Ben Bolstad
| Snapshot Date: 2024-11-19 13:40 -0500 (Tue, 19 Nov 2024) |
| 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 2024-11-20 12:02 -0500 (Wed, 20 Nov 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| teran2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4481 |
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4479 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves" | 4359 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4539 |
| kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4493 |
| 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
| teran2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | ||||||||||
| palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | 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: 1.70.0 |
| 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: 2024-11-19 23:44:21 -0500 (Tue, 19 Nov 2024) |
| EndedAt: 2024-11-19 23:44:39 -0500 (Tue, 19 Nov 2024) |
| EllapsedTime: 18.0 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
###
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* using log directory ‘/media/volume/teran2_disk/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 13.2.0-23ubuntu4) 13.2.0’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/media/volume/teran2_disk/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 ‘/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 13.2.0-23ubuntu4) 13.2.0’
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 /media/volume/teran2_disk/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
0.167 0.052 0.207
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] "/media/volume/teran2_disk/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 471794 25.2 1026277 54.9 643411 34.4
Vcells 872044 6.7 8388608 64.0 2046755 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] "Tue Nov 19 23:44:32 2024"
> 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] "Tue Nov 19 23:44:32 2024"
>
>
> 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: 0x56214bfdb9c0>
>
>
>
> 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] "Tue Nov 19 23:44:32 2024"
> 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] "Tue Nov 19 23:44:32 2024"
>
> ColMode(tmp2)
<pointer: 0x56214bfdb9c0>
>
>
>
> ### 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,] 100.2459842 -0.3673162 -0.26722308 1.0656978
[2,] -0.3524030 0.7764393 -0.09256013 0.5514738
[3,] 0.2973729 0.8840347 -1.58242918 -0.9698104
[4,] -1.2907039 -0.1141884 -1.96651026 -0.4333827
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2.4 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.2459842 0.3673162 0.26722308 1.0656978
[2,] 0.3524030 0.7764393 0.09256013 0.5514738
[3,] 0.2973729 0.8840347 1.58242918 0.9698104
[4,] 1.2907039 0.1141884 1.96651026 0.4333827
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2.4 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0122917 0.6060662 0.5169362 1.0323264
[2,] 0.5936354 0.8811579 0.3042370 0.7426128
[3,] 0.5453190 0.9402312 1.2579464 0.9847895
[4,] 1.1360915 0.3379178 1.4023232 0.6583181
>
> 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: /media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2.4 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.36890 31.42798 30.43659 36.38896
[2,] 31.28876 34.58802 28.13493 32.97760
[3,] 30.75056 35.28635 39.16189 35.81771
[4,] 37.65162 28.49337 40.98974 32.01656
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x56214c94fc40>
> exp(tmp5)
<pointer: 0x56214c94fc40>
> log(tmp5,2)
<pointer: 0x56214c94fc40>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.0758
> Min(tmp5)
[1] 53.99836
> mean(tmp5)
[1] 72.95219
> Sum(tmp5)
[1] 14590.44
> Var(tmp5)
[1] 864.9089
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.90853 69.55095 71.91241 70.39102 67.61695 71.14090 70.92621 71.06236
[9] 75.58906 68.42352
> rowSums(tmp5)
[1] 1858.171 1391.019 1438.248 1407.820 1352.339 1422.818 1418.524 1421.247
[9] 1511.781 1368.470
> rowVars(tmp5)
[1] 7906.82753 67.37782 76.82311 82.80564 53.34681 79.63625
[7] 55.01366 84.47258 75.00337 67.63582
> rowSd(tmp5)
[1] 88.920344 8.208400 8.764879 9.099761 7.303890 8.923914 7.417119
[8] 9.190897 8.660448 8.224100
> rowMax(tmp5)
[1] 469.07584 86.24741 99.16061 89.10566 79.93588 88.17867 86.71181
[8] 89.59413 94.09979 85.09453
> rowMin(tmp5)
[1] 58.03133 56.13374 59.84952 57.16271 56.33836 53.99836 54.41597 60.14079
[9] 58.97140 56.06006
>
> colMeans(tmp5)
[1] 111.72306 72.67982 72.89520 71.42505 71.73078 68.98125 68.29677
[8] 70.17748 71.75900 69.56312 76.02538 71.79239 71.30964 68.73336
[15] 71.38793 76.81034 68.14909 66.64357 67.31662 71.64398
> colSums(tmp5)
[1] 1117.2306 726.7982 728.9520 714.2505 717.3078 689.8125 682.9677
[8] 701.7748 717.5900 695.6312 760.2538 717.9239 713.0964 687.3336
[15] 713.8793 768.1034 681.4909 666.4357 673.1662 716.4398
> colVars(tmp5)
[1] 15825.11789 71.23792 71.66364 41.07160 65.09886 45.05872
[7] 73.21741 117.98905 56.33412 47.19654 133.43586 98.16547
[13] 50.74346 27.36108 54.03589 83.77709 127.74708 73.17978
[19] 64.97388 96.59263
> colSd(tmp5)
[1] 125.797925 8.440256 8.465438 6.408713 8.068386 6.712579
[7] 8.556717 10.862277 7.505606 6.869974 11.551444 9.907849
[13] 7.123444 5.230782 7.350911 9.152982 11.302525 8.554518
[19] 8.060638 9.828155
> colMax(tmp5)
[1] 469.07584 88.77807 85.31478 83.91713 87.23283 77.76278 84.16022
[8] 89.59413 87.02143 79.96402 99.16061 88.17867 85.09453 77.46529
[15] 84.19086 94.09979 86.24741 80.28025 81.58027 89.10566
> colMin(tmp5)
[1] 64.00327 59.30521 58.55917 65.44432 60.28983 59.40040 56.33836 56.71030
[9] 63.73420 57.16271 62.19158 59.37617 62.13939 61.17403 58.62997 63.54492
[17] 53.99836 56.13374 56.06006 58.63405
>
>
> ### 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] 92.90853 69.55095 71.91241 70.39102 67.61695 NA 70.92621 71.06236
[9] 75.58906 68.42352
> rowSums(tmp5)
[1] 1858.171 1391.019 1438.248 1407.820 1352.339 NA 1418.524 1421.247
[9] 1511.781 1368.470
> rowVars(tmp5)
[1] 7906.82753 67.37782 76.82311 82.80564 53.34681 73.05466
[7] 55.01366 84.47258 75.00337 67.63582
> rowSd(tmp5)
[1] 88.920344 8.208400 8.764879 9.099761 7.303890 8.547202 7.417119
[8] 9.190897 8.660448 8.224100
> rowMax(tmp5)
[1] 469.07584 86.24741 99.16061 89.10566 79.93588 NA 86.71181
[8] 89.59413 94.09979 85.09453
> rowMin(tmp5)
[1] 58.03133 56.13374 59.84952 57.16271 56.33836 NA 54.41597 60.14079
[9] 58.97140 56.06006
>
> colMeans(tmp5)
[1] 111.72306 72.67982 72.89520 71.42505 71.73078 68.98125 68.29677
[8] 70.17748 71.75900 69.56312 76.02538 71.79239 71.30964 68.73336
[15] 71.38793 NA 68.14909 66.64357 67.31662 71.64398
> colSums(tmp5)
[1] 1117.2306 726.7982 728.9520 714.2505 717.3078 689.8125 682.9677
[8] 701.7748 717.5900 695.6312 760.2538 717.9239 713.0964 687.3336
[15] 713.8793 NA 681.4909 666.4357 673.1662 716.4398
> colVars(tmp5)
[1] 15825.11789 71.23792 71.66364 41.07160 65.09886 45.05872
[7] 73.21741 117.98905 56.33412 47.19654 133.43586 98.16547
[13] 50.74346 27.36108 54.03589 NA 127.74708 73.17978
[19] 64.97388 96.59263
> colSd(tmp5)
[1] 125.797925 8.440256 8.465438 6.408713 8.068386 6.712579
[7] 8.556717 10.862277 7.505606 6.869974 11.551444 9.907849
[13] 7.123444 5.230782 7.350911 NA 11.302525 8.554518
[19] 8.060638 9.828155
> colMax(tmp5)
[1] 469.07584 88.77807 85.31478 83.91713 87.23283 77.76278 84.16022
[8] 89.59413 87.02143 79.96402 99.16061 88.17867 85.09453 77.46529
[15] 84.19086 NA 86.24741 80.28025 81.58027 89.10566
> colMin(tmp5)
[1] 64.00327 59.30521 58.55917 65.44432 60.28983 59.40040 56.33836 56.71030
[9] 63.73420 57.16271 62.19158 59.37617 62.13939 61.17403 58.62997 NA
[17] 53.99836 56.13374 56.06006 58.63405
>
> Max(tmp5,na.rm=TRUE)
[1] 469.0758
> Min(tmp5,na.rm=TRUE)
[1] 53.99836
> mean(tmp5,na.rm=TRUE)
[1] 72.89236
> Sum(tmp5,na.rm=TRUE)
[1] 14505.58
> Var(tmp5,na.rm=TRUE)
[1] 868.5575
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.90853 69.55095 71.91241 70.39102 67.61695 70.41887 70.92621 71.06236
[9] 75.58906 68.42352
> rowSums(tmp5,na.rm=TRUE)
[1] 1858.171 1391.019 1438.248 1407.820 1352.339 1337.958 1418.524 1421.247
[9] 1511.781 1368.470
> rowVars(tmp5,na.rm=TRUE)
[1] 7906.82753 67.37782 76.82311 82.80564 53.34681 73.05466
[7] 55.01366 84.47258 75.00337 67.63582
> rowSd(tmp5,na.rm=TRUE)
[1] 88.920344 8.208400 8.764879 9.099761 7.303890 8.547202 7.417119
[8] 9.190897 8.660448 8.224100
> rowMax(tmp5,na.rm=TRUE)
[1] 469.07584 86.24741 99.16061 89.10566 79.93588 88.17867 86.71181
[8] 89.59413 94.09979 85.09453
> rowMin(tmp5,na.rm=TRUE)
[1] 58.03133 56.13374 59.84952 57.16271 56.33836 53.99836 54.41597 60.14079
[9] 58.97140 56.06006
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.72306 72.67982 72.89520 71.42505 71.73078 68.98125 68.29677
[8] 70.17748 71.75900 69.56312 76.02538 71.79239 71.30964 68.73336
[15] 71.38793 75.91599 68.14909 66.64357 67.31662 71.64398
> colSums(tmp5,na.rm=TRUE)
[1] 1117.2306 726.7982 728.9520 714.2505 717.3078 689.8125 682.9677
[8] 701.7748 717.5900 695.6312 760.2538 717.9239 713.0964 687.3336
[15] 713.8793 683.2439 681.4909 666.4357 673.1662 716.4398
> colVars(tmp5,na.rm=TRUE)
[1] 15825.11789 71.23792 71.66364 41.07160 65.09886 45.05872
[7] 73.21741 117.98905 56.33412 47.19654 133.43586 98.16547
[13] 50.74346 27.36108 54.03589 85.25079 127.74708 73.17978
[19] 64.97388 96.59263
> colSd(tmp5,na.rm=TRUE)
[1] 125.797925 8.440256 8.465438 6.408713 8.068386 6.712579
[7] 8.556717 10.862277 7.505606 6.869974 11.551444 9.907849
[13] 7.123444 5.230782 7.350911 9.233135 11.302525 8.554518
[19] 8.060638 9.828155
> colMax(tmp5,na.rm=TRUE)
[1] 469.07584 88.77807 85.31478 83.91713 87.23283 77.76278 84.16022
[8] 89.59413 87.02143 79.96402 99.16061 88.17867 85.09453 77.46529
[15] 84.19086 94.09979 86.24741 80.28025 81.58027 89.10566
> colMin(tmp5,na.rm=TRUE)
[1] 64.00327 59.30521 58.55917 65.44432 60.28983 59.40040 56.33836 56.71030
[9] 63.73420 57.16271 62.19158 59.37617 62.13939 61.17403 58.62997 63.54492
[17] 53.99836 56.13374 56.06006 58.63405
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.90853 69.55095 71.91241 70.39102 67.61695 NaN 70.92621 71.06236
[9] 75.58906 68.42352
> rowSums(tmp5,na.rm=TRUE)
[1] 1858.171 1391.019 1438.248 1407.820 1352.339 0.000 1418.524 1421.247
[9] 1511.781 1368.470
> rowVars(tmp5,na.rm=TRUE)
[1] 7906.82753 67.37782 76.82311 82.80564 53.34681 NA
[7] 55.01366 84.47258 75.00337 67.63582
> rowSd(tmp5,na.rm=TRUE)
[1] 88.920344 8.208400 8.764879 9.099761 7.303890 NA 7.417119
[8] 9.190897 8.660448 8.224100
> rowMax(tmp5,na.rm=TRUE)
[1] 469.07584 86.24741 99.16061 89.10566 79.93588 NA 86.71181
[8] 89.59413 94.09979 85.09453
> rowMin(tmp5,na.rm=TRUE)
[1] 58.03133 56.13374 59.84952 57.16271 56.33836 NA 54.41597 60.14079
[9] 58.97140 56.06006
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.07807 71.70836 73.16238 72.08957 71.85340 68.05461 68.70837
[8] 71.18806 71.09958 69.92199 76.31387 69.97169 71.15715 68.44638
[15] 71.55048 NaN 69.72139 67.71403 67.06051 72.35305
> colSums(tmp5,na.rm=TRUE)
[1] 1035.7026 645.3752 658.4614 648.8061 646.6806 612.4915 618.3753
[8] 640.6926 639.8962 629.2979 686.8249 629.7452 640.4144 616.0174
[15] 643.9543 0.0000 627.4925 609.4262 603.5446 651.1774
> colVars(tmp5,na.rm=TRUE)
[1] 17676.62666 69.52568 79.81851 41.23763 73.06707 41.03103
[7] 80.46373 121.24841 58.48401 51.64721 149.17903 73.14305
[13] 56.82479 29.85468 60.49310 NA 115.90392 69.43625
[19] 72.35769 103.01050
> colSd(tmp5,na.rm=TRUE)
[1] 132.953476 8.338206 8.934121 6.421653 8.547928 6.405547
[7] 8.970158 11.011285 7.647484 7.186599 12.213887 8.552371
[13] 7.538222 5.463943 7.777731 NA 10.765868 8.332842
[19] 8.506332 10.149409
> colMax(tmp5,na.rm=TRUE)
[1] 469.07584 88.77807 85.31478 83.91713 87.23283 77.76278 84.16022
[8] 89.59413 87.02143 79.96402 99.16061 82.79015 85.09453 77.46529
[15] 84.19086 -Inf 86.24741 80.28025 81.58027 89.10566
> colMin(tmp5,na.rm=TRUE)
[1] 64.00327 59.30521 58.55917 66.09683 60.28983 59.40040 56.33836 56.71030
[9] 63.73420 57.16271 62.19158 59.37617 62.13939 61.17403 58.62997 Inf
[17] 54.41597 56.13374 56.06006 58.63405
>
>
>
>
> 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] 152.4947 142.5703 280.7803 144.4988 323.7384 177.2953 260.4538 275.7240
[9] 379.0861 243.5124
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 152.4947 142.5703 280.7803 144.4988 323.7384 177.2953 260.4538 275.7240
[9] 379.0861 243.5124
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -8.526513e-14 3.126388e-13 2.842171e-13 -2.842171e-13 1.136868e-13
[6] 1.421085e-13 2.273737e-13 -1.136868e-13 5.684342e-14 0.000000e+00
[11] -1.421085e-14 -2.842171e-14 5.684342e-14 -5.684342e-14 -1.989520e-13
[16] 0.000000e+00 1.136868e-13 0.000000e+00 -5.684342e-14 5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
6 14
9 13
7 19
9 16
10 6
6 1
3 2
10 12
7 15
3 15
7 7
8 16
7 5
7 15
4 20
8 12
10 12
10 20
1 7
1 6
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] 1.914911
> Min(tmp)
[1] -2.220296
> mean(tmp)
[1] -0.2189673
> Sum(tmp)
[1] -21.89673
> Var(tmp)
[1] 0.9227484
>
> rowMeans(tmp)
[1] -0.2189673
> rowSums(tmp)
[1] -21.89673
> rowVars(tmp)
[1] 0.9227484
> rowSd(tmp)
[1] 0.9605979
> rowMax(tmp)
[1] 1.914911
> rowMin(tmp)
[1] -2.220296
>
> colMeans(tmp)
[1] -1.08959606 0.64255579 0.46071892 0.33019068 -1.48103262 0.39750257
[7] 1.48882315 -0.69496351 -0.31113423 -0.80671604 -0.52246741 1.06242887
[13] 1.46103426 0.47089901 -0.68664576 0.74304704 0.10486435 -0.82703931
[19] 0.39478840 -0.55099481 -0.53124562 0.37189600 0.63124295 -0.33317541
[25] -2.13848207 -0.99235709 0.67415459 1.73471909 0.22701731 -0.20583774
[31] -0.12791228 -0.49165054 0.50637128 1.15510364 -0.38261247 -1.51637490
[37] 0.43117447 -1.10539146 1.06654596 -2.16401384 -2.22029575 -0.35155016
[43] -1.31133337 0.69555330 0.60027101 -0.27054988 0.71601795 1.06221949
[49] 1.19227665 0.23354485 -0.56956048 0.33198350 -0.64295290 1.91491136
[55] 0.52770269 1.47194203 -0.51340345 -1.76977108 -0.61250278 -0.82031363
[61] 0.19884596 -1.23182116 -0.83372906 -1.65795752 -0.59279897 -1.01218183
[67] -0.20379430 -0.67515501 -0.99797351 0.67537624 0.81508596 -1.64484310
[73] -0.08322436 0.52537075 0.30614579 -0.46599868 0.88354414 -1.26999983
[79] -0.53270005 -1.48916981 1.38271328 -1.44428795 -0.70150786 0.90628633
[85] -0.19624296 -0.70261677 0.28456469 0.51898197 -0.45437851 -0.34461323
[91] -0.97647670 -0.07271440 -1.22499649 -1.65659459 -1.86883485 -0.37802960
[97] -1.24970991 -2.07397348 0.55140676 0.03164937
> colSums(tmp)
[1] -1.08959606 0.64255579 0.46071892 0.33019068 -1.48103262 0.39750257
[7] 1.48882315 -0.69496351 -0.31113423 -0.80671604 -0.52246741 1.06242887
[13] 1.46103426 0.47089901 -0.68664576 0.74304704 0.10486435 -0.82703931
[19] 0.39478840 -0.55099481 -0.53124562 0.37189600 0.63124295 -0.33317541
[25] -2.13848207 -0.99235709 0.67415459 1.73471909 0.22701731 -0.20583774
[31] -0.12791228 -0.49165054 0.50637128 1.15510364 -0.38261247 -1.51637490
[37] 0.43117447 -1.10539146 1.06654596 -2.16401384 -2.22029575 -0.35155016
[43] -1.31133337 0.69555330 0.60027101 -0.27054988 0.71601795 1.06221949
[49] 1.19227665 0.23354485 -0.56956048 0.33198350 -0.64295290 1.91491136
[55] 0.52770269 1.47194203 -0.51340345 -1.76977108 -0.61250278 -0.82031363
[61] 0.19884596 -1.23182116 -0.83372906 -1.65795752 -0.59279897 -1.01218183
[67] -0.20379430 -0.67515501 -0.99797351 0.67537624 0.81508596 -1.64484310
[73] -0.08322436 0.52537075 0.30614579 -0.46599868 0.88354414 -1.26999983
[79] -0.53270005 -1.48916981 1.38271328 -1.44428795 -0.70150786 0.90628633
[85] -0.19624296 -0.70261677 0.28456469 0.51898197 -0.45437851 -0.34461323
[91] -0.97647670 -0.07271440 -1.22499649 -1.65659459 -1.86883485 -0.37802960
[97] -1.24970991 -2.07397348 0.55140676 0.03164937
> 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] -1.08959606 0.64255579 0.46071892 0.33019068 -1.48103262 0.39750257
[7] 1.48882315 -0.69496351 -0.31113423 -0.80671604 -0.52246741 1.06242887
[13] 1.46103426 0.47089901 -0.68664576 0.74304704 0.10486435 -0.82703931
[19] 0.39478840 -0.55099481 -0.53124562 0.37189600 0.63124295 -0.33317541
[25] -2.13848207 -0.99235709 0.67415459 1.73471909 0.22701731 -0.20583774
[31] -0.12791228 -0.49165054 0.50637128 1.15510364 -0.38261247 -1.51637490
[37] 0.43117447 -1.10539146 1.06654596 -2.16401384 -2.22029575 -0.35155016
[43] -1.31133337 0.69555330 0.60027101 -0.27054988 0.71601795 1.06221949
[49] 1.19227665 0.23354485 -0.56956048 0.33198350 -0.64295290 1.91491136
[55] 0.52770269 1.47194203 -0.51340345 -1.76977108 -0.61250278 -0.82031363
[61] 0.19884596 -1.23182116 -0.83372906 -1.65795752 -0.59279897 -1.01218183
[67] -0.20379430 -0.67515501 -0.99797351 0.67537624 0.81508596 -1.64484310
[73] -0.08322436 0.52537075 0.30614579 -0.46599868 0.88354414 -1.26999983
[79] -0.53270005 -1.48916981 1.38271328 -1.44428795 -0.70150786 0.90628633
[85] -0.19624296 -0.70261677 0.28456469 0.51898197 -0.45437851 -0.34461323
[91] -0.97647670 -0.07271440 -1.22499649 -1.65659459 -1.86883485 -0.37802960
[97] -1.24970991 -2.07397348 0.55140676 0.03164937
> colMin(tmp)
[1] -1.08959606 0.64255579 0.46071892 0.33019068 -1.48103262 0.39750257
[7] 1.48882315 -0.69496351 -0.31113423 -0.80671604 -0.52246741 1.06242887
[13] 1.46103426 0.47089901 -0.68664576 0.74304704 0.10486435 -0.82703931
[19] 0.39478840 -0.55099481 -0.53124562 0.37189600 0.63124295 -0.33317541
[25] -2.13848207 -0.99235709 0.67415459 1.73471909 0.22701731 -0.20583774
[31] -0.12791228 -0.49165054 0.50637128 1.15510364 -0.38261247 -1.51637490
[37] 0.43117447 -1.10539146 1.06654596 -2.16401384 -2.22029575 -0.35155016
[43] -1.31133337 0.69555330 0.60027101 -0.27054988 0.71601795 1.06221949
[49] 1.19227665 0.23354485 -0.56956048 0.33198350 -0.64295290 1.91491136
[55] 0.52770269 1.47194203 -0.51340345 -1.76977108 -0.61250278 -0.82031363
[61] 0.19884596 -1.23182116 -0.83372906 -1.65795752 -0.59279897 -1.01218183
[67] -0.20379430 -0.67515501 -0.99797351 0.67537624 0.81508596 -1.64484310
[73] -0.08322436 0.52537075 0.30614579 -0.46599868 0.88354414 -1.26999983
[79] -0.53270005 -1.48916981 1.38271328 -1.44428795 -0.70150786 0.90628633
[85] -0.19624296 -0.70261677 0.28456469 0.51898197 -0.45437851 -0.34461323
[91] -0.97647670 -0.07271440 -1.22499649 -1.65659459 -1.86883485 -0.37802960
[97] -1.24970991 -2.07397348 0.55140676 0.03164937
> colMedians(tmp)
[1] -1.08959606 0.64255579 0.46071892 0.33019068 -1.48103262 0.39750257
[7] 1.48882315 -0.69496351 -0.31113423 -0.80671604 -0.52246741 1.06242887
[13] 1.46103426 0.47089901 -0.68664576 0.74304704 0.10486435 -0.82703931
[19] 0.39478840 -0.55099481 -0.53124562 0.37189600 0.63124295 -0.33317541
[25] -2.13848207 -0.99235709 0.67415459 1.73471909 0.22701731 -0.20583774
[31] -0.12791228 -0.49165054 0.50637128 1.15510364 -0.38261247 -1.51637490
[37] 0.43117447 -1.10539146 1.06654596 -2.16401384 -2.22029575 -0.35155016
[43] -1.31133337 0.69555330 0.60027101 -0.27054988 0.71601795 1.06221949
[49] 1.19227665 0.23354485 -0.56956048 0.33198350 -0.64295290 1.91491136
[55] 0.52770269 1.47194203 -0.51340345 -1.76977108 -0.61250278 -0.82031363
[61] 0.19884596 -1.23182116 -0.83372906 -1.65795752 -0.59279897 -1.01218183
[67] -0.20379430 -0.67515501 -0.99797351 0.67537624 0.81508596 -1.64484310
[73] -0.08322436 0.52537075 0.30614579 -0.46599868 0.88354414 -1.26999983
[79] -0.53270005 -1.48916981 1.38271328 -1.44428795 -0.70150786 0.90628633
[85] -0.19624296 -0.70261677 0.28456469 0.51898197 -0.45437851 -0.34461323
[91] -0.97647670 -0.07271440 -1.22499649 -1.65659459 -1.86883485 -0.37802960
[97] -1.24970991 -2.07397348 0.55140676 0.03164937
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.089596 0.6425558 0.4607189 0.3301907 -1.481033 0.3975026 1.488823
[2,] -1.089596 0.6425558 0.4607189 0.3301907 -1.481033 0.3975026 1.488823
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.6949635 -0.3111342 -0.806716 -0.5224674 1.062429 1.461034 0.470899
[2,] -0.6949635 -0.3111342 -0.806716 -0.5224674 1.062429 1.461034 0.470899
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.6866458 0.743047 0.1048644 -0.8270393 0.3947884 -0.5509948 -0.5312456
[2,] -0.6866458 0.743047 0.1048644 -0.8270393 0.3947884 -0.5509948 -0.5312456
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.371896 0.6312429 -0.3331754 -2.138482 -0.9923571 0.6741546 1.734719
[2,] 0.371896 0.6312429 -0.3331754 -2.138482 -0.9923571 0.6741546 1.734719
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.2270173 -0.2058377 -0.1279123 -0.4916505 0.5063713 1.155104 -0.3826125
[2,] 0.2270173 -0.2058377 -0.1279123 -0.4916505 0.5063713 1.155104 -0.3826125
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.516375 0.4311745 -1.105391 1.066546 -2.164014 -2.220296 -0.3515502
[2,] -1.516375 0.4311745 -1.105391 1.066546 -2.164014 -2.220296 -0.3515502
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.311333 0.6955533 0.600271 -0.2705499 0.716018 1.062219 1.192277
[2,] -1.311333 0.6955533 0.600271 -0.2705499 0.716018 1.062219 1.192277
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.2335448 -0.5695605 0.3319835 -0.6429529 1.914911 0.5277027 1.471942
[2,] 0.2335448 -0.5695605 0.3319835 -0.6429529 1.914911 0.5277027 1.471942
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.5134035 -1.769771 -0.6125028 -0.8203136 0.198846 -1.231821 -0.8337291
[2,] -0.5134035 -1.769771 -0.6125028 -0.8203136 0.198846 -1.231821 -0.8337291
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.657958 -0.592799 -1.012182 -0.2037943 -0.675155 -0.9979735 0.6753762
[2,] -1.657958 -0.592799 -1.012182 -0.2037943 -0.675155 -0.9979735 0.6753762
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.815086 -1.644843 -0.08322436 0.5253708 0.3061458 -0.4659987 0.8835441
[2,] 0.815086 -1.644843 -0.08322436 0.5253708 0.3061458 -0.4659987 0.8835441
[,78] [,79] [,80] [,81] [,82] [,83] [,84] [,85]
[1,] -1.27 -0.5327 -1.48917 1.382713 -1.444288 -0.7015079 0.9062863 -0.196243
[2,] -1.27 -0.5327 -1.48917 1.382713 -1.444288 -0.7015079 0.9062863 -0.196243
[,86] [,87] [,88] [,89] [,90] [,91] [,92]
[1,] -0.7026168 0.2845647 0.518982 -0.4543785 -0.3446132 -0.9764767 -0.0727144
[2,] -0.7026168 0.2845647 0.518982 -0.4543785 -0.3446132 -0.9764767 -0.0727144
[,93] [,94] [,95] [,96] [,97] [,98] [,99]
[1,] -1.224996 -1.656595 -1.868835 -0.3780296 -1.24971 -2.073973 0.5514068
[2,] -1.224996 -1.656595 -1.868835 -0.3780296 -1.24971 -2.073973 0.5514068
[,100]
[1,] 0.03164937
[2,] 0.03164937
>
>
> Max(tmp2)
[1] 2.481841
> Min(tmp2)
[1] -2.467708
> mean(tmp2)
[1] -0.07930363
> Sum(tmp2)
[1] -7.930363
> Var(tmp2)
[1] 0.9383519
>
> rowMeans(tmp2)
[1] 0.791767411 0.415510809 0.004979237 -0.674000965 -0.126415825
[6] -0.157225341 0.943260373 0.879620523 1.465888641 1.314396848
[11] -1.747285085 0.413802348 1.161416215 -1.663434344 0.595439639
[16] -0.228676288 -1.573547211 -1.210488483 0.203275668 -0.184892919
[21] 0.614752989 -1.222838364 -0.021567343 0.248210057 -1.277513523
[26] 0.173086166 0.385250233 0.106463474 1.540394378 0.681215981
[31] -1.026044290 0.222420989 0.646955491 -1.170285276 -1.824539131
[36] 0.718560389 0.013945655 0.430512306 -1.347302943 -1.458243039
[41] 0.810557472 -1.536446746 0.281243401 -0.048983110 0.458685650
[46] -0.294471530 0.604499512 -2.180551856 0.281095499 0.211009862
[51] -1.454780441 0.484773152 1.507251264 -2.467707693 -0.442439729
[56] -0.134587503 0.517289172 -1.483688371 -0.984672130 -0.202608417
[61] -0.801995404 2.481840877 -0.702501344 -0.046835582 -0.307103536
[66] 1.203620909 -0.755281784 0.336866428 -1.224282062 0.395928105
[71] 1.146092392 -1.703732558 -0.688501066 0.777931117 -0.202883102
[76] 0.750909147 0.759873362 -0.360130129 -0.621551336 -0.573332358
[81] -0.190851219 1.781793971 -0.397460071 -0.456493822 -1.157031765
[86] 0.946335104 -1.037902998 -1.205159924 -0.462031803 1.154337021
[91] 0.195723406 0.582612512 -1.169628312 -0.267006317 1.310455430
[96] 0.053607317 -0.157124035 0.570238593 -0.304914600 1.432913994
> rowSums(tmp2)
[1] 0.791767411 0.415510809 0.004979237 -0.674000965 -0.126415825
[6] -0.157225341 0.943260373 0.879620523 1.465888641 1.314396848
[11] -1.747285085 0.413802348 1.161416215 -1.663434344 0.595439639
[16] -0.228676288 -1.573547211 -1.210488483 0.203275668 -0.184892919
[21] 0.614752989 -1.222838364 -0.021567343 0.248210057 -1.277513523
[26] 0.173086166 0.385250233 0.106463474 1.540394378 0.681215981
[31] -1.026044290 0.222420989 0.646955491 -1.170285276 -1.824539131
[36] 0.718560389 0.013945655 0.430512306 -1.347302943 -1.458243039
[41] 0.810557472 -1.536446746 0.281243401 -0.048983110 0.458685650
[46] -0.294471530 0.604499512 -2.180551856 0.281095499 0.211009862
[51] -1.454780441 0.484773152 1.507251264 -2.467707693 -0.442439729
[56] -0.134587503 0.517289172 -1.483688371 -0.984672130 -0.202608417
[61] -0.801995404 2.481840877 -0.702501344 -0.046835582 -0.307103536
[66] 1.203620909 -0.755281784 0.336866428 -1.224282062 0.395928105
[71] 1.146092392 -1.703732558 -0.688501066 0.777931117 -0.202883102
[76] 0.750909147 0.759873362 -0.360130129 -0.621551336 -0.573332358
[81] -0.190851219 1.781793971 -0.397460071 -0.456493822 -1.157031765
[86] 0.946335104 -1.037902998 -1.205159924 -0.462031803 1.154337021
[91] 0.195723406 0.582612512 -1.169628312 -0.267006317 1.310455430
[96] 0.053607317 -0.157124035 0.570238593 -0.304914600 1.432913994
> 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] 0.791767411 0.415510809 0.004979237 -0.674000965 -0.126415825
[6] -0.157225341 0.943260373 0.879620523 1.465888641 1.314396848
[11] -1.747285085 0.413802348 1.161416215 -1.663434344 0.595439639
[16] -0.228676288 -1.573547211 -1.210488483 0.203275668 -0.184892919
[21] 0.614752989 -1.222838364 -0.021567343 0.248210057 -1.277513523
[26] 0.173086166 0.385250233 0.106463474 1.540394378 0.681215981
[31] -1.026044290 0.222420989 0.646955491 -1.170285276 -1.824539131
[36] 0.718560389 0.013945655 0.430512306 -1.347302943 -1.458243039
[41] 0.810557472 -1.536446746 0.281243401 -0.048983110 0.458685650
[46] -0.294471530 0.604499512 -2.180551856 0.281095499 0.211009862
[51] -1.454780441 0.484773152 1.507251264 -2.467707693 -0.442439729
[56] -0.134587503 0.517289172 -1.483688371 -0.984672130 -0.202608417
[61] -0.801995404 2.481840877 -0.702501344 -0.046835582 -0.307103536
[66] 1.203620909 -0.755281784 0.336866428 -1.224282062 0.395928105
[71] 1.146092392 -1.703732558 -0.688501066 0.777931117 -0.202883102
[76] 0.750909147 0.759873362 -0.360130129 -0.621551336 -0.573332358
[81] -0.190851219 1.781793971 -0.397460071 -0.456493822 -1.157031765
[86] 0.946335104 -1.037902998 -1.205159924 -0.462031803 1.154337021
[91] 0.195723406 0.582612512 -1.169628312 -0.267006317 1.310455430
[96] 0.053607317 -0.157124035 0.570238593 -0.304914600 1.432913994
> rowMin(tmp2)
[1] 0.791767411 0.415510809 0.004979237 -0.674000965 -0.126415825
[6] -0.157225341 0.943260373 0.879620523 1.465888641 1.314396848
[11] -1.747285085 0.413802348 1.161416215 -1.663434344 0.595439639
[16] -0.228676288 -1.573547211 -1.210488483 0.203275668 -0.184892919
[21] 0.614752989 -1.222838364 -0.021567343 0.248210057 -1.277513523
[26] 0.173086166 0.385250233 0.106463474 1.540394378 0.681215981
[31] -1.026044290 0.222420989 0.646955491 -1.170285276 -1.824539131
[36] 0.718560389 0.013945655 0.430512306 -1.347302943 -1.458243039
[41] 0.810557472 -1.536446746 0.281243401 -0.048983110 0.458685650
[46] -0.294471530 0.604499512 -2.180551856 0.281095499 0.211009862
[51] -1.454780441 0.484773152 1.507251264 -2.467707693 -0.442439729
[56] -0.134587503 0.517289172 -1.483688371 -0.984672130 -0.202608417
[61] -0.801995404 2.481840877 -0.702501344 -0.046835582 -0.307103536
[66] 1.203620909 -0.755281784 0.336866428 -1.224282062 0.395928105
[71] 1.146092392 -1.703732558 -0.688501066 0.777931117 -0.202883102
[76] 0.750909147 0.759873362 -0.360130129 -0.621551336 -0.573332358
[81] -0.190851219 1.781793971 -0.397460071 -0.456493822 -1.157031765
[86] 0.946335104 -1.037902998 -1.205159924 -0.462031803 1.154337021
[91] 0.195723406 0.582612512 -1.169628312 -0.267006317 1.310455430
[96] 0.053607317 -0.157124035 0.570238593 -0.304914600 1.432913994
>
> colMeans(tmp2)
[1] -0.07930363
> colSums(tmp2)
[1] -7.930363
> colVars(tmp2)
[1] 0.9383519
> colSd(tmp2)
[1] 0.9686857
> colMax(tmp2)
[1] 2.481841
> colMin(tmp2)
[1] -2.467708
> colMedians(tmp2)
[1] -0.03420146
> colRanges(tmp2)
[,1]
[1,] -2.467708
[2,] 2.481841
>
> 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] -3.2126587 -0.9589422 4.3169527 4.3412068 -6.1967326 0.6837596
[7] -2.3128351 -0.9879024 2.1668545 0.5218219
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.7511657
[2,] -1.0463050
[3,] -0.1876271
[4,] 0.2099284
[5,] 1.2400970
>
> rowApply(tmp,sum)
[1] 4.753201 -1.062192 -3.400807 3.428611 1.280141 -3.918058 2.905477
[8] -1.961399 -1.106766 -2.556682
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 9 2 9 2 8 4 7 1 2
[2,] 5 4 3 10 7 2 1 10 8 3
[3,] 9 10 7 1 8 9 7 3 9 7
[4,] 7 6 10 8 10 5 9 1 7 8
[5,] 4 2 9 2 1 6 3 2 5 4
[6,] 3 3 4 5 9 10 5 4 4 5
[7,] 6 7 1 3 6 1 2 6 10 6
[8,] 2 8 5 4 5 7 10 8 3 1
[9,] 8 5 8 7 3 4 8 5 6 9
[10,] 10 1 6 6 4 3 6 9 2 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.702579279 -5.003790544 1.529611276 0.474992929 0.785234765
[6] -1.998694367 -1.003995388 2.623672066 -1.878672402 -4.738919059
[11] -1.486143240 0.437354621 -0.740674526 1.845738885 0.883256848
[16] 0.002932543 2.180911906 3.716313157 1.560749283 -2.424898539
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.17296053
[2,] 0.01859144
[3,] 0.09140289
[4,] 0.37028862
[5,] 0.39525686
>
> rowApply(tmp,sum)
[1] 5.3668150 -1.5750006 -5.4978437 0.8142677 -1.6406790
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 11 13 16 10 11
[2,] 12 3 4 1 14
[3,] 1 16 7 12 20
[4,] 13 8 5 20 5
[5,] 6 12 11 11 17
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.01859144 0.1720029 -1.3516506 0.4118272 -0.4053870 1.8497478
[2,] 0.39525686 -0.9959314 0.5360855 -0.1401211 0.3814515 -2.4921044
[3,] 0.37028862 -0.9988486 -0.7217580 -0.9242742 -0.4091099 0.6298524
[4,] 0.09140289 -3.4032413 0.2969523 1.8519743 0.1472078 0.4525344
[5,] -0.17296053 0.2222278 2.7699822 -0.7244132 1.0710723 -2.4387246
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.1850174 2.5126819 0.92085836 -0.1716844 -0.7829422 1.1816639
[2,] -0.5513930 1.0230480 -2.18276178 -0.6486348 1.2978631 -0.6999453
[3,] 0.6185463 -0.4621760 0.14179418 -1.1810327 0.4245553 -0.4393585
[4,] 1.0061912 -0.1235293 -0.78734479 -2.3537615 0.4638335 0.9708804
[5,] -0.8923225 -0.3263525 0.02878162 -0.3838057 -2.8894530 -0.5758859
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.08037390 -0.03351926 -1.10172208 1.71714322 -0.06075429 1.2591567
[2,] -0.02335324 0.90964208 -0.09216251 -0.22378499 0.43575888 0.7280414
[3,] -0.47675554 1.10321006 0.36028399 -1.14319251 -0.11323869 -0.3453178
[4,] -0.63035269 -0.25342264 0.42271472 0.01505455 0.06119248 1.0853657
[5,] -0.69058695 0.11982864 1.29414273 -0.36228773 1.85795353 0.9890671
[,19] [,20]
[1,] -0.5052836 -0.1592716
[2,] 0.5305320 0.2375127
[3,] -1.1692691 -0.7620429
[4,] 1.7431373 -0.2425217
[5,] 0.9616327 -1.4985750
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2.3 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 774 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 666 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2.3 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 0.2522884 0.8446543 0.0008347522 0.4641465 -0.1394888 1.610468 0.4132181
col8 col9 col10 col11 col12 col13 col14
row1 -0.3112515 0.5103282 1.529053 0.756957 0.984467 0.2830704 0.3823393
col15 col16 col17 col18 col19 col20
row1 -1.364106 1.336867 1.47724 -1.657921 -0.3300514 0.6336558
> tmp[,"col10"]
col10
row1 1.5290535
row2 1.1778927
row3 0.2352783
row4 -0.8685967
row5 0.3374869
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.2522884 0.8446543 0.0008347522 0.4641465 -0.1394888 1.6104679
row5 -0.4008375 0.9033891 -1.0070492757 -2.4892269 0.8186881 -0.9635527
col7 col8 col9 col10 col11 col12 col13
row1 0.4132181 -0.3112515 0.5103282 1.5290535 0.7569570 0.984467 0.2830704
row5 -0.8605457 -2.3930572 0.8219430 0.3374869 0.6731485 -1.247322 0.4677604
col14 col15 col16 col17 col18 col19 col20
row1 0.3823393 -1.3641056 1.3368670 1.477240 -1.657921 -0.3300514 0.6336558
row5 1.9976864 0.7635486 -0.6968345 1.275888 -1.109085 -0.1059338 -1.9400296
> tmp[,c("col6","col20")]
col6 col20
row1 1.6104679 0.6336558
row2 -1.1897192 -0.5992532
row3 -0.3337769 -0.9831886
row4 -2.6119895 -1.0734735
row5 -0.9635527 -1.9400296
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.6104679 0.6336558
row5 -0.9635527 -1.9400296
>
>
>
>
> 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 50.62772 50.92404 50.44785 48.61287 49.46001 105.3974 48.41615 51.77128
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.52357 47.23063 48.20117 47.53166 51.39022 50.9656 49.14213 50.57082
col17 col18 col19 col20
row1 49.17474 47.70564 50.03204 105.2586
> tmp[,"col10"]
col10
row1 47.23063
row2 29.63216
row3 30.68465
row4 31.13225
row5 50.68639
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.62772 50.92404 50.44785 48.61287 49.46001 105.3974 48.41615 51.77128
row5 50.64119 51.30923 48.95491 47.68950 50.10793 104.4566 49.19783 50.25986
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.52357 47.23063 48.20117 47.53166 51.39022 50.96560 49.14213 50.57082
row5 49.56261 50.68639 49.09931 50.15054 50.64402 49.42592 50.05525 52.04934
col17 col18 col19 col20
row1 49.17474 47.70564 50.03204 105.2586
row5 50.30129 51.21770 49.04153 103.9068
> tmp[,c("col6","col20")]
col6 col20
row1 105.39742 105.25859
row2 75.71140 73.89600
row3 74.05281 74.44639
row4 75.84387 74.57973
row5 104.45662 103.90677
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.3974 105.2586
row5 104.4566 103.9068
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.3974 105.2586
row5 104.4566 103.9068
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.08240551
[2,] 0.73003346
[3,] -0.40747728
[4,] -0.13812649
[5,] -1.52486061
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.4059098 1.0848671
[2,] -0.5903134 0.5731545
[3,] -1.5368647 -1.2267190
[4,] -1.2186613 -0.7544868
[5,] -0.4288373 1.8859725
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 2.9661078 -0.5021463
[2,] -0.8144848 -0.2124292
[3,] 1.6446026 -1.1947241
[4,] 0.6461049 -1.1911963
[5,] 1.0949362 -1.6839229
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 2.966108
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 2.9661078
[2,] -0.8144848
>
>
>
> 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 -0.4997356 -0.06708062 0.1154244 -1.9591044 1.521322 -1.025476 0.1973418
row1 -0.5883052 0.35124541 1.2148214 0.7201455 -0.928605 1.907133 0.3247046
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -0.2689557 -0.3984337 0.2207480 0.8501550 1.223605 0.4655398 -0.8404385
row1 0.3111724 0.3346310 0.8422587 0.9430312 -1.531353 -0.5958156 -0.4355489
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.5337587 0.8397693 0.3271178 0.4733167 -0.1854371 0.2509273
row1 0.4817215 -0.7235817 0.8737510 1.0468505 0.7856614 -0.4234381
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.8274223 0.5681421 -1.550427 1.036412 0.4146437 -0.2757507 0.6498067
[,8] [,9] [,10]
row2 -0.8344673 -0.1450935 -0.7048005
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.7617554 0.1645677 -0.7029063 -0.5198146 -0.5507431 -0.01179033 -1.23649
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.816098 1.484419 0.4273392 -0.8537617 -0.4704599 -1.748838 -0.5298951
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.3370446 -0.5991337 0.9099634 0.6833982 1.423795 -0.4102066
>
>
> 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: 0x56214ce865d0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2275496cc14787"
[2] "/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2275494ba385ae"
[3] "/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2275495e7a3dc"
[4] "/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM22754963cfd5c9"
[5] "/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2275496abe98ac"
[6] "/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2275496aa37e2a"
[7] "/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM22754911b7365b"
[8] "/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM22754979320cbc"
[9] "/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM22754967128e0b"
[10] "/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM22754984affaf"
[11] "/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM227549660c92ae"
[12] "/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2275496a015b6c"
[13] "/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2275492969a3d9"
[14] "/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2275497de01a75"
[15] "/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM22754938326b75"
>
>
> ### 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: 0x56214c4a02d0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x56214c4a02d0>
Warning message:
In dir.create(new.directory) :
'/media/volume/teran2_disk/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x56214c4a02d0>
> rowMedians(tmp)
[1] -0.6179525996 -0.3301841277 0.0061934540 -0.0066350433 0.4851402076
[6] -0.8740802746 0.2771108903 -0.0239734193 0.4555791323 0.5600751880
[11] -0.1331860824 0.4773218896 0.2846184932 0.4008541652 -0.0028499855
[16] 0.1456920543 0.1636451540 -0.2764414882 -0.1758232006 0.0692683449
[21] -0.1762753875 -0.0490202257 0.3361695387 0.2350537842 0.0203434279
[26] -0.3164485157 -0.2084560819 -0.4593909361 -0.5412110969 -0.5457096580
[31] -0.3896402339 0.0969925247 0.1217786182 0.2701580178 -0.5213860401
[36] 0.1889046995 -0.5664824160 0.1039321265 0.3698040812 -0.3672479042
[41] 0.0156314940 -0.0911535128 0.1698550152 -0.1078916613 -0.5529476840
[46] -0.0484870583 0.7682037892 -0.0978976040 -0.1427795286 0.2748991162
[51] 0.1707261766 1.3663536630 0.2437675779 0.2919827307 0.2150988159
[56] -0.0391301722 -0.0649378346 -0.3546222249 -0.4704486355 -0.0571719396
[61] 0.2652625656 0.6298983116 -0.4613538422 0.1165764411 0.1333542911
[66] 0.0240053464 0.1454254746 -0.1507944677 -0.0405820932 0.2981471345
[71] 0.4743621807 -0.0315639090 -0.2021632959 -0.1688184389 -0.4492486168
[76] 0.0379443288 -0.3336559024 0.0952756827 -0.3684354197 -0.0376715870
[81] 0.1052017409 0.2124996637 0.1624942308 0.0691009317 0.2157913842
[86] 0.2362833965 0.4773184570 0.2412663336 0.3568939893 0.0288361547
[91] 0.2753655023 0.2655103351 -0.0216871131 -0.4809736042 0.2289584125
[96] 0.4039583425 0.7246554888 -0.0364949033 -0.0105409330 -0.1098726475
[101] -0.0446204867 0.2415300381 0.3447413759 0.0542519481 -0.0015123269
[106] 0.3125628963 -0.0821508882 0.1313394226 0.3196883179 0.2501460470
[111] -0.3145415251 0.2207504842 -0.5317735621 0.4285520940 -0.0867896924
[116] 0.4348427781 0.2420891897 -0.0696993253 0.1360664851 0.5102352726
[121] -0.0386529281 -0.0687762317 -0.1617523250 -0.3263989391 0.5627605133
[126] -0.0975393922 0.3027276923 -0.2011381005 0.0390864128 0.0630660680
[131] 0.0221842273 -0.4284749044 0.0403268433 0.5701268389 -0.1674251686
[136] 0.0536565362 -0.0983006695 -0.2187680619 0.1656676143 0.1532034488
[141] -0.0059168801 -0.1732639845 -0.2114311359 -0.1612441552 -0.7095567216
[146] 0.4658222085 -0.2043704730 -0.2717875676 0.4390667443 -0.0779763235
[151] 0.2330018946 0.3492597866 0.5605042498 -0.4263070327 -0.6135012651
[156] 0.1643393338 -0.4490731181 -0.1767467065 0.5346786743 0.4281226045
[161] 0.5592829893 -0.1408901027 -0.0551158303 -0.3531538785 -0.1810315676
[166] -0.2493585126 0.1998051286 0.1622034133 -0.3416018631 0.0636889151
[171] 0.0003100947 0.1380646031 0.0448237716 -0.3087811857 -0.1568361808
[176] 0.3197195082 0.1343071496 0.2430392270 -0.2039099499 -0.0355223663
[181] -0.5834724116 -0.3101137881 -0.8408320723 0.0501582814 0.2877061191
[186] -0.3550320581 0.3757228696 0.2214562669 0.2098470580 -0.6338697068
[191] -0.0694854060 -0.0905633435 0.1860693862 -0.2495013307 0.1314547065
[196] -0.2491821674 -0.5588533012 -0.2498452020 -0.6160616142 0.4678994938
[201] -0.0858729977 -0.4732473647 -0.6632131626 0.0941075169 0.0344231024
[206] 0.0692232963 -0.0098549805 0.2045234735 -0.1139005191 -0.5772042432
[211] -0.0947578364 -0.1219144069 0.1519771587 -0.1019458972 -0.2844872404
[216] 0.2851188719 0.4172308090 -0.3876764567 0.3158900450 -0.2144889117
[221] -0.2649305950 -0.2728004930 -0.4488942128 -0.1509656043 -0.5809019421
[226] -0.1631812946 -0.2728820438 -0.3280602443 -0.3273471659 -0.7425423094
>
> proc.time()
user system elapsed
0.957 1.289 2.242
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: 0x5b532f6c49c0>
> .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: 0x5b532f6c49c0>
> .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: 0x5b532f6c49c0>
> .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: 0x5b532f6c49c0>
> 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: 0x5b53317222f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b53317222f0>
> .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: 0x5b53317222f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b53317222f0>
> .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: 0x5b53317222f0>
> 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: 0x5b5331724ad0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b5331724ad0>
> .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: 0x5b5331724ad0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5b5331724ad0>
> .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: 0x5b5331724ad0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5b5331724ad0>
> .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: 0x5b5331724ad0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5b5331724ad0>
> .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: 0x5b5331724ad0>
> 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: 0x5b5331e91930>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5b5331e91930>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b5331e91930>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b5331e91930>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2275db19c2a40f" "BufferedMatrixFile2275db4de45e4d"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2275db19c2a40f" "BufferedMatrixFile2275db4de45e4d"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b5330aa5c20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b5330aa5c20>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5b5330aa5c20>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5b5330aa5c20>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5b5330aa5c20>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5b5330aa5c20>
> .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: 0x5b53307bd1d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5b53307bd1d0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5b53307bd1d0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5b53307bd1d0>
> 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: 0x5b5330bd1510>
> .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: 0x5b5330bd1510>
> rm(P)
>
> proc.time()
user system elapsed
0.172 0.065 0.223
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
0.151 0.062 0.202