Ben Bolstad
| Snapshot Date: 2024-09-26 13:40 -0400 (Thu, 26 Sep 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 2024-09-27 12:29 -0400 (Fri, 27 Sep 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" | 4451 |
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4417 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life" | 4456 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4489 |
| kjohnson3 | macOS 13.6.5 Ventura | arm64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4436 |
| kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4435 |
| 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 250/2262 | 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 | | ||||||||
| nebbiolo2 | Linux (Ubuntu 22.04.3 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: 2024-09-26 19:40:04 -0400 (Thu, 26 Sep 2024) |
| EndedAt: 2024-09-26 19:40:55 -0400 (Thu, 26 Sep 2024) |
| EllapsedTime: 51.7 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: 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 12.7.1
* 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 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
##############################################################################
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###
### 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 4.4.1 (2024-06-14) -- "Race for Your Life"
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
0.341 0.145 0.475
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: 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 474173 25.4 1035461 55.3 NA 638637 34.2
Vcells 877659 6.7 8388608 64.0 98304 2071819 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] "Thu Sep 26 19:40:28 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] "Thu Sep 26 19:40:29 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: 0x6000007f0000>
>
>
>
> 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] "Thu Sep 26 19:40:33 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] "Thu Sep 26 19:40:34 2024"
>
> ColMode(tmp2)
<pointer: 0x6000007f0000>
>
>
>
> ### 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,] 99.5378581 -0.4834260 -0.08287975 -0.5998305
[2,] -0.5091915 -0.5465540 -0.44837037 -1.8700324
[3,] -0.9949266 -1.5922755 1.60467786 0.5042493
[4,] -0.6840672 -0.9590096 -0.48991743 -0.3301441
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.5378581 0.4834260 0.08287975 0.5998305
[2,] 0.5091915 0.5465540 0.44837037 1.8700324
[3,] 0.9949266 1.5922755 1.60467786 0.5042493
[4,] 0.6840672 0.9590096 0.48991743 0.3301441
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9768661 0.6952885 0.2878884 0.7744873
[2,] 0.7135765 0.7392929 0.6696046 1.3674913
[3,] 0.9974601 1.2618540 1.2667588 0.7101052
[4,] 0.8270835 0.9792903 0.6999410 0.5745817
>
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.30652 32.43631 27.96176 33.34470
[2,] 32.64496 32.93948 32.14442 40.54495
[3,] 35.96953 39.21082 39.27227 32.60530
[4,] 33.95490 35.75191 32.48933 31.07596
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000007fc000>
> exp(tmp5)
<pointer: 0x6000007fc000>
> log(tmp5,2)
<pointer: 0x6000007fc000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.8646
> Min(tmp5)
[1] 53.78504
> mean(tmp5)
[1] 73.0811
> Sum(tmp5)
[1] 14616.22
> Var(tmp5)
[1] 853.7371
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.19231 71.35748 69.51523 70.53889 73.56085 72.20310 71.82327 69.60215
[9] 69.46923 72.54852
> rowSums(tmp5)
[1] 1803.846 1427.150 1390.305 1410.778 1471.217 1444.062 1436.465 1392.043
[9] 1389.385 1450.970
> rowVars(tmp5)
[1] 7931.10077 80.69263 75.35079 60.59583 85.96413 69.43247
[7] 84.55604 66.10898 51.37555 75.58652
> rowSd(tmp5)
[1] 89.056728 8.982908 8.680483 7.784333 9.271685 8.332615 9.195436
[8] 8.130743 7.167674 8.694051
> rowMax(tmp5)
[1] 466.86463 85.77311 81.79598 85.20828 87.91761 89.98127 88.93776
[8] 91.78424 82.60392 89.11387
> rowMin(tmp5)
[1] 55.14735 55.65521 55.17323 57.80590 56.83895 57.30856 54.98537 53.78504
[9] 56.78656 56.47895
>
> colMeans(tmp5)
[1] 111.69205 70.31049 69.39312 70.67819 73.24955 67.59874 66.14537
[8] 71.65140 71.18283 69.07599 75.03035 65.83397 74.48654 67.28568
[15] 72.82097 76.22957 74.38235 69.56595 73.90092 71.10804
> colSums(tmp5)
[1] 1116.9205 703.1049 693.9312 706.7819 732.4955 675.9874 661.4537
[8] 716.5140 711.8283 690.7599 750.3035 658.3397 744.8654 672.8568
[15] 728.2097 762.2957 743.8235 695.6595 739.0092 711.0804
> colVars(tmp5)
[1] 15616.87692 33.96970 69.64148 56.87295 122.01652 57.20294
[7] 54.00581 70.07567 99.26133 49.80350 77.24936 61.95998
[13] 141.29060 39.10226 55.38818 24.34152 60.17773 94.88052
[19] 77.41210 84.19906
> colSd(tmp5)
[1] 124.967503 5.828353 8.345147 7.541416 11.046109 7.563263
[7] 7.348865 8.371121 9.962998 7.057160 8.789162 7.871466
[13] 11.886572 6.253180 7.442323 4.933712 7.757431 9.740663
[19] 8.798415 9.176005
> colMax(tmp5)
[1] 466.86463 81.61218 85.08743 84.38899 89.98127 84.59848 79.18130
[8] 83.47444 85.02567 79.52686 88.89693 79.39379 91.78424 75.48015
[15] 87.91761 85.61820 87.48807 85.77311 87.95884 88.93776
> colMin(tmp5)
[1] 56.47895 63.37003 58.19875 57.30856 56.78656 58.01875 56.83895 60.16588
[9] 56.91712 55.14735 62.13983 55.65521 56.66032 55.17323 64.44980 69.49361
[17] 59.53881 54.98537 59.19981 53.78504
>
>
> ### 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] 90.19231 71.35748 NA 70.53889 73.56085 72.20310 71.82327 69.60215
[9] 69.46923 72.54852
> rowSums(tmp5)
[1] 1803.846 1427.150 NA 1410.778 1471.217 1444.062 1436.465 1392.043
[9] 1389.385 1450.970
> rowVars(tmp5)
[1] 7931.10077 80.69263 75.72684 60.59583 85.96413 69.43247
[7] 84.55604 66.10898 51.37555 75.58652
> rowSd(tmp5)
[1] 89.056728 8.982908 8.702117 7.784333 9.271685 8.332615 9.195436
[8] 8.130743 7.167674 8.694051
> rowMax(tmp5)
[1] 466.86463 85.77311 NA 85.20828 87.91761 89.98127 88.93776
[8] 91.78424 82.60392 89.11387
> rowMin(tmp5)
[1] 55.14735 55.65521 NA 57.80590 56.83895 57.30856 54.98537 53.78504
[9] 56.78656 56.47895
>
> colMeans(tmp5)
[1] 111.69205 70.31049 69.39312 70.67819 73.24955 67.59874 66.14537
[8] 71.65140 NA 69.07599 75.03035 65.83397 74.48654 67.28568
[15] 72.82097 76.22957 74.38235 69.56595 73.90092 71.10804
> colSums(tmp5)
[1] 1116.9205 703.1049 693.9312 706.7819 732.4955 675.9874 661.4537
[8] 716.5140 NA 690.7599 750.3035 658.3397 744.8654 672.8568
[15] 728.2097 762.2957 743.8235 695.6595 739.0092 711.0804
> colVars(tmp5)
[1] 15616.87692 33.96970 69.64148 56.87295 122.01652 57.20294
[7] 54.00581 70.07567 NA 49.80350 77.24936 61.95998
[13] 141.29060 39.10226 55.38818 24.34152 60.17773 94.88052
[19] 77.41210 84.19906
> colSd(tmp5)
[1] 124.967503 5.828353 8.345147 7.541416 11.046109 7.563263
[7] 7.348865 8.371121 NA 7.057160 8.789162 7.871466
[13] 11.886572 6.253180 7.442323 4.933712 7.757431 9.740663
[19] 8.798415 9.176005
> colMax(tmp5)
[1] 466.86463 81.61218 85.08743 84.38899 89.98127 84.59848 79.18130
[8] 83.47444 NA 79.52686 88.89693 79.39379 91.78424 75.48015
[15] 87.91761 85.61820 87.48807 85.77311 87.95884 88.93776
> colMin(tmp5)
[1] 56.47895 63.37003 58.19875 57.30856 56.78656 58.01875 56.83895 60.16588
[9] NA 55.14735 62.13983 55.65521 56.66032 55.17323 64.44980 69.49361
[17] 59.53881 54.98537 59.19981 53.78504
>
> Max(tmp5,na.rm=TRUE)
[1] 466.8646
> Min(tmp5,na.rm=TRUE)
[1] 53.78504
> mean(tmp5,na.rm=TRUE)
[1] 73.13958
> Sum(tmp5,na.rm=TRUE)
[1] 14554.78
> Var(tmp5,na.rm=TRUE)
[1] 857.3614
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.19231 71.35748 69.94006 70.53889 73.56085 72.20310 71.82327 69.60215
[9] 69.46923 72.54852
> rowSums(tmp5,na.rm=TRUE)
[1] 1803.846 1427.150 1328.861 1410.778 1471.217 1444.062 1436.465 1392.043
[9] 1389.385 1450.970
> rowVars(tmp5,na.rm=TRUE)
[1] 7931.10077 80.69263 75.72684 60.59583 85.96413 69.43247
[7] 84.55604 66.10898 51.37555 75.58652
> rowSd(tmp5,na.rm=TRUE)
[1] 89.056728 8.982908 8.702117 7.784333 9.271685 8.332615 9.195436
[8] 8.130743 7.167674 8.694051
> rowMax(tmp5,na.rm=TRUE)
[1] 466.86463 85.77311 81.79598 85.20828 87.91761 89.98127 88.93776
[8] 91.78424 82.60392 89.11387
> rowMin(tmp5,na.rm=TRUE)
[1] 55.14735 55.65521 55.17323 57.80590 56.83895 57.30856 54.98537 53.78504
[9] 56.78656 56.47895
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.69205 70.31049 69.39312 70.67819 73.24955 67.59874 66.14537
[8] 71.65140 72.26497 69.07599 75.03035 65.83397 74.48654 67.28568
[15] 72.82097 76.22957 74.38235 69.56595 73.90092 71.10804
> colSums(tmp5,na.rm=TRUE)
[1] 1116.9205 703.1049 693.9312 706.7819 732.4955 675.9874 661.4537
[8] 716.5140 650.3848 690.7599 750.3035 658.3397 744.8654 672.8568
[15] 728.2097 762.2957 743.8235 695.6595 739.0092 711.0804
> colVars(tmp5,na.rm=TRUE)
[1] 15616.87692 33.96970 69.64148 56.87295 122.01652 57.20294
[7] 54.00581 70.07567 98.49477 49.80350 77.24936 61.95998
[13] 141.29060 39.10226 55.38818 24.34152 60.17773 94.88052
[19] 77.41210 84.19906
> colSd(tmp5,na.rm=TRUE)
[1] 124.967503 5.828353 8.345147 7.541416 11.046109 7.563263
[7] 7.348865 8.371121 9.924453 7.057160 8.789162 7.871466
[13] 11.886572 6.253180 7.442323 4.933712 7.757431 9.740663
[19] 8.798415 9.176005
> colMax(tmp5,na.rm=TRUE)
[1] 466.86463 81.61218 85.08743 84.38899 89.98127 84.59848 79.18130
[8] 83.47444 85.02567 79.52686 88.89693 79.39379 91.78424 75.48015
[15] 87.91761 85.61820 87.48807 85.77311 87.95884 88.93776
> colMin(tmp5,na.rm=TRUE)
[1] 56.47895 63.37003 58.19875 57.30856 56.78656 58.01875 56.83895 60.16588
[9] 56.91712 55.14735 62.13983 55.65521 56.66032 55.17323 64.44980 69.49361
[17] 59.53881 54.98537 59.19981 53.78504
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.19231 71.35748 NaN 70.53889 73.56085 72.20310 71.82327 69.60215
[9] 69.46923 72.54852
> rowSums(tmp5,na.rm=TRUE)
[1] 1803.846 1427.150 0.000 1410.778 1471.217 1444.062 1436.465 1392.043
[9] 1389.385 1450.970
> rowVars(tmp5,na.rm=TRUE)
[1] 7931.10077 80.69263 NA 60.59583 85.96413 69.43247
[7] 84.55604 66.10898 51.37555 75.58652
> rowSd(tmp5,na.rm=TRUE)
[1] 89.056728 8.982908 NA 7.784333 9.271685 8.332615 9.195436
[8] 8.130743 7.167674 8.694051
> rowMax(tmp5,na.rm=TRUE)
[1] 466.86463 85.77311 NA 85.20828 87.91761 89.98127 88.93776
[8] 91.78424 82.60392 89.11387
> rowMin(tmp5,na.rm=TRUE)
[1] 55.14735 55.65521 NA 57.80590 56.83895 57.30856 54.98537 53.78504
[9] 56.78656 56.47895
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.78385 69.05475 68.02123 70.99092 72.85529 68.52607 66.03579
[8] 70.52423 NaN 69.62433 76.46263 64.32732 76.46723 68.63150
[15] 72.81048 76.97801 76.03163 68.82922 73.94145 71.38533
> colSums(tmp5,na.rm=TRUE)
[1] 1042.0546 621.4927 612.1911 638.9182 655.6976 616.7346 594.3221
[8] 634.7180 0.0000 626.6190 688.1637 578.9459 688.2050 617.6835
[15] 655.2943 692.8021 684.2847 619.4629 665.4731 642.4680
> colVars(tmp5,na.rm=TRUE)
[1] 17380.62981 20.47591 57.17342 62.88185 135.51987 54.67905
[7] 60.62143 64.54172 NA 52.64637 63.82700 44.16764
[13] 114.81666 23.61348 62.31046 21.08237 37.09846 100.63431
[19] 87.07013 93.85894
> colSd(tmp5,na.rm=TRUE)
[1] 131.835617 4.525031 7.561310 7.929808 11.641300 7.394528
[7] 7.785977 8.033786 NA 7.255782 7.989180 6.645874
[13] 10.715254 4.859370 7.893698 4.591554 6.090851 10.031665
[19] 9.331138 9.688082
> colMax(tmp5,na.rm=TRUE)
[1] 466.86463 77.92625 85.08743 84.38899 89.98127 84.59848 79.18130
[8] 83.47444 -Inf 79.52686 88.89693 78.64181 91.78424 75.48015
[15] 87.91761 85.61820 87.48807 85.77311 87.95884 88.93776
> colMin(tmp5,na.rm=TRUE)
[1] 56.47895 63.37003 58.19875 57.30856 56.78656 58.01875 56.83895 60.16588
[9] Inf 55.14735 65.86654 55.65521 62.61778 61.11781 64.44980 70.53360
[17] 67.56169 54.98537 59.19981 53.78504
>
>
>
>
> 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] 225.4376 222.6500 176.7532 251.2566 192.7932 228.7402 192.0878 151.9309
[9] 183.5364 146.5406
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 225.4376 222.6500 176.7532 251.2566 192.7932 228.7402 192.0878 151.9309
[9] 183.5364 146.5406
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 2.842171e-14 -5.684342e-14 8.526513e-14 1.136868e-13 5.684342e-14
[6] -1.136868e-13 0.000000e+00 -1.421085e-14 8.526513e-14 -2.131628e-14
[11] 2.842171e-13 -5.684342e-14 1.421085e-14 -4.263256e-14 1.421085e-14
[16] -2.842171e-14 5.684342e-14 -8.526513e-14 1.136868e-13 -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)
+ }
2 14
8 10
7 11
5 14
1 10
1 6
10 6
10 3
1 1
9 6
10 18
2 18
10 20
2 12
2 15
3 11
6 16
8 12
4 13
10 17
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.91701
> Min(tmp)
[1] -3.017828
> mean(tmp)
[1] -0.2101135
> Sum(tmp)
[1] -21.01135
> Var(tmp)
[1] 1.148539
>
> rowMeans(tmp)
[1] -0.2101135
> rowSums(tmp)
[1] -21.01135
> rowVars(tmp)
[1] 1.148539
> rowSd(tmp)
[1] 1.071699
> rowMax(tmp)
[1] 2.91701
> rowMin(tmp)
[1] -3.017828
>
> colMeans(tmp)
[1] -0.33492443 -2.26798363 0.74352680 -0.06851868 -0.69186959 2.39809717
[7] -0.86717277 1.06831911 0.20214791 0.27369118 -0.66562973 -1.31062424
[13] -0.63665906 -0.33838435 -1.35933700 -1.52103182 -0.46360875 0.38814285
[19] -0.06026133 -0.78424285 -0.19745262 -0.91757026 0.51814073 1.58063049
[25] 0.64297970 -1.48745843 -0.19500593 -0.47307674 -0.09510571 -0.30597981
[31] -0.19791410 -0.90163603 0.30534240 0.33308642 -1.25479414 -0.89378283
[37] -0.18429110 -1.74063033 -0.62201961 -0.49275803 -1.59909075 -0.65903690
[43] 2.91700981 0.44604647 1.01244460 -0.64357754 -1.80453328 0.57257652
[49] -0.44706649 -0.41585229 1.94684642 0.31832792 0.56026982 0.66948293
[55] -0.32211415 -2.21228347 1.15836977 -1.41529014 -0.62986575 -1.25940854
[61] -0.62821637 0.16013238 1.33036232 -2.05641552 -0.74047029 0.25162172
[67] -0.33438129 -0.33309533 -0.41345744 0.74641994 -0.77238565 0.36049486
[73] -0.88586414 0.58127146 -0.14260994 2.37551280 0.04728832 -0.32270480
[79] -3.01782778 -0.73370950 -0.35106079 -1.30287470 -2.20126675 0.97090202
[85] 0.92152752 0.22150169 0.20075344 -0.48599109 -0.34520671 -2.47818476
[91] -0.05831364 0.41066024 0.97352714 1.37168330 -0.70668843 -0.77070164
[97] -0.60079072 0.35644906 -0.26413747 2.33725733
> colSums(tmp)
[1] -0.33492443 -2.26798363 0.74352680 -0.06851868 -0.69186959 2.39809717
[7] -0.86717277 1.06831911 0.20214791 0.27369118 -0.66562973 -1.31062424
[13] -0.63665906 -0.33838435 -1.35933700 -1.52103182 -0.46360875 0.38814285
[19] -0.06026133 -0.78424285 -0.19745262 -0.91757026 0.51814073 1.58063049
[25] 0.64297970 -1.48745843 -0.19500593 -0.47307674 -0.09510571 -0.30597981
[31] -0.19791410 -0.90163603 0.30534240 0.33308642 -1.25479414 -0.89378283
[37] -0.18429110 -1.74063033 -0.62201961 -0.49275803 -1.59909075 -0.65903690
[43] 2.91700981 0.44604647 1.01244460 -0.64357754 -1.80453328 0.57257652
[49] -0.44706649 -0.41585229 1.94684642 0.31832792 0.56026982 0.66948293
[55] -0.32211415 -2.21228347 1.15836977 -1.41529014 -0.62986575 -1.25940854
[61] -0.62821637 0.16013238 1.33036232 -2.05641552 -0.74047029 0.25162172
[67] -0.33438129 -0.33309533 -0.41345744 0.74641994 -0.77238565 0.36049486
[73] -0.88586414 0.58127146 -0.14260994 2.37551280 0.04728832 -0.32270480
[79] -3.01782778 -0.73370950 -0.35106079 -1.30287470 -2.20126675 0.97090202
[85] 0.92152752 0.22150169 0.20075344 -0.48599109 -0.34520671 -2.47818476
[91] -0.05831364 0.41066024 0.97352714 1.37168330 -0.70668843 -0.77070164
[97] -0.60079072 0.35644906 -0.26413747 2.33725733
> 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] -0.33492443 -2.26798363 0.74352680 -0.06851868 -0.69186959 2.39809717
[7] -0.86717277 1.06831911 0.20214791 0.27369118 -0.66562973 -1.31062424
[13] -0.63665906 -0.33838435 -1.35933700 -1.52103182 -0.46360875 0.38814285
[19] -0.06026133 -0.78424285 -0.19745262 -0.91757026 0.51814073 1.58063049
[25] 0.64297970 -1.48745843 -0.19500593 -0.47307674 -0.09510571 -0.30597981
[31] -0.19791410 -0.90163603 0.30534240 0.33308642 -1.25479414 -0.89378283
[37] -0.18429110 -1.74063033 -0.62201961 -0.49275803 -1.59909075 -0.65903690
[43] 2.91700981 0.44604647 1.01244460 -0.64357754 -1.80453328 0.57257652
[49] -0.44706649 -0.41585229 1.94684642 0.31832792 0.56026982 0.66948293
[55] -0.32211415 -2.21228347 1.15836977 -1.41529014 -0.62986575 -1.25940854
[61] -0.62821637 0.16013238 1.33036232 -2.05641552 -0.74047029 0.25162172
[67] -0.33438129 -0.33309533 -0.41345744 0.74641994 -0.77238565 0.36049486
[73] -0.88586414 0.58127146 -0.14260994 2.37551280 0.04728832 -0.32270480
[79] -3.01782778 -0.73370950 -0.35106079 -1.30287470 -2.20126675 0.97090202
[85] 0.92152752 0.22150169 0.20075344 -0.48599109 -0.34520671 -2.47818476
[91] -0.05831364 0.41066024 0.97352714 1.37168330 -0.70668843 -0.77070164
[97] -0.60079072 0.35644906 -0.26413747 2.33725733
> colMin(tmp)
[1] -0.33492443 -2.26798363 0.74352680 -0.06851868 -0.69186959 2.39809717
[7] -0.86717277 1.06831911 0.20214791 0.27369118 -0.66562973 -1.31062424
[13] -0.63665906 -0.33838435 -1.35933700 -1.52103182 -0.46360875 0.38814285
[19] -0.06026133 -0.78424285 -0.19745262 -0.91757026 0.51814073 1.58063049
[25] 0.64297970 -1.48745843 -0.19500593 -0.47307674 -0.09510571 -0.30597981
[31] -0.19791410 -0.90163603 0.30534240 0.33308642 -1.25479414 -0.89378283
[37] -0.18429110 -1.74063033 -0.62201961 -0.49275803 -1.59909075 -0.65903690
[43] 2.91700981 0.44604647 1.01244460 -0.64357754 -1.80453328 0.57257652
[49] -0.44706649 -0.41585229 1.94684642 0.31832792 0.56026982 0.66948293
[55] -0.32211415 -2.21228347 1.15836977 -1.41529014 -0.62986575 -1.25940854
[61] -0.62821637 0.16013238 1.33036232 -2.05641552 -0.74047029 0.25162172
[67] -0.33438129 -0.33309533 -0.41345744 0.74641994 -0.77238565 0.36049486
[73] -0.88586414 0.58127146 -0.14260994 2.37551280 0.04728832 -0.32270480
[79] -3.01782778 -0.73370950 -0.35106079 -1.30287470 -2.20126675 0.97090202
[85] 0.92152752 0.22150169 0.20075344 -0.48599109 -0.34520671 -2.47818476
[91] -0.05831364 0.41066024 0.97352714 1.37168330 -0.70668843 -0.77070164
[97] -0.60079072 0.35644906 -0.26413747 2.33725733
> colMedians(tmp)
[1] -0.33492443 -2.26798363 0.74352680 -0.06851868 -0.69186959 2.39809717
[7] -0.86717277 1.06831911 0.20214791 0.27369118 -0.66562973 -1.31062424
[13] -0.63665906 -0.33838435 -1.35933700 -1.52103182 -0.46360875 0.38814285
[19] -0.06026133 -0.78424285 -0.19745262 -0.91757026 0.51814073 1.58063049
[25] 0.64297970 -1.48745843 -0.19500593 -0.47307674 -0.09510571 -0.30597981
[31] -0.19791410 -0.90163603 0.30534240 0.33308642 -1.25479414 -0.89378283
[37] -0.18429110 -1.74063033 -0.62201961 -0.49275803 -1.59909075 -0.65903690
[43] 2.91700981 0.44604647 1.01244460 -0.64357754 -1.80453328 0.57257652
[49] -0.44706649 -0.41585229 1.94684642 0.31832792 0.56026982 0.66948293
[55] -0.32211415 -2.21228347 1.15836977 -1.41529014 -0.62986575 -1.25940854
[61] -0.62821637 0.16013238 1.33036232 -2.05641552 -0.74047029 0.25162172
[67] -0.33438129 -0.33309533 -0.41345744 0.74641994 -0.77238565 0.36049486
[73] -0.88586414 0.58127146 -0.14260994 2.37551280 0.04728832 -0.32270480
[79] -3.01782778 -0.73370950 -0.35106079 -1.30287470 -2.20126675 0.97090202
[85] 0.92152752 0.22150169 0.20075344 -0.48599109 -0.34520671 -2.47818476
[91] -0.05831364 0.41066024 0.97352714 1.37168330 -0.70668843 -0.77070164
[97] -0.60079072 0.35644906 -0.26413747 2.33725733
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.3349244 -2.267984 0.7435268 -0.06851868 -0.6918696 2.398097 -0.8671728
[2,] -0.3349244 -2.267984 0.7435268 -0.06851868 -0.6918696 2.398097 -0.8671728
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.068319 0.2021479 0.2736912 -0.6656297 -1.310624 -0.6366591 -0.3383843
[2,] 1.068319 0.2021479 0.2736912 -0.6656297 -1.310624 -0.6366591 -0.3383843
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.359337 -1.521032 -0.4636087 0.3881429 -0.06026133 -0.7842428 -0.1974526
[2,] -1.359337 -1.521032 -0.4636087 0.3881429 -0.06026133 -0.7842428 -0.1974526
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.9175703 0.5181407 1.58063 0.6429797 -1.487458 -0.1950059 -0.4730767
[2,] -0.9175703 0.5181407 1.58063 0.6429797 -1.487458 -0.1950059 -0.4730767
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.09510571 -0.3059798 -0.1979141 -0.901636 0.3053424 0.3330864 -1.254794
[2,] -0.09510571 -0.3059798 -0.1979141 -0.901636 0.3053424 0.3330864 -1.254794
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.8937828 -0.1842911 -1.74063 -0.6220196 -0.492758 -1.599091 -0.6590369
[2,] -0.8937828 -0.1842911 -1.74063 -0.6220196 -0.492758 -1.599091 -0.6590369
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 2.91701 0.4460465 1.012445 -0.6435775 -1.804533 0.5725765 -0.4470665
[2,] 2.91701 0.4460465 1.012445 -0.6435775 -1.804533 0.5725765 -0.4470665
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.4158523 1.946846 0.3183279 0.5602698 0.6694829 -0.3221142 -2.212283
[2,] -0.4158523 1.946846 0.3183279 0.5602698 0.6694829 -0.3221142 -2.212283
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 1.15837 -1.41529 -0.6298658 -1.259409 -0.6282164 0.1601324 1.330362
[2,] 1.15837 -1.41529 -0.6298658 -1.259409 -0.6282164 0.1601324 1.330362
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -2.056416 -0.7404703 0.2516217 -0.3343813 -0.3330953 -0.4134574 0.7464199
[2,] -2.056416 -0.7404703 0.2516217 -0.3343813 -0.3330953 -0.4134574 0.7464199
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.7723857 0.3604949 -0.8858641 0.5812715 -0.1426099 2.375513 0.04728832
[2,] -0.7723857 0.3604949 -0.8858641 0.5812715 -0.1426099 2.375513 0.04728832
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.3227048 -3.017828 -0.7337095 -0.3510608 -1.302875 -2.201267 0.970902
[2,] -0.3227048 -3.017828 -0.7337095 -0.3510608 -1.302875 -2.201267 0.970902
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.9215275 0.2215017 0.2007534 -0.4859911 -0.3452067 -2.478185 -0.05831364
[2,] 0.9215275 0.2215017 0.2007534 -0.4859911 -0.3452067 -2.478185 -0.05831364
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.4106602 0.9735271 1.371683 -0.7066884 -0.7707016 -0.6007907 0.3564491
[2,] 0.4106602 0.9735271 1.371683 -0.7066884 -0.7707016 -0.6007907 0.3564491
[,99] [,100]
[1,] -0.2641375 2.337257
[2,] -0.2641375 2.337257
>
>
> Max(tmp2)
[1] 1.962487
> Min(tmp2)
[1] -2.591203
> mean(tmp2)
[1] 0.04956944
> Sum(tmp2)
[1] 4.956944
> Var(tmp2)
[1] 0.7492873
>
> rowMeans(tmp2)
[1] 0.0667387783 1.0231702672 -0.2347755608 -0.7280429215 -0.6143239321
[6] 0.0458935255 0.0005752241 -0.4192040791 -0.2893525833 0.1012268962
[11] 0.2544963065 0.5132421258 -1.1292720247 -0.0469918571 -1.1768847931
[16] 0.5528218172 -0.9895215705 0.3268946957 -0.9539885153 0.3247707611
[21] -0.2559232910 -2.5912033225 -0.2891292571 0.2415654919 -0.4226455524
[26] 0.7165128543 -0.7300803372 -1.5395663590 -0.3344695245 0.9822034093
[31] -0.8378204079 -0.2344671639 -0.5974636592 0.3904601780 -0.0534857928
[36] -0.3116480757 -0.5732913538 1.0878372145 0.8371859177 0.9876080019
[41] -0.0689104874 0.7372943315 -0.4295457563 -0.7149718104 -0.3526900958
[46] 1.5005850986 0.7021296332 1.9624867705 1.0393142178 -0.4463416251
[51] 0.3161188425 -0.1988714948 -1.7674456662 -0.6460193996 -0.5236796327
[56] 0.5496494794 -0.1343738437 1.6053290637 0.3035753114 0.4950816755
[61] 0.6571294404 1.0868352066 -0.3181597567 -1.2784364860 0.2652702861
[66] 0.1590280617 -0.5270256202 1.4492635602 -0.4336130528 0.6069514719
[71] 0.2228361885 1.3274839815 0.0694698631 -0.5188416184 0.1534147245
[76] 1.2137283701 -0.8411829753 1.2284946812 -1.4252865742 -1.3389764701
[81] 0.2059149099 -1.1035940459 0.3514207258 -1.8271974026 1.2072928357
[86] 0.6085480665 -1.1995867280 0.8609630701 1.8562031585 0.5938430458
[91] 0.3960448280 0.3312744801 0.7069412550 1.2083840299 -0.5332644332
[96] -0.6617364785 0.4485460400 0.9778468998 0.8235618551 0.9187883216
> rowSums(tmp2)
[1] 0.0667387783 1.0231702672 -0.2347755608 -0.7280429215 -0.6143239321
[6] 0.0458935255 0.0005752241 -0.4192040791 -0.2893525833 0.1012268962
[11] 0.2544963065 0.5132421258 -1.1292720247 -0.0469918571 -1.1768847931
[16] 0.5528218172 -0.9895215705 0.3268946957 -0.9539885153 0.3247707611
[21] -0.2559232910 -2.5912033225 -0.2891292571 0.2415654919 -0.4226455524
[26] 0.7165128543 -0.7300803372 -1.5395663590 -0.3344695245 0.9822034093
[31] -0.8378204079 -0.2344671639 -0.5974636592 0.3904601780 -0.0534857928
[36] -0.3116480757 -0.5732913538 1.0878372145 0.8371859177 0.9876080019
[41] -0.0689104874 0.7372943315 -0.4295457563 -0.7149718104 -0.3526900958
[46] 1.5005850986 0.7021296332 1.9624867705 1.0393142178 -0.4463416251
[51] 0.3161188425 -0.1988714948 -1.7674456662 -0.6460193996 -0.5236796327
[56] 0.5496494794 -0.1343738437 1.6053290637 0.3035753114 0.4950816755
[61] 0.6571294404 1.0868352066 -0.3181597567 -1.2784364860 0.2652702861
[66] 0.1590280617 -0.5270256202 1.4492635602 -0.4336130528 0.6069514719
[71] 0.2228361885 1.3274839815 0.0694698631 -0.5188416184 0.1534147245
[76] 1.2137283701 -0.8411829753 1.2284946812 -1.4252865742 -1.3389764701
[81] 0.2059149099 -1.1035940459 0.3514207258 -1.8271974026 1.2072928357
[86] 0.6085480665 -1.1995867280 0.8609630701 1.8562031585 0.5938430458
[91] 0.3960448280 0.3312744801 0.7069412550 1.2083840299 -0.5332644332
[96] -0.6617364785 0.4485460400 0.9778468998 0.8235618551 0.9187883216
> 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] 0.0667387783 1.0231702672 -0.2347755608 -0.7280429215 -0.6143239321
[6] 0.0458935255 0.0005752241 -0.4192040791 -0.2893525833 0.1012268962
[11] 0.2544963065 0.5132421258 -1.1292720247 -0.0469918571 -1.1768847931
[16] 0.5528218172 -0.9895215705 0.3268946957 -0.9539885153 0.3247707611
[21] -0.2559232910 -2.5912033225 -0.2891292571 0.2415654919 -0.4226455524
[26] 0.7165128543 -0.7300803372 -1.5395663590 -0.3344695245 0.9822034093
[31] -0.8378204079 -0.2344671639 -0.5974636592 0.3904601780 -0.0534857928
[36] -0.3116480757 -0.5732913538 1.0878372145 0.8371859177 0.9876080019
[41] -0.0689104874 0.7372943315 -0.4295457563 -0.7149718104 -0.3526900958
[46] 1.5005850986 0.7021296332 1.9624867705 1.0393142178 -0.4463416251
[51] 0.3161188425 -0.1988714948 -1.7674456662 -0.6460193996 -0.5236796327
[56] 0.5496494794 -0.1343738437 1.6053290637 0.3035753114 0.4950816755
[61] 0.6571294404 1.0868352066 -0.3181597567 -1.2784364860 0.2652702861
[66] 0.1590280617 -0.5270256202 1.4492635602 -0.4336130528 0.6069514719
[71] 0.2228361885 1.3274839815 0.0694698631 -0.5188416184 0.1534147245
[76] 1.2137283701 -0.8411829753 1.2284946812 -1.4252865742 -1.3389764701
[81] 0.2059149099 -1.1035940459 0.3514207258 -1.8271974026 1.2072928357
[86] 0.6085480665 -1.1995867280 0.8609630701 1.8562031585 0.5938430458
[91] 0.3960448280 0.3312744801 0.7069412550 1.2083840299 -0.5332644332
[96] -0.6617364785 0.4485460400 0.9778468998 0.8235618551 0.9187883216
> rowMin(tmp2)
[1] 0.0667387783 1.0231702672 -0.2347755608 -0.7280429215 -0.6143239321
[6] 0.0458935255 0.0005752241 -0.4192040791 -0.2893525833 0.1012268962
[11] 0.2544963065 0.5132421258 -1.1292720247 -0.0469918571 -1.1768847931
[16] 0.5528218172 -0.9895215705 0.3268946957 -0.9539885153 0.3247707611
[21] -0.2559232910 -2.5912033225 -0.2891292571 0.2415654919 -0.4226455524
[26] 0.7165128543 -0.7300803372 -1.5395663590 -0.3344695245 0.9822034093
[31] -0.8378204079 -0.2344671639 -0.5974636592 0.3904601780 -0.0534857928
[36] -0.3116480757 -0.5732913538 1.0878372145 0.8371859177 0.9876080019
[41] -0.0689104874 0.7372943315 -0.4295457563 -0.7149718104 -0.3526900958
[46] 1.5005850986 0.7021296332 1.9624867705 1.0393142178 -0.4463416251
[51] 0.3161188425 -0.1988714948 -1.7674456662 -0.6460193996 -0.5236796327
[56] 0.5496494794 -0.1343738437 1.6053290637 0.3035753114 0.4950816755
[61] 0.6571294404 1.0868352066 -0.3181597567 -1.2784364860 0.2652702861
[66] 0.1590280617 -0.5270256202 1.4492635602 -0.4336130528 0.6069514719
[71] 0.2228361885 1.3274839815 0.0694698631 -0.5188416184 0.1534147245
[76] 1.2137283701 -0.8411829753 1.2284946812 -1.4252865742 -1.3389764701
[81] 0.2059149099 -1.1035940459 0.3514207258 -1.8271974026 1.2072928357
[86] 0.6085480665 -1.1995867280 0.8609630701 1.8562031585 0.5938430458
[91] 0.3960448280 0.3312744801 0.7069412550 1.2083840299 -0.5332644332
[96] -0.6617364785 0.4485460400 0.9778468998 0.8235618551 0.9187883216
>
> colMeans(tmp2)
[1] 0.04956944
> colSums(tmp2)
[1] 4.956944
> colVars(tmp2)
[1] 0.7492873
> colSd(tmp2)
[1] 0.8656138
> colMax(tmp2)
[1] 1.962487
> colMin(tmp2)
[1] -2.591203
> colMedians(tmp2)
[1] 0.08534838
> colRanges(tmp2)
[,1]
[1,] -2.591203
[2,] 1.962487
>
> 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] 0.4778192 1.3347770 1.9280737 -1.1219898 -3.8841104 1.1682552
[7] -4.7150350 -0.5417805 1.6487018 2.7789250
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.7315161
[2,] -0.6420465
[3,] 0.5356403
[4,] 0.6266200
[5,] 1.1267129
>
> rowApply(tmp,sum)
[1] -5.5529897 0.2309388 3.5656844 -2.3451783 3.7928068 0.2987848
[7] 3.4746718 0.4618326 -1.9211026 -2.9318124
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 6 9 8 1 8 8 2 3 8
[2,] 4 10 4 6 10 1 7 5 9 4
[3,] 8 9 1 3 6 10 5 4 5 9
[4,] 7 2 5 5 9 6 6 3 10 1
[5,] 2 3 6 2 3 9 4 1 8 7
[6,] 9 7 7 9 5 5 2 8 2 6
[7,] 3 1 2 1 2 7 10 6 1 2
[8,] 6 4 3 4 4 4 3 7 6 10
[9,] 5 5 10 7 7 3 1 10 7 5
[10,] 1 8 8 10 8 2 9 9 4 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.0957447 5.7198134 0.5772878 -2.2000408 -2.0689715 0.5184114
[7] 2.2575496 -0.5081187 -0.2513392 -7.0418996 -1.2344711 -4.5266180
[13] -3.9194933 -1.3689659 2.5917971 1.1751900 -1.6970159 2.7222499
[19] -0.6422409 0.3021376
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.41453287
[2,] -1.26685719
[3,] -0.02956261
[4,] 1.24306317
[5,] 1.56363420
>
> rowApply(tmp,sum)
[1] -0.9366073 3.3834528 -0.2647417 -7.4970130 -4.1840841
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 2 6 18 3 16
[2,] 15 7 20 19 19
[3,] 11 18 10 13 12
[4,] 1 10 8 9 11
[5,] 9 13 7 11 5
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.26685719 0.33672058 0.008053737 -1.4040047 -0.03496179 -0.4446374
[2,] -0.02956261 0.07279963 0.664787761 0.3095468 0.47016110 0.1554250
[3,] 1.56363420 2.17410194 -0.059924829 -0.3863765 -0.46504745 0.3346511
[4,] -1.41453287 1.72607974 -0.177244259 -0.5955242 -0.46790166 -0.8732410
[5,] 1.24306317 1.41011150 0.141615402 -0.1236822 -1.57122169 1.3462137
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.001836721 0.99550891 -0.4470603 0.1480893 0.9685551 -0.4219652
[2,] 0.583365288 0.65503463 1.0252507 -0.2608013 0.3239950 -0.6618807
[3,] 0.939196903 0.06901592 -0.9362868 -1.8912145 -0.6847586 0.4298612
[4,] 0.564454560 -0.50457274 2.2050324 -2.4759756 -1.3497982 -1.4726808
[5,] 0.172369526 -1.72310547 -2.0982752 -2.5619974 -0.4924645 -2.3999524
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.6624942 0.03824087 -1.1655183 0.22112979 -0.97916708 2.2967330
[2,] -0.8564162 -2.17032599 0.5055999 1.76632768 -0.44220519 0.5658985
[3,] -1.4601852 -1.74933913 1.6298498 -1.20684243 0.35460390 0.3769714
[4,] -1.2230270 -0.35211199 0.4452600 0.04012117 0.09727046 0.2558864
[5,] -1.0423590 2.86457036 1.1766056 0.35445381 -0.72751795 -0.7732393
[,19] [,20]
[1,] -0.8763388 0.4302147
[2,] 0.4653003 0.2411524
[3,] 1.0462748 -0.3429274
[4,] -0.6345243 -1.2899829
[5,] -0.6429529 1.2636809
>
>
> 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 : 650 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 563 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-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 0.1621016 0.3306119 0.5512377 0.2960563 -1.977167 -1.202307 -0.1957585
col8 col9 col10 col11 col12 col13 col14
row1 0.626859 -0.8329381 -0.6933592 -0.5715441 0.1956192 -0.1252794 0.5311151
col15 col16 col17 col18 col19 col20
row1 0.6226783 0.6816259 -2.15981 0.048878 0.4410572 0.6256823
> tmp[,"col10"]
col10
row1 -0.6933592
row2 -1.1292715
row3 -0.2096690
row4 -1.7994893
row5 -0.9567939
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.1621016 0.3306119 0.5512377 0.2960563 -1.9771665 -1.20230734
row5 0.6060237 -0.5769396 -0.1564729 0.7062531 -0.4136274 -0.08125498
col7 col8 col9 col10 col11 col12
row1 -0.1957585 6.268590e-01 -0.8329381 -0.6933592 -0.5715441 0.1956192
row5 -0.9114064 -9.749048e-05 1.9873322 -0.9567939 -1.3020393 -0.1743991
col13 col14 col15 col16 col17 col18 col19
row1 -0.1252794 0.5311151 0.6226783 0.6816259 -2.15980986 0.0488780 0.4410572
row5 -0.5086480 0.7521502 0.7887661 1.6342014 0.04742439 0.5470777 0.6528048
col20
row1 0.6256823
row5 0.4267333
> tmp[,c("col6","col20")]
col6 col20
row1 -1.20230734 0.6256823
row2 0.99405411 -1.8505624
row3 -0.52129570 -0.6571152
row4 -0.56622648 0.8787095
row5 -0.08125498 0.4267333
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.20230734 0.6256823
row5 -0.08125498 0.4267333
>
>
>
>
> 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 49.26641 49.16302 49.85367 49.68419 51.69795 104.9593 49.64194 50.71577
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.74067 50.13791 50.91671 49.7246 49.29311 50.09311 49.17044 50.78448
col17 col18 col19 col20
row1 49.69336 50.01743 50.36539 104.8854
> tmp[,"col10"]
col10
row1 50.13791
row2 30.69858
row3 28.38255
row4 28.75689
row5 50.25842
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.26641 49.16302 49.85367 49.68419 51.69795 104.9593 49.64194 50.71577
row5 49.83773 50.70511 51.18879 48.63487 48.57984 105.6306 49.87839 50.10375
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.74067 50.13791 50.91671 49.72460 49.29311 50.09311 49.17044 50.78448
row5 49.18209 50.25842 47.66529 51.65129 49.42306 50.44287 51.37720 51.19190
col17 col18 col19 col20
row1 49.69336 50.01743 50.36539 104.8854
row5 50.55626 49.66754 51.59894 103.9094
> tmp[,c("col6","col20")]
col6 col20
row1 104.95932 104.88537
row2 75.75409 74.27078
row3 73.10068 76.48306
row4 73.94992 75.99239
row5 105.63062 103.90939
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.9593 104.8854
row5 105.6306 103.9094
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.9593 104.8854
row5 105.6306 103.9094
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.4507909
[2,] -0.9206898
[3,] -1.4064207
[4,] 0.5306124
[5,] 2.2753005
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.6343859 1.97046074
[2,] -0.0559353 -0.02688873
[3,] -0.7557319 -0.45918263
[4,] -1.4611960 1.42263186
[5,] -1.6855456 -0.34203250
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.3775134 0.7508615
[2,] 2.0107080 0.2897085
[3,] -0.3091202 -1.9555354
[4,] -0.3755914 -0.5880738
[5,] 0.1842480 -0.4854530
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.3775134
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.3775134
[2,] 2.0107080
>
>
>
> 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 0.9494772 0.3452625 -1.0969827 -1.3580448 -0.1131824 0.6421775 -1.296753
row1 0.9738940 1.5643846 -0.6602663 0.5798645 0.4346739 0.7697828 -1.968030
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.2137313 0.6786962 -0.6258293 -0.4616071 -0.2561841 0.09287836 1.0424847
row1 0.2045291 0.3396177 -0.5193714 -0.9571531 -1.4032148 1.02524759 0.9872667
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.651039 -0.34772816 -0.4990211 1.2401677 0.07383794 0.1220210
row1 -0.264742 0.01218306 0.2173687 0.6140959 0.93597870 -0.8029318
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.7311068 -2.272028 -0.3572017 -1.203106 0.5996283 -0.3895415 0.2029466
[,8] [,9] [,10]
row2 -1.603169 0.2853319 -0.9418681
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -1.36563 0.8433487 0.5843039 0.5369721 -0.797306 -0.1532472 -0.3865552
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.0787563 0.148299 1.71504 0.1042412 -0.2796621 1.294198 -1.08932
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.6143619 0.479294 1.453219 -0.5733457 0.00756394 -1.789147
>
>
> 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: 0x6000007a0000>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM92507d423aeb"
[2] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM925072a5a8c"
[3] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM92506d9ea100"
[4] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM9250495c3f39"
[5] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM9250473adccf"
[6] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM92506976be91"
[7] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM925072d957ae"
[8] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM92501b0b9b6a"
[9] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM925017085a05"
[10] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM9250254e0a13"
[11] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM925026777887"
[12] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM92506d89facb"
[13] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM92507db05d9b"
[14] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM925045d1ab94"
[15] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM92504857a55b"
>
>
> ### 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: 0x6000007ec120>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000007ec120>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6000007ec120>
> rowMedians(tmp)
[1] -0.380338918 0.132098631 0.427904406 0.419965245 -0.119599232
[6] 0.087034440 0.271197970 -0.229222031 0.546452560 0.004556524
[11] -0.266466516 -0.107197067 -0.103065852 0.336529231 -0.322563695
[16] 0.076729182 -0.237289676 0.025064387 0.177218837 1.035327071
[21] -0.112376185 0.115173247 0.119302331 0.242093994 -0.452461397
[26] 0.029950254 0.202809050 -0.160669767 0.264458151 0.265515272
[31] -0.026613329 -0.628405757 0.275671671 0.312135953 -0.372373223
[36] 0.160894251 -0.425497220 0.314287652 0.504509074 0.152193551
[41] 0.606365868 -0.002173067 -0.532666630 0.544740110 0.577130006
[46] 0.355518637 0.245046427 0.128246060 -0.223055154 -0.404223983
[51] -0.018962933 0.428557644 0.140400038 -0.196012726 0.313749046
[56] 0.375198515 -0.208270281 -0.797025025 0.191997467 -0.362484301
[61] -0.133577194 0.018506923 -0.079968883 0.607047491 0.601882054
[66] 0.303895760 0.692029517 -0.117372246 -0.295962419 -0.432561098
[71] -0.019607621 -0.222342533 -0.521963538 -0.019588615 0.487563334
[76] -0.524763941 0.166483698 -0.102565016 0.619225187 -0.229760152
[81] -0.248004643 0.245032716 -0.105789261 -0.225842363 -0.327058725
[86] 0.108783448 -0.027332116 0.216426670 -0.155511512 0.123870575
[91] -0.141795258 0.150479229 -0.196207336 -0.864477089 0.365606759
[96] 0.646997299 0.348929321 0.540921275 0.098878935 -0.049257153
[101] -0.188961637 0.186759437 0.520690968 -0.054168820 0.362266143
[106] -0.079250898 0.357044164 0.254985142 -0.233231047 0.380915150
[111] -0.270208882 0.012336737 0.047088994 -0.269326697 0.233675467
[116] -0.346656898 -0.265245555 -0.152650953 0.148843455 0.141127252
[121] -0.271066574 0.267339927 -0.249622017 0.418950201 0.120247958
[126] 0.670926132 -0.607704295 -0.145180695 0.227256697 -0.037759175
[131] 0.707694068 0.375839378 -0.368446938 -0.440182586 0.332517406
[136] -0.115699022 -0.396372917 -0.048585324 0.470899128 -0.154842054
[141] 0.153603712 -0.368090224 0.177041973 0.844413935 0.035058837
[146] 0.489371157 -0.059341248 -0.419925510 0.187489359 -0.319862355
[151] 0.100696021 0.303537719 -0.112135784 -0.193718310 0.373097025
[156] -0.125310657 -0.360221008 -0.134547292 -0.039950867 0.742398255
[161] 0.192465459 0.406904363 -0.215611791 0.324975572 0.155417897
[166] 0.012026466 0.501434169 0.183723452 0.428530957 -0.170427216
[171] -0.486270231 -0.102606198 -0.170659075 0.157408151 0.353346392
[176] 0.243663510 0.084149333 0.198364078 0.411808417 -0.128886394
[181] 0.244773634 0.102804112 -0.021115200 0.247992106 -0.550215964
[186] 0.629376387 0.051692481 0.407839304 0.580511661 -0.008434854
[191] 0.669482608 -0.403219155 -0.662215860 0.659084239 0.463939871
[196] -0.387782063 0.223443998 0.100453886 -0.245693488 0.037778172
[201] -0.034964017 -0.006974510 -0.057951376 -0.498546696 0.597137048
[206] 0.530183660 -0.118057800 0.133290511 -0.367411671 0.023769962
[211] 0.110708142 0.487984231 -0.243637269 -0.552174919 0.101843349
[216] -0.451078439 -0.054036266 -0.289844872 -0.232868056 -0.154737038
[221] -0.066057737 0.066150629 -0.063603394 0.277147828 -0.066719054
[226] -0.290792274 -0.017044488 -0.076241898 -0.064240469 -0.041996678
>
> proc.time()
user system elapsed
2.676 14.691 18.014
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: 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: 0x6000018cc000>
> .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: 0x6000018cc000>
> .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: 0x6000018cc000>
> .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: 0x6000018cc000>
> 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: 0x6000018c4000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018c4000>
> .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: 0x6000018c4000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018c4000>
> .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: 0x6000018c4000>
> 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: 0x6000018c0000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018c0000>
> .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: 0x6000018c0000>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000018c0000>
> .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: 0x6000018c0000>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000018c0000>
> .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: 0x6000018c0000>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000018c0000>
> .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: 0x6000018c0000>
> 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: 0x6000018dc000>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000018dc000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018dc000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018dc000>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile96a411cb276d" "BufferedMatrixFile96a430896e3b"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile96a411cb276d" "BufferedMatrixFile96a430896e3b"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018dc240>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018dc240>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000018dc240>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000018dc240>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000018dc240>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000018dc240>
> .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: 0x6000018dc420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000018dc420>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000018dc420>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000018dc420>
> 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: 0x6000018b0000>
> .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: 0x6000018b0000>
> rm(P)
>
> proc.time()
user system elapsed
0.343 0.158 0.500
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: 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.
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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
0.362 0.093 0.450