Ben Bolstad
| Snapshot Date: 2024-07-03 14:00 -0400 (Wed, 03 Jul 2024) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: d422a05 |
| git_last_commit_date: 2024-04-30 10:16:21 -0400 (Tue, 30 Apr 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2024-07-04 11:44 -0400 (Thu, 04 Jul 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4411 |
| palomino6 | Windows Server 2022 Datacenter | x64 | 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life" | 4413 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4395 |
| kjohnson3 | macOS 13.6.5 Ventura | arm64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4390 |
| kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4407 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 246/2243 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.69.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino6 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | |||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.6.5 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. - See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host. |
| Package: BufferedMatrix |
| Version: 1.69.0 |
| Command: /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.69.0.tar.gz |
| StartedAt: 2024-07-04 03:10:45 -0000 (Thu, 04 Jul 2024) |
| EndedAt: 2024-07-04 03:11:08 -0000 (Thu, 04 Jul 2024) |
| EllapsedTime: 23.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.69.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.0 (2024-04-24)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
gcc (GCC) 12.2.1 20220819 (openEuler 12.2.1-14)
GNU Fortran (GCC) 10.3.1
* running under: openEuler 22.03 (LTS-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.69.0’
* 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 (GCC) 10.3.1’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/R/R-4.4.0/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘gcc (GCC) 10.3.1’
gcc -I"/home/biocbuild/R/R-4.4.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/R/R-4.4.0/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){
| ^~~~~~~~~~~~~~~~~~~
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/R/R-4.4.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"/home/biocbuild/R/R-4.4.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -c init_package.c -o init_package.o
gcc -shared -L/home/biocbuild/R/R-4.4.0/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/R/R-4.4.0/lib -lR
installing to /home/biocbuild/R/R-4.4.0/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 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.328 0.033 0.346
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/home/biocbuild/bbs-3.20-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 471779 25.2 1026215 54.9 643448 34.4
Vcells 871879 6.7 8388608 64.0 2044613 15.6
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu Jul 4 03:11:02 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] "Thu Jul 4 03:11:02 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: 0xbba0f80>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu Jul 4 03:11:03 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] "Thu Jul 4 03:11:03 2024"
>
> ColMode(tmp2)
<pointer: 0xbba0f80>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 101.9489584 2.6850823 -0.1375670 -0.9224852
[2,] -0.1611288 0.1214964 -0.5131305 -0.1389403
[3,] 0.3058150 2.3978093 -1.0889284 -1.0072561
[4,] -0.3008294 -1.7813540 -0.5790982 1.5701434
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 101.9489584 2.6850823 0.1375670 0.9224852
[2,] 0.1611288 0.1214964 0.5131305 0.1389403
[3,] 0.3058150 2.3978093 1.0889284 1.0072561
[4,] 0.3008294 1.7813540 0.5790982 1.5701434
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0969777 1.6386221 0.3709002 0.9604609
[2,] 0.4014086 0.3485633 0.7163313 0.3727469
[3,] 0.5530054 1.5484861 1.0435173 1.0036215
[4,] 0.5484792 1.3346737 0.7609850 1.2530536
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 227.91874 44.07130 28.84657 35.52709
[2,] 29.17521 28.60713 32.67644 28.86641
[3,] 30.83587 42.88267 36.52410 36.04347
[4,] 30.78562 40.12809 33.18895 39.10068
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0xb1378c0>
> exp(tmp5)
<pointer: 0xb1378c0>
> log(tmp5,2)
<pointer: 0xb1378c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 474.383
> Min(tmp5)
[1] 53.70187
> mean(tmp5)
[1] 72.75361
> Sum(tmp5)
[1] 14550.72
> Var(tmp5)
[1] 894.509
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 94.50987 66.80398 69.03001 72.48599 70.77518 70.24732 71.51854 71.17101
[9] 72.40485 68.58935
> rowSums(tmp5)
[1] 1890.197 1336.080 1380.600 1449.720 1415.504 1404.946 1430.371 1423.420
[9] 1448.097 1371.787
> rowVars(tmp5)
[1] 8093.70581 79.04617 67.33729 74.63111 66.01663 95.95189
[7] 84.10111 75.19641 72.99894 76.28450
> rowSd(tmp5)
[1] 89.965025 8.890791 8.205930 8.638930 8.125062 9.795504 9.170666
[8] 8.671586 8.543942 8.734100
> rowMax(tmp5)
[1] 474.38299 86.45821 89.25466 89.38149 88.35351 85.36174 88.76007
[8] 84.46344 85.63396 86.28895
> rowMin(tmp5)
[1] 57.40892 54.95608 58.38411 60.18863 53.70187 54.58762 55.82315 58.22245
[9] 56.72023 55.09924
>
> colMeans(tmp5)
[1] 109.19771 78.38922 68.73694 73.59183 70.86396 72.34868 69.31322
[8] 74.00253 71.24408 68.35464 72.51809 69.01153 67.33698 72.85537
[15] 68.25766 73.10686 70.95012 71.12412 69.56222 64.30642
> colSums(tmp5)
[1] 1091.9771 783.8922 687.3694 735.9183 708.6396 723.4868 693.1322
[8] 740.0253 712.4408 683.5464 725.1809 690.1153 673.3698 728.5537
[15] 682.5766 731.0686 709.5012 711.2412 695.6222 643.0642
> colVars(tmp5)
[1] 16499.43669 89.88019 44.04637 52.92194 81.37279 26.26454
[7] 87.53292 102.08747 50.58550 77.94903 143.83232 58.60967
[13] 48.93274 146.44000 78.15711 68.56540 105.51154 117.72508
[19] 106.45972 51.47228
> colSd(tmp5)
[1] 128.450133 9.480516 6.636744 7.274747 9.020687 5.124894
[7] 9.355903 10.103834 7.112348 8.828875 11.993011 7.655695
[13] 6.995194 12.101240 8.840651 8.280423 10.271881 10.850119
[19] 10.317932 7.174418
> colMax(tmp5)
[1] 474.38299 91.72864 78.35850 84.46344 85.36174 81.70154 79.84766
[8] 85.08034 84.10508 81.72107 90.21755 81.50516 77.74473 89.38149
[15] 80.03725 86.60037 88.35351 88.98009 86.45821 76.89628
> colMin(tmp5)
[1] 60.72439 59.54199 58.22245 60.08165 58.59398 64.29998 55.24274 55.92991
[9] 60.97530 57.40892 56.72023 56.17673 57.78578 54.95608 56.29268 60.18863
[17] 57.38601 57.62496 54.58762 53.70187
>
>
> ### 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] 94.50987 66.80398 69.03001 72.48599 70.77518 70.24732 71.51854 71.17101
[9] 72.40485 NA
> rowSums(tmp5)
[1] 1890.197 1336.080 1380.600 1449.720 1415.504 1404.946 1430.371 1423.420
[9] 1448.097 NA
> rowVars(tmp5)
[1] 8093.70581 79.04617 67.33729 74.63111 66.01663 95.95189
[7] 84.10111 75.19641 72.99894 79.53638
> rowSd(tmp5)
[1] 89.965025 8.890791 8.205930 8.638930 8.125062 9.795504 9.170666
[8] 8.671586 8.543942 8.918317
> rowMax(tmp5)
[1] 474.38299 86.45821 89.25466 89.38149 88.35351 85.36174 88.76007
[8] 84.46344 85.63396 NA
> rowMin(tmp5)
[1] 57.40892 54.95608 58.38411 60.18863 53.70187 54.58762 55.82315 58.22245
[9] 56.72023 NA
>
> colMeans(tmp5)
[1] 109.19771 78.38922 68.73694 73.59183 70.86396 72.34868 69.31322
[8] 74.00253 71.24408 68.35464 72.51809 69.01153 NA 72.85537
[15] 68.25766 73.10686 70.95012 71.12412 69.56222 64.30642
> colSums(tmp5)
[1] 1091.9771 783.8922 687.3694 735.9183 708.6396 723.4868 693.1322
[8] 740.0253 712.4408 683.5464 725.1809 690.1153 NA 728.5537
[15] 682.5766 731.0686 709.5012 711.2412 695.6222 643.0642
> colVars(tmp5)
[1] 16499.43669 89.88019 44.04637 52.92194 81.37279 26.26454
[7] 87.53292 102.08747 50.58550 77.94903 143.83232 58.60967
[13] NA 146.44000 78.15711 68.56540 105.51154 117.72508
[19] 106.45972 51.47228
> colSd(tmp5)
[1] 128.450133 9.480516 6.636744 7.274747 9.020687 5.124894
[7] 9.355903 10.103834 7.112348 8.828875 11.993011 7.655695
[13] NA 12.101240 8.840651 8.280423 10.271881 10.850119
[19] 10.317932 7.174418
> colMax(tmp5)
[1] 474.38299 91.72864 78.35850 84.46344 85.36174 81.70154 79.84766
[8] 85.08034 84.10508 81.72107 90.21755 81.50516 NA 89.38149
[15] 80.03725 86.60037 88.35351 88.98009 86.45821 76.89628
> colMin(tmp5)
[1] 60.72439 59.54199 58.22245 60.08165 58.59398 64.29998 55.24274 55.92991
[9] 60.97530 57.40892 56.72023 56.17673 NA 54.95608 56.29268 60.18863
[17] 57.38601 57.62496 54.58762 53.70187
>
> Max(tmp5,na.rm=TRUE)
[1] 474.383
> Min(tmp5,na.rm=TRUE)
[1] 53.70187
> mean(tmp5,na.rm=TRUE)
[1] 72.79517
> Sum(tmp5,na.rm=TRUE)
[1] 14486.24
> Var(tmp5,na.rm=TRUE)
[1] 898.6795
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 94.50987 66.80398 69.03001 72.48599 70.77518 70.24732 71.51854 71.17101
[9] 72.40485 68.80548
> rowSums(tmp5,na.rm=TRUE)
[1] 1890.197 1336.080 1380.600 1449.720 1415.504 1404.946 1430.371 1423.420
[9] 1448.097 1307.304
> rowVars(tmp5,na.rm=TRUE)
[1] 8093.70581 79.04617 67.33729 74.63111 66.01663 95.95189
[7] 84.10111 75.19641 72.99894 79.53638
> rowSd(tmp5,na.rm=TRUE)
[1] 89.965025 8.890791 8.205930 8.638930 8.125062 9.795504 9.170666
[8] 8.671586 8.543942 8.918317
> rowMax(tmp5,na.rm=TRUE)
[1] 474.38299 86.45821 89.25466 89.38149 88.35351 85.36174 88.76007
[8] 84.46344 85.63396 86.28895
> rowMin(tmp5,na.rm=TRUE)
[1] 57.40892 54.95608 58.38411 60.18863 53.70187 54.58762 55.82315 58.22245
[9] 56.72023 55.09924
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.19771 78.38922 68.73694 73.59183 70.86396 72.34868 69.31322
[8] 74.00253 71.24408 68.35464 72.51809 69.01153 67.65410 72.85537
[15] 68.25766 73.10686 70.95012 71.12412 69.56222 64.30642
> colSums(tmp5,na.rm=TRUE)
[1] 1091.9771 783.8922 687.3694 735.9183 708.6396 723.4868 693.1322
[8] 740.0253 712.4408 683.5464 725.1809 690.1153 608.8869 728.5537
[15] 682.5766 731.0686 709.5012 711.2412 695.6222 643.0642
> colVars(tmp5,na.rm=TRUE)
[1] 16499.43669 89.88019 44.04637 52.92194 81.37279 26.26454
[7] 87.53292 102.08747 50.58550 77.94903 143.83232 58.60967
[13] 53.91795 146.44000 78.15711 68.56540 105.51154 117.72508
[19] 106.45972 51.47228
> colSd(tmp5,na.rm=TRUE)
[1] 128.450133 9.480516 6.636744 7.274747 9.020687 5.124894
[7] 9.355903 10.103834 7.112348 8.828875 11.993011 7.655695
[13] 7.342885 12.101240 8.840651 8.280423 10.271881 10.850119
[19] 10.317932 7.174418
> colMax(tmp5,na.rm=TRUE)
[1] 474.38299 91.72864 78.35850 84.46344 85.36174 81.70154 79.84766
[8] 85.08034 84.10508 81.72107 90.21755 81.50516 77.74473 89.38149
[15] 80.03725 86.60037 88.35351 88.98009 86.45821 76.89628
> colMin(tmp5,na.rm=TRUE)
[1] 60.72439 59.54199 58.22245 60.08165 58.59398 64.29998 55.24274 55.92991
[9] 60.97530 57.40892 56.72023 56.17673 57.78578 54.95608 56.29268 60.18863
[17] 57.38601 57.62496 54.58762 53.70187
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 94.50987 66.80398 69.03001 72.48599 70.77518 70.24732 71.51854 71.17101
[9] 72.40485 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1890.197 1336.080 1380.600 1449.720 1415.504 1404.946 1430.371 1423.420
[9] 1448.097 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 8093.70581 79.04617 67.33729 74.63111 66.01663 95.95189
[7] 84.10111 75.19641 72.99894 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 89.965025 8.890791 8.205930 8.638930 8.125062 9.795504 9.170666
[8] 8.671586 8.543942 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 474.38299 86.45821 89.25466 89.38149 88.35351 85.36174 88.76007
[8] 84.46344 85.63396 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 57.40892 54.95608 58.38411 60.18863 53.70187 54.58762 55.82315 58.22245
[9] 56.72023 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.33784 78.83163 69.34701 73.45622 71.53110 71.94369 69.08856
[8] 76.01060 71.77151 67.12920 70.98800 70.43762 NaN 73.04594
[15] 68.71910 72.58600 72.04572 70.45526 70.61755 65.32944
> colSums(tmp5,na.rm=TRUE)
[1] 1020.0405 709.4847 624.1231 661.1060 643.7799 647.4932 621.7970
[8] 684.0954 645.9436 604.1628 638.8920 633.9386 0.0000 657.4135
[15] 618.4719 653.2740 648.4115 634.0974 635.5579 587.9650
> colVars(tmp5,na.rm=TRUE)
[1] 18369.03397 98.91328 45.36517 59.33029 86.53732 27.70243
[7] 97.90672 69.48457 53.77911 70.79853 135.47295 43.05642
[13] NA 164.33642 85.53130 74.08404 105.19655 127.40785
[19] 107.23791 46.13240
> colSd(tmp5,na.rm=TRUE)
[1] 135.532409 9.945516 6.735367 7.702616 9.302544 5.263310
[7] 9.894783 8.335741 7.333424 8.414186 11.639285 6.561739
[13] NA 12.819377 9.248313 8.607209 10.256537 11.287508
[19] 10.355574 6.792084
> colMax(tmp5,na.rm=TRUE)
[1] 474.38299 91.72864 78.35850 84.46344 85.36174 81.70154 79.84766
[8] 85.08034 84.10508 81.72107 90.21755 81.50516 -Inf 89.38149
[15] 80.03725 86.60037 88.35351 88.98009 86.45821 76.89628
> colMin(tmp5,na.rm=TRUE)
[1] 60.72439 59.54199 58.22245 60.08165 58.59398 64.29998 55.24274 58.34197
[9] 60.97530 57.40892 56.72023 63.54427 Inf 54.95608 56.29268 60.18863
[17] 57.38601 57.62496 54.58762 53.70187
>
>
>
>
> 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] 585.9335 225.7535 291.9066 362.7453 172.0912 264.4948 167.5707 323.5640
[9] 321.5579 598.6300
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 585.9335 225.7535 291.9066 362.7453 172.0912 264.4948 167.5707 323.5640
[9] 321.5579 598.6300
>
>
>
> 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] 2.273737e-13 1.421085e-14 -1.705303e-13 3.410605e-13 1.136868e-13
[6] -2.842171e-14 5.684342e-14 -1.136868e-13 0.000000e+00 0.000000e+00
[11] -8.526513e-14 1.136868e-13 5.684342e-14 8.526513e-14 -2.842171e-14
[16] 0.000000e+00 2.273737e-13 2.273737e-13 -5.684342e-14 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## 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)
+ }
8 15
6 17
9 2
8 14
4 15
5 9
5 15
3 15
5 20
8 12
2 6
1 15
10 10
10 20
3 13
4 8
1 17
6 7
2 20
2 2
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.562772
> Min(tmp)
[1] -1.736795
> mean(tmp)
[1] 0.01508117
> Sum(tmp)
[1] 1.508117
> Var(tmp)
[1] 0.8599195
>
> rowMeans(tmp)
[1] 0.01508117
> rowSums(tmp)
[1] 1.508117
> rowVars(tmp)
[1] 0.8599195
> rowSd(tmp)
[1] 0.9273185
> rowMax(tmp)
[1] 2.562772
> rowMin(tmp)
[1] -1.736795
>
> colMeans(tmp)
[1] 0.71354992 -0.42406884 1.56555760 0.43769887 -0.37904406 1.06012002
[7] -1.68699564 -0.65479724 0.13088091 -0.76292844 -1.49946213 0.49445273
[13] 1.20236026 -1.02495346 0.50194817 1.84629527 -0.92016750 1.79857790
[19] -0.12210866 -0.16750315 -0.26559281 -0.28410257 -1.09255573 -1.35406514
[25] -0.02356704 -0.12664471 0.67390031 1.80682721 0.49800006 -0.99942342
[31] -1.49373721 0.19474450 -0.37136023 1.05795903 0.60593308 -0.81151187
[37] 1.58078809 0.95106829 -0.28678120 0.02992387 -0.04886932 -0.09395709
[43] 0.55863587 -0.64771643 -0.04116704 0.47961924 -0.23515868 0.71458428
[49] -0.07355395 0.77606932 -0.43349059 -1.31209863 0.31128129 -1.10496387
[55] 1.09956760 0.36470992 -0.88010102 -1.49785436 1.03976169 -0.87464476
[61] 0.49430221 -0.19776730 0.10378933 -0.63274589 -1.34516310 -0.47102169
[67] 0.19430715 -0.26637571 0.77608791 0.80946106 -1.34666689 -0.09629073
[73] 1.11060996 -0.64688502 1.07622994 -1.07117016 0.44297229 0.16238502
[79] -0.24464240 0.93067532 0.45086239 2.56277217 -0.50734389 -1.73679472
[85] 0.47045888 -0.48604266 -1.16501087 -0.99384438 -0.03211560 -1.56862094
[91] 0.85129302 0.19406417 -0.20369894 1.14032784 0.55286413 0.76323806
[97] -0.60898275 -1.09217075 2.25783416 0.37706768
> colSums(tmp)
[1] 0.71354992 -0.42406884 1.56555760 0.43769887 -0.37904406 1.06012002
[7] -1.68699564 -0.65479724 0.13088091 -0.76292844 -1.49946213 0.49445273
[13] 1.20236026 -1.02495346 0.50194817 1.84629527 -0.92016750 1.79857790
[19] -0.12210866 -0.16750315 -0.26559281 -0.28410257 -1.09255573 -1.35406514
[25] -0.02356704 -0.12664471 0.67390031 1.80682721 0.49800006 -0.99942342
[31] -1.49373721 0.19474450 -0.37136023 1.05795903 0.60593308 -0.81151187
[37] 1.58078809 0.95106829 -0.28678120 0.02992387 -0.04886932 -0.09395709
[43] 0.55863587 -0.64771643 -0.04116704 0.47961924 -0.23515868 0.71458428
[49] -0.07355395 0.77606932 -0.43349059 -1.31209863 0.31128129 -1.10496387
[55] 1.09956760 0.36470992 -0.88010102 -1.49785436 1.03976169 -0.87464476
[61] 0.49430221 -0.19776730 0.10378933 -0.63274589 -1.34516310 -0.47102169
[67] 0.19430715 -0.26637571 0.77608791 0.80946106 -1.34666689 -0.09629073
[73] 1.11060996 -0.64688502 1.07622994 -1.07117016 0.44297229 0.16238502
[79] -0.24464240 0.93067532 0.45086239 2.56277217 -0.50734389 -1.73679472
[85] 0.47045888 -0.48604266 -1.16501087 -0.99384438 -0.03211560 -1.56862094
[91] 0.85129302 0.19406417 -0.20369894 1.14032784 0.55286413 0.76323806
[97] -0.60898275 -1.09217075 2.25783416 0.37706768
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] 0.71354992 -0.42406884 1.56555760 0.43769887 -0.37904406 1.06012002
[7] -1.68699564 -0.65479724 0.13088091 -0.76292844 -1.49946213 0.49445273
[13] 1.20236026 -1.02495346 0.50194817 1.84629527 -0.92016750 1.79857790
[19] -0.12210866 -0.16750315 -0.26559281 -0.28410257 -1.09255573 -1.35406514
[25] -0.02356704 -0.12664471 0.67390031 1.80682721 0.49800006 -0.99942342
[31] -1.49373721 0.19474450 -0.37136023 1.05795903 0.60593308 -0.81151187
[37] 1.58078809 0.95106829 -0.28678120 0.02992387 -0.04886932 -0.09395709
[43] 0.55863587 -0.64771643 -0.04116704 0.47961924 -0.23515868 0.71458428
[49] -0.07355395 0.77606932 -0.43349059 -1.31209863 0.31128129 -1.10496387
[55] 1.09956760 0.36470992 -0.88010102 -1.49785436 1.03976169 -0.87464476
[61] 0.49430221 -0.19776730 0.10378933 -0.63274589 -1.34516310 -0.47102169
[67] 0.19430715 -0.26637571 0.77608791 0.80946106 -1.34666689 -0.09629073
[73] 1.11060996 -0.64688502 1.07622994 -1.07117016 0.44297229 0.16238502
[79] -0.24464240 0.93067532 0.45086239 2.56277217 -0.50734389 -1.73679472
[85] 0.47045888 -0.48604266 -1.16501087 -0.99384438 -0.03211560 -1.56862094
[91] 0.85129302 0.19406417 -0.20369894 1.14032784 0.55286413 0.76323806
[97] -0.60898275 -1.09217075 2.25783416 0.37706768
> colMin(tmp)
[1] 0.71354992 -0.42406884 1.56555760 0.43769887 -0.37904406 1.06012002
[7] -1.68699564 -0.65479724 0.13088091 -0.76292844 -1.49946213 0.49445273
[13] 1.20236026 -1.02495346 0.50194817 1.84629527 -0.92016750 1.79857790
[19] -0.12210866 -0.16750315 -0.26559281 -0.28410257 -1.09255573 -1.35406514
[25] -0.02356704 -0.12664471 0.67390031 1.80682721 0.49800006 -0.99942342
[31] -1.49373721 0.19474450 -0.37136023 1.05795903 0.60593308 -0.81151187
[37] 1.58078809 0.95106829 -0.28678120 0.02992387 -0.04886932 -0.09395709
[43] 0.55863587 -0.64771643 -0.04116704 0.47961924 -0.23515868 0.71458428
[49] -0.07355395 0.77606932 -0.43349059 -1.31209863 0.31128129 -1.10496387
[55] 1.09956760 0.36470992 -0.88010102 -1.49785436 1.03976169 -0.87464476
[61] 0.49430221 -0.19776730 0.10378933 -0.63274589 -1.34516310 -0.47102169
[67] 0.19430715 -0.26637571 0.77608791 0.80946106 -1.34666689 -0.09629073
[73] 1.11060996 -0.64688502 1.07622994 -1.07117016 0.44297229 0.16238502
[79] -0.24464240 0.93067532 0.45086239 2.56277217 -0.50734389 -1.73679472
[85] 0.47045888 -0.48604266 -1.16501087 -0.99384438 -0.03211560 -1.56862094
[91] 0.85129302 0.19406417 -0.20369894 1.14032784 0.55286413 0.76323806
[97] -0.60898275 -1.09217075 2.25783416 0.37706768
> colMedians(tmp)
[1] 0.71354992 -0.42406884 1.56555760 0.43769887 -0.37904406 1.06012002
[7] -1.68699564 -0.65479724 0.13088091 -0.76292844 -1.49946213 0.49445273
[13] 1.20236026 -1.02495346 0.50194817 1.84629527 -0.92016750 1.79857790
[19] -0.12210866 -0.16750315 -0.26559281 -0.28410257 -1.09255573 -1.35406514
[25] -0.02356704 -0.12664471 0.67390031 1.80682721 0.49800006 -0.99942342
[31] -1.49373721 0.19474450 -0.37136023 1.05795903 0.60593308 -0.81151187
[37] 1.58078809 0.95106829 -0.28678120 0.02992387 -0.04886932 -0.09395709
[43] 0.55863587 -0.64771643 -0.04116704 0.47961924 -0.23515868 0.71458428
[49] -0.07355395 0.77606932 -0.43349059 -1.31209863 0.31128129 -1.10496387
[55] 1.09956760 0.36470992 -0.88010102 -1.49785436 1.03976169 -0.87464476
[61] 0.49430221 -0.19776730 0.10378933 -0.63274589 -1.34516310 -0.47102169
[67] 0.19430715 -0.26637571 0.77608791 0.80946106 -1.34666689 -0.09629073
[73] 1.11060996 -0.64688502 1.07622994 -1.07117016 0.44297229 0.16238502
[79] -0.24464240 0.93067532 0.45086239 2.56277217 -0.50734389 -1.73679472
[85] 0.47045888 -0.48604266 -1.16501087 -0.99384438 -0.03211560 -1.56862094
[91] 0.85129302 0.19406417 -0.20369894 1.14032784 0.55286413 0.76323806
[97] -0.60898275 -1.09217075 2.25783416 0.37706768
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.7135499 -0.4240688 1.565558 0.4376989 -0.3790441 1.06012 -1.686996
[2,] 0.7135499 -0.4240688 1.565558 0.4376989 -0.3790441 1.06012 -1.686996
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.6547972 0.1308809 -0.7629284 -1.499462 0.4944527 1.20236 -1.024953
[2,] -0.6547972 0.1308809 -0.7629284 -1.499462 0.4944527 1.20236 -1.024953
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.5019482 1.846295 -0.9201675 1.798578 -0.1221087 -0.1675031 -0.2655928
[2,] 0.5019482 1.846295 -0.9201675 1.798578 -0.1221087 -0.1675031 -0.2655928
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.2841026 -1.092556 -1.354065 -0.02356704 -0.1266447 0.6739003 1.806827
[2,] -0.2841026 -1.092556 -1.354065 -0.02356704 -0.1266447 0.6739003 1.806827
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.4980001 -0.9994234 -1.493737 0.1947445 -0.3713602 1.057959 0.6059331
[2,] 0.4980001 -0.9994234 -1.493737 0.1947445 -0.3713602 1.057959 0.6059331
[,36] [,37] [,38] [,39] [,40] [,41]
[1,] -0.8115119 1.580788 0.9510683 -0.2867812 0.02992387 -0.04886932
[2,] -0.8115119 1.580788 0.9510683 -0.2867812 0.02992387 -0.04886932
[,42] [,43] [,44] [,45] [,46] [,47]
[1,] -0.09395709 0.5586359 -0.6477164 -0.04116704 0.4796192 -0.2351587
[2,] -0.09395709 0.5586359 -0.6477164 -0.04116704 0.4796192 -0.2351587
[,48] [,49] [,50] [,51] [,52] [,53] [,54]
[1,] 0.7145843 -0.07355395 0.7760693 -0.4334906 -1.312099 0.3112813 -1.104964
[2,] 0.7145843 -0.07355395 0.7760693 -0.4334906 -1.312099 0.3112813 -1.104964
[,55] [,56] [,57] [,58] [,59] [,60] [,61]
[1,] 1.099568 0.3647099 -0.880101 -1.497854 1.039762 -0.8746448 0.4943022
[2,] 1.099568 0.3647099 -0.880101 -1.497854 1.039762 -0.8746448 0.4943022
[,62] [,63] [,64] [,65] [,66] [,67] [,68]
[1,] -0.1977673 0.1037893 -0.6327459 -1.345163 -0.4710217 0.1943071 -0.2663757
[2,] -0.1977673 0.1037893 -0.6327459 -1.345163 -0.4710217 0.1943071 -0.2663757
[,69] [,70] [,71] [,72] [,73] [,74] [,75]
[1,] 0.7760879 0.8094611 -1.346667 -0.09629073 1.11061 -0.646885 1.07623
[2,] 0.7760879 0.8094611 -1.346667 -0.09629073 1.11061 -0.646885 1.07623
[,76] [,77] [,78] [,79] [,80] [,81] [,82]
[1,] -1.07117 0.4429723 0.162385 -0.2446424 0.9306753 0.4508624 2.562772
[2,] -1.07117 0.4429723 0.162385 -0.2446424 0.9306753 0.4508624 2.562772
[,83] [,84] [,85] [,86] [,87] [,88] [,89]
[1,] -0.5073439 -1.736795 0.4704589 -0.4860427 -1.165011 -0.9938444 -0.0321156
[2,] -0.5073439 -1.736795 0.4704589 -0.4860427 -1.165011 -0.9938444 -0.0321156
[,90] [,91] [,92] [,93] [,94] [,95] [,96]
[1,] -1.568621 0.851293 0.1940642 -0.2036989 1.140328 0.5528641 0.7632381
[2,] -1.568621 0.851293 0.1940642 -0.2036989 1.140328 0.5528641 0.7632381
[,97] [,98] [,99] [,100]
[1,] -0.6089828 -1.092171 2.257834 0.3770677
[2,] -0.6089828 -1.092171 2.257834 0.3770677
>
>
> Max(tmp2)
[1] 2.407871
> Min(tmp2)
[1] -2.568567
> mean(tmp2)
[1] 0.1057972
> Sum(tmp2)
[1] 10.57972
> Var(tmp2)
[1] 1.169424
>
> rowMeans(tmp2)
[1] 0.874546410 0.385370845 0.981049393 1.208664609 1.752067551
[6] -0.131165222 -0.693343692 -0.394158000 -0.742657752 -1.025351203
[11] 1.760383120 0.916713332 0.628959189 -0.999107417 1.967018951
[16] 0.044463240 -1.577406525 1.061391513 1.129387464 -0.874222747
[21] 0.155780765 1.704330906 0.258132512 -1.561689729 0.375924717
[26] -0.353939674 -0.634166243 -2.098810552 0.624531959 1.922843683
[31] -1.297700950 -1.281141331 0.458506349 -1.792479584 -0.087474532
[36] 1.647093189 -0.684860620 1.641686758 2.297655517 0.231019453
[41] 0.814666363 0.026742825 0.609882628 -0.321463452 -0.319818469
[46] -0.099193307 1.003253891 1.678353871 0.761561286 1.210062400
[51] 1.468083360 -0.158774403 -0.395242929 0.099448144 0.649180843
[56] -0.318683565 0.084145740 -0.063172408 -1.810723329 -1.668970430
[61] -1.197231856 0.374858164 -1.463057858 -2.568567193 0.172885972
[66] -0.901957036 0.783187017 -0.728038844 1.700498062 -0.061855350
[71] 1.655590993 0.672812011 0.172091948 0.855859263 0.399813130
[76] 2.407871116 0.933265946 0.186939074 0.331461612 0.008585435
[81] -2.498229860 0.684669856 -0.910549018 0.196225252 -0.550558074
[86] 0.595341210 -0.093830508 -0.403965132 -0.685437699 -1.166176600
[91] 0.989145083 1.860153801 0.198476131 0.705638696 -0.612196765
[96] 0.595435474 -0.464385266 -1.085752885 -0.969980551 -0.586501461
> rowSums(tmp2)
[1] 0.874546410 0.385370845 0.981049393 1.208664609 1.752067551
[6] -0.131165222 -0.693343692 -0.394158000 -0.742657752 -1.025351203
[11] 1.760383120 0.916713332 0.628959189 -0.999107417 1.967018951
[16] 0.044463240 -1.577406525 1.061391513 1.129387464 -0.874222747
[21] 0.155780765 1.704330906 0.258132512 -1.561689729 0.375924717
[26] -0.353939674 -0.634166243 -2.098810552 0.624531959 1.922843683
[31] -1.297700950 -1.281141331 0.458506349 -1.792479584 -0.087474532
[36] 1.647093189 -0.684860620 1.641686758 2.297655517 0.231019453
[41] 0.814666363 0.026742825 0.609882628 -0.321463452 -0.319818469
[46] -0.099193307 1.003253891 1.678353871 0.761561286 1.210062400
[51] 1.468083360 -0.158774403 -0.395242929 0.099448144 0.649180843
[56] -0.318683565 0.084145740 -0.063172408 -1.810723329 -1.668970430
[61] -1.197231856 0.374858164 -1.463057858 -2.568567193 0.172885972
[66] -0.901957036 0.783187017 -0.728038844 1.700498062 -0.061855350
[71] 1.655590993 0.672812011 0.172091948 0.855859263 0.399813130
[76] 2.407871116 0.933265946 0.186939074 0.331461612 0.008585435
[81] -2.498229860 0.684669856 -0.910549018 0.196225252 -0.550558074
[86] 0.595341210 -0.093830508 -0.403965132 -0.685437699 -1.166176600
[91] 0.989145083 1.860153801 0.198476131 0.705638696 -0.612196765
[96] 0.595435474 -0.464385266 -1.085752885 -0.969980551 -0.586501461
> 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] 0.874546410 0.385370845 0.981049393 1.208664609 1.752067551
[6] -0.131165222 -0.693343692 -0.394158000 -0.742657752 -1.025351203
[11] 1.760383120 0.916713332 0.628959189 -0.999107417 1.967018951
[16] 0.044463240 -1.577406525 1.061391513 1.129387464 -0.874222747
[21] 0.155780765 1.704330906 0.258132512 -1.561689729 0.375924717
[26] -0.353939674 -0.634166243 -2.098810552 0.624531959 1.922843683
[31] -1.297700950 -1.281141331 0.458506349 -1.792479584 -0.087474532
[36] 1.647093189 -0.684860620 1.641686758 2.297655517 0.231019453
[41] 0.814666363 0.026742825 0.609882628 -0.321463452 -0.319818469
[46] -0.099193307 1.003253891 1.678353871 0.761561286 1.210062400
[51] 1.468083360 -0.158774403 -0.395242929 0.099448144 0.649180843
[56] -0.318683565 0.084145740 -0.063172408 -1.810723329 -1.668970430
[61] -1.197231856 0.374858164 -1.463057858 -2.568567193 0.172885972
[66] -0.901957036 0.783187017 -0.728038844 1.700498062 -0.061855350
[71] 1.655590993 0.672812011 0.172091948 0.855859263 0.399813130
[76] 2.407871116 0.933265946 0.186939074 0.331461612 0.008585435
[81] -2.498229860 0.684669856 -0.910549018 0.196225252 -0.550558074
[86] 0.595341210 -0.093830508 -0.403965132 -0.685437699 -1.166176600
[91] 0.989145083 1.860153801 0.198476131 0.705638696 -0.612196765
[96] 0.595435474 -0.464385266 -1.085752885 -0.969980551 -0.586501461
> rowMin(tmp2)
[1] 0.874546410 0.385370845 0.981049393 1.208664609 1.752067551
[6] -0.131165222 -0.693343692 -0.394158000 -0.742657752 -1.025351203
[11] 1.760383120 0.916713332 0.628959189 -0.999107417 1.967018951
[16] 0.044463240 -1.577406525 1.061391513 1.129387464 -0.874222747
[21] 0.155780765 1.704330906 0.258132512 -1.561689729 0.375924717
[26] -0.353939674 -0.634166243 -2.098810552 0.624531959 1.922843683
[31] -1.297700950 -1.281141331 0.458506349 -1.792479584 -0.087474532
[36] 1.647093189 -0.684860620 1.641686758 2.297655517 0.231019453
[41] 0.814666363 0.026742825 0.609882628 -0.321463452 -0.319818469
[46] -0.099193307 1.003253891 1.678353871 0.761561286 1.210062400
[51] 1.468083360 -0.158774403 -0.395242929 0.099448144 0.649180843
[56] -0.318683565 0.084145740 -0.063172408 -1.810723329 -1.668970430
[61] -1.197231856 0.374858164 -1.463057858 -2.568567193 0.172885972
[66] -0.901957036 0.783187017 -0.728038844 1.700498062 -0.061855350
[71] 1.655590993 0.672812011 0.172091948 0.855859263 0.399813130
[76] 2.407871116 0.933265946 0.186939074 0.331461612 0.008585435
[81] -2.498229860 0.684669856 -0.910549018 0.196225252 -0.550558074
[86] 0.595341210 -0.093830508 -0.403965132 -0.685437699 -1.166176600
[91] 0.989145083 1.860153801 0.198476131 0.705638696 -0.612196765
[96] 0.595435474 -0.464385266 -1.085752885 -0.969980551 -0.586501461
>
> colMeans(tmp2)
[1] 0.1057972
> colSums(tmp2)
[1] 10.57972
> colVars(tmp2)
[1] 1.169424
> colSd(tmp2)
[1] 1.081399
> colMax(tmp2)
[1] 2.407871
> colMin(tmp2)
[1] -2.568567
> colMedians(tmp2)
[1] 0.1639364
> colRanges(tmp2)
[,1]
[1,] -2.568567
[2,] 2.407871
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.5189918 -3.9418032 1.9084090 4.0275148 2.1205116 -4.4955287
[7] 3.8411284 3.4182901 -2.0777827 0.2510892
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.9322848
[2,] -0.6140034
[3,] -0.1742893
[4,] 0.6171259
[5,] 2.3700191
>
> rowApply(tmp,sum)
[1] 0.03402486 4.26790332 -3.40763628 6.05115997 1.53753642 -0.88196968
[7] 5.66949129 1.62177602 -5.62574453 -2.69572093
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 4 4 8 7 10 3 10 4 4 5
[2,] 8 5 5 3 3 10 1 1 1 2
[3,] 3 3 6 4 6 6 8 8 5 8
[4,] 10 7 7 9 2 9 6 3 8 7
[5,] 2 9 3 2 8 2 2 6 10 9
[6,] 1 2 9 1 1 1 7 7 3 6
[7,] 5 6 10 5 5 4 5 9 6 10
[8,] 6 8 4 8 4 5 4 10 2 4
[9,] 7 1 2 6 9 8 9 5 7 1
[10,] 9 10 1 10 7 7 3 2 9 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.8020290 3.1324077 -3.2305682 5.4197476 -1.2253614 1.0053361
[7] -2.5469034 -1.6832253 1.5823399 2.2039316 -0.1375585 -1.7659818
[13] -2.5538808 4.0283909 0.1032667 4.7759057 -1.4866193 -4.2831209
[19] 0.2905197 0.4732657
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.3341528
[2,] -0.1183944
[3,] 0.1120219
[4,] 0.4055470
[5,] 0.7370072
>
> rowApply(tmp,sum)
[1] -0.3564578 -1.8673730 0.3781539 2.4218471 4.3277506
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 11 15 10 7 12
[2,] 15 12 17 13 18
[3,] 10 3 8 6 4
[4,] 14 17 19 16 14
[5,] 16 2 13 10 7
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.1120219 0.5033850 -0.0348859 0.4375832 0.60730054 -0.7050415
[2,] 0.7370072 0.2318722 -1.2307875 1.0297883 -1.54740294 1.0645092
[3,] -0.3341528 1.0231442 -0.6985279 2.4077754 -0.06405069 -0.1113077
[4,] -0.1183944 0.3112147 -0.2644713 1.0037900 0.04245246 1.0634218
[5,] 0.4055470 1.0627915 -1.0018955 0.5408107 -0.26366081 -0.3062457
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.9728742 -0.7951347 1.0267846 0.698978956 0.3638295 -0.5277074
[2,] 0.7278093 -0.6046639 -1.0082832 0.002294644 -1.1792151 0.5649295
[3,] -1.1374449 0.8966677 -1.0061178 0.891130588 -0.8424923 -0.9360657
[4,] -0.7039640 -2.2352980 2.3191260 0.260679002 1.1446922 -1.5571564
[5,] -0.4604296 1.0552034 0.2508302 0.350848453 0.3756272 0.6900181
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.12923747 1.02089246 -0.3642691 -0.6244821 -0.19062581 -0.98811933
[2,] -0.49070214 1.16429912 0.8157482 1.3900910 0.08313939 -0.02353339
[3,] -0.97578656 1.11417053 -0.8928007 0.3954635 -0.43080932 -1.47379282
[4,] -0.08364712 -0.05056194 0.1389791 1.2373383 0.93722920 -0.60414681
[5,] -1.13298240 0.77959073 0.4056092 2.3774949 -1.88555273 -1.19352852
[,19] [,20]
[1,] -1.1273357 1.07400413
[2,] -2.5507050 -1.04356802
[3,] 2.6358322 -0.08268102
[4,] -0.7496282 0.33019255
[5,] 2.0823565 0.19531804
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 649 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 562 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -1.14581 -0.9449052 -1.488527 0.04509522 0.08377078 -0.06878277 -0.2829624
col8 col9 col10 col11 col12 col13 col14
row1 0.1930403 -0.4219259 -0.92881 0.09869351 0.6019794 -0.1985988 0.1114748
col15 col16 col17 col18 col19 col20
row1 -0.9886464 -1.141287 1.639117 -1.051711 -1.523576 -0.04850908
> tmp[,"col10"]
col10
row1 -0.92881002
row2 -1.65068787
row3 -0.02951375
row4 -0.59805831
row5 -0.75148157
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -1.145810 -0.9449052 -1.488527 0.04509522 0.08377078 -0.06878277
row5 1.064542 2.0366758 1.356440 0.07713771 0.84029629 -0.61990476
col7 col8 col9 col10 col11 col12
row1 -0.2829624 0.1930403 -0.4219259 -0.9288100 0.09869351 0.6019794
row5 0.5515710 0.2898213 -0.2972257 -0.7514816 0.24005795 -0.2479326
col13 col14 col15 col16 col17 col18
row1 -0.1985988 0.1114748 -0.9886464 -1.14128655 1.6391174 -1.051711
row5 -2.1247561 -0.6369654 0.3796694 0.07436444 -0.2813172 -1.698730
col19 col20
row1 -1.5235756 -0.04850908
row5 -0.6255938 0.94099251
> tmp[,c("col6","col20")]
col6 col20
row1 -0.06878277 -0.04850908
row2 -0.69189599 -1.11593182
row3 0.61767391 0.39020504
row4 -0.57033154 -0.46584329
row5 -0.61990476 0.94099251
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.06878277 -0.04850908
row5 -0.61990476 0.94099251
>
>
>
>
> 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 51.07329 50.66396 50.40452 50.19818 50.03059 106.3719 51.42987 50.61503
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.93781 47.76167 49.25001 50.87474 49.10511 50.47196 51.00927 49.82769
col17 col18 col19 col20
row1 49.17537 49.49881 50.19683 103.3815
> tmp[,"col10"]
col10
row1 47.76167
row2 29.12288
row3 29.41792
row4 29.80148
row5 49.48397
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.07329 50.66396 50.40452 50.19818 50.03059 106.3719 51.42987 50.61503
row5 48.26567 49.10685 50.41500 50.04762 51.35151 105.6827 50.69846 50.49467
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.93781 47.76167 49.25001 50.87474 49.10511 50.47196 51.00927 49.82769
row5 50.27258 49.48397 51.89025 49.44865 48.55005 50.46084 50.72168 49.85643
col17 col18 col19 col20
row1 49.17537 49.49881 50.19683 103.3815
row5 49.88354 50.00427 49.51978 104.1065
> tmp[,c("col6","col20")]
col6 col20
row1 106.37193 103.38155
row2 75.63105 75.63296
row3 73.89535 76.01057
row4 75.02472 74.13434
row5 105.68268 104.10647
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.3719 103.3815
row5 105.6827 104.1065
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.3719 103.3815
row5 105.6827 104.1065
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.9138745
[2,] -0.2647402
[3,] -0.1808509
[4,] -0.5973214
[5,] 0.4786659
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.3223363 -1.6785239
[2,] -0.1370587 -0.7264519
[3,] 0.5609418 -0.8976143
[4,] 0.2230693 -0.6381543
[5,] 0.3256787 -0.3577095
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.3879093 0.3014641
[2,] 0.9972987 0.9348224
[3,] 0.3464088 -0.9722929
[4,] 0.2072140 1.2604038
[5,] 2.4263016 0.6050679
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.3879093
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.3879093
[2,] 0.9972987
>
>
>
> 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]
row3 0.04394579 -0.168838 -0.1125902 -0.8907502 -1.739166 -0.8157974
row1 -0.73198653 -1.157386 0.2189898 0.3476206 1.452417 -0.2292160
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 0.4470057 -0.3706429 0.6908462 1.472623 -0.7053339 0.6339252 -0.7339346
row1 -0.5810141 0.8422867 -0.9116364 0.323044 -0.2250271 0.9270681 -0.2169924
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 1.2009764 1.6813216 0.5725456 1.5028694 -0.4435314 1.311552 -1.2078781
row1 -0.1463845 0.1969614 1.4279267 0.1509327 0.2361629 1.095110 0.7326315
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.059284 2.455392 -0.7053851 0.4007506 -1.068066 -0.6216058 1.292686
[,8] [,9] [,10]
row2 0.06426854 -0.06515555 -2.087553
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.5629334 -1.279904 0.6123316 -0.9822183 1.547063 0.2047645 -0.211292
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.650604 1.116398 -0.3463651 1.075844 1.001142 -1.257458 1.855337
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.05020951 0.648302 0.1727949 0.4129978 -0.7629015 -0.7507707
>
>
> 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: 0xc9642f0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMcbda61497ebd8"
[2] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMcbda610fc89a6"
[3] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMcbda63ef005d3"
[4] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMcbda64ed7758e"
[5] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMcbda62909b109"
[6] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMcbda670978a4c"
[7] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMcbda663073bc3"
[8] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMcbda6749f35d3"
[9] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMcbda637e570f3"
[10] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMcbda636351aaa"
[11] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMcbda6285f582f"
[12] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMcbda641f4076f"
[13] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMcbda67e2a26c1"
[14] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMcbda620c1b50f"
[15] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BMcbda67a457d7e"
>
>
> ### 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: 0xb4a55d0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0xb4a55d0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0xb4a55d0>
> rowMedians(tmp)
[1] -0.047180989 0.190968111 0.264847533 -0.095656426 -0.590129742
[6] -0.129658549 0.021370158 0.426150484 0.162990544 0.152436225
[11] 0.144304271 -0.211381912 -0.383538818 0.338679687 0.398673646
[16] 0.100928902 0.078579763 0.174035667 0.077959177 0.212205725
[21] -0.446313850 -0.427038372 -0.357304200 -0.086697225 -0.144814056
[26] 0.409457100 -0.428194825 0.002773594 -0.309130421 -0.069361783
[31] -0.808103867 0.228874400 -0.475305112 -0.091245327 0.383620686
[36] -0.202765278 -0.408774003 0.444169857 -0.133913946 -0.015531990
[41] 0.107267390 0.165373876 -0.416551333 -0.162214931 -0.352450286
[46] 0.006563975 -0.066951450 0.379493066 -0.078474978 0.299749665
[51] 0.565470197 -1.049713225 -0.024329033 -0.171486563 -0.004072087
[56] 0.038017250 -0.377233977 0.317464129 0.030165383 0.211278277
[61] -0.022002975 0.261317642 -0.424221175 -0.357785311 0.180843411
[66] 0.052397131 0.409774329 -0.162077654 -0.187768474 0.004469668
[71] -0.452656432 0.337183969 0.213935715 0.529143071 -0.033843960
[76] 0.425293081 -0.558626935 0.029774725 -0.084587372 -0.621422360
[81] 0.324619363 0.776459265 -0.239926534 0.228774619 0.207462066
[86] -0.254556277 -0.753726479 -0.201525716 0.032690222 -0.463435782
[91] -0.195121456 -0.212817491 -0.079328723 0.140074728 -0.283467302
[96] 0.041629732 0.098820572 -0.325965344 -0.341960857 0.036778582
[101] 0.272545988 -0.492534047 -0.086130214 -0.147757569 -0.347016445
[106] -0.211762931 -0.013704234 0.003549650 0.175352157 0.307246369
[111] 0.300436513 0.541235363 0.129845606 0.299969918 0.565603132
[116] 0.039608097 0.185617854 -0.204859075 0.620500828 0.147446460
[121] 0.471117873 -0.049874482 0.280296466 -0.042739781 -0.543726432
[126] -0.646906555 0.124971537 0.466431161 -0.333969474 0.396614174
[131] 0.433498838 0.006616274 0.207589477 -0.223061666 0.626742598
[136] -0.140973744 0.053687784 0.104262087 -0.119465668 0.226733957
[141] -0.324302371 0.247330266 0.298443345 -0.543541764 -0.247869702
[146] -0.338372882 0.061204200 -0.534116097 -0.202016712 -0.018639385
[151] -0.356089516 -0.195999095 0.456009013 -0.332347290 0.116386717
[156] 0.103776942 0.121171996 0.121159070 -0.556398568 0.558458230
[161] 0.476850899 0.107157937 -0.358632995 -0.323888666 0.074054637
[166] 0.080427875 -0.007015493 0.405586619 0.477768324 0.211648356
[171] -0.110452608 -0.001335742 -0.279877023 -0.176125851 0.386739434
[176] -0.030070174 0.047832150 0.613922879 -0.131346759 0.023041901
[181] -0.559499804 -0.110239139 -0.081967659 -0.075679753 0.237818326
[186] 0.088695401 0.018433150 -0.458187834 -0.496792842 -0.188821638
[191] 0.600097900 0.422620742 -0.205471897 -0.451208077 0.264391371
[196] -0.372788173 -0.139986371 0.083189595 -0.445052230 -0.385588546
[201] -0.250649613 0.217693839 -0.153546707 -0.430631147 -0.075042225
[206] -0.323200628 -0.577523962 -0.208982077 -0.337273016 0.343449983
[211] -0.037767189 -0.103852054 -0.450110803 0.273522540 -0.514698423
[216] -0.021365834 -0.226316200 -0.186715293 -0.859859292 0.275729943
[221] 0.438942464 -0.335331095 0.120364697 0.957936593 0.277424014
[226] 0.136118967 -0.205160984 0.401116117 0.525925249 -0.542871849
>
> proc.time()
user system elapsed
2.006 0.829 2.855
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x35ef2f80>
> .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: 0x35ef2f80>
> .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: 0x35ef2f80>
> .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: 0x35ef2f80>
> 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: 0x35be1c60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x35be1c60>
> .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: 0x35be1c60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x35be1c60>
> .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: 0x35be1c60>
> 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: 0x35d68e40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x35d68e40>
> .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: 0x35d68e40>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x35d68e40>
> .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: 0x35d68e40>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x35d68e40>
> .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: 0x35d68e40>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x35d68e40>
> .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: 0x35d68e40>
> 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: 0x35abb550>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x35abb550>
> .Call("R_bm_AddColumn",P)
<pointer: 0x35abb550>
> .Call("R_bm_AddColumn",P)
<pointer: 0x35abb550>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilecbdd8180afa76" "BufferedMatrixFilecbdd85f15160e"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilecbdd8180afa76" "BufferedMatrixFilecbdd85f15160e"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x36959e00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x36959e00>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x36959e00>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x36959e00>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x36959e00>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x36959e00>
> .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: 0x369577f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x369577f0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x369577f0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x369577f0>
> 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: 0x367fc130>
> .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: 0x367fc130>
> rm(P)
>
> proc.time()
user system elapsed
0.331 0.051 0.364
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.321 0.038 0.344