Ben Bolstad
| Snapshot Date: 2020-04-14 16:46:13 -0400 (Tue, 14 Apr 2020) |
| URL: https://git.bioconductor.org/packages/BufferedMatrix |
| Branch: RELEASE_3_10 |
| Last Commit: c7a0fa5 |
| Last Changed Date: 2019-10-29 13:07:46 -0400 (Tue, 29 Oct 2019) |
| Back to Multiple platform build/check report for BioC 3.10 |
|
This page was generated on 2020-04-15 12:35:00 -0400 (Wed, 15 Apr 2020).
| Package 205/1823 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||
| BufferedMatrix 1.50.0 Ben Bolstad
| malbec1 | Linux (Ubuntu 18.04.4 LTS) / x86_64 | OK | OK | OK | | ||||||
| tokay1 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||
| merida1 | OS X 10.11.6 El Capitan / x86_64 | OK | OK | [ OK ] | OK | |
| Package: BufferedMatrix |
| Version: 1.50.0 |
| 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_1.50.0.tar.gz |
| StartedAt: 2020-04-15 00:51:42 -0400 (Wed, 15 Apr 2020) |
| EndedAt: 2020-04-15 00:52:23 -0400 (Wed, 15 Apr 2020) |
| EllapsedTime: 40.8 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_1.50.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck’ * using R version 3.6.3 (2020-02-29) * 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 ‘1.50.0’ * 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-3.10-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 -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -I/usr/local/include -fPIC -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -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 -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -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 -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -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 version 3.6.3 (2020-02-29) -- "Holding the Windsock"
Copyright (C) 2020 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
0.417 0.108 0.502
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 3.6.3 (2020-02-29) -- "Holding the Windsock"
Copyright (C) 2020 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-3.10-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 415836 22.3 879997 47 NA 616211 33.0
Vcells 749254 5.8 8388608 64 65536 1811279 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] "Wed Apr 15 00:52:06 2020"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed Apr 15 00:52:06 2020"
>
>
> 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: 0x7f92a9910c50>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Wed Apr 15 00:52:08 2020"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed Apr 15 00:52:09 2020"
>
> ColMode(tmp2)
<pointer: 0x7f92a9910c50>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.0682862 0.9168799 0.26827600 -0.008779983
[2,] 0.3250981 -2.7610675 -1.18704795 0.279778476
[3,] 0.9782585 -1.0644497 0.04675994 0.767569917
[4,] 0.6335836 -0.3268276 -0.94739438 0.033803277
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.0682862 0.9168799 0.26827600 0.008779983
[2,] 0.3250981 2.7610675 1.18704795 0.279778476
[3,] 0.9782585 1.0644497 0.04675994 0.767569917
[4,] 0.6335836 0.3268276 0.94739438 0.033803277
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0034137 0.9575384 0.5179537 0.09370156
[2,] 0.5701737 1.6616460 1.0895173 0.52894090
[3,] 0.9890695 1.0317217 0.2162405 0.87611068
[4,] 0.7959797 0.5716884 0.9733419 0.18385667
>
> 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-3.10-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.10242 35.49226 30.44781 25.94580
[2,] 31.02684 44.37753 37.08222 30.56919
[3,] 35.86895 36.38167 27.20916 34.52868
[4,] 33.59338 31.04371 35.68081 26.87237
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x7f92a25236a0>
> exp(tmp5)
<pointer: 0x7f92a25236a0>
> log(tmp5,2)
<pointer: 0x7f92a25236a0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.5212
> Min(tmp5)
[1] 53.80077
> mean(tmp5)
[1] 71.70822
> Sum(tmp5)
[1] 14341.64
> Var(tmp5)
[1] 863.0241
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.11446 70.26261 70.44425 71.92547 71.01145 69.22857 69.13830 68.45717
[9] 68.40488 67.09502
> rowSums(tmp5)
[1] 1822.289 1405.252 1408.885 1438.509 1420.229 1384.571 1382.766 1369.143
[9] 1368.098 1341.900
> rowVars(tmp5)
[1] 7956.62397 76.22303 41.31161 59.94388 107.35571 115.25214
[7] 67.37792 67.96497 39.33306 48.35205
> rowSd(tmp5)
[1] 89.199910 8.730580 6.427411 7.742343 10.361260 10.735555 8.208406
[8] 8.244087 6.271607 6.953564
> rowMax(tmp5)
[1] 468.52120 92.36601 78.26907 87.34712 86.96350 84.51885 85.16931
[8] 83.11466 77.32627 80.94093
> rowMin(tmp5)
[1] 54.00277 58.96425 55.93204 55.93132 53.96733 55.38394 55.43691 53.80077
[9] 59.09431 54.06135
>
> colMeans(tmp5)
[1] 111.01308 71.51002 73.69809 62.57671 71.50552 68.61914 68.90170
[8] 70.62460 70.35891 69.30378 63.57765 68.78395 70.26097 68.54867
[15] 70.53785 69.25954 69.23461 74.15109 73.86634 67.83213
> colSums(tmp5)
[1] 1110.1308 715.1002 736.9809 625.7671 715.0552 686.1914 689.0170
[8] 706.2460 703.5891 693.0378 635.7765 687.8395 702.6097 685.4867
[15] 705.3785 692.5954 692.3461 741.5109 738.6634 678.3213
> colVars(tmp5)
[1] 15816.22452 92.61391 79.55105 55.80158 67.39629 44.69549
[7] 93.83319 65.33914 69.64876 56.61223 42.24526 56.71035
[13] 61.48005 68.82004 61.03634 129.09212 46.37794 32.71777
[19] 121.72872 37.87458
> colSd(tmp5)
[1] 125.762572 9.623612 8.919139 7.470045 8.209524 6.685469
[7] 9.686753 8.083263 8.345583 7.524110 6.499635 7.530628
[13] 7.840921 8.295784 7.812576 11.361871 6.810135 5.719945
[19] 11.033074 6.154233
> colMax(tmp5)
[1] 468.52120 92.36601 84.90136 72.63968 86.96350 81.84568 86.22511
[8] 83.43078 82.44610 77.94167 74.77615 81.92677 84.51885 79.73843
[15] 83.44246 91.96819 84.11330 85.77636 87.34712 73.74175
> colMin(tmp5)
[1] 64.40314 56.73554 56.63231 53.96733 61.87555 59.09431 55.43691 62.10603
[9] 53.80077 55.93204 55.38394 58.96425 56.30028 57.88826 56.77080 55.84243
[17] 61.01485 64.52515 54.06135 56.02960
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 91.11446 70.26261 70.44425 71.92547 71.01145 69.22857 NA 68.45717
[9] 68.40488 67.09502
> rowSums(tmp5)
[1] 1822.289 1405.252 1408.885 1438.509 1420.229 1384.571 NA 1369.143
[9] 1368.098 1341.900
> rowVars(tmp5)
[1] 7956.62397 76.22303 41.31161 59.94388 107.35571 115.25214
[7] 68.41203 67.96497 39.33306 48.35205
> rowSd(tmp5)
[1] 89.199910 8.730580 6.427411 7.742343 10.361260 10.735555 8.271156
[8] 8.244087 6.271607 6.953564
> rowMax(tmp5)
[1] 468.52120 92.36601 78.26907 87.34712 86.96350 84.51885 NA
[8] 83.11466 77.32627 80.94093
> rowMin(tmp5)
[1] 54.00277 58.96425 55.93204 55.93132 53.96733 55.38394 NA 53.80077
[9] 59.09431 54.06135
>
> colMeans(tmp5)
[1] 111.01308 71.51002 73.69809 62.57671 71.50552 68.61914 68.90170
[8] 70.62460 70.35891 69.30378 63.57765 68.78395 70.26097 NA
[15] 70.53785 69.25954 69.23461 74.15109 73.86634 67.83213
> colSums(tmp5)
[1] 1110.1308 715.1002 736.9809 625.7671 715.0552 686.1914 689.0170
[8] 706.2460 703.5891 693.0378 635.7765 687.8395 702.6097 NA
[15] 705.3785 692.5954 692.3461 741.5109 738.6634 678.3213
> colVars(tmp5)
[1] 15816.22452 92.61391 79.55105 55.80158 67.39629 44.69549
[7] 93.83319 65.33914 69.64876 56.61223 42.24526 56.71035
[13] 61.48005 NA 61.03634 129.09212 46.37794 32.71777
[19] 121.72872 37.87458
> colSd(tmp5)
[1] 125.762572 9.623612 8.919139 7.470045 8.209524 6.685469
[7] 9.686753 8.083263 8.345583 7.524110 6.499635 7.530628
[13] 7.840921 NA 7.812576 11.361871 6.810135 5.719945
[19] 11.033074 6.154233
> colMax(tmp5)
[1] 468.52120 92.36601 84.90136 72.63968 86.96350 81.84568 86.22511
[8] 83.43078 82.44610 77.94167 74.77615 81.92677 84.51885 NA
[15] 83.44246 91.96819 84.11330 85.77636 87.34712 73.74175
> colMin(tmp5)
[1] 64.40314 56.73554 56.63231 53.96733 61.87555 59.09431 55.43691 62.10603
[9] 53.80077 55.93204 55.38394 58.96425 56.30028 NA 56.77080 55.84243
[17] 61.01485 64.52515 54.06135 56.02960
>
> Max(tmp5,na.rm=TRUE)
[1] 468.5212
> Min(tmp5,na.rm=TRUE)
[1] 53.80077
> mean(tmp5,na.rm=TRUE)
[1] 71.68693
> Sum(tmp5,na.rm=TRUE)
[1] 14265.7
> Var(tmp5,na.rm=TRUE)
[1] 867.2917
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.11446 70.26261 70.44425 71.92547 71.01145 69.22857 68.78007 68.45717
[9] 68.40488 67.09502
> rowSums(tmp5,na.rm=TRUE)
[1] 1822.289 1405.252 1408.885 1438.509 1420.229 1384.571 1306.821 1369.143
[9] 1368.098 1341.900
> rowVars(tmp5,na.rm=TRUE)
[1] 7956.62397 76.22303 41.31161 59.94388 107.35571 115.25214
[7] 68.41203 67.96497 39.33306 48.35205
> rowSd(tmp5,na.rm=TRUE)
[1] 89.199910 8.730580 6.427411 7.742343 10.361260 10.735555 8.271156
[8] 8.244087 6.271607 6.953564
> rowMax(tmp5,na.rm=TRUE)
[1] 468.52120 92.36601 78.26907 87.34712 86.96350 84.51885 85.16931
[8] 83.11466 77.32627 80.94093
> rowMin(tmp5,na.rm=TRUE)
[1] 54.00277 58.96425 55.93204 55.93132 53.96733 55.38394 55.43691 53.80077
[9] 59.09431 54.06135
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.01308 71.51002 73.69809 62.57671 71.50552 68.61914 68.90170
[8] 70.62460 70.35891 69.30378 63.57765 68.78395 70.26097 67.72690
[15] 70.53785 69.25954 69.23461 74.15109 73.86634 67.83213
> colSums(tmp5,na.rm=TRUE)
[1] 1110.1308 715.1002 736.9809 625.7671 715.0552 686.1914 689.0170
[8] 706.2460 703.5891 693.0378 635.7765 687.8395 702.6097 609.5421
[15] 705.3785 692.5954 692.3461 741.5109 738.6634 678.3213
> colVars(tmp5,na.rm=TRUE)
[1] 15816.22452 92.61391 79.55105 55.80158 67.39629 44.69549
[7] 93.83319 65.33914 69.64876 56.61223 42.24526 56.71035
[13] 61.48005 69.82533 61.03634 129.09212 46.37794 32.71777
[19] 121.72872 37.87458
> colSd(tmp5,na.rm=TRUE)
[1] 125.762572 9.623612 8.919139 7.470045 8.209524 6.685469
[7] 9.686753 8.083263 8.345583 7.524110 6.499635 7.530628
[13] 7.840921 8.356155 7.812576 11.361871 6.810135 5.719945
[19] 11.033074 6.154233
> colMax(tmp5,na.rm=TRUE)
[1] 468.52120 92.36601 84.90136 72.63968 86.96350 81.84568 86.22511
[8] 83.43078 82.44610 77.94167 74.77615 81.92677 84.51885 79.73843
[15] 83.44246 91.96819 84.11330 85.77636 87.34712 73.74175
> colMin(tmp5,na.rm=TRUE)
[1] 64.40314 56.73554 56.63231 53.96733 61.87555 59.09431 55.43691 62.10603
[9] 53.80077 55.93204 55.38394 58.96425 56.30028 57.88826 56.77080 55.84243
[17] 61.01485 64.52515 54.06135 56.02960
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.11446 70.26261 70.44425 71.92547 71.01145 69.22857 NaN 68.45717
[9] 68.40488 67.09502
> rowSums(tmp5,na.rm=TRUE)
[1] 1822.289 1405.252 1408.885 1438.509 1420.229 1384.571 0.000 1369.143
[9] 1368.098 1341.900
> rowVars(tmp5,na.rm=TRUE)
[1] 7956.62397 76.22303 41.31161 59.94388 107.35571 115.25214
[7] NA 67.96497 39.33306 48.35205
> rowSd(tmp5,na.rm=TRUE)
[1] 89.199910 8.730580 6.427411 7.742343 10.361260 10.735555 NA
[8] 8.244087 6.271607 6.953564
> rowMax(tmp5,na.rm=TRUE)
[1] 468.52120 92.36601 78.26907 87.34712 86.96350 84.51885 NA
[8] 83.11466 77.32627 80.94093
> rowMin(tmp5,na.rm=TRUE)
[1] 54.00277 58.96425 55.93204 55.93132 53.96733 55.38394 NA 53.80077
[9] 59.09431 54.06135
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.86894 70.96118 74.35574 62.75499 72.57072 67.14953 70.39778
[8] 69.88574 71.03930 70.02049 63.67865 68.38479 70.81808 NaN
[15] 70.17966 69.19954 69.58153 74.54774 72.61046 69.14353
> colSums(tmp5,na.rm=TRUE)
[1] 1033.8205 638.6506 669.2016 564.7950 653.1365 604.3458 633.5800
[8] 628.9717 639.3537 630.1844 573.1078 615.4631 637.3627 0.0000
[15] 631.6169 622.7958 626.2338 670.9296 653.4941 622.2918
> colVars(tmp5,na.rm=TRUE)
[1] 17625.99103 100.80188 84.62936 62.41920 63.05593 25.98502
[7] 80.38171 67.36493 73.14684 57.90990 47.41116 62.00668
[13] 65.67334 NA 67.22248 145.18813 50.82121 35.03752
[19] 119.20076 23.26169
> colSd(tmp5,na.rm=TRUE)
[1] 132.762913 10.040014 9.199422 7.900583 7.940776 5.097550
[7] 8.965585 8.207614 8.552593 7.609855 6.885576 7.874432
[13] 8.103909 NA 8.198932 12.049404 7.128900 5.919250
[19] 10.917910 4.823037
> colMax(tmp5,na.rm=TRUE)
[1] 468.52120 92.36601 84.90136 72.63968 86.96350 73.14891 86.22511
[8] 83.43078 82.44610 77.94167 74.77615 81.92677 84.51885 -Inf
[15] 83.44246 91.96819 84.11330 85.77636 87.34712 73.74175
> colMin(tmp5,na.rm=TRUE)
[1] 64.40314 56.73554 56.63231 53.96733 61.87555 59.09431 60.85645 62.10603
[9] 53.80077 55.93204 55.38394 58.96425 56.30028 Inf 56.77080 55.84243
[17] 61.01485 64.52515 54.06135 59.35315
>
>
>
>
> 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] 217.1547 273.0180 238.4859 207.3484 155.9404 138.7998 302.8902 312.1685
[9] 384.0223 320.1790
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 217.1547 273.0180 238.4859 207.3484 155.9404 138.7998 302.8902 312.1685
[9] 384.0223 320.1790
>
>
>
> 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] -8.526513e-14 -1.136868e-13 0.000000e+00 -1.136868e-13 5.684342e-14
[6] 2.273737e-13 1.989520e-13 -1.705303e-13 2.842171e-14 2.842171e-14
[11] 5.684342e-14 8.526513e-14 0.000000e+00 0.000000e+00 5.684342e-14
[16] -1.421085e-13 -5.684342e-14 1.705303e-13 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)
+ }
8 2
8 3
8 19
5 4
5 2
2 12
5 10
1 11
5 6
3 4
1 18
7 2
10 11
4 17
3 20
5 13
10 19
9 15
10 2
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] 1.868437
> Min(tmp)
[1] -1.792183
> mean(tmp)
[1] 0.09503146
> Sum(tmp)
[1] 9.503146
> Var(tmp)
[1] 0.7608389
>
> rowMeans(tmp)
[1] 0.09503146
> rowSums(tmp)
[1] 9.503146
> rowVars(tmp)
[1] 0.7608389
> rowSd(tmp)
[1] 0.8722608
> rowMax(tmp)
[1] 1.868437
> rowMin(tmp)
[1] -1.792183
>
> colMeans(tmp)
[1] 0.031197151 -0.467076561 0.655030510 -1.654078971 1.164519159
[6] -1.792183295 0.320035209 0.593359498 0.549742867 0.389220864
[11] 0.474736390 1.787880323 -1.698398489 0.529066551 0.926146577
[16] -1.073997705 0.266136501 -1.270826441 -0.666316999 0.133056255
[21] -0.295734787 0.398237174 0.641403952 -0.322864884 -1.144828232
[26] 0.091373327 -0.245520809 0.094982868 1.703680202 -0.948035455
[31] 1.228170363 -0.491845145 -0.419248927 0.376950845 1.255884095
[36] -0.722278746 0.003197664 0.042865849 -0.734716863 0.098268409
[41] 1.868437178 -0.877687626 -0.421609874 0.808684525 1.444776155
[46] 0.732205414 -0.593077891 1.151366149 0.130015148 0.938622324
[51] 1.315577393 -0.933067367 -0.954402963 -0.988464886 -0.136657926
[56] 0.908593704 0.498771684 0.939328107 0.498963958 0.721456655
[61] 1.324933045 0.223051588 -0.264243998 1.159143057 -0.275657555
[66] -1.236476398 -0.221264050 -0.540648431 -0.327375185 0.755549595
[71] 0.206768051 -0.578918619 1.130945532 1.350263941 -0.744554600
[76] 0.890117194 0.045684493 1.106807830 -0.061458406 0.498085897
[81] 0.250917138 1.101375333 -0.070228670 0.457433009 -0.715671960
[86] 0.305692726 -1.779370695 -1.136658475 1.229138406 -0.807204001
[91] -0.138647394 0.057691766 0.149024260 0.834825712 -1.297991303
[96] 0.532149385 -0.403938300 1.596436692 -0.653181856 -1.308419327
> colSums(tmp)
[1] 0.031197151 -0.467076561 0.655030510 -1.654078971 1.164519159
[6] -1.792183295 0.320035209 0.593359498 0.549742867 0.389220864
[11] 0.474736390 1.787880323 -1.698398489 0.529066551 0.926146577
[16] -1.073997705 0.266136501 -1.270826441 -0.666316999 0.133056255
[21] -0.295734787 0.398237174 0.641403952 -0.322864884 -1.144828232
[26] 0.091373327 -0.245520809 0.094982868 1.703680202 -0.948035455
[31] 1.228170363 -0.491845145 -0.419248927 0.376950845 1.255884095
[36] -0.722278746 0.003197664 0.042865849 -0.734716863 0.098268409
[41] 1.868437178 -0.877687626 -0.421609874 0.808684525 1.444776155
[46] 0.732205414 -0.593077891 1.151366149 0.130015148 0.938622324
[51] 1.315577393 -0.933067367 -0.954402963 -0.988464886 -0.136657926
[56] 0.908593704 0.498771684 0.939328107 0.498963958 0.721456655
[61] 1.324933045 0.223051588 -0.264243998 1.159143057 -0.275657555
[66] -1.236476398 -0.221264050 -0.540648431 -0.327375185 0.755549595
[71] 0.206768051 -0.578918619 1.130945532 1.350263941 -0.744554600
[76] 0.890117194 0.045684493 1.106807830 -0.061458406 0.498085897
[81] 0.250917138 1.101375333 -0.070228670 0.457433009 -0.715671960
[86] 0.305692726 -1.779370695 -1.136658475 1.229138406 -0.807204001
[91] -0.138647394 0.057691766 0.149024260 0.834825712 -1.297991303
[96] 0.532149385 -0.403938300 1.596436692 -0.653181856 -1.308419327
> 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] 0.031197151 -0.467076561 0.655030510 -1.654078971 1.164519159
[6] -1.792183295 0.320035209 0.593359498 0.549742867 0.389220864
[11] 0.474736390 1.787880323 -1.698398489 0.529066551 0.926146577
[16] -1.073997705 0.266136501 -1.270826441 -0.666316999 0.133056255
[21] -0.295734787 0.398237174 0.641403952 -0.322864884 -1.144828232
[26] 0.091373327 -0.245520809 0.094982868 1.703680202 -0.948035455
[31] 1.228170363 -0.491845145 -0.419248927 0.376950845 1.255884095
[36] -0.722278746 0.003197664 0.042865849 -0.734716863 0.098268409
[41] 1.868437178 -0.877687626 -0.421609874 0.808684525 1.444776155
[46] 0.732205414 -0.593077891 1.151366149 0.130015148 0.938622324
[51] 1.315577393 -0.933067367 -0.954402963 -0.988464886 -0.136657926
[56] 0.908593704 0.498771684 0.939328107 0.498963958 0.721456655
[61] 1.324933045 0.223051588 -0.264243998 1.159143057 -0.275657555
[66] -1.236476398 -0.221264050 -0.540648431 -0.327375185 0.755549595
[71] 0.206768051 -0.578918619 1.130945532 1.350263941 -0.744554600
[76] 0.890117194 0.045684493 1.106807830 -0.061458406 0.498085897
[81] 0.250917138 1.101375333 -0.070228670 0.457433009 -0.715671960
[86] 0.305692726 -1.779370695 -1.136658475 1.229138406 -0.807204001
[91] -0.138647394 0.057691766 0.149024260 0.834825712 -1.297991303
[96] 0.532149385 -0.403938300 1.596436692 -0.653181856 -1.308419327
> colMin(tmp)
[1] 0.031197151 -0.467076561 0.655030510 -1.654078971 1.164519159
[6] -1.792183295 0.320035209 0.593359498 0.549742867 0.389220864
[11] 0.474736390 1.787880323 -1.698398489 0.529066551 0.926146577
[16] -1.073997705 0.266136501 -1.270826441 -0.666316999 0.133056255
[21] -0.295734787 0.398237174 0.641403952 -0.322864884 -1.144828232
[26] 0.091373327 -0.245520809 0.094982868 1.703680202 -0.948035455
[31] 1.228170363 -0.491845145 -0.419248927 0.376950845 1.255884095
[36] -0.722278746 0.003197664 0.042865849 -0.734716863 0.098268409
[41] 1.868437178 -0.877687626 -0.421609874 0.808684525 1.444776155
[46] 0.732205414 -0.593077891 1.151366149 0.130015148 0.938622324
[51] 1.315577393 -0.933067367 -0.954402963 -0.988464886 -0.136657926
[56] 0.908593704 0.498771684 0.939328107 0.498963958 0.721456655
[61] 1.324933045 0.223051588 -0.264243998 1.159143057 -0.275657555
[66] -1.236476398 -0.221264050 -0.540648431 -0.327375185 0.755549595
[71] 0.206768051 -0.578918619 1.130945532 1.350263941 -0.744554600
[76] 0.890117194 0.045684493 1.106807830 -0.061458406 0.498085897
[81] 0.250917138 1.101375333 -0.070228670 0.457433009 -0.715671960
[86] 0.305692726 -1.779370695 -1.136658475 1.229138406 -0.807204001
[91] -0.138647394 0.057691766 0.149024260 0.834825712 -1.297991303
[96] 0.532149385 -0.403938300 1.596436692 -0.653181856 -1.308419327
> colMedians(tmp)
[1] 0.031197151 -0.467076561 0.655030510 -1.654078971 1.164519159
[6] -1.792183295 0.320035209 0.593359498 0.549742867 0.389220864
[11] 0.474736390 1.787880323 -1.698398489 0.529066551 0.926146577
[16] -1.073997705 0.266136501 -1.270826441 -0.666316999 0.133056255
[21] -0.295734787 0.398237174 0.641403952 -0.322864884 -1.144828232
[26] 0.091373327 -0.245520809 0.094982868 1.703680202 -0.948035455
[31] 1.228170363 -0.491845145 -0.419248927 0.376950845 1.255884095
[36] -0.722278746 0.003197664 0.042865849 -0.734716863 0.098268409
[41] 1.868437178 -0.877687626 -0.421609874 0.808684525 1.444776155
[46] 0.732205414 -0.593077891 1.151366149 0.130015148 0.938622324
[51] 1.315577393 -0.933067367 -0.954402963 -0.988464886 -0.136657926
[56] 0.908593704 0.498771684 0.939328107 0.498963958 0.721456655
[61] 1.324933045 0.223051588 -0.264243998 1.159143057 -0.275657555
[66] -1.236476398 -0.221264050 -0.540648431 -0.327375185 0.755549595
[71] 0.206768051 -0.578918619 1.130945532 1.350263941 -0.744554600
[76] 0.890117194 0.045684493 1.106807830 -0.061458406 0.498085897
[81] 0.250917138 1.101375333 -0.070228670 0.457433009 -0.715671960
[86] 0.305692726 -1.779370695 -1.136658475 1.229138406 -0.807204001
[91] -0.138647394 0.057691766 0.149024260 0.834825712 -1.297991303
[96] 0.532149385 -0.403938300 1.596436692 -0.653181856 -1.308419327
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.03119715 -0.4670766 0.6550305 -1.654079 1.164519 -1.792183 0.3200352
[2,] 0.03119715 -0.4670766 0.6550305 -1.654079 1.164519 -1.792183 0.3200352
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.5933595 0.5497429 0.3892209 0.4747364 1.78788 -1.698398 0.5290666
[2,] 0.5933595 0.5497429 0.3892209 0.4747364 1.78788 -1.698398 0.5290666
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.9261466 -1.073998 0.2661365 -1.270826 -0.666317 0.1330563 -0.2957348
[2,] 0.9261466 -1.073998 0.2661365 -1.270826 -0.666317 0.1330563 -0.2957348
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.3982372 0.641404 -0.3228649 -1.144828 0.09137333 -0.2455208 0.09498287
[2,] 0.3982372 0.641404 -0.3228649 -1.144828 0.09137333 -0.2455208 0.09498287
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.70368 -0.9480355 1.22817 -0.4918451 -0.4192489 0.3769508 1.255884
[2,] 1.70368 -0.9480355 1.22817 -0.4918451 -0.4192489 0.3769508 1.255884
[,36] [,37] [,38] [,39] [,40] [,41]
[1,] -0.7222787 0.003197664 0.04286585 -0.7347169 0.09826841 1.868437
[2,] -0.7222787 0.003197664 0.04286585 -0.7347169 0.09826841 1.868437
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] -0.8776876 -0.4216099 0.8086845 1.444776 0.7322054 -0.5930779 1.151366
[2,] -0.8776876 -0.4216099 0.8086845 1.444776 0.7322054 -0.5930779 1.151366
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] 0.1300151 0.9386223 1.315577 -0.9330674 -0.954403 -0.9884649 -0.1366579
[2,] 0.1300151 0.9386223 1.315577 -0.9330674 -0.954403 -0.9884649 -0.1366579
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] 0.9085937 0.4987717 0.9393281 0.498964 0.7214567 1.324933 0.2230516
[2,] 0.9085937 0.4987717 0.9393281 0.498964 0.7214567 1.324933 0.2230516
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] -0.264244 1.159143 -0.2756576 -1.236476 -0.2212641 -0.5406484 -0.3273752
[2,] -0.264244 1.159143 -0.2756576 -1.236476 -0.2212641 -0.5406484 -0.3273752
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 0.7555496 0.2067681 -0.5789186 1.130946 1.350264 -0.7445546 0.8901172
[2,] 0.7555496 0.2067681 -0.5789186 1.130946 1.350264 -0.7445546 0.8901172
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] 0.04568449 1.106808 -0.06145841 0.4980859 0.2509171 1.101375 -0.07022867
[2,] 0.04568449 1.106808 -0.06145841 0.4980859 0.2509171 1.101375 -0.07022867
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 0.457433 -0.715672 0.3056927 -1.779371 -1.136658 1.229138 -0.807204
[2,] 0.457433 -0.715672 0.3056927 -1.779371 -1.136658 1.229138 -0.807204
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -0.1386474 0.05769177 0.1490243 0.8348257 -1.297991 0.5321494 -0.4039383
[2,] -0.1386474 0.05769177 0.1490243 0.8348257 -1.297991 0.5321494 -0.4039383
[,98] [,99] [,100]
[1,] 1.596437 -0.6531819 -1.308419
[2,] 1.596437 -0.6531819 -1.308419
>
>
> Max(tmp2)
[1] 3.596107
> Min(tmp2)
[1] -2.169092
> mean(tmp2)
[1] 0.1990787
> Sum(tmp2)
[1] 19.90787
> Var(tmp2)
[1] 1.073782
>
> rowMeans(tmp2)
[1] -0.6184360442 1.6369491967 -1.4178314455 -0.5806316085 0.0958878695
[6] 0.4934733337 -0.5491233793 0.7451173037 -1.8315094064 0.6609103109
[11] -0.4175398472 -0.7421436554 -0.1237675515 0.1088668367 -0.9569630849
[16] 2.9006289325 -0.7675342180 1.3309613361 0.6104945199 1.6369923958
[21] -0.1887587612 0.7987734760 0.1554703419 -2.1690920845 0.5443181414
[26] 0.5117325923 0.0759857734 1.2813131344 0.8424298088 0.1500961918
[31] -0.8149062024 -0.4278386878 1.5858354924 -0.2586031599 -0.1321449719
[36] 0.6090354751 -0.4971783739 0.5775091056 0.0126704542 -0.9719506113
[41] -0.7087655626 1.0424655794 3.5961071808 2.6262685062 1.1145392877
[46] 0.8813262519 -0.6791182313 -0.2136344614 0.7978439804 0.1470226015
[51] 0.6906177669 0.1371349376 -1.3207770626 0.4819761954 -1.2331487603
[56] -0.8459064701 -1.0318608948 2.1872610713 -0.2093499664 -1.0391287685
[61] -0.4059640633 -0.8050267252 1.3894682861 -0.6995546464 1.1520661743
[66] 0.6425697420 -1.3586343174 1.8366262283 0.4990066547 -0.2060714834
[71] 0.1855900513 -0.1582066704 -0.0468193323 0.8212909447 -0.9363141845
[76] -0.3967500232 -0.6316074545 0.3298617270 0.5423518497 -0.1900418296
[81] 0.6499280377 -0.4863119716 1.6538750615 -0.1751335279 1.1393449341
[86] -1.1807678089 1.4085122252 -1.0868251098 -0.7398295640 -0.0006324788
[91] 0.4946622264 2.3357284847 -0.5186268933 0.8283906916 0.9090321523
[96] 0.9665478636 1.2895715425 -0.7684277375 0.8162175765 0.4884042171
> rowSums(tmp2)
[1] -0.6184360442 1.6369491967 -1.4178314455 -0.5806316085 0.0958878695
[6] 0.4934733337 -0.5491233793 0.7451173037 -1.8315094064 0.6609103109
[11] -0.4175398472 -0.7421436554 -0.1237675515 0.1088668367 -0.9569630849
[16] 2.9006289325 -0.7675342180 1.3309613361 0.6104945199 1.6369923958
[21] -0.1887587612 0.7987734760 0.1554703419 -2.1690920845 0.5443181414
[26] 0.5117325923 0.0759857734 1.2813131344 0.8424298088 0.1500961918
[31] -0.8149062024 -0.4278386878 1.5858354924 -0.2586031599 -0.1321449719
[36] 0.6090354751 -0.4971783739 0.5775091056 0.0126704542 -0.9719506113
[41] -0.7087655626 1.0424655794 3.5961071808 2.6262685062 1.1145392877
[46] 0.8813262519 -0.6791182313 -0.2136344614 0.7978439804 0.1470226015
[51] 0.6906177669 0.1371349376 -1.3207770626 0.4819761954 -1.2331487603
[56] -0.8459064701 -1.0318608948 2.1872610713 -0.2093499664 -1.0391287685
[61] -0.4059640633 -0.8050267252 1.3894682861 -0.6995546464 1.1520661743
[66] 0.6425697420 -1.3586343174 1.8366262283 0.4990066547 -0.2060714834
[71] 0.1855900513 -0.1582066704 -0.0468193323 0.8212909447 -0.9363141845
[76] -0.3967500232 -0.6316074545 0.3298617270 0.5423518497 -0.1900418296
[81] 0.6499280377 -0.4863119716 1.6538750615 -0.1751335279 1.1393449341
[86] -1.1807678089 1.4085122252 -1.0868251098 -0.7398295640 -0.0006324788
[91] 0.4946622264 2.3357284847 -0.5186268933 0.8283906916 0.9090321523
[96] 0.9665478636 1.2895715425 -0.7684277375 0.8162175765 0.4884042171
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] -0.6184360442 1.6369491967 -1.4178314455 -0.5806316085 0.0958878695
[6] 0.4934733337 -0.5491233793 0.7451173037 -1.8315094064 0.6609103109
[11] -0.4175398472 -0.7421436554 -0.1237675515 0.1088668367 -0.9569630849
[16] 2.9006289325 -0.7675342180 1.3309613361 0.6104945199 1.6369923958
[21] -0.1887587612 0.7987734760 0.1554703419 -2.1690920845 0.5443181414
[26] 0.5117325923 0.0759857734 1.2813131344 0.8424298088 0.1500961918
[31] -0.8149062024 -0.4278386878 1.5858354924 -0.2586031599 -0.1321449719
[36] 0.6090354751 -0.4971783739 0.5775091056 0.0126704542 -0.9719506113
[41] -0.7087655626 1.0424655794 3.5961071808 2.6262685062 1.1145392877
[46] 0.8813262519 -0.6791182313 -0.2136344614 0.7978439804 0.1470226015
[51] 0.6906177669 0.1371349376 -1.3207770626 0.4819761954 -1.2331487603
[56] -0.8459064701 -1.0318608948 2.1872610713 -0.2093499664 -1.0391287685
[61] -0.4059640633 -0.8050267252 1.3894682861 -0.6995546464 1.1520661743
[66] 0.6425697420 -1.3586343174 1.8366262283 0.4990066547 -0.2060714834
[71] 0.1855900513 -0.1582066704 -0.0468193323 0.8212909447 -0.9363141845
[76] -0.3967500232 -0.6316074545 0.3298617270 0.5423518497 -0.1900418296
[81] 0.6499280377 -0.4863119716 1.6538750615 -0.1751335279 1.1393449341
[86] -1.1807678089 1.4085122252 -1.0868251098 -0.7398295640 -0.0006324788
[91] 0.4946622264 2.3357284847 -0.5186268933 0.8283906916 0.9090321523
[96] 0.9665478636 1.2895715425 -0.7684277375 0.8162175765 0.4884042171
> rowMin(tmp2)
[1] -0.6184360442 1.6369491967 -1.4178314455 -0.5806316085 0.0958878695
[6] 0.4934733337 -0.5491233793 0.7451173037 -1.8315094064 0.6609103109
[11] -0.4175398472 -0.7421436554 -0.1237675515 0.1088668367 -0.9569630849
[16] 2.9006289325 -0.7675342180 1.3309613361 0.6104945199 1.6369923958
[21] -0.1887587612 0.7987734760 0.1554703419 -2.1690920845 0.5443181414
[26] 0.5117325923 0.0759857734 1.2813131344 0.8424298088 0.1500961918
[31] -0.8149062024 -0.4278386878 1.5858354924 -0.2586031599 -0.1321449719
[36] 0.6090354751 -0.4971783739 0.5775091056 0.0126704542 -0.9719506113
[41] -0.7087655626 1.0424655794 3.5961071808 2.6262685062 1.1145392877
[46] 0.8813262519 -0.6791182313 -0.2136344614 0.7978439804 0.1470226015
[51] 0.6906177669 0.1371349376 -1.3207770626 0.4819761954 -1.2331487603
[56] -0.8459064701 -1.0318608948 2.1872610713 -0.2093499664 -1.0391287685
[61] -0.4059640633 -0.8050267252 1.3894682861 -0.6995546464 1.1520661743
[66] 0.6425697420 -1.3586343174 1.8366262283 0.4990066547 -0.2060714834
[71] 0.1855900513 -0.1582066704 -0.0468193323 0.8212909447 -0.9363141845
[76] -0.3967500232 -0.6316074545 0.3298617270 0.5423518497 -0.1900418296
[81] 0.6499280377 -0.4863119716 1.6538750615 -0.1751335279 1.1393449341
[86] -1.1807678089 1.4085122252 -1.0868251098 -0.7398295640 -0.0006324788
[91] 0.4946622264 2.3357284847 -0.5186268933 0.8283906916 0.9090321523
[96] 0.9665478636 1.2895715425 -0.7684277375 0.8162175765 0.4884042171
>
> colMeans(tmp2)
[1] 0.1990787
> colSums(tmp2)
[1] 19.90787
> colVars(tmp2)
[1] 1.073782
> colSd(tmp2)
[1] 1.036235
> colMax(tmp2)
[1] 3.596107
> colMin(tmp2)
[1] -2.169092
> colMedians(tmp2)
[1] 0.1230009
> colRanges(tmp2)
[,1]
[1,] -2.169092
[2,] 3.596107
>
> 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] 2.1470451 -3.3098648 -0.0635931 -1.2630939 1.9166114 0.9732878
[7] -7.5583213 0.1231686 -3.1131492 1.4089466
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.9937587
[2,] -0.5498934
[3,] 0.2730236
[4,] 0.6233587
[5,] 2.0300696
>
> rowApply(tmp,sum)
[1] -7.8793071 -1.7359310 1.9456084 -0.6894045 -0.3625124 -1.1937341
[7] 0.4189405 0.6645571 -0.1338766 0.2266971
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 5 6 10 3 9 8 7 2 2
[2,] 6 1 1 7 10 7 2 2 4 5
[3,] 7 2 3 8 9 8 3 4 6 9
[4,] 5 7 7 1 4 2 7 1 10 8
[5,] 4 3 4 5 6 10 6 8 9 6
[6,] 8 10 8 6 1 5 10 6 5 7
[7,] 1 4 5 3 7 1 1 3 3 4
[8,] 9 6 2 4 2 4 5 9 7 10
[9,] 3 9 10 2 5 6 4 5 1 3
[10,] 2 8 9 9 8 3 9 10 8 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 4.85229488 1.46513712 -0.51834816 -1.20127944 0.28990633 1.05659123
[7] -1.70103955 -1.34587759 0.09044199 -1.64390756 5.85767693 -1.41878538
[13] -2.25322704 2.57268738 -0.98997635 -2.02483006 -0.49977531 -0.48509972
[19] 2.09411565 0.59750308
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.1001459
[2,] 0.5003452
[3,] 0.8869396
[4,] 1.2963635
[5,] 2.2687924
>
> rowApply(tmp,sum)
[1] 3.734284 -4.083666 1.362120 6.010427 -2.228956
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 19 12 16 19 17
[2,] 5 5 18 18 10
[3,] 18 7 3 13 12
[4,] 4 15 6 14 3
[5,] 6 17 8 12 13
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.2963635 -0.4620600 1.04979960 -0.6599723 -0.37091552 0.85794115
[2,] -0.1001459 -1.0331298 -0.82379608 0.3670608 0.73794253 -0.22591901
[3,] 0.8869396 1.3107896 -0.98086587 -0.6273039 -0.27980659 0.04638009
[4,] 2.2687924 2.0308832 0.33314303 0.5672628 0.25044394 0.83181039
[5,] 0.5003452 -0.3813458 -0.09662884 -0.8483268 -0.04775803 -0.45362139
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.8809506 -0.1251783 -0.35344529 0.36958656 0.9667909 0.7504415
[2,] -0.2525464 -1.4136768 1.45740890 -0.89037155 2.4920345 0.5875056
[3,] -1.6216855 0.5254539 -0.21357239 -0.72383182 2.8002729 -1.3107404
[4,] 2.6369022 -0.5967964 0.06707678 -0.01480018 0.1455583 -0.7968656
[5,] -0.5827593 0.2643200 -0.86702601 -0.38449057 -0.5469796 -0.6491264
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.4404266 0.49159447 0.3707809 1.60851218 0.9801809 -0.78540160
[2,] -1.6918052 0.77567137 -1.0929329 -1.75918648 -0.3854826 -0.76627798
[3,] -0.1930847 0.13315598 0.1664111 -0.01895069 -0.7378514 1.28718375
[4,] -0.1815038 0.01877234 -1.6917562 -2.23809884 -0.5040869 0.08111439
[5,] 1.2535933 1.15349321 1.2575207 0.38289377 0.1474646 -0.30171827
[,19] [,20]
[1,] 0.58795792 0.48268462
[2,] -0.04615516 -0.01986386
[3,] 1.43379853 -0.52057227
[4,] 0.88406553 1.91850950
[5,] -0.76555117 -1.26325492
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.10-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-3.10-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 567 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.10-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 -0.6567541 -1.872539 -0.5536373 -0.4005852 0.1719554 -0.4803694 -2.062669
col8 col9 col10 col11 col12 col13 col14
row1 -0.558259 1.900012 -0.3910387 -0.6518288 0.4199666 -0.9724263 1.295234
col15 col16 col17 col18 col19 col20
row1 0.2250245 -0.5633068 -0.7828091 -0.3497952 -1.605394 -1.467985
> tmp[,"col10"]
col10
row1 -0.3910387
row2 0.8267922
row3 -0.8252844
row4 0.5903340
row5 -0.5512609
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.6567541 -1.872539 -0.5536373 -0.4005852 0.1719554 -0.4803694 -2.0626693
row5 -2.7410521 1.836299 0.6905878 0.7268871 0.9838162 -2.3626849 -0.3633442
col8 col9 col10 col11 col12 col13 col14
row1 -0.5582590 1.9000116 -0.3910387 -0.6518288 0.41996658 -0.9724263 1.295234
row5 0.2429543 0.2539994 -0.5512609 -0.8658917 0.07851758 1.3815556 -0.943657
col15 col16 col17 col18 col19 col20
row1 0.2250245 -0.5633068 -0.7828091 -0.3497952 -1.605394 -1.4679855
row5 -0.3525345 1.2848108 -1.0183753 -0.6572045 1.965604 -0.9064703
> tmp[,c("col6","col20")]
col6 col20
row1 -0.4803694 -1.4679855
row2 -1.4863889 -0.1730651
row3 -0.2503530 -0.3891187
row4 -0.4927954 0.8491295
row5 -2.3626849 -0.9064703
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.4803694 -1.4679855
row5 -2.3626849 -0.9064703
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.0773 51.56064 50.16086 49.10859 51.45048 104.1809 49.82359 50.87022
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.23701 49.65411 51.15482 50.12261 51.28252 49.7447 49.44902 48.04473
col17 col18 col19 col20
row1 49.53558 50.64897 50.02606 106.7281
> tmp[,"col10"]
col10
row1 49.65411
row2 30.53248
row3 30.99942
row4 29.36945
row5 49.65418
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.07730 51.56064 50.16086 49.10859 51.45048 104.1809 49.82359 50.87022
row5 51.52336 49.18285 48.10806 47.98649 49.41946 105.3497 50.54226 50.13301
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.23701 49.65411 51.15482 50.12261 51.28252 49.74470 49.44902 48.04473
row5 50.37476 49.65418 50.40753 50.08564 50.00697 49.40785 49.16310 49.90698
col17 col18 col19 col20
row1 49.53558 50.64897 50.02606 106.7281
row5 51.36353 48.48723 49.25495 104.5396
> tmp[,c("col6","col20")]
col6 col20
row1 104.18088 106.72809
row2 75.37958 73.90586
row3 74.42805 75.14202
row4 73.58516 74.42089
row5 105.34965 104.53960
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.1809 106.7281
row5 105.3497 104.5396
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.1809 106.7281
row5 105.3497 104.5396
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.7868133
[2,] 1.7938793
[3,] 0.8968126
[4,] -0.3756508
[5,] -0.5959405
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.1310221 1.7042909
[2,] 0.1986820 0.2245942
[3,] 1.1644991 -0.4689276
[4,] -1.4370356 1.0884700
[5,] 0.8503402 0.5175300
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.4256324 -0.4105534
[2,] 1.7734649 1.7834494
[3,] 0.3136617 -1.6766147
[4,] -2.7217261 0.8549321
[5,] 2.2502291 1.0291483
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.4256324
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.4256324
[2,] 1.7734649
>
>
>
> 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 0.2171634 1.4579766 0.3118843 0.06438733 1.2687663 -0.2842399 0.2036103
row1 -0.6282039 0.6498406 -1.3965538 -1.81199563 0.5067162 0.6458475 2.7189836
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.8896021 0.7742209 0.6310440 0.4533786 0.8582195 -0.6032722 -0.6534307
row1 -0.3779218 0.1801003 0.7402092 -1.3203050 0.6919280 -0.7648441 0.2830550
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.03027922 0.41256401 -0.3450704 -1.42178615 1.7856542 -2.081097
row1 0.58697152 -0.08824524 -0.7030488 0.02617027 0.8799937 1.623906
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.3780234 -1.551537 -1.501436 -1.831253 -0.1912473 1.04586 -1.520267
[,8] [,9] [,10]
row2 1.367157 0.9359332 0.5780771
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.9954869 -1.151713 -1.972983 0.2545416 0.3764509 0.7602619 -0.9521534
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.660939 -1.475153 -0.4288628 0.05551797 -0.1327328 -0.1775207 -0.9659739
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.1851081 -0.7659593 0.203417 -2.075812 -1.076464 -0.7991006
>
>
> 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: 0x7f92a2400a00>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM15d3a7fc186a1"
[2] "/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM15d3a7a6df58d"
[3] "/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM15d3a49143ac6"
[4] "/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM15d3a4f1ec2a5"
[5] "/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM15d3a6c7d0737"
[6] "/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM15d3a464e386"
[7] "/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM15d3a7b9574aa"
[8] "/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM15d3a111e8449"
[9] "/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM15d3a6a7edd66"
[10] "/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM15d3a2ef98a29"
[11] "/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM15d3adda1d7"
[12] "/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM15d3a56ac2ab2"
[13] "/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM15d3a41273892"
[14] "/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM15d3a75f31aa8"
[15] "/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM15d3a2b5b4817"
>
>
> ### 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: 0x7f92aea0b5e0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x7f92aea0b5e0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x7f92aea0b5e0>
> rowMedians(tmp)
[1] -7.179365e-02 -5.423550e-01 3.451036e-01 4.022077e-01 1.206088e-01
[6] -4.863658e-02 1.979518e-03 -3.389816e-01 -1.648681e-01 -3.145217e-01
[11] 5.288489e-02 -4.760794e-03 -1.332705e-01 2.065777e-01 -9.537983e-02
[16] 1.073606e-01 1.751306e-01 2.961117e-01 -5.917090e-02 -7.281195e-01
[21] 2.657239e-01 8.496110e-01 -1.723566e-01 5.327362e-01 -3.291872e-01
[26] -2.453055e-01 4.426801e-01 -4.024913e-01 -8.397539e-02 -3.025319e-01
[31] 2.791097e-01 1.348833e-01 1.184522e-01 2.937070e-01 3.346517e-01
[36] -4.712067e-01 7.517777e-01 1.476678e-01 -7.537686e-02 -3.506570e-01
[41] -9.195046e-02 -3.608954e-01 1.361556e-01 4.271682e-01 5.596293e-02
[46] 3.362676e-02 -9.379688e-01 4.923943e-01 6.798037e-01 -2.265390e-01
[51] 4.455737e-01 2.366039e-01 -7.448574e-01 -2.004880e-01 -2.966491e-01
[56] -8.568066e-02 2.546244e-01 2.110412e-01 -1.986463e-01 -5.605828e-02
[61] -9.513382e-02 3.917979e-02 -4.071036e-02 3.956338e-01 -1.053324e-01
[66] 1.751993e-01 -3.976729e-01 -2.499055e-02 -3.746054e-01 -4.148142e-01
[71] 2.441037e-01 -5.348251e-01 1.365885e-01 -2.270032e-01 -3.372304e-01
[76] -2.510394e-01 2.485935e-01 -8.947475e-02 -3.646062e-01 -6.193156e-02
[81] 2.030381e-01 -1.373238e-01 -3.056263e-01 4.340063e-01 -3.431841e-01
[86] 2.924845e-01 1.389350e-01 -4.257964e-01 -2.700852e-01 -3.166625e-01
[91] 3.238431e-01 -9.623110e-02 -3.775217e-01 3.365238e-01 -8.637299e-02
[96] -6.631347e-01 4.387898e-01 -1.955332e-02 4.249876e-01 -1.278302e-01
[101] -2.593257e-02 7.574727e-02 -2.772585e-02 2.251844e-01 1.763060e-01
[106] -4.761516e-01 -1.611944e-01 -1.977814e-01 5.832397e-01 1.230771e-01
[111] 2.636936e-01 -3.990450e-01 -7.370437e-02 2.315945e-01 -4.940408e-01
[116] -6.134104e-01 -3.554364e-01 -9.803987e-01 3.261300e-01 1.301496e-01
[121] 1.105753e-01 4.357797e-01 6.014632e-02 1.236213e-01 2.491007e-01
[126] 1.851178e-01 1.877072e-01 2.816732e-01 2.756885e-01 -1.490146e-01
[131] -4.765738e-01 4.518213e-01 -4.034406e-02 1.623547e-02 -1.920849e-01
[136] 2.992144e-01 2.791199e-01 -1.744308e-01 -2.658749e-01 -1.944108e-01
[141] 1.149034e-02 -3.518238e-01 -4.647975e-01 -2.278276e-02 -3.869564e-01
[146] -8.348284e-02 -5.043190e-02 1.127761e-01 -5.668828e-02 5.083813e-02
[151] -3.393735e-01 1.053906e-01 4.060472e-01 -1.121423e-01 3.355087e-02
[156] -4.407859e-01 -2.190738e-01 -4.054742e-01 3.616115e-02 3.697268e-02
[161] -8.082266e-02 2.599149e-01 -2.052461e-01 -4.359756e-01 1.818690e-01
[166] 1.808982e-01 -3.392656e-02 -3.888632e-01 5.187299e-01 1.209188e-01
[171] -3.546779e-01 4.233355e-01 -2.236312e-01 3.806291e-01 1.664993e-02
[176] -4.904146e-01 4.964677e-01 -4.118446e-01 2.447706e-01 -7.665212e-02
[181] 1.284168e-01 2.994973e-01 -5.149251e-01 1.257342e-01 -1.302834e-01
[186] -4.968046e-02 1.202617e-01 1.833286e-01 1.564229e-01 7.540314e-02
[191] -1.633905e-01 1.392036e-01 -3.303898e-01 -6.521687e-02 1.611442e-01
[196] 9.983042e-05 -8.462314e-02 4.585896e-01 -1.949121e-01 1.776657e-01
[201] -3.091289e-02 -3.393608e-01 2.211782e-01 -2.716121e-01 -1.179599e-01
[206] -4.679930e-01 5.249679e-01 1.298306e-01 -2.854676e-01 -7.802243e-02
[211] 1.373458e-01 -2.979526e-01 9.662314e-03 -2.526234e-01 6.800735e-02
[216] 8.901646e-03 -3.268025e-01 3.769072e-01 1.218612e-01 7.640357e-01
[221] 2.308573e-01 -1.195075e-01 -1.391981e-01 -3.183464e-02 1.086370e-02
[226] -4.011983e-01 2.235457e-01 -5.275385e-01 -9.532662e-02 -2.143236e-01
>
> proc.time()
user system elapsed
4.043 6.738 11.250
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 3.6.3 (2020-02-29) -- "Holding the Windsock"
Copyright (C) 2020 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: 0x7f87aea06190>
> .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: 0x7f87aea06190>
> .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: 0x7f87aea06190>
> .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: 0x7f87aea06190>
> 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: 0x7f87b3400700>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7f87b3400700>
> .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: 0x7f87b3400700>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7f87b3400700>
> .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: 0x7f87b3400700>
> 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: 0x7f87b3508130>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7f87b3508130>
> .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: 0x7f87b3508130>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x7f87b3508130>
> .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: 0x7f87b3508130>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x7f87b3508130>
> .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: 0x7f87b3508130>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x7f87b3508130>
> .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: 0x7f87b3508130>
> 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: 0x7f87b3506f50>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x7f87b3506f50>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7f87b3506f50>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7f87b3506f50>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile15fca1845b148" "BufferedMatrixFile15fca779fa6b"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile15fca1845b148" "BufferedMatrixFile15fca779fa6b"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x7f87abe20340>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7f87abe20340>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x7f87abe20340>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x7f87abe20340>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x7f87abe20340>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x7f87abe20340>
> .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: 0x7f87b3504dc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7f87b3504dc0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x7f87b3504dc0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x7f87b3504dc0>
> 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: 0x7f87aee011a0>
> .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: 0x7f87aee011a0>
> rm(P)
>
> proc.time()
user system elapsed
0.455 0.118 0.545
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 3.6.3 (2020-02-29) -- "Holding the Windsock"
Copyright (C) 2020 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
0.420 0.082 0.477