Ben Bolstad
| Snapshot Date: 2025-01-30 13:00 -0500 (Thu, 30 Jan 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_20 |
| git_last_commit: 32b6f6a |
| git_last_commit_date: 2024-10-29 09:27:20 -0500 (Tue, 29 Oct 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2025-02-03 12:08 -0500 (Mon, 03 Feb 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4746 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves" | 4494 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4517 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4469 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4400 |
| 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 251/2289 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.70.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / 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: 1.70.0 |
| 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_1.70.0.tar.gz |
| StartedAt: 2025-01-31 01:05:13 -0500 (Fri, 31 Jan 2025) |
| EndedAt: 2025-01-31 01:06:27 -0500 (Fri, 31 Jan 2025) |
| EllapsedTime: 73.8 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_1.70.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.2 (2024-10-31)
* using platform: x86_64-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 Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.70.0’
* 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 14.0.0 (clang-1400.0.29.202)’
* 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-x86_64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
using SDK: ‘MacOSX11.3.sdk’
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/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 x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch x86_64 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/x86_64/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-x86_64/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 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-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
0.605 0.210 0.777
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-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 474188 25.4 1035498 55.4 NA 638648 34.2
Vcells 877698 6.7 8388608 64.0 65536 2071806 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 Jan 31 01:05:48 2025"
> 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 Jan 31 01:05:49 2025"
>
>
> 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: 0x6000009ac060>
>
>
>
> 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 Jan 31 01:05:54 2025"
> 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 Jan 31 01:05:57 2025"
>
> ColMode(tmp2)
<pointer: 0x6000009ac060>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.40109382 0.7667181 0.1118341 0.2566417
[2,] -1.76121021 -2.8725052 0.7861995 0.1651743
[3,] 0.16952454 -1.8967185 -1.4878945 1.5165697
[4,] 0.01780464 -0.2917186 -1.5327044 -0.7238497
> 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,] 99.40109382 0.7667181 0.1118341 0.2566417
[2,] 1.76121021 2.8725052 0.7861995 0.1651743
[3,] 0.16952454 1.8967185 1.4878945 1.5165697
[4,] 0.01780464 0.2917186 1.5327044 0.7238497
> 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,] 9.9700097 0.8756244 0.3344160 0.5065982
[2,] 1.3271060 1.6948467 0.8866789 0.4064164
[3,] 0.4117336 1.3772141 1.2197928 1.2314909
[4,] 0.1334340 0.5401098 1.2380244 0.8507936
>
> 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,] 224.10119 34.52296 28.45599 30.32262
[2,] 40.03227 44.82097 34.65299 29.22934
[3,] 29.28686 40.66886 38.68582 38.83148
[4,] 26.35214 30.69282 38.91295 34.23179
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000009e8000>
> exp(tmp5)
<pointer: 0x6000009e8000>
> log(tmp5,2)
<pointer: 0x6000009e8000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.4373
> Min(tmp5)
[1] 54.5743
> mean(tmp5)
[1] 74.13189
> Sum(tmp5)
[1] 14826.38
> Var(tmp5)
[1] 846.0419
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 88.69606 74.64528 71.34859 70.31180 72.99878 72.41311 73.28473 70.70273
[9] 71.87143 75.04637
> rowSums(tmp5)
[1] 1773.921 1492.906 1426.972 1406.236 1459.976 1448.262 1465.695 1414.055
[9] 1437.429 1500.927
> rowVars(tmp5)
[1] 7953.89450 88.21195 85.91925 92.18273 72.41483 75.12752
[7] 47.78549 71.06342 72.10262 31.54711
> rowSd(tmp5)
[1] 89.184609 9.392122 9.269264 9.601184 8.509691 8.667613 6.912705
[8] 8.429912 8.491326 5.616682
> rowMax(tmp5)
[1] 466.43727 93.28898 84.64690 92.66064 85.63042 92.64295 85.84160
[8] 89.58841 92.08510 85.35492
> rowMin(tmp5)
[1] 59.22742 60.83704 55.15033 54.84854 54.57430 59.87022 61.98310 55.92018
[9] 58.17361 62.87499
>
> colMeans(tmp5)
[1] 109.00442 73.55747 75.04845 68.19845 73.02784 75.59421 72.85807
[8] 69.44041 72.62539 70.91033 71.20048 72.55994 72.90818 73.47740
[15] 75.93577 71.30800 72.00481 71.15259 70.38477 71.44082
> colSums(tmp5)
[1] 1090.0442 735.5747 750.4845 681.9845 730.2784 755.9421 728.5807
[8] 694.4041 726.2539 709.1033 712.0048 725.5994 729.0818 734.7740
[15] 759.3577 713.0800 720.0481 711.5259 703.8477 714.4082
> colVars(tmp5)
[1] 15859.14087 108.00363 70.49170 117.69723 41.70224 71.97642
[7] 91.64133 75.64354 100.07515 52.93195 84.18713 44.76031
[13] 75.29833 44.20477 83.68532 76.00949 58.25578 57.13861
[19] 56.04901 36.91159
> colSd(tmp5)
[1] 125.933081 10.392480 8.395933 10.848836 6.457727 8.483892
[7] 9.572948 8.697330 10.003757 7.275435 9.175354 6.690315
[13] 8.677461 6.648667 9.147968 8.718342 7.632547 7.559008
[19] 7.486589 6.075491
> colMax(tmp5)
[1] 466.43727 93.28898 89.58841 92.08510 86.12371 92.66064 88.14706
[8] 79.71756 92.64295 83.98631 81.38103 81.37866 83.00820 80.82709
[15] 85.63042 85.33800 85.89127 83.69696 83.18150 81.42478
> colMin(tmp5)
[1] 54.84854 58.42012 59.22742 55.92018 64.91520 61.46377 60.88224 55.15033
[9] 60.50323 57.80794 54.57430 59.87022 62.57588 60.08964 59.78632 57.92096
[17] 58.19338 57.07897 62.37267 63.85469
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 88.69606 74.64528 71.34859 70.31180 72.99878 NA 73.28473 70.70273
[9] 71.87143 75.04637
> rowSums(tmp5)
[1] 1773.921 1492.906 1426.972 1406.236 1459.976 NA 1465.695 1414.055
[9] 1437.429 1500.927
> rowVars(tmp5)
[1] 7953.89450 88.21195 85.91925 92.18273 72.41483 79.23837
[7] 47.78549 71.06342 72.10262 31.54711
> rowSd(tmp5)
[1] 89.184609 9.392122 9.269264 9.601184 8.509691 8.901594 6.912705
[8] 8.429912 8.491326 5.616682
> rowMax(tmp5)
[1] 466.43727 93.28898 84.64690 92.66064 85.63042 NA 85.84160
[8] 89.58841 92.08510 85.35492
> rowMin(tmp5)
[1] 59.22742 60.83704 55.15033 54.84854 54.57430 NA 61.98310 55.92018
[9] 58.17361 62.87499
>
> colMeans(tmp5)
[1] 109.00442 NA 75.04845 68.19845 73.02784 75.59421 72.85807
[8] 69.44041 72.62539 70.91033 71.20048 72.55994 72.90818 73.47740
[15] 75.93577 71.30800 72.00481 71.15259 70.38477 71.44082
> colSums(tmp5)
[1] 1090.0442 NA 750.4845 681.9845 730.2784 755.9421 728.5807
[8] 694.4041 726.2539 709.1033 712.0048 725.5994 729.0818 734.7740
[15] 759.3577 713.0800 720.0481 711.5259 703.8477 714.4082
> colVars(tmp5)
[1] 15859.14087 NA 70.49170 117.69723 41.70224 71.97642
[7] 91.64133 75.64354 100.07515 52.93195 84.18713 44.76031
[13] 75.29833 44.20477 83.68532 76.00949 58.25578 57.13861
[19] 56.04901 36.91159
> colSd(tmp5)
[1] 125.933081 NA 8.395933 10.848836 6.457727 8.483892
[7] 9.572948 8.697330 10.003757 7.275435 9.175354 6.690315
[13] 8.677461 6.648667 9.147968 8.718342 7.632547 7.559008
[19] 7.486589 6.075491
> colMax(tmp5)
[1] 466.43727 NA 89.58841 92.08510 86.12371 92.66064 88.14706
[8] 79.71756 92.64295 83.98631 81.38103 81.37866 83.00820 80.82709
[15] 85.63042 85.33800 85.89127 83.69696 83.18150 81.42478
> colMin(tmp5)
[1] 54.84854 NA 59.22742 55.92018 64.91520 61.46377 60.88224 55.15033
[9] 60.50323 57.80794 54.57430 59.87022 62.57588 60.08964 59.78632 57.92096
[17] 58.19338 57.07897 62.37267 63.85469
>
> Max(tmp5,na.rm=TRUE)
[1] 466.4373
> Min(tmp5,na.rm=TRUE)
[1] 54.5743
> mean(tmp5,na.rm=TRUE)
[1] 74.14574
> Sum(tmp5,na.rm=TRUE)
[1] 14755
> Var(tmp5,na.rm=TRUE)
[1] 850.2762
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.69606 74.64528 71.34859 70.31180 72.99878 72.46770 73.28473 70.70273
[9] 71.87143 75.04637
> rowSums(tmp5,na.rm=TRUE)
[1] 1773.921 1492.906 1426.972 1406.236 1459.976 1376.886 1465.695 1414.055
[9] 1437.429 1500.927
> rowVars(tmp5,na.rm=TRUE)
[1] 7953.89450 88.21195 85.91925 92.18273 72.41483 79.23837
[7] 47.78549 71.06342 72.10262 31.54711
> rowSd(tmp5,na.rm=TRUE)
[1] 89.184609 9.392122 9.269264 9.601184 8.509691 8.901594 6.912705
[8] 8.429912 8.491326 5.616682
> rowMax(tmp5,na.rm=TRUE)
[1] 466.43727 93.28898 84.64690 92.66064 85.63042 92.64295 85.84160
[8] 89.58841 92.08510 85.35492
> rowMin(tmp5,na.rm=TRUE)
[1] 59.22742 60.83704 55.15033 54.84854 54.57430 59.87022 61.98310 55.92018
[9] 58.17361 62.87499
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.00442 73.79986 75.04845 68.19845 73.02784 75.59421 72.85807
[8] 69.44041 72.62539 70.91033 71.20048 72.55994 72.90818 73.47740
[15] 75.93577 71.30800 72.00481 71.15259 70.38477 71.44082
> colSums(tmp5,na.rm=TRUE)
[1] 1090.0442 664.1987 750.4845 681.9845 730.2784 755.9421 728.5807
[8] 694.4041 726.2539 709.1033 712.0048 725.5994 729.0818 734.7740
[15] 759.3577 713.0800 720.0481 711.5259 703.8477 714.4082
> colVars(tmp5,na.rm=TRUE)
[1] 15859.14087 120.84316 70.49170 117.69723 41.70224 71.97642
[7] 91.64133 75.64354 100.07515 52.93195 84.18713 44.76031
[13] 75.29833 44.20477 83.68532 76.00949 58.25578 57.13861
[19] 56.04901 36.91159
> colSd(tmp5,na.rm=TRUE)
[1] 125.933081 10.992869 8.395933 10.848836 6.457727 8.483892
[7] 9.572948 8.697330 10.003757 7.275435 9.175354 6.690315
[13] 8.677461 6.648667 9.147968 8.718342 7.632547 7.559008
[19] 7.486589 6.075491
> colMax(tmp5,na.rm=TRUE)
[1] 466.43727 93.28898 89.58841 92.08510 86.12371 92.66064 88.14706
[8] 79.71756 92.64295 83.98631 81.38103 81.37866 83.00820 80.82709
[15] 85.63042 85.33800 85.89127 83.69696 83.18150 81.42478
> colMin(tmp5,na.rm=TRUE)
[1] 54.84854 58.42012 59.22742 55.92018 64.91520 61.46377 60.88224 55.15033
[9] 60.50323 57.80794 54.57430 59.87022 62.57588 60.08964 59.78632 57.92096
[17] 58.19338 57.07897 62.37267 63.85469
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.69606 74.64528 71.34859 70.31180 72.99878 NaN 73.28473 70.70273
[9] 71.87143 75.04637
> rowSums(tmp5,na.rm=TRUE)
[1] 1773.921 1492.906 1426.972 1406.236 1459.976 0.000 1465.695 1414.055
[9] 1437.429 1500.927
> rowVars(tmp5,na.rm=TRUE)
[1] 7953.89450 88.21195 85.91925 92.18273 72.41483 NA
[7] 47.78549 71.06342 72.10262 31.54711
> rowSd(tmp5,na.rm=TRUE)
[1] 89.184609 9.392122 9.269264 9.601184 8.509691 NA 6.912705
[8] 8.429912 8.491326 5.616682
> rowMax(tmp5,na.rm=TRUE)
[1] 466.43727 93.28898 84.64690 92.66064 85.63042 NA 85.84160
[8] 89.58841 92.08510 85.35492
> rowMin(tmp5,na.rm=TRUE)
[1] 59.22742 60.83704 55.15033 54.84854 54.57430 NA 61.98310 55.92018
[9] 58.17361 62.87499
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.80971 NaN 75.68920 69.01543 72.41499 76.45585 71.15929
[8] 68.39148 70.40121 71.03971 70.06930 73.96991 72.08599 73.23230
[15] 76.95693 71.79862 72.05263 71.58123 70.24990 72.28372
> colSums(tmp5,na.rm=TRUE)
[1] 1024.2874 0.0000 681.2028 621.1388 651.7349 688.1026 640.4337
[8] 615.5233 633.6109 639.3574 630.6237 665.7292 648.7739 659.0907
[15] 692.6124 646.1876 648.4737 644.2310 632.2491 650.5535
> colVars(tmp5,na.rm=TRUE)
[1] 17581.76153 NA 74.68434 124.90051 42.68969 72.62121
[7] 70.63078 72.72121 56.93136 59.36010 80.31557 27.99019
[13] 77.10581 49.05452 82.41484 82.80272 65.51202 62.21399
[19] 62.85052 33.53257
> colSd(tmp5,na.rm=TRUE)
[1] 132.596235 NA 8.642010 11.175890 6.533735 8.521808
[7] 8.404212 8.527673 7.545287 7.704551 8.961896 5.290576
[13] 8.780992 7.003893 9.078262 9.099600 8.093950 7.887585
[19] 7.927832 5.790731
> colMax(tmp5,na.rm=TRUE)
[1] 466.43727 -Inf 89.58841 92.08510 86.12371 92.66064 81.36820
[8] 79.71756 85.84160 83.98631 79.63837 81.37866 83.00820 80.82709
[15] 85.63042 85.33800 85.89127 83.69696 83.18150 81.42478
> colMin(tmp5,na.rm=TRUE)
[1] 54.84854 Inf 59.22742 55.92018 64.91520 61.46377 60.88224 55.15033
[9] 60.50323 57.80794 54.57430 65.82516 62.57588 60.08964 59.78632 57.92096
[17] 58.19338 57.07897 62.37267 64.75112
>
>
>
>
> 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] 174.0976 226.9108 229.3542 231.2626 228.0810 410.4556 172.7842 136.5994
[9] 173.6182 169.0230
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 174.0976 226.9108 229.3542 231.2626 228.0810 410.4556 172.7842 136.5994
[9] 173.6182 169.0230
>
>
>
> 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] -1.421085e-13 5.684342e-14 2.842171e-14 2.842171e-14 5.684342e-14
[6] -1.136868e-13 1.705303e-13 -1.136868e-13 0.000000e+00 -5.684342e-14
[11] -5.684342e-14 1.136868e-13 0.000000e+00 -1.989520e-13 2.842171e-14
[16] -1.136868e-13 1.705303e-13 2.273737e-13 -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 18
9 15
5 20
1 17
1 13
1 2
4 10
1 15
7 9
9 11
9 15
8 3
3 5
7 20
4 5
4 4
5 20
10 19
9 2
6 1
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.168072
> Min(tmp)
[1] -3.076789
> mean(tmp)
[1] 0.000905321
> Sum(tmp)
[1] 0.0905321
> Var(tmp)
[1] 0.9986644
>
> rowMeans(tmp)
[1] 0.000905321
> rowSums(tmp)
[1] 0.0905321
> rowVars(tmp)
[1] 0.9986644
> rowSd(tmp)
[1] 0.999332
> rowMax(tmp)
[1] 2.168072
> rowMin(tmp)
[1] -3.076789
>
> colMeans(tmp)
[1] 0.31584166 -1.34706563 0.11797790 -0.12290108 0.12108604 0.22928478
[7] 1.05445253 -0.07501307 -1.96177283 2.00835482 -0.30707781 -1.76737039
[13] 0.82426346 -0.36973939 -1.39535626 -0.50273001 -0.31333500 0.91015474
[19] -0.61834530 1.55601046 -0.51758874 -0.20427193 -0.16088334 0.43984927
[25] -1.05711848 0.59212020 -0.88505163 0.53916856 -0.35009594 -0.36410632
[31] 0.03643529 1.15527639 -0.56723681 0.61855126 1.79181778 0.74139169
[37] -0.63701440 -1.67359382 -0.26282335 -0.69719639 -0.53852576 -0.92368667
[43] 0.03880473 0.43462750 -0.57327009 1.77368416 -0.55790494 0.46932342
[49] 1.22228735 -1.14855189 1.09723281 -0.04089823 -0.98791600 2.14684310
[55] 0.21930567 2.16807176 -0.81920899 -0.23144014 -1.54124861 0.09588024
[61] -2.10034136 0.28344118 -0.71304790 0.24320960 0.31811038 0.27582260
[67] 0.13304339 -0.99679120 -0.32644417 -0.13919672 0.26267859 0.10369423
[73] -0.09617312 0.56915478 1.41971446 -0.85070626 0.58284002 2.07566258
[79] 0.07775094 0.12006163 -0.46713536 1.14828390 0.23018777 0.57780694
[85] -0.38077567 -3.07678922 -0.81520769 1.39412524 0.53301149 -2.23735606
[91] 0.47842743 0.10464003 1.75908093 -0.34574284 0.01693206 -0.39688501
[97] 0.39756824 0.10360638 -1.20320609 1.82971763
> colSums(tmp)
[1] 0.31584166 -1.34706563 0.11797790 -0.12290108 0.12108604 0.22928478
[7] 1.05445253 -0.07501307 -1.96177283 2.00835482 -0.30707781 -1.76737039
[13] 0.82426346 -0.36973939 -1.39535626 -0.50273001 -0.31333500 0.91015474
[19] -0.61834530 1.55601046 -0.51758874 -0.20427193 -0.16088334 0.43984927
[25] -1.05711848 0.59212020 -0.88505163 0.53916856 -0.35009594 -0.36410632
[31] 0.03643529 1.15527639 -0.56723681 0.61855126 1.79181778 0.74139169
[37] -0.63701440 -1.67359382 -0.26282335 -0.69719639 -0.53852576 -0.92368667
[43] 0.03880473 0.43462750 -0.57327009 1.77368416 -0.55790494 0.46932342
[49] 1.22228735 -1.14855189 1.09723281 -0.04089823 -0.98791600 2.14684310
[55] 0.21930567 2.16807176 -0.81920899 -0.23144014 -1.54124861 0.09588024
[61] -2.10034136 0.28344118 -0.71304790 0.24320960 0.31811038 0.27582260
[67] 0.13304339 -0.99679120 -0.32644417 -0.13919672 0.26267859 0.10369423
[73] -0.09617312 0.56915478 1.41971446 -0.85070626 0.58284002 2.07566258
[79] 0.07775094 0.12006163 -0.46713536 1.14828390 0.23018777 0.57780694
[85] -0.38077567 -3.07678922 -0.81520769 1.39412524 0.53301149 -2.23735606
[91] 0.47842743 0.10464003 1.75908093 -0.34574284 0.01693206 -0.39688501
[97] 0.39756824 0.10360638 -1.20320609 1.82971763
> 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] 0.31584166 -1.34706563 0.11797790 -0.12290108 0.12108604 0.22928478
[7] 1.05445253 -0.07501307 -1.96177283 2.00835482 -0.30707781 -1.76737039
[13] 0.82426346 -0.36973939 -1.39535626 -0.50273001 -0.31333500 0.91015474
[19] -0.61834530 1.55601046 -0.51758874 -0.20427193 -0.16088334 0.43984927
[25] -1.05711848 0.59212020 -0.88505163 0.53916856 -0.35009594 -0.36410632
[31] 0.03643529 1.15527639 -0.56723681 0.61855126 1.79181778 0.74139169
[37] -0.63701440 -1.67359382 -0.26282335 -0.69719639 -0.53852576 -0.92368667
[43] 0.03880473 0.43462750 -0.57327009 1.77368416 -0.55790494 0.46932342
[49] 1.22228735 -1.14855189 1.09723281 -0.04089823 -0.98791600 2.14684310
[55] 0.21930567 2.16807176 -0.81920899 -0.23144014 -1.54124861 0.09588024
[61] -2.10034136 0.28344118 -0.71304790 0.24320960 0.31811038 0.27582260
[67] 0.13304339 -0.99679120 -0.32644417 -0.13919672 0.26267859 0.10369423
[73] -0.09617312 0.56915478 1.41971446 -0.85070626 0.58284002 2.07566258
[79] 0.07775094 0.12006163 -0.46713536 1.14828390 0.23018777 0.57780694
[85] -0.38077567 -3.07678922 -0.81520769 1.39412524 0.53301149 -2.23735606
[91] 0.47842743 0.10464003 1.75908093 -0.34574284 0.01693206 -0.39688501
[97] 0.39756824 0.10360638 -1.20320609 1.82971763
> colMin(tmp)
[1] 0.31584166 -1.34706563 0.11797790 -0.12290108 0.12108604 0.22928478
[7] 1.05445253 -0.07501307 -1.96177283 2.00835482 -0.30707781 -1.76737039
[13] 0.82426346 -0.36973939 -1.39535626 -0.50273001 -0.31333500 0.91015474
[19] -0.61834530 1.55601046 -0.51758874 -0.20427193 -0.16088334 0.43984927
[25] -1.05711848 0.59212020 -0.88505163 0.53916856 -0.35009594 -0.36410632
[31] 0.03643529 1.15527639 -0.56723681 0.61855126 1.79181778 0.74139169
[37] -0.63701440 -1.67359382 -0.26282335 -0.69719639 -0.53852576 -0.92368667
[43] 0.03880473 0.43462750 -0.57327009 1.77368416 -0.55790494 0.46932342
[49] 1.22228735 -1.14855189 1.09723281 -0.04089823 -0.98791600 2.14684310
[55] 0.21930567 2.16807176 -0.81920899 -0.23144014 -1.54124861 0.09588024
[61] -2.10034136 0.28344118 -0.71304790 0.24320960 0.31811038 0.27582260
[67] 0.13304339 -0.99679120 -0.32644417 -0.13919672 0.26267859 0.10369423
[73] -0.09617312 0.56915478 1.41971446 -0.85070626 0.58284002 2.07566258
[79] 0.07775094 0.12006163 -0.46713536 1.14828390 0.23018777 0.57780694
[85] -0.38077567 -3.07678922 -0.81520769 1.39412524 0.53301149 -2.23735606
[91] 0.47842743 0.10464003 1.75908093 -0.34574284 0.01693206 -0.39688501
[97] 0.39756824 0.10360638 -1.20320609 1.82971763
> colMedians(tmp)
[1] 0.31584166 -1.34706563 0.11797790 -0.12290108 0.12108604 0.22928478
[7] 1.05445253 -0.07501307 -1.96177283 2.00835482 -0.30707781 -1.76737039
[13] 0.82426346 -0.36973939 -1.39535626 -0.50273001 -0.31333500 0.91015474
[19] -0.61834530 1.55601046 -0.51758874 -0.20427193 -0.16088334 0.43984927
[25] -1.05711848 0.59212020 -0.88505163 0.53916856 -0.35009594 -0.36410632
[31] 0.03643529 1.15527639 -0.56723681 0.61855126 1.79181778 0.74139169
[37] -0.63701440 -1.67359382 -0.26282335 -0.69719639 -0.53852576 -0.92368667
[43] 0.03880473 0.43462750 -0.57327009 1.77368416 -0.55790494 0.46932342
[49] 1.22228735 -1.14855189 1.09723281 -0.04089823 -0.98791600 2.14684310
[55] 0.21930567 2.16807176 -0.81920899 -0.23144014 -1.54124861 0.09588024
[61] -2.10034136 0.28344118 -0.71304790 0.24320960 0.31811038 0.27582260
[67] 0.13304339 -0.99679120 -0.32644417 -0.13919672 0.26267859 0.10369423
[73] -0.09617312 0.56915478 1.41971446 -0.85070626 0.58284002 2.07566258
[79] 0.07775094 0.12006163 -0.46713536 1.14828390 0.23018777 0.57780694
[85] -0.38077567 -3.07678922 -0.81520769 1.39412524 0.53301149 -2.23735606
[91] 0.47842743 0.10464003 1.75908093 -0.34574284 0.01693206 -0.39688501
[97] 0.39756824 0.10360638 -1.20320609 1.82971763
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.3158417 -1.347066 0.1179779 -0.1229011 0.121086 0.2292848 1.054453
[2,] 0.3158417 -1.347066 0.1179779 -0.1229011 0.121086 0.2292848 1.054453
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.07501307 -1.961773 2.008355 -0.3070778 -1.76737 0.8242635 -0.3697394
[2,] -0.07501307 -1.961773 2.008355 -0.3070778 -1.76737 0.8242635 -0.3697394
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.395356 -0.50273 -0.313335 0.9101547 -0.6183453 1.55601 -0.5175887
[2,] -1.395356 -0.50273 -0.313335 0.9101547 -0.6183453 1.55601 -0.5175887
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.2042719 -0.1608833 0.4398493 -1.057118 0.5921202 -0.8850516 0.5391686
[2,] -0.2042719 -0.1608833 0.4398493 -1.057118 0.5921202 -0.8850516 0.5391686
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.3500959 -0.3641063 0.03643529 1.155276 -0.5672368 0.6185513 1.791818
[2,] -0.3500959 -0.3641063 0.03643529 1.155276 -0.5672368 0.6185513 1.791818
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.7413917 -0.6370144 -1.673594 -0.2628233 -0.6971964 -0.5385258 -0.9236867
[2,] 0.7413917 -0.6370144 -1.673594 -0.2628233 -0.6971964 -0.5385258 -0.9236867
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.03880473 0.4346275 -0.5732701 1.773684 -0.5579049 0.4693234 1.222287
[2,] 0.03880473 0.4346275 -0.5732701 1.773684 -0.5579049 0.4693234 1.222287
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -1.148552 1.097233 -0.04089823 -0.987916 2.146843 0.2193057 2.168072
[2,] -1.148552 1.097233 -0.04089823 -0.987916 2.146843 0.2193057 2.168072
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.819209 -0.2314401 -1.541249 0.09588024 -2.100341 0.2834412 -0.7130479
[2,] -0.819209 -0.2314401 -1.541249 0.09588024 -2.100341 0.2834412 -0.7130479
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.2432096 0.3181104 0.2758226 0.1330434 -0.9967912 -0.3264442 -0.1391967
[2,] 0.2432096 0.3181104 0.2758226 0.1330434 -0.9967912 -0.3264442 -0.1391967
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.2626786 0.1036942 -0.09617312 0.5691548 1.419714 -0.8507063 0.58284
[2,] 0.2626786 0.1036942 -0.09617312 0.5691548 1.419714 -0.8507063 0.58284
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 2.075663 0.07775094 0.1200616 -0.4671354 1.148284 0.2301878 0.5778069
[2,] 2.075663 0.07775094 0.1200616 -0.4671354 1.148284 0.2301878 0.5778069
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.3807757 -3.076789 -0.8152077 1.394125 0.5330115 -2.237356 0.4784274
[2,] -0.3807757 -3.076789 -0.8152077 1.394125 0.5330115 -2.237356 0.4784274
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.10464 1.759081 -0.3457428 0.01693206 -0.396885 0.3975682 0.1036064
[2,] 0.10464 1.759081 -0.3457428 0.01693206 -0.396885 0.3975682 0.1036064
[,99] [,100]
[1,] -1.203206 1.829718
[2,] -1.203206 1.829718
>
>
> Max(tmp2)
[1] 3.496302
> Min(tmp2)
[1] -2.401619
> mean(tmp2)
[1] 0.1465052
> Sum(tmp2)
[1] 14.65052
> Var(tmp2)
[1] 1.150997
>
> rowMeans(tmp2)
[1] -0.03369427 -0.60900211 0.50864228 1.86665486 -0.24551951 0.44615774
[7] 0.58434888 0.84565735 0.16644485 0.64506003 -0.32556639 -1.32480588
[13] 0.59571035 0.47930424 1.23687777 -1.01577412 -0.72835987 3.49630191
[19] -1.00215451 1.16102693 -0.16151421 1.30020975 -0.49215812 -1.49607200
[25] 1.61739934 0.86978319 -1.39460106 -0.27061197 -0.60412740 0.36714687
[31] 2.33073673 1.92423464 -1.71429594 0.21724189 0.76271965 0.22776479
[37] 1.64414545 -0.04509089 -0.04346811 0.61502464 -0.88776808 -0.87743036
[43] 1.15438358 -1.58777184 0.61684341 0.53917571 1.50817040 -0.71231661
[49] -0.00677138 -0.21739234 -0.95150892 0.50500463 -1.10700556 0.64265369
[55] 2.33564380 -0.88917155 0.57540460 0.69022968 -0.66299703 1.13481063
[61] 1.29747507 1.32459972 1.06531548 0.88921293 -0.40312233 -1.48656849
[67] -1.60437715 0.67267591 0.18680646 -0.61295595 -1.44425729 0.23753987
[73] 0.72899432 -1.10299030 -0.03265478 -0.29327822 2.00008852 0.37812828
[79] 0.27520533 -0.34368992 -1.39148316 1.70121714 0.34717034 -1.55874684
[85] -0.76285110 0.57186374 -0.39870878 -1.20314457 -1.13940897 0.08392066
[91] -0.09509889 0.74002583 1.26565087 0.64887986 0.42151424 0.60014961
[97] 1.66239237 -0.98789648 -2.40161851 0.61057747
> rowSums(tmp2)
[1] -0.03369427 -0.60900211 0.50864228 1.86665486 -0.24551951 0.44615774
[7] 0.58434888 0.84565735 0.16644485 0.64506003 -0.32556639 -1.32480588
[13] 0.59571035 0.47930424 1.23687777 -1.01577412 -0.72835987 3.49630191
[19] -1.00215451 1.16102693 -0.16151421 1.30020975 -0.49215812 -1.49607200
[25] 1.61739934 0.86978319 -1.39460106 -0.27061197 -0.60412740 0.36714687
[31] 2.33073673 1.92423464 -1.71429594 0.21724189 0.76271965 0.22776479
[37] 1.64414545 -0.04509089 -0.04346811 0.61502464 -0.88776808 -0.87743036
[43] 1.15438358 -1.58777184 0.61684341 0.53917571 1.50817040 -0.71231661
[49] -0.00677138 -0.21739234 -0.95150892 0.50500463 -1.10700556 0.64265369
[55] 2.33564380 -0.88917155 0.57540460 0.69022968 -0.66299703 1.13481063
[61] 1.29747507 1.32459972 1.06531548 0.88921293 -0.40312233 -1.48656849
[67] -1.60437715 0.67267591 0.18680646 -0.61295595 -1.44425729 0.23753987
[73] 0.72899432 -1.10299030 -0.03265478 -0.29327822 2.00008852 0.37812828
[79] 0.27520533 -0.34368992 -1.39148316 1.70121714 0.34717034 -1.55874684
[85] -0.76285110 0.57186374 -0.39870878 -1.20314457 -1.13940897 0.08392066
[91] -0.09509889 0.74002583 1.26565087 0.64887986 0.42151424 0.60014961
[97] 1.66239237 -0.98789648 -2.40161851 0.61057747
> 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] -0.03369427 -0.60900211 0.50864228 1.86665486 -0.24551951 0.44615774
[7] 0.58434888 0.84565735 0.16644485 0.64506003 -0.32556639 -1.32480588
[13] 0.59571035 0.47930424 1.23687777 -1.01577412 -0.72835987 3.49630191
[19] -1.00215451 1.16102693 -0.16151421 1.30020975 -0.49215812 -1.49607200
[25] 1.61739934 0.86978319 -1.39460106 -0.27061197 -0.60412740 0.36714687
[31] 2.33073673 1.92423464 -1.71429594 0.21724189 0.76271965 0.22776479
[37] 1.64414545 -0.04509089 -0.04346811 0.61502464 -0.88776808 -0.87743036
[43] 1.15438358 -1.58777184 0.61684341 0.53917571 1.50817040 -0.71231661
[49] -0.00677138 -0.21739234 -0.95150892 0.50500463 -1.10700556 0.64265369
[55] 2.33564380 -0.88917155 0.57540460 0.69022968 -0.66299703 1.13481063
[61] 1.29747507 1.32459972 1.06531548 0.88921293 -0.40312233 -1.48656849
[67] -1.60437715 0.67267591 0.18680646 -0.61295595 -1.44425729 0.23753987
[73] 0.72899432 -1.10299030 -0.03265478 -0.29327822 2.00008852 0.37812828
[79] 0.27520533 -0.34368992 -1.39148316 1.70121714 0.34717034 -1.55874684
[85] -0.76285110 0.57186374 -0.39870878 -1.20314457 -1.13940897 0.08392066
[91] -0.09509889 0.74002583 1.26565087 0.64887986 0.42151424 0.60014961
[97] 1.66239237 -0.98789648 -2.40161851 0.61057747
> rowMin(tmp2)
[1] -0.03369427 -0.60900211 0.50864228 1.86665486 -0.24551951 0.44615774
[7] 0.58434888 0.84565735 0.16644485 0.64506003 -0.32556639 -1.32480588
[13] 0.59571035 0.47930424 1.23687777 -1.01577412 -0.72835987 3.49630191
[19] -1.00215451 1.16102693 -0.16151421 1.30020975 -0.49215812 -1.49607200
[25] 1.61739934 0.86978319 -1.39460106 -0.27061197 -0.60412740 0.36714687
[31] 2.33073673 1.92423464 -1.71429594 0.21724189 0.76271965 0.22776479
[37] 1.64414545 -0.04509089 -0.04346811 0.61502464 -0.88776808 -0.87743036
[43] 1.15438358 -1.58777184 0.61684341 0.53917571 1.50817040 -0.71231661
[49] -0.00677138 -0.21739234 -0.95150892 0.50500463 -1.10700556 0.64265369
[55] 2.33564380 -0.88917155 0.57540460 0.69022968 -0.66299703 1.13481063
[61] 1.29747507 1.32459972 1.06531548 0.88921293 -0.40312233 -1.48656849
[67] -1.60437715 0.67267591 0.18680646 -0.61295595 -1.44425729 0.23753987
[73] 0.72899432 -1.10299030 -0.03265478 -0.29327822 2.00008852 0.37812828
[79] 0.27520533 -0.34368992 -1.39148316 1.70121714 0.34717034 -1.55874684
[85] -0.76285110 0.57186374 -0.39870878 -1.20314457 -1.13940897 0.08392066
[91] -0.09509889 0.74002583 1.26565087 0.64887986 0.42151424 0.60014961
[97] 1.66239237 -0.98789648 -2.40161851 0.61057747
>
> colMeans(tmp2)
[1] 0.1465052
> colSums(tmp2)
[1] 14.65052
> colVars(tmp2)
[1] 1.150997
> colSd(tmp2)
[1] 1.072845
> colMax(tmp2)
[1] 3.496302
> colMin(tmp2)
[1] -2.401619
> colMedians(tmp2)
[1] 0.2326523
> colRanges(tmp2)
[,1]
[1,] -2.401619
[2,] 3.496302
>
> 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] 1.0649462 3.4294534 0.7640161 -4.5797370 1.3338610 -3.0918594
[7] 0.4833430 1.7570192 -0.6092687 -5.1950477
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.7905417
[2,] -0.4476338
[3,] 0.1695887
[4,] 0.5183192
[5,] 1.4584191
>
> rowApply(tmp,sum)
[1] -0.459545046 -2.910437407 2.598890378 -1.245360367 1.046900353
[6] -1.494363587 -0.002598101 -3.232185348 -4.767547071 5.822972272
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 7 2 9 7 7 9 4 6 3
[2,] 3 4 5 8 1 8 8 10 9 9
[3,] 10 10 6 1 3 6 2 8 4 8
[4,] 1 5 1 3 9 10 3 7 2 5
[5,] 5 9 7 2 2 5 6 3 10 2
[6,] 7 3 10 6 6 1 4 9 1 4
[7,] 4 1 9 5 10 3 7 2 7 10
[8,] 9 8 8 7 5 2 10 1 5 7
[9,] 6 2 4 10 4 4 5 5 3 6
[10,] 2 6 3 4 8 9 1 6 8 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.3912893 2.9434947 0.5276007 3.7521781 2.9444700 3.3057654
[7] 4.2067970 -2.7281613 0.8919778 1.9194459 -1.3037305 0.4505617
[13] -0.8996464 -6.5451342 0.8255337 -1.4252746 1.4109017 1.2252937
[19] 3.6876397 -0.8000301
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.6721152
[2,] -0.1123464
[3,] 0.2039108
[4,] 0.4391557
[5,] 0.5326845
>
> rowApply(tmp,sum)
[1] -3.037683 -1.046366 7.926771 2.649777 8.288473
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 14 6 13 7 8
[2,] 8 17 16 6 13
[3,] 1 14 11 17 19
[4,] 17 9 12 14 20
[5,] 19 2 15 19 14
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.5326845 -0.4196696 -2.5731983 1.2199006 1.4411538 -0.1474594
[2,] -0.6721152 1.1622096 0.3934965 -0.2361181 -1.8434163 1.1748680
[3,] 0.4391557 1.4229076 0.2423747 0.3109586 1.1158665 1.5751022
[4,] -0.1123464 -0.1466076 0.8684763 0.5643688 1.2545187 0.8222290
[5,] 0.2039108 0.9246547 1.5964514 1.8930682 0.9763473 -0.1189744
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.52585167 -0.2724484 1.4275822 -0.70042049 -0.8766277 0.26419105
[2,] 1.59162740 -0.9209030 -0.0033264 2.22810152 0.4355982 0.03333448
[3,] 2.00611138 -0.6766746 -0.4695960 -0.01091619 -0.5220429 -0.77262055
[4,] -0.95865127 0.2159487 0.1971605 0.05980212 0.2032907 -0.08784832
[5,] 0.04185781 -1.0740840 -0.2598426 0.34287893 -0.5439488 1.01350505
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.84141075 -1.2469942 0.9784564 -0.30449045 0.57852795 -1.4007375
[2,] -0.02796672 -2.2753621 -0.4391351 -1.10211124 0.34551497 -1.5180441
[3,] 0.94144552 -0.3544832 2.0139884 -0.63614160 -0.08648398 1.9639528
[4,] -0.95770948 -1.7726627 -0.7817757 -0.05549742 -0.24280977 0.9299409
[5,] 0.98599506 -0.8956319 -0.9460003 0.67296608 0.81615254 1.2501816
[,19] [,20]
[1,] -0.1207308 -1.1018440
[2,] 0.9714798 -0.3440978
[3,] -0.1195775 -0.4565555
[4,] 1.8501529 0.7997967
[5,] 1.1063152 0.3026706
>
>
> 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 : 654 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 : 567 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 -1.173791 0.2213536 -0.6695824 -1.425603 1.515941 1.144283 -0.9072211
col8 col9 col10 col11 col12 col13 col14
row1 0.3825877 -0.00343379 -0.84711 1.558746 1.22424 0.5295463 1.389692
col15 col16 col17 col18 col19 col20
row1 -1.584442 0.6162539 1.267855 -0.4809837 0.9025394 -0.2601774
> tmp[,"col10"]
col10
row1 -0.84711002
row2 0.67247620
row3 0.81558309
row4 -0.01029482
row5 1.10033048
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -1.173791 0.2213536 -0.6695824 -1.425603 1.515941 1.14428321 -0.9072211
row5 2.605872 -0.2419403 0.3673140 1.860869 2.482917 -0.04079292 1.5104464
col8 col9 col10 col11 col12 col13 col14
row1 0.3825877 -0.00343379 -0.84711 1.55874591 1.2242395 0.5295463 1.38969153
row5 -1.0692352 0.03935704 1.10033 0.03463183 0.8175941 1.4080439 -0.01540254
col15 col16 col17 col18 col19 col20
row1 -1.584442 0.6162539 1.267855 -0.48098370 0.9025394 -0.2601774
row5 1.412229 1.1052568 -1.157075 -0.03415738 -1.4811652 -2.0351000
> tmp[,c("col6","col20")]
col6 col20
row1 1.14428321 -0.2601774
row2 0.24790852 1.8745289
row3 2.13714790 -0.1064563
row4 -1.26651666 0.3851329
row5 -0.04079292 -2.0351000
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.14428321 -0.2601774
row5 -0.04079292 -2.0351000
>
>
>
>
> 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 51.35994 49.45725 48.74519 51.63349 49.9184 105.2527 50.68229 48.60967
col9 col10 col11 col12 col13 col14 col15 col16
row1 52.08714 50.28578 50.19235 49.89016 50.17375 50.71362 49.20359 51.55303
col17 col18 col19 col20
row1 49.14586 48.74252 50.76072 105.1393
> tmp[,"col10"]
col10
row1 50.28578
row2 31.47658
row3 27.99139
row4 30.57096
row5 49.46790
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.35994 49.45725 48.74519 51.63349 49.91840 105.2527 50.68229 48.60967
row5 50.10016 50.13652 49.22790 51.85583 48.51357 106.1204 48.65064 48.97123
col9 col10 col11 col12 col13 col14 col15 col16
row1 52.08714 50.28578 50.19235 49.89016 50.17375 50.71362 49.20359 51.55303
row5 50.58224 49.46790 51.04561 50.99505 48.96189 50.88558 49.24407 51.02854
col17 col18 col19 col20
row1 49.14586 48.74252 50.76072 105.1393
row5 51.14758 50.02800 50.02529 104.5385
> tmp[,c("col6","col20")]
col6 col20
row1 105.25273 105.13932
row2 74.05805 75.45233
row3 74.54777 76.04956
row4 74.42651 74.75591
row5 106.12041 104.53848
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.2527 105.1393
row5 106.1204 104.5385
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.2527 105.1393
row5 106.1204 104.5385
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.30853458
[2,] 0.01921497
[3,] 0.73576495
[4,] 0.93941601
[5,] -0.32328331
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.3287928 -1.4629174
[2,] 1.3900125 -0.7512128
[3,] 0.6440833 -0.6987924
[4,] 1.1666353 -0.4115590
[5,] -0.1321099 -1.4786945
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.02368839 0.11491248
[2,] -1.30335718 0.74157113
[3,] 1.03254435 0.01592299
[4,] 0.98554671 -0.10529343
[5,] 0.35306548 0.66041443
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.02368839
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.02368839
[2,] -1.30335718
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 0.7753327 0.9932798 0.4519947 0.2493966 0.04384383 0.22967301
row1 0.4836347 0.2953127 -0.1978570 0.1382698 -0.65627425 0.03983345
[,7] [,8] [,9] [,10] [,11] [,12]
row3 1.850751146 0.7744604 -0.09472114 -0.7863471 1.0276131 0.8110256
row1 -0.004710077 -0.4613547 -0.46354930 -1.5514840 -0.5221852 0.7404158
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 0.7240464 1.312150 1.8254825 0.2827228 0.2291070 0.9091678 0.3152264
row1 0.2408655 2.007475 -0.7886214 -0.5338842 0.8561593 -0.2105592 1.3912449
[,20]
row3 1.2636229
row1 -0.0398853
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.4488005 -0.7044277 0.3649677 0.5076806 -0.4948014 -1.246706 0.532642
[,8] [,9] [,10]
row2 -1.596635 -0.5887776 -0.9407633
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.794244 -1.055202 -0.6406438 1.272425 1.361207 1.890205 1.107314
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.926594 -0.2537485 0.6219015 1.590489 -0.796408 0.7752195 -0.4246286
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.4397104 -0.424762 0.1680598 0.09433879 -1.284084 -0.7784318
>
>
> 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: 0x600000994000>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM168f71745397e"
[2] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM168f741c18b21"
[3] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM168f79954541"
[4] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM168f726f5b351"
[5] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM168f74ccf9ed2"
[6] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM168f752c41463"
[7] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM168f747169a08"
[8] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM168f71cdaa7ae"
[9] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM168f757369f4e"
[10] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM168f74314e69d"
[11] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM168f711306fd3"
[12] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM168f72fd8e76"
[13] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM168f75493e682"
[14] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM168f73a028c2f"
[15] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM168f77d417f69"
>
>
> ### 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: 0x600000994060>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600000994060>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600000994060>
> rowMedians(tmp)
[1] -0.331414016 0.450925959 -0.333624288 0.055264038 0.038334134
[6] -0.120022841 0.571664960 -0.367674178 0.687304017 -0.400316198
[11] 0.022897159 0.137698620 0.277085580 -0.642650953 -0.363348152
[16] 0.645130843 0.387631113 -0.154652619 0.348345188 0.065207577
[21] 0.472746837 -0.163524089 -0.137858086 0.041431075 0.463395078
[26] -0.072543373 0.684758646 0.053243387 0.027216875 0.189311292
[31] 0.092996288 0.185940353 -0.185755343 0.073373771 0.734836571
[36] -0.328666482 0.678738682 0.007917698 0.241979722 0.065668716
[41] -0.042032599 0.347021673 -0.152784612 0.045215600 0.131045449
[46] 0.337070363 0.286598416 0.003888282 -0.128264296 -0.602102974
[51] 0.159967051 0.200986283 -0.024064836 0.022999159 0.066995981
[56] 0.510168820 -0.423297324 0.447519186 0.722113067 -0.660970023
[61] -0.133230908 -0.724758187 0.231678226 -0.018296447 -0.353503570
[66] -0.131035892 0.651415093 -0.201950103 -0.319587627 0.245323696
[71] 0.119096720 -0.567660908 -0.213713881 -0.013644062 0.184109376
[76] 0.141104068 0.129835733 0.028270357 -0.075088440 0.079257946
[81] -0.019018288 -0.163311678 0.038940329 0.010329319 0.126855581
[86] 0.447924181 0.220197104 0.246848997 0.234058012 -0.213084130
[91] -0.376428802 -0.245279299 0.130818387 0.084196779 0.339701838
[96] 0.214614659 0.354358823 -0.332902670 -0.469793433 -0.128942678
[101] 0.007729153 -0.362000980 0.208354441 -0.012697587 0.224397142
[106] -0.561305806 0.303996866 0.079179513 -0.031637156 -0.204976041
[111] 0.163835374 0.015568919 0.098202400 -0.026168784 0.136334884
[116] -0.063211706 0.357707760 0.498239380 0.099850693 -0.141070398
[121] 0.350919754 -0.293583867 0.106394085 0.335779881 0.049476644
[126] 0.289691917 0.005046483 -0.006791212 -0.344466925 0.064799060
[131] -0.255939878 0.388345603 0.216620383 -0.497253652 -0.259034058
[136] -0.220807451 -0.407009284 0.269645818 -0.251641167 -0.475749988
[141] 0.250936928 0.142462868 0.477667544 -0.054442002 -0.326314405
[146] -0.162640593 -0.069141997 -0.309902763 0.189060265 -0.251441652
[151] 0.435830009 0.374177114 0.369594282 -0.088324067 -0.362659318
[156] -0.051098556 -0.419482589 -0.229281575 0.733491305 -0.324512772
[161] 0.024191365 -0.104672528 -0.157804624 0.203359567 -0.232529805
[166] -0.010457760 0.223174959 0.130478170 0.209194410 0.135754748
[171] 0.192142095 0.192347987 -0.060041598 -0.103887621 -0.022205926
[176] -0.106768743 0.389899626 0.259833499 -0.012923214 -0.310044089
[181] -0.807634789 -0.118958003 0.305485735 -0.129980030 0.400188029
[186] 0.028808396 0.608148365 -0.020776269 0.270445749 0.084746347
[191] 0.165468779 -0.160720331 0.041401351 0.107020288 0.143827843
[196] -0.260627525 -0.600932063 0.293922552 -0.300276152 0.238939682
[201] -0.577627568 -0.292004646 -0.229691016 0.237545495 0.519717790
[206] 0.112210815 -0.108794393 -0.220279157 0.361383702 -0.584066633
[211] 0.104392351 -0.186939490 0.197885669 0.362737161 0.058657203
[216] -0.442463783 -0.167313910 -0.005853331 -0.197031188 -0.155467552
[221] 0.021384119 0.413737037 -0.467935678 -0.519114172 0.227541773
[226] -0.417898321 -0.248872666 -0.095904187 0.280292847 -0.562630649
>
> proc.time()
user system elapsed
5.142 19.055 25.596
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-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: 0x6000028e0060>
> .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: 0x6000028e0060>
> .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: 0x6000028e0060>
> .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: 0x6000028e0060>
> 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: 0x6000028c4540>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000028c4540>
> .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: 0x6000028c4540>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000028c4540>
> .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: 0x6000028c4540>
> 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: 0x6000028dc000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000028dc000>
> .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: 0x6000028dc000>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000028dc000>
> .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: 0x6000028dc000>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000028dc000>
> .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: 0x6000028dc000>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000028dc000>
> .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: 0x6000028dc000>
> 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: 0x6000028d8000>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000028d8000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000028d8000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000028d8000>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile16d6b64b45f18" "BufferedMatrixFile16d6b7dbe7bd6"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile16d6b64b45f18" "BufferedMatrixFile16d6b7dbe7bd6"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000028d8240>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000028d8240>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000028d8240>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000028d8240>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000028d8240>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000028d8240>
> .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: 0x6000028d8420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000028d8420>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000028d8420>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000028d8420>
> 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: 0x6000028d8600>
> .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: 0x6000028d8600>
> rm(P)
>
> proc.time()
user system elapsed
0.593 0.222 0.777
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
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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.
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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
0.590 0.139 0.691