Ben Bolstad
| Snapshot Date: 2025-09-25 13:40 -0400 (Thu, 25 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 2025-09-29 11:41 -0400 (Mon, 29 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" | 4580 |
| 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: 2025-09-26 08:40:51 -0000 (Fri, 26 Sep 2025) |
| EndedAt: 2025-09-26 08:41:15 -0000 (Fri, 26 Sep 2025) |
| EllapsedTime: 24.0 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 0.044 0.368
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 Sep 26 08:41:09 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Sep 26 08:41:09 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: 0x4d7e6e0>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Sep 26 08:41:10 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Sep 26 08:41:10 2025"
>
> ColMode(tmp2)
<pointer: 0x4d7e6e0>
>
>
>
> ### 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,] 99.9405235 -0.16918930 0.03810670 1.8943219
[2,] -1.1648290 0.40565366 -0.17109657 1.2388776
[3,] 0.5993933 -0.03607926 0.04244763 0.8892439
[4,] 0.5589440 1.62157441 -0.32522830 -0.7823417
> 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,] 99.9405235 0.16918930 0.03810670 1.8943219
[2,] 1.1648290 0.40565366 0.17109657 1.2388776
[3,] 0.5993933 0.03607926 0.04244763 0.8892439
[4,] 0.5589440 1.62157441 0.32522830 0.7823417
> 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,] 9.9970257 0.4113263 0.1952094 1.3763437
[2,] 1.0792725 0.6369095 0.4136382 1.1130488
[3,] 0.7742049 0.1899454 0.2060282 0.9429973
[4,] 0.7476256 1.2734105 0.5702879 0.8845008
>
> 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,] 224.91078 29.28245 26.99020 40.65776
[2,] 36.95755 31.77475 29.30748 37.36937
[3,] 33.34144 26.93553 27.10273 35.31922
[4,] 33.03520 39.35568 31.02811 34.62735
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x3356520>
> exp(tmp5)
<pointer: 0x3356520>
> log(tmp5,2)
<pointer: 0x3356520>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.1223
> Min(tmp5)
[1] 53.67589
> mean(tmp5)
[1] 73.46643
> Sum(tmp5)
[1] 14693.29
> Var(tmp5)
[1] 866.5008
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.90893 70.73646 71.22437 71.42405 76.75539 66.54825 73.75417 69.91327
[9] 68.38381 75.01564
> rowSums(tmp5)
[1] 1818.179 1414.729 1424.487 1428.481 1535.108 1330.965 1475.083 1398.265
[9] 1367.676 1500.313
> rowVars(tmp5)
[1] 7965.48343 49.08849 94.19443 73.05370 78.40744 70.68148
[7] 86.25681 98.31137 48.26852 69.06715
> rowSd(tmp5)
[1] 89.249557 7.006318 9.705381 8.547146 8.854797 8.407228 9.287454
[8] 9.915209 6.947555 8.310665
> rowMax(tmp5)
[1] 468.12232 83.41378 89.63719 85.86429 89.70370 84.39170 97.07744
[8] 87.16219 78.97046 87.58656
> rowMin(tmp5)
[1] 56.17657 60.99968 56.06278 55.35332 57.61847 53.97807 59.27167 56.54149
[9] 53.67589 54.94976
>
> colMeans(tmp5)
[1] 109.74631 70.81487 69.28598 75.03746 67.86062 71.42262 72.05749
[8] 70.02897 67.59702 75.95992 67.57166 70.30311 72.10547 72.41008
[15] 76.18008 67.93845 73.68597 73.26848 72.64057 73.41356
> colSums(tmp5)
[1] 1097.4631 708.1487 692.8598 750.3746 678.6062 714.2262 720.5749
[8] 700.2897 675.9702 759.5992 675.7166 703.0311 721.0547 724.1008
[15] 761.8008 679.3845 736.8597 732.6848 726.4057 734.1356
> colVars(tmp5)
[1] 15882.81846 67.44677 93.73069 41.78652 56.98220 62.22370
[7] 50.97074 104.22295 133.86422 156.02896 118.59388 80.17270
[13] 70.54190 85.50836 99.11493 79.22442 151.33942 19.49813
[19] 49.30419 67.37424
> colSd(tmp5)
[1] 126.027054 8.212598 9.681461 6.464250 7.548656 7.888200
[7] 7.139379 10.208964 11.569971 12.491155 10.890082 8.953921
[13] 8.398922 9.247073 9.955648 8.900810 12.302009 4.415668
[19] 7.021694 8.208181
> colMax(tmp5)
[1] 468.12232 81.91369 85.20431 84.62380 81.11544 89.70370 83.78946
[8] 86.25507 85.77013 97.07744 85.29462 81.01603 89.65960 83.41378
[15] 84.39170 82.71807 87.58656 84.00999 81.88549 82.46980
> colMin(tmp5)
[1] 63.26655 56.06278 56.17657 64.86896 54.75045 63.00203 59.42151 57.64789
[9] 53.67589 57.40539 54.19764 53.97807 63.23997 57.68870 56.54149 56.50933
[17] 55.35332 67.12622 63.39354 59.13463
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 90.90893 70.73646 71.22437 NA 76.75539 66.54825 73.75417 69.91327
[9] 68.38381 75.01564
> rowSums(tmp5)
[1] 1818.179 1414.729 1424.487 NA 1535.108 1330.965 1475.083 1398.265
[9] 1367.676 1500.313
> rowVars(tmp5)
[1] 7965.48343 49.08849 94.19443 64.91806 78.40744 70.68148
[7] 86.25681 98.31137 48.26852 69.06715
> rowSd(tmp5)
[1] 89.249557 7.006318 9.705381 8.057175 8.854797 8.407228 9.287454
[8] 9.915209 6.947555 8.310665
> rowMax(tmp5)
[1] 468.12232 83.41378 89.63719 NA 89.70370 84.39170 97.07744
[8] 87.16219 78.97046 87.58656
> rowMin(tmp5)
[1] 56.17657 60.99968 56.06278 NA 57.61847 53.97807 59.27167 56.54149
[9] 53.67589 54.94976
>
> colMeans(tmp5)
[1] 109.74631 70.81487 69.28598 75.03746 67.86062 71.42262 72.05749
[8] 70.02897 67.59702 NA 67.57166 70.30311 72.10547 72.41008
[15] 76.18008 67.93845 73.68597 73.26848 72.64057 73.41356
> colSums(tmp5)
[1] 1097.4631 708.1487 692.8598 750.3746 678.6062 714.2262 720.5749
[8] 700.2897 675.9702 NA 675.7166 703.0311 721.0547 724.1008
[15] 761.8008 679.3845 736.8597 732.6848 726.4057 734.1356
> colVars(tmp5)
[1] 15882.81846 67.44677 93.73069 41.78652 56.98220 62.22370
[7] 50.97074 104.22295 133.86422 NA 118.59388 80.17270
[13] 70.54190 85.50836 99.11493 79.22442 151.33942 19.49813
[19] 49.30419 67.37424
> colSd(tmp5)
[1] 126.027054 8.212598 9.681461 6.464250 7.548656 7.888200
[7] 7.139379 10.208964 11.569971 NA 10.890082 8.953921
[13] 8.398922 9.247073 9.955648 8.900810 12.302009 4.415668
[19] 7.021694 8.208181
> colMax(tmp5)
[1] 468.12232 81.91369 85.20431 84.62380 81.11544 89.70370 83.78946
[8] 86.25507 85.77013 NA 85.29462 81.01603 89.65960 83.41378
[15] 84.39170 82.71807 87.58656 84.00999 81.88549 82.46980
> colMin(tmp5)
[1] 63.26655 56.06278 56.17657 64.86896 54.75045 63.00203 59.42151 57.64789
[9] 53.67589 NA 54.19764 53.97807 63.23997 57.68870 56.54149 56.50933
[17] 55.35332 67.12622 63.39354 59.13463
>
> Max(tmp5,na.rm=TRUE)
[1] 468.1223
> Min(tmp5,na.rm=TRUE)
[1] 53.67589
> mean(tmp5,na.rm=TRUE)
[1] 73.40413
> Sum(tmp5,na.rm=TRUE)
[1] 14607.42
> Var(tmp5,na.rm=TRUE)
[1] 870.0969
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.90893 70.73646 71.22437 70.66404 76.75539 66.54825 73.75417 69.91327
[9] 68.38381 75.01564
> rowSums(tmp5,na.rm=TRUE)
[1] 1818.179 1414.729 1424.487 1342.617 1535.108 1330.965 1475.083 1398.265
[9] 1367.676 1500.313
> rowVars(tmp5,na.rm=TRUE)
[1] 7965.48343 49.08849 94.19443 64.91806 78.40744 70.68148
[7] 86.25681 98.31137 48.26852 69.06715
> rowSd(tmp5,na.rm=TRUE)
[1] 89.249557 7.006318 9.705381 8.057175 8.854797 8.407228 9.287454
[8] 9.915209 6.947555 8.310665
> rowMax(tmp5,na.rm=TRUE)
[1] 468.12232 83.41378 89.63719 84.05366 89.70370 84.39170 97.07744
[8] 87.16219 78.97046 87.58656
> rowMin(tmp5,na.rm=TRUE)
[1] 56.17657 60.99968 56.06278 55.35332 57.61847 53.97807 59.27167 56.54149
[9] 53.67589 54.94976
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.74631 70.81487 69.28598 75.03746 67.86062 71.42262 72.05749
[8] 70.02897 67.59702 74.85944 67.57166 70.30311 72.10547 72.41008
[15] 76.18008 67.93845 73.68597 73.26848 72.64057 73.41356
> colSums(tmp5,na.rm=TRUE)
[1] 1097.4631 708.1487 692.8598 750.3746 678.6062 714.2262 720.5749
[8] 700.2897 675.9702 673.7349 675.7166 703.0311 721.0547 724.1008
[15] 761.8008 679.3845 736.8597 732.6848 726.4057 734.1356
> colVars(tmp5,na.rm=TRUE)
[1] 15882.81846 67.44677 93.73069 41.78652 56.98220 62.22370
[7] 50.97074 104.22295 133.86422 161.90807 118.59388 80.17270
[13] 70.54190 85.50836 99.11493 79.22442 151.33942 19.49813
[19] 49.30419 67.37424
> colSd(tmp5,na.rm=TRUE)
[1] 126.027054 8.212598 9.681461 6.464250 7.548656 7.888200
[7] 7.139379 10.208964 11.569971 12.724310 10.890082 8.953921
[13] 8.398922 9.247073 9.955648 8.900810 12.302009 4.415668
[19] 7.021694 8.208181
> colMax(tmp5,na.rm=TRUE)
[1] 468.12232 81.91369 85.20431 84.62380 81.11544 89.70370 83.78946
[8] 86.25507 85.77013 97.07744 85.29462 81.01603 89.65960 83.41378
[15] 84.39170 82.71807 87.58656 84.00999 81.88549 82.46980
> colMin(tmp5,na.rm=TRUE)
[1] 63.26655 56.06278 56.17657 64.86896 54.75045 63.00203 59.42151 57.64789
[9] 53.67589 57.40539 54.19764 53.97807 63.23997 57.68870 56.54149 56.50933
[17] 55.35332 67.12622 63.39354 59.13463
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.90893 70.73646 71.22437 NaN 76.75539 66.54825 73.75417 69.91327
[9] 68.38381 75.01564
> rowSums(tmp5,na.rm=TRUE)
[1] 1818.179 1414.729 1424.487 0.000 1535.108 1330.965 1475.083 1398.265
[9] 1367.676 1500.313
> rowVars(tmp5,na.rm=TRUE)
[1] 7965.48343 49.08849 94.19443 NA 78.40744 70.68148
[7] 86.25681 98.31137 48.26852 69.06715
> rowSd(tmp5,na.rm=TRUE)
[1] 89.249557 7.006318 9.705381 NA 8.854797 8.407228 9.287454
[8] 9.915209 6.947555 8.310665
> rowMax(tmp5,na.rm=TRUE)
[1] 468.12232 83.41378 89.63719 NA 89.70370 84.39170 97.07744
[8] 87.16219 78.97046 87.58656
> rowMin(tmp5,na.rm=TRUE)
[1] 56.17657 60.99968 56.06278 NA 57.61847 53.97807 59.27167 56.54149
[9] 53.67589 54.94976
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.30052 69.58167 69.80876 75.36693 67.11225 71.17802 71.70767
[8] 70.98814 68.22169 NaN 67.31807 69.65846 72.42010 73.54872
[15] 75.30524 68.68559 75.72294 73.64093 71.81874 72.62345
> colSums(tmp5,na.rm=TRUE)
[1] 1028.7046 626.2350 628.2788 678.3023 604.0102 640.6021 645.3690
[8] 638.8932 613.9952 0.0000 605.8626 626.9261 651.7809 661.9385
[15] 677.7471 618.1703 681.5064 662.7684 646.3686 653.6110
> colVars(tmp5,na.rm=TRUE)
[1] 17634.83669 58.76874 102.37239 45.78870 57.80435 69.32858
[7] 55.96538 106.90076 146.20733 NA 132.69465 85.51912
[13] 78.24598 81.61115 102.89412 82.84755 123.57819 20.37477
[19] 47.86886 68.77290
> colSd(tmp5,na.rm=TRUE)
[1] 132.796222 7.666077 10.117924 6.766735 7.602917 8.326379
[7] 7.481002 10.339282 12.091622 NA 11.519316 9.247655
[13] 8.845676 9.033889 10.143674 9.102063 11.116573 4.513842
[19] 6.918732 8.292943
> colMax(tmp5,na.rm=TRUE)
[1] 468.12232 80.89309 85.20431 84.62380 81.11544 89.70370 83.78946
[8] 86.25507 85.77013 -Inf 85.29462 81.01603 89.65960 83.41378
[15] 84.39170 82.71807 87.58656 84.00999 81.88549 82.46980
> colMin(tmp5,na.rm=TRUE)
[1] 63.26655 56.06278 56.17657 64.86896 54.75045 63.00203 59.42151 57.64789
[9] 53.67589 Inf 54.19764 53.97807 63.23997 57.68870 56.54149 56.50933
[17] 57.61847 67.12622 63.39354 59.13463
>
>
>
>
> 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] 281.5098 238.1701 170.2466 152.5640 253.2127 135.4348 279.7686 108.3876
[9] 484.1268 190.6632
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 281.5098 238.1701 170.2466 152.5640 253.2127 135.4348 279.7686 108.3876
[9] 484.1268 190.6632
>
>
>
> 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] -8.526513e-14 2.842171e-13 0.000000e+00 4.263256e-14 -5.684342e-14
[6] -2.842171e-14 -1.989520e-13 -2.842171e-14 -5.684342e-14 5.684342e-14
[11] -2.842171e-14 -8.526513e-14 -1.421085e-13 0.000000e+00 1.705303e-13
[16] 0.000000e+00 -2.842171e-14 8.526513e-14 -1.136868e-13 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)
+ }
10 5
8 9
9 11
4 15
7 6
6 7
5 19
9 2
9 5
10 7
2 14
10 14
4 2
1 12
3 12
8 7
4 10
1 12
1 19
9 6
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] 2.345303
> Min(tmp)
[1] -1.730504
> mean(tmp)
[1] -0.1310281
> Sum(tmp)
[1] -13.10281
> Var(tmp)
[1] 0.764912
>
> rowMeans(tmp)
[1] -0.1310281
> rowSums(tmp)
[1] -13.10281
> rowVars(tmp)
[1] 0.764912
> rowSd(tmp)
[1] 0.8745925
> rowMax(tmp)
[1] 2.345303
> rowMin(tmp)
[1] -1.730504
>
> colMeans(tmp)
[1] 1.008366860 -0.660223364 -0.731874816 -1.600511843 -0.726895955
[6] -0.773116738 1.137189255 1.005466620 -0.748645838 1.282169133
[11] -0.087082535 -0.086680636 -1.094002457 1.505114111 -1.019362678
[16] -1.295805848 0.352702192 0.216368219 0.292958439 -1.419715004
[21] 0.121582550 -0.585383212 0.066332825 1.901214619 0.925064184
[26] -1.161820824 1.134249549 -0.674626272 0.168486641 -0.322001490
[31] -1.207697709 -1.380877102 -1.041245248 0.650395835 -0.898665212
[36] -0.279240257 -0.204305784 -0.422938358 1.423203793 0.191251409
[41] -0.006559531 -0.243502474 -0.869982269 -0.181879795 -1.068360281
[46] -1.012797250 -0.745638273 0.424433239 0.887253619 0.382453091
[51] 0.031444725 -0.347772650 -1.225926689 -1.730504284 -0.269208626
[56] 0.005994374 -1.002678446 0.185127169 0.765549936 1.844200143
[61] -0.085365194 0.194945468 0.408103150 0.518909927 -0.858581107
[66] -0.504214482 -1.575527826 0.782700380 -1.037705977 -1.171474702
[71] -1.064099843 -0.547789302 -1.341071030 0.574166852 -0.067217270
[76] 0.217187172 -0.145073727 0.411606773 -0.095351999 -0.414048279
[81] -0.012071631 0.481374732 0.644976502 0.612140101 -0.350488896
[86] 0.510780369 -0.563299708 -0.373112267 0.917033381 1.547131231
[91] -0.688939239 -0.247871708 -1.668748171 -1.079038072 0.080269353
[96] 0.739135583 -1.022820157 2.345302767 -0.528416745 0.572706763
> colSums(tmp)
[1] 1.008366860 -0.660223364 -0.731874816 -1.600511843 -0.726895955
[6] -0.773116738 1.137189255 1.005466620 -0.748645838 1.282169133
[11] -0.087082535 -0.086680636 -1.094002457 1.505114111 -1.019362678
[16] -1.295805848 0.352702192 0.216368219 0.292958439 -1.419715004
[21] 0.121582550 -0.585383212 0.066332825 1.901214619 0.925064184
[26] -1.161820824 1.134249549 -0.674626272 0.168486641 -0.322001490
[31] -1.207697709 -1.380877102 -1.041245248 0.650395835 -0.898665212
[36] -0.279240257 -0.204305784 -0.422938358 1.423203793 0.191251409
[41] -0.006559531 -0.243502474 -0.869982269 -0.181879795 -1.068360281
[46] -1.012797250 -0.745638273 0.424433239 0.887253619 0.382453091
[51] 0.031444725 -0.347772650 -1.225926689 -1.730504284 -0.269208626
[56] 0.005994374 -1.002678446 0.185127169 0.765549936 1.844200143
[61] -0.085365194 0.194945468 0.408103150 0.518909927 -0.858581107
[66] -0.504214482 -1.575527826 0.782700380 -1.037705977 -1.171474702
[71] -1.064099843 -0.547789302 -1.341071030 0.574166852 -0.067217270
[76] 0.217187172 -0.145073727 0.411606773 -0.095351999 -0.414048279
[81] -0.012071631 0.481374732 0.644976502 0.612140101 -0.350488896
[86] 0.510780369 -0.563299708 -0.373112267 0.917033381 1.547131231
[91] -0.688939239 -0.247871708 -1.668748171 -1.079038072 0.080269353
[96] 0.739135583 -1.022820157 2.345302767 -0.528416745 0.572706763
> 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] 1.008366860 -0.660223364 -0.731874816 -1.600511843 -0.726895955
[6] -0.773116738 1.137189255 1.005466620 -0.748645838 1.282169133
[11] -0.087082535 -0.086680636 -1.094002457 1.505114111 -1.019362678
[16] -1.295805848 0.352702192 0.216368219 0.292958439 -1.419715004
[21] 0.121582550 -0.585383212 0.066332825 1.901214619 0.925064184
[26] -1.161820824 1.134249549 -0.674626272 0.168486641 -0.322001490
[31] -1.207697709 -1.380877102 -1.041245248 0.650395835 -0.898665212
[36] -0.279240257 -0.204305784 -0.422938358 1.423203793 0.191251409
[41] -0.006559531 -0.243502474 -0.869982269 -0.181879795 -1.068360281
[46] -1.012797250 -0.745638273 0.424433239 0.887253619 0.382453091
[51] 0.031444725 -0.347772650 -1.225926689 -1.730504284 -0.269208626
[56] 0.005994374 -1.002678446 0.185127169 0.765549936 1.844200143
[61] -0.085365194 0.194945468 0.408103150 0.518909927 -0.858581107
[66] -0.504214482 -1.575527826 0.782700380 -1.037705977 -1.171474702
[71] -1.064099843 -0.547789302 -1.341071030 0.574166852 -0.067217270
[76] 0.217187172 -0.145073727 0.411606773 -0.095351999 -0.414048279
[81] -0.012071631 0.481374732 0.644976502 0.612140101 -0.350488896
[86] 0.510780369 -0.563299708 -0.373112267 0.917033381 1.547131231
[91] -0.688939239 -0.247871708 -1.668748171 -1.079038072 0.080269353
[96] 0.739135583 -1.022820157 2.345302767 -0.528416745 0.572706763
> colMin(tmp)
[1] 1.008366860 -0.660223364 -0.731874816 -1.600511843 -0.726895955
[6] -0.773116738 1.137189255 1.005466620 -0.748645838 1.282169133
[11] -0.087082535 -0.086680636 -1.094002457 1.505114111 -1.019362678
[16] -1.295805848 0.352702192 0.216368219 0.292958439 -1.419715004
[21] 0.121582550 -0.585383212 0.066332825 1.901214619 0.925064184
[26] -1.161820824 1.134249549 -0.674626272 0.168486641 -0.322001490
[31] -1.207697709 -1.380877102 -1.041245248 0.650395835 -0.898665212
[36] -0.279240257 -0.204305784 -0.422938358 1.423203793 0.191251409
[41] -0.006559531 -0.243502474 -0.869982269 -0.181879795 -1.068360281
[46] -1.012797250 -0.745638273 0.424433239 0.887253619 0.382453091
[51] 0.031444725 -0.347772650 -1.225926689 -1.730504284 -0.269208626
[56] 0.005994374 -1.002678446 0.185127169 0.765549936 1.844200143
[61] -0.085365194 0.194945468 0.408103150 0.518909927 -0.858581107
[66] -0.504214482 -1.575527826 0.782700380 -1.037705977 -1.171474702
[71] -1.064099843 -0.547789302 -1.341071030 0.574166852 -0.067217270
[76] 0.217187172 -0.145073727 0.411606773 -0.095351999 -0.414048279
[81] -0.012071631 0.481374732 0.644976502 0.612140101 -0.350488896
[86] 0.510780369 -0.563299708 -0.373112267 0.917033381 1.547131231
[91] -0.688939239 -0.247871708 -1.668748171 -1.079038072 0.080269353
[96] 0.739135583 -1.022820157 2.345302767 -0.528416745 0.572706763
> colMedians(tmp)
[1] 1.008366860 -0.660223364 -0.731874816 -1.600511843 -0.726895955
[6] -0.773116738 1.137189255 1.005466620 -0.748645838 1.282169133
[11] -0.087082535 -0.086680636 -1.094002457 1.505114111 -1.019362678
[16] -1.295805848 0.352702192 0.216368219 0.292958439 -1.419715004
[21] 0.121582550 -0.585383212 0.066332825 1.901214619 0.925064184
[26] -1.161820824 1.134249549 -0.674626272 0.168486641 -0.322001490
[31] -1.207697709 -1.380877102 -1.041245248 0.650395835 -0.898665212
[36] -0.279240257 -0.204305784 -0.422938358 1.423203793 0.191251409
[41] -0.006559531 -0.243502474 -0.869982269 -0.181879795 -1.068360281
[46] -1.012797250 -0.745638273 0.424433239 0.887253619 0.382453091
[51] 0.031444725 -0.347772650 -1.225926689 -1.730504284 -0.269208626
[56] 0.005994374 -1.002678446 0.185127169 0.765549936 1.844200143
[61] -0.085365194 0.194945468 0.408103150 0.518909927 -0.858581107
[66] -0.504214482 -1.575527826 0.782700380 -1.037705977 -1.171474702
[71] -1.064099843 -0.547789302 -1.341071030 0.574166852 -0.067217270
[76] 0.217187172 -0.145073727 0.411606773 -0.095351999 -0.414048279
[81] -0.012071631 0.481374732 0.644976502 0.612140101 -0.350488896
[86] 0.510780369 -0.563299708 -0.373112267 0.917033381 1.547131231
[91] -0.688939239 -0.247871708 -1.668748171 -1.079038072 0.080269353
[96] 0.739135583 -1.022820157 2.345302767 -0.528416745 0.572706763
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.008367 -0.6602234 -0.7318748 -1.600512 -0.726896 -0.7731167 1.137189
[2,] 1.008367 -0.6602234 -0.7318748 -1.600512 -0.726896 -0.7731167 1.137189
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.005467 -0.7486458 1.282169 -0.08708253 -0.08668064 -1.094002 1.505114
[2,] 1.005467 -0.7486458 1.282169 -0.08708253 -0.08668064 -1.094002 1.505114
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.019363 -1.295806 0.3527022 0.2163682 0.2929584 -1.419715 0.1215826
[2,] -1.019363 -1.295806 0.3527022 0.2163682 0.2929584 -1.419715 0.1215826
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.5853832 0.06633282 1.901215 0.9250642 -1.161821 1.13425 -0.6746263
[2,] -0.5853832 0.06633282 1.901215 0.9250642 -1.161821 1.13425 -0.6746263
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.1684866 -0.3220015 -1.207698 -1.380877 -1.041245 0.6503958 -0.8986652
[2,] 0.1684866 -0.3220015 -1.207698 -1.380877 -1.041245 0.6503958 -0.8986652
[,36] [,37] [,38] [,39] [,40] [,41]
[1,] -0.2792403 -0.2043058 -0.4229384 1.423204 0.1912514 -0.006559531
[2,] -0.2792403 -0.2043058 -0.4229384 1.423204 0.1912514 -0.006559531
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] -0.2435025 -0.8699823 -0.1818798 -1.06836 -1.012797 -0.7456383 0.4244332
[2,] -0.2435025 -0.8699823 -0.1818798 -1.06836 -1.012797 -0.7456383 0.4244332
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] 0.8872536 0.3824531 0.03144473 -0.3477727 -1.225927 -1.730504 -0.2692086
[2,] 0.8872536 0.3824531 0.03144473 -0.3477727 -1.225927 -1.730504 -0.2692086
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] 0.005994374 -1.002678 0.1851272 0.7655499 1.8442 -0.08536519 0.1949455
[2,] 0.005994374 -1.002678 0.1851272 0.7655499 1.8442 -0.08536519 0.1949455
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 0.4081031 0.5189099 -0.8585811 -0.5042145 -1.575528 0.7827004 -1.037706
[2,] 0.4081031 0.5189099 -0.8585811 -0.5042145 -1.575528 0.7827004 -1.037706
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] -1.171475 -1.0641 -0.5477893 -1.341071 0.5741669 -0.06721727 0.2171872
[2,] -1.171475 -1.0641 -0.5477893 -1.341071 0.5741669 -0.06721727 0.2171872
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -0.1450737 0.4116068 -0.095352 -0.4140483 -0.01207163 0.4813747 0.6449765
[2,] -0.1450737 0.4116068 -0.095352 -0.4140483 -0.01207163 0.4813747 0.6449765
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 0.6121401 -0.3504889 0.5107804 -0.5632997 -0.3731123 0.9170334 1.547131
[2,] 0.6121401 -0.3504889 0.5107804 -0.5632997 -0.3731123 0.9170334 1.547131
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -0.6889392 -0.2478717 -1.668748 -1.079038 0.08026935 0.7391356 -1.02282
[2,] -0.6889392 -0.2478717 -1.668748 -1.079038 0.08026935 0.7391356 -1.02282
[,98] [,99] [,100]
[1,] 2.345303 -0.5284167 0.5727068
[2,] 2.345303 -0.5284167 0.5727068
>
>
> Max(tmp2)
[1] 3.22616
> Min(tmp2)
[1] -2.261343
> mean(tmp2)
[1] 0.1672924
> Sum(tmp2)
[1] 16.72924
> Var(tmp2)
[1] 1.020678
>
> rowMeans(tmp2)
[1] -0.843131683 -2.261342518 1.360261944 -0.117251787 0.369379507
[6] -0.796833305 0.573733012 2.281323224 0.300588514 -0.160516493
[11] -0.008116385 2.158702875 0.745587735 -0.630448007 -2.051004343
[16] -0.080734091 0.023203405 -0.782256835 0.598588914 -0.296979622
[21] 1.101818047 -1.152552673 0.045304050 3.226159835 1.190449196
[26] -0.827313198 -0.772841930 -1.196342814 -0.352328218 -0.185303443
[31] -1.836558269 -0.137262758 -0.222192320 -1.442788364 0.730199980
[36] -1.129871280 -0.386922065 1.604000830 -0.589132812 1.070434841
[41] 0.596984563 -0.810392990 1.549871275 1.718052506 0.115980990
[46] 2.054429864 0.741450005 -0.814847962 0.144879415 -0.242694136
[51] -0.126743301 0.189224809 1.323954798 2.686003721 1.012634100
[56] -0.904981479 0.312398695 -2.054034500 -0.952100109 1.063543800
[61] -0.166788719 -0.772386506 0.724961017 0.260234603 0.433613843
[66] -0.084593290 0.738312429 0.614378740 -0.113123237 -0.826814072
[71] 0.748485986 0.262418513 1.017878506 0.306834156 -0.998142008
[76] 0.444142725 1.281368752 -0.411084320 1.079599663 -0.485564222
[81] -0.573476283 -0.267370706 0.302468931 0.692543923 1.026682653
[86] 0.568594933 0.020109781 0.092441568 -0.380364497 0.533465527
[91] 0.441993372 0.967769079 0.487094137 0.141801001 0.175642213
[96] 2.566080642 0.358543919 -0.689539924 0.078883106 -0.591177104
> rowSums(tmp2)
[1] -0.843131683 -2.261342518 1.360261944 -0.117251787 0.369379507
[6] -0.796833305 0.573733012 2.281323224 0.300588514 -0.160516493
[11] -0.008116385 2.158702875 0.745587735 -0.630448007 -2.051004343
[16] -0.080734091 0.023203405 -0.782256835 0.598588914 -0.296979622
[21] 1.101818047 -1.152552673 0.045304050 3.226159835 1.190449196
[26] -0.827313198 -0.772841930 -1.196342814 -0.352328218 -0.185303443
[31] -1.836558269 -0.137262758 -0.222192320 -1.442788364 0.730199980
[36] -1.129871280 -0.386922065 1.604000830 -0.589132812 1.070434841
[41] 0.596984563 -0.810392990 1.549871275 1.718052506 0.115980990
[46] 2.054429864 0.741450005 -0.814847962 0.144879415 -0.242694136
[51] -0.126743301 0.189224809 1.323954798 2.686003721 1.012634100
[56] -0.904981479 0.312398695 -2.054034500 -0.952100109 1.063543800
[61] -0.166788719 -0.772386506 0.724961017 0.260234603 0.433613843
[66] -0.084593290 0.738312429 0.614378740 -0.113123237 -0.826814072
[71] 0.748485986 0.262418513 1.017878506 0.306834156 -0.998142008
[76] 0.444142725 1.281368752 -0.411084320 1.079599663 -0.485564222
[81] -0.573476283 -0.267370706 0.302468931 0.692543923 1.026682653
[86] 0.568594933 0.020109781 0.092441568 -0.380364497 0.533465527
[91] 0.441993372 0.967769079 0.487094137 0.141801001 0.175642213
[96] 2.566080642 0.358543919 -0.689539924 0.078883106 -0.591177104
> 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] -0.843131683 -2.261342518 1.360261944 -0.117251787 0.369379507
[6] -0.796833305 0.573733012 2.281323224 0.300588514 -0.160516493
[11] -0.008116385 2.158702875 0.745587735 -0.630448007 -2.051004343
[16] -0.080734091 0.023203405 -0.782256835 0.598588914 -0.296979622
[21] 1.101818047 -1.152552673 0.045304050 3.226159835 1.190449196
[26] -0.827313198 -0.772841930 -1.196342814 -0.352328218 -0.185303443
[31] -1.836558269 -0.137262758 -0.222192320 -1.442788364 0.730199980
[36] -1.129871280 -0.386922065 1.604000830 -0.589132812 1.070434841
[41] 0.596984563 -0.810392990 1.549871275 1.718052506 0.115980990
[46] 2.054429864 0.741450005 -0.814847962 0.144879415 -0.242694136
[51] -0.126743301 0.189224809 1.323954798 2.686003721 1.012634100
[56] -0.904981479 0.312398695 -2.054034500 -0.952100109 1.063543800
[61] -0.166788719 -0.772386506 0.724961017 0.260234603 0.433613843
[66] -0.084593290 0.738312429 0.614378740 -0.113123237 -0.826814072
[71] 0.748485986 0.262418513 1.017878506 0.306834156 -0.998142008
[76] 0.444142725 1.281368752 -0.411084320 1.079599663 -0.485564222
[81] -0.573476283 -0.267370706 0.302468931 0.692543923 1.026682653
[86] 0.568594933 0.020109781 0.092441568 -0.380364497 0.533465527
[91] 0.441993372 0.967769079 0.487094137 0.141801001 0.175642213
[96] 2.566080642 0.358543919 -0.689539924 0.078883106 -0.591177104
> rowMin(tmp2)
[1] -0.843131683 -2.261342518 1.360261944 -0.117251787 0.369379507
[6] -0.796833305 0.573733012 2.281323224 0.300588514 -0.160516493
[11] -0.008116385 2.158702875 0.745587735 -0.630448007 -2.051004343
[16] -0.080734091 0.023203405 -0.782256835 0.598588914 -0.296979622
[21] 1.101818047 -1.152552673 0.045304050 3.226159835 1.190449196
[26] -0.827313198 -0.772841930 -1.196342814 -0.352328218 -0.185303443
[31] -1.836558269 -0.137262758 -0.222192320 -1.442788364 0.730199980
[36] -1.129871280 -0.386922065 1.604000830 -0.589132812 1.070434841
[41] 0.596984563 -0.810392990 1.549871275 1.718052506 0.115980990
[46] 2.054429864 0.741450005 -0.814847962 0.144879415 -0.242694136
[51] -0.126743301 0.189224809 1.323954798 2.686003721 1.012634100
[56] -0.904981479 0.312398695 -2.054034500 -0.952100109 1.063543800
[61] -0.166788719 -0.772386506 0.724961017 0.260234603 0.433613843
[66] -0.084593290 0.738312429 0.614378740 -0.113123237 -0.826814072
[71] 0.748485986 0.262418513 1.017878506 0.306834156 -0.998142008
[76] 0.444142725 1.281368752 -0.411084320 1.079599663 -0.485564222
[81] -0.573476283 -0.267370706 0.302468931 0.692543923 1.026682653
[86] 0.568594933 0.020109781 0.092441568 -0.380364497 0.533465527
[91] 0.441993372 0.967769079 0.487094137 0.141801001 0.175642213
[96] 2.566080642 0.358543919 -0.689539924 0.078883106 -0.591177104
>
> colMeans(tmp2)
[1] 0.1672924
> colSums(tmp2)
[1] 16.72924
> colVars(tmp2)
[1] 1.020678
> colSd(tmp2)
[1] 1.010286
> colMax(tmp2)
[1] 3.22616
> colMin(tmp2)
[1] -2.261343
> colMedians(tmp2)
[1] 0.128891
> colRanges(tmp2)
[,1]
[1,] -2.261343
[2,] 3.226160
>
> 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] -3.7287788 -1.2682285 0.7847501 3.7767450 -3.8219407 -6.9765803
[7] 4.4046977 1.1189583 -4.3527089 -2.9064128
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5825262
[2,] -0.9055092
[3,] -0.5222159
[4,] 0.1172753
[5,] 1.5039468
>
> rowApply(tmp,sum)
[1] 2.8759150 -2.3634473 0.9349929 -0.2767253 -3.1983835 -5.6275946
[7] 3.3391493 -4.8231833 -3.4849229 -0.3452992
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 10 2 3 4 6 4 4 2 7
[2,] 1 7 7 8 10 8 2 3 5 10
[3,] 7 4 8 7 1 9 10 7 7 3
[4,] 9 6 9 9 9 2 3 5 9 9
[5,] 6 5 1 1 2 5 7 9 3 8
[6,] 2 2 4 5 3 1 5 6 1 5
[7,] 4 9 5 4 8 7 9 10 10 4
[8,] 3 8 3 10 7 3 6 2 8 1
[9,] 8 1 10 2 5 4 8 1 6 6
[10,] 10 3 6 6 6 10 1 8 4 2
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.62963319 -1.09373340 0.32668055 2.82960273 0.39467634 1.77668048
[7] -3.09920493 -3.68273906 1.07898417 -0.51469219 5.59857071 -4.32515211
[13] -0.24850530 1.80638109 -1.06002245 -1.99677329 -4.26543101 0.60029144
[19] 2.21818102 0.09472125
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.34622502
[2,] -0.01726428
[3,] 0.71378463
[4,] 1.09287334
[5,] 1.18646451
>
> rowApply(tmp,sum)
[1] -0.2788715 -0.4855312 1.1273810 1.2916259 -2.5864549
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 17 19 8 9 15
[2,] 7 5 15 16 4
[3,] 15 6 13 18 7
[4,] 19 9 10 14 19
[5,] 18 4 12 7 13
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.09287334 -0.4049660 0.46988904 1.35310565 1.09409427 0.42418556
[2,] 1.18646451 -0.7159144 -0.55318429 -0.01016668 -0.72170545 0.15970896
[3,] -0.34622502 0.4340147 0.06966468 -0.09505828 0.04769254 0.33781989
[4,] -0.01726428 0.5626867 0.97938714 0.45446579 -0.52645086 0.08282449
[5,] 0.71378463 -0.9695544 -0.63907602 1.12725625 0.50104583 0.77214159
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.1588904 -1.1952181 2.2931616 0.1743775 0.3444362 -2.4114591
[2,] -1.5180636 0.1335503 -1.5863528 0.1049363 0.7556555 0.7402338
[3,] -1.6767685 -0.9678868 1.4452508 -1.6173144 0.9559003 -0.6517510
[4,] -0.0871291 -0.9364420 0.4454513 1.5218697 2.7650169 0.5271120
[5,] 0.3416466 -0.7167425 -1.5185268 -0.6985614 0.7775618 -2.5292877
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.0490764 -0.91896199 0.2072241 -0.57458963 0.5905635 -1.4169251
[2,] -0.5033736 0.22201853 0.9255181 0.58511221 -2.3231731 -0.4551629
[3,] 1.3990106 2.79205061 -0.6032268 -0.01470377 -0.6727847 1.0908578
[4,] -0.7724039 0.09904473 -1.7757052 -0.78023468 -1.3877918 0.8746642
[5,] -0.4208148 -0.38777078 0.1861674 -1.21235744 -0.4722449 0.5068574
[,19] [,20]
[1,] 0.006960105 -1.2978085
[2,] 2.018560139 1.0698073
[3,] -0.641421967 -0.1577397
[4,] 0.093783065 -0.8312583
[5,] 0.740299674 1.3117205
>
>
> 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 1.560761 -2.227638 0.7343003 0.8160182 -0.9531362 -0.8348134 0.5647724
col8 col9 col10 col11 col12 col13 col14
row1 -1.138229 -0.677785 0.7283742 -0.5289354 -0.513763 -0.8259163 -0.5482636
col15 col16 col17 col18 col19 col20
row1 -0.9040888 1.75939 0.6889673 -0.1515384 1.010652 -0.9000767
> tmp[,"col10"]
col10
row1 0.7283742
row2 0.4943754
row3 0.1423927
row4 0.3337747
row5 0.9478585
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.56076088 -2.2276377 0.7343003 0.8160182 -0.9531362 -0.8348134 0.5647724
row5 0.07530029 -0.6067194 -1.4228944 0.6121207 0.9489187 -0.6800761 0.7136725
col8 col9 col10 col11 col12 col13
row1 -1.138229 -0.67778501 0.7283742 -0.5289354 -0.5137630 -0.8259163
row5 -1.119054 0.05039458 0.9478585 -0.5364042 0.4778971 -0.7834050
col14 col15 col16 col17 col18 col19
row1 -0.5482636 -0.9040888 1.75938954 0.6889673 -0.1515384 1.010652
row5 1.9961514 1.2094478 -0.06692297 -1.2453832 -1.0789843 1.981166
col20
row1 -0.9000767
row5 -0.8475176
> tmp[,c("col6","col20")]
col6 col20
row1 -0.8348134 -0.9000767
row2 -0.2688113 -0.6420509
row3 1.2394423 1.8143149
row4 1.9232969 -0.4352030
row5 -0.6800761 -0.8475176
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.8348134 -0.9000767
row5 -0.6800761 -0.8475176
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.42153 52.95247 50.13644 49.92329 49.51604 105.4168 49.01755 49.94726
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.00968 49.29011 49.95791 50.67348 49.11198 50.64576 50.23766 50.28303
col17 col18 col19 col20
row1 49.86387 51.00736 50.97274 106.2955
> tmp[,"col10"]
col10
row1 49.29011
row2 30.93523
row3 31.96567
row4 29.70311
row5 50.74541
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.42153 52.95247 50.13644 49.92329 49.51604 105.4168 49.01755 49.94726
row5 51.05350 49.08838 48.80910 50.12460 51.41715 105.6012 50.74717 49.89703
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.00968 49.29011 49.95791 50.67348 49.11198 50.64576 50.23766 50.28303
row5 49.81414 50.74541 50.67842 47.87076 52.00693 50.10250 50.59851 50.58774
col17 col18 col19 col20
row1 49.86387 51.00736 50.97274 106.2955
row5 49.65112 48.97045 50.80640 105.0310
> tmp[,c("col6","col20")]
col6 col20
row1 105.41681 106.29551
row2 74.78551 75.49944
row3 75.59092 75.59144
row4 74.91124 74.37031
row5 105.60124 105.03096
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.4168 106.2955
row5 105.6012 105.0310
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.4168 106.2955
row5 105.6012 105.0310
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.2913066
[2,] 0.1573114
[3,] 1.3627402
[4,] -0.5237721
[5,] -1.6638343
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.7478404 2.31109557
[2,] 0.8325439 0.04256513
[3,] -1.3183058 0.44129850
[4,] 0.1789046 -0.29803754
[5,] 1.5855867 -0.94276138
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.5846113290 -0.4653897
[2,] -0.2292709531 0.1207144
[3,] 0.2271822366 0.4574996
[4,] -0.0006072697 0.2890214
[5,] -0.6187289691 0.2826924
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.5846113
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.5846113
[2,] -0.2292710
>
>
>
> 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 -1.133553 0.6032880 0.009040939 -0.8484622 0.9141849 0.8146725 0.7466813
row1 -0.778686 -0.4165583 0.357192048 1.3474496 -0.6458939 1.8905120 1.2997143
[,8] [,9] [,10] [,11] [,12] [,13]
row3 0.8880593 0.4506743 -0.7117383 -0.5410923 0.7979781 -0.08148468
row1 1.0295359 -1.0255631 -1.0474236 -1.1919968 -0.8223794 -0.85168291
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.3124691 -2.15311335 -0.473741 -0.04688907 -0.07194105 0.1041203
row1 0.5921093 0.06659216 0.418663 2.17776042 -0.13656299 -0.9160959
[,20]
row3 -1.3857187
row1 0.0833961
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.4157898 1.471738 -2.200187 -0.05613088 -0.734187 0.09462525 -0.1957188
[,8] [,9] [,10]
row2 -0.0206465 -1.582721 0.06721803
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.2325008 0.6624616 -1.604254 1.664776 2.06725 -0.4387709 -0.08151472
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.8394729 0.6830196 -1.208584 -1.056124 0.4880475 -2.646615 0.1627072
[,15] [,16] [,17] [,18] [,19] [,20]
row5 2.234819 -0.4977292 0.8907929 -0.1111734 0.3229479 -0.05897577
>
>
> 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: 0x56562b0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2150982367bdba"
[2] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM21509814398bf9"
[3] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM215098c80b56c"
[4] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM215098647ef17"
[5] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2150982de99db9"
[6] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM21509836d244b"
[7] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2150984b305728"
[8] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2150982bc9ff50"
[9] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM21509832b0da84"
[10] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2150982f21e6d9"
[11] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM21509857bb56ea"
[12] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM215098788491de"
[13] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM21509849758983"
[14] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM21509840eeab44"
[15] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM215098db6d66d"
>
>
> ### 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: 0x5a4b680>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5a4b680>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5a4b680>
> rowMedians(tmp)
[1] -0.2206542308 -0.0037252060 0.3495263659 0.2083355944 0.2995127503
[6] 0.2302335463 -0.3301870209 0.3297561665 0.0229323747 0.5158983678
[11] 0.6392083778 0.0158087302 -0.1889215528 -0.4288753421 -0.3189706577
[16] -0.5358567812 0.2520779081 -0.2364324024 -0.1842036926 0.2115033596
[21] 0.1474499351 0.3496108161 0.1545086704 -0.2675689858 0.4946839905
[26] -0.1487936672 -0.3656803293 0.2245176883 0.3620414988 -0.4061240674
[31] 0.0734648966 -0.2869651997 -0.1135606858 0.3408754235 -0.0515108655
[36] -0.6676032883 0.5447530742 -0.6200809251 -0.1118164034 -0.0587273736
[41] 0.1294507068 0.4115257473 0.3109824372 0.1217679293 0.3242659890
[46] -0.2661394082 -0.1186417516 -0.2662314826 0.0432816994 0.0907928051
[51] 0.1899799740 0.0699625540 0.1524798367 -0.1254029852 0.2256063616
[56] -0.0005447252 -0.1202733263 -0.7317062385 0.2471178641 0.2136098496
[61] 0.1523574206 0.2005978051 -0.5338737828 -0.3642848106 0.4682033376
[66] -0.0803305846 0.0885024769 0.3516039814 -0.0893127632 -0.2895839853
[71] 0.0710619143 -0.2441866612 0.1616644277 0.1050957192 0.0330002663
[76] -0.1766309553 0.1381099238 -0.5324652338 0.0148275864 0.3908542283
[81] -0.1839325884 0.1501831042 0.3712511170 -0.0321881231 0.3614183463
[86] -0.1395144759 0.1326255291 -0.0895915082 -0.0260959920 0.6164537025
[91] -0.3558062866 -0.2695466042 -0.1076949560 -0.4584290654 -0.2024537638
[96] 0.7104111591 -0.4032783920 0.4862723852 0.0763748414 -0.1759448226
[101] 0.4885864651 -0.0137084742 -0.1322114716 0.3177930074 -0.1574704495
[106] 0.1326130879 -0.1301061760 -0.0970210839 -0.2972497860 0.0143944458
[111] 0.5019884681 0.2026556543 0.0524694068 0.4790781133 -0.1264709025
[116] -0.2630399302 0.4573754521 -0.2635503855 0.3134150405 0.1389880511
[121] -0.0985230694 -0.1705183017 0.3608867646 -0.1986095512 0.5577353417
[126] 0.5692337479 0.0306285404 -0.5933088539 -0.0707446645 0.2461010962
[131] 0.1476342936 -0.5820744245 0.2946942580 0.1533269435 0.4923437084
[136] 0.0151392024 0.1049752543 -0.6032896615 -0.3652442431 -0.3175113998
[141] -0.2240142581 -0.3095755478 -0.1188954770 0.2289781115 0.2886919671
[146] 0.1816824628 0.0579579839 0.3957078607 0.2136582346 0.2960143264
[151] -0.3444590866 -0.3279775440 0.4180775718 -0.3566855078 0.3617914762
[156] -0.1467718366 -0.1215732939 -0.4293108471 0.3063697696 0.1985980080
[161] 0.1857716793 -0.0032364204 -0.6515833570 -0.7343582054 0.2624720461
[166] 0.3546253099 -0.3139491746 0.0642803525 0.2658124194 0.4315959392
[171] 0.0035920945 0.0360929420 0.0182305956 0.2975633754 0.1171720913
[176] -0.2111609685 0.0823498433 0.5131270296 -0.1735584772 -0.1738975290
[181] 0.1772300518 -0.0200352371 -0.1099019926 -0.2098838410 0.7044904951
[186] 0.6652815310 -0.0632629543 -0.5436068859 0.0296241846 0.1535391278
[191] 0.6319666785 0.5759746935 0.4643814552 -0.3721790374 -0.3757122782
[196] -0.2346718639 -0.0671327615 0.2865903860 -0.0689747464 -0.6383043009
[201] 0.4242611673 0.2460195148 -0.3174300476 0.1116085045 0.1174112400
[206] -0.4816459300 0.0412313732 -0.1040720370 0.2078726696 0.2419109921
[211] 0.0626656961 0.5796205141 -0.2545735557 -0.0262663660 0.1028095900
[216] 0.2286656828 -0.3683836790 -0.0549800736 0.3194259149 0.2980102765
[221] 0.6929197771 -0.4744049279 -0.4111181530 -0.2762402351 0.1545020883
[226] -0.0445066934 -0.2162307611 -0.8035602393 -0.1725590711 -0.2545053124
>
> proc.time()
user system elapsed
1.915 0.853 2.799
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: 0x39c036e0>
> .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: 0x39c036e0>
> .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: 0x39c036e0>
> .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: 0x39c036e0>
> 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: 0x39c4b6a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x39c4b6a0>
> .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: 0x39c4b6a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x39c4b6a0>
> .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: 0x39c4b6a0>
> 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: 0x38e077d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x38e077d0>
> .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: 0x38e077d0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x38e077d0>
> .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: 0x38e077d0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x38e077d0>
> .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: 0x38e077d0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x38e077d0>
> .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: 0x38e077d0>
> 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: 0x39966d70>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x39966d70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x39966d70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x39966d70>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2150d55b6011d7" "BufferedMatrixFile2150d572c4655f"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2150d55b6011d7" "BufferedMatrixFile2150d572c4655f"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x39509cd0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x39509cd0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x39509cd0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x39509cd0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x39509cd0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x39509cd0>
> .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: 0x38478a10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x38478a10>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x38478a10>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x38478a10>
> 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: 0x3a392cc0>
> .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: 0x3a392cc0>
> rm(P)
>
> proc.time()
user system elapsed
0.347 0.041 0.373
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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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
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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
0.335 0.037 0.358