Ben Bolstad
| Snapshot Date: 2021-05-05 14:51:38 -0400 (Wed, 05 May 2021) |
| URL: https://git.bioconductor.org/packages/BufferedMatrix |
| Branch: RELEASE_3_12 |
| Last Commit: eae3841 |
| Last Changed Date: 2020-10-27 10:30:14 -0400 (Tue, 27 Oct 2020) |
| Back to Multiple platform build/check report for BioC 3.12 |
|
This page was generated on 2021-05-06 12:30:05 -0400 (Thu, 06 May 2021).
|
To the developers/maintainers of the BufferedMatrix package: Please make sure to use the following settings in order to reproduce any error or warning you see on this page. |
| Package 215/1974 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.54.0 (landing page) Ben Bolstad
| malbec1 | Linux (Ubuntu 18.04.5 LTS) / x86_64 | OK | OK | OK | | ||||||||
| tokay1 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 10.14.6 Mojave / x86_64 | OK | OK | OK | OK | | ||||||||
| Package: BufferedMatrix |
| Version: 1.54.0 |
| Command: C:\Users\biocbuild\bbs-3.12-bioc\R\bin\R.exe CMD check --force-multiarch --install=check:BufferedMatrix.install-out.txt --library=C:\Users\biocbuild\bbs-3.12-bioc\R\library --no-vignettes --timings BufferedMatrix_1.54.0.tar.gz |
| StartedAt: 2021-05-06 01:03:37 -0400 (Thu, 06 May 2021) |
| EndedAt: 2021-05-06 01:05:23 -0400 (Thu, 06 May 2021) |
| EllapsedTime: 105.5 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### C:\Users\biocbuild\bbs-3.12-bioc\R\bin\R.exe CMD check --force-multiarch --install=check:BufferedMatrix.install-out.txt --library=C:\Users\biocbuild\bbs-3.12-bioc\R\library --no-vignettes --timings BufferedMatrix_1.54.0.tar.gz ### ############################################################################## ############################################################################## * using log directory 'C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck' * using R version 4.0.5 (2021-03-31) * using platform: x86_64-w64-mingw32 (64-bit) * using session charset: ISO8859-1 * using option '--no-vignettes' * checking for file 'BufferedMatrix/DESCRIPTION' ... OK * this is package 'BufferedMatrix' version '1.54.0' * 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 * 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 R files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * loading checks for arch 'i386' ** 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 * loading checks for arch 'x64' ** 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 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 i386 is not available Note: information on .o files for x64 is not available File 'C:/Users/biocbuild/bbs-3.12-bioc/R/library/BufferedMatrix/libs/i386/BufferedMatrix.dll': Found 'abort', possibly from 'abort' (C), 'runtime' (Fortran) File 'C:/Users/biocbuild/bbs-3.12-bioc/R/library/BufferedMatrix/libs/x64/BufferedMatrix.dll': 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. 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 files in 'vignettes' ... OK * checking examples ... NONE * checking for unstated dependencies in 'tests' ... OK * checking tests ... ** running tests for arch 'i386' ... Running 'Rcodetesting.R' Running 'c_code_level_tests.R' Running 'objectTesting.R' Running 'rawCalltesting.R' OK ** running tests for arch 'x64' ... 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 in 'inst/doc' ... 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 'C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/00check.log' for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### C:\cygwin\bin\curl.exe -O http://172.29.0.3/BBS/3.12/bioc/src/contrib/BufferedMatrix_1.54.0.tar.gz && rm -rf BufferedMatrix.buildbin-libdir && mkdir BufferedMatrix.buildbin-libdir && C:\Users\biocbuild\bbs-3.12-bioc\R\bin\R.exe CMD INSTALL --merge-multiarch --build --library=BufferedMatrix.buildbin-libdir BufferedMatrix_1.54.0.tar.gz && C:\Users\biocbuild\bbs-3.12-bioc\R\bin\R.exe CMD INSTALL BufferedMatrix_1.54.0.zip && rm BufferedMatrix_1.54.0.tar.gz BufferedMatrix_1.54.0.zip
###
##############################################################################
##############################################################################
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0
100 202k 100 202k 0 0 2072k 0 --:--:-- --:--:-- --:--:-- 2087k
install for i386
* installing *source* package 'BufferedMatrix' ...
** using staged installation
** libs
"C:/rtools40/mingw32/bin/"gcc -I"C:/Users/BIOCBU~1/BBS-3~1.12-/R/include" -DNDEBUG -I"C:/extsoft/include" -O2 -Wall -std=gnu99 -mfpmath=sse -msse2 -mstackrealign -c RBufferedMatrix.c -o RBufferedMatrix.o
"C:/rtools40/mingw32/bin/"gcc -I"C:/Users/BIOCBU~1/BBS-3~1.12-/R/include" -DNDEBUG -I"C:/extsoft/include" -O2 -Wall -std=gnu99 -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]
if (!(Matrix->readonly) & setting){
^~~~~~~~~~~~~~~~~~~
At top level:
doubleBufferedMatrix.c:3327:12: warning: 'sort_double' defined but not used [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^~~~~~~~~~~
"C:/rtools40/mingw32/bin/"gcc -I"C:/Users/BIOCBU~1/BBS-3~1.12-/R/include" -DNDEBUG -I"C:/extsoft/include" -O2 -Wall -std=gnu99 -mfpmath=sse -msse2 -mstackrealign -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
"C:/rtools40/mingw32/bin/"gcc -I"C:/Users/BIOCBU~1/BBS-3~1.12-/R/include" -DNDEBUG -I"C:/extsoft/include" -O2 -Wall -std=gnu99 -mfpmath=sse -msse2 -mstackrealign -c init_package.c -o init_package.o
C:/rtools40/mingw32/bin/gcc -shared -s -static-libgcc -o BufferedMatrix.dll tmp.def RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -LC:/extsoft/lib/i386 -LC:/extsoft/lib -LC:/Users/BIOCBU~1/BBS-3~1.12-/R/bin/i386 -lR
installing to C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.buildbin-libdir/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs/i386
** 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
converting help for package 'BufferedMatrix'
finding HTML links ... done
BufferedMatrix-class html
as.BufferedMatrix html
createBufferedMatrix html
** 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
install for x64
* installing *source* package 'BufferedMatrix' ...
** libs
"C:/rtools40/mingw64/bin/"gcc -I"C:/Users/BIOCBU~1/BBS-3~1.12-/R/include" -DNDEBUG -I"C:/extsoft/include" -O2 -Wall -std=gnu99 -mfpmath=sse -msse2 -mstackrealign -c RBufferedMatrix.c -o RBufferedMatrix.o
"C:/rtools40/mingw64/bin/"gcc -I"C:/Users/BIOCBU~1/BBS-3~1.12-/R/include" -DNDEBUG -I"C:/extsoft/include" -O2 -Wall -std=gnu99 -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]
if (!(Matrix->readonly) & setting){
^~~~~~~~~~~~~~~~~~~
At top level:
doubleBufferedMatrix.c:3327:12: warning: 'sort_double' defined but not used [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^~~~~~~~~~~
"C:/rtools40/mingw64/bin/"gcc -I"C:/Users/BIOCBU~1/BBS-3~1.12-/R/include" -DNDEBUG -I"C:/extsoft/include" -O2 -Wall -std=gnu99 -mfpmath=sse -msse2 -mstackrealign -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
"C:/rtools40/mingw64/bin/"gcc -I"C:/Users/BIOCBU~1/BBS-3~1.12-/R/include" -DNDEBUG -I"C:/extsoft/include" -O2 -Wall -std=gnu99 -mfpmath=sse -msse2 -mstackrealign -c init_package.c -o init_package.o
C:/rtools40/mingw64/bin/gcc -shared -s -static-libgcc -o BufferedMatrix.dll tmp.def RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -LC:/extsoft/lib/x64 -LC:/extsoft/lib -LC:/Users/BIOCBU~1/BBS-3~1.12-/R/bin/x64 -lR
installing to C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.buildbin-libdir/BufferedMatrix/libs/x64
** testing if installed package can be loaded
* MD5 sums
packaged installation of 'BufferedMatrix' as BufferedMatrix_1.54.0.zip
* DONE (BufferedMatrix)
* installing to library 'C:/Users/biocbuild/bbs-3.12-bioc/R/library'
package 'BufferedMatrix' successfully unpacked and MD5 sums checked
|
BufferedMatrix.Rcheck/tests_i386/c_code_level_tests.Rout
R version 4.0.5 (2021-03-31) -- "Shake and Throw"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: i386-w64-mingw32/i386 (32-bit)
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
0.37 0.03 0.40
|
BufferedMatrix.Rcheck/tests_x64/c_code_level_tests.Rout
R version 4.0.5 (2021-03-31) -- "Shake and Throw"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
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
0.37 0.03 0.40
|
|
BufferedMatrix.Rcheck/tests_i386/objectTesting.Rout
R version 4.0.5 (2021-03-31) -- "Shake and Throw"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: i386-w64-mingw32/i386 (32-bit)
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] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386"
> 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 434371 13.3 920192 28.1 641734 19.6
Vcells 497006 3.8 8388608 64.0 1484756 11.4
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu May 06 01:04:37 2021"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu May 06 01:04:37 2021"
>
>
> 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: 0x02f70c80>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu May 06 01:04:41 2021"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu May 06 01:04:42 2021"
>
> ColMode(tmp2)
<pointer: 0x02f70c80>
>
>
>
> ### 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,] 100.2631894 0.146773811 -0.3384963 0.2566200
[2,] -0.7370351 -0.008972358 -0.3559811 0.4506930
[3,] 0.7953254 1.054716558 0.7875092 -0.3565591
[4,] 0.4528045 -1.042283602 -3.0372702 0.4084834
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.2631894 0.146773811 0.3384963 0.2566200
[2,] 0.7370351 0.008972358 0.3559811 0.4506930
[3,] 0.7953254 1.054716558 0.7875092 0.3565591
[4,] 0.4528045 1.042283602 3.0372702 0.4084834
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0131508 0.38311070 0.5818043 0.5065767
[2,] 0.8585075 0.09472253 0.5966415 0.6713367
[3,] 0.8918102 1.02699394 0.8874172 0.5971257
[4,] 0.6729075 1.02092292 1.7427766 0.6391271
>
> 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: C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.39470 28.97788 31.15654 30.32239
[2,] 34.32211 25.95620 31.32240 32.16406
[3,] 34.71343 36.32466 34.66168 31.32782
[4,] 32.18188 36.25151 45.46504 31.79975
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x086eaa68>
> exp(tmp5)
<pointer: 0x086eaa68>
> log(tmp5,2)
<pointer: 0x086eaa68>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.1295
> Min(tmp5)
[1] 54.02442
> mean(tmp5)
[1] 72.84184
> Sum(tmp5)
[1] 14568.37
> Var(tmp5)
[1] 864.567
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 88.09407 73.02020 70.66034 73.15741 70.22847 71.00757 70.55640 70.97315
[9] 70.40376 70.31707
> rowSums(tmp5)
[1] 1761.881 1460.404 1413.207 1463.148 1404.569 1420.151 1411.128 1419.463
[9] 1408.075 1406.341
> rowVars(tmp5)
[1] 8071.62345 81.76985 61.20329 77.58499 98.43002 70.75950
[7] 81.12077 98.47181 71.15838 60.18580
> rowSd(tmp5)
[1] 89.842214 9.042668 7.823253 8.808234 9.921190 8.411867 9.006707
[8] 9.923296 8.435543 7.757951
> rowMax(tmp5)
[1] 469.12953 96.82425 83.67038 94.62952 91.14040 86.62633 88.47865
[8] 90.41774 86.97679 84.69262
> rowMin(tmp5)
[1] 60.31366 54.02442 58.35089 59.96838 57.51818 55.99496 56.93759 57.62884
[9] 55.54275 54.77369
>
> colMeans(tmp5)
[1] 111.38381 68.24301 70.67912 67.38239 73.24609 70.94499 67.93702
[8] 68.70786 69.09618 69.60127 71.65603 68.25506 73.01403 70.65401
[15] 69.27812 71.68892 75.28381 76.39071 71.28111 72.11332
> colSums(tmp5)
[1] 1113.8381 682.4301 706.7912 673.8239 732.4609 709.4499 679.3702
[8] 687.0786 690.9618 696.0127 716.5603 682.5506 730.1403 706.5401
[15] 692.7812 716.8892 752.8381 763.9071 712.8111 721.1332
> colVars(tmp5)
[1] 15864.68402 106.25312 96.05748 31.97495 84.07094 57.21376
[7] 47.64221 57.00964 49.15056 47.73080 60.75126 78.86820
[13] 78.46657 154.00929 93.31231 109.48284 67.00508 32.52279
[19] 65.51393 75.51690
> colSd(tmp5)
[1] 125.955087 10.307915 9.800892 5.654640 9.169021 7.563978
[7] 6.902334 7.550473 7.010746 6.908748 7.794309 8.880777
[13] 8.858136 12.410048 9.659830 10.463405 8.185663 5.702876
[19] 8.094068 8.690046
> colMax(tmp5)
[1] 469.12953 88.47865 94.62952 78.25081 86.97679 85.97084 80.49527
[8] 82.55053 82.71535 77.19536 84.25993 86.62633 90.41774 91.14040
[15] 85.88827 96.82425 86.00459 83.67038 82.45416 84.69262
> colMin(tmp5)
[1] 60.02624 54.02442 62.73488 62.42397 57.51818 61.92500 58.40242 55.99496
[9] 58.37410 59.04864 54.77369 59.96838 62.45549 55.54275 58.89708 63.17919
[17] 56.93759 66.55161 61.99575 58.35089
>
>
> ### 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] 88.09407 73.02020 70.66034 73.15741 NA 71.00757 70.55640 70.97315
[9] 70.40376 70.31707
> rowSums(tmp5)
[1] 1761.881 1460.404 1413.207 1463.148 NA 1420.151 1411.128 1419.463
[9] 1408.075 1406.341
> rowVars(tmp5)
[1] 8071.62345 81.76985 61.20329 77.58499 94.45089 70.75950
[7] 81.12077 98.47181 71.15838 60.18580
> rowSd(tmp5)
[1] 89.842214 9.042668 7.823253 8.808234 9.718585 8.411867 9.006707
[8] 9.923296 8.435543 7.757951
> rowMax(tmp5)
[1] 469.12953 96.82425 83.67038 94.62952 NA 86.62633 88.47865
[8] 90.41774 86.97679 84.69262
> rowMin(tmp5)
[1] 60.31366 54.02442 58.35089 59.96838 NA 55.99496 56.93759 57.62884
[9] 55.54275 54.77369
>
> colMeans(tmp5)
[1] 111.38381 68.24301 70.67912 67.38239 NA 70.94499 67.93702
[8] 68.70786 69.09618 69.60127 71.65603 68.25506 73.01403 70.65401
[15] 69.27812 71.68892 75.28381 76.39071 71.28111 72.11332
> colSums(tmp5)
[1] 1113.8381 682.4301 706.7912 673.8239 NA 709.4499 679.3702
[8] 687.0786 690.9618 696.0127 716.5603 682.5506 730.1403 706.5401
[15] 692.7812 716.8892 752.8381 763.9071 712.8111 721.1332
> colVars(tmp5)
[1] 15864.68402 106.25312 96.05748 31.97495 NA 57.21376
[7] 47.64221 57.00964 49.15056 47.73080 60.75126 78.86820
[13] 78.46657 154.00929 93.31231 109.48284 67.00508 32.52279
[19] 65.51393 75.51690
> colSd(tmp5)
[1] 125.955087 10.307915 9.800892 5.654640 NA 7.563978
[7] 6.902334 7.550473 7.010746 6.908748 7.794309 8.880777
[13] 8.858136 12.410048 9.659830 10.463405 8.185663 5.702876
[19] 8.094068 8.690046
> colMax(tmp5)
[1] 469.12953 88.47865 94.62952 78.25081 NA 85.97084 80.49527
[8] 82.55053 82.71535 77.19536 84.25993 86.62633 90.41774 91.14040
[15] 85.88827 96.82425 86.00459 83.67038 82.45416 84.69262
> colMin(tmp5)
[1] 60.02624 54.02442 62.73488 62.42397 NA 61.92500 58.40242 55.99496
[9] 58.37410 59.04864 54.77369 59.96838 62.45549 55.54275 58.89708 63.17919
[17] 56.93759 66.55161 61.99575 58.35089
>
> Max(tmp5,na.rm=TRUE)
[1] 469.1295
> Min(tmp5,na.rm=TRUE)
[1] 54.02442
> mean(tmp5,na.rm=TRUE)
[1] 72.91885
> Sum(tmp5,na.rm=TRUE)
[1] 14510.85
> Var(tmp5,na.rm=TRUE)
[1] 867.7416
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.09407 73.02020 70.66034 73.15741 70.89744 71.00757 70.55640 70.97315
[9] 70.40376 70.31707
> rowSums(tmp5,na.rm=TRUE)
[1] 1761.881 1460.404 1413.207 1463.148 1347.051 1420.151 1411.128 1419.463
[9] 1408.075 1406.341
> rowVars(tmp5,na.rm=TRUE)
[1] 8071.62345 81.76985 61.20329 77.58499 94.45089 70.75950
[7] 81.12077 98.47181 71.15838 60.18580
> rowSd(tmp5,na.rm=TRUE)
[1] 89.842214 9.042668 7.823253 8.808234 9.718585 8.411867 9.006707
[8] 9.923296 8.435543 7.757951
> rowMax(tmp5,na.rm=TRUE)
[1] 469.12953 96.82425 83.67038 94.62952 91.14040 86.62633 88.47865
[8] 90.41774 86.97679 84.69262
> rowMin(tmp5,na.rm=TRUE)
[1] 60.31366 54.02442 58.35089 59.96838 57.98027 55.99496 56.93759 57.62884
[9] 55.54275 54.77369
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.38381 68.24301 70.67912 67.38239 74.99364 70.94499 67.93702
[8] 68.70786 69.09618 69.60127 71.65603 68.25506 73.01403 70.65401
[15] 69.27812 71.68892 75.28381 76.39071 71.28111 72.11332
> colSums(tmp5,na.rm=TRUE)
[1] 1113.8381 682.4301 706.7912 673.8239 674.9428 709.4499 679.3702
[8] 687.0786 690.9618 696.0127 716.5603 682.5506 730.1403 706.5401
[15] 692.7812 716.8892 752.8381 763.9071 712.8111 721.1332
> colVars(tmp5,na.rm=TRUE)
[1] 15864.68402 106.25312 96.05748 31.97495 60.22323 57.21376
[7] 47.64221 57.00964 49.15056 47.73080 60.75126 78.86820
[13] 78.46657 154.00929 93.31231 109.48284 67.00508 32.52279
[19] 65.51393 75.51690
> colSd(tmp5,na.rm=TRUE)
[1] 125.955087 10.307915 9.800892 5.654640 7.760363 7.563978
[7] 6.902334 7.550473 7.010746 6.908748 7.794309 8.880777
[13] 8.858136 12.410048 9.659830 10.463405 8.185663 5.702876
[19] 8.094068 8.690046
> colMax(tmp5,na.rm=TRUE)
[1] 469.12953 88.47865 94.62952 78.25081 86.97679 85.97084 80.49527
[8] 82.55053 82.71535 77.19536 84.25993 86.62633 90.41774 91.14040
[15] 85.88827 96.82425 86.00459 83.67038 82.45416 84.69262
> colMin(tmp5,na.rm=TRUE)
[1] 60.02624 54.02442 62.73488 62.42397 63.10853 61.92500 58.40242 55.99496
[9] 58.37410 59.04864 54.77369 59.96838 62.45549 55.54275 58.89708 63.17919
[17] 56.93759 66.55161 61.99575 58.35089
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.09407 73.02020 70.66034 73.15741 NaN 71.00757 70.55640 70.97315
[9] 70.40376 70.31707
> rowSums(tmp5,na.rm=TRUE)
[1] 1761.881 1460.404 1413.207 1463.148 0.000 1420.151 1411.128 1419.463
[9] 1408.075 1406.341
> rowVars(tmp5,na.rm=TRUE)
[1] 8071.62345 81.76985 61.20329 77.58499 NA 70.75950
[7] 81.12077 98.47181 71.15838 60.18580
> rowSd(tmp5,na.rm=TRUE)
[1] 89.842214 9.042668 7.823253 8.808234 NA 8.411867 9.006707
[8] 9.923296 8.435543 7.757951
> rowMax(tmp5,na.rm=TRUE)
[1] 469.12953 96.82425 83.67038 94.62952 NA 86.62633 88.47865
[8] 90.41774 86.97679 84.69262
> rowMin(tmp5,na.rm=TRUE)
[1] 60.31366 54.02442 58.35089 59.96838 NA 55.99496 56.93759 57.62884
[9] 55.54275 54.77369
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 117.09021 69.38332 70.18651 66.17479 NaN 71.86441 67.79582
[8] 67.16978 68.96337 70.77379 71.41940 68.92290 72.21354 68.37775
[15] 70.38717 71.54089 75.49960 76.42837 70.03966 73.41946
> colSums(tmp5,na.rm=TRUE)
[1] 1053.8119 624.4498 631.6786 595.5731 0.0000 646.7797 610.1624
[8] 604.5280 620.6703 636.9641 642.7746 620.3061 649.9219 615.3997
[15] 633.4846 643.8680 679.4964 687.8553 630.3569 660.7751
> colVars(tmp5,na.rm=TRUE)
[1] 17481.43624 104.90644 105.33463 19.56594 NA 54.85548
[7] 53.37318 37.52202 55.09594 38.23074 67.71523 83.70904
[13] 81.06607 114.96987 91.13881 122.92165 74.85683 36.57219
[19] 56.36468 65.76406
> colSd(tmp5,na.rm=TRUE)
[1] 132.217383 10.242384 10.263266 4.423340 NA 7.406449
[7] 7.305695 6.125522 7.422664 6.183101 8.228926 9.149265
[13] 9.003670 10.722400 9.546665 11.087004 8.651984 6.047494
[19] 7.507642 8.109504
> colMax(tmp5,na.rm=TRUE)
[1] 469.12953 88.47865 94.62952 77.01531 -Inf 85.97084 80.49527
[8] 75.80823 82.71535 77.19536 84.25993 86.62633 90.41774 84.86124
[15] 85.88827 96.82425 86.00459 83.67038 82.40425 84.69262
> colMin(tmp5,na.rm=TRUE)
[1] 66.98237 54.02442 62.73488 62.42397 Inf 61.92500 58.40242 55.99496
[9] 58.37410 59.82820 54.77369 59.96838 62.45549 55.54275 58.89708 63.17919
[17] 56.93759 66.55161 61.99575 58.35089
>
>
>
>
> 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] 305.8263 109.1178 213.2876 166.6822 135.6023 204.0610 132.1631 283.6612
[9] 242.1039 228.4226
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 305.8263 109.1178 213.2876 166.6822 135.6023 204.0610 132.1631 283.6612
[9] 242.1039 228.4226
>
>
>
> 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] 5.684342e-14 -1.705303e-13 1.705303e-13 -8.526513e-14 2.842171e-14
[6] -1.136868e-13 2.273737e-13 1.705303e-13 -8.526513e-14 4.263256e-14
[11] 5.684342e-14 -5.684342e-14 2.842171e-14 -2.273737e-13 1.705303e-13
[16] 5.684342e-14 2.273737e-13 -8.526513e-14 1.136868e-13 -4.263256e-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)
+ }
8 2
8 13
6 10
2 14
4 5
5 10
6 15
9 20
1 10
8 4
2 15
3 18
8 18
1 19
1 5
7 16
10 11
3 14
5 4
1 16
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 3.490015
> Min(tmp)
[1] -2.331923
> mean(tmp)
[1] -0.07803391
> Sum(tmp)
[1] -7.803391
> Var(tmp)
[1] 1.114002
>
> rowMeans(tmp)
[1] -0.07803391
> rowSums(tmp)
[1] -7.803391
> rowVars(tmp)
[1] 1.114002
> rowSd(tmp)
[1] 1.055463
> rowMax(tmp)
[1] 3.490015
> rowMin(tmp)
[1] -2.331923
>
> colMeans(tmp)
[1] 0.63679991 -1.06986263 0.29096849 0.91826258 0.46389305 -1.17948063
[7] -0.88739907 -0.80484986 0.32234094 -0.48347246 0.98296391 0.16423129
[13] -0.31218678 0.36798728 2.04510730 0.20038246 -1.33421634 -0.01548397
[19] -2.33192350 -0.21556473 -0.72504847 1.02820263 -0.30801548 1.64639769
[25] -0.18094946 -0.10948861 -0.64945498 -1.24927000 0.94380237 -1.49248841
[31] 0.68937818 0.77657226 1.74579381 -0.66994319 0.15310790 -0.57580342
[37] -0.80914063 -1.31832622 -0.47115355 -1.95328305 1.17556365 1.01055001
[43] -0.13843311 0.21220904 -1.43818555 -1.10548571 0.38688985 -0.24842085
[49] -0.15934092 0.12676429 -0.97879720 -1.15520204 -1.15092622 -0.21847911
[55] 0.81901042 -1.23162982 0.04043877 -0.82190771 -1.23030296 1.36363898
[61] 1.52993253 -1.99245107 -1.02639441 0.39212325 0.84871682 0.60408157
[67] -1.12447550 -0.15416380 0.29737221 3.49001529 1.70114256 -0.63885844
[73] -0.58978826 -0.72388781 -0.49415820 0.40413174 -0.10600353 1.20977874
[79] 0.23965750 -0.85418093 -0.94525527 1.48323621 -1.92567705 1.53651636
[85] 0.32599850 -0.25919232 -2.21501308 -0.33218153 1.19099821 -2.29818621
[91] 0.88289963 -0.31210566 0.14097196 -1.03603794 0.27374757 0.57894820
[97] 0.04622287 1.18499751 0.08456342 1.29122666
> colSums(tmp)
[1] 0.63679991 -1.06986263 0.29096849 0.91826258 0.46389305 -1.17948063
[7] -0.88739907 -0.80484986 0.32234094 -0.48347246 0.98296391 0.16423129
[13] -0.31218678 0.36798728 2.04510730 0.20038246 -1.33421634 -0.01548397
[19] -2.33192350 -0.21556473 -0.72504847 1.02820263 -0.30801548 1.64639769
[25] -0.18094946 -0.10948861 -0.64945498 -1.24927000 0.94380237 -1.49248841
[31] 0.68937818 0.77657226 1.74579381 -0.66994319 0.15310790 -0.57580342
[37] -0.80914063 -1.31832622 -0.47115355 -1.95328305 1.17556365 1.01055001
[43] -0.13843311 0.21220904 -1.43818555 -1.10548571 0.38688985 -0.24842085
[49] -0.15934092 0.12676429 -0.97879720 -1.15520204 -1.15092622 -0.21847911
[55] 0.81901042 -1.23162982 0.04043877 -0.82190771 -1.23030296 1.36363898
[61] 1.52993253 -1.99245107 -1.02639441 0.39212325 0.84871682 0.60408157
[67] -1.12447550 -0.15416380 0.29737221 3.49001529 1.70114256 -0.63885844
[73] -0.58978826 -0.72388781 -0.49415820 0.40413174 -0.10600353 1.20977874
[79] 0.23965750 -0.85418093 -0.94525527 1.48323621 -1.92567705 1.53651636
[85] 0.32599850 -0.25919232 -2.21501308 -0.33218153 1.19099821 -2.29818621
[91] 0.88289963 -0.31210566 0.14097196 -1.03603794 0.27374757 0.57894820
[97] 0.04622287 1.18499751 0.08456342 1.29122666
> 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] 0.63679991 -1.06986263 0.29096849 0.91826258 0.46389305 -1.17948063
[7] -0.88739907 -0.80484986 0.32234094 -0.48347246 0.98296391 0.16423129
[13] -0.31218678 0.36798728 2.04510730 0.20038246 -1.33421634 -0.01548397
[19] -2.33192350 -0.21556473 -0.72504847 1.02820263 -0.30801548 1.64639769
[25] -0.18094946 -0.10948861 -0.64945498 -1.24927000 0.94380237 -1.49248841
[31] 0.68937818 0.77657226 1.74579381 -0.66994319 0.15310790 -0.57580342
[37] -0.80914063 -1.31832622 -0.47115355 -1.95328305 1.17556365 1.01055001
[43] -0.13843311 0.21220904 -1.43818555 -1.10548571 0.38688985 -0.24842085
[49] -0.15934092 0.12676429 -0.97879720 -1.15520204 -1.15092622 -0.21847911
[55] 0.81901042 -1.23162982 0.04043877 -0.82190771 -1.23030296 1.36363898
[61] 1.52993253 -1.99245107 -1.02639441 0.39212325 0.84871682 0.60408157
[67] -1.12447550 -0.15416380 0.29737221 3.49001529 1.70114256 -0.63885844
[73] -0.58978826 -0.72388781 -0.49415820 0.40413174 -0.10600353 1.20977874
[79] 0.23965750 -0.85418093 -0.94525527 1.48323621 -1.92567705 1.53651636
[85] 0.32599850 -0.25919232 -2.21501308 -0.33218153 1.19099821 -2.29818621
[91] 0.88289963 -0.31210566 0.14097196 -1.03603794 0.27374757 0.57894820
[97] 0.04622287 1.18499751 0.08456342 1.29122666
> colMin(tmp)
[1] 0.63679991 -1.06986263 0.29096849 0.91826258 0.46389305 -1.17948063
[7] -0.88739907 -0.80484986 0.32234094 -0.48347246 0.98296391 0.16423129
[13] -0.31218678 0.36798728 2.04510730 0.20038246 -1.33421634 -0.01548397
[19] -2.33192350 -0.21556473 -0.72504847 1.02820263 -0.30801548 1.64639769
[25] -0.18094946 -0.10948861 -0.64945498 -1.24927000 0.94380237 -1.49248841
[31] 0.68937818 0.77657226 1.74579381 -0.66994319 0.15310790 -0.57580342
[37] -0.80914063 -1.31832622 -0.47115355 -1.95328305 1.17556365 1.01055001
[43] -0.13843311 0.21220904 -1.43818555 -1.10548571 0.38688985 -0.24842085
[49] -0.15934092 0.12676429 -0.97879720 -1.15520204 -1.15092622 -0.21847911
[55] 0.81901042 -1.23162982 0.04043877 -0.82190771 -1.23030296 1.36363898
[61] 1.52993253 -1.99245107 -1.02639441 0.39212325 0.84871682 0.60408157
[67] -1.12447550 -0.15416380 0.29737221 3.49001529 1.70114256 -0.63885844
[73] -0.58978826 -0.72388781 -0.49415820 0.40413174 -0.10600353 1.20977874
[79] 0.23965750 -0.85418093 -0.94525527 1.48323621 -1.92567705 1.53651636
[85] 0.32599850 -0.25919232 -2.21501308 -0.33218153 1.19099821 -2.29818621
[91] 0.88289963 -0.31210566 0.14097196 -1.03603794 0.27374757 0.57894820
[97] 0.04622287 1.18499751 0.08456342 1.29122666
> colMedians(tmp)
[1] 0.63679991 -1.06986263 0.29096849 0.91826258 0.46389305 -1.17948063
[7] -0.88739907 -0.80484986 0.32234094 -0.48347246 0.98296391 0.16423129
[13] -0.31218678 0.36798728 2.04510730 0.20038246 -1.33421634 -0.01548397
[19] -2.33192350 -0.21556473 -0.72504847 1.02820263 -0.30801548 1.64639769
[25] -0.18094946 -0.10948861 -0.64945498 -1.24927000 0.94380237 -1.49248841
[31] 0.68937818 0.77657226 1.74579381 -0.66994319 0.15310790 -0.57580342
[37] -0.80914063 -1.31832622 -0.47115355 -1.95328305 1.17556365 1.01055001
[43] -0.13843311 0.21220904 -1.43818555 -1.10548571 0.38688985 -0.24842085
[49] -0.15934092 0.12676429 -0.97879720 -1.15520204 -1.15092622 -0.21847911
[55] 0.81901042 -1.23162982 0.04043877 -0.82190771 -1.23030296 1.36363898
[61] 1.52993253 -1.99245107 -1.02639441 0.39212325 0.84871682 0.60408157
[67] -1.12447550 -0.15416380 0.29737221 3.49001529 1.70114256 -0.63885844
[73] -0.58978826 -0.72388781 -0.49415820 0.40413174 -0.10600353 1.20977874
[79] 0.23965750 -0.85418093 -0.94525527 1.48323621 -1.92567705 1.53651636
[85] 0.32599850 -0.25919232 -2.21501308 -0.33218153 1.19099821 -2.29818621
[91] 0.88289963 -0.31210566 0.14097196 -1.03603794 0.27374757 0.57894820
[97] 0.04622287 1.18499751 0.08456342 1.29122666
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.6367999 -1.069863 0.2909685 0.9182626 0.463893 -1.179481 -0.8873991
[2,] 0.6367999 -1.069863 0.2909685 0.9182626 0.463893 -1.179481 -0.8873991
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.8048499 0.3223409 -0.4834725 0.9829639 0.1642313 -0.3121868 0.3679873
[2,] -0.8048499 0.3223409 -0.4834725 0.9829639 0.1642313 -0.3121868 0.3679873
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 2.045107 0.2003825 -1.334216 -0.01548397 -2.331923 -0.2155647 -0.7250485
[2,] 2.045107 0.2003825 -1.334216 -0.01548397 -2.331923 -0.2155647 -0.7250485
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.028203 -0.3080155 1.646398 -0.1809495 -0.1094886 -0.649455 -1.24927
[2,] 1.028203 -0.3080155 1.646398 -0.1809495 -0.1094886 -0.649455 -1.24927
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.9438024 -1.492488 0.6893782 0.7765723 1.745794 -0.6699432 0.1531079
[2,] 0.9438024 -1.492488 0.6893782 0.7765723 1.745794 -0.6699432 0.1531079
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.5758034 -0.8091406 -1.318326 -0.4711536 -1.953283 1.175564 1.01055
[2,] -0.5758034 -0.8091406 -1.318326 -0.4711536 -1.953283 1.175564 1.01055
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.1384331 0.212209 -1.438186 -1.105486 0.3868898 -0.2484209 -0.1593409
[2,] -0.1384331 0.212209 -1.438186 -1.105486 0.3868898 -0.2484209 -0.1593409
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.1267643 -0.9787972 -1.155202 -1.150926 -0.2184791 0.8190104 -1.23163
[2,] 0.1267643 -0.9787972 -1.155202 -1.150926 -0.2184791 0.8190104 -1.23163
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.04043877 -0.8219077 -1.230303 1.363639 1.529933 -1.992451 -1.026394
[2,] 0.04043877 -0.8219077 -1.230303 1.363639 1.529933 -1.992451 -1.026394
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.3921233 0.8487168 0.6040816 -1.124475 -0.1541638 0.2973722 3.490015
[2,] 0.3921233 0.8487168 0.6040816 -1.124475 -0.1541638 0.2973722 3.490015
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.701143 -0.6388584 -0.5897883 -0.7238878 -0.4941582 0.4041317 -0.1060035
[2,] 1.701143 -0.6388584 -0.5897883 -0.7238878 -0.4941582 0.4041317 -0.1060035
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.209779 0.2396575 -0.8541809 -0.9452553 1.483236 -1.925677 1.536516
[2,] 1.209779 0.2396575 -0.8541809 -0.9452553 1.483236 -1.925677 1.536516
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.3259985 -0.2591923 -2.215013 -0.3321815 1.190998 -2.298186 0.8828996
[2,] 0.3259985 -0.2591923 -2.215013 -0.3321815 1.190998 -2.298186 0.8828996
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.3121057 0.140972 -1.036038 0.2737476 0.5789482 0.04622287 1.184998
[2,] -0.3121057 0.140972 -1.036038 0.2737476 0.5789482 0.04622287 1.184998
[,99] [,100]
[1,] 0.08456342 1.291227
[2,] 0.08456342 1.291227
>
>
> Max(tmp2)
[1] 2.53365
> Min(tmp2)
[1] -2.599261
> mean(tmp2)
[1] 0.1967687
> Sum(tmp2)
[1] 19.67687
> Var(tmp2)
[1] 0.9203204
>
> rowMeans(tmp2)
[1] 1.300033277 0.515645103 1.105565702 -0.877947112 0.659085794
[6] -2.599261124 1.721951767 -0.290967291 1.188773325 1.275166749
[11] -0.471654737 0.316689423 -0.659871396 0.146875039 0.133126963
[16] -0.295584703 1.051303004 -0.768032135 1.420895289 -1.237144725
[21] 0.675668642 1.121952410 0.588727034 0.998856360 -0.084300800
[26] 0.443334429 -0.795554083 0.809815547 -0.151949247 -1.656707289
[31] 0.006514957 -0.184135566 -0.673935675 0.504444655 -1.423816607
[36] -0.007401984 -0.041138746 0.205407230 1.356736570 0.413346944
[41] 0.314083705 -0.211882028 -0.945654371 1.160987967 -0.521664004
[46] -0.544048444 0.167146067 0.068030218 1.329440912 -2.255915945
[51] -0.218016825 0.841767959 0.407504603 0.336695460 0.913875625
[56] -0.417396764 0.387024647 0.918210878 -0.345106896 0.749398307
[61] 0.324302355 1.118778227 -0.125308529 -0.393250200 -0.186372688
[66] -0.230049973 0.477751180 -0.681539397 0.407260370 0.720373927
[71] 0.750734788 1.816886185 -2.358830575 -0.439996551 1.226528691
[76] -0.404040603 -1.584321593 -0.749008322 0.142275300 -0.194494392
[81] -0.431558114 -0.074337536 0.343742683 1.818523014 1.665235159
[86] 1.296923930 0.595530178 2.197199852 0.075829552 0.491546273
[91] 0.454120533 2.533649861 0.947543328 -0.476347341 -1.152415165
[96] 0.228410382 -1.555444407 1.082204946 0.941185479 1.182658600
> rowSums(tmp2)
[1] 1.300033277 0.515645103 1.105565702 -0.877947112 0.659085794
[6] -2.599261124 1.721951767 -0.290967291 1.188773325 1.275166749
[11] -0.471654737 0.316689423 -0.659871396 0.146875039 0.133126963
[16] -0.295584703 1.051303004 -0.768032135 1.420895289 -1.237144725
[21] 0.675668642 1.121952410 0.588727034 0.998856360 -0.084300800
[26] 0.443334429 -0.795554083 0.809815547 -0.151949247 -1.656707289
[31] 0.006514957 -0.184135566 -0.673935675 0.504444655 -1.423816607
[36] -0.007401984 -0.041138746 0.205407230 1.356736570 0.413346944
[41] 0.314083705 -0.211882028 -0.945654371 1.160987967 -0.521664004
[46] -0.544048444 0.167146067 0.068030218 1.329440912 -2.255915945
[51] -0.218016825 0.841767959 0.407504603 0.336695460 0.913875625
[56] -0.417396764 0.387024647 0.918210878 -0.345106896 0.749398307
[61] 0.324302355 1.118778227 -0.125308529 -0.393250200 -0.186372688
[66] -0.230049973 0.477751180 -0.681539397 0.407260370 0.720373927
[71] 0.750734788 1.816886185 -2.358830575 -0.439996551 1.226528691
[76] -0.404040603 -1.584321593 -0.749008322 0.142275300 -0.194494392
[81] -0.431558114 -0.074337536 0.343742683 1.818523014 1.665235159
[86] 1.296923930 0.595530178 2.197199852 0.075829552 0.491546273
[91] 0.454120533 2.533649861 0.947543328 -0.476347341 -1.152415165
[96] 0.228410382 -1.555444407 1.082204946 0.941185479 1.182658600
> 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] 1.300033277 0.515645103 1.105565702 -0.877947112 0.659085794
[6] -2.599261124 1.721951767 -0.290967291 1.188773325 1.275166749
[11] -0.471654737 0.316689423 -0.659871396 0.146875039 0.133126963
[16] -0.295584703 1.051303004 -0.768032135 1.420895289 -1.237144725
[21] 0.675668642 1.121952410 0.588727034 0.998856360 -0.084300800
[26] 0.443334429 -0.795554083 0.809815547 -0.151949247 -1.656707289
[31] 0.006514957 -0.184135566 -0.673935675 0.504444655 -1.423816607
[36] -0.007401984 -0.041138746 0.205407230 1.356736570 0.413346944
[41] 0.314083705 -0.211882028 -0.945654371 1.160987967 -0.521664004
[46] -0.544048444 0.167146067 0.068030218 1.329440912 -2.255915945
[51] -0.218016825 0.841767959 0.407504603 0.336695460 0.913875625
[56] -0.417396764 0.387024647 0.918210878 -0.345106896 0.749398307
[61] 0.324302355 1.118778227 -0.125308529 -0.393250200 -0.186372688
[66] -0.230049973 0.477751180 -0.681539397 0.407260370 0.720373927
[71] 0.750734788 1.816886185 -2.358830575 -0.439996551 1.226528691
[76] -0.404040603 -1.584321593 -0.749008322 0.142275300 -0.194494392
[81] -0.431558114 -0.074337536 0.343742683 1.818523014 1.665235159
[86] 1.296923930 0.595530178 2.197199852 0.075829552 0.491546273
[91] 0.454120533 2.533649861 0.947543328 -0.476347341 -1.152415165
[96] 0.228410382 -1.555444407 1.082204946 0.941185479 1.182658600
> rowMin(tmp2)
[1] 1.300033277 0.515645103 1.105565702 -0.877947112 0.659085794
[6] -2.599261124 1.721951767 -0.290967291 1.188773325 1.275166749
[11] -0.471654737 0.316689423 -0.659871396 0.146875039 0.133126963
[16] -0.295584703 1.051303004 -0.768032135 1.420895289 -1.237144725
[21] 0.675668642 1.121952410 0.588727034 0.998856360 -0.084300800
[26] 0.443334429 -0.795554083 0.809815547 -0.151949247 -1.656707289
[31] 0.006514957 -0.184135566 -0.673935675 0.504444655 -1.423816607
[36] -0.007401984 -0.041138746 0.205407230 1.356736570 0.413346944
[41] 0.314083705 -0.211882028 -0.945654371 1.160987967 -0.521664004
[46] -0.544048444 0.167146067 0.068030218 1.329440912 -2.255915945
[51] -0.218016825 0.841767959 0.407504603 0.336695460 0.913875625
[56] -0.417396764 0.387024647 0.918210878 -0.345106896 0.749398307
[61] 0.324302355 1.118778227 -0.125308529 -0.393250200 -0.186372688
[66] -0.230049973 0.477751180 -0.681539397 0.407260370 0.720373927
[71] 0.750734788 1.816886185 -2.358830575 -0.439996551 1.226528691
[76] -0.404040603 -1.584321593 -0.749008322 0.142275300 -0.194494392
[81] -0.431558114 -0.074337536 0.343742683 1.818523014 1.665235159
[86] 1.296923930 0.595530178 2.197199852 0.075829552 0.491546273
[91] 0.454120533 2.533649861 0.947543328 -0.476347341 -1.152415165
[96] 0.228410382 -1.555444407 1.082204946 0.941185479 1.182658600
>
> colMeans(tmp2)
[1] 0.1967687
> colSums(tmp2)
[1] 19.67687
> colVars(tmp2)
[1] 0.9203204
> colSd(tmp2)
[1] 0.9593333
> colMax(tmp2)
[1] 2.53365
> colMin(tmp2)
[1] -2.599261
> colMedians(tmp2)
[1] 0.271247
> colRanges(tmp2)
[,1]
[1,] -2.599261
[2,] 2.533650
>
> 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] -5.63740861 -1.10344742 -1.52049908 4.18876232 -0.04422162 -1.02303644
[7] -3.07016379 -2.75752537 4.45779765 1.55564361
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.1962557
[2,] -1.7363214
[3,] -0.2194129
[4,] 0.1945224
[5,] 1.5640957
>
> rowApply(tmp,sum)
[1] -2.5487220 -0.1734164 0.7124805 3.4970904 5.3507011 -2.4701209
[7] -6.9969666 1.3357008 -0.6398520 -3.0209935
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 4 6 5 6 1 3 5 1 1
[2,] 1 9 2 4 1 6 1 8 9 7
[3,] 8 7 7 2 8 9 5 3 3 5
[4,] 9 10 3 10 7 4 10 1 6 9
[5,] 3 3 5 3 3 3 8 6 10 8
[6,] 2 8 9 1 4 7 6 2 7 4
[7,] 4 1 1 6 9 5 4 4 4 10
[8,] 5 6 4 9 2 2 2 7 8 3
[9,] 7 5 10 8 10 10 7 10 2 2
[10,] 6 2 8 7 5 8 9 9 5 6
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.6176489 0.4386784 -0.2698176 3.8049020 -0.8026397 -1.9445087
[7] -1.0968007 1.3417801 -2.9243514 1.0425313 -0.4973155 2.8559682
[13] -1.2125126 -2.3930987 3.0171461 1.5363530 0.5245611 2.5412581
[19] 3.2638938 3.2240891
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5449583
[2,] -1.2100847
[3,] -0.4889726
[4,] 0.5499324
[5,] 2.0764342
>
> rowApply(tmp,sum)
[1] -0.8439005 4.1398500 5.3079077 -8.7970918 12.0257020
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 20 14 1 2 3
[2,] 4 15 16 3 16
[3,] 12 7 2 16 10
[4,] 13 20 14 9 14
[5,] 10 2 17 18 1
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 2.0764342 -0.7922467 0.1019329 0.1029604 -0.1238887 -1.1668989
[2,] 0.5499324 0.8309188 -0.3255613 2.8788524 -1.2694137 -1.6824325
[3,] -1.2100847 0.9340276 -1.0227977 0.7863428 1.1310481 0.4251274
[4,] -1.5449583 -1.5002924 0.4076942 -0.8451055 0.5206375 0.0907847
[5,] -0.4889726 0.9662711 0.5689143 0.8818518 -1.0610229 0.3889106
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.67656213 -0.1640841 0.93533985 -0.7120557 -1.7601021 0.4800756
[2,] -0.06928931 0.1213336 -1.24100893 0.3126455 -0.8967546 -0.3576753
[3,] -0.29043037 0.9058512 -0.04977242 0.1240021 0.7063901 1.6019523
[4,] -0.82393450 0.2206976 -2.43460514 0.4162322 0.7708785 -0.9128939
[5,] 0.76341558 0.2579818 -0.13430477 0.9017073 0.6822726 2.0445095
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.9756636 -0.7133308 -0.088915935 -0.6653762 0.2987143 1.8262196
[2,] 0.2642399 0.2399369 1.638575972 1.7067892 -0.4620485 0.9769327
[3,] -0.7341331 -0.3712207 -0.005029132 -0.0196773 2.1647167 -0.6048402
[4,] -0.3902355 -0.8907422 1.367200247 -1.3688333 -1.3211128 0.1475419
[5,] 0.6232797 -0.6577420 0.105314924 1.8834506 -0.1557086 0.1954042
[,19] [,20]
[1,] 0.6918504 0.4816971
[2,] 1.1263487 -0.2024720
[3,] -0.4971415 1.3335767
[4,] 0.3087059 -1.0147512
[5,] 1.6341304 2.6260385
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 638 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 550 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -1.083625 1.457959 -0.4141023 -0.4378642 -0.354782 -1.713561 -0.9334979
col8 col9 col10 col11 col12 col13 col14
row1 0.424791 1.042175 -0.2299333 0.06726554 2.785655 0.9695961 -1.509866
col15 col16 col17 col18 col19 col20
row1 -1.745861 -1.193218 -0.6214161 1.4407 -0.6478855 -0.5865732
> tmp[,"col10"]
col10
row1 -0.2299333
row2 1.6286268
row3 -0.5894382
row4 0.4610139
row5 0.3890902
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -1.083625 1.457959 -0.4141023 -0.4378642 -0.3547820 -1.713561 -0.9334979
row5 0.321574 0.329532 -1.2861163 2.4562750 -0.5617324 -0.330767 -3.3743486
col8 col9 col10 col11 col12 col13 col14
row1 0.4247910 1.0421745 -0.2299333 0.06726554 2.785655 0.9695961 -1.509866
row5 0.7177453 -0.1839312 0.3890902 0.07744360 -1.620873 0.3797483 2.146038
col15 col16 col17 col18 col19 col20
row1 -1.745861 -1.193218 -0.6214161 1.440700 -0.6478855 -0.5865732
row5 -1.627998 1.479130 1.2758543 -0.482678 0.9148167 1.1664044
> tmp[,c("col6","col20")]
col6 col20
row1 -1.7135606 -0.5865732
row2 -0.8755963 -1.9333094
row3 -0.5485321 0.6963978
row4 0.5662403 1.9698287
row5 -0.3307670 1.1664044
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.713561 -0.5865732
row5 -0.330767 1.1664044
>
>
>
>
> 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 49.58731 48.17529 50.13779 52.34983 51.82158 103.9498 49.88016 48.68434
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.20501 51.63932 48.50176 50.38728 50.27752 51.57055 50.69927 50.11973
col17 col18 col19 col20
row1 51.05683 49.59258 50.60696 104.2954
> tmp[,"col10"]
col10
row1 51.63932
row2 32.62867
row3 28.87613
row4 29.87037
row5 49.71829
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.58731 48.17529 50.13779 52.34983 51.82158 103.9498 49.88016 48.68434
row5 49.54380 50.15764 48.08277 51.32488 49.03162 103.7473 49.96840 48.31988
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.20501 51.63932 48.50176 50.38728 50.27752 51.57055 50.69927 50.11973
row5 50.39214 49.71829 49.70989 50.02011 50.42760 50.43969 50.55636 50.83127
col17 col18 col19 col20
row1 51.05683 49.59258 50.60696 104.2954
row5 47.41637 51.01189 51.18696 105.1578
> tmp[,c("col6","col20")]
col6 col20
row1 103.94982 104.29540
row2 76.31476 76.15384
row3 73.82562 74.47877
row4 76.47745 74.38029
row5 103.74733 105.15784
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 103.9498 104.2954
row5 103.7473 105.1578
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 103.9498 104.2954
row5 103.7473 105.1578
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.3028457
[2,] 1.0535529
[3,] -1.1638899
[4,] 2.0350325
[5,] 1.0098994
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.4652231 1.1290014
[2,] -0.9091935 1.0413004
[3,] -0.1869195 1.3773106
[4,] 0.2798180 -0.5264935
[5,] 0.3480631 -0.7999818
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.7506544 -1.5079581
[2,] -1.3141820 -1.7638026
[3,] -1.3091889 2.2088416
[4,] -1.3388632 -2.3995231
[5,] -0.2993170 0.9192931
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.7506544
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.7506544
[2,] -1.3141820
>
>
>
> 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 -1.734055 -0.1227657 1.351745 0.1164702 0.1018282 -1.4055531 -2.156355
row1 -1.098954 -0.2060289 -1.543077 -1.6658189 1.0815010 0.1053004 1.074452
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.8734745 0.08197439 1.5939736 -0.01550746 0.4181700 -2.019473 0.8792975
row1 0.2937033 0.14062523 -0.7712237 -0.82817496 0.5154711 -0.298577 -1.0748032
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -1.0225837 0.07758577 -0.5404019 1.3851822 -0.03601075 -1.0208192
row1 0.5221504 -0.62957883 -0.8526457 -0.5285124 -0.73160780 -0.6044927
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.5526829 -0.1286741 -0.8878176 -1.276438 -1.077589 -0.5324786 -0.7639768
[,8] [,9] [,10]
row2 -0.5832703 -2.3337 -0.3513114
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.2637497 -0.0427435 0.6740463 0.6480848 0.04828542 -0.8919844 -1.041258
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.313955 -0.9736954 -1.843272 -0.3080684 -0.6958145 -0.3897772 0.240795
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.933357 -0.364012 0.3694874 -1.119818 0.1622482 0.7611965
>
>
> 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: 0x0241ae40>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM316c47c76b15"
[2] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM316c3c2c24fd"
[3] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM316c1606101b"
[4] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM316c67be5490"
[5] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM316c313d42c2"
[6] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM316c3d8d6fa6"
[7] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM316c7a79461"
[8] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM316c23863e5"
[9] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM316cf651e6f"
[10] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM316c15d92a1d"
[11] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM316c4f1b50e9"
[12] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM316c3f807d0"
[13] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM316c213a3ff4"
[14] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM316c4ce19f2"
[15] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM316c333964c4"
>
>
> ### 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: 0x0393c378>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x0393c378>
Warning message:
In dir.create(new.directory) :
'C:\Users\biocbuild\bbs-3.12-bioc\meat\BufferedMatrix.Rcheck\tests_i386' already exists
>
>
> RowMode(tmp)
<pointer: 0x0393c378>
> rowMedians(tmp)
[1] -0.204080462 0.095280936 0.433866740 0.131394205 0.509521545
[6] -0.176655953 0.318637444 0.027009272 -0.224218029 0.195652730
[11] -0.015783439 -0.417291011 0.134228674 -0.216183330 0.245033156
[16] 0.363258853 0.781557260 -0.130967531 -0.307434220 0.262421770
[21] 0.343433980 -0.221885632 -0.176883043 0.002632763 -0.556006986
[26] 0.146047859 0.352908339 0.681241067 -0.003180647 0.536998274
[31] 0.036895909 -0.003973121 -0.272045237 0.003126757 -0.143252258
[36] 0.255416072 -0.384140417 -0.351446146 0.468636537 0.296437455
[41] -1.004762139 -0.319605993 -0.318976641 -0.403154226 0.112008924
[46] -0.183911720 -0.184027770 0.321294571 0.149362849 0.088303075
[51] -0.332774058 -0.219221048 0.138064951 -0.279721146 -0.588826444
[56] 0.011325219 0.485495297 0.338262078 -0.430873912 0.625025261
[61] -0.031420235 0.224178672 1.064551168 -0.020109692 -0.679472963
[66] 0.609609843 0.104341552 0.008181631 -0.068012811 -0.387370383
[71] -0.397771406 -0.148955021 -0.388425102 0.143087607 0.168672301
[76] -0.136052817 -0.201451875 0.604163715 -0.116698471 0.229811975
[81] 0.238838048 -0.324115165 -0.107809494 0.285938152 0.198272788
[86] -0.202101156 -0.405930435 -0.561548120 0.084857333 -0.279816742
[91] 0.046188892 -0.309612662 0.150114451 -0.263603384 -0.016729855
[96] -0.339122216 0.134044661 -0.306740811 0.298583877 -0.387349649
[101] -0.010378383 -0.050056877 0.032575342 -0.131712071 -0.357784439
[106] -0.257115652 0.308199831 0.240888055 -0.637218406 -0.083847774
[111] 0.071761184 -0.376438973 0.320426593 0.263740559 0.363783632
[116] 0.003606134 -0.336445593 0.262710708 -0.379068781 -0.215064891
[121] 0.211126638 -0.004692170 0.147615436 0.247817364 0.210205877
[126] -0.447533973 -0.114883223 0.183335501 0.241130344 -0.195500615
[131] -0.032195015 0.026007751 0.045789082 0.059011923 0.057187611
[136] 0.436173694 0.297866201 0.197422964 -0.152338456 0.177032828
[141] 0.334868874 -0.399732450 -0.016598163 0.297145845 0.514165032
[146] 0.425228812 0.083840341 -0.474110845 -0.287107703 0.452228741
[151] 0.190381899 0.029168837 0.443704565 0.472462755 0.406170780
[156] -0.149509662 0.026609566 -0.148481808 0.414345331 0.135488213
[161] 0.386020693 -0.315437738 -1.183680112 -0.356435733 0.265070676
[166] 0.228237826 0.294558574 -0.119098145 -0.341980141 0.387556959
[171] -0.104725594 -0.051265907 0.018460960 -0.122733601 -0.092879674
[176] 0.206200539 -0.112982436 -0.563765267 -0.278082158 -0.710184375
[181] -0.019700565 -0.285870160 0.353198159 0.317107719 0.161283757
[186] -0.001490420 0.200788893 0.297397662 -0.431263532 -0.990340481
[191] -0.085128364 -0.292887103 -0.151195701 0.474439592 0.093809042
[196] 0.222816781 0.348919116 -0.201107971 0.225865259 -0.277774797
[201] -0.517822236 0.354023563 -0.394652803 -0.013409090 0.441886223
[206] -0.014944855 0.114402197 -0.118952496 -0.277432540 0.133767483
[211] 0.616406093 -0.717151351 0.258838365 -0.203920677 -0.857079832
[216] -0.180238096 -0.135882697 -0.870660905 0.280790006 -0.059273772
[221] 0.463167047 0.117715355 -0.362364677 0.623941543 -0.307481049
[226] 0.139019764 0.221111276 0.310789827 0.664580845 0.578791812
>
> proc.time()
user system elapsed
2.21 5.70 21.37
|
BufferedMatrix.Rcheck/tests_x64/objectTesting.Rout
R version 4.0.5 (2021-03-31) -- "Shake and Throw"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
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] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64"
> 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 434372 23.2 920184 49.2 641757 34.3
Vcells 752088 5.8 8388608 64.0 1684481 12.9
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu May 06 01:04:59 2021"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu May 06 01:04:59 2021"
>
>
> 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: 0x00000000078fc2e0>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu May 06 01:05:05 2021"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu May 06 01:05:06 2021"
>
> ColMode(tmp2)
<pointer: 0x00000000078fc2e0>
>
>
>
> ### 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,] 99.4203280 -1.7118091 -0.7163622 0.6267789
[2,] -2.2627719 1.4762308 2.3662023 0.4934079
[3,] -0.2740938 -1.6592087 -1.2418544 -0.9345971
[4,] 1.9322526 0.6024249 -1.5035543 1.1716543
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.4203280 1.7118091 0.7163622 0.6267789
[2,] 2.2627719 1.4762308 2.3662023 0.4934079
[3,] 0.2740938 1.6592087 1.2418544 0.9345971
[4,] 1.9322526 0.6024249 1.5035543 1.1716543
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9709743 1.3083612 0.8463818 0.7916937
[2,] 1.5042513 1.2150024 1.5382465 0.7024300
[3,] 0.5235397 1.2881028 1.1143852 0.9667456
[4,] 1.3900549 0.7761604 1.2261950 1.0824298
>
> 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: C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.13007 39.79542 34.18018 33.54372
[2,] 42.30528 38.62625 42.74867 32.51771
[3,] 30.50949 39.54024 37.38571 35.60205
[4,] 40.83280 33.36403 38.76550 36.99595
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x000000000552bb90>
> exp(tmp5)
<pointer: 0x000000000552bb90>
> log(tmp5,2)
<pointer: 0x000000000552bb90>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.4974
> Min(tmp5)
[1] 52.58971
> mean(tmp5)
[1] 73.71878
> Sum(tmp5)
[1] 14743.76
> Var(tmp5)
[1] 840.1045
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.78862 74.23148 71.92378 72.57421 71.70595 71.56179 71.06034 71.70771
[9] 71.51775 70.11617
> rowSums(tmp5)
[1] 1815.772 1484.630 1438.476 1451.484 1434.119 1431.236 1421.207 1434.154
[9] 1430.355 1402.323
> rowVars(tmp5)
[1] 7908.61611 91.75700 52.04304 57.83328 73.74276 63.70572
[7] 69.73734 64.76729 45.66525 19.73866
> rowSd(tmp5)
[1] 88.930400 9.578987 7.214086 7.604820 8.587360 7.981586 8.350889
[8] 8.047813 6.757607 4.442821
> rowMax(tmp5)
[1] 466.49738 88.97575 82.29782 84.98813 89.09849 82.28186 85.60664
[8] 93.65615 82.83298 78.20836
> rowMin(tmp5)
[1] 52.58971 58.33445 61.78416 56.51348 56.82824 53.51201 55.25421 60.09082
[9] 58.49902 60.37136
>
> colMeans(tmp5)
[1] 113.87701 75.19188 75.35394 72.23846 72.62657 70.16571 67.12104
[8] 71.00254 67.77654 72.89230 76.32259 70.36305 73.52203 69.98921
[15] 74.47961 70.35638 67.25917 73.71878 69.28439 70.83440
> colSums(tmp5)
[1] 1138.7701 751.9188 753.5394 722.3846 726.2657 701.6571 671.2104
[8] 710.0254 677.7654 728.9230 763.2259 703.6305 735.2203 699.8921
[15] 744.7961 703.5638 672.5917 737.1878 692.8439 708.3440
> colVars(tmp5)
[1] 15460.22268 55.02646 45.88310 16.85831 47.75346 24.18153
[7] 43.56391 67.30129 63.57377 90.67463 64.36200 69.15838
[13] 54.12128 67.32663 64.56778 81.86479 83.41497 33.11398
[19] 37.73078 67.14259
> colSd(tmp5)
[1] 124.339144 7.417982 6.773707 4.105888 6.910388 4.917471
[7] 6.600296 8.203736 7.973316 9.522322 8.022593 8.316152
[13] 7.356717 8.205281 8.035408 9.047917 9.133180 5.754475
[19] 6.142538 8.194058
> colMax(tmp5)
[1] 466.49738 82.82896 88.97575 78.95313 83.16078 76.91773 81.70612
[8] 84.62431 76.44854 87.25949 85.60664 89.09849 83.73503 82.28186
[15] 86.28299 82.20775 81.66078 80.77970 82.90914 81.19555
> colMin(tmp5)
[1] 63.50151 60.37136 64.13439 66.61261 63.45764 61.78416 59.35465 58.56689
[9] 55.25421 58.59971 63.60613 58.37124 63.59772 58.33445 63.12383 53.51201
[17] 52.58971 63.04979 60.54543 58.49902
>
>
> ### 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] 90.78862 74.23148 71.92378 72.57421 71.70595 71.56179 71.06034 71.70771
[9] NA 70.11617
> rowSums(tmp5)
[1] 1815.772 1484.630 1438.476 1451.484 1434.119 1431.236 1421.207 1434.154
[9] NA 1402.323
> rowVars(tmp5)
[1] 7908.61611 91.75700 52.04304 57.83328 73.74276 63.70572
[7] 69.73734 64.76729 44.62937 19.73866
> rowSd(tmp5)
[1] 88.930400 9.578987 7.214086 7.604820 8.587360 7.981586 8.350889
[8] 8.047813 6.680521 4.442821
> rowMax(tmp5)
[1] 466.49738 88.97575 82.29782 84.98813 89.09849 82.28186 85.60664
[8] 93.65615 NA 78.20836
> rowMin(tmp5)
[1] 52.58971 58.33445 61.78416 56.51348 56.82824 53.51201 55.25421 60.09082
[9] NA 60.37136
>
> colMeans(tmp5)
[1] 113.87701 75.19188 NA 72.23846 72.62657 70.16571 67.12104
[8] 71.00254 67.77654 72.89230 76.32259 70.36305 73.52203 69.98921
[15] 74.47961 70.35638 67.25917 73.71878 69.28439 70.83440
> colSums(tmp5)
[1] 1138.7701 751.9188 NA 722.3846 726.2657 701.6571 671.2104
[8] 710.0254 677.7654 728.9230 763.2259 703.6305 735.2203 699.8921
[15] 744.7961 703.5638 672.5917 737.1878 692.8439 708.3440
> colVars(tmp5)
[1] 15460.22268 55.02646 NA 16.85831 47.75346 24.18153
[7] 43.56391 67.30129 63.57377 90.67463 64.36200 69.15838
[13] 54.12128 67.32663 64.56778 81.86479 83.41497 33.11398
[19] 37.73078 67.14259
> colSd(tmp5)
[1] 124.339144 7.417982 NA 4.105888 6.910388 4.917471
[7] 6.600296 8.203736 7.973316 9.522322 8.022593 8.316152
[13] 7.356717 8.205281 8.035408 9.047917 9.133180 5.754475
[19] 6.142538 8.194058
> colMax(tmp5)
[1] 466.49738 82.82896 NA 78.95313 83.16078 76.91773 81.70612
[8] 84.62431 76.44854 87.25949 85.60664 89.09849 83.73503 82.28186
[15] 86.28299 82.20775 81.66078 80.77970 82.90914 81.19555
> colMin(tmp5)
[1] 63.50151 60.37136 NA 66.61261 63.45764 61.78416 59.35465 58.56689
[9] 55.25421 58.59971 63.60613 58.37124 63.59772 58.33445 63.12383 53.51201
[17] 52.58971 63.04979 60.54543 58.49902
>
> Max(tmp5,na.rm=TRUE)
[1] 466.4974
> Min(tmp5,na.rm=TRUE)
[1] 52.58971
> mean(tmp5,na.rm=TRUE)
[1] 73.69056
> Sum(tmp5,na.rm=TRUE)
[1] 14664.42
> Var(tmp5,na.rm=TRUE)
[1] 844.1874
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.78862 74.23148 71.92378 72.57421 71.70595 71.56179 71.06034 71.70771
[9] 71.10636 70.11617
> rowSums(tmp5,na.rm=TRUE)
[1] 1815.772 1484.630 1438.476 1451.484 1434.119 1431.236 1421.207 1434.154
[9] 1351.021 1402.323
> rowVars(tmp5,na.rm=TRUE)
[1] 7908.61611 91.75700 52.04304 57.83328 73.74276 63.70572
[7] 69.73734 64.76729 44.62937 19.73866
> rowSd(tmp5,na.rm=TRUE)
[1] 88.930400 9.578987 7.214086 7.604820 8.587360 7.981586 8.350889
[8] 8.047813 6.680521 4.442821
> rowMax(tmp5,na.rm=TRUE)
[1] 466.49738 88.97575 82.29782 84.98813 89.09849 82.28186 85.60664
[8] 93.65615 82.83298 78.20836
> rowMin(tmp5,na.rm=TRUE)
[1] 52.58971 58.33445 61.78416 56.51348 56.82824 53.51201 55.25421 60.09082
[9] 58.49902 60.37136
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.87701 75.19188 74.91170 72.23846 72.62657 70.16571 67.12104
[8] 71.00254 67.77654 72.89230 76.32259 70.36305 73.52203 69.98921
[15] 74.47961 70.35638 67.25917 73.71878 69.28439 70.83440
> colSums(tmp5,na.rm=TRUE)
[1] 1138.7701 751.9188 674.2053 722.3846 726.2657 701.6571 671.2104
[8] 710.0254 677.7654 728.9230 763.2259 703.6305 735.2203 699.8921
[15] 744.7961 703.5638 672.5917 737.1878 692.8439 708.3440
> colVars(tmp5,na.rm=TRUE)
[1] 15460.22268 55.02646 49.41823 16.85831 47.75346 24.18153
[7] 43.56391 67.30129 63.57377 90.67463 64.36200 69.15838
[13] 54.12128 67.32663 64.56778 81.86479 83.41497 33.11398
[19] 37.73078 67.14259
> colSd(tmp5,na.rm=TRUE)
[1] 124.339144 7.417982 7.029810 4.105888 6.910388 4.917471
[7] 6.600296 8.203736 7.973316 9.522322 8.022593 8.316152
[13] 7.356717 8.205281 8.035408 9.047917 9.133180 5.754475
[19] 6.142538 8.194058
> colMax(tmp5,na.rm=TRUE)
[1] 466.49738 82.82896 88.97575 78.95313 83.16078 76.91773 81.70612
[8] 84.62431 76.44854 87.25949 85.60664 89.09849 83.73503 82.28186
[15] 86.28299 82.20775 81.66078 80.77970 82.90914 81.19555
> colMin(tmp5,na.rm=TRUE)
[1] 63.50151 60.37136 64.13439 66.61261 63.45764 61.78416 59.35465 58.56689
[9] 55.25421 58.59971 63.60613 58.37124 63.59772 58.33445 63.12383 53.51201
[17] 52.58971 63.04979 60.54543 58.49902
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.78862 74.23148 71.92378 72.57421 71.70595 71.56179 71.06034 71.70771
[9] NaN 70.11617
> rowSums(tmp5,na.rm=TRUE)
[1] 1815.772 1484.630 1438.476 1451.484 1434.119 1431.236 1421.207 1434.154
[9] 0.000 1402.323
> rowVars(tmp5,na.rm=TRUE)
[1] 7908.61611 91.75700 52.04304 57.83328 73.74276 63.70572
[7] 69.73734 64.76729 NA 19.73866
> rowSd(tmp5,na.rm=TRUE)
[1] 88.930400 9.578987 7.214086 7.604820 8.587360 7.981586 8.350889
[8] 8.047813 NA 4.442821
> rowMax(tmp5,na.rm=TRUE)
[1] 466.49738 88.97575 82.29782 84.98813 89.09849 82.28186 85.60664
[8] 93.65615 NA 78.20836
> rowMin(tmp5,na.rm=TRUE)
[1] 52.58971 58.33445 61.78416 56.51348 56.82824 53.51201 55.25421 60.09082
[9] NA 60.37136
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 119.04306 75.08301 NaN 72.14672 73.26020 69.63760 66.73470
[8] 70.84635 68.71522 73.70757 75.93552 70.21691 72.48748 69.71455
[15] 75.02098 69.72842 67.76143 72.98062 69.12973 72.20499
> colSums(tmp5,na.rm=TRUE)
[1] 1071.3875 675.7471 0.0000 649.3205 659.3418 626.7384 600.6123
[8] 637.6172 618.4370 663.3681 683.4197 631.9522 652.3873 627.4310
[15] 675.1888 627.5558 609.8529 656.8256 622.1675 649.8450
> colVars(tmp5,na.rm=TRUE)
[1] 17092.50993 61.77143 NA 18.87092 49.20584 24.06668
[7] 47.33020 75.43952 61.60799 94.53139 70.72172 77.56293
[13] 48.84563 74.89380 69.34152 87.66158 91.00394 31.12334
[19] 42.17802 54.40188
> colSd(tmp5,na.rm=TRUE)
[1] 130.738326 7.859480 NA 4.344067 7.014687 4.905780
[7] 6.879695 8.685592 7.849076 9.722726 8.409621 8.806982
[13] 6.988965 8.654120 8.327156 9.362776 9.539598 5.578830
[19] 6.494461 7.375763
> colMax(tmp5,na.rm=TRUE)
[1] 466.49738 82.82896 -Inf 78.95313 83.16078 76.91773 81.70612
[8] 84.62431 76.44854 87.25949 85.60664 89.09849 83.73503 82.28186
[15] 86.28299 82.20775 81.66078 80.77970 82.90914 81.19555
> colMin(tmp5,na.rm=TRUE)
[1] 63.50151 60.37136 Inf 66.61261 63.45764 61.78416 59.35465 58.56689
[9] 55.25421 58.59971 63.60613 58.37124 63.59772 58.33445 63.12383 53.51201
[17] 52.58971 63.04979 60.54543 62.64999
>
>
>
>
> 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] 180.3538 161.6949 309.4696 342.7126 213.3873 234.6044 280.7854 184.6201
[9] 143.2229 248.8611
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 180.3538 161.6949 309.4696 342.7126 213.3873 234.6044 280.7854 184.6201
[9] 143.2229 248.8611
>
>
>
> 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] 2.842171e-13 7.105427e-14 5.684342e-14 0.000000e+00 -2.842171e-14
[6] 0.000000e+00 0.000000e+00 2.842171e-14 8.526513e-14 5.684342e-14
[11] 5.684342e-14 -1.136868e-13 8.526513e-14 1.136868e-13 0.000000e+00
[16] 0.000000e+00 0.000000e+00 0.000000e+00 1.136868e-13 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)
+ }
3 13
8 19
1 13
8 17
7 10
4 2
7 3
1 13
6 16
4 17
1 19
4 2
7 15
5 8
10 19
3 18
4 8
9 5
1 3
9 2
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] 1.745974
> Min(tmp)
[1] -1.991914
> mean(tmp)
[1] -0.07677234
> Sum(tmp)
[1] -7.677234
> Var(tmp)
[1] 0.6965035
>
> rowMeans(tmp)
[1] -0.07677234
> rowSums(tmp)
[1] -7.677234
> rowVars(tmp)
[1] 0.6965035
> rowSd(tmp)
[1] 0.8345679
> rowMax(tmp)
[1] 1.745974
> rowMin(tmp)
[1] -1.991914
>
> colMeans(tmp)
[1] -1.024555009 -0.624733842 0.497406858 1.110465082 0.763755418
[6] 1.259674560 0.006237886 -0.880337009 0.579643546 -1.093259354
[11] 0.009237298 -0.301425181 -0.626944735 -1.683017728 1.679820058
[16] 0.460693424 -0.109703186 -0.490052351 0.510460117 -0.067456112
[21] 0.331296015 -1.316523522 -1.591583909 0.043735995 1.003826202
[26] 0.772580793 0.740786111 0.158507459 -0.963672551 -0.371654092
[31] -0.641333916 0.904962274 0.049862043 0.100517693 -0.429896614
[36] 0.020277506 -1.380729985 -0.369326367 -0.743179601 -0.909495430
[41] 0.809052137 0.047940483 0.395463751 -0.289448877 0.086843986
[46] 1.371524180 -0.787089717 0.390906201 -0.392055849 0.155410322
[51] 0.168070844 0.646903817 -0.605663222 1.097394662 -0.593794018
[56] -1.043286086 -0.959487113 0.122179674 0.530983363 -0.177019424
[61] 0.364799138 -0.914435619 0.028006715 1.543462662 -0.924507323
[66] 0.358324240 0.475510107 1.678001892 1.745974454 -0.030692524
[71] -0.818039671 -1.445117794 0.735999951 -0.093450560 -0.773800184
[76] 0.602658807 -1.093727818 -0.060777215 -0.438624569 -1.332552136
[81] -0.626275988 -1.079824775 0.003012200 1.009591982 -0.642399812
[86] 0.870410350 -1.124654614 0.016960704 0.297693092 0.559077176
[91] -0.440722148 0.206421206 -1.991914395 -0.952974260 1.411489352
[96] -1.163010944 0.123432104 -1.352334820 0.720605077 0.511476566
> colSums(tmp)
[1] -1.024555009 -0.624733842 0.497406858 1.110465082 0.763755418
[6] 1.259674560 0.006237886 -0.880337009 0.579643546 -1.093259354
[11] 0.009237298 -0.301425181 -0.626944735 -1.683017728 1.679820058
[16] 0.460693424 -0.109703186 -0.490052351 0.510460117 -0.067456112
[21] 0.331296015 -1.316523522 -1.591583909 0.043735995 1.003826202
[26] 0.772580793 0.740786111 0.158507459 -0.963672551 -0.371654092
[31] -0.641333916 0.904962274 0.049862043 0.100517693 -0.429896614
[36] 0.020277506 -1.380729985 -0.369326367 -0.743179601 -0.909495430
[41] 0.809052137 0.047940483 0.395463751 -0.289448877 0.086843986
[46] 1.371524180 -0.787089717 0.390906201 -0.392055849 0.155410322
[51] 0.168070844 0.646903817 -0.605663222 1.097394662 -0.593794018
[56] -1.043286086 -0.959487113 0.122179674 0.530983363 -0.177019424
[61] 0.364799138 -0.914435619 0.028006715 1.543462662 -0.924507323
[66] 0.358324240 0.475510107 1.678001892 1.745974454 -0.030692524
[71] -0.818039671 -1.445117794 0.735999951 -0.093450560 -0.773800184
[76] 0.602658807 -1.093727818 -0.060777215 -0.438624569 -1.332552136
[81] -0.626275988 -1.079824775 0.003012200 1.009591982 -0.642399812
[86] 0.870410350 -1.124654614 0.016960704 0.297693092 0.559077176
[91] -0.440722148 0.206421206 -1.991914395 -0.952974260 1.411489352
[96] -1.163010944 0.123432104 -1.352334820 0.720605077 0.511476566
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] -1.024555009 -0.624733842 0.497406858 1.110465082 0.763755418
[6] 1.259674560 0.006237886 -0.880337009 0.579643546 -1.093259354
[11] 0.009237298 -0.301425181 -0.626944735 -1.683017728 1.679820058
[16] 0.460693424 -0.109703186 -0.490052351 0.510460117 -0.067456112
[21] 0.331296015 -1.316523522 -1.591583909 0.043735995 1.003826202
[26] 0.772580793 0.740786111 0.158507459 -0.963672551 -0.371654092
[31] -0.641333916 0.904962274 0.049862043 0.100517693 -0.429896614
[36] 0.020277506 -1.380729985 -0.369326367 -0.743179601 -0.909495430
[41] 0.809052137 0.047940483 0.395463751 -0.289448877 0.086843986
[46] 1.371524180 -0.787089717 0.390906201 -0.392055849 0.155410322
[51] 0.168070844 0.646903817 -0.605663222 1.097394662 -0.593794018
[56] -1.043286086 -0.959487113 0.122179674 0.530983363 -0.177019424
[61] 0.364799138 -0.914435619 0.028006715 1.543462662 -0.924507323
[66] 0.358324240 0.475510107 1.678001892 1.745974454 -0.030692524
[71] -0.818039671 -1.445117794 0.735999951 -0.093450560 -0.773800184
[76] 0.602658807 -1.093727818 -0.060777215 -0.438624569 -1.332552136
[81] -0.626275988 -1.079824775 0.003012200 1.009591982 -0.642399812
[86] 0.870410350 -1.124654614 0.016960704 0.297693092 0.559077176
[91] -0.440722148 0.206421206 -1.991914395 -0.952974260 1.411489352
[96] -1.163010944 0.123432104 -1.352334820 0.720605077 0.511476566
> colMin(tmp)
[1] -1.024555009 -0.624733842 0.497406858 1.110465082 0.763755418
[6] 1.259674560 0.006237886 -0.880337009 0.579643546 -1.093259354
[11] 0.009237298 -0.301425181 -0.626944735 -1.683017728 1.679820058
[16] 0.460693424 -0.109703186 -0.490052351 0.510460117 -0.067456112
[21] 0.331296015 -1.316523522 -1.591583909 0.043735995 1.003826202
[26] 0.772580793 0.740786111 0.158507459 -0.963672551 -0.371654092
[31] -0.641333916 0.904962274 0.049862043 0.100517693 -0.429896614
[36] 0.020277506 -1.380729985 -0.369326367 -0.743179601 -0.909495430
[41] 0.809052137 0.047940483 0.395463751 -0.289448877 0.086843986
[46] 1.371524180 -0.787089717 0.390906201 -0.392055849 0.155410322
[51] 0.168070844 0.646903817 -0.605663222 1.097394662 -0.593794018
[56] -1.043286086 -0.959487113 0.122179674 0.530983363 -0.177019424
[61] 0.364799138 -0.914435619 0.028006715 1.543462662 -0.924507323
[66] 0.358324240 0.475510107 1.678001892 1.745974454 -0.030692524
[71] -0.818039671 -1.445117794 0.735999951 -0.093450560 -0.773800184
[76] 0.602658807 -1.093727818 -0.060777215 -0.438624569 -1.332552136
[81] -0.626275988 -1.079824775 0.003012200 1.009591982 -0.642399812
[86] 0.870410350 -1.124654614 0.016960704 0.297693092 0.559077176
[91] -0.440722148 0.206421206 -1.991914395 -0.952974260 1.411489352
[96] -1.163010944 0.123432104 -1.352334820 0.720605077 0.511476566
> colMedians(tmp)
[1] -1.024555009 -0.624733842 0.497406858 1.110465082 0.763755418
[6] 1.259674560 0.006237886 -0.880337009 0.579643546 -1.093259354
[11] 0.009237298 -0.301425181 -0.626944735 -1.683017728 1.679820058
[16] 0.460693424 -0.109703186 -0.490052351 0.510460117 -0.067456112
[21] 0.331296015 -1.316523522 -1.591583909 0.043735995 1.003826202
[26] 0.772580793 0.740786111 0.158507459 -0.963672551 -0.371654092
[31] -0.641333916 0.904962274 0.049862043 0.100517693 -0.429896614
[36] 0.020277506 -1.380729985 -0.369326367 -0.743179601 -0.909495430
[41] 0.809052137 0.047940483 0.395463751 -0.289448877 0.086843986
[46] 1.371524180 -0.787089717 0.390906201 -0.392055849 0.155410322
[51] 0.168070844 0.646903817 -0.605663222 1.097394662 -0.593794018
[56] -1.043286086 -0.959487113 0.122179674 0.530983363 -0.177019424
[61] 0.364799138 -0.914435619 0.028006715 1.543462662 -0.924507323
[66] 0.358324240 0.475510107 1.678001892 1.745974454 -0.030692524
[71] -0.818039671 -1.445117794 0.735999951 -0.093450560 -0.773800184
[76] 0.602658807 -1.093727818 -0.060777215 -0.438624569 -1.332552136
[81] -0.626275988 -1.079824775 0.003012200 1.009591982 -0.642399812
[86] 0.870410350 -1.124654614 0.016960704 0.297693092 0.559077176
[91] -0.440722148 0.206421206 -1.991914395 -0.952974260 1.411489352
[96] -1.163010944 0.123432104 -1.352334820 0.720605077 0.511476566
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.024555 -0.6247338 0.4974069 1.110465 0.7637554 1.259675 0.006237886
[2,] -1.024555 -0.6247338 0.4974069 1.110465 0.7637554 1.259675 0.006237886
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.880337 0.5796435 -1.093259 0.009237298 -0.3014252 -0.6269447 -1.683018
[2,] -0.880337 0.5796435 -1.093259 0.009237298 -0.3014252 -0.6269447 -1.683018
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.67982 0.4606934 -0.1097032 -0.4900524 0.5104601 -0.06745611 0.331296
[2,] 1.67982 0.4606934 -0.1097032 -0.4900524 0.5104601 -0.06745611 0.331296
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.316524 -1.591584 0.043736 1.003826 0.7725808 0.7407861 0.1585075
[2,] -1.316524 -1.591584 0.043736 1.003826 0.7725808 0.7407861 0.1585075
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.9636726 -0.3716541 -0.6413339 0.9049623 0.04986204 0.1005177 -0.4298966
[2,] -0.9636726 -0.3716541 -0.6413339 0.9049623 0.04986204 0.1005177 -0.4298966
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.02027751 -1.38073 -0.3693264 -0.7431796 -0.9094954 0.8090521 0.04794048
[2,] 0.02027751 -1.38073 -0.3693264 -0.7431796 -0.9094954 0.8090521 0.04794048
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.3954638 -0.2894489 0.08684399 1.371524 -0.7870897 0.3909062 -0.3920558
[2,] 0.3954638 -0.2894489 0.08684399 1.371524 -0.7870897 0.3909062 -0.3920558
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.1554103 0.1680708 0.6469038 -0.6056632 1.097395 -0.593794 -1.043286
[2,] 0.1554103 0.1680708 0.6469038 -0.6056632 1.097395 -0.593794 -1.043286
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.9594871 0.1221797 0.5309834 -0.1770194 0.3647991 -0.9144356 0.02800672
[2,] -0.9594871 0.1221797 0.5309834 -0.1770194 0.3647991 -0.9144356 0.02800672
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 1.543463 -0.9245073 0.3583242 0.4755101 1.678002 1.745974 -0.03069252
[2,] 1.543463 -0.9245073 0.3583242 0.4755101 1.678002 1.745974 -0.03069252
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.8180397 -1.445118 0.736 -0.09345056 -0.7738002 0.6026588 -1.093728
[2,] -0.8180397 -1.445118 0.736 -0.09345056 -0.7738002 0.6026588 -1.093728
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.06077722 -0.4386246 -1.332552 -0.626276 -1.079825 0.0030122 1.009592
[2,] -0.06077722 -0.4386246 -1.332552 -0.626276 -1.079825 0.0030122 1.009592
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.6423998 0.8704103 -1.124655 0.0169607 0.2976931 0.5590772 -0.4407221
[2,] -0.6423998 0.8704103 -1.124655 0.0169607 0.2976931 0.5590772 -0.4407221
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.2064212 -1.991914 -0.9529743 1.411489 -1.163011 0.1234321 -1.352335
[2,] 0.2064212 -1.991914 -0.9529743 1.411489 -1.163011 0.1234321 -1.352335
[,99] [,100]
[1,] 0.7206051 0.5114766
[2,] 0.7206051 0.5114766
>
>
> Max(tmp2)
[1] 3.269933
> Min(tmp2)
[1] -2.209855
> mean(tmp2)
[1] 0.2097211
> Sum(tmp2)
[1] 20.97211
> Var(tmp2)
[1] 0.9981095
>
> rowMeans(tmp2)
[1] 1.496825223 0.675031938 0.549126412 0.737548195 1.904387537
[6] 0.006226765 0.977515256 0.086370166 1.513071018 0.318994164
[11] -0.028629725 -0.767178733 -0.375939927 -1.010787870 -1.040461367
[16] -0.070944541 0.376418735 3.269933352 -0.326630150 0.132312426
[21] 0.961810410 0.448365262 0.528468402 1.293248898 -1.822501088
[26] 0.320450462 0.875725295 -0.577564655 0.865654791 0.721469361
[31] 0.406517170 1.058350833 -0.825075610 -0.297119324 2.625442608
[36] 0.851750407 1.347884458 -0.140701159 -0.331904178 -0.287656894
[41] 0.181871044 -0.120282619 0.615382232 -1.851067441 -0.084982331
[46] 1.912313078 -1.325468803 -0.499167151 1.786176603 -0.425640714
[51] 1.199736227 -0.521257941 0.738720433 -1.341495776 -0.056059288
[56] 0.678917767 -2.209854837 0.461324098 0.502952071 0.311339477
[61] 1.157656072 0.271666611 0.238685994 -0.233709307 0.336820115
[66] -0.416446242 -0.937482412 0.333716816 -0.101924660 -1.360412517
[71] 2.154936265 -0.868749865 2.231220389 1.842349504 -1.125318233
[76] 0.553604183 -0.838966767 -1.717311261 -0.669285277 0.351941249
[81] -1.120978309 0.404292877 0.629649760 -0.031507470 -0.292395752
[86] 0.849244256 1.250096213 -0.112784489 0.514669141 1.487227104
[91] 0.961865717 -1.402751325 -0.039949139 -0.334193283 0.693384695
[96] -0.734981766 0.171261810 -0.290122934 0.618461302 0.149369872
> rowSums(tmp2)
[1] 1.496825223 0.675031938 0.549126412 0.737548195 1.904387537
[6] 0.006226765 0.977515256 0.086370166 1.513071018 0.318994164
[11] -0.028629725 -0.767178733 -0.375939927 -1.010787870 -1.040461367
[16] -0.070944541 0.376418735 3.269933352 -0.326630150 0.132312426
[21] 0.961810410 0.448365262 0.528468402 1.293248898 -1.822501088
[26] 0.320450462 0.875725295 -0.577564655 0.865654791 0.721469361
[31] 0.406517170 1.058350833 -0.825075610 -0.297119324 2.625442608
[36] 0.851750407 1.347884458 -0.140701159 -0.331904178 -0.287656894
[41] 0.181871044 -0.120282619 0.615382232 -1.851067441 -0.084982331
[46] 1.912313078 -1.325468803 -0.499167151 1.786176603 -0.425640714
[51] 1.199736227 -0.521257941 0.738720433 -1.341495776 -0.056059288
[56] 0.678917767 -2.209854837 0.461324098 0.502952071 0.311339477
[61] 1.157656072 0.271666611 0.238685994 -0.233709307 0.336820115
[66] -0.416446242 -0.937482412 0.333716816 -0.101924660 -1.360412517
[71] 2.154936265 -0.868749865 2.231220389 1.842349504 -1.125318233
[76] 0.553604183 -0.838966767 -1.717311261 -0.669285277 0.351941249
[81] -1.120978309 0.404292877 0.629649760 -0.031507470 -0.292395752
[86] 0.849244256 1.250096213 -0.112784489 0.514669141 1.487227104
[91] 0.961865717 -1.402751325 -0.039949139 -0.334193283 0.693384695
[96] -0.734981766 0.171261810 -0.290122934 0.618461302 0.149369872
> 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] 1.496825223 0.675031938 0.549126412 0.737548195 1.904387537
[6] 0.006226765 0.977515256 0.086370166 1.513071018 0.318994164
[11] -0.028629725 -0.767178733 -0.375939927 -1.010787870 -1.040461367
[16] -0.070944541 0.376418735 3.269933352 -0.326630150 0.132312426
[21] 0.961810410 0.448365262 0.528468402 1.293248898 -1.822501088
[26] 0.320450462 0.875725295 -0.577564655 0.865654791 0.721469361
[31] 0.406517170 1.058350833 -0.825075610 -0.297119324 2.625442608
[36] 0.851750407 1.347884458 -0.140701159 -0.331904178 -0.287656894
[41] 0.181871044 -0.120282619 0.615382232 -1.851067441 -0.084982331
[46] 1.912313078 -1.325468803 -0.499167151 1.786176603 -0.425640714
[51] 1.199736227 -0.521257941 0.738720433 -1.341495776 -0.056059288
[56] 0.678917767 -2.209854837 0.461324098 0.502952071 0.311339477
[61] 1.157656072 0.271666611 0.238685994 -0.233709307 0.336820115
[66] -0.416446242 -0.937482412 0.333716816 -0.101924660 -1.360412517
[71] 2.154936265 -0.868749865 2.231220389 1.842349504 -1.125318233
[76] 0.553604183 -0.838966767 -1.717311261 -0.669285277 0.351941249
[81] -1.120978309 0.404292877 0.629649760 -0.031507470 -0.292395752
[86] 0.849244256 1.250096213 -0.112784489 0.514669141 1.487227104
[91] 0.961865717 -1.402751325 -0.039949139 -0.334193283 0.693384695
[96] -0.734981766 0.171261810 -0.290122934 0.618461302 0.149369872
> rowMin(tmp2)
[1] 1.496825223 0.675031938 0.549126412 0.737548195 1.904387537
[6] 0.006226765 0.977515256 0.086370166 1.513071018 0.318994164
[11] -0.028629725 -0.767178733 -0.375939927 -1.010787870 -1.040461367
[16] -0.070944541 0.376418735 3.269933352 -0.326630150 0.132312426
[21] 0.961810410 0.448365262 0.528468402 1.293248898 -1.822501088
[26] 0.320450462 0.875725295 -0.577564655 0.865654791 0.721469361
[31] 0.406517170 1.058350833 -0.825075610 -0.297119324 2.625442608
[36] 0.851750407 1.347884458 -0.140701159 -0.331904178 -0.287656894
[41] 0.181871044 -0.120282619 0.615382232 -1.851067441 -0.084982331
[46] 1.912313078 -1.325468803 -0.499167151 1.786176603 -0.425640714
[51] 1.199736227 -0.521257941 0.738720433 -1.341495776 -0.056059288
[56] 0.678917767 -2.209854837 0.461324098 0.502952071 0.311339477
[61] 1.157656072 0.271666611 0.238685994 -0.233709307 0.336820115
[66] -0.416446242 -0.937482412 0.333716816 -0.101924660 -1.360412517
[71] 2.154936265 -0.868749865 2.231220389 1.842349504 -1.125318233
[76] 0.553604183 -0.838966767 -1.717311261 -0.669285277 0.351941249
[81] -1.120978309 0.404292877 0.629649760 -0.031507470 -0.292395752
[86] 0.849244256 1.250096213 -0.112784489 0.514669141 1.487227104
[91] 0.961865717 -1.402751325 -0.039949139 -0.334193283 0.693384695
[96] -0.734981766 0.171261810 -0.290122934 0.618461302 0.149369872
>
> colMeans(tmp2)
[1] 0.2097211
> colSums(tmp2)
[1] 20.97211
> colVars(tmp2)
[1] 0.9981095
> colSd(tmp2)
[1] 0.9990543
> colMax(tmp2)
[1] 3.269933
> colMin(tmp2)
[1] -2.209855
> colMedians(tmp2)
[1] 0.2551763
> colRanges(tmp2)
[,1]
[1,] -2.209855
[2,] 3.269933
>
> 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] 0.8113618 3.8655284 3.2562520 -2.0597074 -1.1409658 0.7750562
[7] 4.7437156 2.6762069 2.2314135 0.9509987
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.88243525
[2,] -0.38191416
[3,] -0.07315471
[4,] 0.58554515
[5,] 1.19448494
>
> rowApply(tmp,sum)
[1] 2.746565 2.125293 -5.447199 -1.329492 1.945420 4.712298 2.418620
[8] 2.101422 4.058563 2.778368
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 4 5 5 10 4 4 1 8 8 5
[2,] 6 9 8 6 3 10 9 1 3 10
[3,] 7 4 4 3 9 7 5 4 1 9
[4,] 3 10 3 5 1 3 2 7 2 6
[5,] 8 6 7 2 7 1 10 5 4 1
[6,] 5 2 9 9 6 8 3 6 6 3
[7,] 1 1 10 7 10 9 8 3 9 2
[8,] 10 7 1 8 8 5 6 2 5 8
[9,] 2 8 6 4 2 6 7 10 7 4
[10,] 9 3 2 1 5 2 4 9 10 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.4073435 -1.0257833 1.8312482 0.1333035 1.3635493 -0.9260714
[7] -1.8284904 0.6297676 0.5022410 0.7604699 -1.3284106 -4.1479610
[13] -1.3594724 -2.3681878 5.2398324 -1.4002742 5.3475002 0.6934626
[19] 0.9759851 1.9593865
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.21239303
[2,] -0.77211770
[3,] 0.05646434
[4,] 0.52156075
[5,] 0.99914218
>
> rowApply(tmp,sum)
[1] 4.671132 3.104607 7.219634 -1.841557 -8.509064
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 10 15 14 4 6
[2,] 15 2 6 16 8
[3,] 16 19 13 8 10
[4,] 14 11 3 9 18
[5,] 2 20 16 2 17
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.05646434 0.7486797 0.8241904 0.42087906 -1.0909016 -0.60499268
[2,] 0.52156075 -1.0034792 1.3244356 0.07264778 1.9336716 0.04107833
[3,] 0.99914218 -0.2923008 0.7016796 -0.83004086 1.2296241 -0.26996502
[4,] -0.77211770 0.2239159 -0.4625418 -0.23478960 -1.3886493 0.19985435
[5,] -1.21239303 -0.7025989 -0.5565156 0.70460709 0.6798046 -0.29204635
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.2248948 -0.76906272 0.138972674 -1.1973126 -0.9349523 0.04033646
[2,] 0.4168051 0.34009098 0.006531521 0.1527855 0.6134632 -1.84160734
[3,] -1.9016700 1.68832188 0.077775316 1.4974213 0.5987426 -0.93865598
[4,] -0.1337976 -0.57447348 -0.555170084 0.8457713 -0.1270843 -1.06640684
[5,] -0.4347226 -0.05510903 0.834131559 -0.5381956 -1.4785799 -0.34162727
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.32033105 -0.2643106 2.0657214 0.027201456 2.16802312 1.47111254
[2,] -0.71537080 -0.1382712 -0.1011423 -0.006589094 -0.25055327 0.04900499
[3,] 0.06932208 -0.5244736 1.2249973 0.634315783 1.87433097 -0.29245742
[4,] -1.40085248 -0.2095962 1.8613465 -0.675958229 0.05990648 0.75800132
[5,] -0.63290222 -1.2315361 0.1889095 -1.379244139 1.49579286 -1.29219887
[,19] [,20]
[1,] -0.32404106 0.34989833
[2,] 0.86704004 0.82250478
[3,] -0.06385376 1.73737875
[4,] 1.88109064 -0.07000578
[5,] -1.38425074 -0.88038955
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 679 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 589 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 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 0.9665786 -0.0383086 0.925293 1.528415 -0.8460476 0.07224391 1.388734
col8 col9 col10 col11 col12 col13 col14
row1 -1.71891 0.6833038 -0.750877 -1.216471 -2.15042 -0.5967329 0.706111
col15 col16 col17 col18 col19 col20
row1 0.4189994 -2.62895 0.9209378 -1.521739 -0.671551 0.3490925
> tmp[,"col10"]
col10
row1 -0.7508770
row2 0.4711448
row3 -0.2771663
row4 -0.5050707
row5 1.6798540
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.9665786 -0.0383086 0.9252930 1.52841471 -0.8460476 0.07224391
row5 -1.1192413 -0.7145259 -0.7346847 -0.03226592 1.5676328 -0.52411879
col7 col8 col9 col10 col11 col12 col13
row1 1.3887342 -1.7189104 0.6833038 -0.750877 -1.216471 -2.1504204 -0.5967329
row5 0.4932658 0.4386106 2.3053476 1.679854 -1.328354 0.6338963 -0.8376689
col14 col15 col16 col17 col18 col19 col20
row1 0.7061110 0.4189994 -2.628950 0.9209378 -1.5217386 -0.67155104 0.3490925
row5 0.9937025 0.1458020 1.305508 0.3015891 0.5735671 0.03217496 0.6692701
> tmp[,c("col6","col20")]
col6 col20
row1 0.07224391 0.3490925
row2 -2.38989516 -0.6664914
row3 -0.44557271 0.4621159
row4 0.29316417 -0.9745962
row5 -0.52411879 0.6692701
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.07224391 0.3490925
row5 -0.52411879 0.6692701
>
>
>
>
> 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 51.05355 51.18531 49.85258 49.21352 49.43354 103.9874 50.40817 48.69859
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.94808 50.5898 49.34655 50.56726 51.18858 49.94807 49.74408 49.8039
col17 col18 col19 col20
row1 47.94785 49.5604 51.737 104.8704
> tmp[,"col10"]
col10
row1 50.58980
row2 29.37294
row3 30.45255
row4 32.07722
row5 49.95047
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.05355 51.18531 49.85258 49.21352 49.43354 103.9874 50.40817 48.69859
row5 49.02544 48.44540 50.59559 48.84880 50.19897 103.8861 50.39836 49.55791
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.94808 50.58980 49.34655 50.56726 51.18858 49.94807 49.74408 49.80390
row5 50.80911 49.95047 50.70186 50.23566 50.37536 48.85031 49.56294 50.48505
col17 col18 col19 col20
row1 47.94785 49.56040 51.73700 104.8704
row5 49.21935 50.17814 50.00916 104.2705
> tmp[,c("col6","col20")]
col6 col20
row1 103.98743 104.87045
row2 73.77374 75.19841
row3 75.08278 75.21283
row4 75.48514 75.16835
row5 103.88608 104.27051
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 103.9874 104.8704
row5 103.8861 104.2705
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 103.9874 104.8704
row5 103.8861 104.2705
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.8886952
[2,] -0.3951284
[3,] 0.7165117
[4,] -0.4262922
[5,] 0.6473624
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.9451658 0.8055901
[2,] -0.7720672 0.3097717
[3,] -2.2073748 1.0342197
[4,] 0.4343291 1.0667801
[5,] -1.3683682 0.2172761
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.1387328 0.561472007
[2,] 0.1053944 -0.004350291
[3,] -0.1839216 0.875160603
[4,] 1.6105928 -0.133839373
[5,] 1.5605419 1.327210038
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.138733
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.1387328
[2,] 0.1053944
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 1.6052743 -0.07735785 1.71807552 -0.4458327 -0.5027909 -0.8087320
row1 -0.7328736 -0.63648457 0.07559555 1.2323967 -0.7185288 0.1549539
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.7874206 -0.4949990 0.4620967 -0.6839021 0.1876741 0.05085142
row1 -1.2621298 0.4752904 -1.5145666 -1.0365178 0.1096328 -0.43543805
[,13] [,14] [,15] [,16] [,17] [,18]
row3 0.6024327 1.05048392 0.002384042 -0.009015186 -0.4376676 0.05416297
row1 0.6404653 -0.07248897 -0.455700568 0.557894400 0.8089042 -0.21877632
[,19] [,20]
row3 -0.6833191 -0.7019817
row1 0.7962904 -1.9239583
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.7248525 -1.114898 -0.1247496 -0.5195435 1.859741 0.2561715 0.5778141
[,8] [,9] [,10]
row2 1.715009 0.1548852 1.421313
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.539732 0.4129937 1.230935 -1.755254 -1.264202 -0.9016928 -0.6583939
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.03247819 0.478373 -2.128251 0.562493 -0.1952674 0.01633883 0.5300143
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.7051553 -0.8585175 -1.533374 0.8786183 -0.3115929 0.04163998
>
>
> 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: 0x00000000062ac408>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BMbf453071140"
[2] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BMbf44b948ae"
[3] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BMbf42e7b4fc7"
[4] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BMbf427365a75"
[5] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BMbf444801416"
[6] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BMbf42b303cce"
[7] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BMbf47d633e59"
[8] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BMbf419f55c64"
[9] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BMbf47b4b8"
[10] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BMbf4463825c0"
[11] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BMbf42bae662b"
[12] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BMbf41fb42ebe"
[13] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BMbf424363f90"
[14] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BMbf46a121442"
[15] "C:/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BMbf464a536fb"
>
>
> ### 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: 0x00000000079e0de0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x00000000079e0de0>
Warning message:
In dir.create(new.directory) :
'C:\Users\biocbuild\bbs-3.12-bioc\meat\BufferedMatrix.Rcheck\tests_x64' already exists
>
>
> RowMode(tmp)
<pointer: 0x00000000079e0de0>
> rowMedians(tmp)
[1] -0.302475246 -0.313084051 0.071393465 0.306612748 -0.525116950
[6] 0.284451174 0.021149192 -0.121599120 -0.255350662 0.187145068
[11] 0.070007157 -0.271248632 0.105586856 0.010175980 0.005037144
[16] 0.414426432 0.033319469 0.131128239 0.027036832 0.470210406
[21] -0.294277432 -0.180945721 -0.532707967 0.534566697 -0.484381692
[26] 0.258217436 0.016561721 -0.156220024 -0.496183450 0.453819046
[31] -0.010816662 0.252975378 -0.034204332 0.217026558 0.150238684
[36] 0.778400819 0.205441674 -0.559131503 0.030907395 0.403736663
[41] -0.020787102 -0.106003406 -0.288846837 0.262359238 0.049872851
[46] 0.269679111 0.190480633 0.271882951 -0.421475228 0.036090108
[51] 0.190188304 -0.048791318 0.065181692 -0.314465585 0.354990079
[56] 0.459230406 -0.138216889 -0.258209520 0.263181199 -0.252739296
[61] 0.347541469 -0.265096009 0.229295695 0.017293197 0.105033473
[66] 0.151574589 0.324989834 -0.167768307 -0.153275986 -0.356869441
[71] 0.328880809 -0.275770137 0.265899059 0.113269132 -0.426982035
[76] 0.159928137 0.054294009 -0.252760563 -0.375666465 0.281106617
[81] 0.135956498 -0.178175051 0.160600082 -0.143130275 -0.119324065
[86] 0.366105598 -0.395189262 -0.398858484 -0.044805908 0.076920756
[91] -0.331137656 0.170671086 0.373916243 0.278982265 -0.229061106
[96] -0.123810631 0.345636230 0.412380744 -0.252484075 -0.228070092
[101] -0.592906472 0.065208077 0.486608906 0.087567391 0.229249376
[106] 0.088992563 0.170917673 -0.097398065 0.454179670 -0.218073027
[111] 0.591493082 0.439863697 -0.036658614 -0.132989905 -0.197415008
[116] 0.178916656 -0.784062440 0.077079295 -0.116961860 -0.027221505
[121] -0.325982517 0.468739234 0.167520280 -0.302019795 0.194584568
[126] 0.076669951 -0.219713103 0.353596165 -0.212439180 -0.217338847
[131] -0.252968273 -0.079019743 -0.029949997 0.623652114 -0.120187738
[136] -0.370946855 0.189322622 0.087011129 0.403469425 0.349624189
[141] 0.052612812 -0.100154984 0.197950126 0.208851196 -0.262901723
[146] 0.383723376 0.222176596 0.109336992 -0.070624364 -0.394683857
[151] 0.269374044 0.046060447 -0.067011328 0.516706069 -0.050807661
[156] 0.181125276 -0.357636777 0.220836882 -0.383799015 0.571836050
[161] 0.197397130 -0.068504184 0.156005746 -0.090319148 0.192077758
[166] 0.026457944 0.322337565 0.123312887 -0.257718837 0.306415145
[171] -0.111659906 -0.121222781 -0.613456802 -0.380120516 -0.035165899
[176] -0.032671905 0.442870193 -0.693671253 -0.199160906 0.031011020
[181] -0.089991118 -0.230699643 -0.323529644 -0.293514020 0.206486810
[186] -0.315978767 0.363581771 -0.587981946 0.059643841 0.140122273
[191] -0.331184091 -0.052100982 0.069260464 -0.006534985 -0.020600436
[196] -0.768312561 0.520947981 -0.190727490 0.063641280 -0.336776640
[201] -0.160416382 0.596031966 -0.583425276 0.381706188 -0.108878747
[206] -0.280647138 0.442935485 0.149145490 -0.479714490 0.145089751
[211] 0.326182340 0.102874512 -0.211700095 0.198912005 0.331454563
[216] 0.213471520 0.149984465 -0.406524816 0.412521942 0.419274731
[221] 0.040791042 0.107315703 -0.046992610 -0.512084535 0.440048988
[226] -0.332328362 -0.454495208 -0.069058647 0.335496498 -0.747136536
>
> proc.time()
user system elapsed
2.12 5.68 19.81
|
|
BufferedMatrix.Rcheck/tests_i386/rawCalltesting.Rout
R version 4.0.5 (2021-03-31) -- "Shake and Throw"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: i386-w64-mingw32/i386 (32-bit)
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: 0x035d82a0>
> .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: 0x035d82a0>
> .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: 0x035d82a0>
> .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: 0x035d82a0>
> 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: 0x02de2638>
> .Call("R_bm_AddColumn",P)
<pointer: 0x02de2638>
> .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: 0x02de2638>
> .Call("R_bm_AddColumn",P)
<pointer: 0x02de2638>
> .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: 0x02de2638>
> 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: 0x02de07c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x02de07c0>
> .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: 0x02de07c0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x02de07c0>
> .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: 0x02de07c0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x02de07c0>
> .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: 0x02de07c0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x02de07c0>
> .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: 0x02de07c0>
> 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: 0x029244c0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x029244c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x029244c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x029244c0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile128c1bca5b3b" "BufferedMatrixFile128c48e66e8"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile128c1bca5b3b" "BufferedMatrixFile128c48e66e8"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x02f73310>
> .Call("R_bm_AddColumn",P)
<pointer: 0x02f73310>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x02f73310>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x02f73310>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x02f73310>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x02f73310>
> .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: 0x023b2e38>
> .Call("R_bm_AddColumn",P)
<pointer: 0x023b2e38>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x023b2e38>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x023b2e38>
> 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: 0x0385fe40>
> .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: 0x0385fe40>
> rm(P)
>
> proc.time()
user system elapsed
0.40 0.03 0.43
|
BufferedMatrix.Rcheck/tests_x64/rawCalltesting.Rout
R version 4.0.5 (2021-03-31) -- "Shake and Throw"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
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: 0x0000000007ce2708>
> .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: 0x0000000007ce2708>
> .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: 0x0000000007ce2708>
> .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: 0x0000000007ce2708>
> 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: 0x0000000007ea8890>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000007ea8890>
> .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: 0x0000000007ea8890>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000007ea8890>
> .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: 0x0000000007ea8890>
> 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: 0x0000000005cca6e8>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000005cca6e8>
> .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: 0x0000000005cca6e8>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x0000000005cca6e8>
> .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: 0x0000000005cca6e8>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x0000000005cca6e8>
> .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: 0x0000000005cca6e8>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x0000000005cca6e8>
> .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: 0x0000000005cca6e8>
> 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: 0x0000000005cea088>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x0000000005cea088>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000005cea088>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000005cea088>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1b802823fa8" "BufferedMatrixFile1b805e1a6ede"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1b802823fa8" "BufferedMatrixFile1b805e1a6ede"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000005ffbe30>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000005ffbe30>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x0000000005ffbe30>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x0000000005ffbe30>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x0000000005ffbe30>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x0000000005ffbe30>
> .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: 0x0000000005f3a570>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000005f3a570>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x0000000005f3a570>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x0000000005f3a570>
> 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: 0x0000000004f0baa0>
> .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: 0x0000000004f0baa0>
> rm(P)
>
> proc.time()
user system elapsed
0.48 0.07 0.54
|
|
BufferedMatrix.Rcheck/tests_i386/Rcodetesting.Rout
R version 4.0.5 (2021-03-31) -- "Shake and Throw"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: i386-w64-mingw32/i386 (32-bit)
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
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.32 0.04 0.36
|
BufferedMatrix.Rcheck/tests_x64/Rcodetesting.Rout
R version 4.0.5 (2021-03-31) -- "Shake and Throw"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
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
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.35 0.04 0.39
|