Ben Bolstad
| Snapshot Date: 2025-08-14 13:40 -0400 (Thu, 14 Aug 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_21 |
| git_last_commit: aa9e634 |
| git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-08-18 11:43 -0400 (Mon, 18 Aug 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4824 |
| palomino7 | Windows Server 2022 Datacenter | x64 | 4.5.1 (2025-06-13 ucrt) -- "Great Square Root" | 4566 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root" | 4604 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4545 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4579 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 252/2341 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.72.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| kunpeng2 | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.72.0 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.72.0.tar.gz |
| StartedAt: 2025-08-15 00:48:18 -0400 (Fri, 15 Aug 2025) |
| EndedAt: 2025-08-15 00:49:29 -0400 (Fri, 15 Aug 2025) |
| EllapsedTime: 71.4 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
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###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.72.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.1 RC (2025-06-05 r88288)
* using platform: x86_64-apple-darwin20
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 14.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.72.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... WARNING
Found the following significant warnings:
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
* used SDK: ‘MacOSX11.3.sdk’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 WARNING, 2 NOTEs
See
‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.72.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
using SDK: ‘MacOSX11.3.sdk’
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch x86_64 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/x86_64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R
installing to /Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.578 0.205 0.743
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
Ncells 480849 25.7 1056621 56.5 NA 634465 33.9
Vcells 891080 6.8 8388608 64.0 65536 2108740 16.1
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Aug 15 00:48:51 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] "Fri Aug 15 00:48:52 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: 0x6000005a8000>
>
>
>
> 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 Aug 15 00:48:58 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 Aug 15 00:49:00 2025"
>
> ColMode(tmp2)
<pointer: 0x6000005a8000>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.91056591 0.08354002 0.04673515 -0.57094904
[2,] 0.61991279 -0.09430599 1.03852175 -1.48666231
[3,] 0.06239384 -0.85265627 0.04687252 -0.04695112
[4,] 0.35676809 -0.23891304 1.49005957 0.96523977
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.91056591 0.08354002 0.04673515 0.57094904
[2,] 0.61991279 0.09430599 1.03852175 1.48666231
[3,] 0.06239384 0.85265627 0.04687252 0.04695112
[4,] 0.35676809 0.23891304 1.49005957 0.96523977
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9955273 0.2890329 0.2161831 0.7556117
[2,] 0.7873454 0.3070928 1.0190789 1.2192876
[3,] 0.2497876 0.9233939 0.2165006 0.2166821
[4,] 0.5973007 0.4887873 1.2206800 0.9824662
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.86584 27.97387 27.20857 33.12707
[2,] 33.49337 28.16523 36.22931 38.67954
[3,] 27.56027 35.08660 27.21188 27.21377
[4,] 31.32977 30.12679 38.69686 35.78990
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000005ac000>
> exp(tmp5)
<pointer: 0x6000005ac000>
> log(tmp5,2)
<pointer: 0x6000005ac000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.0288
> Min(tmp5)
[1] 54.01324
> mean(tmp5)
[1] 72.75124
> Sum(tmp5)
[1] 14550.25
> Var(tmp5)
[1] 860.2838
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.65038 69.82888 67.80502 72.27968 69.70641 69.92498 71.41461 76.09703
[9] 69.70806 70.09737
> rowSums(tmp5)
[1] 1813.008 1396.578 1356.100 1445.594 1394.128 1398.500 1428.292 1521.941
[9] 1394.161 1401.947
> rowVars(tmp5)
[1] 7961.17793 74.91357 96.29722 69.38817 91.88637 68.28395
[7] 49.53468 53.06788 50.70175 73.87820
> rowSd(tmp5)
[1] 89.225433 8.655262 9.813115 8.329956 9.585738 8.263410 7.038088
[8] 7.284771 7.120516 8.595243
> rowMax(tmp5)
[1] 468.02878 90.20954 92.75858 85.68122 90.95693 84.33059 80.83983
[8] 89.07916 87.63374 89.41443
> rowMin(tmp5)
[1] 56.63107 54.77266 56.63796 57.37517 54.01324 54.03311 56.81916 63.78482
[9] 58.72805 54.51954
>
> colMeans(tmp5)
[1] 109.84677 68.63723 70.09493 70.72115 75.25706 73.48263 71.81498
[8] 70.36755 65.00940 71.83135 72.98654 68.12761 72.94252 69.24489
[15] 71.08276 71.00442 71.20807 73.50255 67.40983 70.45260
> colSums(tmp5)
[1] 1098.4677 686.3723 700.9493 707.2115 752.5706 734.8263 718.1498
[8] 703.6755 650.0940 718.3135 729.8654 681.2761 729.4252 692.4489
[15] 710.8276 710.0442 712.0807 735.0255 674.0983 704.5260
> colVars(tmp5)
[1] 15911.81311 50.77939 100.22931 75.44501 72.56744 46.35857
[7] 65.91359 64.39807 81.24514 30.39858 29.40847 73.98363
[13] 68.20601 43.75883 94.68272 42.79184 115.88232 154.87524
[19] 41.16281 130.49120
> colSd(tmp5)
[1] 126.142035 7.125966 10.011459 8.685909 8.518653 6.808712
[7] 8.118718 8.024841 9.013609 5.513490 5.422957 8.601374
[13] 8.258693 6.615046 9.730505 6.541547 10.764865 12.444888
[19] 6.415825 11.423274
> colMax(tmp5)
[1] 468.02878 78.43893 81.04567 80.50639 90.20954 86.17764 84.33059
[8] 83.99984 87.43739 82.59761 83.58609 86.10608 87.63374 81.88557
[15] 89.07916 82.57249 89.41443 92.75858 78.75676 90.95693
> colMin(tmp5)
[1] 57.36309 58.22394 56.63107 56.64190 63.65650 63.78482 59.53297 54.01324
[9] 54.51954 62.46247 63.40227 57.37517 59.30681 59.62471 56.24767 58.72805
[17] 54.77266 54.03311 59.25664 58.35428
>
>
> ### 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] 90.65038 69.82888 67.80502 72.27968 69.70641 NA 71.41461 76.09703
[9] 69.70806 70.09737
> rowSums(tmp5)
[1] 1813.008 1396.578 1356.100 1445.594 1394.128 NA 1428.292 1521.941
[9] 1394.161 1401.947
> rowVars(tmp5)
[1] 7961.17793 74.91357 96.29722 69.38817 91.88637 71.80458
[7] 49.53468 53.06788 50.70175 73.87820
> rowSd(tmp5)
[1] 89.225433 8.655262 9.813115 8.329956 9.585738 8.473758 7.038088
[8] 7.284771 7.120516 8.595243
> rowMax(tmp5)
[1] 468.02878 90.20954 92.75858 85.68122 90.95693 NA 80.83983
[8] 89.07916 87.63374 89.41443
> rowMin(tmp5)
[1] 56.63107 54.77266 56.63796 57.37517 54.01324 NA 56.81916 63.78482
[9] 58.72805 54.51954
>
> colMeans(tmp5)
[1] 109.84677 68.63723 70.09493 NA 75.25706 73.48263 71.81498
[8] 70.36755 65.00940 71.83135 72.98654 68.12761 72.94252 69.24489
[15] 71.08276 71.00442 71.20807 73.50255 67.40983 70.45260
> colSums(tmp5)
[1] 1098.4677 686.3723 700.9493 NA 752.5706 734.8263 718.1498
[8] 703.6755 650.0940 718.3135 729.8654 681.2761 729.4252 692.4489
[15] 710.8276 710.0442 712.0807 735.0255 674.0983 704.5260
> colVars(tmp5)
[1] 15911.81311 50.77939 100.22931 NA 72.56744 46.35857
[7] 65.91359 64.39807 81.24514 30.39858 29.40847 73.98363
[13] 68.20601 43.75883 94.68272 42.79184 115.88232 154.87524
[19] 41.16281 130.49120
> colSd(tmp5)
[1] 126.142035 7.125966 10.011459 NA 8.518653 6.808712
[7] 8.118718 8.024841 9.013609 5.513490 5.422957 8.601374
[13] 8.258693 6.615046 9.730505 6.541547 10.764865 12.444888
[19] 6.415825 11.423274
> colMax(tmp5)
[1] 468.02878 78.43893 81.04567 NA 90.20954 86.17764 84.33059
[8] 83.99984 87.43739 82.59761 83.58609 86.10608 87.63374 81.88557
[15] 89.07916 82.57249 89.41443 92.75858 78.75676 90.95693
> colMin(tmp5)
[1] 57.36309 58.22394 56.63107 NA 63.65650 63.78482 59.53297 54.01324
[9] 54.51954 62.46247 63.40227 57.37517 59.30681 59.62471 56.24767 58.72805
[17] 54.77266 54.03311 59.25664 58.35428
>
> Max(tmp5,na.rm=TRUE)
[1] 468.0288
> Min(tmp5,na.rm=TRUE)
[1] 54.01324
> mean(tmp5,na.rm=TRUE)
[1] 72.75459
> Sum(tmp5,na.rm=TRUE)
[1] 14478.16
> Var(tmp5,na.rm=TRUE)
[1] 864.6264
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.65038 69.82888 67.80502 72.27968 69.70641 69.81128 71.41461 76.09703
[9] 69.70806 70.09737
> rowSums(tmp5,na.rm=TRUE)
[1] 1813.008 1396.578 1356.100 1445.594 1394.128 1326.414 1428.292 1521.941
[9] 1394.161 1401.947
> rowVars(tmp5,na.rm=TRUE)
[1] 7961.17793 74.91357 96.29722 69.38817 91.88637 71.80458
[7] 49.53468 53.06788 50.70175 73.87820
> rowSd(tmp5,na.rm=TRUE)
[1] 89.225433 8.655262 9.813115 8.329956 9.585738 8.473758 7.038088
[8] 7.284771 7.120516 8.595243
> rowMax(tmp5,na.rm=TRUE)
[1] 468.02878 90.20954 92.75858 85.68122 90.95693 84.33059 80.83983
[8] 89.07916 87.63374 89.41443
> rowMin(tmp5,na.rm=TRUE)
[1] 56.63107 54.77266 56.63796 57.37517 54.01324 54.03311 56.81916 63.78482
[9] 58.72805 54.51954
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.84677 68.63723 70.09493 70.56958 75.25706 73.48263 71.81498
[8] 70.36755 65.00940 71.83135 72.98654 68.12761 72.94252 69.24489
[15] 71.08276 71.00442 71.20807 73.50255 67.40983 70.45260
> colSums(tmp5,na.rm=TRUE)
[1] 1098.4677 686.3723 700.9493 635.1262 752.5706 734.8263 718.1498
[8] 703.6755 650.0940 718.3135 729.8654 681.2761 729.4252 692.4489
[15] 710.8276 710.0442 712.0807 735.0255 674.0983 704.5260
> colVars(tmp5,na.rm=TRUE)
[1] 15911.81311 50.77939 100.22931 84.61717 72.56744 46.35857
[7] 65.91359 64.39807 81.24514 30.39858 29.40847 73.98363
[13] 68.20601 43.75883 94.68272 42.79184 115.88232 154.87524
[19] 41.16281 130.49120
> colSd(tmp5,na.rm=TRUE)
[1] 126.142035 7.125966 10.011459 9.198759 8.518653 6.808712
[7] 8.118718 8.024841 9.013609 5.513490 5.422957 8.601374
[13] 8.258693 6.615046 9.730505 6.541547 10.764865 12.444888
[19] 6.415825 11.423274
> colMax(tmp5,na.rm=TRUE)
[1] 468.02878 78.43893 81.04567 80.50639 90.20954 86.17764 84.33059
[8] 83.99984 87.43739 82.59761 83.58609 86.10608 87.63374 81.88557
[15] 89.07916 82.57249 89.41443 92.75858 78.75676 90.95693
> colMin(tmp5,na.rm=TRUE)
[1] 57.36309 58.22394 56.63107 56.64190 63.65650 63.78482 59.53297 54.01324
[9] 54.51954 62.46247 63.40227 57.37517 59.30681 59.62471 56.24767 58.72805
[17] 54.77266 54.03311 59.25664 58.35428
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.65038 69.82888 67.80502 72.27968 69.70641 NaN 71.41461 76.09703
[9] 69.70806 70.09737
> rowSums(tmp5,na.rm=TRUE)
[1] 1813.008 1396.578 1356.100 1445.594 1394.128 0.000 1428.292 1521.941
[9] 1394.161 1401.947
> rowVars(tmp5,na.rm=TRUE)
[1] 7961.17793 74.91357 96.29722 69.38817 91.88637 NA
[7] 49.53468 53.06788 50.70175 73.87820
> rowSd(tmp5,na.rm=TRUE)
[1] 89.225433 8.655262 9.813115 8.329956 9.585738 NA 7.038088
[8] 7.284771 7.120516 8.595243
> rowMax(tmp5,na.rm=TRUE)
[1] 468.02878 90.20954 92.75858 85.68122 90.95693 NA 80.83983
[8] 89.07916 87.63374 89.41443
> rowMin(tmp5,na.rm=TRUE)
[1] 56.63107 54.77266 56.63796 57.37517 54.01324 NA 56.81916 63.78482
[9] 58.72805 54.51954
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.47268 68.60947 69.63071 NaN 74.93949 72.89477 70.42435
[8] 70.87494 65.47083 72.26412 73.27571 67.42656 72.40787 70.08651
[15] 71.88849 70.60108 69.97760 75.66582 68.02797 71.79686
> colSums(tmp5,na.rm=TRUE)
[1] 1030.2541 617.4853 626.6764 0.0000 674.4554 656.0529 633.8192
[8] 637.8745 589.2375 650.3771 659.4814 606.8390 651.6708 630.7786
[15] 646.9964 635.4097 629.7984 680.9924 612.2517 646.1717
> colVars(tmp5,na.rm=TRUE)
[1] 17660.04991 57.11814 110.33357 NA 80.50377 48.26555
[7] 52.39714 69.55156 89.00538 32.09136 32.14386 77.70250
[13] 73.51600 41.25996 99.21454 46.31063 113.33431 121.58757
[19] 42.00957 126.47351
> colSd(tmp5,na.rm=TRUE)
[1] 132.891120 7.557655 10.503979 NA 8.972389 6.947341
[7] 7.238587 8.339758 9.434266 5.664924 5.669555 8.814902
[13] 8.574147 6.423392 9.960649 6.805191 10.645859 11.026675
[19] 6.481479 11.246044
> colMax(tmp5,na.rm=TRUE)
[1] 468.02878 78.43893 81.04567 -Inf 90.20954 86.17764 79.09976
[8] 83.99984 87.43739 82.59761 83.58609 86.10608 87.63374 81.88557
[15] 89.07916 82.57249 89.41443 92.75858 78.75676 90.95693
> colMin(tmp5,na.rm=TRUE)
[1] 57.36309 58.22394 56.63107 Inf 63.65650 63.78482 59.53297 54.01324
[9] 54.51954 62.46247 63.40227 57.37517 59.30681 59.62471 56.24767 58.72805
[17] 54.77266 57.19896 59.25664 59.79278
>
>
>
>
> 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] 211.9463 122.6763 293.6107 195.2445 246.0778 281.3099 218.9205 228.9337
[9] 300.8307 131.7454
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 211.9463 122.6763 293.6107 195.2445 246.0778 281.3099 218.9205 228.9337
[9] 300.8307 131.7454
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -1.421085e-14 8.526513e-14 -2.842171e-14 -1.136868e-13 0.000000e+00
[6] -2.842171e-14 -5.684342e-14 5.684342e-14 9.947598e-14 -2.842171e-14
[11] -5.684342e-14 2.842171e-14 -1.421085e-14 1.705303e-13 1.136868e-13
[16] 2.842171e-14 2.842171e-14 -4.263256e-14 1.705303e-13 2.557954e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
3 3
9 13
8 4
10 9
8 20
9 20
9 8
1 9
4 16
2 19
3 8
10 4
9 9
1 11
5 1
3 11
7 17
9 20
4 18
9 11
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] 2.019535
> Min(tmp)
[1] -2.258272
> mean(tmp)
[1] 0.05091093
> Sum(tmp)
[1] 5.091093
> Var(tmp)
[1] 0.8913527
>
> rowMeans(tmp)
[1] 0.05091093
> rowSums(tmp)
[1] 5.091093
> rowVars(tmp)
[1] 0.8913527
> rowSd(tmp)
[1] 0.9441148
> rowMax(tmp)
[1] 2.019535
> rowMin(tmp)
[1] -2.258272
>
> colMeans(tmp)
[1] 1.167195094 -0.489591317 1.773789115 -0.111710801 0.047369751
[6] -0.629259879 1.501700172 -0.300059422 -0.194146331 -1.726716121
[11] -1.185654670 -1.589250341 -0.351445662 0.981463283 -0.155171508
[16] 0.196459776 -1.468407643 0.354561087 1.443067648 1.516014928
[21] -0.493926555 -0.717316538 0.011755829 1.024592045 -0.016994553
[26] -2.258271996 1.116299120 -1.315821746 0.546963953 -0.270953241
[31] 0.685033755 -1.533498487 -0.737419258 0.413457803 1.798790407
[36] -0.202665899 0.452786791 0.065629709 -1.363740443 0.562725056
[41] -0.415548015 0.469044152 -0.131460354 1.354211799 -0.786875461
[46] -1.161648008 0.248923206 1.050065598 -0.007734580 -0.458312121
[51] 0.530176711 0.002284411 -1.414028922 0.207051192 -0.240198881
[56] 1.772677871 -1.623352659 -0.544607255 0.752856685 0.010273508
[61] -0.123702859 1.007388625 2.019535118 1.516575516 -0.019635385
[66] -0.673457831 0.212173513 -0.690169463 0.347299187 1.728466709
[71] 0.738002804 -0.640708491 -0.693671928 -0.299346911 0.270015467
[76] 0.493717648 0.497946258 -0.699591977 -0.081812984 -1.408709447
[81] -0.670612429 -0.931829313 0.703514367 -0.029372961 1.607546712
[86] -0.762773545 1.167112578 -1.111293894 0.022577177 0.118330069
[91] 1.936523083 0.920860804 -0.873520032 0.036470875 -0.101054620
[96] -1.020235008 0.839149867 0.933526433 0.721096085 -0.076668174
> colSums(tmp)
[1] 1.167195094 -0.489591317 1.773789115 -0.111710801 0.047369751
[6] -0.629259879 1.501700172 -0.300059422 -0.194146331 -1.726716121
[11] -1.185654670 -1.589250341 -0.351445662 0.981463283 -0.155171508
[16] 0.196459776 -1.468407643 0.354561087 1.443067648 1.516014928
[21] -0.493926555 -0.717316538 0.011755829 1.024592045 -0.016994553
[26] -2.258271996 1.116299120 -1.315821746 0.546963953 -0.270953241
[31] 0.685033755 -1.533498487 -0.737419258 0.413457803 1.798790407
[36] -0.202665899 0.452786791 0.065629709 -1.363740443 0.562725056
[41] -0.415548015 0.469044152 -0.131460354 1.354211799 -0.786875461
[46] -1.161648008 0.248923206 1.050065598 -0.007734580 -0.458312121
[51] 0.530176711 0.002284411 -1.414028922 0.207051192 -0.240198881
[56] 1.772677871 -1.623352659 -0.544607255 0.752856685 0.010273508
[61] -0.123702859 1.007388625 2.019535118 1.516575516 -0.019635385
[66] -0.673457831 0.212173513 -0.690169463 0.347299187 1.728466709
[71] 0.738002804 -0.640708491 -0.693671928 -0.299346911 0.270015467
[76] 0.493717648 0.497946258 -0.699591977 -0.081812984 -1.408709447
[81] -0.670612429 -0.931829313 0.703514367 -0.029372961 1.607546712
[86] -0.762773545 1.167112578 -1.111293894 0.022577177 0.118330069
[91] 1.936523083 0.920860804 -0.873520032 0.036470875 -0.101054620
[96] -1.020235008 0.839149867 0.933526433 0.721096085 -0.076668174
> 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] 1.167195094 -0.489591317 1.773789115 -0.111710801 0.047369751
[6] -0.629259879 1.501700172 -0.300059422 -0.194146331 -1.726716121
[11] -1.185654670 -1.589250341 -0.351445662 0.981463283 -0.155171508
[16] 0.196459776 -1.468407643 0.354561087 1.443067648 1.516014928
[21] -0.493926555 -0.717316538 0.011755829 1.024592045 -0.016994553
[26] -2.258271996 1.116299120 -1.315821746 0.546963953 -0.270953241
[31] 0.685033755 -1.533498487 -0.737419258 0.413457803 1.798790407
[36] -0.202665899 0.452786791 0.065629709 -1.363740443 0.562725056
[41] -0.415548015 0.469044152 -0.131460354 1.354211799 -0.786875461
[46] -1.161648008 0.248923206 1.050065598 -0.007734580 -0.458312121
[51] 0.530176711 0.002284411 -1.414028922 0.207051192 -0.240198881
[56] 1.772677871 -1.623352659 -0.544607255 0.752856685 0.010273508
[61] -0.123702859 1.007388625 2.019535118 1.516575516 -0.019635385
[66] -0.673457831 0.212173513 -0.690169463 0.347299187 1.728466709
[71] 0.738002804 -0.640708491 -0.693671928 -0.299346911 0.270015467
[76] 0.493717648 0.497946258 -0.699591977 -0.081812984 -1.408709447
[81] -0.670612429 -0.931829313 0.703514367 -0.029372961 1.607546712
[86] -0.762773545 1.167112578 -1.111293894 0.022577177 0.118330069
[91] 1.936523083 0.920860804 -0.873520032 0.036470875 -0.101054620
[96] -1.020235008 0.839149867 0.933526433 0.721096085 -0.076668174
> colMin(tmp)
[1] 1.167195094 -0.489591317 1.773789115 -0.111710801 0.047369751
[6] -0.629259879 1.501700172 -0.300059422 -0.194146331 -1.726716121
[11] -1.185654670 -1.589250341 -0.351445662 0.981463283 -0.155171508
[16] 0.196459776 -1.468407643 0.354561087 1.443067648 1.516014928
[21] -0.493926555 -0.717316538 0.011755829 1.024592045 -0.016994553
[26] -2.258271996 1.116299120 -1.315821746 0.546963953 -0.270953241
[31] 0.685033755 -1.533498487 -0.737419258 0.413457803 1.798790407
[36] -0.202665899 0.452786791 0.065629709 -1.363740443 0.562725056
[41] -0.415548015 0.469044152 -0.131460354 1.354211799 -0.786875461
[46] -1.161648008 0.248923206 1.050065598 -0.007734580 -0.458312121
[51] 0.530176711 0.002284411 -1.414028922 0.207051192 -0.240198881
[56] 1.772677871 -1.623352659 -0.544607255 0.752856685 0.010273508
[61] -0.123702859 1.007388625 2.019535118 1.516575516 -0.019635385
[66] -0.673457831 0.212173513 -0.690169463 0.347299187 1.728466709
[71] 0.738002804 -0.640708491 -0.693671928 -0.299346911 0.270015467
[76] 0.493717648 0.497946258 -0.699591977 -0.081812984 -1.408709447
[81] -0.670612429 -0.931829313 0.703514367 -0.029372961 1.607546712
[86] -0.762773545 1.167112578 -1.111293894 0.022577177 0.118330069
[91] 1.936523083 0.920860804 -0.873520032 0.036470875 -0.101054620
[96] -1.020235008 0.839149867 0.933526433 0.721096085 -0.076668174
> colMedians(tmp)
[1] 1.167195094 -0.489591317 1.773789115 -0.111710801 0.047369751
[6] -0.629259879 1.501700172 -0.300059422 -0.194146331 -1.726716121
[11] -1.185654670 -1.589250341 -0.351445662 0.981463283 -0.155171508
[16] 0.196459776 -1.468407643 0.354561087 1.443067648 1.516014928
[21] -0.493926555 -0.717316538 0.011755829 1.024592045 -0.016994553
[26] -2.258271996 1.116299120 -1.315821746 0.546963953 -0.270953241
[31] 0.685033755 -1.533498487 -0.737419258 0.413457803 1.798790407
[36] -0.202665899 0.452786791 0.065629709 -1.363740443 0.562725056
[41] -0.415548015 0.469044152 -0.131460354 1.354211799 -0.786875461
[46] -1.161648008 0.248923206 1.050065598 -0.007734580 -0.458312121
[51] 0.530176711 0.002284411 -1.414028922 0.207051192 -0.240198881
[56] 1.772677871 -1.623352659 -0.544607255 0.752856685 0.010273508
[61] -0.123702859 1.007388625 2.019535118 1.516575516 -0.019635385
[66] -0.673457831 0.212173513 -0.690169463 0.347299187 1.728466709
[71] 0.738002804 -0.640708491 -0.693671928 -0.299346911 0.270015467
[76] 0.493717648 0.497946258 -0.699591977 -0.081812984 -1.408709447
[81] -0.670612429 -0.931829313 0.703514367 -0.029372961 1.607546712
[86] -0.762773545 1.167112578 -1.111293894 0.022577177 0.118330069
[91] 1.936523083 0.920860804 -0.873520032 0.036470875 -0.101054620
[96] -1.020235008 0.839149867 0.933526433 0.721096085 -0.076668174
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.167195 -0.4895913 1.773789 -0.1117108 0.04736975 -0.6292599 1.5017
[2,] 1.167195 -0.4895913 1.773789 -0.1117108 0.04736975 -0.6292599 1.5017
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.3000594 -0.1941463 -1.726716 -1.185655 -1.58925 -0.3514457 0.9814633
[2,] -0.3000594 -0.1941463 -1.726716 -1.185655 -1.58925 -0.3514457 0.9814633
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.1551715 0.1964598 -1.468408 0.3545611 1.443068 1.516015 -0.4939266
[2,] -0.1551715 0.1964598 -1.468408 0.3545611 1.443068 1.516015 -0.4939266
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.7173165 0.01175583 1.024592 -0.01699455 -2.258272 1.116299 -1.315822
[2,] -0.7173165 0.01175583 1.024592 -0.01699455 -2.258272 1.116299 -1.315822
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.546964 -0.2709532 0.6850338 -1.533498 -0.7374193 0.4134578 1.79879
[2,] 0.546964 -0.2709532 0.6850338 -1.533498 -0.7374193 0.4134578 1.79879
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.2026659 0.4527868 0.06562971 -1.36374 0.5627251 -0.415548 0.4690442
[2,] -0.2026659 0.4527868 0.06562971 -1.36374 0.5627251 -0.415548 0.4690442
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.1314604 1.354212 -0.7868755 -1.161648 0.2489232 1.050066 -0.00773458
[2,] -0.1314604 1.354212 -0.7868755 -1.161648 0.2489232 1.050066 -0.00773458
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.4583121 0.5301767 0.002284411 -1.414029 0.2070512 -0.2401989 1.772678
[2,] -0.4583121 0.5301767 0.002284411 -1.414029 0.2070512 -0.2401989 1.772678
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -1.623353 -0.5446073 0.7528567 0.01027351 -0.1237029 1.007389 2.019535
[2,] -1.623353 -0.5446073 0.7528567 0.01027351 -0.1237029 1.007389 2.019535
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 1.516576 -0.01963539 -0.6734578 0.2121735 -0.6901695 0.3472992 1.728467
[2,] 1.516576 -0.01963539 -0.6734578 0.2121735 -0.6901695 0.3472992 1.728467
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.7380028 -0.6407085 -0.6936719 -0.2993469 0.2700155 0.4937176 0.4979463
[2,] 0.7380028 -0.6407085 -0.6936719 -0.2993469 0.2700155 0.4937176 0.4979463
[,78] [,79] [,80] [,81] [,82] [,83]
[1,] -0.699592 -0.08181298 -1.408709 -0.6706124 -0.9318293 0.7035144
[2,] -0.699592 -0.08181298 -1.408709 -0.6706124 -0.9318293 0.7035144
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.02937296 1.607547 -0.7627735 1.167113 -1.111294 0.02257718 0.1183301
[2,] -0.02937296 1.607547 -0.7627735 1.167113 -1.111294 0.02257718 0.1183301
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 1.936523 0.9208608 -0.87352 0.03647087 -0.1010546 -1.020235 0.8391499
[2,] 1.936523 0.9208608 -0.87352 0.03647087 -0.1010546 -1.020235 0.8391499
[,98] [,99] [,100]
[1,] 0.9335264 0.7210961 -0.07666817
[2,] 0.9335264 0.7210961 -0.07666817
>
>
> Max(tmp2)
[1] 2.2955
> Min(tmp2)
[1] -2.512741
> mean(tmp2)
[1] -0.1589744
> Sum(tmp2)
[1] -15.89744
> Var(tmp2)
[1] 0.9964817
>
> rowMeans(tmp2)
[1] 0.832245045 -1.416794553 -0.920558570 1.286583136 0.003131468
[6] 0.058736002 0.623742486 -0.127107243 0.053547317 -0.030543975
[11] 0.576245910 0.934963208 -0.348681821 1.435652225 0.893907726
[16] 0.332755620 -1.365522126 0.425292921 1.015415594 -0.320570809
[21] 2.295499859 -0.141307017 0.726089611 0.320285371 -0.614464960
[26] 1.289677568 -0.113796468 -0.528753940 -1.157142029 0.050707855
[31] 1.175769735 1.455886235 -1.119436116 -0.712866346 -1.259721360
[36] -1.760849636 -0.263794311 0.800078514 -1.965484994 -0.909335127
[41] 0.007053336 -2.512741331 1.707819677 1.072146267 -0.087908449
[46] -0.130797510 -0.386179965 0.709637223 -0.328902931 0.754286790
[51] -1.149090241 -0.864642982 -1.267965514 -0.269312724 -0.265992031
[56] -0.051504899 0.928798533 -2.458320588 0.068080793 0.029021459
[61] 0.211038483 -0.737496253 -0.994634753 0.145152703 -0.074322056
[66] 1.652979083 0.495016471 -0.202864339 -0.837819081 0.400047174
[71] -0.470107562 -1.156523751 1.036438595 -1.906337817 0.771798405
[76] 1.365343469 -0.573331564 -1.408890702 -0.423782542 0.711609739
[81] 1.660595421 -0.163090961 -0.908052883 -0.287214810 -0.553117940
[86] -0.013224854 -0.677452453 -1.502082555 -0.767997122 0.036635191
[91] -2.407599995 0.840998961 -0.560418173 0.568565724 -1.701155953
[96] -1.234048134 -1.132283578 -1.240585908 0.400250398 -1.272441599
> rowSums(tmp2)
[1] 0.832245045 -1.416794553 -0.920558570 1.286583136 0.003131468
[6] 0.058736002 0.623742486 -0.127107243 0.053547317 -0.030543975
[11] 0.576245910 0.934963208 -0.348681821 1.435652225 0.893907726
[16] 0.332755620 -1.365522126 0.425292921 1.015415594 -0.320570809
[21] 2.295499859 -0.141307017 0.726089611 0.320285371 -0.614464960
[26] 1.289677568 -0.113796468 -0.528753940 -1.157142029 0.050707855
[31] 1.175769735 1.455886235 -1.119436116 -0.712866346 -1.259721360
[36] -1.760849636 -0.263794311 0.800078514 -1.965484994 -0.909335127
[41] 0.007053336 -2.512741331 1.707819677 1.072146267 -0.087908449
[46] -0.130797510 -0.386179965 0.709637223 -0.328902931 0.754286790
[51] -1.149090241 -0.864642982 -1.267965514 -0.269312724 -0.265992031
[56] -0.051504899 0.928798533 -2.458320588 0.068080793 0.029021459
[61] 0.211038483 -0.737496253 -0.994634753 0.145152703 -0.074322056
[66] 1.652979083 0.495016471 -0.202864339 -0.837819081 0.400047174
[71] -0.470107562 -1.156523751 1.036438595 -1.906337817 0.771798405
[76] 1.365343469 -0.573331564 -1.408890702 -0.423782542 0.711609739
[81] 1.660595421 -0.163090961 -0.908052883 -0.287214810 -0.553117940
[86] -0.013224854 -0.677452453 -1.502082555 -0.767997122 0.036635191
[91] -2.407599995 0.840998961 -0.560418173 0.568565724 -1.701155953
[96] -1.234048134 -1.132283578 -1.240585908 0.400250398 -1.272441599
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 0.832245045 -1.416794553 -0.920558570 1.286583136 0.003131468
[6] 0.058736002 0.623742486 -0.127107243 0.053547317 -0.030543975
[11] 0.576245910 0.934963208 -0.348681821 1.435652225 0.893907726
[16] 0.332755620 -1.365522126 0.425292921 1.015415594 -0.320570809
[21] 2.295499859 -0.141307017 0.726089611 0.320285371 -0.614464960
[26] 1.289677568 -0.113796468 -0.528753940 -1.157142029 0.050707855
[31] 1.175769735 1.455886235 -1.119436116 -0.712866346 -1.259721360
[36] -1.760849636 -0.263794311 0.800078514 -1.965484994 -0.909335127
[41] 0.007053336 -2.512741331 1.707819677 1.072146267 -0.087908449
[46] -0.130797510 -0.386179965 0.709637223 -0.328902931 0.754286790
[51] -1.149090241 -0.864642982 -1.267965514 -0.269312724 -0.265992031
[56] -0.051504899 0.928798533 -2.458320588 0.068080793 0.029021459
[61] 0.211038483 -0.737496253 -0.994634753 0.145152703 -0.074322056
[66] 1.652979083 0.495016471 -0.202864339 -0.837819081 0.400047174
[71] -0.470107562 -1.156523751 1.036438595 -1.906337817 0.771798405
[76] 1.365343469 -0.573331564 -1.408890702 -0.423782542 0.711609739
[81] 1.660595421 -0.163090961 -0.908052883 -0.287214810 -0.553117940
[86] -0.013224854 -0.677452453 -1.502082555 -0.767997122 0.036635191
[91] -2.407599995 0.840998961 -0.560418173 0.568565724 -1.701155953
[96] -1.234048134 -1.132283578 -1.240585908 0.400250398 -1.272441599
> rowMin(tmp2)
[1] 0.832245045 -1.416794553 -0.920558570 1.286583136 0.003131468
[6] 0.058736002 0.623742486 -0.127107243 0.053547317 -0.030543975
[11] 0.576245910 0.934963208 -0.348681821 1.435652225 0.893907726
[16] 0.332755620 -1.365522126 0.425292921 1.015415594 -0.320570809
[21] 2.295499859 -0.141307017 0.726089611 0.320285371 -0.614464960
[26] 1.289677568 -0.113796468 -0.528753940 -1.157142029 0.050707855
[31] 1.175769735 1.455886235 -1.119436116 -0.712866346 -1.259721360
[36] -1.760849636 -0.263794311 0.800078514 -1.965484994 -0.909335127
[41] 0.007053336 -2.512741331 1.707819677 1.072146267 -0.087908449
[46] -0.130797510 -0.386179965 0.709637223 -0.328902931 0.754286790
[51] -1.149090241 -0.864642982 -1.267965514 -0.269312724 -0.265992031
[56] -0.051504899 0.928798533 -2.458320588 0.068080793 0.029021459
[61] 0.211038483 -0.737496253 -0.994634753 0.145152703 -0.074322056
[66] 1.652979083 0.495016471 -0.202864339 -0.837819081 0.400047174
[71] -0.470107562 -1.156523751 1.036438595 -1.906337817 0.771798405
[76] 1.365343469 -0.573331564 -1.408890702 -0.423782542 0.711609739
[81] 1.660595421 -0.163090961 -0.908052883 -0.287214810 -0.553117940
[86] -0.013224854 -0.677452453 -1.502082555 -0.767997122 0.036635191
[91] -2.407599995 0.840998961 -0.560418173 0.568565724 -1.701155953
[96] -1.234048134 -1.132283578 -1.240585908 0.400250398 -1.272441599
>
> colMeans(tmp2)
[1] -0.1589744
> colSums(tmp2)
[1] -15.89744
> colVars(tmp2)
[1] 0.9964817
> colSd(tmp2)
[1] 0.9982393
> colMax(tmp2)
[1] 2.2955
> colMin(tmp2)
[1] -2.512741
> colMedians(tmp2)
[1] -0.1289524
> colRanges(tmp2)
[,1]
[1,] -2.512741
[2,] 2.295500
>
> 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] -7.4440833 -0.1278542 -0.6526737 1.3564921 2.0697416 1.1429518
[7] 1.0040737 -0.3986870 1.6359957 -1.7720990
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.73997556
[2,] -1.05358996
[3,] -0.53232007
[4,] 0.04164232
[5,] 0.72519716
>
> rowApply(tmp,sum)
[1] -2.84402696 -3.57858617 3.35629220 -0.09807847 -3.24242811 -0.96807748
[7] -2.23719679 -1.54631574 5.14129645 2.83097887
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 1 3 5 4 8 8 3 2 1
[2,] 8 6 1 1 5 4 6 9 9 5
[3,] 5 9 8 8 2 9 3 5 5 2
[4,] 2 4 4 4 7 10 4 10 6 7
[5,] 6 2 2 7 10 5 10 4 3 4
[6,] 7 7 6 3 9 6 1 7 10 8
[7,] 10 5 7 10 1 1 7 6 7 6
[8,] 4 10 10 2 8 2 2 1 8 9
[9,] 3 8 9 6 3 3 9 8 4 10
[10,] 9 3 5 9 6 7 5 2 1 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.58325163 1.73586018 -1.46786993 0.30295734 0.64180517 0.69887102
[7] 0.71959061 4.15337634 1.07265610 -0.01483327 -0.90602808 0.33061782
[13] -1.14672827 2.38821957 -1.92678906 -1.31858413 2.90220377 -2.80156175
[19] -0.25523344 3.71710194
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.9395131
[2,] -1.0045502
[3,] -0.2373123
[4,] 0.2761867
[5,] 1.3219372
>
> rowApply(tmp,sum)
[1] 4.2183024 2.9034764 1.9631900 0.6276732 -2.4702618
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 20 12 5 1
[2,] 20 14 20 1 9
[3,] 1 11 6 11 20
[4,] 17 10 5 10 6
[5,] 5 15 4 15 13
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.2373123 2.3552029 -2.1964317 1.36718287 -0.3603293 0.3845287
[2,] 1.3219372 0.4303921 0.1694490 0.05578727 0.4363016 -0.2997022
[3,] 0.2761867 1.6632377 -0.3487600 -0.52140889 -0.8160624 0.5642381
[4,] -1.0045502 -2.5281905 -0.1750194 -0.24043210 1.2041307 -0.5645483
[5,] -1.9395131 -0.1847821 1.0828921 -0.35817182 0.1777646 0.6143547
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.44203798 0.14505892 0.71111828 0.7931842 0.33931527 0.50653991
[2,] 0.40041793 1.05415419 0.18259965 -0.3348437 0.51297348 -0.82889151
[3,] 0.29302326 0.02809799 0.09486402 0.5224618 -0.09308386 -0.02691152
[4,] -1.44931999 1.98187640 -0.73039029 -1.4602441 -0.94230581 1.66532318
[5,] 0.03343144 0.94418883 0.81446442 0.4646085 -0.72292716 -0.98544225
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.4341931 2.2140363 -1.5582983 0.3265015 0.1759858 -0.07021562
[2,] -0.3767947 -0.2746677 -0.5545078 -0.6124122 -0.1321980 -0.13021136
[3,] -1.0573588 0.8803634 0.1952445 -1.8057929 1.2645025 -1.16849395
[4,] 0.8306518 1.2393412 0.1742353 2.2180050 0.8453638 -1.09620320
[5,] -0.1090334 -1.6708537 -0.1834627 -1.4448856 0.7485497 -0.33643763
[,19] [,20]
[1,] -1.9757641 0.2901541
[2,] 1.1786011 0.7050920
[3,] 1.5185098 0.5003325
[4,] -0.6573330 1.3172827
[5,] -0.3192473 0.9042406
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.9451878 0.9359567 -0.6409427 1.494122 0.3346907 0.6228446 -0.2758024
col8 col9 col10 col11 col12 col13 col14
row1 -1.481396 0.7910584 0.1679665 -1.624055 -0.2352432 0.4327874 -1.624065
col15 col16 col17 col18 col19 col20
row1 0.3151664 -0.3745167 0.4008738 -0.9993165 0.8576888 -0.5565773
> tmp[,"col10"]
col10
row1 0.1679665
row2 -1.2804681
row3 1.5133136
row4 1.5077612
row5 0.1724864
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.9451878 0.9359567 -0.6409427 1.4941217 0.3346907 0.6228446
row5 0.9397699 -1.2164717 -0.5319153 -0.2445053 -0.5279576 -1.2217151
col7 col8 col9 col10 col11 col12 col13
row1 -0.2758024 -1.4813963 0.7910584 0.1679665 -1.6240548 -0.2352432 0.4327874
row5 -2.1629734 0.3641297 -0.5869168 0.1724864 -0.6292983 -0.3614713 0.5147928
col14 col15 col16 col17 col18 col19 col20
row1 -1.6240648 0.3151664 -0.3745167 0.4008738 -0.9993165 0.8576888 -0.5565773
row5 0.4827414 0.4566357 -1.5760701 1.2745840 0.2664151 -0.7555173 -0.8512582
> tmp[,c("col6","col20")]
col6 col20
row1 0.6228446 -0.5565773
row2 -0.7739947 1.0924803
row3 0.3534069 1.2754835
row4 -0.9038005 0.4303581
row5 -1.2217151 -0.8512582
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.6228446 -0.5565773
row5 -1.2217151 -0.8512582
>
>
>
>
> 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 50.22396 50.30883 49.06811 50.94444 51.67038 104.3165 49.19831 50.98802
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.09219 47.94168 50.10637 50.60789 50.17843 50.97002 50.4656 49.92264
col17 col18 col19 col20
row1 48.19156 50.0793 51.41304 103.5032
> tmp[,"col10"]
col10
row1 47.94168
row2 30.37750
row3 31.05947
row4 28.02940
row5 49.60736
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.22396 50.30883 49.06811 50.94444 51.67038 104.3165 49.19831 50.98802
row5 51.17826 50.06708 48.12940 49.47889 49.71786 104.0751 49.78259 50.21377
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.09219 47.94168 50.10637 50.60789 50.17843 50.97002 50.46560 49.92264
row5 50.19705 49.60736 49.54838 50.78648 50.44969 48.42682 48.95861 50.35298
col17 col18 col19 col20
row1 48.19156 50.07930 51.41304 103.5032
row5 49.91611 50.44707 49.92095 103.4340
> tmp[,c("col6","col20")]
col6 col20
row1 104.31649 103.50316
row2 74.76737 73.56174
row3 74.75556 75.06801
row4 74.72392 75.52329
row5 104.07510 103.43398
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.3165 103.5032
row5 104.0751 103.4340
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.3165 103.5032
row5 104.0751 103.4340
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.4766158
[2,] -0.7121026
[3,] 0.1902166
[4,] -0.9349984
[5,] 1.3923929
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.4916269 0.68996287
[2,] 1.0145788 -1.24018568
[3,] -1.3441414 0.05062612
[4,] 0.4248473 0.32021214
[5,] -0.2442195 0.62867763
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.009531877 0.04094595
[2,] -0.925826822 1.15939876
[3,] 0.566598786 0.10617923
[4,] -0.106251600 0.52628270
[5,] -0.191626117 0.40672291
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.009531877
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.009531877
[2,] -0.925826822
>
>
>
> 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 1.215973 -0.08967611 1.2592345 0.7579268 0.03165719 0.8521632
row1 1.100344 0.63318378 0.9909061 -1.3421514 -1.29185737 -0.5920386
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.5201346 -0.9462125 -0.7375150 -0.5597967 -1.4919773 -1.2043627
row1 -1.5149251 -0.5069302 -0.2785106 0.7422045 -0.6873371 -0.4847532
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.6298617 -1.524554 0.1233266 -0.3727897 1.383182 -0.08329700 0.6657581
row1 -0.4081799 -0.685402 0.9217044 0.8314323 -1.291265 -0.02917959 -1.5568730
[,20]
row3 1.0819584
row1 0.7165018
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.475721 -0.01091528 0.2432015 1.395345 -1.262217 -0.08303494 -0.3304775
[,8] [,9] [,10]
row2 -0.8528358 -1.313147 1.158486
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.1825707 0.4404727 1.260805 -0.6088278 -0.7461195 -0.6858332 -1.59863
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.04474224 0.162856 0.2992841 1.169296 -0.8607484 0.4955 0.6849824
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.8041193 -0.6830451 -1.093166 -0.9681581 -0.5501178 -0.9960199
>
>
> 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: 0x6000005880c0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM167fe7245548c"
[2] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM167fe25b1edf0"
[3] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM167fe447c3ae5"
[4] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM167fe37feb383"
[5] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM167fe32bb7a2d"
[6] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM167fe32523a60"
[7] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM167fe34768e6f"
[8] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM167fe53813451"
[9] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM167fe4791dcab"
[10] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM167fe392e8342"
[11] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM167fe1cab7f62"
[12] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM167fe3f3809a2"
[13] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM167fe78008b1a"
[14] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM167fe6bac9582"
[15] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM167fef8bc108"
>
>
> ### 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: 0x6000005801e0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000005801e0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6000005801e0>
> rowMedians(tmp)
[1] -0.600644440 -0.200747284 -0.193976288 -0.150077114 0.295738519
[6] 0.429565781 0.372424366 0.290467425 0.240317425 0.244867363
[11] -0.312647186 0.390866419 0.533207980 0.286783773 0.076033424
[16] -0.414640305 0.245697023 0.055673910 0.184433757 0.361107563
[21] 0.053371507 -0.418527495 -0.020672475 -0.226216095 -0.342449882
[26] 0.310315811 -0.417368598 0.307014278 0.078376003 0.263871000
[31] 0.540392078 -0.037021336 0.316502354 0.276432772 0.205551884
[36] 0.200926611 -0.409164387 -0.147210441 -0.039865366 0.195476379
[41] 0.127714626 -0.382323188 -0.740989488 0.089474832 0.310159862
[46] -0.258461796 0.154939978 0.060356160 -0.210959694 0.199153438
[51] -0.336445395 0.249793071 -0.182123520 0.056526225 -0.491279699
[56] -0.351713499 -0.333658174 -0.105128165 0.213270997 -0.240437916
[61] -0.461079813 0.179830332 -0.419772378 0.231965565 0.059520199
[66] -0.189782807 -0.455329769 -0.070068879 0.474881710 0.246587443
[71] -0.310412389 -0.310717140 0.159250196 0.216978528 -0.475538874
[76] -0.488902422 0.109347769 -0.182191098 0.222220072 0.390484904
[81] -0.216728939 -0.525445030 -0.149789406 -0.176158290 -0.031951954
[86] 0.238170872 -0.105104238 -0.183401987 -0.003947215 -0.362137174
[91] 0.695056288 -0.038418012 0.366880991 -0.303700486 0.461258237
[96] -0.283813771 0.344476194 -0.312461876 -0.129906240 -0.152080918
[101] 0.355031059 0.357251854 0.322883340 -0.066904803 -0.152283533
[106] 0.179805595 -0.664411602 -0.315483975 -0.098116060 -0.323694316
[111] 0.455322903 -0.029011227 -0.445752099 0.385253820 0.004795397
[116] 0.256559852 0.396954091 0.156998502 0.182191936 0.347600926
[121] 0.127996381 0.069897968 0.381651418 0.341138854 -0.051710647
[126] -0.405471345 0.503443190 -0.287823176 0.359617602 0.120027187
[131] -0.432591243 0.050500457 0.315397348 -0.347172126 0.223119414
[136] -0.023564927 0.149431130 -0.302882564 -0.041123221 0.238105575
[141] -0.469331695 0.472763861 -0.120493712 -0.376780624 0.282429419
[146] 0.582183783 -0.643817929 0.137943883 0.022078219 -0.257139294
[151] -0.243574899 0.166489366 -0.190737974 0.323742834 -0.062602234
[156] -0.312380572 -0.088143694 -0.048246900 -0.189652329 0.243397029
[161] -0.126703799 -0.122484616 0.454246717 -0.351527877 -0.022717815
[166] 0.681197571 0.208048692 0.148273145 -0.313059854 0.384902563
[171] 0.238201368 0.134869957 -0.017113781 -0.398431567 0.397419380
[176] -0.264603741 -0.052444684 -0.387333281 0.798713691 -0.655790582
[181] 0.237480062 0.061097557 0.250018120 0.035465243 0.630962748
[186] 0.389281175 -0.213451291 -0.056021372 -0.226891171 0.093470840
[191] -0.463067963 0.162269578 -0.704906964 -0.322037391 0.311789050
[196] 0.207232842 0.162326621 -0.055287605 -0.106083549 0.427059669
[201] 0.194604085 -0.164957309 0.055348223 0.072015913 0.012613351
[206] -0.254346244 -0.058978372 0.676428976 -0.231711815 0.181618981
[211] -0.110180321 0.255206925 -0.279592076 0.208217813 0.495962131
[216] 0.118793916 -0.233451889 -0.209919268 -0.215665893 -0.203117503
[221] 0.289464550 0.270766861 -0.258284061 0.460606769 -0.028421759
[226] 0.184414735 -0.443225234 -0.515006579 0.375197953 0.178099846
>
> proc.time()
user system elapsed
5.093 18.802 26.264
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x600002978000>
> .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: 0x600002978000>
> .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: 0x600002978000>
> .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: 0x600002978000>
> 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: 0x600002950120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002950120>
> .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: 0x600002950120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002950120>
> .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: 0x600002950120>
> 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: 0x600002974360>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002974360>
> .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: 0x600002974360>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600002974360>
> .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: 0x600002974360>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600002974360>
> .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: 0x600002974360>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600002974360>
> .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: 0x600002974360>
> 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: 0x600002974540>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600002974540>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002974540>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002974540>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile16af92d5bd206" "BufferedMatrixFile16af967399f2d"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile16af92d5bd206" "BufferedMatrixFile16af967399f2d"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000029747e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000029747e0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000029747e0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000029747e0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000029747e0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000029747e0>
> .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: 0x600002968000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002968000>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600002968000>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600002968000>
> 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: 0x6000029501e0>
> .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: 0x6000029501e0>
> rm(P)
>
> proc.time()
user system elapsed
0.597 0.217 0.783
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.588 0.134 0.703