Ben Bolstad
| Snapshot Date: 2024-05-15 14:05:05 -0400 (Wed, 15 May 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 2024-05-17 11:36:28 -0400 (Fri, 17 May 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 RC (2024-04-16 r86468) -- "Puppy Cup" | 4663 |
| palomino4 | Windows Server 2022 Datacenter | x64 | 4.4.0 RC (2024-04-16 r86468 ucrt) -- "Puppy Cup" | 4398 |
| merida1 | macOS 12.7.4 Monterey | x86_64 | 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup" | 4425 |
| 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 244/2230 | 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 | | ||||||||
| palomino4 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.4 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | see weekly results here | ||||||||||||
|
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: 1.69.0 |
| Command: /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings BufferedMatrix_1.69.0.tar.gz |
| StartedAt: 2024-05-15 20:41:51 -0400 (Wed, 15 May 2024) |
| EndedAt: 2024-05-15 20:42:14 -0400 (Wed, 15 May 2024) |
| EllapsedTime: 23.3 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings BufferedMatrix_1.69.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.0 RC (2024-04-16 r86468)
* 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 22.04.4 LTS
* using session charset: UTF-8
* 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 (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-3.20-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.20-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
gcc -I"/home/biocbuild/bbs-3.20-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.20-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
gcc -I"/home/biocbuild/bbs-3.20-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"/home/biocbuild/bbs-3.20-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c init_package.c -o init_package.o
gcc -shared -L/home/biocbuild/bbs-3.20-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.20-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.20-bioc/R/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.4.0 RC (2024-04-16 r86468) -- "Puppy Cup"
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
0.264 0.037 0.290
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.0 RC (2024-04-16 r86468) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 471778 25.2 1026220 54.9 643434 34.4
Vcells 871903 6.7 8388608 64.0 2046581 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 May 15 20:42:06 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 May 15 20:42:06 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: 0x55f88d88c690>
>
>
>
> 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 May 15 20:42:06 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 May 15 20:42:06 2024"
>
> ColMode(tmp2)
<pointer: 0x55f88d88c690>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.6223916 -0.9502607 -0.6830584 -1.4868336
[2,] 0.5470559 -0.4397309 -2.5739250 -1.1558477
[3,] -1.7493433 3.1953412 -1.2391172 0.1433266
[4,] -1.5496997 -0.1178632 1.5126003 -0.6857526
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.6223916 0.9502607 0.6830584 1.4868336
[2,] 0.5470559 0.4397309 2.5739250 1.1558477
[3,] 1.7493433 3.1953412 1.2391172 0.1433266
[4,] 1.5496997 0.1178632 1.5126003 0.6857526
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0310713 0.9748131 0.8264735 1.2193579
[2,] 0.7396323 0.6631221 1.6043457 1.0751036
[3,] 1.3226274 1.7875517 1.1131564 0.3785849
[4,] 1.2448693 0.3433122 1.2298782 0.8281018
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.93310 35.69839 33.94779 38.68041
[2,] 32.94338 32.07095 43.61738 36.90688
[3,] 39.97562 46.07086 37.37068 28.92918
[4,] 38.99839 28.55098 38.81138 33.96677
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x55f88c73d510>
> exp(tmp5)
<pointer: 0x55f88c73d510>
> log(tmp5,2)
<pointer: 0x55f88c73d510>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.2502
> Min(tmp5)
[1] 52.63975
> mean(tmp5)
[1] 72.88722
> Sum(tmp5)
[1] 14577.44
> Var(tmp5)
[1] 874.7743
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 93.04989 72.31041 72.83926 70.84649 66.74196 69.73207 69.97597 69.31840
[9] 72.00447 72.05330
> rowSums(tmp5)
[1] 1860.998 1446.208 1456.785 1416.930 1334.839 1394.641 1399.519 1386.368
[9] 1440.089 1441.066
> rowVars(tmp5)
[1] 7972.80992 61.06270 116.93307 67.48329 47.54183 35.77782
[7] 71.75210 102.82334 105.06066 74.08804
> rowSd(tmp5)
[1] 89.290593 7.814263 10.813560 8.214821 6.895059 5.981456 8.470661
[8] 10.140184 10.249910 8.607441
> rowMax(tmp5)
[1] 470.25016 90.78386 95.89046 81.17005 80.18601 81.96283 85.40193
[8] 90.57400 95.70774 89.49544
> rowMin(tmp5)
[1] 52.63975 56.98527 58.91495 53.55262 55.60415 61.53611 54.01001 55.45131
[9] 55.28719 58.78354
>
> colMeans(tmp5)
[1] 117.90106 71.80567 70.95510 72.14833 73.88769 68.68459 70.38541
[8] 69.69628 70.40580 68.07525 66.53967 72.80623 67.59434 70.21091
[15] 70.33072 74.52693 70.26160 72.21781 68.91725 70.39380
> colSums(tmp5)
[1] 1179.0106 718.0567 709.5510 721.4833 738.8769 686.8459 703.8541
[8] 696.9628 704.0580 680.7525 665.3967 728.0623 675.9434 702.1091
[15] 703.3072 745.2693 702.6160 722.1781 689.1725 703.9380
> colVars(tmp5)
[1] 15411.97065 142.95844 93.03035 51.00238 118.35148 44.94939
[7] 62.66716 55.27757 84.44979 79.47944 41.41872 69.10198
[13] 89.69032 65.64516 92.92491 75.08466 103.86442 34.12211
[19] 46.24808 124.29520
> colSd(tmp5)
[1] 124.144958 11.956523 9.645224 7.141595 10.878946 6.704430
[7] 7.916259 7.434889 9.189657 8.915124 6.435737 8.312760
[13] 9.470497 8.102170 9.639756 8.665140 10.191390 5.841413
[19] 6.800594 11.148776
> colMax(tmp5)
[1] 470.25016 95.89046 90.78386 80.50821 88.60588 81.96283 81.42115
[8] 81.92677 82.52761 84.49690 79.47763 85.95393 85.40193 88.07557
[15] 90.57400 85.42332 91.52242 81.44345 78.16455 89.49544
> colMin(tmp5)
[1] 62.12096 59.35478 58.29312 59.45009 57.56274 60.91704 56.98527 55.60415
[9] 57.91336 55.45131 52.63975 58.91495 57.43883 62.08651 58.61984 58.78354
[17] 53.55262 64.90063 55.28719 54.01001
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 93.04989 72.31041 72.83926 70.84649 66.74196 69.73207 NA 69.31840
[9] 72.00447 72.05330
> rowSums(tmp5)
[1] 1860.998 1446.208 1456.785 1416.930 1334.839 1394.641 NA 1386.368
[9] 1440.089 1441.066
> rowVars(tmp5)
[1] 7972.80992 61.06270 116.93307 67.48329 47.54183 35.77782
[7] 66.52524 102.82334 105.06066 74.08804
> rowSd(tmp5)
[1] 89.290593 7.814263 10.813560 8.214821 6.895059 5.981456 8.156301
[8] 10.140184 10.249910 8.607441
> rowMax(tmp5)
[1] 470.25016 90.78386 95.89046 81.17005 80.18601 81.96283 NA
[8] 90.57400 95.70774 89.49544
> rowMin(tmp5)
[1] 52.63975 56.98527 58.91495 53.55262 55.60415 61.53611 NA 55.45131
[9] 55.28719 58.78354
>
> colMeans(tmp5)
[1] 117.90106 71.80567 70.95510 72.14833 73.88769 68.68459 70.38541
[8] 69.69628 NA 68.07525 66.53967 72.80623 67.59434 70.21091
[15] 70.33072 74.52693 70.26160 72.21781 68.91725 70.39380
> colSums(tmp5)
[1] 1179.0106 718.0567 709.5510 721.4833 738.8769 686.8459 703.8541
[8] 696.9628 NA 680.7525 665.3967 728.0623 675.9434 702.1091
[15] 703.3072 745.2693 702.6160 722.1781 689.1725 703.9380
> colVars(tmp5)
[1] 15411.97065 142.95844 93.03035 51.00238 118.35148 44.94939
[7] 62.66716 55.27757 NA 79.47944 41.41872 69.10198
[13] 89.69032 65.64516 92.92491 75.08466 103.86442 34.12211
[19] 46.24808 124.29520
> colSd(tmp5)
[1] 124.144958 11.956523 9.645224 7.141595 10.878946 6.704430
[7] 7.916259 7.434889 NA 8.915124 6.435737 8.312760
[13] 9.470497 8.102170 9.639756 8.665140 10.191390 5.841413
[19] 6.800594 11.148776
> colMax(tmp5)
[1] 470.25016 95.89046 90.78386 80.50821 88.60588 81.96283 81.42115
[8] 81.92677 NA 84.49690 79.47763 85.95393 85.40193 88.07557
[15] 90.57400 85.42332 91.52242 81.44345 78.16455 89.49544
> colMin(tmp5)
[1] 62.12096 59.35478 58.29312 59.45009 57.56274 60.91704 56.98527 55.60415
[9] NA 55.45131 52.63975 58.91495 57.43883 62.08651 58.61984 58.78354
[17] 53.55262 64.90063 55.28719 54.01001
>
> Max(tmp5,na.rm=TRUE)
[1] 470.2502
> Min(tmp5,na.rm=TRUE)
[1] 52.63975
> mean(tmp5,na.rm=TRUE)
[1] 72.83878
> Sum(tmp5,na.rm=TRUE)
[1] 14494.92
> Var(tmp5,na.rm=TRUE)
[1] 878.7207
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.04989 72.31041 72.83926 70.84649 66.74196 69.73207 69.31536 69.31840
[9] 72.00447 72.05330
> rowSums(tmp5,na.rm=TRUE)
[1] 1860.998 1446.208 1456.785 1416.930 1334.839 1394.641 1316.992 1386.368
[9] 1440.089 1441.066
> rowVars(tmp5,na.rm=TRUE)
[1] 7972.80992 61.06270 116.93307 67.48329 47.54183 35.77782
[7] 66.52524 102.82334 105.06066 74.08804
> rowSd(tmp5,na.rm=TRUE)
[1] 89.290593 7.814263 10.813560 8.214821 6.895059 5.981456 8.156301
[8] 10.140184 10.249910 8.607441
> rowMax(tmp5,na.rm=TRUE)
[1] 470.25016 90.78386 95.89046 81.17005 80.18601 81.96283 85.40193
[8] 90.57400 95.70774 89.49544
> rowMin(tmp5,na.rm=TRUE)
[1] 52.63975 56.98527 58.91495 53.55262 55.60415 61.53611 54.01001 55.45131
[9] 55.28719 58.78354
>
> colMeans(tmp5,na.rm=TRUE)
[1] 117.90106 71.80567 70.95510 72.14833 73.88769 68.68459 70.38541
[8] 69.69628 69.05893 68.07525 66.53967 72.80623 67.59434 70.21091
[15] 70.33072 74.52693 70.26160 72.21781 68.91725 70.39380
> colSums(tmp5,na.rm=TRUE)
[1] 1179.0106 718.0567 709.5510 721.4833 738.8769 686.8459 703.8541
[8] 696.9628 621.5304 680.7525 665.3967 728.0623 675.9434 702.1091
[15] 703.3072 745.2693 702.6160 722.1781 689.1725 703.9380
> colVars(tmp5,na.rm=TRUE)
[1] 15411.97065 142.95844 93.03035 51.00238 118.35148 44.94939
[7] 62.66716 55.27757 74.59790 79.47944 41.41872 69.10198
[13] 89.69032 65.64516 92.92491 75.08466 103.86442 34.12211
[19] 46.24808 124.29520
> colSd(tmp5,na.rm=TRUE)
[1] 124.144958 11.956523 9.645224 7.141595 10.878946 6.704430
[7] 7.916259 7.434889 8.637008 8.915124 6.435737 8.312760
[13] 9.470497 8.102170 9.639756 8.665140 10.191390 5.841413
[19] 6.800594 11.148776
> colMax(tmp5,na.rm=TRUE)
[1] 470.25016 95.89046 90.78386 80.50821 88.60588 81.96283 81.42115
[8] 81.92677 81.83757 84.49690 79.47763 85.95393 85.40193 88.07557
[15] 90.57400 85.42332 91.52242 81.44345 78.16455 89.49544
> colMin(tmp5,na.rm=TRUE)
[1] 62.12096 59.35478 58.29312 59.45009 57.56274 60.91704 56.98527 55.60415
[9] 57.91336 55.45131 52.63975 58.91495 57.43883 62.08651 58.61984 58.78354
[17] 53.55262 64.90063 55.28719 54.01001
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.04989 72.31041 72.83926 70.84649 66.74196 69.73207 NaN 69.31840
[9] 72.00447 72.05330
> rowSums(tmp5,na.rm=TRUE)
[1] 1860.998 1446.208 1456.785 1416.930 1334.839 1394.641 0.000 1386.368
[9] 1440.089 1441.066
> rowVars(tmp5,na.rm=TRUE)
[1] 7972.80992 61.06270 116.93307 67.48329 47.54183 35.77782
[7] NA 102.82334 105.06066 74.08804
> rowSd(tmp5,na.rm=TRUE)
[1] 89.290593 7.814263 10.813560 8.214821 6.895059 5.981456 NA
[8] 10.140184 10.249910 8.607441
> rowMax(tmp5,na.rm=TRUE)
[1] 470.25016 90.78386 95.89046 81.17005 80.18601 81.96283 NA
[8] 90.57400 95.70774 89.49544
> rowMin(tmp5,na.rm=TRUE)
[1] 52.63975 56.98527 58.91495 53.55262 55.60415 61.53611 NA 55.45131
[9] 55.28719 58.78354
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 124.09885 73.18911 72.36198 73.55925 73.35842 68.44023 69.77847
[8] 68.78011 NaN 67.42416 66.75436 72.52160 65.61572 69.77600
[15] 70.40200 75.55812 70.32931 72.39562 68.59742 72.21422
> colSums(tmp5,na.rm=TRUE)
[1] 1116.8896 658.7020 651.2578 662.0332 660.2257 615.9621 628.0062
[8] 619.0210 0.0000 606.8175 600.7893 652.6944 590.5415 627.9840
[15] 633.6180 680.0231 632.9638 651.5606 617.3768 649.9280
> colVars(tmp5,na.rm=TRUE)
[1] 16906.32538 139.29703 82.39168 34.98249 129.99398 49.89632
[7] 66.35633 52.74444 NA 84.64529 46.07750 76.82831
[13] 56.85851 71.72293 104.48336 72.50761 116.79589 38.03168
[19] 50.87831 102.55034
> colSd(tmp5,na.rm=TRUE)
[1] 130.024326 11.802416 9.076986 5.914600 11.401490 7.063733
[7] 8.145940 7.262537 NA 9.200288 6.788041 8.765176
[13] 7.540458 8.468939 10.221710 8.515140 10.807215 6.166983
[19] 7.132903 10.126714
> colMax(tmp5,na.rm=TRUE)
[1] 470.25016 95.89046 90.78386 80.50821 88.60588 81.96283 81.42115
[8] 81.92677 -Inf 84.49690 79.47763 85.95393 83.51060 88.07557
[15] 90.57400 85.42332 91.52242 81.44345 78.16455 89.49544
> colMin(tmp5,na.rm=TRUE)
[1] 68.56733 59.42513 62.24201 60.21229 57.56274 60.91704 56.98527 55.60415
[9] Inf 55.45131 52.63975 58.91495 57.43883 62.08651 58.61984 58.78354
[17] 53.55262 64.90063 55.28719 58.62973
>
>
>
>
> 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] 111.62526 280.87311 181.57826 149.35110 236.91937 189.54860 267.35056
[8] 99.11847 119.99042 341.03691
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 111.62526 280.87311 181.57826 149.35110 236.91937 189.54860 267.35056
[8] 99.11847 119.99042 341.03691
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -5.684342e-14 2.842171e-14 -7.105427e-14 -1.705303e-13 5.684342e-14
[6] -2.842171e-14 1.421085e-13 1.421085e-14 2.842171e-14 -8.526513e-14
[11] -1.136868e-13 0.000000e+00 5.684342e-14 -5.684342e-14 -5.684342e-14
[16] -2.842171e-14 5.684342e-14 5.684342e-14 8.526513e-14 1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
1 4
7 2
5 14
1 18
9 11
10 15
4 10
6 17
8 10
10 8
7 20
3 14
2 4
7 5
1 9
7 3
4 18
10 13
10 1
9 3
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] 2.223243
> Min(tmp)
[1] -2.713536
> mean(tmp)
[1] -0.0762582
> Sum(tmp)
[1] -7.62582
> Var(tmp)
[1] 0.9484081
>
> rowMeans(tmp)
[1] -0.0762582
> rowSums(tmp)
[1] -7.62582
> rowVars(tmp)
[1] 0.9484081
> rowSd(tmp)
[1] 0.9738625
> rowMax(tmp)
[1] 2.223243
> rowMin(tmp)
[1] -2.713536
>
> colMeans(tmp)
[1] 1.276676905 -1.007414905 0.914211266 -0.286569259 -0.577570536
[6] 0.005245672 -1.201210235 -1.417402147 -0.931724251 -1.624224393
[11] -0.751274899 0.358356461 -0.626507541 -0.037389362 -0.410609296
[16] -0.027654376 0.281884173 -0.149431580 -1.559156669 -0.309539802
[21] -0.657822617 -2.713535507 1.068880300 -0.181126211 0.070564760
[26] 0.599866873 0.340923868 1.891358579 -1.318473877 -2.022807644
[31] 0.062932022 -0.233388774 -0.221757375 -1.391751401 -0.160292809
[36] -0.688916360 0.737743235 -1.093365634 1.109785781 2.223243236
[41] -0.492735313 1.726525237 -0.694495961 0.822325493 -0.309648948
[46] 0.077550594 -0.095895357 0.743463955 -0.497529215 0.494459396
[51] -0.282292930 0.690867096 -1.738243902 1.485786889 -1.822481710
[56] 1.489351162 -1.266498744 0.671936540 -1.019544189 0.989151320
[61] -0.568461733 0.750498344 0.044757840 0.632748662 0.425046998
[66] 0.367765179 0.370811701 0.371255431 0.720243985 1.361731989
[71] -0.887092749 1.412826180 -1.039328485 -0.780458008 -0.338551855
[76] 0.076801027 -0.089777478 1.351390227 1.172353883 -0.207229238
[81] -0.720659591 0.044954579 -0.093435617 0.779505389 -0.551146868
[86] -0.345994341 -2.080130881 -1.143590627 -0.420897813 -1.111506664
[91] 0.810554330 -0.064056677 -0.258108074 0.655169972 1.336807814
[96] -1.362042758 -0.946067554 0.199463276 1.663197616 0.522025449
> colSums(tmp)
[1] 1.276676905 -1.007414905 0.914211266 -0.286569259 -0.577570536
[6] 0.005245672 -1.201210235 -1.417402147 -0.931724251 -1.624224393
[11] -0.751274899 0.358356461 -0.626507541 -0.037389362 -0.410609296
[16] -0.027654376 0.281884173 -0.149431580 -1.559156669 -0.309539802
[21] -0.657822617 -2.713535507 1.068880300 -0.181126211 0.070564760
[26] 0.599866873 0.340923868 1.891358579 -1.318473877 -2.022807644
[31] 0.062932022 -0.233388774 -0.221757375 -1.391751401 -0.160292809
[36] -0.688916360 0.737743235 -1.093365634 1.109785781 2.223243236
[41] -0.492735313 1.726525237 -0.694495961 0.822325493 -0.309648948
[46] 0.077550594 -0.095895357 0.743463955 -0.497529215 0.494459396
[51] -0.282292930 0.690867096 -1.738243902 1.485786889 -1.822481710
[56] 1.489351162 -1.266498744 0.671936540 -1.019544189 0.989151320
[61] -0.568461733 0.750498344 0.044757840 0.632748662 0.425046998
[66] 0.367765179 0.370811701 0.371255431 0.720243985 1.361731989
[71] -0.887092749 1.412826180 -1.039328485 -0.780458008 -0.338551855
[76] 0.076801027 -0.089777478 1.351390227 1.172353883 -0.207229238
[81] -0.720659591 0.044954579 -0.093435617 0.779505389 -0.551146868
[86] -0.345994341 -2.080130881 -1.143590627 -0.420897813 -1.111506664
[91] 0.810554330 -0.064056677 -0.258108074 0.655169972 1.336807814
[96] -1.362042758 -0.946067554 0.199463276 1.663197616 0.522025449
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] 1.276676905 -1.007414905 0.914211266 -0.286569259 -0.577570536
[6] 0.005245672 -1.201210235 -1.417402147 -0.931724251 -1.624224393
[11] -0.751274899 0.358356461 -0.626507541 -0.037389362 -0.410609296
[16] -0.027654376 0.281884173 -0.149431580 -1.559156669 -0.309539802
[21] -0.657822617 -2.713535507 1.068880300 -0.181126211 0.070564760
[26] 0.599866873 0.340923868 1.891358579 -1.318473877 -2.022807644
[31] 0.062932022 -0.233388774 -0.221757375 -1.391751401 -0.160292809
[36] -0.688916360 0.737743235 -1.093365634 1.109785781 2.223243236
[41] -0.492735313 1.726525237 -0.694495961 0.822325493 -0.309648948
[46] 0.077550594 -0.095895357 0.743463955 -0.497529215 0.494459396
[51] -0.282292930 0.690867096 -1.738243902 1.485786889 -1.822481710
[56] 1.489351162 -1.266498744 0.671936540 -1.019544189 0.989151320
[61] -0.568461733 0.750498344 0.044757840 0.632748662 0.425046998
[66] 0.367765179 0.370811701 0.371255431 0.720243985 1.361731989
[71] -0.887092749 1.412826180 -1.039328485 -0.780458008 -0.338551855
[76] 0.076801027 -0.089777478 1.351390227 1.172353883 -0.207229238
[81] -0.720659591 0.044954579 -0.093435617 0.779505389 -0.551146868
[86] -0.345994341 -2.080130881 -1.143590627 -0.420897813 -1.111506664
[91] 0.810554330 -0.064056677 -0.258108074 0.655169972 1.336807814
[96] -1.362042758 -0.946067554 0.199463276 1.663197616 0.522025449
> colMin(tmp)
[1] 1.276676905 -1.007414905 0.914211266 -0.286569259 -0.577570536
[6] 0.005245672 -1.201210235 -1.417402147 -0.931724251 -1.624224393
[11] -0.751274899 0.358356461 -0.626507541 -0.037389362 -0.410609296
[16] -0.027654376 0.281884173 -0.149431580 -1.559156669 -0.309539802
[21] -0.657822617 -2.713535507 1.068880300 -0.181126211 0.070564760
[26] 0.599866873 0.340923868 1.891358579 -1.318473877 -2.022807644
[31] 0.062932022 -0.233388774 -0.221757375 -1.391751401 -0.160292809
[36] -0.688916360 0.737743235 -1.093365634 1.109785781 2.223243236
[41] -0.492735313 1.726525237 -0.694495961 0.822325493 -0.309648948
[46] 0.077550594 -0.095895357 0.743463955 -0.497529215 0.494459396
[51] -0.282292930 0.690867096 -1.738243902 1.485786889 -1.822481710
[56] 1.489351162 -1.266498744 0.671936540 -1.019544189 0.989151320
[61] -0.568461733 0.750498344 0.044757840 0.632748662 0.425046998
[66] 0.367765179 0.370811701 0.371255431 0.720243985 1.361731989
[71] -0.887092749 1.412826180 -1.039328485 -0.780458008 -0.338551855
[76] 0.076801027 -0.089777478 1.351390227 1.172353883 -0.207229238
[81] -0.720659591 0.044954579 -0.093435617 0.779505389 -0.551146868
[86] -0.345994341 -2.080130881 -1.143590627 -0.420897813 -1.111506664
[91] 0.810554330 -0.064056677 -0.258108074 0.655169972 1.336807814
[96] -1.362042758 -0.946067554 0.199463276 1.663197616 0.522025449
> colMedians(tmp)
[1] 1.276676905 -1.007414905 0.914211266 -0.286569259 -0.577570536
[6] 0.005245672 -1.201210235 -1.417402147 -0.931724251 -1.624224393
[11] -0.751274899 0.358356461 -0.626507541 -0.037389362 -0.410609296
[16] -0.027654376 0.281884173 -0.149431580 -1.559156669 -0.309539802
[21] -0.657822617 -2.713535507 1.068880300 -0.181126211 0.070564760
[26] 0.599866873 0.340923868 1.891358579 -1.318473877 -2.022807644
[31] 0.062932022 -0.233388774 -0.221757375 -1.391751401 -0.160292809
[36] -0.688916360 0.737743235 -1.093365634 1.109785781 2.223243236
[41] -0.492735313 1.726525237 -0.694495961 0.822325493 -0.309648948
[46] 0.077550594 -0.095895357 0.743463955 -0.497529215 0.494459396
[51] -0.282292930 0.690867096 -1.738243902 1.485786889 -1.822481710
[56] 1.489351162 -1.266498744 0.671936540 -1.019544189 0.989151320
[61] -0.568461733 0.750498344 0.044757840 0.632748662 0.425046998
[66] 0.367765179 0.370811701 0.371255431 0.720243985 1.361731989
[71] -0.887092749 1.412826180 -1.039328485 -0.780458008 -0.338551855
[76] 0.076801027 -0.089777478 1.351390227 1.172353883 -0.207229238
[81] -0.720659591 0.044954579 -0.093435617 0.779505389 -0.551146868
[86] -0.345994341 -2.080130881 -1.143590627 -0.420897813 -1.111506664
[91] 0.810554330 -0.064056677 -0.258108074 0.655169972 1.336807814
[96] -1.362042758 -0.946067554 0.199463276 1.663197616 0.522025449
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.276677 -1.007415 0.9142113 -0.2865693 -0.5775705 0.005245672 -1.20121
[2,] 1.276677 -1.007415 0.9142113 -0.2865693 -0.5775705 0.005245672 -1.20121
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.417402 -0.9317243 -1.624224 -0.7512749 0.3583565 -0.6265075 -0.03738936
[2,] -1.417402 -0.9317243 -1.624224 -0.7512749 0.3583565 -0.6265075 -0.03738936
[,15] [,16] [,17] [,18] [,19] [,20]
[1,] -0.4106093 -0.02765438 0.2818842 -0.1494316 -1.559157 -0.3095398
[2,] -0.4106093 -0.02765438 0.2818842 -0.1494316 -1.559157 -0.3095398
[,21] [,22] [,23] [,24] [,25] [,26] [,27]
[1,] -0.6578226 -2.713536 1.06888 -0.1811262 0.07056476 0.5998669 0.3409239
[2,] -0.6578226 -2.713536 1.06888 -0.1811262 0.07056476 0.5998669 0.3409239
[,28] [,29] [,30] [,31] [,32] [,33] [,34]
[1,] 1.891359 -1.318474 -2.022808 0.06293202 -0.2333888 -0.2217574 -1.391751
[2,] 1.891359 -1.318474 -2.022808 0.06293202 -0.2333888 -0.2217574 -1.391751
[,35] [,36] [,37] [,38] [,39] [,40] [,41]
[1,] -0.1602928 -0.6889164 0.7377432 -1.093366 1.109786 2.223243 -0.4927353
[2,] -0.1602928 -0.6889164 0.7377432 -1.093366 1.109786 2.223243 -0.4927353
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] 1.726525 -0.694496 0.8223255 -0.3096489 0.07755059 -0.09589536 0.743464
[2,] 1.726525 -0.694496 0.8223255 -0.3096489 0.07755059 -0.09589536 0.743464
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.4975292 0.4944594 -0.2822929 0.6908671 -1.738244 1.485787 -1.822482
[2,] -0.4975292 0.4944594 -0.2822929 0.6908671 -1.738244 1.485787 -1.822482
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] 1.489351 -1.266499 0.6719365 -1.019544 0.9891513 -0.5684617 0.7504983
[2,] 1.489351 -1.266499 0.6719365 -1.019544 0.9891513 -0.5684617 0.7504983
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 0.04475784 0.6327487 0.425047 0.3677652 0.3708117 0.3712554 0.720244
[2,] 0.04475784 0.6327487 0.425047 0.3677652 0.3708117 0.3712554 0.720244
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 1.361732 -0.8870927 1.412826 -1.039328 -0.780458 -0.3385519 0.07680103
[2,] 1.361732 -0.8870927 1.412826 -1.039328 -0.780458 -0.3385519 0.07680103
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -0.08977748 1.35139 1.172354 -0.2072292 -0.7206596 0.04495458 -0.09343562
[2,] -0.08977748 1.35139 1.172354 -0.2072292 -0.7206596 0.04495458 -0.09343562
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 0.7795054 -0.5511469 -0.3459943 -2.080131 -1.143591 -0.4208978 -1.111507
[2,] 0.7795054 -0.5511469 -0.3459943 -2.080131 -1.143591 -0.4208978 -1.111507
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 0.8105543 -0.06405668 -0.2581081 0.65517 1.336808 -1.362043 -0.9460676
[2,] 0.8105543 -0.06405668 -0.2581081 0.65517 1.336808 -1.362043 -0.9460676
[,98] [,99] [,100]
[1,] 0.1994633 1.663198 0.5220254
[2,] 0.1994633 1.663198 0.5220254
>
>
> Max(tmp2)
[1] 2.392418
> Min(tmp2)
[1] -2.070121
> mean(tmp2)
[1] 0.03416256
> Sum(tmp2)
[1] 3.416256
> Var(tmp2)
[1] 0.9088548
>
> rowMeans(tmp2)
[1] -0.555729122 0.559385241 0.137413065 0.402110326 1.463568546
[6] -1.385346911 -0.510086909 0.052397555 0.422100949 -0.441526340
[11] 0.112901567 -0.516258091 -0.646667819 0.418432560 0.323324067
[16] 0.809913648 -0.771098227 0.071607905 0.280870771 -2.070121293
[21] 0.243058011 1.041182727 0.549544183 -0.242156910 -1.084564717
[26] -0.274909883 1.188497674 -1.555768383 0.082594752 -0.356575984
[31] -0.893868728 -0.780089661 0.559111439 -0.204609153 0.132101553
[36] 1.641980463 0.543122856 1.255560187 -0.835549104 2.392417923
[41] -0.184652883 -1.625961176 0.167418418 1.842858525 0.851089290
[46] 0.792471449 -0.986084925 1.400675418 -1.532914440 -1.490585615
[51] 1.075023927 1.119369113 -0.109500815 0.651336721 -0.236977960
[56] 1.263101374 -0.665233856 -0.791503598 0.406285031 0.300669075
[61] 1.556745388 0.004486575 -1.574963666 -0.706304938 -1.771463334
[66] 0.535367165 0.612879505 1.475968615 0.999093693 1.048932249
[71] -1.031016025 0.023130170 -1.134323108 0.875989029 0.913395303
[76] -0.532987108 -0.894947766 1.443567211 0.106666671 -0.869991894
[81] 0.882399771 -1.720931905 -0.064388119 -0.446285642 -0.135408413
[86] -0.572029087 0.228763720 0.715152895 0.484296760 -1.889520924
[91] -0.152039955 -1.409389422 0.880101236 1.519057838 0.581959032
[96] -0.455128944 -0.412042544 -0.895532130 0.451508101 0.940335827
> rowSums(tmp2)
[1] -0.555729122 0.559385241 0.137413065 0.402110326 1.463568546
[6] -1.385346911 -0.510086909 0.052397555 0.422100949 -0.441526340
[11] 0.112901567 -0.516258091 -0.646667819 0.418432560 0.323324067
[16] 0.809913648 -0.771098227 0.071607905 0.280870771 -2.070121293
[21] 0.243058011 1.041182727 0.549544183 -0.242156910 -1.084564717
[26] -0.274909883 1.188497674 -1.555768383 0.082594752 -0.356575984
[31] -0.893868728 -0.780089661 0.559111439 -0.204609153 0.132101553
[36] 1.641980463 0.543122856 1.255560187 -0.835549104 2.392417923
[41] -0.184652883 -1.625961176 0.167418418 1.842858525 0.851089290
[46] 0.792471449 -0.986084925 1.400675418 -1.532914440 -1.490585615
[51] 1.075023927 1.119369113 -0.109500815 0.651336721 -0.236977960
[56] 1.263101374 -0.665233856 -0.791503598 0.406285031 0.300669075
[61] 1.556745388 0.004486575 -1.574963666 -0.706304938 -1.771463334
[66] 0.535367165 0.612879505 1.475968615 0.999093693 1.048932249
[71] -1.031016025 0.023130170 -1.134323108 0.875989029 0.913395303
[76] -0.532987108 -0.894947766 1.443567211 0.106666671 -0.869991894
[81] 0.882399771 -1.720931905 -0.064388119 -0.446285642 -0.135408413
[86] -0.572029087 0.228763720 0.715152895 0.484296760 -1.889520924
[91] -0.152039955 -1.409389422 0.880101236 1.519057838 0.581959032
[96] -0.455128944 -0.412042544 -0.895532130 0.451508101 0.940335827
> 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] -0.555729122 0.559385241 0.137413065 0.402110326 1.463568546
[6] -1.385346911 -0.510086909 0.052397555 0.422100949 -0.441526340
[11] 0.112901567 -0.516258091 -0.646667819 0.418432560 0.323324067
[16] 0.809913648 -0.771098227 0.071607905 0.280870771 -2.070121293
[21] 0.243058011 1.041182727 0.549544183 -0.242156910 -1.084564717
[26] -0.274909883 1.188497674 -1.555768383 0.082594752 -0.356575984
[31] -0.893868728 -0.780089661 0.559111439 -0.204609153 0.132101553
[36] 1.641980463 0.543122856 1.255560187 -0.835549104 2.392417923
[41] -0.184652883 -1.625961176 0.167418418 1.842858525 0.851089290
[46] 0.792471449 -0.986084925 1.400675418 -1.532914440 -1.490585615
[51] 1.075023927 1.119369113 -0.109500815 0.651336721 -0.236977960
[56] 1.263101374 -0.665233856 -0.791503598 0.406285031 0.300669075
[61] 1.556745388 0.004486575 -1.574963666 -0.706304938 -1.771463334
[66] 0.535367165 0.612879505 1.475968615 0.999093693 1.048932249
[71] -1.031016025 0.023130170 -1.134323108 0.875989029 0.913395303
[76] -0.532987108 -0.894947766 1.443567211 0.106666671 -0.869991894
[81] 0.882399771 -1.720931905 -0.064388119 -0.446285642 -0.135408413
[86] -0.572029087 0.228763720 0.715152895 0.484296760 -1.889520924
[91] -0.152039955 -1.409389422 0.880101236 1.519057838 0.581959032
[96] -0.455128944 -0.412042544 -0.895532130 0.451508101 0.940335827
> rowMin(tmp2)
[1] -0.555729122 0.559385241 0.137413065 0.402110326 1.463568546
[6] -1.385346911 -0.510086909 0.052397555 0.422100949 -0.441526340
[11] 0.112901567 -0.516258091 -0.646667819 0.418432560 0.323324067
[16] 0.809913648 -0.771098227 0.071607905 0.280870771 -2.070121293
[21] 0.243058011 1.041182727 0.549544183 -0.242156910 -1.084564717
[26] -0.274909883 1.188497674 -1.555768383 0.082594752 -0.356575984
[31] -0.893868728 -0.780089661 0.559111439 -0.204609153 0.132101553
[36] 1.641980463 0.543122856 1.255560187 -0.835549104 2.392417923
[41] -0.184652883 -1.625961176 0.167418418 1.842858525 0.851089290
[46] 0.792471449 -0.986084925 1.400675418 -1.532914440 -1.490585615
[51] 1.075023927 1.119369113 -0.109500815 0.651336721 -0.236977960
[56] 1.263101374 -0.665233856 -0.791503598 0.406285031 0.300669075
[61] 1.556745388 0.004486575 -1.574963666 -0.706304938 -1.771463334
[66] 0.535367165 0.612879505 1.475968615 0.999093693 1.048932249
[71] -1.031016025 0.023130170 -1.134323108 0.875989029 0.913395303
[76] -0.532987108 -0.894947766 1.443567211 0.106666671 -0.869991894
[81] 0.882399771 -1.720931905 -0.064388119 -0.446285642 -0.135408413
[86] -0.572029087 0.228763720 0.715152895 0.484296760 -1.889520924
[91] -0.152039955 -1.409389422 0.880101236 1.519057838 0.581959032
[96] -0.455128944 -0.412042544 -0.895532130 0.451508101 0.940335827
>
> colMeans(tmp2)
[1] 0.03416256
> colSums(tmp2)
[1] 3.416256
> colVars(tmp2)
[1] 0.9088548
> colSd(tmp2)
[1] 0.9533388
> colMax(tmp2)
[1] 2.392418
> colMin(tmp2)
[1] -2.070121
> colMedians(tmp2)
[1] 0.09463071
> colRanges(tmp2)
[,1]
[1,] -2.070121
[2,] 2.392418
>
> 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] 2.2899376446 0.0005610424 -4.2034175091 -3.8182597734 3.1699930820
[6] -0.1440385513 2.9387050574 -1.8596634001 -1.7131986845 0.2590709940
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.4265316
[2,] -0.3585372
[3,] 0.1937979
[4,] 0.8512989
[5,] 1.9975651
>
> rowApply(tmp,sum)
[1] -0.2321467 2.4008187 -5.0296683 -3.4563260 3.4511458 -3.7907227
[7] -0.6675703 2.3359477 2.1752919 -0.2670802
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 4 5 2 6 2 8 4 9 8
[2,] 8 1 8 10 9 7 3 8 2 4
[3,] 4 2 1 6 1 1 6 9 5 5
[4,] 1 10 3 1 4 3 5 7 8 6
[5,] 6 9 2 9 7 9 10 10 3 3
[6,] 2 8 6 5 8 10 1 1 1 9
[7,] 3 3 9 8 10 4 9 5 7 2
[8,] 5 6 7 7 5 8 4 2 10 1
[9,] 7 7 4 4 2 5 7 3 4 7
[10,] 9 5 10 3 3 6 2 6 6 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.7450685 2.5848167 -2.8358914 1.9487531 1.2618497 -3.1820828
[7] 1.5098460 1.0045434 2.6175675 -1.7347206 1.9346774 -1.0390357
[13] 0.1695960 1.4023975 -1.0371904 1.7574139 -0.9303101 0.3623290
[19] 0.1202426 -0.7061711
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.83679821
[2,] -0.20773274
[3,] -0.01887637
[4,] 0.79621195
[5,] 1.01226392
>
> rowApply(tmp,sum)
[1] 4.588790 -2.765540 4.734048 -0.420224 -0.183375
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 16 17 4 9 8
[2,] 20 5 10 14 15
[3,] 1 3 12 11 2
[4,] 17 10 16 6 13
[5,] 4 14 20 4 17
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.01226392 1.6252796 -1.0317889 1.0279890 -0.67785380 -0.0391296
[2,] 0.79621195 -0.6689758 -0.7100299 -0.2409253 0.08206707 0.3042923
[3,] -0.83679821 0.3965921 0.5766769 0.9607173 1.82811719 -0.3805286
[4,] -0.01887637 0.3899827 0.1605615 -0.2889479 -0.87086244 -1.8902737
[5,] -0.20773274 0.8419380 -1.8313108 0.4899199 0.90038165 -1.1764432
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.6692782 0.4225049 1.1096228 -1.0167254 -0.95827231 0.76322926
[2,] 1.0290070 -0.3565210 -0.4364815 -0.2107621 1.57526411 -3.26143621
[3,] 1.2273453 0.9233974 -1.0864240 0.2519048 1.07871567 -0.05893041
[4,] -0.8928660 0.2345699 0.8765296 -0.8637150 0.19563254 0.71031648
[5,] -0.5229184 -0.2194078 2.1543206 0.1045772 0.04333735 0.80778521
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.35575632 0.10030790 0.3173589 -0.2912398 0.2930850 1.3611771
[2,] -0.27927147 -0.02678396 -0.6760612 1.2658463 -0.1898435 -0.8707064
[3,] -0.10906561 0.68469336 -2.4970463 -0.9765241 0.5169197 0.8429760
[4,] 0.02784714 0.85520092 0.8208136 0.6151459 -0.1320803 -1.1422923
[5,] 0.88584226 -0.21102074 0.9977445 1.1441855 -1.4183910 0.1711746
[,19] [,20]
[1,] 0.22985351 0.02760561
[2,] -0.33769178 0.44726188
[3,] 0.39261227 0.99869728
[4,] -0.26394420 1.05703385
[5,] 0.09941278 -3.23676970
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 563 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 -1.167689 -0.2225264 -0.8830447 -1.597256 -0.1777088 1.789549 -1.187021
col8 col9 col10 col11 col12 col13 col14
row1 -0.2753883 -0.2819729 0.234625 -0.3107185 2.101304 0.3835766 -1.539423
col15 col16 col17 col18 col19 col20
row1 -1.013134 -0.08768371 0.6707714 -0.6813063 0.4067745 1.464821
> tmp[,"col10"]
col10
row1 0.2346250
row2 -0.5972472
row3 -1.7675427
row4 -0.1027053
row5 -0.7357542
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -1.1676894 -0.2225264 -0.8830447 -1.5972559 -0.1777088 1.7895491
row5 -0.8418087 0.9713935 0.4611865 0.9556793 1.1802372 0.4877435
col7 col8 col9 col10 col11 col12
row1 -1.1870211 -0.2753883 -0.2819729 0.2346250 -0.3107185 2.1013038
row5 -0.5074651 -0.3118476 -1.5302810 -0.7357542 1.2222239 -0.6794742
col13 col14 col15 col16 col17 col18 col19
row1 0.3835766 -1.539423 -1.0131342 -0.08768371 0.6707714 -0.6813063 0.4067745
row5 0.3406983 -1.095047 0.1730393 -0.85457096 -0.3671256 -0.5471160 0.8677523
col20
row1 1.4648209
row5 -0.2785008
> tmp[,c("col6","col20")]
col6 col20
row1 1.78954912 1.4648209
row2 -0.25798459 0.3513862
row3 -1.87298897 -0.5768196
row4 0.04284994 0.4387431
row5 0.48774350 -0.2785008
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.7895491 1.4648209
row5 0.4877435 -0.2785008
>
>
>
>
> 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 50.39136 49.57584 50.28022 49.68471 50.65676 104.7974 49.42113 49.13351
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.66426 50.11616 51.41928 49.40118 50.45747 50.41461 49.28745 50.14128
col17 col18 col19 col20
row1 51.07242 48.18802 49.50779 105.8931
> tmp[,"col10"]
col10
row1 50.11616
row2 30.17185
row3 31.26645
row4 30.84491
row5 50.31986
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.39136 49.57584 50.28022 49.68471 50.65676 104.7974 49.42113 49.13351
row5 50.07384 50.97974 50.07635 49.64153 49.65119 104.9794 47.66184 50.97199
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.66426 50.11616 51.41928 49.40118 50.45747 50.41461 49.28745 50.14128
row5 52.35545 50.31986 49.77376 52.11868 48.74666 48.28436 50.62076 50.80967
col17 col18 col19 col20
row1 51.07242 48.18802 49.50779 105.8931
row5 49.38307 49.73763 48.70794 104.8886
> tmp[,c("col6","col20")]
col6 col20
row1 104.79737 105.89315
row2 76.21756 74.18269
row3 75.33466 75.26357
row4 75.41206 73.36477
row5 104.97940 104.88858
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.7974 105.8931
row5 104.9794 104.8886
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.7974 105.8931
row5 104.9794 104.8886
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.44663690
[2,] -0.41400250
[3,] -0.02989759
[4,] -2.11211948
[5,] -1.33783826
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.9061432 -0.06544822
[2,] -0.9282807 0.37800587
[3,] 0.4916085 -1.84796730
[4,] 0.9116356 0.82761335
[5,] 1.0911720 0.35433972
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 2.7855387 -0.46814774
[2,] 0.4025407 0.12832190
[3,] -1.1263194 -0.74527937
[4,] -0.1529646 -0.26452908
[5,] -0.7564990 0.01094947
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 2.785539
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 2.7855387
[2,] 0.4025407
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 -0.7450685 -0.8154758 1.192335 -0.3608045 -1.7822000 -1.384490 -0.2046563
row1 -0.8718982 -1.3863991 1.208605 -0.1346908 -0.2199181 0.128945 0.4055929
[,8] [,9] [,10] [,11] [,12] [,13]
row3 0.5872875 1.3159764 0.08724421 0.3261764 -1.1559753 -0.026832464
row1 -0.8389400 -0.6417707 -0.04016658 0.3365121 0.8698108 0.008467798
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.1310540 0.1515411 0.6158469 0.8191017 -1.053999 -1.9545660 -1.017298
row1 -0.5115994 1.5395695 2.5767992 0.9417013 1.429096 0.2335413 -0.597544
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.4246095 -0.6689012 0.000855011 -1.103653 1.555051 -0.38511 -0.1724407
[,8] [,9] [,10]
row2 0.7278725 2.033925 -0.1537424
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row5 0.8040575 0.09865817 0.5519886 0.02058308 -0.07504176 -0.9375011
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row5 -0.3183197 -0.210534 -0.5377373 -0.5315732 2.002255 0.3215938 -1.20506
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row5 0.2446055 1.185969 -1.182674 -0.8037931 -0.1240106 0.2669447 -0.2813004
>
>
> 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: 0x55f88ea11cb0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1732b61cd7d392"
[2] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1732b624f7fb19"
[3] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1732b674745988"
[4] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1732b612f14f14"
[5] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1732b625acb4ff"
[6] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1732b655635651"
[7] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1732b6659a977e"
[8] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1732b677e67331"
[9] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1732b64855d4f4"
[10] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1732b63762f591"
[11] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1732b643cc8ab3"
[12] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1732b66646f5ae"
[13] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1732b621b467c9"
[14] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1732b674ab6449"
[15] "/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1732b626d3c962"
>
>
> ### 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: 0x55f88cb00510>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x55f88cb00510>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x55f88cb00510>
> rowMedians(tmp)
[1] -0.048046520 -0.169963783 -0.610877182 0.203852800 -0.202772696
[6] -0.878581732 -0.252561463 -0.229499618 -0.486934137 0.222111491
[11] 0.428516220 -0.622493695 0.094535991 -0.042190784 -0.292640054
[16] 0.469744088 -0.262164958 0.430293136 0.116749845 0.264677751
[21] -0.152130161 -0.382330973 -0.119601770 0.486873184 0.261910202
[26] -0.019764840 0.038374919 -0.221547058 -0.226525042 -0.003723618
[31] 0.008800785 0.200169729 -0.055967447 0.408224332 0.093873304
[36] -0.023748897 -0.258464124 0.306365164 0.172971170 0.412989583
[41] -0.259838487 -0.321860646 0.345990692 0.757960506 0.209966014
[46] 0.251095417 -0.541377738 0.173449561 0.150956321 -0.075265067
[51] -0.351015465 0.240715163 -0.081904619 -0.068533546 -0.506518714
[56] -0.249427953 -0.043160032 -0.052500338 -0.376636602 -0.522964226
[61] 0.342823173 0.419943641 0.410203623 0.045103287 0.235133572
[66] -0.057574247 0.133635425 0.262630299 0.658736033 0.159776647
[71] 0.593044311 0.113160977 -0.142621854 -0.117262930 -0.137225095
[76] 0.533395159 0.270497355 0.370778951 0.360095339 0.669434545
[81] 0.073984846 -0.077409796 0.214375027 0.045662310 -0.074448532
[86] -0.024393471 -0.004436607 0.060265914 0.132800884 0.060636334
[91] 0.294032944 -0.057142952 -0.021741910 -0.206950004 -0.239129150
[96] 0.303019700 -0.385687700 -0.060472995 0.081340839 0.059935525
[101] 0.265926600 -0.155918644 -0.206545256 0.153044721 -0.665883992
[106] 0.341353512 -0.123637824 -0.172183893 -0.409055128 -0.376141514
[111] -0.583164642 -0.307894638 0.055319462 -0.111663962 -0.255006073
[116] -0.366166101 0.428866829 0.340183702 0.460040768 -0.270105372
[121] 0.179979053 0.207845438 -0.106937517 0.566213859 0.056899613
[126] 0.660147940 -0.124668359 0.408582597 0.185001920 -0.009888225
[131] -0.734499056 -0.375270561 0.181999358 0.502356035 -0.151240465
[136] -0.473694004 -0.424396951 -0.486006943 0.060149983 0.266687642
[141] -0.320463701 -0.291328620 -0.134832521 -0.331306343 -0.232777731
[146] 0.276205152 -0.204373234 -0.186764965 -0.262306663 0.034028528
[151] 0.523900637 -0.387632694 0.179896328 0.140709035 0.299768036
[156] 0.603599753 0.127508282 0.330479217 -0.034216106 0.191008221
[161] 0.517792465 -0.196620441 -0.092263020 -0.228615023 -0.222262437
[166] -0.194903610 0.184399785 -0.126370033 0.123972342 0.276949667
[171] -0.108271987 0.003285643 -0.299977844 -0.181842548 0.766324871
[176] 0.438268604 0.069538165 -0.327880392 0.097645878 0.070689253
[181] 0.583233328 -0.527112684 0.247315811 0.016418929 -0.041864543
[186] -0.238799175 0.052024597 -0.031372423 0.456983789 0.464604567
[191] -0.348334136 0.011587784 0.582573699 0.072296375 -0.299620179
[196] 0.603457785 0.449954047 -0.254990645 -0.361555577 0.121227451
[201] 0.188115909 0.359447414 0.282768525 0.226914295 -0.173227521
[206] -0.637231791 -0.186916575 0.018236153 0.039219150 -0.424291412
[211] 0.235047525 0.402681651 -0.160666230 -0.265323127 -0.136742115
[216] 0.230339288 -0.433888176 0.146055272 -0.066488737 -0.129313790
[221] 0.312941250 0.040913819 -0.229532617 -0.393155910 0.124664930
[226] -0.006356814 -0.323306602 -0.364055936 -0.235807360 0.163867013
>
> proc.time()
user system elapsed
1.337 0.583 1.923
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.0 RC (2024-04-16 r86468) -- "Puppy Cup"
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: 0x55f365b86690>
> .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: 0x55f365b86690>
> .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: 0x55f365b86690>
> .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: 0x55f365b86690>
> 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: 0x55f365c72970>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55f365c72970>
> .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: 0x55f365c72970>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55f365c72970>
> .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: 0x55f365c72970>
> 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: 0x55f365b7af00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55f365b7af00>
> .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: 0x55f365b7af00>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x55f365b7af00>
> .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: 0x55f365b7af00>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x55f365b7af00>
> .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: 0x55f365b7af00>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x55f365b7af00>
> .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: 0x55f365b7af00>
> 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: 0x55f364535650>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x55f364535650>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55f364535650>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55f364535650>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1733953715951d" "BufferedMatrixFile1733955f96ebe1"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1733953715951d" "BufferedMatrixFile1733955f96ebe1"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x55f364919060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55f364919060>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x55f364919060>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x55f364919060>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x55f364919060>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x55f364919060>
> .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: 0x55f3655789c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55f3655789c0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x55f3655789c0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x55f3655789c0>
> 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: 0x55f3655bcca0>
> .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: 0x55f3655bcca0>
> rm(P)
>
> proc.time()
user system elapsed
0.286 0.019 0.296
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.0 RC (2024-04-16 r86468) -- "Puppy Cup"
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
0.254 0.040 0.284