Ben Bolstad
| Snapshot Date: 2025-01-02 13:00 -0500 (Thu, 02 Jan 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 2025-01-09 12:07 -0500 (Thu, 09 Jan 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" | 4744 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves" | 4487 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4515 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4467 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4358 |
| 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: 2025-01-03 00:27:54 -0500 (Fri, 03 Jan 2025) |
| EndedAt: 2025-01-03 00:29:08 -0500 (Fri, 03 Jan 2025) |
| EllapsedTime: 74.0 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: 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
0.597 0.208 0.768
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] "Fri Jan 3 00:28:28 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Jan 3 00:28:29 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: 0x6000035a4120>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Jan 3 00:28:35 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Jan 3 00:28:38 2025"
>
> ColMode(tmp2)
<pointer: 0x6000035a4120>
>
>
>
> ### 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,] 99.65880487 0.1237992 0.8327231 0.7942049
[2,] -0.42704824 -0.1121095 -1.3038416 -0.2314927
[3,] -0.03861886 0.9777902 1.3882805 -0.2139120
[4,] -2.23301102 0.2432721 0.1165189 -0.9224491
> 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,] 99.65880487 0.1237992 0.8327231 0.7942049
[2,] 0.42704824 0.1121095 1.3038416 0.2314927
[3,] 0.03861886 0.9777902 1.3882805 0.2139120
[4,] 2.23301102 0.2432721 0.1165189 0.9224491
> 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,] 9.9829257 0.3518511 0.9125366 0.8911817
[2,] 0.6534893 0.3348276 1.1418588 0.4811369
[3,] 0.1965168 0.9888327 1.1782532 0.4625062
[4,] 1.4943263 0.4932262 0.3413487 0.9604421
>
> 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,] 224.48806 28.64231 34.95809 34.70602
[2,] 31.96194 28.46039 37.72243 30.04286
[3,] 27.00379 35.86612 38.17081 29.83897
[4,] 42.17627 30.17553 28.53001 35.52687
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000035ac360>
> exp(tmp5)
<pointer: 0x6000035ac360>
> log(tmp5,2)
<pointer: 0x6000035ac360>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.2425
> Min(tmp5)
[1] 53.5904
> mean(tmp5)
[1] 72.44727
> Sum(tmp5)
[1] 14489.45
> Var(tmp5)
[1] 864.6221
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.09098 69.61246 65.90953 72.17400 71.73949 73.37879 64.88032 72.51818
[9] 73.28091 69.88807
> rowSums(tmp5)
[1] 1821.820 1392.249 1318.191 1443.480 1434.790 1467.576 1297.606 1450.364
[9] 1465.618 1397.761
> rowVars(tmp5)
[1] 7907.64138 51.28537 57.66682 78.61714 67.65196 83.71524
[7] 51.52469 65.55131 95.08998 108.27955
> rowSd(tmp5)
[1] 88.924920 7.161381 7.593867 8.866631 8.225081 9.149603 7.178070
[8] 8.096377 9.751409 10.405746
> rowMax(tmp5)
[1] 467.24249 81.43611 79.44754 87.78439 86.54510 93.98638 78.57750
[8] 85.46389 87.22465 95.75642
> rowMin(tmp5)
[1] 55.65178 57.18805 53.59040 54.46574 57.11862 58.99569 54.60135 58.57995
[9] 58.58825 55.12072
>
> colMeans(tmp5)
[1] 111.51236 65.03634 71.87942 68.21795 68.99111 67.57128 70.32939
[8] 71.11852 71.48255 76.11607 73.46902 70.84168 68.54254 70.89692
[15] 66.13775 73.66353 70.08455 71.87819 69.50336 71.67295
> colSums(tmp5)
[1] 1115.1236 650.3634 718.7942 682.1795 689.9111 675.7128 703.2939
[8] 711.1852 714.8255 761.1607 734.6902 708.4168 685.4254 708.9692
[15] 661.3775 736.6353 700.8455 718.7819 695.0336 716.7295
> colVars(tmp5)
[1] 15695.64955 51.62046 77.75749 48.42597 83.90585 49.65430
[7] 153.96596 52.33096 90.26854 35.94796 40.10920 47.22152
[13] 81.28057 112.56628 80.51703 124.46864 87.59376 121.52375
[19] 90.76832 66.28100
> colSd(tmp5)
[1] 125.282279 7.184738 8.818021 6.958877 9.160014 7.046581
[7] 12.408302 7.234014 9.500976 5.995662 6.333183 6.871792
[13] 9.015574 10.609726 8.973128 11.156552 9.359154 11.023781
[19] 9.527241 8.141314
> colMax(tmp5)
[1] 467.24249 75.59025 86.54510 81.91755 87.99840 79.51661 95.75642
[8] 81.43611 85.04198 86.95918 81.32835 82.60708 83.52979 87.31384
[15] 80.21257 90.94910 82.55017 93.98638 85.88625 79.62664
> colMin(tmp5)
[1] 56.20484 57.82404 59.38147 59.67811 55.65178 54.46574 53.59040 59.71594
[9] 59.43708 69.89459 62.28462 60.59632 56.86136 57.69820 55.12072 57.18088
[17] 56.97239 54.60135 55.37893 57.18805
>
>
> ### 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] 91.09098 69.61246 65.90953 72.17400 71.73949 73.37879 64.88032 72.51818
[9] 73.28091 NA
> rowSums(tmp5)
[1] 1821.820 1392.249 1318.191 1443.480 1434.790 1467.576 1297.606 1450.364
[9] 1465.618 NA
> rowVars(tmp5)
[1] 7907.64138 51.28537 57.66682 78.61714 67.65196 83.71524
[7] 51.52469 65.55131 95.08998 108.65823
> rowSd(tmp5)
[1] 88.924920 7.161381 7.593867 8.866631 8.225081 9.149603 7.178070
[8] 8.096377 9.751409 10.423926
> rowMax(tmp5)
[1] 467.24249 81.43611 79.44754 87.78439 86.54510 93.98638 78.57750
[8] 85.46389 87.22465 NA
> rowMin(tmp5)
[1] 55.65178 57.18805 53.59040 54.46574 57.11862 58.99569 54.60135 58.57995
[9] 58.58825 NA
>
> colMeans(tmp5)
[1] 111.51236 65.03634 71.87942 68.21795 68.99111 67.57128 70.32939
[8] 71.11852 71.48255 76.11607 73.46902 70.84168 68.54254 70.89692
[15] 66.13775 73.66353 70.08455 71.87819 69.50336 NA
> colSums(tmp5)
[1] 1115.1236 650.3634 718.7942 682.1795 689.9111 675.7128 703.2939
[8] 711.1852 714.8255 761.1607 734.6902 708.4168 685.4254 708.9692
[15] 661.3775 736.6353 700.8455 718.7819 695.0336 NA
> colVars(tmp5)
[1] 15695.64955 51.62046 77.75749 48.42597 83.90585 49.65430
[7] 153.96596 52.33096 90.26854 35.94796 40.10920 47.22152
[13] 81.28057 112.56628 80.51703 124.46864 87.59376 121.52375
[19] 90.76832 NA
> colSd(tmp5)
[1] 125.282279 7.184738 8.818021 6.958877 9.160014 7.046581
[7] 12.408302 7.234014 9.500976 5.995662 6.333183 6.871792
[13] 9.015574 10.609726 8.973128 11.156552 9.359154 11.023781
[19] 9.527241 NA
> colMax(tmp5)
[1] 467.24249 75.59025 86.54510 81.91755 87.99840 79.51661 95.75642
[8] 81.43611 85.04198 86.95918 81.32835 82.60708 83.52979 87.31384
[15] 80.21257 90.94910 82.55017 93.98638 85.88625 NA
> colMin(tmp5)
[1] 56.20484 57.82404 59.38147 59.67811 55.65178 54.46574 53.59040 59.71594
[9] 59.43708 69.89459 62.28462 60.59632 56.86136 57.69820 55.12072 57.18088
[17] 56.97239 54.60135 55.37893 NA
>
> Max(tmp5,na.rm=TRUE)
[1] 467.2425
> Min(tmp5,na.rm=TRUE)
[1] 53.5904
> mean(tmp5,na.rm=TRUE)
[1] 72.50947
> Sum(tmp5,na.rm=TRUE)
[1] 14429.38
> Var(tmp5,na.rm=TRUE)
[1] 868.2113
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.09098 69.61246 65.90953 72.17400 71.73949 73.37879 64.88032 72.51818
[9] 73.28091 70.40480
> rowSums(tmp5,na.rm=TRUE)
[1] 1821.820 1392.249 1318.191 1443.480 1434.790 1467.576 1297.606 1450.364
[9] 1465.618 1337.691
> rowVars(tmp5,na.rm=TRUE)
[1] 7907.64138 51.28537 57.66682 78.61714 67.65196 83.71524
[7] 51.52469 65.55131 95.08998 108.65823
> rowSd(tmp5,na.rm=TRUE)
[1] 88.924920 7.161381 7.593867 8.866631 8.225081 9.149603 7.178070
[8] 8.096377 9.751409 10.423926
> rowMax(tmp5,na.rm=TRUE)
[1] 467.24249 81.43611 79.44754 87.78439 86.54510 93.98638 78.57750
[8] 85.46389 87.22465 95.75642
> rowMin(tmp5,na.rm=TRUE)
[1] 55.65178 57.18805 53.59040 54.46574 57.11862 58.99569 54.60135 58.57995
[9] 58.58825 55.12072
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.51236 65.03634 71.87942 68.21795 68.99111 67.57128 70.32939
[8] 71.11852 71.48255 76.11607 73.46902 70.84168 68.54254 70.89692
[15] 66.13775 73.66353 70.08455 71.87819 69.50336 72.96215
> colSums(tmp5,na.rm=TRUE)
[1] 1115.1236 650.3634 718.7942 682.1795 689.9111 675.7128 703.2939
[8] 711.1852 714.8255 761.1607 734.6902 708.4168 685.4254 708.9692
[15] 661.3775 736.6353 700.8455 718.7819 695.0336 656.6593
> colVars(tmp5,na.rm=TRUE)
[1] 15695.64955 51.62046 77.75749 48.42597 83.90585 49.65430
[7] 153.96596 52.33096 90.26854 35.94796 40.10920 47.22152
[13] 81.28057 112.56628 80.51703 124.46864 87.59376 121.52375
[19] 90.76832 55.86844
> colSd(tmp5,na.rm=TRUE)
[1] 125.282279 7.184738 8.818021 6.958877 9.160014 7.046581
[7] 12.408302 7.234014 9.500976 5.995662 6.333183 6.871792
[13] 9.015574 10.609726 8.973128 11.156552 9.359154 11.023781
[19] 9.527241 7.474519
> colMax(tmp5,na.rm=TRUE)
[1] 467.24249 75.59025 86.54510 81.91755 87.99840 79.51661 95.75642
[8] 81.43611 85.04198 86.95918 81.32835 82.60708 83.52979 87.31384
[15] 80.21257 90.94910 82.55017 93.98638 85.88625 79.62664
> colMin(tmp5,na.rm=TRUE)
[1] 56.20484 57.82404 59.38147 59.67811 55.65178 54.46574 53.59040 59.71594
[9] 59.43708 69.89459 62.28462 60.59632 56.86136 57.69820 55.12072 57.18088
[17] 56.97239 54.60135 55.37893 57.18805
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.09098 69.61246 65.90953 72.17400 71.73949 73.37879 64.88032 72.51818
[9] 73.28091 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1821.820 1392.249 1318.191 1443.480 1434.790 1467.576 1297.606 1450.364
[9] 1465.618 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 7907.64138 51.28537 57.66682 78.61714 67.65196 83.71524
[7] 51.52469 65.55131 95.08998 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 88.924920 7.161381 7.593867 8.866631 8.225081 9.149603 7.178070
[8] 8.096377 9.751409 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 467.24249 81.43611 79.44754 87.78439 86.54510 93.98638 78.57750
[8] 85.46389 87.22465 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 55.65178 57.18805 53.59040 54.46574 57.11862 58.99569 54.60135 58.57995
[9] 58.58825 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.83138 64.00019 71.82219 68.24043 66.87919 67.92808 67.50416
[8] 72.10864 70.97068 74.91127 74.31010 71.09702 69.84045 71.26219
[15] 67.36186 74.03289 69.82443 72.78093 69.96434 NaN
> colSums(tmp5,na.rm=TRUE)
[1] 1051.4824 576.0017 646.3997 614.1638 601.9127 611.3528 607.5375
[8] 648.9778 638.7362 674.2015 668.7909 639.8732 628.5641 641.3597
[15] 606.2568 666.2960 628.4198 655.0284 629.6791 0.0000
> colVars(tmp5,na.rm=TRUE)
[1] 17339.32023 45.99494 87.44033 54.47353 44.21670 54.42887
[7] 83.41534 47.84337 98.60450 24.11185 37.16431 52.39069
[13] 72.48925 125.13601 73.72404 138.49247 97.78174 127.54621
[19] 99.72366 NA
> colSd(tmp5,na.rm=TRUE)
[1] 131.678853 6.781957 9.350953 7.380619 6.649564 7.377592
[7] 9.133200 6.916890 9.929980 4.910382 6.096254 7.238141
[13] 8.514062 11.186421 8.586270 11.768282 9.888465 11.293636
[19] 9.986173 NA
> colMax(tmp5,na.rm=TRUE)
[1] 467.24249 75.59025 86.54510 81.91755 73.56487 79.51661 82.11410
[8] 81.43611 85.04198 85.46389 81.32835 82.60708 83.52979 87.31384
[15] 80.21257 90.94910 82.55017 93.98638 85.88625 -Inf
> colMin(tmp5,na.rm=TRUE)
[1] 56.20484 57.82404 59.38147 59.67811 55.65178 54.46574 53.59040 59.71594
[9] 59.43708 69.89459 62.28462 60.59632 59.78890 57.69820 58.99569 57.18088
[17] 56.97239 54.60135 55.37893 Inf
>
>
>
>
> 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] 152.0402 181.2737 202.3450 206.0393 185.6287 267.4543 183.3056 135.2627
[9] 172.4033 323.7999
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 152.0402 181.2737 202.3450 206.0393 185.6287 267.4543 183.3056 135.2627
[9] 172.4033 323.7999
>
>
>
> 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] 2.842171e-14 -5.684342e-14 -2.131628e-14 -1.421085e-13 1.421085e-14
[6] -8.526513e-14 1.136868e-13 5.684342e-14 2.842171e-14 0.000000e+00
[11] 5.684342e-14 -5.684342e-14 1.136868e-13 -5.684342e-14 5.684342e-14
[16] 5.684342e-14 -8.526513e-14 0.000000e+00 8.526513e-14 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)
+ }
8 5
8 8
7 11
9 2
4 10
3 5
6 9
10 1
5 15
2 10
8 2
8 18
5 6
5 2
10 5
3 16
3 6
9 15
8 14
4 3
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] 2.508383
> Min(tmp)
[1] -2.179262
> mean(tmp)
[1] -0.113296
> Sum(tmp)
[1] -11.3296
> Var(tmp)
[1] 0.8356853
>
> rowMeans(tmp)
[1] -0.113296
> rowSums(tmp)
[1] -11.3296
> rowVars(tmp)
[1] 0.8356853
> rowSd(tmp)
[1] 0.9141583
> rowMax(tmp)
[1] 2.508383
> rowMin(tmp)
[1] -2.179262
>
> colMeans(tmp)
[1] -1.29033336 0.16705644 -1.04961482 0.82685021 -0.18309020 0.71742062
[7] 1.23579105 0.62308580 -0.13504030 0.96403751 0.49019687 -0.02361194
[13] -1.90656144 1.25676457 1.30930926 -0.90311340 0.22112029 0.84353091
[19] 0.09841310 -0.02376371 -1.52475643 -0.86185532 0.35771063 -1.02849428
[25] 0.87849335 -0.15115196 1.58013437 -1.05878703 0.45005968 -0.91303654
[31] -1.01118376 -1.86769126 -1.13323756 -0.37657687 -1.96208488 0.30684022
[37] 0.16167253 -0.37218813 -0.66242266 -0.05382095 0.02729535 2.50838253
[43] 0.98244867 0.09982127 -0.41136190 -0.63736414 -0.48266755 -0.32395480
[49] -0.31762378 0.32661913 0.51837845 -0.12773528 0.22777156 -2.17926220
[55] -0.61615194 -0.09802623 0.55036499 -1.19705270 -0.82373947 -0.21510699
[61] -0.99281125 0.04785147 -0.77174929 -0.89154112 -0.39789961 0.21022074
[67] 0.19962001 -0.08386917 0.16321727 -1.04028814 0.38672624 -0.86845971
[73] -1.28582835 -1.17101764 0.15605237 -0.53496427 1.42816784 -0.89203872
[79] -0.27757413 -1.18530928 -0.17255101 0.85380294 1.04826133 0.83289504
[85] -0.11326354 -1.56570109 -0.57646442 -1.21508323 0.75117491 -0.07520650
[91] -1.25460791 0.46133373 -0.26406417 1.53502403 0.57783846 -0.55811912
[97] 2.22238132 0.50008329 1.43696447 0.24009453
> colSums(tmp)
[1] -1.29033336 0.16705644 -1.04961482 0.82685021 -0.18309020 0.71742062
[7] 1.23579105 0.62308580 -0.13504030 0.96403751 0.49019687 -0.02361194
[13] -1.90656144 1.25676457 1.30930926 -0.90311340 0.22112029 0.84353091
[19] 0.09841310 -0.02376371 -1.52475643 -0.86185532 0.35771063 -1.02849428
[25] 0.87849335 -0.15115196 1.58013437 -1.05878703 0.45005968 -0.91303654
[31] -1.01118376 -1.86769126 -1.13323756 -0.37657687 -1.96208488 0.30684022
[37] 0.16167253 -0.37218813 -0.66242266 -0.05382095 0.02729535 2.50838253
[43] 0.98244867 0.09982127 -0.41136190 -0.63736414 -0.48266755 -0.32395480
[49] -0.31762378 0.32661913 0.51837845 -0.12773528 0.22777156 -2.17926220
[55] -0.61615194 -0.09802623 0.55036499 -1.19705270 -0.82373947 -0.21510699
[61] -0.99281125 0.04785147 -0.77174929 -0.89154112 -0.39789961 0.21022074
[67] 0.19962001 -0.08386917 0.16321727 -1.04028814 0.38672624 -0.86845971
[73] -1.28582835 -1.17101764 0.15605237 -0.53496427 1.42816784 -0.89203872
[79] -0.27757413 -1.18530928 -0.17255101 0.85380294 1.04826133 0.83289504
[85] -0.11326354 -1.56570109 -0.57646442 -1.21508323 0.75117491 -0.07520650
[91] -1.25460791 0.46133373 -0.26406417 1.53502403 0.57783846 -0.55811912
[97] 2.22238132 0.50008329 1.43696447 0.24009453
> 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] -1.29033336 0.16705644 -1.04961482 0.82685021 -0.18309020 0.71742062
[7] 1.23579105 0.62308580 -0.13504030 0.96403751 0.49019687 -0.02361194
[13] -1.90656144 1.25676457 1.30930926 -0.90311340 0.22112029 0.84353091
[19] 0.09841310 -0.02376371 -1.52475643 -0.86185532 0.35771063 -1.02849428
[25] 0.87849335 -0.15115196 1.58013437 -1.05878703 0.45005968 -0.91303654
[31] -1.01118376 -1.86769126 -1.13323756 -0.37657687 -1.96208488 0.30684022
[37] 0.16167253 -0.37218813 -0.66242266 -0.05382095 0.02729535 2.50838253
[43] 0.98244867 0.09982127 -0.41136190 -0.63736414 -0.48266755 -0.32395480
[49] -0.31762378 0.32661913 0.51837845 -0.12773528 0.22777156 -2.17926220
[55] -0.61615194 -0.09802623 0.55036499 -1.19705270 -0.82373947 -0.21510699
[61] -0.99281125 0.04785147 -0.77174929 -0.89154112 -0.39789961 0.21022074
[67] 0.19962001 -0.08386917 0.16321727 -1.04028814 0.38672624 -0.86845971
[73] -1.28582835 -1.17101764 0.15605237 -0.53496427 1.42816784 -0.89203872
[79] -0.27757413 -1.18530928 -0.17255101 0.85380294 1.04826133 0.83289504
[85] -0.11326354 -1.56570109 -0.57646442 -1.21508323 0.75117491 -0.07520650
[91] -1.25460791 0.46133373 -0.26406417 1.53502403 0.57783846 -0.55811912
[97] 2.22238132 0.50008329 1.43696447 0.24009453
> colMin(tmp)
[1] -1.29033336 0.16705644 -1.04961482 0.82685021 -0.18309020 0.71742062
[7] 1.23579105 0.62308580 -0.13504030 0.96403751 0.49019687 -0.02361194
[13] -1.90656144 1.25676457 1.30930926 -0.90311340 0.22112029 0.84353091
[19] 0.09841310 -0.02376371 -1.52475643 -0.86185532 0.35771063 -1.02849428
[25] 0.87849335 -0.15115196 1.58013437 -1.05878703 0.45005968 -0.91303654
[31] -1.01118376 -1.86769126 -1.13323756 -0.37657687 -1.96208488 0.30684022
[37] 0.16167253 -0.37218813 -0.66242266 -0.05382095 0.02729535 2.50838253
[43] 0.98244867 0.09982127 -0.41136190 -0.63736414 -0.48266755 -0.32395480
[49] -0.31762378 0.32661913 0.51837845 -0.12773528 0.22777156 -2.17926220
[55] -0.61615194 -0.09802623 0.55036499 -1.19705270 -0.82373947 -0.21510699
[61] -0.99281125 0.04785147 -0.77174929 -0.89154112 -0.39789961 0.21022074
[67] 0.19962001 -0.08386917 0.16321727 -1.04028814 0.38672624 -0.86845971
[73] -1.28582835 -1.17101764 0.15605237 -0.53496427 1.42816784 -0.89203872
[79] -0.27757413 -1.18530928 -0.17255101 0.85380294 1.04826133 0.83289504
[85] -0.11326354 -1.56570109 -0.57646442 -1.21508323 0.75117491 -0.07520650
[91] -1.25460791 0.46133373 -0.26406417 1.53502403 0.57783846 -0.55811912
[97] 2.22238132 0.50008329 1.43696447 0.24009453
> colMedians(tmp)
[1] -1.29033336 0.16705644 -1.04961482 0.82685021 -0.18309020 0.71742062
[7] 1.23579105 0.62308580 -0.13504030 0.96403751 0.49019687 -0.02361194
[13] -1.90656144 1.25676457 1.30930926 -0.90311340 0.22112029 0.84353091
[19] 0.09841310 -0.02376371 -1.52475643 -0.86185532 0.35771063 -1.02849428
[25] 0.87849335 -0.15115196 1.58013437 -1.05878703 0.45005968 -0.91303654
[31] -1.01118376 -1.86769126 -1.13323756 -0.37657687 -1.96208488 0.30684022
[37] 0.16167253 -0.37218813 -0.66242266 -0.05382095 0.02729535 2.50838253
[43] 0.98244867 0.09982127 -0.41136190 -0.63736414 -0.48266755 -0.32395480
[49] -0.31762378 0.32661913 0.51837845 -0.12773528 0.22777156 -2.17926220
[55] -0.61615194 -0.09802623 0.55036499 -1.19705270 -0.82373947 -0.21510699
[61] -0.99281125 0.04785147 -0.77174929 -0.89154112 -0.39789961 0.21022074
[67] 0.19962001 -0.08386917 0.16321727 -1.04028814 0.38672624 -0.86845971
[73] -1.28582835 -1.17101764 0.15605237 -0.53496427 1.42816784 -0.89203872
[79] -0.27757413 -1.18530928 -0.17255101 0.85380294 1.04826133 0.83289504
[85] -0.11326354 -1.56570109 -0.57646442 -1.21508323 0.75117491 -0.07520650
[91] -1.25460791 0.46133373 -0.26406417 1.53502403 0.57783846 -0.55811912
[97] 2.22238132 0.50008329 1.43696447 0.24009453
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.290333 0.1670564 -1.049615 0.8268502 -0.1830902 0.7174206 1.235791
[2,] -1.290333 0.1670564 -1.049615 0.8268502 -0.1830902 0.7174206 1.235791
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.6230858 -0.1350403 0.9640375 0.4901969 -0.02361194 -1.906561 1.256765
[2,] 0.6230858 -0.1350403 0.9640375 0.4901969 -0.02361194 -1.906561 1.256765
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.309309 -0.9031134 0.2211203 0.8435309 0.0984131 -0.02376371 -1.524756
[2,] 1.309309 -0.9031134 0.2211203 0.8435309 0.0984131 -0.02376371 -1.524756
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.8618553 0.3577106 -1.028494 0.8784933 -0.151152 1.580134 -1.058787
[2,] -0.8618553 0.3577106 -1.028494 0.8784933 -0.151152 1.580134 -1.058787
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.4500597 -0.9130365 -1.011184 -1.867691 -1.133238 -0.3765769 -1.962085
[2,] 0.4500597 -0.9130365 -1.011184 -1.867691 -1.133238 -0.3765769 -1.962085
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.3068402 0.1616725 -0.3721881 -0.6624227 -0.05382095 0.02729535 2.508383
[2,] 0.3068402 0.1616725 -0.3721881 -0.6624227 -0.05382095 0.02729535 2.508383
[,43] [,44] [,45] [,46] [,47] [,48]
[1,] 0.9824487 0.09982127 -0.4113619 -0.6373641 -0.4826675 -0.3239548
[2,] 0.9824487 0.09982127 -0.4113619 -0.6373641 -0.4826675 -0.3239548
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.3176238 0.3266191 0.5183784 -0.1277353 0.2277716 -2.179262 -0.6161519
[2,] -0.3176238 0.3266191 0.5183784 -0.1277353 0.2277716 -2.179262 -0.6161519
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.09802623 0.550365 -1.197053 -0.8237395 -0.215107 -0.9928112 0.04785147
[2,] -0.09802623 0.550365 -1.197053 -0.8237395 -0.215107 -0.9928112 0.04785147
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] -0.7717493 -0.8915411 -0.3978996 0.2102207 0.19962 -0.08386917 0.1632173
[2,] -0.7717493 -0.8915411 -0.3978996 0.2102207 0.19962 -0.08386917 0.1632173
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] -1.040288 0.3867262 -0.8684597 -1.285828 -1.171018 0.1560524 -0.5349643
[2,] -1.040288 0.3867262 -0.8684597 -1.285828 -1.171018 0.1560524 -0.5349643
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] 1.428168 -0.8920387 -0.2775741 -1.185309 -0.172551 0.8538029 1.048261
[2,] 1.428168 -0.8920387 -0.2775741 -1.185309 -0.172551 0.8538029 1.048261
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 0.832895 -0.1132635 -1.565701 -0.5764644 -1.215083 0.7511749 -0.0752065
[2,] 0.832895 -0.1132635 -1.565701 -0.5764644 -1.215083 0.7511749 -0.0752065
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -1.254608 0.4613337 -0.2640642 1.535024 0.5778385 -0.5581191 2.222381
[2,] -1.254608 0.4613337 -0.2640642 1.535024 0.5778385 -0.5581191 2.222381
[,98] [,99] [,100]
[1,] 0.5000833 1.436964 0.2400945
[2,] 0.5000833 1.436964 0.2400945
>
>
> Max(tmp2)
[1] 2.681042
> Min(tmp2)
[1] -2.058986
> mean(tmp2)
[1] 0.1593421
> Sum(tmp2)
[1] 15.93421
> Var(tmp2)
[1] 0.9333542
>
> rowMeans(tmp2)
[1] 0.53045686 -0.92100419 -1.76330927 0.31605531 0.43167298 1.40703368
[7] -0.32362428 -0.30815491 0.56396656 0.74278877 0.68505059 -0.12621105
[13] -0.42123763 -0.58113129 -0.17496264 -0.30956217 -0.99897686 1.26329500
[19] 0.63494358 0.07878003 0.67970839 2.18199746 -0.07792986 0.30200019
[25] 0.51982237 1.48482680 -0.98285551 -0.09687770 -1.12937027 0.42000034
[31] -2.05898595 0.48824145 -0.22571975 1.24892496 -0.99094753 1.45969451
[37] 1.01399963 -0.54777176 0.41523379 0.29679035 0.23597768 1.27726408
[43] 1.14833249 0.06719483 0.55399795 1.54277566 0.57714092 -1.76793538
[49] -0.69413067 -0.30015835 -1.15960671 -0.32936989 0.18625354 -0.87001705
[55] -0.02399286 0.85576122 1.68952215 0.87624927 1.85196796 -0.13888202
[61] -1.30302151 -0.20653309 1.53659553 1.42024243 0.08454372 -0.91536703
[67] 0.44640250 0.75627420 -0.09802807 1.07620568 -0.42870445 0.22482798
[73] -0.88884420 0.33203220 -0.14021178 -1.31679810 1.84510496 -0.64043897
[79] -0.61015060 0.98184366 -0.99884532 -0.23038405 0.35319281 -0.77268329
[85] -1.27243590 0.30486831 -0.56486269 2.59229851 1.58447717 0.46566424
[91] 0.72190768 0.15495205 -0.65113517 -1.55572895 -0.66408936 2.68104221
[97] 0.38229116 -0.50853846 0.89863227 0.15261303
> rowSums(tmp2)
[1] 0.53045686 -0.92100419 -1.76330927 0.31605531 0.43167298 1.40703368
[7] -0.32362428 -0.30815491 0.56396656 0.74278877 0.68505059 -0.12621105
[13] -0.42123763 -0.58113129 -0.17496264 -0.30956217 -0.99897686 1.26329500
[19] 0.63494358 0.07878003 0.67970839 2.18199746 -0.07792986 0.30200019
[25] 0.51982237 1.48482680 -0.98285551 -0.09687770 -1.12937027 0.42000034
[31] -2.05898595 0.48824145 -0.22571975 1.24892496 -0.99094753 1.45969451
[37] 1.01399963 -0.54777176 0.41523379 0.29679035 0.23597768 1.27726408
[43] 1.14833249 0.06719483 0.55399795 1.54277566 0.57714092 -1.76793538
[49] -0.69413067 -0.30015835 -1.15960671 -0.32936989 0.18625354 -0.87001705
[55] -0.02399286 0.85576122 1.68952215 0.87624927 1.85196796 -0.13888202
[61] -1.30302151 -0.20653309 1.53659553 1.42024243 0.08454372 -0.91536703
[67] 0.44640250 0.75627420 -0.09802807 1.07620568 -0.42870445 0.22482798
[73] -0.88884420 0.33203220 -0.14021178 -1.31679810 1.84510496 -0.64043897
[79] -0.61015060 0.98184366 -0.99884532 -0.23038405 0.35319281 -0.77268329
[85] -1.27243590 0.30486831 -0.56486269 2.59229851 1.58447717 0.46566424
[91] 0.72190768 0.15495205 -0.65113517 -1.55572895 -0.66408936 2.68104221
[97] 0.38229116 -0.50853846 0.89863227 0.15261303
> 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] 0.53045686 -0.92100419 -1.76330927 0.31605531 0.43167298 1.40703368
[7] -0.32362428 -0.30815491 0.56396656 0.74278877 0.68505059 -0.12621105
[13] -0.42123763 -0.58113129 -0.17496264 -0.30956217 -0.99897686 1.26329500
[19] 0.63494358 0.07878003 0.67970839 2.18199746 -0.07792986 0.30200019
[25] 0.51982237 1.48482680 -0.98285551 -0.09687770 -1.12937027 0.42000034
[31] -2.05898595 0.48824145 -0.22571975 1.24892496 -0.99094753 1.45969451
[37] 1.01399963 -0.54777176 0.41523379 0.29679035 0.23597768 1.27726408
[43] 1.14833249 0.06719483 0.55399795 1.54277566 0.57714092 -1.76793538
[49] -0.69413067 -0.30015835 -1.15960671 -0.32936989 0.18625354 -0.87001705
[55] -0.02399286 0.85576122 1.68952215 0.87624927 1.85196796 -0.13888202
[61] -1.30302151 -0.20653309 1.53659553 1.42024243 0.08454372 -0.91536703
[67] 0.44640250 0.75627420 -0.09802807 1.07620568 -0.42870445 0.22482798
[73] -0.88884420 0.33203220 -0.14021178 -1.31679810 1.84510496 -0.64043897
[79] -0.61015060 0.98184366 -0.99884532 -0.23038405 0.35319281 -0.77268329
[85] -1.27243590 0.30486831 -0.56486269 2.59229851 1.58447717 0.46566424
[91] 0.72190768 0.15495205 -0.65113517 -1.55572895 -0.66408936 2.68104221
[97] 0.38229116 -0.50853846 0.89863227 0.15261303
> rowMin(tmp2)
[1] 0.53045686 -0.92100419 -1.76330927 0.31605531 0.43167298 1.40703368
[7] -0.32362428 -0.30815491 0.56396656 0.74278877 0.68505059 -0.12621105
[13] -0.42123763 -0.58113129 -0.17496264 -0.30956217 -0.99897686 1.26329500
[19] 0.63494358 0.07878003 0.67970839 2.18199746 -0.07792986 0.30200019
[25] 0.51982237 1.48482680 -0.98285551 -0.09687770 -1.12937027 0.42000034
[31] -2.05898595 0.48824145 -0.22571975 1.24892496 -0.99094753 1.45969451
[37] 1.01399963 -0.54777176 0.41523379 0.29679035 0.23597768 1.27726408
[43] 1.14833249 0.06719483 0.55399795 1.54277566 0.57714092 -1.76793538
[49] -0.69413067 -0.30015835 -1.15960671 -0.32936989 0.18625354 -0.87001705
[55] -0.02399286 0.85576122 1.68952215 0.87624927 1.85196796 -0.13888202
[61] -1.30302151 -0.20653309 1.53659553 1.42024243 0.08454372 -0.91536703
[67] 0.44640250 0.75627420 -0.09802807 1.07620568 -0.42870445 0.22482798
[73] -0.88884420 0.33203220 -0.14021178 -1.31679810 1.84510496 -0.64043897
[79] -0.61015060 0.98184366 -0.99884532 -0.23038405 0.35319281 -0.77268329
[85] -1.27243590 0.30486831 -0.56486269 2.59229851 1.58447717 0.46566424
[91] 0.72190768 0.15495205 -0.65113517 -1.55572895 -0.66408936 2.68104221
[97] 0.38229116 -0.50853846 0.89863227 0.15261303
>
> colMeans(tmp2)
[1] 0.1593421
> colSums(tmp2)
[1] 15.93421
> colVars(tmp2)
[1] 0.9333542
> colSd(tmp2)
[1] 0.9661026
> colMax(tmp2)
[1] 2.681042
> colMin(tmp2)
[1] -2.058986
> colMedians(tmp2)
[1] 0.1706028
> colRanges(tmp2)
[,1]
[1,] -2.058986
[2,] 2.681042
>
> 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] -5.9613848 2.9593599 -3.6699857 -1.7997395 7.0740498 1.5126014
[7] 0.1757351 -4.3707157 -3.1973653 -3.1718648
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.92094260
[2,] -0.88429936
[3,] -0.53927183
[4,] 0.09279288
[5,] 0.58262812
>
> rowApply(tmp,sum)
[1] 1.7963950 -0.9179059 0.2411419 -3.7571532 -1.6106434 1.1939587
[7] -2.4752469 -2.9663042 -3.8798125 1.9262610
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 6 1 3 1 3 8 8 6 3 3
[2,] 1 3 10 10 5 6 3 3 10 8
[3,] 8 7 5 4 2 9 9 1 5 2
[4,] 2 5 6 8 6 5 2 4 6 5
[5,] 10 10 9 7 4 10 10 8 1 10
[6,] 3 9 8 9 8 4 4 5 9 4
[7,] 4 8 1 5 7 2 7 10 7 9
[8,] 5 2 4 2 10 3 6 7 2 6
[9,] 7 4 2 6 1 7 5 9 8 1
[10,] 9 6 7 3 9 1 1 2 4 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.8288176 -0.9281507 -1.8420287 -2.5831824 4.4659025 2.0104149
[7] -2.3473475 0.8406739 -1.8361781 -0.1051880 1.0586356 -0.9030103
[13] 0.9772423 -3.0362910 2.5175159 2.2104540 2.5252226 0.5728295
[19] 1.1995010 -2.2412926
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.97478058
[2,] -0.78570857
[3,] -0.59569074
[4,] -0.09732445
[5,] 0.62468672
>
> rowApply(tmp,sum)
[1] 2.5195889 -2.5046417 0.8171155 3.4849155 -3.5900729
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 2 15 9 3 4
[2,] 12 7 3 17 7
[3,] 6 8 5 8 11
[4,] 7 12 12 12 1
[5,] 18 20 14 13 13
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.97478058 0.2753911 -0.2905105 -0.2239510 1.0895531 -0.4179624
[2,] 0.62468672 -0.6629903 -0.6540136 -0.3249737 1.9837572 1.2611190
[3,] -0.09732445 -0.9081430 -0.5475827 0.2132971 0.4478041 0.7651326
[4,] -0.59569074 0.9407912 -0.2383619 0.2016755 0.5308499 -0.2607096
[5,] -0.78570857 -0.5731997 -0.1115599 -2.4492301 0.4139382 0.6628353
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.3729822 -0.4219518 0.5160613 0.08754645 1.4293097 0.7387441
[2,] -1.1730583 0.9396774 -1.5278579 -0.47314312 -0.5929840 -1.1913203
[3,] -1.5611251 -0.7174359 -0.1726790 -1.48044191 0.8494919 0.5953359
[4,] 0.1259355 0.1437733 -1.4517197 0.82076049 -0.3760026 -0.2715373
[5,] -0.1120819 0.8966109 0.8000171 0.94009013 -0.2511794 -0.7742326
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.1572326 0.2650592 0.481673077 1.1117616 0.29026246 0.1005701
[2,] -0.7371520 -1.1168455 0.715023760 1.7421595 -0.06000006 -1.0037919
[3,] -0.2328605 -0.1353422 0.005015961 0.2774494 1.13810056 1.2313437
[4,] 1.5484923 -0.2133257 1.705263468 -1.4826238 0.68658683 0.8654440
[5,] 0.5559951 -1.8358368 -0.389460392 0.5617074 0.47027282 -0.6207365
[,19] [,20]
[1,] -0.70764498 -1.04529150
[2,] -0.33662703 0.08369242
[3,] 1.06966763 0.07741135
[4,] 1.20721152 -0.40189710
[5,] -0.03310616 -0.95520774
>
>
> 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 : 563 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.2917382 -0.9702547 0.2772137 1.21386 0.6113572 -0.7970752 -0.3160906
col8 col9 col10 col11 col12 col13 col14
row1 -0.6866954 -1.106955 -0.3161114 -0.4332187 0.2007629 -0.4217506 -0.1558964
col15 col16 col17 col18 col19 col20
row1 0.0969108 -2.26649 -1.147549 -0.8573803 -1.371311 1.140457
> tmp[,"col10"]
col10
row1 -0.31611139
row2 -1.06692414
row3 -0.05610702
row4 -1.96029662
row5 -0.92149642
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.2917382 -0.9702547 0.2772137 1.213860 0.6113572 -0.7970752 -0.3160906
row5 0.1063426 0.5380840 1.0778216 -1.431676 -1.7627202 -1.0411697 -0.8103454
col8 col9 col10 col11 col12 col13
row1 -0.68669539 -1.1069550 -0.3161114 -0.4332187 0.2007629 -0.4217506
row5 -0.06953965 -0.5636341 -0.9214964 -0.9444954 -0.8152302 -0.2538702
col14 col15 col16 col17 col18 col19 col20
row1 -0.1558964 0.0969108 -2.2664903 -1.147549 -0.8573803 -1.3713113 1.140457
row5 1.8680759 0.2915687 0.0342581 0.753317 -1.0386753 0.8481415 1.317084
> tmp[,c("col6","col20")]
col6 col20
row1 -0.7970752 1.1404568
row2 -2.0507656 -0.6888891
row3 0.7572163 -1.1201284
row4 0.1637288 -0.8957172
row5 -1.0411697 1.3170845
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.7970752 1.140457
row5 -1.0411697 1.317084
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.51104 48.29801 48.42604 51.53571 49.79422 106.2426 50.5175 49.26698
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.25776 50.58809 49.60273 48.41547 47.74001 48.77008 50.25127 50.88115
col17 col18 col19 col20
row1 50.5657 48.20744 49.60692 103.396
> tmp[,"col10"]
col10
row1 50.58809
row2 29.58536
row3 29.67649
row4 29.01970
row5 50.48545
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.51104 48.29801 48.42604 51.53571 49.79422 106.2426 50.51750 49.26698
row5 51.30963 51.47062 49.78516 49.24394 49.42133 105.9735 50.64889 49.43191
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.25776 50.58809 49.60273 48.41547 47.74001 48.77008 50.25127 50.88115
row5 47.87963 50.48545 50.76148 49.03420 51.40074 49.75554 48.49595 50.87063
col17 col18 col19 col20
row1 50.56570 48.20744 49.60692 103.396
row5 49.32905 47.89902 49.18843 103.718
> tmp[,c("col6","col20")]
col6 col20
row1 106.24261 103.39604
row2 74.61200 73.87331
row3 73.75173 74.90832
row4 76.01087 74.18308
row5 105.97353 103.71800
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.2426 103.396
row5 105.9735 103.718
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.2426 103.396
row5 105.9735 103.718
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.1222713
[2,] -1.4117532
[3,] -1.7273937
[4,] 0.6749037
[5,] -0.6443665
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.23354825 -0.4416130
[2,] -0.06817768 -0.6486126
[3,] -1.86516096 0.1051438
[4,] -1.06357646 -0.3542864
[5,] 0.52903925 0.9538730
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.1170137 -0.2611810
[2,] 0.6510877 -0.1875264
[3,] -0.7090776 1.1321114
[4,] 1.0705038 -0.6145217
[5,] 0.9514786 -0.3444435
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.117014
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.1170137
[2,] 0.6510877
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 0.90011181 1.0450387 -0.7419093 -0.5989943 -1.54826329 2.285253
row1 0.04468493 -0.6097204 -0.0507977 -1.7232189 0.02516622 1.986690
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.08617688 -0.5688614 0.8182693 -0.35864711 -0.4075083 -0.8269061
row1 -0.14545725 -4.0222637 -2.1953261 -0.01529411 0.0971657 1.5601206
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.8612224 0.2680828 0.2930872 -1.1671656 1.5143027 0.3578669 -0.3955543
row1 1.5141033 0.1387283 0.5678639 0.9329888 0.2590608 -0.3487306 -0.1122654
[,20]
row3 -0.03011156
row1 0.41138912
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.1548351 -0.9141988 -0.6048387 -0.703718 0.7693834 -0.6077036 -0.6825093
[,8] [,9] [,10]
row2 -0.1159035 -0.3901642 1.821255
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.07624199 -1.174168 0.5557679 -1.472846 1.219264 -0.7974996 0.5788898
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.01532146 0.3061839 -0.2359366 0.4384869 -0.05288233 0.9619008 -0.7263432
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.155932 -1.31774 -0.6705876 0.7493853 1.732103 -1.53431
>
>
> 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: 0x6000035e4000>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMf66b7aa737fc"
[2] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMf66b784cc04c"
[3] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMf66b76e4fb47"
[4] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMf66b332d2f4c"
[5] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMf66b5b7c40d3"
[6] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMf66b3a840b91"
[7] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMf66b33137a9a"
[8] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMf66b43d62ea8"
[9] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMf66b22913a63"
[10] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMf66b6c904b4f"
[11] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMf66b75406737"
[12] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMf66b57388804"
[13] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMf66b4069eb58"
[14] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMf66b69d9ff71"
[15] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMf66b67118a01"
>
>
> ### 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: 0x6000035f41e0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000035f41e0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6000035f41e0>
> rowMedians(tmp)
[1] -0.745087262 0.062857320 0.383686292 0.134683705 -0.465305207
[6] -0.015977886 -0.180101211 0.478427620 -0.240437033 -0.130036709
[11] -0.155648408 -0.124016278 -0.221391720 0.456412817 0.302201108
[16] 0.384404846 -0.048421014 0.438932648 -0.211329679 -0.283943589
[21] -0.002128457 0.023372533 0.562148335 -0.008684426 0.079886016
[26] -0.025389844 -0.025209976 0.315912413 0.382365424 -0.194446346
[31] 0.242301218 -0.091625067 0.288982405 -0.067599729 -0.207953684
[36] 0.387427700 0.649361478 -0.029822782 -0.307329899 0.444019885
[41] -0.297316469 -0.407923348 0.071575676 -0.190550545 -0.041320059
[46] -0.699485173 0.644604211 0.105122261 -0.035890953 -0.586264610
[51] -0.032159451 -0.541190171 0.574840350 0.317963534 -0.074817807
[56] -0.328346433 -0.448368847 -0.144971185 -0.281817522 0.475259362
[61] 0.095864065 0.416059172 -0.162504845 0.231172122 0.088850493
[66] 0.141802882 0.266652532 0.038421708 0.030993651 0.006475672
[71] -0.250600701 -0.459157573 0.557654318 -0.393358269 -0.457247556
[76] -0.627330472 -0.117552198 0.211025664 0.256999856 0.066798063
[81] 0.051459608 0.428942629 0.194592165 -0.462469859 0.289074477
[86] -0.074626677 0.348182605 -0.239846819 0.277385231 -0.066233986
[91] 0.438916213 -0.103402428 0.118896736 -0.395915691 0.322251944
[96] 0.404893910 -0.055200554 -0.186665811 0.209275499 0.344097110
[101] 0.259220671 -0.188995513 -0.248560411 0.433756938 0.414472912
[106] -0.335264671 -0.479557418 -0.017619316 0.032540566 0.176896043
[111] 0.081149060 -0.166763435 -0.014974937 -0.510674383 0.121715909
[116] -0.392466227 -0.466307223 0.163251451 -0.144200787 0.029351292
[121] -0.927973691 -0.130773341 -0.056994738 -0.339905662 -0.006727402
[126] 0.571834639 0.010650089 0.281470945 0.286321008 -0.204359987
[131] 0.432925869 -0.134980822 0.221372570 0.255885068 -0.147215462
[136] 0.525888636 -0.240831762 0.238905395 -0.140041207 -0.052387695
[141] -0.034298105 0.777292683 -0.052381848 -0.522643739 -0.108222725
[146] 0.327474911 0.163383556 0.624351738 0.598602176 -0.365163174
[151] 0.844372324 -0.184016442 -0.281939484 -0.231735611 0.121797774
[156] -0.337997845 -0.261363291 0.011112439 -0.024682909 -0.319719494
[161] 0.461066467 0.242098267 0.159272336 0.074330459 -0.085929704
[166] -0.096586060 0.098849537 -0.412434025 0.164476001 0.273943405
[171] -0.349024212 0.055999853 -0.360205258 -0.306809472 0.038207972
[176] -0.210983284 0.270226707 0.113514563 -0.296824729 -0.403747484
[181] 0.232343097 -0.022668609 0.295763112 0.174455551 -0.121637397
[186] 0.029195458 -0.004774680 -0.386371170 -0.202103623 0.450411525
[191] -0.131871942 0.183064710 -0.092866263 0.012537958 -0.219210875
[196] -0.307352630 0.280396169 -0.792190739 0.135670890 -0.292959725
[201] 0.734502493 0.392862695 0.118856276 -1.320864769 -0.110975079
[206] -0.024508378 -0.314918111 0.369966551 -0.067389755 0.054410573
[211] 0.719450910 0.494523488 0.098605518 -0.361691344 0.146225043
[216] 0.119748348 0.161413319 -0.083337911 -0.252856019 -0.371449654
[221] -1.027092472 -0.373667143 0.615042410 0.255753307 -0.354532812
[226] 0.053303669 0.354573945 -0.250944885 -0.178068451 0.208581718
>
> proc.time()
user system elapsed
5.221 20.009 27.477
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: 0x6000023b0120>
> .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: 0x6000023b0120>
> .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: 0x6000023b0120>
> .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: 0x6000023b0120>
> 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: 0x60000238c0c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000238c0c0>
> .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: 0x60000238c0c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000238c0c0>
> .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: 0x60000238c0c0>
> 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: 0x60000238c240>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000238c240>
> .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: 0x60000238c240>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x60000238c240>
> .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: 0x60000238c240>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x60000238c240>
> .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: 0x60000238c240>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x60000238c240>
> .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: 0x60000238c240>
> 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: 0x600002398180>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600002398180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002398180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002398180>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilefb522a5fb032" "BufferedMatrixFilefb5256447cd5"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilefb522a5fb032" "BufferedMatrixFilefb5256447cd5"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000023b80c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000023b80c0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000023b80c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000023b80c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000023b80c0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000023b80c0>
> .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: 0x6000023dc000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000023dc000>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000023dc000>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000023dc000>
> 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: 0x6000023dc180>
> .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: 0x6000023dc180>
> rm(P)
>
> proc.time()
user system elapsed
0.600 0.218 0.782
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
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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.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.590 0.141 0.695