| Back to Multiple platform build/check report for BioC 3.19: simplified long |
|
This page was generated on 2024-05-17 11:36:43 -0400 (Fri, 17 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" | 4515 |
| 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: 2024-05-16 23:47:12 -0400 (Thu, 16 May 2024) |
| EndedAt: 2024-05-16 23:48:28 -0400 (Thu, 16 May 2024) |
| EllapsedTime: 75.4 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
0.25 0.17 0.59
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 May 16 23:47:45 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 May 16 23:47:46 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: 0x000001b4636fd8f0>
>
>
>
> 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 May 16 23:47:53 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 May 16 23:47:55 2024"
>
> ColMode(tmp2)
<pointer: 0x000001b4636fd8f0>
>
>
>
> ### 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,] 99.1702504 -1.0209159 0.6099268 0.06585374
[2,] 0.3541043 -0.1274593 -0.5929110 1.08844495
[3,] 0.7243139 0.4260460 -0.8562775 -0.40713140
[4,] -0.3201674 -3.0613971 -0.3294195 -0.24792288
> 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,] 99.1702504 1.0209159 0.6099268 0.06585374
[2,] 0.3541043 0.1274593 0.5929110 1.08844495
[3,] 0.7243139 0.4260460 0.8562775 0.40713140
[4,] 0.3201674 3.0613971 0.3294195 0.24792288
> 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,] 9.9584261 1.0104039 0.7809781 0.2566198
[2,] 0.5950666 0.3570145 0.7700072 1.0432857
[3,] 0.8510664 0.6527220 0.9253527 0.6380685
[4,] 0.5658333 1.7496849 0.5739508 0.4979185
>
> 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,] 223.75451 36.12495 33.41971 27.63205
[2,] 31.30477 28.69760 33.29298 36.52130
[3,] 34.23498 31.95327 35.10980 31.78782
[4,] 30.97850 45.55825 31.06893 30.22711
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x000001b4636fda10>
> exp(tmp5)
<pointer: 0x000001b4636fda10>
> log(tmp5,2)
<pointer: 0x000001b4636fda10>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 465.7157
> Min(tmp5)
[1] 54.74681
> mean(tmp5)
[1] 73.0612
> Sum(tmp5)
[1] 14612.24
> Var(tmp5)
[1] 844.8301
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.58397 69.33982 73.04613 71.92476 67.77723 72.10642 73.24781 71.03390
[9] 70.18287 70.36905
> rowSums(tmp5)
[1] 1831.679 1386.796 1460.923 1438.495 1355.545 1442.128 1464.956 1420.678
[9] 1403.657 1407.381
> rowVars(tmp5)
[1] 7814.30805 62.77631 72.34567 96.27027 59.65640 63.78859
[7] 25.94378 64.90538 55.38495 104.95373
> rowSd(tmp5)
[1] 88.398575 7.923150 8.505626 9.811741 7.723756 7.986776 5.093504
[8] 8.056387 7.442106 10.244693
> rowMax(tmp5)
[1] 465.71570 92.04597 94.05804 94.82352 83.76596 90.10307 82.08360
[8] 86.49485 83.65036 85.52792
> rowMin(tmp5)
[1] 57.51250 58.42026 57.81027 57.20333 56.76090 58.70624 62.03645 55.81394
[9] 59.90198 54.74681
>
> colMeans(tmp5)
[1] 107.92675 70.61471 69.91373 68.33086 74.92674 74.01345 69.96429
[8] 71.54597 69.88791 71.63048 74.43256 66.97366 74.84360 66.05180
[15] 68.35474 69.99645 76.96975 75.27511 67.60342 71.96795
> colSums(tmp5)
[1] 1079.2675 706.1471 699.1373 683.3086 749.2674 740.1345 699.6429
[8] 715.4597 698.8791 716.3048 744.3256 669.7366 748.4360 660.5180
[15] 683.5474 699.9645 769.6975 752.7511 676.0342 719.6795
> colVars(tmp5)
[1] 15826.79626 161.00820 42.19372 83.56288 20.71719 113.68953
[7] 57.09153 42.87597 76.21291 102.25293 72.47970 39.01784
[13] 62.66857 24.25759 54.02342 128.45920 14.77440 45.22798
[19] 50.43099 44.37203
> colSd(tmp5)
[1] 125.804596 12.688901 6.495669 9.141273 4.551614 10.662529
[7] 7.555894 6.547974 8.730001 10.112019 8.513501 6.246426
[13] 7.916348 4.925200 7.350062 11.333985 3.843748 6.725175
[19] 7.101478 6.661233
> colMax(tmp5)
[1] 465.71570 94.82352 81.96701 83.65036 81.92357 94.05804 80.90470
[8] 83.18101 81.71088 86.49485 86.69704 78.66574 92.04597 71.07851
[15] 77.17413 90.10307 83.76596 85.86653 82.69234 85.52792
> colMin(tmp5)
[1] 60.41748 54.74681 60.63425 55.73734 69.14831 59.08693 58.08709 62.41619
[9] 57.37722 56.76090 59.90198 57.81027 65.03921 55.81394 57.99401 57.20333
[17] 70.82577 64.09874 57.06079 63.60300
>
>
> ### 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] 91.58397 69.33982 73.04613 71.92476 67.77723 72.10642 NA 71.03390
[9] 70.18287 70.36905
> rowSums(tmp5)
[1] 1831.679 1386.796 1460.923 1438.495 1355.545 1442.128 NA 1420.678
[9] 1403.657 1407.381
> rowVars(tmp5)
[1] 7814.30805 62.77631 72.34567 96.27027 59.65640 63.78859
[7] 26.78435 64.90538 55.38495 104.95373
> rowSd(tmp5)
[1] 88.398575 7.923150 8.505626 9.811741 7.723756 7.986776 5.175360
[8] 8.056387 7.442106 10.244693
> rowMax(tmp5)
[1] 465.71570 92.04597 94.05804 94.82352 83.76596 90.10307 NA
[8] 86.49485 83.65036 85.52792
> rowMin(tmp5)
[1] 57.51250 58.42026 57.81027 57.20333 56.76090 58.70624 NA 55.81394
[9] 59.90198 54.74681
>
> colMeans(tmp5)
[1] 107.92675 70.61471 69.91373 68.33086 74.92674 74.01345 69.96429
[8] NA 69.88791 71.63048 74.43256 66.97366 74.84360 66.05180
[15] 68.35474 69.99645 76.96975 75.27511 67.60342 71.96795
> colSums(tmp5)
[1] 1079.2675 706.1471 699.1373 683.3086 749.2674 740.1345 699.6429
[8] NA 698.8791 716.3048 744.3256 669.7366 748.4360 660.5180
[15] 683.5474 699.9645 769.6975 752.7511 676.0342 719.6795
> colVars(tmp5)
[1] 15826.79626 161.00820 42.19372 83.56288 20.71719 113.68953
[7] 57.09153 NA 76.21291 102.25293 72.47970 39.01784
[13] 62.66857 24.25759 54.02342 128.45920 14.77440 45.22798
[19] 50.43099 44.37203
> colSd(tmp5)
[1] 125.804596 12.688901 6.495669 9.141273 4.551614 10.662529
[7] 7.555894 NA 8.730001 10.112019 8.513501 6.246426
[13] 7.916348 4.925200 7.350062 11.333985 3.843748 6.725175
[19] 7.101478 6.661233
> colMax(tmp5)
[1] 465.71570 94.82352 81.96701 83.65036 81.92357 94.05804 80.90470
[8] NA 81.71088 86.49485 86.69704 78.66574 92.04597 71.07851
[15] 77.17413 90.10307 83.76596 85.86653 82.69234 85.52792
> colMin(tmp5)
[1] 60.41748 54.74681 60.63425 55.73734 69.14831 59.08693 58.08709 NA
[9] 57.37722 56.76090 59.90198 57.81027 65.03921 55.81394 57.99401 57.20333
[17] 70.82577 64.09874 57.06079 63.60300
>
> Max(tmp5,na.rm=TRUE)
[1] 465.7157
> Min(tmp5,na.rm=TRUE)
[1] 54.74681
> mean(tmp5,na.rm=TRUE)
[1] 73.07636
> Sum(tmp5,na.rm=TRUE)
[1] 14542.2
> Var(tmp5,na.rm=TRUE)
[1] 849.0506
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.58397 69.33982 73.04613 71.92476 67.77723 72.10642 73.41650 71.03390
[9] 70.18287 70.36905
> rowSums(tmp5,na.rm=TRUE)
[1] 1831.679 1386.796 1460.923 1438.495 1355.545 1442.128 1394.913 1420.678
[9] 1403.657 1407.381
> rowVars(tmp5,na.rm=TRUE)
[1] 7814.30805 62.77631 72.34567 96.27027 59.65640 63.78859
[7] 26.78435 64.90538 55.38495 104.95373
> rowSd(tmp5,na.rm=TRUE)
[1] 88.398575 7.923150 8.505626 9.811741 7.723756 7.986776 5.175360
[8] 8.056387 7.442106 10.244693
> rowMax(tmp5,na.rm=TRUE)
[1] 465.71570 92.04597 94.05804 94.82352 83.76596 90.10307 82.08360
[8] 86.49485 83.65036 85.52792
> rowMin(tmp5,na.rm=TRUE)
[1] 57.51250 58.42026 57.81027 57.20333 56.76090 58.70624 62.03645 55.81394
[9] 59.90198 54.74681
>
> colMeans(tmp5,na.rm=TRUE)
[1] 107.92675 70.61471 69.91373 68.33086 74.92674 74.01345 69.96429
[8] 71.71300 69.88791 71.63048 74.43256 66.97366 74.84360 66.05180
[15] 68.35474 69.99645 76.96975 75.27511 67.60342 71.96795
> colSums(tmp5,na.rm=TRUE)
[1] 1079.2675 706.1471 699.1373 683.3086 749.2674 740.1345 699.6429
[8] 645.4170 698.8791 716.3048 744.3256 669.7366 748.4360 660.5180
[15] 683.5474 699.9645 769.6975 752.7511 676.0342 719.6795
> colVars(tmp5,na.rm=TRUE)
[1] 15826.79626 161.00820 42.19372 83.56288 20.71719 113.68953
[7] 57.09153 47.92160 76.21291 102.25293 72.47970 39.01784
[13] 62.66857 24.25759 54.02342 128.45920 14.77440 45.22798
[19] 50.43099 44.37203
> colSd(tmp5,na.rm=TRUE)
[1] 125.804596 12.688901 6.495669 9.141273 4.551614 10.662529
[7] 7.555894 6.922543 8.730001 10.112019 8.513501 6.246426
[13] 7.916348 4.925200 7.350062 11.333985 3.843748 6.725175
[19] 7.101478 6.661233
> colMax(tmp5,na.rm=TRUE)
[1] 465.71570 94.82352 81.96701 83.65036 81.92357 94.05804 80.90470
[8] 83.18101 81.71088 86.49485 86.69704 78.66574 92.04597 71.07851
[15] 77.17413 90.10307 83.76596 85.86653 82.69234 85.52792
> colMin(tmp5,na.rm=TRUE)
[1] 60.41748 54.74681 60.63425 55.73734 69.14831 59.08693 58.08709 62.41619
[9] 57.37722 56.76090 59.90198 57.81027 65.03921 55.81394 57.99401 57.20333
[17] 70.82577 64.09874 57.06079 63.60300
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.58397 69.33982 73.04613 71.92476 67.77723 72.10642 NaN 71.03390
[9] 70.18287 70.36905
> rowSums(tmp5,na.rm=TRUE)
[1] 1831.679 1386.796 1460.923 1438.495 1355.545 1442.128 0.000 1420.678
[9] 1403.657 1407.381
> rowVars(tmp5,na.rm=TRUE)
[1] 7814.30805 62.77631 72.34567 96.27027 59.65640 63.78859
[7] NA 64.90538 55.38495 104.95373
> rowSd(tmp5,na.rm=TRUE)
[1] 88.398575 7.923150 8.505626 9.811741 7.723756 7.986776 NA
[8] 8.056387 7.442106 10.244693
> rowMax(tmp5,na.rm=TRUE)
[1] 465.71570 92.04597 94.05804 94.82352 83.76596 90.10307 NA
[8] 86.49485 83.65036 85.52792
> rowMin(tmp5,na.rm=TRUE)
[1] 57.51250 58.42026 57.81027 57.20333 56.76090 58.70624 NA 55.81394
[9] 59.90198 54.74681
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 111.78477 69.34039 70.01927 69.03024 74.44438 73.28866 69.19875
[8] NaN 69.82789 71.87604 75.02098 66.62778 74.80441 65.49327
[15] 67.50566 69.23497 76.68694 75.62239 67.64696 71.64249
> colSums(tmp5,na.rm=TRUE)
[1] 1006.0629 624.0635 630.1735 621.2721 669.9994 659.5979 622.7888
[8] 0.0000 628.4510 646.8844 675.1888 599.6500 673.2397 589.4395
[15] 607.5509 623.1147 690.1825 680.6015 608.8226 644.7824
> colVars(tmp5,na.rm=TRUE)
[1] 17637.69692 162.86540 47.34261 88.50551 20.68926 121.99088
[7] 57.63497 NA 85.69900 114.35616 77.64450 42.54913
[13] 70.48486 23.78037 52.66572 137.99328 15.72142 49.52475
[19] 56.71354 48.72685
> colSd(tmp5,na.rm=TRUE)
[1] 132.806991 12.761873 6.880597 9.407737 4.548545 11.044948
[7] 7.591770 NA 9.257376 10.693744 8.811612 6.522969
[13] 8.395526 4.876512 7.257115 11.747054 3.965024 7.037382
[19] 7.530840 6.980462
> colMax(tmp5,na.rm=TRUE)
[1] 465.71570 94.82352 81.96701 83.65036 81.92357 94.05804 80.90470
[8] -Inf 81.71088 86.49485 86.69704 78.66574 92.04597 70.73431
[15] 77.17413 90.10307 83.76596 85.86653 82.69234 85.52792
> colMin(tmp5,na.rm=TRUE)
[1] 60.41748 54.74681 60.63425 55.73734 69.14831 59.08693 58.08709 Inf
[9] 57.37722 56.76090 59.90198 57.81027 65.03921 55.81394 57.99401 57.20333
[17] 70.82577 64.09874 57.06079 63.60300
>
>
>
>
> 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] 144.1443 150.8787 239.5403 159.8919 253.5455 332.9410 301.1977 192.8987
[9] 324.2413 200.1905
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 144.1443 150.8787 239.5403 159.8919 253.5455 332.9410 301.1977 192.8987
[9] 324.2413 200.1905
>
>
>
> 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] -3.552714e-14 1.705303e-13 0.000000e+00 1.136868e-13 8.526513e-14
[6] -5.684342e-14 1.136868e-13 -2.842171e-14 2.842171e-14 -2.842171e-14
[11] 1.136868e-13 -2.842171e-14 -1.136868e-13 2.842171e-14 1.136868e-13
[16] -5.684342e-14 0.000000e+00 0.000000e+00 -5.684342e-14 1.421085e-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)
+ }
7 3
5 5
5 7
3 2
5 8
3 16
3 18
8 4
1 6
8 9
10 18
2 5
5 2
10 2
7 12
5 4
1 13
10 6
6 20
4 8
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] 2.877763
> Min(tmp)
[1] -2.363981
> mean(tmp)
[1] -0.1340585
> Sum(tmp)
[1] -13.40585
> Var(tmp)
[1] 0.9386652
>
> rowMeans(tmp)
[1] -0.1340585
> rowSums(tmp)
[1] -13.40585
> rowVars(tmp)
[1] 0.9386652
> rowSd(tmp)
[1] 0.9688473
> rowMax(tmp)
[1] 2.877763
> rowMin(tmp)
[1] -2.363981
>
> colMeans(tmp)
[1] 1.47001470 0.03247778 0.45551120 -0.80926010 -0.64670907 -1.03594514
[7] -1.06943270 2.02660749 -0.33999952 -1.40746060 0.19771188 -0.20019214
[13] 0.41217257 -1.46091363 0.03240682 0.26046498 -0.84135811 -0.66570094
[19] -0.57405335 -1.04859797 0.61439811 -0.50145385 -0.43298429 -0.02888839
[25] -1.00979138 0.42324168 -0.01270714 1.04368720 -0.23391281 -1.16587242
[31] -0.89676225 1.04566353 0.39437771 0.14953136 -0.69654060 1.29871869
[37] 0.78572076 1.43870217 -0.55757329 0.50065305 -0.44764485 0.63667136
[43] 0.57355271 0.87478591 1.19685443 -0.98765834 -0.11417665 -0.74919342
[49] -0.07598869 0.02439070 -0.34924917 0.65683057 -0.53962300 0.42355161
[55] 0.32292057 -0.34129014 0.40034444 -1.31861709 0.91789085 -2.02989822
[61] 0.67282171 0.92536513 -1.25455431 -1.45804595 -1.00638833 1.38148373
[67] -0.99372194 -1.97985739 -0.30007372 0.66663899 2.87776254 -0.67024823
[73] -0.80702935 0.46009361 -0.03662258 -1.13361373 -1.00138096 -2.33449281
[79] 0.52440452 -0.16691899 -0.79202160 0.15922117 -0.14700336 0.98274786
[85] 2.16059290 0.46538970 -0.12162274 -0.13761924 -0.11168413 -0.04500050
[91] -0.50532966 -2.36398085 -1.44955368 1.08363404 -1.25756106 0.98285595
[97] 0.08941147 -0.04198613 -1.34589329 -1.39647232
> colSums(tmp)
[1] 1.47001470 0.03247778 0.45551120 -0.80926010 -0.64670907 -1.03594514
[7] -1.06943270 2.02660749 -0.33999952 -1.40746060 0.19771188 -0.20019214
[13] 0.41217257 -1.46091363 0.03240682 0.26046498 -0.84135811 -0.66570094
[19] -0.57405335 -1.04859797 0.61439811 -0.50145385 -0.43298429 -0.02888839
[25] -1.00979138 0.42324168 -0.01270714 1.04368720 -0.23391281 -1.16587242
[31] -0.89676225 1.04566353 0.39437771 0.14953136 -0.69654060 1.29871869
[37] 0.78572076 1.43870217 -0.55757329 0.50065305 -0.44764485 0.63667136
[43] 0.57355271 0.87478591 1.19685443 -0.98765834 -0.11417665 -0.74919342
[49] -0.07598869 0.02439070 -0.34924917 0.65683057 -0.53962300 0.42355161
[55] 0.32292057 -0.34129014 0.40034444 -1.31861709 0.91789085 -2.02989822
[61] 0.67282171 0.92536513 -1.25455431 -1.45804595 -1.00638833 1.38148373
[67] -0.99372194 -1.97985739 -0.30007372 0.66663899 2.87776254 -0.67024823
[73] -0.80702935 0.46009361 -0.03662258 -1.13361373 -1.00138096 -2.33449281
[79] 0.52440452 -0.16691899 -0.79202160 0.15922117 -0.14700336 0.98274786
[85] 2.16059290 0.46538970 -0.12162274 -0.13761924 -0.11168413 -0.04500050
[91] -0.50532966 -2.36398085 -1.44955368 1.08363404 -1.25756106 0.98285595
[97] 0.08941147 -0.04198613 -1.34589329 -1.39647232
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] 1.47001470 0.03247778 0.45551120 -0.80926010 -0.64670907 -1.03594514
[7] -1.06943270 2.02660749 -0.33999952 -1.40746060 0.19771188 -0.20019214
[13] 0.41217257 -1.46091363 0.03240682 0.26046498 -0.84135811 -0.66570094
[19] -0.57405335 -1.04859797 0.61439811 -0.50145385 -0.43298429 -0.02888839
[25] -1.00979138 0.42324168 -0.01270714 1.04368720 -0.23391281 -1.16587242
[31] -0.89676225 1.04566353 0.39437771 0.14953136 -0.69654060 1.29871869
[37] 0.78572076 1.43870217 -0.55757329 0.50065305 -0.44764485 0.63667136
[43] 0.57355271 0.87478591 1.19685443 -0.98765834 -0.11417665 -0.74919342
[49] -0.07598869 0.02439070 -0.34924917 0.65683057 -0.53962300 0.42355161
[55] 0.32292057 -0.34129014 0.40034444 -1.31861709 0.91789085 -2.02989822
[61] 0.67282171 0.92536513 -1.25455431 -1.45804595 -1.00638833 1.38148373
[67] -0.99372194 -1.97985739 -0.30007372 0.66663899 2.87776254 -0.67024823
[73] -0.80702935 0.46009361 -0.03662258 -1.13361373 -1.00138096 -2.33449281
[79] 0.52440452 -0.16691899 -0.79202160 0.15922117 -0.14700336 0.98274786
[85] 2.16059290 0.46538970 -0.12162274 -0.13761924 -0.11168413 -0.04500050
[91] -0.50532966 -2.36398085 -1.44955368 1.08363404 -1.25756106 0.98285595
[97] 0.08941147 -0.04198613 -1.34589329 -1.39647232
> colMin(tmp)
[1] 1.47001470 0.03247778 0.45551120 -0.80926010 -0.64670907 -1.03594514
[7] -1.06943270 2.02660749 -0.33999952 -1.40746060 0.19771188 -0.20019214
[13] 0.41217257 -1.46091363 0.03240682 0.26046498 -0.84135811 -0.66570094
[19] -0.57405335 -1.04859797 0.61439811 -0.50145385 -0.43298429 -0.02888839
[25] -1.00979138 0.42324168 -0.01270714 1.04368720 -0.23391281 -1.16587242
[31] -0.89676225 1.04566353 0.39437771 0.14953136 -0.69654060 1.29871869
[37] 0.78572076 1.43870217 -0.55757329 0.50065305 -0.44764485 0.63667136
[43] 0.57355271 0.87478591 1.19685443 -0.98765834 -0.11417665 -0.74919342
[49] -0.07598869 0.02439070 -0.34924917 0.65683057 -0.53962300 0.42355161
[55] 0.32292057 -0.34129014 0.40034444 -1.31861709 0.91789085 -2.02989822
[61] 0.67282171 0.92536513 -1.25455431 -1.45804595 -1.00638833 1.38148373
[67] -0.99372194 -1.97985739 -0.30007372 0.66663899 2.87776254 -0.67024823
[73] -0.80702935 0.46009361 -0.03662258 -1.13361373 -1.00138096 -2.33449281
[79] 0.52440452 -0.16691899 -0.79202160 0.15922117 -0.14700336 0.98274786
[85] 2.16059290 0.46538970 -0.12162274 -0.13761924 -0.11168413 -0.04500050
[91] -0.50532966 -2.36398085 -1.44955368 1.08363404 -1.25756106 0.98285595
[97] 0.08941147 -0.04198613 -1.34589329 -1.39647232
> colMedians(tmp)
[1] 1.47001470 0.03247778 0.45551120 -0.80926010 -0.64670907 -1.03594514
[7] -1.06943270 2.02660749 -0.33999952 -1.40746060 0.19771188 -0.20019214
[13] 0.41217257 -1.46091363 0.03240682 0.26046498 -0.84135811 -0.66570094
[19] -0.57405335 -1.04859797 0.61439811 -0.50145385 -0.43298429 -0.02888839
[25] -1.00979138 0.42324168 -0.01270714 1.04368720 -0.23391281 -1.16587242
[31] -0.89676225 1.04566353 0.39437771 0.14953136 -0.69654060 1.29871869
[37] 0.78572076 1.43870217 -0.55757329 0.50065305 -0.44764485 0.63667136
[43] 0.57355271 0.87478591 1.19685443 -0.98765834 -0.11417665 -0.74919342
[49] -0.07598869 0.02439070 -0.34924917 0.65683057 -0.53962300 0.42355161
[55] 0.32292057 -0.34129014 0.40034444 -1.31861709 0.91789085 -2.02989822
[61] 0.67282171 0.92536513 -1.25455431 -1.45804595 -1.00638833 1.38148373
[67] -0.99372194 -1.97985739 -0.30007372 0.66663899 2.87776254 -0.67024823
[73] -0.80702935 0.46009361 -0.03662258 -1.13361373 -1.00138096 -2.33449281
[79] 0.52440452 -0.16691899 -0.79202160 0.15922117 -0.14700336 0.98274786
[85] 2.16059290 0.46538970 -0.12162274 -0.13761924 -0.11168413 -0.04500050
[91] -0.50532966 -2.36398085 -1.44955368 1.08363404 -1.25756106 0.98285595
[97] 0.08941147 -0.04198613 -1.34589329 -1.39647232
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.470015 0.03247778 0.4555112 -0.8092601 -0.6467091 -1.035945 -1.069433
[2,] 1.470015 0.03247778 0.4555112 -0.8092601 -0.6467091 -1.035945 -1.069433
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 2.026607 -0.3399995 -1.407461 0.1977119 -0.2001921 0.4121726 -1.460914
[2,] 2.026607 -0.3399995 -1.407461 0.1977119 -0.2001921 0.4121726 -1.460914
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.03240682 0.260465 -0.8413581 -0.6657009 -0.5740533 -1.048598 0.6143981
[2,] 0.03240682 0.260465 -0.8413581 -0.6657009 -0.5740533 -1.048598 0.6143981
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.5014539 -0.4329843 -0.02888839 -1.009791 0.4232417 -0.01270714 1.043687
[2,] -0.5014539 -0.4329843 -0.02888839 -1.009791 0.4232417 -0.01270714 1.043687
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.2339128 -1.165872 -0.8967623 1.045664 0.3943777 0.1495314 -0.6965406
[2,] -0.2339128 -1.165872 -0.8967623 1.045664 0.3943777 0.1495314 -0.6965406
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.298719 0.7857208 1.438702 -0.5575733 0.500653 -0.4476449 0.6366714
[2,] 1.298719 0.7857208 1.438702 -0.5575733 0.500653 -0.4476449 0.6366714
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.5735527 0.8747859 1.196854 -0.9876583 -0.1141766 -0.7491934 -0.07598869
[2,] 0.5735527 0.8747859 1.196854 -0.9876583 -0.1141766 -0.7491934 -0.07598869
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.0243907 -0.3492492 0.6568306 -0.539623 0.4235516 0.3229206 -0.3412901
[2,] 0.0243907 -0.3492492 0.6568306 -0.539623 0.4235516 0.3229206 -0.3412901
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.4003444 -1.318617 0.9178909 -2.029898 0.6728217 0.9253651 -1.254554
[2,] 0.4003444 -1.318617 0.9178909 -2.029898 0.6728217 0.9253651 -1.254554
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.458046 -1.006388 1.381484 -0.9937219 -1.979857 -0.3000737 0.666639
[2,] -1.458046 -1.006388 1.381484 -0.9937219 -1.979857 -0.3000737 0.666639
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 2.877763 -0.6702482 -0.8070294 0.4600936 -0.03662258 -1.133614 -1.001381
[2,] 2.877763 -0.6702482 -0.8070294 0.4600936 -0.03662258 -1.133614 -1.001381
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -2.334493 0.5244045 -0.166919 -0.7920216 0.1592212 -0.1470034 0.9827479
[2,] -2.334493 0.5244045 -0.166919 -0.7920216 0.1592212 -0.1470034 0.9827479
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 2.160593 0.4653897 -0.1216227 -0.1376192 -0.1116841 -0.0450005 -0.5053297
[2,] 2.160593 0.4653897 -0.1216227 -0.1376192 -0.1116841 -0.0450005 -0.5053297
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -2.363981 -1.449554 1.083634 -1.257561 0.982856 0.08941147 -0.04198613
[2,] -2.363981 -1.449554 1.083634 -1.257561 0.982856 0.08941147 -0.04198613
[,99] [,100]
[1,] -1.345893 -1.396472
[2,] -1.345893 -1.396472
>
>
> Max(tmp2)
[1] 2.467096
> Min(tmp2)
[1] -3.111855
> mean(tmp2)
[1] 0.01192728
> Sum(tmp2)
[1] 1.192728
> Var(tmp2)
[1] 0.8609944
>
> rowMeans(tmp2)
[1] -0.230641920 -0.059494628 0.357235022 -1.048712791 0.150203114
[6] -0.269720744 -3.111854596 0.869869164 0.385851746 0.545476807
[11] 0.795293847 0.608725627 1.350036125 -0.770833584 0.453122038
[16] -0.579188443 -0.837657179 0.935889101 0.137537019 0.022550772
[21] 0.623478816 -0.420036299 0.440768755 0.218119839 -0.294081276
[26] -0.626048049 0.390966519 0.350360694 0.076522598 0.420243871
[31] -0.691271741 1.290289119 1.539081008 -0.189952267 0.156244272
[36] 2.258558215 0.924834502 -0.089124688 -1.193506462 -1.221272789
[41] -0.271661244 -0.389619919 0.032051310 -1.887757435 -0.231325095
[46] 1.528734109 -0.773417030 -0.908890778 0.956401144 1.431198110
[51] -0.580566482 0.629870768 -0.366461936 -0.160691030 1.414692804
[56] -0.755798188 1.304418052 -0.187196163 0.917279624 1.057450767
[61] 2.467096421 0.564324795 0.056730322 0.919788106 -2.727842643
[66] 0.358273036 -0.030999772 -0.001229277 0.573294605 -0.599522066
[71] 0.782606158 -0.005273818 -0.227299951 1.542238519 0.218902436
[76] -0.565481787 -1.199708756 -0.378075951 -0.306420797 -0.446555013
[81] -1.093978197 -0.998686254 -1.398531588 0.774168803 -0.072777616
[86] 0.898359151 0.125468718 -0.618031394 -0.402359445 -0.470345723
[91] -0.623610431 -0.246646577 0.610440115 -0.436879408 -1.857686563
[96] 0.178291287 -1.402394936 -0.070822675 0.942908801 -0.065574986
> rowSums(tmp2)
[1] -0.230641920 -0.059494628 0.357235022 -1.048712791 0.150203114
[6] -0.269720744 -3.111854596 0.869869164 0.385851746 0.545476807
[11] 0.795293847 0.608725627 1.350036125 -0.770833584 0.453122038
[16] -0.579188443 -0.837657179 0.935889101 0.137537019 0.022550772
[21] 0.623478816 -0.420036299 0.440768755 0.218119839 -0.294081276
[26] -0.626048049 0.390966519 0.350360694 0.076522598 0.420243871
[31] -0.691271741 1.290289119 1.539081008 -0.189952267 0.156244272
[36] 2.258558215 0.924834502 -0.089124688 -1.193506462 -1.221272789
[41] -0.271661244 -0.389619919 0.032051310 -1.887757435 -0.231325095
[46] 1.528734109 -0.773417030 -0.908890778 0.956401144 1.431198110
[51] -0.580566482 0.629870768 -0.366461936 -0.160691030 1.414692804
[56] -0.755798188 1.304418052 -0.187196163 0.917279624 1.057450767
[61] 2.467096421 0.564324795 0.056730322 0.919788106 -2.727842643
[66] 0.358273036 -0.030999772 -0.001229277 0.573294605 -0.599522066
[71] 0.782606158 -0.005273818 -0.227299951 1.542238519 0.218902436
[76] -0.565481787 -1.199708756 -0.378075951 -0.306420797 -0.446555013
[81] -1.093978197 -0.998686254 -1.398531588 0.774168803 -0.072777616
[86] 0.898359151 0.125468718 -0.618031394 -0.402359445 -0.470345723
[91] -0.623610431 -0.246646577 0.610440115 -0.436879408 -1.857686563
[96] 0.178291287 -1.402394936 -0.070822675 0.942908801 -0.065574986
> 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] -0.230641920 -0.059494628 0.357235022 -1.048712791 0.150203114
[6] -0.269720744 -3.111854596 0.869869164 0.385851746 0.545476807
[11] 0.795293847 0.608725627 1.350036125 -0.770833584 0.453122038
[16] -0.579188443 -0.837657179 0.935889101 0.137537019 0.022550772
[21] 0.623478816 -0.420036299 0.440768755 0.218119839 -0.294081276
[26] -0.626048049 0.390966519 0.350360694 0.076522598 0.420243871
[31] -0.691271741 1.290289119 1.539081008 -0.189952267 0.156244272
[36] 2.258558215 0.924834502 -0.089124688 -1.193506462 -1.221272789
[41] -0.271661244 -0.389619919 0.032051310 -1.887757435 -0.231325095
[46] 1.528734109 -0.773417030 -0.908890778 0.956401144 1.431198110
[51] -0.580566482 0.629870768 -0.366461936 -0.160691030 1.414692804
[56] -0.755798188 1.304418052 -0.187196163 0.917279624 1.057450767
[61] 2.467096421 0.564324795 0.056730322 0.919788106 -2.727842643
[66] 0.358273036 -0.030999772 -0.001229277 0.573294605 -0.599522066
[71] 0.782606158 -0.005273818 -0.227299951 1.542238519 0.218902436
[76] -0.565481787 -1.199708756 -0.378075951 -0.306420797 -0.446555013
[81] -1.093978197 -0.998686254 -1.398531588 0.774168803 -0.072777616
[86] 0.898359151 0.125468718 -0.618031394 -0.402359445 -0.470345723
[91] -0.623610431 -0.246646577 0.610440115 -0.436879408 -1.857686563
[96] 0.178291287 -1.402394936 -0.070822675 0.942908801 -0.065574986
> rowMin(tmp2)
[1] -0.230641920 -0.059494628 0.357235022 -1.048712791 0.150203114
[6] -0.269720744 -3.111854596 0.869869164 0.385851746 0.545476807
[11] 0.795293847 0.608725627 1.350036125 -0.770833584 0.453122038
[16] -0.579188443 -0.837657179 0.935889101 0.137537019 0.022550772
[21] 0.623478816 -0.420036299 0.440768755 0.218119839 -0.294081276
[26] -0.626048049 0.390966519 0.350360694 0.076522598 0.420243871
[31] -0.691271741 1.290289119 1.539081008 -0.189952267 0.156244272
[36] 2.258558215 0.924834502 -0.089124688 -1.193506462 -1.221272789
[41] -0.271661244 -0.389619919 0.032051310 -1.887757435 -0.231325095
[46] 1.528734109 -0.773417030 -0.908890778 0.956401144 1.431198110
[51] -0.580566482 0.629870768 -0.366461936 -0.160691030 1.414692804
[56] -0.755798188 1.304418052 -0.187196163 0.917279624 1.057450767
[61] 2.467096421 0.564324795 0.056730322 0.919788106 -2.727842643
[66] 0.358273036 -0.030999772 -0.001229277 0.573294605 -0.599522066
[71] 0.782606158 -0.005273818 -0.227299951 1.542238519 0.218902436
[76] -0.565481787 -1.199708756 -0.378075951 -0.306420797 -0.446555013
[81] -1.093978197 -0.998686254 -1.398531588 0.774168803 -0.072777616
[86] 0.898359151 0.125468718 -0.618031394 -0.402359445 -0.470345723
[91] -0.623610431 -0.246646577 0.610440115 -0.436879408 -1.857686563
[96] 0.178291287 -1.402394936 -0.070822675 0.942908801 -0.065574986
>
> colMeans(tmp2)
[1] 0.01192728
> colSums(tmp2)
[1] 1.192728
> colVars(tmp2)
[1] 0.8609944
> colSd(tmp2)
[1] 0.9278978
> colMax(tmp2)
[1] 2.467096
> colMin(tmp2)
[1] -3.111855
> colMedians(tmp2)
[1] -0.0181368
> colRanges(tmp2)
[,1]
[1,] -3.111855
[2,] 2.467096
>
> 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] -1.9916483 3.5376113 -0.8385374 0.8842515 0.5391171 -1.1211752
[7] -3.4818895 -3.5638108 1.4820475 -0.7957777
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5784693
[2,] -0.5510894
[3,] -0.1252096
[4,] 0.0348603
[5,] 1.3079443
>
> rowApply(tmp,sum)
[1] -1.47388656 4.69165760 -1.05679570 -4.05361443 -0.17951949 -4.64716530
[7] 0.14286223 1.93819184 -0.79588952 0.08434782
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 4 5 8 10 6 4 5 4 3
[2,] 8 9 8 9 2 5 10 6 3 9
[3,] 10 10 1 4 8 4 7 2 8 1
[4,] 6 7 3 10 4 7 5 7 5 7
[5,] 5 2 10 5 3 10 6 4 1 10
[6,] 9 3 9 2 5 9 1 8 7 2
[7,] 2 8 4 3 9 1 3 3 2 8
[8,] 3 5 6 6 1 8 2 1 6 6
[9,] 7 6 2 7 7 2 8 10 9 5
[10,] 4 1 7 1 6 3 9 9 10 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.31214781 0.05233853 -5.18852506 -2.66382954 3.24747778 4.06161895
[7] -5.38174258 1.70080134 -0.61922137 -1.87270576 1.78048365 0.54702737
[13] -2.71893501 1.43323827 -0.24137778 -0.15524888 -1.27808215 2.94019036
[19] -0.11766077 1.20210680
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.7987641
[2,] -0.6168743
[3,] -0.5056868
[4,] 0.6978070
[5,] 2.5356659
>
> rowApply(tmp,sum)
[1] 3.08735558 -7.22528664 -0.05378343 -2.72147751 4.95329397
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 16 9 4 8 20
[2,] 10 18 8 7 12
[3,] 1 19 2 1 5
[4,] 13 5 17 2 4
[5,] 18 11 10 20 11
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.6978070 0.3474485 -2.0959597 0.5065494 0.7888584 1.6415561
[2,] -0.5056868 0.5276271 1.1136367 -1.3829276 -0.2887487 -0.9613292
[3,] -0.6168743 -0.1782334 -1.5016189 0.7395678 -0.0434335 2.3138912
[4,] -0.7987641 -0.9128797 -2.0363918 -1.5341485 2.5341521 -0.4416532
[5,] 2.5356659 0.2683761 -0.6681914 -0.9928707 0.2566496 1.5091540
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.41264583 1.30648591 0.53175887 0.3435802 0.70246181 0.17800324
[2,] -1.68964342 -0.73874321 -0.15975012 -0.2504150 -0.35941620 -2.27874914
[3,] 0.02998943 -0.07622679 0.02851587 -0.3735680 0.29014293 0.95136147
[4,] -1.17957762 0.70774511 0.03773860 -1.3386078 1.21968866 -0.01312576
[5,] -1.12986515 0.50154031 -1.05748459 -0.2536952 -0.07239355 1.70953757
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.6131199 -0.3425370 0.5131807 -0.7595601 -0.1074191 0.49307619
[2,] 2.0680789 0.4083429 -1.5499601 0.3656170 -0.6173674 0.05794563
[3,] -1.9253285 0.8662812 -0.4295807 0.5578201 0.5260119 0.43579787
[4,] -0.9967507 1.0693561 0.5487933 -1.2387878 -0.6752952 0.99674203
[5,] -1.2518148 -0.5682048 0.6761890 0.9196619 -0.4040124 0.95662863
[,19] [,20]
[1,] -0.04794012 0.4157709
[2,] 0.50445145 -1.4882493
[3,] -1.15293625 -0.4953630
[4,] 0.83608313 0.4942056
[5,] -0.25731898 2.2757426
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.8 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 625 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 541 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.8 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.712828 0.3468902 0.5032788 0.4861797 -0.09583008 1.430157 0.191492
col8 col9 col10 col11 col12 col13 col14
row1 0.3858786 -0.8647999 0.3671482 -0.3917724 -1.020274 0.2790958 1.002814
col15 col16 col17 col18 col19 col20
row1 0.5381602 0.5854534 0.2151633 -1.432727 0.721069 0.8198343
> tmp[,"col10"]
col10
row1 0.3671482
row2 1.1883270
row3 -0.4162536
row4 1.2868228
row5 -2.1275863
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.7128280 0.3468902 0.5032788 0.4861797 -0.09583008 1.4301571 0.191492
row5 0.9530108 1.3402713 1.8588784 -1.3648529 0.70314534 0.4203984 2.110615
col8 col9 col10 col11 col12 col13 col14
row1 0.3858786 -0.8647999 0.3671482 -0.3917724 -1.0202735 0.2790958 1.00281442
row5 2.3265091 -0.6145140 -2.1275863 -1.2221206 0.1836594 1.1150472 0.08374449
col15 col16 col17 col18 col19 col20
row1 0.5381602 0.5854534 0.21516334 -1.4327269 0.7210690 0.8198343
row5 0.2111699 -1.7634153 0.09361132 -0.8233105 -0.5856158 -0.4017160
> tmp[,c("col6","col20")]
col6 col20
row1 1.43015709 0.8198343
row2 0.07241647 0.7524496
row3 -0.83397645 0.2588748
row4 -0.52480855 -1.1819097
row5 0.42039839 -0.4017160
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.4301571 0.8198343
row5 0.4203984 -0.4017160
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.36537 51.58408 49.26473 49.08403 49.1583 103.8329 50.40098 47.11419
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.21677 52.05671 49.05208 51.22376 48.39722 49.82702 49.7949 52.25578
col17 col18 col19 col20
row1 49.35334 48.56046 48.97239 105.8416
> tmp[,"col10"]
col10
row1 52.05671
row2 30.10764
row3 31.46315
row4 30.07463
row5 51.30528
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.36537 51.58408 49.26473 49.08403 49.15830 103.8329 50.40098 47.11419
row5 48.87635 49.60461 50.15227 48.34579 47.78729 103.5117 48.09030 47.44730
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.21677 52.05671 49.05208 51.22376 48.39722 49.82702 49.79490 52.25578
row5 50.12495 51.30528 47.97744 49.18119 49.51528 49.96275 48.26854 50.33634
col17 col18 col19 col20
row1 49.35334 48.56046 48.97239 105.8416
row5 50.85708 50.08356 49.24277 105.9291
> tmp[,c("col6","col20")]
col6 col20
row1 103.83293 105.84158
row2 77.11910 74.55121
row3 75.26761 76.51490
row4 72.98702 74.68697
row5 103.51168 105.92909
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 103.8329 105.8416
row5 103.5117 105.9291
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 103.8329 105.8416
row5 103.5117 105.9291
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.3041934
[2,] 1.5160165
[3,] -0.3213563
[4,] -0.7623237
[5,] -0.9702956
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.023702186 1.3585628
[2,] 0.574943789 -0.1924532
[3,] 0.631120767 0.1524371
[4,] -0.009133221 -0.3152127
[5,] 1.988453575 -1.7128124
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.01722296 -0.55891721
[2,] 0.20661988 -1.62963426
[3,] -0.25066534 0.14865176
[4,] -0.05528690 0.27540880
[5,] -1.57126774 -0.01151077
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.01722296
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.01722296
[2,] 0.20661988
>
>
>
> 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 0.1126673 -1.2681009 -0.7019434 -0.6791806 -1.2418710 1.7183439 1.2820814
row1 0.5031108 0.1802954 -0.8045298 -0.1575854 0.2947703 -0.6520306 0.1073961
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -0.5623251 0.5899265 0.7539296 -0.4067490 -0.4521149 1.45310 1.594029
row1 0.7535113 -1.3799146 0.8877638 0.6836083 1.0605110 1.70532 2.219555
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.5890979 1.319851 -0.6521583 -0.01711037 1.2194603 0.01070924
row1 1.1478674 -1.010181 0.1301660 0.16372389 -0.4198443 0.40844954
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6]
row2 -0.05195507 0.6325032 -0.5472355 -0.6591799 0.06860744 -0.5273091
[,7] [,8] [,9] [,10]
row2 -0.721211 -0.4307493 -1.425226 1.078169
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.9651937 0.06714546 1.338149 2.049852 -1.366571 -0.7720222 -0.6748581
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.115199 -0.5601785 1.623178 0.7579456 1.535009 -0.746851 0.8966914
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.5588583 0.9004602 -1.397114 1.605572 1.184567 -1.547722
>
>
> 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: 0x000001b4636fdd10>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM365051586e8e"
[2] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3650d916f07"
[3] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM365067da5bb3"
[4] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM36503626813"
[5] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3650367066fc"
[6] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3650fa37f3b"
[7] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM36506a79569c"
[8] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM365034cd6de0"
[9] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM365055607da5"
[10] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM365063b76350"
[11] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM365023cc6671"
[12] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3650c662247"
[13] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM365015167c42"
[14] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM3650312617b6"
[15] "F:/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests\\BM365047007825"
>
>
> ### 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: 0x000001b465dff110>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x000001b465dff110>
Warning message:
In dir.create(new.directory) :
'F:\biocbuild\bbs-3.19-bioc\meat\BufferedMatrix.Rcheck\tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x000001b465dff110>
> rowMedians(tmp)
[1] -0.101428724 -0.250850036 0.234164677 -0.506847280 0.182193683
[6] 0.526114853 -0.153988858 -0.084328936 -0.823022990 0.200020889
[11] 0.220700819 -0.177813548 -0.702407610 0.391021167 -0.038135286
[16] -0.258601349 -0.297152080 0.222719282 0.192193568 0.235492077
[21] -0.104377630 0.269777190 -0.127635144 0.138679662 -0.056464448
[26] 0.092566132 0.071780758 -0.354926944 -0.316114961 -0.156741486
[31] 0.475060336 -0.250450022 0.082857883 -0.026526916 0.563755283
[36] 0.022444991 -0.006919366 -0.139439932 -0.169185098 -0.154434151
[41] -0.371725861 -0.028433955 -0.246523217 0.014098171 0.013557220
[46] 0.282131286 0.195367248 -0.177759616 -0.538110495 0.030269419
[51] 0.315561027 0.170605505 -0.309241832 0.155569085 -0.864322358
[56] -0.280614634 -0.086837779 -0.009489430 -0.102992766 0.581269437
[61] 0.510786135 -0.534982974 0.072790889 0.131501686 -0.267796993
[66] 0.272979041 0.276527338 0.195481199 0.437429750 0.864592037
[71] 0.146381886 0.434659426 0.344596361 -0.225150934 -0.131663393
[76] 0.246773924 -0.512198815 -0.308725091 -0.060845246 0.780953854
[81] -0.065748398 -0.018141271 -0.335178229 0.803813341 0.440977407
[86] 0.303748317 -0.343383832 -0.118520050 -0.233273145 0.023892887
[91] -0.381586469 -0.343336977 -0.176340167 -0.163333614 -0.362264693
[96] -0.318478036 -0.212629166 -0.321186926 0.087987653 -0.164756314
[101] -0.141885563 -0.513394600 0.032648999 -0.512626438 0.274962767
[106] 0.535481723 -0.182607300 -0.125498245 0.227878056 0.062632286
[111] -0.339061196 0.024372383 0.140165054 0.045270355 -0.043694056
[116] 0.522297267 -0.267116585 0.121500004 0.277702340 0.332953124
[121] 0.030962072 0.322797271 0.646011999 -0.024847041 0.047730828
[126] -0.419470290 0.189276243 0.025816234 0.184323431 -0.237282973
[131] 0.101286514 -0.193571572 0.095986388 0.168708965 0.069389038
[136] -0.076530589 0.106584211 -0.358070594 0.317263057 -0.291336604
[141] -0.284618287 0.245912058 -0.356513517 0.051873596 -0.790823796
[146] -0.514355678 -0.710424594 0.182059683 -0.225842186 -0.322455060
[151] -0.273460332 0.070102327 0.030700952 0.128827671 -0.130547924
[156] -0.183942149 -0.568246196 0.316086099 0.274477012 -0.074965455
[161] -0.147821446 -0.095031893 -0.175201932 -0.216627941 -0.549308847
[166] 0.671711332 0.267091060 0.094233101 -0.239776078 -0.152552337
[171] 0.469856026 0.367017289 -0.897061164 -0.443014181 0.014896205
[176] 0.191193724 -0.004201269 -0.184902047 -0.202540691 -0.274634088
[181] 0.251398935 -0.149954603 0.013787440 -0.587050562 0.033258739
[186] -0.224117998 -0.246634815 0.093873490 0.268988714 -0.021729967
[191] -0.209522982 0.031479947 -0.155481525 0.259576314 0.356450429
[196] 0.209354469 -0.101148473 -0.022636767 0.129767340 -0.088022292
[201] -0.625127850 0.209942143 0.086712060 0.170827723 -0.288346618
[206] -0.275075191 -0.135324961 0.856283381 -0.025850333 0.057777045
[211] 0.466377986 0.232560030 -0.493939397 -0.027600778 0.029083982
[216] -0.049471138 0.048414922 0.115347954 -0.217378018 0.498439625
[221] 0.303644433 0.337447173 -0.280215064 0.150380642 0.125306816
[226] -0.221555372 0.046460735 -0.127734729 0.501678924 -0.202459163
>
> proc.time()
user system elapsed
3.43 17.93 34.40
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: 0x000002d15c2fd1d0>
> .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: 0x000002d15c2fd1d0>
> .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: 0x000002d15c2fd1d0>
> .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: 0x000002d15c2fd1d0>
> 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: 0x000002d15c2fd230>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002d15c2fd230>
> .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: 0x000002d15c2fd230>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002d15c2fd230>
> .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: 0x000002d15c2fd230>
> 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: 0x000002d15c2fdbf0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002d15c2fdbf0>
> .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: 0x000002d15c2fdbf0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000002d15c2fdbf0>
> .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: 0x000002d15c2fdbf0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x000002d15c2fdbf0>
> .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: 0x000002d15c2fdbf0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x000002d15c2fdbf0>
> .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: 0x000002d15c2fdbf0>
> 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: 0x000002d15c2fdad0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x000002d15c2fdad0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002d15c2fdad0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002d15c2fdad0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3ab42b71cb6" "BufferedMatrixFile3ab43a254a7e"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3ab42b71cb6" "BufferedMatrixFile3ab43a254a7e"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002d15c2fd470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002d15c2fd470>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000002d15c2fd470>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000002d15c2fd470>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x000002d15c2fd470>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x000002d15c2fd470>
> .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: 0x000002d15c2fdb90>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002d15c2fdb90>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000002d15c2fdb90>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x000002d15c2fdb90>
> 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: 0x000002d15c2fd650>
> .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: 0x000002d15c2fd650>
> rm(P)
>
> proc.time()
user system elapsed
0.34 0.14 0.54
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup"
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Platform: x86_64-w64-mingw32/x64
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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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
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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
0.21 0.07 1.12