| Back to Multiple platform build/check report for BioC 3.19: simplified long |
|
This page was generated on 2024-05-22 11:35:28 -0400 (Wed, 22 May 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" | 4751 |
| palomino3 | Windows Server 2022 Datacenter | x64 | 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup" | 4485 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 3444 |
| 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 | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.6.5 Ventura / arm64 | see weekly results here | ||||||||||||
|
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: 2024-05-21 23:47:03 -0400 (Tue, 21 May 2024) |
| EndedAt: 2024-05-21 23:48:09 -0400 (Tue, 21 May 2024) |
| EllapsedTime: 65.9 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
0.34 0.21 0.65
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] "Tue May 21 23:47:28 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] "Tue May 21 23:47:28 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: 0x000001de556fe950>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Tue May 21 23:47:35 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] "Tue May 21 23:47:37 2024"
>
> ColMode(tmp2)
<pointer: 0x000001de556fe950>
>
>
>
> ### 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,] 100.172220 -0.0528543 -1.1108952 0.8181821
[2,] -0.112033 0.2430282 -1.0332961 0.5764320
[3,] 2.389489 -0.9663995 0.3907871 0.4409474
[4,] 1.213411 -0.6618786 -2.6606043 -0.2885368
> 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,] 100.172220 0.0528543 1.1108952 0.8181821
[2,] 0.112033 0.2430282 1.0332961 0.5764320
[3,] 2.389489 0.9663995 0.3907871 0.4409474
[4,] 1.213411 0.6618786 2.6606043 0.2885368
> 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,] 10.0086073 0.2299006 1.0539901 0.9045342
[2,] 0.3347134 0.4929789 1.0165117 0.7592312
[3,] 1.5457973 0.9830562 0.6251297 0.6640387
[4,] 1.1015491 0.8135592 1.6311359 0.5371562
>
> 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,] 225.25829 27.35186 36.65080 34.86352
[2,] 28.45917 30.17282 36.19841 33.16874
[3,] 42.84746 35.79696 31.64208 32.08133
[4,] 37.22890 33.79747 43.97196 30.66010
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x000001de556fe770>
> exp(tmp5)
<pointer: 0x000001de556fe770>
> log(tmp5,2)
<pointer: 0x000001de556fe770>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.8456
> Min(tmp5)
[1] 53.14271
> mean(tmp5)
[1] 73.05107
> Sum(tmp5)
[1] 14610.21
> Var(tmp5)
[1] 868.4023
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 87.99465 69.73377 72.11791 73.89919 71.96889 73.05314 68.36522 70.83934
[9] 72.08333 70.45527
> rowSums(tmp5)
[1] 1759.893 1394.675 1442.358 1477.984 1439.378 1461.063 1367.304 1416.787
[9] 1441.667 1409.105
> rowVars(tmp5)
[1] 8113.71856 45.66075 51.63128 100.44281 76.77598 99.35265
[7] 98.88313 100.30620 66.37227 56.33345
> rowSd(tmp5)
[1] 90.076182 6.757274 7.185491 10.022116 8.762191 9.967580 9.944000
[8] 10.015298 8.146918 7.505561
> rowMax(tmp5)
[1] 468.84563 83.24903 89.18138 91.52188 86.48529 89.26058 89.29757
[8] 87.85461 85.32939 82.77957
> rowMin(tmp5)
[1] 53.14271 59.23403 58.87028 58.21302 56.80950 55.95716 55.75782 56.36765
[9] 55.34379 54.34722
>
> colMeans(tmp5)
[1] 109.00144 74.29979 72.70378 66.95501 70.42522 72.61210 69.63767
[8] 74.14138 71.76394 70.41550 72.31571 67.56870 68.55147 70.87841
[15] 76.88682 68.07674 65.12716 74.45552 72.08127 73.12378
> colSums(tmp5)
[1] 1090.0144 742.9979 727.0378 669.5501 704.2522 726.1210 696.3767
[8] 741.4138 717.6394 704.1550 723.1571 675.6870 685.5147 708.7841
[15] 768.8682 680.7674 651.2716 744.5552 720.8127 731.2378
> colVars(tmp5)
[1] 16091.22462 133.69227 79.95813 83.37170 91.87600 55.39146
[7] 65.48480 99.95817 117.78264 59.09261 72.00353 50.82830
[13] 65.40884 55.08650 76.37580 32.53332 60.48034 77.92985
[19] 89.69532 53.68903
> colSd(tmp5)
[1] 126.851191 11.562537 8.941931 9.130810 9.585197 7.442544
[7] 8.092268 9.997908 10.852771 7.687172 8.485489 7.129397
[13] 8.087573 7.422028 8.739325 5.703799 7.776911 8.827789
[19] 9.470761 7.327280
> colMax(tmp5)
[1] 468.84563 88.55664 91.52188 86.72412 87.73755 85.32484 80.71765
[8] 89.29757 89.26058 80.00957 88.98232 80.72792 84.55026 84.17436
[15] 89.25569 75.64757 77.80789 88.43828 83.95742 83.24903
> colMin(tmp5)
[1] 56.80950 56.92931 62.26801 55.34379 53.14271 62.36864 54.34722 58.87028
[9] 56.36765 55.75782 63.79862 55.95716 54.56156 58.79520 63.06390 56.67692
[17] 53.29599 62.22697 58.97444 62.84202
>
>
> ### 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] 87.99465 NA 72.11791 73.89919 71.96889 73.05314 68.36522 70.83934
[9] 72.08333 70.45527
> rowSums(tmp5)
[1] 1759.893 NA 1442.358 1477.984 1439.378 1461.063 1367.304 1416.787
[9] 1441.667 1409.105
> rowVars(tmp5)
[1] 8113.71856 41.75040 51.63128 100.44281 76.77598 99.35265
[7] 98.88313 100.30620 66.37227 56.33345
> rowSd(tmp5)
[1] 90.076182 6.461455 7.185491 10.022116 8.762191 9.967580 9.944000
[8] 10.015298 8.146918 7.505561
> rowMax(tmp5)
[1] 468.84563 NA 89.18138 91.52188 86.48529 89.26058 89.29757
[8] 87.85461 85.32939 82.77957
> rowMin(tmp5)
[1] 53.14271 NA 58.87028 58.21302 56.80950 55.95716 55.75782 56.36765
[9] 55.34379 54.34722
>
> colMeans(tmp5)
[1] NA 74.29979 72.70378 66.95501 70.42522 72.61210 69.63767 74.14138
[9] 71.76394 70.41550 72.31571 67.56870 68.55147 70.87841 76.88682 68.07674
[17] 65.12716 74.45552 72.08127 73.12378
> colSums(tmp5)
[1] NA 742.9979 727.0378 669.5501 704.2522 726.1210 696.3767 741.4138
[9] 717.6394 704.1550 723.1571 675.6870 685.5147 708.7841 768.8682 680.7674
[17] 651.2716 744.5552 720.8127 731.2378
> colVars(tmp5)
[1] NA 133.69227 79.95813 83.37170 91.87600 55.39146 65.48480
[8] 99.95817 117.78264 59.09261 72.00353 50.82830 65.40884 55.08650
[15] 76.37580 32.53332 60.48034 77.92985 89.69532 53.68903
> colSd(tmp5)
[1] NA 11.562537 8.941931 9.130810 9.585197 7.442544 8.092268
[8] 9.997908 10.852771 7.687172 8.485489 7.129397 8.087573 7.422028
[15] 8.739325 5.703799 7.776911 8.827789 9.470761 7.327280
> colMax(tmp5)
[1] NA 88.55664 91.52188 86.72412 87.73755 85.32484 80.71765 89.29757
[9] 89.26058 80.00957 88.98232 80.72792 84.55026 84.17436 89.25569 75.64757
[17] 77.80789 88.43828 83.95742 83.24903
> colMin(tmp5)
[1] NA 56.92931 62.26801 55.34379 53.14271 62.36864 54.34722 58.87028
[9] 56.36765 55.75782 63.79862 55.95716 54.56156 58.79520 63.06390 56.67692
[17] 53.29599 62.22697 58.97444 62.84202
>
> Max(tmp5,na.rm=TRUE)
[1] 468.8456
> Min(tmp5,na.rm=TRUE)
[1] 53.14271
> mean(tmp5,na.rm=TRUE)
[1] 73.1205
> Sum(tmp5,na.rm=TRUE)
[1] 14550.98
> Var(tmp5,na.rm=TRUE)
[1] 871.8192
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.99465 70.28639 72.11791 73.89919 71.96889 73.05314 68.36522 70.83934
[9] 72.08333 70.45527
> rowSums(tmp5,na.rm=TRUE)
[1] 1759.893 1335.441 1442.358 1477.984 1439.378 1461.063 1367.304 1416.787
[9] 1441.667 1409.105
> rowVars(tmp5,na.rm=TRUE)
[1] 8113.71856 41.75040 51.63128 100.44281 76.77598 99.35265
[7] 98.88313 100.30620 66.37227 56.33345
> rowSd(tmp5,na.rm=TRUE)
[1] 90.076182 6.461455 7.185491 10.022116 8.762191 9.967580 9.944000
[8] 10.015298 8.146918 7.505561
> rowMax(tmp5,na.rm=TRUE)
[1] 468.84563 83.24903 89.18138 91.52188 86.48529 89.26058 89.29757
[8] 87.85461 85.32939 82.77957
> rowMin(tmp5,na.rm=TRUE)
[1] 53.14271 61.97752 58.87028 58.21302 56.80950 55.95716 55.75782 56.36765
[9] 55.34379 54.34722
>
> colMeans(tmp5,na.rm=TRUE)
[1] 114.53115 74.29979 72.70378 66.95501 70.42522 72.61210 69.63767
[8] 74.14138 71.76394 70.41550 72.31571 67.56870 68.55147 70.87841
[15] 76.88682 68.07674 65.12716 74.45552 72.08127 73.12378
> colSums(tmp5,na.rm=TRUE)
[1] 1030.7804 742.9979 727.0378 669.5501 704.2522 726.1210 696.3767
[8] 741.4138 717.6394 704.1550 723.1571 675.6870 685.5147 708.7841
[15] 768.8682 680.7674 651.2716 744.5552 720.8127 731.2378
> colVars(tmp5,na.rm=TRUE)
[1] 17758.62833 133.69227 79.95813 83.37170 91.87600 55.39146
[7] 65.48480 99.95817 117.78264 59.09261 72.00353 50.82830
[13] 65.40884 55.08650 76.37580 32.53332 60.48034 77.92985
[19] 89.69532 53.68903
> colSd(tmp5,na.rm=TRUE)
[1] 133.261504 11.562537 8.941931 9.130810 9.585197 7.442544
[7] 8.092268 9.997908 10.852771 7.687172 8.485489 7.129397
[13] 8.087573 7.422028 8.739325 5.703799 7.776911 8.827789
[19] 9.470761 7.327280
> colMax(tmp5,na.rm=TRUE)
[1] 468.84563 88.55664 91.52188 86.72412 87.73755 85.32484 80.71765
[8] 89.29757 89.26058 80.00957 88.98232 80.72792 84.55026 84.17436
[15] 89.25569 75.64757 77.80789 88.43828 83.95742 83.24903
> colMin(tmp5,na.rm=TRUE)
[1] 56.80950 56.92931 62.26801 55.34379 53.14271 62.36864 54.34722 58.87028
[9] 56.36765 55.75782 63.79862 55.95716 54.56156 58.79520 63.06390 56.67692
[17] 53.29599 62.22697 58.97444 62.84202
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.99465 NaN 72.11791 73.89919 71.96889 73.05314 68.36522 70.83934
[9] 72.08333 70.45527
> rowSums(tmp5,na.rm=TRUE)
[1] 1759.893 0.000 1442.358 1477.984 1439.378 1461.063 1367.304 1416.787
[9] 1441.667 1409.105
> rowVars(tmp5,na.rm=TRUE)
[1] 8113.71856 NA 51.63128 100.44281 76.77598 99.35265
[7] 98.88313 100.30620 66.37227 56.33345
> rowSd(tmp5,na.rm=TRUE)
[1] 90.076182 NA 7.185491 10.022116 8.762191 9.967580 9.944000
[8] 10.015298 8.146918 7.505561
> rowMax(tmp5,na.rm=TRUE)
[1] 468.84563 NA 89.18138 91.52188 86.48529 89.26058 89.29757
[8] 87.85461 85.32939 82.77957
> rowMin(tmp5,na.rm=TRUE)
[1] 53.14271 NA 58.87028 58.21302 56.80950 55.95716 55.75782 56.36765
[9] 55.34379 54.34722
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] NaN 75.57746 72.41062 66.72374 71.36386 72.47979 69.25135 73.23078
[9] 72.24773 69.57905 72.83994 67.12024 67.99260 70.73035 78.42270 68.65456
[17] 65.28746 75.39800 72.55307 71.99875
> colSums(tmp5,na.rm=TRUE)
[1] 0.0000 680.1971 651.6956 600.5137 642.2747 652.3181 623.2622 659.0770
[9] 650.2295 626.2114 655.5594 604.0822 611.9334 636.5731 705.8043 617.8910
[17] 587.5872 678.5820 652.9776 647.9887
> colVars(tmp5,na.rm=TRUE)
[1] NA 132.03886 88.98602 93.19147 93.44887 62.11842 71.99145
[8] 103.12457 129.87245 58.60808 77.91234 54.91931 70.07123 61.72570
[15] 59.38483 32.84391 67.75127 77.67816 98.40311 46.16117
> colSd(tmp5,na.rm=TRUE)
[1] NA 11.490817 9.433240 9.653573 9.666896 7.881524 8.484778
[8] 10.155027 11.396159 7.655592 8.826797 7.410757 8.370856 7.856571
[15] 7.706155 5.730960 8.231116 8.813522 9.919834 6.794201
> colMax(tmp5,na.rm=TRUE)
[1] -Inf 88.55664 91.52188 86.72412 87.73755 85.32484 80.71765 89.29757
[9] 89.26058 80.00957 88.98232 80.72792 84.55026 84.17436 89.25569 75.64757
[17] 77.80789 88.43828 83.95742 80.57576
> colMin(tmp5,na.rm=TRUE)
[1] Inf 56.92931 62.26801 55.34379 53.14271 62.36864 54.34722 58.87028
[9] 56.36765 55.75782 63.79862 55.95716 54.56156 58.79520 67.00258 56.67692
[17] 53.29599 62.22697 58.97444 62.84202
>
>
>
>
> 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] 84.35834 225.64069 270.71837 349.72262 177.31498 231.29623 189.01976
[8] 151.09925 221.11328 118.50822
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 84.35834 225.64069 270.71837 349.72262 177.31498 231.29623 189.01976
[8] 151.09925 221.11328 118.50822
>
>
>
> 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 -5.684342e-14 -2.842171e-14 -1.421085e-13 2.842171e-14
[6] -2.273737e-13 2.842171e-14 4.547474e-13 -5.684342e-14 0.000000e+00
[11] -1.136868e-13 2.842171e-14 -5.684342e-14 1.705303e-13 5.684342e-14
[16] -2.273737e-13 -8.526513e-14 2.842171e-14 -5.684342e-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 11
7 13
9 16
2 15
2 16
7 14
2 15
5 19
1 15
3 6
6 20
7 1
5 8
1 20
9 12
9 15
1 19
5 19
4 17
10 3
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.477246
> Min(tmp)
[1] -3.117192
> mean(tmp)
[1] -0.1032401
> Sum(tmp)
[1] -10.32401
> Var(tmp)
[1] 1.037865
>
> rowMeans(tmp)
[1] -0.1032401
> rowSums(tmp)
[1] -10.32401
> rowVars(tmp)
[1] 1.037865
> rowSd(tmp)
[1] 1.018756
> rowMax(tmp)
[1] 2.477246
> rowMin(tmp)
[1] -3.117192
>
> colMeans(tmp)
[1] 0.301853408 -1.557572627 2.477246339 0.873138554 0.671134344
[6] 0.039411799 0.697057006 -0.722300504 0.299063030 1.796884908
[11] 0.027202845 -0.145809683 0.405989223 -0.845336030 -0.003927448
[16] 0.128227348 0.531392272 -0.274092299 -1.741937299 -0.881879105
[21] 0.648731617 0.535872112 -0.285177996 1.295239757 0.121308002
[26] -1.173842296 0.044887619 0.459567880 -0.898810921 -1.083111946
[31] -0.498250995 -0.172206993 0.462251546 -0.254505697 -0.553797848
[36] 0.060598428 1.214722132 2.045257698 0.727190308 0.923009693
[41] 0.415856628 0.676037950 -0.272495592 -0.602548437 -1.076828018
[46] 0.658678709 0.088481965 -0.617680513 1.493171212 -3.117192180
[51] -0.530773109 0.483216078 -1.331416342 -1.781277671 -1.006616541
[56] -0.971365482 -0.477833103 -0.630473774 0.763631104 -0.488176140
[61] 0.309402015 1.329777505 -2.178704245 0.473664834 0.377856277
[66] -1.294480666 0.572859492 -0.504179367 0.119753054 -1.326522768
[71] 0.590632058 -0.648885765 0.087670982 0.025707236 1.533916955
[76] 0.718324669 -2.189889062 -0.297017252 0.586787819 0.825366883
[81] -0.468687198 -0.122447352 -0.874875447 -1.803431625 0.415118487
[86] 0.024125433 0.200337468 -1.684822302 -1.692788794 0.907937171
[91] -1.322242599 0.080754032 -0.520434529 -2.642298395 -0.153160186
[96] 0.117132123 -0.089473903 1.563004898 1.826445549 -0.565317871
> colSums(tmp)
[1] 0.301853408 -1.557572627 2.477246339 0.873138554 0.671134344
[6] 0.039411799 0.697057006 -0.722300504 0.299063030 1.796884908
[11] 0.027202845 -0.145809683 0.405989223 -0.845336030 -0.003927448
[16] 0.128227348 0.531392272 -0.274092299 -1.741937299 -0.881879105
[21] 0.648731617 0.535872112 -0.285177996 1.295239757 0.121308002
[26] -1.173842296 0.044887619 0.459567880 -0.898810921 -1.083111946
[31] -0.498250995 -0.172206993 0.462251546 -0.254505697 -0.553797848
[36] 0.060598428 1.214722132 2.045257698 0.727190308 0.923009693
[41] 0.415856628 0.676037950 -0.272495592 -0.602548437 -1.076828018
[46] 0.658678709 0.088481965 -0.617680513 1.493171212 -3.117192180
[51] -0.530773109 0.483216078 -1.331416342 -1.781277671 -1.006616541
[56] -0.971365482 -0.477833103 -0.630473774 0.763631104 -0.488176140
[61] 0.309402015 1.329777505 -2.178704245 0.473664834 0.377856277
[66] -1.294480666 0.572859492 -0.504179367 0.119753054 -1.326522768
[71] 0.590632058 -0.648885765 0.087670982 0.025707236 1.533916955
[76] 0.718324669 -2.189889062 -0.297017252 0.586787819 0.825366883
[81] -0.468687198 -0.122447352 -0.874875447 -1.803431625 0.415118487
[86] 0.024125433 0.200337468 -1.684822302 -1.692788794 0.907937171
[91] -1.322242599 0.080754032 -0.520434529 -2.642298395 -0.153160186
[96] 0.117132123 -0.089473903 1.563004898 1.826445549 -0.565317871
> 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] 0.301853408 -1.557572627 2.477246339 0.873138554 0.671134344
[6] 0.039411799 0.697057006 -0.722300504 0.299063030 1.796884908
[11] 0.027202845 -0.145809683 0.405989223 -0.845336030 -0.003927448
[16] 0.128227348 0.531392272 -0.274092299 -1.741937299 -0.881879105
[21] 0.648731617 0.535872112 -0.285177996 1.295239757 0.121308002
[26] -1.173842296 0.044887619 0.459567880 -0.898810921 -1.083111946
[31] -0.498250995 -0.172206993 0.462251546 -0.254505697 -0.553797848
[36] 0.060598428 1.214722132 2.045257698 0.727190308 0.923009693
[41] 0.415856628 0.676037950 -0.272495592 -0.602548437 -1.076828018
[46] 0.658678709 0.088481965 -0.617680513 1.493171212 -3.117192180
[51] -0.530773109 0.483216078 -1.331416342 -1.781277671 -1.006616541
[56] -0.971365482 -0.477833103 -0.630473774 0.763631104 -0.488176140
[61] 0.309402015 1.329777505 -2.178704245 0.473664834 0.377856277
[66] -1.294480666 0.572859492 -0.504179367 0.119753054 -1.326522768
[71] 0.590632058 -0.648885765 0.087670982 0.025707236 1.533916955
[76] 0.718324669 -2.189889062 -0.297017252 0.586787819 0.825366883
[81] -0.468687198 -0.122447352 -0.874875447 -1.803431625 0.415118487
[86] 0.024125433 0.200337468 -1.684822302 -1.692788794 0.907937171
[91] -1.322242599 0.080754032 -0.520434529 -2.642298395 -0.153160186
[96] 0.117132123 -0.089473903 1.563004898 1.826445549 -0.565317871
> colMin(tmp)
[1] 0.301853408 -1.557572627 2.477246339 0.873138554 0.671134344
[6] 0.039411799 0.697057006 -0.722300504 0.299063030 1.796884908
[11] 0.027202845 -0.145809683 0.405989223 -0.845336030 -0.003927448
[16] 0.128227348 0.531392272 -0.274092299 -1.741937299 -0.881879105
[21] 0.648731617 0.535872112 -0.285177996 1.295239757 0.121308002
[26] -1.173842296 0.044887619 0.459567880 -0.898810921 -1.083111946
[31] -0.498250995 -0.172206993 0.462251546 -0.254505697 -0.553797848
[36] 0.060598428 1.214722132 2.045257698 0.727190308 0.923009693
[41] 0.415856628 0.676037950 -0.272495592 -0.602548437 -1.076828018
[46] 0.658678709 0.088481965 -0.617680513 1.493171212 -3.117192180
[51] -0.530773109 0.483216078 -1.331416342 -1.781277671 -1.006616541
[56] -0.971365482 -0.477833103 -0.630473774 0.763631104 -0.488176140
[61] 0.309402015 1.329777505 -2.178704245 0.473664834 0.377856277
[66] -1.294480666 0.572859492 -0.504179367 0.119753054 -1.326522768
[71] 0.590632058 -0.648885765 0.087670982 0.025707236 1.533916955
[76] 0.718324669 -2.189889062 -0.297017252 0.586787819 0.825366883
[81] -0.468687198 -0.122447352 -0.874875447 -1.803431625 0.415118487
[86] 0.024125433 0.200337468 -1.684822302 -1.692788794 0.907937171
[91] -1.322242599 0.080754032 -0.520434529 -2.642298395 -0.153160186
[96] 0.117132123 -0.089473903 1.563004898 1.826445549 -0.565317871
> colMedians(tmp)
[1] 0.301853408 -1.557572627 2.477246339 0.873138554 0.671134344
[6] 0.039411799 0.697057006 -0.722300504 0.299063030 1.796884908
[11] 0.027202845 -0.145809683 0.405989223 -0.845336030 -0.003927448
[16] 0.128227348 0.531392272 -0.274092299 -1.741937299 -0.881879105
[21] 0.648731617 0.535872112 -0.285177996 1.295239757 0.121308002
[26] -1.173842296 0.044887619 0.459567880 -0.898810921 -1.083111946
[31] -0.498250995 -0.172206993 0.462251546 -0.254505697 -0.553797848
[36] 0.060598428 1.214722132 2.045257698 0.727190308 0.923009693
[41] 0.415856628 0.676037950 -0.272495592 -0.602548437 -1.076828018
[46] 0.658678709 0.088481965 -0.617680513 1.493171212 -3.117192180
[51] -0.530773109 0.483216078 -1.331416342 -1.781277671 -1.006616541
[56] -0.971365482 -0.477833103 -0.630473774 0.763631104 -0.488176140
[61] 0.309402015 1.329777505 -2.178704245 0.473664834 0.377856277
[66] -1.294480666 0.572859492 -0.504179367 0.119753054 -1.326522768
[71] 0.590632058 -0.648885765 0.087670982 0.025707236 1.533916955
[76] 0.718324669 -2.189889062 -0.297017252 0.586787819 0.825366883
[81] -0.468687198 -0.122447352 -0.874875447 -1.803431625 0.415118487
[86] 0.024125433 0.200337468 -1.684822302 -1.692788794 0.907937171
[91] -1.322242599 0.080754032 -0.520434529 -2.642298395 -0.153160186
[96] 0.117132123 -0.089473903 1.563004898 1.826445549 -0.565317871
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.3018534 -1.557573 2.477246 0.8731386 0.6711343 0.0394118 0.697057
[2,] 0.3018534 -1.557573 2.477246 0.8731386 0.6711343 0.0394118 0.697057
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.7223005 0.299063 1.796885 0.02720285 -0.1458097 0.4059892 -0.845336
[2,] -0.7223005 0.299063 1.796885 0.02720285 -0.1458097 0.4059892 -0.845336
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.003927448 0.1282273 0.5313923 -0.2740923 -1.741937 -0.8818791 0.6487316
[2,] -0.003927448 0.1282273 0.5313923 -0.2740923 -1.741937 -0.8818791 0.6487316
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.5358721 -0.285178 1.29524 0.121308 -1.173842 0.04488762 0.4595679
[2,] 0.5358721 -0.285178 1.29524 0.121308 -1.173842 0.04488762 0.4595679
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.8988109 -1.083112 -0.498251 -0.172207 0.4622515 -0.2545057 -0.5537978
[2,] -0.8988109 -1.083112 -0.498251 -0.172207 0.4622515 -0.2545057 -0.5537978
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.06059843 1.214722 2.045258 0.7271903 0.9230097 0.4158566 0.676038
[2,] 0.06059843 1.214722 2.045258 0.7271903 0.9230097 0.4158566 0.676038
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.2724956 -0.6025484 -1.076828 0.6586787 0.08848196 -0.6176805 1.493171
[2,] -0.2724956 -0.6025484 -1.076828 0.6586787 0.08848196 -0.6176805 1.493171
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -3.117192 -0.5307731 0.4832161 -1.331416 -1.781278 -1.006617 -0.9713655
[2,] -3.117192 -0.5307731 0.4832161 -1.331416 -1.781278 -1.006617 -0.9713655
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.4778331 -0.6304738 0.7636311 -0.4881761 0.309402 1.329778 -2.178704
[2,] -0.4778331 -0.6304738 0.7636311 -0.4881761 0.309402 1.329778 -2.178704
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.4736648 0.3778563 -1.294481 0.5728595 -0.5041794 0.1197531 -1.326523
[2,] 0.4736648 0.3778563 -1.294481 0.5728595 -0.5041794 0.1197531 -1.326523
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.5906321 -0.6488858 0.08767098 0.02570724 1.533917 0.7183247 -2.189889
[2,] 0.5906321 -0.6488858 0.08767098 0.02570724 1.533917 0.7183247 -2.189889
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.2970173 0.5867878 0.8253669 -0.4686872 -0.1224474 -0.8748754 -1.803432
[2,] -0.2970173 0.5867878 0.8253669 -0.4686872 -0.1224474 -0.8748754 -1.803432
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.4151185 0.02412543 0.2003375 -1.684822 -1.692789 0.9079372 -1.322243
[2,] 0.4151185 0.02412543 0.2003375 -1.684822 -1.692789 0.9079372 -1.322243
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.08075403 -0.5204345 -2.642298 -0.1531602 0.1171321 -0.0894739 1.563005
[2,] 0.08075403 -0.5204345 -2.642298 -0.1531602 0.1171321 -0.0894739 1.563005
[,99] [,100]
[1,] 1.826446 -0.5653179
[2,] 1.826446 -0.5653179
>
>
> Max(tmp2)
[1] 2.137673
> Min(tmp2)
[1] -1.825151
> mean(tmp2)
[1] -0.01060469
> Sum(tmp2)
[1] -1.060469
> Var(tmp2)
[1] 0.7860301
>
> rowMeans(tmp2)
[1] 0.555826169 0.655715668 0.167385560 0.452889024 -0.157935202
[6] 0.107401338 -0.849236463 1.005558022 0.704555214 -1.683946337
[11] -1.705727950 -0.137861318 -0.160164241 -0.745389141 1.097964306
[16] 2.137673208 -0.682896967 0.018776076 0.267436881 -0.604896567
[21] 0.318977178 0.299966778 -0.081529422 0.346816948 0.284906979
[26] -0.430411743 -1.729979849 -0.309768436 0.105561404 -0.336260807
[31] 1.433837099 -0.576573842 0.435230944 0.963118827 -0.573655641
[36] 0.476313075 -0.369246857 1.542599858 -0.398198709 -0.403983870
[41] -1.824590162 1.687605021 0.952724491 -0.451478765 -0.081864189
[46] 0.477686289 0.574971627 0.737493344 0.951450164 1.667631986
[51] 0.076969463 -0.448289839 0.582947929 1.108278088 0.016930289
[56] 0.217645348 0.656586182 -1.184028458 0.575406296 -1.236047338
[61] -0.056925689 2.082638218 0.921501330 0.565657211 -0.965576997
[66] -1.170940981 0.358747812 0.004932476 0.720206633 -0.259010133
[71] -0.958226223 -1.152360453 -0.409852252 -0.351794336 -0.193744240
[76] 0.177042624 0.401686477 -0.578258036 1.509025656 -1.498116749
[81] -0.820158252 0.221429276 0.725514925 -1.825150616 -0.236284785
[86] -1.037215509 0.163568294 -0.857491838 0.919934238 -0.900183978
[91] -1.448781960 0.043427215 0.113006366 1.521766241 -1.057781504
[96] -0.580281636 -1.599992225 0.511967856 -0.033388070 -0.529879923
> rowSums(tmp2)
[1] 0.555826169 0.655715668 0.167385560 0.452889024 -0.157935202
[6] 0.107401338 -0.849236463 1.005558022 0.704555214 -1.683946337
[11] -1.705727950 -0.137861318 -0.160164241 -0.745389141 1.097964306
[16] 2.137673208 -0.682896967 0.018776076 0.267436881 -0.604896567
[21] 0.318977178 0.299966778 -0.081529422 0.346816948 0.284906979
[26] -0.430411743 -1.729979849 -0.309768436 0.105561404 -0.336260807
[31] 1.433837099 -0.576573842 0.435230944 0.963118827 -0.573655641
[36] 0.476313075 -0.369246857 1.542599858 -0.398198709 -0.403983870
[41] -1.824590162 1.687605021 0.952724491 -0.451478765 -0.081864189
[46] 0.477686289 0.574971627 0.737493344 0.951450164 1.667631986
[51] 0.076969463 -0.448289839 0.582947929 1.108278088 0.016930289
[56] 0.217645348 0.656586182 -1.184028458 0.575406296 -1.236047338
[61] -0.056925689 2.082638218 0.921501330 0.565657211 -0.965576997
[66] -1.170940981 0.358747812 0.004932476 0.720206633 -0.259010133
[71] -0.958226223 -1.152360453 -0.409852252 -0.351794336 -0.193744240
[76] 0.177042624 0.401686477 -0.578258036 1.509025656 -1.498116749
[81] -0.820158252 0.221429276 0.725514925 -1.825150616 -0.236284785
[86] -1.037215509 0.163568294 -0.857491838 0.919934238 -0.900183978
[91] -1.448781960 0.043427215 0.113006366 1.521766241 -1.057781504
[96] -0.580281636 -1.599992225 0.511967856 -0.033388070 -0.529879923
> 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] 0.555826169 0.655715668 0.167385560 0.452889024 -0.157935202
[6] 0.107401338 -0.849236463 1.005558022 0.704555214 -1.683946337
[11] -1.705727950 -0.137861318 -0.160164241 -0.745389141 1.097964306
[16] 2.137673208 -0.682896967 0.018776076 0.267436881 -0.604896567
[21] 0.318977178 0.299966778 -0.081529422 0.346816948 0.284906979
[26] -0.430411743 -1.729979849 -0.309768436 0.105561404 -0.336260807
[31] 1.433837099 -0.576573842 0.435230944 0.963118827 -0.573655641
[36] 0.476313075 -0.369246857 1.542599858 -0.398198709 -0.403983870
[41] -1.824590162 1.687605021 0.952724491 -0.451478765 -0.081864189
[46] 0.477686289 0.574971627 0.737493344 0.951450164 1.667631986
[51] 0.076969463 -0.448289839 0.582947929 1.108278088 0.016930289
[56] 0.217645348 0.656586182 -1.184028458 0.575406296 -1.236047338
[61] -0.056925689 2.082638218 0.921501330 0.565657211 -0.965576997
[66] -1.170940981 0.358747812 0.004932476 0.720206633 -0.259010133
[71] -0.958226223 -1.152360453 -0.409852252 -0.351794336 -0.193744240
[76] 0.177042624 0.401686477 -0.578258036 1.509025656 -1.498116749
[81] -0.820158252 0.221429276 0.725514925 -1.825150616 -0.236284785
[86] -1.037215509 0.163568294 -0.857491838 0.919934238 -0.900183978
[91] -1.448781960 0.043427215 0.113006366 1.521766241 -1.057781504
[96] -0.580281636 -1.599992225 0.511967856 -0.033388070 -0.529879923
> rowMin(tmp2)
[1] 0.555826169 0.655715668 0.167385560 0.452889024 -0.157935202
[6] 0.107401338 -0.849236463 1.005558022 0.704555214 -1.683946337
[11] -1.705727950 -0.137861318 -0.160164241 -0.745389141 1.097964306
[16] 2.137673208 -0.682896967 0.018776076 0.267436881 -0.604896567
[21] 0.318977178 0.299966778 -0.081529422 0.346816948 0.284906979
[26] -0.430411743 -1.729979849 -0.309768436 0.105561404 -0.336260807
[31] 1.433837099 -0.576573842 0.435230944 0.963118827 -0.573655641
[36] 0.476313075 -0.369246857 1.542599858 -0.398198709 -0.403983870
[41] -1.824590162 1.687605021 0.952724491 -0.451478765 -0.081864189
[46] 0.477686289 0.574971627 0.737493344 0.951450164 1.667631986
[51] 0.076969463 -0.448289839 0.582947929 1.108278088 0.016930289
[56] 0.217645348 0.656586182 -1.184028458 0.575406296 -1.236047338
[61] -0.056925689 2.082638218 0.921501330 0.565657211 -0.965576997
[66] -1.170940981 0.358747812 0.004932476 0.720206633 -0.259010133
[71] -0.958226223 -1.152360453 -0.409852252 -0.351794336 -0.193744240
[76] 0.177042624 0.401686477 -0.578258036 1.509025656 -1.498116749
[81] -0.820158252 0.221429276 0.725514925 -1.825150616 -0.236284785
[86] -1.037215509 0.163568294 -0.857491838 0.919934238 -0.900183978
[91] -1.448781960 0.043427215 0.113006366 1.521766241 -1.057781504
[96] -0.580281636 -1.599992225 0.511967856 -0.033388070 -0.529879923
>
> colMeans(tmp2)
[1] -0.01060469
> colSums(tmp2)
[1] -1.060469
> colVars(tmp2)
[1] 0.7860301
> colSd(tmp2)
[1] 0.8865834
> colMax(tmp2)
[1] 2.137673
> colMin(tmp2)
[1] -1.825151
> colMedians(tmp2)
[1] 0.01785318
> colRanges(tmp2)
[,1]
[1,] -1.825151
[2,] 2.137673
>
> 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] -4.701640 2.801637 -1.896186 -2.215110 -1.992015 -4.166101 -2.389509
[8] 3.998704 1.606308 1.602793
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.0853871
[2,] -0.8715843
[3,] -0.6368444
[4,] 0.1865089
[5,] 0.8062253
>
> rowApply(tmp,sum)
[1] -5.0178355 0.4983606 -1.6950619 1.5463142 1.1236288 -2.9982409
[7] -5.6820776 0.9544270 3.4558900 0.4634752
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 2 2 3 7 7 1 4 1 5
[2,] 10 10 8 1 4 3 7 3 10 10
[3,] 2 8 1 5 6 10 5 5 2 9
[4,] 4 9 7 2 10 4 8 1 5 2
[5,] 7 3 3 6 5 2 4 8 7 1
[6,] 1 4 5 10 3 1 9 2 3 4
[7,] 3 6 10 9 1 9 2 7 4 3
[8,] 8 1 9 4 8 8 10 6 6 8
[9,] 5 7 6 7 2 5 6 10 9 6
[10,] 6 5 4 8 9 6 3 9 8 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.2561458 1.1296196 -1.0401881 -2.0790577 2.6738504 -1.4106353
[7] -2.9667195 0.9339818 0.5422532 1.1257038 -2.0902557 2.8652010
[13] -1.5910098 1.1251998 1.1083483 -0.1079099 -0.5998268 2.9572082
[19] 3.6151997 3.5168000
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8474953
[2,] -0.2993028
[3,] 0.1182507
[4,] 1.3883586
[5,] 1.8963345
>
> rowApply(tmp,sum)
[1] 3.5133486 0.4701891 0.7438402 8.0952611 -0.8587304
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 9 20 17 3 8
[2,] 4 11 20 18 1
[3,] 12 16 7 1 13
[4,] 17 4 11 2 3
[5,] 7 13 16 17 11
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.1182507 -1.1887635 0.3461946 0.8563335 -0.04357084 -0.27254490
[2,] 1.8963345 -0.0642375 0.7261951 -0.9759589 0.34760490 -0.67597838
[3,] 1.3883586 2.1886170 -0.5742011 -0.1276559 0.89973549 -0.93909023
[4,] -0.8474953 1.8697498 -1.6460207 -0.8541956 1.63928591 0.03747455
[5,] -0.2993028 -1.6757462 0.1076440 -0.9775809 -0.16920510 0.43950367
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.1659602 0.1562272 -0.6134565 -1.2722188 -1.27217698 0.7302127
[2,] -1.6814286 0.2052167 -1.0151428 1.8099922 -0.24123679 -1.2894492
[3,] -1.9709766 -0.1796190 0.1501408 0.1295956 -1.13632903 1.4294185
[4,] 0.8926632 -0.2956842 2.2317099 0.0643364 0.62900765 0.4238938
[5,] -0.3729376 1.0478411 -0.2109982 0.3939984 -0.06952052 1.5711251
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.7196761 0.61716899 0.09789775 1.5230640 0.3824173 2.1667586
[2,] -0.4011362 -0.75592299 1.82417320 0.7744499 0.4816434 -0.2876937
[3,] -0.6629793 -0.01889192 -0.41633760 -0.7169744 -1.1919044 -0.4270892
[4,] -0.1496005 0.67775928 -0.16036928 -0.7288705 0.4799254 0.3250912
[5,] -1.0969699 0.60508640 -0.23701577 -0.9595789 -0.7519084 1.1801414
[,19] [,20]
[1,] 1.7303266 -1.4344081
[2,] 0.6010332 -0.8082689
[3,] 0.7470163 2.1730067
[4,] 1.3507544 2.1558457
[5,] -0.8139308 1.4306247
>
>
> 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 : 542 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 -1.040713 0.5986861 -1.04206 0.03538356 -2.033063 1.035285 -0.7745909
col8 col9 col10 col11 col12 col13 col14
row1 -0.3937599 -0.950935 -1.218336 -0.2567564 -0.4995077 1.116039 -2.224827
col15 col16 col17 col18 col19 col20
row1 -0.8567434 -1.509992 -0.1352556 1.257642 -0.6643453 0.5426464
> tmp[,"col10"]
col10
row1 -1.2183361
row2 0.7627836
row3 -1.0002728
row4 -0.2956728
row5 -0.4806786
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -1.0407134 0.5986861 -1.0420605 0.03538356 -2.033063 1.0352849 -0.7745909
row5 -0.2891099 1.8778922 -0.3276161 0.08726515 0.848575 -0.1577214 1.3391030
col8 col9 col10 col11 col12 col13
row1 -0.3937599 -0.9509350 -1.2183361 -0.2567564 -0.4995077 1.1160393
row5 -1.6080233 0.3186714 -0.4806786 -0.0180851 -0.4881255 -0.1011651
col14 col15 col16 col17 col18 col19
row1 -2.2248270 -0.8567434 -1.50999192 -0.1352556 1.2576416 -0.6643453
row5 0.9425219 0.9056917 0.09033015 0.6673224 0.1266486 -2.8415306
col20
row1 0.5426464
row5 -0.5209129
> tmp[,c("col6","col20")]
col6 col20
row1 1.0352849 0.54264636
row2 -0.7616361 1.12485522
row3 -0.2133725 1.96432360
row4 0.8540924 0.06839847
row5 -0.1577214 -0.52091293
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.0352849 0.5426464
row5 -0.1577214 -0.5209129
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.51764 51.56445 48.74908 48.97822 49.69027 105.2137 49.46457 50.67164
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.09262 51.35257 50.51192 50.23333 50.94256 49.74954 49.74389 50.39422
col17 col18 col19 col20
row1 51.0273 48.73478 49.73905 106.9123
> tmp[,"col10"]
col10
row1 51.35257
row2 29.65031
row3 30.62034
row4 29.64388
row5 49.99461
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.51764 51.56445 48.74908 48.97822 49.69027 105.2137 49.46457 50.67164
row5 50.00968 51.40472 50.81375 49.82548 49.60646 105.9789 47.44012 50.58917
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.09262 51.35257 50.51192 50.23333 50.94256 49.74954 49.74389 50.39422
row5 49.99757 49.99461 50.90529 50.13404 49.45991 49.84578 48.90213 48.58105
col17 col18 col19 col20
row1 51.02730 48.73478 49.73905 106.9123
row5 49.84542 49.40975 49.76724 105.9642
> tmp[,c("col6","col20")]
col6 col20
row1 105.21366 106.91234
row2 74.77081 75.27631
row3 74.82138 75.33371
row4 73.68808 74.00949
row5 105.97893 105.96419
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.2137 106.9123
row5 105.9789 105.9642
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.2137 106.9123
row5 105.9789 105.9642
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.1618191
[2,] 0.8551250
[3,] -1.8773117
[4,] -0.0321808
[5,] 1.9110644
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.7751627 -0.04579120
[2,] -0.6679620 0.58820548
[3,] 0.3768024 -0.44941985
[4,] 1.4325594 -1.06372817
[5,] 0.4347388 0.04796337
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.3413969 -0.1389651
[2,] 0.7214747 -0.2131230
[3,] 1.0875860 -0.8021511
[4,] -0.1923505 -1.8237300
[5,] 0.2116784 0.1326116
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.341397
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.3413969
[2,] 0.7214747
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 -0.002209271 2.2134802 -0.3141717 0.6924580 1.7313934 -0.3308427
row1 1.490079675 0.4551455 0.5933109 -0.9152932 0.6535312 1.2124374
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 1.485998 1.9646208 1.2257391 0.90145078 0.1580269 -0.2555829 0.04103264
row1 -1.028236 0.6300288 0.6276712 -0.05169995 -0.5851685 0.8846219 0.54837709
[,14] [,15] [,16] [,17] [,18] [,19]
row3 0.4066673 -1.9418604 1.3479706 0.02231476 -1.4821991 0.8442369
row1 -0.7658889 0.1691594 0.1004932 -0.92539380 0.3587071 -0.9354429
[,20]
row3 -0.1554411
row1 -0.3600427
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.3314537 1.053741 1.121712 -0.4182315 -1.632808 -0.02814523 0.6536383
[,8] [,9] [,10]
row2 -0.6339702 1.170057 0.356073
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -1.344188 1.054742 -0.5108515 1.418389 0.6563166 0.7788005 0.3569565
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.9316738 -0.8813519 -1.570334 1.094398 0.2034618 0.04060115 1.916475
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.1506938 0.9501852 0.8279819 -0.6702958 0.02689572 0.3318471
>
>
> 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: 0x000001de556fed70>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM466028eaf00"
[2] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM466018206788"
[3] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM466022267c39"
[4] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM46602e9580f"
[5] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4660652f7f86"
[6] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4660750c69c6"
[7] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM466062e32c19"
[8] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM466043833214"
[9] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM46605e237023"
[10] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM46603f492b56"
[11] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM46605fe2899"
[12] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM46606a0f66c8"
[13] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4660317b6238"
[14] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4660633115a9"
[15] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM46605148bc7"
>
>
> ### 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: 0x000001de57dff950>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x000001de57dff950>
Warning message:
In dir.create(new.directory) :
'F:\biocbuild\bbs-3.19-bioc\meat\BufferedMatrix.Rcheck\tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x000001de57dff950>
> rowMedians(tmp)
[1] 0.674177914 0.173827372 -1.000907229 0.231605664 -0.296982541
[6] -0.107807473 0.354890042 -0.110523403 0.379626329 -0.037087221
[11] -0.408049083 -0.449015089 0.148517788 0.217327440 0.627443947
[16] -0.552586069 -0.004884545 0.366363280 0.281490885 -0.053908362
[21] 0.646380560 0.194594788 -0.098828116 -0.010613155 0.197336527
[26] 0.025268702 -0.061000468 -0.563668130 -0.144707600 0.252072466
[31] 0.352091275 -0.087965322 0.052782371 0.132705670 0.110170848
[36] -0.088493984 0.259536958 -0.112559213 0.451386163 0.125810963
[41] -0.002649814 0.092743296 0.107441154 -0.081249395 -0.307661596
[46] -0.126030766 -0.466559251 0.130931396 -0.126972919 -0.091596496
[51] -0.244976463 -0.055793844 0.184241141 0.641369202 0.335777382
[56] 0.022138594 0.043234198 0.237725164 0.667067338 0.115350085
[61] 0.593095449 -0.192735381 0.042953311 0.281253854 0.037993158
[66] -0.054091279 0.315509170 0.383163194 0.598420621 -0.078495714
[71] -0.083002025 -0.158063505 -0.321692942 0.026938856 0.178591108
[76] 0.380994268 0.045156990 0.421810992 0.224965145 0.219681063
[81] -0.048137237 0.217348345 0.154812244 0.086593243 -0.317206769
[86] -0.135048370 -0.088347018 0.024527035 0.169462200 0.314210508
[91] 0.011426857 0.225570478 0.086697374 0.429927114 -0.251636269
[96] -0.273151516 -0.228636404 -0.333709498 -0.188539541 0.681413298
[101] -0.077710093 0.064064345 0.600859237 -0.652133894 0.149821491
[106] -0.071461293 0.731464157 -0.458538493 -0.255954232 -0.093792584
[111] -0.168061813 -0.090412104 -0.427143202 -0.179713347 0.659028470
[116] -0.345200958 -0.312032022 -0.059269895 0.145120236 -0.446217421
[121] -0.018073570 -0.415502805 0.047035231 -0.379484279 0.063302923
[126] 0.357874037 -0.050454649 -0.179692188 0.011135704 0.034538749
[131] 0.150070241 0.530364734 -0.395994241 -0.624236810 -0.469507418
[136] 0.547280884 -0.283315464 0.111529362 0.045842595 -0.198953995
[141] -0.234695122 -0.514072228 0.361716663 -0.019918908 -0.133687575
[146] -0.228346970 0.248416974 0.044383083 -0.280308561 0.043045734
[151] -0.041611034 0.243526216 0.554348650 0.552576908 -0.090350842
[156] -0.132948488 0.164198940 0.266363473 0.021612425 0.227301413
[161] 0.268828097 -0.213643201 0.073397823 0.129998974 -0.260789830
[166] 0.381246717 0.033244041 -0.586992066 -0.075347235 0.118295286
[171] -0.310466947 -0.645051001 0.639382853 0.257160392 0.348089706
[176] 0.316620924 -0.035260042 0.106676712 0.358294971 0.034943211
[181] -0.408265163 0.004818626 -0.130187690 0.747663952 -0.319043138
[186] 0.040169260 -0.040131711 0.383177086 0.312654530 0.162060991
[191] 0.105405747 0.456362839 -0.043598772 0.186203606 -0.372099285
[196] 0.076106707 0.161195569 0.259020102 -0.169258158 0.099962322
[201] -0.250160889 -0.290029970 -0.272718528 0.259031271 -0.644422869
[206] -0.101098381 -0.004847313 0.290132493 0.079304876 0.257499132
[211] 0.372433789 -0.592568733 0.176236572 -0.257491777 -0.452079537
[216] 0.126526755 0.283885248 -0.025033804 -0.191526546 0.460919199
[221] 0.043748077 0.433386657 0.101126202 0.027611981 0.008851805
[226] 0.140095158 0.136778763 0.450626148 0.054572833 -0.249784440
>
> proc.time()
user system elapsed
3.39 17.82 32.98
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: 0x000002ef302f91d0>
> .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: 0x000002ef302f91d0>
> .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: 0x000002ef302f91d0>
> .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: 0x000002ef302f91d0>
> 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: 0x000002ef302f9470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002ef302f9470>
> .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: 0x000002ef302f9470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002ef302f9470>
> .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: 0x000002ef302f9470>
> 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: 0x000002ef302f9230>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002ef302f9230>
> .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: 0x000002ef302f9230>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000002ef302f9230>
> .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: 0x000002ef302f9230>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x000002ef302f9230>
> .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: 0x000002ef302f9230>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x000002ef302f9230>
> .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: 0x000002ef302f9230>
> 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: 0x000002ef302f9a10>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x000002ef302f9a10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002ef302f9a10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002ef302f9a10>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile11e018887f5c" "BufferedMatrixFile11e0375421c"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile11e018887f5c" "BufferedMatrixFile11e0375421c"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002ef302f9290>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002ef302f9290>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000002ef302f9290>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000002ef302f9290>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x000002ef302f9290>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x000002ef302f9290>
> .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: 0x000002ef302f97d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002ef302f97d0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000002ef302f97d0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x000002ef302f97d0>
> 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: 0x000002ef302f9530>
> .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: 0x000002ef302f9530>
> rm(P)
>
> proc.time()
user system elapsed
0.31 0.14 0.54
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.
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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
0.23 0.07 0.29