Ben Bolstad
| Snapshot Date: 2025-06-18 13:25 -0400 (Wed, 18 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 2025-06-19 12:04 -0400 (Thu, 19 Jun 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.2 LTS) | x86_64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4810 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.5.0 (2025-04-11 ucrt) -- "How About a Twenty-Six" | 4548 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | 4.5.0 Patched (2025-04-21 r88169) -- "How About a Twenty-Six" | 4528 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4493 |
| 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 250/2309 | 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 | | ||||||||
| 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: 2025-06-18 18:20:42 -0400 (Wed, 18 Jun 2025) |
| EndedAt: 2025-06-18 18:20:58 -0400 (Wed, 18 Jun 2025) |
| EllapsedTime: 16.2 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 4.5.0 Patched (2025-04-21 r88169)
* 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 13.7.1
* 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 15.0.0 (clang-1500.1.0.2.5)’
* 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-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.73.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
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 4.5.0 Patched (2025-04-21 r88169) -- "How About a Twenty-Six"
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
0.111 0.041 0.148
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.0 Patched (2025-04-21 r88169) -- "How About a Twenty-Six"
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-3.22-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 480809 25.7 1056570 56.5 NA 634340 33.9
Vcells 890978 6.8 8388608 64.0 196608 2109658 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] "Wed Jun 18 18:20:51 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] "Wed Jun 18 18:20:51 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: 0x600003368000>
>
>
>
> 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] "Wed Jun 18 18:20:52 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed Jun 18 18:20:52 2025"
>
> ColMode(tmp2)
<pointer: 0x600003368000>
>
>
>
> ### 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,] 98.6081189 1.3165675 0.4135951 0.6384698
[2,] -0.2870285 -0.4123004 0.8387638 -0.0718987
[3,] 0.7260045 0.3644875 -2.3320882 -3.5300452
[4,] 0.4845135 -0.8717581 1.0383076 -0.8765256
> 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,] 98.6081189 1.3165675 0.4135951 0.6384698
[2,] 0.2870285 0.4123004 0.8387638 0.0718987
[3,] 0.7260045 0.3644875 2.3320882 3.5300452
[4,] 0.4845135 0.8717581 1.0383076 0.8765256
> 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,] 9.9301621 1.1474177 0.6431136 0.7990430
[2,] 0.5357504 0.6421062 0.9158405 0.2681393
[3,] 0.8520590 0.6037280 1.5271176 1.8788415
[4,] 0.6960700 0.9336799 1.0189738 0.9362295
>
> 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,] 222.90974 37.79074 31.84473 33.62890
[2,] 30.64453 31.83336 34.99717 27.75329
[3,] 34.24659 31.40177 42.60326 47.31846
[4,] 32.44521 35.20856 36.22805 35.23882
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600003364000>
> exp(tmp5)
<pointer: 0x600003364000>
> log(tmp5,2)
<pointer: 0x600003364000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 463.9574
> Min(tmp5)
[1] 52.51605
> mean(tmp5)
[1] 71.63529
> Sum(tmp5)
[1] 14327.06
> Var(tmp5)
[1] 846.7005
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.60321 69.65327 73.39685 70.18989 68.70081 68.01277 69.40610 69.88309
[9] 67.27462 70.23226
> rowSums(tmp5)
[1] 1792.064 1393.065 1467.937 1403.798 1374.016 1360.255 1388.122 1397.662
[9] 1345.492 1404.645
> rowVars(tmp5)
[1] 7798.63205 60.65764 112.99210 114.91511 81.16278 42.44814
[7] 63.15591 44.67681 82.93516 63.63032
> rowSd(tmp5)
[1] 88.309864 7.788301 10.629774 10.719846 9.009039 6.515224 7.947069
[8] 6.684072 9.106875 7.976862
> rowMax(tmp5)
[1] 463.95742 83.31209 98.48717 93.11057 89.25081 82.41935 87.62581
[8] 81.38898 87.29711 90.76845
> rowMin(tmp5)
[1] 58.37094 56.29391 57.62351 55.47885 52.51605 59.23872 56.88337 58.51186
[9] 53.34695 59.04466
>
> colMeans(tmp5)
[1] 108.04549 67.58144 71.88884 71.37965 71.28361 71.58595 70.40507
[8] 74.35338 65.37055 69.26657 68.22945 66.10569 70.30446 72.75684
[15] 70.34960 69.60649 70.66506 70.30555 65.59308 67.62897
> colSums(tmp5)
[1] 1080.4549 675.8144 718.8884 713.7965 712.8361 715.8595 704.0507
[8] 743.5338 653.7055 692.6657 682.2945 661.0569 703.0446 727.5684
[15] 703.4960 696.0649 706.6506 703.0555 655.9308 676.2897
> colVars(tmp5)
[1] 15667.44988 63.91706 75.18238 140.30418 56.44003 88.52674
[7] 67.43932 95.22705 50.32861 84.70144 52.29909 109.80751
[13] 59.72694 72.16917 79.30119 51.57137 25.33143 117.99214
[19] 40.70480 53.74155
> colSd(tmp5)
[1] 125.169684 7.994814 8.670777 11.845007 7.512658 9.408865
[7] 8.212145 9.758435 7.094266 9.203339 7.231811 10.478908
[13] 7.728320 8.495244 8.905122 7.181321 5.033034 10.862419
[19] 6.380032 7.330863
> colMax(tmp5)
[1] 463.95742 78.65648 88.67311 98.48717 82.41935 87.29711 83.58872
[8] 90.76845 77.25479 89.25081 80.54096 82.03809 82.57484 87.62581
[15] 93.11057 83.31209 78.05157 91.65246 75.82961 76.67081
> colMin(tmp5)
[1] 58.06347 57.43829 56.71356 56.88337 59.67780 56.50070 61.33432 62.40588
[9] 57.06841 55.47885 59.23872 56.18382 56.29391 55.84268 58.37094 58.87545
[17] 61.34253 54.09580 53.34695 52.51605
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 89.60321 69.65327 73.39685 70.18989 68.70081 68.01277 69.40610 69.88309
[9] 67.27462 NA
> rowSums(tmp5)
[1] 1792.064 1393.065 1467.937 1403.798 1374.016 1360.255 1388.122 1397.662
[9] 1345.492 NA
> rowVars(tmp5)
[1] 7798.63205 60.65764 112.99210 114.91511 81.16278 42.44814
[7] 63.15591 44.67681 82.93516 64.84345
> rowSd(tmp5)
[1] 88.309864 7.788301 10.629774 10.719846 9.009039 6.515224 7.947069
[8] 6.684072 9.106875 8.052543
> rowMax(tmp5)
[1] 463.95742 83.31209 98.48717 93.11057 89.25081 82.41935 87.62581
[8] 81.38898 87.29711 NA
> rowMin(tmp5)
[1] 58.37094 56.29391 57.62351 55.47885 52.51605 59.23872 56.88337 58.51186
[9] 53.34695 NA
>
> colMeans(tmp5)
[1] 108.04549 67.58144 71.88884 71.37965 71.28361 71.58595 NA
[8] 74.35338 65.37055 69.26657 68.22945 66.10569 70.30446 72.75684
[15] 70.34960 69.60649 70.66506 70.30555 65.59308 67.62897
> colSums(tmp5)
[1] 1080.4549 675.8144 718.8884 713.7965 712.8361 715.8595 NA
[8] 743.5338 653.7055 692.6657 682.2945 661.0569 703.0446 727.5684
[15] 703.4960 696.0649 706.6506 703.0555 655.9308 676.2897
> colVars(tmp5)
[1] 15667.44988 63.91706 75.18238 140.30418 56.44003 88.52674
[7] NA 95.22705 50.32861 84.70144 52.29909 109.80751
[13] 59.72694 72.16917 79.30119 51.57137 25.33143 117.99214
[19] 40.70480 53.74155
> colSd(tmp5)
[1] 125.169684 7.994814 8.670777 11.845007 7.512658 9.408865
[7] NA 9.758435 7.094266 9.203339 7.231811 10.478908
[13] 7.728320 8.495244 8.905122 7.181321 5.033034 10.862419
[19] 6.380032 7.330863
> colMax(tmp5)
[1] 463.95742 78.65648 88.67311 98.48717 82.41935 87.29711 NA
[8] 90.76845 77.25479 89.25081 80.54096 82.03809 82.57484 87.62581
[15] 93.11057 83.31209 78.05157 91.65246 75.82961 76.67081
> colMin(tmp5)
[1] 58.06347 57.43829 56.71356 56.88337 59.67780 56.50070 NA 62.40588
[9] 57.06841 55.47885 59.23872 56.18382 56.29391 55.84268 58.37094 58.87545
[17] 61.34253 54.09580 53.34695 52.51605
>
> Max(tmp5,na.rm=TRUE)
[1] 463.9574
> Min(tmp5,na.rm=TRUE)
[1] 52.51605
> mean(tmp5,na.rm=TRUE)
[1] 71.674
> Sum(tmp5,na.rm=TRUE)
[1] 14263.13
> Var(tmp5,na.rm=TRUE)
[1] 850.6755
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.60321 69.65327 73.39685 70.18989 68.70081 68.01277 69.40610 69.88309
[9] 67.27462 70.56389
> rowSums(tmp5,na.rm=TRUE)
[1] 1792.064 1393.065 1467.937 1403.798 1374.016 1360.255 1388.122 1397.662
[9] 1345.492 1340.714
> rowVars(tmp5,na.rm=TRUE)
[1] 7798.63205 60.65764 112.99210 114.91511 81.16278 42.44814
[7] 63.15591 44.67681 82.93516 64.84345
> rowSd(tmp5,na.rm=TRUE)
[1] 88.309864 7.788301 10.629774 10.719846 9.009039 6.515224 7.947069
[8] 6.684072 9.106875 8.052543
> rowMax(tmp5,na.rm=TRUE)
[1] 463.95742 83.31209 98.48717 93.11057 89.25081 82.41935 87.62581
[8] 81.38898 87.29711 90.76845
> rowMin(tmp5,na.rm=TRUE)
[1] 58.37094 56.29391 57.62351 55.47885 52.51605 59.23872 56.88337 58.51186
[9] 53.34695 59.04466
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.04549 67.58144 71.88884 71.37965 71.28361 71.58595 71.12439
[8] 74.35338 65.37055 69.26657 68.22945 66.10569 70.30446 72.75684
[15] 70.34960 69.60649 70.66506 70.30555 65.59308 67.62897
> colSums(tmp5,na.rm=TRUE)
[1] 1080.4549 675.8144 718.8884 713.7965 712.8361 715.8595 640.1195
[8] 743.5338 653.7055 692.6657 682.2945 661.0569 703.0446 727.5684
[15] 703.4960 696.0649 706.6506 703.0555 655.9308 676.2897
> colVars(tmp5,na.rm=TRUE)
[1] 15667.44988 63.91706 75.18238 140.30418 56.44003 88.52674
[7] 70.04811 95.22705 50.32861 84.70144 52.29909 109.80751
[13] 59.72694 72.16917 79.30119 51.57137 25.33143 117.99214
[19] 40.70480 53.74155
> colSd(tmp5,na.rm=TRUE)
[1] 125.169684 7.994814 8.670777 11.845007 7.512658 9.408865
[7] 8.369475 9.758435 7.094266 9.203339 7.231811 10.478908
[13] 7.728320 8.495244 8.905122 7.181321 5.033034 10.862419
[19] 6.380032 7.330863
> colMax(tmp5,na.rm=TRUE)
[1] 463.95742 78.65648 88.67311 98.48717 82.41935 87.29711 83.58872
[8] 90.76845 77.25479 89.25081 80.54096 82.03809 82.57484 87.62581
[15] 93.11057 83.31209 78.05157 91.65246 75.82961 76.67081
> colMin(tmp5,na.rm=TRUE)
[1] 58.06347 57.43829 56.71356 56.88337 59.67780 56.50070 61.33432 62.40588
[9] 57.06841 55.47885 59.23872 56.18382 56.29391 55.84268 58.37094 58.87545
[17] 61.34253 54.09580 53.34695 52.51605
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.60321 69.65327 73.39685 70.18989 68.70081 68.01277 69.40610 69.88309
[9] 67.27462 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1792.064 1393.065 1467.937 1403.798 1374.016 1360.255 1388.122 1397.662
[9] 1345.492 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 7798.63205 60.65764 112.99210 114.91511 81.16278 42.44814
[7] 63.15591 44.67681 82.93516 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 88.309864 7.788301 10.629774 10.719846 9.009039 6.515224 7.947069
[8] 6.684072 9.106875 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 463.95742 83.31209 98.48717 93.11057 89.25081 82.41935 87.62581
[8] 81.38898 87.29711 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 58.37094 56.29391 57.62351 55.47885 52.51605 59.23872 56.88337 58.51186
[9] 53.34695 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 112.33859 68.38185 71.92515 71.61563 72.57314 70.84493 NaN
[8] 72.52948 65.64808 69.28431 68.57168 65.37460 69.64286 71.86817
[15] 69.91126 69.41187 70.69945 69.60581 65.88954 68.58279
> colSums(tmp5,na.rm=TRUE)
[1] 1011.0473 615.4366 647.3263 644.5407 653.1583 637.6044 0.0000
[8] 652.7653 590.8327 623.5588 617.1451 588.3714 626.7857 646.8135
[15] 629.2014 624.7069 636.2951 626.4523 593.0059 617.2451
> colVars(tmp5,na.rm=TRUE)
[1] 17418.53575 64.69940 84.56534 157.21574 44.78741 93.41510
[7] NA 69.70620 55.75321 95.28559 57.51889 117.52042
[13] 62.26849 72.30576 87.05233 57.59172 28.48455 127.23267
[19] 44.80414 50.22447
> colSd(tmp5,na.rm=TRUE)
[1] 131.979300 8.043594 9.195942 12.538570 6.692340 9.665149
[7] NA 8.349024 7.466807 9.761434 7.584121 10.840684
[13] 7.891039 8.503279 9.330184 7.588921 5.337092 11.279746
[19] 6.693589 7.086922
> colMax(tmp5,na.rm=TRUE)
[1] 463.95742 78.65648 88.67311 98.48717 82.41935 87.29711 -Inf
[8] 89.40133 77.25479 89.25081 80.54096 82.03809 82.57484 87.62581
[15] 93.11057 83.31209 78.05157 91.65246 75.82961 76.67081
> colMin(tmp5,na.rm=TRUE)
[1] 58.06347 57.43829 56.71356 56.88337 64.60692 56.50070 Inf 62.40588
[9] 57.06841 55.47885 59.23872 56.18382 56.29391 55.84268 58.37094 58.87545
[17] 61.34253 54.09580 53.34695 52.51605
>
>
>
>
> 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] 209.8674 246.6339 316.0207 259.5637 287.6330 310.7270 204.8435 257.7771
[9] 317.8124 243.3613
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 209.8674 246.6339 316.0207 259.5637 287.6330 310.7270 204.8435 257.7771
[9] 317.8124 243.3613
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 5.684342e-14 5.684342e-14 0.000000e+00 0.000000e+00 -1.705303e-13
[6] 1.136868e-13 -3.979039e-13 1.705303e-13 2.842171e-14 5.684342e-14
[11] -1.136868e-13 -1.705303e-13 -1.136868e-13 1.136868e-13 0.000000e+00
[16] 4.263256e-14 1.136868e-13 1.136868e-13 4.263256e-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)
+ }
5 20
3 3
9 19
5 18
6 3
8 15
7 5
1 9
10 13
2 20
5 9
3 8
5 18
7 20
10 20
7 3
3 12
6 4
4 9
2 5
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] 2.250877
> Min(tmp)
[1] -2.591901
> mean(tmp)
[1] -0.1132992
> Sum(tmp)
[1] -11.32992
> Var(tmp)
[1] 0.9173422
>
> rowMeans(tmp)
[1] -0.1132992
> rowSums(tmp)
[1] -11.32992
> rowVars(tmp)
[1] 0.9173422
> rowSd(tmp)
[1] 0.9577798
> rowMax(tmp)
[1] 2.250877
> rowMin(tmp)
[1] -2.591901
>
> colMeans(tmp)
[1] -0.43605778 -0.19318661 -0.06104038 1.01839343 2.25087657 0.20360020
[7] -0.03471967 -1.60415640 -1.73953327 1.33443178 -1.82327196 -0.30833515
[13] -0.51700117 -0.46506592 0.84406837 -0.85700792 1.07547081 -1.65519258
[19] 0.86500164 -1.15036539 1.51292361 0.99899831 -0.42268699 -1.29952540
[25] 0.20795126 -1.01321626 -0.16821065 0.82554328 0.26283879 0.82094371
[31] -0.87564513 2.12805372 -1.36695923 -2.22135869 0.05460296 -2.59190144
[37] 0.88313715 -0.53006106 0.08546511 -0.64371601 -0.36590253 -0.31618564
[43] -0.63534565 1.27747068 -0.13885625 -0.31938073 -0.07307086 0.91088931
[49] 0.44148517 -1.66384727 0.62808640 -0.82968128 1.18699402 -0.46702277
[55] -0.50407578 -0.35153318 0.80853643 1.26995966 -1.90500937 -0.76337811
[61] -0.66540819 -1.25941895 0.76932555 -0.55630980 -0.12693648 -0.39322975
[67] -0.63228740 -0.11195262 -0.29931972 -0.99602469 -1.07379904 -0.79879372
[73] 0.99438152 0.16323456 -1.85769641 0.56039461 -0.02655373 -0.55251278
[79] -0.18774564 0.78390833 0.22709930 -0.06867965 -0.13829495 -1.25905068
[85] 0.04396671 0.36985398 0.42313955 0.78414672 -0.31163371 0.44161207
[91] 0.55548599 -0.12036416 0.03477618 0.52616643 0.36481530 -1.16804086
[97] 1.51841270 0.87987886 1.36447332 -1.11515350
> colSums(tmp)
[1] -0.43605778 -0.19318661 -0.06104038 1.01839343 2.25087657 0.20360020
[7] -0.03471967 -1.60415640 -1.73953327 1.33443178 -1.82327196 -0.30833515
[13] -0.51700117 -0.46506592 0.84406837 -0.85700792 1.07547081 -1.65519258
[19] 0.86500164 -1.15036539 1.51292361 0.99899831 -0.42268699 -1.29952540
[25] 0.20795126 -1.01321626 -0.16821065 0.82554328 0.26283879 0.82094371
[31] -0.87564513 2.12805372 -1.36695923 -2.22135869 0.05460296 -2.59190144
[37] 0.88313715 -0.53006106 0.08546511 -0.64371601 -0.36590253 -0.31618564
[43] -0.63534565 1.27747068 -0.13885625 -0.31938073 -0.07307086 0.91088931
[49] 0.44148517 -1.66384727 0.62808640 -0.82968128 1.18699402 -0.46702277
[55] -0.50407578 -0.35153318 0.80853643 1.26995966 -1.90500937 -0.76337811
[61] -0.66540819 -1.25941895 0.76932555 -0.55630980 -0.12693648 -0.39322975
[67] -0.63228740 -0.11195262 -0.29931972 -0.99602469 -1.07379904 -0.79879372
[73] 0.99438152 0.16323456 -1.85769641 0.56039461 -0.02655373 -0.55251278
[79] -0.18774564 0.78390833 0.22709930 -0.06867965 -0.13829495 -1.25905068
[85] 0.04396671 0.36985398 0.42313955 0.78414672 -0.31163371 0.44161207
[91] 0.55548599 -0.12036416 0.03477618 0.52616643 0.36481530 -1.16804086
[97] 1.51841270 0.87987886 1.36447332 -1.11515350
> 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] -0.43605778 -0.19318661 -0.06104038 1.01839343 2.25087657 0.20360020
[7] -0.03471967 -1.60415640 -1.73953327 1.33443178 -1.82327196 -0.30833515
[13] -0.51700117 -0.46506592 0.84406837 -0.85700792 1.07547081 -1.65519258
[19] 0.86500164 -1.15036539 1.51292361 0.99899831 -0.42268699 -1.29952540
[25] 0.20795126 -1.01321626 -0.16821065 0.82554328 0.26283879 0.82094371
[31] -0.87564513 2.12805372 -1.36695923 -2.22135869 0.05460296 -2.59190144
[37] 0.88313715 -0.53006106 0.08546511 -0.64371601 -0.36590253 -0.31618564
[43] -0.63534565 1.27747068 -0.13885625 -0.31938073 -0.07307086 0.91088931
[49] 0.44148517 -1.66384727 0.62808640 -0.82968128 1.18699402 -0.46702277
[55] -0.50407578 -0.35153318 0.80853643 1.26995966 -1.90500937 -0.76337811
[61] -0.66540819 -1.25941895 0.76932555 -0.55630980 -0.12693648 -0.39322975
[67] -0.63228740 -0.11195262 -0.29931972 -0.99602469 -1.07379904 -0.79879372
[73] 0.99438152 0.16323456 -1.85769641 0.56039461 -0.02655373 -0.55251278
[79] -0.18774564 0.78390833 0.22709930 -0.06867965 -0.13829495 -1.25905068
[85] 0.04396671 0.36985398 0.42313955 0.78414672 -0.31163371 0.44161207
[91] 0.55548599 -0.12036416 0.03477618 0.52616643 0.36481530 -1.16804086
[97] 1.51841270 0.87987886 1.36447332 -1.11515350
> colMin(tmp)
[1] -0.43605778 -0.19318661 -0.06104038 1.01839343 2.25087657 0.20360020
[7] -0.03471967 -1.60415640 -1.73953327 1.33443178 -1.82327196 -0.30833515
[13] -0.51700117 -0.46506592 0.84406837 -0.85700792 1.07547081 -1.65519258
[19] 0.86500164 -1.15036539 1.51292361 0.99899831 -0.42268699 -1.29952540
[25] 0.20795126 -1.01321626 -0.16821065 0.82554328 0.26283879 0.82094371
[31] -0.87564513 2.12805372 -1.36695923 -2.22135869 0.05460296 -2.59190144
[37] 0.88313715 -0.53006106 0.08546511 -0.64371601 -0.36590253 -0.31618564
[43] -0.63534565 1.27747068 -0.13885625 -0.31938073 -0.07307086 0.91088931
[49] 0.44148517 -1.66384727 0.62808640 -0.82968128 1.18699402 -0.46702277
[55] -0.50407578 -0.35153318 0.80853643 1.26995966 -1.90500937 -0.76337811
[61] -0.66540819 -1.25941895 0.76932555 -0.55630980 -0.12693648 -0.39322975
[67] -0.63228740 -0.11195262 -0.29931972 -0.99602469 -1.07379904 -0.79879372
[73] 0.99438152 0.16323456 -1.85769641 0.56039461 -0.02655373 -0.55251278
[79] -0.18774564 0.78390833 0.22709930 -0.06867965 -0.13829495 -1.25905068
[85] 0.04396671 0.36985398 0.42313955 0.78414672 -0.31163371 0.44161207
[91] 0.55548599 -0.12036416 0.03477618 0.52616643 0.36481530 -1.16804086
[97] 1.51841270 0.87987886 1.36447332 -1.11515350
> colMedians(tmp)
[1] -0.43605778 -0.19318661 -0.06104038 1.01839343 2.25087657 0.20360020
[7] -0.03471967 -1.60415640 -1.73953327 1.33443178 -1.82327196 -0.30833515
[13] -0.51700117 -0.46506592 0.84406837 -0.85700792 1.07547081 -1.65519258
[19] 0.86500164 -1.15036539 1.51292361 0.99899831 -0.42268699 -1.29952540
[25] 0.20795126 -1.01321626 -0.16821065 0.82554328 0.26283879 0.82094371
[31] -0.87564513 2.12805372 -1.36695923 -2.22135869 0.05460296 -2.59190144
[37] 0.88313715 -0.53006106 0.08546511 -0.64371601 -0.36590253 -0.31618564
[43] -0.63534565 1.27747068 -0.13885625 -0.31938073 -0.07307086 0.91088931
[49] 0.44148517 -1.66384727 0.62808640 -0.82968128 1.18699402 -0.46702277
[55] -0.50407578 -0.35153318 0.80853643 1.26995966 -1.90500937 -0.76337811
[61] -0.66540819 -1.25941895 0.76932555 -0.55630980 -0.12693648 -0.39322975
[67] -0.63228740 -0.11195262 -0.29931972 -0.99602469 -1.07379904 -0.79879372
[73] 0.99438152 0.16323456 -1.85769641 0.56039461 -0.02655373 -0.55251278
[79] -0.18774564 0.78390833 0.22709930 -0.06867965 -0.13829495 -1.25905068
[85] 0.04396671 0.36985398 0.42313955 0.78414672 -0.31163371 0.44161207
[91] 0.55548599 -0.12036416 0.03477618 0.52616643 0.36481530 -1.16804086
[97] 1.51841270 0.87987886 1.36447332 -1.11515350
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.4360578 -0.1931866 -0.06104038 1.018393 2.250877 0.2036002 -0.03471967
[2,] -0.4360578 -0.1931866 -0.06104038 1.018393 2.250877 0.2036002 -0.03471967
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.604156 -1.739533 1.334432 -1.823272 -0.3083352 -0.5170012 -0.4650659
[2,] -1.604156 -1.739533 1.334432 -1.823272 -0.3083352 -0.5170012 -0.4650659
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.8440684 -0.8570079 1.075471 -1.655193 0.8650016 -1.150365 1.512924
[2,] 0.8440684 -0.8570079 1.075471 -1.655193 0.8650016 -1.150365 1.512924
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.9989983 -0.422687 -1.299525 0.2079513 -1.013216 -0.1682106 0.8255433
[2,] 0.9989983 -0.422687 -1.299525 0.2079513 -1.013216 -0.1682106 0.8255433
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.2628388 0.8209437 -0.8756451 2.128054 -1.366959 -2.221359 0.05460296
[2,] 0.2628388 0.8209437 -0.8756451 2.128054 -1.366959 -2.221359 0.05460296
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -2.591901 0.8831372 -0.5300611 0.08546511 -0.643716 -0.3659025 -0.3161856
[2,] -2.591901 0.8831372 -0.5300611 0.08546511 -0.643716 -0.3659025 -0.3161856
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.6353456 1.277471 -0.1388563 -0.3193807 -0.07307086 0.9108893 0.4414852
[2,] -0.6353456 1.277471 -0.1388563 -0.3193807 -0.07307086 0.9108893 0.4414852
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -1.663847 0.6280864 -0.8296813 1.186994 -0.4670228 -0.5040758 -0.3515332
[2,] -1.663847 0.6280864 -0.8296813 1.186994 -0.4670228 -0.5040758 -0.3515332
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.8085364 1.26996 -1.905009 -0.7633781 -0.6654082 -1.259419 0.7693256
[2,] 0.8085364 1.26996 -1.905009 -0.7633781 -0.6654082 -1.259419 0.7693256
[,64] [,65] [,66] [,67] [,68] [,69]
[1,] -0.5563098 -0.1269365 -0.3932297 -0.6322874 -0.1119526 -0.2993197
[2,] -0.5563098 -0.1269365 -0.3932297 -0.6322874 -0.1119526 -0.2993197
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] -0.9960247 -1.073799 -0.7987937 0.9943815 0.1632346 -1.857696 0.5603946
[2,] -0.9960247 -1.073799 -0.7987937 0.9943815 0.1632346 -1.857696 0.5603946
[,77] [,78] [,79] [,80] [,81] [,82]
[1,] -0.02655373 -0.5525128 -0.1877456 0.7839083 0.2270993 -0.06867965
[2,] -0.02655373 -0.5525128 -0.1877456 0.7839083 0.2270993 -0.06867965
[,83] [,84] [,85] [,86] [,87] [,88] [,89]
[1,] -0.138295 -1.259051 0.04396671 0.369854 0.4231396 0.7841467 -0.3116337
[2,] -0.138295 -1.259051 0.04396671 0.369854 0.4231396 0.7841467 -0.3116337
[,90] [,91] [,92] [,93] [,94] [,95] [,96]
[1,] 0.4416121 0.555486 -0.1203642 0.03477618 0.5261664 0.3648153 -1.168041
[2,] 0.4416121 0.555486 -0.1203642 0.03477618 0.5261664 0.3648153 -1.168041
[,97] [,98] [,99] [,100]
[1,] 1.518413 0.8798789 1.364473 -1.115153
[2,] 1.518413 0.8798789 1.364473 -1.115153
>
>
> Max(tmp2)
[1] 2.363119
> Min(tmp2)
[1] -2.071269
> mean(tmp2)
[1] 0.1896427
> Sum(tmp2)
[1] 18.96427
> Var(tmp2)
[1] 1.150422
>
> rowMeans(tmp2)
[1] 1.37618670 -0.56225054 2.16322593 -0.64045637 0.20523893 1.16672577
[7] -0.19440540 1.48841280 -0.55411568 0.98878550 -1.59456116 1.23104966
[13] -1.77558453 -0.11032418 0.87207653 -1.55527482 -0.22471185 0.56954173
[19] 1.32184494 0.59849616 0.36446656 1.81148466 0.35065127 -1.71534326
[25] 0.29002145 0.91783117 1.07437823 0.73350720 0.44440041 1.40351977
[31] 0.56907578 -0.48640638 -0.24281627 0.23629110 1.08224326 2.36311876
[37] -1.60887796 -0.03110610 0.78846385 -0.79857031 -0.34183079 0.47978645
[43] 0.76251100 -1.11302121 0.49801605 -1.16886506 -0.80448490 -0.36875858
[49] 2.33142812 -0.14520540 0.17329831 -1.31093574 -0.14918050 0.51213027
[55] 2.19696567 -1.25723578 1.53884554 0.69189142 0.46970390 -0.26835176
[61] 0.48752148 1.92196915 -1.67635039 -2.07126938 -0.27197413 -0.87001075
[67] 0.65850179 0.73725694 1.23564724 1.12354153 0.54219412 -1.02539112
[73] -1.32639644 -1.78037266 0.58424679 -0.08925369 1.26175220 -1.51763681
[79] 0.41078569 -0.33709071 0.36706267 -1.68217733 0.05240268 -1.94802390
[85] 1.63798172 0.35807682 0.88610759 1.89986714 0.47178655 -0.45576372
[91] 1.77569096 0.27744060 1.24376252 0.16420015 0.92205569 -0.89103428
[97] 0.58849921 0.49114915 0.28581729 -0.52124273
> rowSums(tmp2)
[1] 1.37618670 -0.56225054 2.16322593 -0.64045637 0.20523893 1.16672577
[7] -0.19440540 1.48841280 -0.55411568 0.98878550 -1.59456116 1.23104966
[13] -1.77558453 -0.11032418 0.87207653 -1.55527482 -0.22471185 0.56954173
[19] 1.32184494 0.59849616 0.36446656 1.81148466 0.35065127 -1.71534326
[25] 0.29002145 0.91783117 1.07437823 0.73350720 0.44440041 1.40351977
[31] 0.56907578 -0.48640638 -0.24281627 0.23629110 1.08224326 2.36311876
[37] -1.60887796 -0.03110610 0.78846385 -0.79857031 -0.34183079 0.47978645
[43] 0.76251100 -1.11302121 0.49801605 -1.16886506 -0.80448490 -0.36875858
[49] 2.33142812 -0.14520540 0.17329831 -1.31093574 -0.14918050 0.51213027
[55] 2.19696567 -1.25723578 1.53884554 0.69189142 0.46970390 -0.26835176
[61] 0.48752148 1.92196915 -1.67635039 -2.07126938 -0.27197413 -0.87001075
[67] 0.65850179 0.73725694 1.23564724 1.12354153 0.54219412 -1.02539112
[73] -1.32639644 -1.78037266 0.58424679 -0.08925369 1.26175220 -1.51763681
[79] 0.41078569 -0.33709071 0.36706267 -1.68217733 0.05240268 -1.94802390
[85] 1.63798172 0.35807682 0.88610759 1.89986714 0.47178655 -0.45576372
[91] 1.77569096 0.27744060 1.24376252 0.16420015 0.92205569 -0.89103428
[97] 0.58849921 0.49114915 0.28581729 -0.52124273
> 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] 1.37618670 -0.56225054 2.16322593 -0.64045637 0.20523893 1.16672577
[7] -0.19440540 1.48841280 -0.55411568 0.98878550 -1.59456116 1.23104966
[13] -1.77558453 -0.11032418 0.87207653 -1.55527482 -0.22471185 0.56954173
[19] 1.32184494 0.59849616 0.36446656 1.81148466 0.35065127 -1.71534326
[25] 0.29002145 0.91783117 1.07437823 0.73350720 0.44440041 1.40351977
[31] 0.56907578 -0.48640638 -0.24281627 0.23629110 1.08224326 2.36311876
[37] -1.60887796 -0.03110610 0.78846385 -0.79857031 -0.34183079 0.47978645
[43] 0.76251100 -1.11302121 0.49801605 -1.16886506 -0.80448490 -0.36875858
[49] 2.33142812 -0.14520540 0.17329831 -1.31093574 -0.14918050 0.51213027
[55] 2.19696567 -1.25723578 1.53884554 0.69189142 0.46970390 -0.26835176
[61] 0.48752148 1.92196915 -1.67635039 -2.07126938 -0.27197413 -0.87001075
[67] 0.65850179 0.73725694 1.23564724 1.12354153 0.54219412 -1.02539112
[73] -1.32639644 -1.78037266 0.58424679 -0.08925369 1.26175220 -1.51763681
[79] 0.41078569 -0.33709071 0.36706267 -1.68217733 0.05240268 -1.94802390
[85] 1.63798172 0.35807682 0.88610759 1.89986714 0.47178655 -0.45576372
[91] 1.77569096 0.27744060 1.24376252 0.16420015 0.92205569 -0.89103428
[97] 0.58849921 0.49114915 0.28581729 -0.52124273
> rowMin(tmp2)
[1] 1.37618670 -0.56225054 2.16322593 -0.64045637 0.20523893 1.16672577
[7] -0.19440540 1.48841280 -0.55411568 0.98878550 -1.59456116 1.23104966
[13] -1.77558453 -0.11032418 0.87207653 -1.55527482 -0.22471185 0.56954173
[19] 1.32184494 0.59849616 0.36446656 1.81148466 0.35065127 -1.71534326
[25] 0.29002145 0.91783117 1.07437823 0.73350720 0.44440041 1.40351977
[31] 0.56907578 -0.48640638 -0.24281627 0.23629110 1.08224326 2.36311876
[37] -1.60887796 -0.03110610 0.78846385 -0.79857031 -0.34183079 0.47978645
[43] 0.76251100 -1.11302121 0.49801605 -1.16886506 -0.80448490 -0.36875858
[49] 2.33142812 -0.14520540 0.17329831 -1.31093574 -0.14918050 0.51213027
[55] 2.19696567 -1.25723578 1.53884554 0.69189142 0.46970390 -0.26835176
[61] 0.48752148 1.92196915 -1.67635039 -2.07126938 -0.27197413 -0.87001075
[67] 0.65850179 0.73725694 1.23564724 1.12354153 0.54219412 -1.02539112
[73] -1.32639644 -1.78037266 0.58424679 -0.08925369 1.26175220 -1.51763681
[79] 0.41078569 -0.33709071 0.36706267 -1.68217733 0.05240268 -1.94802390
[85] 1.63798172 0.35807682 0.88610759 1.89986714 0.47178655 -0.45576372
[91] 1.77569096 0.27744060 1.24376252 0.16420015 0.92205569 -0.89103428
[97] 0.58849921 0.49114915 0.28581729 -0.52124273
>
> colMeans(tmp2)
[1] 0.1896427
> colSums(tmp2)
[1] 18.96427
> colVars(tmp2)
[1] 1.150422
> colSd(tmp2)
[1] 1.072577
> colMax(tmp2)
[1] 2.363119
> colMin(tmp2)
[1] -2.071269
> colMedians(tmp2)
[1] 0.3612717
> colRanges(tmp2)
[,1]
[1,] -2.071269
[2,] 2.363119
>
> 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] 2.5193485 -3.7535082 0.6169085 2.3682157 0.4134853 5.1354058
[7] 5.2669164 2.7886286 1.7545530 2.2220177
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8421025
[2,] -0.4950382
[3,] 0.2835414
[4,] 0.8764437
[5,] 1.5276985
>
> rowApply(tmp,sum)
[1] 1.8557573 3.6195999 4.3032371 -0.4619225 -0.2340141 3.8555833
[7] 0.4597510 -1.1386959 1.7838469 5.2888282
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 4 1 6 8 9 3 10 2 9
[2,] 1 2 8 1 4 2 6 5 1 1
[3,] 5 7 5 9 9 6 2 6 4 6
[4,] 7 1 9 5 10 8 5 3 7 10
[5,] 2 6 6 3 6 7 1 8 9 8
[6,] 3 9 10 7 7 4 10 2 10 4
[7,] 6 10 7 4 5 5 7 9 6 5
[8,] 10 3 3 10 3 3 9 1 3 7
[9,] 4 5 4 2 1 10 4 7 8 2
[10,] 9 8 2 8 2 1 8 4 5 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.1472864 -0.1885890 0.8922706 0.5605707 -0.8436415 2.1892485
[7] -0.1921886 1.8858198 1.6111923 0.1102950 -2.1079525 -0.6014233
[13] -0.2801795 1.4478843 -2.4162213 0.5303945 5.2174746 2.7141583
[19] -0.8959552 -2.3828448
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.63781722
[2,] -0.31929744
[3,] -0.11976323
[4,] -0.01855375
[5,] 0.94814522
>
> rowApply(tmp,sum)
[1] 3.71060795 -3.76227606 1.17161015 0.09783745 5.88524688
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 11 8 7 9 17
[2,] 6 13 15 4 14
[3,] 17 17 19 8 1
[4,] 5 14 18 10 7
[5,] 3 16 12 7 4
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.01855375 -0.6030000 1.1915658 -0.61813031 -0.7609656 0.64581040
[2,] -0.63781722 0.3429675 0.9511852 0.58849925 0.7930902 0.06053819
[3,] -0.31929744 0.5287043 0.9185847 0.73440147 0.3430520 -0.14659485
[4,] -0.11976323 -1.1030017 -0.4142737 -0.10334938 -0.5284072 0.91176904
[5,] 0.94814522 0.6457408 -1.7547914 -0.04085034 -0.6904109 0.71772576
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.20012581 1.9703252 -0.3732762 0.6710608 -0.73548319 0.66163789
[2,] 1.00273875 0.7787501 1.0146977 -0.8109193 -1.65760430 -1.54488722
[3,] -0.93269254 -0.7002231 0.4406130 0.6441219 -0.02653255 0.04461985
[4,] 0.06476493 0.7546721 -1.3119030 -0.5831693 0.42241353 -0.69211864
[5,] -0.12687392 -0.9177046 1.8410608 0.1892009 -0.11074601 0.92932480
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.8242821 1.60119353 -0.2336544 0.43624795 -0.08813202 1.3128616
[2,] -1.9782129 -1.00202806 -0.3848207 -0.85970278 1.67323279 -1.5486720
[3,] -0.3547454 0.73374415 -0.3567570 -0.24439536 0.43430435 1.2173770
[4,] 2.1388762 0.02487482 -1.8677384 0.02886696 1.26886750 1.1190713
[5,] -0.9103795 0.09009983 0.4267491 1.16937770 1.92920201 0.6135203
[,19] [,20]
[1,] -1.1329614 -0.84009478
[2,] -0.5653598 0.02204838
[3,] -1.1084813 -0.67819313
[4,] 1.5231972 -1.43581155
[5,] 0.3876500 0.54920627
>
>
> 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 : 650 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 562 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 1.093261 0.6507128 0.5765432 1.30536 -0.2694059 1.709574 -1.973497
col8 col9 col10 col11 col12 col13 col14
row1 0.2580475 0.5342538 2.233887 0.5429255 2.229679 -0.4203974 -2.228053
col15 col16 col17 col18 col19 col20
row1 -0.6296621 -0.1409936 0.7395618 -0.8199612 1.511134 0.6156785
> tmp[,"col10"]
col10
row1 2.2338871
row2 1.1322233
row3 -1.1621182
row4 0.2207189
row5 -0.4732328
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.0932614 0.6507128 0.5765432 1.3053598 -0.2694059 1.709574 -1.9734967
row5 0.2732881 0.4640531 -0.8106063 0.5254079 2.9806474 1.151372 0.2070204
col8 col9 col10 col11 col12 col13 col14
row1 0.2580475 0.5342538 2.2338871 0.5429255 2.2296789 -0.4203974 -2.2280527
row5 -1.0645920 -0.1666249 -0.4732328 0.1854344 0.9596732 1.3166657 -0.7943428
col15 col16 col17 col18 col19 col20
row1 -0.62966214 -0.1409936 0.7395618 -0.81996118 1.511134 0.6156785
row5 0.07988734 -0.3776568 -1.2181513 0.03065904 -1.182772 -0.2963841
> tmp[,c("col6","col20")]
col6 col20
row1 1.7095740 0.6156785
row2 -0.4935716 0.6578346
row3 1.3669544 -1.0115761
row4 1.3984733 1.0276629
row5 1.1513718 -0.2963841
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.709574 0.6156785
row5 1.151372 -0.2963841
>
>
>
>
> 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 49.15691 50.66779 50.49095 50.84452 48.81968 105.0566 50.75821 50.59837
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.73824 51.79885 50.67493 50.32215 50.62364 50.69945 48.50028 50.44878
col17 col18 col19 col20
row1 51.05467 49.01408 48.88167 104.2991
> tmp[,"col10"]
col10
row1 51.79885
row2 30.11481
row3 30.16255
row4 31.06545
row5 50.29077
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.15691 50.66779 50.49095 50.84452 48.81968 105.0566 50.75821 50.59837
row5 50.13271 48.69037 50.10108 48.35204 49.90061 103.1149 49.48897 50.79627
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.73824 51.79885 50.67493 50.32215 50.62364 50.69945 48.50028 50.44878
row5 50.74237 50.29077 49.88410 51.32331 50.71794 49.65343 50.45945 49.57064
col17 col18 col19 col20
row1 51.05467 49.01408 48.88167 104.2991
row5 50.73486 50.09579 50.22807 104.2088
> tmp[,c("col6","col20")]
col6 col20
row1 105.05662 104.29908
row2 76.62926 74.83985
row3 74.25204 73.97867
row4 75.81755 75.49450
row5 103.11490 104.20877
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.0566 104.2991
row5 103.1149 104.2088
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.0566 104.2991
row5 103.1149 104.2088
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.25635507
[2,] 1.76349520
[3,] -0.80156137
[4,] -0.05348601
[5,] -0.93288587
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.1107551 -0.9341322
[2,] 0.6767483 2.0146432
[3,] -0.8823703 -1.1187730
[4,] 0.1176192 0.7447526
[5,] -0.4613235 0.2670362
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.3422882 -1.2255475
[2,] 1.2753335 -0.3629290
[3,] -0.5191270 -1.0854819
[4,] -0.4042826 -0.7609039
[5,] -1.0558911 -0.2604338
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.3422882
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.3422882
[2,] 1.2753335
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 -0.8900979 0.55444328 -0.8270470 -1.992567 0.4595330 1.5987560 0.4669979
row1 -0.5401358 -0.09766275 0.2327534 -2.401382 0.9249349 0.1637081 2.5635151
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 1.579125 -1.075471 0.67633633 0.4979023 -0.2715475 2.2911059 -1.1788482
row1 1.731774 -0.295535 -0.05801467 0.4462333 0.2598458 0.6554087 -0.6935688
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.1515397 0.7769234 0.08380698 -0.1827529 -0.7121192 -0.5153317
row1 1.1306214 -0.2914712 0.08797465 -0.1939302 -0.1056892 1.1550387
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.5673654 1.501845 -0.7927021 0.250777 0.6572433 -0.3377997 -0.7048767
[,8] [,9] [,10]
row2 1.323434 -0.6018444 0.583621
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 2.284858 -1.420847 -0.419764 -1.364978 -1.247267 0.4273162 0.05642175
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.1478712 0.9091506 0.2479024 0.9197472 0.2832428 1.380802 -1.490148
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.233525 -0.3146141 1.436006 0.6099543 -0.592717 -0.1050905
>
>
> 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: 0x6000033541e0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f56457e8b97"
[2] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f5676fe8a25"
[3] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f56411fc02b"
[4] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f56b816874"
[5] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f565cf09d92"
[6] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f5638f90be9"
[7] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f56667d0b37"
[8] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f561b6b7c72"
[9] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f562db72e6e"
[10] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f5655494f34"
[11] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f563fef0aaa"
[12] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f5666a53fb0"
[13] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f566af87075"
[14] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f565c9f4830"
[15] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f565d3c76d1"
>
>
> ### 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: 0x600003358240>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600003358240>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600003358240>
> rowMedians(tmp)
[1] 0.3138783447 0.1929863718 -0.8061449718 0.1683766061 0.3677406450
[6] -0.3777225491 0.2075356316 0.3260633969 0.1312447806 0.3652088438
[11] 0.2132157173 0.0729965779 -0.1387905491 -0.1009824072 -0.1418020687
[16] 0.5244789195 -0.6421134696 0.0259277121 0.3492790995 0.4560809190
[21] -0.3789040784 0.3772765614 -0.4005860564 0.3111110005 -0.0957067873
[26] 0.2578052233 -0.3123438961 -0.1823938568 0.1208762685 0.1705721337
[31] -0.0295808838 -0.9503813274 -0.1017962084 -1.0492229244 0.2963861814
[36] 0.4125475554 0.1150912883 -0.0612615561 -0.2310997088 0.0032252719
[41] -0.0462012914 0.0551452697 -0.3311001188 -0.0927592213 0.1556968013
[46] 0.0533327077 0.5398088959 -0.2058736941 0.1336044868 0.0927043122
[51] -0.3366604444 0.4049727207 -0.1553295061 -0.3384630492 -0.4992482650
[56] 0.7613845903 0.3197069766 0.4583349124 0.1278458895 0.0406385692
[61] -0.4863225384 -0.5860402123 -0.1858572155 0.3380979554 -0.0259042739
[66] -0.3717210448 -0.5472406490 0.3476554432 -0.0028323943 -0.2182717969
[71] -0.4278213259 0.3908149617 -0.2680523435 0.3453337157 -0.1133853562
[76] 0.2238268530 -0.3282044653 -0.1466192418 0.0255079993 0.2840454546
[81] -0.0988669156 0.2561761000 0.3382599474 -0.2351064956 -0.2889052352
[86] 0.1108085772 0.0376668247 0.0114521613 0.4333174089 -0.0965072137
[91] 0.2286191229 0.5634815652 -0.1064111214 -0.3181826746 -0.3510582811
[96] -0.1324513165 0.3146060291 -0.0840071950 -0.2494894826 0.1552613794
[101] 0.0257065346 -0.4720297565 -0.4797092298 0.1228050922 -0.2181271193
[106] 0.3622016232 0.0691232451 -0.5280821870 0.0178024259 1.1790348922
[111] -0.1485691364 -0.1096371616 -0.4156903904 0.7452170638 0.0835136965
[116] 0.0482137740 -0.1107720250 0.1228995118 0.6159364235 -0.2998986719
[121] -0.6139156775 -0.0584564410 0.2619779957 -0.2212223916 0.0441965764
[126] 0.1427878508 0.2547279077 0.2188367668 0.0376258378 0.0643203826
[131] 0.1531099554 0.6871348810 0.0012623937 0.3331522699 -0.1736935613
[136] 0.3949286361 -0.0296590404 0.1268469428 0.0173231912 0.3909886262
[141] 0.5380898776 0.4318033659 -0.0712381373 0.3022078529 -0.1305109716
[146] 0.1324902993 -0.4089419498 -0.0213187515 -0.1851795899 0.2428137516
[151] -0.1003474262 0.1550665919 0.3553639913 -0.0242873870 -0.1345455069
[156] 0.1006986504 -0.0347033960 0.1353103112 0.4521428021 -0.0549928168
[161] 0.1094968340 0.4157972171 0.2124707207 0.8516870443 -0.3288832767
[166] 0.0409879725 -0.2674460732 0.0429795544 -0.2651772843 0.0740187290
[171] -0.2648510092 0.2967209943 -0.0916582302 -0.3255189274 0.1042594293
[176] -0.2961732288 -0.2673641210 0.4083805105 0.0599919197 0.3866401985
[181] -0.3120011090 -0.2611130995 0.3046949187 0.4896417608 -0.5883764288
[186] 0.3429881984 -0.4102458643 0.8330759410 -0.2674809144 0.2126887580
[191] -0.0797605460 0.3984745611 -0.2271763822 -0.0245084866 0.1274866103
[196] 0.2070245608 0.5563977488 -0.4527200195 0.2135201878 0.5115916806
[201] 0.2291881410 0.5850996982 0.0996455856 -0.0187553972 0.4239348506
[206] -0.3204987278 -0.0923704386 -0.0411498910 0.0184234532 -0.2462726518
[211] -0.0860534944 -0.2004340591 -0.2935620041 0.3670187524 -0.7010776321
[216] 0.2801165283 0.3020890011 -0.1705405125 0.1781692168 -0.3100208968
[221] 0.3859670047 -0.0712004021 0.1320946688 0.0062385619 -0.0002910615
[226] 0.2216680958 -0.3103151358 -0.2363130031 -0.4352675649 -0.2734715802
>
> proc.time()
user system elapsed
0.685 3.531 4.399
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.0 Patched (2025-04-21 r88169) -- "How About a Twenty-Six"
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: 0x600001c28000>
> .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: 0x600001c28000>
> .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: 0x600001c28000>
> .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: 0x600001c28000>
> 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: 0x600001c30360>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001c30360>
> .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: 0x600001c30360>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001c30360>
> .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: 0x600001c30360>
> 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: 0x600001c30540>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001c30540>
> .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: 0x600001c30540>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600001c30540>
> .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: 0x600001c30540>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600001c30540>
> .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: 0x600001c30540>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600001c30540>
> .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: 0x600001c30540>
> 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: 0x600001c30720>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600001c30720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001c30720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001c30720>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile94c819b547e9" "BufferedMatrixFile94c8741b0444"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile94c819b547e9" "BufferedMatrixFile94c8741b0444"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001c309c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001c309c0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600001c309c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600001c309c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600001c309c0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600001c309c0>
> .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: 0x600001c30ba0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001c30ba0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600001c30ba0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600001c30ba0>
> 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: 0x600001c30d80>
> .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: 0x600001c30d80>
> rm(P)
>
> proc.time()
user system elapsed
0.110 0.039 0.145
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.0 Patched (2025-04-21 r88169) -- "How About a Twenty-Six"
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
0.108 0.024 0.129