Ben Bolstad
| Snapshot Date: 2025-03-31 13:00 -0400 (Mon, 31 Mar 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_20 |
| git_last_commit: 32b6f6a |
| git_last_commit_date: 2024-10-29 09:27:20 -0400 (Tue, 29 Oct 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2025-04-02 19:31 -0400 (Wed, 02 Apr 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4764 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.3 (2025-02-28 ucrt) -- "Trophy Case" | 4495 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4522 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4449 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4426 |
| 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 251/2289 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.70.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino8 | 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 | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.70.0 |
| 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_1.70.0.tar.gz |
| StartedAt: 2025-04-01 00:12:25 -0400 (Tue, 01 Apr 2025) |
| EndedAt: 2025-04-01 00:13:39 -0400 (Tue, 01 Apr 2025) |
| EllapsedTime: 74.7 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_1.70.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.3 (2025-02-28)
* using platform: x86_64-apple-darwin20
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 12.2.0
* 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 ‘1.70.0’
* 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-3.20-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-3.20-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/4.4-x86_64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** 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 -Wl,-framework -Wl,CoreFoundation
installing to /Library/Frameworks/R.framework/Versions/4.4-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 4.4.3 (2025-02-28) -- "Trophy Case"
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
0.569 0.208 0.750
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.3 (2025-02-28) -- "Trophy Case"
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-3.20-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 473668 25.3 1034025 55.3 NA 638622 34.2
Vcells 877290 6.7 8388608 64.0 65536 2072022 15.9
>
>
>
>
> ##
> ## 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] "Tue Apr 1 00:13:01 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] "Tue Apr 1 00:13:02 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: 0x600001ad0000>
>
>
>
> 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] "Tue Apr 1 00:13:08 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] "Tue Apr 1 00:13:10 2025"
>
> ColMode(tmp2)
<pointer: 0x600001ad0000>
>
>
>
> ### 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,] 99.1051682 0.1034748 -0.39326113 0.7008453
[2,] 0.3522688 -2.1062924 -0.11984523 1.2861813
[3,] 0.9127070 -0.9275914 -0.60336335 -0.5876376
[4,] 0.5630499 -0.4174468 0.04057377 0.4424707
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-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,] 99.1051682 0.1034748 0.39326113 0.7008453
[2,] 0.3522688 2.1062924 0.11984523 1.2861813
[3,] 0.9127070 0.9275914 0.60336335 0.5876376
[4,] 0.5630499 0.4174468 0.04057377 0.4424707
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-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,] 9.9551579 0.3216750 0.6271054 0.8371650
[2,] 0.5935224 1.4513072 0.3461867 1.1340993
[3,] 0.9553570 0.9631155 0.7767647 0.7665752
[4,] 0.7503665 0.6461012 0.2014293 0.6651847
>
> 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-3.20-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,] 223.65675 28.32022 31.66431 34.07250
[2,] 31.28749 41.61936 28.58171 37.62717
[3,] 35.46628 35.55875 33.37101 33.25339
[4,] 33.06672 31.87846 27.05487 32.09432
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600001ad0060>
> exp(tmp5)
<pointer: 0x600001ad0060>
> log(tmp5,2)
<pointer: 0x600001ad0060>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 465.5122
> Min(tmp5)
[1] 54.46178
> mean(tmp5)
[1] 73.00767
> Sum(tmp5)
[1] 14601.53
> Var(tmp5)
[1] 858.0246
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.40016 72.01688 69.47718 68.53124 67.12926 76.06635 71.49083 69.92089
[9] 71.76996 72.27395
> rowSums(tmp5)
[1] 1828.003 1440.338 1389.544 1370.625 1342.585 1521.327 1429.817 1398.418
[9] 1435.399 1445.479
> rowVars(tmp5)
[1] 7805.72059 110.72292 50.91673 75.27807 31.28502 103.11564
[7] 48.01097 90.84599 101.61696 116.97775
> rowSd(tmp5)
[1] 88.349989 10.522496 7.135596 8.676294 5.593301 10.154587 6.928995
[8] 9.531316 10.080524 10.815625
> rowMax(tmp5)
[1] 465.51222 90.70710 79.68890 85.26181 77.31707 92.01381 83.60612
[8] 92.29787 87.83918 90.93416
> rowMin(tmp5)
[1] 58.68817 54.86463 56.28796 56.13916 57.99916 58.75558 58.69572 56.67713
[9] 57.18744 54.46178
>
> colMeans(tmp5)
[1] 112.27329 72.25175 66.73997 69.52174 69.68279 72.31701 70.67570
[8] 74.71190 67.29829 70.36936 68.68005 68.64995 76.13026 71.53453
[15] 76.45139 70.46206 66.63807 68.43038 72.15916 75.17575
> colSums(tmp5)
[1] 1122.7329 722.5175 667.3997 695.2174 696.8279 723.1701 706.7570
[8] 747.1190 672.9829 703.6936 686.8005 686.4995 761.3026 715.3453
[15] 764.5139 704.6206 666.3807 684.3038 721.5916 751.7575
> colVars(tmp5)
[1] 15446.90416 130.12234 37.60281 21.11138 76.55136 57.23504
[7] 83.36765 120.43248 66.65532 62.83647 101.29056 39.58611
[13] 93.65497 70.51708 100.65454 70.20626 70.98118 113.17191
[19] 184.57382 37.58905
> colSd(tmp5)
[1] 124.285575 11.407118 6.132113 4.594712 8.749364 7.565384
[7] 9.130589 10.974173 8.164271 7.926946 10.064321 6.291749
[13] 9.677550 8.397445 10.032674 8.378917 8.425033 10.638229
[19] 13.585795 6.130991
> colMax(tmp5)
[1] 465.51222 86.62525 76.16116 78.31603 82.85988 83.13429 84.53723
[8] 88.59129 77.49851 79.03479 83.62142 81.57931 90.93416 83.53809
[15] 92.29787 85.26181 81.89958 87.34101 91.09296 85.76129
> colMin(tmp5)
[1] 62.81319 55.81824 56.31116 61.43819 57.18744 56.28796 54.46178 57.99916
[9] 56.13916 58.69572 57.09794 59.41544 59.74489 59.85761 62.65881 57.75213
[17] 56.67713 59.42726 54.86463 65.94967
>
>
> ### 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] NA 72.01688 69.47718 68.53124 67.12926 76.06635 71.49083 69.92089
[9] 71.76996 72.27395
> rowSums(tmp5)
[1] NA 1440.338 1389.544 1370.625 1342.585 1521.327 1429.817 1398.418
[9] 1435.399 1445.479
> rowVars(tmp5)
[1] 8199.84397 110.72292 50.91673 75.27807 31.28502 103.11564
[7] 48.01097 90.84599 101.61696 116.97775
> rowSd(tmp5)
[1] 90.552990 10.522496 7.135596 8.676294 5.593301 10.154587 6.928995
[8] 9.531316 10.080524 10.815625
> rowMax(tmp5)
[1] NA 90.70710 79.68890 85.26181 77.31707 92.01381 83.60612 92.29787
[9] 87.83918 90.93416
> rowMin(tmp5)
[1] NA 54.86463 56.28796 56.13916 57.99916 58.75558 58.69572 56.67713
[9] 57.18744 54.46178
>
> colMeans(tmp5)
[1] 112.27329 72.25175 66.73997 69.52174 69.68279 72.31701 70.67570
[8] 74.71190 67.29829 70.36936 68.68005 68.64995 76.13026 71.53453
[15] 76.45139 70.46206 NA 68.43038 72.15916 75.17575
> colSums(tmp5)
[1] 1122.7329 722.5175 667.3997 695.2174 696.8279 723.1701 706.7570
[8] 747.1190 672.9829 703.6936 686.8005 686.4995 761.3026 715.3453
[15] 764.5139 704.6206 NA 684.3038 721.5916 751.7575
> colVars(tmp5)
[1] 15446.90416 130.12234 37.60281 21.11138 76.55136 57.23504
[7] 83.36765 120.43248 66.65532 62.83647 101.29056 39.58611
[13] 93.65497 70.51708 100.65454 70.20626 NA 113.17191
[19] 184.57382 37.58905
> colSd(tmp5)
[1] 124.285575 11.407118 6.132113 4.594712 8.749364 7.565384
[7] 9.130589 10.974173 8.164271 7.926946 10.064321 6.291749
[13] 9.677550 8.397445 10.032674 8.378917 NA 10.638229
[19] 13.585795 6.130991
> colMax(tmp5)
[1] 465.51222 86.62525 76.16116 78.31603 82.85988 83.13429 84.53723
[8] 88.59129 77.49851 79.03479 83.62142 81.57931 90.93416 83.53809
[15] 92.29787 85.26181 NA 87.34101 91.09296 85.76129
> colMin(tmp5)
[1] 62.81319 55.81824 56.31116 61.43819 57.18744 56.28796 54.46178 57.99916
[9] 56.13916 58.69572 57.09794 59.41544 59.74489 59.85761 62.65881 57.75213
[17] NA 59.42726 54.86463 65.94967
>
> Max(tmp5,na.rm=TRUE)
[1] 465.5122
> Min(tmp5,na.rm=TRUE)
[1] 54.46178
> mean(tmp5,na.rm=TRUE)
[1] 73.04589
> Sum(tmp5,na.rm=TRUE)
[1] 14536.13
> Var(tmp5,na.rm=TRUE)
[1] 862.0644
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.76851 72.01688 69.47718 68.53124 67.12926 76.06635 71.49083 69.92089
[9] 71.76996 72.27395
> rowSums(tmp5,na.rm=TRUE)
[1] 1762.602 1440.338 1389.544 1370.625 1342.585 1521.327 1429.817 1398.418
[9] 1435.399 1445.479
> rowVars(tmp5,na.rm=TRUE)
[1] 8199.84397 110.72292 50.91673 75.27807 31.28502 103.11564
[7] 48.01097 90.84599 101.61696 116.97775
> rowSd(tmp5,na.rm=TRUE)
[1] 90.552990 10.522496 7.135596 8.676294 5.593301 10.154587 6.928995
[8] 9.531316 10.080524 10.815625
> rowMax(tmp5,na.rm=TRUE)
[1] 465.51222 90.70710 79.68890 85.26181 77.31707 92.01381 83.60612
[8] 92.29787 87.83918 90.93416
> rowMin(tmp5,na.rm=TRUE)
[1] 58.68817 54.86463 56.28796 56.13916 57.99916 58.75558 58.69572 56.67713
[9] 57.18744 54.46178
>
> colMeans(tmp5,na.rm=TRUE)
[1] 112.27329 72.25175 66.73997 69.52174 69.68279 72.31701 70.67570
[8] 74.71190 67.29829 70.36936 68.68005 68.64995 76.13026 71.53453
[15] 76.45139 70.46206 66.77546 68.43038 72.15916 75.17575
> colSums(tmp5,na.rm=TRUE)
[1] 1122.7329 722.5175 667.3997 695.2174 696.8279 723.1701 706.7570
[8] 747.1190 672.9829 703.6936 686.8005 686.4995 761.3026 715.3453
[15] 764.5139 704.6206 600.9791 684.3038 721.5916 751.7575
> colVars(tmp5,na.rm=TRUE)
[1] 15446.90416 130.12234 37.60281 21.11138 76.55136 57.23504
[7] 83.36765 120.43248 66.65532 62.83647 101.29056 39.58611
[13] 93.65497 70.51708 100.65454 70.20626 79.64148 113.17191
[19] 184.57382 37.58905
> colSd(tmp5,na.rm=TRUE)
[1] 124.285575 11.407118 6.132113 4.594712 8.749364 7.565384
[7] 9.130589 10.974173 8.164271 7.926946 10.064321 6.291749
[13] 9.677550 8.397445 10.032674 8.378917 8.924208 10.638229
[19] 13.585795 6.130991
> colMax(tmp5,na.rm=TRUE)
[1] 465.51222 86.62525 76.16116 78.31603 82.85988 83.13429 84.53723
[8] 88.59129 77.49851 79.03479 83.62142 81.57931 90.93416 83.53809
[15] 92.29787 85.26181 81.89958 87.34101 91.09296 85.76129
> colMin(tmp5,na.rm=TRUE)
[1] 62.81319 55.81824 56.31116 61.43819 57.18744 56.28796 54.46178 57.99916
[9] 56.13916 58.69572 57.09794 59.41544 59.74489 59.85761 62.65881 57.75213
[17] 56.67713 59.42726 54.86463 65.94967
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 72.01688 69.47718 68.53124 67.12926 76.06635 71.49083 69.92089
[9] 71.76996 72.27395
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1440.338 1389.544 1370.625 1342.585 1521.327 1429.817 1398.418
[9] 1435.399 1445.479
> rowVars(tmp5,na.rm=TRUE)
[1] NA 110.72292 50.91673 75.27807 31.28502 103.11564 48.01097
[8] 90.84599 101.61696 116.97775
> rowSd(tmp5,na.rm=TRUE)
[1] NA 10.522496 7.135596 8.676294 5.593301 10.154587 6.928995
[8] 9.531316 10.080524 10.815625
> rowMax(tmp5,na.rm=TRUE)
[1] NA 90.70710 79.68890 85.26181 77.31707 92.01381 83.60612 92.29787
[9] 87.83918 90.93416
> rowMin(tmp5,na.rm=TRUE)
[1] NA 54.86463 56.28796 56.13916 57.99916 58.75558 58.69572 56.67713
[9] 57.18744 54.46178
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 73.02452 73.73030 66.83273 69.36666 69.25182 72.08620 70.24304 75.25941
[9] 66.42610 69.86439 69.79026 67.21336 76.57495 71.63975 77.22700 70.40470
[17] NaN 68.56970 70.05540 74.94547
> colSums(tmp5,na.rm=TRUE)
[1] 657.2206 663.5727 601.4946 624.2999 623.2664 648.7758 632.1874 677.3347
[9] 597.8349 628.7795 628.1124 604.9202 689.1745 644.7577 695.0430 633.6423
[17] 0.0000 617.1273 630.4986 674.5092
> colVars(tmp5,na.rm=TRUE)
[1] 47.52529 121.79403 42.20635 23.47975 84.03086 63.79007 91.68262
[8] 132.11412 66.42911 67.82227 100.08553 21.31656 103.13715 79.20717
[15] 106.46886 78.94503 NA 127.10003 157.85540 41.69111
> colSd(tmp5,na.rm=TRUE)
[1] 6.893859 11.036033 6.496642 4.845591 9.166835 7.986869 9.575104
[8] 11.494091 8.150405 8.235427 10.004275 4.616986 10.155646 8.899841
[15] 10.318375 8.885101 NA 11.273865 12.564052 6.456866
> colMax(tmp5,na.rm=TRUE)
[1] 81.99504 86.62525 76.16116 78.31603 82.85988 83.13429 84.53723 88.59129
[9] 77.49851 79.03479 83.62142 71.88857 90.93416 83.53809 92.29787 85.26181
[17] -Inf 87.34101 89.33007 85.76129
> colMin(tmp5,na.rm=TRUE)
[1] 62.81319 55.81824 56.31116 61.43819 57.18744 56.28796 54.46178 57.99916
[9] 56.13916 58.69572 57.09794 59.41544 59.74489 59.85761 62.65881 57.75213
[17] Inf 59.42726 54.86463 65.94967
>
>
>
>
> 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] 316.0806 277.6753 162.4774 260.0123 305.0097 221.0187 102.7335 165.0827
[9] 241.5494 152.1963
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 316.0806 277.6753 162.4774 260.0123 305.0097 221.0187 102.7335 165.0827
[9] 241.5494 152.1963
>
>
>
> 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] -1.278977e-13 -1.136868e-13 -5.684342e-14 -5.684342e-14 -2.842171e-14
[6] 2.842171e-14 0.000000e+00 0.000000e+00 5.684342e-14 -5.684342e-14
[11] 8.526513e-14 -5.684342e-14 0.000000e+00 -1.705303e-13 -1.705303e-13
[16] -1.705303e-13 -2.842171e-14 -1.989520e-13 -5.684342e-14 2.842171e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
5 19
2 13
2 1
4 17
3 17
10 11
10 19
1 13
2 6
6 18
8 4
8 12
9 13
4 13
4 1
8 4
1 6
4 8
10 18
9 12
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.429932
> Min(tmp)
[1] -2.070279
> mean(tmp)
[1] 0.08158677
> Sum(tmp)
[1] 8.158677
> Var(tmp)
[1] 0.9718563
>
> rowMeans(tmp)
[1] 0.08158677
> rowSums(tmp)
[1] 8.158677
> rowVars(tmp)
[1] 0.9718563
> rowSd(tmp)
[1] 0.9858277
> rowMax(tmp)
[1] 2.429932
> rowMin(tmp)
[1] -2.070279
>
> colMeans(tmp)
[1] -0.11953861 -1.86720651 0.30662549 -0.87685291 1.12793411 0.88545117
[7] -1.43778296 -1.64437113 -1.08113144 -0.47534572 -0.21475558 0.56843283
[13] -0.36590865 -0.38371919 1.67184630 0.52131900 -1.23755756 0.25537161
[19] 1.87647431 -0.36266387 0.76905461 1.61843696 0.61393425 -0.46918647
[25] 0.30529808 1.33511670 1.53509112 0.74562157 -0.06646442 0.97368776
[31] -2.07027853 1.59322283 0.76900810 -0.44794685 0.95413592 1.58451495
[37] 0.21177113 0.04905762 -0.41491412 -1.01059626 0.17487434 -0.15522150
[43] 1.37162757 -0.71307639 -1.56485710 -0.20970039 1.65597856 -1.55026197
[49] 0.11345550 0.58807951 0.56909401 0.49281305 0.54186292 -1.45672791
[55] -1.39239742 0.37280554 0.22908080 0.35665050 -0.46273425 -1.59166913
[61] 0.52691380 0.87257533 -1.06872967 0.97489655 -0.14857523 -0.44510211
[67] -0.18842331 -1.10658421 0.28910353 -1.22319611 -0.94214064 -0.22369078
[73] 1.35501137 -0.82017116 0.38352298 -0.15581420 1.66120239 0.60747468
[79] 0.65153782 0.74673540 -0.35774142 0.64155075 1.00127509 -0.16159157
[85] 0.29935521 0.80315651 2.42993153 0.14698075 -0.91827974 -0.72992144
[91] -0.14767008 0.75579723 1.56175845 -0.50527547 -0.81332538 0.08051257
[97] 0.90123584 -1.54074131 -1.54744287 1.41770360
> colSums(tmp)
[1] -0.11953861 -1.86720651 0.30662549 -0.87685291 1.12793411 0.88545117
[7] -1.43778296 -1.64437113 -1.08113144 -0.47534572 -0.21475558 0.56843283
[13] -0.36590865 -0.38371919 1.67184630 0.52131900 -1.23755756 0.25537161
[19] 1.87647431 -0.36266387 0.76905461 1.61843696 0.61393425 -0.46918647
[25] 0.30529808 1.33511670 1.53509112 0.74562157 -0.06646442 0.97368776
[31] -2.07027853 1.59322283 0.76900810 -0.44794685 0.95413592 1.58451495
[37] 0.21177113 0.04905762 -0.41491412 -1.01059626 0.17487434 -0.15522150
[43] 1.37162757 -0.71307639 -1.56485710 -0.20970039 1.65597856 -1.55026197
[49] 0.11345550 0.58807951 0.56909401 0.49281305 0.54186292 -1.45672791
[55] -1.39239742 0.37280554 0.22908080 0.35665050 -0.46273425 -1.59166913
[61] 0.52691380 0.87257533 -1.06872967 0.97489655 -0.14857523 -0.44510211
[67] -0.18842331 -1.10658421 0.28910353 -1.22319611 -0.94214064 -0.22369078
[73] 1.35501137 -0.82017116 0.38352298 -0.15581420 1.66120239 0.60747468
[79] 0.65153782 0.74673540 -0.35774142 0.64155075 1.00127509 -0.16159157
[85] 0.29935521 0.80315651 2.42993153 0.14698075 -0.91827974 -0.72992144
[91] -0.14767008 0.75579723 1.56175845 -0.50527547 -0.81332538 0.08051257
[97] 0.90123584 -1.54074131 -1.54744287 1.41770360
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] -0.11953861 -1.86720651 0.30662549 -0.87685291 1.12793411 0.88545117
[7] -1.43778296 -1.64437113 -1.08113144 -0.47534572 -0.21475558 0.56843283
[13] -0.36590865 -0.38371919 1.67184630 0.52131900 -1.23755756 0.25537161
[19] 1.87647431 -0.36266387 0.76905461 1.61843696 0.61393425 -0.46918647
[25] 0.30529808 1.33511670 1.53509112 0.74562157 -0.06646442 0.97368776
[31] -2.07027853 1.59322283 0.76900810 -0.44794685 0.95413592 1.58451495
[37] 0.21177113 0.04905762 -0.41491412 -1.01059626 0.17487434 -0.15522150
[43] 1.37162757 -0.71307639 -1.56485710 -0.20970039 1.65597856 -1.55026197
[49] 0.11345550 0.58807951 0.56909401 0.49281305 0.54186292 -1.45672791
[55] -1.39239742 0.37280554 0.22908080 0.35665050 -0.46273425 -1.59166913
[61] 0.52691380 0.87257533 -1.06872967 0.97489655 -0.14857523 -0.44510211
[67] -0.18842331 -1.10658421 0.28910353 -1.22319611 -0.94214064 -0.22369078
[73] 1.35501137 -0.82017116 0.38352298 -0.15581420 1.66120239 0.60747468
[79] 0.65153782 0.74673540 -0.35774142 0.64155075 1.00127509 -0.16159157
[85] 0.29935521 0.80315651 2.42993153 0.14698075 -0.91827974 -0.72992144
[91] -0.14767008 0.75579723 1.56175845 -0.50527547 -0.81332538 0.08051257
[97] 0.90123584 -1.54074131 -1.54744287 1.41770360
> colMin(tmp)
[1] -0.11953861 -1.86720651 0.30662549 -0.87685291 1.12793411 0.88545117
[7] -1.43778296 -1.64437113 -1.08113144 -0.47534572 -0.21475558 0.56843283
[13] -0.36590865 -0.38371919 1.67184630 0.52131900 -1.23755756 0.25537161
[19] 1.87647431 -0.36266387 0.76905461 1.61843696 0.61393425 -0.46918647
[25] 0.30529808 1.33511670 1.53509112 0.74562157 -0.06646442 0.97368776
[31] -2.07027853 1.59322283 0.76900810 -0.44794685 0.95413592 1.58451495
[37] 0.21177113 0.04905762 -0.41491412 -1.01059626 0.17487434 -0.15522150
[43] 1.37162757 -0.71307639 -1.56485710 -0.20970039 1.65597856 -1.55026197
[49] 0.11345550 0.58807951 0.56909401 0.49281305 0.54186292 -1.45672791
[55] -1.39239742 0.37280554 0.22908080 0.35665050 -0.46273425 -1.59166913
[61] 0.52691380 0.87257533 -1.06872967 0.97489655 -0.14857523 -0.44510211
[67] -0.18842331 -1.10658421 0.28910353 -1.22319611 -0.94214064 -0.22369078
[73] 1.35501137 -0.82017116 0.38352298 -0.15581420 1.66120239 0.60747468
[79] 0.65153782 0.74673540 -0.35774142 0.64155075 1.00127509 -0.16159157
[85] 0.29935521 0.80315651 2.42993153 0.14698075 -0.91827974 -0.72992144
[91] -0.14767008 0.75579723 1.56175845 -0.50527547 -0.81332538 0.08051257
[97] 0.90123584 -1.54074131 -1.54744287 1.41770360
> colMedians(tmp)
[1] -0.11953861 -1.86720651 0.30662549 -0.87685291 1.12793411 0.88545117
[7] -1.43778296 -1.64437113 -1.08113144 -0.47534572 -0.21475558 0.56843283
[13] -0.36590865 -0.38371919 1.67184630 0.52131900 -1.23755756 0.25537161
[19] 1.87647431 -0.36266387 0.76905461 1.61843696 0.61393425 -0.46918647
[25] 0.30529808 1.33511670 1.53509112 0.74562157 -0.06646442 0.97368776
[31] -2.07027853 1.59322283 0.76900810 -0.44794685 0.95413592 1.58451495
[37] 0.21177113 0.04905762 -0.41491412 -1.01059626 0.17487434 -0.15522150
[43] 1.37162757 -0.71307639 -1.56485710 -0.20970039 1.65597856 -1.55026197
[49] 0.11345550 0.58807951 0.56909401 0.49281305 0.54186292 -1.45672791
[55] -1.39239742 0.37280554 0.22908080 0.35665050 -0.46273425 -1.59166913
[61] 0.52691380 0.87257533 -1.06872967 0.97489655 -0.14857523 -0.44510211
[67] -0.18842331 -1.10658421 0.28910353 -1.22319611 -0.94214064 -0.22369078
[73] 1.35501137 -0.82017116 0.38352298 -0.15581420 1.66120239 0.60747468
[79] 0.65153782 0.74673540 -0.35774142 0.64155075 1.00127509 -0.16159157
[85] 0.29935521 0.80315651 2.42993153 0.14698075 -0.91827974 -0.72992144
[91] -0.14767008 0.75579723 1.56175845 -0.50527547 -0.81332538 0.08051257
[97] 0.90123584 -1.54074131 -1.54744287 1.41770360
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.1195386 -1.867207 0.3066255 -0.8768529 1.127934 0.8854512 -1.437783
[2,] -0.1195386 -1.867207 0.3066255 -0.8768529 1.127934 0.8854512 -1.437783
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.644371 -1.081131 -0.4753457 -0.2147556 0.5684328 -0.3659087 -0.3837192
[2,] -1.644371 -1.081131 -0.4753457 -0.2147556 0.5684328 -0.3659087 -0.3837192
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.671846 0.521319 -1.237558 0.2553716 1.876474 -0.3626639 0.7690546
[2,] 1.671846 0.521319 -1.237558 0.2553716 1.876474 -0.3626639 0.7690546
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.618437 0.6139342 -0.4691865 0.3052981 1.335117 1.535091 0.7456216
[2,] 1.618437 0.6139342 -0.4691865 0.3052981 1.335117 1.535091 0.7456216
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.06646442 0.9736878 -2.070279 1.593223 0.7690081 -0.4479469 0.9541359
[2,] -0.06646442 0.9736878 -2.070279 1.593223 0.7690081 -0.4479469 0.9541359
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.584515 0.2117711 0.04905762 -0.4149141 -1.010596 0.1748743 -0.1552215
[2,] 1.584515 0.2117711 0.04905762 -0.4149141 -1.010596 0.1748743 -0.1552215
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 1.371628 -0.7130764 -1.564857 -0.2097004 1.655979 -1.550262 0.1134555
[2,] 1.371628 -0.7130764 -1.564857 -0.2097004 1.655979 -1.550262 0.1134555
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.5880795 0.569094 0.4928131 0.5418629 -1.456728 -1.392397 0.3728055
[2,] 0.5880795 0.569094 0.4928131 0.5418629 -1.456728 -1.392397 0.3728055
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.2290808 0.3566505 -0.4627342 -1.591669 0.5269138 0.8725753 -1.06873
[2,] 0.2290808 0.3566505 -0.4627342 -1.591669 0.5269138 0.8725753 -1.06873
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.9748965 -0.1485752 -0.4451021 -0.1884233 -1.106584 0.2891035 -1.223196
[2,] 0.9748965 -0.1485752 -0.4451021 -0.1884233 -1.106584 0.2891035 -1.223196
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.9421406 -0.2236908 1.355011 -0.8201712 0.383523 -0.1558142 1.661202
[2,] -0.9421406 -0.2236908 1.355011 -0.8201712 0.383523 -0.1558142 1.661202
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.6074747 0.6515378 0.7467354 -0.3577414 0.6415507 1.001275 -0.1615916
[2,] 0.6074747 0.6515378 0.7467354 -0.3577414 0.6415507 1.001275 -0.1615916
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.2993552 0.8031565 2.429932 0.1469807 -0.9182797 -0.7299214 -0.1476701
[2,] 0.2993552 0.8031565 2.429932 0.1469807 -0.9182797 -0.7299214 -0.1476701
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.7557972 1.561758 -0.5052755 -0.8133254 0.08051257 0.9012358 -1.540741
[2,] 0.7557972 1.561758 -0.5052755 -0.8133254 0.08051257 0.9012358 -1.540741
[,99] [,100]
[1,] -1.547443 1.417704
[2,] -1.547443 1.417704
>
>
> Max(tmp2)
[1] 2.469414
> Min(tmp2)
[1] -3.766395
> mean(tmp2)
[1] -0.1387799
> Sum(tmp2)
[1] -13.87799
> Var(tmp2)
[1] 1.002525
>
> rowMeans(tmp2)
[1] 1.3921879791 0.0001771936 0.3575897222 0.7443222765 -3.7663954668
[6] -0.0322521191 -1.0646845756 0.0146279808 -0.6921776787 -0.6974673768
[11] -0.4835810899 -0.8508480530 0.2875440855 0.0540048278 0.0007046087
[16] 1.5426581911 -0.0280833038 1.5575258214 -0.9655119067 -0.6873350978
[21] -1.0528146638 0.8051648403 -0.5319166036 -0.8050230724 1.6238550056
[26] -0.1349440812 0.2601540200 -0.7040365917 2.4694135240 0.6655621867
[31] -0.7062258792 0.7742273837 -0.3639354634 -0.3846925170 -0.3538352128
[36] 1.4960234661 0.8854081973 1.9857472404 -0.5936634802 -0.2457954271
[41] -1.7297977642 0.2294397213 -0.0313239603 1.5313581625 -1.3166897649
[46] 0.0414960019 0.4492656286 0.6018192129 1.3449574010 1.1706683048
[51] 0.4499489604 -0.7352096616 -0.7607704698 -0.6828300521 -1.1503660661
[56] -0.6442664003 -1.7386411300 0.2872077481 -0.6757355376 2.1238297921
[61] 0.7243778331 -0.6541464554 1.1450202615 -1.7030192058 0.0669651278
[66] -1.5448223601 -1.4376052927 -0.2259632052 -0.3934019739 -0.7260947529
[71] 0.9986466446 0.3837178474 -0.1170150892 -1.8411230081 -0.4334288523
[76] -1.4656972527 0.8747929172 -1.2235626622 -0.0106945460 -0.6598709575
[81] -0.1899377792 -1.7771287052 -0.6976481624 -0.6020860905 1.0224818701
[86] -0.2690130824 -0.1718854276 -0.6505266787 -0.0170930785 0.2668890282
[91] -0.4663224331 0.5030222062 -0.1978808676 -0.4502773335 0.2750087358
[96] -0.1814190350 0.3971942134 -1.8314549843 -0.0095541251 -1.1234696245
> rowSums(tmp2)
[1] 1.3921879791 0.0001771936 0.3575897222 0.7443222765 -3.7663954668
[6] -0.0322521191 -1.0646845756 0.0146279808 -0.6921776787 -0.6974673768
[11] -0.4835810899 -0.8508480530 0.2875440855 0.0540048278 0.0007046087
[16] 1.5426581911 -0.0280833038 1.5575258214 -0.9655119067 -0.6873350978
[21] -1.0528146638 0.8051648403 -0.5319166036 -0.8050230724 1.6238550056
[26] -0.1349440812 0.2601540200 -0.7040365917 2.4694135240 0.6655621867
[31] -0.7062258792 0.7742273837 -0.3639354634 -0.3846925170 -0.3538352128
[36] 1.4960234661 0.8854081973 1.9857472404 -0.5936634802 -0.2457954271
[41] -1.7297977642 0.2294397213 -0.0313239603 1.5313581625 -1.3166897649
[46] 0.0414960019 0.4492656286 0.6018192129 1.3449574010 1.1706683048
[51] 0.4499489604 -0.7352096616 -0.7607704698 -0.6828300521 -1.1503660661
[56] -0.6442664003 -1.7386411300 0.2872077481 -0.6757355376 2.1238297921
[61] 0.7243778331 -0.6541464554 1.1450202615 -1.7030192058 0.0669651278
[66] -1.5448223601 -1.4376052927 -0.2259632052 -0.3934019739 -0.7260947529
[71] 0.9986466446 0.3837178474 -0.1170150892 -1.8411230081 -0.4334288523
[76] -1.4656972527 0.8747929172 -1.2235626622 -0.0106945460 -0.6598709575
[81] -0.1899377792 -1.7771287052 -0.6976481624 -0.6020860905 1.0224818701
[86] -0.2690130824 -0.1718854276 -0.6505266787 -0.0170930785 0.2668890282
[91] -0.4663224331 0.5030222062 -0.1978808676 -0.4502773335 0.2750087358
[96] -0.1814190350 0.3971942134 -1.8314549843 -0.0095541251 -1.1234696245
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 1.3921879791 0.0001771936 0.3575897222 0.7443222765 -3.7663954668
[6] -0.0322521191 -1.0646845756 0.0146279808 -0.6921776787 -0.6974673768
[11] -0.4835810899 -0.8508480530 0.2875440855 0.0540048278 0.0007046087
[16] 1.5426581911 -0.0280833038 1.5575258214 -0.9655119067 -0.6873350978
[21] -1.0528146638 0.8051648403 -0.5319166036 -0.8050230724 1.6238550056
[26] -0.1349440812 0.2601540200 -0.7040365917 2.4694135240 0.6655621867
[31] -0.7062258792 0.7742273837 -0.3639354634 -0.3846925170 -0.3538352128
[36] 1.4960234661 0.8854081973 1.9857472404 -0.5936634802 -0.2457954271
[41] -1.7297977642 0.2294397213 -0.0313239603 1.5313581625 -1.3166897649
[46] 0.0414960019 0.4492656286 0.6018192129 1.3449574010 1.1706683048
[51] 0.4499489604 -0.7352096616 -0.7607704698 -0.6828300521 -1.1503660661
[56] -0.6442664003 -1.7386411300 0.2872077481 -0.6757355376 2.1238297921
[61] 0.7243778331 -0.6541464554 1.1450202615 -1.7030192058 0.0669651278
[66] -1.5448223601 -1.4376052927 -0.2259632052 -0.3934019739 -0.7260947529
[71] 0.9986466446 0.3837178474 -0.1170150892 -1.8411230081 -0.4334288523
[76] -1.4656972527 0.8747929172 -1.2235626622 -0.0106945460 -0.6598709575
[81] -0.1899377792 -1.7771287052 -0.6976481624 -0.6020860905 1.0224818701
[86] -0.2690130824 -0.1718854276 -0.6505266787 -0.0170930785 0.2668890282
[91] -0.4663224331 0.5030222062 -0.1978808676 -0.4502773335 0.2750087358
[96] -0.1814190350 0.3971942134 -1.8314549843 -0.0095541251 -1.1234696245
> rowMin(tmp2)
[1] 1.3921879791 0.0001771936 0.3575897222 0.7443222765 -3.7663954668
[6] -0.0322521191 -1.0646845756 0.0146279808 -0.6921776787 -0.6974673768
[11] -0.4835810899 -0.8508480530 0.2875440855 0.0540048278 0.0007046087
[16] 1.5426581911 -0.0280833038 1.5575258214 -0.9655119067 -0.6873350978
[21] -1.0528146638 0.8051648403 -0.5319166036 -0.8050230724 1.6238550056
[26] -0.1349440812 0.2601540200 -0.7040365917 2.4694135240 0.6655621867
[31] -0.7062258792 0.7742273837 -0.3639354634 -0.3846925170 -0.3538352128
[36] 1.4960234661 0.8854081973 1.9857472404 -0.5936634802 -0.2457954271
[41] -1.7297977642 0.2294397213 -0.0313239603 1.5313581625 -1.3166897649
[46] 0.0414960019 0.4492656286 0.6018192129 1.3449574010 1.1706683048
[51] 0.4499489604 -0.7352096616 -0.7607704698 -0.6828300521 -1.1503660661
[56] -0.6442664003 -1.7386411300 0.2872077481 -0.6757355376 2.1238297921
[61] 0.7243778331 -0.6541464554 1.1450202615 -1.7030192058 0.0669651278
[66] -1.5448223601 -1.4376052927 -0.2259632052 -0.3934019739 -0.7260947529
[71] 0.9986466446 0.3837178474 -0.1170150892 -1.8411230081 -0.4334288523
[76] -1.4656972527 0.8747929172 -1.2235626622 -0.0106945460 -0.6598709575
[81] -0.1899377792 -1.7771287052 -0.6976481624 -0.6020860905 1.0224818701
[86] -0.2690130824 -0.1718854276 -0.6505266787 -0.0170930785 0.2668890282
[91] -0.4663224331 0.5030222062 -0.1978808676 -0.4502773335 0.2750087358
[96] -0.1814190350 0.3971942134 -1.8314549843 -0.0095541251 -1.1234696245
>
> colMeans(tmp2)
[1] -0.1387799
> colSums(tmp2)
[1] -13.87799
> colVars(tmp2)
[1] 1.002525
> colSd(tmp2)
[1] 1.001262
> colMax(tmp2)
[1] 2.469414
> colMin(tmp2)
[1] -3.766395
> colMedians(tmp2)
[1] -0.1856784
> colRanges(tmp2)
[,1]
[1,] -3.766395
[2,] 2.469414
>
> 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] -6.3978824 -1.9937269 -5.2147521 -0.2022783 -0.9570171 3.7781407
[7] 0.2192748 0.2153994 1.0148842 -0.2872577
> colApply(tmp,quantile)[,1]
[,1]
[1,] -3.3824652
[2,] -0.8133229
[3,] -0.4202179
[4,] 0.1023559
[5,] 0.7252500
>
> rowApply(tmp,sum)
[1] -2.2399558 -3.4153739 -2.2339283 -0.9390056 -1.6580861 -1.8892403
[7] -1.1797613 -0.3308806 0.7161709 3.3448457
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 1 5 9 4 5 2 6 8 4
[2,] 10 4 8 3 5 6 6 4 3 8
[3,] 2 2 1 4 3 1 9 3 6 10
[4,] 8 8 2 2 1 4 4 10 9 9
[5,] 7 7 6 8 2 3 8 7 1 2
[6,] 3 3 10 6 10 8 10 9 10 7
[7,] 4 5 7 10 7 7 3 5 7 6
[8,] 6 10 4 5 6 2 7 8 2 3
[9,] 9 6 9 7 8 9 1 2 5 1
[10,] 5 9 3 1 9 10 5 1 4 5
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -3.4418036 -6.6582566 0.9681691 -0.1507722 0.1161875 -0.1256616
[7] -0.1383755 -0.8866072 4.5463103 1.5195293 1.2728479 0.4984938
[13] -2.2925777 1.6671763 -1.9242858 -2.0036186 -0.3196411 0.6024083
[19] 0.2912125 3.6067074
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5689467
[2,] -1.3704104
[3,] -0.5447731
[4,] -0.1651117
[5,] 0.2074383
>
> rowApply(tmp,sum)
[1] 2.2938535 0.1481281 -4.3718980 1.5312695 -2.4539105
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 4 14 10 3 2
[2,] 3 1 16 1 4
[3,] 11 6 17 12 11
[4,] 10 16 8 17 1
[5,] 13 3 19 4 19
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.5447731 -0.8029159 0.1563891 0.1544812 0.3747859 1.07652943
[2,] 0.2074383 -2.2411536 -0.1614992 0.6565377 -1.4375541 -0.04962799
[3,] -0.1651117 0.3509457 0.3656711 -0.3017745 1.0104940 -0.97169861
[4,] -1.3704104 -2.6572734 0.7140195 1.2078963 -1.0669040 -0.38039569
[5,] -1.5689467 -1.3078594 -0.1064115 -1.8679129 1.2353657 0.19953130
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.1453637 -0.2261215 1.1342932 0.9814347 -0.23693923 0.94000178
[2,] -2.0962561 -0.1999460 1.7761208 0.6569065 0.01632034 0.08824273
[3,] 0.5434791 -1.4277781 1.7181520 -0.7894618 -0.05621838 0.16049452
[4,] 0.7371294 1.3895230 -0.5229319 0.8087372 0.37059475 -1.87857957
[5,] -0.4680915 -0.4222846 0.4406763 -0.1380874 1.17909040 1.18833439
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.08299349 0.2617973 -1.6705155 -1.11278907 -0.44932524 -0.3105207
[2,] 0.23440564 1.6061424 -0.7238157 -0.11810267 0.06858484 0.1941093
[3,] -1.47534989 0.1708452 -0.6896321 -0.03465725 -0.28305885 -0.9993037
[4,] -0.72536248 -0.5340722 1.0680657 0.02004424 1.29125633 1.7633624
[5,] -0.24327743 0.1624635 0.0916119 -0.75811387 -0.94709819 -0.0452391
[,19] [,20]
[1,] 0.68866775 0.8170031
[2,] -0.04484276 1.7161175
[3,] 0.07130013 -1.5692349
[4,] 1.05423810 0.2423324
[5,] -1.47815067 2.4004893
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-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-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 655 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 567 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-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 0.6216749 -0.25973 0.2799877 0.2129633 0.113811 0.5934298 -0.5724716
col8 col9 col10 col11 col12 col13 col14
row1 -2.549046 -2.318313 0.1607926 -0.9232986 -1.537908 1.209114 0.1956376
col15 col16 col17 col18 col19 col20
row1 0.5882577 -1.892201 -1.616813 2.00109 -0.6760903 0.5174747
> tmp[,"col10"]
col10
row1 0.16079259
row2 0.09415456
row3 0.61850097
row4 1.58944113
row5 -1.27307917
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.6216749 -0.259730 0.2799877 0.2129633 0.1138110 0.5934298 -0.5724716
row5 -0.3023155 -1.076172 -0.6609632 -1.2763961 -0.8729613 1.4701254 1.8669179
col8 col9 col10 col11 col12 col13 col14
row1 -2.5490462 -2.3183127 0.1607926 -0.9232986 -1.53790784 1.209114 0.1956376
row5 0.2516744 0.1528744 -1.2730792 1.7311973 0.07069345 1.621279 0.8401331
col15 col16 col17 col18 col19 col20
row1 0.5882577 -1.8922008 -1.616813 2.0010900 -0.6760903 0.5174747
row5 0.3960694 -0.9356172 -2.090879 0.6130921 2.4088784 -2.3382840
> tmp[,c("col6","col20")]
col6 col20
row1 0.5934298 0.5174747
row2 -0.4306524 0.3537646
row3 0.8116122 0.3377167
row4 -1.5570924 -0.8548229
row5 1.4701254 -2.3382840
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.5934298 0.5174747
row5 1.4701254 -2.3382840
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.12938 50.049 50.12247 49.91194 50.19603 106.2384 49.96089 51.04738
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.56787 49.13979 49.80134 50.79547 48.62925 48.41317 51.47723 48.39572
col17 col18 col19 col20
row1 51.00445 48.25907 47.97565 105.4785
> tmp[,"col10"]
col10
row1 49.13979
row2 29.18641
row3 29.98744
row4 29.50488
row5 50.43833
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.12938 50.04900 50.12247 49.91194 50.19603 106.2384 49.96089 51.04738
row5 49.48759 48.41792 50.91038 51.82989 50.31005 104.1624 50.34394 49.43053
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.56787 49.13979 49.80134 50.79547 48.62925 48.41317 51.47723 48.39572
row5 50.01371 50.43833 51.29968 51.60881 50.78978 50.27922 49.91415 50.56907
col17 col18 col19 col20
row1 51.00445 48.25907 47.97565 105.4785
row5 49.50829 51.10261 49.46911 104.2698
> tmp[,c("col6","col20")]
col6 col20
row1 106.23841 105.47855
row2 74.48417 74.15261
row3 74.71060 75.95204
row4 74.97630 74.96275
row5 104.16243 104.26982
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.2384 105.4785
row5 104.1624 104.2698
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.2384 105.4785
row5 104.1624 104.2698
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.1973660
[2,] 0.9572285
[3,] 0.6871701
[4,] -1.1278560
[5,] 1.0189606
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.0512156 0.5159743
[2,] -0.9760616 0.7821885
[3,] 0.9591849 2.3855420
[4,] -1.8770868 -0.3945583
[5,] 0.8861799 0.1998446
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.103357 -1.63666199
[2,] 1.064749 -0.13664471
[3,] -1.449004 0.74773464
[4,] -1.431958 -0.09492106
[5,] 1.506494 0.01008524
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.103357
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.103357
[2,] 1.064749
>
>
>
> 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 0.5911642 -1.8719480 -0.7803995 -1.2341828 -0.2769755 0.5589559
row1 -1.0271767 0.8884266 1.2971895 0.6503826 -0.3738449 -1.1932656
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 0.8958641 1.0013615 0.5511124 0.1743410 0.4626751 1.4792293 1.016289
row1 1.4350746 -0.4187808 -0.5489281 -0.2267474 0.1024530 0.5322504 -2.484911
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -1.019031 -0.5651294 -0.3712044 -0.4089143 -0.1540632 -1.446590 -1.119878
row1 1.070273 -1.4073092 0.6814162 -0.7583925 0.1868131 -1.435023 -2.244002
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.113738 -0.962421 0.3121871 -0.3975965 -0.8804163 -0.1999689 -0.2730022
[,8] [,9] [,10]
row2 0.3781846 -1.499077 -0.4157991
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.4180823 0.6652152 -1.486779 -1.805505 -2.26426 0.9727924 -0.6556056
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.2182564 -1.203206 0.1813855 1.401175 -0.2732219 0.7064237 1.253885
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.320933 -1.583583 0.7276033 0.5980282 0.5312304 0.114346
>
>
> 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: 0x600001ac4060>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM139c1686831dc"
[2] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM139c110a19811"
[3] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM139c161068c9e"
[4] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM139c174fa0ad5"
[5] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM139c14bdd61f2"
[6] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM139c133497dc7"
[7] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM139c11de0ae1f"
[8] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM139c19c7848c"
[9] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM139c19cf0858"
[10] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM139c1772cce6f"
[11] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM139c11ea51689"
[12] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM139c1686a8c16"
[13] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM139c12b132de8"
[14] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM139c1782af06f"
[15] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM139c14b0f450b"
>
>
> ### 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: 0x600001a9c000>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600001a9c000>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600001a9c000>
> rowMedians(tmp)
[1] -0.4976786158 -0.2931706004 0.4783915465 -0.0261899861 0.1874622752
[6] -0.0208355789 0.0192982702 -0.3411441847 -0.2629933115 -0.5425474033
[11] -0.1324860811 -0.2606437744 -0.2743922485 -0.3268941575 -0.4919560553
[16] 0.0641355728 0.3709114261 0.0819403755 -0.4840177126 0.0231117781
[21] -0.4667513994 0.3237742843 0.0776623221 0.0373211716 -0.4226615403
[26] -0.0865776241 0.2637339208 -0.2429772668 0.0662666486 0.0381585154
[31] -0.3508498210 -0.2706339316 0.1285039040 0.1602833470 -0.1193136737
[36] -0.3124989730 -0.2249786866 0.5720106529 0.0202475152 -0.1903864138
[41] -0.5460137076 -0.1077566487 -0.7755783841 0.0249597996 -0.3864090406
[46] 0.2768771828 0.6213824277 -0.4335539670 -0.1645323883 -0.2318991291
[51] -0.3128939660 0.5876366771 -0.1525596196 0.0993268601 0.1383899119
[56] 0.2641939681 -0.3079921375 -0.1332390282 -0.0963362244 -0.4296788165
[61] -0.4431080247 0.0743448594 0.0026817567 -0.6853345845 -0.5018463400
[66] -0.2194177580 -0.6109993930 0.1775293182 0.2444366297 0.3337978803
[71] -0.1115438713 0.0399154193 -0.3090858335 0.0004417457 -0.1427714575
[76] -0.4536184841 0.1429318772 0.1650532902 0.0087896557 0.4289960721
[81] 0.2012648628 0.3863662385 0.1162316041 0.0701871679 0.0138189120
[86] -0.2871020443 -0.2609618762 -0.0443576233 -0.4543339500 0.4087399612
[91] 0.1668002976 0.0683824935 0.5177900852 0.2852727212 -0.2649963074
[96] 0.1483132578 0.0957972522 0.6973924673 -0.3480488647 -0.0441485237
[101] 0.2104511841 0.1818878114 -0.1700889527 -0.1145045145 -0.0174752102
[106] -0.0344075258 0.3280729354 -0.2295113348 -0.2513334725 -0.2046082191
[111] 0.1794241340 -0.2317765895 -0.2898230669 0.6448936245 0.0728040888
[116] -0.4246556934 0.5661924718 0.3002715424 0.1591500628 0.3747180078
[121] 0.2652254322 -0.1871286517 -0.7984796269 0.0456510485 -0.1156038940
[126] 0.4318376660 -0.7318008434 -0.5204470408 -0.2404925202 -0.3034460676
[131] -0.0674615417 0.0894622996 0.2239888096 0.1953477740 0.4145179984
[136] -0.1008852912 -0.0342198514 0.2048564259 -0.3824002902 0.1750689868
[141] -0.4215510784 0.0726990893 0.4284428326 0.1888722991 -0.1702660294
[146] -0.3755685069 0.4146896061 -0.1575357087 0.0801539967 0.0948622903
[151] -0.4729724099 -0.0692886284 -0.2351645281 0.1482511225 -0.3512281442
[156] -0.0537274277 -0.0587725371 0.2130011273 -0.1595566038 0.5826337403
[161] 0.5085131143 -0.0572669112 0.1852620468 0.0854847607 -0.2375277884
[166] 0.1114074399 0.2143132831 -0.3944758434 -0.2846386536 0.0134352708
[171] 0.0483682576 -0.4512108067 -0.2481580802 -0.3220625115 -0.0822659543
[176] -0.0107837068 0.0358043302 -0.2356133409 -0.2748153044 0.0047981246
[181] 0.1618022784 0.0277484898 -0.1601108813 0.4930030031 -0.1657050246
[186] 0.4496775641 -0.2989486094 0.1684703054 0.4158629110 -0.0632900142
[191] 0.3419876439 0.0037464336 -0.4048846694 0.2328406263 0.6940523566
[196] 0.1349343501 -0.1962362601 -0.3532981824 -0.1254453252 -0.1454219619
[201] 0.2313028974 0.0928644477 -0.4170999269 -0.3067830876 0.4709598665
[206] 0.1198416444 0.6606883622 -0.3553124643 0.0740090492 -0.1539983735
[211] 0.0228429941 0.1472664607 0.1230899957 -0.0167324629 -0.0633370188
[216] -0.3777601148 0.1098396065 -0.0402223774 -0.5149620685 0.6419894963
[221] -0.0882203945 0.0497747009 0.0519718332 -0.3249488325 0.2648514098
[226] 0.0204343400 -0.0721420217 -0.3320032714 0.3315661931 0.1166968501
>
> proc.time()
user system elapsed
5.106 18.747 25.757
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.3 (2025-02-28) -- "Trophy Case"
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: 0x6000019b4000>
> .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: 0x6000019b4000>
> .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: 0x6000019b4000>
> .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: 0x6000019b4000>
> 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: 0x6000019b40c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000019b40c0>
> .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: 0x6000019b40c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000019b40c0>
> .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: 0x6000019b40c0>
> 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: 0x6000019bc000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000019bc000>
> .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: 0x6000019bc000>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000019bc000>
> .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: 0x6000019bc000>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000019bc000>
> .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: 0x6000019bc000>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000019bc000>
> .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: 0x6000019bc000>
> 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: 0x6000019a0000>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000019a0000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000019a0000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000019a0000>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile13e7c2d2c52c2" "BufferedMatrixFile13e7c38ed55b9"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile13e7c2d2c52c2" "BufferedMatrixFile13e7c38ed55b9"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000019a4120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000019a4120>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000019a4120>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000019a4120>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000019a4120>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000019a4120>
> .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: 0x6000019a4300>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000019a4300>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000019a4300>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000019a4300>
> 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: 0x6000019a8000>
> .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: 0x6000019a8000>
> rm(P)
>
> proc.time()
user system elapsed
0.567 0.213 0.766
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.3 (2025-02-28) -- "Trophy Case"
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.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.583 0.137 0.688