Ben Bolstad
| Snapshot Date: 2019-04-08 17:01:18 -0400 (Mon, 08 Apr 2019) |
| URL: https://git.bioconductor.org/packages/BufferedMatrix |
| Branch: master |
| Last Commit: eca2e36 |
| Last Changed Date: 2018-10-30 11:54:27 -0400 (Tue, 30 Oct 2018) |
| Back to Multiple platform build/check report for BioC 3.9 |
|
This page was generated on 2019-04-09 12:53:00 -0400 (Tue, 09 Apr 2019).
| Package 190/1703 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||
| BufferedMatrix 1.47.0 Ben Bolstad
| malbec2 | Linux (Ubuntu 18.04.2 LTS) / x86_64 | OK | OK | OK | | ||||||
| tokay2 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||
| celaya2 | OS X 10.11.6 El Capitan / x86_64 | OK | OK | [ OK ] | OK | | ||||||
| merida2 | OS X 10.11.6 El Capitan / x86_64 | OK | OK | OK | OK |
| Package: BufferedMatrix |
| Version: 1.47.0 |
| 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_1.47.0.tar.gz |
| StartedAt: 2019-04-09 00:19:24 -0400 (Tue, 09 Apr 2019) |
| EndedAt: 2019-04-09 00:20:25 -0400 (Tue, 09 Apr 2019) |
| EllapsedTime: 61.2 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_1.47.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck’ * using R Under development (unstable) (2019-03-18 r76245) * 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 ‘1.47.0’ * 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-3.9-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/3.6/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** 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/3.6/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 Under development (unstable) (2019-03-18 r76245) -- "Unsuffered Consequences"
Copyright (C) 2019 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
0.504 0.209 0.662
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2019-03-18 r76245) -- "Unsuffered Consequences"
Copyright (C) 2019 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-3.9-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 414490 22.2 875445 46.8 NA 617622 33.0
Vcells 745592 5.7 8388608 64.0 57344 1816447 13.9
>
>
>
>
> ##
> ## 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 Apr 9 00:19:54 2019"
> 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 Apr 9 00:19:55 2019"
>
>
> 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: 0x7fb6cd300180>
>
>
>
> 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 Apr 9 00:20:00 2019"
> 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 Apr 9 00:20:02 2019"
>
> ColMode(tmp2)
<pointer: 0x7fb6cd300180>
>
>
>
> ### 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,] 98.288500 0.9808941 -0.04700253 0.8961255
[2,] -1.888465 -0.9743595 -0.74275519 2.5167847
[3,] 2.627225 1.8139640 0.94128900 -1.3138863
[4,] 1.133381 -0.9147736 -1.21229712 0.1350726
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.9-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,] 98.288500 0.9808941 0.04700253 0.8961255
[2,] 1.888465 0.9743595 0.74275519 2.5167847
[3,] 2.627225 1.8139640 0.94128900 1.3138863
[4,] 1.133381 0.9147736 1.21229712 0.1350726
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.9-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,] 9.914056 0.9904010 0.2168007 0.9466391
[2,] 1.374214 0.9870965 0.8618325 1.5864378
[3,] 1.620872 1.3468348 0.9702005 1.1462488
[4,] 1.064604 0.9564380 1.1010436 0.3675222
>
> 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-3.9-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,] 222.42906 35.88490 27.21501 35.36252
[2,] 40.63061 35.84532 34.36108 43.38116
[3,] 43.83594 40.28231 35.64329 37.77637
[4,] 36.77942 35.47915 37.22273 28.81029
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x7fb6c8fd6500>
> exp(tmp5)
<pointer: 0x7fb6c8fd6500>
> log(tmp5,2)
<pointer: 0x7fb6c8fd6500>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 462.9569
> Min(tmp5)
[1] 53.87189
> mean(tmp5)
[1] 72.66982
> Sum(tmp5)
[1] 14533.96
> Var(tmp5)
[1] 840.8899
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.50311 74.27395 74.27175 66.71006 71.89139 70.22046 66.82452 71.31080
[9] 70.29714 71.39507
> rowSums(tmp5)
[1] 1790.062 1485.479 1485.435 1334.201 1437.828 1404.409 1336.490 1426.216
[9] 1405.943 1427.901
> rowVars(tmp5)
[1] 7809.44435 67.38155 102.52330 48.76081 91.98797 78.68124
[7] 25.06386 80.74447 53.60715 55.45008
> rowSd(tmp5)
[1] 88.371061 8.208626 10.125379 6.982894 9.591036 8.870245 5.006382
[8] 8.985793 7.321690 7.446481
> rowMax(tmp5)
[1] 462.95694 90.29221 91.23877 78.22113 87.17170 88.86445 74.24625
[8] 84.40938 87.56506 89.59556
> rowMin(tmp5)
[1] 55.27765 58.87370 56.06899 57.92582 53.87383 54.79210 57.24660 53.87189
[9] 59.13332 60.53703
>
> colMeans(tmp5)
[1] 114.27416 72.78816 72.82713 73.07616 69.81651 68.70443 74.43546
[8] 72.96526 69.63435 71.95669 69.62472 69.12015 71.82118 65.51447
[15] 66.26452 67.97374 68.06872 71.55340 71.81517 71.16208
> colSums(tmp5)
[1] 1142.7416 727.8816 728.2713 730.7616 698.1651 687.0443 744.3546
[8] 729.6526 696.3435 719.5669 696.2472 691.2015 718.2118 655.1447
[15] 662.6452 679.7374 680.6872 715.5340 718.1517 711.6208
> colVars(tmp5)
[1] 15082.08145 33.97409 94.22804 142.93383 64.19483 60.59921
[7] 121.97807 106.59684 60.54533 41.97225 73.09783 132.02642
[13] 19.89370 28.21366 43.12257 59.36026 62.38220 71.43020
[19] 81.33645 68.36425
> colSd(tmp5)
[1] 122.809126 5.828729 9.707113 11.955494 8.012168 7.784550
[7] 11.044368 10.324575 7.781088 6.478600 8.549727 11.490275
[13] 4.460235 5.311654 6.566777 7.704561 7.898240 8.451639
[19] 9.018672 8.268267
> colMax(tmp5)
[1] 462.95694 83.84236 87.17170 90.29221 82.01377 80.90385 88.86445
[8] 87.03294 82.70479 84.40938 80.61005 84.25708 81.30570 77.18651
[15] 77.40797 82.35882 84.09530 87.56506 89.59556 82.84014
> colMin(tmp5)
[1] 63.19554 62.21938 56.64448 53.87383 58.87370 57.92582 55.27765 53.87189
[9] 59.81491 59.84822 56.06899 53.87826 64.49271 60.79068 56.13071 57.24660
[17] 58.89307 60.72540 59.69290 58.28549
>
>
> ### 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] 89.50311 74.27395 NA 66.71006 71.89139 70.22046 66.82452 71.31080
[9] 70.29714 71.39507
> rowSums(tmp5)
[1] 1790.062 1485.479 NA 1334.201 1437.828 1404.409 1336.490 1426.216
[9] 1405.943 1427.901
> rowVars(tmp5)
[1] 7809.44435 67.38155 107.57668 48.76081 91.98797 78.68124
[7] 25.06386 80.74447 53.60715 55.45008
> rowSd(tmp5)
[1] 88.371061 8.208626 10.371918 6.982894 9.591036 8.870245 5.006382
[8] 8.985793 7.321690 7.446481
> rowMax(tmp5)
[1] 462.95694 90.29221 NA 78.22113 87.17170 88.86445 74.24625
[8] 84.40938 87.56506 89.59556
> rowMin(tmp5)
[1] 55.27765 58.87370 NA 57.92582 53.87383 54.79210 57.24660 53.87189
[9] 59.13332 60.53703
>
> colMeans(tmp5)
[1] 114.27416 72.78816 72.82713 73.07616 69.81651 68.70443 74.43546
[8] 72.96526 69.63435 71.95669 69.62472 69.12015 NA 65.51447
[15] 66.26452 67.97374 68.06872 71.55340 71.81517 71.16208
> colSums(tmp5)
[1] 1142.7416 727.8816 728.2713 730.7616 698.1651 687.0443 744.3546
[8] 729.6526 696.3435 719.5669 696.2472 691.2015 NA 655.1447
[15] 662.6452 679.7374 680.6872 715.5340 718.1517 711.6208
> colVars(tmp5)
[1] 15082.08145 33.97409 94.22804 142.93383 64.19483 60.59921
[7] 121.97807 106.59684 60.54533 41.97225 73.09783 132.02642
[13] NA 28.21366 43.12257 59.36026 62.38220 71.43020
[19] 81.33645 68.36425
> colSd(tmp5)
[1] 122.809126 5.828729 9.707113 11.955494 8.012168 7.784550
[7] 11.044368 10.324575 7.781088 6.478600 8.549727 11.490275
[13] NA 5.311654 6.566777 7.704561 7.898240 8.451639
[19] 9.018672 8.268267
> colMax(tmp5)
[1] 462.95694 83.84236 87.17170 90.29221 82.01377 80.90385 88.86445
[8] 87.03294 82.70479 84.40938 80.61005 84.25708 NA 77.18651
[15] 77.40797 82.35882 84.09530 87.56506 89.59556 82.84014
> colMin(tmp5)
[1] 63.19554 62.21938 56.64448 53.87383 58.87370 57.92582 55.27765 53.87189
[9] 59.81491 59.84822 56.06899 53.87826 NA 60.79068 56.13071 57.24660
[17] 58.89307 60.72540 59.69290 58.28549
>
> Max(tmp5,na.rm=TRUE)
[1] 462.9569
> Min(tmp5,na.rm=TRUE)
[1] 53.87189
> mean(tmp5,na.rm=TRUE)
[1] 72.67843
> Sum(tmp5,na.rm=TRUE)
[1] 14463.01
> Var(tmp5,na.rm=TRUE)
[1] 845.122
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.50311 74.27395 74.44619 66.71006 71.89139 70.22046 66.82452 71.31080
[9] 70.29714 71.39507
> rowSums(tmp5,na.rm=TRUE)
[1] 1790.062 1485.479 1414.478 1334.201 1437.828 1404.409 1336.490 1426.216
[9] 1405.943 1427.901
> rowVars(tmp5,na.rm=TRUE)
[1] 7809.44435 67.38155 107.57668 48.76081 91.98797 78.68124
[7] 25.06386 80.74447 53.60715 55.45008
> rowSd(tmp5,na.rm=TRUE)
[1] 88.371061 8.208626 10.371918 6.982894 9.591036 8.870245 5.006382
[8] 8.985793 7.321690 7.446481
> rowMax(tmp5,na.rm=TRUE)
[1] 462.95694 90.29221 91.23877 78.22113 87.17170 88.86445 74.24625
[8] 84.40938 87.56506 89.59556
> rowMin(tmp5,na.rm=TRUE)
[1] 55.27765 58.87370 56.06899 57.92582 53.87383 54.79210 57.24660 53.87189
[9] 59.13332 60.53703
>
> colMeans(tmp5,na.rm=TRUE)
[1] 114.27416 72.78816 72.82713 73.07616 69.81651 68.70443 74.43546
[8] 72.96526 69.63435 71.95669 69.62472 69.12015 71.91715 65.51447
[15] 66.26452 67.97374 68.06872 71.55340 71.81517 71.16208
> colSums(tmp5,na.rm=TRUE)
[1] 1142.7416 727.8816 728.2713 730.7616 698.1651 687.0443 744.3546
[8] 729.6526 696.3435 719.5669 696.2472 691.2015 647.2544 655.1447
[15] 662.6452 679.7374 680.6872 715.5340 718.1517 711.6208
> colVars(tmp5,na.rm=TRUE)
[1] 15082.08145 33.97409 94.22804 142.93383 64.19483 60.59921
[7] 121.97807 106.59684 60.54533 41.97225 73.09783 132.02642
[13] 22.27680 28.21366 43.12257 59.36026 62.38220 71.43020
[19] 81.33645 68.36425
> colSd(tmp5,na.rm=TRUE)
[1] 122.809126 5.828729 9.707113 11.955494 8.012168 7.784550
[7] 11.044368 10.324575 7.781088 6.478600 8.549727 11.490275
[13] 4.719831 5.311654 6.566777 7.704561 7.898240 8.451639
[19] 9.018672 8.268267
> colMax(tmp5,na.rm=TRUE)
[1] 462.95694 83.84236 87.17170 90.29221 82.01377 80.90385 88.86445
[8] 87.03294 82.70479 84.40938 80.61005 84.25708 81.30570 77.18651
[15] 77.40797 82.35882 84.09530 87.56506 89.59556 82.84014
> colMin(tmp5,na.rm=TRUE)
[1] 63.19554 62.21938 56.64448 53.87383 58.87370 57.92582 55.27765 53.87189
[9] 59.81491 59.84822 56.06899 53.87826 64.49271 60.79068 56.13071 57.24660
[17] 58.89307 60.72540 59.69290 58.28549
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.50311 74.27395 NaN 66.71006 71.89139 70.22046 66.82452 71.31080
[9] 70.29714 71.39507
> rowSums(tmp5,na.rm=TRUE)
[1] 1790.062 1485.479 0.000 1334.201 1437.828 1404.409 1336.490 1426.216
[9] 1405.943 1427.901
> rowVars(tmp5,na.rm=TRUE)
[1] 7809.44435 67.38155 NA 48.76081 91.98797 78.68124
[7] 25.06386 80.74447 53.60715 55.45008
> rowSd(tmp5,na.rm=TRUE)
[1] 88.371061 8.208626 NA 6.982894 9.591036 8.870245 5.006382
[8] 8.985793 7.321690 7.446481
> rowMax(tmp5,na.rm=TRUE)
[1] 462.95694 90.29221 NA 78.22113 87.17170 88.86445 74.24625
[8] 84.40938 87.56506 89.59556
> rowMin(tmp5,na.rm=TRUE)
[1] 55.27765 58.87370 NA 57.92582 53.87383 54.79210 57.24660 53.87189
[9] 59.13332 60.53703
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.83365 71.55991 72.67605 72.45945 68.46126 69.83700 74.24764
[8] 71.40219 68.45661 71.38439 71.13091 67.63218 NaN 65.56192
[15] 66.48559 69.04534 67.24902 70.37579 71.15478 71.96581
> colSums(tmp5,na.rm=TRUE)
[1] 1051.5029 644.0392 654.0844 652.1350 616.1513 628.5330 668.2288
[8] 642.6197 616.1095 642.4595 640.1782 608.6897 0.0000 590.0573
[15] 598.3703 621.4081 605.2412 633.3821 640.3930 647.6923
> colVars(tmp5,na.rm=TRUE)
[1] 16893.64314 21.24928 105.74976 156.52180 51.55626 53.74370
[7] 136.82846 92.43540 52.50897 43.53401 56.71315 123.62167
[13] NA 31.71504 47.96308 53.86163 62.62105 64.75792
[19] 86.59710 69.64253
> colSd(tmp5,na.rm=TRUE)
[1] 129.975548 4.609694 10.283470 12.510867 7.180269 7.331009
[7] 11.697370 9.614333 7.246307 6.598031 7.530813 11.118528
[13] NA 5.631611 6.925538 7.339048 7.913346 8.047231
[19] 9.305756 8.345210
> colMax(tmp5,na.rm=TRUE)
[1] 462.95694 77.15294 87.17170 90.29221 81.71534 80.90385 88.86445
[8] 83.82682 82.70479 84.40938 80.61005 84.25708 -Inf 77.18651
[15] 77.40797 82.35882 84.09530 87.56506 89.59556 82.84014
> colMin(tmp5,na.rm=TRUE)
[1] 63.19554 62.21938 56.64448 53.87383 58.87370 57.92582 55.27765 53.87189
[9] 59.81491 59.84822 59.36954 53.87826 Inf 60.79068 56.13071 57.24660
[17] 58.89307 60.72540 59.69290 58.28549
>
>
>
>
> 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] 314.8743 254.5871 170.6176 268.7847 286.5535 243.5041 279.9598 151.7423
[9] 207.1813 142.0792
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 314.8743 254.5871 170.6176 268.7847 286.5535 243.5041 279.9598 151.7423
[9] 207.1813 142.0792
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 0.000000e+00 -5.684342e-14 -1.136868e-13 0.000000e+00 -4.263256e-14
[6] -2.842171e-14 4.263256e-14 -5.684342e-14 2.842171e-14 -7.105427e-14
[11] -1.136868e-13 -8.526513e-14 1.989520e-13 -8.526513e-14 -2.842171e-14
[16] 5.684342e-14 -5.684342e-14 0.000000e+00 5.684342e-14 -1.421085e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
4 18
9 15
6 5
7 12
9 4
7 10
6 15
10 5
4 4
3 6
9 14
5 7
5 18
7 19
7 7
2 14
5 7
5 2
2 9
6 6
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] 2.663956
> Min(tmp)
[1] -3.172449
> mean(tmp)
[1] -0.1048769
> Sum(tmp)
[1] -10.48769
> Var(tmp)
[1] 1.130384
>
> rowMeans(tmp)
[1] -0.1048769
> rowSums(tmp)
[1] -10.48769
> rowVars(tmp)
[1] 1.130384
> rowSd(tmp)
[1] 1.063195
> rowMax(tmp)
[1] 2.663956
> rowMin(tmp)
[1] -3.172449
>
> colMeans(tmp)
[1] 0.42588760 -2.23248594 -0.75977372 -0.49613803 0.53618051 -0.80635241
[7] -0.62809653 1.20470442 -1.51099715 2.66395604 0.62535126 -1.05293395
[13] 0.18151117 0.60094929 0.02988397 0.06033790 -1.24822955 -1.31170392
[19] -0.01220440 -1.77098915 2.32285927 0.28907246 -0.09113477 2.29116521
[25] -1.84056515 -1.00497881 0.34968095 0.31571385 0.68274482 0.59341988
[31] -0.75458633 0.05010318 -0.14163608 1.51025268 0.01929071 -0.57234866
[37] -0.28902152 -0.80530032 -0.37537915 -0.23112276 0.43554565 0.78706886
[43] -0.42110250 -0.82638191 0.10168533 -0.04777946 0.63059857 -0.24118999
[49] 0.09514602 -1.67341962 -0.26069152 1.50717877 -1.86436211 -0.42946962
[55] -1.03503608 -1.53044786 -0.12339763 0.16545060 0.22320987 -0.72139008
[61] -1.29973812 -1.31700454 -0.29893407 -1.17183160 0.14551160 1.50541803
[67] 0.50006910 -0.99138966 -1.48747878 0.42359872 -0.21139277 0.43991529
[73] -0.46747065 0.37857236 -1.22327225 0.59368532 0.81915906 0.67537092
[79] -0.20830137 -3.17244906 -1.60250477 2.10430600 -0.20000963 -0.17667263
[85] -0.43463278 -0.46211278 -0.75229681 0.09493190 1.11576984 -1.08576236
[91] 0.11728060 2.15698512 1.17162467 -0.82109200 -1.28743391 2.02304575
[97] -0.52278092 0.23712247 1.08412701 1.53207568
> colSums(tmp)
[1] 0.42588760 -2.23248594 -0.75977372 -0.49613803 0.53618051 -0.80635241
[7] -0.62809653 1.20470442 -1.51099715 2.66395604 0.62535126 -1.05293395
[13] 0.18151117 0.60094929 0.02988397 0.06033790 -1.24822955 -1.31170392
[19] -0.01220440 -1.77098915 2.32285927 0.28907246 -0.09113477 2.29116521
[25] -1.84056515 -1.00497881 0.34968095 0.31571385 0.68274482 0.59341988
[31] -0.75458633 0.05010318 -0.14163608 1.51025268 0.01929071 -0.57234866
[37] -0.28902152 -0.80530032 -0.37537915 -0.23112276 0.43554565 0.78706886
[43] -0.42110250 -0.82638191 0.10168533 -0.04777946 0.63059857 -0.24118999
[49] 0.09514602 -1.67341962 -0.26069152 1.50717877 -1.86436211 -0.42946962
[55] -1.03503608 -1.53044786 -0.12339763 0.16545060 0.22320987 -0.72139008
[61] -1.29973812 -1.31700454 -0.29893407 -1.17183160 0.14551160 1.50541803
[67] 0.50006910 -0.99138966 -1.48747878 0.42359872 -0.21139277 0.43991529
[73] -0.46747065 0.37857236 -1.22327225 0.59368532 0.81915906 0.67537092
[79] -0.20830137 -3.17244906 -1.60250477 2.10430600 -0.20000963 -0.17667263
[85] -0.43463278 -0.46211278 -0.75229681 0.09493190 1.11576984 -1.08576236
[91] 0.11728060 2.15698512 1.17162467 -0.82109200 -1.28743391 2.02304575
[97] -0.52278092 0.23712247 1.08412701 1.53207568
> 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] 0.42588760 -2.23248594 -0.75977372 -0.49613803 0.53618051 -0.80635241
[7] -0.62809653 1.20470442 -1.51099715 2.66395604 0.62535126 -1.05293395
[13] 0.18151117 0.60094929 0.02988397 0.06033790 -1.24822955 -1.31170392
[19] -0.01220440 -1.77098915 2.32285927 0.28907246 -0.09113477 2.29116521
[25] -1.84056515 -1.00497881 0.34968095 0.31571385 0.68274482 0.59341988
[31] -0.75458633 0.05010318 -0.14163608 1.51025268 0.01929071 -0.57234866
[37] -0.28902152 -0.80530032 -0.37537915 -0.23112276 0.43554565 0.78706886
[43] -0.42110250 -0.82638191 0.10168533 -0.04777946 0.63059857 -0.24118999
[49] 0.09514602 -1.67341962 -0.26069152 1.50717877 -1.86436211 -0.42946962
[55] -1.03503608 -1.53044786 -0.12339763 0.16545060 0.22320987 -0.72139008
[61] -1.29973812 -1.31700454 -0.29893407 -1.17183160 0.14551160 1.50541803
[67] 0.50006910 -0.99138966 -1.48747878 0.42359872 -0.21139277 0.43991529
[73] -0.46747065 0.37857236 -1.22327225 0.59368532 0.81915906 0.67537092
[79] -0.20830137 -3.17244906 -1.60250477 2.10430600 -0.20000963 -0.17667263
[85] -0.43463278 -0.46211278 -0.75229681 0.09493190 1.11576984 -1.08576236
[91] 0.11728060 2.15698512 1.17162467 -0.82109200 -1.28743391 2.02304575
[97] -0.52278092 0.23712247 1.08412701 1.53207568
> colMin(tmp)
[1] 0.42588760 -2.23248594 -0.75977372 -0.49613803 0.53618051 -0.80635241
[7] -0.62809653 1.20470442 -1.51099715 2.66395604 0.62535126 -1.05293395
[13] 0.18151117 0.60094929 0.02988397 0.06033790 -1.24822955 -1.31170392
[19] -0.01220440 -1.77098915 2.32285927 0.28907246 -0.09113477 2.29116521
[25] -1.84056515 -1.00497881 0.34968095 0.31571385 0.68274482 0.59341988
[31] -0.75458633 0.05010318 -0.14163608 1.51025268 0.01929071 -0.57234866
[37] -0.28902152 -0.80530032 -0.37537915 -0.23112276 0.43554565 0.78706886
[43] -0.42110250 -0.82638191 0.10168533 -0.04777946 0.63059857 -0.24118999
[49] 0.09514602 -1.67341962 -0.26069152 1.50717877 -1.86436211 -0.42946962
[55] -1.03503608 -1.53044786 -0.12339763 0.16545060 0.22320987 -0.72139008
[61] -1.29973812 -1.31700454 -0.29893407 -1.17183160 0.14551160 1.50541803
[67] 0.50006910 -0.99138966 -1.48747878 0.42359872 -0.21139277 0.43991529
[73] -0.46747065 0.37857236 -1.22327225 0.59368532 0.81915906 0.67537092
[79] -0.20830137 -3.17244906 -1.60250477 2.10430600 -0.20000963 -0.17667263
[85] -0.43463278 -0.46211278 -0.75229681 0.09493190 1.11576984 -1.08576236
[91] 0.11728060 2.15698512 1.17162467 -0.82109200 -1.28743391 2.02304575
[97] -0.52278092 0.23712247 1.08412701 1.53207568
> colMedians(tmp)
[1] 0.42588760 -2.23248594 -0.75977372 -0.49613803 0.53618051 -0.80635241
[7] -0.62809653 1.20470442 -1.51099715 2.66395604 0.62535126 -1.05293395
[13] 0.18151117 0.60094929 0.02988397 0.06033790 -1.24822955 -1.31170392
[19] -0.01220440 -1.77098915 2.32285927 0.28907246 -0.09113477 2.29116521
[25] -1.84056515 -1.00497881 0.34968095 0.31571385 0.68274482 0.59341988
[31] -0.75458633 0.05010318 -0.14163608 1.51025268 0.01929071 -0.57234866
[37] -0.28902152 -0.80530032 -0.37537915 -0.23112276 0.43554565 0.78706886
[43] -0.42110250 -0.82638191 0.10168533 -0.04777946 0.63059857 -0.24118999
[49] 0.09514602 -1.67341962 -0.26069152 1.50717877 -1.86436211 -0.42946962
[55] -1.03503608 -1.53044786 -0.12339763 0.16545060 0.22320987 -0.72139008
[61] -1.29973812 -1.31700454 -0.29893407 -1.17183160 0.14551160 1.50541803
[67] 0.50006910 -0.99138966 -1.48747878 0.42359872 -0.21139277 0.43991529
[73] -0.46747065 0.37857236 -1.22327225 0.59368532 0.81915906 0.67537092
[79] -0.20830137 -3.17244906 -1.60250477 2.10430600 -0.20000963 -0.17667263
[85] -0.43463278 -0.46211278 -0.75229681 0.09493190 1.11576984 -1.08576236
[91] 0.11728060 2.15698512 1.17162467 -0.82109200 -1.28743391 2.02304575
[97] -0.52278092 0.23712247 1.08412701 1.53207568
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.4258876 -2.232486 -0.7597737 -0.496138 0.5361805 -0.8063524 -0.6280965
[2,] 0.4258876 -2.232486 -0.7597737 -0.496138 0.5361805 -0.8063524 -0.6280965
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.204704 -1.510997 2.663956 0.6253513 -1.052934 0.1815112 0.6009493
[2,] 1.204704 -1.510997 2.663956 0.6253513 -1.052934 0.1815112 0.6009493
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.02988397 0.0603379 -1.24823 -1.311704 -0.0122044 -1.770989 2.322859
[2,] 0.02988397 0.0603379 -1.24823 -1.311704 -0.0122044 -1.770989 2.322859
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.2890725 -0.09113477 2.291165 -1.840565 -1.004979 0.3496809 0.3157139
[2,] 0.2890725 -0.09113477 2.291165 -1.840565 -1.004979 0.3496809 0.3157139
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.6827448 0.5934199 -0.7545863 0.05010318 -0.1416361 1.510253 0.01929071
[2,] 0.6827448 0.5934199 -0.7545863 0.05010318 -0.1416361 1.510253 0.01929071
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.5723487 -0.2890215 -0.8053003 -0.3753791 -0.2311228 0.4355456 0.7870689
[2,] -0.5723487 -0.2890215 -0.8053003 -0.3753791 -0.2311228 0.4355456 0.7870689
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.4211025 -0.8263819 0.1016853 -0.04777946 0.6305986 -0.24119 0.09514602
[2,] -0.4211025 -0.8263819 0.1016853 -0.04777946 0.6305986 -0.24119 0.09514602
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -1.67342 -0.2606915 1.507179 -1.864362 -0.4294696 -1.035036 -1.530448
[2,] -1.67342 -0.2606915 1.507179 -1.864362 -0.4294696 -1.035036 -1.530448
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.1233976 0.1654506 0.2232099 -0.7213901 -1.299738 -1.317005 -0.2989341
[2,] -0.1233976 0.1654506 0.2232099 -0.7213901 -1.299738 -1.317005 -0.2989341
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.171832 0.1455116 1.505418 0.5000691 -0.9913897 -1.487479 0.4235987
[2,] -1.171832 0.1455116 1.505418 0.5000691 -0.9913897 -1.487479 0.4235987
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.2113928 0.4399153 -0.4674706 0.3785724 -1.223272 0.5936853 0.8191591
[2,] -0.2113928 0.4399153 -0.4674706 0.3785724 -1.223272 0.5936853 0.8191591
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.6753709 -0.2083014 -3.172449 -1.602505 2.104306 -0.2000096 -0.1766726
[2,] 0.6753709 -0.2083014 -3.172449 -1.602505 2.104306 -0.2000096 -0.1766726
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.4346328 -0.4621128 -0.7522968 0.0949319 1.11577 -1.085762 0.1172806
[2,] -0.4346328 -0.4621128 -0.7522968 0.0949319 1.11577 -1.085762 0.1172806
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 2.156985 1.171625 -0.821092 -1.287434 2.023046 -0.5227809 0.2371225
[2,] 2.156985 1.171625 -0.821092 -1.287434 2.023046 -0.5227809 0.2371225
[,99] [,100]
[1,] 1.084127 1.532076
[2,] 1.084127 1.532076
>
>
> Max(tmp2)
[1] 2.004066
> Min(tmp2)
[1] -2.464072
> mean(tmp2)
[1] -0.1735756
> Sum(tmp2)
[1] -17.35756
> Var(tmp2)
[1] 1.042121
>
> rowMeans(tmp2)
[1] 1.11820103 -2.14528634 1.26253922 1.00111306 1.01829841 0.48960064
[7] 2.00406642 0.27315598 0.56372427 0.13493742 0.25832754 -0.95998418
[13] 0.78629136 -1.71557378 -1.78742380 0.38229641 0.14333718 -2.17854826
[19] -0.08393134 -0.29792356 -0.29947184 1.61591407 0.46998250 -0.08667514
[25] -0.47323871 -0.42945226 -0.22115244 -0.69815131 -2.08435714 0.22754303
[31] -2.46407242 -1.00906737 0.99379334 1.37023161 0.50289832 -1.57198241
[37] 0.38987893 -1.42389143 -0.50140673 -0.23411005 -0.20338444 0.39684034
[43] -1.72706616 0.78749371 -0.44038728 -0.82459527 -1.35863377 -0.85905096
[49] -0.75760357 -1.42346018 -1.59277590 1.01542002 1.43794315 -0.79181924
[55] -0.58237503 -0.02618831 -0.91615317 -1.34965162 0.39286676 -1.63885691
[61] 1.55180816 -1.32045005 -1.24029256 1.44502266 1.06545503 -1.30803558
[67] 1.05831363 -1.47483302 1.21899198 -0.28462994 -1.15138475 0.27183992
[73] 0.41719182 0.32386524 0.22998511 -1.54339589 -1.00195540 -1.26201228
[79] 0.43511204 -0.32296452 0.17336498 0.85815966 -1.83723571 -0.06872148
[85] -0.24897214 0.92912377 -0.45240660 -0.57804744 1.43317924 -0.61014964
[91] 0.80668720 -0.24026232 0.27908205 0.56093154 0.19602453 -0.19378407
[97] 1.29135680 0.19897999 -0.18249342 -0.65899916
> rowSums(tmp2)
[1] 1.11820103 -2.14528634 1.26253922 1.00111306 1.01829841 0.48960064
[7] 2.00406642 0.27315598 0.56372427 0.13493742 0.25832754 -0.95998418
[13] 0.78629136 -1.71557378 -1.78742380 0.38229641 0.14333718 -2.17854826
[19] -0.08393134 -0.29792356 -0.29947184 1.61591407 0.46998250 -0.08667514
[25] -0.47323871 -0.42945226 -0.22115244 -0.69815131 -2.08435714 0.22754303
[31] -2.46407242 -1.00906737 0.99379334 1.37023161 0.50289832 -1.57198241
[37] 0.38987893 -1.42389143 -0.50140673 -0.23411005 -0.20338444 0.39684034
[43] -1.72706616 0.78749371 -0.44038728 -0.82459527 -1.35863377 -0.85905096
[49] -0.75760357 -1.42346018 -1.59277590 1.01542002 1.43794315 -0.79181924
[55] -0.58237503 -0.02618831 -0.91615317 -1.34965162 0.39286676 -1.63885691
[61] 1.55180816 -1.32045005 -1.24029256 1.44502266 1.06545503 -1.30803558
[67] 1.05831363 -1.47483302 1.21899198 -0.28462994 -1.15138475 0.27183992
[73] 0.41719182 0.32386524 0.22998511 -1.54339589 -1.00195540 -1.26201228
[79] 0.43511204 -0.32296452 0.17336498 0.85815966 -1.83723571 -0.06872148
[85] -0.24897214 0.92912377 -0.45240660 -0.57804744 1.43317924 -0.61014964
[91] 0.80668720 -0.24026232 0.27908205 0.56093154 0.19602453 -0.19378407
[97] 1.29135680 0.19897999 -0.18249342 -0.65899916
> 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] 1.11820103 -2.14528634 1.26253922 1.00111306 1.01829841 0.48960064
[7] 2.00406642 0.27315598 0.56372427 0.13493742 0.25832754 -0.95998418
[13] 0.78629136 -1.71557378 -1.78742380 0.38229641 0.14333718 -2.17854826
[19] -0.08393134 -0.29792356 -0.29947184 1.61591407 0.46998250 -0.08667514
[25] -0.47323871 -0.42945226 -0.22115244 -0.69815131 -2.08435714 0.22754303
[31] -2.46407242 -1.00906737 0.99379334 1.37023161 0.50289832 -1.57198241
[37] 0.38987893 -1.42389143 -0.50140673 -0.23411005 -0.20338444 0.39684034
[43] -1.72706616 0.78749371 -0.44038728 -0.82459527 -1.35863377 -0.85905096
[49] -0.75760357 -1.42346018 -1.59277590 1.01542002 1.43794315 -0.79181924
[55] -0.58237503 -0.02618831 -0.91615317 -1.34965162 0.39286676 -1.63885691
[61] 1.55180816 -1.32045005 -1.24029256 1.44502266 1.06545503 -1.30803558
[67] 1.05831363 -1.47483302 1.21899198 -0.28462994 -1.15138475 0.27183992
[73] 0.41719182 0.32386524 0.22998511 -1.54339589 -1.00195540 -1.26201228
[79] 0.43511204 -0.32296452 0.17336498 0.85815966 -1.83723571 -0.06872148
[85] -0.24897214 0.92912377 -0.45240660 -0.57804744 1.43317924 -0.61014964
[91] 0.80668720 -0.24026232 0.27908205 0.56093154 0.19602453 -0.19378407
[97] 1.29135680 0.19897999 -0.18249342 -0.65899916
> rowMin(tmp2)
[1] 1.11820103 -2.14528634 1.26253922 1.00111306 1.01829841 0.48960064
[7] 2.00406642 0.27315598 0.56372427 0.13493742 0.25832754 -0.95998418
[13] 0.78629136 -1.71557378 -1.78742380 0.38229641 0.14333718 -2.17854826
[19] -0.08393134 -0.29792356 -0.29947184 1.61591407 0.46998250 -0.08667514
[25] -0.47323871 -0.42945226 -0.22115244 -0.69815131 -2.08435714 0.22754303
[31] -2.46407242 -1.00906737 0.99379334 1.37023161 0.50289832 -1.57198241
[37] 0.38987893 -1.42389143 -0.50140673 -0.23411005 -0.20338444 0.39684034
[43] -1.72706616 0.78749371 -0.44038728 -0.82459527 -1.35863377 -0.85905096
[49] -0.75760357 -1.42346018 -1.59277590 1.01542002 1.43794315 -0.79181924
[55] -0.58237503 -0.02618831 -0.91615317 -1.34965162 0.39286676 -1.63885691
[61] 1.55180816 -1.32045005 -1.24029256 1.44502266 1.06545503 -1.30803558
[67] 1.05831363 -1.47483302 1.21899198 -0.28462994 -1.15138475 0.27183992
[73] 0.41719182 0.32386524 0.22998511 -1.54339589 -1.00195540 -1.26201228
[79] 0.43511204 -0.32296452 0.17336498 0.85815966 -1.83723571 -0.06872148
[85] -0.24897214 0.92912377 -0.45240660 -0.57804744 1.43317924 -0.61014964
[91] 0.80668720 -0.24026232 0.27908205 0.56093154 0.19602453 -0.19378407
[97] 1.29135680 0.19897999 -0.18249342 -0.65899916
>
> colMeans(tmp2)
[1] -0.1735756
> colSums(tmp2)
[1] -17.35756
> colVars(tmp2)
[1] 1.042121
> colSd(tmp2)
[1] 1.020843
> colMax(tmp2)
[1] 2.004066
> colMin(tmp2)
[1] -2.464072
> colMedians(tmp2)
[1] -0.1881387
> colRanges(tmp2)
[,1]
[1,] -2.464072
[2,] 2.004066
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.9502213 -1.9024663 2.2657478 2.2767552 0.7934448 -6.8769024
[7] -2.8492098 -5.6433335 -0.4804894 0.8494200
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.1194717
[2,] -0.2096842
[3,] 0.2188379
[4,] 0.3504487
[5,] 1.3915128
>
> rowApply(tmp,sum)
[1] -4.8223529 4.7282312 5.6747089 -7.1556921 -2.7819472 -2.3458003
[7] 3.3111178 0.8209522 -4.8613739 -3.1846560
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 3 5 2 6 8 10 7 10 5
[2,] 3 9 4 5 5 10 8 5 3 1
[3,] 6 10 2 10 4 2 7 8 7 3
[4,] 7 8 9 7 10 7 6 3 1 8
[5,] 2 7 6 8 2 5 9 10 2 4
[6,] 1 2 1 1 7 3 4 9 5 2
[7,] 4 4 8 9 3 4 1 6 6 6
[8,] 5 6 7 3 1 1 3 1 8 7
[9,] 10 1 10 4 9 6 5 4 4 9
[10,] 8 5 3 6 8 9 2 2 9 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.68204432 1.30221623 -0.19924266 -0.35674313 -3.59834291 -4.65354749
[7] -3.73291546 -0.97269021 -1.56131132 5.25937588 -0.91903018 0.60592761
[13] 0.07351182 0.22381654 0.20567689 2.76741375 5.30237547 -1.56153301
[19] -1.50570858 2.13412534
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5448131
[2,] 0.6557160
[3,] 0.8763071
[4,] 1.2988238
[5,] 1.3960105
>
> rowApply(tmp,sum)
[1] -1.69432675 -2.21658635 0.93523464 -0.08288053 4.55397791
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 4 18 17 19 15
[2,] 12 19 8 14 6
[3,] 10 13 12 3 13
[4,] 2 5 15 17 11
[5,] 3 7 5 6 16
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.5448131 -0.01097433 -0.1618442 -1.9133775 -1.7482837 -0.2899817
[2,] 0.8763071 1.56168503 0.3850332 -0.8463862 -0.5265465 -1.6567527
[3,] 1.2988238 -0.30071807 0.3248084 0.8467162 -1.2397867 0.2877281
[4,] 1.3960105 0.47232945 -1.2785833 1.1461890 -0.7884184 -1.4972382
[5,] 0.6557160 -0.42010586 0.5313432 0.4101153 0.7046925 -1.4973030
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.5037330 0.3139460 -1.0727957 -0.1571320 -2.0111866 0.9916706
[2,] -0.8013314 0.5121541 -0.3023175 0.4561253 -0.1144124 -0.2347737
[3,] -1.3451300 -1.7274542 1.9988396 2.6000881 1.0957585 -0.2470191
[4,] -0.5602734 -0.5358657 -1.0383312 0.6169564 -1.3017065 -0.8785553
[5,] -0.5224477 0.4645296 -1.1467066 1.7433382 1.4125168 0.9746050
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.4025851 0.8084923 1.11490447 2.3581404 0.9861253 0.5683579
[2,] 0.5181420 1.6954846 0.81307769 -1.0916584 0.3234975 -1.3300192
[3,] -0.5886097 -2.1188879 -2.26085321 0.7361690 1.6493952 -0.9117334
[4,] 1.1837189 -0.4962118 0.46668141 0.4267628 1.7701391 0.5830599
[5,] -0.6371543 0.3349394 0.07186653 0.3380000 0.5732183 -0.4711982
[,19] [,20]
[1,] -0.4189184 1.3996615
[2,] -1.9432694 -0.5106255
[3,] 0.3130369 0.5240632
[4,] 0.3425582 -0.1121025
[5,] 0.2008841 0.8331286
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.9-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-3.9-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 644 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 558 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.9-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 0.9867351 -0.1572972 -0.7398504 -1.10079 -2.113512 1.146055 0.1296722
col8 col9 col10 col11 col12 col13 col14
row1 -0.07141885 2.31966 1.215659 0.09679109 -0.3571098 0.1121948 0.522653
col15 col16 col17 col18 col19 col20
row1 0.892627 2.396756 0.00404484 -0.4627571 1.112394 0.05600396
> tmp[,"col10"]
col10
row1 1.2156593
row2 0.6705291
row3 -1.9946112
row4 0.7931762
row5 -0.5950995
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.9867351 -0.1572972 -0.7398504 -1.100790 -2.1135116 1.1460549 0.1296722
row5 0.1467389 0.9572088 -0.8338278 -0.333034 -0.8165136 -0.3365341 -1.2780404
col8 col9 col10 col11 col12 col13
row1 -0.07141885 2.3196603 1.2156593 0.09679109 -0.3571098 0.1121948
row5 -1.08806353 -0.3126668 -0.5950995 -2.52944973 -1.9545277 3.1169844
col14 col15 col16 col17 col18 col19 col20
row1 0.5226530 0.892627 2.396756 0.00404484 -0.4627571 1.1123941 0.05600396
row5 0.7575808 -1.528467 1.402332 1.14175364 -0.3763123 -0.2551744 0.50750022
> tmp[,c("col6","col20")]
col6 col20
row1 1.1460549 0.05600396
row2 0.9417362 1.48296563
row3 -0.5061413 -1.78322602
row4 -0.3194401 -1.87481792
row5 -0.3365341 0.50750022
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.1460549 0.05600396
row5 -0.3365341 0.50750022
>
>
>
>
> 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 50.13841 51.05548 48.7673 50.21472 50.92561 105.7646 51.52277 51.56282
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.28165 51.24594 49.60593 48.71443 51.37015 49.78729 50.69206 51.71644
col17 col18 col19 col20
row1 51.11577 49.5563 48.8254 105.3076
> tmp[,"col10"]
col10
row1 51.24594
row2 29.88859
row3 30.66775
row4 29.43175
row5 50.49646
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.13841 51.05548 48.76730 50.21472 50.92561 105.7646 51.52277 51.56282
row5 49.18655 50.66663 50.77465 50.85008 49.89960 106.4861 49.98441 50.71324
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.28165 51.24594 49.60593 48.71443 51.37015 49.78729 50.69206 51.71644
row5 49.69442 50.49646 49.17750 49.68630 49.89584 50.23816 51.13316 51.09526
col17 col18 col19 col20
row1 51.11577 49.55630 48.82540 105.3076
row5 49.69624 50.76003 50.03485 105.4020
> tmp[,c("col6","col20")]
col6 col20
row1 105.76458 105.30756
row2 75.87944 76.61015
row3 75.37313 74.48603
row4 74.27463 74.70059
row5 106.48615 105.40202
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.7646 105.3076
row5 106.4861 105.4020
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.7646 105.3076
row5 106.4861 105.4020
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.1772122
[2,] 1.0298332
[3,] -1.9097120
[4,] -1.1675047
[5,] 1.3271349
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.09457872 0.25725525
[2,] -0.95807823 0.06738742
[3,] -0.06326238 -0.25738237
[4,] -0.17181268 0.13922126
[5,] -0.45043162 0.86193584
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.0553914 -0.2565589
[2,] 1.4379972 0.5131435
[3,] -1.6505131 -1.5709836
[4,] 1.5588675 0.6396438
[5,] -0.2574703 -0.1214035
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.055391
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.055391
[2,] 1.437997
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 0.6310630 1.302381 -0.4253174 2.082030 -0.2227667 1.2249645 0.4631692
row1 0.6288099 1.628057 -0.1845900 -1.268725 0.8730940 0.5278564 -1.5564047
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.20199755 -1.885849 0.3782459 -0.5847543 -0.2217648 1.1775233
row1 -0.03661473 -1.916804 -1.0911076 -1.6640710 0.9112650 -0.3285622
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.695332 1.0511305 1.176790 1.0301034 0.9782270 -1.6876544 -0.50695276
row1 -0.859589 0.9386665 -2.196072 0.2712571 -0.1774191 0.7444282 0.09231892
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.64505 2.476847 0.06564678 -1.759704 -0.2504844 -0.8876197 1.922485
[,8] [,9] [,10]
row2 -0.8988956 0.0006305222 0.4483738
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.0199142 -0.6907483 0.3560494 -1.903161 -0.8726784 0.004969085 -0.2890695
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.9354055 0.2012445 -0.9067713 -1.121592 2.017135 -1.326204 -0.6540554
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.04490112 0.5979913 2.014615 -1.14668 -1.026504 0.8843672
>
>
> 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: 0x7fb6c8f4e860>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM198b14f2b885"
[2] "/Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM198b4b302e81"
[3] "/Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM198b483d3db7"
[4] "/Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM198b2c9ede6e"
[5] "/Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM198b721d1ea4"
[6] "/Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM198b55c6db83"
[7] "/Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM198b7275a173"
[8] "/Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM198b8babfba"
[9] "/Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM198b1c8150d0"
[10] "/Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM198b6de0964e"
[11] "/Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM198b33ac133d"
[12] "/Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM198b6623244b"
[13] "/Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM198bd23ec50"
[14] "/Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM198b316f7eed"
[15] "/Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM198bef612f6"
>
>
> ### 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: 0x7fb6c8c2bc40>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x7fb6c8c2bc40>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x7fb6c8c2bc40>
> rowMedians(tmp)
[1] 0.0003803568 0.1946579185 -0.1152450352 -0.0695813639 0.1288260568
[6] 0.1985770010 -0.0451578018 -0.1837573953 -0.2823614541 0.3093502214
[11] -0.1133678507 0.1897303645 0.3155512828 0.4539182819 0.2293478295
[16] 0.0360983373 0.2991363435 -0.8717438753 0.1098875367 0.5377958301
[21] 0.3651682366 0.3395522351 0.3815584168 0.1754240883 0.3350170381
[26] 0.0312077118 0.0511848362 0.1169769566 -0.0760101043 0.2221201414
[31] 0.1273623317 0.0355256077 -0.3528208120 -0.0063271627 -0.0787912769
[36] -0.0015149435 -0.1049277660 0.0386119558 -0.6219857030 0.0315781855
[41] -0.3072357984 0.6181183723 -0.5233127781 -0.0037794137 -0.0239478747
[46] 0.3297577745 0.1642953000 0.4794966881 0.2983869691 0.2427912058
[51] -0.6192085161 0.0107165916 0.0788156903 0.2217816869 -0.1042505314
[56] -0.1879249605 0.2682903808 0.1479735078 0.0798324041 0.6675346224
[61] 0.3682561405 -0.5706730774 -0.1011478076 0.0523648657 0.3161473476
[66] -0.1938076599 0.2586980973 0.1069990302 -0.4588528971 -0.3308704328
[71] 0.3213076522 -0.1287248536 0.4093443794 0.2225614514 0.1859103361
[76] -0.1305226179 -0.5242797827 0.3374013195 -0.1646312204 -0.2668855922
[81] 0.2023854459 -0.0742815199 -0.3722849724 -0.1696385505 -0.2222364355
[86] -0.1094770032 -0.6189767943 0.4134353708 -0.0505109744 0.4947339388
[91] -0.4416382573 0.2327863836 -0.3437905604 -0.1105724113 -0.2406977497
[96] 0.3975304302 0.4525723964 -0.0344787017 -0.3198746501 0.2958267297
[101] -0.6336029294 0.3560727356 0.0913693456 0.3981992804 0.2191697579
[106] -0.0360292899 0.4222488344 -0.1368570539 0.0646210285 -0.2991317477
[111] -0.4978371267 0.5885439419 -1.0096506176 0.2184124259 -0.1856598133
[116] -0.3407981639 0.1475721261 -0.6202145781 -0.2319814509 -0.2505210689
[121] -0.2280261492 0.0192247846 -0.1325360345 0.2230355833 0.1421325010
[126] 0.1030913808 -0.2025212531 0.3002118070 -0.0481001530 0.2973054568
[131] 0.1043302887 -0.1760280236 0.1895445817 -0.1733237907 0.5141677563
[136] 0.0076601490 -0.0947824997 -0.0899103269 0.1299670870 -0.6454313513
[141] -0.2349073260 -0.0480188449 -0.3177620144 -0.2782750316 0.2353832318
[146] 0.2992137336 -0.8535404330 0.1050823849 -0.3764950619 0.2189814224
[151] -0.4226322647 0.0908014217 0.1613750801 -0.0321950967 0.1717881483
[156] -0.1591715277 -0.6326997670 -0.5367306101 -0.1696503325 -0.5965736714
[161] -0.1213619203 -0.2650785387 -0.3835393987 -0.3867993835 -0.1497037174
[166] -0.0670951696 -0.1571383392 0.0531551725 -0.3216648721 0.2020433747
[171] 0.0095477528 -0.1038246921 -0.0735587312 0.3844595837 -0.0098094883
[176] 0.4047988127 -0.2346751610 0.2663610835 -0.0721839951 -0.3958089231
[181] 0.1291414896 0.3676493168 0.1476975673 -0.2135495720 0.1405200889
[186] -0.0110973905 0.4848991579 -0.1620439699 0.4563074267 0.0255171509
[191] 0.2896456012 0.5879663584 0.0903522786 0.0781741327 0.1676185149
[196] 0.4260834555 0.0805125345 0.1658014558 0.1515420925 -0.1828608923
[201] 0.3092377986 0.3894705235 -0.2857174535 0.3136468339 -0.0703851667
[206] 0.1789683143 0.1802302716 0.3304256625 0.0807245929 -0.1907585889
[211] -0.3384780679 -0.1389029787 0.7592582007 0.1386311449 0.4494808245
[216] -0.6526946531 -0.1466737221 0.0551555166 0.2394726217 -0.0905209365
[221] 0.3857512993 -0.2574978208 -0.5894263569 -0.1042696504 -0.6035500040
[226] 0.1674974325 0.5634226395 -0.2534476706 -0.4163831865 -0.7027786311
>
> proc.time()
user system elapsed
6.455 15.544 23.911
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2019-03-18 r76245) -- "Unsuffered Consequences"
Copyright (C) 2019 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: 0x7fdfc2d00000>
> .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: 0x7fdfc2d00000>
> .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: 0x7fdfc2d00000>
> .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: 0x7fdfc2d00000>
> 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: 0x7fdfcd000aa0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fdfcd000aa0>
> .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: 0x7fdfcd000aa0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fdfcd000aa0>
> .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: 0x7fdfcd000aa0>
> 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: 0x7fdfc2e00250>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fdfc2e00250>
> .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: 0x7fdfc2e00250>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x7fdfc2e00250>
> .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: 0x7fdfc2e00250>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x7fdfc2e00250>
> .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: 0x7fdfc2e00250>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x7fdfc2e00250>
> .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: 0x7fdfc2e00250>
> 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: 0x7fdfc2e003e0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x7fdfc2e003e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fdfc2e003e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fdfc2e003e0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1eab5886bb95" "BufferedMatrixFile1eab7585609a"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1eab5886bb95" "BufferedMatrixFile1eab7585609a"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fdfcd000db0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fdfcd000db0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x7fdfcd000db0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x7fdfcd000db0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x7fdfcd000db0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x7fdfcd000db0>
> .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: 0x7fdfc2f00270>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fdfc2f00270>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x7fdfc2f00270>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x7fdfc2f00270>
> 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: 0x7fdfcd100130>
> .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: 0x7fdfcd100130>
> rm(P)
>
> proc.time()
user system elapsed
0.605 0.244 0.800
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2019-03-18 r76245) -- "Unsuffered Consequences"
Copyright (C) 2019 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
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.546 0.160 0.650