Ben Bolstad
| Snapshot Date: 2021-05-05 14:51:38 -0400 (Wed, 05 May 2021) |
| URL: https://git.bioconductor.org/packages/BufferedMatrix |
| Branch: RELEASE_3_12 |
| Last Commit: eae3841 |
| Last Changed Date: 2020-10-27 10:30:14 -0400 (Tue, 27 Oct 2020) |
| Back to Multiple platform build/check report for BioC 3.12 |
|
This page was generated on 2021-05-06 12:34:28 -0400 (Thu, 06 May 2021).
|
To the developers/maintainers of the BufferedMatrix package: Please make sure to use the following settings in order to reproduce any error or warning you see on this page. |
| Package 215/1974 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.54.0 (landing page) Ben Bolstad
| malbec1 | Linux (Ubuntu 18.04.5 LTS) / x86_64 | OK | OK | OK | | ||||||||
| tokay1 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 10.14.6 Mojave / x86_64 | OK | OK | OK | OK | | ||||||||
| Package: BufferedMatrix |
| Version: 1.54.0 |
| Command: /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Versions/Current/Resources/library --no-vignettes --timings BufferedMatrix_1.54.0.tar.gz |
| StartedAt: 2021-05-05 23:51:37 -0400 (Wed, 05 May 2021) |
| EndedAt: 2021-05-05 23:52:27 -0400 (Wed, 05 May 2021) |
| EllapsedTime: 50.1 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Versions/Current/Resources/library --no-vignettes --timings BufferedMatrix_1.54.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck’ * using R version 4.0.5 (2021-03-31) * using platform: x86_64-apple-darwin17.0 (64-bit) * using session charset: UTF-8 * using option ‘--no-vignettes’ * checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK * this is package ‘BufferedMatrix’ version ‘1.54.0’ * 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 for sufficient/correct file permissions ... OK * checking whether package ‘BufferedMatrix’ can be installed ... OK * 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 is not available * 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 ‘/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/00check.log’ for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.0/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
clang -mmacosx-version-min=10.13 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/usr/local/include -fPIC -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -mmacosx-version-min=10.13 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/usr/local/include -fPIC -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -mmacosx-version-min=10.13 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/usr/local/include -fPIC -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -mmacosx-version-min=10.13 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/usr/local/include -fPIC -Wall -g -O2 -c init_package.c -o init_package.o
clang -mmacosx-version-min=10.13 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -single_module -multiply_defined suppress -L/Library/Frameworks/R.framework/Resources/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation
installing to /Library/Frameworks/R.framework/Versions/4.0/Resources/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** 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
** checking absolute paths in shared objects and dynamic libraries
** 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 4.0.5 (2021-03-31) -- "Shake and Throw"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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
0.461 0.125 0.604
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.0.5 (2021-03-31) -- "Shake and Throw"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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] "/Users/biocbuild/bbs-3.12-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) limit (Mb) max used (Mb)
Ncells 442561 23.7 955595 51.1 NA 617728 33.0
Vcells 799010 6.1 8388608 64.0 65536 1931409 14.8
>
>
>
>
> ##
> ## 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 May 5 23:52:01 2021"
> 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 May 5 23:52:01 2021"
>
>
> 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: 0x7f851d766320>
>
>
>
> 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 May 5 23:52:04 2021"
> 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 May 5 23:52:06 2021"
>
> ColMode(tmp2)
<pointer: 0x7f851d766320>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 101.0482172 -1.2014778 0.75775710 0.4623214
[2,] 0.1792142 0.3007322 1.58700108 0.4056275
[3,] 0.5074770 1.2219443 -0.09038108 -1.0278772
[4,] -0.7560583 0.5131962 1.67824908 -0.3991714
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 101.0482172 1.2014778 0.75775710 0.4623214
[2,] 0.1792142 0.3007322 1.58700108 0.4056275
[3,] 0.5074770 1.2219443 0.09038108 1.0278772
[4,] 0.7560583 0.5131962 1.67824908 0.3991714
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0522742 1.0961194 0.8704924 0.6799422
[2,] 0.4233369 0.5483906 1.2597623 0.6368889
[3,] 0.7123742 1.1054159 0.3006345 1.0138428
[4,] 0.8695161 0.7163771 1.2954725 0.6318001
>
> 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: /Users/biocbuild/bbs-3.12-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,] 226.57096 37.16267 34.46268 32.26174
[2,] 29.41258 30.78464 39.18462 31.77452
[3,] 32.63122 37.27610 28.09673 36.16631
[4,] 34.45122 32.67697 39.63297 31.71717
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x7f852d506360>
> exp(tmp5)
<pointer: 0x7f852d506360>
> log(tmp5,2)
<pointer: 0x7f852d506360>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.5778
> Min(tmp5)
[1] 54.18713
> mean(tmp5)
[1] 72.76107
> Sum(tmp5)
[1] 14552.21
> Var(tmp5)
[1] 871.1045
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.74140 69.41205 67.99455 68.06274 70.13999 72.21601 72.76051 70.96846
[9] 73.90416 70.41083
> rowSums(tmp5)
[1] 1834.828 1388.241 1359.891 1361.255 1402.800 1444.320 1455.210 1419.369
[9] 1478.083 1408.217
> rowVars(tmp5)
[1] 8043.61811 90.81345 39.88571 73.84360 36.79405 111.67179
[7] 42.04257 56.34190 84.88451 87.48883
> rowSd(tmp5)
[1] 89.686220 9.529609 6.315514 8.593230 6.065810 10.567487 6.484025
[8] 7.506124 9.213279 9.353547
> rowMax(tmp5)
[1] 471.57777 86.58175 78.09607 86.72315 82.29112 92.69312 85.31610
[8] 86.40751 93.14704 89.01543
> rowMin(tmp5)
[1] 57.92562 55.33430 58.47965 54.83227 61.92306 56.68384 63.17767 57.69650
[9] 54.31973 54.18713
>
> colMeans(tmp5)
[1] 108.77722 70.37248 71.60390 73.70620 70.22041 67.58196 62.91411
[8] 74.79957 69.20169 76.91000 67.23298 71.03824 72.69378 70.94290
[15] 71.51140 70.64164 70.84815 69.95614 73.61977 70.64884
> colSums(tmp5)
[1] 1087.7722 703.7248 716.0390 737.0620 702.2041 675.8196 629.1411
[8] 747.9957 692.0169 769.1000 672.3298 710.3824 726.9378 709.4290
[15] 715.1140 706.4164 708.4815 699.5614 736.1977 706.4884
> colVars(tmp5)
[1] 16271.00656 53.11488 80.18677 41.96189 49.21058 65.70505
[7] 37.56583 94.69621 117.56688 71.32464 37.16783 40.74710
[13] 29.77380 140.00966 31.41468 71.25409 88.35659 113.64028
[19] 55.77935 71.71813
> colSd(tmp5)
[1] 127.557856 7.287996 8.954706 6.477800 7.015025 8.105865
[7] 6.129097 9.731198 10.842826 8.445392 6.096543 6.383346
[13] 5.456537 11.832568 5.604880 8.441214 9.399818 10.660219
[19] 7.468557 8.468656
> colMax(tmp5)
[1] 471.57777 85.70534 82.49084 83.10490 83.87485 80.85144 72.94647
[8] 92.69312 86.72315 91.54782 76.41624 81.53959 78.86465 93.14704
[15] 80.76686 84.04992 89.01543 86.40751 85.31610 87.62520
> colMin(tmp5)
[1] 61.21844 64.07419 56.68384 66.01514 60.73139 57.73677 54.18713 55.84798
[9] 54.31973 65.34346 59.12656 62.29126 62.33724 55.33430 63.24719 60.54133
[17] 58.52892 54.83227 62.16301 59.83156
>
>
> ### 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] 91.74140 69.41205 67.99455 NA 70.13999 72.21601 72.76051 70.96846
[9] 73.90416 70.41083
> rowSums(tmp5)
[1] 1834.828 1388.241 1359.891 NA 1402.800 1444.320 1455.210 1419.369
[9] 1478.083 1408.217
> rowVars(tmp5)
[1] 8043.61811 90.81345 39.88571 74.91791 36.79405 111.67179
[7] 42.04257 56.34190 84.88451 87.48883
> rowSd(tmp5)
[1] 89.686220 9.529609 6.315514 8.655513 6.065810 10.567487 6.484025
[8] 7.506124 9.213279 9.353547
> rowMax(tmp5)
[1] 471.57777 86.58175 78.09607 NA 82.29112 92.69312 85.31610
[8] 86.40751 93.14704 89.01543
> rowMin(tmp5)
[1] 57.92562 55.33430 58.47965 NA 61.92306 56.68384 63.17767 57.69650
[9] 54.31973 54.18713
>
> colMeans(tmp5)
[1] 108.77722 70.37248 71.60390 73.70620 70.22041 67.58196 62.91411
[8] 74.79957 69.20169 76.91000 67.23298 71.03824 72.69378 70.94290
[15] 71.51140 70.64164 70.84815 69.95614 NA 70.64884
> colSums(tmp5)
[1] 1087.7722 703.7248 716.0390 737.0620 702.2041 675.8196 629.1411
[8] 747.9957 692.0169 769.1000 672.3298 710.3824 726.9378 709.4290
[15] 715.1140 706.4164 708.4815 699.5614 NA 706.4884
> colVars(tmp5)
[1] 16271.00656 53.11488 80.18677 41.96189 49.21058 65.70505
[7] 37.56583 94.69621 117.56688 71.32464 37.16783 40.74710
[13] 29.77380 140.00966 31.41468 71.25409 88.35659 113.64028
[19] NA 71.71813
> colSd(tmp5)
[1] 127.557856 7.287996 8.954706 6.477800 7.015025 8.105865
[7] 6.129097 9.731198 10.842826 8.445392 6.096543 6.383346
[13] 5.456537 11.832568 5.604880 8.441214 9.399818 10.660219
[19] NA 8.468656
> colMax(tmp5)
[1] 471.57777 85.70534 82.49084 83.10490 83.87485 80.85144 72.94647
[8] 92.69312 86.72315 91.54782 76.41624 81.53959 78.86465 93.14704
[15] 80.76686 84.04992 89.01543 86.40751 NA 87.62520
> colMin(tmp5)
[1] 61.21844 64.07419 56.68384 66.01514 60.73139 57.73677 54.18713 55.84798
[9] 54.31973 65.34346 59.12656 62.29126 62.33724 55.33430 63.24719 60.54133
[17] 58.52892 54.83227 NA 59.83156
>
> Max(tmp5,na.rm=TRUE)
[1] 471.5778
> Min(tmp5,na.rm=TRUE)
[1] 54.18713
> mean(tmp5,na.rm=TRUE)
[1] 72.74852
> Sum(tmp5,na.rm=TRUE)
[1] 14476.96
> Var(tmp5,na.rm=TRUE)
[1] 875.4723
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.74140 69.41205 67.99455 67.68401 70.13999 72.21601 72.76051 70.96846
[9] 73.90416 70.41083
> rowSums(tmp5,na.rm=TRUE)
[1] 1834.828 1388.241 1359.891 1285.996 1402.800 1444.320 1455.210 1419.369
[9] 1478.083 1408.217
> rowVars(tmp5,na.rm=TRUE)
[1] 8043.61811 90.81345 39.88571 74.91791 36.79405 111.67179
[7] 42.04257 56.34190 84.88451 87.48883
> rowSd(tmp5,na.rm=TRUE)
[1] 89.686220 9.529609 6.315514 8.655513 6.065810 10.567487 6.484025
[8] 7.506124 9.213279 9.353547
> rowMax(tmp5,na.rm=TRUE)
[1] 471.57777 86.58175 78.09607 86.72315 82.29112 92.69312 85.31610
[8] 86.40751 93.14704 89.01543
> rowMin(tmp5,na.rm=TRUE)
[1] 57.92562 55.33430 58.47965 54.83227 61.92306 56.68384 63.17767 57.69650
[9] 54.31973 54.18713
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.77722 70.37248 71.60390 73.70620 70.22041 67.58196 62.91411
[8] 74.79957 69.20169 76.91000 67.23298 71.03824 72.69378 70.94290
[15] 71.51140 70.64164 70.84815 69.95614 73.43768 70.64884
> colSums(tmp5,na.rm=TRUE)
[1] 1087.7722 703.7248 716.0390 737.0620 702.2041 675.8196 629.1411
[8] 747.9957 692.0169 769.1000 672.3298 710.3824 726.9378 709.4290
[15] 715.1140 706.4164 708.4815 699.5614 660.9391 706.4884
> colVars(tmp5,na.rm=TRUE)
[1] 16271.00656 53.11488 80.18677 41.96189 49.21058 65.70505
[7] 37.56583 94.69621 117.56688 71.32464 37.16783 40.74710
[13] 29.77380 140.00966 31.41468 71.25409 88.35659 113.64028
[19] 62.37874 71.71813
> colSd(tmp5,na.rm=TRUE)
[1] 127.557856 7.287996 8.954706 6.477800 7.015025 8.105865
[7] 6.129097 9.731198 10.842826 8.445392 6.096543 6.383346
[13] 5.456537 11.832568 5.604880 8.441214 9.399818 10.660219
[19] 7.898021 8.468656
> colMax(tmp5,na.rm=TRUE)
[1] 471.57777 85.70534 82.49084 83.10490 83.87485 80.85144 72.94647
[8] 92.69312 86.72315 91.54782 76.41624 81.53959 78.86465 93.14704
[15] 80.76686 84.04992 89.01543 86.40751 85.31610 87.62520
> colMin(tmp5,na.rm=TRUE)
[1] 61.21844 64.07419 56.68384 66.01514 60.73139 57.73677 54.18713 55.84798
[9] 54.31973 65.34346 59.12656 62.29126 62.33724 55.33430 63.24719 60.54133
[17] 58.52892 54.83227 62.16301 59.83156
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.74140 69.41205 67.99455 NaN 70.13999 72.21601 72.76051 70.96846
[9] 73.90416 70.41083
> rowSums(tmp5,na.rm=TRUE)
[1] 1834.828 1388.241 1359.891 0.000 1402.800 1444.320 1455.210 1419.369
[9] 1478.083 1408.217
> rowVars(tmp5,na.rm=TRUE)
[1] 8043.61811 90.81345 39.88571 NA 36.79405 111.67179
[7] 42.04257 56.34190 84.88451 87.48883
> rowSd(tmp5,na.rm=TRUE)
[1] 89.686220 9.529609 6.315514 NA 6.065810 10.567487 6.484025
[8] 7.506124 9.213279 9.353547
> rowMax(tmp5,na.rm=TRUE)
[1] 471.57777 86.58175 78.09607 NA 82.29112 92.69312 85.31610
[8] 86.40751 93.14704 89.01543
> rowMin(tmp5,na.rm=TRUE)
[1] 57.92562 55.33430 58.47965 NA 61.92306 56.68384 63.17767 57.69650
[9] 54.31973 54.18713
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 112.89628 70.63466 70.39424 74.56076 70.11912 68.67587 63.33207
[8] 76.90530 67.25486 78.19517 67.47076 71.37155 72.00813 71.84691
[15] 72.16181 70.05889 71.15470 71.63657 NaN 71.54678
> colSums(tmp5,na.rm=TRUE)
[1] 1016.0665 635.7119 633.5482 671.0469 631.0721 618.0828 569.9886
[8] 692.1477 605.2937 703.7565 607.2368 642.3439 648.0732 646.6222
[15] 649.4563 630.5300 640.3923 644.7291 0.0000 643.9211
> colVars(tmp5,na.rm=TRUE)
[1] 18114.00766 58.98091 73.74825 38.99152 55.24648 60.45599
[7] 40.29623 56.64951 89.62361 61.65898 41.17778 44.59070
[13] 28.20668 148.31696 30.58235 76.34038 98.34395 96.07707
[19] NA 71.61196
> colSd(tmp5,na.rm=TRUE)
[1] 134.588289 7.679903 8.587680 6.244319 7.432797 7.775345
[7] 6.347931 7.526587 9.466975 7.852323 6.416992 6.677627
[13] 5.310997 12.178545 5.530131 8.737298 9.916852 9.801891
[19] NA 8.462385
> colMax(tmp5,na.rm=TRUE)
[1] 471.57777 85.70534 81.55766 83.10490 83.87485 80.85144 72.94647
[8] 92.69312 81.04797 91.54782 76.41624 81.53959 78.09607 93.14704
[15] 80.76686 84.04992 89.01543 86.40751 -Inf 87.62520
> colMin(tmp5,na.rm=TRUE)
[1] 61.21844 64.07419 56.68384 66.13449 60.73139 57.92562 54.18713 67.52949
[9] 54.31973 68.15453 59.12656 62.29126 62.33724 55.33430 63.24719 60.54133
[17] 58.52892 61.41709 Inf 59.83156
>
>
>
>
> 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] 176.3482 217.5408 218.1118 231.4991 246.5268 104.5713 158.6742 165.0468
[9] 239.0113 295.6972
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 176.3482 217.5408 218.1118 231.4991 246.5268 104.5713 158.6742 165.0468
[9] 239.0113 295.6972
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 5.684342e-14 2.273737e-13 -5.684342e-14 -2.842171e-14 -5.684342e-14
[6] 1.136868e-13 -1.705303e-13 -7.105427e-15 5.684342e-14 -2.842171e-14
[11] -2.842171e-14 5.684342e-14 7.105427e-14 5.684342e-14 2.842171e-14
[16] 2.842171e-14 -1.705303e-13 -5.684342e-14 -1.705303e-13 -1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
8 12
3 15
8 19
5 20
9 2
2 18
3 8
4 15
2 4
1 6
2 2
7 1
3 18
3 13
7 16
9 16
4 5
10 8
9 4
6 20
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] 2.598141
> Min(tmp)
[1] -2.431358
> mean(tmp)
[1] -0.1106063
> Sum(tmp)
[1] -11.06063
> Var(tmp)
[1] 0.8683889
>
> rowMeans(tmp)
[1] -0.1106063
> rowSums(tmp)
[1] -11.06063
> rowVars(tmp)
[1] 0.8683889
> rowSd(tmp)
[1] 0.9318739
> rowMax(tmp)
[1] 2.598141
> rowMin(tmp)
[1] -2.431358
>
> colMeans(tmp)
[1] 0.763422302 -0.966070198 1.075760207 -0.120325249 -0.900427065
[6] 0.627480101 -0.568650320 1.134814825 0.398628405 1.930899211
[11] 1.619202646 0.456154510 0.708010379 -2.431358460 -0.267283485
[16] -0.645490278 1.848892748 -0.492894599 -0.328047618 0.330983395
[21] -1.102554578 0.026717282 0.590667069 -0.818966100 0.895007381
[26] -1.031686873 -0.268583004 -1.490131712 -0.487339919 2.598141113
[31] 0.135254358 0.361199236 -1.294772916 0.131586325 -1.515871126
[36] -0.963002480 -1.379352567 -0.934602469 0.360955953 0.210836907
[41] 0.702233303 -1.288434016 -0.800469138 0.248504393 -0.722472308
[46] 0.921298510 -0.904579697 -0.233770614 1.289036774 -0.015344235
[51] -1.676992904 0.036476856 0.383420008 0.701105670 0.855515435
[56] -0.128546290 -0.846992108 -1.301485374 -0.588715139 -0.053246995
[61] 0.252448509 -1.822907345 1.517257365 0.207735793 0.459980189
[66] -1.364999782 1.030969097 -0.497088219 0.579662236 0.158817602
[71] -0.098697524 -0.026898050 -0.432093587 -1.212987832 -0.357541283
[76] -0.739983958 0.338237592 -1.404740220 -0.394515342 -0.880821681
[81] 1.139606276 -0.007359061 -0.807851311 0.970476268 0.881110618
[86] 1.454048322 -1.030936531 -0.229794761 -1.087576937 -0.011548380
[91] -0.284283804 -0.379534780 -0.212338055 1.043148859 0.660121848
[96] -0.198798355 -0.802203705 -0.363749257 0.002248528 -1.880992457
> colSums(tmp)
[1] 0.763422302 -0.966070198 1.075760207 -0.120325249 -0.900427065
[6] 0.627480101 -0.568650320 1.134814825 0.398628405 1.930899211
[11] 1.619202646 0.456154510 0.708010379 -2.431358460 -0.267283485
[16] -0.645490278 1.848892748 -0.492894599 -0.328047618 0.330983395
[21] -1.102554578 0.026717282 0.590667069 -0.818966100 0.895007381
[26] -1.031686873 -0.268583004 -1.490131712 -0.487339919 2.598141113
[31] 0.135254358 0.361199236 -1.294772916 0.131586325 -1.515871126
[36] -0.963002480 -1.379352567 -0.934602469 0.360955953 0.210836907
[41] 0.702233303 -1.288434016 -0.800469138 0.248504393 -0.722472308
[46] 0.921298510 -0.904579697 -0.233770614 1.289036774 -0.015344235
[51] -1.676992904 0.036476856 0.383420008 0.701105670 0.855515435
[56] -0.128546290 -0.846992108 -1.301485374 -0.588715139 -0.053246995
[61] 0.252448509 -1.822907345 1.517257365 0.207735793 0.459980189
[66] -1.364999782 1.030969097 -0.497088219 0.579662236 0.158817602
[71] -0.098697524 -0.026898050 -0.432093587 -1.212987832 -0.357541283
[76] -0.739983958 0.338237592 -1.404740220 -0.394515342 -0.880821681
[81] 1.139606276 -0.007359061 -0.807851311 0.970476268 0.881110618
[86] 1.454048322 -1.030936531 -0.229794761 -1.087576937 -0.011548380
[91] -0.284283804 -0.379534780 -0.212338055 1.043148859 0.660121848
[96] -0.198798355 -0.802203705 -0.363749257 0.002248528 -1.880992457
> 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] 0.763422302 -0.966070198 1.075760207 -0.120325249 -0.900427065
[6] 0.627480101 -0.568650320 1.134814825 0.398628405 1.930899211
[11] 1.619202646 0.456154510 0.708010379 -2.431358460 -0.267283485
[16] -0.645490278 1.848892748 -0.492894599 -0.328047618 0.330983395
[21] -1.102554578 0.026717282 0.590667069 -0.818966100 0.895007381
[26] -1.031686873 -0.268583004 -1.490131712 -0.487339919 2.598141113
[31] 0.135254358 0.361199236 -1.294772916 0.131586325 -1.515871126
[36] -0.963002480 -1.379352567 -0.934602469 0.360955953 0.210836907
[41] 0.702233303 -1.288434016 -0.800469138 0.248504393 -0.722472308
[46] 0.921298510 -0.904579697 -0.233770614 1.289036774 -0.015344235
[51] -1.676992904 0.036476856 0.383420008 0.701105670 0.855515435
[56] -0.128546290 -0.846992108 -1.301485374 -0.588715139 -0.053246995
[61] 0.252448509 -1.822907345 1.517257365 0.207735793 0.459980189
[66] -1.364999782 1.030969097 -0.497088219 0.579662236 0.158817602
[71] -0.098697524 -0.026898050 -0.432093587 -1.212987832 -0.357541283
[76] -0.739983958 0.338237592 -1.404740220 -0.394515342 -0.880821681
[81] 1.139606276 -0.007359061 -0.807851311 0.970476268 0.881110618
[86] 1.454048322 -1.030936531 -0.229794761 -1.087576937 -0.011548380
[91] -0.284283804 -0.379534780 -0.212338055 1.043148859 0.660121848
[96] -0.198798355 -0.802203705 -0.363749257 0.002248528 -1.880992457
> colMin(tmp)
[1] 0.763422302 -0.966070198 1.075760207 -0.120325249 -0.900427065
[6] 0.627480101 -0.568650320 1.134814825 0.398628405 1.930899211
[11] 1.619202646 0.456154510 0.708010379 -2.431358460 -0.267283485
[16] -0.645490278 1.848892748 -0.492894599 -0.328047618 0.330983395
[21] -1.102554578 0.026717282 0.590667069 -0.818966100 0.895007381
[26] -1.031686873 -0.268583004 -1.490131712 -0.487339919 2.598141113
[31] 0.135254358 0.361199236 -1.294772916 0.131586325 -1.515871126
[36] -0.963002480 -1.379352567 -0.934602469 0.360955953 0.210836907
[41] 0.702233303 -1.288434016 -0.800469138 0.248504393 -0.722472308
[46] 0.921298510 -0.904579697 -0.233770614 1.289036774 -0.015344235
[51] -1.676992904 0.036476856 0.383420008 0.701105670 0.855515435
[56] -0.128546290 -0.846992108 -1.301485374 -0.588715139 -0.053246995
[61] 0.252448509 -1.822907345 1.517257365 0.207735793 0.459980189
[66] -1.364999782 1.030969097 -0.497088219 0.579662236 0.158817602
[71] -0.098697524 -0.026898050 -0.432093587 -1.212987832 -0.357541283
[76] -0.739983958 0.338237592 -1.404740220 -0.394515342 -0.880821681
[81] 1.139606276 -0.007359061 -0.807851311 0.970476268 0.881110618
[86] 1.454048322 -1.030936531 -0.229794761 -1.087576937 -0.011548380
[91] -0.284283804 -0.379534780 -0.212338055 1.043148859 0.660121848
[96] -0.198798355 -0.802203705 -0.363749257 0.002248528 -1.880992457
> colMedians(tmp)
[1] 0.763422302 -0.966070198 1.075760207 -0.120325249 -0.900427065
[6] 0.627480101 -0.568650320 1.134814825 0.398628405 1.930899211
[11] 1.619202646 0.456154510 0.708010379 -2.431358460 -0.267283485
[16] -0.645490278 1.848892748 -0.492894599 -0.328047618 0.330983395
[21] -1.102554578 0.026717282 0.590667069 -0.818966100 0.895007381
[26] -1.031686873 -0.268583004 -1.490131712 -0.487339919 2.598141113
[31] 0.135254358 0.361199236 -1.294772916 0.131586325 -1.515871126
[36] -0.963002480 -1.379352567 -0.934602469 0.360955953 0.210836907
[41] 0.702233303 -1.288434016 -0.800469138 0.248504393 -0.722472308
[46] 0.921298510 -0.904579697 -0.233770614 1.289036774 -0.015344235
[51] -1.676992904 0.036476856 0.383420008 0.701105670 0.855515435
[56] -0.128546290 -0.846992108 -1.301485374 -0.588715139 -0.053246995
[61] 0.252448509 -1.822907345 1.517257365 0.207735793 0.459980189
[66] -1.364999782 1.030969097 -0.497088219 0.579662236 0.158817602
[71] -0.098697524 -0.026898050 -0.432093587 -1.212987832 -0.357541283
[76] -0.739983958 0.338237592 -1.404740220 -0.394515342 -0.880821681
[81] 1.139606276 -0.007359061 -0.807851311 0.970476268 0.881110618
[86] 1.454048322 -1.030936531 -0.229794761 -1.087576937 -0.011548380
[91] -0.284283804 -0.379534780 -0.212338055 1.043148859 0.660121848
[96] -0.198798355 -0.802203705 -0.363749257 0.002248528 -1.880992457
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.7634223 -0.9660702 1.07576 -0.1203252 -0.9004271 0.6274801 -0.5686503
[2,] 0.7634223 -0.9660702 1.07576 -0.1203252 -0.9004271 0.6274801 -0.5686503
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.134815 0.3986284 1.930899 1.619203 0.4561545 0.7080104 -2.431358
[2,] 1.134815 0.3986284 1.930899 1.619203 0.4561545 0.7080104 -2.431358
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.2672835 -0.6454903 1.848893 -0.4928946 -0.3280476 0.3309834 -1.102555
[2,] -0.2672835 -0.6454903 1.848893 -0.4928946 -0.3280476 0.3309834 -1.102555
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.02671728 0.5906671 -0.8189661 0.8950074 -1.031687 -0.268583 -1.490132
[2,] 0.02671728 0.5906671 -0.8189661 0.8950074 -1.031687 -0.268583 -1.490132
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.4873399 2.598141 0.1352544 0.3611992 -1.294773 0.1315863 -1.515871
[2,] -0.4873399 2.598141 0.1352544 0.3611992 -1.294773 0.1315863 -1.515871
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.9630025 -1.379353 -0.9346025 0.360956 0.2108369 0.7022333 -1.288434
[2,] -0.9630025 -1.379353 -0.9346025 0.360956 0.2108369 0.7022333 -1.288434
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.8004691 0.2485044 -0.7224723 0.9212985 -0.9045797 -0.2337706 1.289037
[2,] -0.8004691 0.2485044 -0.7224723 0.9212985 -0.9045797 -0.2337706 1.289037
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.01534423 -1.676993 0.03647686 0.38342 0.7011057 0.8555154 -0.1285463
[2,] -0.01534423 -1.676993 0.03647686 0.38342 0.7011057 0.8555154 -0.1285463
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.8469921 -1.301485 -0.5887151 -0.05324699 0.2524485 -1.822907 1.517257
[2,] -0.8469921 -1.301485 -0.5887151 -0.05324699 0.2524485 -1.822907 1.517257
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.2077358 0.4599802 -1.365 1.030969 -0.4970882 0.5796622 0.1588176
[2,] 0.2077358 0.4599802 -1.365 1.030969 -0.4970882 0.5796622 0.1588176
[,71] [,72] [,73] [,74] [,75] [,76]
[1,] -0.09869752 -0.02689805 -0.4320936 -1.212988 -0.3575413 -0.739984
[2,] -0.09869752 -0.02689805 -0.4320936 -1.212988 -0.3575413 -0.739984
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] 0.3382376 -1.40474 -0.3945153 -0.8808217 1.139606 -0.007359061 -0.8078513
[2,] 0.3382376 -1.40474 -0.3945153 -0.8808217 1.139606 -0.007359061 -0.8078513
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 0.9704763 0.8811106 1.454048 -1.030937 -0.2297948 -1.087577 -0.01154838
[2,] 0.9704763 0.8811106 1.454048 -1.030937 -0.2297948 -1.087577 -0.01154838
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -0.2842838 -0.3795348 -0.2123381 1.043149 0.6601218 -0.1987984 -0.8022037
[2,] -0.2842838 -0.3795348 -0.2123381 1.043149 0.6601218 -0.1987984 -0.8022037
[,98] [,99] [,100]
[1,] -0.3637493 0.002248528 -1.880992
[2,] -0.3637493 0.002248528 -1.880992
>
>
> Max(tmp2)
[1] 2.449373
> Min(tmp2)
[1] -2.611327
> mean(tmp2)
[1] -0.04590038
> Sum(tmp2)
[1] -4.590038
> Var(tmp2)
[1] 1.113507
>
> rowMeans(tmp2)
[1] 0.98734212 -0.33556576 0.13997506 1.50345079 -0.60138022 -0.18706744
[7] 2.44937257 -2.13240723 -1.06583951 0.12587594 -1.37848889 0.68857948
[13] 0.23477232 -0.23519380 0.23353689 0.39599897 -1.59834507 -0.13844542
[19] 0.06017419 1.42539823 0.68593863 -1.16059935 -0.40615594 -2.18440559
[25] 0.50091119 1.45820755 -0.17440224 -0.59457062 -1.15897679 0.49586215
[31] 1.37664758 -1.55418974 -0.83640319 -0.20847606 -1.19716786 -0.65327338
[37] -1.78436147 1.68241784 -0.13942552 0.65224517 1.61696117 0.67603924
[43] 0.34594125 -1.66303947 0.49685619 -0.41660137 2.05012293 0.08801378
[49] -0.24592838 0.29474860 -2.15165692 -1.46231697 0.48728455 0.46902321
[55] -0.74333837 -1.20888993 -1.00119210 -0.71567160 0.66973606 -1.19323948
[61] -0.84952686 -0.60481595 -1.08955715 1.81837107 0.67416107 1.36446285
[67] 0.53499310 0.20625666 -2.61132719 -0.36723498 2.37656744 0.07973461
[73] 0.34225696 -0.11267602 -0.04429730 1.80582404 0.08058808 0.23602824
[79] -0.90003233 0.75798345 1.28792001 -0.01406463 -0.98304109 -0.61822069
[85] -0.86768700 0.06661726 1.44855480 -0.21539571 0.69306042 1.26634475
[91] 1.31567518 -0.48832008 0.54865178 -0.78060480 -0.51443296 -0.08800259
[97] 0.45097254 -1.42164097 -0.84162412 -0.29697738
> rowSums(tmp2)
[1] 0.98734212 -0.33556576 0.13997506 1.50345079 -0.60138022 -0.18706744
[7] 2.44937257 -2.13240723 -1.06583951 0.12587594 -1.37848889 0.68857948
[13] 0.23477232 -0.23519380 0.23353689 0.39599897 -1.59834507 -0.13844542
[19] 0.06017419 1.42539823 0.68593863 -1.16059935 -0.40615594 -2.18440559
[25] 0.50091119 1.45820755 -0.17440224 -0.59457062 -1.15897679 0.49586215
[31] 1.37664758 -1.55418974 -0.83640319 -0.20847606 -1.19716786 -0.65327338
[37] -1.78436147 1.68241784 -0.13942552 0.65224517 1.61696117 0.67603924
[43] 0.34594125 -1.66303947 0.49685619 -0.41660137 2.05012293 0.08801378
[49] -0.24592838 0.29474860 -2.15165692 -1.46231697 0.48728455 0.46902321
[55] -0.74333837 -1.20888993 -1.00119210 -0.71567160 0.66973606 -1.19323948
[61] -0.84952686 -0.60481595 -1.08955715 1.81837107 0.67416107 1.36446285
[67] 0.53499310 0.20625666 -2.61132719 -0.36723498 2.37656744 0.07973461
[73] 0.34225696 -0.11267602 -0.04429730 1.80582404 0.08058808 0.23602824
[79] -0.90003233 0.75798345 1.28792001 -0.01406463 -0.98304109 -0.61822069
[85] -0.86768700 0.06661726 1.44855480 -0.21539571 0.69306042 1.26634475
[91] 1.31567518 -0.48832008 0.54865178 -0.78060480 -0.51443296 -0.08800259
[97] 0.45097254 -1.42164097 -0.84162412 -0.29697738
> 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] 0.98734212 -0.33556576 0.13997506 1.50345079 -0.60138022 -0.18706744
[7] 2.44937257 -2.13240723 -1.06583951 0.12587594 -1.37848889 0.68857948
[13] 0.23477232 -0.23519380 0.23353689 0.39599897 -1.59834507 -0.13844542
[19] 0.06017419 1.42539823 0.68593863 -1.16059935 -0.40615594 -2.18440559
[25] 0.50091119 1.45820755 -0.17440224 -0.59457062 -1.15897679 0.49586215
[31] 1.37664758 -1.55418974 -0.83640319 -0.20847606 -1.19716786 -0.65327338
[37] -1.78436147 1.68241784 -0.13942552 0.65224517 1.61696117 0.67603924
[43] 0.34594125 -1.66303947 0.49685619 -0.41660137 2.05012293 0.08801378
[49] -0.24592838 0.29474860 -2.15165692 -1.46231697 0.48728455 0.46902321
[55] -0.74333837 -1.20888993 -1.00119210 -0.71567160 0.66973606 -1.19323948
[61] -0.84952686 -0.60481595 -1.08955715 1.81837107 0.67416107 1.36446285
[67] 0.53499310 0.20625666 -2.61132719 -0.36723498 2.37656744 0.07973461
[73] 0.34225696 -0.11267602 -0.04429730 1.80582404 0.08058808 0.23602824
[79] -0.90003233 0.75798345 1.28792001 -0.01406463 -0.98304109 -0.61822069
[85] -0.86768700 0.06661726 1.44855480 -0.21539571 0.69306042 1.26634475
[91] 1.31567518 -0.48832008 0.54865178 -0.78060480 -0.51443296 -0.08800259
[97] 0.45097254 -1.42164097 -0.84162412 -0.29697738
> rowMin(tmp2)
[1] 0.98734212 -0.33556576 0.13997506 1.50345079 -0.60138022 -0.18706744
[7] 2.44937257 -2.13240723 -1.06583951 0.12587594 -1.37848889 0.68857948
[13] 0.23477232 -0.23519380 0.23353689 0.39599897 -1.59834507 -0.13844542
[19] 0.06017419 1.42539823 0.68593863 -1.16059935 -0.40615594 -2.18440559
[25] 0.50091119 1.45820755 -0.17440224 -0.59457062 -1.15897679 0.49586215
[31] 1.37664758 -1.55418974 -0.83640319 -0.20847606 -1.19716786 -0.65327338
[37] -1.78436147 1.68241784 -0.13942552 0.65224517 1.61696117 0.67603924
[43] 0.34594125 -1.66303947 0.49685619 -0.41660137 2.05012293 0.08801378
[49] -0.24592838 0.29474860 -2.15165692 -1.46231697 0.48728455 0.46902321
[55] -0.74333837 -1.20888993 -1.00119210 -0.71567160 0.66973606 -1.19323948
[61] -0.84952686 -0.60481595 -1.08955715 1.81837107 0.67416107 1.36446285
[67] 0.53499310 0.20625666 -2.61132719 -0.36723498 2.37656744 0.07973461
[73] 0.34225696 -0.11267602 -0.04429730 1.80582404 0.08058808 0.23602824
[79] -0.90003233 0.75798345 1.28792001 -0.01406463 -0.98304109 -0.61822069
[85] -0.86768700 0.06661726 1.44855480 -0.21539571 0.69306042 1.26634475
[91] 1.31567518 -0.48832008 0.54865178 -0.78060480 -0.51443296 -0.08800259
[97] 0.45097254 -1.42164097 -0.84162412 -0.29697738
>
> colMeans(tmp2)
[1] -0.04590038
> colSums(tmp2)
[1] -4.590038
> colVars(tmp2)
[1] 1.113507
> colSd(tmp2)
[1] 1.055228
> colMax(tmp2)
[1] 2.449373
> colMin(tmp2)
[1] -2.611327
> colMedians(tmp2)
[1] -0.06614995
> colRanges(tmp2)
[,1]
[1,] -2.611327
[2,] 2.449373
>
> 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] -1.59568593 -5.71741241 0.09126204 -1.26603524 4.97620483 -1.50555193
[7] 2.68429383 2.41327946 -1.24065503 -2.98617971
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5728599
[2,] -0.9930266
[3,] -0.1077800
[4,] 0.4315835
[5,] 1.4374564
>
> rowApply(tmp,sum)
[1] 3.3057479 5.1718064 -2.7790989 -3.1873518 3.2973323 -5.7003770
[7] 2.4335007 -2.1862228 -4.8854321 0.3836151
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 2 2 2 7 8 2 2 9 10 1
[2,] 4 9 3 5 1 10 1 2 1 3
[3,] 7 6 5 3 9 6 5 4 3 7
[4,] 5 3 10 9 5 3 4 1 6 4
[5,] 9 5 8 8 10 9 9 6 7 6
[6,] 1 1 7 1 6 8 6 5 5 9
[7,] 6 4 6 10 7 1 8 7 8 8
[8,] 3 10 4 4 3 7 10 8 9 5
[9,] 8 7 9 2 2 5 7 10 4 2
[10,] 10 8 1 6 4 4 3 3 2 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.50415432 0.12456281 -2.09543837 1.34605662 -2.69059946 2.16172835
[7] -0.65513857 -3.14672833 1.94667176 0.04637672 -2.10080485 2.18036788
[13] -1.69423228 -0.17852402 -1.30938278 1.33376351 2.10121610 3.76693367
[19] -0.81527466 1.88750244
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.14570260
[2,] 0.09577296
[3,] 0.60333108
[4,] 0.89071942
[5,] 1.06003346
>
> rowApply(tmp,sum)
[1] 9.1429139 -3.4736384 1.9365463 -3.2893812 0.3967703
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 10 14 15 14 17
[2,] 17 11 10 6 8
[3,] 9 2 9 4 12
[4,] 16 9 16 15 1
[5,] 5 7 8 3 9
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.09577296 1.6184044 0.039079435 1.5873966 -0.29143006 1.2021351
[2,] -0.14570260 -0.2547559 -0.991418338 -0.3205231 -0.53260578 0.4712019
[3,] 0.60333108 0.2911515 0.176984541 0.6407717 0.07486022 -0.7719195
[4,] 0.89071942 -1.1385252 -1.328409177 0.8962942 -1.83065594 -0.1740195
[5,] 1.06003346 -0.3917121 0.008325166 -1.4578828 -0.11076790 1.4343303
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.8448490 -0.06328849 -0.2244489 -0.37504103 -1.5452638 0.46177536
[2,] -0.9375424 -0.82343996 0.2577951 -0.83829275 0.4154511 -0.21798547
[3,] 0.9336086 -1.49629685 -0.6339572 0.99318875 0.3717463 -0.01143463
[4,] -0.4696122 -1.16269952 1.0962663 0.36590379 -0.3432425 1.26932128
[5,] -1.0264416 0.39899648 1.4510165 -0.09938204 -0.9994960 0.67869134
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 2.881304 2.0813097 -0.26005249 1.4587842 -2.0574445 2.0340638523
[2,] -0.065546 -0.6667819 -0.50005529 1.0242772 -0.1638570 -0.3112119395
[3,] -1.391582 -0.6903778 0.43762627 0.3965727 2.0351186 0.3748708728
[4,] -1.993250 -1.9827963 0.07658831 -0.9984230 1.5516252 1.6688272775
[5,] -1.125158 1.0801222 -1.06348958 -0.5474476 0.7357738 0.0003836067
[,19] [,20]
[1,] 0.6590558 -1.004047
[2,] -1.2467351 2.374090
[3,] 1.3697148 -1.767432
[4,] -0.9555020 1.272208
[5,] -0.6418082 1.012684
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 650 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 562 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 1.599066 -2.186662 -0.06580542 0.1262258 0.6372753 -1.763081 -1.188112
col8 col9 col10 col11 col12 col13 col14
row1 -0.3353673 0.1262244 1.115746 -0.1597654 0.5562834 -0.9588145 -1.599758
col15 col16 col17 col18 col19 col20
row1 0.4491821 -1.642785 0.5385808 -0.9021812 0.1895741 0.05826449
> tmp[,"col10"]
col10
row1 1.1157464
row2 -0.9916652
row3 0.9579188
row4 0.7072856
row5 -1.0918651
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.5990661 -2.1866621 -0.06580542 0.1262258 0.6372753 -1.7630810 -1.188112
row5 0.4626485 0.3373631 -1.65701200 0.8196243 0.1502944 -0.6481549 -1.387247
col8 col9 col10 col11 col12 col13 col14
row1 -0.3353673 0.1262244 1.115746 -0.1597654 0.5562834 -0.9588145 -1.5997579
row5 -0.2589415 1.0988261 -1.091865 0.8673644 0.7057833 0.9565833 -0.0606719
col15 col16 col17 col18 col19 col20
row1 0.4491821 -1.64278488 0.53858084 -0.9021812 0.1895741 0.05826449
row5 -2.0586121 0.01810964 0.05470109 0.8688801 0.8323151 0.60223896
> tmp[,c("col6","col20")]
col6 col20
row1 -1.76308096 0.05826449
row2 -0.85352597 -0.22017450
row3 0.35468513 1.34302575
row4 -0.04545769 0.97092391
row5 -0.64815489 0.60223896
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.7630810 0.05826449
row5 -0.6481549 0.60223896
>
>
>
>
> 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 50.42062 50.13824 51.17107 50.73534 49.51619 105.7256 49.75013 51.20809
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.52641 50.59449 49.55406 49.58215 51.87564 49.47903 50.06626 50.30449
col17 col18 col19 col20
row1 48.52188 51.78094 51.02814 104.8558
> tmp[,"col10"]
col10
row1 50.59449
row2 33.41182
row3 28.26404
row4 30.26634
row5 49.59185
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.42062 50.13824 51.17107 50.73534 49.51619 105.7256 49.75013 51.20809
row5 50.25634 50.19115 51.73770 49.88095 50.19888 104.6794 48.53659 49.54317
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.52641 50.59449 49.55406 49.58215 51.87564 49.47903 50.06626 50.30449
row5 52.07585 49.59185 50.59787 49.70169 48.54808 50.51615 51.44068 50.39143
col17 col18 col19 col20
row1 48.52188 51.78094 51.02814 104.8558
row5 49.53151 48.03434 52.10039 105.0549
> tmp[,c("col6","col20")]
col6 col20
row1 105.72558 104.85582
row2 73.14293 76.07347
row3 74.27795 75.55681
row4 74.66803 75.15760
row5 104.67937 105.05493
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.7256 104.8558
row5 104.6794 105.0549
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.7256 104.8558
row5 104.6794 105.0549
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.7945345
[2,] -0.4681871
[3,] 1.0344316
[4,] 0.8853888
[5,] -1.0343411
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.5755534 0.34035854
[2,] -1.0351828 -0.66642226
[3,] -1.0502862 -0.03782425
[4,] -0.8503370 0.10628977
[5,] -0.3271535 -0.97137858
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.6492037 1.29142796
[2,] 0.4018763 0.17418740
[3,] 0.6338376 0.06513857
[4,] 1.2106431 0.36495714
[5,] 0.8792924 0.39736281
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.649204
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.6492037
[2,] 0.4018763
>
>
>
> 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 2.2772348 0.3157650 0.1904837 -1.093795 -0.1483441 -0.6699893 0.4085039
row1 -0.1381598 0.9956965 -0.3864694 -1.018921 1.5483773 0.2508285 -1.2102544
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.2941499 -0.3953054 0.822699 1.3358319 -0.9920481 2.4325153 0.0429875
row1 -0.5895359 -0.7389858 -2.779049 0.9223387 1.1305364 0.2502944 0.9805275
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -1.4869591 -0.2547829 -1.7098157 -0.2804821 0.149548 2.358031
row1 -0.2435424 -0.2260440 0.4317297 -2.4187621 -0.850630 0.848983
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.911783 0.6387954 0.05934235 0.9887959 0.1559212 0.8966604 0.1698863
[,8] [,9] [,10]
row2 -0.1420401 0.2069138 -0.2799358
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row5 -0.2844297 -0.2801892 -1.977026 0.3986028 -0.04279643 -0.2034184
[,7] [,8] [,9] [,10] [,11] [,12]
row5 -0.3844054 0.06271099 -0.06620314 -0.723593 -0.7613145 0.08162645
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row5 0.2970767 0.6096035 -0.6947322 0.5093532 0.5659084 -1.238983 -0.861927
[,20]
row5 -0.3567945
>
>
> 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: 0x7f84fd523430>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM569d5c699eb4"
[2] "/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM569d1a326ad2"
[3] "/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM569d64030e6d"
[4] "/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM569d4a84967"
[5] "/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM569d446b0b94"
[6] "/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM569d4fc544a3"
[7] "/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM569d201d523f"
[8] "/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM569d6502b691"
[9] "/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM569d15201d66"
[10] "/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM569d6f6a1e5f"
[11] "/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM569d1ff0281e"
[12] "/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM569d4fd9d9f3"
[13] "/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM569d67740979"
[14] "/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM569d731a1bfe"
[15] "/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM569d3723fbbb"
>
>
> ### 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: 0x7f850d43b6c0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x7f850d43b6c0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x7f850d43b6c0>
> rowMedians(tmp)
[1] -0.0238798649 0.3557580544 0.1583523561 -0.3658277767 0.0109031750
[6] 0.0083242186 0.4582153821 0.2354704580 0.0808204861 0.0525787838
[11] 0.3093147764 -0.3352538274 -0.0809316009 0.0270496441 0.2487566537
[16] 0.0581169820 0.0028073345 0.5926711873 0.0807031671 -0.1358855695
[21] -0.2522359144 -0.1012213041 0.1654371519 -0.1170846856 -0.1510942943
[26] -0.2631134068 0.4660517023 0.5749976252 0.1126279468 0.2395877686
[31] -0.5648680619 -0.2194271833 0.0333097520 -0.2589143315 0.0196480956
[36] 0.1672126333 -0.8004946163 0.0918395208 0.1671029840 0.0167389901
[41] -0.1606834023 -0.0502041624 -0.5951638255 0.0846320633 0.1906365511
[46] -0.3605560336 0.0171469839 -0.4375744024 -0.3812009305 0.0971353533
[51] -0.1459911135 -0.1243679642 0.0771749965 -0.3966351479 -0.3182946659
[56] -0.2245240191 0.0204424894 -0.3234630341 0.6651996746 -0.3806815639
[61] -0.1138858793 -0.1396465603 0.2545800895 0.2734313015 0.4160972576
[66] 0.4713950428 0.1377574700 0.0386458323 0.2020105719 0.1506416059
[71] -0.2975328899 0.0271578320 0.1407393554 0.8029664816 0.2907449499
[76] 0.0913199131 0.4005794441 0.0326193517 0.0609128269 0.0172911732
[81] -0.3453926031 0.0632495392 0.3903223427 -0.0521256772 -0.2142335949
[86] -0.3529850251 0.0571383237 0.4527779047 -0.6544397514 0.2493594457
[91] -0.5539426821 0.1696384665 0.0072958579 0.1133044807 0.1632998624
[96] 0.1757754751 -0.9000286379 0.1052595894 0.0078387315 -0.0381543428
[101] -0.2385082585 0.0981179348 0.2083469635 0.3552317900 -0.4849738285
[106] 0.3782722673 0.1677488417 -0.1449510331 0.5365349295 -0.8976326187
[111] 0.2051283534 -0.1288893841 -0.0721406345 -0.3119418568 -0.5231068282
[116] 0.3334628687 -0.2786887463 0.0009870922 -0.5739513441 -0.1435314243
[121] -0.1969909670 0.1364790525 0.0634268673 -0.0108452185 0.0434952259
[126] -0.0210535612 0.6788897074 0.4266813581 0.2767434905 -0.1316568286
[131] 0.0513805318 -0.1660994383 0.0298172796 0.1117094907 0.2530230950
[136] 0.8769374256 0.2703121595 0.4911489579 -0.1670792292 0.0605208242
[141] -0.5197441617 0.7017580839 0.2209488168 -0.1424574855 0.2257788494
[146] 0.0495714426 0.3627852438 0.4262670769 -0.2845812751 -0.0271198604
[151] 0.7245910086 0.5737405703 0.6017436949 0.0560566711 -0.3699531284
[156] 0.8416746378 -0.3358331961 -0.6170798790 0.4182078579 -0.0935544078
[161] 0.2604478266 -0.1928550396 0.0814969523 0.4140369396 0.9105399646
[166] -0.3014495208 0.2091407327 0.3828890207 -0.0189445739 0.2235538811
[171] -0.0598905405 -0.5931292884 -0.3949708137 -0.0122130159 0.0407895779
[176] 0.2498295709 -0.0230342411 -0.3785375614 0.1569657839 0.1013162480
[181] 0.0490016662 0.2766310654 0.2359493887 -0.0129198473 -0.1024672826
[186] 0.4375330658 0.2044817923 -0.1759127953 0.1741253382 -0.0626340067
[191] -0.2428129024 0.0410437015 0.2940014318 0.1594445244 0.6034611782
[196] 0.6833949072 -0.1338320090 0.0674120980 -0.0479978904 0.5585723293
[201] -0.4055004187 0.1271911429 -0.3794713626 -0.3652497405 -0.3926093260
[206] -0.0792713681 0.2859771517 -0.5183859525 -0.3028941891 0.9266846682
[211] -0.4781121373 0.3126185372 0.6035568500 -0.0935909256 -0.1818729314
[216] 0.0240108796 -0.5626181675 -0.2277281872 0.3592437705 0.6308869981
[221] -0.3008130710 -0.7411092430 -0.2307422144 0.1138445261 0.0560993553
[226] -0.6758244817 0.3516551468 -0.7570547337 0.1036454912 -0.1724221447
>
> proc.time()
user system elapsed
3.265 10.493 14.082
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.0.5 (2021-03-31) -- "Shake and Throw"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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: 0x7ff2a7c03360>
> .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: 0x7ff2a7c03360>
> .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: 0x7ff2a7c03360>
> .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: 0x7ff2a7c03360>
> 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: 0x7ff2a7d00aa0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7ff2a7d00aa0>
> .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: 0x7ff2a7d00aa0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7ff2a7d00aa0>
> .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: 0x7ff2a7d00aa0>
> 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: 0x7ff2a7d00ce0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7ff2a7d00ce0>
> .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: 0x7ff2a7d00ce0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x7ff2a7d00ce0>
> .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: 0x7ff2a7d00ce0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x7ff2a7d00ce0>
> .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: 0x7ff2a7d00ce0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x7ff2a7d00ce0>
> .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: 0x7ff2a7d00ce0>
> 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: 0x7ff2a7c04070>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x7ff2a7c04070>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7ff2a7c04070>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7ff2a7c04070>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile58d93fb141a9" "BufferedMatrixFile58d9d56d4de"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile58d93fb141a9" "BufferedMatrixFile58d9d56d4de"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x7ff2a7c04310>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7ff2a7c04310>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x7ff2a7c04310>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x7ff2a7c04310>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x7ff2a7c04310>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x7ff2a7c04310>
> .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: 0x7ff2a7c046c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7ff2a7c046c0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x7ff2a7c046c0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x7ff2a7c046c0>
> 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: 0x7ff2a7c04aa0>
> .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: 0x7ff2a7c04aa0>
> rm(P)
>
> proc.time()
user system elapsed
0.386 0.109 0.478
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.0.5 (2021-03-31) -- "Shake and Throw"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (64-bit)
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Type 'license()' or 'licence()' for distribution details.
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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
0.420 0.072 0.473