Ben Bolstad
| Snapshot Date: 2025-01-23 13:40 -0500 (Thu, 23 Jan 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 -0500 (Sat, 14 Dec 2024) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-01-24 11:38 -0500 (Fri, 24 Jan 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | R Under development (unstable) (2025-01-20 r87609) -- "Unsuffered Consequences" | 4609 |
| palomino7 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2025-01-21 r87610 ucrt) -- "Unsuffered Consequences" | 4393 |
| lconway | macOS 12.7.1 Monterey | x86_64 | R Under development (unstable) (2025-01-20 r87609) -- "Unsuffered Consequences" | 3839 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | R Under development (unstable) (2025-01-20 r87609) -- "Unsuffered Consequences" | 3835 |
| kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | R Under development (unstable) (2024-11-24 r87369) -- "Unsuffered Consequences" | 4408 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 246/2286 | 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 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: 1.71.1 |
| 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: 2025-01-23 20:26:43 -0500 (Thu, 23 Jan 2025) |
| EndedAt: 2025-01-23 20:27:09 -0500 (Thu, 23 Jan 2025) |
| EllapsedTime: 26.0 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) (2025-01-20 r87609)
* 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 24.04.1 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 -I"/home/biocbuild/bbs-3.21-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o gcc -I"/home/biocbuild/bbs-3.21-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o gcc -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 -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 -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) (2025-01-20 r87609) -- "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
0.250 0.048 0.286
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2025-01-20 r87609) -- "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 477782 25.6 1045192 55.9 639797 34.2
Vcells 884184 6.8 8388608 64.0 2080672 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 Jan 23 20:26:59 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 Jan 23 20:26:59 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: 0x62d356b84280>
>
>
>
> 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 Jan 23 20:26:59 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 Jan 23 20:26:59 2025"
>
> ColMode(tmp2)
<pointer: 0x62d356b84280>
>
>
>
> ### 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,] 101.1706505 -0.001170347 -2.0431785 -0.65862078
[2,] 0.8445786 -0.063629845 -0.2563640 -0.29327945
[3,] -2.2947118 0.183580202 -0.2181165 -0.07431373
[4,] 0.1993860 -0.399687672 0.4362038 0.62015909
> 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,] 101.1706505 0.001170347 2.0431785 0.65862078
[2,] 0.8445786 0.063629845 0.2563640 0.29327945
[3,] 2.2947118 0.183580202 0.2181165 0.07431373
[4,] 0.1993860 0.399687672 0.4362038 0.62015909
> 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,] 10.0583622 0.03421034 1.4293979 0.8115545
[2,] 0.9190096 0.25224957 0.5063240 0.5415528
[3,] 1.5148306 0.42846260 0.4670295 0.2726054
[4,] 0.4465266 0.63220857 0.6604573 0.7875018
>
> 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,] 226.75427 25.34327 41.33716 33.77417
[2,] 35.03467 27.58613 30.31960 30.70881
[3,] 42.44302 29.46821 29.88841 27.80037
[4,] 29.66465 31.72177 32.04078 33.49518
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x62d358f95fb0>
> exp(tmp5)
<pointer: 0x62d358f95fb0>
> log(tmp5,2)
<pointer: 0x62d358f95fb0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.9593
> Min(tmp5)
[1] 52.7487
> mean(tmp5)
[1] 72.59
> Sum(tmp5)
[1] 14518
> Var(tmp5)
[1] 880.5874
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.81295 71.83784 68.24603 68.74024 71.91654 69.54272 72.96641 69.37362
[9] 74.12509 68.33851
> rowSums(tmp5)
[1] 1816.259 1436.757 1364.921 1374.805 1438.331 1390.854 1459.328 1387.472
[9] 1482.502 1366.770
> rowVars(tmp5)
[1] 8121.25158 106.34455 71.60970 92.95915 70.96070 57.42180
[7] 84.19532 68.92393 69.55649 51.36054
> rowSd(tmp5)
[1] 90.117987 10.312349 8.462252 9.641533 8.423818 7.577717 9.175801
[8] 8.302044 8.340053 7.166627
> rowMax(tmp5)
[1] 471.95931 100.62083 88.33958 93.35890 89.13110 89.91149 92.25763
[8] 81.97779 88.90148 79.79442
> rowMin(tmp5)
[1] 52.74870 56.24880 56.47228 52.78851 58.77093 59.40291 58.41723 57.27684
[9] 54.00555 55.90261
>
> colMeans(tmp5)
[1] 110.89705 64.32449 68.92547 69.70453 67.46374 71.36802 68.91360
[8] 67.09545 72.19708 71.68248 72.09096 73.21898 73.68474 72.25743
[15] 72.88624 67.83319 71.95399 70.57795 72.04770 72.67680
> colSums(tmp5)
[1] 1108.9705 643.2449 689.2547 697.0453 674.6374 713.6802 689.1360
[8] 670.9545 721.9708 716.8248 720.9096 732.1898 736.8474 722.5743
[15] 728.8624 678.3319 719.5399 705.7795 720.4770 726.7680
> colVars(tmp5)
[1] 16177.76621 58.64112 72.28885 59.35228 41.45678 17.69744
[7] 66.97689 44.82826 40.73786 96.67316 96.62267 142.67094
[13] 127.79674 74.72084 172.45906 50.45006 113.25837 56.28041
[19] 81.37085 34.95884
> colSd(tmp5)
[1] 127.191848 7.657749 8.502285 7.704043 6.438694 4.206833
[7] 8.183941 6.695391 6.382621 9.832251 9.829683 11.944494
[13] 11.304722 8.644122 13.132367 7.102820 10.642292 7.502027
[19] 9.020579 5.912600
> colMax(tmp5)
[1] 471.95931 77.12011 86.03788 79.79998 79.48980 76.48049 83.97997
[8] 79.81357 81.46937 89.13110 89.91149 92.25763 90.18241 88.90148
[15] 100.62083 78.18837 93.35890 83.39654 85.01698 79.79442
> colMin(tmp5)
[1] 59.40291 52.74870 59.83310 57.86282 56.24880 64.67058 58.25396 59.80714
[9] 63.10979 54.00555 52.78851 57.84031 58.77093 61.49419 56.79805 55.90261
[17] 59.41333 57.27684 56.47228 60.69642
>
>
> ### 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] 90.81295 71.83784 68.24603 NA 71.91654 69.54272 72.96641 69.37362
[9] 74.12509 68.33851
> rowSums(tmp5)
[1] 1816.259 1436.757 1364.921 NA 1438.331 1390.854 1459.328 1387.472
[9] 1482.502 1366.770
> rowVars(tmp5)
[1] 8121.25158 106.34455 71.60970 93.45687 70.96070 57.42180
[7] 84.19532 68.92393 69.55649 51.36054
> rowSd(tmp5)
[1] 90.117987 10.312349 8.462252 9.667309 8.423818 7.577717 9.175801
[8] 8.302044 8.340053 7.166627
> rowMax(tmp5)
[1] 471.95931 100.62083 88.33958 NA 89.13110 89.91149 92.25763
[8] 81.97779 88.90148 79.79442
> rowMin(tmp5)
[1] 52.74870 56.24880 56.47228 NA 58.77093 59.40291 58.41723 57.27684
[9] 54.00555 55.90261
>
> colMeans(tmp5)
[1] 110.89705 64.32449 68.92547 69.70453 67.46374 71.36802 68.91360
[8] NA 72.19708 71.68248 72.09096 73.21898 73.68474 72.25743
[15] 72.88624 67.83319 71.95399 70.57795 72.04770 72.67680
> colSums(tmp5)
[1] 1108.9705 643.2449 689.2547 697.0453 674.6374 713.6802 689.1360
[8] NA 721.9708 716.8248 720.9096 732.1898 736.8474 722.5743
[15] 728.8624 678.3319 719.5399 705.7795 720.4770 726.7680
> colVars(tmp5)
[1] 16177.76621 58.64112 72.28885 59.35228 41.45678 17.69744
[7] 66.97689 NA 40.73786 96.67316 96.62267 142.67094
[13] 127.79674 74.72084 172.45906 50.45006 113.25837 56.28041
[19] 81.37085 34.95884
> colSd(tmp5)
[1] 127.191848 7.657749 8.502285 7.704043 6.438694 4.206833
[7] 8.183941 NA 6.382621 9.832251 9.829683 11.944494
[13] 11.304722 8.644122 13.132367 7.102820 10.642292 7.502027
[19] 9.020579 5.912600
> colMax(tmp5)
[1] 471.95931 77.12011 86.03788 79.79998 79.48980 76.48049 83.97997
[8] NA 81.46937 89.13110 89.91149 92.25763 90.18241 88.90148
[15] 100.62083 78.18837 93.35890 83.39654 85.01698 79.79442
> colMin(tmp5)
[1] 59.40291 52.74870 59.83310 57.86282 56.24880 64.67058 58.25396 NA
[9] 63.10979 54.00555 52.78851 57.84031 58.77093 61.49419 56.79805 55.90261
[17] 59.41333 57.27684 56.47228 60.69642
>
> Max(tmp5,na.rm=TRUE)
[1] 471.9593
> Min(tmp5,na.rm=TRUE)
[1] 52.7487
> mean(tmp5,na.rm=TRUE)
[1] 72.65423
> Sum(tmp5,na.rm=TRUE)
[1] 14458.19
> Var(tmp5,na.rm=TRUE)
[1] 884.2054
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.81295 71.83784 68.24603 69.21040 71.91654 69.54272 72.96641 69.37362
[9] 74.12509 68.33851
> rowSums(tmp5,na.rm=TRUE)
[1] 1816.259 1436.757 1364.921 1314.998 1438.331 1390.854 1459.328 1387.472
[9] 1482.502 1366.770
> rowVars(tmp5,na.rm=TRUE)
[1] 8121.25158 106.34455 71.60970 93.45687 70.96070 57.42180
[7] 84.19532 68.92393 69.55649 51.36054
> rowSd(tmp5,na.rm=TRUE)
[1] 90.117987 10.312349 8.462252 9.667309 8.423818 7.577717 9.175801
[8] 8.302044 8.340053 7.166627
> rowMax(tmp5,na.rm=TRUE)
[1] 471.95931 100.62083 88.33958 93.35890 89.13110 89.91149 92.25763
[8] 81.97779 88.90148 79.79442
> rowMin(tmp5,na.rm=TRUE)
[1] 52.74870 56.24880 56.47228 52.78851 58.77093 59.40291 58.41723 57.27684
[9] 54.00555 55.90261
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.89705 64.32449 68.92547 69.70453 67.46374 71.36802 68.91360
[8] 67.90527 72.19708 71.68248 72.09096 73.21898 73.68474 72.25743
[15] 72.88624 67.83319 71.95399 70.57795 72.04770 72.67680
> colSums(tmp5,na.rm=TRUE)
[1] 1108.9705 643.2449 689.2547 697.0453 674.6374 713.6802 689.1360
[8] 611.1474 721.9708 716.8248 720.9096 732.1898 736.8474 722.5743
[15] 728.8624 678.3319 719.5399 705.7795 720.4770 726.7680
> colVars(tmp5,na.rm=TRUE)
[1] 16177.76621 58.64112 72.28885 59.35228 41.45678 17.69744
[7] 66.97689 43.05409 40.73786 96.67316 96.62267 142.67094
[13] 127.79674 74.72084 172.45906 50.45006 113.25837 56.28041
[19] 81.37085 34.95884
> colSd(tmp5,na.rm=TRUE)
[1] 127.191848 7.657749 8.502285 7.704043 6.438694 4.206833
[7] 8.183941 6.561562 6.382621 9.832251 9.829683 11.944494
[13] 11.304722 8.644122 13.132367 7.102820 10.642292 7.502027
[19] 9.020579 5.912600
> colMax(tmp5,na.rm=TRUE)
[1] 471.95931 77.12011 86.03788 79.79998 79.48980 76.48049 83.97997
[8] 79.81357 81.46937 89.13110 89.91149 92.25763 90.18241 88.90148
[15] 100.62083 78.18837 93.35890 83.39654 85.01698 79.79442
> colMin(tmp5,na.rm=TRUE)
[1] 59.40291 52.74870 59.83310 57.86282 56.24880 64.67058 58.25396 60.68380
[9] 63.10979 54.00555 52.78851 57.84031 58.77093 61.49419 56.79805 55.90261
[17] 59.41333 57.27684 56.47228 60.69642
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.81295 71.83784 68.24603 NaN 71.91654 69.54272 72.96641 69.37362
[9] 74.12509 68.33851
> rowSums(tmp5,na.rm=TRUE)
[1] 1816.259 1436.757 1364.921 0.000 1438.331 1390.854 1459.328 1387.472
[9] 1482.502 1366.770
> rowVars(tmp5,na.rm=TRUE)
[1] 8121.25158 106.34455 71.60970 NA 70.96070 57.42180
[7] 84.19532 68.92393 69.55649 51.36054
> rowSd(tmp5,na.rm=TRUE)
[1] 90.117987 10.312349 8.462252 NA 8.423818 7.577717 9.175801
[8] 8.302044 8.340053 7.166627
> rowMax(tmp5,na.rm=TRUE)
[1] 471.95931 100.62083 88.33958 NA 89.13110 89.91149 92.25763
[8] 81.97779 88.90148 79.79442
> rowMin(tmp5,na.rm=TRUE)
[1] 52.74870 56.24880 56.47228 NA 58.77093 59.40291 58.41723 57.27684
[9] 54.00555 55.90261
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.35861 64.13558 69.17400 69.70327 66.85690 70.79997 69.82236
[8] NaN 71.23498 71.81171 74.23568 74.92772 74.98829 72.20565
[15] 74.45079 68.05551 69.57567 70.67662 71.16546 72.27086
> colSums(tmp5,na.rm=TRUE)
[1] 1047.2275 577.2202 622.5660 627.3294 601.7121 637.1997 628.4012
[8] 0.0000 641.1149 646.3054 668.1211 674.3495 674.8946 649.8509
[15] 670.0571 612.4996 626.1810 636.0896 640.4891 650.4378
> colVars(tmp5,na.rm=TRUE)
[1] 17864.41579 65.56976 80.63007 66.77130 42.49608 16.27944
[7] 66.05831 NA 35.41670 108.56941 56.95263 127.65710
[13] 124.65473 84.03078 166.47846 56.20025 63.78095 63.20594
[19] 82.78573 37.47490
> colSd(tmp5,na.rm=TRUE)
[1] 133.657831 8.097516 8.979425 8.171370 6.518902 4.034779
[7] 8.127626 NA 5.951193 10.419665 7.546697 11.298544
[13] 11.164888 9.166830 12.902653 7.496683 7.986298 7.950216
[19] 9.098666 6.121675
> colMax(tmp5,na.rm=TRUE)
[1] 471.95931 77.12011 86.03788 79.79998 79.48980 75.78423 83.97997
[8] -Inf 81.46937 89.13110 89.91149 92.25763 90.18241 88.90148
[15] 100.62083 78.18837 81.10030 83.39654 85.01698 79.79442
> colMin(tmp5,na.rm=TRUE)
[1] 59.40291 52.74870 59.83310 57.86282 56.24880 64.67058 58.25396 Inf
[9] 63.10979 54.00555 65.31412 59.87870 58.77093 61.49419 56.79805 55.90261
[17] 59.41333 57.27684 56.47228 60.69642
>
>
>
>
> 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] 277.2339 239.0815 155.9300 190.9698 426.4538 314.6257 115.7641 199.5384
[9] 255.4348 256.1271
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 277.2339 239.0815 155.9300 190.9698 426.4538 314.6257 115.7641 199.5384
[9] 255.4348 256.1271
>
>
>
> 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] 0.000000e+00 8.526513e-14 0.000000e+00 1.136868e-13 2.842171e-14
[6] -2.273737e-13 0.000000e+00 8.526513e-14 5.684342e-14 1.136868e-13
[11] -2.842171e-14 1.421085e-13 -2.842171e-14 -8.526513e-14 0.000000e+00
[16] 2.842171e-14 5.684342e-14 2.842171e-14 5.684342e-14 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
1 5
1 12
6 12
3 15
1 17
7 9
1 5
3 1
2 6
5 8
1 16
8 6
10 18
10 18
5 13
2 15
10 4
6 7
9 5
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] 2.477459
> Min(tmp)
[1] -2.716868
> mean(tmp)
[1] -0.1039642
> Sum(tmp)
[1] -10.39642
> Var(tmp)
[1] 1.033899
>
> rowMeans(tmp)
[1] -0.1039642
> rowSums(tmp)
[1] -10.39642
> rowVars(tmp)
[1] 1.033899
> rowSd(tmp)
[1] 1.016808
> rowMax(tmp)
[1] 2.477459
> rowMin(tmp)
[1] -2.716868
>
> colMeans(tmp)
[1] -0.42929840 -1.32876959 0.79794072 -0.74538089 1.06119582 0.68952079
[7] 0.47014033 -0.92136740 -0.25670435 0.81240860 -0.09500020 1.46896741
[13] 0.15474195 -0.82223085 0.35163170 -0.69005844 0.89219876 0.27414066
[19] 0.41623273 -0.87031268 0.20286840 -0.79296371 0.29893869 -2.57720592
[25] -1.42137262 -1.35454728 -1.35608777 0.07875756 -1.28323885 -0.01704405
[31] 0.65231349 -0.10389885 0.67252197 0.97622768 -2.71686806 0.36003753
[37] -0.53880033 0.50159569 -0.23934881 0.72415913 0.47149626 0.90688908
[43] 1.08694588 -1.84445603 -1.18498595 1.13680331 1.04765537 -0.38108295
[49] -0.11895181 -0.47120814 0.58923510 -1.08771476 -0.07724167 0.28528120
[55] 0.16373968 -0.45646398 0.71214038 -1.01189325 -0.84972385 0.20602574
[61] -0.82787088 -0.23184450 0.86867920 -0.17494234 -0.39635326 2.47745933
[67] 1.22584454 0.77469274 -1.85235795 0.86240450 -1.13594985 0.57438753
[73] 0.01210241 0.70980849 -0.15507567 -0.72473193 -1.21199248 -1.36068845
[79] 0.09418795 2.26952852 -0.85838811 -0.26046734 -1.83831882 -0.09765756
[85] 0.20270533 -0.01464311 0.75308845 0.25805287 -1.93515445 -0.49308155
[91] 0.76165122 -1.72434063 -1.98707631 -0.28984540 1.91058548 0.54592770
[97] 0.58681380 -1.69483687 -0.30771170 1.87045525
> colSums(tmp)
[1] -0.42929840 -1.32876959 0.79794072 -0.74538089 1.06119582 0.68952079
[7] 0.47014033 -0.92136740 -0.25670435 0.81240860 -0.09500020 1.46896741
[13] 0.15474195 -0.82223085 0.35163170 -0.69005844 0.89219876 0.27414066
[19] 0.41623273 -0.87031268 0.20286840 -0.79296371 0.29893869 -2.57720592
[25] -1.42137262 -1.35454728 -1.35608777 0.07875756 -1.28323885 -0.01704405
[31] 0.65231349 -0.10389885 0.67252197 0.97622768 -2.71686806 0.36003753
[37] -0.53880033 0.50159569 -0.23934881 0.72415913 0.47149626 0.90688908
[43] 1.08694588 -1.84445603 -1.18498595 1.13680331 1.04765537 -0.38108295
[49] -0.11895181 -0.47120814 0.58923510 -1.08771476 -0.07724167 0.28528120
[55] 0.16373968 -0.45646398 0.71214038 -1.01189325 -0.84972385 0.20602574
[61] -0.82787088 -0.23184450 0.86867920 -0.17494234 -0.39635326 2.47745933
[67] 1.22584454 0.77469274 -1.85235795 0.86240450 -1.13594985 0.57438753
[73] 0.01210241 0.70980849 -0.15507567 -0.72473193 -1.21199248 -1.36068845
[79] 0.09418795 2.26952852 -0.85838811 -0.26046734 -1.83831882 -0.09765756
[85] 0.20270533 -0.01464311 0.75308845 0.25805287 -1.93515445 -0.49308155
[91] 0.76165122 -1.72434063 -1.98707631 -0.28984540 1.91058548 0.54592770
[97] 0.58681380 -1.69483687 -0.30771170 1.87045525
> 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] -0.42929840 -1.32876959 0.79794072 -0.74538089 1.06119582 0.68952079
[7] 0.47014033 -0.92136740 -0.25670435 0.81240860 -0.09500020 1.46896741
[13] 0.15474195 -0.82223085 0.35163170 -0.69005844 0.89219876 0.27414066
[19] 0.41623273 -0.87031268 0.20286840 -0.79296371 0.29893869 -2.57720592
[25] -1.42137262 -1.35454728 -1.35608777 0.07875756 -1.28323885 -0.01704405
[31] 0.65231349 -0.10389885 0.67252197 0.97622768 -2.71686806 0.36003753
[37] -0.53880033 0.50159569 -0.23934881 0.72415913 0.47149626 0.90688908
[43] 1.08694588 -1.84445603 -1.18498595 1.13680331 1.04765537 -0.38108295
[49] -0.11895181 -0.47120814 0.58923510 -1.08771476 -0.07724167 0.28528120
[55] 0.16373968 -0.45646398 0.71214038 -1.01189325 -0.84972385 0.20602574
[61] -0.82787088 -0.23184450 0.86867920 -0.17494234 -0.39635326 2.47745933
[67] 1.22584454 0.77469274 -1.85235795 0.86240450 -1.13594985 0.57438753
[73] 0.01210241 0.70980849 -0.15507567 -0.72473193 -1.21199248 -1.36068845
[79] 0.09418795 2.26952852 -0.85838811 -0.26046734 -1.83831882 -0.09765756
[85] 0.20270533 -0.01464311 0.75308845 0.25805287 -1.93515445 -0.49308155
[91] 0.76165122 -1.72434063 -1.98707631 -0.28984540 1.91058548 0.54592770
[97] 0.58681380 -1.69483687 -0.30771170 1.87045525
> colMin(tmp)
[1] -0.42929840 -1.32876959 0.79794072 -0.74538089 1.06119582 0.68952079
[7] 0.47014033 -0.92136740 -0.25670435 0.81240860 -0.09500020 1.46896741
[13] 0.15474195 -0.82223085 0.35163170 -0.69005844 0.89219876 0.27414066
[19] 0.41623273 -0.87031268 0.20286840 -0.79296371 0.29893869 -2.57720592
[25] -1.42137262 -1.35454728 -1.35608777 0.07875756 -1.28323885 -0.01704405
[31] 0.65231349 -0.10389885 0.67252197 0.97622768 -2.71686806 0.36003753
[37] -0.53880033 0.50159569 -0.23934881 0.72415913 0.47149626 0.90688908
[43] 1.08694588 -1.84445603 -1.18498595 1.13680331 1.04765537 -0.38108295
[49] -0.11895181 -0.47120814 0.58923510 -1.08771476 -0.07724167 0.28528120
[55] 0.16373968 -0.45646398 0.71214038 -1.01189325 -0.84972385 0.20602574
[61] -0.82787088 -0.23184450 0.86867920 -0.17494234 -0.39635326 2.47745933
[67] 1.22584454 0.77469274 -1.85235795 0.86240450 -1.13594985 0.57438753
[73] 0.01210241 0.70980849 -0.15507567 -0.72473193 -1.21199248 -1.36068845
[79] 0.09418795 2.26952852 -0.85838811 -0.26046734 -1.83831882 -0.09765756
[85] 0.20270533 -0.01464311 0.75308845 0.25805287 -1.93515445 -0.49308155
[91] 0.76165122 -1.72434063 -1.98707631 -0.28984540 1.91058548 0.54592770
[97] 0.58681380 -1.69483687 -0.30771170 1.87045525
> colMedians(tmp)
[1] -0.42929840 -1.32876959 0.79794072 -0.74538089 1.06119582 0.68952079
[7] 0.47014033 -0.92136740 -0.25670435 0.81240860 -0.09500020 1.46896741
[13] 0.15474195 -0.82223085 0.35163170 -0.69005844 0.89219876 0.27414066
[19] 0.41623273 -0.87031268 0.20286840 -0.79296371 0.29893869 -2.57720592
[25] -1.42137262 -1.35454728 -1.35608777 0.07875756 -1.28323885 -0.01704405
[31] 0.65231349 -0.10389885 0.67252197 0.97622768 -2.71686806 0.36003753
[37] -0.53880033 0.50159569 -0.23934881 0.72415913 0.47149626 0.90688908
[43] 1.08694588 -1.84445603 -1.18498595 1.13680331 1.04765537 -0.38108295
[49] -0.11895181 -0.47120814 0.58923510 -1.08771476 -0.07724167 0.28528120
[55] 0.16373968 -0.45646398 0.71214038 -1.01189325 -0.84972385 0.20602574
[61] -0.82787088 -0.23184450 0.86867920 -0.17494234 -0.39635326 2.47745933
[67] 1.22584454 0.77469274 -1.85235795 0.86240450 -1.13594985 0.57438753
[73] 0.01210241 0.70980849 -0.15507567 -0.72473193 -1.21199248 -1.36068845
[79] 0.09418795 2.26952852 -0.85838811 -0.26046734 -1.83831882 -0.09765756
[85] 0.20270533 -0.01464311 0.75308845 0.25805287 -1.93515445 -0.49308155
[91] 0.76165122 -1.72434063 -1.98707631 -0.28984540 1.91058548 0.54592770
[97] 0.58681380 -1.69483687 -0.30771170 1.87045525
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.4292984 -1.32877 0.7979407 -0.7453809 1.061196 0.6895208 0.4701403
[2,] -0.4292984 -1.32877 0.7979407 -0.7453809 1.061196 0.6895208 0.4701403
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.9213674 -0.2567044 0.8124086 -0.0950002 1.468967 0.154742 -0.8222308
[2,] -0.9213674 -0.2567044 0.8124086 -0.0950002 1.468967 0.154742 -0.8222308
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.3516317 -0.6900584 0.8921988 0.2741407 0.4162327 -0.8703127 0.2028684
[2,] 0.3516317 -0.6900584 0.8921988 0.2741407 0.4162327 -0.8703127 0.2028684
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.7929637 0.2989387 -2.577206 -1.421373 -1.354547 -1.356088 0.07875756
[2,] -0.7929637 0.2989387 -2.577206 -1.421373 -1.354547 -1.356088 0.07875756
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.283239 -0.01704405 0.6523135 -0.1038989 0.672522 0.9762277 -2.716868
[2,] -1.283239 -0.01704405 0.6523135 -0.1038989 0.672522 0.9762277 -2.716868
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.3600375 -0.5388003 0.5015957 -0.2393488 0.7241591 0.4714963 0.9068891
[2,] 0.3600375 -0.5388003 0.5015957 -0.2393488 0.7241591 0.4714963 0.9068891
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 1.086946 -1.844456 -1.184986 1.136803 1.047655 -0.3810829 -0.1189518
[2,] 1.086946 -1.844456 -1.184986 1.136803 1.047655 -0.3810829 -0.1189518
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.4712081 0.5892351 -1.087715 -0.07724167 0.2852812 0.1637397 -0.456464
[2,] -0.4712081 0.5892351 -1.087715 -0.07724167 0.2852812 0.1637397 -0.456464
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.7121404 -1.011893 -0.8497238 0.2060257 -0.8278709 -0.2318445 0.8686792
[2,] 0.7121404 -1.011893 -0.8497238 0.2060257 -0.8278709 -0.2318445 0.8686792
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.1749423 -0.3963533 2.477459 1.225845 0.7746927 -1.852358 0.8624045
[2,] -0.1749423 -0.3963533 2.477459 1.225845 0.7746927 -1.852358 0.8624045
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -1.13595 0.5743875 0.01210241 0.7098085 -0.1550757 -0.7247319 -1.211992
[2,] -1.13595 0.5743875 0.01210241 0.7098085 -0.1550757 -0.7247319 -1.211992
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -1.360688 0.09418795 2.269529 -0.8583881 -0.2604673 -1.838319 -0.09765756
[2,] -1.360688 0.09418795 2.269529 -0.8583881 -0.2604673 -1.838319 -0.09765756
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.2027053 -0.01464311 0.7530885 0.2580529 -1.935154 -0.4930816 0.7616512
[2,] 0.2027053 -0.01464311 0.7530885 0.2580529 -1.935154 -0.4930816 0.7616512
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.724341 -1.987076 -0.2898454 1.910585 0.5459277 0.5868138 -1.694837
[2,] -1.724341 -1.987076 -0.2898454 1.910585 0.5459277 0.5868138 -1.694837
[,99] [,100]
[1,] -0.3077117 1.870455
[2,] -0.3077117 1.870455
>
>
> Max(tmp2)
[1] 1.975245
> Min(tmp2)
[1] -2.267979
> mean(tmp2)
[1] 0.08935099
> Sum(tmp2)
[1] 8.935099
> Var(tmp2)
[1] 1.042289
>
> rowMeans(tmp2)
[1] 1.403046082 0.178441267 1.707778301 -0.967506004 1.355715940
[6] 0.409321184 1.322220596 -0.332339757 0.743848333 1.639937910
[11] -0.377571717 0.239189124 0.709952335 0.132746773 -0.493132312
[16] -0.099626725 0.218827107 -0.269608514 -0.218182025 1.718713833
[21] 0.800205461 0.819620376 -0.486160908 0.550710094 -1.991507092
[26] -0.639299897 -1.587605241 -0.726509596 0.431077326 -1.278714756
[31] -0.251328661 1.197644299 0.505337174 -1.179572864 -0.664518868
[36] 0.335052514 1.784656954 1.485657342 -0.124508032 -1.682808511
[41] 1.305740654 0.941206301 0.459109749 0.600744330 0.944716301
[46] -1.579805600 -1.087065449 -0.474149682 -0.968877270 -0.123700882
[51] -0.376733977 1.159109735 0.825621570 -0.381196423 -1.389983414
[56] 0.925887776 1.165466161 0.727081846 -1.727144399 1.975244626
[61] 1.928346181 0.575582238 0.042070980 -0.266080565 -0.084132321
[66] -0.389639431 -0.955733325 0.402549406 1.378417100 -0.476321876
[71] 1.178302265 -1.913647182 -2.267979133 0.986990311 -0.747147975
[76] 0.171588079 0.652269148 1.642528850 -0.001225337 -0.986457466
[81] -0.264090984 -1.384393741 -1.852622561 -0.422824213 -0.492036762
[86] -0.035232913 -0.346437574 -0.489586036 -1.579411513 1.590829303
[91] 1.445719501 0.448532449 -0.802427529 1.363288591 0.107999126
[96] -0.448698524 0.516756337 0.834429927 -0.116986500 0.751541777
> rowSums(tmp2)
[1] 1.403046082 0.178441267 1.707778301 -0.967506004 1.355715940
[6] 0.409321184 1.322220596 -0.332339757 0.743848333 1.639937910
[11] -0.377571717 0.239189124 0.709952335 0.132746773 -0.493132312
[16] -0.099626725 0.218827107 -0.269608514 -0.218182025 1.718713833
[21] 0.800205461 0.819620376 -0.486160908 0.550710094 -1.991507092
[26] -0.639299897 -1.587605241 -0.726509596 0.431077326 -1.278714756
[31] -0.251328661 1.197644299 0.505337174 -1.179572864 -0.664518868
[36] 0.335052514 1.784656954 1.485657342 -0.124508032 -1.682808511
[41] 1.305740654 0.941206301 0.459109749 0.600744330 0.944716301
[46] -1.579805600 -1.087065449 -0.474149682 -0.968877270 -0.123700882
[51] -0.376733977 1.159109735 0.825621570 -0.381196423 -1.389983414
[56] 0.925887776 1.165466161 0.727081846 -1.727144399 1.975244626
[61] 1.928346181 0.575582238 0.042070980 -0.266080565 -0.084132321
[66] -0.389639431 -0.955733325 0.402549406 1.378417100 -0.476321876
[71] 1.178302265 -1.913647182 -2.267979133 0.986990311 -0.747147975
[76] 0.171588079 0.652269148 1.642528850 -0.001225337 -0.986457466
[81] -0.264090984 -1.384393741 -1.852622561 -0.422824213 -0.492036762
[86] -0.035232913 -0.346437574 -0.489586036 -1.579411513 1.590829303
[91] 1.445719501 0.448532449 -0.802427529 1.363288591 0.107999126
[96] -0.448698524 0.516756337 0.834429927 -0.116986500 0.751541777
> 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] 1.403046082 0.178441267 1.707778301 -0.967506004 1.355715940
[6] 0.409321184 1.322220596 -0.332339757 0.743848333 1.639937910
[11] -0.377571717 0.239189124 0.709952335 0.132746773 -0.493132312
[16] -0.099626725 0.218827107 -0.269608514 -0.218182025 1.718713833
[21] 0.800205461 0.819620376 -0.486160908 0.550710094 -1.991507092
[26] -0.639299897 -1.587605241 -0.726509596 0.431077326 -1.278714756
[31] -0.251328661 1.197644299 0.505337174 -1.179572864 -0.664518868
[36] 0.335052514 1.784656954 1.485657342 -0.124508032 -1.682808511
[41] 1.305740654 0.941206301 0.459109749 0.600744330 0.944716301
[46] -1.579805600 -1.087065449 -0.474149682 -0.968877270 -0.123700882
[51] -0.376733977 1.159109735 0.825621570 -0.381196423 -1.389983414
[56] 0.925887776 1.165466161 0.727081846 -1.727144399 1.975244626
[61] 1.928346181 0.575582238 0.042070980 -0.266080565 -0.084132321
[66] -0.389639431 -0.955733325 0.402549406 1.378417100 -0.476321876
[71] 1.178302265 -1.913647182 -2.267979133 0.986990311 -0.747147975
[76] 0.171588079 0.652269148 1.642528850 -0.001225337 -0.986457466
[81] -0.264090984 -1.384393741 -1.852622561 -0.422824213 -0.492036762
[86] -0.035232913 -0.346437574 -0.489586036 -1.579411513 1.590829303
[91] 1.445719501 0.448532449 -0.802427529 1.363288591 0.107999126
[96] -0.448698524 0.516756337 0.834429927 -0.116986500 0.751541777
> rowMin(tmp2)
[1] 1.403046082 0.178441267 1.707778301 -0.967506004 1.355715940
[6] 0.409321184 1.322220596 -0.332339757 0.743848333 1.639937910
[11] -0.377571717 0.239189124 0.709952335 0.132746773 -0.493132312
[16] -0.099626725 0.218827107 -0.269608514 -0.218182025 1.718713833
[21] 0.800205461 0.819620376 -0.486160908 0.550710094 -1.991507092
[26] -0.639299897 -1.587605241 -0.726509596 0.431077326 -1.278714756
[31] -0.251328661 1.197644299 0.505337174 -1.179572864 -0.664518868
[36] 0.335052514 1.784656954 1.485657342 -0.124508032 -1.682808511
[41] 1.305740654 0.941206301 0.459109749 0.600744330 0.944716301
[46] -1.579805600 -1.087065449 -0.474149682 -0.968877270 -0.123700882
[51] -0.376733977 1.159109735 0.825621570 -0.381196423 -1.389983414
[56] 0.925887776 1.165466161 0.727081846 -1.727144399 1.975244626
[61] 1.928346181 0.575582238 0.042070980 -0.266080565 -0.084132321
[66] -0.389639431 -0.955733325 0.402549406 1.378417100 -0.476321876
[71] 1.178302265 -1.913647182 -2.267979133 0.986990311 -0.747147975
[76] 0.171588079 0.652269148 1.642528850 -0.001225337 -0.986457466
[81] -0.264090984 -1.384393741 -1.852622561 -0.422824213 -0.492036762
[86] -0.035232913 -0.346437574 -0.489586036 -1.579411513 1.590829303
[91] 1.445719501 0.448532449 -0.802427529 1.363288591 0.107999126
[96] -0.448698524 0.516756337 0.834429927 -0.116986500 0.751541777
>
> colMeans(tmp2)
[1] 0.08935099
> colSums(tmp2)
[1] 8.935099
> colVars(tmp2)
[1] 1.042289
> colSd(tmp2)
[1] 1.020925
> colMax(tmp2)
[1] 1.975245
> colMin(tmp2)
[1] -2.267979
> colMedians(tmp2)
[1] 0.07503505
> colRanges(tmp2)
[,1]
[1,] -2.267979
[2,] 1.975245
>
> 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] -1.8857709 -0.3722336 3.9068614 -3.8567580 -2.0221038 2.6174029
[7] -2.7369846 3.0262356 3.3226960 -2.8113538
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5617816
[2,] -0.6935025
[3,] -0.3214966
[4,] 0.5374416
[5,] 0.8104190
>
> rowApply(tmp,sum)
[1] 0.9435663 0.6087289 0.3185011 1.0274466 -0.3421251 -3.1344311
[7] 3.0391175 -0.5762061 -0.3372987 -2.3593081
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 7 3 1 3 5 7 4 1 8
[2,] 3 6 10 3 8 3 5 7 2 7
[3,] 9 8 2 8 4 9 8 6 8 4
[4,] 2 4 4 2 9 1 6 9 4 2
[5,] 5 2 5 4 6 7 10 1 6 6
[6,] 8 3 9 5 7 8 2 8 9 5
[7,] 1 1 6 10 1 2 4 10 3 10
[8,] 10 5 1 9 10 4 9 3 5 9
[9,] 6 9 8 7 2 10 3 5 10 1
[10,] 4 10 7 6 5 6 1 2 7 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.7127004 0.1226704 1.4832618 -4.0568084 -3.1870005 -1.6410598
[7] -1.4141026 1.4346452 -0.5192740 1.0558836 3.9934477 1.3702382
[13] -1.5294799 -3.1057251 -1.0976769 -5.2517504 4.0444847 -3.1939857
[19] -0.8297909 1.6064101
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.1591508
[2,] 0.0957332
[3,] 0.3379022
[4,] 0.9124296
[5,] 1.5257862
>
> rowApply(tmp,sum)
[1] -1.0220888 -0.9673229 -8.5198113 3.1806743 -0.6743635
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 10 16 14 18 13
[2,] 15 13 4 20 5
[3,] 13 5 10 8 20
[4,] 1 12 6 15 2
[5,] 8 2 2 14 4
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.1591508 0.71637358 0.388040057 -2.239349 -0.3501826 1.40682979
[2,] 0.9124296 -0.02007457 -0.650987923 -0.201856 -0.7544112 -0.47872884
[3,] 0.0957332 -1.43677541 -0.535900284 -1.173689 -1.8748625 0.09618493
[4,] 1.5257862 2.03028693 0.002742509 1.139657 1.0738679 -0.48505295
[5,] 0.3379022 -1.16714014 2.279367452 -1.581571 -1.2814121 -2.18029273
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.93368012 0.8330759 -2.0174011 1.6490191 0.7871042 -0.6684364
[2,] -0.73364062 0.2234849 -0.5567428 0.9409731 -0.4824542 1.1181876
[3,] -0.40235938 -0.1564645 -0.1399630 0.4985736 1.0975486 0.4297797
[4,] 0.03129941 0.2602790 1.5274594 -0.8827799 1.1483487 0.3203438
[5,] 0.62427814 0.2742699 0.6673735 -1.1499022 1.4429004 0.1703636
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.4256524 -0.1087373 -0.2934360 -0.7392440 0.11547333 -0.6573537
[2,] 0.3577126 1.1974123 -0.5443402 -1.7139007 1.65246025 -0.6952638
[3,] -1.3908167 -2.1004283 1.5677891 -0.8741259 1.60485899 -1.6155327
[4,] -0.2392431 -1.4170106 -2.0410499 -0.8337202 0.03572612 1.1948443
[5,] 0.1685198 -0.6769612 0.2133602 -1.0907596 0.63596601 -1.4206798
[,19] [,20]
[1,] 0.6719956 1.00262300
[2,] -0.2331967 -0.30438554
[3,] -1.1735688 -1.03579276
[4,] -1.2425639 0.03145359
[5,] 1.1475428 1.91251177
>
>
> 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 : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.21-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 -0.2334869 -0.8599856 -0.587991 -0.7561798 1.453613 0.1090329 1.334931
col8 col9 col10 col11 col12 col13 col14
row1 1.900159 -0.08655009 0.7445889 0.2792647 1.290611 0.754313 -1.341285
col15 col16 col17 col18 col19 col20
row1 1.246885 1.470716 0.988699 -0.6457016 0.8904415 0.1149943
> tmp[,"col10"]
col10
row1 0.74458893
row2 0.03864389
row3 -0.41646989
row4 -0.34922999
row5 0.08777797
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.2334869 -0.8599856 -0.587991 -0.7561798 1.453613 0.1090329 1.3349314
row5 -0.7356376 0.5031284 1.379147 0.1232691 -1.547863 -1.1604048 0.8376108
col8 col9 col10 col11 col12 col13 col14
row1 1.9001589 -0.08655009 0.74458893 0.2792647 1.290611 0.7543130 -1.341285
row5 0.3281351 0.05491974 0.08777797 0.3877019 -1.104466 0.1381691 1.310869
col15 col16 col17 col18 col19 col20
row1 1.2468854 1.470716 0.988699 -0.6457016 0.8904415 0.1149943
row5 0.4224672 -1.541517 -1.166196 0.8698054 1.1254409 -0.8637299
> tmp[,c("col6","col20")]
col6 col20
row1 0.1090329 0.1149943
row2 1.6874147 -0.7826550
row3 -0.1141939 1.2875865
row4 0.2876597 -0.7493450
row5 -1.1604048 -0.8637299
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.1090329 0.1149943
row5 -1.1604048 -0.8637299
>
>
>
>
> 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 50.13504 50.98209 48.61225 51.14797 49.9596 105.1603 48.487 50.186
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.16697 48.77683 49.12483 48.34756 50.91561 49.19627 49.10987 49.83564
col17 col18 col19 col20
row1 50.78768 50.64603 50.31029 105.0571
> tmp[,"col10"]
col10
row1 48.77683
row2 31.36956
row3 31.02919
row4 32.11931
row5 50.72791
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.13504 50.98209 48.61225 51.14797 49.95960 105.1603 48.48700 50.1860
row5 50.99557 51.04788 49.53854 48.65162 50.36557 103.5824 49.42529 51.0084
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.16697 48.77683 49.12483 48.34756 50.91561 49.19627 49.10987 49.83564
row5 50.88302 50.72791 48.99012 49.48134 47.86310 51.09562 50.37021 49.98483
col17 col18 col19 col20
row1 50.78768 50.64603 50.31029 105.0571
row5 51.31400 50.13308 49.51394 104.9753
> tmp[,c("col6","col20")]
col6 col20
row1 105.16027 105.05708
row2 73.95848 74.23288
row3 76.45812 74.32072
row4 74.06574 74.22484
row5 103.58237 104.97532
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.1603 105.0571
row5 103.5824 104.9753
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.1603 105.0571
row5 103.5824 104.9753
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.8463690
[2,] -1.3632495
[3,] -0.5579107
[4,] -0.5016597
[5,] 2.4004019
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.7301176 0.3787054
[2,] 0.9343317 -1.3714312
[3,] -0.7927776 -1.1693096
[4,] 0.3875338 -1.8855307
[5,] -1.1238375 -2.0089958
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.9950836 -1.54919248
[2,] -0.4033476 -1.52046657
[3,] -0.5350570 -0.70459063
[4,] -1.4624794 -0.08117247
[5,] 0.3388617 -1.08021248
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.9950836
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.9950836
[2,] -0.4033476
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 0.3207011 -0.05178379 -0.1673461 -2.4059815 -1.808880 0.7074831 0.1966987
row1 -0.4336011 0.06960574 -0.1655998 0.1826182 1.646333 0.7485485 1.6054745
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -0.5116517 0.5830032 0.1402148 -1.031728 -0.8985303 -0.7522393 0.8014604
row1 2.4722655 1.9024077 0.5638982 -1.493849 -0.6820986 1.5583969 0.4060076
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.8969508 -0.2468823 -1.067299 0.6974858 1.6448837 1.491528
row1 -1.2534905 0.3508560 1.443674 1.5252534 -0.3547548 1.908800
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.5497051 0.9474017 -0.245782 -0.1010681 -1.34092 -1.98062 -0.01036289
[,8] [,9] [,10]
row2 0.4299841 -0.9563938 -2.222325
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.2401538 1.377813 -0.2640998 -0.6209687 0.8781445 0.07750027 1.326805
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.904318 -0.5286777 0.5042167 0.3090946 -0.3699216 1.577691 -0.862091
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.222173 -1.913858 -0.1186782 1.05202 -1.139518 -1.485542
>
>
> 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: 0x62d358f95500>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM108a6e7478186b"
[2] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM108a6e777cd836"
[3] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM108a6e2b73c0e0"
[4] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM108a6e6c435195"
[5] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM108a6e44790c20"
[6] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM108a6e80d33de"
[7] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM108a6e307ba01b"
[8] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM108a6e79b2b9c8"
[9] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM108a6e186022aa"
[10] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM108a6e1cbc3755"
[11] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM108a6e16965dac"
[12] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM108a6e1b9f688"
[13] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM108a6e5327f61f"
[14] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM108a6e4c6ca421"
[15] "/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM108a6e5dba266e"
>
>
> ### 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: 0x62d35792d810>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x62d35792d810>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x62d35792d810>
> rowMedians(tmp)
[1] 0.131611198 -0.598770661 0.144083483 0.048488707 -0.414761414
[6] 0.321176901 0.192338931 -0.670029102 -0.108916355 0.276260722
[11] -0.730670851 -0.395412523 0.337891083 -0.552365346 -0.629729242
[16] 0.048215862 -0.347430812 -0.164111157 -0.335187078 0.112640371
[21] -0.232341520 0.239829739 -0.305835441 0.160375647 -0.293060003
[26] -0.473637232 0.250230925 0.597876937 0.171268607 -0.173813823
[31] -0.411531197 -0.512844719 0.181571279 -0.684641953 0.189230826
[36] -0.264933736 -0.012870477 -0.201162167 -0.186716431 0.228966381
[41] -0.477270050 -0.474139061 -0.464132960 -0.616035973 0.343853593
[46] -0.374667160 0.141137440 0.070868522 0.340163963 0.385510044
[51] -0.409212550 0.214319464 -0.260691908 0.492060718 0.025529507
[56] 0.213804022 0.236381701 0.745670570 -0.048991761 0.013838257
[61] -0.447873593 -0.432406770 -0.156425725 0.246748604 -0.039022203
[66] 0.688198265 0.171011323 0.054770883 0.115952843 -0.391352834
[71] 0.310643995 -0.125677517 -0.079466164 -0.412138869 -0.136578376
[76] -0.205389281 -0.757880499 0.140639840 -0.152588952 -0.016817405
[81] -0.196307873 -0.020312671 -0.275384217 -0.279247191 0.163319747
[86] 0.084892853 -0.090007225 -0.527056110 -0.286909386 -0.283068729
[91] 0.169221921 0.318015422 0.149465658 -0.141969361 0.024481473
[96] -0.310495611 0.027335397 -0.201725470 -0.067244945 0.237836498
[101] 0.574012993 -0.399667019 0.095298924 -0.206382389 0.064519337
[106] -0.032821166 -0.397920745 0.210794187 -0.348847740 0.217076000
[111] -0.200096684 0.005860402 -0.108266959 0.263025521 -0.236916198
[116] 0.365361508 0.272191629 -0.227790784 -0.127644107 0.160643067
[121] 0.198304835 0.263648273 -0.318545146 -0.288329900 -0.178776735
[126] -0.178629130 -0.043513155 -0.052595662 0.385716457 0.422630118
[131] 0.570933819 -0.181089871 -0.106298875 0.042573565 0.160379422
[136] -0.340644630 -0.792414600 -0.587257001 0.114534776 0.049983421
[141] 0.297373969 0.262864042 -0.234294794 -0.093228259 0.120634854
[146] -0.190085657 -0.353410131 -0.400284724 -0.910041039 0.005753620
[151] 0.500305074 -0.318968805 -0.107826495 0.012667449 0.069378375
[156] -0.391209639 0.117732599 -0.397241021 -0.296282026 0.015486026
[161] 0.214337352 0.212755611 0.453369781 0.447259852 0.355505262
[166] 0.439583507 0.084569710 0.231939349 0.200254577 -0.121050056
[171] -0.193983875 -0.278569274 0.239581304 0.028785967 -0.115160188
[176] 0.324635399 -0.130957026 -0.183126694 -0.229110382 0.049220784
[181] -0.093142253 0.743357587 -0.270295539 -0.335685270 -0.063536926
[186] 0.085965828 0.202011855 0.133778677 0.658753478 0.232750534
[191] 0.120574574 -0.262817038 -0.608791439 0.010824217 0.317774628
[196] -0.238902155 0.409437535 0.279487593 0.007667462 -0.594724215
[201] -0.341564990 -0.253563203 -0.038164209 -0.378792147 -0.084937630
[206] 0.217988140 0.218969768 -0.205735014 0.298694420 0.070557873
[211] -0.248575001 0.517780805 0.169706070 0.339353168 0.395508520
[216] 0.141084499 -0.325056411 -0.100219466 0.362834912 0.452852111
[221] 0.077128577 0.403155187 -0.403214153 -0.345671669 -0.259887221
[226] 0.622216165 0.877420669 -0.043695377 -0.028105683 0.172339105
>
> proc.time()
user system elapsed
1.382 1.502 2.863
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2025-01-20 r87609) -- "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: 0x5cea042893e0>
> .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: 0x5cea042893e0>
> .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: 0x5cea042893e0>
> .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: 0x5cea042893e0>
> 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: 0x5cea03f9f280>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5cea03f9f280>
> .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: 0x5cea03f9f280>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5cea03f9f280>
> .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: 0x5cea03f9f280>
> 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: 0x5cea04ba1b90>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5cea04ba1b90>
> .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: 0x5cea04ba1b90>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5cea04ba1b90>
> .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: 0x5cea04ba1b90>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5cea04ba1b90>
> .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: 0x5cea04ba1b90>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5cea04ba1b90>
> .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: 0x5cea04ba1b90>
> 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: 0x5cea03bb72d0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5cea03bb72d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5cea03bb72d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5cea03bb72d0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile108b6e2f4866c8" "BufferedMatrixFile108b6e5c359549"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile108b6e2f4866c8" "BufferedMatrixFile108b6e5c359549"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5cea05255cc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5cea05255cc0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5cea05255cc0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5cea05255cc0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5cea05255cc0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5cea05255cc0>
> .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: 0x5cea05f5bab0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5cea05f5bab0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5cea05f5bab0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5cea05f5bab0>
> 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: 0x5cea069210c0>
> .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: 0x5cea069210c0>
> rm(P)
>
> proc.time()
user system elapsed
0.247 0.062 0.296
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-01-20 r87609) -- "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
0.260 0.037 0.285