Ben Bolstad
| Snapshot Date: 2025-08-03 13:25 -0400 (Sun, 03 Aug 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 0147962 |
| git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-08-04 12:08 -0400 (Mon, 04 Aug 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.2 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4796 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.5.1 (2025-06-13 ucrt) -- "Great Square Root" | 4536 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4578 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4519 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4517 |
| 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 251/2313 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.73.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.2 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino8 | 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 | | ||||||||
| taishan | 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. |
| Package: BufferedMatrix |
| Version: 1.73.0 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.73.0.tar.gz |
| StartedAt: 2025-08-03 19:51:22 -0400 (Sun, 03 Aug 2025) |
| EndedAt: 2025-08-03 19:52:16 -0400 (Sun, 03 Aug 2025) |
| EllapsedTime: 53.8 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.73.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.1 (2025-06-13)
* using platform: x86_64-apple-darwin20
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 14.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.73.0’
* 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 ... WARNING
Found the following significant warnings:
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
* used SDK: ‘MacOSX11.3.sdk’
* 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 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 sizes of PDF files under ‘inst/doc’ ... OK
* 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: 1 WARNING, 2 NOTEs
See
‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.73.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
using SDK: ‘MacOSX11.3.sdk’
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch x86_64 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/x86_64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R
installing to /Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/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 version 4.5.1 (2025-06-13) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
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
0.366 0.158 0.512
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 (2025-06-13) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
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] "/Users/biocbuild/bbs-3.22-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) limit (Mb) max used (Mb)
Ncells 480847 25.7 1056617 56.5 NA 634462 33.9
Vcells 891074 6.8 8388608 64.0 98304 2108713 16.1
>
>
>
>
> ##
> ## 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] "Sun Aug 3 19:51:47 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] "Sun Aug 3 19:51:47 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: 0x600000c982a0>
>
>
>
> 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] "Sun Aug 3 19:51:52 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] "Sun Aug 3 19:51:53 2025"
>
> ColMode(tmp2)
<pointer: 0x600000c982a0>
>
>
>
> ### 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,] 100.26037879 -0.07091319 1.25626121 0.2686200
[2,] -1.10222258 0.55392953 -0.26914745 0.9966381
[3,] -0.80371758 -0.25833148 -0.70415185 -1.4900130
[4,] -0.02663043 -2.68496878 0.01535344 0.7338904
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-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,] 100.26037879 0.07091319 1.25626121 0.2686200
[2,] 1.10222258 0.55392953 0.26914745 0.9966381
[3,] 0.80371758 0.25833148 0.70415185 1.4900130
[4,] 0.02663043 2.68496878 0.01535344 0.7338904
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-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,] 10.0130105 0.2662953 1.1208306 0.5182857
[2,] 1.0498679 0.7442644 0.5187942 0.9983176
[3,] 0.8965030 0.5082632 0.8391376 1.2206609
[4,] 0.1631883 1.6385874 0.1239090 0.8566740
>
> 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: /Users/biocbuild/bbs-3.22-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,] 225.39048 27.73387 37.46457 30.45148
[2,] 36.60090 32.99657 30.45709 35.97981
[3,] 34.76875 30.34096 34.09553 38.69662
[4,] 26.65851 44.07084 26.25444 34.30063
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600000c98240>
> exp(tmp5)
<pointer: 0x600000c98240>
> log(tmp5,2)
<pointer: 0x600000c98240>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.1208
> Min(tmp5)
[1] 53.33445
> mean(tmp5)
[1] 72.42132
> Sum(tmp5)
[1] 14484.26
> Var(tmp5)
[1] 866.2339
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 87.96923 70.03173 67.20516 71.54101 69.25622 72.50312 72.51338 71.27858
[9] 70.91016 71.00464
> rowSums(tmp5)
[1] 1759.385 1400.635 1344.103 1430.820 1385.124 1450.062 1450.268 1425.572
[9] 1418.203 1420.093
> rowVars(tmp5)
[1] 8094.75931 117.78737 43.88654 97.78862 68.01139 59.83865
[7] 32.91528 70.78906 68.22350 112.28162
> rowSd(tmp5)
[1] 89.970880 10.852989 6.624692 9.888813 8.246902 7.735544 5.737184
[8] 8.413624 8.259752 10.596302
> rowMax(tmp5)
[1] 469.12076 89.91301 80.54195 91.72769 82.15639 84.16583 81.42079
[8] 87.71081 87.69014 93.99727
> rowMin(tmp5)
[1] 57.72441 55.35191 58.15404 54.64518 54.43604 56.32877 59.76004 56.62593
[9] 58.48021 53.33445
>
> colMeans(tmp5)
[1] 110.92500 77.41008 67.85505 69.52944 70.11750 74.01312 69.48820
[8] 71.12156 68.27701 69.66724 72.21954 69.30767 69.17949 73.53200
[15] 72.08083 70.21486 66.63659 71.31654 68.80887 66.72586
> colSums(tmp5)
[1] 1109.2500 774.1008 678.5505 695.2944 701.1750 740.1312 694.8820
[8] 711.2156 682.7701 696.6724 722.1954 693.0767 691.7949 735.3200
[15] 720.8083 702.1486 666.3659 713.1654 688.0887 667.2586
> colVars(tmp5)
[1] 15910.81537 144.44882 62.63297 38.67690 43.50712 58.87552
[7] 83.89613 101.52249 37.19946 67.79431 57.28974 53.14068
[13] 60.85766 92.79203 96.67824 62.28198 75.29176 106.37194
[19] 49.47764 76.32860
> colSd(tmp5)
[1] 126.138081 12.018686 7.914100 6.219076 6.595992 7.673038
[7] 9.159483 10.075837 6.099136 8.233730 7.568998 7.289765
[13] 7.801132 9.632862 9.832509 7.891893 8.677083 10.313677
[19] 7.034034 8.736624
> colMax(tmp5)
[1] 469.12076 93.99727 77.97759 80.54195 85.34780 86.16623 88.30654
[8] 82.15639 78.76188 84.43996 82.05995 80.37696 86.03500 89.91301
[15] 84.34460 82.73592 78.73878 87.71081 77.45737 82.55867
> colMin(tmp5)
[1] 55.48620 57.72441 54.64518 61.37783 63.62880 61.12454 56.62593 55.35191
[9] 59.37513 58.58985 59.76004 58.76285 58.55350 53.33445 58.48021 56.94999
[17] 54.43604 60.87409 55.86679 56.70685
>
>
> ### 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] 87.96923 70.03173 67.20516 71.54101 69.25622 NA 72.51338 71.27858
[9] 70.91016 71.00464
> rowSums(tmp5)
[1] 1759.385 1400.635 1344.103 1430.820 1385.124 NA 1450.268 1425.572
[9] 1418.203 1420.093
> rowVars(tmp5)
[1] 8094.75931 117.78737 43.88654 97.78862 68.01139 62.48316
[7] 32.91528 70.78906 68.22350 112.28162
> rowSd(tmp5)
[1] 89.970880 10.852989 6.624692 9.888813 8.246902 7.904629 5.737184
[8] 8.413624 8.259752 10.596302
> rowMax(tmp5)
[1] 469.12076 89.91301 80.54195 91.72769 82.15639 NA 81.42079
[8] 87.71081 87.69014 93.99727
> rowMin(tmp5)
[1] 57.72441 55.35191 58.15404 54.64518 54.43604 NA 59.76004 56.62593
[9] 58.48021 53.33445
>
> colMeans(tmp5)
[1] 110.92500 77.41008 67.85505 69.52944 70.11750 74.01312 69.48820
[8] 71.12156 68.27701 69.66724 72.21954 69.30767 69.17949 73.53200
[15] 72.08083 NA 66.63659 71.31654 68.80887 66.72586
> colSums(tmp5)
[1] 1109.2500 774.1008 678.5505 695.2944 701.1750 740.1312 694.8820
[8] 711.2156 682.7701 696.6724 722.1954 693.0767 691.7949 735.3200
[15] 720.8083 NA 666.3659 713.1654 688.0887 667.2586
> colVars(tmp5)
[1] 15910.81537 144.44882 62.63297 38.67690 43.50712 58.87552
[7] 83.89613 101.52249 37.19946 67.79431 57.28974 53.14068
[13] 60.85766 92.79203 96.67824 NA 75.29176 106.37194
[19] 49.47764 76.32860
> colSd(tmp5)
[1] 126.138081 12.018686 7.914100 6.219076 6.595992 7.673038
[7] 9.159483 10.075837 6.099136 8.233730 7.568998 7.289765
[13] 7.801132 9.632862 9.832509 NA 8.677083 10.313677
[19] 7.034034 8.736624
> colMax(tmp5)
[1] 469.12076 93.99727 77.97759 80.54195 85.34780 86.16623 88.30654
[8] 82.15639 78.76188 84.43996 82.05995 80.37696 86.03500 89.91301
[15] 84.34460 NA 78.73878 87.71081 77.45737 82.55867
> colMin(tmp5)
[1] 55.48620 57.72441 54.64518 61.37783 63.62880 61.12454 56.62593 55.35191
[9] 59.37513 58.58985 59.76004 58.76285 58.55350 53.33445 58.48021 NA
[17] 54.43604 60.87409 55.86679 56.70685
>
> Max(tmp5,na.rm=TRUE)
[1] 469.1208
> Min(tmp5,na.rm=TRUE)
[1] 53.33445
> mean(tmp5,na.rm=TRUE)
[1] 72.40378
> Sum(tmp5,na.rm=TRUE)
[1] 14408.35
> Var(tmp5,na.rm=TRUE)
[1] 870.547
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.96923 70.03173 67.20516 71.54101 69.25622 72.32366 72.51338 71.27858
[9] 70.91016 71.00464
> rowSums(tmp5,na.rm=TRUE)
[1] 1759.385 1400.635 1344.103 1430.820 1385.124 1374.150 1450.268 1425.572
[9] 1418.203 1420.093
> rowVars(tmp5,na.rm=TRUE)
[1] 8094.75931 117.78737 43.88654 97.78862 68.01139 62.48316
[7] 32.91528 70.78906 68.22350 112.28162
> rowSd(tmp5,na.rm=TRUE)
[1] 89.970880 10.852989 6.624692 9.888813 8.246902 7.904629 5.737184
[8] 8.413624 8.259752 10.596302
> rowMax(tmp5,na.rm=TRUE)
[1] 469.12076 89.91301 80.54195 91.72769 82.15639 84.16583 81.42079
[8] 87.71081 87.69014 93.99727
> rowMin(tmp5,na.rm=TRUE)
[1] 57.72441 55.35191 58.15404 54.64518 54.43604 56.32877 59.76004 56.62593
[9] 58.48021 53.33445
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.92500 77.41008 67.85505 69.52944 70.11750 74.01312 69.48820
[8] 71.12156 68.27701 69.66724 72.21954 69.30767 69.17949 73.53200
[15] 72.08083 69.58176 66.63659 71.31654 68.80887 66.72586
> colSums(tmp5,na.rm=TRUE)
[1] 1109.2500 774.1008 678.5505 695.2944 701.1750 740.1312 694.8820
[8] 711.2156 682.7701 696.6724 722.1954 693.0767 691.7949 735.3200
[15] 720.8083 626.2358 666.3659 713.1654 688.0887 667.2586
> colVars(tmp5,na.rm=TRUE)
[1] 15910.81537 144.44882 62.63297 38.67690 43.50712 58.87552
[7] 83.89613 101.52249 37.19946 67.79431 57.28974 53.14068
[13] 60.85766 92.79203 96.67824 65.55806 75.29176 106.37194
[19] 49.47764 76.32860
> colSd(tmp5,na.rm=TRUE)
[1] 126.138081 12.018686 7.914100 6.219076 6.595992 7.673038
[7] 9.159483 10.075837 6.099136 8.233730 7.568998 7.289765
[13] 7.801132 9.632862 9.832509 8.096793 8.677083 10.313677
[19] 7.034034 8.736624
> colMax(tmp5,na.rm=TRUE)
[1] 469.12076 93.99727 77.97759 80.54195 85.34780 86.16623 88.30654
[8] 82.15639 78.76188 84.43996 82.05995 80.37696 86.03500 89.91301
[15] 84.34460 82.73592 78.73878 87.71081 77.45737 82.55867
> colMin(tmp5,na.rm=TRUE)
[1] 55.48620 57.72441 54.64518 61.37783 63.62880 61.12454 56.62593 55.35191
[9] 59.37513 58.58985 59.76004 58.76285 58.55350 53.33445 58.48021 56.94999
[17] 54.43604 60.87409 55.86679 56.70685
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.96923 70.03173 67.20516 71.54101 69.25622 NaN 72.51338 71.27858
[9] 70.91016 71.00464
> rowSums(tmp5,na.rm=TRUE)
[1] 1759.385 1400.635 1344.103 1430.820 1385.124 0.000 1450.268 1425.572
[9] 1418.203 1420.093
> rowVars(tmp5,na.rm=TRUE)
[1] 8094.75931 117.78737 43.88654 97.78862 68.01139 NA
[7] 32.91528 70.78906 68.22350 112.28162
> rowSd(tmp5,na.rm=TRUE)
[1] 89.970880 10.852989 6.624692 9.888813 8.246902 NA 5.737184
[8] 8.413624 8.259752 10.596302
> rowMax(tmp5,na.rm=TRUE)
[1] 469.12076 89.91301 80.54195 91.72769 82.15639 NA 81.42079
[8] 87.71081 87.69014 93.99727
> rowMin(tmp5,na.rm=TRUE)
[1] 57.72441 55.35191 58.15404 54.64518 54.43604 NA 59.76004 56.62593
[9] 58.48021 53.33445
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.89824 77.31862 69.13575 70.24319 69.99107 73.32648 69.26537
[8] 72.18051 68.15198 70.54191 71.31195 69.04000 69.23894 73.96220
[15] 70.79332 NaN 65.73263 70.25811 68.59361 65.67905
> colSums(tmp5,na.rm=TRUE)
[1] 1025.0842 695.8676 622.2218 632.1887 629.9197 659.9383 623.3883
[8] 649.6246 613.3678 634.8771 641.8075 621.3600 623.1504 665.6598
[15] 637.1399 0.0000 591.5936 632.3230 617.3425 591.1114
> colVars(tmp5,na.rm=TRUE)
[1] 17800.21549 162.41082 52.00998 37.78042 48.76569 60.93086
[7] 93.82455 101.59734 41.67352 67.66194 55.18409 58.97725
[13] 68.42511 102.30897 90.11425 NA 75.51026 107.06540
[19] 55.14108 73.54177
> colSd(tmp5,na.rm=TRUE)
[1] 133.417448 12.744050 7.211794 6.146578 6.983244 7.805822
[7] 9.686308 10.079551 6.455503 8.225688 7.428599 7.679665
[13] 8.271947 10.114789 9.492853 NA 8.689664 10.347241
[19] 7.425704 8.575650
> colMax(tmp5,na.rm=TRUE)
[1] 469.12076 93.99727 77.97759 80.54195 85.34780 86.16623 88.30654
[8] 82.15639 78.76188 84.43996 82.05995 80.37696 86.03500 89.91301
[15] 84.34460 -Inf 78.73878 87.71081 77.45737 82.55867
> colMin(tmp5,na.rm=TRUE)
[1] 55.48620 57.72441 54.64518 61.37783 63.62880 61.12454 56.62593 55.35191
[9] 59.37513 58.58985 59.76004 58.76285 58.55350 53.33445 58.48021 Inf
[17] 54.43604 60.87409 55.86679 56.70685
>
>
>
>
> 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] 190.5412 153.5934 215.8567 365.5884 224.1622 213.1549 252.9684 176.1101
[9] 188.4890 444.8396
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 190.5412 153.5934 215.8567 365.5884 224.1622 213.1549 252.9684 176.1101
[9] 188.4890 444.8396
>
>
>
> 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 1.136868e-13 2.842171e-14 5.684342e-14 4.263256e-14
[6] 5.684342e-14 1.136868e-13 -2.842171e-14 1.705303e-13 2.842171e-14
[11] -8.526513e-14 2.842171e-14 8.526513e-14 2.842171e-14 1.705303e-13
[16] -1.421085e-13 8.526513e-14 -1.136868e-13 -2.842171e-14 5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
10 2
1 15
8 10
10 19
7 16
6 5
9 18
9 12
3 12
10 18
9 20
7 6
4 10
2 15
4 14
2 7
6 11
9 3
9 8
6 20
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] 2.965584
> Min(tmp)
[1] -2.035934
> mean(tmp)
[1] 0.04213959
> Sum(tmp)
[1] 4.213959
> Var(tmp)
[1] 0.8649841
>
> rowMeans(tmp)
[1] 0.04213959
> rowSums(tmp)
[1] 4.213959
> rowVars(tmp)
[1] 0.8649841
> rowSd(tmp)
[1] 0.9300452
> rowMax(tmp)
[1] 2.965584
> rowMin(tmp)
[1] -2.035934
>
> colMeans(tmp)
[1] 0.19026728 -1.31628034 0.94732203 -0.95000418 0.89238156 1.69242012
[7] -0.25578039 -0.95986229 0.59551897 -1.64554127 -0.42908201 0.09320275
[13] 0.25099316 -1.01483770 -1.16373100 0.16357179 -0.07410876 0.25167323
[19] -0.15255374 0.55720469 0.66903993 -0.46879873 0.77020140 -0.43105264
[25] -0.82110234 0.28410602 -1.40837916 0.47907289 -1.67947129 1.10831726
[31] -0.17041925 -0.37173508 -0.93379110 -1.05709547 -0.82127496 1.11758068
[37] -1.58082325 0.42781056 0.93646276 0.29109818 0.55416587 0.44942779
[43] -0.02575963 0.48724840 2.17751191 -0.12256123 0.10138563 2.96558435
[49] 0.50352238 -0.76625990 0.47297847 0.23292864 1.03343896 1.16124647
[55] -0.01379102 0.45931913 -1.26099871 0.19598607 -0.47825235 -0.76860908
[61] -0.19441227 -0.07870726 -1.78398247 1.05630553 0.72637168 -0.80632322
[67] -0.47622017 -0.02413821 1.57536238 1.40596958 0.74870798 0.53170422
[73] 0.86155600 1.13936395 1.39931753 -0.13909844 0.75576613 0.98055399
[79] -1.27212192 -0.49003050 0.23414809 0.20932077 -1.92711283 -0.15899458
[85] -0.61177139 1.01851107 -0.83672144 1.29629328 -0.18761119 -0.03884008
[91] -2.03593362 0.45422625 -0.73036639 -0.04154832 0.53319468 -1.06999309
[97] 0.77367934 -1.00441982 0.23152724 0.81939394
> colSums(tmp)
[1] 0.19026728 -1.31628034 0.94732203 -0.95000418 0.89238156 1.69242012
[7] -0.25578039 -0.95986229 0.59551897 -1.64554127 -0.42908201 0.09320275
[13] 0.25099316 -1.01483770 -1.16373100 0.16357179 -0.07410876 0.25167323
[19] -0.15255374 0.55720469 0.66903993 -0.46879873 0.77020140 -0.43105264
[25] -0.82110234 0.28410602 -1.40837916 0.47907289 -1.67947129 1.10831726
[31] -0.17041925 -0.37173508 -0.93379110 -1.05709547 -0.82127496 1.11758068
[37] -1.58082325 0.42781056 0.93646276 0.29109818 0.55416587 0.44942779
[43] -0.02575963 0.48724840 2.17751191 -0.12256123 0.10138563 2.96558435
[49] 0.50352238 -0.76625990 0.47297847 0.23292864 1.03343896 1.16124647
[55] -0.01379102 0.45931913 -1.26099871 0.19598607 -0.47825235 -0.76860908
[61] -0.19441227 -0.07870726 -1.78398247 1.05630553 0.72637168 -0.80632322
[67] -0.47622017 -0.02413821 1.57536238 1.40596958 0.74870798 0.53170422
[73] 0.86155600 1.13936395 1.39931753 -0.13909844 0.75576613 0.98055399
[79] -1.27212192 -0.49003050 0.23414809 0.20932077 -1.92711283 -0.15899458
[85] -0.61177139 1.01851107 -0.83672144 1.29629328 -0.18761119 -0.03884008
[91] -2.03593362 0.45422625 -0.73036639 -0.04154832 0.53319468 -1.06999309
[97] 0.77367934 -1.00441982 0.23152724 0.81939394
> 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] 0.19026728 -1.31628034 0.94732203 -0.95000418 0.89238156 1.69242012
[7] -0.25578039 -0.95986229 0.59551897 -1.64554127 -0.42908201 0.09320275
[13] 0.25099316 -1.01483770 -1.16373100 0.16357179 -0.07410876 0.25167323
[19] -0.15255374 0.55720469 0.66903993 -0.46879873 0.77020140 -0.43105264
[25] -0.82110234 0.28410602 -1.40837916 0.47907289 -1.67947129 1.10831726
[31] -0.17041925 -0.37173508 -0.93379110 -1.05709547 -0.82127496 1.11758068
[37] -1.58082325 0.42781056 0.93646276 0.29109818 0.55416587 0.44942779
[43] -0.02575963 0.48724840 2.17751191 -0.12256123 0.10138563 2.96558435
[49] 0.50352238 -0.76625990 0.47297847 0.23292864 1.03343896 1.16124647
[55] -0.01379102 0.45931913 -1.26099871 0.19598607 -0.47825235 -0.76860908
[61] -0.19441227 -0.07870726 -1.78398247 1.05630553 0.72637168 -0.80632322
[67] -0.47622017 -0.02413821 1.57536238 1.40596958 0.74870798 0.53170422
[73] 0.86155600 1.13936395 1.39931753 -0.13909844 0.75576613 0.98055399
[79] -1.27212192 -0.49003050 0.23414809 0.20932077 -1.92711283 -0.15899458
[85] -0.61177139 1.01851107 -0.83672144 1.29629328 -0.18761119 -0.03884008
[91] -2.03593362 0.45422625 -0.73036639 -0.04154832 0.53319468 -1.06999309
[97] 0.77367934 -1.00441982 0.23152724 0.81939394
> colMin(tmp)
[1] 0.19026728 -1.31628034 0.94732203 -0.95000418 0.89238156 1.69242012
[7] -0.25578039 -0.95986229 0.59551897 -1.64554127 -0.42908201 0.09320275
[13] 0.25099316 -1.01483770 -1.16373100 0.16357179 -0.07410876 0.25167323
[19] -0.15255374 0.55720469 0.66903993 -0.46879873 0.77020140 -0.43105264
[25] -0.82110234 0.28410602 -1.40837916 0.47907289 -1.67947129 1.10831726
[31] -0.17041925 -0.37173508 -0.93379110 -1.05709547 -0.82127496 1.11758068
[37] -1.58082325 0.42781056 0.93646276 0.29109818 0.55416587 0.44942779
[43] -0.02575963 0.48724840 2.17751191 -0.12256123 0.10138563 2.96558435
[49] 0.50352238 -0.76625990 0.47297847 0.23292864 1.03343896 1.16124647
[55] -0.01379102 0.45931913 -1.26099871 0.19598607 -0.47825235 -0.76860908
[61] -0.19441227 -0.07870726 -1.78398247 1.05630553 0.72637168 -0.80632322
[67] -0.47622017 -0.02413821 1.57536238 1.40596958 0.74870798 0.53170422
[73] 0.86155600 1.13936395 1.39931753 -0.13909844 0.75576613 0.98055399
[79] -1.27212192 -0.49003050 0.23414809 0.20932077 -1.92711283 -0.15899458
[85] -0.61177139 1.01851107 -0.83672144 1.29629328 -0.18761119 -0.03884008
[91] -2.03593362 0.45422625 -0.73036639 -0.04154832 0.53319468 -1.06999309
[97] 0.77367934 -1.00441982 0.23152724 0.81939394
> colMedians(tmp)
[1] 0.19026728 -1.31628034 0.94732203 -0.95000418 0.89238156 1.69242012
[7] -0.25578039 -0.95986229 0.59551897 -1.64554127 -0.42908201 0.09320275
[13] 0.25099316 -1.01483770 -1.16373100 0.16357179 -0.07410876 0.25167323
[19] -0.15255374 0.55720469 0.66903993 -0.46879873 0.77020140 -0.43105264
[25] -0.82110234 0.28410602 -1.40837916 0.47907289 -1.67947129 1.10831726
[31] -0.17041925 -0.37173508 -0.93379110 -1.05709547 -0.82127496 1.11758068
[37] -1.58082325 0.42781056 0.93646276 0.29109818 0.55416587 0.44942779
[43] -0.02575963 0.48724840 2.17751191 -0.12256123 0.10138563 2.96558435
[49] 0.50352238 -0.76625990 0.47297847 0.23292864 1.03343896 1.16124647
[55] -0.01379102 0.45931913 -1.26099871 0.19598607 -0.47825235 -0.76860908
[61] -0.19441227 -0.07870726 -1.78398247 1.05630553 0.72637168 -0.80632322
[67] -0.47622017 -0.02413821 1.57536238 1.40596958 0.74870798 0.53170422
[73] 0.86155600 1.13936395 1.39931753 -0.13909844 0.75576613 0.98055399
[79] -1.27212192 -0.49003050 0.23414809 0.20932077 -1.92711283 -0.15899458
[85] -0.61177139 1.01851107 -0.83672144 1.29629328 -0.18761119 -0.03884008
[91] -2.03593362 0.45422625 -0.73036639 -0.04154832 0.53319468 -1.06999309
[97] 0.77367934 -1.00441982 0.23152724 0.81939394
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.1902673 -1.31628 0.947322 -0.9500042 0.8923816 1.69242 -0.2557804
[2,] 0.1902673 -1.31628 0.947322 -0.9500042 0.8923816 1.69242 -0.2557804
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.9598623 0.595519 -1.645541 -0.429082 0.09320275 0.2509932 -1.014838
[2,] -0.9598623 0.595519 -1.645541 -0.429082 0.09320275 0.2509932 -1.014838
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.163731 0.1635718 -0.07410876 0.2516732 -0.1525537 0.5572047 0.6690399
[2,] -1.163731 0.1635718 -0.07410876 0.2516732 -0.1525537 0.5572047 0.6690399
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.4687987 0.7702014 -0.4310526 -0.8211023 0.284106 -1.408379 0.4790729
[2,] -0.4687987 0.7702014 -0.4310526 -0.8211023 0.284106 -1.408379 0.4790729
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.679471 1.108317 -0.1704193 -0.3717351 -0.9337911 -1.057095 -0.821275
[2,] -1.679471 1.108317 -0.1704193 -0.3717351 -0.9337911 -1.057095 -0.821275
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.117581 -1.580823 0.4278106 0.9364628 0.2910982 0.5541659 0.4494278
[2,] 1.117581 -1.580823 0.4278106 0.9364628 0.2910982 0.5541659 0.4494278
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.02575963 0.4872484 2.177512 -0.1225612 0.1013856 2.965584 0.5035224
[2,] -0.02575963 0.4872484 2.177512 -0.1225612 0.1013856 2.965584 0.5035224
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.7662599 0.4729785 0.2329286 1.033439 1.161246 -0.01379102 0.4593191
[2,] -0.7662599 0.4729785 0.2329286 1.033439 1.161246 -0.01379102 0.4593191
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -1.260999 0.1959861 -0.4782524 -0.7686091 -0.1944123 -0.07870726 -1.783982
[2,] -1.260999 0.1959861 -0.4782524 -0.7686091 -0.1944123 -0.07870726 -1.783982
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 1.056306 0.7263717 -0.8063232 -0.4762202 -0.02413821 1.575362 1.40597
[2,] 1.056306 0.7263717 -0.8063232 -0.4762202 -0.02413821 1.575362 1.40597
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.748708 0.5317042 0.861556 1.139364 1.399318 -0.1390984 0.7557661
[2,] 0.748708 0.5317042 0.861556 1.139364 1.399318 -0.1390984 0.7557661
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.980554 -1.272122 -0.4900305 0.2341481 0.2093208 -1.927113 -0.1589946
[2,] 0.980554 -1.272122 -0.4900305 0.2341481 0.2093208 -1.927113 -0.1589946
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.6117714 1.018511 -0.8367214 1.296293 -0.1876112 -0.03884008 -2.035934
[2,] -0.6117714 1.018511 -0.8367214 1.296293 -0.1876112 -0.03884008 -2.035934
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.4542263 -0.7303664 -0.04154832 0.5331947 -1.069993 0.7736793 -1.00442
[2,] 0.4542263 -0.7303664 -0.04154832 0.5331947 -1.069993 0.7736793 -1.00442
[,99] [,100]
[1,] 0.2315272 0.8193939
[2,] 0.2315272 0.8193939
>
>
> Max(tmp2)
[1] 2.963708
> Min(tmp2)
[1] -2.852615
> mean(tmp2)
[1] -0.03169857
> Sum(tmp2)
[1] -3.169857
> Var(tmp2)
[1] 0.9921086
>
> rowMeans(tmp2)
[1] 0.2847713436 -2.0153559214 -0.6639702688 0.4160145180 -0.6673649256
[6] -0.4215829440 0.5441629759 0.7135353119 0.0932601441 -0.2564934683
[11] -1.3858880119 0.0006043232 -0.1926510919 -0.6673640471 -0.3151040131
[16] 0.0008188910 0.4569874746 1.9264335963 -0.8315494866 -2.8526150041
[21] -0.1458327270 0.2393049233 -0.3495618895 2.9637075858 0.3208241032
[26] -0.3135328657 -0.7702180534 0.4099679564 -1.2101072796 0.9817118781
[31] -1.6435493306 -0.6646897216 -1.1548654558 0.5863248989 -0.4433414451
[36] -0.1476017412 0.5584339558 -1.2035230615 0.4544609853 -0.3328938782
[41] 0.5343976085 -0.7531816425 0.9513698386 -0.0883685945 1.1696546196
[46] 0.2396514304 -1.2743325512 0.6139360047 1.0895515990 1.5332147376
[51] 0.5866586718 0.4563285038 -0.9079036489 0.1220350160 0.3099436875
[56] 0.2140528558 0.1359915042 1.9037380743 1.0876811182 -0.5610898293
[61] -0.2501110293 -0.8886923553 -1.5300216915 -1.1916215581 0.5874025882
[66] 0.3641960238 -1.2061510442 2.0062065244 0.8504354853 0.4039230867
[71] -0.1504049569 0.8629438786 0.6467703686 -0.4607937343 -0.5442388188
[76] 0.6522574462 -1.6800623644 -0.3722714679 -0.3862631296 1.3253536266
[81] 1.1204912444 0.4781734872 -1.9419793546 -1.3884765159 -0.6595863021
[86] 1.2271435360 0.5012005644 -0.6152798085 -0.6946921435 -0.9074420487
[91] 0.4291004093 0.7004435792 -0.0550850030 1.5453314018 0.2456565328
[96] -1.1602108567 -0.6901092964 -0.7464363026 2.1898970075 -1.4518515749
> rowSums(tmp2)
[1] 0.2847713436 -2.0153559214 -0.6639702688 0.4160145180 -0.6673649256
[6] -0.4215829440 0.5441629759 0.7135353119 0.0932601441 -0.2564934683
[11] -1.3858880119 0.0006043232 -0.1926510919 -0.6673640471 -0.3151040131
[16] 0.0008188910 0.4569874746 1.9264335963 -0.8315494866 -2.8526150041
[21] -0.1458327270 0.2393049233 -0.3495618895 2.9637075858 0.3208241032
[26] -0.3135328657 -0.7702180534 0.4099679564 -1.2101072796 0.9817118781
[31] -1.6435493306 -0.6646897216 -1.1548654558 0.5863248989 -0.4433414451
[36] -0.1476017412 0.5584339558 -1.2035230615 0.4544609853 -0.3328938782
[41] 0.5343976085 -0.7531816425 0.9513698386 -0.0883685945 1.1696546196
[46] 0.2396514304 -1.2743325512 0.6139360047 1.0895515990 1.5332147376
[51] 0.5866586718 0.4563285038 -0.9079036489 0.1220350160 0.3099436875
[56] 0.2140528558 0.1359915042 1.9037380743 1.0876811182 -0.5610898293
[61] -0.2501110293 -0.8886923553 -1.5300216915 -1.1916215581 0.5874025882
[66] 0.3641960238 -1.2061510442 2.0062065244 0.8504354853 0.4039230867
[71] -0.1504049569 0.8629438786 0.6467703686 -0.4607937343 -0.5442388188
[76] 0.6522574462 -1.6800623644 -0.3722714679 -0.3862631296 1.3253536266
[81] 1.1204912444 0.4781734872 -1.9419793546 -1.3884765159 -0.6595863021
[86] 1.2271435360 0.5012005644 -0.6152798085 -0.6946921435 -0.9074420487
[91] 0.4291004093 0.7004435792 -0.0550850030 1.5453314018 0.2456565328
[96] -1.1602108567 -0.6901092964 -0.7464363026 2.1898970075 -1.4518515749
> 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] 0.2847713436 -2.0153559214 -0.6639702688 0.4160145180 -0.6673649256
[6] -0.4215829440 0.5441629759 0.7135353119 0.0932601441 -0.2564934683
[11] -1.3858880119 0.0006043232 -0.1926510919 -0.6673640471 -0.3151040131
[16] 0.0008188910 0.4569874746 1.9264335963 -0.8315494866 -2.8526150041
[21] -0.1458327270 0.2393049233 -0.3495618895 2.9637075858 0.3208241032
[26] -0.3135328657 -0.7702180534 0.4099679564 -1.2101072796 0.9817118781
[31] -1.6435493306 -0.6646897216 -1.1548654558 0.5863248989 -0.4433414451
[36] -0.1476017412 0.5584339558 -1.2035230615 0.4544609853 -0.3328938782
[41] 0.5343976085 -0.7531816425 0.9513698386 -0.0883685945 1.1696546196
[46] 0.2396514304 -1.2743325512 0.6139360047 1.0895515990 1.5332147376
[51] 0.5866586718 0.4563285038 -0.9079036489 0.1220350160 0.3099436875
[56] 0.2140528558 0.1359915042 1.9037380743 1.0876811182 -0.5610898293
[61] -0.2501110293 -0.8886923553 -1.5300216915 -1.1916215581 0.5874025882
[66] 0.3641960238 -1.2061510442 2.0062065244 0.8504354853 0.4039230867
[71] -0.1504049569 0.8629438786 0.6467703686 -0.4607937343 -0.5442388188
[76] 0.6522574462 -1.6800623644 -0.3722714679 -0.3862631296 1.3253536266
[81] 1.1204912444 0.4781734872 -1.9419793546 -1.3884765159 -0.6595863021
[86] 1.2271435360 0.5012005644 -0.6152798085 -0.6946921435 -0.9074420487
[91] 0.4291004093 0.7004435792 -0.0550850030 1.5453314018 0.2456565328
[96] -1.1602108567 -0.6901092964 -0.7464363026 2.1898970075 -1.4518515749
> rowMin(tmp2)
[1] 0.2847713436 -2.0153559214 -0.6639702688 0.4160145180 -0.6673649256
[6] -0.4215829440 0.5441629759 0.7135353119 0.0932601441 -0.2564934683
[11] -1.3858880119 0.0006043232 -0.1926510919 -0.6673640471 -0.3151040131
[16] 0.0008188910 0.4569874746 1.9264335963 -0.8315494866 -2.8526150041
[21] -0.1458327270 0.2393049233 -0.3495618895 2.9637075858 0.3208241032
[26] -0.3135328657 -0.7702180534 0.4099679564 -1.2101072796 0.9817118781
[31] -1.6435493306 -0.6646897216 -1.1548654558 0.5863248989 -0.4433414451
[36] -0.1476017412 0.5584339558 -1.2035230615 0.4544609853 -0.3328938782
[41] 0.5343976085 -0.7531816425 0.9513698386 -0.0883685945 1.1696546196
[46] 0.2396514304 -1.2743325512 0.6139360047 1.0895515990 1.5332147376
[51] 0.5866586718 0.4563285038 -0.9079036489 0.1220350160 0.3099436875
[56] 0.2140528558 0.1359915042 1.9037380743 1.0876811182 -0.5610898293
[61] -0.2501110293 -0.8886923553 -1.5300216915 -1.1916215581 0.5874025882
[66] 0.3641960238 -1.2061510442 2.0062065244 0.8504354853 0.4039230867
[71] -0.1504049569 0.8629438786 0.6467703686 -0.4607937343 -0.5442388188
[76] 0.6522574462 -1.6800623644 -0.3722714679 -0.3862631296 1.3253536266
[81] 1.1204912444 0.4781734872 -1.9419793546 -1.3884765159 -0.6595863021
[86] 1.2271435360 0.5012005644 -0.6152798085 -0.6946921435 -0.9074420487
[91] 0.4291004093 0.7004435792 -0.0550850030 1.5453314018 0.2456565328
[96] -1.1602108567 -0.6901092964 -0.7464363026 2.1898970075 -1.4518515749
>
> colMeans(tmp2)
[1] -0.03169857
> colSums(tmp2)
[1] -3.169857
> colVars(tmp2)
[1] 0.9921086
> colSd(tmp2)
[1] 0.9960465
> colMax(tmp2)
[1] 2.963708
> colMin(tmp2)
[1] -2.852615
> colMedians(tmp2)
[1] -0.02724034
> colRanges(tmp2)
[,1]
[1,] -2.852615
[2,] 2.963708
>
> 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] 1.2417015 3.9354390 -4.6870950 1.4361402 3.8837899 0.5913530
[7] 1.6833877 -0.9456157 -1.3629687 1.2816592
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.4125495
[2,] -0.5927228
[3,] 0.3085287
[4,] 0.6139451
[5,] 1.6626949
>
> rowApply(tmp,sum)
[1] 3.3050432 -6.6130120 0.2812700 1.9682682 0.6759396 2.7196461
[7] 2.6162787 1.4044227 -3.0333201 3.7332547
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 2 3 10 8 7 10 5 1 4 10
[2,] 7 10 7 5 10 8 4 2 7 9
[3,] 6 1 8 1 2 4 7 3 3 4
[4,] 9 8 4 10 9 2 2 10 2 2
[5,] 8 9 9 3 1 7 10 7 8 8
[6,] 10 4 6 7 6 5 6 8 5 1
[7,] 3 2 5 4 4 3 9 5 10 6
[8,] 4 7 1 6 5 6 1 9 1 3
[9,] 1 5 2 9 8 1 3 6 6 7
[10,] 5 6 3 2 3 9 8 4 9 5
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.2474639 1.1853509 0.5511503 -2.3237893 1.6829675 -1.5349372
[7] 1.6272306 0.4571533 4.3450374 -0.5204846 0.4939928 0.1124484
[13] -1.7957027 -3.1075298 1.9280732 -1.4575095 -1.1295585 -1.3132463
[19] -0.5018497 -1.2305550
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.20842676
[2,] -0.82211414
[3,] 0.07031117
[4,] 0.55353582
[5,] 1.15923000
>
> rowApply(tmp,sum)
[1] 0.9352596 -7.0497954 -4.5969728 1.2312737 6.7010127
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 11 8 18 19 2
[2,] 10 13 6 13 17
[3,] 19 6 9 15 7
[4,] 15 1 11 1 12
[5,] 7 7 17 11 20
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.07031117 -0.0415754313 1.2905560 0.65347110 -0.2437095 -0.07008886
[2,] -0.82211414 -0.0004576132 -1.0256959 -2.06664843 -0.8999444 1.45558308
[3,] 0.55353582 -0.6862027521 -0.4028295 -0.00652652 0.4993436 -1.37045201
[4,] 1.15923000 0.4136142012 0.8117122 -1.46407613 0.2212824 -1.21841450
[5,] -1.20842676 1.4999724530 -0.1225924 0.55999065 2.1059954 -0.33156488
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.61398551 0.3726892 0.9581253 -1.8252948 2.1947516 0.3366280
[2,] -0.30886581 0.9687645 0.7840018 0.9456715 -0.4522316 0.1400842
[3,] -0.25969469 -1.2123373 -0.5878183 -0.6488534 0.2612661 2.0880637
[4,] 0.06493478 -0.6620275 1.8247516 0.4300223 -0.9255819 -1.1271029
[5,] 1.51687079 0.9900645 1.3659770 0.5779697 -0.5842114 -1.3252245
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.8241043 -0.862720146 1.2525481 -1.94227482 -0.7825260 -1.2106466
[2,] -0.5770649 -1.818085267 -1.0912332 -1.28721565 -1.9347450 0.5723034
[3,] -1.9427381 0.558493598 0.1177359 0.08911792 0.3981939 -1.2350758
[4,] -0.3409438 -0.001551152 1.0394284 -0.35864471 0.9940348 0.2848100
[5,] 0.2409398 -0.983666821 0.6095940 2.04150777 0.1954837 0.2753627
[,19] [,20]
[1,] -0.05664123 -0.5964333
[2,] -0.66843242 1.0365305
[3,] 0.12462622 -0.9348209
[4,] 1.14250522 -1.0567098
[5,] -1.04390744 0.3208785
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-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: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 648 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 563 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-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 -0.2141046 1.358877 0.6090726 -1.564192 0.01793638 -1.733922 2.170536
col8 col9 col10 col11 col12 col13 col14
row1 1.257608 1.250171 1.477706 -0.3775431 -0.002882192 0.4052029 -1.628536
col15 col16 col17 col18 col19 col20
row1 0.04423271 0.659438 -0.3378096 0.6472425 0.273734 0.1005592
> tmp[,"col10"]
col10
row1 1.4777058
row2 -0.9386238
row3 0.4562046
row4 -1.2113050
row5 1.1924366
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.2141046 1.3588766 0.6090726 -1.564192 0.01793638 -1.7339217
row5 -1.8301047 -0.9209254 -1.7142836 0.910668 -1.00574793 0.1376793
col7 col8 col9 col10 col11 col12 col13
row1 2.1705363 1.2576083 1.250171 1.477706 -0.3775431 -0.002882192 0.4052029
row5 -0.3420503 0.8980526 -2.515245 1.192437 -1.0061050 -0.727442157 -0.7201310
col14 col15 col16 col17 col18 col19
row1 -1.628535840 0.04423271 0.6594380 -0.3378096 0.6472425 0.273734
row5 -0.007497708 0.48130494 0.2011714 0.2217638 -0.6221760 -1.819633
col20
row1 0.1005592
row5 1.3710768
> tmp[,c("col6","col20")]
col6 col20
row1 -1.7339217 0.1005592
row2 1.4603580 1.6813557
row3 0.5864655 -1.2760388
row4 -0.1838940 0.4418017
row5 0.1376793 1.3710768
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.7339217 0.1005592
row5 0.1376793 1.3710768
>
>
>
>
> 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 50.46091 48.92833 48.78885 51.67295 49.37277 103.9672 49.76403 51.89509
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.58739 49.06645 50.55225 48.79969 50.50477 49.26081 50.89398 48.73596
col17 col18 col19 col20
row1 50.98846 50.12037 49.46982 104.614
> tmp[,"col10"]
col10
row1 49.06645
row2 28.94357
row3 31.24635
row4 28.96373
row5 49.75535
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.46091 48.92833 48.78885 51.67295 49.37277 103.9672 49.76403 51.89509
row5 50.10422 49.30027 49.29442 49.62454 50.77756 106.5536 50.93346 49.70632
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.58739 49.06645 50.55225 48.79969 50.50477 49.26081 50.89398 48.73596
row5 49.05480 49.75535 48.85064 49.54961 49.36505 50.47104 50.77377 49.91501
col17 col18 col19 col20
row1 50.98846 50.12037 49.46982 104.6140
row5 52.15965 50.18169 49.46050 104.8793
> tmp[,c("col6","col20")]
col6 col20
row1 103.96723 104.61397
row2 74.16697 76.06003
row3 74.52524 75.62305
row4 74.96903 74.42125
row5 106.55364 104.87928
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 103.9672 104.6140
row5 106.5536 104.8793
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 103.9672 104.6140
row5 106.5536 104.8793
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.1601378
[2,] -0.9896502
[3,] 0.7225228
[4,] -0.3140288
[5,] -1.1547431
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.47045913 0.01069146
[2,] -0.04871238 1.05182984
[3,] -0.69024905 -1.02765540
[4,] 1.18004062 -0.68806555
[5,] 1.13775366 1.19040169
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 2.417792814 -0.4278454
[2,] -1.726810171 0.2040757
[3,] -0.490443747 0.3899344
[4,] 0.007762294 -0.4565841
[5,] -0.528498185 -1.0106926
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 2.417793
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 2.417793
[2,] -1.726810
>
>
>
> 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 0.1433117 0.7711254 -0.8448362 -1.3376279 0.2160665 0.2757061
row1 -0.8273320 0.1769838 0.3668659 0.6425662 -0.7185841 -1.6159259
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.5084816 1.1315457 1.4526608 0.5980678 2.1298682 1.0757623 -0.2281656
row1 1.8906228 0.2105259 -0.7649097 -2.6842425 0.8687093 0.9240994 -1.2956795
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -1.0451553 1.283235 0.4393488 -1.716780 0.07697257 -0.1395741 -0.1253114
row1 -0.9935268 1.656142 0.7645128 -1.190021 -1.04127543 -0.8911829 2.2070088
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.027794 -1.495539 -1.117323 -1.368028 0.7493122 0.6080861 -1.29883
[,8] [,9] [,10]
row2 2.186133 -1.762729 0.1623777
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row5 -0.3871825 -0.6846363 -0.06225975 -0.4666781 -0.3742603 -1.246386
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row5 -0.869992 0.2335033 -1.287075 0.4231696 -1.147674 -0.7142115 0.9645586
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.943359 0.1283784 -0.3660376 -0.01534121 0.02731391 -0.4321699 1.008792
>
>
> 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: 0x600000cd8000>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM4e4042442129"
[2] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM4e406dd2cbc"
[3] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM4e4022a3ee29"
[4] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM4e403868d783"
[5] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM4e406b1cf663"
[6] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM4e403a741485"
[7] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM4e401aef45be"
[8] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM4e4052cbcac2"
[9] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM4e40416cb105"
[10] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM4e4046d9e0d1"
[11] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM4e40a36ddae"
[12] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM4e401813cfbf"
[13] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM4e403cac10f2"
[14] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM4e40448c9efc"
[15] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM4e406c19d58c"
>
>
> ### 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: 0x600000ce0180>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600000ce0180>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600000ce0180>
> rowMedians(tmp)
[1] 0.045484448 0.599281767 -0.202229631 -0.079003464 0.305615120
[6] 0.179772396 0.011061743 -0.662038905 0.150951405 0.190711829
[11] 0.179524151 -0.067314897 0.196757843 0.051107044 -0.280033980
[16] 0.375649291 -0.261242104 -0.028483870 0.088431443 0.226795926
[21] -0.082341655 0.365896979 -0.248400444 0.529609988 0.543721090
[26] -0.120700787 -0.019925953 0.483913620 0.197870143 0.284111860
[31] 0.081962671 -0.411970203 0.116765232 -0.396565283 0.090569307
[36] 0.295096197 -0.349435436 -0.254186212 0.226246858 0.502977514
[41] -0.492452792 0.474798916 -0.211253930 0.016618478 -0.001793626
[46] 0.056783455 0.258359304 -0.044113475 0.470244938 -0.239095542
[51] -0.589717448 0.300377354 -0.324748912 0.618962265 0.108340879
[56] -0.292619121 -0.204795810 0.247187281 0.178768008 -0.223921500
[61] -0.085880571 0.168068311 0.021633711 0.266829577 0.437528779
[66] 0.391961586 0.270823690 -0.238208539 -0.034667361 0.413287227
[71] 0.032890487 0.585759981 -0.512564699 -0.362342527 -0.146375965
[76] 0.041291424 -0.389837434 -0.397485147 0.033926892 0.006689695
[81] 0.303358163 -0.451977437 -0.112131931 0.386538562 -0.428651048
[86] -0.415480289 -0.007758295 -0.652773593 0.120294141 -0.083308703
[91] 0.086248122 -0.040087617 -0.245642886 -0.164586033 0.031331681
[96] -0.115375919 -0.130205584 -0.118926978 -0.335723833 -0.049153886
[101] -0.661217724 -0.076052518 0.466830308 -0.256789790 -0.117666418
[106] -0.728675772 -0.302002813 -0.313608984 0.126120937 0.486334369
[111] -0.215489637 -0.366918543 -0.010886933 -0.596491728 -0.012112803
[116] -0.663338327 0.202107969 0.202976225 -0.101794997 0.372379047
[121] 0.323295601 -0.150091231 -0.360477342 0.287022182 0.604669068
[126] 0.366947620 -0.283739395 0.027426431 0.668792630 0.675389256
[131] -0.208914790 -0.183751677 0.246439056 -0.060030604 -0.097582127
[136] 0.321534010 -0.081892402 -0.692007123 -0.083816941 -0.260477413
[141] 0.015657078 0.597967755 -0.173536588 -0.051444405 -0.276390853
[146] -0.096666153 -0.231656110 0.014958775 -0.206519633 0.148996142
[151] -0.207882462 0.244886968 -0.425079167 0.697802580 0.639919192
[156] 0.134509306 -0.475952054 -0.018701763 -0.398501720 0.196158902
[161] 0.053285093 -0.328968669 -0.076855138 -0.383336511 0.436099250
[166] -0.106516030 -0.078006298 -0.313627293 0.143106346 -0.636229569
[171] -0.686933828 -0.155889411 -0.409841047 -0.104041890 -0.127838420
[176] 0.145584233 0.407474005 -0.096664291 0.040739901 0.154413018
[181] 0.380957461 -0.218333704 0.441534278 0.080553049 0.275224796
[186] -0.729789910 -0.470455984 0.033080792 0.010144902 -0.331488729
[191] -0.045006259 0.118102662 0.301626498 0.462078619 0.269278806
[196] -0.276014870 -0.036195973 -0.513030478 -0.175551363 -0.484268620
[201] -0.283238065 -0.545356143 0.376495731 -0.404067486 -0.069816207
[206] -0.123789400 -0.307109486 0.404272378 -0.162211726 -0.311960979
[211] -0.576786012 0.065553840 -0.039985013 -0.123402181 -0.092124667
[216] -0.212569194 -0.191459427 -0.308820825 -0.080873247 -0.122197949
[221] -0.227820523 -0.002640243 0.163807437 -0.065110243 0.427583995
[226] -0.449524236 -0.369011260 -0.452304062 -0.040041322 0.014556902
>
> proc.time()
user system elapsed
2.777 16.204 19.811
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.1 (2025-06-13) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
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: 0x60000300c000>
> .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: 0x60000300c000>
> .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: 0x60000300c000>
> .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: 0x60000300c000>
> 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: 0x600003078120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003078120>
> .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: 0x600003078120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003078120>
> .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: 0x600003078120>
> 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: 0x6000030446c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000030446c0>
> .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: 0x6000030446c0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000030446c0>
> .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: 0x6000030446c0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000030446c0>
> .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: 0x6000030446c0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000030446c0>
> .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: 0x6000030446c0>
> 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: 0x6000030448a0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000030448a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000030448a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000030448a0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile543c3e186971" "BufferedMatrixFile543c467d15a6"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile543c3e186971" "BufferedMatrixFile543c467d15a6"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003044b40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003044b40>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003044b40>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003044b40>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600003044b40>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600003044b40>
> .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: 0x60000301c000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000301c000>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x60000301c000>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x60000301c000>
> 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: 0x600003018000>
> .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: 0x600003018000>
> rm(P)
>
> proc.time()
user system elapsed
0.361 0.165 0.516
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.1 (2025-06-13) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.350 0.093 0.434