Ben Bolstad
| Snapshot Date: 2025-03-13 13:40 -0400 (Thu, 13 Mar 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 824836d |
| git_last_commit_date: 2024-12-14 17:47:34 -0400 (Sat, 14 Dec 2024) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-03-14 11:39 -0400 (Fri, 14 Mar 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4781 |
| palomino7 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2025-03-01 r87860 ucrt) -- "Unsuffered Consequences" | 4537 |
| lconway | macOS 12.7.1 Monterey | x86_64 | R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences" | 4567 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences" | 4519 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4451 |
| 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 248/2309 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.71.1 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.1 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| kunpeng2 | Linux (openEuler 24.03 LTS) / 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: 1.71.1 |
| Command: /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.21-bioc/R/site-library --timings BufferedMatrix_1.71.1.tar.gz |
| StartedAt: 2025-03-13 20:22:25 -0400 (Thu, 13 Mar 2025) |
| EndedAt: 2025-03-13 20:22:50 -0400 (Thu, 13 Mar 2025) |
| EllapsedTime: 25.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.21-bioc/R/site-library --timings BufferedMatrix_1.71.1.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2025-02-19 r87757)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.2 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.71.1’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
* 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-3.21-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.21-bioc/R/bin/R CMD INSTALL BufferedMatrix ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.21-bioc/R/site-library’ * installing *source* package ‘BufferedMatrix’ ... ** this is package ‘BufferedMatrix’ version ‘1.71.1’ ** using staged installation ** libs using C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’ gcc -std=gnu2x -I"/home/biocbuild/bbs-3.21-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o gcc -std=gnu2x -I"/home/biocbuild/bbs-3.21-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o gcc -std=gnu2x -I"/home/biocbuild/bbs-3.21-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o gcc -std=gnu2x -I"/home/biocbuild/bbs-3.21-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -c init_package.c -o init_package.o gcc -std=gnu2x -shared -L/home/biocbuild/bbs-3.21-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-3.21-bioc/R/lib -lR installing to /home/biocbuild/bbs-3.21-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) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 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
0.247 0.056 0.291
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 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-3.21-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 477833 25.6 1045335 55.9 639802 34.2
Vcells 884275 6.8 8388608 64.0 2080986 15.9
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu Mar 13 20:22:40 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu Mar 13 20:22:40 2025"
>
>
> 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: 0x5e623d68cb80>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu Mar 13 20:22:41 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu Mar 13 20:22:41 2025"
>
> ColMode(tmp2)
<pointer: 0x5e623d68cb80>
>
>
>
> ### 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,] 99.8865752 1.3770977 0.200330353 -1.622368
[2,] 0.5127652 0.6391073 0.007943289 1.074620
[3,] 1.2474559 0.1225465 0.530903229 -1.170024
[4,] -0.9703740 1.4018453 -0.925687637 0.489023
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-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,] 99.8865752 1.3770977 0.200330353 1.622368
[2,] 0.5127652 0.6391073 0.007943289 1.074620
[3,] 1.2474559 0.1225465 0.530903229 1.170024
[4,] 0.9703740 1.4018453 0.925687637 0.489023
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9943272 1.1734981 0.44758279 1.2737222
[2,] 0.7160762 0.7994419 0.08912513 1.0366388
[3,] 1.1168957 0.3500664 0.72863106 1.0816764
[4,] 0.9850756 1.1839955 0.96212662 0.6993018
>
> 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-3.21-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,] 224.82985 38.11208 29.67616 39.35959
[2,] 32.67353 33.63353 25.89919 36.44101
[3,] 37.41641 28.62321 32.81721 36.98679
[4,] 35.82113 38.24180 35.54695 32.48204
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5e623c0e6f10>
> exp(tmp5)
<pointer: 0x5e623c0e6f10>
> log(tmp5,2)
<pointer: 0x5e623c0e6f10>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.9539
> Min(tmp5)
[1] 53.90578
> mean(tmp5)
[1] 73.78319
> Sum(tmp5)
[1] 14756.64
> Var(tmp5)
[1] 859.5231
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 93.84801 68.82297 74.38201 71.53470 71.44584 69.20199 75.11010 70.52059
[9] 69.08196 73.88370
> rowSums(tmp5)
[1] 1876.960 1376.459 1487.640 1430.694 1428.917 1384.040 1502.202 1410.412
[9] 1381.639 1477.674
> rowVars(tmp5)
[1] 7866.62307 66.47716 76.85766 55.45104 98.35909 96.43106
[7] 45.67971 52.18083 55.53252 69.22105
> rowSd(tmp5)
[1] 88.693986 8.153353 8.766850 7.446546 9.917615 9.819932 6.758676
[8] 7.223630 7.452015 8.319919
> rowMax(tmp5)
[1] 467.95387 81.98610 92.81798 85.19435 86.78587 85.13768 85.69342
[8] 80.67275 87.43779 89.87976
> rowMin(tmp5)
[1] 55.09996 53.90578 59.57546 56.20429 54.94681 55.57545 62.63533 59.26945
[9] 55.74380 59.22722
>
> colMeans(tmp5)
[1] 111.60261 75.22488 68.23267 75.82441 70.20436 69.48119 74.50724
[8] 71.44742 71.12016 71.04375 71.50370 68.77095 69.97866 72.64404
[15] 68.01659 76.22613 73.27448 74.15956 70.05956 72.34137
> colSums(tmp5)
[1] 1116.0261 752.2488 682.3267 758.2441 702.0436 694.8119 745.0724
[8] 714.4742 711.2016 710.4375 715.0370 687.7095 699.7866 726.4404
[15] 680.1659 762.2613 732.7448 741.5956 700.5956 723.4137
> colVars(tmp5)
[1] 15743.02451 55.91176 112.71428 58.61143 67.39417 86.83702
[7] 38.78733 89.85073 112.84758 65.63914 59.99456 71.40181
[13] 115.38823 100.81717 52.17318 48.71546 110.51200 63.58421
[19] 42.26761 107.52791
> colSd(tmp5)
[1] 125.471210 7.477416 10.616698 7.655810 8.209395 9.318639
[7] 6.227947 9.478962 10.622974 8.101799 7.745616 8.449959
[13] 10.741891 10.040775 7.223100 6.979646 10.512469 7.973971
[19] 6.501354 10.369566
> colMax(tmp5)
[1] 467.95387 87.43779 85.13768 83.64145 83.65741 79.64115 82.30977
[8] 86.78587 85.74958 87.02611 85.69342 84.14895 85.10814 87.34543
[15] 76.39931 85.19435 92.81798 89.87976 77.26463 89.88945
> colMin(tmp5)
[1] 58.02927 59.57546 53.90578 57.74338 59.88574 55.42848 64.62974 59.91703
[9] 55.74380 58.14905 60.70685 54.54316 57.06899 55.57545 54.94681 65.67543
[17] 61.02533 62.78336 55.09996 55.80696
>
>
> ### 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] 93.84801 68.82297 74.38201 71.53470 71.44584 69.20199 75.11010 NA
[9] 69.08196 73.88370
> rowSums(tmp5)
[1] 1876.960 1376.459 1487.640 1430.694 1428.917 1384.040 1502.202 NA
[9] 1381.639 1477.674
> rowVars(tmp5)
[1] 7866.62307 66.47716 76.85766 55.45104 98.35909 96.43106
[7] 45.67971 52.30026 55.53252 69.22105
> rowSd(tmp5)
[1] 88.693986 8.153353 8.766850 7.446546 9.917615 9.819932 6.758676
[8] 7.231892 7.452015 8.319919
> rowMax(tmp5)
[1] 467.95387 81.98610 92.81798 85.19435 86.78587 85.13768 85.69342
[8] NA 87.43779 89.87976
> rowMin(tmp5)
[1] 55.09996 53.90578 59.57546 56.20429 54.94681 55.57545 62.63533 NA
[9] 55.74380 59.22722
>
> colMeans(tmp5)
[1] 111.60261 75.22488 68.23267 75.82441 70.20436 69.48119 74.50724
[8] 71.44742 71.12016 71.04375 71.50370 68.77095 69.97866 NA
[15] 68.01659 76.22613 73.27448 74.15956 70.05956 72.34137
> colSums(tmp5)
[1] 1116.0261 752.2488 682.3267 758.2441 702.0436 694.8119 745.0724
[8] 714.4742 711.2016 710.4375 715.0370 687.7095 699.7866 NA
[15] 680.1659 762.2613 732.7448 741.5956 700.5956 723.4137
> colVars(tmp5)
[1] 15743.02451 55.91176 112.71428 58.61143 67.39417 86.83702
[7] 38.78733 89.85073 112.84758 65.63914 59.99456 71.40181
[13] 115.38823 NA 52.17318 48.71546 110.51200 63.58421
[19] 42.26761 107.52791
> colSd(tmp5)
[1] 125.471210 7.477416 10.616698 7.655810 8.209395 9.318639
[7] 6.227947 9.478962 10.622974 8.101799 7.745616 8.449959
[13] 10.741891 NA 7.223100 6.979646 10.512469 7.973971
[19] 6.501354 10.369566
> colMax(tmp5)
[1] 467.95387 87.43779 85.13768 83.64145 83.65741 79.64115 82.30977
[8] 86.78587 85.74958 87.02611 85.69342 84.14895 85.10814 NA
[15] 76.39931 85.19435 92.81798 89.87976 77.26463 89.88945
> colMin(tmp5)
[1] 58.02927 59.57546 53.90578 57.74338 59.88574 55.42848 64.62974 59.91703
[9] 55.74380 58.14905 60.70685 54.54316 57.06899 NA 54.94681 65.67543
[17] 61.02533 62.78336 55.09996 55.80696
>
> Max(tmp5,na.rm=TRUE)
[1] 467.9539
> Min(tmp5,na.rm=TRUE)
[1] 53.90578
> mean(tmp5,na.rm=TRUE)
[1] 73.76494
> Sum(tmp5,na.rm=TRUE)
[1] 14679.22
> Var(tmp5,na.rm=TRUE)
[1] 863.7972
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.84801 68.82297 74.38201 71.53470 71.44584 69.20199 75.11010 70.15774
[9] 69.08196 73.88370
> rowSums(tmp5,na.rm=TRUE)
[1] 1876.960 1376.459 1487.640 1430.694 1428.917 1384.040 1502.202 1332.997
[9] 1381.639 1477.674
> rowVars(tmp5,na.rm=TRUE)
[1] 7866.62307 66.47716 76.85766 55.45104 98.35909 96.43106
[7] 45.67971 52.30026 55.53252 69.22105
> rowSd(tmp5,na.rm=TRUE)
[1] 88.693986 8.153353 8.766850 7.446546 9.917615 9.819932 6.758676
[8] 7.231892 7.452015 8.319919
> rowMax(tmp5,na.rm=TRUE)
[1] 467.95387 81.98610 92.81798 85.19435 86.78587 85.13768 85.69342
[8] 80.67275 87.43779 89.87976
> rowMin(tmp5,na.rm=TRUE)
[1] 55.09996 53.90578 59.57546 56.20429 54.94681 55.57545 62.63533 59.26945
[9] 55.74380 59.22722
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.60261 75.22488 68.23267 75.82441 70.20436 69.48119 74.50724
[8] 71.44742 71.12016 71.04375 71.50370 68.77095 69.97866 72.11396
[15] 68.01659 76.22613 73.27448 74.15956 70.05956 72.34137
> colSums(tmp5,na.rm=TRUE)
[1] 1116.0261 752.2488 682.3267 758.2441 702.0436 694.8119 745.0724
[8] 714.4742 711.2016 710.4375 715.0370 687.7095 699.7866 649.0257
[15] 680.1659 762.2613 732.7448 741.5956 700.5956 723.4137
> colVars(tmp5,na.rm=TRUE)
[1] 15743.02451 55.91176 112.71428 58.61143 67.39417 86.83702
[7] 38.78733 89.85073 112.84758 65.63914 59.99456 71.40181
[13] 115.38823 110.25826 52.17318 48.71546 110.51200 63.58421
[19] 42.26761 107.52791
> colSd(tmp5,na.rm=TRUE)
[1] 125.471210 7.477416 10.616698 7.655810 8.209395 9.318639
[7] 6.227947 9.478962 10.622974 8.101799 7.745616 8.449959
[13] 10.741891 10.500393 7.223100 6.979646 10.512469 7.973971
[19] 6.501354 10.369566
> colMax(tmp5,na.rm=TRUE)
[1] 467.95387 87.43779 85.13768 83.64145 83.65741 79.64115 82.30977
[8] 86.78587 85.74958 87.02611 85.69342 84.14895 85.10814 87.34543
[15] 76.39931 85.19435 92.81798 89.87976 77.26463 89.88945
> colMin(tmp5,na.rm=TRUE)
[1] 58.02927 59.57546 53.90578 57.74338 59.88574 55.42848 64.62974 59.91703
[9] 55.74380 58.14905 60.70685 54.54316 57.06899 55.57545 54.94681 65.67543
[17] 61.02533 62.78336 55.09996 55.80696
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.84801 68.82297 74.38201 71.53470 71.44584 69.20199 75.11010 NaN
[9] 69.08196 73.88370
> rowSums(tmp5,na.rm=TRUE)
[1] 1876.960 1376.459 1487.640 1430.694 1428.917 1384.040 1502.202 0.000
[9] 1381.639 1477.674
> rowVars(tmp5,na.rm=TRUE)
[1] 7866.62307 66.47716 76.85766 55.45104 98.35909 96.43106
[7] 45.67971 NA 55.53252 69.22105
> rowSd(tmp5,na.rm=TRUE)
[1] 88.693986 8.153353 8.766850 7.446546 9.917615 9.819932 6.758676
[8] NA 7.452015 8.319919
> rowMax(tmp5,na.rm=TRUE)
[1] 467.95387 81.98610 92.81798 85.19435 86.78587 85.13768 85.69342
[8] NA 87.43779 89.87976
> rowMin(tmp5,na.rm=TRUE)
[1] 55.09996 53.90578 59.57546 56.20429 54.94681 55.57545 62.63533 NA
[9] 55.74380 59.22722
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 117.19138 75.13475 67.72473 75.48707 71.35088 68.35231 75.60474
[8] 70.42239 70.53777 71.02795 71.93050 69.21790 69.01975 NaN
[15] 68.98849 76.40142 74.31226 74.96950 69.66412 73.46208
> colSums(tmp5,na.rm=TRUE)
[1] 1054.7224 676.2128 609.5225 679.3837 642.1579 615.1708 680.4427
[8] 633.8015 634.8399 639.2516 647.3745 622.9611 621.1778 0.0000
[15] 620.8965 687.6128 668.8104 674.7255 626.9771 661.1587
> colVars(tmp5,na.rm=TRUE)
[1] 17359.51627 62.80935 123.90097 64.65768 61.03040 83.35489
[7] 30.08506 89.26170 123.13777 73.84122 65.44458 78.07973
[13] 119.46742 NA 48.06808 54.45921 112.20992 64.15222
[19] 45.79187 106.83896
> colSd(tmp5,na.rm=TRUE)
[1] 131.755517 7.925235 11.131081 8.041000 7.812196 9.129890
[7] 5.484985 9.447841 11.096746 8.593092 8.089782 8.836273
[13] 10.930115 NA 6.933115 7.379648 10.592918 8.009508
[19] 6.766969 10.336293
> colMax(tmp5,na.rm=TRUE)
[1] 467.95387 87.43779 85.13768 83.64145 83.65741 78.23371 82.30977
[8] 86.78587 85.74958 87.02611 85.69342 84.14895 85.10814 -Inf
[15] 76.39931 85.19435 92.81798 89.87976 77.26463 89.88945
> colMin(tmp5,na.rm=TRUE)
[1] 58.02927 59.57546 53.90578 57.74338 62.16921 55.42848 68.25450 59.91703
[9] 55.74380 58.14905 60.70685 54.54316 57.06899 Inf 54.94681 65.67543
[17] 61.02533 62.78336 55.09996 55.80696
>
>
>
>
> 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] 217.2282 199.2012 122.0530 245.3524 134.4619 189.7884 266.3850 190.8704
[9] 121.2708 269.8761
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 217.2282 199.2012 122.0530 245.3524 134.4619 189.7884 266.3850 190.8704
[9] 121.2708 269.8761
>
>
>
> 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] -1.136868e-13 0.000000e+00 1.421085e-14 -5.684342e-14 -2.842171e-14
[6] 1.421085e-14 -1.705303e-13 0.000000e+00 2.842171e-13 -1.136868e-13
[11] -2.842171e-14 0.000000e+00 2.842171e-14 2.273737e-13 -4.263256e-13
[16] -1.421085e-13 -2.842171e-14 1.136868e-13 0.000000e+00 5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
4 1
2 11
7 9
9 13
2 18
9 16
1 11
3 10
5 7
7 16
10 6
4 6
2 20
7 1
3 11
10 5
1 4
3 6
3 13
3 19
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] 2.178666
> Min(tmp)
[1] -2.099094
> mean(tmp)
[1] 0.002143267
> Sum(tmp)
[1] 0.2143267
> Var(tmp)
[1] 0.7367972
>
> rowMeans(tmp)
[1] 0.002143267
> rowSums(tmp)
[1] 0.2143267
> rowVars(tmp)
[1] 0.7367972
> rowSd(tmp)
[1] 0.8583689
> rowMax(tmp)
[1] 2.178666
> rowMin(tmp)
[1] -2.099094
>
> colMeans(tmp)
[1] 0.36125747 0.14323540 0.40513656 0.03575163 0.66875909 0.05171213
[7] -1.12416921 0.16545994 0.57302209 0.19677217 0.10810015 -1.78122562
[13] -1.53445596 -0.84273932 0.26027993 0.21073279 0.01577188 0.70354142
[19] -0.57771200 0.12955825 -0.20550799 -0.66209260 0.59266383 1.17445172
[25] -0.86086059 0.24536624 0.27477733 0.86957993 0.34482576 0.04311561
[31] -1.03699626 -2.09909410 0.86829081 -1.76560492 -0.98868980 -0.32913677
[37] 0.27966231 0.74342143 -0.13542158 -1.90403792 0.36182834 -0.14315469
[43] -0.25214461 1.58644727 1.53394536 -2.04938538 -0.54426675 1.54929179
[49] -0.73966597 0.89348164 0.32271954 -0.60269246 0.38828111 1.75211452
[55] 0.18144272 -0.02358513 -0.23305612 0.40572657 0.57923187 -1.04240345
[61] 1.26441524 -0.16703640 -0.21600113 0.27560503 -0.42379558 1.22812733
[67] -1.15317078 -0.54918287 0.31898417 1.08463204 0.28120016 -0.10093868
[73] 0.80543874 -0.57418010 2.17866613 -0.43874397 0.48201360 -0.05488516
[79] 0.23791536 0.88615684 0.13305947 1.20076934 -0.29385841 0.87309348
[85] 0.10921776 -0.83161426 0.06798765 -0.85257394 0.69154512 -1.20095851
[91] -0.36108448 -1.91280473 0.58772018 -0.54155396 -0.68473539 0.95857010
[97] -0.40527996 -0.79544383 0.08609208 0.47930160
> colSums(tmp)
[1] 0.36125747 0.14323540 0.40513656 0.03575163 0.66875909 0.05171213
[7] -1.12416921 0.16545994 0.57302209 0.19677217 0.10810015 -1.78122562
[13] -1.53445596 -0.84273932 0.26027993 0.21073279 0.01577188 0.70354142
[19] -0.57771200 0.12955825 -0.20550799 -0.66209260 0.59266383 1.17445172
[25] -0.86086059 0.24536624 0.27477733 0.86957993 0.34482576 0.04311561
[31] -1.03699626 -2.09909410 0.86829081 -1.76560492 -0.98868980 -0.32913677
[37] 0.27966231 0.74342143 -0.13542158 -1.90403792 0.36182834 -0.14315469
[43] -0.25214461 1.58644727 1.53394536 -2.04938538 -0.54426675 1.54929179
[49] -0.73966597 0.89348164 0.32271954 -0.60269246 0.38828111 1.75211452
[55] 0.18144272 -0.02358513 -0.23305612 0.40572657 0.57923187 -1.04240345
[61] 1.26441524 -0.16703640 -0.21600113 0.27560503 -0.42379558 1.22812733
[67] -1.15317078 -0.54918287 0.31898417 1.08463204 0.28120016 -0.10093868
[73] 0.80543874 -0.57418010 2.17866613 -0.43874397 0.48201360 -0.05488516
[79] 0.23791536 0.88615684 0.13305947 1.20076934 -0.29385841 0.87309348
[85] 0.10921776 -0.83161426 0.06798765 -0.85257394 0.69154512 -1.20095851
[91] -0.36108448 -1.91280473 0.58772018 -0.54155396 -0.68473539 0.95857010
[97] -0.40527996 -0.79544383 0.08609208 0.47930160
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] 0.36125747 0.14323540 0.40513656 0.03575163 0.66875909 0.05171213
[7] -1.12416921 0.16545994 0.57302209 0.19677217 0.10810015 -1.78122562
[13] -1.53445596 -0.84273932 0.26027993 0.21073279 0.01577188 0.70354142
[19] -0.57771200 0.12955825 -0.20550799 -0.66209260 0.59266383 1.17445172
[25] -0.86086059 0.24536624 0.27477733 0.86957993 0.34482576 0.04311561
[31] -1.03699626 -2.09909410 0.86829081 -1.76560492 -0.98868980 -0.32913677
[37] 0.27966231 0.74342143 -0.13542158 -1.90403792 0.36182834 -0.14315469
[43] -0.25214461 1.58644727 1.53394536 -2.04938538 -0.54426675 1.54929179
[49] -0.73966597 0.89348164 0.32271954 -0.60269246 0.38828111 1.75211452
[55] 0.18144272 -0.02358513 -0.23305612 0.40572657 0.57923187 -1.04240345
[61] 1.26441524 -0.16703640 -0.21600113 0.27560503 -0.42379558 1.22812733
[67] -1.15317078 -0.54918287 0.31898417 1.08463204 0.28120016 -0.10093868
[73] 0.80543874 -0.57418010 2.17866613 -0.43874397 0.48201360 -0.05488516
[79] 0.23791536 0.88615684 0.13305947 1.20076934 -0.29385841 0.87309348
[85] 0.10921776 -0.83161426 0.06798765 -0.85257394 0.69154512 -1.20095851
[91] -0.36108448 -1.91280473 0.58772018 -0.54155396 -0.68473539 0.95857010
[97] -0.40527996 -0.79544383 0.08609208 0.47930160
> colMin(tmp)
[1] 0.36125747 0.14323540 0.40513656 0.03575163 0.66875909 0.05171213
[7] -1.12416921 0.16545994 0.57302209 0.19677217 0.10810015 -1.78122562
[13] -1.53445596 -0.84273932 0.26027993 0.21073279 0.01577188 0.70354142
[19] -0.57771200 0.12955825 -0.20550799 -0.66209260 0.59266383 1.17445172
[25] -0.86086059 0.24536624 0.27477733 0.86957993 0.34482576 0.04311561
[31] -1.03699626 -2.09909410 0.86829081 -1.76560492 -0.98868980 -0.32913677
[37] 0.27966231 0.74342143 -0.13542158 -1.90403792 0.36182834 -0.14315469
[43] -0.25214461 1.58644727 1.53394536 -2.04938538 -0.54426675 1.54929179
[49] -0.73966597 0.89348164 0.32271954 -0.60269246 0.38828111 1.75211452
[55] 0.18144272 -0.02358513 -0.23305612 0.40572657 0.57923187 -1.04240345
[61] 1.26441524 -0.16703640 -0.21600113 0.27560503 -0.42379558 1.22812733
[67] -1.15317078 -0.54918287 0.31898417 1.08463204 0.28120016 -0.10093868
[73] 0.80543874 -0.57418010 2.17866613 -0.43874397 0.48201360 -0.05488516
[79] 0.23791536 0.88615684 0.13305947 1.20076934 -0.29385841 0.87309348
[85] 0.10921776 -0.83161426 0.06798765 -0.85257394 0.69154512 -1.20095851
[91] -0.36108448 -1.91280473 0.58772018 -0.54155396 -0.68473539 0.95857010
[97] -0.40527996 -0.79544383 0.08609208 0.47930160
> colMedians(tmp)
[1] 0.36125747 0.14323540 0.40513656 0.03575163 0.66875909 0.05171213
[7] -1.12416921 0.16545994 0.57302209 0.19677217 0.10810015 -1.78122562
[13] -1.53445596 -0.84273932 0.26027993 0.21073279 0.01577188 0.70354142
[19] -0.57771200 0.12955825 -0.20550799 -0.66209260 0.59266383 1.17445172
[25] -0.86086059 0.24536624 0.27477733 0.86957993 0.34482576 0.04311561
[31] -1.03699626 -2.09909410 0.86829081 -1.76560492 -0.98868980 -0.32913677
[37] 0.27966231 0.74342143 -0.13542158 -1.90403792 0.36182834 -0.14315469
[43] -0.25214461 1.58644727 1.53394536 -2.04938538 -0.54426675 1.54929179
[49] -0.73966597 0.89348164 0.32271954 -0.60269246 0.38828111 1.75211452
[55] 0.18144272 -0.02358513 -0.23305612 0.40572657 0.57923187 -1.04240345
[61] 1.26441524 -0.16703640 -0.21600113 0.27560503 -0.42379558 1.22812733
[67] -1.15317078 -0.54918287 0.31898417 1.08463204 0.28120016 -0.10093868
[73] 0.80543874 -0.57418010 2.17866613 -0.43874397 0.48201360 -0.05488516
[79] 0.23791536 0.88615684 0.13305947 1.20076934 -0.29385841 0.87309348
[85] 0.10921776 -0.83161426 0.06798765 -0.85257394 0.69154512 -1.20095851
[91] -0.36108448 -1.91280473 0.58772018 -0.54155396 -0.68473539 0.95857010
[97] -0.40527996 -0.79544383 0.08609208 0.47930160
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.3612575 0.1432354 0.4051366 0.03575163 0.6687591 0.05171213 -1.124169
[2,] 0.3612575 0.1432354 0.4051366 0.03575163 0.6687591 0.05171213 -1.124169
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.1654599 0.5730221 0.1967722 0.1081001 -1.781226 -1.534456 -0.8427393
[2,] 0.1654599 0.5730221 0.1967722 0.1081001 -1.781226 -1.534456 -0.8427393
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.2602799 0.2107328 0.01577188 0.7035414 -0.577712 0.1295583 -0.205508
[2,] 0.2602799 0.2107328 0.01577188 0.7035414 -0.577712 0.1295583 -0.205508
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.6620926 0.5926638 1.174452 -0.8608606 0.2453662 0.2747773 0.8695799
[2,] -0.6620926 0.5926638 1.174452 -0.8608606 0.2453662 0.2747773 0.8695799
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.3448258 0.04311561 -1.036996 -2.099094 0.8682908 -1.765605 -0.9886898
[2,] 0.3448258 0.04311561 -1.036996 -2.099094 0.8682908 -1.765605 -0.9886898
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.3291368 0.2796623 0.7434214 -0.1354216 -1.904038 0.3618283 -0.1431547
[2,] -0.3291368 0.2796623 0.7434214 -0.1354216 -1.904038 0.3618283 -0.1431547
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.2521446 1.586447 1.533945 -2.049385 -0.5442667 1.549292 -0.739666
[2,] -0.2521446 1.586447 1.533945 -2.049385 -0.5442667 1.549292 -0.739666
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.8934816 0.3227195 -0.6026925 0.3882811 1.752115 0.1814427 -0.02358513
[2,] 0.8934816 0.3227195 -0.6026925 0.3882811 1.752115 0.1814427 -0.02358513
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.2330561 0.4057266 0.5792319 -1.042403 1.264415 -0.1670364 -0.2160011
[2,] -0.2330561 0.4057266 0.5792319 -1.042403 1.264415 -0.1670364 -0.2160011
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.275605 -0.4237956 1.228127 -1.153171 -0.5491829 0.3189842 1.084632
[2,] 0.275605 -0.4237956 1.228127 -1.153171 -0.5491829 0.3189842 1.084632
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.2812002 -0.1009387 0.8054387 -0.5741801 2.178666 -0.438744 0.4820136
[2,] 0.2812002 -0.1009387 0.8054387 -0.5741801 2.178666 -0.438744 0.4820136
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.05488516 0.2379154 0.8861568 0.1330595 1.200769 -0.2938584 0.8730935
[2,] -0.05488516 0.2379154 0.8861568 0.1330595 1.200769 -0.2938584 0.8730935
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.1092178 -0.8316143 0.06798765 -0.8525739 0.6915451 -1.200959 -0.3610845
[2,] 0.1092178 -0.8316143 0.06798765 -0.8525739 0.6915451 -1.200959 -0.3610845
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.912805 0.5877202 -0.541554 -0.6847354 0.9585701 -0.40528 -0.7954438
[2,] -1.912805 0.5877202 -0.541554 -0.6847354 0.9585701 -0.40528 -0.7954438
[,99] [,100]
[1,] 0.08609208 0.4793016
[2,] 0.08609208 0.4793016
>
>
> Max(tmp2)
[1] 3.294584
> Min(tmp2)
[1] -2.479939
> mean(tmp2)
[1] -0.03044323
> Sum(tmp2)
[1] -3.044323
> Var(tmp2)
[1] 1.207685
>
> rowMeans(tmp2)
[1] 0.443532158 0.564409985 0.027610491 1.697239404 1.031265486
[6] -0.210011687 -1.081482584 1.368032543 -1.599241044 -0.687324457
[11] 0.890944792 0.180847091 -0.407176299 -0.703630013 -0.698104058
[16] 0.037498960 -0.826614651 -0.537855269 -1.635267082 1.114251361
[21] -1.043875256 0.528796112 0.605618000 3.294584147 -1.903533068
[26] -1.127512723 -1.637951832 0.327333505 0.543746343 -1.659854877
[31] -0.775582392 -0.512641193 -1.413651254 0.228750766 0.593037225
[36] 0.724868492 0.001354165 0.137777456 0.545245145 0.409985541
[41] -0.703684618 -0.513226182 0.057404437 -1.162520245 0.236041399
[46] 1.924290701 1.867705655 -0.292987690 -0.041685183 -0.517255458
[51] 1.625647566 -0.346356304 0.209610917 0.158884484 0.219016845
[56] 2.076722119 2.622668199 -0.148573623 1.357214749 -1.375272356
[61] 0.591549802 -1.583778935 -1.369779698 -2.479938724 2.173376337
[66] 1.602392473 0.888830318 -0.317312075 0.817013988 0.165326796
[71] 0.063768161 -1.285493573 -1.533350490 0.989752190 0.895155849
[76] 0.069423225 -0.732644971 -2.469528891 -0.222421991 0.767432812
[81] -0.108890992 -0.261692689 0.182734585 0.891357584 -0.405968629
[86] -0.976592305 0.470656705 -0.046628457 -0.723549616 -1.608264218
[91] -0.442911761 -0.290448164 0.262533032 -0.819190536 0.334147458
[96] -0.403914189 2.157803073 -0.981654300 0.009106314 -1.401793442
> rowSums(tmp2)
[1] 0.443532158 0.564409985 0.027610491 1.697239404 1.031265486
[6] -0.210011687 -1.081482584 1.368032543 -1.599241044 -0.687324457
[11] 0.890944792 0.180847091 -0.407176299 -0.703630013 -0.698104058
[16] 0.037498960 -0.826614651 -0.537855269 -1.635267082 1.114251361
[21] -1.043875256 0.528796112 0.605618000 3.294584147 -1.903533068
[26] -1.127512723 -1.637951832 0.327333505 0.543746343 -1.659854877
[31] -0.775582392 -0.512641193 -1.413651254 0.228750766 0.593037225
[36] 0.724868492 0.001354165 0.137777456 0.545245145 0.409985541
[41] -0.703684618 -0.513226182 0.057404437 -1.162520245 0.236041399
[46] 1.924290701 1.867705655 -0.292987690 -0.041685183 -0.517255458
[51] 1.625647566 -0.346356304 0.209610917 0.158884484 0.219016845
[56] 2.076722119 2.622668199 -0.148573623 1.357214749 -1.375272356
[61] 0.591549802 -1.583778935 -1.369779698 -2.479938724 2.173376337
[66] 1.602392473 0.888830318 -0.317312075 0.817013988 0.165326796
[71] 0.063768161 -1.285493573 -1.533350490 0.989752190 0.895155849
[76] 0.069423225 -0.732644971 -2.469528891 -0.222421991 0.767432812
[81] -0.108890992 -0.261692689 0.182734585 0.891357584 -0.405968629
[86] -0.976592305 0.470656705 -0.046628457 -0.723549616 -1.608264218
[91] -0.442911761 -0.290448164 0.262533032 -0.819190536 0.334147458
[96] -0.403914189 2.157803073 -0.981654300 0.009106314 -1.401793442
> 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] 0.443532158 0.564409985 0.027610491 1.697239404 1.031265486
[6] -0.210011687 -1.081482584 1.368032543 -1.599241044 -0.687324457
[11] 0.890944792 0.180847091 -0.407176299 -0.703630013 -0.698104058
[16] 0.037498960 -0.826614651 -0.537855269 -1.635267082 1.114251361
[21] -1.043875256 0.528796112 0.605618000 3.294584147 -1.903533068
[26] -1.127512723 -1.637951832 0.327333505 0.543746343 -1.659854877
[31] -0.775582392 -0.512641193 -1.413651254 0.228750766 0.593037225
[36] 0.724868492 0.001354165 0.137777456 0.545245145 0.409985541
[41] -0.703684618 -0.513226182 0.057404437 -1.162520245 0.236041399
[46] 1.924290701 1.867705655 -0.292987690 -0.041685183 -0.517255458
[51] 1.625647566 -0.346356304 0.209610917 0.158884484 0.219016845
[56] 2.076722119 2.622668199 -0.148573623 1.357214749 -1.375272356
[61] 0.591549802 -1.583778935 -1.369779698 -2.479938724 2.173376337
[66] 1.602392473 0.888830318 -0.317312075 0.817013988 0.165326796
[71] 0.063768161 -1.285493573 -1.533350490 0.989752190 0.895155849
[76] 0.069423225 -0.732644971 -2.469528891 -0.222421991 0.767432812
[81] -0.108890992 -0.261692689 0.182734585 0.891357584 -0.405968629
[86] -0.976592305 0.470656705 -0.046628457 -0.723549616 -1.608264218
[91] -0.442911761 -0.290448164 0.262533032 -0.819190536 0.334147458
[96] -0.403914189 2.157803073 -0.981654300 0.009106314 -1.401793442
> rowMin(tmp2)
[1] 0.443532158 0.564409985 0.027610491 1.697239404 1.031265486
[6] -0.210011687 -1.081482584 1.368032543 -1.599241044 -0.687324457
[11] 0.890944792 0.180847091 -0.407176299 -0.703630013 -0.698104058
[16] 0.037498960 -0.826614651 -0.537855269 -1.635267082 1.114251361
[21] -1.043875256 0.528796112 0.605618000 3.294584147 -1.903533068
[26] -1.127512723 -1.637951832 0.327333505 0.543746343 -1.659854877
[31] -0.775582392 -0.512641193 -1.413651254 0.228750766 0.593037225
[36] 0.724868492 0.001354165 0.137777456 0.545245145 0.409985541
[41] -0.703684618 -0.513226182 0.057404437 -1.162520245 0.236041399
[46] 1.924290701 1.867705655 -0.292987690 -0.041685183 -0.517255458
[51] 1.625647566 -0.346356304 0.209610917 0.158884484 0.219016845
[56] 2.076722119 2.622668199 -0.148573623 1.357214749 -1.375272356
[61] 0.591549802 -1.583778935 -1.369779698 -2.479938724 2.173376337
[66] 1.602392473 0.888830318 -0.317312075 0.817013988 0.165326796
[71] 0.063768161 -1.285493573 -1.533350490 0.989752190 0.895155849
[76] 0.069423225 -0.732644971 -2.469528891 -0.222421991 0.767432812
[81] -0.108890992 -0.261692689 0.182734585 0.891357584 -0.405968629
[86] -0.976592305 0.470656705 -0.046628457 -0.723549616 -1.608264218
[91] -0.442911761 -0.290448164 0.262533032 -0.819190536 0.334147458
[96] -0.403914189 2.157803073 -0.981654300 0.009106314 -1.401793442
>
> colMeans(tmp2)
[1] -0.03044323
> colSums(tmp2)
[1] -3.044323
> colVars(tmp2)
[1] 1.207685
> colSd(tmp2)
[1] 1.098947
> colMax(tmp2)
[1] 3.294584
> colMin(tmp2)
[1] -2.479939
> colMedians(tmp2)
[1] 0.00523024
> colRanges(tmp2)
[,1]
[1,] -2.479939
[2,] 3.294584
>
> 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] 0.5829849 2.2562281 3.1493472 -1.3208793 -3.5129543 4.5542806
[7] 5.5112432 -2.1396987 3.3090442 0.9936656
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1410692
[2,] -0.3635156
[3,] 0.3566815
[4,] 0.4579558
[5,] 0.8198380
>
> rowApply(tmp,sum)
[1] 3.2329646 3.5984138 -0.4254712 -3.6220849 -3.4977577 1.5361444
[7] 5.2887458 -0.9361878 5.0116817 3.1968129
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 2 6 7 6 2 6 4 7 6
[2,] 9 9 9 3 2 3 10 3 4 5
[3,] 4 3 7 1 5 7 9 10 8 10
[4,] 1 6 8 5 10 1 4 1 10 3
[5,] 7 7 1 4 7 5 2 6 3 2
[6,] 6 5 10 9 8 6 3 7 2 8
[7,] 10 1 5 8 4 10 8 5 6 1
[8,] 3 10 2 2 9 9 7 2 1 4
[9,] 8 4 3 10 1 4 5 9 5 9
[10,] 2 8 4 6 3 8 1 8 9 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -4.64144731 -1.15897945 -1.69598427 1.13158210 2.89063576 0.93188557
[7] 1.08553397 0.62681921 -0.61906670 -0.65860954 -2.02731450 -0.03024681
[13] 3.52075307 3.71430054 -0.76248074 5.14267206 -0.94947814 -1.76110482
[19] -1.54608519 -3.54576882
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.03896865
[2,] -1.49549172
[3,] -1.40673880
[4,] -0.07676733
[5,] 0.37651919
>
> rowApply(tmp,sum)
[1] -1.9025379 2.1299373 -1.4561732 0.3692263 0.5071636
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 13 9 1 1 2
[2,] 4 4 9 16 12
[3,] 5 6 6 7 17
[4,] 7 3 11 14 20
[5,] 16 19 20 15 3
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.37651919 -1.2135697 -1.1722469 -0.82278744 1.0320149 -0.2070896
[2,] -0.07676733 -0.6774453 -0.4360780 -0.83645187 1.0463338 0.4904281
[3,] -1.49549172 -0.1865537 -0.6980690 -0.02672689 1.5106147 -0.4896120
[4,] -2.03896865 0.7258784 -0.4547475 0.57635842 0.6747832 0.2267382
[5,] -1.40673880 0.1927109 1.0651572 2.24118988 -1.3731109 0.9114209
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.2874622 -0.28184667 -0.06894593 1.1065850 -1.6198800 1.56930339
[2,] 0.3801791 -0.45228049 -0.03892764 0.4358045 -0.2687853 0.11497626
[3,] 1.1169246 0.64308986 0.61581903 0.5216908 0.3796381 -0.09635393
[4,] 1.0796480 -0.08209227 -0.87224851 -1.2227600 0.4360463 -0.90288048
[5,] -0.2037554 0.79994878 -0.25476366 -1.4999299 -0.9543336 -0.71529206
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.3799670 1.3348088 -0.15786483 0.9834133 1.3796312 -0.6662252
[2,] 0.6856440 0.7869825 0.70261286 0.7812315 -0.2190687 -1.2961407
[3,] 0.1318368 -0.6784788 -1.04689489 1.0240638 -1.2803640 -0.7061248
[4,] 0.8776789 2.0476453 -0.06050501 0.2647434 0.3139047 1.4191839
[5,] 1.4456264 0.2233427 -0.19982887 2.0892201 -1.1435814 -0.5117981
[,19] [,20]
[1,] -1.0438815 -1.5229807
[2,] 2.0373063 -1.0296163
[3,] -1.4740291 0.7788479
[4,] -0.6538013 -1.9853787
[5,] -0.4116796 0.2133589
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-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-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 652 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-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-3.21-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 -1.800605 -0.04231536 -0.9133605 -0.1736808 0.3097549 -0.9625367 -1.175631
col8 col9 col10 col11 col12 col13 col14
row1 -0.4193157 0.391823 0.03804803 -1.116507 1.324246 0.4183033 0.212143
col15 col16 col17 col18 col19 col20
row1 -1.49689 -0.5308622 -0.6603987 -0.3893979 -0.4448098 0.1710198
> tmp[,"col10"]
col10
row1 0.03804803
row2 -0.10392910
row3 0.11857269
row4 0.68681004
row5 -0.09353124
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -1.8006049 -0.04231536 -0.9133605 -0.1736808 0.3097549 -0.9625367
row5 0.6156014 1.02386090 -1.2717363 1.8800783 0.4006827 -0.9492979
col7 col8 col9 col10 col11 col12 col13
row1 -1.175631 -0.4193157 0.391823 0.03804803 -1.1165069 1.3242455 0.41830330
row5 0.978672 1.6581101 0.447192 -0.09353124 -0.5016924 0.6188846 0.08616556
col14 col15 col16 col17 col18 col19 col20
row1 0.212143 -1.4968896 -0.5308622 -0.6603987 -0.3893979 -0.4448098 0.1710198
row5 1.129231 -0.6349809 1.5811507 -0.7639146 -0.4762903 -1.1195961 0.8969751
> tmp[,c("col6","col20")]
col6 col20
row1 -0.96253672 0.1710198
row2 0.99335197 -1.0235804
row3 -1.44618917 2.7157537
row4 -0.04358788 -1.0130309
row5 -0.94929790 0.8969751
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.9625367 0.1710198
row5 -0.9492979 0.8969751
>
>
>
>
> 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 50.62479 49.15526 49.39846 50.35642 49.43609 104.2273 50.0241 51.64468
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.3609 49.02213 48.71953 48.49696 49.68421 50.59675 47.95633 50.80433
col17 col18 col19 col20
row1 49.04715 48.5686 48.93336 102.9855
> tmp[,"col10"]
col10
row1 49.02213
row2 31.85264
row3 29.14521
row4 31.06794
row5 50.85064
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.62479 49.15526 49.39846 50.35642 49.43609 104.2273 50.02410 51.64468
row5 49.43694 49.44805 49.16846 49.15225 50.68486 104.9758 50.64032 49.67869
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.36090 49.02213 48.71953 48.49696 49.68421 50.59675 47.95633 50.80433
row5 49.60942 50.85064 49.36215 49.80788 50.61449 49.00467 49.32216 49.28840
col17 col18 col19 col20
row1 49.04715 48.56860 48.93336 102.9855
row5 50.40940 48.50642 49.60321 105.3137
> tmp[,c("col6","col20")]
col6 col20
row1 104.22731 102.98549
row2 73.96369 75.76178
row3 74.60252 74.32849
row4 73.38415 73.47180
row5 104.97583 105.31367
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.2273 102.9855
row5 104.9758 105.3137
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.2273 102.9855
row5 104.9758 105.3137
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.1522282
[2,] -0.1626864
[3,] 1.1522438
[4,] 0.7979575
[5,] 0.6942896
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.6091525 1.1893453
[2,] -0.7089254 0.1149035
[3,] 0.9711246 -1.0758801
[4,] -0.8099462 -0.7664378
[5,] -0.7066731 1.9121988
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.8454829 -0.3696009
[2,] -0.1169377 0.6839246
[3,] -0.2094740 -0.9096636
[4,] 0.6555435 0.6860671
[5,] -1.5539775 -0.2876842
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.8454829
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.8454829
[2,] -0.1169377
>
>
>
> 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 -1.1617028 -1.018979449 1.1330607 -1.0068480 -0.09424234 -1.019264
row1 -0.1762983 -0.008016456 -0.1408913 -0.9350065 0.92635083 -1.195637
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -1.103748061 -0.01132365 -0.9568491 -1.0782207 0.01027674 -0.3048244
row1 0.002535883 -1.73133806 -1.2720585 -0.3567968 -0.30340038 -1.2188742
[,13] [,14] [,15] [,16] [,17] [,18]
row3 0.1058452 -0.7853425 -0.1009585 -0.3425564 -0.1461619 -0.08714025
row1 0.4840296 -2.6319934 -0.6708420 -0.8482340 -0.8618292 0.03382070
[,19] [,20]
row3 -1.7105779 -0.2396672
row1 0.1967489 0.2810343
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.9692918 -0.09603053 1.65676 -1.159746 -0.4288515 -0.2899652 0.8067488
[,8] [,9] [,10]
row2 -0.3592836 1.044431 -0.8995034
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -1.329189 0.7386501 -1.547354 0.7610348 -1.62183 -0.5293277 0.197466
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.6839152 0.4547396 -0.3201649 0.4826546 -0.8699325 0.3486154 -0.7315235
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.5407223 -0.1086289 1.056208 2.457398 2.830191 -0.8947691
>
>
> 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: 0x5e623e10e5d0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dfe7e12502c13"
[2] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dfe7e37b543ae"
[3] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dfe7e1a91c8b9"
[4] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dfe7e4c22f014"
[5] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dfe7e3b6be699"
[6] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dfe7e12722aca"
[7] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dfe7e5eaf9bf9"
[8] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dfe7e1bde5705"
[9] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dfe7e73916a82"
[10] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dfe7e5c470788"
[11] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dfe7e7804a331"
[12] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dfe7e29c82f7e"
[13] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dfe7e6f97a815"
[14] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dfe7e3c34e394"
[15] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1dfe7e74ffc485"
>
>
> ### 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: 0x5e623dd7de10>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5e623dd7de10>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5e623dd7de10>
> rowMedians(tmp)
[1] 0.3394805169 0.0218873683 -0.0479955495 -0.1721158374 -0.2931076517
[6] 0.2130394639 0.0204855863 0.5717936886 0.2968500479 0.1749007136
[11] 0.2904344236 -0.8584258171 -0.0491539585 -0.0807747737 -0.0440244989
[16] -0.0022149709 0.3592588438 -0.3333641305 -0.5693225435 0.4792621004
[21] -0.1423853914 -0.2729966996 -0.3682259632 0.6583958125 -0.1287448317
[26] -0.0300343025 -0.3992469288 -0.3033944522 -0.4548519693 0.3182789445
[31] 0.0333961244 -0.4799667656 -0.3047689089 -0.0499023319 0.1201914104
[36] -0.0027031200 0.1999334292 -0.1984655792 -0.4677630675 0.0319751700
[41] -0.2771117505 0.1072047777 -0.3735990955 0.0029534881 0.2697633472
[46] -0.3316900453 -0.4808151572 -0.0550560951 -0.4764223580 -0.6560453127
[51] 0.2620617716 0.2455497531 -0.3716388201 -0.2567296040 0.1658683937
[56] 0.1841631862 0.1874931402 0.1517322202 -0.2607498590 -0.1415264292
[61] 0.0620614671 -0.1949968177 -0.3805634958 -0.1605882481 -0.3471051320
[66] 0.1464832920 0.3185318028 -0.2961376764 0.2798439609 -0.2793978401
[71] -0.5412092897 -0.1573850940 0.1940670348 0.3412490715 0.3521357480
[76] 0.5443500800 0.0338187334 0.3424669136 0.6939469584 -0.0228314508
[81] 0.1556383869 0.1539345866 0.2656526025 -0.2250571941 -0.3220268565
[86] -0.0866684715 0.1745999820 0.0414650545 -0.2694555474 -0.1364695329
[91] 0.2895984946 -0.2522266223 -0.6702153417 0.3340960681 0.2529613821
[96] 0.1081455104 0.5140739428 0.2669941694 0.3627761274 0.1691425668
[101] 0.6345212823 -0.4855892545 -0.3605473877 0.1138192412 -0.1355351684
[106] 0.6384100808 0.1272295062 0.2740870340 0.2738525298 0.4463313946
[111] -0.3865915580 -0.0269245120 -0.1149988245 0.3971502444 -0.0116062386
[116] 0.2080319100 0.2317685118 0.2010774781 -0.0377591143 0.0907951374
[121] -0.4339622595 -0.0639226728 0.4079831519 -0.1377459712 -0.0335966787
[126] 0.1094523423 -0.0449812620 -0.0280648748 0.5333521129 -0.2014924407
[131] -0.2037346563 0.0677334397 0.3375244264 -0.3717472420 0.0007657528
[136] 0.2390679628 0.3429580659 0.3779482279 0.0081960430 0.3629381014
[141] 0.2233702942 -0.4211145236 0.0473887377 0.1014059191 -0.2132628900
[146] 0.1847949364 -0.5629759230 0.0432202289 0.2864338847 0.1458968236
[151] -0.1192312182 0.0616162905 -0.0763635890 0.5042977284 0.1261258261
[156] -0.5405995374 0.3440093551 0.3534475096 0.3189783726 -0.1551039105
[161] 0.0790509786 0.0163160425 -0.3582421899 0.3806771891 -0.2575320944
[166] -0.7426897077 0.1978028301 -0.3936683484 0.1861698717 0.0564168277
[171] 0.1555666998 -0.3571950001 0.0475410873 0.2925842613 0.1429381231
[176] -0.2544623480 0.0304083784 -0.2343163548 0.7484034957 0.1445429322
[181] -0.8785870836 -0.0028915606 -0.4473055576 -0.0809831461 -0.0886088335
[186] -0.3043175302 -0.3522562991 -0.1698984465 -0.0160567682 -0.4274052621
[191] -0.1544621270 -0.1361458156 0.6111838301 0.3110077579 0.1442541864
[196] 0.1529470839 0.2875484400 -0.3373796600 0.1411757656 -0.5542007478
[201] -0.0818751719 -0.1247319809 -0.3180250952 -0.3775094945 0.1534957363
[206] 0.1903596486 0.0839966681 0.4281742295 0.1627499275 0.3970809085
[211] -0.0618409023 -0.4282606116 0.1353904391 -0.1840262846 0.0030467061
[216] -0.3447298260 -0.1675031287 0.4348955691 0.0017465603 0.1349035763
[221] -0.2171829733 0.1658992986 0.0145300345 0.2626553039 -0.4521248022
[226] 0.2726870927 -0.1380239691 -0.0858283686 -0.3351856756 -0.1774934076
>
> proc.time()
user system elapsed
1.348 1.467 2.802
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 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: 0x5895a2986640>
> .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: 0x5895a2986640>
> .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: 0x5895a2986640>
> .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: 0x5895a2986640>
> 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: 0x5895a3227420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5895a3227420>
> .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: 0x5895a3227420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5895a3227420>
> .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: 0x5895a3227420>
> 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: 0x5895a1d11c30>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5895a1d11c30>
> .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: 0x5895a1d11c30>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5895a1d11c30>
> .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: 0x5895a1d11c30>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5895a1d11c30>
> .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: 0x5895a1d11c30>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5895a1d11c30>
> .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: 0x5895a1d11c30>
> 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: 0x5895a1c15090>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5895a1c15090>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5895a1c15090>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5895a1c15090>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1dff061bf18ee3" "BufferedMatrixFile1dff0667ef7ce9"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1dff061bf18ee3" "BufferedMatrixFile1dff0667ef7ce9"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5895a3e58400>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5895a3e58400>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5895a3e58400>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5895a3e58400>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5895a3e58400>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5895a3e58400>
> .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: 0x5895a42c5c80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5895a42c5c80>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5895a42c5c80>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5895a42c5c80>
> 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: 0x5895a430ff80>
> .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: 0x5895a430ff80>
> rm(P)
>
> proc.time()
user system elapsed
0.242 0.059 0.289
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
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Platform: x86_64-pc-linux-gnu
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You are welcome to redistribute it under certain conditions.
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
0.253 0.046 0.284