Ben Bolstad
| Snapshot Date: 2025-04-17 13:40 -0400 (Thu, 17 Apr 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_21 |
| git_last_commit: aa9e634 |
| git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-04-18 11:45 -0400 (Fri, 18 Apr 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six" | 4831 |
| palomino7 | Windows Server 2022 Datacenter | x64 | 4.5.0 RC (2025-04-04 r88126 ucrt) -- "How About a Twenty-Six" | 4573 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six" | 4599 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six" | 4553 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4570 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 252/2341 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.72.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.1 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| kunpeng2 | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.72.0 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.72.0.tar.gz |
| StartedAt: 2025-04-17 18:28:14 -0400 (Thu, 17 Apr 2025) |
| EndedAt: 2025-04-17 18:28:31 -0400 (Thu, 17 Apr 2025) |
| EllapsedTime: 17.2 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
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###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.72.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.0 RC (2025-04-04 r88126)
* using platform: aarch64-apple-darwin20
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.72.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... WARNING
Found the following significant warnings:
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
* used SDK: ‘MacOSX11.3.sdk’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 WARNING, 2 NOTEs
See
‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
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###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.72.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
using SDK: ‘MacOSX11.3.sdk’
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch arm64 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/arm64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R
installing to /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.111 0.037 0.144
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
Ncells 480809 25.7 1056568 56.5 NA 634342 33.9
Vcells 890978 6.8 8388608 64.0 196608 2109696 16.1
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu Apr 17 18:28:23 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] "Thu Apr 17 18:28:23 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: 0x600000ff0000>
>
>
>
> 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] "Thu Apr 17 18:28:24 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] "Thu Apr 17 18:28:25 2025"
>
> ColMode(tmp2)
<pointer: 0x600000ff0000>
>
>
>
> ### 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,] 100.9324085 -0.2383241 -0.07619894 0.5992282
[2,] -1.0370263 1.1571947 0.61391435 0.2167578
[3,] -1.0759273 -0.2921145 -0.38895479 -0.1933739
[4,] 0.6468912 0.7452125 -1.17927713 1.2047048
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.9324085 0.2383241 0.07619894 0.5992282
[2,] 1.0370263 1.1571947 0.61391435 0.2167578
[3,] 1.0759273 0.2921145 0.38895479 0.1933739
[4,] 0.6468912 0.7452125 1.17927713 1.2047048
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0465123 0.4881845 0.2760415 0.7740983
[2,] 1.0183449 1.0757298 0.7835269 0.4655726
[3,] 1.0372692 0.5404762 0.6236624 0.4397430
[4,] 0.8042955 0.8632569 1.0859453 1.0975904
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 226.39753 30.12017 27.83661 33.34021
[2,] 36.22048 36.91449 33.44918 29.87248
[3,] 36.44862 30.69688 31.62558 29.59080
[4,] 33.68985 34.37778 37.03873 37.18061
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600000fe02a0>
> exp(tmp5)
<pointer: 0x600000fe02a0>
> log(tmp5,2)
<pointer: 0x600000fe02a0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.2168
> Min(tmp5)
[1] 55.79278
> mean(tmp5)
[1] 72.97974
> Sum(tmp5)
[1] 14595.95
> Var(tmp5)
[1] 872.187
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 87.77484 70.84495 68.37984 71.99393 73.95595 70.68583 71.61747 71.01745
[9] 72.06666 71.46048
> rowSums(tmp5)
[1] 1755.497 1416.899 1367.597 1439.879 1479.119 1413.717 1432.349 1420.349
[9] 1441.333 1429.210
> rowVars(tmp5)
[1] 8204.29416 71.92692 74.51918 61.24675 43.32474 114.22471
[7] 91.48774 32.19736 118.55335 48.87222
> rowSd(tmp5)
[1] 90.577559 8.480974 8.632449 7.826030 6.582153 10.687596 9.564922
[8] 5.674272 10.888221 6.990867
> rowMax(tmp5)
[1] 471.21680 92.75328 86.26996 90.25384 88.10687 94.56147 86.24980
[8] 78.94276 97.23034 83.30470
> rowMin(tmp5)
[1] 57.07129 59.95578 57.29040 56.22491 61.30291 56.14030 57.41060 60.38878
[9] 55.79278 57.10276
>
> colMeans(tmp5)
[1] 115.19862 70.12304 67.82817 67.42334 76.73762 66.83815 67.65669
[8] 72.58761 69.99843 67.63195 65.78571 71.68370 69.56261 70.89036
[15] 71.68284 73.33786 74.67551 79.14145 70.61979 70.19138
> colSums(tmp5)
[1] 1151.9862 701.2304 678.2817 674.2334 767.3762 668.3815 676.5669
[8] 725.8761 699.9843 676.3195 657.8571 716.8370 695.6261 708.9036
[15] 716.8284 733.3786 746.7551 791.4145 706.1979 701.9138
> colVars(tmp5)
[1] 15674.34051 67.88273 49.75251 68.82027 37.02885 35.23819
[7] 129.99187 46.10878 70.51809 55.51868 80.60740 79.49548
[13] 40.17061 36.38071 62.82638 77.88743 117.63311 80.51249
[19] 82.22473 68.42337
> colSd(tmp5)
[1] 125.197206 8.239098 7.053546 8.295798 6.085134 5.936177
[7] 11.401398 6.790344 8.397505 7.451086 8.978163 8.916024
[13] 6.338029 6.031642 7.926310 8.825385 10.845880 8.972875
[19] 9.067785 8.271842
> colMax(tmp5)
[1] 471.21680 85.19567 77.75382 78.31467 85.12064 78.10716 88.10687
[8] 86.26996 80.36523 79.06810 78.25372 86.24980 80.82879 79.10587
[15] 84.59538 92.75328 97.23034 94.56147 90.25384 87.67053
> colMin(tmp5)
[1] 67.55917 55.79278 57.93827 57.10276 69.38589 57.16538 56.22491 60.38878
[9] 58.77061 57.61150 56.14030 61.32751 62.56834 61.39447 61.30291 60.65815
[17] 57.07129 60.69595 59.81965 57.29040
>
>
> ### 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] 87.77484 70.84495 NA 71.99393 73.95595 70.68583 71.61747 71.01745
[9] 72.06666 71.46048
> rowSums(tmp5)
[1] 1755.497 1416.899 NA 1439.879 1479.119 1413.717 1432.349 1420.349
[9] 1441.333 1429.210
> rowVars(tmp5)
[1] 8204.29416 71.92692 78.41849 61.24675 43.32474 114.22471
[7] 91.48774 32.19736 118.55335 48.87222
> rowSd(tmp5)
[1] 90.577559 8.480974 8.855421 7.826030 6.582153 10.687596 9.564922
[8] 5.674272 10.888221 6.990867
> rowMax(tmp5)
[1] 471.21680 92.75328 NA 90.25384 88.10687 94.56147 86.24980
[8] 78.94276 97.23034 83.30470
> rowMin(tmp5)
[1] 57.07129 59.95578 NA 56.22491 61.30291 56.14030 57.41060 60.38878
[9] 55.79278 57.10276
>
> colMeans(tmp5)
[1] 115.19862 70.12304 67.82817 67.42334 76.73762 NA 67.65669
[8] 72.58761 69.99843 67.63195 65.78571 71.68370 69.56261 70.89036
[15] 71.68284 73.33786 74.67551 79.14145 70.61979 70.19138
> colSums(tmp5)
[1] 1151.9862 701.2304 678.2817 674.2334 767.3762 NA 676.5669
[8] 725.8761 699.9843 676.3195 657.8571 716.8370 695.6261 708.9036
[15] 716.8284 733.3786 746.7551 791.4145 706.1979 701.9138
> colVars(tmp5)
[1] 15674.34051 67.88273 49.75251 68.82027 37.02885 NA
[7] 129.99187 46.10878 70.51809 55.51868 80.60740 79.49548
[13] 40.17061 36.38071 62.82638 77.88743 117.63311 80.51249
[19] 82.22473 68.42337
> colSd(tmp5)
[1] 125.197206 8.239098 7.053546 8.295798 6.085134 NA
[7] 11.401398 6.790344 8.397505 7.451086 8.978163 8.916024
[13] 6.338029 6.031642 7.926310 8.825385 10.845880 8.972875
[19] 9.067785 8.271842
> colMax(tmp5)
[1] 471.21680 85.19567 77.75382 78.31467 85.12064 NA 88.10687
[8] 86.26996 80.36523 79.06810 78.25372 86.24980 80.82879 79.10587
[15] 84.59538 92.75328 97.23034 94.56147 90.25384 87.67053
> colMin(tmp5)
[1] 67.55917 55.79278 57.93827 57.10276 69.38589 NA 56.22491 60.38878
[9] 58.77061 57.61150 56.14030 61.32751 62.56834 61.39447 61.30291 60.65815
[17] 57.07129 60.69595 59.81965 57.29040
>
> Max(tmp5,na.rm=TRUE)
[1] 471.2168
> Min(tmp5,na.rm=TRUE)
[1] 55.79278
> mean(tmp5,na.rm=TRUE)
[1] 73.01305
> Sum(tmp5,na.rm=TRUE)
[1] 14529.6
> Var(tmp5,na.rm=TRUE)
[1] 876.369
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.77484 70.84495 68.48661 71.99393 73.95595 70.68583 71.61747 71.01745
[9] 72.06666 71.46048
> rowSums(tmp5,na.rm=TRUE)
[1] 1755.497 1416.899 1301.246 1439.879 1479.119 1413.717 1432.349 1420.349
[9] 1441.333 1429.210
> rowVars(tmp5,na.rm=TRUE)
[1] 8204.29416 71.92692 78.41849 61.24675 43.32474 114.22471
[7] 91.48774 32.19736 118.55335 48.87222
> rowSd(tmp5,na.rm=TRUE)
[1] 90.577559 8.480974 8.855421 7.826030 6.582153 10.687596 9.564922
[8] 5.674272 10.888221 6.990867
> rowMax(tmp5,na.rm=TRUE)
[1] 471.21680 92.75328 86.26996 90.25384 88.10687 94.56147 86.24980
[8] 78.94276 97.23034 83.30470
> rowMin(tmp5,na.rm=TRUE)
[1] 57.07129 59.95578 57.29040 56.22491 61.30291 56.14030 57.41060 60.38878
[9] 55.79278 57.10276
>
> colMeans(tmp5,na.rm=TRUE)
[1] 115.19862 70.12304 67.82817 67.42334 76.73762 66.89225 67.65669
[8] 72.58761 69.99843 67.63195 65.78571 71.68370 69.56261 70.89036
[15] 71.68284 73.33786 74.67551 79.14145 70.61979 70.19138
> colSums(tmp5,na.rm=TRUE)
[1] 1151.9862 701.2304 678.2817 674.2334 767.3762 602.0302 676.5669
[8] 725.8761 699.9843 676.3195 657.8571 716.8370 695.6261 708.9036
[15] 716.8284 733.3786 746.7551 791.4145 706.1979 701.9138
> colVars(tmp5,na.rm=TRUE)
[1] 15674.34051 67.88273 49.75251 68.82027 37.02885 39.61004
[7] 129.99187 46.10878 70.51809 55.51868 80.60740 79.49548
[13] 40.17061 36.38071 62.82638 77.88743 117.63311 80.51249
[19] 82.22473 68.42337
> colSd(tmp5,na.rm=TRUE)
[1] 125.197206 8.239098 7.053546 8.295798 6.085134 6.293651
[7] 11.401398 6.790344 8.397505 7.451086 8.978163 8.916024
[13] 6.338029 6.031642 7.926310 8.825385 10.845880 8.972875
[19] 9.067785 8.271842
> colMax(tmp5,na.rm=TRUE)
[1] 471.21680 85.19567 77.75382 78.31467 85.12064 78.10716 88.10687
[8] 86.26996 80.36523 79.06810 78.25372 86.24980 80.82879 79.10587
[15] 84.59538 92.75328 97.23034 94.56147 90.25384 87.67053
> colMin(tmp5,na.rm=TRUE)
[1] 67.55917 55.79278 57.93827 57.10276 69.38589 57.16538 56.22491 60.38878
[9] 58.77061 57.61150 56.14030 61.32751 62.56834 61.39447 61.30291 60.65815
[17] 57.07129 60.69595 59.81965 57.29040
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.77484 70.84495 NaN 71.99393 73.95595 70.68583 71.61747 71.01745
[9] 72.06666 71.46048
> rowSums(tmp5,na.rm=TRUE)
[1] 1755.497 1416.899 0.000 1439.879 1479.119 1413.717 1432.349 1420.349
[9] 1441.333 1429.210
> rowVars(tmp5,na.rm=TRUE)
[1] 8204.29416 71.92692 NA 61.24675 43.32474 114.22471
[7] 91.48774 32.19736 118.55335 48.87222
> rowSd(tmp5,na.rm=TRUE)
[1] 90.577559 8.480974 NA 7.826030 6.582153 10.687596 9.564922
[8] 5.674272 10.888221 6.990867
> rowMax(tmp5,na.rm=TRUE)
[1] 471.21680 92.75328 NA 90.25384 88.10687 94.56147 86.24980
[8] 78.94276 97.23034 83.30470
> rowMin(tmp5,na.rm=TRUE)
[1] 57.07129 59.95578 NA 56.22491 61.30291 56.14030 57.41060 60.38878
[9] 55.79278 57.10276
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 119.56924 70.81543 68.05080 68.07156 76.50925 NaN 67.81457
[8] 71.06735 71.24596 68.74533 64.46713 72.53961 68.79685 71.77508
[15] 72.48197 72.58858 75.77888 81.19095 69.79121 71.62482
> colSums(tmp5,na.rm=TRUE)
[1] 1076.1232 637.3389 612.4572 612.6440 688.5832 0.0000 610.3311
[8] 639.6062 641.2137 618.7080 580.2041 652.8565 619.1716 645.9757
[15] 652.3377 653.2973 682.0099 730.7186 628.1209 644.6234
> colVars(tmp5,na.rm=TRUE)
[1] 17418.73183 70.97477 55.41397 72.69571 41.07070 NA
[7] 145.96042 25.87144 61.82398 48.51275 71.12336 81.19076
[13] 38.59506 32.12262 63.49531 81.30740 118.64120 43.32150
[19] 84.77920 53.86029
> colSd(tmp5,na.rm=TRUE)
[1] 131.980043 8.424653 7.444056 8.526178 6.408643 NA
[7] 12.081408 5.086397 7.862822 6.965109 8.433467 9.010592
[13] 6.212493 5.667682 7.968395 9.017062 10.892254 6.581907
[19] 9.207562 7.338957
> colMax(tmp5,na.rm=TRUE)
[1] 471.21680 85.19567 77.75382 78.31467 85.12064 -Inf 88.10687
[8] 76.01320 80.36523 79.06810 78.25372 86.24980 80.82879 79.10587
[15] 84.59538 92.75328 97.23034 94.56147 90.25384 87.67053
> colMin(tmp5,na.rm=TRUE)
[1] 67.55917 55.79278 57.93827 57.10276 69.38589 Inf 56.22491 60.38878
[9] 60.38205 57.68938 56.14030 61.32751 62.56834 61.39447 61.30291 60.65815
[17] 57.07129 70.75682 59.81965 63.70028
>
>
>
>
> 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] 321.6436 386.3088 280.9887 111.3166 239.3678 265.7107 181.4839 334.5804
[9] 362.8090 269.8329
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 321.6436 386.3088 280.9887 111.3166 239.3678 265.7107 181.4839 334.5804
[9] 362.8090 269.8329
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 1.421085e-13 5.684342e-14 5.684342e-14 8.526513e-14 1.421085e-14
[6] -5.684342e-14 5.684342e-14 -5.684342e-14 5.684342e-14 5.684342e-14
[11] 1.136868e-13 5.684342e-14 0.000000e+00 0.000000e+00 5.684342e-14
[16] 1.421085e-13 -1.136868e-13 5.684342e-14 0.000000e+00 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)
+ }
8 16
7 1
3 13
5 17
7 4
3 1
1 6
3 11
5 10
6 2
2 15
4 5
9 2
1 12
5 18
1 9
4 8
2 5
7 14
9 12
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.648444
> Min(tmp)
[1] -2.879592
> mean(tmp)
[1] -0.05653903
> Sum(tmp)
[1] -5.653903
> Var(tmp)
[1] 1.110788
>
> rowMeans(tmp)
[1] -0.05653903
> rowSums(tmp)
[1] -5.653903
> rowVars(tmp)
[1] 1.110788
> rowSd(tmp)
[1] 1.053939
> rowMax(tmp)
[1] 2.648444
> rowMin(tmp)
[1] -2.879592
>
> colMeans(tmp)
[1] -0.04009987 -0.68943675 -0.60102765 0.07493972 -0.40652377 -1.17844581
[7] 1.30075697 -0.62226098 0.94443856 1.27477598 0.75544169 -1.83268163
[13] 2.10377451 0.07443519 -0.68389623 -1.33817206 -0.17059095 -0.41739820
[19] -0.65456012 -1.50628666 1.93884130 -1.40279287 0.19994122 -0.53769576
[25] 0.73231663 -0.23636589 0.03511458 0.77003409 0.64762862 0.43651457
[31] 0.50443013 0.28167470 0.34809728 0.48256532 -0.97362633 -0.34792827
[37] -0.25879600 0.38333477 0.68497336 -0.46038284 -1.51303118 0.13082014
[43] -0.13978337 -2.87959163 -0.91382282 2.55661598 -1.13873075 0.42981585
[49] -1.44263902 -0.25025335 0.81120780 -0.90219278 1.70003688 0.18564973
[55] -0.26185693 -0.44251506 0.30969535 1.12662228 -1.02144914 -0.08680809
[61] 0.12658441 0.55937521 -0.05712588 -1.26237107 0.99288854 2.16004964
[67] -2.35953412 0.14644134 -0.86709963 1.26132532 -0.75661180 -1.28254514
[73] -0.36810587 -0.37694527 -0.45068011 1.05274205 0.84252746 -1.07832259
[79] -2.38833110 -1.31067565 -2.14296797 -0.72656388 -0.54908732 -0.32255687
[85] 0.86318271 -0.34362653 0.07461739 1.31649545 2.64844353 0.78972703
[91] -0.73524238 0.42710429 -0.21145576 1.17982471 -0.16206766 -0.24198265
[97] 0.79742000 -0.49895777 -0.02544022 1.75279495
> colSums(tmp)
[1] -0.04009987 -0.68943675 -0.60102765 0.07493972 -0.40652377 -1.17844581
[7] 1.30075697 -0.62226098 0.94443856 1.27477598 0.75544169 -1.83268163
[13] 2.10377451 0.07443519 -0.68389623 -1.33817206 -0.17059095 -0.41739820
[19] -0.65456012 -1.50628666 1.93884130 -1.40279287 0.19994122 -0.53769576
[25] 0.73231663 -0.23636589 0.03511458 0.77003409 0.64762862 0.43651457
[31] 0.50443013 0.28167470 0.34809728 0.48256532 -0.97362633 -0.34792827
[37] -0.25879600 0.38333477 0.68497336 -0.46038284 -1.51303118 0.13082014
[43] -0.13978337 -2.87959163 -0.91382282 2.55661598 -1.13873075 0.42981585
[49] -1.44263902 -0.25025335 0.81120780 -0.90219278 1.70003688 0.18564973
[55] -0.26185693 -0.44251506 0.30969535 1.12662228 -1.02144914 -0.08680809
[61] 0.12658441 0.55937521 -0.05712588 -1.26237107 0.99288854 2.16004964
[67] -2.35953412 0.14644134 -0.86709963 1.26132532 -0.75661180 -1.28254514
[73] -0.36810587 -0.37694527 -0.45068011 1.05274205 0.84252746 -1.07832259
[79] -2.38833110 -1.31067565 -2.14296797 -0.72656388 -0.54908732 -0.32255687
[85] 0.86318271 -0.34362653 0.07461739 1.31649545 2.64844353 0.78972703
[91] -0.73524238 0.42710429 -0.21145576 1.17982471 -0.16206766 -0.24198265
[97] 0.79742000 -0.49895777 -0.02544022 1.75279495
> 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] -0.04009987 -0.68943675 -0.60102765 0.07493972 -0.40652377 -1.17844581
[7] 1.30075697 -0.62226098 0.94443856 1.27477598 0.75544169 -1.83268163
[13] 2.10377451 0.07443519 -0.68389623 -1.33817206 -0.17059095 -0.41739820
[19] -0.65456012 -1.50628666 1.93884130 -1.40279287 0.19994122 -0.53769576
[25] 0.73231663 -0.23636589 0.03511458 0.77003409 0.64762862 0.43651457
[31] 0.50443013 0.28167470 0.34809728 0.48256532 -0.97362633 -0.34792827
[37] -0.25879600 0.38333477 0.68497336 -0.46038284 -1.51303118 0.13082014
[43] -0.13978337 -2.87959163 -0.91382282 2.55661598 -1.13873075 0.42981585
[49] -1.44263902 -0.25025335 0.81120780 -0.90219278 1.70003688 0.18564973
[55] -0.26185693 -0.44251506 0.30969535 1.12662228 -1.02144914 -0.08680809
[61] 0.12658441 0.55937521 -0.05712588 -1.26237107 0.99288854 2.16004964
[67] -2.35953412 0.14644134 -0.86709963 1.26132532 -0.75661180 -1.28254514
[73] -0.36810587 -0.37694527 -0.45068011 1.05274205 0.84252746 -1.07832259
[79] -2.38833110 -1.31067565 -2.14296797 -0.72656388 -0.54908732 -0.32255687
[85] 0.86318271 -0.34362653 0.07461739 1.31649545 2.64844353 0.78972703
[91] -0.73524238 0.42710429 -0.21145576 1.17982471 -0.16206766 -0.24198265
[97] 0.79742000 -0.49895777 -0.02544022 1.75279495
> colMin(tmp)
[1] -0.04009987 -0.68943675 -0.60102765 0.07493972 -0.40652377 -1.17844581
[7] 1.30075697 -0.62226098 0.94443856 1.27477598 0.75544169 -1.83268163
[13] 2.10377451 0.07443519 -0.68389623 -1.33817206 -0.17059095 -0.41739820
[19] -0.65456012 -1.50628666 1.93884130 -1.40279287 0.19994122 -0.53769576
[25] 0.73231663 -0.23636589 0.03511458 0.77003409 0.64762862 0.43651457
[31] 0.50443013 0.28167470 0.34809728 0.48256532 -0.97362633 -0.34792827
[37] -0.25879600 0.38333477 0.68497336 -0.46038284 -1.51303118 0.13082014
[43] -0.13978337 -2.87959163 -0.91382282 2.55661598 -1.13873075 0.42981585
[49] -1.44263902 -0.25025335 0.81120780 -0.90219278 1.70003688 0.18564973
[55] -0.26185693 -0.44251506 0.30969535 1.12662228 -1.02144914 -0.08680809
[61] 0.12658441 0.55937521 -0.05712588 -1.26237107 0.99288854 2.16004964
[67] -2.35953412 0.14644134 -0.86709963 1.26132532 -0.75661180 -1.28254514
[73] -0.36810587 -0.37694527 -0.45068011 1.05274205 0.84252746 -1.07832259
[79] -2.38833110 -1.31067565 -2.14296797 -0.72656388 -0.54908732 -0.32255687
[85] 0.86318271 -0.34362653 0.07461739 1.31649545 2.64844353 0.78972703
[91] -0.73524238 0.42710429 -0.21145576 1.17982471 -0.16206766 -0.24198265
[97] 0.79742000 -0.49895777 -0.02544022 1.75279495
> colMedians(tmp)
[1] -0.04009987 -0.68943675 -0.60102765 0.07493972 -0.40652377 -1.17844581
[7] 1.30075697 -0.62226098 0.94443856 1.27477598 0.75544169 -1.83268163
[13] 2.10377451 0.07443519 -0.68389623 -1.33817206 -0.17059095 -0.41739820
[19] -0.65456012 -1.50628666 1.93884130 -1.40279287 0.19994122 -0.53769576
[25] 0.73231663 -0.23636589 0.03511458 0.77003409 0.64762862 0.43651457
[31] 0.50443013 0.28167470 0.34809728 0.48256532 -0.97362633 -0.34792827
[37] -0.25879600 0.38333477 0.68497336 -0.46038284 -1.51303118 0.13082014
[43] -0.13978337 -2.87959163 -0.91382282 2.55661598 -1.13873075 0.42981585
[49] -1.44263902 -0.25025335 0.81120780 -0.90219278 1.70003688 0.18564973
[55] -0.26185693 -0.44251506 0.30969535 1.12662228 -1.02144914 -0.08680809
[61] 0.12658441 0.55937521 -0.05712588 -1.26237107 0.99288854 2.16004964
[67] -2.35953412 0.14644134 -0.86709963 1.26132532 -0.75661180 -1.28254514
[73] -0.36810587 -0.37694527 -0.45068011 1.05274205 0.84252746 -1.07832259
[79] -2.38833110 -1.31067565 -2.14296797 -0.72656388 -0.54908732 -0.32255687
[85] 0.86318271 -0.34362653 0.07461739 1.31649545 2.64844353 0.78972703
[91] -0.73524238 0.42710429 -0.21145576 1.17982471 -0.16206766 -0.24198265
[97] 0.79742000 -0.49895777 -0.02544022 1.75279495
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.04009987 -0.6894367 -0.6010277 0.07493972 -0.4065238 -1.178446 1.300757
[2,] -0.04009987 -0.6894367 -0.6010277 0.07493972 -0.4065238 -1.178446 1.300757
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.622261 0.9444386 1.274776 0.7554417 -1.832682 2.103775 0.07443519
[2,] -0.622261 0.9444386 1.274776 0.7554417 -1.832682 2.103775 0.07443519
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.6838962 -1.338172 -0.1705909 -0.4173982 -0.6545601 -1.506287 1.938841
[2,] -0.6838962 -1.338172 -0.1705909 -0.4173982 -0.6545601 -1.506287 1.938841
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.402793 0.1999412 -0.5376958 0.7323166 -0.2363659 0.03511458 0.7700341
[2,] -1.402793 0.1999412 -0.5376958 0.7323166 -0.2363659 0.03511458 0.7700341
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.6476286 0.4365146 0.5044301 0.2816747 0.3480973 0.4825653 -0.9736263
[2,] 0.6476286 0.4365146 0.5044301 0.2816747 0.3480973 0.4825653 -0.9736263
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.3479283 -0.258796 0.3833348 0.6849734 -0.4603828 -1.513031 0.1308201
[2,] -0.3479283 -0.258796 0.3833348 0.6849734 -0.4603828 -1.513031 0.1308201
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.1397834 -2.879592 -0.9138228 2.556616 -1.138731 0.4298158 -1.442639
[2,] -0.1397834 -2.879592 -0.9138228 2.556616 -1.138731 0.4298158 -1.442639
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.2502534 0.8112078 -0.9021928 1.700037 0.1856497 -0.2618569 -0.4425151
[2,] -0.2502534 0.8112078 -0.9021928 1.700037 0.1856497 -0.2618569 -0.4425151
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.3096954 1.126622 -1.021449 -0.08680809 0.1265844 0.5593752 -0.05712588
[2,] 0.3096954 1.126622 -1.021449 -0.08680809 0.1265844 0.5593752 -0.05712588
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.262371 0.9928885 2.16005 -2.359534 0.1464413 -0.8670996 1.261325
[2,] -1.262371 0.9928885 2.16005 -2.359534 0.1464413 -0.8670996 1.261325
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.7566118 -1.282545 -0.3681059 -0.3769453 -0.4506801 1.052742 0.8425275
[2,] -0.7566118 -1.282545 -0.3681059 -0.3769453 -0.4506801 1.052742 0.8425275
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -1.078323 -2.388331 -1.310676 -2.142968 -0.7265639 -0.5490873 -0.3225569
[2,] -1.078323 -2.388331 -1.310676 -2.142968 -0.7265639 -0.5490873 -0.3225569
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.8631827 -0.3436265 0.07461739 1.316495 2.648444 0.789727 -0.7352424
[2,] 0.8631827 -0.3436265 0.07461739 1.316495 2.648444 0.789727 -0.7352424
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.4271043 -0.2114558 1.179825 -0.1620677 -0.2419826 0.79742 -0.4989578
[2,] 0.4271043 -0.2114558 1.179825 -0.1620677 -0.2419826 0.79742 -0.4989578
[,99] [,100]
[1,] -0.02544022 1.752795
[2,] -0.02544022 1.752795
>
>
> Max(tmp2)
[1] 2.206857
> Min(tmp2)
[1] -2.615147
> mean(tmp2)
[1] 0.02101129
> Sum(tmp2)
[1] 2.101129
> Var(tmp2)
[1] 1.039479
>
> rowMeans(tmp2)
[1] -0.01022310 1.26610360 -1.47945981 -1.31315802 -0.44355220 0.42662110
[7] -0.30048898 0.03494274 1.19502267 1.75357250 -0.50578168 0.75617150
[13] -0.31528155 -1.21199672 1.11432860 0.88666127 0.64267710 -1.83987251
[19] 0.82399031 0.49078942 0.57442031 0.18128184 -0.41879204 0.38879048
[25] -1.77594524 -1.58922284 0.03986224 -0.63071160 0.34482561 -0.30415779
[31] -0.70574609 0.95682399 -0.36761650 1.49026425 0.54562399 -1.74631296
[37] 0.83634231 0.68951096 0.43386257 -0.42976091 0.28054092 1.13732050
[43] -0.90948394 1.56798606 0.30067433 0.10755312 0.76004583 1.40934015
[49] 0.28871591 0.45031675 -1.32004816 -0.05047722 0.84185185 -0.69396881
[55] 2.20685657 0.70099191 -0.76873918 -0.34911039 1.20995192 -1.56228925
[61] -0.33141540 -0.05642018 -0.48960698 1.13946114 0.36509672 1.46521312
[67] -0.48851479 0.20336354 -2.42138781 -1.41946713 -0.13281374 0.19966118
[73] -0.05450908 1.06234698 -0.58793904 0.24826220 -0.52699637 -2.32717665
[79] 1.71569579 -1.97518725 0.86822302 -1.01212263 0.60384020 -2.61514703
[85] 0.83402961 -0.04172977 0.14521953 -0.53676022 0.77573480 -0.14424903
[91] -0.06127010 -2.38399713 0.26946759 1.41954165 0.67356521 0.55386424
[97] -0.38770681 0.47422832 -0.18507908 1.17137230
> rowSums(tmp2)
[1] -0.01022310 1.26610360 -1.47945981 -1.31315802 -0.44355220 0.42662110
[7] -0.30048898 0.03494274 1.19502267 1.75357250 -0.50578168 0.75617150
[13] -0.31528155 -1.21199672 1.11432860 0.88666127 0.64267710 -1.83987251
[19] 0.82399031 0.49078942 0.57442031 0.18128184 -0.41879204 0.38879048
[25] -1.77594524 -1.58922284 0.03986224 -0.63071160 0.34482561 -0.30415779
[31] -0.70574609 0.95682399 -0.36761650 1.49026425 0.54562399 -1.74631296
[37] 0.83634231 0.68951096 0.43386257 -0.42976091 0.28054092 1.13732050
[43] -0.90948394 1.56798606 0.30067433 0.10755312 0.76004583 1.40934015
[49] 0.28871591 0.45031675 -1.32004816 -0.05047722 0.84185185 -0.69396881
[55] 2.20685657 0.70099191 -0.76873918 -0.34911039 1.20995192 -1.56228925
[61] -0.33141540 -0.05642018 -0.48960698 1.13946114 0.36509672 1.46521312
[67] -0.48851479 0.20336354 -2.42138781 -1.41946713 -0.13281374 0.19966118
[73] -0.05450908 1.06234698 -0.58793904 0.24826220 -0.52699637 -2.32717665
[79] 1.71569579 -1.97518725 0.86822302 -1.01212263 0.60384020 -2.61514703
[85] 0.83402961 -0.04172977 0.14521953 -0.53676022 0.77573480 -0.14424903
[91] -0.06127010 -2.38399713 0.26946759 1.41954165 0.67356521 0.55386424
[97] -0.38770681 0.47422832 -0.18507908 1.17137230
> 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] -0.01022310 1.26610360 -1.47945981 -1.31315802 -0.44355220 0.42662110
[7] -0.30048898 0.03494274 1.19502267 1.75357250 -0.50578168 0.75617150
[13] -0.31528155 -1.21199672 1.11432860 0.88666127 0.64267710 -1.83987251
[19] 0.82399031 0.49078942 0.57442031 0.18128184 -0.41879204 0.38879048
[25] -1.77594524 -1.58922284 0.03986224 -0.63071160 0.34482561 -0.30415779
[31] -0.70574609 0.95682399 -0.36761650 1.49026425 0.54562399 -1.74631296
[37] 0.83634231 0.68951096 0.43386257 -0.42976091 0.28054092 1.13732050
[43] -0.90948394 1.56798606 0.30067433 0.10755312 0.76004583 1.40934015
[49] 0.28871591 0.45031675 -1.32004816 -0.05047722 0.84185185 -0.69396881
[55] 2.20685657 0.70099191 -0.76873918 -0.34911039 1.20995192 -1.56228925
[61] -0.33141540 -0.05642018 -0.48960698 1.13946114 0.36509672 1.46521312
[67] -0.48851479 0.20336354 -2.42138781 -1.41946713 -0.13281374 0.19966118
[73] -0.05450908 1.06234698 -0.58793904 0.24826220 -0.52699637 -2.32717665
[79] 1.71569579 -1.97518725 0.86822302 -1.01212263 0.60384020 -2.61514703
[85] 0.83402961 -0.04172977 0.14521953 -0.53676022 0.77573480 -0.14424903
[91] -0.06127010 -2.38399713 0.26946759 1.41954165 0.67356521 0.55386424
[97] -0.38770681 0.47422832 -0.18507908 1.17137230
> rowMin(tmp2)
[1] -0.01022310 1.26610360 -1.47945981 -1.31315802 -0.44355220 0.42662110
[7] -0.30048898 0.03494274 1.19502267 1.75357250 -0.50578168 0.75617150
[13] -0.31528155 -1.21199672 1.11432860 0.88666127 0.64267710 -1.83987251
[19] 0.82399031 0.49078942 0.57442031 0.18128184 -0.41879204 0.38879048
[25] -1.77594524 -1.58922284 0.03986224 -0.63071160 0.34482561 -0.30415779
[31] -0.70574609 0.95682399 -0.36761650 1.49026425 0.54562399 -1.74631296
[37] 0.83634231 0.68951096 0.43386257 -0.42976091 0.28054092 1.13732050
[43] -0.90948394 1.56798606 0.30067433 0.10755312 0.76004583 1.40934015
[49] 0.28871591 0.45031675 -1.32004816 -0.05047722 0.84185185 -0.69396881
[55] 2.20685657 0.70099191 -0.76873918 -0.34911039 1.20995192 -1.56228925
[61] -0.33141540 -0.05642018 -0.48960698 1.13946114 0.36509672 1.46521312
[67] -0.48851479 0.20336354 -2.42138781 -1.41946713 -0.13281374 0.19966118
[73] -0.05450908 1.06234698 -0.58793904 0.24826220 -0.52699637 -2.32717665
[79] 1.71569579 -1.97518725 0.86822302 -1.01212263 0.60384020 -2.61514703
[85] 0.83402961 -0.04172977 0.14521953 -0.53676022 0.77573480 -0.14424903
[91] -0.06127010 -2.38399713 0.26946759 1.41954165 0.67356521 0.55386424
[97] -0.38770681 0.47422832 -0.18507908 1.17137230
>
> colMeans(tmp2)
[1] 0.02101129
> colSums(tmp2)
[1] 2.101129
> colVars(tmp2)
[1] 1.039479
> colSd(tmp2)
[1] 1.019548
> colMax(tmp2)
[1] 2.206857
> colMin(tmp2)
[1] -2.615147
> colMedians(tmp2)
[1] 0.1632507
> colRanges(tmp2)
[,1]
[1,] -2.615147
[2,] 2.206857
>
> 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] 0.2078589 2.0536185 6.8005071 -4.3553128 -0.9322660 -1.8474596
[7] 2.1156484 -2.3898956 4.1550239 -2.6652659
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.4637658
[2,] -0.7999004
[3,] 0.3273019
[4,] 0.8165543
[5,] 1.1661191
>
> rowApply(tmp,sum)
[1] -5.0336843 9.8483373 2.8664785 -3.4927275 -4.1486161 0.3736274
[7] -0.9936058 2.0256994 -3.0184091 4.7153573
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 5 10 10 9 8 5 1 1 1
[2,] 3 2 3 7 4 7 10 9 7 6
[3,] 8 4 6 8 10 10 3 8 2 10
[4,] 1 3 9 2 5 3 4 3 10 4
[5,] 9 8 1 1 6 5 7 6 3 3
[6,] 5 9 4 9 1 1 1 7 4 7
[7,] 6 10 7 6 7 6 8 2 5 5
[8,] 4 1 5 5 8 4 6 4 6 2
[9,] 7 7 2 4 3 9 9 10 9 8
[10,] 2 6 8 3 2 2 2 5 8 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.3255885 -0.8178419 -1.0327301 -3.0583071 2.2904266 -2.2681721
[7] 1.2128761 -2.5426030 -0.4570467 4.1816229 -1.8703174 -1.7085677
[13] -0.6848687 1.5266017 -0.5848735 0.6198050 -1.8308135 0.2383953
[19] -0.8988167 1.2429390
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8125195
[2,] -0.7198117
[3,] 0.1595753
[4,] 0.2495661
[5,] 0.7976012
>
> rowApply(tmp,sum)
[1] -5.5179550 -3.1983820 -2.8176918 0.1758136 4.5903349
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 11 17 7 1 11
[2,] 14 2 10 9 18
[3,] 9 7 4 7 20
[4,] 3 9 6 4 14
[5,] 16 13 19 19 2
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.1595753 0.3719421 -0.1179483 -1.6221845 0.4975119 -1.752177722
[2,] 0.7976012 -1.5185584 -0.9059405 -0.6079725 0.3794879 -1.399322785
[3,] -0.7198117 -0.3106179 -0.8461616 -0.7216339 0.8037473 1.650726992
[4,] -0.8125195 -0.1807406 -0.2917042 -0.7009339 1.1834442 -0.762365840
[5,] 0.2495661 0.8201330 1.1290246 0.5944177 -0.5737647 -0.005032776
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.14856050 0.6955085 -1.5298376 0.39557794 -0.8129185 -1.7311191
[2,] 0.08514882 -1.4121876 0.7736501 3.17521711 -0.7155189 -1.4056409
[3,] 0.73805650 -1.0372818 0.5383114 0.07454112 0.6141724 0.2616766
[4,] 1.37684152 -0.6815951 -0.7362442 0.72892326 -0.6935500 0.5176905
[5,] 0.16138975 -0.1070471 0.4970736 -0.19263654 -0.2625024 0.6488252
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.497289620 0.3348396 0.50175239 0.6145321 0.3360375 1.0471933
[2,] 0.510826853 0.5976827 0.02448745 -0.1069636 -2.0735995 -1.0568051
[3,] 0.198182288 -0.7506188 -0.91659207 -1.1728430 0.2300433 -0.6000747
[4,] 0.105031932 0.6217744 -0.04901102 0.7425472 -0.0253516 -0.2728977
[5,] -0.001620114 0.7229238 -0.14551021 0.5425324 -0.2979432 1.1209794
[,19] [,20]
[1,] 0.1405790 -0.4009688
[2,] 0.8100523 0.8499734
[3,] -0.6309605 -0.2205537
[4,] -0.1470034 0.2534777
[5,] -1.0714842 0.7610104
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 648 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 562 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -2.365686 0.2691417 0.7800683 0.338067 0.6257509 -0.8872915 -0.1982044
col8 col9 col10 col11 col12 col13 col14
row1 -0.4691085 1.011228 -1.314819 0.9008923 -0.506821 1.407992 -0.2884159
col15 col16 col17 col18 col19 col20
row1 0.2422202 0.09279993 -0.5405115 -1.419508 0.9963242 0.2027389
> tmp[,"col10"]
col10
row1 -1.3148192
row2 0.1552078
row3 0.9912681
row4 0.8668237
row5 -0.3096323
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -2.365686 0.2691417 0.7800683 0.338067 0.62575087 -0.8872915 -0.1982044
row5 -2.100085 0.6123327 -0.2631436 -1.903289 0.08889803 0.5211006 1.7498930
col8 col9 col10 col11 col12 col13 col14
row1 -0.4691085 1.0112282 -1.3148192 0.9008923 -0.5068210 1.407992 -0.2884159
row5 -1.4906199 -0.2973667 -0.3096323 0.8921884 -0.1423818 -1.443162 0.6148848
col15 col16 col17 col18 col19 col20
row1 0.24222023 0.09279993 -0.5405115 -1.4195079 0.9963242 0.2027389
row5 -0.09412707 -0.82449367 0.7505116 0.6804979 2.0197736 -0.5944782
> tmp[,c("col6","col20")]
col6 col20
row1 -0.8872915 0.2027389
row2 1.5159921 0.6571866
row3 0.2785608 1.3942366
row4 1.5629696 -0.1176988
row5 0.5211006 -0.5944782
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.8872915 0.2027389
row5 0.5211006 -0.5944782
>
>
>
>
> 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 49.08813 47.56305 49.74202 51.39271 50.23475 105.6758 49.23634 49.70709
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.61384 48.66522 50.12748 49.02083 50.32391 49.21701 48.27327 49.73806
col17 col18 col19 col20
row1 48.53796 49.77679 49.41328 103.8276
> tmp[,"col10"]
col10
row1 48.66522
row2 28.91262
row3 30.21734
row4 29.08928
row5 50.10887
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.08813 47.56305 49.74202 51.39271 50.23475 105.6758 49.23634 49.70709
row5 50.24395 51.32610 48.69241 51.94575 48.42154 104.9492 48.74952 50.05354
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.61384 48.66522 50.12748 49.02083 50.32391 49.21701 48.27327 49.73806
row5 51.06769 50.10887 50.03745 51.46968 51.20483 48.28689 51.18177 50.69862
col17 col18 col19 col20
row1 48.53796 49.77679 49.41328 103.8276
row5 49.49829 50.67098 49.69859 104.5733
> tmp[,c("col6","col20")]
col6 col20
row1 105.67580 103.82761
row2 75.02685 73.18126
row3 74.56826 74.54908
row4 76.18628 74.89228
row5 104.94918 104.57332
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.6758 103.8276
row5 104.9492 104.5733
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.6758 103.8276
row5 104.9492 104.5733
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.85840929
[2,] -1.23049018
[3,] 0.36933557
[4,] -1.52473034
[5,] -0.05230805
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.33045950 -0.265563025
[2,] 0.30747524 -2.200669085
[3,] 0.49790781 -0.009795901
[4,] 0.02222497 0.015920721
[5,] 1.98924134 1.541340812
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.35107399 0.4845826
[2,] 0.76642566 -1.0121389
[3,] 0.08297385 1.2328201
[4,] -1.29173453 0.8989529
[5,] -0.77450016 -1.8668856
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.351074
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.3510740
[2,] 0.7664257
>
>
>
> 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 0.1939185 -1.077065 -0.5959391 0.3259884 0.8559003 -0.7963110
row1 -0.8353746 1.043154 0.5400920 -1.7335827 -0.5425364 -0.7291928
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 0.08018018 1.380588 -1.1987029 -1.539639 0.3598406 -0.1334915 -0.1645036
row1 0.09547424 -1.424377 0.3087725 0.264234 -0.8062518 0.1005812 -1.5678674
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.02045681 1.6143717 -0.3355208 -2.260788 -0.5971922 -1.008172
row1 1.38561454 -0.5931422 -1.3564702 -0.472816 2.0008644 1.496696
[,20]
row3 -0.2216022
row1 0.1637276
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.5342819 0.3332895 0.1822961 0.1953903 0.7950475 -1.109975 1.181113
[,8] [,9] [,10]
row2 -0.02045283 0.8874319 0.591714
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.7792645 0.9460392 -0.7228367 0.2035518 -1.082489 0.1305648 -0.6321148
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.771139 -0.6988548 0.9998773 0.9078679 0.8746148 0.7524547 -2.009933
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.491324 -0.3286114 1.16246 0.4154166 -1.130231 1.245682
>
>
> 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: 0x600000ff4120>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMcb5057e6603f"
[2] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMcb5055b8f52e"
[3] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMcb5061e8caf9"
[4] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMcb507a65d3a6"
[5] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMcb50332a7611"
[6] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMcb5028ad7055"
[7] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMcb5012a9f150"
[8] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMcb505321c4c2"
[9] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMcb504dfcc731"
[10] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMcb50e7989f7"
[11] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMcb504d50be8d"
[12] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMcb50700e42a2"
[13] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMcb503838d327"
[14] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMcb501aaec247"
[15] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMcb504754d100"
>
>
> ### 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: 0x600000ffc240>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600000ffc240>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600000ffc240>
> rowMedians(tmp)
[1] -0.257911207 0.238098673 -0.328736791 -0.221972316 -0.229584010
[6] -0.161747457 -0.060405469 0.398993190 -0.597865754 -0.005637593
[11] -0.244986109 0.120423014 -0.204958937 -0.148541134 0.010863434
[16] 0.120596478 -0.006289236 0.077630640 -0.168351535 0.236362374
[21] -0.324073880 -0.047292870 0.288773253 0.275478455 -0.895492001
[26] 0.265227372 -0.217023658 0.035166711 -0.088628258 -0.143029057
[31] -0.096672878 -0.489482437 -0.115185319 0.126291019 -0.100800608
[36] -0.357178316 0.108015495 -0.190952387 -0.056692423 -0.321559563
[41] -0.637872061 0.386214735 -0.190587155 -0.203767409 -0.045991939
[46] 0.200283113 -0.374331799 0.328007077 -0.166022373 0.403210387
[51] -0.111395040 0.031746358 -0.112602990 -0.058292491 -0.214280112
[56] 0.448346740 0.089253097 -0.569629641 0.168567488 -0.154091805
[61] -0.169844171 0.022098859 0.553854349 0.257759717 0.203238224
[66] -0.144257605 0.006770177 0.459335718 0.366164037 0.013407342
[71] -0.374288927 -0.016581503 0.477161324 -0.089335929 -0.119075353
[76] -0.866317996 -0.138796178 -0.406141451 -0.267216377 0.716123894
[81] 0.372042969 0.110436115 0.245716361 -0.545888180 0.034733446
[86] 0.093185038 0.189712102 -0.133100096 0.519894879 0.201102881
[91] -0.071493272 0.453305038 -0.060841229 0.378053041 0.681919646
[96] -0.652146588 -0.154464763 0.229420154 0.797087733 -0.142897900
[101] -0.075676983 0.127007108 -0.301624768 -0.569063286 -0.047560155
[106] 0.087412539 -0.089751734 0.047160358 -0.072526382 0.356644669
[111] 0.324321506 -0.309347345 -0.270079037 -0.166981480 -0.492426780
[116] 0.076105170 -0.299726041 0.051349933 0.361836108 -0.103764005
[121] -0.135485681 -0.298916550 0.201708505 0.029039934 -0.511226397
[126] 0.452193955 -0.327121089 -0.817285921 -0.666565828 0.182211980
[131] 0.250803407 0.663000297 -0.007999844 -0.262811632 -0.065276645
[136] -0.155561813 -0.341395927 -0.305477781 -0.220610334 0.495057751
[141] 0.188473004 0.468424153 0.136051863 0.196379046 -0.798014529
[146] -0.013984247 -0.312438734 0.406432145 0.124861901 0.017124516
[151] -0.143084100 0.043761588 0.446538930 -0.057755160 0.357890278
[156] 0.137566656 0.604880663 -0.383379864 -0.129587363 -0.077954941
[161] 0.176946380 0.448472634 -0.439691930 0.427433366 0.010114065
[166] 0.440472710 0.675878181 -0.032575405 0.230317432 0.175121743
[171] -0.155455782 -0.417440164 0.301961026 0.065534330 0.476713776
[176] 0.082281428 0.616416665 0.016125225 -0.331414783 0.253971530
[181] -0.201207769 0.431290356 -0.132612278 0.137054767 0.125585234
[186] -0.391287181 -0.063855850 0.583910736 -0.203871893 -0.023439456
[191] 0.461968266 0.107224796 0.218976341 0.063315412 -0.410639172
[196] 0.222774897 -0.627051306 -0.602482301 0.447034303 0.457303759
[201] 0.384015876 -0.290655415 0.798689175 0.351260541 -0.176632653
[206] -0.091063453 -0.084781804 -0.178445008 0.533835828 -0.141128465
[211] 0.251043967 0.029063322 0.888487102 -0.752008849 -0.106607469
[216] -0.094359368 0.324094219 -0.100255073 0.390345057 0.011568150
[221] -0.144252667 0.707728584 0.066042931 -0.231564709 -0.557611893
[226] 0.295836288 -0.080168195 0.485139382 0.087828028 -0.161258355
>
> proc.time()
user system elapsed
0.630 3.433 4.222
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x60000234c000>
> .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: 0x60000234c000>
> .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: 0x60000234c000>
> .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: 0x60000234c000>
> 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: 0x600002348540>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002348540>
> .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: 0x600002348540>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002348540>
> .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: 0x600002348540>
> 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: 0x600002350060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002350060>
> .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: 0x600002350060>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600002350060>
> .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: 0x600002350060>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600002350060>
> .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: 0x600002350060>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600002350060>
> .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: 0x600002350060>
> 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: 0x600002348780>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600002348780>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002348780>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002348780>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilece233c2b85f8" "BufferedMatrixFilece23401f22e3"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilece233c2b85f8" "BufferedMatrixFilece23401f22e3"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002348a20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002348a20>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600002348a20>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600002348a20>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600002348a20>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600002348a20>
> .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: 0x600002348c00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002348c00>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600002348c00>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600002348c00>
> 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: 0x600002348de0>
> .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: 0x600002348de0>
> rm(P)
>
> proc.time()
user system elapsed
0.110 0.042 0.148
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.107 0.028 0.139