Ben Bolstad
| Snapshot Date: 2025-08-28 13:40 -0400 (Thu, 28 Aug 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_21 |
| git_last_commit: aa9e634 |
| git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-09-01 11:38 -0400 (Mon, 01 Sep 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4824 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root" | 4606 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4547 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4579 |
| 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 252/2341 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.72.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| kunpeng2 | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.72.0 |
| Command: /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.21-bioc/R/site-library --timings BufferedMatrix_1.72.0.tar.gz |
| StartedAt: 2025-08-31 20:40:08 -0400 (Sun, 31 Aug 2025) |
| EndedAt: 2025-08-31 20:40:33 -0400 (Sun, 31 Aug 2025) |
| EllapsedTime: 25.1 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.21-bioc/R/site-library --timings BufferedMatrix_1.72.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.1 (2025-06-13)
* 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 ‘1.72.0’
* 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 ... 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-3.21-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.21-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.72.0’
** 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-3.21-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-3.21-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-3.21-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-3.21-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-3.21-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-3.21-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.21-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 4.5.1 (2025-06-13) -- "Great Square Root"
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
0.259 0.054 0.300
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 (2025-06-13) -- "Great Square Root"
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-3.21-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 478417 25.6 1047105 56 639600 34.2
Vcells 885231 6.8 8388608 64 2081598 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] "Sun Aug 31 20:40:23 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] "Sun Aug 31 20:40:23 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: 0x6065a7552ad0>
>
>
>
> 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] "Sun Aug 31 20:40:24 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] "Sun Aug 31 20:40:24 2025"
>
> ColMode(tmp2)
<pointer: 0x6065a7552ad0>
>
>
>
> ### 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,] 101.09519947 0.10307208 1.1209725 0.6660944
[2,] 0.01739696 1.48654485 2.3689864 -1.1421940
[3,] -1.78312963 -0.01082322 0.8567945 0.3609484
[4,] -0.27789715 -0.15068666 1.0905238 0.7484635
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-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,] 101.09519947 0.10307208 1.1209725 0.6660944
[2,] 0.01739696 1.48654485 2.3689864 1.1421940
[3,] 1.78312963 0.01082322 0.8567945 0.3609484
[4,] 0.27789715 0.15068666 1.0905238 0.7484635
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-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,] 10.0546109 0.3210484 1.0587599 0.8161461
[2,] 0.1318975 1.2192395 1.5391512 1.0687348
[3,] 1.3353388 0.1040347 0.9256319 0.6007898
[4,] 0.5271595 0.3881838 1.0442815 0.8651379
>
> 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-3.21-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,] 226.64131 28.31356 36.70857 33.82756
[2,] 26.33637 38.67894 42.76050 36.82954
[3,] 40.13652 26.05117 35.11311 31.36885
[4,] 30.54949 29.03252 36.53334 34.39984
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6065a818e960>
> exp(tmp5)
<pointer: 0x6065a818e960>
> log(tmp5,2)
<pointer: 0x6065a818e960>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.7242
> Min(tmp5)
[1] 54.0026
> mean(tmp5)
[1] 71.94043
> Sum(tmp5)
[1] 14388.09
> Var(tmp5)
[1] 877.5391
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.30255 67.88687 71.56697 69.13849 68.14797 68.72668 67.24538 71.48467
[9] 73.97242 69.93226
> rowSums(tmp5)
[1] 1826.051 1357.737 1431.339 1382.770 1362.959 1374.534 1344.908 1429.693
[9] 1479.448 1398.645
> rowVars(tmp5)
[1] 8071.20932 81.84358 65.06880 68.11659 46.07373 18.58889
[7] 34.86348 110.94066 110.17166 105.83578
> rowSd(tmp5)
[1] 89.839909 9.046744 8.066524 8.253277 6.787764 4.311483 5.904530
[8] 10.532837 10.496269 10.287652
> rowMax(tmp5)
[1] 471.72419 89.00038 86.29992 83.75739 79.79061 78.86182 80.03121
[8] 87.51468 90.93890 89.43641
> rowMin(tmp5)
[1] 58.93096 54.81571 54.22210 55.49732 54.50357 60.91257 60.24762 54.00260
[9] 57.13932 54.47079
>
> colMeans(tmp5)
[1] 107.24565 69.17083 71.94759 67.37605 67.77238 72.03864 73.88447
[8] 69.28025 70.27534 70.22738 69.14036 70.37643 71.31445 73.72310
[15] 69.73105 70.00304 71.67336 69.42794 67.17530 67.02489
> colSums(tmp5)
[1] 1072.4565 691.7083 719.4759 673.7605 677.7238 720.3864 738.8447
[8] 692.8025 702.7534 702.2738 691.4036 703.7643 713.1445 737.2310
[15] 697.3105 700.0304 716.7336 694.2794 671.7530 670.2489
> colVars(tmp5)
[1] 16515.18916 107.78215 95.69052 46.70006 13.31004 50.86648
[7] 71.49344 47.86733 88.08609 29.14565 21.29389 73.40349
[13] 104.97872 130.08874 123.16452 57.32942 130.84973 82.59056
[19] 23.60462 51.42782
> colSd(tmp5)
[1] 128.511436 10.381818 9.782153 6.833744 3.648293 7.132074
[7] 8.455380 6.918622 9.385419 5.398671 4.614531 8.567584
[13] 10.245912 11.405645 11.097951 7.571619 11.438957 9.087935
[19] 4.858459 7.171320
> colMax(tmp5)
[1] 471.72419 86.05036 89.00038 76.65587 74.11611 78.75202 90.93890
[8] 82.46943 90.78667 81.28117 77.61391 85.33570 86.09045 88.75335
[15] 89.43641 82.29246 90.81167 86.29992 77.28007 77.16901
> colMin(tmp5)
[1] 54.81571 54.22210 54.00260 54.47079 60.95158 55.49732 62.12255 61.93115
[9] 60.91257 64.07952 63.58858 55.85156 55.24374 56.11626 57.64568 59.32525
[17] 54.50357 56.34820 60.17268 57.13932
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 91.30255 67.88687 71.56697 69.13849 68.14797 68.72668 67.24538 71.48467
[9] NA 69.93226
> rowSums(tmp5)
[1] 1826.051 1357.737 1431.339 1382.770 1362.959 1374.534 1344.908 1429.693
[9] NA 1398.645
> rowVars(tmp5)
[1] 8071.20932 81.84358 65.06880 68.11659 46.07373 18.58889
[7] 34.86348 110.94066 111.27231 105.83578
> rowSd(tmp5)
[1] 89.839909 9.046744 8.066524 8.253277 6.787764 4.311483 5.904530
[8] 10.532837 10.548569 10.287652
> rowMax(tmp5)
[1] 471.72419 89.00038 86.29992 83.75739 79.79061 78.86182 80.03121
[8] 87.51468 NA 89.43641
> rowMin(tmp5)
[1] 58.93096 54.81571 54.22210 55.49732 54.50357 60.91257 60.24762 54.00260
[9] NA 54.47079
>
> colMeans(tmp5)
[1] 107.24565 69.17083 71.94759 67.37605 67.77238 72.03864 73.88447
[8] 69.28025 70.27534 NA 69.14036 70.37643 71.31445 73.72310
[15] 69.73105 70.00304 71.67336 69.42794 67.17530 67.02489
> colSums(tmp5)
[1] 1072.4565 691.7083 719.4759 673.7605 677.7238 720.3864 738.8447
[8] 692.8025 702.7534 NA 691.4036 703.7643 713.1445 737.2310
[15] 697.3105 700.0304 716.7336 694.2794 671.7530 670.2489
> colVars(tmp5)
[1] 16515.18916 107.78215 95.69052 46.70006 13.31004 50.86648
[7] 71.49344 47.86733 88.08609 NA 21.29389 73.40349
[13] 104.97872 130.08874 123.16452 57.32942 130.84973 82.59056
[19] 23.60462 51.42782
> colSd(tmp5)
[1] 128.511436 10.381818 9.782153 6.833744 3.648293 7.132074
[7] 8.455380 6.918622 9.385419 NA 4.614531 8.567584
[13] 10.245912 11.405645 11.097951 7.571619 11.438957 9.087935
[19] 4.858459 7.171320
> colMax(tmp5)
[1] 471.72419 86.05036 89.00038 76.65587 74.11611 78.75202 90.93890
[8] 82.46943 90.78667 NA 77.61391 85.33570 86.09045 88.75335
[15] 89.43641 82.29246 90.81167 86.29992 77.28007 77.16901
> colMin(tmp5)
[1] 54.81571 54.22210 54.00260 54.47079 60.95158 55.49732 62.12255 61.93115
[9] 60.91257 NA 63.58858 55.85156 55.24374 56.11626 57.64568 59.32525
[17] 54.50357 56.34820 60.17268 57.13932
>
> Max(tmp5,na.rm=TRUE)
[1] 471.7242
> Min(tmp5,na.rm=TRUE)
[1] 54.0026
> mean(tmp5,na.rm=TRUE)
[1] 71.97677
> Sum(tmp5,na.rm=TRUE)
[1] 14323.38
> Var(tmp5,na.rm=TRUE)
[1] 881.7056
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.30255 67.88687 71.56697 69.13849 68.14797 68.72668 67.24538 71.48467
[9] 74.46006 69.93226
> rowSums(tmp5,na.rm=TRUE)
[1] 1826.051 1357.737 1431.339 1382.770 1362.959 1374.534 1344.908 1429.693
[9] 1414.741 1398.645
> rowVars(tmp5,na.rm=TRUE)
[1] 8071.20932 81.84358 65.06880 68.11659 46.07373 18.58889
[7] 34.86348 110.94066 111.27231 105.83578
> rowSd(tmp5,na.rm=TRUE)
[1] 89.839909 9.046744 8.066524 8.253277 6.787764 4.311483 5.904530
[8] 10.532837 10.548569 10.287652
> rowMax(tmp5,na.rm=TRUE)
[1] 471.72419 89.00038 86.29992 83.75739 79.79061 78.86182 80.03121
[8] 87.51468 90.93890 89.43641
> rowMin(tmp5,na.rm=TRUE)
[1] 58.93096 54.81571 54.22210 55.49732 54.50357 60.91257 60.24762 54.00260
[9] 57.13932 54.47079
>
> colMeans(tmp5,na.rm=TRUE)
[1] 107.24565 69.17083 71.94759 67.37605 67.77238 72.03864 73.88447
[8] 69.28025 70.27534 70.84072 69.14036 70.37643 71.31445 73.72310
[15] 69.73105 70.00304 71.67336 69.42794 67.17530 67.02489
> colSums(tmp5,na.rm=TRUE)
[1] 1072.4565 691.7083 719.4759 673.7605 677.7238 720.3864 738.8447
[8] 692.8025 702.7534 637.5665 691.4036 703.7643 713.1445 737.2310
[15] 697.3105 700.0304 716.7336 694.2794 671.7530 670.2489
> colVars(tmp5,na.rm=TRUE)
[1] 16515.18916 107.78215 95.69052 46.70006 13.31004 50.86648
[7] 71.49344 47.86733 88.08609 28.55677 21.29389 73.40349
[13] 104.97872 130.08874 123.16452 57.32942 130.84973 82.59056
[19] 23.60462 51.42782
> colSd(tmp5,na.rm=TRUE)
[1] 128.511436 10.381818 9.782153 6.833744 3.648293 7.132074
[7] 8.455380 6.918622 9.385419 5.343853 4.614531 8.567584
[13] 10.245912 11.405645 11.097951 7.571619 11.438957 9.087935
[19] 4.858459 7.171320
> colMax(tmp5,na.rm=TRUE)
[1] 471.72419 86.05036 89.00038 76.65587 74.11611 78.75202 90.93890
[8] 82.46943 90.78667 81.28117 77.61391 85.33570 86.09045 88.75335
[15] 89.43641 82.29246 90.81167 86.29992 77.28007 77.16901
> colMin(tmp5,na.rm=TRUE)
[1] 54.81571 54.22210 54.00260 54.47079 60.95158 55.49732 62.12255 61.93115
[9] 60.91257 64.07952 63.58858 55.85156 55.24374 56.11626 57.64568 59.32525
[17] 54.50357 56.34820 60.17268 57.13932
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.30255 67.88687 71.56697 69.13849 68.14797 68.72668 67.24538 71.48467
[9] NaN 69.93226
> rowSums(tmp5,na.rm=TRUE)
[1] 1826.051 1357.737 1431.339 1382.770 1362.959 1374.534 1344.908 1429.693
[9] 0.000 1398.645
> rowVars(tmp5,na.rm=TRUE)
[1] 8071.20932 81.84358 65.06880 68.11659 46.07373 18.58889
[7] 34.86348 110.94066 NA 105.83578
> rowSd(tmp5,na.rm=TRUE)
[1] 89.839909 9.046744 8.066524 8.253277 6.787764 4.311483 5.904530
[8] 10.532837 NA 10.287652
> rowMax(tmp5,na.rm=TRUE)
[1] 471.72419 89.00038 86.29992 83.75739 79.79061 78.86182 80.03121
[8] 87.51468 NA 89.43641
> rowMin(tmp5,na.rm=TRUE)
[1] 58.93096 54.81571 54.22210 55.49732 54.50357 60.91257 60.24762 54.00260
[9] NA 54.47079
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 109.56400 67.29533 72.93619 66.45960 67.54234 72.47739 71.98954
[8] 69.21396 69.66941 NaN 69.02331 68.71429 71.48126 72.17552
[15] 70.43856 70.83315 69.54689 68.66796 67.30028 68.12329
> colSums(tmp5,na.rm=TRUE)
[1] 986.0760 605.6580 656.4257 598.1364 607.8810 652.2965 647.9058 622.9256
[9] 627.0247 0.0000 621.2098 618.4286 643.3313 649.5797 633.9470 637.4983
[17] 625.9220 618.0116 605.7025 613.1096
> colVars(tmp5,na.rm=TRUE)
[1] 18519.12197 81.68293 96.65678 43.08882 14.37848 55.05913
[7] 40.03382 53.80130 94.96648 NA 23.80150 51.49841
[13] 117.78803 119.40608 132.92882 56.74354 96.33446 86.41681
[19] 26.37950 44.28344
> colSd(tmp5,na.rm=TRUE)
[1] 136.084981 9.037861 9.831418 6.564207 3.791897 7.420184
[7] 6.327229 7.334937 9.745075 NA 4.878679 7.176239
[13] 10.853020 10.927309 11.529476 7.532831 9.815012 9.296064
[19] 5.136097 6.654581
> colMax(tmp5,na.rm=TRUE)
[1] 471.72419 80.50514 89.00038 76.65587 74.11611 78.75202 82.03797
[8] 82.46943 90.78667 -Inf 77.61391 78.86182 86.09045 88.75335
[15] 89.43641 82.29246 84.92583 86.29992 77.28007 77.16901
> colMin(tmp5,na.rm=TRUE)
[1] 54.81571 54.22210 54.00260 54.47079 60.95158 55.49732 62.12255 61.93115
[9] 60.91257 Inf 63.58858 55.85156 55.24374 56.11626 57.64568 59.32525
[17] 54.50357 56.34820 60.17268 57.25494
>
>
>
>
> 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] 174.0327 220.3462 371.3754 173.7669 143.2838 362.1467 242.1788 140.2536
[9] 175.6078 265.3893
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 174.0327 220.3462 371.3754 173.7669 143.2838 362.1467 242.1788 140.2536
[9] 175.6078 265.3893
>
>
>
> 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] 5.684342e-14 -2.842171e-14 2.842171e-14 0.000000e+00 2.842171e-14
[6] 5.684342e-14 5.684342e-14 -2.842171e-13 -5.684342e-14 0.000000e+00
[11] 5.684342e-14 2.842171e-14 -2.842171e-13 0.000000e+00 5.684342e-14
[16] 8.526513e-14 1.136868e-13 -2.842171e-14 -2.557954e-13 -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 9
9 7
6 13
5 3
3 9
10 1
2 8
7 3
10 16
7 9
10 14
9 15
6 3
1 18
1 1
7 14
5 14
6 9
6 14
4 16
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] 2.880643
> Min(tmp)
[1] -2.523519
> mean(tmp)
[1] -0.06514593
> Sum(tmp)
[1] -6.514593
> Var(tmp)
[1] 1.270041
>
> rowMeans(tmp)
[1] -0.06514593
> rowSums(tmp)
[1] -6.514593
> rowVars(tmp)
[1] 1.270041
> rowSd(tmp)
[1] 1.126961
> rowMax(tmp)
[1] 2.880643
> rowMin(tmp)
[1] -2.523519
>
> colMeans(tmp)
[1] -0.16988630 -2.41339441 -0.37808838 -0.69103144 -0.66550308 0.54157393
[7] 1.83806066 -0.76739783 0.70326992 0.98310396 -0.14255119 0.91352546
[13] 0.52398701 -0.51117841 -2.49381315 0.25209782 0.07793456 1.10131715
[19] -0.12912212 0.10425371 -0.75707209 -0.46030928 -1.47824416 0.36085092
[25] -2.02824768 -1.64795428 -0.33183910 1.89443215 0.46637774 -0.49844420
[31] -0.64160373 0.25515214 1.10744112 -0.02805720 0.82961077 -1.92953488
[37] -0.56807789 0.29765206 -0.47966093 -0.52229731 -0.25185029 1.64688453
[43] -0.88882367 0.13646230 -1.07141946 0.13894158 -0.34200889 0.77765493
[49] -1.20204368 0.69778682 1.20878205 -0.48935603 -0.79620692 -0.08507150
[55] 0.52350186 0.31498361 -0.29393884 -1.67420798 1.95466627 0.04043920
[61] 2.82168799 1.99811812 -0.20708427 -1.94222010 -2.52351881 -2.01586368
[67] -0.94011374 0.07205329 -1.76511070 -0.17655553 0.76722642 -1.18444448
[73] -0.50141331 0.37750892 1.33689657 -1.76592367 0.25898456 2.88064271
[79] -1.08144477 -0.33600389 -0.07168579 -0.47499825 -1.14133350 -2.12890006
[85] 1.42271299 -0.98800048 0.88680819 0.63621626 0.10626125 -0.38961686
[91] 0.21448866 0.12663303 0.94437030 1.69321875 -0.18314761 0.92219358
[97] 0.31150666 0.06879395 0.63489125 1.95906477
> colSums(tmp)
[1] -0.16988630 -2.41339441 -0.37808838 -0.69103144 -0.66550308 0.54157393
[7] 1.83806066 -0.76739783 0.70326992 0.98310396 -0.14255119 0.91352546
[13] 0.52398701 -0.51117841 -2.49381315 0.25209782 0.07793456 1.10131715
[19] -0.12912212 0.10425371 -0.75707209 -0.46030928 -1.47824416 0.36085092
[25] -2.02824768 -1.64795428 -0.33183910 1.89443215 0.46637774 -0.49844420
[31] -0.64160373 0.25515214 1.10744112 -0.02805720 0.82961077 -1.92953488
[37] -0.56807789 0.29765206 -0.47966093 -0.52229731 -0.25185029 1.64688453
[43] -0.88882367 0.13646230 -1.07141946 0.13894158 -0.34200889 0.77765493
[49] -1.20204368 0.69778682 1.20878205 -0.48935603 -0.79620692 -0.08507150
[55] 0.52350186 0.31498361 -0.29393884 -1.67420798 1.95466627 0.04043920
[61] 2.82168799 1.99811812 -0.20708427 -1.94222010 -2.52351881 -2.01586368
[67] -0.94011374 0.07205329 -1.76511070 -0.17655553 0.76722642 -1.18444448
[73] -0.50141331 0.37750892 1.33689657 -1.76592367 0.25898456 2.88064271
[79] -1.08144477 -0.33600389 -0.07168579 -0.47499825 -1.14133350 -2.12890006
[85] 1.42271299 -0.98800048 0.88680819 0.63621626 0.10626125 -0.38961686
[91] 0.21448866 0.12663303 0.94437030 1.69321875 -0.18314761 0.92219358
[97] 0.31150666 0.06879395 0.63489125 1.95906477
> 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] -0.16988630 -2.41339441 -0.37808838 -0.69103144 -0.66550308 0.54157393
[7] 1.83806066 -0.76739783 0.70326992 0.98310396 -0.14255119 0.91352546
[13] 0.52398701 -0.51117841 -2.49381315 0.25209782 0.07793456 1.10131715
[19] -0.12912212 0.10425371 -0.75707209 -0.46030928 -1.47824416 0.36085092
[25] -2.02824768 -1.64795428 -0.33183910 1.89443215 0.46637774 -0.49844420
[31] -0.64160373 0.25515214 1.10744112 -0.02805720 0.82961077 -1.92953488
[37] -0.56807789 0.29765206 -0.47966093 -0.52229731 -0.25185029 1.64688453
[43] -0.88882367 0.13646230 -1.07141946 0.13894158 -0.34200889 0.77765493
[49] -1.20204368 0.69778682 1.20878205 -0.48935603 -0.79620692 -0.08507150
[55] 0.52350186 0.31498361 -0.29393884 -1.67420798 1.95466627 0.04043920
[61] 2.82168799 1.99811812 -0.20708427 -1.94222010 -2.52351881 -2.01586368
[67] -0.94011374 0.07205329 -1.76511070 -0.17655553 0.76722642 -1.18444448
[73] -0.50141331 0.37750892 1.33689657 -1.76592367 0.25898456 2.88064271
[79] -1.08144477 -0.33600389 -0.07168579 -0.47499825 -1.14133350 -2.12890006
[85] 1.42271299 -0.98800048 0.88680819 0.63621626 0.10626125 -0.38961686
[91] 0.21448866 0.12663303 0.94437030 1.69321875 -0.18314761 0.92219358
[97] 0.31150666 0.06879395 0.63489125 1.95906477
> colMin(tmp)
[1] -0.16988630 -2.41339441 -0.37808838 -0.69103144 -0.66550308 0.54157393
[7] 1.83806066 -0.76739783 0.70326992 0.98310396 -0.14255119 0.91352546
[13] 0.52398701 -0.51117841 -2.49381315 0.25209782 0.07793456 1.10131715
[19] -0.12912212 0.10425371 -0.75707209 -0.46030928 -1.47824416 0.36085092
[25] -2.02824768 -1.64795428 -0.33183910 1.89443215 0.46637774 -0.49844420
[31] -0.64160373 0.25515214 1.10744112 -0.02805720 0.82961077 -1.92953488
[37] -0.56807789 0.29765206 -0.47966093 -0.52229731 -0.25185029 1.64688453
[43] -0.88882367 0.13646230 -1.07141946 0.13894158 -0.34200889 0.77765493
[49] -1.20204368 0.69778682 1.20878205 -0.48935603 -0.79620692 -0.08507150
[55] 0.52350186 0.31498361 -0.29393884 -1.67420798 1.95466627 0.04043920
[61] 2.82168799 1.99811812 -0.20708427 -1.94222010 -2.52351881 -2.01586368
[67] -0.94011374 0.07205329 -1.76511070 -0.17655553 0.76722642 -1.18444448
[73] -0.50141331 0.37750892 1.33689657 -1.76592367 0.25898456 2.88064271
[79] -1.08144477 -0.33600389 -0.07168579 -0.47499825 -1.14133350 -2.12890006
[85] 1.42271299 -0.98800048 0.88680819 0.63621626 0.10626125 -0.38961686
[91] 0.21448866 0.12663303 0.94437030 1.69321875 -0.18314761 0.92219358
[97] 0.31150666 0.06879395 0.63489125 1.95906477
> colMedians(tmp)
[1] -0.16988630 -2.41339441 -0.37808838 -0.69103144 -0.66550308 0.54157393
[7] 1.83806066 -0.76739783 0.70326992 0.98310396 -0.14255119 0.91352546
[13] 0.52398701 -0.51117841 -2.49381315 0.25209782 0.07793456 1.10131715
[19] -0.12912212 0.10425371 -0.75707209 -0.46030928 -1.47824416 0.36085092
[25] -2.02824768 -1.64795428 -0.33183910 1.89443215 0.46637774 -0.49844420
[31] -0.64160373 0.25515214 1.10744112 -0.02805720 0.82961077 -1.92953488
[37] -0.56807789 0.29765206 -0.47966093 -0.52229731 -0.25185029 1.64688453
[43] -0.88882367 0.13646230 -1.07141946 0.13894158 -0.34200889 0.77765493
[49] -1.20204368 0.69778682 1.20878205 -0.48935603 -0.79620692 -0.08507150
[55] 0.52350186 0.31498361 -0.29393884 -1.67420798 1.95466627 0.04043920
[61] 2.82168799 1.99811812 -0.20708427 -1.94222010 -2.52351881 -2.01586368
[67] -0.94011374 0.07205329 -1.76511070 -0.17655553 0.76722642 -1.18444448
[73] -0.50141331 0.37750892 1.33689657 -1.76592367 0.25898456 2.88064271
[79] -1.08144477 -0.33600389 -0.07168579 -0.47499825 -1.14133350 -2.12890006
[85] 1.42271299 -0.98800048 0.88680819 0.63621626 0.10626125 -0.38961686
[91] 0.21448866 0.12663303 0.94437030 1.69321875 -0.18314761 0.92219358
[97] 0.31150666 0.06879395 0.63489125 1.95906477
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.1698863 -2.413394 -0.3780884 -0.6910314 -0.6655031 0.5415739 1.838061
[2,] -0.1698863 -2.413394 -0.3780884 -0.6910314 -0.6655031 0.5415739 1.838061
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.7673978 0.7032699 0.983104 -0.1425512 0.9135255 0.523987 -0.5111784
[2,] -0.7673978 0.7032699 0.983104 -0.1425512 0.9135255 0.523987 -0.5111784
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -2.493813 0.2520978 0.07793456 1.101317 -0.1291221 0.1042537 -0.7570721
[2,] -2.493813 0.2520978 0.07793456 1.101317 -0.1291221 0.1042537 -0.7570721
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.4603093 -1.478244 0.3608509 -2.028248 -1.647954 -0.3318391 1.894432
[2,] -0.4603093 -1.478244 0.3608509 -2.028248 -1.647954 -0.3318391 1.894432
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.4663777 -0.4984442 -0.6416037 0.2551521 1.107441 -0.0280572 0.8296108
[2,] 0.4663777 -0.4984442 -0.6416037 0.2551521 1.107441 -0.0280572 0.8296108
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.929535 -0.5680779 0.2976521 -0.4796609 -0.5222973 -0.2518503 1.646885
[2,] -1.929535 -0.5680779 0.2976521 -0.4796609 -0.5222973 -0.2518503 1.646885
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.8888237 0.1364623 -1.071419 0.1389416 -0.3420089 0.7776549 -1.202044
[2,] -0.8888237 0.1364623 -1.071419 0.1389416 -0.3420089 0.7776549 -1.202044
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.6977868 1.208782 -0.489356 -0.7962069 -0.0850715 0.5235019 0.3149836
[2,] 0.6977868 1.208782 -0.489356 -0.7962069 -0.0850715 0.5235019 0.3149836
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.2939388 -1.674208 1.954666 0.0404392 2.821688 1.998118 -0.2070843
[2,] -0.2939388 -1.674208 1.954666 0.0404392 2.821688 1.998118 -0.2070843
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.94222 -2.523519 -2.015864 -0.9401137 0.07205329 -1.765111 -0.1765555
[2,] -1.94222 -2.523519 -2.015864 -0.9401137 0.07205329 -1.765111 -0.1765555
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.7672264 -1.184444 -0.5014133 0.3775089 1.336897 -1.765924 0.2589846
[2,] 0.7672264 -1.184444 -0.5014133 0.3775089 1.336897 -1.765924 0.2589846
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 2.880643 -1.081445 -0.3360039 -0.07168579 -0.4749983 -1.141333 -2.1289
[2,] 2.880643 -1.081445 -0.3360039 -0.07168579 -0.4749983 -1.141333 -2.1289
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 1.422713 -0.9880005 0.8868082 0.6362163 0.1062612 -0.3896169 0.2144887
[2,] 1.422713 -0.9880005 0.8868082 0.6362163 0.1062612 -0.3896169 0.2144887
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.126633 0.9443703 1.693219 -0.1831476 0.9221936 0.3115067 0.06879395
[2,] 0.126633 0.9443703 1.693219 -0.1831476 0.9221936 0.3115067 0.06879395
[,99] [,100]
[1,] 0.6348913 1.959065
[2,] 0.6348913 1.959065
>
>
> Max(tmp2)
[1] 2.909925
> Min(tmp2)
[1] -2.270974
> mean(tmp2)
[1] -0.05571543
> Sum(tmp2)
[1] -5.571543
> Var(tmp2)
[1] 1.331673
>
> rowMeans(tmp2)
[1] -1.708804580 0.397379207 -0.568998357 -0.555757683 0.025378660
[6] 0.048127890 -0.566272555 2.069278091 -1.000789423 2.264040595
[11] 1.030306246 -0.536511255 -0.735112440 -1.529319046 1.227577574
[16] 0.201675343 -1.192248872 -1.493927280 -0.366517792 0.214539933
[21] -0.436203641 -1.499173542 -0.330468431 -0.821892405 -0.025980882
[26] -1.657994661 -0.989584341 -0.082196840 1.030423783 1.379544258
[31] 0.416025761 -0.463713548 -0.739952019 0.275329836 1.757781995
[36] 0.324603678 -1.159266974 0.006493295 0.134783160 0.096130551
[41] 1.980309540 0.707102001 1.015018774 -0.021810691 -0.432959182
[46] 0.557847015 -0.916651469 -1.004513747 -0.708527270 -0.820206139
[51] 0.463004750 -0.964629056 1.226999586 -0.125175617 1.168603734
[56] -1.269206429 -1.409844831 2.586476750 -2.270973637 0.318458963
[61] -0.415693961 1.079855284 0.137106730 -0.764029082 0.003062784
[66] -0.337723545 2.370537039 1.254879264 -1.725087440 -0.504513679
[71] 1.168019212 -1.087554694 -1.069871878 -0.601579156 1.736435570
[76] -0.513300313 1.355936818 2.010074942 0.494034078 -0.262437086
[81] -1.870187776 -1.362658601 -0.462857863 0.379373112 -2.069380229
[86] 1.419418832 0.337102687 -0.899652425 -1.856193740 -0.275820259
[91] 1.148168398 0.283015473 -0.709933372 2.381375233 0.276822665
[96] -0.976188847 -1.708811484 -1.255980997 -0.105286042 2.909925184
> rowSums(tmp2)
[1] -1.708804580 0.397379207 -0.568998357 -0.555757683 0.025378660
[6] 0.048127890 -0.566272555 2.069278091 -1.000789423 2.264040595
[11] 1.030306246 -0.536511255 -0.735112440 -1.529319046 1.227577574
[16] 0.201675343 -1.192248872 -1.493927280 -0.366517792 0.214539933
[21] -0.436203641 -1.499173542 -0.330468431 -0.821892405 -0.025980882
[26] -1.657994661 -0.989584341 -0.082196840 1.030423783 1.379544258
[31] 0.416025761 -0.463713548 -0.739952019 0.275329836 1.757781995
[36] 0.324603678 -1.159266974 0.006493295 0.134783160 0.096130551
[41] 1.980309540 0.707102001 1.015018774 -0.021810691 -0.432959182
[46] 0.557847015 -0.916651469 -1.004513747 -0.708527270 -0.820206139
[51] 0.463004750 -0.964629056 1.226999586 -0.125175617 1.168603734
[56] -1.269206429 -1.409844831 2.586476750 -2.270973637 0.318458963
[61] -0.415693961 1.079855284 0.137106730 -0.764029082 0.003062784
[66] -0.337723545 2.370537039 1.254879264 -1.725087440 -0.504513679
[71] 1.168019212 -1.087554694 -1.069871878 -0.601579156 1.736435570
[76] -0.513300313 1.355936818 2.010074942 0.494034078 -0.262437086
[81] -1.870187776 -1.362658601 -0.462857863 0.379373112 -2.069380229
[86] 1.419418832 0.337102687 -0.899652425 -1.856193740 -0.275820259
[91] 1.148168398 0.283015473 -0.709933372 2.381375233 0.276822665
[96] -0.976188847 -1.708811484 -1.255980997 -0.105286042 2.909925184
> 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] -1.708804580 0.397379207 -0.568998357 -0.555757683 0.025378660
[6] 0.048127890 -0.566272555 2.069278091 -1.000789423 2.264040595
[11] 1.030306246 -0.536511255 -0.735112440 -1.529319046 1.227577574
[16] 0.201675343 -1.192248872 -1.493927280 -0.366517792 0.214539933
[21] -0.436203641 -1.499173542 -0.330468431 -0.821892405 -0.025980882
[26] -1.657994661 -0.989584341 -0.082196840 1.030423783 1.379544258
[31] 0.416025761 -0.463713548 -0.739952019 0.275329836 1.757781995
[36] 0.324603678 -1.159266974 0.006493295 0.134783160 0.096130551
[41] 1.980309540 0.707102001 1.015018774 -0.021810691 -0.432959182
[46] 0.557847015 -0.916651469 -1.004513747 -0.708527270 -0.820206139
[51] 0.463004750 -0.964629056 1.226999586 -0.125175617 1.168603734
[56] -1.269206429 -1.409844831 2.586476750 -2.270973637 0.318458963
[61] -0.415693961 1.079855284 0.137106730 -0.764029082 0.003062784
[66] -0.337723545 2.370537039 1.254879264 -1.725087440 -0.504513679
[71] 1.168019212 -1.087554694 -1.069871878 -0.601579156 1.736435570
[76] -0.513300313 1.355936818 2.010074942 0.494034078 -0.262437086
[81] -1.870187776 -1.362658601 -0.462857863 0.379373112 -2.069380229
[86] 1.419418832 0.337102687 -0.899652425 -1.856193740 -0.275820259
[91] 1.148168398 0.283015473 -0.709933372 2.381375233 0.276822665
[96] -0.976188847 -1.708811484 -1.255980997 -0.105286042 2.909925184
> rowMin(tmp2)
[1] -1.708804580 0.397379207 -0.568998357 -0.555757683 0.025378660
[6] 0.048127890 -0.566272555 2.069278091 -1.000789423 2.264040595
[11] 1.030306246 -0.536511255 -0.735112440 -1.529319046 1.227577574
[16] 0.201675343 -1.192248872 -1.493927280 -0.366517792 0.214539933
[21] -0.436203641 -1.499173542 -0.330468431 -0.821892405 -0.025980882
[26] -1.657994661 -0.989584341 -0.082196840 1.030423783 1.379544258
[31] 0.416025761 -0.463713548 -0.739952019 0.275329836 1.757781995
[36] 0.324603678 -1.159266974 0.006493295 0.134783160 0.096130551
[41] 1.980309540 0.707102001 1.015018774 -0.021810691 -0.432959182
[46] 0.557847015 -0.916651469 -1.004513747 -0.708527270 -0.820206139
[51] 0.463004750 -0.964629056 1.226999586 -0.125175617 1.168603734
[56] -1.269206429 -1.409844831 2.586476750 -2.270973637 0.318458963
[61] -0.415693961 1.079855284 0.137106730 -0.764029082 0.003062784
[66] -0.337723545 2.370537039 1.254879264 -1.725087440 -0.504513679
[71] 1.168019212 -1.087554694 -1.069871878 -0.601579156 1.736435570
[76] -0.513300313 1.355936818 2.010074942 0.494034078 -0.262437086
[81] -1.870187776 -1.362658601 -0.462857863 0.379373112 -2.069380229
[86] 1.419418832 0.337102687 -0.899652425 -1.856193740 -0.275820259
[91] 1.148168398 0.283015473 -0.709933372 2.381375233 0.276822665
[96] -0.976188847 -1.708811484 -1.255980997 -0.105286042 2.909925184
>
> colMeans(tmp2)
[1] -0.05571543
> colSums(tmp2)
[1] -5.571543
> colVars(tmp2)
[1] 1.331673
> colSd(tmp2)
[1] 1.153981
> colMax(tmp2)
[1] 2.909925
> colMin(tmp2)
[1] -2.270974
> colMedians(tmp2)
[1] -0.1938064
> colRanges(tmp2)
[,1]
[1,] -2.270974
[2,] 2.909925
>
> 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] 1.7570914 -4.5145189 -1.0462635 -2.0209510 2.0144098 2.4009296
[7] 1.4575884 5.5131028 -0.3560883 -0.5498948
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8414107
[2,] -0.3547066
[3,] -0.2223984
[4,] 0.7016391
[5,] 2.0203478
>
> rowApply(tmp,sum)
[1] 8.4497817 -2.2414597 0.8429532 1.6706689 1.4582541 -0.9713410
[7] -1.3667075 0.4798115 -5.0655360 1.3989802
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 2 9 4 4 9 3 9 5 4 7
[2,] 3 3 6 3 5 4 10 1 5 2
[3,] 5 1 1 9 4 5 5 9 6 6
[4,] 7 4 2 1 3 1 6 7 9 8
[5,] 6 7 9 8 2 2 3 2 10 9
[6,] 10 2 5 10 10 10 4 6 2 1
[7,] 8 6 3 7 8 7 1 3 3 10
[8,] 9 10 8 2 7 9 7 10 1 5
[9,] 1 8 7 6 6 6 2 8 8 3
[10,] 4 5 10 5 1 8 8 4 7 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.05978440 0.45645076 3.70885734 0.52988215 0.75291587 2.74766144
[7] 0.47493262 0.08218977 -1.24969458 -2.74176113 -0.10915419 -0.09467964
[13] -2.19176573 -0.67374401 3.67957769 0.07761050 -2.60055383 4.53035851
[19] 2.00439152 -3.26292174
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.1955221
[2,] -0.1259398
[3,] 0.5387216
[4,] 0.8801218
[5,] 0.9624029
>
> rowApply(tmp,sum)
[1] 8.890104 4.577003 -0.909725 -1.927029 -2.450015
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 16 12 11 16 12
[2,] 18 8 19 1 6
[3,] 3 6 20 5 20
[4,] 2 18 17 4 14
[5,] 20 7 8 11 13
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.8801218 1.55675243 -0.34688802 -0.4966197 1.74996962 0.4121978
[2,] 0.5387216 0.06171625 -0.08196264 1.2757038 -0.04816822 0.8726623
[3,] -0.1259398 1.56099030 1.96232221 0.6980808 -0.49790621 -0.2030520
[4,] 0.9624029 -1.77709114 -0.75363016 -1.0288084 -0.25884745 1.3207679
[5,] -0.1955221 -0.94591708 2.92901594 0.0815257 -0.19213187 0.3450854
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.05782811 0.8646060 0.29580100 -0.007287439 -0.17074545 -0.2323463
[2,] 0.71667782 -0.4718802 -0.08347926 0.625505424 1.47843668 -1.6581186
[3,] -0.10887055 0.3714180 -1.01210344 -1.227400841 -1.08453018 1.2462263
[4,] 1.07034348 0.1434483 -0.01701246 -0.694575851 -0.01269633 -1.0334012
[5,] -1.26104624 -0.8254024 -0.43290041 -1.438002425 -0.31961891 1.5829601
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.2999639 0.009950275 0.7749342 0.6798604 1.7475862 0.08451988
[2,] -1.8794248 0.089091017 0.5259732 0.1558974 -1.7089117 1.26463546
[3,] -0.2088778 0.440781818 0.4459180 -0.6892292 -1.4700773 0.19921772
[4,] -0.4131447 -0.669818814 0.7934946 1.8892349 -0.4281232 1.18525028
[5,] -0.9902824 -0.543748310 1.1392578 -1.9581531 -0.7410279 1.79673517
[,19] [,20]
[1,] 0.6403296 -0.9104307
[2,] 2.1706105 0.7333166
[3,] -0.5429956 -0.6636973
[4,] -1.6720544 -0.5327668
[5,] 1.4085015 -1.8893436
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-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-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-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-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -1.218818 -0.2861393 -0.3272472 0.05937129 0.6882563 0.2798448 0.6788428
col8 col9 col10 col11 col12 col13 col14
row1 0.07010266 0.04581946 1.068981 -0.08266893 -0.1363366 -0.950946 1.193148
col15 col16 col17 col18 col19 col20
row1 1.431088 0.9399981 0.3708173 1.290708 -0.2572479 0.7791764
> tmp[,"col10"]
col10
row1 1.0689808
row2 0.5318771
row3 -0.9892383
row4 -1.3909460
row5 -0.2230784
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -1.2188182 -0.2861393 -0.3272472 0.05937129 0.6882563 0.2798448
row5 0.8769224 -0.2288733 -0.5721597 0.61140508 -0.3672539 1.6444867
col7 col8 col9 col10 col11 col12
row1 0.6788428 0.07010266 0.04581946 1.0689808 -0.08266893 -0.1363366
row5 -2.3485344 0.46991047 -0.85132886 -0.2230784 1.04030060 -1.6805621
col13 col14 col15 col16 col17 col18 col19
row1 -0.950946 1.1931481 1.4310876 0.9399981 0.3708173 1.2907083 -0.2572479
row5 -1.235085 -0.5973942 0.5930711 -1.1533127 1.0932180 0.0618595 0.1920286
col20
row1 0.7791764
row5 -0.2690878
> tmp[,c("col6","col20")]
col6 col20
row1 0.2798448 0.7791764
row2 -2.5271946 -0.2526699
row3 1.8220441 -0.2776288
row4 0.9686356 -0.6712596
row5 1.6444867 -0.2690878
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.2798448 0.7791764
row5 1.6444867 -0.2690878
>
>
>
>
> 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 50.32671 51.15401 50.48969 50.73536 47.00827 106.0998 51.38286 50.07075
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.53806 49.87034 49.35523 50.85071 51.67107 50.0753 49.53175 50.88287
col17 col18 col19 col20
row1 51.40434 48.82125 48.98977 103.1225
> tmp[,"col10"]
col10
row1 49.87034
row2 31.29195
row3 28.73639
row4 28.38117
row5 51.27613
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.32671 51.15401 50.48969 50.73536 47.00827 106.0998 51.38286 50.07075
row5 49.30552 48.14530 51.10435 50.51696 47.74899 104.4251 49.75285 50.04039
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.53806 49.87034 49.35523 50.85071 51.67107 50.07530 49.53175 50.88287
row5 49.76152 51.27613 49.62924 49.05798 49.56681 48.45991 50.48344 49.62985
col17 col18 col19 col20
row1 51.40434 48.82125 48.98977 103.1225
row5 50.31752 50.85164 50.40443 105.8247
> tmp[,c("col6","col20")]
col6 col20
row1 106.09979 103.12247
row2 75.34995 75.38633
row3 74.58702 78.04992
row4 73.71291 76.36834
row5 104.42509 105.82472
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.0998 103.1225
row5 104.4251 105.8247
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.0998 103.1225
row5 104.4251 105.8247
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.07123777
[2,] 0.35644658
[3,] -0.89405818
[4,] -0.01260141
[5,] -0.20208623
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.7006796 -0.1308120
[2,] 1.7098866 -0.3425989
[3,] -0.3632755 0.1122498
[4,] -0.4261151 0.2214441
[5,] 1.2716417 2.5563799
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.2983116 1.5185112
[2,] -0.3018682 0.2922711
[3,] 0.6781263 -0.8147322
[4,] -0.4375996 0.7030780
[5,] 0.1420518 -0.2159104
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.2983116
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.2983116
[2,] -0.3018682
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 0.4360686 0.5626101 0.9273549 1.3083416 -1.4813910 -0.9967692 0.5313904
row1 -1.1993756 1.1619793 -0.5632926 0.3926133 0.1243122 0.3136326 -0.1901175
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.7361673 -0.2771419 0.2973041 -1.696038 -0.2359406 0.9181132
row1 -0.4851599 -0.7170025 -0.9236054 -1.384242 0.2753315 1.4445204
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.84591095 1.37722635 -0.3757647 -0.1540679 -0.3503438 -0.2281266
row1 0.04813367 -0.02475185 -0.5585503 1.1426110 -1.0163914 0.4190854
[,20]
row3 -2.2528375
row1 -0.4984021
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
row2 1.662795 1.495066 0.2820967 1.245959 -0.876503 -1.691408 0.30119 1.49053
[,9] [,10]
row2 0.7212521 -0.9228534
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.1802822 1.075957 0.3581582 -1.814456 -1.959139 -1.144981 1.97332
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.5891686 -0.977593 0.6835544 -0.7580822 0.5948913 0.05672898 -1.129393
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.4059079 1.942285 1.305311 -0.4374693 -0.01429701 -0.0664136
>
>
> 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: 0x6065a8362980>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM27132d5c7ea94d"
[2] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM27132d14ce7329"
[3] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM27132d2974d673"
[4] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM27132d54563029"
[5] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM27132d21b27fcc"
[6] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM27132d304217e1"
[7] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM27132d1809db71"
[8] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM27132d38ef8a7c"
[9] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM27132d28cf97b8"
[10] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM27132d15ffbcff"
[11] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM27132dd64a5f5"
[12] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM27132d6d36d2ad"
[13] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM27132d53b3876a"
[14] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM27132d72c3934b"
[15] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM27132d11130a97"
>
>
> ### 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: 0x6065a7e1df60>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6065a7e1df60>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6065a7e1df60>
> rowMedians(tmp)
[1] 0.126371328 -0.782135553 -0.411653985 -0.007243598 0.021588501
[6] 0.727933252 -0.469745773 -0.537301164 0.055536086 -0.268436829
[11] 0.448838246 0.153611852 0.001874778 -0.110956426 0.032379866
[16] 0.144829782 0.125566482 -0.431423622 0.067576355 0.282924578
[21] -0.435149687 -0.230662516 -0.547225465 -0.738418356 0.052514072
[26] 0.719584203 -0.073717074 -0.020578130 0.333475027 -0.439799380
[31] -0.705318881 -0.129721829 -0.681431421 0.064882050 -0.337684464
[36] 0.125747805 -0.335387123 0.299796272 -0.418851255 -0.092777054
[41] 0.108608773 0.245954035 0.334433857 0.543229670 0.228857035
[46] 0.283013138 -0.229333509 0.126315771 0.154473379 0.346474757
[51] -0.064341992 0.431817597 -0.068426484 -0.312297449 0.365958137
[56] -0.078786102 0.049468980 0.058192793 -0.049916177 -0.110724515
[61] -0.136786514 0.177959639 0.259128133 -0.242782344 0.106564043
[66] -0.475533884 -0.321160138 0.454284294 0.398429375 -0.025651666
[71] 0.484737372 -0.219388546 -0.136398637 -0.176183277 0.203700746
[76] 0.611944909 0.399501207 1.010824238 -0.319786674 0.043452248
[81] 0.211041263 -0.056953976 0.324024114 0.111140446 0.085903012
[86] -0.187740599 0.186223518 0.098565292 0.630872171 -0.254290294
[91] 0.104629571 -0.067922332 -0.302998192 -0.197228868 -0.274996761
[96] -0.179945669 0.127875048 0.425894042 -0.110199060 -0.608223752
[101] -0.058502581 -0.649375185 -0.281903341 0.392098948 0.043967573
[106] -0.069824389 0.095150058 0.570742879 -0.094483547 -0.502049483
[111] -0.133401760 -0.046341623 -0.034778461 -0.023519476 -0.172763490
[116] -0.083288058 0.228419740 -0.326240532 -0.561643144 0.238419569
[121] 0.669974429 0.301662216 -0.451321931 0.083510366 -0.350086489
[126] -0.049652331 0.146282201 -0.040334031 0.045943172 0.028915224
[131] -0.163786409 -0.514588884 -0.229990171 -0.476148693 -0.198146006
[136] -0.070626996 0.024875279 0.140107576 -0.115913167 -0.211297009
[141] -0.296079064 0.269549390 -0.343519830 -0.035566384 0.123830366
[146] -0.163567079 0.141621077 -0.425353088 -0.328937653 0.851382715
[151] 0.295332873 -0.489517926 0.682676631 -0.084666821 -0.356326058
[156] 0.015747417 0.148566655 -0.087465837 -0.419291433 -0.222201541
[161] 0.189971756 0.451666588 0.341794824 0.065641980 -0.021423402
[166] -0.452296809 -0.121617811 -0.887802038 -0.351830363 0.068177310
[171] -0.249795174 0.473235998 0.056398704 -0.135218971 0.059019158
[176] 0.117699901 0.302987369 -0.583022025 -0.004566939 0.247196953
[181] -0.522705688 -0.440106785 0.334432241 -0.424429528 0.476875168
[186] 0.608884719 0.057800913 -0.022943344 -0.332918345 0.211316150
[191] -0.248728633 -0.299687102 -0.075695084 0.427135093 -0.499496336
[196] 0.457258565 -0.097327899 -0.038259632 -0.038375046 0.306588536
[201] 0.502328368 -0.805924957 0.151130480 -0.307874176 -0.219260267
[206] 0.179697529 -0.211130535 -0.280354498 0.087904681 -0.078906332
[211] 0.009118340 0.256194928 -0.200046180 0.138240412 0.282669164
[216] 0.005610789 -0.425638123 -0.560123235 -0.702106897 -0.061224009
[221] 0.038005217 0.128119468 -0.480936344 -0.105298439 0.020505595
[226] -0.211647897 0.183476343 0.103811794 0.497474837 -0.247661346
>
> proc.time()
user system elapsed
1.277 1.527 2.794
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.1 (2025-06-13) -- "Great Square Root"
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: 0x55b5669d4ad0>
> .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: 0x55b5669d4ad0>
> .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: 0x55b5669d4ad0>
> .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: 0x55b5669d4ad0>
> 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: 0x55b5669c6a30>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55b5669c6a30>
> .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: 0x55b5669c6a30>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55b5669c6a30>
> .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: 0x55b5669c6a30>
> 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: 0x55b565792870>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55b565792870>
> .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: 0x55b565792870>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x55b565792870>
> .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: 0x55b565792870>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x55b565792870>
> .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: 0x55b565792870>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x55b565792870>
> .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: 0x55b565792870>
> 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: 0x55b565ba31a0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x55b565ba31a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55b565ba31a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55b565ba31a0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2715703cf075ef" "BufferedMatrixFile2715707b5862e0"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2715703cf075ef" "BufferedMatrixFile2715707b5862e0"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x55b567d4d870>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55b567d4d870>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x55b567d4d870>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x55b567d4d870>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x55b567d4d870>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x55b567d4d870>
> .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: 0x55b5661a1ca0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55b5661a1ca0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x55b5661a1ca0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x55b5661a1ca0>
> 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: 0x55b566954a20>
> .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: 0x55b566954a20>
> rm(P)
>
> proc.time()
user system elapsed
0.251 0.048 0.286
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.1 (2025-06-13) -- "Great Square Root"
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.
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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
0.246 0.045 0.280