Ben Bolstad
| Snapshot Date: 2025-03-20 13:40 -0400 (Thu, 20 Mar 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 824836d |
| git_last_commit_date: 2024-12-14 17:47:34 -0400 (Sat, 14 Dec 2024) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-03-21 11:43 -0400 (Fri, 21 Mar 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | R Under development (unstable) (2025-03-13 r87965) -- "Unsuffered Consequences" | 4777 |
| palomino7 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2025-03-01 r87860 ucrt) -- "Unsuffered Consequences" | 4545 |
| lconway | macOS 12.7.1 Monterey | x86_64 | R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences" | 4576 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences" | 4528 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4458 |
| 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 249/2313 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.71.1 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.1 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| kunpeng2 | Linux (openEuler 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: 1.71.1 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.71.1.tar.gz |
| StartedAt: 2025-03-20 19:42:30 -0400 (Thu, 20 Mar 2025) |
| EndedAt: 2025-03-20 19:43:20 -0400 (Thu, 20 Mar 2025) |
| EllapsedTime: 50.5 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_1.71.1.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2025-03-02 r87868)
* using platform: x86_64-apple-darwin20
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 14.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.71.1’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... WARNING
Found the following significant warnings:
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 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-3.21-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.71.1’
** 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/4.5-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 Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences"
Copyright (C) 2025 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
0.343 0.150 0.488
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences"
Copyright (C) 2025 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-3.21-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
Ncells 480291 25.7 1055038 56.4 NA 634442 33.9
Vcells 890168 6.8 8388608 64.0 98304 2107859 16.1
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu Mar 20 19:42:54 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu Mar 20 19:42:54 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: 0x600001ff0000>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu Mar 20 19:42:59 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu Mar 20 19:43:01 2025"
>
> ColMode(tmp2)
<pointer: 0x600001ff0000>
>
>
>
> ### 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,] 99.5483493 0.1890729 -1.6207225 0.3270184
[2,] 0.2678773 -0.5703456 -0.1164796 0.9175882
[3,] 0.6948394 1.0275439 0.1655387 2.0126216
[4,] 0.7815814 1.1148010 -0.5294338 0.5912750
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.5483493 0.1890729 1.6207225 0.3270184
[2,] 0.2678773 0.5703456 0.1164796 0.9175882
[3,] 0.6948394 1.0275439 0.1655387 2.0126216
[4,] 0.7815814 1.1148010 0.5294338 0.5912750
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9773919 0.4348251 1.2730760 0.5718552
[2,] 0.5175687 0.7552123 0.3412911 0.9579082
[3,] 0.8335703 1.0136784 0.4068645 1.4186690
[4,] 0.8840709 1.0558414 0.7276221 0.7689441
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.32227 29.53732 39.35148 31.04557
[2,] 30.44356 33.12247 28.52939 35.49667
[3,] 34.03054 36.16433 29.23418 41.19931
[4,] 34.62229 36.67321 32.80565 33.28072
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600001fec000>
> exp(tmp5)
<pointer: 0x600001fec000>
> log(tmp5,2)
<pointer: 0x600001fec000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.8974
> Min(tmp5)
[1] 53.10019
> mean(tmp5)
[1] 71.85016
> Sum(tmp5)
[1] 14370.03
> Var(tmp5)
[1] 859.4981
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.40337 65.33155 69.25642 67.28750 73.52262 68.11663 76.41579 68.30855
[9] 69.59557 70.26361
> rowSums(tmp5)
[1] 1808.067 1306.631 1385.128 1345.750 1470.452 1362.333 1528.316 1366.171
[9] 1391.911 1405.272
> rowVars(tmp5)
[1] 7941.09914 56.78048 52.36654 68.84590 65.67305 47.74760
[7] 91.28683 70.46587 25.35998 85.66091
> rowSd(tmp5)
[1] 89.112845 7.535282 7.236473 8.297343 8.103891 6.909964 9.554414
[8] 8.394395 5.035869 9.255318
> rowMax(tmp5)
[1] 466.89741 81.33070 85.75097 82.55602 87.59836 79.75834 92.51758
[8] 84.12810 79.49515 88.94603
> rowMin(tmp5)
[1] 56.99665 55.01681 56.91624 53.63958 55.59003 58.64905 56.30344 53.10019
[9] 60.43225 56.62140
>
> colMeans(tmp5)
[1] 109.78416 66.45222 70.04204 70.16366 68.78187 72.26776 67.97144
[8] 72.54782 68.87135 71.10127 70.97417 67.07739 63.52400 73.95304
[15] 71.76662 67.24892 70.08082 71.79610 70.52710 72.07151
> colSums(tmp5)
[1] 1097.8416 664.5222 700.4204 701.6366 687.8187 722.6776 679.7144
[8] 725.4782 688.7135 711.0127 709.7417 670.7739 635.2400 739.5304
[15] 717.6662 672.4892 700.8082 717.9610 705.2710 720.7151
> colVars(tmp5)
[1] 15825.28047 78.14038 88.00765 68.57937 88.98737 97.73069
[7] 42.16576 69.52915 122.30644 22.48079 79.87217 27.46264
[13] 39.30809 52.00784 68.42178 82.28775 70.65864 127.18489
[19] 82.09988 58.39177
> colSd(tmp5)
[1] 125.798571 8.839705 9.381239 8.281266 9.433312 9.885883
[7] 6.493517 8.338414 11.059224 4.741391 8.937123 5.240481
[13] 6.269617 7.211646 8.271746 9.071259 8.405870 11.277628
[19] 9.060898 7.641451
> colMax(tmp5)
[1] 466.89741 78.26495 81.90496 85.75097 85.24978 85.87529 80.99293
[8] 83.79643 88.94603 81.46497 84.12810 77.67460 75.10996 87.69272
[15] 88.83979 82.55602 87.21515 92.51758 81.69411 85.41519
> colMin(tmp5)
[1] 59.67566 53.10019 55.59003 56.30344 56.99665 56.91624 56.34907 58.23568
[9] 53.63958 65.39411 56.74463 61.12786 55.01681 66.59774 60.07216 54.95892
[17] 58.53527 56.83910 56.25645 61.65913
>
>
> ### 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] 90.40337 NA 69.25642 67.28750 73.52262 68.11663 76.41579 68.30855
[9] 69.59557 70.26361
> rowSums(tmp5)
[1] 1808.067 NA 1385.128 1345.750 1470.452 1362.333 1528.316 1366.171
[9] 1391.911 1405.272
> rowVars(tmp5)
[1] 7941.09914 55.21653 52.36654 68.84590 65.67305 47.74760
[7] 91.28683 70.46587 25.35998 85.66091
> rowSd(tmp5)
[1] 89.112845 7.430783 7.236473 8.297343 8.103891 6.909964 9.554414
[8] 8.394395 5.035869 9.255318
> rowMax(tmp5)
[1] 466.89741 NA 85.75097 82.55602 87.59836 79.75834 92.51758
[8] 84.12810 79.49515 88.94603
> rowMin(tmp5)
[1] 56.99665 NA 56.91624 53.63958 55.59003 58.64905 56.30344 53.10019
[9] 60.43225 56.62140
>
> colMeans(tmp5)
[1] 109.78416 66.45222 70.04204 70.16366 68.78187 72.26776 NA
[8] 72.54782 68.87135 71.10127 70.97417 67.07739 63.52400 73.95304
[15] 71.76662 67.24892 70.08082 71.79610 70.52710 72.07151
> colSums(tmp5)
[1] 1097.8416 664.5222 700.4204 701.6366 687.8187 722.6776 NA
[8] 725.4782 688.7135 711.0127 709.7417 670.7739 635.2400 739.5304
[15] 717.6662 672.4892 700.8082 717.9610 705.2710 720.7151
> colVars(tmp5)
[1] 15825.28047 78.14038 88.00765 68.57937 88.98737 97.73069
[7] NA 69.52915 122.30644 22.48079 79.87217 27.46264
[13] 39.30809 52.00784 68.42178 82.28775 70.65864 127.18489
[19] 82.09988 58.39177
> colSd(tmp5)
[1] 125.798571 8.839705 9.381239 8.281266 9.433312 9.885883
[7] NA 8.338414 11.059224 4.741391 8.937123 5.240481
[13] 6.269617 7.211646 8.271746 9.071259 8.405870 11.277628
[19] 9.060898 7.641451
> colMax(tmp5)
[1] 466.89741 78.26495 81.90496 85.75097 85.24978 85.87529 NA
[8] 83.79643 88.94603 81.46497 84.12810 77.67460 75.10996 87.69272
[15] 88.83979 82.55602 87.21515 92.51758 81.69411 85.41519
> colMin(tmp5)
[1] 59.67566 53.10019 55.59003 56.30344 56.99665 56.91624 NA 58.23568
[9] 53.63958 65.39411 56.74463 61.12786 55.01681 66.59774 60.07216 54.95892
[17] 58.53527 56.83910 56.25645 61.65913
>
> Max(tmp5,na.rm=TRUE)
[1] 466.8974
> Min(tmp5,na.rm=TRUE)
[1] 53.10019
> mean(tmp5,na.rm=TRUE)
[1] 71.92806
> Sum(tmp5,na.rm=TRUE)
[1] 14313.68
> Var(tmp5,na.rm=TRUE)
[1] 862.6193
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.40337 65.80431 69.25642 67.28750 73.52262 68.11663 76.41579 68.30855
[9] 69.59557 70.26361
> rowSums(tmp5,na.rm=TRUE)
[1] 1808.067 1250.282 1385.128 1345.750 1470.452 1362.333 1528.316 1366.171
[9] 1391.911 1405.272
> rowVars(tmp5,na.rm=TRUE)
[1] 7941.09914 55.21653 52.36654 68.84590 65.67305 47.74760
[7] 91.28683 70.46587 25.35998 85.66091
> rowSd(tmp5,na.rm=TRUE)
[1] 89.112845 7.430783 7.236473 8.297343 8.103891 6.909964 9.554414
[8] 8.394395 5.035869 9.255318
> rowMax(tmp5,na.rm=TRUE)
[1] 466.89741 81.33070 85.75097 82.55602 87.59836 79.75834 92.51758
[8] 84.12810 79.49515 88.94603
> rowMin(tmp5,na.rm=TRUE)
[1] 56.99665 55.01681 56.91624 53.63958 55.59003 58.64905 56.30344 53.10019
[9] 60.43225 56.62140
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.78416 66.45222 70.04204 70.16366 68.78187 72.26776 69.26281
[8] 72.54782 68.87135 71.10127 70.97417 67.07739 63.52400 73.95304
[15] 71.76662 67.24892 70.08082 71.79610 70.52710 72.07151
> colSums(tmp5,na.rm=TRUE)
[1] 1097.8416 664.5222 700.4204 701.6366 687.8187 722.6776 623.3653
[8] 725.4782 688.7135 711.0127 709.7417 670.7739 635.2400 739.5304
[15] 717.6662 672.4892 700.8082 717.9610 705.2710 720.7151
> colVars(tmp5,na.rm=TRUE)
[1] 15825.28047 78.14038 88.00765 68.57937 88.98737 97.73069
[7] 28.67545 69.52915 122.30644 22.48079 79.87217 27.46264
[13] 39.30809 52.00784 68.42178 82.28775 70.65864 127.18489
[19] 82.09988 58.39177
> colSd(tmp5,na.rm=TRUE)
[1] 125.798571 8.839705 9.381239 8.281266 9.433312 9.885883
[7] 5.354946 8.338414 11.059224 4.741391 8.937123 5.240481
[13] 6.269617 7.211646 8.271746 9.071259 8.405870 11.277628
[19] 9.060898 7.641451
> colMax(tmp5,na.rm=TRUE)
[1] 466.89741 78.26495 81.90496 85.75097 85.24978 85.87529 80.99293
[8] 83.79643 88.94603 81.46497 84.12810 77.67460 75.10996 87.69272
[15] 88.83979 82.55602 87.21515 92.51758 81.69411 85.41519
> colMin(tmp5,na.rm=TRUE)
[1] 59.67566 53.10019 55.59003 56.30344 56.99665 56.91624 63.58136 58.23568
[9] 53.63958 65.39411 56.74463 61.12786 55.01681 66.59774 60.07216 54.95892
[17] 58.53527 56.83910 56.25645 61.65913
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.40337 NaN 69.25642 67.28750 73.52262 68.11663 76.41579 68.30855
[9] 69.59557 70.26361
> rowSums(tmp5,na.rm=TRUE)
[1] 1808.067 0.000 1385.128 1345.750 1470.452 1362.333 1528.316 1366.171
[9] 1391.911 1405.272
> rowVars(tmp5,na.rm=TRUE)
[1] 7941.09914 NA 52.36654 68.84590 65.67305 47.74760
[7] 91.28683 70.46587 25.35998 85.66091
> rowSd(tmp5,na.rm=TRUE)
[1] 89.112845 NA 7.236473 8.297343 8.103891 6.909964 9.554414
[8] 8.394395 5.035869 9.255318
> rowMax(tmp5,na.rm=TRUE)
[1] 466.89741 NA 85.75097 82.55602 87.59836 79.75834 92.51758
[8] 84.12810 79.49515 88.94603
> rowMin(tmp5,na.rm=TRUE)
[1] 56.99665 NA 56.91624 53.63958 55.59003 58.64905 56.30344 53.10019
[9] 60.43225 56.62140
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.94192 66.17579 71.22669 69.75055 69.15007 73.93257 NaN
[8] 73.37977 68.72293 71.43639 72.55522 66.63117 64.46925 74.77030
[15] 72.07977 67.80084 68.83083 73.45799 71.62275 71.29144
> colSums(tmp5,na.rm=TRUE)
[1] 1034.4773 595.5821 641.0402 627.7549 622.3506 665.3931 0.0000
[8] 660.4180 618.5063 642.9275 652.9970 599.6805 580.2232 672.9327
[15] 648.7179 610.2076 619.4775 661.1219 644.6048 641.6230
> colVars(tmp5,na.rm=TRUE)
[1] 17504.16218 87.04828 83.22040 75.23185 98.58559 78.76660
[7] NA 70.43364 137.34691 24.02745 61.73402 28.65547
[13] 34.16989 50.99486 75.87129 89.14680 61.91322 112.01192
[19] 78.85719 58.84498
> colSd(tmp5,na.rm=TRUE)
[1] 132.303296 9.329967 9.122521 8.673630 9.929027 8.875055
[7] NA 8.392475 11.719510 4.901781 7.857100 5.353080
[13] 5.845502 7.141069 8.710413 9.441758 7.868495 10.583568
[19] 8.880157 7.671048
> colMax(tmp5,na.rm=TRUE)
[1] 466.89741 78.26495 81.90496 85.75097 85.24978 85.87529 -Inf
[8] 83.79643 88.94603 81.46497 84.12810 77.67460 75.10996 87.69272
[15] 88.83979 82.55602 87.21515 92.51758 81.69411 85.41519
> colMin(tmp5,na.rm=TRUE)
[1] 59.67566 53.10019 55.59003 56.30344 56.99665 56.91624 Inf 58.23568
[9] 53.63958 65.39411 59.80390 61.12786 58.18989 67.16529 60.07216 54.95892
[17] 58.53527 62.34342 56.25645 61.65913
>
>
>
>
> 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] 287.7343 235.0350 171.8282 244.6791 266.3862 236.1659 363.0856 226.3336
[9] 182.9164 204.1310
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 287.7343 235.0350 171.8282 244.6791 266.3862 236.1659 363.0856 226.3336
[9] 182.9164 204.1310
>
>
>
> 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] 8.526513e-14 -1.421085e-14 -5.684342e-14 -8.526513e-14 2.842171e-14
[6] 7.105427e-14 1.136868e-13 -1.421085e-14 -8.526513e-14 4.263256e-14
[11] -5.684342e-14 5.684342e-14 4.263256e-14 -1.705303e-13 -2.842171e-13
[16] -5.684342e-14 -5.684342e-14 -5.684342e-14 1.278977e-13 -7.105427e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
6 9
4 7
2 7
3 18
1 11
1 11
8 10
3 13
1 15
4 13
5 10
4 3
7 20
8 6
1 6
8 11
1 5
7 18
6 10
1 4
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] 1.702344
> Min(tmp)
[1] -3.153578
> mean(tmp)
[1] -0.1478192
> Sum(tmp)
[1] -14.78192
> Var(tmp)
[1] 0.889854
>
> rowMeans(tmp)
[1] -0.1478192
> rowSums(tmp)
[1] -14.78192
> rowVars(tmp)
[1] 0.889854
> rowSd(tmp)
[1] 0.9433207
> rowMax(tmp)
[1] 1.702344
> rowMin(tmp)
[1] -3.153578
>
> colMeans(tmp)
[1] -0.084640311 -0.944402529 -0.753759379 -0.219428526 1.702344098
[6] 0.271054325 -0.091767527 -1.330881680 0.774810254 1.339842898
[11] -1.698955005 -0.763365480 1.145082895 -0.278397131 -0.278114284
[16] 0.923767439 -1.057823708 -1.026124626 1.014055041 1.213796193
[21] -0.406799919 -0.675060606 -1.447979352 -1.135168072 -1.367750661
[26] 0.967974960 -1.599100501 -3.153577719 0.562683310 0.078922915
[31] -0.481033097 0.125075813 -0.620736123 -0.327399476 0.358604720
[36] -0.350913880 -1.273115543 -1.035237895 0.388638032 1.088651777
[41] -0.659582217 -1.382766207 0.211096678 -0.043145101 0.186563558
[46] 0.244163824 -1.011014747 0.666270367 -0.495076872 0.003572096
[51] -1.225991843 0.433849048 -1.135957872 -0.410892672 -0.203703317
[56] 0.267286688 0.095514896 0.963818692 -0.291883401 0.228670128
[61] 0.566627666 1.112118755 -0.612995395 -1.081857450 -1.128129628
[66] -1.333135894 -1.819915871 1.445834952 0.737635032 -0.640178011
[71] -1.869682092 -0.134902860 0.590895782 1.459665908 -0.594106166
[76] -0.308144004 -0.184830554 1.392686094 0.575212472 -1.498737138
[81] 0.275580633 -0.488756957 0.248134209 0.958971215 0.951714072
[86] -0.223959187 -0.133262031 1.280695331 -0.103701787 -0.348617400
[91] 1.050446322 0.089266242 0.221249292 -1.566148358 1.201079296
[96] 0.757371874 0.672942332 -1.384029613 -1.455443215 0.545927175
> colSums(tmp)
[1] -0.084640311 -0.944402529 -0.753759379 -0.219428526 1.702344098
[6] 0.271054325 -0.091767527 -1.330881680 0.774810254 1.339842898
[11] -1.698955005 -0.763365480 1.145082895 -0.278397131 -0.278114284
[16] 0.923767439 -1.057823708 -1.026124626 1.014055041 1.213796193
[21] -0.406799919 -0.675060606 -1.447979352 -1.135168072 -1.367750661
[26] 0.967974960 -1.599100501 -3.153577719 0.562683310 0.078922915
[31] -0.481033097 0.125075813 -0.620736123 -0.327399476 0.358604720
[36] -0.350913880 -1.273115543 -1.035237895 0.388638032 1.088651777
[41] -0.659582217 -1.382766207 0.211096678 -0.043145101 0.186563558
[46] 0.244163824 -1.011014747 0.666270367 -0.495076872 0.003572096
[51] -1.225991843 0.433849048 -1.135957872 -0.410892672 -0.203703317
[56] 0.267286688 0.095514896 0.963818692 -0.291883401 0.228670128
[61] 0.566627666 1.112118755 -0.612995395 -1.081857450 -1.128129628
[66] -1.333135894 -1.819915871 1.445834952 0.737635032 -0.640178011
[71] -1.869682092 -0.134902860 0.590895782 1.459665908 -0.594106166
[76] -0.308144004 -0.184830554 1.392686094 0.575212472 -1.498737138
[81] 0.275580633 -0.488756957 0.248134209 0.958971215 0.951714072
[86] -0.223959187 -0.133262031 1.280695331 -0.103701787 -0.348617400
[91] 1.050446322 0.089266242 0.221249292 -1.566148358 1.201079296
[96] 0.757371874 0.672942332 -1.384029613 -1.455443215 0.545927175
> 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] -0.084640311 -0.944402529 -0.753759379 -0.219428526 1.702344098
[6] 0.271054325 -0.091767527 -1.330881680 0.774810254 1.339842898
[11] -1.698955005 -0.763365480 1.145082895 -0.278397131 -0.278114284
[16] 0.923767439 -1.057823708 -1.026124626 1.014055041 1.213796193
[21] -0.406799919 -0.675060606 -1.447979352 -1.135168072 -1.367750661
[26] 0.967974960 -1.599100501 -3.153577719 0.562683310 0.078922915
[31] -0.481033097 0.125075813 -0.620736123 -0.327399476 0.358604720
[36] -0.350913880 -1.273115543 -1.035237895 0.388638032 1.088651777
[41] -0.659582217 -1.382766207 0.211096678 -0.043145101 0.186563558
[46] 0.244163824 -1.011014747 0.666270367 -0.495076872 0.003572096
[51] -1.225991843 0.433849048 -1.135957872 -0.410892672 -0.203703317
[56] 0.267286688 0.095514896 0.963818692 -0.291883401 0.228670128
[61] 0.566627666 1.112118755 -0.612995395 -1.081857450 -1.128129628
[66] -1.333135894 -1.819915871 1.445834952 0.737635032 -0.640178011
[71] -1.869682092 -0.134902860 0.590895782 1.459665908 -0.594106166
[76] -0.308144004 -0.184830554 1.392686094 0.575212472 -1.498737138
[81] 0.275580633 -0.488756957 0.248134209 0.958971215 0.951714072
[86] -0.223959187 -0.133262031 1.280695331 -0.103701787 -0.348617400
[91] 1.050446322 0.089266242 0.221249292 -1.566148358 1.201079296
[96] 0.757371874 0.672942332 -1.384029613 -1.455443215 0.545927175
> colMin(tmp)
[1] -0.084640311 -0.944402529 -0.753759379 -0.219428526 1.702344098
[6] 0.271054325 -0.091767527 -1.330881680 0.774810254 1.339842898
[11] -1.698955005 -0.763365480 1.145082895 -0.278397131 -0.278114284
[16] 0.923767439 -1.057823708 -1.026124626 1.014055041 1.213796193
[21] -0.406799919 -0.675060606 -1.447979352 -1.135168072 -1.367750661
[26] 0.967974960 -1.599100501 -3.153577719 0.562683310 0.078922915
[31] -0.481033097 0.125075813 -0.620736123 -0.327399476 0.358604720
[36] -0.350913880 -1.273115543 -1.035237895 0.388638032 1.088651777
[41] -0.659582217 -1.382766207 0.211096678 -0.043145101 0.186563558
[46] 0.244163824 -1.011014747 0.666270367 -0.495076872 0.003572096
[51] -1.225991843 0.433849048 -1.135957872 -0.410892672 -0.203703317
[56] 0.267286688 0.095514896 0.963818692 -0.291883401 0.228670128
[61] 0.566627666 1.112118755 -0.612995395 -1.081857450 -1.128129628
[66] -1.333135894 -1.819915871 1.445834952 0.737635032 -0.640178011
[71] -1.869682092 -0.134902860 0.590895782 1.459665908 -0.594106166
[76] -0.308144004 -0.184830554 1.392686094 0.575212472 -1.498737138
[81] 0.275580633 -0.488756957 0.248134209 0.958971215 0.951714072
[86] -0.223959187 -0.133262031 1.280695331 -0.103701787 -0.348617400
[91] 1.050446322 0.089266242 0.221249292 -1.566148358 1.201079296
[96] 0.757371874 0.672942332 -1.384029613 -1.455443215 0.545927175
> colMedians(tmp)
[1] -0.084640311 -0.944402529 -0.753759379 -0.219428526 1.702344098
[6] 0.271054325 -0.091767527 -1.330881680 0.774810254 1.339842898
[11] -1.698955005 -0.763365480 1.145082895 -0.278397131 -0.278114284
[16] 0.923767439 -1.057823708 -1.026124626 1.014055041 1.213796193
[21] -0.406799919 -0.675060606 -1.447979352 -1.135168072 -1.367750661
[26] 0.967974960 -1.599100501 -3.153577719 0.562683310 0.078922915
[31] -0.481033097 0.125075813 -0.620736123 -0.327399476 0.358604720
[36] -0.350913880 -1.273115543 -1.035237895 0.388638032 1.088651777
[41] -0.659582217 -1.382766207 0.211096678 -0.043145101 0.186563558
[46] 0.244163824 -1.011014747 0.666270367 -0.495076872 0.003572096
[51] -1.225991843 0.433849048 -1.135957872 -0.410892672 -0.203703317
[56] 0.267286688 0.095514896 0.963818692 -0.291883401 0.228670128
[61] 0.566627666 1.112118755 -0.612995395 -1.081857450 -1.128129628
[66] -1.333135894 -1.819915871 1.445834952 0.737635032 -0.640178011
[71] -1.869682092 -0.134902860 0.590895782 1.459665908 -0.594106166
[76] -0.308144004 -0.184830554 1.392686094 0.575212472 -1.498737138
[81] 0.275580633 -0.488756957 0.248134209 0.958971215 0.951714072
[86] -0.223959187 -0.133262031 1.280695331 -0.103701787 -0.348617400
[91] 1.050446322 0.089266242 0.221249292 -1.566148358 1.201079296
[96] 0.757371874 0.672942332 -1.384029613 -1.455443215 0.545927175
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.08464031 -0.9444025 -0.7537594 -0.2194285 1.702344 0.2710543
[2,] -0.08464031 -0.9444025 -0.7537594 -0.2194285 1.702344 0.2710543
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] -0.09176753 -1.330882 0.7748103 1.339843 -1.698955 -0.7633655 1.145083
[2,] -0.09176753 -1.330882 0.7748103 1.339843 -1.698955 -0.7633655 1.145083
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] -0.2783971 -0.2781143 0.9237674 -1.057824 -1.026125 1.014055 1.213796
[2,] -0.2783971 -0.2781143 0.9237674 -1.057824 -1.026125 1.014055 1.213796
[,21] [,22] [,23] [,24] [,25] [,26] [,27]
[1,] -0.4067999 -0.6750606 -1.447979 -1.135168 -1.367751 0.967975 -1.599101
[2,] -0.4067999 -0.6750606 -1.447979 -1.135168 -1.367751 0.967975 -1.599101
[,28] [,29] [,30] [,31] [,32] [,33] [,34]
[1,] -3.153578 0.5626833 0.07892292 -0.4810331 0.1250758 -0.6207361 -0.3273995
[2,] -3.153578 0.5626833 0.07892292 -0.4810331 0.1250758 -0.6207361 -0.3273995
[,35] [,36] [,37] [,38] [,39] [,40] [,41]
[1,] 0.3586047 -0.3509139 -1.273116 -1.035238 0.388638 1.088652 -0.6595822
[2,] 0.3586047 -0.3509139 -1.273116 -1.035238 0.388638 1.088652 -0.6595822
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] -1.382766 0.2110967 -0.0431451 0.1865636 0.2441638 -1.011015 0.6662704
[2,] -1.382766 0.2110967 -0.0431451 0.1865636 0.2441638 -1.011015 0.6662704
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.4950769 0.003572096 -1.225992 0.433849 -1.135958 -0.4108927 -0.2037033
[2,] -0.4950769 0.003572096 -1.225992 0.433849 -1.135958 -0.4108927 -0.2037033
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] 0.2672867 0.0955149 0.9638187 -0.2918834 0.2286701 0.5666277 1.112119
[2,] 0.2672867 0.0955149 0.9638187 -0.2918834 0.2286701 0.5666277 1.112119
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] -0.6129954 -1.081857 -1.12813 -1.333136 -1.819916 1.445835 0.737635
[2,] -0.6129954 -1.081857 -1.12813 -1.333136 -1.819916 1.445835 0.737635
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] -0.640178 -1.869682 -0.1349029 0.5908958 1.459666 -0.5941062 -0.308144
[2,] -0.640178 -1.869682 -0.1349029 0.5908958 1.459666 -0.5941062 -0.308144
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -0.1848306 1.392686 0.5752125 -1.498737 0.2755806 -0.488757 0.2481342
[2,] -0.1848306 1.392686 0.5752125 -1.498737 0.2755806 -0.488757 0.2481342
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 0.9589712 0.9517141 -0.2239592 -0.133262 1.280695 -0.1037018 -0.3486174
[2,] 0.9589712 0.9517141 -0.2239592 -0.133262 1.280695 -0.1037018 -0.3486174
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 1.050446 0.08926624 0.2212493 -1.566148 1.201079 0.7573719 0.6729423
[2,] 1.050446 0.08926624 0.2212493 -1.566148 1.201079 0.7573719 0.6729423
[,98] [,99] [,100]
[1,] -1.38403 -1.455443 0.5459272
[2,] -1.38403 -1.455443 0.5459272
>
>
> Max(tmp2)
[1] 2.762366
> Min(tmp2)
[1] -2.394399
> mean(tmp2)
[1] 0.1735328
> Sum(tmp2)
[1] 17.35328
> Var(tmp2)
[1] 1.200902
>
> rowMeans(tmp2)
[1] -1.375217073 -0.545532516 0.279428738 0.234421468 -0.008790002
[6] 0.608050496 -0.153514155 0.838809567 -0.388592080 0.865432560
[11] -0.263016382 -1.064577730 -1.064882917 0.633135123 -1.334886291
[16] 2.043179750 0.327357367 -0.439932147 1.960958256 0.434258807
[21] 0.181690640 -0.130817919 -1.080738745 -0.128943877 -0.061750133
[26] -0.359589470 2.649385156 -1.067374812 -0.326727937 -0.173925135
[31] 2.213068064 0.399083281 0.550997502 1.135107531 0.703357486
[36] -0.151760008 0.142013419 0.785545486 2.424559009 0.581973521
[41] 0.379013183 -0.314143351 0.708112295 2.762366378 -0.432973089
[46] 1.527332310 -0.319711227 0.939606793 -1.531735213 -0.447603538
[51] -1.227861177 -0.508381557 -0.223366012 -0.731682602 0.649164441
[56] -0.020015572 -0.746708301 -0.581884578 2.399404051 -1.160173782
[61] -0.734006895 -1.538236882 0.581704019 0.093195756 2.279089960
[66] -0.796815764 0.797855059 -0.815666307 -0.561079657 0.581944707
[71] -1.084652532 0.601905678 0.131689220 0.761748496 -0.060660189
[76] 1.991554524 1.114361456 -2.156274506 0.360842727 0.507130013
[81] 0.757809265 2.095765079 0.310132530 1.084792242 0.611057278
[86] 0.037046471 -0.877182728 1.670037636 1.785072954 -1.652150392
[91] 0.798187009 0.515175214 1.519002155 -0.765041003 -1.154729097
[96] 0.919131902 0.226775583 -2.394399036 -1.950837858 0.772000636
> rowSums(tmp2)
[1] -1.375217073 -0.545532516 0.279428738 0.234421468 -0.008790002
[6] 0.608050496 -0.153514155 0.838809567 -0.388592080 0.865432560
[11] -0.263016382 -1.064577730 -1.064882917 0.633135123 -1.334886291
[16] 2.043179750 0.327357367 -0.439932147 1.960958256 0.434258807
[21] 0.181690640 -0.130817919 -1.080738745 -0.128943877 -0.061750133
[26] -0.359589470 2.649385156 -1.067374812 -0.326727937 -0.173925135
[31] 2.213068064 0.399083281 0.550997502 1.135107531 0.703357486
[36] -0.151760008 0.142013419 0.785545486 2.424559009 0.581973521
[41] 0.379013183 -0.314143351 0.708112295 2.762366378 -0.432973089
[46] 1.527332310 -0.319711227 0.939606793 -1.531735213 -0.447603538
[51] -1.227861177 -0.508381557 -0.223366012 -0.731682602 0.649164441
[56] -0.020015572 -0.746708301 -0.581884578 2.399404051 -1.160173782
[61] -0.734006895 -1.538236882 0.581704019 0.093195756 2.279089960
[66] -0.796815764 0.797855059 -0.815666307 -0.561079657 0.581944707
[71] -1.084652532 0.601905678 0.131689220 0.761748496 -0.060660189
[76] 1.991554524 1.114361456 -2.156274506 0.360842727 0.507130013
[81] 0.757809265 2.095765079 0.310132530 1.084792242 0.611057278
[86] 0.037046471 -0.877182728 1.670037636 1.785072954 -1.652150392
[91] 0.798187009 0.515175214 1.519002155 -0.765041003 -1.154729097
[96] 0.919131902 0.226775583 -2.394399036 -1.950837858 0.772000636
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] -1.375217073 -0.545532516 0.279428738 0.234421468 -0.008790002
[6] 0.608050496 -0.153514155 0.838809567 -0.388592080 0.865432560
[11] -0.263016382 -1.064577730 -1.064882917 0.633135123 -1.334886291
[16] 2.043179750 0.327357367 -0.439932147 1.960958256 0.434258807
[21] 0.181690640 -0.130817919 -1.080738745 -0.128943877 -0.061750133
[26] -0.359589470 2.649385156 -1.067374812 -0.326727937 -0.173925135
[31] 2.213068064 0.399083281 0.550997502 1.135107531 0.703357486
[36] -0.151760008 0.142013419 0.785545486 2.424559009 0.581973521
[41] 0.379013183 -0.314143351 0.708112295 2.762366378 -0.432973089
[46] 1.527332310 -0.319711227 0.939606793 -1.531735213 -0.447603538
[51] -1.227861177 -0.508381557 -0.223366012 -0.731682602 0.649164441
[56] -0.020015572 -0.746708301 -0.581884578 2.399404051 -1.160173782
[61] -0.734006895 -1.538236882 0.581704019 0.093195756 2.279089960
[66] -0.796815764 0.797855059 -0.815666307 -0.561079657 0.581944707
[71] -1.084652532 0.601905678 0.131689220 0.761748496 -0.060660189
[76] 1.991554524 1.114361456 -2.156274506 0.360842727 0.507130013
[81] 0.757809265 2.095765079 0.310132530 1.084792242 0.611057278
[86] 0.037046471 -0.877182728 1.670037636 1.785072954 -1.652150392
[91] 0.798187009 0.515175214 1.519002155 -0.765041003 -1.154729097
[96] 0.919131902 0.226775583 -2.394399036 -1.950837858 0.772000636
> rowMin(tmp2)
[1] -1.375217073 -0.545532516 0.279428738 0.234421468 -0.008790002
[6] 0.608050496 -0.153514155 0.838809567 -0.388592080 0.865432560
[11] -0.263016382 -1.064577730 -1.064882917 0.633135123 -1.334886291
[16] 2.043179750 0.327357367 -0.439932147 1.960958256 0.434258807
[21] 0.181690640 -0.130817919 -1.080738745 -0.128943877 -0.061750133
[26] -0.359589470 2.649385156 -1.067374812 -0.326727937 -0.173925135
[31] 2.213068064 0.399083281 0.550997502 1.135107531 0.703357486
[36] -0.151760008 0.142013419 0.785545486 2.424559009 0.581973521
[41] 0.379013183 -0.314143351 0.708112295 2.762366378 -0.432973089
[46] 1.527332310 -0.319711227 0.939606793 -1.531735213 -0.447603538
[51] -1.227861177 -0.508381557 -0.223366012 -0.731682602 0.649164441
[56] -0.020015572 -0.746708301 -0.581884578 2.399404051 -1.160173782
[61] -0.734006895 -1.538236882 0.581704019 0.093195756 2.279089960
[66] -0.796815764 0.797855059 -0.815666307 -0.561079657 0.581944707
[71] -1.084652532 0.601905678 0.131689220 0.761748496 -0.060660189
[76] 1.991554524 1.114361456 -2.156274506 0.360842727 0.507130013
[81] 0.757809265 2.095765079 0.310132530 1.084792242 0.611057278
[86] 0.037046471 -0.877182728 1.670037636 1.785072954 -1.652150392
[91] 0.798187009 0.515175214 1.519002155 -0.765041003 -1.154729097
[96] 0.919131902 0.226775583 -2.394399036 -1.950837858 0.772000636
>
> colMeans(tmp2)
[1] 0.1735328
> colSums(tmp2)
[1] 17.35328
> colVars(tmp2)
[1] 1.200902
> colSd(tmp2)
[1] 1.095857
> colMax(tmp2)
[1] 2.762366
> colMin(tmp2)
[1] -2.394399
> colMedians(tmp2)
[1] 0.161852
> colRanges(tmp2)
[,1]
[1,] -2.394399
[2,] 2.762366
>
> 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] -3.0261232 1.0564689 -3.0402369 -7.3327101 -0.4472298 0.2651516
[7] 2.2756327 -1.7454099 4.3035312 -4.1362891
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.033173765
[2,] -0.899251660
[3,] 0.009354082
[4,] 0.393430960
[5,] 0.799708278
>
> rowApply(tmp,sum)
[1] -1.9924222 3.0198544 -5.7290452 1.1028285 1.2503028 -0.3677105
[7] -2.8711946 -3.2087777 -5.5649874 2.5339373
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 9 1 5 7 5 1 9 9 8
[2,] 8 7 6 9 9 3 4 3 6 5
[3,] 5 1 9 7 2 2 3 7 7 2
[4,] 2 8 2 1 3 8 2 2 4 1
[5,] 10 2 4 3 5 9 7 6 10 3
[6,] 6 3 10 8 8 6 6 4 1 6
[7,] 4 6 7 4 10 7 8 8 3 9
[8,] 3 5 8 10 4 1 5 5 5 4
[9,] 7 4 5 6 6 10 10 10 8 10
[10,] 9 10 3 2 1 4 9 1 2 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.6719176 3.4176205 -0.9827612 -3.3695367 -1.9774853 0.7412575
[7] 6.8031248 3.7956936 -3.6678340 0.5930730 -1.0175163 3.0015158
[13] -0.8243805 1.5355443 -3.2595134 -4.0659803 -0.7670719 3.4340253
[19] -1.8562510 -0.8246003
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.4778869
[2,] -1.2491203
[3,] -0.6778013
[4,] 0.2303989
[5,] 1.5024920
>
> rowApply(tmp,sum)
[1] 11.549645 8.100682 -9.234259 -8.852059 -2.527002
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 17 1 7 6 13
[2,] 10 18 20 16 19
[3,] 8 2 9 15 15
[4,] 2 8 4 4 10
[5,] 14 7 1 12 5
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.5024920 0.2730071 0.0967222 -0.48905816 0.9799344 1.4191370
[2,] -1.2491203 1.2350392 -1.1212210 0.08172621 -0.1521614 0.8795793
[3,] -0.6778013 0.9714281 -0.6605829 -1.15410884 -1.9071686 -0.4313287
[4,] -1.4778869 0.1935685 0.1496272 -1.56405153 -0.1548589 -1.5966591
[5,] 0.2303989 0.7445777 0.5526933 -0.24404442 -0.7432308 0.4705290
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 3.5664030 0.77177022 -2.0979624 1.7213660 -0.2062352 0.05560456
[2,] 0.8402256 0.60697089 -0.2505283 1.3206939 0.4711923 1.15464766
[3,] -0.5199350 -0.09594218 0.1579226 -0.2430554 -0.9814726 0.86581494
[4,] 0.9573447 1.93292925 -0.9940833 -1.2399257 -0.1488742 1.53664068
[5,] 1.9590864 0.57996538 -0.4831827 -0.9660058 -0.1521265 -0.61119204
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.2257128 0.0762103 1.0914486 0.3107707 -0.2237006 1.797658508
[2,] 0.2533205 0.9280810 -0.6689531 -0.2819334 0.9460647 2.608248169
[3,] -0.1270717 -1.4586952 0.5321817 -1.7064759 -0.1355436 0.006243103
[4,] -1.8012271 1.4268618 -2.1167249 -1.5303316 -0.8765496 -0.754568557
[5,] 0.6248850 0.5630864 -2.0974658 -0.8580101 -0.4773427 -0.223555973
[,19] [,20]
[1,] 0.8725012 -0.1941375
[2,] -0.3655959 0.8644060
[3,] -1.0051875 -0.6634807
[4,] -0.8971892 0.1038997
[5,] -0.4607797 -0.9352880
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 567 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.0739043 -0.336983 -1.177113 0.01035385 1.551458 1.657147 0.9125913
col8 col9 col10 col11 col12 col13 col14
row1 -0.4632858 0.6806568 -0.1786963 0.04530452 0.1632008 1.152188 0.9245888
col15 col16 col17 col18 col19 col20
row1 1.213559 -0.9383858 -0.6560729 -0.9787725 0.2666587 -0.6919161
> tmp[,"col10"]
col10
row1 -0.17869630
row2 0.03371543
row3 1.79436828
row4 -0.55193288
row5 -0.46090755
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.0739043 -0.3369830 -1.177113 0.01035385 1.5514584 1.6571471 0.9125913
row5 -0.1774558 0.4364496 1.039266 -0.91192472 0.3232876 -0.1768801 0.3966924
col8 col9 col10 col11 col12 col13 col14
row1 -0.4632858 0.6806568 -0.1786963 0.04530452 0.1632008 1.1521876 0.9245888
row5 -1.2740416 1.3266391 -0.4609075 0.03866288 1.0483522 0.2247771 0.8227399
col15 col16 col17 col18 col19 col20
row1 1.213559 -0.9383858 -0.6560729 -0.9787725 0.2666587 -0.6919161
row5 -1.223020 -0.4783482 -1.4652028 0.9174073 0.6130782 0.2298588
> tmp[,c("col6","col20")]
col6 col20
row1 1.6571471 -0.69191605
row2 -0.2872181 -0.04105727
row3 -0.2180809 1.42695779
row4 -0.4736571 -0.25789981
row5 -0.1768801 0.22985876
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.6571471 -0.6919161
row5 -0.1768801 0.2298588
>
>
>
>
> 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 49.66773 49.46338 47.70178 49.70818 49.70693 104.02 49.70828 48.91531
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.71367 50.35018 48.1584 52.07192 48.75835 49.74868 47.51258 50.31676
col17 col18 col19 col20
row1 51.18852 52.00863 49.19248 104.5429
> tmp[,"col10"]
col10
row1 50.35018
row2 28.82469
row3 30.32728
row4 29.43712
row5 48.46822
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.66773 49.46338 47.70178 49.70818 49.70693 104.0200 49.70828 48.91531
row5 50.00336 49.48040 49.59369 50.69733 49.33194 105.1016 49.92827 49.51428
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.71367 50.35018 48.15840 52.07192 48.75835 49.74868 47.51258 50.31676
row5 48.05057 48.46822 51.09506 49.43823 48.18138 51.14336 49.64632 49.37303
col17 col18 col19 col20
row1 51.18852 52.00863 49.19248 104.5429
row5 50.05867 50.35204 50.91500 103.7949
> tmp[,c("col6","col20")]
col6 col20
row1 104.02004 104.54285
row2 75.96241 75.29411
row3 74.62554 74.95277
row4 75.50242 75.40575
row5 105.10156 103.79494
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.0200 104.5429
row5 105.1016 103.7949
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.0200 104.5429
row5 105.1016 103.7949
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 2.5590183
[2,] 1.1069495
[3,] -0.8306050
[4,] -0.1548442
[5,] -0.2651481
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.714073 -1.00188813
[2,] 0.366543 -0.26190854
[3,] -1.271100 0.95504346
[4,] 1.082812 1.98925449
[5,] -1.192963 -0.08166097
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.5016521 1.0625742
[2,] 0.5490390 0.6845523
[3,] 1.2646645 1.9777122
[4,] -1.0558310 0.1081644
[5,] 0.4325209 -0.1253315
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.5016521
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.5016521
[2,] 0.5490390
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 0.14115201 0.5961177 -1.200336 1.3320457 -1.293864 1.001835 -1.352228
row1 -0.01275308 -0.4445429 1.397367 0.7332728 -1.105802 1.315113 1.537154
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -1.4510281 -0.7849569 0.2185064 0.3867011 0.6959117 -0.7793154
row1 -0.5507435 0.1092431 0.8458496 -0.2605931 -0.3831287 0.7105416
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.3326215 0.0407681 -0.7134538 0.110682897 0.4816639 -0.3752734
row1 -0.7410453 -0.1456669 -0.4478331 -0.006749889 0.1234863 0.1660047
[,20]
row3 0.703779
row1 -1.575948
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.7852653 2.673472 0.914058 -0.6309629 -0.9317577 0.2034586 1.176023
[,8] [,9] [,10]
row2 -1.248811 1.586946 -1.174322
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 2.246448 0.1675827 0.2413862 2.04568 -0.9247631 2.453759 0.3585678
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.225315 0.3581842 -0.0996739 -0.723294 1.838446 0.7818277 -0.7234692
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.09678188 -0.8160882 0.496889 1.541648 -0.3672109 -0.7373644
>
>
> 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: 0x600001f98120>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM104de3ff7ae47"
[2] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM104de1dd2d820"
[3] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM104de7d6b2c2b"
[4] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM104de720fb61"
[5] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM104de657a0ef"
[6] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM104de6306ae29"
[7] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM104de4b943889"
[8] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM104de700bd122"
[9] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM104de17cf48a6"
[10] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM104de29aa9680"
[11] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM104de7e7ec2de"
[12] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM104de342bbdb3"
[13] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM104de23b34d87"
[14] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM104de50a6ec60"
[15] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM104de7ee8bbfd"
>
>
> ### 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: 0x600001f906c0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600001f906c0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600001f906c0>
> rowMedians(tmp)
[1] 0.175308085 0.283574896 0.061117052 0.528938608 0.236522262
[6] -0.244583345 0.383240067 -0.271356065 0.369761531 0.054757395
[11] 0.130053902 -0.759689439 -0.230076527 -0.206095009 0.299431158
[16] -0.340986253 -0.253016657 -0.021798580 0.294314236 -0.077933825
[21] -0.107419772 -0.283470915 -0.152886854 -0.223396592 -0.307904853
[26] -0.457808590 0.607668095 0.758140361 0.287585867 -0.250807573
[31] -0.092621629 0.105072113 -0.159746366 0.242036490 -0.158691000
[36] -0.003614251 0.605566837 0.260358786 0.094072526 0.086814887
[41] 0.136142394 0.555094326 0.181759975 0.095305902 0.356344321
[46] 0.033150261 -0.150871398 -0.014107001 0.784145341 0.351345486
[51] 0.910718701 -0.075491129 0.428604710 0.100373614 0.139698521
[56] 0.037457725 -0.084831745 0.109026833 -0.047342720 0.162372165
[61] -0.290864523 0.329936161 -0.121683016 -0.014970740 -0.061561157
[66] 0.630675309 0.292180589 0.287551580 0.396039262 -0.066223616
[71] 0.048261851 -0.384192535 -0.098667965 0.447381866 -0.059367381
[76] -0.393458769 0.298510348 0.070851653 0.383167288 -0.125542382
[81] 0.260243645 -0.288946765 -0.139743119 0.467698340 -0.374535034
[86] 0.258596905 0.298341864 0.056104967 0.265315834 -0.605927179
[91] -0.347965220 -0.571307656 0.133629040 -0.338483492 0.350465337
[96] 0.196009417 0.127146787 -0.007753598 -0.035827645 0.563739306
[101] 0.234547933 -0.090207412 -0.028464147 0.252507574 0.130134246
[106] -0.049174150 0.799503653 -0.366693388 -0.143964809 0.022415588
[111] 0.278598719 0.322805011 -0.052149972 -0.179722821 -0.163400225
[116] 0.118309261 0.500131325 0.444034274 -0.042408852 -0.026275140
[121] 0.515374993 0.653230624 -0.272471087 0.330797730 -0.290475159
[126] 0.526158418 -0.060554016 -0.221315948 0.149105176 -0.270001015
[131] -0.373519681 0.134279889 0.132869798 0.449672670 -0.571353471
[136] -0.063403908 -0.325586112 -0.647243837 -0.408303053 -0.477710761
[141] 0.077901604 0.096867861 -0.527831478 -0.023273558 -0.107116797
[146] 0.011490313 -0.079975199 0.010949694 -0.518218143 -0.269577129
[151] -0.410764983 -0.158706805 0.255782532 0.027039493 0.570792767
[156] -0.350391695 -0.283329509 -0.071125449 0.809281589 -0.417269623
[161] 0.310101130 0.102914179 0.092943905 -0.156660463 -0.268965663
[166] 0.156212446 -0.114174505 0.172320885 0.219417359 0.262483491
[171] 0.209023672 -0.329938892 0.052223330 -0.148345683 0.113517363
[176] -0.176798368 -0.197160213 0.408879221 0.088311079 -0.117050097
[181] -0.175828334 0.509076649 -0.711100612 0.270775457 0.112999453
[186] -0.057703299 0.236874870 0.093458780 0.355499530 0.099655246
[191] -0.132070618 0.140794189 -0.830784052 -0.355339913 0.465566629
[196] 0.228451308 -0.228316874 -0.282312603 -0.187897290 0.050207194
[201] -0.167429957 0.206272861 -0.345036017 -0.254762129 -0.018411447
[206] 0.398843469 -0.681180344 -0.414562291 -0.464946278 -0.188955477
[211] -0.104823341 -0.181998013 0.007574187 0.053282116 0.120232099
[216] 0.062355654 0.612042722 -0.020524987 -0.317154209 -0.444333533
[221] -0.263584183 0.237668926 -0.085489066 0.281467119 0.373240446
[226] -0.380948153 0.545288186 -0.171089401 0.076249017 0.080571395
>
> proc.time()
user system elapsed
2.569 15.257 18.557
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences"
Copyright (C) 2025 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: 0x6000025483c0>
> .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: 0x6000025483c0>
> .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: 0x6000025483c0>
> .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: 0x6000025483c0>
> 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: 0x600002540000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002540000>
> .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: 0x600002540000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002540000>
> .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: 0x600002540000>
> 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: 0x60000251c000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000251c000>
> .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: 0x60000251c000>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x60000251c000>
> .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: 0x60000251c000>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x60000251c000>
> .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: 0x60000251c000>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x60000251c000>
> .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: 0x60000251c000>
> 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: 0x600002518000>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600002518000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002518000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002518000>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile10be0407fa0" "BufferedMatrixFile10be0a7ae181"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile10be0407fa0" "BufferedMatrixFile10be0a7ae181"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002564420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002564420>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600002564420>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600002564420>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600002564420>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600002564420>
> .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: 0x600002564600>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002564600>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600002564600>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600002564600>
> 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: 0x6000025647e0>
> .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: 0x6000025647e0>
> rm(P)
>
> proc.time()
user system elapsed
0.308 0.137 0.440
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences"
Copyright (C) 2025 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.
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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
0.317 0.085 0.394