Ben Bolstad
| Snapshot Date: 2019-04-15 17:01:12 -0400 (Mon, 15 Apr 2019) |
| URL: https://git.bioconductor.org/packages/BufferedMatrix |
| Branch: RELEASE_3_8 |
| Last Commit: 9fb17da |
| Last Changed Date: 2018-10-30 11:41:43 -0400 (Tue, 30 Oct 2018) |
| Back to Multiple platform build/check report for BioC 3.8 |
|
This page was generated on 2019-04-16 11:54:35 -0400 (Tue, 16 Apr 2019).
| Package 183/1649 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||
| BufferedMatrix 1.46.0 Ben Bolstad
| malbec1 | Linux (Ubuntu 16.04.6 LTS) / x86_64 | OK | OK | OK | | ||||||
| merida1 | OS X 10.11.6 El Capitan / x86_64 | OK | OK | [ OK ] | OK | |
| Package: BufferedMatrix |
| Version: 1.46.0 |
| 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_1.46.0.tar.gz |
| StartedAt: 2019-04-15 22:42:32 -0400 (Mon, 15 Apr 2019) |
| EndedAt: 2019-04-15 22:43:10 -0400 (Mon, 15 Apr 2019) |
| EllapsedTime: 38.4 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_1.46.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck’ * using R version 3.5.3 (2019-03-11) * 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 ‘1.46.0’ * 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-3.8-bioc/meat/BufferedMatrix.Rcheck/00check.log’ for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/3.5/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** libs
clang -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/usr/local/include -fPIC -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/usr/local/include -fPIC -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ˜
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/usr/local/include -fPIC -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/usr/local/include -fPIC -Wall -g -O2 -c init_package.c -o init_package.o
clang -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -single_module -multiply_defined suppress -L/Library/Frameworks/R.framework/Resources/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation
installing to /Library/Frameworks/R.framework/Versions/3.5/Resources/library/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 3.5.3 (2019-03-11) -- "Great Truth"
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
0.353 0.089 0.416
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 3.5.3 (2019-03-11) -- "Great Truth"
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-3.8-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 410406 22.0 867110 46.4 NA 610957 32.7
Vcells 745501 5.7 8388608 64.0 65536 1801998 13.8
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Mon Apr 15 22:42:53 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] "Mon Apr 15 22:42:53 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: 0x7fee0bf03c00>
>
>
>
> 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] "Mon Apr 15 22:42:56 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] "Mon Apr 15 22:42:57 2019"
>
> ColMode(tmp2)
<pointer: 0x7fee0bf03c00>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.54681885 -0.8339565 0.2122096 -1.1112079
[2,] -0.09987717 -0.4209788 -1.6927968 -1.1113734
[3,] -0.74150068 -0.8423694 2.1452775 0.4947072
[4,] -0.17421624 1.1918463 -0.1103544 0.6215638
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.54681885 0.8339565 0.2122096 1.1112079
[2,] 0.09987717 0.4209788 1.6927968 1.1113734
[3,] 0.74150068 0.8423694 2.1452775 0.4947072
[4,] 0.17421624 1.1918463 0.1103544 0.6215638
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.8-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,] 9.9773152 0.9132122 0.4606622 1.0541385
[2,] 0.3160335 0.6488288 1.3010752 1.0542170
[3,] 0.8611043 0.9178068 1.4646766 0.7033542
[4,] 0.4173922 1.0917171 0.3321964 0.7883932
>
> 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-3.8-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,] 224.31997 34.96608 29.81883 36.65259
[2,] 28.26021 31.90927 39.70355 36.65354
[3,] 34.35254 35.02044 41.79204 32.52825
[4,] 29.34814 37.10902 28.43232 33.50550
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x7fee10b21790>
> exp(tmp5)
<pointer: 0x7fee10b21790>
> log(tmp5,2)
<pointer: 0x7fee10b21790>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.8926
> Min(tmp5)
[1] 53.33362
> mean(tmp5)
[1] 72.98872
> Sum(tmp5)
[1] 14597.74
> Var(tmp5)
[1] 858.8607
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.76479 72.07028 68.36356 70.30411 72.93697 70.36780 70.57415 69.31334
[9] 70.78742 73.40483
> rowSums(tmp5)
[1] 1835.296 1441.406 1367.271 1406.082 1458.739 1407.356 1411.483 1386.267
[9] 1415.748 1468.097
> rowVars(tmp5)
[1] 7844.80912 73.91243 90.38614 47.26330 57.93177 58.00896
[7] 85.57708 127.62536 69.27712 105.68348
> rowSd(tmp5)
[1] 88.570927 8.597234 9.507162 6.874831 7.611293 7.616361 9.250788
[8] 11.297139 8.323288 10.280247
> rowMax(tmp5)
[1] 466.89263 86.18911 86.98466 80.60651 84.23498 82.60388 87.20390
[8] 99.28508 84.25129 93.59974
> rowMin(tmp5)
[1] 60.83028 58.81993 53.33362 59.17815 57.91282 53.85977 56.65068 55.25621
[9] 56.71099 59.41010
>
> colMeans(tmp5)
[1] 106.65966 70.37301 73.38126 71.80939 69.18285 69.34583 69.35767
[8] 72.71877 67.45077 69.05615 73.32779 75.75351 69.19725 73.47386
[15] 65.16500 69.25889 71.81766 77.12166 73.57879 71.74475
> colSums(tmp5)
[1] 1066.5966 703.7301 733.8126 718.0939 691.8285 693.4583 693.5767
[8] 727.1877 674.5077 690.5615 733.2779 757.5351 691.9725 734.7386
[15] 651.6500 692.5889 718.1766 771.2166 735.7879 717.4475
> colVars(tmp5)
[1] 16047.28737 84.57727 113.99808 59.74168 61.60804 49.02796
[7] 76.79489 78.70528 76.04674 54.15744 88.86333 37.19813
[13] 54.02772 72.74943 33.84290 104.88531 68.71138 125.22632
[19] 116.45488 89.67571
> colSd(tmp5)
[1] 126.677888 9.196590 10.676989 7.729274 7.849079 7.001997
[7] 8.763269 8.871600 8.720478 7.359174 9.426735 6.099027
[13] 7.350355 8.529328 5.817465 10.241353 8.289233 11.190457
[19] 10.791426 9.469726
> colMax(tmp5)
[1] 466.89263 86.19313 86.98466 83.85041 81.69279 78.45082 80.90506
[8] 85.10278 80.67383 77.51546 93.59974 83.15671 79.41399 87.20390
[15] 73.36752 87.26345 83.68776 99.28508 87.09852 84.25129
> colMin(tmp5)
[1] 58.81993 55.25621 59.17815 58.01569 59.36300 56.36203 57.91282 55.25699
[9] 53.33362 55.88554 58.87426 63.54825 56.78020 60.97557 56.65068 56.59448
[17] 60.83401 59.41010 53.85977 61.38577
>
>
> ### 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] 91.76479 72.07028 68.36356 70.30411 72.93697 70.36780 70.57415 69.31334
[9] 70.78742 NA
> rowSums(tmp5)
[1] 1835.296 1441.406 1367.271 1406.082 1458.739 1407.356 1411.483 1386.267
[9] 1415.748 NA
> rowVars(tmp5)
[1] 7844.80912 73.91243 90.38614 47.26330 57.93177 58.00896
[7] 85.57708 127.62536 69.27712 104.72493
> rowSd(tmp5)
[1] 88.570927 8.597234 9.507162 6.874831 7.611293 7.616361 9.250788
[8] 11.297139 8.323288 10.233520
> rowMax(tmp5)
[1] 466.89263 86.18911 86.98466 80.60651 84.23498 82.60388 87.20390
[8] 99.28508 84.25129 NA
> rowMin(tmp5)
[1] 60.83028 58.81993 53.33362 59.17815 57.91282 53.85977 56.65068 55.25621
[9] 56.71099 NA
>
> colMeans(tmp5)
[1] 106.65966 70.37301 73.38126 71.80939 69.18285 69.34583 69.35767
[8] 72.71877 67.45077 69.05615 73.32779 75.75351 69.19725 73.47386
[15] 65.16500 69.25889 71.81766 77.12166 73.57879 NA
> colSums(tmp5)
[1] 1066.5966 703.7301 733.8126 718.0939 691.8285 693.4583 693.5767
[8] 727.1877 674.5077 690.5615 733.2779 757.5351 691.9725 734.7386
[15] 651.6500 692.5889 718.1766 771.2166 735.7879 NA
> colVars(tmp5)
[1] 16047.28737 84.57727 113.99808 59.74168 61.60804 49.02796
[7] 76.79489 78.70528 76.04674 54.15744 88.86333 37.19813
[13] 54.02772 72.74943 33.84290 104.88531 68.71138 125.22632
[19] 116.45488 NA
> colSd(tmp5)
[1] 126.677888 9.196590 10.676989 7.729274 7.849079 7.001997
[7] 8.763269 8.871600 8.720478 7.359174 9.426735 6.099027
[13] 7.350355 8.529328 5.817465 10.241353 8.289233 11.190457
[19] 10.791426 NA
> colMax(tmp5)
[1] 466.89263 86.19313 86.98466 83.85041 81.69279 78.45082 80.90506
[8] 85.10278 80.67383 77.51546 93.59974 83.15671 79.41399 87.20390
[15] 73.36752 87.26345 83.68776 99.28508 87.09852 NA
> colMin(tmp5)
[1] 58.81993 55.25621 59.17815 58.01569 59.36300 56.36203 57.91282 55.25699
[9] 53.33362 55.88554 58.87426 63.54825 56.78020 60.97557 56.65068 56.59448
[17] 60.83401 59.41010 53.85977 NA
>
> Max(tmp5,na.rm=TRUE)
[1] 466.8926
> Min(tmp5,na.rm=TRUE)
[1] 53.33362
> mean(tmp5,na.rm=TRUE)
[1] 73.04094
> Sum(tmp5,na.rm=TRUE)
[1] 14535.15
> Var(tmp5,na.rm=TRUE)
[1] 862.6503
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.76479 72.07028 68.36356 70.30411 72.93697 70.36780 70.57415 69.31334
[9] 70.78742 73.97362
> rowSums(tmp5,na.rm=TRUE)
[1] 1835.296 1441.406 1367.271 1406.082 1458.739 1407.356 1411.483 1386.267
[9] 1415.748 1405.499
> rowVars(tmp5,na.rm=TRUE)
[1] 7844.80912 73.91243 90.38614 47.26330 57.93177 58.00896
[7] 85.57708 127.62536 69.27712 104.72493
> rowSd(tmp5,na.rm=TRUE)
[1] 88.570927 8.597234 9.507162 6.874831 7.611293 7.616361 9.250788
[8] 11.297139 8.323288 10.233520
> rowMax(tmp5,na.rm=TRUE)
[1] 466.89263 86.18911 86.98466 80.60651 84.23498 82.60388 87.20390
[8] 99.28508 84.25129 93.59974
> rowMin(tmp5,na.rm=TRUE)
[1] 60.83028 58.81993 53.33362 59.17815 57.91282 53.85977 56.65068 55.25621
[9] 56.71099 59.41010
>
> colMeans(tmp5,na.rm=TRUE)
[1] 106.65966 70.37301 73.38126 71.80939 69.18285 69.34583 69.35767
[8] 72.71877 67.45077 69.05615 73.32779 75.75351 69.19725 73.47386
[15] 65.16500 69.25889 71.81766 77.12166 73.57879 72.76107
> colSums(tmp5,na.rm=TRUE)
[1] 1066.5966 703.7301 733.8126 718.0939 691.8285 693.4583 693.5767
[8] 727.1877 674.5077 690.5615 733.2779 757.5351 691.9725 734.7386
[15] 651.6500 692.5889 718.1766 771.2166 735.7879 654.8496
> colVars(tmp5,na.rm=TRUE)
[1] 16047.28737 84.57727 113.99808 59.74168 61.60804 49.02796
[7] 76.79489 78.70528 76.04674 54.15744 88.86333 37.19813
[13] 54.02772 72.74943 33.84290 104.88531 68.71138 125.22632
[19] 116.45488 89.26497
> colSd(tmp5,na.rm=TRUE)
[1] 126.677888 9.196590 10.676989 7.729274 7.849079 7.001997
[7] 8.763269 8.871600 8.720478 7.359174 9.426735 6.099027
[13] 7.350355 8.529328 5.817465 10.241353 8.289233 11.190457
[19] 10.791426 9.448014
> colMax(tmp5,na.rm=TRUE)
[1] 466.89263 86.19313 86.98466 83.85041 81.69279 78.45082 80.90506
[8] 85.10278 80.67383 77.51546 93.59974 83.15671 79.41399 87.20390
[15] 73.36752 87.26345 83.68776 99.28508 87.09852 84.25129
> colMin(tmp5,na.rm=TRUE)
[1] 58.81993 55.25621 59.17815 58.01569 59.36300 56.36203 57.91282 55.25699
[9] 53.33362 55.88554 58.87426 63.54825 56.78020 60.97557 56.65068 56.59448
[17] 60.83401 59.41010 53.85977 61.38577
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.76479 72.07028 68.36356 70.30411 72.93697 70.36780 70.57415 69.31334
[9] 70.78742 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1835.296 1441.406 1367.271 1406.082 1458.739 1407.356 1411.483 1386.267
[9] 1415.748 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 7844.80912 73.91243 90.38614 47.26330 57.93177 58.00896
[7] 85.57708 127.62536 69.27712 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 88.570927 8.597234 9.507162 6.874831 7.611293 7.616361 9.250788
[8] 11.297139 8.323288 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 466.89263 86.18911 86.98466 80.60651 84.23498 82.60388 87.20390
[8] 99.28508 84.25129 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 60.83028 58.81993 53.33362 59.17815 57.91282 53.85977 56.65068 55.25621
[9] 56.71099 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 111.07188 68.61522 73.79769 70.47150 68.83177 70.32773 68.44982
[8] 73.53500 66.55940 69.67005 71.07535 76.36184 69.45070 73.82781
[15] 65.11965 67.25839 70.49876 79.08961 72.07660 NaN
> colSums(tmp5,na.rm=TRUE)
[1] 999.6470 617.5370 664.1792 634.2435 619.4859 632.9495 616.0484 661.8150
[9] 599.0346 627.0304 639.6781 687.2566 625.0563 664.4503 586.0769 605.3255
[17] 634.4888 711.8065 648.6894 0.0000
> colVars(tmp5,na.rm=TRUE)
[1] 17834.18656 60.38885 126.29696 47.07242 67.92243 44.31006
[7] 77.12228 81.04831 76.61408 56.68730 42.89458 37.68472
[13] 60.05852 80.43369 38.05012 72.97319 57.73094 97.31029
[19] 105.62520 NA
> colSd(tmp5,na.rm=TRUE)
[1] 133.544699 7.771026 11.238192 6.860935 8.241506 6.656580
[7] 8.781929 9.002683 8.752947 7.529097 6.549395 6.138788
[13] 7.749743 8.968483 6.168478 8.542434 7.598088 9.864598
[19] 10.277412 NA
> colMax(tmp5,na.rm=TRUE)
[1] 466.89263 79.50564 86.98466 76.28955 81.69279 78.45082 80.90506
[8] 85.10278 80.67383 77.51546 78.09743 83.15671 79.41399 87.20390
[15] 73.36752 81.42702 83.11113 99.28508 84.99841 -Inf
> colMin(tmp5,na.rm=TRUE)
[1] 58.81993 55.25621 59.17815 58.01569 59.36300 56.36203 57.91282 55.25699
[9] 53.33362 55.88554 58.87426 63.54825 56.78020 60.97557 56.65068 56.59448
[17] 60.83401 65.08252 53.85977 Inf
>
>
>
>
> 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] 180.4919 258.3827 253.1794 301.7204 193.5614 213.1570 169.5038 267.6973
[9] 225.3764 195.2554
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 180.4919 258.3827 253.1794 301.7204 193.5614 213.1570 169.5038 267.6973
[9] 225.3764 195.2554
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 1.421085e-13 -1.421085e-13 -2.842171e-14 -5.684342e-14 1.136868e-13
[6] -2.273737e-13 5.684342e-14 0.000000e+00 -5.684342e-14 -2.842171e-14
[11] 2.842171e-13 -5.684342e-14 -2.842171e-14 2.842171e-13 0.000000e+00
[16] 5.684342e-14 -1.136868e-13 -1.136868e-13 -2.842171e-14 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
10 9
7 11
7 1
9 4
4 17
3 11
2 12
1 17
2 1
4 2
9 20
6 19
1 13
3 5
3 14
4 6
7 17
1 4
5 8
10 18
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] 2.754224
> Min(tmp)
[1] -3.357582
> mean(tmp)
[1] -0.03489907
> Sum(tmp)
[1] -3.489907
> Var(tmp)
[1] 1.021759
>
> rowMeans(tmp)
[1] -0.03489907
> rowSums(tmp)
[1] -3.489907
> rowVars(tmp)
[1] 1.021759
> rowSd(tmp)
[1] 1.010821
> rowMax(tmp)
[1] 2.754224
> rowMin(tmp)
[1] -3.357582
>
> colMeans(tmp)
[1] -1.13573544 0.17081048 -0.89596461 -0.35975825 0.95578283 0.22167329
[7] -1.10217303 1.45104762 -0.57757160 0.76461479 -0.74496110 -1.28627932
[13] 0.73951991 -0.31268898 -0.26733306 -1.02805615 -0.79712453 0.63503481
[19] -0.37379926 -1.00888358 -0.26905649 -0.78665805 -0.08460737 -0.54260181
[25] 0.15324752 -1.39463997 -0.77727183 0.43561377 1.31236680 -0.77233473
[31] 0.99898775 1.72372547 0.61034204 -2.41876864 -1.15043692 -0.03418723
[37] -0.21539015 -0.16493187 -0.73157408 0.91048952 0.50978071 2.06849512
[43] -0.01944232 -0.97996206 2.49128095 -0.04195505 -1.22864602 0.19531610
[49] -0.40027722 -0.29582330 -1.21050802 -0.13935320 0.55160411 0.91157100
[55] 0.34888419 0.38739220 0.66331324 -1.25338850 -0.22359671 0.47102445
[61] 1.46699331 1.32128076 0.32557221 -0.01185674 0.72641511 -0.43068280
[67] 0.03155065 1.24891216 0.54761157 -0.34724175 -0.82806131 0.07083034
[73] 0.07429687 1.18351297 0.86572379 -0.79443356 -1.73309956 0.77942556
[79] -0.20308934 1.02839823 -0.10448423 0.26872657 -1.00091317 0.06656402
[85] -0.06381272 -3.35758217 0.08980416 -1.47682062 -1.06863540 -1.98964176
[91] 1.08929685 -1.13487065 1.52384061 0.20844296 0.18027254 -0.45054388
[97] -0.58197732 0.03237768 2.75422375 1.54758902
> colSums(tmp)
[1] -1.13573544 0.17081048 -0.89596461 -0.35975825 0.95578283 0.22167329
[7] -1.10217303 1.45104762 -0.57757160 0.76461479 -0.74496110 -1.28627932
[13] 0.73951991 -0.31268898 -0.26733306 -1.02805615 -0.79712453 0.63503481
[19] -0.37379926 -1.00888358 -0.26905649 -0.78665805 -0.08460737 -0.54260181
[25] 0.15324752 -1.39463997 -0.77727183 0.43561377 1.31236680 -0.77233473
[31] 0.99898775 1.72372547 0.61034204 -2.41876864 -1.15043692 -0.03418723
[37] -0.21539015 -0.16493187 -0.73157408 0.91048952 0.50978071 2.06849512
[43] -0.01944232 -0.97996206 2.49128095 -0.04195505 -1.22864602 0.19531610
[49] -0.40027722 -0.29582330 -1.21050802 -0.13935320 0.55160411 0.91157100
[55] 0.34888419 0.38739220 0.66331324 -1.25338850 -0.22359671 0.47102445
[61] 1.46699331 1.32128076 0.32557221 -0.01185674 0.72641511 -0.43068280
[67] 0.03155065 1.24891216 0.54761157 -0.34724175 -0.82806131 0.07083034
[73] 0.07429687 1.18351297 0.86572379 -0.79443356 -1.73309956 0.77942556
[79] -0.20308934 1.02839823 -0.10448423 0.26872657 -1.00091317 0.06656402
[85] -0.06381272 -3.35758217 0.08980416 -1.47682062 -1.06863540 -1.98964176
[91] 1.08929685 -1.13487065 1.52384061 0.20844296 0.18027254 -0.45054388
[97] -0.58197732 0.03237768 2.75422375 1.54758902
> 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] -1.13573544 0.17081048 -0.89596461 -0.35975825 0.95578283 0.22167329
[7] -1.10217303 1.45104762 -0.57757160 0.76461479 -0.74496110 -1.28627932
[13] 0.73951991 -0.31268898 -0.26733306 -1.02805615 -0.79712453 0.63503481
[19] -0.37379926 -1.00888358 -0.26905649 -0.78665805 -0.08460737 -0.54260181
[25] 0.15324752 -1.39463997 -0.77727183 0.43561377 1.31236680 -0.77233473
[31] 0.99898775 1.72372547 0.61034204 -2.41876864 -1.15043692 -0.03418723
[37] -0.21539015 -0.16493187 -0.73157408 0.91048952 0.50978071 2.06849512
[43] -0.01944232 -0.97996206 2.49128095 -0.04195505 -1.22864602 0.19531610
[49] -0.40027722 -0.29582330 -1.21050802 -0.13935320 0.55160411 0.91157100
[55] 0.34888419 0.38739220 0.66331324 -1.25338850 -0.22359671 0.47102445
[61] 1.46699331 1.32128076 0.32557221 -0.01185674 0.72641511 -0.43068280
[67] 0.03155065 1.24891216 0.54761157 -0.34724175 -0.82806131 0.07083034
[73] 0.07429687 1.18351297 0.86572379 -0.79443356 -1.73309956 0.77942556
[79] -0.20308934 1.02839823 -0.10448423 0.26872657 -1.00091317 0.06656402
[85] -0.06381272 -3.35758217 0.08980416 -1.47682062 -1.06863540 -1.98964176
[91] 1.08929685 -1.13487065 1.52384061 0.20844296 0.18027254 -0.45054388
[97] -0.58197732 0.03237768 2.75422375 1.54758902
> colMin(tmp)
[1] -1.13573544 0.17081048 -0.89596461 -0.35975825 0.95578283 0.22167329
[7] -1.10217303 1.45104762 -0.57757160 0.76461479 -0.74496110 -1.28627932
[13] 0.73951991 -0.31268898 -0.26733306 -1.02805615 -0.79712453 0.63503481
[19] -0.37379926 -1.00888358 -0.26905649 -0.78665805 -0.08460737 -0.54260181
[25] 0.15324752 -1.39463997 -0.77727183 0.43561377 1.31236680 -0.77233473
[31] 0.99898775 1.72372547 0.61034204 -2.41876864 -1.15043692 -0.03418723
[37] -0.21539015 -0.16493187 -0.73157408 0.91048952 0.50978071 2.06849512
[43] -0.01944232 -0.97996206 2.49128095 -0.04195505 -1.22864602 0.19531610
[49] -0.40027722 -0.29582330 -1.21050802 -0.13935320 0.55160411 0.91157100
[55] 0.34888419 0.38739220 0.66331324 -1.25338850 -0.22359671 0.47102445
[61] 1.46699331 1.32128076 0.32557221 -0.01185674 0.72641511 -0.43068280
[67] 0.03155065 1.24891216 0.54761157 -0.34724175 -0.82806131 0.07083034
[73] 0.07429687 1.18351297 0.86572379 -0.79443356 -1.73309956 0.77942556
[79] -0.20308934 1.02839823 -0.10448423 0.26872657 -1.00091317 0.06656402
[85] -0.06381272 -3.35758217 0.08980416 -1.47682062 -1.06863540 -1.98964176
[91] 1.08929685 -1.13487065 1.52384061 0.20844296 0.18027254 -0.45054388
[97] -0.58197732 0.03237768 2.75422375 1.54758902
> colMedians(tmp)
[1] -1.13573544 0.17081048 -0.89596461 -0.35975825 0.95578283 0.22167329
[7] -1.10217303 1.45104762 -0.57757160 0.76461479 -0.74496110 -1.28627932
[13] 0.73951991 -0.31268898 -0.26733306 -1.02805615 -0.79712453 0.63503481
[19] -0.37379926 -1.00888358 -0.26905649 -0.78665805 -0.08460737 -0.54260181
[25] 0.15324752 -1.39463997 -0.77727183 0.43561377 1.31236680 -0.77233473
[31] 0.99898775 1.72372547 0.61034204 -2.41876864 -1.15043692 -0.03418723
[37] -0.21539015 -0.16493187 -0.73157408 0.91048952 0.50978071 2.06849512
[43] -0.01944232 -0.97996206 2.49128095 -0.04195505 -1.22864602 0.19531610
[49] -0.40027722 -0.29582330 -1.21050802 -0.13935320 0.55160411 0.91157100
[55] 0.34888419 0.38739220 0.66331324 -1.25338850 -0.22359671 0.47102445
[61] 1.46699331 1.32128076 0.32557221 -0.01185674 0.72641511 -0.43068280
[67] 0.03155065 1.24891216 0.54761157 -0.34724175 -0.82806131 0.07083034
[73] 0.07429687 1.18351297 0.86572379 -0.79443356 -1.73309956 0.77942556
[79] -0.20308934 1.02839823 -0.10448423 0.26872657 -1.00091317 0.06656402
[85] -0.06381272 -3.35758217 0.08980416 -1.47682062 -1.06863540 -1.98964176
[91] 1.08929685 -1.13487065 1.52384061 0.20844296 0.18027254 -0.45054388
[97] -0.58197732 0.03237768 2.75422375 1.54758902
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.135735 0.1708105 -0.8959646 -0.3597583 0.9557828 0.2216733 -1.102173
[2,] -1.135735 0.1708105 -0.8959646 -0.3597583 0.9557828 0.2216733 -1.102173
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.451048 -0.5775716 0.7646148 -0.7449611 -1.286279 0.7395199 -0.312689
[2,] 1.451048 -0.5775716 0.7646148 -0.7449611 -1.286279 0.7395199 -0.312689
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.2673331 -1.028056 -0.7971245 0.6350348 -0.3737993 -1.008884 -0.2690565
[2,] -0.2673331 -1.028056 -0.7971245 0.6350348 -0.3737993 -1.008884 -0.2690565
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.7866581 -0.08460737 -0.5426018 0.1532475 -1.39464 -0.7772718 0.4356138
[2,] -0.7866581 -0.08460737 -0.5426018 0.1532475 -1.39464 -0.7772718 0.4356138
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.312367 -0.7723347 0.9989878 1.723725 0.610342 -2.418769 -1.150437
[2,] 1.312367 -0.7723347 0.9989878 1.723725 0.610342 -2.418769 -1.150437
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.03418723 -0.2153901 -0.1649319 -0.7315741 0.9104895 0.5097807 2.068495
[2,] -0.03418723 -0.2153901 -0.1649319 -0.7315741 0.9104895 0.5097807 2.068495
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.01944232 -0.9799621 2.491281 -0.04195505 -1.228646 0.1953161 -0.4002772
[2,] -0.01944232 -0.9799621 2.491281 -0.04195505 -1.228646 0.1953161 -0.4002772
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.2958233 -1.210508 -0.1393532 0.5516041 0.911571 0.3488842 0.3873922
[2,] -0.2958233 -1.210508 -0.1393532 0.5516041 0.911571 0.3488842 0.3873922
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.6633132 -1.253388 -0.2235967 0.4710244 1.466993 1.321281 0.3255722
[2,] 0.6633132 -1.253388 -0.2235967 0.4710244 1.466993 1.321281 0.3255722
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.01185674 0.7264151 -0.4306828 0.03155065 1.248912 0.5476116 -0.3472417
[2,] -0.01185674 0.7264151 -0.4306828 0.03155065 1.248912 0.5476116 -0.3472417
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.8280613 0.07083034 0.07429687 1.183513 0.8657238 -0.7944336 -1.7331
[2,] -0.8280613 0.07083034 0.07429687 1.183513 0.8657238 -0.7944336 -1.7331
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.7794256 -0.2030893 1.028398 -0.1044842 0.2687266 -1.000913 0.06656402
[2,] 0.7794256 -0.2030893 1.028398 -0.1044842 0.2687266 -1.000913 0.06656402
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.06381272 -3.357582 0.08980416 -1.476821 -1.068635 -1.989642 1.089297
[2,] -0.06381272 -3.357582 0.08980416 -1.476821 -1.068635 -1.989642 1.089297
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.134871 1.523841 0.208443 0.1802725 -0.4505439 -0.5819773 0.03237768
[2,] -1.134871 1.523841 0.208443 0.1802725 -0.4505439 -0.5819773 0.03237768
[,99] [,100]
[1,] 2.754224 1.547589
[2,] 2.754224 1.547589
>
>
> Max(tmp2)
[1] 2.681737
> Min(tmp2)
[1] -2.090442
> mean(tmp2)
[1] -0.14211
> Sum(tmp2)
[1] -14.211
> Var(tmp2)
[1] 1.051647
>
> rowMeans(tmp2)
[1] -0.436207444 2.681737404 1.480251732 -0.279429662 -0.608753483
[6] -0.028479444 -0.372736208 0.648639709 -2.053584387 0.152918563
[11] 0.859630382 1.101139388 -1.381681415 -1.516087474 -0.734526139
[16] -0.995147780 -0.717557979 -1.662152160 1.561961564 1.226516927
[21] -0.982889581 0.955336051 0.262269871 -0.353191512 -2.083800660
[26] 0.300279320 -1.600515534 0.627068190 -0.174230591 -0.422526802
[31] 0.672018960 0.062829239 -1.162151390 0.823770848 -1.958029408
[36] 0.939022007 1.290243771 0.867429873 -0.879481045 0.050143864
[41] 0.633893984 0.001198771 0.620158027 0.257563601 -0.194567953
[46] -0.227131504 -0.258073833 0.211442175 -0.913177268 -0.557938703
[51] -1.937854713 0.950128450 0.666435012 0.438674616 -1.970970011
[56] 0.592146133 1.602155792 0.592363692 0.487781362 -0.983202424
[61] -0.103375943 -1.828384246 -0.557529225 -0.818670928 -0.311719055
[66] 0.057865708 0.053833704 0.956645601 0.277422876 -1.640802508
[71] -0.595504149 0.124784941 0.166690542 -0.032277553 0.555363479
[76] -1.017360358 -1.573588632 0.696120891 -0.851253906 1.278515816
[81] -1.575010898 1.474764229 0.067154466 0.238758080 -1.369466072
[86] 0.382900404 0.132496160 -2.090441826 -0.983367065 -0.610233365
[91] -0.509788118 1.362298814 1.132849623 -1.005399863 1.845462395
[96] -0.405617914 -1.077623971 -1.883108152 0.036805136 -0.382286235
> rowSums(tmp2)
[1] -0.436207444 2.681737404 1.480251732 -0.279429662 -0.608753483
[6] -0.028479444 -0.372736208 0.648639709 -2.053584387 0.152918563
[11] 0.859630382 1.101139388 -1.381681415 -1.516087474 -0.734526139
[16] -0.995147780 -0.717557979 -1.662152160 1.561961564 1.226516927
[21] -0.982889581 0.955336051 0.262269871 -0.353191512 -2.083800660
[26] 0.300279320 -1.600515534 0.627068190 -0.174230591 -0.422526802
[31] 0.672018960 0.062829239 -1.162151390 0.823770848 -1.958029408
[36] 0.939022007 1.290243771 0.867429873 -0.879481045 0.050143864
[41] 0.633893984 0.001198771 0.620158027 0.257563601 -0.194567953
[46] -0.227131504 -0.258073833 0.211442175 -0.913177268 -0.557938703
[51] -1.937854713 0.950128450 0.666435012 0.438674616 -1.970970011
[56] 0.592146133 1.602155792 0.592363692 0.487781362 -0.983202424
[61] -0.103375943 -1.828384246 -0.557529225 -0.818670928 -0.311719055
[66] 0.057865708 0.053833704 0.956645601 0.277422876 -1.640802508
[71] -0.595504149 0.124784941 0.166690542 -0.032277553 0.555363479
[76] -1.017360358 -1.573588632 0.696120891 -0.851253906 1.278515816
[81] -1.575010898 1.474764229 0.067154466 0.238758080 -1.369466072
[86] 0.382900404 0.132496160 -2.090441826 -0.983367065 -0.610233365
[91] -0.509788118 1.362298814 1.132849623 -1.005399863 1.845462395
[96] -0.405617914 -1.077623971 -1.883108152 0.036805136 -0.382286235
> 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] -0.436207444 2.681737404 1.480251732 -0.279429662 -0.608753483
[6] -0.028479444 -0.372736208 0.648639709 -2.053584387 0.152918563
[11] 0.859630382 1.101139388 -1.381681415 -1.516087474 -0.734526139
[16] -0.995147780 -0.717557979 -1.662152160 1.561961564 1.226516927
[21] -0.982889581 0.955336051 0.262269871 -0.353191512 -2.083800660
[26] 0.300279320 -1.600515534 0.627068190 -0.174230591 -0.422526802
[31] 0.672018960 0.062829239 -1.162151390 0.823770848 -1.958029408
[36] 0.939022007 1.290243771 0.867429873 -0.879481045 0.050143864
[41] 0.633893984 0.001198771 0.620158027 0.257563601 -0.194567953
[46] -0.227131504 -0.258073833 0.211442175 -0.913177268 -0.557938703
[51] -1.937854713 0.950128450 0.666435012 0.438674616 -1.970970011
[56] 0.592146133 1.602155792 0.592363692 0.487781362 -0.983202424
[61] -0.103375943 -1.828384246 -0.557529225 -0.818670928 -0.311719055
[66] 0.057865708 0.053833704 0.956645601 0.277422876 -1.640802508
[71] -0.595504149 0.124784941 0.166690542 -0.032277553 0.555363479
[76] -1.017360358 -1.573588632 0.696120891 -0.851253906 1.278515816
[81] -1.575010898 1.474764229 0.067154466 0.238758080 -1.369466072
[86] 0.382900404 0.132496160 -2.090441826 -0.983367065 -0.610233365
[91] -0.509788118 1.362298814 1.132849623 -1.005399863 1.845462395
[96] -0.405617914 -1.077623971 -1.883108152 0.036805136 -0.382286235
> rowMin(tmp2)
[1] -0.436207444 2.681737404 1.480251732 -0.279429662 -0.608753483
[6] -0.028479444 -0.372736208 0.648639709 -2.053584387 0.152918563
[11] 0.859630382 1.101139388 -1.381681415 -1.516087474 -0.734526139
[16] -0.995147780 -0.717557979 -1.662152160 1.561961564 1.226516927
[21] -0.982889581 0.955336051 0.262269871 -0.353191512 -2.083800660
[26] 0.300279320 -1.600515534 0.627068190 -0.174230591 -0.422526802
[31] 0.672018960 0.062829239 -1.162151390 0.823770848 -1.958029408
[36] 0.939022007 1.290243771 0.867429873 -0.879481045 0.050143864
[41] 0.633893984 0.001198771 0.620158027 0.257563601 -0.194567953
[46] -0.227131504 -0.258073833 0.211442175 -0.913177268 -0.557938703
[51] -1.937854713 0.950128450 0.666435012 0.438674616 -1.970970011
[56] 0.592146133 1.602155792 0.592363692 0.487781362 -0.983202424
[61] -0.103375943 -1.828384246 -0.557529225 -0.818670928 -0.311719055
[66] 0.057865708 0.053833704 0.956645601 0.277422876 -1.640802508
[71] -0.595504149 0.124784941 0.166690542 -0.032277553 0.555363479
[76] -1.017360358 -1.573588632 0.696120891 -0.851253906 1.278515816
[81] -1.575010898 1.474764229 0.067154466 0.238758080 -1.369466072
[86] 0.382900404 0.132496160 -2.090441826 -0.983367065 -0.610233365
[91] -0.509788118 1.362298814 1.132849623 -1.005399863 1.845462395
[96] -0.405617914 -1.077623971 -1.883108152 0.036805136 -0.382286235
>
> colMeans(tmp2)
[1] -0.14211
> colSums(tmp2)
[1] -14.211
> colVars(tmp2)
[1] 1.051647
> colSd(tmp2)
[1] 1.025498
> colMax(tmp2)
[1] 2.681737
> colMin(tmp2)
[1] -2.090442
> colMedians(tmp2)
[1] -0.0303785
> colRanges(tmp2)
[,1]
[1,] -2.090442
[2,] 2.681737
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.3388136 8.7324261 -0.7971716 2.2764847 4.6364646 1.3978307
[7] 10.2172950 2.8763700 -0.1091605 1.6961567
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.2645312
[2,] -0.4534326
[3,] 0.2074173
[4,] 0.6992524
[5,] 1.3295380
>
> rowApply(tmp,sum)
[1] 2.4995205 2.1263301 0.2879000 3.5759247 4.2807803 -4.1891557
[7] 9.1686047 9.3978883 0.7861408 4.3315754
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 4 1 5 2 6 5 6 5 3 7
[2,] 10 5 7 5 10 10 7 7 1 8
[3,] 1 3 4 8 3 2 9 2 7 4
[4,] 2 7 1 1 8 7 5 10 5 9
[5,] 7 9 6 3 4 3 8 6 4 6
[6,] 8 6 2 4 1 9 1 8 9 10
[7,] 3 10 10 9 9 6 10 3 10 5
[8,] 9 8 3 6 2 8 2 9 6 3
[9,] 6 2 8 7 7 1 3 4 8 2
[10,] 5 4 9 10 5 4 4 1 2 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.71424905 1.81588566 -0.07718397 0.37593274 -1.01800080 1.60937845
[7] -0.96350287 6.19246997 0.04322233 1.25798398 -2.17961001 -0.24699385
[13] 0.34379320 1.55280713 1.17751452 0.13360187 -1.18161869 0.87777541
[19] 3.53853330 4.55812976
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5361289
[2,] -0.9683192
[3,] -0.3501732
[4,] -0.2337344
[5,] 0.3741065
>
> rowApply(tmp,sum)
[1] 6.287033 -4.557662 5.701577 5.756607 1.908315
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 3 16 5 4 1
[2,] 8 20 7 9 4
[3,] 4 8 1 15 20
[4,] 13 2 10 19 13
[5,] 5 9 11 11 11
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.9683192 0.05037483 -0.7878940 0.60074474 -0.66338836 1.116875098
[2,] 0.3741065 2.31387865 -0.9963710 -1.72655891 -0.91325121 1.454526448
[3,] -0.2337344 -0.14447561 -0.9679539 0.05434623 0.07719229 -0.005569981
[4,] -0.3501732 0.26826043 0.6911065 1.21221543 0.39196401 -1.124209763
[5,] -1.5361289 -0.67215264 1.9839284 0.23518525 0.08948247 0.167756648
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.1053142 0.2326084 1.00584552 0.22505302 0.8331492 -1.8788258
[2,] 0.2394338 1.1396065 -0.47592837 -1.84033055 -1.4609716 0.1750699
[3,] 1.5290536 1.2938813 -0.42628977 1.87125279 0.7558732 0.1259364
[4,] -1.7550097 3.0791661 -0.12586421 1.07385258 -0.8931625 0.3612860
[5,] -0.8716664 0.4472078 0.06545915 -0.07184385 -1.4144983 0.9695398
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.8990839 2.0045875 0.007803946 1.7895263 -1.4718316 0.16718830
[2,] -1.1227310 -0.3233430 -1.118238432 -1.5145095 -1.0450096 -0.01640626
[3,] -0.3828775 -0.1333759 0.700323140 -0.2152886 0.4014797 0.99575316
[4,] -0.2618576 0.6041505 -0.035858371 0.4587494 0.5756759 -0.03256651
[5,] 1.2121755 -0.5992118 1.623484240 -0.3848757 0.3580670 -0.23619328
[,19] [,20]
[1,] 0.5357970 2.6939682
[2,] 1.9335444 0.3658208
[3,] 0.6978069 -0.2917561
[4,] 0.8259839 0.7928985
[5,] -0.4545989 0.9971984
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.8-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-3.8-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 643 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 557 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.8-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 0.2905391 -0.9325353 -0.08490627 -0.746611 -0.85045 0.04060528 0.06394053
col8 col9 col10 col11 col12 col13 col14
row1 -1.813229 -0.1884056 0.1388779 1.113085 0.4490033 -0.8496906 0.4162083
col15 col16 col17 col18 col19 col20
row1 0.009345528 1.690581 -0.2138986 1.35455 -0.5313301 -0.2657279
> tmp[,"col10"]
col10
row1 0.13887786
row2 -0.07486792
row3 -0.88109523
row4 0.48173002
row5 -0.40089194
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.2905391 -0.9325353 -0.08490627 -0.7466110 -0.850450 0.04060528
row5 -0.8971833 0.5179676 0.47470943 -0.1882778 -2.135144 0.69970460
col7 col8 col9 col10 col11 col12
row1 0.06394053 -1.8132294 -0.1884056 0.1388779 1.1130852 0.4490033
row5 0.87786787 -0.5106481 0.4248070 -0.4008919 -0.2885663 -0.7074811
col13 col14 col15 col16 col17 col18
row1 -0.8496906 0.41620831 0.009345528 1.690581 -0.2138986 1.354550
row5 1.0761467 -0.06406282 -0.118103210 -0.648123 -0.1103405 -2.786475
col19 col20
row1 -0.5313301 -0.2657279
row5 -1.1735320 -1.8433311
> tmp[,c("col6","col20")]
col6 col20
row1 0.04060528 -0.2657279
row2 0.81868426 -0.2513437
row3 0.26922739 -1.4924995
row4 0.88157828 1.5988669
row5 0.69970460 -1.8433311
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.04060528 -0.2657279
row5 0.69970460 -1.8433311
>
>
>
>
> 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 50.30718 49.94869 50.43461 48.97541 48.91302 104.9864 50.83509 51.02143
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.6437 50.11467 49.25833 49.49338 49.44654 50.85696 48.52124 50.56787
col17 col18 col19 col20
row1 50.42166 48.91429 49.81684 104.9948
> tmp[,"col10"]
col10
row1 50.11467
row2 29.52282
row3 30.21451
row4 28.70871
row5 50.89919
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.30718 49.94869 50.43461 48.97541 48.91302 104.9864 50.83509 51.02143
row5 47.51584 48.53017 49.56965 50.49397 48.52047 105.9783 50.26225 50.26876
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.64370 50.11467 49.25833 49.49338 49.44654 50.85696 48.52124 50.56787
row5 51.42971 50.89919 48.76895 50.97733 50.10945 50.16995 51.61175 50.05162
col17 col18 col19 col20
row1 50.42166 48.91429 49.81684 104.9948
row5 50.70110 49.28128 50.89488 105.8236
> tmp[,c("col6","col20")]
col6 col20
row1 104.98642 104.99479
row2 73.70939 74.90228
row3 75.62675 74.54802
row4 73.58783 75.65014
row5 105.97834 105.82359
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.9864 104.9948
row5 105.9783 105.8236
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.9864 104.9948
row5 105.9783 105.8236
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.0701514
[2,] -0.6574963
[3,] 0.7012744
[4,] -0.8878584
[5,] 0.8297635
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.1167038 -1.2775666
[2,] -0.5689732 -0.1853999
[3,] -0.4215021 -0.3857993
[4,] -0.6148156 -0.6231725
[5,] -1.8218320 -0.9042520
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.4662015 0.6014586
[2,] -0.1599493 -0.4289814
[3,] 0.8942368 1.6272848
[4,] 0.1575409 -0.2743861
[5,] -1.2837767 0.7360147
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.4662015
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.4662015
[2,] -0.1599493
>
>
>
> 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 0.6098944 0.1157595 -0.7704562 -2.006088 2.163457 2.582757 -1.339126
row1 -0.7528881 0.3591003 0.3419658 1.378785 -1.111332 1.358603 1.164394
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -0.1936330 0.9204550 0.5909745 -1.47007987 0.4165462 -0.9292037 1.355748
row1 0.5221224 -0.4111198 -0.3330074 -0.06998837 0.5649999 -1.2006134 1.163559
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.2596327 -0.7498988 -1.8131255 -1.197491 -0.3189705 -0.6248689
row1 0.1915400 0.3036875 -0.8579107 -1.334231 -1.2919882 -0.6217537
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.179042 -0.9465975 -2.219232 0.8034382 -0.1560794 -0.8702692 -0.471342
[,8] [,9] [,10]
row2 0.3781815 -1.415648 0.6572602
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.5091152 1.43795 0.5359517 0.507844 0.1263291 -2.360088 -0.1943933
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.0009533452 0.2691409 -0.2344938 -0.3795952 1.332536 1.13373 -0.2987795
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.999441 -1.880204 0.6346099 0.1179567 0.7395513 -0.01517907
>
>
> 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: 0x7fee1090f0a0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BMaef53dc36497"
[2] "/Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BMaef56701152e"
[3] "/Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BMaef57815b3d6"
[4] "/Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BMaef558d1e431"
[5] "/Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BMaef53bdc7a85"
[6] "/Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BMaef57efd077"
[7] "/Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BMaef5115f38b3"
[8] "/Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BMaef528378ae"
[9] "/Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BMaef5567e8cc"
[10] "/Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BMaef568e4abd9"
[11] "/Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BMaef57cce695b"
[12] "/Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BMaef553671560"
[13] "/Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BMaef514ac7c67"
[14] "/Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BMaef5481b58cb"
[15] "/Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BMaef57b629c68"
>
>
> ### 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: 0x7fee10a1d220>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x7fee10a1d220>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x7fee10a1d220>
> rowMedians(tmp)
[1] -0.5009764428 -0.3540968173 -0.0866371953 0.1008297856 0.0070142945
[6] -0.3101516633 0.0422044583 0.1378408815 0.3181615929 0.1641885750
[11] 0.3795219767 0.3422677572 0.4797338459 0.4213034364 0.0927014909
[16] 0.4003370166 -0.5081494687 0.4167316038 -0.0527502950 0.2332505820
[21] 0.3138181228 -0.1777286964 0.1273990987 -0.2850495483 -0.2751253854
[26] 0.3620596430 0.3925023227 -0.0722779775 -0.5455956894 0.5864404687
[31] 0.5672820725 -0.3590009474 -0.2219899170 0.4203673600 0.3073265927
[36] 0.4975873491 0.3247699824 0.0478649300 0.0110185050 0.0447579518
[41] -0.8363714847 -0.1796406823 0.2923426614 -0.6537139587 -0.0805100686
[46] 0.5671278719 0.2666966710 0.2489543420 0.3697042347 0.5052759295
[51] -0.2021422483 -0.1835883529 0.0228998280 -0.3415146549 -0.0385469653
[56] -0.2745469434 0.3222676012 -0.2826173336 0.2502629655 0.1188107913
[61] -0.2881854651 -0.6076418282 -0.6284283839 -0.3302615060 -0.0598608982
[66] 0.0680726520 0.0225548472 0.3070162873 -0.3624365457 -0.4150200800
[71] 0.3626103027 -0.2094845469 0.3184103915 0.5386832233 0.0413011979
[76] -0.0090102637 0.4549674086 0.5291525575 -0.6368240891 0.0867634800
[81] 0.5166551252 0.5686413235 0.4853787646 0.1482289574 -0.1816918771
[86] 0.0542755386 0.2719823004 -0.2858520143 -0.0556921374 0.1340066867
[91] 0.0627473072 0.3392128945 -0.1485305602 0.1060231282 0.6528788202
[96] 0.2836145751 0.5009882745 0.0660205660 -0.1916933993 0.0160248691
[101] -0.3887938193 -0.1234692183 0.3450933255 -0.0238386988 0.0102421040
[106] 0.0401045270 0.3249758875 -0.0843170622 -0.7437601271 0.2639752839
[111] -0.1180804498 0.2070545442 0.3535277349 0.1147677025 -0.1201714483
[116] 0.1796356100 0.3383529705 -0.3638372267 -0.0523299429 0.3653678751
[121] -0.3206494972 0.0503420066 -0.2371556493 0.2008756951 -0.1982642749
[126] -0.6224278527 0.3711058176 0.3129582727 -0.0077658911 -0.0114572051
[131] -0.2778664197 0.3147223461 -0.3124368674 -0.2795112469 0.2492618887
[136] 0.3263341320 0.7243567672 -0.3276480945 -0.1592973419 0.2543767266
[141] -0.2688713601 0.1666068784 -0.1147377648 -0.1253852554 0.3365643300
[146] -0.4600738468 -0.6457004585 -0.3979937872 -0.2834410193 -0.0005793893
[151] -0.2249461909 -0.0458173531 -0.0846546460 0.3155910702 0.1569853368
[156] -0.6968553269 -0.5007648053 -0.6341182119 0.1321429076 0.0886687153
[161] -0.1706406515 -0.3673330959 0.0894670414 -0.0791426349 -0.5034388559
[166] -0.3686084219 0.0671696824 -0.3682222104 0.0340995340 -0.0169454860
[171] 0.2654106198 -0.0641404971 0.6972261563 0.6223818795 -0.0741055637
[176] -0.3360948997 0.4877076080 -0.4677981149 -0.3504810865 0.2200612813
[181] -0.0219427268 -0.2144786037 -0.4431174196 -0.1529090618 -0.6128791213
[186] -0.2971584761 0.0530405609 0.1316630654 -0.1416115976 -0.3389767435
[191] 0.6377446384 0.8957868419 -0.1711809396 -0.2218348234 -0.4259309719
[196] -0.5580581102 -0.1205711234 0.5283505227 0.0309435097 0.1571762527
[201] 0.1776655891 0.4118539354 0.3345966332 -0.0557633717 0.2569716366
[206] 0.2445497534 -0.3944774407 0.3554538442 0.8107439116 0.4476532836
[211] 0.0706267302 0.5960960218 -0.1608916451 0.4878140283 0.2952681202
[216] 0.6838393018 -0.7089271210 -0.3239575597 -0.0524603580 0.0504133336
[221] -0.5104453721 -0.7162707382 -0.1677797689 0.2871132819 -0.3269947402
[226] -0.0518336231 0.3566531998 0.3679909639 -0.0918226599 -0.5381124704
>
> proc.time()
user system elapsed
4.231 6.878 11.485
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 3.5.3 (2019-03-11) -- "Great Truth"
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: 0x7fe1d3331150>
> .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: 0x7fe1d3331150>
> .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: 0x7fe1d3331150>
> .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: 0x7fe1d3331150>
> 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: 0x7fe1ce61af80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fe1ce61af80>
> .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: 0x7fe1ce61af80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fe1ce61af80>
> .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: 0x7fe1ce61af80>
> 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: 0x7fe1d36078b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fe1d36078b0>
> .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: 0x7fe1d36078b0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x7fe1d36078b0>
> .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: 0x7fe1d36078b0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x7fe1d36078b0>
> .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: 0x7fe1d36078b0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x7fe1d36078b0>
> .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: 0x7fe1d36078b0>
> 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: 0x7fe1d3313570>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x7fe1d3313570>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fe1d3313570>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fe1d3313570>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFileb25130de0662" "BufferedMatrixFileb251407524fe"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFileb25130de0662" "BufferedMatrixFileb251407524fe"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fe1d320d970>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fe1d320d970>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x7fe1d320d970>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x7fe1d320d970>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x7fe1d320d970>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x7fe1d320d970>
> .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: 0x7fe1d7801520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fe1d7801520>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x7fe1d7801520>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x7fe1d7801520>
> 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: 0x7fe1d361e320>
> .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: 0x7fe1d361e320>
> rm(P)
>
> proc.time()
user system elapsed
0.444 0.107 0.523
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 3.5.3 (2019-03-11) -- "Great Truth"
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
0.364 0.067 0.406