Ben Bolstad
| Snapshot Date: 2025-09-26 13:45 -0400 (Fri, 26 Sep 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 2025-09-27 12:05 -0400 (Sat, 27 Sep 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" | 4832 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4620 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4565 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4563 |
| 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 253/2334 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.73.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 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: 2025-09-26 18:28:36 -0400 (Fri, 26 Sep 2025) |
| EndedAt: 2025-09-26 18:28:54 -0400 (Fri, 26 Sep 2025) |
| EllapsedTime: 17.2 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 4.5.1 Patched (2025-09-10 r88807)
* 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 13.7.7
* 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: ‘MacOSX11.3.1.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: ‘MacOSX11.3.1.sdk’
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch arm64 -std=gnu2x -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/arm64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R
installing to /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.114 0.045 0.155
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/Users/biocbuild/bbs-3.22-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 480828 25.7 1056624 56.5 NA 634340 33.9
Vcells 891019 6.8 8388608 64.0 196608 2109889 16.1
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Sep 26 18:28:45 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Sep 26 18:28:45 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: 0x60000048c000>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Sep 26 18:28:46 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Sep 26 18:28:47 2025"
>
> ColMode(tmp2)
<pointer: 0x60000048c000>
>
>
>
> ### 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,] 100.59923027 0.4973803 0.1656609 0.7763171
[2,] -0.03321657 1.4839279 -0.8105086 0.2962588
[3,] -0.67700613 -0.5704877 -0.8350913 -0.0234799
[4,] -0.04625997 -0.5943769 -0.1147039 0.1828965
> 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 : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.59923027 0.4973803 0.1656609 0.7763171
[2,] 0.03321657 1.4839279 0.8105086 0.2962588
[3,] 0.67700613 0.5704877 0.8350913 0.0234799
[4,] 0.04625997 0.5943769 0.1147039 0.1828965
> 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 : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0299168 0.7052520 0.4070146 0.8810886
[2,] 0.1822541 1.2181658 0.9002825 0.5442966
[3,] 0.8228038 0.7553063 0.9138333 0.1532315
[4,] 0.2150813 0.7709584 0.3386796 0.4276640
>
> 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 : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.89840 32.54990 29.23581 34.58720
[2,] 26.85576 38.66559 34.81333 30.73922
[3,] 33.90504 33.12355 34.97342 26.55580
[4,] 27.19707 33.30396 28.50150 29.45954
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600000480000>
> exp(tmp5)
<pointer: 0x600000480000>
> log(tmp5,2)
<pointer: 0x600000480000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.1779
> Min(tmp5)
[1] 53.0432
> mean(tmp5)
[1] 72.2855
> Sum(tmp5)
[1] 14457.1
> Var(tmp5)
[1] 873.1841
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.82334 70.07762 68.42449 68.68681 72.42838 71.36904 69.72777 70.22477
[9] 70.55975 70.53307
> rowSums(tmp5)
[1] 1816.467 1401.552 1368.490 1373.736 1448.568 1427.381 1394.555 1404.495
[9] 1411.195 1410.661
> rowVars(tmp5)
[1] 8024.61205 71.99201 79.86087 69.16916 80.88602 81.27473
[7] 100.67927 61.54208 69.55111 91.06421
> rowSd(tmp5)
[1] 89.580199 8.484810 8.936491 8.316800 8.993666 9.015250 10.033906
[8] 7.844876 8.339731 9.542757
> rowMax(tmp5)
[1] 470.17792 80.47735 85.81365 86.24468 88.63035 84.65160 87.52602
[8] 91.56372 82.87647 85.78998
> rowMin(tmp5)
[1] 56.61960 55.35750 53.58444 56.60714 54.44791 53.04320 53.39706 57.43337
[9] 56.33327 54.56758
>
> colMeans(tmp5)
[1] 108.66674 73.64580 68.62904 67.90757 71.54550 70.70513 68.81472
[8] 68.96367 71.51574 71.45575 67.92834 74.58892 67.03001 76.53757
[15] 68.03791 69.87761 67.86743 73.95487 71.87703 66.16076
> colSums(tmp5)
[1] 1086.6674 736.4580 686.2904 679.0757 715.4550 707.0513 688.1472
[8] 689.6367 715.1574 714.5575 679.2834 745.8892 670.3001 765.3757
[15] 680.3791 698.7761 678.6743 739.5487 718.7703 661.6076
> colVars(tmp5)
[1] 16210.89373 67.10834 46.54482 50.47219 59.79958 89.05708
[7] 57.24809 99.22349 111.03440 111.52912 133.10528 105.88223
[13] 57.88779 38.10562 41.81883 41.43028 66.80429 65.97121
[19] 58.52003 84.40777
> colSd(tmp5)
[1] 127.322008 8.191968 6.822377 7.104378 7.733019 9.437006
[7] 7.566247 9.961099 10.537286 10.560735 11.537126 10.289909
[13] 7.608403 6.172975 6.466748 6.436636 8.173389 8.122267
[19] 7.649838 9.187370
> colMax(tmp5)
[1] 470.17792 84.32848 78.79930 78.56898 78.46193 81.67012 77.02329
[8] 82.87647 88.18962 88.63035 91.56372 87.52602 80.39919 86.24468
[15] 79.16793 79.35155 80.69981 86.65628 82.22058 84.63557
> colMin(tmp5)
[1] 55.89674 60.42521 59.32214 55.27241 53.58444 54.56758 55.35750 56.38474
[9] 59.02506 57.08774 54.44791 60.24355 56.33327 67.83391 56.61960 59.31573
[17] 53.04320 60.36000 53.39706 56.74597
>
>
> ### 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] 90.82334 70.07762 68.42449 68.68681 72.42838 71.36904 69.72777 NA
[9] 70.55975 70.53307
> rowSums(tmp5)
[1] 1816.467 1401.552 1368.490 1373.736 1448.568 1427.381 1394.555 NA
[9] 1411.195 1410.661
> rowVars(tmp5)
[1] 8024.61205 71.99201 79.86087 69.16916 80.88602 81.27473
[7] 100.67927 55.39266 69.55111 91.06421
> rowSd(tmp5)
[1] 89.580199 8.484810 8.936491 8.316800 8.993666 9.015250 10.033906
[8] 7.442625 8.339731 9.542757
> rowMax(tmp5)
[1] 470.17792 80.47735 85.81365 86.24468 88.63035 84.65160 87.52602
[8] NA 82.87647 85.78998
> rowMin(tmp5)
[1] 56.61960 55.35750 53.58444 56.60714 54.44791 53.04320 53.39706 NA
[9] 56.33327 54.56758
>
> colMeans(tmp5)
[1] 108.66674 73.64580 68.62904 67.90757 71.54550 70.70513 68.81472
[8] 68.96367 71.51574 71.45575 67.92834 74.58892 67.03001 76.53757
[15] 68.03791 69.87761 67.86743 73.95487 71.87703 NA
> colSums(tmp5)
[1] 1086.6674 736.4580 686.2904 679.0757 715.4550 707.0513 688.1472
[8] 689.6367 715.1574 714.5575 679.2834 745.8892 670.3001 765.3757
[15] 680.3791 698.7761 678.6743 739.5487 718.7703 NA
> colVars(tmp5)
[1] 16210.89373 67.10834 46.54482 50.47219 59.79958 89.05708
[7] 57.24809 99.22349 111.03440 111.52912 133.10528 105.88223
[13] 57.88779 38.10562 41.81883 41.43028 66.80429 65.97121
[19] 58.52003 NA
> colSd(tmp5)
[1] 127.322008 8.191968 6.822377 7.104378 7.733019 9.437006
[7] 7.566247 9.961099 10.537286 10.560735 11.537126 10.289909
[13] 7.608403 6.172975 6.466748 6.436636 8.173389 8.122267
[19] 7.649838 NA
> colMax(tmp5)
[1] 470.17792 84.32848 78.79930 78.56898 78.46193 81.67012 77.02329
[8] 82.87647 88.18962 88.63035 91.56372 87.52602 80.39919 86.24468
[15] 79.16793 79.35155 80.69981 86.65628 82.22058 NA
> colMin(tmp5)
[1] 55.89674 60.42521 59.32214 55.27241 53.58444 54.56758 55.35750 56.38474
[9] 59.02506 57.08774 54.44791 60.24355 56.33327 67.83391 56.61960 59.31573
[17] 53.04320 60.36000 53.39706 NA
>
> Max(tmp5,na.rm=TRUE)
[1] 470.1779
> Min(tmp5,na.rm=TRUE)
[1] 53.0432
> mean(tmp5,na.rm=TRUE)
[1] 72.36014
> Sum(tmp5,na.rm=TRUE)
[1] 14399.67
> Var(tmp5,na.rm=TRUE)
[1] 876.4745
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.82334 70.07762 68.42449 68.68681 72.42838 71.36904 69.72777 70.89800
[9] 70.55975 70.53307
> rowSums(tmp5,na.rm=TRUE)
[1] 1816.467 1401.552 1368.490 1373.736 1448.568 1427.381 1394.555 1347.062
[9] 1411.195 1410.661
> rowVars(tmp5,na.rm=TRUE)
[1] 8024.61205 71.99201 79.86087 69.16916 80.88602 81.27473
[7] 100.67927 55.39266 69.55111 91.06421
> rowSd(tmp5,na.rm=TRUE)
[1] 89.580199 8.484810 8.936491 8.316800 8.993666 9.015250 10.033906
[8] 7.442625 8.339731 9.542757
> rowMax(tmp5,na.rm=TRUE)
[1] 470.17792 80.47735 85.81365 86.24468 88.63035 84.65160 87.52602
[8] 91.56372 82.87647 85.78998
> rowMin(tmp5,na.rm=TRUE)
[1] 56.61960 55.35750 53.58444 56.60714 54.44791 53.04320 53.39706 59.02506
[9] 56.33327 54.56758
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.66674 73.64580 68.62904 67.90757 71.54550 70.70513 68.81472
[8] 68.96367 71.51574 71.45575 67.92834 74.58892 67.03001 76.53757
[15] 68.03791 69.87761 67.86743 73.95487 71.87703 67.13047
> colSums(tmp5,na.rm=TRUE)
[1] 1086.6674 736.4580 686.2904 679.0757 715.4550 707.0513 688.1472
[8] 689.6367 715.1574 714.5575 679.2834 745.8892 670.3001 765.3757
[15] 680.3791 698.7761 678.6743 739.5487 718.7703 604.1743
> colVars(tmp5,na.rm=TRUE)
[1] 16210.89373 67.10834 46.54482 50.47219 59.79958 89.05708
[7] 57.24809 99.22349 111.03440 111.52912 133.10528 105.88223
[13] 57.88779 38.10562 41.81883 41.43028 66.80429 65.97121
[19] 58.52003 84.37992
> colSd(tmp5,na.rm=TRUE)
[1] 127.322008 8.191968 6.822377 7.104378 7.733019 9.437006
[7] 7.566247 9.961099 10.537286 10.560735 11.537126 10.289909
[13] 7.608403 6.172975 6.466748 6.436636 8.173389 8.122267
[19] 7.649838 9.185855
> colMax(tmp5,na.rm=TRUE)
[1] 470.17792 84.32848 78.79930 78.56898 78.46193 81.67012 77.02329
[8] 82.87647 88.18962 88.63035 91.56372 87.52602 80.39919 86.24468
[15] 79.16793 79.35155 80.69981 86.65628 82.22058 84.63557
> colMin(tmp5,na.rm=TRUE)
[1] 55.89674 60.42521 59.32214 55.27241 53.58444 54.56758 55.35750 56.38474
[9] 59.02506 57.08774 54.44791 60.24355 56.33327 67.83391 56.61960 59.31573
[17] 53.04320 60.36000 53.39706 56.74597
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.82334 70.07762 68.42449 68.68681 72.42838 71.36904 69.72777 NaN
[9] 70.55975 70.53307
> rowSums(tmp5,na.rm=TRUE)
[1] 1816.467 1401.552 1368.490 1373.736 1448.568 1427.381 1394.555 0.000
[9] 1411.195 1410.661
> rowVars(tmp5,na.rm=TRUE)
[1] 8024.61205 71.99201 79.86087 69.16916 80.88602 81.27473
[7] 100.67927 NA 69.55111 91.06421
> rowSd(tmp5,na.rm=TRUE)
[1] 89.580199 8.484810 8.936491 8.316800 8.993666 9.015250 10.033906
[8] NA 8.339731 9.542757
> rowMax(tmp5,na.rm=TRUE)
[1] 470.17792 80.47735 85.81365 86.24468 88.63035 84.65160 87.52602
[8] NA 82.87647 85.78998
> rowMin(tmp5,na.rm=TRUE)
[1] 56.61960 55.35750 53.58444 56.60714 54.44791 53.04320 53.39706 NA
[9] 56.33327 54.56758
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.22203 74.58032 68.94327 68.15167 71.04435 70.01136 68.55361
[8] 67.54886 72.90359 71.08110 65.30218 75.64678 67.12380 77.06405
[15] 68.23683 69.80869 68.05080 73.65773 72.22801 NaN
> colSums(tmp5,na.rm=TRUE)
[1] 1018.9983 671.2229 620.4894 613.3650 639.3991 630.1022 616.9825
[8] 607.9397 656.1323 639.7299 587.7197 680.8210 604.1142 693.5764
[15] 614.1315 628.2782 612.4572 662.9196 650.0521 0.0000
> colVars(tmp5,na.rm=TRUE)
[1] 18003.81056 65.67184 51.25209 56.11087 64.44899 94.77433
[7] 63.63714 89.10759 103.24468 123.89116 72.15578 106.52806
[13] 65.02481 39.75061 46.60101 46.55563 74.77652 73.22438
[19] 64.44918 NA
> colSd(tmp5,na.rm=TRUE)
[1] 134.178279 8.103816 7.159057 7.490719 8.028013 9.735211
[7] 7.977289 9.439682 10.160939 11.130640 8.494456 10.321243
[13] 8.063796 6.304809 6.826493 6.823169 8.647342 8.557124
[19] 8.028025 NA
> colMax(tmp5,na.rm=TRUE)
[1] 470.17792 84.32848 78.79930 78.56898 78.46193 81.67012 77.02329
[8] 82.87647 88.18962 88.63035 79.83593 87.52602 80.39919 86.24468
[15] 79.16793 79.35155 80.69981 86.65628 82.22058 -Inf
> colMin(tmp5,na.rm=TRUE)
[1] 55.89674 60.42521 59.32214 55.27241 53.58444 54.56758 55.35750 56.38474
[9] 61.96535 57.08774 54.44791 60.24355 56.33327 67.83391 56.61960 59.31573
[17] 53.04320 60.36000 53.39706 Inf
>
>
>
>
> 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] 409.6817 134.1953 279.5009 411.7872 132.3454 240.6492 442.1429 131.3547
[9] 291.3382 121.0262
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 409.6817 134.1953 279.5009 411.7872 132.3454 240.6492 442.1429 131.3547
[9] 291.3382 121.0262
>
>
>
> 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 5.684342e-14 -8.526513e-14 0.000000e+00 -2.842171e-13
[6] -1.278977e-13 -2.842171e-14 0.000000e+00 -5.684342e-14 1.421085e-14
[11] -5.684342e-14 -5.684342e-14 -2.842171e-14 -1.705303e-13 5.684342e-14
[16] 4.263256e-14 0.000000e+00 2.273737e-13 0.000000e+00 -5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
4 1
4 11
1 8
10 19
8 3
4 17
5 5
4 9
1 8
3 15
6 15
3 20
8 2
9 13
10 16
7 19
7 14
1 17
6 11
7 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] 2.372599
> Min(tmp)
[1] -1.791987
> mean(tmp)
[1] 0.02801552
> Sum(tmp)
[1] 2.801552
> Var(tmp)
[1] 0.8279257
>
> rowMeans(tmp)
[1] 0.02801552
> rowSums(tmp)
[1] 2.801552
> rowVars(tmp)
[1] 0.8279257
> rowSd(tmp)
[1] 0.9099042
> rowMax(tmp)
[1] 2.372599
> rowMin(tmp)
[1] -1.791987
>
> colMeans(tmp)
[1] -1.69318251 0.63366457 1.19332418 1.94498956 -0.88330686 -0.42870941
[7] 1.22018607 0.43744382 -0.51757857 -0.22131686 -1.17308537 -0.23979549
[13] 1.62108637 0.69650488 -0.22380953 0.62144670 -1.46486145 0.15689194
[19] 0.06867894 -0.75316603 -0.51849987 -1.48017181 1.89985935 -0.16870039
[25] 0.31385315 0.72210848 -1.02989598 -0.48194438 2.08744821 -0.44300675
[31] 0.17418931 -0.32445273 0.06282487 -0.73993885 0.24978704 -0.31351289
[37] 0.19048378 0.54203424 -0.74108886 -0.43858207 0.12058012 1.59497887
[43] 0.54579848 -0.25341939 -0.74917593 0.80697076 -0.84865200 -0.57885683
[49] -1.50954003 -0.78690910 -0.55079155 0.64639827 1.57478878 0.19869832
[55] -0.11629073 0.88453071 0.45304862 0.03523322 2.37259901 1.07876878
[61] -0.07046420 2.00944329 -0.18902130 -0.93463213 0.65107857 0.19534333
[67] -0.02300911 -1.18032838 1.26989411 1.54352490 0.68274643 1.14363170
[73] 1.58445995 0.10741367 -1.27322425 -0.10639006 0.32280411 -0.17143606
[79] -1.30380820 -0.41705973 0.49996305 0.30863043 0.26444208 -0.47462991
[85] -0.18806844 -0.17258956 0.10562253 -0.99250115 -0.56080438 -0.19242987
[91] -0.47163236 0.32975864 -0.77036386 -0.52022637 -0.68985993 -1.79198696
[97] -1.29991317 1.12892451 -0.74593244 -0.28277421
> colSums(tmp)
[1] -1.69318251 0.63366457 1.19332418 1.94498956 -0.88330686 -0.42870941
[7] 1.22018607 0.43744382 -0.51757857 -0.22131686 -1.17308537 -0.23979549
[13] 1.62108637 0.69650488 -0.22380953 0.62144670 -1.46486145 0.15689194
[19] 0.06867894 -0.75316603 -0.51849987 -1.48017181 1.89985935 -0.16870039
[25] 0.31385315 0.72210848 -1.02989598 -0.48194438 2.08744821 -0.44300675
[31] 0.17418931 -0.32445273 0.06282487 -0.73993885 0.24978704 -0.31351289
[37] 0.19048378 0.54203424 -0.74108886 -0.43858207 0.12058012 1.59497887
[43] 0.54579848 -0.25341939 -0.74917593 0.80697076 -0.84865200 -0.57885683
[49] -1.50954003 -0.78690910 -0.55079155 0.64639827 1.57478878 0.19869832
[55] -0.11629073 0.88453071 0.45304862 0.03523322 2.37259901 1.07876878
[61] -0.07046420 2.00944329 -0.18902130 -0.93463213 0.65107857 0.19534333
[67] -0.02300911 -1.18032838 1.26989411 1.54352490 0.68274643 1.14363170
[73] 1.58445995 0.10741367 -1.27322425 -0.10639006 0.32280411 -0.17143606
[79] -1.30380820 -0.41705973 0.49996305 0.30863043 0.26444208 -0.47462991
[85] -0.18806844 -0.17258956 0.10562253 -0.99250115 -0.56080438 -0.19242987
[91] -0.47163236 0.32975864 -0.77036386 -0.52022637 -0.68985993 -1.79198696
[97] -1.29991317 1.12892451 -0.74593244 -0.28277421
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] -1.69318251 0.63366457 1.19332418 1.94498956 -0.88330686 -0.42870941
[7] 1.22018607 0.43744382 -0.51757857 -0.22131686 -1.17308537 -0.23979549
[13] 1.62108637 0.69650488 -0.22380953 0.62144670 -1.46486145 0.15689194
[19] 0.06867894 -0.75316603 -0.51849987 -1.48017181 1.89985935 -0.16870039
[25] 0.31385315 0.72210848 -1.02989598 -0.48194438 2.08744821 -0.44300675
[31] 0.17418931 -0.32445273 0.06282487 -0.73993885 0.24978704 -0.31351289
[37] 0.19048378 0.54203424 -0.74108886 -0.43858207 0.12058012 1.59497887
[43] 0.54579848 -0.25341939 -0.74917593 0.80697076 -0.84865200 -0.57885683
[49] -1.50954003 -0.78690910 -0.55079155 0.64639827 1.57478878 0.19869832
[55] -0.11629073 0.88453071 0.45304862 0.03523322 2.37259901 1.07876878
[61] -0.07046420 2.00944329 -0.18902130 -0.93463213 0.65107857 0.19534333
[67] -0.02300911 -1.18032838 1.26989411 1.54352490 0.68274643 1.14363170
[73] 1.58445995 0.10741367 -1.27322425 -0.10639006 0.32280411 -0.17143606
[79] -1.30380820 -0.41705973 0.49996305 0.30863043 0.26444208 -0.47462991
[85] -0.18806844 -0.17258956 0.10562253 -0.99250115 -0.56080438 -0.19242987
[91] -0.47163236 0.32975864 -0.77036386 -0.52022637 -0.68985993 -1.79198696
[97] -1.29991317 1.12892451 -0.74593244 -0.28277421
> colMin(tmp)
[1] -1.69318251 0.63366457 1.19332418 1.94498956 -0.88330686 -0.42870941
[7] 1.22018607 0.43744382 -0.51757857 -0.22131686 -1.17308537 -0.23979549
[13] 1.62108637 0.69650488 -0.22380953 0.62144670 -1.46486145 0.15689194
[19] 0.06867894 -0.75316603 -0.51849987 -1.48017181 1.89985935 -0.16870039
[25] 0.31385315 0.72210848 -1.02989598 -0.48194438 2.08744821 -0.44300675
[31] 0.17418931 -0.32445273 0.06282487 -0.73993885 0.24978704 -0.31351289
[37] 0.19048378 0.54203424 -0.74108886 -0.43858207 0.12058012 1.59497887
[43] 0.54579848 -0.25341939 -0.74917593 0.80697076 -0.84865200 -0.57885683
[49] -1.50954003 -0.78690910 -0.55079155 0.64639827 1.57478878 0.19869832
[55] -0.11629073 0.88453071 0.45304862 0.03523322 2.37259901 1.07876878
[61] -0.07046420 2.00944329 -0.18902130 -0.93463213 0.65107857 0.19534333
[67] -0.02300911 -1.18032838 1.26989411 1.54352490 0.68274643 1.14363170
[73] 1.58445995 0.10741367 -1.27322425 -0.10639006 0.32280411 -0.17143606
[79] -1.30380820 -0.41705973 0.49996305 0.30863043 0.26444208 -0.47462991
[85] -0.18806844 -0.17258956 0.10562253 -0.99250115 -0.56080438 -0.19242987
[91] -0.47163236 0.32975864 -0.77036386 -0.52022637 -0.68985993 -1.79198696
[97] -1.29991317 1.12892451 -0.74593244 -0.28277421
> colMedians(tmp)
[1] -1.69318251 0.63366457 1.19332418 1.94498956 -0.88330686 -0.42870941
[7] 1.22018607 0.43744382 -0.51757857 -0.22131686 -1.17308537 -0.23979549
[13] 1.62108637 0.69650488 -0.22380953 0.62144670 -1.46486145 0.15689194
[19] 0.06867894 -0.75316603 -0.51849987 -1.48017181 1.89985935 -0.16870039
[25] 0.31385315 0.72210848 -1.02989598 -0.48194438 2.08744821 -0.44300675
[31] 0.17418931 -0.32445273 0.06282487 -0.73993885 0.24978704 -0.31351289
[37] 0.19048378 0.54203424 -0.74108886 -0.43858207 0.12058012 1.59497887
[43] 0.54579848 -0.25341939 -0.74917593 0.80697076 -0.84865200 -0.57885683
[49] -1.50954003 -0.78690910 -0.55079155 0.64639827 1.57478878 0.19869832
[55] -0.11629073 0.88453071 0.45304862 0.03523322 2.37259901 1.07876878
[61] -0.07046420 2.00944329 -0.18902130 -0.93463213 0.65107857 0.19534333
[67] -0.02300911 -1.18032838 1.26989411 1.54352490 0.68274643 1.14363170
[73] 1.58445995 0.10741367 -1.27322425 -0.10639006 0.32280411 -0.17143606
[79] -1.30380820 -0.41705973 0.49996305 0.30863043 0.26444208 -0.47462991
[85] -0.18806844 -0.17258956 0.10562253 -0.99250115 -0.56080438 -0.19242987
[91] -0.47163236 0.32975864 -0.77036386 -0.52022637 -0.68985993 -1.79198696
[97] -1.29991317 1.12892451 -0.74593244 -0.28277421
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.693183 0.6336646 1.193324 1.94499 -0.8833069 -0.4287094 1.220186
[2,] -1.693183 0.6336646 1.193324 1.94499 -0.8833069 -0.4287094 1.220186
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.4374438 -0.5175786 -0.2213169 -1.173085 -0.2397955 1.621086 0.6965049
[2,] 0.4374438 -0.5175786 -0.2213169 -1.173085 -0.2397955 1.621086 0.6965049
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.2238095 0.6214467 -1.464861 0.1568919 0.06867894 -0.753166 -0.5184999
[2,] -0.2238095 0.6214467 -1.464861 0.1568919 0.06867894 -0.753166 -0.5184999
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.480172 1.899859 -0.1687004 0.3138532 0.7221085 -1.029896 -0.4819444
[2,] -1.480172 1.899859 -0.1687004 0.3138532 0.7221085 -1.029896 -0.4819444
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 2.087448 -0.4430067 0.1741893 -0.3244527 0.06282487 -0.7399389 0.249787
[2,] 2.087448 -0.4430067 0.1741893 -0.3244527 0.06282487 -0.7399389 0.249787
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.3135129 0.1904838 0.5420342 -0.7410889 -0.4385821 0.1205801 1.594979
[2,] -0.3135129 0.1904838 0.5420342 -0.7410889 -0.4385821 0.1205801 1.594979
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.5457985 -0.2534194 -0.7491759 0.8069708 -0.848652 -0.5788568 -1.50954
[2,] 0.5457985 -0.2534194 -0.7491759 0.8069708 -0.848652 -0.5788568 -1.50954
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.7869091 -0.5507916 0.6463983 1.574789 0.1986983 -0.1162907 0.8845307
[2,] -0.7869091 -0.5507916 0.6463983 1.574789 0.1986983 -0.1162907 0.8845307
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.4530486 0.03523322 2.372599 1.078769 -0.0704642 2.009443 -0.1890213
[2,] 0.4530486 0.03523322 2.372599 1.078769 -0.0704642 2.009443 -0.1890213
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.9346321 0.6510786 0.1953433 -0.02300911 -1.180328 1.269894 1.543525
[2,] -0.9346321 0.6510786 0.1953433 -0.02300911 -1.180328 1.269894 1.543525
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.6827464 1.143632 1.58446 0.1074137 -1.273224 -0.1063901 0.3228041
[2,] 0.6827464 1.143632 1.58446 0.1074137 -1.273224 -0.1063901 0.3228041
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.1714361 -1.303808 -0.4170597 0.4999631 0.3086304 0.2644421 -0.4746299
[2,] -0.1714361 -1.303808 -0.4170597 0.4999631 0.3086304 0.2644421 -0.4746299
[,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.1880684 -0.1725896 0.1056225 -0.9925012 -0.5608044 -0.1924299
[2,] -0.1880684 -0.1725896 0.1056225 -0.9925012 -0.5608044 -0.1924299
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -0.4716324 0.3297586 -0.7703639 -0.5202264 -0.6898599 -1.791987 -1.299913
[2,] -0.4716324 0.3297586 -0.7703639 -0.5202264 -0.6898599 -1.791987 -1.299913
[,98] [,99] [,100]
[1,] 1.128925 -0.7459324 -0.2827742
[2,] 1.128925 -0.7459324 -0.2827742
>
>
> Max(tmp2)
[1] 2.135728
> Min(tmp2)
[1] -2.602343
> mean(tmp2)
[1] -0.1333854
> Sum(tmp2)
[1] -13.33854
> Var(tmp2)
[1] 1.10391
>
> rowMeans(tmp2)
[1] -1.28950047 1.46208415 -0.32618004 -0.88897557 1.57204690 1.98508162
[7] 0.55742786 0.96795965 0.49193848 0.42107831 -0.99181985 1.70498452
[13] -0.50186130 0.66547929 -0.42273749 0.93279800 -0.70365284 0.59349377
[19] -0.99801501 0.66380263 0.10579871 2.13572784 0.16115791 -2.12753041
[25] -1.64323669 0.20988708 -0.32991860 -0.33849137 1.14904976 -0.60149286
[31] 0.50904630 1.59763922 -1.13664378 0.85106627 -0.98019619 0.05029064
[37] -0.07199384 1.94844585 0.29640290 0.34158871 -2.09998048 -0.40758303
[43] 1.04415651 0.42657988 -2.14748605 -1.62108742 0.13781713 -0.19306905
[49] -1.56028482 -0.48846727 -0.55073130 -1.93285927 -1.05936548 -0.15930456
[55] -0.97091736 1.03523387 0.61341566 1.93080583 0.55339580 -0.82483925
[61] 0.15983492 -0.65111784 -1.01757992 -1.26318665 0.44947958 0.92528425
[67] -0.66255468 -1.31211594 -0.49771638 -1.65581301 1.31269350 0.08386882
[73] 1.44865677 1.07365460 -0.18334554 -0.09376984 -0.87473493 0.22833906
[79] -1.05959298 0.26755229 -0.68950867 -0.94615501 0.16484942 -0.07222169
[85] 1.08041069 -0.82671964 -0.31632655 -0.39459675 -0.24931369 -1.56231662
[91] 1.69625733 -1.42370966 -0.72361212 -2.60234315 -0.90049592 0.83604856
[97] -0.95847559 -0.41935415 -1.22248629 -0.23376982
> rowSums(tmp2)
[1] -1.28950047 1.46208415 -0.32618004 -0.88897557 1.57204690 1.98508162
[7] 0.55742786 0.96795965 0.49193848 0.42107831 -0.99181985 1.70498452
[13] -0.50186130 0.66547929 -0.42273749 0.93279800 -0.70365284 0.59349377
[19] -0.99801501 0.66380263 0.10579871 2.13572784 0.16115791 -2.12753041
[25] -1.64323669 0.20988708 -0.32991860 -0.33849137 1.14904976 -0.60149286
[31] 0.50904630 1.59763922 -1.13664378 0.85106627 -0.98019619 0.05029064
[37] -0.07199384 1.94844585 0.29640290 0.34158871 -2.09998048 -0.40758303
[43] 1.04415651 0.42657988 -2.14748605 -1.62108742 0.13781713 -0.19306905
[49] -1.56028482 -0.48846727 -0.55073130 -1.93285927 -1.05936548 -0.15930456
[55] -0.97091736 1.03523387 0.61341566 1.93080583 0.55339580 -0.82483925
[61] 0.15983492 -0.65111784 -1.01757992 -1.26318665 0.44947958 0.92528425
[67] -0.66255468 -1.31211594 -0.49771638 -1.65581301 1.31269350 0.08386882
[73] 1.44865677 1.07365460 -0.18334554 -0.09376984 -0.87473493 0.22833906
[79] -1.05959298 0.26755229 -0.68950867 -0.94615501 0.16484942 -0.07222169
[85] 1.08041069 -0.82671964 -0.31632655 -0.39459675 -0.24931369 -1.56231662
[91] 1.69625733 -1.42370966 -0.72361212 -2.60234315 -0.90049592 0.83604856
[97] -0.95847559 -0.41935415 -1.22248629 -0.23376982
> 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] -1.28950047 1.46208415 -0.32618004 -0.88897557 1.57204690 1.98508162
[7] 0.55742786 0.96795965 0.49193848 0.42107831 -0.99181985 1.70498452
[13] -0.50186130 0.66547929 -0.42273749 0.93279800 -0.70365284 0.59349377
[19] -0.99801501 0.66380263 0.10579871 2.13572784 0.16115791 -2.12753041
[25] -1.64323669 0.20988708 -0.32991860 -0.33849137 1.14904976 -0.60149286
[31] 0.50904630 1.59763922 -1.13664378 0.85106627 -0.98019619 0.05029064
[37] -0.07199384 1.94844585 0.29640290 0.34158871 -2.09998048 -0.40758303
[43] 1.04415651 0.42657988 -2.14748605 -1.62108742 0.13781713 -0.19306905
[49] -1.56028482 -0.48846727 -0.55073130 -1.93285927 -1.05936548 -0.15930456
[55] -0.97091736 1.03523387 0.61341566 1.93080583 0.55339580 -0.82483925
[61] 0.15983492 -0.65111784 -1.01757992 -1.26318665 0.44947958 0.92528425
[67] -0.66255468 -1.31211594 -0.49771638 -1.65581301 1.31269350 0.08386882
[73] 1.44865677 1.07365460 -0.18334554 -0.09376984 -0.87473493 0.22833906
[79] -1.05959298 0.26755229 -0.68950867 -0.94615501 0.16484942 -0.07222169
[85] 1.08041069 -0.82671964 -0.31632655 -0.39459675 -0.24931369 -1.56231662
[91] 1.69625733 -1.42370966 -0.72361212 -2.60234315 -0.90049592 0.83604856
[97] -0.95847559 -0.41935415 -1.22248629 -0.23376982
> rowMin(tmp2)
[1] -1.28950047 1.46208415 -0.32618004 -0.88897557 1.57204690 1.98508162
[7] 0.55742786 0.96795965 0.49193848 0.42107831 -0.99181985 1.70498452
[13] -0.50186130 0.66547929 -0.42273749 0.93279800 -0.70365284 0.59349377
[19] -0.99801501 0.66380263 0.10579871 2.13572784 0.16115791 -2.12753041
[25] -1.64323669 0.20988708 -0.32991860 -0.33849137 1.14904976 -0.60149286
[31] 0.50904630 1.59763922 -1.13664378 0.85106627 -0.98019619 0.05029064
[37] -0.07199384 1.94844585 0.29640290 0.34158871 -2.09998048 -0.40758303
[43] 1.04415651 0.42657988 -2.14748605 -1.62108742 0.13781713 -0.19306905
[49] -1.56028482 -0.48846727 -0.55073130 -1.93285927 -1.05936548 -0.15930456
[55] -0.97091736 1.03523387 0.61341566 1.93080583 0.55339580 -0.82483925
[61] 0.15983492 -0.65111784 -1.01757992 -1.26318665 0.44947958 0.92528425
[67] -0.66255468 -1.31211594 -0.49771638 -1.65581301 1.31269350 0.08386882
[73] 1.44865677 1.07365460 -0.18334554 -0.09376984 -0.87473493 0.22833906
[79] -1.05959298 0.26755229 -0.68950867 -0.94615501 0.16484942 -0.07222169
[85] 1.08041069 -0.82671964 -0.31632655 -0.39459675 -0.24931369 -1.56231662
[91] 1.69625733 -1.42370966 -0.72361212 -2.60234315 -0.90049592 0.83604856
[97] -0.95847559 -0.41935415 -1.22248629 -0.23376982
>
> colMeans(tmp2)
[1] -0.1333854
> colSums(tmp2)
[1] -13.33854
> colVars(tmp2)
[1] 1.10391
> colSd(tmp2)
[1] 1.050671
> colMax(tmp2)
[1] 2.135728
> colMin(tmp2)
[1] -2.602343
> colMedians(tmp2)
[1] -0.2134194
> colRanges(tmp2)
[,1]
[1,] -2.602343
[2,] 2.135728
>
> 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] 5.2086195 0.1233954 2.1444779 -0.3577572 -1.1879531 2.2425230
[7] 4.3690613 -1.1082750 3.6650895 -2.3656322
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.7990474
[2,] -0.1003805
[3,] 0.1910851
[4,] 0.8941573
[5,] 3.3199573
>
> rowApply(tmp,sum)
[1] 3.4103278 3.7354575 -3.4269892 0.4805160 0.1595597 0.5386671
[7] 1.6695202 0.2324969 2.5917090 3.3422840
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 6 6 7 9 6 4 7 1 5
[2,] 6 1 7 9 4 7 6 8 2 3
[3,] 1 4 5 4 7 4 7 10 10 1
[4,] 9 3 8 1 10 1 1 3 9 10
[5,] 5 8 9 8 3 2 2 4 5 2
[6,] 3 7 1 5 1 9 8 9 6 8
[7,] 2 10 10 6 2 3 10 6 4 9
[8,] 4 2 2 3 8 8 9 2 8 4
[9,] 8 9 3 10 6 10 5 5 3 6
[10,] 7 5 4 2 5 5 3 1 7 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.8508667 0.6134547 0.7115320 0.6198001 1.7322754 0.7628097
[7] 4.2147550 1.6610630 3.7022433 -2.9347980 -3.0439751 -2.0510979
[13] -1.2344186 -2.6031812 -3.7179080 -1.4758413 1.2777073 -1.7631019
[19] 6.1671615 0.8768963
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.7149761
[2,] -0.3575600
[3,] -0.1461032
[4,] 0.1270536
[5,] 0.2407191
>
> rowApply(tmp,sum)
[1] -6.8448654 2.0418849 0.6694487 -3.4935005 10.2915419
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 15 10 7 14 2
[2,] 1 19 17 18 13
[3,] 13 3 8 17 16
[4,] 8 7 5 13 20
[5,] 9 8 19 16 7
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.1461032 -2.9992627 -0.31270509 -0.6154074 -0.604457344 1.45573156
[2,] 0.1270536 1.0395885 -0.91516094 -0.1137945 -0.006331851 0.02476823
[3,] -0.3575600 0.9679679 -0.04727495 -0.8877579 1.459688559 -0.91962537
[4,] 0.2407191 0.9844112 0.85037068 0.1424116 0.638039697 -0.90241737
[5,] -0.7149761 0.6207498 1.13630236 2.0943482 0.245336385 1.10435266
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.6295378 -0.4356938 1.31106179 -1.1159130 -0.5975014 -1.9026928
[2,] 0.9497405 0.2840379 0.90332753 0.1845423 -0.5914591 0.5039221
[3,] 0.9002775 0.2438767 0.11365361 0.4896146 0.4855361 0.3349341
[4,] 0.4817050 1.1511597 0.08499874 -3.0268122 -1.4883953 -0.7930753
[5,] 0.2534942 0.4176824 1.28920162 0.5337703 -0.8521554 -0.1941861
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.8818013 -1.2659745 -0.73480055 -0.72359110 -1.27752713 1.236089152
[2,] 0.7791987 0.8600556 -1.81774247 -0.98150023 1.39576844 -0.568450341
[3,] -1.7487315 -0.8688538 -1.76227198 0.95170968 0.72899266 -2.290129874
[4,] -1.7729941 -1.0465249 0.07690791 -0.79597580 0.05984147 -0.139257078
[5,] 0.6263070 -0.2818836 0.51999909 0.07351615 0.37063183 -0.001353754
[,19] [,20]
[1,] -0.1883536 -0.4391034
[2,] 0.7126527 -0.7283317
[3,] 1.6455612 1.2298413
[4,] 2.6006956 -0.8393092
[5,] 1.3966056 1.6537993
>
>
> 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 : 655 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 : 567 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 0.9507352 1.386511 -1.001736 0.9173754 -0.8106044 2.352788 -0.2934578
col8 col9 col10 col11 col12 col13 col14
row1 -0.1709964 -0.5046047 -0.4200156 -1.457057 0.9842446 1.357992 0.7014387
col15 col16 col17 col18 col19 col20
row1 -0.2008602 -0.6315457 -1.10563 0.1346235 -0.5549282 -0.5416043
> tmp[,"col10"]
col10
row1 -0.4200156
row2 0.2830103
row3 -0.5432206
row4 1.7912821
row5 1.9520202
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.9507352 1.3865112 -1.001736 0.9173754 -0.8106044 2.352788 -0.2934578
row5 -0.5148042 -0.1221256 -1.304552 1.1697084 -2.6017205 0.158355 0.9195873
col8 col9 col10 col11 col12 col13
row1 -0.1709964 -0.5046047 -0.4200156 -1.457057 0.9842446 1.35799183
row5 2.0458068 -0.9682317 1.9520202 1.390221 0.3574368 -0.01783671
col14 col15 col16 col17 col18 col19
row1 0.7014387 -0.2008602 -0.63154567 -1.105630 0.1346235 -0.55492816
row5 -0.8974877 1.5227938 -0.03080705 1.443021 -0.2346659 -0.02981248
col20
row1 -0.5416043
row5 -0.4707721
> tmp[,c("col6","col20")]
col6 col20
row1 2.3527881 -0.5416043
row2 -0.8597225 -0.8316347
row3 0.7386570 -1.0168695
row4 1.0507199 2.0098423
row5 0.1583550 -0.4707721
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 2.352788 -0.5416043
row5 0.158355 -0.4707721
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.29626 50.3749 49.64636 49.62063 49.79786 104.5072 50.00159 49.57053
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.61071 49.43131 51.0465 50.15503 50.77819 48.3258 49.06234 49.8581
col17 col18 col19 col20
row1 51.19797 49.23453 50.33191 105.0613
> tmp[,"col10"]
col10
row1 49.43131
row2 30.57336
row3 29.93357
row4 30.67325
row5 50.39218
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.29626 50.37490 49.64636 49.62063 49.79786 104.5072 50.00159 49.57053
row5 50.47457 48.29755 50.32919 50.04245 49.35619 103.6364 50.21686 49.68123
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.61071 49.43131 51.04650 50.15503 50.77819 48.32580 49.06234 49.85810
row5 49.95907 50.39218 49.39059 50.48317 50.39393 50.02355 49.62589 50.69554
col17 col18 col19 col20
row1 51.19797 49.23453 50.33191 105.0613
row5 49.33362 47.88391 49.67871 105.9829
> tmp[,c("col6","col20")]
col6 col20
row1 104.50719 105.06130
row2 74.77810 74.90371
row3 74.37624 74.35247
row4 72.03919 76.01651
row5 103.63635 105.98294
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.5072 105.0613
row5 103.6364 105.9829
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.5072 105.0613
row5 103.6364 105.9829
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.4491687
[2,] -0.7132112
[3,] -0.1309632
[4,] 0.2603560
[5,] 1.3817597
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.197011152 0.6315947
[2,] 1.022942396 0.6482327
[3,] -0.758927453 1.8504448
[4,] 0.921019242 -1.4391705
[5,] 0.007520158 0.7145922
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.5708709 0.41683756
[2,] 0.2958344 0.04346097
[3,] -1.7138605 0.84606562
[4,] 0.8882867 0.23598608
[5,] -0.2869831 -0.14886048
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.570871
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.5708709
[2,] 0.2958344
>
>
>
> 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 -1.7773452 -0.03230344 -0.2125116 0.07780616 0.1192804 0.008912024
row1 -0.9330395 -0.25120889 -0.7796091 -2.51216132 -0.1920759 1.847502467
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.1609941 0.3599991 -0.3911584 0.7659962 1.272779 0.1655737 1.239078
row1 -0.3076629 -2.0760098 0.5108368 0.5798692 -0.689367 -0.4196384 -1.104770
[,14] [,15] [,16] [,17] [,18] [,19]
row3 0.2882244 -0.9780907 0.7296131 0.02380583 -1.38462432 1.9846982
row1 1.1281815 -0.0841039 0.1882590 -1.11530816 -0.06892719 0.5194192
[,20]
row3 -1.7080264
row1 0.6411115
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.8487953 0.6418153 0.6478828 -0.1433803 -1.148977 0.692201 -0.103259
[,8] [,9] [,10]
row2 -0.6157237 -0.2045247 -0.06958103
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -1.421555 -0.4573241 0.7725091 -1.71834 0.8277206 1.557399 -0.4651406
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.9159873 0.03080285 0.7188937 2.166913 0.6751662 -1.110979 0.3004943
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.400898 -1.388381 0.9793416 0.3368133 1.381036 0.2053646
>
>
> 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: 0x6000004b0480>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11c377d2e6c03"
[2] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11c3772b57929"
[3] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11c376825ad94"
[4] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11c371a704f7"
[5] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11c377c36f4f9"
[6] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11c377c0d4724"
[7] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11c374bb9cc1c"
[8] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11c371307691b"
[9] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11c374b85755f"
[10] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11c3726dcd6b5"
[11] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11c376c941901"
[12] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11c376ef5c857"
[13] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11c374a3400aa"
[14] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11c371c17bef5"
[15] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11c375af9d53b"
>
>
> ### 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: 0x6000004bc000>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000004bc000>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6000004bc000>
> rowMedians(tmp)
[1] -0.555432705 -0.351213331 -0.099585994 -0.086944881 0.404572800
[6] -0.310142103 0.176007190 0.232702602 0.251457471 -0.282035114
[11] -0.279408574 0.043234228 -0.285920138 0.292242505 -0.088345230
[16] 0.058270068 0.333319554 -0.717664021 -0.078309795 -0.324681791
[21] 0.120151293 -0.167892419 -0.255844506 -0.428541388 0.151639767
[26] -0.034778629 -0.100718762 0.603489719 -0.084268321 0.464882632
[31] -0.041761232 0.209310673 0.055095878 0.393283338 -0.573134840
[36] -0.177073250 -0.203169767 0.596996345 -0.722119796 -0.233761453
[41] -0.235078852 0.016008409 -0.536324069 0.196689136 -0.302416016
[46] -0.046073563 -0.036658472 -0.008328290 0.077947104 0.167202561
[51] -0.008413989 -0.474363266 0.041547901 -0.029058434 0.370974152
[56] -0.401202504 -0.366303525 0.508985835 -0.814133277 -0.407630699
[61] -0.087959709 -0.019274900 0.115777131 0.390355622 0.022734169
[66] -0.347239004 -0.164273738 -0.039906674 0.074909158 -0.369063714
[71] -0.765889943 -0.058420376 0.113343380 0.012614149 0.164697370
[76] 0.073124495 0.103641726 0.222760063 0.086276800 0.448328850
[81] -0.581327176 -0.111128872 -0.283930488 -0.142697362 0.153694838
[86] -0.256089172 -0.125473413 -0.328725937 -0.402900155 -0.148268041
[91] -0.255138102 0.096617586 0.087007973 0.115770037 -0.360461610
[96] 0.255705275 -0.034867681 0.323179098 -0.121510339 -0.029636666
[101] 0.037094502 0.201296390 -0.404643947 0.157276964 -0.219216481
[106] 0.024669126 -0.205208478 0.059301765 -0.267314378 -0.513032781
[111] -0.013610208 0.028959707 -0.017884182 0.079940114 -0.054129697
[116] -0.038935825 0.325960329 0.558921040 -0.086033312 -0.121654800
[121] -0.401890701 -0.390617930 0.126950788 -0.468845196 -0.315769778
[126] 0.484151666 -0.089318362 -0.442522458 0.538855544 0.544200436
[131] 0.212916727 -0.348750150 -0.008717494 0.006709040 -0.656315833
[136] 0.562704348 -0.147347884 0.168056149 0.061815978 -0.100801410
[141] 0.178869110 0.093986652 0.901862514 -0.036619392 -0.261619726
[146] 0.140294045 -0.523008602 -0.007640090 0.187027580 -0.437386875
[151] 0.054201793 -0.107848460 -0.355717331 0.189827198 0.150397915
[156] -0.174729326 -0.203114493 -0.187140657 -0.099332150 0.323698749
[161] 0.363899147 0.309150365 0.172364357 0.216382618 0.329838260
[166] 0.321527183 0.476757531 0.017469919 -0.064727946 -0.248453775
[171] -0.169521528 -0.085265378 -0.171684792 0.324701304 -0.569169336
[176] -0.919677842 -0.284527040 0.338320693 -0.089246217 -0.391242914
[181] 0.071533487 0.142116767 0.260886894 0.084256402 0.135563932
[186] 0.005365919 -0.056639303 0.180505394 0.368030646 0.303500727
[191] -0.489336028 -0.225730940 -0.465441398 -0.640853659 0.056811370
[196] 0.149566599 -0.052970555 0.226035518 0.474141940 0.079825679
[201] -0.044040441 0.132724262 -0.205637005 -0.537375422 0.419573024
[206] 0.073331143 -0.257514954 0.737489378 0.109959150 -0.043459678
[211] -0.394534840 0.149011240 -0.218063300 0.292480534 -0.445320326
[216] -0.031308242 0.172631166 0.565581551 -0.145333847 -0.172098474
[221] 0.386479811 -0.246974589 -0.108885573 -0.862267264 -0.558077717
[226] 1.146126227 -0.091339065 0.013074860 -0.720084269 -0.028994897
>
> proc.time()
user system elapsed
0.642 3.231 4.261
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x6000010f8240>
> .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: 0x6000010f8240>
> .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: 0x6000010f8240>
> .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: 0x6000010f8240>
> 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: 0x6000010f42a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000010f42a0>
> .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: 0x6000010f42a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000010f42a0>
> .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: 0x6000010f42a0>
> 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: 0x6000010f4420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000010f4420>
> .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: 0x6000010f4420>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000010f4420>
> .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: 0x6000010f4420>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000010f4420>
> .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: 0x6000010f4420>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000010f4420>
> .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: 0x6000010f4420>
> 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: 0x6000010f4600>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000010f4600>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000010f4600>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000010f4600>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile11ee72fa5d2e" "BufferedMatrixFile11ee7545e6bd8"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile11ee72fa5d2e" "BufferedMatrixFile11ee7545e6bd8"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000010f48a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000010f48a0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000010f48a0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000010f48a0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000010f48a0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000010f48a0>
> .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: 0x6000010f4a80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000010f4a80>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000010f4a80>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000010f4a80>
> 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: 0x6000010f4c60>
> .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: 0x6000010f4c60>
> rm(P)
>
> proc.time()
user system elapsed
0.112 0.039 0.151
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.117 0.027 0.143