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 12:07 -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 00:39:48 -0500 (Tue, 04 Feb 2025) |
| EndedAt: 2025-02-04 00:41:14 -0500 (Tue, 04 Feb 2025) |
| EllapsedTime: 85.4 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
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###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.70.0.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: x86_64-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 Monterey 12.7.6
* 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 14.0.0 (clang-1400.0.29.202)’
* 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-x86_64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
using SDK: ‘MacOSX11.3.sdk’
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/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 x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch x86_64 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/x86_64/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-x86_64/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: x86_64-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
0.602 0.212 0.831
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: x86_64-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 474188 25.4 1035498 55.4 NA 638648 34.2
Vcells 877698 6.7 8388608 64.0 65536 2071806 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 00:40:30 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 00:40:31 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: 0x6000014bc000>
>
>
>
> 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 00:40:37 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 00:40:40 2025"
>
> ColMode(tmp2)
<pointer: 0x6000014bc000>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.5140915 -0.3685723 -0.6249777 0.7070072
[2,] 1.3153707 -1.2812095 0.7364815 0.3391511
[3,] 0.5890352 0.8490275 0.4874497 0.9722867
[4,] 0.6399357 1.0028905 -0.9137558 -0.3644999
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.5140915 0.3685723 0.6249777 0.7070072
[2,] 1.3153707 1.2812095 0.7364815 0.3391511
[3,] 0.5890352 0.8490275 0.4874497 0.9722867
[4,] 0.6399357 1.0028905 0.9137558 0.3644999
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9756750 0.6071016 0.7905553 0.8408372
[2,] 1.1468961 1.1319053 0.8581850 0.5823668
[3,] 0.7674863 0.9214269 0.6981760 0.9860460
[4,] 0.7999598 1.0014442 0.9559058 0.6037382
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.27084 31.43959 33.53053 34.11538
[2,] 37.78433 37.60026 34.31833 31.16282
[3,] 33.26390 35.06330 32.46921 35.83275
[4,] 33.63953 36.01733 35.47281 31.40188
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000014f0000>
> exp(tmp5)
<pointer: 0x6000014f0000>
> log(tmp5,2)
<pointer: 0x6000014f0000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.7904
> Min(tmp5)
[1] 53.33024
> mean(tmp5)
[1] 72.68514
> Sum(tmp5)
[1] 14537.03
> Var(tmp5)
[1] 844.0032
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 87.48264 71.87172 69.80695 72.74876 71.73647 70.85791 72.77400 72.12551
[9] 67.90305 69.54440
> rowSums(tmp5)
[1] 1749.653 1437.434 1396.139 1454.975 1434.729 1417.158 1455.480 1442.510
[9] 1358.061 1390.888
> rowVars(tmp5)
[1] 8030.18513 65.47777 61.47084 59.04447 64.46399 47.69199
[7] 44.42844 50.06896 65.09146 72.73324
> rowSd(tmp5)
[1] 89.611300 8.091834 7.840334 7.684040 8.028947 6.905939 6.665466
[8] 7.075942 8.067928 8.528378
> rowMax(tmp5)
[1] 466.79037 89.33987 82.70988 87.57080 86.55496 86.98942 83.00438
[8] 85.86101 84.95347 87.29058
> rowMin(tmp5)
[1] 56.85155 58.75486 53.33024 54.08158 54.19063 56.42473 61.25317 60.55214
[9] 56.66880 57.38904
>
> colMeans(tmp5)
[1] 109.78259 69.94734 68.42155 70.58069 67.92745 63.24460 69.75745
[8] 71.70075 73.64184 71.59934 73.24571 73.56930 73.74584 74.83113
[15] 67.41813 70.30900 69.06370 71.45526 73.31122 70.14991
> colSums(tmp5)
[1] 1097.8259 699.4734 684.2155 705.8069 679.2745 632.4460 697.5745
[8] 717.0075 736.4184 715.9934 732.4571 735.6930 737.4584 748.3113
[15] 674.1813 703.0900 690.6370 714.5526 733.1122 701.4991
> colVars(tmp5)
[1] 15776.67033 67.54805 25.51784 42.97349 90.47147 36.84840
[7] 52.31460 99.67415 44.34778 81.22090 74.40574 49.23435
[13] 58.47101 24.03323 31.06927 30.90236 58.05584 76.45721
[19] 41.87722 131.55725
> colSd(tmp5)
[1] 125.605216 8.218762 5.051519 6.555417 9.511649 6.070288
[7] 7.232883 9.983694 6.659413 9.012264 8.625876 7.016719
[13] 7.646634 4.902370 5.573982 5.558989 7.619439 8.743981
[19] 6.471261 11.469841
> colMax(tmp5)
[1] 466.79037 80.14429 75.17140 81.90379 80.05731 73.93550 80.81136
[8] 85.27458 84.95347 78.59106 86.55496 87.57080 86.98942 82.14745
[15] 75.25070 78.75969 86.24140 89.33987 83.89147 87.29058
> colMin(tmp5)
[1] 61.00830 56.42473 61.40023 62.70919 54.08158 54.19063 57.38904 57.99057
[9] 60.53288 53.33024 59.72767 61.04313 58.95502 67.80116 59.57023 61.25317
[17] 60.26114 60.71348 63.15053 55.63161
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 87.48264 71.87172 69.80695 72.74876 71.73647 70.85791 NA 72.12551
[9] 67.90305 69.54440
> rowSums(tmp5)
[1] 1749.653 1437.434 1396.139 1454.975 1434.729 1417.158 NA 1442.510
[9] 1358.061 1390.888
> rowVars(tmp5)
[1] 8030.18513 65.47777 61.47084 59.04447 64.46399 47.69199
[7] 43.11895 50.06896 65.09146 72.73324
> rowSd(tmp5)
[1] 89.611300 8.091834 7.840334 7.684040 8.028947 6.905939 6.566502
[8] 7.075942 8.067928 8.528378
> rowMax(tmp5)
[1] 466.79037 89.33987 82.70988 87.57080 86.55496 86.98942 NA
[8] 85.86101 84.95347 87.29058
> rowMin(tmp5)
[1] 56.85155 58.75486 53.33024 54.08158 54.19063 56.42473 NA 60.55214
[9] 56.66880 57.38904
>
> colMeans(tmp5)
[1] 109.78259 69.94734 68.42155 70.58069 67.92745 63.24460 NA
[8] 71.70075 73.64184 71.59934 73.24571 73.56930 73.74584 74.83113
[15] 67.41813 70.30900 69.06370 71.45526 73.31122 70.14991
> colSums(tmp5)
[1] 1097.8259 699.4734 684.2155 705.8069 679.2745 632.4460 NA
[8] 717.0075 736.4184 715.9934 732.4571 735.6930 737.4584 748.3113
[15] 674.1813 703.0900 690.6370 714.5526 733.1122 701.4991
> colVars(tmp5)
[1] 15776.67033 67.54805 25.51784 42.97349 90.47147 36.84840
[7] NA 99.67415 44.34778 81.22090 74.40574 49.23435
[13] 58.47101 24.03323 31.06927 30.90236 58.05584 76.45721
[19] 41.87722 131.55725
> colSd(tmp5)
[1] 125.605216 8.218762 5.051519 6.555417 9.511649 6.070288
[7] NA 9.983694 6.659413 9.012264 8.625876 7.016719
[13] 7.646634 4.902370 5.573982 5.558989 7.619439 8.743981
[19] 6.471261 11.469841
> colMax(tmp5)
[1] 466.79037 80.14429 75.17140 81.90379 80.05731 73.93550 NA
[8] 85.27458 84.95347 78.59106 86.55496 87.57080 86.98942 82.14745
[15] 75.25070 78.75969 86.24140 89.33987 83.89147 87.29058
> colMin(tmp5)
[1] 61.00830 56.42473 61.40023 62.70919 54.08158 54.19063 NA 57.99057
[9] 60.53288 53.33024 59.72767 61.04313 58.95502 67.80116 59.57023 61.25317
[17] 60.26114 60.71348 63.15053 55.63161
>
> Max(tmp5,na.rm=TRUE)
[1] 466.7904
> Min(tmp5,na.rm=TRUE)
[1] 53.33024
> mean(tmp5,na.rm=TRUE)
[1] 72.64431
> Sum(tmp5,na.rm=TRUE)
[1] 14456.22
> Var(tmp5,na.rm=TRUE)
[1] 847.9306
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.48264 71.87172 69.80695 72.74876 71.73647 70.85791 72.35098 72.12551
[9] 67.90305 69.54440
> rowSums(tmp5,na.rm=TRUE)
[1] 1749.653 1437.434 1396.139 1454.975 1434.729 1417.158 1374.669 1442.510
[9] 1358.061 1390.888
> rowVars(tmp5,na.rm=TRUE)
[1] 8030.18513 65.47777 61.47084 59.04447 64.46399 47.69199
[7] 43.11895 50.06896 65.09146 72.73324
> rowSd(tmp5,na.rm=TRUE)
[1] 89.611300 8.091834 7.840334 7.684040 8.028947 6.905939 6.566502
[8] 7.075942 8.067928 8.528378
> rowMax(tmp5,na.rm=TRUE)
[1] 466.79037 89.33987 82.70988 87.57080 86.55496 86.98942 83.00438
[8] 85.86101 84.95347 87.29058
> rowMin(tmp5,na.rm=TRUE)
[1] 56.85155 58.75486 53.33024 54.08158 54.19063 56.42473 61.25317 60.55214
[9] 56.66880 57.38904
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.78259 69.94734 68.42155 70.58069 67.92745 63.24460 68.52923
[8] 71.70075 73.64184 71.59934 73.24571 73.56930 73.74584 74.83113
[15] 67.41813 70.30900 69.06370 71.45526 73.31122 70.14991
> colSums(tmp5,na.rm=TRUE)
[1] 1097.8259 699.4734 684.2155 705.8069 679.2745 632.4460 616.7631
[8] 717.0075 736.4184 715.9934 732.4571 735.6930 737.4584 748.3113
[15] 674.1813 703.0900 690.6370 714.5526 733.1122 701.4991
> colVars(tmp5,na.rm=TRUE)
[1] 15776.67033 67.54805 25.51784 42.97349 90.47147 36.84840
[7] 41.88324 99.67415 44.34778 81.22090 74.40574 49.23435
[13] 58.47101 24.03323 31.06927 30.90236 58.05584 76.45721
[19] 41.87722 131.55725
> colSd(tmp5,na.rm=TRUE)
[1] 125.605216 8.218762 5.051519 6.555417 9.511649 6.070288
[7] 6.471726 9.983694 6.659413 9.012264 8.625876 7.016719
[13] 7.646634 4.902370 5.573982 5.558989 7.619439 8.743981
[19] 6.471261 11.469841
> colMax(tmp5,na.rm=TRUE)
[1] 466.79037 80.14429 75.17140 81.90379 80.05731 73.93550 79.78191
[8] 85.27458 84.95347 78.59106 86.55496 87.57080 86.98942 82.14745
[15] 75.25070 78.75969 86.24140 89.33987 83.89147 87.29058
> colMin(tmp5,na.rm=TRUE)
[1] 61.00830 56.42473 61.40023 62.70919 54.08158 54.19063 57.38904 57.99057
[9] 60.53288 53.33024 59.72767 61.04313 58.95502 67.80116 59.57023 61.25317
[17] 60.26114 60.71348 63.15053 55.63161
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.48264 71.87172 69.80695 72.74876 71.73647 70.85791 NaN 72.12551
[9] 67.90305 69.54440
> rowSums(tmp5,na.rm=TRUE)
[1] 1749.653 1437.434 1396.139 1454.975 1434.729 1417.158 0.000 1442.510
[9] 1358.061 1390.888
> rowVars(tmp5,na.rm=TRUE)
[1] 8030.18513 65.47777 61.47084 59.04447 64.46399 47.69199
[7] NA 50.06896 65.09146 72.73324
> rowSd(tmp5,na.rm=TRUE)
[1] 89.611300 8.091834 7.840334 7.684040 8.028947 6.905939 NA
[8] 7.075942 8.067928 8.528378
> rowMax(tmp5,na.rm=TRUE)
[1] 466.79037 89.33987 82.70988 87.57080 86.55496 86.98942 NA
[8] 85.86101 84.95347 87.29058
> rowMin(tmp5,na.rm=TRUE)
[1] 56.85155 58.75486 53.33024 54.08158 54.19063 56.42473 NA 60.55214
[9] 56.66880 57.38904
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.75680 68.81435 69.13261 70.64158 67.35532 62.93130 NaN
[8] 70.68745 74.07985 71.06612 73.01151 74.09504 73.59370 74.23593
[15] 67.44677 71.31521 69.07736 70.58057 72.23420 69.92045
> colSums(tmp5,na.rm=TRUE)
[1] 1032.8112 619.3291 622.1935 635.7742 606.1978 566.3817 0.0000
[8] 636.1871 666.7186 639.5951 657.1036 666.8554 662.3433 668.1234
[15] 607.0210 641.8369 621.6962 635.2251 650.1078 629.2840
> colVars(tmp5,na.rm=TRUE)
[1] 17470.39875 61.55020 23.01958 48.30348 98.09784 40.35016
[7] NA 100.58213 47.73290 88.17497 83.08939 52.27914
[13] 65.51952 23.05201 34.94370 23.37514 65.31073 77.40716
[19] 34.06225 147.40956
> colSd(tmp5,na.rm=TRUE)
[1] 132.175636 7.845393 4.797872 6.950070 9.904436 6.352178
[7] NA 10.029064 6.908900 9.390153 9.115338 7.230432
[13] 8.094413 4.801251 5.911320 4.834785 8.081505 8.798134
[19] 5.836287 12.141234
> colMax(tmp5,na.rm=TRUE)
[1] 466.79037 78.92540 75.17140 81.90379 80.05731 73.93550 -Inf
[8] 85.27458 84.95347 78.59106 86.55496 87.57080 86.98942 82.14745
[15] 75.25070 78.75969 86.24140 89.33987 83.89147 87.29058
> colMin(tmp5,na.rm=TRUE)
[1] 61.00830 56.42473 61.40023 62.70919 54.08158 54.19063 Inf 57.99057
[9] 60.53288 53.33024 59.72767 61.04313 58.95502 67.80116 59.57023 64.78391
[17] 60.26114 60.71348 63.15053 55.63161
>
>
>
>
> 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] 257.9482 171.2771 176.8015 363.9950 125.8587 299.8414 148.1842 190.2311
[9] 371.6026 175.6800
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 257.9482 171.2771 176.8015 363.9950 125.8587 299.8414 148.1842 190.2311
[9] 371.6026 175.6800
>
>
>
> 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 1.136868e-13 -2.842171e-13 -2.842171e-14
[6] 1.989520e-13 -2.842171e-14 1.136868e-13 0.000000e+00 -1.136868e-13
[11] 2.842171e-14 2.842171e-14 0.000000e+00 5.684342e-14 -1.989520e-13
[16] -2.557954e-13 2.273737e-13 8.526513e-14 1.705303e-13 1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## 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)
+ }
4 15
3 8
9 12
5 7
5 1
9 6
6 17
4 4
6 11
2 2
8 1
10 14
9 11
7 15
3 13
10 19
8 5
8 15
10 12
4 10
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] 2.537421
> Min(tmp)
[1] -2.497992
> mean(tmp)
[1] 0.01073605
> Sum(tmp)
[1] 1.073605
> Var(tmp)
[1] 0.9112792
>
> rowMeans(tmp)
[1] 0.01073605
> rowSums(tmp)
[1] 1.073605
> rowVars(tmp)
[1] 0.9112792
> rowSd(tmp)
[1] 0.9546095
> rowMax(tmp)
[1] 2.537421
> rowMin(tmp)
[1] -2.497992
>
> colMeans(tmp)
[1] 0.601672636 -0.164962544 0.078819016 0.793775917 -0.116227842
[6] 0.634570352 -0.563669408 0.505972152 0.113937136 -0.375612717
[11] 0.317797521 -1.518242405 -1.256877292 -1.062552397 0.739793502
[16] -0.043596317 -1.848266535 0.518868334 2.537421298 1.801866174
[21] -0.985454242 0.205245216 1.407649487 -0.817826052 -0.493243669
[26] 1.432760176 -0.731154192 -0.488744449 -0.367053557 -0.711984852
[31] -0.049321995 -0.749113743 0.771903429 -2.497992151 1.119667406
[36] -0.144357155 0.780932989 -0.551503162 -1.893818430 0.401672544
[41] -1.099816796 -0.801198438 -0.375202554 -1.761036191 -0.068536912
[46] -0.345435175 0.405421540 -1.044575759 0.260399598 -0.510332117
[51] 0.245570629 0.192566925 0.005216335 -0.552008821 -0.071828801
[56] -0.354338898 -0.396070847 -1.266697949 1.410448233 0.514083504
[61] 0.682407712 1.455856842 -0.405749127 -1.525139312 0.308110306
[66] 1.069069138 0.658081932 -0.646763448 -1.560285833 2.188431809
[71] 0.158177601 -1.358330143 0.126331278 -0.743804100 0.804830304
[76] 0.060725326 0.099426073 1.424279699 -0.731763185 0.715619071
[81] -0.237734907 -0.245749548 -0.247562307 -0.137456379 0.344736753
[86] 1.554426523 -0.515758032 0.189640225 -0.923328534 -0.657194694
[91] 0.597754644 1.265013042 1.463457440 0.552705460 1.879000881
[96] 0.543983691 0.828855543 1.506283862 -0.285576379 -0.900781466
> colSums(tmp)
[1] 0.601672636 -0.164962544 0.078819016 0.793775917 -0.116227842
[6] 0.634570352 -0.563669408 0.505972152 0.113937136 -0.375612717
[11] 0.317797521 -1.518242405 -1.256877292 -1.062552397 0.739793502
[16] -0.043596317 -1.848266535 0.518868334 2.537421298 1.801866174
[21] -0.985454242 0.205245216 1.407649487 -0.817826052 -0.493243669
[26] 1.432760176 -0.731154192 -0.488744449 -0.367053557 -0.711984852
[31] -0.049321995 -0.749113743 0.771903429 -2.497992151 1.119667406
[36] -0.144357155 0.780932989 -0.551503162 -1.893818430 0.401672544
[41] -1.099816796 -0.801198438 -0.375202554 -1.761036191 -0.068536912
[46] -0.345435175 0.405421540 -1.044575759 0.260399598 -0.510332117
[51] 0.245570629 0.192566925 0.005216335 -0.552008821 -0.071828801
[56] -0.354338898 -0.396070847 -1.266697949 1.410448233 0.514083504
[61] 0.682407712 1.455856842 -0.405749127 -1.525139312 0.308110306
[66] 1.069069138 0.658081932 -0.646763448 -1.560285833 2.188431809
[71] 0.158177601 -1.358330143 0.126331278 -0.743804100 0.804830304
[76] 0.060725326 0.099426073 1.424279699 -0.731763185 0.715619071
[81] -0.237734907 -0.245749548 -0.247562307 -0.137456379 0.344736753
[86] 1.554426523 -0.515758032 0.189640225 -0.923328534 -0.657194694
[91] 0.597754644 1.265013042 1.463457440 0.552705460 1.879000881
[96] 0.543983691 0.828855543 1.506283862 -0.285576379 -0.900781466
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] 0.601672636 -0.164962544 0.078819016 0.793775917 -0.116227842
[6] 0.634570352 -0.563669408 0.505972152 0.113937136 -0.375612717
[11] 0.317797521 -1.518242405 -1.256877292 -1.062552397 0.739793502
[16] -0.043596317 -1.848266535 0.518868334 2.537421298 1.801866174
[21] -0.985454242 0.205245216 1.407649487 -0.817826052 -0.493243669
[26] 1.432760176 -0.731154192 -0.488744449 -0.367053557 -0.711984852
[31] -0.049321995 -0.749113743 0.771903429 -2.497992151 1.119667406
[36] -0.144357155 0.780932989 -0.551503162 -1.893818430 0.401672544
[41] -1.099816796 -0.801198438 -0.375202554 -1.761036191 -0.068536912
[46] -0.345435175 0.405421540 -1.044575759 0.260399598 -0.510332117
[51] 0.245570629 0.192566925 0.005216335 -0.552008821 -0.071828801
[56] -0.354338898 -0.396070847 -1.266697949 1.410448233 0.514083504
[61] 0.682407712 1.455856842 -0.405749127 -1.525139312 0.308110306
[66] 1.069069138 0.658081932 -0.646763448 -1.560285833 2.188431809
[71] 0.158177601 -1.358330143 0.126331278 -0.743804100 0.804830304
[76] 0.060725326 0.099426073 1.424279699 -0.731763185 0.715619071
[81] -0.237734907 -0.245749548 -0.247562307 -0.137456379 0.344736753
[86] 1.554426523 -0.515758032 0.189640225 -0.923328534 -0.657194694
[91] 0.597754644 1.265013042 1.463457440 0.552705460 1.879000881
[96] 0.543983691 0.828855543 1.506283862 -0.285576379 -0.900781466
> colMin(tmp)
[1] 0.601672636 -0.164962544 0.078819016 0.793775917 -0.116227842
[6] 0.634570352 -0.563669408 0.505972152 0.113937136 -0.375612717
[11] 0.317797521 -1.518242405 -1.256877292 -1.062552397 0.739793502
[16] -0.043596317 -1.848266535 0.518868334 2.537421298 1.801866174
[21] -0.985454242 0.205245216 1.407649487 -0.817826052 -0.493243669
[26] 1.432760176 -0.731154192 -0.488744449 -0.367053557 -0.711984852
[31] -0.049321995 -0.749113743 0.771903429 -2.497992151 1.119667406
[36] -0.144357155 0.780932989 -0.551503162 -1.893818430 0.401672544
[41] -1.099816796 -0.801198438 -0.375202554 -1.761036191 -0.068536912
[46] -0.345435175 0.405421540 -1.044575759 0.260399598 -0.510332117
[51] 0.245570629 0.192566925 0.005216335 -0.552008821 -0.071828801
[56] -0.354338898 -0.396070847 -1.266697949 1.410448233 0.514083504
[61] 0.682407712 1.455856842 -0.405749127 -1.525139312 0.308110306
[66] 1.069069138 0.658081932 -0.646763448 -1.560285833 2.188431809
[71] 0.158177601 -1.358330143 0.126331278 -0.743804100 0.804830304
[76] 0.060725326 0.099426073 1.424279699 -0.731763185 0.715619071
[81] -0.237734907 -0.245749548 -0.247562307 -0.137456379 0.344736753
[86] 1.554426523 -0.515758032 0.189640225 -0.923328534 -0.657194694
[91] 0.597754644 1.265013042 1.463457440 0.552705460 1.879000881
[96] 0.543983691 0.828855543 1.506283862 -0.285576379 -0.900781466
> colMedians(tmp)
[1] 0.601672636 -0.164962544 0.078819016 0.793775917 -0.116227842
[6] 0.634570352 -0.563669408 0.505972152 0.113937136 -0.375612717
[11] 0.317797521 -1.518242405 -1.256877292 -1.062552397 0.739793502
[16] -0.043596317 -1.848266535 0.518868334 2.537421298 1.801866174
[21] -0.985454242 0.205245216 1.407649487 -0.817826052 -0.493243669
[26] 1.432760176 -0.731154192 -0.488744449 -0.367053557 -0.711984852
[31] -0.049321995 -0.749113743 0.771903429 -2.497992151 1.119667406
[36] -0.144357155 0.780932989 -0.551503162 -1.893818430 0.401672544
[41] -1.099816796 -0.801198438 -0.375202554 -1.761036191 -0.068536912
[46] -0.345435175 0.405421540 -1.044575759 0.260399598 -0.510332117
[51] 0.245570629 0.192566925 0.005216335 -0.552008821 -0.071828801
[56] -0.354338898 -0.396070847 -1.266697949 1.410448233 0.514083504
[61] 0.682407712 1.455856842 -0.405749127 -1.525139312 0.308110306
[66] 1.069069138 0.658081932 -0.646763448 -1.560285833 2.188431809
[71] 0.158177601 -1.358330143 0.126331278 -0.743804100 0.804830304
[76] 0.060725326 0.099426073 1.424279699 -0.731763185 0.715619071
[81] -0.237734907 -0.245749548 -0.247562307 -0.137456379 0.344736753
[86] 1.554426523 -0.515758032 0.189640225 -0.923328534 -0.657194694
[91] 0.597754644 1.265013042 1.463457440 0.552705460 1.879000881
[96] 0.543983691 0.828855543 1.506283862 -0.285576379 -0.900781466
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.6016726 -0.1649625 0.07881902 0.7937759 -0.1162278 0.6345704 -0.5636694
[2,] 0.6016726 -0.1649625 0.07881902 0.7937759 -0.1162278 0.6345704 -0.5636694
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.5059722 0.1139371 -0.3756127 0.3177975 -1.518242 -1.256877 -1.062552
[2,] 0.5059722 0.1139371 -0.3756127 0.3177975 -1.518242 -1.256877 -1.062552
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.7397935 -0.04359632 -1.848267 0.5188683 2.537421 1.801866 -0.9854542
[2,] 0.7397935 -0.04359632 -1.848267 0.5188683 2.537421 1.801866 -0.9854542
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.2052452 1.407649 -0.8178261 -0.4932437 1.43276 -0.7311542 -0.4887444
[2,] 0.2052452 1.407649 -0.8178261 -0.4932437 1.43276 -0.7311542 -0.4887444
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.3670536 -0.7119849 -0.04932199 -0.7491137 0.7719034 -2.497992 1.119667
[2,] -0.3670536 -0.7119849 -0.04932199 -0.7491137 0.7719034 -2.497992 1.119667
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.1443572 0.780933 -0.5515032 -1.893818 0.4016725 -1.099817 -0.8011984
[2,] -0.1443572 0.780933 -0.5515032 -1.893818 0.4016725 -1.099817 -0.8011984
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.3752026 -1.761036 -0.06853691 -0.3454352 0.4054215 -1.044576 0.2603996
[2,] -0.3752026 -1.761036 -0.06853691 -0.3454352 0.4054215 -1.044576 0.2603996
[,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.5103321 0.2455706 0.1925669 0.005216335 -0.5520088 -0.0718288
[2,] -0.5103321 0.2455706 0.1925669 0.005216335 -0.5520088 -0.0718288
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.3543389 -0.3960708 -1.266698 1.410448 0.5140835 0.6824077 1.455857
[2,] -0.3543389 -0.3960708 -1.266698 1.410448 0.5140835 0.6824077 1.455857
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] -0.4057491 -1.525139 0.3081103 1.069069 0.6580819 -0.6467634 -1.560286
[2,] -0.4057491 -1.525139 0.3081103 1.069069 0.6580819 -0.6467634 -1.560286
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 2.188432 0.1581776 -1.35833 0.1263313 -0.7438041 0.8048303 0.06072533
[2,] 2.188432 0.1581776 -1.35833 0.1263313 -0.7438041 0.8048303 0.06072533
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] 0.09942607 1.42428 -0.7317632 0.7156191 -0.2377349 -0.2457495 -0.2475623
[2,] 0.09942607 1.42428 -0.7317632 0.7156191 -0.2377349 -0.2457495 -0.2475623
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.1374564 0.3447368 1.554427 -0.515758 0.1896402 -0.9233285 -0.6571947
[2,] -0.1374564 0.3447368 1.554427 -0.515758 0.1896402 -0.9233285 -0.6571947
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 0.5977546 1.265013 1.463457 0.5527055 1.879001 0.5439837 0.8288555
[2,] 0.5977546 1.265013 1.463457 0.5527055 1.879001 0.5439837 0.8288555
[,98] [,99] [,100]
[1,] 1.506284 -0.2855764 -0.9007815
[2,] 1.506284 -0.2855764 -0.9007815
>
>
> Max(tmp2)
[1] 2.95658
> Min(tmp2)
[1] -1.932972
> mean(tmp2)
[1] 0.08675139
> Sum(tmp2)
[1] 8.675139
> Var(tmp2)
[1] 1.011206
>
> rowMeans(tmp2)
[1] -0.183956521 -0.263573876 0.440580053 -0.065539882 -0.508846295
[6] -0.752303977 0.431224634 -0.623134651 -0.533380652 0.180257369
[11] -1.427950943 0.362736040 -1.582134596 -1.228142423 1.459128037
[16] 0.465683051 0.236544271 -0.551555696 1.285045212 1.168342633
[21] 2.151744665 -1.005262440 0.229810314 0.341678408 -1.094866167
[26] -0.964679354 0.482140791 -0.121211968 -1.229755540 1.714634891
[31] 0.232026935 -0.231958399 0.493216092 -0.586873172 1.409939228
[36] 1.454551285 0.998174988 -0.394444106 0.325478585 1.451204800
[41] 0.214693140 1.216613429 0.079975453 1.827802544 0.628984883
[46] 0.202734917 1.264857366 0.215501289 -0.300339726 -0.762713166
[51] -1.671674575 0.001562922 -1.294377855 1.265711952 -0.495737428
[56] -0.225852673 0.404902712 -0.488426492 -0.223439604 0.719217996
[61] 0.421983462 -0.447083346 0.030565115 -1.566335957 -1.872552664
[66] -1.166315606 1.104850820 2.471692106 0.113331727 0.343635037
[71] 0.072714050 0.227102497 -1.932972323 2.956579777 0.869086731
[76] -1.082983137 1.496602313 -0.307217929 -0.574230253 0.294228969
[81] -0.253465062 1.368270600 -1.698594142 0.513232165 0.638557275
[86] -1.333773521 1.165787313 -1.915557044 0.375606942 0.615545566
[91] -0.106829486 -1.018351599 1.064623800 -0.186378915 -0.817739145
[96] 1.601504616 0.133757346 0.300350270 0.558773303 -0.327431166
> rowSums(tmp2)
[1] -0.183956521 -0.263573876 0.440580053 -0.065539882 -0.508846295
[6] -0.752303977 0.431224634 -0.623134651 -0.533380652 0.180257369
[11] -1.427950943 0.362736040 -1.582134596 -1.228142423 1.459128037
[16] 0.465683051 0.236544271 -0.551555696 1.285045212 1.168342633
[21] 2.151744665 -1.005262440 0.229810314 0.341678408 -1.094866167
[26] -0.964679354 0.482140791 -0.121211968 -1.229755540 1.714634891
[31] 0.232026935 -0.231958399 0.493216092 -0.586873172 1.409939228
[36] 1.454551285 0.998174988 -0.394444106 0.325478585 1.451204800
[41] 0.214693140 1.216613429 0.079975453 1.827802544 0.628984883
[46] 0.202734917 1.264857366 0.215501289 -0.300339726 -0.762713166
[51] -1.671674575 0.001562922 -1.294377855 1.265711952 -0.495737428
[56] -0.225852673 0.404902712 -0.488426492 -0.223439604 0.719217996
[61] 0.421983462 -0.447083346 0.030565115 -1.566335957 -1.872552664
[66] -1.166315606 1.104850820 2.471692106 0.113331727 0.343635037
[71] 0.072714050 0.227102497 -1.932972323 2.956579777 0.869086731
[76] -1.082983137 1.496602313 -0.307217929 -0.574230253 0.294228969
[81] -0.253465062 1.368270600 -1.698594142 0.513232165 0.638557275
[86] -1.333773521 1.165787313 -1.915557044 0.375606942 0.615545566
[91] -0.106829486 -1.018351599 1.064623800 -0.186378915 -0.817739145
[96] 1.601504616 0.133757346 0.300350270 0.558773303 -0.327431166
> 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] -0.183956521 -0.263573876 0.440580053 -0.065539882 -0.508846295
[6] -0.752303977 0.431224634 -0.623134651 -0.533380652 0.180257369
[11] -1.427950943 0.362736040 -1.582134596 -1.228142423 1.459128037
[16] 0.465683051 0.236544271 -0.551555696 1.285045212 1.168342633
[21] 2.151744665 -1.005262440 0.229810314 0.341678408 -1.094866167
[26] -0.964679354 0.482140791 -0.121211968 -1.229755540 1.714634891
[31] 0.232026935 -0.231958399 0.493216092 -0.586873172 1.409939228
[36] 1.454551285 0.998174988 -0.394444106 0.325478585 1.451204800
[41] 0.214693140 1.216613429 0.079975453 1.827802544 0.628984883
[46] 0.202734917 1.264857366 0.215501289 -0.300339726 -0.762713166
[51] -1.671674575 0.001562922 -1.294377855 1.265711952 -0.495737428
[56] -0.225852673 0.404902712 -0.488426492 -0.223439604 0.719217996
[61] 0.421983462 -0.447083346 0.030565115 -1.566335957 -1.872552664
[66] -1.166315606 1.104850820 2.471692106 0.113331727 0.343635037
[71] 0.072714050 0.227102497 -1.932972323 2.956579777 0.869086731
[76] -1.082983137 1.496602313 -0.307217929 -0.574230253 0.294228969
[81] -0.253465062 1.368270600 -1.698594142 0.513232165 0.638557275
[86] -1.333773521 1.165787313 -1.915557044 0.375606942 0.615545566
[91] -0.106829486 -1.018351599 1.064623800 -0.186378915 -0.817739145
[96] 1.601504616 0.133757346 0.300350270 0.558773303 -0.327431166
> rowMin(tmp2)
[1] -0.183956521 -0.263573876 0.440580053 -0.065539882 -0.508846295
[6] -0.752303977 0.431224634 -0.623134651 -0.533380652 0.180257369
[11] -1.427950943 0.362736040 -1.582134596 -1.228142423 1.459128037
[16] 0.465683051 0.236544271 -0.551555696 1.285045212 1.168342633
[21] 2.151744665 -1.005262440 0.229810314 0.341678408 -1.094866167
[26] -0.964679354 0.482140791 -0.121211968 -1.229755540 1.714634891
[31] 0.232026935 -0.231958399 0.493216092 -0.586873172 1.409939228
[36] 1.454551285 0.998174988 -0.394444106 0.325478585 1.451204800
[41] 0.214693140 1.216613429 0.079975453 1.827802544 0.628984883
[46] 0.202734917 1.264857366 0.215501289 -0.300339726 -0.762713166
[51] -1.671674575 0.001562922 -1.294377855 1.265711952 -0.495737428
[56] -0.225852673 0.404902712 -0.488426492 -0.223439604 0.719217996
[61] 0.421983462 -0.447083346 0.030565115 -1.566335957 -1.872552664
[66] -1.166315606 1.104850820 2.471692106 0.113331727 0.343635037
[71] 0.072714050 0.227102497 -1.932972323 2.956579777 0.869086731
[76] -1.082983137 1.496602313 -0.307217929 -0.574230253 0.294228969
[81] -0.253465062 1.368270600 -1.698594142 0.513232165 0.638557275
[86] -1.333773521 1.165787313 -1.915557044 0.375606942 0.615545566
[91] -0.106829486 -1.018351599 1.064623800 -0.186378915 -0.817739145
[96] 1.601504616 0.133757346 0.300350270 0.558773303 -0.327431166
>
> colMeans(tmp2)
[1] 0.08675139
> colSums(tmp2)
[1] 8.675139
> colVars(tmp2)
[1] 1.011206
> colSd(tmp2)
[1] 1.005588
> colMax(tmp2)
[1] 2.95658
> colMin(tmp2)
[1] -1.932972
> colMedians(tmp2)
[1] 0.1570074
> colRanges(tmp2)
[,1]
[1,] -1.932972
[2,] 2.956580
>
> 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] 1.8460094 0.2961248 2.3029075 3.0799779 3.3257070 -3.0798014
[7] -0.7038997 1.1723957 -8.2694120 0.8323506
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8017189
[2,] -0.7603030
[3,] 0.3096222
[4,] 0.7261680
[5,] 2.0962229
>
> rowApply(tmp,sum)
[1] -2.0280069 0.7564602 6.9999978 -0.5828130 2.8585299 -2.2433278
[7] -0.2886259 -3.7417590 0.6082190 -1.5363143
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 2 5 6 9 10 1 2 5 5 10
[2,] 5 1 10 8 8 6 10 1 3 1
[3,] 10 6 2 3 6 9 5 3 9 5
[4,] 8 10 3 4 1 10 6 6 10 4
[5,] 4 8 1 10 7 4 9 8 8 6
[6,] 1 9 8 5 4 2 7 4 1 7
[7,] 9 4 4 1 9 3 8 10 4 3
[8,] 7 7 7 6 3 8 4 2 7 8
[9,] 3 2 5 2 5 7 1 9 2 2
[10,] 6 3 9 7 2 5 3 7 6 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.4393042 -0.3386134 0.3183947 -0.1186315 1.2548939 4.0127787
[7] 1.3412990 1.5053138 1.0557234 -1.4026140 -0.8241976 2.0562824
[13] -1.7045023 -1.5355672 -2.4466490 0.5103387 1.0583916 -2.3726096
[19] 0.6628793 -2.6247744
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.48501436
[2,] -0.38293401
[3,] -0.05886909
[4,] 0.66222468
[5,] 1.70389700
>
> rowApply(tmp,sum)
[1] 3.4851169 -1.0213350 3.2778981 -0.6048533 -4.2893858
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 1 20 15 8 8
[2,] 17 10 8 7 10
[3,] 9 11 12 11 14
[4,] 2 19 16 5 9
[5,] 7 18 5 18 12
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.48501436 1.0341180 -0.16131336 -0.9889640 -0.1875366 1.5494583
[2,] 1.70389700 -0.2123908 -0.08725920 1.3651389 0.8553834 0.3467429
[3,] 0.66222468 -0.2495447 0.21201065 0.7065106 -0.3145590 1.2483996
[4,] -0.05886909 -0.5821713 0.09421987 -0.8378973 1.0284587 0.5569950
[5,] -0.38293401 -0.3286244 0.26073677 -0.3634197 -0.1268526 0.3111829
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.2952787 0.2226027535 2.19865075 -0.1821991 -0.6269618 0.48235466
[2,] 0.5558791 0.5740707776 -0.96410585 0.7988293 -0.7983119 -0.04704562
[3,] 1.3701744 -0.0992777539 -0.23551682 1.6355218 -0.3094602 1.63880671
[4,] -1.3728040 0.0005479801 0.14938459 -2.3784610 0.0831623 1.74245338
[5,] -0.5072291 0.8073700074 -0.09268922 -1.2763051 0.8273739 -1.76028676
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.8075014 -0.6503344 0.31490807 0.5927644 0.32628113 0.2461790
[2,] -0.7844932 -0.5775462 -1.08898679 -0.2958582 -0.01551979 -1.1855162
[3,] -0.5059754 -1.1101978 -0.06192541 0.2500168 0.36418182 -0.3547033
[4,] -0.8417300 0.4427214 -1.18873075 -0.6139245 0.62763733 0.2630948
[5,] 1.2351978 0.3597898 -0.42191410 0.5773402 -0.24418890 -1.3416639
[,19] [,20]
[1,] 0.6566345 -0.3442884
[2,] -0.7750496 -0.3891929
[3,] -0.2726951 -1.2960936
[4,] 1.7856463 0.4954131
[5,] -0.7316568 -1.0906125
>
>
> 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 : 650 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 : 562 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-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 1.909674 -0.09260703 0.498084 -0.03323992 1.00846 -1.73208 -0.4831878
col8 col9 col10 col11 col12 col13 col14 col15
row1 1.604958 1.760382 0.6592904 2.588081 -2.404761 1.50159 -2.52827 -2.051197
col16 col17 col18 col19 col20
row1 0.1325836 -0.4699077 0.6204899 -0.2588035 -0.5707402
> tmp[,"col10"]
col10
row1 0.6592904
row2 1.3304621
row3 0.6255414
row4 1.4658745
row5 -0.2522519
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 1.90967417 -0.09260703 0.498083956 -0.03323992 1.008460 -1.732080
row5 0.06959473 1.81551500 0.007305859 -0.78207549 -1.445471 1.602404
col7 col8 col9 col10 col11 col12 col13
row1 -0.4831878 1.604958 1.760382 0.6592904 2.588081 -2.4047606 1.5015904
row5 2.4650488 1.237019 1.032706 -0.2522519 1.506272 0.3057758 -0.1507529
col14 col15 col16 col17 col18 col19 col20
row1 -2.528270 -2.051197 0.1325836 -0.4699077 0.6204899 -0.2588035 -0.5707402
row5 1.354269 -0.388302 -0.3211829 0.5491110 -0.7541373 0.5420821 0.6332146
> tmp[,c("col6","col20")]
col6 col20
row1 -1.7320799 -0.5707402
row2 2.9694628 1.1476862
row3 -0.2812736 -0.6139874
row4 0.2826005 -0.6414885
row5 1.6024044 0.6332146
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.732080 -0.5707402
row5 1.602404 0.6332146
>
>
>
>
> 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 50.27744 49.8822 49.89919 51.79403 51.37771 105.7877 49.2601 47.72249
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.91098 50.2827 49.90793 49.49766 50.20473 50.50048 50.11832 50.22772
col17 col18 col19 col20
row1 50.69191 49.57847 50.78884 104.1763
> tmp[,"col10"]
col10
row1 50.28270
row2 29.60872
row3 29.30065
row4 31.01962
row5 50.25373
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.27744 49.88220 49.89919 51.79403 51.37771 105.7877 49.26010 47.72249
row5 50.51230 49.82826 52.40479 48.98547 51.44545 105.1508 51.35262 49.40558
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.91098 50.28270 49.90793 49.49766 50.20473 50.50048 50.11832 50.22772
row5 49.64918 50.25373 49.54058 50.16807 49.40749 50.19976 50.03846 48.64561
col17 col18 col19 col20
row1 50.69191 49.57847 50.78884 104.1763
row5 49.92876 50.39391 49.73940 104.7953
> tmp[,c("col6","col20")]
col6 col20
row1 105.78767 104.17625
row2 74.32516 75.43799
row3 76.43120 75.36415
row4 75.59931 74.99091
row5 105.15077 104.79533
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.7877 104.1763
row5 105.1508 104.7953
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.7877 104.1763
row5 105.1508 104.7953
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.2088890
[2,] -0.5252352
[3,] 1.4767448
[4,] -1.0646221
[5,] -1.2414558
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.9733381 -0.5751563
[2,] 0.8139470 -1.0240337
[3,] 0.1623051 0.7532597
[4,] 1.7343151 -2.1261913
[5,] -0.5879139 -1.4720302
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.3509797 -0.4243261
[2,] -2.2255987 -0.2770550
[3,] -1.1974867 -0.6466171
[4,] 1.3419083 -1.3296794
[5,] 0.5524406 0.1696859
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.3509797
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.3509797
[2,] -2.2255987
>
>
>
> 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 -1.0938509 -1.004341 -0.4270229 0.4651515 0.1030819 -1.6967288 1.3333038
row1 -0.2826371 -1.227557 -1.2893811 1.7796031 0.2804823 -0.4510582 -0.3218276
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -1.7209723 1.9966326 -0.05622325 -0.6774970 -0.228001 0.2067511 1.39701019
row1 0.4115266 0.5579799 0.41585353 0.1010964 2.077937 0.4773228 0.08246275
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -1.2977466 0.0932216 0.6873312 0.1081629 -0.4720911 0.7887280
row1 0.8272865 0.3580718 -0.4292304 0.7616397 -1.5094483 0.4481654
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.1963406 0.4001278 -1.076031 0.2964687 -1.061527 0.4343241 -0.8046574
[,8] [,9] [,10]
row2 -0.3353526 0.2905646 -1.101653
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.072978 -1.189921 -0.6807817 -0.1573065 -0.3939618 -0.2759849 0.5758342
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.7526603 0.7419944 0.7538755 0.2060046 1.019058 0.767128 2.23314
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.231316 -1.422809 -0.8426541 0.726272 0.6032613 0.3810405
>
>
> 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: 0x6000014fc060>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMddf719f9f8d8"
[2] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMddf76a403a3a"
[3] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMddf71eaeec55"
[4] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMddf76e1dd02f"
[5] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMddf7674ef623"
[6] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMddf77101a8d1"
[7] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMddf723f26b4d"
[8] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMddf7629eab"
[9] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMddf74a9eecbf"
[10] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMddf77c915df"
[11] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMddf722bae777"
[12] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMddf71cb24771"
[13] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMddf77c705a6e"
[14] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMddf734412b95"
[15] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMddf722945e00"
>
>
> ### 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: 0x6000014a01e0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000014a01e0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6000014a01e0>
> rowMedians(tmp)
[1] 0.0035761641 -0.1040322152 -0.2504694126 -0.1531715600 0.1554015504
[6] 0.0146206242 0.4051993108 -1.0051758430 -0.2228014683 0.7515507228
[11] -0.4068303112 0.5313413122 -0.1826784010 -0.4769876444 -0.3843536569
[16] 0.0043686935 0.5424999918 0.1165037830 0.2945930637 0.1044685726
[21] -0.0075075800 0.1094042592 0.5453805001 0.1966804654 0.3836507337
[26] 0.1796886975 0.2429280226 0.4775342326 -0.4603582536 -0.2676103534
[31] -0.5019302995 0.3532026501 0.3956769174 0.0066881232 0.3647856881
[36] 0.3750608559 0.0245339169 -0.1382076532 0.0718561734 0.0727720454
[41] 0.2622059874 -0.1067258612 -0.0600484619 -0.7128266281 0.0800038032
[46] -0.2200284984 0.3315678258 0.4163733844 0.1292936781 -0.3247414973
[51] -0.1452068494 0.6673067202 -0.0617876443 0.0916527681 -0.1276226693
[56] 0.1650911723 0.4033064161 -0.0783557295 0.4792459698 0.2426946772
[61] -0.2246277802 0.0171734883 0.0747427977 0.2092679907 0.4327730023
[66] -0.0171942161 -0.0992323748 0.3494106228 -0.1684624168 0.2853883253
[71] 0.0704839872 -0.2657050492 -0.1687321360 -0.1504786953 0.0591890221
[76] -0.1723418718 -0.6555980199 -0.7340816783 -0.4260345145 0.2383603655
[81] -0.2327022511 -0.2317865055 -0.3605409113 0.4297760488 -0.1769575402
[86] 0.1165816414 -0.0597566145 -0.0260138988 -0.1223887222 0.0892396995
[91] 0.3503383741 0.2487215967 -0.0110375669 0.2554754774 -0.0332505056
[96] 0.4221780464 0.3744879631 0.4594837950 -0.0936310397 0.1690020179
[101] 0.1884841624 -0.5583610822 0.5850229629 0.0746453102 0.5669493099
[106] 0.0208408379 0.2406315037 -0.0930212382 0.3718332376 0.0627000584
[111] -0.2185385039 0.1369442917 0.4877912446 0.0098938127 0.0026731622
[116] 0.6893559415 -0.3180226718 -0.2755960851 0.1036331619 0.5647578637
[121] 0.2652454044 0.8467333674 0.1663823630 -0.1910261774 -0.0096605725
[126] 0.2929052715 -0.5613652883 0.2730123907 -0.1421099637 -0.0570231996
[131] -0.3111881584 0.1755112622 -0.3338029861 0.2250147369 0.3689177812
[136] 0.4070142947 -0.2153024548 0.2539692184 0.2790529826 -0.2763960763
[141] -0.0533141376 0.0779742564 -0.3976899425 0.2284674944 0.3751710709
[146] 0.2027951644 -0.2260303780 0.5167984689 -0.0373356467 0.1563467068
[151] 0.1471624379 -0.2107219578 0.0088983961 0.2321897771 0.2271539308
[156] -0.0136959852 0.0562073643 -0.2544491052 -0.2499331374 0.2379580496
[161] -0.5436081273 -0.0459076631 0.0420954237 0.2035721421 0.0321038072
[166] -0.1603489005 0.1208462776 0.2939092013 0.0295338097 0.2041681751
[171] -0.1041820383 0.3320139722 -0.0378891870 -0.0210987226 -0.7909034083
[176] 0.0621289715 0.6603287477 -0.2129895280 0.0129849374 0.3775090735
[181] -0.3345407627 -0.7341888323 0.5486595021 -0.3158821874 -0.5200891287
[186] -0.2289468981 -0.5154019422 -0.1707034138 0.1324762166 -0.2256623120
[191] -0.0516057694 0.3119201376 0.5811226218 -0.1359111832 -0.3057230340
[196] -0.2225422467 0.1041914987 -0.0523571337 -0.2253181480 -0.1368576973
[201] -0.2363396927 -0.2345699301 -0.2848576803 0.4014776388 -0.0615824000
[206] -0.0483322887 0.5788233141 -0.0468328975 -0.3989491335 0.2628577973
[211] 0.0482573677 -0.0334566927 0.7228344058 0.0720949805 0.0441964022
[216] 0.2979798988 -0.4452236549 -0.2203262004 0.2572667397 -0.4199482857
[221] -0.0731343637 0.3915217784 -0.0398365900 -0.1046345297 -0.1799549843
[226] -0.2953180783 -0.0001444492 -0.1665129723 0.3694563252 -0.6723477722
>
> proc.time()
user system elapsed
5.217 19.979 29.880
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: x86_64-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: 0x600000454000>
> .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: 0x600000454000>
> .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: 0x600000454000>
> .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: 0x600000454000>
> 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: 0x600000464120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000464120>
> .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: 0x600000464120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000464120>
> .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: 0x600000464120>
> 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: 0x600000440000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000440000>
> .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: 0x600000440000>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600000440000>
> .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: 0x600000440000>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600000440000>
> .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: 0x600000440000>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600000440000>
> .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: 0x600000440000>
> 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: 0x600000440180>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600000440180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000440180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000440180>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilee1d33c7b46cd" "BufferedMatrixFilee1d369d3800a"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilee1d33c7b46cd" "BufferedMatrixFilee1d369d3800a"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000440420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000440420>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600000440420>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600000440420>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600000440420>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600000440420>
> .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: 0x600000464180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000464180>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600000464180>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600000464180>
> 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: 0x600000464300>
> .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: 0x600000464300>
> rm(P)
>
> proc.time()
user system elapsed
0.605 0.223 0.892
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: x86_64-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
0.588 0.141 0.726