Ben Bolstad
| Snapshot Date: 2024-10-04 13:40 -0400 (Fri, 04 Oct 2024) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: d422a05 |
| git_last_commit_date: 2024-04-30 10:16:21 -0400 (Tue, 30 Apr 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2024-10-05 11:43 -0400 (Sat, 05 Oct 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| teran2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4461 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life" | 4466 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4498 |
| kjohnson3 | macOS 13.6.5 Ventura | arm64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4446 |
| kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4445 |
| 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 | ||||
| Package 250/2266 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.69.0 (landing page) Ben Bolstad
| teran2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.6.5 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| kunpeng2 | Linux (openEuler 22.03 LTS-SP1) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - 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 Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.69.0 |
| 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_1.69.0.tar.gz |
| StartedAt: 2024-10-04 19:51:21 -0400 (Fri, 04 Oct 2024) |
| EndedAt: 2024-10-04 19:51:36 -0400 (Fri, 04 Oct 2024) |
| EllapsedTime: 15.2 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
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###
### 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_1.69.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: aarch64-apple-darwin20
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.6.7
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.69.0’
* 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-3.20-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
* used SDK: ‘MacOSX11.3.sdk’
* 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 code 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
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
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 ... 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-3.20-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/4.4-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
using SDK: ‘MacOSX11.3.sdk’
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -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 -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch arm64 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/arm64/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/4.4-arm64/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 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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
0.110 0.036 0.141
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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-3.20-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 474153 25.4 1035438 55.3 NA 638568 34.2
Vcells 877599 6.7 8388608 64.0 196608 2072936 15.9
>
>
>
>
> ##
> ## 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] "Fri Oct 4 19:51:29 2024"
> 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] "Fri Oct 4 19:51:29 2024"
>
>
> 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: 0x600001e90000>
>
>
>
> 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] "Fri Oct 4 19:51:30 2024"
> 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] "Fri Oct 4 19:51:30 2024"
>
> ColMode(tmp2)
<pointer: 0x600001e90000>
>
>
>
> ### 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,] 97.8382209 2.9363332 0.7485263 1.5564489
[2,] 0.4712039 -0.3817991 1.3120741 1.6473778
[3,] -0.9802186 -0.7930606 -0.3696647 -0.4650463
[4,] -0.4702865 0.8742598 -1.4247944 -2.3202570
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 97.8382209 2.9363332 0.7485263 1.5564489
[2,] 0.4712039 0.3817991 1.3120741 1.6473778
[3,] 0.9802186 0.7930606 0.3696647 0.4650463
[4,] 0.4702865 0.8742598 1.4247944 2.3202570
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.8913205 1.7135732 0.8651741 1.247577
[2,] 0.6864429 0.6178989 1.1454580 1.283502
[3,] 0.9900599 0.8905395 0.6080006 0.681943
[4,] 0.6857744 0.9350186 1.1936475 1.523239
>
> 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-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 221.75143 45.07207 34.40027 39.03222
[2,] 32.33563 31.56079 37.76665 39.48240
[3,] 35.88082 34.69846 31.44967 32.28448
[4,] 32.32803 35.22445 38.36127 42.55265
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600001e88120>
> exp(tmp5)
<pointer: 0x600001e88120>
> log(tmp5,2)
<pointer: 0x600001e88120>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 461.5465
> Min(tmp5)
[1] 53.75078
> mean(tmp5)
[1] 73.24101
> Sum(tmp5)
[1] 14648.2
> Var(tmp5)
[1] 823.5489
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.13763 71.00582 72.77474 73.96001 70.30232 70.71436 71.74817 70.75172
[9] 72.13578 68.87958
> rowSums(tmp5)
[1] 1802.753 1420.116 1455.495 1479.200 1406.046 1414.287 1434.963 1415.034
[9] 1442.716 1377.592
> rowVars(tmp5)
[1] 7726.22118 65.08116 79.90234 63.79940 57.86090 50.76018
[7] 39.49820 58.76101 53.26624 77.89830
> rowSd(tmp5)
[1] 87.898926 8.067290 8.938811 7.987453 7.606635 7.124618 6.284759
[8] 7.665573 7.298372 8.826001
> rowMax(tmp5)
[1] 461.54654 82.17744 92.62792 88.61363 83.46564 79.34507 84.42781
[8] 87.28720 89.34340 87.05729
> rowMin(tmp5)
[1] 53.75078 59.03661 59.65248 61.20192 57.50354 57.64595 61.88286 59.53277
[9] 61.92551 57.34427
>
> colMeans(tmp5)
[1] 111.04577 72.11273 69.89705 70.30755 70.73167 72.05950 69.21518
[8] 72.80673 69.36496 73.59983 68.74064 70.87453 73.39952 70.33617
[15] 71.16419 67.10043 74.35923 72.32063 72.78506 72.59891
> colSums(tmp5)
[1] 1110.4577 721.1273 698.9705 703.0755 707.3167 720.5950 692.1518
[8] 728.0673 693.6496 735.9983 687.4064 708.7453 733.9952 703.3617
[15] 711.6419 671.0043 743.5923 723.2063 727.8506 725.9891
> colVars(tmp5)
[1] 15204.68433 95.22861 77.69221 107.58162 67.34686 51.12807
[7] 55.82173 66.23569 76.57774 52.35487 24.90129 58.85456
[13] 44.44554 40.77341 121.25859 35.26710 57.44728 54.34222
[19] 78.58069 96.21875
> colSd(tmp5)
[1] 123.307276 9.758515 8.814319 10.372156 8.206513 7.150389
[7] 7.471394 8.138531 8.750871 7.235666 4.990119 7.671673
[13] 6.666748 6.385406 11.011748 5.938611 7.579399 7.371717
[19] 8.864575 9.809116
> colMax(tmp5)
[1] 461.54654 93.81160 82.57906 88.56776 83.78569 80.91676 77.72102
[8] 92.62792 86.75709 87.28720 74.34554 88.61363 83.46564 78.56151
[15] 86.59286 77.90007 85.93485 83.20955 87.05729 89.34340
> colMin(tmp5)
[1] 64.13861 57.50354 58.09440 58.33363 61.63366 59.53277 56.47631 61.60472
[9] 53.75078 63.38048 62.07409 61.88286 59.06306 57.34427 57.64595 59.65248
[17] 61.81598 63.06544 59.51217 61.96619
>
>
> ### 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] NA 71.00582 72.77474 73.96001 70.30232 70.71436 71.74817 70.75172
[9] 72.13578 68.87958
> rowSums(tmp5)
[1] NA 1420.116 1455.495 1479.200 1406.046 1414.287 1434.963 1415.034
[9] 1442.716 1377.592
> rowVars(tmp5)
[1] 8078.02863 65.08116 79.90234 63.79940 57.86090 50.76018
[7] 39.49820 58.76101 53.26624 77.89830
> rowSd(tmp5)
[1] 89.877854 8.067290 8.938811 7.987453 7.606635 7.124618 6.284759
[8] 7.665573 7.298372 8.826001
> rowMax(tmp5)
[1] NA 82.17744 92.62792 88.61363 83.46564 79.34507 84.42781 87.28720
[9] 89.34340 87.05729
> rowMin(tmp5)
[1] NA 59.03661 59.65248 61.20192 57.50354 57.64595 61.88286 59.53277
[9] 61.92551 57.34427
>
> colMeans(tmp5)
[1] 111.04577 72.11273 69.89705 70.30755 70.73167 72.05950 69.21518
[8] 72.80673 NA 73.59983 68.74064 70.87453 73.39952 70.33617
[15] 71.16419 67.10043 74.35923 72.32063 72.78506 72.59891
> colSums(tmp5)
[1] 1110.4577 721.1273 698.9705 703.0755 707.3167 720.5950 692.1518
[8] 728.0673 NA 735.9983 687.4064 708.7453 733.9952 703.3617
[15] 711.6419 671.0043 743.5923 723.2063 727.8506 725.9891
> colVars(tmp5)
[1] 15204.68433 95.22861 77.69221 107.58162 67.34686 51.12807
[7] 55.82173 66.23569 NA 52.35487 24.90129 58.85456
[13] 44.44554 40.77341 121.25859 35.26710 57.44728 54.34222
[19] 78.58069 96.21875
> colSd(tmp5)
[1] 123.307276 9.758515 8.814319 10.372156 8.206513 7.150389
[7] 7.471394 8.138531 NA 7.235666 4.990119 7.671673
[13] 6.666748 6.385406 11.011748 5.938611 7.579399 7.371717
[19] 8.864575 9.809116
> colMax(tmp5)
[1] 461.54654 93.81160 82.57906 88.56776 83.78569 80.91676 77.72102
[8] 92.62792 NA 87.28720 74.34554 88.61363 83.46564 78.56151
[15] 86.59286 77.90007 85.93485 83.20955 87.05729 89.34340
> colMin(tmp5)
[1] 64.13861 57.50354 58.09440 58.33363 61.63366 59.53277 56.47631 61.60472
[9] NA 63.38048 62.07409 61.88286 59.06306 57.34427 57.64595 59.65248
[17] 61.81598 63.06544 59.51217 61.96619
>
> Max(tmp5,na.rm=TRUE)
[1] 461.5465
> Min(tmp5,na.rm=TRUE)
[1] 56.47631
> mean(tmp5,na.rm=TRUE)
[1] 73.33895
> Sum(tmp5,na.rm=TRUE)
[1] 14594.45
> Var(tmp5,na.rm=TRUE)
[1] 825.78
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.05273 71.00582 72.77474 73.96001 70.30232 70.71436 71.74817 70.75172
[9] 72.13578 68.87958
> rowSums(tmp5,na.rm=TRUE)
[1] 1749.002 1420.116 1455.495 1479.200 1406.046 1414.287 1434.963 1415.034
[9] 1442.716 1377.592
> rowVars(tmp5,na.rm=TRUE)
[1] 8078.02863 65.08116 79.90234 63.79940 57.86090 50.76018
[7] 39.49820 58.76101 53.26624 77.89830
> rowSd(tmp5,na.rm=TRUE)
[1] 89.877854 8.067290 8.938811 7.987453 7.606635 7.124618 6.284759
[8] 7.665573 7.298372 8.826001
> rowMax(tmp5,na.rm=TRUE)
[1] 461.54654 82.17744 92.62792 88.61363 83.46564 79.34507 84.42781
[8] 87.28720 89.34340 87.05729
> rowMin(tmp5,na.rm=TRUE)
[1] 56.47631 59.03661 59.65248 61.20192 57.50354 57.64595 61.88286 59.53277
[9] 61.92551 57.34427
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.04577 72.11273 69.89705 70.30755 70.73167 72.05950 69.21518
[8] 72.80673 71.09987 73.59983 68.74064 70.87453 73.39952 70.33617
[15] 71.16419 67.10043 74.35923 72.32063 72.78506 72.59891
> colSums(tmp5,na.rm=TRUE)
[1] 1110.4577 721.1273 698.9705 703.0755 707.3167 720.5950 692.1518
[8] 728.0673 639.8988 735.9983 687.4064 708.7453 733.9952 703.3617
[15] 711.6419 671.0043 743.5923 723.2063 727.8506 725.9891
> colVars(tmp5,na.rm=TRUE)
[1] 15204.68433 95.22861 77.69221 107.58162 67.34686 51.12807
[7] 55.82173 66.23569 52.28851 52.35487 24.90129 58.85456
[13] 44.44554 40.77341 121.25859 35.26710 57.44728 54.34222
[19] 78.58069 96.21875
> colSd(tmp5,na.rm=TRUE)
[1] 123.307276 9.758515 8.814319 10.372156 8.206513 7.150389
[7] 7.471394 8.138531 7.231079 7.235666 4.990119 7.671673
[13] 6.666748 6.385406 11.011748 5.938611 7.579399 7.371717
[19] 8.864575 9.809116
> colMax(tmp5,na.rm=TRUE)
[1] 461.54654 93.81160 82.57906 88.56776 83.78569 80.91676 77.72102
[8] 92.62792 86.75709 87.28720 74.34554 88.61363 83.46564 78.56151
[15] 86.59286 77.90007 85.93485 83.20955 87.05729 89.34340
> colMin(tmp5,na.rm=TRUE)
[1] 64.13861 57.50354 58.09440 58.33363 61.63366 59.53277 56.47631 61.60472
[9] 60.56386 63.38048 62.07409 61.88286 59.06306 57.34427 57.64595 59.65248
[17] 61.81598 63.06544 59.51217 61.96619
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 71.00582 72.77474 73.96001 70.30232 70.71436 71.74817 70.75172
[9] 72.13578 68.87958
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1420.116 1455.495 1479.200 1406.046 1414.287 1434.963 1415.034
[9] 1442.716 1377.592
> rowVars(tmp5,na.rm=TRUE)
[1] NA 65.08116 79.90234 63.79940 57.86090 50.76018 39.49820 58.76101
[9] 53.26624 77.89830
> rowSd(tmp5,na.rm=TRUE)
[1] NA 8.067290 8.938811 7.987453 7.606635 7.124618 6.284759 7.665573
[9] 7.298372 8.826001
> rowMax(tmp5,na.rm=TRUE)
[1] NA 82.17744 92.62792 88.61363 83.46564 79.34507 84.42781 87.28720
[9] 89.34340 87.05729
> rowMin(tmp5,na.rm=TRUE)
[1] NA 59.03661 59.65248 61.20192 57.50354 57.64595 61.88286 59.53277
[9] 61.92551 57.34427
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 72.10124 69.70174 69.70787 69.09278 69.28122 71.91751 70.63061 72.66242
[9] NaN 74.14078 69.13514 70.46393 73.66051 71.16325 71.93566 67.55610
[17] 74.23314 73.13238 72.95983 72.69625
> colSums(tmp5,na.rm=TRUE)
[1] 648.9111 627.3157 627.3708 621.8350 623.5310 647.2576 635.6755 653.9617
[9] 0.0000 667.2671 622.2163 634.1754 662.9446 640.4693 647.4209 608.0049
[17] 668.0982 658.1914 656.6385 654.2663
> colVars(tmp5,na.rm=TRUE)
[1] 42.66000 41.73760 87.00112 104.42815 52.09749 57.29225 40.26074
[8] 74.28084 NA 55.60710 26.26308 64.31474 49.23495 38.17430
[15] 129.72046 37.33957 64.44933 53.72199 88.05964 108.13949
> colSd(tmp5,na.rm=TRUE)
[1] 6.531462 6.460464 9.327439 10.219009 7.217859 7.569164 6.345135
[8] 8.618633 NA 7.457017 5.124751 8.019647 7.016762 6.178535
[15] 11.389489 6.110611 8.028034 7.329528 9.384010 10.399014
> colMax(tmp5,na.rm=TRUE)
[1] 83.37135 79.72575 82.57906 88.56776 80.73499 80.91676 77.72102 92.62792
[9] -Inf 87.28720 74.34554 88.61363 83.46564 78.56151 86.59286 77.90007
[17] 85.93485 83.20955 87.05729 89.34340
> colMin(tmp5,na.rm=TRUE)
[1] 64.13861 57.50354 58.09440 58.33363 61.63366 59.53277 57.92890 61.60472
[9] Inf 63.38048 62.07409 61.88286 59.06306 57.34427 57.64595 59.65248
[17] 61.81598 63.06544 59.51217 61.96619
>
>
>
>
> 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] 428.0227 179.6295 365.1436 200.8263 138.9200 243.1818 344.2562 307.7718
[9] 320.4988 182.3714
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 428.0227 179.6295 365.1436 200.8263 138.9200 243.1818 344.2562 307.7718
[9] 320.4988 182.3714
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 1.136868e-13 0.000000e+00 1.136868e-13 -3.126388e-13 -5.684342e-14
[6] 2.842171e-14 -5.684342e-14 8.526513e-14 -1.705303e-13 2.842171e-14
[11] -3.410605e-13 -5.684342e-14 2.842171e-13 -5.684342e-14 0.000000e+00
[16] 0.000000e+00 1.421085e-14 2.273737e-13 -2.842171e-14 1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
10 14
1 19
4 6
4 14
7 13
3 13
6 9
2 14
9 5
2 2
7 18
8 12
4 19
3 14
1 11
6 14
8 3
5 9
1 14
3 4
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] 2.000176
> Min(tmp)
[1] -2.803146
> mean(tmp)
[1] -0.077104
> Sum(tmp)
[1] -7.7104
> Var(tmp)
[1] 1.036662
>
> rowMeans(tmp)
[1] -0.077104
> rowSums(tmp)
[1] -7.7104
> rowVars(tmp)
[1] 1.036662
> rowSd(tmp)
[1] 1.018166
> rowMax(tmp)
[1] 2.000176
> rowMin(tmp)
[1] -2.803146
>
> colMeans(tmp)
[1] 1.3786890177 1.8725307430 -0.3921778157 -2.1213438634 -0.1619436448
[6] -0.4510178012 -0.6699385463 0.9256011401 -1.0467502059 0.7558970351
[11] -0.3129864921 0.6250091197 -2.0428484589 -0.2237117738 0.1281904808
[16] -0.0211852336 -0.8985870192 0.2319887938 -0.5360861648 -2.7895971221
[21] -0.3197517193 -0.5383213657 0.1417335223 -1.5100739739 0.2137392514
[26] 0.1487327908 -1.7194878915 -1.2516648920 -1.1568129843 0.7980311127
[31] 1.5217487864 -0.4271125391 1.8633771046 -0.7979507432 -0.3897861020
[36] 1.0537619641 -1.3607025468 -0.2141253095 0.5996440510 1.1629908668
[41] -0.0913616052 0.0851022938 0.5325478653 0.7993778343 -1.3683926341
[46] -0.3289240751 0.2209131949 -0.2011274863 0.6083642386 0.7334493281
[51] 0.5019528131 -0.5448227852 -1.1378718103 -0.4099045359 0.7505552651
[56] 1.4909670359 0.3379944859 0.6137771621 2.0001755508 -0.6100454435
[61] 1.1452311387 -2.8031460791 -0.9060632975 0.6126065861 -0.9805280373
[66] -0.4281189996 -0.0864262631 -0.1136822156 0.8959317801 0.1867256202
[71] 0.4323298331 1.2818663206 -0.0427584429 0.5933321224 1.1187788056
[76] -1.0645828524 1.2545219740 -2.2697188162 -0.2051499239 0.6245556037
[81] -1.7200888356 0.5336036988 -0.1492399864 1.2675793515 -0.2783737338
[86] -1.1244615870 0.0236820450 -1.9508420368 -0.0258493193 -0.9531214337
[91] 1.1567700287 -0.8539690846 -0.5083097560 1.1318598517 0.5140493063
[96] 0.0006534511 -1.1633965475 0.7739636140 0.8967290003 -0.5777715574
> colSums(tmp)
[1] 1.3786890177 1.8725307430 -0.3921778157 -2.1213438634 -0.1619436448
[6] -0.4510178012 -0.6699385463 0.9256011401 -1.0467502059 0.7558970351
[11] -0.3129864921 0.6250091197 -2.0428484589 -0.2237117738 0.1281904808
[16] -0.0211852336 -0.8985870192 0.2319887938 -0.5360861648 -2.7895971221
[21] -0.3197517193 -0.5383213657 0.1417335223 -1.5100739739 0.2137392514
[26] 0.1487327908 -1.7194878915 -1.2516648920 -1.1568129843 0.7980311127
[31] 1.5217487864 -0.4271125391 1.8633771046 -0.7979507432 -0.3897861020
[36] 1.0537619641 -1.3607025468 -0.2141253095 0.5996440510 1.1629908668
[41] -0.0913616052 0.0851022938 0.5325478653 0.7993778343 -1.3683926341
[46] -0.3289240751 0.2209131949 -0.2011274863 0.6083642386 0.7334493281
[51] 0.5019528131 -0.5448227852 -1.1378718103 -0.4099045359 0.7505552651
[56] 1.4909670359 0.3379944859 0.6137771621 2.0001755508 -0.6100454435
[61] 1.1452311387 -2.8031460791 -0.9060632975 0.6126065861 -0.9805280373
[66] -0.4281189996 -0.0864262631 -0.1136822156 0.8959317801 0.1867256202
[71] 0.4323298331 1.2818663206 -0.0427584429 0.5933321224 1.1187788056
[76] -1.0645828524 1.2545219740 -2.2697188162 -0.2051499239 0.6245556037
[81] -1.7200888356 0.5336036988 -0.1492399864 1.2675793515 -0.2783737338
[86] -1.1244615870 0.0236820450 -1.9508420368 -0.0258493193 -0.9531214337
[91] 1.1567700287 -0.8539690846 -0.5083097560 1.1318598517 0.5140493063
[96] 0.0006534511 -1.1633965475 0.7739636140 0.8967290003 -0.5777715574
> 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] 1.3786890177 1.8725307430 -0.3921778157 -2.1213438634 -0.1619436448
[6] -0.4510178012 -0.6699385463 0.9256011401 -1.0467502059 0.7558970351
[11] -0.3129864921 0.6250091197 -2.0428484589 -0.2237117738 0.1281904808
[16] -0.0211852336 -0.8985870192 0.2319887938 -0.5360861648 -2.7895971221
[21] -0.3197517193 -0.5383213657 0.1417335223 -1.5100739739 0.2137392514
[26] 0.1487327908 -1.7194878915 -1.2516648920 -1.1568129843 0.7980311127
[31] 1.5217487864 -0.4271125391 1.8633771046 -0.7979507432 -0.3897861020
[36] 1.0537619641 -1.3607025468 -0.2141253095 0.5996440510 1.1629908668
[41] -0.0913616052 0.0851022938 0.5325478653 0.7993778343 -1.3683926341
[46] -0.3289240751 0.2209131949 -0.2011274863 0.6083642386 0.7334493281
[51] 0.5019528131 -0.5448227852 -1.1378718103 -0.4099045359 0.7505552651
[56] 1.4909670359 0.3379944859 0.6137771621 2.0001755508 -0.6100454435
[61] 1.1452311387 -2.8031460791 -0.9060632975 0.6126065861 -0.9805280373
[66] -0.4281189996 -0.0864262631 -0.1136822156 0.8959317801 0.1867256202
[71] 0.4323298331 1.2818663206 -0.0427584429 0.5933321224 1.1187788056
[76] -1.0645828524 1.2545219740 -2.2697188162 -0.2051499239 0.6245556037
[81] -1.7200888356 0.5336036988 -0.1492399864 1.2675793515 -0.2783737338
[86] -1.1244615870 0.0236820450 -1.9508420368 -0.0258493193 -0.9531214337
[91] 1.1567700287 -0.8539690846 -0.5083097560 1.1318598517 0.5140493063
[96] 0.0006534511 -1.1633965475 0.7739636140 0.8967290003 -0.5777715574
> colMin(tmp)
[1] 1.3786890177 1.8725307430 -0.3921778157 -2.1213438634 -0.1619436448
[6] -0.4510178012 -0.6699385463 0.9256011401 -1.0467502059 0.7558970351
[11] -0.3129864921 0.6250091197 -2.0428484589 -0.2237117738 0.1281904808
[16] -0.0211852336 -0.8985870192 0.2319887938 -0.5360861648 -2.7895971221
[21] -0.3197517193 -0.5383213657 0.1417335223 -1.5100739739 0.2137392514
[26] 0.1487327908 -1.7194878915 -1.2516648920 -1.1568129843 0.7980311127
[31] 1.5217487864 -0.4271125391 1.8633771046 -0.7979507432 -0.3897861020
[36] 1.0537619641 -1.3607025468 -0.2141253095 0.5996440510 1.1629908668
[41] -0.0913616052 0.0851022938 0.5325478653 0.7993778343 -1.3683926341
[46] -0.3289240751 0.2209131949 -0.2011274863 0.6083642386 0.7334493281
[51] 0.5019528131 -0.5448227852 -1.1378718103 -0.4099045359 0.7505552651
[56] 1.4909670359 0.3379944859 0.6137771621 2.0001755508 -0.6100454435
[61] 1.1452311387 -2.8031460791 -0.9060632975 0.6126065861 -0.9805280373
[66] -0.4281189996 -0.0864262631 -0.1136822156 0.8959317801 0.1867256202
[71] 0.4323298331 1.2818663206 -0.0427584429 0.5933321224 1.1187788056
[76] -1.0645828524 1.2545219740 -2.2697188162 -0.2051499239 0.6245556037
[81] -1.7200888356 0.5336036988 -0.1492399864 1.2675793515 -0.2783737338
[86] -1.1244615870 0.0236820450 -1.9508420368 -0.0258493193 -0.9531214337
[91] 1.1567700287 -0.8539690846 -0.5083097560 1.1318598517 0.5140493063
[96] 0.0006534511 -1.1633965475 0.7739636140 0.8967290003 -0.5777715574
> colMedians(tmp)
[1] 1.3786890177 1.8725307430 -0.3921778157 -2.1213438634 -0.1619436448
[6] -0.4510178012 -0.6699385463 0.9256011401 -1.0467502059 0.7558970351
[11] -0.3129864921 0.6250091197 -2.0428484589 -0.2237117738 0.1281904808
[16] -0.0211852336 -0.8985870192 0.2319887938 -0.5360861648 -2.7895971221
[21] -0.3197517193 -0.5383213657 0.1417335223 -1.5100739739 0.2137392514
[26] 0.1487327908 -1.7194878915 -1.2516648920 -1.1568129843 0.7980311127
[31] 1.5217487864 -0.4271125391 1.8633771046 -0.7979507432 -0.3897861020
[36] 1.0537619641 -1.3607025468 -0.2141253095 0.5996440510 1.1629908668
[41] -0.0913616052 0.0851022938 0.5325478653 0.7993778343 -1.3683926341
[46] -0.3289240751 0.2209131949 -0.2011274863 0.6083642386 0.7334493281
[51] 0.5019528131 -0.5448227852 -1.1378718103 -0.4099045359 0.7505552651
[56] 1.4909670359 0.3379944859 0.6137771621 2.0001755508 -0.6100454435
[61] 1.1452311387 -2.8031460791 -0.9060632975 0.6126065861 -0.9805280373
[66] -0.4281189996 -0.0864262631 -0.1136822156 0.8959317801 0.1867256202
[71] 0.4323298331 1.2818663206 -0.0427584429 0.5933321224 1.1187788056
[76] -1.0645828524 1.2545219740 -2.2697188162 -0.2051499239 0.6245556037
[81] -1.7200888356 0.5336036988 -0.1492399864 1.2675793515 -0.2783737338
[86] -1.1244615870 0.0236820450 -1.9508420368 -0.0258493193 -0.9531214337
[91] 1.1567700287 -0.8539690846 -0.5083097560 1.1318598517 0.5140493063
[96] 0.0006534511 -1.1633965475 0.7739636140 0.8967290003 -0.5777715574
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.378689 1.872531 -0.3921778 -2.121344 -0.1619436 -0.4510178 -0.6699385
[2,] 1.378689 1.872531 -0.3921778 -2.121344 -0.1619436 -0.4510178 -0.6699385
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.9256011 -1.04675 0.755897 -0.3129865 0.6250091 -2.042848 -0.2237118
[2,] 0.9256011 -1.04675 0.755897 -0.3129865 0.6250091 -2.042848 -0.2237118
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.1281905 -0.02118523 -0.898587 0.2319888 -0.5360862 -2.789597 -0.3197517
[2,] 0.1281905 -0.02118523 -0.898587 0.2319888 -0.5360862 -2.789597 -0.3197517
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.5383214 0.1417335 -1.510074 0.2137393 0.1487328 -1.719488 -1.251665
[2,] -0.5383214 0.1417335 -1.510074 0.2137393 0.1487328 -1.719488 -1.251665
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.156813 0.7980311 1.521749 -0.4271125 1.863377 -0.7979507 -0.3897861
[2,] -1.156813 0.7980311 1.521749 -0.4271125 1.863377 -0.7979507 -0.3897861
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.053762 -1.360703 -0.2141253 0.5996441 1.162991 -0.09136161 0.08510229
[2,] 1.053762 -1.360703 -0.2141253 0.5996441 1.162991 -0.09136161 0.08510229
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.5325479 0.7993778 -1.368393 -0.3289241 0.2209132 -0.2011275 0.6083642
[2,] 0.5325479 0.7993778 -1.368393 -0.3289241 0.2209132 -0.2011275 0.6083642
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.7334493 0.5019528 -0.5448228 -1.137872 -0.4099045 0.7505553 1.490967
[2,] 0.7334493 0.5019528 -0.5448228 -1.137872 -0.4099045 0.7505553 1.490967
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.3379945 0.6137772 2.000176 -0.6100454 1.145231 -2.803146 -0.9060633
[2,] 0.3379945 0.6137772 2.000176 -0.6100454 1.145231 -2.803146 -0.9060633
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.6126066 -0.980528 -0.428119 -0.08642626 -0.1136822 0.8959318 0.1867256
[2,] 0.6126066 -0.980528 -0.428119 -0.08642626 -0.1136822 0.8959318 0.1867256
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.4323298 1.281866 -0.04275844 0.5933321 1.118779 -1.064583 1.254522
[2,] 0.4323298 1.281866 -0.04275844 0.5933321 1.118779 -1.064583 1.254522
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -2.269719 -0.2051499 0.6245556 -1.720089 0.5336037 -0.14924 1.267579
[2,] -2.269719 -0.2051499 0.6245556 -1.720089 0.5336037 -0.14924 1.267579
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.2783737 -1.124462 0.02368204 -1.950842 -0.02584932 -0.9531214 1.15677
[2,] -0.2783737 -1.124462 0.02368204 -1.950842 -0.02584932 -0.9531214 1.15677
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.8539691 -0.5083098 1.13186 0.5140493 0.0006534511 -1.163397 0.7739636
[2,] -0.8539691 -0.5083098 1.13186 0.5140493 0.0006534511 -1.163397 0.7739636
[,99] [,100]
[1,] 0.896729 -0.5777716
[2,] 0.896729 -0.5777716
>
>
> Max(tmp2)
[1] 1.68897
> Min(tmp2)
[1] -2.716259
> mean(tmp2)
[1] -0.04312793
> Sum(tmp2)
[1] -4.312793
> Var(tmp2)
[1] 0.9068638
>
> rowMeans(tmp2)
[1] -0.319735220 0.418654415 -0.496887477 -0.204520910 1.224667612
[6] 0.068415704 -2.716258876 0.628221220 0.677208607 0.206703167
[11] 0.318662070 0.671724696 0.092985788 -0.953404451 0.809072089
[16] 0.266546686 1.006942815 0.825579554 -0.330360761 -0.024654932
[21] 0.391346373 -0.773604813 1.688970164 0.387169364 -0.686914032
[26] -0.329115851 1.355365115 1.361644156 -0.263909591 0.426341474
[31] 0.080022386 -1.389755870 0.473423523 1.606961875 0.521674109
[36] -1.233676997 0.016411361 1.620980176 1.033480111 0.317284744
[41] 0.095368223 0.736329710 -0.950078435 0.459834148 -1.946803749
[46] -0.266357599 -0.108111346 0.880620703 1.109089110 -0.339254406
[51] -0.393490366 -0.170621620 0.646575170 1.478847637 0.501792543
[56] 0.006241987 -1.743473405 -0.769122690 -0.846741391 -0.442645211
[61] 0.162474072 0.925468664 0.931774011 1.119679366 -1.704223956
[66] 0.316489562 -1.933390298 -0.798124422 -0.880676546 -2.166876364
[71] 0.412720417 0.151818484 -0.533222137 0.536724929 0.549194179
[76] 0.337076217 1.654474073 0.468788432 -0.291189296 -1.107053629
[81] 0.633369359 -0.266401378 -1.649576367 0.402447897 -1.063486593
[86] -0.069098349 0.136426821 -1.934010275 0.719206858 1.448393561
[91] -0.050598870 -0.069202151 -1.111500307 -1.093896846 -1.651953925
[96] -1.765581011 -0.841519007 0.131097530 -0.555716422 -0.524777795
> rowSums(tmp2)
[1] -0.319735220 0.418654415 -0.496887477 -0.204520910 1.224667612
[6] 0.068415704 -2.716258876 0.628221220 0.677208607 0.206703167
[11] 0.318662070 0.671724696 0.092985788 -0.953404451 0.809072089
[16] 0.266546686 1.006942815 0.825579554 -0.330360761 -0.024654932
[21] 0.391346373 -0.773604813 1.688970164 0.387169364 -0.686914032
[26] -0.329115851 1.355365115 1.361644156 -0.263909591 0.426341474
[31] 0.080022386 -1.389755870 0.473423523 1.606961875 0.521674109
[36] -1.233676997 0.016411361 1.620980176 1.033480111 0.317284744
[41] 0.095368223 0.736329710 -0.950078435 0.459834148 -1.946803749
[46] -0.266357599 -0.108111346 0.880620703 1.109089110 -0.339254406
[51] -0.393490366 -0.170621620 0.646575170 1.478847637 0.501792543
[56] 0.006241987 -1.743473405 -0.769122690 -0.846741391 -0.442645211
[61] 0.162474072 0.925468664 0.931774011 1.119679366 -1.704223956
[66] 0.316489562 -1.933390298 -0.798124422 -0.880676546 -2.166876364
[71] 0.412720417 0.151818484 -0.533222137 0.536724929 0.549194179
[76] 0.337076217 1.654474073 0.468788432 -0.291189296 -1.107053629
[81] 0.633369359 -0.266401378 -1.649576367 0.402447897 -1.063486593
[86] -0.069098349 0.136426821 -1.934010275 0.719206858 1.448393561
[91] -0.050598870 -0.069202151 -1.111500307 -1.093896846 -1.651953925
[96] -1.765581011 -0.841519007 0.131097530 -0.555716422 -0.524777795
> 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] -0.319735220 0.418654415 -0.496887477 -0.204520910 1.224667612
[6] 0.068415704 -2.716258876 0.628221220 0.677208607 0.206703167
[11] 0.318662070 0.671724696 0.092985788 -0.953404451 0.809072089
[16] 0.266546686 1.006942815 0.825579554 -0.330360761 -0.024654932
[21] 0.391346373 -0.773604813 1.688970164 0.387169364 -0.686914032
[26] -0.329115851 1.355365115 1.361644156 -0.263909591 0.426341474
[31] 0.080022386 -1.389755870 0.473423523 1.606961875 0.521674109
[36] -1.233676997 0.016411361 1.620980176 1.033480111 0.317284744
[41] 0.095368223 0.736329710 -0.950078435 0.459834148 -1.946803749
[46] -0.266357599 -0.108111346 0.880620703 1.109089110 -0.339254406
[51] -0.393490366 -0.170621620 0.646575170 1.478847637 0.501792543
[56] 0.006241987 -1.743473405 -0.769122690 -0.846741391 -0.442645211
[61] 0.162474072 0.925468664 0.931774011 1.119679366 -1.704223956
[66] 0.316489562 -1.933390298 -0.798124422 -0.880676546 -2.166876364
[71] 0.412720417 0.151818484 -0.533222137 0.536724929 0.549194179
[76] 0.337076217 1.654474073 0.468788432 -0.291189296 -1.107053629
[81] 0.633369359 -0.266401378 -1.649576367 0.402447897 -1.063486593
[86] -0.069098349 0.136426821 -1.934010275 0.719206858 1.448393561
[91] -0.050598870 -0.069202151 -1.111500307 -1.093896846 -1.651953925
[96] -1.765581011 -0.841519007 0.131097530 -0.555716422 -0.524777795
> rowMin(tmp2)
[1] -0.319735220 0.418654415 -0.496887477 -0.204520910 1.224667612
[6] 0.068415704 -2.716258876 0.628221220 0.677208607 0.206703167
[11] 0.318662070 0.671724696 0.092985788 -0.953404451 0.809072089
[16] 0.266546686 1.006942815 0.825579554 -0.330360761 -0.024654932
[21] 0.391346373 -0.773604813 1.688970164 0.387169364 -0.686914032
[26] -0.329115851 1.355365115 1.361644156 -0.263909591 0.426341474
[31] 0.080022386 -1.389755870 0.473423523 1.606961875 0.521674109
[36] -1.233676997 0.016411361 1.620980176 1.033480111 0.317284744
[41] 0.095368223 0.736329710 -0.950078435 0.459834148 -1.946803749
[46] -0.266357599 -0.108111346 0.880620703 1.109089110 -0.339254406
[51] -0.393490366 -0.170621620 0.646575170 1.478847637 0.501792543
[56] 0.006241987 -1.743473405 -0.769122690 -0.846741391 -0.442645211
[61] 0.162474072 0.925468664 0.931774011 1.119679366 -1.704223956
[66] 0.316489562 -1.933390298 -0.798124422 -0.880676546 -2.166876364
[71] 0.412720417 0.151818484 -0.533222137 0.536724929 0.549194179
[76] 0.337076217 1.654474073 0.468788432 -0.291189296 -1.107053629
[81] 0.633369359 -0.266401378 -1.649576367 0.402447897 -1.063486593
[86] -0.069098349 0.136426821 -1.934010275 0.719206858 1.448393561
[91] -0.050598870 -0.069202151 -1.111500307 -1.093896846 -1.651953925
[96] -1.765581011 -0.841519007 0.131097530 -0.555716422 -0.524777795
>
> colMeans(tmp2)
[1] -0.04312793
> colSums(tmp2)
[1] -4.312793
> colVars(tmp2)
[1] 0.9068638
> colSd(tmp2)
[1] 0.9522939
> colMax(tmp2)
[1] 1.68897
> colMin(tmp2)
[1] -2.716259
> colMedians(tmp2)
[1] 0.08650409
> colRanges(tmp2)
[,1]
[1,] -2.716259
[2,] 1.688970
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.2776892 2.3515205 -3.9533318 -2.1788170 1.7006744 -2.1178716
[7] 5.5329797 1.6801682 5.6361282 2.0171056
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8438014
[2,] -0.4752567
[3,] -0.3359439
[4,] 0.5145242
[5,] 1.6047411
>
> rowApply(tmp,sum)
[1] 1.4026852 -3.9766624 -0.6671985 -2.2524281 2.3895009 0.3220451
[7] 3.2668475 3.7716437 1.8904357 4.7993765
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 6 6 2 4 4 9 3 10 2 3
[2,] 8 1 7 10 2 6 6 9 5 4
[3,] 1 5 3 1 3 8 1 7 6 5
[4,] 4 10 4 3 1 3 2 5 10 2
[5,] 5 8 5 6 7 5 10 6 8 1
[6,] 2 4 1 7 5 2 9 2 4 8
[7,] 3 3 10 9 9 10 8 3 7 7
[8,] 9 2 8 8 6 1 4 1 9 10
[9,] 10 7 9 2 10 4 7 8 1 9
[10,] 7 9 6 5 8 7 5 4 3 6
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.9862433 -0.5623318 3.4370897 4.0189649 -0.7404882 -0.3189150
[7] 0.5658071 1.1442698 -0.8400356 5.0701133 -1.3936573 1.1758592
[13] 0.8745843 3.7271823 -5.2372529 1.5214314 1.4355262 4.1760295
[19] 3.3207114 1.6396021
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.05958301
[2,] -0.29790968
[3,] 0.05012199
[4,] 0.06144508
[5,] 0.25968229
>
> rowApply(tmp,sum)
[1] 4.746284 1.772098 6.436651 6.259845 1.813369
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 9 9 1 7 13
[2,] 3 8 13 3 16
[3,] 17 7 11 20 5
[4,] 4 20 15 19 12
[5,] 1 6 20 8 2
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.25968229 -1.22067814 1.3635558 -0.73408026 -1.686630299 -0.09901991
[2,] 0.05012199 0.03038724 -0.3089746 1.61679164 -0.435627155 0.88430001
[3,] -2.05958301 0.77152176 0.4357122 1.06812349 2.171857688 0.32100318
[4,] -0.29790968 -0.81047542 2.3824236 2.12897498 -0.008296918 -0.87222044
[5,] 0.06144508 0.66691272 -0.4356274 -0.06084492 -0.781791472 -0.55297785
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.47381261 1.5445591 -1.3575541 0.8267502 -0.56947500 1.8463754
[2,] -2.39703741 0.7593948 -0.9895651 0.8573973 0.82565906 0.5346293
[3,] 0.03693386 -0.8810955 0.2675906 1.2728120 0.07945049 -0.4760153
[4,] 1.08780721 0.2893369 1.5545713 1.4532979 -0.30221248 -0.5359060
[5,] 1.36429081 -0.5679256 -0.3150784 0.6598558 -1.42707939 -0.1932242
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
[1,] -0.4317021 1.4983195 0.3506135 0.7013173 1.0575391 0.8590248 0.5899095
[2,] -1.0358176 1.1100662 -2.0795338 0.3309180 -1.1991617 1.2513960 1.3634436
[3,] 1.4261114 0.7468806 -1.6294299 -0.1751782 1.2052456 0.8804362 1.1148529
[4,] -0.7342795 0.1445374 -1.7446014 0.9684939 0.5895084 0.1439126 0.6585415
[5,] 1.6502721 0.2273785 -0.1343013 -0.3041197 -0.2176053 1.0412598 -0.4060361
[,20]
[1,] -0.5260356
[2,] 0.6033105
[3,] -0.1405793
[4,] 0.1643408
[5,] 1.5385656
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-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-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 655 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-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 1.508614 0.1030961 -1.825447 -0.8141932 -1.415414 -0.8298429 0.5244453
col8 col9 col10 col11 col12 col13 col14
row1 1.222956 1.581396 1.231962 -0.5116294 1.045862 0.7279804 -1.56136
col15 col16 col17 col18 col19 col20
row1 -0.6802379 -1.561992 0.04562171 0.5538328 0.1396905 0.6881067
> tmp[,"col10"]
col10
row1 1.2319623
row2 0.4036945
row3 -0.8477034
row4 1.6756424
row5 0.7273867
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.508614 0.1030961 -1.825447 -0.8141932 -1.4154139 -0.8298429 0.5244453
row5 -1.070638 2.2883839 -0.505168 0.4445116 0.1471005 -0.2828860 1.6801002
col8 col9 col10 col11 col12 col13 col14
row1 1.222956 1.5813963 1.2319623 -0.5116294 1.0458623 0.7279804 -1.5613599
row5 1.274876 -0.3304029 0.7273867 -2.3444612 -0.8014333 -1.7468185 -0.9076491
col15 col16 col17 col18 col19 col20
row1 -0.6802379 -1.561992 0.04562171 0.5538328 0.1396905 0.6881067
row5 -2.4409695 1.088378 0.12687050 1.7959023 -0.8692399 0.2057218
> tmp[,c("col6","col20")]
col6 col20
row1 -0.82984287 0.6881067
row2 0.08463126 -0.3087404
row3 0.45064632 0.6995727
row4 0.43437638 -1.3517067
row5 -0.28288600 0.2057218
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.8298429 0.6881067
row5 -0.2828860 0.2057218
>
>
>
>
> 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 52.41735 49.73423 49.31513 49.85867 50.29232 103.9246 49.78368 49.80203
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.66016 49.41134 50.35758 49.42957 50.25178 50.81186 48.85473 51.9175
col17 col18 col19 col20
row1 51.40701 49.29607 49.92546 105.2377
> tmp[,"col10"]
col10
row1 49.41134
row2 29.58942
row3 30.36471
row4 27.22378
row5 49.56894
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 52.41735 49.73423 49.31513 49.85867 50.29232 103.9246 49.78368 49.80203
row5 50.86983 48.18892 49.97584 50.79579 48.30807 102.0098 49.82475 52.16179
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.66016 49.41134 50.35758 49.42957 50.25178 50.81186 48.85473 51.91750
row5 50.91639 49.56894 49.82666 50.36584 49.92412 50.04708 49.62806 48.33733
col17 col18 col19 col20
row1 51.40701 49.29607 49.92546 105.2377
row5 51.95326 50.09711 49.59898 105.8252
> tmp[,c("col6","col20")]
col6 col20
row1 103.92455 105.23775
row2 74.32994 74.72397
row3 73.87529 74.13883
row4 76.54249 74.52527
row5 102.00977 105.82516
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 103.9246 105.2377
row5 102.0098 105.8252
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 103.9246 105.2377
row5 102.0098 105.8252
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.7676317
[2,] 0.7070225
[3,] 0.2753674
[4,] 0.1302856
[5,] 1.0530048
> tmp[,c("col17","col7")]
col17 col7
[1,] -2.2444939 1.3262847
[2,] 0.8272759 -1.3697151
[3,] 0.1246638 0.5208886
[4,] -0.5526798 -0.1331786
[5,] -0.1537687 1.3663920
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.4855981 0.2300065
[2,] -1.7547542 1.3412385
[3,] -0.4559814 0.4723153
[4,] -2.1935195 1.2817778
[5,] 0.3432001 -0.7089019
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.4855981
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.4855981
[2,] -1.7547542
>
>
>
> 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 0.5423135 -0.9461761 1.8958207 1.2473325 0.2422181 1.699365 1.8039121
row1 -0.6311675 0.8992552 -0.4440485 -0.8320124 0.3898944 -1.681252 0.7221386
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -1.090892 -0.8410418 -1.155481 0.7256745 -1.6634507 0.3693888 -0.9287949
row1 -1.535923 1.2298581 2.667963 -1.6739743 0.4065139 -1.9398092 1.2798959
[,15] [,16] [,17] [,18] [,19] [,20]
row3 2.5218938 0.8630465 -0.6066056 0.6361333 1.0572751 0.9216200
row1 -0.3029602 0.0603353 -0.8968403 -0.9324005 0.2682666 0.1061076
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -2.30846 0.7493087 -0.4376324 1.157499 -1.388094 -1.046154 -2.153563
[,8] [,9] [,10]
row2 1.675165 0.4468554 -1.459784
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.6886257 -1.106123 -1.181367 0.5433356 1.404144 -0.07018226 0.7342028
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.8754357 -2.038122 -0.4106552 -1.124286 0.5528438 1.127444 0.1618548
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.3469708 -0.239986 -1.315981 0.7440951 0.2218815 0.05019753
>
>
> 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: 0x600001e98240>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1675a3350329b"
[2] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1675a562a786e"
[3] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1675a7e48a9f3"
[4] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1675a548dd14a"
[5] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1675a2aa77ca4"
[6] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1675a59e808dc"
[7] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1675a109dd1a1"
[8] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1675a692da98c"
[9] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1675a34d65c46"
[10] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1675a654412c3"
[11] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1675a582bf425"
[12] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1675a2da9d65c"
[13] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1675a6938496f"
[14] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1675a6e5d4c60"
[15] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1675a2f416b3b"
>
>
> ### 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: 0x600001e9c360>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600001e9c360>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600001e9c360>
> rowMedians(tmp)
[1] 5.609813e-03 4.683146e-01 -3.534943e-01 7.347045e-02 5.738536e-01
[6] -3.699313e-01 1.839480e-01 -1.431220e-01 -1.081819e-01 -5.949811e-01
[11] 3.189802e-01 -1.974214e-01 -3.050131e-01 2.053821e-01 5.367521e-03
[16] -2.931159e-01 1.872894e-01 2.386491e-01 -8.663741e-01 -2.439150e-01
[21] 1.766192e-01 1.190719e-01 -2.751320e-01 -1.606341e-01 1.272599e-01
[26] -7.003901e-01 1.313638e-01 4.780114e-01 2.091577e-01 -3.385928e-02
[31] -2.744178e-02 1.686945e-01 -2.000826e-01 1.557657e-01 -1.788178e-02
[36] -3.907677e-01 4.109249e-01 -1.226066e-01 2.354266e-01 -2.171253e-02
[41] 3.709545e-02 -5.844089e-01 2.708350e-03 -1.832759e-01 1.383790e-01
[46] 2.407698e-01 2.132010e-01 5.795934e-01 -4.323857e-01 -1.754009e-01
[51] -9.931905e-02 8.009665e-01 5.025878e-01 -2.807147e-02 1.849991e-01
[56] -2.163908e-01 4.057743e-01 -3.290788e-01 3.502764e-01 1.008198e-01
[61] -7.159544e-01 4.150298e-01 2.106435e-01 -3.751358e-01 -4.780225e-02
[66] 3.019222e-01 -2.106875e-01 4.774662e-01 -1.560974e-01 4.362659e-01
[71] 5.619344e-01 -4.767743e-01 -1.110469e-01 1.322407e-01 -5.470401e-01
[76] 1.547931e-01 4.546808e-02 -1.158782e-01 -3.805596e-03 -5.187389e-02
[81] 2.469205e-01 -1.510033e-01 4.242293e-01 1.008951e-01 -6.205037e-01
[86] -1.651009e-01 3.379535e-02 -2.201579e-01 1.609646e-01 4.589557e-01
[91] 3.175785e-01 -1.399358e-01 2.051104e-01 1.470616e-01 1.028259e-02
[96] 2.760727e-01 1.471593e-01 -1.302868e-01 5.811882e-02 -4.891921e-01
[101] -2.308092e-01 1.210032e-01 -4.257086e-01 5.526209e-01 1.555280e-04
[106] -1.554664e-01 -3.830619e-02 3.163847e-03 -7.964077e-02 -5.020799e-01
[111] 2.410308e-01 -1.803069e-01 5.009058e-01 -1.947808e-01 6.340195e-02
[116] 2.854923e-01 -5.122548e-01 -1.889110e-01 -2.436122e-01 2.731705e-01
[121] 4.761594e-01 -8.219631e-01 4.302769e-01 3.193384e-01 -1.805633e-01
[126] -4.194987e-01 7.058658e-03 1.976129e-01 -1.267063e-01 1.173301e-01
[131] 2.008661e-01 4.484038e-01 -3.249720e-02 4.287093e-01 5.307598e-01
[136] 1.477048e-03 4.475830e-02 6.451036e-01 1.605835e-01 3.261747e-01
[141] 4.659357e-01 3.805276e-02 1.211170e-02 -2.938640e-01 3.098403e-01
[146] 7.985598e-02 1.619994e-01 -4.609226e-01 -2.113510e-02 -3.633489e-01
[151] -2.017599e-01 7.779958e-02 4.988984e-01 -1.534901e-01 1.024386e-02
[156] -1.910156e-01 4.913351e-02 3.108258e-02 2.235128e-02 3.003329e-01
[161] 4.314318e-01 -1.557990e-01 9.127393e-02 -1.777262e-01 -2.628618e-01
[166] -1.037123e-01 3.737634e-01 -2.557882e-02 9.674434e-02 4.064030e-01
[171] -1.316567e-02 -1.188477e-01 -2.171752e-01 6.493546e-03 -9.483416e-02
[176] -3.632134e-01 -1.872171e-02 -2.240749e-01 -2.195324e-01 1.196487e-01
[181] -2.988321e-01 1.701951e-01 -3.380518e-01 -3.557539e-01 6.542758e-02
[186] 3.409734e-01 -3.766564e-01 2.220831e-01 -3.869482e-02 2.189042e-02
[191] -8.921066e-02 -2.645990e-01 1.033695e+00 -3.432739e-01 3.982259e-01
[196] -2.196775e-01 -5.999315e-01 -3.229775e-01 2.334169e-01 -1.717136e-01
[201] 2.275570e-03 -5.096761e-01 2.003986e-01 3.532284e-01 -3.871698e-01
[206] -1.018290e-01 2.323324e-01 -4.828175e-01 -4.863469e-01 -4.367393e-01
[211] 6.095269e-01 2.896509e-01 -1.884716e-01 1.068460e-01 -1.953327e-01
[216] 5.358139e-01 -5.030143e-02 -2.283322e-01 -6.629588e-01 -1.079681e-01
[221] 2.358782e-01 1.834405e-01 5.579471e-01 9.932126e-02 -2.961307e-01
[226] -2.557970e-01 6.816931e-05 -9.141906e-02 4.431814e-01 -5.973332e-01
>
> proc.time()
user system elapsed
0.617 2.653 3.448
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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: 0x6000034000c0>
> .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: 0x6000034000c0>
> .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: 0x6000034000c0>
> .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: 0x6000034000c0>
> 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: 0x60000341c360>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000341c360>
> .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: 0x60000341c360>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000341c360>
> .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: 0x60000341c360>
> 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: 0x60000341c540>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000341c540>
> .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: 0x60000341c540>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x60000341c540>
> .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: 0x60000341c540>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x60000341c540>
> .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: 0x60000341c540>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x60000341c540>
> .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: 0x60000341c540>
> 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: 0x60000341c720>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x60000341c720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000341c720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000341c720>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1678a5d45b512" "BufferedMatrixFile1678ab72e095"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1678a5d45b512" "BufferedMatrixFile1678ab72e095"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000341c9c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000341c9c0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x60000341c9c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x60000341c9c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x60000341c9c0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x60000341c9c0>
> .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: 0x60000341cba0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000341cba0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x60000341cba0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x60000341cba0>
> 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: 0x60000341cd80>
> .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: 0x60000341cd80>
> rm(P)
>
> proc.time()
user system elapsed
0.112 0.038 0.147
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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.
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Type 'contributors()' for more information and
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Type 'demo()' for some demos, 'help()' for on-line help, or
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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
0.113 0.025 0.133