| Back to Build/check report for BioC 3.17 |
|
This page was generated on 2023-01-02 09:00:21 -0500 (Mon, 02 Jan 2023).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| palomino5 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2022-12-25 r83502 ucrt) -- "Unsuffered Consequences" | 4165 |
| 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 | ||||
|
To the developers/maintainers of the BufferedMatrix package: Make sure to use the following settings in order to reproduce any error or warning you see on this page. |
| Package 227/2158 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.63.0 (landing page) Ben Bolstad
| palomino5 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | ||||||||
| Package: BufferedMatrix |
| Version: 1.63.0 |
| Command: F:\biocbuild\bbs-3.17-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=F:\biocbuild\bbs-3.17-bioc\R\library --no-vignettes --timings BufferedMatrix_1.63.0.tar.gz |
| StartedAt: 2022-12-28 22:09:15 -0500 (Wed, 28 Dec 2022) |
| EndedAt: 2022-12-28 22:10:55 -0500 (Wed, 28 Dec 2022) |
| EllapsedTime: 100.4 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.17-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=F:\biocbuild\bbs-3.17-bioc\R\library --no-vignettes --timings BufferedMatrix_1.63.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck'
* using R Under development (unstable) (2022-12-25 r83502 ucrt)
* using platform: x86_64-w64-mingw32 (64-bit)
* R was compiled by
gcc.exe (GCC) 10.4.0
GNU Fortran (GCC) 10.4.0
* running under: Windows Server x64 (build 20348)
* using session charset: UTF-8
* using option '--no-vignettes'
* checking for file 'BufferedMatrix/DESCRIPTION' ... OK
* this is package 'BufferedMatrix' version '1.63.0'
* 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) 12.2.0'
* 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 R 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
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-3.17-bioc/R/library/BufferedMatrix/libs/x64/BufferedMatrix.dll':
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 in 'inst/doc' ... 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-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/00check.log'
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.17-bioc\R\bin\R.exe CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library 'F:/biocbuild/bbs-3.17-bioc/R/library'
* installing *source* package 'BufferedMatrix' ...
** using staged installation
** libs
using C compiler: 'gcc.exe (GCC) 12.2.0'
gcc -I"F:/biocbuild/bbs-3.17-bioc/R/include" -DNDEBUG -I"c:/rtools42/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -std=gnu99 -mfpmath=sse -msse2 -mstackrealign -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"F:/biocbuild/bbs-3.17-bioc/R/include" -DNDEBUG -I"c:/rtools42/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -std=gnu99 -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-3.17-bioc/R/include" -DNDEBUG -I"c:/rtools42/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -std=gnu99 -mfpmath=sse -msse2 -mstackrealign -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"F:/biocbuild/bbs-3.17-bioc/R/include" -DNDEBUG -I"c:/rtools42/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -std=gnu99 -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:/rtools42/x86_64-w64-mingw32.static.posix/lib/x64 -Lc:/rtools42/x86_64-w64-mingw32.static.posix/lib -LF:/biocbuild/bbs-3.17-bioc/R/bin/x64 -lR
installing to F:/biocbuild/bbs-3.17-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 Under development (unstable) (2022-12-25 r83502 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
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
0.28 0.12 0.62
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2022-12-25 r83502 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
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-3.17-bioc-rtools43/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 453754 24.3 975562 52.2 641754 34.3
Vcells 824665 6.3 8388608 64.0 1993296 15.3
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Wed Dec 28 22:09:38 2022"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed Dec 28 22:09:39 2022"
>
>
> 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: 0x000001a52ac778f0>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Wed Dec 28 22:10:01 2022"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed Dec 28 22:10:09 2022"
>
> ColMode(tmp2)
<pointer: 0x000001a52ac778f0>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.4149416 0.1503060 0.3675674 -1.86420861
[2,] 0.1308226 1.6056892 1.1509038 0.04140905
[3,] -0.4633666 -1.2975514 -1.4845682 -0.22760725
[4,] -0.5337812 0.8332684 -0.1682810 1.41752372
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.4149416 0.1503060 0.3675674 1.86420861
[2,] 0.1308226 1.6056892 1.1509038 0.04140905
[3,] 0.4633666 1.2975514 1.4845682 0.22760725
[4,] 0.5337812 0.8332684 0.1682810 1.41752372
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0207256 0.3876931 0.6062734 1.3653603
[2,] 0.3616940 1.2671579 1.0728019 0.2034921
[3,] 0.6807104 1.1391011 1.2184286 0.4770820
[4,] 0.7306033 0.9128354 0.4102206 1.1905981
>
> 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-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.62220 29.02724 31.43030 40.51781
[2,] 28.74776 39.27727 36.87892 27.07633
[3,] 32.27047 37.68856 38.66885 29.99843
[4,] 32.83981 34.96162 29.27049 38.32350
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x000001a52ac779d0>
> exp(tmp5)
<pointer: 0x000001a52ac779d0>
> log(tmp5,2)
<pointer: 0x000001a52ac779d0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.603
> Min(tmp5)
[1] 52.41473
> mean(tmp5)
[1] 73.74008
> Sum(tmp5)
[1] 14748.02
> Var(tmp5)
[1] 867.3454
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 93.27004 71.08147 71.11330 73.20872 67.43268 68.74433 72.08731 73.79907
[9] 72.04345 74.62043
> rowSums(tmp5)
[1] 1865.401 1421.629 1422.266 1464.174 1348.654 1374.887 1441.746 1475.981
[9] 1440.869 1492.409
> rowVars(tmp5)
[1] 7926.91835 91.68655 50.26797 89.14037 74.44556 71.78916
[7] 71.49572 62.53561 66.43868 88.21612
> rowSd(tmp5)
[1] 89.033243 9.575309 7.089991 9.441418 8.628184 8.472848 8.455514
[8] 7.907946 8.150993 9.392344
> rowMax(tmp5)
[1] 469.60304 86.52930 83.14212 94.42732 79.80259 88.26358 83.46834
[8] 85.73359 85.72646 90.28332
> rowMin(tmp5)
[1] 60.41639 56.35583 61.65990 60.19844 54.15945 52.41473 59.05012 58.55409
[9] 60.44314 55.19533
>
> colMeans(tmp5)
[1] 109.98994 76.16676 72.35261 72.13643 71.85957 70.86850 69.47078
[8] 70.59286 68.00964 69.54060 73.88145 71.48987 69.07282 73.04398
[15] 68.85044 72.90768 74.22051 71.92070 75.48890 72.93758
> colSums(tmp5)
[1] 1099.8994 761.6676 723.5261 721.3643 718.5957 708.6850 694.7078
[8] 705.9286 680.0964 695.4060 738.8145 714.8987 690.7282 730.4398
[15] 688.5044 729.0768 742.2051 719.2070 754.8890 729.3758
> colVars(tmp5)
[1] 16043.16239 62.66089 54.71214 160.65872 72.17228 63.73814
[7] 49.52130 66.34450 97.02668 53.96475 72.15738 95.95021
[13] 106.63774 70.71686 78.05306 126.93552 69.53253 61.69811
[19] 78.81491 55.71142
> colSd(tmp5)
[1] 126.661606 7.915863 7.396765 12.675122 8.495427 7.983617
[7] 7.037137 8.145213 9.850212 7.346070 8.494550 9.795418
[13] 10.326555 8.409332 8.834764 11.266566 8.338617 7.854814
[19] 8.877776 7.464009
> colMax(tmp5)
[1] 469.60304 85.73359 81.54867 87.43793 84.81166 83.25946 79.96128
[8] 86.52930 79.96226 80.90558 86.43463 94.42732 83.20207 83.03259
[15] 83.46834 91.58902 84.14025 84.02882 90.28332 81.69629
> colMin(tmp5)
[1] 59.83470 60.41639 60.92268 54.15945 58.34849 58.63605 59.05027 61.24175
[9] 52.41473 60.00540 62.08060 62.95743 55.19533 57.14773 54.61264 59.11837
[17] 59.05012 58.55409 60.19844 59.38015
>
>
> ### 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] 93.27004 71.08147 71.11330 73.20872 67.43268 NA 72.08731 73.79907
[9] 72.04345 74.62043
> rowSums(tmp5)
[1] 1865.401 1421.629 1422.266 1464.174 1348.654 NA 1441.746 1475.981
[9] 1440.869 1492.409
> rowVars(tmp5)
[1] 7926.91835 91.68655 50.26797 89.14037 74.44556 75.68743
[7] 71.49572 62.53561 66.43868 88.21612
> rowSd(tmp5)
[1] 89.033243 9.575309 7.089991 9.441418 8.628184 8.699853 8.455514
[8] 7.907946 8.150993 9.392344
> rowMax(tmp5)
[1] 469.60304 86.52930 83.14212 94.42732 79.80259 NA 83.46834
[8] 85.73359 85.72646 90.28332
> rowMin(tmp5)
[1] 60.41639 56.35583 61.65990 60.19844 54.15945 NA 59.05012 58.55409
[9] 60.44314 55.19533
>
> colMeans(tmp5)
[1] 109.98994 76.16676 NA 72.13643 71.85957 70.86850 69.47078
[8] 70.59286 68.00964 69.54060 73.88145 71.48987 69.07282 73.04398
[15] 68.85044 72.90768 74.22051 71.92070 75.48890 72.93758
> colSums(tmp5)
[1] 1099.8994 761.6676 NA 721.3643 718.5957 708.6850 694.7078
[8] 705.9286 680.0964 695.4060 738.8145 714.8987 690.7282 730.4398
[15] 688.5044 729.0768 742.2051 719.2070 754.8890 729.3758
> colVars(tmp5)
[1] 16043.16239 62.66089 NA 160.65872 72.17228 63.73814
[7] 49.52130 66.34450 97.02668 53.96475 72.15738 95.95021
[13] 106.63774 70.71686 78.05306 126.93552 69.53253 61.69811
[19] 78.81491 55.71142
> colSd(tmp5)
[1] 126.661606 7.915863 NA 12.675122 8.495427 7.983617
[7] 7.037137 8.145213 9.850212 7.346070 8.494550 9.795418
[13] 10.326555 8.409332 8.834764 11.266566 8.338617 7.854814
[19] 8.877776 7.464009
> colMax(tmp5)
[1] 469.60304 85.73359 NA 87.43793 84.81166 83.25946 79.96128
[8] 86.52930 79.96226 80.90558 86.43463 94.42732 83.20207 83.03259
[15] 83.46834 91.58902 84.14025 84.02882 90.28332 81.69629
> colMin(tmp5)
[1] 59.83470 60.41639 NA 54.15945 58.34849 58.63605 59.05027 61.24175
[9] 52.41473 60.00540 62.08060 62.95743 55.19533 57.14773 54.61264 59.11837
[17] 59.05012 58.55409 60.19844 59.38015
>
> Max(tmp5,na.rm=TRUE)
[1] 469.603
> Min(tmp5,na.rm=TRUE)
[1] 52.41473
> mean(tmp5,na.rm=TRUE)
[1] 73.75895
> Sum(tmp5,na.rm=TRUE)
[1] 14678.03
> Var(tmp5,na.rm=TRUE)
[1] 871.6544
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.27004 71.08147 71.11330 73.20872 67.43268 68.67903 72.08731 73.79907
[9] 72.04345 74.62043
> rowSums(tmp5,na.rm=TRUE)
[1] 1865.401 1421.629 1422.266 1464.174 1348.654 1304.902 1441.746 1475.981
[9] 1440.869 1492.409
> rowVars(tmp5,na.rm=TRUE)
[1] 7926.91835 91.68655 50.26797 89.14037 74.44556 75.68743
[7] 71.49572 62.53561 66.43868 88.21612
> rowSd(tmp5,na.rm=TRUE)
[1] 89.033243 9.575309 7.089991 9.441418 8.628184 8.699853 8.455514
[8] 7.907946 8.150993 9.392344
> rowMax(tmp5,na.rm=TRUE)
[1] 469.60304 86.52930 83.14212 94.42732 79.80259 88.26358 83.46834
[8] 85.73359 85.72646 90.28332
> rowMin(tmp5,na.rm=TRUE)
[1] 60.41639 56.35583 61.65990 60.19844 54.15945 52.41473 59.05012 58.55409
[9] 60.44314 55.19533
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.98994 76.16676 72.61568 72.13643 71.85957 70.86850 69.47078
[8] 70.59286 68.00964 69.54060 73.88145 71.48987 69.07282 73.04398
[15] 68.85044 72.90768 74.22051 71.92070 75.48890 72.93758
> colSums(tmp5,na.rm=TRUE)
[1] 1099.8994 761.6676 653.5411 721.3643 718.5957 708.6850 694.7078
[8] 705.9286 680.0964 695.4060 738.8145 714.8987 690.7282 730.4398
[15] 688.5044 729.0768 742.2051 719.2070 754.8890 729.3758
> colVars(tmp5,na.rm=TRUE)
[1] 16043.16239 62.66089 60.77258 160.65872 72.17228 63.73814
[7] 49.52130 66.34450 97.02668 53.96475 72.15738 95.95021
[13] 106.63774 70.71686 78.05306 126.93552 69.53253 61.69811
[19] 78.81491 55.71142
> colSd(tmp5,na.rm=TRUE)
[1] 126.661606 7.915863 7.795677 12.675122 8.495427 7.983617
[7] 7.037137 8.145213 9.850212 7.346070 8.494550 9.795418
[13] 10.326555 8.409332 8.834764 11.266566 8.338617 7.854814
[19] 8.877776 7.464009
> colMax(tmp5,na.rm=TRUE)
[1] 469.60304 85.73359 81.54867 87.43793 84.81166 83.25946 79.96128
[8] 86.52930 79.96226 80.90558 86.43463 94.42732 83.20207 83.03259
[15] 83.46834 91.58902 84.14025 84.02882 90.28332 81.69629
> colMin(tmp5,na.rm=TRUE)
[1] 59.83470 60.41639 60.92268 54.15945 58.34849 58.63605 59.05027 61.24175
[9] 52.41473 60.00540 62.08060 62.95743 55.19533 57.14773 54.61264 59.11837
[17] 59.05012 58.55409 60.19844 59.38015
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.27004 71.08147 71.11330 73.20872 67.43268 NaN 72.08731 73.79907
[9] 72.04345 74.62043
> rowSums(tmp5,na.rm=TRUE)
[1] 1865.401 1421.629 1422.266 1464.174 1348.654 0.000 1441.746 1475.981
[9] 1440.869 1492.409
> rowVars(tmp5,na.rm=TRUE)
[1] 7926.91835 91.68655 50.26797 89.14037 74.44556 NA
[7] 71.49572 62.53561 66.43868 88.21612
> rowSd(tmp5,na.rm=TRUE)
[1] 89.033243 9.575309 7.089991 9.441418 8.628184 NA 8.455514
[8] 7.907946 8.150993 9.392344
> rowMax(tmp5,na.rm=TRUE)
[1] 469.60304 86.52930 83.14212 94.42732 79.80259 NA 83.46834
[8] 85.73359 85.72646 90.28332
> rowMin(tmp5,na.rm=TRUE)
[1] 60.41639 56.35583 61.65990 60.19844 54.15945 NA 59.05012 58.55409
[9] 60.44314 55.19533
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 112.40397 77.24266 NaN 73.37525 72.73434 71.56216 69.09265
[8] 70.70102 69.74241 70.60007 74.45063 72.37794 70.35453 72.24598
[15] 67.71909 73.68808 73.73780 71.94687 75.86198 73.45016
> colSums(tmp5,na.rm=TRUE)
[1] 1011.6358 695.1840 0.0000 660.3772 654.6091 644.0595 621.8339
[8] 636.3092 627.6816 635.4006 670.0557 651.4014 633.1908 650.2139
[15] 609.4718 663.1927 663.6402 647.5218 682.7578 661.0514
> colVars(tmp5,na.rm=TRUE)
[1] 17982.99738 57.47074 NA 163.47595 72.58515 66.29230
[7] 54.10292 74.50595 75.37710 48.08256 77.53237 99.07164
[13] 101.48612 72.39249 73.41009 135.95085 75.60275 69.40266
[19] 87.10090 59.71951
> colSd(tmp5,na.rm=TRUE)
[1] 134.100699 7.580946 NA 12.785771 8.519692 8.142008
[7] 7.355469 8.631683 8.681999 6.934159 8.805247 9.953474
[13] 10.074032 8.508378 8.567969 11.659796 8.694984 8.330826
[19] 9.332786 7.727840
> colMax(tmp5,na.rm=TRUE)
[1] 469.60304 85.73359 -Inf 87.43793 84.81166 83.25946 79.96128
[8] 86.52930 79.96226 80.90558 86.43463 94.42732 83.20207 83.03259
[15] 83.46834 91.58902 84.14025 84.02882 90.28332 81.69629
> colMin(tmp5,na.rm=TRUE)
[1] 59.83470 60.41639 Inf 54.15945 58.34849 58.63605 59.05027 61.24175
[9] 57.47129 62.37847 62.08060 62.95743 55.19533 57.14773 54.61264 59.11837
[17] 59.05012 58.55409 60.19844 59.38015
>
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 3
> which.col <- 1
> cat(which.row," ",which.col,"\n")
3 1
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> rowVars(tmp5,na.rm=TRUE)
[1] 192.64832 170.21320 244.16341 233.95987 210.68272 83.28207 222.90815
[8] 194.60219 215.05084 285.67849
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 192.64832 170.21320 244.16341 233.95987 210.68272 83.28207 222.90815
[8] 194.60219 215.05084 285.67849
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 0.000000e+00 -5.684342e-14 1.421085e-13 0.000000e+00 1.136868e-13
[6] 9.947598e-14 -1.136868e-13 5.684342e-14 2.273737e-13 -1.989520e-13
[11] -5.684342e-14 -2.842171e-14 -2.273737e-13 0.000000e+00 1.705303e-13
[16] 2.842171e-14 2.842171e-14 1.705303e-13 0.000000e+00 -5.684342e-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)
+ }
9 19
8 10
10 12
10 15
3 14
5 17
10 19
8 3
8 14
1 1
7 12
2 10
6 12
6 1
5 8
5 7
7 10
8 15
6 8
3 19
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] 2.576775
> Min(tmp)
[1] -2.571205
> mean(tmp)
[1] -0.08291464
> Sum(tmp)
[1] -8.291464
> Var(tmp)
[1] 1.101951
>
> rowMeans(tmp)
[1] -0.08291464
> rowSums(tmp)
[1] -8.291464
> rowVars(tmp)
[1] 1.101951
> rowSd(tmp)
[1] 1.049739
> rowMax(tmp)
[1] 2.576775
> rowMin(tmp)
[1] -2.571205
>
> colMeans(tmp)
[1] -0.570543084 -0.697764910 2.047992848 0.737072782 0.180694010
[6] 0.039857886 -0.956469778 -1.567691780 -0.246714804 -1.604299748
[11] -0.811600927 -0.419006171 0.666913063 -2.571204697 -1.957005836
[16] -1.031674276 0.294806065 -1.265062412 -1.149824972 -2.450894471
[21] 1.767318050 0.902957140 1.109781594 -0.643651765 -0.526687076
[26] 0.354014265 -0.461831429 -1.908639885 -0.449308003 -1.735972739
[31] 1.241472635 -0.476569730 1.032535868 1.812925909 -0.233766599
[36] -1.547763672 1.045517940 0.419061919 0.408914842 -1.430074720
[41] -1.301300896 0.775914787 -0.244585900 1.580859558 2.576775190
[46] 0.043846918 0.916457251 1.100237447 -0.900172829 0.112525551
[51] 1.373634846 -0.009947252 -0.982980702 0.997084312 -0.692532583
[56] 0.216952524 -1.065301906 0.516320575 -1.048687990 0.791763605
[61] 0.300965131 0.434959466 -1.201306724 -0.539892955 0.020318381
[66] 0.597237529 0.129974651 0.251984374 0.670162197 -0.867892529
[71] -0.167670628 -1.124278648 -0.450226131 0.312167882 -1.031629971
[76] 0.304043700 -0.772078761 0.312672183 1.080883899 1.047611333
[81] 0.387570886 0.741914442 -0.855876993 0.096759089 -0.470483508
[86] 1.041830115 0.115112363 -1.529812550 1.097215480 0.034276537
[91] 1.470885293 0.363058595 -2.145694293 0.095997183 0.039158521
[96] 0.840000927 -1.864000625 1.213842297 -0.929755936 0.553857626
> colSums(tmp)
[1] -0.570543084 -0.697764910 2.047992848 0.737072782 0.180694010
[6] 0.039857886 -0.956469778 -1.567691780 -0.246714804 -1.604299748
[11] -0.811600927 -0.419006171 0.666913063 -2.571204697 -1.957005836
[16] -1.031674276 0.294806065 -1.265062412 -1.149824972 -2.450894471
[21] 1.767318050 0.902957140 1.109781594 -0.643651765 -0.526687076
[26] 0.354014265 -0.461831429 -1.908639885 -0.449308003 -1.735972739
[31] 1.241472635 -0.476569730 1.032535868 1.812925909 -0.233766599
[36] -1.547763672 1.045517940 0.419061919 0.408914842 -1.430074720
[41] -1.301300896 0.775914787 -0.244585900 1.580859558 2.576775190
[46] 0.043846918 0.916457251 1.100237447 -0.900172829 0.112525551
[51] 1.373634846 -0.009947252 -0.982980702 0.997084312 -0.692532583
[56] 0.216952524 -1.065301906 0.516320575 -1.048687990 0.791763605
[61] 0.300965131 0.434959466 -1.201306724 -0.539892955 0.020318381
[66] 0.597237529 0.129974651 0.251984374 0.670162197 -0.867892529
[71] -0.167670628 -1.124278648 -0.450226131 0.312167882 -1.031629971
[76] 0.304043700 -0.772078761 0.312672183 1.080883899 1.047611333
[81] 0.387570886 0.741914442 -0.855876993 0.096759089 -0.470483508
[86] 1.041830115 0.115112363 -1.529812550 1.097215480 0.034276537
[91] 1.470885293 0.363058595 -2.145694293 0.095997183 0.039158521
[96] 0.840000927 -1.864000625 1.213842297 -0.929755936 0.553857626
> 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] -0.570543084 -0.697764910 2.047992848 0.737072782 0.180694010
[6] 0.039857886 -0.956469778 -1.567691780 -0.246714804 -1.604299748
[11] -0.811600927 -0.419006171 0.666913063 -2.571204697 -1.957005836
[16] -1.031674276 0.294806065 -1.265062412 -1.149824972 -2.450894471
[21] 1.767318050 0.902957140 1.109781594 -0.643651765 -0.526687076
[26] 0.354014265 -0.461831429 -1.908639885 -0.449308003 -1.735972739
[31] 1.241472635 -0.476569730 1.032535868 1.812925909 -0.233766599
[36] -1.547763672 1.045517940 0.419061919 0.408914842 -1.430074720
[41] -1.301300896 0.775914787 -0.244585900 1.580859558 2.576775190
[46] 0.043846918 0.916457251 1.100237447 -0.900172829 0.112525551
[51] 1.373634846 -0.009947252 -0.982980702 0.997084312 -0.692532583
[56] 0.216952524 -1.065301906 0.516320575 -1.048687990 0.791763605
[61] 0.300965131 0.434959466 -1.201306724 -0.539892955 0.020318381
[66] 0.597237529 0.129974651 0.251984374 0.670162197 -0.867892529
[71] -0.167670628 -1.124278648 -0.450226131 0.312167882 -1.031629971
[76] 0.304043700 -0.772078761 0.312672183 1.080883899 1.047611333
[81] 0.387570886 0.741914442 -0.855876993 0.096759089 -0.470483508
[86] 1.041830115 0.115112363 -1.529812550 1.097215480 0.034276537
[91] 1.470885293 0.363058595 -2.145694293 0.095997183 0.039158521
[96] 0.840000927 -1.864000625 1.213842297 -0.929755936 0.553857626
> colMin(tmp)
[1] -0.570543084 -0.697764910 2.047992848 0.737072782 0.180694010
[6] 0.039857886 -0.956469778 -1.567691780 -0.246714804 -1.604299748
[11] -0.811600927 -0.419006171 0.666913063 -2.571204697 -1.957005836
[16] -1.031674276 0.294806065 -1.265062412 -1.149824972 -2.450894471
[21] 1.767318050 0.902957140 1.109781594 -0.643651765 -0.526687076
[26] 0.354014265 -0.461831429 -1.908639885 -0.449308003 -1.735972739
[31] 1.241472635 -0.476569730 1.032535868 1.812925909 -0.233766599
[36] -1.547763672 1.045517940 0.419061919 0.408914842 -1.430074720
[41] -1.301300896 0.775914787 -0.244585900 1.580859558 2.576775190
[46] 0.043846918 0.916457251 1.100237447 -0.900172829 0.112525551
[51] 1.373634846 -0.009947252 -0.982980702 0.997084312 -0.692532583
[56] 0.216952524 -1.065301906 0.516320575 -1.048687990 0.791763605
[61] 0.300965131 0.434959466 -1.201306724 -0.539892955 0.020318381
[66] 0.597237529 0.129974651 0.251984374 0.670162197 -0.867892529
[71] -0.167670628 -1.124278648 -0.450226131 0.312167882 -1.031629971
[76] 0.304043700 -0.772078761 0.312672183 1.080883899 1.047611333
[81] 0.387570886 0.741914442 -0.855876993 0.096759089 -0.470483508
[86] 1.041830115 0.115112363 -1.529812550 1.097215480 0.034276537
[91] 1.470885293 0.363058595 -2.145694293 0.095997183 0.039158521
[96] 0.840000927 -1.864000625 1.213842297 -0.929755936 0.553857626
> colMedians(tmp)
[1] -0.570543084 -0.697764910 2.047992848 0.737072782 0.180694010
[6] 0.039857886 -0.956469778 -1.567691780 -0.246714804 -1.604299748
[11] -0.811600927 -0.419006171 0.666913063 -2.571204697 -1.957005836
[16] -1.031674276 0.294806065 -1.265062412 -1.149824972 -2.450894471
[21] 1.767318050 0.902957140 1.109781594 -0.643651765 -0.526687076
[26] 0.354014265 -0.461831429 -1.908639885 -0.449308003 -1.735972739
[31] 1.241472635 -0.476569730 1.032535868 1.812925909 -0.233766599
[36] -1.547763672 1.045517940 0.419061919 0.408914842 -1.430074720
[41] -1.301300896 0.775914787 -0.244585900 1.580859558 2.576775190
[46] 0.043846918 0.916457251 1.100237447 -0.900172829 0.112525551
[51] 1.373634846 -0.009947252 -0.982980702 0.997084312 -0.692532583
[56] 0.216952524 -1.065301906 0.516320575 -1.048687990 0.791763605
[61] 0.300965131 0.434959466 -1.201306724 -0.539892955 0.020318381
[66] 0.597237529 0.129974651 0.251984374 0.670162197 -0.867892529
[71] -0.167670628 -1.124278648 -0.450226131 0.312167882 -1.031629971
[76] 0.304043700 -0.772078761 0.312672183 1.080883899 1.047611333
[81] 0.387570886 0.741914442 -0.855876993 0.096759089 -0.470483508
[86] 1.041830115 0.115112363 -1.529812550 1.097215480 0.034276537
[91] 1.470885293 0.363058595 -2.145694293 0.095997183 0.039158521
[96] 0.840000927 -1.864000625 1.213842297 -0.929755936 0.553857626
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.5705431 -0.6977649 2.047993 0.7370728 0.180694 0.03985789 -0.9564698
[2,] -0.5705431 -0.6977649 2.047993 0.7370728 0.180694 0.03985789 -0.9564698
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.567692 -0.2467148 -1.6043 -0.8116009 -0.4190062 0.6669131 -2.571205
[2,] -1.567692 -0.2467148 -1.6043 -0.8116009 -0.4190062 0.6669131 -2.571205
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.957006 -1.031674 0.2948061 -1.265062 -1.149825 -2.450894 1.767318
[2,] -1.957006 -1.031674 0.2948061 -1.265062 -1.149825 -2.450894 1.767318
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.9029571 1.109782 -0.6436518 -0.5266871 0.3540143 -0.4618314 -1.90864
[2,] 0.9029571 1.109782 -0.6436518 -0.5266871 0.3540143 -0.4618314 -1.90864
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.449308 -1.735973 1.241473 -0.4765697 1.032536 1.812926 -0.2337666
[2,] -0.449308 -1.735973 1.241473 -0.4765697 1.032536 1.812926 -0.2337666
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.547764 1.045518 0.4190619 0.4089148 -1.430075 -1.301301 0.7759148
[2,] -1.547764 1.045518 0.4190619 0.4089148 -1.430075 -1.301301 0.7759148
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.2445859 1.58086 2.576775 0.04384692 0.9164573 1.100237 -0.9001728
[2,] -0.2445859 1.58086 2.576775 0.04384692 0.9164573 1.100237 -0.9001728
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.1125256 1.373635 -0.009947252 -0.9829807 0.9970843 -0.6925326 0.2169525
[2,] 0.1125256 1.373635 -0.009947252 -0.9829807 0.9970843 -0.6925326 0.2169525
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -1.065302 0.5163206 -1.048688 0.7917636 0.3009651 0.4349595 -1.201307
[2,] -1.065302 0.5163206 -1.048688 0.7917636 0.3009651 0.4349595 -1.201307
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.539893 0.02031838 0.5972375 0.1299747 0.2519844 0.6701622 -0.8678925
[2,] -0.539893 0.02031838 0.5972375 0.1299747 0.2519844 0.6701622 -0.8678925
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.1676706 -1.124279 -0.4502261 0.3121679 -1.03163 0.3040437 -0.7720788
[2,] -0.1676706 -1.124279 -0.4502261 0.3121679 -1.03163 0.3040437 -0.7720788
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.3126722 1.080884 1.047611 0.3875709 0.7419144 -0.855877 0.09675909
[2,] 0.3126722 1.080884 1.047611 0.3875709 0.7419144 -0.855877 0.09675909
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.4704835 1.04183 0.1151124 -1.529813 1.097215 0.03427654 1.470885
[2,] -0.4704835 1.04183 0.1151124 -1.529813 1.097215 0.03427654 1.470885
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.3630586 -2.145694 0.09599718 0.03915852 0.8400009 -1.864001 1.213842
[2,] 0.3630586 -2.145694 0.09599718 0.03915852 0.8400009 -1.864001 1.213842
[,99] [,100]
[1,] -0.9297559 0.5538576
[2,] -0.9297559 0.5538576
>
>
> Max(tmp2)
[1] 2.46358
> Min(tmp2)
[1] -2.637171
> mean(tmp2)
[1] -0.008858803
> Sum(tmp2)
[1] -0.8858803
> Var(tmp2)
[1] 1.057085
>
> rowMeans(tmp2)
[1] -0.98716373 -0.20635007 -0.41546194 -0.24642900 -0.89497612 -0.18597905
[7] -1.50166787 2.35497709 -0.15581396 1.44389769 0.99467165 0.48754298
[13] -0.75258882 -1.58444677 -1.54336751 0.34481776 1.48620969 -2.63717082
[19] -1.11117604 0.61206132 -0.31938094 -0.06504965 -1.62664414 -1.35264966
[25] -0.17714687 -1.55357378 0.90164244 0.80190601 0.20631124 -0.25478740
[31] -1.92114419 -1.48440141 -0.60498667 0.46961826 1.06179674 0.76157705
[37] -0.37732846 -0.52149591 2.01609483 -0.59324549 -0.67924397 1.55718246
[43] 1.12849231 1.21406831 1.06850073 -0.29661966 0.56840792 0.98018404
[49] 1.06916629 0.97431025 0.36124605 0.25692954 -1.03901363 -0.66485395
[55] -0.78287094 -0.09132060 -0.16264397 0.60022904 0.96666759 -0.59218953
[61] 0.98969391 -0.07690465 -0.15407423 -0.91272562 0.11322220 2.46358001
[67] -1.38317713 -1.21767201 -0.46348832 -0.81503499 -0.77868394 -0.59698030
[73] 0.55636413 2.10123982 -0.04081569 -0.68250804 0.14235884 1.13218082
[79] 0.26046448 -1.02266570 1.18611568 0.92266784 1.00183107 -1.68856006
[85] -0.48425511 -0.41524420 -1.30977823 1.51968423 -0.21461554 1.59168258
[91] 0.41193826 0.28870030 -0.54544083 -1.37541984 0.79814621 -0.66040249
[97] 0.59662766 -0.39778669 1.12931190 -0.16078340
> rowSums(tmp2)
[1] -0.98716373 -0.20635007 -0.41546194 -0.24642900 -0.89497612 -0.18597905
[7] -1.50166787 2.35497709 -0.15581396 1.44389769 0.99467165 0.48754298
[13] -0.75258882 -1.58444677 -1.54336751 0.34481776 1.48620969 -2.63717082
[19] -1.11117604 0.61206132 -0.31938094 -0.06504965 -1.62664414 -1.35264966
[25] -0.17714687 -1.55357378 0.90164244 0.80190601 0.20631124 -0.25478740
[31] -1.92114419 -1.48440141 -0.60498667 0.46961826 1.06179674 0.76157705
[37] -0.37732846 -0.52149591 2.01609483 -0.59324549 -0.67924397 1.55718246
[43] 1.12849231 1.21406831 1.06850073 -0.29661966 0.56840792 0.98018404
[49] 1.06916629 0.97431025 0.36124605 0.25692954 -1.03901363 -0.66485395
[55] -0.78287094 -0.09132060 -0.16264397 0.60022904 0.96666759 -0.59218953
[61] 0.98969391 -0.07690465 -0.15407423 -0.91272562 0.11322220 2.46358001
[67] -1.38317713 -1.21767201 -0.46348832 -0.81503499 -0.77868394 -0.59698030
[73] 0.55636413 2.10123982 -0.04081569 -0.68250804 0.14235884 1.13218082
[79] 0.26046448 -1.02266570 1.18611568 0.92266784 1.00183107 -1.68856006
[85] -0.48425511 -0.41524420 -1.30977823 1.51968423 -0.21461554 1.59168258
[91] 0.41193826 0.28870030 -0.54544083 -1.37541984 0.79814621 -0.66040249
[97] 0.59662766 -0.39778669 1.12931190 -0.16078340
> 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] -0.98716373 -0.20635007 -0.41546194 -0.24642900 -0.89497612 -0.18597905
[7] -1.50166787 2.35497709 -0.15581396 1.44389769 0.99467165 0.48754298
[13] -0.75258882 -1.58444677 -1.54336751 0.34481776 1.48620969 -2.63717082
[19] -1.11117604 0.61206132 -0.31938094 -0.06504965 -1.62664414 -1.35264966
[25] -0.17714687 -1.55357378 0.90164244 0.80190601 0.20631124 -0.25478740
[31] -1.92114419 -1.48440141 -0.60498667 0.46961826 1.06179674 0.76157705
[37] -0.37732846 -0.52149591 2.01609483 -0.59324549 -0.67924397 1.55718246
[43] 1.12849231 1.21406831 1.06850073 -0.29661966 0.56840792 0.98018404
[49] 1.06916629 0.97431025 0.36124605 0.25692954 -1.03901363 -0.66485395
[55] -0.78287094 -0.09132060 -0.16264397 0.60022904 0.96666759 -0.59218953
[61] 0.98969391 -0.07690465 -0.15407423 -0.91272562 0.11322220 2.46358001
[67] -1.38317713 -1.21767201 -0.46348832 -0.81503499 -0.77868394 -0.59698030
[73] 0.55636413 2.10123982 -0.04081569 -0.68250804 0.14235884 1.13218082
[79] 0.26046448 -1.02266570 1.18611568 0.92266784 1.00183107 -1.68856006
[85] -0.48425511 -0.41524420 -1.30977823 1.51968423 -0.21461554 1.59168258
[91] 0.41193826 0.28870030 -0.54544083 -1.37541984 0.79814621 -0.66040249
[97] 0.59662766 -0.39778669 1.12931190 -0.16078340
> rowMin(tmp2)
[1] -0.98716373 -0.20635007 -0.41546194 -0.24642900 -0.89497612 -0.18597905
[7] -1.50166787 2.35497709 -0.15581396 1.44389769 0.99467165 0.48754298
[13] -0.75258882 -1.58444677 -1.54336751 0.34481776 1.48620969 -2.63717082
[19] -1.11117604 0.61206132 -0.31938094 -0.06504965 -1.62664414 -1.35264966
[25] -0.17714687 -1.55357378 0.90164244 0.80190601 0.20631124 -0.25478740
[31] -1.92114419 -1.48440141 -0.60498667 0.46961826 1.06179674 0.76157705
[37] -0.37732846 -0.52149591 2.01609483 -0.59324549 -0.67924397 1.55718246
[43] 1.12849231 1.21406831 1.06850073 -0.29661966 0.56840792 0.98018404
[49] 1.06916629 0.97431025 0.36124605 0.25692954 -1.03901363 -0.66485395
[55] -0.78287094 -0.09132060 -0.16264397 0.60022904 0.96666759 -0.59218953
[61] 0.98969391 -0.07690465 -0.15407423 -0.91272562 0.11322220 2.46358001
[67] -1.38317713 -1.21767201 -0.46348832 -0.81503499 -0.77868394 -0.59698030
[73] 0.55636413 2.10123982 -0.04081569 -0.68250804 0.14235884 1.13218082
[79] 0.26046448 -1.02266570 1.18611568 0.92266784 1.00183107 -1.68856006
[85] -0.48425511 -0.41524420 -1.30977823 1.51968423 -0.21461554 1.59168258
[91] 0.41193826 0.28870030 -0.54544083 -1.37541984 0.79814621 -0.66040249
[97] 0.59662766 -0.39778669 1.12931190 -0.16078340
>
> colMeans(tmp2)
[1] -0.008858803
> colSums(tmp2)
[1] -0.8858803
> colVars(tmp2)
[1] 1.057085
> colSd(tmp2)
[1] 1.028146
> colMax(tmp2)
[1] 2.46358
> colMin(tmp2)
[1] -2.637171
> colMedians(tmp2)
[1] -0.1582987
> colRanges(tmp2)
[,1]
[1,] -2.637171
[2,] 2.463580
>
> 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] 0.04371892 -3.51411460 -1.12302199 3.80291888 -2.83176895 3.37296838
[7] 0.12873854 5.31555591 0.68938817 3.99748757
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.45584004
[2,] -1.44731475
[3,] 0.06768714
[4,] 1.19127804
[5,] 2.25598570
>
> rowApply(tmp,sum)
[1] 1.1065767 2.0695002 -1.3779270 -2.1445398 -1.2205824 -0.4893368
[7] 2.4130956 2.8088630 5.3920288 1.3241925
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 6 1 7 1 5 10 10 10 10 1
[2,] 4 5 1 10 1 4 2 5 3 5
[3,] 7 6 5 4 2 2 1 7 5 8
[4,] 9 3 6 9 9 6 3 2 9 7
[5,] 5 4 4 2 4 8 5 1 2 3
[6,] 3 10 9 3 6 5 6 3 4 9
[7,] 10 2 2 7 10 1 9 9 6 4
[8,] 2 7 10 5 8 9 7 8 8 2
[9,] 8 8 3 6 7 3 4 4 1 10
[10,] 1 9 8 8 3 7 8 6 7 6
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.862348138 -0.352121989 1.697868986 -1.382305141 3.532457558
[6] 2.525667268 0.724700245 1.409048696 0.171078617 0.842491074
[11] -0.002031903 -2.418712142 1.099942158 -2.369379372 2.942403306
[16] -0.495108733 -1.572933040 2.228599929 -1.189084099 -5.584915530
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5121566
[2,] -1.0988353
[3,] -0.5828824
[4,] 0.4716919
[5,] 0.8598343
>
> rowApply(tmp,sum)
[1] -4.722591 2.637042 7.521902 2.092921 -7.583957
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 17 3 1 13 6
[2,] 5 17 20 6 1
[3,] 20 7 17 10 2
[4,] 2 20 3 5 14
[5,] 9 16 14 18 20
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.8598343 -0.6406133 1.8761356 -1.71641482 -0.3822770 0.9057281
[2,] -0.5828824 0.6411495 -0.2147605 1.79128074 0.4828100 0.4386845
[3,] -1.5121566 2.1591387 1.4758605 -0.89069658 0.8309848 0.0694816
[4,] 0.4716919 -0.3220543 0.2839546 -0.61044971 1.1456831 0.3940295
[5,] -1.0988353 -2.1897426 -1.7233213 0.04397524 1.4552566 0.7177436
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.49513724 -0.59864011 -0.2360502 -0.4073023 -1.30193989 -1.3429679
[2,] -0.52057147 0.04539992 0.3299622 1.3894404 -0.09901632 -1.3519672
[3,] 0.82350044 0.45226475 0.5222442 -0.1757332 0.59699014 0.9433690
[4,] -0.14477559 0.56208620 0.7725687 0.1548561 0.63371392 0.5941196
[5,] 0.07140962 0.94793794 -1.2176463 -0.1187698 0.16822024 -1.2612657
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.2212260 -0.0597181 -0.4635180 0.2035531 -0.1537269 0.2238089
[2,] 0.3587251 -0.5696773 0.2426741 1.1941190 0.2513982 -0.2039683
[3,] 1.9248608 -0.6348240 1.0372925 -1.3269612 0.1176981 1.8177923
[4,] -1.9812993 -0.8921041 1.1576333 0.3180852 -0.7793449 1.4971013
[5,] -0.4235706 -0.2130559 0.9683213 -0.8839049 -1.0089575 -1.1061343
[,19] [,20]
[1,] -0.204196427 -3.0006487
[2,] -0.318862237 -0.6668961
[3,] -0.386187782 -0.3230168
[4,] -0.272762403 -0.8898119
[5,] -0.007075251 -0.7045420
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 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-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 679 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 588 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 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
row1 -0.5009465 -0.06162662 0.1682691 -0.3128538 0.07337178 -1.219785
col7 col8 col9 col10 col11 col12 col13
row1 0.06647932 -1.580407 -0.1609404 -1.006945 -1.005598 -0.4132964 1.221922
col14 col15 col16 col17 col18 col19 col20
row1 1.1632 -1.766938 -0.970222 9.371156e-05 1.580287 -0.2970555 -0.1985179
> tmp[,"col10"]
col10
row1 -1.0069451
row2 0.7933408
row3 0.7996242
row4 0.9361613
row5 -0.3087235
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.5009465 -0.06162662 0.1682691 -0.3128538 0.07337178 -1.2197850
row5 -1.6101506 -0.06184463 1.8854874 0.9597863 0.19804848 -0.5917559
col7 col8 col9 col10 col11 col12
row1 0.06647932 -1.58040674 -0.1609404 -1.0069451 -1.0055981 -0.4132964
row5 -0.39007812 -0.02519524 -0.5687984 -0.3087235 -0.7343503 0.8507062
col13 col14 col15 col16 col17 col18
row1 1.2219217 1.1632000 -1.7669381 -0.970222 9.371156e-05 1.5802873
row5 0.1924382 -0.9149388 -0.1937464 -2.051217 -8.217951e-01 -0.5695945
col19 col20
row1 -0.29705549 -0.19851788
row5 0.06799963 -0.09882209
> tmp[,c("col6","col20")]
col6 col20
row1 -1.21978498 -0.198517884
row2 -0.03087416 -1.733328958
row3 -0.20529676 0.312075055
row4 0.13527903 -0.002001225
row5 -0.59175592 -0.098822086
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.2197850 -0.19851788
row5 -0.5917559 -0.09882209
>
>
>
>
> 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 49.2774 49.066 51.1591 49.33634 50.31307 105.4908 50.75615 50.72523
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.48602 50.3668 50.10763 48.15512 50.12267 50.35153 50.60167 47.79668
col17 col18 col19 col20
row1 50.87033 50.67171 50.72089 103.6037
> tmp[,"col10"]
col10
row1 50.36680
row2 30.39967
row3 30.06466
row4 28.51288
row5 49.79470
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.27740 49.06600 51.15910 49.33634 50.31307 105.4908 50.75615 50.72523
row5 50.76862 51.18114 49.77165 50.09283 48.86642 105.1921 50.81111 49.33602
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.48602 50.3668 50.10763 48.15512 50.12267 50.35153 50.60167 47.79668
row5 51.03530 49.7947 49.92825 50.18134 48.48977 48.68597 50.06444 50.89903
col17 col18 col19 col20
row1 50.87033 50.67171 50.72089 103.6037
row5 50.84426 50.85322 49.25011 106.2499
> tmp[,c("col6","col20")]
col6 col20
row1 105.49081 103.60370
row2 75.35157 77.14583
row3 74.87182 73.72580
row4 75.43197 74.77335
row5 105.19212 106.24989
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.4908 103.6037
row5 105.1921 106.2499
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.4908 103.6037
row5 105.1921 106.2499
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.2344077
[2,] -0.1047767
[3,] -0.5210945
[4,] 0.3614631
[5,] -0.7766923
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.2976284 1.8291191
[2,] 0.2083963 0.4536249
[3,] 2.2638750 -1.2796793
[4,] -0.8014480 0.8426548
[5,] -0.7605641 -0.2688751
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.8650127 0.7966175
[2,] -1.3984976 1.7326814
[3,] 0.1384276 -1.2059833
[4,] -1.4448800 1.2307045
[5,] -1.1505530 -0.1934109
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.8650127
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.8650127
[2,] -1.3984976
>
>
>
> 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 -0.4966845 -0.3294354 -1.250707 0.9134441 0.3949310 1.021416 -0.9468323
row1 -0.5009578 1.1860201 2.536280 -0.4513368 0.2495861 -1.110513 0.7397280
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -1.2907094 0.6668029 -1.4112851 1.714120 -0.2925681 1.258132 -0.3266542
row1 0.9625585 0.6267581 -0.6908328 -0.231494 -2.5816774 1.280396 -0.2876458
[,15] [,16] [,17] [,18] [,19] [,20]
row3 1.1115767 1.080927 2.4958575 -0.52193415 1.674607 -0.08307978
row1 0.8498169 1.130703 -0.8385228 0.03347825 4.190021 0.67959135
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.01290847 1.456348 -0.573354 -0.6772938 0.7571471 -0.2736225 -0.8422254
[,8] [,9] [,10]
row2 -0.2659923 -1.197424 -0.1165496
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.9533804 0.1705866 -0.8883284 0.3105475 -1.470219 -1.088581 -0.234081
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.86844 -0.175082 -1.060031 -0.1569092 -0.9814598 1.30775 -0.8074657
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.2048239 -0.4343003 0.5806401 1.598204 -1.933774 -1.586284
>
>
> 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: 0x000001a52ba07230>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests\\BM286853d95073"
[2] "F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests\\BM286840b53ad9"
[3] "F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests\\BM286871581338"
[4] "F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests\\BM2868197e102d"
[5] "F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests\\BM28682b0357cf"
[6] "F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests\\BM2868691c701d"
[7] "F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests\\BM2868261857e8"
[8] "F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests\\BM286886833fc"
[9] "F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests\\BM286858c81a8e"
[10] "F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests\\BM28682ab41748"
[11] "F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests\\BM28687997145a"
[12] "F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests\\BM286868517981"
[13] "F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests\\BM28687e0517e7"
[14] "F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests\\BM28685255723b"
[15] "F:/biocbuild/bbs-3.17-bioc-rtools43/meat/BufferedMatrix.Rcheck/tests\\BM28686c6e2a85"
>
>
> ### 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: 0x000001a52ad59230>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x000001a52ad59230>
Warning message:
In dir.create(new.directory) :
'F:\biocbuild\bbs-3.17-bioc-rtools43\meat\BufferedMatrix.Rcheck\tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x000001a52ad59230>
> rowMedians(tmp)
[1] -0.079045394 0.252300589 0.204029945 -0.512269089 -0.057382975
[6] -0.833957179 0.362549268 -0.034158143 0.268605068 0.337520969
[11] -0.582753257 -0.170087977 -0.385734965 0.104222665 0.114930450
[16] -0.143958968 -0.114446243 -0.360756083 -0.177855322 -0.091841103
[21] 0.525059963 0.317225539 -0.418524618 -0.125883877 -0.273243436
[26] -0.143344297 0.163853383 0.054547574 -0.245088761 -0.716590941
[31] -0.518144873 -0.250814992 -0.852062860 -0.187044019 -0.109856254
[36] 0.150552819 0.171731389 0.386166844 -0.936372366 0.032455888
[41] 0.096914454 -0.277467108 -0.185103438 -0.162728679 0.206945250
[46] -0.824634731 -0.108733726 -0.369059890 -0.149350005 0.410692644
[51] 0.464736611 0.275046229 -0.358033152 -0.002768920 0.254430149
[56] -0.263312122 -0.124664866 0.728462368 0.125218711 0.005656734
[61] -0.122584285 0.002241557 0.016812582 -0.017993094 -0.371962489
[66] -0.345496652 0.112858182 0.117054064 -0.186888335 0.226115639
[71] -0.177594783 0.352855158 -0.190298850 0.446781552 -0.516404745
[76] 0.237063113 0.344645439 0.556933252 0.145085502 -0.063677733
[81] 0.176000979 -0.166865533 0.337593986 -0.236122840 0.122656692
[86] 0.331255748 0.053949510 0.472922859 0.001236276 -0.523957310
[91] 0.212679041 0.528846643 0.056343498 0.035183031 -0.277901676
[96] 0.388613269 0.678186396 -0.044451898 0.004360032 0.071254746
[101] 0.161996914 -0.387022207 -0.337343577 0.373053623 -0.394748985
[106] -0.188806807 0.060657700 0.168953468 -0.305320988 -0.044708762
[111] 0.314371071 0.156579451 0.159660323 -0.531546636 -0.045742023
[116] -0.610107791 0.115058125 -0.332765267 -0.344175618 0.313797011
[121] -0.194064413 -0.272828091 -0.137660130 0.302005545 -0.189595761
[126] 0.070568383 0.253477246 0.257344707 -0.228530898 0.273349220
[131] 0.106218010 -0.622252144 0.616123648 0.137192106 0.164273152
[136] 0.277537731 -0.209348684 -0.421093785 -0.016558092 0.730088433
[141] -0.042784139 0.552060936 -0.658763891 0.255432790 0.394861062
[146] 0.045780852 0.320570169 0.183199546 -0.527680894 0.200936299
[151] 0.421974537 -0.622884038 0.278008233 0.150304484 -0.207732505
[156] 0.142793891 -0.515544924 0.057513989 0.031851444 -0.625620011
[161] -0.304498394 0.342187891 0.192137542 -0.060028985 -0.221986683
[166] -0.242699795 -0.004168864 -0.424534135 -0.160886214 0.086282252
[171] 0.189996921 0.176489988 -0.711067650 0.131057847 -0.442970214
[176] -0.069840523 -0.329025481 -0.230916600 -0.101551787 0.039956139
[181] -0.237725739 -0.300154236 0.154237170 0.184923205 -0.222383521
[186] 0.205054774 0.270796940 0.266191046 -0.203940491 -0.056258168
[191] 0.180587543 0.074120679 0.306185378 0.232219820 -0.396575700
[196] -0.179404877 0.066666291 0.058383472 -0.484832525 0.140388927
[201] 0.256683141 0.305268079 0.179928262 0.468497188 -0.349926791
[206] 0.140866274 0.037273973 0.125066915 0.159732371 -0.123786704
[211] -0.067013829 0.065328744 0.235288170 0.245051027 0.069382368
[216] -0.061403826 0.291507322 -0.285635817 0.825623558 -0.395672094
[221] -0.408560165 -0.303693873 -0.303831250 -0.458118939 -0.022335092
[226] -0.172799839 0.546912660 0.224506275 0.051160328 -0.384666469
>
> proc.time()
user system elapsed
2.96 16.84 69.28
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2022-12-25 r83502 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
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: 0x000001a8d0d40d00>
> .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: 0x000001a8d0d40d00>
> .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: 0x000001a8d0d40d00>
> .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: 0x000001a8d0d40d00>
> 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: 0x000001a8d2427310>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001a8d2427310>
> .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: 0x000001a8d2427310>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001a8d2427310>
> .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: 0x000001a8d2427310>
> 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: 0x000001a8d2426b30>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001a8d2426b30>
> .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: 0x000001a8d2426b30>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000001a8d2426b30>
> .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: 0x000001a8d2426b30>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x000001a8d2426b30>
> .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: 0x000001a8d2426b30>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x000001a8d2426b30>
> .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: 0x000001a8d2426b30>
> 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: 0x000001a8d2426c80>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x000001a8d2426c80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001a8d2426c80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001a8d2426c80>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile45f83da270d0" "BufferedMatrixFile45f8558d3105"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile45f83da270d0" "BufferedMatrixFile45f8558d3105"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001a8d2426e40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001a8d2426e40>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000001a8d2426e40>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000001a8d2426e40>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x000001a8d2426e40>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x000001a8d2426e40>
> .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: 0x000001a8d2427070>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001a8d2427070>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000001a8d2427070>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x000001a8d2427070>
> 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: 0x000001a8d24275b0>
> .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: 0x000001a8d24275b0>
> rm(P)
>
> proc.time()
user system elapsed
0.29 0.17 0.67
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2022-12-25 r83502 ucrt) -- "Unsuffered Consequences"
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Platform: x86_64-w64-mingw32/x64 (64-bit)
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You are welcome to redistribute it under certain conditions.
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Type 'contributors()' for more information and
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.23 0.01 0.25