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 11:54 -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. - See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host. |
| Package: BufferedMatrix |
| Version: 1.71.1 |
| Command: /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.71.1.tar.gz |
| StartedAt: 2025-03-28 04:30:52 -0000 (Fri, 28 Mar 2025) |
| EndedAt: 2025-03-28 04:31:16 -0000 (Fri, 28 Mar 2025) |
| EllapsedTime: 24.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.71.1.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2025-02-19 r87757)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS-SP1)
* 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 ... OK
* used C compiler: ‘aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0’
* 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 loading without being on the library search path ... 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 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: 2 NOTEs
See
‘/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/R/R-devel_2025-02-19/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.71.1’
** using staged installation
** libs
using C compiler: ‘aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0’
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c init_package.c -o init_package.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -shared -L/home/biocbuild/R/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/R/R/lib -lR
installing to /home/biocbuild/R/R-devel_2025-02-19/site-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) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
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
0.353 0.052 0.392
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
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] "/home/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) max used (Mb)
Ncells 477833 25.6 1045337 55.9 639800 34.2
Vcells 884297 6.8 8388608 64.0 2080696 15.9
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Mar 28 04:31:10 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Mar 28 04:31:10 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: 0x28136e0>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Mar 28 04:31:10 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Mar 28 04:31:10 2025"
>
> ColMode(tmp2)
<pointer: 0x28136e0>
>
>
>
> ### 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,] 99.5074702 1.2946766 -0.1534697 0.9976369
[2,] 0.9591945 0.1086413 -0.8443688 -0.4648408
[3,] 1.5960916 0.6382680 2.1546444 0.2205626
[4,] 0.6067701 -0.3076759 0.1946399 0.7469850
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/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,] 99.5074702 1.2946766 0.1534697 0.9976369
[2,] 0.9591945 0.1086413 0.8443688 0.4648408
[3,] 1.5960916 0.6382680 2.1546444 0.2205626
[4,] 0.6067701 0.3076759 0.1946399 0.7469850
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/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,] 9.9753431 1.1378386 0.3917520 0.9988177
[2,] 0.9793848 0.3296078 0.9188954 0.6817923
[3,] 1.2633652 0.7989168 1.4678707 0.4696409
[4,] 0.7789545 0.5546854 0.4411801 0.8642829
>
> 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: /home/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,] 224.26090 37.67306 29.07099 35.98581
[2,] 35.75304 28.40472 35.03332 32.28276
[3,] 39.22974 33.62744 41.83335 29.91697
[4,] 33.39632 30.85453 29.60644 34.38981
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x180c4e0>
> exp(tmp5)
<pointer: 0x180c4e0>
> log(tmp5,2)
<pointer: 0x180c4e0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.7697
> Min(tmp5)
[1] 53.53502
> mean(tmp5)
[1] 72.82081
> Sum(tmp5)
[1] 14564.16
> Var(tmp5)
[1] 858.3246
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.56282 69.29237 70.51923 68.79830 72.21143 70.45546 72.88570 69.46830
[9] 72.40812 71.60639
> rowSums(tmp5)
[1] 1811.256 1385.847 1410.385 1375.966 1444.229 1409.109 1457.714 1389.366
[9] 1448.162 1432.128
> rowVars(tmp5)
[1] 7887.00962 108.95391 115.04823 48.29734 40.66893 94.40801
[7] 100.43674 58.49127 78.02633 71.57313
> rowSd(tmp5)
[1] 88.808838 10.438099 10.726054 6.949629 6.377220 9.716378 10.021813
[8] 7.647958 8.833252 8.460091
> rowMax(tmp5)
[1] 466.76968 96.24759 94.26691 80.35529 81.33170 86.04735 91.70991
[8] 82.78886 91.25023 84.05621
> rowMin(tmp5)
[1] 59.62685 57.97252 53.53502 57.41737 55.76124 53.92372 54.62939 55.52217
[9] 59.66503 54.89090
>
> colMeans(tmp5)
[1] 111.97147 67.74508 69.28386 72.15011 71.08034 74.40851 70.83901
[8] 68.96806 66.55657 67.79090 74.53614 74.28565 68.58376 72.16360
[15] 71.28503 71.80064 70.67279 69.66286 73.04510 69.58675
> colSums(tmp5)
[1] 1119.7147 677.4508 692.8386 721.5011 710.8034 744.0851 708.3901
[8] 689.6806 665.5657 677.9090 745.3614 742.8565 685.8376 721.6360
[15] 712.8503 718.0064 706.7279 696.6286 730.4510 695.8675
> colVars(tmp5)
[1] 15573.61542 54.64710 79.14348 44.70497 68.48829 135.65190
[7] 98.01574 73.83614 81.12085 104.85451 41.89786 85.77942
[13] 52.25627 131.49199 48.72713 27.33181 124.92809 80.73789
[19] 100.88907 67.80604
> colSd(tmp5)
[1] 124.794292 7.392368 8.896262 6.686177 8.275766 11.646970
[7] 9.900290 8.592796 9.006711 10.239849 6.472856 9.261718
[13] 7.228850 11.466996 6.980482 5.227984 11.177124 8.985426
[19] 10.044355 8.234442
> colMax(tmp5)
[1] 466.76968 78.41154 87.07064 85.07249 86.43376 94.26691 85.24213
[8] 80.75435 78.25857 81.89716 82.78886 83.21391 79.35262 96.24759
[15] 81.05894 79.46489 86.04735 78.88405 91.70991 85.98873
> colMin(tmp5)
[1] 62.24593 58.39180 60.13574 62.26826 59.66503 62.31939 58.06246 54.40821
[9] 54.62939 55.52217 57.97252 53.53502 55.76124 59.62685 58.94647 62.10819
[17] 54.94631 53.92372 60.62487 56.96828
>
>
> ### 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] 90.56282 69.29237 70.51923 68.79830 72.21143 70.45546 NA 69.46830
[9] 72.40812 71.60639
> rowSums(tmp5)
[1] 1811.256 1385.847 1410.385 1375.966 1444.229 1409.109 NA 1389.366
[9] 1448.162 1432.128
> rowVars(tmp5)
[1] 7887.00962 108.95391 115.04823 48.29734 40.66893 94.40801
[7] 105.44666 58.49127 78.02633 71.57313
> rowSd(tmp5)
[1] 88.808838 10.438099 10.726054 6.949629 6.377220 9.716378 10.268723
[8] 7.647958 8.833252 8.460091
> rowMax(tmp5)
[1] 466.76968 96.24759 94.26691 80.35529 81.33170 86.04735 NA
[8] 82.78886 91.25023 84.05621
> rowMin(tmp5)
[1] 59.62685 57.97252 53.53502 57.41737 55.76124 53.92372 NA 55.52217
[9] 59.66503 54.89090
>
> colMeans(tmp5)
[1] 111.97147 67.74508 69.28386 72.15011 71.08034 NA 70.83901
[8] 68.96806 66.55657 67.79090 74.53614 74.28565 68.58376 72.16360
[15] 71.28503 71.80064 70.67279 69.66286 73.04510 69.58675
> colSums(tmp5)
[1] 1119.7147 677.4508 692.8386 721.5011 710.8034 NA 708.3901
[8] 689.6806 665.5657 677.9090 745.3614 742.8565 685.8376 721.6360
[15] 712.8503 718.0064 706.7279 696.6286 730.4510 695.8675
> colVars(tmp5)
[1] 15573.61542 54.64710 79.14348 44.70497 68.48829 NA
[7] 98.01574 73.83614 81.12085 104.85451 41.89786 85.77942
[13] 52.25627 131.49199 48.72713 27.33181 124.92809 80.73789
[19] 100.88907 67.80604
> colSd(tmp5)
[1] 124.794292 7.392368 8.896262 6.686177 8.275766 NA
[7] 9.900290 8.592796 9.006711 10.239849 6.472856 9.261718
[13] 7.228850 11.466996 6.980482 5.227984 11.177124 8.985426
[19] 10.044355 8.234442
> colMax(tmp5)
[1] 466.76968 78.41154 87.07064 85.07249 86.43376 NA 85.24213
[8] 80.75435 78.25857 81.89716 82.78886 83.21391 79.35262 96.24759
[15] 81.05894 79.46489 86.04735 78.88405 91.70991 85.98873
> colMin(tmp5)
[1] 62.24593 58.39180 60.13574 62.26826 59.66503 NA 58.06246 54.40821
[9] 54.62939 55.52217 57.97252 53.53502 55.76124 59.62685 58.94647 62.10819
[17] 54.94631 53.92372 60.62487 56.96828
>
> Max(tmp5,na.rm=TRUE)
[1] 466.7697
> Min(tmp5,na.rm=TRUE)
[1] 53.53502
> mean(tmp5,na.rm=TRUE)
[1] 72.8048
> Sum(tmp5,na.rm=TRUE)
[1] 14488.16
> Var(tmp5,na.rm=TRUE)
[1] 862.608
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.56282 69.29237 70.51923 68.79830 72.21143 70.45546 72.72140 69.46830
[9] 72.40812 71.60639
> rowSums(tmp5,na.rm=TRUE)
[1] 1811.256 1385.847 1410.385 1375.966 1444.229 1409.109 1381.707 1389.366
[9] 1448.162 1432.128
> rowVars(tmp5,na.rm=TRUE)
[1] 7887.00962 108.95391 115.04823 48.29734 40.66893 94.40801
[7] 105.44666 58.49127 78.02633 71.57313
> rowSd(tmp5,na.rm=TRUE)
[1] 88.808838 10.438099 10.726054 6.949629 6.377220 9.716378 10.268723
[8] 7.647958 8.833252 8.460091
> rowMax(tmp5,na.rm=TRUE)
[1] 466.76968 96.24759 94.26691 80.35529 81.33170 86.04735 91.70991
[8] 82.78886 91.25023 84.05621
> rowMin(tmp5,na.rm=TRUE)
[1] 59.62685 57.97252 53.53502 57.41737 55.76124 53.92372 54.62939 55.52217
[9] 59.66503 54.89090
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.97147 67.74508 69.28386 72.15011 71.08034 74.23085 70.83901
[8] 68.96806 66.55657 67.79090 74.53614 74.28565 68.58376 72.16360
[15] 71.28503 71.80064 70.67279 69.66286 73.04510 69.58675
> colSums(tmp5,na.rm=TRUE)
[1] 1119.7147 677.4508 692.8386 721.5011 710.8034 668.0777 708.3901
[8] 689.6806 665.5657 677.9090 745.3614 742.8565 685.8376 721.6360
[15] 712.8503 718.0064 706.7279 696.6286 730.4510 695.8675
> colVars(tmp5,na.rm=TRUE)
[1] 15573.61542 54.64710 79.14348 44.70497 68.48829 152.25331
[7] 98.01574 73.83614 81.12085 104.85451 41.89786 85.77942
[13] 52.25627 131.49199 48.72713 27.33181 124.92809 80.73789
[19] 100.88907 67.80604
> colSd(tmp5,na.rm=TRUE)
[1] 124.794292 7.392368 8.896262 6.686177 8.275766 12.339097
[7] 9.900290 8.592796 9.006711 10.239849 6.472856 9.261718
[13] 7.228850 11.466996 6.980482 5.227984 11.177124 8.985426
[19] 10.044355 8.234442
> colMax(tmp5,na.rm=TRUE)
[1] 466.76968 78.41154 87.07064 85.07249 86.43376 94.26691 85.24213
[8] 80.75435 78.25857 81.89716 82.78886 83.21391 79.35262 96.24759
[15] 81.05894 79.46489 86.04735 78.88405 91.70991 85.98873
> colMin(tmp5,na.rm=TRUE)
[1] 62.24593 58.39180 60.13574 62.26826 59.66503 62.31939 58.06246 54.40821
[9] 54.62939 55.52217 57.97252 53.53502 55.76124 59.62685 58.94647 62.10819
[17] 54.94631 53.92372 60.62487 56.96828
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.56282 69.29237 70.51923 68.79830 72.21143 70.45546 NaN 69.46830
[9] 72.40812 71.60639
> rowSums(tmp5,na.rm=TRUE)
[1] 1811.256 1385.847 1410.385 1375.966 1444.229 1409.109 0.000 1389.366
[9] 1448.162 1432.128
> rowVars(tmp5,na.rm=TRUE)
[1] 7887.00962 108.95391 115.04823 48.29734 40.66893 94.40801
[7] NA 58.49127 78.02633 71.57313
> rowSd(tmp5,na.rm=TRUE)
[1] 88.808838 10.438099 10.726054 6.949629 6.377220 9.716378 NA
[8] 7.647958 8.833252 8.460091
> rowMax(tmp5,na.rm=TRUE)
[1] 466.76968 96.24759 94.26691 80.35529 81.33170 86.04735 NA
[8] 82.78886 91.25023 84.05621
> rowMin(tmp5,na.rm=TRUE)
[1] 59.62685 57.97252 53.53502 57.41737 55.76124 53.92372 NA 55.52217
[9] 59.66503 54.89090
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.32165 68.78433 69.09768 71.79732 69.37440 NaN 71.57458
[8] 68.18946 67.88181 66.23796 74.00478 73.63465 67.38722 72.66329
[15] 71.82777 72.02663 69.18322 70.09439 70.97123 70.98881
> colSums(tmp5,na.rm=TRUE)
[1] 1046.8949 619.0590 621.8791 646.1759 624.3696 0.0000 644.1712
[8] 613.7052 610.9363 596.1416 666.0430 662.7119 606.4850 653.9696
[15] 646.4500 648.2397 622.6489 630.8495 638.7411 638.8993
> colVars(tmp5,na.rm=TRUE)
[1] 17307.42157 49.32747 88.64646 48.89289 44.30938 NA
[7] 104.18090 76.24586 71.50294 90.83063 43.95869 91.73418
[13] 42.68159 145.11953 51.50415 30.17375 115.58224 88.73513
[19] 65.11478 54.16707
> colSd(tmp5,na.rm=TRUE)
[1] 131.557674 7.023352 9.415225 6.992345 6.656529 NA
[7] 10.206905 8.731887 8.455941 9.530510 6.630135 9.577796
[13] 6.533115 12.046557 7.176639 5.493064 10.750918 9.419933
[19] 8.069373 7.359828
> colMax(tmp5,na.rm=TRUE)
[1] 466.76968 78.41154 87.07064 85.07249 78.03491 -Inf 85.24213
[8] 80.75435 78.25857 81.89716 82.78886 83.21391 73.41505 96.24759
[15] 81.05894 79.46489 86.04735 78.88405 87.87759 85.98873
> colMin(tmp5,na.rm=TRUE)
[1] 62.24593 59.12070 60.13574 62.26826 59.66503 Inf 58.06246 54.40821
[9] 57.44392 55.52217 57.97252 53.53502 55.76124 59.62685 58.94647 62.10819
[17] 54.94631 53.92372 60.62487 60.04267
>
>
>
>
> 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] 196.0488 234.1884 118.2677 137.8794 232.6211 186.8331 176.0087 346.6000
[9] 163.2370 162.0297
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 196.0488 234.1884 118.2677 137.8794 232.6211 186.8331 176.0087 346.6000
[9] 163.2370 162.0297
>
>
>
> 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 0.000000e+00 -5.684342e-14 5.684342e-14 1.136868e-13
[6] 2.842171e-14 5.684342e-14 -1.136868e-13 -4.263256e-14 2.273737e-13
[11] 4.547474e-13 5.684342e-14 5.684342e-14 2.842171e-14 1.136868e-13
[16] -1.705303e-13 -2.842171e-14 1.136868e-13 -1.421085e-13 -1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
5 15
3 8
9 7
3 5
5 18
6 12
6 8
5 12
4 13
7 2
9 5
10 2
6 13
1 16
5 1
7 19
7 14
10 18
2 19
10 7
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] 1.746857
> Min(tmp)
[1] -2.353924
> mean(tmp)
[1] -0.0653567
> Sum(tmp)
[1] -6.53567
> Var(tmp)
[1] 0.82996
>
> rowMeans(tmp)
[1] -0.0653567
> rowSums(tmp)
[1] -6.53567
> rowVars(tmp)
[1] 0.82996
> rowSd(tmp)
[1] 0.9110214
> rowMax(tmp)
[1] 1.746857
> rowMin(tmp)
[1] -2.353924
>
> colMeans(tmp)
[1] -0.78180899 -1.26825836 0.67447426 -0.08065411 -0.97686078 -0.03780090
[7] -0.64386885 -1.55140177 1.50082697 0.37386960 -2.31689485 -0.70813700
[13] 0.35874954 -0.48185890 1.12585271 0.33481474 0.49495730 0.47457062
[19] -1.03887386 0.07589607 -0.48886014 0.39536320 1.12928117 -0.57659029
[25] 1.74685744 1.44406956 0.33744551 -0.04140227 -0.60497473 -0.16533261
[31] -0.74594225 -0.39452393 -1.01471636 -0.25535472 -0.87582421 -0.06078151
[37] -0.72828661 0.40599826 -0.80503555 -0.66631718 -0.29403269 0.11215911
[43] -0.25176948 -0.36674791 -0.44083423 0.98273460 0.16407796 1.50770014
[49] 1.22528391 0.05001593 0.46232834 0.27919353 0.88808139 1.19929684
[55] 0.30362483 -1.02105224 -1.32971333 -0.44909234 -0.81930117 1.49298377
[61] 1.17264062 -0.31340836 -0.34935713 0.99294016 1.62108195 1.63786686
[67] -0.40642834 -0.78009755 -0.42716691 -0.34647432 -1.09650797 -0.84597419
[73] -0.75205296 -0.24191472 -0.33344816 -2.35392432 -0.36204049 -1.07840014
[79] -1.38879280 1.55276965 -0.14101667 -1.29895698 -1.61448946 -0.58456520
[85] 1.10362798 -0.31475749 -0.27385619 0.33489255 1.38720736 1.45588702
[91] 0.44220812 0.62159489 -0.30550849 0.88742823 -0.57238625 0.54130649
[97] 0.02270562 -1.88881276 0.27827254 0.22463506
> colSums(tmp)
[1] -0.78180899 -1.26825836 0.67447426 -0.08065411 -0.97686078 -0.03780090
[7] -0.64386885 -1.55140177 1.50082697 0.37386960 -2.31689485 -0.70813700
[13] 0.35874954 -0.48185890 1.12585271 0.33481474 0.49495730 0.47457062
[19] -1.03887386 0.07589607 -0.48886014 0.39536320 1.12928117 -0.57659029
[25] 1.74685744 1.44406956 0.33744551 -0.04140227 -0.60497473 -0.16533261
[31] -0.74594225 -0.39452393 -1.01471636 -0.25535472 -0.87582421 -0.06078151
[37] -0.72828661 0.40599826 -0.80503555 -0.66631718 -0.29403269 0.11215911
[43] -0.25176948 -0.36674791 -0.44083423 0.98273460 0.16407796 1.50770014
[49] 1.22528391 0.05001593 0.46232834 0.27919353 0.88808139 1.19929684
[55] 0.30362483 -1.02105224 -1.32971333 -0.44909234 -0.81930117 1.49298377
[61] 1.17264062 -0.31340836 -0.34935713 0.99294016 1.62108195 1.63786686
[67] -0.40642834 -0.78009755 -0.42716691 -0.34647432 -1.09650797 -0.84597419
[73] -0.75205296 -0.24191472 -0.33344816 -2.35392432 -0.36204049 -1.07840014
[79] -1.38879280 1.55276965 -0.14101667 -1.29895698 -1.61448946 -0.58456520
[85] 1.10362798 -0.31475749 -0.27385619 0.33489255 1.38720736 1.45588702
[91] 0.44220812 0.62159489 -0.30550849 0.88742823 -0.57238625 0.54130649
[97] 0.02270562 -1.88881276 0.27827254 0.22463506
> 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] -0.78180899 -1.26825836 0.67447426 -0.08065411 -0.97686078 -0.03780090
[7] -0.64386885 -1.55140177 1.50082697 0.37386960 -2.31689485 -0.70813700
[13] 0.35874954 -0.48185890 1.12585271 0.33481474 0.49495730 0.47457062
[19] -1.03887386 0.07589607 -0.48886014 0.39536320 1.12928117 -0.57659029
[25] 1.74685744 1.44406956 0.33744551 -0.04140227 -0.60497473 -0.16533261
[31] -0.74594225 -0.39452393 -1.01471636 -0.25535472 -0.87582421 -0.06078151
[37] -0.72828661 0.40599826 -0.80503555 -0.66631718 -0.29403269 0.11215911
[43] -0.25176948 -0.36674791 -0.44083423 0.98273460 0.16407796 1.50770014
[49] 1.22528391 0.05001593 0.46232834 0.27919353 0.88808139 1.19929684
[55] 0.30362483 -1.02105224 -1.32971333 -0.44909234 -0.81930117 1.49298377
[61] 1.17264062 -0.31340836 -0.34935713 0.99294016 1.62108195 1.63786686
[67] -0.40642834 -0.78009755 -0.42716691 -0.34647432 -1.09650797 -0.84597419
[73] -0.75205296 -0.24191472 -0.33344816 -2.35392432 -0.36204049 -1.07840014
[79] -1.38879280 1.55276965 -0.14101667 -1.29895698 -1.61448946 -0.58456520
[85] 1.10362798 -0.31475749 -0.27385619 0.33489255 1.38720736 1.45588702
[91] 0.44220812 0.62159489 -0.30550849 0.88742823 -0.57238625 0.54130649
[97] 0.02270562 -1.88881276 0.27827254 0.22463506
> colMin(tmp)
[1] -0.78180899 -1.26825836 0.67447426 -0.08065411 -0.97686078 -0.03780090
[7] -0.64386885 -1.55140177 1.50082697 0.37386960 -2.31689485 -0.70813700
[13] 0.35874954 -0.48185890 1.12585271 0.33481474 0.49495730 0.47457062
[19] -1.03887386 0.07589607 -0.48886014 0.39536320 1.12928117 -0.57659029
[25] 1.74685744 1.44406956 0.33744551 -0.04140227 -0.60497473 -0.16533261
[31] -0.74594225 -0.39452393 -1.01471636 -0.25535472 -0.87582421 -0.06078151
[37] -0.72828661 0.40599826 -0.80503555 -0.66631718 -0.29403269 0.11215911
[43] -0.25176948 -0.36674791 -0.44083423 0.98273460 0.16407796 1.50770014
[49] 1.22528391 0.05001593 0.46232834 0.27919353 0.88808139 1.19929684
[55] 0.30362483 -1.02105224 -1.32971333 -0.44909234 -0.81930117 1.49298377
[61] 1.17264062 -0.31340836 -0.34935713 0.99294016 1.62108195 1.63786686
[67] -0.40642834 -0.78009755 -0.42716691 -0.34647432 -1.09650797 -0.84597419
[73] -0.75205296 -0.24191472 -0.33344816 -2.35392432 -0.36204049 -1.07840014
[79] -1.38879280 1.55276965 -0.14101667 -1.29895698 -1.61448946 -0.58456520
[85] 1.10362798 -0.31475749 -0.27385619 0.33489255 1.38720736 1.45588702
[91] 0.44220812 0.62159489 -0.30550849 0.88742823 -0.57238625 0.54130649
[97] 0.02270562 -1.88881276 0.27827254 0.22463506
> colMedians(tmp)
[1] -0.78180899 -1.26825836 0.67447426 -0.08065411 -0.97686078 -0.03780090
[7] -0.64386885 -1.55140177 1.50082697 0.37386960 -2.31689485 -0.70813700
[13] 0.35874954 -0.48185890 1.12585271 0.33481474 0.49495730 0.47457062
[19] -1.03887386 0.07589607 -0.48886014 0.39536320 1.12928117 -0.57659029
[25] 1.74685744 1.44406956 0.33744551 -0.04140227 -0.60497473 -0.16533261
[31] -0.74594225 -0.39452393 -1.01471636 -0.25535472 -0.87582421 -0.06078151
[37] -0.72828661 0.40599826 -0.80503555 -0.66631718 -0.29403269 0.11215911
[43] -0.25176948 -0.36674791 -0.44083423 0.98273460 0.16407796 1.50770014
[49] 1.22528391 0.05001593 0.46232834 0.27919353 0.88808139 1.19929684
[55] 0.30362483 -1.02105224 -1.32971333 -0.44909234 -0.81930117 1.49298377
[61] 1.17264062 -0.31340836 -0.34935713 0.99294016 1.62108195 1.63786686
[67] -0.40642834 -0.78009755 -0.42716691 -0.34647432 -1.09650797 -0.84597419
[73] -0.75205296 -0.24191472 -0.33344816 -2.35392432 -0.36204049 -1.07840014
[79] -1.38879280 1.55276965 -0.14101667 -1.29895698 -1.61448946 -0.58456520
[85] 1.10362798 -0.31475749 -0.27385619 0.33489255 1.38720736 1.45588702
[91] 0.44220812 0.62159489 -0.30550849 0.88742823 -0.57238625 0.54130649
[97] 0.02270562 -1.88881276 0.27827254 0.22463506
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.781809 -1.268258 0.6744743 -0.08065411 -0.9768608 -0.0378009 -0.6438689
[2,] -0.781809 -1.268258 0.6744743 -0.08065411 -0.9768608 -0.0378009 -0.6438689
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.551402 1.500827 0.3738696 -2.316895 -0.708137 0.3587495 -0.4818589
[2,] -1.551402 1.500827 0.3738696 -2.316895 -0.708137 0.3587495 -0.4818589
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.125853 0.3348147 0.4949573 0.4745706 -1.038874 0.07589607 -0.4888601
[2,] 1.125853 0.3348147 0.4949573 0.4745706 -1.038874 0.07589607 -0.4888601
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.3953632 1.129281 -0.5765903 1.746857 1.44407 0.3374455 -0.04140227
[2,] 0.3953632 1.129281 -0.5765903 1.746857 1.44407 0.3374455 -0.04140227
[,29] [,30] [,31] [,32] [,33] [,34]
[1,] -0.6049747 -0.1653326 -0.7459422 -0.3945239 -1.014716 -0.2553547
[2,] -0.6049747 -0.1653326 -0.7459422 -0.3945239 -1.014716 -0.2553547
[,35] [,36] [,37] [,38] [,39] [,40]
[1,] -0.8758242 -0.06078151 -0.7282866 0.4059983 -0.8050356 -0.6663172
[2,] -0.8758242 -0.06078151 -0.7282866 0.4059983 -0.8050356 -0.6663172
[,41] [,42] [,43] [,44] [,45] [,46] [,47]
[1,] -0.2940327 0.1121591 -0.2517695 -0.3667479 -0.4408342 0.9827346 0.164078
[2,] -0.2940327 0.1121591 -0.2517695 -0.3667479 -0.4408342 0.9827346 0.164078
[,48] [,49] [,50] [,51] [,52] [,53] [,54]
[1,] 1.5077 1.225284 0.05001593 0.4623283 0.2791935 0.8880814 1.199297
[2,] 1.5077 1.225284 0.05001593 0.4623283 0.2791935 0.8880814 1.199297
[,55] [,56] [,57] [,58] [,59] [,60] [,61]
[1,] 0.3036248 -1.021052 -1.329713 -0.4490923 -0.8193012 1.492984 1.172641
[2,] 0.3036248 -1.021052 -1.329713 -0.4490923 -0.8193012 1.492984 1.172641
[,62] [,63] [,64] [,65] [,66] [,67] [,68]
[1,] -0.3134084 -0.3493571 0.9929402 1.621082 1.637867 -0.4064283 -0.7800975
[2,] -0.3134084 -0.3493571 0.9929402 1.621082 1.637867 -0.4064283 -0.7800975
[,69] [,70] [,71] [,72] [,73] [,74] [,75]
[1,] -0.4271669 -0.3464743 -1.096508 -0.8459742 -0.752053 -0.2419147 -0.3334482
[2,] -0.4271669 -0.3464743 -1.096508 -0.8459742 -0.752053 -0.2419147 -0.3334482
[,76] [,77] [,78] [,79] [,80] [,81] [,82]
[1,] -2.353924 -0.3620405 -1.0784 -1.388793 1.55277 -0.1410167 -1.298957
[2,] -2.353924 -0.3620405 -1.0784 -1.388793 1.55277 -0.1410167 -1.298957
[,83] [,84] [,85] [,86] [,87] [,88] [,89]
[1,] -1.614489 -0.5845652 1.103628 -0.3147575 -0.2738562 0.3348926 1.387207
[2,] -1.614489 -0.5845652 1.103628 -0.3147575 -0.2738562 0.3348926 1.387207
[,90] [,91] [,92] [,93] [,94] [,95] [,96]
[1,] 1.455887 0.4422081 0.6215949 -0.3055085 0.8874282 -0.5723863 0.5413065
[2,] 1.455887 0.4422081 0.6215949 -0.3055085 0.8874282 -0.5723863 0.5413065
[,97] [,98] [,99] [,100]
[1,] 0.02270562 -1.888813 0.2782725 0.2246351
[2,] 0.02270562 -1.888813 0.2782725 0.2246351
>
>
> Max(tmp2)
[1] 2.34429
> Min(tmp2)
[1] -2.207282
> mean(tmp2)
[1] -0.1612384
> Sum(tmp2)
[1] -16.12384
> Var(tmp2)
[1] 0.9571995
>
> rowMeans(tmp2)
[1] -1.29796036 -0.19825260 0.24999891 -2.20728225 1.09798806 -1.95729807
[7] -1.99091785 -0.73367054 -1.33141788 1.00086322 0.64817720 -2.03167358
[13] 0.73016687 0.53745381 -0.98574560 -0.49210752 0.01075759 0.51876162
[19] -1.10194869 -1.20532341 1.36226482 0.07716515 -0.30993786 -0.07715123
[25] -1.39804215 -1.76487565 0.48608865 -1.45008854 -1.79989493 1.21966748
[31] -0.44817695 -0.76631814 -0.16895672 -0.97082993 0.05188504 1.16825299
[37] -0.34584920 -1.57974146 0.55305616 -0.81036385 -0.47732026 0.23703729
[43] -1.26237802 -0.37691252 1.31986327 0.56267300 0.09808044 -0.63988221
[49] 0.62633129 -0.32032228 -1.43335473 1.06192067 -0.28875195 -0.26686334
[55] -0.27273017 -0.96211094 -0.08595296 0.76391704 -0.09174948 -0.06075078
[61] -1.67979706 -1.18162192 -0.60269059 0.80762114 0.58944814 0.55044529
[67] 0.01430080 -1.13544585 1.03843242 -1.61539232 1.04358298 0.51813002
[73] 1.92611848 0.12357417 1.35020609 -0.65474661 0.68667414 -1.55248707
[79] -0.15245109 -0.39085973 1.49060480 -0.16206020 -1.90202412 -0.99608427
[85] -0.27844386 0.92178647 0.53432290 0.19613169 0.40883497 0.19045167
[91] -0.31346615 0.61187895 -0.29772191 -0.47550817 -0.14260841 -0.48823873
[97] 1.27781509 0.30448831 0.54920758 2.34429033
> rowSums(tmp2)
[1] -1.29796036 -0.19825260 0.24999891 -2.20728225 1.09798806 -1.95729807
[7] -1.99091785 -0.73367054 -1.33141788 1.00086322 0.64817720 -2.03167358
[13] 0.73016687 0.53745381 -0.98574560 -0.49210752 0.01075759 0.51876162
[19] -1.10194869 -1.20532341 1.36226482 0.07716515 -0.30993786 -0.07715123
[25] -1.39804215 -1.76487565 0.48608865 -1.45008854 -1.79989493 1.21966748
[31] -0.44817695 -0.76631814 -0.16895672 -0.97082993 0.05188504 1.16825299
[37] -0.34584920 -1.57974146 0.55305616 -0.81036385 -0.47732026 0.23703729
[43] -1.26237802 -0.37691252 1.31986327 0.56267300 0.09808044 -0.63988221
[49] 0.62633129 -0.32032228 -1.43335473 1.06192067 -0.28875195 -0.26686334
[55] -0.27273017 -0.96211094 -0.08595296 0.76391704 -0.09174948 -0.06075078
[61] -1.67979706 -1.18162192 -0.60269059 0.80762114 0.58944814 0.55044529
[67] 0.01430080 -1.13544585 1.03843242 -1.61539232 1.04358298 0.51813002
[73] 1.92611848 0.12357417 1.35020609 -0.65474661 0.68667414 -1.55248707
[79] -0.15245109 -0.39085973 1.49060480 -0.16206020 -1.90202412 -0.99608427
[85] -0.27844386 0.92178647 0.53432290 0.19613169 0.40883497 0.19045167
[91] -0.31346615 0.61187895 -0.29772191 -0.47550817 -0.14260841 -0.48823873
[97] 1.27781509 0.30448831 0.54920758 2.34429033
> 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] -1.29796036 -0.19825260 0.24999891 -2.20728225 1.09798806 -1.95729807
[7] -1.99091785 -0.73367054 -1.33141788 1.00086322 0.64817720 -2.03167358
[13] 0.73016687 0.53745381 -0.98574560 -0.49210752 0.01075759 0.51876162
[19] -1.10194869 -1.20532341 1.36226482 0.07716515 -0.30993786 -0.07715123
[25] -1.39804215 -1.76487565 0.48608865 -1.45008854 -1.79989493 1.21966748
[31] -0.44817695 -0.76631814 -0.16895672 -0.97082993 0.05188504 1.16825299
[37] -0.34584920 -1.57974146 0.55305616 -0.81036385 -0.47732026 0.23703729
[43] -1.26237802 -0.37691252 1.31986327 0.56267300 0.09808044 -0.63988221
[49] 0.62633129 -0.32032228 -1.43335473 1.06192067 -0.28875195 -0.26686334
[55] -0.27273017 -0.96211094 -0.08595296 0.76391704 -0.09174948 -0.06075078
[61] -1.67979706 -1.18162192 -0.60269059 0.80762114 0.58944814 0.55044529
[67] 0.01430080 -1.13544585 1.03843242 -1.61539232 1.04358298 0.51813002
[73] 1.92611848 0.12357417 1.35020609 -0.65474661 0.68667414 -1.55248707
[79] -0.15245109 -0.39085973 1.49060480 -0.16206020 -1.90202412 -0.99608427
[85] -0.27844386 0.92178647 0.53432290 0.19613169 0.40883497 0.19045167
[91] -0.31346615 0.61187895 -0.29772191 -0.47550817 -0.14260841 -0.48823873
[97] 1.27781509 0.30448831 0.54920758 2.34429033
> rowMin(tmp2)
[1] -1.29796036 -0.19825260 0.24999891 -2.20728225 1.09798806 -1.95729807
[7] -1.99091785 -0.73367054 -1.33141788 1.00086322 0.64817720 -2.03167358
[13] 0.73016687 0.53745381 -0.98574560 -0.49210752 0.01075759 0.51876162
[19] -1.10194869 -1.20532341 1.36226482 0.07716515 -0.30993786 -0.07715123
[25] -1.39804215 -1.76487565 0.48608865 -1.45008854 -1.79989493 1.21966748
[31] -0.44817695 -0.76631814 -0.16895672 -0.97082993 0.05188504 1.16825299
[37] -0.34584920 -1.57974146 0.55305616 -0.81036385 -0.47732026 0.23703729
[43] -1.26237802 -0.37691252 1.31986327 0.56267300 0.09808044 -0.63988221
[49] 0.62633129 -0.32032228 -1.43335473 1.06192067 -0.28875195 -0.26686334
[55] -0.27273017 -0.96211094 -0.08595296 0.76391704 -0.09174948 -0.06075078
[61] -1.67979706 -1.18162192 -0.60269059 0.80762114 0.58944814 0.55044529
[67] 0.01430080 -1.13544585 1.03843242 -1.61539232 1.04358298 0.51813002
[73] 1.92611848 0.12357417 1.35020609 -0.65474661 0.68667414 -1.55248707
[79] -0.15245109 -0.39085973 1.49060480 -0.16206020 -1.90202412 -0.99608427
[85] -0.27844386 0.92178647 0.53432290 0.19613169 0.40883497 0.19045167
[91] -0.31346615 0.61187895 -0.29772191 -0.47550817 -0.14260841 -0.48823873
[97] 1.27781509 0.30448831 0.54920758 2.34429033
>
> colMeans(tmp2)
[1] -0.1612384
> colSums(tmp2)
[1] -16.12384
> colVars(tmp2)
[1] 0.9571995
> colSd(tmp2)
[1] 0.9783657
> colMax(tmp2)
[1] 2.34429
> colMin(tmp2)
[1] -2.207282
> colMedians(tmp2)
[1] -0.1572556
> colRanges(tmp2)
[,1]
[1,] -2.207282
[2,] 2.344290
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.0389112 1.0023776 -5.3167101 -0.3958729 2.8985088 -1.7185941
[7] -1.6181566 -0.6704035 0.5289618 -1.8265984
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.6670842
[2,] -0.1969868
[3,] 0.1782085
[4,] 0.5579388
[5,] 1.2355374
>
> rowApply(tmp,sum)
[1] 3.69392057 -5.89332183 -5.75595180 1.45733096 6.58542065 3.25597757
[7] -8.40946634 -3.35778402 2.43624076 -0.08994273
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 4 7 8 4 5 5 2 9 9 5
[2,] 5 10 1 9 4 7 4 6 2 10
[3,] 7 2 4 3 7 3 3 3 5 2
[4,] 6 4 7 7 1 6 8 5 7 6
[5,] 8 9 2 5 3 10 9 7 8 3
[6,] 1 1 5 2 9 9 5 4 10 9
[7,] 3 5 10 1 10 2 6 8 1 4
[8,] 2 6 3 6 8 8 10 1 6 8
[9,] 9 3 9 8 6 1 7 10 4 1
[10,] 10 8 6 10 2 4 1 2 3 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.3491800 -1.8343836 2.3303888 -0.4097500 2.2916784 -1.1906291
[7] 2.0319594 -0.1046019 3.6590181 1.2264286 3.1005248 -0.3996460
[13] 4.7970339 0.1659387 -2.6799833 -1.6899013 -1.0639483 1.9065909
[19] -1.3467919 4.8283540
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5712979
[2,] -0.5666385
[3,] -0.4792854
[4,] -0.3641232
[5,] 0.6321651
>
> rowApply(tmp,sum)
[1] 1.348827 8.847455 -7.202910 8.158997 2.116732
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 7 5 4 12 5
[2,] 8 8 1 10 16
[3,] 14 9 13 11 19
[4,] 4 13 8 17 7
[5,] 19 20 3 14 2
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.3641232 -0.34671772 0.5936427 -0.8006543 1.3520100 1.1927075
[2,] -0.5666385 -0.07819687 0.2315443 0.5810665 2.7147951 -0.9467260
[3,] -1.5712979 -2.91493331 -0.1156314 -0.9507397 -1.5819956 -0.5309660
[4,] 0.6321651 0.55492962 0.6039177 1.2073629 0.7757279 -0.2041561
[5,] -0.4792854 0.95053469 1.0169154 -0.4467854 -0.9688591 -0.7014885
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.3452988 0.02946341 -0.6699703 -1.4018333 0.6609949 -0.1910475
[2,] 1.3693786 0.41819651 0.8691388 1.4760326 1.0286731 -0.5809764
[3,] -2.3440067 -0.26046782 1.7061856 -0.4327260 2.0260313 0.7292868
[4,] 0.6622846 -0.33561499 1.4940841 0.9192637 -0.1518544 0.9403916
[5,] 0.9990041 0.04382101 0.2595799 0.6656915 -0.4633201 -1.2973004
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.0365039 -0.4877541 -1.133396377 -0.96413602 -0.2641527 0.4700294
[2,] 0.4858493 -0.7266012 -0.333519574 0.45517548 1.3987200 -0.4909978
[3,] 1.1449504 0.5230756 -1.056341801 -1.20336597 -1.0833278 0.1077458
[4,] 1.4235713 -0.4500086 -0.161029689 0.03468008 -0.5587206 1.3006195
[5,] 0.7061591 1.3072270 0.004304123 -0.01225484 -0.5564673 0.5191940
[,19] [,20]
[1,] -0.2296611 1.5216225
[2,] -1.0615058 2.6040466
[3,] -0.1602086 0.7658235
[4,] -0.8579210 0.3293043
[5,] 0.9625047 -0.3924428
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/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: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 652 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/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 2.242222 0.4009498 0.02442665 -0.7051772 -0.1009103 0.8743298 -1.278914
col8 col9 col10 col11 col12 col13 col14
row1 0.4171238 -1.646187 1.539191 1.286413 -0.1145848 0.4814396 1.591384
col15 col16 col17 col18 col19 col20
row1 0.8090059 -0.2482203 -0.1342766 -0.915639 0.0461342 1.703802
> tmp[,"col10"]
col10
row1 1.5391909
row2 0.7649891
row3 -0.6663766
row4 -1.1286331
row5 -0.1143825
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 2.2422216 0.4009498 0.02442665 -0.7051772 -0.1009103 0.8743298
row5 0.7066856 0.8750101 -0.34831438 -0.2900750 0.6835973 -1.2920288
col7 col8 col9 col10 col11 col12 col13
row1 -1.27891428 0.4171238 -1.646187 1.5391909 1.286413 -0.1145848 0.4814396
row5 -0.04786267 0.4244440 -1.248698 -0.1143825 -2.244809 0.9350047 -1.5518590
col14 col15 col16 col17 col18 col19 col20
row1 1.591384 0.8090059 -0.2482203 -0.1342766 -0.915639 0.0461342 1.703802
row5 -1.111937 -0.3052777 -0.2323300 -0.8548760 1.412721 1.1081050 -1.516491
> tmp[,c("col6","col20")]
col6 col20
row1 0.8743298 1.7038019
row2 0.1230633 -0.6548127
row3 1.1574291 -2.4415148
row4 0.4795266 -0.7441637
row5 -1.2920288 -1.5164913
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.8743298 1.703802
row5 -1.2920288 -1.516491
>
>
>
>
> 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 50.24095 48.76179 50.61866 48.35056 49.36155 104.9595 48.31415 49.54039
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.06206 49.92254 48.79796 48.73059 50.05179 49.34338 52.11327 49.2206
col17 col18 col19 col20
row1 50.52892 51.58825 50.99183 104.5402
> tmp[,"col10"]
col10
row1 49.92254
row2 28.77239
row3 30.72906
row4 30.53814
row5 49.69802
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.24095 48.76179 50.61866 48.35056 49.36155 104.9595 48.31415 49.54039
row5 51.34970 49.63443 49.11859 51.86870 49.64918 104.7023 50.44162 50.79628
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.06206 49.92254 48.79796 48.73059 50.05179 49.34338 52.11327 49.22060
row5 51.12799 49.69802 51.04453 49.36829 49.86726 49.73228 50.11109 49.50051
col17 col18 col19 col20
row1 50.52892 51.58825 50.99183 104.5402
row5 50.07756 51.62270 48.27144 105.7684
> tmp[,c("col6","col20")]
col6 col20
row1 104.95945 104.54024
row2 75.39034 76.84891
row3 73.45917 74.71909
row4 74.50660 74.44553
row5 104.70231 105.76835
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.9595 104.5402
row5 104.7023 105.7684
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.9595 104.5402
row5 104.7023 105.7684
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.1335190
[2,] 1.8229274
[3,] 0.2403840
[4,] 0.1734375
[5,] 0.8477074
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.7084536 -2.3565059
[2,] -0.2217210 0.5967957
[3,] 0.5853794 -0.3372339
[4,] -1.8087020 -2.2044986
[5,] -0.8101447 -0.6121464
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.01379178 1.1731023
[2,] 0.13954384 -0.1505601
[3,] 1.04821847 -0.2072465
[4,] 1.28877366 0.8978760
[5,] 0.19185428 -0.1064666
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.01379178
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.01379178
[2,] 0.13954384
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 1.392831 0.4937815 0.8578545 0.5565284 1.4036549 -0.7503421 0.5469572
row1 -1.045326 0.1011518 -1.1845430 2.1914982 0.5464501 0.9494989 -1.0408628
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -1.6553783 -0.6224674 0.4292276 0.3641328 -1.207414 0.1735822 0.02564672
row1 -0.9790685 1.0434048 2.3164679 1.3653541 2.112212 2.3253797 1.58752517
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -2.0495596 -0.2195161 -1.329444 0.9353875 -0.1812689 0.7193354
row1 -0.9136442 2.0158410 -0.455501 0.8004515 2.4657792 -0.8861184
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.3751644 0.01928681 -1.949616 -0.3002921 -0.4751405 -1.503794 -0.2067662
[,8] [,9] [,10]
row2 -1.026393 -1.42328 0.7380038
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.1780594 -2.31235 -0.07742219 0.7721294 -1.010932 -1.371826 0.9629467
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.6773854 0.2578559 0.1093758 -0.4904603 -0.8524382 1.33407 -0.7912619
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.01724977 1.10603 -1.45682 0.1710232 0.9338264 1.061751
>
>
> 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: 0x1cefdb0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f86e4731d446f"
[2] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f86e46a131b34"
[3] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f86e4793530e0"
[4] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f86e42dc1fea4"
[5] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f86e4109ce5cb"
[6] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f86e42c0d67f7"
[7] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f86e4307f5711"
[8] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f86e42898b600"
[9] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f86e43a78c257"
[10] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f86e46e65e79"
[11] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f86e45e8f9885"
[12] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f86e4c1262c5"
[13] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f86e45246fe71"
[14] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f86e44fc3f8a9"
[15] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM2f86e4d5bbb77"
>
>
> ### 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: 0x3a09260>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x3a09260>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x3a09260>
> rowMedians(tmp)
[1] 0.059785302 0.244753393 -0.171241427 -0.149913852 -0.341217668
[6] 0.171845495 -0.266773993 0.133876784 -0.202994382 0.269435183
[11] -0.474967734 0.395774300 -0.545249184 -0.017079444 0.116351483
[16] -0.156017656 0.266245550 -0.362655184 -0.098808927 0.781736272
[21] -0.133938411 0.079397286 -0.061378577 0.011890332 0.084268345
[26] -0.426770124 0.230623595 -0.072546824 0.613455053 0.135066373
[31] -0.005674510 -0.145408039 -0.344522153 -0.498562253 0.411318811
[36] -0.207658715 0.132221568 0.160607801 -0.089068042 0.313778157
[41] 0.085793530 -0.003805837 0.095713593 0.160077481 0.072983360
[46] 0.297798819 -0.094321820 0.194571539 0.396501101 0.135030173
[51] 0.491445049 -0.442753708 -0.035677720 0.429090968 -0.220005659
[56] -0.347088438 0.193432546 -0.384131619 0.342077342 0.232349371
[61] 0.057594395 0.433358964 -0.064281114 -0.415248788 -0.363014053
[66] 0.368871009 0.614143502 0.623994270 0.279637122 0.368843963
[71] 0.019480594 -0.347869900 -0.092053089 0.397164143 -0.162413230
[76] -0.252781755 -0.249686872 -0.215698079 0.283570496 0.001275459
[81] 0.320253768 -0.199568374 0.060085420 0.292605279 -0.245019876
[86] -0.131042556 -0.153996899 0.354694946 -0.601517792 0.024519438
[91] -0.240806371 -0.272690353 -0.536456593 -0.076266779 0.318461451
[96] 0.268296931 0.534517259 0.234157762 -0.564439542 0.103975900
[101] 0.248776655 0.770322307 0.180940802 -0.288960951 -0.146479600
[106] -0.158614580 0.356064735 -0.762151724 -0.328316904 0.140745812
[111] 0.083101467 0.278680736 0.546349208 -0.069556633 0.336880346
[116] -0.137757140 0.159859028 -0.007498644 -0.500081399 -0.006059229
[121] 0.209416619 -0.291831721 -0.198362634 0.203046118 0.139483182
[126] -0.044037918 0.027373688 0.164232504 0.682708571 0.371207924
[131] -0.112688723 0.087689024 -0.006583630 -0.624012775 0.213306076
[136] -0.058536904 -0.274240737 0.185868621 -0.266291336 0.484431141
[141] -0.435310665 -0.146497535 -0.008351043 -0.271359228 -0.035121816
[146] 0.272719132 -0.433826444 -0.337082226 0.482472630 0.255399047
[151] 0.524431216 -0.374428657 -0.422468895 0.140678252 -0.385830526
[156] -0.408817261 -0.146601922 0.281076319 -0.378862428 0.197842189
[161] -0.008612297 0.174651256 -0.233624436 -0.311114926 -0.364654338
[166] -0.098454025 -0.212965833 -0.064703926 -0.073414804 0.206426888
[171] -0.157491521 0.149060907 -0.423467886 -0.873086676 0.083062300
[176] 0.099392060 -0.334943717 0.078229064 0.636047390 0.017444157
[181] -0.302002407 -0.219252818 -0.441998282 0.134217963 0.023255251
[186] -0.045605407 -0.030412809 -0.555256758 0.178257981 -0.493740575
[191] 0.310156125 -0.281965386 -0.100862842 0.108133808 0.400405742
[196] -0.079978726 0.357057872 0.308887650 -0.269557003 -0.382903770
[201] -0.054687934 -0.534797921 -0.116305717 0.240538329 -0.560767059
[206] -0.081808771 0.161659017 0.316391951 0.294803200 -0.010101499
[211] 0.020989969 0.203167169 0.149529118 -0.136864083 0.664068352
[216] -0.138124002 -0.007300635 -0.006091282 0.063058185 -0.143219556
[221] 0.408766646 0.561271350 0.040268950 -0.671903624 0.124636362
[226] -0.990085150 -0.117058180 0.149006568 -0.593179217 -0.010752609
>
> proc.time()
user system elapsed
1.829 0.925 2.779
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
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: 0x3c016e0>
> .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: 0x3c016e0>
> .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: 0x3c016e0>
> .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: 0x3c016e0>
> 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: 0x3c496a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3c496a0>
> .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: 0x3c496a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3c496a0>
> .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: 0x3c496a0>
> 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: 0x2e057d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2e057d0>
> .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: 0x2e057d0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x2e057d0>
> .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: 0x2e057d0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x2e057d0>
> .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: 0x2e057d0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x2e057d0>
> .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: 0x2e057d0>
> 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: 0x3964d70>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x3964d70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3964d70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3964d70>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2f878c6cb15898" "BufferedMatrixFile2f878c713b51a0"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2f878c6cb15898" "BufferedMatrixFile2f878c713b51a0"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x3507cd0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3507cd0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x3507cd0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x3507cd0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x3507cd0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x3507cd0>
> .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: 0x2476a10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2476a10>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x2476a10>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x2476a10>
> 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: 0x4390c70>
> .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: 0x4390c70>
> rm(P)
>
> proc.time()
user system elapsed
0.361 0.044 0.391
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
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Platform: aarch64-unknown-linux-gnu
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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
0.344 0.040 0.369