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 11:40 -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 14:49:57 -0400 (Tue, 14 Oct 2025) |
| EndedAt: 2025-10-14 14:50:39 -0400 (Tue, 14 Oct 2025) |
| EllapsedTime: 42.3 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
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###
### 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
0.333 0.120 0.444
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] "Tue Oct 14 14:50:18 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 14:50:18 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: 0x600001ed40c0>
>
>
>
> 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 14:50:20 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 14:50:22 2025"
>
> ColMode(tmp2)
<pointer: 0x600001ed40c0>
>
>
>
> ### 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,] 101.5535683 -0.4324129 1.0710464 0.3290371
[2,] 0.3819205 0.1132789 0.1048957 0.5106765
[3,] -1.8526619 -0.7171068 -1.0721561 0.7058684
[4,] 0.1696426 0.0982392 -1.0842639 -0.9735733
> 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,] 101.5535683 0.4324129 1.0710464 0.3290371
[2,] 0.3819205 0.1132789 0.1048957 0.5106765
[3,] 1.8526619 0.7171068 1.0721561 0.7058684
[4,] 0.1696426 0.0982392 1.0842639 0.9735733
> 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,] 10.0773790 0.6575811 1.034914 0.5736175
[2,] 0.6179971 0.3365694 0.323876 0.7146163
[3,] 1.3611252 0.8468216 1.035450 0.8401598
[4,] 0.4118770 0.3134313 1.041280 0.9866982
>
> 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,] 227.32736 32.00822 36.42018 31.06521
[2,] 31.56189 28.47897 28.34366 32.65684
[3,] 40.46391 34.18532 36.42665 34.10747
[4,] 29.28841 28.23255 36.49706 35.84056
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600001ed4120>
> exp(tmp5)
<pointer: 0x600001ed4120>
> log(tmp5,2)
<pointer: 0x600001ed4120>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 473.1521
> Min(tmp5)
[1] 53.70329
> mean(tmp5)
[1] 72.88979
> Sum(tmp5)
[1] 14577.96
> Var(tmp5)
[1] 881.4214
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.79999 66.99191 70.03777 71.07878 73.27992 69.76225 72.67027 70.36367
[9] 70.00931 72.90406
> rowSums(tmp5)
[1] 1836.000 1339.838 1400.755 1421.576 1465.598 1395.245 1453.405 1407.273
[9] 1400.186 1458.081
> rowVars(tmp5)
[1] 8112.57294 52.73185 69.32331 76.11831 66.69660 79.82208
[7] 71.64658 88.98269 76.54141 86.28874
> rowSd(tmp5)
[1] 90.069823 7.261670 8.326062 8.724581 8.166799 8.934320 8.464430
[8] 9.433063 8.748795 9.289173
> rowMax(tmp5)
[1] 473.15211 82.01308 84.22034 89.62243 88.49012 85.15400 86.55751
[8] 87.79513 86.38525 86.23733
> rowMin(tmp5)
[1] 60.27907 57.37854 56.12044 56.55023 57.47202 53.70329 58.75234 54.56356
[9] 58.62232 54.54624
>
> colMeans(tmp5)
[1] 113.54601 68.96794 75.81742 71.27456 72.12334 69.26533 72.21713
[8] 71.50865 75.07004 65.10194 75.51035 67.84206 75.56837 69.99112
[15] 64.73192 66.44715 67.34253 70.52583 67.02821 77.91596
> colSums(tmp5)
[1] 1135.4601 689.6794 758.1742 712.7456 721.2334 692.6533 722.1713
[8] 715.0865 750.7004 651.0194 755.1035 678.4206 755.6837 699.9112
[15] 647.3192 664.4715 673.4253 705.2583 670.2821 779.1596
> colVars(tmp5)
[1] 16052.88114 95.05548 66.48557 100.58381 38.80751 37.46109
[7] 46.18376 49.51487 52.95439 27.30405 102.04078 59.73204
[13] 53.70915 75.48845 93.96381 43.47184 114.88739 41.59556
[19] 72.86358 27.62175
> colSd(tmp5)
[1] 126.699965 9.749640 8.153869 10.029148 6.229567 6.120547
[7] 6.795864 7.036680 7.276976 5.225327 10.101524 7.728651
[13] 7.328653 8.688409 9.693493 6.593318 10.718553 6.449462
[19] 8.536016 5.255639
> colMax(tmp5)
[1] 473.15211 84.57255 88.49012 86.09218 80.77133 77.55035 80.22206
[8] 83.52144 86.55751 72.41289 88.79683 78.72047 89.62243 83.62227
[15] 83.43797 75.75292 86.38525 82.07028 85.10526 87.15014
> colMin(tmp5)
[1] 60.95999 58.76236 58.99361 54.54624 58.80133 58.75234 59.57761 57.60038
[9] 63.93837 57.47202 60.07157 59.31577 65.44153 54.56356 54.71661 54.78341
[17] 53.70329 60.14787 58.98912 67.40724
>
>
> ### 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] 91.79999 NA 70.03777 71.07878 73.27992 69.76225 72.67027 70.36367
[9] 70.00931 72.90406
> rowSums(tmp5)
[1] 1836.000 NA 1400.755 1421.576 1465.598 1395.245 1453.405 1407.273
[9] 1400.186 1458.081
> rowVars(tmp5)
[1] 8112.57294 52.17913 69.32331 76.11831 66.69660 79.82208
[7] 71.64658 88.98269 76.54141 86.28874
> rowSd(tmp5)
[1] 90.069823 7.223512 8.326062 8.724581 8.166799 8.934320 8.464430
[8] 9.433063 8.748795 9.289173
> rowMax(tmp5)
[1] 473.15211 NA 84.22034 89.62243 88.49012 85.15400 86.55751
[8] 87.79513 86.38525 86.23733
> rowMin(tmp5)
[1] 60.27907 NA 56.12044 56.55023 57.47202 53.70329 58.75234 54.56356
[9] 58.62232 54.54624
>
> colMeans(tmp5)
[1] 113.54601 NA 75.81742 71.27456 72.12334 69.26533 72.21713
[8] 71.50865 75.07004 65.10194 75.51035 67.84206 75.56837 69.99112
[15] 64.73192 66.44715 67.34253 70.52583 67.02821 77.91596
> colSums(tmp5)
[1] 1135.4601 NA 758.1742 712.7456 721.2334 692.6533 722.1713
[8] 715.0865 750.7004 651.0194 755.1035 678.4206 755.6837 699.9112
[15] 647.3192 664.4715 673.4253 705.2583 670.2821 779.1596
> colVars(tmp5)
[1] 16052.88114 NA 66.48557 100.58381 38.80751 37.46109
[7] 46.18376 49.51487 52.95439 27.30405 102.04078 59.73204
[13] 53.70915 75.48845 93.96381 43.47184 114.88739 41.59556
[19] 72.86358 27.62175
> colSd(tmp5)
[1] 126.699965 NA 8.153869 10.029148 6.229567 6.120547
[7] 6.795864 7.036680 7.276976 5.225327 10.101524 7.728651
[13] 7.328653 8.688409 9.693493 6.593318 10.718553 6.449462
[19] 8.536016 5.255639
> colMax(tmp5)
[1] 473.15211 NA 88.49012 86.09218 80.77133 77.55035 80.22206
[8] 83.52144 86.55751 72.41289 88.79683 78.72047 89.62243 83.62227
[15] 83.43797 75.75292 86.38525 82.07028 85.10526 87.15014
> colMin(tmp5)
[1] 60.95999 NA 58.99361 54.54624 58.80133 58.75234 59.57761 57.60038
[9] 63.93837 57.47202 60.07157 59.31577 65.44153 54.56356 54.71661 54.78341
[17] 53.70329 60.14787 58.98912 67.40724
>
> Max(tmp5,na.rm=TRUE)
[1] 473.1521
> Min(tmp5,na.rm=TRUE)
[1] 53.70329
> mean(tmp5,na.rm=TRUE)
[1] 72.95821
> Sum(tmp5,na.rm=TRUE)
[1] 14518.68
> Var(tmp5,na.rm=TRUE)
[1] 884.9322
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.79999 67.39805 70.03777 71.07878 73.27992 69.76225 72.67027 70.36367
[9] 70.00931 72.90406
> rowSums(tmp5,na.rm=TRUE)
[1] 1836.000 1280.563 1400.755 1421.576 1465.598 1395.245 1453.405 1407.273
[9] 1400.186 1458.081
> rowVars(tmp5,na.rm=TRUE)
[1] 8112.57294 52.17913 69.32331 76.11831 66.69660 79.82208
[7] 71.64658 88.98269 76.54141 86.28874
> rowSd(tmp5,na.rm=TRUE)
[1] 90.069823 7.223512 8.326062 8.724581 8.166799 8.934320 8.464430
[8] 9.433063 8.748795 9.289173
> rowMax(tmp5,na.rm=TRUE)
[1] 473.15211 82.01308 84.22034 89.62243 88.49012 85.15400 86.55751
[8] 87.79513 86.38525 86.23733
> rowMin(tmp5,na.rm=TRUE)
[1] 60.27907 57.37854 56.12044 56.55023 57.47202 53.70329 58.75234 54.56356
[9] 58.62232 54.54624
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.54601 70.04490 75.81742 71.27456 72.12334 69.26533 72.21713
[8] 71.50865 75.07004 65.10194 75.51035 67.84206 75.56837 69.99112
[15] 64.73192 66.44715 67.34253 70.52583 67.02821 77.91596
> colSums(tmp5,na.rm=TRUE)
[1] 1135.4601 630.4041 758.1742 712.7456 721.2334 692.6533 722.1713
[8] 715.0865 750.7004 651.0194 755.1035 678.4206 755.6837 699.9112
[15] 647.3192 664.4715 673.4253 705.2583 670.2821 779.1596
> colVars(tmp5,na.rm=TRUE)
[1] 16052.88114 93.88906 66.48557 100.58381 38.80751 37.46109
[7] 46.18376 49.51487 52.95439 27.30405 102.04078 59.73204
[13] 53.70915 75.48845 93.96381 43.47184 114.88739 41.59556
[19] 72.86358 27.62175
> colSd(tmp5,na.rm=TRUE)
[1] 126.699965 9.689637 8.153869 10.029148 6.229567 6.120547
[7] 6.795864 7.036680 7.276976 5.225327 10.101524 7.728651
[13] 7.328653 8.688409 9.693493 6.593318 10.718553 6.449462
[19] 8.536016 5.255639
> colMax(tmp5,na.rm=TRUE)
[1] 473.15211 84.57255 88.49012 86.09218 80.77133 77.55035 80.22206
[8] 83.52144 86.55751 72.41289 88.79683 78.72047 89.62243 83.62227
[15] 83.43797 75.75292 86.38525 82.07028 85.10526 87.15014
> colMin(tmp5,na.rm=TRUE)
[1] 60.95999 58.76236 58.99361 54.54624 58.80133 58.75234 59.57761 57.60038
[9] 63.93837 57.47202 60.07157 59.31577 65.44153 54.56356 54.71661 54.78341
[17] 53.70329 60.14787 58.98912 67.40724
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.79999 NaN 70.03777 71.07878 73.27992 69.76225 72.67027 70.36367
[9] 70.00931 72.90406
> rowSums(tmp5,na.rm=TRUE)
[1] 1836.000 0.000 1400.755 1421.576 1465.598 1395.245 1453.405 1407.273
[9] 1400.186 1458.081
> rowVars(tmp5,na.rm=TRUE)
[1] 8112.57294 NA 69.32331 76.11831 66.69660 79.82208
[7] 71.64658 88.98269 76.54141 86.28874
> rowSd(tmp5,na.rm=TRUE)
[1] 90.069823 NA 8.326062 8.724581 8.166799 8.934320 8.464430
[8] 9.433063 8.748795 9.289173
> rowMax(tmp5,na.rm=TRUE)
[1] 473.15211 NA 84.22034 89.62243 88.49012 85.15400 86.55751
[8] 87.79513 86.38525 86.23733
> rowMin(tmp5,na.rm=TRUE)
[1] 60.27907 NA 56.12044 56.55023 57.47202 53.70329 58.75234 54.56356
[9] 58.62232 54.54624
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 118.86313 NaN 77.68674 71.64163 72.48366 68.34477 72.12516
[8] 71.69228 74.29859 65.38697 77.22577 68.78942 76.18606 71.39252
[15] 65.53938 65.83427 67.39404 70.19076 67.61935 78.16288
> colSums(tmp5,na.rm=TRUE)
[1] 1069.7682 0.0000 699.1806 644.7747 652.3530 615.1030 649.1264
[8] 645.2305 668.6873 588.4827 695.0319 619.1048 685.6745 642.5327
[15] 589.8544 592.5085 606.5463 631.7168 608.5741 703.4659
> colVars(tmp5,na.rm=TRUE)
[1] 17741.43405 NA 35.48505 111.64096 42.19781 32.61018
[7] 51.86156 55.32489 52.87843 29.80312 81.69089 57.10166
[13] 56.13056 62.83046 98.37434 44.68007 129.21847 45.53197
[19] 78.04032 30.38855
> colSd(tmp5,na.rm=TRUE)
[1] 133.196975 NA 5.956933 10.566028 6.495984 5.710532
[7] 7.201497 7.438070 7.271756 5.459223 9.038301 7.556564
[13] 7.492033 7.926567 9.918384 6.684315 11.367430 6.747738
[19] 8.834043 5.512581
> colMax(tmp5,na.rm=TRUE)
[1] 473.15211 -Inf 88.49012 86.09218 80.77133 77.36717 80.22206
[8] 83.52144 86.55751 72.41289 88.79683 78.72047 89.62243 83.62227
[15] 83.43797 75.75292 86.38525 82.07028 85.10526 87.15014
> colMin(tmp5,na.rm=TRUE)
[1] 60.95999 Inf 70.11277 54.54624 58.80133 58.75234 59.57761 57.60038
[9] 63.93837 57.47202 62.33294 59.91073 65.44153 54.56356 54.71661 54.78341
[17] 53.70329 60.14787 58.98912 67.40724
>
>
>
>
> 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] 169.0629 368.7909 168.2467 297.7577 191.6308 252.1409 177.8394 208.4706
[9] 546.4352 130.1898
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 169.0629 368.7909 168.2467 297.7577 191.6308 252.1409 177.8394 208.4706
[9] 546.4352 130.1898
>
>
>
> 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] -1.421085e-14 2.842171e-14 -1.705303e-13 5.684342e-14 -5.684342e-14
[6] 0.000000e+00 -5.684342e-14 -5.684342e-14 5.684342e-14 5.684342e-14
[11] -1.136868e-13 2.273737e-13 -1.421085e-13 0.000000e+00 -8.526513e-14
[16] -5.684342e-14 5.684342e-14 1.136868e-13 -5.684342e-14 5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
9 7
8 2
10 1
3 18
7 3
9 7
5 4
10 17
5 3
5 2
6 10
4 17
9 1
4 6
2 2
9 11
4 7
1 19
5 18
6 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] 2.885789
> Min(tmp)
[1] -2.328091
> mean(tmp)
[1] 0.0005641685
> Sum(tmp)
[1] 0.05641685
> Var(tmp)
[1] 1.162447
>
> rowMeans(tmp)
[1] 0.0005641685
> rowSums(tmp)
[1] 0.05641685
> rowVars(tmp)
[1] 1.162447
> rowSd(tmp)
[1] 1.078168
> rowMax(tmp)
[1] 2.885789
> rowMin(tmp)
[1] -2.328091
>
> colMeans(tmp)
[1] -0.926636307 2.885788603 -0.971502850 2.004953482 1.002976079
[6] 1.138138283 1.610571868 -0.590928040 1.913694898 0.298646626
[11] 0.633872506 -0.500760880 -0.860835949 0.408982587 -0.212505177
[16] -0.153579552 -0.527386586 0.394370226 -1.121999916 -0.922978194
[21] -0.198670459 -0.461142512 1.938177888 0.217323362 -0.648408954
[26] 0.964815462 0.011193548 0.848478963 -0.887233473 0.199534441
[31] -2.328091206 -0.055853654 -1.269957236 2.317897548 -0.383396398
[36] -1.155428694 0.311662765 0.524684921 -1.828342829 0.425147685
[41] 1.696034376 -0.497231473 -0.625893168 0.678418833 0.009172152
[46] -2.043068081 -1.255155583 0.346912815 -0.966818065 -0.552038941
[51] 2.420919557 -0.140905001 0.324781025 0.653920564 -0.557612362
[56] 0.884555064 1.419568126 0.704496377 -0.208197863 -0.005626649
[61] -1.477083332 -0.985627428 -1.514968363 0.012651931 0.688875507
[66] -1.327128609 -1.308743610 -1.170533016 -1.196261778 -0.253492265
[71] 1.529281793 -1.121047709 -0.515689155 0.351236477 -0.183698105
[76] -0.734117078 -0.467169598 0.837824130 -0.119263799 0.101917867
[81] 2.109200701 2.119459143 0.159797450 1.614555672 -0.300423946
[86] 0.201259289 -1.968984871 -1.304244709 -0.108428316 2.084656259
[91] -0.590167867 -0.166576834 0.432812835 -0.433706892 0.196590509
[96] 0.236482179 0.196378330 -0.615525825 -0.206342556 -1.078842140
> colSums(tmp)
[1] -0.926636307 2.885788603 -0.971502850 2.004953482 1.002976079
[6] 1.138138283 1.610571868 -0.590928040 1.913694898 0.298646626
[11] 0.633872506 -0.500760880 -0.860835949 0.408982587 -0.212505177
[16] -0.153579552 -0.527386586 0.394370226 -1.121999916 -0.922978194
[21] -0.198670459 -0.461142512 1.938177888 0.217323362 -0.648408954
[26] 0.964815462 0.011193548 0.848478963 -0.887233473 0.199534441
[31] -2.328091206 -0.055853654 -1.269957236 2.317897548 -0.383396398
[36] -1.155428694 0.311662765 0.524684921 -1.828342829 0.425147685
[41] 1.696034376 -0.497231473 -0.625893168 0.678418833 0.009172152
[46] -2.043068081 -1.255155583 0.346912815 -0.966818065 -0.552038941
[51] 2.420919557 -0.140905001 0.324781025 0.653920564 -0.557612362
[56] 0.884555064 1.419568126 0.704496377 -0.208197863 -0.005626649
[61] -1.477083332 -0.985627428 -1.514968363 0.012651931 0.688875507
[66] -1.327128609 -1.308743610 -1.170533016 -1.196261778 -0.253492265
[71] 1.529281793 -1.121047709 -0.515689155 0.351236477 -0.183698105
[76] -0.734117078 -0.467169598 0.837824130 -0.119263799 0.101917867
[81] 2.109200701 2.119459143 0.159797450 1.614555672 -0.300423946
[86] 0.201259289 -1.968984871 -1.304244709 -0.108428316 2.084656259
[91] -0.590167867 -0.166576834 0.432812835 -0.433706892 0.196590509
[96] 0.236482179 0.196378330 -0.615525825 -0.206342556 -1.078842140
> 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] -0.926636307 2.885788603 -0.971502850 2.004953482 1.002976079
[6] 1.138138283 1.610571868 -0.590928040 1.913694898 0.298646626
[11] 0.633872506 -0.500760880 -0.860835949 0.408982587 -0.212505177
[16] -0.153579552 -0.527386586 0.394370226 -1.121999916 -0.922978194
[21] -0.198670459 -0.461142512 1.938177888 0.217323362 -0.648408954
[26] 0.964815462 0.011193548 0.848478963 -0.887233473 0.199534441
[31] -2.328091206 -0.055853654 -1.269957236 2.317897548 -0.383396398
[36] -1.155428694 0.311662765 0.524684921 -1.828342829 0.425147685
[41] 1.696034376 -0.497231473 -0.625893168 0.678418833 0.009172152
[46] -2.043068081 -1.255155583 0.346912815 -0.966818065 -0.552038941
[51] 2.420919557 -0.140905001 0.324781025 0.653920564 -0.557612362
[56] 0.884555064 1.419568126 0.704496377 -0.208197863 -0.005626649
[61] -1.477083332 -0.985627428 -1.514968363 0.012651931 0.688875507
[66] -1.327128609 -1.308743610 -1.170533016 -1.196261778 -0.253492265
[71] 1.529281793 -1.121047709 -0.515689155 0.351236477 -0.183698105
[76] -0.734117078 -0.467169598 0.837824130 -0.119263799 0.101917867
[81] 2.109200701 2.119459143 0.159797450 1.614555672 -0.300423946
[86] 0.201259289 -1.968984871 -1.304244709 -0.108428316 2.084656259
[91] -0.590167867 -0.166576834 0.432812835 -0.433706892 0.196590509
[96] 0.236482179 0.196378330 -0.615525825 -0.206342556 -1.078842140
> colMin(tmp)
[1] -0.926636307 2.885788603 -0.971502850 2.004953482 1.002976079
[6] 1.138138283 1.610571868 -0.590928040 1.913694898 0.298646626
[11] 0.633872506 -0.500760880 -0.860835949 0.408982587 -0.212505177
[16] -0.153579552 -0.527386586 0.394370226 -1.121999916 -0.922978194
[21] -0.198670459 -0.461142512 1.938177888 0.217323362 -0.648408954
[26] 0.964815462 0.011193548 0.848478963 -0.887233473 0.199534441
[31] -2.328091206 -0.055853654 -1.269957236 2.317897548 -0.383396398
[36] -1.155428694 0.311662765 0.524684921 -1.828342829 0.425147685
[41] 1.696034376 -0.497231473 -0.625893168 0.678418833 0.009172152
[46] -2.043068081 -1.255155583 0.346912815 -0.966818065 -0.552038941
[51] 2.420919557 -0.140905001 0.324781025 0.653920564 -0.557612362
[56] 0.884555064 1.419568126 0.704496377 -0.208197863 -0.005626649
[61] -1.477083332 -0.985627428 -1.514968363 0.012651931 0.688875507
[66] -1.327128609 -1.308743610 -1.170533016 -1.196261778 -0.253492265
[71] 1.529281793 -1.121047709 -0.515689155 0.351236477 -0.183698105
[76] -0.734117078 -0.467169598 0.837824130 -0.119263799 0.101917867
[81] 2.109200701 2.119459143 0.159797450 1.614555672 -0.300423946
[86] 0.201259289 -1.968984871 -1.304244709 -0.108428316 2.084656259
[91] -0.590167867 -0.166576834 0.432812835 -0.433706892 0.196590509
[96] 0.236482179 0.196378330 -0.615525825 -0.206342556 -1.078842140
> colMedians(tmp)
[1] -0.926636307 2.885788603 -0.971502850 2.004953482 1.002976079
[6] 1.138138283 1.610571868 -0.590928040 1.913694898 0.298646626
[11] 0.633872506 -0.500760880 -0.860835949 0.408982587 -0.212505177
[16] -0.153579552 -0.527386586 0.394370226 -1.121999916 -0.922978194
[21] -0.198670459 -0.461142512 1.938177888 0.217323362 -0.648408954
[26] 0.964815462 0.011193548 0.848478963 -0.887233473 0.199534441
[31] -2.328091206 -0.055853654 -1.269957236 2.317897548 -0.383396398
[36] -1.155428694 0.311662765 0.524684921 -1.828342829 0.425147685
[41] 1.696034376 -0.497231473 -0.625893168 0.678418833 0.009172152
[46] -2.043068081 -1.255155583 0.346912815 -0.966818065 -0.552038941
[51] 2.420919557 -0.140905001 0.324781025 0.653920564 -0.557612362
[56] 0.884555064 1.419568126 0.704496377 -0.208197863 -0.005626649
[61] -1.477083332 -0.985627428 -1.514968363 0.012651931 0.688875507
[66] -1.327128609 -1.308743610 -1.170533016 -1.196261778 -0.253492265
[71] 1.529281793 -1.121047709 -0.515689155 0.351236477 -0.183698105
[76] -0.734117078 -0.467169598 0.837824130 -0.119263799 0.101917867
[81] 2.109200701 2.119459143 0.159797450 1.614555672 -0.300423946
[86] 0.201259289 -1.968984871 -1.304244709 -0.108428316 2.084656259
[91] -0.590167867 -0.166576834 0.432812835 -0.433706892 0.196590509
[96] 0.236482179 0.196378330 -0.615525825 -0.206342556 -1.078842140
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.9266363 2.885789 -0.9715029 2.004953 1.002976 1.138138 1.610572
[2,] -0.9266363 2.885789 -0.9715029 2.004953 1.002976 1.138138 1.610572
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.590928 1.913695 0.2986466 0.6338725 -0.5007609 -0.8608359 0.4089826
[2,] -0.590928 1.913695 0.2986466 0.6338725 -0.5007609 -0.8608359 0.4089826
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.2125052 -0.1535796 -0.5273866 0.3943702 -1.122 -0.9229782 -0.1986705
[2,] -0.2125052 -0.1535796 -0.5273866 0.3943702 -1.122 -0.9229782 -0.1986705
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.4611425 1.938178 0.2173234 -0.648409 0.9648155 0.01119355 0.848479
[2,] -0.4611425 1.938178 0.2173234 -0.648409 0.9648155 0.01119355 0.848479
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.8872335 0.1995344 -2.328091 -0.05585365 -1.269957 2.317898 -0.3833964
[2,] -0.8872335 0.1995344 -2.328091 -0.05585365 -1.269957 2.317898 -0.3833964
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.155429 0.3116628 0.5246849 -1.828343 0.4251477 1.696034 -0.4972315
[2,] -1.155429 0.3116628 0.5246849 -1.828343 0.4251477 1.696034 -0.4972315
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.6258932 0.6784188 0.009172152 -2.043068 -1.255156 0.3469128 -0.9668181
[2,] -0.6258932 0.6784188 0.009172152 -2.043068 -1.255156 0.3469128 -0.9668181
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.5520389 2.42092 -0.140905 0.324781 0.6539206 -0.5576124 0.8845551
[2,] -0.5520389 2.42092 -0.140905 0.324781 0.6539206 -0.5576124 0.8845551
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 1.419568 0.7044964 -0.2081979 -0.005626649 -1.477083 -0.9856274 -1.514968
[2,] 1.419568 0.7044964 -0.2081979 -0.005626649 -1.477083 -0.9856274 -1.514968
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.01265193 0.6888755 -1.327129 -1.308744 -1.170533 -1.196262 -0.2534923
[2,] 0.01265193 0.6888755 -1.327129 -1.308744 -1.170533 -1.196262 -0.2534923
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.529282 -1.121048 -0.5156892 0.3512365 -0.1836981 -0.7341171 -0.4671696
[2,] 1.529282 -1.121048 -0.5156892 0.3512365 -0.1836981 -0.7341171 -0.4671696
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.8378241 -0.1192638 0.1019179 2.109201 2.119459 0.1597974 1.614556
[2,] 0.8378241 -0.1192638 0.1019179 2.109201 2.119459 0.1597974 1.614556
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.3004239 0.2012593 -1.968985 -1.304245 -0.1084283 2.084656 -0.5901679
[2,] -0.3004239 0.2012593 -1.968985 -1.304245 -0.1084283 2.084656 -0.5901679
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.1665768 0.4328128 -0.4337069 0.1965905 0.2364822 0.1963783 -0.6155258
[2,] -0.1665768 0.4328128 -0.4337069 0.1965905 0.2364822 0.1963783 -0.6155258
[,99] [,100]
[1,] -0.2063426 -1.078842
[2,] -0.2063426 -1.078842
>
>
> Max(tmp2)
[1] 2.251569
> Min(tmp2)
[1] -3.073048
> mean(tmp2)
[1] -0.1664997
> Sum(tmp2)
[1] -16.64997
> Var(tmp2)
[1] 1.096045
>
> rowMeans(tmp2)
[1] -2.122085043 0.749210207 0.757519589 0.503826765 -1.159997496
[6] 0.263114342 0.373759831 -1.236230171 -1.344820863 0.781585463
[11] 0.086463853 1.374526026 0.616377503 -0.048695104 0.928607373
[16] 0.500254547 -0.413361015 -1.271486790 0.091230973 -3.073048059
[21] -1.027793513 -0.603329944 0.787854776 -0.094085505 -0.044829001
[26] -0.627573876 -0.442966266 1.070212557 0.770115749 1.861232104
[31] -0.124327787 1.018934937 1.243932238 0.333223645 -0.257762421
[36] 0.169129511 -0.047527227 2.128736764 -0.624853448 0.641711203
[41] 0.656278035 -0.025821970 -0.477511077 -1.514787422 2.251569397
[46] -1.935101289 -1.483503887 -0.766655189 -0.298860496 -0.597048012
[51] 0.087060550 0.177045916 0.333952539 -0.291967914 0.037767299
[56] -0.796479458 -1.462693610 0.887658742 -0.287496028 1.394293423
[61] -0.560911872 -3.019591962 -0.867866776 1.778127397 -2.250869646
[66] -1.715277906 0.134405533 0.589526542 -0.660105505 1.920153644
[71] -0.745943357 -0.767668930 0.004539125 -0.628433961 0.924265376
[76] 0.120650470 -1.501849196 0.579801557 0.993208616 -1.528992819
[81] -0.768851683 -0.763361504 1.377977885 0.251281946 0.039425214
[86] -0.077370014 -1.272814290 0.225030056 -1.710263645 0.279367216
[91] -0.618729009 0.337208084 -0.504139174 -0.323650604 -0.974889042
[96] -0.583260100 -1.979188278 -0.201074479 0.034981479 -0.589305190
> rowSums(tmp2)
[1] -2.122085043 0.749210207 0.757519589 0.503826765 -1.159997496
[6] 0.263114342 0.373759831 -1.236230171 -1.344820863 0.781585463
[11] 0.086463853 1.374526026 0.616377503 -0.048695104 0.928607373
[16] 0.500254547 -0.413361015 -1.271486790 0.091230973 -3.073048059
[21] -1.027793513 -0.603329944 0.787854776 -0.094085505 -0.044829001
[26] -0.627573876 -0.442966266 1.070212557 0.770115749 1.861232104
[31] -0.124327787 1.018934937 1.243932238 0.333223645 -0.257762421
[36] 0.169129511 -0.047527227 2.128736764 -0.624853448 0.641711203
[41] 0.656278035 -0.025821970 -0.477511077 -1.514787422 2.251569397
[46] -1.935101289 -1.483503887 -0.766655189 -0.298860496 -0.597048012
[51] 0.087060550 0.177045916 0.333952539 -0.291967914 0.037767299
[56] -0.796479458 -1.462693610 0.887658742 -0.287496028 1.394293423
[61] -0.560911872 -3.019591962 -0.867866776 1.778127397 -2.250869646
[66] -1.715277906 0.134405533 0.589526542 -0.660105505 1.920153644
[71] -0.745943357 -0.767668930 0.004539125 -0.628433961 0.924265376
[76] 0.120650470 -1.501849196 0.579801557 0.993208616 -1.528992819
[81] -0.768851683 -0.763361504 1.377977885 0.251281946 0.039425214
[86] -0.077370014 -1.272814290 0.225030056 -1.710263645 0.279367216
[91] -0.618729009 0.337208084 -0.504139174 -0.323650604 -0.974889042
[96] -0.583260100 -1.979188278 -0.201074479 0.034981479 -0.589305190
> 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] -2.122085043 0.749210207 0.757519589 0.503826765 -1.159997496
[6] 0.263114342 0.373759831 -1.236230171 -1.344820863 0.781585463
[11] 0.086463853 1.374526026 0.616377503 -0.048695104 0.928607373
[16] 0.500254547 -0.413361015 -1.271486790 0.091230973 -3.073048059
[21] -1.027793513 -0.603329944 0.787854776 -0.094085505 -0.044829001
[26] -0.627573876 -0.442966266 1.070212557 0.770115749 1.861232104
[31] -0.124327787 1.018934937 1.243932238 0.333223645 -0.257762421
[36] 0.169129511 -0.047527227 2.128736764 -0.624853448 0.641711203
[41] 0.656278035 -0.025821970 -0.477511077 -1.514787422 2.251569397
[46] -1.935101289 -1.483503887 -0.766655189 -0.298860496 -0.597048012
[51] 0.087060550 0.177045916 0.333952539 -0.291967914 0.037767299
[56] -0.796479458 -1.462693610 0.887658742 -0.287496028 1.394293423
[61] -0.560911872 -3.019591962 -0.867866776 1.778127397 -2.250869646
[66] -1.715277906 0.134405533 0.589526542 -0.660105505 1.920153644
[71] -0.745943357 -0.767668930 0.004539125 -0.628433961 0.924265376
[76] 0.120650470 -1.501849196 0.579801557 0.993208616 -1.528992819
[81] -0.768851683 -0.763361504 1.377977885 0.251281946 0.039425214
[86] -0.077370014 -1.272814290 0.225030056 -1.710263645 0.279367216
[91] -0.618729009 0.337208084 -0.504139174 -0.323650604 -0.974889042
[96] -0.583260100 -1.979188278 -0.201074479 0.034981479 -0.589305190
> rowMin(tmp2)
[1] -2.122085043 0.749210207 0.757519589 0.503826765 -1.159997496
[6] 0.263114342 0.373759831 -1.236230171 -1.344820863 0.781585463
[11] 0.086463853 1.374526026 0.616377503 -0.048695104 0.928607373
[16] 0.500254547 -0.413361015 -1.271486790 0.091230973 -3.073048059
[21] -1.027793513 -0.603329944 0.787854776 -0.094085505 -0.044829001
[26] -0.627573876 -0.442966266 1.070212557 0.770115749 1.861232104
[31] -0.124327787 1.018934937 1.243932238 0.333223645 -0.257762421
[36] 0.169129511 -0.047527227 2.128736764 -0.624853448 0.641711203
[41] 0.656278035 -0.025821970 -0.477511077 -1.514787422 2.251569397
[46] -1.935101289 -1.483503887 -0.766655189 -0.298860496 -0.597048012
[51] 0.087060550 0.177045916 0.333952539 -0.291967914 0.037767299
[56] -0.796479458 -1.462693610 0.887658742 -0.287496028 1.394293423
[61] -0.560911872 -3.019591962 -0.867866776 1.778127397 -2.250869646
[66] -1.715277906 0.134405533 0.589526542 -0.660105505 1.920153644
[71] -0.745943357 -0.767668930 0.004539125 -0.628433961 0.924265376
[76] 0.120650470 -1.501849196 0.579801557 0.993208616 -1.528992819
[81] -0.768851683 -0.763361504 1.377977885 0.251281946 0.039425214
[86] -0.077370014 -1.272814290 0.225030056 -1.710263645 0.279367216
[91] -0.618729009 0.337208084 -0.504139174 -0.323650604 -0.974889042
[96] -0.583260100 -1.979188278 -0.201074479 0.034981479 -0.589305190
>
> colMeans(tmp2)
[1] -0.1664997
> colSums(tmp2)
[1] -16.64997
> colVars(tmp2)
[1] 1.096045
> colSd(tmp2)
[1] 1.046922
> colMax(tmp2)
[1] 2.251569
> colMin(tmp2)
[1] -3.073048
> colMedians(tmp2)
[1] -0.06303256
> colRanges(tmp2)
[,1]
[1,] -3.073048
[2,] 2.251569
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 3.2078893 -3.6881276 -2.1952955 -1.1459359 3.1936829 -2.3147670
[7] -2.1192376 -0.6650122 0.3400188 -2.0498316
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.3091777
[2,] -0.5229375
[3,] 0.3864087
[4,] 0.9716037
[5,] 2.3842715
>
> rowApply(tmp,sum)
[1] -2.4829274 -0.5883071 -4.9208613 -0.6493345 -2.3933455 2.7065026
[7] 1.2757773 1.1088912 -0.9429693 -0.5500424
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 4 6 8 2 8 7 8 9 10
[2,] 4 2 7 3 6 5 4 5 2 7
[3,] 5 8 3 7 1 7 5 10 3 4
[4,] 9 5 5 5 8 2 1 6 7 6
[5,] 1 10 9 4 7 10 10 1 4 8
[6,] 2 9 4 6 5 3 3 3 5 9
[7,] 10 1 10 2 3 6 9 7 1 2
[8,] 8 7 1 10 10 1 8 4 6 3
[9,] 7 6 8 9 9 4 6 2 10 1
[10,] 6 3 2 1 4 9 2 9 8 5
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.691898325 0.973208342 3.078885342 -1.129149519 -0.768323765
[6] 0.798072999 1.854800591 -3.949856573 2.353967193 -0.804809519
[11] -0.460681591 3.205700165 2.169387703 -0.533440562 2.412509582
[16] -5.375892459 -1.731085574 -1.363113147 0.009232465 -0.677147266
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.964827
[2,] -1.158433
[3,] -1.083670
[4,] 0.858444
[5,] 1.656587
>
> rowApply(tmp,sum)
[1] -3.0502376 -6.6994213 0.6222328 1.6942502 5.8035420
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 5 1 2 16 17
[2,] 4 18 16 18 4
[3,] 18 6 20 20 6
[4,] 14 3 6 9 12
[5,] 2 7 15 19 9
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.158433 -1.2481152 1.0106554 0.4245942 -1.735965155 0.9218287
[2,] -1.964827 0.6825237 -0.6798405 -1.4825122 -0.562566137 -1.3638858
[3,] -1.083670 0.8861518 1.7924215 -0.4258351 0.270640191 -0.1823965
[4,] 0.858444 1.2394415 1.4077085 -0.2000074 1.252588352 0.9689978
[5,] 1.656587 -0.5867934 -0.4520596 0.5546110 0.006978985 0.4535289
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.8451484 -0.50728417 1.5310187 -0.8195147 -1.0441239 2.7159716
[2,] 0.3124520 -0.72625849 -0.2557221 -0.5441144 0.2227999 -0.1366883
[3,] 1.1222505 -0.01335416 -0.2260651 0.1714420 1.7680307 -0.9720085
[4,] -0.7880624 -0.31088894 0.5593524 -1.0397160 0.4544217 -0.1719042
[5,] 0.3630121 -2.39207081 0.7453833 1.4270936 -1.8618100 1.7703295
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.3015186 0.37128757 -0.3495089 -1.5509198 -2.416011379 -1.1480413
[2,] 0.8860144 0.03495696 -0.2620333 -1.8283096 0.005361193 1.3296947
[3,] -0.4046282 -0.08662729 1.3221486 -0.5550526 -0.344817444 -0.6607112
[4,] 0.5710836 -0.58015905 -0.5734737 -0.9686637 -0.819736435 -0.2333684
[5,] 0.8153993 -0.27289876 2.2753767 -0.4729468 1.844118491 -0.6506870
[,19] [,20]
[1,] -0.165666893 0.97132308
[2,] -0.220690881 -0.14577588
[3,] -0.411106041 -1.34458079
[4,] -0.007513209 0.07570569
[5,] 0.814209489 -0.23381936
>
>
> 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 -0.06605059 -0.7676257 1.181434 -0.5708188 -1.000295 -0.6665039 -0.8426932
col8 col9 col10 col11 col12 col13 col14
row1 1.069789 1.977714 0.1754859 0.2197319 0.1575196 0.241553 1.310781
col15 col16 col17 col18 col19 col20
row1 -1.319402 -0.5252875 -1.260141 1.812406 -1.497687 -0.7425686
> tmp[,"col10"]
col10
row1 0.17548592
row2 1.54931661
row3 1.16317977
row4 -0.12785071
row5 -0.08682874
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.06605059 -0.7676257 1.1814340 -0.5708188 -1.0002946 -0.6665039
row5 0.44223060 0.6943327 -0.1453222 -0.8549851 -0.4223877 -0.8502684
col7 col8 col9 col10 col11 col12
row1 -0.8426932 1.0697894 1.9777135 0.17548592 0.2197319 0.1575196
row5 -1.3731391 0.8475898 0.1687815 -0.08682874 -0.2770601 -0.7551080
col13 col14 col15 col16 col17 col18
row1 0.24155295 1.3107810 -1.3194020 -0.5252875 -1.2601414 1.8124058
row5 0.04107438 -0.5823472 -0.3012288 1.0626122 0.6124437 0.1488566
col19 col20
row1 -1.4976871 -0.7425686
row5 0.9213859 -0.5461645
> tmp[,c("col6","col20")]
col6 col20
row1 -0.6665039 -0.7425686
row2 -1.3121104 -0.2701992
row3 -0.1078786 -2.4710833
row4 0.3119568 0.2513838
row5 -0.8502684 -0.5461645
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.6665039 -0.7425686
row5 -0.8502684 -0.5461645
>
>
>
>
> 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 49.60912 50.13405 49.30238 49.62502 49.98904 105.0308 50.97933 50.31908
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.01528 50.65866 48.0816 50.4108 48.81126 48.36523 51.26113 51.70145
col17 col18 col19 col20
row1 49.24174 51.18345 48.31057 104.4093
> tmp[,"col10"]
col10
row1 50.65866
row2 30.04993
row3 30.84394
row4 30.21413
row5 51.08075
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.60912 50.13405 49.30238 49.62502 49.98904 105.0308 50.97933 50.31908
row5 49.79688 50.88328 51.44176 51.31413 50.54936 106.9321 50.54496 48.38701
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.01528 50.65866 48.08160 50.41080 48.81126 48.36523 51.26113 51.70145
row5 51.21221 51.08075 50.28891 50.53887 49.69854 49.76853 52.01648 48.46869
col17 col18 col19 col20
row1 49.24174 51.18345 48.31057 104.4093
row5 50.01620 49.04669 50.02916 106.5046
> tmp[,c("col6","col20")]
col6 col20
row1 105.03081 104.40927
row2 74.05160 74.65338
row3 75.16035 76.07903
row4 74.37506 74.90146
row5 106.93205 106.50459
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.0308 104.4093
row5 106.9321 106.5046
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.0308 104.4093
row5 106.9321 106.5046
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.7580935
[2,] -1.2049327
[3,] 1.1311452
[4,] -0.3283741
[5,] -0.2495104
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.3434903 -1.4822513
[2,] 1.0722634 1.3907582
[3,] 0.6279880 0.2161382
[4,] -0.3541591 1.1601924
[5,] -0.3929391 0.5324108
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.1963120 -0.41194626
[2,] -0.3809131 -1.41101152
[3,] 0.2719239 -0.08969407
[4,] -0.9123117 0.11489857
[5,] 0.4392498 1.44413254
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.196312
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.1963120
[2,] -0.3809131
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 -0.3208333 -0.8369239 1.1667539 0.1029894 0.7040276 1.2385799
row1 -0.8320952 0.3394966 0.1411675 -0.4915897 1.4515787 -0.5085321
[,7] [,8] [,9] [,10] [,11] [,12]
row3 1.23725879 0.40165001 0.6364437 -0.5412862 -1.7010067 0.6995368
row1 -0.08785711 -0.07575514 -2.0488648 1.7164541 0.5898485 -0.5620255
[,13] [,14] [,15] [,16] [,17] [,18]
row3 -1.632001 -0.8649483 0.6815468 0.1747886 0.01641027 0.3959197
row1 0.877416 0.4137007 -1.3287030 -1.7253173 -0.11396321 -0.5652859
[,19] [,20]
row3 -0.5226253 1.6237395
row1 -0.6483615 0.6039459
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.3258517 -0.3515893 -1.212909 -1.202784 -0.6330399 -0.4654763 0.5325728
[,8] [,9] [,10]
row2 -0.3180905 0.2020615 -0.5661335
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.009681 -0.06486576 0.7251325 -0.08789713 1.315895 -0.2973351 0.3571363
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.752227 0.1793448 -0.3503693 1.741905 -1.128666 -0.2046575 -0.1120686
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.5532862 -1.559536 1.227967 -1.525106 -0.8581671 0.5770137
>
>
> 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: 0x600001ed4240>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6f8d4417ac62"
[2] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6f8d6e3678da"
[3] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6f8d3a3868bd"
[4] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6f8d4d646e27"
[5] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6f8d7c7bea22"
[6] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6f8d2b489e07"
[7] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6f8d2c7ef3c4"
[8] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6f8d42b5dfae"
[9] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6f8d32703ab9"
[10] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6f8d661f618d"
[11] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6f8d163da45c"
[12] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6f8d28f19f6c"
[13] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6f8df198074"
[14] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6f8d5340476a"
[15] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6f8d2110aad9"
>
>
> ### 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: 0x600001ec43c0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600001ec43c0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600001ec43c0>
> rowMedians(tmp)
[1] -0.366671709 0.037980863 -0.218969193 0.223274913 0.145374678
[6] -0.236192228 0.206311061 0.112925701 -0.288868785 -0.025140380
[11] 0.008875674 -0.371607540 -0.031345116 -0.643503133 0.327590752
[16] 0.227202780 0.136817220 0.281439495 -0.252534096 0.058112320
[21] 0.367515273 -0.182409528 0.614503292 -0.315125473 0.317750467
[26] 0.029097475 0.497990894 -0.303027257 -0.227429325 0.113880285
[31] 0.109492279 -0.301157611 -0.118985851 0.173147300 0.724878481
[36] 0.013231936 -0.583130393 0.076681860 0.165410136 -0.376160404
[41] 0.268430583 0.186776613 -0.080522830 0.023878305 -0.039380085
[46] -0.074869862 -0.433679437 0.111291315 0.385626553 0.229294881
[51] 0.231472905 -0.105176995 -0.103932974 -0.303303751 -0.109896677
[56] 0.081778290 -0.201957433 0.279038685 0.002602175 0.003671711
[61] -0.855116420 -0.104767047 -0.349825307 0.258508456 -0.414495170
[66] -0.104978476 0.078965486 -0.307085242 0.448753039 0.152710434
[71] -0.125222827 -0.466096721 -0.328296246 0.163451183 -0.904967380
[76] -0.473215628 -0.057735646 0.040823821 0.002827908 -0.379077045
[81] 0.913614169 -0.345035629 -0.200186362 0.285774787 0.424500268
[86] 0.310775001 -0.135104674 -0.035840567 0.289722653 0.627711176
[91] 0.397830945 0.051716610 -0.342382630 0.287347629 -0.298977037
[96] 0.213997995 -0.373828168 -0.438238858 -0.494972313 0.156234066
[101] 0.003230054 0.165671568 0.308377658 -0.799775148 -0.018909767
[106] -0.491906418 0.210100242 0.025447567 -0.122482159 0.552824777
[111] -0.308651366 0.460335986 -0.288229972 0.021527538 -0.223259453
[116] -0.249958713 0.399292627 0.635192889 0.158967433 -0.547092838
[121] -0.069186581 0.069324970 0.178923554 -0.326844853 0.418066431
[126] 0.773000201 0.353128943 0.001027653 0.304786032 0.023053733
[131] -0.040727921 0.058663392 0.332397764 -0.014571249 -0.112629136
[136] 0.085775495 -0.112655082 0.155505610 0.049020810 0.238133481
[141] 0.183845195 0.106481281 -0.014668873 0.173535076 0.206906134
[146] -0.214548880 0.032026821 0.067648390 0.139854658 -0.226074457
[151] -0.755146124 0.144274102 -0.143575915 0.323868934 0.407116692
[156] 0.170209960 0.254128946 -0.460004944 0.431635551 0.157917010
[161] 0.568951848 -0.457850561 -0.437362296 -0.258713750 -0.160831776
[166] -0.402325583 -0.338139377 -0.001625346 0.183239094 -0.539273407
[171] -0.452438998 0.050758008 0.069775560 -0.378897205 -0.209949553
[176] -0.279591162 -0.180884152 -0.053034331 -0.164367393 0.294225724
[181] -0.045696438 0.177488064 -0.558073905 -0.357419071 0.160091138
[186] 0.512421477 -0.604269116 -0.222896185 -0.402876153 -0.122228503
[191] -0.308763277 -0.152380551 0.408557445 -0.136858588 -0.089417289
[196] 0.074885902 -0.583730651 -0.313699179 0.215055258 0.093615337
[201] 0.563534228 0.135829323 -0.369522625 -0.237630546 -0.457041025
[206] -0.103471088 0.220909561 -0.111540184 0.208942634 -0.068114983
[211] 0.116580348 -0.300193982 -0.479884380 0.169334994 -0.083008953
[216] -0.095394246 0.544293934 0.087479310 -0.155072891 0.042153105
[221] 0.296253354 0.306042103 0.319320931 -0.260066540 0.070197297
[226] 0.358112421 0.601620734 0.002858571 0.008147996 0.462566112
>
> proc.time()
user system elapsed
2.090 8.601 11.309
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: 0x6000006f8240>
> .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: 0x6000006f8240>
> .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: 0x6000006f8240>
> .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: 0x6000006f8240>
> 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: 0x6000006e8600>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000006e8600>
> .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: 0x6000006e8600>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000006e8600>
> .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: 0x6000006e8600>
> 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: 0x6000006e87e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000006e87e0>
> .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: 0x6000006e87e0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000006e87e0>
> .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: 0x6000006e87e0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000006e87e0>
> .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: 0x6000006e87e0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000006e87e0>
> .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: 0x6000006e87e0>
> 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: 0x6000006e89c0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000006e89c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000006e89c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000006e89c0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile6fb716715775" "BufferedMatrixFile6fb76b24cdd5"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile6fb716715775" "BufferedMatrixFile6fb76b24cdd5"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000006e8c60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000006e8c60>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000006e8c60>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000006e8c60>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000006e8c60>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000006e8c60>
> .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: 0x6000006e8e40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000006e8e40>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000006e8e40>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000006e8e40>
> 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: 0x6000006e9020>
> .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: 0x6000006e9020>
> rm(P)
>
> proc.time()
user system elapsed
0.338 0.132 0.468
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
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
0.335 0.096 0.415