| Back to Multiple platform build/check report for BioC 3.14 |
|
This page was generated on 2022-04-13 12:05:08 -0400 (Wed, 13 Apr 2022).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 20.04.4 LTS) | x86_64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4324 |
| tokay2 | Windows Server 2012 R2 Standard | x64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4077 |
| machv2 | macOS 10.14.6 Mojave | x86_64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4137 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
|
To the developers/maintainers of the BufferedMatrix package: - Please allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See How and When does the builder pull? When will my changes propagate? for more information. - Make sure to use the following settings in order to reproduce any error or warning you see on this page. |
| Package 223/2083 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.58.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 20.04.4 LTS) / x86_64 | OK | OK | OK |  | ||||||||
| tokay2 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||||
| machv2 | macOS 10.14.6 Mojave / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| Package: BufferedMatrix |
| Version: 1.58.0 |
| Command: /home/biocbuild/bbs-3.14-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.14-bioc/R/library --no-vignettes --timings BufferedMatrix_1.58.0.tar.gz |
| StartedAt: 2022-04-12 06:38:58 -0400 (Tue, 12 Apr 2022) |
| EndedAt: 2022-04-12 06:39:19 -0400 (Tue, 12 Apr 2022) |
| EllapsedTime: 20.6 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.14-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.14-bioc/R/library --no-vignettes --timings BufferedMatrix_1.58.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck’ * using R version 4.1.3 (2022-03-10) * using platform: x86_64-pc-linux-gnu (64-bit) * using session charset: UTF-8 * using option ‘--no-vignettes’ * checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK * this is package ‘BufferedMatrix’ version ‘1.58.0’ * 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-3.14-bioc/meat/BufferedMatrix.Rcheck/00check.log’ for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.14-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.14-bioc/R/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
gcc -I"/home/biocbuild/bbs-3.14-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.14-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]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
gcc -I"/home/biocbuild/bbs-3.14-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-3.14-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-3.14-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-3.14-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.14-bioc/R/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 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
0.223 0.062 0.269
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 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-3.14-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 440871 23.6 932408 49.8 654445 35.0
Vcells 792814 6.1 8388608 64.0 2012904 15.4
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Tue Apr 12 06:39:14 2022"
> 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] "Tue Apr 12 06:39:14 2022"
>
>
> 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: 0x56186da51940>
>
>
>
> 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] "Tue Apr 12 06:39:14 2022"
> 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] "Tue Apr 12 06:39:14 2022"
>
> ColMode(tmp2)
<pointer: 0x56186da51940>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.7925066 0.01464674 -0.8366490 -1.8115178
[2,] -1.8984443 -0.63282235 0.1811331 -0.2297524
[3,] 1.1449970 0.68138361 0.7514797 -0.5407701
[4,] 0.8010893 2.32739599 0.3610668 1.4328151
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.7925066 0.01464674 0.8366490 1.8115178
[2,] 1.8984443 0.63282235 0.1811331 0.2297524
[3,] 1.1449970 0.68138361 0.7514797 0.5407701
[4,] 0.8010893 2.32739599 0.3610668 1.4328151
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9896199 0.1210237 0.9146852 1.3459264
[2,] 1.3778405 0.7955013 0.4255973 0.4793249
[3,] 1.0700453 0.8254596 0.8668793 0.7353708
[4,] 0.8950359 1.5255805 0.6008883 1.1970026
>
> 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-3.14-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.68871 26.22488 34.98350 40.27078
[2,] 40.67685 33.58784 29.43711 30.02300
[3,] 36.84545 33.93598 34.42027 32.89448
[4,] 34.75145 42.58320 31.36995 38.40284
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x56186d50b970>
> exp(tmp5)
<pointer: 0x56186d50b970>
> log(tmp5,2)
<pointer: 0x56186d50b970>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.6601
> Min(tmp5)
[1] 53.17427
> mean(tmp5)
[1] 73.61195
> Sum(tmp5)
[1] 14722.39
> Var(tmp5)
[1] 861.3596
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.31742 73.01246 72.94338 71.07784 70.65490 73.94721 73.02193 73.95050
[9] 69.21467 68.97921
> rowSums(tmp5)
[1] 1786.348 1460.249 1458.868 1421.557 1413.098 1478.944 1460.439 1479.010
[9] 1384.293 1379.584
> rowVars(tmp5)
[1] 8010.70601 82.88882 37.90748 101.96641 75.59479 61.39062
[7] 107.96313 95.90539 69.61577 57.66168
> rowSd(tmp5)
[1] 89.502548 9.104330 6.156905 10.097842 8.694527 7.835217 10.390531
[8] 9.793130 8.343606 7.593529
> rowMax(tmp5)
[1] 467.66010 90.51353 85.40947 91.09974 89.37573 87.95640 97.79751
[8] 93.19980 83.77880 82.65512
> rowMin(tmp5)
[1] 54.58366 53.17427 60.75433 57.49369 56.50024 59.04345 55.16364 56.58111
[9] 56.78273 55.44797
>
> colMeans(tmp5)
[1] 111.90730 70.87421 68.68145 71.30961 69.77675 70.34820 68.95801
[8] 71.35427 73.00367 73.19812 77.41121 70.51732 76.36208 71.72342
[15] 72.56854 71.99762 72.49759 67.84271 75.56797 66.33900
> colSums(tmp5)
[1] 1119.0730 708.7421 686.8145 713.0961 697.7675 703.4820 689.5801
[8] 713.5427 730.0367 731.9812 774.1121 705.1732 763.6208 717.2342
[15] 725.6854 719.9762 724.9759 678.4271 755.6797 663.3900
> colVars(tmp5)
[1] 15693.70581 109.84386 87.96491 69.40833 66.32972 19.46377
[7] 63.75094 109.06990 81.96344 85.48504 46.71980 137.71706
[13] 44.99173 37.91607 187.01860 56.29704 54.07562 66.83516
[19] 74.17331 79.12980
> colSd(tmp5)
[1] 125.274522 10.480642 9.378961 8.331166 8.144306 4.411776
[7] 7.984419 10.443654 9.053366 9.245812 6.835189 11.735291
[13] 6.707588 6.157603 13.675475 7.503136 7.353613 8.175277
[19] 8.612393 8.895493
> colMax(tmp5)
[1] 467.66010 88.63135 90.03710 83.81836 82.73034 81.13677 85.16284
[8] 85.45092 93.19980 87.95640 90.51353 90.12962 87.91480 79.02668
[15] 97.79751 80.47237 84.91942 78.49095 84.41298 83.12228
> colMin(tmp5)
[1] 55.44797 54.58366 56.50024 61.24453 60.46334 64.34412 61.08208 57.54175
[9] 62.01078 57.49369 65.04593 56.78273 66.83548 59.81995 56.58111 55.16364
[17] 59.17101 53.17427 59.36139 56.43856
>
>
> ### 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] 89.31742 73.01246 72.94338 71.07784 70.65490 73.94721 73.02193 73.95050
[9] 69.21467 NA
> rowSums(tmp5)
[1] 1786.348 1460.249 1458.868 1421.557 1413.098 1478.944 1460.439 1479.010
[9] 1384.293 NA
> rowVars(tmp5)
[1] 8010.70601 82.88882 37.90748 101.96641 75.59479 61.39062
[7] 107.96313 95.90539 69.61577 60.47413
> rowSd(tmp5)
[1] 89.502548 9.104330 6.156905 10.097842 8.694527 7.835217 10.390531
[8] 9.793130 8.343606 7.776511
> rowMax(tmp5)
[1] 467.66010 90.51353 85.40947 91.09974 89.37573 87.95640 97.79751
[8] 93.19980 83.77880 NA
> rowMin(tmp5)
[1] 54.58366 53.17427 60.75433 57.49369 56.50024 59.04345 55.16364 56.58111
[9] 56.78273 NA
>
> colMeans(tmp5)
[1] 111.90730 70.87421 68.68145 71.30961 69.77675 70.34820 68.95801
[8] 71.35427 73.00367 73.19812 77.41121 70.51732 76.36208 71.72342
[15] 72.56854 71.99762 NA 67.84271 75.56797 66.33900
> colSums(tmp5)
[1] 1119.0730 708.7421 686.8145 713.0961 697.7675 703.4820 689.5801
[8] 713.5427 730.0367 731.9812 774.1121 705.1732 763.6208 717.2342
[15] 725.6854 719.9762 NA 678.4271 755.6797 663.3900
> colVars(tmp5)
[1] 15693.70581 109.84386 87.96491 69.40833 66.32972 19.46377
[7] 63.75094 109.06990 81.96344 85.48504 46.71980 137.71706
[13] 44.99173 37.91607 187.01860 56.29704 NA 66.83516
[19] 74.17331 79.12980
> colSd(tmp5)
[1] 125.274522 10.480642 9.378961 8.331166 8.144306 4.411776
[7] 7.984419 10.443654 9.053366 9.245812 6.835189 11.735291
[13] 6.707588 6.157603 13.675475 7.503136 NA 8.175277
[19] 8.612393 8.895493
> colMax(tmp5)
[1] 467.66010 88.63135 90.03710 83.81836 82.73034 81.13677 85.16284
[8] 85.45092 93.19980 87.95640 90.51353 90.12962 87.91480 79.02668
[15] 97.79751 80.47237 NA 78.49095 84.41298 83.12228
> colMin(tmp5)
[1] 55.44797 54.58366 56.50024 61.24453 60.46334 64.34412 61.08208 57.54175
[9] 62.01078 57.49369 65.04593 56.78273 66.83548 59.81995 56.58111 55.16364
[17] NA 53.17427 59.36139 56.43856
>
> Max(tmp5,na.rm=TRUE)
[1] 467.6601
> Min(tmp5,na.rm=TRUE)
[1] 53.17427
> mean(tmp5,na.rm=TRUE)
[1] 73.62224
> Sum(tmp5,na.rm=TRUE)
[1] 14650.83
> Var(tmp5,na.rm=TRUE)
[1] 865.6886
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.31742 73.01246 72.94338 71.07784 70.65490 73.94721 73.02193 73.95050
[9] 69.21467 68.84313
> rowSums(tmp5,na.rm=TRUE)
[1] 1786.348 1460.249 1458.868 1421.557 1413.098 1478.944 1460.439 1479.010
[9] 1384.293 1308.019
> rowVars(tmp5,na.rm=TRUE)
[1] 8010.70601 82.88882 37.90748 101.96641 75.59479 61.39062
[7] 107.96313 95.90539 69.61577 60.47413
> rowSd(tmp5,na.rm=TRUE)
[1] 89.502548 9.104330 6.156905 10.097842 8.694527 7.835217 10.390531
[8] 9.793130 8.343606 7.776511
> rowMax(tmp5,na.rm=TRUE)
[1] 467.66010 90.51353 85.40947 91.09974 89.37573 87.95640 97.79751
[8] 93.19980 83.77880 82.65512
> rowMin(tmp5,na.rm=TRUE)
[1] 54.58366 53.17427 60.75433 57.49369 56.50024 59.04345 55.16364 56.58111
[9] 56.78273 55.44797
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.90730 70.87421 68.68145 71.30961 69.77675 70.34820 68.95801
[8] 71.35427 73.00367 73.19812 77.41121 70.51732 76.36208 71.72342
[15] 72.56854 71.99762 72.60122 67.84271 75.56797 66.33900
> colSums(tmp5,na.rm=TRUE)
[1] 1119.0730 708.7421 686.8145 713.0961 697.7675 703.4820 689.5801
[8] 713.5427 730.0367 731.9812 774.1121 705.1732 763.6208 717.2342
[15] 725.6854 719.9762 653.4110 678.4271 755.6797 663.3900
> colVars(tmp5,na.rm=TRUE)
[1] 15693.70581 109.84386 87.96491 69.40833 66.32972 19.46377
[7] 63.75094 109.06990 81.96344 85.48504 46.71980 137.71706
[13] 44.99173 37.91607 187.01860 56.29704 60.71426 66.83516
[19] 74.17331 79.12980
> colSd(tmp5,na.rm=TRUE)
[1] 125.274522 10.480642 9.378961 8.331166 8.144306 4.411776
[7] 7.984419 10.443654 9.053366 9.245812 6.835189 11.735291
[13] 6.707588 6.157603 13.675475 7.503136 7.791935 8.175277
[19] 8.612393 8.895493
> colMax(tmp5,na.rm=TRUE)
[1] 467.66010 88.63135 90.03710 83.81836 82.73034 81.13677 85.16284
[8] 85.45092 93.19980 87.95640 90.51353 90.12962 87.91480 79.02668
[15] 97.79751 80.47237 84.91942 78.49095 84.41298 83.12228
> colMin(tmp5,na.rm=TRUE)
[1] 55.44797 54.58366 56.50024 61.24453 60.46334 64.34412 61.08208 57.54175
[9] 62.01078 57.49369 65.04593 56.78273 66.83548 59.81995 56.58111 55.16364
[17] 59.17101 53.17427 59.36139 56.43856
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.31742 73.01246 72.94338 71.07784 70.65490 73.94721 73.02193 73.95050
[9] 69.21467 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1786.348 1460.249 1458.868 1421.557 1413.098 1478.944 1460.439 1479.010
[9] 1384.293 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 8010.70601 82.88882 37.90748 101.96641 75.59479 61.39062
[7] 107.96313 95.90539 69.61577 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 89.502548 9.104330 6.156905 10.097842 8.694527 7.835217 10.390531
[8] 9.793130 8.343606 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 467.66010 90.51353 85.40947 91.09974 89.37573 87.95640 97.79751
[8] 93.19980 83.77880 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 54.58366 53.17427 60.75433 57.49369 56.50024 59.04345 55.16364 56.58111
[9] 56.78273 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 118.18056 71.42117 69.11368 71.01393 70.34353 71.01532 69.44052
[8] 72.68711 73.58245 73.02938 77.10945 70.51221 76.88586 72.36458
[15] 71.90143 71.29089 NaN 67.82116 74.78050 67.43905
> colSums(tmp5,na.rm=TRUE)
[1] 1063.6250 642.7905 622.0231 639.1254 633.0918 639.1378 624.9647
[8] 654.1840 662.2421 657.2644 693.9851 634.6099 691.9727 651.2812
[15] 647.1129 641.6180 0.0000 610.3904 673.0245 606.9515
> colVars(tmp5,na.rm=TRUE)
[1] 17212.68911 120.20876 96.85880 77.10086 71.00697 16.88994
[7] 69.10057 102.71830 88.44022 95.85031 51.53538 154.93140
[13] 47.52927 38.03081 205.38931 57.71519 NA 75.18432
[19] 76.46889 75.40730
> colSd(tmp5,na.rm=TRUE)
[1] 131.197138 10.963975 9.841687 8.780709 8.426563 4.109738
[7] 8.312676 10.135004 9.404266 9.790317 7.178815 12.447144
[13] 6.894148 6.166912 14.331410 7.597051 NA 8.670889
[19] 8.744649 8.683737
> colMax(tmp5,na.rm=TRUE)
[1] 467.66010 88.63135 90.03710 83.81836 82.73034 81.13677 85.16284
[8] 85.45092 93.19980 87.95640 90.51353 90.12962 87.91480 79.02668
[15] 97.79751 80.47237 -Inf 78.49095 84.41298 83.12228
> colMin(tmp5,na.rm=TRUE)
[1] 65.42331 54.58366 56.50024 61.24453 60.46334 66.41908 61.08208 57.54175
[9] 62.01078 57.49369 65.04593 56.78273 66.83548 59.81995 56.58111 55.16364
[17] Inf 53.17427 59.36139 56.57244
>
>
>
>
> 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] 302.87030 156.30603 407.90578 216.30019 282.00399 98.43126 178.14715
[8] 147.38149 370.29138 153.78323
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 302.87030 156.30603 407.90578 216.30019 282.00399 98.43126 178.14715
[8] 147.38149 370.29138 153.78323
>
>
>
> 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] 1.705303e-13 -2.842171e-14 -2.273737e-13 4.547474e-13 2.842171e-14
[6] -1.705303e-13 5.684342e-14 2.842171e-13 1.421085e-14 -5.684342e-14
[11] 2.842171e-13 3.410605e-13 8.526513e-14 8.526513e-14 -5.684342e-14
[16] -1.989520e-13 2.842171e-14 0.000000e+00 1.705303e-13 2.842171e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
10 9
5 17
2 9
6 19
2 9
5 11
9 11
7 14
1 12
4 19
6 11
2 11
10 16
6 1
3 14
7 6
1 3
4 15
5 11
5 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] 1.830853
> Min(tmp)
[1] -2.37352
> mean(tmp)
[1] -0.1918741
> Sum(tmp)
[1] -19.18741
> Var(tmp)
[1] 0.9463
>
> rowMeans(tmp)
[1] -0.1918741
> rowSums(tmp)
[1] -19.18741
> rowVars(tmp)
[1] 0.9463
> rowSd(tmp)
[1] 0.9727795
> rowMax(tmp)
[1] 1.830853
> rowMin(tmp)
[1] -2.37352
>
> colMeans(tmp)
[1] 0.92731911 0.25727466 0.26155439 -0.61402260 0.36278386 -1.59414682
[7] 1.35628872 -2.12505135 1.40732760 -0.13910566 -1.28958250 0.72930095
[13] -0.37045065 -0.57775157 0.08157620 1.83085340 -0.53288458 1.71624300
[19] -0.80486638 -0.07902942 -0.89746807 -0.69041152 -1.96421694 -0.10925520
[25] -0.37562198 -1.09774481 0.18816690 0.06228843 0.27800293 0.02643284
[31] 1.55850839 0.82245669 -0.55842705 -1.82084853 -0.45540349 -1.11245988
[37] 0.98759300 -0.32565099 0.51163088 0.04437113 0.02436616 0.30279483
[43] 0.35971908 -0.60729881 -0.79209095 -0.92186491 0.34730186 -1.21372347
[49] -0.21354890 -0.62760943 -0.50113377 -0.15591675 0.77672238 -1.20801392
[55] 1.66302939 -2.37351952 -0.21427676 0.26272187 -2.14889185 -0.34079541
[61] -0.40358425 1.29765077 0.74901542 -1.14600649 1.01257540 0.17999698
[67] -0.34150445 -1.66184095 1.68107780 -0.16069886 1.13084198 0.84458741
[73] -2.09836310 1.11617306 1.07903855 -0.76193698 -0.39988610 -0.67097934
[79] -0.61377948 -0.10802730 0.04281491 0.00957979 -0.56625867 -1.71416253
[85] -0.47472756 -0.17372493 0.94959658 -0.03820938 -0.47477453 0.83237758
[91] -2.26025487 -1.13268878 -0.45611968 -1.82966978 0.49421791 -1.23157752
[97] 0.32761663 0.12234928 -1.01231181 0.38062206
> colSums(tmp)
[1] 0.92731911 0.25727466 0.26155439 -0.61402260 0.36278386 -1.59414682
[7] 1.35628872 -2.12505135 1.40732760 -0.13910566 -1.28958250 0.72930095
[13] -0.37045065 -0.57775157 0.08157620 1.83085340 -0.53288458 1.71624300
[19] -0.80486638 -0.07902942 -0.89746807 -0.69041152 -1.96421694 -0.10925520
[25] -0.37562198 -1.09774481 0.18816690 0.06228843 0.27800293 0.02643284
[31] 1.55850839 0.82245669 -0.55842705 -1.82084853 -0.45540349 -1.11245988
[37] 0.98759300 -0.32565099 0.51163088 0.04437113 0.02436616 0.30279483
[43] 0.35971908 -0.60729881 -0.79209095 -0.92186491 0.34730186 -1.21372347
[49] -0.21354890 -0.62760943 -0.50113377 -0.15591675 0.77672238 -1.20801392
[55] 1.66302939 -2.37351952 -0.21427676 0.26272187 -2.14889185 -0.34079541
[61] -0.40358425 1.29765077 0.74901542 -1.14600649 1.01257540 0.17999698
[67] -0.34150445 -1.66184095 1.68107780 -0.16069886 1.13084198 0.84458741
[73] -2.09836310 1.11617306 1.07903855 -0.76193698 -0.39988610 -0.67097934
[79] -0.61377948 -0.10802730 0.04281491 0.00957979 -0.56625867 -1.71416253
[85] -0.47472756 -0.17372493 0.94959658 -0.03820938 -0.47477453 0.83237758
[91] -2.26025487 -1.13268878 -0.45611968 -1.82966978 0.49421791 -1.23157752
[97] 0.32761663 0.12234928 -1.01231181 0.38062206
> 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] 0.92731911 0.25727466 0.26155439 -0.61402260 0.36278386 -1.59414682
[7] 1.35628872 -2.12505135 1.40732760 -0.13910566 -1.28958250 0.72930095
[13] -0.37045065 -0.57775157 0.08157620 1.83085340 -0.53288458 1.71624300
[19] -0.80486638 -0.07902942 -0.89746807 -0.69041152 -1.96421694 -0.10925520
[25] -0.37562198 -1.09774481 0.18816690 0.06228843 0.27800293 0.02643284
[31] 1.55850839 0.82245669 -0.55842705 -1.82084853 -0.45540349 -1.11245988
[37] 0.98759300 -0.32565099 0.51163088 0.04437113 0.02436616 0.30279483
[43] 0.35971908 -0.60729881 -0.79209095 -0.92186491 0.34730186 -1.21372347
[49] -0.21354890 -0.62760943 -0.50113377 -0.15591675 0.77672238 -1.20801392
[55] 1.66302939 -2.37351952 -0.21427676 0.26272187 -2.14889185 -0.34079541
[61] -0.40358425 1.29765077 0.74901542 -1.14600649 1.01257540 0.17999698
[67] -0.34150445 -1.66184095 1.68107780 -0.16069886 1.13084198 0.84458741
[73] -2.09836310 1.11617306 1.07903855 -0.76193698 -0.39988610 -0.67097934
[79] -0.61377948 -0.10802730 0.04281491 0.00957979 -0.56625867 -1.71416253
[85] -0.47472756 -0.17372493 0.94959658 -0.03820938 -0.47477453 0.83237758
[91] -2.26025487 -1.13268878 -0.45611968 -1.82966978 0.49421791 -1.23157752
[97] 0.32761663 0.12234928 -1.01231181 0.38062206
> colMin(tmp)
[1] 0.92731911 0.25727466 0.26155439 -0.61402260 0.36278386 -1.59414682
[7] 1.35628872 -2.12505135 1.40732760 -0.13910566 -1.28958250 0.72930095
[13] -0.37045065 -0.57775157 0.08157620 1.83085340 -0.53288458 1.71624300
[19] -0.80486638 -0.07902942 -0.89746807 -0.69041152 -1.96421694 -0.10925520
[25] -0.37562198 -1.09774481 0.18816690 0.06228843 0.27800293 0.02643284
[31] 1.55850839 0.82245669 -0.55842705 -1.82084853 -0.45540349 -1.11245988
[37] 0.98759300 -0.32565099 0.51163088 0.04437113 0.02436616 0.30279483
[43] 0.35971908 -0.60729881 -0.79209095 -0.92186491 0.34730186 -1.21372347
[49] -0.21354890 -0.62760943 -0.50113377 -0.15591675 0.77672238 -1.20801392
[55] 1.66302939 -2.37351952 -0.21427676 0.26272187 -2.14889185 -0.34079541
[61] -0.40358425 1.29765077 0.74901542 -1.14600649 1.01257540 0.17999698
[67] -0.34150445 -1.66184095 1.68107780 -0.16069886 1.13084198 0.84458741
[73] -2.09836310 1.11617306 1.07903855 -0.76193698 -0.39988610 -0.67097934
[79] -0.61377948 -0.10802730 0.04281491 0.00957979 -0.56625867 -1.71416253
[85] -0.47472756 -0.17372493 0.94959658 -0.03820938 -0.47477453 0.83237758
[91] -2.26025487 -1.13268878 -0.45611968 -1.82966978 0.49421791 -1.23157752
[97] 0.32761663 0.12234928 -1.01231181 0.38062206
> colMedians(tmp)
[1] 0.92731911 0.25727466 0.26155439 -0.61402260 0.36278386 -1.59414682
[7] 1.35628872 -2.12505135 1.40732760 -0.13910566 -1.28958250 0.72930095
[13] -0.37045065 -0.57775157 0.08157620 1.83085340 -0.53288458 1.71624300
[19] -0.80486638 -0.07902942 -0.89746807 -0.69041152 -1.96421694 -0.10925520
[25] -0.37562198 -1.09774481 0.18816690 0.06228843 0.27800293 0.02643284
[31] 1.55850839 0.82245669 -0.55842705 -1.82084853 -0.45540349 -1.11245988
[37] 0.98759300 -0.32565099 0.51163088 0.04437113 0.02436616 0.30279483
[43] 0.35971908 -0.60729881 -0.79209095 -0.92186491 0.34730186 -1.21372347
[49] -0.21354890 -0.62760943 -0.50113377 -0.15591675 0.77672238 -1.20801392
[55] 1.66302939 -2.37351952 -0.21427676 0.26272187 -2.14889185 -0.34079541
[61] -0.40358425 1.29765077 0.74901542 -1.14600649 1.01257540 0.17999698
[67] -0.34150445 -1.66184095 1.68107780 -0.16069886 1.13084198 0.84458741
[73] -2.09836310 1.11617306 1.07903855 -0.76193698 -0.39988610 -0.67097934
[79] -0.61377948 -0.10802730 0.04281491 0.00957979 -0.56625867 -1.71416253
[85] -0.47472756 -0.17372493 0.94959658 -0.03820938 -0.47477453 0.83237758
[91] -2.26025487 -1.13268878 -0.45611968 -1.82966978 0.49421791 -1.23157752
[97] 0.32761663 0.12234928 -1.01231181 0.38062206
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.9273191 0.2572747 0.2615544 -0.6140226 0.3627839 -1.594147 1.356289
[2,] 0.9273191 0.2572747 0.2615544 -0.6140226 0.3627839 -1.594147 1.356289
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -2.125051 1.407328 -0.1391057 -1.289582 0.7293009 -0.3704506 -0.5777516
[2,] -2.125051 1.407328 -0.1391057 -1.289582 0.7293009 -0.3704506 -0.5777516
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.0815762 1.830853 -0.5328846 1.716243 -0.8048664 -0.07902942 -0.8974681
[2,] 0.0815762 1.830853 -0.5328846 1.716243 -0.8048664 -0.07902942 -0.8974681
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.6904115 -1.964217 -0.1092552 -0.375622 -1.097745 0.1881669 0.06228843
[2,] -0.6904115 -1.964217 -0.1092552 -0.375622 -1.097745 0.1881669 0.06228843
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.2780029 0.02643284 1.558508 0.8224567 -0.5584271 -1.820849 -0.4554035
[2,] 0.2780029 0.02643284 1.558508 0.8224567 -0.5584271 -1.820849 -0.4554035
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.11246 0.987593 -0.325651 0.5116309 0.04437113 0.02436616 0.3027948
[2,] -1.11246 0.987593 -0.325651 0.5116309 0.04437113 0.02436616 0.3027948
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.3597191 -0.6072988 -0.7920909 -0.9218649 0.3473019 -1.213723 -0.2135489
[2,] 0.3597191 -0.6072988 -0.7920909 -0.9218649 0.3473019 -1.213723 -0.2135489
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.6276094 -0.5011338 -0.1559167 0.7767224 -1.208014 1.663029 -2.37352
[2,] -0.6276094 -0.5011338 -0.1559167 0.7767224 -1.208014 1.663029 -2.37352
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.2142768 0.2627219 -2.148892 -0.3407954 -0.4035843 1.297651 0.7490154
[2,] -0.2142768 0.2627219 -2.148892 -0.3407954 -0.4035843 1.297651 0.7490154
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.146006 1.012575 0.179997 -0.3415044 -1.661841 1.681078 -0.1606989
[2,] -1.146006 1.012575 0.179997 -0.3415044 -1.661841 1.681078 -0.1606989
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.130842 0.8445874 -2.098363 1.116173 1.079039 -0.761937 -0.3998861
[2,] 1.130842 0.8445874 -2.098363 1.116173 1.079039 -0.761937 -0.3998861
[,78] [,79] [,80] [,81] [,82] [,83]
[1,] -0.6709793 -0.6137795 -0.1080273 0.04281491 0.00957979 -0.5662587
[2,] -0.6709793 -0.6137795 -0.1080273 0.04281491 0.00957979 -0.5662587
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -1.714163 -0.4747276 -0.1737249 0.9495966 -0.03820938 -0.4747745 0.8323776
[2,] -1.714163 -0.4747276 -0.1737249 0.9495966 -0.03820938 -0.4747745 0.8323776
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -2.260255 -1.132689 -0.4561197 -1.82967 0.4942179 -1.231578 0.3276166
[2,] -2.260255 -1.132689 -0.4561197 -1.82967 0.4942179 -1.231578 0.3276166
[,98] [,99] [,100]
[1,] 0.1223493 -1.012312 0.3806221
[2,] 0.1223493 -1.012312 0.3806221
>
>
> Max(tmp2)
[1] 2.728169
> Min(tmp2)
[1] -2.061296
> mean(tmp2)
[1] 0.08608301
> Sum(tmp2)
[1] 8.608301
> Var(tmp2)
[1] 0.9477542
>
> rowMeans(tmp2)
[1] -0.935653908 -0.623402353 1.756467523 -1.566714670 -2.061296202
[6] 0.837431144 0.058522370 -0.620927939 1.809933138 1.679914056
[11] -0.612446380 1.439734558 -0.661276194 -1.164817669 -0.519263892
[16] -0.840852216 0.319397686 2.274417199 0.375639520 0.552093667
[21] -0.157530432 -0.513708440 1.554105613 1.906308397 1.640986609
[26] 1.227944207 -0.538153967 0.461087544 -0.227886546 0.864629399
[31] -0.573395498 -1.013003568 0.132851046 -0.196534630 -1.092080513
[36] -1.642154728 0.462951160 0.346996175 -0.857192966 -0.192452332
[41] 0.445316325 0.338246946 -1.695718821 0.340287932 -1.236934680
[46] 0.008178949 -0.719759482 -0.075050091 -0.474327997 0.205658170
[51] -1.334565419 -0.580775696 0.354569181 0.271700684 -0.759383011
[56] 1.651455350 1.785285474 1.827779849 0.019564780 0.356509952
[61] 0.302388445 0.556104148 0.013931347 -0.024830717 0.507426569
[66] 0.173511212 -0.503020174 -0.443266522 1.297711825 0.682551957
[71] -0.015224592 0.555333541 0.444369735 0.472753253 0.207938122
[76] -0.352194328 -1.501055164 -0.072505178 0.032640367 1.031767470
[81] -1.491085093 -0.365439097 -1.193712402 0.247484398 -0.113455603
[86] -0.317159608 0.182454962 -0.664939067 -0.697320062 -1.238633444
[91] -1.023304390 -0.080156922 1.151230745 0.179843197 1.767344744
[96] 0.147305883 2.728168570 0.571113963 0.261513498 1.372010694
> rowSums(tmp2)
[1] -0.935653908 -0.623402353 1.756467523 -1.566714670 -2.061296202
[6] 0.837431144 0.058522370 -0.620927939 1.809933138 1.679914056
[11] -0.612446380 1.439734558 -0.661276194 -1.164817669 -0.519263892
[16] -0.840852216 0.319397686 2.274417199 0.375639520 0.552093667
[21] -0.157530432 -0.513708440 1.554105613 1.906308397 1.640986609
[26] 1.227944207 -0.538153967 0.461087544 -0.227886546 0.864629399
[31] -0.573395498 -1.013003568 0.132851046 -0.196534630 -1.092080513
[36] -1.642154728 0.462951160 0.346996175 -0.857192966 -0.192452332
[41] 0.445316325 0.338246946 -1.695718821 0.340287932 -1.236934680
[46] 0.008178949 -0.719759482 -0.075050091 -0.474327997 0.205658170
[51] -1.334565419 -0.580775696 0.354569181 0.271700684 -0.759383011
[56] 1.651455350 1.785285474 1.827779849 0.019564780 0.356509952
[61] 0.302388445 0.556104148 0.013931347 -0.024830717 0.507426569
[66] 0.173511212 -0.503020174 -0.443266522 1.297711825 0.682551957
[71] -0.015224592 0.555333541 0.444369735 0.472753253 0.207938122
[76] -0.352194328 -1.501055164 -0.072505178 0.032640367 1.031767470
[81] -1.491085093 -0.365439097 -1.193712402 0.247484398 -0.113455603
[86] -0.317159608 0.182454962 -0.664939067 -0.697320062 -1.238633444
[91] -1.023304390 -0.080156922 1.151230745 0.179843197 1.767344744
[96] 0.147305883 2.728168570 0.571113963 0.261513498 1.372010694
> 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] -0.935653908 -0.623402353 1.756467523 -1.566714670 -2.061296202
[6] 0.837431144 0.058522370 -0.620927939 1.809933138 1.679914056
[11] -0.612446380 1.439734558 -0.661276194 -1.164817669 -0.519263892
[16] -0.840852216 0.319397686 2.274417199 0.375639520 0.552093667
[21] -0.157530432 -0.513708440 1.554105613 1.906308397 1.640986609
[26] 1.227944207 -0.538153967 0.461087544 -0.227886546 0.864629399
[31] -0.573395498 -1.013003568 0.132851046 -0.196534630 -1.092080513
[36] -1.642154728 0.462951160 0.346996175 -0.857192966 -0.192452332
[41] 0.445316325 0.338246946 -1.695718821 0.340287932 -1.236934680
[46] 0.008178949 -0.719759482 -0.075050091 -0.474327997 0.205658170
[51] -1.334565419 -0.580775696 0.354569181 0.271700684 -0.759383011
[56] 1.651455350 1.785285474 1.827779849 0.019564780 0.356509952
[61] 0.302388445 0.556104148 0.013931347 -0.024830717 0.507426569
[66] 0.173511212 -0.503020174 -0.443266522 1.297711825 0.682551957
[71] -0.015224592 0.555333541 0.444369735 0.472753253 0.207938122
[76] -0.352194328 -1.501055164 -0.072505178 0.032640367 1.031767470
[81] -1.491085093 -0.365439097 -1.193712402 0.247484398 -0.113455603
[86] -0.317159608 0.182454962 -0.664939067 -0.697320062 -1.238633444
[91] -1.023304390 -0.080156922 1.151230745 0.179843197 1.767344744
[96] 0.147305883 2.728168570 0.571113963 0.261513498 1.372010694
> rowMin(tmp2)
[1] -0.935653908 -0.623402353 1.756467523 -1.566714670 -2.061296202
[6] 0.837431144 0.058522370 -0.620927939 1.809933138 1.679914056
[11] -0.612446380 1.439734558 -0.661276194 -1.164817669 -0.519263892
[16] -0.840852216 0.319397686 2.274417199 0.375639520 0.552093667
[21] -0.157530432 -0.513708440 1.554105613 1.906308397 1.640986609
[26] 1.227944207 -0.538153967 0.461087544 -0.227886546 0.864629399
[31] -0.573395498 -1.013003568 0.132851046 -0.196534630 -1.092080513
[36] -1.642154728 0.462951160 0.346996175 -0.857192966 -0.192452332
[41] 0.445316325 0.338246946 -1.695718821 0.340287932 -1.236934680
[46] 0.008178949 -0.719759482 -0.075050091 -0.474327997 0.205658170
[51] -1.334565419 -0.580775696 0.354569181 0.271700684 -0.759383011
[56] 1.651455350 1.785285474 1.827779849 0.019564780 0.356509952
[61] 0.302388445 0.556104148 0.013931347 -0.024830717 0.507426569
[66] 0.173511212 -0.503020174 -0.443266522 1.297711825 0.682551957
[71] -0.015224592 0.555333541 0.444369735 0.472753253 0.207938122
[76] -0.352194328 -1.501055164 -0.072505178 0.032640367 1.031767470
[81] -1.491085093 -0.365439097 -1.193712402 0.247484398 -0.113455603
[86] -0.317159608 0.182454962 -0.664939067 -0.697320062 -1.238633444
[91] -1.023304390 -0.080156922 1.151230745 0.179843197 1.767344744
[96] 0.147305883 2.728168570 0.571113963 0.261513498 1.372010694
>
> colMeans(tmp2)
[1] 0.08608301
> colSums(tmp2)
[1] 8.608301
> colVars(tmp2)
[1] 0.9477542
> colSd(tmp2)
[1] 0.9735267
> colMax(tmp2)
[1] 2.728169
> colMin(tmp2)
[1] -2.061296
> colMedians(tmp2)
[1] 0.04558137
> colRanges(tmp2)
[,1]
[1,] -2.061296
[2,] 2.728169
>
> 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] 2.1588216 2.5967687 -1.5822154 -0.2174701 -0.7269352 2.3503964
[7] 1.0654509 6.0749803 2.4281744 5.3977215
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.11139601
[2,] -0.21902010
[3,] -0.01583552
[4,] 0.31933349
[5,] 2.02358300
>
> rowApply(tmp,sum)
[1] -1.3995719 7.3894402 2.7371794 0.5985796 2.5885833 -0.4148566
[7] 0.4963060 1.7825520 3.5160025 2.2514789
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 2 4 10 1 3 5 6 3 10
[2,] 1 7 10 6 4 6 1 10 7 7
[3,] 2 10 2 4 9 8 4 1 1 5
[4,] 7 5 6 2 7 5 6 8 2 4
[5,] 9 1 8 3 8 1 2 7 5 3
[6,] 10 4 3 7 6 4 7 4 10 2
[7,] 3 8 5 5 10 7 3 3 9 1
[8,] 8 9 7 9 3 2 10 5 4 9
[9,] 4 6 9 1 2 10 8 2 6 8
[10,] 6 3 1 8 5 9 9 9 8 6
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 3.0447688 -2.2671246 0.4670722 -1.3819494 -2.2281054 1.0338597
[7] -1.4949032 2.7052186 -1.9552454 0.7562982 -3.5885659 1.2203177
[13] -0.8508175 0.4016647 -5.9188002 -0.3014335 -2.3061699 1.0854218
[19] -3.3561883 -0.1040787
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.28678996
[2,] -0.01348074
[3,] 0.53344213
[4,] 1.24562247
[5,] 1.56597491
>
> rowApply(tmp,sum)
[1] 0.1793889 -8.7171777 -4.2252659 4.7496639 -7.0253694
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 11 20 11 18 17
[2,] 10 10 2 16 4
[3,] 6 3 20 12 13
[4,] 8 15 17 5 3
[5,] 9 2 16 11 15
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.01348074 -0.0996027 -0.63224952 -0.4667335 -0.3579494 0.8082992
[2,] 1.24562247 -0.4997326 -1.42970814 0.2845550 -2.7401346 0.6319455
[3,] -0.28678996 -1.6061782 2.20309132 0.6275788 0.3886158 -0.3944305
[4,] 1.56597491 1.0335973 0.38116667 -0.7210908 0.2469728 -0.4467778
[5,] 0.53344213 -1.0952084 -0.05522811 -1.1062589 0.2343900 0.4348232
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.48081944 1.2258590 0.7693612 -0.6984147 -0.009604687 0.1763933
[2,] -1.39704446 0.8320373 -0.5459067 -0.9341683 -0.209994126 -0.5154896
[3,] -0.05414074 1.4170941 -0.6351672 0.9966744 -1.511428917 -0.6999302
[4,] 0.42827525 0.7067725 -0.8507427 1.8727527 -0.903744312 1.2096280
[5,] -0.95281273 -1.4765442 -0.6927900 -0.4805460 -0.953793824 1.0497162
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.7404835 1.64687139 -0.5871283 1.0492842 -0.903194259 0.9130130
[2,] 0.6259118 0.14821149 -2.8828689 -0.3534604 1.180508769 -0.9589068
[3,] -0.6041624 -0.68790741 -0.3189779 -0.1089788 -2.677635474 -0.1105993
[4,] -1.2993349 0.07561147 -1.7356339 0.1810743 0.103604881 0.1044244
[5,] 1.1672515 -0.78112222 -0.3941911 -1.0693528 -0.009453837 1.1374905
[,19] [,20]
[1,] -0.8743530 -1.5073174
[2,] -1.4146337 0.2160785
[3,] 0.1635616 -0.3255552
[4,] 0.7342705 2.0628627
[5,] -1.9650336 -0.5501473
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.14-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-3.14-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.14-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 -1.290934 0.5792628 0.2929432 -0.07013572 -0.4003264 -0.4014679 -2.263183
col8 col9 col10 col11 col12 col13 col14
row1 -0.4174322 -1.985914 -1.241657 -0.1807027 1.191731 3.209051 -0.134652
col15 col16 col17 col18 col19 col20
row1 2.017015 0.3347337 0.49814 0.1950232 0.5028277 0.1826063
> tmp[,"col10"]
col10
row1 -1.2416571
row2 -0.0747854
row3 -0.1250250
row4 -0.6520374
row5 0.1289455
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -1.290934 0.5792628 0.2929432 -0.07013572 -0.4003264 -0.4014679
row5 1.061343 -0.6528671 -1.6732518 0.90091108 0.4366218 0.1594931
col7 col8 col9 col10 col11 col12
row1 -2.2631834 -0.4174322 -1.9859144 -1.2416571 -0.1807027 1.191731493
row5 0.6522827 -2.1991744 -0.4555746 0.1289455 -0.2583105 -0.006318251
col13 col14 col15 col16 col17 col18 col19
row1 3.2090512 -0.1346520 2.0170152 0.3347337 0.4981400 0.1950232 0.50282773
row5 -0.5415474 -0.2278796 0.7142213 1.1887434 -0.3273431 -0.8418010 0.09632694
col20
row1 0.1826063
row5 -0.5177177
> tmp[,c("col6","col20")]
col6 col20
row1 -0.4014679 0.1826063
row2 -0.1301960 -0.8503421
row3 0.6748588 1.7941930
row4 -1.6441572 0.6166063
row5 0.1594931 -0.5177177
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.4014679 0.1826063
row5 0.1594931 -0.5177177
>
>
>
>
> 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 49.67643 50.61446 48.65525 49.34026 50.42622 105.6633 51.05941 49.94891
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.83095 49.92431 49.24382 49.37417 51.19203 50.50921 50.40005 49.86191
col17 col18 col19 col20
row1 49.61792 50.4237 50.14564 104.6407
> tmp[,"col10"]
col10
row1 49.92431
row2 29.65332
row3 30.75297
row4 31.88099
row5 49.28484
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.67643 50.61446 48.65525 49.34026 50.42622 105.6633 51.05941 49.94891
row5 48.71186 49.07662 50.63118 49.78307 50.37874 105.1349 49.58328 49.79605
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.83095 49.92431 49.24382 49.37417 51.19203 50.50921 50.40005 49.86191
row5 51.01960 49.28484 48.13674 48.44053 50.50298 51.44587 49.67349 50.84899
col17 col18 col19 col20
row1 49.61792 50.42370 50.14564 104.6407
row5 50.15790 52.10689 50.12519 103.7369
> tmp[,c("col6","col20")]
col6 col20
row1 105.66326 104.64070
row2 76.77853 75.07330
row3 76.01476 75.49519
row4 74.02431 74.86438
row5 105.13492 103.73694
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.6633 104.6407
row5 105.1349 103.7369
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.6633 104.6407
row5 105.1349 103.7369
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.7878908
[2,] -1.4739006
[3,] -0.6942503
[4,] 1.1526195
[5,] 1.8700805
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.24492625 -0.6773555
[2,] 0.74801384 -0.6185986
[3,] -0.67218755 -2.1048015
[4,] -0.14916776 -0.2058322
[5,] -0.06908463 -0.1404075
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.5133257 1.70930709
[2,] -0.3617282 0.07560518
[3,] -1.2626063 0.84510241
[4,] 0.3983258 0.78296150
[5,] -0.2355764 0.85551821
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.513326
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.5133257
[2,] -0.3617282
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 1.6671282 0.3810971 -1.0834722 0.4357372 0.9214044 -0.6338083 -0.71794440
row1 0.3435776 0.5845422 0.2070315 0.2656564 2.0122495 -1.3762693 -0.02293103
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.3181976 1.3642359 -1.545955 0.96569710 -0.6553647 -1.364675 -0.3691530
row1 -0.9929423 0.9834535 1.158435 0.01224577 1.7069143 2.379509 -0.4263639
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.4533605 0.3654477 0.42259980 0.3880108 0.2580708 0.3618901
row1 0.3977290 0.4917431 -0.08552609 0.2044654 -0.2143536 -2.4125218
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.092517 2.080477 0.5878029 -0.4870549 1.062081 -0.8401505 -1.54606
[,8] [,9] [,10]
row2 0.6986508 -2.089483 -1.617158
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row5 -0.3776924 0.1917489 -0.009180899 -0.1171532 0.9116158 -1.341974
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row5 -0.2981516 0.1740392 -1.036778 1.245047 0.5910268 -0.6448697 -0.4142833
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.5749953 -0.3739117 -2.207466 1.273024 0.2500928 0.6506191 2.150114
>
>
> 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: 0x56186d6a75f0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM218bde5d2abeac"
[2] "/home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM218bde100fcce5"
[3] "/home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM218bde747edca1"
[4] "/home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM218bde65c72be9"
[5] "/home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM218bde1a11aab4"
[6] "/home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM218bde1081d7e8"
[7] "/home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM218bde16555fb9"
[8] "/home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM218bde6dc57897"
[9] "/home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM218bde6cc8e5fc"
[10] "/home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM218bde5171b32"
[11] "/home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM218bde50e89f73"
[12] "/home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM218bde1e0b0c27"
[13] "/home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM218bde6821aa6"
[14] "/home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM218bde2b1b8573"
[15] "/home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM218bde9ab805c"
>
>
> ### 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: 0x56186eaf99d0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x56186eaf99d0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x56186eaf99d0>
> rowMedians(tmp)
[1] 0.020039336 0.121510791 0.491582029 -0.080502006 -0.127349832
[6] 0.326903530 -0.401169570 -0.414702692 0.046821362 -0.694958868
[11] -0.122391485 -0.199039212 0.518716974 -0.365053693 -0.324091385
[16] 0.203893196 0.413036333 0.382663285 0.211132558 0.249839613
[21] 0.137051905 -0.107550407 0.041947052 0.362173120 -0.196719738
[26] 0.040612308 0.148999451 0.461524855 0.628981377 -0.340320195
[31] -0.599794243 -0.395085041 -0.012710149 0.449956627 -0.133442477
[36] 0.160474982 -0.193594283 -0.066529799 -0.418318977 0.173704728
[41] -0.253360243 -0.171963149 0.001928924 0.161321087 -0.682722564
[46] 0.393982919 -0.584347418 0.119430643 0.372248565 -0.047986274
[51] -0.266539887 0.237200690 0.385795125 0.449959381 -0.044552532
[56] -0.038394836 -0.288166524 0.023388038 0.359851949 -0.003551800
[61] 0.053059723 -0.138542327 -0.351832597 0.290746035 -0.459029909
[66] 0.224186618 -0.558505706 0.407934399 -0.016599309 -0.068601667
[71] 0.020092679 0.139415025 -0.102285112 0.232033166 0.091405294
[76] -0.324648981 -0.057209729 -0.048583166 -0.065794366 0.347401966
[81] -0.281519310 0.128736281 -0.179985283 -0.343906941 0.143851803
[86] 0.262305216 -0.279915237 -0.791916518 -0.225846062 0.365897542
[91] 0.111751960 -0.040525987 0.229323747 -0.014366817 0.424519715
[96] -0.124092250 0.124341166 -0.259845746 0.066141686 -0.173444194
[101] -0.063790639 0.416660003 0.380338712 0.308941544 -0.598923024
[106] -0.381826795 0.114910873 -0.186558489 -0.349112134 -0.045380811
[111] -0.519804706 -0.297265414 -0.112482844 -0.308992686 0.661497276
[116] -0.217293478 -0.076992488 -0.495022225 -0.572050405 -0.604158095
[121] -0.122452609 0.150054221 0.043780206 -0.061258216 0.009175288
[126] -0.291127096 -0.599242070 0.250695733 -0.422603660 0.536622684
[131] -0.071584053 -0.077258956 0.205860811 0.384543115 0.465818821
[136] -0.181016491 0.088454803 -0.080975563 -0.455227238 -0.133382973
[141] -0.430839240 0.485583719 0.216247520 -0.404043270 0.102751945
[146] -0.283832146 -0.257466814 -0.161476442 -0.658386440 0.052234307
[151] -0.009144498 -0.117080883 -0.311143938 -0.006667146 -0.285543171
[156] 0.052117177 0.464927948 0.713788699 -0.442753285 -0.204511144
[161] -0.131146069 0.288087262 -0.342886069 -0.414216870 -0.170945415
[166] -0.025636830 -0.432544044 0.025419215 0.027702359 -0.184307520
[171] 0.057390629 -0.476904340 -0.188035765 0.149920212 0.094846481
[176] 0.252856775 0.042909655 0.830105558 0.460000585 -0.685276185
[181] -0.269770310 0.152242274 0.013199818 0.057198898 -0.195112178
[186] 0.037111469 -0.045289884 -0.082197014 -0.086787704 -0.538536948
[191] -0.447548785 0.104225149 0.132317223 -0.205739081 -0.508468567
[196] 0.319844890 0.494589894 0.472017851 -0.234498475 0.111505390
[201] 0.147124081 0.336796917 0.610131950 0.636073775 -0.252454470
[206] 0.300684027 0.183896535 -0.134284958 0.491332504 -0.414012966
[211] 0.130094845 0.510591722 0.209079919 -0.049742730 -0.366721965
[216] -0.234609669 -0.017812632 0.387031476 -0.107322393 -0.602122986
[221] -0.230573155 -0.068648243 -0.041733468 0.194590478 0.348173913
[226] -0.119088560 -0.766625235 -0.137591808 0.039090254 -0.052038911
>
> proc.time()
user system elapsed
1.239 0.576 1.807
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 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: 0x55c1e9c5b940>
> .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: 0x55c1e9c5b940>
> .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: 0x55c1e9c5b940>
> .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: 0x55c1e9c5b940>
> 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: 0x55c1ea08a190>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55c1ea08a190>
> .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: 0x55c1ea08a190>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55c1ea08a190>
> .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: 0x55c1ea08a190>
> 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: 0x55c1ea628230>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55c1ea628230>
> .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: 0x55c1ea628230>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x55c1ea628230>
> .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: 0x55c1ea628230>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x55c1ea628230>
> .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: 0x55c1ea628230>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x55c1ea628230>
> .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: 0x55c1ea628230>
> 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: 0x55c1ea8a2330>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x55c1ea8a2330>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55c1ea8a2330>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55c1ea8a2330>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile218d8c191611bb" "BufferedMatrixFile218d8c4f5b4739"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile218d8c191611bb" "BufferedMatrixFile218d8c4f5b4739"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x55c1eb75ce80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55c1eb75ce80>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x55c1eb75ce80>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x55c1eb75ce80>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x55c1eb75ce80>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x55c1eb75ce80>
> .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: 0x55c1e995e5d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55c1e995e5d0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x55c1e995e5d0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x55c1e995e5d0>
> 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: 0x55c1e9957120>
> .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: 0x55c1e9957120>
> rm(P)
>
> proc.time()
user system elapsed
0.285 0.051 0.320
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 The R Foundation for Statistical Computing
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> 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
0.254 0.037 0.274