Ben Bolstad
| Snapshot Date: 2025-01-20 13:40 -0500 (Mon, 20 Jan 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 824836d |
| git_last_commit_date: 2024-12-14 17:47:34 -0500 (Sat, 14 Dec 2024) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-01-21 11:39 -0500 (Tue, 21 Jan 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | R Under development (unstable) (2024-10-21 r87258) -- "Unsuffered Consequences" | 4777 |
| palomino7 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2024-10-26 r87273 ucrt) -- "Unsuffered Consequences" | 4502 |
| lconway | macOS 12.7.1 Monterey | x86_64 | R Under development (unstable) (2024-11-20 r87352) -- "Unsuffered Consequences" | 4467 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | R Under development (unstable) (2024-11-20 r87352) -- "Unsuffered Consequences" | 4422 |
| kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | R Under development (unstable) (2024-11-24 r87369) -- "Unsuffered Consequences" | 4406 |
| 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 246/2286 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.71.1 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.1 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| kunpeng2 | Linux (openEuler 22.03 LTS-SP1) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.71.1 |
| Command: /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.21-bioc/R/site-library --timings BufferedMatrix_1.71.1.tar.gz |
| StartedAt: 2025-01-20 20:23:45 -0500 (Mon, 20 Jan 2025) |
| EndedAt: 2025-01-20 20:24:10 -0500 (Mon, 20 Jan 2025) |
| EllapsedTime: 25.1 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.21-bioc/R/site-library --timings BufferedMatrix_1.71.1.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2024-10-21 r87258)
* 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 ‘1.71.1’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘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-3.21-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.21-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-3.21-bioc/R/include" -DNDEBUG -I/usr/local/include -DSTRICT_R_HEADERS=1 -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.21-bioc/R/include" -DNDEBUG -I/usr/local/include -DSTRICT_R_HEADERS=1 -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-3.21-bioc/R/include" -DNDEBUG -I/usr/local/include -DSTRICT_R_HEADERS=1 -fpic -g -O2 -Wall -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"/home/biocbuild/bbs-3.21-bioc/R/include" -DNDEBUG -I/usr/local/include -DSTRICT_R_HEADERS=1 -fpic -g -O2 -Wall -c init_package.c -o init_package.o
gcc -shared -L/home/biocbuild/bbs-3.21-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-3.21-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.21-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 Under development (unstable) (2024-10-21 r87258) -- "Unsuffered Consequences"
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
0.236 0.056 0.279
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2024-10-21 r87258) -- "Unsuffered Consequences"
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-3.21-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 478210 25.6 1046370 55.9 639888 34.2
Vcells 884339 6.8 8388608 64.0 2080978 15.9
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Mon Jan 20 20:24:00 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 Jan 20 20:24:00 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: 0x576e20b919c0>
>
>
>
> 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 Jan 20 20:24:00 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 Jan 20 20:24:01 2025"
>
> ColMode(tmp2)
<pointer: 0x576e20b919c0>
>
>
>
> ### 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,] 100.1238109 0.7449397 -0.3666194 -0.4624012
[2,] 0.3023793 0.2710464 0.5523029 0.1780288
[3,] -1.2451704 1.5228380 -1.8009533 1.4087322
[4,] 1.0522399 1.4118618 -1.6783820 0.1950529
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.1238109 0.7449397 0.3666194 0.4624012
[2,] 0.3023793 0.2710464 0.5523029 0.1780288
[3,] 1.2451704 1.5228380 1.8009533 1.4087322
[4,] 1.0522399 1.4118618 1.6783820 0.1950529
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0061886 0.8630989 0.6054910 0.6800009
[2,] 0.5498903 0.5206211 0.7431708 0.4219346
[3,] 1.1158721 1.2340332 1.3419960 1.1869003
[4,] 1.0257874 1.1882179 1.2955238 0.4416479
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.18570 34.37593 31.42153 32.26241
[2,] 30.80128 30.47726 32.98401 29.39737
[3,] 37.40389 38.86317 40.22091 38.27773
[4,] 36.31011 38.29404 39.63362 29.61153
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x576e22b20e40>
> exp(tmp5)
<pointer: 0x576e22b20e40>
> log(tmp5,2)
<pointer: 0x576e22b20e40>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.6945
> Min(tmp5)
[1] 55.1179
> mean(tmp5)
[1] 74.06855
> Sum(tmp5)
[1] 14813.71
> Var(tmp5)
[1] 858.5224
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.76251 72.22281 73.21759 69.93505 73.95225 72.14993 70.04858 75.18907
[9] 68.67127 72.53639
> rowSums(tmp5)
[1] 1855.250 1444.456 1464.352 1398.701 1479.045 1442.999 1400.972 1503.781
[9] 1373.425 1450.728
> rowVars(tmp5)
[1] 7898.73218 107.12247 84.88526 65.13267 74.25714 66.56361
[7] 55.28160 78.87186 66.59853 48.90025
> rowSd(tmp5)
[1] 88.874812 10.349998 9.213320 8.070481 8.617258 8.158653 7.435159
[8] 8.880983 8.160793 6.992872
> rowMax(tmp5)
[1] 468.69453 92.58083 85.30024 85.21234 87.33477 91.21627 82.73061
[8] 92.81741 81.69914 87.24253
> rowMin(tmp5)
[1] 59.47684 55.11790 55.27765 55.11989 58.76348 57.45552 57.11224 56.87671
[9] 55.15672 60.64187
>
> colMeans(tmp5)
[1] 109.92020 74.30353 74.40210 69.30233 72.22605 71.00831 70.97366
[8] 74.92273 67.48442 70.10366 73.57296 69.76465 74.05839 68.28870
[15] 74.07108 73.63095 72.87358 71.13179 76.96351 72.36831
> colSums(tmp5)
[1] 1099.2020 743.0353 744.0210 693.0233 722.2605 710.0831 709.7366
[8] 749.2273 674.8442 701.0366 735.7296 697.6465 740.5839 682.8870
[15] 740.7108 736.3095 728.7358 711.3179 769.6351 723.6831
> colVars(tmp5)
[1] 15950.20823 46.17671 68.91798 71.69276 77.23276 24.00263
[7] 98.99889 103.60929 46.91475 103.65449 43.61332 130.68827
[13] 41.65618 69.92723 104.63391 106.10289 57.08522 87.90682
[19] 71.97907 51.15544
> colSd(tmp5)
[1] 126.294134 6.795345 8.301686 8.467158 8.788217 4.899248
[7] 9.949819 10.178865 6.849434 10.181085 6.604038 11.431897
[13] 6.454160 8.362250 10.229072 10.300626 7.555476 9.375864
[19] 8.484048 7.152303
> colMax(tmp5)
[1] 468.69453 81.39409 85.27023 81.69914 85.60537 76.68790 87.24253
[8] 92.81741 78.32326 85.30024 85.10121 90.51586 85.02740 82.79887
[15] 92.58083 85.21234 87.33477 83.50738 91.21627 83.34273
> colMin(tmp5)
[1] 57.62254 63.43442 63.22028 57.11224 55.15672 59.52155 55.11790 60.77152
[9] 57.45552 55.11989 63.06893 55.27765 65.24533 55.52618 61.88555 56.87671
[17] 64.42323 58.76348 60.27944 61.25582
>
>
> ### 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] 92.76251 NA 73.21759 69.93505 73.95225 72.14993 70.04858 75.18907
[9] 68.67127 72.53639
> rowSums(tmp5)
[1] 1855.250 NA 1464.352 1398.701 1479.045 1442.999 1400.972 1503.781
[9] 1373.425 1450.728
> rowVars(tmp5)
[1] 7898.73218 105.62684 84.88526 65.13267 74.25714 66.56361
[7] 55.28160 78.87186 66.59853 48.90025
> rowSd(tmp5)
[1] 88.874812 10.277492 9.213320 8.070481 8.617258 8.158653 7.435159
[8] 8.880983 8.160793 6.992872
> rowMax(tmp5)
[1] 468.69453 NA 85.30024 85.21234 87.33477 91.21627 82.73061
[8] 92.81741 81.69914 87.24253
> rowMin(tmp5)
[1] 59.47684 NA 55.27765 55.11989 58.76348 57.45552 57.11224 56.87671
[9] 55.15672 60.64187
>
> colMeans(tmp5)
[1] 109.92020 74.30353 74.40210 69.30233 72.22605 71.00831 70.97366
[8] 74.92273 67.48442 70.10366 73.57296 69.76465 74.05839 68.28870
[15] 74.07108 73.63095 72.87358 NA 76.96351 72.36831
> colSums(tmp5)
[1] 1099.2020 743.0353 744.0210 693.0233 722.2605 710.0831 709.7366
[8] 749.2273 674.8442 701.0366 735.7296 697.6465 740.5839 682.8870
[15] 740.7108 736.3095 728.7358 NA 769.6351 723.6831
> colVars(tmp5)
[1] 15950.20823 46.17671 68.91798 71.69276 77.23276 24.00263
[7] 98.99889 103.60929 46.91475 103.65449 43.61332 130.68827
[13] 41.65618 69.92723 104.63391 106.10289 57.08522 NA
[19] 71.97907 51.15544
> colSd(tmp5)
[1] 126.294134 6.795345 8.301686 8.467158 8.788217 4.899248
[7] 9.949819 10.178865 6.849434 10.181085 6.604038 11.431897
[13] 6.454160 8.362250 10.229072 10.300626 7.555476 NA
[19] 8.484048 7.152303
> colMax(tmp5)
[1] 468.69453 81.39409 85.27023 81.69914 85.60537 76.68790 87.24253
[8] 92.81741 78.32326 85.30024 85.10121 90.51586 85.02740 82.79887
[15] 92.58083 85.21234 87.33477 NA 91.21627 83.34273
> colMin(tmp5)
[1] 57.62254 63.43442 63.22028 57.11224 55.15672 59.52155 55.11790 60.77152
[9] 57.45552 55.11989 63.06893 55.27765 65.24533 55.52618 61.88555 56.87671
[17] 64.42323 NA 60.27944 61.25582
>
> Max(tmp5,na.rm=TRUE)
[1] 468.6945
> Min(tmp5,na.rm=TRUE)
[1] 55.1179
> mean(tmp5,na.rm=TRUE)
[1] 74.02111
> Sum(tmp5,na.rm=TRUE)
[1] 14730.2
> Var(tmp5,na.rm=TRUE)
[1] 862.4061
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.76251 71.62888 73.21759 69.93505 73.95225 72.14993 70.04858 75.18907
[9] 68.67127 72.53639
> rowSums(tmp5,na.rm=TRUE)
[1] 1855.250 1360.949 1464.352 1398.701 1479.045 1442.999 1400.972 1503.781
[9] 1373.425 1450.728
> rowVars(tmp5,na.rm=TRUE)
[1] 7898.73218 105.62684 84.88526 65.13267 74.25714 66.56361
[7] 55.28160 78.87186 66.59853 48.90025
> rowSd(tmp5,na.rm=TRUE)
[1] 88.874812 10.277492 9.213320 8.070481 8.617258 8.158653 7.435159
[8] 8.880983 8.160793 6.992872
> rowMax(tmp5,na.rm=TRUE)
[1] 468.69453 92.58083 85.30024 85.21234 87.33477 91.21627 82.73061
[8] 92.81741 81.69914 87.24253
> rowMin(tmp5,na.rm=TRUE)
[1] 59.47684 55.11790 55.27765 55.11989 58.76348 57.45552 57.11224 56.87671
[9] 55.15672 60.64187
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.92020 74.30353 74.40210 69.30233 72.22605 71.00831 70.97366
[8] 74.92273 67.48442 70.10366 73.57296 69.76465 74.05839 68.28870
[15] 74.07108 73.63095 72.87358 69.75673 76.96351 72.36831
> colSums(tmp5,na.rm=TRUE)
[1] 1099.2020 743.0353 744.0210 693.0233 722.2605 710.0831 709.7366
[8] 749.2273 674.8442 701.0366 735.7296 697.6465 740.5839 682.8870
[15] 740.7108 736.3095 728.7358 627.8105 769.6351 723.6831
> colVars(tmp5,na.rm=TRUE)
[1] 15950.20823 46.17671 68.91798 71.69276 77.23276 24.00263
[7] 98.99889 103.60929 46.91475 103.65449 43.61332 130.68827
[13] 41.65618 69.92723 104.63391 106.10289 57.08522 77.62363
[19] 71.97907 51.15544
> colSd(tmp5,na.rm=TRUE)
[1] 126.294134 6.795345 8.301686 8.467158 8.788217 4.899248
[7] 9.949819 10.178865 6.849434 10.181085 6.604038 11.431897
[13] 6.454160 8.362250 10.229072 10.300626 7.555476 8.810428
[19] 8.484048 7.152303
> colMax(tmp5,na.rm=TRUE)
[1] 468.69453 81.39409 85.27023 81.69914 85.60537 76.68790 87.24253
[8] 92.81741 78.32326 85.30024 85.10121 90.51586 85.02740 82.79887
[15] 92.58083 85.21234 87.33477 82.35558 91.21627 83.34273
> colMin(tmp5,na.rm=TRUE)
[1] 57.62254 63.43442 63.22028 57.11224 55.15672 59.52155 55.11790 60.77152
[9] 57.45552 55.11989 63.06893 55.27765 65.24533 55.52618 61.88555 56.87671
[17] 64.42323 58.76348 60.27944 61.25582
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.76251 NaN 73.21759 69.93505 73.95225 72.14993 70.04858 75.18907
[9] 68.67127 72.53639
> rowSums(tmp5,na.rm=TRUE)
[1] 1855.250 0.000 1464.352 1398.701 1479.045 1442.999 1400.972 1503.781
[9] 1373.425 1450.728
> rowVars(tmp5,na.rm=TRUE)
[1] 7898.73218 NA 84.88526 65.13267 74.25714 66.56361
[7] 55.28160 78.87186 66.59853 48.90025
> rowSd(tmp5,na.rm=TRUE)
[1] 88.874812 NA 9.213320 8.070481 8.617258 8.158653 7.435159
[8] 8.880983 8.160793 6.992872
> rowMax(tmp5,na.rm=TRUE)
[1] 468.69453 NA 85.30024 85.21234 87.33477 91.21627 82.73061
[8] 92.81741 81.69914 87.24253
> rowMin(tmp5,na.rm=TRUE)
[1] 59.47684 NA 55.27765 55.11989 58.76348 57.45552 57.11224 56.87671
[9] 55.15672 60.64187
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.01035 75.51121 75.04101 70.20406 71.66217 70.93110 72.73541
[8] 74.80924 67.26476 71.20422 73.03304 67.45896 74.99918 69.13930
[15] 72.01444 72.75469 72.75953 NaN 76.48164 72.70150
> colSums(tmp5,na.rm=TRUE)
[1] 1035.0931 679.6009 675.3691 631.8365 644.9595 638.3799 654.6187
[8] 673.2832 605.3828 640.8380 657.2974 607.1307 674.9927 622.2537
[15] 648.1299 654.7923 654.8357 0.0000 688.3348 654.3135
> colVars(tmp5,na.rm=TRUE)
[1] 17652.50078 35.54079 72.94040 71.50684 83.30984 26.93589
[7] 76.45638 116.41557 52.23626 102.98491 45.78546 87.21701
[13] 36.90591 70.52855 70.12831 110.72778 64.07455 NA
[19] 78.36421 56.30090
> colSd(tmp5,na.rm=TRUE)
[1] 132.862714 5.961609 8.540515 8.456172 9.127423 5.189980
[7] 8.743934 10.789605 7.227466 10.148148 6.766496 9.339005
[13] 6.075023 8.398128 8.374265 10.522727 8.004658 NA
[19] 8.852356 7.503392
> colMax(tmp5,na.rm=TRUE)
[1] 468.69453 81.39409 85.27023 81.69914 85.60537 76.68790 87.24253
[8] 92.81741 78.32326 85.30024 85.10121 80.81698 85.02740 82.79887
[15] 86.01829 85.21234 87.33477 -Inf 91.21627 83.34273
> colMin(tmp5,na.rm=TRUE)
[1] 57.62254 66.03719 63.22028 57.11224 55.15672 59.52155 58.75818 60.77152
[9] 57.45552 55.11989 63.06893 55.27765 65.24533 55.52618 61.88555 56.87671
[17] 64.42323 Inf 60.27944 61.25582
>
>
>
>
> 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] 343.8732 205.2078 125.1372 191.8160 150.2533 314.7581 196.6828 163.4423
[9] 139.8913 178.2918
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 343.8732 205.2078 125.1372 191.8160 150.2533 314.7581 196.6828 163.4423
[9] 139.8913 178.2918
>
>
>
> 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] -1.421085e-14 0.000000e+00 1.136868e-13 -5.684342e-14 2.842171e-14
[6] 0.000000e+00 1.136868e-13 5.684342e-14 -2.842171e-14 -7.105427e-15
[11] 2.842171e-14 1.421085e-13 -2.842171e-14 -2.842171e-14 -8.526513e-14
[16] -5.684342e-14 2.842171e-13 -2.842171e-14 -1.421085e-13 3.410605e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
9 7
6 2
2 10
10 20
8 11
5 8
8 11
3 14
4 4
8 16
4 3
3 10
5 11
2 14
10 2
6 19
1 8
3 14
6 14
2 20
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 1.965989
> Min(tmp)
[1] -2.601982
> mean(tmp)
[1] -0.1223228
> Sum(tmp)
[1] -12.23228
> Var(tmp)
[1] 0.9235908
>
> rowMeans(tmp)
[1] -0.1223228
> rowSums(tmp)
[1] -12.23228
> rowVars(tmp)
[1] 0.9235908
> rowSd(tmp)
[1] 0.9610363
> rowMax(tmp)
[1] 1.965989
> rowMin(tmp)
[1] -2.601982
>
> colMeans(tmp)
[1] -1.48855866 -1.74340754 -0.97413513 -0.85109089 -0.07572477 0.95985355
[7] 1.73058515 -1.06904540 1.22790973 0.61856210 -0.35240450 -1.40512582
[13] -0.95296620 -0.22163231 -0.21263079 0.42840776 -0.28098041 0.31321363
[19] -0.65537599 0.54655428 -0.22142185 0.67333086 0.06072068 0.13698561
[25] -0.30459991 0.93797818 -0.08463491 -0.09324042 -0.93146932 -0.26704374
[31] -0.68706660 -0.46476626 0.46169251 1.91590010 -0.46019707 1.02785640
[37] -0.29225798 0.17664732 -1.27919118 -1.15186001 0.06298135 0.74581667
[43] 0.42254093 -0.49528370 -0.19594831 -1.61048046 1.75101623 -0.67037355
[49] -0.72196513 -0.54462700 1.23222668 0.33706234 -0.24161605 -1.59864626
[55] -0.11248605 1.07536536 0.16364007 1.15245951 -0.56104681 0.45438181
[61] -1.09637592 -1.14661139 1.96598866 0.33074008 0.99998235 -1.01573137
[67] -0.46054689 0.46080843 -1.53099691 0.30422370 -0.15782894 -0.27460291
[73] 1.16230502 -0.43084664 1.43690185 0.11255976 -2.54804918 -0.07527335
[79] 0.13175439 -1.01047285 -0.18229400 -2.60198167 -1.17540608 -1.15732595
[85] 1.35410287 -1.31763025 -0.53755616 0.79130686 0.21850753 1.30608914
[91] -0.68122887 0.21538074 1.11519790 0.09641807 0.03373307 -1.84393236
[97] -0.36513473 -1.28209758 1.66201276 -0.37875778
> colSums(tmp)
[1] -1.48855866 -1.74340754 -0.97413513 -0.85109089 -0.07572477 0.95985355
[7] 1.73058515 -1.06904540 1.22790973 0.61856210 -0.35240450 -1.40512582
[13] -0.95296620 -0.22163231 -0.21263079 0.42840776 -0.28098041 0.31321363
[19] -0.65537599 0.54655428 -0.22142185 0.67333086 0.06072068 0.13698561
[25] -0.30459991 0.93797818 -0.08463491 -0.09324042 -0.93146932 -0.26704374
[31] -0.68706660 -0.46476626 0.46169251 1.91590010 -0.46019707 1.02785640
[37] -0.29225798 0.17664732 -1.27919118 -1.15186001 0.06298135 0.74581667
[43] 0.42254093 -0.49528370 -0.19594831 -1.61048046 1.75101623 -0.67037355
[49] -0.72196513 -0.54462700 1.23222668 0.33706234 -0.24161605 -1.59864626
[55] -0.11248605 1.07536536 0.16364007 1.15245951 -0.56104681 0.45438181
[61] -1.09637592 -1.14661139 1.96598866 0.33074008 0.99998235 -1.01573137
[67] -0.46054689 0.46080843 -1.53099691 0.30422370 -0.15782894 -0.27460291
[73] 1.16230502 -0.43084664 1.43690185 0.11255976 -2.54804918 -0.07527335
[79] 0.13175439 -1.01047285 -0.18229400 -2.60198167 -1.17540608 -1.15732595
[85] 1.35410287 -1.31763025 -0.53755616 0.79130686 0.21850753 1.30608914
[91] -0.68122887 0.21538074 1.11519790 0.09641807 0.03373307 -1.84393236
[97] -0.36513473 -1.28209758 1.66201276 -0.37875778
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] -1.48855866 -1.74340754 -0.97413513 -0.85109089 -0.07572477 0.95985355
[7] 1.73058515 -1.06904540 1.22790973 0.61856210 -0.35240450 -1.40512582
[13] -0.95296620 -0.22163231 -0.21263079 0.42840776 -0.28098041 0.31321363
[19] -0.65537599 0.54655428 -0.22142185 0.67333086 0.06072068 0.13698561
[25] -0.30459991 0.93797818 -0.08463491 -0.09324042 -0.93146932 -0.26704374
[31] -0.68706660 -0.46476626 0.46169251 1.91590010 -0.46019707 1.02785640
[37] -0.29225798 0.17664732 -1.27919118 -1.15186001 0.06298135 0.74581667
[43] 0.42254093 -0.49528370 -0.19594831 -1.61048046 1.75101623 -0.67037355
[49] -0.72196513 -0.54462700 1.23222668 0.33706234 -0.24161605 -1.59864626
[55] -0.11248605 1.07536536 0.16364007 1.15245951 -0.56104681 0.45438181
[61] -1.09637592 -1.14661139 1.96598866 0.33074008 0.99998235 -1.01573137
[67] -0.46054689 0.46080843 -1.53099691 0.30422370 -0.15782894 -0.27460291
[73] 1.16230502 -0.43084664 1.43690185 0.11255976 -2.54804918 -0.07527335
[79] 0.13175439 -1.01047285 -0.18229400 -2.60198167 -1.17540608 -1.15732595
[85] 1.35410287 -1.31763025 -0.53755616 0.79130686 0.21850753 1.30608914
[91] -0.68122887 0.21538074 1.11519790 0.09641807 0.03373307 -1.84393236
[97] -0.36513473 -1.28209758 1.66201276 -0.37875778
> colMin(tmp)
[1] -1.48855866 -1.74340754 -0.97413513 -0.85109089 -0.07572477 0.95985355
[7] 1.73058515 -1.06904540 1.22790973 0.61856210 -0.35240450 -1.40512582
[13] -0.95296620 -0.22163231 -0.21263079 0.42840776 -0.28098041 0.31321363
[19] -0.65537599 0.54655428 -0.22142185 0.67333086 0.06072068 0.13698561
[25] -0.30459991 0.93797818 -0.08463491 -0.09324042 -0.93146932 -0.26704374
[31] -0.68706660 -0.46476626 0.46169251 1.91590010 -0.46019707 1.02785640
[37] -0.29225798 0.17664732 -1.27919118 -1.15186001 0.06298135 0.74581667
[43] 0.42254093 -0.49528370 -0.19594831 -1.61048046 1.75101623 -0.67037355
[49] -0.72196513 -0.54462700 1.23222668 0.33706234 -0.24161605 -1.59864626
[55] -0.11248605 1.07536536 0.16364007 1.15245951 -0.56104681 0.45438181
[61] -1.09637592 -1.14661139 1.96598866 0.33074008 0.99998235 -1.01573137
[67] -0.46054689 0.46080843 -1.53099691 0.30422370 -0.15782894 -0.27460291
[73] 1.16230502 -0.43084664 1.43690185 0.11255976 -2.54804918 -0.07527335
[79] 0.13175439 -1.01047285 -0.18229400 -2.60198167 -1.17540608 -1.15732595
[85] 1.35410287 -1.31763025 -0.53755616 0.79130686 0.21850753 1.30608914
[91] -0.68122887 0.21538074 1.11519790 0.09641807 0.03373307 -1.84393236
[97] -0.36513473 -1.28209758 1.66201276 -0.37875778
> colMedians(tmp)
[1] -1.48855866 -1.74340754 -0.97413513 -0.85109089 -0.07572477 0.95985355
[7] 1.73058515 -1.06904540 1.22790973 0.61856210 -0.35240450 -1.40512582
[13] -0.95296620 -0.22163231 -0.21263079 0.42840776 -0.28098041 0.31321363
[19] -0.65537599 0.54655428 -0.22142185 0.67333086 0.06072068 0.13698561
[25] -0.30459991 0.93797818 -0.08463491 -0.09324042 -0.93146932 -0.26704374
[31] -0.68706660 -0.46476626 0.46169251 1.91590010 -0.46019707 1.02785640
[37] -0.29225798 0.17664732 -1.27919118 -1.15186001 0.06298135 0.74581667
[43] 0.42254093 -0.49528370 -0.19594831 -1.61048046 1.75101623 -0.67037355
[49] -0.72196513 -0.54462700 1.23222668 0.33706234 -0.24161605 -1.59864626
[55] -0.11248605 1.07536536 0.16364007 1.15245951 -0.56104681 0.45438181
[61] -1.09637592 -1.14661139 1.96598866 0.33074008 0.99998235 -1.01573137
[67] -0.46054689 0.46080843 -1.53099691 0.30422370 -0.15782894 -0.27460291
[73] 1.16230502 -0.43084664 1.43690185 0.11255976 -2.54804918 -0.07527335
[79] 0.13175439 -1.01047285 -0.18229400 -2.60198167 -1.17540608 -1.15732595
[85] 1.35410287 -1.31763025 -0.53755616 0.79130686 0.21850753 1.30608914
[91] -0.68122887 0.21538074 1.11519790 0.09641807 0.03373307 -1.84393236
[97] -0.36513473 -1.28209758 1.66201276 -0.37875778
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.488559 -1.743408 -0.9741351 -0.8510909 -0.07572477 0.9598536 1.730585
[2,] -1.488559 -1.743408 -0.9741351 -0.8510909 -0.07572477 0.9598536 1.730585
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.069045 1.22791 0.6185621 -0.3524045 -1.405126 -0.9529662 -0.2216323
[2,] -1.069045 1.22791 0.6185621 -0.3524045 -1.405126 -0.9529662 -0.2216323
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.2126308 0.4284078 -0.2809804 0.3132136 -0.655376 0.5465543 -0.2214219
[2,] -0.2126308 0.4284078 -0.2809804 0.3132136 -0.655376 0.5465543 -0.2214219
[,22] [,23] [,24] [,25] [,26] [,27]
[1,] 0.6733309 0.06072068 0.1369856 -0.3045999 0.9379782 -0.08463491
[2,] 0.6733309 0.06072068 0.1369856 -0.3045999 0.9379782 -0.08463491
[,28] [,29] [,30] [,31] [,32] [,33] [,34]
[1,] -0.09324042 -0.9314693 -0.2670437 -0.6870666 -0.4647663 0.4616925 1.9159
[2,] -0.09324042 -0.9314693 -0.2670437 -0.6870666 -0.4647663 0.4616925 1.9159
[,35] [,36] [,37] [,38] [,39] [,40] [,41]
[1,] -0.4601971 1.027856 -0.292258 0.1766473 -1.279191 -1.15186 0.06298135
[2,] -0.4601971 1.027856 -0.292258 0.1766473 -1.279191 -1.15186 0.06298135
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] 0.7458167 0.4225409 -0.4952837 -0.1959483 -1.61048 1.751016 -0.6703736
[2,] 0.7458167 0.4225409 -0.4952837 -0.1959483 -1.61048 1.751016 -0.6703736
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.7219651 -0.544627 1.232227 0.3370623 -0.241616 -1.598646 -0.1124861
[2,] -0.7219651 -0.544627 1.232227 0.3370623 -0.241616 -1.598646 -0.1124861
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] 1.075365 0.1636401 1.15246 -0.5610468 0.4543818 -1.096376 -1.146611
[2,] 1.075365 0.1636401 1.15246 -0.5610468 0.4543818 -1.096376 -1.146611
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 1.965989 0.3307401 0.9999824 -1.015731 -0.4605469 0.4608084 -1.530997
[2,] 1.965989 0.3307401 0.9999824 -1.015731 -0.4605469 0.4608084 -1.530997
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 0.3042237 -0.1578289 -0.2746029 1.162305 -0.4308466 1.436902 0.1125598
[2,] 0.3042237 -0.1578289 -0.2746029 1.162305 -0.4308466 1.436902 0.1125598
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -2.548049 -0.07527335 0.1317544 -1.010473 -0.182294 -2.601982 -1.175406
[2,] -2.548049 -0.07527335 0.1317544 -1.010473 -0.182294 -2.601982 -1.175406
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -1.157326 1.354103 -1.31763 -0.5375562 0.7913069 0.2185075 1.306089
[2,] -1.157326 1.354103 -1.31763 -0.5375562 0.7913069 0.2185075 1.306089
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -0.6812289 0.2153807 1.115198 0.09641807 0.03373307 -1.843932 -0.3651347
[2,] -0.6812289 0.2153807 1.115198 0.09641807 0.03373307 -1.843932 -0.3651347
[,98] [,99] [,100]
[1,] -1.282098 1.662013 -0.3787578
[2,] -1.282098 1.662013 -0.3787578
>
>
> Max(tmp2)
[1] 2.260568
> Min(tmp2)
[1] -2.492203
> mean(tmp2)
[1] 0.06492825
> Sum(tmp2)
[1] 6.492825
> Var(tmp2)
[1] 0.9257211
>
> rowMeans(tmp2)
[1] 1.8650173759 -0.6718334600 1.2211200142 1.1782043494 0.6587339727
[6] -0.1983036971 0.6950269463 0.6645530382 1.7302964723 -1.6273781545
[11] 0.3635603254 -0.8664788368 1.5021773713 0.1280537910 -0.1303705752
[16] -1.2078803396 -0.1126312320 0.1436827619 1.6768699512 0.8088291668
[21] -1.4273267685 0.3973654041 -1.3344410406 -0.5242018195 -0.1965277392
[26] 1.0966407866 -0.4277867918 -0.0211510539 0.8747588645 -0.1944083410
[31] 0.8031267763 0.0004546179 0.9019171102 -0.5359291061 -0.1089318301
[36] -1.2856461585 1.0094635633 -0.3479919594 -0.1047075214 -0.1353064231
[41] 0.5007839341 0.5455712275 1.1787861179 -0.2673352313 -0.4611410291
[46] 0.4717290281 0.8110773053 1.2801043180 0.5354676530 -0.4150350671
[51] 0.4467390285 -0.8916779376 -0.0788100716 -0.9413306580 -0.3624751991
[56] -1.1460240961 -0.1144093427 1.4963634502 -2.4922034097 0.4597094032
[61] 0.4361793314 -1.7144936468 0.6063100285 -1.5961116676 -0.0644742416
[66] -1.0046951527 0.4464828591 1.6300017224 1.0559439306 -1.7557719880
[71] 0.7283915918 -1.2147550314 1.7403054991 -2.3753381702 -0.1642900116
[76] -0.1017891594 -0.9457977403 0.0164044673 0.4288937089 1.3599618513
[81] 0.0057440146 1.0137554981 0.1446147534 2.2605676019 0.0432199654
[86] -0.4006302884 -0.1200965958 -1.0924846058 0.2577974486 0.4963889261
[91] -0.8427686337 0.7400336230 0.1254137773 0.6815355829 0.0615837644
[96] -0.4902271203 0.2983574487 -1.6465856807 1.1035130548 -0.4747752047
> rowSums(tmp2)
[1] 1.8650173759 -0.6718334600 1.2211200142 1.1782043494 0.6587339727
[6] -0.1983036971 0.6950269463 0.6645530382 1.7302964723 -1.6273781545
[11] 0.3635603254 -0.8664788368 1.5021773713 0.1280537910 -0.1303705752
[16] -1.2078803396 -0.1126312320 0.1436827619 1.6768699512 0.8088291668
[21] -1.4273267685 0.3973654041 -1.3344410406 -0.5242018195 -0.1965277392
[26] 1.0966407866 -0.4277867918 -0.0211510539 0.8747588645 -0.1944083410
[31] 0.8031267763 0.0004546179 0.9019171102 -0.5359291061 -0.1089318301
[36] -1.2856461585 1.0094635633 -0.3479919594 -0.1047075214 -0.1353064231
[41] 0.5007839341 0.5455712275 1.1787861179 -0.2673352313 -0.4611410291
[46] 0.4717290281 0.8110773053 1.2801043180 0.5354676530 -0.4150350671
[51] 0.4467390285 -0.8916779376 -0.0788100716 -0.9413306580 -0.3624751991
[56] -1.1460240961 -0.1144093427 1.4963634502 -2.4922034097 0.4597094032
[61] 0.4361793314 -1.7144936468 0.6063100285 -1.5961116676 -0.0644742416
[66] -1.0046951527 0.4464828591 1.6300017224 1.0559439306 -1.7557719880
[71] 0.7283915918 -1.2147550314 1.7403054991 -2.3753381702 -0.1642900116
[76] -0.1017891594 -0.9457977403 0.0164044673 0.4288937089 1.3599618513
[81] 0.0057440146 1.0137554981 0.1446147534 2.2605676019 0.0432199654
[86] -0.4006302884 -0.1200965958 -1.0924846058 0.2577974486 0.4963889261
[91] -0.8427686337 0.7400336230 0.1254137773 0.6815355829 0.0615837644
[96] -0.4902271203 0.2983574487 -1.6465856807 1.1035130548 -0.4747752047
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 1.8650173759 -0.6718334600 1.2211200142 1.1782043494 0.6587339727
[6] -0.1983036971 0.6950269463 0.6645530382 1.7302964723 -1.6273781545
[11] 0.3635603254 -0.8664788368 1.5021773713 0.1280537910 -0.1303705752
[16] -1.2078803396 -0.1126312320 0.1436827619 1.6768699512 0.8088291668
[21] -1.4273267685 0.3973654041 -1.3344410406 -0.5242018195 -0.1965277392
[26] 1.0966407866 -0.4277867918 -0.0211510539 0.8747588645 -0.1944083410
[31] 0.8031267763 0.0004546179 0.9019171102 -0.5359291061 -0.1089318301
[36] -1.2856461585 1.0094635633 -0.3479919594 -0.1047075214 -0.1353064231
[41] 0.5007839341 0.5455712275 1.1787861179 -0.2673352313 -0.4611410291
[46] 0.4717290281 0.8110773053 1.2801043180 0.5354676530 -0.4150350671
[51] 0.4467390285 -0.8916779376 -0.0788100716 -0.9413306580 -0.3624751991
[56] -1.1460240961 -0.1144093427 1.4963634502 -2.4922034097 0.4597094032
[61] 0.4361793314 -1.7144936468 0.6063100285 -1.5961116676 -0.0644742416
[66] -1.0046951527 0.4464828591 1.6300017224 1.0559439306 -1.7557719880
[71] 0.7283915918 -1.2147550314 1.7403054991 -2.3753381702 -0.1642900116
[76] -0.1017891594 -0.9457977403 0.0164044673 0.4288937089 1.3599618513
[81] 0.0057440146 1.0137554981 0.1446147534 2.2605676019 0.0432199654
[86] -0.4006302884 -0.1200965958 -1.0924846058 0.2577974486 0.4963889261
[91] -0.8427686337 0.7400336230 0.1254137773 0.6815355829 0.0615837644
[96] -0.4902271203 0.2983574487 -1.6465856807 1.1035130548 -0.4747752047
> rowMin(tmp2)
[1] 1.8650173759 -0.6718334600 1.2211200142 1.1782043494 0.6587339727
[6] -0.1983036971 0.6950269463 0.6645530382 1.7302964723 -1.6273781545
[11] 0.3635603254 -0.8664788368 1.5021773713 0.1280537910 -0.1303705752
[16] -1.2078803396 -0.1126312320 0.1436827619 1.6768699512 0.8088291668
[21] -1.4273267685 0.3973654041 -1.3344410406 -0.5242018195 -0.1965277392
[26] 1.0966407866 -0.4277867918 -0.0211510539 0.8747588645 -0.1944083410
[31] 0.8031267763 0.0004546179 0.9019171102 -0.5359291061 -0.1089318301
[36] -1.2856461585 1.0094635633 -0.3479919594 -0.1047075214 -0.1353064231
[41] 0.5007839341 0.5455712275 1.1787861179 -0.2673352313 -0.4611410291
[46] 0.4717290281 0.8110773053 1.2801043180 0.5354676530 -0.4150350671
[51] 0.4467390285 -0.8916779376 -0.0788100716 -0.9413306580 -0.3624751991
[56] -1.1460240961 -0.1144093427 1.4963634502 -2.4922034097 0.4597094032
[61] 0.4361793314 -1.7144936468 0.6063100285 -1.5961116676 -0.0644742416
[66] -1.0046951527 0.4464828591 1.6300017224 1.0559439306 -1.7557719880
[71] 0.7283915918 -1.2147550314 1.7403054991 -2.3753381702 -0.1642900116
[76] -0.1017891594 -0.9457977403 0.0164044673 0.4288937089 1.3599618513
[81] 0.0057440146 1.0137554981 0.1446147534 2.2605676019 0.0432199654
[86] -0.4006302884 -0.1200965958 -1.0924846058 0.2577974486 0.4963889261
[91] -0.8427686337 0.7400336230 0.1254137773 0.6815355829 0.0615837644
[96] -0.4902271203 0.2983574487 -1.6465856807 1.1035130548 -0.4747752047
>
> colMeans(tmp2)
[1] 0.06492825
> colSums(tmp2)
[1] 6.492825
> colVars(tmp2)
[1] 0.9257211
> colSd(tmp2)
[1] 0.962144
> colMax(tmp2)
[1] 2.260568
> colMin(tmp2)
[1] -2.492203
> colMedians(tmp2)
[1] 0.02981222
> colRanges(tmp2)
[,1]
[1,] -2.492203
[2,] 2.260568
>
> 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] -0.8116975 0.1419012 -0.4291599 0.0124734 -1.0472524 -2.2353120
[7] -1.8704863 -0.1843432 -0.5861046 2.1824358
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.9013996
[2,] -0.8950579
[3,] 0.2849506
[4,] 0.8016856
[5,] 1.5436519
>
> rowApply(tmp,sum)
[1] 2.8160038 0.7789491 0.2147260 0.1377071 -2.2477337 0.6275769
[7] -1.3581895 -1.3802552 -1.0226844 -3.3936456
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 5 6 9 10 2 1 9 1 8
[2,] 8 2 8 7 5 3 7 5 4 9
[3,] 9 6 3 10 1 4 4 4 7 4
[4,] 2 7 5 6 3 5 8 1 5 10
[5,] 1 4 1 4 8 8 9 6 9 7
[6,] 3 10 7 1 2 6 6 7 2 6
[7,] 7 8 2 3 4 9 3 8 3 2
[8,] 5 3 4 2 6 7 10 10 8 3
[9,] 6 9 10 8 7 1 2 2 6 5
[10,] 4 1 9 5 9 10 5 3 10 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 4.1676522 0.2906305 -3.0499720 -1.0873795 -1.1775787 -0.4565185
[7] -0.5341806 -0.6593740 6.0050995 0.5487958 2.7442495 -3.0786715
[13] -1.7286023 -4.4377322 -0.2516079 -3.9618876 3.5843937 3.9375568
[19] 0.8900035 -0.7956709
> colApply(tmp,quantile)[,1]
[,1]
[1,] 0.3803804
[2,] 0.4180690
[3,] 0.4592163
[4,] 0.8493836
[5,] 2.0606028
>
> rowApply(tmp,sum)
[1] 7.648575 1.738394 -1.426571 -2.871456 -4.139736
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 19 15 16 11 18
[2,] 4 6 17 17 8
[3,] 6 8 11 5 2
[4,] 11 10 2 7 11
[5,] 13 16 1 8 4
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 2.0606028 -0.5558641 -0.3685846 0.71325637 0.7998529 -1.6199840
[2,] 0.8493836 -0.3899127 -0.2020887 0.21369280 1.2746323 0.3329475
[3,] 0.4592163 0.5249139 0.2296532 -1.42444561 -1.7114344 0.8599818
[4,] 0.3803804 1.0642897 -1.2675873 -0.49906522 -0.2910919 0.2850290
[5,] 0.4180690 -0.3527963 -1.4413646 -0.09081781 -1.2495377 -0.3144928
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.41881774 -1.5114508 1.2057266 0.8503654 2.1377567 1.18104728
[2,] -0.70557136 -0.1725372 1.3217340 0.7758651 1.5260707 -1.29216875
[3,] 2.33521196 -0.4116666 0.9866430 0.3360100 -1.3618268 0.02024894
[4,] -1.70098901 1.1031489 0.8176656 -0.7167223 0.1168517 -2.46837119
[5,] -0.04401446 0.3331318 1.6733303 -0.6967224 0.3253972 -0.51942774
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.1434279 0.9379243 0.5058968 0.6374405 1.12032019 0.6333229
[2,] -1.9838641 -2.6041544 -0.2850601 0.4351367 1.90604867 1.5680447
[3,] 0.2610968 0.3001761 -0.7618449 -0.6517156 -0.20513380 -0.1075095
[4,] 0.6717734 -3.2853322 1.8511656 -2.9767227 0.74086489 0.8098326
[5,] -0.5341806 0.2136540 -1.5617653 -1.4060266 0.02229374 1.0338660
[,19] [,20]
[1,] 0.7617971 -1.2786057
[2,] -1.1406387 0.3108336
[3,] 0.3160717 -1.4202177
[4,] 0.7512389 1.7421853
[5,] 0.2015345 -0.1498664
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-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-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.3541789 0.3102047 -0.4369096 -0.1848577 1.826496 0.2664231 1.089181
col8 col9 col10 col11 col12 col13 col14
row1 -1.984934 0.4263655 -1.301 -0.2620171 1.118457 -1.480853 1.138914
col15 col16 col17 col18 col19 col20
row1 0.5971984 -0.01299097 -0.9456853 -0.09970701 -1.397863 0.7726101
> tmp[,"col10"]
col10
row1 -1.3009999
row2 -0.3715327
row3 -0.5945811
row4 -1.4507938
row5 -0.1889091
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.3541789 0.3102047 -0.43690964 -0.18485769 1.826496 0.2664231
row5 0.6003857 -0.4303789 0.09094107 -0.09631763 1.997117 -2.0649708
col7 col8 col9 col10 col11 col12 col13
row1 1.089181 -1.984934 0.4263655 -1.3009999 -0.2620171 1.118457 -1.480853
row5 -1.427280 -1.429314 0.8156098 -0.1889091 -1.7352877 0.401667 -0.102412
col14 col15 col16 col17 col18 col19
row1 1.1389144 0.5971984 -0.01299097 -0.9456853 -0.09970701 -1.3978628
row5 0.8381234 2.5337930 -0.14242789 -0.2095471 0.02405770 -0.1303987
col20
row1 0.7726101
row5 0.1213598
> tmp[,c("col6","col20")]
col6 col20
row1 0.2664231 0.77261010
row2 -0.7506052 -0.01810709
row3 1.3157390 -0.85011760
row4 0.2378782 1.10713642
row5 -2.0649708 0.12135985
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.2664231 0.7726101
row5 -2.0649708 0.1213598
>
>
>
>
> 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 50.10503 48.64503 51.30814 51.59495 47.49809 104.5768 49.11146 48.27
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.47848 50.68839 49.55624 48.44932 49.68608 49.2015 50.59032 49.83024
col17 col18 col19 col20
row1 49.68789 50.36627 49.14352 105.8201
> tmp[,"col10"]
col10
row1 50.68839
row2 30.01026
row3 29.15320
row4 29.77852
row5 50.31049
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.10503 48.64503 51.30814 51.59495 47.49809 104.5768 49.11146 48.27000
row5 49.85952 47.71083 50.13765 48.23559 49.52445 106.6144 49.32432 49.64803
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.47848 50.68839 49.55624 48.44932 49.68608 49.2015 50.59032 49.83024
row5 50.87291 50.31049 50.68878 51.00540 49.28899 49.5277 48.55692 48.73209
col17 col18 col19 col20
row1 49.68789 50.36627 49.14352 105.8201
row5 50.63483 49.96708 51.82976 103.2859
> tmp[,c("col6","col20")]
col6 col20
row1 104.57677 105.82013
row2 75.13045 75.12719
row3 74.30393 77.23533
row4 77.71894 76.60990
row5 106.61436 103.28592
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.5768 105.8201
row5 106.6144 103.2859
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.5768 105.8201
row5 106.6144 103.2859
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.0399740
[2,] -1.1412596
[3,] -0.1907587
[4,] -1.2297951
[5,] -0.4433775
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.1118645 -0.6813123
[2,] -0.4410643 0.3433267
[3,] 0.4297392 -0.3168000
[4,] -2.6484296 -1.1373757
[5,] -0.8583916 1.8715013
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.38384330 0.1290165
[2,] 0.01970382 -0.1528699
[3,] -0.72807710 -0.2188892
[4,] 0.16939440 -0.7413483
[5,] -0.19656312 0.9004028
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.3838433
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.38384330
[2,] 0.01970382
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 -0.3433378 -0.6439003 -1.2388644 -0.193104 -1.827918 -1.2442830 -0.5038804
row1 -0.2115552 1.3792029 -0.4582003 0.645531 1.607091 0.9044417 -1.6335497
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -1.138844 -0.2774855 -0.1980851 0.3805171 -0.5794292 1.2509870
row1 -1.011090 -0.2768126 0.6040313 -0.6864926 0.4936337 -0.9351325
[,14] [,15] [,16] [,17] [,18] [,19]
row3 0.2035391 0.4863182 -1.181231 0.23509889 0.78384765 1.3078699
row1 -1.0093024 -0.3139753 1.721627 -0.06750181 0.04213711 0.4592152
[,20]
row3 0.4489014
row1 -0.2845447
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.7516623 0.4061871 -0.7548508 -1.44474 0.05808915 -1.002579 0.2005615
[,8] [,9] [,10]
row2 -0.9917175 -0.1568448 0.08804197
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.3419656 -0.1124943 0.5017767 -0.2293334 -0.2746854 0.7540696 2.40211
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.8492568 -1.130877 -0.1024641 0.2585926 0.607435 -0.8787025 -0.2458879
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -2.198598 -0.00725326 -0.5818959 0.7709009 0.05085004 0.8356463
>
>
> 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: 0x576e217cdd60>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a69de1a9e416"
[2] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a69de6620c37b"
[3] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a69de4a3186c"
[4] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a69de20a09229"
[5] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a69de4d9363be"
[6] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a69de48321729"
[7] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a69de7bde409b"
[8] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a69de5975a425"
[9] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a69de13a87a51"
[10] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a69de6907625a"
[11] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a69de2d7ab7db"
[12] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a69de19003ffb"
[13] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a69de5f649a1a"
[14] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a69de1f981687"
[15] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a69de110b2a8d"
>
>
> ### 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: 0x576e21e64260>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x576e21e64260>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x576e21e64260>
> rowMedians(tmp)
[1] -0.113189913 0.375827302 -0.282900091 0.444466184 -0.395740191
[6] 0.097120068 -0.356870409 0.415050874 -0.022152950 -0.118864422
[11] 0.113977440 -0.114370220 -0.197986699 0.312535735 0.104835189
[16] -0.524286088 -0.020778611 0.150193387 0.036954164 -0.066125556
[21] -0.259843803 -0.427384852 -0.169437269 -0.398477631 0.214468897
[26] 0.682774367 -0.236249675 0.088488201 0.082972266 0.721869329
[31] -0.031411438 -0.075101140 0.057290064 0.592983325 -0.141359637
[36] -0.388833852 0.008790535 0.258353516 0.332678997 -0.009477803
[41] -0.242282519 0.330653481 0.472955036 -0.369071247 0.148447615
[46] 0.311392526 0.072236162 -0.057423358 0.342762105 -0.434116081
[51] 0.079708325 -0.109993373 0.371527712 0.021843981 -0.154849139
[56] -0.131993466 -0.241249339 -0.491601216 0.409636629 0.269033274
[61] 0.046767281 0.177060372 0.127658995 0.006961478 -0.451435439
[66] -0.121732956 -0.151189957 0.273096829 0.400646035 -0.364846063
[71] 0.217293680 -0.068117400 0.666435179 0.122725576 -0.056478078
[76] 0.586767546 0.069760639 -0.058497920 0.065699115 0.068381480
[81] 0.043680204 0.386968586 -0.225148925 0.216399498 0.053962970
[86] -0.153624396 -0.501718899 0.166461342 0.310040843 -0.107059799
[91] 0.001627675 -0.259020990 -0.061506808 -0.301748237 -0.234854683
[96] 0.294549376 -0.280443789 0.303754564 0.291318961 0.129000180
[101] -0.002578635 0.329116601 -0.207823143 -0.048658467 -0.203747696
[106] 0.089218517 -0.179861852 0.104334539 0.039233139 -0.221401645
[111] -0.416876915 0.432761658 -0.518359905 0.155912995 -0.399144471
[116] 0.226570137 0.085970669 -0.224498024 0.277688906 0.100985329
[121] -0.739016067 -0.006227101 0.091066724 -0.511968330 0.557529272
[126] 0.175260919 -0.343906474 -0.200646958 -0.422903030 0.899613044
[131] -0.080101237 -0.334084960 -0.465471006 -0.195318004 0.577165163
[136] -0.864825693 -0.357928532 0.597463732 0.034359899 -0.139362655
[141] -0.396595583 0.012163164 0.476402242 0.042121186 0.355984802
[146] -0.129952556 0.105427248 -0.284425730 -0.030656865 0.141087804
[151] 0.087034630 -0.395789371 -0.097497189 -0.352740673 0.307963883
[156] 0.302785098 0.283737204 0.455520285 0.035291604 -0.143260977
[161] 0.248762344 0.116333343 -0.152873451 -0.466158095 -0.070555683
[166] 0.025469764 0.557507992 -0.081336033 0.376382142 0.181477045
[171] 0.093631363 0.212338052 -0.030599969 -0.387190789 0.254521792
[176] 0.125946899 -0.256550669 -0.253656319 0.196934173 -0.585252269
[181] -0.041660054 -0.210976643 0.049620747 0.317249394 0.352715101
[186] -0.325262399 -0.052183733 0.131945246 0.270088704 -0.077030133
[191] 0.292930783 -0.041475431 0.428005328 -0.462100085 -0.140454569
[196] 0.077963500 -0.142073548 0.424590284 0.099590996 0.093782615
[201] 0.249085246 0.229746992 -0.527516268 -0.382223567 0.210940684
[206] -0.178495352 0.497171057 0.890557579 0.126710025 -0.303448936
[211] 0.079930663 0.037093661 0.609750513 0.391859254 0.141294508
[216] -0.432236534 0.028067500 0.328953741 0.231848725 -0.036763055
[221] 0.120433557 0.073911695 -0.226381254 -0.745641969 -0.114223665
[226] -0.116245738 -0.910120697 0.025750938 0.139159387 -0.060217242
>
> proc.time()
user system elapsed
1.398 1.432 2.819
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2024-10-21 r87258) -- "Unsuffered Consequences"
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: 0x5d434d61eb90>
> .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: 0x5d434d61eb90>
> .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: 0x5d434d61eb90>
> .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: 0x5d434d61eb90>
> 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: 0x5d434c4ad820>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5d434c4ad820>
> .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: 0x5d434c4ad820>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5d434c4ad820>
> .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: 0x5d434c4ad820>
> 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: 0x5d434c5369c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5d434c5369c0>
> .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: 0x5d434c5369c0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5d434c5369c0>
> .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: 0x5d434c5369c0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5d434c5369c0>
> .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: 0x5d434c5369c0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5d434c5369c0>
> .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: 0x5d434c5369c0>
> 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: 0x5d434c7d2230>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5d434c7d2230>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5d434c7d2230>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5d434c7d2230>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3a6c6d180c1bbf" "BufferedMatrixFile3a6c6db0e6322"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3a6c6d180c1bbf" "BufferedMatrixFile3a6c6db0e6322"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5d434d004330>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5d434d004330>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5d434d004330>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5d434d004330>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5d434d004330>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5d434d004330>
> .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: 0x5d434e5f6c60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5d434e5f6c60>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5d434e5f6c60>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5d434e5f6c60>
> 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: 0x5d434e709140>
> .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: 0x5d434e709140>
> rm(P)
>
> proc.time()
user system elapsed
0.251 0.059 0.300
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2024-10-21 r87258) -- "Unsuffered Consequences"
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
0.238 0.044 0.271