Ben Bolstad
| Snapshot Date: 2025-08-07 13:40 -0400 (Thu, 07 Aug 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_21 |
| git_last_commit: aa9e634 |
| git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-08-11 11:47 -0400 (Mon, 11 Aug 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.2 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4823 |
| palomino7 | Windows Server 2022 Datacenter | x64 | 4.5.1 (2025-06-13 ucrt) -- "Great Square Root" | 4565 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root" | 4603 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4544 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4579 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 252/2341 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.72.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.2 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| kunpeng2 | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. - See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host. |
| Package: BufferedMatrix |
| Version: 1.72.0 |
| 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_1.72.0.tar.gz |
| StartedAt: 2025-08-08 06:51:18 -0000 (Fri, 08 Aug 2025) |
| EndedAt: 2025-08-08 06:51:41 -0000 (Fri, 08 Aug 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_1.72.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2025-02-19 r87757)
* 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-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.72.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘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-3.21-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
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###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/R/R-devel_2025-02-19/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.72.0’
** 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/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/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/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/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/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/R/R/lib -lR
installing to /home/biocbuild/R/R-devel_2025-02-19/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
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
0.335 0.040 0.362
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
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-3.21-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 477833 25.6 1045337 55.9 639800 34.2
Vcells 884297 6.8 8388608 64.0 2080696 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 Aug 8 06:51:35 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 Aug 8 06:51:35 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: 0x1c6216e0>
>
>
>
> 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 Aug 8 06:51:35 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 Aug 8 06:51:36 2025"
>
> ColMode(tmp2)
<pointer: 0x1c6216e0>
>
>
>
> ### 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,] 100.1896908 3.0538752 0.4687137 -2.0958012
[2,] -0.1334347 0.1243505 0.7110710 0.5853084
[3,] -0.3143995 0.4546027 0.1125105 0.1801865
[4,] -0.3123297 1.6072337 -1.5761552 -0.4827834
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.1896908 3.0538752 0.4687137 2.0958012
[2,] 0.1334347 0.1243505 0.7110710 0.5853084
[3,] 0.3143995 0.4546027 0.1125105 0.1801865
[4,] 0.3123297 1.6072337 1.5761552 0.4827834
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0094800 1.7475340 0.6846267 1.4476882
[2,] 0.3652872 0.3526337 0.8432503 0.7650545
[3,] 0.5607134 0.6742423 0.3354258 0.4244838
[4,] 0.5588647 1.2677672 1.2554502 0.6948262
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.28449 45.52922 32.31498 41.57268
[2,] 28.78631 28.65069 34.14357 33.23585
[3,] 30.92153 32.19703 28.46677 29.42502
[4,] 30.90098 39.28491 39.13066 32.43104
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x1abf9520>
> exp(tmp5)
<pointer: 0x1abf9520>
> log(tmp5,2)
<pointer: 0x1abf9520>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.9002
> Min(tmp5)
[1] 53.2765
> mean(tmp5)
[1] 73.1719
> Sum(tmp5)
[1] 14634.38
> Var(tmp5)
[1] 873.6837
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 93.14931 68.14043 71.49008 74.02829 69.14578 68.59531 73.39713 72.63336
[9] 70.25408 70.88524
> rowSums(tmp5)
[1] 1862.986 1362.809 1429.802 1480.566 1382.916 1371.906 1467.943 1452.667
[9] 1405.082 1417.705
> rowVars(tmp5)
[1] 7948.04847 69.76775 85.53731 59.86800 61.86016 106.53868
[7] 70.10485 63.75428 104.42345 76.34981
> rowSd(tmp5)
[1] 89.151828 8.352709 9.248639 7.737442 7.865123 10.321758 8.372864
[8] 7.984628 10.218779 8.737838
> rowMax(tmp5)
[1] 468.90015 86.24933 87.77182 86.13904 89.19224 88.92299 89.49916
[8] 87.71698 92.96611 86.03247
> rowMin(tmp5)
[1] 58.14974 55.42118 57.99997 59.99251 58.90157 54.26706 57.19994 58.04838
[9] 54.86556 53.27650
>
> colMeans(tmp5)
[1] 110.98704 71.51234 69.38272 69.17170 75.01836 65.14607 73.25411
[8] 73.99340 71.53037 71.28621 70.28192 69.31616 71.76443 69.31120
[15] 69.77893 71.29794 75.32015 70.10101 71.16745 73.81652
> colSums(tmp5)
[1] 1109.8704 715.1234 693.8272 691.7170 750.1836 651.4607 732.5411
[8] 739.9340 715.3037 712.8621 702.8192 693.1616 717.6443 693.1120
[15] 697.7893 712.9794 753.2015 701.0101 711.6745 738.1652
> colVars(tmp5)
[1] 15909.94885 209.21062 41.52688 103.42632 62.42251 94.51232
[7] 70.55601 117.07265 54.46639 76.31596 90.04660 18.09205
[13] 87.31708 54.40087 77.60826 70.63536 124.79969 96.29197
[19] 87.23178 81.72250
> colSd(tmp5)
[1] 126.134646 14.464115 6.444136 10.169873 7.900792 9.721745
[7] 8.399762 10.820012 7.380135 8.735900 9.489289 4.253475
[13] 9.344361 7.375694 8.809555 8.404485 11.171378 9.812847
[19] 9.339795 9.040050
> colMax(tmp5)
[1] 468.90015 94.76310 81.44534 86.52809 86.24933 87.71698 87.36862
[8] 92.96611 84.03103 82.50486 82.56593 76.67744 86.03247 79.66736
[15] 84.93735 89.49916 96.59126 82.45736 86.13904 88.00886
> colMin(tmp5)
[1] 58.04838 56.63595 59.24985 53.27650 64.79554 55.42118 57.99997 61.72140
[9] 58.81842 59.49727 54.26706 61.66744 55.30882 57.13459 58.83744 58.79054
[17] 56.67599 54.86556 57.07067 60.41381
>
>
> ### 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] 93.14931 68.14043 71.49008 74.02829 69.14578 68.59531 73.39713 72.63336
[9] 70.25408 NA
> rowSums(tmp5)
[1] 1862.986 1362.809 1429.802 1480.566 1382.916 1371.906 1467.943 1452.667
[9] 1405.082 NA
> rowVars(tmp5)
[1] 7948.04847 69.76775 85.53731 59.86800 61.86016 106.53868
[7] 70.10485 63.75428 104.42345 78.65602
> rowSd(tmp5)
[1] 89.151828 8.352709 9.248639 7.737442 7.865123 10.321758 8.372864
[8] 7.984628 10.218779 8.868823
> rowMax(tmp5)
[1] 468.90015 86.24933 87.77182 86.13904 89.19224 88.92299 89.49916
[8] 87.71698 92.96611 NA
> rowMin(tmp5)
[1] 58.14974 55.42118 57.99997 59.99251 58.90157 54.26706 57.19994 58.04838
[9] 54.86556 NA
>
> colMeans(tmp5)
[1] 110.98704 71.51234 69.38272 69.17170 75.01836 65.14607 73.25411
[8] 73.99340 71.53037 71.28621 70.28192 69.31616 71.76443 69.31120
[15] 69.77893 71.29794 75.32015 NA 71.16745 73.81652
> colSums(tmp5)
[1] 1109.8704 715.1234 693.8272 691.7170 750.1836 651.4607 732.5411
[8] 739.9340 715.3037 712.8621 702.8192 693.1616 717.6443 693.1120
[15] 697.7893 712.9794 753.2015 NA 711.6745 738.1652
> colVars(tmp5)
[1] 15909.94885 209.21062 41.52688 103.42632 62.42251 94.51232
[7] 70.55601 117.07265 54.46639 76.31596 90.04660 18.09205
[13] 87.31708 54.40087 77.60826 70.63536 124.79969 NA
[19] 87.23178 81.72250
> colSd(tmp5)
[1] 126.134646 14.464115 6.444136 10.169873 7.900792 9.721745
[7] 8.399762 10.820012 7.380135 8.735900 9.489289 4.253475
[13] 9.344361 7.375694 8.809555 8.404485 11.171378 NA
[19] 9.339795 9.040050
> colMax(tmp5)
[1] 468.90015 94.76310 81.44534 86.52809 86.24933 87.71698 87.36862
[8] 92.96611 84.03103 82.50486 82.56593 76.67744 86.03247 79.66736
[15] 84.93735 89.49916 96.59126 NA 86.13904 88.00886
> colMin(tmp5)
[1] 58.04838 56.63595 59.24985 53.27650 64.79554 55.42118 57.99997 61.72140
[9] 58.81842 59.49727 54.26706 61.66744 55.30882 57.13459 58.83744 58.79054
[17] 56.67599 NA 57.07067 60.41381
>
> Max(tmp5,na.rm=TRUE)
[1] 468.9002
> Min(tmp5,na.rm=TRUE)
[1] 53.2765
> mean(tmp5,na.rm=TRUE)
[1] 73.15448
> Sum(tmp5,na.rm=TRUE)
[1] 14557.74
> Var(tmp5,na.rm=TRUE)
[1] 878.0353
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.14931 68.14043 71.49008 74.02829 69.14578 68.59531 73.39713 72.63336
[9] 70.25408 70.58246
> rowSums(tmp5,na.rm=TRUE)
[1] 1862.986 1362.809 1429.802 1480.566 1382.916 1371.906 1467.943 1452.667
[9] 1405.082 1341.067
> rowVars(tmp5,na.rm=TRUE)
[1] 7948.04847 69.76775 85.53731 59.86800 61.86016 106.53868
[7] 70.10485 63.75428 104.42345 78.65602
> rowSd(tmp5,na.rm=TRUE)
[1] 89.151828 8.352709 9.248639 7.737442 7.865123 10.321758 8.372864
[8] 7.984628 10.218779 8.868823
> rowMax(tmp5,na.rm=TRUE)
[1] 468.90015 86.24933 87.77182 86.13904 89.19224 88.92299 89.49916
[8] 87.71698 92.96611 86.03247
> rowMin(tmp5,na.rm=TRUE)
[1] 58.14974 55.42118 57.99997 59.99251 58.90157 54.26706 57.19994 58.04838
[9] 54.86556 53.27650
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.98704 71.51234 69.38272 69.17170 75.01836 65.14607 73.25411
[8] 73.99340 71.53037 71.28621 70.28192 69.31616 71.76443 69.31120
[15] 69.77893 71.29794 75.32015 69.37466 71.16745 73.81652
> colSums(tmp5,na.rm=TRUE)
[1] 1109.8704 715.1234 693.8272 691.7170 750.1836 651.4607 732.5411
[8] 739.9340 715.3037 712.8621 702.8192 693.1616 717.6443 693.1120
[15] 697.7893 712.9794 753.2015 624.3720 711.6745 738.1652
> colVars(tmp5,na.rm=TRUE)
[1] 15909.94885 209.21062 41.52688 103.42632 62.42251 94.51232
[7] 70.55601 117.07265 54.46639 76.31596 90.04660 18.09205
[13] 87.31708 54.40087 77.60826 70.63536 124.79969 102.39315
[19] 87.23178 81.72250
> colSd(tmp5,na.rm=TRUE)
[1] 126.134646 14.464115 6.444136 10.169873 7.900792 9.721745
[7] 8.399762 10.820012 7.380135 8.735900 9.489289 4.253475
[13] 9.344361 7.375694 8.809555 8.404485 11.171378 10.118950
[19] 9.339795 9.040050
> colMax(tmp5,na.rm=TRUE)
[1] 468.90015 94.76310 81.44534 86.52809 86.24933 87.71698 87.36862
[8] 92.96611 84.03103 82.50486 82.56593 76.67744 86.03247 79.66736
[15] 84.93735 89.49916 96.59126 82.45736 86.13904 88.00886
> colMin(tmp5,na.rm=TRUE)
[1] 58.04838 56.63595 59.24985 53.27650 64.79554 55.42118 57.99997 61.72140
[9] 58.81842 59.49727 54.26706 61.66744 55.30882 57.13459 58.83744 58.79054
[17] 56.67599 54.86556 57.07067 60.41381
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.14931 68.14043 71.49008 74.02829 69.14578 68.59531 73.39713 72.63336
[9] 70.25408 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1862.986 1362.809 1429.802 1480.566 1382.916 1371.906 1467.943 1452.667
[9] 1405.082 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 7948.04847 69.76775 85.53731 59.86800 61.86016 106.53868
[7] 70.10485 63.75428 104.42345 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 89.151828 8.352709 9.248639 7.737442 7.865123 10.321758 8.372864
[8] 7.984628 10.218779 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 468.90015 86.24933 87.77182 86.13904 89.19224 88.92299 89.49916
[8] 87.71698 92.96611 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 58.14974 55.42118 57.99997 59.99251 58.90157 54.26706 57.19994 58.04838
[9] 54.86556 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.15606 72.64943 69.23262 70.93784 73.91406 64.76517 73.73649
[8] 74.21901 70.99173 72.52978 69.98842 69.38467 70.17909 69.12687
[15] 68.09466 72.68765 75.54684 NaN 70.98734 75.01712
> colSums(tmp5,na.rm=TRUE)
[1] 1036.4046 653.8449 623.0936 638.4406 665.2265 582.8866 663.6284
[8] 667.9711 638.9256 652.7680 629.8958 624.4620 631.6118 622.1418
[15] 612.8520 654.1889 679.9216 0.0000 638.8860 675.1541
> colVars(tmp5,na.rm=TRUE)
[1] 17703.15924 220.81596 46.46429 81.26327 56.50613 104.69417
[7] 76.75775 131.13414 58.01070 68.45770 100.33331 20.30076
[13] 69.95711 60.81875 55.39573 57.73767 139.82153 NA
[19] 97.77077 75.72161
> colSd(tmp5,na.rm=TRUE)
[1] 133.053220 14.859877 6.816472 9.014615 7.517056 10.232017
[7] 8.761150 11.451382 7.616475 8.273917 10.016652 4.505636
[13] 8.364037 7.798638 7.442831 7.598531 11.824616 NA
[19] 9.887910 8.701816
> colMax(tmp5,na.rm=TRUE)
[1] 468.90015 94.76310 81.44534 86.52809 86.24933 87.71698 87.36862
[8] 92.96611 84.03103 82.50486 82.56593 76.67744 83.51594 79.66736
[15] 80.55213 89.49916 96.59126 -Inf 86.13904 88.00886
> colMin(tmp5,na.rm=TRUE)
[1] 58.04838 56.63595 59.24985 58.90157 64.79554 55.42118 57.99997 61.72140
[9] 58.81842 59.49727 54.26706 61.66744 55.30882 57.13459 58.83744 65.89902
[17] 56.67599 Inf 57.07067 60.41381
>
>
>
>
> 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] 250.9181 235.2103 208.9706 319.3807 257.4950 199.9234 139.0563 234.6415
[9] 101.8781 312.8749
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 250.9181 235.2103 208.9706 319.3807 257.4950 199.9234 139.0563 234.6415
[9] 101.8781 312.8749
>
>
>
> 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] -1.421085e-13 -1.136868e-13 1.421085e-14 0.000000e+00 -8.526513e-14
[6] 0.000000e+00 0.000000e+00 -8.526513e-14 -2.842171e-14 0.000000e+00
[11] -1.421085e-13 2.842171e-14 -2.842171e-14 -1.136868e-13 -5.684342e-14
[16] -2.842171e-14 0.000000e+00 -8.526513e-14 -5.684342e-14 5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## 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)
+ }
5 18
6 19
4 7
9 5
1 2
5 2
1 13
6 12
2 7
4 14
5 13
4 10
1 6
10 11
9 14
8 3
8 14
2 12
5 2
2 19
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] 2.383925
> Min(tmp)
[1] -1.96
> mean(tmp)
[1] -0.1452131
> Sum(tmp)
[1] -14.52131
> Var(tmp)
[1] 0.83152
>
> rowMeans(tmp)
[1] -0.1452131
> rowSums(tmp)
[1] -14.52131
> rowVars(tmp)
[1] 0.83152
> rowSd(tmp)
[1] 0.9118772
> rowMax(tmp)
[1] 2.383925
> rowMin(tmp)
[1] -1.96
>
> colMeans(tmp)
[1] 0.313168194 -0.137735438 0.136205270 0.056423399 -0.903814331
[6] -0.359331869 -0.319166312 0.783658404 -1.618403684 0.448494856
[11] 0.588200335 -1.839945245 -0.201214156 1.492587582 -0.387160737
[16] -0.038544160 0.133974132 -0.521401340 -1.183009430 -1.385641284
[21] 0.591380781 -0.357802988 -0.165904590 -1.690728499 0.369458376
[26] -1.547098658 0.009429096 -0.453070736 -0.600544947 -0.391649829
[31] -1.178052784 1.250692077 -0.790704278 -0.363047598 0.925965040
[36] -1.395412918 -0.902384477 1.508917397 0.831009789 -0.545114754
[41] 1.011186156 -0.822750219 -0.612431318 -0.213477978 -1.551000519
[46] 1.061633996 1.096161752 -1.221533021 -1.474885278 -1.349971228
[51] 0.130905130 -0.578564884 -0.113224467 -0.608827426 0.090453551
[56] -0.983817377 -0.467153065 -0.823810088 1.435325002 1.660788349
[61] -0.687309467 1.405872871 0.239185295 0.421465114 -0.820800827
[66] -0.950585681 -0.492843144 -1.228033390 -0.645237332 -1.684756634
[71] -0.351089575 0.971739791 0.001655480 1.264360697 0.247546168
[76] -1.226399129 0.071590253 -0.005703694 0.825923228 0.131466352
[81] 0.073081116 0.578780119 0.235095842 -0.254559882 -1.353438141
[86] 1.603838116 -0.239353749 -0.876997141 0.353893736 0.588542622
[91] 0.197162839 -1.164363858 0.552692799 -0.439193177 2.383925360
[96] 0.721838188 -0.016970451 0.778765608 0.400212533 -1.960000021
> colSums(tmp)
[1] 0.313168194 -0.137735438 0.136205270 0.056423399 -0.903814331
[6] -0.359331869 -0.319166312 0.783658404 -1.618403684 0.448494856
[11] 0.588200335 -1.839945245 -0.201214156 1.492587582 -0.387160737
[16] -0.038544160 0.133974132 -0.521401340 -1.183009430 -1.385641284
[21] 0.591380781 -0.357802988 -0.165904590 -1.690728499 0.369458376
[26] -1.547098658 0.009429096 -0.453070736 -0.600544947 -0.391649829
[31] -1.178052784 1.250692077 -0.790704278 -0.363047598 0.925965040
[36] -1.395412918 -0.902384477 1.508917397 0.831009789 -0.545114754
[41] 1.011186156 -0.822750219 -0.612431318 -0.213477978 -1.551000519
[46] 1.061633996 1.096161752 -1.221533021 -1.474885278 -1.349971228
[51] 0.130905130 -0.578564884 -0.113224467 -0.608827426 0.090453551
[56] -0.983817377 -0.467153065 -0.823810088 1.435325002 1.660788349
[61] -0.687309467 1.405872871 0.239185295 0.421465114 -0.820800827
[66] -0.950585681 -0.492843144 -1.228033390 -0.645237332 -1.684756634
[71] -0.351089575 0.971739791 0.001655480 1.264360697 0.247546168
[76] -1.226399129 0.071590253 -0.005703694 0.825923228 0.131466352
[81] 0.073081116 0.578780119 0.235095842 -0.254559882 -1.353438141
[86] 1.603838116 -0.239353749 -0.876997141 0.353893736 0.588542622
[91] 0.197162839 -1.164363858 0.552692799 -0.439193177 2.383925360
[96] 0.721838188 -0.016970451 0.778765608 0.400212533 -1.960000021
> 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] 0.313168194 -0.137735438 0.136205270 0.056423399 -0.903814331
[6] -0.359331869 -0.319166312 0.783658404 -1.618403684 0.448494856
[11] 0.588200335 -1.839945245 -0.201214156 1.492587582 -0.387160737
[16] -0.038544160 0.133974132 -0.521401340 -1.183009430 -1.385641284
[21] 0.591380781 -0.357802988 -0.165904590 -1.690728499 0.369458376
[26] -1.547098658 0.009429096 -0.453070736 -0.600544947 -0.391649829
[31] -1.178052784 1.250692077 -0.790704278 -0.363047598 0.925965040
[36] -1.395412918 -0.902384477 1.508917397 0.831009789 -0.545114754
[41] 1.011186156 -0.822750219 -0.612431318 -0.213477978 -1.551000519
[46] 1.061633996 1.096161752 -1.221533021 -1.474885278 -1.349971228
[51] 0.130905130 -0.578564884 -0.113224467 -0.608827426 0.090453551
[56] -0.983817377 -0.467153065 -0.823810088 1.435325002 1.660788349
[61] -0.687309467 1.405872871 0.239185295 0.421465114 -0.820800827
[66] -0.950585681 -0.492843144 -1.228033390 -0.645237332 -1.684756634
[71] -0.351089575 0.971739791 0.001655480 1.264360697 0.247546168
[76] -1.226399129 0.071590253 -0.005703694 0.825923228 0.131466352
[81] 0.073081116 0.578780119 0.235095842 -0.254559882 -1.353438141
[86] 1.603838116 -0.239353749 -0.876997141 0.353893736 0.588542622
[91] 0.197162839 -1.164363858 0.552692799 -0.439193177 2.383925360
[96] 0.721838188 -0.016970451 0.778765608 0.400212533 -1.960000021
> colMin(tmp)
[1] 0.313168194 -0.137735438 0.136205270 0.056423399 -0.903814331
[6] -0.359331869 -0.319166312 0.783658404 -1.618403684 0.448494856
[11] 0.588200335 -1.839945245 -0.201214156 1.492587582 -0.387160737
[16] -0.038544160 0.133974132 -0.521401340 -1.183009430 -1.385641284
[21] 0.591380781 -0.357802988 -0.165904590 -1.690728499 0.369458376
[26] -1.547098658 0.009429096 -0.453070736 -0.600544947 -0.391649829
[31] -1.178052784 1.250692077 -0.790704278 -0.363047598 0.925965040
[36] -1.395412918 -0.902384477 1.508917397 0.831009789 -0.545114754
[41] 1.011186156 -0.822750219 -0.612431318 -0.213477978 -1.551000519
[46] 1.061633996 1.096161752 -1.221533021 -1.474885278 -1.349971228
[51] 0.130905130 -0.578564884 -0.113224467 -0.608827426 0.090453551
[56] -0.983817377 -0.467153065 -0.823810088 1.435325002 1.660788349
[61] -0.687309467 1.405872871 0.239185295 0.421465114 -0.820800827
[66] -0.950585681 -0.492843144 -1.228033390 -0.645237332 -1.684756634
[71] -0.351089575 0.971739791 0.001655480 1.264360697 0.247546168
[76] -1.226399129 0.071590253 -0.005703694 0.825923228 0.131466352
[81] 0.073081116 0.578780119 0.235095842 -0.254559882 -1.353438141
[86] 1.603838116 -0.239353749 -0.876997141 0.353893736 0.588542622
[91] 0.197162839 -1.164363858 0.552692799 -0.439193177 2.383925360
[96] 0.721838188 -0.016970451 0.778765608 0.400212533 -1.960000021
> colMedians(tmp)
[1] 0.313168194 -0.137735438 0.136205270 0.056423399 -0.903814331
[6] -0.359331869 -0.319166312 0.783658404 -1.618403684 0.448494856
[11] 0.588200335 -1.839945245 -0.201214156 1.492587582 -0.387160737
[16] -0.038544160 0.133974132 -0.521401340 -1.183009430 -1.385641284
[21] 0.591380781 -0.357802988 -0.165904590 -1.690728499 0.369458376
[26] -1.547098658 0.009429096 -0.453070736 -0.600544947 -0.391649829
[31] -1.178052784 1.250692077 -0.790704278 -0.363047598 0.925965040
[36] -1.395412918 -0.902384477 1.508917397 0.831009789 -0.545114754
[41] 1.011186156 -0.822750219 -0.612431318 -0.213477978 -1.551000519
[46] 1.061633996 1.096161752 -1.221533021 -1.474885278 -1.349971228
[51] 0.130905130 -0.578564884 -0.113224467 -0.608827426 0.090453551
[56] -0.983817377 -0.467153065 -0.823810088 1.435325002 1.660788349
[61] -0.687309467 1.405872871 0.239185295 0.421465114 -0.820800827
[66] -0.950585681 -0.492843144 -1.228033390 -0.645237332 -1.684756634
[71] -0.351089575 0.971739791 0.001655480 1.264360697 0.247546168
[76] -1.226399129 0.071590253 -0.005703694 0.825923228 0.131466352
[81] 0.073081116 0.578780119 0.235095842 -0.254559882 -1.353438141
[86] 1.603838116 -0.239353749 -0.876997141 0.353893736 0.588542622
[91] 0.197162839 -1.164363858 0.552692799 -0.439193177 2.383925360
[96] 0.721838188 -0.016970451 0.778765608 0.400212533 -1.960000021
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.3131682 -0.1377354 0.1362053 0.0564234 -0.9038143 -0.3593319 -0.3191663
[2,] 0.3131682 -0.1377354 0.1362053 0.0564234 -0.9038143 -0.3593319 -0.3191663
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.7836584 -1.618404 0.4484949 0.5882003 -1.839945 -0.2012142 1.492588
[2,] 0.7836584 -1.618404 0.4484949 0.5882003 -1.839945 -0.2012142 1.492588
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.3871607 -0.03854416 0.1339741 -0.5214013 -1.183009 -1.385641 0.5913808
[2,] -0.3871607 -0.03854416 0.1339741 -0.5214013 -1.183009 -1.385641 0.5913808
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.357803 -0.1659046 -1.690728 0.3694584 -1.547099 0.009429096 -0.4530707
[2,] -0.357803 -0.1659046 -1.690728 0.3694584 -1.547099 0.009429096 -0.4530707
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.6005449 -0.3916498 -1.178053 1.250692 -0.7907043 -0.3630476 0.925965
[2,] -0.6005449 -0.3916498 -1.178053 1.250692 -0.7907043 -0.3630476 0.925965
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.395413 -0.9023845 1.508917 0.8310098 -0.5451148 1.011186 -0.8227502
[2,] -1.395413 -0.9023845 1.508917 0.8310098 -0.5451148 1.011186 -0.8227502
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.6124313 -0.213478 -1.551001 1.061634 1.096162 -1.221533 -1.474885
[2,] -0.6124313 -0.213478 -1.551001 1.061634 1.096162 -1.221533 -1.474885
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -1.349971 0.1309051 -0.5785649 -0.1132245 -0.6088274 0.09045355 -0.9838174
[2,] -1.349971 0.1309051 -0.5785649 -0.1132245 -0.6088274 0.09045355 -0.9838174
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.4671531 -0.8238101 1.435325 1.660788 -0.6873095 1.405873 0.2391853
[2,] -0.4671531 -0.8238101 1.435325 1.660788 -0.6873095 1.405873 0.2391853
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.4214651 -0.8208008 -0.9505857 -0.4928431 -1.228033 -0.6452373 -1.684757
[2,] 0.4214651 -0.8208008 -0.9505857 -0.4928431 -1.228033 -0.6452373 -1.684757
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.3510896 0.9717398 0.00165548 1.264361 0.2475462 -1.226399 0.07159025
[2,] -0.3510896 0.9717398 0.00165548 1.264361 0.2475462 -1.226399 0.07159025
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.005703694 0.8259232 0.1314664 0.07308112 0.5787801 0.2350958 -0.2545599
[2,] -0.005703694 0.8259232 0.1314664 0.07308112 0.5787801 0.2350958 -0.2545599
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -1.353438 1.603838 -0.2393537 -0.8769971 0.3538937 0.5885426 0.1971628
[2,] -1.353438 1.603838 -0.2393537 -0.8769971 0.3538937 0.5885426 0.1971628
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.164364 0.5526928 -0.4391932 2.383925 0.7218382 -0.01697045 0.7787656
[2,] -1.164364 0.5526928 -0.4391932 2.383925 0.7218382 -0.01697045 0.7787656
[,99] [,100]
[1,] 0.4002125 -1.96
[2,] 0.4002125 -1.96
>
>
> Max(tmp2)
[1] 2.510085
> Min(tmp2)
[1] -2.361179
> mean(tmp2)
[1] 0.05396885
> Sum(tmp2)
[1] 5.396885
> Var(tmp2)
[1] 1.058764
>
> rowMeans(tmp2)
[1] -0.0968264294 -0.3969004913 -2.2290593118 -0.9554961393 -0.3516383698
[6] -0.3825563661 0.2363654403 -0.8212043744 1.8779230073 0.8456320149
[11] -0.2056484830 1.0939865682 0.0333471435 0.9412126953 -0.2508862438
[16] 0.1980096056 1.8271287561 -0.0894172080 -0.4162726927 0.5400061227
[21] -1.0031406905 -2.0240125812 0.1155564507 0.3725280051 0.6856729498
[26] 0.8062105297 0.3710532977 1.1559464640 1.1049173960 -0.3083429281
[31] -2.3611785472 -0.9036879699 -0.5393025959 1.7061188739 -1.7142488693
[36] 0.7206769704 -0.4082647153 0.4158499223 -0.5516363088 2.5100850432
[41] -0.7767051743 -1.1170439536 0.8949406288 1.5138255947 -0.3438579945
[46] -0.4053999419 1.1130212072 0.1421627405 2.2379801866 -1.3618017582
[51] 0.3825189250 -0.5381475577 0.7317143454 -0.9989706880 -1.1217767426
[56] 1.4103042461 0.4415083825 0.5505899893 -1.2504271349 -0.6320388981
[61] 1.5838237001 0.2680938883 0.3597902013 -0.2365900422 0.0063228558
[66] 0.9705917817 0.5415094027 0.4863422119 1.6170378501 -1.2128055041
[71] 0.5500572496 0.9015246384 0.6351530674 -1.3109719349 0.0005471039
[76] -0.5722890274 0.2032874453 0.8140383608 -0.2518883413 -0.2568957775
[81] -0.0276458783 1.1914838241 0.0699814262 1.4734438038 -0.7281023767
[86] -1.8173722912 -0.8142377531 1.0397209909 1.1732897604 0.3781724431
[91] -1.4938767256 2.0988904190 -0.1975604819 0.4669563562 -0.0170817160
[96] -1.6998478844 -0.3655423598 -1.2497393079 0.0403953338 -1.6420237073
> rowSums(tmp2)
[1] -0.0968264294 -0.3969004913 -2.2290593118 -0.9554961393 -0.3516383698
[6] -0.3825563661 0.2363654403 -0.8212043744 1.8779230073 0.8456320149
[11] -0.2056484830 1.0939865682 0.0333471435 0.9412126953 -0.2508862438
[16] 0.1980096056 1.8271287561 -0.0894172080 -0.4162726927 0.5400061227
[21] -1.0031406905 -2.0240125812 0.1155564507 0.3725280051 0.6856729498
[26] 0.8062105297 0.3710532977 1.1559464640 1.1049173960 -0.3083429281
[31] -2.3611785472 -0.9036879699 -0.5393025959 1.7061188739 -1.7142488693
[36] 0.7206769704 -0.4082647153 0.4158499223 -0.5516363088 2.5100850432
[41] -0.7767051743 -1.1170439536 0.8949406288 1.5138255947 -0.3438579945
[46] -0.4053999419 1.1130212072 0.1421627405 2.2379801866 -1.3618017582
[51] 0.3825189250 -0.5381475577 0.7317143454 -0.9989706880 -1.1217767426
[56] 1.4103042461 0.4415083825 0.5505899893 -1.2504271349 -0.6320388981
[61] 1.5838237001 0.2680938883 0.3597902013 -0.2365900422 0.0063228558
[66] 0.9705917817 0.5415094027 0.4863422119 1.6170378501 -1.2128055041
[71] 0.5500572496 0.9015246384 0.6351530674 -1.3109719349 0.0005471039
[76] -0.5722890274 0.2032874453 0.8140383608 -0.2518883413 -0.2568957775
[81] -0.0276458783 1.1914838241 0.0699814262 1.4734438038 -0.7281023767
[86] -1.8173722912 -0.8142377531 1.0397209909 1.1732897604 0.3781724431
[91] -1.4938767256 2.0988904190 -0.1975604819 0.4669563562 -0.0170817160
[96] -1.6998478844 -0.3655423598 -1.2497393079 0.0403953338 -1.6420237073
> 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] -0.0968264294 -0.3969004913 -2.2290593118 -0.9554961393 -0.3516383698
[6] -0.3825563661 0.2363654403 -0.8212043744 1.8779230073 0.8456320149
[11] -0.2056484830 1.0939865682 0.0333471435 0.9412126953 -0.2508862438
[16] 0.1980096056 1.8271287561 -0.0894172080 -0.4162726927 0.5400061227
[21] -1.0031406905 -2.0240125812 0.1155564507 0.3725280051 0.6856729498
[26] 0.8062105297 0.3710532977 1.1559464640 1.1049173960 -0.3083429281
[31] -2.3611785472 -0.9036879699 -0.5393025959 1.7061188739 -1.7142488693
[36] 0.7206769704 -0.4082647153 0.4158499223 -0.5516363088 2.5100850432
[41] -0.7767051743 -1.1170439536 0.8949406288 1.5138255947 -0.3438579945
[46] -0.4053999419 1.1130212072 0.1421627405 2.2379801866 -1.3618017582
[51] 0.3825189250 -0.5381475577 0.7317143454 -0.9989706880 -1.1217767426
[56] 1.4103042461 0.4415083825 0.5505899893 -1.2504271349 -0.6320388981
[61] 1.5838237001 0.2680938883 0.3597902013 -0.2365900422 0.0063228558
[66] 0.9705917817 0.5415094027 0.4863422119 1.6170378501 -1.2128055041
[71] 0.5500572496 0.9015246384 0.6351530674 -1.3109719349 0.0005471039
[76] -0.5722890274 0.2032874453 0.8140383608 -0.2518883413 -0.2568957775
[81] -0.0276458783 1.1914838241 0.0699814262 1.4734438038 -0.7281023767
[86] -1.8173722912 -0.8142377531 1.0397209909 1.1732897604 0.3781724431
[91] -1.4938767256 2.0988904190 -0.1975604819 0.4669563562 -0.0170817160
[96] -1.6998478844 -0.3655423598 -1.2497393079 0.0403953338 -1.6420237073
> rowMin(tmp2)
[1] -0.0968264294 -0.3969004913 -2.2290593118 -0.9554961393 -0.3516383698
[6] -0.3825563661 0.2363654403 -0.8212043744 1.8779230073 0.8456320149
[11] -0.2056484830 1.0939865682 0.0333471435 0.9412126953 -0.2508862438
[16] 0.1980096056 1.8271287561 -0.0894172080 -0.4162726927 0.5400061227
[21] -1.0031406905 -2.0240125812 0.1155564507 0.3725280051 0.6856729498
[26] 0.8062105297 0.3710532977 1.1559464640 1.1049173960 -0.3083429281
[31] -2.3611785472 -0.9036879699 -0.5393025959 1.7061188739 -1.7142488693
[36] 0.7206769704 -0.4082647153 0.4158499223 -0.5516363088 2.5100850432
[41] -0.7767051743 -1.1170439536 0.8949406288 1.5138255947 -0.3438579945
[46] -0.4053999419 1.1130212072 0.1421627405 2.2379801866 -1.3618017582
[51] 0.3825189250 -0.5381475577 0.7317143454 -0.9989706880 -1.1217767426
[56] 1.4103042461 0.4415083825 0.5505899893 -1.2504271349 -0.6320388981
[61] 1.5838237001 0.2680938883 0.3597902013 -0.2365900422 0.0063228558
[66] 0.9705917817 0.5415094027 0.4863422119 1.6170378501 -1.2128055041
[71] 0.5500572496 0.9015246384 0.6351530674 -1.3109719349 0.0005471039
[76] -0.5722890274 0.2032874453 0.8140383608 -0.2518883413 -0.2568957775
[81] -0.0276458783 1.1914838241 0.0699814262 1.4734438038 -0.7281023767
[86] -1.8173722912 -0.8142377531 1.0397209909 1.1732897604 0.3781724431
[91] -1.4938767256 2.0988904190 -0.1975604819 0.4669563562 -0.0170817160
[96] -1.6998478844 -0.3655423598 -1.2497393079 0.0403953338 -1.6420237073
>
> colMeans(tmp2)
[1] 0.05396885
> colSums(tmp2)
[1] 5.396885
> colVars(tmp2)
[1] 1.058764
> colSd(tmp2)
[1] 1.028962
> colMax(tmp2)
[1] 2.510085
> colMin(tmp2)
[1] -2.361179
> colMedians(tmp2)
[1] 0.03687124
> colRanges(tmp2)
[,1]
[1,] -2.361179
[2,] 2.510085
>
> 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] -3.4507965 -5.1894963 0.9374622 -4.1831112 -2.6474658 2.4415482
[7] 7.2615112 0.2058747 -1.9452887 -0.1561129
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.47227383
[2,] -1.04966061
[3,] -0.55823807
[4,] -0.08637328
[5,] 1.65876180
>
> rowApply(tmp,sum)
[1] -0.3188697 3.2452848 -1.0062120 -0.2777812 -1.6911811 -0.1287068
[7] -5.3740737 2.4790046 -3.3540433 -0.2992968
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 2 2 5 2 3 5 2 3 9
[2,] 2 6 1 1 10 4 9 7 2 3
[3,] 1 3 6 7 7 5 10 9 4 7
[4,] 6 1 9 2 9 2 1 6 7 6
[5,] 4 9 10 3 1 7 8 3 6 4
[6,] 10 5 8 10 8 6 7 5 1 2
[7,] 3 10 7 6 3 10 6 10 10 5
[8,] 5 8 3 4 5 1 3 8 9 10
[9,] 7 4 5 9 6 9 2 1 5 8
[10,] 9 7 4 8 4 8 4 4 8 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.1099697 -0.5716574 1.1671276 2.8514476 -4.8319651 -1.1610679
[7] 0.9877887 -1.2852411 -0.6676009 0.3417312 -3.1294255 1.7806748
[13] 2.5374031 -3.6661062 -0.6973124 -3.0348491 2.0128089 -2.8710923
[19] 1.2666993 -0.6460288
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.5386088
[2,] -0.3685121
[3,] 0.1601665
[4,] 0.5192092
[5,] 1.1177756
>
> rowApply(tmp,sum)
[1] -4.890251 -3.506586 3.793639 -2.646689 -3.476748
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 17 15 1 14 9
[2,] 12 7 9 8 18
[3,] 7 18 18 2 19
[4,] 15 13 17 16 17
[5,] 1 1 10 17 6
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.1177756 -0.04359969 -0.8609446 0.4620621 -2.2717309 -0.8664542
[2,] 0.5192092 -0.78926151 1.3789962 0.3819625 -2.7259453 1.0864809
[3,] -2.5386088 0.11239368 1.0923274 1.0892538 0.2207107 0.2592163
[4,] 0.1601665 -0.41027800 -1.5358717 0.5382625 0.5645349 -1.0833469
[5,] -0.3685121 0.55908812 1.0926203 0.3799068 -0.6195345 -0.5569639
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.4993852 -0.2330275 -1.7194430 -0.8255991 -0.6691629 0.16983517
[2,] 0.4824638 -1.4744825 1.5279152 -0.1048777 -0.9636534 -0.34239108
[3,] -0.2684274 0.5414023 1.4842462 0.7568522 -0.6284009 0.31945600
[4,] 0.0610081 0.8862882 -0.5682515 0.1720038 -1.0812888 0.08490925
[5,] 0.2133589 -1.0054217 -1.3920678 0.3433520 0.2130806 1.54886543
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.6900072 -0.65732861 0.2097577 -1.21799274 1.17879340 -0.91222100
[2,] -1.0995864 -2.28762117 0.6765402 0.02799607 -0.02672879 0.23792944
[3,] 0.4549891 0.08330567 -0.4676687 -0.31951756 1.27128391 -0.06900847
[4,] 1.7725781 -0.42924266 -0.3159108 -1.59321782 -0.23153454 -1.26587439
[5,] -0.2805849 -0.37521945 -0.8000308 0.06788296 -0.17900504 -0.86191790
[,19] [,20]
[1,] 1.30979339 -1.25015645
[2,] 1.93613104 -1.94766278
[3,] -0.44083982 0.84067328
[4,] -0.06514043 1.69351766
[5,] -1.47324488 0.01759951
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.2568129 0.5330751 1.280458 1.91666 -0.3903915 -0.3255015 -0.4661926
col8 col9 col10 col11 col12 col13 col14
row1 0.8520265 -0.3829074 -0.585689 0.3457069 -0.2285833 1.233534 -0.2087945
col15 col16 col17 col18 col19 col20
row1 0.6842555 1.785066 -0.102975 1.218584 0.4413522 -0.5770913
> tmp[,"col10"]
col10
row1 -0.5856890
row2 0.3249115
row3 0.2757611
row4 1.0872009
row5 -0.6003134
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.2568129 0.5330751 1.2804578 1.9166602 -0.3903915 -0.3255015 -0.4661926
row5 1.7493120 -1.6447373 0.8926491 0.9677866 -1.6569052 -0.1636127 -0.3888821
col8 col9 col10 col11 col12 col13 col14
row1 0.8520265 -0.3829074 -0.5856890 0.3457069 -0.2285833 1.233534 -0.2087945
row5 0.3189833 -0.4730685 -0.6003134 -0.4516793 1.2569969 -1.274010 -0.1720620
col15 col16 col17 col18 col19 col20
row1 0.6842555 1.785066 -0.1029750 1.218584 0.4413522 -0.5770913
row5 -0.2783823 -2.001157 0.3149475 -0.270962 0.4153455 -1.3970491
> tmp[,c("col6","col20")]
col6 col20
row1 -0.3255015 -0.5770913
row2 0.3150319 1.6548328
row3 0.8749905 -1.4640063
row4 -0.2871948 0.5386146
row5 -0.1636127 -1.3970491
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.3255015 -0.5770913
row5 -0.1636127 -1.3970491
>
>
>
>
> 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 48.85681 49.90389 50.14703 49.72871 49.16249 103.4956 49.86859 49.38941
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.52466 51.83445 51.24029 51.64486 49.53177 50.57511 49.4321 50.1156
col17 col18 col19 col20
row1 50.97577 50.79636 50.94244 104.4968
> tmp[,"col10"]
col10
row1 51.83445
row2 30.77386
row3 30.38874
row4 30.88545
row5 48.86109
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.85681 49.90389 50.14703 49.72871 49.16249 103.4956 49.86859 49.38941
row5 49.48300 51.31603 48.44900 49.02960 51.57864 104.3855 49.05309 51.06912
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.52466 51.83445 51.24029 51.64486 49.53177 50.57511 49.43210 50.11560
row5 50.33309 48.86109 51.13101 49.50291 51.15118 49.47812 50.83942 50.36853
col17 col18 col19 col20
row1 50.97577 50.79636 50.94244 104.4968
row5 49.42578 50.03837 50.58365 105.2539
> tmp[,c("col6","col20")]
col6 col20
row1 103.49565 104.49683
row2 74.94440 74.47055
row3 74.59913 74.25298
row4 76.54821 74.63416
row5 104.38547 105.25389
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 103.4956 104.4968
row5 104.3855 105.2539
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 103.4956 104.4968
row5 104.3855 105.2539
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.6520088
[2,] 1.3271233
[3,] -0.4288616
[4,] 1.6702406
[5,] -0.6620026
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.09877343 0.7082076
[2,] 0.31763789 -1.1362741
[3,] 1.46282919 0.1572284
[4,] -0.04723905 -0.8860541
[5,] -1.35069766 -0.1741094
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -2.19644237 -0.4091058
[2,] 0.05844806 -0.7824431
[3,] -0.83659235 0.1789550
[4,] -0.87871619 0.4726888
[5,] -0.37518040 0.9785887
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -2.196442
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -2.19644237
[2,] 0.05844806
>
>
>
> 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 -0.4319631 0.36626644 -1.992466 0.2472436 -0.4648443 -1.727447 0.4971440
row1 1.0101184 0.04046754 -1.806466 -0.3093194 1.0135857 0.186323 -0.4678184
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -0.09786023 2.552757 -0.2919742 1.1145783 -0.4593356 -0.0271485 -1.305777
row1 0.10900385 -1.405054 0.1715840 0.1195334 0.5987537 0.4927265 -1.305786
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -1.3095276 2.783681 -0.8307835 0.4574595 -1.138019 0.3763902
row1 -0.8962861 2.573496 -0.5960993 -0.7717493 -2.004071 0.2845357
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.2915328 1.370238 -1.276331 0.2839889 0.1837705 0.04554639 -0.5229826
[,8] [,9] [,10]
row2 -0.02996518 -0.4758382 -1.893396
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.4432285 1.607904 -2.023024 -0.5708816 -1.470965 -0.2255157 -0.9004076
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.4168382 -0.5208629 1.130996 -0.6894688 -0.3967904 1.726511 -0.02090186
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.4462891 0.8652756 -0.5991093 -1.353957 0.7821723 -1.211791
>
>
> 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: 0x1cfb0570>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e7c8b5eee7225"
[2] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e7c8b2b8377ec"
[3] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e7c8b32e7f760"
[4] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e7c8b5e24eb53"
[5] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e7c8b7d134c1e"
[6] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e7c8b425203ae"
[7] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e7c8b1daabf98"
[8] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e7c8b3c8a61a4"
[9] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e7c8b73ed9953"
[10] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e7c8b732aba91"
[11] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e7c8b2f9088a6"
[12] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e7c8b71d072f8"
[13] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e7c8b26e864d2"
[14] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e7c8b1b6067ee"
[15] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1e7c8b193de312"
>
>
> ### 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: 0x1d8be880>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x1d8be880>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x1d8be880>
> rowMedians(tmp)
[1] -0.2222688017 -0.2210072483 -0.2392769537 -0.2738113998 0.2678648289
[6] -0.2683063653 -0.1692739847 0.1997596666 0.3197632713 -0.1776529667
[11] -0.3620836702 0.2045047621 -0.0273973450 0.3171527092 -0.0131048432
[16] -0.0805767703 0.4208735120 -0.2354836013 0.7931541265 0.2792559103
[21] -0.5518849302 -0.5887212902 0.1909178376 -0.0677187310 0.4568210918
[26] 0.3503788838 0.3531146409 0.0604691910 0.0142015536 -0.0378912703
[31] -0.3320600292 -0.4268485879 -0.4186942720 0.0261679784 0.0005686099
[36] 0.0893436019 0.6328848227 -0.3406739751 -0.0218329337 -0.2316503679
[41] 0.0593629777 -0.0986830062 0.4716293446 -0.6697543360 -0.0791609311
[46] 0.1354419772 -0.5077161364 0.3182992872 -0.3959620134 -0.1885347238
[51] -0.4364283412 -0.3378998217 -0.3680622506 0.0369394431 -0.5468268982
[56] 0.4909162552 -0.2665937944 -0.0489201206 0.4059015715 -0.4092863996
[61] 0.1868982487 -0.0938398719 0.0795764991 -0.4344060851 0.1893140420
[66] 1.0700208463 -0.6273534054 -0.3922043448 0.2539775749 0.3297400652
[71] 0.2614196171 0.3575900914 -0.2042199528 0.0195545953 -0.0407383810
[76] -0.3660206553 0.0054257115 0.1444526402 -0.4408882699 -0.0808499645
[81] -0.0073297209 -0.3192051030 0.1102898141 0.2108221418 -0.3872816620
[86] -0.4390287467 -0.1298247388 -0.3000669572 -0.2987443311 -0.1728443327
[91] 0.3089745169 0.3561534475 0.2375656114 -0.4386590574 -0.3858369725
[96] 0.0947081277 0.4941526052 0.1560608398 -0.4175462774 -0.1891296442
[101] 0.4058171189 0.2411575583 0.1476991202 -0.0560719860 0.0200683865
[106] 0.2355165789 -0.2238279875 0.1875122634 0.3515430649 0.2477837710
[111] -0.0951525458 0.4141676902 0.0109014277 -0.4058104367 0.1633032824
[116] -0.6672192112 -0.0153968073 -0.4341832796 0.7391925518 0.2175751228
[121] -0.0563046978 0.0808877249 0.2036844303 -0.0397705623 -0.1023774572
[126] 0.5897657668 -0.2159667709 0.1993799474 0.2777789466 0.1166209510
[131] -0.1870119014 -0.1451644519 -0.1488480193 0.1051535851 -0.2579510451
[136] -0.1584673377 0.1257337339 0.0576173356 0.3340814139 -0.2637721581
[141] -0.2011705331 0.0893465776 -0.5009079095 -0.0980849529 0.3150945142
[146] -0.2969538085 0.3246925531 0.4902164033 -0.1536837294 0.1287840717
[151] -0.2153058330 0.1458170349 -0.0276249224 -0.3404404639 0.5909321036
[156] 0.0654216939 -0.4640099470 0.0090092512 -0.0965651277 0.0948327559
[161] 0.7192575057 0.1818712146 0.4894866045 -0.2895568245 0.5212333412
[166] -0.0930531615 0.2673320931 0.1051659357 0.1272207457 -0.0729693556
[171] 0.0786686702 -0.2464256570 -0.3083365664 0.1233304911 -0.5171382807
[176] -0.4604883803 0.0371398674 -0.3991585306 -0.2781056393 -0.2105490466
[181] -0.3901073867 0.0945575898 -0.0094120488 0.2704541959 -0.0939600095
[186] 0.4562368975 0.2809152073 -0.3830405952 0.4139797284 0.5093669791
[191] 0.4874214235 -0.2732168134 0.1440795035 -0.2334537418 -0.2574794847
[196] -0.3670809913 0.6789775461 0.6890405914 0.1822957744 0.0724338982
[201] -0.4247077561 0.2831703226 -0.1623584600 -0.1966672678 0.3357671498
[206] 0.5760934368 0.0969835088 -0.2548177815 0.6000786864 0.0643468967
[211] 0.2319575618 -0.3714296079 0.8264797969 0.0462827986 -0.1552580253
[216] -0.1193284358 -0.3090318323 0.1667948651 0.5427672647 -0.1950174724
[221] 0.1615346336 0.1222683248 -0.2222432587 -0.5031093756 -0.0096102650
[226] -0.1029092901 -0.0210346432 0.0502359474 -0.4108752691 -0.1177379039
>
> proc.time()
user system elapsed
1.904 0.878 2.807
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
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: 0x2c10f6e0>
> .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: 0x2c10f6e0>
> .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: 0x2c10f6e0>
> .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: 0x2c10f6e0>
> 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: 0x2c1576a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2c1576a0>
> .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: 0x2c1576a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2c1576a0>
> .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: 0x2c1576a0>
> 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: 0x2b3137d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2b3137d0>
> .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: 0x2b3137d0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x2b3137d0>
> .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: 0x2b3137d0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x2b3137d0>
> .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: 0x2b3137d0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x2b3137d0>
> .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: 0x2b3137d0>
> 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: 0x2be72d70>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x2be72d70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2be72d70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2be72d70>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1e7f76313ec07c" "BufferedMatrixFile1e7f7645cd82a1"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1e7f76313ec07c" "BufferedMatrixFile1e7f7645cd82a1"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x2ba15cd0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2ba15cd0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x2ba15cd0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x2ba15cd0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x2ba15cd0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x2ba15cd0>
> .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: 0x2a984a10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2a984a10>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x2a984a10>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x2a984a10>
> 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: 0x2c89ecc0>
> .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: 0x2c89ecc0>
> rm(P)
>
> proc.time()
user system elapsed
0.329 0.054 0.370
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
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.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.356 0.029 0.373