Ben Bolstad
| Snapshot Date: 2018-10-15 16:45:08 -0400 (Mon, 15 Oct 2018) |
| URL: https://git.bioconductor.org/packages/BufferedMatrix |
| Branch: RELEASE_3_7 |
| Last Commit: 6087ec6 |
| Last Changed Date: 2018-04-30 10:35:06 -0400 (Mon, 30 Apr 2018) |
| Back to Multiple platform build/check report for BioC 3.7 |
|
This page was generated on 2018-10-17 08:21:55 -0400 (Wed, 17 Oct 2018).
| Package 172/1561 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||
| BufferedMatrix 1.44.0 Ben Bolstad
| malbec2 | Linux (Ubuntu 16.04.1 LTS) / x86_64 | OK | OK | [ OK ] | | ||||||
| tokay2 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||
| merida2 | OS X 10.11.6 El Capitan / x86_64 | OK | OK | OK | OK | |
| Package: BufferedMatrix |
| Version: 1.44.0 |
| Command: /home/biocbuild/bbs-3.7-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.7-bioc/R/library --no-vignettes --timings BufferedMatrix_1.44.0.tar.gz |
| StartedAt: 2018-10-15 22:54:46 -0400 (Mon, 15 Oct 2018) |
| EndedAt: 2018-10-15 22:55:07 -0400 (Mon, 15 Oct 2018) |
| EllapsedTime: 21.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.7-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.7-bioc/R/library --no-vignettes --timings BufferedMatrix_1.44.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck’ * using R version 3.5.1 Patched (2018-07-12 r74967) * using platform: x86_64-pc-linux-gnu (64-bit) * using session charset: UTF-8 * using option ‘--no-vignettes’ * checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK * this is package ‘BufferedMatrix’ version ‘1.44.0’ * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking whether package ‘BufferedMatrix’ can be installed ... OK * checking installed package size ... OK * checking package directory ... OK * checking ‘build’ directory ... OK * checking DESCRIPTION meta-information ... OK * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking R files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... OK * checking whether the package can be loaded with stated dependencies ... OK * checking whether the package can be unloaded cleanly ... OK * checking whether the namespace can be loaded with stated dependencies ... OK * checking whether the namespace can be unloaded cleanly ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... OK * checking Rd files ... NOTE prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples * checking Rd metadata ... OK * checking Rd cross-references ... OK * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking line endings in C/C++/Fortran sources/headers ... OK * checking compiled code ... NOTE Note: information on .o files is not available * checking 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 ‘/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/00check.log’ for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.7-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.7-bioc/R/library’
* installing *source* package ‘BufferedMatrix’ ...
** libs
gcc -I"/home/biocbuild/bbs-3.7-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.7-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘˜’ [-Wparentheses]
if (!(Matrix->readonly) & setting){
^
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
gcc -I"/home/biocbuild/bbs-3.7-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"/home/biocbuild/bbs-3.7-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c init_package.c -o init_package.o
gcc -shared -L/home/biocbuild/bbs-3.7-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.7-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.7-bioc/R/library/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 3.5.1 Patched (2018-07-12 r74967) -- "Feather Spray"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (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
0.224 0.044 0.263
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 3.5.1 Patched (2018-07-12 r74967) -- "Feather Spray"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (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] "/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 406484 21.8 844295 45.1 634174 33.9
Vcells 743969 5.7 8388608 64.0 1812828 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] "Mon Oct 15 22:55:02 2018"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Mon Oct 15 22:55:02 2018"
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
>
>
> RowMode(tmp2)
<pointer: 0x3394190>
>
>
>
> 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 Oct 15 22:55:03 2018"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Mon Oct 15 22:55:03 2018"
>
> ColMode(tmp2)
<pointer: 0x3394190>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 98.2797393 -1.3739251 0.2139432 -0.39417747
[2,] -0.3108225 0.6071871 1.0307623 1.70983227
[3,] -2.1512637 0.4350449 0.3652376 -2.85462518
[4,] 0.1209955 -0.2441085 -0.2833995 0.07056359
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 98.2797393 1.3739251 0.2139432 0.39417747
[2,] 0.3108225 0.6071871 1.0307623 1.70983227
[3,] 2.1512637 0.4350449 0.3652376 2.85462518
[4,] 0.1209955 0.2441085 0.2833995 0.07056359
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9136138 1.1721455 0.4625399 0.6278355
[2,] 0.5575146 0.7792221 1.0152646 1.3076055
[3,] 1.4667187 0.6595794 0.6043489 1.6895636
[4,] 0.3478441 0.4940734 0.5323528 0.2656381
>
> 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: /home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 222.41588 38.09538 29.83934 31.67253
[2,] 30.88597 33.39941 36.18341 39.78589
[3,] 41.81845 32.03084 31.40873 44.75026
[4,] 28.59944 30.18484 30.60693 27.72694
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x2eb8a80>
> exp(tmp5)
<pointer: 0x2eb8a80>
> log(tmp5,2)
<pointer: 0x2eb8a80>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 462.9295
> Min(tmp5)
[1] 52.94641
> mean(tmp5)
[1] 73.9478
> Sum(tmp5)
[1] 14789.56
> Var(tmp5)
[1] 846.7066
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.93608 70.10306 73.31914 68.29358 73.30417 73.99432 71.82750 71.81699
[9] 70.83563 74.04747
> rowSums(tmp5)
[1] 1838.722 1402.061 1466.383 1365.872 1466.083 1479.886 1436.550 1436.340
[9] 1416.713 1480.949
> rowVars(tmp5)
[1] 7689.49017 70.75865 115.30417 58.89659 63.41654 138.07568
[7] 129.73050 42.80642 48.03298 101.23271
> rowSd(tmp5)
[1] 87.689738 8.411816 10.737978 7.674411 7.963451 11.750561 11.389930
[8] 6.542662 6.930583 10.061447
> rowMax(tmp5)
[1] 462.92951 82.80911 93.14181 85.14333 90.29510 92.66693 92.75610
[8] 82.79271 84.20323 90.64727
> rowMin(tmp5)
[1] 59.52083 56.19008 57.35403 57.71000 61.06579 55.91303 52.94641 60.19946
[9] 56.01120 54.79724
>
> colMeans(tmp5)
[1] 107.27288 74.10171 72.42177 72.93114 74.03275 72.06553 73.13928
[8] 78.61797 66.34849 72.08887 71.92701 71.13552 69.00636 70.18697
[15] 71.61596 72.80767 75.18247 68.18958 73.26140 72.62258
> colSums(tmp5)
[1] 1072.7288 741.0171 724.2177 729.3114 740.3275 720.6553 731.3928
[8] 786.1797 663.4849 720.8887 719.2701 711.3552 690.0636 701.8697
[15] 716.1596 728.0767 751.8247 681.8958 732.6140 726.2258
> colVars(tmp5)
[1] 15686.99181 101.29733 69.51307 160.61699 161.11240 129.89242
[7] 56.33497 22.18348 54.23978 97.26639 81.06825 93.11661
[13] 89.82942 49.75887 82.92353 123.61135 86.07615 40.64829
[19] 51.65321 44.19295
> colSd(tmp5)
[1] 125.247722 10.064658 8.337450 12.673476 12.693006 11.397036
[7] 7.505663 4.709934 7.364766 9.862372 9.003791 9.649695
[13] 9.477838 7.053997 9.106236 11.118064 9.277723 6.375601
[19] 7.187016 6.647778
> colMax(tmp5)
[1] 462.92951 88.79965 86.44158 93.14181 90.64727 92.75610 82.79271
[8] 85.14333 78.92923 84.70590 80.81674 88.91689 81.40566 81.65445
[15] 84.20323 88.77634 90.29510 79.48324 86.37049 83.01425
> colMin(tmp5)
[1] 59.05675 61.89171 62.10668 57.71000 52.94641 55.91303 60.79973 70.18008
[9] 53.37196 57.35403 56.01120 61.98428 55.61238 60.73846 58.77627 54.79724
[17] 56.19008 60.77895 63.65973 63.80672
>
>
> ### 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] 91.93608 70.10306 73.31914 68.29358 73.30417 73.99432 71.82750 71.81699
[9] 70.83563 NA
> rowSums(tmp5)
[1] 1838.722 1402.061 1466.383 1365.872 1466.083 1479.886 1436.550 1436.340
[9] 1416.713 NA
> rowVars(tmp5)
[1] 7689.49017 70.75865 115.30417 58.89659 63.41654 138.07568
[7] 129.73050 42.80642 48.03298 99.41324
> rowSd(tmp5)
[1] 87.689738 8.411816 10.737978 7.674411 7.963451 11.750561 11.389930
[8] 6.542662 6.930583 9.970619
> rowMax(tmp5)
[1] 462.92951 82.80911 93.14181 85.14333 90.29510 92.66693 92.75610
[8] 82.79271 84.20323 NA
> rowMin(tmp5)
[1] 59.52083 56.19008 57.35403 57.71000 61.06579 55.91303 52.94641 60.19946
[9] 56.01120 NA
>
> colMeans(tmp5)
[1] 107.27288 NA 72.42177 72.93114 74.03275 72.06553 73.13928
[8] 78.61797 66.34849 72.08887 71.92701 71.13552 69.00636 70.18697
[15] 71.61596 72.80767 75.18247 68.18958 73.26140 72.62258
> colSums(tmp5)
[1] 1072.7288 NA 724.2177 729.3114 740.3275 720.6553 731.3928
[8] 786.1797 663.4849 720.8887 719.2701 711.3552 690.0636 701.8697
[15] 716.1596 728.0767 751.8247 681.8958 732.6140 726.2258
> colVars(tmp5)
[1] 15686.99181 NA 69.51307 160.61699 161.11240 129.89242
[7] 56.33497 22.18348 54.23978 97.26639 81.06825 93.11661
[13] 89.82942 49.75887 82.92353 123.61135 86.07615 40.64829
[19] 51.65321 44.19295
> colSd(tmp5)
[1] 125.247722 NA 8.337450 12.673476 12.693006 11.397036
[7] 7.505663 4.709934 7.364766 9.862372 9.003791 9.649695
[13] 9.477838 7.053997 9.106236 11.118064 9.277723 6.375601
[19] 7.187016 6.647778
> colMax(tmp5)
[1] 462.92951 NA 86.44158 93.14181 90.64727 92.75610 82.79271
[8] 85.14333 78.92923 84.70590 80.81674 88.91689 81.40566 81.65445
[15] 84.20323 88.77634 90.29510 79.48324 86.37049 83.01425
> colMin(tmp5)
[1] 59.05675 NA 62.10668 57.71000 52.94641 55.91303 60.79973 70.18008
[9] 53.37196 57.35403 56.01120 61.98428 55.61238 60.73846 58.77627 54.79724
[17] 56.19008 60.77895 63.65973 63.80672
>
> Max(tmp5,na.rm=TRUE)
[1] 462.9295
> Min(tmp5,na.rm=TRUE)
[1] 52.94641
> mean(tmp5,na.rm=TRUE)
[1] 73.8906
> Sum(tmp5,na.rm=TRUE)
[1] 14704.23
> Var(tmp5,na.rm=TRUE)
[1] 850.3254
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.93608 70.10306 73.31914 68.29358 73.30417 73.99432 71.82750 71.81699
[9] 70.83563 73.45368
> rowSums(tmp5,na.rm=TRUE)
[1] 1838.722 1402.061 1466.383 1365.872 1466.083 1479.886 1436.550 1436.340
[9] 1416.713 1395.620
> rowVars(tmp5,na.rm=TRUE)
[1] 7689.49017 70.75865 115.30417 58.89659 63.41654 138.07568
[7] 129.73050 42.80642 48.03298 99.41324
> rowSd(tmp5,na.rm=TRUE)
[1] 87.689738 8.411816 10.737978 7.674411 7.963451 11.750561 11.389930
[8] 6.542662 6.930583 9.970619
> rowMax(tmp5,na.rm=TRUE)
[1] 462.92951 82.80911 93.14181 85.14333 90.29510 92.66693 92.75610
[8] 82.79271 84.20323 90.64727
> rowMin(tmp5,na.rm=TRUE)
[1] 59.52083 56.19008 57.35403 57.71000 61.06579 55.91303 52.94641 60.19946
[9] 56.01120 54.79724
>
> colMeans(tmp5,na.rm=TRUE)
[1] 107.27288 72.85418 72.42177 72.93114 74.03275 72.06553 73.13928
[8] 78.61797 66.34849 72.08887 71.92701 71.13552 69.00636 70.18697
[15] 71.61596 72.80767 75.18247 68.18958 73.26140 72.62258
> colSums(tmp5,na.rm=TRUE)
[1] 1072.7288 655.6876 724.2177 729.3114 740.3275 720.6553 731.3928
[8] 786.1797 663.4849 720.8887 719.2701 711.3552 690.0636 701.8697
[15] 716.1596 728.0767 751.8247 681.8958 732.6140 726.2258
> colVars(tmp5,na.rm=TRUE)
[1] 15686.99181 96.45074 69.51307 160.61699 161.11240 129.89242
[7] 56.33497 22.18348 54.23978 97.26639 81.06825 93.11661
[13] 89.82942 49.75887 82.92353 123.61135 86.07615 40.64829
[19] 51.65321 44.19295
> colSd(tmp5,na.rm=TRUE)
[1] 125.247722 9.820934 8.337450 12.673476 12.693006 11.397036
[7] 7.505663 4.709934 7.364766 9.862372 9.003791 9.649695
[13] 9.477838 7.053997 9.106236 11.118064 9.277723 6.375601
[19] 7.187016 6.647778
> colMax(tmp5,na.rm=TRUE)
[1] 462.92951 88.79965 86.44158 93.14181 90.64727 92.75610 82.79271
[8] 85.14333 78.92923 84.70590 80.81674 88.91689 81.40566 81.65445
[15] 84.20323 88.77634 90.29510 79.48324 86.37049 83.01425
> colMin(tmp5,na.rm=TRUE)
[1] 59.05675 61.89171 62.10668 57.71000 52.94641 55.91303 60.79973 70.18008
[9] 53.37196 57.35403 56.01120 61.98428 55.61238 60.73846 58.77627 54.79724
[17] 56.19008 60.77895 63.65973 63.80672
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.93608 70.10306 73.31914 68.29358 73.30417 73.99432 71.82750 71.81699
[9] 70.83563 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1838.722 1402.061 1466.383 1365.872 1466.083 1479.886 1436.550 1436.340
[9] 1416.713 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 7689.49017 70.75865 115.30417 58.89659 63.41654 138.07568
[7] 129.73050 42.80642 48.03298 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 87.689738 8.411816 10.737978 7.674411 7.963451 11.750561 11.389930
[8] 6.542662 6.930583 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 462.92951 82.80911 93.14181 85.14333 90.29510 92.66693 92.75610
[8] 82.79271 84.20323 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 59.52083 56.19008 57.35403 57.71000 61.06579 55.91303 52.94641 60.19946
[9] 56.01120 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 112.16807 NaN 71.78003 73.84438 72.18669 72.15240 72.95095
[8] 78.70511 65.79264 71.55208 71.40555 71.51364 70.49458 71.13617
[15] 70.35983 74.80883 74.63662 66.93472 71.80484 71.65309
> colSums(tmp5,na.rm=TRUE)
[1] 1009.5126 0.0000 646.0203 664.5994 649.6802 649.3716 656.5585
[8] 708.3460 592.1338 643.9688 642.6499 643.6227 634.4512 640.2256
[15] 633.2385 673.2795 671.7296 602.4125 646.2435 644.8778
> colVars(tmp5,na.rm=TRUE)
[1] 17378.28404 NA 73.56918 171.31141 142.91226 146.04409
[7] 62.97781 24.87100 57.54383 106.18311 88.14260 103.14776
[13] 76.14162 45.84266 75.53824 94.01059 93.48379 28.01448
[19] 34.24206 39.14309
> colSd(tmp5,na.rm=TRUE)
[1] 131.826720 NA 8.577248 13.088599 11.954592 12.084870
[7] 7.935856 4.987083 7.585765 10.304519 9.388429 10.156168
[13] 8.725916 6.770721 8.691274 9.695906 9.668701 5.292870
[19] 5.851671 6.256444
> colMax(tmp5,na.rm=TRUE)
[1] 462.92951 -Inf 86.44158 93.14181 87.17566 92.75610 82.79271
[8] 85.14333 78.92923 84.70590 80.81674 88.91689 81.40566 81.65445
[15] 84.20323 88.77634 90.29510 72.81485 78.65932 83.01425
> colMin(tmp5,na.rm=TRUE)
[1] 59.05675 Inf 62.10668 57.71000 52.94641 55.91303 60.79973 70.18008
[9] 53.37196 57.35403 56.01120 61.98428 58.94555 60.73846 58.77627 61.69728
[17] 56.19008 60.77895 63.65973 63.80672
>
>
>
>
> 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] 281.7632 154.2022 232.0202 139.7498 177.8487 237.7420 287.4364 193.8477
[9] 206.5938 330.9984
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 281.7632 154.2022 232.0202 139.7498 177.8487 237.7420 287.4364 193.8477
[9] 206.5938 330.9984
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 1.136868e-13 1.705303e-13 0.000000e+00 -5.684342e-14 -3.410605e-13
[6] 1.705303e-13 -1.421085e-13 1.421085e-13 5.684342e-14 1.136868e-13
[11] -2.842171e-14 2.842171e-14 -4.263256e-14 2.273737e-13 -8.526513e-14
[16] -2.842171e-14 -1.705303e-13 -2.131628e-14 4.973799e-14 8.526513e-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)
+ }
6 19
4 12
7 14
4 14
4 19
7 12
1 2
8 6
3 8
7 18
4 4
8 14
10 9
1 2
1 8
9 6
7 20
4 11
2 1
1 8
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.580156
> Min(tmp)
[1] -2.448139
> mean(tmp)
[1] -0.118724
> Sum(tmp)
[1] -11.8724
> Var(tmp)
[1] 0.8236697
>
> rowMeans(tmp)
[1] -0.118724
> rowSums(tmp)
[1] -11.8724
> rowVars(tmp)
[1] 0.8236697
> rowSd(tmp)
[1] 0.9075625
> rowMax(tmp)
[1] 2.580156
> rowMin(tmp)
[1] -2.448139
>
> colMeans(tmp)
[1] -0.339427907 0.800280901 -1.138260793 0.396465753 -0.996415946
[6] -0.308440878 -0.332984553 -0.094374805 -0.342368592 -0.995484732
[11] -0.904700694 -1.251529089 0.504767394 -0.880639040 0.249671816
[16] -0.704648145 -0.397059743 -0.408852103 0.452793102 0.442357908
[21] -0.239497089 -0.392043369 -1.186767088 -0.176191732 -0.698699894
[26] 0.495297103 -1.510695738 -0.945051541 1.659241386 0.739697032
[31] 0.886045712 1.179374292 -2.448138583 0.081067297 0.137985222
[36] 1.564160035 0.069451637 0.697292594 -0.911071677 0.934766570
[41] 0.657848765 -0.911909737 -0.745313061 -1.047196200 1.183750952
[46] 0.857879415 -0.838923923 0.148299876 0.095061255 -0.560241254
[51] -1.220940849 -0.512384364 -0.099068752 1.314617409 0.288834462
[56] -0.560117419 -0.321381053 0.535743926 -0.571842723 -0.069292528
[61] 1.355272431 0.001725702 -1.750563670 -1.916781849 0.690157632
[66] -1.025910176 -1.317185572 -0.081183741 0.558042726 -0.894019023
[71] -0.994317341 0.356085505 -0.609739904 0.030456151 -0.766357142
[76] -0.849988575 -0.107859627 -0.570562170 -1.455623509 1.065796051
[81] -0.328687426 0.049814050 0.110846459 -1.056061748 0.176696748
[86] 0.476900027 -1.300385915 -1.360082475 -1.293075264 0.598242555
[91] 0.992282246 0.223790719 -0.315212678 2.580156058 0.901116534
[96] 0.926643048 0.409449497 1.602241442 0.059740058 1.644944413
> colSums(tmp)
[1] -0.339427907 0.800280901 -1.138260793 0.396465753 -0.996415946
[6] -0.308440878 -0.332984553 -0.094374805 -0.342368592 -0.995484732
[11] -0.904700694 -1.251529089 0.504767394 -0.880639040 0.249671816
[16] -0.704648145 -0.397059743 -0.408852103 0.452793102 0.442357908
[21] -0.239497089 -0.392043369 -1.186767088 -0.176191732 -0.698699894
[26] 0.495297103 -1.510695738 -0.945051541 1.659241386 0.739697032
[31] 0.886045712 1.179374292 -2.448138583 0.081067297 0.137985222
[36] 1.564160035 0.069451637 0.697292594 -0.911071677 0.934766570
[41] 0.657848765 -0.911909737 -0.745313061 -1.047196200 1.183750952
[46] 0.857879415 -0.838923923 0.148299876 0.095061255 -0.560241254
[51] -1.220940849 -0.512384364 -0.099068752 1.314617409 0.288834462
[56] -0.560117419 -0.321381053 0.535743926 -0.571842723 -0.069292528
[61] 1.355272431 0.001725702 -1.750563670 -1.916781849 0.690157632
[66] -1.025910176 -1.317185572 -0.081183741 0.558042726 -0.894019023
[71] -0.994317341 0.356085505 -0.609739904 0.030456151 -0.766357142
[76] -0.849988575 -0.107859627 -0.570562170 -1.455623509 1.065796051
[81] -0.328687426 0.049814050 0.110846459 -1.056061748 0.176696748
[86] 0.476900027 -1.300385915 -1.360082475 -1.293075264 0.598242555
[91] 0.992282246 0.223790719 -0.315212678 2.580156058 0.901116534
[96] 0.926643048 0.409449497 1.602241442 0.059740058 1.644944413
> 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] -0.339427907 0.800280901 -1.138260793 0.396465753 -0.996415946
[6] -0.308440878 -0.332984553 -0.094374805 -0.342368592 -0.995484732
[11] -0.904700694 -1.251529089 0.504767394 -0.880639040 0.249671816
[16] -0.704648145 -0.397059743 -0.408852103 0.452793102 0.442357908
[21] -0.239497089 -0.392043369 -1.186767088 -0.176191732 -0.698699894
[26] 0.495297103 -1.510695738 -0.945051541 1.659241386 0.739697032
[31] 0.886045712 1.179374292 -2.448138583 0.081067297 0.137985222
[36] 1.564160035 0.069451637 0.697292594 -0.911071677 0.934766570
[41] 0.657848765 -0.911909737 -0.745313061 -1.047196200 1.183750952
[46] 0.857879415 -0.838923923 0.148299876 0.095061255 -0.560241254
[51] -1.220940849 -0.512384364 -0.099068752 1.314617409 0.288834462
[56] -0.560117419 -0.321381053 0.535743926 -0.571842723 -0.069292528
[61] 1.355272431 0.001725702 -1.750563670 -1.916781849 0.690157632
[66] -1.025910176 -1.317185572 -0.081183741 0.558042726 -0.894019023
[71] -0.994317341 0.356085505 -0.609739904 0.030456151 -0.766357142
[76] -0.849988575 -0.107859627 -0.570562170 -1.455623509 1.065796051
[81] -0.328687426 0.049814050 0.110846459 -1.056061748 0.176696748
[86] 0.476900027 -1.300385915 -1.360082475 -1.293075264 0.598242555
[91] 0.992282246 0.223790719 -0.315212678 2.580156058 0.901116534
[96] 0.926643048 0.409449497 1.602241442 0.059740058 1.644944413
> colMin(tmp)
[1] -0.339427907 0.800280901 -1.138260793 0.396465753 -0.996415946
[6] -0.308440878 -0.332984553 -0.094374805 -0.342368592 -0.995484732
[11] -0.904700694 -1.251529089 0.504767394 -0.880639040 0.249671816
[16] -0.704648145 -0.397059743 -0.408852103 0.452793102 0.442357908
[21] -0.239497089 -0.392043369 -1.186767088 -0.176191732 -0.698699894
[26] 0.495297103 -1.510695738 -0.945051541 1.659241386 0.739697032
[31] 0.886045712 1.179374292 -2.448138583 0.081067297 0.137985222
[36] 1.564160035 0.069451637 0.697292594 -0.911071677 0.934766570
[41] 0.657848765 -0.911909737 -0.745313061 -1.047196200 1.183750952
[46] 0.857879415 -0.838923923 0.148299876 0.095061255 -0.560241254
[51] -1.220940849 -0.512384364 -0.099068752 1.314617409 0.288834462
[56] -0.560117419 -0.321381053 0.535743926 -0.571842723 -0.069292528
[61] 1.355272431 0.001725702 -1.750563670 -1.916781849 0.690157632
[66] -1.025910176 -1.317185572 -0.081183741 0.558042726 -0.894019023
[71] -0.994317341 0.356085505 -0.609739904 0.030456151 -0.766357142
[76] -0.849988575 -0.107859627 -0.570562170 -1.455623509 1.065796051
[81] -0.328687426 0.049814050 0.110846459 -1.056061748 0.176696748
[86] 0.476900027 -1.300385915 -1.360082475 -1.293075264 0.598242555
[91] 0.992282246 0.223790719 -0.315212678 2.580156058 0.901116534
[96] 0.926643048 0.409449497 1.602241442 0.059740058 1.644944413
> colMedians(tmp)
[1] -0.339427907 0.800280901 -1.138260793 0.396465753 -0.996415946
[6] -0.308440878 -0.332984553 -0.094374805 -0.342368592 -0.995484732
[11] -0.904700694 -1.251529089 0.504767394 -0.880639040 0.249671816
[16] -0.704648145 -0.397059743 -0.408852103 0.452793102 0.442357908
[21] -0.239497089 -0.392043369 -1.186767088 -0.176191732 -0.698699894
[26] 0.495297103 -1.510695738 -0.945051541 1.659241386 0.739697032
[31] 0.886045712 1.179374292 -2.448138583 0.081067297 0.137985222
[36] 1.564160035 0.069451637 0.697292594 -0.911071677 0.934766570
[41] 0.657848765 -0.911909737 -0.745313061 -1.047196200 1.183750952
[46] 0.857879415 -0.838923923 0.148299876 0.095061255 -0.560241254
[51] -1.220940849 -0.512384364 -0.099068752 1.314617409 0.288834462
[56] -0.560117419 -0.321381053 0.535743926 -0.571842723 -0.069292528
[61] 1.355272431 0.001725702 -1.750563670 -1.916781849 0.690157632
[66] -1.025910176 -1.317185572 -0.081183741 0.558042726 -0.894019023
[71] -0.994317341 0.356085505 -0.609739904 0.030456151 -0.766357142
[76] -0.849988575 -0.107859627 -0.570562170 -1.455623509 1.065796051
[81] -0.328687426 0.049814050 0.110846459 -1.056061748 0.176696748
[86] 0.476900027 -1.300385915 -1.360082475 -1.293075264 0.598242555
[91] 0.992282246 0.223790719 -0.315212678 2.580156058 0.901116534
[96] 0.926643048 0.409449497 1.602241442 0.059740058 1.644944413
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.3394279 0.8002809 -1.138261 0.3964658 -0.9964159 -0.3084409 -0.3329846
[2,] -0.3394279 0.8002809 -1.138261 0.3964658 -0.9964159 -0.3084409 -0.3329846
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.0943748 -0.3423686 -0.9954847 -0.9047007 -1.251529 0.5047674 -0.880639
[2,] -0.0943748 -0.3423686 -0.9954847 -0.9047007 -1.251529 0.5047674 -0.880639
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.2496718 -0.7046481 -0.3970597 -0.4088521 0.4527931 0.4423579 -0.2394971
[2,] 0.2496718 -0.7046481 -0.3970597 -0.4088521 0.4527931 0.4423579 -0.2394971
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.3920434 -1.186767 -0.1761917 -0.6986999 0.4952971 -1.510696 -0.9450515
[2,] -0.3920434 -1.186767 -0.1761917 -0.6986999 0.4952971 -1.510696 -0.9450515
[,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36]
[1,] 1.659241 0.739697 0.8860457 1.179374 -2.448139 0.0810673 0.1379852 1.56416
[2,] 1.659241 0.739697 0.8860457 1.179374 -2.448139 0.0810673 0.1379852 1.56416
[,37] [,38] [,39] [,40] [,41] [,42] [,43]
[1,] 0.06945164 0.6972926 -0.9110717 0.9347666 0.6578488 -0.9119097 -0.7453131
[2,] 0.06945164 0.6972926 -0.9110717 0.9347666 0.6578488 -0.9119097 -0.7453131
[,44] [,45] [,46] [,47] [,48] [,49] [,50]
[1,] -1.047196 1.183751 0.8578794 -0.8389239 0.1482999 0.09506126 -0.5602413
[2,] -1.047196 1.183751 0.8578794 -0.8389239 0.1482999 0.09506126 -0.5602413
[,51] [,52] [,53] [,54] [,55] [,56] [,57]
[1,] -1.220941 -0.5123844 -0.09906875 1.314617 0.2888345 -0.5601174 -0.3213811
[2,] -1.220941 -0.5123844 -0.09906875 1.314617 0.2888345 -0.5601174 -0.3213811
[,58] [,59] [,60] [,61] [,62] [,63] [,64]
[1,] 0.5357439 -0.5718427 -0.06929253 1.355272 0.001725702 -1.750564 -1.916782
[2,] 0.5357439 -0.5718427 -0.06929253 1.355272 0.001725702 -1.750564 -1.916782
[,65] [,66] [,67] [,68] [,69] [,70] [,71]
[1,] 0.6901576 -1.02591 -1.317186 -0.08118374 0.5580427 -0.894019 -0.9943173
[2,] 0.6901576 -1.02591 -1.317186 -0.08118374 0.5580427 -0.894019 -0.9943173
[,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.3560855 -0.6097399 0.03045615 -0.7663571 -0.8499886 -0.1078596
[2,] 0.3560855 -0.6097399 0.03045615 -0.7663571 -0.8499886 -0.1078596
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.5705622 -1.455624 1.065796 -0.3286874 0.04981405 0.1108465 -1.056062
[2,] -0.5705622 -1.455624 1.065796 -0.3286874 0.04981405 0.1108465 -1.056062
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.1766967 0.4769 -1.300386 -1.360082 -1.293075 0.5982426 0.9922822
[2,] 0.1766967 0.4769 -1.300386 -1.360082 -1.293075 0.5982426 0.9922822
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.2237907 -0.3152127 2.580156 0.9011165 0.926643 0.4094495 1.602241
[2,] 0.2237907 -0.3152127 2.580156 0.9011165 0.926643 0.4094495 1.602241
[,99] [,100]
[1,] 0.05974006 1.644944
[2,] 0.05974006 1.644944
>
>
> Max(tmp2)
[1] 2.666392
> Min(tmp2)
[1] -2.565714
> mean(tmp2)
[1] -0.130105
> Sum(tmp2)
[1] -13.0105
> Var(tmp2)
[1] 0.9932579
>
> rowMeans(tmp2)
[1] -1.1085216415 -1.2123550331 1.1353542976 -0.3818006389 -2.5657140764
[6] -0.1190137363 0.1800306976 -1.7894259754 -0.2896249144 0.5499100244
[11] -1.5699460824 -1.5633996857 0.8765362356 0.6729186943 -0.4785643697
[16] 0.8906843500 -0.6880772619 -0.5114947062 -0.1147816433 2.6663924506
[21] -0.5251835815 0.7413546304 -0.3043932080 -0.0646302372 0.2822762848
[26] -0.9505923700 0.1600902827 -0.7735436944 -0.7101871072 -0.5244231881
[31] 0.2526346669 -0.6278710607 -1.4803124622 2.0353851858 -0.9287336829
[36] -1.2629525005 0.3429918722 -0.6498118635 0.1800635831 -1.5564134634
[41] 0.4142366514 0.9058631905 0.2778494549 -0.4604359765 -0.6960090984
[46] 1.6297897963 -1.3301801605 0.1072883101 -0.3367321341 2.1640692844
[51] -0.7466939814 1.0263301696 -1.1162928433 -0.4574273847 0.4135362255
[56] 0.9099366540 -0.0002006004 1.1947148636 1.3420296706 0.7508919896
[61] -0.3545831346 -0.0589414730 -1.6591739332 0.5974202163 -0.2179318721
[66] -1.1885423659 -0.3145728051 -0.6031363351 -0.9746983106 0.1160772726
[71] -0.8570913886 -1.4661913789 0.0091922364 1.7505713979 0.4550486318
[76] 0.7204181303 1.5758313181 1.1369734644 -1.4476123678 -1.9223254039
[81] -0.9172294614 -1.7150343420 -0.1401811266 1.1028296691 0.0203062101
[86] 0.6258108722 0.7931016849 0.6453310133 -0.2700749585 -1.1335145259
[91] 0.0464961819 -0.7844490797 -1.2422107309 -0.1787810325 -1.0932835768
[96] -0.1321414980 0.5099828566 -0.2982235403 0.1296744847 1.5169419894
> rowSums(tmp2)
[1] -1.1085216415 -1.2123550331 1.1353542976 -0.3818006389 -2.5657140764
[6] -0.1190137363 0.1800306976 -1.7894259754 -0.2896249144 0.5499100244
[11] -1.5699460824 -1.5633996857 0.8765362356 0.6729186943 -0.4785643697
[16] 0.8906843500 -0.6880772619 -0.5114947062 -0.1147816433 2.6663924506
[21] -0.5251835815 0.7413546304 -0.3043932080 -0.0646302372 0.2822762848
[26] -0.9505923700 0.1600902827 -0.7735436944 -0.7101871072 -0.5244231881
[31] 0.2526346669 -0.6278710607 -1.4803124622 2.0353851858 -0.9287336829
[36] -1.2629525005 0.3429918722 -0.6498118635 0.1800635831 -1.5564134634
[41] 0.4142366514 0.9058631905 0.2778494549 -0.4604359765 -0.6960090984
[46] 1.6297897963 -1.3301801605 0.1072883101 -0.3367321341 2.1640692844
[51] -0.7466939814 1.0263301696 -1.1162928433 -0.4574273847 0.4135362255
[56] 0.9099366540 -0.0002006004 1.1947148636 1.3420296706 0.7508919896
[61] -0.3545831346 -0.0589414730 -1.6591739332 0.5974202163 -0.2179318721
[66] -1.1885423659 -0.3145728051 -0.6031363351 -0.9746983106 0.1160772726
[71] -0.8570913886 -1.4661913789 0.0091922364 1.7505713979 0.4550486318
[76] 0.7204181303 1.5758313181 1.1369734644 -1.4476123678 -1.9223254039
[81] -0.9172294614 -1.7150343420 -0.1401811266 1.1028296691 0.0203062101
[86] 0.6258108722 0.7931016849 0.6453310133 -0.2700749585 -1.1335145259
[91] 0.0464961819 -0.7844490797 -1.2422107309 -0.1787810325 -1.0932835768
[96] -0.1321414980 0.5099828566 -0.2982235403 0.1296744847 1.5169419894
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] -1.1085216415 -1.2123550331 1.1353542976 -0.3818006389 -2.5657140764
[6] -0.1190137363 0.1800306976 -1.7894259754 -0.2896249144 0.5499100244
[11] -1.5699460824 -1.5633996857 0.8765362356 0.6729186943 -0.4785643697
[16] 0.8906843500 -0.6880772619 -0.5114947062 -0.1147816433 2.6663924506
[21] -0.5251835815 0.7413546304 -0.3043932080 -0.0646302372 0.2822762848
[26] -0.9505923700 0.1600902827 -0.7735436944 -0.7101871072 -0.5244231881
[31] 0.2526346669 -0.6278710607 -1.4803124622 2.0353851858 -0.9287336829
[36] -1.2629525005 0.3429918722 -0.6498118635 0.1800635831 -1.5564134634
[41] 0.4142366514 0.9058631905 0.2778494549 -0.4604359765 -0.6960090984
[46] 1.6297897963 -1.3301801605 0.1072883101 -0.3367321341 2.1640692844
[51] -0.7466939814 1.0263301696 -1.1162928433 -0.4574273847 0.4135362255
[56] 0.9099366540 -0.0002006004 1.1947148636 1.3420296706 0.7508919896
[61] -0.3545831346 -0.0589414730 -1.6591739332 0.5974202163 -0.2179318721
[66] -1.1885423659 -0.3145728051 -0.6031363351 -0.9746983106 0.1160772726
[71] -0.8570913886 -1.4661913789 0.0091922364 1.7505713979 0.4550486318
[76] 0.7204181303 1.5758313181 1.1369734644 -1.4476123678 -1.9223254039
[81] -0.9172294614 -1.7150343420 -0.1401811266 1.1028296691 0.0203062101
[86] 0.6258108722 0.7931016849 0.6453310133 -0.2700749585 -1.1335145259
[91] 0.0464961819 -0.7844490797 -1.2422107309 -0.1787810325 -1.0932835768
[96] -0.1321414980 0.5099828566 -0.2982235403 0.1296744847 1.5169419894
> rowMin(tmp2)
[1] -1.1085216415 -1.2123550331 1.1353542976 -0.3818006389 -2.5657140764
[6] -0.1190137363 0.1800306976 -1.7894259754 -0.2896249144 0.5499100244
[11] -1.5699460824 -1.5633996857 0.8765362356 0.6729186943 -0.4785643697
[16] 0.8906843500 -0.6880772619 -0.5114947062 -0.1147816433 2.6663924506
[21] -0.5251835815 0.7413546304 -0.3043932080 -0.0646302372 0.2822762848
[26] -0.9505923700 0.1600902827 -0.7735436944 -0.7101871072 -0.5244231881
[31] 0.2526346669 -0.6278710607 -1.4803124622 2.0353851858 -0.9287336829
[36] -1.2629525005 0.3429918722 -0.6498118635 0.1800635831 -1.5564134634
[41] 0.4142366514 0.9058631905 0.2778494549 -0.4604359765 -0.6960090984
[46] 1.6297897963 -1.3301801605 0.1072883101 -0.3367321341 2.1640692844
[51] -0.7466939814 1.0263301696 -1.1162928433 -0.4574273847 0.4135362255
[56] 0.9099366540 -0.0002006004 1.1947148636 1.3420296706 0.7508919896
[61] -0.3545831346 -0.0589414730 -1.6591739332 0.5974202163 -0.2179318721
[66] -1.1885423659 -0.3145728051 -0.6031363351 -0.9746983106 0.1160772726
[71] -0.8570913886 -1.4661913789 0.0091922364 1.7505713979 0.4550486318
[76] 0.7204181303 1.5758313181 1.1369734644 -1.4476123678 -1.9223254039
[81] -0.9172294614 -1.7150343420 -0.1401811266 1.1028296691 0.0203062101
[86] 0.6258108722 0.7931016849 0.6453310133 -0.2700749585 -1.1335145259
[91] 0.0464961819 -0.7844490797 -1.2422107309 -0.1787810325 -1.0932835768
[96] -0.1321414980 0.5099828566 -0.2982235403 0.1296744847 1.5169419894
>
> colMeans(tmp2)
[1] -0.130105
> colSums(tmp2)
[1] -13.0105
> colVars(tmp2)
[1] 0.9932579
> colSd(tmp2)
[1] 0.9966232
> colMax(tmp2)
[1] 2.666392
> colMin(tmp2)
[1] -2.565714
> colMedians(tmp2)
[1] -0.1594811
> colRanges(tmp2)
[,1]
[1,] -2.565714
[2,] 2.666392
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -3.116817 -2.117329 4.436937 -2.380856 5.280603 -4.116216 1.262359
[8] -6.268848 4.675304 -3.237694
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.9099228
[2,] -0.7048814
[3,] -0.1920653
[4,] 0.4262119
[5,] 0.8139965
>
> rowApply(tmp,sum)
[1] -0.2322224 0.9338134 0.7057551 2.2682545 -3.9169822 -1.4800773
[7] -5.6928345 5.0602390 -1.9736960 -1.2548059
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 1 9 2 3 8 8 7 4 8
[2,] 7 9 10 7 2 3 5 4 2 2
[3,] 1 4 6 3 10 2 9 9 9 9
[4,] 8 5 4 8 6 6 6 3 6 1
[5,] 10 10 2 5 9 9 1 10 3 4
[6,] 5 8 8 1 8 1 2 1 8 3
[7,] 6 7 3 10 7 7 4 6 7 6
[8,] 4 3 7 4 1 5 7 2 1 7
[9,] 9 2 5 6 5 10 10 8 10 10
[10,] 2 6 1 9 4 4 3 5 5 5
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.1582728 1.6003254 3.3776144 3.2116692 1.7114696 -1.2361701
[7] -1.0053944 0.3259104 2.4945858 -1.4917044 1.4380102 -3.4026078
[13] -1.0927706 2.7548165 -3.1017846 0.6172657 -2.7917858 0.8810117
[19] -1.1558110 -0.6075769
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.2878039
[2,] -1.0063378
[3,] -0.4028877
[4,] 0.8071271
[5,] 1.7316295
>
> rowApply(tmp,sum)
[1] -1.5956379 5.3937823 3.6750900 -4.1811231 -0.9233109
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 5 20 5 19 2
[2,] 10 18 13 11 11
[3,] 19 17 14 13 12
[4,] 7 16 20 4 20
[5,] 2 15 17 2 19
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.0063378 -0.18006702 1.38479497 -0.7207419 -1.291772 0.9675127
[2,] 1.7316295 1.60502553 1.20285216 1.1710217 1.036333 -0.7733304
[3,] -0.4028877 0.37174001 0.58309316 1.6244481 1.332134 0.1966075
[4,] 0.8071271 -0.21017970 -0.09112707 -0.9132992 -1.308820 -0.5765491
[5,] -1.2878039 0.01380659 0.29800121 2.0502405 1.943595 -1.0504106
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.2628027 1.04658929 1.18106715 -0.08120714 -0.1814461 -0.8901842
[2,] -1.2170409 0.16352697 0.84376823 -1.49455850 0.8669357 0.7366050
[3,] -0.3416430 0.14967554 -0.08853686 0.19723149 0.6418447 -1.0020381
[4,] -0.2108495 0.07188936 -0.91973226 -0.68598806 0.5092741 -0.4996173
[5,] 0.5013363 -1.10577075 1.47801955 0.57281777 -0.3985981 -1.7473732
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.09485846 0.2589761 -0.008657028 -0.3682624 -1.8739975 2.1893302
[2,] 1.61591455 0.5209681 -1.574278652 0.6929776 -1.7260091 0.2391949
[3,] -0.52784173 0.1395977 -1.436093062 1.3018014 1.5796095 -1.8466948
[4,] -1.63306898 1.4769557 -0.503782480 -0.1777137 0.4682563 0.7462825
[5,] -0.45291598 0.3583190 0.421026599 -0.8315373 -1.2396451 -0.4471011
[,19] [,20]
[1,] -1.1110827 -1.0780966
[2,] 0.4868711 -0.7346239
[3,] -0.3968307 1.5998732
[4,] -0.4725979 -0.0575831
[5,] 0.3378293 -0.3371466
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 638 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 550 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.8 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.3870909 -0.56379 -0.7557998 -0.5131578 1.804665 -0.1215587 -1.366059
col8 col9 col10 col11 col12 col13 col14
row1 0.9682797 0.8004317 -1.020097 1.845719 0.04002196 -1.363009 -0.07060162
col15 col16 col17 col18 col19 col20
row1 -0.7065232 -0.379137 0.9851575 -0.8268981 0.51595 0.06835488
> tmp[,"col10"]
col10
row1 -1.0200972
row2 0.9466209
row3 -1.4429549
row4 -0.5037770
row5 -0.3461159
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.3870909 -0.5637900 -0.7557998 -0.51315776 1.8046648 -0.1215587
row5 -0.2288039 0.0893262 -0.4945288 0.01019662 -0.1344917 0.3787128
col7 col8 col9 col10 col11 col12 col13
row1 -1.366059 0.9682797 0.8004317 -1.0200972 1.845719 0.04002196 -1.363009
row5 2.406622 0.3897649 -1.5566480 -0.3461159 1.020282 0.50675793 -1.226495
col14 col15 col16 col17 col18 col19
row1 -0.07060162 -0.7065232 -0.379137 0.9851575 -0.8268981 0.515950
row5 0.46904907 0.0743171 -2.286862 -0.5745289 -0.2112435 -1.238098
col20
row1 0.06835488
row5 0.52857588
> tmp[,c("col6","col20")]
col6 col20
row1 -0.1215587 0.06835488
row2 -0.3215764 -0.95621473
row3 -0.2292673 -0.27916830
row4 0.7694323 1.32839376
row5 0.3787128 0.52857588
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.1215587 0.06835488
row5 0.3787128 0.52857588
>
>
>
>
> 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 50.02115 47.95393 49.28036 51.89902 51.00455 105.0991 51.58408 51.41136
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.9685 52.32677 50.74439 51.47307 50.67258 48.36532 50.57705 49.09002
col17 col18 col19 col20
row1 50.01096 49.98777 49.42036 105.845
> tmp[,"col10"]
col10
row1 52.32677
row2 29.98163
row3 29.70985
row4 30.55759
row5 50.00365
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.02115 47.95393 49.28036 51.89902 51.00455 105.0991 51.58408 51.41136
row5 50.64131 49.53303 51.04982 50.40541 51.30498 104.2924 48.56275 49.97449
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.9685 52.32677 50.74439 51.47307 50.67258 48.36532 50.57705 49.09002
row5 49.5024 50.00365 48.25281 49.65828 51.40064 49.01911 49.63007 52.19523
col17 col18 col19 col20
row1 50.01096 49.98777 49.42036 105.8450
row5 49.97598 49.31436 51.46240 103.6611
> tmp[,c("col6","col20")]
col6 col20
row1 105.09910 105.84502
row2 74.63210 73.33096
row3 73.08255 72.28712
row4 74.75678 73.34092
row5 104.29241 103.66113
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.0991 105.8450
row5 104.2924 103.6611
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.0991 105.8450
row5 104.2924 103.6611
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.11194260
[2,] 0.08200302
[3,] 0.50337419
[4,] 0.15317154
[5,] -0.19158562
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.1072395 -0.18830154
[2,] -1.2493089 0.68530440
[3,] -0.4783996 0.09485507
[4,] -0.1871930 0.47121627
[5,] 0.2301238 1.51022141
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.1534989 0.43626409
[2,] -0.6617807 0.02987399
[3,] -1.6688571 0.35052402
[4,] 1.2345802 1.06667704
[5,] 0.3556872 -0.21174143
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.153499
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.1534989
[2,] -0.6617807
>
>
>
> 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 -0.3430693 0.6351022 0.9377363 1.02637441 1.1548149 -0.1697443 -0.8638620
row1 -1.9258295 -0.9581523 1.2090299 0.03114765 0.3592054 -0.3388700 -0.7139818
[,8] [,9] [,10] [,11] [,12] [,13]
row3 0.29693007 -0.5901790 0.7273832 1.25045545 -0.4825102 0.1998837
row1 0.08715114 -0.6069969 -0.3727047 0.06673731 1.0262060 0.5677896
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -1.5543262 -1.4969985 1.5673735 -1.180450 -1.296596 -1.097654047
row1 0.1843801 -0.8890525 0.4784413 1.423371 0.652866 -0.002540171
[,20]
row3 -0.8166615
row1 -1.7566564
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.1703665 0.3060998 0.3845834 0.2918454 1.35381 0.1732276 -0.4555602
[,8] [,9] [,10]
row2 -1.475556 0.8202504 1.205387
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.8108938 -1.068058 -0.08297125 1.535038 0.04851997 -0.4238441 -0.4088601
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.08575037 -1.044371 0.04250211 0.9825112 0.5060864 1.288372 -0.1705826
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.583054 0.5061283 1.059671 2.500045 0.4601893 0.3318025
>
>
> 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: 0x211d5a0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM181449702f28"
[2] "/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM18144b0fd478"
[3] "/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM1814782f4bf2"
[4] "/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM18146706fef5"
[5] "/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM181460588237"
[6] "/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM18141bb9cac7"
[7] "/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM18142121955d"
[8] "/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM181446a2105a"
[9] "/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM181436a44ce4"
[10] "/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM1814777118f"
[11] "/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM181446ad4992"
[12] "/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM181461a239"
[13] "/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM181436a03384"
[14] "/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM1814170651b"
[15] "/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests/BM181429519c80"
>
>
> ### 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: 0x20a4a10>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x20a4a10>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.7-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x20a4a10>
> rowMedians(tmp)
[1] 0.275337303 0.021057815 0.148981403 0.346613896 -0.058081293
[6] -0.109560673 -0.219131455 0.275522045 -0.088017386 0.339188449
[11] 0.614715000 0.236915817 0.338035912 -0.247958463 0.057951269
[16] -0.024411723 -0.381289557 -0.413637194 -0.441504731 -0.543220602
[21] 0.126457134 -0.111823591 0.170076146 -0.090135121 -0.140953331
[26] 0.507782591 -0.418375507 0.248985316 -0.321610499 0.321115701
[31] 0.164415527 0.545203599 -0.315315129 0.464672697 -0.484345079
[36] -0.148846993 0.011948115 0.116702819 0.258125039 0.143258814
[41] 0.185038984 -0.180214149 -0.052761501 -0.464165909 -0.040360382
[46] -0.146865701 0.388372041 0.133175468 -0.302130747 0.049308717
[51] -0.165003073 -0.574829010 0.573338775 -0.121575230 -0.554333918
[56] -0.218979663 -0.086263639 0.265040873 0.203096565 -0.064315795
[61] -0.030218203 0.408080424 -0.282518123 -0.427347052 0.100178565
[66] 0.033122038 -0.334329947 -0.420435855 -0.062673778 0.461487414
[71] 0.116631792 -0.020681395 -0.459634486 -0.104927080 0.012312164
[76] -0.469930005 -0.099298418 0.333410173 -0.355302577 0.134043909
[81] -0.025073787 -0.147244158 0.136855517 -0.097261955 0.113229590
[86] 0.250098576 0.502630294 -0.020676088 0.014821230 0.340457675
[91] 0.201345283 0.193734603 0.590421363 -0.481960434 0.472008741
[96] 0.181267995 -0.118332655 0.046255142 0.266151067 0.189616149
[101] -0.411248568 0.240794154 -0.510651973 -0.134092481 0.465005555
[106] -0.207858650 0.180047773 0.134790547 -0.066233439 -0.157336383
[111] -0.297989998 -0.335770689 0.255159717 -0.245881768 -0.530080726
[116] -0.174069478 0.693939280 -0.216374412 0.121650164 -0.440196487
[121] 0.126986882 0.221511755 -0.021119582 -0.238203864 -0.293810300
[126] -0.215318459 0.034210627 0.413887372 -0.081255376 -0.194828164
[131] 0.409288215 0.426036092 0.075466591 0.017820197 0.115715029
[136] 0.025093382 0.093734173 0.084100490 -0.456254235 0.375153802
[141] 0.271413994 0.169221249 -0.356753069 -0.116923693 0.230780814
[146] 0.177108292 -0.010905593 0.058108090 -0.078478970 0.184994491
[151] -0.037273226 -0.412917660 -0.082638205 -0.163417898 -0.171127745
[156] -0.199595041 -0.360448045 0.016128949 -0.495148398 0.221439712
[161] -0.282857543 -0.249536682 -0.123647599 0.339386390 0.098704473
[166] 0.187941190 -0.050045086 0.190977228 -0.489421123 0.341442615
[171] 0.447734107 0.118509254 0.250306507 0.049316363 0.092399489
[176] 0.840469038 0.062839906 -0.476056415 -0.124809682 0.058828527
[181] -0.430987363 0.202840711 -0.134682502 0.008069723 0.245232209
[186] -0.196879411 -0.010491821 -0.044221586 0.084719070 0.190341445
[191] 0.269966759 0.205040429 0.231789931 -0.130471328 0.858444753
[196] -0.335553855 -0.262338096 0.271051708 0.509726597 0.099002645
[201] 0.003055461 0.222445950 0.074900487 -0.053646979 0.267701966
[206] 0.077192636 0.106467468 0.920299428 0.614772650 0.524313841
[211] -0.382163549 0.756025446 0.465915912 0.306144068 -0.085435942
[216] -0.223228256 -0.085803137 0.151114250 -0.187645431 0.079862312
[221] 0.122723765 0.271689713 0.195509097 0.254010038 0.066461887
[226] 0.045876336 0.526455424 -0.431178663 -0.085738935 -0.042777287
>
> proc.time()
user system elapsed
1.648 0.788 2.479
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 3.5.1 Patched (2018-07-12 r74967) -- "Feather Spray"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (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: 0x30f8190>
> .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: 0x30f8190>
> .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: 0x30f8190>
> .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: 0x30f8190>
> 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: 0x2173c60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2173c60>
> .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: 0x2173c60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2173c60>
> .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: 0x2173c60>
> 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: 0x1d53040>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1d53040>
> .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: 0x1d53040>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x1d53040>
> .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: 0x1d53040>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x1d53040>
> .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: 0x1d53040>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x1d53040>
> .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: 0x1d53040>
> 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: 0x1762eb0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x1762eb0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1762eb0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1762eb0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile18d23082ee51" "BufferedMatrixFile18d27af71dc7"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile18d23082ee51" "BufferedMatrixFile18d27af71dc7"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x330eee0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x330eee0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x330eee0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x330eee0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x330eee0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x330eee0>
> .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: 0x1bf62e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1bf62e0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x1bf62e0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x1bf62e0>
> 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: 0x23b08d0>
> .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: 0x23b08d0>
> rm(P)
>
> proc.time()
user system elapsed
0.240 0.024 0.261
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 3.5.1 Patched (2018-07-12 r74967) -- "Feather Spray"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (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
0.236 0.008 0.240