Ben Bolstad
| Snapshot Date: 2024-03-27 14:00:18 -0400 (Wed, 27 Mar 2024) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 9250806 |
| git_last_commit_date: 2023-10-24 09:37:50 -0400 (Tue, 24 Oct 2023) |
| Back to Multiple platform build/check report for BioC 3.19: simplified long |
|
This page was generated on 2024-03-28 11:36:15 -0400 (Thu, 28 Mar 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | R Under development (unstable) (2024-03-18 r86148) -- "Unsuffered Consequences" | 4708 |
| palomino3 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2024-03-16 r86144 ucrt) -- "Unsuffered Consequences" | 4446 |
| lconway | macOS 12.7.1 Monterey | x86_64 | R Under development (unstable) (2024-03-18 r86148) -- "Unsuffered Consequences" | 4471 |
| kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | R Under development (unstable) (2024-03-19 r86153) -- "Unsuffered Consequences" | 4426 |
| 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 247/2270 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.67.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kunpeng2 | Linux (openEuler 22.03 LTS-SP1) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.67.0 |
| 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_1.67.0.tar.gz |
| StartedAt: 2024-03-27 20:49:10 -0400 (Wed, 27 Mar 2024) |
| EndedAt: 2024-03-27 20:49:34 -0400 (Wed, 27 Mar 2024) |
| EllapsedTime: 24.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### 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_1.67.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2024-03-18 r86148)
* 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 ‘1.67.0’
* 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 Under development (unstable) (2024-03-18 r86148) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.285 0.037 0.311
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2024-03-18 r86148) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/home/biocbuild/bbs-3.19-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 471733 25.2 1025798 54.8 644020 34.4
Vcells 871903 6.7 8388608 64.0 2046929 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 Mar 27 20:49:25 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 Mar 27 20:49:25 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: 0x55c6ffdd1240>
>
>
>
> 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 Mar 27 20:49:26 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 Mar 27 20:49:26 2024"
>
> ColMode(tmp2)
<pointer: 0x55c6ffdd1240>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 101.8558409 -0.1749566 0.68086761 0.8640821
[2,] -0.4036520 -0.2033412 0.33240695 -0.4668665
[3,] -0.3182562 0.6295775 0.05397901 0.5381864
[4,] 0.6252805 -0.9463793 -0.64709669 -0.3177640
> 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,] 101.8558409 0.1749566 0.68086761 0.8640821
[2,] 0.4036520 0.2033412 0.33240695 0.4668665
[3,] 0.3182562 0.6295775 0.05397901 0.5381864
[4,] 0.6252805 0.9463793 0.64709669 0.3177640
> 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,] 10.0923655 0.4182782 0.8251470 0.9295602
[2,] 0.6353361 0.4509337 0.5765474 0.6832763
[3,] 0.5641420 0.7934592 0.2323338 0.7336119
[4,] 0.7907468 0.9728203 0.8044232 0.5637056
>
> 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,] 227.77950 29.35774 33.93234 35.15968
[2,] 31.75701 29.71268 31.09788 32.29963
[3,] 30.95968 33.56417 27.37732 32.87431
[4,] 33.53275 35.67458 33.69133 30.95482
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x55c7011530d0>
> exp(tmp5)
<pointer: 0x55c7011530d0>
> log(tmp5,2)
<pointer: 0x55c7011530d0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 474.0932
> Min(tmp5)
[1] 52.26901
> mean(tmp5)
[1] 71.71613
> Sum(tmp5)
[1] 14343.23
> Var(tmp5)
[1] 894.6939
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 86.36819 69.24963 69.65166 71.79798 68.24033 69.43233 71.50918 67.57305
[9] 73.61084 69.72810
> rowSums(tmp5)
[1] 1727.364 1384.993 1393.033 1435.960 1364.807 1388.647 1430.184 1351.461
[9] 1472.217 1394.562
> rowVars(tmp5)
[1] 8361.89036 69.10666 73.60978 86.18329 95.71377 85.57551
[7] 62.91529 68.24295 100.92995 85.43471
> rowSd(tmp5)
[1] 91.443372 8.313041 8.579614 9.283496 9.783341 9.250703 7.931916
[8] 8.260929 10.046390 9.243090
> rowMax(tmp5)
[1] 474.09318 90.78461 86.67261 95.15200 89.25669 83.58634 87.88001
[8] 86.25566 86.74080 88.87848
> rowMin(tmp5)
[1] 57.22143 57.42924 56.98230 52.90670 55.34964 53.53500 59.37429 54.06437
[9] 52.26901 54.12190
>
> colMeans(tmp5)
[1] 108.49425 71.93159 65.51355 70.25888 68.21653 70.17238 70.31157
[8] 68.38433 76.81323 73.74866 72.11412 68.77239 71.93725 70.47954
[15] 69.84720 67.42684 66.10861 60.23191 72.46562 71.09413
> colSums(tmp5)
[1] 1084.9425 719.3159 655.1355 702.5888 682.1653 701.7238 703.1157
[8] 683.8433 768.1323 737.4866 721.1412 687.7239 719.3725 704.7954
[15] 698.4720 674.2684 661.0861 602.3191 724.6562 710.9413
> colVars(tmp5)
[1] 16573.19404 104.88542 51.38110 45.21250 51.19761 81.23882
[7] 45.93679 125.65338 70.90069 48.58641 73.30396 21.08416
[13] 99.11587 92.39603 53.94833 93.37808 100.07455 44.42574
[19] 69.16690 106.86145
> colSd(tmp5)
[1] 128.736918 10.241358 7.168061 6.724024 7.155251 9.013258
[7] 6.777668 11.209522 8.420255 6.970395 8.561773 4.591749
[13] 9.955696 9.612285 7.344953 9.663233 10.003727 6.665263
[19] 8.316664 10.337381
> colMax(tmp5)
[1] 474.09318 87.88001 79.14746 85.99178 81.20862 88.87848 80.85340
[8] 95.15200 90.78461 86.25566 86.74080 76.74222 86.47336 83.05940
[15] 83.58634 82.89247 85.45994 71.44408 84.48396 86.67261
> colMin(tmp5)
[1] 58.85713 61.10429 56.98230 62.53247 60.15124 57.66303 60.65540 54.12190
[9] 66.54451 65.81154 60.41207 63.33899 53.85559 57.55301 58.33893 53.62927
[17] 54.06437 52.26901 60.66327 53.53500
>
>
> ### 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] 86.36819 69.24963 69.65166 71.79798 68.24033 NA 71.50918 67.57305
[9] 73.61084 69.72810
> rowSums(tmp5)
[1] 1727.364 1384.993 1393.033 1435.960 1364.807 NA 1430.184 1351.461
[9] 1472.217 1394.562
> rowVars(tmp5)
[1] 8361.89036 69.10666 73.60978 86.18329 95.71377 90.28210
[7] 62.91529 68.24295 100.92995 85.43471
> rowSd(tmp5)
[1] 91.443372 8.313041 8.579614 9.283496 9.783341 9.501689 7.931916
[8] 8.260929 10.046390 9.243090
> rowMax(tmp5)
[1] 474.09318 90.78461 86.67261 95.15200 89.25669 NA 87.88001
[8] 86.25566 86.74080 88.87848
> rowMin(tmp5)
[1] 57.22143 57.42924 56.98230 52.90670 55.34964 NA 59.37429 54.06437
[9] 52.26901 54.12190
>
> colMeans(tmp5)
[1] 108.49425 71.93159 65.51355 70.25888 68.21653 70.17238 70.31157
[8] 68.38433 76.81323 73.74866 72.11412 68.77239 71.93725 70.47954
[15] 69.84720 67.42684 66.10861 60.23191 NA 71.09413
> colSums(tmp5)
[1] 1084.9425 719.3159 655.1355 702.5888 682.1653 701.7238 703.1157
[8] 683.8433 768.1323 737.4866 721.1412 687.7239 719.3725 704.7954
[15] 698.4720 674.2684 661.0861 602.3191 NA 710.9413
> colVars(tmp5)
[1] 16573.19404 104.88542 51.38110 45.21250 51.19761 81.23882
[7] 45.93679 125.65338 70.90069 48.58641 73.30396 21.08416
[13] 99.11587 92.39603 53.94833 93.37808 100.07455 44.42574
[19] NA 106.86145
> colSd(tmp5)
[1] 128.736918 10.241358 7.168061 6.724024 7.155251 9.013258
[7] 6.777668 11.209522 8.420255 6.970395 8.561773 4.591749
[13] 9.955696 9.612285 7.344953 9.663233 10.003727 6.665263
[19] NA 10.337381
> colMax(tmp5)
[1] 474.09318 87.88001 79.14746 85.99178 81.20862 88.87848 80.85340
[8] 95.15200 90.78461 86.25566 86.74080 76.74222 86.47336 83.05940
[15] 83.58634 82.89247 85.45994 71.44408 NA 86.67261
> colMin(tmp5)
[1] 58.85713 61.10429 56.98230 62.53247 60.15124 57.66303 60.65540 54.12190
[9] 66.54451 65.81154 60.41207 63.33899 53.85559 57.55301 58.33893 53.62927
[17] 54.06437 52.26901 NA 53.53500
>
> Max(tmp5,na.rm=TRUE)
[1] 474.0932
> Min(tmp5,na.rm=TRUE)
[1] 52.26901
> mean(tmp5,na.rm=TRUE)
[1] 71.72307
> Sum(tmp5,na.rm=TRUE)
[1] 14272.89
> Var(tmp5,na.rm=TRUE)
[1] 899.2029
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 86.36819 69.24963 69.65166 71.79798 68.24033 69.38484 71.50918 67.57305
[9] 73.61084 69.72810
> rowSums(tmp5,na.rm=TRUE)
[1] 1727.364 1384.993 1393.033 1435.960 1364.807 1318.312 1430.184 1351.461
[9] 1472.217 1394.562
> rowVars(tmp5,na.rm=TRUE)
[1] 8361.89036 69.10666 73.60978 86.18329 95.71377 90.28210
[7] 62.91529 68.24295 100.92995 85.43471
> rowSd(tmp5,na.rm=TRUE)
[1] 91.443372 8.313041 8.579614 9.283496 9.783341 9.501689 7.931916
[8] 8.260929 10.046390 9.243090
> rowMax(tmp5,na.rm=TRUE)
[1] 474.09318 90.78461 86.67261 95.15200 89.25669 83.58634 87.88001
[8] 86.25566 86.74080 88.87848
> rowMin(tmp5,na.rm=TRUE)
[1] 57.22143 57.42924 56.98230 52.90670 55.34964 53.53500 59.37429 54.06437
[9] 52.26901 54.12190
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.49425 71.93159 65.51355 70.25888 68.21653 70.17238 70.31157
[8] 68.38433 76.81323 73.74866 72.11412 68.77239 71.93725 70.47954
[15] 69.84720 67.42684 66.10861 60.23191 72.70240 71.09413
> colSums(tmp5,na.rm=TRUE)
[1] 1084.9425 719.3159 655.1355 702.5888 682.1653 701.7238 703.1157
[8] 683.8433 768.1323 737.4866 721.1412 687.7239 719.3725 704.7954
[15] 698.4720 674.2684 661.0861 602.3191 654.3216 710.9413
> colVars(tmp5,na.rm=TRUE)
[1] 16573.19404 104.88542 51.38110 45.21250 51.19761 81.23882
[7] 45.93679 125.65338 70.90069 48.58641 73.30396 21.08416
[13] 99.11587 92.39603 53.94833 93.37808 100.07455 44.42574
[19] 77.18202 106.86145
> colSd(tmp5,na.rm=TRUE)
[1] 128.736918 10.241358 7.168061 6.724024 7.155251 9.013258
[7] 6.777668 11.209522 8.420255 6.970395 8.561773 4.591749
[13] 9.955696 9.612285 7.344953 9.663233 10.003727 6.665263
[19] 8.785330 10.337381
> colMax(tmp5,na.rm=TRUE)
[1] 474.09318 87.88001 79.14746 85.99178 81.20862 88.87848 80.85340
[8] 95.15200 90.78461 86.25566 86.74080 76.74222 86.47336 83.05940
[15] 83.58634 82.89247 85.45994 71.44408 84.48396 86.67261
> colMin(tmp5,na.rm=TRUE)
[1] 58.85713 61.10429 56.98230 62.53247 60.15124 57.66303 60.65540 54.12190
[9] 66.54451 65.81154 60.41207 63.33899 53.85559 57.55301 58.33893 53.62927
[17] 54.06437 52.26901 60.66327 53.53500
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 86.36819 69.24963 69.65166 71.79798 68.24033 NaN 71.50918 67.57305
[9] 73.61084 69.72810
> rowSums(tmp5,na.rm=TRUE)
[1] 1727.364 1384.993 1393.033 1435.960 1364.807 0.000 1430.184 1351.461
[9] 1472.217 1394.562
> rowVars(tmp5,na.rm=TRUE)
[1] 8361.89036 69.10666 73.60978 86.18329 95.71377 NA
[7] 62.91529 68.24295 100.92995 85.43471
> rowSd(tmp5,na.rm=TRUE)
[1] 91.443372 8.313041 8.579614 9.283496 9.783341 NA 7.931916
[8] 8.260929 10.046390 9.243090
> rowMax(tmp5,na.rm=TRUE)
[1] 474.09318 90.78461 86.67261 95.15200 89.25669 NA 87.88001
[8] 86.25566 86.74080 88.87848
> rowMin(tmp5,na.rm=TRUE)
[1] 57.22143 57.42924 56.98230 52.90670 55.34964 NA 59.37429 54.06437
[9] 52.26901 54.12190
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.77925 70.64666 64.96495 69.71567 67.27135 70.26760 71.38448
[8] 68.44065 76.98647 73.89411 71.57989 69.15419 73.94632 69.11178
[15] 68.32063 67.96927 65.64365 60.57322 NaN 73.04515
> colSums(tmp5,na.rm=TRUE)
[1] 1024.0133 635.8199 584.6846 627.4411 605.4421 632.4084 642.4603
[8] 615.9658 692.8782 665.0470 644.2190 622.3877 665.5169 622.0060
[15] 614.8857 611.7235 590.7929 545.1590 0.0000 657.4063
> colVars(tmp5,na.rm=TRUE)
[1] 18330.61682 99.42184 54.41792 47.54448 47.54689 91.29168
[7] 38.72864 141.32437 79.42564 54.42172 79.25617 22.07972
[13] 66.09611 82.89939 34.47464 101.74018 110.15182 48.66836
[19] NA 77.39648
> colSd(tmp5,na.rm=TRUE)
[1] 135.390608 9.971050 7.376850 6.895251 6.895425 9.554668
[7] 6.223234 11.887993 8.912106 7.377108 8.902593 4.698906
[13] 8.129952 9.104910 5.871511 10.086633 10.495324 6.976271
[19] NA 8.797527
> colMax(tmp5,na.rm=TRUE)
[1] 474.09318 87.88001 79.14746 85.99178 81.20862 88.87848 80.85340
[8] 95.15200 90.78461 86.25566 86.74080 76.74222 86.47336 83.05940
[15] 80.32980 82.89247 85.45994 71.44408 -Inf 86.67261
> colMin(tmp5,na.rm=TRUE)
[1] 58.85713 61.10429 56.98230 62.53247 60.15124 57.66303 63.48185 54.12190
[9] 66.54451 65.81154 60.41207 63.33899 62.46995 57.55301 58.33893 53.62927
[17] 54.06437 52.26901 Inf 61.57813
>
>
>
>
> 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] 221.0717 210.6939 220.7339 272.7135 213.9229 247.4090 131.2120 383.6726
[9] 225.8654 223.0103
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 221.0717 210.6939 220.7339 272.7135 213.9229 247.4090 131.2120 383.6726
[9] 225.8654 223.0103
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -1.421085e-14 -1.136868e-13 5.684342e-14 0.000000e+00 -1.989520e-13
[6] -1.705303e-13 5.684342e-14 -1.705303e-13 1.421085e-13 -1.421085e-13
[11] 0.000000e+00 1.705303e-13 0.000000e+00 -2.842171e-14 5.684342e-14
[16] -1.705303e-13 -2.273737e-13 -1.421085e-13 1.136868e-13 2.842171e-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)
+ }
3 15
3 20
1 17
6 8
1 16
5 16
6 5
9 14
6 15
2 4
3 13
2 1
8 20
6 14
1 12
8 3
7 13
8 13
5 8
1 16
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] 2.354001
> Min(tmp)
[1] -2.672615
> mean(tmp)
[1] 0.0993358
> Sum(tmp)
[1] 9.93358
> Var(tmp)
[1] 0.8283716
>
> rowMeans(tmp)
[1] 0.0993358
> rowSums(tmp)
[1] 9.93358
> rowVars(tmp)
[1] 0.8283716
> rowSd(tmp)
[1] 0.9101492
> rowMax(tmp)
[1] 2.354001
> rowMin(tmp)
[1] -2.672615
>
> colMeans(tmp)
[1] 1.713278515 -1.575964638 1.056691347 -2.272993842 -0.296305509
[6] 1.009676244 -2.672614834 0.237449858 -0.801368061 0.828698402
[11] 0.097315555 1.230757898 1.367920138 0.262177248 -1.235451751
[16] 0.146982217 0.701966284 0.561562087 -0.841527259 -1.224304521
[21] 0.415128281 -0.334676112 0.593310506 -0.140748527 -0.211388433
[26] -0.252959330 -0.636465075 -1.061240957 0.534125745 0.514981640
[31] 0.034202669 -0.728480617 -0.457400972 0.460809357 -0.690582516
[36] 0.724958671 0.966738971 0.928863420 -0.199797971 1.826468501
[41] -0.022616009 0.220776014 0.388809956 1.972102596 0.132674401
[46] 0.826554303 1.041484168 0.711387380 0.755063732 -0.198676440
[51] 0.397611119 -0.525336615 0.365045944 0.986256762 0.108286049
[56] 1.709404303 0.516448035 1.437073767 -0.424479633 0.952013609
[61] -1.003413822 -1.538449934 0.378230110 -0.866861254 0.728982549
[66] 0.029176875 0.182514306 -0.812368225 -0.279263699 2.295849992
[71] -1.682825886 0.009018416 0.271216418 -0.099046924 0.484563578
[76] -1.109018472 0.094663370 -0.647679852 -0.468494340 -0.215747693
[81] 2.354000556 0.522668908 0.184276104 0.051085555 -0.622908564
[86] 0.354016728 -1.546502166 -0.045392643 -0.751334901 0.572459473
[91] -1.144543675 -0.118034032 0.232861736 0.965617232 0.368624866
[96] -0.165963414 -0.288297289 0.322505357 0.370600922 0.637117172
> colSums(tmp)
[1] 1.713278515 -1.575964638 1.056691347 -2.272993842 -0.296305509
[6] 1.009676244 -2.672614834 0.237449858 -0.801368061 0.828698402
[11] 0.097315555 1.230757898 1.367920138 0.262177248 -1.235451751
[16] 0.146982217 0.701966284 0.561562087 -0.841527259 -1.224304521
[21] 0.415128281 -0.334676112 0.593310506 -0.140748527 -0.211388433
[26] -0.252959330 -0.636465075 -1.061240957 0.534125745 0.514981640
[31] 0.034202669 -0.728480617 -0.457400972 0.460809357 -0.690582516
[36] 0.724958671 0.966738971 0.928863420 -0.199797971 1.826468501
[41] -0.022616009 0.220776014 0.388809956 1.972102596 0.132674401
[46] 0.826554303 1.041484168 0.711387380 0.755063732 -0.198676440
[51] 0.397611119 -0.525336615 0.365045944 0.986256762 0.108286049
[56] 1.709404303 0.516448035 1.437073767 -0.424479633 0.952013609
[61] -1.003413822 -1.538449934 0.378230110 -0.866861254 0.728982549
[66] 0.029176875 0.182514306 -0.812368225 -0.279263699 2.295849992
[71] -1.682825886 0.009018416 0.271216418 -0.099046924 0.484563578
[76] -1.109018472 0.094663370 -0.647679852 -0.468494340 -0.215747693
[81] 2.354000556 0.522668908 0.184276104 0.051085555 -0.622908564
[86] 0.354016728 -1.546502166 -0.045392643 -0.751334901 0.572459473
[91] -1.144543675 -0.118034032 0.232861736 0.965617232 0.368624866
[96] -0.165963414 -0.288297289 0.322505357 0.370600922 0.637117172
> 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] 1.713278515 -1.575964638 1.056691347 -2.272993842 -0.296305509
[6] 1.009676244 -2.672614834 0.237449858 -0.801368061 0.828698402
[11] 0.097315555 1.230757898 1.367920138 0.262177248 -1.235451751
[16] 0.146982217 0.701966284 0.561562087 -0.841527259 -1.224304521
[21] 0.415128281 -0.334676112 0.593310506 -0.140748527 -0.211388433
[26] -0.252959330 -0.636465075 -1.061240957 0.534125745 0.514981640
[31] 0.034202669 -0.728480617 -0.457400972 0.460809357 -0.690582516
[36] 0.724958671 0.966738971 0.928863420 -0.199797971 1.826468501
[41] -0.022616009 0.220776014 0.388809956 1.972102596 0.132674401
[46] 0.826554303 1.041484168 0.711387380 0.755063732 -0.198676440
[51] 0.397611119 -0.525336615 0.365045944 0.986256762 0.108286049
[56] 1.709404303 0.516448035 1.437073767 -0.424479633 0.952013609
[61] -1.003413822 -1.538449934 0.378230110 -0.866861254 0.728982549
[66] 0.029176875 0.182514306 -0.812368225 -0.279263699 2.295849992
[71] -1.682825886 0.009018416 0.271216418 -0.099046924 0.484563578
[76] -1.109018472 0.094663370 -0.647679852 -0.468494340 -0.215747693
[81] 2.354000556 0.522668908 0.184276104 0.051085555 -0.622908564
[86] 0.354016728 -1.546502166 -0.045392643 -0.751334901 0.572459473
[91] -1.144543675 -0.118034032 0.232861736 0.965617232 0.368624866
[96] -0.165963414 -0.288297289 0.322505357 0.370600922 0.637117172
> colMin(tmp)
[1] 1.713278515 -1.575964638 1.056691347 -2.272993842 -0.296305509
[6] 1.009676244 -2.672614834 0.237449858 -0.801368061 0.828698402
[11] 0.097315555 1.230757898 1.367920138 0.262177248 -1.235451751
[16] 0.146982217 0.701966284 0.561562087 -0.841527259 -1.224304521
[21] 0.415128281 -0.334676112 0.593310506 -0.140748527 -0.211388433
[26] -0.252959330 -0.636465075 -1.061240957 0.534125745 0.514981640
[31] 0.034202669 -0.728480617 -0.457400972 0.460809357 -0.690582516
[36] 0.724958671 0.966738971 0.928863420 -0.199797971 1.826468501
[41] -0.022616009 0.220776014 0.388809956 1.972102596 0.132674401
[46] 0.826554303 1.041484168 0.711387380 0.755063732 -0.198676440
[51] 0.397611119 -0.525336615 0.365045944 0.986256762 0.108286049
[56] 1.709404303 0.516448035 1.437073767 -0.424479633 0.952013609
[61] -1.003413822 -1.538449934 0.378230110 -0.866861254 0.728982549
[66] 0.029176875 0.182514306 -0.812368225 -0.279263699 2.295849992
[71] -1.682825886 0.009018416 0.271216418 -0.099046924 0.484563578
[76] -1.109018472 0.094663370 -0.647679852 -0.468494340 -0.215747693
[81] 2.354000556 0.522668908 0.184276104 0.051085555 -0.622908564
[86] 0.354016728 -1.546502166 -0.045392643 -0.751334901 0.572459473
[91] -1.144543675 -0.118034032 0.232861736 0.965617232 0.368624866
[96] -0.165963414 -0.288297289 0.322505357 0.370600922 0.637117172
> colMedians(tmp)
[1] 1.713278515 -1.575964638 1.056691347 -2.272993842 -0.296305509
[6] 1.009676244 -2.672614834 0.237449858 -0.801368061 0.828698402
[11] 0.097315555 1.230757898 1.367920138 0.262177248 -1.235451751
[16] 0.146982217 0.701966284 0.561562087 -0.841527259 -1.224304521
[21] 0.415128281 -0.334676112 0.593310506 -0.140748527 -0.211388433
[26] -0.252959330 -0.636465075 -1.061240957 0.534125745 0.514981640
[31] 0.034202669 -0.728480617 -0.457400972 0.460809357 -0.690582516
[36] 0.724958671 0.966738971 0.928863420 -0.199797971 1.826468501
[41] -0.022616009 0.220776014 0.388809956 1.972102596 0.132674401
[46] 0.826554303 1.041484168 0.711387380 0.755063732 -0.198676440
[51] 0.397611119 -0.525336615 0.365045944 0.986256762 0.108286049
[56] 1.709404303 0.516448035 1.437073767 -0.424479633 0.952013609
[61] -1.003413822 -1.538449934 0.378230110 -0.866861254 0.728982549
[66] 0.029176875 0.182514306 -0.812368225 -0.279263699 2.295849992
[71] -1.682825886 0.009018416 0.271216418 -0.099046924 0.484563578
[76] -1.109018472 0.094663370 -0.647679852 -0.468494340 -0.215747693
[81] 2.354000556 0.522668908 0.184276104 0.051085555 -0.622908564
[86] 0.354016728 -1.546502166 -0.045392643 -0.751334901 0.572459473
[91] -1.144543675 -0.118034032 0.232861736 0.965617232 0.368624866
[96] -0.165963414 -0.288297289 0.322505357 0.370600922 0.637117172
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.713279 -1.575965 1.056691 -2.272994 -0.2963055 1.009676 -2.672615
[2,] 1.713279 -1.575965 1.056691 -2.272994 -0.2963055 1.009676 -2.672615
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.2374499 -0.8013681 0.8286984 0.09731556 1.230758 1.36792 0.2621772
[2,] 0.2374499 -0.8013681 0.8286984 0.09731556 1.230758 1.36792 0.2621772
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.235452 0.1469822 0.7019663 0.5615621 -0.8415273 -1.224305 0.4151283
[2,] -1.235452 0.1469822 0.7019663 0.5615621 -0.8415273 -1.224305 0.4151283
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.3346761 0.5933105 -0.1407485 -0.2113884 -0.2529593 -0.6364651 -1.061241
[2,] -0.3346761 0.5933105 -0.1407485 -0.2113884 -0.2529593 -0.6364651 -1.061241
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.5341257 0.5149816 0.03420267 -0.7284806 -0.457401 0.4608094 -0.6905825
[2,] 0.5341257 0.5149816 0.03420267 -0.7284806 -0.457401 0.4608094 -0.6905825
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.7249587 0.966739 0.9288634 -0.199798 1.826469 -0.02261601 0.220776
[2,] 0.7249587 0.966739 0.9288634 -0.199798 1.826469 -0.02261601 0.220776
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.38881 1.972103 0.1326744 0.8265543 1.041484 0.7113874 0.7550637
[2,] 0.38881 1.972103 0.1326744 0.8265543 1.041484 0.7113874 0.7550637
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.1986764 0.3976111 -0.5253366 0.3650459 0.9862568 0.108286 1.709404
[2,] -0.1986764 0.3976111 -0.5253366 0.3650459 0.9862568 0.108286 1.709404
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.516448 1.437074 -0.4244796 0.9520136 -1.003414 -1.53845 0.3782301
[2,] 0.516448 1.437074 -0.4244796 0.9520136 -1.003414 -1.53845 0.3782301
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.8668613 0.7289825 0.02917687 0.1825143 -0.8123682 -0.2792637 2.29585
[2,] -0.8668613 0.7289825 0.02917687 0.1825143 -0.8123682 -0.2792637 2.29585
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -1.682826 0.009018416 0.2712164 -0.09904692 0.4845636 -1.109018 0.09466337
[2,] -1.682826 0.009018416 0.2712164 -0.09904692 0.4845636 -1.109018 0.09466337
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.6476799 -0.4684943 -0.2157477 2.354001 0.5226689 0.1842761 0.05108555
[2,] -0.6476799 -0.4684943 -0.2157477 2.354001 0.5226689 0.1842761 0.05108555
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.6229086 0.3540167 -1.546502 -0.04539264 -0.7513349 0.5724595 -1.144544
[2,] -0.6229086 0.3540167 -1.546502 -0.04539264 -0.7513349 0.5724595 -1.144544
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.118034 0.2328617 0.9656172 0.3686249 -0.1659634 -0.2882973 0.3225054
[2,] -0.118034 0.2328617 0.9656172 0.3686249 -0.1659634 -0.2882973 0.3225054
[,99] [,100]
[1,] 0.3706009 0.6371172
[2,] 0.3706009 0.6371172
>
>
> Max(tmp2)
[1] 2.430543
> Min(tmp2)
[1] -2.091212
> mean(tmp2)
[1] 0.2984395
> Sum(tmp2)
[1] 29.84395
> Var(tmp2)
[1] 0.8531219
>
> rowMeans(tmp2)
[1] -0.05431999 -0.69682468 1.35989514 -0.13336264 0.59433736 -1.57756807
[7] 1.03635665 -1.18683383 0.03872968 0.51375133 0.28275903 -0.44810751
[13] 1.54194759 -1.26874116 0.27479350 0.68539631 0.66397926 0.33893535
[19] 0.54368451 -0.46585939 0.61388429 1.28442296 -0.04936831 -0.44866047
[25] 1.62134448 -0.73485757 0.72867857 0.78704358 -0.99964617 1.68852523
[31] -1.06728798 0.46856396 0.85349210 1.59577663 0.07739266 2.43054298
[37] -0.20729257 1.08336111 1.23158553 -0.75358758 0.75285432 -0.61150264
[43] 1.25472198 0.33621479 -1.58553560 -0.43581665 1.63363275 0.26041916
[49] 0.51798157 0.95197763 1.75311337 -1.70562773 2.25276354 0.54110103
[55] 0.55796658 0.84406656 -1.00396123 0.45008801 -0.64496953 0.33607456
[61] -2.09121236 0.19836621 0.40060434 -0.59544612 0.23416114 0.94973826
[67] 0.92318839 -0.31982025 0.13574596 -0.34916108 -0.48172186 1.01724150
[73] -0.59091517 0.47660163 -0.23300716 0.45830348 0.04074469 1.45123231
[79] 0.22779693 1.31055023 0.28917382 1.12816662 -0.04714923 0.90870759
[85] 1.87133524 0.42392850 -1.04264977 0.28423972 -1.54918723 0.09936715
[91] 1.33189396 1.31590223 -0.35099335 0.99306995 -0.71060774 1.55563638
[97] 0.10916935 0.23125762 1.36665015 -0.22937627
> rowSums(tmp2)
[1] -0.05431999 -0.69682468 1.35989514 -0.13336264 0.59433736 -1.57756807
[7] 1.03635665 -1.18683383 0.03872968 0.51375133 0.28275903 -0.44810751
[13] 1.54194759 -1.26874116 0.27479350 0.68539631 0.66397926 0.33893535
[19] 0.54368451 -0.46585939 0.61388429 1.28442296 -0.04936831 -0.44866047
[25] 1.62134448 -0.73485757 0.72867857 0.78704358 -0.99964617 1.68852523
[31] -1.06728798 0.46856396 0.85349210 1.59577663 0.07739266 2.43054298
[37] -0.20729257 1.08336111 1.23158553 -0.75358758 0.75285432 -0.61150264
[43] 1.25472198 0.33621479 -1.58553560 -0.43581665 1.63363275 0.26041916
[49] 0.51798157 0.95197763 1.75311337 -1.70562773 2.25276354 0.54110103
[55] 0.55796658 0.84406656 -1.00396123 0.45008801 -0.64496953 0.33607456
[61] -2.09121236 0.19836621 0.40060434 -0.59544612 0.23416114 0.94973826
[67] 0.92318839 -0.31982025 0.13574596 -0.34916108 -0.48172186 1.01724150
[73] -0.59091517 0.47660163 -0.23300716 0.45830348 0.04074469 1.45123231
[79] 0.22779693 1.31055023 0.28917382 1.12816662 -0.04714923 0.90870759
[85] 1.87133524 0.42392850 -1.04264977 0.28423972 -1.54918723 0.09936715
[91] 1.33189396 1.31590223 -0.35099335 0.99306995 -0.71060774 1.55563638
[97] 0.10916935 0.23125762 1.36665015 -0.22937627
> 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] -0.05431999 -0.69682468 1.35989514 -0.13336264 0.59433736 -1.57756807
[7] 1.03635665 -1.18683383 0.03872968 0.51375133 0.28275903 -0.44810751
[13] 1.54194759 -1.26874116 0.27479350 0.68539631 0.66397926 0.33893535
[19] 0.54368451 -0.46585939 0.61388429 1.28442296 -0.04936831 -0.44866047
[25] 1.62134448 -0.73485757 0.72867857 0.78704358 -0.99964617 1.68852523
[31] -1.06728798 0.46856396 0.85349210 1.59577663 0.07739266 2.43054298
[37] -0.20729257 1.08336111 1.23158553 -0.75358758 0.75285432 -0.61150264
[43] 1.25472198 0.33621479 -1.58553560 -0.43581665 1.63363275 0.26041916
[49] 0.51798157 0.95197763 1.75311337 -1.70562773 2.25276354 0.54110103
[55] 0.55796658 0.84406656 -1.00396123 0.45008801 -0.64496953 0.33607456
[61] -2.09121236 0.19836621 0.40060434 -0.59544612 0.23416114 0.94973826
[67] 0.92318839 -0.31982025 0.13574596 -0.34916108 -0.48172186 1.01724150
[73] -0.59091517 0.47660163 -0.23300716 0.45830348 0.04074469 1.45123231
[79] 0.22779693 1.31055023 0.28917382 1.12816662 -0.04714923 0.90870759
[85] 1.87133524 0.42392850 -1.04264977 0.28423972 -1.54918723 0.09936715
[91] 1.33189396 1.31590223 -0.35099335 0.99306995 -0.71060774 1.55563638
[97] 0.10916935 0.23125762 1.36665015 -0.22937627
> rowMin(tmp2)
[1] -0.05431999 -0.69682468 1.35989514 -0.13336264 0.59433736 -1.57756807
[7] 1.03635665 -1.18683383 0.03872968 0.51375133 0.28275903 -0.44810751
[13] 1.54194759 -1.26874116 0.27479350 0.68539631 0.66397926 0.33893535
[19] 0.54368451 -0.46585939 0.61388429 1.28442296 -0.04936831 -0.44866047
[25] 1.62134448 -0.73485757 0.72867857 0.78704358 -0.99964617 1.68852523
[31] -1.06728798 0.46856396 0.85349210 1.59577663 0.07739266 2.43054298
[37] -0.20729257 1.08336111 1.23158553 -0.75358758 0.75285432 -0.61150264
[43] 1.25472198 0.33621479 -1.58553560 -0.43581665 1.63363275 0.26041916
[49] 0.51798157 0.95197763 1.75311337 -1.70562773 2.25276354 0.54110103
[55] 0.55796658 0.84406656 -1.00396123 0.45008801 -0.64496953 0.33607456
[61] -2.09121236 0.19836621 0.40060434 -0.59544612 0.23416114 0.94973826
[67] 0.92318839 -0.31982025 0.13574596 -0.34916108 -0.48172186 1.01724150
[73] -0.59091517 0.47660163 -0.23300716 0.45830348 0.04074469 1.45123231
[79] 0.22779693 1.31055023 0.28917382 1.12816662 -0.04714923 0.90870759
[85] 1.87133524 0.42392850 -1.04264977 0.28423972 -1.54918723 0.09936715
[91] 1.33189396 1.31590223 -0.35099335 0.99306995 -0.71060774 1.55563638
[97] 0.10916935 0.23125762 1.36665015 -0.22937627
>
> colMeans(tmp2)
[1] 0.2984395
> colSums(tmp2)
[1] 29.84395
> colVars(tmp2)
[1] 0.8531219
> colSd(tmp2)
[1] 0.923646
> colMax(tmp2)
[1] 2.430543
> colMin(tmp2)
[1] -2.091212
> colMedians(tmp2)
[1] 0.3361447
> colRanges(tmp2)
[,1]
[1,] -2.091212
[2,] 2.430543
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.856453 -2.635592 3.526368 1.207049 -1.271950 -1.134287 4.902460
[8] -1.731351 -0.698034 3.025040
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.4802207
[2,] -0.5413310
[3,] 0.1495051
[4,] 0.9225734
[5,] 1.5430418
>
> rowApply(tmp,sum)
[1] 4.6817369 3.8590388 1.8286492 -4.3862375 -2.0669326 0.4135001
[7] -0.9214540 2.3688027 0.7314069 0.5376458
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 9 4 9 10 3 3 9 1 4
[2,] 2 7 1 3 6 1 7 2 8 10
[3,] 10 6 7 7 8 2 10 5 2 8
[4,] 4 4 2 4 5 9 4 7 6 6
[5,] 3 2 8 2 2 6 9 1 9 9
[6,] 1 3 5 10 3 5 2 8 10 7
[7,] 7 10 10 6 7 7 6 6 5 2
[8,] 8 1 6 1 4 8 5 3 7 3
[9,] 6 8 3 5 1 4 8 4 4 5
[10,] 9 5 9 8 9 10 1 10 3 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.5106001 -0.3817959 5.3525020 3.4961560 -1.8461473 0.6066638
[7] 1.1369664 -2.7347472 -1.4793899 1.5232368 1.4192434 -1.7470224
[13] -3.6135242 -1.7259064 -2.0068809 1.0852573 3.9336308 1.9956039
[19] 1.3300615 -1.4442868
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.9237985
[2,] -0.6854959
[3,] -0.6655892
[4,] -0.6410587
[5,] 0.4053423
>
> rowApply(tmp,sum)
[1] -2.8707872 -2.2232227 2.9865955 0.4297994 4.0666358
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 7 7 4 6 13
[2,] 14 6 10 10 11
[3,] 12 17 7 20 20
[4,] 20 19 8 19 7
[5,] 19 4 6 3 9
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.6854959 0.40443602 0.0879219 1.3301489 1.3020890 0.248655559
[2,] -0.6410587 -0.65241334 0.7918969 1.3434296 -1.3330043 -0.005083735
[3,] -0.9237985 -0.03789595 -0.4737275 -0.4062025 -0.5165118 1.412093887
[4,] -0.6655892 -0.12975999 2.1427412 1.6172854 -1.0404149 -0.665504287
[5,] 0.4053423 0.03383740 2.8036695 -0.3885055 -0.2583054 -0.383497667
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.7175774 -1.03126410 -1.7091770 -0.318040764 -1.3716605 0.4490854
[2,] 0.3999476 -1.42673831 1.0306714 1.851023034 -0.4650252 -1.9278493
[3,] -1.0863419 0.20236809 -0.3422216 1.043222533 1.4270438 0.5887836
[4,] 0.8392862 -0.03753305 0.3779028 -1.044986681 -0.3674200 -1.5943786
[5,] 0.2664970 -0.44157981 -0.8365656 -0.007981369 2.1963052 0.7373365
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.63150439 -0.203615139 -0.7904020 0.76324390 -1.0322576 -0.6991294
[2,] -0.08518696 0.000738533 0.1880690 -0.66633350 0.3891148 -1.6108201
[3,] -0.72088446 0.165123398 -1.7601549 -0.96224211 2.0839633 2.9804612
[4,] -0.36466253 -0.857400133 -0.8335851 -0.05846936 0.7179301 0.8859342
[5,] -1.81128588 -0.830753061 1.1891921 2.00905837 1.7748801 0.4391580
[,19] [,20]
[1,] -0.1513273 0.44992876
[2,] 0.7464274 -0.15102766
[3,] 0.2584692 0.05504760
[4,] 1.4667792 0.04164397
[5,] -0.9902870 -1.83987945
>
>
> 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 : 654 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 : 565 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 -0.1687895 0.3995764 0.8678538 0.2792613 -0.5697195 1.654112 0.7346743
col8 col9 col10 col11 col12 col13 col14
row1 -0.4861671 0.3021208 0.5896845 0.3004523 -1.115783 0.2057328 0.3220835
col15 col16 col17 col18 col19 col20
row1 -0.3119627 -0.6079042 -0.07661919 -0.4814981 -0.7208153 -1.264042
> tmp[,"col10"]
col10
row1 0.58968448
row2 1.09083356
row3 0.22369331
row4 0.20749982
row5 -0.02612333
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.1687895 0.3995764 0.8678538 0.2792613 -0.5697195 1.654112 0.7346743
row5 0.1344235 -0.9275174 -1.5189912 -0.1656378 0.8482474 -2.156468 1.2200215
col8 col9 col10 col11 col12 col13
row1 -0.4861671 0.3021208 0.58968448 0.3004523 -1.1157831 0.2057328
row5 -0.6740755 -0.3022513 -0.02612333 -2.6405305 -0.3275123 0.3056205
col14 col15 col16 col17 col18 col19
row1 0.3220835 -0.3119627 -0.6079042 -0.07661919 -0.4814981 -0.7208153
row5 0.1221049 -0.6884565 -1.8034130 0.72583307 0.5766869 1.2798677
col20
row1 -1.2640423
row5 -0.8944139
> tmp[,c("col6","col20")]
col6 col20
row1 1.65411175 -1.2640423
row2 -0.07354717 0.1895382
row3 -0.38034718 1.4755063
row4 -1.30612767 0.1003543
row5 -2.15646762 -0.8944139
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.654112 -1.2640423
row5 -2.156468 -0.8944139
>
>
>
>
> 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 50.05374 48.50151 50.28174 51.53117 48.91448 104.082 50.11706 50.1178
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.53327 48.61238 50.29071 49.77229 50.1943 49.8261 48.67918 50.1978
col17 col18 col19 col20
row1 51.00629 49.11221 50.85458 104.7155
> tmp[,"col10"]
col10
row1 48.61238
row2 29.07039
row3 28.63987
row4 31.38293
row5 49.79842
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.05374 48.50151 50.28174 51.53117 48.91448 104.0820 50.11706 50.11780
row5 49.80464 50.24627 48.51868 48.93986 50.27006 105.1412 48.86384 52.27104
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.53327 48.61238 50.29071 49.77229 50.19430 49.82610 48.67918 50.19780
row5 50.23904 49.79842 50.11639 50.30451 49.14076 48.72486 50.03703 50.99952
col17 col18 col19 col20
row1 51.00629 49.11221 50.85458 104.7155
row5 48.79305 49.74184 51.18365 104.4929
> tmp[,c("col6","col20")]
col6 col20
row1 104.08195 104.71546
row2 74.16105 75.60716
row3 74.58789 77.01459
row4 75.58808 76.60234
row5 105.14125 104.49287
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.0820 104.7155
row5 105.1412 104.4929
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.0820 104.7155
row5 105.1412 104.4929
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.8360259
[2,] -0.8249702
[3,] 0.1639967
[4,] -0.4007516
[5,] 0.2183127
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.5557322 0.388689827
[2,] 0.9086763 0.001270262
[3,] 0.8522526 0.025059223
[4,] 0.5031926 -0.496595395
[5,] -0.3624985 -2.487038128
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.9312069 1.0506747
[2,] -1.5730644 0.2904529
[3,] -0.5185144 1.0597695
[4,] 0.2018226 -2.2324054
[5,] 0.3481039 -1.4060544
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.9312069
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.9312069
[2,] -1.5730644
>
>
>
> 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 -1.273968 -1.2934491 0.1610124 -2.285797 -0.7964211 -0.003192139
row1 -1.893546 -0.4115057 1.1818053 1.594648 -2.0025332 -0.517236289
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 0.45185023 0.8878188 0.4526914 -2.001896 0.1646280 0.9078968 0.3695702
row1 0.09661908 -0.7785472 0.6745115 0.759813 0.1881928 1.9650180 -0.1698925
[,14] [,15] [,16] [,17] [,18] [,19]
row3 0.3198826 -0.8319643 0.1544049 0.3753692 0.04441278 0.34093658
row1 0.3443747 -1.0370136 0.7288714 1.0231674 -1.36073629 -0.02125454
[,20]
row3 -0.5634143
row1 0.5834470
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.385977 -0.7129176 -1.129317 -1.268033 1.939977 2.294986 -0.6442971
[,8] [,9] [,10]
row2 -0.3151353 -1.127945 -2.109186
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.345293 0.148582 1.133535 -0.4495897 -0.5333647 -1.16665 -0.6385092
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.7059176 -1.072618 -0.7405061 -0.9063735 -0.8603509 0.4392058 -0.06741133
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.951515 -0.588981 -0.3719432 0.7547068 0.4565875 0.201219
>
>
> 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: 0x55c6ffde54b0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc8f312ec1066"
[2] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc8f37cb7ae2f"
[3] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc8f35f88a61b"
[4] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc8f3238ac8d8"
[5] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc8f341d18099"
[6] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc8f321780e6b"
[7] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc8f3268371a8"
[8] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc8f341d94625"
[9] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc8f3b3fcd0e"
[10] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc8f3537ef912"
[11] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc8f3e6d9429"
[12] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc8f35be3446c"
[13] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc8f3580e5b54"
[14] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc8f372a4d27"
[15] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc8f32d0dcffa"
>
>
> ### 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: 0x55c7010cf750>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x55c7010cf750>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x55c7010cf750>
> rowMedians(tmp)
[1] 0.179568863 -0.533273971 0.671875129 -0.496796087 -0.676492248
[6] -0.113340187 -0.613413395 -0.163787859 -0.190422973 -0.076336219
[11] 0.175715049 -0.166304967 0.320942058 0.066075654 -0.219731860
[16] 0.365517838 0.212309459 0.478903525 -0.324489511 -0.152204154
[21] 0.133056223 -0.005592004 0.207456717 0.301953079 0.122669950
[26] -0.297605325 -0.023587668 0.172043557 0.126589612 -0.819631328
[31] 0.071200592 0.296630671 0.273180499 -0.080207524 -0.119752885
[36] -0.141727832 -0.183291037 -0.357897407 -0.126411262 -0.390527578
[41] 0.136093957 -0.001930305 1.032089914 -0.245700317 0.038630260
[46] 0.237219378 0.338216526 -0.179605629 0.166823391 0.036709905
[51] 0.028321269 0.322800241 -0.209294525 -0.275412181 0.080831836
[56] 0.122566071 -0.618408026 -0.020150113 -0.076805734 -0.438393176
[61] -0.249293767 -0.260631675 0.573361846 -0.052861580 -0.463024585
[66] 0.075061570 0.044987724 -0.274652047 -0.012177955 -0.079868269
[71] 0.390646629 -0.291472389 0.376155082 0.504400138 -0.034385733
[76] -0.391752359 -0.540460546 -0.344513620 -0.343554165 -0.448638169
[81] -0.363448228 0.102785914 -0.104207224 -0.553985008 -0.332151240
[86] -0.252207884 -0.515611575 -0.048639856 0.520441333 -0.234898802
[91] -0.309993081 -0.298114075 -0.689505383 -0.139256193 -0.311049033
[96] 0.100765534 0.392821037 0.061592165 0.051330968 -0.429470363
[101] 0.166765834 -0.157533348 0.857187634 0.567030903 -0.669173232
[106] 0.851145064 0.324096766 0.034071032 0.217008596 -0.035067706
[111] 0.253602437 0.035912845 0.344508182 0.303410891 -0.424067930
[116] -0.330119974 0.160546441 -0.304029693 0.436425770 -0.606785252
[121] 0.477098324 0.214596175 -0.592908548 0.351588664 -0.049866853
[126] -0.223467857 -0.151567857 -0.079549251 -0.042287705 -0.054988278
[131] 0.628883143 0.222126420 0.841564423 -0.007055723 0.470548245
[136] 0.108823424 0.223215021 0.226353313 0.570924191 -0.101290454
[141] 0.294753824 0.096695779 0.033836903 0.034825104 0.476872532
[146] -0.873776288 0.454551666 0.198069709 -0.100613467 -0.641522761
[151] 0.079733188 0.320287716 0.542549537 -0.227279575 0.412085500
[156] 0.064290414 0.069496463 0.140943714 -0.160958392 0.437549208
[161] -0.353666828 0.048406379 -0.129181319 0.507550931 0.250007018
[166] 0.403730342 0.107462556 0.454967327 0.426480080 -0.061077818
[171] -0.163244263 -0.018157893 0.445751341 0.134050341 -0.271688317
[176] 0.359014709 -0.562110776 0.460246423 0.054711626 0.011605830
[181] -0.242574006 0.368827450 0.258458325 -0.241758712 -0.009063432
[186] -0.471057868 0.121471370 0.925308589 0.467114608 -0.295332211
[191] -0.014408758 -0.035882753 0.319174152 0.031719504 -0.484468147
[196] 0.023337762 -0.466253368 0.191100061 0.413638033 -0.343291716
[201] 0.218979692 -0.052518331 -0.142314067 -0.523043757 0.365135568
[206] -0.222363413 0.135267576 -0.219117026 -0.097358263 0.110413410
[211] 0.054011066 0.032064978 -0.443302635 0.417714784 0.221017159
[216] -0.033484076 -0.017619078 0.034838602 0.288133245 -0.109535103
[221] -0.024613665 0.225750092 0.081023649 -0.547074640 -0.230993402
[226] 0.123836119 0.034331134 -0.280603286 0.372018511 -0.285498286
>
> proc.time()
user system elapsed
1.287 1.536 2.840
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2024-03-18 r86148) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x55d757c15240>
> .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: 0x55d757c15240>
> .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: 0x55d757c15240>
> .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: 0x55d757c15240>
> 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: 0x55d758b8cd60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55d758b8cd60>
> .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: 0x55d758b8cd60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55d758b8cd60>
> .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: 0x55d758b8cd60>
> 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: 0x55d75964f830>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55d75964f830>
> .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: 0x55d75964f830>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x55d75964f830>
> .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: 0x55d75964f830>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x55d75964f830>
> .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: 0x55d75964f830>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x55d75964f830>
> .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: 0x55d75964f830>
> 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: 0x55d759698cc0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x55d759698cc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55d759698cc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55d759698cc0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2dcba25fea3ba0" "BufferedMatrixFile2dcba2c68579a"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2dcba25fea3ba0" "BufferedMatrixFile2dcba2c68579a"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x55d758ee27a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55d758ee27a0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x55d758ee27a0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x55d758ee27a0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x55d758ee27a0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x55d758ee27a0>
> .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: 0x55d758ee4f80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55d758ee4f80>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x55d758ee4f80>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x55d758ee4f80>
> 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: 0x55d758eeaa90>
> .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: 0x55d758eeaa90>
> rm(P)
>
> proc.time()
user system elapsed
0.250 0.057 0.297
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2024-03-18 r86148) -- "Unsuffered Consequences"
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Platform: x86_64-pc-linux-gnu
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Type 'license()' or 'licence()' for distribution details.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.258 0.041 0.288