Ben Bolstad
| Snapshot Date: 2024-10-16 14:00 -0400 (Wed, 16 Oct 2024) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_19 |
| git_last_commit: af6c73d |
| git_last_commit_date: 2024-04-30 10:16:21 -0400 (Tue, 30 Apr 2024) |
| Back to Multiple platform build/check report for BioC 3.19: simplified long |
|
This page was generated on 2024-10-18 20:39 -0400 (Fri, 18 Oct 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4763 |
| palomino7 | Windows Server 2022 Datacenter | x64 | 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life" | 4500 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4530 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4480 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 249/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.68.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.68.0 |
| Command: E:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=E:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings BufferedMatrix_1.68.0.tar.gz |
| StartedAt: 2024-10-16 23:33:16 -0400 (Wed, 16 Oct 2024) |
| EndedAt: 2024-10-16 23:49:53 -0400 (Wed, 16 Oct 2024) |
| EllapsedTime: 997.3 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### E:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=E:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings BufferedMatrix_1.68.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck'
* using R version 4.4.1 (2024-06-14 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
gcc.exe (GCC) 13.2.0
GNU Fortran (GCC) 13.2.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* using option '--no-vignettes'
* checking for file 'BufferedMatrix/DESCRIPTION' ... OK
* this is package 'BufferedMatrix' version '1.68.0'
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'BufferedMatrix' can be installed ... OK
* used C compiler: 'gcc.exe (GCC) 13.2.0'
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files for x64 is not available
File 'E:/biocbuild/bbs-3.19-bioc/R/library/BufferedMatrix/libs/x64/BufferedMatrix.dll':
Found '_exit', possibly from '_exit' (C)
Found 'abort', possibly from 'abort' (C), 'runtime' (Fortran)
Compiled code should not call entry points which might terminate R nor
write to stdout/stderr instead of to the console, nor use Fortran I/O
nor system RNGs nor [v]sprintf. The detected symbols are linked into
the code but might come from libraries and not actually be called.
See 'Writing portable packages' in the 'Writing R Extensions' manual.
* checking sizes of PDF files under 'inst/doc' ... OK
* checking files in 'vignettes' ... OK
* checking examples ... NONE
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
Running 'Rcodetesting.R'
Running 'c_code_level_tests.R'
Running 'objectTesting.R'
Running 'rawCalltesting.R'
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
'E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/00check.log'
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### E:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library 'E:/biocbuild/bbs-3.19-bioc/R/library'
* installing *source* package 'BufferedMatrix' ...
** using staged installation
** libs
using C compiler: 'gcc.exe (GCC) 13.2.0'
gcc -I"E:/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -mfpmath=sse -msse2 -mstackrealign -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"E:/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -mfpmath=sse -msse2 -mstackrealign -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function 'dbm_ReadOnlyMode':
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of '!' or change '&' to '&&' or '!' to '~' [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: 'sort_double' defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
gcc -I"E:/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -mfpmath=sse -msse2 -mstackrealign -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"E:/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -mfpmath=sse -msse2 -mstackrealign -c init_package.c -o init_package.o
gcc -shared -s -static-libgcc -o BufferedMatrix.dll tmp.def RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -LC:/rtools44/x86_64-w64-mingw32.static.posix/lib/x64 -LC:/rtools44/x86_64-w64-mingw32.static.posix/lib -LE:/biocbuild/bbs-3.19-bioc/R/bin/x64 -lR
installing to E:/biocbuild/bbs-3.19-bioc/R/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs/x64
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for 'rowMeans' in package 'BufferedMatrix'
Creating a new generic function for 'rowSums' in package 'BufferedMatrix'
Creating a new generic function for 'colMeans' in package 'BufferedMatrix'
Creating a new generic function for 'colSums' in package 'BufferedMatrix'
Creating a generic function for 'ncol' from package 'base' in package 'BufferedMatrix'
Creating a generic function for 'nrow' from package 'base' in package 'BufferedMatrix'
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.31 0.12 69.56
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 468463 25.1 1021760 54.6 633411 33.9
Vcells 853871 6.6 8388608 64.0 2003091 15.3
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Wed Oct 16 23:41:31 2024"
> 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 Oct 16 23:44:58 2024"
>
>
> 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: 0x000001fcaceffbf0>
>
>
>
> 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 Oct 16 23:48:06 2024"
> 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 Oct 16 23:48:17 2024"
>
> ColMode(tmp2)
<pointer: 0x000001fcaceffbf0>
>
>
>
> ### 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,] 100.7740563 -0.8521121 -0.3431714 0.7385865
[2,] 1.4798638 1.2239538 -1.3991479 -0.3660381
[3,] -0.9208759 0.4510155 0.2647469 -0.6446992
[4,] 1.6387275 0.3328177 -1.1811483 1.8690465
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.7740563 0.8521121 0.3431714 0.7385865
[2,] 1.4798638 1.2239538 1.3991479 0.3660381
[3,] 0.9208759 0.4510155 0.2647469 0.6446992
[4,] 1.6387275 0.3328177 1.1811483 1.8690465
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0386282 0.9230992 0.5858083 0.8594106
[2,] 1.2164965 1.1063244 1.1828558 0.6050108
[3,] 0.9596228 0.6715769 0.5145356 0.8029316
[4,] 1.2801279 0.5769036 1.0868065 1.3671308
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 226.16034 35.08310 31.20125 34.33269
[2,] 38.64483 37.28720 38.22771 31.41615
[3,] 35.51710 32.16678 30.41010 33.67402
[4,] 39.44001 31.10185 37.04921 40.54035
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x000001fcaceff830>
> exp(tmp5)
<pointer: 0x000001fcaceff830>
> log(tmp5,2)
<pointer: 0x000001fcaceff830>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.7231
> Min(tmp5)
[1] 54.80885
> mean(tmp5)
[1] 72.96113
> Sum(tmp5)
[1] 14592.23
> Var(tmp5)
[1] 875.0995
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 87.13557 67.82141 73.92425 71.90961 73.46804 69.99053 72.32771 70.59738
[9] 68.68871 73.74809
> rowSums(tmp5)
[1] 1742.711 1356.428 1478.485 1438.192 1469.361 1399.811 1446.554 1411.948
[9] 1373.774 1474.962
> rowVars(tmp5)
[1] 8201.91496 61.41982 103.58448 85.48523 79.79780 72.15978
[7] 73.50142 59.63755 84.18816 66.66102
> rowSd(tmp5)
[1] 90.564424 7.837080 10.177646 9.245822 8.932961 8.494691 8.573297
[8] 7.722535 9.175411 8.164620
> rowMax(tmp5)
[1] 470.72311 80.43415 91.46898 85.23029 84.33739 86.92740 92.57318
[8] 85.42743 85.49242 91.48454
> rowMin(tmp5)
[1] 58.20077 54.80885 55.36807 54.85830 56.00185 56.10763 55.03309 60.49166
[9] 55.22769 59.40296
>
> colMeans(tmp5)
[1] 112.12293 71.83879 70.55545 74.23400 68.34343 69.07507 72.45547
[8] 73.39862 68.84014 68.33822 69.90875 67.31039 72.78840 68.41559
[15] 70.21975 66.70044 71.16642 75.20124 74.96358 73.34590
> colSums(tmp5)
[1] 1121.2293 718.3879 705.5545 742.3400 683.4343 690.7507 724.5547
[8] 733.9862 688.4014 683.3822 699.0875 673.1039 727.8840 684.1559
[15] 702.1975 667.0044 711.6642 752.0124 749.6358 733.4590
> colVars(tmp5)
[1] 15937.16556 74.85986 41.82241 86.06953 52.10763 80.60970
[7] 98.09603 121.79490 65.45863 44.10196 32.78712 94.96145
[13] 97.07182 87.19334 50.36753 104.13753 83.38893 151.10215
[19] 50.76624 63.79636
> colSd(tmp5)
[1] 126.242487 8.652159 6.467025 9.277367 7.218561 8.978290
[7] 9.904344 11.036073 8.090651 6.640931 5.726004 9.744816
[13] 9.852503 9.337737 7.097008 10.204780 9.131754 12.292361
[19] 7.125043 7.987262
> colMax(tmp5)
[1] 470.72311 86.92740 80.24541 91.48454 80.91838 84.01084 84.72053
[8] 89.84730 84.33739 80.39882 78.75699 85.85100 85.49242 85.23029
[15] 83.57537 79.81057 82.13020 92.57318 85.19991 81.52937
> colMin(tmp5)
[1] 61.42281 61.59189 63.12009 61.82117 58.20892 55.22769 55.92185 58.16637
[9] 58.46602 60.17868 60.28571 55.03309 56.68954 57.16151 61.20767 54.85830
[17] 54.80885 60.29642 63.11727 62.30667
>
>
> ### 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] 87.13557 67.82141 73.92425 71.90961 73.46804 69.99053 72.32771 70.59738
[9] NA 73.74809
> rowSums(tmp5)
[1] 1742.711 1356.428 1478.485 1438.192 1469.361 1399.811 1446.554 1411.948
[9] NA 1474.962
> rowVars(tmp5)
[1] 8201.91496 61.41982 103.58448 85.48523 79.79780 72.15978
[7] 73.50142 59.63755 88.86422 66.66102
> rowSd(tmp5)
[1] 90.564424 7.837080 10.177646 9.245822 8.932961 8.494691 8.573297
[8] 7.722535 9.426782 8.164620
> rowMax(tmp5)
[1] 470.72311 80.43415 91.46898 85.23029 84.33739 86.92740 92.57318
[8] 85.42743 NA 91.48454
> rowMin(tmp5)
[1] 58.20077 54.80885 55.36807 54.85830 56.00185 56.10763 55.03309 60.49166
[9] NA 59.40296
>
> colMeans(tmp5)
[1] 112.12293 71.83879 70.55545 NA 68.34343 69.07507 72.45547
[8] 73.39862 68.84014 68.33822 69.90875 67.31039 72.78840 68.41559
[15] 70.21975 66.70044 71.16642 75.20124 74.96358 73.34590
> colSums(tmp5)
[1] 1121.2293 718.3879 705.5545 NA 683.4343 690.7507 724.5547
[8] 733.9862 688.4014 683.3822 699.0875 673.1039 727.8840 684.1559
[15] 702.1975 667.0044 711.6642 752.0124 749.6358 733.4590
> colVars(tmp5)
[1] 15937.16556 74.85986 41.82241 NA 52.10763 80.60970
[7] 98.09603 121.79490 65.45863 44.10196 32.78712 94.96145
[13] 97.07182 87.19334 50.36753 104.13753 83.38893 151.10215
[19] 50.76624 63.79636
> colSd(tmp5)
[1] 126.242487 8.652159 6.467025 NA 7.218561 8.978290
[7] 9.904344 11.036073 8.090651 6.640931 5.726004 9.744816
[13] 9.852503 9.337737 7.097008 10.204780 9.131754 12.292361
[19] 7.125043 7.987262
> colMax(tmp5)
[1] 470.72311 86.92740 80.24541 NA 80.91838 84.01084 84.72053
[8] 89.84730 84.33739 80.39882 78.75699 85.85100 85.49242 85.23029
[15] 83.57537 79.81057 82.13020 92.57318 85.19991 81.52937
> colMin(tmp5)
[1] 61.42281 61.59189 63.12009 NA 58.20892 55.22769 55.92185 58.16637
[9] 58.46602 60.17868 60.28571 55.03309 56.68954 57.16151 61.20767 54.85830
[17] 54.80885 60.29642 63.11727 62.30667
>
> Max(tmp5,na.rm=TRUE)
[1] 470.7231
> Min(tmp5,na.rm=TRUE)
[1] 54.80885
> mean(tmp5,na.rm=TRUE)
[1] 72.98328
> Sum(tmp5,na.rm=TRUE)
[1] 14523.67
> Var(tmp5,na.rm=TRUE)
[1] 879.4206
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.13557 67.82141 73.92425 71.90961 73.46804 69.99053 72.32771 70.59738
[9] 68.69580 73.74809
> rowSums(tmp5,na.rm=TRUE)
[1] 1742.711 1356.428 1478.485 1438.192 1469.361 1399.811 1446.554 1411.948
[9] 1305.220 1474.962
> rowVars(tmp5,na.rm=TRUE)
[1] 8201.91496 61.41982 103.58448 85.48523 79.79780 72.15978
[7] 73.50142 59.63755 88.86422 66.66102
> rowSd(tmp5,na.rm=TRUE)
[1] 90.564424 7.837080 10.177646 9.245822 8.932961 8.494691 8.573297
[8] 7.722535 9.426782 8.164620
> rowMax(tmp5,na.rm=TRUE)
[1] 470.72311 80.43415 91.46898 85.23029 84.33739 86.92740 92.57318
[8] 85.42743 85.49242 91.48454
> rowMin(tmp5,na.rm=TRUE)
[1] 58.20077 54.80885 55.36807 54.85830 56.00185 56.10763 55.03309 60.49166
[9] 55.22769 59.40296
>
> colMeans(tmp5,na.rm=TRUE)
[1] 112.12293 71.83879 70.55545 74.86512 68.34343 69.07507 72.45547
[8] 73.39862 68.84014 68.33822 69.90875 67.31039 72.78840 68.41559
[15] 70.21975 66.70044 71.16642 75.20124 74.96358 73.34590
> colSums(tmp5,na.rm=TRUE)
[1] 1121.2293 718.3879 705.5545 673.7861 683.4343 690.7507 724.5547
[8] 733.9862 688.4014 683.3822 699.0875 673.1039 727.8840 684.1559
[15] 702.1975 667.0044 711.6642 752.0124 749.6358 733.4590
> colVars(tmp5,na.rm=TRUE)
[1] 15937.16556 74.85986 41.82241 92.34714 52.10763 80.60970
[7] 98.09603 121.79490 65.45863 44.10196 32.78712 94.96145
[13] 97.07182 87.19334 50.36753 104.13753 83.38893 151.10215
[19] 50.76624 63.79636
> colSd(tmp5,na.rm=TRUE)
[1] 126.242487 8.652159 6.467025 9.609742 7.218561 8.978290
[7] 9.904344 11.036073 8.090651 6.640931 5.726004 9.744816
[13] 9.852503 9.337737 7.097008 10.204780 9.131754 12.292361
[19] 7.125043 7.987262
> colMax(tmp5,na.rm=TRUE)
[1] 470.72311 86.92740 80.24541 91.48454 80.91838 84.01084 84.72053
[8] 89.84730 84.33739 80.39882 78.75699 85.85100 85.49242 85.23029
[15] 83.57537 79.81057 82.13020 92.57318 85.19991 81.52937
> colMin(tmp5,na.rm=TRUE)
[1] 61.42281 61.59189 63.12009 61.82117 58.20892 55.22769 55.92185 58.16637
[9] 58.46602 60.17868 60.28571 55.03309 56.68954 57.16151 61.20767 54.85830
[17] 54.80885 60.29642 63.11727 62.30667
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.13557 67.82141 73.92425 71.90961 73.46804 69.99053 72.32771 70.59738
[9] NaN 73.74809
> rowSums(tmp5,na.rm=TRUE)
[1] 1742.711 1356.428 1478.485 1438.192 1469.361 1399.811 1446.554 1411.948
[9] 0.000 1474.962
> rowVars(tmp5,na.rm=TRUE)
[1] 8201.91496 61.41982 103.58448 85.48523 79.79780 72.15978
[7] 73.50142 59.63755 NA 66.66102
> rowSd(tmp5,na.rm=TRUE)
[1] 90.564424 7.837080 10.177646 9.245822 8.932961 8.494691 8.573297
[8] 7.722535 NA 8.164620
> rowMax(tmp5,na.rm=TRUE)
[1] 470.72311 80.43415 91.46898 85.23029 84.33739 86.92740 92.57318
[8] 85.42743 NA 91.48454
> rowMin(tmp5,na.rm=TRUE)
[1] 58.20077 54.80885 55.36807 54.85830 56.00185 56.10763 55.03309 60.49166
[9] NA 59.40296
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 117.75628 72.90713 70.83723 NaN 67.25294 70.61367 74.29253
[8] 75.09109 68.48187 68.74049 69.71042 68.26270 71.37684 69.29011
[15] 69.13996 66.38192 71.73358 74.67550 74.87082 72.43662
> colSums(tmp5,na.rm=TRUE)
[1] 1059.8065 656.1642 637.5350 0.0000 605.2765 635.5230 668.6328
[8] 675.8198 616.3368 618.6644 627.3938 614.3643 642.3916 623.6110
[15] 622.2597 597.4372 645.6023 672.0795 673.8374 651.9296
> colVars(tmp5,na.rm=TRUE)
[1] 17572.29696 71.37712 46.15698 NA 45.24294 64.05396
[7] 72.39129 104.79408 72.19695 47.79423 36.44299 96.62889
[13] 86.79023 89.48862 43.54674 116.01331 90.19372 166.88042
[19] 57.01521 62.46962
> colSd(tmp5,na.rm=TRUE)
[1] 132.560541 8.448498 6.793893 NA 6.726287 8.003372
[7] 8.508307 10.236898 8.496879 6.913337 6.036803 9.830000
[13] 9.316127 9.459842 6.598996 10.770947 9.497037 12.918221
[19] 7.550842 7.903772
> colMax(tmp5,na.rm=TRUE)
[1] 470.72311 86.92740 80.24541 -Inf 80.91838 84.01084 84.72053
[8] 89.84730 84.33739 80.39882 78.75699 85.85100 82.40465 85.23029
[15] 83.57537 79.81057 82.13020 92.57318 85.19991 80.25670
> colMin(tmp5,na.rm=TRUE)
[1] 63.54736 61.59189 63.12009 Inf 58.20892 56.00185 58.85501 59.82811
[9] 58.46602 60.17868 60.28571 55.03309 56.68954 57.16151 61.20767 54.85830
[17] 54.80885 60.29642 63.11727 62.30667
>
>
>
>
> 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] 208.6645 190.1880 245.6293 188.5683 218.7021 213.0721 193.7910 218.0024
[9] 266.5101 323.6747
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 208.6645 190.1880 245.6293 188.5683 218.7021 213.0721 193.7910 218.0024
[9] 266.5101 323.6747
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 0.000000e+00 -1.136868e-13 -2.842171e-14 1.421085e-13 1.705303e-13
[6] 0.000000e+00 -2.842171e-14 0.000000e+00 1.989520e-13 -8.526513e-14
[11] -1.136868e-13 0.000000e+00 7.105427e-14 -1.705303e-13 1.421085e-14
[16] 5.684342e-14 -1.136868e-13 -1.705303e-13 -8.526513e-14 -1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## 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)
+ }
6 4
8 6
4 1
2 11
7 11
6 2
6 10
10 17
3 5
9 2
9 11
5 12
8 4
4 9
10 2
4 8
5 2
3 19
5 5
8 7
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] 2.428673
> Min(tmp)
[1] -2.958934
> mean(tmp)
[1] -0.06188605
> Sum(tmp)
[1] -6.188605
> Var(tmp)
[1] 1.118204
>
> rowMeans(tmp)
[1] -0.06188605
> rowSums(tmp)
[1] -6.188605
> rowVars(tmp)
[1] 1.118204
> rowSd(tmp)
[1] 1.057452
> rowMax(tmp)
[1] 2.428673
> rowMin(tmp)
[1] -2.958934
>
> colMeans(tmp)
[1] 0.924282620 0.116370229 0.728807174 1.934934851 0.287711839
[6] 1.414581700 -0.161207454 -1.084543286 -0.260197075 -0.578621472
[11] -0.751869638 2.068826014 -0.091866160 -0.839019754 -0.748650830
[16] -1.664703757 -0.023392619 0.398349559 0.005750148 2.428673217
[21] 0.761262891 0.549190129 -1.188560670 1.218215874 1.120350114
[26] 0.422103930 0.480858717 0.559956834 1.277610675 -1.341266733
[31] 0.128408336 -0.151821056 -0.028358917 -0.958928753 -1.514398402
[36] 0.660923930 0.283690490 -0.685150487 0.288990608 1.636465178
[41] -0.126371141 0.517513400 -0.809943875 -1.186636025 1.427025929
[46] 0.066023601 -0.391566143 -0.243632093 1.055419404 -1.407531825
[51] -1.073683044 -0.116586502 0.161849799 -0.259592822 -0.184420250
[56] -1.894329335 1.654771699 -1.328010885 -1.053836567 0.638708256
[61] -2.958933825 -0.832998546 -1.052509978 -0.342365207 0.421362315
[66] 0.231147470 0.775492808 1.295131166 0.109058320 1.190127714
[71] 1.150981217 1.140839884 -1.153170194 0.869934683 -0.448410613
[76] 0.664412065 0.460445603 -0.567017832 -0.650378658 -0.966546796
[81] 2.098612555 -0.059404216 0.439657720 0.028463034 0.680560149
[86] -0.477904002 -2.755925329 -0.681777122 -0.710516021 -1.234464855
[91] -2.559554565 -0.258095172 0.256043519 -0.160814673 -0.533524018
[96] -0.394063001 -2.675631509 0.638502614 0.399880771 -0.634181833
> colSums(tmp)
[1] 0.924282620 0.116370229 0.728807174 1.934934851 0.287711839
[6] 1.414581700 -0.161207454 -1.084543286 -0.260197075 -0.578621472
[11] -0.751869638 2.068826014 -0.091866160 -0.839019754 -0.748650830
[16] -1.664703757 -0.023392619 0.398349559 0.005750148 2.428673217
[21] 0.761262891 0.549190129 -1.188560670 1.218215874 1.120350114
[26] 0.422103930 0.480858717 0.559956834 1.277610675 -1.341266733
[31] 0.128408336 -0.151821056 -0.028358917 -0.958928753 -1.514398402
[36] 0.660923930 0.283690490 -0.685150487 0.288990608 1.636465178
[41] -0.126371141 0.517513400 -0.809943875 -1.186636025 1.427025929
[46] 0.066023601 -0.391566143 -0.243632093 1.055419404 -1.407531825
[51] -1.073683044 -0.116586502 0.161849799 -0.259592822 -0.184420250
[56] -1.894329335 1.654771699 -1.328010885 -1.053836567 0.638708256
[61] -2.958933825 -0.832998546 -1.052509978 -0.342365207 0.421362315
[66] 0.231147470 0.775492808 1.295131166 0.109058320 1.190127714
[71] 1.150981217 1.140839884 -1.153170194 0.869934683 -0.448410613
[76] 0.664412065 0.460445603 -0.567017832 -0.650378658 -0.966546796
[81] 2.098612555 -0.059404216 0.439657720 0.028463034 0.680560149
[86] -0.477904002 -2.755925329 -0.681777122 -0.710516021 -1.234464855
[91] -2.559554565 -0.258095172 0.256043519 -0.160814673 -0.533524018
[96] -0.394063001 -2.675631509 0.638502614 0.399880771 -0.634181833
> 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] 0.924282620 0.116370229 0.728807174 1.934934851 0.287711839
[6] 1.414581700 -0.161207454 -1.084543286 -0.260197075 -0.578621472
[11] -0.751869638 2.068826014 -0.091866160 -0.839019754 -0.748650830
[16] -1.664703757 -0.023392619 0.398349559 0.005750148 2.428673217
[21] 0.761262891 0.549190129 -1.188560670 1.218215874 1.120350114
[26] 0.422103930 0.480858717 0.559956834 1.277610675 -1.341266733
[31] 0.128408336 -0.151821056 -0.028358917 -0.958928753 -1.514398402
[36] 0.660923930 0.283690490 -0.685150487 0.288990608 1.636465178
[41] -0.126371141 0.517513400 -0.809943875 -1.186636025 1.427025929
[46] 0.066023601 -0.391566143 -0.243632093 1.055419404 -1.407531825
[51] -1.073683044 -0.116586502 0.161849799 -0.259592822 -0.184420250
[56] -1.894329335 1.654771699 -1.328010885 -1.053836567 0.638708256
[61] -2.958933825 -0.832998546 -1.052509978 -0.342365207 0.421362315
[66] 0.231147470 0.775492808 1.295131166 0.109058320 1.190127714
[71] 1.150981217 1.140839884 -1.153170194 0.869934683 -0.448410613
[76] 0.664412065 0.460445603 -0.567017832 -0.650378658 -0.966546796
[81] 2.098612555 -0.059404216 0.439657720 0.028463034 0.680560149
[86] -0.477904002 -2.755925329 -0.681777122 -0.710516021 -1.234464855
[91] -2.559554565 -0.258095172 0.256043519 -0.160814673 -0.533524018
[96] -0.394063001 -2.675631509 0.638502614 0.399880771 -0.634181833
> colMin(tmp)
[1] 0.924282620 0.116370229 0.728807174 1.934934851 0.287711839
[6] 1.414581700 -0.161207454 -1.084543286 -0.260197075 -0.578621472
[11] -0.751869638 2.068826014 -0.091866160 -0.839019754 -0.748650830
[16] -1.664703757 -0.023392619 0.398349559 0.005750148 2.428673217
[21] 0.761262891 0.549190129 -1.188560670 1.218215874 1.120350114
[26] 0.422103930 0.480858717 0.559956834 1.277610675 -1.341266733
[31] 0.128408336 -0.151821056 -0.028358917 -0.958928753 -1.514398402
[36] 0.660923930 0.283690490 -0.685150487 0.288990608 1.636465178
[41] -0.126371141 0.517513400 -0.809943875 -1.186636025 1.427025929
[46] 0.066023601 -0.391566143 -0.243632093 1.055419404 -1.407531825
[51] -1.073683044 -0.116586502 0.161849799 -0.259592822 -0.184420250
[56] -1.894329335 1.654771699 -1.328010885 -1.053836567 0.638708256
[61] -2.958933825 -0.832998546 -1.052509978 -0.342365207 0.421362315
[66] 0.231147470 0.775492808 1.295131166 0.109058320 1.190127714
[71] 1.150981217 1.140839884 -1.153170194 0.869934683 -0.448410613
[76] 0.664412065 0.460445603 -0.567017832 -0.650378658 -0.966546796
[81] 2.098612555 -0.059404216 0.439657720 0.028463034 0.680560149
[86] -0.477904002 -2.755925329 -0.681777122 -0.710516021 -1.234464855
[91] -2.559554565 -0.258095172 0.256043519 -0.160814673 -0.533524018
[96] -0.394063001 -2.675631509 0.638502614 0.399880771 -0.634181833
> colMedians(tmp)
[1] 0.924282620 0.116370229 0.728807174 1.934934851 0.287711839
[6] 1.414581700 -0.161207454 -1.084543286 -0.260197075 -0.578621472
[11] -0.751869638 2.068826014 -0.091866160 -0.839019754 -0.748650830
[16] -1.664703757 -0.023392619 0.398349559 0.005750148 2.428673217
[21] 0.761262891 0.549190129 -1.188560670 1.218215874 1.120350114
[26] 0.422103930 0.480858717 0.559956834 1.277610675 -1.341266733
[31] 0.128408336 -0.151821056 -0.028358917 -0.958928753 -1.514398402
[36] 0.660923930 0.283690490 -0.685150487 0.288990608 1.636465178
[41] -0.126371141 0.517513400 -0.809943875 -1.186636025 1.427025929
[46] 0.066023601 -0.391566143 -0.243632093 1.055419404 -1.407531825
[51] -1.073683044 -0.116586502 0.161849799 -0.259592822 -0.184420250
[56] -1.894329335 1.654771699 -1.328010885 -1.053836567 0.638708256
[61] -2.958933825 -0.832998546 -1.052509978 -0.342365207 0.421362315
[66] 0.231147470 0.775492808 1.295131166 0.109058320 1.190127714
[71] 1.150981217 1.140839884 -1.153170194 0.869934683 -0.448410613
[76] 0.664412065 0.460445603 -0.567017832 -0.650378658 -0.966546796
[81] 2.098612555 -0.059404216 0.439657720 0.028463034 0.680560149
[86] -0.477904002 -2.755925329 -0.681777122 -0.710516021 -1.234464855
[91] -2.559554565 -0.258095172 0.256043519 -0.160814673 -0.533524018
[96] -0.394063001 -2.675631509 0.638502614 0.399880771 -0.634181833
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.9242826 0.1163702 0.7288072 1.934935 0.2877118 1.414582 -0.1612075
[2,] 0.9242826 0.1163702 0.7288072 1.934935 0.2877118 1.414582 -0.1612075
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.084543 -0.2601971 -0.5786215 -0.7518696 2.068826 -0.09186616 -0.8390198
[2,] -1.084543 -0.2601971 -0.5786215 -0.7518696 2.068826 -0.09186616 -0.8390198
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.7486508 -1.664704 -0.02339262 0.3983496 0.005750148 2.428673 0.7612629
[2,] -0.7486508 -1.664704 -0.02339262 0.3983496 0.005750148 2.428673 0.7612629
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.5491901 -1.188561 1.218216 1.12035 0.4221039 0.4808587 0.5599568
[2,] 0.5491901 -1.188561 1.218216 1.12035 0.4221039 0.4808587 0.5599568
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.277611 -1.341267 0.1284083 -0.1518211 -0.02835892 -0.9589288 -1.514398
[2,] 1.277611 -1.341267 0.1284083 -0.1518211 -0.02835892 -0.9589288 -1.514398
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.6609239 0.2836905 -0.6851505 0.2889906 1.636465 -0.1263711 0.5175134
[2,] 0.6609239 0.2836905 -0.6851505 0.2889906 1.636465 -0.1263711 0.5175134
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.8099439 -1.186636 1.427026 0.0660236 -0.3915661 -0.2436321 1.055419
[2,] -0.8099439 -1.186636 1.427026 0.0660236 -0.3915661 -0.2436321 1.055419
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -1.407532 -1.073683 -0.1165865 0.1618498 -0.2595928 -0.1844203 -1.894329
[2,] -1.407532 -1.073683 -0.1165865 0.1618498 -0.2595928 -0.1844203 -1.894329
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 1.654772 -1.328011 -1.053837 0.6387083 -2.958934 -0.8329985 -1.05251
[2,] 1.654772 -1.328011 -1.053837 0.6387083 -2.958934 -0.8329985 -1.05251
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.3423652 0.4213623 0.2311475 0.7754928 1.295131 0.1090583 1.190128
[2,] -0.3423652 0.4213623 0.2311475 0.7754928 1.295131 0.1090583 1.190128
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.150981 1.14084 -1.15317 0.8699347 -0.4484106 0.6644121 0.4604456
[2,] 1.150981 1.14084 -1.15317 0.8699347 -0.4484106 0.6644121 0.4604456
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.5670178 -0.6503787 -0.9665468 2.098613 -0.05940422 0.4396577 0.02846303
[2,] -0.5670178 -0.6503787 -0.9665468 2.098613 -0.05940422 0.4396577 0.02846303
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.6805601 -0.477904 -2.755925 -0.6817771 -0.710516 -1.234465 -2.559555
[2,] 0.6805601 -0.477904 -2.755925 -0.6817771 -0.710516 -1.234465 -2.559555
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.2580952 0.2560435 -0.1608147 -0.533524 -0.394063 -2.675632 0.6385026
[2,] -0.2580952 0.2560435 -0.1608147 -0.533524 -0.394063 -2.675632 0.6385026
[,99] [,100]
[1,] 0.3998808 -0.6341818
[2,] 0.3998808 -0.6341818
>
>
> Max(tmp2)
[1] 2.152114
> Min(tmp2)
[1] -2.852465
> mean(tmp2)
[1] -0.1318381
> Sum(tmp2)
[1] -13.18381
> Var(tmp2)
[1] 1.031398
>
> rowMeans(tmp2)
[1] -0.183051007 1.754877043 -0.905110658 1.390007384 0.142544168
[6] -1.098904674 0.605671085 -0.331293373 -0.327020973 -0.252514947
[11] -1.823397324 0.360649113 -1.659387780 -1.022034338 1.237791089
[16] -1.301067061 -2.852464511 -0.138610988 -1.293668211 -0.358429740
[21] 0.124754543 -0.368684726 -0.463531114 -0.674245980 -0.606575675
[26] 0.751950848 -1.709987047 0.473857523 -0.352599237 -1.385445008
[31] 0.002498617 0.111874173 -0.737860044 0.620210003 -0.774465545
[36] 0.483508872 -0.143785823 -1.348581839 -0.256150971 0.611173444
[41] -1.066917164 -0.817214420 0.160397639 1.746217206 -0.912809779
[46] -1.080398922 -1.275984412 0.274100501 -0.966359675 -2.336682626
[51] 0.147638429 -1.175006001 0.279019141 1.560884186 -1.007086966
[56] 1.019754262 1.659543564 -0.130324182 -0.771575250 1.420398275
[61] -1.431057156 -1.061537173 -1.279463027 -0.868761575 -1.276259308
[66] 0.618423268 1.114909060 2.152113650 0.252220957 0.886364178
[71] 0.134205264 0.110670929 0.408603228 0.064778363 -0.014580234
[76] 1.042127261 0.347735236 0.358978087 1.566682952 -1.021856226
[81] -0.740331298 -0.071404699 -0.635544867 0.047807623 -0.214812369
[86] 0.106989485 0.513593465 0.284736035 -1.754175460 0.688739483
[91] -0.572573233 -2.113078691 0.700761110 -0.560549098 0.095062155
[96] 1.280974253 0.269298527 1.377293214 1.025187451 1.953824307
> rowSums(tmp2)
[1] -0.183051007 1.754877043 -0.905110658 1.390007384 0.142544168
[6] -1.098904674 0.605671085 -0.331293373 -0.327020973 -0.252514947
[11] -1.823397324 0.360649113 -1.659387780 -1.022034338 1.237791089
[16] -1.301067061 -2.852464511 -0.138610988 -1.293668211 -0.358429740
[21] 0.124754543 -0.368684726 -0.463531114 -0.674245980 -0.606575675
[26] 0.751950848 -1.709987047 0.473857523 -0.352599237 -1.385445008
[31] 0.002498617 0.111874173 -0.737860044 0.620210003 -0.774465545
[36] 0.483508872 -0.143785823 -1.348581839 -0.256150971 0.611173444
[41] -1.066917164 -0.817214420 0.160397639 1.746217206 -0.912809779
[46] -1.080398922 -1.275984412 0.274100501 -0.966359675 -2.336682626
[51] 0.147638429 -1.175006001 0.279019141 1.560884186 -1.007086966
[56] 1.019754262 1.659543564 -0.130324182 -0.771575250 1.420398275
[61] -1.431057156 -1.061537173 -1.279463027 -0.868761575 -1.276259308
[66] 0.618423268 1.114909060 2.152113650 0.252220957 0.886364178
[71] 0.134205264 0.110670929 0.408603228 0.064778363 -0.014580234
[76] 1.042127261 0.347735236 0.358978087 1.566682952 -1.021856226
[81] -0.740331298 -0.071404699 -0.635544867 0.047807623 -0.214812369
[86] 0.106989485 0.513593465 0.284736035 -1.754175460 0.688739483
[91] -0.572573233 -2.113078691 0.700761110 -0.560549098 0.095062155
[96] 1.280974253 0.269298527 1.377293214 1.025187451 1.953824307
> 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] -0.183051007 1.754877043 -0.905110658 1.390007384 0.142544168
[6] -1.098904674 0.605671085 -0.331293373 -0.327020973 -0.252514947
[11] -1.823397324 0.360649113 -1.659387780 -1.022034338 1.237791089
[16] -1.301067061 -2.852464511 -0.138610988 -1.293668211 -0.358429740
[21] 0.124754543 -0.368684726 -0.463531114 -0.674245980 -0.606575675
[26] 0.751950848 -1.709987047 0.473857523 -0.352599237 -1.385445008
[31] 0.002498617 0.111874173 -0.737860044 0.620210003 -0.774465545
[36] 0.483508872 -0.143785823 -1.348581839 -0.256150971 0.611173444
[41] -1.066917164 -0.817214420 0.160397639 1.746217206 -0.912809779
[46] -1.080398922 -1.275984412 0.274100501 -0.966359675 -2.336682626
[51] 0.147638429 -1.175006001 0.279019141 1.560884186 -1.007086966
[56] 1.019754262 1.659543564 -0.130324182 -0.771575250 1.420398275
[61] -1.431057156 -1.061537173 -1.279463027 -0.868761575 -1.276259308
[66] 0.618423268 1.114909060 2.152113650 0.252220957 0.886364178
[71] 0.134205264 0.110670929 0.408603228 0.064778363 -0.014580234
[76] 1.042127261 0.347735236 0.358978087 1.566682952 -1.021856226
[81] -0.740331298 -0.071404699 -0.635544867 0.047807623 -0.214812369
[86] 0.106989485 0.513593465 0.284736035 -1.754175460 0.688739483
[91] -0.572573233 -2.113078691 0.700761110 -0.560549098 0.095062155
[96] 1.280974253 0.269298527 1.377293214 1.025187451 1.953824307
> rowMin(tmp2)
[1] -0.183051007 1.754877043 -0.905110658 1.390007384 0.142544168
[6] -1.098904674 0.605671085 -0.331293373 -0.327020973 -0.252514947
[11] -1.823397324 0.360649113 -1.659387780 -1.022034338 1.237791089
[16] -1.301067061 -2.852464511 -0.138610988 -1.293668211 -0.358429740
[21] 0.124754543 -0.368684726 -0.463531114 -0.674245980 -0.606575675
[26] 0.751950848 -1.709987047 0.473857523 -0.352599237 -1.385445008
[31] 0.002498617 0.111874173 -0.737860044 0.620210003 -0.774465545
[36] 0.483508872 -0.143785823 -1.348581839 -0.256150971 0.611173444
[41] -1.066917164 -0.817214420 0.160397639 1.746217206 -0.912809779
[46] -1.080398922 -1.275984412 0.274100501 -0.966359675 -2.336682626
[51] 0.147638429 -1.175006001 0.279019141 1.560884186 -1.007086966
[56] 1.019754262 1.659543564 -0.130324182 -0.771575250 1.420398275
[61] -1.431057156 -1.061537173 -1.279463027 -0.868761575 -1.276259308
[66] 0.618423268 1.114909060 2.152113650 0.252220957 0.886364178
[71] 0.134205264 0.110670929 0.408603228 0.064778363 -0.014580234
[76] 1.042127261 0.347735236 0.358978087 1.566682952 -1.021856226
[81] -0.740331298 -0.071404699 -0.635544867 0.047807623 -0.214812369
[86] 0.106989485 0.513593465 0.284736035 -1.754175460 0.688739483
[91] -0.572573233 -2.113078691 0.700761110 -0.560549098 0.095062155
[96] 1.280974253 0.269298527 1.377293214 1.025187451 1.953824307
>
> colMeans(tmp2)
[1] -0.1318381
> colSums(tmp2)
[1] -13.18381
> colVars(tmp2)
[1] 1.031398
> colSd(tmp2)
[1] 1.015578
> colMax(tmp2)
[1] 2.152114
> colMin(tmp2)
[1] -2.852465
> colMedians(tmp2)
[1] -0.1008644
> colRanges(tmp2)
[,1]
[1,] -2.852465
[2,] 2.152114
>
> 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] -1.498277 -2.039096 -1.636590 -3.095272 -1.588931 8.161939 -1.101544
[8] 4.771588 -1.398279 -1.805469
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.0496687
[2,] -0.6067326
[3,] -0.1203187
[4,] 0.2952683
[5,] 1.7678652
>
> rowApply(tmp,sum)
[1] 0.52151926 4.91894651 -4.82966360 5.44846444 -0.04106703 -0.32249812
[7] -1.02615705 -2.70196527 -4.06940868 0.87189823
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 4 6 6 4 4 7 7 1 4
[2,] 2 8 1 3 8 3 10 1 3 10
[3,] 1 10 7 2 7 5 3 3 10 1
[4,] 5 1 8 8 5 2 9 6 2 3
[5,] 3 3 4 10 2 6 2 9 7 6
[6,] 7 5 10 9 9 8 8 4 6 9
[7,] 6 6 5 4 10 1 6 2 5 7
[8,] 9 2 9 5 3 10 5 10 8 8
[9,] 4 7 2 1 6 9 1 5 9 2
[10,] 8 9 3 7 1 7 4 8 4 5
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.67476941 0.62121575 -2.37363135 -1.23555871 -0.05713761 -2.76956045
[7] 2.92067513 5.30260497 -0.39443051 3.24767431 0.72894111 0.99613352
[13] 1.64225376 2.88019212 -1.73827081 1.80874502 -3.61184606 0.66233302
[19] 1.60561004 -0.63162505
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.02891868
[2,] -0.08272782
[3,] 0.01906862
[4,] 0.07869380
[5,] 0.33911467
>
> rowApply(tmp,sum)
[1] 3.7415274 1.6100629 5.4210029 0.7901107 -2.6331551
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 3 8 9 12 13
[2,] 16 9 6 16 7
[3,] 4 16 8 14 1
[4,] 7 13 4 10 4
[5,] 17 17 14 11 2
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.02891868 0.89962474 -0.7427297 -0.24362948 1.143312023 -1.6089257
[2,] -0.08272782 0.01649329 0.7338879 0.47604122 0.758331461 -0.3511046
[3,] 0.07869380 -0.38939797 -0.1296042 -0.48718326 0.521581990 -0.8880560
[4,] 0.01906862 0.57103018 0.4240378 -0.04738227 -0.009397524 -0.3091616
[5,] 0.33911467 -0.47653450 -2.6592232 -0.93340492 -2.470965565 0.3876875
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.3996585 2.3965318 -0.4824413 1.9119006 0.5018649 0.71150020
[2,] 1.4234545 -0.3205291 0.2130901 -1.2582843 -0.5078632 -0.55798126
[3,] 0.2896922 2.1915326 0.3163792 0.5994002 0.9409468 1.26272212
[4,] -0.2813750 1.7770131 -0.3089483 0.2818371 -0.6180981 -0.36085899
[5,] 1.0892450 -0.7419435 -0.1325102 1.7128207 0.4120907 -0.05924855
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.5879925 1.5848236 0.41031394 0.04817023 -2.3984361 -0.6835606
[2,] -1.8432111 0.4030876 0.05618452 1.07255987 -0.5906640 0.6241579
[3,] 2.1019890 -0.3055997 -1.12406721 0.20510199 -0.9330061 0.2446427
[4,] -0.9901141 1.4918591 -0.91256172 0.79552676 -0.5830583 1.5023971
[5,] 1.7855974 -0.2939785 -0.16814035 -0.31261383 0.8933184 -1.0253041
[,19] [,20]
[1,] 0.1199478 0.2145281
[2,] 0.5783160 0.7668240
[3,] 1.3176153 -0.3923805
[4,] 0.4520215 -2.1037248
[5,] -0.8622905 0.8831282
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.8 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 626 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 543 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.8 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.3929964 -1.673071 0.1808757 1.427413 0.2128399 -1.500692 -0.6828315
col8 col9 col10 col11 col12 col13 col14
row1 1.165061 0.1823223 -0.9126449 1.58777 0.9451178 0.170792 0.01477911
col15 col16 col17 col18 col19 col20
row1 0.9408223 0.1513678 -0.7209336 0.2911687 1.453825 -1.764196
> tmp[,"col10"]
col10
row1 -0.9126449
row2 2.1082290
row3 0.7008783
row4 -0.2949526
row5 0.9360881
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.3929964 -1.6730706 0.1808757 1.4274126 0.2128399 -1.50069190
row5 -0.1385175 0.2021836 0.1868075 -0.9988668 -0.5060999 0.02504219
col7 col8 col9 col10 col11 col12 col13
row1 -0.6828315 1.165061 0.1823223 -0.9126449 1.5877699 0.94511779 0.1707920
row5 -0.4850793 1.836651 -0.2812602 0.9360881 0.5256839 -0.02723311 -0.3150035
col14 col15 col16 col17 col18 col19
row1 0.01477911 0.9408223 0.1513678 -0.7209336 0.2911687 1.4538246
row5 0.29172837 -1.5080685 -1.6102716 -1.1899423 -1.0865755 -0.9851569
col20
row1 -1.7641964
row5 0.2104301
> tmp[,c("col6","col20")]
col6 col20
row1 -1.50069190 -1.76419642
row2 1.70712125 2.27725888
row3 0.68405082 -0.04008696
row4 0.87876404 0.17943748
row5 0.02504219 0.21043012
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.50069190 -1.7641964
row5 0.02504219 0.2104301
>
>
>
>
> 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 48.12916 49.19221 51.42635 49.2258 50.27168 104.5185 48.52339 51.36248
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.50501 50.51308 50.07973 49.56742 49.58283 48.67902 51.64638 49.11046
col17 col18 col19 col20
row1 49.5568 49.3898 49.31867 105.3235
> tmp[,"col10"]
col10
row1 50.51308
row2 28.70475
row3 29.17950
row4 30.15464
row5 50.36886
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.12916 49.19221 51.42635 49.22580 50.27168 104.5185 48.52339 51.36248
row5 50.13123 50.07173 48.89153 49.87218 51.44963 106.8499 47.79011 48.41125
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.50501 50.51308 50.07973 49.56742 49.58283 48.67902 51.64638 49.11046
row5 50.19096 50.36886 50.38387 50.10053 48.39536 49.85032 50.16784 50.17469
col17 col18 col19 col20
row1 49.55680 49.38980 49.31867 105.3235
row5 50.60626 48.46998 49.80642 103.7019
> tmp[,c("col6","col20")]
col6 col20
row1 104.51847 105.32349
row2 73.76544 74.92110
row3 75.39657 75.92959
row4 75.09505 75.92550
row5 106.84989 103.70188
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.5185 105.3235
row5 106.8499 103.7019
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.5185 105.3235
row5 106.8499 103.7019
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.8804255
[2,] 1.3260415
[3,] 1.1791059
[4,] -1.1207391
[5,] -0.6079569
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.4646774 0.6457002
[2,] -1.0326333 1.0123135
[3,] 0.3283261 -0.4195874
[4,] 0.7881224 0.3536940
[5,] 1.1221205 0.9608691
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.4353742 -1.97243717
[2,] 0.2797167 0.01258132
[3,] -0.8192626 1.67377545
[4,] -0.5757517 1.59744319
[5,] -2.2480170 0.23432258
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.4353742
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.4353742
[2,] 0.2797167
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 -0.3003954 0.119719 -1.2858047 -0.6861162 -0.3757553 -1.638416 1.894434
row1 -0.7481030 2.583061 -0.9867833 0.8931010 1.1354243 1.354806 -2.018516
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -3.247591 -0.2607484 -0.04704542 -1.2059476 1.3813342 -0.4859410
row1 0.732507 -1.8369049 0.92076088 0.5233018 0.9442565 -0.8540122
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 0.1210878 -0.0480118 -0.6415182 0.342352272 -1.269583 -1.5515907 1.233561
row1 -0.6612091 2.1447005 0.2123182 0.001416156 -1.060786 -0.7507957 1.440908
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.927998 0.8131812 0.9676133 0.3546222 -0.169985 -0.6238426 0.1448211
[,8] [,9] [,10]
row2 -0.09901959 0.04117864 -0.9373565
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.542556 -0.03048578 0.2878586 -1.544807 0.7479892 1.261223 -0.6454238
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.1874996 1.450195 -0.5792309 1.676828 -0.5798245 0.4928745 1.312724
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.7199686 0.3154272 -1.099943 1.69587 -0.5450279 0.1130206
>
>
> 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: 0x000001fcaceffef0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM30406b046e60"
[2] "E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM30404e053a97"
[3] "E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3040385030b"
[4] "E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM30406c965270"
[5] "E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM30407a5f734a"
[6] "E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM30407ed2600d"
[7] "E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM30403cd7413c"
[8] "E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM30404f305199"
[9] "E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3040c7f9b"
[10] "E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM304034512dc2"
[11] "E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM304075a46b90"
[12] "E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM304022856f25"
[13] "E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM304041bb39cc"
[14] "E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM304076913406"
[15] "E:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM304038476dd4"
>
>
> ### 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: 0x000001fcafbff2f0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x000001fcafbff2f0>
Warning message:
In dir.create(new.directory) :
'E:\biocbuild\bbs-3.19-bioc\meat\BufferedMatrix.Rcheck\tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x000001fcafbff2f0>
> rowMedians(tmp)
[1] 0.127810695 -0.316351401 0.058245303 -0.269383752 -0.181307045
[6] -0.398456082 -0.293914299 0.142868607 -0.315351420 -0.163077139
[11] 0.029790108 -0.341961728 0.118953967 0.106644702 -0.016974811
[16] 0.297845264 -0.046419584 0.545663753 0.098583577 -0.193994161
[21] -0.142586238 -0.167650746 -0.202029344 0.325233216 0.183138964
[26] -0.576374026 -0.836454057 0.183351508 0.008012296 0.099200475
[31] 0.320559933 0.258377829 0.177021632 0.118297687 -0.154478783
[36] -0.495005569 -0.358631906 -0.174732059 0.278293733 -0.767552470
[41] 0.165199909 -0.114399401 0.442639950 0.384810666 0.008180979
[46] 0.838792237 0.092303432 0.040895539 -0.096481104 0.219535793
[51] 0.065988256 -0.083958300 0.232217206 -0.573184621 0.587156123
[56] 0.428714497 0.076479169 0.679740822 -0.368402362 0.237279725
[61] 0.048135065 -0.120620974 -0.208367730 -0.104976485 -0.475942252
[66] 0.142097662 -0.668030088 0.338564198 -0.212670103 0.375676639
[71] 0.430846953 -0.447092333 -0.049123918 -0.181300451 0.089322090
[76] 0.336729596 0.512198655 -0.318494506 0.297321734 -0.228344530
[81] -0.463256223 0.188584772 -0.235745912 -0.138384027 -0.305021500
[86] -0.237924090 0.221962090 -0.123766972 -0.088440374 -0.269178137
[91] -0.284654956 0.312584523 -0.032795822 -0.095451432 -0.244311067
[96] -0.095241350 0.001235307 -0.294057792 0.581826981 -0.080085106
[101] 0.012459084 0.076276996 -0.590708868 -0.220383140 0.481556243
[106] -0.498840734 0.595176911 -0.245403950 -0.080361003 -0.428095061
[111] -0.399546634 -0.371406357 0.224153254 0.408566974 0.035870412
[116] 0.220168995 -0.146843302 0.018906748 -0.387804782 -0.031285877
[121] 0.047182173 -0.107730732 0.061925719 -0.003457197 -0.284020472
[126] -0.144390907 -0.114248703 0.143851950 -0.006208798 0.245855302
[131] -0.096017449 -0.055100288 -0.300249220 0.039566440 -0.577548272
[136] -0.017898449 0.105560318 0.181458522 0.259821371 0.272510588
[141] -0.818305225 -0.033160283 -0.398406642 -0.467657910 -0.252759070
[146] 0.090909022 0.498615312 -0.469147458 0.126021491 -0.368112476
[151] -0.154447341 -0.166935993 0.341160833 0.109890715 0.140608618
[156] 0.366119273 -0.351760456 0.493501378 0.041632015 -0.475343515
[161] 0.640464218 0.279964946 0.316475776 0.383314442 0.361504967
[166] 0.362463508 0.433373532 -0.526108193 0.061248804 -0.028350052
[171] -0.080994595 0.430054117 0.269216928 0.030125621 -0.050673305
[176] -0.360109805 -0.104561814 0.041089470 -0.055288451 -0.272671946
[181] 0.022028757 0.071103320 0.024896537 -0.556049478 -0.257043008
[186] -0.651450922 0.129018375 -0.002739938 0.072953416 0.051596277
[191] 0.218648463 -0.267470009 -0.190363347 0.067042498 -0.085137482
[196] -0.384833993 -0.521195653 -0.006684037 -0.550788111 -0.193856163
[201] 0.292303728 0.685497953 0.030425824 -0.465552550 -0.302618285
[206] -0.438122177 0.070647917 0.265191757 -0.139137246 -0.252457839
[211] -0.230318939 0.040808018 0.342908975 -0.046590691 0.538474490
[216] -0.569231958 0.084874243 0.067782623 0.081223039 -0.349737885
[221] 0.022755629 0.351757974 0.319347343 -0.059100996 0.071635623
[226] 0.282504036 0.519522421 0.078229769 -0.191334146 0.195251540
>
> proc.time()
user system elapsed
3.71 18.56 884.28
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x000001c68c4ff3b0>
> .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: 0x000001c68c4ff3b0>
> .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: 0x000001c68c4ff3b0>
> .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: 0x000001c68c4ff3b0>
> 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: 0x000001c68c4ffa10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001c68c4ffa10>
> .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: 0x000001c68c4ffa10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001c68c4ffa10>
> .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: 0x000001c68c4ffa10>
> 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: 0x000001c68c4ff5f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001c68c4ff5f0>
> .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: 0x000001c68c4ff5f0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000001c68c4ff5f0>
> .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: 0x000001c68c4ff5f0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x000001c68c4ff5f0>
> .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: 0x000001c68c4ff5f0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x000001c68c4ff5f0>
> .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: 0x000001c68c4ff5f0>
> 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: 0x000001c68c4ff6b0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x000001c68c4ff6b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001c68c4ff6b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001c68c4ff6b0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1e40664e6580" "BufferedMatrixFile1e4067b01e89"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1e40664e6580" "BufferedMatrixFile1e4067b01e89"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001c68c4ff050>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001c68c4ff050>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000001c68c4ff050>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000001c68c4ff050>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x000001c68c4ff050>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x000001c68c4ff050>
> .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: 0x000001c68b87a290>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001c68b87a290>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000001c68b87a290>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x000001c68b87a290>
> 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: 0x000001c68c4ff290>
> .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: 0x000001c68c4ff290>
> rm(P)
>
> proc.time()
user system elapsed
0.34 0.14 0.64
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.25 0.09 0.50