -0.209413324 -1.833177583 0.203414531 -0.909724436 0.008487737
[21] -0.295412039 -0.209957981 -0.445948543 -0.549860555 0.263837336
[26] -0.686624267 0.655193131 -1.192218628 0.318606280 -1.148653402
[31] 1.440322321 -1.901891982 0.009296838 0.407527984 -0.986006047
[36] 0.200503199 -0.302091700 -0.040494923 -0.692309987 -0.365991278
[41] 1.285948583 -0.135165003 -2.489088661 -1.050595075 2.149148601
[46] 0.965330637 -1.475317584 0.109002509 -1.154132000 0.622923346
[51] -0.460756015 0.828078079 -0.592147755 0.092848575 -0.967738462
[56] 1.041357483 -0.390103232 -0.774029640 0.066736524 0.334718303
[61] 0.617484769 1.657325191 -0.355564441 -0.558103987 -0.690023883
[66] -0.113978648 -0.781240808 -0.637632671 0.030768038 1.065235087
[71] 1.115749391 -1.040803391 1.703195355 -0.768071394 -0.567494471
[76] -0.847993079 0.167645515 0.313848165 0.845721170 -0.792089902
[81] 0.179828018 -0.747131753 0.987059720 -1.422700652 -1.104625906
[86] 1.426316601 -0.293148173 0.205516441 1.351184062 0.537349526
[91] 2.115957463 -1.256798882 2.315986768 0.606306533 1.275720451
[96] -0.587368706 0.229442542 0.748356165 -0.424185578 0.024709853
> 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] 0.567427475 0.237790569 -0.396422011 -0.387405120 -0.323672391
[6] -0.649054242 1.560157651 -0.002063835 -1.622641299 0.556162958
[11] -1.963009154 0.989208207 1.046529603 0.231532418 0.701760156
[16] -0.209413324 -1.833177583 0.203414531 -0.909724436 0.008487737
[21] -0.295412039 -0.209957981 -0.445948543 -0.549860555 0.263837336
[26] -0.686624267 0.655193131 -1.192218628 0.318606280 -1.148653402
[31] 1.440322321 -1.901891982 0.009296838 0.407527984 -0.986006047
[36] 0.200503199 -0.302091700 -0.040494923 -0.692309987 -0.365991278
[41] 1.285948583 -0.135165003 -2.489088661 -1.050595075 2.149148601
[46] 0.965330637 -1.475317584 0.109002509 -1.154132000 0.622923346
[51] -0.460756015 0.828078079 -0.592147755 0.092848575 -0.967738462
[56] 1.041357483 -0.390103232 -0.774029640 0.066736524 0.334718303
[61] 0.617484769 1.657325191 -0.355564441 -0.558103987 -0.690023883
[66] -0.113978648 -0.781240808 -0.637632671 0.030768038 1.065235087
[71] 1.115749391 -1.040803391 1.703195355 -0.768071394 -0.567494471
[76] -0.847993079 0.167645515 0.313848165 0.845721170 -0.792089902
[81] 0.179828018 -0.747131753 0.987059720 -1.422700652 -1.104625906
[86] 1.426316601 -0.293148173 0.205516441 1.351184062 0.537349526
[91] 2.115957463 -1.256798882 2.315986768 0.606306533 1.275720451
[96] -0.587368706 0.229442542 0.748356165 -0.424185578 0.024709853
> colMin(tmp)
[1] 0.567427475 0.237790569 -0.396422011 -0.387405120 -0.323672391
[6] -0.649054242 1.560157651 -0.002063835 -1.622641299 0.556162958
[11] -1.963009154 0.989208207 1.046529603 0.231532418 0.701760156
[16] -0.209413324 -1.833177583 0.203414531 -0.909724436 0.008487737
[21] -0.295412039 -0.209957981 -0.445948543 -0.549860555 0.263837336
[26] -0.686624267 0.655193131 -1.192218628 0.318606280 -1.148653402
[31] 1.440322321 -1.901891982 0.009296838 0.407527984 -0.986006047
[36] 0.200503199 -0.302091700 -0.040494923 -0.692309987 -0.365991278
[41] 1.285948583 -0.135165003 -2.489088661 -1.050595075 2.149148601
[46] 0.965330637 -1.475317584 0.109002509 -1.154132000 0.622923346
[51] -0.460756015 0.828078079 -0.592147755 0.092848575 -0.967738462
[56] 1.041357483 -0.390103232 -0.774029640 0.066736524 0.334718303
[61] 0.617484769 1.657325191 -0.355564441 -0.558103987 -0.690023883
[66] -0.113978648 -0.781240808 -0.637632671 0.030768038 1.065235087
[71] 1.115749391 -1.040803391 1.703195355 -0.768071394 -0.567494471
[76] -0.847993079 0.167645515 0.313848165 0.845721170 -0.792089902
[81] 0.179828018 -0.747131753 0.987059720 -1.422700652 -1.104625906
[86] 1.426316601 -0.293148173 0.205516441 1.351184062 0.537349526
[91] 2.115957463 -1.256798882 2.315986768 0.606306533 1.275720451
[96] -0.587368706 0.229442542 0.748356165 -0.424185578 0.024709853
> colMedians(tmp)
[1] 0.567427475 0.237790569 -0.396422011 -0.387405120 -0.323672391
[6] -0.649054242 1.560157651 -0.002063835 -1.622641299 0.556162958
[11] -1.963009154 0.989208207 1.046529603 0.231532418 0.701760156
[16] -0.209413324 -1.833177583 0.203414531 -0.909724436 0.008487737
[21] -0.295412039 -0.209957981 -0.445948543 -0.549860555 0.263837336
[26] -0.686624267 0.655193131 -1.192218628 0.318606280 -1.148653402
[31] 1.440322321 -1.901891982 0.009296838 0.407527984 -0.986006047
[36] 0.200503199 -0.302091700 -0.040494923 -0.692309987 -0.365991278
[41] 1.285948583 -0.135165003 -2.489088661 -1.050595075 2.149148601
[46] 0.965330637 -1.475317584 0.109002509 -1.154132000 0.622923346
[51] -0.460756015 0.828078079 -0.592147755 0.092848575 -0.967738462
[56] 1.041357483 -0.390103232 -0.774029640 0.066736524 0.334718303
[61] 0.617484769 1.657325191 -0.355564441 -0.558103987 -0.690023883
[66] -0.113978648 -0.781240808 -0.637632671 0.030768038 1.065235087
[71] 1.115749391 -1.040803391 1.703195355 -0.768071394 -0.567494471
[76] -0.847993079 0.167645515 0.313848165 0.845721170 -0.792089902
[81] 0.179828018 -0.747131753 0.987059720 -1.422700652 -1.104625906
[86] 1.426316601 -0.293148173 0.205516441 1.351184062 0.537349526
[91] 2.115957463 -1.256798882 2.315986768 0.606306533 1.275720451
[96] -0.587368706 0.229442542 0.748356165 -0.424185578 0.024709853
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.5674275 0.2377906 -0.396422 -0.3874051 -0.3236724 -0.6490542 1.560158
[2,] 0.5674275 0.2377906 -0.396422 -0.3874051 -0.3236724 -0.6490542 1.560158
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.002063835 -1.622641 0.556163 -1.963009 0.9892082 1.04653 0.2315324
[2,] -0.002063835 -1.622641 0.556163 -1.963009 0.9892082 1.04653 0.2315324
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.7017602 -0.2094133 -1.833178 0.2034145 -0.9097244 0.008487737 -0.295412
[2,] 0.7017602 -0.2094133 -1.833178 0.2034145 -0.9097244 0.008487737 -0.295412
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.209958 -0.4459485 -0.5498606 0.2638373 -0.6866243 0.6551931 -1.192219
[2,] -0.209958 -0.4459485 -0.5498606 0.2638373 -0.6866243 0.6551931 -1.192219
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.3186063 -1.148653 1.440322 -1.901892 0.009296838 0.407528 -0.986006
[2,] 0.3186063 -1.148653 1.440322 -1.901892 0.009296838 0.407528 -0.986006
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.2005032 -0.3020917 -0.04049492 -0.69231 -0.3659913 1.285949 -0.135165
[2,] 0.2005032 -0.3020917 -0.04049492 -0.69231 -0.3659913 1.285949 -0.135165
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -2.489089 -1.050595 2.149149 0.9653306 -1.475318 0.1090025 -1.154132
[2,] -2.489089 -1.050595 2.149149 0.9653306 -1.475318 0.1090025 -1.154132
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.6229233 -0.460756 0.8280781 -0.5921478 0.09284857 -0.9677385 1.041357
[2,] 0.6229233 -0.460756 0.8280781 -0.5921478 0.09284857 -0.9677385 1.041357
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.3901032 -0.7740296 0.06673652 0.3347183 0.6174848 1.657325 -0.3555644
[2,] -0.3901032 -0.7740296 0.06673652 0.3347183 0.6174848 1.657325 -0.3555644
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.558104 -0.6900239 -0.1139786 -0.7812408 -0.6376327 0.03076804 1.065235
[2,] -0.558104 -0.6900239 -0.1139786 -0.7812408 -0.6376327 0.03076804 1.065235
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.115749 -1.040803 1.703195 -0.7680714 -0.5674945 -0.8479931 0.1676455
[2,] 1.115749 -1.040803 1.703195 -0.7680714 -0.5674945 -0.8479931 0.1676455
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.3138482 0.8457212 -0.7920899 0.179828 -0.7471318 0.9870597 -1.422701
[2,] 0.3138482 0.8457212 -0.7920899 0.179828 -0.7471318 0.9870597 -1.422701
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -1.104626 1.426317 -0.2931482 0.2055164 1.351184 0.5373495 2.115957
[2,] -1.104626 1.426317 -0.2931482 0.2055164 1.351184 0.5373495 2.115957
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.256799 2.315987 0.6063065 1.27572 -0.5873687 0.2294425 0.7483562
[2,] -1.256799 2.315987 0.6063065 1.27572 -0.5873687 0.2294425 0.7483562
[,99] [,100]
[1,] -0.4241856 0.02470985
[2,] -0.4241856 0.02470985
>
>
> Max(tmp2)
[1] 2.933476
> Min(tmp2)
[1] -2.513134
> mean(tmp2)
[1] 0.06293789
> Sum(tmp2)
[1] 6.293789
> Var(tmp2)
[1] 1.124989
>
> rowMeans(tmp2)
[1] 0.221963794 0.931059174 1.600807003 1.194026183 1.656749196
[6] -1.431468107 -0.111112921 -2.513134376 0.811307980 0.555173265
[11] 0.340382268 0.063679543 -0.691054350 0.021751264 0.634067819
[16] -1.271373259 0.177710390 2.835817854 -0.097105206 0.602992918
[21] 1.455474765 -0.534426563 0.742086126 -0.488195456 -0.287892025
[26] 0.008735225 -2.049599825 2.933476120 1.782515134 -0.022194681
[31] -1.325124797 -1.096920636 -0.059427332 -0.097426300 0.376209547
[36] -0.553833930 -0.213881945 -1.006208713 -1.243822091 1.054854815
[41] -0.273479495 -0.232510917 0.053146513 -0.923058747 -0.564664267
[46] 0.094523257 -0.977624780 -0.823937011 0.548794660 -1.102194334
[51] -0.555916710 -0.826848563 -0.580525566 -2.006395772 -0.893500837
[56] 1.550247770 -0.428518050 -1.435118291 1.024318132 0.001375095
[61] -0.500081525 1.198160343 0.232054095 -0.009938510 0.350845886
[66] 1.725963438 -0.695053139 0.794237094 -1.443040891 1.370318265
[71] 0.619832240 -0.656314763 -0.467108111 1.978084490 -0.584809921
[76] -0.302129257 1.055426481 0.881756557 0.423297084 -0.421402346
[81] 0.511381677 -1.846209624 1.174398063 -0.331747523 -0.163380601
[86] 1.682277946 0.984534538 -0.460743722 0.480844927 0.363090352
[91] 2.082890808 -0.149602854 0.460537114 0.984729840 1.785966214
[96] -0.421094666 -0.094145529 -1.045961740 -1.965543395 0.156719846
> rowSums(tmp2)
[1] 0.221963794 0.931059174 1.600807003 1.194026183 1.656749196
[6] -1.431468107 -0.111112921 -2.513134376 0.811307980 0.555173265
[11] 0.340382268 0.063679543 -0.691054350 0.021751264 0.634067819
[16] -1.271373259 0.177710390 2.835817854 -0.097105206 0.602992918
[21] 1.455474765 -0.534426563 0.742086126 -0.488195456 -0.287892025
[26] 0.008735225 -2.049599825 2.933476120 1.782515134 -0.022194681
[31] -1.325124797 -1.096920636 -0.059427332 -0.097426300 0.376209547
[36] -0.553833930 -0.213881945 -1.006208713 -1.243822091 1.054854815
[41] -0.273479495 -0.232510917 0.053146513 -0.923058747 -0.564664267
[46] 0.094523257 -0.977624780 -0.823937011 0.548794660 -1.102194334
[51] -0.555916710 -0.826848563 -0.580525566 -2.006395772 -0.893500837
[56] 1.550247770 -0.428518050 -1.435118291 1.024318132 0.001375095
[61] -0.500081525 1.198160343 0.232054095 -0.009938510 0.350845886
[66] 1.725963438 -0.695053139 0.794237094 -1.443040891 1.370318265
[71] 0.619832240 -0.656314763 -0.467108111 1.978084490 -0.584809921
[76] -0.302129257 1.055426481 0.881756557 0.423297084 -0.421402346
[81] 0.511381677 -1.846209624 1.174398063 -0.331747523 -0.163380601
[86] 1.682277946 0.984534538 -0.460743722 0.480844927 0.363090352
[91] 2.082890808 -0.149602854 0.460537114 0.984729840 1.785966214
[96] -0.421094666 -0.094145529 -1.045961740 -1.965543395 0.156719846
> 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] 0.221963794 0.931059174 1.600807003 1.194026183 1.656749196
[6] -1.431468107 -0.111112921 -2.513134376 0.811307980 0.555173265
[11] 0.340382268 0.063679543 -0.691054350 0.021751264 0.634067819
[16] -1.271373259 0.177710390 2.835817854 -0.097105206 0.602992918
[21] 1.455474765 -0.534426563 0.742086126 -0.488195456 -0.287892025
[26] 0.008735225 -2.049599825 2.933476120 1.782515134 -0.022194681
[31] -1.325124797 -1.096920636 -0.059427332 -0.097426300 0.376209547
[36] -0.553833930 -0.213881945 -1.006208713 -1.243822091 1.054854815
[41] -0.273479495 -0.232510917 0.053146513 -0.923058747 -0.564664267
[46] 0.094523257 -0.977624780 -0.823937011 0.548794660 -1.102194334
[51] -0.555916710 -0.826848563 -0.580525566 -2.006395772 -0.893500837
[56] 1.550247770 -0.428518050 -1.435118291 1.024318132 0.001375095
[61] -0.500081525 1.198160343 0.232054095 -0.009938510 0.350845886
[66] 1.725963438 -0.695053139 0.794237094 -1.443040891 1.370318265
[71] 0.619832240 -0.656314763 -0.467108111 1.978084490 -0.584809921
[76] -0.302129257 1.055426481 0.881756557 0.423297084 -0.421402346
[81] 0.511381677 -1.846209624 1.174398063 -0.331747523 -0.163380601
[86] 1.682277946 0.984534538 -0.460743722 0.480844927 0.363090352
[91] 2.082890808 -0.149602854 0.460537114 0.984729840 1.785966214
[96] -0.421094666 -0.094145529 -1.045961740 -1.965543395 0.156719846
> rowMin(tmp2)
[1] 0.221963794 0.931059174 1.600807003 1.194026183 1.656749196
[6] -1.431468107 -0.111112921 -2.513134376 0.811307980 0.555173265
[11] 0.340382268 0.063679543 -0.691054350 0.021751264 0.634067819
[16] -1.271373259 0.177710390 2.835817854 -0.097105206 0.602992918
[21] 1.455474765 -0.534426563 0.742086126 -0.488195456 -0.287892025
[26] 0.008735225 -2.049599825 2.933476120 1.782515134 -0.022194681
[31] -1.325124797 -1.096920636 -0.059427332 -0.097426300 0.376209547
[36] -0.553833930 -0.213881945 -1.006208713 -1.243822091 1.054854815
[41] -0.273479495 -0.232510917 0.053146513 -0.923058747 -0.564664267
[46] 0.094523257 -0.977624780 -0.823937011 0.548794660 -1.102194334
[51] -0.555916710 -0.826848563 -0.580525566 -2.006395772 -0.893500837
[56] 1.550247770 -0.428518050 -1.435118291 1.024318132 0.001375095
[61] -0.500081525 1.198160343 0.232054095 -0.009938510 0.350845886
[66] 1.725963438 -0.695053139 0.794237094 -1.443040891 1.370318265
[71] 0.619832240 -0.656314763 -0.467108111 1.978084490 -0.584809921
[76] -0.302129257 1.055426481 0.881756557 0.423297084 -0.421402346
[81] 0.511381677 -1.846209624 1.174398063 -0.331747523 -0.163380601
[86] 1.682277946 0.984534538 -0.460743722 0.480844927 0.363090352
[91] 2.082890808 -0.149602854 0.460537114 0.984729840 1.785966214
[96] -0.421094666 -0.094145529 -1.045961740 -1.965543395 0.156719846
>
> colMeans(tmp2)
[1] 0.06293789
> colSums(tmp2)
[1] 6.293789
> colVars(tmp2)
[1] 1.124989
> colSd(tmp2)
[1] 1.060655
> colMax(tmp2)
[1] 2.933476
> colMin(tmp2)
[1] -2.513134
> colMedians(tmp2)
[1] -0.0160666
> colRanges(tmp2)
[,1]
[1,] -2.513134
[2,] 2.933476
>
> 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] -2.05878430 2.61741261 3.94737590 -0.00175216 1.95568479 -1.07905333
[7] -2.09912486 0.47451660 -2.23706479 3.25424868
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.6402481
[2,] -0.6699741
[3,] -0.3610334
[4,] 0.4436199
[5,] 1.1310048
>
> rowApply(tmp,sum)
[1] 3.4960376 1.5544739 -0.9281525 0.2404966 2.5556604 0.3290195
[7] 0.9498076 -1.9041748 0.9503548 -2.4700640
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 6 2 1 7 1 10 2 4 2 6
[2,] 8 3 6 9 3 9 3 10 9 4
[3,] 5 10 8 8 8 4 6 9 1 10
[4,] 1 4 9 1 9 5 7 7 10 3
[5,] 7 5 7 6 2 8 10 2 7 2
[6,] 4 7 4 5 5 1 5 5 6 8
[7,] 9 9 3 3 6 7 1 1 5 1
[8,] 10 1 2 2 10 6 8 6 4 9
[9,] 2 8 10 4 4 2 4 3 3 7
[10,] 3 6 5 10 7 3 9 8 8 5
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.66954202 -0.06757144 -4.18521586 -0.92126148 0.22499332 3.73420000
[7] 1.98850633 -2.94290187 -1.90432935 1.92376802 -0.10087491 2.02575264
[13] -1.58922405 -3.06996593 0.65913935 -0.48444699 -1.04529871 -0.33304040
[19] -0.69979108 2.40614796
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.6905402
[2,] -0.4836764
[3,] 0.7311017
[4,] 0.8999056
[5,] 2.2127513
>
> rowApply(tmp,sum)
[1] 4.264121 2.736232 -4.470049 -3.503848 -1.738328
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 20 20 1 17
[2,] 3 14 3 18 7
[3,] 7 1 2 7 3
[4,] 18 17 9 4 2
[5,] 13 9 12 10 12
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.4836764 -0.7634055 -0.1814483 1.6094583 0.50137523 1.09111431
[2,] 2.2127513 0.7014748 -1.4600927 0.8438833 0.07526714 0.31613669
[3,] 0.7311017 -0.9047075 -0.9462563 -0.3166096 -0.12329164 0.01370267
[4,] -1.6905402 1.6344206 -0.4428541 -1.5523393 -0.26734868 -0.10537990
[5,] 0.8999056 -0.7353538 -1.1545645 -1.5056543 0.03899128 2.41862623
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.735051158 0.8116679 -0.5299254 1.22629111 -1.8512024 0.3122226
[2,] -1.168835478 -0.4137450 0.7951925 1.05644566 1.4207441 0.8186518
[3,] -0.005955675 -0.2817346 0.5273527 0.22945881 -0.4826025 0.6002776
[4,] 1.808579893 -1.4751826 -1.5805121 0.07176758 -0.1211654 -0.2557740
[5,] -0.380333568 -1.5839076 -1.1164371 -0.66019514 0.9333513 0.5503746
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.04474777 -1.4742737 -0.17941043 1.6501556 -0.4907703 0.01078636
[2,] -0.62822757 -1.3817093 0.23883834 0.5661225 -0.3107614 -0.27945077
[3,] -0.68626810 -0.7912115 0.09113454 -1.0404301 -0.4613317 -0.18258508
[4,] -1.63313279 1.3228357 -0.25410718 -1.0787726 -0.3203189 1.15969730
[5,] 1.40315218 -0.7456071 0.76268407 -0.5815224 0.5378837 -1.04148820
[,19] [,20]
[1,] 0.29866774 1.0161909
[2,] -0.94790266 0.2814483
[3,] 0.42478997 -0.8648827
[4,] -0.39456366 1.6708422
[5,] -0.08078247 0.3025492
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 652 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.23-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-3.23-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.882015 0.7037565 -1.474278 0.1216807 -2.206401 -0.5566554 0.5735491
col8 col9 col10 col11 col12 col13 col14
row1 -0.1156908 0.7927286 0.1748872 -0.8619647 -1.780689 -0.8036401 0.2534584
col15 col16 col17 col18 col19 col20
row1 -0.6798811 1.175636 0.6951786 0.3893865 1.597784 -0.8292514
> tmp[,"col10"]
col10
row1 0.1748872
row2 0.8027495
row3 -1.0438107
row4 -1.7683477
row5 1.0155509
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.882015 0.7037565 -1.4742784 0.1216807 -2.2064006 -0.5566554 0.5735491
row5 -0.332587 0.9551798 0.2003636 0.1272846 0.4334106 -0.8319897 -0.5159378
col8 col9 col10 col11 col12 col13 col14
row1 -0.1156908 0.7927286 0.1748872 -0.8619647 -1.7806888 -0.8036401 0.2534584
row5 -0.1017641 0.3522037 1.0155509 -0.7367159 0.7093499 -1.5750373 0.7847975
col15 col16 col17 col18 col19 col20
row1 -0.6798811 1.17563623 0.6951786 0.3893865 1.597784 -0.8292514
row5 -0.6853034 -0.02792892 -0.4358201 -1.2828000 0.796912 1.7079908
> tmp[,c("col6","col20")]
col6 col20
row1 -0.5566554 -0.82925135
row2 -0.1398194 1.74564469
row3 1.2407992 -0.04444825
row4 0.3069813 -0.04581310
row5 -0.8319897 1.70799078
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.5566554 -0.8292514
row5 -0.8319897 1.7079908
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.72469 49.44048 48.73923 50.25144 48.81751 104.7924 49.61423 48.70171
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.90474 48.00845 51.26357 49.67104 50.71907 49.35664 50.75496 52.04769
col17 col18 col19 col20
row1 50.2628 47.9749 49.35344 105.7779
> tmp[,"col10"]
col10
row1 48.00845
row2 28.44140
row3 29.58843
row4 29.97890
row5 49.37050
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.72469 49.44048 48.73923 50.25144 48.81751 104.7924 49.61423 48.70171
row5 49.56514 50.17351 49.25396 51.41898 51.00699 105.3745 49.58091 51.22299
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.90474 48.00845 51.26357 49.67104 50.71907 49.35664 50.75496 52.04769
row5 49.87381 49.37050 50.15817 49.67755 46.74431 49.88591 51.32903 48.84555
col17 col18 col19 col20
row1 50.26280 47.97490 49.35344 105.7779
row5 51.28186 49.83069 47.94524 105.1766
> tmp[,c("col6","col20")]
col6 col20
row1 104.79240 105.77791
row2 75.39489 76.53316
row3 74.63767 74.54678
row4 76.18507 75.04273
row5 105.37451 105.17655
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.7924 105.7779
row5 105.3745 105.1766
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.7924 105.7779
row5 105.3745 105.1766
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.35715369
[2,] 1.06724306
[3,] -0.09021719
[4,] -0.54692443
[5,] 0.65496496
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.1338108 -0.7002964
[2,] 0.9657730 0.7299729
[3,] 1.0299353 0.9066856
[4,] -0.6057864 -1.0373074
[5,] -1.7999851 1.8492790
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.3300532 -0.5807892
[2,] 0.0124068 0.3381008
[3,] 1.1662621 1.0905322
[4,] 0.4085120 -0.4682030
[5,] 0.3979740 0.1794036
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.3300532
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.3300532
[2,] 0.0124068
>
>
>
> 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 -0.07867782 -0.2901258 -0.7128567 0.2147730 -0.3984314 -1.2317419
row1 0.32853784 -0.8784173 0.4447412 0.3186902 1.8570563 0.7382832
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -1.3685220 1.2736994 0.2917756 -0.9232025 1.68208999 1.077982 -2.5116231
row1 -0.9798132 -0.5474345 0.3249205 -0.2251598 -0.04632948 1.396094 -0.6836344
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.919681 0.9797314 -0.8332691 -1.915390 -2.7252768 1.347601 1.7164102
row1 1.487752 -1.8713231 -0.7593938 -0.419001 0.6869265 0.131488 -0.4536383
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.4693476 0.9891445 0.9796127 -0.7269229 -1.402519 1.372235 -0.04197612
[,8] [,9] [,10]
row2 0.2955601 1.439193 -0.02565466
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.4970338 1.386307 -0.4635299 1.417386 -0.650054 -0.3943007 -0.4572451
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.05984374 1.751798 0.6545103 -0.5187024 -0.4442943 -0.6740389 0.7603299
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.151453 -0.1517035 -0.4527583 -1.121134 -1.022856 0.2016821
>
>
> 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: 0x60e5f1c02f70>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM203ef054fb5821"
[2] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM203ef0169e1cbd"
[3] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM203ef0556fd93"
[4] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM203ef01f130811"
[5] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM203ef04fe52048"
[6] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM203ef04c86e94d"
[7] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM203ef03f72d721"
[8] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM203ef013acee96"
[9] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM203ef01c20a002"
[10] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM203ef07ec4901c"
[11] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM203ef048fd7396"
[12] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM203ef02ab4dfff"
[13] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM203ef02232b8ef"
[14] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM203ef05515cd57"
[15] "/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM203ef04e6219b5"
>
>
> ### 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: 0x60e5f1a78410>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x60e5f1a78410>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x60e5f1a78410>
> rowMedians(tmp)
[1] -0.4534690620 -0.2789227347 0.4066375173 0.2279811409 0.3713333004
[6] -0.5196354647 -0.4733461511 0.0440568332 0.1005168016 -0.1290050834
[11] 0.4148821775 0.4683329637 -0.0497295951 0.1851268476 -0.1984458267
[16] -0.1722829808 -0.0853024120 0.3728401102 -0.0618174003 0.4026763641
[21] -0.1714847421 -0.2750568796 0.1639239095 -0.0551170049 0.1487860626
[26] -0.1208254895 0.0694969903 -0.0268221932 0.1666084950 0.0191194891
[31] -0.0630806586 -0.2733474283 0.2879929934 0.3124072780 0.2335870704
[36] -0.3219312735 -0.1515489826 0.3670233281 0.2423778566 0.5217411542
[41] 0.4865601466 -0.8187197579 0.1363817205 -0.0537661642 -0.2555922336
[46] 0.4200815892 -0.9292094922 -0.2873294349 -0.4449546758 0.0735606129
[51] 0.2920226010 -0.1518765048 0.7740547399 -0.1539321168 -0.1530164145
[56] -0.0520228493 0.6149890051 -0.3224704465 0.1390867125 -0.0706103029
[61] 0.0270869820 -0.0346215179 -0.5046327489 0.5230405749 0.3453849520
[66] 0.1647673852 -0.6068129507 -0.1037682782 0.5136991615 0.3924696899
[71] 0.1205757295 -0.1158959251 -0.3094952838 -0.1109199931 -0.4943045595
[76] 0.2832412157 -0.0814751290 -0.2921680604 -0.1613747340 -0.3784976105
[81] 0.0499844820 -0.1147868903 -0.4548996448 0.3664128069 0.1188777068
[86] -0.2085364057 0.0033815433 -0.4984441213 -0.0953923866 -0.3803846517
[91] 0.3096477622 0.3171426690 0.3831472004 0.4947206420 0.0010144911
[96] -0.0313120554 0.1193529093 -0.1582892481 0.2278400645 0.0551262790
[101] 0.0367445701 0.1581301065 0.4765498975 -0.7697377044 0.8717145866
[106] 0.1420801056 0.4378678139 0.0550453042 0.4780919239 0.2735502406
[111] -0.2007195519 -0.0193401573 -0.1333041581 0.2033184268 0.0581562282
[116] 0.2257253908 -0.1311929075 -0.6011219564 -0.3184438795 0.0425928486
[121] 0.0438124649 -0.3335358655 0.0161714063 -0.2224623866 0.3540630108
[126] -0.0628261796 0.3194297100 -0.5724667459 -0.0410835032 -0.3779537439
[131] 0.3187267361 0.4722202649 0.7607600841 -0.6687796243 -0.0870860718
[136] -0.2387255250 0.1101379191 0.0107841014 0.2801940997 0.1315604071
[141] 0.0863707461 -0.0726000688 -0.0940148493 -0.3513354713 0.2030822050
[146] -0.1753949083 -0.6244052936 0.3271857446 0.2814975178 0.0757100638
[151] -0.1854454569 0.3964689159 -0.1809050685 -0.0850447404 0.3749961708
[156] -0.0770874163 -0.1611840401 0.1740522139 0.1812139422 -0.1237706104
[161] -0.2439684751 0.4701355295 0.1975573025 -0.5585466709 -0.2994212237
[166] 0.0941768030 -0.0218326453 -0.1224060897 0.0007036165 0.8226849563
[171] -0.2940963623 -0.1603800580 0.1881283674 0.7103374949 0.4871629523
[176] -0.1622697768 0.1344022944 -0.1216451945 0.6696128695 -0.1837187110
[181] -0.3802177226 0.4476782874 -0.3364029433 0.2182848884 -0.0488099252
[186] 0.0377954885 -0.7067048059 -0.3877491883 -0.4798283571 0.1198150603
[191] 0.0729353965 0.4494526192 -0.0002056692 0.6166558709 -0.1560371053
[196] -0.4617639786 -0.7910410475 0.5071704118 -0.5304433523 0.0047261943
[201] -0.2533051143 0.2727334007 0.1749138236 -0.1424989636 0.1376174216
[206] 0.1366204113 0.0352729433 -0.1378637430 -0.4799514801 -0.5151543325
[211] 0.1819316852 0.0097326724 -0.0644438354 -0.1385422930 0.0595155532
[216] -0.0482279344 -0.2461520805 -0.1715796340 0.1558584803 -0.2305050176
[221] -0.1184210506 0.1454765026 -0.0204853923 -0.8503071004 0.0905729459
[226] -0.0343400263 0.0757261643 -0.1525012367 -0.3836490461 -0.0887573928
>
> proc.time()
user system elapsed
1.337 1.449 2.775
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences"
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: 0x64064f826b20>
> .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: 0x64064f826b20>
> .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: 0x64064f826b20>
> .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: 0x64064f826b20>
> 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: 0x64064f807410>
> .Call("R_bm_AddColumn",P)
<pointer: 0x64064f807410>
> .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: 0x64064f807410>
> .Call("R_bm_AddColumn",P)
<pointer: 0x64064f807410>
> .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: 0x64064f807410>
> 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: 0x64064e0b47a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x64064e0b47a0>
> .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: 0x64064e0b47a0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x64064e0b47a0>
> .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: 0x64064e0b47a0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x64064e0b47a0>
> .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: 0x64064e0b47a0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x64064e0b47a0>
> .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: 0x64064e0b47a0>
> 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: 0x64064f086680>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x64064f086680>
> .Call("R_bm_AddColumn",P)
<pointer: 0x64064f086680>
> .Call("R_bm_AddColumn",P)
<pointer: 0x64064f086680>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile203f782d2e8d49" "BufferedMatrixFile203f786a6e021b"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile203f782d2e8d49" "BufferedMatrixFile203f786a6e021b"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x64064ee1a490>
> .Call("R_bm_AddColumn",P)
<pointer: 0x64064ee1a490>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x64064ee1a490>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x64064ee1a490>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x64064ee1a490>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x64064ee1a490>
> .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: 0x640650476110>
> .Call("R_bm_AddColumn",P)
<pointer: 0x640650476110>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x640650476110>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x640650476110>
> 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: 0x6406505195e0>
> .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: 0x6406505195e0>
> rm(P)
>
> proc.time()
user system elapsed
0.258 0.047 0.292
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences"
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Platform: x86_64-pc-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
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.232 0.053 0.271