Ben Bolstad
| Snapshot Date: 2025-01-28 13:40 -0500 (Tue, 28 Jan 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 824836d |
| git_last_commit_date: 2024-12-14 17:47:34 -0500 (Sat, 14 Dec 2024) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-01-29 11:45 -0500 (Wed, 29 Jan 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | R Under development (unstable) (2025-01-20 r87609) -- "Unsuffered Consequences" | 4661 |
| palomino7 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2025-01-21 r87610 ucrt) -- "Unsuffered Consequences" | 4457 |
| lconway | macOS 12.7.1 Monterey | x86_64 | R Under development (unstable) (2025-01-22 r87618) -- "Unsuffered Consequences" | 4468 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | R Under development (unstable) (2025-01-20 r87609) -- "Unsuffered Consequences" | 4421 |
| kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | R Under development (unstable) (2024-11-24 r87369) -- "Unsuffered Consequences" | 4411 |
| 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 246/2286 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.71.1 (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 22.03 LTS-SP1) / aarch64 | OK | OK | NA | ||||||||||
|
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: 1.71.1 |
| 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_1.71.1.tar.gz |
| StartedAt: 2025-01-28 18:17:05 -0500 (Tue, 28 Jan 2025) |
| EndedAt: 2025-01-28 18:17:21 -0500 (Tue, 28 Jan 2025) |
| EllapsedTime: 16.2 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_1.71.1.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2025-01-20 r87609)
* 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 ‘1.71.1’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... WARNING
Found the following significant warnings:
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
* used SDK: ‘MacOSX11.3.sdk’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 WARNING, 2 NOTEs
See
‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.71.1’
** 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 -Wl,-framework -Wl,CoreFoundation
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 Under development (unstable) (2025-01-20 r87609) -- "Unsuffered Consequences"
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
0.107 0.038 0.146
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2025-01-20 r87609) -- "Unsuffered Consequences"
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 480164 25.7 1054624 56.4 NA 634545 33.9
Vcells 889893 6.8 8388608 64.0 196608 2108497 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] "Tue Jan 28 18:17:14 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Jan 28 18:17:14 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: 0x600001558000>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Tue Jan 28 18:17:15 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Jan 28 18:17:15 2025"
>
> ColMode(tmp2)
<pointer: 0x600001558000>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 98.5465524 0.0335819 -0.02164245 -0.4417323
[2,] 1.0715497 -0.5196425 -0.94425846 1.5349757
[3,] -1.9598656 1.8819786 0.81984916 0.5014375
[4,] 0.8594649 0.5834446 -0.03852555 -1.8029567
> 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,] 98.5465524 0.0335819 0.02164245 0.4417323
[2,] 1.0715497 0.5196425 0.94425846 1.5349757
[3,] 1.9598656 1.8819786 0.81984916 0.5014375
[4,] 0.8594649 0.5834446 0.03852555 1.8029567
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9270616 0.1832537 0.1471137 0.6646294
[2,] 1.0351569 0.7208623 0.9717296 1.2389414
[3,] 1.3999520 1.3718522 0.9054552 0.7081225
[4,] 0.9270733 0.7638355 0.1962793 1.3427422
>
> 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,] 222.81717 26.86612 26.49278 32.08803
[2,] 36.42312 32.72827 35.66155 38.92439
[3,] 40.95939 40.60050 34.87440 32.58266
[4,] 35.13020 33.22180 27.00132 40.23038
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600001558060>
> exp(tmp5)
<pointer: 0x600001558060>
> log(tmp5,2)
<pointer: 0x600001558060>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 463.7647
> Min(tmp5)
[1] 55.01965
> mean(tmp5)
[1] 72.62579
> Sum(tmp5)
[1] 14525.16
> Var(tmp5)
[1] 843.8894
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 88.60853 71.19241 72.59736 70.13302 68.22627 69.21738 70.88857 71.51225
[9] 71.96855 71.91352
> rowSums(tmp5)
[1] 1772.171 1423.848 1451.947 1402.660 1364.525 1384.348 1417.771 1430.245
[9] 1439.371 1438.270
> rowVars(tmp5)
[1] 7907.64982 63.64128 72.53680 94.79819 69.11239 68.31166
[7] 42.54727 70.32580 56.73894 77.29785
> rowSd(tmp5)
[1] 88.924967 7.977548 8.516854 9.736436 8.313386 8.265087 6.522827
[8] 8.386048 7.532526 8.791919
> rowMax(tmp5)
[1] 463.76474 90.18853 86.95047 94.98470 82.64316 84.27327 84.58919
[8] 86.13561 87.23507 89.24149
> rowMin(tmp5)
[1] 55.10069 56.45696 59.98311 56.19971 55.01965 57.37564 60.13888 55.86071
[9] 59.69200 58.05472
>
> colMeans(tmp5)
[1] 113.09506 70.46977 67.73686 73.24919 64.52433 73.78120 69.86265
[8] 69.69120 66.52557 71.10677 68.01098 74.19121 72.95575 67.59796
[15] 69.66371 72.39592 71.02313 71.66244 73.38665 71.58536
> colSums(tmp5)
[1] 1130.9506 704.6977 677.3686 732.4919 645.2433 737.8120 698.6265
[8] 696.9120 665.2557 711.0677 680.1098 741.9121 729.5575 675.9796
[15] 696.6371 723.9592 710.2313 716.6244 733.8665 715.8536
> colVars(tmp5)
[1] 15236.67797 68.17541 68.08377 65.21905 44.11386 82.17265
[7] 32.05675 109.04473 57.40503 98.08867 45.73628 80.96789
[13] 102.14536 71.37188 86.93805 28.94225 46.66527 102.98688
[19] 105.93738 68.20766
> colSd(tmp5)
[1] 123.436939 8.256840 8.251289 8.075831 6.641826 9.064913
[7] 5.661868 10.442448 7.576611 9.903973 6.762860 8.998216
[13] 10.106699 8.448188 9.324058 5.379800 6.831198 10.148245
[19] 10.292589 8.258793
> colMax(tmp5)
[1] 463.76474 84.50462 81.23133 84.27327 75.37343 86.51613 76.49672
[8] 86.95047 81.83630 90.18853 79.33252 87.23507 89.24149 80.37940
[15] 86.13561 82.64316 85.18234 83.61377 94.98470 83.62850
> colMin(tmp5)
[1] 57.64371 55.91831 55.14125 64.79287 55.01965 61.30601 59.69200 57.05150
[9] 55.10069 55.86071 57.44079 61.23117 57.46264 56.45696 59.36429 64.51349
[17] 61.12369 59.98311 57.37564 57.49624
>
>
> ### 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] 88.60853 71.19241 72.59736 70.13302 68.22627 69.21738 NA 71.51225
[9] 71.96855 71.91352
> rowSums(tmp5)
[1] 1772.171 1423.848 1451.947 1402.660 1364.525 1384.348 NA 1430.245
[9] 1439.371 1438.270
> rowVars(tmp5)
[1] 7907.64982 63.64128 72.53680 94.79819 69.11239 68.31166
[7] 44.35749 70.32580 56.73894 77.29785
> rowSd(tmp5)
[1] 88.924967 7.977548 8.516854 9.736436 8.313386 8.265087 6.660142
[8] 8.386048 7.532526 8.791919
> rowMax(tmp5)
[1] 463.76474 90.18853 86.95047 94.98470 82.64316 84.27327 NA
[8] 86.13561 87.23507 89.24149
> rowMin(tmp5)
[1] 55.10069 56.45696 59.98311 56.19971 55.01965 57.37564 NA 55.86071
[9] 59.69200 58.05472
>
> colMeans(tmp5)
[1] 113.09506 70.46977 67.73686 73.24919 NA 73.78120 69.86265
[8] 69.69120 66.52557 71.10677 68.01098 74.19121 72.95575 67.59796
[15] 69.66371 72.39592 71.02313 71.66244 73.38665 71.58536
> colSums(tmp5)
[1] 1130.9506 704.6977 677.3686 732.4919 NA 737.8120 698.6265
[8] 696.9120 665.2557 711.0677 680.1098 741.9121 729.5575 675.9796
[15] 696.6371 723.9592 710.2313 716.6244 733.8665 715.8536
> colVars(tmp5)
[1] 15236.67797 68.17541 68.08377 65.21905 NA 82.17265
[7] 32.05675 109.04473 57.40503 98.08867 45.73628 80.96789
[13] 102.14536 71.37188 86.93805 28.94225 46.66527 102.98688
[19] 105.93738 68.20766
> colSd(tmp5)
[1] 123.436939 8.256840 8.251289 8.075831 NA 9.064913
[7] 5.661868 10.442448 7.576611 9.903973 6.762860 8.998216
[13] 10.106699 8.448188 9.324058 5.379800 6.831198 10.148245
[19] 10.292589 8.258793
> colMax(tmp5)
[1] 463.76474 84.50462 81.23133 84.27327 NA 86.51613 76.49672
[8] 86.95047 81.83630 90.18853 79.33252 87.23507 89.24149 80.37940
[15] 86.13561 82.64316 85.18234 83.61377 94.98470 83.62850
> colMin(tmp5)
[1] 57.64371 55.91831 55.14125 64.79287 NA 61.30601 59.69200 57.05150
[9] 55.10069 55.86071 57.44079 61.23117 57.46264 56.45696 59.36429 64.51349
[17] 61.12369 59.98311 57.37564 57.49624
>
> Max(tmp5,na.rm=TRUE)
[1] 463.7647
> Min(tmp5,na.rm=TRUE)
[1] 55.01965
> mean(tmp5,na.rm=TRUE)
[1] 72.64997
> Sum(tmp5,na.rm=TRUE)
[1] 14457.34
> Var(tmp5,na.rm=TRUE)
[1] 848.0338
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.60853 71.19241 72.59736 70.13302 68.22627 69.21738 71.05050 71.51225
[9] 71.96855 71.91352
> rowSums(tmp5,na.rm=TRUE)
[1] 1772.171 1423.848 1451.947 1402.660 1364.525 1384.348 1349.959 1430.245
[9] 1439.371 1438.270
> rowVars(tmp5,na.rm=TRUE)
[1] 7907.64982 63.64128 72.53680 94.79819 69.11239 68.31166
[7] 44.35749 70.32580 56.73894 77.29785
> rowSd(tmp5,na.rm=TRUE)
[1] 88.924967 7.977548 8.516854 9.736436 8.313386 8.265087 6.660142
[8] 8.386048 7.532526 8.791919
> rowMax(tmp5,na.rm=TRUE)
[1] 463.76474 90.18853 86.95047 94.98470 82.64316 84.27327 84.58919
[8] 86.13561 87.23507 89.24149
> rowMin(tmp5,na.rm=TRUE)
[1] 55.10069 56.45696 59.98311 56.19971 55.01965 57.37564 60.13888 55.86071
[9] 59.69200 58.05472
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.09506 70.46977 67.73686 73.24919 64.15903 73.78120 69.86265
[8] 69.69120 66.52557 71.10677 68.01098 74.19121 72.95575 67.59796
[15] 69.66371 72.39592 71.02313 71.66244 73.38665 71.58536
> colSums(tmp5,na.rm=TRUE)
[1] 1130.9506 704.6977 677.3686 732.4919 577.4313 737.8120 698.6265
[8] 696.9120 665.2557 711.0677 680.1098 741.9121 729.5575 675.9796
[15] 696.6371 723.9592 710.2313 716.6244 733.8665 715.8536
> colVars(tmp5,na.rm=TRUE)
[1] 15236.67797 68.17541 68.08377 65.21905 48.12686 82.17265
[7] 32.05675 109.04473 57.40503 98.08867 45.73628 80.96789
[13] 102.14536 71.37188 86.93805 28.94225 46.66527 102.98688
[19] 105.93738 68.20766
> colSd(tmp5,na.rm=TRUE)
[1] 123.436939 8.256840 8.251289 8.075831 6.937353 9.064913
[7] 5.661868 10.442448 7.576611 9.903973 6.762860 8.998216
[13] 10.106699 8.448188 9.324058 5.379800 6.831198 10.148245
[19] 10.292589 8.258793
> colMax(tmp5,na.rm=TRUE)
[1] 463.76474 84.50462 81.23133 84.27327 75.37343 86.51613 76.49672
[8] 86.95047 81.83630 90.18853 79.33252 87.23507 89.24149 80.37940
[15] 86.13561 82.64316 85.18234 83.61377 94.98470 83.62850
> colMin(tmp5,na.rm=TRUE)
[1] 57.64371 55.91831 55.14125 64.79287 55.01965 61.30601 59.69200 57.05150
[9] 55.10069 55.86071 57.44079 61.23117 57.46264 56.45696 59.36429 64.51349
[17] 61.12369 59.98311 57.37564 57.49624
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.60853 71.19241 72.59736 70.13302 68.22627 69.21738 NaN 71.51225
[9] 71.96855 71.91352
> rowSums(tmp5,na.rm=TRUE)
[1] 1772.171 1423.848 1451.947 1402.660 1364.525 1384.348 0.000 1430.245
[9] 1439.371 1438.270
> rowVars(tmp5,na.rm=TRUE)
[1] 7907.64982 63.64128 72.53680 94.79819 69.11239 68.31166
[7] NA 70.32580 56.73894 77.29785
> rowSd(tmp5,na.rm=TRUE)
[1] 88.924967 7.977548 8.516854 9.736436 8.313386 8.265087 NA
[8] 8.386048 7.532526 8.791919
> rowMax(tmp5,na.rm=TRUE)
[1] 463.76474 90.18853 86.95047 94.98470 82.64316 84.27327 NA
[8] 86.13561 87.23507 89.24149
> rowMin(tmp5,na.rm=TRUE)
[1] 55.10069 56.45696 59.98311 56.19971 55.01965 57.37564 NA 55.86071
[9] 59.69200 58.05472
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 117.56351 70.71535 68.58108 74.18878 NaN 72.58031 69.81406
[8] 69.29937 66.87369 71.37600 68.30792 73.56642 72.08230 66.85393
[15] 70.14550 72.12779 70.80569 72.74387 73.08371 71.50788
> colSums(tmp5,na.rm=TRUE)
[1] 1058.0716 636.4382 617.2297 667.6990 0.0000 653.2228 628.3265
[8] 623.6943 601.8632 642.3840 614.7712 662.0977 648.7407 601.6854
[15] 631.3095 649.1501 637.2512 654.6948 657.7533 643.5709
> colVars(tmp5,na.rm=TRUE)
[1] 16916.63322 76.01886 68.57628 63.43958 NA 76.22023
[7] 36.03728 120.94806 63.21726 109.53428 50.46136 86.69719
[13] 106.33075 74.06548 95.19399 31.75124 51.96650 102.70352
[19] 118.14707 76.66609
> colSd(tmp5,na.rm=TRUE)
[1] 130.063958 8.718879 8.281080 7.964897 NA 8.730420
[7] 6.003106 10.997639 7.950928 10.465863 7.103616 9.311132
[13] 10.311680 8.606130 9.756741 5.634824 7.208779 10.134274
[19] 10.869548 8.755917
> colMax(tmp5,na.rm=TRUE)
[1] 463.76474 84.50462 81.23133 84.27327 -Inf 86.51613 76.49672
[8] 86.95047 81.83630 90.18853 79.33252 87.23507 89.24149 80.37940
[15] 86.13561 82.64316 85.18234 83.61377 94.98470 83.62850
> colMin(tmp5,na.rm=TRUE)
[1] 57.64371 55.91831 55.14125 65.67866 Inf 61.30601 59.69200 57.05150
[9] 55.10069 55.86071 57.44079 61.23117 57.46264 56.45696 59.36429 64.51349
[17] 61.12369 59.98311 57.37564 57.49624
>
>
>
>
> 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] 303.4361 312.2885 173.6489 211.1899 317.6770 195.9067 225.1086 251.9159
[9] 216.8799 207.8217
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 303.4361 312.2885 173.6489 211.1899 317.6770 195.9067 225.1086 251.9159
[9] 216.8799 207.8217
>
>
>
> 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] -1.563194e-13 -1.705303e-13 -1.421085e-13 -5.684342e-14 5.684342e-14
[6] 0.000000e+00 5.684342e-14 -8.526513e-14 -9.947598e-14 -8.526513e-14
[11] -2.842171e-14 1.421085e-13 -3.410605e-13 -1.136868e-13 -5.684342e-14
[16] -1.278977e-13 -1.136868e-13 5.684342e-14 1.705303e-13 -9.947598e-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)
+ }
1 20
1 3
4 15
7 13
2 11
4 14
9 11
4 10
5 18
8 14
8 3
7 1
2 11
3 18
5 11
3 7
6 12
10 18
8 12
9 5
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] 2.61247
> Min(tmp)
[1] -2.25679
> mean(tmp)
[1] 0.007632558
> Sum(tmp)
[1] 0.7632558
> Var(tmp)
[1] 0.9588543
>
> rowMeans(tmp)
[1] 0.007632558
> rowSums(tmp)
[1] 0.7632558
> rowVars(tmp)
[1] 0.9588543
> rowSd(tmp)
[1] 0.9792111
> rowMax(tmp)
[1] 2.61247
> rowMin(tmp)
[1] -2.25679
>
> colMeans(tmp)
[1] -1.320498654 -1.345841248 0.489739069 0.278044209 -0.052064888
[6] 1.196690427 1.126534933 -0.052320969 1.554207872 0.034965921
[11] -0.382188981 -0.455107400 0.417595721 -0.182047362 -0.745151048
[16] 0.124144636 0.442016239 -0.281509136 0.537445724 0.871167050
[21] -0.137647419 -0.391461108 -0.173817863 -1.053350009 -0.383129714
[26] 1.041549197 0.602410220 -0.059661878 0.188461039 1.010398437
[31] 0.795327873 1.193493132 -0.359739327 -0.249495939 -1.679808120
[36] -1.834600625 1.433427012 -0.348902386 -1.679333446 0.272380286
[41] 0.803222622 -0.549819363 -0.064342562 -0.301704159 -0.006171285
[46] -0.780238647 0.757373870 -0.583024654 1.512774676 2.414018698
[51] 1.654173147 0.651835273 -0.919416006 0.807929218 -0.294666520
[56] -0.272203636 -0.709452417 -1.544700466 -1.076703858 -0.001339895
[61] 2.066246830 -0.556047495 0.611710292 -0.144970591 0.339988101
[66] -0.399474978 -1.318553282 0.287053231 0.116928575 1.120905796
[71] 0.612421386 1.218859342 0.575881051 0.936383149 0.211070584
[76] -1.469285848 -2.256790489 -0.468922967 0.607757921 2.612470382
[81] 0.570285758 -1.411350752 -0.753444835 -1.158314461 -1.584197788
[86] 0.170123024 0.964080116 -1.611113514 0.036988866 0.428298470
[91] 0.439186608 0.577621315 -0.433941491 1.272825717 -0.551963806
[96] -2.010825369 1.229017687 -1.062287036 -0.334857359 -0.656371851
> colSums(tmp)
[1] -1.320498654 -1.345841248 0.489739069 0.278044209 -0.052064888
[6] 1.196690427 1.126534933 -0.052320969 1.554207872 0.034965921
[11] -0.382188981 -0.455107400 0.417595721 -0.182047362 -0.745151048
[16] 0.124144636 0.442016239 -0.281509136 0.537445724 0.871167050
[21] -0.137647419 -0.391461108 -0.173817863 -1.053350009 -0.383129714
[26] 1.041549197 0.602410220 -0.059661878 0.188461039 1.010398437
[31] 0.795327873 1.193493132 -0.359739327 -0.249495939 -1.679808120
[36] -1.834600625 1.433427012 -0.348902386 -1.679333446 0.272380286
[41] 0.803222622 -0.549819363 -0.064342562 -0.301704159 -0.006171285
[46] -0.780238647 0.757373870 -0.583024654 1.512774676 2.414018698
[51] 1.654173147 0.651835273 -0.919416006 0.807929218 -0.294666520
[56] -0.272203636 -0.709452417 -1.544700466 -1.076703858 -0.001339895
[61] 2.066246830 -0.556047495 0.611710292 -0.144970591 0.339988101
[66] -0.399474978 -1.318553282 0.287053231 0.116928575 1.120905796
[71] 0.612421386 1.218859342 0.575881051 0.936383149 0.211070584
[76] -1.469285848 -2.256790489 -0.468922967 0.607757921 2.612470382
[81] 0.570285758 -1.411350752 -0.753444835 -1.158314461 -1.584197788
[86] 0.170123024 0.964080116 -1.611113514 0.036988866 0.428298470
[91] 0.439186608 0.577621315 -0.433941491 1.272825717 -0.551963806
[96] -2.010825369 1.229017687 -1.062287036 -0.334857359 -0.656371851
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] -1.320498654 -1.345841248 0.489739069 0.278044209 -0.052064888
[6] 1.196690427 1.126534933 -0.052320969 1.554207872 0.034965921
[11] -0.382188981 -0.455107400 0.417595721 -0.182047362 -0.745151048
[16] 0.124144636 0.442016239 -0.281509136 0.537445724 0.871167050
[21] -0.137647419 -0.391461108 -0.173817863 -1.053350009 -0.383129714
[26] 1.041549197 0.602410220 -0.059661878 0.188461039 1.010398437
[31] 0.795327873 1.193493132 -0.359739327 -0.249495939 -1.679808120
[36] -1.834600625 1.433427012 -0.348902386 -1.679333446 0.272380286
[41] 0.803222622 -0.549819363 -0.064342562 -0.301704159 -0.006171285
[46] -0.780238647 0.757373870 -0.583024654 1.512774676 2.414018698
[51] 1.654173147 0.651835273 -0.919416006 0.807929218 -0.294666520
[56] -0.272203636 -0.709452417 -1.544700466 -1.076703858 -0.001339895
[61] 2.066246830 -0.556047495 0.611710292 -0.144970591 0.339988101
[66] -0.399474978 -1.318553282 0.287053231 0.116928575 1.120905796
[71] 0.612421386 1.218859342 0.575881051 0.936383149 0.211070584
[76] -1.469285848 -2.256790489 -0.468922967 0.607757921 2.612470382
[81] 0.570285758 -1.411350752 -0.753444835 -1.158314461 -1.584197788
[86] 0.170123024 0.964080116 -1.611113514 0.036988866 0.428298470
[91] 0.439186608 0.577621315 -0.433941491 1.272825717 -0.551963806
[96] -2.010825369 1.229017687 -1.062287036 -0.334857359 -0.656371851
> colMin(tmp)
[1] -1.320498654 -1.345841248 0.489739069 0.278044209 -0.052064888
[6] 1.196690427 1.126534933 -0.052320969 1.554207872 0.034965921
[11] -0.382188981 -0.455107400 0.417595721 -0.182047362 -0.745151048
[16] 0.124144636 0.442016239 -0.281509136 0.537445724 0.871167050
[21] -0.137647419 -0.391461108 -0.173817863 -1.053350009 -0.383129714
[26] 1.041549197 0.602410220 -0.059661878 0.188461039 1.010398437
[31] 0.795327873 1.193493132 -0.359739327 -0.249495939 -1.679808120
[36] -1.834600625 1.433427012 -0.348902386 -1.679333446 0.272380286
[41] 0.803222622 -0.549819363 -0.064342562 -0.301704159 -0.006171285
[46] -0.780238647 0.757373870 -0.583024654 1.512774676 2.414018698
[51] 1.654173147 0.651835273 -0.919416006 0.807929218 -0.294666520
[56] -0.272203636 -0.709452417 -1.544700466 -1.076703858 -0.001339895
[61] 2.066246830 -0.556047495 0.611710292 -0.144970591 0.339988101
[66] -0.399474978 -1.318553282 0.287053231 0.116928575 1.120905796
[71] 0.612421386 1.218859342 0.575881051 0.936383149 0.211070584
[76] -1.469285848 -2.256790489 -0.468922967 0.607757921 2.612470382
[81] 0.570285758 -1.411350752 -0.753444835 -1.158314461 -1.584197788
[86] 0.170123024 0.964080116 -1.611113514 0.036988866 0.428298470
[91] 0.439186608 0.577621315 -0.433941491 1.272825717 -0.551963806
[96] -2.010825369 1.229017687 -1.062287036 -0.334857359 -0.656371851
> colMedians(tmp)
[1] -1.320498654 -1.345841248 0.489739069 0.278044209 -0.052064888
[6] 1.196690427 1.126534933 -0.052320969 1.554207872 0.034965921
[11] -0.382188981 -0.455107400 0.417595721 -0.182047362 -0.745151048
[16] 0.124144636 0.442016239 -0.281509136 0.537445724 0.871167050
[21] -0.137647419 -0.391461108 -0.173817863 -1.053350009 -0.383129714
[26] 1.041549197 0.602410220 -0.059661878 0.188461039 1.010398437
[31] 0.795327873 1.193493132 -0.359739327 -0.249495939 -1.679808120
[36] -1.834600625 1.433427012 -0.348902386 -1.679333446 0.272380286
[41] 0.803222622 -0.549819363 -0.064342562 -0.301704159 -0.006171285
[46] -0.780238647 0.757373870 -0.583024654 1.512774676 2.414018698
[51] 1.654173147 0.651835273 -0.919416006 0.807929218 -0.294666520
[56] -0.272203636 -0.709452417 -1.544700466 -1.076703858 -0.001339895
[61] 2.066246830 -0.556047495 0.611710292 -0.144970591 0.339988101
[66] -0.399474978 -1.318553282 0.287053231 0.116928575 1.120905796
[71] 0.612421386 1.218859342 0.575881051 0.936383149 0.211070584
[76] -1.469285848 -2.256790489 -0.468922967 0.607757921 2.612470382
[81] 0.570285758 -1.411350752 -0.753444835 -1.158314461 -1.584197788
[86] 0.170123024 0.964080116 -1.611113514 0.036988866 0.428298470
[91] 0.439186608 0.577621315 -0.433941491 1.272825717 -0.551963806
[96] -2.010825369 1.229017687 -1.062287036 -0.334857359 -0.656371851
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.320499 -1.345841 0.4897391 0.2780442 -0.05206489 1.19669 1.126535
[2,] -1.320499 -1.345841 0.4897391 0.2780442 -0.05206489 1.19669 1.126535
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.05232097 1.554208 0.03496592 -0.382189 -0.4551074 0.4175957 -0.1820474
[2,] -0.05232097 1.554208 0.03496592 -0.382189 -0.4551074 0.4175957 -0.1820474
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.745151 0.1241446 0.4420162 -0.2815091 0.5374457 0.8711671 -0.1376474
[2,] -0.745151 0.1241446 0.4420162 -0.2815091 0.5374457 0.8711671 -0.1376474
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.3914611 -0.1738179 -1.05335 -0.3831297 1.041549 0.6024102 -0.05966188
[2,] -0.3914611 -0.1738179 -1.05335 -0.3831297 1.041549 0.6024102 -0.05966188
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.188461 1.010398 0.7953279 1.193493 -0.3597393 -0.2494959 -1.679808
[2,] 0.188461 1.010398 0.7953279 1.193493 -0.3597393 -0.2494959 -1.679808
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.834601 1.433427 -0.3489024 -1.679333 0.2723803 0.8032226 -0.5498194
[2,] -1.834601 1.433427 -0.3489024 -1.679333 0.2723803 0.8032226 -0.5498194
[,43] [,44] [,45] [,46] [,47] [,48]
[1,] -0.06434256 -0.3017042 -0.006171285 -0.7802386 0.7573739 -0.5830247
[2,] -0.06434256 -0.3017042 -0.006171285 -0.7802386 0.7573739 -0.5830247
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] 1.512775 2.414019 1.654173 0.6518353 -0.919416 0.8079292 -0.2946665
[2,] 1.512775 2.414019 1.654173 0.6518353 -0.919416 0.8079292 -0.2946665
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.2722036 -0.7094524 -1.5447 -1.076704 -0.001339895 2.066247 -0.5560475
[2,] -0.2722036 -0.7094524 -1.5447 -1.076704 -0.001339895 2.066247 -0.5560475
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 0.6117103 -0.1449706 0.3399881 -0.399475 -1.318553 0.2870532 0.1169286
[2,] 0.6117103 -0.1449706 0.3399881 -0.399475 -1.318553 0.2870532 0.1169286
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 1.120906 0.6124214 1.218859 0.5758811 0.9363831 0.2110706 -1.469286
[2,] 1.120906 0.6124214 1.218859 0.5758811 0.9363831 0.2110706 -1.469286
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -2.25679 -0.468923 0.6077579 2.61247 0.5702858 -1.411351 -0.7534448
[2,] -2.25679 -0.468923 0.6077579 2.61247 0.5702858 -1.411351 -0.7534448
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -1.158314 -1.584198 0.170123 0.9640801 -1.611114 0.03698887 0.4282985
[2,] -1.158314 -1.584198 0.170123 0.9640801 -1.611114 0.03698887 0.4282985
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 0.4391866 0.5776213 -0.4339415 1.272826 -0.5519638 -2.010825 1.229018
[2,] 0.4391866 0.5776213 -0.4339415 1.272826 -0.5519638 -2.010825 1.229018
[,98] [,99] [,100]
[1,] -1.062287 -0.3348574 -0.6563719
[2,] -1.062287 -0.3348574 -0.6563719
>
>
> Max(tmp2)
[1] 3.188366
> Min(tmp2)
[1] -2.307085
> mean(tmp2)
[1] -0.1241384
> Sum(tmp2)
[1] -12.41384
> Var(tmp2)
[1] 1.315937
>
> rowMeans(tmp2)
[1] 0.07991978 0.83000594 -1.29150697 0.96796593 0.47750802 -0.14094799
[7] -1.46199638 -1.39601377 -1.11167320 -1.57697953 0.02961655 -0.38646581
[13] -0.92856735 0.38099421 2.31827482 -1.43604047 0.14513230 -0.26112307
[19] 0.61323730 -1.88199018 -1.60791271 2.57510973 0.81501112 -0.78400983
[25] -0.86790522 -0.75857933 1.47678361 -1.73060759 -0.16429173 -0.76875188
[31] 0.23932153 -0.04868111 -0.13928327 -0.44875324 0.32672838 -1.31411894
[37] -0.56400328 -0.46637234 -0.30849755 0.66185838 -0.42292952 1.59695169
[43] 0.12931651 0.73379384 -0.90333712 -0.33132429 0.87196687 0.29477152
[49] -0.66506321 3.18836648 0.83121659 0.89254654 -0.56778974 0.54176483
[55] 1.07352621 1.43571262 0.88348888 1.29758147 -1.59073859 -0.37530177
[61] -1.89290095 -1.09986930 -1.29743758 -1.39775872 -0.46381241 -1.77004645
[67] -0.17416663 0.33582067 -0.30682527 -0.32701763 -1.35379141 -0.18969116
[73] 1.75017183 -0.31373773 2.13279952 -1.78669863 1.07771933 0.52401669
[79] -0.55656105 -1.45614055 0.80241015 -1.17825655 -0.49642243 0.51494719
[85] -1.52071879 1.03746582 0.78540789 -0.56543059 1.27839518 -0.27362945
[91] -2.30708476 -0.27684423 1.51655008 -2.09764554 0.32771762 -1.77255854
[97] 1.99181335 1.38737051 -1.41979293 -0.58852115
> rowSums(tmp2)
[1] 0.07991978 0.83000594 -1.29150697 0.96796593 0.47750802 -0.14094799
[7] -1.46199638 -1.39601377 -1.11167320 -1.57697953 0.02961655 -0.38646581
[13] -0.92856735 0.38099421 2.31827482 -1.43604047 0.14513230 -0.26112307
[19] 0.61323730 -1.88199018 -1.60791271 2.57510973 0.81501112 -0.78400983
[25] -0.86790522 -0.75857933 1.47678361 -1.73060759 -0.16429173 -0.76875188
[31] 0.23932153 -0.04868111 -0.13928327 -0.44875324 0.32672838 -1.31411894
[37] -0.56400328 -0.46637234 -0.30849755 0.66185838 -0.42292952 1.59695169
[43] 0.12931651 0.73379384 -0.90333712 -0.33132429 0.87196687 0.29477152
[49] -0.66506321 3.18836648 0.83121659 0.89254654 -0.56778974 0.54176483
[55] 1.07352621 1.43571262 0.88348888 1.29758147 -1.59073859 -0.37530177
[61] -1.89290095 -1.09986930 -1.29743758 -1.39775872 -0.46381241 -1.77004645
[67] -0.17416663 0.33582067 -0.30682527 -0.32701763 -1.35379141 -0.18969116
[73] 1.75017183 -0.31373773 2.13279952 -1.78669863 1.07771933 0.52401669
[79] -0.55656105 -1.45614055 0.80241015 -1.17825655 -0.49642243 0.51494719
[85] -1.52071879 1.03746582 0.78540789 -0.56543059 1.27839518 -0.27362945
[91] -2.30708476 -0.27684423 1.51655008 -2.09764554 0.32771762 -1.77255854
[97] 1.99181335 1.38737051 -1.41979293 -0.58852115
> 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] 0.07991978 0.83000594 -1.29150697 0.96796593 0.47750802 -0.14094799
[7] -1.46199638 -1.39601377 -1.11167320 -1.57697953 0.02961655 -0.38646581
[13] -0.92856735 0.38099421 2.31827482 -1.43604047 0.14513230 -0.26112307
[19] 0.61323730 -1.88199018 -1.60791271 2.57510973 0.81501112 -0.78400983
[25] -0.86790522 -0.75857933 1.47678361 -1.73060759 -0.16429173 -0.76875188
[31] 0.23932153 -0.04868111 -0.13928327 -0.44875324 0.32672838 -1.31411894
[37] -0.56400328 -0.46637234 -0.30849755 0.66185838 -0.42292952 1.59695169
[43] 0.12931651 0.73379384 -0.90333712 -0.33132429 0.87196687 0.29477152
[49] -0.66506321 3.18836648 0.83121659 0.89254654 -0.56778974 0.54176483
[55] 1.07352621 1.43571262 0.88348888 1.29758147 -1.59073859 -0.37530177
[61] -1.89290095 -1.09986930 -1.29743758 -1.39775872 -0.46381241 -1.77004645
[67] -0.17416663 0.33582067 -0.30682527 -0.32701763 -1.35379141 -0.18969116
[73] 1.75017183 -0.31373773 2.13279952 -1.78669863 1.07771933 0.52401669
[79] -0.55656105 -1.45614055 0.80241015 -1.17825655 -0.49642243 0.51494719
[85] -1.52071879 1.03746582 0.78540789 -0.56543059 1.27839518 -0.27362945
[91] -2.30708476 -0.27684423 1.51655008 -2.09764554 0.32771762 -1.77255854
[97] 1.99181335 1.38737051 -1.41979293 -0.58852115
> rowMin(tmp2)
[1] 0.07991978 0.83000594 -1.29150697 0.96796593 0.47750802 -0.14094799
[7] -1.46199638 -1.39601377 -1.11167320 -1.57697953 0.02961655 -0.38646581
[13] -0.92856735 0.38099421 2.31827482 -1.43604047 0.14513230 -0.26112307
[19] 0.61323730 -1.88199018 -1.60791271 2.57510973 0.81501112 -0.78400983
[25] -0.86790522 -0.75857933 1.47678361 -1.73060759 -0.16429173 -0.76875188
[31] 0.23932153 -0.04868111 -0.13928327 -0.44875324 0.32672838 -1.31411894
[37] -0.56400328 -0.46637234 -0.30849755 0.66185838 -0.42292952 1.59695169
[43] 0.12931651 0.73379384 -0.90333712 -0.33132429 0.87196687 0.29477152
[49] -0.66506321 3.18836648 0.83121659 0.89254654 -0.56778974 0.54176483
[55] 1.07352621 1.43571262 0.88348888 1.29758147 -1.59073859 -0.37530177
[61] -1.89290095 -1.09986930 -1.29743758 -1.39775872 -0.46381241 -1.77004645
[67] -0.17416663 0.33582067 -0.30682527 -0.32701763 -1.35379141 -0.18969116
[73] 1.75017183 -0.31373773 2.13279952 -1.78669863 1.07771933 0.52401669
[79] -0.55656105 -1.45614055 0.80241015 -1.17825655 -0.49642243 0.51494719
[85] -1.52071879 1.03746582 0.78540789 -0.56543059 1.27839518 -0.27362945
[91] -2.30708476 -0.27684423 1.51655008 -2.09764554 0.32771762 -1.77255854
[97] 1.99181335 1.38737051 -1.41979293 -0.58852115
>
> colMeans(tmp2)
[1] -0.1241384
> colSums(tmp2)
[1] -12.41384
> colVars(tmp2)
[1] 1.315937
> colSd(tmp2)
[1] 1.147143
> colMax(tmp2)
[1] 3.188366
> colMin(tmp2)
[1] -2.307085
> colMedians(tmp2)
[1] -0.2752368
> colRanges(tmp2)
[,1]
[1,] -2.307085
[2,] 3.188366
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.369080 3.430698 -5.306587 3.883559 2.091573 -1.173246 4.524237
[8] 4.293726 3.917954 2.443112
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.62929018
[2,] -0.38189172
[3,] -0.07715158
[4,] 0.32518228
[5,] 1.19959887
>
> rowApply(tmp,sum)
[1] -3.23033200 -0.67225716 3.40753737 2.35049799 -0.05388669 1.72928885
[7] 2.40453782 1.74913353 5.78654290 2.26488417
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 6 1 2 5 1 7 7 2 7
[2,] 8 4 4 6 1 7 9 2 10 9
[3,] 1 1 2 8 10 2 2 1 3 6
[4,] 4 3 6 9 9 8 8 9 6 1
[5,] 6 2 9 1 7 6 4 6 5 10
[6,] 2 9 3 7 2 3 3 4 7 3
[7,] 7 5 7 4 8 10 5 5 9 2
[8,] 3 10 8 3 4 9 6 8 4 8
[9,] 5 7 5 10 6 5 1 10 8 4
[10,] 9 8 10 5 3 4 10 3 1 5
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.022793928 -1.137348856 -0.472405743 -1.982603004 -0.801030046
[6] -0.927622716 -2.683658404 0.002022831 0.359887502 -3.041735108
[11] 0.895378516 0.738870467 0.623145075 3.960997439 2.413396088
[16] -5.049601661 0.313230678 -1.968525054 0.988539278 -0.522486385
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8537860
[2,] -1.3001182
[3,] -0.6409353
[4,] 0.5587960
[5,] 1.2132496
>
> rowApply(tmp,sum)
[1] 0.09834475 1.27862633 -2.65194611 -1.32116733 -7.71820068
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 15 3 1 5 18
[2,] 1 13 19 13 17
[3,] 3 18 12 11 11
[4,] 10 10 13 4 4
[5,] 7 5 8 12 16
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.5587960 -3.8656908 -1.15188474 0.03168413 -0.1880677 0.4989538
[2,] -1.3001182 0.3211578 1.17730517 -0.07431034 -0.5581782 -0.8564247
[3,] -1.8537860 1.3513686 -0.05130622 0.17658637 -0.5907659 0.1945991
[4,] -0.6409353 0.1347400 -0.08487868 -0.74903317 0.0659241 0.2655385
[5,] 1.2132496 0.9210756 -0.36164128 -1.36752999 0.4700576 -1.0302894
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.02046845 0.05443147 -0.6098140 -1.4174922 0.03356372 1.2006047
[2,] -2.40521918 0.62668971 1.9200364 -0.4608048 0.13277457 -1.3568623
[3,] -1.22802057 -1.30201074 0.3535012 -0.7328968 1.28856537 0.9837206
[4,] 0.91759103 -1.29329272 1.6383156 0.2210444 -2.15572664 0.9458597
[5,] 0.01152187 1.91620510 -2.9421516 -0.6515857 1.59620149 -1.0344523
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.03994438 2.6668700 1.4014995 -0.9587442 0.9035256 -0.6369067
[2,] 0.36083826 2.3884970 1.1601222 -0.1985954 -0.2970644 -0.4045783
[3,] -1.34262276 -1.1446375 1.8860828 -1.1084644 -0.1323118 -0.3635290
[4,] 2.54227992 -0.3838871 -0.2010751 -0.3869316 0.5441870 -0.3348945
[5,] -0.89740596 0.4341551 -1.8332333 -2.3968661 -0.7051057 -0.2286166
[,19] [,20]
[1,] 1.5602012 0.03629104
[2,] 0.9486417 0.15471928
[3,] 1.0430561 -0.07907439
[4,] -1.9023231 -0.46366967
[5,] -0.6610366 -0.17075265
>
>
> 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 : 649 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-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 -1.385425 -0.1716423 0.1364533 0.2819179 0.4370747 -0.3664235 -0.6417135
col8 col9 col10 col11 col12 col13 col14
row1 1.801097 0.6013345 -0.2693625 0.2261523 1.373418 1.227527 1.803251
col15 col16 col17 col18 col19 col20
row1 -1.770925 1.700097 -0.4066465 0.5926209 -0.09411033 -0.4851058
> tmp[,"col10"]
col10
row1 -0.2693625
row2 0.2349367
row3 -1.2466602
row4 -1.1709680
row5 0.8776646
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -1.385425 -0.17164231 0.1364533 0.2819179 0.4370747 -0.3664235 -0.6417135
row5 2.225967 0.03722004 0.2013387 0.2294714 -1.7231991 0.6008053 -0.1142825
col8 col9 col10 col11 col12 col13 col14
row1 1.8010969 0.60133446 -0.2693625 0.2261523 1.3734178 1.227527 1.8032505
row5 0.9602453 0.01568393 0.8776646 -0.3421731 0.4092815 -1.943257 -0.2725502
col15 col16 col17 col18 col19 col20
row1 -1.7709247 1.700097 -0.4066465 0.5926209 -0.09411033 -0.4851058
row5 -0.7797115 -0.149051 -1.0831307 -0.8892142 0.44742803 -0.7907540
> tmp[,c("col6","col20")]
col6 col20
row1 -0.3664235 -0.4851058
row2 -0.1606247 1.4069260
row3 1.1945699 -0.5842737
row4 -0.2413358 0.5599870
row5 0.6008053 -0.7907540
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.3664235 -0.4851058
row5 0.6008053 -0.7907540
>
>
>
>
> 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 49.6924 50.79541 49.20875 49.49961 48.99185 104.4603 52.57234 49.9752
col9 col10 col11 col12 col13 col14 col15 col16
row1 46.95446 48.71996 49.15057 49.44799 49.52978 49.43422 51.768 49.30249
col17 col18 col19 col20
row1 48.75638 49.12953 50.19268 102.2846
> tmp[,"col10"]
col10
row1 48.71996
row2 30.12237
row3 29.10126
row4 30.95430
row5 51.39014
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.69240 50.79541 49.20875 49.49961 48.99185 104.4603 52.57234 49.97520
row5 50.21457 50.52943 50.61208 48.39973 51.13495 103.6731 48.57023 51.61342
col9 col10 col11 col12 col13 col14 col15 col16
row1 46.95446 48.71996 49.15057 49.44799 49.52978 49.43422 51.76800 49.30249
row5 49.63610 51.39014 49.24448 49.57135 48.94897 51.10932 48.56255 51.12991
col17 col18 col19 col20
row1 48.75638 49.12953 50.19268 102.2846
row5 49.68212 49.96477 49.49480 104.6175
> tmp[,c("col6","col20")]
col6 col20
row1 104.46027 102.28463
row2 73.99027 75.57958
row3 76.48316 76.23163
row4 74.68624 74.54619
row5 103.67305 104.61747
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.4603 102.2846
row5 103.6731 104.6175
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.4603 102.2846
row5 103.6731 104.6175
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.3046810
[2,] 1.7368437
[3,] -0.7598609
[4,] -1.4247584
[5,] 1.5601835
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.8292983 -0.6189964
[2,] 0.7344583 -0.4562643
[3,] 0.9717712 -0.2501536
[4,] 1.5457160 3.7329134
[5,] 0.2670014 -0.8309683
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.27998390 -0.8174959
[2,] 0.04789242 1.4235026
[3,] 0.75797217 -0.8389043
[4,] -0.17329296 -1.5049095
[5,] -1.17830361 1.5586333
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.2799839
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.27998390
[2,] 0.04789242
>
>
>
> 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] [,7]
row3 0.7918773 0.9165954 0.5707198 0.6797104 1.6789293 -0.8504034 -1.6207516
row1 0.2109500 0.1972051 -0.3604360 -0.7128864 -0.5849061 -1.1389788 0.8486393
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 1.5955895 -0.2022587 1.5986692 -0.9690434 0.1847973 -2.4460954 -0.4897318
row1 -0.1039295 2.1208611 0.8721737 -0.7108975 0.1920437 -0.7023691 -1.1362437
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.3211005 0.4432477 -1.1679042 0.36699021 1.3315376 -0.6421317
row1 0.6894406 -2.0495018 -0.9556854 -0.03876442 0.1292649 -0.8266629
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.125854 -0.9200404 -2.010106 -1.193106 0.6456329 0.7335845 0.3122092
[,8] [,9] [,10]
row2 0.5923875 -1.390077 -1.864427
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.551252 0.3814271 1.097267 0.7305085 -0.7416617 -0.2057475 -0.5909107
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.380822 -0.06411718 0.3953108 0.2655646 0.02808619 -1.014643 -0.6926293
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.855655 -0.09641569 0.2081538 -0.4892805 0.4461708 0.1225252
>
>
> 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: 0x600001568000>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM795a4d871dda"
[2] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM795a61b8faf9"
[3] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM795a3765238e"
[4] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM795a51015c0b"
[5] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM795a3041ffb9"
[6] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM795a3cfbe36f"
[7] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM795a3d10abb0"
[8] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM795a1177cf22"
[9] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM795a50bfca23"
[10] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM795a5f6fe93f"
[11] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM795a2c3a580c"
[12] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM795a2a6a9283"
[13] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM795a3ab8ec36"
[14] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM795a429beb58"
[15] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM795aa780092"
>
>
> ### 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: 0x60000156c180>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x60000156c180>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x60000156c180>
> rowMedians(tmp)
[1] 0.1515228343 0.0814741796 0.2567696722 0.7890600135 -0.1227527292
[6] 0.2127996192 0.0345935198 0.4709720008 0.0917678564 -0.4177211070
[11] 0.2048936488 -0.2186182985 -0.2085633360 -0.0389303313 -0.5688128567
[16] -0.0219787469 -0.0969490541 -0.2242418400 0.6155761910 -0.1343972196
[21] 0.2221411932 0.4664593493 -0.2738672596 -0.4279056563 -0.0096304316
[26] -0.2169155673 0.4684379698 -0.4316212708 -0.0375710729 0.0868785777
[31] -0.3864577053 -0.3984390737 0.0061044112 0.2221837851 0.4978058007
[36] -0.0687654488 0.5268889040 0.4820785366 -0.1169443272 0.0423133904
[41] 0.5381203336 0.0719967700 0.2709537095 0.2284612668 -0.1778436572
[46] -0.0767310744 0.1295984320 -0.5746944870 0.3810716300 0.2602714542
[51] -0.0097637173 0.2299219009 0.2333721723 -0.0879332345 0.2015322531
[56] -0.0050697342 0.0195338542 0.1191116236 -0.2310392135 -0.1696311668
[61] -0.3160072182 0.4901431346 0.2626909055 -0.0074845598 -0.1298090056
[66] 0.2041701432 -0.0315548834 -0.0347835680 -0.0818509541 0.0373947598
[71] 0.3292450442 -0.0654109051 -0.5015307477 0.2879438745 -0.4230472630
[76] -0.4231866284 0.1552635187 -0.0499649393 0.5027706975 -0.0043817689
[81] 0.2589269184 -0.5025612375 -0.4145339526 0.3775531007 -0.4623716666
[86] -0.1960067753 -0.9316862124 -0.1976497402 -0.1196587979 -0.2370465961
[91] 0.0093754657 0.3596935341 -0.1716611387 -0.1182044495 0.0969653037
[96] -0.0154479836 0.0408943315 -0.2231205630 0.3295035763 -0.4221000004
[101] 0.1142557196 -0.0472451890 -0.1549457064 0.2473410601 0.1281311152
[106] 0.1440266943 -0.2830958672 0.2398303897 -0.0644692134 -0.0161550780
[111] 0.1535132376 -0.3113333567 -0.2798658169 -0.1742486416 -0.0381488085
[116] -0.2682023422 -0.5174879483 0.3080775600 -0.1888463454 0.1992180057
[121] -0.5893281953 -0.4030997438 -0.3914865161 -0.0946977012 0.0545476536
[126] -0.3106037083 0.1404518339 -0.1360537911 -0.0796009650 -0.1089988031
[131] -0.2115525348 0.0625437406 0.0455979985 -0.4402565873 0.0727717618
[136] 0.3639362015 -0.1641960022 -0.2480863425 0.8339963572 -0.1789470106
[141] 0.2193982504 0.3043964713 -0.0236497600 0.3435326425 0.1262926547
[146] -0.1849941023 -0.4374044754 0.6021799305 -0.1164660793 -0.2469093703
[151] 0.0102327685 -0.0724051552 -0.3298758978 -0.0107807894 0.0926680576
[156] 0.3442945319 0.2519041992 -0.1211336818 -0.5418512458 -0.2029140515
[161] -0.2697448891 0.1005504657 0.0737357171 -0.5323913893 -0.1833642520
[166] 0.0412251778 -0.0277421581 0.0554170310 0.4802201958 -0.0206820560
[171] -0.0125743856 0.2016463427 -0.5874366737 -0.1951458562 0.4052349140
[176] -0.3997158568 0.4987170464 -0.3286482228 0.3939871313 0.3472901124
[181] 0.1397307472 0.1841642403 0.4431981481 0.0974549371 0.3860233917
[186] 0.0400247065 0.1450947594 -0.3910024418 -0.3608988083 0.7228290289
[191] 0.1596685941 0.2990696973 0.0431672562 0.0294896757 0.1707296560
[196] 0.1808480859 0.5087465400 -0.1968188049 0.3047239788 0.1665237531
[201] -0.1239041026 0.3296910397 0.0811728018 0.0752346075 -0.4069471696
[206] 0.2478436503 -0.6093173689 0.3058387057 -0.1221241113 -0.2966148624
[211] 0.1479149394 -0.6322836931 0.1031213764 0.0511232453 -0.0458889912
[216] 0.0570700591 0.0754529524 0.3244330965 -0.1281117736 0.3509396362
[221] -0.0005368762 -0.3050014606 0.1120358935 0.0722663188 0.0927789982
[226] 0.0678960656 -0.2879344883 0.3423816900 -0.2000267355 0.3260158462
>
> proc.time()
user system elapsed
0.637 3.161 3.966
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2025-01-20 r87609) -- "Unsuffered Consequences"
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: 0x6000024e4000>
> .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: 0x6000024e4000>
> .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: 0x6000024e4000>
> .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: 0x6000024e4000>
> 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: 0x6000024d4540>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000024d4540>
> .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: 0x6000024d4540>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000024d4540>
> .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: 0x6000024d4540>
> 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: 0x6000024d4720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000024d4720>
> .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: 0x6000024d4720>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000024d4720>
> .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: 0x6000024d4720>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000024d4720>
> .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: 0x6000024d4720>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000024d4720>
> .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: 0x6000024d4720>
> 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: 0x6000024c03c0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000024c03c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000024c03c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000024c03c0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile7a8e4bc70704" "BufferedMatrixFile7a8e779dbe79"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile7a8e4bc70704" "BufferedMatrixFile7a8e779dbe79"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000024c0660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000024c0660>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000024c0660>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000024c0660>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000024c0660>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000024c0660>
> .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: 0x6000024c0840>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000024c0840>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000024c0840>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000024c0840>
> 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: 0x6000024e8060>
> .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: 0x6000024e8060>
> rm(P)
>
> proc.time()
user system elapsed
0.112 0.042 0.155
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-01-20 r87609) -- "Unsuffered Consequences"
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
0.114 0.027 0.142