Ben Bolstad
| Snapshot Date: 2025-02-03 13:00 -0500 (Mon, 03 Feb 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_20 |
| git_last_commit: 32b6f6a |
| git_last_commit_date: 2024-10-29 09:27:20 -0500 (Tue, 29 Oct 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2025-02-06 12:04 -0500 (Thu, 06 Feb 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4753 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves" | 4501 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4524 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4476 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4407 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 251/2289 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.70.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.70.0 |
| Command: /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings BufferedMatrix_1.70.0.tar.gz |
| StartedAt: 2025-02-03 20:37:17 -0500 (Mon, 03 Feb 2025) |
| EndedAt: 2025-02-03 20:37:40 -0500 (Mon, 03 Feb 2025) |
| EllapsedTime: 23.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings BufferedMatrix_1.70.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.2 (2024-10-31)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.2.0-23ubuntu4) 13.2.0
GNU Fortran (Ubuntu 13.2.0-23ubuntu4) 13.2.0
* running under: Ubuntu 24.04.1 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.70.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
* 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 re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.20-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
gcc -I"/home/biocbuild/bbs-3.20-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.20-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -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){
| ^~~~~~~~~~~
gcc -I"/home/biocbuild/bbs-3.20-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"/home/biocbuild/bbs-3.20-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c init_package.c -o init_package.o
gcc -shared -L/home/biocbuild/bbs-3.20-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.20-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.20-bioc/R/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 version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-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
0.233 0.044 0.265
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-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-3.20-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 471792 25.2 1026261 54.9 643431 34.4
Vcells 871947 6.7 8388608 64.0 2046621 15.7
>
>
>
>
> ##
> ## 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] "Mon Feb 3 20:37:31 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] "Mon Feb 3 20:37:31 2025"
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
>
>
> RowMode(tmp2)
<pointer: 0x5c503a2dfac0>
>
>
>
> 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] "Mon Feb 3 20:37:31 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] "Mon Feb 3 20:37:31 2025"
>
> ColMode(tmp2)
<pointer: 0x5c503a2dfac0>
>
>
>
> ### 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,] 101.2573963 -1.2444858 -0.8171322 -0.8847452
[2,] 0.8611474 1.1085564 1.1606416 1.5245063
[3,] 0.9567339 -0.8812928 0.4999629 -1.1949297
[4,] -0.2779604 -1.6806918 -1.5004461 0.1133573
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-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,] 101.2573963 1.2444858 0.8171322 0.8847452
[2,] 0.8611474 1.1085564 1.1606416 1.5245063
[3,] 0.9567339 0.8812928 0.4999629 1.1949297
[4,] 0.2779604 1.6806918 1.5004461 0.1133573
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-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,] 10.0626734 1.1155652 0.9039536 0.9406090
[2,] 0.9279803 1.0528800 1.0773308 1.2347090
[3,] 0.9781278 0.9387719 0.7070805 1.0931284
[4,] 0.5272195 1.2964150 1.2249270 0.3366858
>
> 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-3.20-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,] 226.88413 37.40014 34.85667 35.29083
[2,] 35.14095 36.63736 36.93395 38.87160
[3,] 35.73801 35.26901 32.57077 37.12621
[4,] 30.55016 39.64484 38.74972 28.48022
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5c503828e470>
> exp(tmp5)
<pointer: 0x5c503828e470>
> log(tmp5,2)
<pointer: 0x5c503828e470>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 472.2296
> Min(tmp5)
[1] 53.48598
> mean(tmp5)
[1] 73.90612
> Sum(tmp5)
[1] 14781.22
> Var(tmp5)
[1] 870.5284
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 93.60076 74.59909 71.58946 70.31510 72.79987 71.66863 71.17137 70.54170
[9] 72.26987 70.50533
> rowSums(tmp5)
[1] 1872.015 1491.982 1431.789 1406.302 1455.997 1433.373 1423.427 1410.834
[9] 1445.397 1410.107
> rowVars(tmp5)
[1] 8010.99627 65.68625 77.60675 78.89056 83.88050 73.15061
[7] 81.18062 81.96797 52.34054 42.57841
> rowSd(tmp5)
[1] 89.504169 8.104705 8.809469 8.882036 9.158630 8.552813 9.010029
[8] 9.053616 7.234676 6.525214
> rowMax(tmp5)
[1] 472.22959 85.44743 85.12403 87.82696 90.15151 83.17632 88.58881
[8] 93.14137 81.91179 85.43944
> rowMin(tmp5)
[1] 59.86102 55.55338 53.48598 56.09379 56.44612 53.98804 58.87639 55.94310
[9] 53.95402 60.81550
>
> colMeans(tmp5)
[1] 110.45318 76.98227 74.33567 70.56943 75.56427 68.59085 71.75363
[8] 76.11913 75.79701 73.06142 67.90028 67.92542 69.59221 67.28707
[15] 73.12840 70.38690 74.03167 70.87868 71.92945 71.83539
> colSums(tmp5)
[1] 1104.5318 769.8227 743.3567 705.6943 755.6427 685.9085 717.5363
[8] 761.1913 757.9701 730.6142 679.0028 679.2542 695.9221 672.8707
[15] 731.2840 703.8690 740.3167 708.7868 719.2945 718.3539
> colVars(tmp5)
[1] 16185.20452 33.03270 95.47527 92.14052 149.80849 63.30910
[7] 99.76798 23.33580 48.21277 106.15747 81.87699 36.05257
[13] 66.40967 42.48993 28.14369 85.72405 78.07005 51.02751
[19] 43.18336 99.02025
> colSd(tmp5)
[1] 127.221085 5.747408 9.771145 9.598985 12.239628 7.956702
[7] 9.988392 4.830714 6.943542 10.303275 9.048590 6.004379
[13] 8.149213 6.518430 5.305062 9.258728 8.835726 7.143354
[19] 6.571405 9.950892
> colMax(tmp5)
[1] 472.22959 87.68569 86.78490 89.12974 93.14137 86.97432 85.44743
[8] 83.08507 84.75945 90.15151 85.43944 76.46026 81.59444 78.43370
[15] 80.46825 82.29852 85.13410 79.68947 81.56347 87.82696
> colMin(tmp5)
[1] 60.81550 68.48521 53.95402 59.27784 55.55338 60.55462 56.44612 69.15220
[9] 62.57786 56.77597 57.81033 53.98804 53.48598 58.87639 65.81011 55.54697
[17] 58.89876 58.80074 61.28779 58.28410
>
>
> ### 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] 93.60076 74.59909 71.58946 70.31510 72.79987 71.66863 71.17137 70.54170
[9] 72.26987 NA
> rowSums(tmp5)
[1] 1872.015 1491.982 1431.789 1406.302 1455.997 1433.373 1423.427 1410.834
[9] 1445.397 NA
> rowVars(tmp5)
[1] 8010.99627 65.68625 77.60675 78.89056 83.88050 73.15061
[7] 81.18062 81.96797 52.34054 43.68398
> rowSd(tmp5)
[1] 89.504169 8.104705 8.809469 8.882036 9.158630 8.552813 9.010029
[8] 9.053616 7.234676 6.609386
> rowMax(tmp5)
[1] 472.22959 85.44743 85.12403 87.82696 90.15151 83.17632 88.58881
[8] 93.14137 81.91179 NA
> rowMin(tmp5)
[1] 59.86102 55.55338 53.48598 56.09379 56.44612 53.98804 58.87639 55.94310
[9] 53.95402 NA
>
> colMeans(tmp5)
[1] 110.45318 76.98227 74.33567 70.56943 75.56427 68.59085 71.75363
[8] 76.11913 75.79701 73.06142 67.90028 67.92542 NA 67.28707
[15] 73.12840 70.38690 74.03167 70.87868 71.92945 71.83539
> colSums(tmp5)
[1] 1104.5318 769.8227 743.3567 705.6943 755.6427 685.9085 717.5363
[8] 761.1913 757.9701 730.6142 679.0028 679.2542 NA 672.8707
[15] 731.2840 703.8690 740.3167 708.7868 719.2945 718.3539
> colVars(tmp5)
[1] 16185.20452 33.03270 95.47527 92.14052 149.80849 63.30910
[7] 99.76798 23.33580 48.21277 106.15747 81.87699 36.05257
[13] NA 42.48993 28.14369 85.72405 78.07005 51.02751
[19] 43.18336 99.02025
> colSd(tmp5)
[1] 127.221085 5.747408 9.771145 9.598985 12.239628 7.956702
[7] 9.988392 4.830714 6.943542 10.303275 9.048590 6.004379
[13] NA 6.518430 5.305062 9.258728 8.835726 7.143354
[19] 6.571405 9.950892
> colMax(tmp5)
[1] 472.22959 87.68569 86.78490 89.12974 93.14137 86.97432 85.44743
[8] 83.08507 84.75945 90.15151 85.43944 76.46026 NA 78.43370
[15] 80.46825 82.29852 85.13410 79.68947 81.56347 87.82696
> colMin(tmp5)
[1] 60.81550 68.48521 53.95402 59.27784 55.55338 60.55462 56.44612 69.15220
[9] 62.57786 56.77597 57.81033 53.98804 NA 58.87639 65.81011 55.54697
[17] 58.89876 58.80074 61.28779 58.28410
>
> Max(tmp5,na.rm=TRUE)
[1] 472.2296
> Min(tmp5,na.rm=TRUE)
[1] 53.48598
> mean(tmp5,na.rm=TRUE)
[1] 73.89988
> Sum(tmp5,na.rm=TRUE)
[1] 14706.08
> Var(tmp5,na.rm=TRUE)
[1] 874.9171
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.60076 74.59909 71.58946 70.31510 72.79987 71.66863 71.17137 70.54170
[9] 72.26987 70.26104
> rowSums(tmp5,na.rm=TRUE)
[1] 1872.015 1491.982 1431.789 1406.302 1455.997 1433.373 1423.427 1410.834
[9] 1445.397 1334.960
> rowVars(tmp5,na.rm=TRUE)
[1] 8010.99627 65.68625 77.60675 78.89056 83.88050 73.15061
[7] 81.18062 81.96797 52.34054 43.68398
> rowSd(tmp5,na.rm=TRUE)
[1] 89.504169 8.104705 8.809469 8.882036 9.158630 8.552813 9.010029
[8] 9.053616 7.234676 6.609386
> rowMax(tmp5,na.rm=TRUE)
[1] 472.22959 85.44743 85.12403 87.82696 90.15151 83.17632 88.58881
[8] 93.14137 81.91179 85.43944
> rowMin(tmp5,na.rm=TRUE)
[1] 59.86102 55.55338 53.48598 56.09379 56.44612 53.98804 58.87639 55.94310
[9] 53.95402 60.81550
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.45318 76.98227 74.33567 70.56943 75.56427 68.59085 71.75363
[8] 76.11913 75.79701 73.06142 67.90028 67.92542 68.97502 67.28707
[15] 73.12840 70.38690 74.03167 70.87868 71.92945 71.83539
> colSums(tmp5,na.rm=TRUE)
[1] 1104.5318 769.8227 743.3567 705.6943 755.6427 685.9085 717.5363
[8] 761.1913 757.9701 730.6142 679.0028 679.2542 620.7752 672.8707
[15] 731.2840 703.8690 740.3167 708.7868 719.2945 718.3539
> colVars(tmp5,na.rm=TRUE)
[1] 16185.20452 33.03270 95.47527 92.14052 149.80849 63.30910
[7] 99.76798 23.33580 48.21277 106.15747 81.87699 36.05257
[13] 70.42550 42.48993 28.14369 85.72405 78.07005 51.02751
[19] 43.18336 99.02025
> colSd(tmp5,na.rm=TRUE)
[1] 127.221085 5.747408 9.771145 9.598985 12.239628 7.956702
[7] 9.988392 4.830714 6.943542 10.303275 9.048590 6.004379
[13] 8.391990 6.518430 5.305062 9.258728 8.835726 7.143354
[19] 6.571405 9.950892
> colMax(tmp5,na.rm=TRUE)
[1] 472.22959 87.68569 86.78490 89.12974 93.14137 86.97432 85.44743
[8] 83.08507 84.75945 90.15151 85.43944 76.46026 81.59444 78.43370
[15] 80.46825 82.29852 85.13410 79.68947 81.56347 87.82696
> colMin(tmp5,na.rm=TRUE)
[1] 60.81550 68.48521 53.95402 59.27784 55.55338 60.55462 56.44612 69.15220
[9] 62.57786 56.77597 57.81033 53.98804 53.48598 58.87639 65.81011 55.54697
[17] 58.89876 58.80074 61.28779 58.28410
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.60076 74.59909 71.58946 70.31510 72.79987 71.66863 71.17137 70.54170
[9] 72.26987 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1872.015 1491.982 1431.789 1406.302 1455.997 1433.373 1423.427 1410.834
[9] 1445.397 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 8010.99627 65.68625 77.60675 78.89056 83.88050 73.15061
[7] 81.18062 81.96797 52.34054 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 89.504169 8.104705 8.809469 8.882036 9.158630 8.552813 9.010029
[8] 9.053616 7.234676 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 472.22959 85.44743 85.12403 87.82696 90.15151 83.17632 88.58881
[8] 93.14137 81.91179 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 59.86102 55.55338 53.48598 56.09379 56.44612 53.98804 58.87639 55.94310
[9] 53.95402 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.96848 77.63207 74.96323 71.26235 75.17877 69.23517 70.73520
[8] 76.78034 76.39079 74.01608 65.95149 68.03637 NaN 67.30978
[15] 73.50082 70.58797 73.42453 70.72869 72.70613 72.29640
> colSums(tmp5,na.rm=TRUE)
[1] 1043.7163 698.6886 674.6691 641.3611 676.6089 623.1165 636.6168
[8] 691.0231 687.5171 666.1447 593.5634 612.3274 0.0000 605.7880
[15] 661.5073 635.2917 660.8208 636.5582 654.3551 650.6676
> colVars(tmp5,na.rm=TRUE)
[1] 17866.14692 32.41165 102.97898 98.25661 166.86262 66.55239
[7] 100.57030 21.33426 50.27296 109.17408 49.38635 40.42065
[13] NA 47.79537 30.10137 95.98475 83.68187 57.15285
[19] 41.79499 109.00687
> colSd(tmp5,na.rm=TRUE)
[1] 133.664307 5.693123 10.147856 9.912447 12.917531 8.157965
[7] 10.028474 4.618902 7.090342 10.448640 7.027542 6.357724
[13] NA 6.913420 5.486471 9.797181 9.147779 7.559951
[19] 6.464904 10.440636
> colMax(tmp5,na.rm=TRUE)
[1] 472.22959 87.68569 86.78490 89.12974 93.14137 86.97432 85.44743
[8] 83.08507 84.75945 90.15151 75.95176 76.46026 -Inf 78.43370
[15] 80.46825 82.29852 85.13410 79.68947 81.56347 87.82696
> colMin(tmp5,na.rm=TRUE)
[1] 63.58615 68.48521 53.95402 59.27784 55.55338 60.55462 56.44612 69.15220
[9] 62.57786 56.77597 57.81033 53.98804 Inf 58.87639 65.81011 55.54697
[17] 58.89876 58.80074 61.28779 58.28410
>
>
>
>
> 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] 176.95881 131.69987 108.32057 219.77090 222.46513 199.45982 153.98121
[8] 240.55789 91.44944 267.63586
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 176.95881 131.69987 108.32057 219.77090 222.46513 199.45982 153.98121
[8] 240.55789 91.44944 267.63586
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 1.705303e-13 5.684342e-14 8.526513e-14 0.000000e+00 -5.684342e-14
[6] -7.105427e-14 -5.684342e-14 -1.136868e-13 7.105427e-14 1.776357e-14
[11] -2.273737e-13 -5.684342e-14 -1.421085e-14 -4.263256e-14 5.684342e-14
[16] 8.526513e-14 5.684342e-14 7.105427e-14 -1.421085e-14 4.263256e-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)
+ }
7 12
10 3
5 12
7 7
2 14
5 4
10 20
9 9
7 6
3 1
3 20
8 7
7 8
9 11
10 13
2 1
10 15
2 2
8 18
4 5
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] 2.887543
> Min(tmp)
[1] -2.622048
> mean(tmp)
[1] 0.1079844
> Sum(tmp)
[1] 10.79844
> Var(tmp)
[1] 1.021497
>
> rowMeans(tmp)
[1] 0.1079844
> rowSums(tmp)
[1] 10.79844
> rowVars(tmp)
[1] 1.021497
> rowSd(tmp)
[1] 1.010691
> rowMax(tmp)
[1] 2.887543
> rowMin(tmp)
[1] -2.622048
>
> colMeans(tmp)
[1] -2.622048112 0.554491564 0.553810466 1.186235287 0.474198848
[6] -1.245023110 0.089376240 0.638947699 -0.738272604 0.291104403
[11] 2.615164946 0.675066696 2.505141705 0.114780340 0.400637369
[16] 0.346881046 -0.974803317 0.042415038 0.163502024 -0.199454312
[21] 0.624071452 0.578108317 -0.209560407 -0.626800164 0.831977854
[26] 0.966874134 1.448558125 1.758225793 0.602315010 -0.991788670
[31] 2.887543129 -1.201166304 -0.782924989 -0.478546476 2.047614775
[36] 0.613030850 1.112658286 1.058063974 -1.171677724 -1.388606147
[41] -0.660813363 -2.285072553 -1.030166347 -0.657421678 -1.349119864
[46] -1.170148388 -0.149752862 -0.234982315 0.077411774 -1.168068829
[51] 0.144609142 1.539105391 1.151608641 -0.268510788 0.715416152
[56] 0.581409391 1.061868744 -0.648043658 -0.307413324 -0.718284659
[61] -1.253744824 -1.531295883 0.350018799 0.104205881 -1.286829282
[66] 0.119322630 0.689532177 -1.091956071 -0.154779405 0.220810689
[71] -1.198457700 0.904583729 -0.194116331 -1.523748617 -0.067652434
[76] -0.555917500 1.199404332 0.937442447 -0.002425137 -0.185154600
[81] 0.443950488 0.503673922 0.883096790 0.491315283 1.296848653
[86] 0.845217263 0.868849961 -0.125713859 1.358555238 -0.244671941
[91] 1.287723511 0.605251635 0.723387988 0.110368254 0.398744960
[96] -0.702199719 -1.032372133 0.457589917 -0.774694532 0.750522955
> colSums(tmp)
[1] -2.622048112 0.554491564 0.553810466 1.186235287 0.474198848
[6] -1.245023110 0.089376240 0.638947699 -0.738272604 0.291104403
[11] 2.615164946 0.675066696 2.505141705 0.114780340 0.400637369
[16] 0.346881046 -0.974803317 0.042415038 0.163502024 -0.199454312
[21] 0.624071452 0.578108317 -0.209560407 -0.626800164 0.831977854
[26] 0.966874134 1.448558125 1.758225793 0.602315010 -0.991788670
[31] 2.887543129 -1.201166304 -0.782924989 -0.478546476 2.047614775
[36] 0.613030850 1.112658286 1.058063974 -1.171677724 -1.388606147
[41] -0.660813363 -2.285072553 -1.030166347 -0.657421678 -1.349119864
[46] -1.170148388 -0.149752862 -0.234982315 0.077411774 -1.168068829
[51] 0.144609142 1.539105391 1.151608641 -0.268510788 0.715416152
[56] 0.581409391 1.061868744 -0.648043658 -0.307413324 -0.718284659
[61] -1.253744824 -1.531295883 0.350018799 0.104205881 -1.286829282
[66] 0.119322630 0.689532177 -1.091956071 -0.154779405 0.220810689
[71] -1.198457700 0.904583729 -0.194116331 -1.523748617 -0.067652434
[76] -0.555917500 1.199404332 0.937442447 -0.002425137 -0.185154600
[81] 0.443950488 0.503673922 0.883096790 0.491315283 1.296848653
[86] 0.845217263 0.868849961 -0.125713859 1.358555238 -0.244671941
[91] 1.287723511 0.605251635 0.723387988 0.110368254 0.398744960
[96] -0.702199719 -1.032372133 0.457589917 -0.774694532 0.750522955
> 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] -2.622048112 0.554491564 0.553810466 1.186235287 0.474198848
[6] -1.245023110 0.089376240 0.638947699 -0.738272604 0.291104403
[11] 2.615164946 0.675066696 2.505141705 0.114780340 0.400637369
[16] 0.346881046 -0.974803317 0.042415038 0.163502024 -0.199454312
[21] 0.624071452 0.578108317 -0.209560407 -0.626800164 0.831977854
[26] 0.966874134 1.448558125 1.758225793 0.602315010 -0.991788670
[31] 2.887543129 -1.201166304 -0.782924989 -0.478546476 2.047614775
[36] 0.613030850 1.112658286 1.058063974 -1.171677724 -1.388606147
[41] -0.660813363 -2.285072553 -1.030166347 -0.657421678 -1.349119864
[46] -1.170148388 -0.149752862 -0.234982315 0.077411774 -1.168068829
[51] 0.144609142 1.539105391 1.151608641 -0.268510788 0.715416152
[56] 0.581409391 1.061868744 -0.648043658 -0.307413324 -0.718284659
[61] -1.253744824 -1.531295883 0.350018799 0.104205881 -1.286829282
[66] 0.119322630 0.689532177 -1.091956071 -0.154779405 0.220810689
[71] -1.198457700 0.904583729 -0.194116331 -1.523748617 -0.067652434
[76] -0.555917500 1.199404332 0.937442447 -0.002425137 -0.185154600
[81] 0.443950488 0.503673922 0.883096790 0.491315283 1.296848653
[86] 0.845217263 0.868849961 -0.125713859 1.358555238 -0.244671941
[91] 1.287723511 0.605251635 0.723387988 0.110368254 0.398744960
[96] -0.702199719 -1.032372133 0.457589917 -0.774694532 0.750522955
> colMin(tmp)
[1] -2.622048112 0.554491564 0.553810466 1.186235287 0.474198848
[6] -1.245023110 0.089376240 0.638947699 -0.738272604 0.291104403
[11] 2.615164946 0.675066696 2.505141705 0.114780340 0.400637369
[16] 0.346881046 -0.974803317 0.042415038 0.163502024 -0.199454312
[21] 0.624071452 0.578108317 -0.209560407 -0.626800164 0.831977854
[26] 0.966874134 1.448558125 1.758225793 0.602315010 -0.991788670
[31] 2.887543129 -1.201166304 -0.782924989 -0.478546476 2.047614775
[36] 0.613030850 1.112658286 1.058063974 -1.171677724 -1.388606147
[41] -0.660813363 -2.285072553 -1.030166347 -0.657421678 -1.349119864
[46] -1.170148388 -0.149752862 -0.234982315 0.077411774 -1.168068829
[51] 0.144609142 1.539105391 1.151608641 -0.268510788 0.715416152
[56] 0.581409391 1.061868744 -0.648043658 -0.307413324 -0.718284659
[61] -1.253744824 -1.531295883 0.350018799 0.104205881 -1.286829282
[66] 0.119322630 0.689532177 -1.091956071 -0.154779405 0.220810689
[71] -1.198457700 0.904583729 -0.194116331 -1.523748617 -0.067652434
[76] -0.555917500 1.199404332 0.937442447 -0.002425137 -0.185154600
[81] 0.443950488 0.503673922 0.883096790 0.491315283 1.296848653
[86] 0.845217263 0.868849961 -0.125713859 1.358555238 -0.244671941
[91] 1.287723511 0.605251635 0.723387988 0.110368254 0.398744960
[96] -0.702199719 -1.032372133 0.457589917 -0.774694532 0.750522955
> colMedians(tmp)
[1] -2.622048112 0.554491564 0.553810466 1.186235287 0.474198848
[6] -1.245023110 0.089376240 0.638947699 -0.738272604 0.291104403
[11] 2.615164946 0.675066696 2.505141705 0.114780340 0.400637369
[16] 0.346881046 -0.974803317 0.042415038 0.163502024 -0.199454312
[21] 0.624071452 0.578108317 -0.209560407 -0.626800164 0.831977854
[26] 0.966874134 1.448558125 1.758225793 0.602315010 -0.991788670
[31] 2.887543129 -1.201166304 -0.782924989 -0.478546476 2.047614775
[36] 0.613030850 1.112658286 1.058063974 -1.171677724 -1.388606147
[41] -0.660813363 -2.285072553 -1.030166347 -0.657421678 -1.349119864
[46] -1.170148388 -0.149752862 -0.234982315 0.077411774 -1.168068829
[51] 0.144609142 1.539105391 1.151608641 -0.268510788 0.715416152
[56] 0.581409391 1.061868744 -0.648043658 -0.307413324 -0.718284659
[61] -1.253744824 -1.531295883 0.350018799 0.104205881 -1.286829282
[66] 0.119322630 0.689532177 -1.091956071 -0.154779405 0.220810689
[71] -1.198457700 0.904583729 -0.194116331 -1.523748617 -0.067652434
[76] -0.555917500 1.199404332 0.937442447 -0.002425137 -0.185154600
[81] 0.443950488 0.503673922 0.883096790 0.491315283 1.296848653
[86] 0.845217263 0.868849961 -0.125713859 1.358555238 -0.244671941
[91] 1.287723511 0.605251635 0.723387988 0.110368254 0.398744960
[96] -0.702199719 -1.032372133 0.457589917 -0.774694532 0.750522955
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -2.622048 0.5544916 0.5538105 1.186235 0.4741988 -1.245023 0.08937624
[2,] -2.622048 0.5544916 0.5538105 1.186235 0.4741988 -1.245023 0.08937624
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.6389477 -0.7382726 0.2911044 2.615165 0.6750667 2.505142 0.1147803
[2,] 0.6389477 -0.7382726 0.2911044 2.615165 0.6750667 2.505142 0.1147803
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.4006374 0.346881 -0.9748033 0.04241504 0.163502 -0.1994543 0.6240715
[2,] 0.4006374 0.346881 -0.9748033 0.04241504 0.163502 -0.1994543 0.6240715
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.5781083 -0.2095604 -0.6268002 0.8319779 0.9668741 1.448558 1.758226
[2,] 0.5781083 -0.2095604 -0.6268002 0.8319779 0.9668741 1.448558 1.758226
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.602315 -0.9917887 2.887543 -1.201166 -0.782925 -0.4785465 2.047615
[2,] 0.602315 -0.9917887 2.887543 -1.201166 -0.782925 -0.4785465 2.047615
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.6130309 1.112658 1.058064 -1.171678 -1.388606 -0.6608134 -2.285073
[2,] 0.6130309 1.112658 1.058064 -1.171678 -1.388606 -0.6608134 -2.285073
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.030166 -0.6574217 -1.34912 -1.170148 -0.1497529 -0.2349823 0.07741177
[2,] -1.030166 -0.6574217 -1.34912 -1.170148 -0.1497529 -0.2349823 0.07741177
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -1.168069 0.1446091 1.539105 1.151609 -0.2685108 0.7154162 0.5814094
[2,] -1.168069 0.1446091 1.539105 1.151609 -0.2685108 0.7154162 0.5814094
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 1.061869 -0.6480437 -0.3074133 -0.7182847 -1.253745 -1.531296 0.3500188
[2,] 1.061869 -0.6480437 -0.3074133 -0.7182847 -1.253745 -1.531296 0.3500188
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.1042059 -1.286829 0.1193226 0.6895322 -1.091956 -0.1547794 0.2208107
[2,] 0.1042059 -1.286829 0.1193226 0.6895322 -1.091956 -0.1547794 0.2208107
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -1.198458 0.9045837 -0.1941163 -1.523749 -0.06765243 -0.5559175 1.199404
[2,] -1.198458 0.9045837 -0.1941163 -1.523749 -0.06765243 -0.5559175 1.199404
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.9374424 -0.002425137 -0.1851546 0.4439505 0.5036739 0.8830968 0.4913153
[2,] 0.9374424 -0.002425137 -0.1851546 0.4439505 0.5036739 0.8830968 0.4913153
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 1.296849 0.8452173 0.86885 -0.1257139 1.358555 -0.2446719 1.287724
[2,] 1.296849 0.8452173 0.86885 -0.1257139 1.358555 -0.2446719 1.287724
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.6052516 0.723388 0.1103683 0.398745 -0.7021997 -1.032372 0.4575899
[2,] 0.6052516 0.723388 0.1103683 0.398745 -0.7021997 -1.032372 0.4575899
[,99] [,100]
[1,] -0.7746945 0.750523
[2,] -0.7746945 0.750523
>
>
> Max(tmp2)
[1] 2.061708
> Min(tmp2)
[1] -2.133412
> mean(tmp2)
[1] 0.1186413
> Sum(tmp2)
[1] 11.86413
> Var(tmp2)
[1] 0.7002096
>
> rowMeans(tmp2)
[1] -0.605379661 1.531790476 -1.065998412 -0.618913125 -0.690966203
[6] -0.010985123 0.641965864 1.596894674 1.567884306 0.275857922
[11] 1.149523017 0.008332727 -0.310157781 -2.133411628 -0.320447151
[16] 1.373971928 -0.013304162 0.408860129 0.629978946 -0.229712881
[21] 1.055897504 0.745750894 0.406057725 1.227202723 -0.329962956
[26] 1.207992289 -0.550242089 0.378006414 0.437507706 0.603126810
[31] 2.061707790 0.304953806 -0.222740973 1.027408021 0.685771393
[36] 0.393146557 -0.472758354 -0.062191082 1.864923852 -1.225432982
[41] -1.025422484 1.277201782 -0.340200222 -0.511398681 -0.182879855
[46] 1.079783711 -0.192877268 0.153356878 0.860704434 0.742508186
[51] 0.170571948 -1.439949158 0.200194305 -0.037948602 -0.050073408
[56] -0.495462819 0.702490625 1.027227222 -1.423489526 -0.795312614
[61] 0.818598251 0.432189052 -0.087461861 0.751833370 0.657135234
[66] 0.860464837 1.116784279 -0.846491782 -0.328129509 -0.410107190
[71] 0.617955923 2.001889987 -0.001576154 0.566555802 -0.879198151
[76] -0.193561258 -0.077824694 0.212707809 0.226952778 -0.202282392
[81] -0.804984877 0.476117893 -0.200731851 0.970510598 -0.791750930
[86] -1.338912807 -0.031396503 -1.060186914 -0.443398380 -0.631185680
[91] -0.934662233 0.354846005 -0.180769326 0.762506305 -0.639314655
[96] -1.180391551 -1.301516802 -0.073573582 0.334052469 0.901508039
> rowSums(tmp2)
[1] -0.605379661 1.531790476 -1.065998412 -0.618913125 -0.690966203
[6] -0.010985123 0.641965864 1.596894674 1.567884306 0.275857922
[11] 1.149523017 0.008332727 -0.310157781 -2.133411628 -0.320447151
[16] 1.373971928 -0.013304162 0.408860129 0.629978946 -0.229712881
[21] 1.055897504 0.745750894 0.406057725 1.227202723 -0.329962956
[26] 1.207992289 -0.550242089 0.378006414 0.437507706 0.603126810
[31] 2.061707790 0.304953806 -0.222740973 1.027408021 0.685771393
[36] 0.393146557 -0.472758354 -0.062191082 1.864923852 -1.225432982
[41] -1.025422484 1.277201782 -0.340200222 -0.511398681 -0.182879855
[46] 1.079783711 -0.192877268 0.153356878 0.860704434 0.742508186
[51] 0.170571948 -1.439949158 0.200194305 -0.037948602 -0.050073408
[56] -0.495462819 0.702490625 1.027227222 -1.423489526 -0.795312614
[61] 0.818598251 0.432189052 -0.087461861 0.751833370 0.657135234
[66] 0.860464837 1.116784279 -0.846491782 -0.328129509 -0.410107190
[71] 0.617955923 2.001889987 -0.001576154 0.566555802 -0.879198151
[76] -0.193561258 -0.077824694 0.212707809 0.226952778 -0.202282392
[81] -0.804984877 0.476117893 -0.200731851 0.970510598 -0.791750930
[86] -1.338912807 -0.031396503 -1.060186914 -0.443398380 -0.631185680
[91] -0.934662233 0.354846005 -0.180769326 0.762506305 -0.639314655
[96] -1.180391551 -1.301516802 -0.073573582 0.334052469 0.901508039
> 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] -0.605379661 1.531790476 -1.065998412 -0.618913125 -0.690966203
[6] -0.010985123 0.641965864 1.596894674 1.567884306 0.275857922
[11] 1.149523017 0.008332727 -0.310157781 -2.133411628 -0.320447151
[16] 1.373971928 -0.013304162 0.408860129 0.629978946 -0.229712881
[21] 1.055897504 0.745750894 0.406057725 1.227202723 -0.329962956
[26] 1.207992289 -0.550242089 0.378006414 0.437507706 0.603126810
[31] 2.061707790 0.304953806 -0.222740973 1.027408021 0.685771393
[36] 0.393146557 -0.472758354 -0.062191082 1.864923852 -1.225432982
[41] -1.025422484 1.277201782 -0.340200222 -0.511398681 -0.182879855
[46] 1.079783711 -0.192877268 0.153356878 0.860704434 0.742508186
[51] 0.170571948 -1.439949158 0.200194305 -0.037948602 -0.050073408
[56] -0.495462819 0.702490625 1.027227222 -1.423489526 -0.795312614
[61] 0.818598251 0.432189052 -0.087461861 0.751833370 0.657135234
[66] 0.860464837 1.116784279 -0.846491782 -0.328129509 -0.410107190
[71] 0.617955923 2.001889987 -0.001576154 0.566555802 -0.879198151
[76] -0.193561258 -0.077824694 0.212707809 0.226952778 -0.202282392
[81] -0.804984877 0.476117893 -0.200731851 0.970510598 -0.791750930
[86] -1.338912807 -0.031396503 -1.060186914 -0.443398380 -0.631185680
[91] -0.934662233 0.354846005 -0.180769326 0.762506305 -0.639314655
[96] -1.180391551 -1.301516802 -0.073573582 0.334052469 0.901508039
> rowMin(tmp2)
[1] -0.605379661 1.531790476 -1.065998412 -0.618913125 -0.690966203
[6] -0.010985123 0.641965864 1.596894674 1.567884306 0.275857922
[11] 1.149523017 0.008332727 -0.310157781 -2.133411628 -0.320447151
[16] 1.373971928 -0.013304162 0.408860129 0.629978946 -0.229712881
[21] 1.055897504 0.745750894 0.406057725 1.227202723 -0.329962956
[26] 1.207992289 -0.550242089 0.378006414 0.437507706 0.603126810
[31] 2.061707790 0.304953806 -0.222740973 1.027408021 0.685771393
[36] 0.393146557 -0.472758354 -0.062191082 1.864923852 -1.225432982
[41] -1.025422484 1.277201782 -0.340200222 -0.511398681 -0.182879855
[46] 1.079783711 -0.192877268 0.153356878 0.860704434 0.742508186
[51] 0.170571948 -1.439949158 0.200194305 -0.037948602 -0.050073408
[56] -0.495462819 0.702490625 1.027227222 -1.423489526 -0.795312614
[61] 0.818598251 0.432189052 -0.087461861 0.751833370 0.657135234
[66] 0.860464837 1.116784279 -0.846491782 -0.328129509 -0.410107190
[71] 0.617955923 2.001889987 -0.001576154 0.566555802 -0.879198151
[76] -0.193561258 -0.077824694 0.212707809 0.226952778 -0.202282392
[81] -0.804984877 0.476117893 -0.200731851 0.970510598 -0.791750930
[86] -1.338912807 -0.031396503 -1.060186914 -0.443398380 -0.631185680
[91] -0.934662233 0.354846005 -0.180769326 0.762506305 -0.639314655
[96] -1.180391551 -1.301516802 -0.073573582 0.334052469 0.901508039
>
> colMeans(tmp2)
[1] 0.1186413
> colSums(tmp2)
[1] 11.86413
> colVars(tmp2)
[1] 0.7002096
> colSd(tmp2)
[1] 0.8367853
> colMax(tmp2)
[1] 2.061708
> colMin(tmp2)
[1] -2.133412
> colMedians(tmp2)
[1] 0.003378286
> colRanges(tmp2)
[,1]
[1,] -2.133412
[2,] 2.061708
>
> 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] 7.2307017 3.0807664 0.5253806 0.4106639 0.6308787 -0.7791799
[7] -1.1069119 3.0875435 -4.1376771 -2.2572177
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.5827802
[2,] -0.1133872
[3,] 0.5929798
[4,] 1.5366609
[5,] 2.3055448
>
> rowApply(tmp,sum)
[1] -2.7588435 1.2588117 -1.4720886 -0.9360767 1.6154836 0.2317657
[7] 4.2164043 4.1941493 -2.2059805 2.5413229
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 9 4 7 3 10 6 10 5 8
[2,] 9 5 3 5 2 9 2 9 10 6
[3,] 2 10 2 9 7 1 9 6 4 1
[4,] 7 4 1 8 1 4 8 2 9 3
[5,] 1 8 9 10 4 5 5 4 6 4
[6,] 4 6 7 6 10 2 3 5 8 5
[7,] 5 2 5 4 8 3 10 1 7 7
[8,] 8 7 10 3 6 6 7 3 2 10
[9,] 6 1 8 1 5 8 1 7 3 2
[10,] 3 3 6 2 9 7 4 8 1 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.2633094 -0.3012067 0.5508365 0.7720495 3.4174177 -2.9845468
[7] -4.3445365 1.4427816 -2.7378124 1.4263597 -3.1508865 -7.1083621
[13] -0.5280676 0.7106564 1.3765935 1.0834805 -0.2509902 1.2537584
[19] -2.0807218 3.4696051
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.9355377
[2,] -0.1695661
[3,] 1.0613373
[4,] 1.0928154
[5,] 1.2142605
>
> rowApply(tmp,sum)
[1] -5.7286513 -5.0850063 4.0163916 0.4607873 -0.3838035
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 20 18 5 19 2
[2,] 12 9 15 14 4
[3,] 14 3 18 17 11
[4,] 4 19 13 10 10
[5,] 15 11 20 12 17
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.2142605 -0.09220211 0.1609905 -1.44487593 0.2414451 -0.2828047
[2,] 1.0928154 -0.40001727 -2.0116801 1.46675931 0.3742038 -2.8201823
[3,] -0.1695661 0.87456692 1.4145054 0.65595573 1.4643398 0.1497394
[4,] 1.0613373 0.35042534 0.7635086 -0.04298621 0.2258345 0.3747983
[5,] -1.9355377 -1.03397958 0.2235120 0.13719663 1.1115945 -0.4060974
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.7269148 0.5911341 -1.5184293 -0.68305821 -0.4040700 -1.7240553
[2,] -3.2789180 -0.5662343 0.9552475 0.88556691 -0.6624272 -1.8192286
[3,] -0.4986562 1.0752729 -3.2458274 -0.08566694 0.3749995 0.1977111
[4,] -0.3317040 -0.1311845 -0.1243794 2.58454540 -1.4352278 -1.3813066
[5,] 1.4916565 0.4737934 1.1955762 -1.27502741 -1.0241609 -2.3814827
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.0886108 -0.7322663 0.7530428 -0.3369404 0.4887897 -0.4035919
[2,] -0.7802281 -0.2495761 1.5797414 0.5101667 -1.4489263 0.6156890
[3,] -1.0215499 0.4025271 0.6833945 0.1553142 0.2714313 1.0405538
[4,] 0.2765838 0.4636992 -1.2478004 -0.3629191 0.8892752 -0.4437714
[5,] 1.0857373 0.8262725 -0.3917848 1.1178592 -0.4515600 0.4448789
[,19] [,20]
[1,] -0.30315264 0.5626584
[2,] 0.56502832 0.9071936
[3,] -1.16011117 1.4374577
[4,] -1.19871703 0.1707762
[5,] 0.01623071 0.3915192
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.8503656 -1.787638 0.940756 2.186234 -1.26966 0.7745708 1.329328
col8 col9 col10 col11 col12 col13 col14
row1 0.4238545 1.580338 -0.9747466 -0.4516687 -1.377427 0.6268011 -0.7003601
col15 col16 col17 col18 col19 col20
row1 1.636702 -1.038976 -0.7928074 0.7545784 -0.2348011 -1.313894
> tmp[,"col10"]
col10
row1 -0.9747466276
row2 1.1768536530
row3 -1.6823864231
row4 0.4057081522
row5 -0.0008126538
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.8503656 -1.787638 0.9407560 2.1862336 -1.2696600 0.7745708
row5 -0.6933485 1.071072 0.9352095 -0.6451465 -0.2130844 -0.6701839
col7 col8 col9 col10 col11 col12
row1 1.329328114 0.4238545 1.5803376 -0.9747466276 -0.4516687 -1.3774272
row5 -0.001675233 1.5704435 0.2755013 -0.0008126538 -0.4601658 0.3083077
col13 col14 col15 col16 col17 col18
row1 0.6268011 -0.7003601 1.6367024 -1.0389757 -0.7928074 0.7545784
row5 0.4842319 -0.8994918 -0.7898023 0.2062669 -1.6831287 -2.2970426
col19 col20
row1 -0.2348011 -1.313894
row5 0.8840135 -0.369560
> tmp[,c("col6","col20")]
col6 col20
row1 0.7745708 -1.3138937
row2 1.3867736 -1.1751959
row3 0.3890033 0.0245813
row4 0.3870297 -0.4540795
row5 -0.6701839 -0.3695600
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.7745708 -1.313894
row5 -0.6701839 -0.369560
>
>
>
>
> 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 50.40622 49.03584 51.20676 51.63985 49.1199 106.1931 50.70948 49.12844
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.76734 49.21596 50.13806 49.70726 51.38096 48.08093 49.08826 48.01451
col17 col18 col19 col20
row1 51.67946 51.41372 50.7262 104.0004
> tmp[,"col10"]
col10
row1 49.21596
row2 29.91228
row3 30.37618
row4 30.12032
row5 50.59811
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.40622 49.03584 51.20676 51.63985 49.11990 106.1931 50.70948 49.12844
row5 48.95367 51.21245 50.98417 47.97335 51.00655 105.6546 48.33789 51.48843
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.76734 49.21596 50.13806 49.70726 51.38096 48.08093 49.08826 48.01451
row5 49.84572 50.59811 50.38167 49.21888 49.57702 48.50145 50.48224 52.05815
col17 col18 col19 col20
row1 51.67946 51.41372 50.72620 104.0004
row5 50.29719 49.70840 49.45121 105.8984
> tmp[,c("col6","col20")]
col6 col20
row1 106.19306 104.00037
row2 74.13486 75.15710
row3 73.47964 75.52248
row4 76.16459 75.21023
row5 105.65456 105.89843
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.1931 104.0004
row5 105.6546 105.8984
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.1931 104.0004
row5 105.6546 105.8984
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.18602013
[2,] -1.91496721
[3,] -0.12206840
[4,] -0.82558970
[5,] -0.08567774
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.47027653 1.0050633
[2,] 0.15538172 1.3327516
[3,] 0.34073915 -0.3722245
[4,] -0.02660086 0.1686633
[5,] -0.77345595 0.5665408
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.0339654 -0.13036944
[2,] -2.3962841 1.14875643
[3,] -0.2025788 -2.48000312
[4,] -0.1552965 -0.00996902
[5,] 0.7182685 -1.35935662
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.033965
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.033965
[2,] -2.396284
>
>
>
> 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 -1.065587 0.9982733 -1.524015 -1.558117 -0.02249198 0.4766977 -0.8035386
row1 -1.363569 -0.1544663 3.391661 -1.192833 1.65699402 2.1196755 0.2554167
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.4390252 -0.33984633 -0.5857292 -0.1011810 1.3363336 0.5070140
row1 -0.2530786 0.08925593 -2.4447546 0.2646574 -0.9319915 -0.5455165
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.04948217 0.07405512 -0.3694576 0.7692787 -1.4742816 -0.7321573
row1 -0.50943813 1.53559962 -1.5377590 -0.4427053 -0.9687827 -1.3140749
[,20]
row3 -0.3835946
row1 0.5154656
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.3578411 -0.9544651 0.9544915 -1.164507 -1.075623 -1.310243 -1.037037
[,8] [,9] [,10]
row2 0.6275664 -0.91839 -0.8520303
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.1622139 -0.7591248 -0.4187867 0.4294059 0.1057996 0.6013375 -0.2994925
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.6068181 0.5462259 0.3240565 -2.771292 -0.3308855 -0.1703817 0.8124224
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.1778124 -0.2812867 0.9151213 0.6191916 -0.5679633 -0.5325774
>
>
> 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: 0x5c503901fd00>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e4dbf4bd19533"
[2] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e4dbf15a7c8f3"
[3] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e4dbf7c040da0"
[4] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e4dbf53e45418"
[5] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e4dbf7857fea6"
[6] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e4dbfcc08f2f"
[7] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e4dbf13972824"
[8] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e4dbf2d2818fb"
[9] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e4dbfb36c0d9"
[10] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e4dbf18f37095"
[11] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e4dbf176fe856"
[12] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e4dbf7a917064"
[13] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e4dbf3aeb20cc"
[14] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e4dbf29a3b089"
[15] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e4dbf3c647b1"
>
>
> ### 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: 0x5c503ac2f590>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5c503ac2f590>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5c503ac2f590>
> rowMedians(tmp)
[1] -4.010938e-01 8.551505e-02 -2.905283e-01 -5.463203e-02 -2.327237e-05
[6] 4.241552e-01 1.694057e-01 3.384005e-01 2.558867e-01 -5.960455e-02
[11] -8.150417e-01 -2.832887e-01 -1.172762e-01 -9.001785e-02 2.085079e-01
[16] 1.008477e-01 2.801890e-03 -1.608720e-01 2.844474e-01 3.587008e-01
[21] -8.317003e-02 1.320591e-01 1.010310e-01 2.503078e-01 -3.323978e-01
[26] 7.611929e-01 5.428992e-01 1.895317e-01 3.280698e-01 -2.386377e-02
[31] 3.775758e-01 -6.806250e-02 1.515677e-01 -9.911303e-02 1.899370e-01
[36] 1.819786e-01 3.148271e-01 1.996219e-01 3.969295e-01 4.724296e-01
[41] -7.221478e-02 1.969170e-01 -1.024307e-01 -2.912803e-02 -1.038516e-01
[46] -4.585851e-01 -1.488757e-02 2.349692e-01 -3.464195e-01 -2.646989e-01
[51] 4.220980e-02 1.698630e-01 -3.322866e-01 -4.912664e-02 -3.360612e-02
[56] -1.697819e-01 5.695489e-01 -3.199639e-01 -4.124194e-01 -2.155456e-01
[61] 6.403701e-01 -2.826663e-01 -1.669265e-02 -3.223320e-01 -1.663576e-01
[66] 7.709717e-02 -5.849957e-02 7.346021e-01 2.450080e-01 5.204609e-01
[71] 2.869129e-01 5.455059e-01 5.053877e-01 2.434890e-02 -2.239655e-01
[76] 1.411729e-02 2.252136e-01 2.757241e-01 -1.237382e-01 -6.945315e-01
[81] -1.073511e-01 -2.678453e-01 2.261477e-01 -6.814845e-02 2.693793e-01
[86] 1.264965e-01 -1.032554e-01 1.766258e-01 -5.895937e-01 9.979072e-02
[91] -2.598949e-01 1.843678e-01 -5.975202e-02 -2.895220e-01 3.502584e-01
[96] 1.325646e-01 5.269453e-01 -3.259724e-02 2.821467e-02 -4.266106e-02
[101] -2.972306e-02 2.651578e-01 2.207353e-01 4.785252e-02 4.027994e-02
[106] 2.053455e-01 1.888693e-01 3.698790e-02 -8.362602e-01 9.188662e-02
[111] -1.657834e-01 -2.264967e-02 1.025962e-01 6.856258e-04 -2.435947e-01
[116] 1.059579e-01 1.336473e-01 3.114273e-01 -5.363717e-01 -4.614945e-01
[121] 1.009254e-01 1.204509e-01 -8.818174e-02 -4.723045e-01 2.514461e-01
[126] -1.434495e-01 -4.753293e-01 -5.916437e-02 1.067383e-02 3.974910e-01
[131] 1.295305e-01 -2.385305e-01 -4.177788e-01 3.406265e-02 3.660318e-02
[136] -4.842477e-02 -4.155593e-01 -1.989939e-02 2.569405e-01 -3.130523e-01
[141] 9.323408e-02 2.084527e-01 -1.600961e-01 7.656064e-02 1.153657e-01
[146] 3.785566e-01 7.264393e-02 -2.406474e-01 7.540045e-02 -7.494578e-01
[151] -5.892214e-02 6.177350e-01 -1.377880e-01 -6.083680e-01 -8.325561e-01
[156] 1.804643e-01 2.406505e-01 7.581869e-02 5.094488e-02 -2.921009e-02
[161] -1.342052e-01 -1.073307e-01 7.844601e-01 -1.399277e-01 2.352758e-02
[166] -4.960915e-01 3.520659e-01 2.535274e-01 -3.933660e-01 -1.273133e-01
[171] -9.470026e-02 -4.383564e-01 -7.693840e-02 -5.213159e-01 7.021200e-01
[176] 9.280741e-02 -1.362078e-01 6.104906e-02 2.160743e-01 -1.117221e-01
[181] -7.731032e-02 6.922255e-01 -7.160785e-01 -3.240346e-01 2.056605e-01
[186] 5.692878e-01 -2.763958e-01 3.692559e-02 -1.456260e-01 -1.315742e-01
[191] -8.466832e-03 1.663017e-01 6.004229e-01 2.636883e-01 -3.024246e-01
[196] -8.079969e-02 3.147986e-01 4.769968e-01 -8.658511e-03 -1.985938e-01
[201] -1.058648e+00 -1.571185e-01 -2.377304e-01 1.346189e-01 2.707888e-01
[206] -1.893968e-01 2.572818e-01 -1.519056e-01 1.626036e-01 1.196811e-01
[211] -3.525008e-01 2.469563e-01 -2.131038e-01 -9.853459e-02 2.652209e-01
[216] -1.638029e-01 2.095755e-01 -1.795591e-01 -1.755161e-01 -2.433528e-01
[221] 3.107393e-01 -3.393739e-01 -2.720777e-01 5.731336e-01 -3.052328e-01
[226] -1.652557e-01 -1.065246e-02 4.646363e-01 5.011253e-02 1.848324e-01
>
> proc.time()
user system elapsed
1.238 0.670 1.894
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-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: 0x63dfbed1eac0>
> .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: 0x63dfbed1eac0>
> .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: 0x63dfbed1eac0>
> .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: 0x63dfbed1eac0>
> 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: 0x63dfbed212a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63dfbed212a0>
> .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: 0x63dfbed212a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63dfbed212a0>
> .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: 0x63dfbed212a0>
> 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: 0x63dfbe398920>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63dfbe398920>
> .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: 0x63dfbe398920>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x63dfbe398920>
> .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: 0x63dfbe398920>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x63dfbe398920>
> .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: 0x63dfbe398920>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x63dfbe398920>
> .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: 0x63dfbe398920>
> 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: 0x63dfbed26d80>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x63dfbed26d80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63dfbed26d80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63dfbed26d80>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3e4ea02b52af94" "BufferedMatrixFile3e4ea02b9ffd06"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3e4ea02b52af94" "BufferedMatrixFile3e4ea02b9ffd06"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x63dfbf4e3040>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63dfbf4e3040>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x63dfbf4e3040>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x63dfbf4e3040>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x63dfbf4e3040>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x63dfbf4e3040>
> .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: 0x63dfbee821d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x63dfbee821d0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x63dfbee821d0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x63dfbee821d0>
> 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: 0x63dfbda9fba0>
> .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: 0x63dfbda9fba0>
> rm(P)
>
> proc.time()
user system elapsed
0.247 0.045 0.279
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-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
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.234 0.041 0.264