Ben Bolstad
| Snapshot Date: 2025-06-23 13:25 -0400 (Mon, 23 Jun 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 0147962 |
| git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-06-24 12:08 -0400 (Tue, 24 Jun 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.2 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4565 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.5.1 (2025-06-13 ucrt) -- "Great Square Root" | 4506 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4544 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4492 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4497 |
| 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 250/2310 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.73.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.2 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.1 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.73.0 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.73.0.tar.gz |
| StartedAt: 2025-06-23 19:21:05 -0400 (Mon, 23 Jun 2025) |
| EndedAt: 2025-06-23 19:23:00 -0400 (Mon, 23 Jun 2025) |
| EllapsedTime: 114.6 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_1.73.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.1 (2025-06-13)
* using platform: x86_64-apple-darwin20
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 14.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.73.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... WARNING
Found the following significant warnings:
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
* used SDK: ‘MacOSX11.3.sdk’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 WARNING, 2 NOTEs
See
‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.73.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
using SDK: ‘MacOSX11.3.sdk’
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch x86_64 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/x86_64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R
installing to /Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.5.1 (2025-06-13) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.339 0.161 1.119
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 (2025-06-13) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
Ncells 480847 25.7 1056620 56.5 NA 634457 33.9
Vcells 891074 6.8 8388608 64.0 98304 2108777 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] "Mon Jun 23 19:21:33 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] "Mon Jun 23 19:21:34 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: 0x600001d0c000>
>
>
>
> 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] "Mon Jun 23 19:22:04 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] "Mon Jun 23 19:22:16 2025"
>
> ColMode(tmp2)
<pointer: 0x600001d0c000>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.4552344 -0.04953501 -1.0488798 0.1427822
[2,] 1.0714260 -0.07651039 0.2455268 0.7409911
[3,] -0.5720933 1.17589344 1.0761147 -0.9700587
[4,] -0.1363803 -0.71535447 -1.5157942 0.8769185
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.4552344 0.04953501 1.0488798 0.1427822
[2,] 1.0714260 0.07651039 0.2455268 0.7409911
[3,] 0.5720933 1.17589344 1.0761147 0.9700587
[4,] 0.1363803 0.71535447 1.5157942 0.8769185
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0227359 0.2225646 1.0241483 0.3778654
[2,] 1.0350971 0.2766051 0.4955066 0.8608084
[3,] 0.7563685 1.0843862 1.0373595 0.9849156
[4,] 0.3692970 0.8457863 1.2311759 0.9364393
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.68259 27.27518 36.29036 28.92144
[2,] 36.42240 27.84256 30.20059 34.34908
[3,] 33.13578 37.01976 36.44971 35.81921
[4,] 28.82935 34.17322 38.82755 35.24131
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600001d40000>
> exp(tmp5)
<pointer: 0x600001d40000>
> log(tmp5,2)
<pointer: 0x600001d40000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.7287
> Min(tmp5)
[1] 54.12446
> mean(tmp5)
[1] 72.82884
> Sum(tmp5)
[1] 14565.77
> Var(tmp5)
[1] 865.0668
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.01033 71.55394 72.72575 72.74144 72.30813 68.85553 71.56854 69.77179
[9] 66.75574 71.99720
> rowSums(tmp5)
[1] 1800.207 1431.079 1454.515 1454.829 1446.163 1377.111 1431.371 1395.436
[9] 1335.115 1439.944
> rowVars(tmp5)
[1] 8049.31901 70.98240 63.41833 56.13681 67.83271 103.24119
[7] 63.85191 61.60886 67.24012 76.37004
> rowSd(tmp5)
[1] 89.717997 8.425105 7.963563 7.492450 8.236062 10.160767 7.990739
[8] 7.849131 8.200007 8.738996
> rowMax(tmp5)
[1] 469.72875 94.90969 91.67738 88.14647 87.70394 90.46518 88.64994
[8] 87.70749 85.89369 89.07278
> rowMin(tmp5)
[1] 56.76972 57.95064 60.06746 60.00452 56.81561 56.43785 58.82205 58.13316
[9] 54.12446 59.02981
>
> colMeans(tmp5)
[1] 110.34369 65.72671 70.73558 68.55611 67.82236 76.34028 71.69981
[8] 71.48521 67.60095 68.32688 70.34184 77.44995 73.01452 72.91857
[15] 74.02560 70.41138 71.77040 69.71200 69.83855 68.45637
> colSums(tmp5)
[1] 1103.4369 657.2671 707.3558 685.5611 678.2236 763.4028 716.9981
[8] 714.8521 676.0095 683.2688 703.4184 774.4995 730.1452 729.1857
[15] 740.2560 704.1138 717.7040 697.1200 698.3855 684.5637
> colVars(tmp5)
[1] 15979.46346 68.99519 38.80297 33.59710 47.78168 101.05195
[7] 129.30400 73.90333 41.96524 33.35319 73.43140 72.01929
[13] 68.45516 55.17751 72.00976 47.36601 107.00761 63.63743
[19] 83.63984 111.88239
> colSd(tmp5)
[1] 126.409903 8.306334 6.229203 5.796301 6.912429 10.052460
[7] 11.371192 8.596705 6.478058 5.775222 8.569212 8.486418
[13] 8.273763 7.428156 8.485857 6.882297 10.344448 7.977307
[19] 9.145482 10.577447
> colMax(tmp5)
[1] 469.72875 78.02984 80.81447 74.77022 78.20270 94.90969 88.07941
[8] 87.70394 80.42061 79.53269 82.63424 88.64994 82.74879 89.07278
[15] 88.14647 85.21414 91.67738 84.37194 84.39101 90.46518
> colMin(tmp5)
[1] 60.00452 56.76972 62.68001 58.13316 54.48708 60.80194 54.12446 57.36140
[9] 56.89317 59.25255 56.70386 62.98857 62.35039 64.50017 61.33399 60.86493
[17] 56.43785 60.02341 58.59729 56.33974
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 90.01033 71.55394 72.72575 72.74144 72.30813 68.85553 71.56854 69.77179
[9] NA 71.99720
> rowSums(tmp5)
[1] 1800.207 1431.079 1454.515 1454.829 1446.163 1377.111 1431.371 1395.436
[9] NA 1439.944
> rowVars(tmp5)
[1] 8049.31901 70.98240 63.41833 56.13681 67.83271 103.24119
[7] 63.85191 61.60886 70.89423 76.37004
> rowSd(tmp5)
[1] 89.717997 8.425105 7.963563 7.492450 8.236062 10.160767 7.990739
[8] 7.849131 8.419871 8.738996
> rowMax(tmp5)
[1] 469.72875 94.90969 91.67738 88.14647 87.70394 90.46518 88.64994
[8] 87.70749 NA 89.07278
> rowMin(tmp5)
[1] 56.76972 57.95064 60.06746 60.00452 56.81561 56.43785 58.82205 58.13316
[9] NA 59.02981
>
> colMeans(tmp5)
[1] 110.34369 65.72671 70.73558 68.55611 67.82236 76.34028 71.69981
[8] 71.48521 67.60095 68.32688 70.34184 77.44995 73.01452 72.91857
[15] 74.02560 70.41138 71.77040 69.71200 NA 68.45637
> colSums(tmp5)
[1] 1103.4369 657.2671 707.3558 685.5611 678.2236 763.4028 716.9981
[8] 714.8521 676.0095 683.2688 703.4184 774.4995 730.1452 729.1857
[15] 740.2560 704.1138 717.7040 697.1200 NA 684.5637
> colVars(tmp5)
[1] 15979.46346 68.99519 38.80297 33.59710 47.78168 101.05195
[7] 129.30400 73.90333 41.96524 33.35319 73.43140 72.01929
[13] 68.45516 55.17751 72.00976 47.36601 107.00761 63.63743
[19] NA 111.88239
> colSd(tmp5)
[1] 126.409903 8.306334 6.229203 5.796301 6.912429 10.052460
[7] 11.371192 8.596705 6.478058 5.775222 8.569212 8.486418
[13] 8.273763 7.428156 8.485857 6.882297 10.344448 7.977307
[19] NA 10.577447
> colMax(tmp5)
[1] 469.72875 78.02984 80.81447 74.77022 78.20270 94.90969 88.07941
[8] 87.70394 80.42061 79.53269 82.63424 88.64994 82.74879 89.07278
[15] 88.14647 85.21414 91.67738 84.37194 NA 90.46518
> colMin(tmp5)
[1] 60.00452 56.76972 62.68001 58.13316 54.48708 60.80194 54.12446 57.36140
[9] 56.89317 59.25255 56.70386 62.98857 62.35039 64.50017 61.33399 60.86493
[17] 56.43785 60.02341 NA 56.33974
>
> Max(tmp5,na.rm=TRUE)
[1] 469.7287
> Min(tmp5,na.rm=TRUE)
[1] 54.12446
> mean(tmp5,na.rm=TRUE)
[1] 72.86529
> Sum(tmp5,na.rm=TRUE)
[1] 14500.19
> Var(tmp5,na.rm=TRUE)
[1] 869.1688
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.01033 71.55394 72.72575 72.74144 72.30813 68.85553 71.56854 69.77179
[9] 66.81785 71.99720
> rowSums(tmp5,na.rm=TRUE)
[1] 1800.207 1431.079 1454.515 1454.829 1446.163 1377.111 1431.371 1395.436
[9] 1269.539 1439.944
> rowVars(tmp5,na.rm=TRUE)
[1] 8049.31901 70.98240 63.41833 56.13681 67.83271 103.24119
[7] 63.85191 61.60886 70.89423 76.37004
> rowSd(tmp5,na.rm=TRUE)
[1] 89.717997 8.425105 7.963563 7.492450 8.236062 10.160767 7.990739
[8] 7.849131 8.419871 8.738996
> rowMax(tmp5,na.rm=TRUE)
[1] 469.72875 94.90969 91.67738 88.14647 87.70394 90.46518 88.64994
[8] 87.70749 85.89369 89.07278
> rowMin(tmp5,na.rm=TRUE)
[1] 56.76972 57.95064 60.06746 60.00452 56.81561 56.43785 58.82205 58.13316
[9] 54.12446 59.02981
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.34369 65.72671 70.73558 68.55611 67.82236 76.34028 71.69981
[8] 71.48521 67.60095 68.32688 70.34184 77.44995 73.01452 72.91857
[15] 74.02560 70.41138 71.77040 69.71200 70.31221 68.45637
> colSums(tmp5,na.rm=TRUE)
[1] 1103.4369 657.2671 707.3558 685.5611 678.2236 763.4028 716.9981
[8] 714.8521 676.0095 683.2688 703.4184 774.4995 730.1452 729.1857
[15] 740.2560 704.1138 717.7040 697.1200 632.8099 684.5637
> colVars(tmp5,na.rm=TRUE)
[1] 15979.46346 68.99519 38.80297 33.59710 47.78168 101.05195
[7] 129.30400 73.90333 41.96524 33.35319 73.43140 72.01929
[13] 68.45516 55.17751 72.00976 47.36601 107.00761 63.63743
[19] 91.57084 111.88239
> colSd(tmp5,na.rm=TRUE)
[1] 126.409903 8.306334 6.229203 5.796301 6.912429 10.052460
[7] 11.371192 8.596705 6.478058 5.775222 8.569212 8.486418
[13] 8.273763 7.428156 8.485857 6.882297 10.344448 7.977307
[19] 9.569265 10.577447
> colMax(tmp5,na.rm=TRUE)
[1] 469.72875 78.02984 80.81447 74.77022 78.20270 94.90969 88.07941
[8] 87.70394 80.42061 79.53269 82.63424 88.64994 82.74879 89.07278
[15] 88.14647 85.21414 91.67738 84.37194 84.39101 90.46518
> colMin(tmp5,na.rm=TRUE)
[1] 60.00452 56.76972 62.68001 58.13316 54.48708 60.80194 54.12446 57.36140
[9] 56.89317 59.25255 56.70386 62.98857 62.35039 64.50017 61.33399 60.86493
[17] 56.43785 60.02341 58.59729 56.33974
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.01033 71.55394 72.72575 72.74144 72.30813 68.85553 71.56854 69.77179
[9] NaN 71.99720
> rowSums(tmp5,na.rm=TRUE)
[1] 1800.207 1431.079 1454.515 1454.829 1446.163 1377.111 1431.371 1395.436
[9] 0.000 1439.944
> rowVars(tmp5,na.rm=TRUE)
[1] 8049.31901 70.98240 63.41833 56.13681 67.83271 103.24119
[7] 63.85191 61.60886 NA 76.37004
> rowSd(tmp5,na.rm=TRUE)
[1] 89.717997 8.425105 7.963563 7.492450 8.236062 10.160767 7.990739
[8] 7.849131 NA 8.738996
> rowMax(tmp5,na.rm=TRUE)
[1] 469.72875 94.90969 91.67738 88.14647 87.70394 90.46518 88.64994
[8] 87.70749 NA 89.07278
> rowMin(tmp5,na.rm=TRUE)
[1] 56.76972 57.95064 60.06746 60.00452 56.81561 56.43785 58.82205 58.13316
[9] NA 59.02981
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.96960 65.99966 71.20469 68.46611 69.30406 77.20485 73.65262
[8] 71.96406 67.70893 68.30595 71.20083 76.51176 73.17904 73.77118
[15] 73.11614 71.30520 72.30450 70.78851 NaN 69.80266
> colSums(tmp5,na.rm=TRUE)
[1] 1025.7264 593.9969 640.8422 616.1950 623.7365 694.8437 662.8736
[8] 647.6765 609.3803 614.7535 640.8075 688.6058 658.6113 663.9407
[15] 658.0453 641.7468 650.7405 637.0966 0.0000 628.2239
> colVars(tmp5,na.rm=TRUE)
[1] 17828.99038 76.78148 41.17767 37.70562 29.05582 105.27425
[7] 102.56524 80.56170 47.07974 37.51741 74.30928 71.11938
[13] 76.70757 53.89642 71.70596 44.29916 117.17440 58.55477
[19] NA 105.47706
> colSd(tmp5,na.rm=TRUE)
[1] 133.525242 8.762504 6.416983 6.140490 5.390345 10.260324
[7] 10.127450 8.975617 6.861468 6.125146 8.620283 8.433231
[13] 8.758286 7.341418 8.467937 6.655761 10.824712 7.652109
[19] NA 10.270202
> colMax(tmp5,na.rm=TRUE)
[1] 469.72875 78.02984 80.81447 74.77022 78.20270 94.90969 88.07941
[8] 87.70394 80.42061 79.53269 82.63424 88.64994 82.74879 89.07278
[15] 88.14647 85.21414 91.67738 84.37194 -Inf 90.46518
> colMin(tmp5,na.rm=TRUE)
[1] 60.00452 56.76972 62.68001 58.13316 62.02113 60.80194 59.56838 57.36140
[9] 56.89317 59.25255 56.70386 62.98857 62.35039 64.50017 61.33399 60.86493
[17] 56.43785 60.06746 Inf 56.81561
>
>
>
>
> 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] 278.7114 299.6066 183.9086 199.7659 281.2994 159.7392 203.3620 222.0385
[9] 209.4101 222.3733
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 278.7114 299.6066 183.9086 199.7659 281.2994 159.7392 203.3620 222.0385
[9] 209.4101 222.3733
>
>
>
> 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] -2.842171e-14 -7.105427e-14 2.842171e-13 2.273737e-13 -3.552714e-14
[6] 1.705303e-13 5.684342e-14 2.842171e-14 5.684342e-14 2.131628e-14
[11] -5.684342e-14 1.136868e-13 -1.705303e-13 0.000000e+00 1.278977e-13
[16] -5.684342e-14 2.842171e-14 -5.684342e-14 2.842171e-14 1.705303e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
6 15
6 14
8 10
4 18
8 11
7 20
1 10
8 18
10 20
5 11
2 9
7 4
2 10
6 13
10 8
8 15
7 1
5 2
4 3
1 12
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] 1.751517
> Min(tmp)
[1] -2.67152
> mean(tmp)
[1] -0.120513
> Sum(tmp)
[1] -12.0513
> Var(tmp)
[1] 0.9674154
>
> rowMeans(tmp)
[1] -0.120513
> rowSums(tmp)
[1] -12.0513
> rowVars(tmp)
[1] 0.9674154
> rowSd(tmp)
[1] 0.9835728
> rowMax(tmp)
[1] 1.751517
> rowMin(tmp)
[1] -2.67152
>
> colMeans(tmp)
[1] -0.35043373 0.52568079 -1.16764135 -1.83774634 -0.48519304 -0.89771507
[7] -0.95458323 -1.25955153 0.96288685 -2.45380188 -0.71624020 0.53342596
[13] -0.91281918 1.03982398 0.18899342 0.08320925 -0.48745566 -0.30347331
[19] -0.95022268 0.73845005 -1.50951413 0.25424936 -0.68604857 1.48870252
[25] 1.19518142 1.19922486 0.22290516 1.24908873 0.14012282 1.14934886
[31] -0.11493984 -1.59597031 -1.29425022 1.04681745 1.48395299 -1.18912894
[37] 0.66513779 -0.37251162 0.54985658 0.95772807 -2.67152027 1.51664790
[43] 0.39221913 -0.12980615 1.61664042 -0.96066388 1.20906116 0.04863015
[49] -0.27710941 -0.11782010 -0.91572395 -0.48687859 0.34112564 -2.13393674
[55] -1.17618246 -1.97976839 -1.00289955 -0.34804023 1.04971403 0.03872986
[61] 1.24734405 -0.87920111 0.13828871 -1.18728501 0.59254525 -0.17229405
[67] 0.48640851 0.19472282 -0.42923570 0.15016345 -0.81734705 0.70507504
[73] -0.18443973 -1.02225375 -1.77943713 -1.18173501 0.59853617 -0.28492036
[79] 0.25791211 0.25041664 1.03786219 -1.23908069 0.98226849 0.39143785
[85] 0.03932415 0.82360965 0.52712142 -0.55817651 -1.52400739 -0.89511393
[91] -0.08674030 -0.50775534 -0.25189174 -0.81857175 1.33933375 1.75151653
[97] -0.64764593 0.13458073 -0.35519049 0.97459383
> colSums(tmp)
[1] -0.35043373 0.52568079 -1.16764135 -1.83774634 -0.48519304 -0.89771507
[7] -0.95458323 -1.25955153 0.96288685 -2.45380188 -0.71624020 0.53342596
[13] -0.91281918 1.03982398 0.18899342 0.08320925 -0.48745566 -0.30347331
[19] -0.95022268 0.73845005 -1.50951413 0.25424936 -0.68604857 1.48870252
[25] 1.19518142 1.19922486 0.22290516 1.24908873 0.14012282 1.14934886
[31] -0.11493984 -1.59597031 -1.29425022 1.04681745 1.48395299 -1.18912894
[37] 0.66513779 -0.37251162 0.54985658 0.95772807 -2.67152027 1.51664790
[43] 0.39221913 -0.12980615 1.61664042 -0.96066388 1.20906116 0.04863015
[49] -0.27710941 -0.11782010 -0.91572395 -0.48687859 0.34112564 -2.13393674
[55] -1.17618246 -1.97976839 -1.00289955 -0.34804023 1.04971403 0.03872986
[61] 1.24734405 -0.87920111 0.13828871 -1.18728501 0.59254525 -0.17229405
[67] 0.48640851 0.19472282 -0.42923570 0.15016345 -0.81734705 0.70507504
[73] -0.18443973 -1.02225375 -1.77943713 -1.18173501 0.59853617 -0.28492036
[79] 0.25791211 0.25041664 1.03786219 -1.23908069 0.98226849 0.39143785
[85] 0.03932415 0.82360965 0.52712142 -0.55817651 -1.52400739 -0.89511393
[91] -0.08674030 -0.50775534 -0.25189174 -0.81857175 1.33933375 1.75151653
[97] -0.64764593 0.13458073 -0.35519049 0.97459383
> 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] -0.35043373 0.52568079 -1.16764135 -1.83774634 -0.48519304 -0.89771507
[7] -0.95458323 -1.25955153 0.96288685 -2.45380188 -0.71624020 0.53342596
[13] -0.91281918 1.03982398 0.18899342 0.08320925 -0.48745566 -0.30347331
[19] -0.95022268 0.73845005 -1.50951413 0.25424936 -0.68604857 1.48870252
[25] 1.19518142 1.19922486 0.22290516 1.24908873 0.14012282 1.14934886
[31] -0.11493984 -1.59597031 -1.29425022 1.04681745 1.48395299 -1.18912894
[37] 0.66513779 -0.37251162 0.54985658 0.95772807 -2.67152027 1.51664790
[43] 0.39221913 -0.12980615 1.61664042 -0.96066388 1.20906116 0.04863015
[49] -0.27710941 -0.11782010 -0.91572395 -0.48687859 0.34112564 -2.13393674
[55] -1.17618246 -1.97976839 -1.00289955 -0.34804023 1.04971403 0.03872986
[61] 1.24734405 -0.87920111 0.13828871 -1.18728501 0.59254525 -0.17229405
[67] 0.48640851 0.19472282 -0.42923570 0.15016345 -0.81734705 0.70507504
[73] -0.18443973 -1.02225375 -1.77943713 -1.18173501 0.59853617 -0.28492036
[79] 0.25791211 0.25041664 1.03786219 -1.23908069 0.98226849 0.39143785
[85] 0.03932415 0.82360965 0.52712142 -0.55817651 -1.52400739 -0.89511393
[91] -0.08674030 -0.50775534 -0.25189174 -0.81857175 1.33933375 1.75151653
[97] -0.64764593 0.13458073 -0.35519049 0.97459383
> colMin(tmp)
[1] -0.35043373 0.52568079 -1.16764135 -1.83774634 -0.48519304 -0.89771507
[7] -0.95458323 -1.25955153 0.96288685 -2.45380188 -0.71624020 0.53342596
[13] -0.91281918 1.03982398 0.18899342 0.08320925 -0.48745566 -0.30347331
[19] -0.95022268 0.73845005 -1.50951413 0.25424936 -0.68604857 1.48870252
[25] 1.19518142 1.19922486 0.22290516 1.24908873 0.14012282 1.14934886
[31] -0.11493984 -1.59597031 -1.29425022 1.04681745 1.48395299 -1.18912894
[37] 0.66513779 -0.37251162 0.54985658 0.95772807 -2.67152027 1.51664790
[43] 0.39221913 -0.12980615 1.61664042 -0.96066388 1.20906116 0.04863015
[49] -0.27710941 -0.11782010 -0.91572395 -0.48687859 0.34112564 -2.13393674
[55] -1.17618246 -1.97976839 -1.00289955 -0.34804023 1.04971403 0.03872986
[61] 1.24734405 -0.87920111 0.13828871 -1.18728501 0.59254525 -0.17229405
[67] 0.48640851 0.19472282 -0.42923570 0.15016345 -0.81734705 0.70507504
[73] -0.18443973 -1.02225375 -1.77943713 -1.18173501 0.59853617 -0.28492036
[79] 0.25791211 0.25041664 1.03786219 -1.23908069 0.98226849 0.39143785
[85] 0.03932415 0.82360965 0.52712142 -0.55817651 -1.52400739 -0.89511393
[91] -0.08674030 -0.50775534 -0.25189174 -0.81857175 1.33933375 1.75151653
[97] -0.64764593 0.13458073 -0.35519049 0.97459383
> colMedians(tmp)
[1] -0.35043373 0.52568079 -1.16764135 -1.83774634 -0.48519304 -0.89771507
[7] -0.95458323 -1.25955153 0.96288685 -2.45380188 -0.71624020 0.53342596
[13] -0.91281918 1.03982398 0.18899342 0.08320925 -0.48745566 -0.30347331
[19] -0.95022268 0.73845005 -1.50951413 0.25424936 -0.68604857 1.48870252
[25] 1.19518142 1.19922486 0.22290516 1.24908873 0.14012282 1.14934886
[31] -0.11493984 -1.59597031 -1.29425022 1.04681745 1.48395299 -1.18912894
[37] 0.66513779 -0.37251162 0.54985658 0.95772807 -2.67152027 1.51664790
[43] 0.39221913 -0.12980615 1.61664042 -0.96066388 1.20906116 0.04863015
[49] -0.27710941 -0.11782010 -0.91572395 -0.48687859 0.34112564 -2.13393674
[55] -1.17618246 -1.97976839 -1.00289955 -0.34804023 1.04971403 0.03872986
[61] 1.24734405 -0.87920111 0.13828871 -1.18728501 0.59254525 -0.17229405
[67] 0.48640851 0.19472282 -0.42923570 0.15016345 -0.81734705 0.70507504
[73] -0.18443973 -1.02225375 -1.77943713 -1.18173501 0.59853617 -0.28492036
[79] 0.25791211 0.25041664 1.03786219 -1.23908069 0.98226849 0.39143785
[85] 0.03932415 0.82360965 0.52712142 -0.55817651 -1.52400739 -0.89511393
[91] -0.08674030 -0.50775534 -0.25189174 -0.81857175 1.33933375 1.75151653
[97] -0.64764593 0.13458073 -0.35519049 0.97459383
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.3504337 0.5256808 -1.167641 -1.837746 -0.485193 -0.8977151 -0.9545832
[2,] -0.3504337 0.5256808 -1.167641 -1.837746 -0.485193 -0.8977151 -0.9545832
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.259552 0.9628868 -2.453802 -0.7162402 0.533426 -0.9128192 1.039824
[2,] -1.259552 0.9628868 -2.453802 -0.7162402 0.533426 -0.9128192 1.039824
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.1889934 0.08320925 -0.4874557 -0.3034733 -0.9502227 0.73845 -1.509514
[2,] 0.1889934 0.08320925 -0.4874557 -0.3034733 -0.9502227 0.73845 -1.509514
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.2542494 -0.6860486 1.488703 1.195181 1.199225 0.2229052 1.249089
[2,] 0.2542494 -0.6860486 1.488703 1.195181 1.199225 0.2229052 1.249089
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.1401228 1.149349 -0.1149398 -1.59597 -1.29425 1.046817 1.483953
[2,] 0.1401228 1.149349 -0.1149398 -1.59597 -1.29425 1.046817 1.483953
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.189129 0.6651378 -0.3725116 0.5498566 0.9577281 -2.67152 1.516648
[2,] -1.189129 0.6651378 -0.3725116 0.5498566 0.9577281 -2.67152 1.516648
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.3922191 -0.1298061 1.61664 -0.9606639 1.209061 0.04863015 -0.2771094
[2,] 0.3922191 -0.1298061 1.61664 -0.9606639 1.209061 0.04863015 -0.2771094
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.1178201 -0.915724 -0.4868786 0.3411256 -2.133937 -1.176182 -1.979768
[2,] -0.1178201 -0.915724 -0.4868786 0.3411256 -2.133937 -1.176182 -1.979768
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -1.0029 -0.3480402 1.049714 0.03872986 1.247344 -0.8792011 0.1382887
[2,] -1.0029 -0.3480402 1.049714 0.03872986 1.247344 -0.8792011 0.1382887
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.187285 0.5925452 -0.172294 0.4864085 0.1947228 -0.4292357 0.1501635
[2,] -1.187285 0.5925452 -0.172294 0.4864085 0.1947228 -0.4292357 0.1501635
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.8173471 0.705075 -0.1844397 -1.022254 -1.779437 -1.181735 0.5985362
[2,] -0.8173471 0.705075 -0.1844397 -1.022254 -1.779437 -1.181735 0.5985362
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.2849204 0.2579121 0.2504166 1.037862 -1.239081 0.9822685 0.3914378
[2,] -0.2849204 0.2579121 0.2504166 1.037862 -1.239081 0.9822685 0.3914378
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.03932415 0.8236096 0.5271214 -0.5581765 -1.524007 -0.8951139 -0.0867403
[2,] 0.03932415 0.8236096 0.5271214 -0.5581765 -1.524007 -0.8951139 -0.0867403
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.5077553 -0.2518917 -0.8185717 1.339334 1.751517 -0.6476459 0.1345807
[2,] -0.5077553 -0.2518917 -0.8185717 1.339334 1.751517 -0.6476459 0.1345807
[,99] [,100]
[1,] -0.3551905 0.9745938
[2,] -0.3551905 0.9745938
>
>
> Max(tmp2)
[1] 2.471022
> Min(tmp2)
[1] -2.889624
> mean(tmp2)
[1] 0.0233452
> Sum(tmp2)
[1] 2.33452
> Var(tmp2)
[1] 1.171783
>
> rowMeans(tmp2)
[1] -1.280444030 0.819221850 -0.046485365 -0.679977503 -0.133946613
[6] 0.660080414 -0.469711101 1.408767879 -0.036020654 -1.172012493
[11] -1.001319545 -1.592158879 -0.044051691 -1.474802756 -0.883482357
[16] 0.046665936 0.171656404 1.380624770 0.378192303 0.634494779
[21] -0.159768862 -0.526304139 0.701655138 0.125237963 -0.003693129
[26] 0.359840686 -0.805214627 2.447464749 -0.306614134 0.692561968
[31] 1.609368964 -0.332288632 1.054586405 -1.053002402 -0.640966539
[36] 0.386528988 -1.046849050 0.244757230 -0.134786237 -0.877190806
[41] 1.058591473 0.114524442 -1.225194214 2.016995922 1.176907268
[46] -1.288145319 -1.176681708 0.908644201 0.498000740 -1.329940430
[51] 1.441204801 0.751829111 -0.542716027 -2.308340070 -1.989403199
[56] 1.389243651 -0.318430055 1.188256668 -0.807826227 -2.889623672
[61] 0.129717106 0.099532475 0.287091277 1.749759649 0.279374823
[66] 1.840241992 -0.437830404 0.184421574 -1.135889744 0.794544685
[71] 0.434300805 -0.492853695 1.013126918 1.091264170 2.471021734
[76] -0.656245019 -0.672239760 -1.129492915 -0.190381039 -0.522729846
[81] -0.225740585 -2.563194897 2.134980841 1.466070149 -0.002441474
[86] -0.343876269 0.023906468 -0.620276579 0.829511015 0.349827937
[91] 0.053211026 -0.667710932 0.687660091 0.413408998 -0.022098922
[96] 0.421644900 1.700879071 0.972746226 -2.509014467 0.009780414
> rowSums(tmp2)
[1] -1.280444030 0.819221850 -0.046485365 -0.679977503 -0.133946613
[6] 0.660080414 -0.469711101 1.408767879 -0.036020654 -1.172012493
[11] -1.001319545 -1.592158879 -0.044051691 -1.474802756 -0.883482357
[16] 0.046665936 0.171656404 1.380624770 0.378192303 0.634494779
[21] -0.159768862 -0.526304139 0.701655138 0.125237963 -0.003693129
[26] 0.359840686 -0.805214627 2.447464749 -0.306614134 0.692561968
[31] 1.609368964 -0.332288632 1.054586405 -1.053002402 -0.640966539
[36] 0.386528988 -1.046849050 0.244757230 -0.134786237 -0.877190806
[41] 1.058591473 0.114524442 -1.225194214 2.016995922 1.176907268
[46] -1.288145319 -1.176681708 0.908644201 0.498000740 -1.329940430
[51] 1.441204801 0.751829111 -0.542716027 -2.308340070 -1.989403199
[56] 1.389243651 -0.318430055 1.188256668 -0.807826227 -2.889623672
[61] 0.129717106 0.099532475 0.287091277 1.749759649 0.279374823
[66] 1.840241992 -0.437830404 0.184421574 -1.135889744 0.794544685
[71] 0.434300805 -0.492853695 1.013126918 1.091264170 2.471021734
[76] -0.656245019 -0.672239760 -1.129492915 -0.190381039 -0.522729846
[81] -0.225740585 -2.563194897 2.134980841 1.466070149 -0.002441474
[86] -0.343876269 0.023906468 -0.620276579 0.829511015 0.349827937
[91] 0.053211026 -0.667710932 0.687660091 0.413408998 -0.022098922
[96] 0.421644900 1.700879071 0.972746226 -2.509014467 0.009780414
> 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] -1.280444030 0.819221850 -0.046485365 -0.679977503 -0.133946613
[6] 0.660080414 -0.469711101 1.408767879 -0.036020654 -1.172012493
[11] -1.001319545 -1.592158879 -0.044051691 -1.474802756 -0.883482357
[16] 0.046665936 0.171656404 1.380624770 0.378192303 0.634494779
[21] -0.159768862 -0.526304139 0.701655138 0.125237963 -0.003693129
[26] 0.359840686 -0.805214627 2.447464749 -0.306614134 0.692561968
[31] 1.609368964 -0.332288632 1.054586405 -1.053002402 -0.640966539
[36] 0.386528988 -1.046849050 0.244757230 -0.134786237 -0.877190806
[41] 1.058591473 0.114524442 -1.225194214 2.016995922 1.176907268
[46] -1.288145319 -1.176681708 0.908644201 0.498000740 -1.329940430
[51] 1.441204801 0.751829111 -0.542716027 -2.308340070 -1.989403199
[56] 1.389243651 -0.318430055 1.188256668 -0.807826227 -2.889623672
[61] 0.129717106 0.099532475 0.287091277 1.749759649 0.279374823
[66] 1.840241992 -0.437830404 0.184421574 -1.135889744 0.794544685
[71] 0.434300805 -0.492853695 1.013126918 1.091264170 2.471021734
[76] -0.656245019 -0.672239760 -1.129492915 -0.190381039 -0.522729846
[81] -0.225740585 -2.563194897 2.134980841 1.466070149 -0.002441474
[86] -0.343876269 0.023906468 -0.620276579 0.829511015 0.349827937
[91] 0.053211026 -0.667710932 0.687660091 0.413408998 -0.022098922
[96] 0.421644900 1.700879071 0.972746226 -2.509014467 0.009780414
> rowMin(tmp2)
[1] -1.280444030 0.819221850 -0.046485365 -0.679977503 -0.133946613
[6] 0.660080414 -0.469711101 1.408767879 -0.036020654 -1.172012493
[11] -1.001319545 -1.592158879 -0.044051691 -1.474802756 -0.883482357
[16] 0.046665936 0.171656404 1.380624770 0.378192303 0.634494779
[21] -0.159768862 -0.526304139 0.701655138 0.125237963 -0.003693129
[26] 0.359840686 -0.805214627 2.447464749 -0.306614134 0.692561968
[31] 1.609368964 -0.332288632 1.054586405 -1.053002402 -0.640966539
[36] 0.386528988 -1.046849050 0.244757230 -0.134786237 -0.877190806
[41] 1.058591473 0.114524442 -1.225194214 2.016995922 1.176907268
[46] -1.288145319 -1.176681708 0.908644201 0.498000740 -1.329940430
[51] 1.441204801 0.751829111 -0.542716027 -2.308340070 -1.989403199
[56] 1.389243651 -0.318430055 1.188256668 -0.807826227 -2.889623672
[61] 0.129717106 0.099532475 0.287091277 1.749759649 0.279374823
[66] 1.840241992 -0.437830404 0.184421574 -1.135889744 0.794544685
[71] 0.434300805 -0.492853695 1.013126918 1.091264170 2.471021734
[76] -0.656245019 -0.672239760 -1.129492915 -0.190381039 -0.522729846
[81] -0.225740585 -2.563194897 2.134980841 1.466070149 -0.002441474
[86] -0.343876269 0.023906468 -0.620276579 0.829511015 0.349827937
[91] 0.053211026 -0.667710932 0.687660091 0.413408998 -0.022098922
[96] 0.421644900 1.700879071 0.972746226 -2.509014467 0.009780414
>
> colMeans(tmp2)
[1] 0.0233452
> colSums(tmp2)
[1] 2.33452
> colVars(tmp2)
[1] 1.171783
> colSd(tmp2)
[1] 1.082489
> colMax(tmp2)
[1] 2.471022
> colMin(tmp2)
[1] -2.889624
> colMedians(tmp2)
[1] 0.01684344
> colRanges(tmp2)
[,1]
[1,] -2.889624
[2,] 2.471022
>
> 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] -2.76030783 1.85387447 -0.73600967 3.73665475 2.61023513 -0.52906915
[7] -3.88177653 -2.00098979 -0.46242219 0.07007581
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.6183332
[2,] -0.9191822
[3,] -0.3178854
[4,] 0.5664576
[5,] 1.3663793
>
> rowApply(tmp,sum)
[1] -6.8789805 0.9230215 0.6960309 1.3247280 -5.9844772 2.5123945
[7] -0.3819283 0.3778165 4.8070936 0.5045660
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 8 8 2 7 2 8 1 2 10
[2,] 5 9 6 1 8 10 7 10 3 7
[3,] 2 3 10 10 4 3 1 5 5 3
[4,] 9 6 9 8 5 6 6 4 8 5
[5,] 8 7 4 3 10 4 10 6 7 4
[6,] 6 2 3 4 6 5 9 9 4 1
[7,] 10 4 5 5 1 1 2 8 6 6
[8,] 3 5 1 6 9 9 5 7 10 2
[9,] 7 10 7 7 2 8 4 3 1 9
[10,] 4 1 2 9 3 7 3 2 9 8
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 4.9888404 -1.3823473 5.7196820 1.4932903 -1.8050747 -3.4923410
[7] 1.3483006 -1.2214338 0.9016658 -0.5652086 -3.2208256 6.9070959
[13] 0.2086798 -1.0488994 -0.8206585 1.6659175 0.5156931 -3.3274206
[19] 0.1694588 2.3823543
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.6845238
[2,] 0.9973330
[3,] 1.1896813
[4,] 1.5860346
[5,] 1.9003152
>
> rowApply(tmp,sum)
[1] 3.3040152 9.2944595 -1.2816330 -0.1876534 -1.7124194
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 5 16 19 20 18
[2,] 7 14 2 13 8
[3,] 17 19 13 19 15
[4,] 20 6 16 9 7
[5,] 2 4 5 14 17
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.6845238 -0.52099852 1.36382338 2.1198352 -1.4339087 -0.6715987
[2,] 0.9973330 0.92334024 1.93076683 -0.2451073 -0.4956898 0.3137501
[3,] 1.5860346 -1.26809679 0.01057649 0.6231579 -1.0813786 -1.8915583
[4,] 1.9003152 0.05145372 1.79272081 -0.3815219 0.2582977 -1.9069310
[5,] 1.1896813 -0.56804597 0.62179449 -0.6230737 0.9476047 0.6639969
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.36976574 0.4829851 0.5647714 0.53286064 -0.77997591 0.2718572
[2,] 2.30537702 0.6459259 0.9697421 0.02824829 -0.61976999 1.9139025
[3,] -0.56009754 -0.3600118 -1.0713748 0.53571317 -0.07934573 2.1102007
[4,] -0.09625782 -0.7035575 -0.8909427 0.44254198 -0.61153758 1.1397789
[5,] 0.06904468 -1.2867756 1.3294697 -2.10457273 -1.13019643 1.4713567
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.76283552 -1.73325376 1.3906558 0.4956562 0.4597431 -0.78540152
[2,] -0.07467869 0.58896234 -1.1062050 1.1239298 -0.2638663 -0.74198243
[3,] -0.04816217 1.41733613 -1.0931402 -1.1673943 0.2259110 -0.23133341
[4,] -0.48808003 -0.02969943 -0.5146252 1.3164834 -0.5100423 0.02505338
[5,] -0.94323479 -1.29224468 0.5026561 -0.1027575 0.6039477 -1.59375662
[,19] [,20]
[1,] 0.7826302 0.05578803
[2,] 0.8638508 0.23663019
[3,] -0.4101659 1.47149660
[4,] -1.5760348 0.59493165
[5,] 0.5091785 0.02350785
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 649 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 563 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.1934751 1.390332 -0.6245899 1.774442 -1.403148 0.6437919 -0.3354652
col8 col9 col10 col11 col12 col13 col14
row1 -0.1400864 1.061113 -0.7509705 -1.063901 1.413365 -1.599693 -0.1960182
col15 col16 col17 col18 col19 col20
row1 0.3411939 -0.5463749 -1.293938 0.5278799 -0.242992 0.1842607
> tmp[,"col10"]
col10
row1 -0.750970536
row2 -0.009259163
row3 -0.360167535
row4 -2.110184575
row5 -0.490877102
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.1934751 1.3903316 -0.6245899 1.774442 -1.4031483 0.6437919 -0.3354652
row5 0.3393170 0.5005943 0.2155613 2.071402 -0.1298506 -0.4192224 -0.1926035
col8 col9 col10 col11 col12 col13
row1 -0.1400864 1.0611130 -0.7509705 -1.06390078 1.41336513 -1.599693
row5 -0.1823079 0.1773905 -0.4908771 -0.08997703 0.01650737 -0.359911
col14 col15 col16 col17 col18 col19 col20
row1 -0.1960182 0.3411939 -0.5463749 -1.2939385 0.5278799 -0.2429920 0.1842607
row5 0.7518109 1.0510360 0.5108146 0.2710688 -1.5109564 -0.6672977 0.4835405
> tmp[,c("col6","col20")]
col6 col20
row1 0.6437919 0.1842607
row2 1.4526485 0.6236176
row3 -0.3818453 0.5515134
row4 1.5846815 -0.3578084
row5 -0.4192224 0.4835405
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.6437919 0.1842607
row5 -0.4192224 0.4835405
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.1609 49.97035 49.39337 52.47213 50.68065 104.8153 51.21843 49.43453
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.14371 48.29816 50.1564 50.38376 50.62588 48.9022 49.9185 49.12568
col17 col18 col19 col20
row1 50.75212 49.43568 47.67167 105.2121
> tmp[,"col10"]
col10
row1 48.29816
row2 29.21584
row3 29.08324
row4 28.88618
row5 50.07045
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.16090 49.97035 49.39337 52.47213 50.68065 104.8153 51.21843 49.43453
row5 47.38464 51.12914 49.74793 49.17820 49.09129 103.4160 50.04344 50.28694
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.14371 48.29816 50.15640 50.38376 50.62588 48.90220 49.9185 49.12568
row5 49.70414 50.07045 48.23751 48.46671 48.93777 50.61809 51.4888 49.86845
col17 col18 col19 col20
row1 50.75212 49.43568 47.67167 105.2121
row5 49.80843 50.53601 51.32582 105.5957
> tmp[,c("col6","col20")]
col6 col20
row1 104.81530 105.21212
row2 74.11445 74.73592
row3 75.33264 75.03060
row4 74.64170 75.27619
row5 103.41602 105.59567
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.8153 105.2121
row5 103.4160 105.5957
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.8153 105.2121
row5 103.4160 105.5957
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.1695858
[2,] 0.3711315
[3,] -0.8506665
[4,] 1.6435079
[5,] 2.2241375
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.01840163 -0.5108183
[2,] 0.45331726 0.5124735
[3,] 0.75973855 0.8776009
[4,] -0.10963137 0.4473261
[5,] 0.99061168 0.2465651
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.4724669 -1.1171922
[2,] 0.9586907 -0.7505321
[3,] -0.2390857 -0.5501943
[4,] 1.3956359 1.2285308
[5,] -0.1345147 0.5139646
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.4724669
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.4724669
[2,] 0.9586907
>
>
>
> 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 -0.4063193 0.7992088 -0.93698028 -0.3385527 -1.8062309 -1.5205982
row1 0.9059050 -0.6819158 0.07088597 1.8477675 -0.3690454 -0.2419491
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 0.6180941 -0.2899308 -0.9737575 -0.197625 0.3663301 0.5630790 0.4188058
row1 -1.1916514 -2.7517198 -0.3684207 1.232114 -0.7490245 0.0153192 0.9244464
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.6675871 -0.5223952 -0.3883847 -1.57635436 -0.4337013 -0.3683053
row1 0.1194561 -0.1165421 -0.6067877 -0.07417176 0.1526776 1.3004173
[,20]
row3 0.9002980
row1 -0.4886884
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.2926573 0.06861602 0.5552556 1.563884 1.879156 0.9439802 1.47774
[,8] [,9] [,10]
row2 -0.8565675 0.8399576 1.492665
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.5475095 -0.5254279 0.9251613 1.587361 -0.05043592 0.5614599 -1.60448
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.6129035 -0.3703102 -0.760789 -0.644066 1.721319 2.001515 0.3138998
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.2552079 -0.3895617 -0.2036389 0.5123627 0.4004575 0.09761244
>
>
> 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: 0x600001d34060>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3cdb3d8bea30"
[2] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3cdb2cbc14e1"
[3] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3cdb6ffed6b8"
[4] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3cdb43c30379"
[5] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3cdb38191fb0"
[6] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3cdb796f7895"
[7] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3cdb555bc7c"
[8] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3cdb3fc973a0"
[9] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3cdb42c62e17"
[10] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3cdb60fc0a40"
[11] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3cdb4305217e"
[12] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3cdb5d9f992"
[13] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3cdb298fe33e"
[14] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3cdb259010c3"
[15] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3cdb153c8579"
>
>
> ### 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: 0x600001d60420>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600001d60420>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600001d60420>
> rowMedians(tmp)
[1] 0.181901907 0.089841551 -0.538835866 0.010408441 0.105003236
[6] -0.175124913 0.103409832 0.088264590 -0.312591277 0.080989441
[11] -0.114360072 0.290808572 0.192468850 -0.073096374 -0.057173344
[16] -0.207709177 -0.089338675 -0.498074708 0.058694551 0.371375975
[21] -0.135558590 0.387626140 0.155314075 -0.134632389 -0.538104840
[26] 0.679621922 0.436952893 0.205971147 0.151639571 0.350884937
[31] -0.366588351 -0.395139514 0.820320018 0.630662340 0.116683098
[36] -0.617807524 -0.111922956 0.157057871 0.369122418 0.358704002
[41] -0.018828083 0.048398869 -0.314260825 0.515442932 0.151299504
[46] -0.115852767 -0.208474393 0.223502817 -0.015989536 -0.236060515
[51] 0.070407620 0.164424054 0.052123557 -0.360138061 -0.001574299
[56] -0.411656219 0.060918441 0.219414029 0.001614645 -0.381777837
[61] -0.097011773 0.118190957 -0.032004070 -0.112643173 -0.024253338
[66] 0.068722834 -0.097546117 0.023699350 -0.286453777 -0.496548427
[71] -0.058533388 -0.365813809 0.333292484 0.080590615 0.238846125
[76] 0.039567149 -0.396967686 0.214119805 -0.045256570 0.343338807
[81] 0.151130494 0.057610734 0.078367615 0.245636619 -0.152071464
[86] 0.086710885 0.248296842 0.031612678 0.107062402 -0.110160559
[91] -0.418426423 -0.300551560 -0.394331971 0.114894305 0.374626671
[96] 0.031192647 0.483437855 -0.146471588 0.353859184 0.374472036
[101] 0.150804734 -0.088972500 -0.076793755 0.114553998 0.175130763
[106] -0.290786385 -0.155823601 -0.631354690 0.718315388 0.471174411
[111] 0.723894789 0.146283100 0.549192019 -0.333800387 -0.271168057
[116] 0.044369006 -0.349392744 0.181353604 0.170066895 -0.019670169
[121] 0.272367240 -0.176899012 -0.347306181 -0.282855618 0.047459923
[126] -0.299128617 0.062768519 0.294009079 0.284237060 -0.420122629
[131] -0.403313129 0.233879315 -0.481915211 -0.134304800 0.576328731
[136] 0.262382930 -0.220316322 -0.045302960 0.498143881 -0.012032846
[141] -0.194349414 -0.213508663 0.020011931 -0.829104498 0.235945587
[146] -0.399369369 0.272506100 -0.484032937 0.459834639 -0.284856749
[151] -0.572355851 -0.385124288 -0.247995353 0.188512150 -0.053262965
[156] -0.164913444 -0.062205640 0.214276090 0.262102354 -0.276502580
[161] 0.022051232 -0.037163874 0.208870335 -0.235289785 -0.714848917
[166] -0.116283098 -0.311226159 0.522350160 0.256152693 0.145592044
[171] 0.110396501 -0.018808796 -0.040681613 0.147253689 -0.455686969
[176] 0.192501757 -0.339812305 0.005553184 0.165859317 0.368367594
[181] -0.130714879 -0.073331567 -0.370307505 0.276002025 0.011915289
[186] 0.093100087 0.396401348 0.279743578 0.234580428 -0.699609056
[191] 0.321873847 0.026876243 0.421142907 0.265530830 0.598273191
[196] -0.327621629 -0.041216098 -0.449349391 0.060133598 0.435539552
[201] 0.079672880 0.348864150 -0.403953127 -0.277264336 -0.068687635
[206] 0.105125651 -0.161788485 0.242877566 -0.385777931 -0.678181012
[211] 0.049299458 0.163528001 0.144758847 -0.309937777 0.057672901
[216] -0.201420841 -0.195488365 -0.163777906 0.076531770 -0.457934577
[221] 0.251305464 -0.278253585 0.184223254 -0.216175727 -0.262923405
[226] 0.056933031 0.576805235 0.050923978 0.358697818 -0.525916632
>
> proc.time()
user system elapsed
2.747 15.837 82.244
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.1 (2025-06-13) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x60000133c000>
> .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: 0x60000133c000>
> .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: 0x60000133c000>
> .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: 0x60000133c000>
> 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: 0x600001330000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001330000>
> .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: 0x600001330000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001330000>
> .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: 0x600001330000>
> 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: 0x600001334000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001334000>
> .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: 0x600001334000>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600001334000>
> .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: 0x600001334000>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600001334000>
> .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: 0x600001334000>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600001334000>
> .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: 0x600001334000>
> 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: 0x600001304120>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600001304120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001304120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001304120>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile4ecf5daef4a1" "BufferedMatrixFile4ecf93ea614"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile4ecf5daef4a1" "BufferedMatrixFile4ecf93ea614"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001338120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001338120>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600001338120>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600001338120>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600001338120>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600001338120>
> .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: 0x600001348000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001348000>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600001348000>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600001348000>
> 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: 0x600001348180>
> .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: 0x600001348180>
> rm(P)
>
> proc.time()
user system elapsed
0.336 0.134 0.464
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.1 (2025-06-13) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
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.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.343 0.091 0.431