Ben Bolstad
| Snapshot Date: 2019-10-15 17:01:26 -0400 (Tue, 15 Oct 2019) |
| URL: https://git.bioconductor.org/packages/BufferedMatrix |
| Branch: RELEASE_3_9 |
| Last Commit: 5368d45 |
| Last Changed Date: 2019-05-02 11:53:07 -0400 (Thu, 02 May 2019) |
| Back to Multiple platform build/check report for BioC 3.9 |
|
This page was generated on 2019-10-16 11:56:23 -0400 (Wed, 16 Oct 2019).
| Package 193/1741 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||
| BufferedMatrix 1.48.0 Ben Bolstad
| malbec2 | Linux (Ubuntu 18.04.2 LTS) / x86_64 | OK | OK | [ OK ] | | ||||||
| tokay2 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||
| celaya2 | OS X 10.11.6 El Capitan / x86_64 | OK | OK | OK | OK | |
| Package: BufferedMatrix |
| Version: 1.48.0 |
| Command: /home/biocbuild/bbs-3.9-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.9-bioc/R/library --no-vignettes --timings BufferedMatrix_1.48.0.tar.gz |
| StartedAt: 2019-10-16 00:12:36 -0400 (Wed, 16 Oct 2019) |
| EndedAt: 2019-10-16 00:13:03 -0400 (Wed, 16 Oct 2019) |
| EllapsedTime: 27.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.9-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.9-bioc/R/library --no-vignettes --timings BufferedMatrix_1.48.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck’ * using R version 3.6.1 (2019-07-05) * 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 ‘1.48.0’ * 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-3.9-bioc/meat/BufferedMatrix.Rcheck/00check.log’ for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.9-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.9-bioc/R/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
gcc -I"/home/biocbuild/bbs-3.9-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.9-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){
^~~~~~~~~~~~~~~~~~~
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-3.9-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-3.9-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-3.9-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-3.9-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.9-bioc/R/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 3.6.1 (2019-07-05) -- "Action of the Toes"
Copyright (C) 2019 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
0.239 0.040 0.265
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 3.6.1 (2019-07-05) -- "Action of the Toes"
Copyright (C) 2019 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-3.9-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 412188 22.1 857928 45.9 639502 34.2
Vcells 738921 5.7 8388608 64.0 1807591 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] "Wed Oct 16 00:12:56 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] "Wed Oct 16 00:12:56 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)
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Wed Oct 16 00:12:57 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] "Wed Oct 16 00:12:57 2019"
>
> ColMode(tmp2)
>
>
>
> ### 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,] 98.95247400 -0.4792002 0.99819913 -0.1507704
[2,] 0.05853488 0.2327322 1.96157666 0.5853327
[3,] 0.88003621 -1.0735564 0.08511377 -0.9320439
[4,] 1.54523058 -1.5156964 0.74131303 -0.3176398
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 98.95247400 0.4792002 0.99819913 0.1507704
[2,] 0.05853488 0.2327322 1.96157666 0.5853327
[3,] 0.88003621 1.0735564 0.08511377 0.9320439
[4,] 1.54523058 1.5156964 0.74131303 0.3176398
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9474858 0.6922429 0.9990992 0.3882916
[2,] 0.2419398 0.4824233 1.4005630 0.7650704
[3,] 0.9381025 1.0361257 0.2917427 0.9654242
[4,] 1.2430730 1.2311362 0.8609954 0.5635954
>
> 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-3.9-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 223.42733 32.40163 35.98919 29.03369
[2,] 27.47793 30.05696 40.96721 33.23604
[3,] 35.26106 36.43481 28.00254 35.58629
[4,] 38.97596 38.82706 34.35127 30.95359
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
> exp(tmp5)
> log(tmp5,2)
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 465.0347
> Min(tmp5)
[1] 53.54752
> mean(tmp5)
[1] 72.18873
> Sum(tmp5)
[1] 14437.75
> Var(tmp5)
[1] 856.5686
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.24819 72.54689 72.68299 71.18718 68.43769 72.26689 64.37861 69.93785
[9] 67.42784 70.77320
> rowSums(tmp5)
[1] 1844.964 1450.938 1453.660 1423.744 1368.754 1445.338 1287.572 1398.757
[9] 1348.557 1415.464
> rowVars(tmp5)
[1] 7796.99752 81.33945 64.55438 69.55021 85.29625 96.13035
[7] 64.37813 61.95822 61.26348 54.62637
> rowSd(tmp5)
[1] 88.300609 9.018838 8.034574 8.339677 9.235597 9.804609 8.023598
[8] 7.871355 7.827099 7.390965
> rowMax(tmp5)
[1] 465.03472 86.48082 84.97577 83.23718 82.19136 97.12094 84.07308
[8] 82.23716 80.37097 83.92876
> rowMin(tmp5)
[1] 54.12009 56.32638 56.63828 59.51065 53.65360 55.17675 53.54752 57.80277
[9] 55.70391 59.19899
>
> colMeans(tmp5)
[1] 105.63180 69.14745 70.50654 71.42346 76.90206 72.36530 73.45613
[8] 72.07828 68.61107 70.56728 70.87035 65.21414 75.67418 68.60951
[15] 65.58497 69.07153 70.25242 70.45504 72.77513 64.57799
> colSums(tmp5)
[1] 1056.3180 691.4745 705.0654 714.2346 769.0206 723.6530 734.5613
[8] 720.7828 686.1107 705.6728 708.7035 652.1414 756.7418 686.0951
[15] 655.8497 690.7153 702.5242 704.5504 727.7513 645.7799
> colVars(tmp5)
[1] 16033.39915 63.77488 72.81054 64.33918 89.59061 72.72944
[7] 48.39035 90.26592 82.75765 108.53428 104.16931 65.60285
[13] 89.04887 25.79326 74.26694 71.96966 75.29929 110.59938
[19] 50.18959 30.49848
> colSd(tmp5)
[1] 126.623059 7.985918 8.532909 8.021171 9.465232 8.528155
[7] 6.956317 9.500838 9.097123 10.417979 10.206337 8.099559
[13] 9.436571 5.078707 8.617827 8.483493 8.677516 10.516624
[19] 7.084461 5.522543
> colMax(tmp5)
[1] 465.03472 80.81344 85.26787 80.56854 85.44070 84.97577 84.48147
[8] 83.92876 86.03217 86.48082 88.52588 77.35592 97.12094 77.57803
[15] 80.32132 81.57615 81.65816 85.55495 82.95738 72.72892
> colMin(tmp5)
[1] 53.54752 59.19899 58.28362 60.42981 62.29799 59.51065 61.48282 56.99433
[9] 55.70391 54.12009 54.07866 54.84995 61.67263 62.69680 55.07027 53.65360
[17] 55.17879 54.74938 62.54306 56.32638
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 92.24819 72.54689 72.68299 71.18718 68.43769 72.26689 64.37861 NA
[9] 67.42784 70.77320
> rowSums(tmp5)
[1] 1844.964 1450.938 1453.660 1423.744 1368.754 1445.338 1287.572 NA
[9] 1348.557 1415.464
> rowVars(tmp5)
[1] 7796.99752 81.33945 64.55438 69.55021 85.29625 96.13035
[7] 64.37813 65.40022 61.26348 54.62637
> rowSd(tmp5)
[1] 88.300609 9.018838 8.034574 8.339677 9.235597 9.804609 8.023598
[8] 8.087040 7.827099 7.390965
> rowMax(tmp5)
[1] 465.03472 86.48082 84.97577 83.23718 82.19136 97.12094 84.07308
[8] NA 80.37097 83.92876
> rowMin(tmp5)
[1] 54.12009 56.32638 56.63828 59.51065 53.65360 55.17675 53.54752 NA
[9] 55.70391 59.19899
>
> colMeans(tmp5)
[1] 105.63180 69.14745 70.50654 71.42346 76.90206 72.36530 73.45613
[8] 72.07828 68.61107 70.56728 70.87035 65.21414 75.67418 68.60951
[15] 65.58497 69.07153 70.25242 70.45504 NA 64.57799
> colSums(tmp5)
[1] 1056.3180 691.4745 705.0654 714.2346 769.0206 723.6530 734.5613
[8] 720.7828 686.1107 705.6728 708.7035 652.1414 756.7418 686.0951
[15] 655.8497 690.7153 702.5242 704.5504 NA 645.7799
> colVars(tmp5)
[1] 16033.39915 63.77488 72.81054 64.33918 89.59061 72.72944
[7] 48.39035 90.26592 82.75765 108.53428 104.16931 65.60285
[13] 89.04887 25.79326 74.26694 71.96966 75.29929 110.59938
[19] NA 30.49848
> colSd(tmp5)
[1] 126.623059 7.985918 8.532909 8.021171 9.465232 8.528155
[7] 6.956317 9.500838 9.097123 10.417979 10.206337 8.099559
[13] 9.436571 5.078707 8.617827 8.483493 8.677516 10.516624
[19] NA 5.522543
> colMax(tmp5)
[1] 465.03472 80.81344 85.26787 80.56854 85.44070 84.97577 84.48147
[8] 83.92876 86.03217 86.48082 88.52588 77.35592 97.12094 77.57803
[15] 80.32132 81.57615 81.65816 85.55495 NA 72.72892
> colMin(tmp5)
[1] 53.54752 59.19899 58.28362 60.42981 62.29799 59.51065 61.48282 56.99433
[9] 55.70391 54.12009 54.07866 54.84995 61.67263 62.69680 55.07027 53.65360
[17] 55.17879 54.74938 NA 56.32638
>
> Max(tmp5,na.rm=TRUE)
[1] 465.0347
> Min(tmp5,na.rm=TRUE)
[1] 53.54752
> mean(tmp5,na.rm=TRUE)
[1] 72.20028
> Sum(tmp5,na.rm=TRUE)
[1] 14367.85
> Var(tmp5,na.rm=TRUE)
[1] 860.8679
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.24819 72.54689 72.68299 71.18718 68.43769 72.26689 64.37861 69.94029
[9] 67.42784 70.77320
> rowSums(tmp5,na.rm=TRUE)
[1] 1844.964 1450.938 1453.660 1423.744 1368.754 1445.338 1287.572 1328.865
[9] 1348.557 1415.464
> rowVars(tmp5,na.rm=TRUE)
[1] 7796.99752 81.33945 64.55438 69.55021 85.29625 96.13035
[7] 64.37813 65.40022 61.26348 54.62637
> rowSd(tmp5,na.rm=TRUE)
[1] 88.300609 9.018838 8.034574 8.339677 9.235597 9.804609 8.023598
[8] 8.087040 7.827099 7.390965
> rowMax(tmp5,na.rm=TRUE)
[1] 465.03472 86.48082 84.97577 83.23718 82.19136 97.12094 84.07308
[8] 82.23716 80.37097 83.92876
> rowMin(tmp5,na.rm=TRUE)
[1] 54.12009 56.32638 56.63828 59.51065 53.65360 55.17675 53.54752 57.80277
[9] 55.70391 59.19899
>
> colMeans(tmp5,na.rm=TRUE)
[1] 105.63180 69.14745 70.50654 71.42346 76.90206 72.36530 73.45613
[8] 72.07828 68.61107 70.56728 70.87035 65.21414 75.67418 68.60951
[15] 65.58497 69.07153 70.25242 70.45504 73.09553 64.57799
> colSums(tmp5,na.rm=TRUE)
[1] 1056.3180 691.4745 705.0654 714.2346 769.0206 723.6530 734.5613
[8] 720.7828 686.1107 705.6728 708.7035 652.1414 756.7418 686.0951
[15] 655.8497 690.7153 702.5242 704.5504 657.8598 645.7799
> colVars(tmp5,na.rm=TRUE)
[1] 16033.39915 63.77488 72.81054 64.33918 89.59061 72.72944
[7] 48.39035 90.26592 82.75765 108.53428 104.16931 65.60285
[13] 89.04887 25.79326 74.26694 71.96966 75.29929 110.59938
[19] 55.30838 30.49848
> colSd(tmp5,na.rm=TRUE)
[1] 126.623059 7.985918 8.532909 8.021171 9.465232 8.528155
[7] 6.956317 9.500838 9.097123 10.417979 10.206337 8.099559
[13] 9.436571 5.078707 8.617827 8.483493 8.677516 10.516624
[19] 7.436960 5.522543
> colMax(tmp5,na.rm=TRUE)
[1] 465.03472 80.81344 85.26787 80.56854 85.44070 84.97577 84.48147
[8] 83.92876 86.03217 86.48082 88.52588 77.35592 97.12094 77.57803
[15] 80.32132 81.57615 81.65816 85.55495 82.95738 72.72892
> colMin(tmp5,na.rm=TRUE)
[1] 53.54752 59.19899 58.28362 60.42981 62.29799 59.51065 61.48282 56.99433
[9] 55.70391 54.12009 54.07866 54.84995 61.67263 62.69680 55.07027 53.65360
[17] 55.17879 54.74938 62.54306 56.32638
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.24819 72.54689 72.68299 71.18718 68.43769 72.26689 64.37861 NaN
[9] 67.42784 70.77320
> rowSums(tmp5,na.rm=TRUE)
[1] 1844.964 1450.938 1453.660 1423.744 1368.754 1445.338 1287.572 0.000
[9] 1348.557 1415.464
> rowVars(tmp5,na.rm=TRUE)
[1] 7796.99752 81.33945 64.55438 69.55021 85.29625 96.13035
[7] 64.37813 NA 61.26348 54.62637
> rowSd(tmp5,na.rm=TRUE)
[1] 88.300609 9.018838 8.034574 8.339677 9.235597 9.804609 8.023598
[8] NA 7.827099 7.390965
> rowMax(tmp5,na.rm=TRUE)
[1] 465.03472 86.48082 84.97577 83.23718 82.19136 97.12094 84.07308
[8] NA 80.37097 83.92876
> rowMin(tmp5,na.rm=TRUE)
[1] 54.12009 56.32638 56.63828 59.51065 53.65360 55.17675 53.54752 NA
[9] 55.70391 59.19899
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 110.94614 67.97687 71.76362 70.46432 78.38209 71.26843 73.85737
[8] 71.48692 68.86385 71.56931 70.67653 63.86505 75.55486 68.49152
[15] 66.26296 68.58160 71.51830 69.92181 NaN 64.22953
> colSums(tmp5,na.rm=TRUE)
[1] 998.5153 611.7918 645.8726 634.1788 705.4388 641.4158 664.7164 643.3823
[9] 619.7747 644.1238 636.0888 574.7855 679.9938 616.4237 596.3666 617.2344
[17] 643.6647 629.2963 0.0000 578.0658
> colVars(tmp5,na.rm=TRUE)
[1] 17719.84954 56.33121 64.13402 62.03197 76.14646 68.28540
[7] 52.62795 97.61501 92.38352 110.80534 116.76787 53.32782
[13] 100.01982 28.86081 78.37909 78.26544 66.68417 121.22551
[19] NA 32.94479
> colSd(tmp5,na.rm=TRUE)
[1] 133.115925 7.505412 8.008372 7.876038 8.726194 8.263498
[7] 7.254512 9.880031 9.611635 10.526411 10.805918 7.302590
[13] 10.000991 5.372225 8.853197 8.846776 8.166037 11.010246
[19] NA 5.739755
> colMax(tmp5,na.rm=TRUE)
[1] 465.03472 80.81344 85.26787 80.56854 85.44070 84.97577 84.48147
[8] 83.92876 86.03217 86.48082 88.52588 76.33140 97.12094 77.57803
[15] 80.32132 81.57615 81.65816 85.55495 -Inf 72.72892
> colMin(tmp5,na.rm=TRUE)
[1] 53.54752 59.19899 58.28362 60.42981 62.29799 59.51065 61.48282 56.99433
[9] 55.70391 54.12009 54.07866 54.84995 61.67263 62.69680 55.07027 53.65360
[17] 55.17879 54.74938 Inf 56.32638
>
>
>
>
> 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] 242.5445 235.9308 271.9968 277.7289 328.6097 220.0889 199.1705 196.7868
[9] 407.2232 280.4673
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 242.5445 235.9308 271.9968 277.7289 328.6097 220.0889 199.1705 196.7868
[9] 407.2232 280.4673
>
>
>
> 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] 5.684342e-14 -5.684342e-14 -1.705303e-13 2.842171e-13 5.684342e-14
[6] 1.136868e-13 -2.842171e-14 1.136868e-13 0.000000e+00 0.000000e+00
[11] 1.705303e-13 -1.421085e-14 -1.136868e-13 2.842171e-14 1.136868e-13
[16] 4.263256e-14 0.000000e+00 4.263256e-14 -1.136868e-13 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)
+ }
5 2
8 10
6 12
7 8
7 2
5 8
6 14
2 2
1 3
5 15
2 8
6 10
6 5
2 7
10 1
6 3
5 19
9 11
9 11
7 4
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] 2.898046
> Min(tmp)
[1] -2.95789
> mean(tmp)
[1] 0.1771919
> Sum(tmp)
[1] 17.71919
> Var(tmp)
[1] 1.190984
>
> rowMeans(tmp)
[1] 0.1771919
> rowSums(tmp)
[1] 17.71919
> rowVars(tmp)
[1] 1.190984
> rowSd(tmp)
[1] 1.091322
> rowMax(tmp)
[1] 2.898046
> rowMin(tmp)
[1] -2.95789
>
> colMeans(tmp)
[1] -0.87580614 -0.57617624 0.31813689 0.01854199 -0.61613299 0.74976548
[7] -0.54450768 2.40453260 -0.20748689 1.90387459 0.24213362 0.45274542
[13] 0.37415409 0.72526878 0.37668156 -1.26306264 2.22053486 0.23847307
[19] 1.93316209 1.68170094 1.76142709 0.86630873 -1.04723924 -0.74029146
[25] 1.30668657 0.48621475 0.55717236 -0.82886496 1.70488047 0.58889509
[31] -0.18300864 1.95564536 0.71196531 -0.54662650 -0.44130421 2.10265795
[37] -0.79953634 -0.79113856 0.38311002 1.33949490 0.62507859 1.15615217
[43] -1.20949625 0.73820723 -0.71200538 -0.40604690 0.46319365 -0.65250278
[49] -0.64462724 1.33784127 -0.43536910 1.74768271 0.22192162 1.19674636
[55] -0.85342423 0.12221722 -2.95789042 0.30301936 1.07903907 0.67698870
[61] -1.83684134 1.94253307 -0.54406865 -0.01728374 0.30654456 1.99364543
[67] 0.35335797 -0.98561305 0.65540662 1.06021922 0.95827312 0.26742606
[73] 1.31606462 0.23270512 -0.45694657 -0.64284684 -1.15221052 -1.36279219
[79] -0.05547535 -0.36863639 -0.47406085 1.76509164 0.05012414 -1.46161916
[85] 0.55837367 -1.13253220 -0.20623314 -0.77044263 -1.11883732 -0.49716520
[91] -0.01121951 -0.60572163 -0.38606320 2.89804583 1.19216396 -0.66504102
[97] -2.16877678 -0.92034297 -0.61239032 0.88266623
> colSums(tmp)
[1] -0.87580614 -0.57617624 0.31813689 0.01854199 -0.61613299 0.74976548
[7] -0.54450768 2.40453260 -0.20748689 1.90387459 0.24213362 0.45274542
[13] 0.37415409 0.72526878 0.37668156 -1.26306264 2.22053486 0.23847307
[19] 1.93316209 1.68170094 1.76142709 0.86630873 -1.04723924 -0.74029146
[25] 1.30668657 0.48621475 0.55717236 -0.82886496 1.70488047 0.58889509
[31] -0.18300864 1.95564536 0.71196531 -0.54662650 -0.44130421 2.10265795
[37] -0.79953634 -0.79113856 0.38311002 1.33949490 0.62507859 1.15615217
[43] -1.20949625 0.73820723 -0.71200538 -0.40604690 0.46319365 -0.65250278
[49] -0.64462724 1.33784127 -0.43536910 1.74768271 0.22192162 1.19674636
[55] -0.85342423 0.12221722 -2.95789042 0.30301936 1.07903907 0.67698870
[61] -1.83684134 1.94253307 -0.54406865 -0.01728374 0.30654456 1.99364543
[67] 0.35335797 -0.98561305 0.65540662 1.06021922 0.95827312 0.26742606
[73] 1.31606462 0.23270512 -0.45694657 -0.64284684 -1.15221052 -1.36279219
[79] -0.05547535 -0.36863639 -0.47406085 1.76509164 0.05012414 -1.46161916
[85] 0.55837367 -1.13253220 -0.20623314 -0.77044263 -1.11883732 -0.49716520
[91] -0.01121951 -0.60572163 -0.38606320 2.89804583 1.19216396 -0.66504102
[97] -2.16877678 -0.92034297 -0.61239032 0.88266623
> 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] -0.87580614 -0.57617624 0.31813689 0.01854199 -0.61613299 0.74976548
[7] -0.54450768 2.40453260 -0.20748689 1.90387459 0.24213362 0.45274542
[13] 0.37415409 0.72526878 0.37668156 -1.26306264 2.22053486 0.23847307
[19] 1.93316209 1.68170094 1.76142709 0.86630873 -1.04723924 -0.74029146
[25] 1.30668657 0.48621475 0.55717236 -0.82886496 1.70488047 0.58889509
[31] -0.18300864 1.95564536 0.71196531 -0.54662650 -0.44130421 2.10265795
[37] -0.79953634 -0.79113856 0.38311002 1.33949490 0.62507859 1.15615217
[43] -1.20949625 0.73820723 -0.71200538 -0.40604690 0.46319365 -0.65250278
[49] -0.64462724 1.33784127 -0.43536910 1.74768271 0.22192162 1.19674636
[55] -0.85342423 0.12221722 -2.95789042 0.30301936 1.07903907 0.67698870
[61] -1.83684134 1.94253307 -0.54406865 -0.01728374 0.30654456 1.99364543
[67] 0.35335797 -0.98561305 0.65540662 1.06021922 0.95827312 0.26742606
[73] 1.31606462 0.23270512 -0.45694657 -0.64284684 -1.15221052 -1.36279219
[79] -0.05547535 -0.36863639 -0.47406085 1.76509164 0.05012414 -1.46161916
[85] 0.55837367 -1.13253220 -0.20623314 -0.77044263 -1.11883732 -0.49716520
[91] -0.01121951 -0.60572163 -0.38606320 2.89804583 1.19216396 -0.66504102
[97] -2.16877678 -0.92034297 -0.61239032 0.88266623
> colMin(tmp)
[1] -0.87580614 -0.57617624 0.31813689 0.01854199 -0.61613299 0.74976548
[7] -0.54450768 2.40453260 -0.20748689 1.90387459 0.24213362 0.45274542
[13] 0.37415409 0.72526878 0.37668156 -1.26306264 2.22053486 0.23847307
[19] 1.93316209 1.68170094 1.76142709 0.86630873 -1.04723924 -0.74029146
[25] 1.30668657 0.48621475 0.55717236 -0.82886496 1.70488047 0.58889509
[31] -0.18300864 1.95564536 0.71196531 -0.54662650 -0.44130421 2.10265795
[37] -0.79953634 -0.79113856 0.38311002 1.33949490 0.62507859 1.15615217
[43] -1.20949625 0.73820723 -0.71200538 -0.40604690 0.46319365 -0.65250278
[49] -0.64462724 1.33784127 -0.43536910 1.74768271 0.22192162 1.19674636
[55] -0.85342423 0.12221722 -2.95789042 0.30301936 1.07903907 0.67698870
[61] -1.83684134 1.94253307 -0.54406865 -0.01728374 0.30654456 1.99364543
[67] 0.35335797 -0.98561305 0.65540662 1.06021922 0.95827312 0.26742606
[73] 1.31606462 0.23270512 -0.45694657 -0.64284684 -1.15221052 -1.36279219
[79] -0.05547535 -0.36863639 -0.47406085 1.76509164 0.05012414 -1.46161916
[85] 0.55837367 -1.13253220 -0.20623314 -0.77044263 -1.11883732 -0.49716520
[91] -0.01121951 -0.60572163 -0.38606320 2.89804583 1.19216396 -0.66504102
[97] -2.16877678 -0.92034297 -0.61239032 0.88266623
> colMedians(tmp)
[1] -0.87580614 -0.57617624 0.31813689 0.01854199 -0.61613299 0.74976548
[7] -0.54450768 2.40453260 -0.20748689 1.90387459 0.24213362 0.45274542
[13] 0.37415409 0.72526878 0.37668156 -1.26306264 2.22053486 0.23847307
[19] 1.93316209 1.68170094 1.76142709 0.86630873 -1.04723924 -0.74029146
[25] 1.30668657 0.48621475 0.55717236 -0.82886496 1.70488047 0.58889509
[31] -0.18300864 1.95564536 0.71196531 -0.54662650 -0.44130421 2.10265795
[37] -0.79953634 -0.79113856 0.38311002 1.33949490 0.62507859 1.15615217
[43] -1.20949625 0.73820723 -0.71200538 -0.40604690 0.46319365 -0.65250278
[49] -0.64462724 1.33784127 -0.43536910 1.74768271 0.22192162 1.19674636
[55] -0.85342423 0.12221722 -2.95789042 0.30301936 1.07903907 0.67698870
[61] -1.83684134 1.94253307 -0.54406865 -0.01728374 0.30654456 1.99364543
[67] 0.35335797 -0.98561305 0.65540662 1.06021922 0.95827312 0.26742606
[73] 1.31606462 0.23270512 -0.45694657 -0.64284684 -1.15221052 -1.36279219
[79] -0.05547535 -0.36863639 -0.47406085 1.76509164 0.05012414 -1.46161916
[85] 0.55837367 -1.13253220 -0.20623314 -0.77044263 -1.11883732 -0.49716520
[91] -0.01121951 -0.60572163 -0.38606320 2.89804583 1.19216396 -0.66504102
[97] -2.16877678 -0.92034297 -0.61239032 0.88266623
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.8758061 -0.5761762 0.3181369 0.01854199 -0.616133 0.7497655 -0.5445077
[2,] -0.8758061 -0.5761762 0.3181369 0.01854199 -0.616133 0.7497655 -0.5445077
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 2.404533 -0.2074869 1.903875 0.2421336 0.4527454 0.3741541 0.7252688
[2,] 2.404533 -0.2074869 1.903875 0.2421336 0.4527454 0.3741541 0.7252688
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.3766816 -1.263063 2.220535 0.2384731 1.933162 1.681701 1.761427
[2,] 0.3766816 -1.263063 2.220535 0.2384731 1.933162 1.681701 1.761427
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.8663087 -1.047239 -0.7402915 1.306687 0.4862148 0.5571724 -0.828865
[2,] 0.8663087 -1.047239 -0.7402915 1.306687 0.4862148 0.5571724 -0.828865
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.70488 0.5888951 -0.1830086 1.955645 0.7119653 -0.5466265 -0.4413042
[2,] 1.70488 0.5888951 -0.1830086 1.955645 0.7119653 -0.5466265 -0.4413042
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 2.102658 -0.7995363 -0.7911386 0.38311 1.339495 0.6250786 1.156152
[2,] 2.102658 -0.7995363 -0.7911386 0.38311 1.339495 0.6250786 1.156152
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.209496 0.7382072 -0.7120054 -0.4060469 0.4631937 -0.6525028 -0.6446272
[2,] -1.209496 0.7382072 -0.7120054 -0.4060469 0.4631937 -0.6525028 -0.6446272
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 1.337841 -0.4353691 1.747683 0.2219216 1.196746 -0.8534242 0.1222172
[2,] 1.337841 -0.4353691 1.747683 0.2219216 1.196746 -0.8534242 0.1222172
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -2.95789 0.3030194 1.079039 0.6769887 -1.836841 1.942533 -0.5440687
[2,] -2.95789 0.3030194 1.079039 0.6769887 -1.836841 1.942533 -0.5440687
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.01728374 0.3065446 1.993645 0.353358 -0.985613 0.6554066 1.060219
[2,] -0.01728374 0.3065446 1.993645 0.353358 -0.985613 0.6554066 1.060219
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.9582731 0.2674261 1.316065 0.2327051 -0.4569466 -0.6428468 -1.152211
[2,] 0.9582731 0.2674261 1.316065 0.2327051 -0.4569466 -0.6428468 -1.152211
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -1.362792 -0.05547535 -0.3686364 -0.4740608 1.765092 0.05012414 -1.461619
[2,] -1.362792 -0.05547535 -0.3686364 -0.4740608 1.765092 0.05012414 -1.461619
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.5583737 -1.132532 -0.2062331 -0.7704426 -1.118837 -0.4971652 -0.01121951
[2,] 0.5583737 -1.132532 -0.2062331 -0.7704426 -1.118837 -0.4971652 -0.01121951
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.6057216 -0.3860632 2.898046 1.192164 -0.665041 -2.168777 -0.920343
[2,] -0.6057216 -0.3860632 2.898046 1.192164 -0.665041 -2.168777 -0.920343
[,99] [,100]
[1,] -0.6123903 0.8826662
[2,] -0.6123903 0.8826662
>
>
> Max(tmp2)
[1] 2.007197
> Min(tmp2)
[1] -1.911931
> mean(tmp2)
[1] -0.1039279
> Sum(tmp2)
[1] -10.39279
> Var(tmp2)
[1] 0.7190201
>
> rowMeans(tmp2)
[1] 0.720622864 0.670995737 -0.401151647 -0.413652161 0.230604788
[6] 0.989870489 -0.554185885 -0.570907927 0.263699370 -1.590521361
[11] -0.146422871 -0.227035841 0.631925894 -0.108198344 -0.238955347
[16] -0.314888595 -0.851669004 0.007217767 0.836161580 -1.530371028
[21] 0.520866898 0.012069285 0.049163131 0.236961156 -0.307373742
[26] -0.711468530 -0.585090755 0.514355477 1.115010393 -0.081899979
[31] -0.353070454 2.007197428 -0.352485202 1.255159367 0.247498385
[36] -1.911930815 0.624407064 -1.477955190 -0.475533821 0.721904164
[41] 0.655695067 -0.761257980 -1.112646397 0.304741188 -0.199883834
[46] 0.519596176 -1.605407740 -0.936399059 -0.876997353 -0.562755549
[51] 1.290612862 0.008788104 -0.889306944 0.199236880 -0.638056241
[56] -1.046783459 -0.340249129 0.133440406 0.818899483 -0.111179344
[61] 1.471021525 -0.004190175 -0.842863886 -0.279640964 -0.630133392
[66] -0.682537878 -0.759449347 1.398078992 1.749497205 1.041931982
[71] 1.497670146 0.242846924 -0.351087542 -0.102426071 -0.924992111
[76] -1.758505236 0.632872236 -1.108991596 -0.434905698 -0.381550060
[81] 1.064022444 0.640360672 -0.473779139 -0.805890909 1.948334660
[86] -0.230811977 -0.236297010 0.225043029 -0.076437185 0.734058054
[91] 0.129209346 1.037871312 -0.840468638 -1.319594994 -0.914241565
[96] -0.568711675 -0.395804499 -1.326817437 -0.790290461 -1.266194511
> rowSums(tmp2)
[1] 0.720622864 0.670995737 -0.401151647 -0.413652161 0.230604788
[6] 0.989870489 -0.554185885 -0.570907927 0.263699370 -1.590521361
[11] -0.146422871 -0.227035841 0.631925894 -0.108198344 -0.238955347
[16] -0.314888595 -0.851669004 0.007217767 0.836161580 -1.530371028
[21] 0.520866898 0.012069285 0.049163131 0.236961156 -0.307373742
[26] -0.711468530 -0.585090755 0.514355477 1.115010393 -0.081899979
[31] -0.353070454 2.007197428 -0.352485202 1.255159367 0.247498385
[36] -1.911930815 0.624407064 -1.477955190 -0.475533821 0.721904164
[41] 0.655695067 -0.761257980 -1.112646397 0.304741188 -0.199883834
[46] 0.519596176 -1.605407740 -0.936399059 -0.876997353 -0.562755549
[51] 1.290612862 0.008788104 -0.889306944 0.199236880 -0.638056241
[56] -1.046783459 -0.340249129 0.133440406 0.818899483 -0.111179344
[61] 1.471021525 -0.004190175 -0.842863886 -0.279640964 -0.630133392
[66] -0.682537878 -0.759449347 1.398078992 1.749497205 1.041931982
[71] 1.497670146 0.242846924 -0.351087542 -0.102426071 -0.924992111
[76] -1.758505236 0.632872236 -1.108991596 -0.434905698 -0.381550060
[81] 1.064022444 0.640360672 -0.473779139 -0.805890909 1.948334660
[86] -0.230811977 -0.236297010 0.225043029 -0.076437185 0.734058054
[91] 0.129209346 1.037871312 -0.840468638 -1.319594994 -0.914241565
[96] -0.568711675 -0.395804499 -1.326817437 -0.790290461 -1.266194511
> 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] 0.720622864 0.670995737 -0.401151647 -0.413652161 0.230604788
[6] 0.989870489 -0.554185885 -0.570907927 0.263699370 -1.590521361
[11] -0.146422871 -0.227035841 0.631925894 -0.108198344 -0.238955347
[16] -0.314888595 -0.851669004 0.007217767 0.836161580 -1.530371028
[21] 0.520866898 0.012069285 0.049163131 0.236961156 -0.307373742
[26] -0.711468530 -0.585090755 0.514355477 1.115010393 -0.081899979
[31] -0.353070454 2.007197428 -0.352485202 1.255159367 0.247498385
[36] -1.911930815 0.624407064 -1.477955190 -0.475533821 0.721904164
[41] 0.655695067 -0.761257980 -1.112646397 0.304741188 -0.199883834
[46] 0.519596176 -1.605407740 -0.936399059 -0.876997353 -0.562755549
[51] 1.290612862 0.008788104 -0.889306944 0.199236880 -0.638056241
[56] -1.046783459 -0.340249129 0.133440406 0.818899483 -0.111179344
[61] 1.471021525 -0.004190175 -0.842863886 -0.279640964 -0.630133392
[66] -0.682537878 -0.759449347 1.398078992 1.749497205 1.041931982
[71] 1.497670146 0.242846924 -0.351087542 -0.102426071 -0.924992111
[76] -1.758505236 0.632872236 -1.108991596 -0.434905698 -0.381550060
[81] 1.064022444 0.640360672 -0.473779139 -0.805890909 1.948334660
[86] -0.230811977 -0.236297010 0.225043029 -0.076437185 0.734058054
[91] 0.129209346 1.037871312 -0.840468638 -1.319594994 -0.914241565
[96] -0.568711675 -0.395804499 -1.326817437 -0.790290461 -1.266194511
> rowMin(tmp2)
[1] 0.720622864 0.670995737 -0.401151647 -0.413652161 0.230604788
[6] 0.989870489 -0.554185885 -0.570907927 0.263699370 -1.590521361
[11] -0.146422871 -0.227035841 0.631925894 -0.108198344 -0.238955347
[16] -0.314888595 -0.851669004 0.007217767 0.836161580 -1.530371028
[21] 0.520866898 0.012069285 0.049163131 0.236961156 -0.307373742
[26] -0.711468530 -0.585090755 0.514355477 1.115010393 -0.081899979
[31] -0.353070454 2.007197428 -0.352485202 1.255159367 0.247498385
[36] -1.911930815 0.624407064 -1.477955190 -0.475533821 0.721904164
[41] 0.655695067 -0.761257980 -1.112646397 0.304741188 -0.199883834
[46] 0.519596176 -1.605407740 -0.936399059 -0.876997353 -0.562755549
[51] 1.290612862 0.008788104 -0.889306944 0.199236880 -0.638056241
[56] -1.046783459 -0.340249129 0.133440406 0.818899483 -0.111179344
[61] 1.471021525 -0.004190175 -0.842863886 -0.279640964 -0.630133392
[66] -0.682537878 -0.759449347 1.398078992 1.749497205 1.041931982
[71] 1.497670146 0.242846924 -0.351087542 -0.102426071 -0.924992111
[76] -1.758505236 0.632872236 -1.108991596 -0.434905698 -0.381550060
[81] 1.064022444 0.640360672 -0.473779139 -0.805890909 1.948334660
[86] -0.230811977 -0.236297010 0.225043029 -0.076437185 0.734058054
[91] 0.129209346 1.037871312 -0.840468638 -1.319594994 -0.914241565
[96] -0.568711675 -0.395804499 -1.326817437 -0.790290461 -1.266194511
>
> colMeans(tmp2)
[1] -0.1039279
> colSums(tmp2)
[1] -10.39279
> colVars(tmp2)
[1] 0.7190201
> colSd(tmp2)
[1] 0.8479505
> colMax(tmp2)
[1] 2.007197
> colMin(tmp2)
[1] -1.911931
> colMedians(tmp2)
[1] -0.2289239
> colRanges(tmp2)
[,1]
[1,] -1.911931
[2,] 2.007197
>
> 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] 1.015225 1.549149 5.965775 -4.549146 -1.474171 -0.192928 4.346110
[8] -3.927250 -2.998784 4.437890
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.6428483
[2,] -0.6583455
[3,] 0.2568018
[4,] 0.9292599
[5,] 1.6193544
>
> rowApply(tmp,sum)
[1] 5.4946693 4.4963842 -2.4986475 -3.3218941 -0.5237355 -4.0479298
[7] -3.2122829 2.1326027 8.8004857 -3.1477834
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 6 5 3 10 4 1 5 4 10
[2,] 9 5 9 5 9 8 3 6 1 4
[3,] 6 10 3 8 7 9 6 10 6 9
[4,] 3 7 1 2 1 1 2 9 8 7
[5,] 5 3 7 6 3 6 4 7 2 6
[6,] 8 1 6 4 5 3 7 8 9 5
[7,] 2 2 8 7 6 10 8 4 10 8
[8,] 4 9 2 9 2 2 5 3 3 1
[9,] 1 4 4 1 4 5 9 2 5 2
[10,] 7 8 10 10 8 7 10 1 7 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.4158162 2.4354836 0.5783760 2.4188316 3.7694038 1.4850356
[7] -3.2188346 3.7374332 1.9881823 1.2655105 -2.1696732 -1.4636133
[13] 0.7691724 1.4872672 -1.3718514 -0.2089207 -1.0692872 -1.5413140
[19] -2.0261020 -0.1223338
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.74226739
[2,] -1.41943308
[3,] -0.01687566
[4,] 0.08658424
[5,] 1.67617570
>
> rowApply(tmp,sum)
[1] 2.3970879 -0.5690914 1.2495634 -0.5408236 2.7902137
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 11 4 19 2 11
[2,] 17 8 10 19 16
[3,] 7 11 2 10 20
[4,] 9 17 13 17 15
[5,] 12 13 18 20 13
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.01687566 1.004590681 -0.36047833 -0.2941707 0.03953415 -0.7895078
[2,] -1.74226739 -0.128156601 0.20492092 1.0188203 0.47445198 0.5450981
[3,] 1.67617570 0.005916118 -1.74850777 0.2393284 1.60702811 0.8682926
[4,] -1.41943308 0.802586750 0.02118541 0.7197680 1.23556799 -0.2938281
[5,] 0.08658424 0.750546675 2.46125582 0.7350855 0.41282160 1.1549807
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -2.1673049 0.79014446 1.0508263 0.5832760 -0.3090173 1.5391798
[2,] 0.8533449 2.63930631 1.9069797 -0.4611811 -2.6407037 -2.2938097
[3,] -0.5324462 -0.05794174 -0.5085974 1.5822363 0.3136155 -0.7908843
[4,] -0.5575236 0.17523031 0.3116670 0.4970439 0.7762637 -0.9755266
[5,] -0.8149048 0.19069382 -0.7726934 -0.9358645 -0.3098314 1.0574276
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 2.2834074 -0.5106750 0.42351523 -0.16246752 -0.6295713 -0.50264508
[2,] -1.7590932 0.6335410 -0.09779503 -0.64566047 1.0393266 -0.08019732
[3,] 1.7415940 -0.3182156 -1.75325807 0.04077210 0.5735568 -0.58003361
[4,] -0.6381417 -0.3966727 0.13729515 0.02070829 -1.4991806 0.60612331
[5,] -0.8585942 2.0792895 -0.08160866 0.53772689 -0.5534186 -0.98456136
[,19] [,20]
[1,] -0.5120231 0.93735069
[2,] 0.3275391 -0.36355583
[3,] 0.2070891 -1.31615683
[4,] -0.6298677 0.56591064
[5,] -1.4188394 0.05411754
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.8 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-3.9-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 631 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 547 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.8 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 1.215101 0.565755 -0.7485253 -1.368808 3.631666 0.9291274 0.6812602
col8 col9 col10 col11 col12 col13 col14
row1 -0.4878459 -1.549651 0.2378886 0.6529027 1.159608 1.049799 -0.03844412
col15 col16 col17 col18 col19 col20
row1 1.337015 -0.7084791 0.4738634 0.7482714 -0.5701183 -1.245833
> tmp[,"col10"]
col10
row1 0.2378886
row2 1.6525975
row3 0.3597993
row4 2.1415353
row5 -0.1498462
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.215101 0.56575497 -0.7485253 -1.3688083 3.631666 0.9291274 0.6812602
row5 0.534946 -0.01735794 1.2945834 -0.6724845 1.442024 0.2237151 -0.7645207
col8 col9 col10 col11 col12 col13
row1 -0.4878459 -1.5496514 0.2378886 0.6529027 1.1596078 1.0497992
row5 0.1825307 -0.9414998 -0.1498462 -2.1774655 0.6482932 0.9160959
col14 col15 col16 col17 col18 col19
row1 -0.03844412 1.3370146 -0.7084791 0.4738634 0.74827137 -0.5701183
row5 0.47387916 0.1655164 1.8529517 0.6158661 -0.04376376 -0.8364838
col20
row1 -1.2458325
row5 0.4283522
> tmp[,c("col6","col20")]
col6 col20
row1 0.9291274 -1.2458325
row2 -0.7604898 -0.2997866
row3 1.2483629 0.1500262
row4 0.2409291 -0.5505318
row5 0.2237151 0.4283522
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.9291274 -1.2458325
row5 0.2237151 0.4283522
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.36612 49.59025 50.74993 51.09344 51.82627 104.2301 49.60528 48.95262
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.49952 50.74423 48.46674 49.19152 48.38966 49.23538 48.07787 50.6493
col17 col18 col19 col20
row1 50.15542 49.89194 50.57008 104.813
> tmp[,"col10"]
col10
row1 50.74423
row2 30.86723
row3 30.29624
row4 29.41159
row5 48.30044
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.36612 49.59025 50.74993 51.09344 51.82627 104.2301 49.60528 48.95262
row5 50.16394 50.77413 49.36667 51.06468 50.74358 104.4643 49.95755 48.64601
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.49952 50.74423 48.46674 49.19152 48.38966 49.23538 48.07787 50.6493
row5 50.90329 48.30044 53.03248 50.11609 50.35018 49.87032 49.85437 48.7613
col17 col18 col19 col20
row1 50.15542 49.89194 50.57008 104.813
row5 49.43137 50.10952 50.77213 104.103
> tmp[,c("col6","col20")]
col6 col20
row1 104.23012 104.81302
row2 74.93316 75.98624
row3 75.99755 74.28958
row4 74.94155 75.52532
row5 104.46429 104.10298
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.2301 104.813
row5 104.4643 104.103
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.2301 104.813
row5 104.4643 104.103
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.0703519
[2,] -0.9983591
[3,] 1.0835026
[4,] 1.7279388
[5,] 0.3718186
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.22327636 0.7318607
[2,] -1.53822888 -0.9555203
[3,] -0.33595056 -1.0417958
[4,] -0.56770080 -0.4303123
[5,] 0.05539802 -1.0655746
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -2.2845691 0.483035543
[2,] -1.0747893 -0.636377076
[3,] -0.6327408 0.003314354
[4,] -0.2465585 0.662287731
[5,] -0.6000832 0.388251566
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -2.284569
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -2.284569
[2,] -1.074789
>
>
>
> 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 1.2594249 -0.5148894 -2.0702653 -0.1267661 -1.856810 -0.3980276 0.1948698
row1 0.9984306 -0.6351132 0.8624412 0.7076202 2.593364 -0.1049648 0.2962113
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -0.8030661 -0.798124 0.8443972 1.490000 -1.1885043 0.72954384 2.232302
row1 0.1507134 1.858705 -0.8043377 1.399742 -0.1026796 0.02630805 1.339956
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.6703168 -1.153475 -0.8770311 -0.1949876 -0.4986131 -1.3997940
row1 -0.3435061 -0.726937 -0.9286588 3.1580218 2.1840804 -0.4453285
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.809727 1.165252 -0.394022 -1.230976 -0.006994381 -0.01086769 0.3682717
[,8] [,9] [,10]
row2 0.855629 0.236024 -0.3604105
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.7488302 1.775546 0.01338494 -2.142486 1.144449 0.05672027 -0.4081914
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.010847 -0.6427123 -0.3853149 -0.5644911 0.564494 -2.44015 -0.38177
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.5750133 0.3439617 -1.012511 -0.4714238 -0.04771581 0.4262016
>
>
> 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)
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BMd8171d4981"
[2] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BMd817130048c"
[3] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BMd816b9071c0"
[4] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BMd814d892c9d"
[5] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BMd81177bc71b"
[6] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BMd814de1f456"
[7] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BMd815c810468"
[8] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BMd812bd6eb1e"
[9] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BMd8113d267f"
[10] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BMd81a8660bb"
[11] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BMd81ba1a44f"
[12] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BMd816690df34"
[13] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BMd8137d03977"
[14] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BMd8117fa63a5"
[15] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BMd81378ea754"
>
>
> ### 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)
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
> rowMedians(tmp)
[1] -0.575465586 -0.600542044 0.092038817 0.150931265 0.208827859
[6] -0.193260358 -0.225130101 -0.106672147 -0.237417222 -0.070249533
[11] 0.009290566 -0.215928627 0.051242653 0.455416850 0.179676893
[16] 0.393281702 -0.155304370 0.249988663 -0.171744400 0.098529776
[21] 0.066151498 -0.611747130 0.293043895 0.250451400 0.281531767
[26] 0.531033816 -0.297553503 0.209149693 0.226589567 0.416546596
[31] -0.473659977 0.143860673 -0.078770144 0.397477561 -0.297841428
[36] 0.202842589 -0.250817303 -0.094577761 -0.437264773 0.203651781
[41] -0.163961658 0.060579088 0.127925152 -0.065290029 -0.305864900
[46] 0.026983039 0.485905268 -0.453117024 0.434376946 0.438419285
[51] -0.537621789 0.275805750 0.345618518 0.209791169 0.431323745
[56] -0.024286007 0.290567777 0.075874494 0.252370156 -0.818104682
[61] 0.312151032 -0.737824773 0.374994238 -0.591749169 0.136966045
[66] 0.260438386 0.125998905 -0.069556572 0.498281443 -0.454006763
[71] -0.078726958 0.701381769 -0.426540517 0.112931346 0.068224716
[76] 0.405368362 -0.100878565 0.091414868 -0.077318737 0.037102815
[81] -0.321838380 -0.054251664 0.048794490 -0.339847838 -0.240993625
[86] -0.246508670 0.115097053 -0.617590837 0.273952137 0.678292929
[91] -0.340448529 -0.494181510 0.272056673 -0.400427647 -0.347570154
[96] -0.196184100 0.116846019 -0.176844003 -0.616160391 0.122973206
[101] 0.101304797 0.079842069 0.366360800 -0.374122121 0.057982939
[106] -0.034267153 -0.036775192 -0.432836247 -0.057425414 -0.336163322
[111] -0.355253698 0.088624208 -0.011264286 0.166121648 -0.502283745
[116] 0.067824253 0.287869667 0.344873867 -0.353332791 -0.433261592
[121] -0.803804310 0.163968082 0.507082316 0.412920580 0.095784202
[126] -0.223961159 0.162755548 0.331312763 -0.310252714 0.464391882
[131] -0.040410136 -0.191618941 0.290690605 0.033801904 0.019077867
[136] -0.054058083 0.058296977 -0.221381057 0.050580924 0.050592913
[141] -0.360816798 0.448029826 -0.097253341 -0.303325424 -0.025948432
[146] -0.099011726 0.016522638 -0.048151531 -0.070600968 -0.250733464
[151] -0.483551799 -0.171123517 -0.367896573 0.636508819 -0.392724524
[156] -0.445654439 0.055396323 0.074669564 0.425131170 0.166404872
[161] 0.858755478 0.129889976 0.063559342 0.284098174 0.574659806
[166] 0.275087822 -0.728972898 -0.396416753 -0.197075741 -0.331525667
[171] -0.391516404 0.216250905 -0.140580214 -0.196495482 0.056925921
[176] -0.018087949 0.137735945 0.116210154 0.269934476 0.313203438
[181] -0.058766970 -0.542709373 0.435914316 0.234723148 0.242951380
[186] 0.430408982 -0.135964456 0.293630506 0.813653188 -0.469784950
[191] -0.196874327 0.173277000 -0.292481113 -0.308971983 -0.475613439
[196] 0.316490380 0.608747618 -0.349102502 -0.155334541 0.126802988
[201] 0.305532226 0.076026979 0.002657199 0.455579513 0.723081173
[206] -0.189705928 -0.244594248 0.095401573 -0.154513964 0.128335873
[211] -0.440673618 -0.187000967 0.566693179 0.263166044 -0.368931926
[216] 0.282071298 -0.117128013 0.429446464 -0.242440956 0.207015149
[221] -0.143088045 -0.418672288 0.145209052 -0.004776312 -0.134084811
[226] -0.086568201 0.164490534 0.453576121 -0.088251865 -0.771328401
>
> proc.time()
user system elapsed
2.269 1.045 3.395
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 3.6.1 (2019-07-05) -- "Action of the Toes"
Copyright (C) 2019 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
> .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
> .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
> .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
> 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
> .Call("R_bm_AddColumn",P)
> .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
> .Call("R_bm_AddColumn",P)
> .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
> rm(P)
>
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,5)
[1] TRUE
> .Call("R_bm_AddColumn",P)
> .Call("R_bm_AddColumn",P)
> .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
>
> .Call("R_bm_ResizeBuffer",P,5,5)
> .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
>
> .Call("R_bm_RowMode",P)
> .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
>
> .Call("R_bm_ColMode",P)
> .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
> rm(P)
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
> .Call("R_bm_AddColumn",P)
> .Call("R_bm_AddColumn",P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile109839333170" "BufferedMatrixFile1098762a4ca5"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile109839333170" "BufferedMatrixFile1098762a4ca5"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
> .Call("R_bm_AddColumn",P)
> .Call("R_bm_ReadOnlyModeToggle",P)
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
> .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)
> .Call("R_bm_AddColumn",P)
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
> 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
> .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
> rm(P)
>
> proc.time()
user system elapsed
0.251 0.030 0.265
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 3.6.1 (2019-07-05) -- "Action of the Toes"
Copyright (C) 2019 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
0.375 0.051 0.411