Ben Bolstad
| Snapshot Date: 2024-10-16 14:00 -0400 (Wed, 16 Oct 2024) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_19 |
| git_last_commit: af6c73d |
| git_last_commit_date: 2024-04-30 10:16:21 -0400 (Tue, 30 Apr 2024) |
| Back to Multiple platform build/check report for BioC 3.19: simplified long |
|
This page was generated on 2024-10-18 20:38 -0400 (Fri, 18 Oct 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4763 |
| palomino7 | Windows Server 2022 Datacenter | x64 | 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life" | 4500 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4530 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4480 |
| 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 249/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.68.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
|
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: 1.68.0 |
| Command: /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings BufferedMatrix_1.68.0.tar.gz |
| StartedAt: 2024-10-16 22:20:28 -0400 (Wed, 16 Oct 2024) |
| EndedAt: 2024-10-16 22:20:53 -0400 (Wed, 16 Oct 2024) |
| EllapsedTime: 25.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings BufferedMatrix_1.68.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
* running under: Ubuntu 22.04.5 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.68.0’
* 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 11.4.0-1ubuntu1~22.04) 11.4.0’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.19-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
gcc -I"/home/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.19-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){
| ^~~~~~~~~~~~~~~~~~~
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-3.19-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-3.19-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-3.19-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-3.19-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.19-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 4.4.1 (2024-06-14) -- "Race for Your Life"
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
0.26 0.04 0.29
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/home/biocbuild/bbs-3.19-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 471777 25.2 1026220 54.9 643428 34.4
Vcells 871900 6.7 8388608 64.0 2046605 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] "Wed Oct 16 22:20:44 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] "Wed Oct 16 22:20:44 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: 0x5652dcf85cf0>
>
>
>
> 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] "Wed Oct 16 22:20:45 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] "Wed Oct 16 22:20:45 2024"
>
> ColMode(tmp2)
<pointer: 0x5652dcf85cf0>
>
>
>
> ### 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,] 98.754843150 -0.004131181 -0.1284168 -0.6250934
[2,] 0.766854610 0.896309467 -1.0662713 1.0029597
[3,] 2.971546370 -0.806087007 -0.6708548 0.5392746
[4,] 0.006536991 -0.071377521 -1.4272806 -0.3504208
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 98.754843150 0.004131181 0.1284168 0.6250934
[2,] 0.766854610 0.896309467 1.0662713 1.0029597
[3,] 2.971546370 0.806087007 0.6708548 0.5392746
[4,] 0.006536991 0.071377521 1.4272806 0.3504208
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.93754714 0.06427426 0.3583528 0.7906285
[2,] 0.87570235 0.94673622 1.0326042 1.0014788
[3,] 1.72381738 0.89782348 0.8190573 0.7343532
[4,] 0.08085166 0.26716572 1.1946885 0.5919635
>
> 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-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 223.13031 25.64687 28.71195 33.53138
[2,] 34.52388 35.36367 36.39231 36.01775
[3,] 45.20972 34.78432 33.86143 32.88281
[4,] 25.81505 27.74303 38.37417 31.27006
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5652ddaf96b0>
> exp(tmp5)
<pointer: 0x5652ddaf96b0>
> log(tmp5,2)
<pointer: 0x5652ddaf96b0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 464.4165
> Min(tmp5)
[1] 52.92613
> mean(tmp5)
[1] 72.34008
> Sum(tmp5)
[1] 14468.02
> Var(tmp5)
[1] 850.934
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.96652 71.56855 72.63304 69.86684 70.30198 68.12556 69.69544 70.81716
[9] 71.27259 69.15311
> rowSums(tmp5)
[1] 1799.330 1431.371 1452.661 1397.337 1406.040 1362.511 1393.909 1416.343
[9] 1425.452 1383.062
> rowVars(tmp5)
[1] 7851.27386 50.84147 84.65633 103.18521 82.34008 67.39545
[7] 78.11126 80.10712 62.49532 73.04471
> rowSd(tmp5)
[1] 88.607414 7.130321 9.200887 10.158012 9.074143 8.209473 8.838057
[8] 8.950258 7.905398 8.546620
> rowMax(tmp5)
[1] 464.41652 88.03581 94.09811 85.79966 91.10992 93.74589 82.13813
[8] 85.40878 86.83178 84.36115
> rowMin(tmp5)
[1] 53.38061 59.81065 58.36527 53.73065 55.08304 55.79687 53.38350 53.85365
[9] 59.15484 52.92613
>
> colMeans(tmp5)
[1] 108.17224 67.84096 72.12534 68.79589 66.32393 64.50497 68.62618
[8] 73.83265 73.13322 71.92781 64.44139 73.48782 71.02012 77.58740
[15] 70.56023 73.11756 72.06033 69.45706 68.47187 71.31461
> colSums(tmp5)
[1] 1081.7224 678.4096 721.2534 687.9589 663.2393 645.0497 686.2618
[8] 738.3265 731.3322 719.2781 644.4139 734.8782 710.2012 775.8740
[15] 705.6023 731.1756 720.6033 694.5706 684.7187 713.1461
> colVars(tmp5)
[1] 15805.54467 58.43755 78.79338 30.64499 105.85948 61.98488
[7] 67.86991 59.28139 54.38109 47.58794 55.92814 91.25252
[13] 89.61484 84.54622 74.76204 70.00027 60.98527 40.18765
[19] 90.92668 61.66688
> colSd(tmp5)
[1] 125.720104 7.644446 8.876564 5.535792 10.288804 7.873048
[7] 8.238319 7.699441 7.374353 6.898401 7.478512 9.552619
[13] 9.466512 9.194902 8.646505 8.366616 7.809307 6.339373
[19] 9.535548 7.852826
> colMax(tmp5)
[1] 464.41652 78.74507 86.83178 79.39682 85.40878 81.60699 79.53155
[8] 82.95994 91.10992 85.79966 80.86467 92.86918 84.09716 93.74589
[15] 83.30950 88.03581 84.36115 76.64812 83.17025 82.13813
> colMin(tmp5)
[1] 53.73065 53.38061 59.76015 60.26642 52.92613 55.08304 58.39271 64.22114
[9] 65.39334 61.79032 53.85365 61.86195 53.94517 63.22983 59.15484 59.90709
[17] 60.64067 56.71365 55.79687 59.81065
>
>
> ### 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] NA 71.56855 72.63304 69.86684 70.30198 68.12556 69.69544 70.81716
[9] 71.27259 69.15311
> rowSums(tmp5)
[1] NA 1431.371 1452.661 1397.337 1406.040 1362.511 1393.909 1416.343
[9] 1425.452 1383.062
> rowVars(tmp5)
[1] 8252.43899 50.84147 84.65633 103.18521 82.34008 67.39545
[7] 78.11126 80.10712 62.49532 73.04471
> rowSd(tmp5)
[1] 90.842936 7.130321 9.200887 10.158012 9.074143 8.209473 8.838057
[8] 8.950258 7.905398 8.546620
> rowMax(tmp5)
[1] NA 88.03581 94.09811 85.79966 91.10992 93.74589 82.13813 85.40878
[9] 86.83178 84.36115
> rowMin(tmp5)
[1] NA 59.81065 58.36527 53.73065 55.08304 55.79687 53.38350 53.85365
[9] 59.15484 52.92613
>
> colMeans(tmp5)
[1] 108.17224 67.84096 72.12534 68.79589 66.32393 NA 68.62618
[8] 73.83265 73.13322 71.92781 64.44139 73.48782 71.02012 77.58740
[15] 70.56023 73.11756 72.06033 69.45706 68.47187 71.31461
> colSums(tmp5)
[1] 1081.7224 678.4096 721.2534 687.9589 663.2393 NA 686.2618
[8] 738.3265 731.3322 719.2781 644.4139 734.8782 710.2012 775.8740
[15] 705.6023 731.1756 720.6033 694.5706 684.7187 713.1461
> colVars(tmp5)
[1] 15805.54467 58.43755 78.79338 30.64499 105.85948 NA
[7] 67.86991 59.28139 54.38109 47.58794 55.92814 91.25252
[13] 89.61484 84.54622 74.76204 70.00027 60.98527 40.18765
[19] 90.92668 61.66688
> colSd(tmp5)
[1] 125.720104 7.644446 8.876564 5.535792 10.288804 NA
[7] 8.238319 7.699441 7.374353 6.898401 7.478512 9.552619
[13] 9.466512 9.194902 8.646505 8.366616 7.809307 6.339373
[19] 9.535548 7.852826
> colMax(tmp5)
[1] 464.41652 78.74507 86.83178 79.39682 85.40878 NA 79.53155
[8] 82.95994 91.10992 85.79966 80.86467 92.86918 84.09716 93.74589
[15] 83.30950 88.03581 84.36115 76.64812 83.17025 82.13813
> colMin(tmp5)
[1] 53.73065 53.38061 59.76015 60.26642 52.92613 NA 58.39271 64.22114
[9] 65.39334 61.79032 53.85365 61.86195 53.94517 63.22983 59.15484 59.90709
[17] 60.64067 56.71365 55.79687 59.81065
>
> Max(tmp5,na.rm=TRUE)
[1] 464.4165
> Min(tmp5,na.rm=TRUE)
[1] 52.92613
> mean(tmp5,na.rm=TRUE)
[1] 72.37447
> Sum(tmp5,na.rm=TRUE)
[1] 14402.52
> Var(tmp5,na.rm=TRUE)
[1] 854.9939
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.25442 71.56855 72.63304 69.86684 70.30198 68.12556 69.69544 70.81716
[9] 71.27259 69.15311
> rowSums(tmp5,na.rm=TRUE)
[1] 1733.834 1431.371 1452.661 1397.337 1406.040 1362.511 1393.909 1416.343
[9] 1425.452 1383.062
> rowVars(tmp5,na.rm=TRUE)
[1] 8252.43899 50.84147 84.65633 103.18521 82.34008 67.39545
[7] 78.11126 80.10712 62.49532 73.04471
> rowSd(tmp5,na.rm=TRUE)
[1] 90.842936 7.130321 9.200887 10.158012 9.074143 8.209473 8.838057
[8] 8.950258 7.905398 8.546620
> rowMax(tmp5,na.rm=TRUE)
[1] 464.41652 88.03581 94.09811 85.79966 91.10992 93.74589 82.13813
[8] 85.40878 86.83178 84.36115
> rowMin(tmp5,na.rm=TRUE)
[1] 53.38061 59.81065 58.36527 53.73065 55.08304 55.79687 53.38350 53.85365
[9] 59.15484 52.92613
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.17224 67.84096 72.12534 68.79589 66.32393 64.39481 68.62618
[8] 73.83265 73.13322 71.92781 64.44139 73.48782 71.02012 77.58740
[15] 70.56023 73.11756 72.06033 69.45706 68.47187 71.31461
> colSums(tmp5,na.rm=TRUE)
[1] 1081.7224 678.4096 721.2534 687.9589 663.2393 579.5533 686.2618
[8] 738.3265 731.3322 719.2781 644.4139 734.8782 710.2012 775.8740
[15] 705.6023 731.1756 720.6033 694.5706 684.7187 713.1461
> colVars(tmp5,na.rm=TRUE)
[1] 15805.54467 58.43755 78.79338 30.64499 105.85948 69.59647
[7] 67.86991 59.28139 54.38109 47.58794 55.92814 91.25252
[13] 89.61484 84.54622 74.76204 70.00027 60.98527 40.18765
[19] 90.92668 61.66688
> colSd(tmp5,na.rm=TRUE)
[1] 125.720104 7.644446 8.876564 5.535792 10.288804 8.342450
[7] 8.238319 7.699441 7.374353 6.898401 7.478512 9.552619
[13] 9.466512 9.194902 8.646505 8.366616 7.809307 6.339373
[19] 9.535548 7.852826
> colMax(tmp5,na.rm=TRUE)
[1] 464.41652 78.74507 86.83178 79.39682 85.40878 81.60699 79.53155
[8] 82.95994 91.10992 85.79966 80.86467 92.86918 84.09716 93.74589
[15] 83.30950 88.03581 84.36115 76.64812 83.17025 82.13813
> colMin(tmp5,na.rm=TRUE)
[1] 53.73065 53.38061 59.76015 60.26642 52.92613 55.08304 58.39271 64.22114
[9] 65.39334 61.79032 53.85365 61.86195 53.94517 63.22983 59.15484 59.90709
[17] 60.64067 56.71365 55.79687 59.81065
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 71.56855 72.63304 69.86684 70.30198 68.12556 69.69544 70.81716
[9] 71.27259 69.15311
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1431.371 1452.661 1397.337 1406.040 1362.511 1393.909 1416.343
[9] 1425.452 1383.062
> rowVars(tmp5,na.rm=TRUE)
[1] NA 50.84147 84.65633 103.18521 82.34008 67.39545 78.11126
[8] 80.10712 62.49532 73.04471
> rowSd(tmp5,na.rm=TRUE)
[1] NA 7.130321 9.200887 10.158012 9.074143 8.209473 8.838057
[8] 8.950258 7.905398 8.546620
> rowMax(tmp5,na.rm=TRUE)
[1] NA 88.03581 94.09811 85.79966 91.10992 93.74589 82.13813 85.40878
[9] 86.83178 84.36115
> rowMin(tmp5,na.rm=TRUE)
[1] NA 59.81065 58.36527 53.73065 55.08304 55.79687 53.38350 53.85365
[9] 59.15484 52.92613
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 68.58954 69.44766 73.49925 68.68530 66.60979 NaN 67.60267 73.17011
[9] 73.10989 72.55484 62.61658 71.33433 71.68864 79.18268 71.30913 73.42283
[17] 72.14485 68.98480 69.13240 70.15160
> colSums(tmp5,na.rm=TRUE)
[1] 617.3059 625.0290 661.4932 618.1677 599.4881 0.0000 608.4241 658.5310
[9] 657.9890 652.9936 563.5492 642.0090 645.1977 712.6441 641.7822 660.8054
[17] 649.3037 620.8632 622.1916 631.3644
> colVars(tmp5,na.rm=TRUE)
[1] 154.85098 36.70033 67.40674 34.33803 118.17260 NA 64.56842
[8] 61.75326 61.17260 49.11329 25.45747 50.48725 95.78890 66.48397
[15] 77.79772 77.70193 68.52807 42.70202 97.38413 54.15878
> colSd(tmp5,na.rm=TRUE)
[1] 12.443913 6.058080 8.210161 5.859866 10.870722 NA 8.035448
[8] 7.858324 7.821291 7.008087 5.045540 7.105438 9.787181 8.153770
[15] 8.820302 8.814870 8.278168 6.534678 9.868340 7.359265
> colMax(tmp5,na.rm=TRUE)
[1] 94.09811 78.74507 86.83178 79.39682 85.40878 -Inf 79.53155 82.95994
[9] 91.10992 85.79966 69.56284 80.49050 84.09716 93.74589 83.30950 88.03581
[17] 84.36115 76.64812 83.17025 82.13813
> colMin(tmp5,na.rm=TRUE)
[1] 53.73065 57.74349 61.57854 60.26642 52.92613 Inf 58.39271 64.22114
[9] 65.39334 61.79032 53.85365 61.86195 53.94517 68.77121 59.15484 59.90709
[17] 60.64067 56.71365 55.79687 59.81065
>
>
>
>
> 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] 140.28672 131.60137 98.30434 193.32450 286.75342 145.21457 235.56647
[8] 175.64144 205.12564 296.22873
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 140.28672 131.60137 98.30434 193.32450 286.75342 145.21457 235.56647
[8] 175.64144 205.12564 296.22873
>
>
>
> 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] -7.105427e-14 -1.705303e-13 1.705303e-13 -9.947598e-14 1.421085e-14
[6] 2.842171e-14 -5.684342e-14 5.684342e-14 1.278977e-13 -2.842171e-14
[11] -5.684342e-14 -5.684342e-14 2.842171e-13 1.705303e-13 8.526513e-14
[16] -4.263256e-14 2.842171e-13 5.684342e-14 -1.421085e-13 8.526513e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
7 12
9 2
2 10
7 14
2 7
7 17
6 1
6 1
3 3
4 13
9 4
9 14
6 11
1 12
5 13
4 10
3 2
2 1
3 13
1 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] 2.507631
> Min(tmp)
[1] -2.408682
> mean(tmp)
[1] -0.1080915
> Sum(tmp)
[1] -10.80915
> Var(tmp)
[1] 0.7972646
>
> rowMeans(tmp)
[1] -0.1080915
> rowSums(tmp)
[1] -10.80915
> rowVars(tmp)
[1] 0.7972646
> rowSd(tmp)
[1] 0.8928968
> rowMax(tmp)
[1] 2.507631
> rowMin(tmp)
[1] -2.408682
>
> colMeans(tmp)
[1] 0.12995907 -0.67916838 0.66968703 -0.33846554 -0.48410472 -0.32334708
[7] -0.02317957 1.08145994 -0.97322064 -1.51396548 0.97978487 1.14690495
[13] -1.31813753 0.07978224 -0.16886183 -1.11168893 -0.32618353 -0.45026464
[19] -0.32531797 0.48464221 -0.27881775 -0.72030113 -0.67542440 -2.24786373
[25] -0.69137850 0.03753405 -1.16435919 -0.90522815 -1.08024333 -0.04432012
[31] -0.50004548 -0.56305731 0.04327686 -0.34858467 -0.53770716 -0.77518975
[37] 2.04683022 -1.39694367 -1.15425023 0.46154725 0.27603814 0.03576238
[43] 0.78326785 -0.23206599 0.95383093 -0.33490080 -1.80307191 -0.70421739
[49] 0.42282285 2.50763071 -1.49404873 0.80721604 -0.29999736 -0.04384469
[55] 0.19364501 -0.49555162 -0.29139581 0.06644511 0.27012162 -0.14525448
[61] 0.51175676 -1.14241350 -0.14926765 -0.68988057 0.01410715 1.58818879
[67] -0.22986226 0.12909042 1.14226222 -0.57841171 -2.40868219 -0.01363911
[73] -0.19399593 0.57211478 1.52899358 0.98129821 1.46609096 -0.82412760
[79] 0.40366057 -0.37183479 -0.85586864 0.24547951 -0.51524360 0.29375345
[85] 0.42019864 0.20788839 1.20401509 0.23908471 0.12428160 -0.51366089
[91] 0.87053874 1.43802490 -0.87366048 0.41196899 -1.37341750 -0.31997666
[97] -1.13730927 0.91185762 1.46466303 -1.30143659
> colSums(tmp)
[1] 0.12995907 -0.67916838 0.66968703 -0.33846554 -0.48410472 -0.32334708
[7] -0.02317957 1.08145994 -0.97322064 -1.51396548 0.97978487 1.14690495
[13] -1.31813753 0.07978224 -0.16886183 -1.11168893 -0.32618353 -0.45026464
[19] -0.32531797 0.48464221 -0.27881775 -0.72030113 -0.67542440 -2.24786373
[25] -0.69137850 0.03753405 -1.16435919 -0.90522815 -1.08024333 -0.04432012
[31] -0.50004548 -0.56305731 0.04327686 -0.34858467 -0.53770716 -0.77518975
[37] 2.04683022 -1.39694367 -1.15425023 0.46154725 0.27603814 0.03576238
[43] 0.78326785 -0.23206599 0.95383093 -0.33490080 -1.80307191 -0.70421739
[49] 0.42282285 2.50763071 -1.49404873 0.80721604 -0.29999736 -0.04384469
[55] 0.19364501 -0.49555162 -0.29139581 0.06644511 0.27012162 -0.14525448
[61] 0.51175676 -1.14241350 -0.14926765 -0.68988057 0.01410715 1.58818879
[67] -0.22986226 0.12909042 1.14226222 -0.57841171 -2.40868219 -0.01363911
[73] -0.19399593 0.57211478 1.52899358 0.98129821 1.46609096 -0.82412760
[79] 0.40366057 -0.37183479 -0.85586864 0.24547951 -0.51524360 0.29375345
[85] 0.42019864 0.20788839 1.20401509 0.23908471 0.12428160 -0.51366089
[91] 0.87053874 1.43802490 -0.87366048 0.41196899 -1.37341750 -0.31997666
[97] -1.13730927 0.91185762 1.46466303 -1.30143659
> 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] 0.12995907 -0.67916838 0.66968703 -0.33846554 -0.48410472 -0.32334708
[7] -0.02317957 1.08145994 -0.97322064 -1.51396548 0.97978487 1.14690495
[13] -1.31813753 0.07978224 -0.16886183 -1.11168893 -0.32618353 -0.45026464
[19] -0.32531797 0.48464221 -0.27881775 -0.72030113 -0.67542440 -2.24786373
[25] -0.69137850 0.03753405 -1.16435919 -0.90522815 -1.08024333 -0.04432012
[31] -0.50004548 -0.56305731 0.04327686 -0.34858467 -0.53770716 -0.77518975
[37] 2.04683022 -1.39694367 -1.15425023 0.46154725 0.27603814 0.03576238
[43] 0.78326785 -0.23206599 0.95383093 -0.33490080 -1.80307191 -0.70421739
[49] 0.42282285 2.50763071 -1.49404873 0.80721604 -0.29999736 -0.04384469
[55] 0.19364501 -0.49555162 -0.29139581 0.06644511 0.27012162 -0.14525448
[61] 0.51175676 -1.14241350 -0.14926765 -0.68988057 0.01410715 1.58818879
[67] -0.22986226 0.12909042 1.14226222 -0.57841171 -2.40868219 -0.01363911
[73] -0.19399593 0.57211478 1.52899358 0.98129821 1.46609096 -0.82412760
[79] 0.40366057 -0.37183479 -0.85586864 0.24547951 -0.51524360 0.29375345
[85] 0.42019864 0.20788839 1.20401509 0.23908471 0.12428160 -0.51366089
[91] 0.87053874 1.43802490 -0.87366048 0.41196899 -1.37341750 -0.31997666
[97] -1.13730927 0.91185762 1.46466303 -1.30143659
> colMin(tmp)
[1] 0.12995907 -0.67916838 0.66968703 -0.33846554 -0.48410472 -0.32334708
[7] -0.02317957 1.08145994 -0.97322064 -1.51396548 0.97978487 1.14690495
[13] -1.31813753 0.07978224 -0.16886183 -1.11168893 -0.32618353 -0.45026464
[19] -0.32531797 0.48464221 -0.27881775 -0.72030113 -0.67542440 -2.24786373
[25] -0.69137850 0.03753405 -1.16435919 -0.90522815 -1.08024333 -0.04432012
[31] -0.50004548 -0.56305731 0.04327686 -0.34858467 -0.53770716 -0.77518975
[37] 2.04683022 -1.39694367 -1.15425023 0.46154725 0.27603814 0.03576238
[43] 0.78326785 -0.23206599 0.95383093 -0.33490080 -1.80307191 -0.70421739
[49] 0.42282285 2.50763071 -1.49404873 0.80721604 -0.29999736 -0.04384469
[55] 0.19364501 -0.49555162 -0.29139581 0.06644511 0.27012162 -0.14525448
[61] 0.51175676 -1.14241350 -0.14926765 -0.68988057 0.01410715 1.58818879
[67] -0.22986226 0.12909042 1.14226222 -0.57841171 -2.40868219 -0.01363911
[73] -0.19399593 0.57211478 1.52899358 0.98129821 1.46609096 -0.82412760
[79] 0.40366057 -0.37183479 -0.85586864 0.24547951 -0.51524360 0.29375345
[85] 0.42019864 0.20788839 1.20401509 0.23908471 0.12428160 -0.51366089
[91] 0.87053874 1.43802490 -0.87366048 0.41196899 -1.37341750 -0.31997666
[97] -1.13730927 0.91185762 1.46466303 -1.30143659
> colMedians(tmp)
[1] 0.12995907 -0.67916838 0.66968703 -0.33846554 -0.48410472 -0.32334708
[7] -0.02317957 1.08145994 -0.97322064 -1.51396548 0.97978487 1.14690495
[13] -1.31813753 0.07978224 -0.16886183 -1.11168893 -0.32618353 -0.45026464
[19] -0.32531797 0.48464221 -0.27881775 -0.72030113 -0.67542440 -2.24786373
[25] -0.69137850 0.03753405 -1.16435919 -0.90522815 -1.08024333 -0.04432012
[31] -0.50004548 -0.56305731 0.04327686 -0.34858467 -0.53770716 -0.77518975
[37] 2.04683022 -1.39694367 -1.15425023 0.46154725 0.27603814 0.03576238
[43] 0.78326785 -0.23206599 0.95383093 -0.33490080 -1.80307191 -0.70421739
[49] 0.42282285 2.50763071 -1.49404873 0.80721604 -0.29999736 -0.04384469
[55] 0.19364501 -0.49555162 -0.29139581 0.06644511 0.27012162 -0.14525448
[61] 0.51175676 -1.14241350 -0.14926765 -0.68988057 0.01410715 1.58818879
[67] -0.22986226 0.12909042 1.14226222 -0.57841171 -2.40868219 -0.01363911
[73] -0.19399593 0.57211478 1.52899358 0.98129821 1.46609096 -0.82412760
[79] 0.40366057 -0.37183479 -0.85586864 0.24547951 -0.51524360 0.29375345
[85] 0.42019864 0.20788839 1.20401509 0.23908471 0.12428160 -0.51366089
[91] 0.87053874 1.43802490 -0.87366048 0.41196899 -1.37341750 -0.31997666
[97] -1.13730927 0.91185762 1.46466303 -1.30143659
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.1299591 -0.6791684 0.669687 -0.3384655 -0.4841047 -0.3233471 -0.02317957
[2,] 0.1299591 -0.6791684 0.669687 -0.3384655 -0.4841047 -0.3233471 -0.02317957
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.08146 -0.9732206 -1.513965 0.9797849 1.146905 -1.318138 0.07978224
[2,] 1.08146 -0.9732206 -1.513965 0.9797849 1.146905 -1.318138 0.07978224
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.1688618 -1.111689 -0.3261835 -0.4502646 -0.325318 0.4846422 -0.2788178
[2,] -0.1688618 -1.111689 -0.3261835 -0.4502646 -0.325318 0.4846422 -0.2788178
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.7203011 -0.6754244 -2.247864 -0.6913785 0.03753405 -1.164359 -0.9052282
[2,] -0.7203011 -0.6754244 -2.247864 -0.6913785 0.03753405 -1.164359 -0.9052282
[,29] [,30] [,31] [,32] [,33] [,34]
[1,] -1.080243 -0.04432012 -0.5000455 -0.5630573 0.04327686 -0.3485847
[2,] -1.080243 -0.04432012 -0.5000455 -0.5630573 0.04327686 -0.3485847
[,35] [,36] [,37] [,38] [,39] [,40] [,41]
[1,] -0.5377072 -0.7751898 2.04683 -1.396944 -1.15425 0.4615472 0.2760381
[2,] -0.5377072 -0.7751898 2.04683 -1.396944 -1.15425 0.4615472 0.2760381
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] 0.03576238 0.7832678 -0.232066 0.9538309 -0.3349008 -1.803072 -0.7042174
[2,] 0.03576238 0.7832678 -0.232066 0.9538309 -0.3349008 -1.803072 -0.7042174
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] 0.4228229 2.507631 -1.494049 0.807216 -0.2999974 -0.04384469 0.193645
[2,] 0.4228229 2.507631 -1.494049 0.807216 -0.2999974 -0.04384469 0.193645
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.4955516 -0.2913958 0.06644511 0.2701216 -0.1452545 0.5117568 -1.142413
[2,] -0.4955516 -0.2913958 0.06644511 0.2701216 -0.1452545 0.5117568 -1.142413
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] -0.1492677 -0.6898806 0.01410715 1.588189 -0.2298623 0.1290904 1.142262
[2,] -0.1492677 -0.6898806 0.01410715 1.588189 -0.2298623 0.1290904 1.142262
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] -0.5784117 -2.408682 -0.01363911 -0.1939959 0.5721148 1.528994 0.9812982
[2,] -0.5784117 -2.408682 -0.01363911 -0.1939959 0.5721148 1.528994 0.9812982
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] 1.466091 -0.8241276 0.4036606 -0.3718348 -0.8558686 0.2454795 -0.5152436
[2,] 1.466091 -0.8241276 0.4036606 -0.3718348 -0.8558686 0.2454795 -0.5152436
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 0.2937534 0.4201986 0.2078884 1.204015 0.2390847 0.1242816 -0.5136609
[2,] 0.2937534 0.4201986 0.2078884 1.204015 0.2390847 0.1242816 -0.5136609
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 0.8705387 1.438025 -0.8736605 0.411969 -1.373417 -0.3199767 -1.137309
[2,] 0.8705387 1.438025 -0.8736605 0.411969 -1.373417 -0.3199767 -1.137309
[,98] [,99] [,100]
[1,] 0.9118576 1.464663 -1.301437
[2,] 0.9118576 1.464663 -1.301437
>
>
> Max(tmp2)
[1] 2.828261
> Min(tmp2)
[1] -2.432596
> mean(tmp2)
[1] 0.1595556
> Sum(tmp2)
[1] 15.95556
> Var(tmp2)
[1] 1.12946
>
> rowMeans(tmp2)
[1] 0.1700349220 0.6797219060 -1.0949994686 0.5600294658 -0.6739747343
[6] -0.2065979617 -0.9966688727 0.0657644406 1.3331836535 0.9578170558
[11] -0.7937018084 0.5419185069 1.7144108097 0.4715056046 0.4252111352
[16] 1.4126680734 1.1272849008 2.8282607993 0.3852682623 -0.3252659586
[21] 0.3034225092 0.0731612267 -0.8930439034 -1.2616634225 1.1888209764
[26] -2.4325960158 1.4437432901 1.3900111291 -0.7887250358 -0.1675721912
[31] -0.5673192579 0.7054368235 -1.7537013736 0.8804560594 -0.7950824837
[36] 1.0272176902 2.7810746260 0.4549169168 1.0001777048 -0.1561923851
[41] 1.1085821979 -0.1686196637 0.4274144440 0.0076171447 -2.0547081340
[46] 0.1343255385 -0.0870011419 0.4599849332 0.3291138226 -0.0004626236
[51] -0.3766178023 -0.2439303209 -0.7708521337 0.5857208626 -0.1099632350
[56] -0.9876278188 -0.7198025556 1.1861414225 -0.7164450520 0.4504266865
[61] 1.7596657540 -0.9318390836 -0.2893603522 1.7622673020 2.6722386908
[66] -0.7692949663 -1.9674470797 -1.3034415738 0.9547609646 0.6498810471
[71] 2.1504930172 -1.9496199133 0.0679832543 -0.8398873106 -0.0929416323
[76] 0.8110313508 -0.7830007922 0.0121084768 -0.5789882289 1.5508349627
[81] -0.3846093631 0.6151938877 1.2156294325 0.0429969902 2.3493390811
[86] -1.3709595018 -1.6099531821 0.3890707077 0.3724178558 0.7025023115
[91] 0.9813046081 0.0890936403 0.2560189799 -0.7486144349 -0.4647771866
[96] 0.5287190326 0.1655724176 1.2639759344 -0.2460169667 -0.5444988522
> rowSums(tmp2)
[1] 0.1700349220 0.6797219060 -1.0949994686 0.5600294658 -0.6739747343
[6] -0.2065979617 -0.9966688727 0.0657644406 1.3331836535 0.9578170558
[11] -0.7937018084 0.5419185069 1.7144108097 0.4715056046 0.4252111352
[16] 1.4126680734 1.1272849008 2.8282607993 0.3852682623 -0.3252659586
[21] 0.3034225092 0.0731612267 -0.8930439034 -1.2616634225 1.1888209764
[26] -2.4325960158 1.4437432901 1.3900111291 -0.7887250358 -0.1675721912
[31] -0.5673192579 0.7054368235 -1.7537013736 0.8804560594 -0.7950824837
[36] 1.0272176902 2.7810746260 0.4549169168 1.0001777048 -0.1561923851
[41] 1.1085821979 -0.1686196637 0.4274144440 0.0076171447 -2.0547081340
[46] 0.1343255385 -0.0870011419 0.4599849332 0.3291138226 -0.0004626236
[51] -0.3766178023 -0.2439303209 -0.7708521337 0.5857208626 -0.1099632350
[56] -0.9876278188 -0.7198025556 1.1861414225 -0.7164450520 0.4504266865
[61] 1.7596657540 -0.9318390836 -0.2893603522 1.7622673020 2.6722386908
[66] -0.7692949663 -1.9674470797 -1.3034415738 0.9547609646 0.6498810471
[71] 2.1504930172 -1.9496199133 0.0679832543 -0.8398873106 -0.0929416323
[76] 0.8110313508 -0.7830007922 0.0121084768 -0.5789882289 1.5508349627
[81] -0.3846093631 0.6151938877 1.2156294325 0.0429969902 2.3493390811
[86] -1.3709595018 -1.6099531821 0.3890707077 0.3724178558 0.7025023115
[91] 0.9813046081 0.0890936403 0.2560189799 -0.7486144349 -0.4647771866
[96] 0.5287190326 0.1655724176 1.2639759344 -0.2460169667 -0.5444988522
> 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] 0.1700349220 0.6797219060 -1.0949994686 0.5600294658 -0.6739747343
[6] -0.2065979617 -0.9966688727 0.0657644406 1.3331836535 0.9578170558
[11] -0.7937018084 0.5419185069 1.7144108097 0.4715056046 0.4252111352
[16] 1.4126680734 1.1272849008 2.8282607993 0.3852682623 -0.3252659586
[21] 0.3034225092 0.0731612267 -0.8930439034 -1.2616634225 1.1888209764
[26] -2.4325960158 1.4437432901 1.3900111291 -0.7887250358 -0.1675721912
[31] -0.5673192579 0.7054368235 -1.7537013736 0.8804560594 -0.7950824837
[36] 1.0272176902 2.7810746260 0.4549169168 1.0001777048 -0.1561923851
[41] 1.1085821979 -0.1686196637 0.4274144440 0.0076171447 -2.0547081340
[46] 0.1343255385 -0.0870011419 0.4599849332 0.3291138226 -0.0004626236
[51] -0.3766178023 -0.2439303209 -0.7708521337 0.5857208626 -0.1099632350
[56] -0.9876278188 -0.7198025556 1.1861414225 -0.7164450520 0.4504266865
[61] 1.7596657540 -0.9318390836 -0.2893603522 1.7622673020 2.6722386908
[66] -0.7692949663 -1.9674470797 -1.3034415738 0.9547609646 0.6498810471
[71] 2.1504930172 -1.9496199133 0.0679832543 -0.8398873106 -0.0929416323
[76] 0.8110313508 -0.7830007922 0.0121084768 -0.5789882289 1.5508349627
[81] -0.3846093631 0.6151938877 1.2156294325 0.0429969902 2.3493390811
[86] -1.3709595018 -1.6099531821 0.3890707077 0.3724178558 0.7025023115
[91] 0.9813046081 0.0890936403 0.2560189799 -0.7486144349 -0.4647771866
[96] 0.5287190326 0.1655724176 1.2639759344 -0.2460169667 -0.5444988522
> rowMin(tmp2)
[1] 0.1700349220 0.6797219060 -1.0949994686 0.5600294658 -0.6739747343
[6] -0.2065979617 -0.9966688727 0.0657644406 1.3331836535 0.9578170558
[11] -0.7937018084 0.5419185069 1.7144108097 0.4715056046 0.4252111352
[16] 1.4126680734 1.1272849008 2.8282607993 0.3852682623 -0.3252659586
[21] 0.3034225092 0.0731612267 -0.8930439034 -1.2616634225 1.1888209764
[26] -2.4325960158 1.4437432901 1.3900111291 -0.7887250358 -0.1675721912
[31] -0.5673192579 0.7054368235 -1.7537013736 0.8804560594 -0.7950824837
[36] 1.0272176902 2.7810746260 0.4549169168 1.0001777048 -0.1561923851
[41] 1.1085821979 -0.1686196637 0.4274144440 0.0076171447 -2.0547081340
[46] 0.1343255385 -0.0870011419 0.4599849332 0.3291138226 -0.0004626236
[51] -0.3766178023 -0.2439303209 -0.7708521337 0.5857208626 -0.1099632350
[56] -0.9876278188 -0.7198025556 1.1861414225 -0.7164450520 0.4504266865
[61] 1.7596657540 -0.9318390836 -0.2893603522 1.7622673020 2.6722386908
[66] -0.7692949663 -1.9674470797 -1.3034415738 0.9547609646 0.6498810471
[71] 2.1504930172 -1.9496199133 0.0679832543 -0.8398873106 -0.0929416323
[76] 0.8110313508 -0.7830007922 0.0121084768 -0.5789882289 1.5508349627
[81] -0.3846093631 0.6151938877 1.2156294325 0.0429969902 2.3493390811
[86] -1.3709595018 -1.6099531821 0.3890707077 0.3724178558 0.7025023115
[91] 0.9813046081 0.0890936403 0.2560189799 -0.7486144349 -0.4647771866
[96] 0.5287190326 0.1655724176 1.2639759344 -0.2460169667 -0.5444988522
>
> colMeans(tmp2)
[1] 0.1595556
> colSums(tmp2)
[1] 15.95556
> colVars(tmp2)
[1] 1.12946
> colSd(tmp2)
[1] 1.06276
> colMax(tmp2)
[1] 2.828261
> colMin(tmp2)
[1] -2.432596
> colMedians(tmp2)
[1] 0.1117096
> colRanges(tmp2)
[,1]
[1,] -2.432596
[2,] 2.828261
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.0004692 -5.3560177 -3.5314805 1.3778538 0.5455067 0.9580513
[7] 4.7842100 -0.1797488 -0.1447351 -1.0225345
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8761928
[2,] -1.3253743
[3,] -0.1641571
[4,] 0.8916318
[5,] 2.0133997
>
> rowApply(tmp,sum)
[1] -0.03619541 0.58782032 -2.20332988 -0.84998921 0.29692578 -2.28742530
[7] 0.92084070 -0.12341715 2.48658289 -3.36117667
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 6 2 10 1 9 5 8 7
[2,] 2 1 4 6 3 2 6 8 9 2
[3,] 7 8 1 5 4 5 2 1 6 8
[4,] 10 7 3 7 8 3 4 9 3 5
[5,] 6 5 9 3 2 10 1 10 7 3
[6,] 5 10 5 8 5 7 10 2 2 4
[7,] 8 6 10 4 9 8 7 4 4 10
[8,] 4 4 8 10 6 9 3 3 10 1
[9,] 9 3 7 9 1 4 8 7 1 6
[10,] 3 9 2 1 7 6 5 6 5 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 4.0023108 -2.5731694 -2.0627593 -0.8428720 -2.4033609 0.3093464
[7] -0.2351272 0.6602134 3.1703607 -0.8629511 0.2173176 -1.2810145
[13] -3.4207629 0.8733247 -0.3885954 0.4970883 -2.6389832 -3.9382325
[19] -4.1562584 -2.7071815
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.88300963
[2,] 0.07380217
[3,] 1.40623499
[4,] 1.44438285
[5,] 1.96090047
>
> rowApply(tmp,sum)
[1] -0.4739093 -3.4634299 -1.0503343 -14.2543386 1.4607058
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 19 19 18 7 11
[2,] 1 14 5 6 15
[3,] 18 15 15 3 1
[4,] 20 1 3 14 10
[5,] 2 3 7 19 9
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.96090047 -1.33814066 1.1773514 1.98469825 -1.1003368 -0.34008093
[2,] 1.44438285 0.08271178 0.2524829 -1.18563367 -1.1302553 0.03500289
[3,] 1.40623499 -0.82453300 0.4733922 -1.05046745 -0.3944083 0.08008849
[4,] -0.88300963 -1.00246245 -1.8101123 -0.56164989 0.3919899 0.08794582
[5,] 0.07380217 0.50925498 -2.1558735 -0.02981928 -0.1703505 0.44639018
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.95036801 -0.54059133 1.1678729 -1.0590412 0.1413488 0.90716326
[2,] 0.77097344 0.89944925 1.5787339 -0.9810441 1.2863098 -0.73957935
[3,] -0.09483415 0.75453237 -0.2158967 -0.1229473 -1.7182188 -0.06960514
[4,] -0.78877033 0.09502363 0.8407826 -0.5821237 -0.6278037 -1.05315244
[5,] 0.82787185 -0.54820051 -0.2011319 1.8822052 1.1356814 -0.32584082
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.1477701 -0.4677065 -0.01476138 0.3596520 -0.5126622 -0.3872867
[2,] -1.1564610 -1.0704148 0.04776771 -0.1596011 -0.9377171 -1.1155559
[3,] -1.4272392 1.7638969 1.43520697 -0.5393412 0.6679144 -0.8554400
[4,] -0.8791238 -0.6792511 -0.74237677 -0.3303713 -2.2377761 -1.2042465
[5,] 0.1898311 1.3268002 -1.11443193 1.1667499 0.3812578 -0.3757034
[,19] [,20]
[1,] -0.4154018 -0.89874881
[2,] -0.6792036 -0.70577847
[3,] -0.3820340 0.06336456
[4,] -1.9511124 -0.33673808
[5,] -0.7285065 -0.82928070
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-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-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.7933462 -1.160147 1.376962 0.08661224 0.09485184 0.09536935 0.1119436
col8 col9 col10 col11 col12 col13
row1 0.3560853 -0.03186981 -1.232879 -1.379584 -0.08938812 0.3287724
col14 col15 col16 col17 col18 col19 col20
row1 -0.05968532 -1.570688 0.1339185 -0.4166372 -1.828259 -0.2939716 -0.5250622
> tmp[,"col10"]
col10
row1 -1.23287932
row2 1.15209155
row3 -0.31836432
row4 0.05835846
row5 -0.72787004
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.7933462 -1.1601474 1.3769622 0.08661224 0.09485184 0.09536935
row5 0.3706359 0.4699922 -0.6769299 0.44999690 -0.42774356 1.42487827
col7 col8 col9 col10 col11 col12
row1 0.1119436 0.3560853 -0.03186981 -1.232879 -1.379584 -0.08938812
row5 -1.0103812 0.3601890 -0.30141937 -0.727870 -1.925472 -0.94953002
col13 col14 col15 col16 col17 col18
row1 0.3287724 -0.05968532 -1.5706883 0.1339185 -0.4166372 -1.82825932
row5 -0.7394413 -0.57958571 0.2674258 0.1961408 -0.6341131 0.09230714
col19 col20
row1 -0.2939716 -0.52506220
row5 -0.7907981 0.03960612
> tmp[,c("col6","col20")]
col6 col20
row1 0.09536935 -0.52506220
row2 -1.22129003 0.63785054
row3 -0.70915656 -0.29173348
row4 -1.72065601 -0.55030924
row5 1.42487827 0.03960612
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.09536935 -0.52506220
row5 1.42487827 0.03960612
>
>
>
>
> 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 50.21431 50.57282 49.68405 48.74238 49.35988 104.6118 49.17585 50.93406
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.52928 50.96787 50.20845 48.64611 50.10321 49.53237 50.08738 49.96261
col17 col18 col19 col20
row1 49.43375 49.3544 50.27169 105.6224
> tmp[,"col10"]
col10
row1 50.96787
row2 31.26059
row3 30.35724
row4 29.71934
row5 51.09524
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.21431 50.57282 49.68405 48.74238 49.35988 104.6118 49.17585 50.93406
row5 49.43351 49.23085 50.44764 50.50431 47.77362 104.5019 49.53203 50.38405
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.52928 50.96787 50.20845 48.64611 50.10321 49.53237 50.08738 49.96261
row5 48.45097 51.09524 49.66677 49.49868 52.18649 51.53729 49.58456 50.87310
col17 col18 col19 col20
row1 49.43375 49.35440 50.27169 105.6224
row5 48.93733 50.73972 52.21699 104.0029
> tmp[,c("col6","col20")]
col6 col20
row1 104.61178 105.62241
row2 75.44911 75.77429
row3 73.17448 75.17952
row4 76.41944 74.33323
row5 104.50189 104.00292
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.6118 105.6224
row5 104.5019 104.0029
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.6118 105.6224
row5 104.5019 104.0029
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.02974676
[2,] -0.63061516
[3,] 0.53998154
[4,] -2.06379655
[5,] -0.77942784
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.1967871 0.27028781
[2,] 0.8879811 0.47450854
[3,] 1.2506085 -0.08124487
[4,] 1.7618275 0.21689917
[5,] -0.6046136 -0.14221095
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.7170574 1.35994844
[2,] -1.7150700 -0.03452054
[3,] 1.2165463 0.23057768
[4,] 0.1513032 0.98944498
[5,] -0.9853831 0.73775871
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.7170574
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.7170574
[2,] -1.7150700
>
>
>
> 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 -1.16234365 0.229149280 0.040932 -0.3580857 0.3902886 1.2710014
row1 -0.04823673 -0.005090696 1.244706 -0.7152081 -0.7621566 -0.4787983
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.3955556 0.3830004 1.415159751 0.8101845 -0.4332915 -0.4985282
row1 -0.3924950 -0.3726731 -0.009061709 -0.3235513 -1.6008033 1.1963555
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.9259803 1.4857537 -0.2837887 0.5696379 2.5011682 -1.5258512 -0.08806507
row1 1.2665258 0.1617868 -0.8403796 0.6147062 0.4937702 0.4176482 -0.64489531
[,20]
row3 0.7123177
row1 2.7867420
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.5332893 -0.575057 0.8014793 0.3740107 -1.905966 -0.5568741 0.7860431
[,8] [,9] [,10]
row2 0.490838 0.5511697 0.3855568
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.9313837 0.7523543 -1.428357 0.7066759 1.434311 0.4009558 0.2363123
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.408126 -0.3711474 0.2274043 -0.6008721 0.09666331 -0.5555333 -1.245055
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.6555165 -0.4350096 -0.07219527 -0.2741097 -0.9259217 1.00769
>
>
> 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: 0x5652dcae0de0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM1edc7a710b843a"
[2] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM1edc7ac033ac4"
[3] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM1edc7ac39e82"
[4] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM1edc7a2ce8ae61"
[5] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM1edc7a543c67bb"
[6] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM1edc7a492e0994"
[7] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM1edc7a172ec0b1"
[8] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM1edc7a53f43f1f"
[9] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM1edc7a63d20cb9"
[10] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM1edc7a2eb06fed"
[11] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM1edc7a66e5350f"
[12] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM1edc7a3445a34f"
[13] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM1edc7a7c844d41"
[14] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM1edc7a6ee453c2"
[15] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM1edc7a3744cf70"
>
>
> ### 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: 0x5652de7b1920>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5652de7b1920>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5652de7b1920>
> rowMedians(tmp)
[1] 0.612697783 0.289056864 -0.230789023 0.215073107 0.630618765
[6] 0.110987449 0.184644017 0.335489160 -0.243337023 -0.003949911
[11] -0.335502130 0.051073461 -0.265658003 0.018266299 0.175925799
[16] 0.384080545 0.327927639 0.078004674 -0.384942836 0.104122581
[21] -0.283560016 0.723567327 -0.217347335 0.142022083 -0.631540616
[26] -0.044784231 -0.254698434 0.183695301 0.324392783 0.527055776
[31] 0.579684967 -0.010009610 0.145801791 0.188858633 -0.160346746
[36] 0.384536871 -0.170069715 -0.006192938 -0.763734851 0.559279776
[41] 0.050715586 -0.387395690 0.188951913 0.047484155 -0.229369478
[46] -0.056832237 -0.115123894 0.009764451 -0.223531093 -0.115978652
[51] -0.480339384 -0.313303507 0.395547958 -0.116399818 -0.260347976
[56] -0.134588375 0.471058280 0.094045438 0.027513957 0.253169087
[61] 0.063756204 -0.184407509 -0.191945403 -0.326544253 0.008639577
[66] -0.050673376 0.022700683 0.367560231 -0.002470200 -0.369807150
[71] -0.058306360 -0.011049817 0.456485619 0.030072205 -0.270487083
[76] 0.272879004 0.325452439 -0.160200470 0.208471801 -0.110750645
[81] -0.078711245 0.160578514 -0.228227637 0.156345518 -0.532065109
[86] -0.516822619 -0.275585920 0.521092917 -0.045782860 0.062899567
[91] 0.034292549 0.063786496 -0.374046735 0.330064772 0.558509196
[96] 0.136180328 0.669301501 -0.123769131 0.109402463 -0.200192242
[101] 0.623175158 0.326874136 -0.010369822 -0.404381033 0.739080753
[106] -0.332778732 0.067557583 0.195992977 0.435204826 -0.480909844
[111] -0.610706376 0.317743163 -0.522007626 -0.679358846 0.008437299
[116] 0.145179263 -0.536601749 0.744682531 -0.011088652 0.165151681
[121] -0.333465760 -0.045240256 0.144469227 -0.195232412 -0.411772013
[126] -0.098280797 -0.446039588 -0.290470299 -0.095490366 -0.568767540
[131] -0.058257601 -0.234042014 -0.025095340 -0.350705417 0.152164788
[136] 0.061627287 0.464012451 -0.263687894 0.069249489 -0.187886992
[141] -0.166802277 -0.034217029 -0.057559447 -0.338205696 0.305897921
[146] 0.127222730 -0.458345501 0.518637941 -0.362652829 0.231530189
[151] 0.291141058 -0.243134068 0.714407834 0.137159281 -0.072271093
[156] 0.149841272 -0.211622283 0.633556678 0.563451179 0.054324685
[161] 0.662715783 -0.253411830 0.482934890 -0.344193241 -0.048563584
[166] 0.248118768 -0.108855440 0.390031791 -0.139627889 0.206124844
[171] 0.437002372 0.068465234 -0.951216951 0.222246213 -0.079009852
[176] 0.460486757 0.690865768 -0.097774267 -0.304692244 -0.014278545
[181] 0.327237649 -0.017882686 -0.235864591 -0.288941078 0.556534623
[186] -1.070515917 -0.122783950 0.049617078 0.034346421 -0.070227091
[191] 0.208281353 0.171355841 -0.264674420 0.047790632 -0.198935366
[196] 0.488812367 -0.053510212 -0.215917569 -0.377117214 -0.761068167
[201] 0.366160210 -0.573481615 0.147961054 0.057332907 -0.123638320
[206] -0.296306184 0.388745731 0.030675077 0.005921264 -0.253329260
[211] 0.022066288 0.237174036 -0.530420306 0.251509937 0.804538295
[216] -0.113599144 0.052159102 0.131077649 -0.124912784 -0.545229783
[221] 0.395569323 -0.034904834 0.827187455 -0.255920170 0.076921925
[226] 0.449689650 0.474800572 -0.155678621 -0.186867087 0.141551407
>
> proc.time()
user system elapsed
1.543 1.783 3.324
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.1 (2024-06-14) -- "Race for Your Life"
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: 0x55a6e553af20>
> .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: 0x55a6e553af20>
> .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: 0x55a6e553af20>
> .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: 0x55a6e553af20>
> 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: 0x55a6e69c01f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55a6e69c01f0>
> .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: 0x55a6e69c01f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55a6e69c01f0>
> .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: 0x55a6e69c01f0>
> 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: 0x55a6e6a0b5a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55a6e6a0b5a0>
> .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: 0x55a6e6a0b5a0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x55a6e6a0b5a0>
> .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: 0x55a6e6a0b5a0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x55a6e6a0b5a0>
> .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: 0x55a6e6a0b5a0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x55a6e6a0b5a0>
> .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: 0x55a6e6a0b5a0>
> 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: 0x55a6e63aab60>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x55a6e63aab60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55a6e63aab60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55a6e63aab60>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1eecf1179c1080" "BufferedMatrixFile1eecf12c79033c"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1eecf1179c1080" "BufferedMatrixFile1eecf12c79033c"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x55a6e6255440>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55a6e6255440>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x55a6e6255440>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x55a6e6255440>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x55a6e6255440>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x55a6e6255440>
> .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: 0x55a6e55d57e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55a6e55d57e0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x55a6e55d57e0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x55a6e55d57e0>
> 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: 0x55a6e5639fc0>
> .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: 0x55a6e5639fc0>
> rm(P)
>
> proc.time()
user system elapsed
0.273 0.041 0.303
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.1 (2024-06-14) -- "Race for Your Life"
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
0.272 0.024 0.285