Ben Bolstad
| Snapshot Date: 2025-03-27 13:40 -0400 (Thu, 27 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 2025-03-28 11:53 -0400 (Fri, 28 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" | 4783 |
| palomino7 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2025-03-01 r87860 ucrt) -- "Unsuffered Consequences" | 4552 |
| lconway | macOS 12.7.1 Monterey | x86_64 | R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences" | 4581 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4518 |
| 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 249/2315 | 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 | | ||||||||
| 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: 2025-03-27 20:00:31 -0400 (Thu, 27 Mar 2025) |
| EndedAt: 2025-03-27 20:01:26 -0400 (Thu, 27 Mar 2025) |
| EllapsedTime: 55.1 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
0.339 0.157 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 27 20:00:56 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 27 20:00:56 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: 0x600001ad0000>
>
>
>
> 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 27 20:01:01 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 27 20:01:03 2025"
>
> ColMode(tmp2)
<pointer: 0x600001ad0000>
>
>
>
> ### 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,] 99.6655965 0.1484671 0.8296873 0.4987719
[2,] -1.1776359 2.2283464 1.2232380 1.1425273
[3,] 0.3952731 -1.7261228 -1.6829212 3.3920364
[4,] 0.4364120 0.2562666 -1.9925793 -0.6894853
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.6655965 0.1484671 0.8296873 0.4987719
[2,] 1.1776359 2.2283464 1.2232380 1.1425273
[3,] 0.3952731 1.7261228 1.6829212 3.3920364
[4,] 0.4364120 0.2562666 1.9925793 0.6894853
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9832658 0.3853142 0.9108717 0.7062379
[2,] 1.0851893 1.4927647 1.1060009 1.0688907
[3,] 0.6287074 1.3138199 1.2972745 1.8417482
[4,] 0.6606149 0.5062278 1.4115875 0.8303525
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.49825 29.00161 34.93840 32.56115
[2,] 37.02953 42.15599 37.28325 36.83143
[3,] 31.68235 39.86432 39.65567 46.80952
[4,] 32.04256 30.31855 41.10845 33.99301
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600001a88000>
> exp(tmp5)
<pointer: 0x600001a88000>
> log(tmp5,2)
<pointer: 0x600001a88000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.2637
> Min(tmp5)
[1] 53.13942
> mean(tmp5)
[1] 73.17857
> Sum(tmp5)
[1] 14635.71
> Var(tmp5)
[1] 866.203
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 88.80416 71.57617 71.19861 71.39812 71.31213 73.11932 70.99082 69.56299
[9] 71.00270 72.82067
> rowSums(tmp5)
[1] 1776.083 1431.523 1423.972 1427.962 1426.243 1462.386 1419.816 1391.260
[9] 1420.054 1456.413
> rowVars(tmp5)
[1] 7987.10446 98.19393 115.73242 54.22298 94.59983 83.45284
[7] 90.75558 98.72565 82.07386 72.71157
> rowSd(tmp5)
[1] 89.370602 9.909285 10.757901 7.363625 9.726245 9.135253 9.526572
[8] 9.936078 9.059463 8.527108
> rowMax(tmp5)
[1] 467.26370 90.40602 97.42788 85.56186 87.99912 84.56905 90.35100
[8] 86.36914 86.90931 91.56817
> rowMin(tmp5)
[1] 58.44028 57.37847 53.91465 61.42164 55.07040 58.52087 57.35597 54.83822
[9] 53.13942 59.51877
>
> colMeans(tmp5)
[1] 108.79749 75.43970 72.93667 72.19453 72.43400 70.13980 73.34643
[8] 71.57258 70.15306 71.96346 71.73004 71.87515 66.90604 74.67336
[15] 69.59442 71.07498 66.92420 74.01730 64.34322 73.45494
> colSums(tmp5)
[1] 1087.9749 754.3970 729.3667 721.9453 724.3400 701.3980 733.4643
[8] 715.7258 701.5306 719.6346 717.3004 718.7515 669.0604 746.7336
[15] 695.9442 710.7498 669.2420 740.1730 643.4322 734.5494
> colVars(tmp5)
[1] 15952.95735 156.52757 68.51552 114.70422 57.48096 81.88780
[7] 44.72979 44.93367 164.31342 71.76547 75.27255 62.22238
[13] 64.04480 98.01061 34.97097 69.25840 44.04007 123.47005
[19] 40.17828 140.67010
> colSd(tmp5)
[1] 126.305017 12.511098 8.277410 10.710006 7.581620 9.049188
[7] 6.688034 6.703258 12.818480 8.471450 8.675975 7.888116
[13] 8.002800 9.900031 5.913626 8.322163 6.636269 11.111708
[19] 6.338634 11.860443
> colMax(tmp5)
[1] 467.26370 90.35100 85.56186 97.42788 83.80173 82.53958 85.69440
[8] 82.88396 90.40602 82.92277 86.36914 81.96764 82.75094 89.08994
[15] 77.13165 84.56905 77.91614 87.05260 75.68209 91.56817
> colMin(tmp5)
[1] 55.46780 54.83822 59.96473 58.17140 58.72844 57.35597 65.99459 63.85540
[9] 53.91465 61.42164 58.44028 60.57705 57.51156 60.88979 58.52087 59.63622
[17] 57.05036 53.13942 55.07040 56.21665
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 88.80416 71.57617 71.19861 71.39812 71.31213 73.11932 NA 69.56299
[9] 71.00270 72.82067
> rowSums(tmp5)
[1] 1776.083 1431.523 1423.972 1427.962 1426.243 1462.386 NA 1391.260
[9] 1420.054 1456.413
> rowVars(tmp5)
[1] 7987.10446 98.19393 115.73242 54.22298 94.59983 83.45284
[7] 94.83162 98.72565 82.07386 72.71157
> rowSd(tmp5)
[1] 89.370602 9.909285 10.757901 7.363625 9.726245 9.135253 9.738153
[8] 9.936078 9.059463 8.527108
> rowMax(tmp5)
[1] 467.26370 90.40602 97.42788 85.56186 87.99912 84.56905 NA
[8] 86.36914 86.90931 91.56817
> rowMin(tmp5)
[1] 58.44028 57.37847 53.91465 61.42164 55.07040 58.52087 NA 54.83822
[9] 53.13942 59.51877
>
> colMeans(tmp5)
[1] 108.79749 75.43970 72.93667 72.19453 72.43400 70.13980 73.34643
[8] NA 70.15306 71.96346 71.73004 71.87515 66.90604 74.67336
[15] 69.59442 71.07498 66.92420 74.01730 64.34322 73.45494
> colSums(tmp5)
[1] 1087.9749 754.3970 729.3667 721.9453 724.3400 701.3980 733.4643
[8] NA 701.5306 719.6346 717.3004 718.7515 669.0604 746.7336
[15] 695.9442 710.7498 669.2420 740.1730 643.4322 734.5494
> colVars(tmp5)
[1] 15952.95735 156.52757 68.51552 114.70422 57.48096 81.88780
[7] 44.72979 NA 164.31342 71.76547 75.27255 62.22238
[13] 64.04480 98.01061 34.97097 69.25840 44.04007 123.47005
[19] 40.17828 140.67010
> colSd(tmp5)
[1] 126.305017 12.511098 8.277410 10.710006 7.581620 9.049188
[7] 6.688034 NA 12.818480 8.471450 8.675975 7.888116
[13] 8.002800 9.900031 5.913626 8.322163 6.636269 11.111708
[19] 6.338634 11.860443
> colMax(tmp5)
[1] 467.26370 90.35100 85.56186 97.42788 83.80173 82.53958 85.69440
[8] NA 90.40602 82.92277 86.36914 81.96764 82.75094 89.08994
[15] 77.13165 84.56905 77.91614 87.05260 75.68209 91.56817
> colMin(tmp5)
[1] 55.46780 54.83822 59.96473 58.17140 58.72844 57.35597 65.99459 NA
[9] 53.91465 61.42164 58.44028 60.57705 57.51156 60.88979 58.52087 59.63622
[17] 57.05036 53.13942 55.07040 56.21665
>
> Max(tmp5,na.rm=TRUE)
[1] 467.2637
> Min(tmp5,na.rm=TRUE)
[1] 53.13942
> mean(tmp5,na.rm=TRUE)
[1] 73.16914
> Sum(tmp5,na.rm=TRUE)
[1] 14560.66
> Var(tmp5,na.rm=TRUE)
[1] 870.5599
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.80416 71.57617 71.19861 71.39812 71.31213 73.11932 70.77692 69.56299
[9] 71.00270 72.82067
> rowSums(tmp5,na.rm=TRUE)
[1] 1776.083 1431.523 1423.972 1427.962 1426.243 1462.386 1344.761 1391.260
[9] 1420.054 1456.413
> rowVars(tmp5,na.rm=TRUE)
[1] 7987.10446 98.19393 115.73242 54.22298 94.59983 83.45284
[7] 94.83162 98.72565 82.07386 72.71157
> rowSd(tmp5,na.rm=TRUE)
[1] 89.370602 9.909285 10.757901 7.363625 9.726245 9.135253 9.738153
[8] 9.936078 9.059463 8.527108
> rowMax(tmp5,na.rm=TRUE)
[1] 467.26370 90.40602 97.42788 85.56186 87.99912 84.56905 90.35100
[8] 86.36914 86.90931 91.56817
> rowMin(tmp5,na.rm=TRUE)
[1] 58.44028 57.37847 53.91465 61.42164 55.07040 58.52087 57.35597 54.83822
[9] 53.13942 59.51877
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.79749 75.43970 72.93667 72.19453 72.43400 70.13980 73.34643
[8] 71.18564 70.15306 71.96346 71.73004 71.87515 66.90604 74.67336
[15] 69.59442 71.07498 66.92420 74.01730 64.34322 73.45494
> colSums(tmp5,na.rm=TRUE)
[1] 1087.9749 754.3970 729.3667 721.9453 724.3400 701.3980 733.4643
[8] 640.6708 701.5306 719.6346 717.3004 718.7515 669.0604 746.7336
[15] 695.9442 710.7498 669.2420 740.1730 643.4322 734.5494
> colVars(tmp5,na.rm=TRUE)
[1] 15952.95735 156.52757 68.51552 114.70422 57.48096 81.88780
[7] 44.72979 48.86605 164.31342 71.76547 75.27255 62.22238
[13] 64.04480 98.01061 34.97097 69.25840 44.04007 123.47005
[19] 40.17828 140.67010
> colSd(tmp5,na.rm=TRUE)
[1] 126.305017 12.511098 8.277410 10.710006 7.581620 9.049188
[7] 6.688034 6.990426 12.818480 8.471450 8.675975 7.888116
[13] 8.002800 9.900031 5.913626 8.322163 6.636269 11.111708
[19] 6.338634 11.860443
> colMax(tmp5,na.rm=TRUE)
[1] 467.26370 90.35100 85.56186 97.42788 83.80173 82.53958 85.69440
[8] 82.88396 90.40602 82.92277 86.36914 81.96764 82.75094 89.08994
[15] 77.13165 84.56905 77.91614 87.05260 75.68209 91.56817
> colMin(tmp5,na.rm=TRUE)
[1] 55.46780 54.83822 59.96473 58.17140 58.72844 57.35597 65.99459 63.85540
[9] 53.91465 61.42164 58.44028 60.57705 57.51156 60.88979 58.52087 59.63622
[17] 57.05036 53.13942 55.07040 56.21665
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.80416 71.57617 71.19861 71.39812 71.31213 73.11932 NaN 69.56299
[9] 71.00270 72.82067
> rowSums(tmp5,na.rm=TRUE)
[1] 1776.083 1431.523 1423.972 1427.962 1426.243 1462.386 0.000 1391.260
[9] 1420.054 1456.413
> rowVars(tmp5,na.rm=TRUE)
[1] 7987.10446 98.19393 115.73242 54.22298 94.59983 83.45284
[7] NA 98.72565 82.07386 72.71157
> rowSd(tmp5,na.rm=TRUE)
[1] 89.370602 9.909285 10.757901 7.363625 9.726245 9.135253 NA
[8] 9.936078 9.059463 8.527108
> rowMax(tmp5,na.rm=TRUE)
[1] 467.26370 90.40602 97.42788 85.56186 87.99912 84.56905 NA
[8] 86.36914 86.90931 91.56817
> rowMin(tmp5,na.rm=TRUE)
[1] 58.44028 57.37847 53.91465 61.42164 55.07040 58.52087 NA 54.83822
[9] 53.13942 59.51877
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.50374 73.78289 72.53202 71.69467 72.03852 71.56022 74.16331
[8] NaN 71.21305 70.74576 70.74751 70.94937 66.41081 76.20487
[15] 70.14371 70.61761 67.53044 74.23958 63.08335 75.08600
> colSums(tmp5,na.rm=TRUE)
[1] 1030.5336 664.0460 652.7882 645.2520 648.3467 644.0420 667.4697
[8] 0.0000 640.9174 636.7119 636.7275 638.5443 597.6972 685.8439
[15] 631.2933 635.5585 607.7739 668.1562 567.7502 675.7740
> colVars(tmp5,na.rm=TRUE)
[1] 17580.76249 145.21200 75.23793 126.23129 62.90656 69.42569
[7] 42.81413 NA 172.21234 64.05471 73.82105 60.35808
[13] 69.29126 83.87486 35.94804 75.56227 45.41048 138.34798
[19] 27.34363 128.32488
> colSd(tmp5,na.rm=TRUE)
[1] 132.592468 12.050394 8.673980 11.235270 7.931366 8.332208
[7] 6.543250 NA 13.122970 8.003419 8.591918 7.769046
[13] 8.324137 9.158322 5.995668 8.692656 6.738730 11.762142
[19] 5.229114 11.328057
> colMax(tmp5,na.rm=TRUE)
[1] 467.26370 87.74218 85.56186 97.42788 83.80173 82.53958 85.69440
[8] -Inf 90.40602 82.09910 86.36914 81.96764 82.75094 89.08994
[15] 77.13165 84.56905 77.91614 87.05260 70.96026 91.56817
> colMin(tmp5,na.rm=TRUE)
[1] 55.46780 54.83822 59.96473 58.17140 58.72844 57.37847 66.79029 Inf
[9] 53.91465 61.42164 58.44028 60.57705 57.51156 61.53931 58.52087 59.63622
[17] 57.05036 53.13942 55.07040 56.21665
>
>
>
>
> 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] 335.14943 145.92930 283.74792 256.81215 186.33634 289.24028 97.92746
[8] 134.80685 335.51143 182.47933
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 335.14943 145.92930 283.74792 256.81215 186.33634 289.24028 97.92746
[8] 134.80685 335.51143 182.47933
>
>
>
> 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-13 -1.136868e-13 1.705303e-13 1.421085e-14 -5.684342e-14
[6] 2.842171e-14 8.526513e-14 -8.526513e-14 -8.526513e-14 -8.526513e-14
[11] 0.000000e+00 5.684342e-14 0.000000e+00 8.526513e-14 -1.421085e-13
[16] -1.705303e-13 -2.842171e-14 0.000000e+00 -1.136868e-13 5.684342e-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)
+ }
8 12
6 12
8 4
3 17
9 11
1 12
7 6
3 6
3 1
9 19
7 16
1 9
5 2
9 12
7 18
2 3
6 10
8 5
1 13
2 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] 2.612677
> Min(tmp)
[1] -2.237441
> mean(tmp)
[1] 0.02651416
> Sum(tmp)
[1] 2.651416
> Var(tmp)
[1] 0.9486064
>
> rowMeans(tmp)
[1] 0.02651416
> rowSums(tmp)
[1] 2.651416
> rowVars(tmp)
[1] 0.9486064
> rowSd(tmp)
[1] 0.9739643
> rowMax(tmp)
[1] 2.612677
> rowMin(tmp)
[1] -2.237441
>
> colMeans(tmp)
[1] 1.896589602 0.834884079 -0.965919632 -1.809911375 -0.633962694
[6] 1.265727920 0.401893316 -0.380266482 -0.080944078 0.919550476
[11] 1.120941769 -0.377795634 -0.685089853 0.857187394 1.070470208
[16] -0.650313169 1.230725100 -1.146800390 0.104250661 0.747695372
[21] 0.078030632 2.612677143 0.949788231 -0.009550016 -0.100774203
[26] -0.287380260 0.154848137 -0.822307525 -1.473696741 -0.487935527
[31] -0.465129641 0.174405663 1.105780720 1.128349980 1.958036104
[36] -0.554115967 0.524577771 0.835632143 -0.468681232 0.541928372
[41] 0.042948007 0.496781879 0.654209847 1.072456506 1.420000469
[46] 0.385873564 0.498995824 0.805786910 -0.576526047 1.570588189
[51] -0.381075254 -0.243156667 0.834948762 -1.023649990 -0.885950743
[56] 0.863612721 -0.475409876 1.039635468 -1.305510772 -0.082831277
[61] -1.611577179 0.872565108 -0.029520167 0.047251814 -0.063889866
[66] 0.998862263 -1.885560465 0.577980109 0.424474872 -1.177640256
[71] 0.398177779 -0.459747922 -0.866184104 0.653575686 -0.709656803
[76] -0.518390336 -0.531350245 -0.580226594 -1.497413569 -1.216298364
[81] 2.460761058 -1.430557156 0.281649226 -1.732953274 -0.763368028
[86] -0.070185770 0.700714087 0.281631805 0.285167936 -0.929180699
[91] 0.335466866 -0.818208535 0.197488758 1.740371911 -0.269152169
[96] -1.126819227 0.486743124 -0.895608189 -2.237441387 -0.495659730
> colSums(tmp)
[1] 1.896589602 0.834884079 -0.965919632 -1.809911375 -0.633962694
[6] 1.265727920 0.401893316 -0.380266482 -0.080944078 0.919550476
[11] 1.120941769 -0.377795634 -0.685089853 0.857187394 1.070470208
[16] -0.650313169 1.230725100 -1.146800390 0.104250661 0.747695372
[21] 0.078030632 2.612677143 0.949788231 -0.009550016 -0.100774203
[26] -0.287380260 0.154848137 -0.822307525 -1.473696741 -0.487935527
[31] -0.465129641 0.174405663 1.105780720 1.128349980 1.958036104
[36] -0.554115967 0.524577771 0.835632143 -0.468681232 0.541928372
[41] 0.042948007 0.496781879 0.654209847 1.072456506 1.420000469
[46] 0.385873564 0.498995824 0.805786910 -0.576526047 1.570588189
[51] -0.381075254 -0.243156667 0.834948762 -1.023649990 -0.885950743
[56] 0.863612721 -0.475409876 1.039635468 -1.305510772 -0.082831277
[61] -1.611577179 0.872565108 -0.029520167 0.047251814 -0.063889866
[66] 0.998862263 -1.885560465 0.577980109 0.424474872 -1.177640256
[71] 0.398177779 -0.459747922 -0.866184104 0.653575686 -0.709656803
[76] -0.518390336 -0.531350245 -0.580226594 -1.497413569 -1.216298364
[81] 2.460761058 -1.430557156 0.281649226 -1.732953274 -0.763368028
[86] -0.070185770 0.700714087 0.281631805 0.285167936 -0.929180699
[91] 0.335466866 -0.818208535 0.197488758 1.740371911 -0.269152169
[96] -1.126819227 0.486743124 -0.895608189 -2.237441387 -0.495659730
> 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] 1.896589602 0.834884079 -0.965919632 -1.809911375 -0.633962694
[6] 1.265727920 0.401893316 -0.380266482 -0.080944078 0.919550476
[11] 1.120941769 -0.377795634 -0.685089853 0.857187394 1.070470208
[16] -0.650313169 1.230725100 -1.146800390 0.104250661 0.747695372
[21] 0.078030632 2.612677143 0.949788231 -0.009550016 -0.100774203
[26] -0.287380260 0.154848137 -0.822307525 -1.473696741 -0.487935527
[31] -0.465129641 0.174405663 1.105780720 1.128349980 1.958036104
[36] -0.554115967 0.524577771 0.835632143 -0.468681232 0.541928372
[41] 0.042948007 0.496781879 0.654209847 1.072456506 1.420000469
[46] 0.385873564 0.498995824 0.805786910 -0.576526047 1.570588189
[51] -0.381075254 -0.243156667 0.834948762 -1.023649990 -0.885950743
[56] 0.863612721 -0.475409876 1.039635468 -1.305510772 -0.082831277
[61] -1.611577179 0.872565108 -0.029520167 0.047251814 -0.063889866
[66] 0.998862263 -1.885560465 0.577980109 0.424474872 -1.177640256
[71] 0.398177779 -0.459747922 -0.866184104 0.653575686 -0.709656803
[76] -0.518390336 -0.531350245 -0.580226594 -1.497413569 -1.216298364
[81] 2.460761058 -1.430557156 0.281649226 -1.732953274 -0.763368028
[86] -0.070185770 0.700714087 0.281631805 0.285167936 -0.929180699
[91] 0.335466866 -0.818208535 0.197488758 1.740371911 -0.269152169
[96] -1.126819227 0.486743124 -0.895608189 -2.237441387 -0.495659730
> colMin(tmp)
[1] 1.896589602 0.834884079 -0.965919632 -1.809911375 -0.633962694
[6] 1.265727920 0.401893316 -0.380266482 -0.080944078 0.919550476
[11] 1.120941769 -0.377795634 -0.685089853 0.857187394 1.070470208
[16] -0.650313169 1.230725100 -1.146800390 0.104250661 0.747695372
[21] 0.078030632 2.612677143 0.949788231 -0.009550016 -0.100774203
[26] -0.287380260 0.154848137 -0.822307525 -1.473696741 -0.487935527
[31] -0.465129641 0.174405663 1.105780720 1.128349980 1.958036104
[36] -0.554115967 0.524577771 0.835632143 -0.468681232 0.541928372
[41] 0.042948007 0.496781879 0.654209847 1.072456506 1.420000469
[46] 0.385873564 0.498995824 0.805786910 -0.576526047 1.570588189
[51] -0.381075254 -0.243156667 0.834948762 -1.023649990 -0.885950743
[56] 0.863612721 -0.475409876 1.039635468 -1.305510772 -0.082831277
[61] -1.611577179 0.872565108 -0.029520167 0.047251814 -0.063889866
[66] 0.998862263 -1.885560465 0.577980109 0.424474872 -1.177640256
[71] 0.398177779 -0.459747922 -0.866184104 0.653575686 -0.709656803
[76] -0.518390336 -0.531350245 -0.580226594 -1.497413569 -1.216298364
[81] 2.460761058 -1.430557156 0.281649226 -1.732953274 -0.763368028
[86] -0.070185770 0.700714087 0.281631805 0.285167936 -0.929180699
[91] 0.335466866 -0.818208535 0.197488758 1.740371911 -0.269152169
[96] -1.126819227 0.486743124 -0.895608189 -2.237441387 -0.495659730
> colMedians(tmp)
[1] 1.896589602 0.834884079 -0.965919632 -1.809911375 -0.633962694
[6] 1.265727920 0.401893316 -0.380266482 -0.080944078 0.919550476
[11] 1.120941769 -0.377795634 -0.685089853 0.857187394 1.070470208
[16] -0.650313169 1.230725100 -1.146800390 0.104250661 0.747695372
[21] 0.078030632 2.612677143 0.949788231 -0.009550016 -0.100774203
[26] -0.287380260 0.154848137 -0.822307525 -1.473696741 -0.487935527
[31] -0.465129641 0.174405663 1.105780720 1.128349980 1.958036104
[36] -0.554115967 0.524577771 0.835632143 -0.468681232 0.541928372
[41] 0.042948007 0.496781879 0.654209847 1.072456506 1.420000469
[46] 0.385873564 0.498995824 0.805786910 -0.576526047 1.570588189
[51] -0.381075254 -0.243156667 0.834948762 -1.023649990 -0.885950743
[56] 0.863612721 -0.475409876 1.039635468 -1.305510772 -0.082831277
[61] -1.611577179 0.872565108 -0.029520167 0.047251814 -0.063889866
[66] 0.998862263 -1.885560465 0.577980109 0.424474872 -1.177640256
[71] 0.398177779 -0.459747922 -0.866184104 0.653575686 -0.709656803
[76] -0.518390336 -0.531350245 -0.580226594 -1.497413569 -1.216298364
[81] 2.460761058 -1.430557156 0.281649226 -1.732953274 -0.763368028
[86] -0.070185770 0.700714087 0.281631805 0.285167936 -0.929180699
[91] 0.335466866 -0.818208535 0.197488758 1.740371911 -0.269152169
[96] -1.126819227 0.486743124 -0.895608189 -2.237441387 -0.495659730
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.89659 0.8348841 -0.9659196 -1.809911 -0.6339627 1.265728 0.4018933
[2,] 1.89659 0.8348841 -0.9659196 -1.809911 -0.6339627 1.265728 0.4018933
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.3802665 -0.08094408 0.9195505 1.120942 -0.3777956 -0.6850899 0.8571874
[2,] -0.3802665 -0.08094408 0.9195505 1.120942 -0.3777956 -0.6850899 0.8571874
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.07047 -0.6503132 1.230725 -1.1468 0.1042507 0.7476954 0.07803063
[2,] 1.07047 -0.6503132 1.230725 -1.1468 0.1042507 0.7476954 0.07803063
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 2.612677 0.9497882 -0.009550016 -0.1007742 -0.2873803 0.1548481 -0.8223075
[2,] 2.612677 0.9497882 -0.009550016 -0.1007742 -0.2873803 0.1548481 -0.8223075
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.473697 -0.4879355 -0.4651296 0.1744057 1.105781 1.12835 1.958036
[2,] -1.473697 -0.4879355 -0.4651296 0.1744057 1.105781 1.12835 1.958036
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.554116 0.5245778 0.8356321 -0.4686812 0.5419284 0.04294801 0.4967819
[2,] -0.554116 0.5245778 0.8356321 -0.4686812 0.5419284 0.04294801 0.4967819
[,43] [,44] [,45] [,46] [,47] [,48] [,49] [,50]
[1,] 0.6542098 1.072457 1.42 0.3858736 0.4989958 0.8057869 -0.576526 1.570588
[2,] 0.6542098 1.072457 1.42 0.3858736 0.4989958 0.8057869 -0.576526 1.570588
[,51] [,52] [,53] [,54] [,55] [,56] [,57]
[1,] -0.3810753 -0.2431567 0.8349488 -1.02365 -0.8859507 0.8636127 -0.4754099
[2,] -0.3810753 -0.2431567 0.8349488 -1.02365 -0.8859507 0.8636127 -0.4754099
[,58] [,59] [,60] [,61] [,62] [,63] [,64]
[1,] 1.039635 -1.305511 -0.08283128 -1.611577 0.8725651 -0.02952017 0.04725181
[2,] 1.039635 -1.305511 -0.08283128 -1.611577 0.8725651 -0.02952017 0.04725181
[,65] [,66] [,67] [,68] [,69] [,70] [,71]
[1,] -0.06388987 0.9988623 -1.88556 0.5779801 0.4244749 -1.17764 0.3981778
[2,] -0.06388987 0.9988623 -1.88556 0.5779801 0.4244749 -1.17764 0.3981778
[,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.4597479 -0.8661841 0.6535757 -0.7096568 -0.5183903 -0.5313502
[2,] -0.4597479 -0.8661841 0.6535757 -0.7096568 -0.5183903 -0.5313502
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.5802266 -1.497414 -1.216298 2.460761 -1.430557 0.2816492 -1.732953
[2,] -0.5802266 -1.497414 -1.216298 2.460761 -1.430557 0.2816492 -1.732953
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.763368 -0.07018577 0.7007141 0.2816318 0.2851679 -0.9291807 0.3354669
[2,] -0.763368 -0.07018577 0.7007141 0.2816318 0.2851679 -0.9291807 0.3354669
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.8182085 0.1974888 1.740372 -0.2691522 -1.126819 0.4867431 -0.8956082
[2,] -0.8182085 0.1974888 1.740372 -0.2691522 -1.126819 0.4867431 -0.8956082
[,99] [,100]
[1,] -2.237441 -0.4956597
[2,] -2.237441 -0.4956597
>
>
> Max(tmp2)
[1] 2.519686
> Min(tmp2)
[1] -2.311405
> mean(tmp2)
[1] 0.08063297
> Sum(tmp2)
[1] 8.063297
> Var(tmp2)
[1] 0.9711021
>
> rowMeans(tmp2)
[1] -0.282040138 -1.198391336 -0.988798024 0.464387250 0.083743859
[6] 0.230340593 1.695216533 0.244832621 2.519685950 -2.303885983
[11] -0.961233197 1.254596700 -0.050104044 -1.478654891 -0.615429135
[16] -1.245415241 -2.311405149 -0.208178269 0.787927561 0.325056906
[21] -0.454866608 -1.119296187 0.406623552 0.393326615 -0.977885920
[26] 0.379921851 -0.956359851 0.972535199 1.203916924 0.802564678
[31] -0.015697469 -0.537478132 0.015688114 1.270550001 -0.750773662
[36] -0.455849088 -1.907368752 -0.684754245 -1.236728757 1.046260490
[41] 0.705173245 0.952398663 0.198695233 -0.555491580 -0.011363207
[46] 0.261455651 1.390816579 0.806771944 -0.457047485 0.816814906
[51] -0.590931960 -1.209411440 -0.639479436 0.817219885 0.004756462
[56] -0.409394186 0.001848666 1.879340066 0.934053816 2.412284885
[61] -0.936098643 -0.009339883 -0.534999865 0.691412356 -0.175328356
[66] 0.292010110 2.252339589 -0.149328030 2.171429180 0.009389004
[71] 0.398272273 0.274783048 -0.618569588 1.008078448 -0.576665290
[76] 0.686565148 0.236435751 -0.722958406 1.111831454 1.305625786
[81] -1.020416991 0.304976508 2.287010821 0.052543703 0.820884725
[86] 0.561053683 -0.831572936 1.559508488 0.853424037 -0.218221462
[91] -0.359109336 -0.535755944 -0.294785890 -0.906696627 0.451847751
[96] -0.660796571 0.358170345 -0.621114408 -0.643986458 -0.473642299
> rowSums(tmp2)
[1] -0.282040138 -1.198391336 -0.988798024 0.464387250 0.083743859
[6] 0.230340593 1.695216533 0.244832621 2.519685950 -2.303885983
[11] -0.961233197 1.254596700 -0.050104044 -1.478654891 -0.615429135
[16] -1.245415241 -2.311405149 -0.208178269 0.787927561 0.325056906
[21] -0.454866608 -1.119296187 0.406623552 0.393326615 -0.977885920
[26] 0.379921851 -0.956359851 0.972535199 1.203916924 0.802564678
[31] -0.015697469 -0.537478132 0.015688114 1.270550001 -0.750773662
[36] -0.455849088 -1.907368752 -0.684754245 -1.236728757 1.046260490
[41] 0.705173245 0.952398663 0.198695233 -0.555491580 -0.011363207
[46] 0.261455651 1.390816579 0.806771944 -0.457047485 0.816814906
[51] -0.590931960 -1.209411440 -0.639479436 0.817219885 0.004756462
[56] -0.409394186 0.001848666 1.879340066 0.934053816 2.412284885
[61] -0.936098643 -0.009339883 -0.534999865 0.691412356 -0.175328356
[66] 0.292010110 2.252339589 -0.149328030 2.171429180 0.009389004
[71] 0.398272273 0.274783048 -0.618569588 1.008078448 -0.576665290
[76] 0.686565148 0.236435751 -0.722958406 1.111831454 1.305625786
[81] -1.020416991 0.304976508 2.287010821 0.052543703 0.820884725
[86] 0.561053683 -0.831572936 1.559508488 0.853424037 -0.218221462
[91] -0.359109336 -0.535755944 -0.294785890 -0.906696627 0.451847751
[96] -0.660796571 0.358170345 -0.621114408 -0.643986458 -0.473642299
> 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] -0.282040138 -1.198391336 -0.988798024 0.464387250 0.083743859
[6] 0.230340593 1.695216533 0.244832621 2.519685950 -2.303885983
[11] -0.961233197 1.254596700 -0.050104044 -1.478654891 -0.615429135
[16] -1.245415241 -2.311405149 -0.208178269 0.787927561 0.325056906
[21] -0.454866608 -1.119296187 0.406623552 0.393326615 -0.977885920
[26] 0.379921851 -0.956359851 0.972535199 1.203916924 0.802564678
[31] -0.015697469 -0.537478132 0.015688114 1.270550001 -0.750773662
[36] -0.455849088 -1.907368752 -0.684754245 -1.236728757 1.046260490
[41] 0.705173245 0.952398663 0.198695233 -0.555491580 -0.011363207
[46] 0.261455651 1.390816579 0.806771944 -0.457047485 0.816814906
[51] -0.590931960 -1.209411440 -0.639479436 0.817219885 0.004756462
[56] -0.409394186 0.001848666 1.879340066 0.934053816 2.412284885
[61] -0.936098643 -0.009339883 -0.534999865 0.691412356 -0.175328356
[66] 0.292010110 2.252339589 -0.149328030 2.171429180 0.009389004
[71] 0.398272273 0.274783048 -0.618569588 1.008078448 -0.576665290
[76] 0.686565148 0.236435751 -0.722958406 1.111831454 1.305625786
[81] -1.020416991 0.304976508 2.287010821 0.052543703 0.820884725
[86] 0.561053683 -0.831572936 1.559508488 0.853424037 -0.218221462
[91] -0.359109336 -0.535755944 -0.294785890 -0.906696627 0.451847751
[96] -0.660796571 0.358170345 -0.621114408 -0.643986458 -0.473642299
> rowMin(tmp2)
[1] -0.282040138 -1.198391336 -0.988798024 0.464387250 0.083743859
[6] 0.230340593 1.695216533 0.244832621 2.519685950 -2.303885983
[11] -0.961233197 1.254596700 -0.050104044 -1.478654891 -0.615429135
[16] -1.245415241 -2.311405149 -0.208178269 0.787927561 0.325056906
[21] -0.454866608 -1.119296187 0.406623552 0.393326615 -0.977885920
[26] 0.379921851 -0.956359851 0.972535199 1.203916924 0.802564678
[31] -0.015697469 -0.537478132 0.015688114 1.270550001 -0.750773662
[36] -0.455849088 -1.907368752 -0.684754245 -1.236728757 1.046260490
[41] 0.705173245 0.952398663 0.198695233 -0.555491580 -0.011363207
[46] 0.261455651 1.390816579 0.806771944 -0.457047485 0.816814906
[51] -0.590931960 -1.209411440 -0.639479436 0.817219885 0.004756462
[56] -0.409394186 0.001848666 1.879340066 0.934053816 2.412284885
[61] -0.936098643 -0.009339883 -0.534999865 0.691412356 -0.175328356
[66] 0.292010110 2.252339589 -0.149328030 2.171429180 0.009389004
[71] 0.398272273 0.274783048 -0.618569588 1.008078448 -0.576665290
[76] 0.686565148 0.236435751 -0.722958406 1.111831454 1.305625786
[81] -1.020416991 0.304976508 2.287010821 0.052543703 0.820884725
[86] 0.561053683 -0.831572936 1.559508488 0.853424037 -0.218221462
[91] -0.359109336 -0.535755944 -0.294785890 -0.906696627 0.451847751
[96] -0.660796571 0.358170345 -0.621114408 -0.643986458 -0.473642299
>
> colMeans(tmp2)
[1] 0.08063297
> colSums(tmp2)
[1] 8.063297
> colVars(tmp2)
[1] 0.9711021
> colSd(tmp2)
[1] 0.9854451
> colMax(tmp2)
[1] 2.519686
> colMin(tmp2)
[1] -2.311405
> colMedians(tmp2)
[1] 0.007072733
> colRanges(tmp2)
[,1]
[1,] -2.311405
[2,] 2.519686
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.5025935 1.4669756 -0.6834297 -3.8731925 5.7166044 -0.6077226
[7] 8.7301826 1.4871365 -4.4957503 0.6221203
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.93144917
[2,] -0.51285090
[3,] -0.05923903
[4,] 0.18652452
[5,] 1.30435112
>
> rowApply(tmp,sum)
[1] 2.75149168 3.09637000 3.62065149 -1.80574291 2.71044503 0.83716554
[7] -0.08016221 1.09767215 -4.88854616 -1.47901375
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 1 8 1 4 7 6 5 6 6
[2,] 6 3 9 5 9 4 1 9 2 5
[3,] 1 7 5 9 6 1 4 6 10 3
[4,] 2 2 1 10 3 2 5 3 7 2
[5,] 9 5 6 8 7 10 10 2 3 10
[6,] 3 8 4 2 1 6 9 4 9 8
[7,] 10 9 10 6 10 9 2 8 5 4
[8,] 8 10 7 7 8 5 8 7 1 7
[9,] 5 4 2 3 2 3 3 1 4 9
[10,] 4 6 3 4 5 8 7 10 8 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.3341941 -2.9367896 0.9732163 -1.9929314 -1.1523276 -4.0368656
[7] 0.7260721 -2.8159348 2.5317477 -4.2133114 2.8616342 0.5446277
[13] -0.6777031 3.3912593 -3.4325202 -2.5745374 -3.1626653 3.2846990
[19] 3.7007189 0.1160122
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.58793345
[2,] -0.34194524
[3,] -0.25369265
[4,] 0.02353248
[5,] 0.82584475
>
> rowApply(tmp,sum)
[1] 2.014214 -4.974663 1.061904 -1.758649 -5.542600
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 7 7 9 8 18
[2,] 4 6 1 15 17
[3,] 11 3 12 16 19
[4,] 19 1 18 1 11
[5,] 18 16 6 4 4
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.02353248 -0.7592185 0.2600566 1.00416722 0.8577883 0.6247474
[2,] -0.58793345 -0.6883390 -1.5351761 -2.22768784 0.6031078 -1.0193306
[3,] -0.34194524 -2.3720074 0.4124731 1.08256958 -0.7570344 -1.8946144
[4,] -0.25369265 0.3842230 0.6741738 -1.80823739 -0.6631915 0.1491967
[5,] 0.82584475 0.4985522 1.1616889 -0.04374302 -1.1929977 -1.8968647
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.9616546 0.3613853 -0.3005701 0.6170677 0.47018269 0.2319422
[2,] -0.2603693 -0.5119324 0.6795873 -1.2132629 0.32305690 0.1609486
[3,] 1.0418030 -1.3960539 0.8741455 -0.7372070 1.77725414 0.5224402
[4,] 1.1006351 -1.6674470 1.1324874 0.2225041 -0.05582847 -0.5459318
[5,] -0.1943421 0.3981132 0.1460976 -3.1024133 0.34696896 0.1752286
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.2676763 0.6901223 1.6932551 0.14811768 -1.7856216 0.04890767
[2,] -0.2444181 0.1662028 -1.6155288 -0.36341900 -0.5617723 1.76327181
[3,] 0.4082189 3.4966727 -0.4626319 -1.34596798 -1.0888103 1.01585122
[4,] 0.8212100 -0.6066100 -0.8486318 0.08402475 0.6987599 -0.03456117
[5,] -0.3950377 -0.3551285 -2.1989827 -1.09729288 -0.4252210 0.49122944
[,19] [,20]
[1,] 0.6453682 -0.5876853
[2,] 1.4182938 0.7400378
[3,] 0.3683319 0.4584167
[4,] -0.1903600 -0.3513720
[5,] 1.4590851 -0.1433849
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 649 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 563 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-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 0.2120096 0.3111301 -2.25217 0.9892139 1.528963 -0.4307043 0.5294793
col8 col9 col10 col11 col12 col13 col14
row1 0.06175362 -1.331713 -0.08945914 1.088718 -0.1339928 -1.363032 -1.230935
col15 col16 col17 col18 col19 col20
row1 0.2004633 -0.4354035 2.264343 -1.083627 -1.300331 -1.900628
> tmp[,"col10"]
col10
row1 -0.08945914
row2 -1.44509822
row3 -0.81719556
row4 0.10716528
row5 -0.55495420
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.2120096 0.3111301 -2.252170 0.9892139 1.5289629 -0.4307043
row5 -1.3263012 -1.8212481 1.834946 -0.3385454 -0.2662794 0.2301634
col7 col8 col9 col10 col11 col12
row1 0.529479250 0.06175362 -1.3317128 -0.08945914 1.088718 -0.1339928
row5 0.008759723 0.47338812 0.2475705 -0.55495420 1.237337 0.3461808
col13 col14 col15 col16 col17 col18
row1 -1.3630320 -1.2309352 0.2004633 -0.4354035 2.26434318 -1.083627
row5 -0.1096652 -0.5885351 0.7590660 -0.8139933 -0.03628988 -0.398006
col19 col20
row1 -1.3003313 -1.9006278
row5 -0.5895293 -0.7233096
> tmp[,c("col6","col20")]
col6 col20
row1 -0.43070429 -1.90062783
row2 -1.66382914 1.69276233
row3 1.79105535 0.19906719
row4 0.03034452 0.08661463
row5 0.23016340 -0.72330963
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.4307043 -1.9006278
row5 0.2301634 -0.7233096
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.05136 50.46245 51.03441 51.11253 48.92401 104.8698 50.6082 47.70256
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.11045 48.90419 49.2606 49.18968 49.84126 50.26705 50.41606 49.43528
col17 col18 col19 col20
row1 50.18335 51.06329 50.4688 105.6287
> tmp[,"col10"]
col10
row1 48.90419
row2 30.42905
row3 30.41899
row4 30.22638
row5 50.88239
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.05136 50.46245 51.03441 51.11253 48.92401 104.8698 50.60820 47.70256
row5 50.31022 50.46280 48.16701 49.00917 50.09548 104.6213 48.72699 50.41134
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.11045 48.90419 49.26060 49.18968 49.84126 50.26705 50.41606 49.43528
row5 49.36800 50.88239 48.46375 49.45305 49.89999 50.09209 49.71994 50.74127
col17 col18 col19 col20
row1 50.18335 51.06329 50.46880 105.6287
row5 50.67380 50.09635 49.87199 104.2777
> tmp[,c("col6","col20")]
col6 col20
row1 104.86976 105.62873
row2 76.21319 77.01878
row3 75.86838 75.16216
row4 73.78087 74.28408
row5 104.62135 104.27765
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.8698 105.6287
row5 104.6213 104.2777
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.8698 105.6287
row5 104.6213 104.2777
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.16728069
[2,] -0.01545286
[3,] -0.55464182
[4,] -0.10323899
[5,] 2.18936627
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.2003546 -1.66365037
[2,] 0.6052660 -1.08624394
[3,] -0.6225195 0.04661716
[4,] -1.0418863 0.23602685
[5,] 0.9422002 0.03691252
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.9791782 -1.8232745
[2,] -0.2265028 -1.0101809
[3,] 0.3856856 -0.4281318
[4,] 1.3357317 0.3056942
[5,] 1.1865141 -0.3594322
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.9791782
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.9791782
[2,] -0.2265028
>
>
>
> 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 -0.70381202 -0.5620929 -0.3903651 -0.9701104 1.942884 -0.24146299
row1 0.05483471 -0.6469547 -0.3769169 1.0425160 -1.459007 0.04650051
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.2600884 1.3976000 0.7865235 2.5863825 0.5390881 0.816154 0.8232203
row1 0.4189600 0.3506974 -1.1603252 0.1462168 -0.9945674 -0.842831 -0.4106163
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -1.0496021 0.6494588 0.5033691 -0.2719899 1.0181090 1.1391758 0.9846642
row1 0.4938553 -1.2858766 -0.7860082 -0.1500368 0.2176228 0.9385928 0.2882700
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.2787434 -0.8270983 -0.5726914 -0.5668674 1.582554 2.53558 -1.295531
[,8] [,9] [,10]
row2 0.1068237 1.128008 -0.1607856
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.1485406 -1.546554 -1.374303 -1.465393 -0.140952 -0.1432165 2.714233
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.043376 0.8902445 -0.5555493 -0.3788487 -0.6372748 1.183724 0.2761796
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.794042 1.672018 1.968901 1.581702 0.1731454 0.7504365
>
>
> 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: 0x600001a982a0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMc3b26839d968"
[2] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMc3b22df0704d"
[3] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMc3b245ce6cb"
[4] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMc3b26f341ba9"
[5] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMc3b246042d48"
[6] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMc3b23c38f5e1"
[7] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMc3b23f96a5aa"
[8] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMc3b23b565c83"
[9] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMc3b222d3bae4"
[10] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMc3b27a92e098"
[11] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMc3b240d75a06"
[12] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMc3b27a57612b"
[13] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMc3b27eac8ccc"
[14] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMc3b2724fe60c"
[15] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BMc3b25b885875"
>
>
> ### 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: 0x600001a38000>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600001a38000>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600001a38000>
> rowMedians(tmp)
[1] 0.491715229 0.451375619 0.297592488 0.376959809 0.476398405
[6] 0.165698585 -0.102570031 -0.302017434 -0.635985944 -0.102822691
[11] -0.630173561 -0.314093072 -0.045455823 0.164081371 0.076884042
[16] 0.365566320 -0.533241023 -0.312935173 0.314901206 0.454529584
[21] -0.589593147 -0.133519187 0.107416812 0.361861396 1.081836949
[26] -0.063427552 0.291338880 0.756404162 0.368044466 -0.255486409
[31] -0.104823577 0.198425012 0.038389412 -0.068682739 -0.166682840
[36] 0.129796993 -0.069033166 -0.346807448 -0.303893070 0.174630187
[41] -0.173024149 0.297043246 0.267559682 -0.824212061 -0.190905921
[46] 0.287431387 0.148063957 0.006449487 -0.016117775 0.233159256
[51] 0.257555588 -0.536043851 -0.229308243 0.402522167 0.505667388
[56] 0.676634985 -0.174796778 -0.129970996 -0.216153273 0.099233479
[61] 0.085855368 0.612921061 0.072887507 0.219425259 -0.156879390
[66] 0.059071232 0.149237865 0.049411047 -0.762507409 -0.425339872
[71] 0.234147955 0.144064765 0.148554182 -0.330973429 0.250142434
[76] 0.552095613 -0.357348783 0.209750552 0.136086155 -0.328037090
[81] 0.251312017 0.108047092 0.163341954 0.056389394 0.062805840
[86] -0.372661323 0.402385627 -0.416121809 -0.058252468 0.015098546
[91] 0.048497203 -0.075983201 -0.140451938 0.110464793 0.001091780
[96] -0.583740210 0.177115699 -0.273260298 -0.163821468 0.088993561
[101] 0.144583346 0.365671106 0.096311005 0.225724226 0.226565491
[106] -0.260099119 0.839204312 0.005995107 -0.265039994 -0.622325258
[111] -0.078031672 -0.690538269 -0.521785104 -0.339152156 -0.141462549
[116] 0.281225645 -0.043374247 -0.176769730 0.531955700 -0.115498608
[121] -0.099057372 0.665190600 -0.216461794 -0.220502757 -0.600186034
[126] -0.419518800 -0.627332374 0.365860757 0.223610779 0.580164146
[131] 0.298824701 -0.184657385 0.711937720 0.262668807 0.078977069
[136] 0.624635976 0.402993178 -0.136001014 0.304468638 -0.083070312
[141] 0.133105754 0.114619887 0.487764027 0.022577287 -0.265584388
[146] 0.115488758 -0.198926823 -0.211587764 0.080006317 -0.242728515
[151] -0.341485067 -0.007938497 -0.149296250 0.132801707 -0.303595454
[156] 0.170767802 0.032337953 -0.068639452 0.163429359 -0.371788350
[161] -0.064453828 -0.199401363 0.052824705 -0.085749091 0.387219971
[166] -0.028963092 -0.094147624 0.114886656 -0.286217191 0.136093068
[171] 0.451727773 -0.094039779 0.400945991 -0.301025861 -0.418638287
[176] -0.063501677 -0.359919964 0.108757302 -0.596223550 -0.065779010
[181] 0.390358205 -0.081632898 0.143889134 -0.376967767 0.236378130
[186] 0.342167454 0.116801168 0.094761401 -0.082017963 0.256664679
[191] -0.009857821 0.143821309 -0.089013950 0.390979871 -0.184163606
[196] -0.576508596 -0.124694188 -0.177313463 -0.126169022 -0.014520932
[201] -0.021382033 -0.046355201 -0.282259937 0.188302583 -0.266463894
[206] -0.020670333 -0.110908004 -0.201936351 0.274009454 0.046540633
[211] 0.146959554 -0.174552149 -0.177176649 0.439178228 0.259110270
[216] 0.614625373 0.185264484 -0.276800635 0.023837417 -0.305766700
[221] -0.033859627 -0.204010971 -0.497947593 -0.016584492 0.231866419
[226] 0.153870306 0.162887669 0.134028388 -0.136818035 0.381139442
>
> proc.time()
user system elapsed
2.743 16.444 20.036
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: 0x600003bf8000>
> .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: 0x600003bf8000>
> .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: 0x600003bf8000>
> .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: 0x600003bf8000>
> 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: 0x600003bfc360>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003bfc360>
> .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: 0x600003bfc360>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003bfc360>
> .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: 0x600003bfc360>
> 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: 0x600003bb00c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003bb00c0>
> .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: 0x600003bb00c0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003bb00c0>
> .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: 0x600003bb00c0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600003bb00c0>
> .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: 0x600003bb00c0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600003bb00c0>
> .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: 0x600003bb00c0>
> 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: 0x600003bf00c0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600003bf00c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003bf00c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003bf00c0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilec9612244becb" "BufferedMatrixFilec9614f4a1300"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilec9612244becb" "BufferedMatrixFilec9614f4a1300"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003bc8000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003bc8000>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003bc8000>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003bc8000>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600003bc8000>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600003bc8000>
> .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: 0x600003bc8180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003bc8180>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003bc8180>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600003bc8180>
> 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: 0x600003bac060>
> .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: 0x600003bac060>
> rm(P)
>
> proc.time()
user system elapsed
0.355 0.172 0.515
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences"
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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
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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
0.335 0.100 0.423