| Back to Multiple platform build/check report for BioC 3.16: simplified long |
|
This page was generated on 2023-04-12 11:06:01 -0400 (Wed, 12 Apr 2023).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 20.04.5 LTS) | x86_64 | 4.2.3 (2023-03-15) -- "Shortstop Beagle" | 4502 |
| palomino4 | Windows Server 2022 Datacenter | x64 | 4.2.3 (2023-03-15 ucrt) -- "Shortstop Beagle" | 4282 |
| lconway | macOS 12.5.1 Monterey | x86_64 | 4.2.3 (2023-03-15) -- "Shortstop Beagle" | 4310 |
| 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 232/2183 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.62.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 20.04.5 LTS) / x86_64 | OK | OK | OK |  | ||||||||
| palomino4 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.5.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| Package: BufferedMatrix |
| Version: 1.62.0 |
| 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_1.62.0.tar.gz |
| StartedAt: 2023-04-10 19:10:37 -0400 (Mon, 10 Apr 2023) |
| EndedAt: 2023-04-10 19:12:09 -0400 (Mon, 10 Apr 2023) |
| EllapsedTime: 92.1 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_1.62.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck’ * using R version 4.2.3 (2023-03-15) * 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 ‘1.62.0’ * 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-3.16-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-3.16-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 4.2.3 (2023-03-15) -- "Shortstop Beagle"
Copyright (C) 2023 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
0.321 0.205 1.903
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.2.3 (2023-03-15) -- "Shortstop Beagle"
Copyright (C) 2023 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-3.16-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 448605 24.0 969425 51.8 NA 624605 33.4
Vcells 811930 6.2 8388608 64.0 98304 1889187 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] "Mon Apr 10 19:11:05 2023"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Mon Apr 10 19:11:07 2023"
>
>
> 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: 0x60000254c000>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Mon Apr 10 19:11:25 2023"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Mon Apr 10 19:11:29 2023"
>
> ColMode(tmp2)
<pointer: 0x60000254c000>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 101.6631575 1.1514225 0.1720080 0.1268592
[2,] 1.0664085 -2.1076650 1.0710948 -0.1895638
[3,] 0.4308063 1.4534216 0.1370200 -3.2103057
[4,] -0.2196170 0.2281656 0.1743593 0.2192946
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 101.6631575 1.1514225 0.1720080 0.1268592
[2,] 1.0664085 2.1076650 1.0710948 0.1895638
[3,] 0.4308063 1.4534216 0.1370200 3.2103057
[4,] 0.2196170 0.2281656 0.1743593 0.2192946
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0828150 1.0730436 0.4147385 0.3561730
[2,] 1.0326706 1.4517799 1.0349371 0.4353892
[3,] 0.6563584 1.2055794 0.3701621 1.7917326
[4,] 0.4686332 0.4776668 0.4175636 0.4682890
>
> 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-3.16-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 227.49131 36.88186 29.31939 28.68859
[2,] 36.39311 41.62546 36.42047 29.54346
[3,] 31.99439 38.50922 28.83864 46.12763
[4,] 29.90595 30.00483 29.34999 29.90218
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000025200c0>
> exp(tmp5)
<pointer: 0x6000025200c0>
> log(tmp5,2)
<pointer: 0x6000025200c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 473.4934
> Min(tmp5)
[1] 52.37768
> mean(tmp5)
[1] 72.22258
> Sum(tmp5)
[1] 14444.52
> Var(tmp5)
[1] 893.381
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 93.74500 69.97967 69.25264 69.95783 69.26291 70.06179 71.65685 69.22325
[9] 69.61035 69.47549
> rowSums(tmp5)
[1] 1874.900 1399.593 1385.053 1399.157 1385.258 1401.236 1433.137 1384.465
[9] 1392.207 1389.510
> rowVars(tmp5)
[1] 8049.31620 93.31133 83.32622 83.91493 97.83352 79.15999
[7] 94.24336 90.28525 89.54206 49.41540
> rowSd(tmp5)
[1] 89.717981 9.659779 9.128320 9.160509 9.891083 8.897190 9.707902
[8] 9.501855 9.462667 7.029609
> rowMax(tmp5)
[1] 473.49335 86.63795 96.00862 86.15628 92.43497 86.53577 93.27954
[8] 84.14962 90.89071 80.90977
> rowMin(tmp5)
[1] 59.71154 54.46284 54.38572 54.81102 54.22158 57.45539 54.99172 52.37768
[9] 55.22932 57.32599
>
> colMeans(tmp5)
[1] 113.67686 73.68637 67.29105 71.50421 72.59195 65.37331 68.32404
[8] 70.92994 70.07107 70.52049 76.46878 68.03169 69.54460 67.04955
[15] 70.76779 69.41669 70.55840 71.87200 67.59905 69.17375
> colSums(tmp5)
[1] 1136.7686 736.8637 672.9105 715.0421 725.9195 653.7331 683.2404
[8] 709.2994 700.7107 705.2049 764.6878 680.3169 695.4460 670.4955
[15] 707.6779 694.1669 705.5840 718.7200 675.9905 691.7375
> colVars(tmp5)
[1] 16043.29993 127.52427 35.12796 127.39730 137.62068 61.95647
[7] 82.69131 76.52372 36.47981 116.76012 76.50454 70.73738
[13] 63.59281 68.95233 71.02021 69.67462 94.87691 82.60088
[19] 94.09140 71.81228
> colSd(tmp5)
[1] 126.662149 11.292664 5.926884 11.287041 11.731184 7.871243
[7] 9.093476 8.747784 6.039852 10.805560 8.746688 8.410552
[13] 7.974510 8.303754 8.427349 8.347132 9.740478 9.088503
[19] 9.700072 8.474213
> colMax(tmp5)
[1] 473.49335 86.63795 75.86261 96.00862 92.43497 78.14904 83.29457
[8] 86.15628 78.19470 93.27954 90.89071 81.32565 81.76614 80.90977
[15] 85.63677 80.42572 85.39621 83.49734 83.03205 84.22657
> colMin(tmp5)
[1] 62.24531 54.99172 60.02385 59.71154 56.16304 55.66778 58.12542 58.31029
[9] 62.10558 52.37768 65.24643 57.32599 59.97135 57.45539 54.22158 55.22932
[17] 54.81102 54.38572 54.46284 58.20944
>
>
> ### 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] 93.74500 NA 69.25264 69.95783 69.26291 70.06179 71.65685 69.22325
[9] 69.61035 69.47549
> rowSums(tmp5)
[1] 1874.900 NA 1385.053 1399.157 1385.258 1401.236 1433.137 1384.465
[9] 1392.207 1389.510
> rowVars(tmp5)
[1] 8049.31620 84.41506 83.32622 83.91493 97.83352 79.15999
[7] 94.24336 90.28525 89.54206 49.41540
> rowSd(tmp5)
[1] 89.717981 9.187767 9.128320 9.160509 9.891083 8.897190 9.707902
[8] 9.501855 9.462667 7.029609
> rowMax(tmp5)
[1] 473.49335 NA 96.00862 86.15628 92.43497 86.53577 93.27954
[8] 84.14962 90.89071 80.90977
> rowMin(tmp5)
[1] 59.71154 NA 54.38572 54.81102 54.22158 57.45539 54.99172 52.37768
[9] 55.22932 57.32599
>
> colMeans(tmp5)
[1] 113.67686 73.68637 67.29105 71.50421 72.59195 65.37331 68.32404
[8] 70.92994 70.07107 70.52049 76.46878 68.03169 69.54460 67.04955
[15] 70.76779 69.41669 70.55840 71.87200 NA 69.17375
> colSums(tmp5)
[1] 1136.7686 736.8637 672.9105 715.0421 725.9195 653.7331 683.2404
[8] 709.2994 700.7107 705.2049 764.6878 680.3169 695.4460 670.4955
[15] 707.6779 694.1669 705.5840 718.7200 NA 691.7375
> colVars(tmp5)
[1] 16043.29993 127.52427 35.12796 127.39730 137.62068 61.95647
[7] 82.69131 76.52372 36.47981 116.76012 76.50454 70.73738
[13] 63.59281 68.95233 71.02021 69.67462 94.87691 82.60088
[19] NA 71.81228
> colSd(tmp5)
[1] 126.662149 11.292664 5.926884 11.287041 11.731184 7.871243
[7] 9.093476 8.747784 6.039852 10.805560 8.746688 8.410552
[13] 7.974510 8.303754 8.427349 8.347132 9.740478 9.088503
[19] NA 8.474213
> colMax(tmp5)
[1] 473.49335 86.63795 75.86261 96.00862 92.43497 78.14904 83.29457
[8] 86.15628 78.19470 93.27954 90.89071 81.32565 81.76614 80.90977
[15] 85.63677 80.42572 85.39621 83.49734 NA 84.22657
> colMin(tmp5)
[1] 62.24531 54.99172 60.02385 59.71154 56.16304 55.66778 58.12542 58.31029
[9] 62.10558 52.37768 65.24643 57.32599 59.97135 57.45539 54.22158 55.22932
[17] 54.81102 54.38572 NA 58.20944
>
> Max(tmp5,na.rm=TRUE)
[1] 473.4934
> Min(tmp5,na.rm=TRUE)
[1] 52.37768
> mean(tmp5,na.rm=TRUE)
[1] 72.31182
> Sum(tmp5,na.rm=TRUE)
[1] 14390.05
> Var(tmp5,na.rm=TRUE)
[1] 896.292
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.74500 70.79634 69.25264 69.95783 69.26291 70.06179 71.65685 69.22325
[9] 69.61035 69.47549
> rowSums(tmp5,na.rm=TRUE)
[1] 1874.900 1345.130 1385.053 1399.157 1385.258 1401.236 1433.137 1384.465
[9] 1392.207 1389.510
> rowVars(tmp5,na.rm=TRUE)
[1] 8049.31620 84.41506 83.32622 83.91493 97.83352 79.15999
[7] 94.24336 90.28525 89.54206 49.41540
> rowSd(tmp5,na.rm=TRUE)
[1] 89.717981 9.187767 9.128320 9.160509 9.891083 8.897190 9.707902
[8] 9.501855 9.462667 7.029609
> rowMax(tmp5,na.rm=TRUE)
[1] 473.49335 86.63795 96.00862 86.15628 92.43497 86.53577 93.27954
[8] 84.14962 90.89071 80.90977
> rowMin(tmp5,na.rm=TRUE)
[1] 59.71154 57.95682 54.38572 54.81102 54.22158 57.45539 54.99172 52.37768
[9] 55.22932 57.32599
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.67686 73.68637 67.29105 71.50421 72.59195 65.37331 68.32404
[8] 70.92994 70.07107 70.52049 76.46878 68.03169 69.54460 67.04955
[15] 70.76779 69.41669 70.55840 71.87200 69.05863 69.17375
> colSums(tmp5,na.rm=TRUE)
[1] 1136.7686 736.8637 672.9105 715.0421 725.9195 653.7331 683.2404
[8] 709.2994 700.7107 705.2049 764.6878 680.3169 695.4460 670.4955
[15] 707.6779 694.1669 705.5840 718.7200 621.5276 691.7375
> colVars(tmp5,na.rm=TRUE)
[1] 16043.29993 127.52427 35.12796 127.39730 137.62068 61.95647
[7] 82.69131 76.52372 36.47981 116.76012 76.50454 70.73738
[13] 63.59281 68.95233 71.02021 69.67462 94.87691 82.60088
[19] 81.88614 71.81228
> colSd(tmp5,na.rm=TRUE)
[1] 126.662149 11.292664 5.926884 11.287041 11.731184 7.871243
[7] 9.093476 8.747784 6.039852 10.805560 8.746688 8.410552
[13] 7.974510 8.303754 8.427349 8.347132 9.740478 9.088503
[19] 9.049096 8.474213
> colMax(tmp5,na.rm=TRUE)
[1] 473.49335 86.63795 75.86261 96.00862 92.43497 78.14904 83.29457
[8] 86.15628 78.19470 93.27954 90.89071 81.32565 81.76614 80.90977
[15] 85.63677 80.42572 85.39621 83.49734 83.03205 84.22657
> colMin(tmp5,na.rm=TRUE)
[1] 62.24531 54.99172 60.02385 59.71154 56.16304 55.66778 58.12542 58.31029
[9] 62.10558 52.37768 65.24643 57.32599 59.97135 57.45539 54.22158 55.22932
[17] 54.81102 54.38572 58.01830 58.20944
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.74500 NaN 69.25264 69.95783 69.26291 70.06179 71.65685 69.22325
[9] 69.61035 69.47549
> rowSums(tmp5,na.rm=TRUE)
[1] 1874.900 0.000 1385.053 1399.157 1385.258 1401.236 1433.137 1384.465
[9] 1392.207 1389.510
> rowVars(tmp5,na.rm=TRUE)
[1] 8049.31620 NA 83.32622 83.91493 97.83352 79.15999
[7] 94.24336 90.28525 89.54206 49.41540
> rowSd(tmp5,na.rm=TRUE)
[1] 89.717981 NA 9.128320 9.160509 9.891083 8.897190 9.707902
[8] 9.501855 9.462667 7.029609
> rowMax(tmp5,na.rm=TRUE)
[1] 473.49335 NA 96.00862 86.15628 92.43497 86.53577 93.27954
[8] 84.14962 90.89071 80.90977
> rowMin(tmp5,na.rm=TRUE)
[1] 59.71154 NA 54.38572 54.81102 54.22158 57.45539 54.99172 52.37768
[9] 55.22932 57.32599
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 117.89124 72.24731 66.34512 72.61680 74.04584 66.15310 67.90665
[8] 71.39421 69.20672 71.45235 75.66659 69.15112 69.47945 66.66375
[15] 70.04226 68.71069 68.90975 72.88864 NaN 69.60561
> colSums(tmp5,na.rm=TRUE)
[1] 1061.0211 650.2258 597.1060 653.5512 666.4125 595.3779 611.1599
[8] 642.5479 622.8605 643.0711 680.9993 622.3601 625.3151 599.9738
[15] 630.3803 618.3962 620.1878 655.9977 0.0000 626.4505
> colVars(tmp5,na.rm=TRUE)
[1] 17848.90176 120.16711 29.45262 129.39590 131.04318 62.86018
[7] 91.06783 83.66428 32.63503 121.58617 78.82816 65.48192
[13] 71.49416 75.89695 73.97578 72.77657 76.15865 81.29845
[19] NA 78.69066
> colSd(tmp5,na.rm=TRUE)
[1] 133.599782 10.962076 5.427026 11.375232 11.447409 7.928441
[7] 9.542946 9.146818 5.712708 11.026612 8.878522 8.092090
[13] 8.455422 8.711885 8.600917 8.530918 8.726892 9.016565
[19] NA 8.870776
> colMax(tmp5,na.rm=TRUE)
[1] 473.49335 86.53577 75.86261 96.00862 92.43497 78.14904 83.29457
[8] 86.15628 78.19470 93.27954 90.89071 81.32565 81.76614 80.90977
[15] 85.63677 80.42572 81.62042 83.49734 -Inf 84.22657
> colMin(tmp5,na.rm=TRUE)
[1] 62.24531 54.99172 60.02385 59.71154 56.16304 55.66778 58.12542 58.31029
[9] 62.10558 52.37768 65.24643 57.32599 59.97135 57.45539 54.22158 55.22932
[17] 54.81102 54.38572 Inf 58.20944
>
>
>
>
> 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] 143.3553 342.4220 131.6664 277.9926 156.8183 247.9354 301.6599 214.3795
[9] 188.8959 305.9053
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 143.3553 342.4220 131.6664 277.9926 156.8183 247.9354 301.6599 214.3795
[9] 188.8959 305.9053
>
>
>
> 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] -5.684342e-14 1.705303e-13 -5.684342e-14 7.105427e-14 -5.684342e-14
[6] -1.705303e-13 -5.684342e-14 5.684342e-14 -7.105427e-14 1.136868e-13
[11] -4.973799e-14 0.000000e+00 -1.989520e-13 5.684342e-14 5.684342e-14
[16] -5.684342e-14 -4.263256e-14 -5.684342e-14 2.842171e-14 5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
4 11
8 2
7 12
3 6
9 15
6 5
5 16
7 14
9 12
9 6
6 5
10 19
2 8
10 16
9 15
9 11
6 9
5 4
5 2
8 5
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] 2.686031
> Min(tmp)
[1] -3.0612
> mean(tmp)
[1] 0.007732439
> Sum(tmp)
[1] 0.7732439
> Var(tmp)
[1] 1.101651
>
> rowMeans(tmp)
[1] 0.007732439
> rowSums(tmp)
[1] 0.7732439
> rowVars(tmp)
[1] 1.101651
> rowSd(tmp)
[1] 1.049596
> rowMax(tmp)
[1] 2.686031
> rowMin(tmp)
[1] -3.0612
>
> colMeans(tmp)
[1] 1.51296601 -1.55353175 1.41832885 0.65523449 0.62371321 0.16673383
[7] 0.30651835 -0.68339952 1.54070302 -2.20502635 0.47302164 -1.24792764
[13] -1.10842791 1.21327918 -1.53585066 -1.37544930 0.15868676 1.65908477
[19] 0.55408184 0.69527724 -1.23623057 -3.06119977 0.52678808 0.43653829
[25] -0.83670033 0.33492666 0.28615171 -0.52810654 1.07507117 -0.79974984
[31] 0.32373440 0.19653804 0.06147551 -0.15331669 -1.28671251 -0.04164491
[37] 0.59873980 -0.33584024 -0.43911739 -0.70020265 1.44571971 -1.27010206
[43] 0.21960901 -0.21727855 0.95448776 0.56869362 -0.06477602 -0.49151454
[49] 2.53978390 1.03544923 -0.41675850 -0.60716300 0.81302434 0.72694201
[55] -1.25192498 1.45335949 -0.01825764 -0.06934377 -0.54052316 2.68603124
[61] -0.33357628 0.29840997 1.41107617 -0.17118220 0.78411246 -2.82906556
[67] 0.65869385 -0.11210997 0.04401439 0.13283939 0.35978739 -2.33512263
[73] 0.53009098 -0.05056615 -0.71447282 0.73465285 -0.40326088 -0.48974865
[79] -0.23479031 0.30137490 1.18858804 -0.58301982 0.16569507 0.05602347
[85] 0.16423419 2.51986163 -0.15819183 -0.48295522 0.54006546 -0.10431560
[91] 0.55420064 -1.33198717 -0.83776286 -0.16700020 1.44337477 -1.54081445
[97] -1.40699119 1.02743481 -0.38795380 -0.65101533
> colSums(tmp)
[1] 1.51296601 -1.55353175 1.41832885 0.65523449 0.62371321 0.16673383
[7] 0.30651835 -0.68339952 1.54070302 -2.20502635 0.47302164 -1.24792764
[13] -1.10842791 1.21327918 -1.53585066 -1.37544930 0.15868676 1.65908477
[19] 0.55408184 0.69527724 -1.23623057 -3.06119977 0.52678808 0.43653829
[25] -0.83670033 0.33492666 0.28615171 -0.52810654 1.07507117 -0.79974984
[31] 0.32373440 0.19653804 0.06147551 -0.15331669 -1.28671251 -0.04164491
[37] 0.59873980 -0.33584024 -0.43911739 -0.70020265 1.44571971 -1.27010206
[43] 0.21960901 -0.21727855 0.95448776 0.56869362 -0.06477602 -0.49151454
[49] 2.53978390 1.03544923 -0.41675850 -0.60716300 0.81302434 0.72694201
[55] -1.25192498 1.45335949 -0.01825764 -0.06934377 -0.54052316 2.68603124
[61] -0.33357628 0.29840997 1.41107617 -0.17118220 0.78411246 -2.82906556
[67] 0.65869385 -0.11210997 0.04401439 0.13283939 0.35978739 -2.33512263
[73] 0.53009098 -0.05056615 -0.71447282 0.73465285 -0.40326088 -0.48974865
[79] -0.23479031 0.30137490 1.18858804 -0.58301982 0.16569507 0.05602347
[85] 0.16423419 2.51986163 -0.15819183 -0.48295522 0.54006546 -0.10431560
[91] 0.55420064 -1.33198717 -0.83776286 -0.16700020 1.44337477 -1.54081445
[97] -1.40699119 1.02743481 -0.38795380 -0.65101533
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] 1.51296601 -1.55353175 1.41832885 0.65523449 0.62371321 0.16673383
[7] 0.30651835 -0.68339952 1.54070302 -2.20502635 0.47302164 -1.24792764
[13] -1.10842791 1.21327918 -1.53585066 -1.37544930 0.15868676 1.65908477
[19] 0.55408184 0.69527724 -1.23623057 -3.06119977 0.52678808 0.43653829
[25] -0.83670033 0.33492666 0.28615171 -0.52810654 1.07507117 -0.79974984
[31] 0.32373440 0.19653804 0.06147551 -0.15331669 -1.28671251 -0.04164491
[37] 0.59873980 -0.33584024 -0.43911739 -0.70020265 1.44571971 -1.27010206
[43] 0.21960901 -0.21727855 0.95448776 0.56869362 -0.06477602 -0.49151454
[49] 2.53978390 1.03544923 -0.41675850 -0.60716300 0.81302434 0.72694201
[55] -1.25192498 1.45335949 -0.01825764 -0.06934377 -0.54052316 2.68603124
[61] -0.33357628 0.29840997 1.41107617 -0.17118220 0.78411246 -2.82906556
[67] 0.65869385 -0.11210997 0.04401439 0.13283939 0.35978739 -2.33512263
[73] 0.53009098 -0.05056615 -0.71447282 0.73465285 -0.40326088 -0.48974865
[79] -0.23479031 0.30137490 1.18858804 -0.58301982 0.16569507 0.05602347
[85] 0.16423419 2.51986163 -0.15819183 -0.48295522 0.54006546 -0.10431560
[91] 0.55420064 -1.33198717 -0.83776286 -0.16700020 1.44337477 -1.54081445
[97] -1.40699119 1.02743481 -0.38795380 -0.65101533
> colMin(tmp)
[1] 1.51296601 -1.55353175 1.41832885 0.65523449 0.62371321 0.16673383
[7] 0.30651835 -0.68339952 1.54070302 -2.20502635 0.47302164 -1.24792764
[13] -1.10842791 1.21327918 -1.53585066 -1.37544930 0.15868676 1.65908477
[19] 0.55408184 0.69527724 -1.23623057 -3.06119977 0.52678808 0.43653829
[25] -0.83670033 0.33492666 0.28615171 -0.52810654 1.07507117 -0.79974984
[31] 0.32373440 0.19653804 0.06147551 -0.15331669 -1.28671251 -0.04164491
[37] 0.59873980 -0.33584024 -0.43911739 -0.70020265 1.44571971 -1.27010206
[43] 0.21960901 -0.21727855 0.95448776 0.56869362 -0.06477602 -0.49151454
[49] 2.53978390 1.03544923 -0.41675850 -0.60716300 0.81302434 0.72694201
[55] -1.25192498 1.45335949 -0.01825764 -0.06934377 -0.54052316 2.68603124
[61] -0.33357628 0.29840997 1.41107617 -0.17118220 0.78411246 -2.82906556
[67] 0.65869385 -0.11210997 0.04401439 0.13283939 0.35978739 -2.33512263
[73] 0.53009098 -0.05056615 -0.71447282 0.73465285 -0.40326088 -0.48974865
[79] -0.23479031 0.30137490 1.18858804 -0.58301982 0.16569507 0.05602347
[85] 0.16423419 2.51986163 -0.15819183 -0.48295522 0.54006546 -0.10431560
[91] 0.55420064 -1.33198717 -0.83776286 -0.16700020 1.44337477 -1.54081445
[97] -1.40699119 1.02743481 -0.38795380 -0.65101533
> colMedians(tmp)
[1] 1.51296601 -1.55353175 1.41832885 0.65523449 0.62371321 0.16673383
[7] 0.30651835 -0.68339952 1.54070302 -2.20502635 0.47302164 -1.24792764
[13] -1.10842791 1.21327918 -1.53585066 -1.37544930 0.15868676 1.65908477
[19] 0.55408184 0.69527724 -1.23623057 -3.06119977 0.52678808 0.43653829
[25] -0.83670033 0.33492666 0.28615171 -0.52810654 1.07507117 -0.79974984
[31] 0.32373440 0.19653804 0.06147551 -0.15331669 -1.28671251 -0.04164491
[37] 0.59873980 -0.33584024 -0.43911739 -0.70020265 1.44571971 -1.27010206
[43] 0.21960901 -0.21727855 0.95448776 0.56869362 -0.06477602 -0.49151454
[49] 2.53978390 1.03544923 -0.41675850 -0.60716300 0.81302434 0.72694201
[55] -1.25192498 1.45335949 -0.01825764 -0.06934377 -0.54052316 2.68603124
[61] -0.33357628 0.29840997 1.41107617 -0.17118220 0.78411246 -2.82906556
[67] 0.65869385 -0.11210997 0.04401439 0.13283939 0.35978739 -2.33512263
[73] 0.53009098 -0.05056615 -0.71447282 0.73465285 -0.40326088 -0.48974865
[79] -0.23479031 0.30137490 1.18858804 -0.58301982 0.16569507 0.05602347
[85] 0.16423419 2.51986163 -0.15819183 -0.48295522 0.54006546 -0.10431560
[91] 0.55420064 -1.33198717 -0.83776286 -0.16700020 1.44337477 -1.54081445
[97] -1.40699119 1.02743481 -0.38795380 -0.65101533
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.512966 -1.553532 1.418329 0.6552345 0.6237132 0.1667338 0.3065183
[2,] 1.512966 -1.553532 1.418329 0.6552345 0.6237132 0.1667338 0.3065183
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.6833995 1.540703 -2.205026 0.4730216 -1.247928 -1.108428 1.213279
[2,] -0.6833995 1.540703 -2.205026 0.4730216 -1.247928 -1.108428 1.213279
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.535851 -1.375449 0.1586868 1.659085 0.5540818 0.6952772 -1.236231
[2,] -1.535851 -1.375449 0.1586868 1.659085 0.5540818 0.6952772 -1.236231
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -3.0612 0.5267881 0.4365383 -0.8367003 0.3349267 0.2861517 -0.5281065
[2,] -3.0612 0.5267881 0.4365383 -0.8367003 0.3349267 0.2861517 -0.5281065
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.075071 -0.7997498 0.3237344 0.196538 0.06147551 -0.1533167 -1.286713
[2,] 1.075071 -0.7997498 0.3237344 0.196538 0.06147551 -0.1533167 -1.286713
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.04164491 0.5987398 -0.3358402 -0.4391174 -0.7002027 1.44572 -1.270102
[2,] -0.04164491 0.5987398 -0.3358402 -0.4391174 -0.7002027 1.44572 -1.270102
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.219609 -0.2172785 0.9544878 0.5686936 -0.06477602 -0.4915145 2.539784
[2,] 0.219609 -0.2172785 0.9544878 0.5686936 -0.06477602 -0.4915145 2.539784
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 1.035449 -0.4167585 -0.607163 0.8130243 0.726942 -1.251925 1.453359
[2,] 1.035449 -0.4167585 -0.607163 0.8130243 0.726942 -1.251925 1.453359
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.01825764 -0.06934377 -0.5405232 2.686031 -0.3335763 0.29841 1.411076
[2,] -0.01825764 -0.06934377 -0.5405232 2.686031 -0.3335763 0.29841 1.411076
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.1711822 0.7841125 -2.829066 0.6586939 -0.11211 0.04401439 0.1328394
[2,] -0.1711822 0.7841125 -2.829066 0.6586939 -0.11211 0.04401439 0.1328394
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.3597874 -2.335123 0.530091 -0.05056615 -0.7144728 0.7346529 -0.4032609
[2,] 0.3597874 -2.335123 0.530091 -0.05056615 -0.7144728 0.7346529 -0.4032609
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.4897486 -0.2347903 0.3013749 1.188588 -0.5830198 0.1656951 0.05602347
[2,] -0.4897486 -0.2347903 0.3013749 1.188588 -0.5830198 0.1656951 0.05602347
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.1642342 2.519862 -0.1581918 -0.4829552 0.5400655 -0.1043156 0.5542006
[2,] 0.1642342 2.519862 -0.1581918 -0.4829552 0.5400655 -0.1043156 0.5542006
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.331987 -0.8377629 -0.1670002 1.443375 -1.540814 -1.406991 1.027435
[2,] -1.331987 -0.8377629 -0.1670002 1.443375 -1.540814 -1.406991 1.027435
[,99] [,100]
[1,] -0.3879538 -0.6510153
[2,] -0.3879538 -0.6510153
>
>
> Max(tmp2)
[1] 2.108765
> Min(tmp2)
[1] -1.722456
> mean(tmp2)
[1] 0.1139423
> Sum(tmp2)
[1] 11.39423
> Var(tmp2)
[1] 0.7917013
>
> rowMeans(tmp2)
[1] 0.56417504 -1.11001798 -0.22011769 1.19815403 0.76925509 0.31664380
[7] -1.13775834 0.57247662 -0.75924534 0.80039269 -0.57806719 -0.47078283
[13] 0.91682680 0.73212216 0.09328969 1.76756340 -1.37921321 0.59467389
[19] -0.50655313 -0.83206485 -0.49412450 -0.51950600 0.38142585 -0.42819686
[25] 1.23940206 0.39839167 -0.30356688 -1.47620422 -0.98008051 0.65300433
[31] 0.97242945 1.18451734 1.69787971 0.46652039 -1.09657486 -0.63725344
[37] -0.41664626 0.08932743 -1.24724612 0.35600972 1.34799594 0.60696068
[43] 0.67380273 0.46563954 -0.63530950 -0.40870322 0.33352973 -0.86109420
[49] -0.63756886 0.68714299 0.11539337 0.88393137 0.89841342 0.39661250
[55] 1.80723321 -0.27847362 0.38053527 0.43212294 0.89939735 1.13950503
[61] 1.33375016 -1.52240679 0.32985139 -0.78622196 0.22479328 2.10876466
[67] -1.49255932 0.20436080 -0.21805918 0.26827385 1.34774941 0.34071719
[73] -0.65609846 0.52110337 1.80100595 0.26206909 0.87108774 -1.44989675
[79] -1.59261388 0.72282326 -0.61155382 -0.63385947 0.50200374 -1.17473680
[85] -0.86706941 1.50666279 0.71061590 -0.06820746 -0.86489260 0.43068636
[91] 1.28713834 0.37346576 -0.50519177 -0.31926249 0.47194597 0.72945749
[97] -0.16638693 -1.72245562 -0.42257895 0.70162550
> rowSums(tmp2)
[1] 0.56417504 -1.11001798 -0.22011769 1.19815403 0.76925509 0.31664380
[7] -1.13775834 0.57247662 -0.75924534 0.80039269 -0.57806719 -0.47078283
[13] 0.91682680 0.73212216 0.09328969 1.76756340 -1.37921321 0.59467389
[19] -0.50655313 -0.83206485 -0.49412450 -0.51950600 0.38142585 -0.42819686
[25] 1.23940206 0.39839167 -0.30356688 -1.47620422 -0.98008051 0.65300433
[31] 0.97242945 1.18451734 1.69787971 0.46652039 -1.09657486 -0.63725344
[37] -0.41664626 0.08932743 -1.24724612 0.35600972 1.34799594 0.60696068
[43] 0.67380273 0.46563954 -0.63530950 -0.40870322 0.33352973 -0.86109420
[49] -0.63756886 0.68714299 0.11539337 0.88393137 0.89841342 0.39661250
[55] 1.80723321 -0.27847362 0.38053527 0.43212294 0.89939735 1.13950503
[61] 1.33375016 -1.52240679 0.32985139 -0.78622196 0.22479328 2.10876466
[67] -1.49255932 0.20436080 -0.21805918 0.26827385 1.34774941 0.34071719
[73] -0.65609846 0.52110337 1.80100595 0.26206909 0.87108774 -1.44989675
[79] -1.59261388 0.72282326 -0.61155382 -0.63385947 0.50200374 -1.17473680
[85] -0.86706941 1.50666279 0.71061590 -0.06820746 -0.86489260 0.43068636
[91] 1.28713834 0.37346576 -0.50519177 -0.31926249 0.47194597 0.72945749
[97] -0.16638693 -1.72245562 -0.42257895 0.70162550
> 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] 0.56417504 -1.11001798 -0.22011769 1.19815403 0.76925509 0.31664380
[7] -1.13775834 0.57247662 -0.75924534 0.80039269 -0.57806719 -0.47078283
[13] 0.91682680 0.73212216 0.09328969 1.76756340 -1.37921321 0.59467389
[19] -0.50655313 -0.83206485 -0.49412450 -0.51950600 0.38142585 -0.42819686
[25] 1.23940206 0.39839167 -0.30356688 -1.47620422 -0.98008051 0.65300433
[31] 0.97242945 1.18451734 1.69787971 0.46652039 -1.09657486 -0.63725344
[37] -0.41664626 0.08932743 -1.24724612 0.35600972 1.34799594 0.60696068
[43] 0.67380273 0.46563954 -0.63530950 -0.40870322 0.33352973 -0.86109420
[49] -0.63756886 0.68714299 0.11539337 0.88393137 0.89841342 0.39661250
[55] 1.80723321 -0.27847362 0.38053527 0.43212294 0.89939735 1.13950503
[61] 1.33375016 -1.52240679 0.32985139 -0.78622196 0.22479328 2.10876466
[67] -1.49255932 0.20436080 -0.21805918 0.26827385 1.34774941 0.34071719
[73] -0.65609846 0.52110337 1.80100595 0.26206909 0.87108774 -1.44989675
[79] -1.59261388 0.72282326 -0.61155382 -0.63385947 0.50200374 -1.17473680
[85] -0.86706941 1.50666279 0.71061590 -0.06820746 -0.86489260 0.43068636
[91] 1.28713834 0.37346576 -0.50519177 -0.31926249 0.47194597 0.72945749
[97] -0.16638693 -1.72245562 -0.42257895 0.70162550
> rowMin(tmp2)
[1] 0.56417504 -1.11001798 -0.22011769 1.19815403 0.76925509 0.31664380
[7] -1.13775834 0.57247662 -0.75924534 0.80039269 -0.57806719 -0.47078283
[13] 0.91682680 0.73212216 0.09328969 1.76756340 -1.37921321 0.59467389
[19] -0.50655313 -0.83206485 -0.49412450 -0.51950600 0.38142585 -0.42819686
[25] 1.23940206 0.39839167 -0.30356688 -1.47620422 -0.98008051 0.65300433
[31] 0.97242945 1.18451734 1.69787971 0.46652039 -1.09657486 -0.63725344
[37] -0.41664626 0.08932743 -1.24724612 0.35600972 1.34799594 0.60696068
[43] 0.67380273 0.46563954 -0.63530950 -0.40870322 0.33352973 -0.86109420
[49] -0.63756886 0.68714299 0.11539337 0.88393137 0.89841342 0.39661250
[55] 1.80723321 -0.27847362 0.38053527 0.43212294 0.89939735 1.13950503
[61] 1.33375016 -1.52240679 0.32985139 -0.78622196 0.22479328 2.10876466
[67] -1.49255932 0.20436080 -0.21805918 0.26827385 1.34774941 0.34071719
[73] -0.65609846 0.52110337 1.80100595 0.26206909 0.87108774 -1.44989675
[79] -1.59261388 0.72282326 -0.61155382 -0.63385947 0.50200374 -1.17473680
[85] -0.86706941 1.50666279 0.71061590 -0.06820746 -0.86489260 0.43068636
[91] 1.28713834 0.37346576 -0.50519177 -0.31926249 0.47194597 0.72945749
[97] -0.16638693 -1.72245562 -0.42257895 0.70162550
>
> colMeans(tmp2)
[1] 0.1139423
> colSums(tmp2)
[1] 11.39423
> colVars(tmp2)
[1] 0.7917013
> colSd(tmp2)
[1] 0.889776
> colMax(tmp2)
[1] 2.108765
> colMin(tmp2)
[1] -1.722456
> colMedians(tmp2)
[1] 0.3232476
> colRanges(tmp2)
[,1]
[1,] -1.722456
[2,] 2.108765
>
> 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] 3.14313764 -1.97717161 1.96091500 2.33269147 -1.30184907 -0.43136822
[7] -0.30554173 2.81317502 0.08762252 -0.98902090
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.7358265
[2,] -0.4215861
[3,] 0.3824011
[4,] 0.7899804
[5,] 1.3789948
>
> rowApply(tmp,sum)
[1] -0.47016730 -4.50166150 0.69317444 -0.69958127 3.50083558 1.03536887
[7] -0.01771426 3.14913301 1.06543261 1.57776995
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 10 6 8 1 4 9 1 8 10
[2,] 9 3 9 2 10 8 1 2 1 4
[3,] 4 1 7 10 8 7 10 6 5 2
[4,] 5 5 10 5 2 3 5 7 10 8
[5,] 1 9 8 6 9 5 2 5 2 6
[6,] 10 4 4 3 4 1 6 3 9 5
[7,] 2 7 1 7 5 9 3 8 4 9
[8,] 8 8 2 9 6 10 4 9 7 3
[9,] 7 6 5 1 3 6 7 4 6 7
[10,] 6 2 3 4 7 2 8 10 3 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.87098798 -1.69892554 -2.04443240 -0.00886948 -1.07338721 -0.11676654
[7] -3.46394078 -0.48782120 0.32368283 1.94483338 2.56318253 3.73479222
[13] -0.64974370 -2.04220376 -1.17313583 -1.86221870 -4.23386864 1.65124933
[19] 0.36601697 1.16815598
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.405296270
[2,] -0.794775709
[3,] -0.691631314
[4,] -0.005941072
[5,] 0.026656387
>
> rowApply(tmp,sum)
[1] -5.5847543 1.0954893 -10.0894644 3.7099976 0.8943431
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 11 9 7 3 2
[2,] 19 4 2 9 10
[3,] 2 16 19 2 7
[4,] 13 13 1 13 18
[5,] 5 8 12 17 8
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.005941072 1.0985437 -1.6827054 0.1325826 -1.3154324 0.1252776
[2,] 0.026656387 -0.7623232 0.4950316 0.2408958 -0.2934437 0.1691741
[3,] -0.691631314 -2.0350022 1.0104798 -2.0351392 -0.3299830 -0.2472353
[4,] -0.794775709 0.1126369 -1.3542663 0.4472109 1.2926258 0.3904564
[5,] -1.405296270 -0.1127807 -0.5129721 1.2055805 -0.4271539 -0.5544394
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.0724076 -0.2273948 -0.9015081 1.2043289 0.6353421 -0.4317101
[2,] 0.2815231 -0.3297068 -1.1169587 0.3233856 0.8652880 2.7212512
[3,] -0.8836231 -0.6419693 -1.5385556 -0.4028743 -0.1498128 0.7386445
[4,] -0.3963486 0.3899716 1.3210941 1.6490417 -0.4834940 1.1291435
[5,] -1.3930846 0.3212781 2.5596111 -0.8290486 1.6958592 -0.4225369
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.6466000 -1.3633974 -1.6816890 0.9077241 -2.54771730 0.73852530
[2,] 0.1365025 0.7255611 1.7225030 -1.7105535 -1.54752639 -0.50021802
[3,] -1.6130875 -0.4185657 1.2455137 -0.2678231 -0.44715245 -0.26357939
[4,] -0.2225249 -2.0786345 -0.6919686 0.5813902 0.21859811 1.61550061
[5,] 0.4027663 1.0928327 -1.7674949 -1.3729565 0.08992939 0.06102082
[,19] [,20]
[1,] -0.638419682 0.7946442
[2,] -0.554440738 0.2028879
[3,] 0.008228255 -1.1262963
[4,] 0.475353449 0.1089869
[5,] 1.075295683 1.1879333
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.16-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-3.16-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 649 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.16-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-3.16-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 -0.4480019 -0.3367536 1.313258 1.119392 0.8079616 -0.9364835 -0.4302494
col8 col9 col10 col11 col12 col13 col14
row1 0.7451777 -2.500764 0.7762266 1.397966 0.7702913 1.316764 -0.1620977
col15 col16 col17 col18 col19 col20
row1 -0.7422938 0.6711705 -0.8349211 1.474523 0.3980224 1.495844
> tmp[,"col10"]
col10
row1 0.77622656
row2 -0.08899477
row3 0.80998526
row4 -0.65946816
row5 0.46456685
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.4480019 -0.3367536 1.3132576 1.1193918 0.8079616 -0.9364835 -0.4302494
row5 -1.5643873 -0.3118782 -0.1824106 0.0941028 1.2468118 0.7828359 0.1778993
col8 col9 col10 col11 col12 col13 col14
row1 0.7451777 -2.5007638 0.7762266 1.3979664 0.7702913 1.316764 -0.1620977
row5 -0.2760611 0.4740478 0.4645669 -0.4494201 -0.0593841 1.665395 0.8952196
col15 col16 col17 col18 col19 col20
row1 -0.7422938 0.6711705 -0.8349211 1.4745231 0.3980224 1.495844
row5 0.5056406 -0.1568010 1.7464113 0.7200847 -0.4211994 1.476947
> tmp[,c("col6","col20")]
col6 col20
row1 -0.9364835 1.49584435
row2 0.2609351 -0.80505191
row3 0.3137735 -0.07249832
row4 1.4403446 -0.04248177
row5 0.7828359 1.47694709
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.9364835 1.495844
row5 0.7828359 1.476947
>
>
>
>
> 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 48.89566 50.10111 51.08203 49.74653 50.04597 104.0253 48.83968 49.89663
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.56106 51.75663 50.29562 50.91124 49.34776 50.41196 49.50692 52.06391
col17 col18 col19 col20
row1 49.73615 49.62215 50.26385 104.8013
> tmp[,"col10"]
col10
row1 51.75663
row2 28.29479
row3 29.98220
row4 30.52597
row5 49.95786
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.89566 50.10111 51.08203 49.74653 50.04597 104.0253 48.83968 49.89663
row5 50.44393 50.84507 50.35779 50.55732 49.50599 103.8441 49.32224 50.31865
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.56106 51.75663 50.29562 50.91124 49.34776 50.41196 49.50692 52.06391
row5 51.02158 49.95786 49.81255 47.73667 49.22212 49.13365 49.47704 49.23085
col17 col18 col19 col20
row1 49.73615 49.62215 50.26385 104.8013
row5 50.55837 49.95886 49.91479 104.3389
> tmp[,c("col6","col20")]
col6 col20
row1 104.02530 104.80126
row2 76.71049 77.02320
row3 75.14514 74.70135
row4 75.87180 75.48617
row5 103.84413 104.33887
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.0253 104.8013
row5 103.8441 104.3389
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.0253 104.8013
row5 103.8441 104.3389
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.4768548
[2,] 1.5424829
[3,] -0.1501905
[4,] -2.0488038
[5,] 0.9450060
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.3544945 0.4390444
[2,] -0.9716171 1.2080035
[3,] -0.2541014 -0.6020361
[4,] 1.4865233 0.1826354
[5,] 0.8293983 -1.2358400
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.1105284 -0.88599215
[2,] -0.7803532 -0.82427408
[3,] 0.2642252 0.79861083
[4,] 1.0801875 0.01102349
[5,] -0.4986302 -0.65651693
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.1105284
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.1105284
[2,] -0.7803532
>
>
>
> 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 1.0537751 0.3326406 1.9618075 0.2156218 -1.1003958 0.5365710 -0.5288265
row1 -0.4928938 -0.2841769 0.9087803 -0.1323216 0.5743496 0.7827555 -1.0673509
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -0.1255684 0.3479782 0.344461 0.9785095 -0.0643898 0.6935757 -0.8145702
row1 -1.0603023 0.3017823 1.302709 -1.0959329 0.3932523 -0.9944418 1.5938283
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.4221057 -1.1332971 0.5461115 0.8074415 -1.97861057 -0.9081509
row1 0.5423218 -0.4566722 -0.8022886 1.2481565 -0.01819649 0.7231448
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.9291353 1.01315 1.368872 0.3518444 0.0182941 -0.06523732 -2.40208
[,8] [,9] [,10]
row2 -1.375784 0.07314706 0.3090484
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -1.84968 -0.3522318 -0.09343504 -0.4870131 1.464061 -1.427377 -1.991882
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -2.348474 0.998809 0.8721311 -1.247786 -0.6711546 1.285721 0.07136395
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.9250405 0.9298066 -0.3636719 1.376575 -0.9001012 0.1214018
>
>
> 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: 0x600002568000>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM8cc641933548"
[2] "/Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM8cc6278f2b9a"
[3] "/Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM8cc628779fc0"
[4] "/Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM8cc645990b01"
[5] "/Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM8cc642a19259"
[6] "/Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM8cc67d8f333b"
[7] "/Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM8cc6446ca6e3"
[8] "/Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM8cc63940a42d"
[9] "/Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM8cc642daa3b8"
[10] "/Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM8cc62032a752"
[11] "/Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM8cc65d870901"
[12] "/Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM8cc64c60509f"
[13] "/Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM8cc6474d1de5"
[14] "/Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM8cc617e5c9f5"
[15] "/Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM8cc66f2e0014"
>
>
> ### 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: 0x600002558180>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600002558180>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600002558180>
> rowMedians(tmp)
[1] -0.090856092 -0.037407662 -0.079572311 -0.044560230 0.655897664
[6] -0.179731587 -0.060803813 -0.024633865 -0.050059821 0.076924570
[11] 0.049355572 0.310632519 -0.221235204 -0.233878179 0.164417169
[16] -0.068164796 0.651531275 0.310964887 -0.309291304 0.257947510
[21] -0.046052777 -0.419896667 0.064197363 0.114238663 -0.026617434
[26] 0.412669231 -0.070121149 0.369062220 0.059612172 -0.111910791
[31] -0.549116744 -0.171531097 0.108299023 -0.673025043 -0.205939807
[36] 0.202871778 -0.298631223 0.494632626 0.750035295 -0.035288776
[41] -0.153345421 -0.233057981 0.123293637 0.359624833 0.099114181
[46] -0.234434749 0.246810019 -0.056709146 -0.356434195 0.566707595
[51] -0.411424566 -0.245860099 0.140629853 0.028437138 -0.106085596
[56] -0.012281482 0.295087572 -0.092227950 0.423426208 0.400628863
[61] 0.164025351 0.274963780 0.101227187 0.052839702 0.603679815
[66] -0.099727544 -0.192401989 0.136199637 0.092162256 0.175089208
[71] -0.281109398 -0.181944517 -0.187596597 -0.043391912 -0.107901085
[76] 0.292274294 0.602956733 -0.211316424 0.122029377 -0.067440881
[81] 0.287127896 0.099692280 0.014682557 0.106742357 -0.730029076
[86] -0.557528096 0.045831721 -0.243227601 0.058085308 0.476168972
[91] -0.058957420 -0.476559895 -0.445294247 -0.750052304 0.086272482
[96] -0.212589500 -0.153979365 -0.651730707 0.136043495 0.109923787
[101] 0.180335959 0.024406728 0.055592451 -0.511693036 0.123653836
[106] -0.003878486 -0.394220881 0.644714056 -0.119749212 0.150011157
[111] -0.463490059 0.230558348 0.220512567 -0.156407758 0.134260061
[116] -0.495998049 -0.165850468 0.052732518 -0.161896343 0.329020832
[121] 0.183765628 0.059678279 0.015336884 0.007959637 0.027703606
[126] -0.462042039 0.281813750 -0.738029378 0.126338050 -0.048083383
[131] -0.112391840 0.081195894 0.064107707 0.105144069 -0.134279474
[136] -0.274684051 0.037865005 0.545413769 -0.097873312 0.212369703
[141] -0.427639701 -0.137184775 -0.061269334 -0.225975125 0.613584375
[146] -0.035513000 -0.507249556 0.447522361 -0.223107782 0.144542070
[151] 0.630380996 0.209601780 -0.340889413 0.308110285 0.030193442
[156] 0.471471996 -0.069959942 -0.373936516 -0.178740136 -0.030856251
[161] 0.188044949 0.245456492 0.278266129 -0.263728366 0.086702716
[166] 0.055495384 -0.184479998 -0.528530914 -0.025453389 0.112073052
[171] 0.008264349 0.363638095 -0.070117011 -0.306478415 -0.112619653
[176] -0.180013948 0.328912244 -0.039007609 -0.228490305 -0.406665256
[181] -0.560758015 -0.215509907 -0.177059407 -0.449837647 0.553394730
[186] 0.465880314 -0.028897923 -0.108037499 0.104482742 -0.284071417
[191] -0.093632465 -0.247229742 -0.639123911 -0.300467796 -0.345853443
[196] -0.784073104 0.153163461 0.053702452 -0.357345867 -0.326933013
[201] 0.253497413 0.713988137 0.449107679 0.105423925 -0.150615957
[206] -0.429266378 -0.081936409 0.352582521 -0.169105319 0.056608836
[211] -0.216031755 -0.413293027 0.703692738 -0.372542546 -0.285878810
[216] 0.040506390 0.077879604 0.249994247 -0.371187356 0.663335932
[221] 0.089083347 0.482237083 -0.266909888 0.215984359 -0.314364688
[226] 0.126852270 -0.197774452 -0.107726982 0.384976901 0.074802840
>
> proc.time()
user system elapsed
2.605 14.133 56.951
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.2.3 (2023-03-15) -- "Shortstop Beagle"
Copyright (C) 2023 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: 0x600002210000>
> .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: 0x600002210000>
> .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: 0x600002210000>
> .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: 0x600002210000>
> 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: 0x600002214000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002214000>
> .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: 0x600002214000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002214000>
> .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: 0x600002214000>
> 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: 0x60000226c000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000226c000>
> .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: 0x60000226c000>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x60000226c000>
> .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: 0x60000226c000>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x60000226c000>
> .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: 0x60000226c000>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x60000226c000>
> .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: 0x60000226c000>
> 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: 0x600002228180>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600002228180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002228180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002228180>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilea11543889f21" "BufferedMatrixFilea1154b552752"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilea11543889f21" "BufferedMatrixFilea1154b552752"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000223c2a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000223c2a0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x60000223c2a0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x60000223c2a0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x60000223c2a0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x60000223c2a0>
> .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: 0x6000022003c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000022003c0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000022003c0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000022003c0>
> 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: 0x60000223c3c0>
> .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: 0x60000223c3c0>
> rm(P)
>
> proc.time()
user system elapsed
0.304 0.145 1.216
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.2.3 (2023-03-15) -- "Shortstop Beagle"
Copyright (C) 2023 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
0.288 0.078 0.369