Ben Bolstad
| Snapshot Date: 2025-08-28 13:40 -0400 (Thu, 28 Aug 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_21 |
| git_last_commit: aa9e634 |
| git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-09-01 11:42 -0400 (Mon, 01 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" | 4824 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root" | 4606 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4547 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4579 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 252/2341 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.72.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.3 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: 2025-08-29 07:04:58 -0000 (Fri, 29 Aug 2025) |
| EndedAt: 2025-08-29 07:05:21 -0000 (Fri, 29 Aug 2025) |
| EllapsedTime: 23.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.72.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2025-02-19 r87757)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.72.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
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###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/R/R-devel_2025-02-19/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.72.0’
** using staged installation
** libs
using C compiler: ‘aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0’
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c init_package.c -o init_package.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -shared -L/home/biocbuild/R/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/R/R/lib -lR
installing to /home/biocbuild/R/R-devel_2025-02-19/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.333 0.032 0.353
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 477833 25.6 1045337 55.9 639800 34.2
Vcells 884297 6.8 8388608 64.0 2080696 15.9
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Aug 29 07:05:16 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Aug 29 07:05:16 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: 0xde946e0>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Aug 29 07:05:16 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Aug 29 07:05:16 2025"
>
> ColMode(tmp2)
<pointer: 0xde946e0>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.0959841 0.9116966 -0.968570 -0.01785811
[2,] -0.6726652 -0.3272832 -1.515464 0.07108145
[3,] 0.1625737 -0.6451082 1.384621 -0.93746731
[4,] 0.6693026 0.7065825 -1.563135 -2.36315198
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.0959841 0.9116966 0.968570 0.01785811
[2,] 0.6726652 0.3272832 1.515464 0.07108145
[3,] 0.1625737 0.6451082 1.384621 0.93746731
[4,] 0.6693026 0.7065825 1.563135 2.36315198
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0047981 0.9548281 0.9841596 0.1336343
[2,] 0.8201617 0.5720867 1.2310417 0.2666110
[3,] 0.4032043 0.8031863 1.1766993 0.9682290
[4,] 0.8181092 0.8405846 1.2502539 1.5372547
>
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.14396 35.45998 35.81017 26.35420
[2,] 33.87428 31.04815 38.82588 27.73719
[3,] 29.19462 33.67697 38.15161 35.61976
[4,] 33.85039 34.11243 39.06567 42.73570
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0xc46c520>
> exp(tmp5)
<pointer: 0xc46c520>
> log(tmp5,2)
<pointer: 0xc46c520>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.6077
> Min(tmp5)
[1] 53.47185
> mean(tmp5)
[1] 72.19724
> Sum(tmp5)
[1] 14439.45
> Var(tmp5)
[1] 860.3932
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.19064 66.42517 70.48970 72.36829 69.66420 71.44975 70.65596 70.91274
[9] 68.42961 72.38632
> rowSums(tmp5)
[1] 1783.813 1328.503 1409.794 1447.366 1393.284 1428.995 1413.119 1418.255
[9] 1368.592 1447.726
> rowVars(tmp5)
[1] 8028.36601 85.32401 68.58041 97.91504 72.97904 43.01053
[7] 68.73037 55.42029 78.41905 44.03813
> rowSd(tmp5)
[1] 89.601150 9.237100 8.281329 9.895203 8.542777 6.558241 8.290378
[8] 7.444480 8.855453 6.636123
> rowMax(tmp5)
[1] 468.60766 88.43192 86.57259 88.94876 84.41042 81.00451 88.42700
[8] 86.51790 86.81714 83.96180
> rowMin(tmp5)
[1] 54.85282 55.09536 58.90065 53.68386 54.16637 55.89166 56.09410 60.13988
[9] 53.47185 58.56558
>
> colMeans(tmp5)
[1] 107.80789 71.04734 72.16597 73.28824 73.73187 67.81919 73.61270
[8] 67.25553 70.89898 71.61318 70.19092 69.86379 69.92661 69.60793
[15] 69.42690 65.04706 72.62880 68.55558 69.29114 70.16514
> colSums(tmp5)
[1] 1078.0789 710.4734 721.6597 732.8824 737.3187 678.1919 736.1270
[8] 672.5553 708.9898 716.1318 701.9092 698.6379 699.2661 696.0793
[15] 694.2690 650.4706 726.2880 685.5558 692.9114 701.6514
> colVars(tmp5)
[1] 16109.40150 39.56443 66.20466 130.38516 64.27655 81.48014
[7] 52.39944 94.42486 47.38248 38.18169 54.19181 100.01209
[13] 42.23968 68.15417 97.26436 73.65671 65.72040 80.11270
[19] 88.33077 45.57941
> colSd(tmp5)
[1] 126.922817 6.290026 8.136624 11.418632 8.017266 9.026635
[7] 7.238746 9.717245 6.883493 6.179133 7.361509 10.000605
[13] 6.499206 8.255554 9.862270 8.582349 8.106812 8.950570
[19] 9.398445 6.751252
> colMax(tmp5)
[1] 468.60766 86.51790 81.31008 88.94876 84.41042 77.98238 80.89930
[8] 85.38571 80.65262 80.47450 86.81714 88.43192 80.22516 86.57259
[15] 83.96180 76.06863 84.15127 83.50426 88.42700 80.84416
> colMin(tmp5)
[1] 56.09410 63.59515 57.22931 54.85282 60.90970 53.68386 60.48242 53.47185
[9] 58.56558 60.88434 61.26164 55.89166 62.57692 55.68761 54.16637 54.34033
[17] 60.77616 56.74090 55.70199 61.64097
>
>
> ### 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] 89.19064 66.42517 NA 72.36829 69.66420 71.44975 70.65596 70.91274
[9] 68.42961 72.38632
> rowSums(tmp5)
[1] 1783.813 1328.503 NA 1447.366 1393.284 1428.995 1413.119 1418.255
[9] 1368.592 1447.726
> rowVars(tmp5)
[1] 8028.36601 85.32401 70.00555 97.91504 72.97904 43.01053
[7] 68.73037 55.42029 78.41905 44.03813
> rowSd(tmp5)
[1] 89.601150 9.237100 8.366932 9.895203 8.542777 6.558241 8.290378
[8] 7.444480 8.855453 6.636123
> rowMax(tmp5)
[1] 468.60766 88.43192 NA 88.94876 84.41042 81.00451 88.42700
[8] 86.51790 86.81714 83.96180
> rowMin(tmp5)
[1] 54.85282 55.09536 NA 53.68386 54.16637 55.89166 56.09410 60.13988
[9] 53.47185 58.56558
>
> colMeans(tmp5)
[1] 107.80789 71.04734 72.16597 73.28824 73.73187 67.81919 73.61270
[8] 67.25553 70.89898 71.61318 70.19092 69.86379 69.92661 69.60793
[15] 69.42690 65.04706 72.62880 NA 69.29114 70.16514
> colSums(tmp5)
[1] 1078.0789 710.4734 721.6597 732.8824 737.3187 678.1919 736.1270
[8] 672.5553 708.9898 716.1318 701.9092 698.6379 699.2661 696.0793
[15] 694.2690 650.4706 726.2880 NA 692.9114 701.6514
> colVars(tmp5)
[1] 16109.40150 39.56443 66.20466 130.38516 64.27655 81.48014
[7] 52.39944 94.42486 47.38248 38.18169 54.19181 100.01209
[13] 42.23968 68.15417 97.26436 73.65671 65.72040 NA
[19] 88.33077 45.57941
> colSd(tmp5)
[1] 126.922817 6.290026 8.136624 11.418632 8.017266 9.026635
[7] 7.238746 9.717245 6.883493 6.179133 7.361509 10.000605
[13] 6.499206 8.255554 9.862270 8.582349 8.106812 NA
[19] 9.398445 6.751252
> colMax(tmp5)
[1] 468.60766 86.51790 81.31008 88.94876 84.41042 77.98238 80.89930
[8] 85.38571 80.65262 80.47450 86.81714 88.43192 80.22516 86.57259
[15] 83.96180 76.06863 84.15127 NA 88.42700 80.84416
> colMin(tmp5)
[1] 56.09410 63.59515 57.22931 54.85282 60.90970 53.68386 60.48242 53.47185
[9] 58.56558 60.88434 61.26164 55.89166 62.57692 55.68761 54.16637 54.34033
[17] 60.77616 NA 55.70199 61.64097
>
> Max(tmp5,na.rm=TRUE)
[1] 468.6077
> Min(tmp5,na.rm=TRUE)
[1] 53.47185
> mean(tmp5,na.rm=TRUE)
[1] 72.23791
> Sum(tmp5,na.rm=TRUE)
[1] 14375.34
> Var(tmp5,na.rm=TRUE)
[1] 864.4061
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.19064 66.42517 70.82581 72.36829 69.66420 71.44975 70.65596 70.91274
[9] 68.42961 72.38632
> rowSums(tmp5,na.rm=TRUE)
[1] 1783.813 1328.503 1345.690 1447.366 1393.284 1428.995 1413.119 1418.255
[9] 1368.592 1447.726
> rowVars(tmp5,na.rm=TRUE)
[1] 8028.36601 85.32401 70.00555 97.91504 72.97904 43.01053
[7] 68.73037 55.42029 78.41905 44.03813
> rowSd(tmp5,na.rm=TRUE)
[1] 89.601150 9.237100 8.366932 9.895203 8.542777 6.558241 8.290378
[8] 7.444480 8.855453 6.636123
> rowMax(tmp5,na.rm=TRUE)
[1] 468.60766 88.43192 86.57259 88.94876 84.41042 81.00451 88.42700
[8] 86.51790 86.81714 83.96180
> rowMin(tmp5,na.rm=TRUE)
[1] 54.85282 55.09536 58.90065 53.68386 54.16637 55.89166 56.09410 60.13988
[9] 53.47185 58.56558
>
> colMeans(tmp5,na.rm=TRUE)
[1] 107.80789 71.04734 72.16597 73.28824 73.73187 67.81919 73.61270
[8] 67.25553 70.89898 71.61318 70.19092 69.86379 69.92661 69.60793
[15] 69.42690 65.04706 72.62880 69.05024 69.29114 70.16514
> colSums(tmp5,na.rm=TRUE)
[1] 1078.0789 710.4734 721.6597 732.8824 737.3187 678.1919 736.1270
[8] 672.5553 708.9898 716.1318 701.9092 698.6379 699.2661 696.0793
[15] 694.2690 650.4706 726.2880 621.4522 692.9114 701.6514
> colVars(tmp5,na.rm=TRUE)
[1] 16109.40150 39.56443 66.20466 130.38516 64.27655 81.48014
[7] 52.39944 94.42486 47.38248 38.18169 54.19181 100.01209
[13] 42.23968 68.15417 97.26436 73.65671 65.72040 87.37406
[19] 88.33077 45.57941
> colSd(tmp5,na.rm=TRUE)
[1] 126.922817 6.290026 8.136624 11.418632 8.017266 9.026635
[7] 7.238746 9.717245 6.883493 6.179133 7.361509 10.000605
[13] 6.499206 8.255554 9.862270 8.582349 8.106812 9.347409
[19] 9.398445 6.751252
> colMax(tmp5,na.rm=TRUE)
[1] 468.60766 86.51790 81.31008 88.94876 84.41042 77.98238 80.89930
[8] 85.38571 80.65262 80.47450 86.81714 88.43192 80.22516 86.57259
[15] 83.96180 76.06863 84.15127 83.50426 88.42700 80.84416
> colMin(tmp5,na.rm=TRUE)
[1] 56.09410 63.59515 57.22931 54.85282 60.90970 53.68386 60.48242 53.47185
[9] 58.56558 60.88434 61.26164 55.89166 62.57692 55.68761 54.16637 54.34033
[17] 60.77616 56.74090 55.70199 61.64097
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.19064 66.42517 NaN 72.36829 69.66420 71.44975 70.65596 70.91274
[9] 68.42961 72.38632
> rowSums(tmp5,na.rm=TRUE)
[1] 1783.813 1328.503 0.000 1447.366 1393.284 1428.995 1413.119 1418.255
[9] 1368.592 1447.726
> rowVars(tmp5,na.rm=TRUE)
[1] 8028.36601 85.32401 NA 97.91504 72.97904 43.01053
[7] 68.73037 55.42029 78.41905 44.03813
> rowSd(tmp5,na.rm=TRUE)
[1] 89.601150 9.237100 NA 9.895203 8.542777 6.558241 8.290378
[8] 7.444480 8.855453 6.636123
> rowMax(tmp5,na.rm=TRUE)
[1] 468.60766 88.43192 NA 88.94876 84.41042 81.00451 88.42700
[8] 86.51790 86.81714 83.96180
> rowMin(tmp5,na.rm=TRUE)
[1] 54.85282 55.09536 NA 53.68386 54.16637 55.89166 56.09410 60.13988
[9] 53.47185 58.56558
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.03490 71.15324 71.36135 73.19384 73.57772 68.64044 75.07162
[8] 66.94781 70.76693 71.39584 69.84885 70.79248 70.72048 67.72297
[15] 67.98881 65.72999 71.77337 NaN 68.40675 70.56164
> colSums(tmp5,na.rm=TRUE)
[1] 1017.3141 640.3792 642.2521 658.7446 662.1995 617.7640 675.6445
[8] 602.5303 636.9023 642.5626 628.6396 637.1323 636.4844 609.5067
[15] 611.8993 591.5699 645.9603 0.0000 615.6608 635.0548
> colVars(tmp5,na.rm=TRUE)
[1] 17815.70792 44.38380 67.19677 146.58305 72.04377 84.07748
[7] 35.00434 105.16269 53.10911 42.42299 59.64941 102.81093
[13] 40.42938 36.70127 86.15634 77.61681 65.70310 NA
[19] 90.57294 49.50820
> colSd(tmp5,na.rm=TRUE)
[1] 133.475496 6.662117 8.197364 12.107149 8.487860 9.169377
[7] 5.916447 10.254886 7.287600 6.513293 7.723303 10.139572
[13] 6.358410 6.058157 9.282044 8.810040 8.105745 NA
[19] 9.516982 7.036207
> colMax(tmp5,na.rm=TRUE)
[1] 468.60766 86.51790 81.31008 88.94876 84.41042 77.98238 80.89930
[8] 85.38571 80.65262 80.47450 86.81714 88.43192 80.22516 73.99901
[15] 83.96180 76.06863 84.15127 -Inf 88.42700 80.84416
> colMin(tmp5,na.rm=TRUE)
[1] 56.09410 63.59515 57.22931 54.85282 60.90970 53.68386 64.90204 53.47185
[9] 58.56558 60.88434 61.26164 55.89166 62.57692 55.68761 54.16637 54.34033
[17] 60.77616 Inf 55.70199 61.64097
>
>
>
>
> 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] 161.0359 163.3255 225.6928 243.3994 210.8361 199.7685 285.1227 239.0654
[9] 256.6060 237.4944
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 161.0359 163.3255 225.6928 243.3994 210.8361 199.7685 285.1227 239.0654
[9] 256.6060 237.4944
>
>
>
> 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] 0.000000e+00 5.684342e-14 -1.136868e-13 -3.410605e-13 -1.136868e-13
[6] -5.684342e-14 0.000000e+00 -2.273737e-13 6.252776e-13 -5.684342e-14
[11] 8.526513e-14 -1.136868e-13 5.684342e-14 5.684342e-14 2.557954e-13
[16] -1.136868e-13 0.000000e+00 -2.842171e-14 0.000000e+00 2.842171e-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)
+ }
3 19
3 19
7 18
1 15
7 8
2 1
7 17
2 4
7 19
1 13
4 9
2 13
1 6
9 18
3 13
5 19
4 11
2 12
2 5
3 2
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.840931
> Min(tmp)
[1] -2.958813
> mean(tmp)
[1] 0.1949279
> Sum(tmp)
[1] 19.49279
> Var(tmp)
[1] 1.359678
>
> rowMeans(tmp)
[1] 0.1949279
> rowSums(tmp)
[1] 19.49279
> rowVars(tmp)
[1] 1.359678
> rowSd(tmp)
[1] 1.166052
> rowMax(tmp)
[1] 2.840931
> rowMin(tmp)
[1] -2.958813
>
> colMeans(tmp)
[1] 1.2337589085 0.1461411244 -0.3992480280 -0.0004584311 1.0609199326
[6] 1.1387939531 0.1689133190 0.3508767006 -0.8707957980 1.0411993589
[11] 0.7153271817 0.5068969115 -0.0821533808 1.9470908406 -1.6033372203
[16] 0.8311280264 0.7793561205 -1.6644534045 0.4783146868 -0.0306493939
[21] -0.7955555956 0.0487775186 -1.2815909800 -0.8148966136 1.0527393676
[26] 2.2827355317 -0.3045191074 -0.4748196369 1.1872427260 0.0970908777
[31] 1.0613043250 0.6162074591 -1.0038181737 -0.0733161599 0.9125792820
[36] 1.6201269959 -0.4786088455 0.6515170777 1.5959578744 0.6528816873
[41] 1.7089665016 2.1280158818 1.0583204648 -1.0438208693 -0.9386897389
[46] 0.6686103810 -1.7608222701 1.3121273031 0.4621626236 -0.5929484719
[51] 0.2987864826 2.7269579246 -1.2964996588 1.0961252265 -0.3585084946
[56] 1.6773779626 1.5361080549 0.5544288674 -2.9588134656 1.2234526187
[61] 0.0356537749 -0.9932724072 -1.2450193358 -1.3559031189 0.2833304814
[66] -0.4525861140 0.1535196302 -0.4321389475 1.1144106885 0.2113117440
[71] 0.0021675615 0.7907540746 0.2647148117 1.8564332222 -1.5323803162
[76] -1.0354979064 -2.3708528461 1.4789634830 1.4577589309 -1.0169793143
[81] 0.2211045759 -0.2447290150 1.5928768753 2.8409309344 1.0416982041
[86] 2.5107156126 -1.1970739221 -1.0348042891 -1.0597298605 0.4517925320
[91] -0.8044361981 -1.1283570271 0.9735652503 0.5792160249 0.7437293672
[96] -1.5593751943 -0.8993396480 0.8732878868 0.3394502393 -1.7631113252
> colSums(tmp)
[1] 1.2337589085 0.1461411244 -0.3992480280 -0.0004584311 1.0609199326
[6] 1.1387939531 0.1689133190 0.3508767006 -0.8707957980 1.0411993589
[11] 0.7153271817 0.5068969115 -0.0821533808 1.9470908406 -1.6033372203
[16] 0.8311280264 0.7793561205 -1.6644534045 0.4783146868 -0.0306493939
[21] -0.7955555956 0.0487775186 -1.2815909800 -0.8148966136 1.0527393676
[26] 2.2827355317 -0.3045191074 -0.4748196369 1.1872427260 0.0970908777
[31] 1.0613043250 0.6162074591 -1.0038181737 -0.0733161599 0.9125792820
[36] 1.6201269959 -0.4786088455 0.6515170777 1.5959578744 0.6528816873
[41] 1.7089665016 2.1280158818 1.0583204648 -1.0438208693 -0.9386897389
[46] 0.6686103810 -1.7608222701 1.3121273031 0.4621626236 -0.5929484719
[51] 0.2987864826 2.7269579246 -1.2964996588 1.0961252265 -0.3585084946
[56] 1.6773779626 1.5361080549 0.5544288674 -2.9588134656 1.2234526187
[61] 0.0356537749 -0.9932724072 -1.2450193358 -1.3559031189 0.2833304814
[66] -0.4525861140 0.1535196302 -0.4321389475 1.1144106885 0.2113117440
[71] 0.0021675615 0.7907540746 0.2647148117 1.8564332222 -1.5323803162
[76] -1.0354979064 -2.3708528461 1.4789634830 1.4577589309 -1.0169793143
[81] 0.2211045759 -0.2447290150 1.5928768753 2.8409309344 1.0416982041
[86] 2.5107156126 -1.1970739221 -1.0348042891 -1.0597298605 0.4517925320
[91] -0.8044361981 -1.1283570271 0.9735652503 0.5792160249 0.7437293672
[96] -1.5593751943 -0.8993396480 0.8732878868 0.3394502393 -1.7631113252
> 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] 1.2337589085 0.1461411244 -0.3992480280 -0.0004584311 1.0609199326
[6] 1.1387939531 0.1689133190 0.3508767006 -0.8707957980 1.0411993589
[11] 0.7153271817 0.5068969115 -0.0821533808 1.9470908406 -1.6033372203
[16] 0.8311280264 0.7793561205 -1.6644534045 0.4783146868 -0.0306493939
[21] -0.7955555956 0.0487775186 -1.2815909800 -0.8148966136 1.0527393676
[26] 2.2827355317 -0.3045191074 -0.4748196369 1.1872427260 0.0970908777
[31] 1.0613043250 0.6162074591 -1.0038181737 -0.0733161599 0.9125792820
[36] 1.6201269959 -0.4786088455 0.6515170777 1.5959578744 0.6528816873
[41] 1.7089665016 2.1280158818 1.0583204648 -1.0438208693 -0.9386897389
[46] 0.6686103810 -1.7608222701 1.3121273031 0.4621626236 -0.5929484719
[51] 0.2987864826 2.7269579246 -1.2964996588 1.0961252265 -0.3585084946
[56] 1.6773779626 1.5361080549 0.5544288674 -2.9588134656 1.2234526187
[61] 0.0356537749 -0.9932724072 -1.2450193358 -1.3559031189 0.2833304814
[66] -0.4525861140 0.1535196302 -0.4321389475 1.1144106885 0.2113117440
[71] 0.0021675615 0.7907540746 0.2647148117 1.8564332222 -1.5323803162
[76] -1.0354979064 -2.3708528461 1.4789634830 1.4577589309 -1.0169793143
[81] 0.2211045759 -0.2447290150 1.5928768753 2.8409309344 1.0416982041
[86] 2.5107156126 -1.1970739221 -1.0348042891 -1.0597298605 0.4517925320
[91] -0.8044361981 -1.1283570271 0.9735652503 0.5792160249 0.7437293672
[96] -1.5593751943 -0.8993396480 0.8732878868 0.3394502393 -1.7631113252
> colMin(tmp)
[1] 1.2337589085 0.1461411244 -0.3992480280 -0.0004584311 1.0609199326
[6] 1.1387939531 0.1689133190 0.3508767006 -0.8707957980 1.0411993589
[11] 0.7153271817 0.5068969115 -0.0821533808 1.9470908406 -1.6033372203
[16] 0.8311280264 0.7793561205 -1.6644534045 0.4783146868 -0.0306493939
[21] -0.7955555956 0.0487775186 -1.2815909800 -0.8148966136 1.0527393676
[26] 2.2827355317 -0.3045191074 -0.4748196369 1.1872427260 0.0970908777
[31] 1.0613043250 0.6162074591 -1.0038181737 -0.0733161599 0.9125792820
[36] 1.6201269959 -0.4786088455 0.6515170777 1.5959578744 0.6528816873
[41] 1.7089665016 2.1280158818 1.0583204648 -1.0438208693 -0.9386897389
[46] 0.6686103810 -1.7608222701 1.3121273031 0.4621626236 -0.5929484719
[51] 0.2987864826 2.7269579246 -1.2964996588 1.0961252265 -0.3585084946
[56] 1.6773779626 1.5361080549 0.5544288674 -2.9588134656 1.2234526187
[61] 0.0356537749 -0.9932724072 -1.2450193358 -1.3559031189 0.2833304814
[66] -0.4525861140 0.1535196302 -0.4321389475 1.1144106885 0.2113117440
[71] 0.0021675615 0.7907540746 0.2647148117 1.8564332222 -1.5323803162
[76] -1.0354979064 -2.3708528461 1.4789634830 1.4577589309 -1.0169793143
[81] 0.2211045759 -0.2447290150 1.5928768753 2.8409309344 1.0416982041
[86] 2.5107156126 -1.1970739221 -1.0348042891 -1.0597298605 0.4517925320
[91] -0.8044361981 -1.1283570271 0.9735652503 0.5792160249 0.7437293672
[96] -1.5593751943 -0.8993396480 0.8732878868 0.3394502393 -1.7631113252
> colMedians(tmp)
[1] 1.2337589085 0.1461411244 -0.3992480280 -0.0004584311 1.0609199326
[6] 1.1387939531 0.1689133190 0.3508767006 -0.8707957980 1.0411993589
[11] 0.7153271817 0.5068969115 -0.0821533808 1.9470908406 -1.6033372203
[16] 0.8311280264 0.7793561205 -1.6644534045 0.4783146868 -0.0306493939
[21] -0.7955555956 0.0487775186 -1.2815909800 -0.8148966136 1.0527393676
[26] 2.2827355317 -0.3045191074 -0.4748196369 1.1872427260 0.0970908777
[31] 1.0613043250 0.6162074591 -1.0038181737 -0.0733161599 0.9125792820
[36] 1.6201269959 -0.4786088455 0.6515170777 1.5959578744 0.6528816873
[41] 1.7089665016 2.1280158818 1.0583204648 -1.0438208693 -0.9386897389
[46] 0.6686103810 -1.7608222701 1.3121273031 0.4621626236 -0.5929484719
[51] 0.2987864826 2.7269579246 -1.2964996588 1.0961252265 -0.3585084946
[56] 1.6773779626 1.5361080549 0.5544288674 -2.9588134656 1.2234526187
[61] 0.0356537749 -0.9932724072 -1.2450193358 -1.3559031189 0.2833304814
[66] -0.4525861140 0.1535196302 -0.4321389475 1.1144106885 0.2113117440
[71] 0.0021675615 0.7907540746 0.2647148117 1.8564332222 -1.5323803162
[76] -1.0354979064 -2.3708528461 1.4789634830 1.4577589309 -1.0169793143
[81] 0.2211045759 -0.2447290150 1.5928768753 2.8409309344 1.0416982041
[86] 2.5107156126 -1.1970739221 -1.0348042891 -1.0597298605 0.4517925320
[91] -0.8044361981 -1.1283570271 0.9735652503 0.5792160249 0.7437293672
[96] -1.5593751943 -0.8993396480 0.8732878868 0.3394502393 -1.7631113252
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.233759 0.1461411 -0.399248 -0.0004584311 1.06092 1.138794 0.1689133
[2,] 1.233759 0.1461411 -0.399248 -0.0004584311 1.06092 1.138794 0.1689133
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.3508767 -0.8707958 1.041199 0.7153272 0.5068969 -0.08215338 1.947091
[2,] 0.3508767 -0.8707958 1.041199 0.7153272 0.5068969 -0.08215338 1.947091
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.603337 0.831128 0.7793561 -1.664453 0.4783147 -0.03064939 -0.7955556
[2,] -1.603337 0.831128 0.7793561 -1.664453 0.4783147 -0.03064939 -0.7955556
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.04877752 -1.281591 -0.8148966 1.052739 2.282736 -0.3045191 -0.4748196
[2,] 0.04877752 -1.281591 -0.8148966 1.052739 2.282736 -0.3045191 -0.4748196
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.187243 0.09709088 1.061304 0.6162075 -1.003818 -0.07331616 0.9125793
[2,] 1.187243 0.09709088 1.061304 0.6162075 -1.003818 -0.07331616 0.9125793
[,36] [,37] [,38] [,39] [,40] [,41] [,42] [,43]
[1,] 1.620127 -0.4786088 0.6515171 1.595958 0.6528817 1.708967 2.128016 1.05832
[2,] 1.620127 -0.4786088 0.6515171 1.595958 0.6528817 1.708967 2.128016 1.05832
[,44] [,45] [,46] [,47] [,48] [,49] [,50]
[1,] -1.043821 -0.9386897 0.6686104 -1.760822 1.312127 0.4621626 -0.5929485
[2,] -1.043821 -0.9386897 0.6686104 -1.760822 1.312127 0.4621626 -0.5929485
[,51] [,52] [,53] [,54] [,55] [,56] [,57] [,58]
[1,] 0.2987865 2.726958 -1.2965 1.096125 -0.3585085 1.677378 1.536108 0.5544289
[2,] 0.2987865 2.726958 -1.2965 1.096125 -0.3585085 1.677378 1.536108 0.5544289
[,59] [,60] [,61] [,62] [,63] [,64] [,65]
[1,] -2.958813 1.223453 0.03565377 -0.9932724 -1.245019 -1.355903 0.2833305
[2,] -2.958813 1.223453 0.03565377 -0.9932724 -1.245019 -1.355903 0.2833305
[,66] [,67] [,68] [,69] [,70] [,71] [,72]
[1,] -0.4525861 0.1535196 -0.4321389 1.114411 0.2113117 0.002167561 0.7907541
[2,] -0.4525861 0.1535196 -0.4321389 1.114411 0.2113117 0.002167561 0.7907541
[,73] [,74] [,75] [,76] [,77] [,78] [,79]
[1,] 0.2647148 1.856433 -1.53238 -1.035498 -2.370853 1.478963 1.457759
[2,] 0.2647148 1.856433 -1.53238 -1.035498 -2.370853 1.478963 1.457759
[,80] [,81] [,82] [,83] [,84] [,85] [,86]
[1,] -1.016979 0.2211046 -0.244729 1.592877 2.840931 1.041698 2.510716
[2,] -1.016979 0.2211046 -0.244729 1.592877 2.840931 1.041698 2.510716
[,87] [,88] [,89] [,90] [,91] [,92] [,93]
[1,] -1.197074 -1.034804 -1.05973 0.4517925 -0.8044362 -1.128357 0.9735653
[2,] -1.197074 -1.034804 -1.05973 0.4517925 -0.8044362 -1.128357 0.9735653
[,94] [,95] [,96] [,97] [,98] [,99] [,100]
[1,] 0.579216 0.7437294 -1.559375 -0.8993396 0.8732879 0.3394502 -1.763111
[2,] 0.579216 0.7437294 -1.559375 -0.8993396 0.8732879 0.3394502 -1.763111
>
>
> Max(tmp2)
[1] 1.831058
> Min(tmp2)
[1] -2.554891
> mean(tmp2)
[1] -0.2333521
> Sum(tmp2)
[1] -23.33521
> Var(tmp2)
[1] 0.9622049
>
> rowMeans(tmp2)
[1] 0.009177403 -1.417661109 1.005116862 -1.149546192 -0.140955762
[6] -0.171180221 1.385095982 -1.153218041 0.733938131 0.971783954
[11] 1.208080384 -1.080369265 0.257748784 -0.821120184 0.216534972
[16] -0.044330655 -1.471360095 1.310553576 0.964954296 -1.695393274
[21] -1.282992920 0.502641369 -1.193929177 -0.126792626 0.149726038
[26] -1.150042272 0.069727834 -0.219998199 -0.289567543 -0.890603408
[31] -1.295111794 -1.228447030 1.476907257 0.144615279 -0.507936657
[36] -1.777206896 0.181114877 -0.143996962 0.114658420 -2.554891317
[41] -0.101776496 -1.928095097 0.907945617 0.358337254 -0.008465827
[46] -0.194866165 0.661348734 0.352801268 -1.066439552 -0.214450139
[51] 0.776184766 1.450156251 -1.176988985 0.517817078 0.591857569
[56] -0.918194476 -0.190190776 0.656537503 -0.283690849 -1.754289677
[61] -0.774069197 -1.839048914 -0.313657986 1.064326789 0.751581341
[66] 1.179560845 0.042653766 -0.960660374 0.243123123 -1.051169922
[71] -0.571678994 1.831058438 0.499196630 0.584124503 -1.278476820
[76] -2.367169750 -1.233203425 -0.224449586 0.216184905 0.380671415
[81] -0.598492202 -0.702730197 -2.067533613 -0.065060222 -0.407428373
[86] 0.838734211 -2.018377568 1.319396191 -0.022190099 -0.012826914
[91] 0.988780734 -0.368501795 0.318621346 -1.425134797 -1.158152541
[96] -0.436543499 -0.499752440 -1.765027647 0.084854990 1.151996679
> rowSums(tmp2)
[1] 0.009177403 -1.417661109 1.005116862 -1.149546192 -0.140955762
[6] -0.171180221 1.385095982 -1.153218041 0.733938131 0.971783954
[11] 1.208080384 -1.080369265 0.257748784 -0.821120184 0.216534972
[16] -0.044330655 -1.471360095 1.310553576 0.964954296 -1.695393274
[21] -1.282992920 0.502641369 -1.193929177 -0.126792626 0.149726038
[26] -1.150042272 0.069727834 -0.219998199 -0.289567543 -0.890603408
[31] -1.295111794 -1.228447030 1.476907257 0.144615279 -0.507936657
[36] -1.777206896 0.181114877 -0.143996962 0.114658420 -2.554891317
[41] -0.101776496 -1.928095097 0.907945617 0.358337254 -0.008465827
[46] -0.194866165 0.661348734 0.352801268 -1.066439552 -0.214450139
[51] 0.776184766 1.450156251 -1.176988985 0.517817078 0.591857569
[56] -0.918194476 -0.190190776 0.656537503 -0.283690849 -1.754289677
[61] -0.774069197 -1.839048914 -0.313657986 1.064326789 0.751581341
[66] 1.179560845 0.042653766 -0.960660374 0.243123123 -1.051169922
[71] -0.571678994 1.831058438 0.499196630 0.584124503 -1.278476820
[76] -2.367169750 -1.233203425 -0.224449586 0.216184905 0.380671415
[81] -0.598492202 -0.702730197 -2.067533613 -0.065060222 -0.407428373
[86] 0.838734211 -2.018377568 1.319396191 -0.022190099 -0.012826914
[91] 0.988780734 -0.368501795 0.318621346 -1.425134797 -1.158152541
[96] -0.436543499 -0.499752440 -1.765027647 0.084854990 1.151996679
> 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] 0.009177403 -1.417661109 1.005116862 -1.149546192 -0.140955762
[6] -0.171180221 1.385095982 -1.153218041 0.733938131 0.971783954
[11] 1.208080384 -1.080369265 0.257748784 -0.821120184 0.216534972
[16] -0.044330655 -1.471360095 1.310553576 0.964954296 -1.695393274
[21] -1.282992920 0.502641369 -1.193929177 -0.126792626 0.149726038
[26] -1.150042272 0.069727834 -0.219998199 -0.289567543 -0.890603408
[31] -1.295111794 -1.228447030 1.476907257 0.144615279 -0.507936657
[36] -1.777206896 0.181114877 -0.143996962 0.114658420 -2.554891317
[41] -0.101776496 -1.928095097 0.907945617 0.358337254 -0.008465827
[46] -0.194866165 0.661348734 0.352801268 -1.066439552 -0.214450139
[51] 0.776184766 1.450156251 -1.176988985 0.517817078 0.591857569
[56] -0.918194476 -0.190190776 0.656537503 -0.283690849 -1.754289677
[61] -0.774069197 -1.839048914 -0.313657986 1.064326789 0.751581341
[66] 1.179560845 0.042653766 -0.960660374 0.243123123 -1.051169922
[71] -0.571678994 1.831058438 0.499196630 0.584124503 -1.278476820
[76] -2.367169750 -1.233203425 -0.224449586 0.216184905 0.380671415
[81] -0.598492202 -0.702730197 -2.067533613 -0.065060222 -0.407428373
[86] 0.838734211 -2.018377568 1.319396191 -0.022190099 -0.012826914
[91] 0.988780734 -0.368501795 0.318621346 -1.425134797 -1.158152541
[96] -0.436543499 -0.499752440 -1.765027647 0.084854990 1.151996679
> rowMin(tmp2)
[1] 0.009177403 -1.417661109 1.005116862 -1.149546192 -0.140955762
[6] -0.171180221 1.385095982 -1.153218041 0.733938131 0.971783954
[11] 1.208080384 -1.080369265 0.257748784 -0.821120184 0.216534972
[16] -0.044330655 -1.471360095 1.310553576 0.964954296 -1.695393274
[21] -1.282992920 0.502641369 -1.193929177 -0.126792626 0.149726038
[26] -1.150042272 0.069727834 -0.219998199 -0.289567543 -0.890603408
[31] -1.295111794 -1.228447030 1.476907257 0.144615279 -0.507936657
[36] -1.777206896 0.181114877 -0.143996962 0.114658420 -2.554891317
[41] -0.101776496 -1.928095097 0.907945617 0.358337254 -0.008465827
[46] -0.194866165 0.661348734 0.352801268 -1.066439552 -0.214450139
[51] 0.776184766 1.450156251 -1.176988985 0.517817078 0.591857569
[56] -0.918194476 -0.190190776 0.656537503 -0.283690849 -1.754289677
[61] -0.774069197 -1.839048914 -0.313657986 1.064326789 0.751581341
[66] 1.179560845 0.042653766 -0.960660374 0.243123123 -1.051169922
[71] -0.571678994 1.831058438 0.499196630 0.584124503 -1.278476820
[76] -2.367169750 -1.233203425 -0.224449586 0.216184905 0.380671415
[81] -0.598492202 -0.702730197 -2.067533613 -0.065060222 -0.407428373
[86] 0.838734211 -2.018377568 1.319396191 -0.022190099 -0.012826914
[91] 0.988780734 -0.368501795 0.318621346 -1.425134797 -1.158152541
[96] -0.436543499 -0.499752440 -1.765027647 0.084854990 1.151996679
>
> colMeans(tmp2)
[1] -0.2333521
> colSums(tmp2)
[1] -23.33521
> colVars(tmp2)
[1] 0.9622049
> colSd(tmp2)
[1] 0.9809205
> colMax(tmp2)
[1] 1.831058
> colMin(tmp2)
[1] -2.554891
> colMedians(tmp2)
[1] -0.1424764
> colRanges(tmp2)
[,1]
[1,] -2.554891
[2,] 1.831058
>
> 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] 3.4152401 -1.9561118 -2.7659873 -2.5580470 -4.6114655 -3.5109113
[7] -0.9847843 3.9842356 -2.2287558 1.1001562
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8291415
[2,] -0.2313829
[3,] 0.3666052
[4,] 0.8843950
[5,] 1.5076958
>
> rowApply(tmp,sum)
[1] -3.0003678 -5.8045322 4.3577478 0.7369102 6.7094559 -2.8127306
[7] -4.7554942 -6.1801464 0.1828084 0.4499178
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 6 3 10 1 7 4 9 7 8
[2,] 4 9 1 6 3 9 6 1 6 7
[3,] 10 1 9 3 5 4 8 2 2 4
[4,] 2 3 6 9 9 1 5 4 3 10
[5,] 6 4 7 1 7 2 7 7 5 1
[6,] 3 2 8 8 6 3 1 8 1 6
[7,] 8 7 5 4 2 10 3 3 4 5
[8,] 7 10 4 7 4 8 9 10 8 3
[9,] 5 5 2 2 8 5 10 6 9 2
[10,] 1 8 10 5 10 6 2 5 10 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.638807727 2.798492189 0.528076383 -2.379813244 -0.277086871
[6] -4.100615477 -0.700003400 -1.259176496 -2.757924413 2.298819505
[11] 2.672286100 -2.051217625 -0.434251866 2.962097029 0.943445628
[16] 0.280888029 -0.003555411 -0.235943881 -2.980093608 -0.058145630
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8907547
[2,] -0.8580272
[3,] 0.2146409
[4,] 0.3099085
[5,] 0.5854247
>
> rowApply(tmp,sum)
[1] 9.342060 3.451168 -1.717928 -10.717273 -5.750557
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 9 13 16 7 3
[2,] 18 9 15 20 14
[3,] 11 5 7 8 19
[4,] 4 3 12 1 18
[5,] 17 11 8 6 9
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.2146409 1.70294783 0.4289420 -0.5152282 1.68020966 -0.90045835
[2,] 0.3099085 -0.08849923 -0.3581448 -0.6334615 -0.02347308 0.26592017
[3,] 0.5854247 0.55370188 -0.6196960 0.3833135 -0.52068042 -0.83413871
[4,] -0.8907547 0.84928689 -0.3881173 -2.8894578 -0.91170102 -0.03383861
[5,] -0.8580272 -0.21894518 1.4650925 1.2750207 -0.50144200 -2.59809997
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.9836798 -0.7639961 -0.76046442 -0.06968846 2.0410348 0.9463205
[2,] -1.3336736 -0.3039182 -0.09657284 2.04888724 0.9233460 -0.5424447
[3,] -1.4109495 0.8101139 -1.03642173 0.39027186 0.8205308 -0.1675272
[4,] -0.1031522 -0.2411077 -0.36584247 0.42333587 -0.2604117 -1.3513536
[5,] 0.1640921 -0.7602684 -0.49862296 -0.49398700 -0.8522138 -0.9362126
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.2528402 0.48285809 -0.1000649 0.7659587 -0.2240329 1.65410569
[2,] 0.6590928 1.62475656 -0.3122297 -0.7720805 0.8253136 -0.07228075
[3,] 0.4039893 1.00218854 1.0394346 0.3588732 0.1917875 -1.14791374
[4,] -1.1117910 -0.24516964 -1.4333575 0.5322907 -0.2145536 -0.36358010
[5,] -0.6383831 0.09746348 1.7496633 -0.6041540 -0.5820699 -0.30627497
[,19] [,20]
[1,] 0.08533384 0.43712145
[2,] 0.32643301 1.00428862
[3,] -1.40042380 -1.11980711
[4,] -1.80218569 0.08418866
[5,] -0.18925097 -0.46393726
>
>
> 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 : 649 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 : 561 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 -0.2918086 -0.7243557 0.9090174 0.472968 0.564617 -1.631831 3.028308
col8 col9 col10 col11 col12 col13 col14
row1 -0.08275555 1.049841 1.932056 0.699986 1.03007 0.5415187 -0.03691932
col15 col16 col17 col18 col19 col20
row1 0.3586119 -0.5982853 -0.8224129 -1.50271 -1.134935 0.8190534
> tmp[,"col10"]
col10
row1 1.932056056
row2 -0.006590122
row3 -0.733943958
row4 -0.474725411
row5 0.150364502
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.2918086 -0.7243557 0.909017359 0.4729680 0.5646170 -1.6318315
row5 -0.7796749 -0.3401915 -0.004506808 0.8619262 0.2503895 0.7674142
col7 col8 col9 col10 col11 col12 col13
row1 3.0283084 -0.08275555 1.0498405 1.9320561 0.6999860 1.03007 0.54151865
row5 0.1742823 -1.01741379 -0.7125421 0.1503645 -0.9225746 1.12126 -0.08538703
col14 col15 col16 col17 col18 col19
row1 -0.03691932 0.3586119 -0.5982853 -0.8224129 -1.5027102 -1.134935480
row5 -0.86620504 0.1436244 0.4069805 -0.1946362 -0.9203295 0.002387458
col20
row1 0.81905341
row5 0.07399676
> tmp[,c("col6","col20")]
col6 col20
row1 -1.63183147 0.81905341
row2 -0.63220208 2.47762802
row3 0.01482008 0.37610504
row4 -0.46123851 -2.19076818
row5 0.76741419 0.07399676
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.6318315 0.81905341
row5 0.7674142 0.07399676
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.34215 50.9967 49.58712 50.46606 51.39483 106.347 50.86139 50.6206
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.05311 50.10402 52.80726 48.25368 49.82524 49.16527 51.10444 49.38645
col17 col18 col19 col20
row1 50.61352 49.15112 49.86392 105.7079
> tmp[,"col10"]
col10
row1 50.10402
row2 29.62419
row3 29.95562
row4 30.26361
row5 49.95177
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.34215 50.99670 49.58712 50.46606 51.39483 106.3470 50.86139 50.62060
row5 49.79393 50.12988 51.22040 49.46990 49.56597 102.8418 48.23662 51.01313
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.05311 50.10402 52.80726 48.25368 49.82524 49.16527 51.10444 49.38645
row5 49.85804 49.95177 50.02847 50.07205 49.39324 49.81415 50.85221 49.83586
col17 col18 col19 col20
row1 50.61352 49.15112 49.86392 105.7079
row5 49.13545 51.37690 51.00500 105.3345
> tmp[,c("col6","col20")]
col6 col20
row1 106.34703 105.70794
row2 74.17161 75.33309
row3 74.00848 73.84941
row4 74.83638 74.27534
row5 102.84185 105.33446
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.3470 105.7079
row5 102.8418 105.3345
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.3470 105.7079
row5 102.8418 105.3345
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.0478666
[2,] 0.4483358
[3,] 2.2496851
[4,] -0.6255842
[5,] 1.8561583
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.8680249 -0.6588790
[2,] 2.5048405 1.4294590
[3,] 0.4703105 -0.6335425
[4,] -0.1207758 -0.4784997
[5,] 0.3178544 -1.1312677
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.7677934 -1.0839017
[2,] -1.8642665 -2.0513714
[3,] -0.4522644 -1.6004073
[4,] 1.6232165 -0.4593323
[5,] -1.4676548 -1.2013490
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.7677934
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.7677934
[2,] -1.8642665
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 0.6615734 1.344219 1.4405220 -0.1177452 1.946633 0.40254216 0.2378172
row1 0.9139232 -1.684395 0.5221683 0.4722034 -0.915926 0.01685083 1.2873370
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -2.443078 -0.3542457 -0.5372983 -0.8786049 -1.305312 1.2588085 0.2426631
row1 1.583989 2.0407582 -1.1196675 -0.1348495 -2.227705 0.8466317 -0.1492620
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.2078428 0.05432988 2.309352 -1.4840371 -1.2187213 0.551198344
row1 -0.4692134 0.40714418 -0.631121 0.2147352 0.8500846 0.007989645
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.2859995 -1.805117 -0.9391254 -1.449142 -0.3482762 -2.142276 2.12617
[,8] [,9] [,10]
row2 -1.174332 -1.455971 0.3108407
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.3955175 1.695866 0.8164367 -0.2911909 0.3946498 0.107373 -0.9524128
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.1704617 0.6501737 -0.09876641 0.160111 0.2740405 0.1462642 -3.238594
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.5195188 -0.179211 -0.9386438 0.2690749 0.8827865 -0.4933757
>
>
> 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: 0xe9361b0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e243244b8524"
[2] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e2433fd70234"
[3] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e24314a534ee"
[4] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e2434468433f"
[5] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e2431a2ebf90"
[6] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e24354ab9647"
[7] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e2435d5fc1c8"
[8] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e243156036f"
[9] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e243760a9b14"
[10] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e243ca4f3ec"
[11] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e24336d605ee"
[12] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e2434b6c0921"
[13] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e2435d32e3ad"
[14] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e2437ed63c3c"
[15] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e24352325015"
>
>
> ### 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: 0xf0e4d80>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0xf0e4d80>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0xf0e4d80>
> rowMedians(tmp)
[1] -5.782559e-01 -4.243277e-01 4.717668e-01 -6.227202e-03 7.771221e-02
[6] 7.639480e-02 -1.867118e-01 2.577999e-02 -5.895824e-01 3.981163e-01
[11] -5.831589e-01 8.576330e-02 1.642585e-01 -3.530224e-02 -1.078438e-01
[16] -6.220284e-02 -3.242798e-01 2.686594e-01 -1.187729e-01 1.837481e-01
[21] -1.051353e-01 -2.479670e-01 -5.374408e-01 3.467150e-01 6.792842e-02
[26] -9.284943e-02 6.552734e-01 -5.836690e-02 -1.551272e-02 4.864432e-01
[31] 4.791756e-01 -1.393468e-02 -1.234291e-01 3.828202e-01 -5.329014e-02
[36] -1.203752e-01 -2.499202e-05 2.806752e-01 -5.417512e-01 -1.619985e-01
[41] 7.066460e-02 -1.667597e-01 1.293238e-01 -8.333817e-01 2.415383e-01
[46] -6.878454e-01 5.015177e-01 -1.636642e-01 -5.204408e-01 1.304265e-01
[51] 5.364922e-01 -1.565042e-01 -3.282028e-01 2.130578e-01 -5.280780e-01
[56] -6.870096e-02 -1.566530e-01 -9.509395e-02 -2.705805e-01 -7.345040e-02
[61] 5.611928e-02 2.357480e-01 -6.514354e-02 2.770665e-01 -2.570703e-02
[66] 2.166786e-01 -2.817316e-02 -1.375623e-01 1.924534e-01 1.700297e-02
[71] 3.853238e-01 1.044542e-01 2.360070e-01 -3.133988e-01 1.504771e-01
[76] -9.927360e-02 -6.468483e-02 -1.415745e-01 4.795055e-01 3.420896e-01
[81] 1.315382e-01 2.442022e-01 1.985508e-01 -2.561444e-01 -1.614042e-01
[86] -2.686415e-01 3.614821e-01 5.977955e-01 -5.946654e-02 -1.370961e-01
[91] 7.092511e-01 2.324387e-01 2.149054e-02 3.572502e-01 6.462104e-01
[96] -3.924710e-01 3.485005e-01 -1.974249e-01 3.346002e-01 2.355096e-01
[101] -5.370889e-01 1.695874e-01 6.408193e-01 -2.589645e-01 2.211450e-01
[106] -3.639636e-01 5.535644e-01 1.417500e-01 -1.343321e-01 -1.081323e-01
[111] -3.385101e-01 5.176149e-01 1.760036e-01 -1.998552e-01 2.875084e-01
[116] -4.058174e-01 3.466817e-02 3.104302e-01 -6.004264e-01 1.797808e-01
[121] -3.084739e-01 3.064402e-01 6.043067e-01 -4.716396e-02 -1.515147e-01
[126] -1.954492e-01 -3.047348e-01 -4.085792e-01 -1.755014e-01 -3.588475e-01
[131] -9.836891e-02 -3.554570e-01 2.761490e-01 9.560595e-02 -1.314389e-01
[136] -2.626527e-01 -3.355021e-01 -1.770894e-01 4.904193e-01 -1.797504e-01
[141] -3.846731e-01 -3.210097e-01 -2.709634e-03 2.891850e-01 -1.222028e-01
[146] -8.341600e-02 3.930618e-01 -1.213206e-01 5.569140e-01 2.309238e-02
[151] -1.529349e-01 -1.380514e-01 1.653628e-01 -1.777585e-01 -1.486129e-01
[156] -1.276648e-01 3.656730e-01 -8.579543e-03 1.550840e-01 5.535239e-02
[161] 3.517330e-01 -4.524043e-01 -4.589641e-02 2.800568e-01 -1.642621e-02
[166] 1.845446e-01 3.079261e-01 2.282176e-01 1.062837e-01 3.663627e-02
[171] -3.851450e-01 3.127273e-01 1.196031e-01 3.247468e-01 2.383782e-01
[176] 1.616641e-01 -2.130810e-03 2.990355e-01 -7.112165e-01 -2.665108e-02
[181] 2.401838e-01 1.484985e-01 1.329464e-01 1.717379e-01 -1.595412e-01
[186] -9.013982e-01 3.547787e-01 1.112638e-01 1.316612e-01 1.916469e-01
[191] -7.459686e-02 8.034751e-01 -4.444241e-01 6.592266e-02 -3.580094e-01
[196] -3.243324e-01 1.909480e-01 1.332418e-01 1.953898e-01 9.884464e-02
[201] -6.894613e-03 5.020349e-01 5.625318e-01 -9.501833e-02 -5.761398e-01
[206] -6.909157e-01 3.638353e-02 5.959982e-01 -3.871368e-01 -9.303414e-02
[211] 1.020567e-01 -3.123301e-03 8.298783e-02 5.469480e-02 -4.523607e-01
[216] -1.767917e-01 -8.140686e-02 -1.988410e-01 -2.965652e-01 -5.140381e-02
[221] -5.128028e-01 -3.028148e-02 2.433645e-01 -1.274857e-01 -1.638314e-01
[226] 1.772547e-01 4.628188e-02 -2.849272e-01 8.931314e-02 -3.747760e-01
>
> proc.time()
user system elapsed
1.841 0.879 2.745
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: 0xd2136e0>
> .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: 0xd2136e0>
> .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: 0xd2136e0>
> .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: 0xd2136e0>
> 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: 0xd25b6a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xd25b6a0>
> .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: 0xd25b6a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xd25b6a0>
> .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: 0xd25b6a0>
> 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: 0xc4177d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xc4177d0>
> .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: 0xc4177d0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0xc4177d0>
> .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: 0xc4177d0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0xc4177d0>
> .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: 0xc4177d0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0xc4177d0>
> .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: 0xc4177d0>
> 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: 0xcf76d70>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0xcf76d70>
> .Call("R_bm_AddColumn",P)
<pointer: 0xcf76d70>
> .Call("R_bm_AddColumn",P)
<pointer: 0xcf76d70>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2e3fa245b785" "BufferedMatrixFile2e3fa34679e43"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2e3fa245b785" "BufferedMatrixFile2e3fa34679e43"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0xcb19cd0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xcb19cd0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0xcb19cd0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0xcb19cd0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0xcb19cd0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0xcb19cd0>
> .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: 0xba88a10>
> .Call("R_bm_AddColumn",P)
<pointer: 0xba88a10>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0xba88a10>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0xba88a10>
> 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: 0xd9a2cc0>
> .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: 0xd9a2cc0>
> rm(P)
>
> proc.time()
user system elapsed
0.354 0.028 0.368
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
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Platform: aarch64-unknown-linux-gnu
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.324 0.055 0.366