Ben Bolstad
| Snapshot Date: 2024-06-30 14:00 -0400 (Sun, 30 Jun 2024) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_19 |
| git_last_commit: af6c73d |
| git_last_commit_date: 2024-04-30 10:16:21 -0400 (Tue, 30 Apr 2024) |
| Back to Multiple platform build/check report for BioC 3.19: simplified long |
|
This page was generated on 2024-07-03 10:18 -0400 (Wed, 03 Jul 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4757 |
| palomino7 | Windows Server 2022 Datacenter | x64 | 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life" | 4480 |
| merida1 | macOS 12.7.4 Monterey | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4511 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4469 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 249/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.68.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | |||||||||
| merida1 | macOS 12.7.4 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.68.0 |
| Command: /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings BufferedMatrix_1.68.0.tar.gz |
| StartedAt: 2024-06-30 21:14:46 -0400 (Sun, 30 Jun 2024) |
| EndedAt: 2024-06-30 21:15:10 -0400 (Sun, 30 Jun 2024) |
| EllapsedTime: 24.1 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings BufferedMatrix_1.68.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.0 (2024-04-24)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
* running under: Ubuntu 22.04.4 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.68.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.19-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
gcc -I"/home/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
gcc -I"/home/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"/home/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c init_package.c -o init_package.o
gcc -shared -L/home/biocbuild/bbs-3.19-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.19-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.19-bioc/R/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.248 0.056 0.293
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 471778 25.2 1026221 54.9 643431 34.4
Vcells 871899 6.7 8388608 64.0 2046580 15.7
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Sun Jun 30 21:15:01 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Sun Jun 30 21:15:01 2024"
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
>
>
> RowMode(tmp2)
<pointer: 0x5595eb9a9440>
>
>
>
> 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] "Sun Jun 30 21:15:02 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Sun Jun 30 21:15:02 2024"
>
> ColMode(tmp2)
<pointer: 0x5595eb9a9440>
>
>
>
> ### 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,] 99.163838 0.3804326 0.14920215 1.2418156
[2,] 1.539730 -0.3096129 0.19805145 0.6521751
[3,] -1.181386 -1.2909690 0.08562591 1.1394486
[4,] -1.346457 2.2630236 -0.41136688 -1.3438113
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.163838 0.3804326 0.14920215 1.2418156
[2,] 1.539730 0.3096129 0.19805145 0.6521751
[3,] 1.181386 1.2909690 0.08562591 1.1394486
[4,] 1.346457 2.2630236 0.41136688 1.3438113
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.958104 0.6167922 0.3862669 1.1143678
[2,] 1.240858 0.5564287 0.4450297 0.8075736
[3,] 1.086916 1.1362081 0.2926190 1.0674496
[4,] 1.160369 1.5043349 0.6413789 1.1592287
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 223.74488 31.54835 29.01187 37.38549
[2,] 38.94831 30.87390 29.64835 33.72791
[3,] 37.05054 37.65305 28.01182 36.81394
[4,] 37.95015 42.30637 31.82516 37.93610
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5595eb51b3b0>
> exp(tmp5)
<pointer: 0x5595eb51b3b0>
> log(tmp5,2)
<pointer: 0x5595eb51b3b0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 465.6957
> Min(tmp5)
[1] 54.33714
> mean(tmp5)
[1] 72.88778
> Sum(tmp5)
[1] 14577.56
> Var(tmp5)
[1] 846.759
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.43319 71.43744 70.05452 72.05092 70.19677 69.92816 71.38696 72.16493
[9] 71.85982 69.36510
> rowSums(tmp5)
[1] 1808.664 1428.749 1401.090 1441.018 1403.935 1398.563 1427.739 1443.299
[9] 1437.196 1387.302
> rowVars(tmp5)
[1] 7860.04141 88.26349 53.66108 72.93377 46.30640 104.82039
[7] 66.04688 68.51801 61.79417 76.91692
> rowSd(tmp5)
[1] 88.656875 9.394865 7.325372 8.540127 6.804881 10.238183 8.126923
[8] 8.277561 7.860927 8.770229
> rowMax(tmp5)
[1] 465.69565 93.38212 78.91290 88.05517 87.38248 90.85023 87.01757
[8] 85.42943 84.23229 86.75168
> rowMin(tmp5)
[1] 57.38162 59.01002 56.00296 56.85133 58.50042 54.33714 61.60718 60.10253
[9] 54.77520 55.46916
>
> colMeans(tmp5)
[1] 117.45257 73.86909 67.85127 73.41631 66.67944 62.77425 70.27163
[8] 74.04619 75.71165 68.89794 65.53652 69.66098 70.72016 71.02171
[15] 71.40011 72.56117 73.53628 75.03390 68.25247 69.06201
> colSums(tmp5)
[1] 1174.5257 738.6909 678.5127 734.1631 666.7944 627.7425 702.7163
[8] 740.4619 757.1165 688.9794 655.3652 696.6098 707.2016 710.2171
[15] 714.0011 725.6117 735.3628 750.3390 682.5247 690.6201
> colVars(tmp5)
[1] 14990.22544 88.23451 76.93644 78.54017 22.41558 28.48736
[7] 73.85410 41.03888 94.38899 72.01855 36.75495 34.06159
[13] 61.88908 26.66599 75.01747 105.49804 54.52355 78.95119
[19] 90.68904 35.21467
> colSd(tmp5)
[1] 122.434576 9.393323 8.771342 8.862289 4.734510 5.337355
[7] 8.593841 6.406159 9.715400 8.486374 6.062586 5.836231
[13] 7.866962 5.163913 8.661262 10.271224 7.384006 8.885448
[19] 9.523079 5.934195
> colMax(tmp5)
[1] 465.69565 88.05517 84.23229 90.85023 73.42849 72.51879 82.68585
[8] 82.51100 93.38212 86.04185 76.22089 80.39093 81.13283 77.36340
[15] 86.75168 85.42943 88.50197 87.01757 83.83693 81.85715
> colMin(tmp5)
[1] 73.69074 60.55079 58.30293 60.70791 60.56069 55.46916 56.85133 63.39078
[9] 61.01332 62.21191 58.46570 59.21163 54.77520 59.53692 59.58384 54.33714
[17] 65.62892 59.30411 55.73541 62.38365
>
>
> ### 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] 90.43319 NA 70.05452 72.05092 70.19677 69.92816 71.38696 72.16493
[9] 71.85982 69.36510
> rowSums(tmp5)
[1] 1808.664 NA 1401.090 1441.018 1403.935 1398.563 1427.739 1443.299
[9] 1437.196 1387.302
> rowVars(tmp5)
[1] 7860.04141 88.69710 53.66108 72.93377 46.30640 104.82039
[7] 66.04688 68.51801 61.79417 76.91692
> rowSd(tmp5)
[1] 88.656875 9.417914 7.325372 8.540127 6.804881 10.238183 8.126923
[8] 8.277561 7.860927 8.770229
> rowMax(tmp5)
[1] 465.69565 NA 78.91290 88.05517 87.38248 90.85023 87.01757
[8] 85.42943 84.23229 86.75168
> rowMin(tmp5)
[1] 57.38162 NA 56.00296 56.85133 58.50042 54.33714 61.60718 60.10253
[9] 54.77520 55.46916
>
> colMeans(tmp5)
[1] 117.45257 73.86909 67.85127 73.41631 66.67944 62.77425 70.27163
[8] 74.04619 75.71165 68.89794 65.53652 69.66098 70.72016 71.02171
[15] NA 72.56117 73.53628 75.03390 68.25247 69.06201
> colSums(tmp5)
[1] 1174.5257 738.6909 678.5127 734.1631 666.7944 627.7425 702.7163
[8] 740.4619 757.1165 688.9794 655.3652 696.6098 707.2016 710.2171
[15] NA 725.6117 735.3628 750.3390 682.5247 690.6201
> colVars(tmp5)
[1] 14990.22544 88.23451 76.93644 78.54017 22.41558 28.48736
[7] 73.85410 41.03888 94.38899 72.01855 36.75495 34.06159
[13] 61.88908 26.66599 NA 105.49804 54.52355 78.95119
[19] 90.68904 35.21467
> colSd(tmp5)
[1] 122.434576 9.393323 8.771342 8.862289 4.734510 5.337355
[7] 8.593841 6.406159 9.715400 8.486374 6.062586 5.836231
[13] 7.866962 5.163913 NA 10.271224 7.384006 8.885448
[19] 9.523079 5.934195
> colMax(tmp5)
[1] 465.69565 88.05517 84.23229 90.85023 73.42849 72.51879 82.68585
[8] 82.51100 93.38212 86.04185 76.22089 80.39093 81.13283 77.36340
[15] NA 85.42943 88.50197 87.01757 83.83693 81.85715
> colMin(tmp5)
[1] 73.69074 60.55079 58.30293 60.70791 60.56069 55.46916 56.85133 63.39078
[9] 61.01332 62.21191 58.46570 59.21163 54.77520 59.53692 NA 54.33714
[17] 65.62892 59.30411 55.73541 62.38365
>
> Max(tmp5,na.rm=TRUE)
[1] 465.6957
> Min(tmp5,na.rm=TRUE)
[1] 54.33714
> mean(tmp5,na.rm=TRUE)
[1] 72.85114
> Sum(tmp5,na.rm=TRUE)
[1] 14497.38
> Var(tmp5,na.rm=TRUE)
[1] 850.7656
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.43319 70.97730 70.05452 72.05092 70.19677 69.92816 71.38696 72.16493
[9] 71.85982 69.36510
> rowSums(tmp5,na.rm=TRUE)
[1] 1808.664 1348.569 1401.090 1441.018 1403.935 1398.563 1427.739 1443.299
[9] 1437.196 1387.302
> rowVars(tmp5,na.rm=TRUE)
[1] 7860.04141 88.69710 53.66108 72.93377 46.30640 104.82039
[7] 66.04688 68.51801 61.79417 76.91692
> rowSd(tmp5,na.rm=TRUE)
[1] 88.656875 9.417914 7.325372 8.540127 6.804881 10.238183 8.126923
[8] 8.277561 7.860927 8.770229
> rowMax(tmp5,na.rm=TRUE)
[1] 465.69565 93.38212 78.91290 88.05517 87.38248 90.85023 87.01757
[8] 85.42943 84.23229 86.75168
> rowMin(tmp5,na.rm=TRUE)
[1] 57.38162 59.01002 56.00296 56.85133 58.50042 54.33714 61.60718 60.10253
[9] 54.77520 55.46916
>
> colMeans(tmp5,na.rm=TRUE)
[1] 117.45257 73.86909 67.85127 73.41631 66.67944 62.77425 70.27163
[8] 74.04619 75.71165 68.89794 65.53652 69.66098 70.72016 71.02171
[15] 70.42455 72.56117 73.53628 75.03390 68.25247 69.06201
> colSums(tmp5,na.rm=TRUE)
[1] 1174.5257 738.6909 678.5127 734.1631 666.7944 627.7425 702.7163
[8] 740.4619 757.1165 688.9794 655.3652 696.6098 707.2016 710.2171
[15] 633.8209 725.6117 735.3628 750.3390 682.5247 690.6201
> colVars(tmp5,na.rm=TRUE)
[1] 14990.22544 88.23451 76.93644 78.54017 22.41558 28.48736
[7] 73.85410 41.03888 94.38899 72.01855 36.75495 34.06159
[13] 61.88908 26.66599 73.68774 105.49804 54.52355 78.95119
[19] 90.68904 35.21467
> colSd(tmp5,na.rm=TRUE)
[1] 122.434576 9.393323 8.771342 8.862289 4.734510 5.337355
[7] 8.593841 6.406159 9.715400 8.486374 6.062586 5.836231
[13] 7.866962 5.163913 8.584157 10.271224 7.384006 8.885448
[19] 9.523079 5.934195
> colMax(tmp5,na.rm=TRUE)
[1] 465.69565 88.05517 84.23229 90.85023 73.42849 72.51879 82.68585
[8] 82.51100 93.38212 86.04185 76.22089 80.39093 81.13283 77.36340
[15] 86.75168 85.42943 88.50197 87.01757 83.83693 81.85715
> colMin(tmp5,na.rm=TRUE)
[1] 73.69074 60.55079 58.30293 60.70791 60.56069 55.46916 56.85133 63.39078
[9] 61.01332 62.21191 58.46570 59.21163 54.77520 59.53692 59.58384 54.33714
[17] 65.62892 59.30411 55.73541 62.38365
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.43319 NaN 70.05452 72.05092 70.19677 69.92816 71.38696 72.16493
[9] 71.85982 69.36510
> rowSums(tmp5,na.rm=TRUE)
[1] 1808.664 0.000 1401.090 1441.018 1403.935 1398.563 1427.739 1443.299
[9] 1437.196 1387.302
> rowVars(tmp5,na.rm=TRUE)
[1] 7860.04141 NA 53.66108 72.93377 46.30640 104.82039
[7] 66.04688 68.51801 61.79417 76.91692
> rowSd(tmp5,na.rm=TRUE)
[1] 88.656875 NA 7.325372 8.540127 6.804881 10.238183 8.126923
[8] 8.277561 7.860927 8.770229
> rowMax(tmp5,na.rm=TRUE)
[1] 465.69565 NA 78.91290 88.05517 87.38248 90.85023 87.01757
[8] 85.42943 84.23229 86.75168
> rowMin(tmp5,na.rm=TRUE)
[1] 57.38162 NA 56.00296 56.85133 58.50042 54.33714 61.60718 60.10253
[9] 54.77520 55.46916
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 121.49554 74.93677 68.53372 73.77366 66.14651 62.93722 68.89227
[8] 73.64994 73.74826 69.64083 66.26169 69.81677 71.12115 71.49083
[15] NaN 73.26685 73.77438 74.41195 69.01540 67.64032
> colSums(tmp5,na.rm=TRUE)
[1] 1093.4599 674.4309 616.8035 663.9629 595.3186 566.4349 620.0304
[8] 662.8494 663.7344 626.7675 596.3552 628.3509 640.0903 643.4175
[15] 0.0000 659.4017 663.9695 669.7076 621.1386 608.7629
> colVars(tmp5,na.rm=TRUE)
[1] 16680.11530 86.43951 81.31384 86.92113 22.02233 31.74951
[7] 61.68128 44.40230 62.82019 74.81212 35.43332 38.04622
[13] 67.81637 27.52334 NA 113.08290 60.70117 84.46837
[19] 95.47704 16.87822
> colSd(tmp5,na.rm=TRUE)
[1] 129.151521 9.297285 9.017419 9.323150 4.692796 5.634671
[7] 7.853743 6.663505 7.925919 8.649400 5.952589 6.168162
[13] 8.235069 5.246270 NA 10.634044 7.791096 9.190668
[19] 9.771235 4.108311
> colMax(tmp5,na.rm=TRUE)
[1] 465.69565 88.05517 84.23229 90.85023 73.42849 72.51879 80.78400
[8] 82.51100 84.65975 86.04185 76.22089 80.39093 81.13283 77.36340
[15] -Inf 85.42943 88.50197 87.01757 83.83693 74.30666
> colMin(tmp5,na.rm=TRUE)
[1] 73.69074 60.55079 58.30293 60.70791 60.56069 55.46916 56.85133 63.39078
[9] 61.01332 62.31672 58.46570 59.21163 54.77520 59.53692 Inf 54.33714
[17] 65.62892 59.30411 55.73541 62.38365
>
>
>
>
> 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] 179.4518 109.0552 219.9164 187.7403 277.8258 224.1523 171.1520 216.8638
[9] 151.7684 218.8988
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 179.4518 109.0552 219.9164 187.7403 277.8258 224.1523 171.1520 216.8638
[9] 151.7684 218.8988
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -1.421085e-14 -2.842171e-14 -5.684342e-14 -5.684342e-14 -1.136868e-13
[6] 5.684342e-14 5.684342e-14 5.684342e-14 -1.705303e-13 -1.136868e-13
[11] 1.136868e-13 1.136868e-13 -1.136868e-13 -1.136868e-13 -2.842171e-14
[16] 5.684342e-14 -8.526513e-14 2.273737e-13 1.705303e-13 4.973799e-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 12
9 18
8 20
4 10
4 13
1 1
9 8
8 15
5 16
10 9
7 16
5 17
9 2
6 14
1 3
6 9
1 1
10 10
9 4
7 16
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 3.166586
> Min(tmp)
[1] -2.182434
> mean(tmp)
[1] 0.1120749
> Sum(tmp)
[1] 11.20749
> Var(tmp)
[1] 1.129961
>
> rowMeans(tmp)
[1] 0.1120749
> rowSums(tmp)
[1] 11.20749
> rowVars(tmp)
[1] 1.129961
> rowSd(tmp)
[1] 1.062996
> rowMax(tmp)
[1] 3.166586
> rowMin(tmp)
[1] -2.182434
>
> colMeans(tmp)
[1] 1.03992254 3.16658620 -0.26189376 -0.68306440 0.95964764 -0.69915181
[7] -0.51954455 0.45833938 -0.11969831 1.24485619 1.47014413 0.46391159
[13] 0.73560543 -0.78658468 0.57308733 0.36237421 -1.00856861 -0.74910938
[19] -1.93042655 -0.66930054 -1.18880915 1.76240324 -0.59291539 -1.15059139
[25] -1.41213622 0.53069495 -0.23819409 -0.70836277 0.39196362 -0.55690697
[31] 1.52960783 -1.36607001 0.07243179 -0.29105247 -0.23203821 2.47281515
[37] 1.70256713 0.74154396 0.42439400 1.00040871 -0.67846006 -1.50053948
[43] -0.24908791 -0.93742565 1.51511393 -0.62570105 -0.86202723 -0.30142133
[49] 0.77948839 -0.20896927 -0.44832142 -1.01124828 -1.23770260 0.54177228
[55] 0.69265777 0.14978555 -0.69756255 0.58102244 0.32661377 -0.68173152
[61] 1.17760344 0.73513594 -1.41430722 1.54887173 0.85247544 -2.18243439
[67] 1.78873997 -0.04774794 -0.33613882 1.73927458 0.64607127 0.04973618
[73] 1.48918208 -0.45675166 1.61584865 1.23847329 0.34400414 0.90307138
[79] 0.22384703 -0.72330793 0.55978104 0.18605584 -0.61274872 -0.37885339
[85] -0.89007228 2.78376535 1.11020756 -2.15134855 -1.76658360 0.03207923
[91] 1.43103774 -0.18854134 0.01770751 0.87463302 0.27667087 0.02107801
[97] -0.64653531 -1.15773589 1.00205728 0.42804516
> colSums(tmp)
[1] 1.03992254 3.16658620 -0.26189376 -0.68306440 0.95964764 -0.69915181
[7] -0.51954455 0.45833938 -0.11969831 1.24485619 1.47014413 0.46391159
[13] 0.73560543 -0.78658468 0.57308733 0.36237421 -1.00856861 -0.74910938
[19] -1.93042655 -0.66930054 -1.18880915 1.76240324 -0.59291539 -1.15059139
[25] -1.41213622 0.53069495 -0.23819409 -0.70836277 0.39196362 -0.55690697
[31] 1.52960783 -1.36607001 0.07243179 -0.29105247 -0.23203821 2.47281515
[37] 1.70256713 0.74154396 0.42439400 1.00040871 -0.67846006 -1.50053948
[43] -0.24908791 -0.93742565 1.51511393 -0.62570105 -0.86202723 -0.30142133
[49] 0.77948839 -0.20896927 -0.44832142 -1.01124828 -1.23770260 0.54177228
[55] 0.69265777 0.14978555 -0.69756255 0.58102244 0.32661377 -0.68173152
[61] 1.17760344 0.73513594 -1.41430722 1.54887173 0.85247544 -2.18243439
[67] 1.78873997 -0.04774794 -0.33613882 1.73927458 0.64607127 0.04973618
[73] 1.48918208 -0.45675166 1.61584865 1.23847329 0.34400414 0.90307138
[79] 0.22384703 -0.72330793 0.55978104 0.18605584 -0.61274872 -0.37885339
[85] -0.89007228 2.78376535 1.11020756 -2.15134855 -1.76658360 0.03207923
[91] 1.43103774 -0.18854134 0.01770751 0.87463302 0.27667087 0.02107801
[97] -0.64653531 -1.15773589 1.00205728 0.42804516
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] 1.03992254 3.16658620 -0.26189376 -0.68306440 0.95964764 -0.69915181
[7] -0.51954455 0.45833938 -0.11969831 1.24485619 1.47014413 0.46391159
[13] 0.73560543 -0.78658468 0.57308733 0.36237421 -1.00856861 -0.74910938
[19] -1.93042655 -0.66930054 -1.18880915 1.76240324 -0.59291539 -1.15059139
[25] -1.41213622 0.53069495 -0.23819409 -0.70836277 0.39196362 -0.55690697
[31] 1.52960783 -1.36607001 0.07243179 -0.29105247 -0.23203821 2.47281515
[37] 1.70256713 0.74154396 0.42439400 1.00040871 -0.67846006 -1.50053948
[43] -0.24908791 -0.93742565 1.51511393 -0.62570105 -0.86202723 -0.30142133
[49] 0.77948839 -0.20896927 -0.44832142 -1.01124828 -1.23770260 0.54177228
[55] 0.69265777 0.14978555 -0.69756255 0.58102244 0.32661377 -0.68173152
[61] 1.17760344 0.73513594 -1.41430722 1.54887173 0.85247544 -2.18243439
[67] 1.78873997 -0.04774794 -0.33613882 1.73927458 0.64607127 0.04973618
[73] 1.48918208 -0.45675166 1.61584865 1.23847329 0.34400414 0.90307138
[79] 0.22384703 -0.72330793 0.55978104 0.18605584 -0.61274872 -0.37885339
[85] -0.89007228 2.78376535 1.11020756 -2.15134855 -1.76658360 0.03207923
[91] 1.43103774 -0.18854134 0.01770751 0.87463302 0.27667087 0.02107801
[97] -0.64653531 -1.15773589 1.00205728 0.42804516
> colMin(tmp)
[1] 1.03992254 3.16658620 -0.26189376 -0.68306440 0.95964764 -0.69915181
[7] -0.51954455 0.45833938 -0.11969831 1.24485619 1.47014413 0.46391159
[13] 0.73560543 -0.78658468 0.57308733 0.36237421 -1.00856861 -0.74910938
[19] -1.93042655 -0.66930054 -1.18880915 1.76240324 -0.59291539 -1.15059139
[25] -1.41213622 0.53069495 -0.23819409 -0.70836277 0.39196362 -0.55690697
[31] 1.52960783 -1.36607001 0.07243179 -0.29105247 -0.23203821 2.47281515
[37] 1.70256713 0.74154396 0.42439400 1.00040871 -0.67846006 -1.50053948
[43] -0.24908791 -0.93742565 1.51511393 -0.62570105 -0.86202723 -0.30142133
[49] 0.77948839 -0.20896927 -0.44832142 -1.01124828 -1.23770260 0.54177228
[55] 0.69265777 0.14978555 -0.69756255 0.58102244 0.32661377 -0.68173152
[61] 1.17760344 0.73513594 -1.41430722 1.54887173 0.85247544 -2.18243439
[67] 1.78873997 -0.04774794 -0.33613882 1.73927458 0.64607127 0.04973618
[73] 1.48918208 -0.45675166 1.61584865 1.23847329 0.34400414 0.90307138
[79] 0.22384703 -0.72330793 0.55978104 0.18605584 -0.61274872 -0.37885339
[85] -0.89007228 2.78376535 1.11020756 -2.15134855 -1.76658360 0.03207923
[91] 1.43103774 -0.18854134 0.01770751 0.87463302 0.27667087 0.02107801
[97] -0.64653531 -1.15773589 1.00205728 0.42804516
> colMedians(tmp)
[1] 1.03992254 3.16658620 -0.26189376 -0.68306440 0.95964764 -0.69915181
[7] -0.51954455 0.45833938 -0.11969831 1.24485619 1.47014413 0.46391159
[13] 0.73560543 -0.78658468 0.57308733 0.36237421 -1.00856861 -0.74910938
[19] -1.93042655 -0.66930054 -1.18880915 1.76240324 -0.59291539 -1.15059139
[25] -1.41213622 0.53069495 -0.23819409 -0.70836277 0.39196362 -0.55690697
[31] 1.52960783 -1.36607001 0.07243179 -0.29105247 -0.23203821 2.47281515
[37] 1.70256713 0.74154396 0.42439400 1.00040871 -0.67846006 -1.50053948
[43] -0.24908791 -0.93742565 1.51511393 -0.62570105 -0.86202723 -0.30142133
[49] 0.77948839 -0.20896927 -0.44832142 -1.01124828 -1.23770260 0.54177228
[55] 0.69265777 0.14978555 -0.69756255 0.58102244 0.32661377 -0.68173152
[61] 1.17760344 0.73513594 -1.41430722 1.54887173 0.85247544 -2.18243439
[67] 1.78873997 -0.04774794 -0.33613882 1.73927458 0.64607127 0.04973618
[73] 1.48918208 -0.45675166 1.61584865 1.23847329 0.34400414 0.90307138
[79] 0.22384703 -0.72330793 0.55978104 0.18605584 -0.61274872 -0.37885339
[85] -0.89007228 2.78376535 1.11020756 -2.15134855 -1.76658360 0.03207923
[91] 1.43103774 -0.18854134 0.01770751 0.87463302 0.27667087 0.02107801
[97] -0.64653531 -1.15773589 1.00205728 0.42804516
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.039923 3.166586 -0.2618938 -0.6830644 0.9596476 -0.6991518 -0.5195445
[2,] 1.039923 3.166586 -0.2618938 -0.6830644 0.9596476 -0.6991518 -0.5195445
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.4583394 -0.1196983 1.244856 1.470144 0.4639116 0.7356054 -0.7865847
[2,] 0.4583394 -0.1196983 1.244856 1.470144 0.4639116 0.7356054 -0.7865847
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.5730873 0.3623742 -1.008569 -0.7491094 -1.930427 -0.6693005 -1.188809
[2,] 0.5730873 0.3623742 -1.008569 -0.7491094 -1.930427 -0.6693005 -1.188809
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.762403 -0.5929154 -1.150591 -1.412136 0.5306949 -0.2381941 -0.7083628
[2,] 1.762403 -0.5929154 -1.150591 -1.412136 0.5306949 -0.2381941 -0.7083628
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.3919636 -0.556907 1.529608 -1.36607 0.07243179 -0.2910525 -0.2320382
[2,] 0.3919636 -0.556907 1.529608 -1.36607 0.07243179 -0.2910525 -0.2320382
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 2.472815 1.702567 0.741544 0.424394 1.000409 -0.6784601 -1.500539
[2,] 2.472815 1.702567 0.741544 0.424394 1.000409 -0.6784601 -1.500539
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.2490879 -0.9374256 1.515114 -0.625701 -0.8620272 -0.3014213 0.7794884
[2,] -0.2490879 -0.9374256 1.515114 -0.625701 -0.8620272 -0.3014213 0.7794884
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.2089693 -0.4483214 -1.011248 -1.237703 0.5417723 0.6926578 0.1497855
[2,] -0.2089693 -0.4483214 -1.011248 -1.237703 0.5417723 0.6926578 0.1497855
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.6975626 0.5810224 0.3266138 -0.6817315 1.177603 0.7351359 -1.414307
[2,] -0.6975626 0.5810224 0.3266138 -0.6817315 1.177603 0.7351359 -1.414307
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 1.548872 0.8524754 -2.182434 1.78874 -0.04774794 -0.3361388 1.739275
[2,] 1.548872 0.8524754 -2.182434 1.78874 -0.04774794 -0.3361388 1.739275
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.6460713 0.04973618 1.489182 -0.4567517 1.615849 1.238473 0.3440041
[2,] 0.6460713 0.04973618 1.489182 -0.4567517 1.615849 1.238473 0.3440041
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.9030714 0.223847 -0.7233079 0.559781 0.1860558 -0.6127487 -0.3788534
[2,] 0.9030714 0.223847 -0.7233079 0.559781 0.1860558 -0.6127487 -0.3788534
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.8900723 2.783765 1.110208 -2.151349 -1.766584 0.03207923 1.431038
[2,] -0.8900723 2.783765 1.110208 -2.151349 -1.766584 0.03207923 1.431038
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.1885413 0.01770751 0.874633 0.2766709 0.02107801 -0.6465353 -1.157736
[2,] -0.1885413 0.01770751 0.874633 0.2766709 0.02107801 -0.6465353 -1.157736
[,99] [,100]
[1,] 1.002057 0.4280452
[2,] 1.002057 0.4280452
>
>
> Max(tmp2)
[1] 2.614194
> Min(tmp2)
[1] -2.216346
> mean(tmp2)
[1] 0.01112429
> Sum(tmp2)
[1] 1.112429
> Var(tmp2)
[1] 1.117293
>
> rowMeans(tmp2)
[1] 1.33423871 -0.60806152 -0.24190754 -1.26992647 0.68992993 2.50837005
[7] -0.85891902 -0.07787267 -1.40897628 1.75067726 -0.40570483 -0.64679902
[13] 0.69431154 -1.45009593 0.89421999 -0.32452574 -2.21634563 -0.53591177
[19] 0.77158140 -0.41607048 0.19799787 -0.30933251 -0.01076331 0.29746599
[25] 1.48591751 0.98724329 0.87352248 -0.09449257 2.11388494 2.09941578
[31] -0.09732302 -2.02033955 -0.71117874 -0.62085964 0.02363708 -1.72962009
[37] -1.36693093 -0.69884931 -0.90211825 -1.83367550 0.41358043 -0.00194581
[43] -0.06200746 0.29389856 -0.93932628 -0.37160338 0.77514256 -0.16494340
[49] -1.27501896 0.52446429 0.93588984 0.18863562 0.45508489 -0.09042090
[55] 1.48528957 -1.08654139 1.75801977 -0.85550379 -0.36635951 -1.45846419
[61] -0.47532312 -1.32509153 1.39429251 -0.23701862 0.59393675 1.00557028
[67] 1.82204538 0.44537084 -0.47251490 0.15079212 -0.82219427 -0.36005755
[73] 1.74963440 -0.53422099 1.35420155 -0.82135090 -0.77079407 -0.92584448
[79] 0.24781216 -0.22306915 -0.19965111 -1.41786541 -0.07546642 -0.66881044
[85] 0.96956553 -0.06905846 -0.03149163 1.41037894 0.98026750 -1.84781473
[91] -0.03444782 -0.05270418 -1.90110634 1.20730556 1.06704920 -0.36232142
[97] 2.61419384 0.87891079 -0.21619521 1.04183062
> rowSums(tmp2)
[1] 1.33423871 -0.60806152 -0.24190754 -1.26992647 0.68992993 2.50837005
[7] -0.85891902 -0.07787267 -1.40897628 1.75067726 -0.40570483 -0.64679902
[13] 0.69431154 -1.45009593 0.89421999 -0.32452574 -2.21634563 -0.53591177
[19] 0.77158140 -0.41607048 0.19799787 -0.30933251 -0.01076331 0.29746599
[25] 1.48591751 0.98724329 0.87352248 -0.09449257 2.11388494 2.09941578
[31] -0.09732302 -2.02033955 -0.71117874 -0.62085964 0.02363708 -1.72962009
[37] -1.36693093 -0.69884931 -0.90211825 -1.83367550 0.41358043 -0.00194581
[43] -0.06200746 0.29389856 -0.93932628 -0.37160338 0.77514256 -0.16494340
[49] -1.27501896 0.52446429 0.93588984 0.18863562 0.45508489 -0.09042090
[55] 1.48528957 -1.08654139 1.75801977 -0.85550379 -0.36635951 -1.45846419
[61] -0.47532312 -1.32509153 1.39429251 -0.23701862 0.59393675 1.00557028
[67] 1.82204538 0.44537084 -0.47251490 0.15079212 -0.82219427 -0.36005755
[73] 1.74963440 -0.53422099 1.35420155 -0.82135090 -0.77079407 -0.92584448
[79] 0.24781216 -0.22306915 -0.19965111 -1.41786541 -0.07546642 -0.66881044
[85] 0.96956553 -0.06905846 -0.03149163 1.41037894 0.98026750 -1.84781473
[91] -0.03444782 -0.05270418 -1.90110634 1.20730556 1.06704920 -0.36232142
[97] 2.61419384 0.87891079 -0.21619521 1.04183062
> 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] 1.33423871 -0.60806152 -0.24190754 -1.26992647 0.68992993 2.50837005
[7] -0.85891902 -0.07787267 -1.40897628 1.75067726 -0.40570483 -0.64679902
[13] 0.69431154 -1.45009593 0.89421999 -0.32452574 -2.21634563 -0.53591177
[19] 0.77158140 -0.41607048 0.19799787 -0.30933251 -0.01076331 0.29746599
[25] 1.48591751 0.98724329 0.87352248 -0.09449257 2.11388494 2.09941578
[31] -0.09732302 -2.02033955 -0.71117874 -0.62085964 0.02363708 -1.72962009
[37] -1.36693093 -0.69884931 -0.90211825 -1.83367550 0.41358043 -0.00194581
[43] -0.06200746 0.29389856 -0.93932628 -0.37160338 0.77514256 -0.16494340
[49] -1.27501896 0.52446429 0.93588984 0.18863562 0.45508489 -0.09042090
[55] 1.48528957 -1.08654139 1.75801977 -0.85550379 -0.36635951 -1.45846419
[61] -0.47532312 -1.32509153 1.39429251 -0.23701862 0.59393675 1.00557028
[67] 1.82204538 0.44537084 -0.47251490 0.15079212 -0.82219427 -0.36005755
[73] 1.74963440 -0.53422099 1.35420155 -0.82135090 -0.77079407 -0.92584448
[79] 0.24781216 -0.22306915 -0.19965111 -1.41786541 -0.07546642 -0.66881044
[85] 0.96956553 -0.06905846 -0.03149163 1.41037894 0.98026750 -1.84781473
[91] -0.03444782 -0.05270418 -1.90110634 1.20730556 1.06704920 -0.36232142
[97] 2.61419384 0.87891079 -0.21619521 1.04183062
> rowMin(tmp2)
[1] 1.33423871 -0.60806152 -0.24190754 -1.26992647 0.68992993 2.50837005
[7] -0.85891902 -0.07787267 -1.40897628 1.75067726 -0.40570483 -0.64679902
[13] 0.69431154 -1.45009593 0.89421999 -0.32452574 -2.21634563 -0.53591177
[19] 0.77158140 -0.41607048 0.19799787 -0.30933251 -0.01076331 0.29746599
[25] 1.48591751 0.98724329 0.87352248 -0.09449257 2.11388494 2.09941578
[31] -0.09732302 -2.02033955 -0.71117874 -0.62085964 0.02363708 -1.72962009
[37] -1.36693093 -0.69884931 -0.90211825 -1.83367550 0.41358043 -0.00194581
[43] -0.06200746 0.29389856 -0.93932628 -0.37160338 0.77514256 -0.16494340
[49] -1.27501896 0.52446429 0.93588984 0.18863562 0.45508489 -0.09042090
[55] 1.48528957 -1.08654139 1.75801977 -0.85550379 -0.36635951 -1.45846419
[61] -0.47532312 -1.32509153 1.39429251 -0.23701862 0.59393675 1.00557028
[67] 1.82204538 0.44537084 -0.47251490 0.15079212 -0.82219427 -0.36005755
[73] 1.74963440 -0.53422099 1.35420155 -0.82135090 -0.77079407 -0.92584448
[79] 0.24781216 -0.22306915 -0.19965111 -1.41786541 -0.07546642 -0.66881044
[85] 0.96956553 -0.06905846 -0.03149163 1.41037894 0.98026750 -1.84781473
[91] -0.03444782 -0.05270418 -1.90110634 1.20730556 1.06704920 -0.36232142
[97] 2.61419384 0.87891079 -0.21619521 1.04183062
>
> colMeans(tmp2)
[1] 0.01112429
> colSums(tmp2)
[1] 1.112429
> colVars(tmp2)
[1] 1.117293
> colSd(tmp2)
[1] 1.057021
> colMax(tmp2)
[1] 2.614194
> colMin(tmp2)
[1] -2.216346
> colMedians(tmp2)
[1] -0.08414679
> colRanges(tmp2)
[,1]
[1,] -2.216346
[2,] 2.614194
>
> 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] 3.9039550 1.5827621 -1.0308292 0.6171919 -6.9381820 -1.3383680
[7] 1.6469427 2.1231015 3.0107039 5.1881822
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.83897641
[2,] -0.09067582
[3,] 0.51269177
[4,] 1.04933026
[5,] 1.28150505
>
> rowApply(tmp,sum)
[1] -5.3912481 -5.6170870 4.2985182 -3.5532744 3.1971151 4.0954442
[7] 0.3424129 0.4100136 5.2174571 5.7661087
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 8 7 7 4 6 2 10 5 9
[2,] 9 3 1 5 9 9 5 2 4 10
[3,] 4 5 5 9 2 7 9 8 1 5
[4,] 3 6 3 6 7 10 7 4 9 4
[5,] 1 2 4 2 1 2 6 9 2 7
[6,] 2 10 8 3 8 1 1 1 6 2
[7,] 6 1 9 4 6 4 8 5 8 1
[8,] 7 9 10 1 5 3 3 6 3 8
[9,] 10 7 2 10 3 5 10 7 7 3
[10,] 8 4 6 8 10 8 4 3 10 6
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.6860304 3.1857840 6.2604204 1.4701641 -0.9493246 -0.7068901
[7] 0.6897480 1.3463428 2.7102883 -5.9622101 -2.1000266 -0.7897821
[13] 2.4548314 2.3967899 -2.8459640 -1.6404908 -1.3386685 -1.2233244
[19] 4.3008936 1.8651763
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.1240554
[2,] -0.4434626
[3,] -0.2251875
[4,] 0.4652428
[5,] 0.6414322
>
> rowApply(tmp,sum)
[1] -2.9198480 -0.7234648 14.1466618 -2.9126695 -0.1529524
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 11 14 8 2 7
[2,] 6 20 20 14 5
[3,] 14 12 7 18 20
[4,] 7 6 19 20 2
[5,] 8 19 15 1 9
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.2251875 -0.6438061 0.5955780 -0.5229134 -0.47781695 -1.0476118
[2,] 0.4652428 1.5270378 0.1878451 -0.5236805 1.36910012 0.5465290
[3,] 0.6414322 2.6063801 0.5300865 2.1595693 1.27971901 0.7514126
[4,] -2.1240554 0.2840063 1.8799699 2.0092491 -3.03881303 -1.5717160
[5,] -0.4434626 -0.5878342 3.0669409 -1.6520604 -0.08151379 0.6144961
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.50853555 -1.6899931 1.18147606 -1.6414542 -0.13337080 -0.9489256
[2,] -0.15244312 0.8372957 -0.19016925 -1.6147469 0.21046265 -0.2637342
[3,] 0.74638013 0.9550317 1.72980863 -0.8925012 -1.07249305 1.5100302
[4,] 1.64861082 1.5618740 -0.08502711 -0.9488100 -1.06862629 -1.9476551
[5,] -0.04426431 -0.3178654 0.07420001 -0.8646979 -0.03599916 0.8605026
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.6420993 -0.4352809 0.60303676 0.2526766 -0.44589828 0.74769634
[2,] -0.8597452 -0.2051678 -0.56946267 -0.4699796 -0.70672479 -1.75755104
[3,] 1.2334686 0.9523711 0.04237644 -0.8519901 -0.54595817 -0.33777663
[4,] 1.9922689 1.1383655 -1.00954774 -1.4100076 -0.09945938 0.11188710
[5,] -0.5532601 0.9465021 -1.91236674 0.8388100 0.45937211 0.01241983
[,19] [,20]
[1,] 1.35405779 1.4243254
[2,] 0.61586656 0.8305607
[3,] 1.97204798 0.7372666
[4,] -0.09465967 -0.1405239
[5,] 0.45358099 -0.9864526
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 649 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 562 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 1.352387 -1.285214 -1.0255 0.7774224 1.422982 0.2873948 -0.06538262
col8 col9 col10 col11 col12 col13 col14
row1 0.2315229 -0.8059219 -0.4255199 -1.214289 -0.8021182 0.3519962 0.3665567
col15 col16 col17 col18 col19 col20
row1 1.329538 -0.392241 -0.3000654 2.324857 -0.6324762 -0.5623199
> tmp[,"col10"]
col10
row1 -0.4255199
row2 0.3197457
row3 -0.3661404
row4 1.0855719
row5 0.1941767
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.3523871 -1.285214 -1.025500 0.7774224 1.4229820 0.2873948 -0.06538262
row5 0.9640521 -1.434047 -1.428971 -1.5687300 -0.6625947 -0.6796229 -1.88563660
col8 col9 col10 col11 col12 col13
row1 0.2315229 -0.8059219 -0.4255199 -1.2142886 -0.8021182 0.351996208
row5 -1.0784123 -0.9914189 0.1941767 0.3840308 -0.4519998 -0.003782324
col14 col15 col16 col17 col18 col19 col20
row1 0.3665567 1.329538 -0.3922410 -0.3000654 2.3248568 -0.6324762 -0.5623199
row5 0.7649208 1.246266 -0.5509307 1.6404836 0.3253398 -1.9249298 -1.2505019
> tmp[,c("col6","col20")]
col6 col20
row1 0.2873948 -0.56231988
row2 -1.8742281 0.01069453
row3 1.8149439 0.30589559
row4 0.3947849 -0.23069433
row5 -0.6796229 -1.25050188
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.2873948 -0.5623199
row5 -0.6796229 -1.2505019
>
>
>
>
> 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 47.14527 49.10325 48.5169 49.48334 49.41115 103.4731 49.0904 49.62408
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.74387 51.06314 49.71222 50.18114 50.61809 48.94088 49.25627 49.82276
col17 col18 col19 col20
row1 48.81464 50.79244 51.42541 106.7198
> tmp[,"col10"]
col10
row1 51.06314
row2 29.59771
row3 27.85788
row4 28.11916
row5 48.77920
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 47.14527 49.10325 48.51690 49.48334 49.41115 103.4731 49.09040 49.62408
row5 50.43399 50.15318 49.75408 49.57924 50.17970 104.8031 50.15603 50.01019
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.74387 51.06314 49.71222 50.18114 50.61809 48.94088 49.25627 49.82276
row5 48.36577 48.77920 49.57564 50.99919 49.85296 51.21940 50.81897 50.60288
col17 col18 col19 col20
row1 48.81464 50.79244 51.42541 106.7198
row5 49.35788 48.75599 49.60094 105.1516
> tmp[,c("col6","col20")]
col6 col20
row1 103.47309 106.71983
row2 74.38829 75.76363
row3 76.42225 75.64073
row4 73.39273 74.96253
row5 104.80305 105.15157
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 103.4731 106.7198
row5 104.8031 105.1516
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 103.4731 106.7198
row5 104.8031 105.1516
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.31650621
[2,] -0.45113587
[3,] 0.02666887
[4,] 0.13992946
[5,] -0.31883743
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.2339539 0.48127236
[2,] -0.3691267 -1.17765887
[3,] 0.4869384 0.89788382
[4,] -1.8184467 0.77076719
[5,] 0.3269474 -0.03579649
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.61553050 1.2380101
[2,] -0.69245787 -0.9669001
[3,] 0.09949476 1.4104035
[4,] -0.49323500 1.5778529
[5,] 1.09481519 -0.2191506
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.6155305
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.6155305
[2,] -0.6924579
>
>
>
> 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 -0.8844112 -0.2189609 0.4858766 -1.407028 -0.5098321 0.004142428
row1 0.5278562 2.6282767 1.3238210 0.405696 -0.5064323 0.427975936
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -1.4015700 -0.2417318 0.08884298 0.1342196 1.472583 -0.9062211
row1 -0.3349247 0.6078603 -1.05652459 -0.8461964 1.204166 1.0552855
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.8333328 -0.81382292 -0.7931499 -0.6709457 0.3178080 0.741238 1.5498898
row1 -1.4130203 0.07109675 0.4094348 1.8837928 -0.6318484 1.537706 0.5282688
[,20]
row3 1.146293
row1 -1.191791
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.602032 1.378159 -0.6791207 0.2008812 -0.8214072 -0.08761712 -0.6806939
[,8] [,9] [,10]
row2 -0.718004 0.6154309 0.1159651
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.4166801 0.1810667 0.5568765 1.991018 0.6235063 -1.719466 0.003198847
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.1750754 0.02371091 1.395727 0.1227965 0.9829741 -0.5172037 -1.612272
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.7921775 0.8896501 -0.6860877 0.1945879 1.160724 -0.03861185
>
>
> 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: 0x5595ec01c860>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM469335ef4262a"
[2] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM469331b3a1c01"
[3] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM469334942a932"
[4] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM469333a25ef13"
[5] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM469331d23f26d"
[6] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM46933294ea906"
[7] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM469332fa1f312"
[8] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM46933382aff00"
[9] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM469335c124a5c"
[10] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM469332e2476fc"
[11] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM469334f3eae1f"
[12] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM469334f69613f"
[13] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM4693363104e1e"
[14] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM46933704dcf81"
[15] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM469337e2155fa"
>
>
> ### 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: 0x5595ecd0b590>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5595ecd0b590>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5595ecd0b590>
> rowMedians(tmp)
[1] 0.079925492 -0.087512488 0.129234071 -0.095848603 0.279233797
[6] -0.118758420 0.489144636 -0.358702886 -0.104395712 -0.059162497
[11] -0.021113056 0.264646781 0.167291750 0.410465594 0.240689393
[16] -0.318753096 0.079649589 0.080009741 0.063100739 0.177973710
[21] 0.068425249 0.905721857 0.594909802 0.231210044 0.180705023
[26] -0.078399556 -0.243302327 0.061503112 0.044816375 0.116032466
[31] 0.075247889 -0.010788994 0.199416857 -0.531170482 -0.229571538
[36] 0.216846169 0.244280756 0.222835578 -0.327297428 -0.237311083
[41] 0.041983360 -0.299995883 0.150046540 0.109100919 -0.162962562
[46] -0.333994682 -0.324088426 -0.367254152 0.195308815 -0.089574049
[51] 0.103990985 -0.385586600 -0.078631016 0.884261850 -0.660896110
[56] -0.079425979 0.059205182 -0.228039440 0.015194630 -0.639175498
[61] -0.376876730 0.076498437 0.013929667 -0.181755661 0.055426801
[66] -0.235155653 0.344882755 0.275855353 0.749745194 -0.298749596
[71] 0.108998943 0.207556181 0.288746921 0.424040069 0.996854362
[76] -0.201685883 -0.552913143 -0.781986017 -0.960995323 -0.281311335
[81] -0.513436052 0.150806385 -0.107813562 0.295175876 -0.109992086
[86] -0.216223666 -0.241523559 0.122837760 -0.219305535 -0.191693346
[91] 0.101414341 -0.032037683 -0.156811393 0.219207660 -0.805994696
[96] -0.021045540 0.020761146 0.358857791 0.387183584 -0.131239289
[101] 0.592810966 0.117013765 -0.744125447 0.514733895 0.326830420
[106] 0.010878870 -0.449893682 -0.319100399 0.514966295 -0.056536977
[111] -0.057587664 -1.018675334 0.259036058 -0.421005876 -0.115916728
[116] 0.114291761 -0.039130417 0.393425755 -0.282339973 -0.277207355
[121] -0.046137134 -0.321290913 -0.009291802 -0.060696020 0.174557822
[126] -0.046475318 -0.200040398 -0.465265654 -0.013009738 -0.278542552
[131] -0.146669174 0.075448221 -0.184608673 -0.024172580 -0.280752915
[136] 0.158373427 0.252342089 0.430674271 0.239387887 -0.340510782
[141] 0.254372756 0.101345654 -0.251718688 0.494762199 -0.554947107
[146] 0.254702407 -0.028759080 0.544868224 -0.505424585 0.051579639
[151] 0.491949733 0.138442711 -0.296711511 -0.170670191 -0.141475298
[156] -0.310932451 -0.096580154 0.428720003 -0.093387849 0.241614671
[161] 0.023458879 0.313010348 0.204598748 0.008316728 0.239034573
[166] 0.182113047 -0.863274017 0.073008621 -0.200039379 -0.138615311
[171] 0.959055076 0.264839368 0.076886191 0.390412704 -0.058385850
[176] 0.001878313 0.009161822 0.023894866 -0.198560897 0.100391890
[181] 0.227372589 -0.329211481 -0.213494165 -0.401061463 0.578074853
[186] 0.158479722 -0.042034311 -0.007301361 -0.459911642 0.218879591
[191] 0.281520232 0.449934070 -0.247626680 -0.029892166 -0.457750026
[196] 0.588127080 0.598155902 -0.282075013 -0.503279480 -0.590132876
[201] -0.134640098 -0.006014258 0.149255069 -0.496009851 0.154671534
[206] -0.475461675 0.533866157 -0.282361170 0.351500028 -0.308709251
[211] -0.238688100 0.257171539 -0.038089325 0.303408351 -0.183549159
[216] -0.363469606 0.329229375 0.366471887 -0.052836355 0.091249885
[221] -0.417559680 -0.148848486 -0.037108448 0.191443723 -0.080462727
[226] -0.151792047 0.039596883 0.423482199 -0.119717833 -0.124934013
>
> proc.time()
user system elapsed
1.368 1.608 2.987
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x5620c3605b80>
> .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: 0x5620c3605b80>
> .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: 0x5620c3605b80>
> .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: 0x5620c3605b80>
> 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: 0x5620c2c7b290>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5620c2c7b290>
> .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: 0x5620c2c7b290>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5620c2c7b290>
> .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: 0x5620c2c7b290>
> 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: 0x5620c3a3a1a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5620c3a3a1a0>
> .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: 0x5620c3a3a1a0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5620c3a3a1a0>
> .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: 0x5620c3a3a1a0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5620c3a3a1a0>
> .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: 0x5620c3a3a1a0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5620c3a3a1a0>
> .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: 0x5620c3a3a1a0>
> 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: 0x5620c3410440>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5620c3410440>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5620c3410440>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5620c3410440>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile46b905c17939f" "BufferedMatrixFile46b906c88a6b5"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile46b905c17939f" "BufferedMatrixFile46b906c88a6b5"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5620c3841aa0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5620c3841aa0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5620c3841aa0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5620c3841aa0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5620c3841aa0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5620c3841aa0>
> .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: 0x5620c3b18fc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5620c3b18fc0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5620c3b18fc0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5620c3b18fc0>
> 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: 0x5620c4785770>
> .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: 0x5620c4785770>
> rm(P)
>
> proc.time()
user system elapsed
0.266 0.042 0.297
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
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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Type 'contributors()' for more information and
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Type 'demo()' for some demos, 'help()' for on-line help, or
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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
0.256 0.048 0.294