| Back to Multiple platform build/check report for BioC 3.15 |
|
This page was generated on 2022-10-19 13:22:39 -0400 (Wed, 19 Oct 2022).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 20.04.5 LTS) | x86_64 | 4.2.1 (2022-06-23) -- "Funny-Looking Kid" | 4386 |
| palomino3 | Windows Server 2022 Datacenter | x64 | 4.2.1 (2022-06-23 ucrt) -- "Funny-Looking Kid" | 4138 |
| merida1 | macOS 10.14.6 Mojave | x86_64 | 4.2.1 (2022-06-23) -- "Funny-Looking Kid" | 4205 |
| 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 229/2140 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.60.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 20.04.5 LTS) / x86_64 | OK | OK | OK |  | ||||||||
| palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 10.14.6 Mojave / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| Package: BufferedMatrix |
| Version: 1.60.0 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.60.0.tar.gz |
| StartedAt: 2022-10-19 00:03:15 -0400 (Wed, 19 Oct 2022) |
| EndedAt: 2022-10-19 00:04:11 -0400 (Wed, 19 Oct 2022) |
| EllapsedTime: 55.9 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.60.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck’ * using R version 4.2.1 (2022-06-23) * using platform: x86_64-apple-darwin17.0 (64-bit) * using session charset: UTF-8 * using option ‘--no-vignettes’ * checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK * this is package ‘BufferedMatrix’ version ‘1.60.0’ * 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 ... WARNING Found the following significant warnings: doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses] See ‘/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details. * 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 sizes of PDF files under ‘inst/doc’ ... OK * 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: 1 WARNING, 2 NOTEs See ‘/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/00check.log’ for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.2/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
clang -mmacosx-version-min=10.13 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/usr/local/include -fPIC -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -mmacosx-version-min=10.13 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/usr/local/include -fPIC -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -mmacosx-version-min=10.13 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/usr/local/include -fPIC -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -mmacosx-version-min=10.13 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/usr/local/include -fPIC -Wall -g -O2 -c init_package.c -o init_package.o
clang -mmacosx-version-min=10.13 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -single_module -multiply_defined suppress -L/Library/Frameworks/R.framework/Resources/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation
installing to /Library/Frameworks/R.framework/Versions/4.2/Resources/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 4.2.1 (2022-06-23) -- "Funny-Looking Kid"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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
0.555 0.132 0.664
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.2.1 (2022-06-23) -- "Funny-Looking Kid"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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] "/Users/biocbuild/bbs-3.15-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) limit (Mb) max used (Mb)
Ncells 448552 24.0 969261 51.8 NA 624631 33.4
Vcells 811752 6.2 8388608 64.0 65536 1889589 14.5
>
>
>
>
> ##
> ## 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 Oct 19 00:03:45 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] "Wed Oct 19 00:03:45 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: 0x7f9106c087f0>
>
>
>
> 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 Oct 19 00:03:49 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] "Wed Oct 19 00:03:50 2022"
>
> ColMode(tmp2)
<pointer: 0x7f9106c087f0>
>
>
>
> ### 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,] 99.3746377 0.2247440 -0.7066117 -0.8232293
[2,] -1.7419447 0.4426740 0.3271461 0.1820249
[3,] 0.9612718 0.5107692 -0.1093216 -0.8156746
[4,] -0.3999078 0.6381163 0.9646326 -0.7324200
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.3746377 0.2247440 0.7066117 0.8232293
[2,] 1.7419447 0.4426740 0.3271461 0.1820249
[3,] 0.9612718 0.5107692 0.1093216 0.8156746
[4,] 0.3999078 0.6381163 0.9646326 0.7324200
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9686828 0.4740717 0.8406020 0.9073198
[2,] 1.3198275 0.6653375 0.5719669 0.4266438
[3,] 0.9804447 0.7146812 0.3306382 0.9031471
[4,] 0.6323827 0.7988218 0.9821571 0.8558154
>
> 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: /Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.06147 29.96546 34.11263 34.89643
[2,] 39.94022 32.09605 31.04682 29.44846
[3,] 35.76572 32.65758 28.41570 34.84715
[4,] 31.72373 33.62633 35.78620 34.29057
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x7f90c6d00600>
> exp(tmp5)
<pointer: 0x7f90c6d00600>
> log(tmp5,2)
<pointer: 0x7f90c6d00600>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.3546
> Min(tmp5)
[1] 53.8876
> mean(tmp5)
[1] 71.70937
> Sum(tmp5)
[1] 14341.87
> Var(tmp5)
[1] 849.5834
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 88.92097 69.29699 68.16872 70.15417 71.98987 72.77109 69.47680 69.63825
[9] 68.14528 68.53159
> rowSums(tmp5)
[1] 1778.419 1385.940 1363.374 1403.083 1439.797 1455.422 1389.536 1392.765
[9] 1362.906 1370.632
> rowVars(tmp5)
[1] 7930.44282 114.15440 48.42900 47.86896 54.65635 82.21537
[7] 60.56028 61.11889 77.10850 52.98294
> rowSd(tmp5)
[1] 89.053034 10.684306 6.959095 6.918740 7.392993 9.067269 7.782048
[8] 7.817857 8.781145 7.278938
> rowMax(tmp5)
[1] 466.35459 95.91512 82.10674 83.97533 88.68770 89.94876 83.23848
[8] 81.54990 84.46629 83.01726
> rowMin(tmp5)
[1] 58.52994 53.88760 55.71009 57.72583 60.73041 57.25591 57.57194 55.60824
[9] 54.35094 57.18217
>
> colMeans(tmp5)
[1] 113.64430 66.80394 69.16791 68.07237 68.14734 65.88456 70.87714
[8] 72.10183 67.16553 75.22085 75.50403 68.95980 67.42101 65.61939
[15] 71.67263 70.72797 69.75059 65.58424 70.22393 71.63809
> colSums(tmp5)
[1] 1136.4430 668.0394 691.6791 680.7237 681.4734 658.8456 708.7714
[8] 721.0183 671.6553 752.2085 755.0403 689.5980 674.2101 656.1939
[15] 716.7263 707.2797 697.5059 655.8424 702.2393 716.3809
> colVars(tmp5)
[1] 15395.779241 44.084333 59.473689 41.532595 96.164787
[6] 9.219842 101.641370 57.285126 115.057976 49.031798
[11] 95.004206 46.279146 18.922793 39.157496 49.945289
[16] 113.085480 92.671261 23.992345 54.354087 55.110604
> colSd(tmp5)
[1] 124.079729 6.639603 7.711919 6.444579 9.806365 3.036419
[7] 10.081734 7.568694 10.726508 7.002271 9.747010 6.802878
[13] 4.350034 6.257595 7.067198 10.634166 9.626591 4.898198
[19] 7.372522 7.423652
> colMax(tmp5)
[1] 466.35459 78.78538 84.21658 80.91982 85.12953 69.40199 89.94876
[8] 83.17347 83.97533 82.84464 95.91512 81.63705 75.35361 74.98158
[15] 85.84414 88.68770 83.17629 71.77038 85.16882 82.51441
> colMin(tmp5)
[1] 65.28527 58.08503 57.81232 59.83907 55.05591 60.83621 55.60824 54.35094
[9] 53.88760 62.83522 62.68431 61.44221 62.99701 57.72583 61.99565 57.18217
[17] 55.95254 55.95521 62.27308 58.40131
>
>
> ### 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] 88.92097 69.29699 68.16872 NA 71.98987 72.77109 69.47680 69.63825
[9] 68.14528 68.53159
> rowSums(tmp5)
[1] 1778.419 1385.940 1363.374 NA 1439.797 1455.422 1389.536 1392.765
[9] 1362.906 1370.632
> rowVars(tmp5)
[1] 7930.44282 114.15440 48.42900 46.08985 54.65635 82.21537
[7] 60.56028 61.11889 77.10850 52.98294
> rowSd(tmp5)
[1] 89.053034 10.684306 6.959095 6.788951 7.392993 9.067269 7.782048
[8] 7.817857 8.781145 7.278938
> rowMax(tmp5)
[1] 466.35459 95.91512 82.10674 NA 88.68770 89.94876 83.23848
[8] 81.54990 84.46629 83.01726
> rowMin(tmp5)
[1] 58.52994 53.88760 55.71009 NA 60.73041 57.25591 57.57194 55.60824
[9] 54.35094 57.18217
>
> colMeans(tmp5)
[1] 113.64430 66.80394 69.16791 68.07237 68.14734 65.88456 70.87714
[8] 72.10183 67.16553 75.22085 75.50403 NA 67.42101 65.61939
[15] 71.67263 70.72797 69.75059 65.58424 70.22393 71.63809
> colSums(tmp5)
[1] 1136.4430 668.0394 691.6791 680.7237 681.4734 658.8456 708.7714
[8] 721.0183 671.6553 752.2085 755.0403 NA 674.2101 656.1939
[15] 716.7263 707.2797 697.5059 655.8424 702.2393 716.3809
> colVars(tmp5)
[1] 15395.779241 44.084333 59.473689 41.532595 96.164787
[6] 9.219842 101.641370 57.285126 115.057976 49.031798
[11] 95.004206 NA 18.922793 39.157496 49.945289
[16] 113.085480 92.671261 23.992345 54.354087 55.110604
> colSd(tmp5)
[1] 124.079729 6.639603 7.711919 6.444579 9.806365 3.036419
[7] 10.081734 7.568694 10.726508 7.002271 9.747010 NA
[13] 4.350034 6.257595 7.067198 10.634166 9.626591 4.898198
[19] 7.372522 7.423652
> colMax(tmp5)
[1] 466.35459 78.78538 84.21658 80.91982 85.12953 69.40199 89.94876
[8] 83.17347 83.97533 82.84464 95.91512 NA 75.35361 74.98158
[15] 85.84414 88.68770 83.17629 71.77038 85.16882 82.51441
> colMin(tmp5)
[1] 65.28527 58.08503 57.81232 59.83907 55.05591 60.83621 55.60824 54.35094
[9] 53.88760 62.83522 62.68431 NA 62.99701 57.72583 61.99565 57.18217
[17] 55.95254 55.95521 62.27308 58.40131
>
> Max(tmp5,na.rm=TRUE)
[1] 466.3546
> Min(tmp5,na.rm=TRUE)
[1] 53.8876
> mean(tmp5,na.rm=TRUE)
[1] 71.76097
> Sum(tmp5,na.rm=TRUE)
[1] 14280.43
> Var(tmp5,na.rm=TRUE)
[1] 853.3392
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.92097 69.29699 68.16872 70.61270 71.98987 72.77109 69.47680 69.63825
[9] 68.14528 68.53159
> rowSums(tmp5,na.rm=TRUE)
[1] 1778.419 1385.940 1363.374 1341.641 1439.797 1455.422 1389.536 1392.765
[9] 1362.906 1370.632
> rowVars(tmp5,na.rm=TRUE)
[1] 7930.44282 114.15440 48.42900 46.08985 54.65635 82.21537
[7] 60.56028 61.11889 77.10850 52.98294
> rowSd(tmp5,na.rm=TRUE)
[1] 89.053034 10.684306 6.959095 6.788951 7.392993 9.067269 7.782048
[8] 7.817857 8.781145 7.278938
> rowMax(tmp5,na.rm=TRUE)
[1] 466.35459 95.91512 82.10674 83.97533 88.68770 89.94876 83.23848
[8] 81.54990 84.46629 83.01726
> rowMin(tmp5,na.rm=TRUE)
[1] 58.52994 53.88760 55.71009 57.72583 60.73041 57.25591 57.57194 55.60824
[9] 54.35094 57.18217
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.64430 66.80394 69.16791 68.07237 68.14734 65.88456 70.87714
[8] 72.10183 67.16553 75.22085 75.50403 69.79509 67.42101 65.61939
[15] 71.67263 70.72797 69.75059 65.58424 70.22393 71.63809
> colSums(tmp5,na.rm=TRUE)
[1] 1136.4430 668.0394 691.6791 680.7237 681.4734 658.8456 708.7714
[8] 721.0183 671.6553 752.2085 755.0403 628.1558 674.2101 656.1939
[15] 716.7263 707.2797 697.5059 655.8424 702.2393 716.3809
> colVars(tmp5,na.rm=TRUE)
[1] 15395.779241 44.084333 59.473689 41.532595 96.164787
[6] 9.219842 101.641370 57.285126 115.057976 49.031798
[11] 95.004206 44.214853 18.922793 39.157496 49.945289
[16] 113.085480 92.671261 23.992345 54.354087 55.110604
> colSd(tmp5,na.rm=TRUE)
[1] 124.079729 6.639603 7.711919 6.444579 9.806365 3.036419
[7] 10.081734 7.568694 10.726508 7.002271 9.747010 6.649425
[13] 4.350034 6.257595 7.067198 10.634166 9.626591 4.898198
[19] 7.372522 7.423652
> colMax(tmp5,na.rm=TRUE)
[1] 466.35459 78.78538 84.21658 80.91982 85.12953 69.40199 89.94876
[8] 83.17347 83.97533 82.84464 95.91512 81.63705 75.35361 74.98158
[15] 85.84414 88.68770 83.17629 71.77038 85.16882 82.51441
> colMin(tmp5,na.rm=TRUE)
[1] 65.28527 58.08503 57.81232 59.83907 55.05591 60.83621 55.60824 54.35094
[9] 53.88760 62.83522 62.68431 62.22792 62.99701 57.72583 61.99565 57.18217
[17] 55.95254 55.95521 62.27308 58.40131
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.92097 69.29699 68.16872 NaN 71.98987 72.77109 69.47680 69.63825
[9] 68.14528 68.53159
> rowSums(tmp5,na.rm=TRUE)
[1] 1778.419 1385.940 1363.374 0.000 1439.797 1455.422 1389.536 1392.765
[9] 1362.906 1370.632
> rowVars(tmp5,na.rm=TRUE)
[1] 7930.44282 114.15440 48.42900 NA 54.65635 82.21537
[7] 60.56028 61.11889 77.10850 52.98294
> rowSd(tmp5,na.rm=TRUE)
[1] 89.053034 10.684306 6.959095 NA 7.392993 9.067269 7.782048
[8] 7.817857 8.781145 7.278938
> rowMax(tmp5,na.rm=TRUE)
[1] 466.35459 95.91512 82.10674 NA 88.68770 89.94876 83.23848
[8] 81.54990 84.46629 83.01726
> rowMin(tmp5,na.rm=TRUE)
[1] 58.52994 53.88760 55.71009 NA 60.73041 57.25591 57.57194 55.60824
[9] 54.35094 57.18217
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 118.93491 66.45007 68.57720 67.70582 68.04833 65.55076 71.84033
[8] 72.13337 65.29777 74.79390 76.51364 NaN 66.74101 66.49645
[15] 71.14619 70.68960 68.25885 65.48636 70.86877 72.31505
> colSums(tmp5,na.rm=TRUE)
[1] 1070.4142 598.0506 617.1948 609.3524 612.4350 589.9568 646.5630
[8] 649.2003 587.6799 673.1451 688.6228 0.0000 600.6691 598.4681
[15] 640.3157 636.2064 614.3296 589.3773 637.8189 650.8355
> colVars(tmp5,na.rm=TRUE)
[1] 17005.35777 48.18607 62.98235 45.21262 108.07510 9.11879
[7] 103.90949 64.43458 90.19446 53.11001 95.41246 NA
[13] 16.08612 35.39824 53.07061 127.20460 79.22055 26.88361
[19] 56.47041 56.84385
> colSd(tmp5,na.rm=TRUE)
[1] 130.404593 6.941619 7.936142 6.724033 10.395918 3.019733
[7] 10.193600 8.027115 9.497076 7.287662 9.767930 NA
[13] 4.010751 5.949642 7.284958 11.278502 8.900593 5.184941
[19] 7.514679 7.539486
> colMax(tmp5,na.rm=TRUE)
[1] 466.35459 78.78538 84.21658 80.91982 85.12953 69.40199 89.94876
[8] 83.17347 81.54990 82.84464 95.91512 -Inf 75.35361 74.98158
[15] 85.84414 88.68770 83.01726 71.77038 85.16882 82.51441
> colMin(tmp5,na.rm=TRUE)
[1] 65.28527 58.08503 57.81232 59.83907 55.05591 60.83621 55.60824 54.35094
[9] 53.88760 62.83522 62.68431 Inf 62.99701 57.85172 61.99565 57.18217
[17] 55.95254 55.95521 62.27308 58.40131
>
>
>
>
> 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] 116.9665 134.5317 248.1996 313.5150 285.9426 217.6210 324.7667 231.5634
[9] 228.4337 210.3505
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 116.9665 134.5317 248.1996 313.5150 285.9426 217.6210 324.7667 231.5634
[9] 228.4337 210.3505
>
>
>
> 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] -2.273737e-13 1.705303e-13 5.684342e-14 0.000000e+00 -4.263256e-14
[6] 0.000000e+00 1.421085e-13 0.000000e+00 1.705303e-13 0.000000e+00
[11] -2.842171e-14 2.273737e-13 -2.842171e-13 -1.563194e-13 0.000000e+00
[16] 1.421085e-13 1.136868e-13 1.136868e-13 5.684342e-14 -1.421085e-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)
+ }
2 6
9 13
1 11
6 5
2 20
5 11
7 16
7 3
1 10
4 3
6 13
10 13
5 18
10 14
3 6
4 13
6 2
3 8
9 16
7 1
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] 2.591624
> Min(tmp)
[1] -2.198961
> mean(tmp)
[1] 0.05173353
> Sum(tmp)
[1] 5.173353
> Var(tmp)
[1] 0.9322703
>
> rowMeans(tmp)
[1] 0.05173353
> rowSums(tmp)
[1] 5.173353
> rowVars(tmp)
[1] 0.9322703
> rowSd(tmp)
[1] 0.9655414
> rowMax(tmp)
[1] 2.591624
> rowMin(tmp)
[1] -2.198961
>
> colMeans(tmp)
[1] -0.9291834717 -0.6380497344 0.7521251498 -0.3810700550 0.3515285432
[6] 0.5961799467 0.4396872418 0.2911073709 0.3361616935 1.3215189871
[11] -0.8525350229 1.0414658164 0.2496211502 -0.3755182921 0.9465267900
[16] -1.0415486797 0.0505358935 0.1749020575 0.1464667018 -0.1787303901
[21] 0.7665079092 -0.4388666629 -0.2454511754 0.1206135642 -0.8260962012
[26] 0.5971578477 -0.3736894061 0.4012469975 -1.0648526585 -0.9529267910
[31] -0.1577802767 -0.5128446790 0.0803002798 0.1356905108 -0.9881969849
[36] -1.9865873298 1.3185692338 -0.5425513264 -0.5417256547 0.4610674013
[41] -1.1848288996 -0.3388016892 1.4412226411 0.6777624605 -0.9634090489
[46] -1.1092975942 1.5877387574 -0.2373675824 -1.2529619413 0.0909306859
[51] 1.5174329701 2.5916235025 -1.1838600369 0.9031846542 0.0196444455
[56] -0.1462692644 0.4871655973 0.5070610566 -0.1190944644 1.1923812817
[61] 0.5374490537 -1.7686526253 -0.0001482986 -0.0574711019 -1.9953868903
[66] -0.7513712930 -0.0402963949 2.2383608817 2.5127770736 -0.0301855937
[71] 0.4288832539 2.1416763932 0.1770814462 -0.7672589812 1.2430786549
[76] 0.3744255763 -0.7659333090 -0.9453555484 0.3574916615 -0.1282812082
[81] 0.5834249356 -1.2126447551 -1.0148049136 0.5105184923 0.1246815948
[86] -0.5110193981 2.1792805831 -0.2832316171 0.0652666105 -0.4947857066
[91] -2.1989605095 1.4805879795 -0.4382241522 1.3679599383 0.4572725405
[96] -0.0863314516 -0.2604178199 -0.3601833736 1.2961524825 -0.8231050253
> colSums(tmp)
[1] -0.9291834717 -0.6380497344 0.7521251498 -0.3810700550 0.3515285432
[6] 0.5961799467 0.4396872418 0.2911073709 0.3361616935 1.3215189871
[11] -0.8525350229 1.0414658164 0.2496211502 -0.3755182921 0.9465267900
[16] -1.0415486797 0.0505358935 0.1749020575 0.1464667018 -0.1787303901
[21] 0.7665079092 -0.4388666629 -0.2454511754 0.1206135642 -0.8260962012
[26] 0.5971578477 -0.3736894061 0.4012469975 -1.0648526585 -0.9529267910
[31] -0.1577802767 -0.5128446790 0.0803002798 0.1356905108 -0.9881969849
[36] -1.9865873298 1.3185692338 -0.5425513264 -0.5417256547 0.4610674013
[41] -1.1848288996 -0.3388016892 1.4412226411 0.6777624605 -0.9634090489
[46] -1.1092975942 1.5877387574 -0.2373675824 -1.2529619413 0.0909306859
[51] 1.5174329701 2.5916235025 -1.1838600369 0.9031846542 0.0196444455
[56] -0.1462692644 0.4871655973 0.5070610566 -0.1190944644 1.1923812817
[61] 0.5374490537 -1.7686526253 -0.0001482986 -0.0574711019 -1.9953868903
[66] -0.7513712930 -0.0402963949 2.2383608817 2.5127770736 -0.0301855937
[71] 0.4288832539 2.1416763932 0.1770814462 -0.7672589812 1.2430786549
[76] 0.3744255763 -0.7659333090 -0.9453555484 0.3574916615 -0.1282812082
[81] 0.5834249356 -1.2126447551 -1.0148049136 0.5105184923 0.1246815948
[86] -0.5110193981 2.1792805831 -0.2832316171 0.0652666105 -0.4947857066
[91] -2.1989605095 1.4805879795 -0.4382241522 1.3679599383 0.4572725405
[96] -0.0863314516 -0.2604178199 -0.3601833736 1.2961524825 -0.8231050253
> 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] -0.9291834717 -0.6380497344 0.7521251498 -0.3810700550 0.3515285432
[6] 0.5961799467 0.4396872418 0.2911073709 0.3361616935 1.3215189871
[11] -0.8525350229 1.0414658164 0.2496211502 -0.3755182921 0.9465267900
[16] -1.0415486797 0.0505358935 0.1749020575 0.1464667018 -0.1787303901
[21] 0.7665079092 -0.4388666629 -0.2454511754 0.1206135642 -0.8260962012
[26] 0.5971578477 -0.3736894061 0.4012469975 -1.0648526585 -0.9529267910
[31] -0.1577802767 -0.5128446790 0.0803002798 0.1356905108 -0.9881969849
[36] -1.9865873298 1.3185692338 -0.5425513264 -0.5417256547 0.4610674013
[41] -1.1848288996 -0.3388016892 1.4412226411 0.6777624605 -0.9634090489
[46] -1.1092975942 1.5877387574 -0.2373675824 -1.2529619413 0.0909306859
[51] 1.5174329701 2.5916235025 -1.1838600369 0.9031846542 0.0196444455
[56] -0.1462692644 0.4871655973 0.5070610566 -0.1190944644 1.1923812817
[61] 0.5374490537 -1.7686526253 -0.0001482986 -0.0574711019 -1.9953868903
[66] -0.7513712930 -0.0402963949 2.2383608817 2.5127770736 -0.0301855937
[71] 0.4288832539 2.1416763932 0.1770814462 -0.7672589812 1.2430786549
[76] 0.3744255763 -0.7659333090 -0.9453555484 0.3574916615 -0.1282812082
[81] 0.5834249356 -1.2126447551 -1.0148049136 0.5105184923 0.1246815948
[86] -0.5110193981 2.1792805831 -0.2832316171 0.0652666105 -0.4947857066
[91] -2.1989605095 1.4805879795 -0.4382241522 1.3679599383 0.4572725405
[96] -0.0863314516 -0.2604178199 -0.3601833736 1.2961524825 -0.8231050253
> colMin(tmp)
[1] -0.9291834717 -0.6380497344 0.7521251498 -0.3810700550 0.3515285432
[6] 0.5961799467 0.4396872418 0.2911073709 0.3361616935 1.3215189871
[11] -0.8525350229 1.0414658164 0.2496211502 -0.3755182921 0.9465267900
[16] -1.0415486797 0.0505358935 0.1749020575 0.1464667018 -0.1787303901
[21] 0.7665079092 -0.4388666629 -0.2454511754 0.1206135642 -0.8260962012
[26] 0.5971578477 -0.3736894061 0.4012469975 -1.0648526585 -0.9529267910
[31] -0.1577802767 -0.5128446790 0.0803002798 0.1356905108 -0.9881969849
[36] -1.9865873298 1.3185692338 -0.5425513264 -0.5417256547 0.4610674013
[41] -1.1848288996 -0.3388016892 1.4412226411 0.6777624605 -0.9634090489
[46] -1.1092975942 1.5877387574 -0.2373675824 -1.2529619413 0.0909306859
[51] 1.5174329701 2.5916235025 -1.1838600369 0.9031846542 0.0196444455
[56] -0.1462692644 0.4871655973 0.5070610566 -0.1190944644 1.1923812817
[61] 0.5374490537 -1.7686526253 -0.0001482986 -0.0574711019 -1.9953868903
[66] -0.7513712930 -0.0402963949 2.2383608817 2.5127770736 -0.0301855937
[71] 0.4288832539 2.1416763932 0.1770814462 -0.7672589812 1.2430786549
[76] 0.3744255763 -0.7659333090 -0.9453555484 0.3574916615 -0.1282812082
[81] 0.5834249356 -1.2126447551 -1.0148049136 0.5105184923 0.1246815948
[86] -0.5110193981 2.1792805831 -0.2832316171 0.0652666105 -0.4947857066
[91] -2.1989605095 1.4805879795 -0.4382241522 1.3679599383 0.4572725405
[96] -0.0863314516 -0.2604178199 -0.3601833736 1.2961524825 -0.8231050253
> colMedians(tmp)
[1] -0.9291834717 -0.6380497344 0.7521251498 -0.3810700550 0.3515285432
[6] 0.5961799467 0.4396872418 0.2911073709 0.3361616935 1.3215189871
[11] -0.8525350229 1.0414658164 0.2496211502 -0.3755182921 0.9465267900
[16] -1.0415486797 0.0505358935 0.1749020575 0.1464667018 -0.1787303901
[21] 0.7665079092 -0.4388666629 -0.2454511754 0.1206135642 -0.8260962012
[26] 0.5971578477 -0.3736894061 0.4012469975 -1.0648526585 -0.9529267910
[31] -0.1577802767 -0.5128446790 0.0803002798 0.1356905108 -0.9881969849
[36] -1.9865873298 1.3185692338 -0.5425513264 -0.5417256547 0.4610674013
[41] -1.1848288996 -0.3388016892 1.4412226411 0.6777624605 -0.9634090489
[46] -1.1092975942 1.5877387574 -0.2373675824 -1.2529619413 0.0909306859
[51] 1.5174329701 2.5916235025 -1.1838600369 0.9031846542 0.0196444455
[56] -0.1462692644 0.4871655973 0.5070610566 -0.1190944644 1.1923812817
[61] 0.5374490537 -1.7686526253 -0.0001482986 -0.0574711019 -1.9953868903
[66] -0.7513712930 -0.0402963949 2.2383608817 2.5127770736 -0.0301855937
[71] 0.4288832539 2.1416763932 0.1770814462 -0.7672589812 1.2430786549
[76] 0.3744255763 -0.7659333090 -0.9453555484 0.3574916615 -0.1282812082
[81] 0.5834249356 -1.2126447551 -1.0148049136 0.5105184923 0.1246815948
[86] -0.5110193981 2.1792805831 -0.2832316171 0.0652666105 -0.4947857066
[91] -2.1989605095 1.4805879795 -0.4382241522 1.3679599383 0.4572725405
[96] -0.0863314516 -0.2604178199 -0.3601833736 1.2961524825 -0.8231050253
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.9291835 -0.6380497 0.7521251 -0.3810701 0.3515285 0.5961799 0.4396872
[2,] -0.9291835 -0.6380497 0.7521251 -0.3810701 0.3515285 0.5961799 0.4396872
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.2911074 0.3361617 1.321519 -0.852535 1.041466 0.2496212 -0.3755183
[2,] 0.2911074 0.3361617 1.321519 -0.852535 1.041466 0.2496212 -0.3755183
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.9465268 -1.041549 0.05053589 0.1749021 0.1464667 -0.1787304 0.7665079
[2,] 0.9465268 -1.041549 0.05053589 0.1749021 0.1464667 -0.1787304 0.7665079
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.4388667 -0.2454512 0.1206136 -0.8260962 0.5971578 -0.3736894 0.401247
[2,] -0.4388667 -0.2454512 0.1206136 -0.8260962 0.5971578 -0.3736894 0.401247
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.064853 -0.9529268 -0.1577803 -0.5128447 0.08030028 0.1356905 -0.988197
[2,] -1.064853 -0.9529268 -0.1577803 -0.5128447 0.08030028 0.1356905 -0.988197
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.986587 1.318569 -0.5425513 -0.5417257 0.4610674 -1.184829 -0.3388017
[2,] -1.986587 1.318569 -0.5425513 -0.5417257 0.4610674 -1.184829 -0.3388017
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 1.441223 0.6777625 -0.963409 -1.109298 1.587739 -0.2373676 -1.252962
[2,] 1.441223 0.6777625 -0.963409 -1.109298 1.587739 -0.2373676 -1.252962
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.09093069 1.517433 2.591624 -1.18386 0.9031847 0.01964445 -0.1462693
[2,] 0.09093069 1.517433 2.591624 -1.18386 0.9031847 0.01964445 -0.1462693
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.4871656 0.5070611 -0.1190945 1.192381 0.5374491 -1.768653 -0.0001482986
[2,] 0.4871656 0.5070611 -0.1190945 1.192381 0.5374491 -1.768653 -0.0001482986
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.0574711 -1.995387 -0.7513713 -0.04029639 2.238361 2.512777 -0.03018559
[2,] -0.0574711 -1.995387 -0.7513713 -0.04029639 2.238361 2.512777 -0.03018559
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.4288833 2.141676 0.1770814 -0.767259 1.243079 0.3744256 -0.7659333
[2,] 0.4288833 2.141676 0.1770814 -0.767259 1.243079 0.3744256 -0.7659333
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.9453555 0.3574917 -0.1282812 0.5834249 -1.212645 -1.014805 0.5105185
[2,] -0.9453555 0.3574917 -0.1282812 0.5834249 -1.212645 -1.014805 0.5105185
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.1246816 -0.5110194 2.179281 -0.2832316 0.06526661 -0.4947857 -2.198961
[2,] 0.1246816 -0.5110194 2.179281 -0.2832316 0.06526661 -0.4947857 -2.198961
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 1.480588 -0.4382242 1.36796 0.4572725 -0.08633145 -0.2604178 -0.3601834
[2,] 1.480588 -0.4382242 1.36796 0.4572725 -0.08633145 -0.2604178 -0.3601834
[,99] [,100]
[1,] 1.296152 -0.823105
[2,] 1.296152 -0.823105
>
>
> Max(tmp2)
[1] 2.520865
> Min(tmp2)
[1] -2.18053
> mean(tmp2)
[1] 0.02507307
> Sum(tmp2)
[1] 2.507307
> Var(tmp2)
[1] 0.9079281
>
> rowMeans(tmp2)
[1] -0.369755056 2.030788013 -0.675712972 -0.337595168 0.660982237
[6] 0.078522844 -0.713722027 -0.565587163 1.366472707 0.235685830
[11] -1.841457085 -1.430644948 -2.180529835 -0.738240235 0.367437790
[16] 0.424008464 1.365652362 1.945895864 1.477411902 0.105180994
[21] -1.222209718 -0.147789385 1.732020955 -0.222419739 -1.104208786
[26] -0.307571994 -0.409890910 0.760866900 -0.566581264 1.080915142
[31] 2.520864558 -0.592257854 -1.240233812 0.150373597 0.590372985
[36] -0.507235068 -0.579007657 0.562477100 -0.194602521 -0.930039464
[41] -0.051630149 0.275849767 -2.155224494 0.715192770 -0.844705684
[46] 0.985382622 1.220484928 2.133920783 0.482627119 -0.185829136
[51] -1.247918054 0.674880088 -0.105093092 -0.405493848 -0.008343138
[56] 1.128148418 -1.344801017 -0.561874919 -1.232034400 0.275160481
[61] -0.501269493 -0.344266246 0.972069346 -0.366069987 -0.080295313
[66] -0.943445440 0.773001099 0.038856882 1.343078410 -1.004367717
[71] 0.791072314 -0.698313087 0.561340345 -0.646569472 0.070170404
[76] -0.648317832 -0.901591570 -0.840518412 1.080478733 -0.130577372
[81] -0.117420532 1.361444028 0.439899509 -1.564600872 0.386860040
[86] 0.786307817 -1.027146795 0.240677322 0.596683533 -0.959392124
[91] 0.431419935 0.603097885 0.100382447 -0.247698633 -0.950163035
[96] 1.175969130 -0.184119897 1.269009856 1.016943202 0.297352306
> rowSums(tmp2)
[1] -0.369755056 2.030788013 -0.675712972 -0.337595168 0.660982237
[6] 0.078522844 -0.713722027 -0.565587163 1.366472707 0.235685830
[11] -1.841457085 -1.430644948 -2.180529835 -0.738240235 0.367437790
[16] 0.424008464 1.365652362 1.945895864 1.477411902 0.105180994
[21] -1.222209718 -0.147789385 1.732020955 -0.222419739 -1.104208786
[26] -0.307571994 -0.409890910 0.760866900 -0.566581264 1.080915142
[31] 2.520864558 -0.592257854 -1.240233812 0.150373597 0.590372985
[36] -0.507235068 -0.579007657 0.562477100 -0.194602521 -0.930039464
[41] -0.051630149 0.275849767 -2.155224494 0.715192770 -0.844705684
[46] 0.985382622 1.220484928 2.133920783 0.482627119 -0.185829136
[51] -1.247918054 0.674880088 -0.105093092 -0.405493848 -0.008343138
[56] 1.128148418 -1.344801017 -0.561874919 -1.232034400 0.275160481
[61] -0.501269493 -0.344266246 0.972069346 -0.366069987 -0.080295313
[66] -0.943445440 0.773001099 0.038856882 1.343078410 -1.004367717
[71] 0.791072314 -0.698313087 0.561340345 -0.646569472 0.070170404
[76] -0.648317832 -0.901591570 -0.840518412 1.080478733 -0.130577372
[81] -0.117420532 1.361444028 0.439899509 -1.564600872 0.386860040
[86] 0.786307817 -1.027146795 0.240677322 0.596683533 -0.959392124
[91] 0.431419935 0.603097885 0.100382447 -0.247698633 -0.950163035
[96] 1.175969130 -0.184119897 1.269009856 1.016943202 0.297352306
> 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] -0.369755056 2.030788013 -0.675712972 -0.337595168 0.660982237
[6] 0.078522844 -0.713722027 -0.565587163 1.366472707 0.235685830
[11] -1.841457085 -1.430644948 -2.180529835 -0.738240235 0.367437790
[16] 0.424008464 1.365652362 1.945895864 1.477411902 0.105180994
[21] -1.222209718 -0.147789385 1.732020955 -0.222419739 -1.104208786
[26] -0.307571994 -0.409890910 0.760866900 -0.566581264 1.080915142
[31] 2.520864558 -0.592257854 -1.240233812 0.150373597 0.590372985
[36] -0.507235068 -0.579007657 0.562477100 -0.194602521 -0.930039464
[41] -0.051630149 0.275849767 -2.155224494 0.715192770 -0.844705684
[46] 0.985382622 1.220484928 2.133920783 0.482627119 -0.185829136
[51] -1.247918054 0.674880088 -0.105093092 -0.405493848 -0.008343138
[56] 1.128148418 -1.344801017 -0.561874919 -1.232034400 0.275160481
[61] -0.501269493 -0.344266246 0.972069346 -0.366069987 -0.080295313
[66] -0.943445440 0.773001099 0.038856882 1.343078410 -1.004367717
[71] 0.791072314 -0.698313087 0.561340345 -0.646569472 0.070170404
[76] -0.648317832 -0.901591570 -0.840518412 1.080478733 -0.130577372
[81] -0.117420532 1.361444028 0.439899509 -1.564600872 0.386860040
[86] 0.786307817 -1.027146795 0.240677322 0.596683533 -0.959392124
[91] 0.431419935 0.603097885 0.100382447 -0.247698633 -0.950163035
[96] 1.175969130 -0.184119897 1.269009856 1.016943202 0.297352306
> rowMin(tmp2)
[1] -0.369755056 2.030788013 -0.675712972 -0.337595168 0.660982237
[6] 0.078522844 -0.713722027 -0.565587163 1.366472707 0.235685830
[11] -1.841457085 -1.430644948 -2.180529835 -0.738240235 0.367437790
[16] 0.424008464 1.365652362 1.945895864 1.477411902 0.105180994
[21] -1.222209718 -0.147789385 1.732020955 -0.222419739 -1.104208786
[26] -0.307571994 -0.409890910 0.760866900 -0.566581264 1.080915142
[31] 2.520864558 -0.592257854 -1.240233812 0.150373597 0.590372985
[36] -0.507235068 -0.579007657 0.562477100 -0.194602521 -0.930039464
[41] -0.051630149 0.275849767 -2.155224494 0.715192770 -0.844705684
[46] 0.985382622 1.220484928 2.133920783 0.482627119 -0.185829136
[51] -1.247918054 0.674880088 -0.105093092 -0.405493848 -0.008343138
[56] 1.128148418 -1.344801017 -0.561874919 -1.232034400 0.275160481
[61] -0.501269493 -0.344266246 0.972069346 -0.366069987 -0.080295313
[66] -0.943445440 0.773001099 0.038856882 1.343078410 -1.004367717
[71] 0.791072314 -0.698313087 0.561340345 -0.646569472 0.070170404
[76] -0.648317832 -0.901591570 -0.840518412 1.080478733 -0.130577372
[81] -0.117420532 1.361444028 0.439899509 -1.564600872 0.386860040
[86] 0.786307817 -1.027146795 0.240677322 0.596683533 -0.959392124
[91] 0.431419935 0.603097885 0.100382447 -0.247698633 -0.950163035
[96] 1.175969130 -0.184119897 1.269009856 1.016943202 0.297352306
>
> colMeans(tmp2)
[1] 0.02507307
> colSums(tmp2)
[1] 2.507307
> colVars(tmp2)
[1] 0.9079281
> colSd(tmp2)
[1] 0.9528526
> colMax(tmp2)
[1] 2.520865
> colMin(tmp2)
[1] -2.18053
> colMedians(tmp2)
[1] -0.06596273
> colRanges(tmp2)
[,1]
[1,] -2.180530
[2,] 2.520865
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 3.14749288 -1.34656949 2.00121700 -2.73987756 2.05064545 -1.25940734
[7] 5.35553939 -0.03061802 -2.99727495 5.37928939
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.3579794
[2,] -0.7717826
[3,] 0.8951563
[4,] 1.2296653
[5,] 1.5239657
>
> rowApply(tmp,sum)
[1] -1.422708 2.595031 2.555050 -1.771179 2.869401 -1.561250 -1.025874
[8] 4.738919 -1.947010 4.530056
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 8 9 1 9 2 3 9 10 6
[2,] 2 2 3 3 10 3 5 8 8 9
[3,] 6 9 2 9 2 6 8 4 5 5
[4,] 4 3 8 5 7 1 4 6 3 3
[5,] 7 6 7 8 6 5 6 2 7 7
[6,] 10 5 10 2 1 4 1 10 1 2
[7,] 8 4 6 7 4 9 10 5 4 10
[8,] 9 7 1 4 5 8 7 1 2 4
[9,] 3 1 4 6 3 7 9 3 6 8
[10,] 1 10 5 10 8 10 2 7 9 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -5.57738421 -0.09564100 2.07884755 0.53604685 0.45363458 2.26663888
[7] 2.51090698 -3.12335291 0.75776452 -0.85852298 -0.67008078 -1.28709257
[13] -1.13731005 -4.61898574 2.78322229 5.00451960 -0.03092591 -1.96190100
[19] 2.75155680 -1.14257015
> colApply(tmp,quantile)[,1]
[,1]
[1,] -3.2304797
[2,] -1.1268545
[3,] -0.8124555
[4,] -0.7569395
[5,] 0.3493449
>
> rowApply(tmp,sum)
[1] -1.0208739 5.9646959 -2.9648353 -2.3492388 -0.9903771
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 1 2 6 15 6
[2,] 12 14 15 5 7
[3,] 11 17 12 8 12
[4,] 3 3 7 20 15
[5,] 9 12 17 6 11
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -3.2304797 0.1389086 0.04733421 -0.8815402 -0.07939436 -1.3789317
[2,] -1.1268545 0.8995811 1.88359153 -0.9849243 0.17443322 2.3713811
[3,] -0.7569395 0.4113117 0.15069000 -0.6571798 0.80652458 0.5028879
[4,] 0.3493449 -0.9217063 -0.41646882 2.3221444 -0.81078131 -0.3579625
[5,] -0.8124555 -0.6237362 0.41370062 0.7375467 0.36285245 1.1292640
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.01630436 -0.58958706 0.8810058 -0.5215737 1.3281848 0.6546732
[2,] 1.28432550 -0.08897662 -1.7305035 -0.6992882 -0.1595672 -0.5367176
[3,] -1.36808277 -0.31217162 1.5192577 0.3185236 0.1838139 -0.6176628
[4,] 0.95865272 -0.07288170 -0.2299337 -0.3999208 -1.0854029 -1.6170964
[5,] 1.65231589 -2.05973591 0.3179382 0.4437362 -0.9371094 0.8297110
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.68199331 0.4316671 1.7023505 1.7360634 -0.22948721 -0.76376802
[2,] 2.21465867 -0.3902119 0.9595887 2.0050681 0.05769638 0.09339521
[3,] -1.74393296 -0.8523428 1.0592352 -1.1041286 -1.41276785 -0.07258827
[4,] 0.06081724 -0.6354700 0.7916009 0.3302776 0.88473970 -1.29754513
[5,] -0.98685969 -3.1726281 -1.7295530 2.0372390 0.66889307 0.07860521
[,19] [,20]
[1,] 0.1868437 0.2451543
[2,] 0.6769578 -0.9389377
[3,] 1.4875779 -0.5068608
[4,] 0.7457270 -0.9473738
[5,] -0.3455495 1.0054478
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.15-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: /Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 648 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 563 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.15-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 0.8640816 0.4001838 0.9119491 1.123368 0.289121 1.31404 -1.426124
col8 col9 col10 col11 col12 col13 col14
row1 0.0529195 -0.7197557 -1.537205 0.06384409 0.2058025 -0.6477287 1.484229
col15 col16 col17 col18 col19 col20
row1 -1.0056 -0.7082226 -0.7986263 0.1393362 0.7437141 -0.6284528
> tmp[,"col10"]
col10
row1 -1.5372055
row2 -0.2030892
row3 0.8997229
row4 -0.8292730
row5 0.6089370
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.8640816 0.4001838 0.9119491 1.1233683 0.2891210 1.3140402 -1.4261245
row5 -1.3075215 0.3073932 0.3532231 0.4648911 -0.4112323 -0.9328007 -0.2584498
col8 col9 col10 col11 col12 col13 col14
row1 0.0529195 -0.7197557 -1.537205 0.06384409 0.2058025 -0.6477287 1.4842291
row5 0.1953849 -0.0839440 0.608937 1.85702376 0.2846413 -0.4994180 0.1698849
col15 col16 col17 col18 col19 col20
row1 -1.0056000 -0.7082226 -0.7986263 0.13933617 0.7437141 -0.6284528
row5 -0.8472107 0.1392922 -0.1738054 -0.01264897 1.4254247 1.0124664
> tmp[,c("col6","col20")]
col6 col20
row1 1.31404022 -0.6284528
row2 -0.09825848 0.2867177
row3 0.73497182 1.3533279
row4 -0.21243289 -1.5762116
row5 -0.93280074 1.0124664
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.3140402 -0.6284528
row5 -0.9328007 1.0124664
>
>
>
>
> 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 48.4613 50.25185 48.56407 50.27813 49.24073 105.3572 50.62027 50.49066
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.28517 49.53186 49.84861 51.26276 49.89632 50.64104 49.16665 49.59451
col17 col18 col19 col20
row1 51.16377 48.81161 47.5785 105.6071
> tmp[,"col10"]
col10
row1 49.53186
row2 30.62074
row3 30.28187
row4 30.74882
row5 48.85461
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.46130 50.25185 48.56407 50.27813 49.24073 105.3572 50.62027 50.49066
row5 48.48291 51.04469 48.64812 50.90979 50.39240 104.1379 50.31120 49.58952
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.28517 49.53186 49.84861 51.26276 49.89632 50.64104 49.16665 49.59451
row5 52.27742 48.85461 48.92007 50.52961 51.21096 50.85261 51.75797 50.56182
col17 col18 col19 col20
row1 51.16377 48.81161 47.5785 105.6071
row5 50.37889 48.55420 50.0186 105.8266
> tmp[,c("col6","col20")]
col6 col20
row1 105.35723 105.60712
row2 74.64374 74.76559
row3 73.80459 74.05980
row4 76.32165 74.63149
row5 104.13786 105.82664
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.3572 105.6071
row5 104.1379 105.8266
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.3572 105.6071
row5 104.1379 105.8266
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.4744810
[2,] 0.1802154
[3,] -0.9484525
[4,] 0.5624270
[5,] -1.2589747
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.0683675 0.25336046
[2,] -0.4879747 -0.03385409
[3,] -0.1060812 1.41027925
[4,] -0.8502086 -0.97022922
[5,] -0.4142644 -0.98149619
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.23442023 -0.655471
[2,] -0.13214016 1.088533
[3,] -1.39436816 1.232372
[4,] -0.06458078 1.341078
[5,] 0.57303791 0.991986
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.2344202
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.2344202
[2,] -0.1321402
>
>
>
> 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 0.2229629 -1.2408420 -0.5605786 0.01180227 -0.1367228 -0.8332769
row1 1.6065149 -0.5624159 -1.4149421 -0.01018690 0.4496385 -1.5891341
[,7] [,8] [,9] [,10] [,11] [,12]
row3 0.8725546 0.7763533 0.29934911 -0.7401074 -1.3357646 0.9738867
row1 -0.4420013 1.0839652 -0.03870084 -0.8822743 -0.4261581 2.4271094
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.9154632 -0.3239722 -0.0142818 1.0435840 -0.6215165 0.4620619 0.9992475
row1 -0.7088694 -0.3974923 -0.3482853 -0.8707748 -2.9681481 1.7493467 1.3989264
[,20]
row3 -0.8234644
row1 -1.3165006
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.828448 0.9536818 -2.290768 0.1633661 0.3649942 -0.3081976 -0.477634
[,8] [,9] [,10]
row2 0.5287619 0.2320961 -0.6864145
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.5107183 -0.4873935 -1.876081 -1.025006 1.275908 1.554008 -2.720587
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.2885285 -0.1340868 -0.5129465 -0.2935757 0.2804225 1.091927 0.9393809
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.4119479 0.7032064 -0.5812854 0.8835267 0.1803495 0.8934668
>
>
> 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: 0x7f9086c0b860>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests/BMad96535f9d7d"
[2] "/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests/BMad962a5ca44e"
[3] "/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests/BMad962827129c"
[4] "/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests/BMad961d36d45c"
[5] "/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests/BMad967aaff2ff"
[6] "/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests/BMad96357a8246"
[7] "/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests/BMad967dfedd17"
[8] "/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests/BMad96676551a0"
[9] "/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests/BMad962cd21468"
[10] "/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests/BMad961439ced5"
[11] "/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests/BMad965f3a0c52"
[12] "/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests/BMad965bff0c55"
[13] "/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests/BMad964582cfa2"
[14] "/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests/BMad96f0db855"
[15] "/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests/BMad964dc0dc2b"
>
>
> ### 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: 0x7f90a6f298b0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x7f90a6f298b0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.15-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x7f90a6f298b0>
> rowMedians(tmp)
[1] -0.427698092 -0.301724088 0.336698501 0.390690856 0.434351506
[6] -0.143409636 -0.091075477 -0.525191852 -0.002412178 0.349019302
[11] -0.206954288 0.044420646 0.516092554 -0.403213648 -0.160079063
[16] -0.130113956 0.272920946 0.316891386 0.149908193 0.164438368
[21] -0.481131444 -0.450274265 -0.618061440 -0.233507531 0.449305462
[26] -0.516054215 -0.549509441 -0.238042563 0.298223066 0.322171420
[31] 0.516418915 -0.130377812 -0.013910247 0.233888549 0.178182831
[36] -0.131954055 0.090297471 -0.234576289 0.304070465 -0.454297300
[41] 0.369552446 -0.400995819 0.602814026 0.292296556 0.530027842
[46] 0.069784056 -0.094431077 0.141001189 -0.007602955 -0.290492778
[51] 0.026076492 0.237072021 -0.250614077 -0.458304958 -0.032387984
[56] 0.534926461 0.295146232 -0.350397796 -0.309361889 0.346187703
[61] 0.464342232 -0.112750007 -0.133334422 -0.034729542 -0.117160584
[66] 0.169003988 -0.024236546 0.441937133 0.118166712 0.111509196
[71] -0.180966206 -0.007287372 0.063368805 0.281784575 -0.143046404
[76] -0.208766688 -0.131824427 0.001542179 0.093054164 0.714996224
[81] 0.410712847 -0.211688290 0.612218578 -0.029511567 -0.014738037
[86] 0.621870287 0.242415886 0.210288555 0.468973880 -0.475771622
[91] -0.168591786 -0.049544092 -0.629699030 0.799822362 0.005332679
[96] 0.304703260 -0.091383637 -0.210853164 -0.316013403 0.559860615
[101] 0.029452155 0.394805723 0.429798375 0.368632766 0.354702789
[106] -0.178719445 0.122792043 0.549834115 -0.246836243 -0.622231098
[111] -0.028795858 0.310452527 0.035569228 0.004400015 0.056332523
[116] -0.067749042 0.141109812 0.364031019 -0.226969238 -0.056846927
[121] -0.262343399 -0.403030249 0.486536470 -0.153654243 -0.376645685
[126] 0.074716897 0.343826516 -0.311239648 0.034554063 -0.608312622
[131] 0.444848074 -0.178435057 -0.301795931 -0.182859437 -0.068920387
[136] 0.074537042 0.117942123 -0.302459459 0.507657129 -0.391762832
[141] -0.194165592 0.067756955 0.474115547 -0.459126702 -0.023652982
[146] 0.341231683 0.146396169 -0.282570259 0.768302230 0.759154212
[151] -0.337607697 0.222147496 0.161295748 0.034653342 -0.628705282
[156] 0.191773911 0.329480008 0.420554038 0.263052166 0.053640649
[161] -0.610039667 0.035908764 0.032615039 -0.175140821 0.042149527
[166] -0.016950937 -0.385001653 -0.456436308 0.255585220 -0.027193317
[171] -0.349225643 0.141468756 0.089583681 0.542318737 -0.050115109
[176] -0.360192184 -0.279784707 0.687187105 0.076290552 0.542081131
[181] -0.084390007 0.129564290 0.468504251 0.823369051 0.545390392
[186] 0.078120474 0.152766828 -0.628497358 -0.327601542 -0.356107253
[191] 0.036088477 0.353557002 0.111131616 0.067474834 -0.548907479
[196] -0.174537102 -0.126631775 0.043173634 0.685978669 0.032034664
[201] 0.155292071 -0.397400845 0.030520878 0.574388277 -0.085389732
[206] 0.488915087 -0.330375964 -0.008965820 -0.245052934 0.598847300
[211] -0.132874931 0.066472977 -0.265494847 -0.104388748 0.401187471
[216] -0.191610958 0.259153248 -0.028343671 -0.107779062 -0.627339570
[221] 0.304005906 0.128053811 0.293612256 -0.235345554 0.161917946
[226] 0.375216452 -0.130773009 -0.239251381 0.131886907 -0.174132746
>
> proc.time()
user system elapsed
4.232 11.974 16.465
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.2.1 (2022-06-23) -- "Funny-Looking Kid"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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: 0x7fce16f0f220>
> .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: 0x7fce16f0f220>
> .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: 0x7fce16f0f220>
> .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: 0x7fce16f0f220>
> 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: 0x7fce20900270>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fce20900270>
> .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: 0x7fce20900270>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fce20900270>
> .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: 0x7fce20900270>
> 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: 0x7fce20910f20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fce20910f20>
> .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: 0x7fce20910f20>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x7fce20910f20>
> .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: 0x7fce20910f20>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x7fce20910f20>
> .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: 0x7fce20910f20>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x7fce20910f20>
> .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: 0x7fce20910f20>
> 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: 0x7fcda6d02bc0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x7fcda6d02bc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fcda6d02bc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fcda6d02bc0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFileaf0c26fff7c3" "BufferedMatrixFileaf0c6ee33735"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFileaf0c26fff7c3" "BufferedMatrixFileaf0c6ee33735"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fcda6d00150>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fcda6d00150>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x7fcda6d00150>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x7fcda6d00150>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x7fcda6d00150>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x7fcda6d00150>
> .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: 0x7fcda6d1dd10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fcda6d1dd10>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x7fcda6d1dd10>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x7fcda6d1dd10>
> 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: 0x7fcda6d1da70>
> .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: 0x7fcda6d1da70>
> rm(P)
>
> proc.time()
user system elapsed
0.562 0.138 0.676
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.2.1 (2022-06-23) -- "Funny-Looking Kid"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.551 0.091 0.619