Ben Bolstad
| Snapshot Date: 2021-05-05 14:51:38 -0400 (Wed, 05 May 2021) |
| URL: https://git.bioconductor.org/packages/BufferedMatrix |
| Branch: RELEASE_3_12 |
| Last Commit: eae3841 |
| Last Changed Date: 2020-10-27 10:30:14 -0400 (Tue, 27 Oct 2020) |
| Back to Multiple platform build/check report for BioC 3.12 |
|
This page was generated on 2021-05-06 12:27:02 -0400 (Thu, 06 May 2021).
|
To the developers/maintainers of the BufferedMatrix package: Please make sure to use the following settings in order to reproduce any error or warning you see on this page. |
| Package 215/1974 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.54.0 (landing page) Ben Bolstad
| malbec1 | Linux (Ubuntu 18.04.5 LTS) / x86_64 | OK | OK | OK | | ||||||||
| tokay1 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 10.14.6 Mojave / x86_64 | OK | OK | OK | OK | | ||||||||
| Package: BufferedMatrix |
| Version: 1.54.0 |
| Command: /home/biocbuild/bbs-3.12-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.12-bioc/R/library --no-vignettes --timings BufferedMatrix_1.54.0.tar.gz |
| StartedAt: 2021-05-05 23:38:58 -0400 (Wed, 05 May 2021) |
| EndedAt: 2021-05-05 23:39:23 -0400 (Wed, 05 May 2021) |
| EllapsedTime: 25.3 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.12-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.12-bioc/R/library --no-vignettes --timings BufferedMatrix_1.54.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck’ * using R version 4.0.5 (2021-03-31) * 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 ‘1.54.0’ * 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-3.12-bioc/meat/BufferedMatrix.Rcheck/00check.log’ for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.12-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.12-bioc/R/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
gcc -I"/home/biocbuild/bbs-3.12-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.12-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-3.12-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-3.12-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-3.12-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-3.12-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.12-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 4.0.5 (2021-03-31) -- "Shake and Throw"
Copyright (C) 2021 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
0.440 0.040 0.477
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.0.5 (2021-03-31) -- "Shake and Throw"
Copyright (C) 2021 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-3.12-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 438446 23.5 927717 49.6 649971 34.8
Vcells 788872 6.1 8388608 64.0 2015373 15.4
>
>
>
>
> ##
> ## 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 May 5 23:39:17 2021"
> 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 May 5 23:39:17 2021"
>
>
> 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: 0x561a94139f00>
>
>
>
> 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 May 5 23:39:18 2021"
> 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 May 5 23:39:18 2021"
>
> ColMode(tmp2)
<pointer: 0x561a94139f00>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.3463174 -0.5097277 -0.7591917 0.52807592
[2,] -0.6333747 0.4449361 -0.2222271 -0.57566884
[3,] 0.6617167 0.5970811 -0.1397774 -1.60483090
[4,] 1.2677289 -1.2049985 0.6007691 -0.08837716
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.12-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,] 100.3463174 0.5097277 0.7591917 0.52807592
[2,] 0.6333747 0.4449361 0.2222271 0.57566884
[3,] 0.6617167 0.5970811 0.1397774 1.60483090
[4,] 1.2677289 1.2049985 0.6007691 0.08837716
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.12-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,] 10.0173009 0.7139522 0.8713161 0.7266883
[2,] 0.7958484 0.6670353 0.4714097 0.7587284
[3,] 0.8134597 0.7727103 0.3738682 1.2668192
[4,] 1.1259347 1.0977242 0.7750930 0.2972830
>
> 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-3.12-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,] 225.51933 32.64925 34.47235 32.79496
[2,] 33.59186 32.11529 29.93632 33.16295
[3,] 33.79631 33.32418 28.87846 39.27302
[4,] 37.52708 37.18224 33.35170 28.06121
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x561a93f66e70>
> exp(tmp5)
<pointer: 0x561a93f66e70>
> log(tmp5,2)
<pointer: 0x561a93f66e70>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.3889
> Min(tmp5)
[1] 52.7603
> mean(tmp5)
[1] 72.23519
> Sum(tmp5)
[1] 14447.04
> Var(tmp5)
[1] 867.0992
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.89044 69.38888 69.96788 71.55318 69.41589 68.77576 73.44891 68.08200
[9] 67.19968 73.62931
> rowSums(tmp5)
[1] 1817.809 1387.778 1399.358 1431.064 1388.318 1375.515 1468.978 1361.640
[9] 1343.994 1472.586
> rowVars(tmp5)
[1] 8002.22697 61.14877 74.80901 60.17360 86.07922 67.62531
[7] 61.59448 69.31507 89.17374 59.40463
> rowSd(tmp5)
[1] 89.455167 7.819768 8.649220 7.757164 9.277889 8.223461 7.848215
[8] 8.325568 9.443185 7.707440
> rowMax(tmp5)
[1] 469.38893 85.25760 86.23847 84.48052 89.81589 86.60382 84.79949
[8] 85.02522 88.48742 88.51181
> rowMin(tmp5)
[1] 57.66136 57.84884 56.53265 55.35690 52.76030 58.21392 59.49819 55.94062
[9] 53.92803 60.60860
>
> colMeans(tmp5)
[1] 110.61001 67.77073 68.38789 68.65453 67.24951 72.06714 74.58763
[8] 67.70344 71.62026 68.21568 71.15598 71.08537 67.89337 72.29327
[15] 71.31063 72.94705 68.48561 69.87194 72.04430 70.74952
> colSums(tmp5)
[1] 1106.1001 677.7073 683.8789 686.5453 672.4951 720.6714 745.8763
[8] 677.0344 716.2026 682.1568 711.5598 710.8537 678.9337 722.9327
[15] 713.1063 729.4705 684.8561 698.7194 720.4430 707.4952
> colVars(tmp5)
[1] 15912.05137 83.88086 63.71335 68.20528 61.44620 120.15189
[7] 69.41486 37.93911 83.01817 38.88286 95.85996 58.64062
[13] 78.07577 91.54339 98.70555 94.93349 68.49764 106.99635
[19] 75.01559 51.92938
> colSd(tmp5)
[1] 126.142980 9.158650 7.982064 8.258649 7.838763 10.961382
[7] 8.331558 6.159473 9.111431 6.235613 9.790810 7.657716
[13] 8.836049 9.567831 9.935067 9.743382 8.276330 10.343904
[19] 8.661154 7.206204
> colMax(tmp5)
[1] 469.38893 82.68801 84.04702 81.74165 77.82030 89.96725 86.23847
[8] 74.48301 83.36630 77.76764 88.51181 85.58353 82.11095 84.79949
[15] 86.60382 85.02522 85.25760 88.48742 84.42988 81.46743
> colMin(tmp5)
[1] 64.15450 55.98993 59.54164 58.40573 56.01169 55.94062 62.54449 58.75797
[9] 56.53265 55.76673 56.78988 63.31762 53.92803 55.35690 60.41616 52.76030
[17] 60.14803 58.16867 60.60860 60.55735
>
>
> ### 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] 90.89044 69.38888 69.96788 71.55318 69.41589 68.77576 73.44891 68.08200
[9] NA 73.62931
> rowSums(tmp5)
[1] 1817.809 1387.778 1399.358 1431.064 1388.318 1375.515 1468.978 1361.640
[9] NA 1472.586
> rowVars(tmp5)
[1] 8002.22697 61.14877 74.80901 60.17360 86.07922 67.62531
[7] 61.59448 69.31507 90.69827 59.40463
> rowSd(tmp5)
[1] 89.455167 7.819768 8.649220 7.757164 9.277889 8.223461 7.848215
[8] 8.325568 9.523564 7.707440
> rowMax(tmp5)
[1] 469.38893 85.25760 86.23847 84.48052 89.81589 86.60382 84.79949
[8] 85.02522 NA 88.51181
> rowMin(tmp5)
[1] 57.66136 57.84884 56.53265 55.35690 52.76030 58.21392 59.49819 55.94062
[9] NA 60.60860
>
> colMeans(tmp5)
[1] 110.61001 67.77073 NA 68.65453 67.24951 72.06714 74.58763
[8] 67.70344 71.62026 68.21568 71.15598 71.08537 67.89337 72.29327
[15] 71.31063 72.94705 68.48561 69.87194 72.04430 70.74952
> colSums(tmp5)
[1] 1106.1001 677.7073 NA 686.5453 672.4951 720.6714 745.8763
[8] 677.0344 716.2026 682.1568 711.5598 710.8537 678.9337 722.9327
[15] 713.1063 729.4705 684.8561 698.7194 720.4430 707.4952
> colVars(tmp5)
[1] 15912.05137 83.88086 NA 68.20528 61.44620 120.15189
[7] 69.41486 37.93911 83.01817 38.88286 95.85996 58.64062
[13] 78.07577 91.54339 98.70555 94.93349 68.49764 106.99635
[19] 75.01559 51.92938
> colSd(tmp5)
[1] 126.142980 9.158650 NA 8.258649 7.838763 10.961382
[7] 8.331558 6.159473 9.111431 6.235613 9.790810 7.657716
[13] 8.836049 9.567831 9.935067 9.743382 8.276330 10.343904
[19] 8.661154 7.206204
> colMax(tmp5)
[1] 469.38893 82.68801 NA 81.74165 77.82030 89.96725 86.23847
[8] 74.48301 83.36630 77.76764 88.51181 85.58353 82.11095 84.79949
[15] 86.60382 85.02522 85.25760 88.48742 84.42988 81.46743
> colMin(tmp5)
[1] 64.15450 55.98993 NA 58.40573 56.01169 55.94062 62.54449 58.75797
[9] 56.53265 55.76673 56.78988 63.31762 53.92803 55.35690 60.41616 52.76030
[17] 60.14803 58.16867 60.60860 60.55735
>
> Max(tmp5,na.rm=TRUE)
[1] 469.3889
> Min(tmp5,na.rm=TRUE)
[1] 52.7603
> mean(tmp5,na.rm=TRUE)
[1] 72.29898
> Sum(tmp5,na.rm=TRUE)
[1] 14387.5
> Var(tmp5,na.rm=TRUE)
[1] 870.6606
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.89044 69.38888 69.96788 71.55318 69.41589 68.77576 73.44891 68.08200
[9] 67.60273 73.62931
> rowSums(tmp5,na.rm=TRUE)
[1] 1817.809 1387.778 1399.358 1431.064 1388.318 1375.515 1468.978 1361.640
[9] 1284.452 1472.586
> rowVars(tmp5,na.rm=TRUE)
[1] 8002.22697 61.14877 74.80901 60.17360 86.07922 67.62531
[7] 61.59448 69.31507 90.69827 59.40463
> rowSd(tmp5,na.rm=TRUE)
[1] 89.455167 7.819768 8.649220 7.757164 9.277889 8.223461 7.848215
[8] 8.325568 9.523564 7.707440
> rowMax(tmp5,na.rm=TRUE)
[1] 469.38893 85.25760 86.23847 84.48052 89.81589 86.60382 84.79949
[8] 85.02522 88.48742 88.51181
> rowMin(tmp5,na.rm=TRUE)
[1] 57.66136 57.84884 56.53265 55.35690 52.76030 58.21392 59.49819 55.94062
[9] 53.92803 60.60860
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.61001 67.77073 69.37081 68.65453 67.24951 72.06714 74.58763
[8] 67.70344 71.62026 68.21568 71.15598 71.08537 67.89337 72.29327
[15] 71.31063 72.94705 68.48561 69.87194 72.04430 70.74952
> colSums(tmp5,na.rm=TRUE)
[1] 1106.1001 677.7073 624.3373 686.5453 672.4951 720.6714 745.8763
[8] 677.0344 716.2026 682.1568 711.5598 710.8537 678.9337 722.9327
[15] 713.1063 729.4705 684.8561 698.7194 720.4430 707.4952
> colVars(tmp5,na.rm=TRUE)
[1] 15912.05137 83.88086 60.80861 68.20528 61.44620 120.15189
[7] 69.41486 37.93911 83.01817 38.88286 95.85996 58.64062
[13] 78.07577 91.54339 98.70555 94.93349 68.49764 106.99635
[19] 75.01559 51.92938
> colSd(tmp5,na.rm=TRUE)
[1] 126.142980 9.158650 7.797988 8.258649 7.838763 10.961382
[7] 8.331558 6.159473 9.111431 6.235613 9.790810 7.657716
[13] 8.836049 9.567831 9.935067 9.743382 8.276330 10.343904
[19] 8.661154 7.206204
> colMax(tmp5,na.rm=TRUE)
[1] 469.38893 82.68801 84.04702 81.74165 77.82030 89.96725 86.23847
[8] 74.48301 83.36630 77.76764 88.51181 85.58353 82.11095 84.79949
[15] 86.60382 85.02522 85.25760 88.48742 84.42988 81.46743
> colMin(tmp5,na.rm=TRUE)
[1] 64.15450 55.98993 60.10673 58.40573 56.01169 55.94062 62.54449 58.75797
[9] 56.53265 55.76673 56.78988 63.31762 53.92803 55.35690 60.41616 52.76030
[17] 60.14803 58.16867 60.60860 60.55735
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.89044 69.38888 69.96788 71.55318 69.41589 68.77576 73.44891 68.08200
[9] NaN 73.62931
> rowSums(tmp5,na.rm=TRUE)
[1] 1817.809 1387.778 1399.358 1431.064 1388.318 1375.515 1468.978 1361.640
[9] 0.000 1472.586
> rowVars(tmp5,na.rm=TRUE)
[1] 8002.22697 61.14877 74.80901 60.17360 86.07922 67.62531
[7] 61.59448 69.31507 NA 59.40463
> rowSd(tmp5,na.rm=TRUE)
[1] 89.455167 7.819768 8.649220 7.757164 9.277889 8.223461 7.848215
[8] 8.325568 NA 7.707440
> rowMax(tmp5,na.rm=TRUE)
[1] 469.38893 85.25760 86.23847 84.48052 89.81589 86.60382 84.79949
[8] 85.02522 NA 88.51181
> rowMin(tmp5,na.rm=TRUE)
[1] 57.66136 57.84884 56.53265 55.35690 52.76030 58.21392 59.49819 55.94062
[9] NA 60.60860
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.39225 69.00169 NaN 69.76765 68.49816 71.98654 75.66591
[8] 68.11259 71.21008 68.38327 70.39378 71.43725 69.44507 72.14473
[15] 72.44676 74.34697 69.41201 67.80356 72.51618 69.55864
> colSums(tmp5,na.rm=TRUE)
[1] 1029.5302 621.0152 0.0000 627.9089 616.4834 647.8789 680.9932
[8] 613.0133 640.8907 615.4494 633.5440 642.9352 625.0057 649.3026
[15] 652.0209 669.1227 624.7081 610.2320 652.6456 626.0277
> colVars(tmp5,na.rm=TRUE)
[1] 17740.12246 77.31913 NA 62.79162 51.58688 135.09780
[7] 65.01147 40.79821 91.50266 43.42723 101.30672 64.57772
[13] 60.74764 102.73808 96.52233 84.75285 67.40495 72.24088
[19] 81.88756 42.46587
> colSd(tmp5,na.rm=TRUE)
[1] 133.192051 8.793129 NA 7.924116 7.182400 11.623158
[7] 8.062969 6.387348 9.565702 6.589934 10.065124 8.036026
[13] 7.794077 10.135980 9.824578 9.206131 8.210052 8.499463
[19] 9.049175 6.516584
> colMax(tmp5,na.rm=TRUE)
[1] 469.38893 82.68801 -Inf 81.74165 77.82030 89.96725 86.23847
[8] 74.48301 83.36630 77.76764 88.51181 85.58353 82.11095 84.79949
[15] 86.60382 85.02522 85.25760 86.77887 84.42988 80.80028
> colMin(tmp5,na.rm=TRUE)
[1] 64.15450 55.98993 Inf 58.40573 57.66136 55.94062 62.54449 58.75797
[9] 56.53265 55.76673 56.78988 63.31762 57.84884 55.35690 60.41616 52.76030
[17] 61.28743 58.16867 60.60860 60.55735
>
>
>
>
> 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] 359.6394 324.8175 250.6337 251.1963 370.9287 144.4447 346.1090 237.1139
[9] 241.7855 495.8962
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 359.6394 324.8175 250.6337 251.1963 370.9287 144.4447 346.1090 237.1139
[9] 241.7855 495.8962
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 8.526513e-14 -1.421085e-14 5.684342e-14 0.000000e+00 1.421085e-14
[6] 2.842171e-14 7.105427e-14 -2.842171e-14 -1.136868e-13 5.684342e-14
[11] -1.705303e-13 -5.684342e-14 3.552714e-14 1.705303e-13 1.705303e-13
[16] 5.684342e-14 0.000000e+00 -5.684342e-14 5.684342e-14 -1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
9 14
7 9
1 9
9 7
7 12
2 7
3 14
3 5
7 2
9 3
4 2
6 19
4 4
5 16
7 8
10 18
9 15
6 15
6 14
10 17
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 1.956451
> Min(tmp)
[1] -2.462793
> mean(tmp)
[1] 0.03057252
> Sum(tmp)
[1] 3.057252
> Var(tmp)
[1] 0.9554403
>
> rowMeans(tmp)
[1] 0.03057252
> rowSums(tmp)
[1] 3.057252
> rowVars(tmp)
[1] 0.9554403
> rowSd(tmp)
[1] 0.9774663
> rowMax(tmp)
[1] 1.956451
> rowMin(tmp)
[1] -2.462793
>
> colMeans(tmp)
[1] 0.09672077 -1.49281514 -0.80734169 -1.29490980 -1.61334335 0.61671289
[7] -0.14002501 -0.31444453 0.89136798 1.14310829 -1.65553169 0.55296236
[13] 1.24075942 1.95645091 -0.02470280 -0.31341325 0.90577701 -1.58761794
[19] -1.50455827 -0.72026325 0.37661952 0.75732393 0.12057789 1.77896427
[25] 0.24682917 1.31468930 -0.98451414 0.24256333 0.59719657 0.43623044
[31] 0.60065192 0.28142414 -1.19107764 -0.67022725 -0.12495858 0.84064362
[37] 0.78171700 -0.51347015 0.99990983 0.49133323 1.79210204 -1.72054782
[43] -1.07850348 0.73389000 0.67149764 -0.87377146 -1.55345794 0.14109628
[49] 1.02334317 0.09995410 1.27613889 -0.12063251 -0.33296962 -1.13669521
[55] -0.12026325 1.33854279 0.18545645 -1.04583575 -0.11204903 0.13565989
[61] 0.22130274 -1.65745171 0.14291786 0.96725220 -1.14654752 0.89110115
[67] -0.58854075 0.62678402 1.38605889 1.07840608 0.37110119 0.20947740
[73] -1.61229024 -0.76044079 0.47126500 -0.34634587 -1.59880951 1.36628879
[79] -0.87523018 1.29128655 -1.11861178 -0.37262056 0.67583678 -0.13579712
[85] 0.07062978 0.02972125 0.86033336 -2.46279312 0.22896512 -1.25687483
[91] 1.17424756 -0.75435615 0.32293527 0.15833185 0.71171758 1.86823560
[97] 0.75828444 0.71876707 -1.09062004 0.61306062
> colSums(tmp)
[1] 0.09672077 -1.49281514 -0.80734169 -1.29490980 -1.61334335 0.61671289
[7] -0.14002501 -0.31444453 0.89136798 1.14310829 -1.65553169 0.55296236
[13] 1.24075942 1.95645091 -0.02470280 -0.31341325 0.90577701 -1.58761794
[19] -1.50455827 -0.72026325 0.37661952 0.75732393 0.12057789 1.77896427
[25] 0.24682917 1.31468930 -0.98451414 0.24256333 0.59719657 0.43623044
[31] 0.60065192 0.28142414 -1.19107764 -0.67022725 -0.12495858 0.84064362
[37] 0.78171700 -0.51347015 0.99990983 0.49133323 1.79210204 -1.72054782
[43] -1.07850348 0.73389000 0.67149764 -0.87377146 -1.55345794 0.14109628
[49] 1.02334317 0.09995410 1.27613889 -0.12063251 -0.33296962 -1.13669521
[55] -0.12026325 1.33854279 0.18545645 -1.04583575 -0.11204903 0.13565989
[61] 0.22130274 -1.65745171 0.14291786 0.96725220 -1.14654752 0.89110115
[67] -0.58854075 0.62678402 1.38605889 1.07840608 0.37110119 0.20947740
[73] -1.61229024 -0.76044079 0.47126500 -0.34634587 -1.59880951 1.36628879
[79] -0.87523018 1.29128655 -1.11861178 -0.37262056 0.67583678 -0.13579712
[85] 0.07062978 0.02972125 0.86033336 -2.46279312 0.22896512 -1.25687483
[91] 1.17424756 -0.75435615 0.32293527 0.15833185 0.71171758 1.86823560
[97] 0.75828444 0.71876707 -1.09062004 0.61306062
> 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] 0.09672077 -1.49281514 -0.80734169 -1.29490980 -1.61334335 0.61671289
[7] -0.14002501 -0.31444453 0.89136798 1.14310829 -1.65553169 0.55296236
[13] 1.24075942 1.95645091 -0.02470280 -0.31341325 0.90577701 -1.58761794
[19] -1.50455827 -0.72026325 0.37661952 0.75732393 0.12057789 1.77896427
[25] 0.24682917 1.31468930 -0.98451414 0.24256333 0.59719657 0.43623044
[31] 0.60065192 0.28142414 -1.19107764 -0.67022725 -0.12495858 0.84064362
[37] 0.78171700 -0.51347015 0.99990983 0.49133323 1.79210204 -1.72054782
[43] -1.07850348 0.73389000 0.67149764 -0.87377146 -1.55345794 0.14109628
[49] 1.02334317 0.09995410 1.27613889 -0.12063251 -0.33296962 -1.13669521
[55] -0.12026325 1.33854279 0.18545645 -1.04583575 -0.11204903 0.13565989
[61] 0.22130274 -1.65745171 0.14291786 0.96725220 -1.14654752 0.89110115
[67] -0.58854075 0.62678402 1.38605889 1.07840608 0.37110119 0.20947740
[73] -1.61229024 -0.76044079 0.47126500 -0.34634587 -1.59880951 1.36628879
[79] -0.87523018 1.29128655 -1.11861178 -0.37262056 0.67583678 -0.13579712
[85] 0.07062978 0.02972125 0.86033336 -2.46279312 0.22896512 -1.25687483
[91] 1.17424756 -0.75435615 0.32293527 0.15833185 0.71171758 1.86823560
[97] 0.75828444 0.71876707 -1.09062004 0.61306062
> colMin(tmp)
[1] 0.09672077 -1.49281514 -0.80734169 -1.29490980 -1.61334335 0.61671289
[7] -0.14002501 -0.31444453 0.89136798 1.14310829 -1.65553169 0.55296236
[13] 1.24075942 1.95645091 -0.02470280 -0.31341325 0.90577701 -1.58761794
[19] -1.50455827 -0.72026325 0.37661952 0.75732393 0.12057789 1.77896427
[25] 0.24682917 1.31468930 -0.98451414 0.24256333 0.59719657 0.43623044
[31] 0.60065192 0.28142414 -1.19107764 -0.67022725 -0.12495858 0.84064362
[37] 0.78171700 -0.51347015 0.99990983 0.49133323 1.79210204 -1.72054782
[43] -1.07850348 0.73389000 0.67149764 -0.87377146 -1.55345794 0.14109628
[49] 1.02334317 0.09995410 1.27613889 -0.12063251 -0.33296962 -1.13669521
[55] -0.12026325 1.33854279 0.18545645 -1.04583575 -0.11204903 0.13565989
[61] 0.22130274 -1.65745171 0.14291786 0.96725220 -1.14654752 0.89110115
[67] -0.58854075 0.62678402 1.38605889 1.07840608 0.37110119 0.20947740
[73] -1.61229024 -0.76044079 0.47126500 -0.34634587 -1.59880951 1.36628879
[79] -0.87523018 1.29128655 -1.11861178 -0.37262056 0.67583678 -0.13579712
[85] 0.07062978 0.02972125 0.86033336 -2.46279312 0.22896512 -1.25687483
[91] 1.17424756 -0.75435615 0.32293527 0.15833185 0.71171758 1.86823560
[97] 0.75828444 0.71876707 -1.09062004 0.61306062
> colMedians(tmp)
[1] 0.09672077 -1.49281514 -0.80734169 -1.29490980 -1.61334335 0.61671289
[7] -0.14002501 -0.31444453 0.89136798 1.14310829 -1.65553169 0.55296236
[13] 1.24075942 1.95645091 -0.02470280 -0.31341325 0.90577701 -1.58761794
[19] -1.50455827 -0.72026325 0.37661952 0.75732393 0.12057789 1.77896427
[25] 0.24682917 1.31468930 -0.98451414 0.24256333 0.59719657 0.43623044
[31] 0.60065192 0.28142414 -1.19107764 -0.67022725 -0.12495858 0.84064362
[37] 0.78171700 -0.51347015 0.99990983 0.49133323 1.79210204 -1.72054782
[43] -1.07850348 0.73389000 0.67149764 -0.87377146 -1.55345794 0.14109628
[49] 1.02334317 0.09995410 1.27613889 -0.12063251 -0.33296962 -1.13669521
[55] -0.12026325 1.33854279 0.18545645 -1.04583575 -0.11204903 0.13565989
[61] 0.22130274 -1.65745171 0.14291786 0.96725220 -1.14654752 0.89110115
[67] -0.58854075 0.62678402 1.38605889 1.07840608 0.37110119 0.20947740
[73] -1.61229024 -0.76044079 0.47126500 -0.34634587 -1.59880951 1.36628879
[79] -0.87523018 1.29128655 -1.11861178 -0.37262056 0.67583678 -0.13579712
[85] 0.07062978 0.02972125 0.86033336 -2.46279312 0.22896512 -1.25687483
[91] 1.17424756 -0.75435615 0.32293527 0.15833185 0.71171758 1.86823560
[97] 0.75828444 0.71876707 -1.09062004 0.61306062
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.09672077 -1.492815 -0.8073417 -1.29491 -1.613343 0.6167129 -0.140025
[2,] 0.09672077 -1.492815 -0.8073417 -1.29491 -1.613343 0.6167129 -0.140025
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.3144445 0.891368 1.143108 -1.655532 0.5529624 1.240759 1.956451
[2,] -0.3144445 0.891368 1.143108 -1.655532 0.5529624 1.240759 1.956451
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.0247028 -0.3134133 0.905777 -1.587618 -1.504558 -0.7202632 0.3766195
[2,] -0.0247028 -0.3134133 0.905777 -1.587618 -1.504558 -0.7202632 0.3766195
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.7573239 0.1205779 1.778964 0.2468292 1.314689 -0.9845141 0.2425633
[2,] 0.7573239 0.1205779 1.778964 0.2468292 1.314689 -0.9845141 0.2425633
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.5971966 0.4362304 0.6006519 0.2814241 -1.191078 -0.6702272 -0.1249586
[2,] 0.5971966 0.4362304 0.6006519 0.2814241 -1.191078 -0.6702272 -0.1249586
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.8406436 0.781717 -0.5134702 0.9999098 0.4913332 1.792102 -1.720548
[2,] 0.8406436 0.781717 -0.5134702 0.9999098 0.4913332 1.792102 -1.720548
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.078503 0.73389 0.6714976 -0.8737715 -1.553458 0.1410963 1.023343
[2,] -1.078503 0.73389 0.6714976 -0.8737715 -1.553458 0.1410963 1.023343
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.0999541 1.276139 -0.1206325 -0.3329696 -1.136695 -0.1202632 1.338543
[2,] 0.0999541 1.276139 -0.1206325 -0.3329696 -1.136695 -0.1202632 1.338543
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.1854564 -1.045836 -0.112049 0.1356599 0.2213027 -1.657452 0.1429179
[2,] 0.1854564 -1.045836 -0.112049 0.1356599 0.2213027 -1.657452 0.1429179
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.9672522 -1.146548 0.8911012 -0.5885407 0.626784 1.386059 1.078406
[2,] 0.9672522 -1.146548 0.8911012 -0.5885407 0.626784 1.386059 1.078406
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.3711012 0.2094774 -1.61229 -0.7604408 0.471265 -0.3463459 -1.59881
[2,] 0.3711012 0.2094774 -1.61229 -0.7604408 0.471265 -0.3463459 -1.59881
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.366289 -0.8752302 1.291287 -1.118612 -0.3726206 0.6758368 -0.1357971
[2,] 1.366289 -0.8752302 1.291287 -1.118612 -0.3726206 0.6758368 -0.1357971
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.07062978 0.02972125 0.8603334 -2.462793 0.2289651 -1.256875 1.174248
[2,] 0.07062978 0.02972125 0.8603334 -2.462793 0.2289651 -1.256875 1.174248
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.7543561 0.3229353 0.1583318 0.7117176 1.868236 0.7582844 0.7187671
[2,] -0.7543561 0.3229353 0.1583318 0.7117176 1.868236 0.7582844 0.7187671
[,99] [,100]
[1,] -1.09062 0.6130606
[2,] -1.09062 0.6130606
>
>
> Max(tmp2)
[1] 2.685496
> Min(tmp2)
[1] -2.445369
> mean(tmp2)
[1] 0.1074398
> Sum(tmp2)
[1] 10.74398
> Var(tmp2)
[1] 0.8741982
>
> rowMeans(tmp2)
[1] -2.29772582 0.21448343 0.26178730 -0.97890409 0.99115584 -0.01899818
[7] 0.10433935 0.58127870 -0.07137334 1.12666504 0.05091171 0.11577746
[13] 1.66989756 0.20239807 0.45089004 -0.15345394 -0.14809989 1.15262758
[19] -1.43226274 0.56123595 -0.28017253 1.03986013 -0.38318574 0.52987787
[25] -0.97646297 0.55877234 -0.18325258 0.21758616 -1.53160302 -0.19780679
[31] 2.68549552 -0.98287644 -0.74192790 1.88130272 0.40748813 0.03055673
[37] 1.57553792 0.45328435 0.69663735 0.32981902 0.85766039 -0.28527238
[43] 1.44849627 -0.20777807 0.41346850 -0.91993635 0.54098140 -1.49092000
[49] 0.71207360 -0.10147271 0.55576858 -2.44536937 -0.66891819 -0.10605979
[55] -1.00343669 -0.03899469 -1.27148547 -0.27899769 -0.74214591 -0.82415088
[61] 1.86044087 1.80936908 0.17288763 2.09928098 0.64971304 2.01899767
[67] 0.36977096 -1.22201171 -1.86348999 -0.43637153 1.11473730 -0.95902186
[73] 1.21352016 -1.20630564 -0.42612982 0.27881905 -0.20491567 -0.07135638
[79] 0.08479656 0.09313049 0.64081047 0.10541664 0.12032610 -0.82253361
[85] 0.69455869 1.14063817 0.16463992 0.39539451 -0.61755929 0.58640273
[91] -0.94296510 0.83303285 0.44956713 -0.27444111 -0.26472757 0.22631573
[97] 0.75942102 0.45643424 -0.34199988 0.40432096
> rowSums(tmp2)
[1] -2.29772582 0.21448343 0.26178730 -0.97890409 0.99115584 -0.01899818
[7] 0.10433935 0.58127870 -0.07137334 1.12666504 0.05091171 0.11577746
[13] 1.66989756 0.20239807 0.45089004 -0.15345394 -0.14809989 1.15262758
[19] -1.43226274 0.56123595 -0.28017253 1.03986013 -0.38318574 0.52987787
[25] -0.97646297 0.55877234 -0.18325258 0.21758616 -1.53160302 -0.19780679
[31] 2.68549552 -0.98287644 -0.74192790 1.88130272 0.40748813 0.03055673
[37] 1.57553792 0.45328435 0.69663735 0.32981902 0.85766039 -0.28527238
[43] 1.44849627 -0.20777807 0.41346850 -0.91993635 0.54098140 -1.49092000
[49] 0.71207360 -0.10147271 0.55576858 -2.44536937 -0.66891819 -0.10605979
[55] -1.00343669 -0.03899469 -1.27148547 -0.27899769 -0.74214591 -0.82415088
[61] 1.86044087 1.80936908 0.17288763 2.09928098 0.64971304 2.01899767
[67] 0.36977096 -1.22201171 -1.86348999 -0.43637153 1.11473730 -0.95902186
[73] 1.21352016 -1.20630564 -0.42612982 0.27881905 -0.20491567 -0.07135638
[79] 0.08479656 0.09313049 0.64081047 0.10541664 0.12032610 -0.82253361
[85] 0.69455869 1.14063817 0.16463992 0.39539451 -0.61755929 0.58640273
[91] -0.94296510 0.83303285 0.44956713 -0.27444111 -0.26472757 0.22631573
[97] 0.75942102 0.45643424 -0.34199988 0.40432096
> 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] -2.29772582 0.21448343 0.26178730 -0.97890409 0.99115584 -0.01899818
[7] 0.10433935 0.58127870 -0.07137334 1.12666504 0.05091171 0.11577746
[13] 1.66989756 0.20239807 0.45089004 -0.15345394 -0.14809989 1.15262758
[19] -1.43226274 0.56123595 -0.28017253 1.03986013 -0.38318574 0.52987787
[25] -0.97646297 0.55877234 -0.18325258 0.21758616 -1.53160302 -0.19780679
[31] 2.68549552 -0.98287644 -0.74192790 1.88130272 0.40748813 0.03055673
[37] 1.57553792 0.45328435 0.69663735 0.32981902 0.85766039 -0.28527238
[43] 1.44849627 -0.20777807 0.41346850 -0.91993635 0.54098140 -1.49092000
[49] 0.71207360 -0.10147271 0.55576858 -2.44536937 -0.66891819 -0.10605979
[55] -1.00343669 -0.03899469 -1.27148547 -0.27899769 -0.74214591 -0.82415088
[61] 1.86044087 1.80936908 0.17288763 2.09928098 0.64971304 2.01899767
[67] 0.36977096 -1.22201171 -1.86348999 -0.43637153 1.11473730 -0.95902186
[73] 1.21352016 -1.20630564 -0.42612982 0.27881905 -0.20491567 -0.07135638
[79] 0.08479656 0.09313049 0.64081047 0.10541664 0.12032610 -0.82253361
[85] 0.69455869 1.14063817 0.16463992 0.39539451 -0.61755929 0.58640273
[91] -0.94296510 0.83303285 0.44956713 -0.27444111 -0.26472757 0.22631573
[97] 0.75942102 0.45643424 -0.34199988 0.40432096
> rowMin(tmp2)
[1] -2.29772582 0.21448343 0.26178730 -0.97890409 0.99115584 -0.01899818
[7] 0.10433935 0.58127870 -0.07137334 1.12666504 0.05091171 0.11577746
[13] 1.66989756 0.20239807 0.45089004 -0.15345394 -0.14809989 1.15262758
[19] -1.43226274 0.56123595 -0.28017253 1.03986013 -0.38318574 0.52987787
[25] -0.97646297 0.55877234 -0.18325258 0.21758616 -1.53160302 -0.19780679
[31] 2.68549552 -0.98287644 -0.74192790 1.88130272 0.40748813 0.03055673
[37] 1.57553792 0.45328435 0.69663735 0.32981902 0.85766039 -0.28527238
[43] 1.44849627 -0.20777807 0.41346850 -0.91993635 0.54098140 -1.49092000
[49] 0.71207360 -0.10147271 0.55576858 -2.44536937 -0.66891819 -0.10605979
[55] -1.00343669 -0.03899469 -1.27148547 -0.27899769 -0.74214591 -0.82415088
[61] 1.86044087 1.80936908 0.17288763 2.09928098 0.64971304 2.01899767
[67] 0.36977096 -1.22201171 -1.86348999 -0.43637153 1.11473730 -0.95902186
[73] 1.21352016 -1.20630564 -0.42612982 0.27881905 -0.20491567 -0.07135638
[79] 0.08479656 0.09313049 0.64081047 0.10541664 0.12032610 -0.82253361
[85] 0.69455869 1.14063817 0.16463992 0.39539451 -0.61755929 0.58640273
[91] -0.94296510 0.83303285 0.44956713 -0.27444111 -0.26472757 0.22631573
[97] 0.75942102 0.45643424 -0.34199988 0.40432096
>
> colMeans(tmp2)
[1] 0.1074398
> colSums(tmp2)
[1] 10.74398
> colVars(tmp2)
[1] 0.8741982
> colSd(tmp2)
[1] 0.9349857
> colMax(tmp2)
[1] 2.685496
> colMin(tmp2)
[1] -2.445369
> colMedians(tmp2)
[1] 0.1180518
> colRanges(tmp2)
[,1]
[1,] -2.445369
[2,] 2.685496
>
> 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] 5.80406113 -4.47532396 -1.25269368 0.80185563 2.28787715 6.11378096
[7] -5.41523203 3.57107639 0.04966145 -0.58669791
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1815958
[2,] 0.1416066
[3,] 0.7803797
[4,] 1.2564714
[5,] 1.9727666
>
> rowApply(tmp,sum)
[1] -0.09179899 -4.01335451 2.16849046 1.96379342 0.83341671 -0.39346223
[7] 0.34939418 0.26135298 3.98621865 1.83431445
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 4 8 9 9 10 5 9 7 3
[2,] 1 3 4 7 8 1 9 1 4 8
[3,] 7 5 10 1 3 6 4 4 3 5
[4,] 10 8 6 3 10 4 2 2 6 7
[5,] 5 2 3 2 7 5 7 7 10 10
[6,] 6 9 9 6 5 9 8 5 9 2
[7,] 9 1 1 5 6 3 3 3 5 1
[8,] 2 7 5 10 4 8 6 6 2 9
[9,] 3 10 7 8 1 2 1 10 8 6
[10,] 4 6 2 4 2 7 10 8 1 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.4917600 1.2078619 -0.7003772 1.5723925 -2.7294672 -0.6664013
[7] -0.1176194 0.3007449 0.5895927 -0.3186406 -1.1325630 1.4499639
[13] -2.6599660 3.3256903 -0.6409072 -0.8786358 0.1550480 -0.8235784
[19] 4.0684465 -4.0021597
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.9488418
[2,] 0.5147402
[3,] 0.5754182
[4,] 1.6173935
[5,] 1.7330499
>
> rowApply(tmp,sum)
[1] 3.263056 -3.050081 -1.740569 -1.391284 3.410063
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 17 16 1 19 18
[2,] 8 6 18 13 9
[3,] 16 17 3 15 5
[4,] 19 8 10 20 4
[5,] 11 10 2 3 13
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.5754182 0.04173444 0.5140198 1.1860247 0.2035666 0.05026832
[2,] 0.5147402 -0.57000544 0.6452678 -0.5276462 -0.3947131 -0.80851361
[3,] -1.9488418 1.44276271 -1.6495918 -0.3723303 -1.7563652 -0.43752238
[4,] 1.6173935 0.30916768 0.7570229 2.5989793 -1.3483997 0.11862813
[5,] 1.7330499 -0.01579749 -0.9670959 -1.3126350 0.5664443 0.41073824
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.156027685 0.31540509 0.2348442 -0.5299266 0.24298639 0.5138782
[2,] -0.259735082 0.01406953 -0.6342091 0.4649095 0.04460606 0.8603763
[3,] 0.005280191 -0.45303171 0.1897122 -0.8955086 0.20480405 1.4936012
[4,] 0.047127848 -1.95245764 -0.4047327 0.9795683 0.05574280 0.8769170
[5,] -0.066320084 2.37675959 1.2039781 -0.3376832 -1.68070234 -2.2948087
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.8996143 -0.3205813 -0.1502649 2.4042271 -0.27082798 -0.0241891
[2,] -1.7685591 2.8719370 -1.4273183 -0.4783492 0.05863833 1.0839120
[3,] 0.6795082 1.1652102 0.9541095 -0.9426020 0.38808007 -0.4855519
[4,] -0.4054003 -1.1512936 -0.5474491 -2.7230743 -0.45870091 0.3874578
[5,] -0.2659004 0.7604180 0.5300155 0.8611626 0.43785849 -1.7852073
[,19] [,20]
[1,] 0.9488184 -1.9287593
[2,] -0.5404437 -2.1990446
[3,] 2.2675121 -1.5898038
[4,] -1.0766241 0.9288431
[5,] 2.4691839 0.7866048
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.12-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-3.12-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 643 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 557 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.7299579 0.3658242 -0.2789747 -0.3081705 -1.092395 -2.641777 0.2565123
col8 col9 col10 col11 col12 col13 col14
row1 0.2731016 -2.111201 -1.280045 0.1387341 0.4320504 -0.5535289 0.2822348
col15 col16 col17 col18 col19 col20
row1 -0.4188562 0.2043726 -0.3768025 -0.05568755 -0.2851608 0.9420863
> tmp[,"col10"]
col10
row1 -1.2800447
row2 0.2067200
row3 0.0851163
row4 1.4582999
row5 -0.9311985
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.7299579 0.3658242 -0.2789747 -0.3081705 -1.0923946 -2.641777 0.25651232
row5 -0.9547894 0.1493403 -2.4056252 -1.5567063 -0.9115856 -1.027616 0.05815897
col8 col9 col10 col11 col12 col13 col14
row1 0.2731016 -2.11120067 -1.2800447 0.13873412 0.4320504 -0.5535289 0.2822348
row5 0.1394605 -0.03625719 -0.9311985 0.02956137 1.5255927 -1.1676965 0.1000045
col15 col16 col17 col18 col19 col20
row1 -0.4188562 0.2043726 -0.3768025 -0.05568755 -0.2851608 0.9420863
row5 -0.2683924 -1.6608424 0.8183182 0.64120063 1.3250697 0.6057415
> tmp[,c("col6","col20")]
col6 col20
row1 -2.6417771 0.9420863
row2 0.3474087 0.1766540
row3 -0.1101456 0.3617805
row4 1.0799641 -0.3391132
row5 -1.0276156 0.6057415
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -2.641777 0.9420863
row5 -1.027616 0.6057415
>
>
>
>
> 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 51.94793 50.14296 51.42822 50.74854 49.89538 105.3567 50.49909 48.25689
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.15875 49.36407 50.63396 50.66658 51.4313 49.35605 50.03443 50.42118
col17 col18 col19 col20
row1 49.4226 50.13953 49.10519 104.7602
> tmp[,"col10"]
col10
row1 49.36407
row2 29.86770
row3 29.76534
row4 27.91565
row5 49.61567
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.94793 50.14296 51.42822 50.74854 49.89538 105.3567 50.49909 48.25689
row5 50.55095 49.93036 50.02158 48.33338 51.54638 106.8290 48.71040 50.01576
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.15875 49.36407 50.63396 50.66658 51.43130 49.35605 50.03443 50.42118
row5 50.13950 49.61567 49.16378 50.63294 50.87444 52.64693 49.47214 48.40135
col17 col18 col19 col20
row1 49.42260 50.13953 49.10519 104.7602
row5 51.01458 49.24124 49.35569 104.1723
> tmp[,c("col6","col20")]
col6 col20
row1 105.35675 104.76020
row2 76.38227 73.73274
row3 74.03227 74.03559
row4 75.23853 75.94056
row5 106.82905 104.17234
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.3567 104.7602
row5 106.8290 104.1723
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.3567 104.7602
row5 106.8290 104.1723
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.4604951
[2,] 0.6507438
[3,] 0.4879294
[4,] 0.1217501
[5,] 0.5195779
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.2685673 -0.2451353
[2,] 0.4221587 1.1640291
[3,] -0.8778341 0.7263656
[4,] 0.7156538 -1.3816941
[5,] -0.7394544 -1.1201337
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.5737516 1.0367623
[2,] -0.1706549 -1.2622736
[3,] 0.9154256 0.2738147
[4,] -0.1286708 1.2910616
[5,] -0.1852898 -0.7545009
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.5737516
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.5737516
[2,] -0.1706549
>
>
>
> 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 0.1242422 1.0705522 0.3033832 2.5311850 2.288234 0.4888426 -1.6105692
row1 -0.7033648 0.6678833 0.3013866 0.9139087 -1.517514 -0.3022860 -0.3086583
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.658302485 0.6874265 -0.2593528 -0.6937124 0.03992787 -0.1743117
row1 -0.009318539 -0.7923447 -0.3342760 0.1110686 -0.23760058 2.1014220
[,14] [,15] [,16] [,17] [,18] [,19]
row3 0.2703414 -0.1114627 0.2378414 -0.05442239 -3.5246292 -0.8058419
row1 0.8419930 1.4106000 0.7364951 -1.13926403 -0.4093548 -1.6140130
[,20]
row3 0.2720120
row1 -0.3041405
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.619772 0.1462217 0.6889143 -0.09885961 0.3368772 -1.637844 -0.01678956
[,8] [,9] [,10]
row2 0.4248217 0.3241071 0.6161781
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -1.28546 -0.0490565 0.1619281 -0.7597975 0.6077137 0.8461641 -1.596328
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.7504548 -0.3075077 1.093243 -0.09572805 1.768426 -0.1474676 0.3561583
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.2552035 0.8435312 -0.9463372 1.517584 0.2406781 0.08592998
>
>
> 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: 0x561a95d4c710>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cd95db6012c"
[2] "/home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cd956a4d35c"
[3] "/home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cd93c9f5360"
[4] "/home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cd93e11ffda"
[5] "/home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cd9552b2b6a"
[6] "/home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cd96258bcc4"
[7] "/home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cd975a294ef"
[8] "/home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cd96e8c8eff"
[9] "/home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cd924811a72"
[10] "/home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cd973e73093"
[11] "/home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cd93a30a8df"
[12] "/home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cd977f02eaa"
[13] "/home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cd96e364e3f"
[14] "/home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cd95b20145f"
[15] "/home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests/BM1cd92aa54a18"
>
>
> ### 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: 0x561a956bbbd0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x561a956bbbd0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.12-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x561a956bbbd0>
> rowMedians(tmp)
[1] 0.628798123 0.226203591 -0.265457382 0.027775047 0.037524465
[6] 0.257646526 0.190996608 0.075738899 -0.346599802 -0.052313700
[11] -0.035177512 0.382570537 0.343795457 -0.215118188 -0.348825561
[16] 0.037460050 0.071084391 -0.282057088 -0.097927867 0.064349665
[21] -0.113428505 0.274946296 -0.063808733 -0.120501713 -0.052808675
[26] 0.153608849 0.131179067 -0.324386767 0.081544892 -0.390544333
[31] 0.363063381 0.429250641 -0.061887042 -0.099039280 0.164716953
[36] 0.407523720 0.170909071 0.050720468 0.453774360 0.028742398
[41] -0.449234330 0.142416633 -0.359485138 -0.007491006 0.302422211
[46] -0.349675151 -0.417923673 0.710831943 -0.163175749 -0.121520627
[51] 0.464791012 0.041028657 -0.096406472 -0.002806320 -0.019466479
[56] 0.462591138 0.279613659 0.564009607 -0.122260410 -0.239829585
[61] -0.316001544 0.156833136 -0.784502180 0.259929963 -0.222743483
[66] 0.108841535 -0.064524218 -0.278218538 -0.203534599 0.510115852
[71] 0.134396618 -0.072526879 -0.172326458 0.225908110 0.076121584
[76] -0.186350569 0.173771215 -0.374228434 0.085403266 0.112348764
[81] 0.223584635 -0.143026211 -0.231370707 0.343484541 -0.051817553
[86] 0.685071876 0.190007193 0.187441580 -0.272675458 0.349225449
[91] 0.296165174 0.199330109 0.491465371 0.086967102 0.147950008
[96] -0.096855552 0.326166443 -0.059728647 0.210990602 -0.676887238
[101] 0.095128701 0.246418942 -0.202917287 -0.449013988 0.692300708
[106] 0.054341505 -0.023457962 0.001945120 0.163476639 -0.581698548
[111] -0.013980975 -0.124075412 0.354135729 -0.365563319 0.168557813
[116] 0.070143713 -0.279862296 -0.252502740 0.182851909 0.183610642
[121] 0.006727515 0.465883136 0.187348382 0.084194599 0.285384095
[126] 0.125565112 -0.109804218 -0.652267166 0.107392208 -0.483429514
[131] -0.417860000 0.088201432 -0.015761262 0.465088599 -0.013323775
[136] -0.361946734 -0.460585152 0.371507341 -0.090111044 -0.771747616
[141] -0.001079074 0.422379442 -0.591589276 0.123265018 0.160989207
[146] -0.058238359 -0.457339666 0.292516764 0.169939855 -0.205906144
[151] -0.158528165 0.155239481 -0.213627055 0.017037345 0.331416413
[156] -0.208041033 -0.489266500 -0.139891077 -0.095522290 -0.151825578
[161] 0.117108660 0.066848407 0.178375013 0.383305799 0.318755478
[166] 0.085794538 -0.077591767 -0.813061924 0.496670296 -0.172878960
[171] -0.086282325 -0.072057588 0.500172050 0.182774349 0.396609996
[176] -0.097556734 -0.376868686 -0.135618932 -0.323646239 0.088236214
[181] 0.016040923 -0.158060247 -0.182938839 0.376446481 -0.205793442
[186] -0.108751211 0.086531904 0.081967891 -0.189311765 -0.607985858
[191] 0.133757927 -0.154638293 -0.215886688 -0.311272058 0.019896057
[196] 0.279684320 -0.001034853 -0.127671777 -0.844065858 0.218741453
[201] -0.062660808 -0.165904928 0.404753532 0.442397215 -0.248968614
[206] 0.003305806 0.208716678 0.104100318 0.061249642 0.450263882
[211] 0.579346695 -0.123246135 -0.174989176 0.152030853 -0.289988830
[216] 0.134931468 0.357084638 0.509003366 -0.107265547 -0.128387384
[221] 0.527165557 0.469466725 0.528699320 0.385298011 0.487845023
[226] 0.122442192 0.313172642 0.003348258 -0.344864652 0.490919012
>
> proc.time()
user system elapsed
1.868 0.808 2.699
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.0.5 (2021-03-31) -- "Shake and Throw"
Copyright (C) 2021 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: 0x560240946f00>
> .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: 0x560240946f00>
> .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: 0x560240946f00>
> .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: 0x560240946f00>
> 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: 0x5602429c2250>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5602429c2250>
> .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: 0x5602429c2250>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5602429c2250>
> .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: 0x5602429c2250>
> 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: 0x560242b78260>
> .Call("R_bm_AddColumn",P)
<pointer: 0x560242b78260>
> .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: 0x560242b78260>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x560242b78260>
> .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: 0x560242b78260>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x560242b78260>
> .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: 0x560242b78260>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x560242b78260>
> .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: 0x560242b78260>
> 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: 0x5602412d3e50>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5602412d3e50>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5602412d3e50>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5602412d3e50>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1e923919ec46" "BufferedMatrixFile1e926760e376"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1e923919ec46" "BufferedMatrixFile1e926760e376"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x560242cbb2a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x560242cbb2a0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x560242cbb2a0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x560242cbb2a0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x560242cbb2a0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x560242cbb2a0>
> .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: 0x560240a62040>
> .Call("R_bm_AddColumn",P)
<pointer: 0x560240a62040>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x560240a62040>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x560240a62040>
> 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: 0x560240a8d8e0>
> .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: 0x560240a8d8e0>
> rm(P)
>
> proc.time()
user system elapsed
0.432 0.032 0.464
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.0.5 (2021-03-31) -- "Shake and Throw"
Copyright (C) 2021 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
0.388 0.024 0.411