| Back to Multiple platform build/check report for BioC 3.14 |
|
This page was generated on 2022-04-13 12:06:16 -0400 (Wed, 13 Apr 2022).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 20.04.4 LTS) | x86_64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4324 |
| tokay2 | Windows Server 2012 R2 Standard | x64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4077 |
| machv2 | macOS 10.14.6 Mojave | x86_64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4137 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
|
To the developers/maintainers of the BufferedMatrix package: - Please allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See How and When does the builder pull? When will my changes propagate? for more information. - Make sure to use the following settings in order to reproduce any error or warning you see on this page. |
| Package 223/2083 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.58.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 20.04.4 LTS) / x86_64 | OK | OK | OK |  | ||||||||
| tokay2 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||||
| machv2 | macOS 10.14.6 Mojave / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| Package: BufferedMatrix |
| Version: 1.58.0 |
| Command: C:\Users\biocbuild\bbs-3.14-bioc\R\bin\R.exe CMD check --force-multiarch --install=check:BufferedMatrix.install-out.txt --library=C:\Users\biocbuild\bbs-3.14-bioc\R\library --no-vignettes --timings BufferedMatrix_1.58.0.tar.gz |
| StartedAt: 2022-04-12 16:40:35 -0400 (Tue, 12 Apr 2022) |
| EndedAt: 2022-04-12 16:41:52 -0400 (Tue, 12 Apr 2022) |
| EllapsedTime: 77.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### C:\Users\biocbuild\bbs-3.14-bioc\R\bin\R.exe CMD check --force-multiarch --install=check:BufferedMatrix.install-out.txt --library=C:\Users\biocbuild\bbs-3.14-bioc\R\library --no-vignettes --timings BufferedMatrix_1.58.0.tar.gz ### ############################################################################## ############################################################################## * using log directory 'C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck' * using R version 4.1.3 (2022-03-10) * 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 '1.58.0' * 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-3.14-bioc/R/library/BufferedMatrix/libs/i386/BufferedMatrix.dll': Found 'abort', possibly from 'abort' (C), 'runtime' (Fortran) File 'C:/Users/biocbuild/bbs-3.14-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-3.14-bioc/meat/BufferedMatrix.Rcheck/00check.log' for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### C:\cygwin\bin\curl.exe -O http://155.52.207.166/BBS/3.14/bioc/src/contrib/BufferedMatrix_1.58.0.tar.gz && rm -rf BufferedMatrix.buildbin-libdir && mkdir BufferedMatrix.buildbin-libdir && C:\Users\biocbuild\bbs-3.14-bioc\R\bin\R.exe CMD INSTALL --merge-multiarch --build --library=BufferedMatrix.buildbin-libdir BufferedMatrix_1.58.0.tar.gz && C:\Users\biocbuild\bbs-3.14-bioc\R\bin\R.exe CMD INSTALL BufferedMatrix_1.58.0.zip && rm BufferedMatrix_1.58.0.tar.gz BufferedMatrix_1.58.0.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
6 202k 6 13311 0 0 111k 0 0:00:01 --:--:-- 0:00:01 112k
100 202k 100 202k 0 0 348k 0 --:--:-- --:--:-- --:--:-- 348k
install for i386
* installing *source* package 'BufferedMatrix' ...
** using staged installation
** libs
"C:/rtools40/mingw32/bin/"gcc -I"C:/Users/BIOCBU~1/BBS-3~1.14-/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-3~1.14-/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-3~1.14-/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-3~1.14-/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-3~1.14-/R/bin/i386 -lR
installing to C:/Users/biocbuild/bbs-3.14-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-3~1.14-/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-3~1.14-/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-3~1.14-/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-3~1.14-/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-3~1.14-/R/bin/x64 -lR
installing to C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.buildbin-libdir/BufferedMatrix/libs/x64
** testing if installed package can be loaded
* MD5 sums
packaged installation of 'BufferedMatrix' as BufferedMatrix_1.58.0.zip
* DONE (BufferedMatrix)
* installing to library 'C:/Users/biocbuild/bbs-3.14-bioc/R/library'
package 'BufferedMatrix' successfully unpacked and MD5 sums checked
|
BufferedMatrix.Rcheck/tests_i386/c_code_level_tests.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 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
0.56 0.07 0.62
|
BufferedMatrix.Rcheck/tests_x64/c_code_level_tests.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 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
0.59 0.10 0.68
|
|
BufferedMatrix.Rcheck/tests_i386/objectTesting.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 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-3.14-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 436754 13.4 924427 28.3 646882 19.8
Vcells 499421 3.9 8388608 64.0 1648009 12.6
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Tue Apr 12 16:41:18 2022"
> 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] "Tue Apr 12 16:41:18 2022"
>
>
> 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: 0x036746a8>
>
>
>
> 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] "Tue Apr 12 16:41:20 2022"
> 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] "Tue Apr 12 16:41:21 2022"
>
> ColMode(tmp2)
<pointer: 0x036746a8>
>
>
>
> ### 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,] 99.6235117 -1.7734127 0.8561771 -2.18467166
[2,] 0.8316364 -0.2270611 -1.1410895 -0.05878097
[3,] -0.2756779 0.2978849 0.8821490 0.24691828
[4,] 1.0205611 0.8957574 0.1233232 -0.88032878
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.14-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,] 99.6235117 1.7734127 0.8561771 2.18467166
[2,] 0.8316364 0.2270611 1.1410895 0.05878097
[3,] 0.2756779 0.2978849 0.8821490 0.24691828
[4,] 1.0205611 0.8957574 0.1233232 0.88032878
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.14-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,] 9.9811578 1.3316954 0.9252984 1.4780635
[2,] 0.9119410 0.4765092 1.0682179 0.2424479
[3,] 0.5250503 0.5457883 0.9392279 0.4969087
[4,] 1.0102282 0.9464446 0.3511741 0.9382584
>
> 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-3.14-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,] 224.43509 40.09037 35.10916 41.96531
[2,] 34.95105 29.99215 36.82327 27.48326
[3,] 30.52618 30.75577 35.27443 30.21601
[4,] 36.12284 35.36020 28.63506 35.26291
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x030e0738>
> exp(tmp5)
<pointer: 0x030e0738>
> log(tmp5,2)
<pointer: 0x030e0738>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.1322
> Min(tmp5)
[1] 52.31468
> mean(tmp5)
[1] 72.85872
> Sum(tmp5)
[1] 14571.74
> Var(tmp5)
[1] 852.5929
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.35129 70.15346 70.40037 70.67958 72.48387 71.86857 70.35402 73.53351
[9] 69.16953 70.59304
> rowSums(tmp5)
[1] 1787.026 1403.069 1408.007 1413.592 1449.677 1437.371 1407.080 1470.670
[9] 1383.391 1411.861
> rowVars(tmp5)
[1] 7974.39707 74.61185 84.89680 46.06734 71.71644 65.00570
[7] 78.72879 82.89402 78.24630 39.84698
> rowSd(tmp5)
[1] 89.299480 8.637815 9.213946 6.787292 8.468556 8.062611 8.872925
[8] 9.104616 8.845694 6.312447
> rowMax(tmp5)
[1] 467.13223 86.14123 89.54421 82.03922 89.22222 84.36933 94.97404
[8] 87.88716 83.23082 85.69658
> rowMin(tmp5)
[1] 53.86372 55.27357 52.31468 59.03987 55.29435 57.64845 59.07106 57.80875
[9] 53.05612 59.79683
>
> colMeans(tmp5)
[1] 107.27741 69.51389 71.67480 68.70574 74.22314 69.58159 76.60678
[8] 68.73097 67.65901 70.27320 70.79721 72.66246 68.84766 66.85970
[15] 76.42492 72.69571 67.82584 71.53837 71.19540 74.08065
> colSums(tmp5)
[1] 1072.7741 695.1389 716.7480 687.0574 742.2314 695.8159 766.0678
[8] 687.3097 676.5901 702.7320 707.9721 726.6246 688.4766 668.5970
[15] 764.2492 726.9571 678.2584 715.3837 711.9540 740.8065
> colVars(tmp5)
[1] 16029.20714 66.70826 55.44576 125.72749 79.92515 110.87380
[7] 63.81051 14.11865 60.06617 36.52673 67.71418 68.91093
[13] 93.07388 79.03410 76.75128 89.84693 29.12163 28.06007
[19] 45.09256 84.72224
> colSd(tmp5)
[1] 126.606505 8.167512 7.446191 11.212827 8.940087 10.529663
[7] 7.988148 3.757479 7.750237 6.043735 8.228862 8.301261
[13] 9.647480 8.890112 8.760781 9.478762 5.396446 5.297175
[19] 6.715099 9.204468
> colMax(tmp5)
[1] 467.13223 83.44285 81.38929 87.34529 85.92632 87.88716 89.54421
[8] 77.04336 86.14123 79.48048 83.42476 87.33384 80.77594 83.27520
[15] 94.97404 84.36933 78.92233 78.04319 80.89840 89.22222
> colMin(tmp5)
[1] 53.05612 60.36897 59.60013 56.50402 57.07493 52.31468 63.87384 63.80197
[9] 57.64845 60.52338 60.29403 63.43830 55.27357 53.86372 65.94768 55.29435
[17] 59.38892 62.72993 60.34731 61.38873
>
>
> ### 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] NA 70.15346 70.40037 70.67958 72.48387 71.86857 70.35402 73.53351
[9] 69.16953 70.59304
> rowSums(tmp5)
[1] NA 1403.069 1408.007 1413.592 1449.677 1437.371 1407.080 1470.670
[9] 1383.391 1411.861
> rowVars(tmp5)
[1] 8401.92710 74.61185 84.89680 46.06734 71.71644 65.00570
[7] 78.72879 82.89402 78.24630 39.84698
> rowSd(tmp5)
[1] 91.662026 8.637815 9.213946 6.787292 8.468556 8.062611 8.872925
[8] 9.104616 8.845694 6.312447
> rowMax(tmp5)
[1] NA 86.14123 89.54421 82.03922 89.22222 84.36933 94.97404 87.88716
[9] 83.23082 85.69658
> rowMin(tmp5)
[1] NA 55.27357 52.31468 59.03987 55.29435 57.64845 59.07106 57.80875
[9] 53.05612 59.79683
>
> colMeans(tmp5)
[1] 107.27741 69.51389 NA 68.70574 74.22314 69.58159 76.60678
[8] 68.73097 67.65901 70.27320 70.79721 72.66246 68.84766 66.85970
[15] 76.42492 72.69571 67.82584 71.53837 71.19540 74.08065
> colSums(tmp5)
[1] 1072.7741 695.1389 NA 687.0574 742.2314 695.8159 766.0678
[8] 687.3097 676.5901 702.7320 707.9721 726.6246 688.4766 668.5970
[15] 764.2492 726.9571 678.2584 715.3837 711.9540 740.8065
> colVars(tmp5)
[1] 16029.20714 66.70826 NA 125.72749 79.92515 110.87380
[7] 63.81051 14.11865 60.06617 36.52673 67.71418 68.91093
[13] 93.07388 79.03410 76.75128 89.84693 29.12163 28.06007
[19] 45.09256 84.72224
> colSd(tmp5)
[1] 126.606505 8.167512 NA 11.212827 8.940087 10.529663
[7] 7.988148 3.757479 7.750237 6.043735 8.228862 8.301261
[13] 9.647480 8.890112 8.760781 9.478762 5.396446 5.297175
[19] 6.715099 9.204468
> colMax(tmp5)
[1] 467.13223 83.44285 NA 87.34529 85.92632 87.88716 89.54421
[8] 77.04336 86.14123 79.48048 83.42476 87.33384 80.77594 83.27520
[15] 94.97404 84.36933 78.92233 78.04319 80.89840 89.22222
> colMin(tmp5)
[1] 53.05612 60.36897 NA 56.50402 57.07493 52.31468 63.87384 63.80197
[9] 57.64845 60.52338 60.29403 63.43830 55.27357 53.86372 65.94768 55.29435
[17] 59.38892 62.72993 60.34731 61.38873
>
> Max(tmp5,na.rm=TRUE)
[1] 467.1322
> Min(tmp5,na.rm=TRUE)
[1] 52.31468
> mean(tmp5,na.rm=TRUE)
[1] 72.85764
> Sum(tmp5,na.rm=TRUE)
[1] 14498.67
> Var(tmp5,na.rm=TRUE)
[1] 856.8987
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.20793 70.15346 70.40037 70.67958 72.48387 71.86857 70.35402 73.53351
[9] 69.16953 70.59304
> rowSums(tmp5,na.rm=TRUE)
[1] 1713.951 1403.069 1408.007 1413.592 1449.677 1437.371 1407.080 1470.670
[9] 1383.391 1411.861
> rowVars(tmp5,na.rm=TRUE)
[1] 8401.92710 74.61185 84.89680 46.06734 71.71644 65.00570
[7] 78.72879 82.89402 78.24630 39.84698
> rowSd(tmp5,na.rm=TRUE)
[1] 91.662026 8.637815 9.213946 6.787292 8.468556 8.062611 8.872925
[8] 9.104616 8.845694 6.312447
> rowMax(tmp5,na.rm=TRUE)
[1] 467.13223 86.14123 89.54421 82.03922 89.22222 84.36933 94.97404
[8] 87.88716 83.23082 85.69658
> rowMin(tmp5,na.rm=TRUE)
[1] 53.86372 55.27357 52.31468 59.03987 55.29435 57.64845 59.07106 57.80875
[9] 53.05612 59.79683
>
> colMeans(tmp5,na.rm=TRUE)
[1] 107.27741 69.51389 71.51920 68.70574 74.22314 69.58159 76.60678
[8] 68.73097 67.65901 70.27320 70.79721 72.66246 68.84766 66.85970
[15] 76.42492 72.69571 67.82584 71.53837 71.19540 74.08065
> colSums(tmp5,na.rm=TRUE)
[1] 1072.7741 695.1389 643.6728 687.0574 742.2314 695.8159 766.0678
[8] 687.3097 676.5901 702.7320 707.9721 726.6246 688.4766 668.5970
[15] 764.2492 726.9571 678.2584 715.3837 711.9540 740.8065
> colVars(tmp5,na.rm=TRUE)
[1] 16029.20714 66.70826 62.10413 125.72749 79.92515 110.87380
[7] 63.81051 14.11865 60.06617 36.52673 67.71418 68.91093
[13] 93.07388 79.03410 76.75128 89.84693 29.12163 28.06007
[19] 45.09256 84.72224
> colSd(tmp5,na.rm=TRUE)
[1] 126.606505 8.167512 7.880617 11.212827 8.940087 10.529663
[7] 7.988148 3.757479 7.750237 6.043735 8.228862 8.301261
[13] 9.647480 8.890112 8.760781 9.478762 5.396446 5.297175
[19] 6.715099 9.204468
> colMax(tmp5,na.rm=TRUE)
[1] 467.13223 83.44285 81.38929 87.34529 85.92632 87.88716 89.54421
[8] 77.04336 86.14123 79.48048 83.42476 87.33384 80.77594 83.27520
[15] 94.97404 84.36933 78.92233 78.04319 80.89840 89.22222
> colMin(tmp5,na.rm=TRUE)
[1] 53.05612 60.36897 59.60013 56.50402 57.07493 52.31468 63.87384 63.80197
[9] 57.64845 60.52338 60.29403 63.43830 55.27357 53.86372 65.94768 55.29435
[17] 59.38892 62.72993 60.34731 61.38873
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 70.15346 70.40037 70.67958 72.48387 71.86857 70.35402 73.53351
[9] 69.16953 70.59304
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1403.069 1408.007 1413.592 1449.677 1437.371 1407.080 1470.670
[9] 1383.391 1411.861
> rowVars(tmp5,na.rm=TRUE)
[1] NA 74.61185 84.89680 46.06734 71.71644 65.00570 78.72879 82.89402
[9] 78.24630 39.84698
> rowSd(tmp5,na.rm=TRUE)
[1] NA 8.637815 9.213946 6.787292 8.468556 8.062611 8.872925 9.104616
[9] 8.845694 6.312447
> rowMax(tmp5,na.rm=TRUE)
[1] NA 86.14123 89.54421 82.03922 89.22222 84.36933 94.97404 87.88716
[9] 83.23082 85.69658
> rowMin(tmp5,na.rm=TRUE)
[1] NA 55.27357 52.31468 59.03987 55.29435 57.64845 59.07106 57.80875
[9] 53.05612 59.79683
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 67.29355 67.96622 NaN 66.63468 73.46172 70.22841 77.63487 69.03962
[9] 68.34542 71.35651 71.35966 73.44578 68.30633 68.30369 76.63737 73.18288
[17] 67.79045 72.38278 71.88799 73.74715
> colSums(tmp5,na.rm=TRUE)
[1] 605.6419 611.6960 0.0000 599.7121 661.1555 632.0557 698.7139 621.3566
[9] 615.1088 642.2086 642.2369 661.0120 614.7570 614.7332 689.7363 658.6460
[17] 610.1140 651.4450 646.9919 663.7243
> colVars(tmp5,na.rm=TRUE)
[1] 47.37307 48.10014 NA 93.18889 83.39347 120.02627 59.89589
[8] 14.81174 62.27386 27.88995 72.61953 70.62180 101.41146 65.45565
[15] 85.83743 98.40779 32.74774 23.54600 45.33280 94.06126
> colSd(tmp5,na.rm=TRUE)
[1] 6.882810 6.935426 NA 9.653439 9.132002 10.955650 7.739243
[8] 3.848602 7.891379 5.281093 8.521709 8.403678 10.070326 8.090467
[15] 9.264849 9.920070 5.722564 4.852422 6.732964 9.698518
> colMax(tmp5,na.rm=TRUE)
[1] 75.18497 81.35584 -Inf 79.64973 85.92632 87.88716 89.54421 77.04336
[9] 86.14123 79.48048 83.42476 87.33384 80.77594 83.27520 94.97404 84.36933
[17] 78.92233 78.04319 80.89840 89.22222
> colMin(tmp5,na.rm=TRUE)
[1] 53.05612 60.36897 Inf 56.50402 57.07493 52.31468 63.87384 63.80197
[9] 57.64845 62.46630 60.29403 63.43830 55.27357 59.03987 65.94768 55.29435
[17] 59.38892 62.72993 60.34731 61.38873
>
>
>
>
> 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] 329.1829 209.4597 224.5264 352.8215 264.3569 294.2205 202.8104 178.2544
[9] 185.5814 122.8890
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 329.1829 209.4597 224.5264 352.8215 264.3569 294.2205 202.8104 178.2544
[9] 185.5814 122.8890
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 1.136868e-13 0.000000e+00 -2.842171e-13 -2.842171e-14 5.684342e-14
[6] 1.421085e-14 -5.684342e-14 -1.421085e-13 -1.136868e-13 -1.136868e-13
[11] 5.684342e-14 0.000000e+00 2.842171e-14 -5.684342e-14 1.421085e-14
[16] 5.684342e-14 5.684342e-14 -2.842171e-14 -2.842171e-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)
+ }
5 4
9 19
1 7
7 1
4 2
3 9
2 19
7 1
4 10
6 10
3 17
9 16
5 18
4 7
2 14
5 2
6 12
8 14
4 9
3 13
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.186224
> Min(tmp)
[1] -2.343475
> mean(tmp)
[1] 0.03798216
> Sum(tmp)
[1] 3.798216
> Var(tmp)
[1] 1.097505
>
> rowMeans(tmp)
[1] 0.03798216
> rowSums(tmp)
[1] 3.798216
> rowVars(tmp)
[1] 1.097505
> rowSd(tmp)
[1] 1.047619
> rowMax(tmp)
[1] 2.186224
> rowMin(tmp)
[1] -2.343475
>
> colMeans(tmp)
[1] 1.47645820 0.34141214 -1.26808763 1.39681680 1.12744502 -0.70360037
[7] 1.58970918 2.14547151 -0.50102482 -1.50162338 1.96141232 0.54844315
[13] -0.55995115 -0.22262678 1.89340374 0.83294616 -1.47626642 -0.19525457
[19] -0.78473676 0.32453177 -0.05764606 -0.82365547 0.24499220 -1.22627213
[25] -0.23638302 -0.71369009 0.09441837 -0.89358299 0.08707250 -1.67731141
[31] -1.09910346 2.18622433 0.22140355 -0.99312465 0.17543793 0.51338926
[37] 0.81807283 0.85751307 -0.55357280 0.31230794 1.35859910 1.69331699
[43] -1.20230948 -0.62354545 -1.00347113 -1.09292524 0.80475150 -0.46690058
[49] -1.01343999 0.31401589 -0.03425370 -0.88873367 1.46385337 -1.02127528
[55] 1.62684694 -0.05660135 1.24211407 -0.14683739 0.89435053 0.55673753
[61] -1.67507274 -1.21139490 0.79079616 -0.75328509 -2.34347491 0.44433303
[67] 1.93057115 -0.40692137 -0.23475039 -1.98718846 -0.36136304 1.67808923
[73] -0.49473446 -0.03916104 0.82341573 0.63591172 -0.75109216 1.45998854
[79] 0.68874003 -0.13163983 1.39168846 -0.16028740 0.26131037 0.11535128
[85] 1.25212528 1.01961378 -2.09834821 0.22656130 0.76002687 0.45048337
[91] -1.22760458 -1.02221929 0.22724828 -0.90459847 -0.79184355 -0.06150404
[97] -1.15966218 -0.50910821 0.53916986 1.36238537
> colSums(tmp)
[1] 1.47645820 0.34141214 -1.26808763 1.39681680 1.12744502 -0.70360037
[7] 1.58970918 2.14547151 -0.50102482 -1.50162338 1.96141232 0.54844315
[13] -0.55995115 -0.22262678 1.89340374 0.83294616 -1.47626642 -0.19525457
[19] -0.78473676 0.32453177 -0.05764606 -0.82365547 0.24499220 -1.22627213
[25] -0.23638302 -0.71369009 0.09441837 -0.89358299 0.08707250 -1.67731141
[31] -1.09910346 2.18622433 0.22140355 -0.99312465 0.17543793 0.51338926
[37] 0.81807283 0.85751307 -0.55357280 0.31230794 1.35859910 1.69331699
[43] -1.20230948 -0.62354545 -1.00347113 -1.09292524 0.80475150 -0.46690058
[49] -1.01343999 0.31401589 -0.03425370 -0.88873367 1.46385337 -1.02127528
[55] 1.62684694 -0.05660135 1.24211407 -0.14683739 0.89435053 0.55673753
[61] -1.67507274 -1.21139490 0.79079616 -0.75328509 -2.34347491 0.44433303
[67] 1.93057115 -0.40692137 -0.23475039 -1.98718846 -0.36136304 1.67808923
[73] -0.49473446 -0.03916104 0.82341573 0.63591172 -0.75109216 1.45998854
[79] 0.68874003 -0.13163983 1.39168846 -0.16028740 0.26131037 0.11535128
[85] 1.25212528 1.01961378 -2.09834821 0.22656130 0.76002687 0.45048337
[91] -1.22760458 -1.02221929 0.22724828 -0.90459847 -0.79184355 -0.06150404
[97] -1.15966218 -0.50910821 0.53916986 1.36238537
> 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] 1.47645820 0.34141214 -1.26808763 1.39681680 1.12744502 -0.70360037
[7] 1.58970918 2.14547151 -0.50102482 -1.50162338 1.96141232 0.54844315
[13] -0.55995115 -0.22262678 1.89340374 0.83294616 -1.47626642 -0.19525457
[19] -0.78473676 0.32453177 -0.05764606 -0.82365547 0.24499220 -1.22627213
[25] -0.23638302 -0.71369009 0.09441837 -0.89358299 0.08707250 -1.67731141
[31] -1.09910346 2.18622433 0.22140355 -0.99312465 0.17543793 0.51338926
[37] 0.81807283 0.85751307 -0.55357280 0.31230794 1.35859910 1.69331699
[43] -1.20230948 -0.62354545 -1.00347113 -1.09292524 0.80475150 -0.46690058
[49] -1.01343999 0.31401589 -0.03425370 -0.88873367 1.46385337 -1.02127528
[55] 1.62684694 -0.05660135 1.24211407 -0.14683739 0.89435053 0.55673753
[61] -1.67507274 -1.21139490 0.79079616 -0.75328509 -2.34347491 0.44433303
[67] 1.93057115 -0.40692137 -0.23475039 -1.98718846 -0.36136304 1.67808923
[73] -0.49473446 -0.03916104 0.82341573 0.63591172 -0.75109216 1.45998854
[79] 0.68874003 -0.13163983 1.39168846 -0.16028740 0.26131037 0.11535128
[85] 1.25212528 1.01961378 -2.09834821 0.22656130 0.76002687 0.45048337
[91] -1.22760458 -1.02221929 0.22724828 -0.90459847 -0.79184355 -0.06150404
[97] -1.15966218 -0.50910821 0.53916986 1.36238537
> colMin(tmp)
[1] 1.47645820 0.34141214 -1.26808763 1.39681680 1.12744502 -0.70360037
[7] 1.58970918 2.14547151 -0.50102482 -1.50162338 1.96141232 0.54844315
[13] -0.55995115 -0.22262678 1.89340374 0.83294616 -1.47626642 -0.19525457
[19] -0.78473676 0.32453177 -0.05764606 -0.82365547 0.24499220 -1.22627213
[25] -0.23638302 -0.71369009 0.09441837 -0.89358299 0.08707250 -1.67731141
[31] -1.09910346 2.18622433 0.22140355 -0.99312465 0.17543793 0.51338926
[37] 0.81807283 0.85751307 -0.55357280 0.31230794 1.35859910 1.69331699
[43] -1.20230948 -0.62354545 -1.00347113 -1.09292524 0.80475150 -0.46690058
[49] -1.01343999 0.31401589 -0.03425370 -0.88873367 1.46385337 -1.02127528
[55] 1.62684694 -0.05660135 1.24211407 -0.14683739 0.89435053 0.55673753
[61] -1.67507274 -1.21139490 0.79079616 -0.75328509 -2.34347491 0.44433303
[67] 1.93057115 -0.40692137 -0.23475039 -1.98718846 -0.36136304 1.67808923
[73] -0.49473446 -0.03916104 0.82341573 0.63591172 -0.75109216 1.45998854
[79] 0.68874003 -0.13163983 1.39168846 -0.16028740 0.26131037 0.11535128
[85] 1.25212528 1.01961378 -2.09834821 0.22656130 0.76002687 0.45048337
[91] -1.22760458 -1.02221929 0.22724828 -0.90459847 -0.79184355 -0.06150404
[97] -1.15966218 -0.50910821 0.53916986 1.36238537
> colMedians(tmp)
[1] 1.47645820 0.34141214 -1.26808763 1.39681680 1.12744502 -0.70360037
[7] 1.58970918 2.14547151 -0.50102482 -1.50162338 1.96141232 0.54844315
[13] -0.55995115 -0.22262678 1.89340374 0.83294616 -1.47626642 -0.19525457
[19] -0.78473676 0.32453177 -0.05764606 -0.82365547 0.24499220 -1.22627213
[25] -0.23638302 -0.71369009 0.09441837 -0.89358299 0.08707250 -1.67731141
[31] -1.09910346 2.18622433 0.22140355 -0.99312465 0.17543793 0.51338926
[37] 0.81807283 0.85751307 -0.55357280 0.31230794 1.35859910 1.69331699
[43] -1.20230948 -0.62354545 -1.00347113 -1.09292524 0.80475150 -0.46690058
[49] -1.01343999 0.31401589 -0.03425370 -0.88873367 1.46385337 -1.02127528
[55] 1.62684694 -0.05660135 1.24211407 -0.14683739 0.89435053 0.55673753
[61] -1.67507274 -1.21139490 0.79079616 -0.75328509 -2.34347491 0.44433303
[67] 1.93057115 -0.40692137 -0.23475039 -1.98718846 -0.36136304 1.67808923
[73] -0.49473446 -0.03916104 0.82341573 0.63591172 -0.75109216 1.45998854
[79] 0.68874003 -0.13163983 1.39168846 -0.16028740 0.26131037 0.11535128
[85] 1.25212528 1.01961378 -2.09834821 0.22656130 0.76002687 0.45048337
[91] -1.22760458 -1.02221929 0.22724828 -0.90459847 -0.79184355 -0.06150404
[97] -1.15966218 -0.50910821 0.53916986 1.36238537
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.476458 0.3414121 -1.268088 1.396817 1.127445 -0.7036004 1.589709
[2,] 1.476458 0.3414121 -1.268088 1.396817 1.127445 -0.7036004 1.589709
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 2.145472 -0.5010248 -1.501623 1.961412 0.5484432 -0.5599512 -0.2226268
[2,] 2.145472 -0.5010248 -1.501623 1.961412 0.5484432 -0.5599512 -0.2226268
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.893404 0.8329462 -1.476266 -0.1952546 -0.7847368 0.3245318 -0.05764606
[2,] 1.893404 0.8329462 -1.476266 -0.1952546 -0.7847368 0.3245318 -0.05764606
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.8236555 0.2449922 -1.226272 -0.236383 -0.7136901 0.09441837 -0.893583
[2,] -0.8236555 0.2449922 -1.226272 -0.236383 -0.7136901 0.09441837 -0.893583
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.0870725 -1.677311 -1.099103 2.186224 0.2214035 -0.9931246 0.1754379
[2,] 0.0870725 -1.677311 -1.099103 2.186224 0.2214035 -0.9931246 0.1754379
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.5133893 0.8180728 0.8575131 -0.5535728 0.3123079 1.358599 1.693317
[2,] 0.5133893 0.8180728 0.8575131 -0.5535728 0.3123079 1.358599 1.693317
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.202309 -0.6235455 -1.003471 -1.092925 0.8047515 -0.4669006 -1.01344
[2,] -1.202309 -0.6235455 -1.003471 -1.092925 0.8047515 -0.4669006 -1.01344
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.3140159 -0.0342537 -0.8887337 1.463853 -1.021275 1.626847 -0.05660135
[2,] 0.3140159 -0.0342537 -0.8887337 1.463853 -1.021275 1.626847 -0.05660135
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 1.242114 -0.1468374 0.8943505 0.5567375 -1.675073 -1.211395 0.7907962
[2,] 1.242114 -0.1468374 0.8943505 0.5567375 -1.675073 -1.211395 0.7907962
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.7532851 -2.343475 0.444333 1.930571 -0.4069214 -0.2347504 -1.987188
[2,] -0.7532851 -2.343475 0.444333 1.930571 -0.4069214 -0.2347504 -1.987188
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.361363 1.678089 -0.4947345 -0.03916104 0.8234157 0.6359117 -0.7510922
[2,] -0.361363 1.678089 -0.4947345 -0.03916104 0.8234157 0.6359117 -0.7510922
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.459989 0.68874 -0.1316398 1.391688 -0.1602874 0.2613104 0.1153513
[2,] 1.459989 0.68874 -0.1316398 1.391688 -0.1602874 0.2613104 0.1153513
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 1.252125 1.019614 -2.098348 0.2265613 0.7600269 0.4504834 -1.227605
[2,] 1.252125 1.019614 -2.098348 0.2265613 0.7600269 0.4504834 -1.227605
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.022219 0.2272483 -0.9045985 -0.7918435 -0.06150404 -1.159662 -0.5091082
[2,] -1.022219 0.2272483 -0.9045985 -0.7918435 -0.06150404 -1.159662 -0.5091082
[,99] [,100]
[1,] 0.5391699 1.362385
[2,] 0.5391699 1.362385
>
>
> Max(tmp2)
[1] 2.322982
> Min(tmp2)
[1] -2.704695
> mean(tmp2)
[1] -0.01748343
> Sum(tmp2)
[1] -1.748343
> Var(tmp2)
[1] 0.7978441
>
> rowMeans(tmp2)
[1] 0.16094548 0.74633902 -0.59048513 1.87191167 0.57330429 -0.92263523
[7] -0.87992147 -0.57123278 -0.22368962 -1.72606420 0.49738390 -0.87191410
[13] 0.14297398 -0.18898374 0.25394765 -0.69157398 0.52326540 -0.61972592
[19] -0.20516813 1.38795287 0.80720095 -0.38132111 0.53727945 -0.05241017
[25] 1.69050316 -0.12798031 0.93450137 0.78365638 -0.87429729 0.85986591
[31] -0.12165996 1.07077646 -1.06107320 -0.50942521 0.11248938 -0.11643163
[37] -0.26545233 -0.58187586 0.22758876 0.06459201 0.46830716 0.21460867
[43] 0.91622818 -0.52472506 0.97546286 0.34420641 -0.38424454 0.69438152
[49] 0.01068779 0.77725692 -1.59818471 -0.50894792 -1.28899574 -0.64207076
[55] -1.83534863 1.40952666 -0.23774175 -0.97306640 -0.59728924 -1.73676485
[61] 0.08164728 1.29702870 0.52080885 1.25865010 2.32298247 -0.23051557
[67] 0.14726598 0.89794517 0.23352929 0.07907697 -0.54356474 -1.19502073
[73] 0.67810759 0.02514662 0.62001252 1.14586545 -1.51697654 -1.10685419
[79] -0.89703370 0.03899681 -0.94452813 0.13720738 0.94342651 -0.09173537
[85] 0.01193865 -1.86115300 -0.43668274 0.62078862 -0.11120774 1.19199939
[91] -0.21067559 1.08611286 0.07842183 0.59628427 -2.70469488 -1.09278643
[97] -0.43415253 0.23321277 0.82479980 -0.58846023
> rowSums(tmp2)
[1] 0.16094548 0.74633902 -0.59048513 1.87191167 0.57330429 -0.92263523
[7] -0.87992147 -0.57123278 -0.22368962 -1.72606420 0.49738390 -0.87191410
[13] 0.14297398 -0.18898374 0.25394765 -0.69157398 0.52326540 -0.61972592
[19] -0.20516813 1.38795287 0.80720095 -0.38132111 0.53727945 -0.05241017
[25] 1.69050316 -0.12798031 0.93450137 0.78365638 -0.87429729 0.85986591
[31] -0.12165996 1.07077646 -1.06107320 -0.50942521 0.11248938 -0.11643163
[37] -0.26545233 -0.58187586 0.22758876 0.06459201 0.46830716 0.21460867
[43] 0.91622818 -0.52472506 0.97546286 0.34420641 -0.38424454 0.69438152
[49] 0.01068779 0.77725692 -1.59818471 -0.50894792 -1.28899574 -0.64207076
[55] -1.83534863 1.40952666 -0.23774175 -0.97306640 -0.59728924 -1.73676485
[61] 0.08164728 1.29702870 0.52080885 1.25865010 2.32298247 -0.23051557
[67] 0.14726598 0.89794517 0.23352929 0.07907697 -0.54356474 -1.19502073
[73] 0.67810759 0.02514662 0.62001252 1.14586545 -1.51697654 -1.10685419
[79] -0.89703370 0.03899681 -0.94452813 0.13720738 0.94342651 -0.09173537
[85] 0.01193865 -1.86115300 -0.43668274 0.62078862 -0.11120774 1.19199939
[91] -0.21067559 1.08611286 0.07842183 0.59628427 -2.70469488 -1.09278643
[97] -0.43415253 0.23321277 0.82479980 -0.58846023
> 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] 0.16094548 0.74633902 -0.59048513 1.87191167 0.57330429 -0.92263523
[7] -0.87992147 -0.57123278 -0.22368962 -1.72606420 0.49738390 -0.87191410
[13] 0.14297398 -0.18898374 0.25394765 -0.69157398 0.52326540 -0.61972592
[19] -0.20516813 1.38795287 0.80720095 -0.38132111 0.53727945 -0.05241017
[25] 1.69050316 -0.12798031 0.93450137 0.78365638 -0.87429729 0.85986591
[31] -0.12165996 1.07077646 -1.06107320 -0.50942521 0.11248938 -0.11643163
[37] -0.26545233 -0.58187586 0.22758876 0.06459201 0.46830716 0.21460867
[43] 0.91622818 -0.52472506 0.97546286 0.34420641 -0.38424454 0.69438152
[49] 0.01068779 0.77725692 -1.59818471 -0.50894792 -1.28899574 -0.64207076
[55] -1.83534863 1.40952666 -0.23774175 -0.97306640 -0.59728924 -1.73676485
[61] 0.08164728 1.29702870 0.52080885 1.25865010 2.32298247 -0.23051557
[67] 0.14726598 0.89794517 0.23352929 0.07907697 -0.54356474 -1.19502073
[73] 0.67810759 0.02514662 0.62001252 1.14586545 -1.51697654 -1.10685419
[79] -0.89703370 0.03899681 -0.94452813 0.13720738 0.94342651 -0.09173537
[85] 0.01193865 -1.86115300 -0.43668274 0.62078862 -0.11120774 1.19199939
[91] -0.21067559 1.08611286 0.07842183 0.59628427 -2.70469488 -1.09278643
[97] -0.43415253 0.23321277 0.82479980 -0.58846023
> rowMin(tmp2)
[1] 0.16094548 0.74633902 -0.59048513 1.87191167 0.57330429 -0.92263523
[7] -0.87992147 -0.57123278 -0.22368962 -1.72606420 0.49738390 -0.87191410
[13] 0.14297398 -0.18898374 0.25394765 -0.69157398 0.52326540 -0.61972592
[19] -0.20516813 1.38795287 0.80720095 -0.38132111 0.53727945 -0.05241017
[25] 1.69050316 -0.12798031 0.93450137 0.78365638 -0.87429729 0.85986591
[31] -0.12165996 1.07077646 -1.06107320 -0.50942521 0.11248938 -0.11643163
[37] -0.26545233 -0.58187586 0.22758876 0.06459201 0.46830716 0.21460867
[43] 0.91622818 -0.52472506 0.97546286 0.34420641 -0.38424454 0.69438152
[49] 0.01068779 0.77725692 -1.59818471 -0.50894792 -1.28899574 -0.64207076
[55] -1.83534863 1.40952666 -0.23774175 -0.97306640 -0.59728924 -1.73676485
[61] 0.08164728 1.29702870 0.52080885 1.25865010 2.32298247 -0.23051557
[67] 0.14726598 0.89794517 0.23352929 0.07907697 -0.54356474 -1.19502073
[73] 0.67810759 0.02514662 0.62001252 1.14586545 -1.51697654 -1.10685419
[79] -0.89703370 0.03899681 -0.94452813 0.13720738 0.94342651 -0.09173537
[85] 0.01193865 -1.86115300 -0.43668274 0.62078862 -0.11120774 1.19199939
[91] -0.21067559 1.08611286 0.07842183 0.59628427 -2.70469488 -1.09278643
[97] -0.43415253 0.23321277 0.82479980 -0.58846023
>
> colMeans(tmp2)
[1] -0.01748343
> colSums(tmp2)
[1] -1.748343
> colVars(tmp2)
[1] 0.7978441
> colSd(tmp2)
[1] 0.8932212
> colMax(tmp2)
[1] 2.322982
> colMin(tmp2)
[1] -2.704695
> colMedians(tmp2)
[1] 0.01854264
> colRanges(tmp2)
[,1]
[1,] -2.704695
[2,] 2.322982
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.2036185 -2.9051500 3.1846348 2.9028797 -3.0942672 0.5429374
[7] 3.4942109 -0.4927915 3.1068220 -1.6152182
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.1427319
[2,] -0.8707015
[3,] 0.4002428
[4,] 0.8241730
[5,] 0.9005954
>
> rowApply(tmp,sum)
[1] -5.7987265 3.6256069 1.3908545 5.3276203 -1.6910207 3.1582242
[7] -0.7672006 -2.4008030 0.4487652 0.6271189
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 9 8 4 3 6 2 8 5 1
[2,] 9 5 6 1 1 4 5 5 1 8
[3,] 6 10 2 5 8 3 4 9 6 9
[4,] 2 2 10 6 10 5 7 10 4 3
[5,] 3 6 1 3 9 1 3 2 9 10
[6,] 4 3 7 7 7 7 8 1 8 5
[7,] 8 8 5 10 5 9 9 7 2 6
[8,] 5 7 4 8 2 10 6 3 3 2
[9,] 10 4 9 9 4 8 1 6 7 7
[10,] 7 1 3 2 6 2 10 4 10 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.7333906 -0.7187850 -3.7048727 -1.7522942 -0.7489923 -1.0831639
[7] -2.5380966 -0.9282080 2.2992085 -2.8425508 -0.8638862 5.1992271
[13] -3.3146698 -1.1079211 -1.0066007 5.4452454 -3.1185116 -2.0860594
[19] 0.1706397 0.4368673
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.5602582
[2,] -0.2759425
[3,] -0.2449072
[4,] 0.3961214
[5,] 1.4183772
>
> rowApply(tmp,sum)
[1] 0.6618533 -2.6040477 -9.6085057 -5.8546182 5.8752844
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 7 10 13 20 11
[2,] 18 3 3 10 10
[3,] 5 12 9 8 2
[4,] 19 9 7 2 13
[5,] 13 8 11 7 12
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.5602582 1.28680346 -0.9645792 1.2883300 0.2495346 -1.4309427
[2,] -0.2449072 -0.81371356 -0.1541456 -0.2536979 -0.3061966 -0.3421048
[3,] -0.2759425 -1.48524987 -0.7361854 -0.8157515 -0.5946121 0.6969905
[4,] 1.4183772 0.04646916 -0.4824419 -2.6821219 -0.6445629 0.1169903
[5,] 0.3961214 0.24690583 -1.3675206 0.7109470 0.5468447 -0.1240973
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.2126493 1.21784761 1.2840400 -1.13871833 -1.01464121 -0.3048616
[2,] 0.9597158 -0.01230732 0.5024105 -0.77961609 0.73031695 1.3915872
[3,] -1.0217446 0.04853130 -0.8248135 -0.05474621 0.03864026 2.5033129
[4,] -1.1262207 -1.25926689 0.5755528 -2.79623915 -0.82872077 0.7550370
[5,] -1.5624963 -0.92301271 0.7620186 1.92676898 0.21051852 0.8541517
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.11792110 0.3037116 -0.2899934 2.19502160 -0.2911051 -0.85058843
[2,] -1.92855059 -0.1832143 0.3283231 0.04693966 0.9556668 -0.60553016
[3,] -0.17298001 -1.3926761 -2.7392155 0.84658179 -1.7673466 -0.79369291
[4,] -0.04471272 0.9515920 0.5967817 0.58630921 -1.6548718 0.17834035
[5,] -0.05050542 -0.7873342 1.0975034 1.77039317 -0.3608549 -0.01458825
[,19] [,20]
[1,] -0.0996640 0.6871884
[2,] -0.7652816 -1.1297420
[3,] -0.6946369 -0.3729689
[4,] 0.1572503 0.2818408
[5,] 1.5729719 0.9705489
>
>
> 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-3.14-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-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_i386
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 639 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.14-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-3.14-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 1.134538 -0.5923307 -0.1816431 0.2660417 -0.7465161 0.3422961 -1.311357
col8 col9 col10 col11 col12 col13 col14
row1 0.3058668 0.1645938 0.1579187 0.2771277 2.093472 1.054771 1.440773
col15 col16 col17 col18 col19 col20
row1 -0.762363 0.4850025 1.055431 -0.6116995 1.218865 -1.690987
> tmp[,"col10"]
col10
row1 0.1579187
row2 -0.1626779
row3 -0.9612716
row4 0.8071988
row5 1.9084120
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.134538 -0.5923307 -0.1816431 0.2660417 -0.7465161 0.3422961 -1.311357
row5 -1.069517 -0.1139450 0.9193851 0.7044172 1.0584400 0.8462504 1.115475
col8 col9 col10 col11 col12 col13 col14
row1 0.3058668 0.1645938 0.1579187 0.2771277 2.0934720 1.054771 1.4407727
row5 -0.2077867 0.4051476 1.9084120 0.1423689 0.3589205 -1.133217 0.9956742
col15 col16 col17 col18 col19 col20
row1 -0.7623630 0.4850025 1.0554313 -0.6116995 1.2188649 -1.6909865
row5 0.6975455 1.4285230 0.1572232 0.8389884 -0.3208874 -0.2540058
> tmp[,c("col6","col20")]
col6 col20
row1 0.3422961 -1.6909865
row2 0.7166167 0.9138544
row3 -1.4504045 -0.9674546
row4 -0.5162199 0.2687614
row5 0.8462504 -0.2540058
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.3422961 -1.6909865
row5 0.8462504 -0.2540058
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.39911 49.78605 49.9882 49.90703 52.76113 106.4639 49.30601 49.596
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.12047 51.56138 48.73793 49.67474 51.16177 48.29462 49.98027 51.50957
col17 col18 col19 col20
row1 49.03118 49.20621 50.25384 104.0184
> tmp[,"col10"]
col10
row1 51.56138
row2 30.02598
row3 30.97107
row4 31.08735
row5 49.70902
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.39911 49.78605 49.9882 49.90703 52.76113 106.4639 49.30601 49.59600
row5 50.18819 49.48850 47.8489 50.36738 48.70986 105.5893 52.16831 50.40286
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.12047 51.56138 48.73793 49.67474 51.16177 48.29462 49.98027 51.50957
row5 51.69057 49.70902 50.59590 50.83756 50.04665 49.52670 51.00166 50.35956
col17 col18 col19 col20
row1 49.03118 49.20621 50.25384 104.0184
row5 47.33528 49.70934 51.21785 105.4037
> tmp[,c("col6","col20")]
col6 col20
row1 106.46386 104.01837
row2 74.51352 77.04080
row3 75.87161 74.72711
row4 74.72633 74.51125
row5 105.58934 105.40370
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.4639 104.0184
row5 105.5893 105.4037
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.4639 104.0184
row5 105.5893 105.4037
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 2.95972969
[2,] 1.96803887
[3,] 0.03591941
[4,] 0.44030791
[5,] -0.09960218
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.6413004 0.5686564
[2,] 0.6255331 2.3430337
[3,] 1.4815334 -0.8997047
[4,] -0.6489051 -0.7315041
[5,] 0.6546100 1.0103246
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.10171616 -0.7310872
[2,] 0.09387949 -0.7603363
[3,] 0.70618462 -1.1576324
[4,] 0.73954423 -0.7697644
[5,] 1.33642022 -2.3034851
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.101716
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.10171616
[2,] 0.09387949
>
>
>
> 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 -1.739846 0.3208581 0.9425562 -0.1764555 0.8308484 -1.3145175
row1 2.840774 -0.4700222 -0.5326757 -0.5871983 -1.1214914 -0.9756424
[,7] [,8] [,9] [,10] [,11] [,12]
row3 0.3069430 0.3300835 -0.5043995 0.02102789 -0.5176034 -0.4420901
row1 -0.8330745 0.8484105 1.1570301 -0.71763450 -0.9621175 0.2272178
[,13] [,14] [,15] [,16] [,17] [,18]
row3 0.216183 2.0264127 -0.4377050 -1.1568078 -1.598101268 0.5488106
row1 -1.025969 -0.5012767 0.4078797 0.4392477 -0.005490846 0.5075002
[,19] [,20]
row3 0.2537844 -0.1617679
row1 0.4864908 2.0817326
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.182581 0.1312161 0.7415275 0.3293227 1.127574 -0.8786396 1.262209
[,8] [,9] [,10]
row2 -1.255076 0.0356578 -0.8095076
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.7649589 0.916942 -0.4205701 0.9677418 -0.3911871 -1.556802 -1.707215
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.5629331 -0.9544669 0.8544623 0.4964537 0.3503735 -2.445956 -0.1892284
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.04328235 -0.7964785 -0.2449463 0.2821954 0.6454814 1.001917
>
>
> 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: 0x02fe8318>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM196c2282f2d"
[2] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM196c69bb3fe7"
[3] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM196c761da6"
[4] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM196c7c8a4cab"
[5] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM196c445682a"
[6] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM196ce1d60f2"
[7] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM196c61797a7a"
[8] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM196c5938512a"
[9] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM196c60fe2c1b"
[10] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM196c6a072da1"
[11] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM196c7b7f615a"
[12] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM196c62b25ba2"
[13] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM196c69877d8e"
[14] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM196c6e3149e1"
[15] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM196c4cf25a9d"
>
>
> ### 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: 0x028b2080>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x028b2080>
Warning message:
In dir.create(new.directory) :
'C:\Users\biocbuild\bbs-3.14-bioc\meat\BufferedMatrix.Rcheck\tests_i386' already exists
>
>
> RowMode(tmp)
<pointer: 0x028b2080>
> rowMedians(tmp)
[1] 0.3437909062 0.3030680057 -0.3043744997 -0.1156366781 -0.3504236806
[6] 0.8449162071 -0.0784292649 0.1175367339 0.7914011047 0.5246282356
[11] -0.3870653815 -0.0131423457 -0.2132405206 0.0792983911 -0.1964427161
[16] -0.5953809064 -0.1398255810 -0.2188208031 -0.3890852958 -0.2114769821
[21] -0.0827569036 -0.0001824704 0.0691284792 -0.0677531279 0.0607433224
[26] 0.2128002285 -0.3094226557 0.3816033273 -0.0095893805 -0.3313524299
[31] 0.0549361518 -0.0168124318 -0.1782534162 -0.1660614255 -0.1826248269
[36] -0.1889482321 -0.2837641996 -0.6967147508 -0.1382300796 -0.4908455649
[41] -0.1970148396 0.2522170004 -0.2548459016 -0.3760555338 -0.3836710115
[46] 0.1526275623 -0.4563202647 0.0197236693 0.4415531745 0.3852741220
[51] 0.2000720143 0.1129828211 0.0750092142 -0.0250287515 0.3415283119
[56] -0.3421793293 -0.0547335324 0.2069936075 -0.1209896916 -0.3348647118
[61] 0.0367180336 -0.4141545514 0.2825178690 -0.2397539826 0.1650012400
[66] -0.3228397931 0.2768065212 0.1218283542 -0.3046060753 -0.2976789777
[71] -0.4185757462 -0.1623580030 -0.0795783440 -0.1702321664 0.3856942070
[76] -0.1163750552 -0.2962271435 -0.2427666247 0.0029916061 0.2144480808
[81] -0.0531736379 -0.2949240285 0.0908055288 -0.0310206311 -0.4034962827
[86] -0.0466343897 -0.6355671834 -0.1354741066 0.3962218198 -0.2326115332
[91] 0.1616096638 -0.0541635304 0.0733106844 -0.2676024496 0.4399264521
[96] 0.1657579613 0.1894066632 0.8441469978 0.1782181559 0.0740173805
[101] 0.6817414409 0.1105701679 -0.1518625577 -0.2414645203 0.1286259677
[106] 0.5174954167 -0.4469595125 -0.1742368548 0.3546472486 0.2370492348
[111] -0.2086305978 -0.0358134734 -0.1128620228 0.6396314236 0.1155357310
[116] 0.5445152256 0.2635932962 -0.0364971071 -0.7538403422 -0.0626212010
[121] 0.6818564669 -0.1818967602 -0.6346489079 -0.1631745062 -0.3508387821
[126] 0.1984349912 0.1757159504 0.4392694300 -0.5036599317 -0.0192105572
[131] 0.0548187940 0.3156259784 0.2001971131 0.4077110589 -0.2737548591
[136] 0.2462737839 -0.3091499437 0.2229736490 0.0419779126 0.4321359626
[141] -0.1284460375 0.6376803444 -0.2237203695 -0.7664240979 0.4275648384
[146] 0.0322015916 0.0797915683 -0.1606352327 -0.1236167499 -0.1320036179
[151] 0.2786045457 -0.0896985051 0.1474647829 0.0327733969 0.5429871760
[156] 0.2747921511 -0.3707394062 -0.1582723021 0.2884843899 0.2775657767
[161] 0.4984147228 0.0610237903 -0.6234545837 -0.1451650566 0.4251190384
[166] -0.3763008229 0.5593602355 -0.0518139031 0.6699684632 -0.1867859399
[171] 0.0241341516 0.4286534354 -0.4869611482 0.2778669074 -0.2952404771
[176] 0.4802133299 -0.1195728908 0.1730603232 -0.0224111066 -0.0064419592
[181] -0.0484180356 -0.3815127384 0.6387585321 -0.2638393095 0.0857745537
[186] -0.1437916946 -0.1634323686 0.1206826092 -0.4698546855 0.1666817149
[191] -0.0464976526 0.3130820671 -0.5009828686 -0.6358211749 -0.1954563137
[196] -0.1615535400 -0.2579298356 -0.0210912563 -0.2316761035 0.1231627334
[201] -0.3986118171 -0.0704408876 -0.2181400524 -0.0506174042 0.6107380518
[206] 0.3099611204 -0.2214588871 0.0843241437 0.8866754759 -0.0572668375
[211] 0.1344056444 0.6326237384 0.1526251551 0.2838036099 0.2145736995
[216] -0.2530062218 0.5123002804 0.2495105170 -0.2588100977 0.3784727630
[221] -0.0240493403 0.1189414045 0.5350155493 0.0699869027 0.1230085855
[226] -0.2975998756 -0.5691061737 -0.1410681867 0.1144868017 -0.0117765821
>
> proc.time()
user system elapsed
3.09 7.25 11.31
|
BufferedMatrix.Rcheck/tests_x64/objectTesting.Rout
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### 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-3.14-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 436755 23.4 924417 49.4 646908 34.6
Vcells 756020 5.8 8388608 64.0 1962980 15.0
>
>
>
>
> ##
> ## 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] "Tue Apr 12 16:41:32 2022"
> 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] "Tue Apr 12 16:41:32 2022"
>
>
> 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: 0x000000000627be18>
>
>
>
> 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] "Tue Apr 12 16:41:34 2022"
> 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] "Tue Apr 12 16:41:35 2022"
>
> ColMode(tmp2)
<pointer: 0x000000000627be18>
>
>
>
> ### 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,] 99.8012568 -1.2018989 -0.2094496 0.76299924
[2,] -0.3070747 -0.3124583 -2.0784301 -0.18517594
[3,] 0.4274119 1.0220778 0.7927138 0.19305826
[4,] -1.7686196 0.1210299 -0.4475475 -0.07796622
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2.1 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.8012568 1.2018989 0.2094496 0.76299924
[2,] 0.3070747 0.3124583 2.0784301 0.18517594
[3,] 0.4274119 1.0220778 0.7927138 0.19305826
[4,] 1.7686196 0.1210299 0.4475475 0.07796622
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2.1 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9900579 1.0963115 0.4576566 0.8734983
[2,] 0.5541432 0.5589797 1.4416761 0.4303207
[3,] 0.6537675 1.0109786 0.8903448 0.4393840
[4,] 1.3298946 0.3478935 0.6689899 0.2792243
>
> 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-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2.1 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.70184 37.16501 29.78602 34.49798
[2,] 30.84851 30.90225 41.49519 29.48838
[3,] 31.96509 36.13186 34.69616 29.58690
[4,] 40.06757 28.59997 32.13745 27.87021
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x0000000004f85fe0>
> exp(tmp5)
<pointer: 0x0000000004f85fe0>
> log(tmp5,2)
<pointer: 0x0000000004f85fe0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.6874
> Min(tmp5)
[1] 54.84008
> mean(tmp5)
[1] 73.70786
> Sum(tmp5)
[1] 14741.57
> Var(tmp5)
[1] 850.7717
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.15419 71.63648 74.52967 72.10670 71.96192 71.55368 72.21182 71.73424
[9] 67.82794 71.36192
> rowSums(tmp5)
[1] 1843.084 1432.730 1490.593 1442.134 1439.238 1431.074 1444.236 1434.685
[9] 1356.559 1427.238
> rowVars(tmp5)
[1] 7877.70573 61.03704 89.98400 87.50201 79.10345 46.99566
[7] 48.22228 76.68003 51.85133 68.79531
> rowSd(tmp5)
[1] 88.756440 7.812620 9.485990 9.354251 8.894012 6.855338 6.944226
[8] 8.756714 7.200786 8.294294
> rowMax(tmp5)
[1] 467.68743 86.36680 93.16191 85.17825 84.91725 84.14420 83.65845
[8] 84.46202 82.40468 88.36384
> rowMin(tmp5)
[1] 59.14676 61.37621 57.15926 58.00819 55.91513 56.94656 60.96724 54.84008
[9] 57.42078 55.84360
>
> colMeans(tmp5)
[1] 111.81404 72.53245 67.24824 65.32457 70.52059 70.90910 78.26687
[8] 71.56001 73.88620 75.22058 71.65471 70.97524 74.84376 70.33023
[15] 73.28846 71.35596 72.59408 71.26608 71.32177 69.24417
> colSums(tmp5)
[1] 1118.1404 725.3245 672.4824 653.2457 705.2059 709.0910 782.6687
[8] 715.6001 738.8620 752.2058 716.5471 709.7524 748.4376 703.3023
[15] 732.8846 713.5596 725.9408 712.6608 713.2177 692.4417
> colVars(tmp5)
[1] 15707.84977 84.97735 100.45065 38.31438 68.96010 65.58967
[7] 64.78869 35.05671 59.98738 68.20418 61.00104 61.71254
[13] 94.70405 46.84942 69.83316 72.46523 86.65466 40.85052
[19] 82.75728 40.40426
> colSd(tmp5)
[1] 125.330961 9.218316 10.022507 6.189861 8.304222 8.098745
[7] 8.049142 5.920870 7.745152 8.258582 7.810316 7.855733
[13] 9.731601 6.844664 8.356624 8.512651 9.308848 6.391441
[19] 9.097103 6.356435
> colMax(tmp5)
[1] 467.68743 83.99745 86.36680 76.26864 84.47094 81.47789 88.33641
[8] 84.91725 84.72977 87.05173 83.72387 80.96301 93.16191 79.69577
[15] 84.46202 83.65845 83.44276 81.51826 87.17878 78.46410
> colMin(tmp5)
[1] 62.13446 59.52708 55.91513 58.00819 56.94656 54.84008 64.96324 62.93504
[9] 55.84360 64.39274 59.45928 59.14676 59.62525 57.15926 56.32789 59.88002
[17] 57.42078 60.96724 61.53069 60.06913
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 92.15419 71.63648 74.52967 NA 71.96192 71.55368 72.21182 71.73424
[9] 67.82794 71.36192
> rowSums(tmp5)
[1] 1843.084 1432.730 1490.593 NA 1439.238 1431.074 1444.236 1434.685
[9] 1356.559 1427.238
> rowVars(tmp5)
[1] 7877.70573 61.03704 89.98400 82.37110 79.10345 46.99566
[7] 48.22228 76.68003 51.85133 68.79531
> rowSd(tmp5)
[1] 88.756440 7.812620 9.485990 9.075853 8.894012 6.855338 6.944226
[8] 8.756714 7.200786 8.294294
> rowMax(tmp5)
[1] 467.68743 86.36680 93.16191 NA 84.91725 84.14420 83.65845
[8] 84.46202 82.40468 88.36384
> rowMin(tmp5)
[1] 59.14676 61.37621 57.15926 NA 55.91513 56.94656 60.96724 54.84008
[9] 57.42078 55.84360
>
> colMeans(tmp5)
[1] 111.81404 72.53245 67.24824 65.32457 70.52059 70.90910 78.26687
[8] 71.56001 73.88620 NA 71.65471 70.97524 74.84376 70.33023
[15] 73.28846 71.35596 72.59408 71.26608 71.32177 69.24417
> colSums(tmp5)
[1] 1118.1404 725.3245 672.4824 653.2457 705.2059 709.0910 782.6687
[8] 715.6001 738.8620 NA 716.5471 709.7524 748.4376 703.3023
[15] 732.8846 713.5596 725.9408 712.6608 713.2177 692.4417
> colVars(tmp5)
[1] 15707.84977 84.97735 100.45065 38.31438 68.96010 65.58967
[7] 64.78869 35.05671 59.98738 NA 61.00104 61.71254
[13] 94.70405 46.84942 69.83316 72.46523 86.65466 40.85052
[19] 82.75728 40.40426
> colSd(tmp5)
[1] 125.330961 9.218316 10.022507 6.189861 8.304222 8.098745
[7] 8.049142 5.920870 7.745152 NA 7.810316 7.855733
[13] 9.731601 6.844664 8.356624 8.512651 9.308848 6.391441
[19] 9.097103 6.356435
> colMax(tmp5)
[1] 467.68743 83.99745 86.36680 76.26864 84.47094 81.47789 88.33641
[8] 84.91725 84.72977 NA 83.72387 80.96301 93.16191 79.69577
[15] 84.46202 83.65845 83.44276 81.51826 87.17878 78.46410
> colMin(tmp5)
[1] 62.13446 59.52708 55.91513 58.00819 56.94656 54.84008 64.96324 62.93504
[9] 55.84360 NA 59.45928 59.14676 59.62525 57.15926 56.32789 59.88002
[17] 57.42078 60.96724 61.53069 60.06913
>
> Max(tmp5,na.rm=TRUE)
[1] 467.6874
> Min(tmp5,na.rm=TRUE)
[1] 54.84008
> mean(tmp5,na.rm=TRUE)
[1] 73.65022
> Sum(tmp5,na.rm=TRUE)
[1] 14656.39
> Var(tmp5,na.rm=TRUE)
[1] 854.4007
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.15419 71.63648 74.52967 71.41873 71.96192 71.55368 72.21182 71.73424
[9] 67.82794 71.36192
> rowSums(tmp5,na.rm=TRUE)
[1] 1843.084 1432.730 1490.593 1356.956 1439.238 1431.074 1444.236 1434.685
[9] 1356.559 1427.238
> rowVars(tmp5,na.rm=TRUE)
[1] 7877.70573 61.03704 89.98400 82.37110 79.10345 46.99566
[7] 48.22228 76.68003 51.85133 68.79531
> rowSd(tmp5,na.rm=TRUE)
[1] 88.756440 7.812620 9.485990 9.075853 8.894012 6.855338 6.944226
[8] 8.756714 7.200786 8.294294
> rowMax(tmp5,na.rm=TRUE)
[1] 467.68743 86.36680 93.16191 83.74880 84.91725 84.14420 83.65845
[8] 84.46202 82.40468 88.36384
> rowMin(tmp5,na.rm=TRUE)
[1] 59.14676 61.37621 57.15926 58.00819 55.91513 56.94656 60.96724 54.84008
[9] 57.42078 55.84360
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.81404 72.53245 67.24824 65.32457 70.52059 70.90910 78.26687
[8] 71.56001 73.88620 74.11418 71.65471 70.97524 74.84376 70.33023
[15] 73.28846 71.35596 72.59408 71.26608 71.32177 69.24417
> colSums(tmp5,na.rm=TRUE)
[1] 1118.1404 725.3245 672.4824 653.2457 705.2059 709.0910 782.6687
[8] 715.6001 738.8620 667.0276 716.5471 709.7524 748.4376 703.3023
[15] 732.8846 713.5596 725.9408 712.6608 713.2177 692.4417
> colVars(tmp5,na.rm=TRUE)
[1] 15707.84977 84.97735 100.45065 38.31438 68.96010 65.58967
[7] 64.78869 35.05671 59.98738 62.95815 61.00104 61.71254
[13] 94.70405 46.84942 69.83316 72.46523 86.65466 40.85052
[19] 82.75728 40.40426
> colSd(tmp5,na.rm=TRUE)
[1] 125.330961 9.218316 10.022507 6.189861 8.304222 8.098745
[7] 8.049142 5.920870 7.745152 7.934617 7.810316 7.855733
[13] 9.731601 6.844664 8.356624 8.512651 9.308848 6.391441
[19] 9.097103 6.356435
> colMax(tmp5,na.rm=TRUE)
[1] 467.68743 83.99745 86.36680 76.26864 84.47094 81.47789 88.33641
[8] 84.91725 84.72977 87.05173 83.72387 80.96301 93.16191 79.69577
[15] 84.46202 83.65845 83.44276 81.51826 87.17878 78.46410
> colMin(tmp5,na.rm=TRUE)
[1] 62.13446 59.52708 55.91513 58.00819 56.94656 54.84008 64.96324 62.93504
[9] 55.84360 64.39274 59.45928 59.14676 59.62525 57.15926 56.32789 59.88002
[17] 57.42078 60.96724 61.53069 60.06913
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.15419 71.63648 74.52967 NaN 71.96192 71.55368 72.21182 71.73424
[9] 67.82794 71.36192
> rowSums(tmp5,na.rm=TRUE)
[1] 1843.084 1432.730 1490.593 0.000 1439.238 1431.074 1444.236 1434.685
[9] 1356.559 1427.238
> rowVars(tmp5,na.rm=TRUE)
[1] 7877.70573 61.03704 89.98400 NA 79.10345 46.99566
[7] 48.22228 76.68003 51.85133 68.79531
> rowSd(tmp5,na.rm=TRUE)
[1] 88.756440 7.812620 9.485990 NA 8.894012 6.855338 6.944226
[8] 8.756714 7.200786 8.294294
> rowMax(tmp5,na.rm=TRUE)
[1] 467.68743 86.36680 93.16191 NA 84.91725 84.14420 83.65845
[8] 84.46202 82.40468 88.36384
> rowMin(tmp5,na.rm=TRUE)
[1] 59.14676 61.37621 57.15926 NA 55.91513 56.94656 60.96724 54.84008
[9] 57.42078 55.84360
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.97167 73.97749 67.28806 66.13750 71.11663 71.15931 77.65776
[8] 71.61689 73.71024 NaN 70.31369 70.39349 74.22186 70.78179
[15] 72.89351 72.39885 71.38867 70.90035 72.40966 70.26362
> colSums(tmp5,na.rm=TRUE)
[1] 1034.7450 665.7974 605.5926 595.2375 640.0497 640.4338 698.9199
[8] 644.5520 663.3922 0.0000 632.8232 633.5414 667.9967 637.0361
[15] 656.0416 651.5897 642.4981 638.1031 651.6870 632.3726
> colVars(tmp5,na.rm=TRUE)
[1] 17559.16159 72.10791 112.98914 35.66904 73.58334 73.08408
[7] 68.71344 39.40240 67.13749 NA 48.39496 65.61932
[13] 102.19093 50.41166 76.80745 69.28761 81.14013 44.45199
[19] 79.78734 33.76293
> colSd(tmp5,na.rm=TRUE)
[1] 132.510987 8.491638 10.629635 5.972356 8.578073 8.548923
[7] 8.289357 6.277133 8.193747 NA 6.956649 8.100575
[13] 10.108953 7.100117 8.763986 8.323918 9.007782 6.667233
[19] 8.932376 5.810588
> colMax(tmp5,na.rm=TRUE)
[1] 467.68743 83.99745 86.36680 76.26864 84.47094 81.47789 88.33641
[8] 84.91725 84.72977 -Inf 80.68089 80.96301 93.16191 79.69577
[15] 84.46202 83.65845 82.58547 81.51826 87.17878 78.46410
> colMin(tmp5,na.rm=TRUE)
[1] 62.13446 61.91604 55.91513 61.37621 56.94656 54.84008 64.96324 62.93504
[9] 55.84360 Inf 59.45928 59.14676 59.62525 57.15926 56.32789 59.88002
[17] 57.42078 60.96724 62.76710 62.92916
>
>
>
>
> 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] 283.2231 505.2269 353.5838 293.9910 114.4784 271.4908 296.7657 261.5559
[9] 162.8281 164.2066
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 283.2231 505.2269 353.5838 293.9910 114.4784 271.4908 296.7657 261.5559
[9] 162.8281 164.2066
>
>
>
> 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-14 5.684342e-14 5.684342e-14 -2.842171e-14 1.136868e-13
[6] -1.136868e-13 -5.684342e-14 5.684342e-14 -5.684342e-14 -5.684342e-14
[11] -1.989520e-13 1.705303e-13 0.000000e+00 1.136868e-13 -2.842171e-14
[16] 5.684342e-14 5.684342e-14 2.273737e-13 7.105427e-14 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## 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)
+ }
1 9
3 2
3 19
8 15
10 5
1 5
9 13
2 8
7 15
2 18
2 3
6 16
10 17
10 4
3 10
5 9
5 8
5 17
1 20
7 12
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.547588
> Min(tmp)
[1] -2.163926
> mean(tmp)
[1] -0.09097586
> Sum(tmp)
[1] -9.097586
> Var(tmp)
[1] 0.8163695
>
> rowMeans(tmp)
[1] -0.09097586
> rowSums(tmp)
[1] -9.097586
> rowVars(tmp)
[1] 0.8163695
> rowSd(tmp)
[1] 0.9035317
> rowMax(tmp)
[1] 2.547588
> rowMin(tmp)
[1] -2.163926
>
> colMeans(tmp)
[1] 0.15253631 0.47779878 0.14070865 0.67386855 -0.72187676 -0.21002049
[7] -0.71348468 0.09487769 1.63381747 0.92319794 0.96459974 -1.21542422
[13] 0.84544916 -0.82186414 -1.23333252 -1.30235952 0.16167603 0.02762809
[19] -0.36908522 -0.76845183 -1.02138589 0.80927035 -1.47424451 -1.09488983
[25] 0.40045650 -1.34536154 0.15849371 1.07146566 -1.65294608 0.66196202
[31] 0.25376160 -0.71002914 -1.18556829 -0.16969788 -0.90726534 0.06092831
[37] 1.19562116 -0.02487887 0.77856116 0.26972368 0.47893061 -0.39921738
[43] -0.73229298 -0.04197176 -0.24139540 0.30048078 0.90835013 0.76966465
[49] -0.04081873 -0.42262841 -0.67440148 0.42670150 -0.68462905 0.22400733
[55] -0.20509350 -1.90106975 0.04769145 -0.36707274 0.49820957 -1.00488442
[61] 1.24012600 2.54758785 0.50742962 -0.27947589 1.72814567 0.77052722
[67] 0.30631893 -1.30848686 -1.69576812 0.15675685 -0.18903201 -1.14370044
[73] -0.09060262 0.71239067 -0.29167817 -0.90380176 -0.77667909 0.44987139
[79] -0.02941063 -0.13459267 -2.16392607 -0.19832624 -0.95397321 0.78042866
[85] 0.38960984 -0.33848246 0.54757787 -0.17423553 -0.04054971 0.27433906
[91] -1.67718964 2.05087455 -0.30708644 1.49652677 0.01671186 1.28421511
[97] -0.28636036 -0.40142951 -2.14890527 -0.57612738
> colSums(tmp)
[1] 0.15253631 0.47779878 0.14070865 0.67386855 -0.72187676 -0.21002049
[7] -0.71348468 0.09487769 1.63381747 0.92319794 0.96459974 -1.21542422
[13] 0.84544916 -0.82186414 -1.23333252 -1.30235952 0.16167603 0.02762809
[19] -0.36908522 -0.76845183 -1.02138589 0.80927035 -1.47424451 -1.09488983
[25] 0.40045650 -1.34536154 0.15849371 1.07146566 -1.65294608 0.66196202
[31] 0.25376160 -0.71002914 -1.18556829 -0.16969788 -0.90726534 0.06092831
[37] 1.19562116 -0.02487887 0.77856116 0.26972368 0.47893061 -0.39921738
[43] -0.73229298 -0.04197176 -0.24139540 0.30048078 0.90835013 0.76966465
[49] -0.04081873 -0.42262841 -0.67440148 0.42670150 -0.68462905 0.22400733
[55] -0.20509350 -1.90106975 0.04769145 -0.36707274 0.49820957 -1.00488442
[61] 1.24012600 2.54758785 0.50742962 -0.27947589 1.72814567 0.77052722
[67] 0.30631893 -1.30848686 -1.69576812 0.15675685 -0.18903201 -1.14370044
[73] -0.09060262 0.71239067 -0.29167817 -0.90380176 -0.77667909 0.44987139
[79] -0.02941063 -0.13459267 -2.16392607 -0.19832624 -0.95397321 0.78042866
[85] 0.38960984 -0.33848246 0.54757787 -0.17423553 -0.04054971 0.27433906
[91] -1.67718964 2.05087455 -0.30708644 1.49652677 0.01671186 1.28421511
[97] -0.28636036 -0.40142951 -2.14890527 -0.57612738
> 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] 0.15253631 0.47779878 0.14070865 0.67386855 -0.72187676 -0.21002049
[7] -0.71348468 0.09487769 1.63381747 0.92319794 0.96459974 -1.21542422
[13] 0.84544916 -0.82186414 -1.23333252 -1.30235952 0.16167603 0.02762809
[19] -0.36908522 -0.76845183 -1.02138589 0.80927035 -1.47424451 -1.09488983
[25] 0.40045650 -1.34536154 0.15849371 1.07146566 -1.65294608 0.66196202
[31] 0.25376160 -0.71002914 -1.18556829 -0.16969788 -0.90726534 0.06092831
[37] 1.19562116 -0.02487887 0.77856116 0.26972368 0.47893061 -0.39921738
[43] -0.73229298 -0.04197176 -0.24139540 0.30048078 0.90835013 0.76966465
[49] -0.04081873 -0.42262841 -0.67440148 0.42670150 -0.68462905 0.22400733
[55] -0.20509350 -1.90106975 0.04769145 -0.36707274 0.49820957 -1.00488442
[61] 1.24012600 2.54758785 0.50742962 -0.27947589 1.72814567 0.77052722
[67] 0.30631893 -1.30848686 -1.69576812 0.15675685 -0.18903201 -1.14370044
[73] -0.09060262 0.71239067 -0.29167817 -0.90380176 -0.77667909 0.44987139
[79] -0.02941063 -0.13459267 -2.16392607 -0.19832624 -0.95397321 0.78042866
[85] 0.38960984 -0.33848246 0.54757787 -0.17423553 -0.04054971 0.27433906
[91] -1.67718964 2.05087455 -0.30708644 1.49652677 0.01671186 1.28421511
[97] -0.28636036 -0.40142951 -2.14890527 -0.57612738
> colMin(tmp)
[1] 0.15253631 0.47779878 0.14070865 0.67386855 -0.72187676 -0.21002049
[7] -0.71348468 0.09487769 1.63381747 0.92319794 0.96459974 -1.21542422
[13] 0.84544916 -0.82186414 -1.23333252 -1.30235952 0.16167603 0.02762809
[19] -0.36908522 -0.76845183 -1.02138589 0.80927035 -1.47424451 -1.09488983
[25] 0.40045650 -1.34536154 0.15849371 1.07146566 -1.65294608 0.66196202
[31] 0.25376160 -0.71002914 -1.18556829 -0.16969788 -0.90726534 0.06092831
[37] 1.19562116 -0.02487887 0.77856116 0.26972368 0.47893061 -0.39921738
[43] -0.73229298 -0.04197176 -0.24139540 0.30048078 0.90835013 0.76966465
[49] -0.04081873 -0.42262841 -0.67440148 0.42670150 -0.68462905 0.22400733
[55] -0.20509350 -1.90106975 0.04769145 -0.36707274 0.49820957 -1.00488442
[61] 1.24012600 2.54758785 0.50742962 -0.27947589 1.72814567 0.77052722
[67] 0.30631893 -1.30848686 -1.69576812 0.15675685 -0.18903201 -1.14370044
[73] -0.09060262 0.71239067 -0.29167817 -0.90380176 -0.77667909 0.44987139
[79] -0.02941063 -0.13459267 -2.16392607 -0.19832624 -0.95397321 0.78042866
[85] 0.38960984 -0.33848246 0.54757787 -0.17423553 -0.04054971 0.27433906
[91] -1.67718964 2.05087455 -0.30708644 1.49652677 0.01671186 1.28421511
[97] -0.28636036 -0.40142951 -2.14890527 -0.57612738
> colMedians(tmp)
[1] 0.15253631 0.47779878 0.14070865 0.67386855 -0.72187676 -0.21002049
[7] -0.71348468 0.09487769 1.63381747 0.92319794 0.96459974 -1.21542422
[13] 0.84544916 -0.82186414 -1.23333252 -1.30235952 0.16167603 0.02762809
[19] -0.36908522 -0.76845183 -1.02138589 0.80927035 -1.47424451 -1.09488983
[25] 0.40045650 -1.34536154 0.15849371 1.07146566 -1.65294608 0.66196202
[31] 0.25376160 -0.71002914 -1.18556829 -0.16969788 -0.90726534 0.06092831
[37] 1.19562116 -0.02487887 0.77856116 0.26972368 0.47893061 -0.39921738
[43] -0.73229298 -0.04197176 -0.24139540 0.30048078 0.90835013 0.76966465
[49] -0.04081873 -0.42262841 -0.67440148 0.42670150 -0.68462905 0.22400733
[55] -0.20509350 -1.90106975 0.04769145 -0.36707274 0.49820957 -1.00488442
[61] 1.24012600 2.54758785 0.50742962 -0.27947589 1.72814567 0.77052722
[67] 0.30631893 -1.30848686 -1.69576812 0.15675685 -0.18903201 -1.14370044
[73] -0.09060262 0.71239067 -0.29167817 -0.90380176 -0.77667909 0.44987139
[79] -0.02941063 -0.13459267 -2.16392607 -0.19832624 -0.95397321 0.78042866
[85] 0.38960984 -0.33848246 0.54757787 -0.17423553 -0.04054971 0.27433906
[91] -1.67718964 2.05087455 -0.30708644 1.49652677 0.01671186 1.28421511
[97] -0.28636036 -0.40142951 -2.14890527 -0.57612738
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.1525363 0.4777988 0.1407086 0.6738685 -0.7218768 -0.2100205 -0.7134847
[2,] 0.1525363 0.4777988 0.1407086 0.6738685 -0.7218768 -0.2100205 -0.7134847
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.09487769 1.633817 0.9231979 0.9645997 -1.215424 0.8454492 -0.8218641
[2,] 0.09487769 1.633817 0.9231979 0.9645997 -1.215424 0.8454492 -0.8218641
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.233333 -1.30236 0.161676 0.02762809 -0.3690852 -0.7684518 -1.021386
[2,] -1.233333 -1.30236 0.161676 0.02762809 -0.3690852 -0.7684518 -1.021386
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.8092703 -1.474245 -1.09489 0.4004565 -1.345362 0.1584937 1.071466
[2,] 0.8092703 -1.474245 -1.09489 0.4004565 -1.345362 0.1584937 1.071466
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.652946 0.661962 0.2537616 -0.7100291 -1.185568 -0.1696979 -0.9072653
[2,] -1.652946 0.661962 0.2537616 -0.7100291 -1.185568 -0.1696979 -0.9072653
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.06092831 1.195621 -0.02487887 0.7785612 0.2697237 0.4789306 -0.3992174
[2,] 0.06092831 1.195621 -0.02487887 0.7785612 0.2697237 0.4789306 -0.3992174
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.732293 -0.04197176 -0.2413954 0.3004808 0.9083501 0.7696647 -0.04081873
[2,] -0.732293 -0.04197176 -0.2413954 0.3004808 0.9083501 0.7696647 -0.04081873
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.4226284 -0.6744015 0.4267015 -0.684629 0.2240073 -0.2050935 -1.90107
[2,] -0.4226284 -0.6744015 0.4267015 -0.684629 0.2240073 -0.2050935 -1.90107
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.04769145 -0.3670727 0.4982096 -1.004884 1.240126 2.547588 0.5074296
[2,] 0.04769145 -0.3670727 0.4982096 -1.004884 1.240126 2.547588 0.5074296
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.2794759 1.728146 0.7705272 0.3063189 -1.308487 -1.695768 0.1567568
[2,] -0.2794759 1.728146 0.7705272 0.3063189 -1.308487 -1.695768 0.1567568
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.189032 -1.1437 -0.09060262 0.7123907 -0.2916782 -0.9038018 -0.7766791
[2,] -0.189032 -1.1437 -0.09060262 0.7123907 -0.2916782 -0.9038018 -0.7766791
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.4498714 -0.02941063 -0.1345927 -2.163926 -0.1983262 -0.9539732 0.7804287
[2,] 0.4498714 -0.02941063 -0.1345927 -2.163926 -0.1983262 -0.9539732 0.7804287
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.3896098 -0.3384825 0.5475779 -0.1742355 -0.04054971 0.2743391 -1.67719
[2,] 0.3896098 -0.3384825 0.5475779 -0.1742355 -0.04054971 0.2743391 -1.67719
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 2.050875 -0.3070864 1.496527 0.01671186 1.284215 -0.2863604 -0.4014295
[2,] 2.050875 -0.3070864 1.496527 0.01671186 1.284215 -0.2863604 -0.4014295
[,99] [,100]
[1,] -2.148905 -0.5761274
[2,] -2.148905 -0.5761274
>
>
> Max(tmp2)
[1] 2.105237
> Min(tmp2)
[1] -2.119077
> mean(tmp2)
[1] -0.02946026
> Sum(tmp2)
[1] -2.946026
> Var(tmp2)
[1] 0.7207617
>
> rowMeans(tmp2)
[1] 0.01285317 -0.71486966 -0.53244244 0.65674339 -0.73874934 0.21553094
[7] -1.06566771 0.66677356 0.30292212 -0.55350137 -0.10261532 -2.11907695
[13] -0.59639718 -0.67705906 -0.72477381 -0.87694316 -1.01351435 0.29716845
[19] -0.28291480 -0.49801340 -0.84917632 -0.37240466 0.28708072 0.55939358
[25] 0.89784560 -0.93310397 -0.82862121 -0.41148095 0.44714528 0.23117246
[31] 1.35998792 1.36471378 0.45644963 0.42112260 0.92934840 0.48683635
[37] -0.34839001 0.51538077 -0.39445080 -0.72378165 0.10961470 0.39346987
[43] -0.53324134 0.33286745 -1.03433598 -0.31816258 -0.01410101 2.10523718
[49] -1.07688549 0.36721670 0.10214342 1.59047448 -0.45101965 -1.32315742
[55] 0.72617172 -0.61405034 -0.37104337 0.58366666 -0.53230863 -0.81542764
[61] 0.91129169 0.65245582 -0.43939269 0.85910603 1.07953722 1.08576965
[67] -0.73880980 -0.34819817 -0.70866280 -0.07304477 -1.75427425 -1.10761417
[73] -0.57648252 -0.26102287 0.51843047 0.46983722 1.49816852 -0.85354995
[79] -0.43681683 0.48998562 -1.03297047 0.59689089 -1.79849403 -0.76695280
[85] 1.85422520 0.46210212 0.02058862 0.19878752 1.23376127 -0.24468146
[91] 0.13668669 0.94177001 0.51448144 -1.60170537 0.38907434 -0.91801356
[97] 2.06672307 0.57504753 0.73487656 -0.55258589
> rowSums(tmp2)
[1] 0.01285317 -0.71486966 -0.53244244 0.65674339 -0.73874934 0.21553094
[7] -1.06566771 0.66677356 0.30292212 -0.55350137 -0.10261532 -2.11907695
[13] -0.59639718 -0.67705906 -0.72477381 -0.87694316 -1.01351435 0.29716845
[19] -0.28291480 -0.49801340 -0.84917632 -0.37240466 0.28708072 0.55939358
[25] 0.89784560 -0.93310397 -0.82862121 -0.41148095 0.44714528 0.23117246
[31] 1.35998792 1.36471378 0.45644963 0.42112260 0.92934840 0.48683635
[37] -0.34839001 0.51538077 -0.39445080 -0.72378165 0.10961470 0.39346987
[43] -0.53324134 0.33286745 -1.03433598 -0.31816258 -0.01410101 2.10523718
[49] -1.07688549 0.36721670 0.10214342 1.59047448 -0.45101965 -1.32315742
[55] 0.72617172 -0.61405034 -0.37104337 0.58366666 -0.53230863 -0.81542764
[61] 0.91129169 0.65245582 -0.43939269 0.85910603 1.07953722 1.08576965
[67] -0.73880980 -0.34819817 -0.70866280 -0.07304477 -1.75427425 -1.10761417
[73] -0.57648252 -0.26102287 0.51843047 0.46983722 1.49816852 -0.85354995
[79] -0.43681683 0.48998562 -1.03297047 0.59689089 -1.79849403 -0.76695280
[85] 1.85422520 0.46210212 0.02058862 0.19878752 1.23376127 -0.24468146
[91] 0.13668669 0.94177001 0.51448144 -1.60170537 0.38907434 -0.91801356
[97] 2.06672307 0.57504753 0.73487656 -0.55258589
> 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] 0.01285317 -0.71486966 -0.53244244 0.65674339 -0.73874934 0.21553094
[7] -1.06566771 0.66677356 0.30292212 -0.55350137 -0.10261532 -2.11907695
[13] -0.59639718 -0.67705906 -0.72477381 -0.87694316 -1.01351435 0.29716845
[19] -0.28291480 -0.49801340 -0.84917632 -0.37240466 0.28708072 0.55939358
[25] 0.89784560 -0.93310397 -0.82862121 -0.41148095 0.44714528 0.23117246
[31] 1.35998792 1.36471378 0.45644963 0.42112260 0.92934840 0.48683635
[37] -0.34839001 0.51538077 -0.39445080 -0.72378165 0.10961470 0.39346987
[43] -0.53324134 0.33286745 -1.03433598 -0.31816258 -0.01410101 2.10523718
[49] -1.07688549 0.36721670 0.10214342 1.59047448 -0.45101965 -1.32315742
[55] 0.72617172 -0.61405034 -0.37104337 0.58366666 -0.53230863 -0.81542764
[61] 0.91129169 0.65245582 -0.43939269 0.85910603 1.07953722 1.08576965
[67] -0.73880980 -0.34819817 -0.70866280 -0.07304477 -1.75427425 -1.10761417
[73] -0.57648252 -0.26102287 0.51843047 0.46983722 1.49816852 -0.85354995
[79] -0.43681683 0.48998562 -1.03297047 0.59689089 -1.79849403 -0.76695280
[85] 1.85422520 0.46210212 0.02058862 0.19878752 1.23376127 -0.24468146
[91] 0.13668669 0.94177001 0.51448144 -1.60170537 0.38907434 -0.91801356
[97] 2.06672307 0.57504753 0.73487656 -0.55258589
> rowMin(tmp2)
[1] 0.01285317 -0.71486966 -0.53244244 0.65674339 -0.73874934 0.21553094
[7] -1.06566771 0.66677356 0.30292212 -0.55350137 -0.10261532 -2.11907695
[13] -0.59639718 -0.67705906 -0.72477381 -0.87694316 -1.01351435 0.29716845
[19] -0.28291480 -0.49801340 -0.84917632 -0.37240466 0.28708072 0.55939358
[25] 0.89784560 -0.93310397 -0.82862121 -0.41148095 0.44714528 0.23117246
[31] 1.35998792 1.36471378 0.45644963 0.42112260 0.92934840 0.48683635
[37] -0.34839001 0.51538077 -0.39445080 -0.72378165 0.10961470 0.39346987
[43] -0.53324134 0.33286745 -1.03433598 -0.31816258 -0.01410101 2.10523718
[49] -1.07688549 0.36721670 0.10214342 1.59047448 -0.45101965 -1.32315742
[55] 0.72617172 -0.61405034 -0.37104337 0.58366666 -0.53230863 -0.81542764
[61] 0.91129169 0.65245582 -0.43939269 0.85910603 1.07953722 1.08576965
[67] -0.73880980 -0.34819817 -0.70866280 -0.07304477 -1.75427425 -1.10761417
[73] -0.57648252 -0.26102287 0.51843047 0.46983722 1.49816852 -0.85354995
[79] -0.43681683 0.48998562 -1.03297047 0.59689089 -1.79849403 -0.76695280
[85] 1.85422520 0.46210212 0.02058862 0.19878752 1.23376127 -0.24468146
[91] 0.13668669 0.94177001 0.51448144 -1.60170537 0.38907434 -0.91801356
[97] 2.06672307 0.57504753 0.73487656 -0.55258589
>
> colMeans(tmp2)
[1] -0.02946026
> colSums(tmp2)
[1] -2.946026
> colVars(tmp2)
[1] 0.7207617
> colSd(tmp2)
[1] 0.8489768
> colMax(tmp2)
[1] 2.105237
> colMin(tmp2)
[1] -2.119077
> colMedians(tmp2)
[1] -0.04357289
> colRanges(tmp2)
[,1]
[1,] -2.119077
[2,] 2.105237
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.9703881 1.1703026 -2.5656875 0.8119384 -2.4636999 -4.0868844
[7] 0.5127596 2.8001599 -1.9501407 -0.7241086
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.46939759
[2,] -0.78651862
[3,] -0.16026386
[4,] 0.07800472
[5,] 1.38941682
>
> rowApply(tmp,sum)
[1] -8.2067998 -0.7588831 1.3204161 0.3059886 -2.4345829 -1.2811080
[7] -0.1875597 2.6260976 -1.1711884 1.3218710
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 7 10 5 2 3 1 9 4 3
[2,] 2 6 9 3 7 6 7 5 10 5
[3,] 10 1 1 6 1 10 5 10 3 1
[4,] 1 9 7 9 10 2 4 8 7 2
[5,] 6 2 2 10 6 4 9 4 1 9
[6,] 4 8 5 1 5 7 3 3 2 8
[7,] 5 3 3 2 8 9 8 1 8 10
[8,] 8 10 8 8 3 1 10 7 9 6
[9,] 7 5 6 4 4 8 2 2 5 7
[10,] 3 4 4 7 9 5 6 6 6 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.6213213 0.9554185 -0.3282998 1.2468067 -0.4292214 -0.5748513
[7] 2.5550250 5.5100251 -2.1405315 2.0535898 -1.1698499 -2.0383819
[13] -2.4079042 -0.9983038 3.3037249 2.1463537 0.9929844 -2.4110286
[19] -0.1094018 -1.2943571
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.5815486
[2,] -0.4264026
[3,] -0.1634005
[4,] 0.5845351
[5,] 1.2081380
>
> rowApply(tmp,sum)
[1] 0.2662017 0.7113208 1.8397860 5.4097180 -2.7439083
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 15 18 4 8 9
[2,] 4 15 7 19 11
[3,] 19 9 2 15 6
[4,] 17 4 17 7 13
[5,] 18 14 10 3 3
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.5845351 -0.9746448 1.3761987 0.9752652 1.02550644 1.5062975
[2,] 1.2081380 0.4990775 0.1431312 -1.0733233 0.41295540 -1.8201212
[3,] -0.5815486 -0.3622531 -1.6486273 1.1501508 0.03969431 0.3104042
[4,] -0.1634005 1.9866967 0.7692509 -0.2309327 -0.67905957 -0.1072493
[5,] -0.4264026 -0.1934579 -0.9682533 0.4256466 -1.22831798 -0.4641824
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.0580549 0.3705849 -0.3658528 0.1888554 -0.6319686 0.6459226
[2,] 0.8732956 0.7510460 0.1915413 -0.0208142 -1.6208059 -1.4120251
[3,] 0.2666674 2.1186518 0.8675635 -0.2131103 -0.4210324 -2.3728806
[4,] 0.0258187 1.6629449 -0.5377976 1.1024682 0.1183947 2.1176464
[5,] 2.4472982 0.6067975 -2.2959859 0.9961908 1.3855623 -1.0170453
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.5673720 0.2718406 -0.4795503 0.3318278 -0.2470253 -1.0381955
[2,] 0.2795882 0.4085761 2.3996978 0.4012386 -0.5406737 -0.6783763
[3,] 0.3168731 -0.5227240 0.5416317 0.8062585 1.4048598 1.3043339
[4,] -0.5052897 0.6322944 0.3578934 1.7693223 -0.5309426 -1.6213834
[5,] -0.9317039 -1.7882909 0.4840523 -1.1622935 0.9067663 -0.3774073
[,19] [,20]
[1,] -0.2842337 -0.3637347
[2,] -0.9235739 1.2327487
[3,] -0.0713320 -1.0937946
[4,] 0.4391885 -1.1961459
[5,] 0.7305493 0.1265694
>
>
> 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-3.14-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-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 685 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 593 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.14-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 0.6834642 0.2699663 -0.05651096 0.02755195 0.816295 -0.9514466 0.456649
col8 col9 col10 col11 col12 col13 col14
row1 0.792234 1.232043 -0.09505748 -0.7103421 0.8014754 0.5528075 0.3724735
col15 col16 col17 col18 col19 col20
row1 -0.3543705 0.3011108 0.6879835 0.07896118 0.1814027 0.07288296
> tmp[,"col10"]
col10
row1 -0.09505748
row2 1.81344414
row3 -0.95819335
row4 2.40797704
row5 -0.61948657
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.6834642 0.2699663 -0.05651096 0.02755195 0.8162950 -0.9514466
row5 0.4193274 0.1332992 -0.23663767 -0.93125775 0.6737271 1.9943374
col7 col8 col9 col10 col11 col12
row1 0.4566490 0.792234 1.23204285 -0.09505748 -0.7103421 0.8014754
row5 -0.2366407 -0.460164 0.09886159 -0.61948657 1.2977439 -0.6565663
col13 col14 col15 col16 col17 col18 col19
row1 0.5528075 0.3724735 -0.3543705 0.3011108 0.6879835 0.07896118 0.1814027
row5 0.2139509 0.9172501 -0.4595917 -1.4214851 -0.8115187 -0.80824680 1.5812762
col20
row1 0.07288296
row5 0.35143620
> tmp[,c("col6","col20")]
col6 col20
row1 -0.95144663 0.07288296
row2 -1.46606369 1.27603069
row3 -0.09853441 -0.47119421
row4 -1.58525892 0.01074742
row5 1.99433739 0.35143620
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.9514466 0.07288296
row5 1.9943374 0.35143620
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.20318 49.69752 49.84489 51.52096 49.65298 105.4084 52.46588 50.27241
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.34471 51.14444 48.68332 49.39858 51.0093 51.91279 51.44406 48.57563
col17 col18 col19 col20
row1 50.69553 50.91536 50.85914 103.5277
> tmp[,"col10"]
col10
row1 51.14444
row2 30.85008
row3 28.13915
row4 28.86967
row5 50.24111
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.20318 49.69752 49.84489 51.52096 49.65298 105.4084 52.46588 50.27241
row5 47.96475 51.86385 50.40238 47.93130 48.78875 105.1142 51.89627 49.48316
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.34471 51.14444 48.68332 49.39858 51.00930 51.91279 51.44406 48.57563
row5 50.11159 50.24111 50.02511 49.49229 47.70687 52.02685 50.41070 48.54633
col17 col18 col19 col20
row1 50.69553 50.91536 50.85914 103.5277
row5 51.34344 48.80678 51.48824 107.2864
> tmp[,c("col6","col20")]
col6 col20
row1 105.40843 103.52766
row2 76.03446 74.16913
row3 74.63559 77.38821
row4 74.12139 76.54268
row5 105.11415 107.28640
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.4084 103.5277
row5 105.1142 107.2864
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.4084 103.5277
row5 105.1142 107.2864
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.6971433
[2,] 0.1809733
[3,] 2.4512493
[4,] -0.8218306
[5,] 2.0653985
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.08390798 0.40764764
[2,] -1.43317121 0.08043374
[3,] -1.18117329 -0.36336980
[4,] -0.38898060 0.89769471
[5,] 0.05867876 1.53682165
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.06240417 -2.956082283
[2,] -0.31357230 0.575671681
[3,] -0.17975190 -0.004150479
[4,] -0.83858389 -0.281807994
[5,] 1.20480988 0.359522124
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.06240417
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.06240417
[2,] -0.31357230
>
>
>
> 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 1.025876 -0.2431744 0.7507149 1.0425799 0.8052638 -2.9929906 0.9811625
row1 -1.004137 -1.1004008 0.3905415 -0.4296408 -0.1150486 -0.1282872 0.5646436
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -1.48927939 -0.0914347 0.5090662 0.3089909 -0.7245839 0.66605153
row1 -0.09823754 -1.4276205 -0.1998754 -0.3771572 -0.8976524 -0.09813716
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.8484694 -0.4886481 2.1140098 -0.3349045 -0.3413620 -0.5633160
row1 0.7148685 0.1297018 0.8027799 0.9372428 0.7812414 0.8539082
[,20]
row3 0.5247465
row1 -0.4746407
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.01491713 -0.1315752 -2.282324 1.544149 -1.072819 0.5347452 2.291346
[,8] [,9] [,10]
row2 -0.5870316 -0.3161327 0.3586145
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.2588275 1.085278 -2.57624 -1.102431 1.416061 -1.057942 0.8333793
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.077488 1.558473 -1.023951 0.3629414 -1.046799 0.455498 0.2197039
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.2099885 1.028739 -0.5521674 -1.944589 -1.269444 -0.6181468
>
>
> 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: 0x00000000050b2c48>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM16c86d581471"
[2] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM16c86c3932e1"
[3] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM16c81a0a7247"
[4] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM16c83201446a"
[5] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM16c8abb6e08"
[6] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM16c81f0364c1"
[7] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM16c84a074d2e"
[8] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM16c839e622de"
[9] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM16c874002110"
[10] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM16c8606c7a5d"
[11] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM16c83e801ebd"
[12] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM16c8325ca7f"
[13] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM16c85bbe2e2b"
[14] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM16c828bf3e72"
[15] "C:/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM16c86b207491"
>
>
> ### 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: 0x0000000004d4af50>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x0000000004d4af50>
Warning message:
In dir.create(new.directory) :
'C:\Users\biocbuild\bbs-3.14-bioc\meat\BufferedMatrix.Rcheck\tests_x64' already exists
>
>
> RowMode(tmp)
<pointer: 0x0000000004d4af50>
> rowMedians(tmp)
[1] 0.2299710208 -0.5069151521 0.3199106846 0.4639884689 -0.4184125432
[6] -0.8249899964 0.0270137793 0.1905763646 0.0942355118 -0.1821131133
[11] -0.1570728269 0.0231905755 -0.2827767547 -0.0595187996 -0.1591176893
[16] 0.1270650825 -0.5349303638 0.1807468147 0.6135386787 0.2582583337
[21] -0.1072405919 -0.3430820451 -0.2391859778 0.3901353951 -0.1910186179
[26] 0.2916993987 0.2471848956 0.6977616486 -0.6796208401 -0.0556655434
[31] -0.4661824615 0.3198350436 0.3436974133 -0.5981549174 0.3912016156
[36] 0.0026397811 0.4703793587 0.1233083304 0.3530422301 0.1811412470
[41] 0.3252932918 0.3572783760 0.1411197645 0.2584504876 0.2320922406
[46] 0.5683779952 0.5132994767 0.4075401180 -0.1378961021 0.1606356529
[51] 0.4229368522 -0.3982031522 -0.2307621988 0.2939086065 0.3332634606
[56] -0.1044333868 0.1397937861 -0.1806619171 0.0426321695 0.0475432063
[61] 0.3865108355 -0.0768159008 0.4529110426 -0.1719795829 0.3939572391
[66] 0.2526150820 0.3843282856 -0.0003572948 0.2140189704 -0.0094990539
[71] -0.3195943863 0.0228441149 0.2706061322 0.2129860712 -0.0773668986
[76] 0.4816901129 -0.0102526542 -0.2582885535 0.3453667347 0.4385134637
[81] 0.0583102527 -0.0077835199 0.1986372408 -0.0929970057 -0.2455331536
[86] -0.1703410558 0.1193525296 0.5011258935 -0.4807686806 0.6845714733
[91] -0.2243235708 0.1788021185 0.2350515334 -0.1030906979 -0.9218851477
[96] -0.6349979356 0.0367410487 -0.0603571412 -0.4969046643 -0.1075200570
[101] -0.2528871955 0.0487849699 -0.2336077078 -0.2757428481 0.4382621554
[106] -0.5626751791 0.1628386646 0.1103580811 -0.2560958121 -0.2806193927
[111] -0.0319836978 0.2070929242 -0.1930897851 0.1232235803 -0.1085470083
[116] 0.3258697608 0.2259360216 -0.1783952985 -0.3033991018 0.6002546984
[121] 0.0139232762 -0.2615573300 -0.0775057816 0.1760684378 0.1762691426
[126] 0.7123082673 0.4997175775 0.2164198786 0.3195715992 -0.0579919211
[131] -0.1439902753 0.0741650152 0.1286194173 -0.3925260970 -0.1390142130
[136] 0.1820963103 -0.5482746968 0.0460317539 -0.3424193546 0.2575280155
[141] -0.5214150219 0.0985732985 -0.0265498998 -0.1730734105 0.4561691013
[146] 0.2152530175 0.2553191790 0.3842242719 0.2851234931 -0.1855807930
[151] 0.1389223983 0.1735011598 -0.1398925603 -0.2533116398 -0.0631671300
[156] 0.2260817857 -0.3557780601 0.0866012988 0.1640494852 -0.2528259114
[161] -0.2163116637 -0.2499767664 -0.3523696822 0.3028103565 -0.5632539062
[166] 0.1203940206 0.2521948895 0.1175944245 0.0994128049 -0.4684181466
[171] -0.2630871337 0.6489204515 -0.2210521880 0.2715702348 0.0877961100
[176] 0.0478868522 0.2545545119 0.5936045680 -0.5415097561 -0.0641607191
[181] 0.5631204431 0.2701403079 0.1484026187 -0.1353480693 0.3407899270
[186] 0.2472799910 -0.1002829521 -0.4969200435 -0.6238742836 0.4590296542
[191] -0.3777856913 -0.0271012390 -0.2341384002 0.3645462513 0.0064473196
[196] 0.2952476631 0.7286410732 0.2337536170 -0.4924815213 -0.1684067623
[201] -0.3083113549 -0.7664622212 -0.1239279593 0.2913123295 0.0328480967
[206] 0.0029451886 -0.0903859041 0.2633755113 -0.3516127917 -0.8167214181
[211] 0.3066510213 -0.0096168036 -0.2125314525 -0.5433976963 -0.0821695931
[216] -0.1999206763 0.0307470129 0.6067477935 0.1788953595 0.6237128361
[221] -0.0145099507 -0.1322090551 0.5613746915 -0.3245750995 0.0913045707
[226] -0.1286001775 -0.1812064399 0.0807537789 -0.2713331044 0.4589044823
>
> proc.time()
user system elapsed
3.26 9.07 13.35
|
|
BufferedMatrix.Rcheck/tests_i386/rawCalltesting.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 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: 0x028d95b0>
> .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: 0x028d95b0>
> .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: 0x028d95b0>
> .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: 0x028d95b0>
> 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: 0x01f59048>
> .Call("R_bm_AddColumn",P)
<pointer: 0x01f59048>
> .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: 0x01f59048>
> .Call("R_bm_AddColumn",P)
<pointer: 0x01f59048>
> .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: 0x01f59048>
> 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: 0x0218c6f8>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0218c6f8>
> .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: 0x0218c6f8>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x0218c6f8>
> .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: 0x0218c6f8>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x0218c6f8>
> .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: 0x0218c6f8>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x0218c6f8>
> .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: 0x0218c6f8>
> 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: 0x035aad40>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x035aad40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x035aad40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x035aad40>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile28dc1b8533d4" "BufferedMatrixFile28dc51b3d21"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile28dc1b8533d4" "BufferedMatrixFile28dc51b3d21"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x01ecc118>
> .Call("R_bm_AddColumn",P)
<pointer: 0x01ecc118>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x01ecc118>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x01ecc118>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x01ecc118>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x01ecc118>
> .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: 0x03906dd8>
> .Call("R_bm_AddColumn",P)
<pointer: 0x03906dd8>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x03906dd8>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x03906dd8>
> 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: 0x03a7f400>
> .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: 0x03a7f400>
> rm(P)
>
> proc.time()
user system elapsed
0.59 0.07 0.65
|
BufferedMatrix.Rcheck/tests_x64/rawCalltesting.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 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: 0x0000000004ea21f8>
> .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: 0x0000000004ea21f8>
> .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: 0x0000000004ea21f8>
> .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: 0x0000000004ea21f8>
> 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: 0x00000000062f3ce0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x00000000062f3ce0>
> .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: 0x00000000062f3ce0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x00000000062f3ce0>
> .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: 0x00000000062f3ce0>
> 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: 0x0000000007ae39a8>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000007ae39a8>
> .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: 0x0000000007ae39a8>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x0000000007ae39a8>
> .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: 0x0000000007ae39a8>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x0000000007ae39a8>
> .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: 0x0000000007ae39a8>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x0000000007ae39a8>
> .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: 0x0000000007ae39a8>
> 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: 0x00000000063db198>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x00000000063db198>
> .Call("R_bm_AddColumn",P)
<pointer: 0x00000000063db198>
> .Call("R_bm_AddColumn",P)
<pointer: 0x00000000063db198>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2098172a4bd8" "BufferedMatrixFile20987cc519eb"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2098172a4bd8" "BufferedMatrixFile20987cc519eb"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000004e189b8>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000004e189b8>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x0000000004e189b8>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x0000000004e189b8>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x0000000004e189b8>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x0000000004e189b8>
> .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: 0x00000000074732d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x00000000074732d0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x00000000074732d0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x00000000074732d0>
> 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: 0x00000000066f80f8>
> .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: 0x00000000066f80f8>
> rm(P)
>
> proc.time()
user system elapsed
0.53 0.09 0.61
|
|
BufferedMatrix.Rcheck/tests_i386/Rcodetesting.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 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
0.53 0.01 0.53
|
BufferedMatrix.Rcheck/tests_x64/Rcodetesting.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 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
0.51 0.04 0.54
|