Ben Bolstad
| Snapshot Date: 2020-04-14 16:46:13 -0400 (Tue, 14 Apr 2020) |
| URL: https://git.bioconductor.org/packages/BufferedMatrix |
| Branch: RELEASE_3_10 |
| Last Commit: c7a0fa5 |
| Last Changed Date: 2019-10-29 13:07:46 -0400 (Tue, 29 Oct 2019) |
| Back to Multiple platform build/check report for BioC 3.10 |
|
This page was generated on 2020-04-15 12:17:54 -0400 (Wed, 15 Apr 2020).
| Package 205/1823 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||
| BufferedMatrix 1.50.0 Ben Bolstad
| malbec1 | Linux (Ubuntu 18.04.4 LTS) / x86_64 | OK | OK | OK | | ||||||
| tokay1 | Windows Server 2012 R2 Standard / x64 | OK | OK | [ OK ] | OK | | ||||||
| merida1 | OS X 10.11.6 El Capitan / x86_64 | OK | OK | OK | OK | |
| Package: BufferedMatrix |
| Version: 1.50.0 |
| Command: C:\Users\biocbuild\bbs-3.10-bioc\R\bin\R.exe CMD check --force-multiarch --install=check:BufferedMatrix.install-out.txt --library=C:\Users\biocbuild\bbs-3.10-bioc\R\library --no-vignettes --timings BufferedMatrix_1.50.0.tar.gz |
| StartedAt: 2020-04-15 01:44:11 -0400 (Wed, 15 Apr 2020) |
| EndedAt: 2020-04-15 01:45:02 -0400 (Wed, 15 Apr 2020) |
| EllapsedTime: 51.2 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### C:\Users\biocbuild\bbs-3.10-bioc\R\bin\R.exe CMD check --force-multiarch --install=check:BufferedMatrix.install-out.txt --library=C:\Users\biocbuild\bbs-3.10-bioc\R\library --no-vignettes --timings BufferedMatrix_1.50.0.tar.gz ### ############################################################################## ############################################################################## * using log directory 'C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck' * using R version 3.6.3 (2020-02-29) * 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 '1.50.0' * 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-3.10-bioc/R/library/BufferedMatrix/libs/i386/BufferedMatrix.dll': Found 'abort', possibly from 'abort' (C), 'runtime' (Fortran) File 'C:/Users/biocbuild/bbs-3.10-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-3.10-bioc/meat/BufferedMatrix.Rcheck/00check.log' for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### C:\cygwin\bin\curl.exe -O https://malbec1.bioconductor.org/BBS/3.10/bioc/src/contrib/BufferedMatrix_1.50.0.tar.gz && rm -rf BufferedMatrix.buildbin-libdir && mkdir BufferedMatrix.buildbin-libdir && C:\Users\biocbuild\bbs-3.10-bioc\R\bin\R.exe CMD INSTALL --merge-multiarch --build --library=BufferedMatrix.buildbin-libdir BufferedMatrix_1.50.0.tar.gz && C:\Users\biocbuild\bbs-3.10-bioc\R\bin\R.exe CMD INSTALL BufferedMatrix_1.50.0.zip && rm BufferedMatrix_1.50.0.tar.gz BufferedMatrix_1.50.0.zip
###
##############################################################################
##############################################################################
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0
100 202k 100 202k 0 0 836k 0 --:--:-- --:--:-- --:--:-- 850k
install for i386
* installing *source* package 'BufferedMatrix' ...
** using staged installation
** libs
C:/Rtools/mingw_32/bin/gcc -I"C:/Users/BIOCBU~1/BBS-3~1.10-/R/include" -DNDEBUG -I"C:/extsoft/include" -O3 -Wall -std=gnu99 -mtune=core2 -c RBufferedMatrix.c -o RBufferedMatrix.o
C:/Rtools/mingw_32/bin/gcc -I"C:/Users/BIOCBU~1/BBS-3~1.10-/R/include" -DNDEBUG -I"C:/extsoft/include" -O3 -Wall -std=gnu99 -mtune=core2 -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){
^
doubleBufferedMatrix.c: 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:/Rtools/mingw_32/bin/gcc -I"C:/Users/BIOCBU~1/BBS-3~1.10-/R/include" -DNDEBUG -I"C:/extsoft/include" -O3 -Wall -std=gnu99 -mtune=core2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
C:/Rtools/mingw_32/bin/gcc -I"C:/Users/BIOCBU~1/BBS-3~1.10-/R/include" -DNDEBUG -I"C:/extsoft/include" -O3 -Wall -std=gnu99 -mtune=core2 -c init_package.c -o init_package.o
C:/Rtools/mingw_32/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-3~1.10-/R/bin/i386 -lR
installing to C:/Users/biocbuild/bbs-3.10-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:/Rtools/mingw_64/bin/gcc -I"C:/Users/BIOCBU~1/BBS-3~1.10-/R/include" -DNDEBUG -I"C:/extsoft/include" -O2 -Wall -std=gnu99 -mtune=core2 -c RBufferedMatrix.c -o RBufferedMatrix.o
C:/Rtools/mingw_64/bin/gcc -I"C:/Users/BIOCBU~1/BBS-3~1.10-/R/include" -DNDEBUG -I"C:/extsoft/include" -O2 -Wall -std=gnu99 -mtune=core2 -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){
^
doubleBufferedMatrix.c: 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:/Rtools/mingw_64/bin/gcc -I"C:/Users/BIOCBU~1/BBS-3~1.10-/R/include" -DNDEBUG -I"C:/extsoft/include" -O2 -Wall -std=gnu99 -mtune=core2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
C:/Rtools/mingw_64/bin/gcc -I"C:/Users/BIOCBU~1/BBS-3~1.10-/R/include" -DNDEBUG -I"C:/extsoft/include" -O2 -Wall -std=gnu99 -mtune=core2 -c init_package.c -o init_package.o
C:/Rtools/mingw_64/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-3~1.10-/R/bin/x64 -lR
installing to C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.buildbin-libdir/BufferedMatrix/libs/x64
** testing if installed package can be loaded
* MD5 sums
packaged installation of 'BufferedMatrix' as BufferedMatrix_1.50.0.zip
* DONE (BufferedMatrix)
* installing to library 'C:/Users/biocbuild/bbs-3.10-bioc/R/library'
package 'BufferedMatrix' successfully unpacked and MD5 sums checked
|
BufferedMatrix.Rcheck/tests_i386/c_code_level_tests.Rout
R version 3.6.3 (2020-02-29) -- "Holding the Windsock"
Copyright (C) 2020 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
0.32 0.06 0.39
|
BufferedMatrix.Rcheck/tests_x64/c_code_level_tests.Rout
R version 3.6.3 (2020-02-29) -- "Holding the Windsock"
Copyright (C) 2020 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
0.40 0.03 0.42
|
|
BufferedMatrix.Rcheck/tests_i386/objectTesting.Rout
R version 3.6.3 (2020-02-29) -- "Holding the Windsock"
Copyright (C) 2020 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-3.10-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 407705 12.5 848897 26 631948 19.3
Vcells 463736 3.6 8388608 64 1454007 11.1
>
>
>
>
> ##
> ## 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] "Wed Apr 15 01:44:37 2020"
> 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] "Wed Apr 15 01:44:37 2020"
>
>
> 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: 0x02e44360>
>
>
>
> 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] "Wed Apr 15 01:44:39 2020"
> 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] "Wed Apr 15 01:44:39 2020"
>
> ColMode(tmp2)
<pointer: 0x02e44360>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 98.99493288 1.0998843 -1.8916242 0.98972272
[2,] 0.01097625 -0.1997131 -0.4928872 -0.27802314
[3,] 1.53553162 -1.3345334 0.2640656 -0.09875082
[4,] 0.02713748 -0.3847570 0.4105852 -0.85120474
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.10-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,] 98.99493288 1.0998843 1.8916242 0.98972272
[2,] 0.01097625 0.1997131 0.4928872 0.27802314
[3,] 1.53553162 1.3345334 0.2640656 0.09875082
[4,] 0.02713748 0.3847570 0.4105852 0.85120474
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.10-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,] 9.9496197 1.0487537 1.3753633 0.9948481
[2,] 0.1047676 0.4468928 0.7020592 0.5272790
[3,] 1.2391657 1.1552201 0.5138732 0.3142464
[4,] 0.1647346 0.6202878 0.6407692 0.9226076
>
> 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-3.10-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,] 223.49113 36.58742 40.64526 35.93820
[2,] 26.05865 29.66864 32.51348 30.55081
[3,] 38.92719 37.88673 30.40280 28.24122
[4,] 26.67448 31.58764 31.81828 35.07728
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x029b6f38>
> exp(tmp5)
<pointer: 0x029b6f38>
> log(tmp5,2)
<pointer: 0x029b6f38>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 465.1675
> Min(tmp5)
[1] 52.98685
> mean(tmp5)
[1] 72.23243
> Sum(tmp5)
[1] 14446.49
> Var(tmp5)
[1] 860.9278
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.57426 69.51196 72.95970 69.65542 69.70612 69.14100 72.03337 68.75327
[9] 67.86284 72.12635
> rowSums(tmp5)
[1] 1811.485 1390.239 1459.194 1393.108 1394.122 1382.820 1440.667 1375.065
[9] 1357.257 1442.527
> rowVars(tmp5)
[1] 7880.62609 105.96707 66.02168 61.07955 92.02936 54.71337
[7] 65.49012 73.61694 78.66429 119.73855
> rowSd(tmp5)
[1] 88.772891 10.294031 8.125372 7.815340 9.593194 7.396849 8.092597
[8] 8.580031 8.869289 10.942511
> rowMax(tmp5)
[1] 465.16751 91.24037 87.58105 82.42807 90.87986 88.10703 81.56669
[8] 85.69144 90.38662 92.67952
> rowMin(tmp5)
[1] 55.36179 54.23767 58.78039 55.51944 57.03592 59.76790 53.96136 56.24217
[9] 55.06860 52.98685
>
> colMeans(tmp5)
[1] 106.36349 67.71173 72.44972 68.67744 69.46042 76.48684 70.71371
[8] 71.82368 66.56731 71.82609 69.67579 65.91068 70.09502 74.27419
[15] 69.73485 68.21384 73.28770 72.55817 71.16311 67.65479
> colSums(tmp5)
[1] 1063.6349 677.1173 724.4972 686.7744 694.6042 764.8684 707.1371
[8] 718.2368 665.6731 718.2609 696.7579 659.1068 700.9502 742.7419
[15] 697.3485 682.1384 732.8770 725.5817 711.6311 676.5479
> colVars(tmp5)
[1] 15999.33774 111.52973 93.03126 51.31314 61.46137 67.34846
[7] 58.02475 61.37819 71.13563 67.08402 51.12177 74.28735
[13] 62.76175 94.40845 141.15632 58.33586 120.45468 118.78685
[19] 108.67496 53.87013
> colSd(tmp5)
[1] 126.488489 10.560764 9.645271 7.163319 7.839730 8.206611
[7] 7.617398 7.834423 8.434194 8.190483 7.149949 8.619011
[13] 7.922231 9.716401 11.880922 7.637791 10.975185 10.898938
[19] 10.424728 7.339627
> colMax(tmp5)
[1] 465.16751 90.38662 84.59778 78.15904 80.38538 91.24037 85.69144
[8] 85.47759 87.58105 83.07573 81.56669 80.02486 84.58202 88.10703
[15] 92.67952 79.13065 90.87986 88.89876 84.93220 78.61077
> colMin(tmp5)
[1] 54.23767 57.54722 53.96136 57.03592 57.26523 62.07493 59.88414 62.79370
[9] 59.34590 58.05655 59.78502 56.81455 59.93708 58.16779 55.36179 55.51928
[17] 58.71744 56.24217 52.98685 57.36670
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 90.57426 69.51196 72.95970 69.65542 69.70612 69.14100 72.03337 68.75327
[9] 67.86284 NA
> rowSums(tmp5)
[1] 1811.485 1390.239 1459.194 1393.108 1394.122 1382.820 1440.667 1375.065
[9] 1357.257 NA
> rowVars(tmp5)
[1] 7880.62609 105.96707 66.02168 61.07955 92.02936 54.71337
[7] 65.49012 73.61694 78.66429 117.62628
> rowSd(tmp5)
[1] 88.772891 10.294031 8.125372 7.815340 9.593194 7.396849 8.092597
[8] 8.580031 8.869289 10.845565
> rowMax(tmp5)
[1] 465.16751 91.24037 87.58105 82.42807 90.87986 88.10703 81.56669
[8] 85.69144 90.38662 NA
> rowMin(tmp5)
[1] 55.36179 54.23767 58.78039 55.51944 57.03592 59.76790 53.96136 56.24217
[9] 55.06860 NA
>
> colMeans(tmp5)
[1] 106.36349 67.71173 72.44972 68.67744 69.46042 76.48684 NA
[8] 71.82368 66.56731 71.82609 69.67579 65.91068 70.09502 74.27419
[15] 69.73485 68.21384 73.28770 72.55817 71.16311 67.65479
> colSums(tmp5)
[1] 1063.6349 677.1173 724.4972 686.7744 694.6042 764.8684 NA
[8] 718.2368 665.6731 718.2609 696.7579 659.1068 700.9502 742.7419
[15] 697.3485 682.1384 732.8770 725.5817 711.6311 676.5479
> colVars(tmp5)
[1] 15999.33774 111.52973 93.03126 51.31314 61.46137 67.34846
[7] NA 61.37819 71.13563 67.08402 51.12177 74.28735
[13] 62.76175 94.40845 141.15632 58.33586 120.45468 118.78685
[19] 108.67496 53.87013
> colSd(tmp5)
[1] 126.488489 10.560764 9.645271 7.163319 7.839730 8.206611
[7] NA 7.834423 8.434194 8.190483 7.149949 8.619011
[13] 7.922231 9.716401 11.880922 7.637791 10.975185 10.898938
[19] 10.424728 7.339627
> colMax(tmp5)
[1] 465.16751 90.38662 84.59778 78.15904 80.38538 91.24037 NA
[8] 85.47759 87.58105 83.07573 81.56669 80.02486 84.58202 88.10703
[15] 92.67952 79.13065 90.87986 88.89876 84.93220 78.61077
> colMin(tmp5)
[1] 54.23767 57.54722 53.96136 57.03592 57.26523 62.07493 NA 62.79370
[9] 59.34590 58.05655 59.78502 56.81455 59.93708 58.16779 55.36179 55.51928
[17] 58.71744 56.24217 52.98685 57.36670
>
> Max(tmp5,na.rm=TRUE)
[1] 465.1675
> Min(tmp5,na.rm=TRUE)
[1] 52.98685
> mean(tmp5,na.rm=TRUE)
[1] 72.29448
> Sum(tmp5,na.rm=TRUE)
[1] 14386.6
> Var(tmp5,na.rm=TRUE)
[1] 864.5019
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.57426 69.51196 72.95970 69.65542 69.70612 69.14100 72.03337 68.75327
[9] 67.86284 72.77067
> rowSums(tmp5,na.rm=TRUE)
[1] 1811.485 1390.239 1459.194 1393.108 1394.122 1382.820 1440.667 1375.065
[9] 1357.257 1382.643
> rowVars(tmp5,na.rm=TRUE)
[1] 7880.62609 105.96707 66.02168 61.07955 92.02936 54.71337
[7] 65.49012 73.61694 78.66429 117.62628
> rowSd(tmp5,na.rm=TRUE)
[1] 88.772891 10.294031 8.125372 7.815340 9.593194 7.396849 8.092597
[8] 8.580031 8.869289 10.845565
> rowMax(tmp5,na.rm=TRUE)
[1] 465.16751 91.24037 87.58105 82.42807 90.87986 88.10703 81.56669
[8] 85.69144 90.38662 92.67952
> rowMin(tmp5,na.rm=TRUE)
[1] 55.36179 54.23767 58.78039 55.51944 57.03592 59.76790 53.96136 56.24217
[9] 55.06860 52.98685
>
> colMeans(tmp5,na.rm=TRUE)
[1] 106.36349 67.71173 72.44972 68.67744 69.46042 76.48684 71.91699
[8] 71.82368 66.56731 71.82609 69.67579 65.91068 70.09502 74.27419
[15] 69.73485 68.21384 73.28770 72.55817 71.16311 67.65479
> colSums(tmp5,na.rm=TRUE)
[1] 1063.6349 677.1173 724.4972 686.7744 694.6042 764.8684 647.2529
[8] 718.2368 665.6731 718.2609 696.7579 659.1068 700.9502 742.7419
[15] 697.3485 682.1384 732.8770 725.5817 711.6311 676.5479
> colVars(tmp5,na.rm=TRUE)
[1] 15999.33774 111.52973 93.03126 51.31314 61.46137 67.34846
[7] 48.98903 61.37819 71.13563 67.08402 51.12177 74.28735
[13] 62.76175 94.40845 141.15632 58.33586 120.45468 118.78685
[19] 108.67496 53.87013
> colSd(tmp5,na.rm=TRUE)
[1] 126.488489 10.560764 9.645271 7.163319 7.839730 8.206611
[7] 6.999216 7.834423 8.434194 8.190483 7.149949 8.619011
[13] 7.922231 9.716401 11.880922 7.637791 10.975185 10.898938
[19] 10.424728 7.339627
> colMax(tmp5,na.rm=TRUE)
[1] 465.16751 90.38662 84.59778 78.15904 80.38538 91.24037 85.69144
[8] 85.47759 87.58105 83.07573 81.56669 80.02486 84.58202 88.10703
[15] 92.67952 79.13065 90.87986 88.89876 84.93220 78.61077
> colMin(tmp5,na.rm=TRUE)
[1] 54.23767 57.54722 53.96136 57.03592 57.26523 62.07493 62.98092 62.79370
[9] 59.34590 58.05655 59.78502 56.81455 59.93708 58.16779 55.36179 55.51928
[17] 58.71744 56.24217 52.98685 57.36670
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.57426 69.51196 72.95970 69.65542 69.70612 69.14100 72.03337 68.75327
[9] 67.86284 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1811.485 1390.239 1459.194 1393.108 1394.122 1382.820 1440.667 1375.065
[9] 1357.257 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 7880.62609 105.96707 66.02168 61.07955 92.02936 54.71337
[7] 65.49012 73.61694 78.66429 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 88.772891 10.294031 8.125372 7.815340 9.593194 7.396849 8.092597
[8] 8.580031 8.869289 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 465.16751 91.24037 87.58105 82.42807 90.87986 88.10703 81.56669
[8] 85.69144 90.38662 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 55.36179 54.23767 58.78039 55.51944 57.03592 59.76790 53.96136 56.24217
[9] 55.06860 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 111.45423 68.47826 72.38175 68.10148 68.85017 78.08816 NaN
[8] 70.30657 66.68347 72.12256 69.74045 66.36817 69.04275 74.33539
[15] 67.18545 67.00086 71.74450 70.74255 73.18270 67.15785
> colSums(tmp5,na.rm=TRUE)
[1] 1003.0880 616.3044 651.4358 612.9133 619.6515 702.7934 0.0000
[8] 632.7592 600.1512 649.1030 627.6641 597.3135 621.3847 669.0185
[15] 604.6690 603.0078 645.7005 636.6829 658.6443 604.4206
> colVars(tmp5,na.rm=TRUE)
[1] 17707.70408 118.86084 104.60819 53.99523 64.95450 46.91937
[7] NA 43.15749 79.87578 74.48075 57.46495 81.21871
[13] 58.15023 106.16737 85.68171 49.07552 108.71992 96.54980
[19] 76.37372 57.82572
> colSd(tmp5,na.rm=TRUE)
[1] 133.070298 10.902332 10.227815 7.348145 8.059435 6.849771
[7] NA 6.569436 8.937325 8.630223 7.580564 9.012142
[13] 7.625630 10.303755 9.256441 7.005392 10.426885 9.825976
[19] 8.739206 7.604323
> colMax(tmp5,na.rm=TRUE)
[1] 465.16751 90.38662 84.59778 78.15904 80.38538 91.24037 -Inf
[8] 81.20138 87.58105 83.07573 81.56669 80.02486 84.58202 88.10703
[15] 80.87594 77.59726 90.87986 88.13336 84.93220 78.61077
> colMin(tmp5,na.rm=TRUE)
[1] 54.23767 57.54722 53.96136 57.03592 57.26523 67.56311 Inf 62.79370
[9] 59.34590 58.05655 59.78502 56.81455 59.93708 58.16779 55.36179 55.51928
[17] 58.71744 56.24217 62.70741 57.36670
>
>
>
>
> 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] 252.4158 241.1550 445.5421 329.6967 336.9602 142.5977 131.0373 149.2582
[9] 133.9126 180.7561
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 252.4158 241.1550 445.5421 329.6967 336.9602 142.5977 131.0373 149.2582
[9] 133.9126 180.7561
>
>
>
> 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] -8.526513e-14 3.979039e-13 -1.421085e-13 5.684342e-14 0.000000e+00
[6] -5.684342e-14 5.684342e-14 -1.136868e-13 -5.684342e-14 -1.705303e-13
[11] 5.684342e-14 -1.136868e-13 2.842171e-14 -7.105427e-14 5.684342e-14
[16] 1.136868e-13 1.705303e-13 2.842171e-14 -1.705303e-13 8.526513e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
3 18
4 14
5 4
4 3
4 2
4 7
10 14
6 9
3 20
2 14
8 6
2 15
3 5
2 8
10 7
2 3
1 20
3 11
5 7
7 3
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] 2.135621
> Min(tmp)
[1] -2.160954
> mean(tmp)
[1] -0.002170002
> Sum(tmp)
[1] -0.2170002
> Var(tmp)
[1] 0.8272617
>
> rowMeans(tmp)
[1] -0.002170002
> rowSums(tmp)
[1] -0.2170002
> rowVars(tmp)
[1] 0.8272617
> rowSd(tmp)
[1] 0.9095393
> rowMax(tmp)
[1] 2.135621
> rowMin(tmp)
[1] -2.160954
>
> colMeans(tmp)
[1] 0.47736760 -0.70314633 -0.52442045 0.31544600 0.63341256 1.94960942
[7] -0.58785104 0.11841478 -0.96918586 0.40568558 -1.36626828 0.91540155
[13] -0.23075084 -0.68636222 0.79895983 -0.92907177 -0.47462242 -0.12893972
[19] 0.03935164 -1.43658404 0.50162863 0.73838371 0.97386231 -0.01489085
[25] 0.34626361 -1.18737708 -0.87917393 -0.60467380 -1.34045050 -0.18928004
[31] -0.25358115 1.46969606 -0.82791815 -0.37588602 0.54226458 0.83931908
[37] -0.19743243 1.53011774 0.74786664 0.65606112 -0.46548772 -0.64769423
[43] 0.15699202 -1.11755468 -0.05065338 -0.85574841 1.20736715 2.13562135
[49] 0.35032298 -0.88139780 -0.70443290 -0.04803729 1.56350277 0.98007685
[55] 2.10613860 -1.19631845 0.64364841 -0.67000623 0.46967655 0.32080368
[61] -0.83952060 -0.47371488 -1.49455430 0.72238163 -0.21866760 -1.15713743
[67] -0.46886512 -0.04402469 -0.45860031 0.50948802 0.29375098 -1.86927524
[73] 0.99735260 -0.79840677 1.18929906 0.37070077 2.06738969 -0.07458534
[79] -0.34450390 -1.38665544 0.36013761 -0.61179827 0.32985747 -0.73163458
[85] -2.16095371 0.58080885 0.20083899 1.49274300 0.90919650 0.22934703
[91] -0.46363356 0.41198449 0.71432770 0.11269112 -0.64801785 1.54373577
[97] -0.90697861 -0.70209237 -0.85466492 0.06718928
> colSums(tmp)
[1] 0.47736760 -0.70314633 -0.52442045 0.31544600 0.63341256 1.94960942
[7] -0.58785104 0.11841478 -0.96918586 0.40568558 -1.36626828 0.91540155
[13] -0.23075084 -0.68636222 0.79895983 -0.92907177 -0.47462242 -0.12893972
[19] 0.03935164 -1.43658404 0.50162863 0.73838371 0.97386231 -0.01489085
[25] 0.34626361 -1.18737708 -0.87917393 -0.60467380 -1.34045050 -0.18928004
[31] -0.25358115 1.46969606 -0.82791815 -0.37588602 0.54226458 0.83931908
[37] -0.19743243 1.53011774 0.74786664 0.65606112 -0.46548772 -0.64769423
[43] 0.15699202 -1.11755468 -0.05065338 -0.85574841 1.20736715 2.13562135
[49] 0.35032298 -0.88139780 -0.70443290 -0.04803729 1.56350277 0.98007685
[55] 2.10613860 -1.19631845 0.64364841 -0.67000623 0.46967655 0.32080368
[61] -0.83952060 -0.47371488 -1.49455430 0.72238163 -0.21866760 -1.15713743
[67] -0.46886512 -0.04402469 -0.45860031 0.50948802 0.29375098 -1.86927524
[73] 0.99735260 -0.79840677 1.18929906 0.37070077 2.06738969 -0.07458534
[79] -0.34450390 -1.38665544 0.36013761 -0.61179827 0.32985747 -0.73163458
[85] -2.16095371 0.58080885 0.20083899 1.49274300 0.90919650 0.22934703
[91] -0.46363356 0.41198449 0.71432770 0.11269112 -0.64801785 1.54373577
[97] -0.90697861 -0.70209237 -0.85466492 0.06718928
> 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] 0.47736760 -0.70314633 -0.52442045 0.31544600 0.63341256 1.94960942
[7] -0.58785104 0.11841478 -0.96918586 0.40568558 -1.36626828 0.91540155
[13] -0.23075084 -0.68636222 0.79895983 -0.92907177 -0.47462242 -0.12893972
[19] 0.03935164 -1.43658404 0.50162863 0.73838371 0.97386231 -0.01489085
[25] 0.34626361 -1.18737708 -0.87917393 -0.60467380 -1.34045050 -0.18928004
[31] -0.25358115 1.46969606 -0.82791815 -0.37588602 0.54226458 0.83931908
[37] -0.19743243 1.53011774 0.74786664 0.65606112 -0.46548772 -0.64769423
[43] 0.15699202 -1.11755468 -0.05065338 -0.85574841 1.20736715 2.13562135
[49] 0.35032298 -0.88139780 -0.70443290 -0.04803729 1.56350277 0.98007685
[55] 2.10613860 -1.19631845 0.64364841 -0.67000623 0.46967655 0.32080368
[61] -0.83952060 -0.47371488 -1.49455430 0.72238163 -0.21866760 -1.15713743
[67] -0.46886512 -0.04402469 -0.45860031 0.50948802 0.29375098 -1.86927524
[73] 0.99735260 -0.79840677 1.18929906 0.37070077 2.06738969 -0.07458534
[79] -0.34450390 -1.38665544 0.36013761 -0.61179827 0.32985747 -0.73163458
[85] -2.16095371 0.58080885 0.20083899 1.49274300 0.90919650 0.22934703
[91] -0.46363356 0.41198449 0.71432770 0.11269112 -0.64801785 1.54373577
[97] -0.90697861 -0.70209237 -0.85466492 0.06718928
> colMin(tmp)
[1] 0.47736760 -0.70314633 -0.52442045 0.31544600 0.63341256 1.94960942
[7] -0.58785104 0.11841478 -0.96918586 0.40568558 -1.36626828 0.91540155
[13] -0.23075084 -0.68636222 0.79895983 -0.92907177 -0.47462242 -0.12893972
[19] 0.03935164 -1.43658404 0.50162863 0.73838371 0.97386231 -0.01489085
[25] 0.34626361 -1.18737708 -0.87917393 -0.60467380 -1.34045050 -0.18928004
[31] -0.25358115 1.46969606 -0.82791815 -0.37588602 0.54226458 0.83931908
[37] -0.19743243 1.53011774 0.74786664 0.65606112 -0.46548772 -0.64769423
[43] 0.15699202 -1.11755468 -0.05065338 -0.85574841 1.20736715 2.13562135
[49] 0.35032298 -0.88139780 -0.70443290 -0.04803729 1.56350277 0.98007685
[55] 2.10613860 -1.19631845 0.64364841 -0.67000623 0.46967655 0.32080368
[61] -0.83952060 -0.47371488 -1.49455430 0.72238163 -0.21866760 -1.15713743
[67] -0.46886512 -0.04402469 -0.45860031 0.50948802 0.29375098 -1.86927524
[73] 0.99735260 -0.79840677 1.18929906 0.37070077 2.06738969 -0.07458534
[79] -0.34450390 -1.38665544 0.36013761 -0.61179827 0.32985747 -0.73163458
[85] -2.16095371 0.58080885 0.20083899 1.49274300 0.90919650 0.22934703
[91] -0.46363356 0.41198449 0.71432770 0.11269112 -0.64801785 1.54373577
[97] -0.90697861 -0.70209237 -0.85466492 0.06718928
> colMedians(tmp)
[1] 0.47736760 -0.70314633 -0.52442045 0.31544600 0.63341256 1.94960942
[7] -0.58785104 0.11841478 -0.96918586 0.40568558 -1.36626828 0.91540155
[13] -0.23075084 -0.68636222 0.79895983 -0.92907177 -0.47462242 -0.12893972
[19] 0.03935164 -1.43658404 0.50162863 0.73838371 0.97386231 -0.01489085
[25] 0.34626361 -1.18737708 -0.87917393 -0.60467380 -1.34045050 -0.18928004
[31] -0.25358115 1.46969606 -0.82791815 -0.37588602 0.54226458 0.83931908
[37] -0.19743243 1.53011774 0.74786664 0.65606112 -0.46548772 -0.64769423
[43] 0.15699202 -1.11755468 -0.05065338 -0.85574841 1.20736715 2.13562135
[49] 0.35032298 -0.88139780 -0.70443290 -0.04803729 1.56350277 0.98007685
[55] 2.10613860 -1.19631845 0.64364841 -0.67000623 0.46967655 0.32080368
[61] -0.83952060 -0.47371488 -1.49455430 0.72238163 -0.21866760 -1.15713743
[67] -0.46886512 -0.04402469 -0.45860031 0.50948802 0.29375098 -1.86927524
[73] 0.99735260 -0.79840677 1.18929906 0.37070077 2.06738969 -0.07458534
[79] -0.34450390 -1.38665544 0.36013761 -0.61179827 0.32985747 -0.73163458
[85] -2.16095371 0.58080885 0.20083899 1.49274300 0.90919650 0.22934703
[91] -0.46363356 0.41198449 0.71432770 0.11269112 -0.64801785 1.54373577
[97] -0.90697861 -0.70209237 -0.85466492 0.06718928
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.4773676 -0.7031463 -0.5244204 0.315446 0.6334126 1.949609 -0.587851
[2,] 0.4773676 -0.7031463 -0.5244204 0.315446 0.6334126 1.949609 -0.587851
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.1184148 -0.9691859 0.4056856 -1.366268 0.9154016 -0.2307508 -0.6863622
[2,] 0.1184148 -0.9691859 0.4056856 -1.366268 0.9154016 -0.2307508 -0.6863622
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.7989598 -0.9290718 -0.4746224 -0.1289397 0.03935164 -1.436584 0.5016286
[2,] 0.7989598 -0.9290718 -0.4746224 -0.1289397 0.03935164 -1.436584 0.5016286
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.7383837 0.9738623 -0.01489085 0.3462636 -1.187377 -0.8791739 -0.6046738
[2,] 0.7383837 0.9738623 -0.01489085 0.3462636 -1.187377 -0.8791739 -0.6046738
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.340451 -0.18928 -0.2535811 1.469696 -0.8279182 -0.375886 0.5422646
[2,] -1.340451 -0.18928 -0.2535811 1.469696 -0.8279182 -0.375886 0.5422646
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.8393191 -0.1974324 1.530118 0.7478666 0.6560611 -0.4654877 -0.6476942
[2,] 0.8393191 -0.1974324 1.530118 0.7478666 0.6560611 -0.4654877 -0.6476942
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.156992 -1.117555 -0.05065338 -0.8557484 1.207367 2.135621 0.350323
[2,] 0.156992 -1.117555 -0.05065338 -0.8557484 1.207367 2.135621 0.350323
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.8813978 -0.7044329 -0.04803729 1.563503 0.9800768 2.106139 -1.196318
[2,] -0.8813978 -0.7044329 -0.04803729 1.563503 0.9800768 2.106139 -1.196318
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.6436484 -0.6700062 0.4696766 0.3208037 -0.8395206 -0.4737149 -1.494554
[2,] 0.6436484 -0.6700062 0.4696766 0.3208037 -0.8395206 -0.4737149 -1.494554
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.7223816 -0.2186676 -1.157137 -0.4688651 -0.04402469 -0.4586003 0.509488
[2,] 0.7223816 -0.2186676 -1.157137 -0.4688651 -0.04402469 -0.4586003 0.509488
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.293751 -1.869275 0.9973526 -0.7984068 1.189299 0.3707008 2.06739
[2,] 0.293751 -1.869275 0.9973526 -0.7984068 1.189299 0.3707008 2.06739
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.07458534 -0.3445039 -1.386655 0.3601376 -0.6117983 0.3298575 -0.7316346
[2,] -0.07458534 -0.3445039 -1.386655 0.3601376 -0.6117983 0.3298575 -0.7316346
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -2.160954 0.5808089 0.200839 1.492743 0.9091965 0.229347 -0.4636336
[2,] -2.160954 0.5808089 0.200839 1.492743 0.9091965 0.229347 -0.4636336
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.4119845 0.7143277 0.1126911 -0.6480178 1.543736 -0.9069786 -0.7020924
[2,] 0.4119845 0.7143277 0.1126911 -0.6480178 1.543736 -0.9069786 -0.7020924
[,99] [,100]
[1,] -0.8546649 0.06718928
[2,] -0.8546649 0.06718928
>
>
> Max(tmp2)
[1] 1.924187
> Min(tmp2)
[1] -2.721942
> mean(tmp2)
[1] -0.1246906
> Sum(tmp2)
[1] -12.46906
> Var(tmp2)
[1] 0.9330681
>
> rowMeans(tmp2)
[1] -1.738297570 -0.335178199 0.485093238 -0.675266911 -0.813829512
[6] 0.118056473 -1.275147414 0.977873149 -0.070191072 -0.270408513
[11] 1.125273112 -1.440125428 -0.791833026 0.980152382 -0.083028007
[16] 0.395356488 0.604567599 0.710761663 1.055525268 -1.723526350
[21] -0.133555207 1.377507294 0.146226527 0.576175897 -0.054101573
[26] -1.010587282 1.015921235 -0.706760751 -0.939954819 -2.707374817
[31] 0.169965800 -0.241786682 -0.172211473 0.962366502 -1.649553415
[36] -2.721941829 0.464558041 -0.114280617 1.214497621 -1.291069068
[41] -2.369751260 -0.942416769 0.960945809 0.523369852 1.321141804
[46] 0.064881442 -1.028152936 -0.160004463 0.542545069 -0.152303844
[51] -0.703415545 -0.274934821 -0.439634478 1.218036836 -0.761796239
[56] -1.500338134 0.634258115 0.511411419 0.758834897 0.806682410
[61] -1.655811474 0.461690314 -1.319470683 0.795085844 0.014211910
[66] 1.255073072 0.494137696 -0.434703347 -1.010532421 1.389153712
[71] 0.206870134 -0.876365943 0.392212736 0.843600612 0.409356317
[76] -1.124606485 0.523373330 1.924187424 -0.293090864 -0.454377818
[81] -0.596349096 0.052445357 0.003819416 -0.880697552 0.581634511
[86] -0.125313608 -1.952633805 0.450086423 -1.101622399 0.695619148
[91] 0.764111657 0.347831329 0.091357256 -0.889910159 -1.360543069
[96] 0.125121162 0.675450302 0.498305131 -0.306257614 -1.510735174
> rowSums(tmp2)
[1] -1.738297570 -0.335178199 0.485093238 -0.675266911 -0.813829512
[6] 0.118056473 -1.275147414 0.977873149 -0.070191072 -0.270408513
[11] 1.125273112 -1.440125428 -0.791833026 0.980152382 -0.083028007
[16] 0.395356488 0.604567599 0.710761663 1.055525268 -1.723526350
[21] -0.133555207 1.377507294 0.146226527 0.576175897 -0.054101573
[26] -1.010587282 1.015921235 -0.706760751 -0.939954819 -2.707374817
[31] 0.169965800 -0.241786682 -0.172211473 0.962366502 -1.649553415
[36] -2.721941829 0.464558041 -0.114280617 1.214497621 -1.291069068
[41] -2.369751260 -0.942416769 0.960945809 0.523369852 1.321141804
[46] 0.064881442 -1.028152936 -0.160004463 0.542545069 -0.152303844
[51] -0.703415545 -0.274934821 -0.439634478 1.218036836 -0.761796239
[56] -1.500338134 0.634258115 0.511411419 0.758834897 0.806682410
[61] -1.655811474 0.461690314 -1.319470683 0.795085844 0.014211910
[66] 1.255073072 0.494137696 -0.434703347 -1.010532421 1.389153712
[71] 0.206870134 -0.876365943 0.392212736 0.843600612 0.409356317
[76] -1.124606485 0.523373330 1.924187424 -0.293090864 -0.454377818
[81] -0.596349096 0.052445357 0.003819416 -0.880697552 0.581634511
[86] -0.125313608 -1.952633805 0.450086423 -1.101622399 0.695619148
[91] 0.764111657 0.347831329 0.091357256 -0.889910159 -1.360543069
[96] 0.125121162 0.675450302 0.498305131 -0.306257614 -1.510735174
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] -1.738297570 -0.335178199 0.485093238 -0.675266911 -0.813829512
[6] 0.118056473 -1.275147414 0.977873149 -0.070191072 -0.270408513
[11] 1.125273112 -1.440125428 -0.791833026 0.980152382 -0.083028007
[16] 0.395356488 0.604567599 0.710761663 1.055525268 -1.723526350
[21] -0.133555207 1.377507294 0.146226527 0.576175897 -0.054101573
[26] -1.010587282 1.015921235 -0.706760751 -0.939954819 -2.707374817
[31] 0.169965800 -0.241786682 -0.172211473 0.962366502 -1.649553415
[36] -2.721941829 0.464558041 -0.114280617 1.214497621 -1.291069068
[41] -2.369751260 -0.942416769 0.960945809 0.523369852 1.321141804
[46] 0.064881442 -1.028152936 -0.160004463 0.542545069 -0.152303844
[51] -0.703415545 -0.274934821 -0.439634478 1.218036836 -0.761796239
[56] -1.500338134 0.634258115 0.511411419 0.758834897 0.806682410
[61] -1.655811474 0.461690314 -1.319470683 0.795085844 0.014211910
[66] 1.255073072 0.494137696 -0.434703347 -1.010532421 1.389153712
[71] 0.206870134 -0.876365943 0.392212736 0.843600612 0.409356317
[76] -1.124606485 0.523373330 1.924187424 -0.293090864 -0.454377818
[81] -0.596349096 0.052445357 0.003819416 -0.880697552 0.581634511
[86] -0.125313608 -1.952633805 0.450086423 -1.101622399 0.695619148
[91] 0.764111657 0.347831329 0.091357256 -0.889910159 -1.360543069
[96] 0.125121162 0.675450302 0.498305131 -0.306257614 -1.510735174
> rowMin(tmp2)
[1] -1.738297570 -0.335178199 0.485093238 -0.675266911 -0.813829512
[6] 0.118056473 -1.275147414 0.977873149 -0.070191072 -0.270408513
[11] 1.125273112 -1.440125428 -0.791833026 0.980152382 -0.083028007
[16] 0.395356488 0.604567599 0.710761663 1.055525268 -1.723526350
[21] -0.133555207 1.377507294 0.146226527 0.576175897 -0.054101573
[26] -1.010587282 1.015921235 -0.706760751 -0.939954819 -2.707374817
[31] 0.169965800 -0.241786682 -0.172211473 0.962366502 -1.649553415
[36] -2.721941829 0.464558041 -0.114280617 1.214497621 -1.291069068
[41] -2.369751260 -0.942416769 0.960945809 0.523369852 1.321141804
[46] 0.064881442 -1.028152936 -0.160004463 0.542545069 -0.152303844
[51] -0.703415545 -0.274934821 -0.439634478 1.218036836 -0.761796239
[56] -1.500338134 0.634258115 0.511411419 0.758834897 0.806682410
[61] -1.655811474 0.461690314 -1.319470683 0.795085844 0.014211910
[66] 1.255073072 0.494137696 -0.434703347 -1.010532421 1.389153712
[71] 0.206870134 -0.876365943 0.392212736 0.843600612 0.409356317
[76] -1.124606485 0.523373330 1.924187424 -0.293090864 -0.454377818
[81] -0.596349096 0.052445357 0.003819416 -0.880697552 0.581634511
[86] -0.125313608 -1.952633805 0.450086423 -1.101622399 0.695619148
[91] 0.764111657 0.347831329 0.091357256 -0.889910159 -1.360543069
[96] 0.125121162 0.675450302 0.498305131 -0.306257614 -1.510735174
>
> colMeans(tmp2)
[1] -0.1246906
> colSums(tmp2)
[1] -12.46906
> colVars(tmp2)
[1] 0.9330681
> colSd(tmp2)
[1] 0.9659545
> colMax(tmp2)
[1] 1.924187
> colMin(tmp2)
[1] -2.721942
> colMedians(tmp2)
[1] -0.02514108
> colRanges(tmp2)
[,1]
[1,] -2.721942
[2,] 1.924187
>
> 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] -1.467098 3.292754 4.697668 2.211417 2.281349 2.701482 1.680629
[8] 5.685798 -2.139783 1.587564
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.82015102
[2,] -0.92723666
[3,] 0.09520897
[4,] 0.33467340
[5,] 1.39524370
>
> rowApply(tmp,sum)
[1] 2.7229641 2.5413919 0.4805351 2.1147595 4.1742887 3.5326379
[7] 1.0967699 3.8003982 -2.1827570 2.2507923
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 2 6 5 2 9 2 5 1 5
[2,] 2 9 8 1 8 4 1 10 4 9
[3,] 1 3 10 9 7 3 10 9 6 1
[4,] 7 8 1 10 9 6 4 1 5 8
[5,] 10 7 3 6 4 8 6 7 3 4
[6,] 3 10 7 4 3 2 8 2 7 10
[7,] 6 5 4 3 5 7 9 8 2 3
[8,] 8 4 2 7 10 10 5 3 8 6
[9,] 4 1 5 2 1 5 3 6 9 7
[10,] 5 6 9 8 6 1 7 4 10 2
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.35715129 0.70748537 -1.53885181 1.88033199 -2.02900503 -0.28257896
[7] -0.05357554 0.94774186 -3.31962830 -0.17498686 0.33473580 -4.83978477
[13] -4.19515872 0.48458799 1.91403101 1.03456151 0.67770578 -0.03166782
[19] -1.18749140 -2.24574344
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.4175641
[2,] 0.2238247
[3,] 0.5242176
[4,] 0.6017962
[5,] 1.4248769
>
> rowApply(tmp,sum)
[1] -4.118983 -1.212595 -2.801426 1.134577 -2.561714
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 17 20 11 15 6
[2,] 7 14 17 10 15
[3,] 19 3 5 14 4
[4,] 20 10 16 7 12
[5,] 2 16 8 3 8
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.6017962 -0.503836266 1.0292151 1.81392309 -1.4365621 -0.6378857
[2,] 1.4248769 0.364600670 -0.8506429 -0.24629323 0.6779706 -0.2873158
[3,] 0.2238247 0.744572843 -1.0071109 0.68464180 -0.1442773 0.4009669
[4,] 0.5242176 -0.003995218 0.3856465 -0.38596699 -0.7934080 0.5955987
[5,] -0.4175641 0.106143344 -1.0959597 0.01402732 -0.3327282 -0.3539431
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.47219624 0.2143480 -1.186628 -0.3505101 -0.5007453 -1.0371639
[2,] -0.30072663 0.9029283 -1.426059 0.3026624 -0.4307337 -0.2415681
[3,] 0.35114187 -0.7368464 1.118367 0.3858977 0.4539375 -2.5464676
[4,] 0.30640090 0.6991731 -1.556211 0.6723821 0.1108321 -0.8918362
[5,] 0.06180457 -0.1318611 -0.269097 -1.1854190 0.7014453 -0.1227488
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.6642454 0.6178436 -1.19105252 0.05923911 0.03125285 0.5047243
[2,] -1.6553076 0.4965582 0.72895095 0.80289930 -0.50830385 -0.2355789
[3,] -1.4690881 0.8690835 1.22282206 0.18330605 0.07489729 -0.5121006
[4,] -0.7398035 -0.6903058 -0.07231548 -0.09219488 2.27596092 -0.7891960
[5,] 1.3332859 -0.8085914 1.22562599 0.08131192 -1.19610142 1.0004834
[,19] [,20]
[1,] 0.005621965 -0.01612178
[2,] -0.247366687 -0.48414532
[3,] -1.349054690 -1.74993899
[4,] 0.056535185 1.52306288
[5,] 0.346772830 -1.51860022
>
>
> 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-3.10-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-3.10-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-3.10-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-3.10-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 -0.5387224 1.490015 0.1976047 0.4550839 0.8584827 1.430357 1.861909
col8 col9 col10 col11 col12 col13 col14
row1 0.02422767 1.323789 -1.033208 0.1485432 -0.08836496 -0.5514128 -1.783312
col15 col16 col17 col18 col19 col20
row1 -0.1437131 1.206511 0.6720322 0.7935979 0.1547584 0.3591186
> tmp[,"col10"]
col10
row1 -1.0332085
row2 -0.6225583
row3 -1.0373239
row4 0.3698028
row5 -0.9224764
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.5387224 1.490015 0.1976047 0.4550839 0.8584827 1.4303572 1.8619095
row5 0.2771007 0.348464 -0.1493599 -0.1850742 -1.4305724 0.6722151 -0.9475341
col8 col9 col10 col11 col12 col13
row1 0.02422767 1.3237889 -1.0332085 0.1485432 -0.08836496 -0.5514128
row5 -0.51491441 0.8002637 -0.9224764 0.7976127 -0.88275308 -1.4118874
col14 col15 col16 col17 col18 col19 col20
row1 -1.7833118 -0.1437131 1.206511 0.6720322 0.79359790 0.15475840 0.3591186
row5 -0.7911232 -1.4857559 1.109247 0.6444241 0.05913673 0.05187961 -1.2549390
> tmp[,c("col6","col20")]
col6 col20
row1 1.4303572 0.3591186
row2 -0.2962496 0.5810508
row3 -0.7096937 0.3987330
row4 0.9585361 1.5337078
row5 0.6722151 -1.2549390
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.4303572 0.3591186
row5 0.6722151 -1.2549390
>
>
>
>
> 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 50.38642 49.46779 49.23264 48.39607 48.95111 106.3599 52.77584 49.12837
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.39126 49.70275 50.52887 50.58954 50.47725 48.8502 49.5927 49.4082
col17 col18 col19 col20
row1 48.65763 49.84467 49.16733 104.9699
> tmp[,"col10"]
col10
row1 49.70275
row2 29.72344
row3 29.83229
row4 29.70163
row5 51.52700
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.38642 49.46779 49.23264 48.39607 48.95111 106.3599 52.77584 49.12837
row5 49.21226 50.16851 49.28296 50.45863 49.12867 104.8830 51.24807 49.03355
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.39126 49.70275 50.52887 50.58954 50.47725 48.85020 49.59270 49.40820
row5 49.66072 51.52700 50.17532 51.62761 51.17018 50.58672 50.76328 50.16111
col17 col18 col19 col20
row1 48.65763 49.84467 49.16733 104.9699
row5 48.68778 49.54730 50.82067 104.9567
> tmp[,c("col6","col20")]
col6 col20
row1 106.35987 104.96993
row2 74.52811 74.61485
row3 74.36961 75.64592
row4 76.88562 74.14890
row5 104.88296 104.95669
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.3599 104.9699
row5 104.8830 104.9567
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.3599 104.9699
row5 104.8830 104.9567
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.3756349
[2,] -0.3082311
[3,] 0.5410510
[4,] 1.1345573
[5,] 0.5422039
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.9314580 -2.2039437
[2,] -0.4300918 0.2331709
[3,] -1.5096990 -0.4113982
[4,] 0.9843455 1.0513689
[5,] 0.1133128 -0.2693115
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.8881729 0.1226949
[2,] 1.9806650 -0.7211598
[3,] -0.7173054 -0.5225916
[4,] -1.4121033 -0.2283347
[5,] 0.7946954 0.4698591
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.8881729
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.8881729
[2,] 1.9806650
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 0.4185524 -1.520893 -0.3061985 0.1215989 0.08636223 0.01511035
row1 -0.2266337 -1.321734 1.1128717 -0.6773445 0.45465292 -0.86769237
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -1.972580 0.3485289 -0.22333824 -0.6368208 -1.5955402 0.6447133
row1 1.581118 -0.5961485 0.02509949 -1.1381047 -0.3467369 -0.7129896
[,13] [,14] [,15] [,16] [,17] [,18]
row3 0.09544286 -1.3274894 0.97460418 0.0412825 1.3842968 0.8007601
row1 -0.32310646 0.4098304 -0.01143957 -0.9798550 0.4739665 1.2385248
[,19] [,20]
row3 -0.6124766 1.6560540
row1 -1.2303990 -0.8601404
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.3658 0.2266522 0.8300281 0.0536519 -1.757097 0.2567962 0.6024191
[,8] [,9] [,10]
row2 0.07593519 0.8709846 0.4290317
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -1.20469 1.288578 0.1427191 1.397306 -1.762116 1.261457 -0.3817961
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.0736297 0.9596973 0.2989863 0.1881306 -1.136585 -1.012172 -0.4585289
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.393934 2.111623 0.07141428 -0.9257952 1.09414 2.188522
>
>
> 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: 0x034df3b0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM1370d422380"
[2] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM13703d4e6b2b"
[3] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM13707ea3afc"
[4] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM1370395852ce"
[5] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM137038c14b48"
[6] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM1370797e6aa5"
[7] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM13708ea6512"
[8] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM137091a1cd8"
[9] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM137045d118e2"
[10] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM13706a115c5f"
[11] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM137023311095"
[12] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM1370259e3a18"
[13] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM137068b33d0c"
[14] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM13705a515017"
[15] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_i386\\BM137010123c25"
>
>
> ### 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: 0x035f8f18>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x035f8f18>
Warning message:
In dir.create(new.directory) :
'C:\Users\biocbuild\bbs-3.10-bioc\meat\BufferedMatrix.Rcheck\tests_i386' already exists
>
>
> RowMode(tmp)
<pointer: 0x035f8f18>
> rowMedians(tmp)
[1] -0.194324542 0.262277821 0.027836422 -0.477649146 0.083326371
[6] 0.108892943 0.085804135 -0.589827447 -0.532613468 0.167024657
[11] -0.327782085 -0.708010010 -0.104552337 -0.191250515 0.090284286
[16] -0.189144044 -0.499750205 0.330309381 -0.152848298 0.457643777
[21] 0.150342329 -0.268575096 -0.172624394 0.526188431 -0.428729204
[26] -0.032533315 -0.157672025 0.244001618 -0.272712225 -0.315772093
[31] 0.407430579 0.209740611 -0.545698186 -0.457230609 0.168471734
[36] 0.019997464 -0.470047002 -0.037883603 -0.151043403 -0.147815267
[41] -0.092504302 0.158544241 -0.534141972 -0.336244433 -0.692415135
[46] -0.292120674 0.466035224 0.357522550 -0.022673744 -0.066007107
[51] -0.125092993 0.504782497 -0.360916149 0.017392009 0.333820183
[56] 0.345639697 0.614775125 0.386070428 -0.292885824 0.165650428
[61] 0.166377483 0.121304693 -0.123819851 0.507102982 0.161633812
[66] 0.244072152 -0.356678312 -0.132964696 -0.315844180 -0.613922977
[71] -0.116762992 -0.209680375 -0.028278180 -0.257769680 0.087720576
[76] -0.402969054 -0.381462948 -0.367433442 -0.162149562 -0.427917045
[81] 0.004561175 0.331142172 -0.127220526 -0.173920595 0.005098911
[86] 0.617955657 0.158820563 0.490472157 0.318300282 -0.191159609
[91] 0.003642331 0.021532903 -0.150373352 0.078838336 0.463882602
[96] 0.019712717 0.289306791 -0.207509302 -0.561891223 0.308455990
[101] -0.528108440 -0.121581224 -0.043431797 -0.315139012 0.165079539
[106] -0.342927170 -0.620021641 -0.377272621 0.668584873 -0.508283790
[111] -0.277771372 0.487061891 -0.184845783 -0.074668455 -0.466810797
[116] -0.082382499 -0.372427663 0.014655061 0.327766647 0.058297255
[121] -0.247823848 0.073098490 0.165480862 0.010432030 -0.202406455
[126] -0.310731328 0.198832082 -0.694310000 0.355951022 0.227837296
[131] -0.221547492 -0.011789714 -0.265495236 -0.222326210 0.047565116
[136] -0.044198495 -0.020518389 0.430670454 0.003397252 -0.096170877
[141] 0.131568380 -0.462300486 0.082311156 -0.312049706 0.116903336
[146] -0.346022757 -0.452847847 0.404332085 0.044692420 0.268902209
[151] 0.260992925 0.409659146 -0.014414011 -0.729126600 -0.341318699
[156] -0.096244557 -0.776857975 0.008455482 -0.447461657 0.468511056
[161] -0.131880803 -0.729933827 -0.141130176 -0.427232577 0.167147485
[166] 0.275489032 -0.085425772 0.130286515 -0.064260105 -0.535843460
[171] -0.732144618 0.635473656 -0.286697236 0.278128983 0.498113370
[176] -0.105397782 -0.035399260 0.115500226 0.590435301 0.376296606
[181] 0.228791941 -0.213436119 0.206616639 0.249763567 -0.254007543
[186] -0.313476900 -0.053750470 -0.213589028 -0.117659380 0.010318425
[191] 0.083224847 -0.330527264 -0.221702117 0.046764432 0.325843552
[196] 0.060102460 0.050148590 0.314632491 0.085539460 0.180055120
[201] 0.101564142 -0.409652577 -0.065395095 0.256712350 0.351589757
[206] 0.188692058 0.276073965 -0.053353314 0.198881174 0.099129618
[211] -0.115500183 0.244489426 -0.953116958 -0.600822484 0.181051018
[216] 0.601962335 -0.608021058 0.184741941 -0.371059690 0.207012630
[221] -0.282667165 -0.170739897 0.419023334 0.124219633 0.085493538
[226] -0.052154096 -0.207585269 0.038830472 0.103393596 -0.053588965
>
> proc.time()
user system elapsed
2.51 5.53 8.20
|
BufferedMatrix.Rcheck/tests_x64/objectTesting.Rout
R version 3.6.3 (2020-02-29) -- "Holding the Windsock"
Copyright (C) 2020 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "C:/Users/biocbuild/bbs-3.10-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 407706 21.8 848900 45.4 631948 33.8
Vcells 702675 5.4 8388608 64.0 1654061 12.7
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Wed Apr 15 01:44:47 2020"
> 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] "Wed Apr 15 01:44:47 2020"
>
>
> 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: 0x00000000052513d8>
>
>
>
> 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] "Wed Apr 15 01:44:49 2020"
> 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] "Wed Apr 15 01:44:50 2020"
>
> ColMode(tmp2)
<pointer: 0x00000000052513d8>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.3154318 -0.4847591 -1.0154669 -0.63458153
[2,] 0.2665363 -1.4367694 -2.3947566 0.09206839
[3,] 1.7617662 -1.6328784 0.8983751 0.67193796
[4,] -1.7772421 1.1246363 1.7699745 -0.40349627
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.10-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,] 100.3154318 0.4847591 1.0154669 0.63458153
[2,] 0.2665363 1.4367694 2.3947566 0.09206839
[3,] 1.7617662 1.6328784 0.8983751 0.67193796
[4,] 1.7772421 1.1246363 1.7699745 0.40349627
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.10-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,] 10.0157592 0.6962465 1.0077038 0.7966063
[2,] 0.5162715 1.1986531 1.5475001 0.3034277
[3,] 1.3273154 1.2778413 0.9478265 0.8197182
[4,] 1.3331325 1.0604887 1.3304039 0.6352136
>
> 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-3.10-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,] 225.47302 32.44722 36.09250 33.60064
[2,] 30.42925 38.42330 42.86976 28.12635
[3,] 40.03492 39.41129 35.37664 33.86912
[4,] 40.10857 36.72952 40.07401 31.75563
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x0000000007840980>
> exp(tmp5)
<pointer: 0x0000000007840980>
> log(tmp5,2)
<pointer: 0x0000000007840980>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.2926
> Min(tmp5)
[1] 52.35304
> mean(tmp5)
[1] 73.51119
> Sum(tmp5)
[1] 14702.24
> Var(tmp5)
[1] 857.1944
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.31384 69.26160 72.15375 72.47321 72.91550 70.69149 72.32030 73.88853
[9] 71.71298 70.38068
> rowSums(tmp5)
[1] 1786.277 1385.232 1443.075 1449.464 1458.310 1413.830 1446.406 1477.771
[9] 1434.260 1407.614
> rowVars(tmp5)
[1] 8066.66079 89.44874 44.51821 51.08445 59.59017 65.03998
[7] 75.66491 48.27755 97.37954 71.26382
> rowSd(tmp5)
[1] 89.814591 9.457734 6.672197 7.147339 7.719467 8.064737 8.698558
[8] 6.948205 9.868107 8.441790
> rowMax(tmp5)
[1] 469.29256 89.22778 83.32744 83.48073 86.58863 84.14798 89.40918
[8] 85.75166 85.06803 85.92481
> rowMin(tmp5)
[1] 57.90080 55.00643 60.18096 60.08047 55.44932 56.23429 58.57019 57.69371
[9] 52.35304 55.41419
>
> colMeans(tmp5)
[1] 113.26337 72.70586 72.27735 69.35390 69.53090 73.44709 69.90825
[8] 73.68518 65.08073 74.43114 73.35049 75.17175 75.45821 70.28109
[15] 75.12389 73.00662 67.04240 69.15634 70.67533 67.27388
> colSums(tmp5)
[1] 1132.6337 727.0586 722.7735 693.5390 695.3090 734.4709 699.0825
[8] 736.8518 650.8073 744.3114 733.5049 751.7175 754.5821 702.8109
[15] 751.2389 730.0662 670.4240 691.5634 706.7533 672.7388
> colVars(tmp5)
[1] 15696.13415 45.80406 115.14147 57.61484 50.54680 94.48939
[7] 43.39491 54.29337 62.13878 45.39286 92.05185 77.12307
[13] 54.68892 44.14420 84.06930 114.38666 73.53042 33.36686
[19] 44.17936 39.82255
> colSd(tmp5)
[1] 125.284213 6.767870 10.730399 7.590444 7.109627 9.720565
[7] 6.587481 7.368404 7.882815 6.737422 9.594366 8.781974
[13] 7.395196 6.644110 9.168931 10.695170 8.574988 5.776405
[19] 6.646756 6.310511
> colMax(tmp5)
[1] 469.29256 82.02944 89.22778 80.30864 77.22652 84.14798 78.49495
[8] 83.19479 81.60244 82.32760 88.68324 86.58863 89.40918 79.86372
[15] 85.06803 86.76307 80.60968 76.54408 80.27610 78.18509
> colMin(tmp5)
[1] 63.33450 58.72630 57.48309 58.54130 56.23429 52.35304 58.57019 62.36521
[9] 55.41419 62.63715 55.44932 63.10857 63.48483 63.61085 56.88271 60.18096
[17] 56.71278 59.63099 57.69371 55.00643
>
>
> ### 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 69.26160 72.15375 72.47321 72.91550 70.69149 72.32030 73.88853
[9] 71.71298 70.38068
> rowSums(tmp5)
[1] NA 1385.232 1443.075 1449.464 1458.310 1413.830 1446.406 1477.771
[9] 1434.260 1407.614
> rowVars(tmp5)
[1] 8492.84800 89.44874 44.51821 51.08445 59.59017 65.03998
[7] 75.66491 48.27755 97.37954 71.26382
> rowSd(tmp5)
[1] 92.156649 9.457734 6.672197 7.147339 7.719467 8.064737 8.698558
[8] 6.948205 9.868107 8.441790
> rowMax(tmp5)
[1] NA 89.22778 83.32744 83.48073 86.58863 84.14798 89.40918 85.75166
[9] 85.06803 85.92481
> rowMin(tmp5)
[1] NA 55.00643 60.18096 60.08047 55.44932 56.23429 58.57019 57.69371
[9] 52.35304 55.41419
>
> colMeans(tmp5)
[1] 113.26337 72.70586 72.27735 NA 69.53090 73.44709 69.90825
[8] 73.68518 65.08073 74.43114 73.35049 75.17175 75.45821 70.28109
[15] 75.12389 73.00662 67.04240 69.15634 70.67533 67.27388
> colSums(tmp5)
[1] 1132.6337 727.0586 722.7735 NA 695.3090 734.4709 699.0825
[8] 736.8518 650.8073 744.3114 733.5049 751.7175 754.5821 702.8109
[15] 751.2389 730.0662 670.4240 691.5634 706.7533 672.7388
> colVars(tmp5)
[1] 15696.13415 45.80406 115.14147 NA 50.54680 94.48939
[7] 43.39491 54.29337 62.13878 45.39286 92.05185 77.12307
[13] 54.68892 44.14420 84.06930 114.38666 73.53042 33.36686
[19] 44.17936 39.82255
> colSd(tmp5)
[1] 125.284213 6.767870 10.730399 NA 7.109627 9.720565
[7] 6.587481 7.368404 7.882815 6.737422 9.594366 8.781974
[13] 7.395196 6.644110 9.168931 10.695170 8.574988 5.776405
[19] 6.646756 6.310511
> colMax(tmp5)
[1] 469.29256 82.02944 89.22778 NA 77.22652 84.14798 78.49495
[8] 83.19479 81.60244 82.32760 88.68324 86.58863 89.40918 79.86372
[15] 85.06803 86.76307 80.60968 76.54408 80.27610 78.18509
> colMin(tmp5)
[1] 63.33450 58.72630 57.48309 NA 56.23429 52.35304 58.57019 62.36521
[9] 55.41419 62.63715 55.44932 63.10857 63.48483 63.61085 56.88271 60.18096
[17] 56.71278 59.63099 57.69371 55.00643
>
> Max(tmp5,na.rm=TRUE)
[1] 469.2926
> Min(tmp5,na.rm=TRUE)
[1] 52.35304
> mean(tmp5,na.rm=TRUE)
[1] 73.52916
> Sum(tmp5,na.rm=TRUE)
[1] 14632.3
> Var(tmp5,na.rm=TRUE)
[1] 861.4588
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.33376 69.26160 72.15375 72.47321 72.91550 70.69149 72.32030 73.88853
[9] 71.71298 70.38068
> rowSums(tmp5,na.rm=TRUE)
[1] 1716.342 1385.232 1443.075 1449.464 1458.310 1413.830 1446.406 1477.771
[9] 1434.260 1407.614
> rowVars(tmp5,na.rm=TRUE)
[1] 8492.84800 89.44874 44.51821 51.08445 59.59017 65.03998
[7] 75.66491 48.27755 97.37954 71.26382
> rowSd(tmp5,na.rm=TRUE)
[1] 92.156649 9.457734 6.672197 7.147339 7.719467 8.064737 8.698558
[8] 6.948205 9.868107 8.441790
> rowMax(tmp5,na.rm=TRUE)
[1] 469.29256 89.22778 83.32744 83.48073 86.58863 84.14798 89.40918
[8] 85.75166 85.06803 85.92481
> rowMin(tmp5,na.rm=TRUE)
[1] 57.90080 55.00643 60.18096 60.08047 55.44932 56.23429 58.57019 57.69371
[9] 52.35304 55.41419
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.26337 72.70586 72.27735 69.28929 69.53090 73.44709 69.90825
[8] 73.68518 65.08073 74.43114 73.35049 75.17175 75.45821 70.28109
[15] 75.12389 73.00662 67.04240 69.15634 70.67533 67.27388
> colSums(tmp5,na.rm=TRUE)
[1] 1132.6337 727.0586 722.7735 623.6036 695.3090 734.4709 699.0825
[8] 736.8518 650.8073 744.3114 733.5049 751.7175 754.5821 702.8109
[15] 751.2389 730.0662 670.4240 691.5634 706.7533 672.7388
> colVars(tmp5,na.rm=TRUE)
[1] 15696.13415 45.80406 115.14147 64.76975 50.54680 94.48939
[7] 43.39491 54.29337 62.13878 45.39286 92.05185 77.12307
[13] 54.68892 44.14420 84.06930 114.38666 73.53042 33.36686
[19] 44.17936 39.82255
> colSd(tmp5,na.rm=TRUE)
[1] 125.284213 6.767870 10.730399 8.047965 7.109627 9.720565
[7] 6.587481 7.368404 7.882815 6.737422 9.594366 8.781974
[13] 7.395196 6.644110 9.168931 10.695170 8.574988 5.776405
[19] 6.646756 6.310511
> colMax(tmp5,na.rm=TRUE)
[1] 469.29256 82.02944 89.22778 80.30864 77.22652 84.14798 78.49495
[8] 83.19479 81.60244 82.32760 88.68324 86.58863 89.40918 79.86372
[15] 85.06803 86.76307 80.60968 76.54408 80.27610 78.18509
> colMin(tmp5,na.rm=TRUE)
[1] 63.33450 58.72630 57.48309 58.54130 56.23429 52.35304 58.57019 62.36521
[9] 55.41419 62.63715 55.44932 63.10857 63.48483 63.61085 56.88271 60.18096
[17] 56.71278 59.63099 57.69371 55.00643
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 69.26160 72.15375 72.47321 72.91550 70.69149 72.32030 73.88853
[9] 71.71298 70.38068
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1385.232 1443.075 1449.464 1458.310 1413.830 1446.406 1477.771
[9] 1434.260 1407.614
> rowVars(tmp5,na.rm=TRUE)
[1] NA 89.44874 44.51821 51.08445 59.59017 65.03998 75.66491 48.27755
[9] 97.37954 71.26382
> rowSd(tmp5,na.rm=TRUE)
[1] NA 9.457734 6.672197 7.147339 7.719467 8.064737 8.698558 6.948205
[9] 9.868107 8.441790
> rowMax(tmp5,na.rm=TRUE)
[1] NA 89.22778 83.32744 83.48073 86.58863 84.14798 89.40918 85.75166
[9] 85.06803 85.92481
> rowMin(tmp5,na.rm=TRUE)
[1] NA 55.00643 60.18096 60.08047 55.44932 56.23429 58.57019 57.69371
[9] 52.35304 55.41419
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 73.70458 73.28044 71.96130 NaN 70.42093 72.74900 70.55395 74.94295
[9] 65.87850 74.05527 74.17485 75.68001 75.47122 70.88555 74.21164 71.47812
[17] 67.95364 70.21471 70.63153 67.56928
> colSums(tmp5,na.rm=TRUE)
[1] 663.3412 659.5240 647.6517 0.0000 633.7883 654.7410 634.9855 674.4866
[9] 592.9065 666.4974 667.5736 681.1201 679.2410 637.9699 667.9047 643.3031
[17] 611.5828 631.9324 635.6838 608.1235
> colVars(tmp5,na.rm=TRUE)
[1] 53.04267 47.81547 128.41041 NA 47.95346 100.81799 44.12879
[8] 43.28258 62.74620 49.47761 95.91321 83.85733 61.52313 45.55184
[15] 85.21568 102.40167 73.38015 24.93603 49.68020 43.81870
> colSd(tmp5,na.rm=TRUE)
[1] 7.283040 6.914873 11.331832 NA 6.924844 10.040816 6.642950
[8] 6.578950 7.921250 7.034032 9.793529 9.157365 7.843668 6.749210
[15] 9.231234 10.119371 8.566222 4.993599 7.048419 6.619570
> colMax(tmp5,na.rm=TRUE)
[1] 83.48073 82.02944 89.22778 -Inf 77.22652 84.14798 78.49495 83.19479
[9] 81.60244 82.32760 88.68324 86.58863 89.40918 79.86372 85.06803 85.92481
[17] 80.60968 76.54408 80.27610 78.18509
> colMin(tmp5,na.rm=TRUE)
[1] 63.33450 58.72630 57.48309 Inf 56.23429 52.35304 58.57019 64.87623
[9] 55.41419 62.63715 55.44932 63.10857 63.48483 63.61085 56.88271 60.18096
[17] 56.71278 62.00212 57.69371 55.00643
>
>
>
>
> 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] 166.7368 142.5909 209.7491 117.9707 230.8507 179.3970 264.9516 224.0158
[9] 261.5984 146.0940
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 166.7368 142.5909 209.7491 117.9707 230.8507 179.3970 264.9516 224.0158
[9] 261.5984 146.0940
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 1.421085e-13 0.000000e+00 0.000000e+00 -8.526513e-14 0.000000e+00
[6] 1.136868e-13 -5.684342e-14 -1.705303e-13 -5.684342e-14 0.000000e+00
[11] 0.000000e+00 -1.136868e-13 -5.684342e-14 5.684342e-14 2.557954e-13
[16] 1.136868e-13 1.989520e-13 2.842171e-14 5.684342e-14 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)
+ }
9 17
5 15
9 12
3 2
8 2
9 19
5 17
2 16
2 10
1 14
7 10
6 19
4 4
3 14
2 8
8 11
5 11
5 4
10 9
2 19
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 3.140662
> Min(tmp)
[1] -2.240285
> mean(tmp)
[1] 0.09684089
> Sum(tmp)
[1] 9.684089
> Var(tmp)
[1] 1.151514
>
> rowMeans(tmp)
[1] 0.09684089
> rowSums(tmp)
[1] 9.684089
> rowVars(tmp)
[1] 1.151514
> rowSd(tmp)
[1] 1.073086
> rowMax(tmp)
[1] 3.140662
> rowMin(tmp)
[1] -2.240285
>
> colMeans(tmp)
[1] 0.816377361 -0.004935786 0.655333824 1.781335622 -0.765896366
[6] -1.144484990 -0.844288740 1.756171535 -1.820861623 1.850918676
[11] 0.230805891 -1.218834082 0.904887897 0.058246081 0.754516503
[16] -0.550353351 -0.450657313 0.589912334 0.107477133 -0.059180220
[21] -0.596863116 1.010564685 -0.657952504 -0.371944059 0.570064307
[26] -1.066297390 0.334931280 -2.240284558 1.598895123 1.547329028
[31] 0.134165969 1.057922214 -0.950460224 -0.343989573 -0.651502277
[36] 1.980503010 -0.564224504 1.194003481 -1.547731745 2.033711238
[41] 0.619490219 1.520989391 -1.049512200 -0.515811722 1.576378627
[46] 0.347202916 2.182149922 0.099396830 0.913267520 1.067738223
[51] 0.139867275 -1.063359018 -0.163237642 0.140846882 0.539327041
[56] 1.390246320 -1.728122997 -0.524934514 -1.104462359 -0.169930041
[61] -1.317557398 0.152058151 -1.098260852 -0.464513018 -0.712484836
[66] -1.647577796 1.076060025 -0.134578183 -1.744277028 -1.244092577
[71] 1.003914986 -1.817037967 -0.207256320 1.683401883 1.133123671
[76] 0.988665118 0.388661089 0.335710256 0.431647302 0.820500489
[81] 0.719367466 0.645435179 -0.262064827 0.098932476 -0.159996445
[86] -0.978573031 -0.784227093 -0.756201178 0.978426007 -0.526866173
[91] -1.359584457 1.260828221 -1.178304488 0.864277637 0.686396068
[96] 1.172637624 -0.181844736 -0.576902324 3.140661668 -0.079276836
> colSums(tmp)
[1] 0.816377361 -0.004935786 0.655333824 1.781335622 -0.765896366
[6] -1.144484990 -0.844288740 1.756171535 -1.820861623 1.850918676
[11] 0.230805891 -1.218834082 0.904887897 0.058246081 0.754516503
[16] -0.550353351 -0.450657313 0.589912334 0.107477133 -0.059180220
[21] -0.596863116 1.010564685 -0.657952504 -0.371944059 0.570064307
[26] -1.066297390 0.334931280 -2.240284558 1.598895123 1.547329028
[31] 0.134165969 1.057922214 -0.950460224 -0.343989573 -0.651502277
[36] 1.980503010 -0.564224504 1.194003481 -1.547731745 2.033711238
[41] 0.619490219 1.520989391 -1.049512200 -0.515811722 1.576378627
[46] 0.347202916 2.182149922 0.099396830 0.913267520 1.067738223
[51] 0.139867275 -1.063359018 -0.163237642 0.140846882 0.539327041
[56] 1.390246320 -1.728122997 -0.524934514 -1.104462359 -0.169930041
[61] -1.317557398 0.152058151 -1.098260852 -0.464513018 -0.712484836
[66] -1.647577796 1.076060025 -0.134578183 -1.744277028 -1.244092577
[71] 1.003914986 -1.817037967 -0.207256320 1.683401883 1.133123671
[76] 0.988665118 0.388661089 0.335710256 0.431647302 0.820500489
[81] 0.719367466 0.645435179 -0.262064827 0.098932476 -0.159996445
[86] -0.978573031 -0.784227093 -0.756201178 0.978426007 -0.526866173
[91] -1.359584457 1.260828221 -1.178304488 0.864277637 0.686396068
[96] 1.172637624 -0.181844736 -0.576902324 3.140661668 -0.079276836
> 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] 0.816377361 -0.004935786 0.655333824 1.781335622 -0.765896366
[6] -1.144484990 -0.844288740 1.756171535 -1.820861623 1.850918676
[11] 0.230805891 -1.218834082 0.904887897 0.058246081 0.754516503
[16] -0.550353351 -0.450657313 0.589912334 0.107477133 -0.059180220
[21] -0.596863116 1.010564685 -0.657952504 -0.371944059 0.570064307
[26] -1.066297390 0.334931280 -2.240284558 1.598895123 1.547329028
[31] 0.134165969 1.057922214 -0.950460224 -0.343989573 -0.651502277
[36] 1.980503010 -0.564224504 1.194003481 -1.547731745 2.033711238
[41] 0.619490219 1.520989391 -1.049512200 -0.515811722 1.576378627
[46] 0.347202916 2.182149922 0.099396830 0.913267520 1.067738223
[51] 0.139867275 -1.063359018 -0.163237642 0.140846882 0.539327041
[56] 1.390246320 -1.728122997 -0.524934514 -1.104462359 -0.169930041
[61] -1.317557398 0.152058151 -1.098260852 -0.464513018 -0.712484836
[66] -1.647577796 1.076060025 -0.134578183 -1.744277028 -1.244092577
[71] 1.003914986 -1.817037967 -0.207256320 1.683401883 1.133123671
[76] 0.988665118 0.388661089 0.335710256 0.431647302 0.820500489
[81] 0.719367466 0.645435179 -0.262064827 0.098932476 -0.159996445
[86] -0.978573031 -0.784227093 -0.756201178 0.978426007 -0.526866173
[91] -1.359584457 1.260828221 -1.178304488 0.864277637 0.686396068
[96] 1.172637624 -0.181844736 -0.576902324 3.140661668 -0.079276836
> colMin(tmp)
[1] 0.816377361 -0.004935786 0.655333824 1.781335622 -0.765896366
[6] -1.144484990 -0.844288740 1.756171535 -1.820861623 1.850918676
[11] 0.230805891 -1.218834082 0.904887897 0.058246081 0.754516503
[16] -0.550353351 -0.450657313 0.589912334 0.107477133 -0.059180220
[21] -0.596863116 1.010564685 -0.657952504 -0.371944059 0.570064307
[26] -1.066297390 0.334931280 -2.240284558 1.598895123 1.547329028
[31] 0.134165969 1.057922214 -0.950460224 -0.343989573 -0.651502277
[36] 1.980503010 -0.564224504 1.194003481 -1.547731745 2.033711238
[41] 0.619490219 1.520989391 -1.049512200 -0.515811722 1.576378627
[46] 0.347202916 2.182149922 0.099396830 0.913267520 1.067738223
[51] 0.139867275 -1.063359018 -0.163237642 0.140846882 0.539327041
[56] 1.390246320 -1.728122997 -0.524934514 -1.104462359 -0.169930041
[61] -1.317557398 0.152058151 -1.098260852 -0.464513018 -0.712484836
[66] -1.647577796 1.076060025 -0.134578183 -1.744277028 -1.244092577
[71] 1.003914986 -1.817037967 -0.207256320 1.683401883 1.133123671
[76] 0.988665118 0.388661089 0.335710256 0.431647302 0.820500489
[81] 0.719367466 0.645435179 -0.262064827 0.098932476 -0.159996445
[86] -0.978573031 -0.784227093 -0.756201178 0.978426007 -0.526866173
[91] -1.359584457 1.260828221 -1.178304488 0.864277637 0.686396068
[96] 1.172637624 -0.181844736 -0.576902324 3.140661668 -0.079276836
> colMedians(tmp)
[1] 0.816377361 -0.004935786 0.655333824 1.781335622 -0.765896366
[6] -1.144484990 -0.844288740 1.756171535 -1.820861623 1.850918676
[11] 0.230805891 -1.218834082 0.904887897 0.058246081 0.754516503
[16] -0.550353351 -0.450657313 0.589912334 0.107477133 -0.059180220
[21] -0.596863116 1.010564685 -0.657952504 -0.371944059 0.570064307
[26] -1.066297390 0.334931280 -2.240284558 1.598895123 1.547329028
[31] 0.134165969 1.057922214 -0.950460224 -0.343989573 -0.651502277
[36] 1.980503010 -0.564224504 1.194003481 -1.547731745 2.033711238
[41] 0.619490219 1.520989391 -1.049512200 -0.515811722 1.576378627
[46] 0.347202916 2.182149922 0.099396830 0.913267520 1.067738223
[51] 0.139867275 -1.063359018 -0.163237642 0.140846882 0.539327041
[56] 1.390246320 -1.728122997 -0.524934514 -1.104462359 -0.169930041
[61] -1.317557398 0.152058151 -1.098260852 -0.464513018 -0.712484836
[66] -1.647577796 1.076060025 -0.134578183 -1.744277028 -1.244092577
[71] 1.003914986 -1.817037967 -0.207256320 1.683401883 1.133123671
[76] 0.988665118 0.388661089 0.335710256 0.431647302 0.820500489
[81] 0.719367466 0.645435179 -0.262064827 0.098932476 -0.159996445
[86] -0.978573031 -0.784227093 -0.756201178 0.978426007 -0.526866173
[91] -1.359584457 1.260828221 -1.178304488 0.864277637 0.686396068
[96] 1.172637624 -0.181844736 -0.576902324 3.140661668 -0.079276836
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.8163774 -0.004935786 0.6553338 1.781336 -0.7658964 -1.144485 -0.8442887
[2,] 0.8163774 -0.004935786 0.6553338 1.781336 -0.7658964 -1.144485 -0.8442887
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.756172 -1.820862 1.850919 0.2308059 -1.218834 0.9048879 0.05824608
[2,] 1.756172 -1.820862 1.850919 0.2308059 -1.218834 0.9048879 0.05824608
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.7545165 -0.5503534 -0.4506573 0.5899123 0.1074771 -0.05918022 -0.5968631
[2,] 0.7545165 -0.5503534 -0.4506573 0.5899123 0.1074771 -0.05918022 -0.5968631
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.010565 -0.6579525 -0.3719441 0.5700643 -1.066297 0.3349313 -2.240285
[2,] 1.010565 -0.6579525 -0.3719441 0.5700643 -1.066297 0.3349313 -2.240285
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.598895 1.547329 0.134166 1.057922 -0.9504602 -0.3439896 -0.6515023
[2,] 1.598895 1.547329 0.134166 1.057922 -0.9504602 -0.3439896 -0.6515023
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.980503 -0.5642245 1.194003 -1.547732 2.033711 0.6194902 1.520989
[2,] 1.980503 -0.5642245 1.194003 -1.547732 2.033711 0.6194902 1.520989
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.049512 -0.5158117 1.576379 0.3472029 2.18215 0.09939683 0.9132675
[2,] -1.049512 -0.5158117 1.576379 0.3472029 2.18215 0.09939683 0.9132675
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 1.067738 0.1398673 -1.063359 -0.1632376 0.1408469 0.539327 1.390246
[2,] 1.067738 0.1398673 -1.063359 -0.1632376 0.1408469 0.539327 1.390246
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -1.728123 -0.5249345 -1.104462 -0.16993 -1.317557 0.1520582 -1.098261
[2,] -1.728123 -0.5249345 -1.104462 -0.16993 -1.317557 0.1520582 -1.098261
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.464513 -0.7124848 -1.647578 1.07606 -0.1345782 -1.744277 -1.244093
[2,] -0.464513 -0.7124848 -1.647578 1.07606 -0.1345782 -1.744277 -1.244093
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.003915 -1.817038 -0.2072563 1.683402 1.133124 0.9886651 0.3886611
[2,] 1.003915 -1.817038 -0.2072563 1.683402 1.133124 0.9886651 0.3886611
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.3357103 0.4316473 0.8205005 0.7193675 0.6454352 -0.2620648 0.09893248
[2,] 0.3357103 0.4316473 0.8205005 0.7193675 0.6454352 -0.2620648 0.09893248
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.1599964 -0.978573 -0.7842271 -0.7562012 0.978426 -0.5268662 -1.359584
[2,] -0.1599964 -0.978573 -0.7842271 -0.7562012 0.978426 -0.5268662 -1.359584
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 1.260828 -1.178304 0.8642776 0.6863961 1.172638 -0.1818447 -0.5769023
[2,] 1.260828 -1.178304 0.8642776 0.6863961 1.172638 -0.1818447 -0.5769023
[,99] [,100]
[1,] 3.140662 -0.07927684
[2,] 3.140662 -0.07927684
>
>
> Max(tmp2)
[1] 2.619972
> Min(tmp2)
[1] -2.296548
> mean(tmp2)
[1] -0.02481071
> Sum(tmp2)
[1] -2.481071
> Var(tmp2)
[1] 1.020214
>
> rowMeans(tmp2)
[1] 0.191081618 -0.051548918 1.291366365 -1.669481252 -0.444617073
[6] 1.351185340 2.619972069 0.446253076 -1.203857484 -0.108777493
[11] 1.392096814 -1.983055042 1.374554802 0.845573921 -1.995480011
[16] 0.290683796 0.851137908 -0.173909165 -0.677269594 -1.803116816
[21] -0.818186249 1.796377216 -0.139089101 -0.479522104 -0.463418425
[26] 0.093570882 -1.037539613 -1.565751455 -1.638141699 -0.102360516
[31] 0.515627914 0.677693520 0.144680772 0.505407868 0.310489594
[36] -1.855315901 1.786314454 0.249252647 -0.272056965 -0.066043178
[41] 1.215544128 -0.054110588 1.505818936 -0.169031626 0.027419230
[46] -0.533267639 -1.181409861 -1.885787833 -0.047131910 -0.091316283
[51] -1.215064675 -2.080630856 -0.829585644 -0.258606831 -1.401558680
[56] 0.814345638 0.728409581 1.535453941 -0.349082618 -1.542476938
[61] -1.546997082 1.121158808 1.260204295 -0.394948859 0.316790683
[66] 0.921039367 1.064595964 0.258249740 0.514063300 -1.087099595
[71] 0.692103946 -0.512519323 0.687562917 -1.006400307 -2.296548494
[76] 1.058761270 0.171764889 -0.045231139 0.307732410 0.456921343
[81] 0.420700210 0.518668515 -0.001283587 -0.212555048 0.832912819
[86] -0.309765213 1.629862009 -0.203749206 0.396223360 0.069005209
[91] 1.684735099 0.370001401 0.184327327 -0.044534260 -0.513975958
[96] -0.570739598 -0.937886801 0.089899276 -0.519997646 0.323164883
> rowSums(tmp2)
[1] 0.191081618 -0.051548918 1.291366365 -1.669481252 -0.444617073
[6] 1.351185340 2.619972069 0.446253076 -1.203857484 -0.108777493
[11] 1.392096814 -1.983055042 1.374554802 0.845573921 -1.995480011
[16] 0.290683796 0.851137908 -0.173909165 -0.677269594 -1.803116816
[21] -0.818186249 1.796377216 -0.139089101 -0.479522104 -0.463418425
[26] 0.093570882 -1.037539613 -1.565751455 -1.638141699 -0.102360516
[31] 0.515627914 0.677693520 0.144680772 0.505407868 0.310489594
[36] -1.855315901 1.786314454 0.249252647 -0.272056965 -0.066043178
[41] 1.215544128 -0.054110588 1.505818936 -0.169031626 0.027419230
[46] -0.533267639 -1.181409861 -1.885787833 -0.047131910 -0.091316283
[51] -1.215064675 -2.080630856 -0.829585644 -0.258606831 -1.401558680
[56] 0.814345638 0.728409581 1.535453941 -0.349082618 -1.542476938
[61] -1.546997082 1.121158808 1.260204295 -0.394948859 0.316790683
[66] 0.921039367 1.064595964 0.258249740 0.514063300 -1.087099595
[71] 0.692103946 -0.512519323 0.687562917 -1.006400307 -2.296548494
[76] 1.058761270 0.171764889 -0.045231139 0.307732410 0.456921343
[81] 0.420700210 0.518668515 -0.001283587 -0.212555048 0.832912819
[86] -0.309765213 1.629862009 -0.203749206 0.396223360 0.069005209
[91] 1.684735099 0.370001401 0.184327327 -0.044534260 -0.513975958
[96] -0.570739598 -0.937886801 0.089899276 -0.519997646 0.323164883
> 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] 0.191081618 -0.051548918 1.291366365 -1.669481252 -0.444617073
[6] 1.351185340 2.619972069 0.446253076 -1.203857484 -0.108777493
[11] 1.392096814 -1.983055042 1.374554802 0.845573921 -1.995480011
[16] 0.290683796 0.851137908 -0.173909165 -0.677269594 -1.803116816
[21] -0.818186249 1.796377216 -0.139089101 -0.479522104 -0.463418425
[26] 0.093570882 -1.037539613 -1.565751455 -1.638141699 -0.102360516
[31] 0.515627914 0.677693520 0.144680772 0.505407868 0.310489594
[36] -1.855315901 1.786314454 0.249252647 -0.272056965 -0.066043178
[41] 1.215544128 -0.054110588 1.505818936 -0.169031626 0.027419230
[46] -0.533267639 -1.181409861 -1.885787833 -0.047131910 -0.091316283
[51] -1.215064675 -2.080630856 -0.829585644 -0.258606831 -1.401558680
[56] 0.814345638 0.728409581 1.535453941 -0.349082618 -1.542476938
[61] -1.546997082 1.121158808 1.260204295 -0.394948859 0.316790683
[66] 0.921039367 1.064595964 0.258249740 0.514063300 -1.087099595
[71] 0.692103946 -0.512519323 0.687562917 -1.006400307 -2.296548494
[76] 1.058761270 0.171764889 -0.045231139 0.307732410 0.456921343
[81] 0.420700210 0.518668515 -0.001283587 -0.212555048 0.832912819
[86] -0.309765213 1.629862009 -0.203749206 0.396223360 0.069005209
[91] 1.684735099 0.370001401 0.184327327 -0.044534260 -0.513975958
[96] -0.570739598 -0.937886801 0.089899276 -0.519997646 0.323164883
> rowMin(tmp2)
[1] 0.191081618 -0.051548918 1.291366365 -1.669481252 -0.444617073
[6] 1.351185340 2.619972069 0.446253076 -1.203857484 -0.108777493
[11] 1.392096814 -1.983055042 1.374554802 0.845573921 -1.995480011
[16] 0.290683796 0.851137908 -0.173909165 -0.677269594 -1.803116816
[21] -0.818186249 1.796377216 -0.139089101 -0.479522104 -0.463418425
[26] 0.093570882 -1.037539613 -1.565751455 -1.638141699 -0.102360516
[31] 0.515627914 0.677693520 0.144680772 0.505407868 0.310489594
[36] -1.855315901 1.786314454 0.249252647 -0.272056965 -0.066043178
[41] 1.215544128 -0.054110588 1.505818936 -0.169031626 0.027419230
[46] -0.533267639 -1.181409861 -1.885787833 -0.047131910 -0.091316283
[51] -1.215064675 -2.080630856 -0.829585644 -0.258606831 -1.401558680
[56] 0.814345638 0.728409581 1.535453941 -0.349082618 -1.542476938
[61] -1.546997082 1.121158808 1.260204295 -0.394948859 0.316790683
[66] 0.921039367 1.064595964 0.258249740 0.514063300 -1.087099595
[71] 0.692103946 -0.512519323 0.687562917 -1.006400307 -2.296548494
[76] 1.058761270 0.171764889 -0.045231139 0.307732410 0.456921343
[81] 0.420700210 0.518668515 -0.001283587 -0.212555048 0.832912819
[86] -0.309765213 1.629862009 -0.203749206 0.396223360 0.069005209
[91] 1.684735099 0.370001401 0.184327327 -0.044534260 -0.513975958
[96] -0.570739598 -0.937886801 0.089899276 -0.519997646 0.323164883
>
> colMeans(tmp2)
[1] -0.02481071
> colSums(tmp2)
[1] -2.481071
> colVars(tmp2)
[1] 1.020214
> colSd(tmp2)
[1] 1.010056
> colMax(tmp2)
[1] 2.619972
> colMin(tmp2)
[1] -2.296548
> colMedians(tmp2)
[1] -0.02290892
> colRanges(tmp2)
[,1]
[1,] -2.296548
[2,] 2.619972
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.3526755 -3.1471759 -2.2303389 -4.6848657 -0.1386485 3.0404466
[7] -1.6619817 -2.5709633 0.6281895 -1.9397446
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.231652995
[2,] -0.469589862
[3,] -0.008106066
[4,] 0.454972816
[5,] 1.312237407
>
> rowApply(tmp,sum)
[1] -0.6785055 0.5288501 -1.5180917 -6.0460345 -2.0301848 1.4010096
[7] 4.7828652 -5.0080077 -2.7866165 -1.7030422
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 7 5 10 2 4 4 3 6 5
[2,] 4 6 3 1 1 6 8 9 9 1
[3,] 2 5 6 4 5 10 9 10 1 4
[4,] 7 1 2 6 9 1 6 7 2 6
[5,] 5 8 1 7 3 7 5 8 10 3
[6,] 6 10 10 8 4 8 7 4 4 2
[7,] 3 2 9 9 6 2 10 2 3 10
[8,] 10 3 4 5 8 3 2 1 7 7
[9,] 8 9 7 2 7 5 3 6 5 9
[10,] 1 4 8 3 10 9 1 5 8 8
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.5933650 3.0708522 -1.4781965 0.7177889 -1.7908948 -4.9246113
[7] 0.7619253 1.6332072 1.4033232 -0.9016917 0.1073329 -2.0476124
[13] -2.7518408 -4.5548274 0.3123033 2.1394028 2.0806037 2.0769557
[19] -0.7772512 2.8979033
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1985794
[2,] -1.0526574
[3,] 0.3319678
[4,] 0.9425270
[5,] 1.5701069
>
> rowApply(tmp,sum)
[1] 2.6071224 -0.1562781 1.3574423 -2.8484719 -2.3917774
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 18 5 3 15 16
[2,] 12 12 5 20 17
[3,] 19 18 6 2 1
[4,] 13 10 8 18 9
[5,] 7 16 2 8 12
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.5701069 0.4321990 1.8768531 0.44728716 -0.640960473 -0.8637336
[2,] -1.0526574 0.1255556 1.2622487 0.06313737 0.794526729 -1.2767569
[3,] -1.1985794 -0.8371329 -0.6987105 -0.48143853 -1.316231338 -0.3086058
[4,] 0.3319678 2.1880605 -1.8621110 1.25067548 -0.635104488 -1.0789851
[5,] 0.9425270 1.1621700 -2.0564769 -0.56187259 0.006874811 -1.3965299
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.8068013 1.3694338 -0.03943903 -0.1510654 -0.6096525 -0.7520880
[2,] 1.8071354 0.8633158 -0.17688150 -0.5884740 -1.5972430 1.2891125
[3,] -0.6245337 -0.9351217 -0.36865729 0.7393330 1.0114312 0.8470039
[4,] -0.2512916 1.1391618 1.31570502 -0.1954183 -0.7725549 -2.0388285
[5,] -0.9761860 -0.8035825 0.67259596 -0.7060669 2.0753522 -1.3928123
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.2949175 -1.05524988 -1.6033703 0.6140376 -0.6759793 1.5657529
[2,] 0.1000414 -1.11661851 -0.8885419 0.3337893 0.5687635 -0.1946926
[3,] -1.6558536 -0.25413668 2.3059044 0.8143205 1.8461957 0.9393841
[4,] -0.7490339 -0.08093676 -0.1630975 -0.9265124 0.4796915 -0.6526088
[5,] -0.1520772 -2.04788559 0.6614085 1.3037677 -0.1380677 0.4191202
[,19] [,20]
[1,] -1.3434786 1.9545853
[2,] 0.7344689 -1.2065073
[3,] 0.4169332 1.1159376
[4,] 0.1942219 -0.3414726
[5,] -0.7793967 1.3753604
>
>
> 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-3.10-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-3.10-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-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_x64
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 589 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: C:/Users/biocbuild/bbs-3.10-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 -1.945115 -0.9091309 0.7658524 0.6683893 -0.4861798 -0.7182272 -0.4712222
col8 col9 col10 col11 col12 col13 col14
row1 -0.8449709 0.8674055 -0.3085495 1.212517 0.8356805 0.2990234 -0.5246808
col15 col16 col17 col18 col19 col20
row1 -0.07053794 0.4477944 -0.2228991 0.8439087 0.2588821 1.381652
> tmp[,"col10"]
col10
row1 -0.3085495
row2 -0.2017414
row3 -0.8530520
row4 2.3210819
row5 -2.0624604
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -1.945115 -0.9091309 0.7658524 0.6683893 -0.4861798 -0.7182272 -0.4712222
row5 1.664584 1.2474776 0.5452608 0.6875178 -0.1734855 0.3863665 0.3035393
col8 col9 col10 col11 col12 col13 col14
row1 -0.8449709 0.86740552 -0.3085495 1.212517 0.8356805 0.2990234 -0.5246808
row5 -1.2642836 -0.03968873 -2.0624604 1.213983 1.6038826 0.1210007 1.6846576
col15 col16 col17 col18 col19 col20
row1 -0.07053794 0.4477944 -0.2228991 0.8439087 0.2588821 1.3816518
row5 1.35507571 -2.2388909 0.9248525 1.4880189 1.9362651 -0.7914821
> tmp[,c("col6","col20")]
col6 col20
row1 -0.7182272 1.3816518
row2 -0.7159260 1.2340923
row3 -1.0965403 0.1644198
row4 -1.2717461 0.9990116
row5 0.3863665 -0.7914821
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.7182272 1.3816518
row5 0.3863665 -0.7914821
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.85653 47.99945 48.44179 50.22986 50.9451 106.3407 51.58004 49.28867
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.51868 49.21693 48.42741 50.79054 50.76063 50.89744 49.27947 50.13433
col17 col18 col19 col20
row1 50.36672 50.46139 52.01763 105.6243
> tmp[,"col10"]
col10
row1 49.21693
row2 29.34767
row3 29.57935
row4 29.12731
row5 48.14758
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.85653 47.99945 48.44179 50.22986 50.94510 106.3407 51.58004 49.28867
row5 49.53646 49.11328 48.73719 49.74526 52.00131 104.8700 50.10343 49.77365
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.51868 49.21693 48.42741 50.79054 50.76063 50.89744 49.27947 50.13433
row5 48.88032 48.14758 50.65688 50.34276 49.25113 50.01830 48.46731 49.13599
col17 col18 col19 col20
row1 50.36672 50.46139 52.01763 105.6243
row5 50.61227 48.29677 49.49057 105.2472
> tmp[,c("col6","col20")]
col6 col20
row1 106.34067 105.62429
row2 75.84335 75.81905
row3 75.44290 73.79321
row4 74.46809 74.55817
row5 104.87000 105.24718
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.3407 105.6243
row5 104.8700 105.2472
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.3407 105.6243
row5 104.8700 105.2472
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.77869184
[2,] -0.87146513
[3,] -2.06961365
[4,] -0.21732243
[5,] -0.06253815
> tmp[,c("col17","col7")]
col17 col7
[1,] -2.522453588 0.8657469
[2,] 0.002985681 0.1917007
[3,] 1.553744028 -1.1436675
[4,] 0.158790426 0.8855300
[5,] 0.761315652 0.6609172
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.2624126 -0.3769302
[2,] -0.1922263 0.4154276
[3,] 1.0254092 0.4259909
[4,] -0.2716356 -0.8955023
[5,] -1.2752274 -0.1998242
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.2624126
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.2624126
[2,] -0.1922263
>
>
>
> 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 1.310478 -0.63112510 -0.1251368 0.9492375 -0.3278290 0.8918406 0.1444202
row1 1.529005 0.07570301 -0.5581717 0.1808425 -0.1494777 -1.0887160 -0.6395873
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.5949876 -0.1756857 -0.2867652 -0.7245582 -0.7589539 -0.2648605
row1 0.2787322 -2.1405610 -0.4207252 -1.1153362 -1.7516513 -1.4419886
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 0.7008772 0.6419777 -0.4034579 -0.2056969 0.7972745 -2.363780 1.9069772
row1 1.2867761 0.3237414 1.6167177 -0.2370326 1.6992933 -1.147707 -0.1966855
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.1953734 -1.328855 -0.7682657 -0.3423856 1.855489 0.2656328 -0.4799835
[,8] [,9] [,10]
row2 -0.9457486 -1.200135 0.1925292
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.207239 -2.263004 -0.1127138 -0.3476189 -0.1447623 -1.715566 0.4465441
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.101269 -0.853284 0.03760334 0.9034665 1.708667 -1.207187 0.07290135
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.02538171 1.008777 0.652652 1.130032 2.123496 0.2666376
>
>
> 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: 0x0000000004f1e530>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM1fa05bd9764f"
[2] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM1fa06ddc3a78"
[3] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM1fa03d7b2f1e"
[4] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM1fa0e552ea5"
[5] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM1fa04a8e7df0"
[6] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM1fa0243f7c17"
[7] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM1fa02b2b2cac"
[8] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM1fa041285910"
[9] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM1fa06aeb29b9"
[10] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM1fa028165e52"
[11] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM1fa014ad4414"
[12] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM1fa0676d43d7"
[13] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM1fa03b936da0"
[14] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM1fa04a1255c1"
[15] "C:/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests_x64\\BM1fa0154e77be"
>
>
> ### 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: 0x0000000005cdf960>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x0000000005cdf960>
Warning message:
In dir.create(new.directory) :
'C:\Users\biocbuild\bbs-3.10-bioc\meat\BufferedMatrix.Rcheck\tests_x64' already exists
>
>
> RowMode(tmp)
<pointer: 0x0000000005cdf960>
> rowMedians(tmp)
[1] -0.0824731839 -0.2220422223 -0.3964814844 0.0623301778 -0.0052697151
[6] 0.0017710246 0.1626357097 0.0058675640 -0.0255060457 0.5574797621
[11] 0.2536327502 -0.0339465017 0.1686494134 0.3715870806 0.0377400834
[16] 0.1895652443 -0.1112304589 0.0809712752 0.2591402924 -0.2610096145
[21] -0.4086520988 0.0335384941 -0.7441895303 0.3840542008 0.0647137562
[26] -0.0081060209 -0.1844756924 0.4639616031 -0.2534284934 0.0540746825
[31] 0.1809181789 0.2090687556 0.0881082379 0.4214777050 0.1073021692
[36] -0.3129256489 -0.1158797299 -0.4009121221 -0.1675521467 0.4071451903
[41] -0.2245337054 -0.2579889324 -0.0818939459 -0.0847147407 0.0861409226
[46] -0.2817248071 0.2385251789 -0.2639545052 0.1219951877 -0.3805382286
[51] -0.2653343003 0.0431270697 0.3642870281 0.2952098384 0.5867267071
[56] -0.3339699204 0.0473815524 0.1386910104 0.1552763172 -0.2373960001
[61] 0.1633632271 0.5385213969 0.0799241272 0.0498751904 -0.6747416810
[66] 0.1485147506 -0.7100400602 0.4774181289 -0.0250675965 -0.3100196292
[71] 0.4740896931 -0.2651472929 0.1238154935 0.0515877654 -0.0237465391
[76] -0.0886544790 -0.1975840452 0.1135095653 0.1558483512 -0.1166284668
[81] -0.3950651267 0.1975439742 -0.1407630564 -0.0213058345 0.0769820335
[86] -0.1802832933 -0.0693963525 0.3289369112 0.0796456457 -0.0983230153
[91] -0.1468758014 -0.7729081093 0.0250155707 0.2774325618 0.1949449792
[96] 0.2044752949 0.0010601074 0.1344900013 0.0405391813 -0.3811161282
[101] -0.2129455587 -0.1003396784 0.4861373272 0.1361427148 -0.2918805909
[106] -0.2755856185 -0.2171806535 -0.1244960081 0.3053648753 -0.3401043421
[111] -0.0815185449 -0.1080325980 0.3124662416 0.1621094192 -0.4618474044
[116] 0.3767061301 0.4264846113 0.0238909336 -0.2605928346 -0.0836720991
[121] -0.1701695265 -0.3819011385 -0.1548979066 -0.3800025815 0.3316144191
[126] -0.0782321175 -0.1057794382 -0.0687983574 -0.1772156581 -0.0611286080
[131] 0.2061776507 0.1943744607 0.3993892058 0.1181850916 0.0931491859
[136] -0.0281502445 -0.1041989684 -0.0606729686 0.4163648227 0.2443429534
[141] 0.4215396090 0.4312535323 -0.0137944455 -0.2288032113 0.0737578200
[146] -0.5884702321 -0.2967157548 -0.0928022137 0.0279730078 0.6449912752
[151] 0.2088248571 -0.3681934030 -0.1110295758 0.0951977333 -0.2579360629
[156] 0.2092165155 0.1307602185 0.0222480675 -0.0455744853 0.2396355977
[161] 0.6386104577 -0.0108009156 0.5628866402 -0.4106836163 0.0522788395
[166] 0.2271549758 0.6156579784 -0.3100988522 -0.2269497329 -0.0373855425
[171] -0.1292307414 0.1098879495 -0.2652314742 -0.2716071165 -0.1470920410
[176] 0.2691431799 0.1569781710 -0.4122883392 0.5649443786 0.0065204412
[181] 0.4678463075 0.3984181530 -0.1379013910 -0.1784783778 0.0041479864
[186] -0.0133340308 0.1361004830 -0.2111076758 0.5886399224 0.7572599463
[191] -0.0551020602 -0.2428776839 -0.0548380205 0.4208723633 -0.0430557878
[196] -0.0864793825 -0.2213143867 0.3021469551 0.0520458623 -0.2891593456
[201] 0.0544382644 -0.0327952287 -0.1393992283 -0.3539739132 -0.0012332355
[206] -0.1951046519 -0.0629549781 -0.5559202610 -0.1429147717 -0.0023920937
[211] 0.0126300541 -0.8017882489 -0.0063948340 0.0170095972 0.2656714676
[216] -0.7276775816 -0.3523560326 -0.0984968046 -0.3540878628 -0.0005457034
[221] -0.1148171775 -0.2191788975 0.2904037365 0.2671823758 -0.2200856263
[226] 0.2079269953 -0.5625199322 0.7178582781 -0.1203381477 -0.2612137523
>
> proc.time()
user system elapsed
2.71 7.79 10.71
|
|
BufferedMatrix.Rcheck/tests_i386/rawCalltesting.Rout
R version 3.6.3 (2020-02-29) -- "Holding the Windsock"
Copyright (C) 2020 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: 0x0364c348>
> .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: 0x0364c348>
> .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: 0x0364c348>
> .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: 0x0364c348>
> 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: 0x03a575e8>
> .Call("R_bm_AddColumn",P)
<pointer: 0x03a575e8>
> .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: 0x03a575e8>
> .Call("R_bm_AddColumn",P)
<pointer: 0x03a575e8>
> .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: 0x03a575e8>
> 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: 0x026d3370>
> .Call("R_bm_AddColumn",P)
<pointer: 0x026d3370>
> .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: 0x026d3370>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x026d3370>
> .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: 0x026d3370>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x026d3370>
> .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: 0x026d3370>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x026d3370>
> .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: 0x026d3370>
> 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: 0x029c9158>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x029c9158>
> .Call("R_bm_AddColumn",P)
<pointer: 0x029c9158>
> .Call("R_bm_AddColumn",P)
<pointer: 0x029c9158>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2b043e074121" "BufferedMatrixFile2b047bd82b32"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2b043e074121" "BufferedMatrixFile2b047bd82b32"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x02ff9210>
> .Call("R_bm_AddColumn",P)
<pointer: 0x02ff9210>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x02ff9210>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x02ff9210>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x02ff9210>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x02ff9210>
> .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: 0x02ff5380>
> .Call("R_bm_AddColumn",P)
<pointer: 0x02ff5380>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x02ff5380>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x02ff5380>
> 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: 0x02e21780>
> .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: 0x02e21780>
> rm(P)
>
> proc.time()
user system elapsed
0.32 0.04 0.35
|
BufferedMatrix.Rcheck/tests_x64/rawCalltesting.Rout
R version 3.6.3 (2020-02-29) -- "Holding the Windsock"
Copyright (C) 2020 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: 0x0000000005e43520>
> .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: 0x0000000005e43520>
> .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: 0x0000000005e43520>
> .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: 0x0000000005e43520>
> 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: 0x0000000007670af8>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000007670af8>
> .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: 0x0000000007670af8>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000007670af8>
> .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: 0x0000000007670af8>
> 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: 0x0000000005fbbf00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000005fbbf00>
> .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: 0x0000000005fbbf00>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x0000000005fbbf00>
> .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: 0x0000000005fbbf00>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x0000000005fbbf00>
> .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: 0x0000000005fbbf00>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x0000000005fbbf00>
> .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: 0x0000000005fbbf00>
> 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: 0x0000000005cedea0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x0000000005cedea0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000005cedea0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000005cedea0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile22185683526d" "BufferedMatrixFile2218585d3fa0"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile22185683526d" "BufferedMatrixFile2218585d3fa0"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000005e24be8>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000005e24be8>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x0000000005e24be8>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x0000000005e24be8>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x0000000005e24be8>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x0000000005e24be8>
> .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: 0x0000000005ac6560>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000000005ac6560>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x0000000005ac6560>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x0000000005ac6560>
> 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: 0x0000000007581930>
> .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: 0x0000000007581930>
> rm(P)
>
> proc.time()
user system elapsed
0.46 0.15 0.60
|
|
BufferedMatrix.Rcheck/tests_i386/Rcodetesting.Rout
R version 3.6.3 (2020-02-29) -- "Holding the Windsock"
Copyright (C) 2020 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
0.37 0.01 0.37
|
BufferedMatrix.Rcheck/tests_x64/Rcodetesting.Rout
R version 3.6.3 (2020-02-29) -- "Holding the Windsock"
Copyright (C) 2020 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.35 0.03 0.37
|