Ben Bolstad
| Snapshot Date: 2020-10-16 14:40:19 -0400 (Fri, 16 Oct 2020) |
| URL: https://git.bioconductor.org/packages/BufferedMatrix |
| Branch: RELEASE_3_11 |
| Last Commit: c4ad43d |
| Last Changed Date: 2020-04-27 14:14:34 -0400 (Mon, 27 Apr 2020) |
| Back to Multiple platform build/check report for BioC 3.11 |
|
This page was generated on 2020-10-17 11:54:30 -0400 (Sat, 17 Oct 2020).
| 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 210/1905 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||
| BufferedMatrix 1.52.0 Ben Bolstad
| malbec2 | Linux (Ubuntu 18.04.4 LTS) / x86_64 | OK | OK | [ OK ] | | ||||||
| tokay2 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||
| machv2 | macOS 10.14.6 Mojave / x86_64 | OK | OK | OK | OK | |
| Package: BufferedMatrix |
| Version: 1.52.0 |
| Command: /home/biocbuild/bbs-3.11-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.11-bioc/R/library --no-vignettes --timings BufferedMatrix_1.52.0.tar.gz |
| StartedAt: 2020-10-16 23:27:30 -0400 (Fri, 16 Oct 2020) |
| EndedAt: 2020-10-16 23:27:58 -0400 (Fri, 16 Oct 2020) |
| EllapsedTime: 27.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.11-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.11-bioc/R/library --no-vignettes --timings BufferedMatrix_1.52.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck’ * using R version 4.0.3 (2020-10-10) * 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 ‘1.52.0’ * 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-3.11-bioc/meat/BufferedMatrix.Rcheck/00check.log’ for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.11-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.11-bioc/R/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
gcc -I"/home/biocbuild/bbs-3.11-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.11-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-3.11-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-3.11-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-3.11-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-3.11-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.11-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 4.0.3 (2020-10-10) -- "Bunny-Wunnies Freak Out"
Copyright (C) 2020 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
0.441 0.035 0.461
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.0.3 (2020-10-10) -- "Bunny-Wunnies Freak Out"
Copyright (C) 2020 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-3.11-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 438349 23.5 927477 49.6 649897 34.8
Vcells 788720 6.1 8388608 64.0 2015275 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] "Fri Oct 16 23:27:51 2020"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Oct 16 23:27:51 2020"
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
>
>
> RowMode(tmp2)
<pointer: 0x5649c1d0e3a0>
>
>
>
> 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] "Fri Oct 16 23:27:52 2020"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Oct 16 23:27:52 2020"
>
> ColMode(tmp2)
<pointer: 0x5649c1d0e3a0>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.8344550 -0.567110 -0.61689345 1.1580406
[2,] 0.6112641 0.292966 -0.07277074 1.0717066
[3,] -1.0078733 -1.582453 0.16625801 -0.7780470
[4,] 0.4018716 1.181310 1.33955567 -0.7336322
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.8344550 0.567110 0.61689345 1.1580406
[2,] 0.6112641 0.292966 0.07277074 1.0717066
[3,] 1.0078733 1.582453 0.16625801 0.7780470
[4,] 0.4018716 1.181310 1.33955567 0.7336322
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.11-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,] 9.9917193 0.7530671 0.7854256 1.0761230
[2,] 0.7818338 0.5412633 0.2697605 1.0352326
[3,] 1.0039289 1.2579557 0.4077475 0.8820697
[4,] 0.6339334 1.0868810 1.1573918 0.8565233
>
> 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-3.11-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.75165 33.09778 33.47115 36.91927
[2,] 33.42960 30.70560 27.77038 36.42403
[3,] 36.04716 39.16201 29.24373 34.59874
[4,] 31.74121 37.05012 37.91347 34.29887
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5649c3546160>
> exp(tmp5)
<pointer: 0x5649c3546160>
> log(tmp5,2)
<pointer: 0x5649c3546160>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.7911
> Min(tmp5)
[1] 53.44712
> mean(tmp5)
[1] 72.57871
> Sum(tmp5)
[1] 14515.74
> Var(tmp5)
[1] 850.7724
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.65707 67.94173 67.09373 70.97324 72.42713 74.01177 68.94689 72.42315
[9] 67.19095 73.12145
> rowSums(tmp5)
[1] 1833.141 1358.835 1341.875 1419.465 1448.543 1480.235 1378.938 1448.463
[9] 1343.819 1462.429
> rowVars(tmp5)
[1] 7876.65365 45.57404 50.84067 70.06433 49.32357 107.55332
[7] 83.75615 48.28978 49.32656 42.22246
> rowSd(tmp5)
[1] 88.750513 6.750854 7.130264 8.370444 7.023074 10.370792 9.151838
[8] 6.949085 7.023287 6.497881
> rowMax(tmp5)
[1] 467.79111 83.14951 81.51059 87.51530 83.53192 94.88394 85.30846
[8] 83.18192 78.18452 86.12594
> rowMin(tmp5)
[1] 57.87761 57.80040 57.58035 53.44712 57.62271 58.13101 54.31064 56.93444
[9] 54.08507 62.00546
>
> colMeans(tmp5)
[1] 111.10159 73.49078 68.06895 73.28827 71.37330 67.99297 75.45340
[8] 68.26563 69.12734 74.05471 75.74848 66.19673 67.92207 70.08489
[15] 67.84580 69.90535 70.78131 67.87671 70.07743 72.91850
> colSums(tmp5)
[1] 1111.0159 734.9078 680.6895 732.8827 713.7330 679.9297 754.5340
[8] 682.6563 691.2734 740.5471 757.4848 661.9673 679.2207 700.8489
[15] 678.4580 699.0535 707.8131 678.7671 700.7743 729.1850
> colVars(tmp5)
[1] 15717.68243 39.22365 43.02004 11.87483 78.25145 73.45608
[7] 83.06602 102.86957 48.80376 43.05292 45.82717 72.62235
[13] 96.09146 49.79433 96.32611 92.43520 124.95697 29.52995
[19] 51.33363 12.34557
> colSd(tmp5)
[1] 125.370182 6.262878 6.558967 3.445988 8.845985 8.570652
[7] 9.114056 10.142463 6.985968 6.561473 6.769577 8.521875
[13] 9.802625 7.056510 9.814586 9.614323 11.178415 5.434147
[19] 7.164749 3.513626
> colMax(tmp5)
[1] 467.79111 82.13341 78.91193 78.28375 83.65844 83.10716 88.82045
[8] 81.18627 79.79381 85.16687 85.30846 79.83145 86.12594 84.39253
[15] 83.53192 93.58029 94.88394 76.77642 87.61927 78.60941
> colMin(tmp5)
[1] 66.06516 63.90968 57.80040 67.55527 54.37473 56.79254 57.62271 53.44712
[9] 59.46676 65.80628 66.16956 54.08507 58.13101 62.31481 54.32669 59.88606
[17] 56.79428 59.96649 60.55371 68.29543
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 91.65707 67.94173 67.09373 70.97324 NA 74.01177 68.94689 72.42315
[9] 67.19095 73.12145
> rowSums(tmp5)
[1] 1833.141 1358.835 1341.875 1419.465 NA 1480.235 1378.938 1448.463
[9] 1343.819 1462.429
> rowVars(tmp5)
[1] 7876.65365 45.57404 50.84067 70.06433 44.85229 107.55332
[7] 83.75615 48.28978 49.32656 42.22246
> rowSd(tmp5)
[1] 88.750513 6.750854 7.130264 8.370444 6.697185 10.370792 9.151838
[8] 6.949085 7.023287 6.497881
> rowMax(tmp5)
[1] 467.79111 83.14951 81.51059 87.51530 NA 94.88394 85.30846
[8] 83.18192 78.18452 86.12594
> rowMin(tmp5)
[1] 57.87761 57.80040 57.58035 53.44712 NA 58.13101 54.31064 56.93444
[9] 54.08507 62.00546
>
> colMeans(tmp5)
[1] 111.10159 73.49078 68.06895 73.28827 71.37330 67.99297 75.45340
[8] 68.26563 69.12734 74.05471 75.74848 66.19673 67.92207 70.08489
[15] NA 69.90535 70.78131 67.87671 70.07743 72.91850
> colSums(tmp5)
[1] 1111.0159 734.9078 680.6895 732.8827 713.7330 679.9297 754.5340
[8] 682.6563 691.2734 740.5471 757.4848 661.9673 679.2207 700.8489
[15] NA 699.0535 707.8131 678.7671 700.7743 729.1850
> colVars(tmp5)
[1] 15717.68243 39.22365 43.02004 11.87483 78.25145 73.45608
[7] 83.06602 102.86957 48.80376 43.05292 45.82717 72.62235
[13] 96.09146 49.79433 NA 92.43520 124.95697 29.52995
[19] 51.33363 12.34557
> colSd(tmp5)
[1] 125.370182 6.262878 6.558967 3.445988 8.845985 8.570652
[7] 9.114056 10.142463 6.985968 6.561473 6.769577 8.521875
[13] 9.802625 7.056510 NA 9.614323 11.178415 5.434147
[19] 7.164749 3.513626
> colMax(tmp5)
[1] 467.79111 82.13341 78.91193 78.28375 83.65844 83.10716 88.82045
[8] 81.18627 79.79381 85.16687 85.30846 79.83145 86.12594 84.39253
[15] NA 93.58029 94.88394 76.77642 87.61927 78.60941
> colMin(tmp5)
[1] 66.06516 63.90968 57.80040 67.55527 54.37473 56.79254 57.62271 53.44712
[9] 59.46676 65.80628 66.16956 54.08507 58.13101 62.31481 NA 59.88606
[17] 56.79428 59.96649 60.55371 68.29543
>
> Max(tmp5,na.rm=TRUE)
[1] 467.7911
> Min(tmp5,na.rm=TRUE)
[1] 53.44712
> mean(tmp5,na.rm=TRUE)
[1] 72.52367
> Sum(tmp5,na.rm=TRUE)
[1] 14432.21
> Var(tmp5,na.rm=TRUE)
[1] 854.4603
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.65707 67.94173 67.09373 70.97324 71.84267 74.01177 68.94689 72.42315
[9] 67.19095 73.12145
> rowSums(tmp5,na.rm=TRUE)
[1] 1833.141 1358.835 1341.875 1419.465 1365.011 1480.235 1378.938 1448.463
[9] 1343.819 1462.429
> rowVars(tmp5,na.rm=TRUE)
[1] 7876.65365 45.57404 50.84067 70.06433 44.85229 107.55332
[7] 83.75615 48.28978 49.32656 42.22246
> rowSd(tmp5,na.rm=TRUE)
[1] 88.750513 6.750854 7.130264 8.370444 6.697185 10.370792 9.151838
[8] 6.949085 7.023287 6.497881
> rowMax(tmp5,na.rm=TRUE)
[1] 467.79111 83.14951 81.51059 87.51530 82.35494 94.88394 85.30846
[8] 83.18192 78.18452 86.12594
> rowMin(tmp5,na.rm=TRUE)
[1] 57.87761 57.80040 57.58035 53.44712 57.62271 58.13101 54.31064 56.93444
[9] 54.08507 62.00546
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.10159 73.49078 68.06895 73.28827 71.37330 67.99297 75.45340
[8] 68.26563 69.12734 74.05471 75.74848 66.19673 67.92207 70.08489
[15] 66.10290 69.90535 70.78131 67.87671 70.07743 72.91850
> colSums(tmp5,na.rm=TRUE)
[1] 1111.0159 734.9078 680.6895 732.8827 713.7330 679.9297 754.5340
[8] 682.6563 691.2734 740.5471 757.4848 661.9673 679.2207 700.8489
[15] 594.9261 699.0535 707.8131 678.7671 700.7743 729.1850
> colVars(tmp5,na.rm=TRUE)
[1] 15717.68243 39.22365 43.02004 11.87483 78.25145 73.45608
[7] 83.06602 102.86957 48.80376 43.05292 45.82717 72.62235
[13] 96.09146 49.79433 74.19266 92.43520 124.95697 29.52995
[19] 51.33363 12.34557
> colSd(tmp5,na.rm=TRUE)
[1] 125.370182 6.262878 6.558967 3.445988 8.845985 8.570652
[7] 9.114056 10.142463 6.985968 6.561473 6.769577 8.521875
[13] 9.802625 7.056510 8.613516 9.614323 11.178415 5.434147
[19] 7.164749 3.513626
> colMax(tmp5,na.rm=TRUE)
[1] 467.79111 82.13341 78.91193 78.28375 83.65844 83.10716 88.82045
[8] 81.18627 79.79381 85.16687 85.30846 79.83145 86.12594 84.39253
[15] 83.18192 93.58029 94.88394 76.77642 87.61927 78.60941
> colMin(tmp5,na.rm=TRUE)
[1] 66.06516 63.90968 57.80040 67.55527 54.37473 56.79254 57.62271 53.44712
[9] 59.46676 65.80628 66.16956 54.08507 58.13101 62.31481 54.32669 59.88606
[17] 56.79428 59.96649 60.55371 68.29543
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.65707 67.94173 67.09373 70.97324 NaN 74.01177 68.94689 72.42315
[9] 67.19095 73.12145
> rowSums(tmp5,na.rm=TRUE)
[1] 1833.141 1358.835 1341.875 1419.465 0.000 1480.235 1378.938 1448.463
[9] 1343.819 1462.429
> rowVars(tmp5,na.rm=TRUE)
[1] 7876.65365 45.57404 50.84067 70.06433 NA 107.55332
[7] 83.75615 48.28978 49.32656 42.22246
> rowSd(tmp5,na.rm=TRUE)
[1] 88.750513 6.750854 7.130264 8.370444 NA 10.370792 9.151838
[8] 6.949085 7.023287 6.497881
> rowMax(tmp5,na.rm=TRUE)
[1] 467.79111 83.14951 81.51059 87.51530 NA 94.88394 85.30846
[8] 83.18192 78.18452 86.12594
> rowMin(tmp5,na.rm=TRUE)
[1] 57.87761 57.80040 57.58035 53.44712 NA 58.13101 54.31064 56.93444
[9] 54.08507 62.00546
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.08389 73.44338 68.51276 73.49090 71.36576 68.67426 77.43458
[8] 67.98673 69.52783 74.05976 75.29634 64.68176 66.31841 69.12725
[15] NaN 70.01632 69.72143 67.78196 70.18840 73.09644
> colSums(tmp5,na.rm=TRUE)
[1] 1035.7550 660.9904 616.6149 661.4181 642.2918 618.0683 696.9112
[8] 611.8805 625.7505 666.5379 677.6671 582.1358 596.8657 622.1452
[15] 0.0000 630.1469 627.4929 610.0377 631.6956 657.8680
> colVars(tmp5,na.rm=TRUE)
[1] 17503.98262 44.10133 46.18162 12.89729 88.03224 77.41637
[7] 49.29186 114.85316 53.09984 48.43425 49.25569 55.87992
[13] 79.17125 45.70149 NA 103.85107 127.93891 33.12020
[19] 57.61182 13.53254
> colSd(tmp5,na.rm=TRUE)
[1] 132.302618 6.640883 6.795706 3.591279 9.382550 8.798657
[7] 7.020816 10.716957 7.286964 6.959472 7.018240 7.475287
[13] 8.897823 6.760288 NA 10.190735 11.311008 5.755015
[19] 7.590245 3.678661
> colMax(tmp5,na.rm=TRUE)
[1] 467.79111 82.13341 78.91193 78.28375 83.65844 83.10716 88.82045
[8] 81.18627 79.79381 85.16687 85.30846 73.40278 86.12594 84.39253
[15] -Inf 93.58029 94.88394 76.77642 87.61927 78.60941
> colMin(tmp5,na.rm=TRUE)
[1] 66.06516 63.90968 57.80040 67.55527 54.37473 56.79254 70.91683 53.44712
[9] 59.46676 65.80628 66.16956 54.08507 58.13101 62.31481 Inf 59.88606
[17] 56.79428 59.96649 60.55371 68.29543
>
>
>
>
> 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] 185.4869 219.0934 251.2344 257.1749 267.4674 189.8045 425.7196 199.0882
[9] 268.0161 225.3822
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 185.4869 219.0934 251.2344 257.1749 267.4674 189.8045 425.7196 199.0882
[9] 268.0161 225.3822
>
>
>
> 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 5.684342e-14 -5.684342e-14 5.684342e-14
[6] 0.000000e+00 -2.842171e-14 5.684342e-14 0.000000e+00 1.421085e-14
[11] -1.421085e-14 -1.705303e-13 5.684342e-14 0.000000e+00 -8.526513e-14
[16] 8.526513e-14 0.000000e+00 -5.684342e-14 -8.526513e-14 2.842171e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
10 12
5 1
10 20
5 3
3 4
10 11
3 11
3 8
1 1
6 16
2 17
1 14
6 20
4 18
9 6
4 12
8 13
5 17
3 20
4 9
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] 3.231534
> Min(tmp)
[1] -1.924555
> mean(tmp)
[1] 0.149804
> Sum(tmp)
[1] 14.9804
> Var(tmp)
[1] 1.042353
>
> rowMeans(tmp)
[1] 0.149804
> rowSums(tmp)
[1] 14.9804
> rowVars(tmp)
[1] 1.042353
> rowSd(tmp)
[1] 1.020957
> rowMax(tmp)
[1] 3.231534
> rowMin(tmp)
[1] -1.924555
>
> colMeans(tmp)
[1] 0.44112915 3.23153397 1.32475067 -1.12182777 0.72410325 0.15934154
[7] 1.07757640 0.57428144 -1.09439823 0.48806117 0.46652795 0.18499041
[13] 0.51497605 -0.69286626 -0.59813067 0.82203847 -0.17816981 -0.61484297
[19] -1.27427388 -1.11440864 -0.35318701 -0.27979035 -0.08774864 0.92557638
[25] 0.08116736 0.88890289 -1.31430910 -0.73257694 1.26009350 -0.97999188
[31] 1.80698012 0.44436327 0.36315533 -0.96172575 -1.56608615 0.83005723
[37] -1.18729499 -1.22245587 1.09671409 0.12092941 -0.91564759 0.08751060
[43] 2.14053755 0.14217415 -0.66891567 1.13317495 0.07951925 1.49842511
[49] 2.11031682 -1.83564589 -0.32774920 0.72728385 -1.21600516 -0.84640748
[55] -0.02756680 1.35489300 -1.47999747 0.77850352 -1.01363603 -1.68436266
[61] 0.43004290 0.77393270 0.39079679 0.66641718 0.09470890 -0.74144314
[67] 1.10294848 1.83524164 0.78679249 1.60599462 0.18030612 0.71498383
[73] 0.52187867 0.67223533 0.89860955 -1.92455519 2.05918529 0.91047941
[79] 0.92187734 0.76443956 -1.73885830 0.23298581 0.72277273 -0.90921988
[85] -0.40453768 -0.97018465 -0.69657081 -0.53129675 -0.39730586 0.15743259
[91] -0.09227643 -1.33057824 0.79016106 1.41006499 0.11628045 0.34845881
[97] 0.78219562 1.28036130 0.79145535 0.26462115
> colSums(tmp)
[1] 0.44112915 3.23153397 1.32475067 -1.12182777 0.72410325 0.15934154
[7] 1.07757640 0.57428144 -1.09439823 0.48806117 0.46652795 0.18499041
[13] 0.51497605 -0.69286626 -0.59813067 0.82203847 -0.17816981 -0.61484297
[19] -1.27427388 -1.11440864 -0.35318701 -0.27979035 -0.08774864 0.92557638
[25] 0.08116736 0.88890289 -1.31430910 -0.73257694 1.26009350 -0.97999188
[31] 1.80698012 0.44436327 0.36315533 -0.96172575 -1.56608615 0.83005723
[37] -1.18729499 -1.22245587 1.09671409 0.12092941 -0.91564759 0.08751060
[43] 2.14053755 0.14217415 -0.66891567 1.13317495 0.07951925 1.49842511
[49] 2.11031682 -1.83564589 -0.32774920 0.72728385 -1.21600516 -0.84640748
[55] -0.02756680 1.35489300 -1.47999747 0.77850352 -1.01363603 -1.68436266
[61] 0.43004290 0.77393270 0.39079679 0.66641718 0.09470890 -0.74144314
[67] 1.10294848 1.83524164 0.78679249 1.60599462 0.18030612 0.71498383
[73] 0.52187867 0.67223533 0.89860955 -1.92455519 2.05918529 0.91047941
[79] 0.92187734 0.76443956 -1.73885830 0.23298581 0.72277273 -0.90921988
[85] -0.40453768 -0.97018465 -0.69657081 -0.53129675 -0.39730586 0.15743259
[91] -0.09227643 -1.33057824 0.79016106 1.41006499 0.11628045 0.34845881
[97] 0.78219562 1.28036130 0.79145535 0.26462115
> 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] 0.44112915 3.23153397 1.32475067 -1.12182777 0.72410325 0.15934154
[7] 1.07757640 0.57428144 -1.09439823 0.48806117 0.46652795 0.18499041
[13] 0.51497605 -0.69286626 -0.59813067 0.82203847 -0.17816981 -0.61484297
[19] -1.27427388 -1.11440864 -0.35318701 -0.27979035 -0.08774864 0.92557638
[25] 0.08116736 0.88890289 -1.31430910 -0.73257694 1.26009350 -0.97999188
[31] 1.80698012 0.44436327 0.36315533 -0.96172575 -1.56608615 0.83005723
[37] -1.18729499 -1.22245587 1.09671409 0.12092941 -0.91564759 0.08751060
[43] 2.14053755 0.14217415 -0.66891567 1.13317495 0.07951925 1.49842511
[49] 2.11031682 -1.83564589 -0.32774920 0.72728385 -1.21600516 -0.84640748
[55] -0.02756680 1.35489300 -1.47999747 0.77850352 -1.01363603 -1.68436266
[61] 0.43004290 0.77393270 0.39079679 0.66641718 0.09470890 -0.74144314
[67] 1.10294848 1.83524164 0.78679249 1.60599462 0.18030612 0.71498383
[73] 0.52187867 0.67223533 0.89860955 -1.92455519 2.05918529 0.91047941
[79] 0.92187734 0.76443956 -1.73885830 0.23298581 0.72277273 -0.90921988
[85] -0.40453768 -0.97018465 -0.69657081 -0.53129675 -0.39730586 0.15743259
[91] -0.09227643 -1.33057824 0.79016106 1.41006499 0.11628045 0.34845881
[97] 0.78219562 1.28036130 0.79145535 0.26462115
> colMin(tmp)
[1] 0.44112915 3.23153397 1.32475067 -1.12182777 0.72410325 0.15934154
[7] 1.07757640 0.57428144 -1.09439823 0.48806117 0.46652795 0.18499041
[13] 0.51497605 -0.69286626 -0.59813067 0.82203847 -0.17816981 -0.61484297
[19] -1.27427388 -1.11440864 -0.35318701 -0.27979035 -0.08774864 0.92557638
[25] 0.08116736 0.88890289 -1.31430910 -0.73257694 1.26009350 -0.97999188
[31] 1.80698012 0.44436327 0.36315533 -0.96172575 -1.56608615 0.83005723
[37] -1.18729499 -1.22245587 1.09671409 0.12092941 -0.91564759 0.08751060
[43] 2.14053755 0.14217415 -0.66891567 1.13317495 0.07951925 1.49842511
[49] 2.11031682 -1.83564589 -0.32774920 0.72728385 -1.21600516 -0.84640748
[55] -0.02756680 1.35489300 -1.47999747 0.77850352 -1.01363603 -1.68436266
[61] 0.43004290 0.77393270 0.39079679 0.66641718 0.09470890 -0.74144314
[67] 1.10294848 1.83524164 0.78679249 1.60599462 0.18030612 0.71498383
[73] 0.52187867 0.67223533 0.89860955 -1.92455519 2.05918529 0.91047941
[79] 0.92187734 0.76443956 -1.73885830 0.23298581 0.72277273 -0.90921988
[85] -0.40453768 -0.97018465 -0.69657081 -0.53129675 -0.39730586 0.15743259
[91] -0.09227643 -1.33057824 0.79016106 1.41006499 0.11628045 0.34845881
[97] 0.78219562 1.28036130 0.79145535 0.26462115
> colMedians(tmp)
[1] 0.44112915 3.23153397 1.32475067 -1.12182777 0.72410325 0.15934154
[7] 1.07757640 0.57428144 -1.09439823 0.48806117 0.46652795 0.18499041
[13] 0.51497605 -0.69286626 -0.59813067 0.82203847 -0.17816981 -0.61484297
[19] -1.27427388 -1.11440864 -0.35318701 -0.27979035 -0.08774864 0.92557638
[25] 0.08116736 0.88890289 -1.31430910 -0.73257694 1.26009350 -0.97999188
[31] 1.80698012 0.44436327 0.36315533 -0.96172575 -1.56608615 0.83005723
[37] -1.18729499 -1.22245587 1.09671409 0.12092941 -0.91564759 0.08751060
[43] 2.14053755 0.14217415 -0.66891567 1.13317495 0.07951925 1.49842511
[49] 2.11031682 -1.83564589 -0.32774920 0.72728385 -1.21600516 -0.84640748
[55] -0.02756680 1.35489300 -1.47999747 0.77850352 -1.01363603 -1.68436266
[61] 0.43004290 0.77393270 0.39079679 0.66641718 0.09470890 -0.74144314
[67] 1.10294848 1.83524164 0.78679249 1.60599462 0.18030612 0.71498383
[73] 0.52187867 0.67223533 0.89860955 -1.92455519 2.05918529 0.91047941
[79] 0.92187734 0.76443956 -1.73885830 0.23298581 0.72277273 -0.90921988
[85] -0.40453768 -0.97018465 -0.69657081 -0.53129675 -0.39730586 0.15743259
[91] -0.09227643 -1.33057824 0.79016106 1.41006499 0.11628045 0.34845881
[97] 0.78219562 1.28036130 0.79145535 0.26462115
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.4411292 3.231534 1.324751 -1.121828 0.7241032 0.1593415 1.077576
[2,] 0.4411292 3.231534 1.324751 -1.121828 0.7241032 0.1593415 1.077576
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.5742814 -1.094398 0.4880612 0.466528 0.1849904 0.514976 -0.6928663
[2,] 0.5742814 -1.094398 0.4880612 0.466528 0.1849904 0.514976 -0.6928663
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.5981307 0.8220385 -0.1781698 -0.614843 -1.274274 -1.114409 -0.353187
[2,] -0.5981307 0.8220385 -0.1781698 -0.614843 -1.274274 -1.114409 -0.353187
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.2797903 -0.08774864 0.9255764 0.08116736 0.8889029 -1.314309 -0.7325769
[2,] -0.2797903 -0.08774864 0.9255764 0.08116736 0.8889029 -1.314309 -0.7325769
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.260094 -0.9799919 1.80698 0.4443633 0.3631553 -0.9617257 -1.566086
[2,] 1.260094 -0.9799919 1.80698 0.4443633 0.3631553 -0.9617257 -1.566086
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.8300572 -1.187295 -1.222456 1.096714 0.1209294 -0.9156476 0.0875106
[2,] 0.8300572 -1.187295 -1.222456 1.096714 0.1209294 -0.9156476 0.0875106
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 2.140538 0.1421741 -0.6689157 1.133175 0.07951925 1.498425 2.110317
[2,] 2.140538 0.1421741 -0.6689157 1.133175 0.07951925 1.498425 2.110317
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -1.835646 -0.3277492 0.7272839 -1.216005 -0.8464075 -0.0275668 1.354893
[2,] -1.835646 -0.3277492 0.7272839 -1.216005 -0.8464075 -0.0275668 1.354893
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -1.479997 0.7785035 -1.013636 -1.684363 0.4300429 0.7739327 0.3907968
[2,] -1.479997 0.7785035 -1.013636 -1.684363 0.4300429 0.7739327 0.3907968
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.6664172 0.0947089 -0.7414431 1.102948 1.835242 0.7867925 1.605995
[2,] 0.6664172 0.0947089 -0.7414431 1.102948 1.835242 0.7867925 1.605995
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.1803061 0.7149838 0.5218787 0.6722353 0.8986096 -1.924555 2.059185
[2,] 0.1803061 0.7149838 0.5218787 0.6722353 0.8986096 -1.924555 2.059185
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.9104794 0.9218773 0.7644396 -1.738858 0.2329858 0.7227727 -0.9092199
[2,] 0.9104794 0.9218773 0.7644396 -1.738858 0.2329858 0.7227727 -0.9092199
[,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.4045377 -0.9701846 -0.6965708 -0.5312968 -0.3973059 0.1574326
[2,] -0.4045377 -0.9701846 -0.6965708 -0.5312968 -0.3973059 0.1574326
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -0.09227643 -1.330578 0.7901611 1.410065 0.1162804 0.3484588 0.7821956
[2,] -0.09227643 -1.330578 0.7901611 1.410065 0.1162804 0.3484588 0.7821956
[,98] [,99] [,100]
[1,] 1.280361 0.7914553 0.2646211
[2,] 1.280361 0.7914553 0.2646211
>
>
> Max(tmp2)
[1] 2.506477
> Min(tmp2)
[1] -3.095228
> mean(tmp2)
[1] 0.02273271
> Sum(tmp2)
[1] 2.273271
> Var(tmp2)
[1] 0.935837
>
> rowMeans(tmp2)
[1] 1.177766044 0.747776910 -0.369419985 0.183092367 -0.191725646
[6] -2.184055284 0.748295293 -0.174296891 -3.095228201 0.905395380
[11] 0.926689011 -0.001984178 1.396305102 -0.553116905 -1.024886402
[16] -1.139132664 -1.938349567 -0.346126104 -0.645763171 -0.021008880
[21] 1.738395094 -2.020222900 -0.447070917 0.636224802 2.506477384
[26] 0.749710281 1.349078473 -0.802514289 -1.016900521 -0.062744645
[31] -1.299669050 0.995521806 1.942993609 1.042279011 -0.526603120
[36] -1.614363916 0.890509042 1.052533499 -0.061582439 1.299169749
[41] -0.014460483 -0.915107340 -0.040543654 0.233530776 0.439937800
[46] 0.414540388 0.301918685 0.979079669 -0.896440292 -1.125469355
[51] 0.007593134 -0.843047582 1.423901036 -0.693647422 0.426934504
[56] 0.192660771 0.550000509 -0.667256021 -0.289651730 -0.184067823
[61] 0.830037208 0.251096438 -0.486857773 -0.221173316 1.562913969
[66] -0.080786022 0.574042118 0.072621579 0.278838662 0.828511800
[71] -0.801928729 -0.808092632 -0.040131829 0.891801527 0.754920477
[76] 0.739719083 0.070818777 0.457534063 1.298754141 0.025504578
[81] 0.562959355 -1.078472777 -1.762565090 -0.416172703 0.130249182
[86] 1.804494383 -0.783888628 0.803471684 -0.426644924 -0.332370686
[91] -0.939099605 -0.370541288 -0.844399636 0.567979301 -0.686320382
[96] -0.294258327 -0.973469307 -0.447791118 0.965758692 0.544355813
> rowSums(tmp2)
[1] 1.177766044 0.747776910 -0.369419985 0.183092367 -0.191725646
[6] -2.184055284 0.748295293 -0.174296891 -3.095228201 0.905395380
[11] 0.926689011 -0.001984178 1.396305102 -0.553116905 -1.024886402
[16] -1.139132664 -1.938349567 -0.346126104 -0.645763171 -0.021008880
[21] 1.738395094 -2.020222900 -0.447070917 0.636224802 2.506477384
[26] 0.749710281 1.349078473 -0.802514289 -1.016900521 -0.062744645
[31] -1.299669050 0.995521806 1.942993609 1.042279011 -0.526603120
[36] -1.614363916 0.890509042 1.052533499 -0.061582439 1.299169749
[41] -0.014460483 -0.915107340 -0.040543654 0.233530776 0.439937800
[46] 0.414540388 0.301918685 0.979079669 -0.896440292 -1.125469355
[51] 0.007593134 -0.843047582 1.423901036 -0.693647422 0.426934504
[56] 0.192660771 0.550000509 -0.667256021 -0.289651730 -0.184067823
[61] 0.830037208 0.251096438 -0.486857773 -0.221173316 1.562913969
[66] -0.080786022 0.574042118 0.072621579 0.278838662 0.828511800
[71] -0.801928729 -0.808092632 -0.040131829 0.891801527 0.754920477
[76] 0.739719083 0.070818777 0.457534063 1.298754141 0.025504578
[81] 0.562959355 -1.078472777 -1.762565090 -0.416172703 0.130249182
[86] 1.804494383 -0.783888628 0.803471684 -0.426644924 -0.332370686
[91] -0.939099605 -0.370541288 -0.844399636 0.567979301 -0.686320382
[96] -0.294258327 -0.973469307 -0.447791118 0.965758692 0.544355813
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 1.177766044 0.747776910 -0.369419985 0.183092367 -0.191725646
[6] -2.184055284 0.748295293 -0.174296891 -3.095228201 0.905395380
[11] 0.926689011 -0.001984178 1.396305102 -0.553116905 -1.024886402
[16] -1.139132664 -1.938349567 -0.346126104 -0.645763171 -0.021008880
[21] 1.738395094 -2.020222900 -0.447070917 0.636224802 2.506477384
[26] 0.749710281 1.349078473 -0.802514289 -1.016900521 -0.062744645
[31] -1.299669050 0.995521806 1.942993609 1.042279011 -0.526603120
[36] -1.614363916 0.890509042 1.052533499 -0.061582439 1.299169749
[41] -0.014460483 -0.915107340 -0.040543654 0.233530776 0.439937800
[46] 0.414540388 0.301918685 0.979079669 -0.896440292 -1.125469355
[51] 0.007593134 -0.843047582 1.423901036 -0.693647422 0.426934504
[56] 0.192660771 0.550000509 -0.667256021 -0.289651730 -0.184067823
[61] 0.830037208 0.251096438 -0.486857773 -0.221173316 1.562913969
[66] -0.080786022 0.574042118 0.072621579 0.278838662 0.828511800
[71] -0.801928729 -0.808092632 -0.040131829 0.891801527 0.754920477
[76] 0.739719083 0.070818777 0.457534063 1.298754141 0.025504578
[81] 0.562959355 -1.078472777 -1.762565090 -0.416172703 0.130249182
[86] 1.804494383 -0.783888628 0.803471684 -0.426644924 -0.332370686
[91] -0.939099605 -0.370541288 -0.844399636 0.567979301 -0.686320382
[96] -0.294258327 -0.973469307 -0.447791118 0.965758692 0.544355813
> rowMin(tmp2)
[1] 1.177766044 0.747776910 -0.369419985 0.183092367 -0.191725646
[6] -2.184055284 0.748295293 -0.174296891 -3.095228201 0.905395380
[11] 0.926689011 -0.001984178 1.396305102 -0.553116905 -1.024886402
[16] -1.139132664 -1.938349567 -0.346126104 -0.645763171 -0.021008880
[21] 1.738395094 -2.020222900 -0.447070917 0.636224802 2.506477384
[26] 0.749710281 1.349078473 -0.802514289 -1.016900521 -0.062744645
[31] -1.299669050 0.995521806 1.942993609 1.042279011 -0.526603120
[36] -1.614363916 0.890509042 1.052533499 -0.061582439 1.299169749
[41] -0.014460483 -0.915107340 -0.040543654 0.233530776 0.439937800
[46] 0.414540388 0.301918685 0.979079669 -0.896440292 -1.125469355
[51] 0.007593134 -0.843047582 1.423901036 -0.693647422 0.426934504
[56] 0.192660771 0.550000509 -0.667256021 -0.289651730 -0.184067823
[61] 0.830037208 0.251096438 -0.486857773 -0.221173316 1.562913969
[66] -0.080786022 0.574042118 0.072621579 0.278838662 0.828511800
[71] -0.801928729 -0.808092632 -0.040131829 0.891801527 0.754920477
[76] 0.739719083 0.070818777 0.457534063 1.298754141 0.025504578
[81] 0.562959355 -1.078472777 -1.762565090 -0.416172703 0.130249182
[86] 1.804494383 -0.783888628 0.803471684 -0.426644924 -0.332370686
[91] -0.939099605 -0.370541288 -0.844399636 0.567979301 -0.686320382
[96] -0.294258327 -0.973469307 -0.447791118 0.965758692 0.544355813
>
> colMeans(tmp2)
[1] 0.02273271
> colSums(tmp2)
[1] 2.273271
> colVars(tmp2)
[1] 0.935837
> colSd(tmp2)
[1] 0.9673867
> colMax(tmp2)
[1] 2.506477
> colMin(tmp2)
[1] -3.095228
> colMedians(tmp2)
[1] -0.008222331
> colRanges(tmp2)
[,1]
[1,] -3.095228
[2,] 2.506477
>
> 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] -1.8021654 3.4405225 -2.5249134 -0.2704118 -1.1064977 1.4015597
[7] -1.3208935 0.8985403 -1.5850456 -1.4834752
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.9882298
[2,] -1.3898745
[3,] 0.3890071
[4,] 0.7571283
[5,] 1.2454630
>
> rowApply(tmp,sum)
[1] -4.4053903 -3.4475219 3.6198526 -0.1132018 0.2499027 -4.8722981
[7] 1.3118049 1.5630438 1.0178130 0.7232149
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 1 8 1 3 1 7 9 8 8
[2,] 9 6 4 10 5 10 10 4 4 5
[3,] 2 9 2 8 6 7 3 7 5 1
[4,] 10 3 10 2 9 6 1 3 6 6
[5,] 5 10 3 7 2 3 2 10 10 2
[6,] 8 4 5 6 7 8 9 6 1 9
[7,] 4 2 9 5 10 2 4 2 2 7
[8,] 1 8 7 4 4 9 8 8 7 10
[9,] 6 7 6 3 1 5 5 5 9 3
[10,] 3 5 1 9 8 4 6 1 3 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.48140517 0.05899565 0.22877960 -2.02108779 2.76303004 0.80355963
[7] 1.49007669 -0.70718324 -1.18032010 -3.04633427 2.42865755 -1.75652802
[13] 0.07818365 1.08137857 -0.58504414 -0.69589174 0.21901335 0.90186500
[19] -2.74495432 0.56270008
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.4539004
[2,] -1.3075662
[3,] -0.0485299
[4,] 0.2984846
[5,] 1.0301067
>
> rowApply(tmp,sum)
[1] 3.719295 4.414030 4.528155 -8.032087 -8.231902
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 1 9 16 16 3
[2,] 16 20 2 2 17
[3,] 7 7 17 19 6
[4,] 4 6 11 6 11
[5,] 12 15 9 15 20
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.4539004 0.7616785 -0.1522576 -0.5205503 0.4019572 1.1858924
[2,] -0.0485299 1.7250558 -0.4310973 -0.5026203 0.7834411 -0.6887193
[3,] 1.0301067 -1.1792437 1.2083753 0.2325370 -0.1398974 0.7113515
[4,] 0.2984846 -1.5396645 0.6388663 -1.0359511 0.1871601 -0.4845346
[5,] -1.3075662 0.2911696 -1.0351071 -0.1945031 1.5303690 0.0795697
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.07185852 0.2191076 0.7736655 0.2033737 0.4696828 -0.1935689
[2,] -0.30218446 0.4896168 -1.2596671 -0.7645396 0.7765185 1.2316894
[3,] 2.32094556 -0.7312505 0.1201760 -0.5149043 1.2272821 -1.3955612
[4,] -0.40691227 -0.5270949 -0.6904650 -1.3498222 -0.6243883 0.4470053
[5,] -0.19363066 -0.1575623 -0.1240295 -0.6204418 0.5795625 -1.8460926
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.3724198 1.59880084 -0.9725137 0.4140740 1.2226070 0.5726961
[2,] 1.2825592 0.19559261 0.4264024 0.5261867 1.0352096 1.6240902
[3,] -0.4229883 -0.67406784 0.9708032 1.4935329 -0.2822982 -0.6843001
[4,] -0.1798475 -0.01499714 0.1091140 -1.8282377 -1.3864802 0.4158761
[5,] -0.2291199 -0.02394991 -1.1188501 -1.3014476 -0.3700248 -1.0264972
[,19] [,20]
[1,] 0.03790907 -0.5487971
[2,] -0.51916773 -1.1658067
[3,] 0.41400695 0.8235494
[4,] -1.08962888 1.0294306
[5,] -1.58807373 0.4243240
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.11-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-3.11-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 644 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.11-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-3.11-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 -0.6730831 -0.4629374 0.06160437 0.5481491 -0.2320029 -1.664663 0.2619752
col8 col9 col10 col11 col12 col13 col14
row1 0.2698693 -1.0034 1.278972 -0.9751605 -1.219454 -0.5945084 0.8775254
col15 col16 col17 col18 col19 col20
row1 -0.376821 0.4430022 0.4015363 -1.294248 0.5001512 -0.490934
> tmp[,"col10"]
col10
row1 1.2789721
row2 -0.3962047
row3 -1.0528103
row4 0.9454441
row5 -0.8476476
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.6730831 -0.4629374 0.06160437 0.5481491 -0.23200294 -1.6646629
row5 1.3223330 1.4440013 0.82084805 -1.7327515 -0.05501528 -0.3354555
col7 col8 col9 col10 col11 col12 col13
row1 0.2619752 0.2698693 -1.003400 1.2789721 -0.9751605 -1.219454 -0.59450840
row5 1.7874396 0.2116565 -1.743663 -0.8476476 -1.7366852 -0.582624 -0.09081492
col14 col15 col16 col17 col18 col19
row1 0.87752540 -0.3768210 0.4430022 0.4015363 -1.294248 0.5001512
row5 -0.04344186 -0.4527134 -0.6491297 0.4175772 -1.420651 -0.5129810
col20
row1 -0.4909340
row5 -0.2205629
> tmp[,c("col6","col20")]
col6 col20
row1 -1.6646629 -0.49093398
row2 -1.1079433 1.35652639
row3 -0.5013239 0.20725062
row4 -0.2787879 -0.07566589
row5 -0.3354555 -0.22056288
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.6646629 -0.4909340
row5 -0.3354555 -0.2205629
>
>
>
>
> 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 49.0336 49.75909 51.80472 49.37255 49.69049 105.9783 49.0372 51.4894
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.82638 49.70628 50.7358 49.55958 49.65597 49.6365 50.5454 50.93378
col17 col18 col19 col20
row1 50.24363 49.68923 52.09609 105.2995
> tmp[,"col10"]
col10
row1 49.70628
row2 30.30080
row3 30.16090
row4 31.66184
row5 50.65666
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.03360 49.75909 51.80472 49.37255 49.69049 105.9783 49.03720 51.48940
row5 47.98478 50.24792 49.83727 50.37023 50.45565 104.5876 48.88598 48.64971
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.82638 49.70628 50.73580 49.55958 49.65597 49.63650 50.54540 50.93378
row5 51.09221 50.65666 47.93728 50.92784 51.59228 50.44834 49.36613 50.73309
col17 col18 col19 col20
row1 50.24363 49.68923 52.09609 105.2995
row5 49.10034 52.25505 49.59924 105.0923
> tmp[,c("col6","col20")]
col6 col20
row1 105.97830 105.29949
row2 76.53363 75.41743
row3 73.73896 76.29435
row4 75.84631 75.68677
row5 104.58760 105.09225
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.9783 105.2995
row5 104.5876 105.0923
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.9783 105.2995
row5 104.5876 105.0923
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.3937532
[2,] -0.1580079
[3,] 1.2036111
[4,] -0.2943479
[5,] 1.5213805
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.8398121 0.2889503
[2,] 0.9648761 0.2029694
[3,] 0.6153492 -1.4014390
[4,] 0.8577111 -0.4275224
[5,] 0.2444218 1.5914235
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.04260921 0.3397071
[2,] 1.51820143 2.7387367
[3,] -1.29258212 -0.7500748
[4,] -1.05476165 0.5725209
[5,] -1.52504434 -0.5047808
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.04260921
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.04260921
[2,] 1.51820143
>
>
>
> 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]
row3 0.08646136 -0.5577229 1.834628 -0.911920620 0.7926065 -2.0842640
row1 0.74414567 -0.3239105 0.579639 0.003908045 -0.3503487 -0.4361683
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 0.6425383 -0.6925287 -0.6418295 1.0079205 1.837805 -1.460227 1.030081
row1 2.1698088 0.3627149 -0.8951416 -0.5072308 -0.475207 1.229441 -1.503309
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.1078840 -0.3485139 -0.2923564 0.1621441 -2.0774897 -0.2394791
row1 -0.3638757 -2.3711398 -0.2275910 0.6326460 0.5120267 0.0468842
[,20]
row3 -0.7964063
row1 0.4780098
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.2902099 1.958107 -0.2341531 -0.2157298 0.6412327 -0.8990138 2.360624
[,8] [,9] [,10]
row2 0.5857483 0.3203744 -0.3847322
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.4262989 -2.621956 -1.195482 -0.625789 0.8775803 -1.529167 0.8683747
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.8927198 -0.07180973 -0.3756913 0.77187 0.2269292 -1.319066 0.0009604008
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.505336 -0.5650308 0.8618968 -0.03121656 0.5916508 -0.1581823
>
>
> 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: 0x5649c2283c80>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck/tests/BM702520fd3bf4"
[2] "/home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck/tests/BM7025105987a9"
[3] "/home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck/tests/BM7025413873b1"
[4] "/home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck/tests/BM702551264258"
[5] "/home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck/tests/BM702565701268"
[6] "/home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck/tests/BM70254d69a5b9"
[7] "/home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck/tests/BM702520ae0f7b"
[8] "/home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck/tests/BM702574d1bf1c"
[9] "/home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck/tests/BM70252932d12e"
[10] "/home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck/tests/BM70252ff8b52"
[11] "/home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck/tests/BM70251d58ae86"
[12] "/home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck/tests/BM7025387e01a4"
[13] "/home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck/tests/BM70256323f816"
[14] "/home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck/tests/BM7025bf3fe1b"
[15] "/home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck/tests/BM7025ef2eafe"
>
>
> ### 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: 0x5649c37b6580>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5649c37b6580>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.11-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5649c37b6580>
> rowMedians(tmp)
[1] -0.260421481 0.243112665 -0.144086744 -0.073254715 0.028155879
[6] 0.166848225 0.285043343 -0.097769750 0.400936836 0.457278630
[11] 0.314403999 0.323957043 -0.007838455 -0.176020484 0.500431368
[16] 0.106376400 0.248659615 0.228529850 0.182514644 -0.213402332
[21] 0.431637168 -0.093971351 0.183462315 -0.356611093 -0.219769140
[26] -0.390907165 0.291652802 -0.048680007 -0.249445831 -0.561408203
[31] 0.330819588 -0.188939769 0.190847400 -0.091785792 -0.015430041
[36] -0.445966573 0.090646363 0.351111781 -0.256260305 -0.175254759
[41] 0.415181051 0.307013731 -0.245330014 -0.175662829 0.517234751
[46] 0.007026112 -0.111866311 0.180689768 -0.265993266 -0.019114854
[51] -0.024329907 0.205154178 -0.038199229 0.028345862 0.193285601
[56] -0.542018608 -0.494067907 0.544896071 0.580781264 -0.044558378
[61] 0.361029461 -0.131039697 0.147917202 0.098485083 -0.189650560
[66] 0.410873214 0.631736461 -0.240797988 -0.007976078 0.304136461
[71] 0.063648527 0.009322872 0.206791583 -0.639539482 0.168688705
[76] 0.026740620 -0.213171393 0.354165575 -0.163634320 0.034749835
[81] 0.144454377 -0.019466076 -0.300832883 -0.490907460 -0.243754775
[86] -0.166460517 0.304320186 0.025069232 0.158045165 -0.547536446
[91] 0.066382371 0.105299383 -0.100419729 -0.074988152 0.420319020
[96] -0.168293362 0.001194618 -0.037968401 -0.105406288 0.120072706
[101] -0.076057443 -0.229229376 0.226628123 0.576688148 0.436481458
[106] 0.068906536 0.500899129 0.372967244 0.090545498 0.114978754
[111] -0.013991687 0.013311286 -0.025247509 -0.519763270 0.090525796
[116] -0.227803770 0.283129825 -0.491699105 -0.351608596 -0.277785448
[121] -0.893803386 0.211903517 0.396760287 -0.142781167 -0.063292674
[126] 0.064202566 0.080811245 0.070793941 0.067590829 0.739450579
[131] -0.639632251 0.002637569 -0.150551792 0.160541629 -0.118198038
[136] 0.118668606 0.497372895 0.499940780 0.068584679 -1.002073192
[141] 0.667125709 -0.136757996 -0.062377850 0.054569356 -0.165212151
[146] -0.041228006 -0.527045339 0.680889763 -0.136539668 -0.070796573
[151] -0.134563626 -0.092883320 0.043924549 0.244770804 -0.260253319
[156] -0.331109304 0.740361283 -0.022999654 -0.085439375 -0.032796950
[161] 0.605584018 0.395929581 0.322809292 0.204512043 0.655516046
[166] -0.413151656 0.200819578 0.299484939 -0.040985605 0.465588911
[171] 0.092425437 0.220400374 -0.171997726 -0.671391824 0.071374740
[176] -0.325285352 0.051848236 0.213204934 -0.376327889 -0.154265658
[181] -0.116362587 -0.660422702 0.009372986 -0.119828425 0.387856726
[186] -0.628612846 0.135580699 -0.429970579 -0.188317293 -0.038850058
[191] 0.283023093 0.273676531 -0.279026024 0.193717874 -0.279224032
[196] -0.090913112 -0.288317138 -0.459371031 -0.171074273 -0.304367713
[201] -0.482944326 -0.166988418 -0.161562597 0.623223771 0.131738036
[206] 0.113104970 0.403372705 0.016810009 0.361512438 -0.115885915
[211] 0.151279455 0.273609652 0.130060850 -0.227722273 0.453647087
[216] -0.460674890 -0.992296396 -0.048033226 -0.384866002 -0.481763443
[221] 0.434474719 -0.370168264 -0.082388300 0.482803880 0.093014633
[226] 0.145259803 -0.116985431 0.148771294 -0.155087043 0.114587824
>
> proc.time()
user system elapsed
2.396 0.935 3.372
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.0.3 (2020-10-10) -- "Bunny-Wunnies Freak Out"
Copyright (C) 2020 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: 0x562cfefd23a0>
> .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: 0x562cfefd23a0>
> .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: 0x562cfefd23a0>
> .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: 0x562cfefd23a0>
> 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: 0x562d00fed5e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x562d00fed5e0>
> .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: 0x562d00fed5e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x562d00fed5e0>
> .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: 0x562d00fed5e0>
> 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: 0x562cfeb57880>
> .Call("R_bm_AddColumn",P)
<pointer: 0x562cfeb57880>
> .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: 0x562cfeb57880>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x562cfeb57880>
> .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: 0x562cfeb57880>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x562cfeb57880>
> .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: 0x562cfeb57880>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x562cfeb57880>
> .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: 0x562cfeb57880>
> 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: 0x562d00e8de70>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x562d00e8de70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x562d00e8de70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x562d00e8de70>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile704a428c4458" "BufferedMatrixFile704a7d744c94"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile704a428c4458" "BufferedMatrixFile704a7d744c94"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x562cfeb16820>
> .Call("R_bm_AddColumn",P)
<pointer: 0x562cfeb16820>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x562cfeb16820>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x562cfeb16820>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x562cfeb16820>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x562cfeb16820>
> .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: 0x562d007efd50>
> .Call("R_bm_AddColumn",P)
<pointer: 0x562d007efd50>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x562d007efd50>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x562d007efd50>
> 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: 0x562d010f5e00>
> .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: 0x562d010f5e00>
> rm(P)
>
> proc.time()
user system elapsed
0.453 0.041 0.479
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.0.3 (2020-10-10) -- "Bunny-Wunnies Freak Out"
Copyright (C) 2020 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
0.446 0.066 0.496