Ben Bolstad
| Snapshot Date: 2025-01-19 12:27 -0500 (Sun, 19 Jan 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_20 |
| git_last_commit: 32b6f6a |
| git_last_commit_date: 2024-10-29 09:27:20 -0500 (Tue, 29 Oct 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2025-01-20 12:16 -0500 (Mon, 20 Jan 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4746 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves" | 4493 |
| 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 251/2289 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.70.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino8 | Windows Server 2022 Datacenter / x64 | OK | 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: 1.70.0 |
| Command: F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings BufferedMatrix_1.70.0.tar.gz |
| StartedAt: 2025-01-19 22:15:06 -0500 (Sun, 19 Jan 2025) |
| EndedAt: 2025-01-19 22:22:05 -0500 (Sun, 19 Jan 2025) |
| EllapsedTime: 418.2 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings BufferedMatrix_1.70.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck'
* using R version 4.4.2 (2024-10-31 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
gcc.exe (GCC) 13.3.0
GNU Fortran (GCC) 13.3.0
* 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 '1.70.0'
* 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 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 'F:/biocbuild/bbs-3.20-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
'F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/00check.log'
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library 'F:/biocbuild/bbs-3.20-bioc/R/library'
* installing *source* package 'BufferedMatrix' ...
** using staged installation
** libs
using C compiler: 'gcc.exe (GCC) 13.3.0'
gcc -I"F:/biocbuild/bbs-3.20-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"F:/biocbuild/bbs-3.20-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"F:/biocbuild/bbs-3.20-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"F:/biocbuild/bbs-3.20-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 -LF:/biocbuild/bbs-3.20-bioc/R/bin/x64 -lR
installing to F:/biocbuild/bbs-3.20-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 version 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves"
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
0.31 0.15 3.79
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves"
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] "F:/biocbuild/bbs-3.20-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 468478 25.1 1021802 54.6 633411 33.9
Vcells 853910 6.6 8388608 64.0 2003128 15.3
>
>
>
>
> ##
> ## 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 Jan 19 22:15:49 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] "Sun Jan 19 22:15:52 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: 0x0000020ca8aff3b0>
>
>
>
> 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 Jan 19 22:16:53 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] "Sun Jan 19 22:17:21 2025"
>
> ColMode(tmp2)
<pointer: 0x0000020ca8aff3b0>
>
>
>
> ### 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,] 99.881520 -0.7352020 0.5069849 0.2456942
[2,] 1.193160 -2.9824368 -0.8321282 -1.7832909
[3,] 1.363837 -0.1923133 0.7575968 -2.0260580
[4,] -1.229348 0.1719058 -1.5755490 -0.3175010
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.20-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,] 99.881520 0.7352020 0.5069849 0.2456942
[2,] 1.193160 2.9824368 0.8321282 1.7832909
[3,] 1.363837 0.1923133 0.7575968 2.0260580
[4,] 1.229348 0.1719058 1.5755490 0.3175010
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.20-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,] 9.994074 0.8574392 0.7120287 0.4956755
[2,] 1.092319 1.7269733 0.9122106 1.3353992
[3,] 1.167834 0.4385354 0.8704004 1.4233966
[4,] 1.108760 0.4146152 1.2552087 0.5634723
>
> 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: F:/biocbuild/bbs-3.20-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,] 224.82226 34.30959 32.62727 30.20245
[2,] 37.11635 45.25217 34.95423 40.13728
[3,] 38.04218 29.57767 34.46160 41.26002
[4,] 37.31694 29.31806 39.12764 30.95222
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x0000020ca8aff2f0>
> exp(tmp5)
<pointer: 0x0000020ca8aff2f0>
> log(tmp5,2)
<pointer: 0x0000020ca8aff2f0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.9381
> Min(tmp5)
[1] 53.37156
> mean(tmp5)
[1] 73.14703
> Sum(tmp5)
[1] 14629.41
> Var(tmp5)
[1] 857.4098
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.31985 70.73424 72.89292 69.46882 72.74965 71.84271 73.69790 70.46068
[9] 70.83332 66.47020
> rowSums(tmp5)
[1] 1846.397 1414.685 1457.858 1389.376 1454.993 1436.854 1473.958 1409.214
[9] 1416.666 1329.404
> rowVars(tmp5)
[1] 7892.24838 97.89902 98.16062 56.85049 94.43424 53.89647
[7] 45.01595 70.75389 48.80836 52.35689
> rowSd(tmp5)
[1] 88.838327 9.894393 9.907604 7.539926 9.717728 7.341422 6.709393
[8] 8.411533 6.986298 7.235806
> rowMax(tmp5)
[1] 467.93808 94.18646 85.87733 81.43905 88.99210 85.92809 82.85373
[8] 89.35691 89.36706 79.25891
> rowMin(tmp5)
[1] 55.63972 56.91305 55.43296 57.91021 53.37156 59.88340 62.28694 59.08270
[9] 58.77745 54.47683
>
> colMeans(tmp5)
[1] 111.06731 70.69738 71.57374 73.90177 68.16340 69.63680 70.61132
[8] 67.85605 72.44004 72.15544 73.09896 70.33658 70.85885 68.41427
[15] 73.07108 71.91119 72.29292 72.00724 71.42633 71.41989
> colSums(tmp5)
[1] 1110.6731 706.9738 715.7374 739.0177 681.6340 696.3680 706.1132
[8] 678.5605 724.4004 721.5544 730.9896 703.3658 708.5885 684.1427
[15] 730.7108 719.1119 722.9292 720.0724 714.2633 714.1989
> colVars(tmp5)
[1] 15759.55135 117.68335 30.95919 85.64434 50.35518 61.11270
[7] 32.27370 109.34401 70.31580 54.32659 82.28786 47.35799
[13] 101.36105 116.58786 41.17916 106.03141 86.13616 98.15824
[19] 95.50693 73.11065
> colSd(tmp5)
[1] 125.537052 10.848196 5.564098 9.254423 7.096138 7.817461
[7] 5.680995 10.456769 8.385452 7.370657 9.071266 6.881714
[13] 10.067823 10.797586 6.417099 10.297155 9.280957 9.907484
[19] 9.772765 8.550476
> colMax(tmp5)
[1] 467.93808 94.18646 81.43905 86.75687 78.99798 81.89197 79.42235
[8] 88.99210 85.74859 80.62125 89.36706 86.46624 84.63586 89.35691
[15] 80.51881 85.92809 87.20006 84.52403 84.24279 85.06100
> colMin(tmp5)
[1] 62.16711 60.54466 63.06831 62.86244 59.54952 55.43296 62.62590 56.07369
[9] 60.84869 54.47683 57.91021 62.26103 53.37156 56.92604 58.77745 56.91305
[17] 58.43707 56.96487 55.63972 55.24029
>
>
> ### 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] 92.31985 NA 72.89292 69.46882 72.74965 71.84271 73.69790 70.46068
[9] 70.83332 66.47020
> rowSums(tmp5)
[1] 1846.397 NA 1457.858 1389.376 1454.993 1436.854 1473.958 1409.214
[9] 1416.666 1329.404
> rowVars(tmp5)
[1] 7892.24838 102.43795 98.16062 56.85049 94.43424 53.89647
[7] 45.01595 70.75389 48.80836 52.35689
> rowSd(tmp5)
[1] 88.838327 10.121163 9.907604 7.539926 9.717728 7.341422 6.709393
[8] 8.411533 6.986298 7.235806
> rowMax(tmp5)
[1] 467.93808 NA 85.87733 81.43905 88.99210 85.92809 82.85373
[8] 89.35691 89.36706 79.25891
> rowMin(tmp5)
[1] 55.63972 NA 55.43296 57.91021 53.37156 59.88340 62.28694 59.08270
[9] 58.77745 54.47683
>
> colMeans(tmp5)
[1] 111.06731 70.69738 71.57374 73.90177 68.16340 69.63680 70.61132
[8] 67.85605 72.44004 72.15544 73.09896 NA 70.85885 68.41427
[15] 73.07108 71.91119 72.29292 72.00724 71.42633 71.41989
> colSums(tmp5)
[1] 1110.6731 706.9738 715.7374 739.0177 681.6340 696.3680 706.1132
[8] 678.5605 724.4004 721.5544 730.9896 NA 708.5885 684.1427
[15] 730.7108 719.1119 722.9292 720.0724 714.2633 714.1989
> colVars(tmp5)
[1] 15759.55135 117.68335 30.95919 85.64434 50.35518 61.11270
[7] 32.27370 109.34401 70.31580 54.32659 82.28786 NA
[13] 101.36105 116.58786 41.17916 106.03141 86.13616 98.15824
[19] 95.50693 73.11065
> colSd(tmp5)
[1] 125.537052 10.848196 5.564098 9.254423 7.096138 7.817461
[7] 5.680995 10.456769 8.385452 7.370657 9.071266 NA
[13] 10.067823 10.797586 6.417099 10.297155 9.280957 9.907484
[19] 9.772765 8.550476
> colMax(tmp5)
[1] 467.93808 94.18646 81.43905 86.75687 78.99798 81.89197 79.42235
[8] 88.99210 85.74859 80.62125 89.36706 NA 84.63586 89.35691
[15] 80.51881 85.92809 87.20006 84.52403 84.24279 85.06100
> colMin(tmp5)
[1] 62.16711 60.54466 63.06831 62.86244 59.54952 55.43296 62.62590 56.07369
[9] 60.84869 54.47683 57.91021 NA 53.37156 56.92604 58.77745 56.91305
[17] 58.43707 56.96487 55.63972 55.24029
>
> Max(tmp5,na.rm=TRUE)
[1] 467.9381
> Min(tmp5,na.rm=TRUE)
[1] 53.37156
> mean(tmp5,na.rm=TRUE)
[1] 73.13944
> Sum(tmp5,na.rm=TRUE)
[1] 14554.75
> Var(tmp5,na.rm=TRUE)
[1] 861.7286
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.31985 70.52778 72.89292 69.46882 72.74965 71.84271 73.69790 70.46068
[9] 70.83332 66.47020
> rowSums(tmp5,na.rm=TRUE)
[1] 1846.397 1340.028 1457.858 1389.376 1454.993 1436.854 1473.958 1409.214
[9] 1416.666 1329.404
> rowVars(tmp5,na.rm=TRUE)
[1] 7892.24838 102.43795 98.16062 56.85049 94.43424 53.89647
[7] 45.01595 70.75389 48.80836 52.35689
> rowSd(tmp5,na.rm=TRUE)
[1] 88.838327 10.121163 9.907604 7.539926 9.717728 7.341422 6.709393
[8] 8.411533 6.986298 7.235806
> rowMax(tmp5,na.rm=TRUE)
[1] 467.93808 94.18646 85.87733 81.43905 88.99210 85.92809 82.85373
[8] 89.35691 89.36706 79.25891
> rowMin(tmp5,na.rm=TRUE)
[1] 55.63972 56.91305 55.43296 57.91021 53.37156 59.88340 62.28694 59.08270
[9] 58.77745 54.47683
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.06731 70.69738 71.57374 73.90177 68.16340 69.63680 70.61132
[8] 67.85605 72.44004 72.15544 73.09896 69.85653 70.85885 68.41427
[15] 73.07108 71.91119 72.29292 72.00724 71.42633 71.41989
> colSums(tmp5,na.rm=TRUE)
[1] 1110.6731 706.9738 715.7374 739.0177 681.6340 696.3680 706.1132
[8] 678.5605 724.4004 721.5544 730.9896 628.7087 708.5885 684.1427
[15] 730.7108 719.1119 722.9292 720.0724 714.2633 714.1989
> colVars(tmp5,na.rm=TRUE)
[1] 15759.55135 117.68335 30.95919 85.64434 50.35518 61.11270
[7] 32.27370 109.34401 70.31580 54.32659 82.28786 50.68518
[13] 101.36105 116.58786 41.17916 106.03141 86.13616 98.15824
[19] 95.50693 73.11065
> colSd(tmp5,na.rm=TRUE)
[1] 125.537052 10.848196 5.564098 9.254423 7.096138 7.817461
[7] 5.680995 10.456769 8.385452 7.370657 9.071266 7.119353
[13] 10.067823 10.797586 6.417099 10.297155 9.280957 9.907484
[19] 9.772765 8.550476
> colMax(tmp5,na.rm=TRUE)
[1] 467.93808 94.18646 81.43905 86.75687 78.99798 81.89197 79.42235
[8] 88.99210 85.74859 80.62125 89.36706 86.46624 84.63586 89.35691
[15] 80.51881 85.92809 87.20006 84.52403 84.24279 85.06100
> colMin(tmp5,na.rm=TRUE)
[1] 62.16711 60.54466 63.06831 62.86244 59.54952 55.43296 62.62590 56.07369
[9] 60.84869 54.47683 57.91021 62.26103 53.37156 56.92604 58.77745 56.91305
[17] 58.43707 56.96487 55.63972 55.24029
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.31985 NaN 72.89292 69.46882 72.74965 71.84271 73.69790 70.46068
[9] 70.83332 66.47020
> rowSums(tmp5,na.rm=TRUE)
[1] 1846.397 0.000 1457.858 1389.376 1454.993 1436.854 1473.958 1409.214
[9] 1416.666 1329.404
> rowVars(tmp5,na.rm=TRUE)
[1] 7892.24838 NA 98.16062 56.85049 94.43424 53.89647
[7] 45.01595 70.75389 48.80836 52.35689
> rowSd(tmp5,na.rm=TRUE)
[1] 88.838327 NA 9.907604 7.539926 9.717728 7.341422 6.709393
[8] 8.411533 6.986298 7.235806
> rowMax(tmp5,na.rm=TRUE)
[1] 467.93808 NA 85.87733 81.43905 88.99210 85.92809 82.85373
[8] 89.35691 89.36706 79.25891
> rowMin(tmp5,na.rm=TRUE)
[1] 55.63972 NA 55.43296 57.91021 53.37156 59.88340 62.28694 59.08270
[9] 58.77745 54.47683
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.82448 68.08749 71.44275 72.83081 68.74384 70.22219 71.39518
[8] 68.13239 72.88103 72.12379 73.96116 NaN 71.74496 69.69074
[15] 73.77842 73.57765 71.23732 71.56970 72.29769 69.90422
> colSums(tmp5,na.rm=TRUE)
[1] 1033.4203 612.7874 642.9847 655.4773 618.6945 631.9997 642.5566
[8] 613.1915 655.9293 649.1141 665.6505 0.0000 645.7046 627.2166
[15] 664.0058 662.1988 641.1359 644.1273 650.6792 629.1379
> colVars(tmp5,na.rm=TRUE)
[1] 17570.68692 55.76365 34.63605 83.44642 52.85939 64.89657
[7] 29.39541 122.15291 76.91745 61.10614 84.21058 NA
[13] 105.19775 112.83086 40.69796 88.04310 84.36746 108.27432
[19] 98.90362 56.40507
> colSd(tmp5,na.rm=TRUE)
[1] 132.554468 7.467507 5.885240 9.134901 7.270446 8.055841
[7] 5.421753 11.052281 8.770259 7.817042 9.176632 NA
[13] 10.256595 10.622187 6.379495 9.383129 9.185176 10.405495
[19] 9.945030 7.510331
> colMax(tmp5,na.rm=TRUE)
[1] 467.93808 84.30860 81.43905 86.75687 78.99798 81.89197 79.42235
[8] 88.99210 85.74859 80.62125 89.36706 -Inf 84.63586 89.35691
[15] 80.51881 85.92809 87.20006 84.52403 84.24279 79.71320
> colMin(tmp5,na.rm=TRUE)
[1] 62.16711 60.54466 63.06831 62.86244 59.54952 55.43296 62.62590 56.07369
[9] 60.84869 54.47683 57.91021 Inf 53.37156 58.33095 58.77745 60.28894
[17] 58.43707 56.96487 55.63972 55.24029
>
>
>
>
> 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] 299.66872 227.35598 137.06689 166.41538 225.63935 315.75059 197.03669
[8] 144.59774 99.50211 253.96704
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 299.66872 227.35598 137.06689 166.41538 225.63935 315.75059 197.03669
[8] 144.59774 99.50211 253.96704
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 1.136868e-13 -1.705303e-13 -5.684342e-14 5.684342e-14 -5.684342e-14
[6] -2.273737e-13 -2.273737e-13 -1.136868e-13 2.842171e-14 0.000000e+00
[11] 2.131628e-14 0.000000e+00 -1.421085e-13 4.263256e-14 8.526513e-14
[16] 1.136868e-13 -8.526513e-14 -8.526513e-14 0.000000e+00 -2.842171e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
7 18
2 4
6 5
6 20
2 15
9 18
1 14
8 2
2 3
3 9
8 14
7 16
1 9
9 13
1 9
4 18
10 6
3 5
2 17
6 18
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.909914
> Min(tmp)
[1] -2.746041
> mean(tmp)
[1] -0.05917491
> Sum(tmp)
[1] -5.917491
> Var(tmp)
[1] 0.9622266
>
> rowMeans(tmp)
[1] -0.05917491
> rowSums(tmp)
[1] -5.917491
> rowVars(tmp)
[1] 0.9622266
> rowSd(tmp)
[1] 0.9809315
> rowMax(tmp)
[1] 2.909914
> rowMin(tmp)
[1] -2.746041
>
> colMeans(tmp)
[1] 0.010664904 0.734275324 -0.036411239 0.128611151 0.397862829
[6] -0.513454337 0.158851400 0.105792884 0.202747488 0.255844190
[11] -0.096016385 -0.657687893 -0.034628582 0.944921481 0.433192368
[16] 0.915800069 0.245443043 0.038056326 0.176735098 0.829246217
[21] -0.306717998 -0.057547588 1.160686264 1.352942523 1.746178089
[26] 2.909914330 0.623419102 0.016783434 -1.356922334 0.085521741
[31] 0.725908678 -0.284661968 0.606981219 1.681057970 -2.044985643
[36] -1.708720425 -0.263863021 0.009110828 -2.020593121 -0.114115727
[41] 1.621575344 0.064167235 -0.671737259 -0.453688292 1.257261953
[46] -0.859790823 0.245720591 0.233311736 -0.187866417 -2.077923809
[51] -0.828607271 -2.368996922 0.125738931 0.675937663 -0.934023590
[56] -0.728909883 -1.304170833 -2.746041054 -1.287344032 0.459346415
[61] -1.087670454 0.295742676 -0.295133305 0.748524932 -0.047412688
[66] 0.799281233 -0.832833644 1.145825303 -0.023749833 -0.236572343
[71] 0.586951934 -0.575003300 -1.631706921 1.030734637 -1.535715645
[76] 0.346664398 1.436968681 0.404523891 -0.355493443 -0.263260649
[81] 0.755355563 0.239209269 -2.498349309 -0.299875113 0.863299378
[86] -0.496433921 -1.048848112 -0.422619922 1.122628812 -0.469439371
[91] -0.360888127 0.103104447 0.832856477 -0.510682239 -0.112290253
[96] -1.099675687 -0.767842412 -0.170716828 1.503818310 -0.224949341
> colSums(tmp)
[1] 0.010664904 0.734275324 -0.036411239 0.128611151 0.397862829
[6] -0.513454337 0.158851400 0.105792884 0.202747488 0.255844190
[11] -0.096016385 -0.657687893 -0.034628582 0.944921481 0.433192368
[16] 0.915800069 0.245443043 0.038056326 0.176735098 0.829246217
[21] -0.306717998 -0.057547588 1.160686264 1.352942523 1.746178089
[26] 2.909914330 0.623419102 0.016783434 -1.356922334 0.085521741
[31] 0.725908678 -0.284661968 0.606981219 1.681057970 -2.044985643
[36] -1.708720425 -0.263863021 0.009110828 -2.020593121 -0.114115727
[41] 1.621575344 0.064167235 -0.671737259 -0.453688292 1.257261953
[46] -0.859790823 0.245720591 0.233311736 -0.187866417 -2.077923809
[51] -0.828607271 -2.368996922 0.125738931 0.675937663 -0.934023590
[56] -0.728909883 -1.304170833 -2.746041054 -1.287344032 0.459346415
[61] -1.087670454 0.295742676 -0.295133305 0.748524932 -0.047412688
[66] 0.799281233 -0.832833644 1.145825303 -0.023749833 -0.236572343
[71] 0.586951934 -0.575003300 -1.631706921 1.030734637 -1.535715645
[76] 0.346664398 1.436968681 0.404523891 -0.355493443 -0.263260649
[81] 0.755355563 0.239209269 -2.498349309 -0.299875113 0.863299378
[86] -0.496433921 -1.048848112 -0.422619922 1.122628812 -0.469439371
[91] -0.360888127 0.103104447 0.832856477 -0.510682239 -0.112290253
[96] -1.099675687 -0.767842412 -0.170716828 1.503818310 -0.224949341
> 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] 0.010664904 0.734275324 -0.036411239 0.128611151 0.397862829
[6] -0.513454337 0.158851400 0.105792884 0.202747488 0.255844190
[11] -0.096016385 -0.657687893 -0.034628582 0.944921481 0.433192368
[16] 0.915800069 0.245443043 0.038056326 0.176735098 0.829246217
[21] -0.306717998 -0.057547588 1.160686264 1.352942523 1.746178089
[26] 2.909914330 0.623419102 0.016783434 -1.356922334 0.085521741
[31] 0.725908678 -0.284661968 0.606981219 1.681057970 -2.044985643
[36] -1.708720425 -0.263863021 0.009110828 -2.020593121 -0.114115727
[41] 1.621575344 0.064167235 -0.671737259 -0.453688292 1.257261953
[46] -0.859790823 0.245720591 0.233311736 -0.187866417 -2.077923809
[51] -0.828607271 -2.368996922 0.125738931 0.675937663 -0.934023590
[56] -0.728909883 -1.304170833 -2.746041054 -1.287344032 0.459346415
[61] -1.087670454 0.295742676 -0.295133305 0.748524932 -0.047412688
[66] 0.799281233 -0.832833644 1.145825303 -0.023749833 -0.236572343
[71] 0.586951934 -0.575003300 -1.631706921 1.030734637 -1.535715645
[76] 0.346664398 1.436968681 0.404523891 -0.355493443 -0.263260649
[81] 0.755355563 0.239209269 -2.498349309 -0.299875113 0.863299378
[86] -0.496433921 -1.048848112 -0.422619922 1.122628812 -0.469439371
[91] -0.360888127 0.103104447 0.832856477 -0.510682239 -0.112290253
[96] -1.099675687 -0.767842412 -0.170716828 1.503818310 -0.224949341
> colMin(tmp)
[1] 0.010664904 0.734275324 -0.036411239 0.128611151 0.397862829
[6] -0.513454337 0.158851400 0.105792884 0.202747488 0.255844190
[11] -0.096016385 -0.657687893 -0.034628582 0.944921481 0.433192368
[16] 0.915800069 0.245443043 0.038056326 0.176735098 0.829246217
[21] -0.306717998 -0.057547588 1.160686264 1.352942523 1.746178089
[26] 2.909914330 0.623419102 0.016783434 -1.356922334 0.085521741
[31] 0.725908678 -0.284661968 0.606981219 1.681057970 -2.044985643
[36] -1.708720425 -0.263863021 0.009110828 -2.020593121 -0.114115727
[41] 1.621575344 0.064167235 -0.671737259 -0.453688292 1.257261953
[46] -0.859790823 0.245720591 0.233311736 -0.187866417 -2.077923809
[51] -0.828607271 -2.368996922 0.125738931 0.675937663 -0.934023590
[56] -0.728909883 -1.304170833 -2.746041054 -1.287344032 0.459346415
[61] -1.087670454 0.295742676 -0.295133305 0.748524932 -0.047412688
[66] 0.799281233 -0.832833644 1.145825303 -0.023749833 -0.236572343
[71] 0.586951934 -0.575003300 -1.631706921 1.030734637 -1.535715645
[76] 0.346664398 1.436968681 0.404523891 -0.355493443 -0.263260649
[81] 0.755355563 0.239209269 -2.498349309 -0.299875113 0.863299378
[86] -0.496433921 -1.048848112 -0.422619922 1.122628812 -0.469439371
[91] -0.360888127 0.103104447 0.832856477 -0.510682239 -0.112290253
[96] -1.099675687 -0.767842412 -0.170716828 1.503818310 -0.224949341
> colMedians(tmp)
[1] 0.010664904 0.734275324 -0.036411239 0.128611151 0.397862829
[6] -0.513454337 0.158851400 0.105792884 0.202747488 0.255844190
[11] -0.096016385 -0.657687893 -0.034628582 0.944921481 0.433192368
[16] 0.915800069 0.245443043 0.038056326 0.176735098 0.829246217
[21] -0.306717998 -0.057547588 1.160686264 1.352942523 1.746178089
[26] 2.909914330 0.623419102 0.016783434 -1.356922334 0.085521741
[31] 0.725908678 -0.284661968 0.606981219 1.681057970 -2.044985643
[36] -1.708720425 -0.263863021 0.009110828 -2.020593121 -0.114115727
[41] 1.621575344 0.064167235 -0.671737259 -0.453688292 1.257261953
[46] -0.859790823 0.245720591 0.233311736 -0.187866417 -2.077923809
[51] -0.828607271 -2.368996922 0.125738931 0.675937663 -0.934023590
[56] -0.728909883 -1.304170833 -2.746041054 -1.287344032 0.459346415
[61] -1.087670454 0.295742676 -0.295133305 0.748524932 -0.047412688
[66] 0.799281233 -0.832833644 1.145825303 -0.023749833 -0.236572343
[71] 0.586951934 -0.575003300 -1.631706921 1.030734637 -1.535715645
[76] 0.346664398 1.436968681 0.404523891 -0.355493443 -0.263260649
[81] 0.755355563 0.239209269 -2.498349309 -0.299875113 0.863299378
[86] -0.496433921 -1.048848112 -0.422619922 1.122628812 -0.469439371
[91] -0.360888127 0.103104447 0.832856477 -0.510682239 -0.112290253
[96] -1.099675687 -0.767842412 -0.170716828 1.503818310 -0.224949341
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.0106649 0.7342753 -0.03641124 0.1286112 0.3978628 -0.5134543 0.1588514
[2,] 0.0106649 0.7342753 -0.03641124 0.1286112 0.3978628 -0.5134543 0.1588514
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.1057929 0.2027475 0.2558442 -0.09601639 -0.6576879 -0.03462858 0.9449215
[2,] 0.1057929 0.2027475 0.2558442 -0.09601639 -0.6576879 -0.03462858 0.9449215
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.4331924 0.9158001 0.245443 0.03805633 0.1767351 0.8292462 -0.306718
[2,] 0.4331924 0.9158001 0.245443 0.03805633 0.1767351 0.8292462 -0.306718
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.05754759 1.160686 1.352943 1.746178 2.909914 0.6234191 0.01678343
[2,] -0.05754759 1.160686 1.352943 1.746178 2.909914 0.6234191 0.01678343
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.356922 0.08552174 0.7259087 -0.284662 0.6069812 1.681058 -2.044986
[2,] -1.356922 0.08552174 0.7259087 -0.284662 0.6069812 1.681058 -2.044986
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.70872 -0.263863 0.009110828 -2.020593 -0.1141157 1.621575 0.06416724
[2,] -1.70872 -0.263863 0.009110828 -2.020593 -0.1141157 1.621575 0.06416724
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.6717373 -0.4536883 1.257262 -0.8597908 0.2457206 0.2333117 -0.1878664
[2,] -0.6717373 -0.4536883 1.257262 -0.8597908 0.2457206 0.2333117 -0.1878664
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -2.077924 -0.8286073 -2.368997 0.1257389 0.6759377 -0.9340236 -0.7289099
[2,] -2.077924 -0.8286073 -2.368997 0.1257389 0.6759377 -0.9340236 -0.7289099
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -1.304171 -2.746041 -1.287344 0.4593464 -1.08767 0.2957427 -0.2951333
[2,] -1.304171 -2.746041 -1.287344 0.4593464 -1.08767 0.2957427 -0.2951333
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.7485249 -0.04741269 0.7992812 -0.8328336 1.145825 -0.02374983 -0.2365723
[2,] 0.7485249 -0.04741269 0.7992812 -0.8328336 1.145825 -0.02374983 -0.2365723
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.5869519 -0.5750033 -1.631707 1.030735 -1.535716 0.3466644 1.436969
[2,] 0.5869519 -0.5750033 -1.631707 1.030735 -1.535716 0.3466644 1.436969
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.4045239 -0.3554934 -0.2632606 0.7553556 0.2392093 -2.498349 -0.2998751
[2,] 0.4045239 -0.3554934 -0.2632606 0.7553556 0.2392093 -2.498349 -0.2998751
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.8632994 -0.4964339 -1.048848 -0.4226199 1.122629 -0.4694394 -0.3608881
[2,] 0.8632994 -0.4964339 -1.048848 -0.4226199 1.122629 -0.4694394 -0.3608881
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.1031044 0.8328565 -0.5106822 -0.1122903 -1.099676 -0.7678424 -0.1707168
[2,] 0.1031044 0.8328565 -0.5106822 -0.1122903 -1.099676 -0.7678424 -0.1707168
[,99] [,100]
[1,] 1.503818 -0.2249493
[2,] 1.503818 -0.2249493
>
>
> Max(tmp2)
[1] 2.791736
> Min(tmp2)
[1] -1.949799
> mean(tmp2)
[1] 0.05541459
> Sum(tmp2)
[1] 5.541459
> Var(tmp2)
[1] 0.946464
>
> rowMeans(tmp2)
[1] 1.06723174 1.80193214 0.59681482 -1.94979882 0.87944061 -1.27827355
[7] -0.21168169 0.83364267 -0.95373668 -0.09831704 0.28848203 -0.36483193
[13] 0.57907729 0.08368005 0.83410673 -0.35388735 -0.78982045 0.99132945
[19] -0.10203961 -0.44392649 0.31500144 -0.09938183 -0.81099311 -1.34566631
[25] 0.24574396 0.16342909 -0.55112503 -0.04840363 0.63459812 -1.48628592
[31] -1.59535909 -0.36999435 -0.64524067 1.33850840 0.15311050 -0.75015876
[37] 1.03857891 0.07499122 0.07742823 -0.64302811 -1.26903660 -0.96498821
[43] 1.44827785 -0.35059502 -0.90844923 -0.76316144 0.48419454 -0.46987227
[49] -1.11666463 0.41244464 -0.95695946 -0.03386962 1.24990890 2.79173563
[55] 2.65693783 0.13191248 -0.56331658 0.16798223 1.37776862 1.20050496
[61] 0.47780772 -0.14452927 0.61728842 -0.33965442 -0.06213677 -0.48453972
[67] 0.53908236 -1.18910283 2.62027769 -0.04891536 1.15624344 0.54870740
[73] -0.01234508 0.98020849 0.46249342 0.46649891 1.22411422 0.37229804
[79] -1.64209632 -1.76706512 -0.23647147 1.49080356 -0.46657894 -0.58808314
[85] -1.72198777 -0.48215841 1.37792096 0.75312199 -1.17932725 1.48068287
[91] 0.16052858 -0.08178640 -1.00661183 -0.29540666 -0.37413151 0.04446429
[97] 1.16611501 1.09790213 -0.71222210 -0.28988195
> rowSums(tmp2)
[1] 1.06723174 1.80193214 0.59681482 -1.94979882 0.87944061 -1.27827355
[7] -0.21168169 0.83364267 -0.95373668 -0.09831704 0.28848203 -0.36483193
[13] 0.57907729 0.08368005 0.83410673 -0.35388735 -0.78982045 0.99132945
[19] -0.10203961 -0.44392649 0.31500144 -0.09938183 -0.81099311 -1.34566631
[25] 0.24574396 0.16342909 -0.55112503 -0.04840363 0.63459812 -1.48628592
[31] -1.59535909 -0.36999435 -0.64524067 1.33850840 0.15311050 -0.75015876
[37] 1.03857891 0.07499122 0.07742823 -0.64302811 -1.26903660 -0.96498821
[43] 1.44827785 -0.35059502 -0.90844923 -0.76316144 0.48419454 -0.46987227
[49] -1.11666463 0.41244464 -0.95695946 -0.03386962 1.24990890 2.79173563
[55] 2.65693783 0.13191248 -0.56331658 0.16798223 1.37776862 1.20050496
[61] 0.47780772 -0.14452927 0.61728842 -0.33965442 -0.06213677 -0.48453972
[67] 0.53908236 -1.18910283 2.62027769 -0.04891536 1.15624344 0.54870740
[73] -0.01234508 0.98020849 0.46249342 0.46649891 1.22411422 0.37229804
[79] -1.64209632 -1.76706512 -0.23647147 1.49080356 -0.46657894 -0.58808314
[85] -1.72198777 -0.48215841 1.37792096 0.75312199 -1.17932725 1.48068287
[91] 0.16052858 -0.08178640 -1.00661183 -0.29540666 -0.37413151 0.04446429
[97] 1.16611501 1.09790213 -0.71222210 -0.28988195
> 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] 1.06723174 1.80193214 0.59681482 -1.94979882 0.87944061 -1.27827355
[7] -0.21168169 0.83364267 -0.95373668 -0.09831704 0.28848203 -0.36483193
[13] 0.57907729 0.08368005 0.83410673 -0.35388735 -0.78982045 0.99132945
[19] -0.10203961 -0.44392649 0.31500144 -0.09938183 -0.81099311 -1.34566631
[25] 0.24574396 0.16342909 -0.55112503 -0.04840363 0.63459812 -1.48628592
[31] -1.59535909 -0.36999435 -0.64524067 1.33850840 0.15311050 -0.75015876
[37] 1.03857891 0.07499122 0.07742823 -0.64302811 -1.26903660 -0.96498821
[43] 1.44827785 -0.35059502 -0.90844923 -0.76316144 0.48419454 -0.46987227
[49] -1.11666463 0.41244464 -0.95695946 -0.03386962 1.24990890 2.79173563
[55] 2.65693783 0.13191248 -0.56331658 0.16798223 1.37776862 1.20050496
[61] 0.47780772 -0.14452927 0.61728842 -0.33965442 -0.06213677 -0.48453972
[67] 0.53908236 -1.18910283 2.62027769 -0.04891536 1.15624344 0.54870740
[73] -0.01234508 0.98020849 0.46249342 0.46649891 1.22411422 0.37229804
[79] -1.64209632 -1.76706512 -0.23647147 1.49080356 -0.46657894 -0.58808314
[85] -1.72198777 -0.48215841 1.37792096 0.75312199 -1.17932725 1.48068287
[91] 0.16052858 -0.08178640 -1.00661183 -0.29540666 -0.37413151 0.04446429
[97] 1.16611501 1.09790213 -0.71222210 -0.28988195
> rowMin(tmp2)
[1] 1.06723174 1.80193214 0.59681482 -1.94979882 0.87944061 -1.27827355
[7] -0.21168169 0.83364267 -0.95373668 -0.09831704 0.28848203 -0.36483193
[13] 0.57907729 0.08368005 0.83410673 -0.35388735 -0.78982045 0.99132945
[19] -0.10203961 -0.44392649 0.31500144 -0.09938183 -0.81099311 -1.34566631
[25] 0.24574396 0.16342909 -0.55112503 -0.04840363 0.63459812 -1.48628592
[31] -1.59535909 -0.36999435 -0.64524067 1.33850840 0.15311050 -0.75015876
[37] 1.03857891 0.07499122 0.07742823 -0.64302811 -1.26903660 -0.96498821
[43] 1.44827785 -0.35059502 -0.90844923 -0.76316144 0.48419454 -0.46987227
[49] -1.11666463 0.41244464 -0.95695946 -0.03386962 1.24990890 2.79173563
[55] 2.65693783 0.13191248 -0.56331658 0.16798223 1.37776862 1.20050496
[61] 0.47780772 -0.14452927 0.61728842 -0.33965442 -0.06213677 -0.48453972
[67] 0.53908236 -1.18910283 2.62027769 -0.04891536 1.15624344 0.54870740
[73] -0.01234508 0.98020849 0.46249342 0.46649891 1.22411422 0.37229804
[79] -1.64209632 -1.76706512 -0.23647147 1.49080356 -0.46657894 -0.58808314
[85] -1.72198777 -0.48215841 1.37792096 0.75312199 -1.17932725 1.48068287
[91] 0.16052858 -0.08178640 -1.00661183 -0.29540666 -0.37413151 0.04446429
[97] 1.16611501 1.09790213 -0.71222210 -0.28988195
>
> colMeans(tmp2)
[1] 0.05541459
> colSums(tmp2)
[1] 5.541459
> colVars(tmp2)
[1] 0.946464
> colSd(tmp2)
[1] 0.9728638
> colMax(tmp2)
[1] 2.791736
> colMin(tmp2)
[1] -1.949799
> colMedians(tmp2)
[1] -0.04113662
> colRanges(tmp2)
[,1]
[1,] -1.949799
[2,] 2.791736
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.0700048 -2.8186933 0.5828904 2.3019223 1.9839174 -1.1441068
[7] 0.8155603 0.8236432 -4.7236527 -2.9840892
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.2355425
[2,] -0.3065364
[3,] 0.3765256
[4,] 0.5952571
[5,] 0.8949565
>
> rowApply(tmp,sum)
[1] 3.7420062 -0.8005872 -7.1621248 0.6629635 1.0730948 1.1714259
[7] 5.4821007 -3.7561664 -3.6684615 -0.8368549
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 6 2 7 2 8 8 6 9 7 8
[2,] 10 1 1 9 5 2 7 4 8 4
[3,] 4 6 3 8 7 6 4 8 6 7
[4,] 8 8 9 1 6 9 3 2 10 9
[5,] 1 10 8 5 1 7 1 10 4 10
[6,] 5 7 6 6 4 4 5 6 9 3
[7,] 9 9 2 4 10 5 10 5 5 2
[8,] 2 5 10 3 9 10 8 3 1 6
[9,] 3 3 5 7 3 3 2 1 3 5
[10,] 7 4 4 10 2 1 9 7 2 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.10306116 1.08854623 1.64054373 3.55111526 -3.12373145 -1.91693091
[7] -1.71854901 3.45689000 -4.40494927 1.81227910 -3.56873028 1.87054345
[13] -1.87816899 2.27958674 0.04914824 -0.43167399 -2.18801905 -1.32596468
[19] -1.41931428 -0.79457120
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.9413628
[2,] -0.6944907
[3,] -0.4640845
[4,] -0.3652315
[5,] 1.3621083
>
> rowApply(tmp,sum)
[1] -2.151086 -7.577108 -4.872589 8.407762 -2.931991
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 20 2 11 5 6
[2,] 15 13 15 9 11
[3,] 10 8 17 15 18
[4,] 17 16 14 20 10
[5,] 4 6 4 14 4
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.3621083 0.6268117 -0.03042974 0.9220191 -1.0623897 1.21517630
[2,] -1.9413628 -0.0900737 -0.78594658 0.5290544 -1.1221012 -0.89001206
[3,] -0.3652315 0.4936807 0.63210842 0.4395809 -0.9724514 -2.10352415
[4,] -0.4640845 0.3524691 1.00702121 1.9924062 0.8745139 -0.10497944
[5,] -0.6944907 -0.2943416 0.81779042 -0.3319454 -0.8413030 -0.03359156
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -2.2111053 0.3138306 -0.9467359 -0.06365577 -1.2201858 -0.9295520
[2,] -0.6495602 0.5398284 -1.2575767 1.47971855 -2.6397704 1.1487538
[3,] -0.9508212 -0.3656920 -0.2929633 -0.05348870 -1.4509516 0.9551804
[4,] 1.8692252 1.0561987 -0.2901588 1.18079449 1.5777581 0.4312093
[5,] 0.2237125 1.9127243 -1.6175145 -0.73108946 0.1644195 0.2649520
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.7070729 0.4328103 0.3779713 -0.02256411 -0.8152216 -1.3339864
[2,] 0.1320917 0.7178144 -0.2881588 -0.15543685 0.4457398 -1.2295661
[3,] -1.1683240 1.3316612 0.9565922 0.50467564 -0.3748411 -0.5533766
[4,] -0.6700380 0.4625690 -0.1557131 -0.86211821 -0.8108473 0.7975240
[5,] 0.5351742 -0.6652681 -0.8415434 0.10376954 -0.6328488 0.9934404
[,19] [,20]
[1,] 0.7116456 1.2294401
[2,] -1.1848096 -0.3357340
[3,] -0.9001010 -0.6343019
[4,] 0.8652657 -0.7012536
[5,] -0.9113149 -0.3527218
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.20-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: F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 625 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 542 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.20-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 0.2119718 0.6487449 -0.5140255 -0.2229049 1.13812 -0.1933071 0.59903
col8 col9 col10 col11 col12 col13 col14
row1 0.3926261 -0.5547602 2.413449 -0.7216033 -1.96917 0.510554 -0.04466518
col15 col16 col17 col18 col19 col20
row1 -0.8741562 1.208425 -0.4697011 -0.05528169 -1.859922 -0.8204608
> tmp[,"col10"]
col10
row1 2.41344871
row2 0.07622329
row3 1.32858277
row4 0.20109343
row5 0.12249817
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.2119718 0.6487449 -0.51402550 -0.2229049 1.138120 -0.1933071 0.5990300
row5 1.4203223 -0.0138210 -0.08500663 0.2566715 0.297964 0.8357052 -0.4884076
col8 col9 col10 col11 col12 col13
row1 0.3926261 -0.5547602 2.4134487 -0.7216033 -1.9691695 0.5105540
row5 -0.2656431 0.5592668 0.1224982 -0.7511612 -0.1261863 -0.8120731
col14 col15 col16 col17 col18 col19
row1 -0.04466518 -0.8741562 1.208425 -0.46970113 -0.05528169 -1.8599217
row5 -1.07219293 -0.6611108 1.111270 -0.01049885 -0.47548729 -0.1847138
col20
row1 -0.8204608
row5 -2.1008310
> tmp[,c("col6","col20")]
col6 col20
row1 -0.19330709 -0.8204608
row2 -0.02550734 -1.5083602
row3 0.37846053 -0.2350865
row4 -0.95690231 -1.7400790
row5 0.83570522 -2.1008310
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.1933071 -0.8204608
row5 0.8357052 -2.1008310
>
>
>
>
> 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 49.71436 50.4843 50.06732 49.30509 49.75819 106.1119 50.35908 51.41913
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.65116 49.88886 51.2047 48.85395 51.35021 50.30941 50.93165 50.99033
col17 col18 col19 col20
row1 50.44304 50.5726 50.0178 105.3128
> tmp[,"col10"]
col10
row1 49.88886
row2 29.03681
row3 30.25527
row4 30.94801
row5 50.62687
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.71436 50.48430 50.06732 49.30509 49.75819 106.1119 50.35908 51.41913
row5 50.44447 48.37427 51.73183 52.31429 49.41169 103.0478 50.21401 49.84960
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.65116 49.88886 51.2047 48.85395 51.35021 50.30941 50.93165 50.99033
row5 49.70382 50.62687 50.4602 48.02979 49.37593 49.82280 50.05744 49.79046
col17 col18 col19 col20
row1 50.44304 50.57260 50.0178 105.3128
row5 50.16889 49.90108 51.6435 104.7289
> tmp[,c("col6","col20")]
col6 col20
row1 106.11192 105.31277
row2 74.68058 75.79352
row3 75.75890 75.27475
row4 75.73877 73.88309
row5 103.04783 104.72889
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.1119 105.3128
row5 103.0478 104.7289
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.1119 105.3128
row5 103.0478 104.7289
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.29633291
[2,] -0.23648687
[3,] -0.05471775
[4,] -0.19908951
[5,] -0.77382074
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.5002735 -0.07391508
[2,] 1.1044160 0.28809885
[3,] 0.2593237 -1.29489159
[4,] -1.4204799 -1.42632791
[5,] 1.5867280 0.64267285
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.7876484 0.67139407
[2,] -0.6551230 1.44393671
[3,] 0.4599736 0.34081816
[4,] -1.7157369 0.04161574
[5,] 1.5003869 -0.23116485
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.7876484
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.7876484
[2,] -0.6551230
>
>
>
> 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 1.7901154 -0.9803269 -0.478724 0.6007617 -1.096253 1.4299755 0.5165155
row1 -0.2100463 -0.9139923 -1.180029 -0.9092423 -2.230363 -0.4168859 1.0548995
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.1831009 -0.8052612 -0.3326885 -0.3256576 -0.6116816 -0.7122096
row1 -0.4709145 1.6286426 -0.1220142 -0.8487218 -0.8582884 0.4378252
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 0.6151112 1.243805 0.9397511 -0.8102649 -1.219298 -0.5758475 -0.3822038
row1 0.5525170 1.545300 -1.2709831 -0.8494554 -2.341035 0.7665847 -0.3614821
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.4119226 -0.346021 -1.059537 0.09810233 0.7430551 -0.5669659 0.6353688
[,8] [,9] [,10]
row2 0.6896536 0.3459793 0.3337321
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.4830198 0.2464175 0.4777515 1.296239 0.2671917 -0.6955852 0.01363267
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.2534989 -0.7949269 -0.4468487 0.04639555 0.472638 0.6415544 -0.124937
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.4390842 1.200537 -0.805722 -0.07063633 -1.424289 -0.6274593
>
>
> 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: 0x0000020ca8aff650>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM220056e346a0"
[2] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM220054cc4e54"
[3] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM220010728ba"
[4] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM220059295c71"
[5] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM2200334b7159"
[6] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM220014d7d49"
[7] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM220027392b71"
[8] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM220045a53ba3"
[9] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM2200204b211f"
[10] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM22004a2c649c"
[11] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM22004bf54b99"
[12] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM22005e8d1741"
[13] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM220062e67f66"
[14] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM2200498c725d"
[15] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM22006f8c28ca"
>
>
> ### 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: 0x0000020cab2ff7d0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x0000020cab2ff7d0>
Warning message:
In dir.create(new.directory) :
'F:\biocbuild\bbs-3.20-bioc\meat\BufferedMatrix.Rcheck\tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x0000020cab2ff7d0>
> rowMedians(tmp)
[1] 0.145795937 0.021627112 -0.069943452 -0.369982500 -0.054668767
[6] 0.475653009 -0.076990596 -0.361230436 0.275039147 0.433062849
[11] 0.130449669 -0.163131504 -0.132556058 -0.101437811 0.311276712
[16] 0.112003749 0.397556787 -0.152789303 0.388318872 0.427857587
[21] 0.146262053 -0.412476627 0.421083077 -0.166605872 0.663899978
[26] -0.132046779 0.083550642 0.400910192 0.199367857 -0.340270104
[31] 0.373530728 0.103856180 0.031942619 -0.136464374 0.117176280
[36] -0.622676720 0.205097575 0.083464223 -0.477629766 0.049447855
[41] 0.064007528 -0.218176287 -0.160849361 -0.280807655 -0.081658770
[46] 0.200951192 0.110440094 -0.029474368 -0.109060178 0.220351212
[51] 0.443245600 -0.171612826 -0.159994726 0.278706633 -0.151558027
[56] -0.194955670 -0.191557813 0.501082907 0.218276661 -0.355177350
[61] 0.127749008 -0.337569464 -0.478698637 0.187126214 -0.526738031
[66] 0.184330385 -0.216206401 -0.237811172 0.185820990 -0.006171869
[71] 0.501908312 -0.689586632 0.277150766 -0.136686863 0.271199542
[76] 0.159445024 0.377142275 -0.594310646 0.369106384 -0.525171895
[81] 0.109137558 0.322886513 -0.510125382 -0.160850932 0.290927846
[86] -0.425146711 0.073166824 0.032057307 0.383428456 -0.378780018
[91] -0.495737621 -0.299908836 -0.113351859 -0.200443124 0.154502567
[96] -0.634723142 -0.562179777 0.156618994 0.225692240 -0.134900799
[101] -0.229674055 -0.416172482 -0.236839154 0.107000300 -0.164488994
[106] -0.240802872 -0.099157858 -0.219545445 0.144270471 0.101556517
[111] 0.143847554 -0.139754438 -0.147984989 0.360932187 0.014613978
[116] 0.150811914 -0.234974157 -0.024089111 -0.009604377 0.107109913
[121] 0.138830737 -0.083748270 0.596871949 -0.402751937 -0.279777084
[126] -0.040672870 -0.233604918 -0.298711909 -0.017834221 0.013024168
[131] -0.149126569 -0.306437594 -0.193766944 0.800783699 -0.213431633
[136] -0.131548124 -0.056176039 -0.186995991 0.016489295 -0.331100008
[141] -0.393997236 -0.098405446 0.163272297 0.071018564 -0.133150794
[146] 0.231461126 0.080055219 -0.559656976 -0.186935629 0.084813053
[151] 0.005740745 0.492225379 0.014011603 0.296738008 0.291227115
[156] 0.629829255 0.021021490 -0.245807160 -0.327522176 -0.826908090
[161] -0.613946938 -0.064983840 -0.256680723 0.114081611 -0.337656312
[166] 0.044725916 0.020392326 0.329258496 0.273966972 -0.300200817
[171] 0.469477115 0.394133346 -0.169792548 -0.657984565 0.190404479
[176] 0.180856375 -0.141674325 -0.530006733 -0.548262678 0.100539074
[181] -0.190322300 -0.248295601 0.350829629 0.037158889 -0.052920443
[186] 0.124842695 0.004370569 0.328729176 0.337627385 -0.464347144
[191] -0.048167619 -0.151478303 -0.113071627 0.140620881 0.351334292
[196] 0.233338877 0.097069496 -0.438552656 0.126569891 0.489470736
[201] 0.041812864 -0.046422216 -0.059789945 -0.034739856 -0.222349302
[206] -0.074021415 0.153969920 -0.079378657 -0.152315680 0.604596594
[211] 0.062393108 -0.005767985 0.129797596 0.172400887 -0.157014039
[216] -0.464982985 -0.472911816 0.246950494 0.141994385 0.273249051
[221] -0.494622104 -0.223225321 -0.242757243 0.200774558 -0.013304869
[226] 0.175043578 -0.022295330 0.407718814 -0.309992078 0.367232613
>
> proc.time()
user system elapsed
3.93 16.54 372.15
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves"
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: 0x0000025788af8110>
> .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: 0x0000025788af8110>
> .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: 0x0000025788af8110>
> .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: 0x0000025788af8110>
> 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: 0x0000025788af8590>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000025788af8590>
> .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: 0x0000025788af8590>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000025788af8590>
> .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: 0x0000025788af8590>
> 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: 0x0000025788af84d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000025788af84d0>
> .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: 0x0000025788af84d0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x0000025788af84d0>
> .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: 0x0000025788af84d0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x0000025788af84d0>
> .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: 0x0000025788af84d0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x0000025788af84d0>
> .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: 0x0000025788af84d0>
> 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: 0x0000025788af85f0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x0000025788af85f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000025788af85f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000025788af85f0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile33407203168b" "BufferedMatrixFile33407bc4bbc"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile33407203168b" "BufferedMatrixFile33407bc4bbc"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000025788af8b90>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000025788af8b90>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x0000025788af8b90>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x0000025788af8b90>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x0000025788af8b90>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x0000025788af8b90>
> .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: 0x0000025788af8650>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000025788af8650>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x0000025788af8650>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x0000025788af8650>
> 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: 0x0000025788af8170>
> .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: 0x0000025788af8170>
> rm(P)
>
> proc.time()
user system elapsed
0.31 0.18 0.98
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves"
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.
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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
0.34 0.06 0.37