Ben Bolstad
| Snapshot Date: 2025-03-20 13:00 -0400 (Thu, 20 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 2025-03-24 12:09 -0400 (Mon, 24 Mar 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" | 4763 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.3 (2025-02-28 ucrt) -- "Trophy Case" | 4494 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4521 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4448 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4414 |
| 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: 2025-03-21 12:53:23 -0400 (Fri, 21 Mar 2025) |
| EndedAt: 2025-03-21 12:54:02 -0400 (Fri, 21 Mar 2025) |
| EllapsedTime: 39.2 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_1.70.0.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: aarch64-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 Ventura 13.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.70.0’
* 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 15.0.0 (clang-1500.0.40.1)’
* 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-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.0.40.1)’
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 -Wl,-framework -Wl,CoreFoundation
installing to /Library/Frameworks/R.framework/Versions/4.4-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 4.4.3 (2025-02-28) -- "Trophy Case"
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
0.348 0.126 0.467
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: 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-3.20-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 473648 25.3 1033988 55.3 NA 638582 34.2
Vcells 877222 6.7 8388608 64.0 65536 2072452 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] "Fri Mar 21 12:53:41 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Mar 21 12:53:41 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: 0x600002ce4240>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Mar 21 12:53:44 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Mar 21 12:53:45 2025"
>
> ColMode(tmp2)
<pointer: 0x600002ce4240>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 98.6629240 -0.42619149 -1.2857570 0.6815332
[2,] 0.5878419 0.05033564 0.7885674 0.2277566
[3,] 0.2451121 -0.23055502 -0.9026399 -1.2728059
[4,] 1.5356296 -1.54622848 -0.1694619 -0.9095924
> 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,] 98.6629240 0.42619149 1.2857570 0.6815332
[2,] 0.5878419 0.05033564 0.7885674 0.2277566
[3,] 0.2451121 0.23055502 0.9026399 1.2728059
[4,] 1.5356296 1.54622848 0.1694619 0.9095924
> 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,] 9.9329212 0.6528334 1.1339122 0.8255502
[2,] 0.7667085 0.2243561 0.8880132 0.4772385
[3,] 0.4950880 0.4801615 0.9500736 1.1281870
[4,] 1.2392052 1.2434744 0.4116575 0.9537256
>
> 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,] 222.99214 31.95453 37.62488 33.93704
[2,] 33.25493 27.29390 34.66870 30.00014
[3,] 30.19599 30.03217 35.40338 37.55468
[4,] 38.92768 38.98097 29.28604 35.44685
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600002ce0120>
> exp(tmp5)
<pointer: 0x600002ce0120>
> log(tmp5,2)
<pointer: 0x600002ce0120>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 464.1289
> Min(tmp5)
[1] 53.78279
> mean(tmp5)
[1] 72.7335
> Sum(tmp5)
[1] 14546.7
> Var(tmp5)
[1] 835.7965
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 93.07571 68.48161 70.64029 71.04627 72.75326 71.02919 67.47779 68.31316
[9] 70.89561 73.62209
> rowSums(tmp5)
[1] 1861.514 1369.632 1412.806 1420.925 1455.065 1420.584 1349.556 1366.263
[9] 1417.912 1472.442
> rowVars(tmp5)
[1] 7680.91470 66.38904 74.54393 57.74183 74.94152 56.25850
[7] 53.41285 66.23666 63.96426 40.15287
> rowSd(tmp5)
[1] 87.640828 8.147947 8.633883 7.598805 8.656877 7.500567 7.308410
[8] 8.138591 7.997766 6.336630
> rowMax(tmp5)
[1] 464.12892 82.00712 86.31325 81.13379 93.71363 81.49219 80.55887
[8] 86.77250 83.23068 83.28050
> rowMin(tmp5)
[1] 61.75776 56.51458 55.56699 58.05150 59.77471 57.94663 53.78279 59.53703
[9] 59.07853 56.64456
>
> colMeans(tmp5)
[1] 108.29362 69.78961 70.32589 72.26328 70.56512 66.85386 65.37735
[8] 70.55173 66.88993 69.84522 67.47685 72.77685 71.85528 73.18538
[15] 73.48649 71.70108 71.62580 77.45123 72.47144 71.88392
> colSums(tmp5)
[1] 1082.9362 697.8961 703.2589 722.6328 705.6512 668.5386 653.7735
[8] 705.5173 668.8993 698.4522 674.7685 727.7685 718.5528 731.8538
[15] 734.8649 717.0108 716.2580 774.5123 724.7144 718.8392
> colVars(tmp5)
[1] 15672.61795 66.71744 77.41195 35.76231 73.02115 31.48560
[7] 73.75616 109.86008 27.96167 62.95392 125.87004 53.58892
[13] 70.24996 46.22866 21.64769 67.98897 93.88294 28.48678
[19] 65.25401 37.46779
> colSd(tmp5)
[1] 125.190327 8.168075 8.798406 5.980160 8.545241 5.611203
[7] 8.588140 10.481416 5.287880 7.934351 11.219182 7.320445
[13] 8.381525 6.799166 4.652708 8.245543 9.689321 5.337301
[19] 8.077996 6.121094
> colMax(tmp5)
[1] 464.12892 81.13379 81.07803 80.14136 84.53920 74.13607 81.47365
[8] 81.49219 73.35604 86.31325 93.71363 86.77250 82.00712 81.55310
[15] 80.55887 87.55029 83.88491 85.18030 86.58977 79.11435
> colMin(tmp5)
[1] 59.07853 56.80867 59.53703 62.44137 59.68665 58.36036 55.56699 53.90472
[9] 57.94663 61.56474 56.64456 61.37427 53.78279 61.26081 64.58349 61.29455
[17] 59.29477 69.57273 61.13795 61.22960
>
>
> ### 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] 93.07571 68.48161 70.64029 71.04627 72.75326 NA 67.47779 68.31316
[9] 70.89561 73.62209
> rowSums(tmp5)
[1] 1861.514 1369.632 1412.806 1420.925 1455.065 NA 1349.556 1366.263
[9] 1417.912 1472.442
> rowVars(tmp5)
[1] 7680.91470 66.38904 74.54393 57.74183 74.94152 57.66280
[7] 53.41285 66.23666 63.96426 40.15287
> rowSd(tmp5)
[1] 87.640828 8.147947 8.633883 7.598805 8.656877 7.593603 7.308410
[8] 8.138591 7.997766 6.336630
> rowMax(tmp5)
[1] 464.12892 82.00712 86.31325 81.13379 93.71363 NA 80.55887
[8] 86.77250 83.23068 83.28050
> rowMin(tmp5)
[1] 61.75776 56.51458 55.56699 58.05150 59.77471 NA 53.78279 59.53703
[9] 59.07853 56.64456
>
> colMeans(tmp5)
[1] 108.29362 69.78961 70.32589 72.26328 70.56512 66.85386 65.37735
[8] 70.55173 66.88993 69.84522 67.47685 72.77685 71.85528 73.18538
[15] 73.48649 71.70108 71.62580 NA 72.47144 71.88392
> colSums(tmp5)
[1] 1082.9362 697.8961 703.2589 722.6328 705.6512 668.5386 653.7735
[8] 705.5173 668.8993 698.4522 674.7685 727.7685 718.5528 731.8538
[15] 734.8649 717.0108 716.2580 NA 724.7144 718.8392
> colVars(tmp5)
[1] 15672.61795 66.71744 77.41195 35.76231 73.02115 31.48560
[7] 73.75616 109.86008 27.96167 62.95392 125.87004 53.58892
[13] 70.24996 46.22866 21.64769 67.98897 93.88294 NA
[19] 65.25401 37.46779
> colSd(tmp5)
[1] 125.190327 8.168075 8.798406 5.980160 8.545241 5.611203
[7] 8.588140 10.481416 5.287880 7.934351 11.219182 7.320445
[13] 8.381525 6.799166 4.652708 8.245543 9.689321 NA
[19] 8.077996 6.121094
> colMax(tmp5)
[1] 464.12892 81.13379 81.07803 80.14136 84.53920 74.13607 81.47365
[8] 81.49219 73.35604 86.31325 93.71363 86.77250 82.00712 81.55310
[15] 80.55887 87.55029 83.88491 NA 86.58977 79.11435
> colMin(tmp5)
[1] 59.07853 56.80867 59.53703 62.44137 59.68665 58.36036 55.56699 53.90472
[9] 57.94663 61.56474 56.64456 61.37427 53.78279 61.26081 64.58349 61.29455
[17] 59.29477 NA 61.13795 61.22960
>
> Max(tmp5,na.rm=TRUE)
[1] 464.1289
> Min(tmp5,na.rm=TRUE)
[1] 53.78279
> mean(tmp5,na.rm=TRUE)
[1] 72.7148
> Sum(tmp5,na.rm=TRUE)
[1] 14470.24
> Var(tmp5,na.rm=TRUE)
[1] 839.9474
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.07571 68.48161 70.64029 71.04627 72.75326 70.74365 67.47779 68.31316
[9] 70.89561 73.62209
> rowSums(tmp5,na.rm=TRUE)
[1] 1861.514 1369.632 1412.806 1420.925 1455.065 1344.129 1349.556 1366.263
[9] 1417.912 1472.442
> rowVars(tmp5,na.rm=TRUE)
[1] 7680.91470 66.38904 74.54393 57.74183 74.94152 57.66280
[7] 53.41285 66.23666 63.96426 40.15287
> rowSd(tmp5,na.rm=TRUE)
[1] 87.640828 8.147947 8.633883 7.598805 8.656877 7.593603 7.308410
[8] 8.138591 7.997766 6.336630
> rowMax(tmp5,na.rm=TRUE)
[1] 464.12892 82.00712 86.31325 81.13379 93.71363 81.49219 80.55887
[8] 86.77250 83.23068 83.28050
> rowMin(tmp5,na.rm=TRUE)
[1] 61.75776 56.51458 55.56699 58.05150 59.77471 57.94663 53.78279 59.53703
[9] 59.07853 56.64456
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.29362 69.78961 70.32589 72.26328 70.56512 66.85386 65.37735
[8] 70.55173 66.88993 69.84522 67.47685 72.77685 71.85528 73.18538
[15] 73.48649 71.70108 71.62580 77.56199 72.47144 71.88392
> colSums(tmp5,na.rm=TRUE)
[1] 1082.9362 697.8961 703.2589 722.6328 705.6512 668.5386 653.7735
[8] 705.5173 668.8993 698.4522 674.7685 727.7685 718.5528 731.8538
[15] 734.8649 717.0108 716.2580 698.0579 724.7144 718.8392
> colVars(tmp5,na.rm=TRUE)
[1] 15672.61795 66.71744 77.41195 35.76231 73.02115 31.48560
[7] 73.75616 109.86008 27.96167 62.95392 125.87004 53.58892
[13] 70.24996 46.22866 21.64769 67.98897 93.88294 31.90960
[19] 65.25401 37.46779
> colSd(tmp5,na.rm=TRUE)
[1] 125.190327 8.168075 8.798406 5.980160 8.545241 5.611203
[7] 8.588140 10.481416 5.287880 7.934351 11.219182 7.320445
[13] 8.381525 6.799166 4.652708 8.245543 9.689321 5.648858
[19] 8.077996 6.121094
> colMax(tmp5,na.rm=TRUE)
[1] 464.12892 81.13379 81.07803 80.14136 84.53920 74.13607 81.47365
[8] 81.49219 73.35604 86.31325 93.71363 86.77250 82.00712 81.55310
[15] 80.55887 87.55029 83.88491 85.18030 86.58977 79.11435
> colMin(tmp5,na.rm=TRUE)
[1] 59.07853 56.80867 59.53703 62.44137 59.68665 58.36036 55.56699 53.90472
[9] 57.94663 61.56474 56.64456 61.37427 53.78279 61.26081 64.58349 61.29455
[17] 59.29477 69.57273 61.13795 61.22960
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.07571 68.48161 70.64029 71.04627 72.75326 NaN 67.47779 68.31316
[9] 70.89561 73.62209
> rowSums(tmp5,na.rm=TRUE)
[1] 1861.514 1369.632 1412.806 1420.925 1455.065 0.000 1349.556 1366.263
[9] 1417.912 1472.442
> rowVars(tmp5,na.rm=TRUE)
[1] 7680.91470 66.38904 74.54393 57.74183 74.94152 NA
[7] 53.41285 66.23666 63.96426 40.15287
> rowSd(tmp5,na.rm=TRUE)
[1] 87.640828 8.147947 8.633883 7.598805 8.656877 NA 7.308410
[8] 8.138591 7.997766 6.336630
> rowMax(tmp5,na.rm=TRUE)
[1] 464.12892 82.00712 86.31325 81.13379 93.71363 NA 80.55887
[8] 86.77250 83.23068 83.28050
> rowMin(tmp5,na.rm=TRUE)
[1] 61.75776 56.51458 55.56699 58.05150 59.77471 NA 53.78279 59.53703
[9] 59.07853 56.64456
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.41771 69.72432 69.19388 72.77667 69.53910 67.79758 65.95320
[8] 69.33613 67.88363 69.14545 67.00301 73.15301 71.27861 73.92222
[15] 73.38933 72.60452 71.44584 NaN 72.03612 71.29497
> colSums(tmp5,na.rm=TRUE)
[1] 1020.7594 627.5189 622.7449 654.9900 625.8519 610.1782 593.5788
[8] 624.0252 610.9527 622.3090 603.0271 658.3771 641.5074 665.2999
[15] 660.5040 653.4407 643.0126 0.0000 648.3251 641.6547
> colVars(tmp5,na.rm=TRUE)
[1] 17336.31120 75.00916 72.67223 37.26739 70.30569 25.40192
[7] 79.24521 106.96849 20.34819 65.31422 139.07792 58.69575
[13] 75.28995 45.89933 24.24747 67.30529 105.25396 NA
[19] 71.27889 38.24907
> colSd(tmp5,na.rm=TRUE)
[1] 131.667426 8.660783 8.524801 6.104702 8.384849 5.040032
[7] 8.901978 10.342557 4.510896 8.081722 11.793130 7.661315
[13] 8.676978 6.774904 4.924172 8.203980 10.259335 NA
[19] 8.442683 6.184583
> colMax(tmp5,na.rm=TRUE)
[1] 464.12892 81.13379 81.07803 80.14136 84.53920 74.13607 81.47365
[8] 81.11449 73.35604 86.31325 93.71363 86.77250 82.00712 81.55310
[15] 80.55887 87.55029 83.88491 -Inf 86.58977 79.11435
> colMin(tmp5,na.rm=TRUE)
[1] 59.07853 56.80867 59.53703 62.44137 59.68665 59.63878 55.56699 53.90472
[9] 61.99690 61.56474 56.64456 61.37427 53.78279 61.26081 64.58349 61.29455
[17] 59.29477 Inf 61.13795 61.22960
>
>
>
>
> 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] 203.3109 158.9737 158.9254 239.0359 265.6012 213.2484 132.2660 193.5713
[9] 397.2343 165.4916
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 203.3109 158.9737 158.9254 239.0359 265.6012 213.2484 132.2660 193.5713
[9] 397.2343 165.4916
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -2.842171e-14 1.421085e-14 -2.842171e-13 0.000000e+00 -1.136868e-13
[6] 1.421085e-14 -2.273737e-13 1.705303e-13 1.136868e-13 -5.684342e-14
[11] -1.136868e-13 -5.684342e-14 -1.136868e-13 5.684342e-14 -1.421085e-13
[16] -1.421085e-14 5.684342e-14 0.000000e+00 -2.273737e-13 -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)
+ }
6 16
9 18
9 7
4 19
8 8
6 9
7 17
1 17
4 15
3 14
1 3
4 10
5 10
5 4
1 11
7 12
7 11
7 12
9 18
2 16
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] 2.31543
> Min(tmp)
[1] -2.018732
> mean(tmp)
[1] -0.06967489
> Sum(tmp)
[1] -6.967489
> Var(tmp)
[1] 0.7313472
>
> rowMeans(tmp)
[1] -0.06967489
> rowSums(tmp)
[1] -6.967489
> rowVars(tmp)
[1] 0.7313472
> rowSd(tmp)
[1] 0.8551884
> rowMax(tmp)
[1] 2.31543
> rowMin(tmp)
[1] -2.018732
>
> colMeans(tmp)
[1] 0.543328929 0.504128778 -0.406395941 -1.143318719 1.546187069
[6] -0.346703682 0.047229285 -1.026584155 -0.653105782 0.656849527
[11] -2.018732187 -0.387532463 -0.999045279 -0.243355473 0.490829033
[16] 0.003254311 -0.371390590 0.858348113 0.592018373 0.813429123
[21] -0.872007051 0.621137046 1.244010105 -0.433760221 0.526677146
[26] 0.309168730 -1.178939631 0.667011810 -0.155462258 1.010836126
[31] 0.288589898 0.017094802 -0.357607852 -0.969413815 -1.626080778
[36] -1.073306673 -0.527733218 1.126156873 0.062538912 1.295970531
[41] 0.080190828 -0.598237127 -1.505284937 0.425330734 0.090934236
[46] -1.324880080 -0.592818867 -0.128286339 -0.324691937 -1.977920608
[51] -0.564171961 -1.058260979 -0.534348803 0.305696402 -0.222163210
[56] -0.895885276 0.328605360 -0.318049287 0.839651519 -0.500304527
[61] -0.389694489 0.645011792 -1.324697450 0.723868282 0.082896551
[66] -0.337343976 1.437170502 -1.285260799 1.105541832 -0.889479462
[71] -0.503984599 1.745403323 -0.367209395 1.140739746 -0.551042311
[76] -0.198907532 0.288234049 0.105849520 -0.108452714 2.315430488
[81] -0.104422159 0.936963560 0.212077009 0.511369671 0.362428798
[86] -0.672128770 1.776679412 -0.796702123 0.962198864 0.099087116
[91] -0.086598981 0.005836285 -1.326890597 -0.232038338 0.170192379
[96] -0.494825326 -0.014443720 0.389827367 -1.958413526 -0.301183421
> colSums(tmp)
[1] 0.543328929 0.504128778 -0.406395941 -1.143318719 1.546187069
[6] -0.346703682 0.047229285 -1.026584155 -0.653105782 0.656849527
[11] -2.018732187 -0.387532463 -0.999045279 -0.243355473 0.490829033
[16] 0.003254311 -0.371390590 0.858348113 0.592018373 0.813429123
[21] -0.872007051 0.621137046 1.244010105 -0.433760221 0.526677146
[26] 0.309168730 -1.178939631 0.667011810 -0.155462258 1.010836126
[31] 0.288589898 0.017094802 -0.357607852 -0.969413815 -1.626080778
[36] -1.073306673 -0.527733218 1.126156873 0.062538912 1.295970531
[41] 0.080190828 -0.598237127 -1.505284937 0.425330734 0.090934236
[46] -1.324880080 -0.592818867 -0.128286339 -0.324691937 -1.977920608
[51] -0.564171961 -1.058260979 -0.534348803 0.305696402 -0.222163210
[56] -0.895885276 0.328605360 -0.318049287 0.839651519 -0.500304527
[61] -0.389694489 0.645011792 -1.324697450 0.723868282 0.082896551
[66] -0.337343976 1.437170502 -1.285260799 1.105541832 -0.889479462
[71] -0.503984599 1.745403323 -0.367209395 1.140739746 -0.551042311
[76] -0.198907532 0.288234049 0.105849520 -0.108452714 2.315430488
[81] -0.104422159 0.936963560 0.212077009 0.511369671 0.362428798
[86] -0.672128770 1.776679412 -0.796702123 0.962198864 0.099087116
[91] -0.086598981 0.005836285 -1.326890597 -0.232038338 0.170192379
[96] -0.494825326 -0.014443720 0.389827367 -1.958413526 -0.301183421
> 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] 0.543328929 0.504128778 -0.406395941 -1.143318719 1.546187069
[6] -0.346703682 0.047229285 -1.026584155 -0.653105782 0.656849527
[11] -2.018732187 -0.387532463 -0.999045279 -0.243355473 0.490829033
[16] 0.003254311 -0.371390590 0.858348113 0.592018373 0.813429123
[21] -0.872007051 0.621137046 1.244010105 -0.433760221 0.526677146
[26] 0.309168730 -1.178939631 0.667011810 -0.155462258 1.010836126
[31] 0.288589898 0.017094802 -0.357607852 -0.969413815 -1.626080778
[36] -1.073306673 -0.527733218 1.126156873 0.062538912 1.295970531
[41] 0.080190828 -0.598237127 -1.505284937 0.425330734 0.090934236
[46] -1.324880080 -0.592818867 -0.128286339 -0.324691937 -1.977920608
[51] -0.564171961 -1.058260979 -0.534348803 0.305696402 -0.222163210
[56] -0.895885276 0.328605360 -0.318049287 0.839651519 -0.500304527
[61] -0.389694489 0.645011792 -1.324697450 0.723868282 0.082896551
[66] -0.337343976 1.437170502 -1.285260799 1.105541832 -0.889479462
[71] -0.503984599 1.745403323 -0.367209395 1.140739746 -0.551042311
[76] -0.198907532 0.288234049 0.105849520 -0.108452714 2.315430488
[81] -0.104422159 0.936963560 0.212077009 0.511369671 0.362428798
[86] -0.672128770 1.776679412 -0.796702123 0.962198864 0.099087116
[91] -0.086598981 0.005836285 -1.326890597 -0.232038338 0.170192379
[96] -0.494825326 -0.014443720 0.389827367 -1.958413526 -0.301183421
> colMin(tmp)
[1] 0.543328929 0.504128778 -0.406395941 -1.143318719 1.546187069
[6] -0.346703682 0.047229285 -1.026584155 -0.653105782 0.656849527
[11] -2.018732187 -0.387532463 -0.999045279 -0.243355473 0.490829033
[16] 0.003254311 -0.371390590 0.858348113 0.592018373 0.813429123
[21] -0.872007051 0.621137046 1.244010105 -0.433760221 0.526677146
[26] 0.309168730 -1.178939631 0.667011810 -0.155462258 1.010836126
[31] 0.288589898 0.017094802 -0.357607852 -0.969413815 -1.626080778
[36] -1.073306673 -0.527733218 1.126156873 0.062538912 1.295970531
[41] 0.080190828 -0.598237127 -1.505284937 0.425330734 0.090934236
[46] -1.324880080 -0.592818867 -0.128286339 -0.324691937 -1.977920608
[51] -0.564171961 -1.058260979 -0.534348803 0.305696402 -0.222163210
[56] -0.895885276 0.328605360 -0.318049287 0.839651519 -0.500304527
[61] -0.389694489 0.645011792 -1.324697450 0.723868282 0.082896551
[66] -0.337343976 1.437170502 -1.285260799 1.105541832 -0.889479462
[71] -0.503984599 1.745403323 -0.367209395 1.140739746 -0.551042311
[76] -0.198907532 0.288234049 0.105849520 -0.108452714 2.315430488
[81] -0.104422159 0.936963560 0.212077009 0.511369671 0.362428798
[86] -0.672128770 1.776679412 -0.796702123 0.962198864 0.099087116
[91] -0.086598981 0.005836285 -1.326890597 -0.232038338 0.170192379
[96] -0.494825326 -0.014443720 0.389827367 -1.958413526 -0.301183421
> colMedians(tmp)
[1] 0.543328929 0.504128778 -0.406395941 -1.143318719 1.546187069
[6] -0.346703682 0.047229285 -1.026584155 -0.653105782 0.656849527
[11] -2.018732187 -0.387532463 -0.999045279 -0.243355473 0.490829033
[16] 0.003254311 -0.371390590 0.858348113 0.592018373 0.813429123
[21] -0.872007051 0.621137046 1.244010105 -0.433760221 0.526677146
[26] 0.309168730 -1.178939631 0.667011810 -0.155462258 1.010836126
[31] 0.288589898 0.017094802 -0.357607852 -0.969413815 -1.626080778
[36] -1.073306673 -0.527733218 1.126156873 0.062538912 1.295970531
[41] 0.080190828 -0.598237127 -1.505284937 0.425330734 0.090934236
[46] -1.324880080 -0.592818867 -0.128286339 -0.324691937 -1.977920608
[51] -0.564171961 -1.058260979 -0.534348803 0.305696402 -0.222163210
[56] -0.895885276 0.328605360 -0.318049287 0.839651519 -0.500304527
[61] -0.389694489 0.645011792 -1.324697450 0.723868282 0.082896551
[66] -0.337343976 1.437170502 -1.285260799 1.105541832 -0.889479462
[71] -0.503984599 1.745403323 -0.367209395 1.140739746 -0.551042311
[76] -0.198907532 0.288234049 0.105849520 -0.108452714 2.315430488
[81] -0.104422159 0.936963560 0.212077009 0.511369671 0.362428798
[86] -0.672128770 1.776679412 -0.796702123 0.962198864 0.099087116
[91] -0.086598981 0.005836285 -1.326890597 -0.232038338 0.170192379
[96] -0.494825326 -0.014443720 0.389827367 -1.958413526 -0.301183421
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.5433289 0.5041288 -0.4063959 -1.143319 1.546187 -0.3467037 0.04722929
[2,] 0.5433289 0.5041288 -0.4063959 -1.143319 1.546187 -0.3467037 0.04722929
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.026584 -0.6531058 0.6568495 -2.018732 -0.3875325 -0.9990453 -0.2433555
[2,] -1.026584 -0.6531058 0.6568495 -2.018732 -0.3875325 -0.9990453 -0.2433555
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.490829 0.003254311 -0.3713906 0.8583481 0.5920184 0.8134291 -0.8720071
[2,] 0.490829 0.003254311 -0.3713906 0.8583481 0.5920184 0.8134291 -0.8720071
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.621137 1.24401 -0.4337602 0.5266771 0.3091687 -1.17894 0.6670118
[2,] 0.621137 1.24401 -0.4337602 0.5266771 0.3091687 -1.17894 0.6670118
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.1554623 1.010836 0.2885899 0.0170948 -0.3576079 -0.9694138 -1.626081
[2,] -0.1554623 1.010836 0.2885899 0.0170948 -0.3576079 -0.9694138 -1.626081
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.073307 -0.5277332 1.126157 0.06253891 1.295971 0.08019083 -0.5982371
[2,] -1.073307 -0.5277332 1.126157 0.06253891 1.295971 0.08019083 -0.5982371
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.505285 0.4253307 0.09093424 -1.32488 -0.5928189 -0.1282863 -0.3246919
[2,] -1.505285 0.4253307 0.09093424 -1.32488 -0.5928189 -0.1282863 -0.3246919
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -1.977921 -0.564172 -1.058261 -0.5343488 0.3056964 -0.2221632 -0.8958853
[2,] -1.977921 -0.564172 -1.058261 -0.5343488 0.3056964 -0.2221632 -0.8958853
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.3286054 -0.3180493 0.8396515 -0.5003045 -0.3896945 0.6450118 -1.324697
[2,] 0.3286054 -0.3180493 0.8396515 -0.5003045 -0.3896945 0.6450118 -1.324697
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.7238683 0.08289655 -0.337344 1.437171 -1.285261 1.105542 -0.8894795
[2,] 0.7238683 0.08289655 -0.337344 1.437171 -1.285261 1.105542 -0.8894795
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.5039846 1.745403 -0.3672094 1.14074 -0.5510423 -0.1989075 0.288234
[2,] -0.5039846 1.745403 -0.3672094 1.14074 -0.5510423 -0.1989075 0.288234
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.1058495 -0.1084527 2.31543 -0.1044222 0.9369636 0.212077 0.5113697
[2,] 0.1058495 -0.1084527 2.31543 -0.1044222 0.9369636 0.212077 0.5113697
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.3624288 -0.6721288 1.776679 -0.7967021 0.9621989 0.09908712 -0.08659898
[2,] 0.3624288 -0.6721288 1.776679 -0.7967021 0.9621989 0.09908712 -0.08659898
[,92] [,93] [,94] [,95] [,96] [,97]
[1,] 0.005836285 -1.326891 -0.2320383 0.1701924 -0.4948253 -0.01444372
[2,] 0.005836285 -1.326891 -0.2320383 0.1701924 -0.4948253 -0.01444372
[,98] [,99] [,100]
[1,] 0.3898274 -1.958414 -0.3011834
[2,] 0.3898274 -1.958414 -0.3011834
>
>
> Max(tmp2)
[1] 2.65216
> Min(tmp2)
[1] -2.767798
> mean(tmp2)
[1] -0.02234083
> Sum(tmp2)
[1] -2.234083
> Var(tmp2)
[1] 1.088072
>
> rowMeans(tmp2)
[1] -0.8068171932 1.4138749286 -2.1426302475 -0.0796449706 -0.3376026836
[6] 0.4761939305 -0.0519683736 0.9382499114 -1.1715883197 -0.4406437828
[11] 0.6367616339 0.2712001091 -0.0362190141 -0.9097744323 0.6470634832
[16] 0.3686678433 0.1182203911 1.7070186862 1.7878158113 1.8957417074
[21] -0.3292339535 0.1607735542 0.0982330204 0.8920559210 0.4281745510
[26] -2.2691131243 0.1754309297 -1.6301384459 -0.2992324914 0.8343367706
[31] 0.6299099574 -1.4301708627 -0.5028810368 -1.4455481156 1.1082779306
[36] -1.3840040259 -0.2167906202 1.1521381716 -0.7111696635 -0.7484851638
[41] -1.1793001701 2.6521604634 -0.7162926008 0.7697279771 0.1260669418
[46] -0.2512912744 -0.8495267930 0.7733892966 0.5815111469 -1.3185015277
[51] -1.4651629795 1.9728473748 -0.3090594291 0.7364788959 -0.0708075632
[56] -0.2989555225 0.3435100026 -1.3461057799 -0.8200951545 -1.0265909890
[61] -1.7148119440 0.1745551337 -0.0003969439 2.5472696388 -0.3005480620
[66] -0.8971419199 -0.8857885050 1.5021132249 0.0023558235 -0.1140142476
[71] 0.3227449491 0.4702453693 1.1634368021 0.4295358354 -0.3777855496
[76] 1.4603435908 -0.3587521372 0.9333677243 -0.0152195302 1.1834372980
[81] -1.0352052766 0.3353714078 -1.1505824845 1.1427442348 0.3469858717
[86] -0.9205347165 -1.5832459372 0.3045651270 0.1004485902 0.0016831457
[91] 1.9070315880 -0.6255778097 -0.3888098293 -2.7677976939 -0.1196842350
[96] -0.2305735669 0.5721902503 1.1223393985 -1.0329397543 -0.8379230499
> rowSums(tmp2)
[1] -0.8068171932 1.4138749286 -2.1426302475 -0.0796449706 -0.3376026836
[6] 0.4761939305 -0.0519683736 0.9382499114 -1.1715883197 -0.4406437828
[11] 0.6367616339 0.2712001091 -0.0362190141 -0.9097744323 0.6470634832
[16] 0.3686678433 0.1182203911 1.7070186862 1.7878158113 1.8957417074
[21] -0.3292339535 0.1607735542 0.0982330204 0.8920559210 0.4281745510
[26] -2.2691131243 0.1754309297 -1.6301384459 -0.2992324914 0.8343367706
[31] 0.6299099574 -1.4301708627 -0.5028810368 -1.4455481156 1.1082779306
[36] -1.3840040259 -0.2167906202 1.1521381716 -0.7111696635 -0.7484851638
[41] -1.1793001701 2.6521604634 -0.7162926008 0.7697279771 0.1260669418
[46] -0.2512912744 -0.8495267930 0.7733892966 0.5815111469 -1.3185015277
[51] -1.4651629795 1.9728473748 -0.3090594291 0.7364788959 -0.0708075632
[56] -0.2989555225 0.3435100026 -1.3461057799 -0.8200951545 -1.0265909890
[61] -1.7148119440 0.1745551337 -0.0003969439 2.5472696388 -0.3005480620
[66] -0.8971419199 -0.8857885050 1.5021132249 0.0023558235 -0.1140142476
[71] 0.3227449491 0.4702453693 1.1634368021 0.4295358354 -0.3777855496
[76] 1.4603435908 -0.3587521372 0.9333677243 -0.0152195302 1.1834372980
[81] -1.0352052766 0.3353714078 -1.1505824845 1.1427442348 0.3469858717
[86] -0.9205347165 -1.5832459372 0.3045651270 0.1004485902 0.0016831457
[91] 1.9070315880 -0.6255778097 -0.3888098293 -2.7677976939 -0.1196842350
[96] -0.2305735669 0.5721902503 1.1223393985 -1.0329397543 -0.8379230499
> 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] -0.8068171932 1.4138749286 -2.1426302475 -0.0796449706 -0.3376026836
[6] 0.4761939305 -0.0519683736 0.9382499114 -1.1715883197 -0.4406437828
[11] 0.6367616339 0.2712001091 -0.0362190141 -0.9097744323 0.6470634832
[16] 0.3686678433 0.1182203911 1.7070186862 1.7878158113 1.8957417074
[21] -0.3292339535 0.1607735542 0.0982330204 0.8920559210 0.4281745510
[26] -2.2691131243 0.1754309297 -1.6301384459 -0.2992324914 0.8343367706
[31] 0.6299099574 -1.4301708627 -0.5028810368 -1.4455481156 1.1082779306
[36] -1.3840040259 -0.2167906202 1.1521381716 -0.7111696635 -0.7484851638
[41] -1.1793001701 2.6521604634 -0.7162926008 0.7697279771 0.1260669418
[46] -0.2512912744 -0.8495267930 0.7733892966 0.5815111469 -1.3185015277
[51] -1.4651629795 1.9728473748 -0.3090594291 0.7364788959 -0.0708075632
[56] -0.2989555225 0.3435100026 -1.3461057799 -0.8200951545 -1.0265909890
[61] -1.7148119440 0.1745551337 -0.0003969439 2.5472696388 -0.3005480620
[66] -0.8971419199 -0.8857885050 1.5021132249 0.0023558235 -0.1140142476
[71] 0.3227449491 0.4702453693 1.1634368021 0.4295358354 -0.3777855496
[76] 1.4603435908 -0.3587521372 0.9333677243 -0.0152195302 1.1834372980
[81] -1.0352052766 0.3353714078 -1.1505824845 1.1427442348 0.3469858717
[86] -0.9205347165 -1.5832459372 0.3045651270 0.1004485902 0.0016831457
[91] 1.9070315880 -0.6255778097 -0.3888098293 -2.7677976939 -0.1196842350
[96] -0.2305735669 0.5721902503 1.1223393985 -1.0329397543 -0.8379230499
> rowMin(tmp2)
[1] -0.8068171932 1.4138749286 -2.1426302475 -0.0796449706 -0.3376026836
[6] 0.4761939305 -0.0519683736 0.9382499114 -1.1715883197 -0.4406437828
[11] 0.6367616339 0.2712001091 -0.0362190141 -0.9097744323 0.6470634832
[16] 0.3686678433 0.1182203911 1.7070186862 1.7878158113 1.8957417074
[21] -0.3292339535 0.1607735542 0.0982330204 0.8920559210 0.4281745510
[26] -2.2691131243 0.1754309297 -1.6301384459 -0.2992324914 0.8343367706
[31] 0.6299099574 -1.4301708627 -0.5028810368 -1.4455481156 1.1082779306
[36] -1.3840040259 -0.2167906202 1.1521381716 -0.7111696635 -0.7484851638
[41] -1.1793001701 2.6521604634 -0.7162926008 0.7697279771 0.1260669418
[46] -0.2512912744 -0.8495267930 0.7733892966 0.5815111469 -1.3185015277
[51] -1.4651629795 1.9728473748 -0.3090594291 0.7364788959 -0.0708075632
[56] -0.2989555225 0.3435100026 -1.3461057799 -0.8200951545 -1.0265909890
[61] -1.7148119440 0.1745551337 -0.0003969439 2.5472696388 -0.3005480620
[66] -0.8971419199 -0.8857885050 1.5021132249 0.0023558235 -0.1140142476
[71] 0.3227449491 0.4702453693 1.1634368021 0.4295358354 -0.3777855496
[76] 1.4603435908 -0.3587521372 0.9333677243 -0.0152195302 1.1834372980
[81] -1.0352052766 0.3353714078 -1.1505824845 1.1427442348 0.3469858717
[86] -0.9205347165 -1.5832459372 0.3045651270 0.1004485902 0.0016831457
[91] 1.9070315880 -0.6255778097 -0.3888098293 -2.7677976939 -0.1196842350
[96] -0.2305735669 0.5721902503 1.1223393985 -1.0329397543 -0.8379230499
>
> colMeans(tmp2)
[1] -0.02234083
> colSums(tmp2)
[1] -2.234083
> colVars(tmp2)
[1] 1.088072
> colSd(tmp2)
[1] 1.043107
> colMax(tmp2)
[1] 2.65216
> colMin(tmp2)
[1] -2.767798
> colMedians(tmp2)
[1] -0.02571927
> colRanges(tmp2)
[,1]
[1,] -2.767798
[2,] 2.652160
>
> 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] 2.68217598 5.67940351 -1.35731282 4.15841980 -5.25935387 1.89855413
[7] -0.93441683 0.64690308 -0.04836779 1.62274084
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8756112
[2,] -0.2005846
[3,] 0.2394876
[4,] 0.3308068
[5,] 1.6948374
>
> rowApply(tmp,sum)
[1] 1.98815901 4.68569972 -1.61119984 1.95248838 -1.05669625 0.86542005
[7] 1.55513921 0.05402168 3.87889608 -3.22318202
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 2 10 8 8 7 4 4 6 6 8
[2,] 5 7 9 9 2 5 6 10 9 7
[3,] 7 5 4 4 9 2 9 8 1 2
[4,] 6 6 5 10 5 7 3 9 5 4
[5,] 1 3 7 1 10 1 5 1 3 9
[6,] 4 8 3 6 3 3 1 7 10 10
[7,] 9 9 6 2 4 6 10 5 4 1
[8,] 3 1 2 7 8 9 8 3 7 6
[9,] 10 2 1 5 6 10 2 2 2 3
[10,] 8 4 10 3 1 8 7 4 8 5
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.98880694 4.19415833 1.19658720 -0.89976243 0.15512970 -4.10630762
[7] -2.89529536 -0.12829078 1.69838855 1.89347493 0.04226794 -3.57715542
[13] -2.63608430 1.79017437 -3.06640273 -0.14333037 -3.13709263 -1.10474591
[19] 0.06769732 -1.66124137
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.24027000
[2,] -1.17252509
[3,] -0.09175181
[4,] 0.44286314
[5,] 1.07287682
>
> rowApply(tmp,sum)
[1] -3.1815608 -2.0864581 -0.5718173 -4.0590746 -3.4077268
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 4 18 3 12 16
[2,] 19 20 20 13 7
[3,] 18 19 8 10 4
[4,] 6 12 16 7 5
[5,] 11 14 15 8 10
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.24027000 1.5024476 1.3045302 -0.8053317 -0.2862131 -0.6643408
[2,] 1.07287682 1.3847513 1.1092756 0.2216030 0.6168580 -1.3360289
[3,] -1.17252509 1.6285847 -0.1464896 0.9522939 0.7477590 -1.2867053
[4,] -0.09175181 0.1944188 -0.3235178 -0.6656975 -0.5801493 0.4263756
[5,] 0.44286314 -0.5160440 -0.7472113 -0.6026302 -0.3431249 -1.2456083
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.4766957 -1.0044390 0.4339121 1.80651810 -0.1138106 -1.4091416
[2,] -0.5689023 0.8798776 0.6879970 -1.23573184 0.2282510 -1.6819557
[3,] -0.1458735 -0.1500020 -0.8988756 -0.02038735 1.0782398 -0.7626631
[4,] 1.3795964 0.3112004 -0.5072567 -0.14532454 -1.4349744 0.7852153
[5,] -2.0834202 -0.1649278 1.9826118 1.48840056 0.2845621 -0.5086103
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.52891431 1.2044139 -0.6408562 0.5733455 -1.4564267 -0.22613038
[2,] -1.52704891 -0.8441699 0.6404410 -0.3519254 -0.2266156 0.13533179
[3,] 1.04940527 0.1139585 -0.1380178 1.0627172 -1.6198135 -0.01947669
[4,] -1.57440577 1.7757827 -1.5908800 -2.0300126 0.7589265 -1.61143761
[5,] -0.05512058 -0.4598108 -1.3370898 0.6025448 -0.5931633 0.61696698
[,19] [,20]
[1,] 0.3656038 -0.5197618
[2,] -1.1612421 -0.1301006
[3,] -0.6976955 -0.1462507
[4,] 1.8729222 -1.0081045
[5,] -0.3118910 0.1429763
>
>
> 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 : 652 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 -1.460762 -1.476896 0.3802462 -0.3240463 -0.7958424 -0.8275098 -1.336995
col8 col9 col10 col11 col12 col13 col14
row1 0.09057665 0.7753943 -1.476623 -0.4256985 -0.6476172 0.1076501 -2.421747
col15 col16 col17 col18 col19 col20
row1 -0.3702797 -0.1168099 -1.58914 0.7583645 -0.4856991 -1.071794
> tmp[,"col10"]
col10
row1 -1.4766226
row2 -1.8823483
row3 -0.9799513
row4 -1.1539284
row5 -0.5173525
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -1.4607624 -1.476896 0.3802462 -0.3240463 -0.7958424 -0.8275098
row5 -0.2640685 1.570339 1.1395435 -1.3606166 -0.1676333 0.9785946
col7 col8 col9 col10 col11 col12
row1 -1.33699538 0.09057665 0.7753943 -1.4766226 -0.4256985 -0.6476172
row5 -0.01972641 -0.68876504 -0.3174249 -0.5173525 0.2816542 1.2766349
col13 col14 col15 col16 col17 col18
row1 0.10765014 -2.421747 -0.3702797 -0.1168099 -1.5891404 0.7583645
row5 0.09001935 1.261504 1.8035482 -0.4979352 0.6670286 0.4694830
col19 col20
row1 -0.48569913 -1.0717945
row5 -0.09973123 -0.6908758
> tmp[,c("col6","col20")]
col6 col20
row1 -0.8275098 -1.071794465
row2 -0.5851627 0.008203596
row3 -0.8106289 0.260266355
row4 -0.4629861 -0.426337814
row5 0.9785946 -0.690875792
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.8275098 -1.0717945
row5 0.9785946 -0.6908758
>
>
>
>
> 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 49.24111 50.35646 52.24938 50.00768 48.55999 105.1117 48.35147 52.07953
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.09613 49.28273 49.58853 51.57874 49.29553 49.77652 48.8424 50.3262
col17 col18 col19 col20
row1 49.70742 51.10651 49.97009 103.9118
> tmp[,"col10"]
col10
row1 49.28273
row2 32.36192
row3 29.87427
row4 31.18043
row5 51.20048
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.24111 50.35646 52.24938 50.00768 48.55999 105.1117 48.35147 52.07953
row5 48.66350 49.69895 50.39408 49.96032 48.93895 105.2389 50.16207 50.18755
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.09613 49.28273 49.58853 51.57874 49.29553 49.77652 48.8424 50.32620
row5 49.84200 51.20048 49.77907 50.93132 50.37259 50.30198 49.6628 49.83108
col17 col18 col19 col20
row1 49.70742 51.10651 49.97009 103.9118
row5 49.14349 49.30873 51.06472 105.5637
> tmp[,c("col6","col20")]
col6 col20
row1 105.11165 103.91178
row2 76.08463 74.96229
row3 74.72424 77.35133
row4 73.65900 75.20094
row5 105.23890 105.56372
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.1117 103.9118
row5 105.2389 105.5637
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.1117 103.9118
row5 105.2389 105.5637
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.5974567
[2,] 1.5106718
[3,] 0.3242778
[4,] -0.2263820
[5,] -0.3687251
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.9120234 2.2176187
[2,] -0.2393902 -1.1561688
[3,] 2.2966226 0.4259957
[4,] -2.6631684 -1.2559121
[5,] -0.2265576 -0.2869878
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.89159373 -1.3482843
[2,] 0.08078198 0.5967187
[3,] -1.16797541 1.2345369
[4,] -0.63230256 -0.9070577
[5,] 0.88476171 0.1473865
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.891594
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.89159373
[2,] 0.08078198
>
>
>
> 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 0.4302948 -0.5408165 0.003570728 -1.3884619 -0.1533346 -1.4980060
row1 0.6581741 1.1183572 -0.623494172 0.1939989 -0.1808487 0.9308425
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 2.047573 0.601294 -0.4880851 -1.513957 -0.5361378 -1.009753 0.2970130
row1 1.267467 1.327764 -0.1039080 1.248877 -1.1967814 1.134987 0.8530625
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.1863695 -1.9119390 -1.135769 0.3542027 0.02584538 0.102689
row1 0.4222111 0.3152329 0.937909 -0.8237284 -0.43870967 -1.296002
[,20]
row3 1.2278779
row1 -0.9060529
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.977096 -0.3178444 0.3161761 0.5170396 -0.8363049 -0.4872678 0.7037783
[,8] [,9] [,10]
row2 1.562712 -0.2206191 1.463346
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.6111689 -0.9577087 -0.6658198 -0.1187838 0.3615993 0.9961363 -0.171976
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.01265809 -0.2597145 0.5515991 -0.3824646 0.3202717 -0.1342487 2.83439
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.5180598 -0.2990513 -1.299753 -0.684235 0.501418 -0.8765175
>
>
> 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: 0x600002cd40c0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1135b164ea1d"
[2] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1135b84616a2"
[3] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1135b3177e9ec"
[4] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1135b379e9e53"
[5] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1135beac77ac"
[6] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1135b5ce4c4ba"
[7] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1135b2f2fbefb"
[8] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1135b67a368f0"
[9] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1135b193e99b8"
[10] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1135b5cde0bfa"
[11] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1135b75e479b7"
[12] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1135b6af319d8"
[13] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1135b7e25eac2"
[14] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1135b6b57a741"
[15] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1135b47a5d375"
>
>
> ### 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: 0x600002cf0960>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600002cf0960>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600002cf0960>
> rowMedians(tmp)
[1] -0.156637979 0.048770537 -0.235517917 0.312181001 -0.163708210
[6] -0.214708029 0.312077777 -0.231777782 -0.042212540 -0.052829938
[11] -0.528281043 -0.060938889 0.086965689 -0.309403808 0.074990843
[16] -0.321669898 0.302246485 -0.336631208 0.141615376 -0.249800565
[21] -0.326497169 0.484217715 0.026006689 -0.369762218 0.156305061
[26] -0.299604970 0.043942441 0.277812865 0.210435402 0.020519036
[31] -0.064492355 -0.497319409 0.393984410 0.003680932 1.036281909
[36] -0.445201243 0.284564232 -0.149540879 0.009857300 0.201882960
[41] 0.181268995 -0.061471494 0.641269080 0.350784531 -0.530221866
[46] 0.074367647 -0.247923121 -0.143117101 0.069639989 -0.372628512
[51] -0.136144100 0.357346000 0.561774601 -0.157161624 -0.095012571
[56] 0.109893710 0.143668946 -0.122005998 -0.228932646 -0.573121519
[61] 0.306870084 -0.506602707 -0.071233280 0.008752762 -0.388871458
[66] -0.247291050 0.245509165 -0.233645337 0.232742848 0.689417663
[71] -0.431431590 -0.264538686 -0.071873856 -0.573442431 -0.012563195
[76] -0.082587894 0.003721488 -0.131335541 -0.540328848 -0.018989554
[81] 0.159341704 -0.101353727 -0.083417161 -0.062566065 -0.026224747
[86] 0.047782577 -0.440470173 0.774914501 -0.430047056 -0.204557834
[91] -0.122869694 0.054133157 -0.578255196 -0.116768831 0.156209507
[96] 0.019043630 -0.116868945 0.090186705 0.185590663 0.308712843
[101] 0.305875194 0.640372608 0.123942679 0.237561619 -0.395508772
[106] 0.555263578 -0.199874716 -0.588325000 -0.747731149 0.180259825
[111] -0.074076336 -0.373060457 -0.296890692 -0.340497214 -0.023561742
[116] 0.184354175 0.136655763 0.051698848 -0.244759732 -0.329173141
[121] 0.113473435 0.188753851 0.387032785 -0.099012618 0.255803962
[126] 0.318010978 -0.117741084 -0.469441395 0.023484179 -0.235912684
[131] -0.003443330 0.125377486 0.245044088 -0.057601705 0.084437107
[136] 0.211310312 0.295961431 -0.106099981 -0.157241031 0.125717715
[141] -0.335679140 -0.747814917 0.239896609 0.090107772 0.263428717
[146] -0.276619683 0.070434373 0.203163889 0.367036126 0.143724474
[151] 0.094349205 -0.019506404 0.804464954 -0.184341734 -0.505396722
[156] -0.369643102 0.219887681 0.032026076 0.062457121 -0.136059706
[161] -0.635884509 0.205191229 0.242794891 0.196883401 0.046090923
[166] -0.302662541 0.051557159 -0.280145258 -0.397415541 -0.555593645
[171] 0.060251344 -0.392158806 0.365956575 -0.608704639 0.197949417
[176] 0.088347101 -0.385620142 0.057909994 0.110253378 0.170911465
[181] -0.166247360 -0.134300859 0.224444860 -0.375324257 0.309136203
[186] -0.051355763 -0.095962338 -0.758119402 -0.030814210 -0.240239059
[191] 0.171865436 0.198636856 0.101459170 0.117166676 -0.247865735
[196] -0.189931102 -0.358729590 0.746482268 -0.452529870 -0.509561183
[201] -0.400473983 -0.259371053 -0.692732399 -0.049624733 -0.249773206
[206] 0.330742667 0.454644632 -0.123433588 0.031794503 0.035250084
[211] 0.324974783 0.379767322 0.643337613 -0.158801984 0.068152600
[216] 0.261309798 0.195297645 -0.099986452 -0.111986979 -0.105365334
[221] 0.041490934 0.159821526 0.237685000 0.146716435 -0.654025845
[226] 0.018339191 -0.214858728 0.008253555 0.155559356 0.036727769
>
> proc.time()
user system elapsed
2.170 8.945 11.731
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: 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: 0x60000390c000>
> .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: 0x60000390c000>
> .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: 0x60000390c000>
> .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: 0x60000390c000>
> 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: 0x600003918840>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003918840>
> .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: 0x600003918840>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003918840>
> .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: 0x600003918840>
> 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: 0x600003918a20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003918a20>
> .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: 0x600003918a20>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003918a20>
> .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: 0x600003918a20>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600003918a20>
> .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: 0x600003918a20>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600003918a20>
> .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: 0x600003918a20>
> 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: 0x600003918c00>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600003918c00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003918c00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003918c00>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1137c1e7fab57" "BufferedMatrixFile1137c4fc9ec65"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1137c1e7fab57" "BufferedMatrixFile1137c4fc9ec65"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003918ea0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003918ea0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003918ea0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003918ea0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600003918ea0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600003918ea0>
> .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: 0x600003919080>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003919080>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003919080>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600003919080>
> 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: 0x600003919260>
> .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: 0x600003919260>
> rm(P)
>
> proc.time()
user system elapsed
0.319 0.115 0.422
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: 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.
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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
0.347 0.085 0.427