Ben Bolstad
| Snapshot Date: 2018-10-15 16:45:08 -0400 (Mon, 15 Oct 2018) |
| URL: https://git.bioconductor.org/packages/BufferedMatrix |
| Branch: RELEASE_3_7 |
| Last Commit: 6087ec6 |
| Last Changed Date: 2018-04-30 10:35:06 -0400 (Mon, 30 Apr 2018) |
| Back to Multiple platform build/check report for BioC 3.7 |
|
This page was generated on 2018-10-17 08:47:12 -0400 (Wed, 17 Oct 2018).
| Package 172/1561 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||
| BufferedMatrix 1.44.0 Ben Bolstad
| malbec2 | Linux (Ubuntu 16.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||
| tokay2 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||
| merida2 | OS X 10.11.6 El Capitan / x86_64 | OK | OK | [ OK ] | OK | |
| Package: BufferedMatrix |
| Version: 1.44.0 |
| 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_1.44.0.tar.gz |
| StartedAt: 2018-10-16 20:12:38 -0400 (Tue, 16 Oct 2018) |
| EndedAt: 2018-10-16 20:13:18 -0400 (Tue, 16 Oct 2018) |
| EllapsedTime: 39.6 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_1.44.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck’ * using R version 3.5.1 Patched (2018-07-12 r74967) * using platform: x86_64-apple-darwin15.6.0 (64-bit) * using session charset: UTF-8 * using option ‘--no-vignettes’ * checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK * this is package ‘BufferedMatrix’ version ‘1.44.0’ * 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-3.7-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/3.5/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** libs
clang -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/usr/local/include -fPIC -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -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 -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 -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 -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/3.5/Resources/library/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
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 3.5.1 Patched (2018-07-12 r74967) -- "Feather Spray"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin15.6.0 (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
0.404 0.098 0.472
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 3.5.1 Patched (2018-07-12 r74967) -- "Feather Spray"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin15.6.0 (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-3.7-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 410030 21.9 866105 46.3 NA 610817 32.7
Vcells 752727 5.8 8388608 64.0 65536 1825159 14.0
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Tue Oct 16 20:13:01 2018"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Oct 16 20:13:01 2018"
>
>
> 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: 0x7fcbadb18800>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Tue Oct 16 20:13:03 2018"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Oct 16 20:13:04 2018"
>
> ColMode(tmp2)
<pointer: 0x7fcbadb18800>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.26874181 -0.2863810 -2.4838393 -0.7876443
[2,] -1.14474206 -0.7917481 -0.5624982 -0.4900416
[3,] -0.09742616 0.7499582 -0.8574317 0.4702997
[4,] 0.61325377 1.5233969 0.8253792 -1.0541815
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.26874181 0.2863810 2.4838393 0.7876443
[2,] 1.14474206 0.7917481 0.5624982 0.4900416
[3,] 0.09742616 0.7499582 0.8574317 0.4702997
[4,] 0.61325377 1.5233969 0.8253792 1.0541815
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9633700 0.5351457 1.5760201 0.8874933
[2,] 1.0699262 0.8898023 0.7499988 0.7000297
[3,] 0.3121316 0.8660013 0.9259761 0.6857840
[4,] 0.7831052 1.2342597 0.9085038 1.0267334
>
> 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-3.7-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 223.90244 30.63784 43.24404 34.66258
[2,] 36.84400 34.68977 33.06249 32.49034
[3,] 28.21874 34.40997 35.11719 32.32814
[4,] 33.44431 38.86599 34.91042 36.32152
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x7fcbad816cb0>
> exp(tmp5)
<pointer: 0x7fcbad816cb0>
> log(tmp5,2)
<pointer: 0x7fcbad816cb0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.0236
> Min(tmp5)
[1] 52.62371
> mean(tmp5)
[1] 73.43521
> Sum(tmp5)
[1] 14687.04
> Var(tmp5)
[1] 864.8239
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.62159 68.53974 72.06033 72.64064 72.78626 73.97841 69.45028 69.58865
[9] 71.61573 71.07049
> rowSums(tmp5)
[1] 1852.432 1370.795 1441.207 1452.813 1455.725 1479.568 1389.006 1391.773
[9] 1432.315 1421.410
> rowVars(tmp5)
[1] 7817.97147 106.65684 76.00552 97.18807 54.64733 128.81612
[7] 112.44463 85.63983 43.59607 77.13842
> rowSd(tmp5)
[1] 88.419294 10.327480 8.718114 9.858401 7.392384 11.349719 10.603991
[8] 9.254179 6.602732 8.782848
> rowMax(tmp5)
[1] 466.02360 97.04910 83.86329 90.48399 85.82406 98.79388 95.58142
[8] 88.42911 86.34637 96.74033
> rowMin(tmp5)
[1] 56.88962 52.89196 56.92801 53.32677 63.35608 57.74204 54.44614 52.62371
[9] 60.40903 58.41551
>
> colMeans(tmp5)
[1] 110.22410 69.69909 74.48280 71.27041 75.24345 73.37556 71.23381
[8] 68.91551 71.90124 73.07094 67.11776 69.40228 76.90690 70.60368
[15] 68.17847 71.88322 66.45310 71.74179 72.88841 74.11168
> colSums(tmp5)
[1] 1102.2410 696.9909 744.8280 712.7041 752.4345 733.7556 712.3381
[8] 689.1551 719.0124 730.7094 671.1776 694.0228 769.0690 706.0368
[15] 681.7847 718.8322 664.5310 717.4179 728.8841 741.1168
> colVars(tmp5)
[1] 15675.31834 86.68768 96.56056 46.09459 112.88395 111.60407
[7] 92.37380 76.07771 130.39759 73.43912 72.71386 30.32626
[13] 159.26768 63.86237 78.66414 92.58112 60.56888 40.11097
[19] 134.30213 151.87312
> colSd(tmp5)
[1] 125.201112 9.310622 9.826524 6.789299 10.624686 10.564283
[7] 9.611129 8.722254 11.419176 8.569663 8.527242 5.506929
[13] 12.620130 7.991394 8.869281 9.621908 7.782601 6.333322
[19] 11.588879 12.323681
> colMax(tmp5)
[1] 466.02360 82.29072 90.00680 85.82406 95.58142 96.74033 93.19210
[8] 82.73884 86.87516 83.86329 81.03058 77.55284 93.69086 82.53463
[15] 82.01205 88.42911 84.66172 83.94352 97.04910 98.79388
> colMin(tmp5)
[1] 58.73362 52.62371 54.44614 63.07050 57.74204 62.29479 59.26115 56.88962
[9] 56.45735 56.69741 57.30919 60.75793 52.89196 59.37463 57.46080 60.64640
[17] 57.62282 59.52292 56.92801 53.32677
>
>
> ### 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] 92.62159 68.53974 72.06033 72.64064 72.78626 73.97841 69.45028 NA
[9] 71.61573 71.07049
> rowSums(tmp5)
[1] 1852.432 1370.795 1441.207 1452.813 1455.725 1479.568 1389.006 NA
[9] 1432.315 1421.410
> rowVars(tmp5)
[1] 7817.97147 106.65684 76.00552 97.18807 54.64733 128.81612
[7] 112.44463 88.76869 43.59607 77.13842
> rowSd(tmp5)
[1] 88.419294 10.327480 8.718114 9.858401 7.392384 11.349719 10.603991
[8] 9.421714 6.602732 8.782848
> rowMax(tmp5)
[1] 466.02360 97.04910 83.86329 90.48399 85.82406 98.79388 95.58142
[8] NA 86.34637 96.74033
> rowMin(tmp5)
[1] 56.88962 52.89196 56.92801 53.32677 63.35608 57.74204 54.44614 NA
[9] 60.40903 58.41551
>
> colMeans(tmp5)
[1] 110.22410 69.69909 74.48280 71.27041 75.24345 73.37556 71.23381
[8] 68.91551 71.90124 73.07094 67.11776 NA 76.90690 70.60368
[15] 68.17847 71.88322 66.45310 71.74179 72.88841 74.11168
> colSums(tmp5)
[1] 1102.2410 696.9909 744.8280 712.7041 752.4345 733.7556 712.3381
[8] 689.1551 719.0124 730.7094 671.1776 NA 769.0690 706.0368
[15] 681.7847 718.8322 664.5310 717.4179 728.8841 741.1168
> colVars(tmp5)
[1] 15675.31834 86.68768 96.56056 46.09459 112.88395 111.60407
[7] 92.37380 76.07771 130.39759 73.43912 72.71386 NA
[13] 159.26768 63.86237 78.66414 92.58112 60.56888 40.11097
[19] 134.30213 151.87312
> colSd(tmp5)
[1] 125.201112 9.310622 9.826524 6.789299 10.624686 10.564283
[7] 9.611129 8.722254 11.419176 8.569663 8.527242 NA
[13] 12.620130 7.991394 8.869281 9.621908 7.782601 6.333322
[19] 11.588879 12.323681
> colMax(tmp5)
[1] 466.02360 82.29072 90.00680 85.82406 95.58142 96.74033 93.19210
[8] 82.73884 86.87516 83.86329 81.03058 NA 93.69086 82.53463
[15] 82.01205 88.42911 84.66172 83.94352 97.04910 98.79388
> colMin(tmp5)
[1] 58.73362 52.62371 54.44614 63.07050 57.74204 62.29479 59.26115 56.88962
[9] 56.45735 56.69741 57.30919 NA 52.89196 59.37463 57.46080 60.64640
[17] 57.62282 59.52292 56.92801 53.32677
>
> Max(tmp5,na.rm=TRUE)
[1] 466.0236
> Min(tmp5,na.rm=TRUE)
[1] 52.62371
> mean(tmp5,na.rm=TRUE)
[1] 73.42802
> Sum(tmp5,na.rm=TRUE)
[1] 14612.18
> Var(tmp5,na.rm=TRUE)
[1] 869.1813
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.62159 68.53974 72.06033 72.64064 72.78626 73.97841 69.45028 69.31087
[9] 71.61573 71.07049
> rowSums(tmp5,na.rm=TRUE)
[1] 1852.432 1370.795 1441.207 1452.813 1455.725 1479.568 1389.006 1316.907
[9] 1432.315 1421.410
> rowVars(tmp5,na.rm=TRUE)
[1] 7817.97147 106.65684 76.00552 97.18807 54.64733 128.81612
[7] 112.44463 88.76869 43.59607 77.13842
> rowSd(tmp5,na.rm=TRUE)
[1] 88.419294 10.327480 8.718114 9.858401 7.392384 11.349719 10.603991
[8] 9.421714 6.602732 8.782848
> rowMax(tmp5,na.rm=TRUE)
[1] 466.02360 97.04910 83.86329 90.48399 85.82406 98.79388 95.58142
[8] 88.42911 86.34637 96.74033
> rowMin(tmp5,na.rm=TRUE)
[1] 56.88962 52.89196 56.92801 53.32677 63.35608 57.74204 54.44614 52.62371
[9] 60.40903 58.41551
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.22410 69.69909 74.48280 71.27041 75.24345 73.37556 71.23381
[8] 68.91551 71.90124 73.07094 67.11776 68.79516 76.90690 70.60368
[15] 68.17847 71.88322 66.45310 71.74179 72.88841 74.11168
> colSums(tmp5,na.rm=TRUE)
[1] 1102.2410 696.9909 744.8280 712.7041 752.4345 733.7556 712.3381
[8] 689.1551 719.0124 730.7094 671.1776 619.1564 769.0690 706.0368
[15] 681.7847 718.8322 664.5310 717.4179 728.8841 741.1168
> colVars(tmp5,na.rm=TRUE)
[1] 15675.31834 86.68768 96.56056 46.09459 112.88395 111.60407
[7] 92.37380 76.07771 130.39759 73.43912 72.71386 29.97036
[13] 159.26768 63.86237 78.66414 92.58112 60.56888 40.11097
[19] 134.30213 151.87312
> colSd(tmp5,na.rm=TRUE)
[1] 125.201112 9.310622 9.826524 6.789299 10.624686 10.564283
[7] 9.611129 8.722254 11.419176 8.569663 8.527242 5.474519
[13] 12.620130 7.991394 8.869281 9.621908 7.782601 6.333322
[19] 11.588879 12.323681
> colMax(tmp5,na.rm=TRUE)
[1] 466.02360 82.29072 90.00680 85.82406 95.58142 96.74033 93.19210
[8] 82.73884 86.87516 83.86329 81.03058 77.55284 93.69086 82.53463
[15] 82.01205 88.42911 84.66172 83.94352 97.04910 98.79388
> colMin(tmp5,na.rm=TRUE)
[1] 58.73362 52.62371 54.44614 63.07050 57.74204 62.29479 59.26115 56.88962
[9] 56.45735 56.69741 57.30919 60.75793 52.89196 59.37463 57.46080 60.64640
[17] 57.62282 59.52292 56.92801 53.32677
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.62159 68.53974 72.06033 72.64064 72.78626 73.97841 69.45028 NaN
[9] 71.61573 71.07049
> rowSums(tmp5,na.rm=TRUE)
[1] 1852.432 1370.795 1441.207 1452.813 1455.725 1479.568 1389.006 0.000
[9] 1432.315 1421.410
> rowVars(tmp5,na.rm=TRUE)
[1] 7817.97147 106.65684 76.00552 97.18807 54.64733 128.81612
[7] 112.44463 NA 43.59607 77.13842
> rowSd(tmp5,na.rm=TRUE)
[1] 88.419294 10.327480 8.718114 9.858401 7.392384 11.349719 10.603991
[8] NA 6.602732 8.782848
> rowMax(tmp5,na.rm=TRUE)
[1] 466.02360 97.04910 83.86329 90.48399 85.82406 98.79388 95.58142
[8] NA 86.34637 96.74033
> rowMin(tmp5,na.rm=TRUE)
[1] 56.88962 52.89196 56.92801 53.32677 63.35608 57.74204 54.44614 NA
[9] 60.40903 58.41551
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.88854 71.59635 74.11315 71.47103 76.61079 74.23854 70.85110
[8] 68.74220 73.07586 74.89022 67.95049 NaN 76.16198 70.43265
[15] 68.38218 70.04478 66.47064 73.09944 72.61457 73.82244
> colSums(tmp5,na.rm=TRUE)
[1] 1024.9969 644.3672 667.0184 643.2392 689.4971 668.1469 637.6599
[8] 618.6798 657.6828 674.0120 611.5544 0.0000 685.4578 633.8938
[15] 615.4396 630.4030 598.2357 657.8950 653.5311 664.4020
> colVars(tmp5,na.rm=TRUE)
[1] 17483.66637 57.02800 107.09349 51.40364 105.96137 117.17624
[7] 102.27276 85.24951 131.17533 45.38395 74.00198 NA
[13] 172.93343 71.51610 88.03032 66.13062 68.13653 24.38863
[19] 150.24624 169.91609
> colSd(tmp5,na.rm=TRUE)
[1] 132.225816 7.551688 10.348599 7.169633 10.293754 10.824798
[7] 10.112999 9.233066 11.453180 6.736761 8.602440 NA
[13] 13.150416 8.456719 9.382447 8.132074 8.254485 4.938485
[19] 12.257497 13.035187
> colMax(tmp5,na.rm=TRUE)
[1] 466.02360 82.29072 90.00680 85.82406 95.58142 96.74033 93.19210
[8] 82.73884 86.87516 83.86329 81.03058 -Inf 93.69086 82.53463
[15] 82.01205 83.28821 84.66172 83.94352 97.04910 98.79388
> colMin(tmp5,na.rm=TRUE)
[1] 58.73362 61.32575 54.44614 63.07050 57.74204 62.29479 59.26115 56.88962
[9] 56.45735 61.85982 57.30919 Inf 52.89196 59.37463 57.46080 60.64640
[17] 57.62282 66.96856 56.92801 53.32677
>
>
>
>
> 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] 192.1751 231.6540 254.2661 243.6946 272.3785 151.9134 320.4623 167.6751
[9] 190.1883 151.0069
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 192.1751 231.6540 254.2661 243.6946 272.3785 151.9134 320.4623 167.6751
[9] 190.1883 151.0069
>
>
>
> 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] -1.136868e-13 5.684342e-14 -1.136868e-13 -5.684342e-14 -1.705303e-13
[6] 0.000000e+00 5.684342e-14 -4.547474e-13 8.526513e-14 -1.421085e-13
[11] -2.842171e-14 -2.273737e-13 2.842171e-14 8.526513e-14 0.000000e+00
[16] 5.684342e-14 1.136868e-13 2.842171e-14 5.684342e-14 -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)
+ }
10 13
6 16
1 5
4 17
3 12
4 5
3 14
1 9
6 2
4 12
10 20
3 17
10 2
8 4
5 15
6 2
2 6
10 10
6 16
7 8
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.862801
> Min(tmp)
[1] -2.920059
> mean(tmp)
[1] -0.09948617
> Sum(tmp)
[1] -9.948617
> Var(tmp)
[1] 1.149308
>
> rowMeans(tmp)
[1] -0.09948617
> rowSums(tmp)
[1] -9.948617
> rowVars(tmp)
[1] 1.149308
> rowSd(tmp)
[1] 1.072058
> rowMax(tmp)
[1] 2.862801
> rowMin(tmp)
[1] -2.920059
>
> colMeans(tmp)
[1] -0.338657126 -0.585929326 -0.848547316 1.074198328 -0.200152222
[6] 0.817265052 -0.466475094 0.970746339 1.546601584 -0.083820335
[11] 1.095083577 -0.314943503 -0.883859826 -1.560527214 0.036790704
[16] 0.314313106 -0.199741207 1.023900584 -0.471729893 -1.058230181
[21] 1.265909532 1.214256876 0.200203633 -0.029509293 0.223949305
[26] -0.379288510 -1.213825677 0.618256124 -0.747820861 0.678707696
[31] -1.089509261 -0.381181047 -0.669434868 2.013210215 -0.007425178
[36] -1.355434147 0.002719001 -1.696059946 -0.845062842 1.912360664
[41] 0.421289141 -0.988532457 1.791025763 -0.470717691 -0.542400759
[46] 1.785047483 -0.088706990 1.200099187 -2.178984747 -1.275005557
[51] -0.294128318 0.076286113 0.268320521 0.657953424 1.392797690
[56] -1.517636263 1.513923637 0.060460998 -1.692935161 -0.791744670
[61] 0.142606259 -1.842484074 1.231237718 -0.215152093 -1.105471852
[66] 0.816763874 -1.250989144 -0.265150513 -0.388244469 -0.076449262
[71] 1.266693495 -0.984252378 0.638706542 -0.227797101 0.364684702
[76] -1.084273576 -1.202259183 0.620903737 0.923360939 -0.128727921
[81] 2.862801408 -1.704418934 0.744695109 -0.455808885 0.325608664
[86] -0.492132302 1.285380561 0.294775353 -1.206517908 0.258810244
[91] 0.701499631 -1.738497287 -2.920058887 -1.387198608 -0.327581758
[96] -2.591953587 0.330677362 -0.965829683 0.226607450 0.669100953
> colSums(tmp)
[1] -0.338657126 -0.585929326 -0.848547316 1.074198328 -0.200152222
[6] 0.817265052 -0.466475094 0.970746339 1.546601584 -0.083820335
[11] 1.095083577 -0.314943503 -0.883859826 -1.560527214 0.036790704
[16] 0.314313106 -0.199741207 1.023900584 -0.471729893 -1.058230181
[21] 1.265909532 1.214256876 0.200203633 -0.029509293 0.223949305
[26] -0.379288510 -1.213825677 0.618256124 -0.747820861 0.678707696
[31] -1.089509261 -0.381181047 -0.669434868 2.013210215 -0.007425178
[36] -1.355434147 0.002719001 -1.696059946 -0.845062842 1.912360664
[41] 0.421289141 -0.988532457 1.791025763 -0.470717691 -0.542400759
[46] 1.785047483 -0.088706990 1.200099187 -2.178984747 -1.275005557
[51] -0.294128318 0.076286113 0.268320521 0.657953424 1.392797690
[56] -1.517636263 1.513923637 0.060460998 -1.692935161 -0.791744670
[61] 0.142606259 -1.842484074 1.231237718 -0.215152093 -1.105471852
[66] 0.816763874 -1.250989144 -0.265150513 -0.388244469 -0.076449262
[71] 1.266693495 -0.984252378 0.638706542 -0.227797101 0.364684702
[76] -1.084273576 -1.202259183 0.620903737 0.923360939 -0.128727921
[81] 2.862801408 -1.704418934 0.744695109 -0.455808885 0.325608664
[86] -0.492132302 1.285380561 0.294775353 -1.206517908 0.258810244
[91] 0.701499631 -1.738497287 -2.920058887 -1.387198608 -0.327581758
[96] -2.591953587 0.330677362 -0.965829683 0.226607450 0.669100953
> 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] -0.338657126 -0.585929326 -0.848547316 1.074198328 -0.200152222
[6] 0.817265052 -0.466475094 0.970746339 1.546601584 -0.083820335
[11] 1.095083577 -0.314943503 -0.883859826 -1.560527214 0.036790704
[16] 0.314313106 -0.199741207 1.023900584 -0.471729893 -1.058230181
[21] 1.265909532 1.214256876 0.200203633 -0.029509293 0.223949305
[26] -0.379288510 -1.213825677 0.618256124 -0.747820861 0.678707696
[31] -1.089509261 -0.381181047 -0.669434868 2.013210215 -0.007425178
[36] -1.355434147 0.002719001 -1.696059946 -0.845062842 1.912360664
[41] 0.421289141 -0.988532457 1.791025763 -0.470717691 -0.542400759
[46] 1.785047483 -0.088706990 1.200099187 -2.178984747 -1.275005557
[51] -0.294128318 0.076286113 0.268320521 0.657953424 1.392797690
[56] -1.517636263 1.513923637 0.060460998 -1.692935161 -0.791744670
[61] 0.142606259 -1.842484074 1.231237718 -0.215152093 -1.105471852
[66] 0.816763874 -1.250989144 -0.265150513 -0.388244469 -0.076449262
[71] 1.266693495 -0.984252378 0.638706542 -0.227797101 0.364684702
[76] -1.084273576 -1.202259183 0.620903737 0.923360939 -0.128727921
[81] 2.862801408 -1.704418934 0.744695109 -0.455808885 0.325608664
[86] -0.492132302 1.285380561 0.294775353 -1.206517908 0.258810244
[91] 0.701499631 -1.738497287 -2.920058887 -1.387198608 -0.327581758
[96] -2.591953587 0.330677362 -0.965829683 0.226607450 0.669100953
> colMin(tmp)
[1] -0.338657126 -0.585929326 -0.848547316 1.074198328 -0.200152222
[6] 0.817265052 -0.466475094 0.970746339 1.546601584 -0.083820335
[11] 1.095083577 -0.314943503 -0.883859826 -1.560527214 0.036790704
[16] 0.314313106 -0.199741207 1.023900584 -0.471729893 -1.058230181
[21] 1.265909532 1.214256876 0.200203633 -0.029509293 0.223949305
[26] -0.379288510 -1.213825677 0.618256124 -0.747820861 0.678707696
[31] -1.089509261 -0.381181047 -0.669434868 2.013210215 -0.007425178
[36] -1.355434147 0.002719001 -1.696059946 -0.845062842 1.912360664
[41] 0.421289141 -0.988532457 1.791025763 -0.470717691 -0.542400759
[46] 1.785047483 -0.088706990 1.200099187 -2.178984747 -1.275005557
[51] -0.294128318 0.076286113 0.268320521 0.657953424 1.392797690
[56] -1.517636263 1.513923637 0.060460998 -1.692935161 -0.791744670
[61] 0.142606259 -1.842484074 1.231237718 -0.215152093 -1.105471852
[66] 0.816763874 -1.250989144 -0.265150513 -0.388244469 -0.076449262
[71] 1.266693495 -0.984252378 0.638706542 -0.227797101 0.364684702
[76] -1.084273576 -1.202259183 0.620903737 0.923360939 -0.128727921
[81] 2.862801408 -1.704418934 0.744695109 -0.455808885 0.325608664
[86] -0.492132302 1.285380561 0.294775353 -1.206517908 0.258810244
[91] 0.701499631 -1.738497287 -2.920058887 -1.387198608 -0.327581758
[96] -2.591953587 0.330677362 -0.965829683 0.226607450 0.669100953
> colMedians(tmp)
[1] -0.338657126 -0.585929326 -0.848547316 1.074198328 -0.200152222
[6] 0.817265052 -0.466475094 0.970746339 1.546601584 -0.083820335
[11] 1.095083577 -0.314943503 -0.883859826 -1.560527214 0.036790704
[16] 0.314313106 -0.199741207 1.023900584 -0.471729893 -1.058230181
[21] 1.265909532 1.214256876 0.200203633 -0.029509293 0.223949305
[26] -0.379288510 -1.213825677 0.618256124 -0.747820861 0.678707696
[31] -1.089509261 -0.381181047 -0.669434868 2.013210215 -0.007425178
[36] -1.355434147 0.002719001 -1.696059946 -0.845062842 1.912360664
[41] 0.421289141 -0.988532457 1.791025763 -0.470717691 -0.542400759
[46] 1.785047483 -0.088706990 1.200099187 -2.178984747 -1.275005557
[51] -0.294128318 0.076286113 0.268320521 0.657953424 1.392797690
[56] -1.517636263 1.513923637 0.060460998 -1.692935161 -0.791744670
[61] 0.142606259 -1.842484074 1.231237718 -0.215152093 -1.105471852
[66] 0.816763874 -1.250989144 -0.265150513 -0.388244469 -0.076449262
[71] 1.266693495 -0.984252378 0.638706542 -0.227797101 0.364684702
[76] -1.084273576 -1.202259183 0.620903737 0.923360939 -0.128727921
[81] 2.862801408 -1.704418934 0.744695109 -0.455808885 0.325608664
[86] -0.492132302 1.285380561 0.294775353 -1.206517908 0.258810244
[91] 0.701499631 -1.738497287 -2.920058887 -1.387198608 -0.327581758
[96] -2.591953587 0.330677362 -0.965829683 0.226607450 0.669100953
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.3386571 -0.5859293 -0.8485473 1.074198 -0.2001522 0.8172651 -0.4664751
[2,] -0.3386571 -0.5859293 -0.8485473 1.074198 -0.2001522 0.8172651 -0.4664751
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.9707463 1.546602 -0.08382034 1.095084 -0.3149435 -0.8838598 -1.560527
[2,] 0.9707463 1.546602 -0.08382034 1.095084 -0.3149435 -0.8838598 -1.560527
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.0367907 0.3143131 -0.1997412 1.023901 -0.4717299 -1.05823 1.26591
[2,] 0.0367907 0.3143131 -0.1997412 1.023901 -0.4717299 -1.05823 1.26591
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.214257 0.2002036 -0.02950929 0.2239493 -0.3792885 -1.213826 0.6182561
[2,] 1.214257 0.2002036 -0.02950929 0.2239493 -0.3792885 -1.213826 0.6182561
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.7478209 0.6787077 -1.089509 -0.381181 -0.6694349 2.01321 -0.007425178
[2,] -0.7478209 0.6787077 -1.089509 -0.381181 -0.6694349 2.01321 -0.007425178
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.355434 0.002719001 -1.69606 -0.8450628 1.912361 0.4212891 -0.9885325
[2,] -1.355434 0.002719001 -1.69606 -0.8450628 1.912361 0.4212891 -0.9885325
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 1.791026 -0.4707177 -0.5424008 1.785047 -0.08870699 1.200099 -2.178985
[2,] 1.791026 -0.4707177 -0.5424008 1.785047 -0.08870699 1.200099 -2.178985
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -1.275006 -0.2941283 0.07628611 0.2683205 0.6579534 1.392798 -1.517636
[2,] -1.275006 -0.2941283 0.07628611 0.2683205 0.6579534 1.392798 -1.517636
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 1.513924 0.060461 -1.692935 -0.7917447 0.1426063 -1.842484 1.231238
[2,] 1.513924 0.060461 -1.692935 -0.7917447 0.1426063 -1.842484 1.231238
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.2151521 -1.105472 0.8167639 -1.250989 -0.2651505 -0.3882445 -0.07644926
[2,] -0.2151521 -1.105472 0.8167639 -1.250989 -0.2651505 -0.3882445 -0.07644926
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.266693 -0.9842524 0.6387065 -0.2277971 0.3646847 -1.084274 -1.202259
[2,] 1.266693 -0.9842524 0.6387065 -0.2277971 0.3646847 -1.084274 -1.202259
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.6209037 0.9233609 -0.1287279 2.862801 -1.704419 0.7446951 -0.4558089
[2,] 0.6209037 0.9233609 -0.1287279 2.862801 -1.704419 0.7446951 -0.4558089
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.3256087 -0.4921323 1.285381 0.2947754 -1.206518 0.2588102 0.7014996
[2,] 0.3256087 -0.4921323 1.285381 0.2947754 -1.206518 0.2588102 0.7014996
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.738497 -2.920059 -1.387199 -0.3275818 -2.591954 0.3306774 -0.9658297
[2,] -1.738497 -2.920059 -1.387199 -0.3275818 -2.591954 0.3306774 -0.9658297
[,99] [,100]
[1,] 0.2266074 0.669101
[2,] 0.2266074 0.669101
>
>
> Max(tmp2)
[1] 3.158198
> Min(tmp2)
[1] -2.551728
> mean(tmp2)
[1] 0.04831837
> Sum(tmp2)
[1] 4.831837
> Var(tmp2)
[1] 1.077863
>
> rowMeans(tmp2)
[1] 1.322655852 -0.459177730 -0.864552866 -0.813915230 -0.127447936
[6] -0.577186510 0.554132228 -2.117823499 -0.165336930 0.813731897
[11] 1.263262194 1.290984244 -1.397773896 -0.042295151 0.178142999
[16] 0.096038457 -0.261570352 2.191015240 0.990309567 0.157062473
[21] 0.251791205 -0.878663165 0.330019101 0.268745992 -0.433224055
[26] 0.256385867 0.591783147 -1.601105247 -1.189873327 0.375723436
[31] -0.237494957 0.111645337 -0.388698660 0.040681582 0.973057356
[36] -0.135251009 -1.541762152 1.189034156 1.229992159 -0.572982593
[41] -0.823608434 -0.565942109 0.975939718 0.677277599 0.909302675
[46] -1.147306959 1.150801887 -1.670438292 -0.867825706 0.202763451
[51] -0.789167226 -0.103484376 -1.254974147 1.421264942 -0.518466092
[56] 3.158197871 0.241331898 0.931328107 0.665474939 0.542874551
[61] -2.042276057 -1.705797301 1.081348993 1.923398295 -0.400548230
[66] 0.422981310 -0.188844003 -0.093993400 1.361537582 -1.794147659
[71] -0.014612750 0.017209296 1.032830141 1.518768223 1.833702149
[76] 1.477455972 0.464592232 -1.485537180 -0.309571691 1.418159691
[81] 1.282481175 -1.328894355 -0.704371109 -2.551727793 0.004169493
[86] -0.127045828 0.404626687 -0.567632040 1.005681231 0.151178152
[91] 0.815284396 -0.461694186 -0.212345204 0.707699082 0.535760561
[96] -1.656978756 0.681090596 -0.535091990 -0.450470765 -0.481941901
> rowSums(tmp2)
[1] 1.322655852 -0.459177730 -0.864552866 -0.813915230 -0.127447936
[6] -0.577186510 0.554132228 -2.117823499 -0.165336930 0.813731897
[11] 1.263262194 1.290984244 -1.397773896 -0.042295151 0.178142999
[16] 0.096038457 -0.261570352 2.191015240 0.990309567 0.157062473
[21] 0.251791205 -0.878663165 0.330019101 0.268745992 -0.433224055
[26] 0.256385867 0.591783147 -1.601105247 -1.189873327 0.375723436
[31] -0.237494957 0.111645337 -0.388698660 0.040681582 0.973057356
[36] -0.135251009 -1.541762152 1.189034156 1.229992159 -0.572982593
[41] -0.823608434 -0.565942109 0.975939718 0.677277599 0.909302675
[46] -1.147306959 1.150801887 -1.670438292 -0.867825706 0.202763451
[51] -0.789167226 -0.103484376 -1.254974147 1.421264942 -0.518466092
[56] 3.158197871 0.241331898 0.931328107 0.665474939 0.542874551
[61] -2.042276057 -1.705797301 1.081348993 1.923398295 -0.400548230
[66] 0.422981310 -0.188844003 -0.093993400 1.361537582 -1.794147659
[71] -0.014612750 0.017209296 1.032830141 1.518768223 1.833702149
[76] 1.477455972 0.464592232 -1.485537180 -0.309571691 1.418159691
[81] 1.282481175 -1.328894355 -0.704371109 -2.551727793 0.004169493
[86] -0.127045828 0.404626687 -0.567632040 1.005681231 0.151178152
[91] 0.815284396 -0.461694186 -0.212345204 0.707699082 0.535760561
[96] -1.656978756 0.681090596 -0.535091990 -0.450470765 -0.481941901
> 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] 1.322655852 -0.459177730 -0.864552866 -0.813915230 -0.127447936
[6] -0.577186510 0.554132228 -2.117823499 -0.165336930 0.813731897
[11] 1.263262194 1.290984244 -1.397773896 -0.042295151 0.178142999
[16] 0.096038457 -0.261570352 2.191015240 0.990309567 0.157062473
[21] 0.251791205 -0.878663165 0.330019101 0.268745992 -0.433224055
[26] 0.256385867 0.591783147 -1.601105247 -1.189873327 0.375723436
[31] -0.237494957 0.111645337 -0.388698660 0.040681582 0.973057356
[36] -0.135251009 -1.541762152 1.189034156 1.229992159 -0.572982593
[41] -0.823608434 -0.565942109 0.975939718 0.677277599 0.909302675
[46] -1.147306959 1.150801887 -1.670438292 -0.867825706 0.202763451
[51] -0.789167226 -0.103484376 -1.254974147 1.421264942 -0.518466092
[56] 3.158197871 0.241331898 0.931328107 0.665474939 0.542874551
[61] -2.042276057 -1.705797301 1.081348993 1.923398295 -0.400548230
[66] 0.422981310 -0.188844003 -0.093993400 1.361537582 -1.794147659
[71] -0.014612750 0.017209296 1.032830141 1.518768223 1.833702149
[76] 1.477455972 0.464592232 -1.485537180 -0.309571691 1.418159691
[81] 1.282481175 -1.328894355 -0.704371109 -2.551727793 0.004169493
[86] -0.127045828 0.404626687 -0.567632040 1.005681231 0.151178152
[91] 0.815284396 -0.461694186 -0.212345204 0.707699082 0.535760561
[96] -1.656978756 0.681090596 -0.535091990 -0.450470765 -0.481941901
> rowMin(tmp2)
[1] 1.322655852 -0.459177730 -0.864552866 -0.813915230 -0.127447936
[6] -0.577186510 0.554132228 -2.117823499 -0.165336930 0.813731897
[11] 1.263262194 1.290984244 -1.397773896 -0.042295151 0.178142999
[16] 0.096038457 -0.261570352 2.191015240 0.990309567 0.157062473
[21] 0.251791205 -0.878663165 0.330019101 0.268745992 -0.433224055
[26] 0.256385867 0.591783147 -1.601105247 -1.189873327 0.375723436
[31] -0.237494957 0.111645337 -0.388698660 0.040681582 0.973057356
[36] -0.135251009 -1.541762152 1.189034156 1.229992159 -0.572982593
[41] -0.823608434 -0.565942109 0.975939718 0.677277599 0.909302675
[46] -1.147306959 1.150801887 -1.670438292 -0.867825706 0.202763451
[51] -0.789167226 -0.103484376 -1.254974147 1.421264942 -0.518466092
[56] 3.158197871 0.241331898 0.931328107 0.665474939 0.542874551
[61] -2.042276057 -1.705797301 1.081348993 1.923398295 -0.400548230
[66] 0.422981310 -0.188844003 -0.093993400 1.361537582 -1.794147659
[71] -0.014612750 0.017209296 1.032830141 1.518768223 1.833702149
[76] 1.477455972 0.464592232 -1.485537180 -0.309571691 1.418159691
[81] 1.282481175 -1.328894355 -0.704371109 -2.551727793 0.004169493
[86] -0.127045828 0.404626687 -0.567632040 1.005681231 0.151178152
[91] 0.815284396 -0.461694186 -0.212345204 0.707699082 0.535760561
[96] -1.656978756 0.681090596 -0.535091990 -0.450470765 -0.481941901
>
> colMeans(tmp2)
[1] 0.04831837
> colSums(tmp2)
[1] 4.831837
> colVars(tmp2)
[1] 1.077863
> colSd(tmp2)
[1] 1.038202
> colMax(tmp2)
[1] 3.158198
> colMin(tmp2)
[1] -2.551728
> colMedians(tmp2)
[1] 0.02894544
> colRanges(tmp2)
[,1]
[1,] -2.551728
[2,] 3.158198
>
> 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] 3.0441374 -0.2394571 0.6382617 -1.6866814 -0.8492223 -7.5749083
[7] 2.6700655 -2.7331756 4.1402832 3.1573215
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.92198751
[2,] -0.06960052
[3,] 0.29641362
[4,] 0.79920680
[5,] 1.17170993
>
> rowApply(tmp,sum)
[1] 1.1302683 -0.4714280 0.3635275 2.5877285 -3.7637735 0.6346763
[7] -1.5164590 4.0738552 -0.5238911 -1.9478797
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 8 10 2 8 4 5 8 6 6
[2,] 5 3 8 4 6 10 1 5 4 7
[3,] 3 7 1 6 5 7 6 7 2 8
[4,] 6 6 4 8 1 5 3 6 3 10
[5,] 2 2 5 3 10 1 10 3 10 4
[6,] 1 4 2 7 3 3 8 1 1 1
[7,] 4 9 6 5 7 2 4 10 8 2
[8,] 7 5 7 1 9 6 2 4 5 5
[9,] 10 10 9 10 2 9 7 9 7 3
[10,] 8 1 3 9 4 8 9 2 9 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -3.08992124 0.02057588 3.59471283 2.54313247 1.02264894 3.02787455
[7] -3.11097725 -0.40628581 0.47007198 -1.31067472 -0.60151353 -2.51572757
[13] 0.87728691 3.60300305 -1.22428031 0.78439393 -3.95802347 0.79848304
[19] 3.67000583 -5.84260561
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.66413523
[2,] -1.20950511
[3,] -0.59882469
[4,] -0.01448195
[5,] 0.39702574
>
> rowApply(tmp,sum)
[1] 4.6707743 -1.1625421 -0.1721491 -7.7422004 2.7582971
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 9 4 5 3 12
[2,] 19 7 13 7 2
[3,] 16 18 15 20 4
[4,] 18 10 12 12 16
[5,] 2 11 17 16 13
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.01448195 1.9455148 0.8579178 1.25986346 -0.8715879 0.94426851
[2,] -1.20950511 -0.1582854 1.6889133 0.02320837 0.1777948 1.69869430
[3,] -0.59882469 0.4753630 0.6955276 0.44558997 0.7354220 0.04548085
[4,] -1.66413523 -0.7242242 1.2583696 -0.16690547 0.5486401 1.14433135
[5,] 0.39702574 -1.5177924 -0.9060154 0.98137614 0.4323800 -0.80490046
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.4684414 -0.3879288 -0.58096020 -0.7120932 -0.04464985 0.1439728
[2,] -2.9542788 0.1999298 0.69867805 -0.4826352 0.31900411 -2.0191118
[3,] 0.5870511 -0.5799025 0.72138725 -1.3921322 0.87803345 -2.5206465
[4,] 0.6456869 -0.6843345 -0.32424946 -0.1258350 -1.62621154 0.4094272
[5,] -0.9209950 1.0459502 -0.04478367 1.4020208 -0.12768971 1.4706307
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.2451851 2.76018683 -1.5672952 0.2519419 0.45325442 0.1712820
[2,] -0.1335996 -0.07087887 0.6423957 0.2886187 -1.68482927 -0.2901052
[3,] -0.8045554 -0.14100935 0.2217993 1.7339116 0.14959836 0.0364109
[4,] 0.6902063 -0.97693758 -0.2193557 -1.2790737 -2.89819185 0.1982982
[5,] 0.8800504 2.03164203 -0.3018245 -0.2110046 0.02214486 0.6825971
[,19] [,20]
[1,] 0.3347073 -0.04988223
[2,] 1.8564436 0.24700644
[3,] 1.3622230 -2.22287677
[4,] -0.2143454 -1.73336058
[5,] 0.3309773 -2.08349247
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.7-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-3.7-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 639 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 554 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.8 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 1.290864 -0.1510287 -0.04975126 1.147651 0.9863728 1.680495 0.08719715
col8 col9 col10 col11 col12 col13 col14
row1 -0.04914625 -1.48388 -0.5508953 0.03279938 -0.2483935 -1.184987 0.09867963
col15 col16 col17 col18 col19 col20
row1 -0.7750183 1.027831 -0.27274 -0.5919857 -0.5054031 -0.191915
> tmp[,"col10"]
col10
row1 -0.5508953
row2 -2.2585549
row3 -0.2468932
row4 0.4648486
row5 0.7234608
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 1.2908639 -0.1510287 -0.04975126 1.14765058 0.9863728 1.6804945
row5 0.2938652 -0.1416761 -1.11167510 0.09414282 -1.0943074 -0.3235116
col7 col8 col9 col10 col11 col12
row1 0.08719715 -0.04914625 -1.4838801 -0.5508953 0.03279938 -0.2483935
row5 2.59338167 0.90592984 -0.3175125 0.7234608 -1.23440896 0.3149628
col13 col14 col15 col16 col17 col18 col19
row1 -1.184987 0.09867963 -0.7750183 1.027831 -0.2727400 -0.5919857 -0.5054031
row5 -1.256738 0.88185997 -1.5752584 1.966252 0.4206613 0.8413154 -1.5713886
col20
row1 -0.191915
row5 1.053695
> tmp[,c("col6","col20")]
col6 col20
row1 1.6804945 -0.1919150
row2 -0.2264414 -0.2565162
row3 -0.2175358 0.8411783
row4 -0.5833450 -1.3134983
row5 -0.3235116 1.0536951
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.6804945 -0.191915
row5 -0.3235116 1.053695
>
>
>
>
> 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 52.58262 49.28534 49.52899 48.86928 49.42192 104.8833 48.91125 50.65688
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.76723 49.47797 51.14205 50.92296 49.47821 48.61301 49.44805 49.3569
col17 col18 col19 col20
row1 49.91218 49.61886 51.20523 104.8105
> tmp[,"col10"]
col10
row1 49.47797
row2 28.85038
row3 30.01080
row4 28.70904
row5 50.36125
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 52.58262 49.28534 49.52899 48.86928 49.42192 104.8833 48.91125 50.65688
row5 49.72224 50.59457 49.13686 51.16057 49.34395 105.1884 49.03248 50.05134
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.76723 49.47797 51.14205 50.92296 49.47821 48.61301 49.44805 49.3569
row5 51.48325 50.36125 51.11233 51.71286 50.34015 50.46777 50.74691 49.2745
col17 col18 col19 col20
row1 49.91218 49.61886 51.20523 104.8105
row5 50.76843 50.74695 49.97607 104.3769
> tmp[,c("col6","col20")]
col6 col20
row1 104.88333 104.81049
row2 73.26795 75.34247
row3 76.61517 75.14581
row4 74.07985 75.22141
row5 105.18841 104.37686
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.8833 104.8105
row5 105.1884 104.3769
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.8833 104.8105
row5 105.1884 104.3769
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.2880304
[2,] -1.0757489
[3,] -1.7007176
[4,] -1.6891421
[5,] -0.2371273
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.4761384 0.7538197
[2,] 1.1471380 -1.7269589
[3,] 0.5405262 -0.5496592
[4,] 1.5607505 -1.8332464
[5,] -1.0184708 -0.4211095
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.7423256 2.9488081
[2,] -1.1793920 -0.2036292
[3,] 1.7810733 -1.9704682
[4,] -0.5669900 0.2673406
[5,] 1.0844116 1.5869898
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.7423256
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.7423256
[2,] -1.1793920
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 -0.81412123 -1.0553070 0.29396943 1.7913752 0.3096088 0.4356529
row1 -0.02436281 -0.2191899 0.06109885 -0.6201808 0.9707726 -0.3829250
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.252075 -0.7632401 -0.5618810 1.288265 -0.1891233 0.3084438 0.5173244
row1 -2.327132 -1.0290638 0.6212426 1.166215 0.5681244 -0.4834974 1.3740933
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.3409266 0.5828332 -1.9900721 -0.9796561 1.1987110 -0.08651321 1.5359752
row1 0.9218703 0.5976345 0.4276389 -0.3435166 0.9995272 0.57321611 0.7069964
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -2.929855 -0.3985388 -0.03426779 0.09810844 1.466827 1.568316 1.626472
[,8] [,9] [,10]
row2 1.496931 0.1817653 0.9064871
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.3539867 -0.1153164 -2.680171 -0.9644139 -1.166805 0.04053956 -0.2332241
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.291262 -0.7826923 0.6371744 0.3766733 0.198999 1.365396 0.3487061
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.4529266 0.3885036 0.8070899 1.42547 0.7953009 0.54169
>
>
> 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: 0x7fcbadc0c0a0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc2949c235"
[2] "/Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc296d3ac0"
[3] "/Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc422c287f"
[4] "/Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc6116cbc9"
[5] "/Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc1f9d2aeb"
[6] "/Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc76cba84"
[7] "/Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc734933ea"
[8] "/Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc4aef82c7"
[9] "/Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc3272fd40"
[10] "/Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc1b508ea0"
[11] "/Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc45c3b862"
[12] "/Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc347e4db6"
[13] "/Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc502002a6"
[14] "/Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc658e0962"
[15] "/Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM2dc500a3504"
>
>
> ### 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: 0x7fcbaac19c20>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x7fcbaac19c20>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x7fcbaac19c20>
> rowMedians(tmp)
[1] 0.501586275 0.033966549 -0.584040399 0.544445025 0.556611398
[6] 0.334328542 0.128396754 0.368938092 0.351678117 -0.244746079
[11] 0.079248289 0.099934979 0.026138984 0.250737978 -0.137949144
[16] -0.176068291 0.030739386 0.332727936 0.170773941 0.446443137
[21] 0.025646543 0.474999099 -0.467688993 0.319711588 0.051220634
[26] 0.534292257 0.294228828 -0.649523071 -0.302578785 0.127988909
[31] -0.161684046 0.511827514 -0.065645192 0.082298652 -0.428455030
[36] 0.244572121 0.060136410 0.019069692 -0.162787884 0.162855852
[41] -0.269371407 0.169295274 -0.269211867 0.156294389 -0.359357794
[46] 0.084479988 -0.327546479 -0.493838657 -0.014026814 0.464407293
[51] -0.060802178 -0.331233928 0.532093326 0.042897225 -0.470428172
[56] 0.349935345 -0.114466247 -0.209616670 -0.194624279 0.084932568
[61] 0.588740237 -0.084025056 -0.044005985 0.503620497 0.083180980
[66] -0.592764289 -0.313560068 0.186319729 0.194286480 0.457202158
[71] -0.018005474 -0.052543118 -0.494014262 -0.230496959 0.093787796
[76] -0.146002378 -0.446185285 0.311927965 0.378634128 0.653949425
[81] 0.561964475 0.548719743 0.027010884 -0.052610074 0.238689858
[86] 0.429889146 -0.015366031 -0.361666923 -0.136518881 0.181983553
[91] -0.067107964 0.192666166 0.375362045 -0.553025702 0.339287578
[96] 0.118532149 0.324008860 -0.039796232 0.441792755 0.013301525
[101] 0.050023329 0.275221125 0.352281109 -0.090892936 -0.310650751
[106] 0.175915098 -0.271024787 -0.060668884 -0.187083174 0.282687353
[111] 0.264993922 -0.321067893 -0.036906597 -0.110065665 0.630819496
[116] -0.283210171 0.299716360 -0.301852718 -0.050639719 -0.053621687
[121] 0.044591222 0.031676532 0.803416652 -0.057314398 -0.313507275
[126] 0.175083808 0.032563467 -0.218021673 -0.151421525 -0.102215952
[131] -0.160979184 -0.239334564 0.087319282 0.140289804 -0.398277851
[136] -0.655177334 0.057303233 -0.128024385 -0.022949389 0.184864807
[141] 0.594106637 -0.351873345 0.268299614 0.094327794 0.052778003
[146] 0.289218853 0.130548173 0.109094440 0.022859619 -0.114743998
[151] 0.257427852 0.461158609 -0.186704735 0.407572786 -0.200425401
[156] -0.168854129 -0.031994938 0.160554677 0.503691284 -0.681824987
[161] -0.282379932 0.200935511 -0.274183562 0.608135224 0.040435220
[166] -0.412746681 -0.199902178 -0.553236485 -0.232354386 -0.428829762
[171] 0.062411831 -0.637885640 -0.276346204 0.006289865 -0.200165617
[176] 1.095540858 0.138668663 0.251446026 0.368880968 -0.039247954
[181] -0.294574585 -0.124908635 -0.269989983 -0.142097160 -0.323566244
[186] 0.050481370 0.366906926 0.091162362 -0.134566800 0.261205271
[191] -0.090621824 0.440777415 -0.013587761 0.014475757 0.340935242
[196] 0.144449149 -0.271118164 0.050260486 -0.005471406 0.069765827
[201] -0.183357981 -0.107488530 -0.039223518 -0.017429598 -0.450453479
[206] 0.069728900 -0.190109954 0.095804318 -0.149688571 -0.166068356
[211] 0.445812254 0.083681352 -0.348775947 -0.100593254 0.464131077
[216] 0.181475785 0.113735447 0.188820751 0.282217326 -0.658315527
[221] -0.312043867 -0.043159985 0.145606785 0.015928871 -0.160980490
[226] -0.650212628 -0.350908178 0.552947860 0.396707870 0.078250209
>
> proc.time()
user system elapsed
4.239 6.764 11.344
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 3.5.1 Patched (2018-07-12 r74967) -- "Feather Spray"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin15.6.0 (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: 0x7ff90f073040>
> .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: 0x7ff90f073040>
> .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: 0x7ff90f073040>
> .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: 0x7ff90f073040>
> 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: 0x7ff90b6017a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7ff90b6017a0>
> .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: 0x7ff90b6017a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7ff90b6017a0>
> .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: 0x7ff90b6017a0>
> 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: 0x7ff90b603e10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7ff90b603e10>
> .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: 0x7ff90b603e10>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x7ff90b603e10>
> .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: 0x7ff90b603e10>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x7ff90b603e10>
> .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: 0x7ff90b603e10>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x7ff90b603e10>
> .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: 0x7ff90b603e10>
> 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: 0x7ff90b6040a0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x7ff90b6040a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7ff90b6040a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7ff90b6040a0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile73816303a11" "BufferedMatrixFile7382e4e4b47"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile73816303a11" "BufferedMatrixFile7382e4e4b47"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x7ff9149000e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7ff9149000e0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x7ff9149000e0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x7ff9149000e0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x7ff9149000e0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x7ff9149000e0>
> .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: 0x7ff9087049e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7ff9087049e0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x7ff9087049e0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x7ff9087049e0>
> 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: 0x7ff9084072c0>
> .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: 0x7ff9084072c0>
> rm(P)
>
> proc.time()
user system elapsed
0.419 0.102 0.488
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 3.5.1 Patched (2018-07-12 r74967) -- "Feather Spray"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin15.6.0 (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.
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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
0.382 0.068 0.424