Ben Bolstad
| Snapshot Date: 2025-03-24 13:40 -0400 (Mon, 24 Mar 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 824836d |
| git_last_commit_date: 2024-12-14 17:47:34 -0400 (Sat, 14 Dec 2024) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-03-25 11:46 -0400 (Tue, 25 Mar 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | R Under development (unstable) (2025-03-13 r87965) -- "Unsuffered Consequences" | 4782 |
| palomino7 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2025-03-01 r87860 ucrt) -- "Unsuffered Consequences" | 4552 |
| lconway | macOS 12.7.1 Monterey | x86_64 | R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences" | 4581 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences" | 4533 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4463 |
| 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 249/2315 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.71.1 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.1 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: 1.71.1 |
| 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_1.71.1.tar.gz |
| StartedAt: 2025-03-25 04:34:44 -0000 (Tue, 25 Mar 2025) |
| EndedAt: 2025-03-25 04:35:07 -0000 (Tue, 25 Mar 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_1.71.1.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 ‘1.71.1’
* 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 ‘1.71.1’
** 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
0.343 0.035 0.364
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 Mar 25 04:35:01 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 Mar 25 04:35:01 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: 0x142d4790>
>
>
>
> 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 Mar 25 04:35:02 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 Mar 25 04:35:02 2025"
>
> ColMode(tmp2)
<pointer: 0x142d4790>
>
>
>
> ### 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,] 97.3820561 -0.0375754 -0.04857732 -0.89253183
[2,] 2.5049851 -0.5431662 -0.49124147 -0.03579974
[3,] 0.1092184 -0.6627278 -1.96703442 -1.13387622
[4,] 1.9081349 -0.3173265 0.55062748 -0.32875398
> 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,] 97.3820561 0.0375754 0.04857732 0.89253183
[2,] 2.5049851 0.5431662 0.49124147 0.03579974
[3,] 0.1092184 0.6627278 1.96703442 1.13387622
[4,] 1.9081349 0.3173265 0.55062748 0.32875398
> 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,] 9.868235 0.1938437 0.2204026 0.9447390
[2,] 1.582714 0.7369981 0.7008862 0.1892082
[3,] 0.330482 0.8140810 1.4025100 1.0648362
[4,] 1.381353 0.5633174 0.7420428 0.5733707
>
> 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,] 221.06440 26.97601 27.25260 35.33992
[2,] 43.33213 32.91315 32.50010 26.92788
[3,] 28.41404 33.80354 40.99213 36.78224
[4,] 40.72166 30.95050 32.97106 31.06246
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x13ba5c00>
> exp(tmp5)
<pointer: 0x13ba5c00>
> log(tmp5,2)
<pointer: 0x13ba5c00>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 460.1166
> Min(tmp5)
[1] 52.34635
> mean(tmp5)
[1] 72.98282
> Sum(tmp5)
[1] 14596.56
> Var(tmp5)
[1] 825.804
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.59251 72.14156 72.17087 71.99925 69.36263 72.02806 68.99871 72.59579
[9] 72.18682 67.75198
> rowSums(tmp5)
[1] 1811.850 1442.831 1443.417 1439.985 1387.253 1440.561 1379.974 1451.916
[9] 1443.736 1355.040
> rowVars(tmp5)
[1] 7623.87327 108.22961 109.80071 91.17208 74.68301 57.79888
[7] 62.01554 51.01137 35.13501 45.52170
> rowSd(tmp5)
[1] 87.314794 10.403346 10.478583 9.548407 8.641933 7.602557 7.874995
[8] 7.142225 5.927479 6.746977
> rowMax(tmp5)
[1] 460.11659 90.19015 92.88049 89.56887 87.94697 87.19483 84.97795
[8] 85.92022 81.19411 77.04938
> rowMin(tmp5)
[1] 56.14704 54.24503 56.21766 56.26582 52.34635 58.68897 57.09382 60.43671
[9] 56.45006 55.76233
>
> colMeans(tmp5)
[1] 110.47092 68.63454 72.06418 72.14628 74.16725 66.35135 73.17190
[8] 71.76554 69.85788 70.13097 68.74321 72.85123 67.93608 67.39233
[15] 73.62045 72.54684 70.02535 73.39821 69.65327 74.72857
> colSums(tmp5)
[1] 1104.7092 686.3454 720.6418 721.4628 741.6725 663.5135 731.7190
[8] 717.6554 698.5788 701.3097 687.4321 728.5123 679.3608 673.9233
[15] 736.2045 725.4684 700.2535 733.9821 696.5327 747.2857
> colVars(tmp5)
[1] 15195.04151 63.33706 89.49257 89.45082 36.33347 61.82833
[7] 56.32684 68.53257 45.38550 40.92068 68.89163 185.89100
[13] 60.53301 80.07458 71.96678 91.14533 50.98215 47.24622
[19] 38.59685 51.94739
> colSd(tmp5)
[1] 123.268169 7.958458 9.460052 9.457845 6.027725 7.863099
[7] 7.505121 8.278440 6.736876 6.396927 8.300098 13.634185
[13] 7.780296 8.948440 8.483324 9.547006 7.140179 6.873589
[19] 6.212636 7.207454
> colMax(tmp5)
[1] 460.11659 84.12832 87.19483 85.92022 83.50434 80.95619 88.51235
[8] 83.62328 80.61589 79.56722 81.33956 92.88049 78.73777 84.53767
[15] 86.86866 87.94697 80.64861 84.36149 79.42635 88.27797
> colMin(tmp5)
[1] 59.14010 56.14704 56.72272 56.04686 61.90522 57.31244 64.91222 56.21766
[9] 59.16197 61.81578 54.61663 52.34635 54.24503 55.76233 63.87593 57.09382
[17] 56.26582 59.07363 60.64625 66.30411
>
>
> ### 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] 90.59251 72.14156 72.17087 71.99925 69.36263 72.02806 68.99871 72.59579
[9] 72.18682 NA
> rowSums(tmp5)
[1] 1811.850 1442.831 1443.417 1439.985 1387.253 1440.561 1379.974 1451.916
[9] 1443.736 NA
> rowVars(tmp5)
[1] 7623.87327 108.22961 109.80071 91.17208 74.68301 57.79888
[7] 62.01554 51.01137 35.13501 47.49893
> rowSd(tmp5)
[1] 87.314794 10.403346 10.478583 9.548407 8.641933 7.602557 7.874995
[8] 7.142225 5.927479 6.891947
> rowMax(tmp5)
[1] 460.11659 90.19015 92.88049 89.56887 87.94697 87.19483 84.97795
[8] 85.92022 81.19411 NA
> rowMin(tmp5)
[1] 56.14704 54.24503 56.21766 56.26582 52.34635 58.68897 57.09382 60.43671
[9] 56.45006 NA
>
> colMeans(tmp5)
[1] 110.47092 NA 72.06418 72.14628 74.16725 66.35135 73.17190
[8] 71.76554 69.85788 70.13097 68.74321 72.85123 67.93608 67.39233
[15] 73.62045 72.54684 70.02535 73.39821 69.65327 74.72857
> colSums(tmp5)
[1] 1104.7092 NA 720.6418 721.4628 741.6725 663.5135 731.7190
[8] 717.6554 698.5788 701.3097 687.4321 728.5123 679.3608 673.9233
[15] 736.2045 725.4684 700.2535 733.9821 696.5327 747.2857
> colVars(tmp5)
[1] 15195.04151 NA 89.49257 89.45082 36.33347 61.82833
[7] 56.32684 68.53257 45.38550 40.92068 68.89163 185.89100
[13] 60.53301 80.07458 71.96678 91.14533 50.98215 47.24622
[19] 38.59685 51.94739
> colSd(tmp5)
[1] 123.268169 NA 9.460052 9.457845 6.027725 7.863099
[7] 7.505121 8.278440 6.736876 6.396927 8.300098 13.634185
[13] 7.780296 8.948440 8.483324 9.547006 7.140179 6.873589
[19] 6.212636 7.207454
> colMax(tmp5)
[1] 460.11659 NA 87.19483 85.92022 83.50434 80.95619 88.51235
[8] 83.62328 80.61589 79.56722 81.33956 92.88049 78.73777 84.53767
[15] 86.86866 87.94697 80.64861 84.36149 79.42635 88.27797
> colMin(tmp5)
[1] 59.14010 NA 56.72272 56.04686 61.90522 57.31244 64.91222 56.21766
[9] 59.16197 61.81578 54.61663 52.34635 54.24503 55.76233 63.87593 57.09382
[17] 56.26582 59.07363 60.64625 66.30411
>
> Max(tmp5,na.rm=TRUE)
[1] 460.1166
> Min(tmp5,na.rm=TRUE)
[1] 52.34635
> mean(tmp5,na.rm=TRUE)
[1] 73.02454
> Sum(tmp5,na.rm=TRUE)
[1] 14531.88
> Var(tmp5,na.rm=TRUE)
[1] 829.6249
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.59251 72.14156 72.17087 71.99925 69.36263 72.02806 68.99871 72.59579
[9] 72.18682 67.91364
> rowSums(tmp5,na.rm=TRUE)
[1] 1811.850 1442.831 1443.417 1439.985 1387.253 1440.561 1379.974 1451.916
[9] 1443.736 1290.359
> rowVars(tmp5,na.rm=TRUE)
[1] 7623.87327 108.22961 109.80071 91.17208 74.68301 57.79888
[7] 62.01554 51.01137 35.13501 47.49893
> rowSd(tmp5,na.rm=TRUE)
[1] 87.314794 10.403346 10.478583 9.548407 8.641933 7.602557 7.874995
[8] 7.142225 5.927479 6.891947
> rowMax(tmp5,na.rm=TRUE)
[1] 460.11659 90.19015 92.88049 89.56887 87.94697 87.19483 84.97795
[8] 85.92022 81.19411 77.04938
> rowMin(tmp5,na.rm=TRUE)
[1] 56.14704 54.24503 56.21766 56.26582 52.34635 58.68897 57.09382 60.43671
[9] 56.45006 55.76233
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.47092 69.07389 72.06418 72.14628 74.16725 66.35135 73.17190
[8] 71.76554 69.85788 70.13097 68.74321 72.85123 67.93608 67.39233
[15] 73.62045 72.54684 70.02535 73.39821 69.65327 74.72857
> colSums(tmp5,na.rm=TRUE)
[1] 1104.7092 621.6650 720.6418 721.4628 741.6725 663.5135 731.7190
[8] 717.6554 698.5788 701.3097 687.4321 728.5123 679.3608 673.9233
[15] 736.2045 725.4684 700.2535 733.9821 696.5327 747.2857
> colVars(tmp5,na.rm=TRUE)
[1] 15195.04151 69.08257 89.49257 89.45082 36.33347 61.82833
[7] 56.32684 68.53257 45.38550 40.92068 68.89163 185.89100
[13] 60.53301 80.07458 71.96678 91.14533 50.98215 47.24622
[19] 38.59685 51.94739
> colSd(tmp5,na.rm=TRUE)
[1] 123.268169 8.311592 9.460052 9.457845 6.027725 7.863099
[7] 7.505121 8.278440 6.736876 6.396927 8.300098 13.634185
[13] 7.780296 8.948440 8.483324 9.547006 7.140179 6.873589
[19] 6.212636 7.207454
> colMax(tmp5,na.rm=TRUE)
[1] 460.11659 84.12832 87.19483 85.92022 83.50434 80.95619 88.51235
[8] 83.62328 80.61589 79.56722 81.33956 92.88049 78.73777 84.53767
[15] 86.86866 87.94697 80.64861 84.36149 79.42635 88.27797
> colMin(tmp5,na.rm=TRUE)
[1] 59.14010 56.14704 56.72272 56.04686 61.90522 57.31244 64.91222 56.21766
[9] 59.16197 61.81578 54.61663 52.34635 54.24503 55.76233 63.87593 57.09382
[17] 56.26582 59.07363 60.64625 66.30411
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.59251 72.14156 72.17087 71.99925 69.36263 72.02806 68.99871 72.59579
[9] 72.18682 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1811.850 1442.831 1443.417 1439.985 1387.253 1440.561 1379.974 1451.916
[9] 1443.736 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 7623.87327 108.22961 109.80071 91.17208 74.68301 57.79888
[7] 62.01554 51.01137 35.13501 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 87.314794 10.403346 10.478583 9.548407 8.641933 7.602557 7.874995
[8] 7.142225 5.927479 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 460.11659 90.19015 92.88049 89.56887 87.94697 87.19483 84.97795
[8] 85.92022 81.19411 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 56.14704 54.24503 56.21766 56.26582 52.34635 58.68897 57.09382 60.43671
[9] 56.45006 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.30420 NaN 73.28360 73.19566 74.32591 67.35567 73.00880
[8] 71.54020 70.99120 69.50071 67.82030 72.71246 68.61634 68.68455
[15] 74.16041 72.32167 70.94992 73.28244 69.80237 75.35011
> colSums(tmp5,na.rm=TRUE)
[1] 1037.7378 0.0000 659.5524 658.7609 668.9332 606.2011 657.0792
[8] 643.8618 638.9208 625.5064 610.3827 654.4121 617.5471 618.1610
[15] 667.4437 650.8950 638.5493 659.5420 628.2213 678.1509
> colVars(tmp5,na.rm=TRUE)
[1] 16831.61555 NA 83.95059 88.24374 40.59197 58.20938
[7] 63.06844 76.52789 36.60896 41.56708 67.92079 208.91072
[13] 62.89353 71.29821 77.68259 101.96809 47.73791 53.00123
[19] 43.17135 54.09490
> colSd(tmp5,na.rm=TRUE)
[1] 129.736716 NA 9.162455 9.393814 6.371183 7.629507
[7] 7.941564 8.748022 6.050534 6.447254 8.241407 14.453744
[13] 7.930544 8.443827 8.813773 10.097925 6.909262 7.280194
[19] 6.570491 7.354924
> colMax(tmp5,na.rm=TRUE)
[1] 460.11659 -Inf 87.19483 85.92022 83.50434 80.95619 88.51235
[8] 83.62328 80.61589 79.56722 81.33956 92.88049 78.73777 84.53767
[15] 86.86866 87.94697 80.64861 84.36149 79.42635 88.27797
> colMin(tmp5,na.rm=TRUE)
[1] 59.14010 Inf 56.72272 56.04686 61.90522 59.29560 64.91222 56.21766
[9] 59.16197 61.81578 54.61663 52.34635 54.24503 57.36563 63.87593 57.09382
[17] 56.26582 59.07363 60.64625 66.30411
>
>
>
>
> 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] 303.6814 181.1677 131.5184 170.2806 207.9096 204.7418 188.9186 156.6227
[9] 214.7067 138.4113
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 303.6814 181.1677 131.5184 170.2806 207.9096 204.7418 188.9186 156.6227
[9] 214.7067 138.4113
>
>
>
> 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] -1.136868e-13 2.842171e-14 0.000000e+00 0.000000e+00 1.136868e-13
[6] 2.842171e-14 -1.421085e-13 1.421085e-13 -8.526513e-14 8.526513e-14
[11] 0.000000e+00 -1.136868e-13 -2.842171e-13 5.684342e-14 1.136868e-13
[16] 5.684342e-14 -1.136868e-13 -5.684342e-14 -2.842171e-14 -1.421085e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
10 12
5 8
6 13
7 6
1 2
4 8
1 15
5 1
10 16
8 13
2 10
5 19
10 8
8 17
10 13
3 14
1 1
5 15
3 2
10 19
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.985353
> Min(tmp)
[1] -1.873549
> mean(tmp)
[1] 0.01098573
> Sum(tmp)
[1] 1.098573
> Var(tmp)
[1] 1.034035
>
> rowMeans(tmp)
[1] 0.01098573
> rowSums(tmp)
[1] 1.098573
> rowVars(tmp)
[1] 1.034035
> rowSd(tmp)
[1] 1.016875
> rowMax(tmp)
[1] 2.985353
> rowMin(tmp)
[1] -1.873549
>
> colMeans(tmp)
[1] 0.15732268 -0.68725311 1.03886073 -1.39128864 0.20346164 -0.68352268
[7] 0.60748417 -0.25663613 -1.87354919 -1.12884822 -0.78784178 -1.19067384
[13] -0.69456403 0.16522239 -0.63736031 -0.98168279 -0.26339714 -0.50285778
[19] -0.46849087 0.94094607 0.37811112 1.66771775 0.88376929 -0.74601697
[25] 0.75219336 -0.16120046 -0.81192732 2.98535269 0.29853174 -0.50746429
[31] -0.52110755 -0.71339982 -0.42058933 0.31135706 -0.49568096 1.17323853
[37] 0.34750827 0.49857591 -0.25728936 -0.33420150 -0.97900803 -1.48246172
[43] 0.60344768 -0.30296384 0.48322224 1.52026978 0.01351950 -1.25834605
[49] -0.18025030 0.72515188 -1.36967981 -1.17745062 -0.21040310 -1.80828923
[55] -0.20554916 -1.08339285 -0.59464085 1.26886849 2.55837034 0.27802347
[61] 0.61465558 0.58916449 -0.84330194 2.04350817 1.25526217 0.79682809
[67] -1.16916993 0.29126426 -0.71104441 0.45803702 0.40343156 -0.81697717
[73] -0.51398696 0.73097577 1.36542021 2.68214242 -0.28618476 -0.65822760
[79] -0.43322779 0.49113852 0.25439775 0.14432000 1.42387555 -1.76098506
[85] 0.59602106 -1.30950709 0.75955589 0.40440056 0.33269722 0.56370088
[91] 0.12470622 -0.16308568 -0.43481458 -0.14127048 2.20103363 -1.66495366
[97] -0.09563006 1.73419495 0.95342999 -1.80446870
> colSums(tmp)
[1] 0.15732268 -0.68725311 1.03886073 -1.39128864 0.20346164 -0.68352268
[7] 0.60748417 -0.25663613 -1.87354919 -1.12884822 -0.78784178 -1.19067384
[13] -0.69456403 0.16522239 -0.63736031 -0.98168279 -0.26339714 -0.50285778
[19] -0.46849087 0.94094607 0.37811112 1.66771775 0.88376929 -0.74601697
[25] 0.75219336 -0.16120046 -0.81192732 2.98535269 0.29853174 -0.50746429
[31] -0.52110755 -0.71339982 -0.42058933 0.31135706 -0.49568096 1.17323853
[37] 0.34750827 0.49857591 -0.25728936 -0.33420150 -0.97900803 -1.48246172
[43] 0.60344768 -0.30296384 0.48322224 1.52026978 0.01351950 -1.25834605
[49] -0.18025030 0.72515188 -1.36967981 -1.17745062 -0.21040310 -1.80828923
[55] -0.20554916 -1.08339285 -0.59464085 1.26886849 2.55837034 0.27802347
[61] 0.61465558 0.58916449 -0.84330194 2.04350817 1.25526217 0.79682809
[67] -1.16916993 0.29126426 -0.71104441 0.45803702 0.40343156 -0.81697717
[73] -0.51398696 0.73097577 1.36542021 2.68214242 -0.28618476 -0.65822760
[79] -0.43322779 0.49113852 0.25439775 0.14432000 1.42387555 -1.76098506
[85] 0.59602106 -1.30950709 0.75955589 0.40440056 0.33269722 0.56370088
[91] 0.12470622 -0.16308568 -0.43481458 -0.14127048 2.20103363 -1.66495366
[97] -0.09563006 1.73419495 0.95342999 -1.80446870
> 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] 0.15732268 -0.68725311 1.03886073 -1.39128864 0.20346164 -0.68352268
[7] 0.60748417 -0.25663613 -1.87354919 -1.12884822 -0.78784178 -1.19067384
[13] -0.69456403 0.16522239 -0.63736031 -0.98168279 -0.26339714 -0.50285778
[19] -0.46849087 0.94094607 0.37811112 1.66771775 0.88376929 -0.74601697
[25] 0.75219336 -0.16120046 -0.81192732 2.98535269 0.29853174 -0.50746429
[31] -0.52110755 -0.71339982 -0.42058933 0.31135706 -0.49568096 1.17323853
[37] 0.34750827 0.49857591 -0.25728936 -0.33420150 -0.97900803 -1.48246172
[43] 0.60344768 -0.30296384 0.48322224 1.52026978 0.01351950 -1.25834605
[49] -0.18025030 0.72515188 -1.36967981 -1.17745062 -0.21040310 -1.80828923
[55] -0.20554916 -1.08339285 -0.59464085 1.26886849 2.55837034 0.27802347
[61] 0.61465558 0.58916449 -0.84330194 2.04350817 1.25526217 0.79682809
[67] -1.16916993 0.29126426 -0.71104441 0.45803702 0.40343156 -0.81697717
[73] -0.51398696 0.73097577 1.36542021 2.68214242 -0.28618476 -0.65822760
[79] -0.43322779 0.49113852 0.25439775 0.14432000 1.42387555 -1.76098506
[85] 0.59602106 -1.30950709 0.75955589 0.40440056 0.33269722 0.56370088
[91] 0.12470622 -0.16308568 -0.43481458 -0.14127048 2.20103363 -1.66495366
[97] -0.09563006 1.73419495 0.95342999 -1.80446870
> colMin(tmp)
[1] 0.15732268 -0.68725311 1.03886073 -1.39128864 0.20346164 -0.68352268
[7] 0.60748417 -0.25663613 -1.87354919 -1.12884822 -0.78784178 -1.19067384
[13] -0.69456403 0.16522239 -0.63736031 -0.98168279 -0.26339714 -0.50285778
[19] -0.46849087 0.94094607 0.37811112 1.66771775 0.88376929 -0.74601697
[25] 0.75219336 -0.16120046 -0.81192732 2.98535269 0.29853174 -0.50746429
[31] -0.52110755 -0.71339982 -0.42058933 0.31135706 -0.49568096 1.17323853
[37] 0.34750827 0.49857591 -0.25728936 -0.33420150 -0.97900803 -1.48246172
[43] 0.60344768 -0.30296384 0.48322224 1.52026978 0.01351950 -1.25834605
[49] -0.18025030 0.72515188 -1.36967981 -1.17745062 -0.21040310 -1.80828923
[55] -0.20554916 -1.08339285 -0.59464085 1.26886849 2.55837034 0.27802347
[61] 0.61465558 0.58916449 -0.84330194 2.04350817 1.25526217 0.79682809
[67] -1.16916993 0.29126426 -0.71104441 0.45803702 0.40343156 -0.81697717
[73] -0.51398696 0.73097577 1.36542021 2.68214242 -0.28618476 -0.65822760
[79] -0.43322779 0.49113852 0.25439775 0.14432000 1.42387555 -1.76098506
[85] 0.59602106 -1.30950709 0.75955589 0.40440056 0.33269722 0.56370088
[91] 0.12470622 -0.16308568 -0.43481458 -0.14127048 2.20103363 -1.66495366
[97] -0.09563006 1.73419495 0.95342999 -1.80446870
> colMedians(tmp)
[1] 0.15732268 -0.68725311 1.03886073 -1.39128864 0.20346164 -0.68352268
[7] 0.60748417 -0.25663613 -1.87354919 -1.12884822 -0.78784178 -1.19067384
[13] -0.69456403 0.16522239 -0.63736031 -0.98168279 -0.26339714 -0.50285778
[19] -0.46849087 0.94094607 0.37811112 1.66771775 0.88376929 -0.74601697
[25] 0.75219336 -0.16120046 -0.81192732 2.98535269 0.29853174 -0.50746429
[31] -0.52110755 -0.71339982 -0.42058933 0.31135706 -0.49568096 1.17323853
[37] 0.34750827 0.49857591 -0.25728936 -0.33420150 -0.97900803 -1.48246172
[43] 0.60344768 -0.30296384 0.48322224 1.52026978 0.01351950 -1.25834605
[49] -0.18025030 0.72515188 -1.36967981 -1.17745062 -0.21040310 -1.80828923
[55] -0.20554916 -1.08339285 -0.59464085 1.26886849 2.55837034 0.27802347
[61] 0.61465558 0.58916449 -0.84330194 2.04350817 1.25526217 0.79682809
[67] -1.16916993 0.29126426 -0.71104441 0.45803702 0.40343156 -0.81697717
[73] -0.51398696 0.73097577 1.36542021 2.68214242 -0.28618476 -0.65822760
[79] -0.43322779 0.49113852 0.25439775 0.14432000 1.42387555 -1.76098506
[85] 0.59602106 -1.30950709 0.75955589 0.40440056 0.33269722 0.56370088
[91] 0.12470622 -0.16308568 -0.43481458 -0.14127048 2.20103363 -1.66495366
[97] -0.09563006 1.73419495 0.95342999 -1.80446870
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.1573227 -0.6872531 1.038861 -1.391289 0.2034616 -0.6835227 0.6074842
[2,] 0.1573227 -0.6872531 1.038861 -1.391289 0.2034616 -0.6835227 0.6074842
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.2566361 -1.873549 -1.128848 -0.7878418 -1.190674 -0.694564 0.1652224
[2,] -0.2566361 -1.873549 -1.128848 -0.7878418 -1.190674 -0.694564 0.1652224
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.6373603 -0.9816828 -0.2633971 -0.5028578 -0.4684909 0.9409461 0.3781111
[2,] -0.6373603 -0.9816828 -0.2633971 -0.5028578 -0.4684909 0.9409461 0.3781111
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.667718 0.8837693 -0.746017 0.7521934 -0.1612005 -0.8119273 2.985353
[2,] 1.667718 0.8837693 -0.746017 0.7521934 -0.1612005 -0.8119273 2.985353
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.2985317 -0.5074643 -0.5211075 -0.7133998 -0.4205893 0.3113571 -0.495681
[2,] 0.2985317 -0.5074643 -0.5211075 -0.7133998 -0.4205893 0.3113571 -0.495681
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.173239 0.3475083 0.4985759 -0.2572894 -0.3342015 -0.979008 -1.482462
[2,] 1.173239 0.3475083 0.4985759 -0.2572894 -0.3342015 -0.979008 -1.482462
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.6034477 -0.3029638 0.4832222 1.52027 0.0135195 -1.258346 -0.1802503
[2,] 0.6034477 -0.3029638 0.4832222 1.52027 0.0135195 -1.258346 -0.1802503
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.7251519 -1.36968 -1.177451 -0.2104031 -1.808289 -0.2055492 -1.083393
[2,] 0.7251519 -1.36968 -1.177451 -0.2104031 -1.808289 -0.2055492 -1.083393
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.5946409 1.268868 2.55837 0.2780235 0.6146556 0.5891645 -0.8433019
[2,] -0.5946409 1.268868 2.55837 0.2780235 0.6146556 0.5891645 -0.8433019
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 2.043508 1.255262 0.7968281 -1.16917 0.2912643 -0.7110444 0.458037
[2,] 2.043508 1.255262 0.7968281 -1.16917 0.2912643 -0.7110444 0.458037
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.4034316 -0.8169772 -0.513987 0.7309758 1.36542 2.682142 -0.2861848
[2,] 0.4034316 -0.8169772 -0.513987 0.7309758 1.36542 2.682142 -0.2861848
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.6582276 -0.4332278 0.4911385 0.2543977 0.14432 1.423876 -1.760985
[2,] -0.6582276 -0.4332278 0.4911385 0.2543977 0.14432 1.423876 -1.760985
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.5960211 -1.309507 0.7595559 0.4044006 0.3326972 0.5637009 0.1247062
[2,] 0.5960211 -1.309507 0.7595559 0.4044006 0.3326972 0.5637009 0.1247062
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.1630857 -0.4348146 -0.1412705 2.201034 -1.664954 -0.09563006 1.734195
[2,] -0.1630857 -0.4348146 -0.1412705 2.201034 -1.664954 -0.09563006 1.734195
[,99] [,100]
[1,] 0.95343 -1.804469
[2,] 0.95343 -1.804469
>
>
> Max(tmp2)
[1] 2.396894
> Min(tmp2)
[1] -3.845115
> mean(tmp2)
[1] 0.002185259
> Sum(tmp2)
[1] 0.2185259
> Var(tmp2)
[1] 1.275774
>
> rowMeans(tmp2)
[1] -1.14731838 -0.53337076 -0.73245659 -1.64517866 0.26620319 0.77629991
[7] 1.34971464 0.75991796 1.01389942 0.54765304 -0.02613105 0.35527699
[13] 1.00659880 1.78854022 0.33789077 0.64848819 -0.13023681 2.13487862
[19] 0.19677319 -0.18154440 -0.92531270 -0.55892148 0.37859204 0.95866345
[25] -2.74751117 -0.44345508 -0.54127633 2.16351799 0.16164728 0.88371672
[31] -0.05077478 2.33081038 -3.84511492 0.84619760 -0.31609171 1.05784444
[37] 0.07614767 -1.44339658 0.21107609 0.24779687 -0.91019380 -1.51506944
[43] 0.25641177 0.68828509 1.64871903 0.11985254 0.37876725 1.24823623
[49] 0.28740231 0.22719101 -0.99944579 -0.91551620 -1.99258008 -0.05540215
[55] -1.83479150 -0.96108192 -0.39756937 0.48835288 -0.09954014 -0.51222721
[61] -0.36145600 -0.55859713 -0.68817502 -2.35476835 0.16534835 1.51063656
[67] 1.02644661 1.89567461 0.52710075 -0.90893223 -0.17768397 0.96317019
[73] 0.85589333 0.76311459 0.16264808 -1.08975933 -0.39287353 -1.53940481
[79] 0.62219145 0.54924703 -0.31663703 0.32615552 0.57792805 -0.51992722
[85] -1.73416114 -1.93204237 1.32167007 2.39689421 -0.19169478 0.02246076
[91] -1.69892180 0.15976662 1.44030807 0.62386582 -1.18022613 -0.20190212
[97] 1.63753407 0.36207500 -0.98985416 -1.23444128
> rowSums(tmp2)
[1] -1.14731838 -0.53337076 -0.73245659 -1.64517866 0.26620319 0.77629991
[7] 1.34971464 0.75991796 1.01389942 0.54765304 -0.02613105 0.35527699
[13] 1.00659880 1.78854022 0.33789077 0.64848819 -0.13023681 2.13487862
[19] 0.19677319 -0.18154440 -0.92531270 -0.55892148 0.37859204 0.95866345
[25] -2.74751117 -0.44345508 -0.54127633 2.16351799 0.16164728 0.88371672
[31] -0.05077478 2.33081038 -3.84511492 0.84619760 -0.31609171 1.05784444
[37] 0.07614767 -1.44339658 0.21107609 0.24779687 -0.91019380 -1.51506944
[43] 0.25641177 0.68828509 1.64871903 0.11985254 0.37876725 1.24823623
[49] 0.28740231 0.22719101 -0.99944579 -0.91551620 -1.99258008 -0.05540215
[55] -1.83479150 -0.96108192 -0.39756937 0.48835288 -0.09954014 -0.51222721
[61] -0.36145600 -0.55859713 -0.68817502 -2.35476835 0.16534835 1.51063656
[67] 1.02644661 1.89567461 0.52710075 -0.90893223 -0.17768397 0.96317019
[73] 0.85589333 0.76311459 0.16264808 -1.08975933 -0.39287353 -1.53940481
[79] 0.62219145 0.54924703 -0.31663703 0.32615552 0.57792805 -0.51992722
[85] -1.73416114 -1.93204237 1.32167007 2.39689421 -0.19169478 0.02246076
[91] -1.69892180 0.15976662 1.44030807 0.62386582 -1.18022613 -0.20190212
[97] 1.63753407 0.36207500 -0.98985416 -1.23444128
> 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] -1.14731838 -0.53337076 -0.73245659 -1.64517866 0.26620319 0.77629991
[7] 1.34971464 0.75991796 1.01389942 0.54765304 -0.02613105 0.35527699
[13] 1.00659880 1.78854022 0.33789077 0.64848819 -0.13023681 2.13487862
[19] 0.19677319 -0.18154440 -0.92531270 -0.55892148 0.37859204 0.95866345
[25] -2.74751117 -0.44345508 -0.54127633 2.16351799 0.16164728 0.88371672
[31] -0.05077478 2.33081038 -3.84511492 0.84619760 -0.31609171 1.05784444
[37] 0.07614767 -1.44339658 0.21107609 0.24779687 -0.91019380 -1.51506944
[43] 0.25641177 0.68828509 1.64871903 0.11985254 0.37876725 1.24823623
[49] 0.28740231 0.22719101 -0.99944579 -0.91551620 -1.99258008 -0.05540215
[55] -1.83479150 -0.96108192 -0.39756937 0.48835288 -0.09954014 -0.51222721
[61] -0.36145600 -0.55859713 -0.68817502 -2.35476835 0.16534835 1.51063656
[67] 1.02644661 1.89567461 0.52710075 -0.90893223 -0.17768397 0.96317019
[73] 0.85589333 0.76311459 0.16264808 -1.08975933 -0.39287353 -1.53940481
[79] 0.62219145 0.54924703 -0.31663703 0.32615552 0.57792805 -0.51992722
[85] -1.73416114 -1.93204237 1.32167007 2.39689421 -0.19169478 0.02246076
[91] -1.69892180 0.15976662 1.44030807 0.62386582 -1.18022613 -0.20190212
[97] 1.63753407 0.36207500 -0.98985416 -1.23444128
> rowMin(tmp2)
[1] -1.14731838 -0.53337076 -0.73245659 -1.64517866 0.26620319 0.77629991
[7] 1.34971464 0.75991796 1.01389942 0.54765304 -0.02613105 0.35527699
[13] 1.00659880 1.78854022 0.33789077 0.64848819 -0.13023681 2.13487862
[19] 0.19677319 -0.18154440 -0.92531270 -0.55892148 0.37859204 0.95866345
[25] -2.74751117 -0.44345508 -0.54127633 2.16351799 0.16164728 0.88371672
[31] -0.05077478 2.33081038 -3.84511492 0.84619760 -0.31609171 1.05784444
[37] 0.07614767 -1.44339658 0.21107609 0.24779687 -0.91019380 -1.51506944
[43] 0.25641177 0.68828509 1.64871903 0.11985254 0.37876725 1.24823623
[49] 0.28740231 0.22719101 -0.99944579 -0.91551620 -1.99258008 -0.05540215
[55] -1.83479150 -0.96108192 -0.39756937 0.48835288 -0.09954014 -0.51222721
[61] -0.36145600 -0.55859713 -0.68817502 -2.35476835 0.16534835 1.51063656
[67] 1.02644661 1.89567461 0.52710075 -0.90893223 -0.17768397 0.96317019
[73] 0.85589333 0.76311459 0.16264808 -1.08975933 -0.39287353 -1.53940481
[79] 0.62219145 0.54924703 -0.31663703 0.32615552 0.57792805 -0.51992722
[85] -1.73416114 -1.93204237 1.32167007 2.39689421 -0.19169478 0.02246076
[91] -1.69892180 0.15976662 1.44030807 0.62386582 -1.18022613 -0.20190212
[97] 1.63753407 0.36207500 -0.98985416 -1.23444128
>
> colMeans(tmp2)
[1] 0.002185259
> colSums(tmp2)
[1] 0.2185259
> colVars(tmp2)
[1] 1.275774
> colSd(tmp2)
[1] 1.129502
> colMax(tmp2)
[1] 2.396894
> colMin(tmp2)
[1] -3.845115
> colMedians(tmp2)
[1] 0.1607069
> colRanges(tmp2)
[,1]
[1,] -3.845115
[2,] 2.396894
>
> 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] -0.05168827 4.49345881 2.22230313 5.56975556 -3.28852855 -2.56991201
[7] -2.71797053 1.65768636 2.60245165 -2.14242536
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.2268521
[2,] -0.7999077
[3,] -0.2302458
[4,] 0.7810979
[5,] 1.9359693
>
> rowApply(tmp,sum)
[1] -2.5294540 1.2879072 3.2727438 2.8179289 3.1835278 1.7472026
[7] -2.8991783 3.4626139 -4.8535971 0.2854359
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 5 8 1 6 2 7 1 10 3
[2,] 5 10 6 6 10 1 5 4 1 10
[3,] 7 9 4 9 3 6 9 6 5 1
[4,] 6 2 7 3 9 9 6 10 6 9
[5,] 3 4 5 4 7 4 4 2 7 4
[6,] 1 6 2 8 1 8 2 7 4 8
[7,] 2 7 1 2 8 10 1 8 3 7
[8,] 10 1 3 10 4 7 8 9 8 2
[9,] 8 8 10 7 5 3 10 5 2 6
[10,] 4 3 9 5 2 5 3 3 9 5
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.8436725713 1.5983340918 -2.1123236746 0.4094623286 0.0907609702
[6] -2.0847250940 4.8244757951 0.3356579942 0.1296827222 -0.0009741956
[11] -0.7605543691 0.0090233619 -3.7428427862 -1.7736834770 -2.7889643992
[16] -2.2501167070 -1.5331437755 5.2605070714 2.4130230007 -0.9443905620
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8949657
[2,] -0.7400377
[3,] -0.6624530
[4,] 0.6554768
[5,] 0.7983069
>
> rowApply(tmp,sum)
[1] 5.8346900 1.5627027 0.2730895 -8.0933427 -3.3416039
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 3 15 5 5 16
[2,] 8 8 15 20 6
[3,] 16 14 1 4 5
[4,] 4 18 13 3 17
[5,] 12 16 6 7 13
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.6624530 -0.1353841 1.1389718 -0.6371003 0.3354533 -0.3418853
[2,] 0.6554768 -0.3293191 0.5931608 1.2768207 0.8252951 -2.3585056
[3,] -0.7400377 0.7238143 -1.5718059 0.3345512 -0.6346253 -0.5537707
[4,] -0.8949657 2.0306389 -1.2866958 -1.3849759 -0.7810208 0.9501437
[5,] 0.7983069 -0.6914160 -0.9859546 0.8201667 0.3456587 0.2192929
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 3.2495658 1.5323417 0.3806375 0.04076604 0.4192813 1.6062365
[2,] 0.0358999 0.4313526 0.3415173 1.71586457 -1.1818272 -0.4573824
[3,] 1.4958340 -1.1140561 -0.8492639 -0.50414239 0.9582443 -0.8271337
[4,] 0.4811363 0.1153448 -0.6423282 -0.02033596 -0.4400037 -0.7039051
[5,] -0.4379602 -0.6293250 0.8991201 -1.23312646 -0.5162491 0.3912081
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.4805660 -0.3371853 1.7746254 -1.1799014 0.2011579 0.55528697
[2,] -0.4864276 -0.7372853 -1.7186449 -1.3474176 0.5232655 2.18371607
[3,] -0.4266537 -0.4558108 -0.0375685 1.1479608 0.6050947 1.63672831
[4,] -2.4795104 -0.8741995 -0.7389391 0.3000817 -0.7346468 0.02313512
[5,] 0.1303150 0.6307975 -2.0684372 -1.1708403 -2.1280151 0.86164060
[,19] [,20]
[1,] -0.09585218 -1.52930651
[2,] 0.59308668 1.00405665
[3,] 1.02129004 0.06444063
[4,] 0.99016607 -2.00246236
[5,] -0.09566761 1.51888103
>
>
> 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 : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.04868924 -0.8961639 -0.185176 0.3495093 -0.08696122 -1.518383 0.5239281
col8 col9 col10 col11 col12 col13 col14
row1 -0.8157675 -0.1110868 0.956445 -0.3444477 2.729747 -0.02006659 -1.517259
col15 col16 col17 col18 col19 col20
row1 -0.3650726 1.693766 -0.04156363 -1.834262 0.7669325 1.087554
> tmp[,"col10"]
col10
row1 0.9564450
row2 -0.4428055
row3 0.4259906
row4 -0.6610344
row5 0.5116321
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.04868924 -0.8961639 -0.1851760 0.3495093 -0.08696122 -1.5183829
row5 -0.68333954 0.5828211 -0.1986337 1.5416808 -0.54187096 0.7122984
col7 col8 col9 col10 col11 col12
row1 0.5239281 -0.8157675 -0.1110868 0.9564450 -0.34444775 2.729747
row5 0.4900659 -2.1944453 0.7640503 0.5116321 -0.01734414 -2.808252
col13 col14 col15 col16 col17 col18
row1 -0.02006659 -1.5172586 -0.3650726 1.693766 -0.04156363 -1.8342624
row5 1.27501188 -0.4845891 0.1590171 -1.183176 1.43887316 0.8744317
col19 col20
row1 0.7669325 1.08755444
row5 0.5896023 -0.06513256
> tmp[,c("col6","col20")]
col6 col20
row1 -1.5183829 1.08755444
row2 0.8263244 -0.52567194
row3 0.5980384 -0.02483075
row4 -0.8638989 1.17009343
row5 0.7122984 -0.06513256
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.5183829 1.08755444
row5 0.7122984 -0.06513256
>
>
>
>
> 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 52.92198 52.23126 50.55984 50.75312 49.23382 105.1078 52.22348 52.27357
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.31729 48.71874 51.28781 49.7654 49.86354 50.72981 49.98664 49.53848
col17 col18 col19 col20
row1 49.56313 49.02628 49.7694 103.8345
> tmp[,"col10"]
col10
row1 48.71874
row2 28.39741
row3 29.80100
row4 30.30511
row5 50.40030
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 52.92198 52.23126 50.55984 50.75312 49.23382 105.1078 52.22348 52.27357
row5 48.46304 48.95584 49.04566 51.92266 49.03581 105.0601 51.14176 48.97093
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.31729 48.71874 51.28781 49.76540 49.86354 50.72981 49.98664 49.53848
row5 50.65004 50.40030 48.99993 52.73802 47.63069 51.57775 50.03733 50.03693
col17 col18 col19 col20
row1 49.56313 49.02628 49.76940 103.8345
row5 50.70214 48.71008 52.21583 103.6491
> tmp[,c("col6","col20")]
col6 col20
row1 105.10777 103.83452
row2 75.19311 75.61758
row3 75.02422 76.67487
row4 73.39368 75.58755
row5 105.06008 103.64906
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.1078 103.8345
row5 105.0601 103.6491
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.1078 103.8345
row5 105.0601 103.6491
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.08800743
[2,] 0.35752705
[3,] 0.93199930
[4,] -2.32158205
[5,] -1.96777323
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.0768956 1.3581883
[2,] 0.3856097 0.1357769
[3,] -0.6544106 -0.7097708
[4,] -1.1594106 -0.3860234
[5,] 1.4867884 -1.0177475
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.5335551 -1.5469505
[2,] -1.2827331 -0.7028662
[3,] -0.3299839 -0.5948795
[4,] -1.5957633 0.1446454
[5,] 0.9263206 -0.5660929
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.5335551
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.5335551
[2,] -1.2827331
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 0.4064510 0.3871693 -0.3959271 -0.5140676 -0.5901209 -0.0825426
row1 -0.8336909 -1.4576344 -0.1402904 0.9460441 -2.0471624 -1.6591235
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 0.9188035 -0.8735014 -0.8410569 0.5550805 0.820129 -1.1269978 -0.01441297
row1 0.5272186 -0.3519546 -1.7311685 0.5018616 -1.659633 -0.4905395 -2.39681274
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -1.4148990 0.1335805 -1.3304934 -0.8386892 -0.9578656 -0.09956401
row1 -0.7132966 0.4308139 -0.8971843 0.3298367 0.7367731 1.16676733
[,20]
row3 1.9958117
row1 -0.1406841
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.2120079 -0.1065186 0.03784373 1.739244 -0.9408638 -0.2088327 -1.371565
[,8] [,9] [,10]
row2 -1.400977 -0.1793308 -1.342935
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.08212801 1.839259 -1.1641 -0.05465101 0.5671335 -0.1508619 -1.175158
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.340364 1.688396 0.1444835 -0.9210965 0.09611273 1.05598 -0.04050086
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.430849 -1.056187 1.335903 -1.395814 0.2130806 0.7162363
>
>
> 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: 0x13b937b0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM359f8f6185b5a6"
[2] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM359f8f7030ef0c"
[3] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM359f8f68ab2994"
[4] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM359f8f1b07a158"
[5] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM359f8f1b85be89"
[6] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM359f8f78de059c"
[7] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM359f8f522ea3b3"
[8] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM359f8f164b9b1d"
[9] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM359f8f179aeffb"
[10] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM359f8f1cbaaffe"
[11] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM359f8ffbf6c6e"
[12] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM359f8f3b26bee7"
[13] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM359f8f67085d29"
[14] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM359f8f106188ab"
[15] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM359f8fdae465d"
>
>
> ### 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: 0x14dc4cb0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x14dc4cb0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x14dc4cb0>
> rowMedians(tmp)
[1] -0.290055628 -0.125862739 -0.188790372 -0.003569734 -0.074966270
[6] -0.373172104 0.153613759 -0.215236209 -0.046439341 -0.145124728
[11] -0.125261550 0.119867205 0.643409682 0.178019045 -0.245815502
[16] 0.034985845 -0.087135338 0.034121213 0.654822800 -0.309008171
[21] -0.204053083 -0.024687497 -0.284943892 0.614664789 0.094670981
[26] -0.381842032 -0.201588008 0.158935069 0.271561637 0.109314986
[31] -0.001555283 -0.082883990 -0.317117946 -0.373245649 -0.295649860
[36] 0.643308539 0.035994387 -0.418383871 -0.115453820 -0.351428878
[41] -0.574006693 -0.187499033 0.109590817 -0.291107520 -0.248782987
[46] 0.076460021 -0.168520783 0.354545243 -0.080628286 -0.526289888
[51] -0.479793557 -0.198397208 0.021621355 0.272103624 0.448484153
[56] -0.034004068 0.414307529 0.324988601 0.351744294 -0.363449431
[61] 0.113528753 -0.138496088 -0.165544516 0.221381444 -0.532672650
[66] 0.569921676 0.119872578 0.367992045 0.099189642 -0.282711762
[71] 0.106595126 -0.147927683 -0.324112416 0.292483964 -0.311398359
[76] 0.205652720 0.511239644 0.118665372 0.274537834 0.082973301
[81] 0.585124944 -0.036573032 0.777631159 -0.463005354 -0.344846467
[86] -0.350439836 0.325453005 -0.122964118 -0.410684536 -0.113666699
[91] -0.525811710 -0.781596543 -0.092333671 0.278515057 -0.016719339
[96] 0.204440680 0.433321636 -0.097373950 0.373617120 -0.489301384
[101] 0.201325103 -0.049671246 -0.286017585 0.082256357 -0.579461813
[106] 0.117663878 -0.157082470 -0.473569748 -0.230801895 0.102163717
[111] -0.278268384 -0.542162375 0.521843387 0.046195303 0.257433200
[116] -0.035823009 -0.824671177 -0.090656644 -0.146441745 0.078754019
[121] 0.090445825 0.126082735 0.087251133 -0.138841940 0.064723583
[126] -0.638700993 0.002709265 -0.384070056 -0.685908379 0.165468713
[131] 0.097998408 -0.080566215 -0.316649432 -0.399741072 -0.031820582
[136] 0.387501295 0.010056506 -0.216493620 0.372332307 -0.215768073
[141] 0.066853660 -0.073916388 0.029003340 -0.447356606 -0.251178419
[146] 0.037374572 0.461186420 -0.024981436 0.248411787 -0.182508814
[151] 0.686326878 0.389326363 -0.097772756 -0.070253352 0.051346206
[156] 0.261382659 -0.425703750 -0.070701916 0.085668240 -0.091161283
[161] 0.336777710 0.297188741 -0.315606405 0.415951395 -0.452830281
[166] -0.148651041 0.125053020 0.058834528 -0.067036158 -0.179123502
[171] -0.020193742 -0.026230442 0.252381943 0.090781699 0.228851505
[176] -0.185510273 0.220781996 0.631331509 0.611433602 0.072239412
[181] -0.740942544 -0.613942362 0.097797201 -0.527520249 -0.259492303
[186] 0.290448647 -0.662504352 -0.080225230 0.194107808 -0.424570299
[191] 0.155114337 -0.016491951 0.410993541 -0.222429767 -0.186704372
[196] -0.240771615 0.384843667 0.464068358 0.356697563 0.218121725
[201] -0.039869956 0.731401951 0.309210692 0.342924017 -0.299061453
[206] -0.016796271 -0.308227907 -0.720446754 0.253178620 0.211743799
[211] -0.659035713 -0.285553164 -0.048842136 -0.002525705 -0.281502439
[216] 0.102441401 -0.186404619 0.084725942 -0.145572650 0.415548501
[221] -0.109140884 -0.618432770 0.130559608 -0.104051074 0.049470137
[226] -0.259088220 -0.810131370 0.359088075 0.012739470 -0.325644783
>
> proc.time()
user system elapsed
1.981 0.810 2.816
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: 0x1e230790>
> .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: 0x1e230790>
> .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: 0x1e230790>
> .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: 0x1e230790>
> 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: 0x1e4fd3c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1e4fd3c0>
> .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: 0x1e4fd3c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1e4fd3c0>
> .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: 0x1e4fd3c0>
> 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: 0x1e4da6d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1e4da6d0>
> .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: 0x1e4da6d0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x1e4da6d0>
> .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: 0x1e4da6d0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x1e4da6d0>
> .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: 0x1e4da6d0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x1e4da6d0>
> .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: 0x1e4da6d0>
> 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: 0x1e506680>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x1e506680>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1e506680>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1e506680>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile359fdb16d3f0ee" "BufferedMatrixFile359fdb6a5615a"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile359fdb16d3f0ee" "BufferedMatrixFile359fdb6a5615a"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x1db01c00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1db01c00>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x1db01c00>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x1db01c00>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x1db01c00>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x1db01c00>
> .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: 0x1ddc4cb0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1ddc4cb0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x1ddc4cb0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x1ddc4cb0>
> 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: 0x1cd33a10>
> .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: 0x1cd33a10>
> rm(P)
>
> proc.time()
user system elapsed
0.353 0.035 0.375
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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Type 'license()' or 'licence()' for distribution details.
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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
0.336 0.032 0.355