Ben Bolstad
| Snapshot Date: 2024-06-12 14:00 -0400 (Wed, 12 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 2024-06-14 14:38 -0400 (Fri, 14 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" | 4757 |
| palomino3 | Windows Server 2022 Datacenter | x64 | 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup" | 4491 |
| 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 | | ||||||||
|
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: 2024-06-13 01:15:56 -0400 (Thu, 13 Jun 2024) |
| EndedAt: 2024-06-13 01:17:45 -0400 (Thu, 13 Jun 2024) |
| EllapsedTime: 108.7 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
0.32 0.43 0.84
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 13 01:16:45 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 13 01:16:46 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: 0x00000219ad6fd710>
>
>
>
> 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 13 01:16:59 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 13 01:17:04 2024"
>
> ColMode(tmp2)
<pointer: 0x00000219ad6fd710>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.3509970 0.03093119 -1.1237977 0.5051234
[2,] -0.6645362 -1.39568446 0.5945722 0.2286706
[3,] 0.8986746 1.99739617 0.5186071 -0.9656813
[4,] 0.9255701 1.62283033 0.7673844 1.4168229
> 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,] 99.3509970 0.03093119 1.1237977 0.5051234
[2,] 0.6645362 1.39568446 0.5945722 0.2286706
[3,] 0.8986746 1.99739617 0.5186071 0.9656813
[4,] 0.9255701 1.62283033 0.7673844 1.4168229
> 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,] 9.9674970 0.1758727 1.0600932 0.7107203
[2,] 0.8151909 1.1813909 0.7710851 0.4781951
[3,] 0.9479845 1.4132927 0.7201438 0.9826908
[4,] 0.9620656 1.2739036 0.8760048 1.1903037
>
> 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,] 224.02597 26.78966 36.72473 32.61233
[2,] 33.81645 38.20959 33.30542 30.01062
[3,] 35.37852 41.13032 32.72004 35.79259
[4,] 35.54623 39.36187 34.52743 38.31986
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x00000219ad6fd4d0>
> exp(tmp5)
<pointer: 0x00000219ad6fd4d0>
> log(tmp5,2)
<pointer: 0x00000219ad6fd4d0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.2807
> Min(tmp5)
[1] 53.11157
> mean(tmp5)
[1] 73.20432
> Sum(tmp5)
[1] 14640.86
> Var(tmp5)
[1] 847.9557
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.20107 67.96238 71.24649 72.90410 68.91901 67.57161 71.24157 72.60623
[9] 74.84769 73.54300
> rowSums(tmp5)
[1] 1824.021 1359.248 1424.930 1458.082 1378.380 1351.432 1424.831 1452.125
[9] 1496.954 1470.860
> rowVars(tmp5)
[1] 7858.64494 53.65885 68.39621 81.92552 57.41289 96.76989
[7] 44.26563 61.48772 71.95395 52.59818
> rowSd(tmp5)
[1] 88.648999 7.325220 8.270200 9.051271 7.577129 9.837169 6.653242
[8] 7.841410 8.482567 7.252460
> rowMax(tmp5)
[1] 466.28070 84.65788 89.33258 97.82650 85.28138 84.09438 88.05812
[8] 92.05820 96.21633 86.42349
> rowMin(tmp5)
[1] 55.75916 55.70498 57.17196 59.39828 54.86847 53.11157 59.47110 61.84584
[9] 53.16539 59.03815
>
> colMeans(tmp5)
[1] 107.57974 75.28410 70.85327 72.17103 66.47882 68.72034 74.45140
[8] 71.73387 73.57459 71.26880 75.97946 73.09139 70.94344 76.82881
[15] 70.51424 70.08389 70.70623 69.00633 69.55049 65.26607
> colSums(tmp5)
[1] 1075.7974 752.8410 708.5327 721.7103 664.7882 687.2034 744.5140
[8] 717.3387 735.7459 712.6880 759.7946 730.9139 709.4344 768.2881
[15] 705.1424 700.8389 707.0623 690.0633 695.5049 652.6607
> colVars(tmp5)
[1] 15939.96447 130.10189 50.44449 48.95406 10.34476 44.11173
[7] 50.04319 146.40838 72.31608 47.77361 13.19946 94.25953
[13] 30.65543 179.83485 35.12032 61.06352 47.00894 51.79402
[19] 62.69391 67.93280
> colSd(tmp5)
[1] 126.253572 11.406221 7.102429 6.996718 3.216327 6.641666
[7] 7.074121 12.099933 8.503886 6.911846 3.633106 9.708735
[13] 5.536734 13.410252 5.926240 7.814315 6.856307 7.196807
[19] 7.917948 8.242136
> colMax(tmp5)
[1] 466.28070 86.42349 83.32945 80.65890 70.94651 83.69494 84.56156
[8] 97.82650 88.05812 80.77332 80.10300 89.33258 81.18739 96.21633
[15] 79.97084 83.29679 79.24591 80.92486 84.30097 77.32056
> colMin(tmp5)
[1] 53.16539 55.75916 58.25102 59.07976 60.11686 59.75561 66.83684 56.42893
[9] 62.81036 59.39828 69.36467 54.86847 62.81937 55.58539 64.01858 56.71903
[17] 57.17196 58.64600 59.77668 53.11157
>
>
> ### 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] 91.20107 67.96238 71.24649 72.90410 68.91901 67.57161 71.24157 72.60623
[9] 74.84769 NA
> rowSums(tmp5)
[1] 1824.021 1359.248 1424.930 1458.082 1378.380 1351.432 1424.831 1452.125
[9] 1496.954 NA
> rowVars(tmp5)
[1] 7858.64494 53.65885 68.39621 81.92552 57.41289 96.76989
[7] 44.26563 61.48772 71.95395 54.23770
> rowSd(tmp5)
[1] 88.648999 7.325220 8.270200 9.051271 7.577129 9.837169 6.653242
[8] 7.841410 8.482567 7.364625
> rowMax(tmp5)
[1] 466.28070 84.65788 89.33258 97.82650 85.28138 84.09438 88.05812
[8] 92.05820 96.21633 NA
> rowMin(tmp5)
[1] 55.75916 55.70498 57.17196 59.39828 54.86847 53.11157 59.47110 61.84584
[9] 53.16539 NA
>
> colMeans(tmp5)
[1] 107.57974 75.28410 70.85327 72.17103 66.47882 68.72034 74.45140
[8] 71.73387 NA 71.26880 75.97946 73.09139 70.94344 76.82881
[15] 70.51424 70.08389 70.70623 69.00633 69.55049 65.26607
> colSums(tmp5)
[1] 1075.7974 752.8410 708.5327 721.7103 664.7882 687.2034 744.5140
[8] 717.3387 NA 712.6880 759.7946 730.9139 709.4344 768.2881
[15] 705.1424 700.8389 707.0623 690.0633 695.5049 652.6607
> colVars(tmp5)
[1] 15939.96447 130.10189 50.44449 48.95406 10.34476 44.11173
[7] 50.04319 146.40838 NA 47.77361 13.19946 94.25953
[13] 30.65543 179.83485 35.12032 61.06352 47.00894 51.79402
[19] 62.69391 67.93280
> colSd(tmp5)
[1] 126.253572 11.406221 7.102429 6.996718 3.216327 6.641666
[7] 7.074121 12.099933 NA 6.911846 3.633106 9.708735
[13] 5.536734 13.410252 5.926240 7.814315 6.856307 7.196807
[19] 7.917948 8.242136
> colMax(tmp5)
[1] 466.28070 86.42349 83.32945 80.65890 70.94651 83.69494 84.56156
[8] 97.82650 NA 80.77332 80.10300 89.33258 81.18739 96.21633
[15] 79.97084 83.29679 79.24591 80.92486 84.30097 77.32056
> colMin(tmp5)
[1] 53.16539 55.75916 58.25102 59.07976 60.11686 59.75561 66.83684 56.42893
[9] NA 59.39828 69.36467 54.86847 62.81937 55.58539 64.01858 56.71903
[17] 57.17196 58.64600 59.77668 53.11157
>
> Max(tmp5,na.rm=TRUE)
[1] 466.2807
> Min(tmp5,na.rm=TRUE)
[1] 53.11157
> mean(tmp5,na.rm=TRUE)
[1] 73.22615
> Sum(tmp5,na.rm=TRUE)
[1] 14572
> Var(tmp5,na.rm=TRUE)
[1] 852.1425
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.20107 67.96238 71.24649 72.90410 68.91901 67.57161 71.24157 72.60623
[9] 74.84769 73.78948
> rowSums(tmp5,na.rm=TRUE)
[1] 1824.021 1359.248 1424.930 1458.082 1378.380 1351.432 1424.831 1452.125
[9] 1496.954 1402.000
> rowVars(tmp5,na.rm=TRUE)
[1] 7858.64494 53.65885 68.39621 81.92552 57.41289 96.76989
[7] 44.26563 61.48772 71.95395 54.23770
> rowSd(tmp5,na.rm=TRUE)
[1] 88.648999 7.325220 8.270200 9.051271 7.577129 9.837169 6.653242
[8] 7.841410 8.482567 7.364625
> rowMax(tmp5,na.rm=TRUE)
[1] 466.28070 84.65788 89.33258 97.82650 85.28138 84.09438 88.05812
[8] 92.05820 96.21633 86.42349
> rowMin(tmp5,na.rm=TRUE)
[1] 55.75916 55.70498 57.17196 59.39828 54.86847 53.11157 59.47110 61.84584
[9] 53.16539 59.03815
>
> colMeans(tmp5,na.rm=TRUE)
[1] 107.57974 75.28410 70.85327 72.17103 66.47882 68.72034 74.45140
[8] 71.73387 74.09845 71.26880 75.97946 73.09139 70.94344 76.82881
[15] 70.51424 70.08389 70.70623 69.00633 69.55049 65.26607
> colSums(tmp5,na.rm=TRUE)
[1] 1075.7974 752.8410 708.5327 721.7103 664.7882 687.2034 744.5140
[8] 717.3387 666.8861 712.6880 759.7946 730.9139 709.4344 768.2881
[15] 705.1424 700.8389 707.0623 690.0633 695.5049 652.6607
> colVars(tmp5,na.rm=TRUE)
[1] 15939.96447 130.10189 50.44449 48.95406 10.34476 44.11173
[7] 50.04319 146.40838 78.26819 47.77361 13.19946 94.25953
[13] 30.65543 179.83485 35.12032 61.06352 47.00894 51.79402
[19] 62.69391 67.93280
> colSd(tmp5,na.rm=TRUE)
[1] 126.253572 11.406221 7.102429 6.996718 3.216327 6.641666
[7] 7.074121 12.099933 8.846931 6.911846 3.633106 9.708735
[13] 5.536734 13.410252 5.926240 7.814315 6.856307 7.196807
[19] 7.917948 8.242136
> colMax(tmp5,na.rm=TRUE)
[1] 466.28070 86.42349 83.32945 80.65890 70.94651 83.69494 84.56156
[8] 97.82650 88.05812 80.77332 80.10300 89.33258 81.18739 96.21633
[15] 79.97084 83.29679 79.24591 80.92486 84.30097 77.32056
> colMin(tmp5,na.rm=TRUE)
[1] 53.16539 55.75916 58.25102 59.07976 60.11686 59.75561 66.83684 56.42893
[9] 62.81036 59.39828 69.36467 54.86847 62.81937 55.58539 64.01858 56.71903
[17] 57.17196 58.64600 59.77668 53.11157
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.20107 67.96238 71.24649 72.90410 68.91901 67.57161 71.24157 72.60623
[9] 74.84769 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1824.021 1359.248 1424.930 1458.082 1378.380 1351.432 1424.831 1452.125
[9] 1496.954 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 7858.64494 53.65885 68.39621 81.92552 57.41289 96.76989
[7] 44.26563 61.48772 71.95395 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 88.648999 7.325220 8.270200 9.051271 7.577129 9.837169 6.653242
[8] 7.841410 8.482567 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 466.28070 84.65788 89.33258 97.82650 85.28138 84.09438 88.05812
[8] 92.05820 96.21633 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 55.75916 55.70498 57.17196 59.39828 54.86847 53.11157 59.47110 61.84584
[9] 53.16539 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 112.15310 74.04639 69.46703 71.90153 66.61174 68.41395 73.60916
[8] 71.37653 NaN 72.43539 76.58085 72.61786 70.98971 78.80555
[15] 70.28403 69.37671 69.75737 67.68205 69.19960 63.92669
> colSums(tmp5,na.rm=TRUE)
[1] 1009.3779 666.4175 625.2032 647.1138 599.5057 615.7256 662.4824
[8] 642.3887 0.0000 651.9185 689.2276 653.5608 638.9074 709.2500
[15] 632.5562 624.3904 627.8164 609.1384 622.7964 575.3402
> colVars(tmp5,na.rm=TRUE)
[1] 17697.15927 129.13045 35.13130 54.25624 11.43909 48.56965
[7] 48.31809 163.27285 NA 38.43496 10.78067 103.51942
[13] 34.46327 158.35483 38.91413 63.07030 42.75641 38.53893
[19] 69.14552 56.24237
> colSd(tmp5,na.rm=TRUE)
[1] 133.030670 11.363558 5.927166 7.365884 3.382172 6.969193
[7] 6.951121 12.777827 NA 6.199594 3.283393 10.174450
[13] 5.870543 12.583911 6.238119 7.941681 6.538839 6.207973
[19] 8.315378 7.499491
> colMax(tmp5,na.rm=TRUE)
[1] 466.28070 85.60738 78.76395 80.65890 70.94651 83.69494 84.56156
[8] 97.82650 -Inf 80.77332 80.10300 89.33258 81.18739 96.21633
[15] 79.97084 83.29679 77.18187 78.32691 84.30097 75.96630
> colMin(tmp5,na.rm=TRUE)
[1] 53.16539 55.75916 58.25102 59.07976 60.11686 59.75561 66.83684 56.42893
[9] Inf 59.39828 69.36467 54.86847 62.81937 55.58539 64.01858 56.71903
[17] 57.17196 58.64600 59.77668 53.11157
>
>
>
>
> 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] 209.1671 336.1965 118.2807 194.1559 137.7625 123.7310 338.8438 209.3832
[9] 288.1347 207.1727
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 209.1671 336.1965 118.2807 194.1559 137.7625 123.7310 338.8438 209.3832
[9] 288.1347 207.1727
>
>
>
> 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] 5.684342e-14 -1.705303e-13 -2.842171e-14 -1.136868e-13 8.526513e-14
[6] -1.421085e-14 0.000000e+00 5.684342e-14 -1.705303e-13 8.526513e-14
[11] 5.684342e-14 -2.842171e-14 -9.947598e-14 1.136868e-13 -1.136868e-13
[16] 1.705303e-13 1.136868e-13 0.000000e+00 5.684342e-14 -9.947598e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
8 8
3 14
5 14
10 13
7 1
5 15
6 10
6 13
1 9
8 9
9 19
9 19
2 13
9 1
6 14
1 7
3 13
3 19
3 1
8 1
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] 2.592283
> Min(tmp)
[1] -2.282909
> mean(tmp)
[1] 0.04815527
> Sum(tmp)
[1] 4.815527
> Var(tmp)
[1] 1.175592
>
> rowMeans(tmp)
[1] 0.04815527
> rowSums(tmp)
[1] 4.815527
> rowVars(tmp)
[1] 1.175592
> rowSd(tmp)
[1] 1.084247
> rowMax(tmp)
[1] 2.592283
> rowMin(tmp)
[1] -2.282909
>
> colMeans(tmp)
[1] 0.34251656 -0.10205659 0.88454304 -1.27403297 -1.52575455 0.50573430
[7] 1.27569570 0.29932304 -1.47083150 -1.24029316 -1.61388471 -0.28424422
[13] 0.02421493 0.63691306 -1.12403151 0.69412874 0.73768871 2.25969236
[19] -1.39815922 1.29326785 -0.18758362 -1.42799564 -0.02664567 0.80742096
[25] 0.92799475 -0.94769289 -0.40552946 1.28084917 -0.98498315 1.74626100
[31] -0.43903022 -2.14772750 1.19158917 1.29034582 -1.09104721 0.43107109
[37] -0.14562244 0.71132011 0.45528915 1.37196787 -0.34802820 1.11144422
[43] -0.58496488 -1.09892946 -1.41447721 1.18142571 0.25576754 -0.60682726
[49] 1.01829469 1.01813520 0.67486734 -0.28894919 1.17441664 0.09961287
[55] 2.59228302 0.21319074 -0.57827865 -0.09595475 -0.21027559 -0.39803033
[61] 1.48873710 -1.23118784 0.30310385 -2.28290868 -0.25804876 0.39244488
[67] 0.81183873 0.53183651 -1.86648612 -0.74426179 -0.39235851 -0.37500852
[73] -0.94388057 -0.89559859 2.29452801 -0.53685714 0.95975940 0.75227445
[79] 1.24791733 1.02870029 -0.62950779 0.23861418 -0.43747322 -0.41721213
[85] -1.52149859 -1.18278997 -1.73960746 1.05075374 0.01796102 -0.66770916
[91] 0.08269321 0.46345613 1.72275211 -1.68203662 2.24847903 1.58938264
[97] -1.32862163 0.07167677 0.61352682 0.99274070
> colSums(tmp)
[1] 0.34251656 -0.10205659 0.88454304 -1.27403297 -1.52575455 0.50573430
[7] 1.27569570 0.29932304 -1.47083150 -1.24029316 -1.61388471 -0.28424422
[13] 0.02421493 0.63691306 -1.12403151 0.69412874 0.73768871 2.25969236
[19] -1.39815922 1.29326785 -0.18758362 -1.42799564 -0.02664567 0.80742096
[25] 0.92799475 -0.94769289 -0.40552946 1.28084917 -0.98498315 1.74626100
[31] -0.43903022 -2.14772750 1.19158917 1.29034582 -1.09104721 0.43107109
[37] -0.14562244 0.71132011 0.45528915 1.37196787 -0.34802820 1.11144422
[43] -0.58496488 -1.09892946 -1.41447721 1.18142571 0.25576754 -0.60682726
[49] 1.01829469 1.01813520 0.67486734 -0.28894919 1.17441664 0.09961287
[55] 2.59228302 0.21319074 -0.57827865 -0.09595475 -0.21027559 -0.39803033
[61] 1.48873710 -1.23118784 0.30310385 -2.28290868 -0.25804876 0.39244488
[67] 0.81183873 0.53183651 -1.86648612 -0.74426179 -0.39235851 -0.37500852
[73] -0.94388057 -0.89559859 2.29452801 -0.53685714 0.95975940 0.75227445
[79] 1.24791733 1.02870029 -0.62950779 0.23861418 -0.43747322 -0.41721213
[85] -1.52149859 -1.18278997 -1.73960746 1.05075374 0.01796102 -0.66770916
[91] 0.08269321 0.46345613 1.72275211 -1.68203662 2.24847903 1.58938264
[97] -1.32862163 0.07167677 0.61352682 0.99274070
> 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] 0.34251656 -0.10205659 0.88454304 -1.27403297 -1.52575455 0.50573430
[7] 1.27569570 0.29932304 -1.47083150 -1.24029316 -1.61388471 -0.28424422
[13] 0.02421493 0.63691306 -1.12403151 0.69412874 0.73768871 2.25969236
[19] -1.39815922 1.29326785 -0.18758362 -1.42799564 -0.02664567 0.80742096
[25] 0.92799475 -0.94769289 -0.40552946 1.28084917 -0.98498315 1.74626100
[31] -0.43903022 -2.14772750 1.19158917 1.29034582 -1.09104721 0.43107109
[37] -0.14562244 0.71132011 0.45528915 1.37196787 -0.34802820 1.11144422
[43] -0.58496488 -1.09892946 -1.41447721 1.18142571 0.25576754 -0.60682726
[49] 1.01829469 1.01813520 0.67486734 -0.28894919 1.17441664 0.09961287
[55] 2.59228302 0.21319074 -0.57827865 -0.09595475 -0.21027559 -0.39803033
[61] 1.48873710 -1.23118784 0.30310385 -2.28290868 -0.25804876 0.39244488
[67] 0.81183873 0.53183651 -1.86648612 -0.74426179 -0.39235851 -0.37500852
[73] -0.94388057 -0.89559859 2.29452801 -0.53685714 0.95975940 0.75227445
[79] 1.24791733 1.02870029 -0.62950779 0.23861418 -0.43747322 -0.41721213
[85] -1.52149859 -1.18278997 -1.73960746 1.05075374 0.01796102 -0.66770916
[91] 0.08269321 0.46345613 1.72275211 -1.68203662 2.24847903 1.58938264
[97] -1.32862163 0.07167677 0.61352682 0.99274070
> colMin(tmp)
[1] 0.34251656 -0.10205659 0.88454304 -1.27403297 -1.52575455 0.50573430
[7] 1.27569570 0.29932304 -1.47083150 -1.24029316 -1.61388471 -0.28424422
[13] 0.02421493 0.63691306 -1.12403151 0.69412874 0.73768871 2.25969236
[19] -1.39815922 1.29326785 -0.18758362 -1.42799564 -0.02664567 0.80742096
[25] 0.92799475 -0.94769289 -0.40552946 1.28084917 -0.98498315 1.74626100
[31] -0.43903022 -2.14772750 1.19158917 1.29034582 -1.09104721 0.43107109
[37] -0.14562244 0.71132011 0.45528915 1.37196787 -0.34802820 1.11144422
[43] -0.58496488 -1.09892946 -1.41447721 1.18142571 0.25576754 -0.60682726
[49] 1.01829469 1.01813520 0.67486734 -0.28894919 1.17441664 0.09961287
[55] 2.59228302 0.21319074 -0.57827865 -0.09595475 -0.21027559 -0.39803033
[61] 1.48873710 -1.23118784 0.30310385 -2.28290868 -0.25804876 0.39244488
[67] 0.81183873 0.53183651 -1.86648612 -0.74426179 -0.39235851 -0.37500852
[73] -0.94388057 -0.89559859 2.29452801 -0.53685714 0.95975940 0.75227445
[79] 1.24791733 1.02870029 -0.62950779 0.23861418 -0.43747322 -0.41721213
[85] -1.52149859 -1.18278997 -1.73960746 1.05075374 0.01796102 -0.66770916
[91] 0.08269321 0.46345613 1.72275211 -1.68203662 2.24847903 1.58938264
[97] -1.32862163 0.07167677 0.61352682 0.99274070
> colMedians(tmp)
[1] 0.34251656 -0.10205659 0.88454304 -1.27403297 -1.52575455 0.50573430
[7] 1.27569570 0.29932304 -1.47083150 -1.24029316 -1.61388471 -0.28424422
[13] 0.02421493 0.63691306 -1.12403151 0.69412874 0.73768871 2.25969236
[19] -1.39815922 1.29326785 -0.18758362 -1.42799564 -0.02664567 0.80742096
[25] 0.92799475 -0.94769289 -0.40552946 1.28084917 -0.98498315 1.74626100
[31] -0.43903022 -2.14772750 1.19158917 1.29034582 -1.09104721 0.43107109
[37] -0.14562244 0.71132011 0.45528915 1.37196787 -0.34802820 1.11144422
[43] -0.58496488 -1.09892946 -1.41447721 1.18142571 0.25576754 -0.60682726
[49] 1.01829469 1.01813520 0.67486734 -0.28894919 1.17441664 0.09961287
[55] 2.59228302 0.21319074 -0.57827865 -0.09595475 -0.21027559 -0.39803033
[61] 1.48873710 -1.23118784 0.30310385 -2.28290868 -0.25804876 0.39244488
[67] 0.81183873 0.53183651 -1.86648612 -0.74426179 -0.39235851 -0.37500852
[73] -0.94388057 -0.89559859 2.29452801 -0.53685714 0.95975940 0.75227445
[79] 1.24791733 1.02870029 -0.62950779 0.23861418 -0.43747322 -0.41721213
[85] -1.52149859 -1.18278997 -1.73960746 1.05075374 0.01796102 -0.66770916
[91] 0.08269321 0.46345613 1.72275211 -1.68203662 2.24847903 1.58938264
[97] -1.32862163 0.07167677 0.61352682 0.99274070
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.3425166 -0.1020566 0.884543 -1.274033 -1.525755 0.5057343 1.275696
[2,] 0.3425166 -0.1020566 0.884543 -1.274033 -1.525755 0.5057343 1.275696
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.299323 -1.470832 -1.240293 -1.613885 -0.2842442 0.02421493 0.6369131
[2,] 0.299323 -1.470832 -1.240293 -1.613885 -0.2842442 0.02421493 0.6369131
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.124032 0.6941287 0.7376887 2.259692 -1.398159 1.293268 -0.1875836
[2,] -1.124032 0.6941287 0.7376887 2.259692 -1.398159 1.293268 -0.1875836
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.427996 -0.02664567 0.807421 0.9279947 -0.9476929 -0.4055295 1.280849
[2,] -1.427996 -0.02664567 0.807421 0.9279947 -0.9476929 -0.4055295 1.280849
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.9849832 1.746261 -0.4390302 -2.147728 1.191589 1.290346 -1.091047
[2,] -0.9849832 1.746261 -0.4390302 -2.147728 1.191589 1.290346 -1.091047
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.4310711 -0.1456224 0.7113201 0.4552892 1.371968 -0.3480282 1.111444
[2,] 0.4310711 -0.1456224 0.7113201 0.4552892 1.371968 -0.3480282 1.111444
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.5849649 -1.098929 -1.414477 1.181426 0.2557675 -0.6068273 1.018295
[2,] -0.5849649 -1.098929 -1.414477 1.181426 0.2557675 -0.6068273 1.018295
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 1.018135 0.6748673 -0.2889492 1.174417 0.09961287 2.592283 0.2131907
[2,] 1.018135 0.6748673 -0.2889492 1.174417 0.09961287 2.592283 0.2131907
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.5782787 -0.09595475 -0.2102756 -0.3980303 1.488737 -1.231188 0.3031038
[2,] -0.5782787 -0.09595475 -0.2102756 -0.3980303 1.488737 -1.231188 0.3031038
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -2.282909 -0.2580488 0.3924449 0.8118387 0.5318365 -1.866486 -0.7442618
[2,] -2.282909 -0.2580488 0.3924449 0.8118387 0.5318365 -1.866486 -0.7442618
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.3923585 -0.3750085 -0.9438806 -0.8955986 2.294528 -0.5368571 0.9597594
[2,] -0.3923585 -0.3750085 -0.9438806 -0.8955986 2.294528 -0.5368571 0.9597594
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.7522744 1.247917 1.0287 -0.6295078 0.2386142 -0.4374732 -0.4172121
[2,] 0.7522744 1.247917 1.0287 -0.6295078 0.2386142 -0.4374732 -0.4172121
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -1.521499 -1.18279 -1.739607 1.050754 0.01796102 -0.6677092 0.08269321
[2,] -1.521499 -1.18279 -1.739607 1.050754 0.01796102 -0.6677092 0.08269321
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.4634561 1.722752 -1.682037 2.248479 1.589383 -1.328622 0.07167677
[2,] 0.4634561 1.722752 -1.682037 2.248479 1.589383 -1.328622 0.07167677
[,99] [,100]
[1,] 0.6135268 0.9927407
[2,] 0.6135268 0.9927407
>
>
> Max(tmp2)
[1] 2.035312
> Min(tmp2)
[1] -2.505414
> mean(tmp2)
[1] -0.003030317
> Sum(tmp2)
[1] -0.3030317
> Var(tmp2)
[1] 0.7528404
>
> rowMeans(tmp2)
[1] 0.4697822469 -0.0007427333 -1.0156307092 -1.3764643312 -1.1906193982
[6] 0.0292988862 -1.3421098153 1.0556162248 0.0587714431 -0.6908100001
[11] -2.5054136471 0.5945478434 0.3199018448 0.0488676268 -0.6351994020
[16] -0.8131468730 -0.8818824237 0.7734023500 -0.5611547313 1.0521719010
[21] -0.9122579226 -0.2913389638 0.4737036988 0.3906356515 0.6655277734
[26] -1.4611849807 -0.4333191544 0.1480422709 -0.6818942786 1.5692272677
[31] 1.6447078474 -1.5163462262 0.4661301342 -0.2118250742 -0.6903583430
[36] -0.9044587062 0.5157980742 1.3154714248 -0.2546819919 1.0943287697
[41] -0.2773381322 0.3507857483 -0.0838797069 -0.8947924284 1.3716578425
[46] 0.2572994262 -1.1778955976 0.5893262415 -0.0797412169 1.8047348478
[51] -0.4596599082 1.2401775934 -0.1444713431 0.0683925232 -0.1334600775
[56] -1.3826081489 -0.2615631691 -0.0268118840 0.9562365351 -0.1516203012
[61] -0.0854973003 0.2795469794 0.1860628095 -0.8078788095 -1.0294135665
[66] 0.0227933396 -0.7467210188 1.1074416273 -0.5061086086 -1.6797315256
[71] 1.1112485087 -1.2108405756 0.7022691380 0.0896853891 0.6414813937
[76] 0.2096030160 0.0541600331 0.7435948543 -0.5245754065 -0.5397502911
[81] 0.1702524134 0.8132496085 0.2332410318 0.0068242313 0.7983243145
[86] -0.5681551849 0.7954108577 -0.7609507905 -0.0376713011 0.1200851669
[91] 1.0111028581 -1.3457188160 1.0542633692 -0.0436082839 0.0737325053
[96] 2.0353124481 0.3272627766 -0.1092293322 1.8593666100 -0.6333585582
> rowSums(tmp2)
[1] 0.4697822469 -0.0007427333 -1.0156307092 -1.3764643312 -1.1906193982
[6] 0.0292988862 -1.3421098153 1.0556162248 0.0587714431 -0.6908100001
[11] -2.5054136471 0.5945478434 0.3199018448 0.0488676268 -0.6351994020
[16] -0.8131468730 -0.8818824237 0.7734023500 -0.5611547313 1.0521719010
[21] -0.9122579226 -0.2913389638 0.4737036988 0.3906356515 0.6655277734
[26] -1.4611849807 -0.4333191544 0.1480422709 -0.6818942786 1.5692272677
[31] 1.6447078474 -1.5163462262 0.4661301342 -0.2118250742 -0.6903583430
[36] -0.9044587062 0.5157980742 1.3154714248 -0.2546819919 1.0943287697
[41] -0.2773381322 0.3507857483 -0.0838797069 -0.8947924284 1.3716578425
[46] 0.2572994262 -1.1778955976 0.5893262415 -0.0797412169 1.8047348478
[51] -0.4596599082 1.2401775934 -0.1444713431 0.0683925232 -0.1334600775
[56] -1.3826081489 -0.2615631691 -0.0268118840 0.9562365351 -0.1516203012
[61] -0.0854973003 0.2795469794 0.1860628095 -0.8078788095 -1.0294135665
[66] 0.0227933396 -0.7467210188 1.1074416273 -0.5061086086 -1.6797315256
[71] 1.1112485087 -1.2108405756 0.7022691380 0.0896853891 0.6414813937
[76] 0.2096030160 0.0541600331 0.7435948543 -0.5245754065 -0.5397502911
[81] 0.1702524134 0.8132496085 0.2332410318 0.0068242313 0.7983243145
[86] -0.5681551849 0.7954108577 -0.7609507905 -0.0376713011 0.1200851669
[91] 1.0111028581 -1.3457188160 1.0542633692 -0.0436082839 0.0737325053
[96] 2.0353124481 0.3272627766 -0.1092293322 1.8593666100 -0.6333585582
> 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] 0.4697822469 -0.0007427333 -1.0156307092 -1.3764643312 -1.1906193982
[6] 0.0292988862 -1.3421098153 1.0556162248 0.0587714431 -0.6908100001
[11] -2.5054136471 0.5945478434 0.3199018448 0.0488676268 -0.6351994020
[16] -0.8131468730 -0.8818824237 0.7734023500 -0.5611547313 1.0521719010
[21] -0.9122579226 -0.2913389638 0.4737036988 0.3906356515 0.6655277734
[26] -1.4611849807 -0.4333191544 0.1480422709 -0.6818942786 1.5692272677
[31] 1.6447078474 -1.5163462262 0.4661301342 -0.2118250742 -0.6903583430
[36] -0.9044587062 0.5157980742 1.3154714248 -0.2546819919 1.0943287697
[41] -0.2773381322 0.3507857483 -0.0838797069 -0.8947924284 1.3716578425
[46] 0.2572994262 -1.1778955976 0.5893262415 -0.0797412169 1.8047348478
[51] -0.4596599082 1.2401775934 -0.1444713431 0.0683925232 -0.1334600775
[56] -1.3826081489 -0.2615631691 -0.0268118840 0.9562365351 -0.1516203012
[61] -0.0854973003 0.2795469794 0.1860628095 -0.8078788095 -1.0294135665
[66] 0.0227933396 -0.7467210188 1.1074416273 -0.5061086086 -1.6797315256
[71] 1.1112485087 -1.2108405756 0.7022691380 0.0896853891 0.6414813937
[76] 0.2096030160 0.0541600331 0.7435948543 -0.5245754065 -0.5397502911
[81] 0.1702524134 0.8132496085 0.2332410318 0.0068242313 0.7983243145
[86] -0.5681551849 0.7954108577 -0.7609507905 -0.0376713011 0.1200851669
[91] 1.0111028581 -1.3457188160 1.0542633692 -0.0436082839 0.0737325053
[96] 2.0353124481 0.3272627766 -0.1092293322 1.8593666100 -0.6333585582
> rowMin(tmp2)
[1] 0.4697822469 -0.0007427333 -1.0156307092 -1.3764643312 -1.1906193982
[6] 0.0292988862 -1.3421098153 1.0556162248 0.0587714431 -0.6908100001
[11] -2.5054136471 0.5945478434 0.3199018448 0.0488676268 -0.6351994020
[16] -0.8131468730 -0.8818824237 0.7734023500 -0.5611547313 1.0521719010
[21] -0.9122579226 -0.2913389638 0.4737036988 0.3906356515 0.6655277734
[26] -1.4611849807 -0.4333191544 0.1480422709 -0.6818942786 1.5692272677
[31] 1.6447078474 -1.5163462262 0.4661301342 -0.2118250742 -0.6903583430
[36] -0.9044587062 0.5157980742 1.3154714248 -0.2546819919 1.0943287697
[41] -0.2773381322 0.3507857483 -0.0838797069 -0.8947924284 1.3716578425
[46] 0.2572994262 -1.1778955976 0.5893262415 -0.0797412169 1.8047348478
[51] -0.4596599082 1.2401775934 -0.1444713431 0.0683925232 -0.1334600775
[56] -1.3826081489 -0.2615631691 -0.0268118840 0.9562365351 -0.1516203012
[61] -0.0854973003 0.2795469794 0.1860628095 -0.8078788095 -1.0294135665
[66] 0.0227933396 -0.7467210188 1.1074416273 -0.5061086086 -1.6797315256
[71] 1.1112485087 -1.2108405756 0.7022691380 0.0896853891 0.6414813937
[76] 0.2096030160 0.0541600331 0.7435948543 -0.5245754065 -0.5397502911
[81] 0.1702524134 0.8132496085 0.2332410318 0.0068242313 0.7983243145
[86] -0.5681551849 0.7954108577 -0.7609507905 -0.0376713011 0.1200851669
[91] 1.0111028581 -1.3457188160 1.0542633692 -0.0436082839 0.0737325053
[96] 2.0353124481 0.3272627766 -0.1092293322 1.8593666100 -0.6333585582
>
> colMeans(tmp2)
[1] -0.003030317
> colSums(tmp2)
[1] -0.3030317
> colVars(tmp2)
[1] 0.7528404
> colSd(tmp2)
[1] 0.8676637
> colMax(tmp2)
[1] 2.035312
> colMin(tmp2)
[1] -2.505414
> colMedians(tmp2)
[1] 0.01480879
> colRanges(tmp2)
[,1]
[1,] -2.505414
[2,] 2.035312
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.4252480 0.3050712 0.3898821 -3.8040239 -2.0465378 1.0805109
[7] 1.1801861 0.3027953 4.2923564 0.2531720
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.2694998
[2,] -0.2325993
[3,] -0.2136992
[4,] 0.5589491
[5,] 1.0535624
>
> rowApply(tmp,sum)
[1] 4.27552834 -2.25055230 1.12693207 -5.16697079 -1.12172683 0.07688355
[7] -2.91324529 4.74485829 0.85435374 3.75259951
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 10 4 8 6 4 4 7 4 8
[2,] 9 8 2 5 5 2 7 4 2 10
[3,] 4 4 9 9 1 10 8 1 5 7
[4,] 6 1 1 4 3 5 6 5 3 9
[5,] 3 6 6 2 4 1 10 2 7 3
[6,] 5 5 5 6 10 7 1 3 10 6
[7,] 2 2 10 3 8 9 5 9 6 5
[8,] 8 9 7 1 2 8 3 6 8 4
[9,] 10 3 8 7 9 3 9 10 9 1
[10,] 7 7 3 10 7 6 2 8 1 2
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.7269373 -0.5682598 1.5380108 -3.0634002 -2.2632327 1.3425402
[7] 0.5951135 0.3261558 -2.3460278 0.2403552 -2.5787864 3.8528082
[13] 1.4999665 -0.8192711 -1.7782823 0.5961130 -1.8493470 0.9143453
[19] 1.2639330 0.5637979
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.2801114
[2,] -0.9964013
[3,] -0.1833252
[4,] 0.8743857
[5,] 2.3123894
>
> rowApply(tmp,sum)
[1] 4.4262912 1.6241298 -8.1309355 -0.8166934 1.0906773
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 3 16 4 9 20
[2,] 6 3 18 20 11
[3,] 2 20 17 7 8
[4,] 18 2 5 11 1
[5,] 14 10 6 8 3
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.9964013 -0.65628115 -1.0284317 1.26240849 0.8768467 0.9316306
[2,] 0.8743857 -1.29537208 2.8179235 -1.36950328 -0.1009105 0.9338548
[3,] -1.2801114 0.43953004 0.4274567 -1.27992691 -1.2345032 -0.1569899
[4,] -0.1833252 1.00042465 -0.3474063 -0.06600475 -0.3094109 -1.0208705
[5,] 2.3123894 -0.05656123 -0.3315314 -1.61037379 -1.4952548 0.6549152
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.2328702 0.4277046 -0.2791000 -0.28591745 0.36850577 0.7631403
[2,] -0.1008952 -0.5639914 -0.3461944 1.00110940 -1.68247883 0.6806658
[3,] -1.3200653 -0.2180560 -1.4266809 0.55607915 -1.15535027 0.8026926
[4,] 0.1873116 -0.4098020 0.3489045 -0.08154934 0.01684819 0.9088046
[5,] 0.5958922 1.0903006 -0.6429570 -0.94936652 -0.12631125 0.6975049
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.39734042 0.25842137 -0.7622795 -1.0642599 -0.2866290 2.0341386
[2,] 0.02142474 -0.79030656 -0.3809152 -0.4019393 0.3523074 1.5210610
[3,] 0.15624696 0.34619513 0.4156810 -0.7172295 -1.0079237 -1.6987310
[4,] -0.72253407 -0.56904534 -1.9018010 0.9012035 0.6563766 0.2839379
[5,] 0.64748850 -0.06453573 0.8510324 1.8783382 -1.5634783 -1.2260613
[,19] [,20]
[1,] 1.10088449 -0.8683004
[2,] -0.22720592 0.6811101
[3,] -0.09636279 0.3171137
[4,] -0.37944959 0.8706940
[5,] 0.86606677 -0.4368196
>
>
> 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 : 623 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 : 540 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 0.5562349 0.7907424 0.8228547 0.7556521 0.1462959 -1.528111 -0.9483595
col8 col9 col10 col11 col12 col13 col14
row1 -0.4084457 -0.2649849 -0.8646501 -0.452581 0.2947061 -0.2703825 -0.6777086
col15 col16 col17 col18 col19 col20
row1 -0.1220097 -0.793263 -1.261195 -0.3560737 0.2564252 0.6256788
> tmp[,"col10"]
col10
row1 -0.8646501
row2 2.2179612
row3 -0.7658430
row4 0.8414791
row5 1.5236249
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.5562349 0.7907424 0.8228547 0.7556521 0.1462959 -1.5281113 -0.9483595
row5 0.2814927 -0.3734021 -0.6036313 2.7228747 0.2398998 -0.1866122 -0.4174925
col8 col9 col10 col11 col12 col13
row1 -0.4084457 -0.2649849 -0.8646501 -0.4525810 0.2947061 -0.2703825
row5 0.1059544 0.6395093 1.5236249 -0.7000941 -0.1268709 1.2391606
col14 col15 col16 col17 col18 col19
row1 -0.6777086 -0.1220097 -0.7932630 -1.2611946 -0.3560737 0.2564252
row5 -0.2814809 -0.6354934 -0.7781916 0.2237976 1.2224043 1.0904080
col20
row1 0.6256788
row5 -1.2512219
> tmp[,c("col6","col20")]
col6 col20
row1 -1.5281113 0.6256788
row2 0.7299017 0.5082162
row3 -1.2692525 0.3481710
row4 -0.1434953 -0.5170580
row5 -0.1866122 -1.2512219
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.5281113 0.6256788
row5 -0.1866122 -1.2512219
>
>
>
>
> 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 48.65734 50.01418 49.3706 49.03092 51.4072 107.1275 52.05452 49.20369
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.45773 51.25571 50.32223 49.86256 50.3348 50.39308 49.71759 51.18192
col17 col18 col19 col20
row1 50.66753 49.59609 49.08908 103.9522
> tmp[,"col10"]
col10
row1 51.25571
row2 29.82439
row3 30.72811
row4 32.16953
row5 49.18758
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.65734 50.01418 49.37060 49.03092 51.40720 107.1275 52.05452 49.20369
row5 50.42414 50.20582 49.65205 48.57728 49.88773 104.1574 49.32346 49.80878
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.45773 51.25571 50.32223 49.86256 50.3348 50.39308 49.71759 51.18192
row5 49.01247 49.18758 50.85093 49.02856 49.1798 48.33891 49.53060 49.95786
col17 col18 col19 col20
row1 50.66753 49.59609 49.08908 103.9522
row5 48.80673 49.85114 50.19663 103.5847
> tmp[,c("col6","col20")]
col6 col20
row1 107.12748 103.95222
row2 75.88070 75.53831
row3 76.44345 75.99190
row4 76.56685 75.58757
row5 104.15741 103.58467
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 107.1275 103.9522
row5 104.1574 103.5847
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 107.1275 103.9522
row5 104.1574 103.5847
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.5212975
[2,] 0.3998496
[3,] -0.8247034
[4,] 0.4281949
[5,] 1.3680450
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.2454762 2.4865797
[2,] 2.0416898 -1.3804722
[3,] -0.3255489 1.2536320
[4,] -1.3708615 0.3318123
[5,] 1.5479976 -0.9696624
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.93899764 -0.2953457
[2,] -0.79119538 -2.8733194
[3,] 0.05582488 2.3829291
[4,] 0.93565126 -0.3612743
[5,] 0.09067922 1.3397127
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.9389976
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.9389976
[2,] -0.7911954
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 -0.3709199 1.617301 0.1166773 -0.3414299 -1.920277 -0.7948145 0.4114677
row1 1.4640562 0.296865 1.8822349 1.3270461 -1.058671 -0.8548100 0.2332579
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -0.5693124 -0.7579491 -0.1532578 -0.9925775 1.449480 -0.9894537 -1.479632
row1 0.9772502 -0.2540554 -0.3748669 0.8000012 -0.389082 -1.1055645 1.368650
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.2210707 -1.904859 -1.084506 -0.67017917 1.8441402 -0.4120927
row1 0.3916726 1.257836 0.235277 -0.07259264 0.6791003 -0.9422944
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6]
row2 -0.1912353 0.9289296 -0.3218446 -0.2776386 -0.3957482 -0.07790884
[,7] [,8] [,9] [,10]
row2 -0.1504614 1.296758 -0.1415186 -1.764781
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row5 -0.889394 -0.08069537 -0.2084904 -0.4272757 -0.9599344 -0.9218063
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row5 0.5373273 0.001437829 -0.7079454 -1.293633 -2.143793 1.117118 1.217697
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.239669 1.403313 1.457514 0.2401834 1.635541 -0.008813837 -1.029858
>
>
> 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: 0x00000219ad6fde30>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4f54115e288f"
[2] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4f54126b647d"
[3] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4f54258a4a05"
[4] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4f543d5f39e3"
[5] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4f5415cd4e1f"
[6] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4f543faa5f78"
[7] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4f5416eef56"
[8] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4f545f724217"
[9] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4f54647214ee"
[10] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4f54197d73bc"
[11] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4f546f6e5679"
[12] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4f5466a32b30"
[13] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4f546f99589e"
[14] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4f54758366e9"
[15] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM4f54aa5718"
>
>
> ### 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: 0x00000219afbff170>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x00000219afbff170>
Warning message:
In dir.create(new.directory) :
'F:\biocbuild\bbs-3.19-bioc\meat\BufferedMatrix.Rcheck\tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x00000219afbff170>
> rowMedians(tmp)
[1] 0.7143575109 0.3626861867 -0.0850798611 -0.0659838297 -0.6508143831
[6] 0.0567908410 -0.2855665813 -0.0170307725 0.0026912315 0.3945830546
[11] 0.4363885367 -0.3052676738 0.0718592364 0.0141692999 -0.3342534918
[16] 0.0821097244 0.1958441543 0.4659644572 -0.4386928794 -0.5935187216
[21] -0.2789076897 0.1508471108 0.0108528428 -0.7554148549 -0.5570172542
[26] 0.0134064295 -0.0103383609 -0.4979936373 0.0645859934 -0.0292092949
[31] -0.1628799588 -0.4977853523 -0.0654746208 -0.0295497084 0.1528315524
[36] -0.0318008461 0.3600589920 -0.1926636482 -0.1242354668 0.5633016037
[41] -0.1943647195 0.1651889560 0.1136182026 -0.3108685954 0.0011428114
[46] -0.6248154444 -0.1148889047 0.0418197007 -0.3690479462 0.5133417720
[51] 0.1991860398 0.4571201071 -0.3512343070 0.3809683009 -0.2902702869
[56] 0.0308384244 0.7624899079 0.1294545214 -0.0826413491 -0.2744963994
[61] -0.5098746325 -0.0933161002 -0.2062993457 -0.2613786764 0.0167996892
[66] 0.1489076715 0.0894291072 -0.5455049797 0.1830543245 -0.1535127793
[71] -0.0802625510 0.0993151563 0.2736479768 -0.1626247706 -0.2221528033
[76] 0.1660932969 0.2500884642 0.2702061009 0.1526240249 -0.0804883454
[81] -0.0434416428 0.3248497050 -0.4979840632 0.2140449769 0.0260952869
[86] 0.2396327032 -0.2857549088 0.8157797434 -0.4652375224 -0.0987610443
[91] 0.2497458515 -0.1498050504 0.4485078597 0.8160370733 -0.2520491622
[96] -0.3716944726 -0.1921223125 -0.3647139086 0.4471572981 0.2633425932
[101] 0.1196388811 0.1402005794 -0.0776574935 0.0141814987 0.1412999050
[106] -0.4382815817 -0.5787836535 0.2258553320 -0.4500350671 0.3950874234
[111] 0.2343316081 -0.1029500824 -0.1039897428 -0.1647784617 0.2222248368
[116] -0.0387492880 -0.6496313553 -0.3426450345 0.4710373956 -0.2240644938
[121] -0.1249135933 -0.3413295499 -0.2952643243 0.2404647325 -0.1640750518
[126] -0.1229415841 -0.1095384766 0.6837892014 -0.1655808174 0.0711028123
[131] -0.1095627981 -0.3995491736 -0.1625458397 0.2844181387 0.0297266768
[136] -0.5329056319 -0.1261860361 0.4282112928 0.1458906205 0.4177898569
[141] 0.5822700838 -0.0315748177 0.2203285309 0.1007789027 -0.3240469500
[146] 0.0318293215 0.0351171682 0.3948831329 -0.2828138595 0.2400357410
[151] 0.0750395895 0.2414083276 0.4883857558 0.1923970270 0.0165971529
[156] 0.1852242091 0.1814057119 -0.4315524711 -0.2428280634 -0.2084986130
[161] 0.0103396865 0.4417701676 -0.0773283391 -0.7722205892 -0.4509736334
[166] 0.2198575420 0.5100670787 -0.2334667306 -0.0092765151 -0.1437935702
[171] 0.1938725877 -0.0236413649 -0.2470149949 0.1674587794 -0.2458017157
[176] -0.1351220508 0.1812998539 -0.6614195758 0.5841785050 -0.6145368733
[181] 0.2581611903 -0.1801237062 -0.3951006805 0.2580440529 0.1671772708
[186] 0.1444621631 -0.7362874112 -0.1750229841 0.1908996669 -0.5242286099
[191] 0.1557487959 -0.2764173990 -0.2510876548 -0.0349417764 -0.3383622255
[196] -0.4583176450 0.1749567000 -0.0455108995 0.0007814213 -0.3308753686
[201] 0.1395904588 -0.2602375366 -0.1460255023 0.2243052443 -0.1757023313
[206] 0.5150825430 -0.1112041536 0.0340359084 0.1940089202 0.4194775760
[211] 0.2746226593 -0.0177725759 0.2482322193 -0.0218330674 0.4353544140
[216] 0.1301802866 0.0072966659 0.1806737984 -0.1248384079 0.2021669347
[221] 0.4057026956 0.0850981922 -0.0633805616 0.4558045757 0.4121740461
[226] -0.1806254263 -0.3906175362 0.0036452061 0.1615548857 -0.0250359839
>
> proc.time()
user system elapsed
4.82 27.35 51.53
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: 0x000001d59cefdb90>
> .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: 0x000001d59cefdb90>
> .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: 0x000001d59cefdb90>
> .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: 0x000001d59cefdb90>
> 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: 0x000001d59cefd050>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001d59cefd050>
> .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: 0x000001d59cefd050>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001d59cefd050>
> .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: 0x000001d59cefd050>
> 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: 0x000001d59cefd830>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001d59cefd830>
> .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: 0x000001d59cefd830>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000001d59cefd830>
> .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: 0x000001d59cefd830>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x000001d59cefd830>
> .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: 0x000001d59cefd830>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x000001d59cefd830>
> .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: 0x000001d59cefd830>
> 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: 0x000001d59cefd170>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x000001d59cefd170>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001d59cefd170>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001d59cefd170>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2f204ee71d62" "BufferedMatrixFile2f20552c6631"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2f204ee71d62" "BufferedMatrixFile2f20552c6631"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001d59cefd9b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001d59cefd9b0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000001d59cefd9b0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000001d59cefd9b0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x000001d59cefd9b0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x000001d59cefd9b0>
> .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: 0x000001d59cefd290>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001d59cefd290>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000001d59cefd290>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x000001d59cefd290>
> 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: 0x000001d59cefd2f0>
> .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: 0x000001d59cefd2f0>
> rm(P)
>
> proc.time()
user system elapsed
0.31 0.37 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.
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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
0.35 0.29 0.54