Ben Bolstad
| Snapshot Date: 2024-06-19 14:00 -0400 (Wed, 19 Jun 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 2024-06-21 17:39 -0400 (Fri, 21 Jun 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4758 |
| palomino3 | Windows Server 2022 Datacenter | x64 | 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup" | 4492 |
| merida1 | macOS 12.7.4 Monterey | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4506 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4464 |
| 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 | | ||||||||
| palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.4 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: F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=F:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings BufferedMatrix_1.68.0.tar.gz |
| StartedAt: 2024-06-20 01:29:03 -0400 (Thu, 20 Jun 2024) |
| EndedAt: 2024-06-20 01:30:56 -0400 (Thu, 20 Jun 2024) |
| EllapsedTime: 113.7 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=F:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings BufferedMatrix_1.68.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck'
* using R version 4.4.0 (2024-04-24 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 'F:/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
'F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/00check.log'
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library 'F:/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"F:/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"F:/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"F:/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"F:/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 -LF:/biocbuild/bbs-3.19-bioc/R/bin/x64 -lR
installing to F:/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 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup"
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
0.29 0.39 0.73
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "F:/biocbuild/bbs-3.19-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 468464 25.1 1021761 54.6 633414 33.9
Vcells 853870 6.6 8388608 64.0 2003138 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] "Thu Jun 20 01:29:57 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] "Thu Jun 20 01:29:57 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: 0x000002d91c2fd230>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu Jun 20 01:30:08 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] "Thu Jun 20 01:30:13 2024"
>
> ColMode(tmp2)
<pointer: 0x000002d91c2fd230>
>
>
>
> ### 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,] 101.3529310 -1.2330891 0.5390382 -0.3760693
[2,] 0.1754802 1.0164021 -0.1434228 -1.6307909
[3,] 1.4264916 2.1631910 -1.6519948 -0.3356334
[4,] 1.4339012 0.9549621 -0.3945945 -0.1609345
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: F:/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,] 101.3529310 1.2330891 0.5390382 0.3760693
[2,] 0.1754802 1.0164021 0.1434228 1.6307909
[3,] 1.4264916 2.1631910 1.6519948 0.3356334
[4,] 1.4339012 0.9549621 0.3945945 0.1609345
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: F:/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,] 10.0674193 1.1104454 0.7341922 0.6132449
[2,] 0.4189036 1.0081677 0.3787121 1.2770242
[3,] 1.1943582 1.4707791 1.2852995 0.5793388
[4,] 1.1974561 0.9772216 0.6281676 0.4011665
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.19-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,] 227.02712 37.33754 32.88096 31.50852
[2,] 29.36452 36.09808 28.93054 39.40103
[3,] 38.37007 41.87098 39.50499 31.12902
[4,] 38.40846 35.72718 31.67627 29.17260
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x000002d91c2fd350>
> exp(tmp5)
<pointer: 0x000002d91c2fd350>
> log(tmp5,2)
<pointer: 0x000002d91c2fd350>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 472.5272
> Min(tmp5)
[1] 53.06667
> mean(tmp5)
[1] 72.26248
> Sum(tmp5)
[1] 14452.5
> Var(tmp5)
[1] 881.9766
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.68299 69.24915 71.27949 68.47066 70.95306 69.67996 73.35374 70.67368
[9] 69.70412 69.57791
> rowSums(tmp5)
[1] 1793.660 1384.983 1425.590 1369.413 1419.061 1393.599 1467.075 1413.474
[9] 1394.082 1391.558
> rowVars(tmp5)
[1] 8174.91018 69.11322 67.08148 79.66743 105.96378 54.88462
[7] 80.43689 106.89863 46.81474 79.40584
> rowSd(tmp5)
[1] 90.415210 8.313436 8.190328 8.925661 10.293871 7.408416 8.968661
[8] 10.339179 6.842130 8.910995
> rowMax(tmp5)
[1] 472.52721 87.01858 87.14896 87.84758 87.69240 84.44410 100.58818
[8] 84.82506 82.44884 88.23462
> rowMin(tmp5)
[1] 53.06667 60.21514 56.74526 55.20625 57.54076 54.48079 58.59653 53.66437
[9] 60.93095 53.21772
>
> colMeans(tmp5)
[1] 109.54006 76.07640 73.32685 68.44024 70.44691 66.90195 72.60243
[8] 77.99375 72.53624 68.40786 69.50137 62.37191 70.32056 66.26220
[15] 65.70924 67.91478 72.27615 68.94637 73.92030 71.75395
> colSums(tmp5)
[1] 1095.4006 760.7640 733.2685 684.4024 704.4691 669.0195 726.0243
[8] 779.9375 725.3624 684.0786 695.0137 623.7191 703.2056 662.6220
[15] 657.0924 679.1478 722.7615 689.4637 739.2030 717.5395
> colVars(tmp5)
[1] 16323.89880 39.95796 55.16291 66.87098 83.34650 48.38291
[7] 82.61542 76.40256 94.20354 63.41650 120.55585 99.78423
[13] 67.89109 62.22172 25.97622 58.72194 66.45307 69.95413
[19] 51.40735 32.14112
> colSd(tmp5)
[1] 127.765014 6.321231 7.427174 8.177468 9.129430 6.955783
[7] 9.089303 8.740856 9.705851 7.963448 10.979793 9.989206
[13] 8.239605 7.888075 5.096687 7.663024 8.151875 8.363859
[19] 7.169892 5.669314
> colMax(tmp5)
[1] 472.52721 87.14896 82.22446 84.44410 84.67497 76.45186 87.84758
[8] 100.58818 88.23462 78.95273 85.56167 85.89120 88.46437 80.45249
[15] 75.00189 78.60752 82.70066 87.69240 86.84191 78.62564
> colMin(tmp5)
[1] 59.66969 63.64264 60.21514 60.52639 58.20603 58.75236 57.54076 69.88918
[9] 58.38209 59.50610 54.18637 53.21772 59.52330 53.06667 58.79058 56.93753
[17] 54.48079 61.02828 63.37966 61.76874
>
>
> ### 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] 89.68299 69.24915 71.27949 68.47066 70.95306 NA 73.35374 70.67368
[9] 69.70412 69.57791
> rowSums(tmp5)
[1] 1793.660 1384.983 1425.590 1369.413 1419.061 NA 1467.075 1413.474
[9] 1394.082 1391.558
> rowVars(tmp5)
[1] 8174.91018 69.11322 67.08148 79.66743 105.96378 51.88070
[7] 80.43689 106.89863 46.81474 79.40584
> rowSd(tmp5)
[1] 90.415210 8.313436 8.190328 8.925661 10.293871 7.202826 8.968661
[8] 10.339179 6.842130 8.910995
> rowMax(tmp5)
[1] 472.52721 87.01858 87.14896 87.84758 87.69240 NA 100.58818
[8] 84.82506 82.44884 88.23462
> rowMin(tmp5)
[1] 53.06667 60.21514 56.74526 55.20625 57.54076 NA 58.59653 53.66437
[9] 60.93095 53.21772
>
> colMeans(tmp5)
[1] 109.54006 76.07640 73.32685 68.44024 70.44691 66.90195 72.60243
[8] 77.99375 72.53624 NA 69.50137 62.37191 70.32056 66.26220
[15] 65.70924 67.91478 72.27615 68.94637 73.92030 71.75395
> colSums(tmp5)
[1] 1095.4006 760.7640 733.2685 684.4024 704.4691 669.0195 726.0243
[8] 779.9375 725.3624 NA 695.0137 623.7191 703.2056 662.6220
[15] 657.0924 679.1478 722.7615 689.4637 739.2030 717.5395
> colVars(tmp5)
[1] 16323.89880 39.95796 55.16291 66.87098 83.34650 48.38291
[7] 82.61542 76.40256 94.20354 NA 120.55585 99.78423
[13] 67.89109 62.22172 25.97622 58.72194 66.45307 69.95413
[19] 51.40735 32.14112
> colSd(tmp5)
[1] 127.765014 6.321231 7.427174 8.177468 9.129430 6.955783
[7] 9.089303 8.740856 9.705851 NA 10.979793 9.989206
[13] 8.239605 7.888075 5.096687 7.663024 8.151875 8.363859
[19] 7.169892 5.669314
> colMax(tmp5)
[1] 472.52721 87.14896 82.22446 84.44410 84.67497 76.45186 87.84758
[8] 100.58818 88.23462 NA 85.56167 85.89120 88.46437 80.45249
[15] 75.00189 78.60752 82.70066 87.69240 86.84191 78.62564
> colMin(tmp5)
[1] 59.66969 63.64264 60.21514 60.52639 58.20603 58.75236 57.54076 69.88918
[9] 58.38209 NA 54.18637 53.21772 59.52330 53.06667 58.79058 56.93753
[17] 54.48079 61.02828 63.37966 61.76874
>
> Max(tmp5,na.rm=TRUE)
[1] 472.5272
> Min(tmp5,na.rm=TRUE)
[1] 53.06667
> mean(tmp5,na.rm=TRUE)
[1] 72.32658
> Sum(tmp5,na.rm=TRUE)
[1] 14392.99
> Var(tmp5,na.rm=TRUE)
[1] 885.6051
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.68299 69.24915 71.27949 68.47066 70.95306 70.21543 73.35374 70.67368
[9] 69.70412 69.57791
> rowSums(tmp5,na.rm=TRUE)
[1] 1793.660 1384.983 1425.590 1369.413 1419.061 1334.093 1467.075 1413.474
[9] 1394.082 1391.558
> rowVars(tmp5,na.rm=TRUE)
[1] 8174.91018 69.11322 67.08148 79.66743 105.96378 51.88070
[7] 80.43689 106.89863 46.81474 79.40584
> rowSd(tmp5,na.rm=TRUE)
[1] 90.415210 8.313436 8.190328 8.925661 10.293871 7.202826 8.968661
[8] 10.339179 6.842130 8.910995
> rowMax(tmp5,na.rm=TRUE)
[1] 472.52721 87.01858 87.14896 87.84758 87.69240 84.44410 100.58818
[8] 84.82506 82.44884 88.23462
> rowMin(tmp5,na.rm=TRUE)
[1] 53.06667 60.21514 56.74526 55.20625 57.54076 54.48079 58.59653 53.66437
[9] 60.93095 53.21772
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.54006 76.07640 73.32685 68.44024 70.44691 66.90195 72.60243
[8] 77.99375 72.53624 69.39695 69.50137 62.37191 70.32056 66.26220
[15] 65.70924 67.91478 72.27615 68.94637 73.92030 71.75395
> colSums(tmp5,na.rm=TRUE)
[1] 1095.4006 760.7640 733.2685 684.4024 704.4691 669.0195 726.0243
[8] 779.9375 725.3624 624.5725 695.0137 623.7191 703.2056 662.6220
[15] 657.0924 679.1478 722.7615 689.4637 739.2030 717.5395
> colVars(tmp5,na.rm=TRUE)
[1] 16323.89880 39.95796 55.16291 66.87098 83.34650 48.38291
[7] 82.61542 76.40256 94.20354 60.33782 120.55585 99.78423
[13] 67.89109 62.22172 25.97622 58.72194 66.45307 69.95413
[19] 51.40735 32.14112
> colSd(tmp5,na.rm=TRUE)
[1] 127.765014 6.321231 7.427174 8.177468 9.129430 6.955783
[7] 9.089303 8.740856 9.705851 7.767742 10.979793 9.989206
[13] 8.239605 7.888075 5.096687 7.663024 8.151875 8.363859
[19] 7.169892 5.669314
> colMax(tmp5,na.rm=TRUE)
[1] 472.52721 87.14896 82.22446 84.44410 84.67497 76.45186 87.84758
[8] 100.58818 88.23462 78.95273 85.56167 85.89120 88.46437 80.45249
[15] 75.00189 78.60752 82.70066 87.69240 86.84191 78.62564
> colMin(tmp5,na.rm=TRUE)
[1] 59.66969 63.64264 60.21514 60.52639 58.20603 58.75236 57.54076 69.88918
[9] 58.38209 59.97713 54.18637 53.21772 59.52330 53.06667 58.79058 56.93753
[17] 54.48079 61.02828 63.37966 61.76874
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.68299 69.24915 71.27949 68.47066 70.95306 NaN 73.35374 70.67368
[9] 69.70412 69.57791
> rowSums(tmp5,na.rm=TRUE)
[1] 1793.660 1384.983 1425.590 1369.413 1419.061 0.000 1467.075 1413.474
[9] 1394.082 1391.558
> rowVars(tmp5,na.rm=TRUE)
[1] 8174.91018 69.11322 67.08148 79.66743 105.96378 NA
[7] 80.43689 106.89863 46.81474 79.40584
> rowSd(tmp5,na.rm=TRUE)
[1] 90.415210 8.313436 8.190328 8.925661 10.293871 NA 8.968661
[8] 10.339179 6.842130 8.910995
> rowMax(tmp5,na.rm=TRUE)
[1] 472.52721 87.01858 87.14896 87.84758 87.69240 NA 100.58818
[8] 84.82506 82.44884 88.23462
> rowMin(tmp5,na.rm=TRUE)
[1] 53.06667 60.21514 56.74526 55.20625 57.54076 NA 58.59653 53.66437
[9] 60.93095 53.21772
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.08121 76.24097 72.81655 66.66204 70.90899 65.84085 72.76617
[8] 78.65003 72.71268 NaN 68.90541 61.49952 70.72526 65.70771
[15] 66.10895 68.05760 74.25341 69.56042 74.10329 70.99043
> colSums(tmp5,na.rm=TRUE)
[1] 1035.7309 686.1687 655.3489 599.9583 638.1809 592.5677 654.8955
[8] 707.8503 654.4142 0.0000 620.1487 553.4957 636.5273 591.3694
[15] 594.9806 612.5184 668.2807 626.0437 666.9296 638.9139
> colVars(tmp5,na.rm=TRUE)
[1] 18018.96203 44.64804 59.12873 39.65715 91.36281 41.76402
[7] 92.64074 81.10745 105.62873 NA 131.62974 103.69524
[13] 74.53494 66.54052 27.42584 65.83269 30.77710 74.45656
[19] 57.45652 29.60043
> colSd(tmp5,na.rm=TRUE)
[1] 134.234727 6.681919 7.689521 6.297393 9.558389 6.462509
[7] 9.625006 9.005968 10.277584 NA 11.473001 10.183086
[13] 8.633362 8.157237 5.236969 8.113734 5.547712 8.628822
[19] 7.580008 5.440627
> colMax(tmp5,na.rm=TRUE)
[1] 472.52721 87.14896 82.22446 82.00809 84.67497 74.35010 87.84758
[8] 100.58818 88.23462 -Inf 85.56167 85.89120 88.46437 80.45249
[15] 75.00189 78.60752 82.70066 87.69240 86.84191 78.22219
> colMin(tmp5,na.rm=TRUE)
[1] 61.11839 63.64264 60.21514 60.52639 58.20603 58.75236 57.54076 69.88918
[9] 58.38209 Inf 54.18637 53.21772 59.52330 53.06667 58.79058 56.93753
[17] 66.04294 61.02828 63.37966 61.76874
>
>
>
>
> 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] 192.0478 246.3944 139.4801 232.4306 446.5859 242.2725 161.6401 314.8169
[9] 375.6115 130.6400
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 192.0478 246.3944 139.4801 232.4306 446.5859 242.2725 161.6401 314.8169
[9] 375.6115 130.6400
>
>
>
> 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] 7.105427e-14 -2.842171e-14 8.526513e-14 5.684342e-14 -1.705303e-13
[6] -1.421085e-13 5.684342e-14 2.842171e-14 2.842171e-14 -8.526513e-14
[11] 2.842171e-14 -8.526513e-14 -1.136868e-13 0.000000e+00 2.557954e-13
[16] 1.136868e-13 0.000000e+00 0.000000e+00 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)
+ }
10 17
6 2
1 4
2 3
1 2
2 9
4 9
9 5
8 19
5 15
5 11
2 10
7 1
1 20
8 5
10 20
3 14
1 19
6 17
1 4
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] 2.167977
> Min(tmp)
[1] -2.033462
> mean(tmp)
[1] 0.1474155
> Sum(tmp)
[1] 14.74155
> Var(tmp)
[1] 1.006613
>
> rowMeans(tmp)
[1] 0.1474155
> rowSums(tmp)
[1] 14.74155
> rowVars(tmp)
[1] 1.006613
> rowSd(tmp)
[1] 1.003301
> rowMax(tmp)
[1] 2.167977
> rowMin(tmp)
[1] -2.033462
>
> colMeans(tmp)
[1] 1.8783159519 -0.5074961794 0.2386622997 0.4478058974 -0.1744822465
[6] -0.1841427794 0.9412338241 -0.4139534598 1.4142356605 1.3207353809
[11] -0.2691670301 0.7230914780 -1.9382422936 -0.0757135152 -1.2544319195
[16] -0.6356012104 -1.1005186983 0.5672036342 -1.5909531483 0.9911389344
[21] 1.6388282906 -1.2668534372 0.4159047923 -1.2160068729 -1.2417005556
[26] 0.5730657014 1.3959668570 2.1679768156 -0.6013274730 0.6269584890
[31] -0.4639605242 0.2372160992 -0.8583546398 2.0649016589 0.1566649621
[36] -0.6432327533 1.4132464428 -0.7597598148 1.2351126006 -0.4979566439
[41] -0.0008145178 -1.0999159975 2.0304174732 0.7313341257 0.3128540083
[46] 0.4173731732 -0.9266621322 0.5976741409 0.1860764909 0.6596943041
[51] 1.8062170615 0.2578136293 1.9417194969 -0.6818246454 0.0677300631
[56] -0.3169946436 1.9421690496 -0.2355701224 0.8868605813 -0.0725029444
[61] 0.0274465452 0.4601903519 1.4290196334 0.3481147114 0.1365209664
[66] 0.6462682019 -1.9559503076 0.1931557635 -0.1843771836 -2.0334624552
[71] 1.2630853170 -0.9231698172 0.5496774700 -0.6281727303 0.0428197383
[76] -0.8081422418 -0.7928159633 -0.3833800013 -0.4270463762 0.4567710005
[81] -0.2792860951 1.1788428358 1.1408411507 0.4028735894 1.2048997540
[86] -0.1292429117 0.2676340345 -1.0738078066 -0.4616657109 2.0363687284
[91] 0.6314809379 -0.2507834458 1.9053039652 -1.0849091356 -1.1975887964
[96] -0.8141349070 1.1340032341 0.8471158679 -0.7889360407 -0.6020682252
> colSums(tmp)
[1] 1.8783159519 -0.5074961794 0.2386622997 0.4478058974 -0.1744822465
[6] -0.1841427794 0.9412338241 -0.4139534598 1.4142356605 1.3207353809
[11] -0.2691670301 0.7230914780 -1.9382422936 -0.0757135152 -1.2544319195
[16] -0.6356012104 -1.1005186983 0.5672036342 -1.5909531483 0.9911389344
[21] 1.6388282906 -1.2668534372 0.4159047923 -1.2160068729 -1.2417005556
[26] 0.5730657014 1.3959668570 2.1679768156 -0.6013274730 0.6269584890
[31] -0.4639605242 0.2372160992 -0.8583546398 2.0649016589 0.1566649621
[36] -0.6432327533 1.4132464428 -0.7597598148 1.2351126006 -0.4979566439
[41] -0.0008145178 -1.0999159975 2.0304174732 0.7313341257 0.3128540083
[46] 0.4173731732 -0.9266621322 0.5976741409 0.1860764909 0.6596943041
[51] 1.8062170615 0.2578136293 1.9417194969 -0.6818246454 0.0677300631
[56] -0.3169946436 1.9421690496 -0.2355701224 0.8868605813 -0.0725029444
[61] 0.0274465452 0.4601903519 1.4290196334 0.3481147114 0.1365209664
[66] 0.6462682019 -1.9559503076 0.1931557635 -0.1843771836 -2.0334624552
[71] 1.2630853170 -0.9231698172 0.5496774700 -0.6281727303 0.0428197383
[76] -0.8081422418 -0.7928159633 -0.3833800013 -0.4270463762 0.4567710005
[81] -0.2792860951 1.1788428358 1.1408411507 0.4028735894 1.2048997540
[86] -0.1292429117 0.2676340345 -1.0738078066 -0.4616657109 2.0363687284
[91] 0.6314809379 -0.2507834458 1.9053039652 -1.0849091356 -1.1975887964
[96] -0.8141349070 1.1340032341 0.8471158679 -0.7889360407 -0.6020682252
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] 1.8783159519 -0.5074961794 0.2386622997 0.4478058974 -0.1744822465
[6] -0.1841427794 0.9412338241 -0.4139534598 1.4142356605 1.3207353809
[11] -0.2691670301 0.7230914780 -1.9382422936 -0.0757135152 -1.2544319195
[16] -0.6356012104 -1.1005186983 0.5672036342 -1.5909531483 0.9911389344
[21] 1.6388282906 -1.2668534372 0.4159047923 -1.2160068729 -1.2417005556
[26] 0.5730657014 1.3959668570 2.1679768156 -0.6013274730 0.6269584890
[31] -0.4639605242 0.2372160992 -0.8583546398 2.0649016589 0.1566649621
[36] -0.6432327533 1.4132464428 -0.7597598148 1.2351126006 -0.4979566439
[41] -0.0008145178 -1.0999159975 2.0304174732 0.7313341257 0.3128540083
[46] 0.4173731732 -0.9266621322 0.5976741409 0.1860764909 0.6596943041
[51] 1.8062170615 0.2578136293 1.9417194969 -0.6818246454 0.0677300631
[56] -0.3169946436 1.9421690496 -0.2355701224 0.8868605813 -0.0725029444
[61] 0.0274465452 0.4601903519 1.4290196334 0.3481147114 0.1365209664
[66] 0.6462682019 -1.9559503076 0.1931557635 -0.1843771836 -2.0334624552
[71] 1.2630853170 -0.9231698172 0.5496774700 -0.6281727303 0.0428197383
[76] -0.8081422418 -0.7928159633 -0.3833800013 -0.4270463762 0.4567710005
[81] -0.2792860951 1.1788428358 1.1408411507 0.4028735894 1.2048997540
[86] -0.1292429117 0.2676340345 -1.0738078066 -0.4616657109 2.0363687284
[91] 0.6314809379 -0.2507834458 1.9053039652 -1.0849091356 -1.1975887964
[96] -0.8141349070 1.1340032341 0.8471158679 -0.7889360407 -0.6020682252
> colMin(tmp)
[1] 1.8783159519 -0.5074961794 0.2386622997 0.4478058974 -0.1744822465
[6] -0.1841427794 0.9412338241 -0.4139534598 1.4142356605 1.3207353809
[11] -0.2691670301 0.7230914780 -1.9382422936 -0.0757135152 -1.2544319195
[16] -0.6356012104 -1.1005186983 0.5672036342 -1.5909531483 0.9911389344
[21] 1.6388282906 -1.2668534372 0.4159047923 -1.2160068729 -1.2417005556
[26] 0.5730657014 1.3959668570 2.1679768156 -0.6013274730 0.6269584890
[31] -0.4639605242 0.2372160992 -0.8583546398 2.0649016589 0.1566649621
[36] -0.6432327533 1.4132464428 -0.7597598148 1.2351126006 -0.4979566439
[41] -0.0008145178 -1.0999159975 2.0304174732 0.7313341257 0.3128540083
[46] 0.4173731732 -0.9266621322 0.5976741409 0.1860764909 0.6596943041
[51] 1.8062170615 0.2578136293 1.9417194969 -0.6818246454 0.0677300631
[56] -0.3169946436 1.9421690496 -0.2355701224 0.8868605813 -0.0725029444
[61] 0.0274465452 0.4601903519 1.4290196334 0.3481147114 0.1365209664
[66] 0.6462682019 -1.9559503076 0.1931557635 -0.1843771836 -2.0334624552
[71] 1.2630853170 -0.9231698172 0.5496774700 -0.6281727303 0.0428197383
[76] -0.8081422418 -0.7928159633 -0.3833800013 -0.4270463762 0.4567710005
[81] -0.2792860951 1.1788428358 1.1408411507 0.4028735894 1.2048997540
[86] -0.1292429117 0.2676340345 -1.0738078066 -0.4616657109 2.0363687284
[91] 0.6314809379 -0.2507834458 1.9053039652 -1.0849091356 -1.1975887964
[96] -0.8141349070 1.1340032341 0.8471158679 -0.7889360407 -0.6020682252
> colMedians(tmp)
[1] 1.8783159519 -0.5074961794 0.2386622997 0.4478058974 -0.1744822465
[6] -0.1841427794 0.9412338241 -0.4139534598 1.4142356605 1.3207353809
[11] -0.2691670301 0.7230914780 -1.9382422936 -0.0757135152 -1.2544319195
[16] -0.6356012104 -1.1005186983 0.5672036342 -1.5909531483 0.9911389344
[21] 1.6388282906 -1.2668534372 0.4159047923 -1.2160068729 -1.2417005556
[26] 0.5730657014 1.3959668570 2.1679768156 -0.6013274730 0.6269584890
[31] -0.4639605242 0.2372160992 -0.8583546398 2.0649016589 0.1566649621
[36] -0.6432327533 1.4132464428 -0.7597598148 1.2351126006 -0.4979566439
[41] -0.0008145178 -1.0999159975 2.0304174732 0.7313341257 0.3128540083
[46] 0.4173731732 -0.9266621322 0.5976741409 0.1860764909 0.6596943041
[51] 1.8062170615 0.2578136293 1.9417194969 -0.6818246454 0.0677300631
[56] -0.3169946436 1.9421690496 -0.2355701224 0.8868605813 -0.0725029444
[61] 0.0274465452 0.4601903519 1.4290196334 0.3481147114 0.1365209664
[66] 0.6462682019 -1.9559503076 0.1931557635 -0.1843771836 -2.0334624552
[71] 1.2630853170 -0.9231698172 0.5496774700 -0.6281727303 0.0428197383
[76] -0.8081422418 -0.7928159633 -0.3833800013 -0.4270463762 0.4567710005
[81] -0.2792860951 1.1788428358 1.1408411507 0.4028735894 1.2048997540
[86] -0.1292429117 0.2676340345 -1.0738078066 -0.4616657109 2.0363687284
[91] 0.6314809379 -0.2507834458 1.9053039652 -1.0849091356 -1.1975887964
[96] -0.8141349070 1.1340032341 0.8471158679 -0.7889360407 -0.6020682252
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.878316 -0.5074962 0.2386623 0.4478059 -0.1744822 -0.1841428 0.9412338
[2,] 1.878316 -0.5074962 0.2386623 0.4478059 -0.1744822 -0.1841428 0.9412338
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.4139535 1.414236 1.320735 -0.269167 0.7230915 -1.938242 -0.07571352
[2,] -0.4139535 1.414236 1.320735 -0.269167 0.7230915 -1.938242 -0.07571352
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.254432 -0.6356012 -1.100519 0.5672036 -1.590953 0.9911389 1.638828
[2,] -1.254432 -0.6356012 -1.100519 0.5672036 -1.590953 0.9911389 1.638828
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.266853 0.4159048 -1.216007 -1.241701 0.5730657 1.395967 2.167977
[2,] -1.266853 0.4159048 -1.216007 -1.241701 0.5730657 1.395967 2.167977
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.6013275 0.6269585 -0.4639605 0.2372161 -0.8583546 2.064902 0.156665
[2,] -0.6013275 0.6269585 -0.4639605 0.2372161 -0.8583546 2.064902 0.156665
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.6432328 1.413246 -0.7597598 1.235113 -0.4979566 -0.0008145178 -1.099916
[2,] -0.6432328 1.413246 -0.7597598 1.235113 -0.4979566 -0.0008145178 -1.099916
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 2.030417 0.7313341 0.312854 0.4173732 -0.9266621 0.5976741 0.1860765
[2,] 2.030417 0.7313341 0.312854 0.4173732 -0.9266621 0.5976741 0.1860765
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.6596943 1.806217 0.2578136 1.941719 -0.6818246 0.06773006 -0.3169946
[2,] 0.6596943 1.806217 0.2578136 1.941719 -0.6818246 0.06773006 -0.3169946
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 1.942169 -0.2355701 0.8868606 -0.07250294 0.02744655 0.4601904 1.42902
[2,] 1.942169 -0.2355701 0.8868606 -0.07250294 0.02744655 0.4601904 1.42902
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.3481147 0.136521 0.6462682 -1.95595 0.1931558 -0.1843772 -2.033462
[2,] 0.3481147 0.136521 0.6462682 -1.95595 0.1931558 -0.1843772 -2.033462
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.263085 -0.9231698 0.5496775 -0.6281727 0.04281974 -0.8081422 -0.792816
[2,] 1.263085 -0.9231698 0.5496775 -0.6281727 0.04281974 -0.8081422 -0.792816
[,78] [,79] [,80] [,81] [,82] [,83] [,84] [,85]
[1,] -0.38338 -0.4270464 0.456771 -0.2792861 1.178843 1.140841 0.4028736 1.2049
[2,] -0.38338 -0.4270464 0.456771 -0.2792861 1.178843 1.140841 0.4028736 1.2049
[,86] [,87] [,88] [,89] [,90] [,91] [,92]
[1,] -0.1292429 0.267634 -1.073808 -0.4616657 2.036369 0.6314809 -0.2507834
[2,] -0.1292429 0.267634 -1.073808 -0.4616657 2.036369 0.6314809 -0.2507834
[,93] [,94] [,95] [,96] [,97] [,98] [,99]
[1,] 1.905304 -1.084909 -1.197589 -0.8141349 1.134003 0.8471159 -0.788936
[2,] 1.905304 -1.084909 -1.197589 -0.8141349 1.134003 0.8471159 -0.788936
[,100]
[1,] -0.6020682
[2,] -0.6020682
>
>
> Max(tmp2)
[1] 2.450212
> Min(tmp2)
[1] -2.696747
> mean(tmp2)
[1] -0.007274685
> Sum(tmp2)
[1] -0.7274685
> Var(tmp2)
[1] 1.079872
>
> rowMeans(tmp2)
[1] 0.44619817 -2.69674735 -2.54827801 0.02710769 1.03929777 -0.28489279
[7] 0.47874785 -0.00261356 0.69660191 1.05250928 -0.64487983 -0.58770249
[13] -0.59285000 -0.50115668 0.53339907 1.04054716 -0.55967556 0.61458723
[19] -0.40491293 0.25013399 -1.86066645 -0.29192573 0.71305781 -0.15948221
[25] -0.17571963 -2.53461693 0.42510599 -0.08422494 -0.58164270 0.71543763
[31] -1.66217489 0.44707485 0.69888003 0.01420275 -0.97566387 -1.05252449
[37] -1.03133378 -0.67259946 -0.07824630 0.64673467 -0.26373978 0.24214257
[43] -1.03895669 -0.82829818 2.11859802 -0.73433047 -1.21846144 -0.54153409
[49] 1.61859404 1.02904892 -0.69855302 -1.14611521 -1.29375166 1.53597629
[55] 1.06160557 -0.74736676 -0.49102234 0.99633395 0.24792487 -0.13472794
[61] -2.13199149 -0.69511258 0.62028829 0.37100966 0.53650195 0.68713924
[67] -0.37989963 0.47716800 -1.11598589 0.23072731 1.43194400 1.75485402
[73] -0.42566940 0.59424659 0.11614468 -1.06161830 1.60401696 0.31480149
[79] 0.79496536 -0.25600171 -1.38544224 -0.44874649 0.08724375 0.27356041
[85] -1.80992278 -0.45224908 -1.12859838 1.51834444 0.53232699 2.13865204
[91] 0.20418461 1.51893826 0.94438108 0.09401025 0.01360457 1.04939809
[97] 0.94501450 2.45021226 -1.27356929 0.96520009
> rowSums(tmp2)
[1] 0.44619817 -2.69674735 -2.54827801 0.02710769 1.03929777 -0.28489279
[7] 0.47874785 -0.00261356 0.69660191 1.05250928 -0.64487983 -0.58770249
[13] -0.59285000 -0.50115668 0.53339907 1.04054716 -0.55967556 0.61458723
[19] -0.40491293 0.25013399 -1.86066645 -0.29192573 0.71305781 -0.15948221
[25] -0.17571963 -2.53461693 0.42510599 -0.08422494 -0.58164270 0.71543763
[31] -1.66217489 0.44707485 0.69888003 0.01420275 -0.97566387 -1.05252449
[37] -1.03133378 -0.67259946 -0.07824630 0.64673467 -0.26373978 0.24214257
[43] -1.03895669 -0.82829818 2.11859802 -0.73433047 -1.21846144 -0.54153409
[49] 1.61859404 1.02904892 -0.69855302 -1.14611521 -1.29375166 1.53597629
[55] 1.06160557 -0.74736676 -0.49102234 0.99633395 0.24792487 -0.13472794
[61] -2.13199149 -0.69511258 0.62028829 0.37100966 0.53650195 0.68713924
[67] -0.37989963 0.47716800 -1.11598589 0.23072731 1.43194400 1.75485402
[73] -0.42566940 0.59424659 0.11614468 -1.06161830 1.60401696 0.31480149
[79] 0.79496536 -0.25600171 -1.38544224 -0.44874649 0.08724375 0.27356041
[85] -1.80992278 -0.45224908 -1.12859838 1.51834444 0.53232699 2.13865204
[91] 0.20418461 1.51893826 0.94438108 0.09401025 0.01360457 1.04939809
[97] 0.94501450 2.45021226 -1.27356929 0.96520009
> 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] 0.44619817 -2.69674735 -2.54827801 0.02710769 1.03929777 -0.28489279
[7] 0.47874785 -0.00261356 0.69660191 1.05250928 -0.64487983 -0.58770249
[13] -0.59285000 -0.50115668 0.53339907 1.04054716 -0.55967556 0.61458723
[19] -0.40491293 0.25013399 -1.86066645 -0.29192573 0.71305781 -0.15948221
[25] -0.17571963 -2.53461693 0.42510599 -0.08422494 -0.58164270 0.71543763
[31] -1.66217489 0.44707485 0.69888003 0.01420275 -0.97566387 -1.05252449
[37] -1.03133378 -0.67259946 -0.07824630 0.64673467 -0.26373978 0.24214257
[43] -1.03895669 -0.82829818 2.11859802 -0.73433047 -1.21846144 -0.54153409
[49] 1.61859404 1.02904892 -0.69855302 -1.14611521 -1.29375166 1.53597629
[55] 1.06160557 -0.74736676 -0.49102234 0.99633395 0.24792487 -0.13472794
[61] -2.13199149 -0.69511258 0.62028829 0.37100966 0.53650195 0.68713924
[67] -0.37989963 0.47716800 -1.11598589 0.23072731 1.43194400 1.75485402
[73] -0.42566940 0.59424659 0.11614468 -1.06161830 1.60401696 0.31480149
[79] 0.79496536 -0.25600171 -1.38544224 -0.44874649 0.08724375 0.27356041
[85] -1.80992278 -0.45224908 -1.12859838 1.51834444 0.53232699 2.13865204
[91] 0.20418461 1.51893826 0.94438108 0.09401025 0.01360457 1.04939809
[97] 0.94501450 2.45021226 -1.27356929 0.96520009
> rowMin(tmp2)
[1] 0.44619817 -2.69674735 -2.54827801 0.02710769 1.03929777 -0.28489279
[7] 0.47874785 -0.00261356 0.69660191 1.05250928 -0.64487983 -0.58770249
[13] -0.59285000 -0.50115668 0.53339907 1.04054716 -0.55967556 0.61458723
[19] -0.40491293 0.25013399 -1.86066645 -0.29192573 0.71305781 -0.15948221
[25] -0.17571963 -2.53461693 0.42510599 -0.08422494 -0.58164270 0.71543763
[31] -1.66217489 0.44707485 0.69888003 0.01420275 -0.97566387 -1.05252449
[37] -1.03133378 -0.67259946 -0.07824630 0.64673467 -0.26373978 0.24214257
[43] -1.03895669 -0.82829818 2.11859802 -0.73433047 -1.21846144 -0.54153409
[49] 1.61859404 1.02904892 -0.69855302 -1.14611521 -1.29375166 1.53597629
[55] 1.06160557 -0.74736676 -0.49102234 0.99633395 0.24792487 -0.13472794
[61] -2.13199149 -0.69511258 0.62028829 0.37100966 0.53650195 0.68713924
[67] -0.37989963 0.47716800 -1.11598589 0.23072731 1.43194400 1.75485402
[73] -0.42566940 0.59424659 0.11614468 -1.06161830 1.60401696 0.31480149
[79] 0.79496536 -0.25600171 -1.38544224 -0.44874649 0.08724375 0.27356041
[85] -1.80992278 -0.45224908 -1.12859838 1.51834444 0.53232699 2.13865204
[91] 0.20418461 1.51893826 0.94438108 0.09401025 0.01360457 1.04939809
[97] 0.94501450 2.45021226 -1.27356929 0.96520009
>
> colMeans(tmp2)
[1] -0.007274685
> colSums(tmp2)
[1] -0.7274685
> colVars(tmp2)
[1] 1.079872
> colSd(tmp2)
[1] 1.039169
> colMax(tmp2)
[1] 2.450212
> colMin(tmp2)
[1] -2.696747
> colMedians(tmp2)
[1] 0.02065522
> colRanges(tmp2)
[,1]
[1,] -2.696747
[2,] 2.450212
>
> 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] 2.9799382 -0.9358392 -2.0663281 0.9645017 2.7938893 0.6823538
[7] -0.7495848 1.4484002 0.9912082 0.6188463
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1263151
[2,] -0.1984732
[3,] 0.4624121
[4,] 0.9341659
[5,] 1.2646295
>
> rowApply(tmp,sum)
[1] 0.002038113 5.397933185 2.008580404 -3.797299960 -1.936085458
[6] -1.526703782 0.124030397 0.538868773 3.412415175 2.503608687
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 7 4 2 10 4 6 6 9 9
[2,] 7 9 1 3 2 7 5 4 7 2
[3,] 1 5 5 8 4 6 3 8 8 1
[4,] 3 3 7 6 7 10 7 2 1 5
[5,] 8 2 6 10 3 9 8 5 3 6
[6,] 6 8 3 4 6 5 2 1 10 7
[7,] 5 6 9 7 1 3 1 10 5 10
[8,] 2 10 10 1 5 8 4 3 4 3
[9,] 9 1 2 9 9 2 10 9 6 8
[10,] 4 4 8 5 8 1 9 7 2 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.3387050 1.7304359 0.8295501 -4.1207087 1.8338572 2.9030513
[7] -1.0242949 3.0747514 0.1114801 -2.0044347 3.0580357 -1.6025426
[13] 0.9150035 0.9460978 1.5191961 -1.8356322 -0.6832828 -3.5182316
[19] -0.7936348 0.9633454
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8196148
[2,] 0.3512830
[3,] 0.5892247
[4,] 0.9554446
[5,] 1.2623676
>
> rowApply(tmp,sum)
[1] -1.160545 -1.144222 -1.693480 3.435704 5.203289
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 18 14 19 13 4
[2,] 20 7 11 11 7
[3,] 19 5 12 9 8
[4,] 5 4 1 6 14
[5,] 17 17 13 4 16
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.2623676 1.51667607 1.27742838 -0.8672384 1.20669680 0.8454731
[2,] 0.3512830 -0.27957939 -0.62489232 -0.9447699 0.50991082 -0.3568305
[3,] 0.9554446 -0.08832473 -0.04992313 -2.3822690 -0.02985058 -0.4875564
[4,] 0.5892247 0.48541451 0.10854800 -0.7349270 -0.86878753 1.4343345
[5,] -0.8196148 0.09624945 0.11838920 0.8084956 1.01588770 1.4676306
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -2.71369555 0.8525813 -0.1905871 0.4262299 0.3036175 -0.6460301
[2,] -1.32158179 0.7520224 0.8393232 -1.1655854 0.4490080 -0.1479379
[3,] 2.69661305 -0.2478569 -0.7832846 -0.7525865 0.4456895 -0.1266361
[4,] -0.08582636 2.0601229 -1.1942716 0.6061840 0.6036229 -1.6122757
[5,] 0.40019574 -0.3421184 1.4403002 -1.1186766 1.2560978 0.9303373
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.8329416 -0.08477852 -0.39540889 -1.3049351 -1.2671912 0.09981127
[2,] 0.1562378 0.25218838 1.16684927 0.3547773 -0.2650339 0.26397894
[3,] 0.2228454 0.51535606 0.43942796 -0.2992866 -0.1675877 -1.52058301
[4,] 0.8716410 0.12003247 -0.09848647 0.4937531 0.8506555 -0.80802561
[5,] 1.4972209 0.14329946 0.40681420 -1.0799408 0.1658744 -1.55341317
[,19] [,20]
[1,] -0.58769109 0.93907108
[2,] -0.06440737 -1.06918271
[3,] 0.59298266 -0.62609349
[4,] -1.04933078 1.66410190
[5,] 0.31481177 0.05544864
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.19-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: F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 625 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 541 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: F:/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 0.790873 -0.7959054 0.08810366 1.102795 -0.6947408 1.261981 -1.353476
col8 col9 col10 col11 col12 col13 col14
row1 -0.7956444 0.9278589 0.9220273 -0.3695107 0.5427902 1.524152 -0.4608363
col15 col16 col17 col18 col19 col20
row1 -0.9880311 0.5325544 -0.2909901 -0.9799375 1.527189 -0.5115265
> tmp[,"col10"]
col10
row1 0.9220273
row2 -0.8850359
row3 0.7526338
row4 0.4942241
row5 -0.2143856
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.7908730 -0.7959054 0.08810366 1.102795 -0.6947408 1.261981 -1.353476
row5 0.9406319 0.8520891 0.76561343 -2.296115 -0.6804371 1.249239 -1.472748
col8 col9 col10 col11 col12 col13
row1 -0.7956444 0.9278589 0.9220273 -0.36951072 0.5427902 1.5241524
row5 -1.6536066 -0.2536745 -0.2143856 -0.02223577 1.2665574 -0.3456855
col14 col15 col16 col17 col18 col19
row1 -0.4608363 -0.9880311 0.5325544 -0.2909901 -0.97993752 1.52718871
row5 1.3256844 -1.0582653 -0.5911403 -1.5924526 -0.06542965 -0.01991762
col20
row1 -0.5115265
row5 -0.9279698
> tmp[,c("col6","col20")]
col6 col20
row1 1.2619814 -0.5115265
row2 0.3510384 0.5928422
row3 -0.8393408 -0.3731376
row4 -0.6564381 -0.8073244
row5 1.2492390 -0.9279698
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.261981 -0.5115265
row5 1.249239 -0.9279698
>
>
>
>
> 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 48.22203 51.33723 49.81949 50.08979 50.79857 106.4343 48.65028 50.46656
col9 col10 col11 col12 col13 col14 col15 col16
row1 47.66104 50.61223 49.61326 50.47756 52.11195 50.71869 50.48799 50.0045
col17 col18 col19 col20
row1 49.22734 50.94795 50.47006 105.2348
> tmp[,"col10"]
col10
row1 50.61223
row2 29.59607
row3 31.22099
row4 30.06955
row5 49.88448
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.22203 51.33723 49.81949 50.08979 50.79857 106.4343 48.65028 50.46656
row5 49.91112 51.05087 50.10439 50.14619 50.32901 105.7403 50.34067 50.61468
col9 col10 col11 col12 col13 col14 col15 col16
row1 47.66104 50.61223 49.61326 50.47756 52.11195 50.71869 50.48799 50.00450
row5 48.94316 49.88448 50.82804 49.95192 50.19950 48.47808 50.33029 48.72807
col17 col18 col19 col20
row1 49.22734 50.94795 50.47006 105.2348
row5 48.88704 47.73946 49.81803 102.9288
> tmp[,c("col6","col20")]
col6 col20
row1 106.43427 105.23480
row2 76.77717 74.77716
row3 73.02005 74.81947
row4 74.66958 75.67155
row5 105.74035 102.92882
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.4343 105.2348
row5 105.7403 102.9288
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.4343 105.2348
row5 105.7403 102.9288
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.2646132
[2,] -1.4610927
[3,] -0.9604105
[4,] 0.7657780
[5,] 0.5762015
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.46251247 0.56841056
[2,] -0.31369603 0.12001558
[3,] 0.02301346 0.01430673
[4,] 0.81146730 0.19235078
[5,] 0.36621830 -0.58621531
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.8964919 0.5963301
[2,] 1.2436194 -0.9468856
[3,] -0.1874116 -1.0920246
[4,] 1.0889991 -1.0752562
[5,] -0.2011969 0.3773615
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.8964919
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.8964919
[2,] 1.2436194
>
>
>
> 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 -2.2335195 0.7655676 -1.7509482 -0.4747357 0.04156397 0.05185082
row1 -0.7924118 1.3811180 0.4211017 0.3260389 0.20692036 -0.33546278
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -1.3841222 1.18116881 -1.1733089 -0.3407964 0.7021700 -0.40520415
row1 -0.9026298 0.08344796 -0.7893756 1.6596364 -0.5756123 -0.07939845
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.2738651 -1.0799147 0.8736614 0.7317158 1.261547072 1.626981 0.8612177
row1 0.9347156 -0.7551526 -1.5686734 0.8343795 0.004936602 -1.207047 1.7210926
[,20]
row3 0.4352899
row1 -1.8012397
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.2889704 -0.3289234 0.4589842 1.226455 -0.1780194 -1.488142 0.1329241
[,8] [,9] [,10]
row2 0.1476405 -1.0135 -0.5076827
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.1566354 -1.294917 -1.276203 1.02179 -0.08760141 -0.4270388 -0.5977864
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.730269 -2.461778 1.034978 0.60976 1.836322 -0.9475719 -0.6128903
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.5662026 1.085602 -1.969061 0.3436913 -0.6128122 -0.5457754
>
>
> 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: 0x000002d91c2fdcb0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM105841a444eb"
[2] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM105856262df6"
[3] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM10582df059f2"
[4] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM10584b8b698d"
[5] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM10587c137012"
[6] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM10587dd21206"
[7] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM10586d02657b"
[8] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM10582f37a39"
[9] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM10581b835fea"
[10] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM10584c5332ec"
[11] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM105831923c7c"
[12] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM10586c9d794b"
[13] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM1058d0331c4"
[14] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM10583c302992"
[15] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM1058176a581b"
>
>
> ### 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: 0x000002d91ebff2f0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x000002d91ebff2f0>
Warning message:
In dir.create(new.directory) :
'F:\biocbuild\bbs-3.19-bioc\meat\BufferedMatrix.Rcheck\tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x000002d91ebff2f0>
> rowMedians(tmp)
[1] -0.0733279935 -0.4473909186 0.2141666824 -0.0671918076 0.2722089775
[6] -0.2795591328 0.0390804199 -0.0405702094 -0.5553287959 -0.0509503594
[11] -0.5219167924 -0.4715705720 0.4244816590 -0.1186481053 0.0764370511
[16] -0.4298968527 -0.1373452326 -0.2922223387 -0.0542469471 0.5113906312
[21] -0.3720906999 -0.5773406823 0.0687254141 0.1487225788 -0.4139764478
[26] 0.1455273817 -0.1696494372 0.3247936023 -0.0603879705 0.1776153407
[31] -0.0739292028 0.0814197082 0.4975961667 -0.1035975479 0.1486948113
[36] -0.1596434609 -0.2786943619 -0.5366543512 -0.2191363161 -0.3767966003
[41] 0.1099522360 0.5272138094 0.0086120765 -0.1970607625 -0.0509348263
[46] -0.1490129922 -0.4979260856 -0.3683034629 -0.4217084583 -0.3166029721
[51] 0.1070946292 -0.0504549022 0.3755962082 -0.1088926694 0.3674096652
[56] -0.2479959335 0.1317658038 -0.4030652508 0.3279276138 0.2821887348
[61] -0.3505087814 0.2257449230 -0.2247911917 0.0888354893 -0.0052049539
[66] -0.0169860891 -0.2830102910 0.0623508495 -0.8600587702 0.5403744251
[71] -0.0788578803 -0.1046103388 -0.2432480144 -0.4538039013 -0.0339139920
[76] -0.0499085326 0.1873779981 0.0503342671 0.5958061712 0.0755502661
[81] -0.3854619852 0.0268655833 -0.4608947849 -0.2565712480 0.1010969246
[86] -0.0823678685 0.0960134254 0.5240255830 -0.0964644682 0.2349797820
[91] -0.3246407477 0.1417065676 0.2783497200 0.0212245802 0.0871779734
[96] 0.1360808533 0.4926233315 0.0291902574 0.3522143178 0.4024117441
[101] -0.3247010234 -0.2210729308 -0.1090719397 -0.2233734597 -0.0111731510
[106] 0.1658716399 -0.0208869546 -0.1332975256 -0.1580636466 -0.0008349674
[111] -0.0563221441 0.4664257911 0.1895774776 0.0206439497 -0.0050059809
[116] 0.0393882825 -0.3250386665 0.2407934639 -0.1124221181 -0.1880427595
[121] 0.0849002958 0.3960185389 0.0438134850 -0.3103504353 0.0167701232
[126] -0.2509791852 -0.0982316503 -0.3685385424 -0.0066170611 0.0009577008
[131] 0.0882975793 0.3368747037 -0.1865968474 -0.3139111834 0.0927119270
[136] 0.0950909476 -0.7330134661 0.1721971055 0.0842858233 -0.3272134097
[141] 0.2831340712 0.4335859638 0.2970149048 0.1471047788 -0.0686024758
[146] -0.4678639089 0.0997966121 0.2319932392 -0.3172378763 -0.2482364306
[151] -0.2603495245 -0.0177309580 0.2139355643 0.5639248911 0.2616041551
[156] -0.2103674502 0.0115889485 0.0034722858 -0.3020340996 0.1281990341
[161] 0.0787780856 -0.5808532656 -0.3375642500 0.4325588415 0.9004452242
[166] -0.0777935955 0.2633563581 -0.2577183504 0.0844479358 -0.0869585770
[171] -0.0181678615 0.0050541171 -0.2083727860 -0.2417317316 0.2020798469
[176] 0.1126104527 -0.4356935835 -0.7450979688 -0.2837866102 0.1267364756
[181] 0.0697589659 0.4917918493 -0.5144616288 0.1269156594 -0.3793258838
[186] -0.2612835947 -0.2248386056 0.0007419047 -0.1286493562 0.7264283403
[191] -0.0854685909 0.7326669287 0.2965341524 -0.6471149761 -0.0858096526
[196] -0.2191683440 0.1718090232 -0.4250992095 -0.1649687668 -0.1534432919
[201] 0.2731471084 -0.0332970918 -0.2226159073 0.5037454726 0.2787113832
[206] -0.0296907732 0.0977639353 0.2456510640 0.1958884639 -0.1516526135
[211] -0.4400952443 0.2054188330 -0.0614140650 0.0477291062 0.3262716678
[216] 0.0491995225 -0.0722968960 -0.0760166726 -0.4766967664 0.3159313452
[221] 0.0090657884 -0.2009050604 -0.1903530131 0.2627318377 -0.2469652432
[226] 0.1104243734 -0.2645863122 -0.0431134221 0.6644120694 -0.0271003022
>
> proc.time()
user system elapsed
4.50 27.68 49.15
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup"
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: 0x000002a12a4f86b0>
> .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: 0x000002a12a4f86b0>
> .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: 0x000002a12a4f86b0>
> .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: 0x000002a12a4f86b0>
> 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: 0x000002a12a4f8b30>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002a12a4f8b30>
> .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: 0x000002a12a4f8b30>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002a12a4f8b30>
> .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: 0x000002a12a4f8b30>
> 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: 0x000002a12a4f8710>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002a12a4f8710>
> .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: 0x000002a12a4f8710>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000002a12a4f8710>
> .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: 0x000002a12a4f8710>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x000002a12a4f8710>
> .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: 0x000002a12a4f8710>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x000002a12a4f8710>
> .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: 0x000002a12a4f8710>
> 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: 0x000002a12a4f8890>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x000002a12a4f8890>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002a12a4f8890>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002a12a4f8890>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile4d45a8d2016" "BufferedMatrixFile4d460ea3547"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile4d45a8d2016" "BufferedMatrixFile4d460ea3547"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002a12a4f8350>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002a12a4f8350>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000002a12a4f8350>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000002a12a4f8350>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x000002a12a4f8350>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x000002a12a4f8350>
> .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: 0x000002a12a4f8ad0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002a12a4f8ad0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000002a12a4f8ad0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x000002a12a4f8ad0>
> 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: 0x000002a12a4f8b90>
> .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: 0x000002a12a4f8b90>
> rm(P)
>
> proc.time()
user system elapsed
0.42 0.31 0.71
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup"
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
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.26 0.29 0.43