| Back to Multiple platform build/check report for BioC 3.14 |
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This page was generated on 2022-04-13 12:07:43 -0400 (Wed, 13 Apr 2022).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 20.04.4 LTS) | x86_64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4324 |
| tokay2 | Windows Server 2012 R2 Standard | x64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4077 |
| machv2 | macOS 10.14.6 Mojave | x86_64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4137 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
|
To the developers/maintainers of the BufferedMatrix package: - Please allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See How and When does the builder pull? When will my changes propagate? for more information. - Make sure to use the following settings in order to reproduce any error or warning you see on this page. |
| Package 223/2083 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.58.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 20.04.4 LTS) / x86_64 | OK | OK | OK |  | ||||||||
| tokay2 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||||
| machv2 | macOS 10.14.6 Mojave / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| Package: BufferedMatrix |
| Version: 1.58.0 |
| Command: /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_1.58.0.tar.gz |
| StartedAt: 2022-04-12 11:03:56 -0400 (Tue, 12 Apr 2022) |
| EndedAt: 2022-04-12 11:04:50 -0400 (Tue, 12 Apr 2022) |
| EllapsedTime: 54.0 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_1.58.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck’ * using R version 4.1.3 (2022-03-10) * 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 ‘1.58.0’ * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking whether package ‘BufferedMatrix’ can be installed ... 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-3.14-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-3.14-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/4.1/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/4.1/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 4.1.3 (2022-03-10) -- "One Push-Up"
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
0.482 0.132 0.588
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-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-3.14-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
Ncells 445257 23.8 947360 50.6 NA 649605 34.7
Vcells 803666 6.2 8388608 64.0 65536 2031734 15.6
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Tue Apr 12 11:04:24 2022"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Apr 12 11:04:25 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: 0x7fc1c1c02d10>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Tue Apr 12 11:04:29 2022"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Apr 12 11:04:30 2022"
>
> ColMode(tmp2)
<pointer: 0x7fc1c1c02d10>
>
>
>
> ### 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,] 98.9516361 0.09133552 1.5886706 -0.002047099
[2,] 0.9933596 1.80804188 -0.4775266 0.569538441
[3,] 0.8528708 0.74051322 0.1749133 -0.944447785
[4,] -0.3780421 0.72050174 -0.3222489 0.353792843
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.14-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,] 98.9516361 0.09133552 1.5886706 0.002047099
[2,] 0.9933596 1.80804188 0.4775266 0.569538441
[3,] 0.8528708 0.74051322 0.1749133 0.944447785
[4,] 0.3780421 0.72050174 0.3222489 0.353792843
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.14-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,] 9.9474437 0.3022177 1.2604248 0.04524488
[2,] 0.9966743 1.3446345 0.6910330 0.75467771
[3,] 0.9235100 0.8605308 0.4182264 0.97182703
[4,] 0.6148513 0.8488237 0.5676697 0.59480488
>
> 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-3.14-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,] 223.42607 28.11351 39.19292 25.45450
[2,] 35.96010 40.25439 32.38786 33.11632
[3,] 35.08797 34.34582 29.35718 35.66272
[4,] 31.52656 34.20874 30.99895 31.30184
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x7fc171ca2810>
> exp(tmp5)
<pointer: 0x7fc171ca2810>
> log(tmp5,2)
<pointer: 0x7fc171ca2810>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 465.0321
> Min(tmp5)
[1] 52.19815
> mean(tmp5)
[1] 72.47299
> Sum(tmp5)
[1] 14494.6
> Var(tmp5)
[1] 850.9076
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.25952 68.62475 72.34764 73.24501 70.11662 70.75467 69.76163 72.81366
[9] 66.34910 71.45730
> rowSums(tmp5)
[1] 1785.190 1372.495 1446.953 1464.900 1402.332 1415.093 1395.233 1456.273
[9] 1326.982 1429.146
> rowVars(tmp5)
[1] 7902.23806 64.52211 66.64624 42.26753 102.99552 102.19122
[7] 51.19126 84.34699 56.59893 68.91396
> rowSd(tmp5)
[1] 88.894533 8.032566 8.163715 6.501348 10.148671 10.108967 7.154807
[8] 9.184062 7.523226 8.301443
> rowMax(tmp5)
[1] 465.03210 83.78423 90.94939 82.48079 89.45321 93.41962 82.33372
[8] 89.47291 77.95739 84.93438
> rowMin(tmp5)
[1] 52.19815 56.95544 55.78363 59.59436 56.86478 55.24640 58.12762 58.94853
[9] 56.50679 54.76693
>
> colMeans(tmp5)
[1] 107.74011 69.64398 68.35068 64.28544 72.14626 71.06946 73.77838
[8] 74.03868 70.55333 71.91733 67.87565 73.62637 70.64209 70.85205
[15] 64.89295 73.38423 73.87276 69.59386 72.96275 68.23347
> colSums(tmp5)
[1] 1077.4011 696.4398 683.5068 642.8544 721.4626 710.6946 737.7838
[8] 740.3868 705.5333 719.1733 678.7565 736.2637 706.4209 708.5205
[15] 648.9295 733.8423 738.7276 695.9386 729.6275 682.3347
> colVars(tmp5)
[1] 15883.40658 58.85872 81.03309 48.20828 58.48433 72.43364
[7] 56.22506 73.38991 106.52976 34.12459 50.12222 42.45729
[13] 70.82433 47.26869 51.52702 47.46066 136.28579 61.72002
[19] 126.27792 84.29385
> colSd(tmp5)
[1] 126.029388 7.671944 9.001838 6.943218 7.647505 8.510795
[7] 7.498337 8.566791 10.321326 5.841626 7.079704 6.515926
[13] 8.415719 6.875223 7.178233 6.889170 11.674150 7.856209
[19] 11.237345 9.181168
> colMax(tmp5)
[1] 465.03210 83.78423 83.95283 74.22728 81.68665 82.06023 83.61275
[8] 90.94939 93.41962 82.24113 77.46585 79.91416 82.74547 80.14026
[15] 77.01876 84.14507 89.45321 75.43706 86.32711 80.06725
> colMin(tmp5)
[1] 56.44752 58.51459 59.52239 52.98020 58.97808 58.34090 60.58310 62.64036
[9] 57.38979 62.02807 56.95544 58.12667 59.47984 60.40716 54.76693 59.59436
[17] 57.10774 52.19815 55.78363 55.24640
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 89.25952 68.62475 72.34764 73.24501 70.11662 70.75467 69.76163 72.81366
[9] NA 71.45730
> rowSums(tmp5)
[1] 1785.190 1372.495 1446.953 1464.900 1402.332 1415.093 1395.233 1456.273
[9] NA 1429.146
> rowVars(tmp5)
[1] 7902.23806 64.52211 66.64624 42.26753 102.99552 102.19122
[7] 51.19126 84.34699 59.39556 68.91396
> rowSd(tmp5)
[1] 88.894533 8.032566 8.163715 6.501348 10.148671 10.108967 7.154807
[8] 9.184062 7.706851 8.301443
> rowMax(tmp5)
[1] 465.03210 83.78423 90.94939 82.48079 89.45321 93.41962 82.33372
[8] 89.47291 NA 84.93438
> rowMin(tmp5)
[1] 52.19815 56.95544 55.78363 59.59436 56.86478 55.24640 58.12762 58.94853
[9] NA 54.76693
>
> colMeans(tmp5)
[1] 107.74011 69.64398 68.35068 64.28544 72.14626 NA 73.77838
[8] 74.03868 70.55333 71.91733 67.87565 73.62637 70.64209 70.85205
[15] 64.89295 73.38423 73.87276 69.59386 72.96275 68.23347
> colSums(tmp5)
[1] 1077.4011 696.4398 683.5068 642.8544 721.4626 NA 737.7838
[8] 740.3868 705.5333 719.1733 678.7565 736.2637 706.4209 708.5205
[15] 648.9295 733.8423 738.7276 695.9386 729.6275 682.3347
> colVars(tmp5)
[1] 15883.40658 58.85872 81.03309 48.20828 58.48433 NA
[7] 56.22506 73.38991 106.52976 34.12459 50.12222 42.45729
[13] 70.82433 47.26869 51.52702 47.46066 136.28579 61.72002
[19] 126.27792 84.29385
> colSd(tmp5)
[1] 126.029388 7.671944 9.001838 6.943218 7.647505 NA
[7] 7.498337 8.566791 10.321326 5.841626 7.079704 6.515926
[13] 8.415719 6.875223 7.178233 6.889170 11.674150 7.856209
[19] 11.237345 9.181168
> colMax(tmp5)
[1] 465.03210 83.78423 83.95283 74.22728 81.68665 NA 83.61275
[8] 90.94939 93.41962 82.24113 77.46585 79.91416 82.74547 80.14026
[15] 77.01876 84.14507 89.45321 75.43706 86.32711 80.06725
> colMin(tmp5)
[1] 56.44752 58.51459 59.52239 52.98020 58.97808 NA 60.58310 62.64036
[9] 57.38979 62.02807 56.95544 58.12667 59.47984 60.40716 54.76693 59.59436
[17] 57.10774 52.19815 55.78363 55.24640
>
> Max(tmp5,na.rm=TRUE)
[1] 465.0321
> Min(tmp5,na.rm=TRUE)
[1] 52.19815
> mean(tmp5,na.rm=TRUE)
[1] 72.51602
> Sum(tmp5,na.rm=TRUE)
[1] 14430.69
> Var(tmp5,na.rm=TRUE)
[1] 854.833
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.25952 68.62475 72.34764 73.24501 70.11662 70.75467 69.76163 72.81366
[9] 66.47744 71.45730
> rowSums(tmp5,na.rm=TRUE)
[1] 1785.190 1372.495 1446.953 1464.900 1402.332 1415.093 1395.233 1456.273
[9] 1263.071 1429.146
> rowVars(tmp5,na.rm=TRUE)
[1] 7902.23806 64.52211 66.64624 42.26753 102.99552 102.19122
[7] 51.19126 84.34699 59.39556 68.91396
> rowSd(tmp5,na.rm=TRUE)
[1] 88.894533 8.032566 8.163715 6.501348 10.148671 10.108967 7.154807
[8] 9.184062 7.706851 8.301443
> rowMax(tmp5,na.rm=TRUE)
[1] 465.03210 83.78423 90.94939 82.48079 89.45321 93.41962 82.33372
[8] 89.47291 77.95739 84.93438
> rowMin(tmp5,na.rm=TRUE)
[1] 52.19815 56.95544 55.78363 59.59436 56.86478 55.24640 58.12762 58.94853
[9] 56.50679 54.76693
>
> colMeans(tmp5,na.rm=TRUE)
[1] 107.74011 69.64398 68.35068 64.28544 72.14626 71.86490 73.77838
[8] 74.03868 70.55333 71.91733 67.87565 73.62637 70.64209 70.85205
[15] 64.89295 73.38423 73.87276 69.59386 72.96275 68.23347
> colSums(tmp5,na.rm=TRUE)
[1] 1077.4011 696.4398 683.5068 642.8544 721.4626 646.7841 737.7838
[8] 740.3868 705.5333 719.1733 678.7565 736.2637 706.4209 708.5205
[15] 648.9295 733.8423 738.7276 695.9386 729.6275 682.3347
> colVars(tmp5,na.rm=TRUE)
[1] 15883.40658 58.85872 81.03309 48.20828 58.48433 74.36971
[7] 56.22506 73.38991 106.52976 34.12459 50.12222 42.45729
[13] 70.82433 47.26869 51.52702 47.46066 136.28579 61.72002
[19] 126.27792 84.29385
> colSd(tmp5,na.rm=TRUE)
[1] 126.029388 7.671944 9.001838 6.943218 7.647505 8.623787
[7] 7.498337 8.566791 10.321326 5.841626 7.079704 6.515926
[13] 8.415719 6.875223 7.178233 6.889170 11.674150 7.856209
[19] 11.237345 9.181168
> colMax(tmp5,na.rm=TRUE)
[1] 465.03210 83.78423 83.95283 74.22728 81.68665 82.06023 83.61275
[8] 90.94939 93.41962 82.24113 77.46585 79.91416 82.74547 80.14026
[15] 77.01876 84.14507 89.45321 75.43706 86.32711 80.06725
> colMin(tmp5,na.rm=TRUE)
[1] 56.44752 58.51459 59.52239 52.98020 58.97808 58.34090 60.58310 62.64036
[9] 57.38979 62.02807 56.95544 58.12667 59.47984 60.40716 54.76693 59.59436
[17] 57.10774 52.19815 55.78363 55.24640
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.25952 68.62475 72.34764 73.24501 70.11662 70.75467 69.76163 72.81366
[9] NaN 71.45730
> rowSums(tmp5,na.rm=TRUE)
[1] 1785.190 1372.495 1446.953 1464.900 1402.332 1415.093 1395.233 1456.273
[9] 0.000 1429.146
> rowVars(tmp5,na.rm=TRUE)
[1] 7902.23806 64.52211 66.64624 42.26753 102.99552 102.19122
[7] 51.19126 84.34699 NA 68.91396
> rowSd(tmp5,na.rm=TRUE)
[1] 88.894533 8.032566 8.163715 6.501348 10.148671 10.108967 7.154807
[8] 9.184062 NA 8.301443
> rowMax(tmp5,na.rm=TRUE)
[1] 465.03210 83.78423 90.94939 82.48079 89.45321 93.41962 82.33372
[8] 89.47291 NA 84.93438
> rowMin(tmp5,na.rm=TRUE)
[1] 52.19815 56.95544 55.78363 59.59436 56.86478 55.24640 58.12762 58.94853
[9] NA 54.76693
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.43270 70.77839 67.89656 65.04339 71.87745 NaN 73.31405
[8] 73.82400 70.66182 73.01613 68.94877 75.34856 71.88234 71.63261
[15] 63.54564 73.34652 74.84901 70.75751 73.56069 67.48743
> colSums(tmp5,na.rm=TRUE)
[1] 1020.8943 637.0055 611.0690 585.3905 646.8971 0.0000 659.8264
[8] 664.4160 635.9564 657.1452 620.5389 678.1371 646.9411 644.6935
[15] 571.9108 660.1187 673.6410 636.8176 662.0462 607.3868
> colVars(tmp5,na.rm=TRUE)
[1] 17504.26942 51.73843 88.84216 47.77130 64.98200 NA
[7] 60.82762 82.04516 119.71357 24.80720 43.43207 14.39768
[13] 62.37239 46.32294 37.54637 53.37725 142.59973 54.20155
[19] 138.04035 88.56912
> colSd(tmp5,na.rm=TRUE)
[1] 132.303701 7.192943 9.425612 6.911679 8.061142 NA
[7] 7.799206 9.057878 10.941370 4.980683 6.590301 3.794427
[13] 7.897619 6.806095 6.127509 7.305974 11.941513 7.362170
[19] 11.749058 9.411117
> colMax(tmp5,na.rm=TRUE)
[1] 465.03210 83.78423 83.95283 74.22728 81.68665 -Inf 83.61275
[8] 90.94939 93.41962 82.24113 77.46585 79.91416 82.74547 80.14026
[15] 72.54381 84.14507 89.45321 75.43706 86.32711 80.06725
> colMin(tmp5,na.rm=TRUE)
[1] 56.44752 58.51459 59.52239 52.98020 58.97808 Inf 60.58310 62.64036
[9] 57.38979 66.30470 56.95544 69.52142 60.16635 60.40716 54.76693 59.59436
[17] 57.10774 52.19815 55.78363 55.24640
>
>
>
>
> 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] 145.1159 320.4036 258.2122 247.9001 187.9449 262.5937 188.2797 252.4455
[9] 219.6882 137.5953
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 145.1159 320.4036 258.2122 247.9001 187.9449 262.5937 188.2797 252.4455
[9] 219.6882 137.5953
>
>
>
> 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 1.136868e-13 -2.273737e-13 -5.684342e-14 0.000000e+00
[6] -8.526513e-14 1.705303e-13 8.526513e-14 0.000000e+00 5.684342e-14
[11] 2.842171e-14 1.136868e-13 -1.421085e-13 -5.684342e-14 1.136868e-13
[16] -1.989520e-13 2.842171e-13 0.000000e+00 5.684342e-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)
+ }
5 5
9 13
5 11
7 17
9 8
10 16
4 11
7 15
2 20
2 6
3 17
8 19
4 15
8 6
9 5
2 19
2 3
8 1
9 1
6 17
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 1.763764
> Min(tmp)
[1] -2.53632
> mean(tmp)
[1] 0.04673834
> Sum(tmp)
[1] 4.673834
> Var(tmp)
[1] 0.6823057
>
> rowMeans(tmp)
[1] 0.04673834
> rowSums(tmp)
[1] 4.673834
> rowVars(tmp)
[1] 0.6823057
> rowSd(tmp)
[1] 0.826018
> rowMax(tmp)
[1] 1.763764
> rowMin(tmp)
[1] -2.53632
>
> colMeans(tmp)
[1] -0.56575049 0.21497543 -0.39723649 -0.51569372 -0.20855858 1.15789868
[7] -0.62010122 0.66184952 0.02710191 0.16210295 -0.48807256 -0.01927296
[13] 0.30615129 0.78645232 0.16759282 0.03847382 0.59268152 0.18948303
[19] 0.04989644 0.12524029 1.08836483 -0.76042201 0.97252004 0.47240810
[25] 0.03169489 -0.06183488 -0.08981465 0.25760654 -0.86027226 -0.48378766
[31] 0.27142912 0.53692436 0.59671929 -0.96976385 -0.75329005 -1.02172536
[37] -0.19142141 -1.26143596 0.24138419 0.22174744 0.03011850 -0.15345524
[43] -0.40038098 0.86575194 0.32300368 0.13484433 -0.11108681 0.05813013
[49] 1.76376434 0.17332511 0.23891343 0.09564053 -0.98213498 -0.17434155
[55] -1.26923668 -1.27425112 -0.93670078 0.60086588 0.17769964 -2.53631975
[61] -1.58236669 1.10262169 1.17608093 1.18701131 1.20863271 1.44658848
[67] 1.55842418 -0.69560496 0.40966983 0.49190413 0.99239417 -0.28350331
[73] -0.90789099 -0.95123779 0.96078375 -1.62437928 1.09564040 0.47625185
[79] -0.53755651 0.08591837 -0.41648399 -0.83414147 1.18081482 -0.34493944
[85] 0.82009229 -0.40783779 -0.79664730 0.28089025 -0.43628114 0.22062841
[91] 1.01156966 0.82903411 1.57770296 0.92097115 0.81786691 1.28014155
[97] -1.62286400 -1.15883683 -0.93599865 0.55237632
> colSums(tmp)
[1] -0.56575049 0.21497543 -0.39723649 -0.51569372 -0.20855858 1.15789868
[7] -0.62010122 0.66184952 0.02710191 0.16210295 -0.48807256 -0.01927296
[13] 0.30615129 0.78645232 0.16759282 0.03847382 0.59268152 0.18948303
[19] 0.04989644 0.12524029 1.08836483 -0.76042201 0.97252004 0.47240810
[25] 0.03169489 -0.06183488 -0.08981465 0.25760654 -0.86027226 -0.48378766
[31] 0.27142912 0.53692436 0.59671929 -0.96976385 -0.75329005 -1.02172536
[37] -0.19142141 -1.26143596 0.24138419 0.22174744 0.03011850 -0.15345524
[43] -0.40038098 0.86575194 0.32300368 0.13484433 -0.11108681 0.05813013
[49] 1.76376434 0.17332511 0.23891343 0.09564053 -0.98213498 -0.17434155
[55] -1.26923668 -1.27425112 -0.93670078 0.60086588 0.17769964 -2.53631975
[61] -1.58236669 1.10262169 1.17608093 1.18701131 1.20863271 1.44658848
[67] 1.55842418 -0.69560496 0.40966983 0.49190413 0.99239417 -0.28350331
[73] -0.90789099 -0.95123779 0.96078375 -1.62437928 1.09564040 0.47625185
[79] -0.53755651 0.08591837 -0.41648399 -0.83414147 1.18081482 -0.34493944
[85] 0.82009229 -0.40783779 -0.79664730 0.28089025 -0.43628114 0.22062841
[91] 1.01156966 0.82903411 1.57770296 0.92097115 0.81786691 1.28014155
[97] -1.62286400 -1.15883683 -0.93599865 0.55237632
> 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] -0.56575049 0.21497543 -0.39723649 -0.51569372 -0.20855858 1.15789868
[7] -0.62010122 0.66184952 0.02710191 0.16210295 -0.48807256 -0.01927296
[13] 0.30615129 0.78645232 0.16759282 0.03847382 0.59268152 0.18948303
[19] 0.04989644 0.12524029 1.08836483 -0.76042201 0.97252004 0.47240810
[25] 0.03169489 -0.06183488 -0.08981465 0.25760654 -0.86027226 -0.48378766
[31] 0.27142912 0.53692436 0.59671929 -0.96976385 -0.75329005 -1.02172536
[37] -0.19142141 -1.26143596 0.24138419 0.22174744 0.03011850 -0.15345524
[43] -0.40038098 0.86575194 0.32300368 0.13484433 -0.11108681 0.05813013
[49] 1.76376434 0.17332511 0.23891343 0.09564053 -0.98213498 -0.17434155
[55] -1.26923668 -1.27425112 -0.93670078 0.60086588 0.17769964 -2.53631975
[61] -1.58236669 1.10262169 1.17608093 1.18701131 1.20863271 1.44658848
[67] 1.55842418 -0.69560496 0.40966983 0.49190413 0.99239417 -0.28350331
[73] -0.90789099 -0.95123779 0.96078375 -1.62437928 1.09564040 0.47625185
[79] -0.53755651 0.08591837 -0.41648399 -0.83414147 1.18081482 -0.34493944
[85] 0.82009229 -0.40783779 -0.79664730 0.28089025 -0.43628114 0.22062841
[91] 1.01156966 0.82903411 1.57770296 0.92097115 0.81786691 1.28014155
[97] -1.62286400 -1.15883683 -0.93599865 0.55237632
> colMin(tmp)
[1] -0.56575049 0.21497543 -0.39723649 -0.51569372 -0.20855858 1.15789868
[7] -0.62010122 0.66184952 0.02710191 0.16210295 -0.48807256 -0.01927296
[13] 0.30615129 0.78645232 0.16759282 0.03847382 0.59268152 0.18948303
[19] 0.04989644 0.12524029 1.08836483 -0.76042201 0.97252004 0.47240810
[25] 0.03169489 -0.06183488 -0.08981465 0.25760654 -0.86027226 -0.48378766
[31] 0.27142912 0.53692436 0.59671929 -0.96976385 -0.75329005 -1.02172536
[37] -0.19142141 -1.26143596 0.24138419 0.22174744 0.03011850 -0.15345524
[43] -0.40038098 0.86575194 0.32300368 0.13484433 -0.11108681 0.05813013
[49] 1.76376434 0.17332511 0.23891343 0.09564053 -0.98213498 -0.17434155
[55] -1.26923668 -1.27425112 -0.93670078 0.60086588 0.17769964 -2.53631975
[61] -1.58236669 1.10262169 1.17608093 1.18701131 1.20863271 1.44658848
[67] 1.55842418 -0.69560496 0.40966983 0.49190413 0.99239417 -0.28350331
[73] -0.90789099 -0.95123779 0.96078375 -1.62437928 1.09564040 0.47625185
[79] -0.53755651 0.08591837 -0.41648399 -0.83414147 1.18081482 -0.34493944
[85] 0.82009229 -0.40783779 -0.79664730 0.28089025 -0.43628114 0.22062841
[91] 1.01156966 0.82903411 1.57770296 0.92097115 0.81786691 1.28014155
[97] -1.62286400 -1.15883683 -0.93599865 0.55237632
> colMedians(tmp)
[1] -0.56575049 0.21497543 -0.39723649 -0.51569372 -0.20855858 1.15789868
[7] -0.62010122 0.66184952 0.02710191 0.16210295 -0.48807256 -0.01927296
[13] 0.30615129 0.78645232 0.16759282 0.03847382 0.59268152 0.18948303
[19] 0.04989644 0.12524029 1.08836483 -0.76042201 0.97252004 0.47240810
[25] 0.03169489 -0.06183488 -0.08981465 0.25760654 -0.86027226 -0.48378766
[31] 0.27142912 0.53692436 0.59671929 -0.96976385 -0.75329005 -1.02172536
[37] -0.19142141 -1.26143596 0.24138419 0.22174744 0.03011850 -0.15345524
[43] -0.40038098 0.86575194 0.32300368 0.13484433 -0.11108681 0.05813013
[49] 1.76376434 0.17332511 0.23891343 0.09564053 -0.98213498 -0.17434155
[55] -1.26923668 -1.27425112 -0.93670078 0.60086588 0.17769964 -2.53631975
[61] -1.58236669 1.10262169 1.17608093 1.18701131 1.20863271 1.44658848
[67] 1.55842418 -0.69560496 0.40966983 0.49190413 0.99239417 -0.28350331
[73] -0.90789099 -0.95123779 0.96078375 -1.62437928 1.09564040 0.47625185
[79] -0.53755651 0.08591837 -0.41648399 -0.83414147 1.18081482 -0.34493944
[85] 0.82009229 -0.40783779 -0.79664730 0.28089025 -0.43628114 0.22062841
[91] 1.01156966 0.82903411 1.57770296 0.92097115 0.81786691 1.28014155
[97] -1.62286400 -1.15883683 -0.93599865 0.55237632
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.5657505 0.2149754 -0.3972365 -0.5156937 -0.2085586 1.157899 -0.6201012
[2,] -0.5657505 0.2149754 -0.3972365 -0.5156937 -0.2085586 1.157899 -0.6201012
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.6618495 0.02710191 0.1621029 -0.4880726 -0.01927296 0.3061513 0.7864523
[2,] 0.6618495 0.02710191 0.1621029 -0.4880726 -0.01927296 0.3061513 0.7864523
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.1675928 0.03847382 0.5926815 0.189483 0.04989644 0.1252403 1.088365
[2,] 0.1675928 0.03847382 0.5926815 0.189483 0.04989644 0.1252403 1.088365
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.760422 0.97252 0.4724081 0.03169489 -0.06183488 -0.08981465 0.2576065
[2,] -0.760422 0.97252 0.4724081 0.03169489 -0.06183488 -0.08981465 0.2576065
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.8602723 -0.4837877 0.2714291 0.5369244 0.5967193 -0.9697638 -0.75329
[2,] -0.8602723 -0.4837877 0.2714291 0.5369244 0.5967193 -0.9697638 -0.75329
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.021725 -0.1914214 -1.261436 0.2413842 0.2217474 0.0301185 -0.1534552
[2,] -1.021725 -0.1914214 -1.261436 0.2413842 0.2217474 0.0301185 -0.1534552
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.400381 0.8657519 0.3230037 0.1348443 -0.1110868 0.05813013 1.763764
[2,] -0.400381 0.8657519 0.3230037 0.1348443 -0.1110868 0.05813013 1.763764
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.1733251 0.2389134 0.09564053 -0.982135 -0.1743416 -1.269237 -1.274251
[2,] 0.1733251 0.2389134 0.09564053 -0.982135 -0.1743416 -1.269237 -1.274251
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.9367008 0.6008659 0.1776996 -2.53632 -1.582367 1.102622 1.176081
[2,] -0.9367008 0.6008659 0.1776996 -2.53632 -1.582367 1.102622 1.176081
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 1.187011 1.208633 1.446588 1.558424 -0.695605 0.4096698 0.4919041
[2,] 1.187011 1.208633 1.446588 1.558424 -0.695605 0.4096698 0.4919041
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.9923942 -0.2835033 -0.907891 -0.9512378 0.9607838 -1.624379 1.09564
[2,] 0.9923942 -0.2835033 -0.907891 -0.9512378 0.9607838 -1.624379 1.09564
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.4762519 -0.5375565 0.08591837 -0.416484 -0.8341415 1.180815 -0.3449394
[2,] 0.4762519 -0.5375565 0.08591837 -0.416484 -0.8341415 1.180815 -0.3449394
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.8200923 -0.4078378 -0.7966473 0.2808903 -0.4362811 0.2206284 1.01157
[2,] 0.8200923 -0.4078378 -0.7966473 0.2808903 -0.4362811 0.2206284 1.01157
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.8290341 1.577703 0.9209711 0.8178669 1.280142 -1.622864 -1.158837
[2,] 0.8290341 1.577703 0.9209711 0.8178669 1.280142 -1.622864 -1.158837
[,99] [,100]
[1,] -0.9359987 0.5523763
[2,] -0.9359987 0.5523763
>
>
> Max(tmp2)
[1] 3.035908
> Min(tmp2)
[1] -2.519423
> mean(tmp2)
[1] 0.2148995
> Sum(tmp2)
[1] 21.48995
> Var(tmp2)
[1] 1.039998
>
> rowMeans(tmp2)
[1] 1.541407588 0.844360851 -0.903417269 0.605168726 -1.093338228
[6] 2.138552045 0.007721516 0.933447815 -0.868135521 -1.102066746
[11] -0.305139027 0.842848359 -0.110883082 0.073341687 -1.137633830
[16] 1.414738928 0.893780707 -0.291534660 0.797452801 -0.318037671
[21] 0.154087463 -0.030765850 -1.330028376 1.987187365 1.547608148
[26] -1.073976471 1.158392161 0.278483506 -0.008651713 0.927170037
[31] 2.013841125 -1.608638500 2.025633683 -0.885362787 -0.467080060
[36] -0.832248470 0.785442076 0.866041010 0.748740223 -0.319654853
[41] 1.163537277 0.647859511 0.435085526 -1.860943088 -0.872637493
[46] -0.595367004 0.905898628 0.292719856 1.049820400 -0.594595630
[51] 0.664215460 0.601158461 -2.519422838 -0.885066196 0.651639071
[56] 0.434930300 -0.617488483 1.308775470 1.614716673 0.267177288
[61] 3.035908057 1.162572782 -0.544934430 -1.340464280 0.627331210
[66] -1.074616371 -0.054685684 2.119208081 0.600646770 0.997644675
[71] -0.020304479 -0.336799966 0.437715562 0.378440682 0.838219784
[76] 0.430067661 0.466946842 1.372608376 -0.753459853 0.285184597
[81] -0.012285451 0.131493571 1.762414643 0.082335852 -1.693486432
[86] 0.137594536 0.318965298 0.110275625 1.696060940 -0.678994908
[91] -0.922954919 -0.667896336 0.514918891 1.521234371 0.845406181
[96] -0.618977490 -0.664989817 0.410936157 -1.206231879 -0.193963955
> rowSums(tmp2)
[1] 1.541407588 0.844360851 -0.903417269 0.605168726 -1.093338228
[6] 2.138552045 0.007721516 0.933447815 -0.868135521 -1.102066746
[11] -0.305139027 0.842848359 -0.110883082 0.073341687 -1.137633830
[16] 1.414738928 0.893780707 -0.291534660 0.797452801 -0.318037671
[21] 0.154087463 -0.030765850 -1.330028376 1.987187365 1.547608148
[26] -1.073976471 1.158392161 0.278483506 -0.008651713 0.927170037
[31] 2.013841125 -1.608638500 2.025633683 -0.885362787 -0.467080060
[36] -0.832248470 0.785442076 0.866041010 0.748740223 -0.319654853
[41] 1.163537277 0.647859511 0.435085526 -1.860943088 -0.872637493
[46] -0.595367004 0.905898628 0.292719856 1.049820400 -0.594595630
[51] 0.664215460 0.601158461 -2.519422838 -0.885066196 0.651639071
[56] 0.434930300 -0.617488483 1.308775470 1.614716673 0.267177288
[61] 3.035908057 1.162572782 -0.544934430 -1.340464280 0.627331210
[66] -1.074616371 -0.054685684 2.119208081 0.600646770 0.997644675
[71] -0.020304479 -0.336799966 0.437715562 0.378440682 0.838219784
[76] 0.430067661 0.466946842 1.372608376 -0.753459853 0.285184597
[81] -0.012285451 0.131493571 1.762414643 0.082335852 -1.693486432
[86] 0.137594536 0.318965298 0.110275625 1.696060940 -0.678994908
[91] -0.922954919 -0.667896336 0.514918891 1.521234371 0.845406181
[96] -0.618977490 -0.664989817 0.410936157 -1.206231879 -0.193963955
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 1.541407588 0.844360851 -0.903417269 0.605168726 -1.093338228
[6] 2.138552045 0.007721516 0.933447815 -0.868135521 -1.102066746
[11] -0.305139027 0.842848359 -0.110883082 0.073341687 -1.137633830
[16] 1.414738928 0.893780707 -0.291534660 0.797452801 -0.318037671
[21] 0.154087463 -0.030765850 -1.330028376 1.987187365 1.547608148
[26] -1.073976471 1.158392161 0.278483506 -0.008651713 0.927170037
[31] 2.013841125 -1.608638500 2.025633683 -0.885362787 -0.467080060
[36] -0.832248470 0.785442076 0.866041010 0.748740223 -0.319654853
[41] 1.163537277 0.647859511 0.435085526 -1.860943088 -0.872637493
[46] -0.595367004 0.905898628 0.292719856 1.049820400 -0.594595630
[51] 0.664215460 0.601158461 -2.519422838 -0.885066196 0.651639071
[56] 0.434930300 -0.617488483 1.308775470 1.614716673 0.267177288
[61] 3.035908057 1.162572782 -0.544934430 -1.340464280 0.627331210
[66] -1.074616371 -0.054685684 2.119208081 0.600646770 0.997644675
[71] -0.020304479 -0.336799966 0.437715562 0.378440682 0.838219784
[76] 0.430067661 0.466946842 1.372608376 -0.753459853 0.285184597
[81] -0.012285451 0.131493571 1.762414643 0.082335852 -1.693486432
[86] 0.137594536 0.318965298 0.110275625 1.696060940 -0.678994908
[91] -0.922954919 -0.667896336 0.514918891 1.521234371 0.845406181
[96] -0.618977490 -0.664989817 0.410936157 -1.206231879 -0.193963955
> rowMin(tmp2)
[1] 1.541407588 0.844360851 -0.903417269 0.605168726 -1.093338228
[6] 2.138552045 0.007721516 0.933447815 -0.868135521 -1.102066746
[11] -0.305139027 0.842848359 -0.110883082 0.073341687 -1.137633830
[16] 1.414738928 0.893780707 -0.291534660 0.797452801 -0.318037671
[21] 0.154087463 -0.030765850 -1.330028376 1.987187365 1.547608148
[26] -1.073976471 1.158392161 0.278483506 -0.008651713 0.927170037
[31] 2.013841125 -1.608638500 2.025633683 -0.885362787 -0.467080060
[36] -0.832248470 0.785442076 0.866041010 0.748740223 -0.319654853
[41] 1.163537277 0.647859511 0.435085526 -1.860943088 -0.872637493
[46] -0.595367004 0.905898628 0.292719856 1.049820400 -0.594595630
[51] 0.664215460 0.601158461 -2.519422838 -0.885066196 0.651639071
[56] 0.434930300 -0.617488483 1.308775470 1.614716673 0.267177288
[61] 3.035908057 1.162572782 -0.544934430 -1.340464280 0.627331210
[66] -1.074616371 -0.054685684 2.119208081 0.600646770 0.997644675
[71] -0.020304479 -0.336799966 0.437715562 0.378440682 0.838219784
[76] 0.430067661 0.466946842 1.372608376 -0.753459853 0.285184597
[81] -0.012285451 0.131493571 1.762414643 0.082335852 -1.693486432
[86] 0.137594536 0.318965298 0.110275625 1.696060940 -0.678994908
[91] -0.922954919 -0.667896336 0.514918891 1.521234371 0.845406181
[96] -0.618977490 -0.664989817 0.410936157 -1.206231879 -0.193963955
>
> colMeans(tmp2)
[1] 0.2148995
> colSums(tmp2)
[1] 21.48995
> colVars(tmp2)
[1] 1.039998
> colSd(tmp2)
[1] 1.019803
> colMax(tmp2)
[1] 3.035908
> colMin(tmp2)
[1] -2.519423
> colMedians(tmp2)
[1] 0.2818341
> colRanges(tmp2)
[,1]
[1,] -2.519423
[2,] 3.035908
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.9740634 0.1334229 -1.6669841 4.7083088 -0.9995599 -1.1131938
[7] -2.9382339 2.2159026 -2.3034038 4.5748742
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.16744718
[2,] 0.07691742
[3,] 0.37819142
[4,] 0.71083610
[5,] 1.38051786
>
> rowApply(tmp,sum)
[1] 1.5927830 3.2537205 0.2758084 -0.7852874 -0.4832212 2.0584503
[7] -2.9212614 -2.5122618 5.3433140 -0.2368481
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 7 9 9 7 7 1 3 5 6
[2,] 6 1 4 2 6 9 9 9 6 9
[3,] 2 6 5 10 3 8 3 5 1 8
[4,] 7 8 8 4 9 10 8 8 8 2
[5,] 8 4 6 3 1 1 10 7 2 4
[6,] 1 3 10 5 8 6 2 1 3 7
[7,] 3 5 1 7 5 4 6 4 7 1
[8,] 10 10 3 6 4 2 7 2 4 10
[9,] 4 2 2 8 2 3 4 6 9 5
[10,] 5 9 7 1 10 5 5 10 10 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.7756454 -0.9840921 1.4253538 0.4485482 -2.9414031 -1.5957047
[7] 2.3489096 -0.5892233 -1.2502611 -0.4454090 1.4888568 -2.3793113
[13] -1.9484507 0.5612413 0.8777669 1.7108042 -1.1036025 0.7983666
[19] -3.6287718 0.2673724
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.49528580
[2,] -0.99223566
[3,] -0.80149518
[4,] 0.04820434
[5,] 1.46516690
>
> rowApply(tmp,sum)
[1] -2.512066 8.674001 -6.370807 -5.089833 -4.415950
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 12 18 6 5 1
[2,] 17 5 18 2 10
[3,] 5 16 12 12 18
[4,] 13 8 19 3 13
[5,] 1 15 9 18 8
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.04820434 0.9344498 -0.64704605 0.28000848 -3.8759175 0.76453219
[2,] 1.46516690 -0.2959844 1.35863103 0.04833819 1.1715444 0.35364850
[3,] -0.99223566 0.9509719 -0.38042303 1.04639831 -0.7003452 -0.83020971
[4,] -0.80149518 -2.3771531 -0.07542999 -1.04126518 0.8165415 -0.06368697
[5,] -2.49528580 -0.1963762 1.16962181 0.11506844 -0.3532264 -1.81998873
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.6894595 -0.9291353 1.3044736 -1.3942855 -0.07527108 1.1437787
[2,] 0.9956407 0.7239465 1.3810033 1.5416653 0.60622246 -0.5324338
[3,] -1.7475169 -1.3878316 -1.2734319 0.5859429 -0.01555299 -0.9552995
[4,] 0.6341268 -0.7126616 -2.5597162 -0.1736787 1.62575109 -0.6788568
[5,] 1.7771996 1.7164587 -0.1025899 -1.0050530 -0.65229272 -1.3564998
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.58659496 1.3075246 -0.2883151 -0.3761767 0.86488580 -0.41159355
[2,] -1.36322737 -0.7071754 0.4912936 0.7505861 0.02798167 -0.05560417
[3,] -1.20188678 0.6153651 -0.4100710 1.7888591 -0.46201406 0.62258212
[4,] 1.29046634 -0.9189947 0.6683377 -0.2053425 -0.40595677 -0.04755651
[5,] -0.08720797 0.2645217 0.4165217 -0.2471219 -1.12849917 0.69053871
[,19] [,20]
[1,] -0.8327667 -0.4322810
[2,] -1.1291436 1.8419011
[3,] -1.5120715 -0.1120364
[4,] -0.6580257 0.5947631
[5,] 0.5032357 -1.6249744
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 650 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.14-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-3.14-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 1.372242 0.321757 1.319175 1.483656 -0.5855439 0.1878883 -1.105076
col8 col9 col10 col11 col12 col13 col14
row1 -0.343128 0.9357857 1.379099 -0.7451625 -0.5118701 0.1213795 0.04586612
col15 col16 col17 col18 col19 col20
row1 -0.7594755 -2.180178 1.236317 1.158107 2.168251 1.672197
> tmp[,"col10"]
col10
row1 1.3790993
row2 1.7814008
row3 0.7954109
row4 -0.1251355
row5 1.0412464
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.3722416 0.3217570 1.319175 1.4836560 -0.5855439 0.1878883 -1.1050758
row5 0.8734574 0.4953281 -1.381026 0.9232126 -2.0763926 0.9157973 0.1218763
col8 col9 col10 col11 col12 col13 col14
row1 -0.3431280 0.9357857 1.379099 -0.7451625 -0.5118701 0.1213795 0.04586612
row5 0.6114295 0.6228742 1.041246 -1.5793954 -0.1465985 -1.5225526 4.57575961
col15 col16 col17 col18 col19 col20
row1 -0.7594755 -2.180178 1.236317 1.1581074 2.1682509 1.672197
row5 -0.1246240 1.534027 0.105858 -0.7676301 -0.3692087 -0.995675
> tmp[,c("col6","col20")]
col6 col20
row1 0.1878883 1.6721967
row2 0.7637953 -0.6922494
row3 0.8824051 0.1139367
row4 -1.5103729 0.6122904
row5 0.9157973 -0.9956750
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.1878883 1.672197
row5 0.9157973 -0.995675
>
>
>
>
> 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 51.36493 49.72959 50.08766 48.70786 48.66352 104.7904 48.41249 49.50522
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.20883 48.8844 49.73531 52.15968 48.38588 48.94914 49.98572 49.78427
col17 col18 col19 col20
row1 50.68912 48.40159 50.45777 104.2119
> tmp[,"col10"]
col10
row1 48.88440
row2 30.58393
row3 30.29702
row4 27.98369
row5 49.85363
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.36493 49.72959 50.08766 48.70786 48.66352 104.7904 48.41249 49.50522
row5 51.99657 49.97369 49.51849 49.86439 49.75867 105.3642 49.37328 50.01424
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.20883 48.88440 49.73531 52.15968 48.38588 48.94914 49.98572 49.78427
row5 50.57836 49.85363 49.71691 48.20322 49.67886 49.52379 50.42261 50.48936
col17 col18 col19 col20
row1 50.68912 48.40159 50.45777 104.2119
row5 47.65408 50.03293 52.30534 105.0146
> tmp[,c("col6","col20")]
col6 col20
row1 104.79044 104.21187
row2 72.81053 74.93958
row3 75.54337 75.16815
row4 74.29424 75.13958
row5 105.36417 105.01462
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.7904 104.2119
row5 105.3642 105.0146
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.7904 104.2119
row5 105.3642 105.0146
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.36475763
[2,] -2.10885777
[3,] 0.08519922
[4,] 0.70753203
[5,] 0.36205775
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.4560031 0.8227432
[2,] -0.2867809 -0.1706928
[3,] 0.9809907 -0.9068887
[4,] 0.7757606 -0.2692635
[5,] -1.0267797 -0.1030356
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.007245062 0.8856985
[2,] 1.537762314 -0.1957987
[3,] -0.475892472 1.1451029
[4,] 0.166035421 0.8016201
[5,] -0.880775578 0.3443540
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.007245062
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.007245062
[2,] 1.537762314
>
>
>
> 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 -0.3669037 -0.0407433 -1.6472439 -0.9219794 0.3474422 1.349676 -1.4157945
row1 -1.3536665 -0.7831792 -0.2854529 -1.0870894 0.2347544 0.633049 0.9237515
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 2.0361332 0.1164718 0.7651202 -2.229480 1.138845 -0.3590144 0.02703403
row1 -0.6741791 -0.7639018 1.5014184 1.439807 1.487742 0.7223072 1.02924527
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.4547231 -0.8015022 0.4796146 0.2022201 0.3858547 -0.6921493
row1 1.1702511 0.1204200 -0.6246393 -0.1951790 1.5022056 1.1604141
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.6039581 0.2212683 0.922836 0.4946728 -0.2238814 1.671798 0.1491435
[,8] [,9] [,10]
row2 -0.4842519 0.6844758 -0.2909295
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.5413645 0.725353 -0.1099321 1.292214 0.2923253 1.796094 1.131766
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.5333555 0.07715284 0.3318226 -0.5593646 -0.3096736 0.6146422 -1.969307
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.4085585 1.648966 0.7074051 -1.410695 -0.8931411 0.3649649
>
>
> 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: 0x7fc141d009d0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM3d8f656afcf2"
[2] "/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM3d8f5304a7e2"
[3] "/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM3d8f56aa1102"
[4] "/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM3d8f3742c6c1"
[5] "/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM3d8f106c53f"
[6] "/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM3d8f637fab9f"
[7] "/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM3d8f52dc86c1"
[8] "/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM3d8fc131367"
[9] "/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM3d8f385ed562"
[10] "/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM3d8f5a0b31d7"
[11] "/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM3d8f14f54870"
[12] "/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM3d8f7366bbcf"
[13] "/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM3d8f5db44e39"
[14] "/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM3d8f687bb03e"
[15] "/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests/BM3d8f106fec09"
>
>
> ### 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: 0x7fc151e022b0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x7fc151e022b0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.14-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x7fc151e022b0>
> rowMedians(tmp)
[1] 0.146695605 -0.141485540 -0.043195781 0.023363749 -0.001642133
[6] 0.170715165 0.350068349 -0.148216929 0.096756153 0.187507069
[11] 0.158840555 -0.368108007 -0.282710842 -0.560106833 0.140803110
[16] -0.011150297 -0.659226444 0.039770306 -0.253163353 0.159413788
[21] 0.256452693 0.242059808 -0.275209904 0.207081799 0.047779616
[26] -0.167959699 -0.308881467 0.826961805 -0.237217756 -0.521237122
[31] 0.414308671 -0.014408067 -0.357548652 0.717394963 -0.245375791
[36] 0.738448521 -0.231717335 0.289301608 0.103687015 -0.169026387
[41] -0.417207828 -0.180934872 0.003813595 0.097598718 -0.005982063
[46] -0.011053913 0.062287033 0.271710845 0.068278668 0.349095782
[51] -0.337683656 -0.038709236 -0.512549263 0.570470265 0.321580264
[56] 0.012602308 -0.174765889 -0.010624045 0.143894307 -0.122938272
[61] 0.352032103 -0.405291110 -0.131836790 -0.368265659 -0.238878758
[66] -0.323237326 0.105034298 0.358553353 -0.327864506 0.046961867
[71] -0.144098603 -0.246654403 -0.274124275 0.130978926 -0.431679165
[76] 0.037924212 0.176949739 -0.367571935 0.214215567 -0.136559913
[81] 0.312506527 -0.146778854 -0.055004389 0.001798168 0.098135234
[86] -0.108104746 0.502935172 0.017334902 0.057152142 0.280137368
[91] -0.269569417 0.017822655 0.241767087 0.066350948 -0.186471188
[96] 0.100032719 0.491767260 0.093649263 -0.018595282 0.766011250
[101] 0.308220511 -0.043539960 -0.274225322 -0.137607106 -0.323069581
[106] 0.397680224 -0.348049881 -0.258061957 -0.318433107 0.255629669
[111] 0.260139074 -0.240046504 -0.445970546 -0.050990632 0.583228848
[116] 0.408539285 -0.423434860 -0.127840504 -0.371757936 -0.081307290
[121] 0.012554175 -0.136259531 -0.040985424 -0.024720694 0.765280077
[126] -0.424572783 -0.026516763 -0.239869739 -0.133292727 -0.020079626
[131] -0.015982269 -0.111794543 0.302637833 0.126467051 -0.428401041
[136] -0.040471181 0.456641165 -0.121774192 0.556975102 0.126789333
[141] 0.009236152 -0.376791506 -0.232605686 -0.341740452 -0.307525369
[146] -0.247913124 0.304040996 -0.603780585 -0.217612067 -0.177594313
[151] 0.340884547 0.102706207 0.220262530 -0.447799607 0.333672423
[156] -0.007323087 0.031041097 -0.225649646 0.162296070 0.340721452
[161] 0.130107340 0.919395883 -0.609019252 -0.291687652 0.089062986
[166] 0.623444012 -0.038159095 0.625378631 0.814644810 0.384606494
[171] 0.290385330 0.222262001 0.097381634 -0.433617584 0.242962731
[176] 0.624131991 -0.101392582 -0.506077818 -0.486987655 0.028985296
[181] 0.315038038 0.405508406 0.264120325 -0.277569674 -0.185888834
[186] 0.235546088 0.214695174 -0.515931040 -0.004629758 -0.375719525
[191] 0.359143928 -0.201821507 -0.298408421 -0.109148674 -0.065987234
[196] 0.512681047 -0.204261535 0.509374398 -0.724482405 0.109512318
[201] -0.073123253 -0.580012583 -0.418847322 0.205984113 0.184246813
[206] -0.099503498 0.235659644 0.049079492 0.022204991 -0.117738108
[211] 0.001025340 -0.526573242 -0.312549714 -0.149539316 0.426450396
[216] -0.288882404 0.401804839 -0.267624831 0.481739761 -0.520212972
[221] -0.003775694 0.485929851 0.379776232 0.343857481 0.182365994
[226] 0.240425352 -0.010507227 0.137422439 0.709111626 -0.214115075
>
> proc.time()
user system elapsed
3.834 12.462 16.562
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-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: 0x7fc73361b250>
> .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: 0x7fc73361b250>
> .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: 0x7fc73361b250>
> .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: 0x7fc73361b250>
> 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: 0x7fc7034007d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fc7034007d0>
> .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: 0x7fc7034007d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fc7034007d0>
> .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: 0x7fc7034007d0>
> 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: 0x7fc703400840>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fc703400840>
> .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: 0x7fc703400840>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x7fc703400840>
> .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: 0x7fc703400840>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x7fc703400840>
> .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: 0x7fc703400840>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x7fc703400840>
> .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: 0x7fc703400840>
> 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: 0x7fc693600090>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x7fc693600090>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fc693600090>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fc693600090>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile403610a709e0" "BufferedMatrixFile4036256af3b9"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile403610a709e0" "BufferedMatrixFile4036256af3b9"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fc6936003b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fc6936003b0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x7fc6936003b0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x7fc6936003b0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x7fc6936003b0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x7fc6936003b0>
> .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: 0x7fc6936007c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fc6936007c0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x7fc6936007c0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x7fc6936007c0>
> 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: 0x7fc693600ba0>
> .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: 0x7fc693600ba0>
> rm(P)
>
> proc.time()
user system elapsed
0.488 0.142 0.605
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up"
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Platform: x86_64-apple-darwin17.0 (64-bit)
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.494 0.092 0.560