Ben Bolstad
| Snapshot Date: 2020-04-14 16:46:13 -0400 (Tue, 14 Apr 2020) |
| URL: https://git.bioconductor.org/packages/BufferedMatrix |
| Branch: RELEASE_3_10 |
| Last Commit: c7a0fa5 |
| Last Changed Date: 2019-10-29 13:07:46 -0400 (Tue, 29 Oct 2019) |
| Back to Multiple platform build/check report for BioC 3.10 |
|
This page was generated on 2020-04-15 12:04:53 -0400 (Wed, 15 Apr 2020).
| Package 205/1823 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||
| BufferedMatrix 1.50.0 Ben Bolstad
| malbec1 | Linux (Ubuntu 18.04.4 LTS) / x86_64 | OK | OK | [ OK ] | | ||||||
| tokay1 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||
| merida1 | OS X 10.11.6 El Capitan / x86_64 | OK | OK | OK | OK | |
| Package: BufferedMatrix |
| Version: 1.50.0 |
| Command: /home/biocbuild/bbs-3.10-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.10-bioc/R/library --no-vignettes --timings BufferedMatrix_1.50.0.tar.gz |
| StartedAt: 2020-04-15 00:22:50 -0400 (Wed, 15 Apr 2020) |
| EndedAt: 2020-04-15 00:23:14 -0400 (Wed, 15 Apr 2020) |
| EllapsedTime: 24.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.10-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.10-bioc/R/library --no-vignettes --timings BufferedMatrix_1.50.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck’ * using R version 3.6.3 (2020-02-29) * 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 ‘1.50.0’ * 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-3.10-bioc/meat/BufferedMatrix.Rcheck/00check.log’ for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.10-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.10-bioc/R/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
gcc -I"/home/biocbuild/bbs-3.10-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.10-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-3.10-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-3.10-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-3.10-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-3.10-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.10-bioc/R/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 3.6.3 (2020-02-29) -- "Holding the Windsock"
Copyright (C) 2020 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.300 0.036 0.335
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 3.6.3 (2020-02-29) -- "Holding the Windsock"
Copyright (C) 2020 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/home/biocbuild/bbs-3.10-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 411706 22.0 856627 45.8 639351 34.2
Vcells 739041 5.7 8388608 64.0 1807347 13.8
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Wed Apr 15 00:23:07 2020"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed Apr 15 00:23:07 2020"
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
>
>
> RowMode(tmp2)
<pointer: 0x5562d2c80ac0>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Wed Apr 15 00:23:08 2020"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed Apr 15 00:23:08 2020"
>
> ColMode(tmp2)
<pointer: 0x5562d2c80ac0>
>
>
>
> ### 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,] 101.632121 0.3431016 -1.9605675 0.240156507
[2,] -1.158716 -1.0899377 -0.1114053 -0.764659802
[3,] 1.586213 1.3344512 2.3714818 -1.960184442
[4,] -1.788782 1.3305239 1.8576692 0.008046121
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.10-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,] 101.632121 0.3431016 1.9605675 0.240156507
[2,] 1.158716 1.0899377 0.1114053 0.764659802
[3,] 1.586213 1.3344512 2.3714818 1.960184442
[4,] 1.788782 1.3305239 1.8576692 0.008046121
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.10-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,] 10.081276 0.5857488 1.4002027 0.49005766
[2,] 1.076437 1.0440008 0.3337743 0.87444828
[3,] 1.259450 1.1551845 1.5399616 1.40006587
[4,] 1.337453 1.1534834 1.3629634 0.08970017
>
> 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-3.10-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,] 227.44488 31.20059 40.96259 30.14073
[2,] 36.92308 36.52995 28.44915 34.50914
[3,] 39.18071 37.88630 42.77110 40.96084
[4,] 40.16332 37.86536 40.48730 25.90505
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5562d49e1800>
> exp(tmp5)
<pointer: 0x5562d49e1800>
> log(tmp5,2)
<pointer: 0x5562d49e1800>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 473.3967
> Min(tmp5)
[1] 52.68489
> mean(tmp5)
[1] 72.69257
> Sum(tmp5)
[1] 14538.51
> Var(tmp5)
[1] 871.1654
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.95564 69.48826 72.16100 70.22835 70.97001 68.71692 69.94454 71.84492
[9] 70.49456 72.12156
> rowSums(tmp5)
[1] 1819.113 1389.765 1443.220 1404.567 1419.400 1374.338 1398.891 1436.898
[9] 1409.891 1442.431
> rowVars(tmp5)
[1] 8160.67646 54.69575 56.37914 98.19351 51.69571 43.85343
[7] 40.08248 61.46934 79.82611 74.95172
> rowSd(tmp5)
[1] 90.336462 7.395657 7.508604 9.909264 7.189973 6.622192 6.331072
[8] 7.840239 8.934546 8.657466
> rowMax(tmp5)
[1] 473.39672 79.13177 89.02244 86.92225 86.34224 81.02808 80.38225
[8] 85.48852 88.53901 86.95150
> rowMin(tmp5)
[1] 58.76347 57.92208 59.86570 53.91796 61.22414 56.21487 59.48247 53.45653
[9] 52.68489 55.74924
>
> colMeans(tmp5)
[1] 115.38137 76.93906 71.90492 71.52297 69.72212 75.61381 70.46723
[8] 69.12823 68.42876 70.82250 67.86718 66.88501 66.39313 71.71383
[15] 69.50193 73.73915 70.07828 73.21764 67.31557 67.20880
> colSums(tmp5)
[1] 1153.8137 769.3906 719.0492 715.2297 697.2212 756.1381 704.6723
[8] 691.2823 684.2876 708.2250 678.6718 668.8501 663.9313 717.1383
[15] 695.0193 737.3915 700.7828 732.1764 673.1557 672.0880
> colVars(tmp5)
[1] 15866.16902 42.97969 125.11729 95.11878 28.73091 45.05815
[7] 36.47386 58.92801 50.82585 43.20747 93.97100 99.99960
[13] 22.94020 47.75679 117.28091 56.97765 36.51795 30.83748
[19] 24.78139 34.24127
> colSd(tmp5)
[1] 125.960982 6.555890 11.185584 9.752886 5.360122 6.712537
[7] 6.039359 7.676458 7.129225 6.573239 9.693864 9.999980
[13] 4.789593 6.910629 10.829631 7.548354 6.043008 5.553150
[19] 4.978091 5.851604
> colMax(tmp5)
[1] 473.39672 82.82552 89.02244 85.48852 77.05847 86.92225 79.13177
[8] 82.45402 79.67028 79.31760 84.41779 80.38225 71.58601 79.11699
[15] 88.53901 86.95150 76.95525 80.82957 75.96436 76.48613
> colMin(tmp5)
[1] 66.81459 64.93994 56.21487 53.91796 61.22414 65.52509 61.72825 60.04999
[9] 56.41918 57.92208 55.74924 52.68489 58.48899 59.48247 54.27684 63.58163
[17] 60.53748 63.73745 57.86950 59.50223
>
>
> ### 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] 90.95564 69.48826 72.16100 70.22835 70.97001 68.71692 69.94454 71.84492
[9] NA 72.12156
> rowSums(tmp5)
[1] 1819.113 1389.765 1443.220 1404.567 1419.400 1374.338 1398.891 1436.898
[9] NA 1442.431
> rowVars(tmp5)
[1] 8160.67646 54.69575 56.37914 98.19351 51.69571 43.85343
[7] 40.08248 61.46934 74.93971 74.95172
> rowSd(tmp5)
[1] 90.336462 7.395657 7.508604 9.909264 7.189973 6.622192 6.331072
[8] 7.840239 8.656772 8.657466
> rowMax(tmp5)
[1] 473.39672 79.13177 89.02244 86.92225 86.34224 81.02808 80.38225
[8] 85.48852 NA 86.95150
> rowMin(tmp5)
[1] 58.76347 57.92208 59.86570 53.91796 61.22414 56.21487 59.48247 53.45653
[9] NA 55.74924
>
> colMeans(tmp5)
[1] 115.38137 76.93906 71.90492 71.52297 69.72212 75.61381 70.46723
[8] 69.12823 68.42876 70.82250 67.86718 66.88501 66.39313 71.71383
[15] 69.50193 73.73915 70.07828 73.21764 NA 67.20880
> colSums(tmp5)
[1] 1153.8137 769.3906 719.0492 715.2297 697.2212 756.1381 704.6723
[8] 691.2823 684.2876 708.2250 678.6718 668.8501 663.9313 717.1383
[15] 695.0193 737.3915 700.7828 732.1764 NA 672.0880
> colVars(tmp5)
[1] 15866.16902 42.97969 125.11729 95.11878 28.73091 45.05815
[7] 36.47386 58.92801 50.82585 43.20747 93.97100 99.99960
[13] 22.94020 47.75679 117.28091 56.97765 36.51795 30.83748
[19] NA 34.24127
> colSd(tmp5)
[1] 125.960982 6.555890 11.185584 9.752886 5.360122 6.712537
[7] 6.039359 7.676458 7.129225 6.573239 9.693864 9.999980
[13] 4.789593 6.910629 10.829631 7.548354 6.043008 5.553150
[19] NA 5.851604
> colMax(tmp5)
[1] 473.39672 82.82552 89.02244 85.48852 77.05847 86.92225 79.13177
[8] 82.45402 79.67028 79.31760 84.41779 80.38225 71.58601 79.11699
[15] 88.53901 86.95150 76.95525 80.82957 NA 76.48613
> colMin(tmp5)
[1] 66.81459 64.93994 56.21487 53.91796 61.22414 65.52509 61.72825 60.04999
[9] 56.41918 57.92208 55.74924 52.68489 58.48899 59.48247 54.27684 63.58163
[17] 60.53748 63.73745 NA 59.50223
>
> Max(tmp5,na.rm=TRUE)
[1] 473.3967
> Min(tmp5,na.rm=TRUE)
[1] 52.68489
> mean(tmp5,na.rm=TRUE)
[1] 72.76706
> Sum(tmp5,na.rm=TRUE)
[1] 14480.65
> Var(tmp5,na.rm=TRUE)
[1] 874.4499
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.95564 69.48826 72.16100 70.22835 70.97001 68.71692 69.94454 71.84492
[9] 71.15904 72.12156
> rowSums(tmp5,na.rm=TRUE)
[1] 1819.113 1389.765 1443.220 1404.567 1419.400 1374.338 1398.891 1436.898
[9] 1352.022 1442.431
> rowVars(tmp5,na.rm=TRUE)
[1] 8160.67646 54.69575 56.37914 98.19351 51.69571 43.85343
[7] 40.08248 61.46934 74.93971 74.95172
> rowSd(tmp5,na.rm=TRUE)
[1] 90.336462 7.395657 7.508604 9.909264 7.189973 6.622192 6.331072
[8] 7.840239 8.656772 8.657466
> rowMax(tmp5,na.rm=TRUE)
[1] 473.39672 79.13177 89.02244 86.92225 86.34224 81.02808 80.38225
[8] 85.48852 88.53901 86.95150
> rowMin(tmp5,na.rm=TRUE)
[1] 58.76347 57.92208 59.86570 53.91796 61.22414 56.21487 59.48247 53.45653
[9] 52.68489 55.74924
>
> colMeans(tmp5,na.rm=TRUE)
[1] 115.38137 76.93906 71.90492 71.52297 69.72212 75.61381 70.46723
[8] 69.12823 68.42876 70.82250 67.86718 66.88501 66.39313 71.71383
[15] 69.50193 73.73915 70.07828 73.21764 68.36513 67.20880
> colSums(tmp5,na.rm=TRUE)
[1] 1153.8137 769.3906 719.0492 715.2297 697.2212 756.1381 704.6723
[8] 691.2823 684.2876 708.2250 678.6718 668.8501 663.9313 717.1383
[15] 695.0193 737.3915 700.7828 732.1764 615.2862 672.0880
> colVars(tmp5,na.rm=TRUE)
[1] 15866.16902 42.97969 125.11729 95.11878 28.73091 45.05815
[7] 36.47386 58.92801 50.82585 43.20747 93.97100 99.99960
[13] 22.94020 47.75679 117.28091 56.97765 36.51795 30.83748
[19] 15.48626 34.24127
> colSd(tmp5,na.rm=TRUE)
[1] 125.960982 6.555890 11.185584 9.752886 5.360122 6.712537
[7] 6.039359 7.676458 7.129225 6.573239 9.693864 9.999980
[13] 4.789593 6.910629 10.829631 7.548354 6.043008 5.553150
[19] 3.935258 5.851604
> colMax(tmp5,na.rm=TRUE)
[1] 473.39672 82.82552 89.02244 85.48852 77.05847 86.92225 79.13177
[8] 82.45402 79.67028 79.31760 84.41779 80.38225 71.58601 79.11699
[15] 88.53901 86.95150 76.95525 80.82957 75.96436 76.48613
> colMin(tmp5,na.rm=TRUE)
[1] 66.81459 64.93994 56.21487 53.91796 61.22414 65.52509 61.72825 60.04999
[9] 56.41918 57.92208 55.74924 52.68489 58.48899 59.48247 54.27684 63.58163
[17] 60.53748 63.73745 62.30723 59.50223
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.95564 69.48826 72.16100 70.22835 70.97001 68.71692 69.94454 71.84492
[9] NaN 72.12156
> rowSums(tmp5,na.rm=TRUE)
[1] 1819.113 1389.765 1443.220 1404.567 1419.400 1374.338 1398.891 1436.898
[9] 0.000 1442.431
> rowVars(tmp5,na.rm=TRUE)
[1] 8160.67646 54.69575 56.37914 98.19351 51.69571 43.85343
[7] 40.08248 61.46934 NA 74.95172
> rowSd(tmp5,na.rm=TRUE)
[1] 90.336462 7.395657 7.508604 9.909264 7.189973 6.622192 6.331072
[8] 7.840239 NA 8.657466
> rowMax(tmp5,na.rm=TRUE)
[1] 473.39672 79.13177 89.02244 86.92225 86.34224 81.02808 80.38225
[8] 85.48852 NA 86.95150
> rowMin(tmp5,na.rm=TRUE)
[1] 58.76347 57.92208 59.86570 53.91796 61.22414 56.21487 59.48247 53.45653
[9] NA 55.74924
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 120.06557 76.43075 72.76821 72.24693 69.19407 76.22301 69.79029
[8] 69.63095 68.49548 70.51274 66.85236 68.46280 67.11157 70.90444
[15] 67.38670 73.35490 69.66097 73.21401 NaN 68.06508
> colSums(tmp5,na.rm=TRUE)
[1] 1080.5901 687.8767 654.9139 650.2224 622.7466 686.0071 628.1126
[8] 626.6786 616.4594 634.6147 601.6713 616.1652 604.0041 638.1400
[15] 606.4803 660.1941 626.9487 658.9261 0.0000 612.5858
> colVars(tmp5,na.rm=TRUE)
[1] 17602.59633 45.44539 132.37264 101.11236 29.18537 46.51536
[7] 35.87767 63.45082 57.12900 47.52894 94.13155 84.49351
[13] 20.00097 46.35644 81.60625 62.43882 39.12353 34.69201
[19] NA 30.27265
> colSd(tmp5,na.rm=TRUE)
[1] 132.674777 6.741319 11.505331 10.055464 5.402349 6.820217
[7] 5.989797 7.965602 7.558373 6.894123 9.702141 9.192035
[13] 4.472244 6.808557 9.033618 7.901824 6.254881 5.889993
[19] NA 5.502058
> colMax(tmp5,na.rm=TRUE)
[1] 473.39672 82.82552 89.02244 85.48852 77.05847 86.92225 79.13177
[8] 82.45402 79.67028 79.31760 84.41779 80.38225 71.58601 79.11699
[15] 81.50932 86.95150 76.95525 80.82957 -Inf 76.48613
> colMin(tmp5,na.rm=TRUE)
[1] 66.81459 64.93994 56.21487 53.91796 61.22414 65.52509 61.72825 60.04999
[9] 56.41918 57.92208 55.74924 53.45653 58.48899 59.48247 54.27684 63.58163
[17] 60.53748 63.73745 Inf 60.43608
>
>
>
>
> 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] 178.00863 90.73256 251.30994 293.07361 271.18288 364.04521 337.84367
[8] 194.94041 131.09277 214.54003
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 178.00863 90.73256 251.30994 293.07361 271.18288 364.04521 337.84367
[8] 194.94041 131.09277 214.54003
>
>
>
> 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 5.684342e-14 0.000000e+00 -7.105427e-14 -8.526513e-14
[6] 0.000000e+00 0.000000e+00 2.842171e-14 3.410605e-13 -1.278977e-13
[11] 7.105427e-14 -5.684342e-14 0.000000e+00 -3.126388e-13 -2.842171e-14
[16] -2.842171e-14 0.000000e+00 -1.705303e-13 2.842171e-14 1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
5 10
4 2
6 17
10 16
6 14
6 8
3 7
5 17
3 12
9 3
4 8
1 6
6 7
2 4
4 2
8 19
7 16
2 20
10 14
9 2
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] 2.096319
> Min(tmp)
[1] -2.626519
> mean(tmp)
[1] -0.130021
> Sum(tmp)
[1] -13.0021
> Var(tmp)
[1] 0.9480278
>
> rowMeans(tmp)
[1] -0.130021
> rowSums(tmp)
[1] -13.0021
> rowVars(tmp)
[1] 0.9480278
> rowSd(tmp)
[1] 0.9736672
> rowMax(tmp)
[1] 2.096319
> rowMin(tmp)
[1] -2.626519
>
> colMeans(tmp)
[1] 0.194398084 -1.083823247 0.038975679 0.120305386 0.031533278
[6] 0.029282859 1.116123060 -0.890433184 -0.342721336 -0.769452792
[11] -0.465889362 1.200438091 -0.131522615 -0.318310585 1.362028342
[16] -0.506961455 0.379533953 0.220806532 -0.856815545 -0.724871035
[21] -1.310862529 0.399885123 -1.356333610 0.660900658 -1.444366166
[26] 0.996530193 0.023590634 1.769318476 -0.324074044 0.517849646
[31] -0.239419381 -0.549599704 -0.923808027 0.396392022 -1.747384661
[36] -0.189432228 -0.175451474 -1.782771880 0.626517069 -1.277460872
[41] -0.486475966 0.858099065 0.640896435 -0.387413795 -2.626518903
[46] 2.096318926 -0.470942438 -0.341863336 -0.195331867 1.098741412
[51] -0.777212481 0.691440846 -0.354697471 -1.836766030 -0.224799065
[56] -0.395593269 -1.313700866 -0.181549212 -0.437693411 -1.312555270
[61] 1.007146789 1.154005481 -0.005035255 -0.945392647 0.595790279
[66] 1.352106448 -0.489812038 -0.153351151 -0.171380846 0.018499007
[71] 0.090338216 -1.905223333 -1.410771477 1.141791965 0.746322897
[76] -1.344745043 0.755185797 1.297562020 0.120136612 -0.902310994
[81] 0.228899134 2.040296807 0.978281091 -0.098480925 -0.220507066
[86] -0.611438503 -0.405399540 0.303795994 -0.102030232 -0.583112026
[91] -1.270964405 1.518866629 -0.264782294 -1.625021429 1.429456819
[96] 0.655552375 1.604777417 -1.197765656 -2.176802679 -0.871615195
> colSums(tmp)
[1] 0.194398084 -1.083823247 0.038975679 0.120305386 0.031533278
[6] 0.029282859 1.116123060 -0.890433184 -0.342721336 -0.769452792
[11] -0.465889362 1.200438091 -0.131522615 -0.318310585 1.362028342
[16] -0.506961455 0.379533953 0.220806532 -0.856815545 -0.724871035
[21] -1.310862529 0.399885123 -1.356333610 0.660900658 -1.444366166
[26] 0.996530193 0.023590634 1.769318476 -0.324074044 0.517849646
[31] -0.239419381 -0.549599704 -0.923808027 0.396392022 -1.747384661
[36] -0.189432228 -0.175451474 -1.782771880 0.626517069 -1.277460872
[41] -0.486475966 0.858099065 0.640896435 -0.387413795 -2.626518903
[46] 2.096318926 -0.470942438 -0.341863336 -0.195331867 1.098741412
[51] -0.777212481 0.691440846 -0.354697471 -1.836766030 -0.224799065
[56] -0.395593269 -1.313700866 -0.181549212 -0.437693411 -1.312555270
[61] 1.007146789 1.154005481 -0.005035255 -0.945392647 0.595790279
[66] 1.352106448 -0.489812038 -0.153351151 -0.171380846 0.018499007
[71] 0.090338216 -1.905223333 -1.410771477 1.141791965 0.746322897
[76] -1.344745043 0.755185797 1.297562020 0.120136612 -0.902310994
[81] 0.228899134 2.040296807 0.978281091 -0.098480925 -0.220507066
[86] -0.611438503 -0.405399540 0.303795994 -0.102030232 -0.583112026
[91] -1.270964405 1.518866629 -0.264782294 -1.625021429 1.429456819
[96] 0.655552375 1.604777417 -1.197765656 -2.176802679 -0.871615195
> 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] 0.194398084 -1.083823247 0.038975679 0.120305386 0.031533278
[6] 0.029282859 1.116123060 -0.890433184 -0.342721336 -0.769452792
[11] -0.465889362 1.200438091 -0.131522615 -0.318310585 1.362028342
[16] -0.506961455 0.379533953 0.220806532 -0.856815545 -0.724871035
[21] -1.310862529 0.399885123 -1.356333610 0.660900658 -1.444366166
[26] 0.996530193 0.023590634 1.769318476 -0.324074044 0.517849646
[31] -0.239419381 -0.549599704 -0.923808027 0.396392022 -1.747384661
[36] -0.189432228 -0.175451474 -1.782771880 0.626517069 -1.277460872
[41] -0.486475966 0.858099065 0.640896435 -0.387413795 -2.626518903
[46] 2.096318926 -0.470942438 -0.341863336 -0.195331867 1.098741412
[51] -0.777212481 0.691440846 -0.354697471 -1.836766030 -0.224799065
[56] -0.395593269 -1.313700866 -0.181549212 -0.437693411 -1.312555270
[61] 1.007146789 1.154005481 -0.005035255 -0.945392647 0.595790279
[66] 1.352106448 -0.489812038 -0.153351151 -0.171380846 0.018499007
[71] 0.090338216 -1.905223333 -1.410771477 1.141791965 0.746322897
[76] -1.344745043 0.755185797 1.297562020 0.120136612 -0.902310994
[81] 0.228899134 2.040296807 0.978281091 -0.098480925 -0.220507066
[86] -0.611438503 -0.405399540 0.303795994 -0.102030232 -0.583112026
[91] -1.270964405 1.518866629 -0.264782294 -1.625021429 1.429456819
[96] 0.655552375 1.604777417 -1.197765656 -2.176802679 -0.871615195
> colMin(tmp)
[1] 0.194398084 -1.083823247 0.038975679 0.120305386 0.031533278
[6] 0.029282859 1.116123060 -0.890433184 -0.342721336 -0.769452792
[11] -0.465889362 1.200438091 -0.131522615 -0.318310585 1.362028342
[16] -0.506961455 0.379533953 0.220806532 -0.856815545 -0.724871035
[21] -1.310862529 0.399885123 -1.356333610 0.660900658 -1.444366166
[26] 0.996530193 0.023590634 1.769318476 -0.324074044 0.517849646
[31] -0.239419381 -0.549599704 -0.923808027 0.396392022 -1.747384661
[36] -0.189432228 -0.175451474 -1.782771880 0.626517069 -1.277460872
[41] -0.486475966 0.858099065 0.640896435 -0.387413795 -2.626518903
[46] 2.096318926 -0.470942438 -0.341863336 -0.195331867 1.098741412
[51] -0.777212481 0.691440846 -0.354697471 -1.836766030 -0.224799065
[56] -0.395593269 -1.313700866 -0.181549212 -0.437693411 -1.312555270
[61] 1.007146789 1.154005481 -0.005035255 -0.945392647 0.595790279
[66] 1.352106448 -0.489812038 -0.153351151 -0.171380846 0.018499007
[71] 0.090338216 -1.905223333 -1.410771477 1.141791965 0.746322897
[76] -1.344745043 0.755185797 1.297562020 0.120136612 -0.902310994
[81] 0.228899134 2.040296807 0.978281091 -0.098480925 -0.220507066
[86] -0.611438503 -0.405399540 0.303795994 -0.102030232 -0.583112026
[91] -1.270964405 1.518866629 -0.264782294 -1.625021429 1.429456819
[96] 0.655552375 1.604777417 -1.197765656 -2.176802679 -0.871615195
> colMedians(tmp)
[1] 0.194398084 -1.083823247 0.038975679 0.120305386 0.031533278
[6] 0.029282859 1.116123060 -0.890433184 -0.342721336 -0.769452792
[11] -0.465889362 1.200438091 -0.131522615 -0.318310585 1.362028342
[16] -0.506961455 0.379533953 0.220806532 -0.856815545 -0.724871035
[21] -1.310862529 0.399885123 -1.356333610 0.660900658 -1.444366166
[26] 0.996530193 0.023590634 1.769318476 -0.324074044 0.517849646
[31] -0.239419381 -0.549599704 -0.923808027 0.396392022 -1.747384661
[36] -0.189432228 -0.175451474 -1.782771880 0.626517069 -1.277460872
[41] -0.486475966 0.858099065 0.640896435 -0.387413795 -2.626518903
[46] 2.096318926 -0.470942438 -0.341863336 -0.195331867 1.098741412
[51] -0.777212481 0.691440846 -0.354697471 -1.836766030 -0.224799065
[56] -0.395593269 -1.313700866 -0.181549212 -0.437693411 -1.312555270
[61] 1.007146789 1.154005481 -0.005035255 -0.945392647 0.595790279
[66] 1.352106448 -0.489812038 -0.153351151 -0.171380846 0.018499007
[71] 0.090338216 -1.905223333 -1.410771477 1.141791965 0.746322897
[76] -1.344745043 0.755185797 1.297562020 0.120136612 -0.902310994
[81] 0.228899134 2.040296807 0.978281091 -0.098480925 -0.220507066
[86] -0.611438503 -0.405399540 0.303795994 -0.102030232 -0.583112026
[91] -1.270964405 1.518866629 -0.264782294 -1.625021429 1.429456819
[96] 0.655552375 1.604777417 -1.197765656 -2.176802679 -0.871615195
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.1943981 -1.083823 0.03897568 0.1203054 0.03153328 0.02928286 1.116123
[2,] 0.1943981 -1.083823 0.03897568 0.1203054 0.03153328 0.02928286 1.116123
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.8904332 -0.3427213 -0.7694528 -0.4658894 1.200438 -0.1315226 -0.3183106
[2,] -0.8904332 -0.3427213 -0.7694528 -0.4658894 1.200438 -0.1315226 -0.3183106
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.362028 -0.5069615 0.379534 0.2208065 -0.8568155 -0.724871 -1.310863
[2,] 1.362028 -0.5069615 0.379534 0.2208065 -0.8568155 -0.724871 -1.310863
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.3998851 -1.356334 0.6609007 -1.444366 0.9965302 0.02359063 1.769318
[2,] 0.3998851 -1.356334 0.6609007 -1.444366 0.9965302 0.02359063 1.769318
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.324074 0.5178496 -0.2394194 -0.5495997 -0.923808 0.396392 -1.747385
[2,] -0.324074 0.5178496 -0.2394194 -0.5495997 -0.923808 0.396392 -1.747385
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.1894322 -0.1754515 -1.782772 0.6265171 -1.277461 -0.486476 0.8580991
[2,] -0.1894322 -0.1754515 -1.782772 0.6265171 -1.277461 -0.486476 0.8580991
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.6408964 -0.3874138 -2.626519 2.096319 -0.4709424 -0.3418633 -0.1953319
[2,] 0.6408964 -0.3874138 -2.626519 2.096319 -0.4709424 -0.3418633 -0.1953319
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 1.098741 -0.7772125 0.6914408 -0.3546975 -1.836766 -0.2247991 -0.3955933
[2,] 1.098741 -0.7772125 0.6914408 -0.3546975 -1.836766 -0.2247991 -0.3955933
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -1.313701 -0.1815492 -0.4376934 -1.312555 1.007147 1.154005 -0.005035255
[2,] -1.313701 -0.1815492 -0.4376934 -1.312555 1.007147 1.154005 -0.005035255
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.9453926 0.5957903 1.352106 -0.489812 -0.1533512 -0.1713808 0.01849901
[2,] -0.9453926 0.5957903 1.352106 -0.489812 -0.1533512 -0.1713808 0.01849901
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.09033822 -1.905223 -1.410771 1.141792 0.7463229 -1.344745 0.7551858
[2,] 0.09033822 -1.905223 -1.410771 1.141792 0.7463229 -1.344745 0.7551858
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.297562 0.1201366 -0.902311 0.2288991 2.040297 0.9782811 -0.09848093
[2,] 1.297562 0.1201366 -0.902311 0.2288991 2.040297 0.9782811 -0.09848093
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.2205071 -0.6114385 -0.4053995 0.303796 -0.1020302 -0.583112 -1.270964
[2,] -0.2205071 -0.6114385 -0.4053995 0.303796 -0.1020302 -0.583112 -1.270964
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 1.518867 -0.2647823 -1.625021 1.429457 0.6555524 1.604777 -1.197766
[2,] 1.518867 -0.2647823 -1.625021 1.429457 0.6555524 1.604777 -1.197766
[,99] [,100]
[1,] -2.176803 -0.8716152
[2,] -2.176803 -0.8716152
>
>
> Max(tmp2)
[1] 2.168335
> Min(tmp2)
[1] -2.475522
> mean(tmp2)
[1] -0.004937547
> Sum(tmp2)
[1] -0.4937547
> Var(tmp2)
[1] 0.8675127
>
> rowMeans(tmp2)
[1] -0.47179419 -0.57451681 0.05358992 0.87773697 -0.20208300 -0.76438625
[7] 1.28930190 -0.80205195 0.37682821 0.22227994 -0.29342954 1.74781965
[13] -0.40951379 2.16833501 -1.14746680 0.45144940 -0.12140826 -0.57888358
[19] 1.15472364 0.77731346 0.25170261 1.16113749 -0.76011633 -1.52119651
[25] -1.09826411 0.24863440 0.27460117 0.25874687 -0.40314693 0.86848686
[31] 0.54236740 -0.46905875 -0.93212363 -0.18349355 0.33573147 -1.75992261
[37] 0.92933064 0.44342693 -0.80467844 1.67557471 0.66878745 -0.82212285
[43] -0.37958828 -0.27187838 0.48807960 -0.03551077 -1.68964041 0.71730003
[49] -1.69056131 0.34007144 0.72808134 -0.62549043 1.79945369 -1.52672321
[55] 0.71812441 1.79292703 0.65552343 0.49687355 -2.17641104 0.24677170
[61] 1.17864239 0.60035068 -0.94100761 0.75214900 1.25312406 0.03012458
[67] -0.58914981 -2.47552150 -0.60998952 -0.26511625 -0.85286376 -1.33114140
[73] 1.10138486 0.28105766 0.33047492 0.23723755 1.38915979 -0.07498068
[79] 0.65278072 0.44583607 -0.59539805 -0.21334673 -0.73791186 -0.50742427
[85] 0.18084663 0.34138748 -0.91701951 0.97607544 0.45608156 1.35325108
[91] 0.53857744 -1.50682694 0.44067317 -0.06653145 -0.11841170 -0.40076545
[97] 0.09973517 -0.69407356 -1.64951614 -0.83135940
> rowSums(tmp2)
[1] -0.47179419 -0.57451681 0.05358992 0.87773697 -0.20208300 -0.76438625
[7] 1.28930190 -0.80205195 0.37682821 0.22227994 -0.29342954 1.74781965
[13] -0.40951379 2.16833501 -1.14746680 0.45144940 -0.12140826 -0.57888358
[19] 1.15472364 0.77731346 0.25170261 1.16113749 -0.76011633 -1.52119651
[25] -1.09826411 0.24863440 0.27460117 0.25874687 -0.40314693 0.86848686
[31] 0.54236740 -0.46905875 -0.93212363 -0.18349355 0.33573147 -1.75992261
[37] 0.92933064 0.44342693 -0.80467844 1.67557471 0.66878745 -0.82212285
[43] -0.37958828 -0.27187838 0.48807960 -0.03551077 -1.68964041 0.71730003
[49] -1.69056131 0.34007144 0.72808134 -0.62549043 1.79945369 -1.52672321
[55] 0.71812441 1.79292703 0.65552343 0.49687355 -2.17641104 0.24677170
[61] 1.17864239 0.60035068 -0.94100761 0.75214900 1.25312406 0.03012458
[67] -0.58914981 -2.47552150 -0.60998952 -0.26511625 -0.85286376 -1.33114140
[73] 1.10138486 0.28105766 0.33047492 0.23723755 1.38915979 -0.07498068
[79] 0.65278072 0.44583607 -0.59539805 -0.21334673 -0.73791186 -0.50742427
[85] 0.18084663 0.34138748 -0.91701951 0.97607544 0.45608156 1.35325108
[91] 0.53857744 -1.50682694 0.44067317 -0.06653145 -0.11841170 -0.40076545
[97] 0.09973517 -0.69407356 -1.64951614 -0.83135940
> 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] -0.47179419 -0.57451681 0.05358992 0.87773697 -0.20208300 -0.76438625
[7] 1.28930190 -0.80205195 0.37682821 0.22227994 -0.29342954 1.74781965
[13] -0.40951379 2.16833501 -1.14746680 0.45144940 -0.12140826 -0.57888358
[19] 1.15472364 0.77731346 0.25170261 1.16113749 -0.76011633 -1.52119651
[25] -1.09826411 0.24863440 0.27460117 0.25874687 -0.40314693 0.86848686
[31] 0.54236740 -0.46905875 -0.93212363 -0.18349355 0.33573147 -1.75992261
[37] 0.92933064 0.44342693 -0.80467844 1.67557471 0.66878745 -0.82212285
[43] -0.37958828 -0.27187838 0.48807960 -0.03551077 -1.68964041 0.71730003
[49] -1.69056131 0.34007144 0.72808134 -0.62549043 1.79945369 -1.52672321
[55] 0.71812441 1.79292703 0.65552343 0.49687355 -2.17641104 0.24677170
[61] 1.17864239 0.60035068 -0.94100761 0.75214900 1.25312406 0.03012458
[67] -0.58914981 -2.47552150 -0.60998952 -0.26511625 -0.85286376 -1.33114140
[73] 1.10138486 0.28105766 0.33047492 0.23723755 1.38915979 -0.07498068
[79] 0.65278072 0.44583607 -0.59539805 -0.21334673 -0.73791186 -0.50742427
[85] 0.18084663 0.34138748 -0.91701951 0.97607544 0.45608156 1.35325108
[91] 0.53857744 -1.50682694 0.44067317 -0.06653145 -0.11841170 -0.40076545
[97] 0.09973517 -0.69407356 -1.64951614 -0.83135940
> rowMin(tmp2)
[1] -0.47179419 -0.57451681 0.05358992 0.87773697 -0.20208300 -0.76438625
[7] 1.28930190 -0.80205195 0.37682821 0.22227994 -0.29342954 1.74781965
[13] -0.40951379 2.16833501 -1.14746680 0.45144940 -0.12140826 -0.57888358
[19] 1.15472364 0.77731346 0.25170261 1.16113749 -0.76011633 -1.52119651
[25] -1.09826411 0.24863440 0.27460117 0.25874687 -0.40314693 0.86848686
[31] 0.54236740 -0.46905875 -0.93212363 -0.18349355 0.33573147 -1.75992261
[37] 0.92933064 0.44342693 -0.80467844 1.67557471 0.66878745 -0.82212285
[43] -0.37958828 -0.27187838 0.48807960 -0.03551077 -1.68964041 0.71730003
[49] -1.69056131 0.34007144 0.72808134 -0.62549043 1.79945369 -1.52672321
[55] 0.71812441 1.79292703 0.65552343 0.49687355 -2.17641104 0.24677170
[61] 1.17864239 0.60035068 -0.94100761 0.75214900 1.25312406 0.03012458
[67] -0.58914981 -2.47552150 -0.60998952 -0.26511625 -0.85286376 -1.33114140
[73] 1.10138486 0.28105766 0.33047492 0.23723755 1.38915979 -0.07498068
[79] 0.65278072 0.44583607 -0.59539805 -0.21334673 -0.73791186 -0.50742427
[85] 0.18084663 0.34138748 -0.91701951 0.97607544 0.45608156 1.35325108
[91] 0.53857744 -1.50682694 0.44067317 -0.06653145 -0.11841170 -0.40076545
[97] 0.09973517 -0.69407356 -1.64951614 -0.83135940
>
> colMeans(tmp2)
[1] -0.004937547
> colSums(tmp2)
[1] -0.4937547
> colVars(tmp2)
[1] 0.8675127
> colSd(tmp2)
[1] 0.9314036
> colMax(tmp2)
[1] 2.168335
> colMin(tmp2)
[1] -2.475522
> colMedians(tmp2)
[1] 0.07666254
> colRanges(tmp2)
[,1]
[1,] -2.475522
[2,] 2.168335
>
> 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] 0.6399358 -3.8509556 -0.8828257 1.1575110 0.2329846 -4.7459306
[7] 1.7425232 0.3993988 -3.5109142 5.3756748
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8140453
[2,] -0.4441963
[3,] 0.3489639
[4,] 0.7315853
[5,] 1.4280518
>
> rowApply(tmp,sum)
[1] 0.2594268 -1.6163235 4.9482570 -2.5334757 -0.6938695 -0.3314919
[7] 3.6372219 2.7843195 -4.4314483 -5.4652142
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 10 5 6 8 9 2 6 2 1
[2,] 1 2 2 2 3 5 6 4 7 7
[3,] 2 1 7 5 5 6 10 8 10 5
[4,] 7 7 8 9 9 3 4 5 6 2
[5,] 10 5 3 10 6 2 8 3 1 9
[6,] 3 8 6 8 1 1 1 10 3 3
[7,] 4 6 4 7 7 4 7 7 5 8
[8,] 9 3 1 3 2 8 9 9 9 10
[9,] 5 4 9 1 4 7 3 2 4 6
[10,] 6 9 10 4 10 10 5 1 8 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.82696466 -0.02521443 -0.87251768 -1.47928893 3.86829395 0.96279565
[7] 1.72631410 -1.98357682 7.06296803 0.06852004 -1.08832247 -3.20179858
[13] 2.13499886 -0.15843921 1.02306137 -0.50868880 -1.57882185 3.77841945
[19] -2.11818445 1.55598318
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1946323
[2,] -0.2531757
[3,] 0.2517583
[4,] 0.5260549
[5,] 1.4969594
>
> rowApply(tmp,sum)
[1] 4.333812 1.539285 1.022903 1.004466 2.093000
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 2 12 19 16 9
[2,] 4 19 6 6 8
[3,] 20 1 16 5 3
[4,] 1 18 4 14 4
[5,] 7 17 12 19 17
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.1946323 -0.7651794 1.8280913 -2.1552519 -0.1409004 0.1320922
[2,] 0.2517583 2.2284011 -1.9252055 1.6128310 1.1805470 0.8610251
[3,] 1.4969594 -0.4459251 0.7341850 -0.5015818 0.1473239 -0.5227424
[4,] 0.5260549 -0.6746625 -0.6850284 0.2516224 1.7764280 0.2557301
[5,] -0.2531757 -0.3678485 -0.8245601 -0.6869087 0.9048955 0.2366906
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.05275776 0.9460450 1.1123390 1.0419333 -0.9447012 -0.6662092
[2,] -0.40063287 -0.4745551 3.3837322 -0.5388709 -0.8773698 -0.5862976
[3,] 0.36655315 -2.2814182 1.6294390 -0.2004689 1.4899122 -0.1583012
[4,] 1.69325008 -0.5902191 0.1495942 -0.9031348 -0.2385524 -1.1781441
[5,] 0.01438598 0.4165705 0.7878637 0.6690614 -0.5176113 -0.6128466
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.7509719 1.00575745 0.8224834 -0.4310380 1.524305 0.8525186
[2,] 0.4328544 -1.51990131 -0.2101341 -0.5758258 -1.522170 0.6086045
[3,] -0.1300863 -0.26066159 -0.4881121 0.2108746 -1.436337 1.4522497
[4,] 2.2146695 0.02222024 -0.2580961 1.3233922 -1.473703 0.1940800
[5,] -1.1334106 0.59414600 1.1569203 -1.0360918 1.329084 0.6709666
[,19] [,20]
[1,] -0.04686703 0.6092967
[2,] -1.27348625 0.8839811
[3,] -0.43278202 0.3538216
[4,] -1.56325460 0.1622199
[5,] 1.19820545 -0.4533362
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.10-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-3.10-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 644 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 558 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.10-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 0.2096991 -0.7263813 -0.9849504 -0.08906859 -0.2543139 -1.882888 -1.029823
col8 col9 col10 col11 col12 col13 col14
row1 0.1929735 -0.2565792 1.716073 -0.1695128 0.6099777 -0.2675385 1.824814
col15 col16 col17 col18 col19 col20
row1 0.4805492 -1.9275 -0.06089231 0.8223889 0.4393883 1.015806
> tmp[,"col10"]
col10
row1 1.7160727
row2 0.3740431
row3 1.3310814
row4 -0.2321510
row5 -1.7680809
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.2096991 -0.7263813 -0.9849504 -0.08906859 -0.2543139 -1.8828876
row5 0.9054441 -2.5774917 1.2159949 -0.53539923 0.4377845 0.2112923
col7 col8 col9 col10 col11 col12
row1 -1.0298232 0.1929735 -0.2565792 1.716073 -0.1695128 0.6099777
row5 0.3195084 -1.3641771 -1.2811018 -1.768081 -0.2345467 0.3700051
col13 col14 col15 col16 col17 col18
row1 -0.26753851 1.8248143 0.48054924 -1.92750002 -0.06089231 0.8223889
row5 0.05250521 0.3093173 0.05984216 0.04540908 0.24265090 -0.3328251
col19 col20
row1 0.4393883 1.0158063
row5 2.1961246 0.1347669
> tmp[,c("col6","col20")]
col6 col20
row1 -1.88288760 1.015806340
row2 1.40118394 2.025957398
row3 0.01763477 -0.009018803
row4 -0.72855550 -0.441049481
row5 0.21129228 0.134766905
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.8828876 1.0158063
row5 0.2112923 0.1347669
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.94211 50.98816 50.3373 50.87888 49.6767 105.4669 50.97246 51.21567
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.47248 51.01014 49.22666 49.82938 48.17986 49.13739 51.76357 49.9051
col17 col18 col19 col20
row1 49.00961 52.33895 50.43914 105.1437
> tmp[,"col10"]
col10
row1 51.01014
row2 29.45655
row3 30.86082
row4 31.07726
row5 50.85634
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.94211 50.98816 50.33730 50.87888 49.67670 105.4669 50.97246 51.21567
row5 49.73270 49.47680 47.84874 50.90112 51.50802 105.4173 50.95969 48.36349
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.47248 51.01014 49.22666 49.82938 48.17986 49.13739 51.76357 49.90510
row5 48.92843 50.85634 51.98514 49.62179 49.29878 48.82653 50.65304 50.73049
col17 col18 col19 col20
row1 49.00961 52.33895 50.43914 105.1437
row5 50.11609 50.12138 49.61719 103.7162
> tmp[,c("col6","col20")]
col6 col20
row1 105.46693 105.14374
row2 75.69668 73.95148
row3 75.22329 76.63208
row4 74.69178 73.32438
row5 105.41733 103.71625
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.4669 105.1437
row5 105.4173 103.7162
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.4669 105.1437
row5 105.4173 103.7162
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.4161581
[2,] -1.3909885
[3,] -1.3325908
[4,] -1.1226650
[5,] -0.6347098
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.11985976 0.348044687
[2,] 1.15090618 -0.749764988
[3,] -0.08451391 1.364147626
[4,] -1.24015562 0.969156762
[5,] -1.08852018 0.001861988
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.5655211 1.88432089
[2,] -1.7177730 -0.05363335
[3,] 0.3752423 -0.38639322
[4,] 1.8292312 -0.23013416
[5,] 1.4682138 1.45474295
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.5655211
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.5655211
[2,] -1.7177730
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 -0.05335515 -0.4947151 0.2149932 -0.4721141 0.6461128 1.2039826
row1 -0.15633324 -0.7294812 -1.6759556 -0.8572948 -0.1779855 -0.4541138
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -1.966025 0.8763824 0.5798431 0.9040571 -0.1873851 0.1412787 -1.2568448
row1 -0.844302 -0.6305396 0.2497965 0.2338027 -0.6088405 -2.3865743 -0.7329474
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 0.4874558 -1.3581500 1.7265367 -0.2609082 1.144761 0.7519602 0.3581896
row1 -0.2009655 -0.6674917 -0.1726081 -0.2688245 -1.587781 0.8168424 -0.3819283
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.559566 1.254845 -1.571284 -0.2748537 1.028239 -0.2191641 -1.306923
[,8] [,9] [,10]
row2 -0.1432824 1.519941 0.6164319
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.7696449 -0.7919905 -1.441117 -0.5690614 2.182935 0.5873326 -0.9416702
[,8] [,9] [,10] [,11] [,12] [,13]
row5 -0.384514 -0.5276518 -0.7953631 -0.04705079 -0.9447596 -1.666137
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.0149784 -0.9875512 -0.4266155 -1.454346 0.5549801 0.4943919 0.9998664
>
>
> 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: 0x5562d459ca50>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM419051f7281a"
[2] "/home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM41902a508757"
[3] "/home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM4190488ce8f8"
[4] "/home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM419019f23977"
[5] "/home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM4190182e797e"
[6] "/home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM41905a24cabe"
[7] "/home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM41906905a71f"
[8] "/home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM4190513cfd00"
[9] "/home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM4190606a4a70"
[10] "/home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM41902dd3f700"
[11] "/home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM41902d4c88ea"
[12] "/home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM419023a6f329"
[13] "/home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM419029e7ce36"
[14] "/home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM419079df7fef"
[15] "/home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests/BM419068c7ee18"
>
>
> ### 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: 0x5562d500abf0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5562d500abf0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.10-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5562d500abf0>
> rowMedians(tmp)
[1] -0.078764194 -0.109178754 -0.299583560 -0.585514235 -0.075689019
[6] 0.199753913 -0.097127251 -0.321583699 0.462867810 -0.074656308
[11] -0.106337213 -0.495920011 0.571552459 0.367817747 0.269983616
[16] -0.253764936 -0.233241930 0.199213620 0.374052778 -0.092141841
[21] 0.123023845 -0.554326453 -0.043878317 0.342466186 -0.326809657
[26] 0.525999040 -0.508278447 -0.305889227 -0.245710495 -0.445664728
[31] 0.689342109 -0.026961713 0.205993463 -0.554062299 0.444233594
[36] -0.487619860 -0.031645546 -0.062507531 -0.269097624 -0.250332305
[41] 0.592408275 -0.509460902 0.146181629 -0.009465656 0.290044974
[46] -0.214271191 -0.651371871 0.238841967 -0.015414006 -0.136429543
[51] 0.299298826 -0.408349308 -0.431086836 -0.057043941 0.233354577
[56] -0.013781675 0.393794778 -0.033478472 0.533919277 0.263109842
[61] 0.078653050 0.133421775 0.050592252 -0.323315704 0.373874168
[66] -0.648841833 0.240739709 -0.155700019 -0.501717061 -0.419192377
[71] 0.014685328 0.696705952 0.394818978 -0.295094652 -0.167141658
[76] -0.432436820 0.405126491 -0.009161487 -0.113672657 -0.081001849
[81] 0.006250328 0.106698556 -0.466397208 -0.613484460 0.240028857
[86] 0.305918754 -0.225023253 -0.198219041 -0.037737112 -0.399497942
[91] -0.496510047 -0.275077369 -0.221688919 0.317699292 -0.197376951
[96] 0.504632220 0.422818246 -0.439072038 -0.062218834 0.202703792
[101] -0.314911003 0.236060151 0.164355796 0.118950094 0.129514176
[106] -0.491059531 -0.327025932 -0.482177499 -0.270117501 -0.475869876
[111] -0.120452665 0.168253685 -0.450048287 -0.568566261 -0.094226541
[116] 0.382879169 -0.314618193 0.342700943 0.225329390 -0.210595512
[121] 0.035061992 -0.242552426 0.044614246 0.127788452 0.524785564
[126] -0.223820138 0.112620798 0.272548411 -0.481391270 0.191779773
[131] 0.043118859 -0.155189619 0.036667555 -0.302843064 0.028887980
[136] -0.036895462 0.005444435 0.378402215 0.116867369 1.232505517
[141] -0.462095183 -0.124998935 -0.245022334 0.441293025 0.007758188
[146] 0.410376911 0.108408811 0.256063968 0.374753306 0.049585957
[151] 0.327005797 0.104057948 -0.149069119 -0.176272707 -0.610678013
[156] 0.321380411 -0.116037597 0.257112727 0.196943951 0.103430610
[161] -0.165661432 0.439207732 -0.225563830 0.350612860 -0.501635813
[166] 0.499134498 -0.288516596 -0.188548012 -0.250783922 -0.252443001
[171] -0.071520229 0.482011317 0.222176888 -0.317090708 -0.550475645
[176] 0.165891106 -0.048293406 -0.070171404 0.074400499 -0.384007418
[181] 0.292571362 0.578814008 0.432643742 -0.225333909 -0.253195381
[186] -0.098549680 0.060343630 0.467165640 0.170516353 -0.121541349
[191] 0.323980382 -0.135143047 -0.297500111 -0.496479415 -0.211983322
[196] 0.307110249 -0.193370403 -0.397336989 -0.082499582 -0.241781387
[201] -0.253196044 -0.801035446 0.400701317 0.072493037 -0.323237695
[206] -0.128939511 -0.281978261 0.148631313 0.242295778 -0.138298213
[211] 0.162617836 0.002959864 -0.033883545 0.012021719 -0.553620331
[216] -0.558690709 -0.392052671 0.230990087 0.381786276 0.385458872
[221] 0.493081475 -0.362065016 -0.221380855 0.050097665 -0.176706489
[226] 0.272725584 0.451558473 -0.034564449 0.165113163 0.179743008
>
> proc.time()
user system elapsed
2.052 0.936 3.054
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 3.6.3 (2020-02-29) -- "Holding the Windsock"
Copyright (C) 2020 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x564186425ac0>
> .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: 0x564186425ac0>
> .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: 0x564186425ac0>
> .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: 0x564186425ac0>
> 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: 0x5641868ea9c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5641868ea9c0>
> .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: 0x5641868ea9c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5641868ea9c0>
> .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: 0x5641868ea9c0>
> 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: 0x564186ba1820>
> .Call("R_bm_AddColumn",P)
<pointer: 0x564186ba1820>
> .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: 0x564186ba1820>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x564186ba1820>
> .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: 0x564186ba1820>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x564186ba1820>
> .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: 0x564186ba1820>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x564186ba1820>
> .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: 0x564186ba1820>
> 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: 0x56418623eb00>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x56418623eb00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56418623eb00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56418623eb00>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile444d6b4d5880" "BufferedMatrixFile444d6e2dd9c7"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile444d6b4d5880" "BufferedMatrixFile444d6e2dd9c7"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x56418644b390>
> .Call("R_bm_AddColumn",P)
<pointer: 0x56418644b390>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x56418644b390>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x56418644b390>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x56418644b390>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x56418644b390>
> .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: 0x5641868f3ba0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5641868f3ba0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5641868f3ba0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5641868f3ba0>
> 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: 0x5641869628c0>
> .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: 0x5641869628c0>
> rm(P)
>
> proc.time()
user system elapsed
0.360 0.028 0.393
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 3.6.3 (2020-02-29) -- "Holding the Windsock"
Copyright (C) 2020 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
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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
0.320 0.040 0.365