Ben Bolstad
| Snapshot Date: 2025-09-26 13:45 -0400 (Fri, 26 Sep 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 2025-09-27 12:07 -0400 (Sat, 27 Sep 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" | 4832 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4620 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4565 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4563 |
| 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 253/2334 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.73.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 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: 2025-09-26 05:55:16 -0000 (Fri, 26 Sep 2025) |
| EndedAt: 2025-09-26 05:55:39 -0000 (Fri, 26 Sep 2025) |
| EllapsedTime: 23.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.73.0.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
0.340 0.036 0.359
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] "Fri Sep 26 05:55:33 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] "Fri Sep 26 05:55:33 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: 0x41a5cff0>
>
>
>
> 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] "Fri Sep 26 05:55:34 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] "Fri Sep 26 05:55:34 2025"
>
> ColMode(tmp2)
<pointer: 0x41a5cff0>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.9075339 -1.62846373 -0.08414151 0.1361665
[2,] -1.5798440 0.01474792 0.25360920 0.0373189
[3,] -0.2725678 -0.44876770 0.76484203 -0.3913036
[4,] -0.1606026 -0.08209723 -2.26250086 0.2673348
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.9075339 1.62846373 0.08414151 0.1361665
[2,] 1.5798440 0.01474792 0.25360920 0.0373189
[3,] 0.2725678 0.44876770 0.76484203 0.3913036
[4,] 0.1606026 0.08209723 2.26250086 0.2673348
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9953756 1.2761127 0.2900716 0.3690074
[2,] 1.2569184 0.1214410 0.5035963 0.1931810
[3,] 0.5220803 0.6699013 0.8745525 0.6255426
[4,] 0.4007526 0.2865261 1.5041612 0.5170443
>
> 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,] 224.86129 39.38959 27.98486 28.82624
[2,] 39.14903 26.22916 30.28957 26.96913
[3,] 30.49337 32.14778 34.51037 31.64673
[4,] 29.16813 27.94736 42.30411 30.43778
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x42c8c9a0>
> exp(tmp5)
<pointer: 0x42c8c9a0>
> log(tmp5,2)
<pointer: 0x42c8c9a0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.0193
> Min(tmp5)
[1] 52.68346
> mean(tmp5)
[1] 72.12416
> Sum(tmp5)
[1] 14424.83
> Var(tmp5)
[1] 863.7103
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.53028 68.52568 68.87145 71.22270 71.20539 70.07781 69.92937 71.64777
[9] 69.51986 69.71126
> rowSums(tmp5)
[1] 1810.606 1370.514 1377.429 1424.454 1424.108 1401.556 1398.587 1432.955
[9] 1390.397 1394.225
> rowVars(tmp5)
[1] 7985.16012 74.51345 72.60770 74.00856 88.81679 47.26688
[7] 37.12281 104.19532 84.43737 71.98659
> rowSd(tmp5)
[1] 89.359723 8.632118 8.521015 8.602823 9.424266 6.875091 6.092849
[8] 10.207611 9.188981 8.484491
> rowMax(tmp5)
[1] 468.01931 81.48357 89.23355 88.05047 87.02640 86.15558 79.68507
[8] 88.00981 84.34541 83.85748
> rowMin(tmp5)
[1] 54.57154 52.68346 54.79595 58.16877 59.11942 58.81842 54.19199 55.71425
[9] 53.62410 53.95265
>
> colMeans(tmp5)
[1] 111.02105 66.94368 70.58323 68.86614 74.78206 70.86133 69.22990
[8] 67.40051 68.89546 72.47433 71.81974 71.76182 68.08791 72.69615
[15] 71.80738 72.62248 74.22946 69.98572 62.17336 66.24145
> colSums(tmp5)
[1] 1110.2105 669.4368 705.8323 688.6614 747.8206 708.6133 692.2990
[8] 674.0051 688.9546 724.7433 718.1974 717.6182 680.8791 726.9615
[15] 718.0738 726.2248 742.2946 699.8572 621.7336 662.4145
> colVars(tmp5)
[1] 15830.92740 81.50375 152.19903 79.22429 37.80962 79.06185
[7] 64.44500 84.09831 77.40855 62.65529 86.16730 61.88716
[13] 77.80797 57.51352 62.78232 53.38388 83.13123 37.70842
[19] 32.95175 36.58077
> colSd(tmp5)
[1] 125.821013 9.027942 12.336897 8.900803 6.148953 8.891673
[7] 8.027764 9.170513 8.798213 7.915510 9.282634 7.866840
[13] 8.820883 7.583767 7.923529 7.306427 9.117633 6.140718
[19] 5.740362 6.048204
> colMax(tmp5)
[1] 468.01931 81.98427 88.05047 84.34541 83.85748 83.03562 84.10441
[8] 79.98445 82.90362 86.15558 89.23355 83.03180 86.53388 87.02858
[15] 80.37812 83.81767 84.23810 79.98372 69.34167 77.73845
> colMin(tmp5)
[1] 54.19199 54.59256 58.24681 56.13271 60.72730 53.95265 58.69912 54.79595
[9] 52.68346 63.16621 57.26394 60.68204 59.11942 58.75889 57.58217 62.13375
[17] 58.94915 61.59690 53.62410 55.15230
>
>
> ### 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] 90.53028 68.52568 68.87145 71.22270 71.20539 70.07781 69.92937 NA
[9] 69.51986 69.71126
> rowSums(tmp5)
[1] 1810.606 1370.514 1377.429 1424.454 1424.108 1401.556 1398.587 NA
[9] 1390.397 1394.225
> rowVars(tmp5)
[1] 7985.16012 74.51345 72.60770 74.00856 88.81679 47.26688
[7] 37.12281 109.38864 84.43737 71.98659
> rowSd(tmp5)
[1] 89.359723 8.632118 8.521015 8.602823 9.424266 6.875091 6.092849
[8] 10.458903 9.188981 8.484491
> rowMax(tmp5)
[1] 468.01931 81.48357 89.23355 88.05047 87.02640 86.15558 79.68507
[8] NA 84.34541 83.85748
> rowMin(tmp5)
[1] 54.57154 52.68346 54.79595 58.16877 59.11942 58.81842 54.19199 NA
[9] 53.62410 53.95265
>
> colMeans(tmp5)
[1] NA 66.94368 70.58323 68.86614 74.78206 70.86133 69.22990 67.40051
[9] 68.89546 72.47433 71.81974 71.76182 68.08791 72.69615 71.80738 72.62248
[17] 74.22946 69.98572 62.17336 66.24145
> colSums(tmp5)
[1] NA 669.4368 705.8323 688.6614 747.8206 708.6133 692.2990 674.0051
[9] 688.9546 724.7433 718.1974 717.6182 680.8791 726.9615 718.0738 726.2248
[17] 742.2946 699.8572 621.7336 662.4145
> colVars(tmp5)
[1] NA 81.50375 152.19903 79.22429 37.80962 79.06185 64.44500
[8] 84.09831 77.40855 62.65529 86.16730 61.88716 77.80797 57.51352
[15] 62.78232 53.38388 83.13123 37.70842 32.95175 36.58077
> colSd(tmp5)
[1] NA 9.027942 12.336897 8.900803 6.148953 8.891673 8.027764
[8] 9.170513 8.798213 7.915510 9.282634 7.866840 8.820883 7.583767
[15] 7.923529 7.306427 9.117633 6.140718 5.740362 6.048204
> colMax(tmp5)
[1] NA 81.98427 88.05047 84.34541 83.85748 83.03562 84.10441 79.98445
[9] 82.90362 86.15558 89.23355 83.03180 86.53388 87.02858 80.37812 83.81767
[17] 84.23810 79.98372 69.34167 77.73845
> colMin(tmp5)
[1] NA 54.59256 58.24681 56.13271 60.72730 53.95265 58.69912 54.79595
[9] 52.68346 63.16621 57.26394 60.68204 59.11942 58.75889 57.58217 62.13375
[17] 58.94915 61.59690 53.62410 55.15230
>
> Max(tmp5,na.rm=TRUE)
[1] 468.0193
> Min(tmp5,na.rm=TRUE)
[1] 52.68346
> mean(tmp5,na.rm=TRUE)
[1] 72.11052
> Sum(tmp5,na.rm=TRUE)
[1] 14349.99
> Var(tmp5,na.rm=TRUE)
[1] 868.0351
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.53028 68.52568 68.87145 71.22270 71.20539 70.07781 69.92937 71.47984
[9] 69.51986 69.71126
> rowSums(tmp5,na.rm=TRUE)
[1] 1810.606 1370.514 1377.429 1424.454 1424.108 1401.556 1398.587 1358.117
[9] 1390.397 1394.225
> rowVars(tmp5,na.rm=TRUE)
[1] 7985.16012 74.51345 72.60770 74.00856 88.81679 47.26688
[7] 37.12281 109.38864 84.43737 71.98659
> rowSd(tmp5,na.rm=TRUE)
[1] 89.359723 8.632118 8.521015 8.602823 9.424266 6.875091 6.092849
[8] 10.458903 9.188981 8.484491
> rowMax(tmp5,na.rm=TRUE)
[1] 468.01931 81.48357 89.23355 88.05047 87.02640 86.15558 79.68507
[8] 88.00981 84.34541 83.85748
> rowMin(tmp5,na.rm=TRUE)
[1] 54.57154 52.68346 54.79595 58.16877 59.11942 58.81842 54.19199 55.71425
[9] 53.62410 53.95265
>
> colMeans(tmp5,na.rm=TRUE)
[1] 115.04136 66.94368 70.58323 68.86614 74.78206 70.86133 69.22990
[8] 67.40051 68.89546 72.47433 71.81974 71.76182 68.08791 72.69615
[15] 71.80738 72.62248 74.22946 69.98572 62.17336 66.24145
> colSums(tmp5,na.rm=TRUE)
[1] 1035.3722 669.4368 705.8323 688.6614 747.8206 708.6133 692.2990
[8] 674.0051 688.9546 724.7433 718.1974 717.6182 680.8791 726.9615
[15] 718.0738 726.2248 742.2946 699.8572 621.7336 662.4145
> colVars(tmp5,na.rm=TRUE)
[1] 17627.96159 81.50375 152.19903 79.22429 37.80962 79.06185
[7] 64.44500 84.09831 77.40855 62.65529 86.16730 61.88716
[13] 77.80797 57.51352 62.78232 53.38388 83.13123 37.70842
[19] 32.95175 36.58077
> colSd(tmp5,na.rm=TRUE)
[1] 132.770334 9.027942 12.336897 8.900803 6.148953 8.891673
[7] 8.027764 9.170513 8.798213 7.915510 9.282634 7.866840
[13] 8.820883 7.583767 7.923529 7.306427 9.117633 6.140718
[19] 5.740362 6.048204
> colMax(tmp5,na.rm=TRUE)
[1] 468.01931 81.98427 88.05047 84.34541 83.85748 83.03562 84.10441
[8] 79.98445 82.90362 86.15558 89.23355 83.03180 86.53388 87.02858
[15] 80.37812 83.81767 84.23810 79.98372 69.34167 77.73845
> colMin(tmp5,na.rm=TRUE)
[1] 54.19199 54.59256 58.24681 56.13271 60.72730 53.95265 58.69912 54.79595
[9] 52.68346 63.16621 57.26394 60.68204 59.11942 58.75889 57.58217 62.13375
[17] 58.94915 61.59690 53.62410 55.15230
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.53028 68.52568 68.87145 71.22270 71.20539 70.07781 69.92937 NaN
[9] 69.51986 69.71126
> rowSums(tmp5,na.rm=TRUE)
[1] 1810.606 1370.514 1377.429 1424.454 1424.108 1401.556 1398.587 0.000
[9] 1390.397 1394.225
> rowVars(tmp5,na.rm=TRUE)
[1] 7985.16012 74.51345 72.60770 74.00856 88.81679 47.26688
[7] 37.12281 NA 84.43737 71.98659
> rowSd(tmp5,na.rm=TRUE)
[1] 89.359723 8.632118 8.521015 8.602823 9.424266 6.875091 6.092849
[8] NA 9.188981 8.484491
> rowMax(tmp5,na.rm=TRUE)
[1] 468.01931 81.48357 89.23355 88.05047 87.02640 86.15558 79.68507
[8] NA 84.34541 83.85748
> rowMin(tmp5,na.rm=TRUE)
[1] 54.57154 52.68346 54.79595 58.16877 59.11942 58.81842 54.19199 NA
[9] 53.62410 53.95265
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] NaN 68.19139 68.64694 67.66293 74.62339 70.99781 69.39805 66.30786
[9] 67.33900 73.36598 73.43705 72.78356 66.03835 72.69042 73.38796 71.37857
[17] 73.53376 69.92212 62.55396 66.24135
> colSums(tmp5,na.rm=TRUE)
[1] 0.0000 613.7225 617.8225 608.9664 671.6105 638.9803 624.5824 596.7707
[9] 606.0510 660.2938 660.9335 655.0520 594.3452 654.2137 660.4916 642.4071
[17] 661.8038 629.2990 562.9856 596.1722
> colVars(tmp5,na.rm=TRUE)
[1] NA 74.17782 129.04535 72.84068 42.25260 88.73502 72.18256
[8] 81.17935 59.83066 61.54302 67.51162 57.87870 40.27645 64.70234
[15] 42.52504 42.64962 88.07764 42.37645 35.44111 41.15336
> colSd(tmp5,na.rm=TRUE)
[1] NA 8.612655 11.359813 8.534675 6.500200 9.419927 8.496032
[8] 9.009958 7.735028 7.844936 8.216546 7.607805 6.346373 8.043777
[15] 6.521123 6.530667 9.384969 6.509720 5.953244 6.415089
> colMax(tmp5,na.rm=TRUE)
[1] -Inf 81.98427 88.05047 84.34541 83.85748 83.03562 84.10441 79.98445
[9] 79.68507 86.15558 89.23355 83.03180 76.72561 87.02858 80.37812 81.70822
[17] 84.23810 79.98372 69.34167 77.73845
> colMin(tmp5,na.rm=TRUE)
[1] Inf 54.59256 58.24681 56.13271 60.72730 53.95265 58.69912 54.79595
[9] 52.68346 63.16621 61.68764 60.68204 59.11942 58.75889 61.79002 62.13375
[17] 58.94915 61.59690 53.62410 55.15230
>
>
>
>
> 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] 331.3929 304.7343 126.3152 129.2193 216.0933 218.6668 113.5183 324.9254
[9] 139.5488 206.8028
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 331.3929 304.7343 126.3152 129.2193 216.0933 218.6668 113.5183 324.9254
[9] 139.5488 206.8028
>
>
>
> 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 5.684342e-14 -2.842171e-14 0.000000e+00 -1.136868e-13
[6] -4.263256e-14 5.684342e-14 5.684342e-14 -2.842171e-14 -1.563194e-13
[11] 8.526513e-14 8.526513e-14 -1.136868e-13 2.842171e-14 5.684342e-14
[16] 0.000000e+00 -2.842171e-14 1.136868e-13 5.684342e-14 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## 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)
+ }
9 3
3 11
5 11
4 3
7 20
7 2
1 7
2 7
1 16
2 8
7 6
2 12
4 3
4 20
1 1
6 7
4 15
6 18
5 16
9 2
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] 2.264464
> Min(tmp)
[1] -1.881385
> mean(tmp)
[1] 0.02456591
> Sum(tmp)
[1] 2.456591
> Var(tmp)
[1] 0.859734
>
> rowMeans(tmp)
[1] 0.02456591
> rowSums(tmp)
[1] 2.456591
> rowVars(tmp)
[1] 0.859734
> rowSd(tmp)
[1] 0.9272184
> rowMax(tmp)
[1] 2.264464
> rowMin(tmp)
[1] -1.881385
>
> colMeans(tmp)
[1] -0.075201513 0.351844534 0.227190364 -1.345323208 -0.453048810
[6] -1.785612866 -1.528092439 0.250082851 1.733443506 -0.300049195
[11] 0.236142617 -0.138915792 0.410389200 0.167816671 -0.995463657
[16] 0.487766401 -0.673014384 -0.451865553 -0.885307748 -0.188956941
[21] -1.126947542 0.963028728 -0.723277750 1.407478362 -1.881385434
[26] 0.233131637 -0.208615235 -0.354444931 -0.060095991 0.332906408
[31] 1.935867332 1.041888116 -1.874423003 -0.606762846 0.728853261
[36] -0.247788221 -0.726599079 0.840125028 -0.919732823 0.805888006
[41] -0.066678153 -0.073020462 1.789116652 0.127044786 -0.519443044
[46] 0.419049628 -0.908130064 -0.167345582 -0.362707336 -0.860642119
[51] -0.072735649 -0.676181344 -0.321827467 1.264849570 1.417802039
[56] -0.397923848 -0.524015532 -0.028826051 0.963889660 0.447536603
[61] 0.059103940 0.419208093 -1.588796726 -1.318453366 0.661537714
[66] -0.305153327 0.536449272 -1.352796736 1.969713332 2.264464018
[71] 0.110235853 -0.437520969 1.776759060 0.990884134 -0.420325471
[76] 1.225612081 0.088784619 -0.479005528 0.887944326 -0.638443736
[81] 0.250180128 0.350654129 1.872186084 -0.346792689 0.189464420
[86] 1.606761619 -0.746300405 -0.001040394 2.160234162 -0.353536066
[91] 0.294786697 -1.442987712 0.502225682 -0.164835437 -0.154546582
[96] -0.975351921 -0.397322379 0.328698605 -0.631110024 -0.387708332
> colSums(tmp)
[1] -0.075201513 0.351844534 0.227190364 -1.345323208 -0.453048810
[6] -1.785612866 -1.528092439 0.250082851 1.733443506 -0.300049195
[11] 0.236142617 -0.138915792 0.410389200 0.167816671 -0.995463657
[16] 0.487766401 -0.673014384 -0.451865553 -0.885307748 -0.188956941
[21] -1.126947542 0.963028728 -0.723277750 1.407478362 -1.881385434
[26] 0.233131637 -0.208615235 -0.354444931 -0.060095991 0.332906408
[31] 1.935867332 1.041888116 -1.874423003 -0.606762846 0.728853261
[36] -0.247788221 -0.726599079 0.840125028 -0.919732823 0.805888006
[41] -0.066678153 -0.073020462 1.789116652 0.127044786 -0.519443044
[46] 0.419049628 -0.908130064 -0.167345582 -0.362707336 -0.860642119
[51] -0.072735649 -0.676181344 -0.321827467 1.264849570 1.417802039
[56] -0.397923848 -0.524015532 -0.028826051 0.963889660 0.447536603
[61] 0.059103940 0.419208093 -1.588796726 -1.318453366 0.661537714
[66] -0.305153327 0.536449272 -1.352796736 1.969713332 2.264464018
[71] 0.110235853 -0.437520969 1.776759060 0.990884134 -0.420325471
[76] 1.225612081 0.088784619 -0.479005528 0.887944326 -0.638443736
[81] 0.250180128 0.350654129 1.872186084 -0.346792689 0.189464420
[86] 1.606761619 -0.746300405 -0.001040394 2.160234162 -0.353536066
[91] 0.294786697 -1.442987712 0.502225682 -0.164835437 -0.154546582
[96] -0.975351921 -0.397322379 0.328698605 -0.631110024 -0.387708332
> 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] -0.075201513 0.351844534 0.227190364 -1.345323208 -0.453048810
[6] -1.785612866 -1.528092439 0.250082851 1.733443506 -0.300049195
[11] 0.236142617 -0.138915792 0.410389200 0.167816671 -0.995463657
[16] 0.487766401 -0.673014384 -0.451865553 -0.885307748 -0.188956941
[21] -1.126947542 0.963028728 -0.723277750 1.407478362 -1.881385434
[26] 0.233131637 -0.208615235 -0.354444931 -0.060095991 0.332906408
[31] 1.935867332 1.041888116 -1.874423003 -0.606762846 0.728853261
[36] -0.247788221 -0.726599079 0.840125028 -0.919732823 0.805888006
[41] -0.066678153 -0.073020462 1.789116652 0.127044786 -0.519443044
[46] 0.419049628 -0.908130064 -0.167345582 -0.362707336 -0.860642119
[51] -0.072735649 -0.676181344 -0.321827467 1.264849570 1.417802039
[56] -0.397923848 -0.524015532 -0.028826051 0.963889660 0.447536603
[61] 0.059103940 0.419208093 -1.588796726 -1.318453366 0.661537714
[66] -0.305153327 0.536449272 -1.352796736 1.969713332 2.264464018
[71] 0.110235853 -0.437520969 1.776759060 0.990884134 -0.420325471
[76] 1.225612081 0.088784619 -0.479005528 0.887944326 -0.638443736
[81] 0.250180128 0.350654129 1.872186084 -0.346792689 0.189464420
[86] 1.606761619 -0.746300405 -0.001040394 2.160234162 -0.353536066
[91] 0.294786697 -1.442987712 0.502225682 -0.164835437 -0.154546582
[96] -0.975351921 -0.397322379 0.328698605 -0.631110024 -0.387708332
> colMin(tmp)
[1] -0.075201513 0.351844534 0.227190364 -1.345323208 -0.453048810
[6] -1.785612866 -1.528092439 0.250082851 1.733443506 -0.300049195
[11] 0.236142617 -0.138915792 0.410389200 0.167816671 -0.995463657
[16] 0.487766401 -0.673014384 -0.451865553 -0.885307748 -0.188956941
[21] -1.126947542 0.963028728 -0.723277750 1.407478362 -1.881385434
[26] 0.233131637 -0.208615235 -0.354444931 -0.060095991 0.332906408
[31] 1.935867332 1.041888116 -1.874423003 -0.606762846 0.728853261
[36] -0.247788221 -0.726599079 0.840125028 -0.919732823 0.805888006
[41] -0.066678153 -0.073020462 1.789116652 0.127044786 -0.519443044
[46] 0.419049628 -0.908130064 -0.167345582 -0.362707336 -0.860642119
[51] -0.072735649 -0.676181344 -0.321827467 1.264849570 1.417802039
[56] -0.397923848 -0.524015532 -0.028826051 0.963889660 0.447536603
[61] 0.059103940 0.419208093 -1.588796726 -1.318453366 0.661537714
[66] -0.305153327 0.536449272 -1.352796736 1.969713332 2.264464018
[71] 0.110235853 -0.437520969 1.776759060 0.990884134 -0.420325471
[76] 1.225612081 0.088784619 -0.479005528 0.887944326 -0.638443736
[81] 0.250180128 0.350654129 1.872186084 -0.346792689 0.189464420
[86] 1.606761619 -0.746300405 -0.001040394 2.160234162 -0.353536066
[91] 0.294786697 -1.442987712 0.502225682 -0.164835437 -0.154546582
[96] -0.975351921 -0.397322379 0.328698605 -0.631110024 -0.387708332
> colMedians(tmp)
[1] -0.075201513 0.351844534 0.227190364 -1.345323208 -0.453048810
[6] -1.785612866 -1.528092439 0.250082851 1.733443506 -0.300049195
[11] 0.236142617 -0.138915792 0.410389200 0.167816671 -0.995463657
[16] 0.487766401 -0.673014384 -0.451865553 -0.885307748 -0.188956941
[21] -1.126947542 0.963028728 -0.723277750 1.407478362 -1.881385434
[26] 0.233131637 -0.208615235 -0.354444931 -0.060095991 0.332906408
[31] 1.935867332 1.041888116 -1.874423003 -0.606762846 0.728853261
[36] -0.247788221 -0.726599079 0.840125028 -0.919732823 0.805888006
[41] -0.066678153 -0.073020462 1.789116652 0.127044786 -0.519443044
[46] 0.419049628 -0.908130064 -0.167345582 -0.362707336 -0.860642119
[51] -0.072735649 -0.676181344 -0.321827467 1.264849570 1.417802039
[56] -0.397923848 -0.524015532 -0.028826051 0.963889660 0.447536603
[61] 0.059103940 0.419208093 -1.588796726 -1.318453366 0.661537714
[66] -0.305153327 0.536449272 -1.352796736 1.969713332 2.264464018
[71] 0.110235853 -0.437520969 1.776759060 0.990884134 -0.420325471
[76] 1.225612081 0.088784619 -0.479005528 0.887944326 -0.638443736
[81] 0.250180128 0.350654129 1.872186084 -0.346792689 0.189464420
[86] 1.606761619 -0.746300405 -0.001040394 2.160234162 -0.353536066
[91] 0.294786697 -1.442987712 0.502225682 -0.164835437 -0.154546582
[96] -0.975351921 -0.397322379 0.328698605 -0.631110024 -0.387708332
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.07520151 0.3518445 0.2271904 -1.345323 -0.4530488 -1.785613 -1.528092
[2,] -0.07520151 0.3518445 0.2271904 -1.345323 -0.4530488 -1.785613 -1.528092
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.2500829 1.733444 -0.3000492 0.2361426 -0.1389158 0.4103892 0.1678167
[2,] 0.2500829 1.733444 -0.3000492 0.2361426 -0.1389158 0.4103892 0.1678167
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.9954637 0.4877664 -0.6730144 -0.4518656 -0.8853077 -0.1889569 -1.126948
[2,] -0.9954637 0.4877664 -0.6730144 -0.4518656 -0.8853077 -0.1889569 -1.126948
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.9630287 -0.7232778 1.407478 -1.881385 0.2331316 -0.2086152 -0.3544449
[2,] 0.9630287 -0.7232778 1.407478 -1.881385 0.2331316 -0.2086152 -0.3544449
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.06009599 0.3329064 1.935867 1.041888 -1.874423 -0.6067628 0.7288533
[2,] -0.06009599 0.3329064 1.935867 1.041888 -1.874423 -0.6067628 0.7288533
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.2477882 -0.7265991 0.840125 -0.9197328 0.805888 -0.06667815 -0.07302046
[2,] -0.2477882 -0.7265991 0.840125 -0.9197328 0.805888 -0.06667815 -0.07302046
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 1.789117 0.1270448 -0.519443 0.4190496 -0.9081301 -0.1673456 -0.3627073
[2,] 1.789117 0.1270448 -0.519443 0.4190496 -0.9081301 -0.1673456 -0.3627073
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.8606421 -0.07273565 -0.6761813 -0.3218275 1.26485 1.417802 -0.3979238
[2,] -0.8606421 -0.07273565 -0.6761813 -0.3218275 1.26485 1.417802 -0.3979238
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.5240155 -0.02882605 0.9638897 0.4475366 0.05910394 0.4192081 -1.588797
[2,] -0.5240155 -0.02882605 0.9638897 0.4475366 0.05910394 0.4192081 -1.588797
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.318453 0.6615377 -0.3051533 0.5364493 -1.352797 1.969713 2.264464
[2,] -1.318453 0.6615377 -0.3051533 0.5364493 -1.352797 1.969713 2.264464
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.1102359 -0.437521 1.776759 0.9908841 -0.4203255 1.225612 0.08878462
[2,] 0.1102359 -0.437521 1.776759 0.9908841 -0.4203255 1.225612 0.08878462
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.4790055 0.8879443 -0.6384437 0.2501801 0.3506541 1.872186 -0.3467927
[2,] -0.4790055 0.8879443 -0.6384437 0.2501801 0.3506541 1.872186 -0.3467927
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.1894644 1.606762 -0.7463004 -0.001040394 2.160234 -0.3535361 0.2947867
[2,] 0.1894644 1.606762 -0.7463004 -0.001040394 2.160234 -0.3535361 0.2947867
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.442988 0.5022257 -0.1648354 -0.1545466 -0.9753519 -0.3973224 0.3286986
[2,] -1.442988 0.5022257 -0.1648354 -0.1545466 -0.9753519 -0.3973224 0.3286986
[,99] [,100]
[1,] -0.63111 -0.3877083
[2,] -0.63111 -0.3877083
>
>
> Max(tmp2)
[1] 3.173574
> Min(tmp2)
[1] -2.210899
> mean(tmp2)
[1] 0.08642923
> Sum(tmp2)
[1] 8.642923
> Var(tmp2)
[1] 1.361193
>
> rowMeans(tmp2)
[1] -1.508552324 0.238554326 0.598041272 -1.320520661 0.171588723
[6] -0.513911945 0.293054622 -0.594950266 -1.183891554 0.445361529
[11] 0.231727751 -0.074679968 1.733618829 0.711464528 -0.964752864
[16] 1.430417186 0.350467878 -0.006057638 2.266351804 -1.405582228
[21] 3.007474621 -0.785028620 -1.157354408 -0.066338499 -1.596310689
[26] 0.765550593 1.982436359 1.177249209 1.810678014 -0.014339259
[31] 0.489577386 -0.046311560 -0.733915552 1.461606137 -1.228658688
[36] -0.044992024 0.581695749 -1.589005857 -0.939514006 1.923509025
[41] -0.589574296 0.355433089 -0.663680413 -0.227196251 -1.315023469
[46] -0.884501905 0.194622827 -0.202572766 -0.772536764 -0.311336361
[51] 0.640229260 0.908780288 0.179869933 2.064566255 -1.677974450
[56] 2.612321464 0.496970286 -0.001118924 -0.252501582 0.016959080
[61] 0.098741461 -1.225387050 -0.394401622 -1.038831655 -0.067626276
[66] -1.014120548 2.490387509 -0.803996815 0.185776802 3.173574427
[71] 1.205054387 0.382831049 0.995054678 -1.649357359 -0.019288777
[76] 0.264443828 -0.833164609 -2.210898714 -0.226862865 0.054008554
[81] 1.186960404 -0.733174515 0.105909037 0.797762107 -0.477623108
[86] 2.692052245 -1.266366048 0.741841367 -1.812320011 0.417021420
[91] -0.682357138 -0.304262482 0.694698684 2.255683281 -0.981852410
[96] 0.096975650 1.148852806 -0.269786430 -1.878130919 1.077610783
> rowSums(tmp2)
[1] -1.508552324 0.238554326 0.598041272 -1.320520661 0.171588723
[6] -0.513911945 0.293054622 -0.594950266 -1.183891554 0.445361529
[11] 0.231727751 -0.074679968 1.733618829 0.711464528 -0.964752864
[16] 1.430417186 0.350467878 -0.006057638 2.266351804 -1.405582228
[21] 3.007474621 -0.785028620 -1.157354408 -0.066338499 -1.596310689
[26] 0.765550593 1.982436359 1.177249209 1.810678014 -0.014339259
[31] 0.489577386 -0.046311560 -0.733915552 1.461606137 -1.228658688
[36] -0.044992024 0.581695749 -1.589005857 -0.939514006 1.923509025
[41] -0.589574296 0.355433089 -0.663680413 -0.227196251 -1.315023469
[46] -0.884501905 0.194622827 -0.202572766 -0.772536764 -0.311336361
[51] 0.640229260 0.908780288 0.179869933 2.064566255 -1.677974450
[56] 2.612321464 0.496970286 -0.001118924 -0.252501582 0.016959080
[61] 0.098741461 -1.225387050 -0.394401622 -1.038831655 -0.067626276
[66] -1.014120548 2.490387509 -0.803996815 0.185776802 3.173574427
[71] 1.205054387 0.382831049 0.995054678 -1.649357359 -0.019288777
[76] 0.264443828 -0.833164609 -2.210898714 -0.226862865 0.054008554
[81] 1.186960404 -0.733174515 0.105909037 0.797762107 -0.477623108
[86] 2.692052245 -1.266366048 0.741841367 -1.812320011 0.417021420
[91] -0.682357138 -0.304262482 0.694698684 2.255683281 -0.981852410
[96] 0.096975650 1.148852806 -0.269786430 -1.878130919 1.077610783
> 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] -1.508552324 0.238554326 0.598041272 -1.320520661 0.171588723
[6] -0.513911945 0.293054622 -0.594950266 -1.183891554 0.445361529
[11] 0.231727751 -0.074679968 1.733618829 0.711464528 -0.964752864
[16] 1.430417186 0.350467878 -0.006057638 2.266351804 -1.405582228
[21] 3.007474621 -0.785028620 -1.157354408 -0.066338499 -1.596310689
[26] 0.765550593 1.982436359 1.177249209 1.810678014 -0.014339259
[31] 0.489577386 -0.046311560 -0.733915552 1.461606137 -1.228658688
[36] -0.044992024 0.581695749 -1.589005857 -0.939514006 1.923509025
[41] -0.589574296 0.355433089 -0.663680413 -0.227196251 -1.315023469
[46] -0.884501905 0.194622827 -0.202572766 -0.772536764 -0.311336361
[51] 0.640229260 0.908780288 0.179869933 2.064566255 -1.677974450
[56] 2.612321464 0.496970286 -0.001118924 -0.252501582 0.016959080
[61] 0.098741461 -1.225387050 -0.394401622 -1.038831655 -0.067626276
[66] -1.014120548 2.490387509 -0.803996815 0.185776802 3.173574427
[71] 1.205054387 0.382831049 0.995054678 -1.649357359 -0.019288777
[76] 0.264443828 -0.833164609 -2.210898714 -0.226862865 0.054008554
[81] 1.186960404 -0.733174515 0.105909037 0.797762107 -0.477623108
[86] 2.692052245 -1.266366048 0.741841367 -1.812320011 0.417021420
[91] -0.682357138 -0.304262482 0.694698684 2.255683281 -0.981852410
[96] 0.096975650 1.148852806 -0.269786430 -1.878130919 1.077610783
> rowMin(tmp2)
[1] -1.508552324 0.238554326 0.598041272 -1.320520661 0.171588723
[6] -0.513911945 0.293054622 -0.594950266 -1.183891554 0.445361529
[11] 0.231727751 -0.074679968 1.733618829 0.711464528 -0.964752864
[16] 1.430417186 0.350467878 -0.006057638 2.266351804 -1.405582228
[21] 3.007474621 -0.785028620 -1.157354408 -0.066338499 -1.596310689
[26] 0.765550593 1.982436359 1.177249209 1.810678014 -0.014339259
[31] 0.489577386 -0.046311560 -0.733915552 1.461606137 -1.228658688
[36] -0.044992024 0.581695749 -1.589005857 -0.939514006 1.923509025
[41] -0.589574296 0.355433089 -0.663680413 -0.227196251 -1.315023469
[46] -0.884501905 0.194622827 -0.202572766 -0.772536764 -0.311336361
[51] 0.640229260 0.908780288 0.179869933 2.064566255 -1.677974450
[56] 2.612321464 0.496970286 -0.001118924 -0.252501582 0.016959080
[61] 0.098741461 -1.225387050 -0.394401622 -1.038831655 -0.067626276
[66] -1.014120548 2.490387509 -0.803996815 0.185776802 3.173574427
[71] 1.205054387 0.382831049 0.995054678 -1.649357359 -0.019288777
[76] 0.264443828 -0.833164609 -2.210898714 -0.226862865 0.054008554
[81] 1.186960404 -0.733174515 0.105909037 0.797762107 -0.477623108
[86] 2.692052245 -1.266366048 0.741841367 -1.812320011 0.417021420
[91] -0.682357138 -0.304262482 0.694698684 2.255683281 -0.981852410
[96] 0.096975650 1.148852806 -0.269786430 -1.878130919 1.077610783
>
> colMeans(tmp2)
[1] 0.08642923
> colSums(tmp2)
[1] 8.642923
> colVars(tmp2)
[1] 1.361193
> colSd(tmp2)
[1] 1.166702
> colMax(tmp2)
[1] 3.173574
> colMin(tmp2)
[1] -2.210899
> colMedians(tmp2)
[1] -0.003588281
> colRanges(tmp2)
[,1]
[1,] -2.210899
[2,] 3.173574
>
> 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] -1.898061 2.349519 -1.065713 4.170507 0.560952 3.630344 -2.244060
[8] 6.850596 -6.097350 -1.723104
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1281028
[2,] -0.5691787
[3,] -0.2981309
[4,] 0.1550791
[5,] 1.0815201
>
> rowApply(tmp,sum)
[1] 1.59099749 -1.36175114 7.42135752 7.38693485 -4.88200563 -0.04771456
[7] -3.12505151 -1.17421390 0.85896225 -2.13388500
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 5 3 2 7 10 5 5 2 7
[2,] 10 3 5 3 10 7 3 9 7 4
[3,] 4 1 1 9 4 6 4 1 10 10
[4,] 6 7 9 10 8 3 9 3 8 9
[5,] 8 4 8 7 1 5 7 8 3 8
[6,] 5 8 10 6 3 8 8 7 5 1
[7,] 7 2 7 8 6 2 2 4 1 6
[8,] 9 10 2 5 9 9 10 6 6 5
[9,] 2 6 4 1 2 4 1 10 9 3
[10,] 3 9 6 4 5 1 6 2 4 2
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.6806383 -2.0756964 3.4219039 -0.9266221 -3.0861778 1.9828898
[7] 2.7525603 -1.8922382 2.4629628 -0.7143359 -1.8340417 5.0636325
[13] -2.2069592 3.0002970 0.2579734 0.2636729 -0.7723690 -1.0061892
[19] -2.5631995 -4.1240042
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.9660392
[2,] -0.6997286
[3,] -0.6278399
[4,] -0.3361099
[5,] 0.9490794
>
> rowApply(tmp,sum)
[1] 3.272298 2.957088 -0.800432 -4.869628 -4.235905
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 15 6 7 9 5
[2,] 3 9 11 3 14
[3,] 5 19 20 1 17
[4,] 14 7 5 7 20
[5,] 13 2 3 12 9
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.9490794 -0.904142260 -0.263551 0.4237843 0.4134563 0.9920422
[2,] -0.6997286 -0.328920293 2.007232 -0.5844450 -1.3056969 1.5945018
[3,] -0.6278399 0.007772614 2.590386 -1.1732937 -1.3910376 1.1373486
[4,] -0.3361099 -1.296421680 -1.627553 -0.9927607 -0.2713921 -1.3993826
[5,] -0.9660392 0.446015224 0.715390 1.4000929 -0.5315075 -0.3416202
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.2120899 -0.06852899 -0.1889103 0.30717888 0.1113350 1.1382444
[2,] -0.8776791 -1.17379954 1.2328931 -0.05516639 -0.1706130 1.7362257
[3,] 1.4949969 0.46756770 -0.3815187 0.69123607 0.1946813 1.9983663
[4,] -0.3143584 0.22468675 0.7294457 0.29001083 -1.2749731 0.6567531
[5,] 1.2375111 -1.34216415 1.0710531 -1.94759526 -0.6944718 -0.4659569
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.1530950 -0.6129700 0.2943678 -0.07954226 -1.5074303 1.23206225
[2,] 1.0571965 2.0767921 -0.3669969 0.52461979 -0.8380863 0.07525803
[3,] -1.5597948 0.2371565 0.1542741 -1.00452496 -0.1389017 -1.61424252
[4,] -1.2517075 0.8277312 -0.2719863 0.94863890 1.4680769 0.52475154
[5,] -0.6057484 0.4715872 0.4483146 -0.12551860 0.2439724 -1.22401847
[,19] [,20]
[1,] 1.5355960 -1.8649586
[2,] -1.3319442 0.3854451
[3,] -0.4965719 -1.3864918
[4,] -1.0844336 -0.4186437
[5,] -1.1858458 -0.8393552
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.09215392 2.265263 -0.6581645 1.10232 -0.4172598 -0.8904022 0.6514685
col8 col9 col10 col11 col12 col13 col14
row1 -1.204765 0.4168155 -1.17195 0.2372958 -0.569435 0.4766135 2.256149
col15 col16 col17 col18 col19 col20
row1 0.8187527 0.3291678 -0.5193852 -0.2818955 1.476502 1.08949
> tmp[,"col10"]
col10
row1 -1.1719498
row2 -0.1957246
row3 -0.0901942
row4 -0.2534880
row5 0.1022335
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.09215392 2.2652635 -0.6581645 1.1023198 -0.4172598 -0.8904022
row5 2.01751814 -0.4142552 -1.9970335 -0.2751219 -0.2460524 0.7268884
col7 col8 col9 col10 col11 col12 col13
row1 0.6514685 -1.204765 0.4168155 -1.1719498 0.2372958 -0.5694350 0.4766135
row5 0.5963116 -2.307571 -0.5125481 0.1022335 3.4954002 0.0601832 1.3208932
col14 col15 col16 col17 col18 col19 col20
row1 2.2561488 0.8187527 0.3291678 -0.5193852 -0.2818955 1.4765016 1.089490
row5 -0.2671816 -0.5119944 1.3114921 0.8218013 -1.9965788 0.1844601 2.435319
> tmp[,c("col6","col20")]
col6 col20
row1 -0.8904022 1.0894897
row2 0.2744832 -1.9036564
row3 -0.7465927 -0.8656954
row4 -1.8524173 -0.6986836
row5 0.7268884 2.4353187
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.8904022 1.089490
row5 0.7268884 2.435319
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.38343 51.84024 50.33029 49.36218 50.00034 106.2076 50.67315 51.84611
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.03824 50.14594 50.48312 51.58745 48.3871 49.82089 49.17015 48.8656
col17 col18 col19 col20
row1 48.83679 50.87541 51.59836 104.8445
> tmp[,"col10"]
col10
row1 50.14594
row2 30.40720
row3 29.00014
row4 28.69742
row5 49.28283
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.38343 51.84024 50.33029 49.36218 50.00034 106.2076 50.67315 51.84611
row5 50.24289 50.33423 50.43624 48.89890 50.83826 106.5681 47.71476 48.75919
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.03824 50.14594 50.48312 51.58745 48.38710 49.82089 49.17015 48.86560
row5 48.93133 49.28283 49.36445 48.37125 50.41414 49.83795 49.90670 51.26855
col17 col18 col19 col20
row1 48.83679 50.87541 51.59836 104.8445
row5 50.06973 50.27939 50.42354 104.3880
> tmp[,c("col6","col20")]
col6 col20
row1 106.20761 104.84450
row2 74.61745 74.19713
row3 75.19553 74.21499
row4 76.33402 75.00223
row5 106.56812 104.38804
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.2076 104.8445
row5 106.5681 104.3880
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.2076 104.8445
row5 106.5681 104.3880
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.3033564
[2,] -0.5417945
[3,] -1.3347916
[4,] 1.6831301
[5,] 0.4317621
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.6568848 -1.2790016
[2,] -1.1075159 0.8741388
[3,] -3.1462560 0.1641246
[4,] -1.0201710 0.1321023
[5,] 0.1173135 0.7583249
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.21911041 0.075548917
[2,] -0.64376594 -0.164004146
[3,] 1.16809604 0.424383269
[4,] -0.62157964 0.837018477
[5,] 0.05041427 0.004577197
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.2191104
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.2191104
[2,] -0.6437659
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 -0.8143601 -1.2122068 -0.4837918 -1.0791444 -1.0055284 1.1442230
row1 0.2985648 -0.7140792 0.1383272 -0.8634585 0.3512434 0.8803734
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.2473921 0.6589100 2.7131037 0.4208615 0.07157025 0.2388681
row1 -0.3242747 -0.2246178 0.6725674 -1.3268870 0.17066181 -0.8014623
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 -1.5638048 0.4461177 0.5185249 1.0475880 1.506075 -1.0028067 0.2155183
row1 0.2408237 0.3711633 0.5704376 -0.1971436 -1.361038 0.8527398 -0.7042435
[,20]
row3 -0.4013222
row1 0.4668749
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.501615 0.1255166 1.77765 -1.095048 -1.569881 2.057456 -0.7876875
[,8] [,9] [,10]
row2 -3.24301 0.5270802 0.2468365
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.7033051 -0.3663884 -0.007608755 1.420168 2.110551 1.233077 0.7196517
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.4096069 -1.085271 0.530661 1.921481 -0.5665719 1.103388 -1.46153
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.5854402 -1.263619 0.310312 0.6541336 0.4832333 -0.7827405
>
>
> 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: 0x424f3090>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM22af207873f882"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM22af204a3a38f5"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM22af20175f2cd0"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM22af2072dc06f8"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM22af2014e86f38"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM22af2066386fe2"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM22af20680b05bc"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM22af203ccde0f0"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM22af202f19fe29"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM22af2035b92646"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM22af20738b05bf"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM22af20897a99c"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM22af203a9ffc14"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM22af208bde4e"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM22af207651dc8"
>
>
> ### 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: 0x4115f400>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x4115f400>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x4115f400>
> rowMedians(tmp)
[1] 0.284803443 -0.129429896 -0.239382691 -0.164503379 -0.709633065
[6] 0.386275999 0.356318009 -0.151656640 0.609269801 -0.475107038
[11] -0.011084365 -0.361251858 0.229261837 0.234310926 -0.162141478
[16] 0.035945839 0.143074235 -0.415928964 0.274537494 -0.292956220
[21] -0.352230955 0.059798784 -0.572565297 0.010531051 0.736129956
[26] 0.123971232 -0.248655020 -0.155720262 -0.076427172 -0.115297371
[31] -0.018062528 0.163973537 0.396525639 0.132660432 -0.079717701
[36] -0.319951178 0.546373333 0.450362553 0.243626391 -0.112994737
[41] -0.343776029 0.078592149 0.186294674 0.137043408 0.395298116
[46] -0.493199987 0.262488527 -0.211397867 0.473780238 -0.015129606
[51] 0.010129359 0.382071028 -0.059845815 -0.158287422 -0.073922993
[56] -0.038466122 0.215629613 -0.651104051 -0.135672685 0.134498612
[61] -0.510784340 -0.100396491 0.018216071 -0.053444577 -0.294984375
[66] -0.537767529 0.310712709 0.291880785 0.205545021 0.436952388
[71] 0.519043028 0.092539911 -0.525744155 0.465392165 0.323373571
[76] 0.337741630 -0.018013385 0.038005913 0.155037523 -0.237217707
[81] 0.065114228 0.281714066 0.305495302 -0.207366719 0.283130440
[86] -0.424191068 -0.007601249 0.063119244 -0.529831928 0.085364847
[91] -0.096437234 0.088916817 -0.046042835 0.036363158 -0.604656627
[96] -0.132716779 0.184207488 -0.358539534 0.734958203 0.261767524
[101] -0.404164679 -0.601989726 -0.295466391 0.018849122 0.630139658
[106] -0.251662551 0.132667747 -0.185877413 -0.062964203 -0.005033212
[111] -0.200440903 0.126426524 -0.262827314 0.015665240 0.143680576
[116] 0.128833997 -0.158404379 -0.073511578 0.064852844 0.289613103
[121] -0.246763229 -0.066864031 0.099045960 -0.242643529 0.250037168
[126] -0.294068410 0.039514882 -0.121316317 0.003185366 0.481106617
[131] 0.215827300 -0.125971842 -0.346001077 0.446870712 0.186253890
[136] 0.153036584 0.222342358 -0.327253995 -0.164924873 -0.132859705
[141] -0.083643948 0.116527125 -0.097936038 -0.285195063 -0.156984952
[146] -0.184867387 0.105305353 0.620618610 -0.053312525 0.502561453
[151] 0.244249383 -0.219960885 0.130407510 0.092932718 0.084921903
[156] 0.125586014 -0.964469666 0.128144962 0.190869561 0.064757185
[161] -0.334319080 0.125154724 -0.038160069 0.172720753 1.035805128
[166] -0.037072504 0.057588667 -0.517049280 -0.108241693 0.360089500
[171] 0.290241624 0.083524345 0.324937385 -0.286265435 0.223996829
[176] 0.165546379 0.053383778 -0.064454319 -0.052400857 -0.037675748
[181] 0.132204501 -0.527637959 0.170771443 0.270850682 -0.024482152
[186] 0.125901161 0.229101919 0.305188461 0.516714465 -0.211577004
[191] 0.486011254 -0.516309481 -0.268618143 0.098768432 -0.051614693
[196] -0.356139897 0.525907419 -0.012080748 0.161953699 0.468023988
[201] -0.124060825 0.145122069 0.067859651 0.450284542 -0.089308404
[206] 0.102313609 -0.152464708 -0.060228463 0.453247695 0.145872813
[211] 0.363700964 -0.163895455 -0.550370822 0.089831163 -0.317223509
[216] 0.598332371 0.037895204 0.138376020 -0.170911987 0.084335142
[221] -0.425639723 -0.174718781 -0.453133180 0.007877211 0.167094007
[226] -0.151500885 0.175098193 0.267224685 0.077332117 0.110903364
>
> proc.time()
user system elapsed
1.933 0.927 2.885
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: 0x20f16ff0>
> .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: 0x20f16ff0>
> .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: 0x20f16ff0>
> .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: 0x20f16ff0>
> 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: 0x20e21470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x20e21470>
> .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: 0x20e21470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x20e21470>
> .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: 0x20e21470>
> 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: 0x20dfc0e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x20dfc0e0>
> .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: 0x20dfc0e0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x20dfc0e0>
> .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: 0x20dfc0e0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x20dfc0e0>
> .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: 0x20dfc0e0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x20dfc0e0>
> .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: 0x20dfc0e0>
> 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: 0x1fd83520>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x1fd83520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1fd83520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1fd83520>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile22b0772a5b5ea1" "BufferedMatrixFile22b0773447a54b"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile22b0772a5b5ea1" "BufferedMatrixFile22b0773447a54b"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x21ccc030>
> .Call("R_bm_AddColumn",P)
<pointer: 0x21ccc030>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x21ccc030>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x21ccc030>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x21ccc030>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x21ccc030>
> .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: 0x206975c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x206975c0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x206975c0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x206975c0>
> 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: 0x21777f30>
> .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: 0x21777f30>
> rm(P)
>
> proc.time()
user system elapsed
0.332 0.043 0.361
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.
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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
0.345 0.037 0.369