Ben Bolstad
| Snapshot Date: 2019-04-15 17:01:12 -0400 (Mon, 15 Apr 2019) |
| URL: https://git.bioconductor.org/packages/BufferedMatrix |
| Branch: RELEASE_3_8 |
| Last Commit: 9fb17da |
| Last Changed Date: 2018-10-30 11:41:43 -0400 (Tue, 30 Oct 2018) |
| Back to Multiple platform build/check report for BioC 3.8 |
|
This page was generated on 2019-04-16 11:48:17 -0400 (Tue, 16 Apr 2019).
| Package 183/1649 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||
| BufferedMatrix 1.46.0 Ben Bolstad
| malbec1 | Linux (Ubuntu 16.04.6 LTS) / x86_64 | OK | OK | [ OK ] | | ||||||
| merida1 | OS X 10.11.6 El Capitan / x86_64 | OK | OK | OK | OK | |
| Package: BufferedMatrix |
| Version: 1.46.0 |
| Command: /home/biocbuild/bbs-3.8-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.8-bioc/R/library --no-vignettes --timings BufferedMatrix_1.46.0.tar.gz |
| StartedAt: 2019-04-15 22:36:00 -0400 (Mon, 15 Apr 2019) |
| EndedAt: 2019-04-15 22:36:22 -0400 (Mon, 15 Apr 2019) |
| EllapsedTime: 22.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.8-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.8-bioc/R/library --no-vignettes --timings BufferedMatrix_1.46.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck’ * using R version 3.5.3 (2019-03-11) * 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 ‘1.46.0’ * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking whether package ‘BufferedMatrix’ can be installed ... OK * checking installed package size ... OK * checking package directory ... OK * checking ‘build’ directory ... OK * checking DESCRIPTION meta-information ... OK * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking R files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... OK * checking whether the package can be loaded with stated dependencies ... OK * checking whether the package can be unloaded cleanly ... OK * checking whether the namespace can be loaded with stated dependencies ... OK * checking whether the namespace can be unloaded cleanly ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... OK * checking Rd files ... NOTE prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples * checking Rd metadata ... OK * checking Rd cross-references ... OK * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking line endings in C/C++/Fortran sources/headers ... OK * checking compiled code ... NOTE Note: information on .o files is not available * checking 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-3.8-bioc/meat/BufferedMatrix.Rcheck/00check.log’ for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.8-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.8-bioc/R/library’
* installing *source* package ‘BufferedMatrix’ ...
** libs
gcc -I"/home/biocbuild/bbs-3.8-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.8-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘˜’ [-Wparentheses]
if (!(Matrix->readonly) & setting){
^
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
gcc -I"/home/biocbuild/bbs-3.8-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-3.8-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-3.8-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-3.8-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.8-bioc/R/library/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 3.5.3 (2019-03-11) -- "Great Truth"
Copyright (C) 2019 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.320 0.020 0.339
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 3.5.3 (2019-03-11) -- "Great Truth"
Copyright (C) 2019 The R Foundation for Statistical Computing
Platform: x86_64-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-3.8-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 406860 21.8 845382 45.2 634148 33.9
Vcells 736743 5.7 8388608 64.0 1798391 13.8
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Mon Apr 15 22:36:16 2019"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Mon Apr 15 22:36:16 2019"
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
>
>
> RowMode(tmp2)
<pointer: 0x29dc370>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Mon Apr 15 22:36:17 2019"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Mon Apr 15 22:36:17 2019"
>
> ColMode(tmp2)
<pointer: 0x29dc370>
>
>
>
> ### 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,] 100.663787494 -0.5559515 0.0001069126 0.04749422
[2,] -1.044327131 -0.8824559 -0.2460498636 0.14421062
[3,] 0.003761096 0.8575826 -0.0558483858 -0.12486417
[4,] -0.809117288 -0.3097809 -1.3413988975 1.57106919
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 1.006638e+02 0.5559515 0.0001069126 0.04749422
[2,] 1.044327e+00 0.8824559 0.2460498636 0.14421062
[3,] 3.761096e-03 0.8575826 0.0558483858 0.12486417
[4,] 8.091173e-01 0.3097809 1.3413988975 1.57106919
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.03313448 0.7456216 0.01033986 0.2179317
[2,] 1.02192325 0.9393912 0.49603414 0.3797507
[3,] 0.06132778 0.9260575 0.23632263 0.3533612
[4,] 0.89950947 0.5565797 1.15818776 1.2534230
>
> 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-3.8-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.99513 33.01217 25.10351 27.22681
[2,] 36.26356 35.27637 30.20639 28.94172
[3,] 25.61704 35.11816 27.41907 28.65848
[4,] 34.80421 30.87558 37.92328 39.10530
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x220a950>
> exp(tmp5)
<pointer: 0x220a950>
> log(tmp5,2)
<pointer: 0x220a950>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.3793
> Min(tmp5)
[1] 52.24966
> mean(tmp5)
[1] 73.21562
> Sum(tmp5)
[1] 14643.12
> Var(tmp5)
[1] 860.1706
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 86.89177 72.90897 67.13919 73.47513 73.87699 73.25367 70.00694 73.76497
[9] 71.71662 69.12191
> rowSums(tmp5)
[1] 1737.835 1458.179 1342.784 1469.503 1477.540 1465.073 1400.139 1475.299
[9] 1434.332 1382.438
> rowVars(tmp5)
[1] 8238.36618 46.87150 55.37921 46.06078 45.79126 55.36902
[7] 38.73011 58.79547 80.34537 75.90652
> rowSd(tmp5)
[1] 90.765446 6.846276 7.441721 6.786809 6.766924 7.441036 6.223352
[8] 7.667820 8.963558 8.712435
> rowMax(tmp5)
[1] 470.37926 83.10843 81.61502 82.74823 85.16877 84.52577 84.12462
[8] 87.98395 85.63825 81.36823
> rowMin(tmp5)
[1] 52.24966 60.23839 53.31851 59.07214 63.07937 57.02811 58.83207 61.07663
[9] 54.76266 55.01603
>
> colMeans(tmp5)
[1] 110.52595 69.70236 69.55019 68.77290 68.88871 71.09743 72.87633
[8] 73.80321 73.65258 70.05671 71.50693 70.63895 73.51437 70.71530
[15] 72.00661 71.25288 73.18283 72.87605 68.75673 70.93530
> colSums(tmp5)
[1] 1105.2595 697.0236 695.5019 687.7290 688.8871 710.9743 728.7633
[8] 738.0321 736.5258 700.5671 715.0693 706.3895 735.1437 707.1530
[15] 720.0661 712.5288 731.8283 728.7605 687.5673 709.3530
> colVars(tmp5)
[1] 16058.99163 54.20005 120.33511 82.57215 67.75073 86.66954
[7] 24.86061 90.98591 57.44705 35.18453 67.32797 23.17849
[13] 73.12204 55.35842 60.70293 61.07909 64.46535 98.08516
[19] 97.55413 52.98296
> colSd(tmp5)
[1] 126.724077 7.362068 10.969736 9.086922 8.231083 9.309648
[7] 4.986042 9.538653 7.579383 5.931655 8.205362 4.814405
[13] 8.551142 7.440324 7.791208 7.815311 8.029031 9.903795
[19] 9.876949 7.278940
> colMax(tmp5)
[1] 470.37926 82.91893 84.28378 81.39256 82.39040 84.96853 79.93147
[8] 85.16226 85.16877 81.16894 81.61502 78.04484 84.52577 80.42241
[15] 87.98395 84.73823 87.21393 85.63825 82.19474 81.91091
> colMin(tmp5)
[1] 53.31851 59.43849 52.24966 56.66904 54.76266 59.07214 66.15697 58.62608
[9] 60.43045 61.78363 58.95016 63.78512 63.75532 57.75302 63.06668 59.14362
[17] 55.01603 54.46010 53.22903 58.01656
>
>
> ### 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] 86.89177 72.90897 67.13919 73.47513 NA 73.25367 70.00694 73.76497
[9] 71.71662 69.12191
> rowSums(tmp5)
[1] 1737.835 1458.179 1342.784 1469.503 NA 1465.073 1400.139 1475.299
[9] 1434.332 1382.438
> rowVars(tmp5)
[1] 8238.36618 46.87150 55.37921 46.06078 47.10370 55.36902
[7] 38.73011 58.79547 80.34537 75.90652
> rowSd(tmp5)
[1] 90.765446 6.846276 7.441721 6.786809 6.863214 7.441036 6.223352
[8] 7.667820 8.963558 8.712435
> rowMax(tmp5)
[1] 470.37926 83.10843 81.61502 82.74823 NA 84.52577 84.12462
[8] 87.98395 85.63825 81.36823
> rowMin(tmp5)
[1] 52.24966 60.23839 53.31851 59.07214 NA 57.02811 58.83207 61.07663
[9] 54.76266 55.01603
>
> colMeans(tmp5)
[1] 110.52595 69.70236 69.55019 68.77290 68.88871 71.09743 72.87633
[8] 73.80321 73.65258 70.05671 71.50693 70.63895 73.51437 NA
[15] 72.00661 71.25288 73.18283 72.87605 68.75673 70.93530
> colSums(tmp5)
[1] 1105.2595 697.0236 695.5019 687.7290 688.8871 710.9743 728.7633
[8] 738.0321 736.5258 700.5671 715.0693 706.3895 735.1437 NA
[15] 720.0661 712.5288 731.8283 728.7605 687.5673 709.3530
> colVars(tmp5)
[1] 16058.99163 54.20005 120.33511 82.57215 67.75073 86.66954
[7] 24.86061 90.98591 57.44705 35.18453 67.32797 23.17849
[13] 73.12204 NA 60.70293 61.07909 64.46535 98.08516
[19] 97.55413 52.98296
> colSd(tmp5)
[1] 126.724077 7.362068 10.969736 9.086922 8.231083 9.309648
[7] 4.986042 9.538653 7.579383 5.931655 8.205362 4.814405
[13] 8.551142 NA 7.791208 7.815311 8.029031 9.903795
[19] 9.876949 7.278940
> colMax(tmp5)
[1] 470.37926 82.91893 84.28378 81.39256 82.39040 84.96853 79.93147
[8] 85.16226 85.16877 81.16894 81.61502 78.04484 84.52577 NA
[15] 87.98395 84.73823 87.21393 85.63825 82.19474 81.91091
> colMin(tmp5)
[1] 53.31851 59.43849 52.24966 56.66904 54.76266 59.07214 66.15697 58.62608
[9] 60.43045 61.78363 58.95016 63.78512 63.75532 NA 63.06668 59.14362
[17] 55.01603 54.46010 53.22903 58.01656
>
> Max(tmp5,na.rm=TRUE)
[1] 470.3793
> Min(tmp5,na.rm=TRUE)
[1] 52.24966
> mean(tmp5,na.rm=TRUE)
[1] 73.18923
> Sum(tmp5,na.rm=TRUE)
[1] 14564.66
> Var(tmp5,na.rm=TRUE)
[1] 864.375
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 86.89177 72.90897 67.13919 73.47513 73.63546 73.25367 70.00694 73.76497
[9] 71.71662 69.12191
> rowSums(tmp5,na.rm=TRUE)
[1] 1737.835 1458.179 1342.784 1469.503 1399.074 1465.073 1400.139 1475.299
[9] 1434.332 1382.438
> rowVars(tmp5,na.rm=TRUE)
[1] 8238.36618 46.87150 55.37921 46.06078 47.10370 55.36902
[7] 38.73011 58.79547 80.34537 75.90652
> rowSd(tmp5,na.rm=TRUE)
[1] 90.765446 6.846276 7.441721 6.786809 6.863214 7.441036 6.223352
[8] 7.667820 8.963558 8.712435
> rowMax(tmp5,na.rm=TRUE)
[1] 470.37926 83.10843 81.61502 82.74823 85.16877 84.52577 84.12462
[8] 87.98395 85.63825 81.36823
> rowMin(tmp5,na.rm=TRUE)
[1] 52.24966 60.23839 53.31851 59.07214 63.07937 57.02811 58.83207 61.07663
[9] 54.76266 55.01603
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.52595 69.70236 69.55019 68.77290 68.88871 71.09743 72.87633
[8] 73.80321 73.65258 70.05671 71.50693 70.63895 73.51437 69.85411
[15] 72.00661 71.25288 73.18283 72.87605 68.75673 70.93530
> colSums(tmp5,na.rm=TRUE)
[1] 1105.2595 697.0236 695.5019 687.7290 688.8871 710.9743 728.7633
[8] 738.0321 736.5258 700.5671 715.0693 706.3895 735.1437 628.6870
[15] 720.0661 712.5288 731.8283 728.7605 687.5673 709.3530
> colVars(tmp5,na.rm=TRUE)
[1] 16058.99163 54.20005 120.33511 82.57215 67.75073 86.66954
[7] 24.86061 90.98591 57.44705 35.18453 67.32797 23.17849
[13] 73.12204 53.93473 60.70293 61.07909 64.46535 98.08516
[19] 97.55413 52.98296
> colSd(tmp5,na.rm=TRUE)
[1] 126.724077 7.362068 10.969736 9.086922 8.231083 9.309648
[7] 4.986042 9.538653 7.579383 5.931655 8.205362 4.814405
[13] 8.551142 7.344027 7.791208 7.815311 8.029031 9.903795
[19] 9.876949 7.278940
> colMax(tmp5,na.rm=TRUE)
[1] 470.37926 82.91893 84.28378 81.39256 82.39040 84.96853 79.93147
[8] 85.16226 85.16877 81.16894 81.61502 78.04484 84.52577 80.42241
[15] 87.98395 84.73823 87.21393 85.63825 82.19474 81.91091
> colMin(tmp5,na.rm=TRUE)
[1] 53.31851 59.43849 52.24966 56.66904 54.76266 59.07214 66.15697 58.62608
[9] 60.43045 61.78363 58.95016 63.78512 63.75532 57.75302 63.06668 59.14362
[17] 55.01603 54.46010 53.22903 58.01656
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 86.89177 72.90897 67.13919 73.47513 NaN 73.25367 70.00694 73.76497
[9] 71.71662 69.12191
> rowSums(tmp5,na.rm=TRUE)
[1] 1737.835 1458.179 1342.784 1469.503 0.000 1465.073 1400.139 1475.299
[9] 1434.332 1382.438
> rowVars(tmp5,na.rm=TRUE)
[1] 8238.36618 46.87150 55.37921 46.06078 NA 55.36902
[7] 38.73011 58.79547 80.34537 75.90652
> rowSd(tmp5,na.rm=TRUE)
[1] 90.765446 6.846276 7.441721 6.786809 NA 7.441036 6.223352
[8] 7.667820 8.963558 8.712435
> rowMax(tmp5,na.rm=TRUE)
[1] 470.37926 83.10843 81.61502 82.74823 NA 84.52577 84.12462
[8] 87.98395 85.63825 81.36823
> rowMin(tmp5,na.rm=TRUE)
[1] 52.24966 60.23839 53.31851 59.07214 NA 57.02811 58.83207 61.07663
[9] 54.76266 55.01603
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.09477 69.09667 70.24335 68.73717 68.45717 69.55619 73.20393
[8] 74.99474 72.37300 69.88165 70.79335 70.27908 74.59871 NaN
[15] 72.36560 71.19019 73.57068 72.57280 67.26361 69.71579
> colSums(tmp5,na.rm=TRUE)
[1] 1026.8529 621.8701 632.1902 618.6345 616.1145 626.0057 658.8354
[8] 674.9527 651.3570 628.9349 637.1402 632.5117 671.3884 0.0000
[15] 651.2904 640.7117 662.1361 653.1552 605.3725 627.4421
> colVars(tmp5,na.rm=TRUE)
[1] 17923.08026 56.84800 129.97166 92.87930 74.12449 70.77998
[7] 26.76079 86.38684 46.20811 39.23783 70.01556 24.61887
[13] 69.03465 NA 66.84097 68.66976 70.83121 109.31129
[19] 84.66782 42.87470
> colSd(tmp5,na.rm=TRUE)
[1] 133.877109 7.539761 11.400512 9.637391 8.609558 8.413084
[7] 5.173083 9.294452 6.797654 6.264011 8.367530 4.961741
[13] 8.308709 NA 8.175633 8.286722 8.416128 10.455204
[19] 9.201512 6.547878
> colMax(tmp5,na.rm=TRUE)
[1] 470.37926 82.91893 84.28378 81.39256 82.39040 82.74581 79.93147
[8] 85.16226 82.74823 81.16894 81.61502 78.04484 84.52577 -Inf
[15] 87.98395 84.73823 87.21393 85.63825 81.36823 81.62904
> colMin(tmp5,na.rm=TRUE)
[1] 53.31851 59.43849 52.24966 56.66904 54.76266 59.07214 66.15697 58.62608
[9] 60.43045 61.78363 58.95016 63.78512 66.83898 Inf 63.06668 59.14362
[17] 55.01603 54.46010 53.22903 58.01656
>
>
>
>
> 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] 176.6884 213.6471 210.8850 214.5544 204.4230 122.6439 185.9767 175.7081
[9] 134.5004 131.0195
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 176.6884 213.6471 210.8850 214.5544 204.4230 122.6439 185.9767 175.7081
[9] 134.5004 131.0195
>
>
>
> 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] -2.842171e-14 4.263256e-14 -2.842171e-14 1.421085e-14 -1.705303e-13
[6] 0.000000e+00 5.684342e-14 -1.705303e-13 5.684342e-14 -2.842171e-14
[11] -2.842171e-14 5.684342e-14 -3.410605e-13 -1.421085e-13 1.421085e-14
[16] 0.000000e+00 -2.273737e-13 -4.263256e-14 2.273737e-13 -5.684342e-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)
+ }
1 11
6 19
6 8
9 1
3 11
4 7
7 11
1 6
6 20
6 14
7 17
8 20
6 12
4 6
2 12
5 11
6 3
8 1
4 14
2 12
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.325224
> Min(tmp)
[1] -2.565316
> mean(tmp)
[1] -0.02914097
> Sum(tmp)
[1] -2.914097
> Var(tmp)
[1] 0.9562141
>
> rowMeans(tmp)
[1] -0.02914097
> rowSums(tmp)
[1] -2.914097
> rowVars(tmp)
[1] 0.9562141
> rowSd(tmp)
[1] 0.977862
> rowMax(tmp)
[1] 2.325224
> rowMin(tmp)
[1] -2.565316
>
> colMeans(tmp)
[1] 1.4541699352 1.4914947203 -1.2189079150 0.1063380335 -1.8185715333
[6] -0.2597950967 -0.4029011139 -0.8926926521 0.0083599151 1.0854292598
[11] -0.3881600711 0.6641545546 0.3122224127 -0.8604799718 0.0239186151
[16] 0.2192066835 -0.8632118139 -2.5653163857 -0.6149168270 0.2705954683
[21] 0.5475052029 1.2750898509 0.5911192314 0.7986655177 0.5202099658
[26] -0.2666159738 -1.7806786203 0.0819753636 -1.5063085747 0.6714565911
[31] -0.1904330309 -0.0559431939 0.0136169374 0.8746419411 -1.1003420682
[36] -1.2467681769 1.5042333803 -0.7145552502 -2.4181332638 1.0590631038
[41] 0.9923066752 1.4688699888 -0.2425458770 -1.1784689907 -1.6394480684
[46] -1.2777663246 0.0001203863 0.0419465756 -0.6510042489 -0.9125070544
[51] 0.5657268756 0.6303569241 -0.1596329475 -0.7403471284 0.9253689643
[56] 0.1184405295 -1.2994730326 -0.5818616707 1.1788055063 0.3346169163
[61] 1.2575908982 -0.7460221910 0.0733326000 0.3534498517 0.0223019548
[66] -0.8865263993 -0.3117035091 -0.0193951076 -0.4378603282 -1.0969215392
[71] 0.1198167932 1.2029848543 0.5462165179 1.5002282843 -0.8792829955
[76] 1.2352176550 1.5541684232 0.2813462584 -1.9094642495 -1.1910572650
[81] 2.3252236244 0.6340589120 -0.3721634767 0.1894640290 -0.0032617051
[86] -1.8526179976 0.0791898862 1.3448043307 0.8554124489 -0.9092969251
[91] 1.5053921932 -0.1467415276 0.4868831070 0.1713320620 -1.0665150681
[96] -0.3070453348 0.6715369541 0.5701989676 0.0220483436 0.2373403678
> colSums(tmp)
[1] 1.4541699352 1.4914947203 -1.2189079150 0.1063380335 -1.8185715333
[6] -0.2597950967 -0.4029011139 -0.8926926521 0.0083599151 1.0854292598
[11] -0.3881600711 0.6641545546 0.3122224127 -0.8604799718 0.0239186151
[16] 0.2192066835 -0.8632118139 -2.5653163857 -0.6149168270 0.2705954683
[21] 0.5475052029 1.2750898509 0.5911192314 0.7986655177 0.5202099658
[26] -0.2666159738 -1.7806786203 0.0819753636 -1.5063085747 0.6714565911
[31] -0.1904330309 -0.0559431939 0.0136169374 0.8746419411 -1.1003420682
[36] -1.2467681769 1.5042333803 -0.7145552502 -2.4181332638 1.0590631038
[41] 0.9923066752 1.4688699888 -0.2425458770 -1.1784689907 -1.6394480684
[46] -1.2777663246 0.0001203863 0.0419465756 -0.6510042489 -0.9125070544
[51] 0.5657268756 0.6303569241 -0.1596329475 -0.7403471284 0.9253689643
[56] 0.1184405295 -1.2994730326 -0.5818616707 1.1788055063 0.3346169163
[61] 1.2575908982 -0.7460221910 0.0733326000 0.3534498517 0.0223019548
[66] -0.8865263993 -0.3117035091 -0.0193951076 -0.4378603282 -1.0969215392
[71] 0.1198167932 1.2029848543 0.5462165179 1.5002282843 -0.8792829955
[76] 1.2352176550 1.5541684232 0.2813462584 -1.9094642495 -1.1910572650
[81] 2.3252236244 0.6340589120 -0.3721634767 0.1894640290 -0.0032617051
[86] -1.8526179976 0.0791898862 1.3448043307 0.8554124489 -0.9092969251
[91] 1.5053921932 -0.1467415276 0.4868831070 0.1713320620 -1.0665150681
[96] -0.3070453348 0.6715369541 0.5701989676 0.0220483436 0.2373403678
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] 1.4541699352 1.4914947203 -1.2189079150 0.1063380335 -1.8185715333
[6] -0.2597950967 -0.4029011139 -0.8926926521 0.0083599151 1.0854292598
[11] -0.3881600711 0.6641545546 0.3122224127 -0.8604799718 0.0239186151
[16] 0.2192066835 -0.8632118139 -2.5653163857 -0.6149168270 0.2705954683
[21] 0.5475052029 1.2750898509 0.5911192314 0.7986655177 0.5202099658
[26] -0.2666159738 -1.7806786203 0.0819753636 -1.5063085747 0.6714565911
[31] -0.1904330309 -0.0559431939 0.0136169374 0.8746419411 -1.1003420682
[36] -1.2467681769 1.5042333803 -0.7145552502 -2.4181332638 1.0590631038
[41] 0.9923066752 1.4688699888 -0.2425458770 -1.1784689907 -1.6394480684
[46] -1.2777663246 0.0001203863 0.0419465756 -0.6510042489 -0.9125070544
[51] 0.5657268756 0.6303569241 -0.1596329475 -0.7403471284 0.9253689643
[56] 0.1184405295 -1.2994730326 -0.5818616707 1.1788055063 0.3346169163
[61] 1.2575908982 -0.7460221910 0.0733326000 0.3534498517 0.0223019548
[66] -0.8865263993 -0.3117035091 -0.0193951076 -0.4378603282 -1.0969215392
[71] 0.1198167932 1.2029848543 0.5462165179 1.5002282843 -0.8792829955
[76] 1.2352176550 1.5541684232 0.2813462584 -1.9094642495 -1.1910572650
[81] 2.3252236244 0.6340589120 -0.3721634767 0.1894640290 -0.0032617051
[86] -1.8526179976 0.0791898862 1.3448043307 0.8554124489 -0.9092969251
[91] 1.5053921932 -0.1467415276 0.4868831070 0.1713320620 -1.0665150681
[96] -0.3070453348 0.6715369541 0.5701989676 0.0220483436 0.2373403678
> colMin(tmp)
[1] 1.4541699352 1.4914947203 -1.2189079150 0.1063380335 -1.8185715333
[6] -0.2597950967 -0.4029011139 -0.8926926521 0.0083599151 1.0854292598
[11] -0.3881600711 0.6641545546 0.3122224127 -0.8604799718 0.0239186151
[16] 0.2192066835 -0.8632118139 -2.5653163857 -0.6149168270 0.2705954683
[21] 0.5475052029 1.2750898509 0.5911192314 0.7986655177 0.5202099658
[26] -0.2666159738 -1.7806786203 0.0819753636 -1.5063085747 0.6714565911
[31] -0.1904330309 -0.0559431939 0.0136169374 0.8746419411 -1.1003420682
[36] -1.2467681769 1.5042333803 -0.7145552502 -2.4181332638 1.0590631038
[41] 0.9923066752 1.4688699888 -0.2425458770 -1.1784689907 -1.6394480684
[46] -1.2777663246 0.0001203863 0.0419465756 -0.6510042489 -0.9125070544
[51] 0.5657268756 0.6303569241 -0.1596329475 -0.7403471284 0.9253689643
[56] 0.1184405295 -1.2994730326 -0.5818616707 1.1788055063 0.3346169163
[61] 1.2575908982 -0.7460221910 0.0733326000 0.3534498517 0.0223019548
[66] -0.8865263993 -0.3117035091 -0.0193951076 -0.4378603282 -1.0969215392
[71] 0.1198167932 1.2029848543 0.5462165179 1.5002282843 -0.8792829955
[76] 1.2352176550 1.5541684232 0.2813462584 -1.9094642495 -1.1910572650
[81] 2.3252236244 0.6340589120 -0.3721634767 0.1894640290 -0.0032617051
[86] -1.8526179976 0.0791898862 1.3448043307 0.8554124489 -0.9092969251
[91] 1.5053921932 -0.1467415276 0.4868831070 0.1713320620 -1.0665150681
[96] -0.3070453348 0.6715369541 0.5701989676 0.0220483436 0.2373403678
> colMedians(tmp)
[1] 1.4541699352 1.4914947203 -1.2189079150 0.1063380335 -1.8185715333
[6] -0.2597950967 -0.4029011139 -0.8926926521 0.0083599151 1.0854292598
[11] -0.3881600711 0.6641545546 0.3122224127 -0.8604799718 0.0239186151
[16] 0.2192066835 -0.8632118139 -2.5653163857 -0.6149168270 0.2705954683
[21] 0.5475052029 1.2750898509 0.5911192314 0.7986655177 0.5202099658
[26] -0.2666159738 -1.7806786203 0.0819753636 -1.5063085747 0.6714565911
[31] -0.1904330309 -0.0559431939 0.0136169374 0.8746419411 -1.1003420682
[36] -1.2467681769 1.5042333803 -0.7145552502 -2.4181332638 1.0590631038
[41] 0.9923066752 1.4688699888 -0.2425458770 -1.1784689907 -1.6394480684
[46] -1.2777663246 0.0001203863 0.0419465756 -0.6510042489 -0.9125070544
[51] 0.5657268756 0.6303569241 -0.1596329475 -0.7403471284 0.9253689643
[56] 0.1184405295 -1.2994730326 -0.5818616707 1.1788055063 0.3346169163
[61] 1.2575908982 -0.7460221910 0.0733326000 0.3534498517 0.0223019548
[66] -0.8865263993 -0.3117035091 -0.0193951076 -0.4378603282 -1.0969215392
[71] 0.1198167932 1.2029848543 0.5462165179 1.5002282843 -0.8792829955
[76] 1.2352176550 1.5541684232 0.2813462584 -1.9094642495 -1.1910572650
[81] 2.3252236244 0.6340589120 -0.3721634767 0.1894640290 -0.0032617051
[86] -1.8526179976 0.0791898862 1.3448043307 0.8554124489 -0.9092969251
[91] 1.5053921932 -0.1467415276 0.4868831070 0.1713320620 -1.0665150681
[96] -0.3070453348 0.6715369541 0.5701989676 0.0220483436 0.2373403678
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.45417 1.491495 -1.218908 0.106338 -1.818572 -0.2597951 -0.4029011
[2,] 1.45417 1.491495 -1.218908 0.106338 -1.818572 -0.2597951 -0.4029011
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.8926927 0.008359915 1.085429 -0.3881601 0.6641546 0.3122224 -0.86048
[2,] -0.8926927 0.008359915 1.085429 -0.3881601 0.6641546 0.3122224 -0.86048
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.02391862 0.2192067 -0.8632118 -2.565316 -0.6149168 0.2705955 0.5475052
[2,] 0.02391862 0.2192067 -0.8632118 -2.565316 -0.6149168 0.2705955 0.5475052
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.27509 0.5911192 0.7986655 0.52021 -0.266616 -1.780679 0.08197536
[2,] 1.27509 0.5911192 0.7986655 0.52021 -0.266616 -1.780679 0.08197536
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.506309 0.6714566 -0.190433 -0.05594319 0.01361694 0.8746419 -1.100342
[2,] -1.506309 0.6714566 -0.190433 -0.05594319 0.01361694 0.8746419 -1.100342
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.246768 1.504233 -0.7145553 -2.418133 1.059063 0.9923067 1.46887
[2,] -1.246768 1.504233 -0.7145553 -2.418133 1.059063 0.9923067 1.46887
[,43] [,44] [,45] [,46] [,47] [,48]
[1,] -0.2425459 -1.178469 -1.639448 -1.277766 0.0001203863 0.04194658
[2,] -0.2425459 -1.178469 -1.639448 -1.277766 0.0001203863 0.04194658
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.6510042 -0.9125071 0.5657269 0.6303569 -0.1596329 -0.7403471 0.925369
[2,] -0.6510042 -0.9125071 0.5657269 0.6303569 -0.1596329 -0.7403471 0.925369
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] 0.1184405 -1.299473 -0.5818617 1.178806 0.3346169 1.257591 -0.7460222
[2,] 0.1184405 -1.299473 -0.5818617 1.178806 0.3346169 1.257591 -0.7460222
[,63] [,64] [,65] [,66] [,67] [,68]
[1,] 0.0733326 0.3534499 0.02230195 -0.8865264 -0.3117035 -0.01939511
[2,] 0.0733326 0.3534499 0.02230195 -0.8865264 -0.3117035 -0.01939511
[,69] [,70] [,71] [,72] [,73] [,74] [,75]
[1,] -0.4378603 -1.096922 0.1198168 1.202985 0.5462165 1.500228 -0.879283
[2,] -0.4378603 -1.096922 0.1198168 1.202985 0.5462165 1.500228 -0.879283
[,76] [,77] [,78] [,79] [,80] [,81] [,82]
[1,] 1.235218 1.554168 0.2813463 -1.909464 -1.191057 2.325224 0.6340589
[2,] 1.235218 1.554168 0.2813463 -1.909464 -1.191057 2.325224 0.6340589
[,83] [,84] [,85] [,86] [,87] [,88] [,89]
[1,] -0.3721635 0.189464 -0.003261705 -1.852618 0.07918989 1.344804 0.8554124
[2,] -0.3721635 0.189464 -0.003261705 -1.852618 0.07918989 1.344804 0.8554124
[,90] [,91] [,92] [,93] [,94] [,95] [,96]
[1,] -0.9092969 1.505392 -0.1467415 0.4868831 0.1713321 -1.066515 -0.3070453
[2,] -0.9092969 1.505392 -0.1467415 0.4868831 0.1713321 -1.066515 -0.3070453
[,97] [,98] [,99] [,100]
[1,] 0.671537 0.570199 0.02204834 0.2373404
[2,] 0.671537 0.570199 0.02204834 0.2373404
>
>
> Max(tmp2)
[1] 2.349114
> Min(tmp2)
[1] -2.496334
> mean(tmp2)
[1] 0.0855046
> Sum(tmp2)
[1] 8.55046
> Var(tmp2)
[1] 1.056615
>
> rowMeans(tmp2)
[1] -0.42859357 0.38460762 0.41506400 -1.09746032 0.79175558 -1.08221771
[7] -1.67468339 0.94200363 0.24352548 -0.71690521 1.02128842 -0.42782943
[13] 1.33608283 -0.54216488 -0.05762457 -1.59486038 -0.24410381 -0.56945117
[19] -1.72086464 -0.54930586 0.64590756 0.37474711 0.42929465 -2.21317095
[25] -0.65226492 -1.42898394 -0.04830438 -1.38314044 0.33936602 -1.67606279
[31] 0.10162258 -0.76130224 1.02428268 -0.68076759 2.34911366 -0.06844029
[37] 1.08704799 0.34161602 0.97925992 0.77928629 2.17268049 1.14899215
[43] 0.33350709 1.90125034 -0.64216414 -0.69678674 -0.01989826 0.60614654
[49] 1.75515336 -0.28015916 0.79465149 0.85694183 0.42991796 -0.73015381
[55] -2.15269243 0.55108463 0.36512390 1.21970955 0.16494676 -1.03311704
[61] 1.84897712 -1.28993090 1.25751713 -0.54219357 -0.09380818 -1.34535449
[67] 0.48847449 -0.60715518 0.40626332 -0.28179710 0.16144166 -0.22921122
[73] 0.24674651 0.53214913 1.00249397 1.98392307 -1.43998029 0.02996704
[79] -0.88619488 0.90544429 -0.68984340 1.26206287 -0.49463170 0.64166213
[85] 0.63275539 0.37567906 0.31371993 1.36686936 -0.24247727 0.31746381
[91] -0.24601949 0.89269738 1.07271680 -0.27681794 1.12407707 2.21873786
[97] -2.49633408 -0.73752380 -0.50095660 1.15634689
> rowSums(tmp2)
[1] -0.42859357 0.38460762 0.41506400 -1.09746032 0.79175558 -1.08221771
[7] -1.67468339 0.94200363 0.24352548 -0.71690521 1.02128842 -0.42782943
[13] 1.33608283 -0.54216488 -0.05762457 -1.59486038 -0.24410381 -0.56945117
[19] -1.72086464 -0.54930586 0.64590756 0.37474711 0.42929465 -2.21317095
[25] -0.65226492 -1.42898394 -0.04830438 -1.38314044 0.33936602 -1.67606279
[31] 0.10162258 -0.76130224 1.02428268 -0.68076759 2.34911366 -0.06844029
[37] 1.08704799 0.34161602 0.97925992 0.77928629 2.17268049 1.14899215
[43] 0.33350709 1.90125034 -0.64216414 -0.69678674 -0.01989826 0.60614654
[49] 1.75515336 -0.28015916 0.79465149 0.85694183 0.42991796 -0.73015381
[55] -2.15269243 0.55108463 0.36512390 1.21970955 0.16494676 -1.03311704
[61] 1.84897712 -1.28993090 1.25751713 -0.54219357 -0.09380818 -1.34535449
[67] 0.48847449 -0.60715518 0.40626332 -0.28179710 0.16144166 -0.22921122
[73] 0.24674651 0.53214913 1.00249397 1.98392307 -1.43998029 0.02996704
[79] -0.88619488 0.90544429 -0.68984340 1.26206287 -0.49463170 0.64166213
[85] 0.63275539 0.37567906 0.31371993 1.36686936 -0.24247727 0.31746381
[91] -0.24601949 0.89269738 1.07271680 -0.27681794 1.12407707 2.21873786
[97] -2.49633408 -0.73752380 -0.50095660 1.15634689
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] -0.42859357 0.38460762 0.41506400 -1.09746032 0.79175558 -1.08221771
[7] -1.67468339 0.94200363 0.24352548 -0.71690521 1.02128842 -0.42782943
[13] 1.33608283 -0.54216488 -0.05762457 -1.59486038 -0.24410381 -0.56945117
[19] -1.72086464 -0.54930586 0.64590756 0.37474711 0.42929465 -2.21317095
[25] -0.65226492 -1.42898394 -0.04830438 -1.38314044 0.33936602 -1.67606279
[31] 0.10162258 -0.76130224 1.02428268 -0.68076759 2.34911366 -0.06844029
[37] 1.08704799 0.34161602 0.97925992 0.77928629 2.17268049 1.14899215
[43] 0.33350709 1.90125034 -0.64216414 -0.69678674 -0.01989826 0.60614654
[49] 1.75515336 -0.28015916 0.79465149 0.85694183 0.42991796 -0.73015381
[55] -2.15269243 0.55108463 0.36512390 1.21970955 0.16494676 -1.03311704
[61] 1.84897712 -1.28993090 1.25751713 -0.54219357 -0.09380818 -1.34535449
[67] 0.48847449 -0.60715518 0.40626332 -0.28179710 0.16144166 -0.22921122
[73] 0.24674651 0.53214913 1.00249397 1.98392307 -1.43998029 0.02996704
[79] -0.88619488 0.90544429 -0.68984340 1.26206287 -0.49463170 0.64166213
[85] 0.63275539 0.37567906 0.31371993 1.36686936 -0.24247727 0.31746381
[91] -0.24601949 0.89269738 1.07271680 -0.27681794 1.12407707 2.21873786
[97] -2.49633408 -0.73752380 -0.50095660 1.15634689
> rowMin(tmp2)
[1] -0.42859357 0.38460762 0.41506400 -1.09746032 0.79175558 -1.08221771
[7] -1.67468339 0.94200363 0.24352548 -0.71690521 1.02128842 -0.42782943
[13] 1.33608283 -0.54216488 -0.05762457 -1.59486038 -0.24410381 -0.56945117
[19] -1.72086464 -0.54930586 0.64590756 0.37474711 0.42929465 -2.21317095
[25] -0.65226492 -1.42898394 -0.04830438 -1.38314044 0.33936602 -1.67606279
[31] 0.10162258 -0.76130224 1.02428268 -0.68076759 2.34911366 -0.06844029
[37] 1.08704799 0.34161602 0.97925992 0.77928629 2.17268049 1.14899215
[43] 0.33350709 1.90125034 -0.64216414 -0.69678674 -0.01989826 0.60614654
[49] 1.75515336 -0.28015916 0.79465149 0.85694183 0.42991796 -0.73015381
[55] -2.15269243 0.55108463 0.36512390 1.21970955 0.16494676 -1.03311704
[61] 1.84897712 -1.28993090 1.25751713 -0.54219357 -0.09380818 -1.34535449
[67] 0.48847449 -0.60715518 0.40626332 -0.28179710 0.16144166 -0.22921122
[73] 0.24674651 0.53214913 1.00249397 1.98392307 -1.43998029 0.02996704
[79] -0.88619488 0.90544429 -0.68984340 1.26206287 -0.49463170 0.64166213
[85] 0.63275539 0.37567906 0.31371993 1.36686936 -0.24247727 0.31746381
[91] -0.24601949 0.89269738 1.07271680 -0.27681794 1.12407707 2.21873786
[97] -2.49633408 -0.73752380 -0.50095660 1.15634689
>
> colMeans(tmp2)
[1] 0.0855046
> colSums(tmp2)
[1] 8.55046
> colVars(tmp2)
[1] 1.056615
> colSd(tmp2)
[1] 1.027918
> colMax(tmp2)
[1] 2.349114
> colMin(tmp2)
[1] -2.496334
> colMedians(tmp2)
[1] 0.2042361
> colRanges(tmp2)
[,1]
[1,] -2.496334
[2,] 2.349114
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -3.2212358 -1.3069340 0.9214186 -3.5610260 4.3074672 1.0793504
[7] 4.4448464 -3.9905927 1.6581142 -1.3920900
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.0160251
[2,] -0.7243142
[3,] -0.4730149
[4,] 0.3212154
[5,] 1.4456752
>
> rowApply(tmp,sum)
[1] 0.30116207 -0.08278765 -4.35347099 1.49594635 -4.28830897 4.33596806
[7] 1.75624519 0.37371449 1.31183572 -1.91098597
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 2 8 1 9 5 1 9 2 6 5
[2,] 8 5 7 5 7 7 5 1 5 1
[3,] 3 7 8 1 9 5 8 3 4 8
[4,] 4 1 3 4 8 3 3 8 8 4
[5,] 5 2 5 7 10 10 4 7 10 6
[6,] 9 3 6 10 2 2 7 9 3 10
[7,] 6 9 10 6 3 6 2 10 9 9
[8,] 7 4 2 8 1 8 1 6 7 2
[9,] 10 6 9 2 6 9 6 5 2 3
[10,] 1 10 4 3 4 4 10 4 1 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 4.15956533 3.81036125 4.65120364 -1.65329077 -0.68859709 -2.88770587
[7] -0.96261651 1.79896021 1.61809877 -1.14513128 -2.01415138 2.42706925
[13] -0.96822803 1.31534467 -0.68136663 -0.01702816 2.91471622 -1.16034694
[19] 1.65884762 1.83587262
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.251958
[2,] 1.051606
[3,] 1.141681
[4,] 1.313095
[5,] 1.905141
>
> rowApply(tmp,sum)
[1] -1.4430877 5.2696808 0.6843615 8.1999748 1.3006477
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 20 18 3 19 18
[2,] 19 19 20 5 3
[3,] 18 12 18 9 17
[4,] 10 2 5 7 10
[5,] 16 14 13 6 1
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.905141 1.8975230 1.89051691 -0.22921207 0.5373358 -1.6020734
[2,] 1.051606 1.4170664 0.70733505 -1.00353786 0.8368433 1.5322354
[3,] -1.251958 2.3895053 0.84761226 -0.55313146 0.3550802 -0.5433679
[4,] 1.141681 -0.4009686 0.09089185 0.00145487 -0.1085418 -1.4692893
[5,] 1.313095 -1.4927647 1.11484758 0.13113575 -2.3093147 -0.8052107
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.3059224 -1.2418636 -0.3788175 -1.1032973 -2.3941275 0.1896369
[2,] -0.2920942 0.4147148 0.9007030 -0.7897903 -0.1490959 -0.3194832
[3,] -0.7325574 0.0105404 0.5990916 0.5490753 0.2155097 1.5678799
[4,] 1.0983709 1.1360399 1.0123014 2.0614461 -0.4987975 -0.4842540
[5,] -0.7304134 1.4795288 -0.5151798 -1.8625651 0.8123597 1.4732897
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.76680659 0.17874442 0.186959932 0.1256100 0.1002731 0.7568232
[2,] 0.32029952 0.05099819 0.002198126 0.7662940 0.8562494 -1.9334336
[3,] -1.54827754 0.52793295 -0.012689184 -1.5601295 -0.1123137 -0.3704628
[4,] 0.99339618 0.05750565 -0.636675265 0.4380616 1.0908552 0.8177796
[5,] 0.03316041 0.50016346 -0.221160235 0.2131358 0.9796523 -0.4310534
[,19] [,20]
[1,] -0.39579272 -0.7937391
[2,] -0.04647098 0.9470431
[3,] -0.07292729 0.3799489
[4,] 1.10494588 0.7537709
[5,] 1.06909273 0.5488489
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 637 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 552 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.8 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 1.315015 -0.9807812 -1.046447 0.5553293 -0.3168411 0.7933034 1.300903
col8 col9 col10 col11 col12 col13 col14
row1 1.25729 0.02574499 -0.7380887 1.809178 -0.2497582 0.3379987 -3.245631
col15 col16 col17 col18 col19 col20
row1 -2.367348 0.1953975 -0.02156328 0.6975018 0.4987587 0.04520757
> tmp[,"col10"]
col10
row1 -0.7380887
row2 0.8504904
row3 -1.5776141
row4 -0.9226608
row5 -0.6036448
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.315015 -0.9807812 -1.046447 0.5553293 -0.3168411 0.7933034 1.30090348
row5 2.193225 0.5085676 1.195032 -0.9618516 1.4659494 -1.1921995 -0.01473277
col8 col9 col10 col11 col12 col13
row1 1.2572902 0.02574499 -0.7380887 1.809178 -0.2497582 0.3379987
row5 0.9130997 -0.37582102 -0.6036448 -0.864833 -0.5919764 -1.2973473
col14 col15 col16 col17 col18 col19
row1 -3.2456305 -2.367348 0.1953975 -0.02156328 0.6975018 0.4987587
row5 -0.5925086 1.269812 -0.2759846 0.71042384 0.5133483 0.7963685
col20
row1 0.04520757
row5 -0.04452835
> tmp[,c("col6","col20")]
col6 col20
row1 0.79330342 0.04520757
row2 0.06727398 0.92545049
row3 0.45360562 0.31455163
row4 1.03735798 -2.78817609
row5 -1.19219947 -0.04452835
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.7933034 0.04520757
row5 -1.1921995 -0.04452835
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.08586 48.73599 48.34086 49.75772 49.7365 104.0649 49.23485 49.11996
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.5135 50.9809 52.05665 48.25022 49.78014 51.72992 49.50406 47.60308
col17 col18 col19 col20
row1 49.55177 50.46352 50.0389 105.327
> tmp[,"col10"]
col10
row1 50.98090
row2 29.93265
row3 31.41351
row4 31.19344
row5 48.60368
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.08586 48.73599 48.34086 49.75772 49.73650 104.0649 49.23485 49.11996
row5 49.65443 50.42164 48.33521 50.16878 48.22609 105.2721 49.25379 50.47910
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.5135 50.98090 52.05665 48.25022 49.78014 51.72992 49.50406 47.60308
row5 51.4808 48.60368 49.39180 49.09865 50.69874 49.23037 50.46720 50.25374
col17 col18 col19 col20
row1 49.55177 50.46352 50.0389 105.3270
row5 50.50646 49.00885 48.1275 107.8308
> tmp[,c("col6","col20")]
col6 col20
row1 104.06491 105.32700
row2 75.62691 75.68051
row3 73.19335 75.13282
row4 74.97031 75.99445
row5 105.27212 107.83079
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.0649 105.3270
row5 105.2721 107.8308
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.0649 105.3270
row5 105.2721 107.8308
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.08002192
[2,] 1.30762706
[3,] 1.34707267
[4,] 1.52954351
[5,] -2.50842376
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.224283506 2.2117818
[2,] -0.007050453 -0.9763102
[3,] -0.970304246 -0.1882333
[4,] -0.715277098 -0.4393956
[5,] 0.688002868 -3.2225284
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.03095729 -0.9506363
[2,] -0.34624913 2.0989136
[3,] 0.25806031 -0.9797887
[4,] 0.21629169 -0.8680871
[5,] -0.49560770 -1.3911386
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.03095729
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.03095729
[2,] -0.34624913
>
>
>
> 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 -1.0243708 -0.2625913 0.6163396 0.7623131 0.864299002 0.3381418
row1 -0.9223113 -2.0775676 -1.0622063 1.1722158 0.006804707 0.1177109
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 0.1884464 0.98933536 -0.7412271 -2.637104 -0.3118599 1.839552 0.4623494
row1 -0.2171269 -0.08328488 -0.8790772 -1.010026 -0.4972213 1.605077 0.2417521
[,14] [,15] [,16] [,17] [,18] [,19]
row3 0.3679714 -0.2469195 0.4943146 0.12245331 -1.006512 -2.1278567
row1 1.2564628 0.9872492 -0.2517833 -0.05538798 1.620078 -0.2546317
[,20]
row3 0.2615006
row1 -1.0418993
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.019855 0.8762093 0.3293389 -0.672569 0.3495172 -0.8512311 1.157007
[,8] [,9] [,10]
row2 0.5570218 -0.6965661 -0.2308174
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.4240216 0.4208928 1.049798 -0.03064316 -0.1089611 -0.6221041 -0.5109272
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.9047699 0.8397531 0.1674296 -0.2192856 -0.9790948 -0.4176104 -1.033407
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.659565 0.4337059 0.7837768 -1.365327 0.05801474 0.8034271
>
>
> 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: 0x1f8eb70>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a2c6df83649"
[2] "/home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a2c6159a09a"
[3] "/home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a2c711bbfb6"
[4] "/home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a2c7b94f9d6"
[5] "/home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a2c55217edc"
[6] "/home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a2c371bc932"
[7] "/home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a2c20037814"
[8] "/home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a2c40a85c9e"
[9] "/home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a2c47866eb2"
[10] "/home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a2c3361f560"
[11] "/home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a2c70257c68"
[12] "/home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a2c44ed7b37"
[13] "/home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a2c61f332d5"
[14] "/home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a2c788b10dd"
[15] "/home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests/BM1a2c44bddcb2"
>
>
> ### 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: 0x1c68db0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x1c68db0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.8-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x1c68db0>
> rowMedians(tmp)
[1] 0.229163614 -0.613371180 -0.020860477 -0.100809523 -0.275885267
[6] 0.074400615 0.100525539 0.057292074 -0.161156338 -0.121208206
[11] 0.309142359 -0.023959132 0.419992724 -0.361330873 -0.353537503
[16] -0.074511328 0.326294860 -0.821307618 0.690436455 0.002487876
[21] 0.333073986 0.320355714 0.239528264 -0.225760757 0.203084790
[26] 0.139728074 -0.354629082 -0.191466452 -0.468718402 0.222246508
[31] 0.032319193 0.194814860 -0.056276822 0.266648159 0.039523670
[36] 0.232005959 -0.054358718 0.048341124 -0.113182479 0.199390986
[41] -0.195793760 -0.216174592 -0.059055345 0.207979094 -0.160211143
[46] 0.162832380 -0.195933945 -0.386277096 -0.069946176 -0.131331314
[51] 0.271544280 -0.422154381 0.348418328 -0.031030821 -0.233484874
[56] -0.245578591 0.576023081 0.690019760 -0.287791156 0.247630817
[61] 0.141617051 0.431241580 -0.303759133 -0.459464188 -0.150697868
[66] -0.106667363 -0.121070560 -0.221446257 0.190986993 -0.349019363
[71] 0.089754610 0.700804201 0.089490353 0.225896275 -0.343972258
[76] -0.030900743 -0.480707201 0.316058726 -0.053575397 0.300430657
[81] -0.273073844 -0.008118840 -0.416675604 -0.018744360 -0.416197096
[86] -0.054261422 0.077510515 0.401593034 0.046451032 0.055433622
[91] -0.405061272 -0.734287101 -0.178875937 -0.458653356 0.520934586
[96] -0.204990651 0.129570930 -0.023848249 -0.064097503 -0.183364431
[101] 0.014429275 0.212531132 0.258323893 0.001124651 -0.196849843
[106] -0.272256442 0.157636102 -0.083235000 0.401231501 -0.181163439
[111] 0.414017690 -0.249651021 0.231429515 0.065534568 0.106955643
[116] -0.277503705 -0.449486911 -0.171383633 0.274298805 0.393199354
[121] 0.095859846 0.206538704 0.201483559 -0.071206826 0.547497835
[126] 0.222087467 -0.246188596 0.340481755 -0.343755852 0.378733192
[131] -0.045352665 0.132692283 0.282987546 -0.123540719 -0.159672811
[136] 0.182610584 -0.217175828 -0.446459863 -0.354460913 0.239493419
[141] -0.632116019 0.255272247 0.180870304 -0.205686590 -0.194444435
[146] -0.054265304 -0.062953458 0.177272681 0.241432696 0.141628578
[151] -0.500412076 0.015538493 -0.158306969 0.131816456 -0.035366039
[156] -0.113849993 0.025629135 0.240290206 -0.275422980 0.131520391
[161] -0.430072729 0.251361088 -0.470685559 0.122755561 0.964258150
[166] 0.009326528 -0.428409980 -0.467191541 0.071594386 -0.420040122
[171] -0.108262729 0.007108700 0.305286263 0.500333434 0.503004699
[176] -0.025174701 0.097843091 -0.081895402 0.052108099 -0.056001931
[181] -0.156170346 -0.388109725 -0.075389606 0.204984104 -0.045025614
[186] 0.133046554 -0.487487064 0.424457453 0.175657281 -0.211171499
[191] -0.391793328 0.250046889 0.500490097 0.304773580 -0.524111799
[196] -0.264554272 0.020308271 -0.310035062 0.168130707 -0.163724431
[201] -0.196672894 0.540226123 0.509913677 0.203165894 -0.093936064
[206] -0.226202533 0.300699261 0.080659000 -0.525148221 0.001208246
[211] 0.088548115 0.156010319 0.038597953 0.243923617 0.118248419
[216] 0.267639297 0.003712841 0.343584204 -0.751468492 -0.372271891
[221] 0.085729327 -0.364400100 -0.513873010 -0.015775901 0.058438592
[226] -0.697152074 -0.093274255 0.320816753 0.296516464 -0.092028161
>
> proc.time()
user system elapsed
1.992 0.844 2.863
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 3.5.3 (2019-03-11) -- "Great Truth"
Copyright (C) 2019 The R Foundation for Statistical Computing
Platform: x86_64-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: 0x3b76370>
> .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: 0x3b76370>
> .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: 0x3b76370>
> .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: 0x3b76370>
> 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: 0x2f6fb10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2f6fb10>
> .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: 0x2f6fb10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2f6fb10>
> .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: 0x2f6fb10>
> 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: 0x3442200>
> .Call("R_bm_AddColumn",P)
<pointer: 0x3442200>
> .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: 0x3442200>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x3442200>
> .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: 0x3442200>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x3442200>
> .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: 0x3442200>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x3442200>
> .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: 0x3442200>
> 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: 0x2f7f890>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x2f7f890>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2f7f890>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2f7f890>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1bf63f618aba" "BufferedMatrixFile1bf64b0a4038"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1bf63f618aba" "BufferedMatrixFile1bf64b0a4038"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x44c34d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x44c34d0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x44c34d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x44c34d0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x44c34d0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x44c34d0>
> .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: 0x36346c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x36346c0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x36346c0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x36346c0>
> 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: 0x3064f40>
> .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: 0x3064f40>
> rm(P)
>
> proc.time()
user system elapsed
0.312 0.048 0.354
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 3.5.3 (2019-03-11) -- "Great Truth"
Copyright (C) 2019 The R Foundation for Statistical Computing
Platform: x86_64-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
0.352 0.032 0.378