Ben Bolstad
| Snapshot Date: 2025-09-18 13:40 -0400 (Thu, 18 Sep 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_21 |
| git_last_commit: aa9e634 |
| git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-09-22 11:40 -0400 (Mon, 22 Sep 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4827 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root" | 4608 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4549 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4581 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 252/2341 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.72.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| kunpeng2 | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.72.0 |
| 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_1.72.0.tar.gz |
| StartedAt: 2025-09-19 15:04:15 -0400 (Fri, 19 Sep 2025) |
| EndedAt: 2025-09-19 15:04:55 -0400 (Fri, 19 Sep 2025) |
| EllapsedTime: 40.4 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_1.72.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.1 Patched (2025-06-14 r88325)
* using platform: aarch64-apple-darwin20
* R was compiled by
Apple clang version 16.0.0 (clang-1600.0.26.6)
GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.5
* 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 ... 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-3.21-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 15.0.0 (clang-1500.0.40.1)’
* 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-3.21-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-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.72.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.0.40.1)’
using SDK: ‘MacOSX11.3.sdk’
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/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 arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch arm64 -std=gnu2x -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/arm64/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-arm64/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 Patched (2025-06-14 r88325) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-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
0.336 0.118 0.446
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-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-3.21-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) limit (Mb) max used (Mb)
Ncells 480828 25.7 1056581 56.5 NA 634425 33.9
Vcells 891011 6.8 8388608 64.0 65536 2109041 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] "Fri Sep 19 15:04:35 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Sep 19 15:04:35 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: 0x600000ab00c0>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Sep 19 15:04:37 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Sep 19 15:04:38 2025"
>
> ColMode(tmp2)
<pointer: 0x600000ab00c0>
>
>
>
> ### 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,] 100.6412557 -0.1080340 1.59936399 -0.3569980
[2,] 1.0368756 1.6663340 -0.18695169 -0.1935073
[3,] -1.1569807 -0.8946074 1.31253748 0.6488535
[4,] -0.6389508 -0.1612991 0.09738559 -0.2640380
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/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,] 100.6412557 0.1080340 1.59936399 0.3569980
[2,] 1.0368756 1.6663340 0.18695169 0.1935073
[3,] 1.1569807 0.8946074 1.31253748 0.6488535
[4,] 0.6389508 0.1612991 0.09738559 0.2640380
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/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,] 10.032012 0.3286853 1.2646596 0.5974931
[2,] 1.018271 1.2908656 0.4323791 0.4398947
[3,] 1.075630 0.9458369 1.1456603 0.8055144
[4,] 0.799344 0.4016206 0.3120666 0.5138463
>
> 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-3.21-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,] 225.96137 28.39489 39.24596 31.33193
[2,] 36.21958 39.57499 29.51074 29.59245
[3,] 36.91328 35.35298 37.76914 33.70400
[4,] 33.63239 29.17751 28.21805 30.40250
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600000abc0c0>
> exp(tmp5)
<pointer: 0x600000abc0c0>
> log(tmp5,2)
<pointer: 0x600000abc0c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.309
> Min(tmp5)
[1] 53.67477
> mean(tmp5)
[1] 73.65047
> Sum(tmp5)
[1] 14730.09
> Var(tmp5)
[1] 864.1513
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.81752 71.44981 72.77439 72.38847 70.77159 75.39050 68.82585 73.13061
[9] 70.57303 70.38293
> rowSums(tmp5)
[1] 1816.350 1428.996 1455.488 1447.769 1415.432 1507.810 1376.517 1462.612
[9] 1411.461 1407.659
> rowVars(tmp5)
[1] 8054.58112 52.44368 61.50723 89.96780 81.73446 58.33275
[7] 97.91737 78.04779 67.65366 32.95598
> rowSd(tmp5)
[1] 89.747318 7.241801 7.842655 9.485136 9.040711 7.637588 9.895321
[8] 8.834466 8.225185 5.740730
> rowMax(tmp5)
[1] 470.30899 85.47640 85.80955 89.94631 85.00213 89.94024 87.44903
[8] 84.59264 85.39059 80.58571
> rowMin(tmp5)
[1] 55.88656 59.56821 59.43075 57.76732 56.36661 64.87577 53.67477 56.95966
[9] 53.86177 61.34692
>
> colMeans(tmp5)
[1] 109.84945 72.07068 68.60975 66.74504 71.07447 69.07683 73.13918
[8] 67.31605 74.47970 70.54586 72.55191 73.28424 74.11461 76.93567
[15] 75.04150 74.45770 73.71307 66.13950 70.72359 73.14057
> colSums(tmp5)
[1] 1098.4945 720.7068 686.0975 667.4504 710.7447 690.7683 731.3918
[8] 673.1605 744.7970 705.4586 725.5191 732.8424 741.1461 769.3567
[15] 750.4150 744.5770 737.1307 661.3950 707.2359 731.4057
> colVars(tmp5)
[1] 16091.62201 122.98538 78.11778 14.22254 53.66060 63.77111
[7] 18.77086 86.16542 49.82923 62.46431 127.87737 72.18705
[13] 60.54016 32.94690 104.70797 52.00757 46.46238 60.91365
[19] 65.15495 126.93523
> colSd(tmp5)
[1] 126.852757 11.089877 8.838426 3.771278 7.325339 7.985682
[7] 4.332535 9.282533 7.058982 7.903436 11.308287 8.496296
[13] 7.780756 5.739939 10.232691 7.211627 6.816332 7.804720
[19] 8.071862 11.266554
> colMax(tmp5)
[1] 470.30899 86.62390 81.68532 72.67352 81.33997 79.20814 78.34829
[8] 85.00213 85.39059 84.83152 89.94024 84.17172 87.44569 85.80955
[15] 87.44903 85.96871 79.38525 80.74539 82.37188 89.94631
> colMin(tmp5)
[1] 59.79862 56.36661 53.67477 61.59282 57.52601 55.88066 65.60064 53.86177
[9] 62.83416 59.56821 56.95966 58.86679 63.50377 69.79310 56.63704 66.39380
[17] 60.25818 55.88656 61.34692 57.34281
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 90.81752 71.44981 72.77439 72.38847 NA 75.39050 68.82585 73.13061
[9] 70.57303 70.38293
> rowSums(tmp5)
[1] 1816.350 1428.996 1455.488 1447.769 NA 1507.810 1376.517 1462.612
[9] 1411.461 1407.659
> rowVars(tmp5)
[1] 8054.58112 52.44368 61.50723 89.96780 80.08131 58.33275
[7] 97.91737 78.04779 67.65366 32.95598
> rowSd(tmp5)
[1] 89.747318 7.241801 7.842655 9.485136 8.948816 7.637588 9.895321
[8] 8.834466 8.225185 5.740730
> rowMax(tmp5)
[1] 470.30899 85.47640 85.80955 89.94631 NA 89.94024 87.44903
[8] 84.59264 85.39059 80.58571
> rowMin(tmp5)
[1] 55.88656 59.56821 59.43075 57.76732 NA 64.87577 53.67477 56.95966
[9] 53.86177 61.34692
>
> colMeans(tmp5)
[1] 109.84945 72.07068 68.60975 66.74504 71.07447 69.07683 73.13918
[8] 67.31605 74.47970 70.54586 72.55191 73.28424 74.11461 76.93567
[15] 75.04150 74.45770 73.71307 66.13950 NA 73.14057
> colSums(tmp5)
[1] 1098.4945 720.7068 686.0975 667.4504 710.7447 690.7683 731.3918
[8] 673.1605 744.7970 705.4586 725.5191 732.8424 741.1461 769.3567
[15] 750.4150 744.5770 737.1307 661.3950 NA 731.4057
> colVars(tmp5)
[1] 16091.62201 122.98538 78.11778 14.22254 53.66060 63.77111
[7] 18.77086 86.16542 49.82923 62.46431 127.87737 72.18705
[13] 60.54016 32.94690 104.70797 52.00757 46.46238 60.91365
[19] NA 126.93523
> colSd(tmp5)
[1] 126.852757 11.089877 8.838426 3.771278 7.325339 7.985682
[7] 4.332535 9.282533 7.058982 7.903436 11.308287 8.496296
[13] 7.780756 5.739939 10.232691 7.211627 6.816332 7.804720
[19] NA 11.266554
> colMax(tmp5)
[1] 470.30899 86.62390 81.68532 72.67352 81.33997 79.20814 78.34829
[8] 85.00213 85.39059 84.83152 89.94024 84.17172 87.44569 85.80955
[15] 87.44903 85.96871 79.38525 80.74539 NA 89.94631
> colMin(tmp5)
[1] 59.79862 56.36661 53.67477 61.59282 57.52601 55.88066 65.60064 53.86177
[9] 62.83416 59.56821 56.95966 58.86679 63.50377 69.79310 56.63704 66.39380
[17] 60.25818 55.88656 NA 57.34281
>
> Max(tmp5,na.rm=TRUE)
[1] 470.309
> Min(tmp5,na.rm=TRUE)
[1] 53.67477
> mean(tmp5,na.rm=TRUE)
[1] 73.61322
> Sum(tmp5,na.rm=TRUE)
[1] 14649.03
> Var(tmp5,na.rm=TRUE)
[1] 868.2368
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.81752 71.44981 72.77439 72.38847 70.22993 75.39050 68.82585 73.13061
[9] 70.57303 70.38293
> rowSums(tmp5,na.rm=TRUE)
[1] 1816.350 1428.996 1455.488 1447.769 1334.369 1507.810 1376.517 1462.612
[9] 1411.461 1407.659
> rowVars(tmp5,na.rm=TRUE)
[1] 8054.58112 52.44368 61.50723 89.96780 80.08131 58.33275
[7] 97.91737 78.04779 67.65366 32.95598
> rowSd(tmp5,na.rm=TRUE)
[1] 89.747318 7.241801 7.842655 9.485136 8.948816 7.637588 9.895321
[8] 8.834466 8.225185 5.740730
> rowMax(tmp5,na.rm=TRUE)
[1] 470.30899 85.47640 85.80955 89.94631 85.00213 89.94024 87.44903
[8] 84.59264 85.39059 80.58571
> rowMin(tmp5,na.rm=TRUE)
[1] 55.88656 59.56821 59.43075 57.76732 56.36661 64.87577 53.67477 56.95966
[9] 53.86177 61.34692
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.84945 72.07068 68.60975 66.74504 71.07447 69.07683 73.13918
[8] 67.31605 74.47970 70.54586 72.55191 73.28424 74.11461 76.93567
[15] 75.04150 74.45770 73.71307 66.13950 69.57475 73.14057
> colSums(tmp5,na.rm=TRUE)
[1] 1098.4945 720.7068 686.0975 667.4504 710.7447 690.7683 731.3918
[8] 673.1605 744.7970 705.4586 725.5191 732.8424 741.1461 769.3567
[15] 750.4150 744.5770 737.1307 661.3950 626.1728 731.4057
> colVars(tmp5,na.rm=TRUE)
[1] 16091.62201 122.98538 78.11778 14.22254 53.66060 63.77111
[7] 18.77086 86.16542 49.82923 62.46431 127.87737 72.18705
[13] 60.54016 32.94690 104.70797 52.00757 46.46238 60.91365
[19] 58.45115 126.93523
> colSd(tmp5,na.rm=TRUE)
[1] 126.852757 11.089877 8.838426 3.771278 7.325339 7.985682
[7] 4.332535 9.282533 7.058982 7.903436 11.308287 8.496296
[13] 7.780756 5.739939 10.232691 7.211627 6.816332 7.804720
[19] 7.645335 11.266554
> colMax(tmp5,na.rm=TRUE)
[1] 470.30899 86.62390 81.68532 72.67352 81.33997 79.20814 78.34829
[8] 85.00213 85.39059 84.83152 89.94024 84.17172 87.44569 85.80955
[15] 87.44903 85.96871 79.38525 80.74539 82.37188 89.94631
> colMin(tmp5,na.rm=TRUE)
[1] 59.79862 56.36661 53.67477 61.59282 57.52601 55.88066 65.60064 53.86177
[9] 62.83416 59.56821 56.95966 58.86679 63.50377 69.79310 56.63704 66.39380
[17] 60.25818 55.88656 61.34692 57.34281
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.81752 71.44981 72.77439 72.38847 NaN 75.39050 68.82585 73.13061
[9] 70.57303 70.38293
> rowSums(tmp5,na.rm=TRUE)
[1] 1816.350 1428.996 1455.488 1447.769 0.000 1507.810 1376.517 1462.612
[9] 1411.461 1407.659
> rowVars(tmp5,na.rm=TRUE)
[1] 8054.58112 52.44368 61.50723 89.96780 NA 58.33275
[7] 97.91737 78.04779 67.65366 32.95598
> rowSd(tmp5,na.rm=TRUE)
[1] 89.747318 7.241801 7.842655 9.485136 NA 7.637588 9.895321
[8] 8.834466 8.225185 5.740730
> rowMax(tmp5,na.rm=TRUE)
[1] 470.30899 85.47640 85.80955 89.94631 NA 89.94024 87.44903
[8] 84.59264 85.39059 80.58571
> rowMin(tmp5,na.rm=TRUE)
[1] 55.88656 59.56821 59.43075 57.76732 NA 64.87577 53.67477 56.95966
[9] 53.86177 61.34692
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.04695 73.81558 68.38690 66.92505 71.43681 69.80317 73.97679
[8] 65.35093 74.70787 70.90193 71.55110 73.03764 73.70913 76.65802
[15] 77.08644 73.60752 73.33861 66.61934 NaN 74.87235
> colSums(tmp5,na.rm=TRUE)
[1] 1026.4226 664.3402 615.4821 602.3255 642.9313 628.2285 665.7911
[8] 588.1583 672.3709 638.1173 643.9599 657.3388 663.3822 689.9222
[15] 693.7779 662.4677 660.0474 599.5740 0.0000 673.8512
> colVars(tmp5,na.rm=TRUE)
[1] 17904.86106 104.10608 87.32379 15.63579 58.89115 65.80742
[7] 13.22422 53.49198 55.47216 68.84604 132.59387 80.52630
[13] 66.25806 36.19803 70.75148 50.37704 50.69269 65.93769
[19] NA 109.06279
> colSd(tmp5,na.rm=TRUE)
[1] 133.809047 10.203239 9.344720 3.954212 7.674057 8.112177
[7] 3.636512 7.313821 7.447964 8.297351 11.514941 8.973645
[13] 8.139905 6.016480 8.411390 7.097678 7.119880 8.120203
[19] NA 10.443313
> colMax(tmp5,na.rm=TRUE)
[1] 470.30899 86.62390 81.68532 72.67352 81.33997 79.20814 78.34829
[8] 74.89900 85.39059 84.83152 89.94024 84.17172 87.44569 85.80955
[15] 87.44903 85.96871 79.38525 80.74539 -Inf 89.94631
> colMin(tmp5,na.rm=TRUE)
[1] 59.79862 59.10024 53.67477 61.59282 57.52601 55.88066 67.96284 53.86177
[9] 62.83416 59.56821 56.95966 58.86679 63.50377 69.79310 59.43075 66.39380
[17] 60.25818 55.88656 Inf 57.34281
>
>
>
>
> 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] 302.8204 282.6669 212.3599 236.0243 256.3705 190.2574 215.6274 205.2628
[9] 233.7884 366.2253
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 302.8204 282.6669 212.3599 236.0243 256.3705 190.2574 215.6274 205.2628
[9] 233.7884 366.2253
>
>
>
> 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] 5.684342e-14 -3.410605e-13 2.273737e-13 0.000000e+00 8.526513e-14
[6] 0.000000e+00 -5.684342e-14 -2.842171e-14 -5.684342e-14 0.000000e+00
[11] -5.684342e-14 5.684342e-14 -2.557954e-13 0.000000e+00 1.989520e-13
[16] -2.842171e-14 2.842171e-14 -4.263256e-13 -4.263256e-14 -1.563194e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
10 12
1 19
5 19
1 2
5 15
8 3
3 10
6 8
4 15
5 19
8 4
8 1
2 16
3 12
1 14
7 15
2 7
6 5
2 19
3 15
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.541775
> Min(tmp)
[1] -2.08523
> mean(tmp)
[1] 0.04764428
> Sum(tmp)
[1] 4.764428
> Var(tmp)
[1] 0.9092767
>
> rowMeans(tmp)
[1] 0.04764428
> rowSums(tmp)
[1] 4.764428
> rowVars(tmp)
[1] 0.9092767
> rowSd(tmp)
[1] 0.95356
> rowMax(tmp)
[1] 2.541775
> rowMin(tmp)
[1] -2.08523
>
> colMeans(tmp)
[1] 0.24596207 -2.08523016 1.45293033 -0.11386102 -0.21207311 -0.86502407
[7] -0.65352610 0.04183482 0.03485097 2.51055419 -0.32659329 -1.10177930
[13] 0.46024155 0.68960449 -0.88101598 0.08785093 0.11547558 0.54045124
[19] -0.40343961 -0.42833037 -0.30368868 0.75428842 0.35910175 -1.19361634
[25] 1.75114460 -1.17677376 1.24723271 1.16045380 -0.44694285 -0.02967069
[31] 0.22954260 -1.23357193 0.75892216 -0.41260241 -0.26878415 0.06610073
[37] 0.28917156 -1.04197165 -0.51473340 0.86350735 -1.11173874 0.26527971
[43] 0.10858089 -1.99886697 1.12215477 -0.71304807 -1.24826054 1.53395555
[49] 1.10202936 0.36073041 0.54686641 -0.39508229 -0.77947149 -0.71592788
[55] -0.59056067 0.77740655 0.75292768 0.74650068 0.47640980 -0.81361571
[61] 1.26435029 -1.19261216 -0.50043606 -1.15272607 -0.71274881 1.00726583
[67] 0.47820051 -0.14489357 0.83312484 1.28276399 -1.15708203 0.53936211
[73] 0.44732598 -1.27089225 -0.21235539 -0.74370997 1.09139149 1.71510157
[79] -0.97875164 0.81454111 -0.59976516 0.54991750 -1.09012911 1.37480482
[85] 1.33123665 2.54177475 -0.21842782 -0.75865222 -0.48790256 -1.00842060
[91] 0.58797145 1.49294663 0.18914760 1.11005539 0.01729191 -0.40224775
[97] -1.93135845 -0.32340650 0.95894377 0.63116537
> colSums(tmp)
[1] 0.24596207 -2.08523016 1.45293033 -0.11386102 -0.21207311 -0.86502407
[7] -0.65352610 0.04183482 0.03485097 2.51055419 -0.32659329 -1.10177930
[13] 0.46024155 0.68960449 -0.88101598 0.08785093 0.11547558 0.54045124
[19] -0.40343961 -0.42833037 -0.30368868 0.75428842 0.35910175 -1.19361634
[25] 1.75114460 -1.17677376 1.24723271 1.16045380 -0.44694285 -0.02967069
[31] 0.22954260 -1.23357193 0.75892216 -0.41260241 -0.26878415 0.06610073
[37] 0.28917156 -1.04197165 -0.51473340 0.86350735 -1.11173874 0.26527971
[43] 0.10858089 -1.99886697 1.12215477 -0.71304807 -1.24826054 1.53395555
[49] 1.10202936 0.36073041 0.54686641 -0.39508229 -0.77947149 -0.71592788
[55] -0.59056067 0.77740655 0.75292768 0.74650068 0.47640980 -0.81361571
[61] 1.26435029 -1.19261216 -0.50043606 -1.15272607 -0.71274881 1.00726583
[67] 0.47820051 -0.14489357 0.83312484 1.28276399 -1.15708203 0.53936211
[73] 0.44732598 -1.27089225 -0.21235539 -0.74370997 1.09139149 1.71510157
[79] -0.97875164 0.81454111 -0.59976516 0.54991750 -1.09012911 1.37480482
[85] 1.33123665 2.54177475 -0.21842782 -0.75865222 -0.48790256 -1.00842060
[91] 0.58797145 1.49294663 0.18914760 1.11005539 0.01729191 -0.40224775
[97] -1.93135845 -0.32340650 0.95894377 0.63116537
> 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] 0.24596207 -2.08523016 1.45293033 -0.11386102 -0.21207311 -0.86502407
[7] -0.65352610 0.04183482 0.03485097 2.51055419 -0.32659329 -1.10177930
[13] 0.46024155 0.68960449 -0.88101598 0.08785093 0.11547558 0.54045124
[19] -0.40343961 -0.42833037 -0.30368868 0.75428842 0.35910175 -1.19361634
[25] 1.75114460 -1.17677376 1.24723271 1.16045380 -0.44694285 -0.02967069
[31] 0.22954260 -1.23357193 0.75892216 -0.41260241 -0.26878415 0.06610073
[37] 0.28917156 -1.04197165 -0.51473340 0.86350735 -1.11173874 0.26527971
[43] 0.10858089 -1.99886697 1.12215477 -0.71304807 -1.24826054 1.53395555
[49] 1.10202936 0.36073041 0.54686641 -0.39508229 -0.77947149 -0.71592788
[55] -0.59056067 0.77740655 0.75292768 0.74650068 0.47640980 -0.81361571
[61] 1.26435029 -1.19261216 -0.50043606 -1.15272607 -0.71274881 1.00726583
[67] 0.47820051 -0.14489357 0.83312484 1.28276399 -1.15708203 0.53936211
[73] 0.44732598 -1.27089225 -0.21235539 -0.74370997 1.09139149 1.71510157
[79] -0.97875164 0.81454111 -0.59976516 0.54991750 -1.09012911 1.37480482
[85] 1.33123665 2.54177475 -0.21842782 -0.75865222 -0.48790256 -1.00842060
[91] 0.58797145 1.49294663 0.18914760 1.11005539 0.01729191 -0.40224775
[97] -1.93135845 -0.32340650 0.95894377 0.63116537
> colMin(tmp)
[1] 0.24596207 -2.08523016 1.45293033 -0.11386102 -0.21207311 -0.86502407
[7] -0.65352610 0.04183482 0.03485097 2.51055419 -0.32659329 -1.10177930
[13] 0.46024155 0.68960449 -0.88101598 0.08785093 0.11547558 0.54045124
[19] -0.40343961 -0.42833037 -0.30368868 0.75428842 0.35910175 -1.19361634
[25] 1.75114460 -1.17677376 1.24723271 1.16045380 -0.44694285 -0.02967069
[31] 0.22954260 -1.23357193 0.75892216 -0.41260241 -0.26878415 0.06610073
[37] 0.28917156 -1.04197165 -0.51473340 0.86350735 -1.11173874 0.26527971
[43] 0.10858089 -1.99886697 1.12215477 -0.71304807 -1.24826054 1.53395555
[49] 1.10202936 0.36073041 0.54686641 -0.39508229 -0.77947149 -0.71592788
[55] -0.59056067 0.77740655 0.75292768 0.74650068 0.47640980 -0.81361571
[61] 1.26435029 -1.19261216 -0.50043606 -1.15272607 -0.71274881 1.00726583
[67] 0.47820051 -0.14489357 0.83312484 1.28276399 -1.15708203 0.53936211
[73] 0.44732598 -1.27089225 -0.21235539 -0.74370997 1.09139149 1.71510157
[79] -0.97875164 0.81454111 -0.59976516 0.54991750 -1.09012911 1.37480482
[85] 1.33123665 2.54177475 -0.21842782 -0.75865222 -0.48790256 -1.00842060
[91] 0.58797145 1.49294663 0.18914760 1.11005539 0.01729191 -0.40224775
[97] -1.93135845 -0.32340650 0.95894377 0.63116537
> colMedians(tmp)
[1] 0.24596207 -2.08523016 1.45293033 -0.11386102 -0.21207311 -0.86502407
[7] -0.65352610 0.04183482 0.03485097 2.51055419 -0.32659329 -1.10177930
[13] 0.46024155 0.68960449 -0.88101598 0.08785093 0.11547558 0.54045124
[19] -0.40343961 -0.42833037 -0.30368868 0.75428842 0.35910175 -1.19361634
[25] 1.75114460 -1.17677376 1.24723271 1.16045380 -0.44694285 -0.02967069
[31] 0.22954260 -1.23357193 0.75892216 -0.41260241 -0.26878415 0.06610073
[37] 0.28917156 -1.04197165 -0.51473340 0.86350735 -1.11173874 0.26527971
[43] 0.10858089 -1.99886697 1.12215477 -0.71304807 -1.24826054 1.53395555
[49] 1.10202936 0.36073041 0.54686641 -0.39508229 -0.77947149 -0.71592788
[55] -0.59056067 0.77740655 0.75292768 0.74650068 0.47640980 -0.81361571
[61] 1.26435029 -1.19261216 -0.50043606 -1.15272607 -0.71274881 1.00726583
[67] 0.47820051 -0.14489357 0.83312484 1.28276399 -1.15708203 0.53936211
[73] 0.44732598 -1.27089225 -0.21235539 -0.74370997 1.09139149 1.71510157
[79] -0.97875164 0.81454111 -0.59976516 0.54991750 -1.09012911 1.37480482
[85] 1.33123665 2.54177475 -0.21842782 -0.75865222 -0.48790256 -1.00842060
[91] 0.58797145 1.49294663 0.18914760 1.11005539 0.01729191 -0.40224775
[97] -1.93135845 -0.32340650 0.95894377 0.63116537
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.2459621 -2.08523 1.45293 -0.113861 -0.2120731 -0.8650241 -0.6535261
[2,] 0.2459621 -2.08523 1.45293 -0.113861 -0.2120731 -0.8650241 -0.6535261
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.04183482 0.03485097 2.510554 -0.3265933 -1.101779 0.4602416 0.6896045
[2,] 0.04183482 0.03485097 2.510554 -0.3265933 -1.101779 0.4602416 0.6896045
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.881016 0.08785093 0.1154756 0.5404512 -0.4034396 -0.4283304 -0.3036887
[2,] -0.881016 0.08785093 0.1154756 0.5404512 -0.4034396 -0.4283304 -0.3036887
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.7542884 0.3591017 -1.193616 1.751145 -1.176774 1.247233 1.160454
[2,] 0.7542884 0.3591017 -1.193616 1.751145 -1.176774 1.247233 1.160454
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.4469429 -0.02967069 0.2295426 -1.233572 0.7589222 -0.4126024 -0.2687842
[2,] -0.4469429 -0.02967069 0.2295426 -1.233572 0.7589222 -0.4126024 -0.2687842
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.06610073 0.2891716 -1.041972 -0.5147334 0.8635074 -1.111739 0.2652797
[2,] 0.06610073 0.2891716 -1.041972 -0.5147334 0.8635074 -1.111739 0.2652797
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.1085809 -1.998867 1.122155 -0.7130481 -1.248261 1.533956 1.102029
[2,] 0.1085809 -1.998867 1.122155 -0.7130481 -1.248261 1.533956 1.102029
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.3607304 0.5468664 -0.3950823 -0.7794715 -0.7159279 -0.5905607 0.7774065
[2,] 0.3607304 0.5468664 -0.3950823 -0.7794715 -0.7159279 -0.5905607 0.7774065
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.7529277 0.7465007 0.4764098 -0.8136157 1.26435 -1.192612 -0.5004361
[2,] 0.7529277 0.7465007 0.4764098 -0.8136157 1.26435 -1.192612 -0.5004361
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.152726 -0.7127488 1.007266 0.4782005 -0.1448936 0.8331248 1.282764
[2,] -1.152726 -0.7127488 1.007266 0.4782005 -0.1448936 0.8331248 1.282764
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -1.157082 0.5393621 0.447326 -1.270892 -0.2123554 -0.74371 1.091391
[2,] -1.157082 0.5393621 0.447326 -1.270892 -0.2123554 -0.74371 1.091391
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.715102 -0.9787516 0.8145411 -0.5997652 0.5499175 -1.090129 1.374805
[2,] 1.715102 -0.9787516 0.8145411 -0.5997652 0.5499175 -1.090129 1.374805
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 1.331237 2.541775 -0.2184278 -0.7586522 -0.4879026 -1.008421 0.5879714
[2,] 1.331237 2.541775 -0.2184278 -0.7586522 -0.4879026 -1.008421 0.5879714
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 1.492947 0.1891476 1.110055 0.01729191 -0.4022477 -1.931358 -0.3234065
[2,] 1.492947 0.1891476 1.110055 0.01729191 -0.4022477 -1.931358 -0.3234065
[,99] [,100]
[1,] 0.9589438 0.6311654
[2,] 0.9589438 0.6311654
>
>
> Max(tmp2)
[1] 3.432346
> Min(tmp2)
[1] -2.853327
> mean(tmp2)
[1] -0.04850799
> Sum(tmp2)
[1] -4.850799
> Var(tmp2)
[1] 1.185478
>
> rowMeans(tmp2)
[1] 0.81965239 -0.39011920 1.25429291 -0.42299082 1.55721770 -0.30510150
[7] 0.42991875 -0.02853051 0.77437058 0.97161752 -0.19742681 -2.11627138
[13] 1.00610083 0.18746136 0.29994913 -0.37906791 -0.04119876 0.46540359
[19] 0.24648933 0.20131799 -0.36207896 -2.51629597 -0.64553110 0.92432890
[25] 1.95003733 0.51259263 -0.27261398 -0.31256378 -1.54535158 0.32592933
[31] -1.20860470 -0.03830864 -0.41949531 -1.48767390 -2.85332747 2.02272246
[37] -0.10967390 -0.89205151 -0.39016262 1.39772547 0.64840591 0.63063020
[43] -1.50928388 -1.20275695 0.30941960 1.32231170 -1.94379356 1.06721252
[49] 0.45953913 1.71287148 1.10772930 1.02489980 -0.93294410 -0.99143743
[55] 0.39800490 -0.28790815 -0.71223451 -0.80077452 -1.15977179 0.72409171
[61] 0.01255172 -0.73538172 -0.62593981 0.11458529 -1.40805149 0.86592675
[67] 3.43234568 -0.82798928 -0.79415061 -0.36919276 -0.33029857 -0.84142022
[73] 1.23932631 -1.03824764 1.00946781 -1.21542308 0.08490328 -1.56350358
[79] 0.32247655 -0.77499117 0.66541682 -0.43655275 0.46201561 1.30778273
[85] 1.26975838 0.59263513 -1.12437283 0.82255886 0.38004095 1.05731270
[91] -2.07440962 -0.44308834 1.56062174 -1.38796128 -0.74074299 1.35054514
[97] -1.48796122 -1.04353200 0.50347397 -0.91823260
> rowSums(tmp2)
[1] 0.81965239 -0.39011920 1.25429291 -0.42299082 1.55721770 -0.30510150
[7] 0.42991875 -0.02853051 0.77437058 0.97161752 -0.19742681 -2.11627138
[13] 1.00610083 0.18746136 0.29994913 -0.37906791 -0.04119876 0.46540359
[19] 0.24648933 0.20131799 -0.36207896 -2.51629597 -0.64553110 0.92432890
[25] 1.95003733 0.51259263 -0.27261398 -0.31256378 -1.54535158 0.32592933
[31] -1.20860470 -0.03830864 -0.41949531 -1.48767390 -2.85332747 2.02272246
[37] -0.10967390 -0.89205151 -0.39016262 1.39772547 0.64840591 0.63063020
[43] -1.50928388 -1.20275695 0.30941960 1.32231170 -1.94379356 1.06721252
[49] 0.45953913 1.71287148 1.10772930 1.02489980 -0.93294410 -0.99143743
[55] 0.39800490 -0.28790815 -0.71223451 -0.80077452 -1.15977179 0.72409171
[61] 0.01255172 -0.73538172 -0.62593981 0.11458529 -1.40805149 0.86592675
[67] 3.43234568 -0.82798928 -0.79415061 -0.36919276 -0.33029857 -0.84142022
[73] 1.23932631 -1.03824764 1.00946781 -1.21542308 0.08490328 -1.56350358
[79] 0.32247655 -0.77499117 0.66541682 -0.43655275 0.46201561 1.30778273
[85] 1.26975838 0.59263513 -1.12437283 0.82255886 0.38004095 1.05731270
[91] -2.07440962 -0.44308834 1.56062174 -1.38796128 -0.74074299 1.35054514
[97] -1.48796122 -1.04353200 0.50347397 -0.91823260
> 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] 0.81965239 -0.39011920 1.25429291 -0.42299082 1.55721770 -0.30510150
[7] 0.42991875 -0.02853051 0.77437058 0.97161752 -0.19742681 -2.11627138
[13] 1.00610083 0.18746136 0.29994913 -0.37906791 -0.04119876 0.46540359
[19] 0.24648933 0.20131799 -0.36207896 -2.51629597 -0.64553110 0.92432890
[25] 1.95003733 0.51259263 -0.27261398 -0.31256378 -1.54535158 0.32592933
[31] -1.20860470 -0.03830864 -0.41949531 -1.48767390 -2.85332747 2.02272246
[37] -0.10967390 -0.89205151 -0.39016262 1.39772547 0.64840591 0.63063020
[43] -1.50928388 -1.20275695 0.30941960 1.32231170 -1.94379356 1.06721252
[49] 0.45953913 1.71287148 1.10772930 1.02489980 -0.93294410 -0.99143743
[55] 0.39800490 -0.28790815 -0.71223451 -0.80077452 -1.15977179 0.72409171
[61] 0.01255172 -0.73538172 -0.62593981 0.11458529 -1.40805149 0.86592675
[67] 3.43234568 -0.82798928 -0.79415061 -0.36919276 -0.33029857 -0.84142022
[73] 1.23932631 -1.03824764 1.00946781 -1.21542308 0.08490328 -1.56350358
[79] 0.32247655 -0.77499117 0.66541682 -0.43655275 0.46201561 1.30778273
[85] 1.26975838 0.59263513 -1.12437283 0.82255886 0.38004095 1.05731270
[91] -2.07440962 -0.44308834 1.56062174 -1.38796128 -0.74074299 1.35054514
[97] -1.48796122 -1.04353200 0.50347397 -0.91823260
> rowMin(tmp2)
[1] 0.81965239 -0.39011920 1.25429291 -0.42299082 1.55721770 -0.30510150
[7] 0.42991875 -0.02853051 0.77437058 0.97161752 -0.19742681 -2.11627138
[13] 1.00610083 0.18746136 0.29994913 -0.37906791 -0.04119876 0.46540359
[19] 0.24648933 0.20131799 -0.36207896 -2.51629597 -0.64553110 0.92432890
[25] 1.95003733 0.51259263 -0.27261398 -0.31256378 -1.54535158 0.32592933
[31] -1.20860470 -0.03830864 -0.41949531 -1.48767390 -2.85332747 2.02272246
[37] -0.10967390 -0.89205151 -0.39016262 1.39772547 0.64840591 0.63063020
[43] -1.50928388 -1.20275695 0.30941960 1.32231170 -1.94379356 1.06721252
[49] 0.45953913 1.71287148 1.10772930 1.02489980 -0.93294410 -0.99143743
[55] 0.39800490 -0.28790815 -0.71223451 -0.80077452 -1.15977179 0.72409171
[61] 0.01255172 -0.73538172 -0.62593981 0.11458529 -1.40805149 0.86592675
[67] 3.43234568 -0.82798928 -0.79415061 -0.36919276 -0.33029857 -0.84142022
[73] 1.23932631 -1.03824764 1.00946781 -1.21542308 0.08490328 -1.56350358
[79] 0.32247655 -0.77499117 0.66541682 -0.43655275 0.46201561 1.30778273
[85] 1.26975838 0.59263513 -1.12437283 0.82255886 0.38004095 1.05731270
[91] -2.07440962 -0.44308834 1.56062174 -1.38796128 -0.74074299 1.35054514
[97] -1.48796122 -1.04353200 0.50347397 -0.91823260
>
> colMeans(tmp2)
[1] -0.04850799
> colSums(tmp2)
[1] -4.850799
> colVars(tmp2)
[1] 1.185478
> colSd(tmp2)
[1] 1.088797
> colMax(tmp2)
[1] 3.432346
> colMin(tmp2)
[1] -2.853327
> colMedians(tmp2)
[1] -0.0397537
> colRanges(tmp2)
[,1]
[1,] -2.853327
[2,] 3.432346
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.5906877 2.3707478 6.5980623 2.7090485 -7.3945946 0.8108616
[7] 3.6807450 1.5254612 2.4836066 2.5613216
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.7271317
[2,] -0.1961827
[3,] 0.2055897
[4,] 0.8261630
[5,] 1.0711221
>
> rowApply(tmp,sum)
[1] 4.44680858 -0.05872287 5.33687784 1.11980853 2.65025467 -0.15388228
[7] -1.75289053 1.79525624 3.88971881 -1.33728127
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 4 6 7 1 7 1 10 7 4
[2,] 1 6 2 8 10 6 9 4 3 5
[3,] 4 5 10 10 5 10 3 7 9 3
[4,] 6 2 4 3 9 4 10 6 5 8
[5,] 7 1 1 2 4 3 6 3 2 2
[6,] 2 8 5 5 3 2 4 9 8 9
[7,] 10 3 7 9 6 8 2 2 4 6
[8,] 9 10 9 4 2 1 8 8 6 1
[9,] 8 7 3 6 8 9 7 1 1 7
[10,] 3 9 8 1 7 5 5 5 10 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.45422455 0.09716940 0.71426922 -2.05556227 -0.59845284 2.58036338
[7] 1.20783882 -1.69507460 0.02816359 -0.99106014 5.35791322 -1.14848500
[13] 0.28618655 0.82935024 4.11292511 -0.37674034 -3.43757476 -0.91537859
[19] -0.60154367 2.00712893
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.7049243
[2,] -0.6250029
[3,] 0.3180330
[4,] 0.5414130
[5,] 1.9247057
>
> rowApply(tmp,sum)
[1] 2.2507276 -3.7843464 5.9548569 0.1577524 2.2766703
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 12 19 5 7 16
[2,] 5 14 17 3 12
[3,] 19 3 14 16 3
[4,] 4 6 15 4 4
[5,] 15 5 4 11 15
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.3180330 -0.48069899 1.2613078 -0.4811104 0.7384124 0.6645001
[2,] 1.9247057 0.18730880 -1.1405296 -0.9269249 -0.9310441 0.3303949
[3,] -0.7049243 1.44488470 0.8863660 0.9737909 -1.1154417 0.5782701
[4,] -0.6250029 -1.14655388 0.6204391 -0.9678394 0.2136403 1.2081294
[5,] 0.5414130 0.09222878 -0.9133141 -0.6534785 0.4959802 -0.2009312
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.6244278 0.18396335 -1.0887796 0.02725226 1.0781481 -0.42638332
[2,] -0.8277869 -1.73204394 -1.2846396 0.59411944 1.5780400 -0.04999705
[3,] 0.6465693 -0.04912056 2.5982357 -0.37714316 0.8056836 -1.30970678
[4,] 0.9688224 0.28484706 -0.6159496 -1.20986409 0.3293946 0.30919779
[5,] -1.2041938 -0.38272050 0.4192967 -0.02542458 1.5666468 0.32840436
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.09391405 0.76598642 0.3236429 -0.1374485 -1.4575455 -1.87137544
[2,] -0.10246435 -0.56225389 0.3000040 1.9668669 -0.5735664 -0.88691015
[3,] 1.62438413 0.78872443 1.5404635 -0.3719444 -1.8313168 0.56606150
[4,] -1.24704345 -0.20788596 1.1312993 -0.7268325 -0.8640855 0.08187809
[5,] -0.08260382 0.04477924 0.8175154 -1.1073818 1.2889395 1.19496742
[,19] [,20]
[1,] 1.16092757 -0.046446426
[2,] -0.53888810 -1.108737250
[3,] -1.72083914 0.981860020
[4,] 0.45007175 2.171089797
[5,] 0.04718425 0.009362785
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-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: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 650 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-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-3.21-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 -2.251842 -0.6573313 0.2567223 0.2144413 -1.267948 -0.6367207 -1.46392
col8 col9 col10 col11 col12 col13 col14
row1 0.1559578 -0.8911253 -0.7930245 -1.162121 0.8424431 0.5149301 1.186352
col15 col16 col17 col18 col19 col20
row1 0.2642006 0.1988697 -0.6257291 -0.5570099 0.385715 0.6215843
> tmp[,"col10"]
col10
row1 -0.7930245
row2 0.4796489
row3 0.8611191
row4 1.3483648
row5 0.8148555
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -2.2518420 -0.6573313 0.2567223 0.2144413 -1.2679478 -0.6367207 -1.463920
row5 -0.2238695 0.9031204 -0.1013506 1.6977278 -0.4555184 -1.1307816 1.428555
col8 col9 col10 col11 col12 col13 col14
row1 0.1559578 -0.8911253 -0.7930245 -1.16212078 0.8424431 0.5149301 1.186352
row5 0.3745330 1.2987168 0.8148555 -0.09366775 -0.3693834 0.7593263 2.322820
col15 col16 col17 col18 col19 col20
row1 0.2642006 0.1988697 -0.6257291 -0.5570099 0.385715 0.6215843
row5 0.5841836 -0.2455375 1.0330638 -1.1385610 2.160414 -1.3750513
> tmp[,c("col6","col20")]
col6 col20
row1 -0.6367207 0.6215843
row2 0.1713620 1.5323695
row3 0.4477822 -0.9704051
row4 -0.2932205 -0.1979746
row5 -1.1307816 -1.3750513
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.6367207 0.6215843
row5 -1.1307816 -1.3750513
>
>
>
>
> 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 48.25875 50.66509 50.26659 49.1827 49.27126 103.4621 48.82615 48.09771
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.9186 49.2594 48.54579 49.59727 50.70613 49.0057 51.34553 50.54514
col17 col18 col19 col20
row1 49.7178 49.32979 49.10908 106.8153
> tmp[,"col10"]
col10
row1 49.25940
row2 30.59426
row3 30.62200
row4 30.02258
row5 47.98700
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.25875 50.66509 50.26659 49.18270 49.27126 103.4621 48.82615 48.09771
row5 50.13786 51.46429 48.79890 49.89403 49.69445 106.1676 48.03050 51.31170
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.91860 49.2594 48.54579 49.59727 50.70613 49.00570 51.34553 50.54514
row5 48.88981 47.9870 50.53128 49.83298 51.70444 50.76709 51.78603 50.54667
col17 col18 col19 col20
row1 49.71780 49.32979 49.10908 106.8153
row5 49.90195 49.95388 50.51231 104.2455
> tmp[,c("col6","col20")]
col6 col20
row1 103.46211 106.81530
row2 75.28915 73.67302
row3 74.23659 74.70486
row4 76.15495 74.74545
row5 106.16761 104.24553
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 103.4621 106.8153
row5 106.1676 104.2455
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 103.4621 106.8153
row5 106.1676 104.2455
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.6741016
[2,] 0.4942409
[3,] 0.1273852
[4,] -0.4630619
[5,] -0.1471217
> tmp[,c("col17","col7")]
col17 col7
[1,] -2.2162436 -1.2807908
[2,] 1.3476852 -1.1676927
[3,] -0.9481037 -1.8929659
[4,] -0.2989612 -0.5380026
[5,] -1.5738925 0.3244379
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.1953463 -0.8205086
[2,] -1.4641827 -1.2899559
[3,] -0.7087590 -0.8253916
[4,] -1.2147998 -0.1342102
[5,] -0.8345790 -0.3796235
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.1953463
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.1953463
[2,] -1.4641827
>
>
>
> 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 0.5563266 2.295418 -0.8221779 -1.240355 1.585060 1.1043970 -1.0734828
row1 1.5870792 -0.428909 -0.1368187 -2.224490 1.154109 0.4870158 0.3085477
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.7895599 0.8889927 0.1111420 0.2992378 -0.5920061 2.1083076
row1 0.5437418 -1.5338899 -0.2134302 -0.2744830 -1.1147993 0.7139556
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.4233795 -0.1822470 -0.15120232 1.202869 1.29103902 -1.2695271
row1 0.6668294 -0.5887869 0.05576616 2.201622 0.08689967 0.3799298
[,20]
row3 0.9770772
row1 -0.5174947
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.04165821 -0.8473875 -0.8479037 -0.744853 0.1127933 0.4993013 -0.6537376
[,8] [,9] [,10]
row2 0.298172 -1.781978 0.2021484
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -1.06259 0.3751439 -0.450586 0.6276784 -0.5433422 -0.6707996 0.7410078
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.6306319 0.1852218 2.286532 -0.5408046 0.08963901 -0.5137681 1.22054
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.6261815 -2.178111 -1.783008 -0.1607824 -1.933505 0.6457345
>
>
> 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: 0x600000ab8660>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMd394600d6df1"
[2] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMd39411ad1a7b"
[3] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMd3947ba58a4d"
[4] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMd394311b04a6"
[5] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMd39464ce4779"
[6] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMd39422b68ca3"
[7] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMd3947ecb3322"
[8] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMd3944e8a3e36"
[9] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMd39455fa7382"
[10] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMd3942db587e7"
[11] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMd39468ed6622"
[12] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMd39439cc77ff"
[13] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMd3941eda23fe"
[14] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMd3943710885"
[15] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMd39471e65586"
>
>
> ### 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: 0x600000ab45a0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600000ab45a0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600000ab45a0>
> rowMedians(tmp)
[1] 0.148578379 0.497270103 -0.299194387 0.519485354 0.309562534
[6] 0.471149344 0.111052283 -0.339837240 0.192345829 0.333493751
[11] 0.096398068 0.344387512 0.462576527 -0.146287898 -0.085228599
[16] -0.197983106 -0.262711096 0.424821584 -0.328033058 0.124101520
[21] -0.366410194 0.140763007 0.262608590 0.009636688 -0.033168889
[26] 0.635108154 0.120948750 0.064833896 0.026823600 0.075348484
[31] 0.315985939 -0.234947190 0.416899691 0.230035325 -0.244612737
[36] 0.192771129 0.709874628 0.129051566 0.130987933 0.533416872
[41] 0.421308851 -0.027879154 0.236016106 0.025473673 0.208083550
[46] -0.599987622 -0.314115007 -0.159675348 0.341876507 -0.007562601
[51] 0.003413679 -0.144173887 -0.074763511 -0.092300659 0.252638086
[56] 0.400785105 0.028064932 -0.567981054 -0.393133089 0.129956688
[61] -0.022264417 -0.119696525 -0.024780506 0.137895000 0.020097578
[66] 0.101458507 -0.512659724 0.351182384 0.123649012 -0.364878808
[71] -0.161112681 0.614439389 -0.246169969 0.351131409 0.422074530
[76] 0.395806969 0.050569168 -0.392463600 -0.003186576 0.141742927
[81] 0.115108397 -0.582248608 0.182508926 -0.133914244 -0.047167177
[86] 0.136394921 0.387044306 -0.483079199 -0.368567244 -0.167408523
[91] -0.404333091 0.225429044 -0.254312196 0.275661258 0.245383176
[96] -0.209682404 -0.036735148 0.258283612 0.139468547 -0.174082230
[101] 0.064115362 0.497896104 0.208193658 0.091122198 -0.024262318
[106] 0.165120943 -0.375664512 -0.449146798 -0.221036073 -0.420330482
[111] -0.092882392 -0.102106531 0.222482602 -0.571199174 -0.325357560
[116] -0.069917689 -0.204680090 -0.728870417 -0.464550867 -0.028275838
[121] 0.305630748 0.624746174 0.369250850 0.109204545 -0.494957457
[126] -0.220315509 0.179521200 0.091809502 0.074540563 0.023675801
[131] -0.178836510 0.345106365 -0.296230010 -0.365770809 -0.492828366
[136] 0.384350101 -0.505712978 0.213762264 -0.386514434 -0.129666703
[141] 0.154449236 -0.214592800 -0.139057750 0.321060292 -0.287018082
[146] -0.498102792 0.115649757 0.242441324 -0.214108854 0.006472844
[151] 0.498228699 -0.119710335 0.197245402 0.040658332 0.051055373
[156] -0.358882588 0.167772368 0.343324663 -0.161882505 -0.933411070
[161] 0.409357528 0.394893860 0.070379418 -0.157973337 -0.290193770
[166] -0.012373633 0.317799986 0.180587213 -0.463002082 -0.072824628
[171] -0.016686113 -0.239207793 -0.411141591 0.103383666 -0.282569898
[176] 0.193908949 -0.265551483 0.044259526 -0.097973133 0.433093991
[181] 0.338921768 -0.282666307 0.332580602 -0.477765851 -0.214628382
[186] -0.292383106 0.658554688 0.121224402 -0.239429506 0.357664475
[191] -0.249362864 0.086603291 -0.490499340 0.457903222 -0.366503058
[196] 0.356820068 0.348784271 0.094440530 -0.122526549 0.090430792
[201] -0.177972750 0.203269230 -0.132938845 -0.285898121 0.322262593
[206] 0.133155387 -0.519913518 -0.187490647 0.264475060 -0.243608204
[211] -0.382187165 0.020544404 0.271776323 0.242435913 0.337805557
[216] -0.127993382 0.353234387 -0.042632398 0.285934867 0.680168604
[221] -0.277392745 0.583037130 -0.461375244 0.101758140 0.282741339
[226] -0.468944341 0.741376533 0.082771456 -0.412091932 0.639095770
>
> proc.time()
user system elapsed
2.043 8.434 10.852
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-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: 0x600003adc060>
> .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: 0x600003adc060>
> .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: 0x600003adc060>
> .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: 0x600003adc060>
> 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: 0x600003ad4b40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003ad4b40>
> .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: 0x600003ad4b40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003ad4b40>
> .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: 0x600003ad4b40>
> 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: 0x600003ad8240>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003ad8240>
> .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: 0x600003ad8240>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003ad8240>
> .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: 0x600003ad8240>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600003ad8240>
> .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: 0x600003ad8240>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600003ad8240>
> .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: 0x600003ad8240>
> 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: 0x600003ad83c0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600003ad83c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003ad83c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003ad83c0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFiled3bf1067a5cd" "BufferedMatrixFiled3bf4b63e25"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFiled3bf1067a5cd" "BufferedMatrixFiled3bf4b63e25"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003ad00c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003ad00c0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003ad00c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003ad00c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600003ad00c0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600003ad00c0>
> .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: 0x600003ad0240>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003ad0240>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003ad0240>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600003ad0240>
> 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: 0x600003ad0420>
> .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: 0x600003ad0420>
> rm(P)
>
> proc.time()
user system elapsed
0.342 0.113 0.445
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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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.
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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
0.345 0.078 0.413