Ben Bolstad
| Snapshot Date: 2025-09-22 13:40 -0400 (Mon, 22 Sep 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_21 |
| git_last_commit: aa9e634 |
| git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-09-25 11:41 -0400 (Thu, 25 Sep 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4827 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root" | 4608 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4549 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4581 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 252/2341 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.72.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| kunpeng2 | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. - 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: 2025-09-23 07:52:35 -0000 (Tue, 23 Sep 2025) |
| EndedAt: 2025-09-23 07:52:58 -0000 (Tue, 23 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_1.72.0.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
0.338 0.029 0.353
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] "Tue Sep 23 07:52:52 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Sep 23 07:52:52 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: 0x394146e0>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Tue Sep 23 07:52:53 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Sep 23 07:52:53 2025"
>
> ColMode(tmp2)
<pointer: 0x394146e0>
>
>
>
> ### 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,] 99.4442254 -0.86287423 0.9065090 1.11426017
[2,] 2.3726247 2.51801442 -0.5758146 0.82846608
[3,] -0.4123106 -0.03859743 -1.7836341 -0.06370041
[4,] -1.1846076 0.56738153 -0.9662035 -1.36849864
> 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,] 99.4442254 0.86287423 0.9065090 1.11426017
[2,] 2.3726247 2.51801442 0.5758146 0.82846608
[3,] 0.4123106 0.03859743 1.7836341 0.06370041
[4,] 1.1846076 0.56738153 0.9662035 1.36849864
> 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,] 9.9721726 0.9289102 0.9521077 1.0555852
[2,] 1.5403327 1.5868253 0.7588245 0.9102011
[3,] 0.6421142 0.1964623 1.3355276 0.2523894
[4,] 1.0883968 0.7532473 0.9829565 1.1698285
>
> 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,] 224.16595 35.15198 35.42759 36.67011
[2,] 42.77595 43.38627 33.16406 34.93048
[3,] 31.83345 27.00322 40.13891 27.58759
[4,] 37.06858 33.09985 35.79577 38.06678
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x379ec520>
> exp(tmp5)
<pointer: 0x379ec520>
> log(tmp5,2)
<pointer: 0x379ec520>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.5721
> Min(tmp5)
[1] 53.66306
> mean(tmp5)
[1] 74.16323
> Sum(tmp5)
[1] 14832.65
> Var(tmp5)
[1] 854.8295
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.02489 72.57427 70.54347 72.11909 72.20814 73.43288 72.01883 74.32714
[9] 72.87890 69.50470
> rowSums(tmp5)
[1] 1840.498 1451.485 1410.869 1442.382 1444.163 1468.658 1440.377 1486.543
[9] 1457.578 1390.094
> rowVars(tmp5)
[1] 7843.67361 78.21512 73.45515 90.78381 64.41163 106.10810
[7] 53.70938 104.03307 65.37566 82.73526
> rowSd(tmp5)
[1] 88.564517 8.843931 8.570598 9.528054 8.025686 10.300879 7.328668
[8] 10.199660 8.085521 9.095893
> rowMax(tmp5)
[1] 466.57206 90.30283 84.75994 95.50367 88.05100 96.10261 90.41330
[8] 97.86764 83.69589 85.18584
> rowMin(tmp5)
[1] 55.66230 56.02671 56.20366 54.05394 59.67471 53.66306 58.50090 58.50036
[9] 57.26354 55.77046
>
> colMeans(tmp5)
[1] 115.63110 69.88384 74.98643 71.04858 71.98780 67.40314 74.46697
[8] 80.69026 72.59190 70.63331 71.56351 67.68671 72.83780 73.26520
[15] 66.32779 72.24411 70.13689 77.70320 72.65200 69.52409
> colSums(tmp5)
[1] 1156.3110 698.8384 749.8643 710.4858 719.8780 674.0314 744.6697
[8] 806.9026 725.9190 706.3331 715.6351 676.8671 728.3780 732.6520
[15] 663.2779 722.4411 701.3689 777.0320 726.5200 695.2409
> colVars(tmp5)
[1] 15303.22827 77.14447 83.28702 53.34081 61.17975 96.79878
[7] 118.17705 139.84889 42.99231 37.52704 44.28916 37.90053
[13] 104.09389 72.04062 39.79218 36.67484 27.72575 129.69572
[19] 50.68246 94.56068
> colSd(tmp5)
[1] 123.706218 8.783193 9.126172 7.303479 7.821749 9.838637
[7] 10.870927 11.825772 6.556852 6.125932 6.655010 6.156341
[13] 10.202641 8.487675 6.308104 6.055976 5.265525 11.388403
[19] 7.119162 9.724232
> colMax(tmp5)
[1] 466.57206 90.30283 87.09744 82.60624 85.68223 85.18584 88.65722
[8] 97.86764 82.21449 83.60084 82.70158 74.03947 90.01431 83.69589
[15] 74.45649 82.27019 79.63395 95.50367 84.83366 86.74362
> colMin(tmp5)
[1] 58.50036 56.20366 53.66306 57.41996 59.55766 54.38285 55.66230 62.12477
[9] 61.45939 61.66684 61.99477 57.26354 56.79753 61.26315 54.05394 62.46824
[17] 60.91437 59.83832 64.77638 55.77046
>
>
> ### 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] 92.02489 72.57427 NA 72.11909 72.20814 73.43288 72.01883 74.32714
[9] 72.87890 69.50470
> rowSums(tmp5)
[1] 1840.498 1451.485 NA 1442.382 1444.163 1468.658 1440.377 1486.543
[9] 1457.578 1390.094
> rowVars(tmp5)
[1] 7843.67361 78.21512 75.10459 90.78381 64.41163 106.10810
[7] 53.70938 104.03307 65.37566 82.73526
> rowSd(tmp5)
[1] 88.564517 8.843931 8.666290 9.528054 8.025686 10.300879 7.328668
[8] 10.199660 8.085521 9.095893
> rowMax(tmp5)
[1] 466.57206 90.30283 NA 95.50367 88.05100 96.10261 90.41330
[8] 97.86764 83.69589 85.18584
> rowMin(tmp5)
[1] 55.66230 56.02671 NA 54.05394 59.67471 53.66306 58.50090 58.50036
[9] 57.26354 55.77046
>
> colMeans(tmp5)
[1] 115.63110 69.88384 74.98643 71.04858 71.98780 67.40314 74.46697
[8] NA 72.59190 70.63331 71.56351 67.68671 72.83780 73.26520
[15] 66.32779 72.24411 70.13689 77.70320 72.65200 69.52409
> colSums(tmp5)
[1] 1156.3110 698.8384 749.8643 710.4858 719.8780 674.0314 744.6697
[8] NA 725.9190 706.3331 715.6351 676.8671 728.3780 732.6520
[15] 663.2779 722.4411 701.3689 777.0320 726.5200 695.2409
> colVars(tmp5)
[1] 15303.22827 77.14447 83.28702 53.34081 61.17975 96.79878
[7] 118.17705 NA 42.99231 37.52704 44.28916 37.90053
[13] 104.09389 72.04062 39.79218 36.67484 27.72575 129.69572
[19] 50.68246 94.56068
> colSd(tmp5)
[1] 123.706218 8.783193 9.126172 7.303479 7.821749 9.838637
[7] 10.870927 NA 6.556852 6.125932 6.655010 6.156341
[13] 10.202641 8.487675 6.308104 6.055976 5.265525 11.388403
[19] 7.119162 9.724232
> colMax(tmp5)
[1] 466.57206 90.30283 87.09744 82.60624 85.68223 85.18584 88.65722
[8] NA 82.21449 83.60084 82.70158 74.03947 90.01431 83.69589
[15] 74.45649 82.27019 79.63395 95.50367 84.83366 86.74362
> colMin(tmp5)
[1] 58.50036 56.20366 53.66306 57.41996 59.55766 54.38285 55.66230 NA
[9] 61.45939 61.66684 61.99477 57.26354 56.79753 61.26315 54.05394 62.46824
[17] 60.91437 59.83832 64.77638 55.77046
>
> Max(tmp5,na.rm=TRUE)
[1] 466.5721
> Min(tmp5,na.rm=TRUE)
[1] 53.66306
> mean(tmp5,na.rm=TRUE)
[1] 74.14902
> Sum(tmp5,na.rm=TRUE)
[1] 14755.65
> Var(tmp5,na.rm=TRUE)
[1] 859.1062
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.02489 72.57427 70.20410 72.11909 72.20814 73.43288 72.01883 74.32714
[9] 72.87890 69.50470
> rowSums(tmp5,na.rm=TRUE)
[1] 1840.498 1451.485 1333.878 1442.382 1444.163 1468.658 1440.377 1486.543
[9] 1457.578 1390.094
> rowVars(tmp5,na.rm=TRUE)
[1] 7843.67361 78.21512 75.10459 90.78381 64.41163 106.10810
[7] 53.70938 104.03307 65.37566 82.73526
> rowSd(tmp5,na.rm=TRUE)
[1] 88.564517 8.843931 8.666290 9.528054 8.025686 10.300879 7.328668
[8] 10.199660 8.085521 9.095893
> rowMax(tmp5,na.rm=TRUE)
[1] 466.57206 90.30283 84.75994 95.50367 88.05100 96.10261 90.41330
[8] 97.86764 83.69589 85.18584
> rowMin(tmp5,na.rm=TRUE)
[1] 55.66230 56.02671 56.20366 54.05394 59.67471 53.66306 58.50090 58.50036
[9] 57.26354 55.77046
>
> colMeans(tmp5,na.rm=TRUE)
[1] 115.63110 69.88384 74.98643 71.04858 71.98780 67.40314 74.46697
[8] 81.10124 72.59190 70.63331 71.56351 67.68671 72.83780 73.26520
[15] 66.32779 72.24411 70.13689 77.70320 72.65200 69.52409
> colSums(tmp5,na.rm=TRUE)
[1] 1156.3110 698.8384 749.8643 710.4858 719.8780 674.0314 744.6697
[8] 729.9111 725.9190 706.3331 715.6351 676.8671 728.3780 732.6520
[15] 663.2779 722.4411 701.3689 777.0320 726.5200 695.2409
> colVars(tmp5,na.rm=TRUE)
[1] 15303.22827 77.14447 83.28702 53.34081 61.17975 96.79878
[7] 118.17705 155.42988 42.99231 37.52704 44.28916 37.90053
[13] 104.09389 72.04062 39.79218 36.67484 27.72575 129.69572
[19] 50.68246 94.56068
> colSd(tmp5,na.rm=TRUE)
[1] 123.706218 8.783193 9.126172 7.303479 7.821749 9.838637
[7] 10.870927 12.467152 6.556852 6.125932 6.655010 6.156341
[13] 10.202641 8.487675 6.308104 6.055976 5.265525 11.388403
[19] 7.119162 9.724232
> colMax(tmp5,na.rm=TRUE)
[1] 466.57206 90.30283 87.09744 82.60624 85.68223 85.18584 88.65722
[8] 97.86764 82.21449 83.60084 82.70158 74.03947 90.01431 83.69589
[15] 74.45649 82.27019 79.63395 95.50367 84.83366 86.74362
> colMin(tmp5,na.rm=TRUE)
[1] 58.50036 56.20366 53.66306 57.41996 59.55766 54.38285 55.66230 62.12477
[9] 61.45939 61.66684 61.99477 57.26354 56.79753 61.26315 54.05394 62.46824
[17] 60.91437 59.83832 64.77638 55.77046
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.02489 72.57427 NaN 72.11909 72.20814 73.43288 72.01883 74.32714
[9] 72.87890 69.50470
> rowSums(tmp5,na.rm=TRUE)
[1] 1840.498 1451.485 0.000 1442.382 1444.163 1468.658 1440.377 1486.543
[9] 1457.578 1390.094
> rowVars(tmp5,na.rm=TRUE)
[1] 7843.67361 78.21512 NA 90.78381 64.41163 106.10810
[7] 53.70938 104.03307 65.37566 82.73526
> rowSd(tmp5,na.rm=TRUE)
[1] 88.564517 8.843931 NA 9.528054 8.025686 10.300879 7.328668
[8] 10.199660 8.085521 9.095893
> rowMax(tmp5,na.rm=TRUE)
[1] 466.57206 90.30283 NA 95.50367 88.05100 96.10261 90.41330
[8] 97.86764 83.69589 85.18584
> rowMin(tmp5,na.rm=TRUE)
[1] 55.66230 56.02671 NA 54.05394 59.67471 53.66306 58.50090 58.50036
[9] 57.26354 55.77046
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 121.11710 71.40386 74.03560 72.56287 72.17608 66.97504 73.32330
[8] NaN 72.57347 71.62958 72.62671 66.98084 72.16746 72.54310
[15] 66.38872 71.89354 69.08166 79.61373 73.10088 70.01376
> colSums(tmp5,na.rm=TRUE)
[1] 1090.0539 642.6347 666.3204 653.0659 649.5847 602.7754 659.9097
[8] 0.0000 653.1612 644.6663 653.6404 602.8276 649.5072 652.8879
[15] 597.4984 647.0419 621.7349 716.5235 657.9079 630.1239
> colVars(tmp5,na.rm=TRUE)
[1] 16877.55038 60.79487 83.52706 34.21129 68.42842 106.83688
[7] 118.23455 NA 48.36253 31.05158 37.10852 37.03288
[13] 112.05047 75.17957 44.72444 39.87660 18.66450 104.84411
[19] 54.75097 103.68329
> colSd(tmp5,na.rm=TRUE)
[1] 129.913627 7.797107 9.139314 5.849042 8.272147 10.336193
[7] 10.873571 NA 6.954317 5.572395 6.091676 6.085465
[13] 10.585389 8.670615 6.687633 6.314792 4.320243 10.239341
[19] 7.399390 10.182499
> colMax(tmp5,na.rm=TRUE)
[1] 466.57206 90.30283 87.09744 82.60624 85.68223 85.18584 88.65722
[8] -Inf 82.21449 83.60084 82.70158 73.70169 90.01431 83.69589
[15] 74.45649 82.27019 75.29277 95.50367 84.83366 86.74362
> colMin(tmp5,na.rm=TRUE)
[1] 58.50036 64.16699 53.66306 64.31271 59.55766 54.38285 55.66230 Inf
[9] 61.45939 64.80227 65.34030 57.26354 56.79753 61.26315 54.05394 62.46824
[17] 60.91437 59.83832 64.77638 55.77046
>
>
>
>
> 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] 255.1957 301.0284 171.8722 246.5348 276.9260 218.2311 159.5856 177.0062
[9] 244.3703 162.9100
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 255.1957 301.0284 171.8722 246.5348 276.9260 218.2311 159.5856 177.0062
[9] 244.3703 162.9100
>
>
>
> 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] 1.563194e-13 2.273737e-13 -8.526513e-14 1.989520e-13 5.684342e-14
[6] 2.273737e-13 2.842171e-14 1.136868e-13 1.136868e-13 -5.684342e-14
[11] 5.684342e-14 4.263256e-14 8.526513e-14 -1.705303e-13 -2.273737e-13
[16] 4.263256e-14 -1.136868e-13 -1.705303e-13 8.526513e-14 -8.526513e-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)
+ }
8 20
6 19
7 6
7 18
10 3
9 7
9 1
5 12
8 9
5 4
9 2
3 5
1 8
8 19
10 11
7 14
10 6
5 14
2 10
2 15
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] 2.776571
> Min(tmp)
[1] -2.00495
> mean(tmp)
[1] 0.1076509
> Sum(tmp)
[1] 10.76509
> Var(tmp)
[1] 1.049186
>
> rowMeans(tmp)
[1] 0.1076509
> rowSums(tmp)
[1] 10.76509
> rowVars(tmp)
[1] 1.049186
> rowSd(tmp)
[1] 1.024298
> rowMax(tmp)
[1] 2.776571
> rowMin(tmp)
[1] -2.00495
>
> colMeans(tmp)
[1] 0.97847198 0.76006784 0.10436338 -0.90287778 0.47133089 0.22598266
[7] 1.07098386 -1.24556572 1.72641076 0.87583476 -1.77587273 0.09764482
[13] -0.37578881 1.49974883 -0.81135445 -0.06509252 0.82486203 -0.65604428
[19] 0.08197466 -1.80648070 0.64998449 -0.46512222 -0.01702472 -0.34313732
[25] 1.01824866 0.57976982 -0.64330796 -0.32193823 -1.16197899 -0.43936920
[31] 0.07367545 0.11758809 0.22264361 2.77657113 -0.18943420 0.68351466
[37] -0.09171519 0.50722593 -0.63535227 -0.38893008 2.26622691 -0.27356780
[43] 0.57328589 0.11417071 -0.04835788 0.37681548 -1.91102023 0.76485674
[49] 0.91808508 0.67784128 -0.02593241 -1.40335799 2.36085648 -0.46776579
[55] 1.93599840 0.35023932 1.84299619 -1.63977761 -0.60436422 0.16307218
[61] 0.26486064 0.59619685 0.62057855 -1.54179845 0.01614865 -0.86797976
[67] -0.12042747 0.39573252 -0.31293900 0.12209944 -0.16167376 0.37040734
[73] -0.09383486 -1.90940031 -2.00495020 1.03680268 -0.54017438 0.46686793
[79] 1.43468361 -0.72659315 -0.39708310 -0.94793982 0.36186042 1.95099091
[85] 1.02921038 1.51422604 -0.10540445 1.91804686 0.66651433 -0.60253328
[91] 1.18651866 0.91769432 0.89146353 0.16839883 -1.69403919 0.34971634
[97] 1.03597233 0.08952341 -1.67104110 -1.92242141
> colSums(tmp)
[1] 0.97847198 0.76006784 0.10436338 -0.90287778 0.47133089 0.22598266
[7] 1.07098386 -1.24556572 1.72641076 0.87583476 -1.77587273 0.09764482
[13] -0.37578881 1.49974883 -0.81135445 -0.06509252 0.82486203 -0.65604428
[19] 0.08197466 -1.80648070 0.64998449 -0.46512222 -0.01702472 -0.34313732
[25] 1.01824866 0.57976982 -0.64330796 -0.32193823 -1.16197899 -0.43936920
[31] 0.07367545 0.11758809 0.22264361 2.77657113 -0.18943420 0.68351466
[37] -0.09171519 0.50722593 -0.63535227 -0.38893008 2.26622691 -0.27356780
[43] 0.57328589 0.11417071 -0.04835788 0.37681548 -1.91102023 0.76485674
[49] 0.91808508 0.67784128 -0.02593241 -1.40335799 2.36085648 -0.46776579
[55] 1.93599840 0.35023932 1.84299619 -1.63977761 -0.60436422 0.16307218
[61] 0.26486064 0.59619685 0.62057855 -1.54179845 0.01614865 -0.86797976
[67] -0.12042747 0.39573252 -0.31293900 0.12209944 -0.16167376 0.37040734
[73] -0.09383486 -1.90940031 -2.00495020 1.03680268 -0.54017438 0.46686793
[79] 1.43468361 -0.72659315 -0.39708310 -0.94793982 0.36186042 1.95099091
[85] 1.02921038 1.51422604 -0.10540445 1.91804686 0.66651433 -0.60253328
[91] 1.18651866 0.91769432 0.89146353 0.16839883 -1.69403919 0.34971634
[97] 1.03597233 0.08952341 -1.67104110 -1.92242141
> 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] 0.97847198 0.76006784 0.10436338 -0.90287778 0.47133089 0.22598266
[7] 1.07098386 -1.24556572 1.72641076 0.87583476 -1.77587273 0.09764482
[13] -0.37578881 1.49974883 -0.81135445 -0.06509252 0.82486203 -0.65604428
[19] 0.08197466 -1.80648070 0.64998449 -0.46512222 -0.01702472 -0.34313732
[25] 1.01824866 0.57976982 -0.64330796 -0.32193823 -1.16197899 -0.43936920
[31] 0.07367545 0.11758809 0.22264361 2.77657113 -0.18943420 0.68351466
[37] -0.09171519 0.50722593 -0.63535227 -0.38893008 2.26622691 -0.27356780
[43] 0.57328589 0.11417071 -0.04835788 0.37681548 -1.91102023 0.76485674
[49] 0.91808508 0.67784128 -0.02593241 -1.40335799 2.36085648 -0.46776579
[55] 1.93599840 0.35023932 1.84299619 -1.63977761 -0.60436422 0.16307218
[61] 0.26486064 0.59619685 0.62057855 -1.54179845 0.01614865 -0.86797976
[67] -0.12042747 0.39573252 -0.31293900 0.12209944 -0.16167376 0.37040734
[73] -0.09383486 -1.90940031 -2.00495020 1.03680268 -0.54017438 0.46686793
[79] 1.43468361 -0.72659315 -0.39708310 -0.94793982 0.36186042 1.95099091
[85] 1.02921038 1.51422604 -0.10540445 1.91804686 0.66651433 -0.60253328
[91] 1.18651866 0.91769432 0.89146353 0.16839883 -1.69403919 0.34971634
[97] 1.03597233 0.08952341 -1.67104110 -1.92242141
> colMin(tmp)
[1] 0.97847198 0.76006784 0.10436338 -0.90287778 0.47133089 0.22598266
[7] 1.07098386 -1.24556572 1.72641076 0.87583476 -1.77587273 0.09764482
[13] -0.37578881 1.49974883 -0.81135445 -0.06509252 0.82486203 -0.65604428
[19] 0.08197466 -1.80648070 0.64998449 -0.46512222 -0.01702472 -0.34313732
[25] 1.01824866 0.57976982 -0.64330796 -0.32193823 -1.16197899 -0.43936920
[31] 0.07367545 0.11758809 0.22264361 2.77657113 -0.18943420 0.68351466
[37] -0.09171519 0.50722593 -0.63535227 -0.38893008 2.26622691 -0.27356780
[43] 0.57328589 0.11417071 -0.04835788 0.37681548 -1.91102023 0.76485674
[49] 0.91808508 0.67784128 -0.02593241 -1.40335799 2.36085648 -0.46776579
[55] 1.93599840 0.35023932 1.84299619 -1.63977761 -0.60436422 0.16307218
[61] 0.26486064 0.59619685 0.62057855 -1.54179845 0.01614865 -0.86797976
[67] -0.12042747 0.39573252 -0.31293900 0.12209944 -0.16167376 0.37040734
[73] -0.09383486 -1.90940031 -2.00495020 1.03680268 -0.54017438 0.46686793
[79] 1.43468361 -0.72659315 -0.39708310 -0.94793982 0.36186042 1.95099091
[85] 1.02921038 1.51422604 -0.10540445 1.91804686 0.66651433 -0.60253328
[91] 1.18651866 0.91769432 0.89146353 0.16839883 -1.69403919 0.34971634
[97] 1.03597233 0.08952341 -1.67104110 -1.92242141
> colMedians(tmp)
[1] 0.97847198 0.76006784 0.10436338 -0.90287778 0.47133089 0.22598266
[7] 1.07098386 -1.24556572 1.72641076 0.87583476 -1.77587273 0.09764482
[13] -0.37578881 1.49974883 -0.81135445 -0.06509252 0.82486203 -0.65604428
[19] 0.08197466 -1.80648070 0.64998449 -0.46512222 -0.01702472 -0.34313732
[25] 1.01824866 0.57976982 -0.64330796 -0.32193823 -1.16197899 -0.43936920
[31] 0.07367545 0.11758809 0.22264361 2.77657113 -0.18943420 0.68351466
[37] -0.09171519 0.50722593 -0.63535227 -0.38893008 2.26622691 -0.27356780
[43] 0.57328589 0.11417071 -0.04835788 0.37681548 -1.91102023 0.76485674
[49] 0.91808508 0.67784128 -0.02593241 -1.40335799 2.36085648 -0.46776579
[55] 1.93599840 0.35023932 1.84299619 -1.63977761 -0.60436422 0.16307218
[61] 0.26486064 0.59619685 0.62057855 -1.54179845 0.01614865 -0.86797976
[67] -0.12042747 0.39573252 -0.31293900 0.12209944 -0.16167376 0.37040734
[73] -0.09383486 -1.90940031 -2.00495020 1.03680268 -0.54017438 0.46686793
[79] 1.43468361 -0.72659315 -0.39708310 -0.94793982 0.36186042 1.95099091
[85] 1.02921038 1.51422604 -0.10540445 1.91804686 0.66651433 -0.60253328
[91] 1.18651866 0.91769432 0.89146353 0.16839883 -1.69403919 0.34971634
[97] 1.03597233 0.08952341 -1.67104110 -1.92242141
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.978472 0.7600678 0.1043634 -0.9028778 0.4713309 0.2259827 1.070984
[2,] 0.978472 0.7600678 0.1043634 -0.9028778 0.4713309 0.2259827 1.070984
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.245566 1.726411 0.8758348 -1.775873 0.09764482 -0.3757888 1.499749
[2,] -1.245566 1.726411 0.8758348 -1.775873 0.09764482 -0.3757888 1.499749
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.8113545 -0.06509252 0.824862 -0.6560443 0.08197466 -1.806481 0.6499845
[2,] -0.8113545 -0.06509252 0.824862 -0.6560443 0.08197466 -1.806481 0.6499845
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.4651222 -0.01702472 -0.3431373 1.018249 0.5797698 -0.643308 -0.3219382
[2,] -0.4651222 -0.01702472 -0.3431373 1.018249 0.5797698 -0.643308 -0.3219382
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.161979 -0.4393692 0.07367545 0.1175881 0.2226436 2.776571 -0.1894342
[2,] -1.161979 -0.4393692 0.07367545 0.1175881 0.2226436 2.776571 -0.1894342
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.6835147 -0.09171519 0.5072259 -0.6353523 -0.3889301 2.266227 -0.2735678
[2,] 0.6835147 -0.09171519 0.5072259 -0.6353523 -0.3889301 2.266227 -0.2735678
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.5732859 0.1141707 -0.04835788 0.3768155 -1.91102 0.7648567 0.9180851
[2,] 0.5732859 0.1141707 -0.04835788 0.3768155 -1.91102 0.7648567 0.9180851
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.6778413 -0.02593241 -1.403358 2.360856 -0.4677658 1.935998 0.3502393
[2,] 0.6778413 -0.02593241 -1.403358 2.360856 -0.4677658 1.935998 0.3502393
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 1.842996 -1.639778 -0.6043642 0.1630722 0.2648606 0.5961968 0.6205785
[2,] 1.842996 -1.639778 -0.6043642 0.1630722 0.2648606 0.5961968 0.6205785
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.541798 0.01614865 -0.8679798 -0.1204275 0.3957325 -0.312939 0.1220994
[2,] -1.541798 0.01614865 -0.8679798 -0.1204275 0.3957325 -0.312939 0.1220994
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.1616738 0.3704073 -0.09383486 -1.9094 -2.00495 1.036803 -0.5401744
[2,] -0.1616738 0.3704073 -0.09383486 -1.9094 -2.00495 1.036803 -0.5401744
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.4668679 1.434684 -0.7265932 -0.3970831 -0.9479398 0.3618604 1.950991
[2,] 0.4668679 1.434684 -0.7265932 -0.3970831 -0.9479398 0.3618604 1.950991
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 1.02921 1.514226 -0.1054044 1.918047 0.6665143 -0.6025333 1.186519
[2,] 1.02921 1.514226 -0.1054044 1.918047 0.6665143 -0.6025333 1.186519
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.9176943 0.8914635 0.1683988 -1.694039 0.3497163 1.035972 0.08952341
[2,] 0.9176943 0.8914635 0.1683988 -1.694039 0.3497163 1.035972 0.08952341
[,99] [,100]
[1,] -1.671041 -1.922421
[2,] -1.671041 -1.922421
>
>
> Max(tmp2)
[1] 2.647963
> Min(tmp2)
[1] -2.720067
> mean(tmp2)
[1] -0.1072866
> Sum(tmp2)
[1] -10.72866
> Var(tmp2)
[1] 1.148566
>
> rowMeans(tmp2)
[1] 1.04587987 -1.14451470 -1.65015764 -0.53736807 -1.09511372 -0.92273155
[7] -1.66245926 -0.24749891 -0.12634937 2.64796311 -0.10459228 -1.25866389
[13] 0.95254036 -0.93443451 0.08205807 0.90178860 -1.30588482 -1.58020240
[19] -0.84386372 0.89020865 0.47152334 -0.06967806 0.89560373 -0.56736907
[25] -1.17978564 1.87400817 0.60576926 0.03893953 0.75054563 -1.63942773
[31] -0.20362640 0.56246958 -0.15828528 -1.77090839 0.16317502 -1.27473662
[37] -1.35905136 0.50344727 -0.53003395 1.59514832 -2.55895056 -2.72006651
[43] -0.80032184 0.58999845 -0.11094844 -1.08390961 -0.12122098 0.28893619
[49] 2.06721705 -0.43494015 -0.57999958 1.76882407 -0.14084635 -0.61552573
[55] -1.21340380 0.68797807 0.33643606 -0.23501559 0.72972627 -0.21851234
[61] 1.97953963 -0.31097627 1.44228762 -0.59970428 0.68329460 0.71369456
[67] -1.29860050 0.25237063 -0.11678912 -1.01885852 -1.56038429 1.69765417
[73] 0.88039799 0.57459493 -0.58804709 0.47018859 -1.68687273 1.68158842
[79] -0.75137253 -0.18452063 -0.23672605 -1.61558972 -0.25474638 -0.29767975
[85] 0.48338042 -0.01523795 -1.22368573 -0.76719948 -0.65335889 0.52917702
[91] 1.00601826 1.11301161 -1.06666093 -0.20463338 1.03885219 0.45748027
[97] 0.27067405 0.67631440 1.86171725 -1.53903966
> rowSums(tmp2)
[1] 1.04587987 -1.14451470 -1.65015764 -0.53736807 -1.09511372 -0.92273155
[7] -1.66245926 -0.24749891 -0.12634937 2.64796311 -0.10459228 -1.25866389
[13] 0.95254036 -0.93443451 0.08205807 0.90178860 -1.30588482 -1.58020240
[19] -0.84386372 0.89020865 0.47152334 -0.06967806 0.89560373 -0.56736907
[25] -1.17978564 1.87400817 0.60576926 0.03893953 0.75054563 -1.63942773
[31] -0.20362640 0.56246958 -0.15828528 -1.77090839 0.16317502 -1.27473662
[37] -1.35905136 0.50344727 -0.53003395 1.59514832 -2.55895056 -2.72006651
[43] -0.80032184 0.58999845 -0.11094844 -1.08390961 -0.12122098 0.28893619
[49] 2.06721705 -0.43494015 -0.57999958 1.76882407 -0.14084635 -0.61552573
[55] -1.21340380 0.68797807 0.33643606 -0.23501559 0.72972627 -0.21851234
[61] 1.97953963 -0.31097627 1.44228762 -0.59970428 0.68329460 0.71369456
[67] -1.29860050 0.25237063 -0.11678912 -1.01885852 -1.56038429 1.69765417
[73] 0.88039799 0.57459493 -0.58804709 0.47018859 -1.68687273 1.68158842
[79] -0.75137253 -0.18452063 -0.23672605 -1.61558972 -0.25474638 -0.29767975
[85] 0.48338042 -0.01523795 -1.22368573 -0.76719948 -0.65335889 0.52917702
[91] 1.00601826 1.11301161 -1.06666093 -0.20463338 1.03885219 0.45748027
[97] 0.27067405 0.67631440 1.86171725 -1.53903966
> 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] 1.04587987 -1.14451470 -1.65015764 -0.53736807 -1.09511372 -0.92273155
[7] -1.66245926 -0.24749891 -0.12634937 2.64796311 -0.10459228 -1.25866389
[13] 0.95254036 -0.93443451 0.08205807 0.90178860 -1.30588482 -1.58020240
[19] -0.84386372 0.89020865 0.47152334 -0.06967806 0.89560373 -0.56736907
[25] -1.17978564 1.87400817 0.60576926 0.03893953 0.75054563 -1.63942773
[31] -0.20362640 0.56246958 -0.15828528 -1.77090839 0.16317502 -1.27473662
[37] -1.35905136 0.50344727 -0.53003395 1.59514832 -2.55895056 -2.72006651
[43] -0.80032184 0.58999845 -0.11094844 -1.08390961 -0.12122098 0.28893619
[49] 2.06721705 -0.43494015 -0.57999958 1.76882407 -0.14084635 -0.61552573
[55] -1.21340380 0.68797807 0.33643606 -0.23501559 0.72972627 -0.21851234
[61] 1.97953963 -0.31097627 1.44228762 -0.59970428 0.68329460 0.71369456
[67] -1.29860050 0.25237063 -0.11678912 -1.01885852 -1.56038429 1.69765417
[73] 0.88039799 0.57459493 -0.58804709 0.47018859 -1.68687273 1.68158842
[79] -0.75137253 -0.18452063 -0.23672605 -1.61558972 -0.25474638 -0.29767975
[85] 0.48338042 -0.01523795 -1.22368573 -0.76719948 -0.65335889 0.52917702
[91] 1.00601826 1.11301161 -1.06666093 -0.20463338 1.03885219 0.45748027
[97] 0.27067405 0.67631440 1.86171725 -1.53903966
> rowMin(tmp2)
[1] 1.04587987 -1.14451470 -1.65015764 -0.53736807 -1.09511372 -0.92273155
[7] -1.66245926 -0.24749891 -0.12634937 2.64796311 -0.10459228 -1.25866389
[13] 0.95254036 -0.93443451 0.08205807 0.90178860 -1.30588482 -1.58020240
[19] -0.84386372 0.89020865 0.47152334 -0.06967806 0.89560373 -0.56736907
[25] -1.17978564 1.87400817 0.60576926 0.03893953 0.75054563 -1.63942773
[31] -0.20362640 0.56246958 -0.15828528 -1.77090839 0.16317502 -1.27473662
[37] -1.35905136 0.50344727 -0.53003395 1.59514832 -2.55895056 -2.72006651
[43] -0.80032184 0.58999845 -0.11094844 -1.08390961 -0.12122098 0.28893619
[49] 2.06721705 -0.43494015 -0.57999958 1.76882407 -0.14084635 -0.61552573
[55] -1.21340380 0.68797807 0.33643606 -0.23501559 0.72972627 -0.21851234
[61] 1.97953963 -0.31097627 1.44228762 -0.59970428 0.68329460 0.71369456
[67] -1.29860050 0.25237063 -0.11678912 -1.01885852 -1.56038429 1.69765417
[73] 0.88039799 0.57459493 -0.58804709 0.47018859 -1.68687273 1.68158842
[79] -0.75137253 -0.18452063 -0.23672605 -1.61558972 -0.25474638 -0.29767975
[85] 0.48338042 -0.01523795 -1.22368573 -0.76719948 -0.65335889 0.52917702
[91] 1.00601826 1.11301161 -1.06666093 -0.20463338 1.03885219 0.45748027
[97] 0.27067405 0.67631440 1.86171725 -1.53903966
>
> colMeans(tmp2)
[1] -0.1072866
> colSums(tmp2)
[1] -10.72866
> colVars(tmp2)
[1] 1.148566
> colSd(tmp2)
[1] 1.071712
> colMax(tmp2)
[1] 2.647963
> colMin(tmp2)
[1] -2.720067
> colMedians(tmp2)
[1] -0.1495658
> colRanges(tmp2)
[,1]
[1,] -2.720067
[2,] 2.647963
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.2178179 -1.0640523 -1.6129335 -1.0348891 -1.2601096 1.9524395
[7] 0.6894016 0.2786049 4.5809478 9.9802018
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.03475692
[2,] -0.43468496
[3,] 0.04043802
[4,] 1.16992468
[5,] 2.16106958
>
> rowApply(tmp,sum)
[1] 4.7948692 -5.3924171 1.8054489 2.3471928 2.6038978 -0.8272535
[7] 5.8479150 5.3506478 -1.6732938 -0.1295780
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 1 4 4 5 2 4 10 9 9
[2,] 8 2 8 2 3 9 8 5 1 4
[3,] 6 7 5 3 4 5 3 1 8 1
[4,] 5 4 1 6 7 8 9 3 3 5
[5,] 9 3 2 8 6 4 1 2 5 7
[6,] 3 10 7 9 1 6 7 6 2 2
[7,] 4 8 3 1 9 3 10 9 4 8
[8,] 2 6 6 10 8 1 2 8 7 6
[9,] 1 9 9 5 2 7 6 4 6 10
[10,] 10 5 10 7 10 10 5 7 10 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.2421110 0.4358652 3.7242459 1.6840004 0.9890459 -1.2483088
[7] 1.1087945 -0.5699861 1.7612427 1.8067819 0.6373490 -3.2500554
[13] 0.2310277 -4.0787048 4.8765610 2.4940986 -3.6135898 3.2288488
[19] 0.8911032 0.1901354
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.23587841
[2,] -0.78511714
[3,] -0.05266058
[4,] 0.76187818
[5,] 1.06966692
>
> rowApply(tmp,sum)
[1] -1.6009490 2.1932747 5.4263789 -0.5456425 5.5832823
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 2 6 17 17
[2,] 14 9 9 5 16
[3,] 20 11 8 19 4
[4,] 18 4 10 14 13
[5,] 16 18 17 2 1
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.78511714 0.04105900 2.5965271 1.6121390 0.8163015 -0.9954248
[2,] -1.23587841 -0.01881869 0.2698928 -1.0176995 1.1347178 0.7489206
[3,] -0.05266058 0.26217194 0.2044584 0.4249347 1.1757209 -1.0387178
[4,] 0.76187818 -0.85968347 1.0628844 0.3572006 -1.5246915 0.3358788
[5,] 1.06966692 1.01113643 -0.4095167 0.3074256 -0.6130027 -0.2989656
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.13822339 -1.23762427 -0.1912875 1.1576519 -0.8690012 -2.99508492
[2,] 1.10373009 -0.05728014 0.5084391 0.7129011 0.2836289 -1.19213981
[3,] -0.48054427 1.00121406 0.4482124 0.5881088 1.9740128 0.42955184
[4,] -0.07560125 -0.08023479 -0.1804266 -0.8022098 -0.3146991 0.53821901
[5,] 0.69943335 -0.19606100 1.1763053 0.1503300 -0.4365924 -0.03060146
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.09222305 -1.3988181 1.965845 -0.4157382 -0.1714630 -0.09227926
[2,] 1.65863056 -0.5140882 1.148233 -0.1414982 -1.8128245 0.15175131
[3,] 0.59367018 -2.2328510 1.334202 2.3489768 -0.9070981 0.55591864
[4,] -1.74203677 -0.2252337 -1.115535 0.4782323 -1.2315892 1.02706776
[5,] -0.18701326 0.2922863 1.543816 0.2241259 0.5093850 1.58639034
[,19] [,20]
[1,] 0.3377225 -0.7459101
[2,] -0.3836664 0.8463235
[3,] -1.3539901 0.1510873
[4,] 2.8826484 0.1622897
[5,] -0.5916111 -0.2236549
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.222748 -0.3000053 -0.4378374 -0.9135632 0.3200198 3.280762 -1.417184
col8 col9 col10 col11 col12 col13
row1 -0.7513473 -0.8570386 0.6148263 -0.9408487 -1.132483 0.03673514
col14 col15 col16 col17 col18 col19 col20
row1 -0.02816072 -0.6936092 0.4071357 0.1317845 0.9256717 0.5806192 -1.312708
> tmp[,"col10"]
col10
row1 0.6148263
row2 -0.6125731
row3 -1.6633089
row4 2.6202150
row5 0.9370316
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.222748 -0.3000053 -0.4378374 -0.9135632 0.3200198 3.2807622 -1.417184
row5 1.635520 0.2820295 0.1205560 -1.1967548 1.5943898 0.5186609 1.332240
col8 col9 col10 col11 col12 col13
row1 -0.7513473 -0.8570386 0.6148263 -0.94084869 -1.1324833 0.03673514
row5 1.7605314 1.0149941 0.9370316 -0.06984413 0.9071715 0.41482934
col14 col15 col16 col17 col18 col19 col20
row1 -0.02816072 -0.6936092 0.4071357 0.1317845 0.9256717 0.5806192 -1.312708
row5 -1.72253544 0.6220618 0.3614583 0.4845441 -1.6766593 -0.9269973 1.389042
> tmp[,c("col6","col20")]
col6 col20
row1 3.2807622 -1.3127085
row2 0.4900725 0.1319621
row3 -2.0119045 0.5291618
row4 1.1870937 -0.5831389
row5 0.5186609 1.3890421
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 3.2807622 -1.312708
row5 0.5186609 1.389042
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.39677 50.77876 50.62065 48.42797 51.32804 102.3427 50.69771 52.12347
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.39505 49.46691 49.62067 50.70682 49.93873 51.06342 49.92352 50.94571
col17 col18 col19 col20
row1 49.47356 50.28416 49.48338 104.6171
> tmp[,"col10"]
col10
row1 49.46691
row2 30.72060
row3 28.54506
row4 30.82934
row5 48.73266
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.39677 50.77876 50.62065 48.42797 51.32804 102.3427 50.69771 52.12347
row5 50.25413 50.61369 47.45518 50.04820 49.76578 104.7902 50.07838 48.33518
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.39505 49.46691 49.62067 50.70682 49.93873 51.06342 49.92352 50.94571
row5 50.75876 48.73266 47.61481 48.37474 49.68861 50.07128 50.91711 48.91332
col17 col18 col19 col20
row1 49.47356 50.28416 49.48338 104.6171
row5 48.91512 50.88843 50.18454 105.5271
> tmp[,c("col6","col20")]
col6 col20
row1 102.34274 104.61709
row2 75.32467 75.78275
row3 74.96509 73.14085
row4 72.12814 74.82948
row5 104.79024 105.52707
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 102.3427 104.6171
row5 104.7902 105.5271
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 102.3427 104.6171
row5 104.7902 105.5271
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 2.0178162
[2,] -1.9131292
[3,] 0.8102917
[4,] 2.2450589
[5,] 0.3651062
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.2871180 0.6618062
[2,] 0.4472589 -0.6000962
[3,] -1.2326368 0.3422676
[4,] 0.2413675 0.3004906
[5,] 1.9635680 0.3170963
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.13689179 -0.2497600
[2,] 0.51647750 0.4944915
[3,] -0.08961904 0.7368653
[4,] -1.89347070 -1.3100413
[5,] 0.10900751 0.3030849
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.1368918
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.1368918
[2,] 0.5164775
>
>
>
> 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 -0.1320936 0.2491213 -0.5267734 1.282402 0.75219856 -0.5545285 -0.8082629
row1 0.6516711 1.5731855 -0.5713141 2.703897 -0.01277568 -0.3618323 -0.1989692
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -0.8370801 0.6669249 -0.7577099 -0.7236740 1.0199367 -1.947180 0.9534150
row1 1.1665127 1.1745952 0.5351408 -0.2709935 0.2331814 -1.523571 -0.4595468
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.7932879 0.2870315 0.5387687 -1.159929 0.95810929 -0.4841378
row1 -0.7480876 -0.4542487 -0.8436719 -2.035341 -0.04897374 0.2246486
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.7102781 0.8204417 -0.7502694 0.5000096 -0.2060868 -0.377759 0.6139101
[,8] [,9] [,10]
row2 -0.3202153 -0.6780956 0.873702
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -2.578102 -0.1787162 -0.4418839 0.481318 0.2304905 0.966169 -1.064972
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.1248608 0.5944278 -0.5902447 1.000019 1.930557 -0.2330155 2.277163
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.5424601 1.124624 1.569597 1.315569 0.6752123 0.1809992
>
>
> 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: 0x39e03c90>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b362a2c95fb6d"
[2] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b362a53566d98"
[3] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b362a172d0662"
[4] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b362a77b7f0f9"
[5] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b362a54f41e9"
[6] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b362a18afe5da"
[7] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b362a6d3273a5"
[8] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b362a1637ad83"
[9] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b362a6572d422"
[10] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b362a55a6c6b5"
[11] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b362a10c77992"
[12] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b362a26953981"
[13] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b362a109da841"
[14] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b362a2d04a472"
[15] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1b362a709a33a5"
>
>
> ### 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: 0x39cf0180>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x39cf0180>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x39cf0180>
> rowMedians(tmp)
[1] 0.1356979535 0.1380520531 -0.0174764362 0.3800054102 0.0359458054
[6] -0.0809947047 -0.3018372784 -0.1242583653 0.0805514676 -0.0007250176
[11] -0.0610530345 -0.2584074414 0.1659644993 0.2021779265 -0.3094302654
[16] 0.1979273046 -0.2897219571 0.1525751660 -0.4973429901 0.0658975856
[21] 0.2946399823 -0.1738416372 0.0452869726 0.0175020629 -0.5484687182
[26] -0.2165451947 -0.1170404675 0.4249662442 -0.3288425705 -0.1751994415
[31] -0.2508308783 -0.2676055855 0.1734657813 0.3324962392 0.2116802937
[36] -0.3465648032 -0.3848665323 0.4764522068 -0.0590523263 0.3420699476
[41] -0.4017666397 0.0538714466 -0.2301766308 0.2515970749 0.1525044702
[46] 0.2959637059 0.9992980201 0.4147850510 -0.2861455271 0.0195373805
[51] 0.0028257960 0.2412807533 -0.2353013270 -0.0275252953 -0.1897041729
[56] -0.3122403434 -0.0897903220 -0.3109365432 -0.0992720425 0.4923416169
[61] 0.1242491857 -0.1101919822 0.4370842205 0.4676699040 0.2445292081
[66] 0.1048943724 -0.3997651042 -0.4150241259 -0.3505566395 -0.7024414815
[71] -0.0927054986 0.4865546760 -0.0805241516 -0.4021265988 0.0350101130
[76] 0.0752846093 0.6591468938 -0.6208922757 -0.3484504121 -0.1512993059
[81] 0.2027805831 0.1827062694 -0.5210989581 -0.1535886138 0.3896762698
[86] -0.2871227686 0.1210525728 0.0974242901 0.2660228191 0.2266889233
[91] -0.2147991130 0.0475730301 -0.3493731680 -0.0551791776 0.1807284333
[96] -0.2551416973 0.2474817694 -0.4422058388 -0.3876508137 -0.0872551035
[101] -0.1791441522 -0.5730788485 0.2454880988 -0.0336518590 0.4465706643
[106] 0.4799747752 0.1864064513 0.1623666342 -0.1332847701 0.3355448829
[111] 0.1076101012 -0.2765946267 0.1703945420 -0.2470347250 0.0020229841
[116] 0.3231008326 0.0624342679 0.0710405049 -0.1611920509 0.0586269645
[121] -0.1691823646 -0.2745102446 0.5980482963 -0.0515258762 -0.3940233405
[126] 0.1181346268 -0.3511246184 -0.2676533141 -0.1470421292 0.3476466561
[131] -0.0709173602 -0.3693254895 -0.0223916380 -0.1091114083 0.1185582027
[136] -0.0942839721 -0.2139674826 -0.2936778009 -0.3468768000 -0.4907579545
[141] -0.0522215998 0.2404447496 0.2052124028 0.1475276415 0.3034862984
[146] 0.1923290699 0.2644041734 0.4584429567 -0.3980436287 -0.3616602700
[151] 0.4181387984 0.2787525459 0.1051746550 -0.1184547391 0.3473541128
[156] 0.1730625076 -0.1805745009 -0.1937323390 0.1296596594 -0.4016867995
[161] 0.4286916401 -0.0694975037 0.3177540704 0.4819243390 0.0746925028
[166] 0.2347563573 0.1041593441 -0.3868830572 0.3113799421 -0.2901207185
[171] -0.2722337129 -0.2367370397 0.1883513878 -0.4729114020 -0.3580882986
[176] 0.4290183342 -0.2297919302 0.3424398216 -0.3627871001 0.1749999933
[181] -0.1117463696 0.1489451846 -0.0958000186 0.7455031586 0.2002229155
[186] -0.1144190706 0.1307079126 -0.1681079659 -0.2791198636 -0.2931363898
[191] 0.3230985257 0.2880951527 0.2147765410 -0.1907569526 -0.0372810601
[196] 0.4215205693 -0.1657285589 -0.1162939758 -0.4220316825 -0.3185776233
[201] -0.1625939522 -0.2603052565 0.1985249844 0.1892840544 0.0300059306
[206] -0.0929765944 0.4460419689 0.3383818937 0.2326838489 0.8887921969
[211] 0.1876983316 0.2209557999 0.3180448644 0.4883456583 0.5063939575
[216] -0.0990456427 0.4645537453 -0.0205007592 -0.2988871246 0.3424948752
[221] 0.0842578658 0.0031026336 0.3949173321 0.2007206004 0.2788457534
[226] -0.4728395717 0.0078034670 0.2817089244 -0.0500936352 -0.3419308402
>
> proc.time()
user system elapsed
1.938 0.836 2.801
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: 0x36bfc6e0>
> .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: 0x36bfc6e0>
> .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: 0x36bfc6e0>
> .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: 0x36bfc6e0>
> 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: 0x36c446a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x36c446a0>
> .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: 0x36c446a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x36c446a0>
> .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: 0x36c446a0>
> 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: 0x35e007d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x35e007d0>
> .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: 0x35e007d0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x35e007d0>
> .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: 0x35e007d0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x35e007d0>
> .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: 0x35e007d0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x35e007d0>
> .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: 0x35e007d0>
> 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: 0x3695fd70>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x3695fd70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3695fd70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3695fd70>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1b364218a109c9" "BufferedMatrixFile1b3642cb2cbee"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1b364218a109c9" "BufferedMatrixFile1b3642cb2cbee"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x36502cd0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x36502cd0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x36502cd0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x36502cd0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x36502cd0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x36502cd0>
> .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: 0x35471a10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x35471a10>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x35471a10>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x35471a10>
> 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: 0x3738bcc0>
> .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: 0x3738bcc0>
> rm(P)
>
> proc.time()
user system elapsed
0.341 0.057 0.385
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
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Platform: aarch64-unknown-linux-gnu
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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
0.314 0.057 0.359