Ben Bolstad
| Snapshot Date: 2025-01-10 13:40 -0500 (Fri, 10 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 2025-01-11 11:41 -0500 (Sat, 11 Jan 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | R Under development (unstable) (2024-10-21 r87258) -- "Unsuffered Consequences" | 4760 |
| palomino7 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2024-10-26 r87273 ucrt) -- "Unsuffered Consequences" | 4479 |
| lconway | macOS 12.7.1 Monterey | x86_64 | R Under development (unstable) (2024-11-20 r87352) -- "Unsuffered Consequences" | 4443 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | R Under development (unstable) (2024-11-20 r87352) -- "Unsuffered Consequences" | 4398 |
| kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | R Under development (unstable) (2024-11-24 r87369) -- "Unsuffered Consequences" | 4391 |
| 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 246/2277 | 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: E:\biocbuild\bbs-3.21-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=E:\biocbuild\bbs-3.21-bioc\R\library --no-vignettes --timings BufferedMatrix_1.71.1.tar.gz |
| StartedAt: 2025-01-10 23:13:32 -0500 (Fri, 10 Jan 2025) |
| EndedAt: 2025-01-10 23:16:43 -0500 (Fri, 10 Jan 2025) |
| EllapsedTime: 191.5 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### E:\biocbuild\bbs-3.21-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=E:\biocbuild\bbs-3.21-bioc\R\library --no-vignettes --timings BufferedMatrix_1.71.1.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck'
* using R Under development (unstable) (2024-10-26 r87273 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
gcc.exe (GCC) 13.2.0
GNU Fortran (GCC) 13.2.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* using option '--no-vignettes'
* 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 whether package 'BufferedMatrix' can be installed ... OK
* used C compiler: 'gcc.exe (GCC) 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 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 for x64 is not available
File 'E:/biocbuild/bbs-3.21-bioc/R/library/BufferedMatrix/libs/x64/BufferedMatrix.dll':
Found '_exit', possibly from '_exit' (C)
Found 'abort', possibly from 'abort' (C), 'runtime' (Fortran)
Compiled code should not call entry points which might terminate R nor
write to stdout/stderr instead of to the console, nor use Fortran I/O
nor system RNGs nor [v]sprintf. The detected symbols are linked into
the code but might come from libraries and not actually be called.
See 'Writing portable packages' in the 'Writing R Extensions' manual.
* checking sizes of PDF files under 'inst/doc' ... OK
* 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 running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
'E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/00check.log'
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### E:\biocbuild\bbs-3.21-bioc\R\bin\R.exe CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library 'E:/biocbuild/bbs-3.21-bioc/R/library'
* installing *source* package 'BufferedMatrix' ...
** using staged installation
** libs
using C compiler: 'gcc.exe (GCC) 13.3.0'
gcc -I"E:/biocbuild/bbs-3.21-bioc/R/include" -DNDEBUG -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -mfpmath=sse -msse2 -mstackrealign -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"E:/biocbuild/bbs-3.21-bioc/R/include" -DNDEBUG -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -mfpmath=sse -msse2 -mstackrealign -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){
| ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: 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"E:/biocbuild/bbs-3.21-bioc/R/include" -DNDEBUG -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -mfpmath=sse -msse2 -mstackrealign -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"E:/biocbuild/bbs-3.21-bioc/R/include" -DNDEBUG -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -mfpmath=sse -msse2 -mstackrealign -c init_package.c -o init_package.o
gcc -shared -s -static-libgcc -o BufferedMatrix.dll tmp.def RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -LC:/rtools44/x86_64-w64-mingw32.static.posix/lib/x64 -LC:/rtools44/x86_64-w64-mingw32.static.posix/lib -LE:/biocbuild/bbs-3.21-bioc/R/bin/x64 -lR
installing to E:/biocbuild/bbs-3.21-bioc/R/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs/x64
** 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
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R Under development (unstable) (2024-10-26 r87273 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
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
0.35 0.12 3.68
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2024-10-26 r87273 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
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] "E:/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 474902 25.4 1041921 55.7 629882 33.7
Vcells 866320 6.7 8388608 64.0 2037043 15.6
>
>
>
>
> ##
> ## 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] "Fri Jan 10 23:14:16 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] "Fri Jan 10 23:14:18 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: 0x0000025b690ff290>
>
>
>
> 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] "Fri Jan 10 23:14:44 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] "Fri Jan 10 23:14:52 2025"
>
> ColMode(tmp2)
<pointer: 0x0000025b690ff290>
>
>
>
> ### 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,] 98.2942155 -0.9983346 -0.7667806 -0.5739697
[2,] -1.4503160 -0.5102901 -0.7775474 -1.4499979
[3,] -0.8141326 1.2170700 0.4649099 0.0734471
[4,] -1.5589858 0.5875924 0.6840744 -1.4785549
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: E:/biocbuild/bbs-3.21-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,] 98.2942155 0.9983346 0.7667806 0.5739697
[2,] 1.4503160 0.5102901 0.7775474 1.4499979
[3,] 0.8141326 1.2170700 0.4649099 0.0734471
[4,] 1.5589858 0.5875924 0.6840744 1.4785549
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: E:/biocbuild/bbs-3.21-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,] 9.914344 0.9991669 0.8756601 0.7576079
[2,] 1.204291 0.7143459 0.8817865 1.2041586
[3,] 0.902293 1.1032089 0.6818430 0.2710113
[4,] 1.248594 0.7665457 0.8270879 1.2159584
>
> 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: E:/biocbuild/bbs-3.21-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,] 222.43765 35.99000 34.52338 33.15005
[2,] 38.49322 32.65375 34.59541 38.49158
[3,] 34.83706 37.24916 32.28334 27.78356
[4,] 39.04492 33.25305 33.95495 38.63814
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x0000025b690ff950>
> exp(tmp5)
<pointer: 0x0000025b690ff950>
> log(tmp5,2)
<pointer: 0x0000025b690ff950>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 462.9748
> Min(tmp5)
[1] 54.22681
> mean(tmp5)
[1] 72.68461
> Sum(tmp5)
[1] 14536.92
> Var(tmp5)
[1] 828.3001
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.16224 68.75818 70.14678 70.75374 71.64937 72.56639 69.14477 72.18596
[9] 67.64051 73.83813
> rowSums(tmp5)
[1] 1803.245 1375.164 1402.936 1415.075 1432.987 1451.328 1382.895 1443.719
[9] 1352.810 1476.763
> rowVars(tmp5)
[1] 7743.34869 44.27535 74.47151 59.65783 61.22662 40.59657
[7] 49.44451 67.83756 88.84444 54.39614
> rowSd(tmp5)
[1] 87.996299 6.653972 8.629688 7.723848 7.824744 6.371543 7.031679
[8] 8.236356 9.425733 7.375374
> rowMax(tmp5)
[1] 462.97483 80.11860 84.32540 93.24061 80.86233 89.81513 80.54476
[8] 85.23098 84.72406 84.12277
> rowMin(tmp5)
[1] 57.18499 57.80071 55.04924 59.44979 55.38490 61.56813 58.15471 56.07756
[9] 55.07448 54.22681
>
> colMeans(tmp5)
[1] 109.72761 72.13187 72.45544 72.58175 70.11388 71.82463 71.83952
[8] 69.83128 75.31718 68.94126 71.50553 65.24183 72.52099 72.68937
[15] 68.23949 73.42760 66.45373 69.70085 70.44084 68.70754
> colSums(tmp5)
[1] 1097.2761 721.3187 724.5544 725.8175 701.1388 718.2463 718.3952
[8] 698.3128 753.1718 689.4126 715.0553 652.4183 725.2099 726.8937
[15] 682.3949 734.2760 664.5373 697.0085 704.4084 687.0754
> colVars(tmp5)
[1] 15483.50689 36.68100 64.18247 70.31778 60.10340 33.55894
[7] 56.80750 46.04971 84.75694 49.00963 60.94006 96.75302
[13] 65.71844 25.81354 68.39564 41.92643 43.43549 84.84848
[19] 80.00396 33.60232
> colSd(tmp5)
[1] 124.432740 6.056485 8.011396 8.385570 7.752638 5.793008
[7] 7.537075 6.785994 9.206353 7.000688 7.806411 9.836312
[13] 8.106691 5.080703 8.270165 6.475062 6.590561 9.211323
[19] 8.944493 5.796751
> colMax(tmp5)
[1] 462.97483 80.67570 85.23098 80.42022 80.86233 82.28715 89.81513
[8] 84.32540 93.24061 79.80003 84.12277 79.53517 84.13476 80.99345
[15] 77.78878 79.78669 77.07404 81.08880 81.83829 75.75115
> colMin(tmp5)
[1] 59.81400 61.56813 61.72622 57.82784 58.41747 65.58845 61.84947 60.27632
[9] 62.35252 57.58910 57.18499 54.22681 59.37138 64.97475 57.80071 60.36663
[17] 58.57917 55.38490 55.63132 55.07448
>
>
> ### 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] 90.16224 NA 70.14678 70.75374 71.64937 72.56639 69.14477 72.18596
[9] 67.64051 73.83813
> rowSums(tmp5)
[1] 1803.245 NA 1402.936 1415.075 1432.987 1451.328 1382.895 1443.719
[9] 1352.810 1476.763
> rowVars(tmp5)
[1] 7743.34869 43.87416 74.47151 59.65783 61.22662 40.59657
[7] 49.44451 67.83756 88.84444 54.39614
> rowSd(tmp5)
[1] 87.996299 6.623757 8.629688 7.723848 7.824744 6.371543 7.031679
[8] 8.236356 9.425733 7.375374
> rowMax(tmp5)
[1] 462.97483 NA 84.32540 93.24061 80.86233 89.81513 80.54476
[8] 85.23098 84.72406 84.12277
> rowMin(tmp5)
[1] 57.18499 NA 55.04924 59.44979 55.38490 61.56813 58.15471 56.07756
[9] 55.07448 54.22681
>
> colMeans(tmp5)
[1] 109.72761 72.13187 72.45544 72.58175 70.11388 71.82463 71.83952
[8] 69.83128 75.31718 68.94126 71.50553 65.24183 72.52099 72.68937
[15] 68.23949 73.42760 66.45373 69.70085 NA 68.70754
> colSums(tmp5)
[1] 1097.2761 721.3187 724.5544 725.8175 701.1388 718.2463 718.3952
[8] 698.3128 753.1718 689.4126 715.0553 652.4183 725.2099 726.8937
[15] 682.3949 734.2760 664.5373 697.0085 NA 687.0754
> colVars(tmp5)
[1] 15483.50689 36.68100 64.18247 70.31778 60.10340 33.55894
[7] 56.80750 46.04971 84.75694 49.00963 60.94006 96.75302
[13] 65.71844 25.81354 68.39564 41.92643 43.43549 84.84848
[19] NA 33.60232
> colSd(tmp5)
[1] 124.432740 6.056485 8.011396 8.385570 7.752638 5.793008
[7] 7.537075 6.785994 9.206353 7.000688 7.806411 9.836312
[13] 8.106691 5.080703 8.270165 6.475062 6.590561 9.211323
[19] NA 5.796751
> colMax(tmp5)
[1] 462.97483 80.67570 85.23098 80.42022 80.86233 82.28715 89.81513
[8] 84.32540 93.24061 79.80003 84.12277 79.53517 84.13476 80.99345
[15] 77.78878 79.78669 77.07404 81.08880 NA 75.75115
> colMin(tmp5)
[1] 59.81400 61.56813 61.72622 57.82784 58.41747 65.58845 61.84947 60.27632
[9] 62.35252 57.58910 57.18499 54.22681 59.37138 64.97475 57.80071 60.36663
[17] 58.57917 55.38490 NA 55.07448
>
> Max(tmp5,na.rm=TRUE)
[1] 462.9748
> Min(tmp5,na.rm=TRUE)
[1] 54.22681
> mean(tmp5,na.rm=TRUE)
[1] 72.66919
> Sum(tmp5,na.rm=TRUE)
[1] 14461.17
> Var(tmp5,na.rm=TRUE)
[1] 832.4356
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.16224 68.39006 70.14678 70.75374 71.64937 72.56639 69.14477 72.18596
[9] 67.64051 73.83813
> rowSums(tmp5,na.rm=TRUE)
[1] 1803.245 1299.411 1402.936 1415.075 1432.987 1451.328 1382.895 1443.719
[9] 1352.810 1476.763
> rowVars(tmp5,na.rm=TRUE)
[1] 7743.34869 43.87416 74.47151 59.65783 61.22662 40.59657
[7] 49.44451 67.83756 88.84444 54.39614
> rowSd(tmp5,na.rm=TRUE)
[1] 87.996299 6.623757 8.629688 7.723848 7.824744 6.371543 7.031679
[8] 8.236356 9.425733 7.375374
> rowMax(tmp5,na.rm=TRUE)
[1] 462.97483 80.11860 84.32540 93.24061 80.86233 89.81513 80.54476
[8] 85.23098 84.72406 84.12277
> rowMin(tmp5,na.rm=TRUE)
[1] 57.18499 57.80071 55.04924 59.44979 55.38490 61.56813 58.15471 56.07756
[9] 55.07448 54.22681
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.72761 72.13187 72.45544 72.58175 70.11388 71.82463 71.83952
[8] 69.83128 75.31718 68.94126 71.50553 65.24183 72.52099 72.68937
[15] 68.23949 73.42760 66.45373 69.70085 69.85064 68.70754
> colSums(tmp5,na.rm=TRUE)
[1] 1097.2761 721.3187 724.5544 725.8175 701.1388 718.2463 718.3952
[8] 698.3128 753.1718 689.4126 715.0553 652.4183 725.2099 726.8937
[15] 682.3949 734.2760 664.5373 697.0085 628.6558 687.0754
> colVars(tmp5,na.rm=TRUE)
[1] 15483.50689 36.68100 64.18247 70.31778 60.10340 33.55894
[7] 56.80750 46.04971 84.75694 49.00963 60.94006 96.75302
[13] 65.71844 25.81354 68.39564 41.92643 43.43549 84.84848
[19] 86.08573 33.60232
> colSd(tmp5,na.rm=TRUE)
[1] 124.432740 6.056485 8.011396 8.385570 7.752638 5.793008
[7] 7.537075 6.785994 9.206353 7.000688 7.806411 9.836312
[13] 8.106691 5.080703 8.270165 6.475062 6.590561 9.211323
[19] 9.278239 5.796751
> colMax(tmp5,na.rm=TRUE)
[1] 462.97483 80.67570 85.23098 80.42022 80.86233 82.28715 89.81513
[8] 84.32540 93.24061 79.80003 84.12277 79.53517 84.13476 80.99345
[15] 77.78878 79.78669 77.07404 81.08880 81.83829 75.75115
> colMin(tmp5,na.rm=TRUE)
[1] 59.81400 61.56813 61.72622 57.82784 58.41747 65.58845 61.84947 60.27632
[9] 62.35252 57.58910 57.18499 54.22681 59.37138 64.97475 57.80071 60.36663
[17] 58.57917 55.38490 55.63132 55.07448
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.16224 NaN 70.14678 70.75374 71.64937 72.56639 69.14477 72.18596
[9] 67.64051 73.83813
> rowSums(tmp5,na.rm=TRUE)
[1] 1803.245 0.000 1402.936 1415.075 1432.987 1451.328 1382.895 1443.719
[9] 1352.810 1476.763
> rowVars(tmp5,na.rm=TRUE)
[1] 7743.34869 NA 74.47151 59.65783 61.22662 40.59657
[7] 49.44451 67.83756 88.84444 54.39614
> rowSd(tmp5,na.rm=TRUE)
[1] 87.996299 NA 8.629688 7.723848 7.824744 6.371543 7.031679
[8] 8.236356 9.425733 7.375374
> rowMax(tmp5,na.rm=TRUE)
[1] 462.97483 NA 84.32540 93.24061 80.86233 89.81513 80.54476
[8] 85.23098 84.72406 84.12277
> rowMin(tmp5,na.rm=TRUE)
[1] 57.18499 NA 55.04924 59.44979 55.38490 61.56813 58.15471 56.07756
[9] 55.07448 54.22681
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.01750 72.59491 72.50540 71.74470 71.14995 72.36093 72.29827
[8] 70.32632 76.75769 69.05320 71.36087 65.59680 73.44611 73.54655
[15] 69.39935 72.72103 66.91216 69.51405 NaN 68.26110
> colSums(tmp5,na.rm=TRUE)
[1] 1017.1575 653.3542 652.5486 645.7023 640.3496 651.2484 650.6844
[8] 632.9369 690.8192 621.4788 642.2478 590.3712 661.0150 661.9190
[15] 624.5941 654.4893 602.2095 625.6265 0.0000 614.3499
> colVars(tmp5,na.rm=TRUE)
[1] 17297.18228 38.85405 72.17720 71.22518 55.54005 34.51802
[7] 61.54083 49.04894 72.00680 54.99488 68.32215 107.42963
[13] 64.30495 20.77421 61.81065 41.55084 46.50060 95.06200
[19] NA 35.56046
> colSd(tmp5,na.rm=TRUE)
[1] 131.518753 6.233302 8.495716 8.439501 7.452519 5.875204
[7] 7.844796 7.003495 8.485682 7.415853 8.265722 10.364826
[13] 8.019036 4.557873 7.861975 6.445994 6.819135 9.749974
[19] NA 5.963259
> colMax(tmp5,na.rm=TRUE)
[1] 462.97483 80.67570 85.23098 80.42022 80.86233 82.28715 89.81513
[8] 84.32540 93.24061 79.80003 84.12277 79.53517 84.13476 80.99345
[15] 77.78878 78.94462 77.07404 81.08880 -Inf 75.75115
> colMin(tmp5,na.rm=TRUE)
[1] 59.81400 61.56813 61.72622 57.82784 58.41747 65.58845 61.84947 60.27632
[9] 65.03089 57.58910 57.18499 54.22681 59.37138 67.79253 58.15471 60.36663
[17] 58.57917 55.38490 Inf 55.07448
>
>
>
>
> 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] 222.1252 208.0232 291.0314 157.4349 221.7691 292.3330 203.3307 281.3925
[9] 240.3753 324.1118
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 222.1252 208.0232 291.0314 157.4349 221.7691 292.3330 203.3307 281.3925
[9] 240.3753 324.1118
>
>
>
> 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 0.000000e+00 -5.684342e-14 0.000000e+00 -5.684342e-14
[6] 2.842171e-14 -3.979039e-13 -2.842171e-14 -1.705303e-13 -1.136868e-13
[11] 5.684342e-14 4.263256e-14 -5.684342e-14 1.705303e-13 -2.842171e-13
[16] 0.000000e+00 2.273737e-13 5.684342e-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)
+ }
3 14
1 20
4 17
10 17
8 2
1 3
6 7
8 3
8 15
6 2
8 10
5 18
1 11
10 3
5 19
1 12
7 18
5 16
5 2
5 9
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] 3.097693
> Min(tmp)
[1] -1.881605
> mean(tmp)
[1] 0.07535169
> Sum(tmp)
[1] 7.535169
> Var(tmp)
[1] 1.066809
>
> rowMeans(tmp)
[1] 0.07535169
> rowSums(tmp)
[1] 7.535169
> rowVars(tmp)
[1] 1.066809
> rowSd(tmp)
[1] 1.032864
> rowMax(tmp)
[1] 3.097693
> rowMin(tmp)
[1] -1.881605
>
> colMeans(tmp)
[1] -0.867092417 -1.128447032 1.428500118 1.185681331 1.112741423
[6] -1.398715528 0.154582373 1.120684505 -0.301896086 0.136793202
[11] -0.460189784 -0.208787890 -0.810790512 0.767544849 1.530224399
[16] -0.571323318 -0.067898935 -0.621528078 0.779811384 1.054973962
[21] -0.162823156 -0.440215815 -0.009024617 -1.771168857 -1.243622481
[26] -0.416188495 0.048808580 1.031481755 -1.522208654 -0.075293555
[31] -1.181807403 1.406786495 0.034493598 0.436273982 -0.329563018
[36] -0.403454984 -1.783458109 0.417600034 2.579384953 -0.001083907
[41] -0.441212298 -1.552283895 -1.575109542 0.258633413 0.787024952
[46] -0.050491016 -0.772235324 1.206952531 -0.079674046 0.002659571
[51] 1.499546003 -1.881605487 0.255190443 -0.336803141 -0.832937017
[56] 0.015040327 -0.460242982 -0.672815575 0.268003960 -1.141164786
[61] 0.099562272 -0.042028651 -0.269992713 1.116103006 1.193360223
[66] 0.800692756 1.801312716 1.722901535 1.048304627 1.390390691
[71] -0.386102379 0.378280949 1.954471600 0.764692016 -0.693236254
[76] 0.290450456 0.001481977 0.372570290 -0.721572560 -0.456062584
[81] -0.332536426 2.610232540 1.580193506 -0.115022469 1.581721498
[86] 0.011237257 0.214717103 1.243733024 -1.110488087 -1.379719353
[91] 0.006363097 -1.385447603 -0.295795637 -0.182007835 3.097692795
[96] -0.812761485 -1.743828877 0.423552763 0.020922220 -0.209429532
> colSums(tmp)
[1] -0.867092417 -1.128447032 1.428500118 1.185681331 1.112741423
[6] -1.398715528 0.154582373 1.120684505 -0.301896086 0.136793202
[11] -0.460189784 -0.208787890 -0.810790512 0.767544849 1.530224399
[16] -0.571323318 -0.067898935 -0.621528078 0.779811384 1.054973962
[21] -0.162823156 -0.440215815 -0.009024617 -1.771168857 -1.243622481
[26] -0.416188495 0.048808580 1.031481755 -1.522208654 -0.075293555
[31] -1.181807403 1.406786495 0.034493598 0.436273982 -0.329563018
[36] -0.403454984 -1.783458109 0.417600034 2.579384953 -0.001083907
[41] -0.441212298 -1.552283895 -1.575109542 0.258633413 0.787024952
[46] -0.050491016 -0.772235324 1.206952531 -0.079674046 0.002659571
[51] 1.499546003 -1.881605487 0.255190443 -0.336803141 -0.832937017
[56] 0.015040327 -0.460242982 -0.672815575 0.268003960 -1.141164786
[61] 0.099562272 -0.042028651 -0.269992713 1.116103006 1.193360223
[66] 0.800692756 1.801312716 1.722901535 1.048304627 1.390390691
[71] -0.386102379 0.378280949 1.954471600 0.764692016 -0.693236254
[76] 0.290450456 0.001481977 0.372570290 -0.721572560 -0.456062584
[81] -0.332536426 2.610232540 1.580193506 -0.115022469 1.581721498
[86] 0.011237257 0.214717103 1.243733024 -1.110488087 -1.379719353
[91] 0.006363097 -1.385447603 -0.295795637 -0.182007835 3.097692795
[96] -0.812761485 -1.743828877 0.423552763 0.020922220 -0.209429532
> 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] -0.867092417 -1.128447032 1.428500118 1.185681331 1.112741423
[6] -1.398715528 0.154582373 1.120684505 -0.301896086 0.136793202
[11] -0.460189784 -0.208787890 -0.810790512 0.767544849 1.530224399
[16] -0.571323318 -0.067898935 -0.621528078 0.779811384 1.054973962
[21] -0.162823156 -0.440215815 -0.009024617 -1.771168857 -1.243622481
[26] -0.416188495 0.048808580 1.031481755 -1.522208654 -0.075293555
[31] -1.181807403 1.406786495 0.034493598 0.436273982 -0.329563018
[36] -0.403454984 -1.783458109 0.417600034 2.579384953 -0.001083907
[41] -0.441212298 -1.552283895 -1.575109542 0.258633413 0.787024952
[46] -0.050491016 -0.772235324 1.206952531 -0.079674046 0.002659571
[51] 1.499546003 -1.881605487 0.255190443 -0.336803141 -0.832937017
[56] 0.015040327 -0.460242982 -0.672815575 0.268003960 -1.141164786
[61] 0.099562272 -0.042028651 -0.269992713 1.116103006 1.193360223
[66] 0.800692756 1.801312716 1.722901535 1.048304627 1.390390691
[71] -0.386102379 0.378280949 1.954471600 0.764692016 -0.693236254
[76] 0.290450456 0.001481977 0.372570290 -0.721572560 -0.456062584
[81] -0.332536426 2.610232540 1.580193506 -0.115022469 1.581721498
[86] 0.011237257 0.214717103 1.243733024 -1.110488087 -1.379719353
[91] 0.006363097 -1.385447603 -0.295795637 -0.182007835 3.097692795
[96] -0.812761485 -1.743828877 0.423552763 0.020922220 -0.209429532
> colMin(tmp)
[1] -0.867092417 -1.128447032 1.428500118 1.185681331 1.112741423
[6] -1.398715528 0.154582373 1.120684505 -0.301896086 0.136793202
[11] -0.460189784 -0.208787890 -0.810790512 0.767544849 1.530224399
[16] -0.571323318 -0.067898935 -0.621528078 0.779811384 1.054973962
[21] -0.162823156 -0.440215815 -0.009024617 -1.771168857 -1.243622481
[26] -0.416188495 0.048808580 1.031481755 -1.522208654 -0.075293555
[31] -1.181807403 1.406786495 0.034493598 0.436273982 -0.329563018
[36] -0.403454984 -1.783458109 0.417600034 2.579384953 -0.001083907
[41] -0.441212298 -1.552283895 -1.575109542 0.258633413 0.787024952
[46] -0.050491016 -0.772235324 1.206952531 -0.079674046 0.002659571
[51] 1.499546003 -1.881605487 0.255190443 -0.336803141 -0.832937017
[56] 0.015040327 -0.460242982 -0.672815575 0.268003960 -1.141164786
[61] 0.099562272 -0.042028651 -0.269992713 1.116103006 1.193360223
[66] 0.800692756 1.801312716 1.722901535 1.048304627 1.390390691
[71] -0.386102379 0.378280949 1.954471600 0.764692016 -0.693236254
[76] 0.290450456 0.001481977 0.372570290 -0.721572560 -0.456062584
[81] -0.332536426 2.610232540 1.580193506 -0.115022469 1.581721498
[86] 0.011237257 0.214717103 1.243733024 -1.110488087 -1.379719353
[91] 0.006363097 -1.385447603 -0.295795637 -0.182007835 3.097692795
[96] -0.812761485 -1.743828877 0.423552763 0.020922220 -0.209429532
> colMedians(tmp)
[1] -0.867092417 -1.128447032 1.428500118 1.185681331 1.112741423
[6] -1.398715528 0.154582373 1.120684505 -0.301896086 0.136793202
[11] -0.460189784 -0.208787890 -0.810790512 0.767544849 1.530224399
[16] -0.571323318 -0.067898935 -0.621528078 0.779811384 1.054973962
[21] -0.162823156 -0.440215815 -0.009024617 -1.771168857 -1.243622481
[26] -0.416188495 0.048808580 1.031481755 -1.522208654 -0.075293555
[31] -1.181807403 1.406786495 0.034493598 0.436273982 -0.329563018
[36] -0.403454984 -1.783458109 0.417600034 2.579384953 -0.001083907
[41] -0.441212298 -1.552283895 -1.575109542 0.258633413 0.787024952
[46] -0.050491016 -0.772235324 1.206952531 -0.079674046 0.002659571
[51] 1.499546003 -1.881605487 0.255190443 -0.336803141 -0.832937017
[56] 0.015040327 -0.460242982 -0.672815575 0.268003960 -1.141164786
[61] 0.099562272 -0.042028651 -0.269992713 1.116103006 1.193360223
[66] 0.800692756 1.801312716 1.722901535 1.048304627 1.390390691
[71] -0.386102379 0.378280949 1.954471600 0.764692016 -0.693236254
[76] 0.290450456 0.001481977 0.372570290 -0.721572560 -0.456062584
[81] -0.332536426 2.610232540 1.580193506 -0.115022469 1.581721498
[86] 0.011237257 0.214717103 1.243733024 -1.110488087 -1.379719353
[91] 0.006363097 -1.385447603 -0.295795637 -0.182007835 3.097692795
[96] -0.812761485 -1.743828877 0.423552763 0.020922220 -0.209429532
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
[1,] -0.8670924 -1.128447 1.4285 1.185681 1.112741 -1.398716 0.1545824 1.120685
[2,] -0.8670924 -1.128447 1.4285 1.185681 1.112741 -1.398716 0.1545824 1.120685
[,9] [,10] [,11] [,12] [,13] [,14] [,15]
[1,] -0.3018961 0.1367932 -0.4601898 -0.2087879 -0.8107905 0.7675448 1.530224
[2,] -0.3018961 0.1367932 -0.4601898 -0.2087879 -0.8107905 0.7675448 1.530224
[,16] [,17] [,18] [,19] [,20] [,21] [,22]
[1,] -0.5713233 -0.06789894 -0.6215281 0.7798114 1.054974 -0.1628232 -0.4402158
[2,] -0.5713233 -0.06789894 -0.6215281 0.7798114 1.054974 -0.1628232 -0.4402158
[,23] [,24] [,25] [,26] [,27] [,28] [,29]
[1,] -0.009024617 -1.771169 -1.243622 -0.4161885 0.04880858 1.031482 -1.522209
[2,] -0.009024617 -1.771169 -1.243622 -0.4161885 0.04880858 1.031482 -1.522209
[,30] [,31] [,32] [,33] [,34] [,35] [,36]
[1,] -0.07529355 -1.181807 1.406786 0.0344936 0.436274 -0.329563 -0.403455
[2,] -0.07529355 -1.181807 1.406786 0.0344936 0.436274 -0.329563 -0.403455
[,37] [,38] [,39] [,40] [,41] [,42] [,43]
[1,] -1.783458 0.4176 2.579385 -0.001083907 -0.4412123 -1.552284 -1.57511
[2,] -1.783458 0.4176 2.579385 -0.001083907 -0.4412123 -1.552284 -1.57511
[,44] [,45] [,46] [,47] [,48] [,49] [,50]
[1,] 0.2586334 0.787025 -0.05049102 -0.7722353 1.206953 -0.07967405 0.002659571
[2,] 0.2586334 0.787025 -0.05049102 -0.7722353 1.206953 -0.07967405 0.002659571
[,51] [,52] [,53] [,54] [,55] [,56] [,57]
[1,] 1.499546 -1.881605 0.2551904 -0.3368031 -0.832937 0.01504033 -0.460243
[2,] 1.499546 -1.881605 0.2551904 -0.3368031 -0.832937 0.01504033 -0.460243
[,58] [,59] [,60] [,61] [,62] [,63] [,64]
[1,] -0.6728156 0.268004 -1.141165 0.09956227 -0.04202865 -0.2699927 1.116103
[2,] -0.6728156 0.268004 -1.141165 0.09956227 -0.04202865 -0.2699927 1.116103
[,65] [,66] [,67] [,68] [,69] [,70] [,71] [,72]
[1,] 1.19336 0.8006928 1.801313 1.722902 1.048305 1.390391 -0.3861024 0.3782809
[2,] 1.19336 0.8006928 1.801313 1.722902 1.048305 1.390391 -0.3861024 0.3782809
[,73] [,74] [,75] [,76] [,77] [,78] [,79]
[1,] 1.954472 0.764692 -0.6932363 0.2904505 0.001481977 0.3725703 -0.7215726
[2,] 1.954472 0.764692 -0.6932363 0.2904505 0.001481977 0.3725703 -0.7215726
[,80] [,81] [,82] [,83] [,84] [,85] [,86]
[1,] -0.4560626 -0.3325364 2.610233 1.580194 -0.1150225 1.581721 0.01123726
[2,] -0.4560626 -0.3325364 2.610233 1.580194 -0.1150225 1.581721 0.01123726
[,87] [,88] [,89] [,90] [,91] [,92] [,93]
[1,] 0.2147171 1.243733 -1.110488 -1.379719 0.006363097 -1.385448 -0.2957956
[2,] 0.2147171 1.243733 -1.110488 -1.379719 0.006363097 -1.385448 -0.2957956
[,94] [,95] [,96] [,97] [,98] [,99] [,100]
[1,] -0.1820078 3.097693 -0.8127615 -1.743829 0.4235528 0.02092222 -0.2094295
[2,] -0.1820078 3.097693 -0.8127615 -1.743829 0.4235528 0.02092222 -0.2094295
>
>
> Max(tmp2)
[1] 2.612105
> Min(tmp2)
[1] -2.311097
> mean(tmp2)
[1] -0.1651315
> Sum(tmp2)
[1] -16.51315
> Var(tmp2)
[1] 1.063174
>
> rowMeans(tmp2)
[1] -2.027675090 -0.171320941 -1.009195398 -2.234186325 0.033111153
[6] -0.165979202 0.771926914 -1.664397808 1.817971642 0.252995586
[11] 0.727788125 -0.036252420 0.318777517 -0.616299113 0.856680146
[16] -0.886484141 -0.488171450 -2.311097253 -1.079431374 -0.300862964
[21] 0.261400760 -0.734294325 -0.934037649 1.048963844 0.532218250
[26] 1.557913160 -0.570105101 -2.094194135 -1.456507209 -0.464705485
[31] 0.713826248 -2.026874573 2.612105393 -0.583056091 -1.736280277
[36] 0.636250234 0.192968880 0.312376093 -0.690544083 0.125496701
[41] 0.291841854 1.279148956 -0.388567361 -0.817134033 -0.346745414
[46] -0.318806446 -0.531823970 -0.709187638 -0.986905140 0.182948433
[51] 1.063406911 -0.239667145 -1.334176606 -1.645050930 0.102280985
[56] -1.553401142 -1.864954811 0.364440437 0.057255061 1.518909655
[61] 2.344900202 -0.065094475 -0.081620059 -1.035166894 1.248537691
[66] 1.481554894 -0.259954709 0.574768134 -0.781078737 0.279749371
[71] -0.723468949 0.008184088 -0.561150712 1.078327772 0.902512846
[76] 0.620826078 -0.461341523 0.549240615 -0.947453944 1.467032969
[81] -0.936779657 -0.023382912 -0.081589927 0.682094868 -1.407148999
[86] 0.202084497 0.586612740 -1.004455806 -1.224161183 -0.882300461
[91] -0.999097570 -1.411529224 -0.286918739 -0.351061676 0.823059232
[96] 0.819719351 -1.079620375 0.185814756 -0.353305608 1.974880400
> rowSums(tmp2)
[1] -2.027675090 -0.171320941 -1.009195398 -2.234186325 0.033111153
[6] -0.165979202 0.771926914 -1.664397808 1.817971642 0.252995586
[11] 0.727788125 -0.036252420 0.318777517 -0.616299113 0.856680146
[16] -0.886484141 -0.488171450 -2.311097253 -1.079431374 -0.300862964
[21] 0.261400760 -0.734294325 -0.934037649 1.048963844 0.532218250
[26] 1.557913160 -0.570105101 -2.094194135 -1.456507209 -0.464705485
[31] 0.713826248 -2.026874573 2.612105393 -0.583056091 -1.736280277
[36] 0.636250234 0.192968880 0.312376093 -0.690544083 0.125496701
[41] 0.291841854 1.279148956 -0.388567361 -0.817134033 -0.346745414
[46] -0.318806446 -0.531823970 -0.709187638 -0.986905140 0.182948433
[51] 1.063406911 -0.239667145 -1.334176606 -1.645050930 0.102280985
[56] -1.553401142 -1.864954811 0.364440437 0.057255061 1.518909655
[61] 2.344900202 -0.065094475 -0.081620059 -1.035166894 1.248537691
[66] 1.481554894 -0.259954709 0.574768134 -0.781078737 0.279749371
[71] -0.723468949 0.008184088 -0.561150712 1.078327772 0.902512846
[76] 0.620826078 -0.461341523 0.549240615 -0.947453944 1.467032969
[81] -0.936779657 -0.023382912 -0.081589927 0.682094868 -1.407148999
[86] 0.202084497 0.586612740 -1.004455806 -1.224161183 -0.882300461
[91] -0.999097570 -1.411529224 -0.286918739 -0.351061676 0.823059232
[96] 0.819719351 -1.079620375 0.185814756 -0.353305608 1.974880400
> 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] -2.027675090 -0.171320941 -1.009195398 -2.234186325 0.033111153
[6] -0.165979202 0.771926914 -1.664397808 1.817971642 0.252995586
[11] 0.727788125 -0.036252420 0.318777517 -0.616299113 0.856680146
[16] -0.886484141 -0.488171450 -2.311097253 -1.079431374 -0.300862964
[21] 0.261400760 -0.734294325 -0.934037649 1.048963844 0.532218250
[26] 1.557913160 -0.570105101 -2.094194135 -1.456507209 -0.464705485
[31] 0.713826248 -2.026874573 2.612105393 -0.583056091 -1.736280277
[36] 0.636250234 0.192968880 0.312376093 -0.690544083 0.125496701
[41] 0.291841854 1.279148956 -0.388567361 -0.817134033 -0.346745414
[46] -0.318806446 -0.531823970 -0.709187638 -0.986905140 0.182948433
[51] 1.063406911 -0.239667145 -1.334176606 -1.645050930 0.102280985
[56] -1.553401142 -1.864954811 0.364440437 0.057255061 1.518909655
[61] 2.344900202 -0.065094475 -0.081620059 -1.035166894 1.248537691
[66] 1.481554894 -0.259954709 0.574768134 -0.781078737 0.279749371
[71] -0.723468949 0.008184088 -0.561150712 1.078327772 0.902512846
[76] 0.620826078 -0.461341523 0.549240615 -0.947453944 1.467032969
[81] -0.936779657 -0.023382912 -0.081589927 0.682094868 -1.407148999
[86] 0.202084497 0.586612740 -1.004455806 -1.224161183 -0.882300461
[91] -0.999097570 -1.411529224 -0.286918739 -0.351061676 0.823059232
[96] 0.819719351 -1.079620375 0.185814756 -0.353305608 1.974880400
> rowMin(tmp2)
[1] -2.027675090 -0.171320941 -1.009195398 -2.234186325 0.033111153
[6] -0.165979202 0.771926914 -1.664397808 1.817971642 0.252995586
[11] 0.727788125 -0.036252420 0.318777517 -0.616299113 0.856680146
[16] -0.886484141 -0.488171450 -2.311097253 -1.079431374 -0.300862964
[21] 0.261400760 -0.734294325 -0.934037649 1.048963844 0.532218250
[26] 1.557913160 -0.570105101 -2.094194135 -1.456507209 -0.464705485
[31] 0.713826248 -2.026874573 2.612105393 -0.583056091 -1.736280277
[36] 0.636250234 0.192968880 0.312376093 -0.690544083 0.125496701
[41] 0.291841854 1.279148956 -0.388567361 -0.817134033 -0.346745414
[46] -0.318806446 -0.531823970 -0.709187638 -0.986905140 0.182948433
[51] 1.063406911 -0.239667145 -1.334176606 -1.645050930 0.102280985
[56] -1.553401142 -1.864954811 0.364440437 0.057255061 1.518909655
[61] 2.344900202 -0.065094475 -0.081620059 -1.035166894 1.248537691
[66] 1.481554894 -0.259954709 0.574768134 -0.781078737 0.279749371
[71] -0.723468949 0.008184088 -0.561150712 1.078327772 0.902512846
[76] 0.620826078 -0.461341523 0.549240615 -0.947453944 1.467032969
[81] -0.936779657 -0.023382912 -0.081589927 0.682094868 -1.407148999
[86] 0.202084497 0.586612740 -1.004455806 -1.224161183 -0.882300461
[91] -0.999097570 -1.411529224 -0.286918739 -0.351061676 0.823059232
[96] 0.819719351 -1.079620375 0.185814756 -0.353305608 1.974880400
>
> colMeans(tmp2)
[1] -0.1651315
> colSums(tmp2)
[1] -16.51315
> colVars(tmp2)
[1] 1.063174
> colSd(tmp2)
[1] 1.031103
> colMax(tmp2)
[1] 2.612105
> colMin(tmp2)
[1] -2.311097
> colMedians(tmp2)
[1] -0.205494
> colRanges(tmp2)
[,1]
[1,] -2.311097
[2,] 2.612105
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.1461524 -0.9056965 2.5110729 2.9022644 -1.1990133 2.4994905
[7] 5.3607365 2.1327674 3.7134908 2.8646033
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.1866428
[2,] -0.3319931
[3,] 0.2558068
[4,] 0.7549026
[5,] 1.1253520
>
> rowApply(tmp,sum)
[1] 3.7849416 0.5836474 -0.6669503 4.9279436 2.9128108 2.2134626
[7] 4.5816602 0.4301617 -1.4792740 2.4451600
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 6 1 4 8 5 8 4 2 5
[2,] 6 1 7 9 10 1 6 2 4 4
[3,] 4 10 4 7 6 2 10 5 3 6
[4,] 10 3 6 3 5 3 3 10 5 8
[5,] 1 5 2 6 3 7 7 6 6 1
[6,] 9 2 8 5 9 4 4 8 1 10
[7,] 2 8 10 8 4 8 5 7 7 7
[8,] 5 7 5 2 7 9 2 1 10 3
[9,] 7 9 9 10 1 6 1 3 9 2
[10,] 3 4 3 1 2 10 9 9 8 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -3.24279872 2.80296224 1.99221262 -1.22244652 0.21637272 -1.31005584
[7] 0.67234544 1.19405012 -5.32741282 0.31549884 -2.29449123 -1.48927925
[13] 0.02446295 -0.85918678 4.65129557 0.40866463 -2.07638415 1.40306773
[19] 1.10202506 -2.31709303
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.0464276
[2,] -1.4617946
[3,] -0.6482962
[4,] -0.2326127
[5,] 1.1463324
>
> rowApply(tmp,sum)
[1] 4.4792171 -5.4536028 -1.4536430 -0.5608147 -2.3673470
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 16 13 2 1 6
[2,] 18 16 15 9 18
[3,] 13 10 5 14 20
[4,] 11 6 1 17 11
[5,] 2 12 11 19 16
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.1463324 1.2630432 0.3930536 0.2479853 -1.5848010 1.25813437
[2,] -0.2326127 0.2519722 -0.6007033 -1.0514292 -0.2893393 0.04389459
[3,] -1.4617946 0.8103974 -0.6722815 -1.7264729 -0.1646684 0.15856629
[4,] -2.0464276 -0.3700888 0.6247950 1.1966185 1.5463044 -1.41702792
[5,] -0.6482962 0.8476382 2.2473488 0.1108518 0.7088771 -1.35362318
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.1939035 -0.7780997 -0.05389266 0.9236082 -0.8002839 0.3280733
[2,] -1.8332014 -1.2650156 -1.38057243 -0.8506100 -0.7271195 -0.5475524
[3,] 0.9811218 1.0715380 -0.55622951 1.3186141 -0.2646490 -0.4819679
[4,] 1.1648015 1.3881851 -1.94935273 -0.7130605 0.1142550 -0.6848732
[5,] 0.1657200 0.7774424 -1.38736549 -0.3630530 -0.6166939 -0.1029590
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.7546461 -0.19300811 1.4864669 0.04905294 -1.88337925 -0.2545512
[2,] -1.9493057 -1.81181781 2.5881742 2.38459430 -0.03978411 -0.6891834
[3,] -0.9005458 0.15489620 1.3508521 -1.26905282 1.00950212 0.1210903
[4,] 0.9212634 0.07367221 -0.3625445 -1.22485017 0.49104048 2.0503668
[5,] 0.1984050 0.91707073 -0.4116531 0.46892038 -1.65376339 0.1753453
[,19] [,20]
[1,] 0.8279844 0.1549487
[2,] 2.2825848 0.2634241
[3,] -0.4363251 -0.4962337
[4,] -0.6623150 -0.7015766
[5,] -0.9099040 -1.5376555
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.8 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 626 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 541 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.8 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 0.942366 1.114764 -0.6754572 -1.581969 1.264649 -0.6948682 1.052347
col8 col9 col10 col11 col12 col13 col14
row1 -0.4049621 -0.3738083 -1.042902 -0.2701079 -1.58345 0.179293 0.29048
col15 col16 col17 col18 col19 col20
row1 1.391292 0.4319204 -0.5170034 -1.114288 -0.6384468 0.07646676
> tmp[,"col10"]
col10
row1 -1.0429020
row2 -0.3688276
row3 0.4028539
row4 -0.3119612
row5 -0.9625071
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.9423660 1.1147645 -0.6754572 -1.5819686 1.264649 -0.69486821 1.0523473
row5 0.3548662 0.8274396 -0.3160259 -0.4242569 0.665300 0.05870781 0.2445026
col8 col9 col10 col11 col12 col13 col14
row1 -0.4049621 -0.3738083 -1.0429020 -0.2701079 -1.5834503 0.179293 0.290480
row5 1.3288740 0.2535018 -0.9625071 -1.6717105 -0.1893013 1.629736 1.779869
col15 col16 col17 col18 col19 col20
row1 1.391292 0.4319204 -0.5170034 -1.114288 -0.6384468 0.07646676
row5 1.648888 -0.1988323 0.1691665 1.554549 -0.7439452 1.03912181
> tmp[,c("col6","col20")]
col6 col20
row1 -0.69486821 0.07646676
row2 -2.05140791 0.51451293
row3 -0.85164256 0.17747092
row4 -0.62502357 1.25377769
row5 0.05870781 1.03912181
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.69486821 0.07646676
row5 0.05870781 1.03912181
>
>
>
>
> 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 49.22904 51.50872 48.86131 51.10755 48.52804 105.8724 50.04851 47.82901
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.89518 49.60515 49.76568 50.10938 48.75853 50.8979 50.49846 50.41074
col17 col18 col19 col20
row1 51.31046 50.94552 52.66431 106.5992
> tmp[,"col10"]
col10
row1 49.60515
row2 28.42213
row3 31.04004
row4 30.83827
row5 50.48158
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.22904 51.50872 48.86131 51.10755 48.52804 105.8724 50.04851 47.82901
row5 48.80692 50.05300 49.40179 48.93794 50.60883 107.8938 49.92516 49.81899
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.89518 49.60515 49.76568 50.10938 48.75853 50.8979 50.49846 50.41074
row5 49.81248 50.48158 50.10217 48.64957 49.97497 50.3082 49.15929 48.88804
col17 col18 col19 col20
row1 51.31046 50.94552 52.66431 106.5992
row5 48.09938 50.17018 47.47594 104.6955
> tmp[,c("col6","col20")]
col6 col20
row1 105.87238 106.59917
row2 75.79206 74.79227
row3 74.56750 75.37464
row4 76.07773 74.53254
row5 107.89375 104.69554
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.8724 106.5992
row5 107.8938 104.6955
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.8724 106.5992
row5 107.8938 104.6955
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.62170986
[2,] 0.57523941
[3,] 1.57656509
[4,] 0.80043891
[5,] -0.01853235
> tmp[,c("col17","col7")]
col17 col7
[1,] 2.07854885 -0.59965409
[2,] 1.10797741 0.04504184
[3,] -0.48084397 -0.53708280
[4,] -0.08911829 -1.51509011
[5,] -0.33722606 0.51118240
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.4234989 0.6143010
[2,] 0.8884539 -1.4727995
[3,] -1.3165585 0.2522887
[4,] -0.4313543 0.7045938
[5,] 0.4164882 0.7554205
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.423499
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.4234989
[2,] 0.8884539
>
>
>
> 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 0.4014219 1.783621 -0.6046685 -1.2512367 0.3453129 -0.64133740 1.538954
row1 -1.0104858 -1.315530 1.0843707 0.1302774 0.5640515 -0.03534918 1.334955
[,8] [,9] [,10] [,11] [,12] [,13]
row3 0.08860194 0.1810576 0.2625046 -0.6821116 0.5238710533 0.9088426
row1 1.12270994 1.2125105 -0.1108230 0.6343496 0.0002299788 -0.2789813
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.9176805 -1.6631877 0.4847361 -0.1014898 0.2210827 0.1305042 1.2329942
row1 0.4775252 0.5278349 -1.8283168 -0.8013826 1.3268032 0.7459077 -0.1053887
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.273486 0.7298729 -0.3044715 0.2229496 -0.9356722 0.6360773 1.480148
[,8] [,9] [,10]
row2 0.5621895 -0.4517385 0.6882384
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.9857391 -0.2804195 0.2565866 0.3314121 0.2663811 1.850722 -0.1474679
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.719369 0.3624666 0.2469189 -0.6707415 -0.6103869 -2.047619 0.7407082
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.247595 -0.7098111 0.6658587 -2.894284 -0.9776648 2.765433
>
>
> 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: 0x0000025b690ffa10>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests\\BMf7d04d637b97"
[2] "E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests\\BMf7d0105f208d"
[3] "E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests\\BMf7d03e63bf4"
[4] "E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests\\BMf7d037751c02"
[5] "E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests\\BMf7d0e1a19c7"
[6] "E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests\\BMf7d04d5379a5"
[7] "E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests\\BMf7d07fba6c8c"
[8] "E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests\\BMf7d08522ffa"
[9] "E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests\\BMf7d023053b0e"
[10] "E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests\\BMf7d051e71934"
[11] "E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests\\BMf7d065b3734"
[12] "E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests\\BMf7d03244da7"
[13] "E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests\\BMf7d054146c1e"
[14] "E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests\\BMf7d04a82280"
[15] "E:/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests\\BMf7d04cf61270"
>
>
> ### 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: 0x0000025b6a9ff2f0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x0000025b6a9ff2f0>
Warning message:
In dir.create(new.directory) :
'E:\biocbuild\bbs-3.21-bioc\meat\BufferedMatrix.Rcheck\tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x0000025b6a9ff2f0>
> rowMedians(tmp)
[1] -0.2905997969 0.1386188992 -0.2754833950 0.2801419021 0.6219276439
[6] -0.2423559285 0.0147153340 -0.3403984115 0.3372956835 -0.3980025904
[11] 0.0722574788 0.1740505852 -0.0718973172 0.9559812734 -0.2739828345
[16] -0.1200719078 0.0465015319 -0.2483172154 -0.2244876583 0.0956534007
[21] 0.2626162752 0.5363286529 -0.3028742637 -0.0810540436 -0.0858243834
[26] -0.1566394934 -0.2868104085 0.3059505099 0.3447522633 0.2659911313
[31] 0.1729085518 0.4624678001 -0.3768444806 0.0052817833 -0.1847090128
[36] -0.2127018620 -0.1593606378 0.0226614626 0.5921259482 -0.1940162921
[41] 0.2647951188 -0.0755682111 -0.0580708660 -0.0017578925 -0.3315317040
[46] 0.0270781902 -0.2013664024 0.0794302035 0.4353046983 -0.2786277428
[51] 0.3215980257 -0.2703262032 0.3069625584 0.2050668786 0.2876006260
[56] -0.7756539074 0.1857895978 0.2089149991 -0.2322584076 -0.0270002209
[61] -0.0820366422 0.4375296574 0.0003236489 -0.0063391969 -0.2601559977
[66] 0.6826224761 0.3456500347 0.2949819500 -0.2668894169 0.1991303593
[71] 0.3122559487 -0.5363883943 0.1989539209 -0.2916140964 -0.3286996314
[76] -0.1795289524 -0.2692435203 0.0733304304 -0.1116809334 0.1572225523
[81] 0.2372249110 -0.2448827002 -0.1576018700 -0.0042885935 0.3469869785
[86] -0.3173331016 0.2314496874 -0.4780171546 0.0557156384 0.0303471334
[91] -0.5308629790 -0.0529242203 -0.0800304655 0.2537996430 0.4878590321
[96] -0.2633696197 0.2396175321 0.0183627726 0.4225939821 -0.2591128894
[101] 0.5227242108 -0.2176502690 0.4861561453 0.2759587477 -0.6077566841
[106] -0.3728097728 0.0017270943 0.2697029577 0.0334837370 -0.0922849782
[111] -0.1071022341 0.0840154491 0.0520667957 -0.2104469566 -0.0473020586
[116] -0.3861428438 -0.6499444727 -0.2958061572 0.0210411049 0.4619434953
[121] -0.6027760706 0.4935037668 0.1309880589 0.5871079745 0.3287180092
[126] 0.2412442354 -0.2495491558 -0.0400213711 0.3530627667 0.4208659682
[131] 0.2815358404 -0.4911398715 -0.2103470468 0.0294456301 0.1071261950
[136] -0.0146808410 0.3242304282 0.5067944334 -0.2143742361 -0.2707423901
[141] -0.1070994490 0.0240372224 0.4347457683 0.6043341955 -0.1704228019
[146] -0.4502464485 0.0312254037 -0.5838880361 -0.2122133657 0.0288781884
[151] -0.0259586741 0.0403446656 0.1093538655 -0.0898704521 0.0700002969
[156] -0.9759340323 0.3675247981 0.1000197730 0.0843276725 -0.3084994658
[161] -0.4638275870 -0.5289583541 0.1638625087 -0.0603600299 0.0459417790
[166] -0.1925424032 0.4041737912 0.3531236402 0.3894488401 0.0375399400
[171] -0.1228112498 -0.3068705048 0.3732605438 0.5778513609 -0.4251339683
[176] -0.3546286820 -0.2494339724 -0.0758821112 -0.2905094421 -0.1525810274
[181] -0.1783402450 0.5118840409 0.1108322140 0.2823125721 -0.4219391223
[186] -0.4870807498 0.1793413785 0.3126223232 -0.3612219103 0.0028846676
[191] -0.0152527258 0.0566212938 -0.4921891818 -0.2003638319 -0.0588203676
[196] -0.1707138171 0.0254075789 -0.1613150258 0.0655766440 -0.3976567356
[201] -0.0600892698 -0.2116458506 -0.1519173657 -0.1343929833 -0.1924990929
[206] 0.0465875899 0.2316491381 0.0377978152 -0.4869810459 0.3576669575
[211] -0.1720352442 0.1868764012 0.0582203157 -0.0506427202 0.5208744577
[216] -0.0339081810 0.5533565314 -0.3009459330 -0.0181268772 -0.3699535605
[221] 0.0665706246 -0.6062640799 0.4533049800 0.1683779932 0.6930705402
[226] 0.0737782916 -0.2399647804 0.0906211938 -0.3665913002 0.1252272247
>
> proc.time()
user system elapsed
3.57 15.53 135.03
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2024-10-26 r87273 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
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: 0x000002b7e16ff0b0>
> .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: 0x000002b7e16ff0b0>
> .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: 0x000002b7e16ff0b0>
> .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: 0x000002b7e16ff0b0>
> 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: 0x000002b7e16ff2f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002b7e16ff2f0>
> .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: 0x000002b7e16ff2f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002b7e16ff2f0>
> .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: 0x000002b7e16ff2f0>
> 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: 0x000002b7e16ff5f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002b7e16ff5f0>
> .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: 0x000002b7e16ff5f0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000002b7e16ff5f0>
> .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: 0x000002b7e16ff5f0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x000002b7e16ff5f0>
> .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: 0x000002b7e16ff5f0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x000002b7e16ff5f0>
> .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: 0x000002b7e16ff5f0>
> 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: 0x000002b7e16ffa10>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x000002b7e16ffa10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002b7e16ffa10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002b7e16ffa10>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1aa8027455ded" "BufferedMatrixFile1aa806f2d7172"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1aa8027455ded" "BufferedMatrixFile1aa806f2d7172"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002b7e16ffdd0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002b7e16ffdd0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000002b7e16ffdd0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000002b7e16ffdd0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x000002b7e16ffdd0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x000002b7e16ffdd0>
> .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: 0x000002b7e0a7aa70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002b7e0a7aa70>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000002b7e0a7aa70>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x000002b7e0a7aa70>
> 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: 0x000002b7e33ff410>
> .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: 0x000002b7e33ff410>
> rm(P)
>
> proc.time()
user system elapsed
0.39 0.06 1.98
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2024-10-26 r87273 ucrt) -- "Unsuffered Consequences"
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Platform: x86_64-w64-mingw32/x64
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.32 0.07 0.39