Ben Bolstad
| Snapshot Date: 2025-02-03 13:00 -0500 (Mon, 03 Feb 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_20 |
| git_last_commit: 32b6f6a |
| git_last_commit_date: 2024-10-29 09:27:20 -0500 (Tue, 29 Oct 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2025-02-06 12:09 -0500 (Thu, 06 Feb 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4753 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves" | 4501 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4524 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4476 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4407 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 251/2289 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.70.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.70.0 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.70.0.tar.gz |
| StartedAt: 2025-02-04 13:29:16 -0500 (Tue, 04 Feb 2025) |
| EndedAt: 2025-02-04 13:29:56 -0500 (Tue, 04 Feb 2025) |
| EllapsedTime: 39.5 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.70.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.2 (2024-10-31)
* using platform: aarch64-apple-darwin20
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.70.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... WARNING
Found the following significant warnings:
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 15.0.0 (clang-1500.0.40.1)’
* used SDK: ‘MacOSX11.3.sdk’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 WARNING, 2 NOTEs
See
‘/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.0.40.1)’
using SDK: ‘MacOSX11.3.sdk’
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch arm64 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/arm64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation
installing to /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 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
0.351 0.101 0.451
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
Ncells 474168 25.4 1035467 55.3 NA 638597 34.2
Vcells 877630 6.7 8388608 64.0 65536 2072107 15.9
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Tue Feb 4 13:29:35 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 Feb 4 13:29:35 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: 0x600000500000>
>
>
>
> 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 Feb 4 13:29:38 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 Feb 4 13:29:39 2025"
>
> ColMode(tmp2)
<pointer: 0x600000500000>
>
>
>
> ### 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,] 100.8822225 0.7938180 -0.6430399 -0.88257409
[2,] 1.4279414 -0.2390616 -0.3132523 -1.63094441
[3,] 0.3726226 0.8557941 0.1112280 -0.48712606
[4,] 0.0923593 2.0286836 -0.3794188 -0.06131445
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.8822225 0.7938180 0.6430399 0.88257409
[2,] 1.4279414 0.2390616 0.3132523 1.63094441
[3,] 0.3726226 0.8557941 0.1112280 0.48712606
[4,] 0.0923593 2.0286836 0.3794188 0.06131445
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0440143 0.8909646 0.8018977 0.9394541
[2,] 1.1949650 0.4889393 0.5596894 1.2770843
[3,] 0.6104282 0.9250914 0.3335087 0.6979442
[4,] 0.3039067 1.4243186 0.6159698 0.2476175
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 226.32237 34.70346 33.66202 35.27712
[2,] 38.37759 30.12845 30.91015 39.40179
[3,] 31.47690 35.10671 28.44631 32.46657
[4,] 28.13143 41.27187 31.53912 27.53749
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600000534120>
> exp(tmp5)
<pointer: 0x600000534120>
> log(tmp5,2)
<pointer: 0x600000534120>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.0604
> Min(tmp5)
[1] 52.26642
> mean(tmp5)
[1] 72.0591
> Sum(tmp5)
[1] 14411.82
> Var(tmp5)
[1] 881.2468
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 88.48719 70.50946 74.32740 68.23620 70.59996 72.34726 65.90749 68.97640
[9] 68.76375 72.43584
> rowSums(tmp5)
[1] 1769.744 1410.189 1486.548 1364.724 1411.999 1446.945 1318.150 1379.528
[9] 1375.275 1448.717
> rowVars(tmp5)
[1] 8155.67725 87.70960 101.40779 76.26081 65.33876 46.11225
[7] 55.51099 96.05935 90.97351 83.69025
> rowSd(tmp5)
[1] 90.308788 9.365341 10.070144 8.732743 8.083239 6.790600 7.450570
[8] 9.800987 9.538003 9.148238
> rowMax(tmp5)
[1] 471.06035 85.14310 97.38927 85.90199 88.21656 81.67449 83.78991
[8] 87.34895 86.72681 91.43770
> rowMin(tmp5)
[1] 54.23123 52.26642 58.56424 56.39990 54.45384 59.02350 55.49640 56.02544
[9] 53.18680 59.87872
>
> colMeans(tmp5)
[1] 113.27390 74.79079 68.18429 65.14230 71.70882 66.61225 73.92951
[8] 72.34520 76.05098 67.18091 69.61389 67.29720 70.73350 69.30257
[15] 70.52572 70.78580 65.65667 69.88803 67.61319 70.54638
> colSums(tmp5)
[1] 1132.7390 747.9079 681.8429 651.4230 717.0882 666.1225 739.2951
[8] 723.4520 760.5098 671.8091 696.1389 672.9720 707.3350 693.0257
[15] 705.2572 707.8580 656.5667 698.8803 676.1319 705.4638
> colVars(tmp5)
[1] 15847.76242 82.68256 53.34806 63.10950 78.30948 102.71756
[7] 79.25648 78.49120 93.49478 64.15358 111.60004 43.07786
[13] 183.27418 68.64624 87.21848 46.01813 32.77799 52.23022
[19] 58.55568 89.92949
> colSd(tmp5)
[1] 125.887896 9.092995 7.303976 7.944149 8.849264 10.134967
[7] 8.902611 8.859526 9.669270 8.009593 10.564092 6.563372
[13] 13.537880 8.285302 9.339084 6.783667 5.725206 7.227048
[19] 7.652169 9.483116
> colMax(tmp5)
[1] 471.06035 91.43770 79.35303 82.00966 84.25501 83.36128 85.14310
[8] 88.21656 87.72531 78.03504 85.93267 79.34185 97.38927 85.92471
[15] 91.27587 83.92392 77.55372 80.26713 80.86230 83.78991
> colMin(tmp5)
[1] 58.55188 62.70843 56.02544 57.31568 54.45384 53.18680 56.39990 63.65481
[9] 65.92982 56.72122 52.26642 58.53471 54.18270 58.56635 56.31764 60.38004
[17] 59.67047 56.41797 55.49640 53.19046
>
>
> ### 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] 88.48719 70.50946 74.32740 68.23620 70.59996 72.34726 65.90749 68.97640
[9] NA 72.43584
> rowSums(tmp5)
[1] 1769.744 1410.189 1486.548 1364.724 1411.999 1446.945 1318.150 1379.528
[9] NA 1448.717
> rowVars(tmp5)
[1] 8155.67725 87.70960 101.40779 76.26081 65.33876 46.11225
[7] 55.51099 96.05935 96.02045 83.69025
> rowSd(tmp5)
[1] 90.308788 9.365341 10.070144 8.732743 8.083239 6.790600 7.450570
[8] 9.800987 9.799003 9.148238
> rowMax(tmp5)
[1] 471.06035 85.14310 97.38927 85.90199 88.21656 81.67449 83.78991
[8] 87.34895 NA 91.43770
> rowMin(tmp5)
[1] 54.23123 52.26642 58.56424 56.39990 54.45384 59.02350 55.49640 56.02544
[9] NA 59.87872
>
> colMeans(tmp5)
[1] 113.27390 74.79079 68.18429 65.14230 71.70882 66.61225 73.92951
[8] 72.34520 76.05098 67.18091 69.61389 67.29720 70.73350 69.30257
[15] 70.52572 NA 65.65667 69.88803 67.61319 70.54638
> colSums(tmp5)
[1] 1132.7390 747.9079 681.8429 651.4230 717.0882 666.1225 739.2951
[8] 723.4520 760.5098 671.8091 696.1389 672.9720 707.3350 693.0257
[15] 705.2572 NA 656.5667 698.8803 676.1319 705.4638
> colVars(tmp5)
[1] 15847.76242 82.68256 53.34806 63.10950 78.30948 102.71756
[7] 79.25648 78.49120 93.49478 64.15358 111.60004 43.07786
[13] 183.27418 68.64624 87.21848 NA 32.77799 52.23022
[19] 58.55568 89.92949
> colSd(tmp5)
[1] 125.887896 9.092995 7.303976 7.944149 8.849264 10.134967
[7] 8.902611 8.859526 9.669270 8.009593 10.564092 6.563372
[13] 13.537880 8.285302 9.339084 NA 5.725206 7.227048
[19] 7.652169 9.483116
> colMax(tmp5)
[1] 471.06035 91.43770 79.35303 82.00966 84.25501 83.36128 85.14310
[8] 88.21656 87.72531 78.03504 85.93267 79.34185 97.38927 85.92471
[15] 91.27587 NA 77.55372 80.26713 80.86230 83.78991
> colMin(tmp5)
[1] 58.55188 62.70843 56.02544 57.31568 54.45384 53.18680 56.39990 63.65481
[9] 65.92982 56.72122 52.26642 58.53471 54.18270 58.56635 56.31764 NA
[17] 59.67047 56.41797 55.49640 53.19046
>
> Max(tmp5,na.rm=TRUE)
[1] 471.0604
> Min(tmp5,na.rm=TRUE)
[1] 52.26642
> mean(tmp5,na.rm=TRUE)
[1] 72.07741
> Sum(tmp5,na.rm=TRUE)
[1] 14343.4
> Var(tmp5,na.rm=TRUE)
[1] 885.6301
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.48719 70.50946 74.32740 68.23620 70.59996 72.34726 65.90749 68.97640
[9] 68.78214 72.43584
> rowSums(tmp5,na.rm=TRUE)
[1] 1769.744 1410.189 1486.548 1364.724 1411.999 1446.945 1318.150 1379.528
[9] 1306.861 1448.717
> rowVars(tmp5,na.rm=TRUE)
[1] 8155.67725 87.70960 101.40779 76.26081 65.33876 46.11225
[7] 55.51099 96.05935 96.02045 83.69025
> rowSd(tmp5,na.rm=TRUE)
[1] 90.308788 9.365341 10.070144 8.732743 8.083239 6.790600 7.450570
[8] 9.800987 9.799003 9.148238
> rowMax(tmp5,na.rm=TRUE)
[1] 471.06035 85.14310 97.38927 85.90199 88.21656 81.67449 83.78991
[8] 87.34895 86.72681 91.43770
> rowMin(tmp5,na.rm=TRUE)
[1] 54.23123 52.26642 58.56424 56.39990 54.45384 59.02350 55.49640 56.02544
[9] 53.18680 59.87872
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.27390 74.79079 68.18429 65.14230 71.70882 66.61225 73.92951
[8] 72.34520 76.05098 67.18091 69.61389 67.29720 70.73350 69.30257
[15] 70.52572 71.04929 65.65667 69.88803 67.61319 70.54638
> colSums(tmp5,na.rm=TRUE)
[1] 1132.7390 747.9079 681.8429 651.4230 717.0882 666.1225 739.2951
[8] 723.4520 760.5098 671.8091 696.1389 672.9720 707.3350 693.0257
[15] 705.2572 639.4436 656.5667 698.8803 676.1319 705.4638
> colVars(tmp5,na.rm=TRUE)
[1] 15847.76242 82.68256 53.34806 63.10950 78.30948 102.71756
[7] 79.25648 78.49120 93.49478 64.15358 111.60004 43.07786
[13] 183.27418 68.64624 87.21848 50.98934 32.77799 52.23022
[19] 58.55568 89.92949
> colSd(tmp5,na.rm=TRUE)
[1] 125.887896 9.092995 7.303976 7.944149 8.849264 10.134967
[7] 8.902611 8.859526 9.669270 8.009593 10.564092 6.563372
[13] 13.537880 8.285302 9.339084 7.140682 5.725206 7.227048
[19] 7.652169 9.483116
> colMax(tmp5,na.rm=TRUE)
[1] 471.06035 91.43770 79.35303 82.00966 84.25501 83.36128 85.14310
[8] 88.21656 87.72531 78.03504 85.93267 79.34185 97.38927 85.92471
[15] 91.27587 83.92392 77.55372 80.26713 80.86230 83.78991
> colMin(tmp5,na.rm=TRUE)
[1] 58.55188 62.70843 56.02544 57.31568 54.45384 53.18680 56.39990 63.65481
[9] 65.92982 56.72122 52.26642 58.53471 54.18270 58.56635 56.31764 60.38004
[17] 59.67047 56.41797 55.49640 53.19046
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.48719 70.50946 74.32740 68.23620 70.59996 72.34726 65.90749 68.97640
[9] NaN 72.43584
> rowSums(tmp5,na.rm=TRUE)
[1] 1769.744 1410.189 1486.548 1364.724 1411.999 1446.945 1318.150 1379.528
[9] 0.000 1448.717
> rowVars(tmp5,na.rm=TRUE)
[1] 8155.67725 87.70960 101.40779 76.26081 65.33876 46.11225
[7] 55.51099 96.05935 NA 83.69025
> rowSd(tmp5,na.rm=TRUE)
[1] 90.308788 9.365341 10.070144 8.732743 8.083239 6.790600 7.450570
[8] 9.800987 NA 9.148238
> rowMax(tmp5,na.rm=TRUE)
[1] 471.06035 85.14310 97.38927 85.90199 88.21656 81.67449 83.78991
[8] 87.34895 NA 91.43770
> rowMin(tmp5,na.rm=TRUE)
[1] 54.23123 52.26642 58.56424 56.39990 54.45384 59.02350 55.49640 56.02544
[9] NA 59.87872
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 117.14502 74.82044 67.72177 65.40450 71.67425 68.10396 74.44689
[8] 73.31080 74.86478 68.27576 67.80069 67.46369 72.22068 69.49330
[15] 70.36492 NaN 64.33477 69.45050 68.08407 72.47482
> colSums(tmp5,na.rm=TRUE)
[1] 1054.3052 673.3839 609.4959 588.6405 645.0682 612.9357 670.0220
[8] 659.7972 673.7830 614.4818 610.2062 607.1732 649.9862 625.4397
[15] 633.2843 0.0000 579.0130 625.0545 612.7566 652.2734
> colVars(tmp5,na.rm=TRUE)
[1] 17660.14444 93.00800 57.60991 70.22479 88.08471 90.52355
[7] 86.15210 77.81332 89.35198 58.68741 88.56358 48.15074
[13] 181.30154 76.81779 97.82990 NA 17.21693 56.60539
[19] 63.38077 59.33342
> colSd(tmp5,na.rm=TRUE)
[1] 132.891476 9.644065 7.590119 8.380023 9.385346 9.514386
[7] 9.281816 8.821186 9.452618 7.660771 9.410823 6.939074
[13] 13.464826 8.764576 9.890900 NA 4.149328 7.523656
[19] 7.961204 7.702819
> colMax(tmp5,na.rm=TRUE)
[1] 471.06035 91.43770 79.35303 82.00966 84.25501 83.36128 85.14310
[8] 88.21656 87.72531 78.03504 78.70180 79.34185 97.38927 85.92471
[15] 91.27587 -Inf 72.46178 80.26713 80.86230 83.78991
> colMin(tmp5,na.rm=TRUE)
[1] 58.55188 62.70843 56.02544 57.31568 54.45384 58.31977 56.39990 64.45693
[9] 65.92982 56.72122 52.26642 58.53471 54.18270 58.56635 56.31764 Inf
[17] 59.67047 56.41797 55.49640 63.82192
>
>
>
>
> 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] 233.3920 319.6929 338.7958 182.6340 213.8903 228.0298 215.7296 202.1057
[9] 171.5618 263.1710
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 233.3920 319.6929 338.7958 182.6340 213.8903 228.0298 215.7296 202.1057
[9] 171.5618 263.1710
>
>
>
> 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] 1.136868e-13 0.000000e+00 2.842171e-14 2.842171e-14 1.989520e-13
[6] 0.000000e+00 -5.684342e-14 -1.136868e-13 -1.136868e-13 1.705303e-13
[11] -5.684342e-14 -5.684342e-14 -5.684342e-14 -2.842171e-14 -9.947598e-14
[16] 5.684342e-14 5.684342e-14 -2.273737e-13 8.526513e-14 8.526513e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
9 7
2 20
3 19
10 19
7 1
10 9
8 11
1 12
7 13
6 3
9 3
2 9
9 8
1 19
3 7
4 7
9 20
10 9
3 15
4 15
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] 3.129634
> Min(tmp)
[1] -2.696195
> mean(tmp)
[1] -0.1319444
> Sum(tmp)
[1] -13.19444
> Var(tmp)
[1] 0.8588821
>
> rowMeans(tmp)
[1] -0.1319444
> rowSums(tmp)
[1] -13.19444
> rowVars(tmp)
[1] 0.8588821
> rowSd(tmp)
[1] 0.9267589
> rowMax(tmp)
[1] 3.129634
> rowMin(tmp)
[1] -2.696195
>
> colMeans(tmp)
[1] 1.24248693 -1.70135778 0.05404346 -1.16138427 2.00732627 -0.23978393
[7] -0.38787507 -0.98951005 -0.01818559 -0.70983004 -0.46026037 -1.23941117
[13] -1.38008315 -1.59568707 0.31605598 0.22535013 0.28567924 -2.69619530
[19] -0.68912092 0.35911623 1.93470896 0.58828788 0.21428189 -0.46854965
[25] 0.92684657 -0.41342541 -1.16140549 0.04671772 -1.65831299 -0.82896233
[31] 0.63942463 1.11515776 0.49715836 1.14526295 0.47968388 -1.35731025
[37] -0.16618790 -0.68826402 -1.25965613 -0.40073457 0.61927474 0.27133036
[43] 0.25099508 -1.24391482 -1.04793602 -0.28316532 0.28265009 0.07159187
[49] 0.01145852 -2.20360921 1.39618047 0.49177142 -0.45012721 0.17378698
[55] 0.34558671 0.07316390 -0.61947178 0.85960876 -0.11898789 -0.28306861
[61] -0.36395030 -0.79421175 -0.38874875 -0.99162770 0.56203418 -0.12047174
[67] -0.01808823 -0.34391601 -0.64366957 0.57830728 0.93774825 0.85202178
[73] -0.09806489 -0.26090251 0.31396629 -0.66131691 -0.77765587 -0.74958532
[79] -0.06337613 -0.72452094 -0.72520011 3.12963376 -0.63195524 -0.63367837
[85] -1.05638189 -0.80345649 -1.10005807 -0.05642173 0.41402300 1.57279158
[91] 0.90961123 0.75672504 0.19757659 -0.05212482 -1.09079860 1.28356329
[97] 0.61278640 0.53102401 -0.08618092 -1.61310383
> colSums(tmp)
[1] 1.24248693 -1.70135778 0.05404346 -1.16138427 2.00732627 -0.23978393
[7] -0.38787507 -0.98951005 -0.01818559 -0.70983004 -0.46026037 -1.23941117
[13] -1.38008315 -1.59568707 0.31605598 0.22535013 0.28567924 -2.69619530
[19] -0.68912092 0.35911623 1.93470896 0.58828788 0.21428189 -0.46854965
[25] 0.92684657 -0.41342541 -1.16140549 0.04671772 -1.65831299 -0.82896233
[31] 0.63942463 1.11515776 0.49715836 1.14526295 0.47968388 -1.35731025
[37] -0.16618790 -0.68826402 -1.25965613 -0.40073457 0.61927474 0.27133036
[43] 0.25099508 -1.24391482 -1.04793602 -0.28316532 0.28265009 0.07159187
[49] 0.01145852 -2.20360921 1.39618047 0.49177142 -0.45012721 0.17378698
[55] 0.34558671 0.07316390 -0.61947178 0.85960876 -0.11898789 -0.28306861
[61] -0.36395030 -0.79421175 -0.38874875 -0.99162770 0.56203418 -0.12047174
[67] -0.01808823 -0.34391601 -0.64366957 0.57830728 0.93774825 0.85202178
[73] -0.09806489 -0.26090251 0.31396629 -0.66131691 -0.77765587 -0.74958532
[79] -0.06337613 -0.72452094 -0.72520011 3.12963376 -0.63195524 -0.63367837
[85] -1.05638189 -0.80345649 -1.10005807 -0.05642173 0.41402300 1.57279158
[91] 0.90961123 0.75672504 0.19757659 -0.05212482 -1.09079860 1.28356329
[97] 0.61278640 0.53102401 -0.08618092 -1.61310383
> 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] 1.24248693 -1.70135778 0.05404346 -1.16138427 2.00732627 -0.23978393
[7] -0.38787507 -0.98951005 -0.01818559 -0.70983004 -0.46026037 -1.23941117
[13] -1.38008315 -1.59568707 0.31605598 0.22535013 0.28567924 -2.69619530
[19] -0.68912092 0.35911623 1.93470896 0.58828788 0.21428189 -0.46854965
[25] 0.92684657 -0.41342541 -1.16140549 0.04671772 -1.65831299 -0.82896233
[31] 0.63942463 1.11515776 0.49715836 1.14526295 0.47968388 -1.35731025
[37] -0.16618790 -0.68826402 -1.25965613 -0.40073457 0.61927474 0.27133036
[43] 0.25099508 -1.24391482 -1.04793602 -0.28316532 0.28265009 0.07159187
[49] 0.01145852 -2.20360921 1.39618047 0.49177142 -0.45012721 0.17378698
[55] 0.34558671 0.07316390 -0.61947178 0.85960876 -0.11898789 -0.28306861
[61] -0.36395030 -0.79421175 -0.38874875 -0.99162770 0.56203418 -0.12047174
[67] -0.01808823 -0.34391601 -0.64366957 0.57830728 0.93774825 0.85202178
[73] -0.09806489 -0.26090251 0.31396629 -0.66131691 -0.77765587 -0.74958532
[79] -0.06337613 -0.72452094 -0.72520011 3.12963376 -0.63195524 -0.63367837
[85] -1.05638189 -0.80345649 -1.10005807 -0.05642173 0.41402300 1.57279158
[91] 0.90961123 0.75672504 0.19757659 -0.05212482 -1.09079860 1.28356329
[97] 0.61278640 0.53102401 -0.08618092 -1.61310383
> colMin(tmp)
[1] 1.24248693 -1.70135778 0.05404346 -1.16138427 2.00732627 -0.23978393
[7] -0.38787507 -0.98951005 -0.01818559 -0.70983004 -0.46026037 -1.23941117
[13] -1.38008315 -1.59568707 0.31605598 0.22535013 0.28567924 -2.69619530
[19] -0.68912092 0.35911623 1.93470896 0.58828788 0.21428189 -0.46854965
[25] 0.92684657 -0.41342541 -1.16140549 0.04671772 -1.65831299 -0.82896233
[31] 0.63942463 1.11515776 0.49715836 1.14526295 0.47968388 -1.35731025
[37] -0.16618790 -0.68826402 -1.25965613 -0.40073457 0.61927474 0.27133036
[43] 0.25099508 -1.24391482 -1.04793602 -0.28316532 0.28265009 0.07159187
[49] 0.01145852 -2.20360921 1.39618047 0.49177142 -0.45012721 0.17378698
[55] 0.34558671 0.07316390 -0.61947178 0.85960876 -0.11898789 -0.28306861
[61] -0.36395030 -0.79421175 -0.38874875 -0.99162770 0.56203418 -0.12047174
[67] -0.01808823 -0.34391601 -0.64366957 0.57830728 0.93774825 0.85202178
[73] -0.09806489 -0.26090251 0.31396629 -0.66131691 -0.77765587 -0.74958532
[79] -0.06337613 -0.72452094 -0.72520011 3.12963376 -0.63195524 -0.63367837
[85] -1.05638189 -0.80345649 -1.10005807 -0.05642173 0.41402300 1.57279158
[91] 0.90961123 0.75672504 0.19757659 -0.05212482 -1.09079860 1.28356329
[97] 0.61278640 0.53102401 -0.08618092 -1.61310383
> colMedians(tmp)
[1] 1.24248693 -1.70135778 0.05404346 -1.16138427 2.00732627 -0.23978393
[7] -0.38787507 -0.98951005 -0.01818559 -0.70983004 -0.46026037 -1.23941117
[13] -1.38008315 -1.59568707 0.31605598 0.22535013 0.28567924 -2.69619530
[19] -0.68912092 0.35911623 1.93470896 0.58828788 0.21428189 -0.46854965
[25] 0.92684657 -0.41342541 -1.16140549 0.04671772 -1.65831299 -0.82896233
[31] 0.63942463 1.11515776 0.49715836 1.14526295 0.47968388 -1.35731025
[37] -0.16618790 -0.68826402 -1.25965613 -0.40073457 0.61927474 0.27133036
[43] 0.25099508 -1.24391482 -1.04793602 -0.28316532 0.28265009 0.07159187
[49] 0.01145852 -2.20360921 1.39618047 0.49177142 -0.45012721 0.17378698
[55] 0.34558671 0.07316390 -0.61947178 0.85960876 -0.11898789 -0.28306861
[61] -0.36395030 -0.79421175 -0.38874875 -0.99162770 0.56203418 -0.12047174
[67] -0.01808823 -0.34391601 -0.64366957 0.57830728 0.93774825 0.85202178
[73] -0.09806489 -0.26090251 0.31396629 -0.66131691 -0.77765587 -0.74958532
[79] -0.06337613 -0.72452094 -0.72520011 3.12963376 -0.63195524 -0.63367837
[85] -1.05638189 -0.80345649 -1.10005807 -0.05642173 0.41402300 1.57279158
[91] 0.90961123 0.75672504 0.19757659 -0.05212482 -1.09079860 1.28356329
[97] 0.61278640 0.53102401 -0.08618092 -1.61310383
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.242487 -1.701358 0.05404346 -1.161384 2.007326 -0.2397839 -0.3878751
[2,] 1.242487 -1.701358 0.05404346 -1.161384 2.007326 -0.2397839 -0.3878751
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.9895101 -0.01818559 -0.70983 -0.4602604 -1.239411 -1.380083 -1.595687
[2,] -0.9895101 -0.01818559 -0.70983 -0.4602604 -1.239411 -1.380083 -1.595687
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.316056 0.2253501 0.2856792 -2.696195 -0.6891209 0.3591162 1.934709
[2,] 0.316056 0.2253501 0.2856792 -2.696195 -0.6891209 0.3591162 1.934709
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.5882879 0.2142819 -0.4685497 0.9268466 -0.4134254 -1.161405 0.04671772
[2,] 0.5882879 0.2142819 -0.4685497 0.9268466 -0.4134254 -1.161405 0.04671772
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.658313 -0.8289623 0.6394246 1.115158 0.4971584 1.145263 0.4796839
[2,] -1.658313 -0.8289623 0.6394246 1.115158 0.4971584 1.145263 0.4796839
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.35731 -0.1661879 -0.688264 -1.259656 -0.4007346 0.6192747 0.2713304
[2,] -1.35731 -0.1661879 -0.688264 -1.259656 -0.4007346 0.6192747 0.2713304
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.2509951 -1.243915 -1.047936 -0.2831653 0.2826501 0.07159187 0.01145852
[2,] 0.2509951 -1.243915 -1.047936 -0.2831653 0.2826501 0.07159187 0.01145852
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -2.203609 1.39618 0.4917714 -0.4501272 0.173787 0.3455867 0.0731639
[2,] -2.203609 1.39618 0.4917714 -0.4501272 0.173787 0.3455867 0.0731639
[,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.6194718 0.8596088 -0.1189879 -0.2830686 -0.3639503 -0.7942118
[2,] -0.6194718 0.8596088 -0.1189879 -0.2830686 -0.3639503 -0.7942118
[,63] [,64] [,65] [,66] [,67] [,68]
[1,] -0.3887488 -0.9916277 0.5620342 -0.1204717 -0.01808823 -0.343916
[2,] -0.3887488 -0.9916277 0.5620342 -0.1204717 -0.01808823 -0.343916
[,69] [,70] [,71] [,72] [,73] [,74] [,75]
[1,] -0.6436696 0.5783073 0.9377483 0.8520218 -0.09806489 -0.2609025 0.3139663
[2,] -0.6436696 0.5783073 0.9377483 0.8520218 -0.09806489 -0.2609025 0.3139663
[,76] [,77] [,78] [,79] [,80] [,81]
[1,] -0.6613169 -0.7776559 -0.7495853 -0.06337613 -0.7245209 -0.7252001
[2,] -0.6613169 -0.7776559 -0.7495853 -0.06337613 -0.7245209 -0.7252001
[,82] [,83] [,84] [,85] [,86] [,87] [,88]
[1,] 3.129634 -0.6319552 -0.6336784 -1.056382 -0.8034565 -1.100058 -0.05642173
[2,] 3.129634 -0.6319552 -0.6336784 -1.056382 -0.8034565 -1.100058 -0.05642173
[,89] [,90] [,91] [,92] [,93] [,94] [,95]
[1,] 0.414023 1.572792 0.9096112 0.756725 0.1975766 -0.05212482 -1.090799
[2,] 0.414023 1.572792 0.9096112 0.756725 0.1975766 -0.05212482 -1.090799
[,96] [,97] [,98] [,99] [,100]
[1,] 1.283563 0.6127864 0.531024 -0.08618092 -1.613104
[2,] 1.283563 0.6127864 0.531024 -0.08618092 -1.613104
>
>
> Max(tmp2)
[1] 2.806065
> Min(tmp2)
[1] -2.159514
> mean(tmp2)
[1] 0.02258166
> Sum(tmp2)
[1] 2.258166
> Var(tmp2)
[1] 1.154132
>
> rowMeans(tmp2)
[1] 1.635772521 0.078920029 -0.183683251 -2.139946297 -0.566889306
[6] 0.236685556 -0.268436445 0.083722414 0.149884068 0.591641441
[11] 0.398870387 -0.228883871 -1.611129142 0.653668781 2.071849257
[16] -0.516582573 0.240636948 1.084937267 -0.132897602 1.213666373
[21] 0.242985719 -1.217102912 -0.185548436 1.391567452 -1.255092788
[26] 0.228477207 -0.313651840 1.697931872 1.106575669 2.806065414
[31] -0.356033303 0.975772804 -1.525644300 -0.398086230 -0.677766597
[36] -0.557028609 0.060244315 -1.339889730 0.471948269 0.776407173
[41] -0.710612289 1.745506678 -0.528125119 -0.624490110 0.027820009
[46] -0.880948216 -0.222291360 -0.899915539 0.237481411 1.590311892
[51] 1.250646632 1.622381515 -0.954218144 0.178842585 -1.041196079
[56] -0.577381309 0.438587827 -0.437781711 -0.130713762 -0.578488427
[61] 1.741034684 -0.627836029 0.151304119 -0.623755136 1.156453430
[66] -0.215647409 -0.117154946 2.610278484 0.762144495 1.806292390
[71] 0.073859178 -0.808941996 -0.424704041 -1.349306820 -0.581949981
[76] -0.837787671 -1.805329535 -0.157965950 -0.255628268 0.430138962
[81] -0.499946351 -0.550257386 -0.354284160 1.014895397 0.184948356
[86] -0.147711853 -1.064059891 0.008260457 2.063611321 -2.041489755
[91] 0.757218021 -0.354543937 2.363713395 -2.159513696 0.753415582
[96] -1.263328382 0.018892392 -2.096175326 1.592377292 -1.122707960
> rowSums(tmp2)
[1] 1.635772521 0.078920029 -0.183683251 -2.139946297 -0.566889306
[6] 0.236685556 -0.268436445 0.083722414 0.149884068 0.591641441
[11] 0.398870387 -0.228883871 -1.611129142 0.653668781 2.071849257
[16] -0.516582573 0.240636948 1.084937267 -0.132897602 1.213666373
[21] 0.242985719 -1.217102912 -0.185548436 1.391567452 -1.255092788
[26] 0.228477207 -0.313651840 1.697931872 1.106575669 2.806065414
[31] -0.356033303 0.975772804 -1.525644300 -0.398086230 -0.677766597
[36] -0.557028609 0.060244315 -1.339889730 0.471948269 0.776407173
[41] -0.710612289 1.745506678 -0.528125119 -0.624490110 0.027820009
[46] -0.880948216 -0.222291360 -0.899915539 0.237481411 1.590311892
[51] 1.250646632 1.622381515 -0.954218144 0.178842585 -1.041196079
[56] -0.577381309 0.438587827 -0.437781711 -0.130713762 -0.578488427
[61] 1.741034684 -0.627836029 0.151304119 -0.623755136 1.156453430
[66] -0.215647409 -0.117154946 2.610278484 0.762144495 1.806292390
[71] 0.073859178 -0.808941996 -0.424704041 -1.349306820 -0.581949981
[76] -0.837787671 -1.805329535 -0.157965950 -0.255628268 0.430138962
[81] -0.499946351 -0.550257386 -0.354284160 1.014895397 0.184948356
[86] -0.147711853 -1.064059891 0.008260457 2.063611321 -2.041489755
[91] 0.757218021 -0.354543937 2.363713395 -2.159513696 0.753415582
[96] -1.263328382 0.018892392 -2.096175326 1.592377292 -1.122707960
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 1.635772521 0.078920029 -0.183683251 -2.139946297 -0.566889306
[6] 0.236685556 -0.268436445 0.083722414 0.149884068 0.591641441
[11] 0.398870387 -0.228883871 -1.611129142 0.653668781 2.071849257
[16] -0.516582573 0.240636948 1.084937267 -0.132897602 1.213666373
[21] 0.242985719 -1.217102912 -0.185548436 1.391567452 -1.255092788
[26] 0.228477207 -0.313651840 1.697931872 1.106575669 2.806065414
[31] -0.356033303 0.975772804 -1.525644300 -0.398086230 -0.677766597
[36] -0.557028609 0.060244315 -1.339889730 0.471948269 0.776407173
[41] -0.710612289 1.745506678 -0.528125119 -0.624490110 0.027820009
[46] -0.880948216 -0.222291360 -0.899915539 0.237481411 1.590311892
[51] 1.250646632 1.622381515 -0.954218144 0.178842585 -1.041196079
[56] -0.577381309 0.438587827 -0.437781711 -0.130713762 -0.578488427
[61] 1.741034684 -0.627836029 0.151304119 -0.623755136 1.156453430
[66] -0.215647409 -0.117154946 2.610278484 0.762144495 1.806292390
[71] 0.073859178 -0.808941996 -0.424704041 -1.349306820 -0.581949981
[76] -0.837787671 -1.805329535 -0.157965950 -0.255628268 0.430138962
[81] -0.499946351 -0.550257386 -0.354284160 1.014895397 0.184948356
[86] -0.147711853 -1.064059891 0.008260457 2.063611321 -2.041489755
[91] 0.757218021 -0.354543937 2.363713395 -2.159513696 0.753415582
[96] -1.263328382 0.018892392 -2.096175326 1.592377292 -1.122707960
> rowMin(tmp2)
[1] 1.635772521 0.078920029 -0.183683251 -2.139946297 -0.566889306
[6] 0.236685556 -0.268436445 0.083722414 0.149884068 0.591641441
[11] 0.398870387 -0.228883871 -1.611129142 0.653668781 2.071849257
[16] -0.516582573 0.240636948 1.084937267 -0.132897602 1.213666373
[21] 0.242985719 -1.217102912 -0.185548436 1.391567452 -1.255092788
[26] 0.228477207 -0.313651840 1.697931872 1.106575669 2.806065414
[31] -0.356033303 0.975772804 -1.525644300 -0.398086230 -0.677766597
[36] -0.557028609 0.060244315 -1.339889730 0.471948269 0.776407173
[41] -0.710612289 1.745506678 -0.528125119 -0.624490110 0.027820009
[46] -0.880948216 -0.222291360 -0.899915539 0.237481411 1.590311892
[51] 1.250646632 1.622381515 -0.954218144 0.178842585 -1.041196079
[56] -0.577381309 0.438587827 -0.437781711 -0.130713762 -0.578488427
[61] 1.741034684 -0.627836029 0.151304119 -0.623755136 1.156453430
[66] -0.215647409 -0.117154946 2.610278484 0.762144495 1.806292390
[71] 0.073859178 -0.808941996 -0.424704041 -1.349306820 -0.581949981
[76] -0.837787671 -1.805329535 -0.157965950 -0.255628268 0.430138962
[81] -0.499946351 -0.550257386 -0.354284160 1.014895397 0.184948356
[86] -0.147711853 -1.064059891 0.008260457 2.063611321 -2.041489755
[91] 0.757218021 -0.354543937 2.363713395 -2.159513696 0.753415582
[96] -1.263328382 0.018892392 -2.096175326 1.592377292 -1.122707960
>
> colMeans(tmp2)
[1] 0.02258166
> colSums(tmp2)
[1] 2.258166
> colVars(tmp2)
[1] 1.154132
> colSd(tmp2)
[1] 1.074305
> colMax(tmp2)
[1] 2.806065
> colMin(tmp2)
[1] -2.159514
> colMedians(tmp2)
[1] -0.1403047
> colRanges(tmp2)
[,1]
[1,] -2.159514
[2,] 2.806065
>
> 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] -0.2043903 -4.3040167 3.9829578 -3.6684381 -1.9673158 3.4117034
[7] -0.3631703 4.5611527 -5.8866749 2.7734835
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8328093
[2,] -0.6437427
[3,] -0.1610295
[4,] 0.4855534
[5,] 1.1769450
>
> rowApply(tmp,sum)
[1] -6.2563249 2.7992629 0.3993760 -5.5027009 2.8818050 1.4187097
[7] -0.3063403 -0.3884846 5.5393718 -2.2493834
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 6 7 8 5 3 7 9 8 1 4
[2,] 3 8 3 2 1 6 4 6 8 1
[3,] 9 6 4 10 6 5 8 7 6 9
[4,] 5 2 2 9 2 8 3 5 4 5
[5,] 1 10 5 4 5 4 5 2 7 10
[6,] 7 3 10 7 9 2 7 3 9 8
[7,] 2 5 1 3 8 3 6 10 2 7
[8,] 10 4 7 8 10 9 10 4 3 2
[9,] 4 1 6 1 4 1 1 9 5 6
[10,] 8 9 9 6 7 10 2 1 10 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.03525098 0.04372709 2.01331323 1.83188266 -1.16195080 1.89923793
[7] 1.59723073 -1.98273792 -2.95409344 1.50417051 -3.35807345 -0.41532416
[13] 1.29857043 -0.55309009 2.70142897 0.52956600 -1.65304547 -5.69083938
[19] -0.15528475 -2.34754456
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8275994
[2,] -0.9752180
[3,] -0.2006388
[4,] 0.1264425
[5,] 0.8417628
>
> rowApply(tmp,sum)
[1] 0.9601873 -3.9514875 2.2535285 0.4256849 -8.5760205
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 2 14 9 3 20
[2,] 13 12 8 6 17
[3,] 17 19 1 16 18
[4,] 12 10 14 12 19
[5,] 3 17 15 4 15
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.8275994 0.49278175 1.3283657 0.3797564 -1.1751885 0.5129832
[2,] 0.1264425 0.02352112 1.1521508 -0.1036959 0.2856641 0.5278744
[3,] -0.2006388 -0.20478656 -1.4862187 0.5692994 0.6203842 0.8073367
[4,] -0.9752180 -0.64244100 0.6156812 0.3448828 -0.6901522 0.6723171
[5,] 0.8417628 0.37465178 0.4033343 0.6416400 -0.2026583 -0.6212735
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.2414980 -0.21196952 0.17119833 -0.49029337 -2.1626504 1.5410076
[2,] -0.2233153 0.14756052 -2.27774713 0.05330186 -0.4532966 -0.1808260
[3,] 1.0112938 -0.06866301 0.06491306 1.76666645 -0.4316039 0.1497622
[4,] -0.2155897 0.28750019 -0.55696400 1.02466126 0.5936940 -1.4498705
[5,] -0.2166561 -2.13716610 -0.35549371 -0.85016568 -0.9042166 -0.4753973
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.1247723 -0.1329206 0.56180814 1.70857015 -0.9484722 -0.9926964
[2,] 2.2393848 -0.2107862 -0.06446717 0.19822859 -0.7268699 -0.9467408
[3,] -0.8863840 -0.3874731 2.40755173 -0.74572426 -0.3028056 -1.0273047
[4,] 0.8891488 1.3687989 0.25441322 0.05814778 0.6024442 -1.4737404
[5,] -1.0683515 -1.1907090 -0.45787696 -0.68965626 -0.2773419 -1.2503570
[,19] [,20]
[1,] 1.5106729 -0.67143651
[2,] -1.7902425 -1.72762841
[3,] 0.6398970 -0.04197348
[4,] -0.6557832 0.37375453
[5,] 0.1401711 -0.28026069
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 655 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 567 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 1.231612 -1.295344 -1.844766 0.372145 1.295232 -0.9720247 0.3132641
col8 col9 col10 col11 col12 col13 col14
row1 -0.9898687 0.1444574 -0.04197361 0.5151563 0.1581402 -0.1641956 2.703805
col15 col16 col17 col18 col19 col20
row1 0.7883676 -0.594006 -1.093403 -0.384612 -0.8394971 -1.586796
> tmp[,"col10"]
col10
row1 -0.04197361
row2 -0.13069467
row3 -0.69242681
row4 0.41131476
row5 -0.41808680
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.231612 -1.295344 -1.844766 0.372145 1.2952320 -0.9720247 0.3132641
row5 -1.179658 2.288505 0.515158 -1.194437 0.3569102 0.4384515 1.8356085
col8 col9 col10 col11 col12 col13
row1 -0.9898687 0.14445740 -0.04197361 0.51515630 0.1581402 -0.1641956
row5 0.8569011 -0.03919917 -0.41808680 -0.07236608 0.7402236 -0.3234640
col14 col15 col16 col17 col18 col19 col20
row1 2.7038052 0.7883676 -0.5940060 -1.0934032 -0.384612 -0.8394971 -1.586796
row5 -0.5423217 -1.5968664 -0.6017607 -0.1666489 -1.023798 -0.7107533 1.166936
> tmp[,c("col6","col20")]
col6 col20
row1 -0.9720247 -1.5867960
row2 -0.1720307 1.1120237
row3 0.5375670 0.6869984
row4 -0.5963581 0.5841146
row5 0.4384515 1.1669357
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.9720247 -1.586796
row5 0.4384515 1.166936
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.16296 47.89931 50.1426 50.00721 49.24926 103.9711 49.19547 49.3196
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.81589 49.03121 50.42688 49.28042 48.37655 48.83422 48.47929 48.76977
col17 col18 col19 col20
row1 49.13781 49.74421 49.47279 102.9059
> tmp[,"col10"]
col10
row1 49.03121
row2 29.00645
row3 31.31247
row4 29.06817
row5 50.26419
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.16296 47.89931 50.14260 50.00721 49.24926 103.9711 49.19547 49.31960
row5 47.99655 50.23426 50.62889 49.03606 50.51237 105.2398 48.04111 49.94898
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.81589 49.03121 50.42688 49.28042 48.37655 48.83422 48.47929 48.76977
row5 50.12236 50.26419 49.40617 49.48268 50.33618 48.41136 50.81887 49.04898
col17 col18 col19 col20
row1 49.13781 49.74421 49.47279 102.9059
row5 49.35909 51.10145 49.09269 105.0277
> tmp[,c("col6","col20")]
col6 col20
row1 103.97107 102.90595
row2 74.43736 74.07690
row3 74.60006 74.46380
row4 74.47298 75.70606
row5 105.23981 105.02771
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 103.9711 102.9059
row5 105.2398 105.0277
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 103.9711 102.9059
row5 105.2398 105.0277
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.3462824
[2,] 1.0174682
[3,] -0.9175585
[4,] 0.5792836
[5,] 0.1936367
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.11636772 -0.31549550
[2,] 0.00845834 0.41713288
[3,] 0.02756258 -0.23697994
[4,] 0.56774222 0.02573986
[5,] -1.03611633 -1.25779413
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.1458313 1.0791773
[2,] -0.4062995 0.4529417
[3,] 0.4019392 0.8478811
[4,] -0.2257044 -1.6005508
[5,] -0.2237482 -0.6708698
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.145831
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.1458313
[2,] -0.4062995
>
>
>
> 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 0.2871448 0.7231346 -0.8532068 -0.7019768 2.520811 -0.3983442 1.5521295
row1 -1.4883783 -1.6505770 -1.0323168 0.6002636 -0.703511 0.4383541 0.8821271
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -1.148957 1.7546047 -1.425307 -1.679665 -1.251992 0.09848337 -0.8939477
row1 1.686956 0.2041324 1.468080 1.393531 -1.489060 1.88069470 0.8729919
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.2874095 0.58952690 0.8728638 -1.376905 0.5231231 0.6972926
row1 1.8992632 0.06194879 0.4375372 -0.399227 -1.1115053 -1.4243220
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -2.201489 -0.5036466 0.06147985 -1.89481 -0.7734522 -0.3082266 0.5827166
[,8] [,9] [,10]
row2 0.1068252 1.617883 0.9532772
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -2.856176 1.600037 -0.9641862 -0.4981928 -0.04416961 1.551642 1.547898
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.05332203 1.0082 -0.4007976 -0.5814706 0.5625111 -1.644444 -0.461431
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.8740829 0.9126091 1.084477 0.8437721 -0.0210158 0.2446403
>
>
> 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: 0x60000053c1e0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f80481b30"
[2] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f807df0ec74"
[3] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f805433f444"
[4] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f801ee9c78c"
[5] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f8062bc82f"
[6] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f80246388d3"
[7] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f802abe74f"
[8] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f8063def4e7"
[9] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f8042a09cea"
[10] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f803e9de8d2"
[11] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f807120531b"
[12] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f801304ba3"
[13] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f809b5baf1"
[14] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f807a042931"
[15] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM10f80272c8e8c"
>
>
> ### 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: 0x60000053c360>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x60000053c360>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x60000053c360>
> rowMedians(tmp)
[1] -0.094578005 -0.177836917 0.024546064 -0.184449207 0.239080551
[6] -0.231300504 0.085092103 0.509362623 -0.385609579 -0.168396281
[11] 0.102321488 -0.382042138 0.339767162 0.128973186 -0.137887180
[16] 0.237118188 0.215811146 0.014619368 0.120900156 0.025487769
[21] 0.036580180 -0.033913355 -0.369706887 0.574947953 -0.523591529
[26] -0.003971660 0.184523032 0.463928606 0.410534237 -0.018840507
[31] 0.690603951 -0.040401740 0.087482397 -0.296563934 0.083109348
[36] 0.015509344 0.086127965 0.479746250 -0.121418341 0.369055792
[41] 0.081766307 -0.101390976 0.165073747 0.197800810 0.097770752
[46] -0.111094642 0.202546192 -0.094260913 0.210873489 -0.041506140
[51] 0.238963061 0.049500357 -0.010040090 0.155302880 -0.174584798
[56] -0.239116698 -0.175398094 -0.154437380 -0.138389797 0.216024747
[61] -0.810197496 -0.035839195 0.126288630 0.120989408 0.004976815
[66] 0.044862723 -0.358383539 0.440604702 -0.320434364 -0.101657978
[71] -0.173149410 0.388566433 -0.028452718 -0.051526738 0.547056764
[76] -0.181304856 0.110643727 -0.004515127 0.320759693 0.038857428
[81] -0.439681074 0.306051293 -0.363305244 0.028809746 -0.703311374
[86] -0.241452533 -0.389982346 0.031439826 0.018573051 0.393720532
[91] 0.232241574 0.245818037 -0.198652476 -0.200233855 0.176867723
[96] -0.033324148 -0.100879094 0.271288585 0.129338223 -0.163480965
[101] -0.061034573 0.343726569 -0.100489417 0.341880484 -0.190227624
[106] -0.191502686 0.032190346 -0.387172255 -0.330221540 0.667510695
[111] -0.135342234 -0.881537986 0.243855430 0.017474488 0.120349057
[116] 0.331775631 -0.231787821 0.350061223 0.247066337 0.120234847
[121] -0.373684324 0.167155444 0.104594049 0.441033437 0.592098091
[126] -0.438115395 -0.045916863 0.511825256 -0.799795445 0.449023268
[131] -0.025695336 -0.294469245 0.514558303 -0.136039996 -0.031983740
[136] -0.517102954 0.105338775 -0.073543259 0.030452297 -0.252628012
[141] -0.157002200 0.206587038 0.060215891 -0.361624056 -0.595568492
[146] 0.502026939 0.248103764 -0.284426450 -0.321706999 0.491126300
[151] -0.716650058 0.227488346 0.209187401 0.645682224 -0.289173305
[156] -0.212041967 0.557136307 0.643154126 0.206721798 0.010144234
[161] -0.040405340 0.357960651 -0.217755001 -0.105200495 0.353340978
[166] -0.337278989 0.435427981 -0.462107813 -0.572777984 -0.113355778
[171] 0.347386599 -0.401269512 -0.772291411 0.373101865 -0.075976168
[176] -0.108469893 -0.039839900 0.487073279 0.407322821 -0.289607865
[181] 0.009055880 0.012327105 0.192985283 0.051507155 0.234268320
[186] 0.479856579 -0.897500054 -0.223368935 0.145856535 0.478279165
[191] 0.053017959 0.254648961 -0.671578282 0.435029209 -0.258268946
[196] -0.278353728 0.144064256 0.056607877 -0.148396598 0.127331062
[201] -0.042974751 -0.358019032 0.308457406 -0.225560441 -0.181655844
[206] 0.312480660 0.136938775 -0.385483746 0.188962627 0.176636585
[211] -0.095673982 -0.053492547 0.335213537 0.447193169 0.068382131
[216] -0.134261999 0.520492994 -0.282383144 -0.449635649 0.102969886
[221] 0.852419695 -0.410324030 0.482200718 0.006865793 0.030423233
[226] -0.060361470 -0.092035593 -0.804045987 0.169391285 0.162159850
>
> proc.time()
user system elapsed
1.990 8.707 10.823
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 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: 0x600000938180>
> .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: 0x600000938180>
> .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: 0x600000938180>
> .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: 0x600000938180>
> 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: 0x600000924de0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000924de0>
> .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: 0x600000924de0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000924de0>
> .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: 0x600000924de0>
> 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: 0x600000934000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000934000>
> .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: 0x600000934000>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600000934000>
> .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: 0x600000934000>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600000934000>
> .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: 0x600000934000>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600000934000>
> .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: 0x600000934000>
> 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: 0x600000934180>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600000934180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000934180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000934180>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile110c81cafbaa1" "BufferedMatrixFile110c87f9d010b"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile110c81cafbaa1" "BufferedMatrixFile110c87f9d010b"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000934420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000934420>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600000934420>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600000934420>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600000934420>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600000934420>
> .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: 0x600000934600>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000934600>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600000934600>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600000934600>
> 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: 0x6000009347e0>
> .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: 0x6000009347e0>
> rm(P)
>
> proc.time()
user system elapsed
0.353 0.118 0.457
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 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
0.355 0.072 0.437