Ben Bolstad
| Snapshot Date: 2025-04-21 13:40 -0400 (Mon, 21 Apr 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 2025-04-22 13:17 -0400 (Tue, 22 Apr 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six" | 4831 |
| palomino7 | Windows Server 2022 Datacenter | x64 | 4.5.0 RC (2025-04-04 r88126 ucrt) -- "How About a Twenty-Six" | 4573 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six" | 4599 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six" | 4553 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4570 |
| 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 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.1 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| 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: 2025-04-21 18:27:52 -0400 (Mon, 21 Apr 2025) |
| EndedAt: 2025-04-21 18:28:09 -0400 (Mon, 21 Apr 2025) |
| EllapsedTime: 17.2 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
##############################################################################
###
### 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 4.5.0 RC (2025-04-04 r88126)
* using platform: aarch64-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 Ventura 13.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.72.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... WARNING
Found the following significant warnings:
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
* used SDK: ‘MacOSX11.3.sdk’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 WARNING, 2 NOTEs
See
‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.72.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
using SDK: ‘MacOSX11.3.sdk’
clang -arch arm64 -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 -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 -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 -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 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/arm64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R
installing to /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.117 0.038 0.153
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/Users/biocbuild/bbs-3.21-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 480809 25.7 1056568 56.5 NA 634342 33.9
Vcells 890978 6.8 8388608 64.0 196608 2109696 16.1
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Mon Apr 21 18:28:02 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Mon Apr 21 18:28:02 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: 0x6000005c8660>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Mon Apr 21 18:28:03 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Mon Apr 21 18:28:03 2025"
>
> ColMode(tmp2)
<pointer: 0x6000005c8660>
>
>
>
> ### 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,] 99.5083293 -1.6343230 1.3842826 0.6942150
[2,] -0.4480056 0.4305315 1.1011430 0.4150054
[3,] -0.5583099 -1.3550827 -0.7232661 1.1806224
[4,] 1.4160752 -0.4051207 -0.2623078 0.6933438
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.5083293 1.6343230 1.3842826 0.6942150
[2,] 0.4480056 0.4305315 1.1011430 0.4150054
[3,] 0.5583099 1.3550827 0.7232661 1.1806224
[4,] 1.4160752 0.4051207 0.2623078 0.6933438
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9753862 1.2784064 1.1765554 0.8331956
[2,] 0.6693322 0.6561490 1.0493536 0.6442091
[3,] 0.7472014 1.1640802 0.8504505 1.0865645
[4,] 1.1899896 0.6364909 0.5121600 0.8326727
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.26219 39.41839 38.14984 34.02617
[2,] 32.14133 31.99202 36.59468 31.85710
[3,] 33.03032 37.99588 34.22777 37.04627
[4,] 38.31597 31.77003 30.38391 34.02007
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000005cc000>
> exp(tmp5)
<pointer: 0x6000005cc000>
> log(tmp5,2)
<pointer: 0x6000005cc000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.7724
> Min(tmp5)
[1] 54.2224
> mean(tmp5)
[1] 72.69919
> Sum(tmp5)
[1] 14539.84
> Var(tmp5)
[1] 853.5796
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 93.16518 72.07074 70.75158 74.47589 69.83677 69.88752 68.74595 70.92844
[9] 69.75013 67.37966
> rowSums(tmp5)
[1] 1863.304 1441.415 1415.032 1489.518 1396.735 1397.750 1374.919 1418.569
[9] 1395.003 1347.593
> rowVars(tmp5)
[1] 7808.84198 63.36778 57.64407 100.48204 80.67691 55.23808
[7] 59.00064 48.96604 69.66607 71.96711
> rowSd(tmp5)
[1] 88.367652 7.960388 7.592369 10.024073 8.982033 7.432232 7.681188
[8] 6.997574 8.346620 8.483343
> rowMax(tmp5)
[1] 466.77237 84.26369 85.86990 96.14931 87.29147 79.65407 84.07298
[8] 84.17482 83.49458 85.19445
> rowMin(tmp5)
[1] 54.83600 56.18087 58.51304 56.53670 55.87586 54.22240 56.93186 60.55325
[9] 57.61244 56.31653
>
> colMeans(tmp5)
[1] 110.43198 71.34249 72.57170 73.16182 72.03460 71.22005 70.34824
[8] 71.86051 71.83235 68.94128 71.31682 68.26817 66.22678 69.25825
[15] 68.72911 75.21992 65.87975 73.32878 70.47575 71.53536
> colSums(tmp5)
[1] 1104.3198 713.4249 725.7170 731.6182 720.3460 712.2005 703.4824
[8] 718.6051 718.3235 689.4128 713.1682 682.6817 662.2678 692.5825
[15] 687.2911 752.1992 658.7975 733.2878 704.7575 715.3536
> colVars(tmp5)
[1] 15711.53149 80.27362 36.83637 18.52971 63.34714 71.90716
[7] 59.71275 61.68390 74.06836 69.24226 109.84400 41.00646
[13] 123.92485 104.06624 26.44583 42.63842 67.36776 118.39759
[19] 63.08237 151.73102
> colSd(tmp5)
[1] 125.345648 8.959555 6.069297 4.304615 7.959092 8.479809
[7] 7.727403 7.853910 8.606298 8.321193 10.480649 6.403628
[13] 11.132154 10.201286 5.142551 6.529810 8.207786 10.881065
[19] 7.942441 12.317915
> colMax(tmp5)
[1] 466.77237 82.04421 79.79850 78.32440 84.26369 81.04332 85.19445
[8] 84.01679 85.86990 83.22438 85.92673 78.54929 88.96517 83.49458
[15] 75.79491 81.70705 78.75174 87.29147 82.39201 96.14931
> colMin(tmp5)
[1] 62.20304 54.22240 63.24012 66.30637 59.00555 57.57939 58.59409 58.62201
[9] 57.65809 56.53670 56.17874 59.45960 54.83600 54.97219 62.78085 61.25241
[17] 54.84097 56.18087 57.61244 56.31653
>
>
> ### 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] 93.16518 72.07074 70.75158 NA 69.83677 69.88752 68.74595 70.92844
[9] 69.75013 67.37966
> rowSums(tmp5)
[1] 1863.304 1441.415 1415.032 NA 1396.735 1397.750 1374.919 1418.569
[9] 1395.003 1347.593
> rowVars(tmp5)
[1] 7808.84198 63.36778 57.64407 104.43790 80.67691 55.23808
[7] 59.00064 48.96604 69.66607 71.96711
> rowSd(tmp5)
[1] 88.367652 7.960388 7.592369 10.219486 8.982033 7.432232 7.681188
[8] 6.997574 8.346620 8.483343
> rowMax(tmp5)
[1] 466.77237 84.26369 85.86990 NA 87.29147 79.65407 84.07298
[8] 84.17482 83.49458 85.19445
> rowMin(tmp5)
[1] 54.83600 56.18087 58.51304 NA 55.87586 54.22240 56.93186 60.55325
[9] 57.61244 56.31653
>
> colMeans(tmp5)
[1] NA 71.34249 72.57170 73.16182 72.03460 71.22005 70.34824 71.86051
[9] 71.83235 68.94128 71.31682 68.26817 66.22678 69.25825 68.72911 75.21992
[17] 65.87975 73.32878 70.47575 71.53536
> colSums(tmp5)
[1] NA 713.4249 725.7170 731.6182 720.3460 712.2005 703.4824 718.6051
[9] 718.3235 689.4128 713.1682 682.6817 662.2678 692.5825 687.2911 752.1992
[17] 658.7975 733.2878 704.7575 715.3536
> colVars(tmp5)
[1] NA 80.27362 36.83637 18.52971 63.34714 71.90716 59.71275
[8] 61.68390 74.06836 69.24226 109.84400 41.00646 123.92485 104.06624
[15] 26.44583 42.63842 67.36776 118.39759 63.08237 151.73102
> colSd(tmp5)
[1] NA 8.959555 6.069297 4.304615 7.959092 8.479809 7.727403
[8] 7.853910 8.606298 8.321193 10.480649 6.403628 11.132154 10.201286
[15] 5.142551 6.529810 8.207786 10.881065 7.942441 12.317915
> colMax(tmp5)
[1] NA 82.04421 79.79850 78.32440 84.26369 81.04332 85.19445 84.01679
[9] 85.86990 83.22438 85.92673 78.54929 88.96517 83.49458 75.79491 81.70705
[17] 78.75174 87.29147 82.39201 96.14931
> colMin(tmp5)
[1] NA 54.22240 63.24012 66.30637 59.00555 57.57939 58.59409 58.62201
[9] 57.65809 56.53670 56.17874 59.45960 54.83600 54.97219 62.78085 61.25241
[17] 54.84097 56.18087 57.61244 56.31653
>
> Max(tmp5,na.rm=TRUE)
[1] 466.7724
> Min(tmp5,na.rm=TRUE)
[1] 54.2224
> mean(tmp5,na.rm=TRUE)
[1] 72.66376
> Sum(tmp5,na.rm=TRUE)
[1] 14460.09
> Var(tmp5,na.rm=TRUE)
[1] 857.6382
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.16518 72.07074 70.75158 74.19833 69.83677 69.88752 68.74595 70.92844
[9] 69.75013 67.37966
> rowSums(tmp5,na.rm=TRUE)
[1] 1863.304 1441.415 1415.032 1409.768 1396.735 1397.750 1374.919 1418.569
[9] 1395.003 1347.593
> rowVars(tmp5,na.rm=TRUE)
[1] 7808.84198 63.36778 57.64407 104.43790 80.67691 55.23808
[7] 59.00064 48.96604 69.66607 71.96711
> rowSd(tmp5,na.rm=TRUE)
[1] 88.367652 7.960388 7.592369 10.219486 8.982033 7.432232 7.681188
[8] 6.997574 8.346620 8.483343
> rowMax(tmp5,na.rm=TRUE)
[1] 466.77237 84.26369 85.86990 96.14931 87.29147 79.65407 84.07298
[8] 84.17482 83.49458 85.19445
> rowMin(tmp5,na.rm=TRUE)
[1] 54.83600 56.18087 58.51304 56.53670 55.87586 54.22240 56.93186 60.55325
[9] 57.61244 56.31653
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.84113 71.34249 72.57170 73.16182 72.03460 71.22005 70.34824
[8] 71.86051 71.83235 68.94128 71.31682 68.26817 66.22678 69.25825
[15] 68.72911 75.21992 65.87975 73.32878 70.47575 71.53536
> colSums(tmp5,na.rm=TRUE)
[1] 1024.5701 713.4249 725.7170 731.6182 720.3460 712.2005 703.4824
[8] 718.6051 718.3235 689.4128 713.1682 682.6817 662.2678 692.5825
[15] 687.2911 752.1992 658.7975 733.2878 704.7575 715.3536
> colVars(tmp5,na.rm=TRUE)
[1] 17544.72235 80.27362 36.83637 18.52971 63.34714 71.90716
[7] 59.71275 61.68390 74.06836 69.24226 109.84400 41.00646
[13] 123.92485 104.06624 26.44583 42.63842 67.36776 118.39759
[19] 63.08237 151.73102
> colSd(tmp5,na.rm=TRUE)
[1] 132.456492 8.959555 6.069297 4.304615 7.959092 8.479809
[7] 7.727403 7.853910 8.606298 8.321193 10.480649 6.403628
[13] 11.132154 10.201286 5.142551 6.529810 8.207786 10.881065
[19] 7.942441 12.317915
> colMax(tmp5,na.rm=TRUE)
[1] 466.77237 82.04421 79.79850 78.32440 84.26369 81.04332 85.19445
[8] 84.01679 85.86990 83.22438 85.92673 78.54929 88.96517 83.49458
[15] 75.79491 81.70705 78.75174 87.29147 82.39201 96.14931
> colMin(tmp5,na.rm=TRUE)
[1] 62.20304 54.22240 63.24012 66.30637 59.00555 57.57939 58.59409 58.62201
[9] 57.65809 56.53670 56.17874 59.45960 54.83600 54.97219 62.78085 61.25241
[17] 54.84097 56.18087 57.61244 56.31653
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.16518 72.07074 70.75158 NaN 69.83677 69.88752 68.74595 70.92844
[9] 69.75013 67.37966
> rowSums(tmp5,na.rm=TRUE)
[1] 1863.304 1441.415 1415.032 0.000 1396.735 1397.750 1374.919 1418.569
[9] 1395.003 1347.593
> rowVars(tmp5,na.rm=TRUE)
[1] 7808.84198 63.36778 57.64407 NA 80.67691 55.23808
[7] 59.00064 48.96604 69.66607 71.96711
> rowSd(tmp5,na.rm=TRUE)
[1] 88.367652 7.960388 7.592369 NA 8.982033 7.432232 7.681188
[8] 6.997574 8.346620 8.483343
> rowMax(tmp5,na.rm=TRUE)
[1] 466.77237 84.26369 85.86990 NA 87.29147 79.65407 84.07298
[8] 84.17482 83.49458 85.19445
> rowMin(tmp5,na.rm=TRUE)
[1] 54.83600 56.18087 58.51304 NA 55.87586 54.22240 56.93186 60.55325
[9] 57.61244 56.31653
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] NaN 71.92219 73.60854 73.42332 72.30040 71.47231 70.53423 73.33145
[9] 71.02849 70.31956 69.69349 67.86937 63.70029 67.95805 68.21694 74.58137
[17] 65.44408 72.70612 69.28364 68.80047
> colSums(tmp5,na.rm=TRUE)
[1] 0.0000 647.2997 662.4769 660.8099 650.7036 643.2508 634.8081 659.9831
[9] 639.2565 632.8761 627.2414 610.8244 573.3026 611.6225 613.9525 671.2323
[17] 588.9967 654.3551 623.5528 619.2042
> colVars(tmp5,na.rm=TRUE)
[1] NA 86.52718 29.34670 20.07662 70.47077 80.17971 66.78769
[8] 45.05300 76.05734 56.52622 93.92872 44.34305 67.60511 98.05635
[15] 26.80050 43.38107 73.65336 128.83565 54.98011 86.55201
> colSd(tmp5,na.rm=TRUE)
[1] NA 9.301999 5.417259 4.480694 8.394687 8.954312 8.172374
[8] 6.712153 8.721086 7.518392 9.691683 6.659057 8.222233 9.902341
[15] 5.176920 6.586431 8.582154 11.350579 7.414857 9.303333
> colMax(tmp5,na.rm=TRUE)
[1] -Inf 82.04421 79.79850 78.32440 84.26369 81.04332 85.19445 84.01679
[9] 85.86990 83.22438 84.07298 78.54929 78.14383 83.49458 75.79491 81.70705
[17] 78.75174 87.29147 82.39201 84.17482
> colMin(tmp5,na.rm=TRUE)
[1] Inf 54.22240 64.49702 66.30637 59.00555 57.57939 58.59409 63.45831
[9] 57.65809 58.51304 56.17874 59.45960 54.83600 54.97219 62.78085 61.25241
[17] 54.84097 56.18087 57.61244 56.31653
>
>
>
>
> 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] 146.8975 212.5134 236.4326 275.1779 114.1189 179.7934 298.2909 262.6244
[9] 141.9550 125.5644
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 146.8975 212.5134 236.4326 275.1779 114.1189 179.7934 298.2909 262.6244
[9] 141.9550 125.5644
>
>
>
> 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] 1.705303e-13 -4.263256e-14 0.000000e+00 -5.684342e-14 5.684342e-14
[6] -2.842171e-14 1.705303e-13 0.000000e+00 -1.136868e-13 5.684342e-14
[11] -1.989520e-13 0.000000e+00 0.000000e+00 -1.705303e-13 -1.136868e-13
[16] -2.273737e-13 0.000000e+00 8.526513e-14 -1.278977e-13 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
5 4
3 14
1 5
10 17
3 16
10 4
10 1
8 13
6 18
1 10
9 11
3 10
1 6
2 4
9 2
5 16
1 18
7 17
2 7
3 3
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] 2.042412
> Min(tmp)
[1] -2.345345
> mean(tmp)
[1] -0.01073302
> Sum(tmp)
[1] -1.073302
> Var(tmp)
[1] 1.024238
>
> rowMeans(tmp)
[1] -0.01073302
> rowSums(tmp)
[1] -1.073302
> rowVars(tmp)
[1] 1.024238
> rowSd(tmp)
[1] 1.012046
> rowMax(tmp)
[1] 2.042412
> rowMin(tmp)
[1] -2.345345
>
> colMeans(tmp)
[1] -1.163376603 1.652879022 1.325247831 0.966296067 -1.790915353
[6] 1.029538769 1.932330660 0.169356720 -0.462676644 -0.597716982
[11] -0.649265319 0.632213083 -1.256579973 -0.568960634 -0.877538068
[16] -0.267548050 0.375990596 0.263350138 -0.880952100 1.099395210
[21] 0.005304298 -1.363499263 -2.345345392 2.042412420 1.226268004
[26] 0.056355664 -0.027401896 -0.742454600 1.354705836 -1.501300913
[31] 0.628515726 1.722826660 -0.687245815 0.889700312 0.335648967
[36] 0.542895275 -1.448786543 -0.624623609 -1.909220122 -0.213324709
[41] -1.296433502 0.247331291 -1.178322523 0.820071396 0.261278057
[46] 0.459632851 -0.246542245 0.631275270 1.739671112 -0.109738174
[51] -1.492077719 -0.215468322 -0.609727804 0.617026573 -0.109730009
[56] 0.954514764 -0.634741416 1.782976187 -1.252626740 -0.869744153
[61] 0.097550670 -0.512614614 -0.791363326 1.816898568 0.078672626
[66] 0.256277868 -0.172721492 -0.821757667 -0.823771729 1.320970967
[71] 0.958373872 1.102524461 0.534693723 1.534982644 0.575756454
[76] 0.641551004 0.626695414 0.722747560 -0.941959346 -0.703675508
[81] -1.003716586 1.122707897 1.291542490 0.635411816 0.259022616
[86] -2.130628728 -1.870675639 0.574269210 -1.113834849 -1.588509460
[91] -0.801202050 -0.191582981 -0.238764078 -0.733408288 -0.297294082
[96] 0.632764221 0.490751777 -0.159993947 -0.177498909 0.356381707
> colSums(tmp)
[1] -1.163376603 1.652879022 1.325247831 0.966296067 -1.790915353
[6] 1.029538769 1.932330660 0.169356720 -0.462676644 -0.597716982
[11] -0.649265319 0.632213083 -1.256579973 -0.568960634 -0.877538068
[16] -0.267548050 0.375990596 0.263350138 -0.880952100 1.099395210
[21] 0.005304298 -1.363499263 -2.345345392 2.042412420 1.226268004
[26] 0.056355664 -0.027401896 -0.742454600 1.354705836 -1.501300913
[31] 0.628515726 1.722826660 -0.687245815 0.889700312 0.335648967
[36] 0.542895275 -1.448786543 -0.624623609 -1.909220122 -0.213324709
[41] -1.296433502 0.247331291 -1.178322523 0.820071396 0.261278057
[46] 0.459632851 -0.246542245 0.631275270 1.739671112 -0.109738174
[51] -1.492077719 -0.215468322 -0.609727804 0.617026573 -0.109730009
[56] 0.954514764 -0.634741416 1.782976187 -1.252626740 -0.869744153
[61] 0.097550670 -0.512614614 -0.791363326 1.816898568 0.078672626
[66] 0.256277868 -0.172721492 -0.821757667 -0.823771729 1.320970967
[71] 0.958373872 1.102524461 0.534693723 1.534982644 0.575756454
[76] 0.641551004 0.626695414 0.722747560 -0.941959346 -0.703675508
[81] -1.003716586 1.122707897 1.291542490 0.635411816 0.259022616
[86] -2.130628728 -1.870675639 0.574269210 -1.113834849 -1.588509460
[91] -0.801202050 -0.191582981 -0.238764078 -0.733408288 -0.297294082
[96] 0.632764221 0.490751777 -0.159993947 -0.177498909 0.356381707
> 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] -1.163376603 1.652879022 1.325247831 0.966296067 -1.790915353
[6] 1.029538769 1.932330660 0.169356720 -0.462676644 -0.597716982
[11] -0.649265319 0.632213083 -1.256579973 -0.568960634 -0.877538068
[16] -0.267548050 0.375990596 0.263350138 -0.880952100 1.099395210
[21] 0.005304298 -1.363499263 -2.345345392 2.042412420 1.226268004
[26] 0.056355664 -0.027401896 -0.742454600 1.354705836 -1.501300913
[31] 0.628515726 1.722826660 -0.687245815 0.889700312 0.335648967
[36] 0.542895275 -1.448786543 -0.624623609 -1.909220122 -0.213324709
[41] -1.296433502 0.247331291 -1.178322523 0.820071396 0.261278057
[46] 0.459632851 -0.246542245 0.631275270 1.739671112 -0.109738174
[51] -1.492077719 -0.215468322 -0.609727804 0.617026573 -0.109730009
[56] 0.954514764 -0.634741416 1.782976187 -1.252626740 -0.869744153
[61] 0.097550670 -0.512614614 -0.791363326 1.816898568 0.078672626
[66] 0.256277868 -0.172721492 -0.821757667 -0.823771729 1.320970967
[71] 0.958373872 1.102524461 0.534693723 1.534982644 0.575756454
[76] 0.641551004 0.626695414 0.722747560 -0.941959346 -0.703675508
[81] -1.003716586 1.122707897 1.291542490 0.635411816 0.259022616
[86] -2.130628728 -1.870675639 0.574269210 -1.113834849 -1.588509460
[91] -0.801202050 -0.191582981 -0.238764078 -0.733408288 -0.297294082
[96] 0.632764221 0.490751777 -0.159993947 -0.177498909 0.356381707
> colMin(tmp)
[1] -1.163376603 1.652879022 1.325247831 0.966296067 -1.790915353
[6] 1.029538769 1.932330660 0.169356720 -0.462676644 -0.597716982
[11] -0.649265319 0.632213083 -1.256579973 -0.568960634 -0.877538068
[16] -0.267548050 0.375990596 0.263350138 -0.880952100 1.099395210
[21] 0.005304298 -1.363499263 -2.345345392 2.042412420 1.226268004
[26] 0.056355664 -0.027401896 -0.742454600 1.354705836 -1.501300913
[31] 0.628515726 1.722826660 -0.687245815 0.889700312 0.335648967
[36] 0.542895275 -1.448786543 -0.624623609 -1.909220122 -0.213324709
[41] -1.296433502 0.247331291 -1.178322523 0.820071396 0.261278057
[46] 0.459632851 -0.246542245 0.631275270 1.739671112 -0.109738174
[51] -1.492077719 -0.215468322 -0.609727804 0.617026573 -0.109730009
[56] 0.954514764 -0.634741416 1.782976187 -1.252626740 -0.869744153
[61] 0.097550670 -0.512614614 -0.791363326 1.816898568 0.078672626
[66] 0.256277868 -0.172721492 -0.821757667 -0.823771729 1.320970967
[71] 0.958373872 1.102524461 0.534693723 1.534982644 0.575756454
[76] 0.641551004 0.626695414 0.722747560 -0.941959346 -0.703675508
[81] -1.003716586 1.122707897 1.291542490 0.635411816 0.259022616
[86] -2.130628728 -1.870675639 0.574269210 -1.113834849 -1.588509460
[91] -0.801202050 -0.191582981 -0.238764078 -0.733408288 -0.297294082
[96] 0.632764221 0.490751777 -0.159993947 -0.177498909 0.356381707
> colMedians(tmp)
[1] -1.163376603 1.652879022 1.325247831 0.966296067 -1.790915353
[6] 1.029538769 1.932330660 0.169356720 -0.462676644 -0.597716982
[11] -0.649265319 0.632213083 -1.256579973 -0.568960634 -0.877538068
[16] -0.267548050 0.375990596 0.263350138 -0.880952100 1.099395210
[21] 0.005304298 -1.363499263 -2.345345392 2.042412420 1.226268004
[26] 0.056355664 -0.027401896 -0.742454600 1.354705836 -1.501300913
[31] 0.628515726 1.722826660 -0.687245815 0.889700312 0.335648967
[36] 0.542895275 -1.448786543 -0.624623609 -1.909220122 -0.213324709
[41] -1.296433502 0.247331291 -1.178322523 0.820071396 0.261278057
[46] 0.459632851 -0.246542245 0.631275270 1.739671112 -0.109738174
[51] -1.492077719 -0.215468322 -0.609727804 0.617026573 -0.109730009
[56] 0.954514764 -0.634741416 1.782976187 -1.252626740 -0.869744153
[61] 0.097550670 -0.512614614 -0.791363326 1.816898568 0.078672626
[66] 0.256277868 -0.172721492 -0.821757667 -0.823771729 1.320970967
[71] 0.958373872 1.102524461 0.534693723 1.534982644 0.575756454
[76] 0.641551004 0.626695414 0.722747560 -0.941959346 -0.703675508
[81] -1.003716586 1.122707897 1.291542490 0.635411816 0.259022616
[86] -2.130628728 -1.870675639 0.574269210 -1.113834849 -1.588509460
[91] -0.801202050 -0.191582981 -0.238764078 -0.733408288 -0.297294082
[96] 0.632764221 0.490751777 -0.159993947 -0.177498909 0.356381707
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.163377 1.652879 1.325248 0.9662961 -1.790915 1.029539 1.932331
[2,] -1.163377 1.652879 1.325248 0.9662961 -1.790915 1.029539 1.932331
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.1693567 -0.4626766 -0.597717 -0.6492653 0.6322131 -1.25658 -0.5689606
[2,] 0.1693567 -0.4626766 -0.597717 -0.6492653 0.6322131 -1.25658 -0.5689606
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.8775381 -0.2675481 0.3759906 0.2633501 -0.8809521 1.099395 0.005304298
[2,] -0.8775381 -0.2675481 0.3759906 0.2633501 -0.8809521 1.099395 0.005304298
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.363499 -2.345345 2.042412 1.226268 0.05635566 -0.0274019 -0.7424546
[2,] -1.363499 -2.345345 2.042412 1.226268 0.05635566 -0.0274019 -0.7424546
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.354706 -1.501301 0.6285157 1.722827 -0.6872458 0.8897003 0.335649
[2,] 1.354706 -1.501301 0.6285157 1.722827 -0.6872458 0.8897003 0.335649
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.5428953 -1.448787 -0.6246236 -1.90922 -0.2133247 -1.296434 0.2473313
[2,] 0.5428953 -1.448787 -0.6246236 -1.90922 -0.2133247 -1.296434 0.2473313
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.178323 0.8200714 0.2612781 0.4596329 -0.2465422 0.6312753 1.739671
[2,] -1.178323 0.8200714 0.2612781 0.4596329 -0.2465422 0.6312753 1.739671
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.1097382 -1.492078 -0.2154683 -0.6097278 0.6170266 -0.10973 0.9545148
[2,] -0.1097382 -1.492078 -0.2154683 -0.6097278 0.6170266 -0.10973 0.9545148
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.6347414 1.782976 -1.252627 -0.8697442 0.09755067 -0.5126146 -0.7913633
[2,] -0.6347414 1.782976 -1.252627 -0.8697442 0.09755067 -0.5126146 -0.7913633
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 1.816899 0.07867263 0.2562779 -0.1727215 -0.8217577 -0.8237717 1.320971
[2,] 1.816899 0.07867263 0.2562779 -0.1727215 -0.8217577 -0.8237717 1.320971
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.9583739 1.102524 0.5346937 1.534983 0.5757565 0.641551 0.6266954
[2,] 0.9583739 1.102524 0.5346937 1.534983 0.5757565 0.641551 0.6266954
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.7227476 -0.9419593 -0.7036755 -1.003717 1.122708 1.291542 0.6354118
[2,] 0.7227476 -0.9419593 -0.7036755 -1.003717 1.122708 1.291542 0.6354118
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.2590226 -2.130629 -1.870676 0.5742692 -1.113835 -1.588509 -0.801202
[2,] 0.2590226 -2.130629 -1.870676 0.5742692 -1.113835 -1.588509 -0.801202
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.191583 -0.2387641 -0.7334083 -0.2972941 0.6327642 0.4907518 -0.1599939
[2,] -0.191583 -0.2387641 -0.7334083 -0.2972941 0.6327642 0.4907518 -0.1599939
[,99] [,100]
[1,] -0.1774989 0.3563817
[2,] -0.1774989 0.3563817
>
>
> Max(tmp2)
[1] 2.266167
> Min(tmp2)
[1] -3.160073
> mean(tmp2)
[1] -0.06130444
> Sum(tmp2)
[1] -6.130444
> Var(tmp2)
[1] 0.9574394
>
> rowMeans(tmp2)
[1] -0.053622098 -0.167510755 -0.666279986 -0.449514495 -0.397950409
[6] -0.636237547 0.866802546 0.020294529 0.926571589 0.533534428
[11] 0.491704181 1.167437490 1.115928281 -0.737980449 -0.551757710
[16] 1.986020322 -0.089698141 1.255518436 -1.120931935 0.649160471
[21] 0.515357785 1.065520412 0.426608685 -0.287866493 -0.972366528
[26] 1.455875208 0.758654597 -1.356765904 -1.319029579 0.425789312
[31] 0.138769762 0.205002682 -0.638002160 -0.635741550 -0.674933516
[36] 0.141305354 -0.796872074 -1.411928656 0.257318108 0.370826042
[41] -0.230307172 -3.160072829 -1.214121130 -1.674444962 -0.120056169
[46] 1.779161649 1.179963616 -0.038944152 1.180277941 -2.637074391
[51] 0.777641952 0.602658661 -0.698305362 -0.319982982 0.508750158
[56] 1.128214356 0.800685237 1.529327595 -0.522422076 -2.442301143
[61] -0.836690587 0.047860320 -0.329918229 0.603789693 0.126703005
[66] -0.348570189 -1.299548943 0.432464074 0.268095771 -0.285826038
[71] 1.355488780 0.191891871 -0.106759616 -0.583072860 -1.537021077
[76] -0.175054081 -0.283168996 -0.960982149 0.232357989 -0.124335449
[81] -0.228475777 -0.171602328 -0.088249339 1.431033416 -1.180728052
[86] -1.087973509 -0.563197417 0.370458975 2.266167427 0.940121771
[91] -0.548051118 0.006863233 -0.103545236 -0.094707843 1.789045334
[96] -0.726485543 -1.414611719 0.337287248 -0.337393530 -1.351761949
> rowSums(tmp2)
[1] -0.053622098 -0.167510755 -0.666279986 -0.449514495 -0.397950409
[6] -0.636237547 0.866802546 0.020294529 0.926571589 0.533534428
[11] 0.491704181 1.167437490 1.115928281 -0.737980449 -0.551757710
[16] 1.986020322 -0.089698141 1.255518436 -1.120931935 0.649160471
[21] 0.515357785 1.065520412 0.426608685 -0.287866493 -0.972366528
[26] 1.455875208 0.758654597 -1.356765904 -1.319029579 0.425789312
[31] 0.138769762 0.205002682 -0.638002160 -0.635741550 -0.674933516
[36] 0.141305354 -0.796872074 -1.411928656 0.257318108 0.370826042
[41] -0.230307172 -3.160072829 -1.214121130 -1.674444962 -0.120056169
[46] 1.779161649 1.179963616 -0.038944152 1.180277941 -2.637074391
[51] 0.777641952 0.602658661 -0.698305362 -0.319982982 0.508750158
[56] 1.128214356 0.800685237 1.529327595 -0.522422076 -2.442301143
[61] -0.836690587 0.047860320 -0.329918229 0.603789693 0.126703005
[66] -0.348570189 -1.299548943 0.432464074 0.268095771 -0.285826038
[71] 1.355488780 0.191891871 -0.106759616 -0.583072860 -1.537021077
[76] -0.175054081 -0.283168996 -0.960982149 0.232357989 -0.124335449
[81] -0.228475777 -0.171602328 -0.088249339 1.431033416 -1.180728052
[86] -1.087973509 -0.563197417 0.370458975 2.266167427 0.940121771
[91] -0.548051118 0.006863233 -0.103545236 -0.094707843 1.789045334
[96] -0.726485543 -1.414611719 0.337287248 -0.337393530 -1.351761949
> 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] -0.053622098 -0.167510755 -0.666279986 -0.449514495 -0.397950409
[6] -0.636237547 0.866802546 0.020294529 0.926571589 0.533534428
[11] 0.491704181 1.167437490 1.115928281 -0.737980449 -0.551757710
[16] 1.986020322 -0.089698141 1.255518436 -1.120931935 0.649160471
[21] 0.515357785 1.065520412 0.426608685 -0.287866493 -0.972366528
[26] 1.455875208 0.758654597 -1.356765904 -1.319029579 0.425789312
[31] 0.138769762 0.205002682 -0.638002160 -0.635741550 -0.674933516
[36] 0.141305354 -0.796872074 -1.411928656 0.257318108 0.370826042
[41] -0.230307172 -3.160072829 -1.214121130 -1.674444962 -0.120056169
[46] 1.779161649 1.179963616 -0.038944152 1.180277941 -2.637074391
[51] 0.777641952 0.602658661 -0.698305362 -0.319982982 0.508750158
[56] 1.128214356 0.800685237 1.529327595 -0.522422076 -2.442301143
[61] -0.836690587 0.047860320 -0.329918229 0.603789693 0.126703005
[66] -0.348570189 -1.299548943 0.432464074 0.268095771 -0.285826038
[71] 1.355488780 0.191891871 -0.106759616 -0.583072860 -1.537021077
[76] -0.175054081 -0.283168996 -0.960982149 0.232357989 -0.124335449
[81] -0.228475777 -0.171602328 -0.088249339 1.431033416 -1.180728052
[86] -1.087973509 -0.563197417 0.370458975 2.266167427 0.940121771
[91] -0.548051118 0.006863233 -0.103545236 -0.094707843 1.789045334
[96] -0.726485543 -1.414611719 0.337287248 -0.337393530 -1.351761949
> rowMin(tmp2)
[1] -0.053622098 -0.167510755 -0.666279986 -0.449514495 -0.397950409
[6] -0.636237547 0.866802546 0.020294529 0.926571589 0.533534428
[11] 0.491704181 1.167437490 1.115928281 -0.737980449 -0.551757710
[16] 1.986020322 -0.089698141 1.255518436 -1.120931935 0.649160471
[21] 0.515357785 1.065520412 0.426608685 -0.287866493 -0.972366528
[26] 1.455875208 0.758654597 -1.356765904 -1.319029579 0.425789312
[31] 0.138769762 0.205002682 -0.638002160 -0.635741550 -0.674933516
[36] 0.141305354 -0.796872074 -1.411928656 0.257318108 0.370826042
[41] -0.230307172 -3.160072829 -1.214121130 -1.674444962 -0.120056169
[46] 1.779161649 1.179963616 -0.038944152 1.180277941 -2.637074391
[51] 0.777641952 0.602658661 -0.698305362 -0.319982982 0.508750158
[56] 1.128214356 0.800685237 1.529327595 -0.522422076 -2.442301143
[61] -0.836690587 0.047860320 -0.329918229 0.603789693 0.126703005
[66] -0.348570189 -1.299548943 0.432464074 0.268095771 -0.285826038
[71] 1.355488780 0.191891871 -0.106759616 -0.583072860 -1.537021077
[76] -0.175054081 -0.283168996 -0.960982149 0.232357989 -0.124335449
[81] -0.228475777 -0.171602328 -0.088249339 1.431033416 -1.180728052
[86] -1.087973509 -0.563197417 0.370458975 2.266167427 0.940121771
[91] -0.548051118 0.006863233 -0.103545236 -0.094707843 1.789045334
[96] -0.726485543 -1.414611719 0.337287248 -0.337393530 -1.351761949
>
> colMeans(tmp2)
[1] -0.06130444
> colSums(tmp2)
[1] -6.130444
> colVars(tmp2)
[1] 0.9574394
> colSd(tmp2)
[1] 0.9784883
> colMax(tmp2)
[1] 2.266167
> colMin(tmp2)
[1] -3.160073
> colMedians(tmp2)
[1] -0.09912654
> colRanges(tmp2)
[,1]
[1,] -3.160073
[2,] 2.266167
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.7756342 -6.1229917 -1.3571686 1.3316764 0.7046070 -2.4786336
[7] -1.0725301 0.6762948 2.7075214 -0.3059694
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.220825702
[2,] -0.524936790
[3,] 0.002595891
[4,] 0.319896580
[5,] 1.060304605
>
> rowApply(tmp,sum)
[1] -3.620366 2.949392 -1.123890 -0.251046 1.138190 -1.067406 1.198549
[8] -6.505870 1.722545 -3.132927
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 5 5 4 6 5 3 1 10 10
[2,] 6 2 1 5 7 1 1 4 6 8
[3,] 5 6 8 2 2 3 8 10 8 4
[4,] 4 3 10 1 8 10 7 9 5 3
[5,] 10 4 6 9 4 7 4 5 1 7
[6,] 7 10 4 3 1 2 9 3 4 5
[7,] 2 7 2 6 9 6 6 8 3 6
[8,] 9 9 7 10 3 4 2 2 2 9
[9,] 8 8 9 8 5 8 5 7 7 2
[10,] 3 1 3 7 10 9 10 6 9 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.54653787 2.74981696 -4.10836998 0.08887193 1.36817091 0.11205954
[7] 2.81324753 -1.15052385 1.73552484 1.16585083 0.67042798 1.96007194
[13] -0.13183750 1.36059793 -2.37995914 5.58828253 -0.40554903 -2.70659155
[19] -3.61403205 -3.48992807
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.2683588
[2,] -1.4243596
[3,] -1.1738971
[4,] 0.8067597
[5,] 2.5133179
>
> rowApply(tmp,sum)
[1] -0.7102461 0.6260321 2.8459024 -3.4035391 0.7214447
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 2 15 20 4 2
[2,] 14 4 12 20 18
[3,] 5 1 2 3 17
[4,] 11 14 3 18 7
[5,] 17 3 15 19 8
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -2.2683588 0.6924329 -1.111167 0.2212012 0.9304984 -1.520831256
[2,] 0.8067597 -1.0466388 -1.501978 0.7909567 -1.4037665 0.556952689
[3,] 2.5133179 0.3621930 -1.468643 -1.4273952 0.9525740 1.571909636
[4,] -1.1738971 1.4859540 -1.255432 0.9406322 1.2918258 0.003889806
[5,] -1.4243596 1.2558759 1.228850 -0.4365230 -0.4029609 -0.499861332
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.9606317 -0.05099362 0.0520435 1.07208797 0.61366512 0.7165275
[2,] 0.5755528 0.89839679 1.0008131 -0.14403022 0.07247199 -1.0453477
[3,] 0.2751237 -1.02805118 -1.6333245 -0.19035111 -0.29699539 1.0084313
[4,] 0.4413028 -0.89684688 0.4623517 0.04098121 0.09964978 0.5573789
[5,] 0.5606365 -0.07302896 1.8536410 0.38716298 0.18163647 0.7230819
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.01328683 0.86020841 -2.2974959 2.0051872 0.31223916 -1.2501719
[2,] 1.28308857 0.46867395 -0.9128105 1.3354536 0.17146361 -0.9151807
[3,] -0.86478090 0.84490972 1.2182201 1.5961386 -0.01845452 -0.6365125
[4,] -1.38097131 -0.72222134 0.5149624 -0.6573351 -0.26197140 0.2156257
[5,] 0.84411298 -0.09097281 -0.9028353 1.3088382 -0.60882588 -0.1203523
[,19] [,20]
[1,] -0.7204741 0.08580961
[2,] -1.4112099 1.04641066
[3,] 0.4743182 -0.40672557
[4,] -0.5328623 -2.57655570
[5,] -1.4238040 -1.63886708
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 650 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 563 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.8018281 0.1955674 0.06117053 2.62044 0.9828861 0.2546188 0.05936395
col8 col9 col10 col11 col12 col13 col14
row1 -1.399804 -0.3642422 -1.915967 -0.4214954 0.1987895 1.257657 0.2453605
col15 col16 col17 col18 col19 col20
row1 0.01141393 -0.2298121 1.278854 1.759073 1.453046 1.669672
> tmp[,"col10"]
col10
row1 -1.9159675
row2 -1.5025703
row3 -0.6300875
row4 1.6668900
row5 0.2814327
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.80182810 0.1955674 0.06117053 2.6204403 0.9828861 0.2546188 0.05936395
row5 0.09602017 0.1031055 -0.51258714 0.3474406 0.2091569 -0.6442742 3.21509846
col8 col9 col10 col11 col12 col13 col14
row1 -1.399804 -0.3642422 -1.9159675 -0.4214954 0.19878953 1.2576568 0.2453605
row5 -1.296924 0.5795363 0.2814327 -0.6086124 0.01062964 0.8409116 -0.8320694
col15 col16 col17 col18 col19 col20
row1 0.01141393 -0.22981206 1.278854 1.759073 1.4530463 1.6696716
row5 -1.48225090 -0.05745326 -1.816980 1.871378 0.8362428 0.4188716
> tmp[,c("col6","col20")]
col6 col20
row1 0.25461884 1.6696716
row2 -0.75008955 0.3929057
row3 -0.26152930 -0.2571028
row4 -0.08036693 -0.3160421
row5 -0.64427415 0.4188716
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.2546188 1.6696716
row5 -0.6442742 0.4188716
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.43148 49.42598 50.05279 49.23376 49.42451 106.0673 49.21554 48.92236
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.95299 49.41896 51.04449 49.67443 50.96345 51.51392 49.82939 50.20726
col17 col18 col19 col20
row1 51.08416 50.50965 50.04441 102.6817
> tmp[,"col10"]
col10
row1 49.41896
row2 28.29840
row3 29.24058
row4 28.10668
row5 50.50141
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.43148 49.42598 50.05279 49.23376 49.42451 106.0673 49.21554 48.92236
row5 51.29031 49.12823 48.51751 50.18578 50.43280 105.9317 49.73290 46.58753
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.95299 49.41896 51.04449 49.67443 50.96345 51.51392 49.82939 50.20726
row5 47.75197 50.50141 49.22539 49.85343 51.11033 50.62667 48.27786 50.16835
col17 col18 col19 col20
row1 51.08416 50.50965 50.04441 102.6817
row5 49.17311 48.66731 48.75297 102.8647
> tmp[,c("col6","col20")]
col6 col20
row1 106.06734 102.68170
row2 74.80547 74.08764
row3 75.06937 75.81755
row4 75.11793 75.21155
row5 105.93169 102.86465
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.0673 102.6817
row5 105.9317 102.8647
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.0673 102.6817
row5 105.9317 102.8647
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.5625972
[2,] 0.2164148
[3,] 0.4037054
[4,] -0.6446547
[5,] 0.6893585
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.5470845 0.4725790
[2,] -1.1149943 0.4676923
[3,] 1.3678497 -0.9989161
[4,] 0.3976685 1.7617032
[5,] -1.0652337 1.0320506
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.08079349 -1.0253469
[2,] -1.48228102 1.0324284
[3,] -0.80287348 -0.6881787
[4,] 0.15775305 -0.5978752
[5,] 1.35128988 -1.7266764
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.08079349
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.08079349
[2,] -1.48228102
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 0.2793857 -0.3319159 -1.0688837 -0.6336419 -1.0257035 0.8875961
row1 -0.8349019 -0.4726103 -0.9076398 0.3863372 -0.3449535 -0.1596183
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 0.08713018 -0.1200480 1.701535 -1.5662310 -0.7080082 0.8200414 -0.3957788
row1 -0.58987172 -0.3091615 0.970409 0.4970068 0.8228862 0.0987731 0.9214925
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.3764016 -0.8871589 0.5185493 -0.5451779 0.209241 -0.003309072 -1.785154
row1 0.7448344 2.1996346 0.7394022 0.2313322 0.885325 -0.058486330 -1.519169
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.5703136 0.1254694 0.6564561 -1.524031 2.224859 0.4035497 0.209372
[,8] [,9] [,10]
row2 -1.223874 1.575989 -0.1922435
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.4264544 0.3214965 0.650929 1.470017 1.489615 0.7228472 1.040199
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.1545214 -1.812929 1.230899 -1.083142 0.428636 -0.02037981 -0.5355843
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.6994515 -1.033231 -0.6615528 -0.3137409 0.4926946 -0.1586776
>
>
> 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: 0x6000005fc120>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM61f6808e7e5"
[2] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM61f6b06f82"
[3] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM61f63f68c028"
[4] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM61f6761fa29d"
[5] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM61f616ed2e01"
[6] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM61f62d674f69"
[7] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM61f6598e8dc8"
[8] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM61f61dfe7367"
[9] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM61f62c4a7e93"
[10] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM61f64ebbfb9c"
[11] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM61f61783e726"
[12] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM61f654bc7bd9"
[13] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM61f622670f05"
[14] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM61f61c0b22e8"
[15] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM61f61f20bbba"
>
>
> ### 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: 0x6000005f8240>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000005f8240>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6000005f8240>
> rowMedians(tmp)
[1] 0.2512266465 0.3944888773 -0.2293012348 0.3346475219 -0.2917450794
[6] -0.1952179654 0.4240309422 0.3415708387 -0.2282915340 -0.0606945076
[11] 0.0019411893 -0.0455427030 0.4731621115 0.0928902828 0.4140940632
[16] -0.0746791560 0.2762959577 0.2142942679 -0.5780558957 0.3192923645
[21] 0.0909162035 0.4971115589 0.1444693978 0.1964308707 0.1820340210
[26] 0.1125748674 0.1363169696 -0.0259446979 -0.1072493534 -0.6707876434
[31] 0.0086765911 -0.1240914111 0.0782709073 -0.0644267780 -0.0060383365
[36] -0.1606342071 0.1226218240 -0.5093508181 0.5287155949 -0.1878262753
[41] -0.2166898817 -0.2781940504 -0.1045911362 -0.8766145889 -0.1879217920
[46] -0.1214893936 0.3902974899 0.3775757180 -0.5156403309 0.0571561619
[51] 0.4954316586 0.5428297016 0.0135577245 -0.2097961984 0.2196822498
[56] -0.0731946926 -0.3001465476 0.0394991338 0.3807347771 0.1203088797
[61] -0.0033586732 0.1632051028 0.1425105966 0.2821411972 0.1436755799
[66] -0.1924162035 -0.0009898620 -0.0756155336 -0.3740681031 -0.1012554886
[71] -0.2803765239 -0.1116572312 -0.2575386944 0.0034603775 0.2270498986
[76] -0.4923186166 0.3004597250 0.0188061588 -0.1548351450 -0.3203561078
[81] 0.2181385422 -0.6005279816 -0.0621201946 -0.4207451110 0.5497815215
[86] -0.2155044163 -0.1876521239 0.2926487567 0.1889523568 -0.1847306571
[91] -0.1986961356 0.1426047243 -0.0803549822 0.1236095438 -0.1719964314
[96] -0.2852835319 -0.3060486100 0.0684421281 -0.0928746491 -0.1917689518
[101] -0.2281941878 -0.3346819095 0.3024065260 0.2690837824 0.6437721653
[106] 0.1332180878 -0.7780505215 -0.2398931319 0.1644046348 -0.2789792064
[111] 0.3360602402 -0.1342833081 0.0980749067 0.0775631603 0.0305357078
[116] -0.2778549023 0.0687899687 0.1586963154 -0.1663632278 0.0219920390
[121] -0.0621044006 0.0283567681 0.2252182050 -0.3494378324 -0.6460300519
[126] -0.1915306565 -0.2661782905 0.1306987613 -0.5961478238 0.0558202515
[131] -0.1783361506 -0.1828510703 0.1395548626 0.1211252928 -0.1672319277
[136] -0.1661053845 -0.0785488146 0.2305888316 -0.4652186320 -0.3292897071
[141] 0.2419562682 -0.1764286931 0.4887751966 0.3122535454 0.1748642779
[146] 0.0973636726 -0.2958614258 0.2654612367 -0.0368040596 0.1376050034
[151] 0.6615734973 -0.0635118888 0.1288845744 0.1446682742 -0.0353993711
[156] -0.1822508893 0.2596358248 -0.3931177958 0.0324079055 0.0602176991
[161] 0.3313620268 0.2038543236 -0.6943165055 0.4012160839 0.3275038833
[166] -0.5274962585 0.4491278322 -0.1547232892 -0.1716454132 -0.0620819638
[171] 0.3274391754 -0.1939220290 0.3031098462 -0.1412843588 0.3089978881
[176] -0.1981395907 -0.7540513626 -0.1362994465 -0.9945417076 0.3511275144
[181] 0.2728855620 0.0536816255 0.2090736722 0.0332241884 0.0714956106
[186] -0.1069090542 0.0155477626 0.3837884899 -0.5609436264 -0.2921118889
[191] 0.3405368664 -0.0925537168 0.2970014221 0.2530584737 0.3285144615
[196] -0.3161014479 -0.0404154486 -0.1597963206 -0.2357760823 0.1727291626
[201] -0.0004987433 -0.0360398074 -0.3545379701 0.0641406394 0.2891120316
[206] -0.4912716337 0.1553118847 0.2324371135 -0.0130442021 0.0370679413
[211] -0.4427204370 -0.0853134003 -0.0061086761 -0.1514320956 -0.4079424749
[216] -0.0662614326 0.0209520275 0.3509401068 -0.8071579719 -0.4416803481
[221] -0.2217453197 -0.0329880105 -0.4577285289 0.4655755841 0.1945284736
[226] 0.3650431048 -0.0346051609 -0.1540935631 0.2954212547 -0.2671186737
>
> proc.time()
user system elapsed
0.629 3.307 4.113
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x600002d64000>
> .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: 0x600002d64000>
> .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: 0x600002d64000>
> .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: 0x600002d64000>
> 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: 0x600002d64780>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002d64780>
> .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: 0x600002d64780>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002d64780>
> .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: 0x600002d64780>
> 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: 0x600002d64960>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002d64960>
> .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: 0x600002d64960>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600002d64960>
> .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: 0x600002d64960>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600002d64960>
> .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: 0x600002d64960>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600002d64960>
> .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: 0x600002d64960>
> 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: 0x600002d64b40>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600002d64b40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002d64b40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002d64b40>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile63d23ab3b5e1" "BufferedMatrixFile63d2410b05f3"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile63d23ab3b5e1" "BufferedMatrixFile63d2410b05f3"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002d64de0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002d64de0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600002d64de0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600002d64de0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600002d64de0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600002d64de0>
> .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: 0x600002d64fc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002d64fc0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600002d64fc0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600002d64fc0>
> 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: 0x600002d651a0>
> .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: 0x600002d651a0>
> rm(P)
>
> proc.time()
user system elapsed
0.110 0.040 0.148
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.111 0.026 0.137