Ben Bolstad
| Snapshot Date: 2025-06-18 13:25 -0400 (Wed, 18 Jun 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 0147962 |
| git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-06-19 12:05 -0400 (Thu, 19 Jun 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.2 LTS) | x86_64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4810 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.5.0 (2025-04-11 ucrt) -- "How About a Twenty-Six" | 4548 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | 4.5.0 Patched (2025-04-21 r88169) -- "How About a Twenty-Six" | 4528 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4493 |
| 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 250/2309 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.73.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.2 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.1 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. - See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host. |
| Package: BufferedMatrix |
| Version: 1.73.0 |
| Command: /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.73.0.tar.gz |
| StartedAt: 2025-06-17 05:28:18 -0000 (Tue, 17 Jun 2025) |
| EndedAt: 2025-06-17 05:28:49 -0000 (Tue, 17 Jun 2025) |
| EllapsedTime: 31.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.73.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.0 (2025-04-11)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.73.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/R/R-4.5.0/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.73.0’
** using staged installation
** libs
using C compiler: ‘aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0’
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c init_package.c -o init_package.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -shared -L/home/biocbuild/R/R-4.5.0/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/R/R-4.5.0/lib -lR
installing to /home/biocbuild/R/R-4.5.0/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.351 0.016 0.352
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 478398 25.6 1047041 56 639620 34.2
Vcells 885166 6.8 8388608 64 2080985 15.9
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Tue Jun 17 05:28:43 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 Jun 17 05:28:43 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: 0x1eb30ff0>
>
>
>
> 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 Jun 17 05:28:44 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 Jun 17 05:28:44 2025"
>
> ColMode(tmp2)
<pointer: 0x1eb30ff0>
>
>
>
> ### 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,] 101.0817693 -0.3505741 1.5118946 -0.07217438
[2,] -1.4632795 -0.7288913 -0.4320967 -0.26927264
[3,] 0.9307134 0.6405087 0.1824915 0.38013196
[4,] 0.5882668 -0.6912847 -0.1847821 0.06261797
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 101.0817693 0.3505741 1.5118946 0.07217438
[2,] 1.4632795 0.7288913 0.4320967 0.26927264
[3,] 0.9307134 0.6405087 0.1824915 0.38013196
[4,] 0.5882668 0.6912847 0.1847821 0.06261797
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0539430 0.5920930 1.2295912 0.2686529
[2,] 1.2096609 0.8537513 0.6573406 0.5189149
[3,] 0.9647349 0.8003179 0.4271903 0.6165484
[4,] 0.7669855 0.8314353 0.4298628 0.2502358
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 226.62120 31.27150 38.80781 27.75870
[2,] 38.55989 34.26640 32.00550 30.45842
[3,] 35.57806 33.64369 29.45439 31.54562
[4,] 33.25812 34.00564 29.48341 27.56498
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x1fd609a0>
> exp(tmp5)
<pointer: 0x1fd609a0>
> log(tmp5,2)
<pointer: 0x1fd609a0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.6823
> Min(tmp5)
[1] 54.74394
> mean(tmp5)
[1] 72.79181
> Sum(tmp5)
[1] 14558.36
> Var(tmp5)
[1] 860.8476
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.96162 73.90618 67.58551 70.29925 68.85467 70.69268 70.66180 70.52755
[9] 73.87812 70.55075
> rowSums(tmp5)
[1] 1819.232 1478.124 1351.710 1405.985 1377.093 1413.854 1413.236 1410.551
[9] 1477.562 1411.015
> rowVars(tmp5)
[1] 8113.45623 54.59101 33.10610 36.15511 75.18619 75.56915
[7] 59.66161 44.02730 52.42936 50.51067
> rowSd(tmp5)
[1] 90.074726 7.388573 5.753790 6.012912 8.670997 8.693052 7.724093
[8] 6.635307 7.240812 7.107086
> rowMax(tmp5)
[1] 471.68233 86.94600 80.64625 82.29084 85.30322 84.09270 83.74625
[8] 83.20565 86.64558 85.32239
> rowMin(tmp5)
[1] 57.77610 60.24011 56.52891 57.37289 56.75631 54.74394 59.92047 58.02017
[9] 60.67416 57.56247
>
> colMeans(tmp5)
[1] 111.98274 70.39325 69.92080 65.71072 68.00073 73.36475 76.34199
[8] 72.76600 69.64457 72.59101 69.88856 71.81750 73.68831 69.84726
[15] 67.46549 71.90721 72.48945 71.92806 67.99876 68.08909
> colSums(tmp5)
[1] 1119.8274 703.9325 699.2080 657.1072 680.0073 733.6475 763.4199
[8] 727.6600 696.4457 725.9101 698.8856 718.1750 736.8831 698.4726
[15] 674.6549 719.0721 724.8945 719.2806 679.9876 680.8909
> colVars(tmp5)
[1] 16025.27957 50.59875 62.22545 65.36243 44.44463 59.10896
[7] 36.90448 50.59676 49.58451 69.81346 95.50653 34.91846
[13] 64.82995 88.48926 47.62868 67.34499 90.03252 35.97218
[19] 32.53771 29.97341
> colSd(tmp5)
[1] 126.590993 7.113280 7.888311 8.084703 6.666680 7.688235
[7] 6.074906 7.113140 7.041627 8.355445 9.772744 5.909184
[13] 8.051705 9.406873 6.901354 8.206399 9.488547 5.997682
[19] 5.704184 5.474797
> colMax(tmp5)
[1] 471.68233 80.17632 80.77337 80.86196 78.09365 85.32239 83.20565
[8] 83.74625 84.00402 82.65151 86.64558 80.09872 84.09270 86.94600
[15] 80.79160 82.29084 85.58087 80.71185 75.90379 76.60799
> colMin(tmp5)
[1] 61.84943 56.75631 61.30546 57.02810 54.74394 65.03074 65.18350 60.44775
[9] 57.56247 58.57231 61.92594 62.96347 58.60089 58.08578 59.92047 56.52891
[17] 59.46539 63.22194 58.17543 58.02017
>
>
> ### 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] 90.96162 73.90618 67.58551 70.29925 68.85467 70.69268 NA 70.52755
[9] 73.87812 70.55075
> rowSums(tmp5)
[1] 1819.232 1478.124 1351.710 1405.985 1377.093 1413.854 NA 1410.551
[9] 1477.562 1411.015
> rowVars(tmp5)
[1] 8113.45623 54.59101 33.10610 36.15511 75.18619 75.56915
[7] 62.37062 44.02730 52.42936 50.51067
> rowSd(tmp5)
[1] 90.074726 7.388573 5.753790 6.012912 8.670997 8.693052 7.897507
[8] 6.635307 7.240812 7.107086
> rowMax(tmp5)
[1] 471.68233 86.94600 80.64625 82.29084 85.30322 84.09270 NA
[8] 83.20565 86.64558 85.32239
> rowMin(tmp5)
[1] 57.77610 60.24011 56.52891 57.37289 56.75631 54.74394 NA 58.02017
[9] 60.67416 57.56247
>
> colMeans(tmp5)
[1] 111.98274 70.39325 69.92080 65.71072 68.00073 73.36475 76.34199
[8] 72.76600 NA 72.59101 69.88856 71.81750 73.68831 69.84726
[15] 67.46549 71.90721 72.48945 71.92806 67.99876 68.08909
> colSums(tmp5)
[1] 1119.8274 703.9325 699.2080 657.1072 680.0073 733.6475 763.4199
[8] 727.6600 NA 725.9101 698.8856 718.1750 736.8831 698.4726
[15] 674.6549 719.0721 724.8945 719.2806 679.9876 680.8909
> colVars(tmp5)
[1] 16025.27957 50.59875 62.22545 65.36243 44.44463 59.10896
[7] 36.90448 50.59676 NA 69.81346 95.50653 34.91846
[13] 64.82995 88.48926 47.62868 67.34499 90.03252 35.97218
[19] 32.53771 29.97341
> colSd(tmp5)
[1] 126.590993 7.113280 7.888311 8.084703 6.666680 7.688235
[7] 6.074906 7.113140 NA 8.355445 9.772744 5.909184
[13] 8.051705 9.406873 6.901354 8.206399 9.488547 5.997682
[19] 5.704184 5.474797
> colMax(tmp5)
[1] 471.68233 80.17632 80.77337 80.86196 78.09365 85.32239 83.20565
[8] 83.74625 NA 82.65151 86.64558 80.09872 84.09270 86.94600
[15] 80.79160 82.29084 85.58087 80.71185 75.90379 76.60799
> colMin(tmp5)
[1] 61.84943 56.75631 61.30546 57.02810 54.74394 65.03074 65.18350 60.44775
[9] NA 58.57231 61.92594 62.96347 58.60089 58.08578 59.92047 56.52891
[17] 59.46539 63.22194 58.17543 58.02017
>
> Max(tmp5,na.rm=TRUE)
[1] 471.6823
> Min(tmp5,na.rm=TRUE)
[1] 54.74394
> mean(tmp5,na.rm=TRUE)
[1] 72.78635
> Sum(tmp5,na.rm=TRUE)
[1] 14484.48
> Var(tmp5,na.rm=TRUE)
[1] 865.1893
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.96162 73.90618 67.58551 70.29925 68.85467 70.69268 70.49244 70.52755
[9] 73.87812 70.55075
> rowSums(tmp5,na.rm=TRUE)
[1] 1819.232 1478.124 1351.710 1405.985 1377.093 1413.854 1339.356 1410.551
[9] 1477.562 1411.015
> rowVars(tmp5,na.rm=TRUE)
[1] 8113.45623 54.59101 33.10610 36.15511 75.18619 75.56915
[7] 62.37062 44.02730 52.42936 50.51067
> rowSd(tmp5,na.rm=TRUE)
[1] 90.074726 7.388573 5.753790 6.012912 8.670997 8.693052 7.897507
[8] 6.635307 7.240812 7.107086
> rowMax(tmp5,na.rm=TRUE)
[1] 471.68233 86.94600 80.64625 82.29084 85.30322 84.09270 83.74625
[8] 83.20565 86.64558 85.32239
> rowMin(tmp5,na.rm=TRUE)
[1] 57.77610 60.24011 56.52891 57.37289 56.75631 54.74394 59.92047 58.02017
[9] 60.67416 57.56247
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.98274 70.39325 69.92080 65.71072 68.00073 73.36475 76.34199
[8] 72.76600 69.17401 72.59101 69.88856 71.81750 73.68831 69.84726
[15] 67.46549 71.90721 72.48945 71.92806 67.99876 68.08909
> colSums(tmp5,na.rm=TRUE)
[1] 1119.8274 703.9325 699.2080 657.1072 680.0073 733.6475 763.4199
[8] 727.6600 622.5661 725.9101 698.8856 718.1750 736.8831 698.4726
[15] 674.6549 719.0721 724.8945 719.2806 679.9876 680.8909
> colVars(tmp5,na.rm=TRUE)
[1] 16025.27957 50.59875 62.22545 65.36243 44.44463 59.10896
[7] 36.90448 50.59676 53.29149 69.81346 95.50653 34.91846
[13] 64.82995 88.48926 47.62868 67.34499 90.03252 35.97218
[19] 32.53771 29.97341
> colSd(tmp5,na.rm=TRUE)
[1] 126.590993 7.113280 7.888311 8.084703 6.666680 7.688235
[7] 6.074906 7.113140 7.300102 8.355445 9.772744 5.909184
[13] 8.051705 9.406873 6.901354 8.206399 9.488547 5.997682
[19] 5.704184 5.474797
> colMax(tmp5,na.rm=TRUE)
[1] 471.68233 80.17632 80.77337 80.86196 78.09365 85.32239 83.20565
[8] 83.74625 84.00402 82.65151 86.64558 80.09872 84.09270 86.94600
[15] 80.79160 82.29084 85.58087 80.71185 75.90379 76.60799
> colMin(tmp5,na.rm=TRUE)
[1] 61.84943 56.75631 61.30546 57.02810 54.74394 65.03074 65.18350 60.44775
[9] 57.56247 58.57231 61.92594 62.96347 58.60089 58.08578 59.92047 56.52891
[17] 59.46539 63.22194 58.17543 58.02017
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.96162 73.90618 67.58551 70.29925 68.85467 70.69268 NaN 70.52755
[9] 73.87812 70.55075
> rowSums(tmp5,na.rm=TRUE)
[1] 1819.232 1478.124 1351.710 1405.985 1377.093 1413.854 0.000 1410.551
[9] 1477.562 1411.015
> rowVars(tmp5,na.rm=TRUE)
[1] 8113.45623 54.59101 33.10610 36.15511 75.18619 75.56915
[7] NA 44.02730 52.42936 50.51067
> rowSd(tmp5,na.rm=TRUE)
[1] 90.074726 7.388573 5.753790 6.012912 8.670997 8.693052 NA
[8] 6.635307 7.240812 7.107086
> rowMax(tmp5,na.rm=TRUE)
[1] 471.68233 86.94600 80.64625 82.29084 85.30322 84.09270 NA
[8] 83.20565 86.64558 85.32239
> rowMin(tmp5,na.rm=TRUE)
[1] 57.77610 60.24011 56.52891 57.37289 56.75631 54.74394 NA 58.02017
[9] 60.67416 57.56247
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 117.55311 69.59627 70.20734 65.35830 67.35081 73.92866 76.35796
[8] 71.54597 NaN 71.47318 70.72205 70.89737 72.90445 70.86465
[15] 68.30383 72.66973 73.64587 71.72912 68.33078 67.95618
> colSums(tmp5,na.rm=TRUE)
[1] 1057.9780 626.3665 631.8661 588.2247 606.1573 665.3579 687.2217
[8] 643.9137 0.0000 643.2586 636.4985 638.0763 656.1401 637.7819
[15] 614.7345 654.0275 662.8128 645.5621 614.9770 611.6056
> colVars(tmp5,na.rm=TRUE)
[1] 17679.36329 49.77794 69.07996 72.13545 45.24826 62.92014
[7] 41.51467 40.17607 NA 64.48269 99.62929 29.75846
[13] 66.02126 87.90564 45.67569 69.22210 86.24198 40.02347
[19] 35.36474 33.52135
> colSd(tmp5,na.rm=TRUE)
[1] 132.963767 7.055348 8.311435 8.493259 6.726682 7.932222
[7] 6.443188 6.338460 NA 8.030111 9.981447 5.455132
[13] 8.125347 9.375801 6.758379 8.319982 9.286656 6.326410
[19] 5.946826 5.789762
> colMax(tmp5,na.rm=TRUE)
[1] 471.68233 80.17632 80.77337 80.86196 78.09365 85.32239 83.20565
[8] 82.86809 -Inf 81.45748 86.64558 79.07715 84.09270 86.94600
[15] 80.79160 82.29084 85.58087 80.71185 75.90379 76.60799
> colMin(tmp5,na.rm=TRUE)
[1] 63.78216 56.75631 61.30546 57.02810 54.74394 65.03074 65.18350 60.44775
[9] Inf 58.57231 61.92594 62.96347 58.60089 58.08578 60.24011 56.52891
[17] 59.46539 63.22194 58.17543 58.02017
>
>
>
>
> 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] 221.6380 195.0823 193.8830 288.1184 491.0535 253.6688 231.9016 140.9735
[9] 213.8383 268.6105
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 221.6380 195.0823 193.8830 288.1184 491.0535 253.6688 231.9016 140.9735
[9] 213.8383 268.6105
>
>
>
> 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] 1.705303e-13 2.842171e-14 -1.136868e-13 5.684342e-14 -5.684342e-14
[6] 2.273737e-13 0.000000e+00 -2.842171e-14 -1.705303e-13 0.000000e+00
[11] 0.000000e+00 1.136868e-13 -5.684342e-14 -2.842171e-14 -3.410605e-13
[16] 1.421085e-14 -5.684342e-14 -1.421085e-14 5.684342e-14 -1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
2 18
7 2
7 1
5 20
2 2
1 17
2 14
6 8
8 5
7 9
6 19
9 16
6 12
4 10
3 13
5 1
6 2
5 15
9 12
1 11
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] 1.991406
> Min(tmp)
[1] -2.664992
> mean(tmp)
[1] 0.0672302
> Sum(tmp)
[1] 6.72302
> Var(tmp)
[1] 0.9079369
>
> rowMeans(tmp)
[1] 0.0672302
> rowSums(tmp)
[1] 6.72302
> rowVars(tmp)
[1] 0.9079369
> rowSd(tmp)
[1] 0.9528572
> rowMax(tmp)
[1] 1.991406
> rowMin(tmp)
[1] -2.664992
>
> colMeans(tmp)
[1] 0.836796350 -0.553520407 0.011929005 0.383488487 -0.431395158
[6] -0.431547909 -0.756298983 -0.118333278 -1.456467967 -0.106074251
[11] 0.096770778 0.657389061 -0.552718765 0.161142090 0.345695137
[16] 0.988389092 -0.068307882 -0.453571941 -0.802505521 -1.277844747
[21] -0.520660144 0.503282216 -0.645582877 0.614603656 -0.239036949
[26] 0.102561983 1.065147756 -0.207246555 0.814327212 1.178215480
[31] -0.440952933 -0.467728843 0.008611898 1.549955613 -1.795246803
[36] -1.076680558 0.712063073 1.494287209 0.136002126 0.652815451
[41] 0.143514115 -1.179588551 0.413209188 0.498538355 -0.211801705
[46] 0.671864768 -0.093910234 1.272774754 1.075306701 -2.539178014
[51] -2.664991541 0.543660376 -1.690654993 1.854153282 0.197504501
[56] 1.391076168 1.108921545 1.579352949 1.617653507 -1.684947694
[61] -0.199177532 -0.211500845 0.813186602 -1.113972031 -0.651475923
[66] 0.302693884 -0.483631002 0.068077305 -0.630114705 0.102314229
[71] -1.142620304 1.094572506 0.198478414 -1.123110783 1.796085416
[76] 0.088466075 -0.153000302 1.578565963 0.470111473 0.590096365
[81] 1.002656634 0.214911883 -0.028671602 -0.215526316 0.938205722
[86] 1.239615860 -0.269004729 -0.895951511 -0.380965668 1.044196169
[91] 0.338153753 0.423701177 0.201840523 -1.312319367 -1.727629936
[96] -0.348383357 -0.514856708 -0.014581935 1.427969865 1.991405905
> colSums(tmp)
[1] 0.836796350 -0.553520407 0.011929005 0.383488487 -0.431395158
[6] -0.431547909 -0.756298983 -0.118333278 -1.456467967 -0.106074251
[11] 0.096770778 0.657389061 -0.552718765 0.161142090 0.345695137
[16] 0.988389092 -0.068307882 -0.453571941 -0.802505521 -1.277844747
[21] -0.520660144 0.503282216 -0.645582877 0.614603656 -0.239036949
[26] 0.102561983 1.065147756 -0.207246555 0.814327212 1.178215480
[31] -0.440952933 -0.467728843 0.008611898 1.549955613 -1.795246803
[36] -1.076680558 0.712063073 1.494287209 0.136002126 0.652815451
[41] 0.143514115 -1.179588551 0.413209188 0.498538355 -0.211801705
[46] 0.671864768 -0.093910234 1.272774754 1.075306701 -2.539178014
[51] -2.664991541 0.543660376 -1.690654993 1.854153282 0.197504501
[56] 1.391076168 1.108921545 1.579352949 1.617653507 -1.684947694
[61] -0.199177532 -0.211500845 0.813186602 -1.113972031 -0.651475923
[66] 0.302693884 -0.483631002 0.068077305 -0.630114705 0.102314229
[71] -1.142620304 1.094572506 0.198478414 -1.123110783 1.796085416
[76] 0.088466075 -0.153000302 1.578565963 0.470111473 0.590096365
[81] 1.002656634 0.214911883 -0.028671602 -0.215526316 0.938205722
[86] 1.239615860 -0.269004729 -0.895951511 -0.380965668 1.044196169
[91] 0.338153753 0.423701177 0.201840523 -1.312319367 -1.727629936
[96] -0.348383357 -0.514856708 -0.014581935 1.427969865 1.991405905
> 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] 0.836796350 -0.553520407 0.011929005 0.383488487 -0.431395158
[6] -0.431547909 -0.756298983 -0.118333278 -1.456467967 -0.106074251
[11] 0.096770778 0.657389061 -0.552718765 0.161142090 0.345695137
[16] 0.988389092 -0.068307882 -0.453571941 -0.802505521 -1.277844747
[21] -0.520660144 0.503282216 -0.645582877 0.614603656 -0.239036949
[26] 0.102561983 1.065147756 -0.207246555 0.814327212 1.178215480
[31] -0.440952933 -0.467728843 0.008611898 1.549955613 -1.795246803
[36] -1.076680558 0.712063073 1.494287209 0.136002126 0.652815451
[41] 0.143514115 -1.179588551 0.413209188 0.498538355 -0.211801705
[46] 0.671864768 -0.093910234 1.272774754 1.075306701 -2.539178014
[51] -2.664991541 0.543660376 -1.690654993 1.854153282 0.197504501
[56] 1.391076168 1.108921545 1.579352949 1.617653507 -1.684947694
[61] -0.199177532 -0.211500845 0.813186602 -1.113972031 -0.651475923
[66] 0.302693884 -0.483631002 0.068077305 -0.630114705 0.102314229
[71] -1.142620304 1.094572506 0.198478414 -1.123110783 1.796085416
[76] 0.088466075 -0.153000302 1.578565963 0.470111473 0.590096365
[81] 1.002656634 0.214911883 -0.028671602 -0.215526316 0.938205722
[86] 1.239615860 -0.269004729 -0.895951511 -0.380965668 1.044196169
[91] 0.338153753 0.423701177 0.201840523 -1.312319367 -1.727629936
[96] -0.348383357 -0.514856708 -0.014581935 1.427969865 1.991405905
> colMin(tmp)
[1] 0.836796350 -0.553520407 0.011929005 0.383488487 -0.431395158
[6] -0.431547909 -0.756298983 -0.118333278 -1.456467967 -0.106074251
[11] 0.096770778 0.657389061 -0.552718765 0.161142090 0.345695137
[16] 0.988389092 -0.068307882 -0.453571941 -0.802505521 -1.277844747
[21] -0.520660144 0.503282216 -0.645582877 0.614603656 -0.239036949
[26] 0.102561983 1.065147756 -0.207246555 0.814327212 1.178215480
[31] -0.440952933 -0.467728843 0.008611898 1.549955613 -1.795246803
[36] -1.076680558 0.712063073 1.494287209 0.136002126 0.652815451
[41] 0.143514115 -1.179588551 0.413209188 0.498538355 -0.211801705
[46] 0.671864768 -0.093910234 1.272774754 1.075306701 -2.539178014
[51] -2.664991541 0.543660376 -1.690654993 1.854153282 0.197504501
[56] 1.391076168 1.108921545 1.579352949 1.617653507 -1.684947694
[61] -0.199177532 -0.211500845 0.813186602 -1.113972031 -0.651475923
[66] 0.302693884 -0.483631002 0.068077305 -0.630114705 0.102314229
[71] -1.142620304 1.094572506 0.198478414 -1.123110783 1.796085416
[76] 0.088466075 -0.153000302 1.578565963 0.470111473 0.590096365
[81] 1.002656634 0.214911883 -0.028671602 -0.215526316 0.938205722
[86] 1.239615860 -0.269004729 -0.895951511 -0.380965668 1.044196169
[91] 0.338153753 0.423701177 0.201840523 -1.312319367 -1.727629936
[96] -0.348383357 -0.514856708 -0.014581935 1.427969865 1.991405905
> colMedians(tmp)
[1] 0.836796350 -0.553520407 0.011929005 0.383488487 -0.431395158
[6] -0.431547909 -0.756298983 -0.118333278 -1.456467967 -0.106074251
[11] 0.096770778 0.657389061 -0.552718765 0.161142090 0.345695137
[16] 0.988389092 -0.068307882 -0.453571941 -0.802505521 -1.277844747
[21] -0.520660144 0.503282216 -0.645582877 0.614603656 -0.239036949
[26] 0.102561983 1.065147756 -0.207246555 0.814327212 1.178215480
[31] -0.440952933 -0.467728843 0.008611898 1.549955613 -1.795246803
[36] -1.076680558 0.712063073 1.494287209 0.136002126 0.652815451
[41] 0.143514115 -1.179588551 0.413209188 0.498538355 -0.211801705
[46] 0.671864768 -0.093910234 1.272774754 1.075306701 -2.539178014
[51] -2.664991541 0.543660376 -1.690654993 1.854153282 0.197504501
[56] 1.391076168 1.108921545 1.579352949 1.617653507 -1.684947694
[61] -0.199177532 -0.211500845 0.813186602 -1.113972031 -0.651475923
[66] 0.302693884 -0.483631002 0.068077305 -0.630114705 0.102314229
[71] -1.142620304 1.094572506 0.198478414 -1.123110783 1.796085416
[76] 0.088466075 -0.153000302 1.578565963 0.470111473 0.590096365
[81] 1.002656634 0.214911883 -0.028671602 -0.215526316 0.938205722
[86] 1.239615860 -0.269004729 -0.895951511 -0.380965668 1.044196169
[91] 0.338153753 0.423701177 0.201840523 -1.312319367 -1.727629936
[96] -0.348383357 -0.514856708 -0.014581935 1.427969865 1.991405905
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.8367964 -0.5535204 0.01192901 0.3834885 -0.4313952 -0.4315479 -0.756299
[2,] 0.8367964 -0.5535204 0.01192901 0.3834885 -0.4313952 -0.4315479 -0.756299
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.1183333 -1.456468 -0.1060743 0.09677078 0.6573891 -0.5527188 0.1611421
[2,] -0.1183333 -1.456468 -0.1060743 0.09677078 0.6573891 -0.5527188 0.1611421
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.3456951 0.9883891 -0.06830788 -0.4535719 -0.8025055 -1.277845 -0.5206601
[2,] 0.3456951 0.9883891 -0.06830788 -0.4535719 -0.8025055 -1.277845 -0.5206601
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.5032822 -0.6455829 0.6146037 -0.2390369 0.102562 1.065148 -0.2072466
[2,] 0.5032822 -0.6455829 0.6146037 -0.2390369 0.102562 1.065148 -0.2072466
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.8143272 1.178215 -0.4409529 -0.4677288 0.008611898 1.549956 -1.795247
[2,] 0.8143272 1.178215 -0.4409529 -0.4677288 0.008611898 1.549956 -1.795247
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.076681 0.7120631 1.494287 0.1360021 0.6528155 0.1435141 -1.179589
[2,] -1.076681 0.7120631 1.494287 0.1360021 0.6528155 0.1435141 -1.179589
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.4132092 0.4985384 -0.2118017 0.6718648 -0.09391023 1.272775 1.075307
[2,] 0.4132092 0.4985384 -0.2118017 0.6718648 -0.09391023 1.272775 1.075307
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -2.539178 -2.664992 0.5436604 -1.690655 1.854153 0.1975045 1.391076
[2,] -2.539178 -2.664992 0.5436604 -1.690655 1.854153 0.1975045 1.391076
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 1.108922 1.579353 1.617654 -1.684948 -0.1991775 -0.2115008 0.8131866
[2,] 1.108922 1.579353 1.617654 -1.684948 -0.1991775 -0.2115008 0.8131866
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.113972 -0.6514759 0.3026939 -0.483631 0.06807731 -0.6301147 0.1023142
[2,] -1.113972 -0.6514759 0.3026939 -0.483631 0.06807731 -0.6301147 0.1023142
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -1.14262 1.094573 0.1984784 -1.123111 1.796085 0.08846607 -0.1530003
[2,] -1.14262 1.094573 0.1984784 -1.123111 1.796085 0.08846607 -0.1530003
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.578566 0.4701115 0.5900964 1.002657 0.2149119 -0.0286716 -0.2155263
[2,] 1.578566 0.4701115 0.5900964 1.002657 0.2149119 -0.0286716 -0.2155263
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.9382057 1.239616 -0.2690047 -0.8959515 -0.3809657 1.044196 0.3381538
[2,] 0.9382057 1.239616 -0.2690047 -0.8959515 -0.3809657 1.044196 0.3381538
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.4237012 0.2018405 -1.312319 -1.72763 -0.3483834 -0.5148567 -0.01458194
[2,] 0.4237012 0.2018405 -1.312319 -1.72763 -0.3483834 -0.5148567 -0.01458194
[,99] [,100]
[1,] 1.42797 1.991406
[2,] 1.42797 1.991406
>
>
> Max(tmp2)
[1] 2.290675
> Min(tmp2)
[1] -3.508958
> mean(tmp2)
[1] -0.1447417
> Sum(tmp2)
[1] -14.47417
> Var(tmp2)
[1] 0.9725881
>
> rowMeans(tmp2)
[1] 0.33219775 -1.40892148 -1.76630775 0.56451786 -3.50895799 -1.03180589
[7] -0.95958127 0.46627862 -0.01221751 -1.02279215 1.05897654 0.32539318
[13] 0.51423088 1.12785061 0.29230386 0.21396490 -0.64955912 -1.07327653
[19] -1.18119065 0.28566614 -0.98760727 -1.05805631 -0.52591048 0.74389060
[25] -0.31695175 -0.65506884 -0.83725553 1.67369277 -0.13009808 1.47531794
[31] -0.69059857 1.14810033 0.30002987 -0.57013080 -1.27492804 0.62247798
[37] -1.52977586 0.73750377 -1.12534880 0.11234097 0.63246629 -0.60116059
[43] -0.21414760 -0.11460136 -0.87777761 -3.32013028 0.57834838 -1.47540004
[49] 1.29786380 -0.32025830 -0.24299463 -0.04488495 -1.47488203 -0.37765284
[55] 0.68598572 -1.58204905 0.22778412 -1.06086996 0.72652663 -1.50251964
[61] -1.62611333 -1.13620604 -0.60399471 -0.36611129 0.39353910 0.26121875
[67] 0.31384791 -0.29675751 -0.10823797 0.75085774 0.09386280 -0.08539941
[73] 0.20154502 1.78594295 -0.63495390 0.56502714 -0.94181583 0.51800741
[79] -1.08949113 -0.62716188 0.90929625 2.29067477 -0.20403129 1.53758119
[85] -0.03603053 -1.09742306 1.31123066 0.29186058 -0.16257776 0.52045358
[91] -0.10474988 0.37405535 0.50349332 1.29260191 -0.79895955 0.87680059
[97] 0.17149064 -0.12642324 -0.26645048 0.25729544
> rowSums(tmp2)
[1] 0.33219775 -1.40892148 -1.76630775 0.56451786 -3.50895799 -1.03180589
[7] -0.95958127 0.46627862 -0.01221751 -1.02279215 1.05897654 0.32539318
[13] 0.51423088 1.12785061 0.29230386 0.21396490 -0.64955912 -1.07327653
[19] -1.18119065 0.28566614 -0.98760727 -1.05805631 -0.52591048 0.74389060
[25] -0.31695175 -0.65506884 -0.83725553 1.67369277 -0.13009808 1.47531794
[31] -0.69059857 1.14810033 0.30002987 -0.57013080 -1.27492804 0.62247798
[37] -1.52977586 0.73750377 -1.12534880 0.11234097 0.63246629 -0.60116059
[43] -0.21414760 -0.11460136 -0.87777761 -3.32013028 0.57834838 -1.47540004
[49] 1.29786380 -0.32025830 -0.24299463 -0.04488495 -1.47488203 -0.37765284
[55] 0.68598572 -1.58204905 0.22778412 -1.06086996 0.72652663 -1.50251964
[61] -1.62611333 -1.13620604 -0.60399471 -0.36611129 0.39353910 0.26121875
[67] 0.31384791 -0.29675751 -0.10823797 0.75085774 0.09386280 -0.08539941
[73] 0.20154502 1.78594295 -0.63495390 0.56502714 -0.94181583 0.51800741
[79] -1.08949113 -0.62716188 0.90929625 2.29067477 -0.20403129 1.53758119
[85] -0.03603053 -1.09742306 1.31123066 0.29186058 -0.16257776 0.52045358
[91] -0.10474988 0.37405535 0.50349332 1.29260191 -0.79895955 0.87680059
[97] 0.17149064 -0.12642324 -0.26645048 0.25729544
> 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] 0.33219775 -1.40892148 -1.76630775 0.56451786 -3.50895799 -1.03180589
[7] -0.95958127 0.46627862 -0.01221751 -1.02279215 1.05897654 0.32539318
[13] 0.51423088 1.12785061 0.29230386 0.21396490 -0.64955912 -1.07327653
[19] -1.18119065 0.28566614 -0.98760727 -1.05805631 -0.52591048 0.74389060
[25] -0.31695175 -0.65506884 -0.83725553 1.67369277 -0.13009808 1.47531794
[31] -0.69059857 1.14810033 0.30002987 -0.57013080 -1.27492804 0.62247798
[37] -1.52977586 0.73750377 -1.12534880 0.11234097 0.63246629 -0.60116059
[43] -0.21414760 -0.11460136 -0.87777761 -3.32013028 0.57834838 -1.47540004
[49] 1.29786380 -0.32025830 -0.24299463 -0.04488495 -1.47488203 -0.37765284
[55] 0.68598572 -1.58204905 0.22778412 -1.06086996 0.72652663 -1.50251964
[61] -1.62611333 -1.13620604 -0.60399471 -0.36611129 0.39353910 0.26121875
[67] 0.31384791 -0.29675751 -0.10823797 0.75085774 0.09386280 -0.08539941
[73] 0.20154502 1.78594295 -0.63495390 0.56502714 -0.94181583 0.51800741
[79] -1.08949113 -0.62716188 0.90929625 2.29067477 -0.20403129 1.53758119
[85] -0.03603053 -1.09742306 1.31123066 0.29186058 -0.16257776 0.52045358
[91] -0.10474988 0.37405535 0.50349332 1.29260191 -0.79895955 0.87680059
[97] 0.17149064 -0.12642324 -0.26645048 0.25729544
> rowMin(tmp2)
[1] 0.33219775 -1.40892148 -1.76630775 0.56451786 -3.50895799 -1.03180589
[7] -0.95958127 0.46627862 -0.01221751 -1.02279215 1.05897654 0.32539318
[13] 0.51423088 1.12785061 0.29230386 0.21396490 -0.64955912 -1.07327653
[19] -1.18119065 0.28566614 -0.98760727 -1.05805631 -0.52591048 0.74389060
[25] -0.31695175 -0.65506884 -0.83725553 1.67369277 -0.13009808 1.47531794
[31] -0.69059857 1.14810033 0.30002987 -0.57013080 -1.27492804 0.62247798
[37] -1.52977586 0.73750377 -1.12534880 0.11234097 0.63246629 -0.60116059
[43] -0.21414760 -0.11460136 -0.87777761 -3.32013028 0.57834838 -1.47540004
[49] 1.29786380 -0.32025830 -0.24299463 -0.04488495 -1.47488203 -0.37765284
[55] 0.68598572 -1.58204905 0.22778412 -1.06086996 0.72652663 -1.50251964
[61] -1.62611333 -1.13620604 -0.60399471 -0.36611129 0.39353910 0.26121875
[67] 0.31384791 -0.29675751 -0.10823797 0.75085774 0.09386280 -0.08539941
[73] 0.20154502 1.78594295 -0.63495390 0.56502714 -0.94181583 0.51800741
[79] -1.08949113 -0.62716188 0.90929625 2.29067477 -0.20403129 1.53758119
[85] -0.03603053 -1.09742306 1.31123066 0.29186058 -0.16257776 0.52045358
[91] -0.10474988 0.37405535 0.50349332 1.29260191 -0.79895955 0.87680059
[97] 0.17149064 -0.12642324 -0.26645048 0.25729544
>
> colMeans(tmp2)
[1] -0.1447417
> colSums(tmp2)
[1] -14.47417
> colVars(tmp2)
[1] 0.9725881
> colSd(tmp2)
[1] 0.9861988
> colMax(tmp2)
[1] 2.290675
> colMin(tmp2)
[1] -3.508958
> colMedians(tmp2)
[1] -0.1064939
> colRanges(tmp2)
[,1]
[1,] -3.508958
[2,] 2.290675
>
> 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] 3.3734960 -5.6585556 2.5111403 1.4831756 -1.6494103 0.9169471
[7] 3.1679023 -1.8802142 0.3823175 1.0952616
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.56296264
[2,] -0.05921687
[3,] 0.30328837
[4,] 0.51806609
[5,] 2.05219829
>
> rowApply(tmp,sum)
[1] -1.9165920 -1.6772547 1.3164329 -0.3102137 6.2396757 0.9268454
[7] 1.1129339 -3.1143637 -1.8827969 3.0473934
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 7 5 3 6 6 10 4 8 4
[2,] 4 6 2 5 2 7 3 3 2 1
[3,] 6 9 10 1 5 10 6 8 4 7
[4,] 5 3 3 6 3 9 9 2 10 10
[5,] 3 10 7 7 8 3 7 1 1 8
[6,] 1 2 6 8 10 4 1 9 5 9
[7,] 8 5 9 10 1 5 5 10 6 2
[8,] 10 1 1 4 4 2 8 7 3 5
[9,] 7 4 4 2 9 8 4 6 7 6
[10,] 2 8 8 9 7 1 2 5 9 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.2541438 -1.9411713 -2.6432172 0.6234066 -2.6311295 0.5814988
[7] 0.2900529 3.4830473 -0.6154717 2.3371519 2.8158757 -0.5779596
[13] -0.2381981 -0.6190822 -4.6021350 -0.2954036 -2.2249637 1.9950191
[19] 3.7430216 2.3888179
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.9573279
[2,] -0.8043151
[3,] -0.2260346
[4,] 0.2200562
[5,] 0.5134775
>
> rowApply(tmp,sum)
[1] 0.9597140 -0.8212625 -5.3786650 -0.3146953 5.1699250
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 2 10 5 14 13
[2,] 6 9 6 8 3
[3,] 11 12 12 1 6
[4,] 17 2 13 17 12
[5,] 5 7 16 3 2
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.9573279 -0.42269637 0.20322947 1.3752952 -0.4710860 -0.38814998
[2,] -0.2260346 -0.23112112 -0.06064643 -1.6761693 -0.5662439 0.27237189
[3,] -0.8043151 -0.65655604 -0.23820225 -0.1087146 0.4446121 0.94097192
[4,] 0.5134775 -0.08370002 -2.36878312 0.8661050 -1.3600038 -0.23105895
[5,] 0.2200562 -0.54709778 -0.17881487 0.1668904 -0.6784079 -0.01263613
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.1752126 0.9934740 0.01604955 -1.33948597 1.4664280 1.5565081
[2,] 0.4466913 1.4350039 -0.18545944 1.69384816 1.5364997 -0.3860434
[3,] -0.3161790 1.3986145 -2.89627682 -0.27640215 -1.3771329 -0.4341940
[4,] 0.4259780 -0.9024546 1.29360255 0.09263009 0.1635754 -0.9660534
[5,] -0.0912248 0.5584095 1.15661242 2.16656175 1.0265055 -0.3481769
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.4491505 0.22568605 -2.105327 -0.3359400 -0.9198714 0.9152139
[2,] -0.6184204 0.34443880 -2.076834 0.9455381 -0.8606628 -0.5814681
[3,] 0.6964352 0.05070564 0.433626 -0.3658266 -1.1834319 -1.1627061
[4,] -1.0286937 -1.37963988 0.302260 -0.0804472 0.6724790 0.9913911
[5,] 0.2633303 0.13972722 -1.155860 -0.4587279 0.0665233 1.8325884
[,19] [,20]
[1,] 0.3465296 1.527247069
[2,] 0.8314463 -0.857997603
[3,] 0.7675246 -0.291217533
[4,] 0.7573502 2.007290631
[5,] 1.0401710 0.003495364
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -1.402828 -0.3376578 -0.747345 -0.3520999 0.06330268 0.6850813 1.034634
col8 col9 col10 col11 col12 col13 col14
row1 0.284861 0.6619149 -0.2325451 -0.05444572 -0.741815 -1.033793 0.6265475
col15 col16 col17 col18 col19 col20
row1 0.3415314 -0.3646474 -0.3233778 -0.4349394 -1.08598 1.275932
> tmp[,"col10"]
col10
row1 -0.2325451
row2 0.5070599
row3 0.3735047
row4 -0.5034275
row5 -0.5993644
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -1.4028276 -0.3376578 -0.7473450 -0.3520999 0.06330268 0.6850813
row5 0.4206945 -1.3186725 -0.3247558 -0.3803636 -1.26615327 -1.6193913
col7 col8 col9 col10 col11 col12 col13
row1 1.0346340 0.284861 0.6619149 -0.2325451 -0.05444572 -0.7418150 -1.033793
row5 0.8038479 1.070802 0.2931584 -0.5993644 1.36982179 0.3864732 1.658465
col14 col15 col16 col17 col18 col19
row1 0.6265475 0.3415314 -0.36464735 -0.3233778 -0.4349394 -1.0859797
row5 -0.4036717 0.7924569 -0.08371754 0.6926588 0.3337170 -0.6813091
col20
row1 1.2759321
row5 -0.5882553
> tmp[,c("col6","col20")]
col6 col20
row1 0.6850813 1.2759321
row2 -0.6524927 -0.8009700
row3 0.8129793 0.4106845
row4 1.5495350 0.8118927
row5 -1.6193913 -0.5882553
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.6850813 1.2759321
row5 -1.6193913 -0.5882553
>
>
>
>
> 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 50.12661 49.50384 50.63544 48.48869 47.28521 105.7196 51.09441 49.54637
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.03405 50.7061 48.62871 51.33166 50.10379 48.79647 49.78108 51.66164
col17 col18 col19 col20
row1 48.83209 50.56093 50.3412 104.3184
> tmp[,"col10"]
col10
row1 50.70610
row2 29.01813
row3 30.13995
row4 30.01309
row5 49.06323
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.12661 49.50384 50.63544 48.48869 47.28521 105.7196 51.09441 49.54637
row5 49.45650 50.37514 49.80543 49.99626 51.02738 105.4623 50.13371 48.45557
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.03405 50.70610 48.62871 51.33166 50.10379 48.79647 49.78108 51.66164
row5 50.18128 49.06323 49.21297 50.16684 51.02246 48.88208 51.96319 50.81886
col17 col18 col19 col20
row1 48.83209 50.56093 50.34120 104.3184
row5 50.28391 50.09236 50.26162 102.3242
> tmp[,c("col6","col20")]
col6 col20
row1 105.71961 104.31844
row2 73.83115 76.01642
row3 74.56451 74.19714
row4 75.14165 75.48821
row5 105.46228 102.32417
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.7196 104.3184
row5 105.4623 102.3242
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.7196 104.3184
row5 105.4623 102.3242
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.3419497
[2,] 0.8853157
[3,] 0.7980341
[4,] 1.2471864
[5,] 0.1804044
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.74545842 1.7099974
[2,] 0.83948199 1.1542710
[3,] 0.62316665 -0.6209435
[4,] 0.81211285 0.2100435
[5,] 0.05276396 0.2817036
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.4939408 1.6365999
[2,] -0.3609606 1.5490626
[3,] -0.4353722 0.2371035
[4,] 1.8896234 0.6760932
[5,] 0.2198584 0.7723762
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.493941
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.4939408
[2,] -0.3609606
>
>
>
> 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 -0.3719403 -1.659909 -0.9589647 -0.1836535 -1.227035 1.346268 0.3208641
row1 0.1245580 -1.418078 -0.1707573 0.2429238 1.382457 1.594216 -0.4738567
[,8] [,9] [,10] [,11] [,12] [,13]
row3 0.9105281 -0.8646553 -0.4976232 0.04028722 -0.3045094 0.4316900
row1 -1.2990300 0.9577346 -0.6599572 -0.77529538 -0.2904259 -0.9475305
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.2718215 -2.189275 1.300237 -0.2865163 -0.06983497 0.6005810
row1 -0.8487033 -1.237495 -0.332001 1.1843992 -0.48307640 -0.2390061
[,20]
row3 -1.133556142
row1 -0.006869029
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.807969 0.3320407 -0.07475996 1.355238 0.7743471 0.8277881 1.880066
[,8] [,9] [,10]
row2 -2.026428 1.005491 -0.50112
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.5489934 0.2920707 0.4068885 -0.6972339 -0.4348218 -0.8208905 0.8876476
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.5888276 -0.5215349 0.9611815 0.1056465 0.04708175 -0.096003 -0.04299184
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.8466214 0.1661258 -0.2023195 -0.5819237 -0.3328998 1.173412
>
>
> 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: 0x1dcf7310>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM16c99053c2dcc6"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM16c99065bf8cfd"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM16c99041fa97e6"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM16c990260a5c46"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM16c9904d1eca3f"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM16c99061be34eb"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM16c990548dcce5"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM16c99090528ef"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM16c99062c4eecb"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM16c9906668aa83"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM16c9901c2b5dee"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM16c990507c1aa0"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM16c990194dc8ad"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM16c9903e9d73f4"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM16c990758a634f"
>
>
> ### 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: 0x1fc40e40>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x1fc40e40>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x1fc40e40>
> rowMedians(tmp)
[1] -1.879468e-01 -2.228971e-01 6.142354e-01 -3.456786e-01 3.823072e-01
[6] -2.329173e-02 1.466748e-01 4.009045e-01 3.391569e-01 -3.477577e-01
[11] -7.173969e-02 -2.507540e-01 -3.357395e-02 2.517658e-01 -3.831342e-01
[16] 5.165347e-01 -1.459670e-01 3.566620e-01 -1.799839e-01 -4.422339e-01
[21] 2.619748e-01 -3.181346e-01 4.753967e-01 4.909021e-01 -2.497639e-01
[26] -5.212997e-01 -3.283123e-01 6.174653e-01 -2.996380e-01 6.730528e-03
[31] -2.812762e-01 4.291838e-02 3.069442e-01 1.951858e-01 4.738356e-01
[36] 2.818977e-01 3.852258e-01 1.078722e-01 1.624909e-01 2.407575e-01
[41] -2.703132e-01 -5.271666e-01 -3.840685e-01 -4.579430e-02 -2.706108e-01
[46] 1.682945e-01 2.621868e-01 -7.468653e-02 1.770043e-01 1.653621e-01
[51] -4.917802e-02 -3.960173e-01 -2.515977e-01 2.157553e-01 9.284469e-01
[56] 2.158591e-01 3.412079e-01 1.980965e-01 1.687705e-01 -1.122053e-01
[61] -1.536297e-01 7.266382e-02 8.425029e-02 5.039798e-02 -6.097104e-01
[66] 2.553302e-01 3.828807e-01 -7.570848e-05 7.410192e-02 1.389953e-01
[71] 1.985836e-01 6.829961e-01 3.362769e-01 1.940277e-01 -2.857831e-01
[76] 7.541006e-01 3.934617e-01 -2.463969e-01 5.437888e-02 -1.727092e-01
[81] 2.939688e-01 2.296584e-01 -3.535784e-03 4.646778e-01 1.196203e-01
[86] -2.518256e-01 3.917648e-01 -1.534204e-02 5.548670e-01 2.669477e-01
[91] -1.042789e-02 -3.457401e-01 4.933852e-01 1.892811e-01 1.126517e-02
[96] 7.812395e-02 5.023924e-01 -1.769927e-02 -2.996962e-01 5.203476e-01
[101] -4.964077e-01 8.546247e-02 -2.486589e-01 -4.441693e-01 2.742445e-01
[106] -4.242081e-01 3.066667e-01 -2.761195e-02 1.368010e-01 2.443592e-01
[111] -1.123423e-01 -8.002127e-02 2.072830e-01 -1.081382e-01 -2.701383e-01
[116] -1.449815e-01 1.283783e-01 -5.423627e-02 2.425961e-01 -7.071493e-02
[121] -4.227773e-02 7.523757e-02 -3.941139e-01 -1.914240e-01 3.415740e-01
[126] 7.759114e-03 -1.667091e-01 -5.489876e-01 -1.667091e-01 2.366211e-01
[131] -1.363178e-01 -4.498771e-01 3.601590e-01 3.217614e-01 5.064006e-01
[136] 7.071162e-02 -2.139671e-01 3.346449e-01 1.381059e-01 -1.594126e-01
[141] 1.209047e-01 1.656996e-01 4.669168e-01 -3.533366e-01 1.023593e-01
[146] -7.261792e-02 2.510939e-01 -6.667388e-01 -1.825190e-01 6.810584e-02
[151] -2.072527e-01 3.710140e-01 -1.630987e-01 7.979891e-02 -1.515591e-01
[156] 2.159526e-01 2.178720e-03 1.282511e-01 -1.765189e-01 -3.317567e-01
[161] -1.644468e-01 -2.796382e-01 -5.117689e-01 -3.828628e-01 8.446262e-01
[166] -2.254438e-01 1.813034e-01 1.781859e-01 -2.336157e-01 -2.367314e-02
[171] 1.997599e-01 2.169208e-01 -1.502520e-02 2.509502e-01 -3.098020e-01
[176] -7.043091e-01 -2.055883e-01 -2.277213e-03 5.737492e-02 6.503023e-02
[181] 6.996543e-02 3.438726e-01 1.882404e-01 4.365052e-02 1.214995e-01
[186] 1.528035e-01 5.910940e-01 3.693884e-01 -7.275457e-02 -1.720553e-02
[191] -1.477377e-01 7.453427e-01 -5.373225e-01 -2.525076e-01 -1.971809e-01
[196] 4.708886e-04 1.303435e-02 2.825251e-01 3.436136e-01 3.160184e-01
[201] 1.931282e-01 -1.526694e-01 1.048519e-02 -2.240697e-01 -2.774940e-01
[206] -5.413341e-01 -4.537243e-01 -1.340065e-01 -1.655692e-01 -1.592247e-02
[211] 2.728978e-02 -2.287433e-01 3.992709e-02 -4.731784e-01 3.401906e-01
[216] -1.118349e-01 -3.813101e-01 1.218915e-01 -1.147240e-01 -2.132465e-02
[221] 4.358406e-02 -2.915617e-01 -8.408362e-02 -5.077003e-01 -2.521170e-01
[226] 2.962895e-01 -5.706485e-02 4.180678e-01 9.371482e-02 -2.207375e-01
>
> proc.time()
user system elapsed
1.825 0.878 2.729
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x3771aff0>
> .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: 0x3771aff0>
> .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: 0x3771aff0>
> .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: 0x3771aff0>
> 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: 0x37625470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x37625470>
> .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: 0x37625470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x37625470>
> .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: 0x37625470>
> 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: 0x376000e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x376000e0>
> .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: 0x376000e0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x376000e0>
> .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: 0x376000e0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x376000e0>
> .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: 0x376000e0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x376000e0>
> .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: 0x376000e0>
> 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: 0x36587520>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x36587520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x36587520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x36587520>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile16ca403bd2e178" "BufferedMatrixFile16ca4041920acb"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile16ca403bd2e178" "BufferedMatrixFile16ca4041920acb"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x384d0030>
> .Call("R_bm_AddColumn",P)
<pointer: 0x384d0030>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x384d0030>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x384d0030>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x384d0030>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x384d0030>
> .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: 0x36e9b5c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x36e9b5c0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x36e9b5c0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x36e9b5c0>
> 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: 0x37f7bf30>
> .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: 0x37f7bf30>
> rm(P)
>
> proc.time()
user system elapsed
0.336 0.036 0.358
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.326 0.035 0.347