Ben Bolstad
| Snapshot Date: 2025-10-13 13:40 -0400 (Mon, 13 Oct 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 2025-10-16 11:38 -0400 (Thu, 16 Oct 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" | 4833 |
| merida1 | macOS 12.7.6 Monterey | x86_64 | 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root" | 4614 |
| kjohnson1 | macOS 13.7.5 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4555 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4586 |
| 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 12.7.6 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.7.5 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: 2025-10-14 00:56:46 -0400 (Tue, 14 Oct 2025) |
| EndedAt: 2025-10-14 00:58:02 -0400 (Tue, 14 Oct 2025) |
| EllapsedTime: 76.2 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 RC (2025-06-05 r88288)
* 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 ‘1.72.0’
* 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 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-3.21-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-x86_64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.72.0’
** 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 RC (2025-06-05 r88288) -- "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
0.575 0.203 0.758
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 RC (2025-06-05 r88288) -- "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-3.21-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 480849 25.7 1056621 56.5 NA 634465 33.9
Vcells 891080 6.8 8388608 64.0 65536 2108740 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] "Tue Oct 14 00:57:20 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Oct 14 00:57:21 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: 0x600002c48000>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Tue Oct 14 00:57:28 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Oct 14 00:57:31 2025"
>
> ColMode(tmp2)
<pointer: 0x600002c48000>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.6864316 3.0467593 0.07487724 1.7748525
[2,] 1.0844363 0.6127982 -0.15486872 0.5912668
[3,] -0.6980916 1.2121693 -0.41852799 -0.6258008
[4,] -0.2922984 -1.0588463 2.10662049 -0.7946823
> 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,] 99.6864316 3.0467593 0.07487724 1.7748525
[2,] 1.0844363 0.6127982 0.15486872 0.5912668
[3,] 0.6980916 1.2121693 0.41852799 0.6258008
[4,] 0.2922984 1.0588463 2.10662049 0.7946823
> 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,] 9.9843093 1.7454969 0.2736371 1.3322359
[2,] 1.0413627 0.7828143 0.3935336 0.7689388
[3,] 0.8355188 1.1009856 0.6469374 0.7910757
[4,] 0.5406462 1.0290026 1.4514202 0.8914495
>
> 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,] 224.52952 45.50173 27.81125 40.09721
[2,] 36.49806 33.44094 29.09021 33.28065
[3,] 34.05328 37.22203 31.88790 33.53656
[4,] 30.69876 36.34887 41.62082 34.70918
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600002c7c0c0>
> exp(tmp5)
<pointer: 0x600002c7c0c0>
> log(tmp5,2)
<pointer: 0x600002c7c0c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.3288
> Min(tmp5)
[1] 53.21017
> mean(tmp5)
[1] 72.90415
> Sum(tmp5)
[1] 14580.83
> Var(tmp5)
[1] 859.4349
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.06300 71.37665 70.12251 71.31681 71.87003 70.16178 71.00060 71.10184
[9] 70.27453 72.75375
> rowSums(tmp5)
[1] 1781.260 1427.533 1402.450 1426.336 1437.401 1403.236 1420.012 1422.037
[9] 1405.491 1455.075
> rowVars(tmp5)
[1] 8023.58761 45.62319 62.47906 72.63300 70.75420 108.22356
[7] 48.63632 61.04377 108.45994 88.32720
> rowSd(tmp5)
[1] 89.574481 6.754494 7.904369 8.522499 8.411552 10.403055 6.973974
[8] 7.813051 10.414410 9.398255
> rowMax(tmp5)
[1] 467.32879 82.19013 82.95261 86.90222 88.05915 93.31769 87.61246
[8] 87.50941 89.32992 94.92410
> rowMin(tmp5)
[1] 56.72026 57.34516 55.19291 59.11401 55.29387 55.38851 56.82417 57.13455
[9] 53.21017 56.44008
>
> colMeans(tmp5)
[1] 113.09854 73.35202 69.83224 76.49297 70.93127 75.22437 64.41761
[8] 73.49437 71.82126 72.96672 71.48272 67.53282 69.48560 70.83590
[15] 67.03168 71.40923 71.46035 69.88617 69.57655 67.75061
> colSums(tmp5)
[1] 1130.9854 733.5202 698.3224 764.9297 709.3127 752.2437 644.1761
[8] 734.9437 718.2126 729.6672 714.8272 675.3282 694.8560 708.3590
[15] 670.3168 714.0923 714.6035 698.8617 695.7655 677.5061
> colVars(tmp5)
[1] 15516.21944 118.06174 96.04412 65.68730 68.62614 107.58228
[7] 29.96059 95.36198 29.28307 63.23742 67.95938 45.75094
[13] 83.34640 109.40280 42.11218 38.67665 88.08867 127.74240
[19] 75.80629 74.87967
> colSd(tmp5)
[1] 124.564118 10.865622 9.800210 8.104770 8.284090 10.372188
[7] 5.473627 9.765346 5.411383 7.952196 8.243748 6.763944
[13] 9.129425 10.459579 6.489390 6.219055 9.385557 11.302319
[19] 8.706681 8.653304
> colMax(tmp5)
[1] 467.32879 94.70588 86.62829 94.92410 87.61246 87.50941 73.71000
[8] 89.32992 79.24439 83.20877 85.48942 78.91109 81.33473 88.05915
[15] 75.34558 79.19254 84.52800 93.31769 81.69050 77.82372
> colMin(tmp5)
[1] 63.89545 56.95063 55.63823 69.26932 61.89084 53.80289 56.72026 56.90889
[9] 64.31416 60.25560 60.28508 55.19291 57.05516 53.70511 55.29387 56.96368
[17] 53.21017 56.82083 56.44008 55.38851
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 89.06300 71.37665 NA 71.31681 71.87003 70.16178 71.00060 71.10184
[9] 70.27453 72.75375
> rowSums(tmp5)
[1] 1781.260 1427.533 NA 1426.336 1437.401 1403.236 1420.012 1422.037
[9] 1405.491 1455.075
> rowVars(tmp5)
[1] 8023.58761 45.62319 65.68679 72.63300 70.75420 108.22356
[7] 48.63632 61.04377 108.45994 88.32720
> rowSd(tmp5)
[1] 89.574481 6.754494 8.104739 8.522499 8.411552 10.403055 6.973974
[8] 7.813051 10.414410 9.398255
> rowMax(tmp5)
[1] 467.32879 82.19013 NA 86.90222 88.05915 93.31769 87.61246
[8] 87.50941 89.32992 94.92410
> rowMin(tmp5)
[1] 56.72026 57.34516 NA 59.11401 55.29387 55.38851 56.82417 57.13455
[9] 53.21017 56.44008
>
> colMeans(tmp5)
[1] 113.09854 73.35202 69.83224 76.49297 70.93127 75.22437 64.41761
[8] 73.49437 71.82126 72.96672 NA 67.53282 69.48560 70.83590
[15] 67.03168 71.40923 71.46035 69.88617 69.57655 67.75061
> colSums(tmp5)
[1] 1130.9854 733.5202 698.3224 764.9297 709.3127 752.2437 644.1761
[8] 734.9437 718.2126 729.6672 NA 675.3282 694.8560 708.3590
[15] 670.3168 714.0923 714.6035 698.8617 695.7655 677.5061
> colVars(tmp5)
[1] 15516.21944 118.06174 96.04412 65.68730 68.62614 107.58228
[7] 29.96059 95.36198 29.28307 63.23742 NA 45.75094
[13] 83.34640 109.40280 42.11218 38.67665 88.08867 127.74240
[19] 75.80629 74.87967
> colSd(tmp5)
[1] 124.564118 10.865622 9.800210 8.104770 8.284090 10.372188
[7] 5.473627 9.765346 5.411383 7.952196 NA 6.763944
[13] 9.129425 10.459579 6.489390 6.219055 9.385557 11.302319
[19] 8.706681 8.653304
> colMax(tmp5)
[1] 467.32879 94.70588 86.62829 94.92410 87.61246 87.50941 73.71000
[8] 89.32992 79.24439 83.20877 NA 78.91109 81.33473 88.05915
[15] 75.34558 79.19254 84.52800 93.31769 81.69050 77.82372
> colMin(tmp5)
[1] 63.89545 56.95063 55.63823 69.26932 61.89084 53.80289 56.72026 56.90889
[9] 64.31416 60.25560 NA 55.19291 57.05516 53.70511 55.29387 56.96368
[17] 53.21017 56.82083 56.44008 55.38851
>
> Max(tmp5,na.rm=TRUE)
[1] 467.3288
> Min(tmp5,na.rm=TRUE)
[1] 53.21017
> mean(tmp5,na.rm=TRUE)
[1] 72.92879
> Sum(tmp5,na.rm=TRUE)
[1] 14512.83
> Var(tmp5,na.rm=TRUE)
[1] 863.6535
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.06300 71.37665 70.23419 71.31681 71.87003 70.16178 71.00060 71.10184
[9] 70.27453 72.75375
> rowSums(tmp5,na.rm=TRUE)
[1] 1781.260 1427.533 1334.450 1426.336 1437.401 1403.236 1420.012 1422.037
[9] 1405.491 1455.075
> rowVars(tmp5,na.rm=TRUE)
[1] 8023.58761 45.62319 65.68679 72.63300 70.75420 108.22356
[7] 48.63632 61.04377 108.45994 88.32720
> rowSd(tmp5,na.rm=TRUE)
[1] 89.574481 6.754494 8.104739 8.522499 8.411552 10.403055 6.973974
[8] 7.813051 10.414410 9.398255
> rowMax(tmp5,na.rm=TRUE)
[1] 467.32879 82.19013 82.95261 86.90222 88.05915 93.31769 87.61246
[8] 87.50941 89.32992 94.92410
> rowMin(tmp5,na.rm=TRUE)
[1] 56.72026 57.34516 55.19291 59.11401 55.29387 55.38851 56.82417 57.13455
[9] 53.21017 56.44008
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.09854 73.35202 69.83224 76.49297 70.93127 75.22437 64.41761
[8] 73.49437 71.82126 72.96672 71.86963 67.53282 69.48560 70.83590
[15] 67.03168 71.40923 71.46035 69.88617 69.57655 67.75061
> colSums(tmp5,na.rm=TRUE)
[1] 1130.9854 733.5202 698.3224 764.9297 709.3127 752.2437 644.1761
[8] 734.9437 718.2126 729.6672 646.8267 675.3282 694.8560 708.3590
[15] 670.3168 714.0923 714.6035 698.8617 695.7655 677.5061
> colVars(tmp5,na.rm=TRUE)
[1] 15516.21944 118.06174 96.04412 65.68730 68.62614 107.58228
[7] 29.96059 95.36198 29.28307 63.23742 74.77017 45.75094
[13] 83.34640 109.40280 42.11218 38.67665 88.08867 127.74240
[19] 75.80629 74.87967
> colSd(tmp5,na.rm=TRUE)
[1] 124.564118 10.865622 9.800210 8.104770 8.284090 10.372188
[7] 5.473627 9.765346 5.411383 7.952196 8.646975 6.763944
[13] 9.129425 10.459579 6.489390 6.219055 9.385557 11.302319
[19] 8.706681 8.653304
> colMax(tmp5,na.rm=TRUE)
[1] 467.32879 94.70588 86.62829 94.92410 87.61246 87.50941 73.71000
[8] 89.32992 79.24439 83.20877 85.48942 78.91109 81.33473 88.05915
[15] 75.34558 79.19254 84.52800 93.31769 81.69050 77.82372
> colMin(tmp5,na.rm=TRUE)
[1] 63.89545 56.95063 55.63823 69.26932 61.89084 53.80289 56.72026 56.90889
[9] 64.31416 60.25560 60.28508 55.19291 57.05516 53.70511 55.29387 56.96368
[17] 53.21017 56.82083 56.44008 55.38851
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.06300 71.37665 NaN 71.31681 71.87003 70.16178 71.00060 71.10184
[9] 70.27453 72.75375
> rowSums(tmp5,na.rm=TRUE)
[1] 1781.260 1427.533 0.000 1426.336 1437.401 1403.236 1420.012 1422.037
[9] 1405.491 1455.075
> rowVars(tmp5,na.rm=TRUE)
[1] 8023.58761 45.62319 NA 72.63300 70.75420 108.22356
[7] 48.63632 61.04377 108.45994 88.32720
> rowSd(tmp5,na.rm=TRUE)
[1] 89.574481 6.754494 NA 8.522499 8.411552 10.403055 6.973974
[8] 7.813051 10.414410 9.398255
> rowMax(tmp5,na.rm=TRUE)
[1] 467.32879 82.19013 NA 86.90222 88.05915 93.31769 87.61246
[8] 87.50941 89.32992 94.92410
> rowMin(tmp5,na.rm=TRUE)
[1] 56.72026 57.34516 NA 59.11401 55.29387 55.38851 56.82417 57.13455
[9] 53.21017 56.44008
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 117.78977 72.89416 70.21688 77.23642 71.32547 74.36568 63.38512
[8] 74.19069 72.65538 72.16108 NaN 68.90393 68.44113 71.14845
[15] 66.63412 73.01430 70.56587 71.33787 69.34254 66.78594
> colSums(tmp5,na.rm=TRUE)
[1] 1060.1079 656.0474 631.9519 695.1278 641.9292 669.2911 570.4661
[8] 667.7162 653.8984 649.4497 0.0000 620.1353 615.9702 640.3360
[15] 599.7071 657.1287 635.0928 642.0408 624.0828 601.0735
> colVars(tmp5,na.rm=TRUE)
[1] 17208.16063 130.46105 106.38523 67.68019 75.45624 112.73484
[7] 21.71281 101.82750 25.11614 63.84008 NA 30.32070
[13] 81.49206 121.97918 45.59813 14.52873 90.09877 120.00145
[19] 84.66599 73.77061
> colSd(tmp5,na.rm=TRUE)
[1] 131.179879 11.421955 10.314322 8.226797 8.686555 10.617666
[7] 4.659700 10.090961 5.011601 7.989999 NA 5.506424
[13] 9.027295 11.044418 6.752639 3.811657 9.492037 10.954517
[19] 9.201412 8.588982
> colMax(tmp5,na.rm=TRUE)
[1] 467.32879 94.70588 86.62829 94.92410 87.61246 87.50941 68.18591
[8] 89.32992 79.24439 83.20877 -Inf 78.91109 81.33473 88.05915
[15] 75.34558 79.19254 84.52800 93.31769 81.69050 77.82372
> colMin(tmp5,na.rm=TRUE)
[1] 63.89545 56.95063 55.63823 69.26932 61.89084 53.80289 56.72026 56.90889
[9] 64.89869 60.25560 Inf 60.60047 57.05516 53.70511 55.29387 66.25654
[17] 53.21017 59.18801 56.44008 55.38851
>
>
>
>
> 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] 229.9115 190.8664 147.0501 221.4971 228.8857 292.0697 218.9553 217.9360
[9] 234.9761 109.8400
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 229.9115 190.8664 147.0501 221.4971 228.8857 292.0697 218.9553 217.9360
[9] 234.9761 109.8400
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -1.705303e-13 0.000000e+00 1.421085e-13 3.410605e-13 -2.842171e-14
[6] -1.421085e-13 -3.410605e-13 -2.273737e-13 -2.842171e-14 0.000000e+00
[11] 1.136868e-13 -2.842171e-14 2.842171e-14 8.526513e-14 1.136868e-13
[16] -8.526513e-14 5.684342e-14 -2.842171e-14 0.000000e+00 -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)
+ }
6 9
5 1
7 7
3 15
1 6
7 11
2 1
7 5
4 9
7 20
4 4
8 17
9 5
4 15
2 16
9 8
4 20
5 9
7 1
7 18
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] 2.420993
> Min(tmp)
[1] -2.33863
> mean(tmp)
[1] 0.09909588
> Sum(tmp)
[1] 9.909588
> Var(tmp)
[1] 1.150233
>
> rowMeans(tmp)
[1] 0.09909588
> rowSums(tmp)
[1] 9.909588
> rowVars(tmp)
[1] 1.150233
> rowSd(tmp)
[1] 1.072489
> rowMax(tmp)
[1] 2.420993
> rowMin(tmp)
[1] -2.33863
>
> colMeans(tmp)
[1] -1.226329362 -0.666096891 0.347852430 0.491371905 0.327639736
[6] -0.522378042 0.077776616 0.378111129 0.699757878 1.002341465
[11] 0.131041334 -1.654636495 -0.767316617 -0.525868552 2.168264623
[16] 1.092581528 0.512858435 1.501451357 2.420992760 -1.824799113
[21] -1.660990721 -0.357671007 0.024083767 0.417199256 -0.022030122
[26] -0.160088720 0.631133912 1.325780348 -0.501583770 0.783224118
[31] 0.955750519 0.829889362 -1.319742343 -0.130133953 1.105041405
[36] 2.046299969 0.589918303 0.647194478 1.196672465 -2.338629528
[41] 0.796843640 0.191142835 0.746343606 0.670894241 -0.924317226
[46] 1.076112352 0.434799959 1.513488000 0.485753396 -1.308832739
[51] 0.365918602 0.227730186 -1.615076503 0.738524372 -0.765815244
[56] -0.871512790 0.321705427 -0.477006508 -0.420540366 -1.827807257
[61] 0.402294619 1.082681346 -0.807254308 -0.007891242 -0.607583055
[66] 1.665190987 -0.945081955 -0.860759940 -0.740204752 -0.069412916
[71] -0.496157165 -0.507074461 -1.941813490 -1.134876845 0.908632824
[76] 0.549195656 1.995771183 1.190328155 -1.476016878 0.265487487
[81] 0.317651684 0.066884869 0.982317169 0.864195837 0.405942074
[86] -0.713422278 2.102619414 -1.205218704 -1.363996189 -1.368144279
[91] 0.009630704 -0.815122046 -0.059415686 2.286025102 0.312164606
[96] -1.342966862 -0.794635637 2.404425011 1.300083758 0.670832146
> colSums(tmp)
[1] -1.226329362 -0.666096891 0.347852430 0.491371905 0.327639736
[6] -0.522378042 0.077776616 0.378111129 0.699757878 1.002341465
[11] 0.131041334 -1.654636495 -0.767316617 -0.525868552 2.168264623
[16] 1.092581528 0.512858435 1.501451357 2.420992760 -1.824799113
[21] -1.660990721 -0.357671007 0.024083767 0.417199256 -0.022030122
[26] -0.160088720 0.631133912 1.325780348 -0.501583770 0.783224118
[31] 0.955750519 0.829889362 -1.319742343 -0.130133953 1.105041405
[36] 2.046299969 0.589918303 0.647194478 1.196672465 -2.338629528
[41] 0.796843640 0.191142835 0.746343606 0.670894241 -0.924317226
[46] 1.076112352 0.434799959 1.513488000 0.485753396 -1.308832739
[51] 0.365918602 0.227730186 -1.615076503 0.738524372 -0.765815244
[56] -0.871512790 0.321705427 -0.477006508 -0.420540366 -1.827807257
[61] 0.402294619 1.082681346 -0.807254308 -0.007891242 -0.607583055
[66] 1.665190987 -0.945081955 -0.860759940 -0.740204752 -0.069412916
[71] -0.496157165 -0.507074461 -1.941813490 -1.134876845 0.908632824
[76] 0.549195656 1.995771183 1.190328155 -1.476016878 0.265487487
[81] 0.317651684 0.066884869 0.982317169 0.864195837 0.405942074
[86] -0.713422278 2.102619414 -1.205218704 -1.363996189 -1.368144279
[91] 0.009630704 -0.815122046 -0.059415686 2.286025102 0.312164606
[96] -1.342966862 -0.794635637 2.404425011 1.300083758 0.670832146
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] -1.226329362 -0.666096891 0.347852430 0.491371905 0.327639736
[6] -0.522378042 0.077776616 0.378111129 0.699757878 1.002341465
[11] 0.131041334 -1.654636495 -0.767316617 -0.525868552 2.168264623
[16] 1.092581528 0.512858435 1.501451357 2.420992760 -1.824799113
[21] -1.660990721 -0.357671007 0.024083767 0.417199256 -0.022030122
[26] -0.160088720 0.631133912 1.325780348 -0.501583770 0.783224118
[31] 0.955750519 0.829889362 -1.319742343 -0.130133953 1.105041405
[36] 2.046299969 0.589918303 0.647194478 1.196672465 -2.338629528
[41] 0.796843640 0.191142835 0.746343606 0.670894241 -0.924317226
[46] 1.076112352 0.434799959 1.513488000 0.485753396 -1.308832739
[51] 0.365918602 0.227730186 -1.615076503 0.738524372 -0.765815244
[56] -0.871512790 0.321705427 -0.477006508 -0.420540366 -1.827807257
[61] 0.402294619 1.082681346 -0.807254308 -0.007891242 -0.607583055
[66] 1.665190987 -0.945081955 -0.860759940 -0.740204752 -0.069412916
[71] -0.496157165 -0.507074461 -1.941813490 -1.134876845 0.908632824
[76] 0.549195656 1.995771183 1.190328155 -1.476016878 0.265487487
[81] 0.317651684 0.066884869 0.982317169 0.864195837 0.405942074
[86] -0.713422278 2.102619414 -1.205218704 -1.363996189 -1.368144279
[91] 0.009630704 -0.815122046 -0.059415686 2.286025102 0.312164606
[96] -1.342966862 -0.794635637 2.404425011 1.300083758 0.670832146
> colMin(tmp)
[1] -1.226329362 -0.666096891 0.347852430 0.491371905 0.327639736
[6] -0.522378042 0.077776616 0.378111129 0.699757878 1.002341465
[11] 0.131041334 -1.654636495 -0.767316617 -0.525868552 2.168264623
[16] 1.092581528 0.512858435 1.501451357 2.420992760 -1.824799113
[21] -1.660990721 -0.357671007 0.024083767 0.417199256 -0.022030122
[26] -0.160088720 0.631133912 1.325780348 -0.501583770 0.783224118
[31] 0.955750519 0.829889362 -1.319742343 -0.130133953 1.105041405
[36] 2.046299969 0.589918303 0.647194478 1.196672465 -2.338629528
[41] 0.796843640 0.191142835 0.746343606 0.670894241 -0.924317226
[46] 1.076112352 0.434799959 1.513488000 0.485753396 -1.308832739
[51] 0.365918602 0.227730186 -1.615076503 0.738524372 -0.765815244
[56] -0.871512790 0.321705427 -0.477006508 -0.420540366 -1.827807257
[61] 0.402294619 1.082681346 -0.807254308 -0.007891242 -0.607583055
[66] 1.665190987 -0.945081955 -0.860759940 -0.740204752 -0.069412916
[71] -0.496157165 -0.507074461 -1.941813490 -1.134876845 0.908632824
[76] 0.549195656 1.995771183 1.190328155 -1.476016878 0.265487487
[81] 0.317651684 0.066884869 0.982317169 0.864195837 0.405942074
[86] -0.713422278 2.102619414 -1.205218704 -1.363996189 -1.368144279
[91] 0.009630704 -0.815122046 -0.059415686 2.286025102 0.312164606
[96] -1.342966862 -0.794635637 2.404425011 1.300083758 0.670832146
> colMedians(tmp)
[1] -1.226329362 -0.666096891 0.347852430 0.491371905 0.327639736
[6] -0.522378042 0.077776616 0.378111129 0.699757878 1.002341465
[11] 0.131041334 -1.654636495 -0.767316617 -0.525868552 2.168264623
[16] 1.092581528 0.512858435 1.501451357 2.420992760 -1.824799113
[21] -1.660990721 -0.357671007 0.024083767 0.417199256 -0.022030122
[26] -0.160088720 0.631133912 1.325780348 -0.501583770 0.783224118
[31] 0.955750519 0.829889362 -1.319742343 -0.130133953 1.105041405
[36] 2.046299969 0.589918303 0.647194478 1.196672465 -2.338629528
[41] 0.796843640 0.191142835 0.746343606 0.670894241 -0.924317226
[46] 1.076112352 0.434799959 1.513488000 0.485753396 -1.308832739
[51] 0.365918602 0.227730186 -1.615076503 0.738524372 -0.765815244
[56] -0.871512790 0.321705427 -0.477006508 -0.420540366 -1.827807257
[61] 0.402294619 1.082681346 -0.807254308 -0.007891242 -0.607583055
[66] 1.665190987 -0.945081955 -0.860759940 -0.740204752 -0.069412916
[71] -0.496157165 -0.507074461 -1.941813490 -1.134876845 0.908632824
[76] 0.549195656 1.995771183 1.190328155 -1.476016878 0.265487487
[81] 0.317651684 0.066884869 0.982317169 0.864195837 0.405942074
[86] -0.713422278 2.102619414 -1.205218704 -1.363996189 -1.368144279
[91] 0.009630704 -0.815122046 -0.059415686 2.286025102 0.312164606
[96] -1.342966862 -0.794635637 2.404425011 1.300083758 0.670832146
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.226329 -0.6660969 0.3478524 0.4913719 0.3276397 -0.522378 0.07777662
[2,] -1.226329 -0.6660969 0.3478524 0.4913719 0.3276397 -0.522378 0.07777662
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.3781111 0.6997579 1.002341 0.1310413 -1.654636 -0.7673166 -0.5258686
[2,] 0.3781111 0.6997579 1.002341 0.1310413 -1.654636 -0.7673166 -0.5258686
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 2.168265 1.092582 0.5128584 1.501451 2.420993 -1.824799 -1.660991
[2,] 2.168265 1.092582 0.5128584 1.501451 2.420993 -1.824799 -1.660991
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.357671 0.02408377 0.4171993 -0.02203012 -0.1600887 0.6311339 1.32578
[2,] -0.357671 0.02408377 0.4171993 -0.02203012 -0.1600887 0.6311339 1.32578
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.5015838 0.7832241 0.9557505 0.8298894 -1.319742 -0.130134 1.105041
[2,] -0.5015838 0.7832241 0.9557505 0.8298894 -1.319742 -0.130134 1.105041
[,36] [,37] [,38] [,39] [,40] [,41] [,42] [,43]
[1,] 2.0463 0.5899183 0.6471945 1.196672 -2.33863 0.7968436 0.1911428 0.7463436
[2,] 2.0463 0.5899183 0.6471945 1.196672 -2.33863 0.7968436 0.1911428 0.7463436
[,44] [,45] [,46] [,47] [,48] [,49] [,50]
[1,] 0.6708942 -0.9243172 1.076112 0.4348 1.513488 0.4857534 -1.308833
[2,] 0.6708942 -0.9243172 1.076112 0.4348 1.513488 0.4857534 -1.308833
[,51] [,52] [,53] [,54] [,55] [,56] [,57]
[1,] 0.3659186 0.2277302 -1.615077 0.7385244 -0.7658152 -0.8715128 0.3217054
[2,] 0.3659186 0.2277302 -1.615077 0.7385244 -0.7658152 -0.8715128 0.3217054
[,58] [,59] [,60] [,61] [,62] [,63] [,64]
[1,] -0.4770065 -0.4205404 -1.827807 0.4022946 1.082681 -0.8072543 -0.007891242
[2,] -0.4770065 -0.4205404 -1.827807 0.4022946 1.082681 -0.8072543 -0.007891242
[,65] [,66] [,67] [,68] [,69] [,70] [,71]
[1,] -0.6075831 1.665191 -0.945082 -0.8607599 -0.7402048 -0.06941292 -0.4961572
[2,] -0.6075831 1.665191 -0.945082 -0.8607599 -0.7402048 -0.06941292 -0.4961572
[,72] [,73] [,74] [,75] [,76] [,77] [,78]
[1,] -0.5070745 -1.941813 -1.134877 0.9086328 0.5491957 1.995771 1.190328
[2,] -0.5070745 -1.941813 -1.134877 0.9086328 0.5491957 1.995771 1.190328
[,79] [,80] [,81] [,82] [,83] [,84] [,85]
[1,] -1.476017 0.2654875 0.3176517 0.06688487 0.9823172 0.8641958 0.4059421
[2,] -1.476017 0.2654875 0.3176517 0.06688487 0.9823172 0.8641958 0.4059421
[,86] [,87] [,88] [,89] [,90] [,91] [,92]
[1,] -0.7134223 2.102619 -1.205219 -1.363996 -1.368144 0.009630704 -0.815122
[2,] -0.7134223 2.102619 -1.205219 -1.363996 -1.368144 0.009630704 -0.815122
[,93] [,94] [,95] [,96] [,97] [,98] [,99]
[1,] -0.05941569 2.286025 0.3121646 -1.342967 -0.7946356 2.404425 1.300084
[2,] -0.05941569 2.286025 0.3121646 -1.342967 -0.7946356 2.404425 1.300084
[,100]
[1,] 0.6708321
[2,] 0.6708321
>
>
> Max(tmp2)
[1] 2.549555
> Min(tmp2)
[1] -1.733014
> mean(tmp2)
[1] 0.2461939
> Sum(tmp2)
[1] 24.61939
> Var(tmp2)
[1] 0.835793
>
> rowMeans(tmp2)
[1] 0.436685665 1.252622478 -1.470252635 0.763331233 -1.263480833
[6] -0.445537654 0.347347881 0.543594137 -0.214807010 -0.169028580
[11] 0.293041396 0.776161786 1.388408340 2.247274880 -0.648041320
[16] 0.054442428 0.239734906 -0.579682247 -0.640643283 2.066193598
[21] 1.292511212 1.381141188 0.857263087 -0.716172255 1.191438345
[26] 0.035225245 0.124498436 0.158607111 -1.008376370 1.871047028
[31] -0.285552496 1.244601292 0.212690369 -1.121641772 0.614635330
[36] 0.613659702 0.128836069 0.789879622 0.408614554 1.332311312
[41] -0.737361222 -0.145340598 1.125065632 0.971283753 -1.073413947
[46] 0.913690346 -1.509809285 -1.733014084 0.011760828 0.251501200
[51] 2.317410820 1.073465124 1.334818120 0.132024405 0.001401135
[56] 0.190837347 -0.760865344 -0.613107104 0.779242235 -1.012846284
[61] -0.333543419 -0.309990826 -0.854453714 0.693548767 -0.557175922
[66] 0.306594727 -0.083564604 0.644717212 -1.330695065 1.532875252
[71] -1.245716234 -0.096850350 1.055049878 -0.289870576 -0.574372674
[76] 0.296160905 0.929269327 -0.627118190 -0.649917790 0.443003490
[81] 0.966147503 0.545065077 0.662291071 1.123214806 -0.374068122
[86] 1.754675280 0.070057279 0.665005654 -0.983895784 2.549555395
[91] -0.013517931 0.507569945 -0.745705261 -0.057853121 -0.361900359
[96] 1.162452546 -0.288771378 0.810336226 0.835067069 1.226393009
> rowSums(tmp2)
[1] 0.436685665 1.252622478 -1.470252635 0.763331233 -1.263480833
[6] -0.445537654 0.347347881 0.543594137 -0.214807010 -0.169028580
[11] 0.293041396 0.776161786 1.388408340 2.247274880 -0.648041320
[16] 0.054442428 0.239734906 -0.579682247 -0.640643283 2.066193598
[21] 1.292511212 1.381141188 0.857263087 -0.716172255 1.191438345
[26] 0.035225245 0.124498436 0.158607111 -1.008376370 1.871047028
[31] -0.285552496 1.244601292 0.212690369 -1.121641772 0.614635330
[36] 0.613659702 0.128836069 0.789879622 0.408614554 1.332311312
[41] -0.737361222 -0.145340598 1.125065632 0.971283753 -1.073413947
[46] 0.913690346 -1.509809285 -1.733014084 0.011760828 0.251501200
[51] 2.317410820 1.073465124 1.334818120 0.132024405 0.001401135
[56] 0.190837347 -0.760865344 -0.613107104 0.779242235 -1.012846284
[61] -0.333543419 -0.309990826 -0.854453714 0.693548767 -0.557175922
[66] 0.306594727 -0.083564604 0.644717212 -1.330695065 1.532875252
[71] -1.245716234 -0.096850350 1.055049878 -0.289870576 -0.574372674
[76] 0.296160905 0.929269327 -0.627118190 -0.649917790 0.443003490
[81] 0.966147503 0.545065077 0.662291071 1.123214806 -0.374068122
[86] 1.754675280 0.070057279 0.665005654 -0.983895784 2.549555395
[91] -0.013517931 0.507569945 -0.745705261 -0.057853121 -0.361900359
[96] 1.162452546 -0.288771378 0.810336226 0.835067069 1.226393009
> 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] 0.436685665 1.252622478 -1.470252635 0.763331233 -1.263480833
[6] -0.445537654 0.347347881 0.543594137 -0.214807010 -0.169028580
[11] 0.293041396 0.776161786 1.388408340 2.247274880 -0.648041320
[16] 0.054442428 0.239734906 -0.579682247 -0.640643283 2.066193598
[21] 1.292511212 1.381141188 0.857263087 -0.716172255 1.191438345
[26] 0.035225245 0.124498436 0.158607111 -1.008376370 1.871047028
[31] -0.285552496 1.244601292 0.212690369 -1.121641772 0.614635330
[36] 0.613659702 0.128836069 0.789879622 0.408614554 1.332311312
[41] -0.737361222 -0.145340598 1.125065632 0.971283753 -1.073413947
[46] 0.913690346 -1.509809285 -1.733014084 0.011760828 0.251501200
[51] 2.317410820 1.073465124 1.334818120 0.132024405 0.001401135
[56] 0.190837347 -0.760865344 -0.613107104 0.779242235 -1.012846284
[61] -0.333543419 -0.309990826 -0.854453714 0.693548767 -0.557175922
[66] 0.306594727 -0.083564604 0.644717212 -1.330695065 1.532875252
[71] -1.245716234 -0.096850350 1.055049878 -0.289870576 -0.574372674
[76] 0.296160905 0.929269327 -0.627118190 -0.649917790 0.443003490
[81] 0.966147503 0.545065077 0.662291071 1.123214806 -0.374068122
[86] 1.754675280 0.070057279 0.665005654 -0.983895784 2.549555395
[91] -0.013517931 0.507569945 -0.745705261 -0.057853121 -0.361900359
[96] 1.162452546 -0.288771378 0.810336226 0.835067069 1.226393009
> rowMin(tmp2)
[1] 0.436685665 1.252622478 -1.470252635 0.763331233 -1.263480833
[6] -0.445537654 0.347347881 0.543594137 -0.214807010 -0.169028580
[11] 0.293041396 0.776161786 1.388408340 2.247274880 -0.648041320
[16] 0.054442428 0.239734906 -0.579682247 -0.640643283 2.066193598
[21] 1.292511212 1.381141188 0.857263087 -0.716172255 1.191438345
[26] 0.035225245 0.124498436 0.158607111 -1.008376370 1.871047028
[31] -0.285552496 1.244601292 0.212690369 -1.121641772 0.614635330
[36] 0.613659702 0.128836069 0.789879622 0.408614554 1.332311312
[41] -0.737361222 -0.145340598 1.125065632 0.971283753 -1.073413947
[46] 0.913690346 -1.509809285 -1.733014084 0.011760828 0.251501200
[51] 2.317410820 1.073465124 1.334818120 0.132024405 0.001401135
[56] 0.190837347 -0.760865344 -0.613107104 0.779242235 -1.012846284
[61] -0.333543419 -0.309990826 -0.854453714 0.693548767 -0.557175922
[66] 0.306594727 -0.083564604 0.644717212 -1.330695065 1.532875252
[71] -1.245716234 -0.096850350 1.055049878 -0.289870576 -0.574372674
[76] 0.296160905 0.929269327 -0.627118190 -0.649917790 0.443003490
[81] 0.966147503 0.545065077 0.662291071 1.123214806 -0.374068122
[86] 1.754675280 0.070057279 0.665005654 -0.983895784 2.549555395
[91] -0.013517931 0.507569945 -0.745705261 -0.057853121 -0.361900359
[96] 1.162452546 -0.288771378 0.810336226 0.835067069 1.226393009
>
> colMeans(tmp2)
[1] 0.2461939
> colSums(tmp2)
[1] 24.61939
> colVars(tmp2)
[1] 0.835793
> colSd(tmp2)
[1] 0.9142172
> colMax(tmp2)
[1] 2.549555
> colMin(tmp2)
[1] -1.733014
> colMedians(tmp2)
[1] 0.2262126
> colRanges(tmp2)
[,1]
[1,] -1.733014
[2,] 2.549555
>
> 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] -1.3702167 -3.0662662 -0.2883026 0.4188834 -0.7566329 7.3921867
[7] -5.3221025 3.4675810 4.0019453 2.1231034
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8463179
[2,] -0.7148769
[3,] -0.0254258
[4,] 0.5180747
[5,] 1.2288387
>
> rowApply(tmp,sum)
[1] 2.3707412 2.6115091 3.0772818 1.7885163 4.4524407 2.0456368
[7] -6.6666552 -0.3141839 -3.8723492 1.1072414
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 5 6 3 6 1 5 8 1 4
[2,] 7 2 1 5 4 5 3 5 3 5
[3,] 3 8 2 2 10 7 10 3 6 1
[4,] 5 3 8 10 7 9 1 9 5 2
[5,] 10 4 10 1 1 4 9 2 2 7
[6,] 8 10 9 4 5 8 6 7 9 8
[7,] 6 1 5 9 2 2 2 6 4 3
[8,] 2 6 7 6 8 3 4 4 10 9
[9,] 4 7 3 7 3 6 7 10 7 10
[10,] 1 9 4 8 9 10 8 1 8 6
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.1753930 -1.9116103 -3.8067052 0.6848522 2.0786863 1.7858159
[7] 3.3947282 -1.4035953 1.6775430 0.3489042 1.6261863 -1.7681317
[13] 2.9885029 2.3561632 4.7594417 3.2773627 -1.1236465 1.5847080
[19] -2.7185386 -0.3472857
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.4706567
[2,] -0.5756225
[3,] -0.2322623
[4,] 0.8441378
[5,] 1.2590108
>
> rowApply(tmp,sum)
[1] 12.288057 -1.987458 4.184630 -3.681415 2.504175
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 16 19 5 2 5
[2,] 3 5 6 4 12
[3,] 5 3 2 14 1
[4,] 17 4 9 13 9
[5,] 2 17 15 19 17
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.2590108 -0.5321077 0.1178291 1.28467718 -1.6700913 0.34525837
[2,] 0.8441378 -0.5724843 -0.7661748 -0.70767905 0.6266080 -0.09747284
[3,] -0.2322623 -0.1213554 -1.9393844 0.09601574 0.7850219 1.40785145
[4,] -1.4706567 -1.0786277 0.3268520 0.06698240 1.1386386 1.48492660
[5,] -0.5756225 0.3929649 -1.5458271 -0.05514412 1.1985091 -1.35474769
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.08288264 1.1481090 1.1828022 0.60156610 -0.20357309 0.1755095
[2,] 0.03937482 -2.3867425 -0.3996348 -1.46186945 -0.04189886 -0.4298102
[3,] 0.05283432 0.2449113 0.3872340 0.09569219 0.82332336 0.5034109
[4,] 0.75341616 0.8371279 -0.7152591 0.53095445 -0.31394395 -1.7739236
[5,] 1.46622028 -1.2470010 1.2224008 0.58256095 1.36227884 -0.2433184
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.9611037 2.0091834 2.7353309 0.3324520 0.74150243 1.2125790
[2,] 0.1044870 0.6672241 0.2394873 2.7709189 0.27427077 0.2279592
[3,] 1.0135795 2.1816844 0.2514498 1.4533629 -1.96342380 0.5148537
[4,] -0.6586064 -1.4207168 0.5797447 -1.0471882 -0.02964154 -0.7282865
[5,] 0.5679390 -1.0812118 0.9534289 -0.2321829 -0.14635436 0.3576026
[,19] [,20]
[1,] -2.05508245 0.55911504
[2,] -0.46620934 -0.45195016
[3,] -0.32742788 -1.04274192
[4,] -0.07950106 -0.08370586
[5,] 0.20968219 0.67199725
>
>
> 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 : 649 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 0.3156844 -0.1350859 -0.9070864 0.9245621 -0.09470027 0.04632339 1.921389
col8 col9 col10 col11 col12 col13 col14
row1 -0.6682362 -0.3032509 0.7971933 0.06062368 -1.354081 1.311621 0.8379505
col15 col16 col17 col18 col19 col20
row1 -1.208254 1.668947 1.631698 0.1766428 -0.5741731 0.2302509
> tmp[,"col10"]
col10
row1 0.7971933
row2 0.2889093
row3 1.0736637
row4 1.9192013
row5 1.2298183
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.3156844 -0.1350859 -0.9070864 0.9245621 -0.09470027 0.04632339
row5 0.7461059 -0.9644909 -1.8837545 0.2975828 0.63581873 -1.51331220
col7 col8 col9 col10 col11 col12 col13
row1 1.9213894 -0.6682362 -0.3032509 0.7971933 0.06062368 -1.354081 1.3116209
row5 0.6452198 -0.8361654 0.5006765 1.2298183 0.54147864 -1.966684 0.5371805
col14 col15 col16 col17 col18 col19 col20
row1 0.8379505 -1.2082540 1.668947 1.631698 0.17664277 -0.5741731 0.2302509
row5 0.5433819 -0.7485104 -0.194977 1.966726 -0.06354905 -1.0193192 2.3929274
> tmp[,c("col6","col20")]
col6 col20
row1 0.04632339 0.2302509
row2 -0.87899601 -1.1542572
row3 1.56397886 -0.1101494
row4 0.08469368 0.1972253
row5 -1.51331220 2.3929274
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.04632339 0.2302509
row5 -1.51331220 2.3929274
>
>
>
>
> 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 50.82284 49.62417 50.73611 49.71264 50.05302 106.5835 47.73029 52.14077
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.10001 48.54838 50.56556 51.38064 51.02991 49.81249 50.05098 49.02911
col17 col18 col19 col20
row1 49.86146 49.21891 50.25462 103.9567
> tmp[,"col10"]
col10
row1 48.54838
row2 28.76100
row3 30.55237
row4 30.51079
row5 51.00371
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.82284 49.62417 50.73611 49.71264 50.05302 106.5835 47.73029 52.14077
row5 50.69431 49.39258 50.68115 50.08407 49.37245 103.8140 51.08146 49.28454
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.10001 48.54838 50.56556 51.38064 51.02991 49.81249 50.05098 49.02911
row5 48.88768 51.00371 47.72124 48.82106 48.90169 51.52910 50.19867 50.03629
col17 col18 col19 col20
row1 49.86146 49.21891 50.25462 103.9567
row5 51.98078 48.52536 49.53997 106.0313
> tmp[,c("col6","col20")]
col6 col20
row1 106.58348 103.95672
row2 74.63809 74.47145
row3 73.77573 76.46019
row4 75.80323 74.42722
row5 103.81400 106.03127
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.5835 103.9567
row5 103.8140 106.0313
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.5835 103.9567
row5 103.8140 106.0313
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.2599470
[2,] 0.7048766
[3,] 0.5704328
[4,] -1.2076764
[5,] 0.3989543
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.15409001 -0.10656531
[2,] 0.03613332 0.04226192
[3,] 0.13183867 -0.38000161
[4,] 0.63588395 -0.73787541
[5,] 0.50820800 0.15133505
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.3281909 1.2968825
[2,] 0.4283609 1.1700884
[3,] -1.0563534 -1.4825168
[4,] -0.6502708 0.1809459
[5,] -0.4301900 -0.7571735
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.328191
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.3281909
[2,] 0.4283609
>
>
>
> 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 0.4698016 0.3926394 -0.3749630 -0.6774789 -0.1818508 -1.8379016 1.3712295
row1 -2.9402950 0.6351069 -0.9760078 1.5514045 2.2749720 0.6151058 0.2258485
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.6316924 0.6532430 0.1498284 -0.7601041 -0.7501855 0.7620686 -0.5621490
row1 0.4964715 -0.4801292 -1.1000738 0.2178844 0.2390507 1.0978503 -0.1368206
[,15] [,16] [,17] [,18] [,19] [,20]
row3 1.1440133 0.06110319 -0.14153369 -0.3721972 0.3608477 0.52124011
row1 -0.7247986 -0.07397470 -0.02944779 -0.4846055 0.5369096 0.05321335
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.257702 -0.1124005 -0.7740254 1.008057 -1.478709 0.2169304 -0.2040497
[,8] [,9] [,10]
row2 1.341997 0.5008331 -1.261974
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.4489534 2.434611 1.400822 -0.08274955 0.9360344 -1.161355 -1.809969
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.0654 -1.598234 0.470049 -2.201122 -1.195823 -0.767715 -0.3983421
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.4583561 2.035152 -0.1969673 0.7268614 -1.627633 -1.533671
>
>
> 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: 0x600002c700c0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMbb53650d1aaf"
[2] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMbb533f530afd"
[3] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMbb5364f68885"
[4] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMbb53757d078b"
[5] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMbb53637a72ef"
[6] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMbb537c0fdbee"
[7] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMbb53753025e3"
[8] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMbb532c079630"
[9] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMbb5326153fe5"
[10] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMbb533d15e6eb"
[11] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMbb5368eb6da1"
[12] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMbb53386a9ad7"
[13] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMbb535edbb630"
[14] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMbb532a9639f7"
[15] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMbb536cb79cf8"
>
>
> ### 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: 0x600002c34060>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600002c34060>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600002c34060>
> rowMedians(tmp)
[1] 0.120727121 0.469381455 0.111095363 0.182059899 -0.600605625
[6] 0.090239735 0.361217889 -0.452812447 -0.205428327 0.325419811
[11] -0.428226998 0.012617986 0.106724323 0.019910070 0.125223482
[16] -0.386083653 -0.430863262 0.264796231 -0.026626847 0.017329615
[21] 0.460984276 -0.009834660 -0.122313409 -0.214423188 -0.042298665
[26] -0.354514091 0.113630648 -0.189376852 -0.203551951 -0.119640138
[31] 0.381668586 0.349380823 0.444469330 -0.027817610 -0.354256006
[36] -0.217086489 0.102374320 -0.008517743 -0.130589348 0.031232592
[41] 0.132308270 -0.925399462 0.319226711 -0.054589399 0.101158217
[46] -0.229538655 -0.158851520 -0.123172794 0.611024285 -0.086148489
[51] -0.081660756 -0.286947743 0.571575775 -0.157816251 0.179504056
[56] 0.178696503 0.421437288 0.375550480 -0.098164185 -0.602039570
[61] -0.115015879 0.027793955 -0.204617508 -0.459615127 0.274663180
[66] -0.019570124 0.356436032 -1.006680430 -0.272946269 0.020055604
[71] 0.242579817 -0.123165339 0.308105586 -0.029828341 -0.396186431
[76] -0.453571979 0.026032353 -0.168447072 -0.082342328 -0.066125304
[81] -0.659215472 0.011283565 -0.067008004 -0.460140337 0.475053092
[86] 0.458587657 0.031175609 0.499842106 0.549065687 -0.269476900
[91] -0.058712470 0.010747543 0.015729705 0.450392904 -0.020061826
[96] -0.252002069 0.376755021 0.066968496 -0.346871395 -0.041510497
[101] -0.104508276 0.420049532 0.529434713 0.094190577 0.435126458
[106] -0.185835659 0.070170846 0.171080209 0.623863372 -0.060174191
[111] -0.547746290 -0.194092521 0.541697531 0.066586033 -0.276507793
[116] 0.205509360 0.911071197 0.323185438 -0.479571644 -0.383519155
[121] -0.170975164 -0.019369350 0.737206175 0.251406848 -0.086919686
[126] -0.599494499 0.142064466 -0.395026813 0.150516880 -0.162222514
[131] 0.458624480 -0.116085452 0.282593869 0.210974031 0.012237487
[136] -0.016360064 -0.292631011 -0.003491023 0.396051416 0.704876696
[141] -0.432484187 -0.505908368 -0.315912187 0.467929006 0.037494603
[146] 0.304833497 0.590506612 0.457274520 -0.381650900 0.559145347
[151] -0.334624286 0.088018864 0.045808857 0.605298873 -0.118826364
[156] 0.210863614 0.058352403 0.524603332 -0.148161684 0.020257432
[161] -0.020624944 -0.238599002 0.819999679 0.260634131 0.399672456
[166] -0.317903151 0.457468377 0.034665930 0.248110264 0.394172514
[171] 0.184715839 0.046536497 0.002027884 0.376774292 0.443447484
[176] 0.086378127 0.366031494 0.529954142 0.260058043 -0.028380003
[181] 0.002958350 0.012281587 -0.298468876 -0.377398585 -0.295038491
[186] -0.114950628 -0.101898067 0.326036830 0.381476769 0.102853752
[191] 0.207626373 0.194543976 0.024279430 0.142230535 -0.171756985
[196] -0.142310649 -0.142358376 -0.006047434 0.023223143 -0.107053576
[201] -0.196650828 0.328525297 -0.062730577 0.371255072 0.646712749
[206] 0.152976132 0.405801990 -0.106744944 0.079656497 0.132877450
[211] -0.037229331 0.039591894 0.290757374 -0.196999366 -0.118832232
[216] -0.177101599 -0.202951974 -0.242610339 -0.053155197 -0.380237386
[221] -0.380510060 -0.138318482 0.386462635 -0.179371599 0.214319596
[226] -0.004248100 -0.603449363 -0.310040160 0.851830645 0.059798441
>
> proc.time()
user system elapsed
5.066 18.949 30.842
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.1 RC (2025-06-05 r88288) -- "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: 0x6000018e8060>
> .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: 0x6000018e8060>
> .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: 0x6000018e8060>
> .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: 0x6000018e8060>
> 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: 0x6000018cc000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018cc000>
> .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: 0x6000018cc000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018cc000>
> .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: 0x6000018cc000>
> 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: 0x6000018cc180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018cc180>
> .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: 0x6000018cc180>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000018cc180>
> .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: 0x6000018cc180>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000018cc180>
> .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: 0x6000018cc180>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000018cc180>
> .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: 0x6000018cc180>
> 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: 0x6000018cc360>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000018cc360>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018cc360>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018cc360>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilec2f632ac450c" "BufferedMatrixFilec2f64a3e1848"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilec2f632ac450c" "BufferedMatrixFilec2f64a3e1848"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018a4000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018a4000>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000018a4000>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000018a4000>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000018a4000>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000018a4000>
> .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: 0x6000018cc6c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018cc6c0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000018cc6c0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000018cc6c0>
> 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: 0x6000018cc8a0>
> .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: 0x6000018cc8a0>
> rm(P)
>
> proc.time()
user system elapsed
0.591 0.218 0.789
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.1 RC (2025-06-05 r88288) -- "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
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.584 0.137 0.712