Ben Bolstad
| Snapshot Date: 2025-01-23 13:00 -0500 (Thu, 23 Jan 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_20 |
| git_last_commit: 32b6f6a |
| git_last_commit_date: 2024-10-29 09:27:20 -0500 (Tue, 29 Oct 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2025-01-27 12:05 -0500 (Mon, 27 Jan 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4746 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves" | 4494 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4517 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4469 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4395 |
| 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: 2025-01-23 20:27:09 -0500 (Thu, 23 Jan 2025) |
| EndedAt: 2025-01-23 20:27:32 -0500 (Thu, 23 Jan 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
0.242 0.043 0.274
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] "Thu Jan 23 20:27:23 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu Jan 23 20:27:23 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: 0x5c02480042a0>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu Jan 23 20:27:23 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu Jan 23 20:27:23 2025"
>
> ColMode(tmp2)
<pointer: 0x5c02480042a0>
>
>
>
> ### 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,] 100.0673789 0.7378160 0.36752089 -0.6508511
[2,] -0.1583652 0.7199826 -0.63153501 -1.6179819
[3,] 0.3646913 0.3367841 0.53331006 -0.4614837
[4,] -0.8313854 0.2424515 -0.01886966 1.4022000
> 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,] 100.0673789 0.7378160 0.36752089 0.6508511
[2,] 0.1583652 0.7199826 0.63153501 1.6179819
[3,] 0.3646913 0.3367841 0.53331006 0.4614837
[4,] 0.8313854 0.2424515 0.01886966 1.4022000
> 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,] 10.0033684 0.8589622 0.6062350 0.8067534
[2,] 0.3979513 0.8485179 0.7946918 1.2719992
[3,] 0.6038968 0.5803310 0.7302808 0.6793259
[4,] 0.9118034 0.4923937 0.1373669 1.1841453
>
> 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,] 225.10106 34.32744 31.42987 33.71839
[2,] 29.13788 34.20516 33.57845 39.33797
[3,] 31.40366 31.14009 32.83612 32.25474
[4,] 34.94942 30.16639 26.39254 38.24365
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5c024801c510>
> exp(tmp5)
<pointer: 0x5c024801c510>
> log(tmp5,2)
<pointer: 0x5c024801c510>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.5184
> Min(tmp5)
[1] 52.82061
> mean(tmp5)
[1] 72.78284
> Sum(tmp5)
[1] 14556.57
> Var(tmp5)
[1] 866.0809
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 93.98882 68.91977 71.54117 67.97942 72.43478 69.33253 72.93452 71.54527
[9] 71.58716 67.56496
> rowSums(tmp5)
[1] 1879.776 1378.395 1430.823 1359.588 1448.696 1386.651 1458.690 1430.905
[9] 1431.743 1351.299
> rowVars(tmp5)
[1] 7820.79308 86.61478 106.96288 61.92127 50.42017 73.68819
[7] 51.62291 61.62392 123.25517 74.71600
> rowSd(tmp5)
[1] 88.435248 9.306706 10.342286 7.869007 7.100716 8.584183 7.184909
[8] 7.850090 11.102035 8.643841
> rowMax(tmp5)
[1] 468.51837 87.25550 91.25555 82.07288 88.08475 82.72412 92.09056
[8] 87.36354 92.07400 85.71079
> rowMin(tmp5)
[1] 60.39404 55.43762 52.82061 54.93261 61.75939 56.27076 56.75703 56.29492
[9] 55.81166 56.93576
>
> colMeans(tmp5)
[1] 109.20927 66.80516 69.96474 72.41186 75.21781 68.69234 73.52979
[8] 72.82687 72.03316 69.17321 69.41876 72.63111 71.06892 75.97938
[15] 78.15645 68.44271 67.46684 67.19944 69.54357 65.88537
> colSums(tmp5)
[1] 1092.0927 668.0516 699.6474 724.1186 752.1781 686.9234 735.2979
[8] 728.2687 720.3316 691.7321 694.1876 726.3111 710.6892 759.7938
[15] 781.5645 684.4271 674.6684 671.9944 695.4357 658.8537
> colVars(tmp5)
[1] 15993.05930 18.64389 65.94839 47.62042 107.60463 49.11182
[7] 65.72079 157.40837 121.33928 125.78719 49.53605 67.34637
[13] 91.63808 49.46271 49.65568 47.51174 88.08609 87.04597
[19] 28.75412 64.04239
> colSd(tmp5)
[1] 126.463668 4.317857 8.120861 6.900755 10.373265 7.007983
[7] 8.106836 12.546249 11.015411 11.215489 7.038185 8.206483
[13] 9.572778 7.032973 7.046679 6.892876 9.385419 9.329843
[19] 5.362287 8.002649
> colMax(tmp5)
[1] 468.51837 71.69563 83.21700 81.87684 88.08475 80.93704 87.36354
[8] 92.09056 92.07400 88.50966 79.85731 88.02548 85.31777 88.44406
[15] 91.25555 78.64152 82.68186 79.07675 75.35277 78.79638
> colMin(tmp5)
[1] 60.64668 58.01004 54.93261 59.98331 57.45242 59.12908 62.58267 56.27076
[9] 55.43762 56.75703 56.65757 62.62406 56.93576 66.73882 66.34172 59.07979
[17] 56.29492 52.82061 60.83721 55.81166
>
>
> ### 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] 93.98882 68.91977 71.54117 67.97942 72.43478 69.33253 72.93452 71.54527
[9] 71.58716 NA
> rowSums(tmp5)
[1] 1879.776 1378.395 1430.823 1359.588 1448.696 1386.651 1458.690 1430.905
[9] 1431.743 NA
> rowVars(tmp5)
[1] 7820.79308 86.61478 106.96288 61.92127 50.42017 73.68819
[7] 51.62291 61.62392 123.25517 67.34138
> rowSd(tmp5)
[1] 88.435248 9.306706 10.342286 7.869007 7.100716 8.584183 7.184909
[8] 7.850090 11.102035 8.206179
> rowMax(tmp5)
[1] 468.51837 87.25550 91.25555 82.07288 88.08475 82.72412 92.09056
[8] 87.36354 92.07400 NA
> rowMin(tmp5)
[1] 60.39404 55.43762 52.82061 54.93261 61.75939 56.27076 56.75703 56.29492
[9] 55.81166 NA
>
> colMeans(tmp5)
[1] 109.20927 66.80516 69.96474 72.41186 75.21781 68.69234 73.52979
[8] 72.82687 72.03316 69.17321 69.41876 NA 71.06892 75.97938
[15] 78.15645 68.44271 67.46684 67.19944 69.54357 65.88537
> colSums(tmp5)
[1] 1092.0927 668.0516 699.6474 724.1186 752.1781 686.9234 735.2979
[8] 728.2687 720.3316 691.7321 694.1876 NA 710.6892 759.7938
[15] 781.5645 684.4271 674.6684 671.9944 695.4357 658.8537
> colVars(tmp5)
[1] 15993.05930 18.64389 65.94839 47.62042 107.60463 49.11182
[7] 65.72079 157.40837 121.33928 125.78719 49.53605 NA
[13] 91.63808 49.46271 49.65568 47.51174 88.08609 87.04597
[19] 28.75412 64.04239
> colSd(tmp5)
[1] 126.463668 4.317857 8.120861 6.900755 10.373265 7.007983
[7] 8.106836 12.546249 11.015411 11.215489 7.038185 NA
[13] 9.572778 7.032973 7.046679 6.892876 9.385419 9.329843
[19] 5.362287 8.002649
> colMax(tmp5)
[1] 468.51837 71.69563 83.21700 81.87684 88.08475 80.93704 87.36354
[8] 92.09056 92.07400 88.50966 79.85731 NA 85.31777 88.44406
[15] 91.25555 78.64152 82.68186 79.07675 75.35277 78.79638
> colMin(tmp5)
[1] 60.64668 58.01004 54.93261 59.98331 57.45242 59.12908 62.58267 56.27076
[9] 55.43762 56.75703 56.65757 NA 56.93576 66.73882 66.34172 59.07979
[17] 56.29492 52.82061 60.83721 55.81166
>
> Max(tmp5,na.rm=TRUE)
[1] 468.5184
> Min(tmp5,na.rm=TRUE)
[1] 52.82061
> mean(tmp5,na.rm=TRUE)
[1] 72.73851
> Sum(tmp5,na.rm=TRUE)
[1] 14474.96
> Var(tmp5,na.rm=TRUE)
[1] 870.0601
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.98882 68.91977 71.54117 67.97942 72.43478 69.33253 72.93452 71.54527
[9] 71.58716 66.82608
> rowSums(tmp5,na.rm=TRUE)
[1] 1879.776 1378.395 1430.823 1359.588 1448.696 1386.651 1458.690 1430.905
[9] 1431.743 1269.696
> rowVars(tmp5,na.rm=TRUE)
[1] 7820.79308 86.61478 106.96288 61.92127 50.42017 73.68819
[7] 51.62291 61.62392 123.25517 67.34138
> rowSd(tmp5,na.rm=TRUE)
[1] 88.435248 9.306706 10.342286 7.869007 7.100716 8.584183 7.184909
[8] 7.850090 11.102035 8.206179
> rowMax(tmp5,na.rm=TRUE)
[1] 468.51837 87.25550 91.25555 82.07288 88.08475 82.72412 92.09056
[8] 87.36354 92.07400 85.71079
> rowMin(tmp5,na.rm=TRUE)
[1] 60.39404 55.43762 52.82061 54.93261 61.75939 56.27076 56.75703 56.29492
[9] 55.81166 56.93576
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.20927 66.80516 69.96474 72.41186 75.21781 68.69234 73.52979
[8] 72.82687 72.03316 69.17321 69.41876 71.63415 71.06892 75.97938
[15] 78.15645 68.44271 67.46684 67.19944 69.54357 65.88537
> colSums(tmp5,na.rm=TRUE)
[1] 1092.0927 668.0516 699.6474 724.1186 752.1781 686.9234 735.2979
[8] 728.2687 720.3316 691.7321 694.1876 644.7074 710.6892 759.7938
[15] 781.5645 684.4271 674.6684 671.9944 695.4357 658.8537
> colVars(tmp5,na.rm=TRUE)
[1] 15993.05930 18.64389 65.94839 47.62042 107.60463 49.11182
[7] 65.72079 157.40837 121.33928 125.78719 49.53605 64.58307
[13] 91.63808 49.46271 49.65568 47.51174 88.08609 87.04597
[19] 28.75412 64.04239
> colSd(tmp5,na.rm=TRUE)
[1] 126.463668 4.317857 8.120861 6.900755 10.373265 7.007983
[7] 8.106836 12.546249 11.015411 11.215489 7.038185 8.036359
[13] 9.572778 7.032973 7.046679 6.892876 9.385419 9.329843
[19] 5.362287 8.002649
> colMax(tmp5,na.rm=TRUE)
[1] 468.51837 71.69563 83.21700 81.87684 88.08475 80.93704 87.36354
[8] 92.09056 92.07400 88.50966 79.85731 88.02548 85.31777 88.44406
[15] 91.25555 78.64152 82.68186 79.07675 75.35277 78.79638
> colMin(tmp5,na.rm=TRUE)
[1] 60.64668 58.01004 54.93261 59.98331 57.45242 59.12908 62.58267 56.27076
[9] 55.43762 56.75703 56.65757 62.62406 56.93576 66.73882 66.34172 59.07979
[17] 56.29492 52.82061 60.83721 55.81166
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.98882 68.91977 71.54117 67.97942 72.43478 69.33253 72.93452 71.54527
[9] 71.58716 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1879.776 1378.395 1430.823 1359.588 1448.696 1386.651 1458.690 1430.905
[9] 1431.743 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 7820.79308 86.61478 106.96288 61.92127 50.42017 73.68819
[7] 51.62291 61.62392 123.25517 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 88.435248 9.306706 10.342286 7.869007 7.100716 8.584183 7.184909
[8] 7.850090 11.102035 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 468.51837 87.25550 91.25555 82.07288 88.08475 82.72412 92.09056
[8] 87.36354 92.07400 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 60.39404 55.43762 52.82061 54.93261 61.75939 56.27076 56.75703 56.29492
[9] 55.81166 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.27795 66.26177 69.11096 73.79281 76.93880 69.67312 74.32626
[8] 74.13373 73.49058 69.35094 70.23909 NaN 72.63928 74.89812
[15] 77.68859 69.02989 67.33973 67.50264 68.89811 66.02554
> colSums(tmp5,na.rm=TRUE)
[1] 1028.5015 596.3560 621.9987 664.1353 692.4492 627.0581 668.9364
[8] 667.2036 661.4152 624.1585 632.1518 0.0000 653.7535 674.0830
[15] 699.1973 621.2690 606.0576 607.5238 620.0830 594.2298
> colVars(tmp5,na.rm=TRUE)
[1] 17703.16267 17.65261 65.99139 32.11895 87.73517 44.42919
[7] 66.79928 157.87085 112.61083 141.15520 48.15736 NA
[13] 75.35030 42.49272 53.40006 49.57194 98.91508 96.89250
[19] 27.66135 71.82664
> colSd(tmp5,na.rm=TRUE)
[1] 133.053232 4.201501 8.123508 5.667359 9.366705 6.665523
[7] 8.173083 12.564667 10.611825 11.880875 6.939550 NA
[13] 8.680455 6.518644 7.307535 7.040735 9.945606 9.843399
[19] 5.259405 8.475060
> colMax(tmp5,na.rm=TRUE)
[1] 468.51837 71.44806 83.21700 81.87684 88.08475 80.93704 87.36354
[8] 92.09056 92.07400 88.50966 79.85731 -Inf 85.31777 88.44406
[15] 91.25555 78.64152 82.68186 79.07675 75.10715 78.79638
> colMin(tmp5,na.rm=TRUE)
[1] 60.64668 58.01004 54.93261 65.28861 57.45242 59.12908 62.58267 56.27076
[9] 55.43762 56.75703 56.65757 Inf 57.01080 66.73882 66.34172 59.07979
[17] 56.29492 52.82061 60.83721 55.81166
>
>
>
>
> 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] 254.2449 158.0604 202.8239 325.3186 185.0685 302.2977 357.4338 157.8688
[9] 273.8527 234.2045
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 254.2449 158.0604 202.8239 325.3186 185.0685 302.2977 357.4338 157.8688
[9] 273.8527 234.2045
>
>
>
> 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] 5.684342e-14 2.842171e-14 8.526513e-14 -2.557954e-13 1.136868e-13
[6] -2.842171e-14 -2.842171e-14 2.273737e-13 1.705303e-13 -4.263256e-14
[11] 5.684342e-14 -5.684342e-14 0.000000e+00 -5.684342e-14 -1.136868e-13
[16] 4.263256e-14 1.989520e-13 -2.273737e-13 0.000000e+00 -9.947598e-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)
+ }
5 2
8 20
3 2
3 3
3 10
3 10
10 11
3 20
10 10
3 5
7 15
3 20
8 7
5 2
5 10
1 18
3 7
2 20
1 17
2 12
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] 3.064125
> Min(tmp)
[1] -2.665161
> mean(tmp)
[1] 0.02880785
> Sum(tmp)
[1] 2.880785
> Var(tmp)
[1] 1.085441
>
> rowMeans(tmp)
[1] 0.02880785
> rowSums(tmp)
[1] 2.880785
> rowVars(tmp)
[1] 1.085441
> rowSd(tmp)
[1] 1.041845
> rowMax(tmp)
[1] 3.064125
> rowMin(tmp)
[1] -2.665161
>
> colMeans(tmp)
[1] -0.45952361 -0.86611818 1.18600788 0.59833140 0.74195507 0.30050090
[7] -0.27954585 0.47242470 0.26367106 -2.03438334 0.33028427 0.38257691
[13] 0.34882786 0.63691554 -1.52859491 -0.98780117 -0.37319575 0.14150309
[19] 1.33462616 0.02290010 0.39716197 -0.06140156 -2.04324649 0.70847596
[25] -0.21936595 0.19854576 -0.40438585 1.72653034 -0.80799505 -0.27859669
[31] 0.61734025 0.87212399 0.43579201 0.20302921 0.91289050 1.14896206
[37] -0.38204712 0.53515942 1.78449847 1.47121840 -0.53673631 -0.12630167
[43] -1.05515790 0.89677896 2.17315442 -1.60352588 0.46916892 -0.20700279
[49] -0.42184098 -0.39087754 -1.06777698 -0.91731360 -0.15418522 1.00425341
[55] -0.12997240 -1.37686031 -0.74578026 0.71803140 -0.75044574 -2.66516095
[61] -0.79624650 0.11628001 -0.91970279 2.72836629 -0.24342449 0.46949671
[67] 0.23470000 0.25544541 -1.41784436 -1.55406694 0.31625762 1.59031220
[73] 1.03833050 -0.99120413 -0.22323873 0.16181718 -1.36718498 -1.54362632
[79] 1.31339303 -1.31604631 -0.20165394 -0.55161868 -0.98419149 1.35303380
[85] 0.26852759 -0.91332033 1.00807248 -0.11513874 0.23642682 0.65962217
[91] -0.77449361 1.81746956 -0.08792307 -0.38420635 -0.14223848 -1.41395571
[97] 1.99249482 0.52020802 -0.48076805 3.06412485
> colSums(tmp)
[1] -0.45952361 -0.86611818 1.18600788 0.59833140 0.74195507 0.30050090
[7] -0.27954585 0.47242470 0.26367106 -2.03438334 0.33028427 0.38257691
[13] 0.34882786 0.63691554 -1.52859491 -0.98780117 -0.37319575 0.14150309
[19] 1.33462616 0.02290010 0.39716197 -0.06140156 -2.04324649 0.70847596
[25] -0.21936595 0.19854576 -0.40438585 1.72653034 -0.80799505 -0.27859669
[31] 0.61734025 0.87212399 0.43579201 0.20302921 0.91289050 1.14896206
[37] -0.38204712 0.53515942 1.78449847 1.47121840 -0.53673631 -0.12630167
[43] -1.05515790 0.89677896 2.17315442 -1.60352588 0.46916892 -0.20700279
[49] -0.42184098 -0.39087754 -1.06777698 -0.91731360 -0.15418522 1.00425341
[55] -0.12997240 -1.37686031 -0.74578026 0.71803140 -0.75044574 -2.66516095
[61] -0.79624650 0.11628001 -0.91970279 2.72836629 -0.24342449 0.46949671
[67] 0.23470000 0.25544541 -1.41784436 -1.55406694 0.31625762 1.59031220
[73] 1.03833050 -0.99120413 -0.22323873 0.16181718 -1.36718498 -1.54362632
[79] 1.31339303 -1.31604631 -0.20165394 -0.55161868 -0.98419149 1.35303380
[85] 0.26852759 -0.91332033 1.00807248 -0.11513874 0.23642682 0.65962217
[91] -0.77449361 1.81746956 -0.08792307 -0.38420635 -0.14223848 -1.41395571
[97] 1.99249482 0.52020802 -0.48076805 3.06412485
> 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] -0.45952361 -0.86611818 1.18600788 0.59833140 0.74195507 0.30050090
[7] -0.27954585 0.47242470 0.26367106 -2.03438334 0.33028427 0.38257691
[13] 0.34882786 0.63691554 -1.52859491 -0.98780117 -0.37319575 0.14150309
[19] 1.33462616 0.02290010 0.39716197 -0.06140156 -2.04324649 0.70847596
[25] -0.21936595 0.19854576 -0.40438585 1.72653034 -0.80799505 -0.27859669
[31] 0.61734025 0.87212399 0.43579201 0.20302921 0.91289050 1.14896206
[37] -0.38204712 0.53515942 1.78449847 1.47121840 -0.53673631 -0.12630167
[43] -1.05515790 0.89677896 2.17315442 -1.60352588 0.46916892 -0.20700279
[49] -0.42184098 -0.39087754 -1.06777698 -0.91731360 -0.15418522 1.00425341
[55] -0.12997240 -1.37686031 -0.74578026 0.71803140 -0.75044574 -2.66516095
[61] -0.79624650 0.11628001 -0.91970279 2.72836629 -0.24342449 0.46949671
[67] 0.23470000 0.25544541 -1.41784436 -1.55406694 0.31625762 1.59031220
[73] 1.03833050 -0.99120413 -0.22323873 0.16181718 -1.36718498 -1.54362632
[79] 1.31339303 -1.31604631 -0.20165394 -0.55161868 -0.98419149 1.35303380
[85] 0.26852759 -0.91332033 1.00807248 -0.11513874 0.23642682 0.65962217
[91] -0.77449361 1.81746956 -0.08792307 -0.38420635 -0.14223848 -1.41395571
[97] 1.99249482 0.52020802 -0.48076805 3.06412485
> colMin(tmp)
[1] -0.45952361 -0.86611818 1.18600788 0.59833140 0.74195507 0.30050090
[7] -0.27954585 0.47242470 0.26367106 -2.03438334 0.33028427 0.38257691
[13] 0.34882786 0.63691554 -1.52859491 -0.98780117 -0.37319575 0.14150309
[19] 1.33462616 0.02290010 0.39716197 -0.06140156 -2.04324649 0.70847596
[25] -0.21936595 0.19854576 -0.40438585 1.72653034 -0.80799505 -0.27859669
[31] 0.61734025 0.87212399 0.43579201 0.20302921 0.91289050 1.14896206
[37] -0.38204712 0.53515942 1.78449847 1.47121840 -0.53673631 -0.12630167
[43] -1.05515790 0.89677896 2.17315442 -1.60352588 0.46916892 -0.20700279
[49] -0.42184098 -0.39087754 -1.06777698 -0.91731360 -0.15418522 1.00425341
[55] -0.12997240 -1.37686031 -0.74578026 0.71803140 -0.75044574 -2.66516095
[61] -0.79624650 0.11628001 -0.91970279 2.72836629 -0.24342449 0.46949671
[67] 0.23470000 0.25544541 -1.41784436 -1.55406694 0.31625762 1.59031220
[73] 1.03833050 -0.99120413 -0.22323873 0.16181718 -1.36718498 -1.54362632
[79] 1.31339303 -1.31604631 -0.20165394 -0.55161868 -0.98419149 1.35303380
[85] 0.26852759 -0.91332033 1.00807248 -0.11513874 0.23642682 0.65962217
[91] -0.77449361 1.81746956 -0.08792307 -0.38420635 -0.14223848 -1.41395571
[97] 1.99249482 0.52020802 -0.48076805 3.06412485
> colMedians(tmp)
[1] -0.45952361 -0.86611818 1.18600788 0.59833140 0.74195507 0.30050090
[7] -0.27954585 0.47242470 0.26367106 -2.03438334 0.33028427 0.38257691
[13] 0.34882786 0.63691554 -1.52859491 -0.98780117 -0.37319575 0.14150309
[19] 1.33462616 0.02290010 0.39716197 -0.06140156 -2.04324649 0.70847596
[25] -0.21936595 0.19854576 -0.40438585 1.72653034 -0.80799505 -0.27859669
[31] 0.61734025 0.87212399 0.43579201 0.20302921 0.91289050 1.14896206
[37] -0.38204712 0.53515942 1.78449847 1.47121840 -0.53673631 -0.12630167
[43] -1.05515790 0.89677896 2.17315442 -1.60352588 0.46916892 -0.20700279
[49] -0.42184098 -0.39087754 -1.06777698 -0.91731360 -0.15418522 1.00425341
[55] -0.12997240 -1.37686031 -0.74578026 0.71803140 -0.75044574 -2.66516095
[61] -0.79624650 0.11628001 -0.91970279 2.72836629 -0.24342449 0.46949671
[67] 0.23470000 0.25544541 -1.41784436 -1.55406694 0.31625762 1.59031220
[73] 1.03833050 -0.99120413 -0.22323873 0.16181718 -1.36718498 -1.54362632
[79] 1.31339303 -1.31604631 -0.20165394 -0.55161868 -0.98419149 1.35303380
[85] 0.26852759 -0.91332033 1.00807248 -0.11513874 0.23642682 0.65962217
[91] -0.77449361 1.81746956 -0.08792307 -0.38420635 -0.14223848 -1.41395571
[97] 1.99249482 0.52020802 -0.48076805 3.06412485
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.4595236 -0.8661182 1.186008 0.5983314 0.7419551 0.3005009 -0.2795458
[2,] -0.4595236 -0.8661182 1.186008 0.5983314 0.7419551 0.3005009 -0.2795458
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.4724247 0.2636711 -2.034383 0.3302843 0.3825769 0.3488279 0.6369155
[2,] 0.4724247 0.2636711 -2.034383 0.3302843 0.3825769 0.3488279 0.6369155
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.528595 -0.9878012 -0.3731957 0.1415031 1.334626 0.0229001 0.397162
[2,] -1.528595 -0.9878012 -0.3731957 0.1415031 1.334626 0.0229001 0.397162
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.06140156 -2.043246 0.708476 -0.219366 0.1985458 -0.4043859 1.72653
[2,] -0.06140156 -2.043246 0.708476 -0.219366 0.1985458 -0.4043859 1.72653
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.807995 -0.2785967 0.6173403 0.872124 0.435792 0.2030292 0.9128905
[2,] -0.807995 -0.2785967 0.6173403 0.872124 0.435792 0.2030292 0.9128905
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.148962 -0.3820471 0.5351594 1.784498 1.471218 -0.5367363 -0.1263017
[2,] 1.148962 -0.3820471 0.5351594 1.784498 1.471218 -0.5367363 -0.1263017
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.055158 0.896779 2.173154 -1.603526 0.4691689 -0.2070028 -0.421841
[2,] -1.055158 0.896779 2.173154 -1.603526 0.4691689 -0.2070028 -0.421841
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.3908775 -1.067777 -0.9173136 -0.1541852 1.004253 -0.1299724 -1.37686
[2,] -0.3908775 -1.067777 -0.9173136 -0.1541852 1.004253 -0.1299724 -1.37686
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.7457803 0.7180314 -0.7504457 -2.665161 -0.7962465 0.11628 -0.9197028
[2,] -0.7457803 0.7180314 -0.7504457 -2.665161 -0.7962465 0.11628 -0.9197028
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 2.728366 -0.2434245 0.4694967 0.2347 0.2554454 -1.417844 -1.554067
[2,] 2.728366 -0.2434245 0.4694967 0.2347 0.2554454 -1.417844 -1.554067
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.3162576 1.590312 1.03833 -0.9912041 -0.2232387 0.1618172 -1.367185
[2,] 0.3162576 1.590312 1.03833 -0.9912041 -0.2232387 0.1618172 -1.367185
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -1.543626 1.313393 -1.316046 -0.2016539 -0.5516187 -0.9841915 1.353034
[2,] -1.543626 1.313393 -1.316046 -0.2016539 -0.5516187 -0.9841915 1.353034
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.2685276 -0.9133203 1.008072 -0.1151387 0.2364268 0.6596222 -0.7744936
[2,] 0.2685276 -0.9133203 1.008072 -0.1151387 0.2364268 0.6596222 -0.7744936
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 1.81747 -0.08792307 -0.3842064 -0.1422385 -1.413956 1.992495 0.520208
[2,] 1.81747 -0.08792307 -0.3842064 -0.1422385 -1.413956 1.992495 0.520208
[,99] [,100]
[1,] -0.4807681 3.064125
[2,] -0.4807681 3.064125
>
>
> Max(tmp2)
[1] 3.34371
> Min(tmp2)
[1] -2.369733
> mean(tmp2)
[1] 0.03493987
> Sum(tmp2)
[1] 3.493987
> Var(tmp2)
[1] 1.265055
>
> rowMeans(tmp2)
[1] 0.410792985 -2.153846840 -1.415684591 0.526182404 -0.543262664
[6] -0.792437357 0.437411703 3.343710216 -0.195913093 -0.359515083
[11] -0.086045631 1.703589222 -1.576934242 -0.201884776 0.255220180
[16] -1.630835204 0.675888083 0.426084725 0.267432721 -0.525657872
[21] -0.739704964 1.091036067 -0.084098129 -0.670670634 1.239637546
[26] 0.918580536 1.144538612 -1.125866472 -1.754546586 -1.606577141
[31] -0.090624863 1.197082094 -0.692206403 -1.194649838 -0.135869866
[36] -1.480184965 -1.127152580 -1.048190581 0.562835580 1.997801921
[41] 0.523249274 0.547796949 0.662918347 0.893916618 0.536044859
[46] 0.845193320 -1.081163319 0.491222837 -0.933549777 0.799380014
[51] 1.152741432 -1.154025681 0.939426329 -0.868930852 1.336213613
[56] 0.303793578 0.235776569 -0.235477356 -1.010985650 1.453829387
[61] -1.263845531 -0.329559492 0.008326412 0.766652177 -0.939498702
[66] -0.248471024 0.249056891 -0.287425021 1.178579954 -0.942099900
[71] -0.184001504 -0.701946668 -0.596726404 1.055712123 0.923502651
[76] 0.941705571 1.782316304 -2.369732667 1.865859604 2.342727895
[81] 1.714976430 -0.869294576 -0.407495027 -1.798433318 -0.278218082
[86] -1.585070083 1.690652600 0.079453540 -1.086018314 1.723596217
[91] -0.646549419 -0.248195058 -1.794675847 -0.654814152 1.226616297
[96] -0.449596997 0.542609047 2.471687563 -0.306606602 0.515395645
> rowSums(tmp2)
[1] 0.410792985 -2.153846840 -1.415684591 0.526182404 -0.543262664
[6] -0.792437357 0.437411703 3.343710216 -0.195913093 -0.359515083
[11] -0.086045631 1.703589222 -1.576934242 -0.201884776 0.255220180
[16] -1.630835204 0.675888083 0.426084725 0.267432721 -0.525657872
[21] -0.739704964 1.091036067 -0.084098129 -0.670670634 1.239637546
[26] 0.918580536 1.144538612 -1.125866472 -1.754546586 -1.606577141
[31] -0.090624863 1.197082094 -0.692206403 -1.194649838 -0.135869866
[36] -1.480184965 -1.127152580 -1.048190581 0.562835580 1.997801921
[41] 0.523249274 0.547796949 0.662918347 0.893916618 0.536044859
[46] 0.845193320 -1.081163319 0.491222837 -0.933549777 0.799380014
[51] 1.152741432 -1.154025681 0.939426329 -0.868930852 1.336213613
[56] 0.303793578 0.235776569 -0.235477356 -1.010985650 1.453829387
[61] -1.263845531 -0.329559492 0.008326412 0.766652177 -0.939498702
[66] -0.248471024 0.249056891 -0.287425021 1.178579954 -0.942099900
[71] -0.184001504 -0.701946668 -0.596726404 1.055712123 0.923502651
[76] 0.941705571 1.782316304 -2.369732667 1.865859604 2.342727895
[81] 1.714976430 -0.869294576 -0.407495027 -1.798433318 -0.278218082
[86] -1.585070083 1.690652600 0.079453540 -1.086018314 1.723596217
[91] -0.646549419 -0.248195058 -1.794675847 -0.654814152 1.226616297
[96] -0.449596997 0.542609047 2.471687563 -0.306606602 0.515395645
> 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] 0.410792985 -2.153846840 -1.415684591 0.526182404 -0.543262664
[6] -0.792437357 0.437411703 3.343710216 -0.195913093 -0.359515083
[11] -0.086045631 1.703589222 -1.576934242 -0.201884776 0.255220180
[16] -1.630835204 0.675888083 0.426084725 0.267432721 -0.525657872
[21] -0.739704964 1.091036067 -0.084098129 -0.670670634 1.239637546
[26] 0.918580536 1.144538612 -1.125866472 -1.754546586 -1.606577141
[31] -0.090624863 1.197082094 -0.692206403 -1.194649838 -0.135869866
[36] -1.480184965 -1.127152580 -1.048190581 0.562835580 1.997801921
[41] 0.523249274 0.547796949 0.662918347 0.893916618 0.536044859
[46] 0.845193320 -1.081163319 0.491222837 -0.933549777 0.799380014
[51] 1.152741432 -1.154025681 0.939426329 -0.868930852 1.336213613
[56] 0.303793578 0.235776569 -0.235477356 -1.010985650 1.453829387
[61] -1.263845531 -0.329559492 0.008326412 0.766652177 -0.939498702
[66] -0.248471024 0.249056891 -0.287425021 1.178579954 -0.942099900
[71] -0.184001504 -0.701946668 -0.596726404 1.055712123 0.923502651
[76] 0.941705571 1.782316304 -2.369732667 1.865859604 2.342727895
[81] 1.714976430 -0.869294576 -0.407495027 -1.798433318 -0.278218082
[86] -1.585070083 1.690652600 0.079453540 -1.086018314 1.723596217
[91] -0.646549419 -0.248195058 -1.794675847 -0.654814152 1.226616297
[96] -0.449596997 0.542609047 2.471687563 -0.306606602 0.515395645
> rowMin(tmp2)
[1] 0.410792985 -2.153846840 -1.415684591 0.526182404 -0.543262664
[6] -0.792437357 0.437411703 3.343710216 -0.195913093 -0.359515083
[11] -0.086045631 1.703589222 -1.576934242 -0.201884776 0.255220180
[16] -1.630835204 0.675888083 0.426084725 0.267432721 -0.525657872
[21] -0.739704964 1.091036067 -0.084098129 -0.670670634 1.239637546
[26] 0.918580536 1.144538612 -1.125866472 -1.754546586 -1.606577141
[31] -0.090624863 1.197082094 -0.692206403 -1.194649838 -0.135869866
[36] -1.480184965 -1.127152580 -1.048190581 0.562835580 1.997801921
[41] 0.523249274 0.547796949 0.662918347 0.893916618 0.536044859
[46] 0.845193320 -1.081163319 0.491222837 -0.933549777 0.799380014
[51] 1.152741432 -1.154025681 0.939426329 -0.868930852 1.336213613
[56] 0.303793578 0.235776569 -0.235477356 -1.010985650 1.453829387
[61] -1.263845531 -0.329559492 0.008326412 0.766652177 -0.939498702
[66] -0.248471024 0.249056891 -0.287425021 1.178579954 -0.942099900
[71] -0.184001504 -0.701946668 -0.596726404 1.055712123 0.923502651
[76] 0.941705571 1.782316304 -2.369732667 1.865859604 2.342727895
[81] 1.714976430 -0.869294576 -0.407495027 -1.798433318 -0.278218082
[86] -1.585070083 1.690652600 0.079453540 -1.086018314 1.723596217
[91] -0.646549419 -0.248195058 -1.794675847 -0.654814152 1.226616297
[96] -0.449596997 0.542609047 2.471687563 -0.306606602 0.515395645
>
> colMeans(tmp2)
[1] 0.03493987
> colSums(tmp2)
[1] 3.493987
> colVars(tmp2)
[1] 1.265055
> colSd(tmp2)
[1] 1.124747
> colMax(tmp2)
[1] 3.34371
> colMin(tmp2)
[1] -2.369733
> colMedians(tmp2)
[1] -0.08833525
> colRanges(tmp2)
[,1]
[1,] -2.369733
[2,] 3.343710
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.90321421 0.55303553 0.06006065 -1.06019711 -5.39864799 2.79206532
[7] -1.18518736 0.23661419 -2.35643615 2.70233553
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.7167334
[2,] -1.0534373
[3,] 0.8792834
[4,] 1.3291471
[5,] 1.7011647
>
> rowApply(tmp,sum)
[1] -1.2381110 -5.5693007 -2.9784271 -0.8762896 0.3555279 -0.9584894
[7] -1.3440903 3.8404704 0.3295105 7.6860560
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 9 5 10 1 8 1 8 2 10
[2,] 3 2 2 7 9 7 9 9 8 1
[3,] 9 7 10 6 2 6 5 6 3 5
[4,] 5 8 1 5 5 9 6 2 10 3
[5,] 2 1 9 1 7 4 4 7 4 2
[6,] 10 3 4 2 6 3 10 10 7 9
[7,] 8 4 6 4 8 1 2 3 9 6
[8,] 6 5 7 3 4 10 3 1 6 4
[9,] 1 6 3 8 10 2 7 5 1 7
[10,] 4 10 8 9 3 5 8 4 5 8
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.93786167 0.58142053 -2.45967161 1.38496570 0.68133885 2.49492138
[7] -1.26311561 -1.71204733 -0.52832135 0.15518655 -1.73842638 2.72361029
[13] -3.38823289 -3.17165855 0.56217343 -1.27939838 -0.12080541 -0.02592554
[19] -0.58521916 -2.81928293
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.0646992
[2,] -0.3016661
[3,] 0.4541736
[4,] 1.8224167
[5,] 2.0276366
>
> rowApply(tmp,sum)
[1] -3.5380147 -1.7091627 -1.6865197 0.5114004 -2.1483299
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 1 14 20 20 10
[2,] 4 8 19 19 2
[3,] 7 5 9 2 17
[4,] 10 20 15 8 12
[5,] 19 2 2 18 20
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -2.0646992 -0.7608957 -0.6994668 -0.38585838 1.082993 1.0766126
[2,] 0.4541736 -0.6740044 -0.8454214 1.71576153 -1.552189 1.0226274
[3,] 1.8224167 1.5899824 -0.1527516 0.50530934 -1.787763 0.7382908
[4,] 2.0276366 1.7338780 -1.4811895 -0.36392551 1.261534 0.5675898
[5,] -0.3016661 -1.3075399 0.7191577 -0.08632128 1.676765 -0.9101992
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.04276579 -0.2100720 -0.75144151 -0.5460099 -0.7459752 1.4331318
[2,] -0.75961033 1.2337037 -0.16520806 0.1322438 -0.5374323 1.5645035
[3,] 0.06726766 -1.9516974 0.27159962 -0.1311848 -0.9353069 -0.6084106
[4,] 0.99056937 -0.6801857 -0.03711302 1.1050809 0.8548630 -0.4742824
[5,] -1.60410809 -0.1037959 0.15384162 -0.4049434 -0.3745751 0.8086679
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.2974664 -0.81949384 0.34980099 -1.4965303 -0.6747923 0.6999523
[2,] -0.4804403 -1.42320191 -0.73350973 0.5419469 1.6512281 -1.6246455
[3,] 0.2944268 -1.19806499 0.79796211 0.4671166 -1.0232571 0.6438106
[4,] -2.4832893 -0.03022116 -0.09477449 -0.1806814 -1.4009056 0.8201742
[5,] -0.4214636 0.29932334 0.24269456 -0.6112502 1.3269215 -0.5652171
[,19] [,20]
[1,] 0.7561818 0.4732490
[2,] -0.8949314 -0.3347568
[3,] -0.4044117 -0.6918541
[4,] -0.5377183 -1.0856391
[5,] 0.4956605 -1.1802820
>
>
> 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 : 653 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 -1.413345 0.02311463 0.1743926 -1.175193 1.983735 -1.147002 -0.7007807
col8 col9 col10 col11 col12 col13 col14
row1 1.44153 0.4292802 -1.245339 -1.17327 0.3114464 -0.5942393 0.3088296
col15 col16 col17 col18 col19 col20
row1 -0.6830937 0.09315442 0.5962796 -1.219265 1.540194 0.4240831
> tmp[,"col10"]
col10
row1 -1.2453388
row2 -0.5908774
row3 -1.6223807
row4 1.8856123
row5 -0.2328131
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -1.413345 0.02311463 0.1743926 -1.175193 1.98373489 -1.1470015 -0.7007807
row5 -1.740906 -1.67001623 0.8982302 -1.722991 0.07207801 0.9330117 1.4701277
col8 col9 col10 col11 col12 col13
row1 1.44152961 0.4292802 -1.2453388 -1.1732696 0.3114464 -0.5942393
row5 -0.09898201 -0.7352398 -0.2328131 0.7286445 1.1901583 0.4670793
col14 col15 col16 col17 col18 col19 col20
row1 0.3088296 -0.6830937 0.09315442 0.5962796 -1.219265 1.5401938 0.4240831
row5 0.2051780 -0.4823789 0.79803341 -1.3130856 -2.348589 0.2832766 0.8478910
> tmp[,c("col6","col20")]
col6 col20
row1 -1.1470015 0.424083141
row2 0.7020283 0.067518248
row3 -0.2599374 0.004306276
row4 -1.4678238 0.176667690
row5 0.9330117 0.847890991
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.1470015 0.4240831
row5 0.9330117 0.8478910
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.95161 50.7647 49.68179 50.74509 49.03538 105.1785 52.3057 49.02319
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.25734 51.52828 48.81017 49.85032 49.08245 51.51225 50.08628 49.46157
col17 col18 col19 col20
row1 49.7203 49.47482 51.53559 105.1965
> tmp[,"col10"]
col10
row1 51.52828
row2 29.60878
row3 30.50173
row4 30.40431
row5 47.76530
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.95161 50.76470 49.68179 50.74509 49.03538 105.1785 52.30570 49.02319
row5 48.77405 49.32431 52.86860 50.77981 48.61784 104.5356 51.10892 52.51679
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.25734 51.52828 48.81017 49.85032 49.08245 51.51225 50.08628 49.46157
row5 49.76073 47.76530 50.36718 52.58340 48.91893 51.88500 49.16797 49.44978
col17 col18 col19 col20
row1 49.72030 49.47482 51.53559 105.1965
row5 50.60567 51.55164 50.96913 107.0549
> tmp[,c("col6","col20")]
col6 col20
row1 105.17854 105.19650
row2 74.65128 74.97299
row3 74.77154 73.58922
row4 75.08179 74.62717
row5 104.53564 107.05488
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.1785 105.1965
row5 104.5356 107.0549
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.1785 105.1965
row5 104.5356 107.0549
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.5654465
[2,] 0.6456950
[3,] -1.0562163
[4,] -0.4665957
[5,] 0.1046191
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.12230494 -0.1224298
[2,] 0.09225485 0.5213340
[3,] -0.79793146 -0.7775219
[4,] 1.29192061 -0.9801348
[5,] 1.00898875 -0.5244977
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.1157619 -1.24064032
[2,] -0.7080717 -0.09646693
[3,] 1.8410540 1.43552380
[4,] -0.1552134 0.34983154
[5,] -0.6983913 -0.69886084
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.1157619
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.1157619
[2,] -0.7080717
>
>
>
> 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 -1.488061 1.694429 1.7849434 0.1092851 -0.397498 -0.1630881 1.1919036
row1 -0.568061 -1.064023 0.3170222 -0.2671569 1.562688 -0.5493752 -0.3035737
[,8] [,9] [,10] [,11] [,12] [,13]
row3 0.7896128 -0.4644234 -0.7339697 1.9988340 0.03655601 0.7295929
row1 -1.0801015 -0.6179196 -1.5085749 -0.8784836 0.40129735 0.1354333
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 0.3166851 -1.5371878 -2.7391087 0.9280158 0.1308433 0.1658024 0.0915611
row1 -0.7523492 0.3777399 -0.1469046 0.4776341 1.6784185 0.4922835 -0.5847796
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.260869 -0.01683949 0.06803107 -1.974525 -0.2879341 0.6226623 2.356096
[,8] [,9] [,10]
row2 -0.8297427 0.2981178 -0.832717
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.601227 -0.1079251 0.7140358 -1.36717 0.1254525 0.3167442 -0.2173431
[,8] [,9] [,10] [,11] [,12] [,13]
row5 -0.07945149 1.159802 -0.6485197 -0.2818446 -0.8464632 -0.1269034
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.5163808 0.2020084 -2.222944 -0.1113588 -1.028228 1.045396 -0.9600002
>
>
> 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: 0x5c02470bf600>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM311a493c4b58c8"
[2] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM311a497d02e45c"
[3] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM311a492ea221b3"
[4] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM311a4926b11721"
[5] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM311a4979070142"
[6] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM311a4936e38bce"
[7] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM311a4946fb878a"
[8] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM311a492f9e13dd"
[9] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM311a492a054f7d"
[10] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM311a492d62324d"
[11] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM311a495537c264"
[12] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM311a493de8d49a"
[13] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM311a495bd2cffe"
[14] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM311a4964402dc3"
[15] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM311a492a5e56ad"
>
>
> ### 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: 0x5c0246db8f10>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5c0246db8f10>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5c0246db8f10>
> rowMedians(tmp)
[1] -0.201418194 0.072130948 -0.105640905 0.118084681 0.007030350
[6] -0.329598568 -0.141266232 -0.068921137 -0.269325185 -0.143522402
[11] -0.547567892 -0.028455285 -0.278396285 -0.483191351 -0.225337392
[16] 0.050322275 0.440453209 -0.830050037 0.186367112 -0.233167482
[21] 0.271246313 0.088348160 -0.167525751 0.351710276 -0.483930125
[26] 0.173518726 -0.226072617 0.126557879 0.893203031 -0.134595262
[31] 0.514404945 -0.104965926 0.269525317 -0.117016217 -0.257163921
[36] -0.383627315 0.561164037 -0.389826931 -0.231952654 -0.417676631
[41] 0.244425978 -0.293363513 0.022680077 -0.029248025 -0.255727565
[46] 0.078110261 -0.037924268 -0.335215466 -0.355871389 -0.045102519
[51] -0.553454328 -0.388268605 -0.158103498 0.295935769 -0.343002872
[56] -0.156962072 -0.293615122 -0.174967269 -0.154846926 0.087979874
[61] -0.587161517 0.244843001 -0.107156205 0.039711272 -0.138358305
[66] 0.092544906 0.183390955 0.037703694 -0.057776366 -0.125867224
[71] -0.170248512 -0.006974548 -0.760326621 0.208226944 -0.012328904
[76] 0.120980352 0.111007146 0.664495662 0.256448483 -0.566084017
[81] -0.313248733 0.270467493 -0.003354828 -0.428131278 0.075264357
[86] 0.197064449 -0.061641457 -0.205153223 0.638373032 0.465839532
[91] 0.054096042 0.285156150 0.276012022 0.430328250 0.045398008
[96] 0.153524238 0.045881942 -0.047562707 -0.195446168 0.374987152
[101] -0.050092621 0.140284526 -0.062195752 -0.160281924 -0.544054369
[106] -0.023808544 -0.636792875 0.331341065 -0.243014146 0.252771510
[111] 0.649189327 0.022086201 -0.461091662 0.343432033 0.252872295
[116] -0.450195334 0.633141014 0.223868906 0.364242835 -0.380040356
[121] 0.370519370 0.722900592 -0.141685379 0.201008358 -0.315965291
[126] 0.230392761 0.283905085 0.074488978 0.030206138 -0.359845259
[131] 0.013831497 0.007688149 0.398611787 -0.062996145 -0.111426221
[136] -0.150125180 -0.027977918 0.531877575 0.411282072 0.146803268
[141] 0.072323775 0.097609256 -0.147880826 -0.000902812 0.042861619
[146] -0.022191403 0.020135452 0.195247321 0.037779120 0.352726172
[151] -0.308588084 0.421468256 0.092761880 0.089939438 -0.270774298
[156] -0.045936150 -0.370364021 0.058734056 -0.195795579 0.286235627
[161] 0.155367052 -0.052362505 -0.539481096 0.543548419 0.200425029
[166] 0.172895035 -0.224901908 -0.077367224 -0.323598753 0.077083951
[171] -0.678268052 0.279048302 0.027205013 0.510310172 -0.114314988
[176] 0.052196206 -0.032551925 -0.148916979 -0.497293524 -0.514544625
[181] -0.046175527 0.235700576 0.657157308 -0.259485027 0.028588112
[186] -0.086792703 0.055634021 -0.108013929 -0.306736830 -0.119060280
[191] 0.482470593 -0.226180619 -0.451501968 -0.317777118 -0.033624514
[196] -0.111552571 0.165330401 -0.082853319 -0.223521262 0.295938338
[201] 0.251518313 -0.167511507 -0.266612296 -0.259026248 -0.301291857
[206] 0.164408265 -0.048031253 -0.474919757 -0.246266325 -0.290783064
[211] 0.238694598 -0.415974607 0.029761686 0.094852201 -0.147544311
[216] 0.247327731 0.368626016 0.623628976 -0.377312571 -0.143422187
[221] -0.056358661 0.085617770 -0.579398723 -0.501149143 -0.051205557
[226] 0.271579940 0.167288078 -0.011954844 0.199211278 0.127031004
>
> proc.time()
user system elapsed
1.261 0.652 1.902
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: 0x5826aa7262a0>
> .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: 0x5826aa7262a0>
> .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: 0x5826aa7262a0>
> .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: 0x5826aa7262a0>
> 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: 0x5826a9d9d920>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5826a9d9d920>
> .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: 0x5826a9d9d920>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5826a9d9d920>
> .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: 0x5826a9d9d920>
> 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: 0x5826aa72bd80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5826aa72bd80>
> .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: 0x5826aa72bd80>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5826aa72bd80>
> .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: 0x5826aa72bd80>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5826aa72bd80>
> .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: 0x5826aa72bd80>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5826aa72bd80>
> .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: 0x5826aa72bd80>
> 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: 0x5826aa72f0b0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5826aa72f0b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5826aa72f0b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5826aa72f0b0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile311b1515abfac0" "BufferedMatrixFile311b155b0f259c"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile311b1515abfac0" "BufferedMatrixFile311b155b0f259c"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5826aa8871d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5826aa8871d0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5826aa8871d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5826aa8871d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5826aa8871d0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5826aa8871d0>
> .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: 0x5826a94a4ba0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5826a94a4ba0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5826a94a4ba0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5826a94a4ba0>
> 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: 0x5826a956a180>
> .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: 0x5826a956a180>
> rm(P)
>
> proc.time()
user system elapsed
0.241 0.046 0.275
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
0.230 0.039 0.257