Ben Bolstad
| Snapshot Date: 2019-04-08 17:01:18 -0400 (Mon, 08 Apr 2019) |
| URL: https://git.bioconductor.org/packages/BufferedMatrix |
| Branch: master |
| Last Commit: eca2e36 |
| Last Changed Date: 2018-10-30 11:54:27 -0400 (Tue, 30 Oct 2018) |
| Back to Multiple platform build/check report for BioC 3.9 |
|
This page was generated on 2019-04-09 11:25:16 -0400 (Tue, 09 Apr 2019).
| Package 190/1703 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||
| BufferedMatrix 1.47.0 Ben Bolstad
| malbec2 | Linux (Ubuntu 18.04.2 LTS) / x86_64 | OK | OK | [ OK ] | | ||||||
| tokay2 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||
| celaya2 | OS X 10.11.6 El Capitan / x86_64 | OK | OK | OK | OK | | ||||||
| merida2 | OS X 10.11.6 El Capitan / x86_64 | OK | OK | OK | OK |
| Package: BufferedMatrix |
| Version: 1.47.0 |
| Command: /home/biocbuild/bbs-3.9-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.9-bioc/R/library --no-vignettes --timings BufferedMatrix_1.47.0.tar.gz |
| StartedAt: 2019-04-08 23:08:24 -0400 (Mon, 08 Apr 2019) |
| EndedAt: 2019-04-08 23:08:50 -0400 (Mon, 08 Apr 2019) |
| EllapsedTime: 26.2 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.9-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.9-bioc/R/library --no-vignettes --timings BufferedMatrix_1.47.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck’ * using R Under development (unstable) (2019-03-18 r76245) * 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 ‘1.47.0’ * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking whether package ‘BufferedMatrix’ can be installed ... OK * checking installed package size ... OK * checking package directory ... OK * checking ‘build’ directory ... OK * checking DESCRIPTION meta-information ... OK * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking R files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... OK * checking whether the package can be loaded with stated dependencies ... OK * checking whether the package can be unloaded cleanly ... OK * checking whether the namespace can be loaded with stated dependencies ... OK * checking whether the namespace can be unloaded cleanly ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... OK * checking Rd files ... NOTE prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples * checking Rd metadata ... OK * checking Rd cross-references ... OK * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking line endings in C/C++/Fortran sources/headers ... OK * checking compiled code ... NOTE Note: information on .o files is not available * checking files in ‘vignettes’ ... OK * checking examples ... NONE * checking for unstated dependencies in ‘tests’ ... OK * checking tests ... Running ‘Rcodetesting.R’ Running ‘c_code_level_tests.R’ Running ‘objectTesting.R’ Running ‘rawCalltesting.R’ OK * checking for unstated dependencies in vignettes ... OK * checking package vignettes in ‘inst/doc’ ... OK * checking running R code from vignettes ... SKIPPED * checking re-building of vignette outputs ... SKIPPED * checking PDF version of manual ... OK * DONE Status: 2 NOTEs See ‘/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/00check.log’ for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.9-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.9-bioc/R/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
gcc -I"/home/biocbuild/bbs-3.9-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.9-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘˜’ [-Wparentheses]
if (!(Matrix->readonly) & setting){
^˜˜˜˜˜˜˜˜˜˜˜˜˜˜˜˜˜˜
At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^˜˜˜˜˜˜˜˜˜˜
gcc -I"/home/biocbuild/bbs-3.9-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"/home/biocbuild/bbs-3.9-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c init_package.c -o init_package.o
gcc -shared -L/home/biocbuild/bbs-3.9-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.9-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.9-bioc/R/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R Under development (unstable) (2019-03-18 r76245) -- "Unsuffered Consequences"
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
0.394 0.023 0.405
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2019-03-18 r76245) -- "Unsuffered Consequences"
Copyright (C) 2019 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 410344 22.0 851668 45.5 641485 34.3
Vcells 735377 5.7 8388608 64.0 1798268 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 8 23:08:43 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 8 23:08:44 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: 0x55717a71beb0>
>
>
>
> 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 8 23:08:44 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 8 23:08:44 2019"
>
> ColMode(tmp2)
<pointer: 0x55717a71beb0>
>
>
>
> ### 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,] 100.9127160 1.1710903 1.0688444 -0.3460070
[2,] -0.2950978 -0.5481263 0.6575957 -0.2904070
[3,] -0.9275532 1.1843278 -0.9985650 -0.2089852
[4,] -0.6758983 0.7402822 -0.5949168 -0.4747719
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.9127160 1.1710903 1.0688444 0.3460070
[2,] 0.2950978 0.5481263 0.6575957 0.2904070
[3,] 0.9275532 1.1843278 0.9985650 0.2089852
[4,] 0.6758983 0.7402822 0.5949168 0.4747719
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0455321 1.0821692 1.0338493 0.5882236
[2,] 0.5432290 0.7403555 0.8109227 0.5388942
[3,] 0.9630957 1.0882682 0.9992823 0.4571489
[4,] 0.8221303 0.8603965 0.7713085 0.6890370
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 226.36804 36.99278 36.40734 31.22824
[2,] 30.72739 32.95168 33.76682 30.67935
[3,] 35.55851 37.06701 35.99139 29.78047
[4,] 33.89720 34.34425 33.30800 32.36514
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x55717bafebd0>
> exp(tmp5)
<pointer: 0x55717bafebd0>
> log(tmp5,2)
<pointer: 0x55717bafebd0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.1554
> Min(tmp5)
[1] 54.54702
> mean(tmp5)
[1] 73.42346
> Sum(tmp5)
[1] 14684.69
> Var(tmp5)
[1] 867.802
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.82216 69.13712 70.74222 70.41594 71.19825 71.84829 70.05765 72.27652
[9] 75.16755 72.56891
> rowSums(tmp5)
[1] 1816.443 1382.742 1414.844 1408.319 1423.965 1436.966 1401.153 1445.530
[9] 1503.351 1451.378
> rowVars(tmp5)
[1] 8057.30602 50.90173 57.79061 72.40995 94.15952 61.66959
[7] 73.95488 147.74932 52.44504 40.51745
> rowSd(tmp5)
[1] 89.762498 7.134545 7.602014 8.509404 9.703583 7.852999 8.599702
[8] 12.155218 7.241894 6.365332
> rowMax(tmp5)
[1] 471.15541 82.32262 86.45470 82.25187 94.50346 86.54296 84.77334
[8] 95.82432 84.56878 87.59895
> rowMin(tmp5)
[1] 56.06672 55.12802 58.25907 54.93560 57.73970 54.54702 57.41862 55.42956
[9] 58.65656 64.24087
>
> colMeans(tmp5)
[1] 112.32620 74.80609 79.53955 67.03448 71.28412 70.73927 71.31208
[8] 72.68234 70.38738 73.04560 69.45489 67.56332 71.37358 74.25183
[15] 70.06541 70.08215 72.92174 74.37607 70.97332 64.24980
> colSums(tmp5)
[1] 1123.2620 748.0609 795.3955 670.3448 712.8412 707.3927 713.1208
[8] 726.8234 703.8738 730.4560 694.5489 675.6332 713.7358 742.5183
[15] 700.6541 700.8215 729.2174 743.7607 709.7332 642.4980
> colVars(tmp5)
[1] 15923.69254 33.61644 72.62038 61.28007 106.41039 74.00448
[7] 85.07599 92.53364 57.92585 112.42371 51.10797 24.88804
[13] 53.80381 70.59029 128.71970 73.78077 49.16339 80.26758
[19] 19.64590 29.35040
> colSd(tmp5)
[1] 126.189114 5.797969 8.521759 7.828159 10.315541 8.602585
[7] 9.223665 9.619441 7.610904 10.603005 7.148984 4.988792
[13] 7.335108 8.401803 11.345470 8.589574 7.011661 8.959217
[19] 4.432369 5.417601
> colMax(tmp5)
[1] 471.15541 82.38813 94.50346 84.77334 95.82432 88.95726 84.79989
[8] 84.64350 80.79628 86.54296 83.94560 75.70615 87.59895 86.45470
[15] 91.30202 83.20710 84.17243 87.81040 77.99789 72.25163
> colMin(tmp5)
[1] 63.95503 62.53572 69.32624 54.54702 54.93560 60.02003 56.06672 55.42956
[9] 57.74262 59.59166 61.00741 61.26328 62.82026 57.50995 55.12802 57.41862
[17] 63.25244 59.62588 63.97622 57.73970
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 90.82216 69.13712 70.74222 70.41594 71.19825 71.84829 70.05765 72.27652
[9] NA 72.56891
> rowSums(tmp5)
[1] 1816.443 1382.742 1414.844 1408.319 1423.965 1436.966 1401.153 1445.530
[9] NA 1451.378
> rowVars(tmp5)
[1] 8057.30602 50.90173 57.79061 72.40995 94.15952 61.66959
[7] 73.95488 147.74932 52.81488 40.51745
> rowSd(tmp5)
[1] 89.762498 7.134545 7.602014 8.509404 9.703583 7.852999 8.599702
[8] 12.155218 7.267385 6.365332
> rowMax(tmp5)
[1] 471.15541 82.32262 86.45470 82.25187 94.50346 86.54296 84.77334
[8] 95.82432 NA 87.59895
> rowMin(tmp5)
[1] 56.06672 55.12802 58.25907 54.93560 57.73970 54.54702 57.41862 55.42956
[9] NA 64.24087
>
> colMeans(tmp5)
[1] 112.32620 74.80609 79.53955 67.03448 71.28412 70.73927 71.31208
[8] 72.68234 70.38738 73.04560 69.45489 67.56332 71.37358 74.25183
[15] 70.06541 70.08215 72.92174 74.37607 70.97332 NA
> colSums(tmp5)
[1] 1123.2620 748.0609 795.3955 670.3448 712.8412 707.3927 713.1208
[8] 726.8234 703.8738 730.4560 694.5489 675.6332 713.7358 742.5183
[15] 700.6541 700.8215 729.2174 743.7607 709.7332 NA
> colVars(tmp5)
[1] 15923.69254 33.61644 72.62038 61.28007 106.41039 74.00448
[7] 85.07599 92.53364 57.92585 112.42371 51.10797 24.88804
[13] 53.80381 70.59029 128.71970 73.78077 49.16339 80.26758
[19] 19.64590 NA
> colSd(tmp5)
[1] 126.189114 5.797969 8.521759 7.828159 10.315541 8.602585
[7] 9.223665 9.619441 7.610904 10.603005 7.148984 4.988792
[13] 7.335108 8.401803 11.345470 8.589574 7.011661 8.959217
[19] 4.432369 NA
> colMax(tmp5)
[1] 471.15541 82.38813 94.50346 84.77334 95.82432 88.95726 84.79989
[8] 84.64350 80.79628 86.54296 83.94560 75.70615 87.59895 86.45470
[15] 91.30202 83.20710 84.17243 87.81040 77.99789 NA
> colMin(tmp5)
[1] 63.95503 62.53572 69.32624 54.54702 54.93560 60.02003 56.06672 55.42956
[9] 57.74262 59.59166 61.00741 61.26328 62.82026 57.50995 55.12802 57.41862
[17] 63.25244 59.62588 63.97622 NA
>
> Max(tmp5,na.rm=TRUE)
[1] 471.1554
> Min(tmp5,na.rm=TRUE)
[1] 54.54702
> mean(tmp5,na.rm=TRUE)
[1] 73.44784
> Sum(tmp5,na.rm=TRUE)
[1] 14616.12
> Var(tmp5,na.rm=TRUE)
[1] 872.0653
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.82216 69.13712 70.74222 70.41594 71.19825 71.84829 70.05765 72.27652
[9] 75.51467 72.56891
> rowSums(tmp5,na.rm=TRUE)
[1] 1816.443 1382.742 1414.844 1408.319 1423.965 1436.966 1401.153 1445.530
[9] 1434.779 1451.378
> rowVars(tmp5,na.rm=TRUE)
[1] 8057.30602 50.90173 57.79061 72.40995 94.15952 61.66959
[7] 73.95488 147.74932 52.81488 40.51745
> rowSd(tmp5,na.rm=TRUE)
[1] 89.762498 7.134545 7.602014 8.509404 9.703583 7.852999 8.599702
[8] 12.155218 7.267385 6.365332
> rowMax(tmp5,na.rm=TRUE)
[1] 471.15541 82.32262 86.45470 82.25187 94.50346 86.54296 84.77334
[8] 95.82432 84.56878 87.59895
> rowMin(tmp5,na.rm=TRUE)
[1] 56.06672 55.12802 58.25907 54.93560 57.73970 54.54702 57.41862 55.42956
[9] 58.65656 64.24087
>
> colMeans(tmp5,na.rm=TRUE)
[1] 112.32620 74.80609 79.53955 67.03448 71.28412 70.73927 71.31208
[8] 72.68234 70.38738 73.04560 69.45489 67.56332 71.37358 74.25183
[15] 70.06541 70.08215 72.92174 74.37607 70.97332 63.76954
> colSums(tmp5,na.rm=TRUE)
[1] 1123.2620 748.0609 795.3955 670.3448 712.8412 707.3927 713.1208
[8] 726.8234 703.8738 730.4560 694.5489 675.6332 713.7358 742.5183
[15] 700.6541 700.8215 729.2174 743.7607 709.7332 573.9258
> colVars(tmp5,na.rm=TRUE)
[1] 15923.69254 33.61644 72.62038 61.28007 106.41039 74.00448
[7] 85.07599 92.53364 57.92585 112.42371 51.10797 24.88804
[13] 53.80381 70.59029 128.71970 73.78077 49.16339 80.26758
[19] 19.64590 30.42431
> colSd(tmp5,na.rm=TRUE)
[1] 126.189114 5.797969 8.521759 7.828159 10.315541 8.602585
[7] 9.223665 9.619441 7.610904 10.603005 7.148984 4.988792
[13] 7.335108 8.401803 11.345470 8.589574 7.011661 8.959217
[19] 4.432369 5.515824
> colMax(tmp5,na.rm=TRUE)
[1] 471.15541 82.38813 94.50346 84.77334 95.82432 88.95726 84.79989
[8] 84.64350 80.79628 86.54296 83.94560 75.70615 87.59895 86.45470
[15] 91.30202 83.20710 84.17243 87.81040 77.99789 72.25163
> colMin(tmp5,na.rm=TRUE)
[1] 63.95503 62.53572 69.32624 54.54702 54.93560 60.02003 56.06672 55.42956
[9] 57.74262 59.59166 61.00741 61.26328 62.82026 57.50995 55.12802 57.41862
[17] 63.25244 59.62588 63.97622 57.73970
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.82216 69.13712 70.74222 70.41594 71.19825 71.84829 70.05765 72.27652
[9] NaN 72.56891
> rowSums(tmp5,na.rm=TRUE)
[1] 1816.443 1382.742 1414.844 1408.319 1423.965 1436.966 1401.153 1445.530
[9] 0.000 1451.378
> rowVars(tmp5,na.rm=TRUE)
[1] 8057.30602 50.90173 57.79061 72.40995 94.15952 61.66959
[7] 73.95488 147.74932 NA 40.51745
> rowSd(tmp5,na.rm=TRUE)
[1] 89.762498 7.134545 7.602014 8.509404 9.703583 7.852999 8.599702
[8] 12.155218 NA 6.365332
> rowMax(tmp5,na.rm=TRUE)
[1] 471.15541 82.32262 86.45470 82.25187 94.50346 86.54296 84.77334
[8] 95.82432 NA 87.59895
> rowMin(tmp5,na.rm=TRUE)
[1] 56.06672 55.12802 58.25907 54.93560 57.73970 54.54702 57.41862 55.42956
[9] NA 64.24087
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.75935 74.54224 79.13093 67.21662 71.06049 69.64739 71.11057
[8] 72.06367 69.62885 71.76525 70.32643 66.91184 71.05600 74.26510
[15] 71.33306 68.62382 71.67166 74.10640 70.60428 NaN
> colSums(tmp5,na.rm=TRUE)
[1] 1041.8342 670.8802 712.1783 604.9496 639.5444 626.8265 639.9951
[8] 648.5730 626.6596 645.8872 632.9379 602.2065 639.5040 668.3859
[15] 641.9975 617.6144 645.0449 666.9576 635.4385 0.0000
> colVars(tmp5,na.rm=TRUE)
[1] 17781.55511 37.03529 79.81952 68.56685 119.14909 69.84258
[7] 95.25368 99.79430 58.69369 108.03452 48.95119 23.22423
[13] 59.39460 79.41209 126.73165 59.07777 37.72851 89.48294
[19] 20.56946 NA
> colSd(tmp5,na.rm=TRUE)
[1] 133.347498 6.085663 8.934177 8.280510 10.915543 8.357187
[7] 9.759799 9.989710 7.661181 10.393965 6.996513 4.819153
[13] 7.706789 8.911346 11.257515 7.686206 6.142354 9.459542
[19] 4.535356 NA
> colMax(tmp5,na.rm=TRUE)
[1] 471.15541 82.38813 94.50346 84.77334 95.82432 88.95726 84.79989
[8] 84.64350 80.79628 86.54296 83.94560 75.70615 87.59895 86.45470
[15] 91.30202 81.56233 81.74255 87.81040 77.99789 -Inf
> colMin(tmp5,na.rm=TRUE)
[1] 63.95503 62.53572 69.32624 54.54702 54.93560 60.02003 56.06672 55.42956
[9] 57.74262 59.59166 61.00741 61.26328 62.82026 57.50995 55.12802 57.41862
[17] 63.25244 59.62588 63.97622 Inf
>
>
>
>
> 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] 208.22558 172.66213 184.83680 242.26949 190.45299 87.44262 180.84554
[8] 176.17029 162.97101 260.06257
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 208.22558 172.66213 184.83680 242.26949 190.45299 87.44262 180.84554
[8] 176.17029 162.97101 260.06257
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 8.526513e-14 -5.684342e-14 -5.684342e-14 5.684342e-14 -5.684342e-14
[6] -5.684342e-14 1.136868e-13 8.526513e-14 8.526513e-14 1.421085e-13
[11] 5.684342e-14 -3.552714e-14 -1.136868e-13 0.000000e+00 5.684342e-14
[16] -5.684342e-14 -5.684342e-14 -5.684342e-14 -4.263256e-14 2.273737e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
3 2
4 12
10 8
4 16
6 15
5 6
6 17
7 1
4 10
2 7
4 4
7 7
2 11
7 4
6 8
10 15
2 15
6 7
6 4
5 17
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.488906
> Min(tmp)
[1] -2.811957
> mean(tmp)
[1] -0.09163743
> Sum(tmp)
[1] -9.163743
> Var(tmp)
[1] 1.293574
>
> rowMeans(tmp)
[1] -0.09163743
> rowSums(tmp)
[1] -9.163743
> rowVars(tmp)
[1] 1.293574
> rowSd(tmp)
[1] 1.137354
> rowMax(tmp)
[1] 2.488906
> rowMin(tmp)
[1] -2.811957
>
> colMeans(tmp)
[1] 0.58671527 -0.13083691 0.02262191 -0.65927622 0.36089749 -0.68094205
[7] 1.30199812 0.08968268 1.58718692 -1.58247841 0.11313630 -0.05634244
[13] 0.22832780 1.91608423 -0.68001989 -0.38844553 -1.50377031 -0.64857062
[19] 0.28899362 0.16129043 -1.06746904 -0.85649157 0.89435894 0.50197867
[25] -2.00372485 -1.09431081 -1.51300369 0.20140738 -0.33872222 1.43421754
[31] 0.98956642 1.48187698 -1.71650817 1.83206186 0.04810629 0.09568335
[37] 0.22856085 0.06295550 1.75937230 -0.44723768 -0.29102298 -1.41469474
[43] 2.38698787 0.29437680 -1.52416912 0.81413425 -0.77440825 1.24818275
[49] -0.06559625 0.26130023 0.57550009 0.78199059 0.37384099 -1.16987246
[55] 1.49346288 -1.90438612 -1.17454573 -2.37247843 -0.62439911 -2.14983046
[61] -1.84459674 -0.70413793 0.65613468 0.29765326 1.19458533 -0.67278414
[67] -0.31691189 1.09755928 -1.31151400 -0.69127563 -0.30545396 -1.36572909
[73] 0.22532199 -0.49117390 -2.81195688 -0.05569302 -1.40686576 1.49453654
[79] 0.49684646 0.08653357 0.73894648 1.57433958 1.76447181 2.07481944
[85] 0.48233243 -0.47396855 0.41115130 0.36276061 -0.26008412 0.30702404
[91] -0.29368181 -0.86478435 0.03309782 -1.36140404 -2.41086040 -0.15329354
[97] -1.18432223 2.48890571 0.12553952 -1.67911442
> colSums(tmp)
[1] 0.58671527 -0.13083691 0.02262191 -0.65927622 0.36089749 -0.68094205
[7] 1.30199812 0.08968268 1.58718692 -1.58247841 0.11313630 -0.05634244
[13] 0.22832780 1.91608423 -0.68001989 -0.38844553 -1.50377031 -0.64857062
[19] 0.28899362 0.16129043 -1.06746904 -0.85649157 0.89435894 0.50197867
[25] -2.00372485 -1.09431081 -1.51300369 0.20140738 -0.33872222 1.43421754
[31] 0.98956642 1.48187698 -1.71650817 1.83206186 0.04810629 0.09568335
[37] 0.22856085 0.06295550 1.75937230 -0.44723768 -0.29102298 -1.41469474
[43] 2.38698787 0.29437680 -1.52416912 0.81413425 -0.77440825 1.24818275
[49] -0.06559625 0.26130023 0.57550009 0.78199059 0.37384099 -1.16987246
[55] 1.49346288 -1.90438612 -1.17454573 -2.37247843 -0.62439911 -2.14983046
[61] -1.84459674 -0.70413793 0.65613468 0.29765326 1.19458533 -0.67278414
[67] -0.31691189 1.09755928 -1.31151400 -0.69127563 -0.30545396 -1.36572909
[73] 0.22532199 -0.49117390 -2.81195688 -0.05569302 -1.40686576 1.49453654
[79] 0.49684646 0.08653357 0.73894648 1.57433958 1.76447181 2.07481944
[85] 0.48233243 -0.47396855 0.41115130 0.36276061 -0.26008412 0.30702404
[91] -0.29368181 -0.86478435 0.03309782 -1.36140404 -2.41086040 -0.15329354
[97] -1.18432223 2.48890571 0.12553952 -1.67911442
> 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] 0.58671527 -0.13083691 0.02262191 -0.65927622 0.36089749 -0.68094205
[7] 1.30199812 0.08968268 1.58718692 -1.58247841 0.11313630 -0.05634244
[13] 0.22832780 1.91608423 -0.68001989 -0.38844553 -1.50377031 -0.64857062
[19] 0.28899362 0.16129043 -1.06746904 -0.85649157 0.89435894 0.50197867
[25] -2.00372485 -1.09431081 -1.51300369 0.20140738 -0.33872222 1.43421754
[31] 0.98956642 1.48187698 -1.71650817 1.83206186 0.04810629 0.09568335
[37] 0.22856085 0.06295550 1.75937230 -0.44723768 -0.29102298 -1.41469474
[43] 2.38698787 0.29437680 -1.52416912 0.81413425 -0.77440825 1.24818275
[49] -0.06559625 0.26130023 0.57550009 0.78199059 0.37384099 -1.16987246
[55] 1.49346288 -1.90438612 -1.17454573 -2.37247843 -0.62439911 -2.14983046
[61] -1.84459674 -0.70413793 0.65613468 0.29765326 1.19458533 -0.67278414
[67] -0.31691189 1.09755928 -1.31151400 -0.69127563 -0.30545396 -1.36572909
[73] 0.22532199 -0.49117390 -2.81195688 -0.05569302 -1.40686576 1.49453654
[79] 0.49684646 0.08653357 0.73894648 1.57433958 1.76447181 2.07481944
[85] 0.48233243 -0.47396855 0.41115130 0.36276061 -0.26008412 0.30702404
[91] -0.29368181 -0.86478435 0.03309782 -1.36140404 -2.41086040 -0.15329354
[97] -1.18432223 2.48890571 0.12553952 -1.67911442
> colMin(tmp)
[1] 0.58671527 -0.13083691 0.02262191 -0.65927622 0.36089749 -0.68094205
[7] 1.30199812 0.08968268 1.58718692 -1.58247841 0.11313630 -0.05634244
[13] 0.22832780 1.91608423 -0.68001989 -0.38844553 -1.50377031 -0.64857062
[19] 0.28899362 0.16129043 -1.06746904 -0.85649157 0.89435894 0.50197867
[25] -2.00372485 -1.09431081 -1.51300369 0.20140738 -0.33872222 1.43421754
[31] 0.98956642 1.48187698 -1.71650817 1.83206186 0.04810629 0.09568335
[37] 0.22856085 0.06295550 1.75937230 -0.44723768 -0.29102298 -1.41469474
[43] 2.38698787 0.29437680 -1.52416912 0.81413425 -0.77440825 1.24818275
[49] -0.06559625 0.26130023 0.57550009 0.78199059 0.37384099 -1.16987246
[55] 1.49346288 -1.90438612 -1.17454573 -2.37247843 -0.62439911 -2.14983046
[61] -1.84459674 -0.70413793 0.65613468 0.29765326 1.19458533 -0.67278414
[67] -0.31691189 1.09755928 -1.31151400 -0.69127563 -0.30545396 -1.36572909
[73] 0.22532199 -0.49117390 -2.81195688 -0.05569302 -1.40686576 1.49453654
[79] 0.49684646 0.08653357 0.73894648 1.57433958 1.76447181 2.07481944
[85] 0.48233243 -0.47396855 0.41115130 0.36276061 -0.26008412 0.30702404
[91] -0.29368181 -0.86478435 0.03309782 -1.36140404 -2.41086040 -0.15329354
[97] -1.18432223 2.48890571 0.12553952 -1.67911442
> colMedians(tmp)
[1] 0.58671527 -0.13083691 0.02262191 -0.65927622 0.36089749 -0.68094205
[7] 1.30199812 0.08968268 1.58718692 -1.58247841 0.11313630 -0.05634244
[13] 0.22832780 1.91608423 -0.68001989 -0.38844553 -1.50377031 -0.64857062
[19] 0.28899362 0.16129043 -1.06746904 -0.85649157 0.89435894 0.50197867
[25] -2.00372485 -1.09431081 -1.51300369 0.20140738 -0.33872222 1.43421754
[31] 0.98956642 1.48187698 -1.71650817 1.83206186 0.04810629 0.09568335
[37] 0.22856085 0.06295550 1.75937230 -0.44723768 -0.29102298 -1.41469474
[43] 2.38698787 0.29437680 -1.52416912 0.81413425 -0.77440825 1.24818275
[49] -0.06559625 0.26130023 0.57550009 0.78199059 0.37384099 -1.16987246
[55] 1.49346288 -1.90438612 -1.17454573 -2.37247843 -0.62439911 -2.14983046
[61] -1.84459674 -0.70413793 0.65613468 0.29765326 1.19458533 -0.67278414
[67] -0.31691189 1.09755928 -1.31151400 -0.69127563 -0.30545396 -1.36572909
[73] 0.22532199 -0.49117390 -2.81195688 -0.05569302 -1.40686576 1.49453654
[79] 0.49684646 0.08653357 0.73894648 1.57433958 1.76447181 2.07481944
[85] 0.48233243 -0.47396855 0.41115130 0.36276061 -0.26008412 0.30702404
[91] -0.29368181 -0.86478435 0.03309782 -1.36140404 -2.41086040 -0.15329354
[97] -1.18432223 2.48890571 0.12553952 -1.67911442
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.5867153 -0.1308369 0.02262191 -0.6592762 0.3608975 -0.6809421 1.301998
[2,] 0.5867153 -0.1308369 0.02262191 -0.6592762 0.3608975 -0.6809421 1.301998
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.08968268 1.587187 -1.582478 0.1131363 -0.05634244 0.2283278 1.916084
[2,] 0.08968268 1.587187 -1.582478 0.1131363 -0.05634244 0.2283278 1.916084
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.6800199 -0.3884455 -1.50377 -0.6485706 0.2889936 0.1612904 -1.067469
[2,] -0.6800199 -0.3884455 -1.50377 -0.6485706 0.2889936 0.1612904 -1.067469
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.8564916 0.8943589 0.5019787 -2.003725 -1.094311 -1.513004 0.2014074
[2,] -0.8564916 0.8943589 0.5019787 -2.003725 -1.094311 -1.513004 0.2014074
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.3387222 1.434218 0.9895664 1.481877 -1.716508 1.832062 0.04810629
[2,] -0.3387222 1.434218 0.9895664 1.481877 -1.716508 1.832062 0.04810629
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.09568335 0.2285608 0.0629555 1.759372 -0.4472377 -0.291023 -1.414695
[2,] 0.09568335 0.2285608 0.0629555 1.759372 -0.4472377 -0.291023 -1.414695
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 2.386988 0.2943768 -1.524169 0.8141342 -0.7744083 1.248183 -0.06559625
[2,] 2.386988 0.2943768 -1.524169 0.8141342 -0.7744083 1.248183 -0.06559625
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.2613002 0.5755001 0.7819906 0.373841 -1.169872 1.493463 -1.904386
[2,] 0.2613002 0.5755001 0.7819906 0.373841 -1.169872 1.493463 -1.904386
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -1.174546 -2.372478 -0.6243991 -2.14983 -1.844597 -0.7041379 0.6561347
[2,] -1.174546 -2.372478 -0.6243991 -2.14983 -1.844597 -0.7041379 0.6561347
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.2976533 1.194585 -0.6727841 -0.3169119 1.097559 -1.311514 -0.6912756
[2,] 0.2976533 1.194585 -0.6727841 -0.3169119 1.097559 -1.311514 -0.6912756
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.305454 -1.365729 0.225322 -0.4911739 -2.811957 -0.05569302 -1.406866
[2,] -0.305454 -1.365729 0.225322 -0.4911739 -2.811957 -0.05569302 -1.406866
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.494537 0.4968465 0.08653357 0.7389465 1.57434 1.764472 2.074819
[2,] 1.494537 0.4968465 0.08653357 0.7389465 1.57434 1.764472 2.074819
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.4823324 -0.4739686 0.4111513 0.3627606 -0.2600841 0.307024 -0.2936818
[2,] 0.4823324 -0.4739686 0.4111513 0.3627606 -0.2600841 0.307024 -0.2936818
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.8647844 0.03309782 -1.361404 -2.41086 -0.1532935 -1.184322 2.488906
[2,] -0.8647844 0.03309782 -1.361404 -2.41086 -0.1532935 -1.184322 2.488906
[,99] [,100]
[1,] 0.1255395 -1.679114
[2,] 0.1255395 -1.679114
>
>
> Max(tmp2)
[1] 2.722728
> Min(tmp2)
[1] -2.147122
> mean(tmp2)
[1] -0.07656063
> Sum(tmp2)
[1] -7.656063
> Var(tmp2)
[1] 0.9481336
>
> rowMeans(tmp2)
[1] -1.03597633 -1.58837136 1.49833713 -0.92272205 0.62489812 1.51070602
[7] 0.22922014 2.72272752 0.56081457 -0.36898842 -0.10679892 -0.20265153
[13] 0.07067372 1.53614869 -1.62174302 -0.16746846 -0.86546114 0.24548061
[19] -1.21619995 -0.15527895 1.10566667 1.90366814 0.83751485 0.77453564
[25] 0.14084048 -0.94442933 0.20570289 0.66978581 -1.30311885 -1.30394816
[31] -0.18103285 0.74452957 -0.94201948 -0.74942076 0.28332827 -0.05454525
[37] 0.04378590 -1.32370212 -0.75952932 1.49929257 0.99982894 0.13443698
[43] -0.95028414 0.10738106 0.77372763 -1.00109860 -0.46532243 -0.50965435
[49] -0.89330982 0.53403571 0.44361558 0.09166104 -1.84721263 0.05991611
[55] 0.59538579 -0.15409958 0.66252805 -0.73424425 -0.21118468 1.31661413
[61] 1.34503588 0.22250837 0.63399767 -1.55908652 0.57279208 -0.93056778
[67] -0.29421408 0.90930271 0.42383451 1.51468073 0.90416955 -1.21779144
[73] -0.48560011 0.42922099 -1.75382682 -0.48209509 1.20690108 0.12098332
[79] 1.19995145 -1.18566799 -2.14712189 0.04625135 -0.37645444 0.56198998
[85] -0.82213466 -0.10478742 -1.63921884 0.60130305 -0.21347259 0.08034925
[91] 0.52192215 -0.80895096 -0.20151527 1.00532154 -1.65935801 0.26316560
[97] -0.18907796 -1.12613692 -1.80485334 -1.56478328
> rowSums(tmp2)
[1] -1.03597633 -1.58837136 1.49833713 -0.92272205 0.62489812 1.51070602
[7] 0.22922014 2.72272752 0.56081457 -0.36898842 -0.10679892 -0.20265153
[13] 0.07067372 1.53614869 -1.62174302 -0.16746846 -0.86546114 0.24548061
[19] -1.21619995 -0.15527895 1.10566667 1.90366814 0.83751485 0.77453564
[25] 0.14084048 -0.94442933 0.20570289 0.66978581 -1.30311885 -1.30394816
[31] -0.18103285 0.74452957 -0.94201948 -0.74942076 0.28332827 -0.05454525
[37] 0.04378590 -1.32370212 -0.75952932 1.49929257 0.99982894 0.13443698
[43] -0.95028414 0.10738106 0.77372763 -1.00109860 -0.46532243 -0.50965435
[49] -0.89330982 0.53403571 0.44361558 0.09166104 -1.84721263 0.05991611
[55] 0.59538579 -0.15409958 0.66252805 -0.73424425 -0.21118468 1.31661413
[61] 1.34503588 0.22250837 0.63399767 -1.55908652 0.57279208 -0.93056778
[67] -0.29421408 0.90930271 0.42383451 1.51468073 0.90416955 -1.21779144
[73] -0.48560011 0.42922099 -1.75382682 -0.48209509 1.20690108 0.12098332
[79] 1.19995145 -1.18566799 -2.14712189 0.04625135 -0.37645444 0.56198998
[85] -0.82213466 -0.10478742 -1.63921884 0.60130305 -0.21347259 0.08034925
[91] 0.52192215 -0.80895096 -0.20151527 1.00532154 -1.65935801 0.26316560
[97] -0.18907796 -1.12613692 -1.80485334 -1.56478328
> 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] -1.03597633 -1.58837136 1.49833713 -0.92272205 0.62489812 1.51070602
[7] 0.22922014 2.72272752 0.56081457 -0.36898842 -0.10679892 -0.20265153
[13] 0.07067372 1.53614869 -1.62174302 -0.16746846 -0.86546114 0.24548061
[19] -1.21619995 -0.15527895 1.10566667 1.90366814 0.83751485 0.77453564
[25] 0.14084048 -0.94442933 0.20570289 0.66978581 -1.30311885 -1.30394816
[31] -0.18103285 0.74452957 -0.94201948 -0.74942076 0.28332827 -0.05454525
[37] 0.04378590 -1.32370212 -0.75952932 1.49929257 0.99982894 0.13443698
[43] -0.95028414 0.10738106 0.77372763 -1.00109860 -0.46532243 -0.50965435
[49] -0.89330982 0.53403571 0.44361558 0.09166104 -1.84721263 0.05991611
[55] 0.59538579 -0.15409958 0.66252805 -0.73424425 -0.21118468 1.31661413
[61] 1.34503588 0.22250837 0.63399767 -1.55908652 0.57279208 -0.93056778
[67] -0.29421408 0.90930271 0.42383451 1.51468073 0.90416955 -1.21779144
[73] -0.48560011 0.42922099 -1.75382682 -0.48209509 1.20690108 0.12098332
[79] 1.19995145 -1.18566799 -2.14712189 0.04625135 -0.37645444 0.56198998
[85] -0.82213466 -0.10478742 -1.63921884 0.60130305 -0.21347259 0.08034925
[91] 0.52192215 -0.80895096 -0.20151527 1.00532154 -1.65935801 0.26316560
[97] -0.18907796 -1.12613692 -1.80485334 -1.56478328
> rowMin(tmp2)
[1] -1.03597633 -1.58837136 1.49833713 -0.92272205 0.62489812 1.51070602
[7] 0.22922014 2.72272752 0.56081457 -0.36898842 -0.10679892 -0.20265153
[13] 0.07067372 1.53614869 -1.62174302 -0.16746846 -0.86546114 0.24548061
[19] -1.21619995 -0.15527895 1.10566667 1.90366814 0.83751485 0.77453564
[25] 0.14084048 -0.94442933 0.20570289 0.66978581 -1.30311885 -1.30394816
[31] -0.18103285 0.74452957 -0.94201948 -0.74942076 0.28332827 -0.05454525
[37] 0.04378590 -1.32370212 -0.75952932 1.49929257 0.99982894 0.13443698
[43] -0.95028414 0.10738106 0.77372763 -1.00109860 -0.46532243 -0.50965435
[49] -0.89330982 0.53403571 0.44361558 0.09166104 -1.84721263 0.05991611
[55] 0.59538579 -0.15409958 0.66252805 -0.73424425 -0.21118468 1.31661413
[61] 1.34503588 0.22250837 0.63399767 -1.55908652 0.57279208 -0.93056778
[67] -0.29421408 0.90930271 0.42383451 1.51468073 0.90416955 -1.21779144
[73] -0.48560011 0.42922099 -1.75382682 -0.48209509 1.20690108 0.12098332
[79] 1.19995145 -1.18566799 -2.14712189 0.04625135 -0.37645444 0.56198998
[85] -0.82213466 -0.10478742 -1.63921884 0.60130305 -0.21347259 0.08034925
[91] 0.52192215 -0.80895096 -0.20151527 1.00532154 -1.65935801 0.26316560
[97] -0.18907796 -1.12613692 -1.80485334 -1.56478328
>
> colMeans(tmp2)
[1] -0.07656063
> colSums(tmp2)
[1] -7.656063
> colVars(tmp2)
[1] 0.9481336
> colSd(tmp2)
[1] 0.9737215
> colMax(tmp2)
[1] 2.722728
> colMin(tmp2)
[1] -2.147122
> colMedians(tmp2)
[1] -0.00537967
> colRanges(tmp2)
[,1]
[1,] -2.147122
[2,] 2.722728
>
> 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] 2.5963384 0.1707731 -6.3058303 -1.2093193 3.8567021 -2.3127413
[7] 3.5102731 1.0227416 -0.8190850 -2.9824206
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1494816
[2,] -0.6375577
[3,] 0.5186938
[4,] 0.9455473
[5,] 1.5476311
>
> rowApply(tmp,sum)
[1] -1.4604870 0.1418563 2.0510264 -5.8352911 1.4711242 -3.5956417
[7] 1.0461191 -0.4158474 3.0820623 1.0425107
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 3 9 9 3 10 6 1 9 3
[2,] 3 6 5 4 9 8 2 2 5 7
[3,] 4 10 2 6 1 1 8 4 4 1
[4,] 5 2 10 5 6 7 7 6 3 2
[5,] 10 4 6 2 8 3 4 9 10 9
[6,] 7 9 1 3 5 2 9 7 2 5
[7,] 2 1 8 10 7 9 3 10 7 8
[8,] 8 5 4 8 4 5 5 8 8 4
[9,] 6 7 3 1 10 6 1 3 6 6
[10,] 1 8 7 7 2 4 10 5 1 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.95047582 -1.88910719 -1.68108638 -1.40931633 -1.34991315 4.78072194
[7] -0.86194222 2.73138004 -3.81357209 -1.17656864 -2.80207870 1.41948030
[13] -0.87251100 -0.07007238 -3.39134334 2.56812980 0.90436650 -0.40429975
[19] 1.84881502 1.67757359
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8840693
[2,] -0.3233033
[3,] -0.1636277
[4,] 0.1038486
[5,] 0.3166759
>
> rowApply(tmp,sum)
[1] 8.548492 -1.068096 -3.569317 -5.083125 -3.569773
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 10 5 15 11 10
[2,] 1 8 8 19 4
[3,] 2 10 6 12 6
[4,] 12 2 12 15 9
[5,] 6 12 20 6 1
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.1038486 -1.2735355 -0.2980029 0.33291126 -0.04390776 1.60388238
[2,] -0.8840693 -0.3018443 0.1347386 -1.55583433 0.30291617 1.57363838
[3,] 0.3166759 -0.3401575 -0.6052797 -0.03459215 1.10195044 -0.03990668
[4,] -0.1636277 1.1342740 -0.1204004 0.25054301 -0.58419815 0.77450619
[5,] -0.3233033 -1.1078439 -0.7921419 -0.40234412 -2.12667385 0.86860167
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.1651065 1.916930724 0.007339376 0.0295138 -0.0968702 0.02404894
[2,] -2.2174590 0.957006408 -0.764606195 0.4787613 -0.9518364 0.40890905
[3,] -0.2253215 -0.006587229 -0.709943820 -0.4911506 0.7559958 0.15609643
[4,] 1.3426553 0.435138658 -0.710811587 -1.0045412 -2.3141324 0.53849681
[5,] 0.4032895 -0.571108524 -1.635549861 -0.1891520 -0.1952355 0.29192906
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.1643298 -0.1606199 0.3771804 0.8815051 1.7400397 0.9442688
[2,] -0.2831692 0.2136202 -1.2389204 0.9780862 1.1913047 -0.4300859
[3,] -0.8356635 -1.3597174 -1.0913025 0.6395855 0.4297960 0.6193808
[4,] -0.3320072 -0.7412456 -0.5840941 -0.4920164 -2.3388076 -0.4187143
[5,] -0.5860009 1.9778902 -0.8542067 0.5609695 -0.1179663 -1.1191493
[,19] [,20]
[1,] 0.17616484 1.2845709
[2,] 0.64833499 0.6724130
[3,] -0.07334291 -1.7758327
[4,] 0.03736667 0.2084903
[5,] 1.06029144 1.2879321
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 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-3.9-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 638 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 553 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 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 0.5276654 1.120377 -0.9992015 -0.7592543 -0.1346965 0.7390214 1.733621
col8 col9 col10 col11 col12 col13 col14
row1 -0.2161316 1.525517 0.2312316 0.2198432 1.478311 -1.278617 -1.705303
col15 col16 col17 col18 col19 col20
row1 0.09978991 -0.8171269 -1.055939 -2.157685 -1.317728 0.1319528
> tmp[,"col10"]
col10
row1 0.2312316
row2 -0.7326713
row3 -0.8094812
row4 -1.2975500
row5 -1.2718556
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.5276654 1.1203767 -0.9992015 -0.7592543 -0.1346965 0.7390214 1.7336205
row5 -0.7801364 0.2620684 -0.3831661 0.3364085 0.8986511 0.8229092 -0.2317166
col8 col9 col10 col11 col12 col13 col14
row1 -0.2161316 1.525517 0.2312316 0.2198432 1.4783108 -1.2786171 -1.7053025
row5 0.1363965 1.492951 -1.2718556 0.4704211 0.8660578 -0.5479028 -0.4562783
col15 col16 col17 col18 col19 col20
row1 0.09978991 -0.81712686 -1.0559389 -2.157685 -1.3177278 0.1319528
row5 0.49040682 -0.07151715 -0.9289506 -0.904602 -0.6028296 -1.0946405
> tmp[,c("col6","col20")]
col6 col20
row1 0.7390214 0.1319528
row2 0.8423524 -0.2190360
row3 0.3370725 0.9740469
row4 -0.7615667 1.6262656
row5 0.8229092 -1.0946405
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.7390214 0.1319528
row5 0.8229092 -1.0946405
>
>
>
>
> 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 50.14609 49.60087 49.7795 49.01361 49.2201 106.1652 49.92027 51.59351
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.606 51.27413 52.77985 49.91565 51.48544 49.63922 48.36849 51.13287
col17 col18 col19 col20
row1 51.08095 49.70577 49.91428 104.0697
> tmp[,"col10"]
col10
row1 51.27413
row2 29.91020
row3 31.21309
row4 29.56005
row5 49.15041
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.14609 49.60087 49.77950 49.01361 49.22010 106.1652 49.92027 51.59351
row5 48.85278 50.32193 48.65088 49.86378 49.02212 103.8758 49.87171 50.69007
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.60600 51.27413 52.77985 49.91565 51.48544 49.63922 48.36849 51.13287
row5 50.21404 49.15041 49.33601 50.32421 51.35481 50.48900 50.77302 51.36451
col17 col18 col19 col20
row1 51.08095 49.70577 49.91428 104.0697
row5 50.77681 50.58448 48.89882 106.4910
> tmp[,c("col6","col20")]
col6 col20
row1 106.16520 104.06970
row2 75.00730 75.03940
row3 74.54527 75.58065
row4 75.89739 73.88792
row5 103.87581 106.49097
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.1652 104.0697
row5 103.8758 106.4910
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.1652 104.0697
row5 103.8758 106.4910
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.9250659
[2,] 1.4665791
[3,] 1.5611584
[4,] 0.8134554
[5,] 0.8588359
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.75448401 -1.7207469
[2,] -0.56474453 1.5717600
[3,] 0.03950901 0.1400496
[4,] -0.64240217 0.7504719
[5,] -0.83975332 -0.1757483
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.0386499 0.7992295
[2,] -0.5979688 0.2914956
[3,] -0.4668978 -0.9216234
[4,] 0.4908331 -1.2031791
[5,] -0.5231784 2.3200065
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.03865
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.0386499
[2,] -0.5979688
>
>
>
> 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 2.2313554 0.9406455 0.9727136 -2.0774899 0.96375738 0.1992275
row1 0.9322706 1.5231455 -1.3526320 0.6265953 -0.08037458 0.6515793
[,7] [,8] [,9] [,10] [,11] [,12]
row3 0.02341069 0.6279958 0.2449760 -0.9538646 -1.2435982 -0.4845892
row1 -0.70777739 2.2747534 0.8446895 0.4085539 0.3312079 -0.6714621
[,13] [,14] [,15] [,16] [,17] [,18]
row3 -0.08849605 -0.37234974 1.6674477 0.1027889 1.2326782 -0.03488008
row1 0.12839464 0.01216302 0.8022021 0.9466081 -0.5068463 0.73039273
[,19] [,20]
row3 1.203377 -0.49937738
row1 -1.049639 -0.04415624
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.773356 1.473774 0.4766734 -0.8268108 0.264947 -0.8856416 2.703495
[,8] [,9] [,10]
row2 1.877182 -0.892799 0.4315649
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.337232 0.2372468 0.06142855 0.4661817 0.7143503 1.245774 -1.681172
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.1918216 0.7737025 1.060714 0.6872023 1.340709 0.06908025 0.6948704
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.9641091 1.141733 -0.2614444 1.013516 1.53328 0.53046
>
>
> 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: 0x55717a65b440>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM45f956a052e7"
[2] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM45f965d3dff7"
[3] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM45f932c7378c"
[4] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM45f9307bba71"
[5] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM45f94b8b4e41"
[6] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM45f937b7d913"
[7] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM45f9386f7be6"
[8] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM45f921c892d3"
[9] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM45f938e1e39e"
[10] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM45f9532d4d73"
[11] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM45f927f97ef"
[12] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM45f92630e9c4"
[13] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM45f96f0d75a3"
[14] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM45f916a0b259"
[15] "/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests/BM45f91c579644"
>
>
> ### 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: 0x55717ac9c340>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x55717ac9c340>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.9-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x55717ac9c340>
> rowMedians(tmp)
[1] -0.3154067612 -0.0466088941 0.3222203683 0.0225561425 -0.1134779793
[6] 0.5377632919 0.2858095020 -0.2441070131 0.5499293509 -0.5361750210
[11] -0.0852569498 -0.0208058807 0.0223641413 0.4067452659 -0.0052545749
[16] 0.6699641782 -0.2657777187 0.2943252318 -0.1604110538 -0.2841689584
[21] 0.1019825138 0.3391979473 0.2144121735 -0.8716119818 0.0283821278
[26] 0.2148049184 -0.1984449749 0.4406298061 -0.8218627807 -0.0427040586
[31] -0.0746459831 -0.4103211733 0.7051961342 -0.3422615093 -0.2228437875
[36] -0.4310919620 -0.2789280317 0.6728952447 -0.2686759324 -0.6305610290
[41] 0.0231365742 0.4105367412 0.0812898480 0.1032420097 0.0545097259
[46] 0.1804147048 -0.1876372200 0.0183412938 0.1199805430 0.0409024786
[51] -0.5087727363 -0.0045216032 -0.5515069942 -0.1669770054 0.2163768492
[56] -0.0363481967 -0.7250023439 0.1001938987 -0.3705007389 0.0406738611
[61] -0.3394661887 -0.1748621104 0.4546705061 -0.1365787349 -0.3586402579
[66] -0.1454843337 -0.1861344837 0.1853772069 0.1826017952 -0.7271449786
[71] -0.6381460062 0.1866232518 -0.3431594621 0.2635404266 -0.3763654087
[76] -0.1998263401 0.1362071441 0.2119389828 0.0064847130 0.0531515980
[81] 0.4655085862 -0.1589529601 0.4051475863 0.1492768193 -0.2831152389
[86] 0.4077943224 -0.9711902694 0.3384996354 -0.0608624686 -0.3477536941
[91] -0.1974415359 0.2902872384 0.1111219115 -0.0662491204 -0.3555866585
[96] -0.2703235008 -0.2214426322 -0.1953992927 0.0375009959 0.4192400562
[101] -0.2095735340 -0.1458688397 0.1052943589 0.3201435833 0.1722085803
[106] 0.0265370925 -0.1146238492 0.0616837447 -0.2077271702 0.1240471855
[111] -0.1491628784 0.1489890058 -0.2524622404 0.2268694022 0.2180252433
[116] 0.3962464942 -0.3369396704 -0.7055964785 0.1529900936 0.4699287754
[121] 0.0012993427 -0.1270675643 -0.1777515599 0.1834645454 -0.4668798550
[126] 0.4187340437 -0.1520610814 -0.0981769301 -0.0388054454 -0.0668364630
[131] 0.0838149201 -0.5041913128 0.4696760938 -0.1432534453 -0.0586058532
[136] -0.2643459190 0.0382194196 0.0269274700 -0.1372617041 -0.7212019577
[141] 0.2684506702 -0.2977697553 0.2253218669 0.1305312745 -0.0854938763
[146] 0.4660882498 0.5861828515 0.2132814360 -0.2347569791 0.3047989290
[151] 0.0285462985 0.1381751527 -0.0281556510 -0.2190915357 -0.1210985732
[156] -0.3941199362 -0.1965459746 -0.6068458995 0.2108582915 0.2837564554
[161] 0.5417702727 0.2288275048 0.3693094666 0.0693501186 0.0645095214
[166] 0.4256695702 -0.1395815065 -0.0918829701 0.4033169726 -0.0841517870
[171] 0.1212043394 0.1406288768 0.1637403347 -0.1849130572 -0.0555794744
[176] 0.1064240484 0.4808474812 0.2042996665 -0.0131452372 0.4261681129
[181] -0.4305159729 0.4048876795 -0.0004917439 -0.0546793435 0.4231056824
[186] -0.5708316391 -0.4155664823 -0.5203821343 -0.3387432368 -0.1672616729
[191] 0.1236987032 -0.1979839415 0.0144161138 0.0994771576 -0.0435917849
[196] -0.0701873266 0.3602514718 -0.1192198647 -0.3342331526 -0.0114523837
[201] -0.2055226387 -0.2712755233 -0.0649756861 -0.2428369863 -0.2275737636
[206] -0.1873845912 -0.1118779235 0.1468163756 0.3044762192 0.5759306943
[211] -0.3805062892 -0.0760231346 -0.0409650121 0.0540040846 0.5513186162
[216] -0.1620935529 0.1665447250 0.1524243404 -0.0411294694 -0.2868261480
[221] 0.2225245587 0.0049123404 0.3380183893 -0.8159282017 -0.0066890773
[226] 0.0605083113 0.2460433991 -0.2985254354 -0.6171409943 -0.1105749088
>
> proc.time()
user system elapsed
2.249 1.068 3.317
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2019-03-18 r76245) -- "Unsuffered Consequences"
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: 0x56495bd33eb0>
> .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: 0x56495bd33eb0>
> .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: 0x56495bd33eb0>
> .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: 0x56495bd33eb0>
> 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: 0x56495bb8ab70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56495bb8ab70>
> .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: 0x56495bb8ab70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56495bb8ab70>
> .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: 0x56495bb8ab70>
> 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: 0x56495c7db670>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56495c7db670>
> .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: 0x56495c7db670>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x56495c7db670>
> .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: 0x56495c7db670>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x56495c7db670>
> .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: 0x56495c7db670>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x56495c7db670>
> .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: 0x56495c7db670>
> 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: 0x56495be6a7d0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x56495be6a7d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56495be6a7d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56495be6a7d0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile48845a7ec639" "BufferedMatrixFile48847ffd000f"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile48845a7ec639" "BufferedMatrixFile48847ffd000f"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x56495b5881b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56495b5881b0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x56495b5881b0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x56495b5881b0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x56495b5881b0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x56495b5881b0>
> .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: 0x56495d902f70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56495d902f70>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x56495d902f70>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x56495d902f70>
> 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: 0x56495bc31890>
> .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: 0x56495bc31890>
> rm(P)
>
> proc.time()
user system elapsed
0.380 0.041 0.407
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2019-03-18 r76245) -- "Unsuffered Consequences"
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
0.257 0.044 0.291