Ben Bolstad
| Snapshot Date: 2025-03-06 13:00 -0500 (Thu, 06 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 -0500 (Tue, 29 Oct 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2025-03-10 12:10 -0400 (Mon, 10 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" | 4670 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.3 (2025-02-28 ucrt) -- "Trophy Case" | 4355 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4446 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4439 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4306 |
| 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: 2025-03-07 13:52:32 -0500 (Fri, 07 Mar 2025) |
| EndedAt: 2025-03-07 13:53:11 -0500 (Fri, 07 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
0.313 0.103 0.419
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 7 13:52:51 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Mar 7 13:52:51 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: 0x600003bfc000>
>
>
>
> 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 7 13:52:54 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 7 13:52:55 2025"
>
> ColMode(tmp2)
<pointer: 0x600003bfc000>
>
>
>
> ### 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,] 99.782034 -0.36391669 -0.04963353 -0.009025274
[2,] -2.877506 -0.07099964 -0.44164054 0.199101014
[3,] -1.645639 0.83126202 -0.30834029 0.801676772
[4,] -1.755866 -2.69197157 1.92797491 -0.699882602
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.782034 0.36391669 0.04963353 0.009025274
[2,] 2.877506 0.07099964 0.44164054 0.199101014
[3,] 1.645639 0.83126202 0.30834029 0.801676772
[4,] 1.755866 2.69197157 1.92797491 0.699882602
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.989096 0.6032551 0.2227858 0.09500144
[2,] 1.696321 0.2664576 0.6645604 0.44620737
[3,] 1.282825 0.9117357 0.5552840 0.89536404
[4,] 1.325091 1.6407229 1.3885154 0.83658987
>
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.67299 31.39647 27.27749 25.95904
[2,] 44.84072 27.73558 32.08724 29.66117
[3,] 39.47388 34.94862 30.86118 34.75532
[4,] 40.00677 44.09920 40.81313 34.06578
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600003bf41e0>
> exp(tmp5)
<pointer: 0x600003bf41e0>
> log(tmp5,2)
<pointer: 0x600003bf41e0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.6274
> Min(tmp5)
[1] 53.19819
> mean(tmp5)
[1] 71.67942
> Sum(tmp5)
[1] 14335.88
> Var(tmp5)
[1] 869.8314
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 87.35271 67.71607 70.15195 74.60007 69.13031 69.40484 69.39551 68.48423
[9] 71.26231 69.29619
> rowSums(tmp5)
[1] 1747.054 1354.321 1403.039 1492.001 1382.606 1388.097 1387.910 1369.685
[9] 1425.246 1385.924
> rowVars(tmp5)
[1] 8078.65244 112.08766 60.46913 83.38736 40.79821 92.00227
[7] 89.99048 76.21498 74.56318 80.93781
> rowSd(tmp5)
[1] 89.881324 10.587146 7.776190 9.131668 6.387347 9.591782 9.486331
[8] 8.730119 8.634997 8.996544
> rowMax(tmp5)
[1] 467.62740 93.33008 85.19963 91.78671 79.64721 95.66220 92.80121
[8] 85.02949 89.61488 84.89046
> rowMin(tmp5)
[1] 53.19819 55.70176 57.07984 57.64677 56.44417 58.03660 58.12973 54.97060
[9] 57.59207 57.06774
>
> colMeans(tmp5)
[1] 115.12885 68.85717 67.46150 68.01698 72.54227 70.06043 69.39277
[8] 67.82196 68.83806 68.26936 68.93583 65.73698 68.22167 72.72528
[15] 68.05718 70.92688 69.41635 75.05743 65.11196 73.00947
> colSums(tmp5)
[1] 1151.2885 688.5717 674.6150 680.1698 725.4227 700.6043 693.9277
[8] 678.2196 688.3806 682.6936 689.3583 657.3698 682.2167 727.2528
[15] 680.5718 709.2688 694.1635 750.5743 651.1196 730.0947
> colVars(tmp5)
[1] 15406.55096 108.09082 68.33570 62.16646 131.02915 98.67184
[7] 78.14837 77.61385 37.74137 37.48605 141.03192 79.94869
[13] 41.85364 50.83546 74.44726 109.03333 135.67087 37.71237
[19] 31.36513 90.53008
> colSd(tmp5)
[1] 124.123128 10.396674 8.266541 7.884571 11.446797 9.933370
[7] 8.840157 8.809872 6.143401 6.122585 11.875686 8.941403
[13] 6.469439 7.129899 8.628283 10.441903 11.647784 6.141040
[19] 5.600458 9.514730
> colMax(tmp5)
[1] 467.62740 91.78671 84.94718 77.07558 92.80121 89.50157 79.99714
[8] 84.89046 78.33932 79.86715 87.63903 85.56128 85.02949 84.36290
[15] 87.69832 89.61488 95.66220 84.66770 77.33516 85.19963
> colMin(tmp5)
[1] 67.42057 54.97060 56.77453 54.03034 58.19994 57.89910 58.19102 56.44417
[9] 61.94360 58.03660 57.06774 53.19819 59.73397 61.97697 56.35296 56.64503
[17] 55.70176 68.41800 57.07984 60.83159
>
>
> ### 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] 87.35271 67.71607 70.15195 74.60007 69.13031 69.40484 69.39551 NA
[9] 71.26231 69.29619
> rowSums(tmp5)
[1] 1747.054 1354.321 1403.039 1492.001 1382.606 1388.097 1387.910 NA
[9] 1425.246 1385.924
> rowVars(tmp5)
[1] 8078.65244 112.08766 60.46913 83.38736 40.79821 92.00227
[7] 89.99048 72.99000 74.56318 80.93781
> rowSd(tmp5)
[1] 89.881324 10.587146 7.776190 9.131668 6.387347 9.591782 9.486331
[8] 8.543419 8.634997 8.996544
> rowMax(tmp5)
[1] 467.62740 93.33008 85.19963 91.78671 79.64721 95.66220 92.80121
[8] NA 89.61488 84.89046
> rowMin(tmp5)
[1] 53.19819 55.70176 57.07984 57.64677 56.44417 58.03660 58.12973 NA
[9] 57.59207 57.06774
>
> colMeans(tmp5)
[1] 115.12885 68.85717 67.46150 68.01698 72.54227 70.06043 69.39277
[8] 67.82196 68.83806 68.26936 NA 65.73698 68.22167 72.72528
[15] 68.05718 70.92688 69.41635 75.05743 65.11196 73.00947
> colSums(tmp5)
[1] 1151.2885 688.5717 674.6150 680.1698 725.4227 700.6043 693.9277
[8] 678.2196 688.3806 682.6936 NA 657.3698 682.2167 727.2528
[15] 680.5718 709.2688 694.1635 750.5743 651.1196 730.0947
> colVars(tmp5)
[1] 15406.55096 108.09082 68.33570 62.16646 131.02915 98.67184
[7] 78.14837 77.61385 37.74137 37.48605 NA 79.94869
[13] 41.85364 50.83546 74.44726 109.03333 135.67087 37.71237
[19] 31.36513 90.53008
> colSd(tmp5)
[1] 124.123128 10.396674 8.266541 7.884571 11.446797 9.933370
[7] 8.840157 8.809872 6.143401 6.122585 NA 8.941403
[13] 6.469439 7.129899 8.628283 10.441903 11.647784 6.141040
[19] 5.600458 9.514730
> colMax(tmp5)
[1] 467.62740 91.78671 84.94718 77.07558 92.80121 89.50157 79.99714
[8] 84.89046 78.33932 79.86715 NA 85.56128 85.02949 84.36290
[15] 87.69832 89.61488 95.66220 84.66770 77.33516 85.19963
> colMin(tmp5)
[1] 67.42057 54.97060 56.77453 54.03034 58.19994 57.89910 58.19102 56.44417
[9] 61.94360 58.03660 NA 53.19819 59.73397 61.97697 56.35296 56.64503
[17] 55.70176 68.41800 57.07984 60.83159
>
> Max(tmp5,na.rm=TRUE)
[1] 467.6274
> Min(tmp5,na.rm=TRUE)
[1] 53.19819
> mean(tmp5,na.rm=TRUE)
[1] 71.75223
> Sum(tmp5,na.rm=TRUE)
[1] 14278.69
> Var(tmp5,na.rm=TRUE)
[1] 873.1589
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.35271 67.71607 70.15195 74.60007 69.13031 69.40484 69.39551 69.07864
[9] 71.26231 69.29619
> rowSums(tmp5,na.rm=TRUE)
[1] 1747.054 1354.321 1403.039 1492.001 1382.606 1388.097 1387.910 1312.494
[9] 1425.246 1385.924
> rowVars(tmp5,na.rm=TRUE)
[1] 8078.65244 112.08766 60.46913 83.38736 40.79821 92.00227
[7] 89.99048 72.99000 74.56318 80.93781
> rowSd(tmp5,na.rm=TRUE)
[1] 89.881324 10.587146 7.776190 9.131668 6.387347 9.591782 9.486331
[8] 8.543419 8.634997 8.996544
> rowMax(tmp5,na.rm=TRUE)
[1] 467.62740 93.33008 85.19963 91.78671 79.64721 95.66220 92.80121
[8] 85.02949 89.61488 84.89046
> rowMin(tmp5,na.rm=TRUE)
[1] 53.19819 55.70176 57.07984 57.64677 56.44417 58.03660 58.12973 54.97060
[9] 57.59207 57.06774
>
> colMeans(tmp5,na.rm=TRUE)
[1] 115.12885 68.85717 67.46150 68.01698 72.54227 70.06043 69.39277
[8] 67.82196 68.83806 68.26936 70.24088 65.73698 68.22167 72.72528
[15] 68.05718 70.92688 69.41635 75.05743 65.11196 73.00947
> colSums(tmp5,na.rm=TRUE)
[1] 1151.2885 688.5717 674.6150 680.1698 725.4227 700.6043 693.9277
[8] 678.2196 688.3806 682.6936 632.1679 657.3698 682.2167 727.2528
[15] 680.5718 709.2688 694.1635 750.5743 651.1196 730.0947
> colVars(tmp5,na.rm=TRUE)
[1] 15406.55096 108.09082 68.33570 62.16646 131.02915 98.67184
[7] 78.14837 77.61385 37.74137 37.48605 139.50038 79.94869
[13] 41.85364 50.83546 74.44726 109.03333 135.67087 37.71237
[19] 31.36513 90.53008
> colSd(tmp5,na.rm=TRUE)
[1] 124.123128 10.396674 8.266541 7.884571 11.446797 9.933370
[7] 8.840157 8.809872 6.143401 6.122585 11.811028 8.941403
[13] 6.469439 7.129899 8.628283 10.441903 11.647784 6.141040
[19] 5.600458 9.514730
> colMax(tmp5,na.rm=TRUE)
[1] 467.62740 91.78671 84.94718 77.07558 92.80121 89.50157 79.99714
[8] 84.89046 78.33932 79.86715 87.63903 85.56128 85.02949 84.36290
[15] 87.69832 89.61488 95.66220 84.66770 77.33516 85.19963
> colMin(tmp5,na.rm=TRUE)
[1] 67.42057 54.97060 56.77453 54.03034 58.19994 57.89910 58.19102 56.44417
[9] 61.94360 58.03660 57.06774 53.19819 59.73397 61.97697 56.35296 56.64503
[17] 55.70176 68.41800 57.07984 60.83159
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.35271 67.71607 70.15195 74.60007 69.13031 69.40484 69.39551 NaN
[9] 71.26231 69.29619
> rowSums(tmp5,na.rm=TRUE)
[1] 1747.054 1354.321 1403.039 1492.001 1382.606 1388.097 1387.910 0.000
[9] 1425.246 1385.924
> rowVars(tmp5,na.rm=TRUE)
[1] 8078.65244 112.08766 60.46913 83.38736 40.79821 92.00227
[7] 89.99048 NA 74.56318 80.93781
> rowSd(tmp5,na.rm=TRUE)
[1] 89.881324 10.587146 7.776190 9.131668 6.387347 9.591782 9.486331
[8] NA 8.634997 8.996544
> rowMax(tmp5,na.rm=TRUE)
[1] 467.62740 93.33008 85.19963 91.78671 79.64721 95.66220 92.80121
[8] NA 89.61488 84.89046
> rowMin(tmp5,na.rm=TRUE)
[1] 53.19819 55.70176 57.07984 57.64677 56.44417 58.03660 58.12973 NA
[9] 57.59207 57.06774
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 119.44973 70.40013 67.99708 67.97515 72.32118 70.15771 69.31846
[8] 68.35485 68.31445 66.98072 NaN 65.75515 66.35414 73.59316
[15] 67.37358 72.51376 70.77092 75.13703 65.49795 72.18279
> colSums(tmp5,na.rm=TRUE)
[1] 1075.0475 633.6011 611.9737 611.7764 650.8906 631.4194 623.8661
[8] 615.1936 614.8301 602.8265 0.0000 591.7963 597.1872 662.3384
[15] 606.3622 652.6238 636.9383 676.2333 589.4815 649.6452
> colVars(tmp5,na.rm=TRUE)
[1] 17122.332846 94.819285 73.650735 69.917584 146.857911
[6] 110.899377 87.854794 84.120909 39.374715 23.490053
[11] NA 89.938567 7.848869 48.716165 78.495978
[16] 94.333124 131.987386 42.355128 33.609667 94.158242
> colSd(tmp5,na.rm=TRUE)
[1] 130.852332 9.737519 8.582001 8.361674 12.118495 10.530877
[7] 9.373089 9.171745 6.274927 4.846654 NA 9.483595
[13] 2.801583 6.979697 8.859796 9.712524 11.488576 6.508082
[19] 5.797385 9.703517
> colMax(tmp5,na.rm=TRUE)
[1] 467.62740 91.78671 84.94718 77.07558 92.80121 89.50157 79.99714
[8] 84.89046 78.33932 71.97236 -Inf 85.56128 69.64137 84.36290
[15] 87.69832 89.61488 95.66220 84.66770 77.33516 85.19963
> colMin(tmp5,na.rm=TRUE)
[1] 67.42057 57.72797 56.77453 54.03034 58.19994 57.89910 58.19102 56.44417
[9] 61.94360 58.03660 Inf 53.19819 59.73397 61.97697 56.35296 58.86851
[17] 55.70176 68.41800 57.07984 60.83159
>
>
>
>
> 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] 185.4140 335.7151 153.5169 140.0244 317.3796 145.9490 183.5729 186.5787
[9] 249.7331 217.1147
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 185.4140 335.7151 153.5169 140.0244 317.3796 145.9490 183.5729 186.5787
[9] 249.7331 217.1147
>
>
>
> 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] -5.684342e-14 -1.278977e-13 -1.421085e-13 0.000000e+00 0.000000e+00
[6] 0.000000e+00 0.000000e+00 3.410605e-13 -2.842171e-14 -9.947598e-14
[11] -2.842171e-14 8.526513e-14 1.136868e-13 2.842171e-14 5.684342e-14
[16] 1.421085e-13 -5.684342e-14 0.000000e+00 2.842171e-13 5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
9 1
5 2
4 12
2 4
6 2
3 11
7 1
6 2
8 16
9 16
9 12
3 18
5 1
2 16
6 2
6 14
5 16
3 11
4 7
8 2
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] 1.956548
> Min(tmp)
[1] -2.271126
> mean(tmp)
[1] -0.07990599
> Sum(tmp)
[1] -7.990599
> Var(tmp)
[1] 0.7839545
>
> rowMeans(tmp)
[1] -0.07990599
> rowSums(tmp)
[1] -7.990599
> rowVars(tmp)
[1] 0.7839545
> rowSd(tmp)
[1] 0.885412
> rowMax(tmp)
[1] 1.956548
> rowMin(tmp)
[1] -2.271126
>
> colMeans(tmp)
[1] 0.48785355 -0.82982182 -0.56320695 -0.35572716 0.07448376 -0.32407261
[7] -2.16348160 0.11333586 -1.51253959 -0.49704971 0.06453591 -1.80531877
[13] 0.48746592 0.06904901 -0.59235711 -0.53872968 -0.34846808 -0.63891719
[19] -0.50885075 0.30810152 -0.13944326 -0.48039829 -0.60740136 0.58369713
[25] 1.07238496 -0.61928322 0.76001790 0.43197322 0.41133905 -1.69084137
[31] -1.21614181 -0.44419306 -0.80475063 -0.42317199 -0.67163764 1.23103369
[37] 1.22774544 0.43056796 -0.57371805 -0.93398006 -0.28349872 0.55318366
[43] -0.30899304 1.14808861 -1.63346577 0.71860557 0.42860066 1.10416632
[49] -0.26494663 -0.59761736 0.37744293 1.26018996 0.12317625 -0.07982237
[55] -0.08936998 -0.92703484 -2.01558777 -1.38314515 0.66336398 -0.08744307
[61] 0.59476331 -0.39416880 0.33007633 0.51949929 -0.14465354 -0.32308508
[67] 1.95654833 0.51622467 0.74987081 0.55496840 -2.27112565 0.83330448
[73] 1.12188011 -0.15467270 0.22364074 -0.47099267 0.31056868 -0.34558692
[79] 0.92965380 1.63252509 -0.60698476 0.28300119 -0.71794830 -1.93326140
[85] -0.31594334 1.31289378 0.91384405 -1.75251424 0.49349981 0.67433778
[91] -0.38360580 0.83547931 -0.37352371 0.30474202 -1.03389921 1.76844332
[97] -0.15740750 0.10506465 -1.13458543 0.38255421
> colSums(tmp)
[1] 0.48785355 -0.82982182 -0.56320695 -0.35572716 0.07448376 -0.32407261
[7] -2.16348160 0.11333586 -1.51253959 -0.49704971 0.06453591 -1.80531877
[13] 0.48746592 0.06904901 -0.59235711 -0.53872968 -0.34846808 -0.63891719
[19] -0.50885075 0.30810152 -0.13944326 -0.48039829 -0.60740136 0.58369713
[25] 1.07238496 -0.61928322 0.76001790 0.43197322 0.41133905 -1.69084137
[31] -1.21614181 -0.44419306 -0.80475063 -0.42317199 -0.67163764 1.23103369
[37] 1.22774544 0.43056796 -0.57371805 -0.93398006 -0.28349872 0.55318366
[43] -0.30899304 1.14808861 -1.63346577 0.71860557 0.42860066 1.10416632
[49] -0.26494663 -0.59761736 0.37744293 1.26018996 0.12317625 -0.07982237
[55] -0.08936998 -0.92703484 -2.01558777 -1.38314515 0.66336398 -0.08744307
[61] 0.59476331 -0.39416880 0.33007633 0.51949929 -0.14465354 -0.32308508
[67] 1.95654833 0.51622467 0.74987081 0.55496840 -2.27112565 0.83330448
[73] 1.12188011 -0.15467270 0.22364074 -0.47099267 0.31056868 -0.34558692
[79] 0.92965380 1.63252509 -0.60698476 0.28300119 -0.71794830 -1.93326140
[85] -0.31594334 1.31289378 0.91384405 -1.75251424 0.49349981 0.67433778
[91] -0.38360580 0.83547931 -0.37352371 0.30474202 -1.03389921 1.76844332
[97] -0.15740750 0.10506465 -1.13458543 0.38255421
> 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] 0.48785355 -0.82982182 -0.56320695 -0.35572716 0.07448376 -0.32407261
[7] -2.16348160 0.11333586 -1.51253959 -0.49704971 0.06453591 -1.80531877
[13] 0.48746592 0.06904901 -0.59235711 -0.53872968 -0.34846808 -0.63891719
[19] -0.50885075 0.30810152 -0.13944326 -0.48039829 -0.60740136 0.58369713
[25] 1.07238496 -0.61928322 0.76001790 0.43197322 0.41133905 -1.69084137
[31] -1.21614181 -0.44419306 -0.80475063 -0.42317199 -0.67163764 1.23103369
[37] 1.22774544 0.43056796 -0.57371805 -0.93398006 -0.28349872 0.55318366
[43] -0.30899304 1.14808861 -1.63346577 0.71860557 0.42860066 1.10416632
[49] -0.26494663 -0.59761736 0.37744293 1.26018996 0.12317625 -0.07982237
[55] -0.08936998 -0.92703484 -2.01558777 -1.38314515 0.66336398 -0.08744307
[61] 0.59476331 -0.39416880 0.33007633 0.51949929 -0.14465354 -0.32308508
[67] 1.95654833 0.51622467 0.74987081 0.55496840 -2.27112565 0.83330448
[73] 1.12188011 -0.15467270 0.22364074 -0.47099267 0.31056868 -0.34558692
[79] 0.92965380 1.63252509 -0.60698476 0.28300119 -0.71794830 -1.93326140
[85] -0.31594334 1.31289378 0.91384405 -1.75251424 0.49349981 0.67433778
[91] -0.38360580 0.83547931 -0.37352371 0.30474202 -1.03389921 1.76844332
[97] -0.15740750 0.10506465 -1.13458543 0.38255421
> colMin(tmp)
[1] 0.48785355 -0.82982182 -0.56320695 -0.35572716 0.07448376 -0.32407261
[7] -2.16348160 0.11333586 -1.51253959 -0.49704971 0.06453591 -1.80531877
[13] 0.48746592 0.06904901 -0.59235711 -0.53872968 -0.34846808 -0.63891719
[19] -0.50885075 0.30810152 -0.13944326 -0.48039829 -0.60740136 0.58369713
[25] 1.07238496 -0.61928322 0.76001790 0.43197322 0.41133905 -1.69084137
[31] -1.21614181 -0.44419306 -0.80475063 -0.42317199 -0.67163764 1.23103369
[37] 1.22774544 0.43056796 -0.57371805 -0.93398006 -0.28349872 0.55318366
[43] -0.30899304 1.14808861 -1.63346577 0.71860557 0.42860066 1.10416632
[49] -0.26494663 -0.59761736 0.37744293 1.26018996 0.12317625 -0.07982237
[55] -0.08936998 -0.92703484 -2.01558777 -1.38314515 0.66336398 -0.08744307
[61] 0.59476331 -0.39416880 0.33007633 0.51949929 -0.14465354 -0.32308508
[67] 1.95654833 0.51622467 0.74987081 0.55496840 -2.27112565 0.83330448
[73] 1.12188011 -0.15467270 0.22364074 -0.47099267 0.31056868 -0.34558692
[79] 0.92965380 1.63252509 -0.60698476 0.28300119 -0.71794830 -1.93326140
[85] -0.31594334 1.31289378 0.91384405 -1.75251424 0.49349981 0.67433778
[91] -0.38360580 0.83547931 -0.37352371 0.30474202 -1.03389921 1.76844332
[97] -0.15740750 0.10506465 -1.13458543 0.38255421
> colMedians(tmp)
[1] 0.48785355 -0.82982182 -0.56320695 -0.35572716 0.07448376 -0.32407261
[7] -2.16348160 0.11333586 -1.51253959 -0.49704971 0.06453591 -1.80531877
[13] 0.48746592 0.06904901 -0.59235711 -0.53872968 -0.34846808 -0.63891719
[19] -0.50885075 0.30810152 -0.13944326 -0.48039829 -0.60740136 0.58369713
[25] 1.07238496 -0.61928322 0.76001790 0.43197322 0.41133905 -1.69084137
[31] -1.21614181 -0.44419306 -0.80475063 -0.42317199 -0.67163764 1.23103369
[37] 1.22774544 0.43056796 -0.57371805 -0.93398006 -0.28349872 0.55318366
[43] -0.30899304 1.14808861 -1.63346577 0.71860557 0.42860066 1.10416632
[49] -0.26494663 -0.59761736 0.37744293 1.26018996 0.12317625 -0.07982237
[55] -0.08936998 -0.92703484 -2.01558777 -1.38314515 0.66336398 -0.08744307
[61] 0.59476331 -0.39416880 0.33007633 0.51949929 -0.14465354 -0.32308508
[67] 1.95654833 0.51622467 0.74987081 0.55496840 -2.27112565 0.83330448
[73] 1.12188011 -0.15467270 0.22364074 -0.47099267 0.31056868 -0.34558692
[79] 0.92965380 1.63252509 -0.60698476 0.28300119 -0.71794830 -1.93326140
[85] -0.31594334 1.31289378 0.91384405 -1.75251424 0.49349981 0.67433778
[91] -0.38360580 0.83547931 -0.37352371 0.30474202 -1.03389921 1.76844332
[97] -0.15740750 0.10506465 -1.13458543 0.38255421
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.4878536 -0.8298218 -0.5632069 -0.3557272 0.07448376 -0.3240726 -2.163482
[2,] 0.4878536 -0.8298218 -0.5632069 -0.3557272 0.07448376 -0.3240726 -2.163482
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.1133359 -1.51254 -0.4970497 0.06453591 -1.805319 0.4874659 0.06904901
[2,] 0.1133359 -1.51254 -0.4970497 0.06453591 -1.805319 0.4874659 0.06904901
[,15] [,16] [,17] [,18] [,19] [,20]
[1,] -0.5923571 -0.5387297 -0.3484681 -0.6389172 -0.5088508 0.3081015
[2,] -0.5923571 -0.5387297 -0.3484681 -0.6389172 -0.5088508 0.3081015
[,21] [,22] [,23] [,24] [,25] [,26] [,27]
[1,] -0.1394433 -0.4803983 -0.6074014 0.5836971 1.072385 -0.6192832 0.7600179
[2,] -0.1394433 -0.4803983 -0.6074014 0.5836971 1.072385 -0.6192832 0.7600179
[,28] [,29] [,30] [,31] [,32] [,33] [,34]
[1,] 0.4319732 0.411339 -1.690841 -1.216142 -0.4441931 -0.8047506 -0.423172
[2,] 0.4319732 0.411339 -1.690841 -1.216142 -0.4441931 -0.8047506 -0.423172
[,35] [,36] [,37] [,38] [,39] [,40] [,41]
[1,] -0.6716376 1.231034 1.227745 0.430568 -0.573718 -0.9339801 -0.2834987
[2,] -0.6716376 1.231034 1.227745 0.430568 -0.573718 -0.9339801 -0.2834987
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] 0.5531837 -0.308993 1.148089 -1.633466 0.7186056 0.4286007 1.104166
[2,] 0.5531837 -0.308993 1.148089 -1.633466 0.7186056 0.4286007 1.104166
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.2649466 -0.5976174 0.3774429 1.26019 0.1231762 -0.07982237 -0.08936998
[2,] -0.2649466 -0.5976174 0.3774429 1.26019 0.1231762 -0.07982237 -0.08936998
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.9270348 -2.015588 -1.383145 0.663364 -0.08744307 0.5947633 -0.3941688
[2,] -0.9270348 -2.015588 -1.383145 0.663364 -0.08744307 0.5947633 -0.3941688
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 0.3300763 0.5194993 -0.1446535 -0.3230851 1.956548 0.5162247 0.7498708
[2,] 0.3300763 0.5194993 -0.1446535 -0.3230851 1.956548 0.5162247 0.7498708
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 0.5549684 -2.271126 0.8333045 1.12188 -0.1546727 0.2236407 -0.4709927
[2,] 0.5549684 -2.271126 0.8333045 1.12188 -0.1546727 0.2236407 -0.4709927
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] 0.3105687 -0.3455869 0.9296538 1.632525 -0.6069848 0.2830012 -0.7179483
[2,] 0.3105687 -0.3455869 0.9296538 1.632525 -0.6069848 0.2830012 -0.7179483
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -1.933261 -0.3159433 1.312894 0.9138441 -1.752514 0.4934998 0.6743378
[2,] -1.933261 -0.3159433 1.312894 0.9138441 -1.752514 0.4934998 0.6743378
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -0.3836058 0.8354793 -0.3735237 0.304742 -1.033899 1.768443 -0.1574075
[2,] -0.3836058 0.8354793 -0.3735237 0.304742 -1.033899 1.768443 -0.1574075
[,98] [,99] [,100]
[1,] 0.1050647 -1.134585 0.3825542
[2,] 0.1050647 -1.134585 0.3825542
>
>
> Max(tmp2)
[1] 2.221749
> Min(tmp2)
[1] -2.671618
> mean(tmp2)
[1] 0.03843553
> Sum(tmp2)
[1] 3.843553
> Var(tmp2)
[1] 1.119726
>
> rowMeans(tmp2)
[1] -0.12395132 0.84043054 0.25688418 1.52989179 1.64407567 -0.88608244
[7] -1.70247630 -0.39817299 -0.27472667 -0.68578883 -0.75817527 0.92113078
[13] 1.10912270 0.06344602 0.29102489 0.76555649 0.31775224 -1.18227360
[19] -0.77912914 -0.55886825 -2.04104476 -2.41290973 -0.54272936 0.53535542
[25] -0.57890001 -0.90813517 -1.13263266 1.27536001 -0.21294817 0.62210622
[31] -1.74755777 0.82026227 1.76285362 0.23952044 0.31620240 0.76376573
[37] 1.08187708 0.84822747 -0.27041641 0.01502170 -1.50591622 1.47571132
[43] 0.47100088 1.64268668 -0.46076550 -1.99776053 -0.23745723 -0.47641500
[49] -0.48710754 0.01030445 0.90100062 0.85336575 0.27697497 0.53959075
[55] 0.23023423 -0.90390230 0.90847382 -0.22890795 1.07447100 1.27845664
[61] -0.72762005 -0.74823892 -0.34282169 0.55641499 0.24079945 -1.67708012
[67] -0.98106145 2.17547320 -0.17337666 0.14023048 -0.35971024 0.70565113
[73] 1.17369796 -0.85902547 -0.80867301 -0.82667394 -1.56534458 -0.08637821
[79] 0.71693040 0.75365376 -2.67161815 2.22174891 1.78385352 -0.51231724
[85] 1.10778224 0.84624323 -0.08352751 1.51240133 -0.26786545 1.49515582
[91] 1.56080915 -0.52639119 -0.18952268 -0.17398087 -1.66238567 -0.19484177
[97] 0.55948655 -1.10091876 1.86586603 -1.22025877
> rowSums(tmp2)
[1] -0.12395132 0.84043054 0.25688418 1.52989179 1.64407567 -0.88608244
[7] -1.70247630 -0.39817299 -0.27472667 -0.68578883 -0.75817527 0.92113078
[13] 1.10912270 0.06344602 0.29102489 0.76555649 0.31775224 -1.18227360
[19] -0.77912914 -0.55886825 -2.04104476 -2.41290973 -0.54272936 0.53535542
[25] -0.57890001 -0.90813517 -1.13263266 1.27536001 -0.21294817 0.62210622
[31] -1.74755777 0.82026227 1.76285362 0.23952044 0.31620240 0.76376573
[37] 1.08187708 0.84822747 -0.27041641 0.01502170 -1.50591622 1.47571132
[43] 0.47100088 1.64268668 -0.46076550 -1.99776053 -0.23745723 -0.47641500
[49] -0.48710754 0.01030445 0.90100062 0.85336575 0.27697497 0.53959075
[55] 0.23023423 -0.90390230 0.90847382 -0.22890795 1.07447100 1.27845664
[61] -0.72762005 -0.74823892 -0.34282169 0.55641499 0.24079945 -1.67708012
[67] -0.98106145 2.17547320 -0.17337666 0.14023048 -0.35971024 0.70565113
[73] 1.17369796 -0.85902547 -0.80867301 -0.82667394 -1.56534458 -0.08637821
[79] 0.71693040 0.75365376 -2.67161815 2.22174891 1.78385352 -0.51231724
[85] 1.10778224 0.84624323 -0.08352751 1.51240133 -0.26786545 1.49515582
[91] 1.56080915 -0.52639119 -0.18952268 -0.17398087 -1.66238567 -0.19484177
[97] 0.55948655 -1.10091876 1.86586603 -1.22025877
> 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] -0.12395132 0.84043054 0.25688418 1.52989179 1.64407567 -0.88608244
[7] -1.70247630 -0.39817299 -0.27472667 -0.68578883 -0.75817527 0.92113078
[13] 1.10912270 0.06344602 0.29102489 0.76555649 0.31775224 -1.18227360
[19] -0.77912914 -0.55886825 -2.04104476 -2.41290973 -0.54272936 0.53535542
[25] -0.57890001 -0.90813517 -1.13263266 1.27536001 -0.21294817 0.62210622
[31] -1.74755777 0.82026227 1.76285362 0.23952044 0.31620240 0.76376573
[37] 1.08187708 0.84822747 -0.27041641 0.01502170 -1.50591622 1.47571132
[43] 0.47100088 1.64268668 -0.46076550 -1.99776053 -0.23745723 -0.47641500
[49] -0.48710754 0.01030445 0.90100062 0.85336575 0.27697497 0.53959075
[55] 0.23023423 -0.90390230 0.90847382 -0.22890795 1.07447100 1.27845664
[61] -0.72762005 -0.74823892 -0.34282169 0.55641499 0.24079945 -1.67708012
[67] -0.98106145 2.17547320 -0.17337666 0.14023048 -0.35971024 0.70565113
[73] 1.17369796 -0.85902547 -0.80867301 -0.82667394 -1.56534458 -0.08637821
[79] 0.71693040 0.75365376 -2.67161815 2.22174891 1.78385352 -0.51231724
[85] 1.10778224 0.84624323 -0.08352751 1.51240133 -0.26786545 1.49515582
[91] 1.56080915 -0.52639119 -0.18952268 -0.17398087 -1.66238567 -0.19484177
[97] 0.55948655 -1.10091876 1.86586603 -1.22025877
> rowMin(tmp2)
[1] -0.12395132 0.84043054 0.25688418 1.52989179 1.64407567 -0.88608244
[7] -1.70247630 -0.39817299 -0.27472667 -0.68578883 -0.75817527 0.92113078
[13] 1.10912270 0.06344602 0.29102489 0.76555649 0.31775224 -1.18227360
[19] -0.77912914 -0.55886825 -2.04104476 -2.41290973 -0.54272936 0.53535542
[25] -0.57890001 -0.90813517 -1.13263266 1.27536001 -0.21294817 0.62210622
[31] -1.74755777 0.82026227 1.76285362 0.23952044 0.31620240 0.76376573
[37] 1.08187708 0.84822747 -0.27041641 0.01502170 -1.50591622 1.47571132
[43] 0.47100088 1.64268668 -0.46076550 -1.99776053 -0.23745723 -0.47641500
[49] -0.48710754 0.01030445 0.90100062 0.85336575 0.27697497 0.53959075
[55] 0.23023423 -0.90390230 0.90847382 -0.22890795 1.07447100 1.27845664
[61] -0.72762005 -0.74823892 -0.34282169 0.55641499 0.24079945 -1.67708012
[67] -0.98106145 2.17547320 -0.17337666 0.14023048 -0.35971024 0.70565113
[73] 1.17369796 -0.85902547 -0.80867301 -0.82667394 -1.56534458 -0.08637821
[79] 0.71693040 0.75365376 -2.67161815 2.22174891 1.78385352 -0.51231724
[85] 1.10778224 0.84624323 -0.08352751 1.51240133 -0.26786545 1.49515582
[91] 1.56080915 -0.52639119 -0.18952268 -0.17398087 -1.66238567 -0.19484177
[97] 0.55948655 -1.10091876 1.86586603 -1.22025877
>
> colMeans(tmp2)
[1] 0.03843553
> colSums(tmp2)
[1] 3.843553
> colVars(tmp2)
[1] 1.119726
> colSd(tmp2)
[1] 1.058171
> colMax(tmp2)
[1] 2.221749
> colMin(tmp2)
[1] -2.671618
> colMedians(tmp2)
[1] -0.03661153
> colRanges(tmp2)
[,1]
[1,] -2.671618
[2,] 2.221749
>
> 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] 0.5128347 3.5958222 2.7226369 -2.3255936 0.2243502 2.2539374
[7] 2.6534532 4.1542068 -1.1622046 1.2103808
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8966178
[2,] -0.4659024
[3,] 0.1054907
[4,] 0.5695514
[5,] 0.9267977
>
> rowApply(tmp,sum)
[1] 3.4314531 4.0007966 3.7555314 -1.7914350 -1.9507029 8.3024543
[7] 0.2253466 0.9962443 -1.1426384 -1.9872260
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 2 8 8 7 5 1 6 3 9 7
[2,] 6 7 10 3 6 9 5 1 6 6
[3,] 5 1 4 9 2 7 9 4 8 10
[4,] 3 6 2 10 4 2 4 2 10 3
[5,] 9 4 9 8 3 4 3 10 4 1
[6,] 8 2 6 5 9 8 2 8 5 4
[7,] 7 9 5 2 8 10 8 6 1 2
[8,] 4 10 1 1 10 6 7 9 2 9
[9,] 1 3 3 6 1 5 10 5 3 8
[10,] 10 5 7 4 7 3 1 7 7 5
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.09351629 1.23461728 -1.05888244 0.72449569 3.83407676 -0.30899973
[7] 1.57620963 0.58359291 -2.50549816 -0.11724448 -2.20174118 0.46274248
[13] 2.41500801 -0.55652045 -1.61582705 -0.69004586 -0.37570241 1.13907717
[19] 2.74111171 5.89993497
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.79685829
[2,] -0.60153043
[3,] 0.07009966
[4,] 0.22521659
[5,] 2.00955619
>
> rowApply(tmp,sum)
[1] 4.211030 5.215553 1.827007 3.504967 -3.671668
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 18 10 3 9 3
[2,] 1 20 20 8 6
[3,] 9 13 5 7 7
[4,] 13 14 14 18 1
[5,] 20 15 4 19 13
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 2.00955619 -1.7439235 -0.1558301 0.5202799 2.1372613 -0.4929728
[2,] 0.22521659 2.2609215 0.4091456 0.4366831 0.7493240 -0.4468472
[3,] -0.60153043 1.5264056 -0.5042099 0.5345893 -0.5324790 -0.2298543
[4,] 0.07009966 -0.1046434 -0.1771637 1.1404289 1.2868093 2.0727070
[5,] -1.79685829 -0.7041429 -0.6308243 -1.9074854 0.1931611 -1.2120324
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.6472739 -0.4050178 -0.5759784 -0.4081147 0.3182485 -1.2391849
[2,] -0.1029436 0.1611085 -0.2377634 0.3940734 0.8984109 1.0441540
[3,] -0.2242333 0.6731594 -0.7904170 -0.2104164 -0.4826372 1.0121275
[4,] 0.2597060 -0.4779697 -0.7873392 -0.4659374 -1.0934067 0.2369220
[5,] 0.9964066 0.6323126 -0.1140001 0.5731506 -1.8423567 -0.5912762
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.732976550 0.75137746 -1.3053724 -0.66245968 0.2087680 0.4191702
[2,] 0.003980561 -0.54012123 -0.9302262 -0.73425273 0.9257972 0.3943628
[3,] 0.144108964 -1.25219004 1.5128352 -0.02938150 -0.2293414 -0.3306193
[4,] 1.084378194 0.39457959 0.2713063 0.82205198 -0.9566824 -1.3573183
[5,] 0.449563742 0.08983377 -1.1643700 -0.08600392 -0.3242438 2.0134818
[,19] [,20]
[1,] 1.4199309 2.0350415
[2,] -1.0034208 1.3079497
[3,] 1.2444365 0.5966543
[4,] 0.1577064 1.1287327
[5,] 0.9224588 0.8315567
>
>
> 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 : 649 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 : 561 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 -0.7294192 0.6166055 -1.152681 0.2883613 0.6658315 -1.836693 0.7140439
col8 col9 col10 col11 col12 col13 col14
row1 -0.03793606 1.44322 1.759003 -2.182939 -1.502901 -0.9082823 -1.138128
col15 col16 col17 col18 col19 col20
row1 0.7767034 -0.3651282 0.5830054 -0.8904876 -1.756074 -1.638673
> tmp[,"col10"]
col10
row1 1.7590029
row2 0.7788634
row3 1.2097812
row4 -0.4221972
row5 -0.5035800
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.7294192 0.6166055 -1.152681 0.2883613 0.6658315 -1.836693 0.7140439
row5 -0.9410609 -1.4337053 -1.586484 0.3336187 -1.4466187 -1.143774 -1.4938485
col8 col9 col10 col11 col12 col13 col14
row1 -0.03793606 1.44322 1.759003 -2.182939 -1.5029012 -0.9082823 -1.1381277
row5 -0.91561968 -2.56010 -0.503580 -1.946295 0.2721363 -1.0923654 0.1684897
col15 col16 col17 col18 col19 col20
row1 0.7767034 -0.3651282 0.5830054 -0.8904876 -1.7560737 -1.638673
row5 -0.8447525 -0.5949528 0.5224258 0.4600949 -0.0147322 -0.820792
> tmp[,c("col6","col20")]
col6 col20
row1 -1.83669252 -1.6386727
row2 -0.47397349 -0.1544299
row3 2.72622942 -1.0982218
row4 -0.08323377 -0.6315541
row5 -1.14377423 -0.8207920
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.836693 -1.638673
row5 -1.143774 -0.820792
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.12128 49.36155 49.47882 50.38528 51.22249 104.1664 48.66654 50.1607
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.01668 49.36991 50.8706 50.14601 51.41254 49.48885 49.26572 50.49275
col17 col18 col19 col20
row1 52.05347 50.3223 49.3441 105.0252
> tmp[,"col10"]
col10
row1 49.36991
row2 29.32874
row3 28.29947
row4 28.52154
row5 50.19698
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.12128 49.36155 49.47882 50.38528 51.22249 104.1664 48.66654 50.16070
row5 50.28894 48.89152 49.70103 51.03245 48.67465 105.9007 50.17169 50.84625
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.01668 49.36991 50.87060 50.14601 51.41254 49.48885 49.26572 50.49275
row5 50.01263 50.19698 50.51735 48.97245 50.17358 51.47130 50.22125 52.07079
col17 col18 col19 col20
row1 52.05347 50.32230 49.3441 105.0252
row5 49.36249 50.28312 49.1614 105.4389
> tmp[,c("col6","col20")]
col6 col20
row1 104.16635 105.02516
row2 76.75711 75.80047
row3 75.51316 74.40209
row4 76.04423 75.06488
row5 105.90069 105.43893
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.1664 105.0252
row5 105.9007 105.4389
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.1664 105.0252
row5 105.9007 105.4389
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.49412696
[2,] -0.35125362
[3,] -0.01455901
[4,] -0.09243918
[5,] 0.20527027
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.2884569 1.34530469
[2,] 0.5039975 -0.54262474
[3,] -0.1613072 1.41124774
[4,] -1.9591710 -0.16497881
[5,] 1.2757244 -0.05604867
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.2510523 0.004594132
[2,] -3.1450544 0.184977161
[3,] -0.6711299 -0.879293427
[4,] -1.2749825 -0.609771574
[5,] 0.3558363 0.420302039
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.2510523
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.2510523
[2,] -3.1450544
>
>
>
> 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 -0.09056234 0.3898155 -0.08551486 0.09321119 -0.5456469 1.0552065
row1 -0.04047210 0.1854620 0.09063587 1.24776110 -1.7329010 0.6006432
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 1.4249800 -0.4188160 -1.0648622 -0.2824326 -0.4124492 -0.3590587 0.869912
row1 0.3731765 0.8774779 0.3911087 1.8078147 -1.5996221 -0.8362057 -2.494154
[,14] [,15] [,16] [,17] [,18] [,19]
row3 0.7156415 0.5718101 -1.2154458 -0.4742087 1.0988608 -0.4482893
row1 -1.4399347 -2.6191064 0.5895833 0.4695054 -0.8315355 -0.9409086
[,20]
row3 -0.3903529
row1 0.3055222
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.613412 0.6927596 0.2417378 0.4675045 -0.1081705 -0.0906996 0.09380927
[,8] [,9] [,10]
row2 0.03490436 1.623496 -2.413178
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.250586 0.3165221 1.332064 1.148712 -1.204002 -0.009780013 1.582785
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.062786 -0.7195343 0.2680933 -2.519529 0.7857299 -0.8726312 -0.08954734
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.03464203 -0.7790136 -0.8830324 -0.6894269 -0.4602456 0.07206013
>
>
> 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: 0x600003bc03c0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8aa313682c0"
[2] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8aa71c2247d"
[3] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8aae9c4e4"
[4] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8aa737d5533"
[5] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8aa2964c281"
[6] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8aa161db862"
[7] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8aa79343545"
[8] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8aa5295832d"
[9] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8aa55d729b6"
[10] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8aa20f397c1"
[11] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8aa587010cd"
[12] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8aa255f3017"
[13] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8aac4e492c"
[14] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8aa67a5ee03"
[15] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMc8aa3ead3c1e"
>
>
> ### 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: 0x600003bec1e0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600003bec1e0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600003bec1e0>
> rowMedians(tmp)
[1] -0.326707176 0.187621297 0.311923148 -0.104520608 0.346276691
[6] 0.034122850 0.005757904 -0.366903769 0.153900451 -0.107069930
[11] -0.171793478 0.097343596 0.292718070 -0.022419381 -0.096900238
[16] 0.139394368 -0.761944726 -0.309131682 -0.171776788 0.097530380
[21] -0.177717243 -0.399593480 0.153598712 0.401620771 -0.227247827
[26] -0.201851322 0.173493885 0.373577449 -0.657826663 -0.087216632
[31] 0.386862915 0.285489441 0.063718536 0.021061823 0.404651228
[36] 0.774970670 -0.514536417 -0.066400112 0.188012987 -0.023395061
[41] 0.364940895 -0.768518753 -0.032574441 0.124033767 -0.597659633
[46] -0.076051614 -0.678461435 0.305184806 -0.245348226 0.432613760
[51] -0.222908513 -0.235264525 0.257002323 -0.052085862 0.008187316
[56] -0.143816293 0.048708136 0.167904643 0.397130626 -0.090762956
[61] -0.634572091 -0.561743222 -0.249212724 0.208201394 0.097410863
[66] 0.083467841 0.088297787 -0.472431199 -0.188585764 0.130934022
[71] 0.394997572 -0.170245648 -0.229662791 0.176786582 0.373159976
[76] -0.041093581 0.238821502 0.659405544 -0.126617210 0.116367797
[81] 0.143180045 -0.233338516 -0.188430412 -0.464783743 0.487344691
[86] 0.133745584 -0.309181616 0.184826517 -0.716020790 0.256995735
[91] -0.724564597 0.049599527 0.126674291 0.312774342 -0.144227680
[96] 0.069654607 0.343958190 -0.496547762 0.325797783 0.053256698
[101] -0.523548982 -0.160571183 -0.121749227 0.208565333 0.422199667
[106] 0.009224755 -0.099770436 -0.061896964 0.094489088 -0.002681239
[111] 0.019743094 0.065472838 -0.321759668 0.318545691 -0.413022788
[116] -0.062675882 0.031704544 -0.250671631 0.382109320 -0.285069919
[121] 0.029437984 0.179500025 0.492313384 0.111154867 0.064678210
[126] 0.696117937 0.071051036 -0.058557164 0.052829917 0.271693700
[131] -0.240944624 0.112165234 0.271790894 -0.585733160 0.188347159
[136] -0.452104093 0.424140471 0.225438422 -0.103825033 -0.353415414
[141] -0.367883059 0.427266143 -0.347368692 0.027196030 -0.116916684
[146] -0.095456042 -0.110679870 -0.465852695 0.240618805 0.188362363
[151] 0.610258727 -0.405807931 -0.223741201 -0.238869727 0.056056898
[156] 0.208996260 0.350506172 -0.082289911 0.047332266 -0.052854966
[161] 0.078113032 -0.287728958 -0.125858133 -0.377388381 -0.288679670
[166] -0.318904238 0.252425561 -0.107218512 0.158099175 -0.257439597
[171] -0.007360607 -0.095689249 -0.071325570 -0.415814002 0.360106179
[176] 0.168554978 -0.467293976 -0.179587639 0.376886183 0.129608607
[181] -0.189755265 0.296025624 -0.004740348 -0.281663692 -0.138316491
[186] -0.288908642 -0.172772689 -0.002979644 -0.211919686 0.025591971
[191] -0.423819330 -0.081373210 0.668931292 0.016714809 0.166167661
[196] 0.144758121 0.220125730 -0.278670266 0.394039057 -0.254486529
[201] -0.030361059 0.117220185 -0.262930013 -0.363642775 0.326975926
[206] -0.047424061 -0.157278022 -0.173890063 -0.197580473 -0.333730427
[211] -0.080658606 0.481771288 0.025333955 0.002325311 0.033611223
[216] -0.433007698 -0.233271946 0.181063218 0.512272562 -0.358970120
[221] 0.142238662 0.280022791 0.587651090 -0.423676068 -0.040023680
[226] 0.030549368 -0.114457320 0.077191344 0.255298931 -0.565109784
>
> proc.time()
user system elapsed
1.988 8.649 10.970
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: 0x600003c4c120>
> .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: 0x600003c4c120>
> .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: 0x600003c4c120>
> .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: 0x600003c4c120>
> 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: 0x600003c6c660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003c6c660>
> .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: 0x600003c6c660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003c6c660>
> .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: 0x600003c6c660>
> 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: 0x600003c6c840>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003c6c840>
> .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: 0x600003c6c840>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003c6c840>
> .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: 0x600003c6c840>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600003c6c840>
> .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: 0x600003c6c840>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600003c6c840>
> .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: 0x600003c6c840>
> 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: 0x600003c6ca20>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600003c6ca20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003c6ca20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003c6ca20>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilec8dd146fa185" "BufferedMatrixFilec8dd2cd52d3e"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilec8dd146fa185" "BufferedMatrixFilec8dd2cd52d3e"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003c6ccc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003c6ccc0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003c6ccc0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003c6ccc0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600003c6ccc0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600003c6ccc0>
> .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: 0x600003c6cea0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003c6cea0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003c6cea0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600003c6cea0>
> 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: 0x600003c6d080>
> .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: 0x600003c6d080>
> rm(P)
>
> proc.time()
user system elapsed
0.326 0.116 0.434
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.3 (2025-02-28) -- "Trophy Case"
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Platform: aarch64-apple-darwin20
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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
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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
0.322 0.071 0.379