Ben Bolstad
| Snapshot Date: 2024-05-30 18:57:37 -0400 (Thu, 30 May 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 2024-05-31 19:31:00 -0400 (Fri, 31 May 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 RC (2024-04-16 r86468) -- "Puppy Cup" | 4669 |
| palomino4 | Windows Server 2022 Datacenter | x64 | 4.4.0 RC (2024-04-16 r86468 ucrt) -- "Puppy Cup" | 4404 |
| merida1 | macOS 12.7.4 Monterey | x86_64 | 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup" | 4431 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup" | 4384 |
| 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 244/2233 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.69.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino4 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.4 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | WARNINGS | 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: 2024-05-31 05:42:05 -0400 (Fri, 31 May 2024) |
| EndedAt: 2024-05-31 05:43:17 -0400 (Fri, 31 May 2024) |
| EllapsedTime: 72.4 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_1.69.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.0 Patched (2024-04-24 r86482)
* 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 12.7.4
* 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
##############################################################################
##############################################################################
###
### 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 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup"
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
0.598 0.216 0.996
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup"
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 474175 25.4 1035502 55.4 NA 638565 34.2
Vcells 877671 6.7 8388608 64.0 65536 2072607 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 May 31 05:42:39 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri May 31 05:42:40 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: 0x6000036f4540>
>
>
>
> 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 May 31 05:42:46 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri May 31 05:42:48 2024"
>
> ColMode(tmp2)
<pointer: 0x6000036f4540>
>
>
>
> ### 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,] 99.3022760 1.76250992 -0.01552943 0.04768582
[2,] 1.2907011 -0.82584417 0.73037657 0.45610617
[3,] 1.5481015 -1.98234366 -0.32805837 1.02915721
[4,] 0.1881271 -0.07831362 -1.33041949 0.55314816
> 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,] 99.3022760 1.76250992 0.01552943 0.04768582
[2,] 1.2907011 0.82584417 0.73037657 0.45610617
[3,] 1.5481015 1.98234366 0.32805837 1.02915721
[4,] 0.1881271 0.07831362 1.33041949 0.55314816
> 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,] 9.9650527 1.3275955 0.1246171 0.2183708
[2,] 1.1360903 0.9087597 0.8546207 0.6753563
[3,] 1.2442273 1.4079573 0.5727638 1.0144739
[4,] 0.4337362 0.2798457 1.1534381 0.7437393
>
> 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,] 223.95280 40.03847 26.26170 27.23139
[2,] 37.65160 34.91344 34.27658 32.20967
[3,] 38.99037 41.06192 31.05570 36.17390
[4,] 29.52549 27.87677 37.86480 32.99054
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000036f02a0>
> exp(tmp5)
<pointer: 0x6000036f02a0>
> log(tmp5,2)
<pointer: 0x6000036f02a0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.1284
> Min(tmp5)
[1] 52.25044
> mean(tmp5)
[1] 72.29917
> Sum(tmp5)
[1] 14459.83
> Var(tmp5)
[1] 860.6575
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.18109 69.78280 70.17098 70.97799 74.72730 69.57427 72.20081 68.47262
[9] 68.10777 69.79606
> rowSums(tmp5)
[1] 1783.622 1395.656 1403.420 1419.560 1494.546 1391.485 1444.016 1369.452
[9] 1362.155 1395.921
> rowVars(tmp5)
[1] 7945.30611 68.15703 75.68838 54.31397 116.95747 72.84821
[7] 37.58243 86.11500 108.20042 81.28292
> rowSd(tmp5)
[1] 89.136447 8.255727 8.699907 7.369801 10.814687 8.535117 6.130451
[8] 9.279817 10.401943 9.015704
> rowMax(tmp5)
[1] 466.12842 85.70433 85.46500 79.97881 93.87904 82.79417 87.44635
[8] 89.65510 86.31212 93.39304
> rowMin(tmp5)
[1] 54.66029 55.90626 56.57405 56.23892 57.27764 53.33438 57.39140 56.56454
[9] 52.25044 56.17414
>
> colMeans(tmp5)
[1] 109.35216 71.45805 68.14734 66.88591 73.07582 71.04519 68.13455
[8] 70.52738 70.55376 71.76549 71.46887 70.41682 71.79922 69.21034
[15] 68.79411 70.96464 68.31725 70.57134 70.16856 73.32655
> colSums(tmp5)
[1] 1093.5216 714.5805 681.4734 668.8591 730.7582 710.4519 681.3455
[8] 705.2738 705.5376 717.6549 714.6887 704.1682 717.9922 692.1034
[15] 687.9411 709.6464 683.1725 705.7134 701.6856 733.2655
> colVars(tmp5)
[1] 15776.77363 150.65103 73.03818 33.46824 45.60056 62.23859
[7] 72.14257 119.87310 111.81548 99.77051 82.99542 108.54834
[13] 115.60168 94.67898 75.03490 76.46704 52.19231 67.87026
[19] 67.94912 78.17344
> colSd(tmp5)
[1] 125.605627 12.273998 8.546238 5.785174 6.752819 7.889144
[7] 8.493678 10.948657 10.574284 9.988519 9.110182 10.418654
[13] 10.751822 9.730313 8.662269 8.744544 7.224425 8.238341
[19] 8.243126 8.841574
> colMax(tmp5)
[1] 466.12842 86.21562 78.81062 75.29122 81.21800 83.81133 81.53912
[8] 89.65510 90.86741 87.44635 93.39304 81.22832 93.87904 81.58542
[15] 86.31212 84.72655 78.39465 80.94397 80.41380 85.70433
> colMin(tmp5)
[1] 61.45344 56.36245 54.66029 56.67858 60.65127 60.40361 55.95861 52.25044
[9] 53.68819 56.17414 62.12933 54.65040 57.42406 55.90626 56.56454 58.08869
[17] 53.33438 56.89560 56.82454 57.27764
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] NA 69.78280 70.17098 70.97799 74.72730 69.57427 72.20081 68.47262
[9] 68.10777 69.79606
> rowSums(tmp5)
[1] NA 1395.656 1403.420 1419.560 1494.546 1391.485 1444.016 1369.452
[9] 1362.155 1395.921
> rowVars(tmp5)
[1] 77.39679 68.15703 75.68838 54.31397 116.95747 72.84821 37.58243
[8] 86.11500 108.20042 81.28292
> rowSd(tmp5)
[1] 8.797545 8.255727 8.699907 7.369801 10.814687 8.535117 6.130451
[8] 9.279817 10.401943 9.015704
> rowMax(tmp5)
[1] NA 85.70433 85.46500 79.97881 93.87904 82.79417 87.44635 89.65510
[9] 86.31212 93.39304
> rowMin(tmp5)
[1] NA 55.90626 56.57405 56.23892 57.27764 53.33438 57.39140 56.56454
[9] 52.25044 56.17414
>
> colMeans(tmp5)
[1] NA 71.45805 68.14734 66.88591 73.07582 71.04519 68.13455 70.52738
[9] 70.55376 71.76549 71.46887 70.41682 71.79922 69.21034 68.79411 70.96464
[17] 68.31725 70.57134 70.16856 73.32655
> colSums(tmp5)
[1] NA 714.5805 681.4734 668.8591 730.7582 710.4519 681.3455 705.2738
[9] 705.5376 717.6549 714.6887 704.1682 717.9922 692.1034 687.9411 709.6464
[17] 683.1725 705.7134 701.6856 733.2655
> colVars(tmp5)
[1] NA 150.65103 73.03818 33.46824 45.60056 62.23859 72.14257
[8] 119.87310 111.81548 99.77051 82.99542 108.54834 115.60168 94.67898
[15] 75.03490 76.46704 52.19231 67.87026 67.94912 78.17344
> colSd(tmp5)
[1] NA 12.273998 8.546238 5.785174 6.752819 7.889144 8.493678
[8] 10.948657 10.574284 9.988519 9.110182 10.418654 10.751822 9.730313
[15] 8.662269 8.744544 7.224425 8.238341 8.243126 8.841574
> colMax(tmp5)
[1] NA 86.21562 78.81062 75.29122 81.21800 83.81133 81.53912 89.65510
[9] 90.86741 87.44635 93.39304 81.22832 93.87904 81.58542 86.31212 84.72655
[17] 78.39465 80.94397 80.41380 85.70433
> colMin(tmp5)
[1] NA 56.36245 54.66029 56.67858 60.65127 60.40361 55.95861 52.25044
[9] 53.68819 56.17414 62.12933 54.65040 57.42406 55.90626 56.56454 58.08869
[17] 53.33438 56.89560 56.82454 57.27764
>
> Max(tmp5,na.rm=TRUE)
[1] 93.87904
> Min(tmp5,na.rm=TRUE)
[1] 52.25044
> mean(tmp5,na.rm=TRUE)
[1] 70.32013
> Sum(tmp5,na.rm=TRUE)
[1] 13993.71
> Var(tmp5,na.rm=TRUE)
[1] 77.72703
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 69.34175 69.78280 70.17098 70.97799 74.72730 69.57427 72.20081 68.47262
[9] 68.10777 69.79606
> rowSums(tmp5,na.rm=TRUE)
[1] 1317.493 1395.656 1403.420 1419.560 1494.546 1391.485 1444.016 1369.452
[9] 1362.155 1395.921
> rowVars(tmp5,na.rm=TRUE)
[1] 77.39679 68.15703 75.68838 54.31397 116.95747 72.84821 37.58243
[8] 86.11500 108.20042 81.28292
> rowSd(tmp5,na.rm=TRUE)
[1] 8.797545 8.255727 8.699907 7.369801 10.814687 8.535117 6.130451
[8] 9.279817 10.401943 9.015704
> rowMax(tmp5,na.rm=TRUE)
[1] 83.33482 85.70433 85.46500 79.97881 93.87904 82.79417 87.44635 89.65510
[9] 86.31212 93.39304
> rowMin(tmp5,na.rm=TRUE)
[1] 54.66029 55.90626 56.57405 56.23892 57.27764 53.33438 57.39140 56.56454
[9] 52.25044 56.17414
>
> colMeans(tmp5,na.rm=TRUE)
[1] 69.71035 71.45805 68.14734 66.88591 73.07582 71.04519 68.13455 70.52738
[9] 70.55376 71.76549 71.46887 70.41682 71.79922 69.21034 68.79411 70.96464
[17] 68.31725 70.57134 70.16856 73.32655
> colSums(tmp5,na.rm=TRUE)
[1] 627.3931 714.5805 681.4734 668.8591 730.7582 710.4519 681.3455 705.2738
[9] 705.5376 717.6549 714.6887 704.1682 717.9922 692.1034 687.9411 709.6464
[17] 683.1725 705.7134 701.6856 733.2655
> colVars(tmp5,na.rm=TRUE)
[1] 69.80066 150.65103 73.03818 33.46824 45.60056 62.23859 72.14257
[8] 119.87310 111.81548 99.77051 82.99542 108.54834 115.60168 94.67898
[15] 75.03490 76.46704 52.19231 67.87026 67.94912 78.17344
> colSd(tmp5,na.rm=TRUE)
[1] 8.354679 12.273998 8.546238 5.785174 6.752819 7.889144 8.493678
[8] 10.948657 10.574284 9.988519 9.110182 10.418654 10.751822 9.730313
[15] 8.662269 8.744544 7.224425 8.238341 8.243126 8.841574
> colMax(tmp5,na.rm=TRUE)
[1] 81.15336 86.21562 78.81062 75.29122 81.21800 83.81133 81.53912 89.65510
[9] 90.86741 87.44635 93.39304 81.22832 93.87904 81.58542 86.31212 84.72655
[17] 78.39465 80.94397 80.41380 85.70433
> colMin(tmp5,na.rm=TRUE)
[1] 61.45344 56.36245 54.66029 56.67858 60.65127 60.40361 55.95861 52.25044
[9] 53.68819 56.17414 62.12933 54.65040 57.42406 55.90626 56.56454 58.08869
[17] 53.33438 56.89560 56.82454 57.27764
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 69.78280 70.17098 70.97799 74.72730 69.57427 72.20081 68.47262
[9] 68.10777 69.79606
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1395.656 1403.420 1419.560 1494.546 1391.485 1444.016 1369.452
[9] 1362.155 1395.921
> rowVars(tmp5,na.rm=TRUE)
[1] NA 68.15703 75.68838 54.31397 116.95747 72.84821 37.58243
[8] 86.11500 108.20042 81.28292
> rowSd(tmp5,na.rm=TRUE)
[1] NA 8.255727 8.699907 7.369801 10.814687 8.535117 6.130451
[8] 9.279817 10.401943 9.015704
> rowMax(tmp5,na.rm=TRUE)
[1] NA 85.70433 85.46500 79.97881 93.87904 82.79417 87.44635 89.65510
[9] 86.31212 93.39304
> rowMin(tmp5,na.rm=TRUE)
[1] NA 55.90626 56.57405 56.23892 57.27764 53.33438 57.39140 56.56454
[9] 52.25044 56.17414
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] NaN 70.13841 69.64591 68.02005 72.38403 71.81501 68.19449 69.65068
[9] 69.61080 72.94339 72.01281 69.71611 72.70138 68.88628 69.28608 71.52913
[17] 68.04267 72.09087 69.23794 72.85160
> colSums(tmp5,na.rm=TRUE)
[1] 0.0000 631.2457 626.8131 612.1805 651.4563 646.3351 613.7504 626.8561
[9] 626.4972 656.4905 648.1153 627.4450 654.3124 619.9765 623.5748 643.7622
[17] 612.3840 648.8178 623.1415 655.6644
> colVars(tmp5,na.rm=TRUE)
[1] NA 149.89108 56.90397 23.18100 45.91673 63.35136 81.11997
[8] 126.21038 115.78940 96.63320 90.04138 116.59314 120.89560 105.33243
[15] 81.69130 82.44063 57.86813 50.37824 66.69968 85.40729
> colSd(tmp5,na.rm=TRUE)
[1] NA 12.243001 7.543472 4.814665 6.776189 7.959357 9.006663
[8] 11.234339 10.760548 9.830218 9.489014 10.797830 10.995253 10.263159
[15] 9.038324 9.079682 7.607110 7.097763 8.166987 9.241606
> colMax(tmp5,na.rm=TRUE)
[1] -Inf 86.21562 78.81062 75.29122 81.21800 83.81133 81.53912 89.65510
[9] 90.86741 87.44635 93.39304 81.22832 93.87904 81.58542 86.31212 84.72655
[17] 78.39465 80.94397 80.41380 85.70433
> colMin(tmp5,na.rm=TRUE)
[1] Inf 56.36245 59.89740 58.36589 60.65127 60.40361 55.95861 52.25044
[9] 53.68819 56.17414 62.12933 54.65040 57.42406 55.90626 56.56454 58.08869
[17] 53.33438 59.73839 56.82454 57.27764
>
>
>
>
> 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] 205.4081 150.8665 274.0625 259.0970 316.9875 192.5746 152.0698 211.8970
[9] 248.6082 159.4387
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 205.4081 150.8665 274.0625 259.0970 316.9875 192.5746 152.0698 211.8970
[9] 248.6082 159.4387
>
>
>
> 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-13 -2.273737e-13 0.000000e+00 -1.136868e-13 5.684342e-14
[6] 2.842171e-14 -1.421085e-13 -5.684342e-14 -8.526513e-14 1.705303e-13
[11] -5.684342e-14 5.684342e-14 -7.105427e-14 1.136868e-13 -5.684342e-14
[16] 5.684342e-14 0.000000e+00 5.684342e-14 -8.526513e-14 -1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
6 14
1 17
8 14
2 12
7 1
4 13
10 8
6 11
3 13
7 4
7 17
4 16
10 20
2 4
5 7
9 10
8 9
5 10
8 10
10 7
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] 2.953053
> Min(tmp)
[1] -2.941447
> mean(tmp)
[1] 0.03692282
> Sum(tmp)
[1] 3.692282
> Var(tmp)
[1] 0.8999627
>
> rowMeans(tmp)
[1] 0.03692282
> rowSums(tmp)
[1] 3.692282
> rowVars(tmp)
[1] 0.8999627
> rowSd(tmp)
[1] 0.9486636
> rowMax(tmp)
[1] 2.953053
> rowMin(tmp)
[1] -2.941447
>
> colMeans(tmp)
[1] -1.215127586 0.608486914 -0.856333610 -0.489263238 1.123382944
[6] 1.120363202 -0.912830761 -0.648391038 0.726612186 -0.601105599
[11] 0.355683450 -0.167899285 -0.793744722 -0.348649226 0.940329361
[16] -1.010101651 -2.941447220 -0.921276843 -0.646768301 1.055070282
[21] 1.235703065 0.703473229 1.145557100 0.006390552 0.676062576
[26] 0.533181947 -0.382286714 -0.442243576 -0.553483736 -0.094919596
[31] 0.111580925 -1.947757911 -0.725917126 -0.169506288 0.858111781
[36] 0.873075072 1.982677253 -1.185636796 -0.789318008 -1.084970498
[41] 0.206661591 -0.484984658 -0.400224746 -0.230069567 2.953052647
[46] 0.879858660 0.410590256 1.298447013 -0.167421756 0.382101849
[51] -1.854430742 -0.369010209 -0.016628167 0.776442207 0.487607338
[56] 0.266396340 -0.549591653 -0.673497412 -2.563906353 0.117180477
[61] 1.272906813 0.113014106 0.990952756 -0.270410372 0.927216904
[66] 0.564738653 0.650469845 -1.306193058 0.318748797 0.058569998
[71] -0.147945520 0.086516567 -0.229292640 1.465673529 0.028419588
[76] 1.175089391 -0.496070210 -0.745116263 1.010893298 -0.136177517
[81] 0.817395496 0.006406518 0.056793277 -0.500569717 0.883743898
[86] -0.142716215 0.755085218 0.047808943 0.685615581 -0.699954787
[91] 0.453866136 0.845595622 -1.463489127 -0.699760747 -0.424875402
[96] 0.611838874 2.279649634 0.898975110 -0.992633072 -0.653833312
> colSums(tmp)
[1] -1.215127586 0.608486914 -0.856333610 -0.489263238 1.123382944
[6] 1.120363202 -0.912830761 -0.648391038 0.726612186 -0.601105599
[11] 0.355683450 -0.167899285 -0.793744722 -0.348649226 0.940329361
[16] -1.010101651 -2.941447220 -0.921276843 -0.646768301 1.055070282
[21] 1.235703065 0.703473229 1.145557100 0.006390552 0.676062576
[26] 0.533181947 -0.382286714 -0.442243576 -0.553483736 -0.094919596
[31] 0.111580925 -1.947757911 -0.725917126 -0.169506288 0.858111781
[36] 0.873075072 1.982677253 -1.185636796 -0.789318008 -1.084970498
[41] 0.206661591 -0.484984658 -0.400224746 -0.230069567 2.953052647
[46] 0.879858660 0.410590256 1.298447013 -0.167421756 0.382101849
[51] -1.854430742 -0.369010209 -0.016628167 0.776442207 0.487607338
[56] 0.266396340 -0.549591653 -0.673497412 -2.563906353 0.117180477
[61] 1.272906813 0.113014106 0.990952756 -0.270410372 0.927216904
[66] 0.564738653 0.650469845 -1.306193058 0.318748797 0.058569998
[71] -0.147945520 0.086516567 -0.229292640 1.465673529 0.028419588
[76] 1.175089391 -0.496070210 -0.745116263 1.010893298 -0.136177517
[81] 0.817395496 0.006406518 0.056793277 -0.500569717 0.883743898
[86] -0.142716215 0.755085218 0.047808943 0.685615581 -0.699954787
[91] 0.453866136 0.845595622 -1.463489127 -0.699760747 -0.424875402
[96] 0.611838874 2.279649634 0.898975110 -0.992633072 -0.653833312
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] -1.215127586 0.608486914 -0.856333610 -0.489263238 1.123382944
[6] 1.120363202 -0.912830761 -0.648391038 0.726612186 -0.601105599
[11] 0.355683450 -0.167899285 -0.793744722 -0.348649226 0.940329361
[16] -1.010101651 -2.941447220 -0.921276843 -0.646768301 1.055070282
[21] 1.235703065 0.703473229 1.145557100 0.006390552 0.676062576
[26] 0.533181947 -0.382286714 -0.442243576 -0.553483736 -0.094919596
[31] 0.111580925 -1.947757911 -0.725917126 -0.169506288 0.858111781
[36] 0.873075072 1.982677253 -1.185636796 -0.789318008 -1.084970498
[41] 0.206661591 -0.484984658 -0.400224746 -0.230069567 2.953052647
[46] 0.879858660 0.410590256 1.298447013 -0.167421756 0.382101849
[51] -1.854430742 -0.369010209 -0.016628167 0.776442207 0.487607338
[56] 0.266396340 -0.549591653 -0.673497412 -2.563906353 0.117180477
[61] 1.272906813 0.113014106 0.990952756 -0.270410372 0.927216904
[66] 0.564738653 0.650469845 -1.306193058 0.318748797 0.058569998
[71] -0.147945520 0.086516567 -0.229292640 1.465673529 0.028419588
[76] 1.175089391 -0.496070210 -0.745116263 1.010893298 -0.136177517
[81] 0.817395496 0.006406518 0.056793277 -0.500569717 0.883743898
[86] -0.142716215 0.755085218 0.047808943 0.685615581 -0.699954787
[91] 0.453866136 0.845595622 -1.463489127 -0.699760747 -0.424875402
[96] 0.611838874 2.279649634 0.898975110 -0.992633072 -0.653833312
> colMin(tmp)
[1] -1.215127586 0.608486914 -0.856333610 -0.489263238 1.123382944
[6] 1.120363202 -0.912830761 -0.648391038 0.726612186 -0.601105599
[11] 0.355683450 -0.167899285 -0.793744722 -0.348649226 0.940329361
[16] -1.010101651 -2.941447220 -0.921276843 -0.646768301 1.055070282
[21] 1.235703065 0.703473229 1.145557100 0.006390552 0.676062576
[26] 0.533181947 -0.382286714 -0.442243576 -0.553483736 -0.094919596
[31] 0.111580925 -1.947757911 -0.725917126 -0.169506288 0.858111781
[36] 0.873075072 1.982677253 -1.185636796 -0.789318008 -1.084970498
[41] 0.206661591 -0.484984658 -0.400224746 -0.230069567 2.953052647
[46] 0.879858660 0.410590256 1.298447013 -0.167421756 0.382101849
[51] -1.854430742 -0.369010209 -0.016628167 0.776442207 0.487607338
[56] 0.266396340 -0.549591653 -0.673497412 -2.563906353 0.117180477
[61] 1.272906813 0.113014106 0.990952756 -0.270410372 0.927216904
[66] 0.564738653 0.650469845 -1.306193058 0.318748797 0.058569998
[71] -0.147945520 0.086516567 -0.229292640 1.465673529 0.028419588
[76] 1.175089391 -0.496070210 -0.745116263 1.010893298 -0.136177517
[81] 0.817395496 0.006406518 0.056793277 -0.500569717 0.883743898
[86] -0.142716215 0.755085218 0.047808943 0.685615581 -0.699954787
[91] 0.453866136 0.845595622 -1.463489127 -0.699760747 -0.424875402
[96] 0.611838874 2.279649634 0.898975110 -0.992633072 -0.653833312
> colMedians(tmp)
[1] -1.215127586 0.608486914 -0.856333610 -0.489263238 1.123382944
[6] 1.120363202 -0.912830761 -0.648391038 0.726612186 -0.601105599
[11] 0.355683450 -0.167899285 -0.793744722 -0.348649226 0.940329361
[16] -1.010101651 -2.941447220 -0.921276843 -0.646768301 1.055070282
[21] 1.235703065 0.703473229 1.145557100 0.006390552 0.676062576
[26] 0.533181947 -0.382286714 -0.442243576 -0.553483736 -0.094919596
[31] 0.111580925 -1.947757911 -0.725917126 -0.169506288 0.858111781
[36] 0.873075072 1.982677253 -1.185636796 -0.789318008 -1.084970498
[41] 0.206661591 -0.484984658 -0.400224746 -0.230069567 2.953052647
[46] 0.879858660 0.410590256 1.298447013 -0.167421756 0.382101849
[51] -1.854430742 -0.369010209 -0.016628167 0.776442207 0.487607338
[56] 0.266396340 -0.549591653 -0.673497412 -2.563906353 0.117180477
[61] 1.272906813 0.113014106 0.990952756 -0.270410372 0.927216904
[66] 0.564738653 0.650469845 -1.306193058 0.318748797 0.058569998
[71] -0.147945520 0.086516567 -0.229292640 1.465673529 0.028419588
[76] 1.175089391 -0.496070210 -0.745116263 1.010893298 -0.136177517
[81] 0.817395496 0.006406518 0.056793277 -0.500569717 0.883743898
[86] -0.142716215 0.755085218 0.047808943 0.685615581 -0.699954787
[91] 0.453866136 0.845595622 -1.463489127 -0.699760747 -0.424875402
[96] 0.611838874 2.279649634 0.898975110 -0.992633072 -0.653833312
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.215128 0.6084869 -0.8563336 -0.4892632 1.123383 1.120363 -0.9128308
[2,] -1.215128 0.6084869 -0.8563336 -0.4892632 1.123383 1.120363 -0.9128308
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.648391 0.7266122 -0.6011056 0.3556834 -0.1678993 -0.7937447 -0.3486492
[2,] -0.648391 0.7266122 -0.6011056 0.3556834 -0.1678993 -0.7937447 -0.3486492
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.9403294 -1.010102 -2.941447 -0.9212768 -0.6467683 1.05507 1.235703
[2,] 0.9403294 -1.010102 -2.941447 -0.9212768 -0.6467683 1.05507 1.235703
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.7034732 1.145557 0.006390552 0.6760626 0.5331819 -0.3822867 -0.4422436
[2,] 0.7034732 1.145557 0.006390552 0.6760626 0.5331819 -0.3822867 -0.4422436
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.5534837 -0.0949196 0.1115809 -1.947758 -0.7259171 -0.1695063 0.8581118
[2,] -0.5534837 -0.0949196 0.1115809 -1.947758 -0.7259171 -0.1695063 0.8581118
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.8730751 1.982677 -1.185637 -0.789318 -1.08497 0.2066616 -0.4849847
[2,] 0.8730751 1.982677 -1.185637 -0.789318 -1.08497 0.2066616 -0.4849847
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.4002247 -0.2300696 2.953053 0.8798587 0.4105903 1.298447 -0.1674218
[2,] -0.4002247 -0.2300696 2.953053 0.8798587 0.4105903 1.298447 -0.1674218
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.3821018 -1.854431 -0.3690102 -0.01662817 0.7764422 0.4876073 0.2663963
[2,] 0.3821018 -1.854431 -0.3690102 -0.01662817 0.7764422 0.4876073 0.2663963
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.5495917 -0.6734974 -2.563906 0.1171805 1.272907 0.1130141 0.9909528
[2,] -0.5495917 -0.6734974 -2.563906 0.1171805 1.272907 0.1130141 0.9909528
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.2704104 0.9272169 0.5647387 0.6504698 -1.306193 0.3187488 0.05857
[2,] -0.2704104 0.9272169 0.5647387 0.6504698 -1.306193 0.3187488 0.05857
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.1479455 0.08651657 -0.2292926 1.465674 0.02841959 1.175089 -0.4960702
[2,] -0.1479455 0.08651657 -0.2292926 1.465674 0.02841959 1.175089 -0.4960702
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.7451163 1.010893 -0.1361775 0.8173955 0.006406518 0.05679328 -0.5005697
[2,] -0.7451163 1.010893 -0.1361775 0.8173955 0.006406518 0.05679328 -0.5005697
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.8837439 -0.1427162 0.7550852 0.04780894 0.6856156 -0.6999548 0.4538661
[2,] 0.8837439 -0.1427162 0.7550852 0.04780894 0.6856156 -0.6999548 0.4538661
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.8455956 -1.463489 -0.6997607 -0.4248754 0.6118389 2.27965 0.8989751
[2,] 0.8455956 -1.463489 -0.6997607 -0.4248754 0.6118389 2.27965 0.8989751
[,99] [,100]
[1,] -0.9926331 -0.6538333
[2,] -0.9926331 -0.6538333
>
>
> Max(tmp2)
[1] 2.602385
> Min(tmp2)
[1] -2.20821
> mean(tmp2)
[1] -0.1093628
> Sum(tmp2)
[1] -10.93628
> Var(tmp2)
[1] 1.046098
>
> rowMeans(tmp2)
[1] 0.042734207 0.447834578 -1.086519612 0.198464526 -0.774564274
[6] -1.448819403 -1.163571302 -1.282702028 -0.914786096 -1.946073451
[11] 0.702988481 -0.698028976 -0.633258038 -1.195822414 -0.003606732
[16] -0.547243146 -1.589245174 -1.240451966 0.782122422 0.225759152
[21] 2.602384994 -1.114210566 0.799753388 0.111255218 0.104675787
[26] 0.016002404 0.314066670 -0.510948951 -2.053838694 0.409239682
[31] 0.238021188 0.729933328 -0.440289923 -1.092750695 1.040877600
[36] 0.063656048 0.685471828 -1.141657989 0.222963571 0.828650818
[41] 0.499624993 0.514130852 -0.743373473 0.114063896 0.926766823
[46] -1.780205864 0.442311776 0.159555172 -0.163279214 -0.143312553
[51] 1.494263680 0.964233735 -1.503946292 0.107139532 -0.002015727
[56] -0.906681280 -0.949497686 -0.781719435 -0.376506739 0.173588917
[61] 2.530206841 0.113427872 1.518211651 -1.848965643 1.809562224
[66] -0.207322117 0.950194364 1.022571233 0.597180118 -1.004033700
[71] 1.433071423 0.114878704 0.977657748 -0.121879887 -2.208209530
[76] -0.509386953 -1.095675526 -0.589348395 1.412736228 -0.435428780
[81] -0.505146933 -2.051561671 -0.146788217 -0.789214395 0.884789665
[86] 0.981642929 1.155544791 -0.405101963 0.709642056 -2.075558559
[91] -0.057678793 1.047428729 1.233195853 -0.839198562 -0.295557141
[96] -1.325407915 0.627223648 -0.189877779 0.645384063 -1.733095279
> rowSums(tmp2)
[1] 0.042734207 0.447834578 -1.086519612 0.198464526 -0.774564274
[6] -1.448819403 -1.163571302 -1.282702028 -0.914786096 -1.946073451
[11] 0.702988481 -0.698028976 -0.633258038 -1.195822414 -0.003606732
[16] -0.547243146 -1.589245174 -1.240451966 0.782122422 0.225759152
[21] 2.602384994 -1.114210566 0.799753388 0.111255218 0.104675787
[26] 0.016002404 0.314066670 -0.510948951 -2.053838694 0.409239682
[31] 0.238021188 0.729933328 -0.440289923 -1.092750695 1.040877600
[36] 0.063656048 0.685471828 -1.141657989 0.222963571 0.828650818
[41] 0.499624993 0.514130852 -0.743373473 0.114063896 0.926766823
[46] -1.780205864 0.442311776 0.159555172 -0.163279214 -0.143312553
[51] 1.494263680 0.964233735 -1.503946292 0.107139532 -0.002015727
[56] -0.906681280 -0.949497686 -0.781719435 -0.376506739 0.173588917
[61] 2.530206841 0.113427872 1.518211651 -1.848965643 1.809562224
[66] -0.207322117 0.950194364 1.022571233 0.597180118 -1.004033700
[71] 1.433071423 0.114878704 0.977657748 -0.121879887 -2.208209530
[76] -0.509386953 -1.095675526 -0.589348395 1.412736228 -0.435428780
[81] -0.505146933 -2.051561671 -0.146788217 -0.789214395 0.884789665
[86] 0.981642929 1.155544791 -0.405101963 0.709642056 -2.075558559
[91] -0.057678793 1.047428729 1.233195853 -0.839198562 -0.295557141
[96] -1.325407915 0.627223648 -0.189877779 0.645384063 -1.733095279
> 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] 0.042734207 0.447834578 -1.086519612 0.198464526 -0.774564274
[6] -1.448819403 -1.163571302 -1.282702028 -0.914786096 -1.946073451
[11] 0.702988481 -0.698028976 -0.633258038 -1.195822414 -0.003606732
[16] -0.547243146 -1.589245174 -1.240451966 0.782122422 0.225759152
[21] 2.602384994 -1.114210566 0.799753388 0.111255218 0.104675787
[26] 0.016002404 0.314066670 -0.510948951 -2.053838694 0.409239682
[31] 0.238021188 0.729933328 -0.440289923 -1.092750695 1.040877600
[36] 0.063656048 0.685471828 -1.141657989 0.222963571 0.828650818
[41] 0.499624993 0.514130852 -0.743373473 0.114063896 0.926766823
[46] -1.780205864 0.442311776 0.159555172 -0.163279214 -0.143312553
[51] 1.494263680 0.964233735 -1.503946292 0.107139532 -0.002015727
[56] -0.906681280 -0.949497686 -0.781719435 -0.376506739 0.173588917
[61] 2.530206841 0.113427872 1.518211651 -1.848965643 1.809562224
[66] -0.207322117 0.950194364 1.022571233 0.597180118 -1.004033700
[71] 1.433071423 0.114878704 0.977657748 -0.121879887 -2.208209530
[76] -0.509386953 -1.095675526 -0.589348395 1.412736228 -0.435428780
[81] -0.505146933 -2.051561671 -0.146788217 -0.789214395 0.884789665
[86] 0.981642929 1.155544791 -0.405101963 0.709642056 -2.075558559
[91] -0.057678793 1.047428729 1.233195853 -0.839198562 -0.295557141
[96] -1.325407915 0.627223648 -0.189877779 0.645384063 -1.733095279
> rowMin(tmp2)
[1] 0.042734207 0.447834578 -1.086519612 0.198464526 -0.774564274
[6] -1.448819403 -1.163571302 -1.282702028 -0.914786096 -1.946073451
[11] 0.702988481 -0.698028976 -0.633258038 -1.195822414 -0.003606732
[16] -0.547243146 -1.589245174 -1.240451966 0.782122422 0.225759152
[21] 2.602384994 -1.114210566 0.799753388 0.111255218 0.104675787
[26] 0.016002404 0.314066670 -0.510948951 -2.053838694 0.409239682
[31] 0.238021188 0.729933328 -0.440289923 -1.092750695 1.040877600
[36] 0.063656048 0.685471828 -1.141657989 0.222963571 0.828650818
[41] 0.499624993 0.514130852 -0.743373473 0.114063896 0.926766823
[46] -1.780205864 0.442311776 0.159555172 -0.163279214 -0.143312553
[51] 1.494263680 0.964233735 -1.503946292 0.107139532 -0.002015727
[56] -0.906681280 -0.949497686 -0.781719435 -0.376506739 0.173588917
[61] 2.530206841 0.113427872 1.518211651 -1.848965643 1.809562224
[66] -0.207322117 0.950194364 1.022571233 0.597180118 -1.004033700
[71] 1.433071423 0.114878704 0.977657748 -0.121879887 -2.208209530
[76] -0.509386953 -1.095675526 -0.589348395 1.412736228 -0.435428780
[81] -0.505146933 -2.051561671 -0.146788217 -0.789214395 0.884789665
[86] 0.981642929 1.155544791 -0.405101963 0.709642056 -2.075558559
[91] -0.057678793 1.047428729 1.233195853 -0.839198562 -0.295557141
[96] -1.325407915 0.627223648 -0.189877779 0.645384063 -1.733095279
>
> colMeans(tmp2)
[1] -0.1093628
> colSums(tmp2)
[1] -10.93628
> colVars(tmp2)
[1] 1.046098
> colSd(tmp2)
[1] 1.022789
> colMax(tmp2)
[1] 2.602385
> colMin(tmp2)
[1] -2.20821
> colMedians(tmp2)
[1] -0.002811229
> colRanges(tmp2)
[,1]
[1,] -2.208210
[2,] 2.602385
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -3.36740932 0.02000315 -1.04202089 -3.45900308 -2.51493286 -3.66081566
[7] 2.91071233 -0.95938903 0.16043491 0.81593160
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.93856809
[2,] -0.83516358
[3,] 0.09121748
[4,] 0.29425725
[5,] 1.43662420
>
> rowApply(tmp,sum)
[1] 1.8710005 1.1962205 0.5401931 -3.0578546 -2.0250464 -4.8253924
[7] -1.2771234 -2.3623640 -1.2431931 0.0870710
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 6 5 1 10 2 6 9 8 4
[2,] 4 5 8 8 6 4 8 1 9 10
[3,] 8 3 10 5 1 3 9 3 7 8
[4,] 5 2 6 2 3 9 1 8 2 9
[5,] 3 4 1 6 9 7 7 6 3 5
[6,] 7 7 4 4 5 1 2 4 4 7
[7,] 10 10 2 10 8 10 3 5 1 6
[8,] 2 9 7 7 7 5 5 2 6 1
[9,] 9 8 3 3 4 6 4 7 10 3
[10,] 6 1 9 9 2 8 10 10 5 2
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.4914130 -3.1571347 0.1198516 -2.9688392 -3.1335800 -1.7119661
[7] -1.8674848 2.4650167 -1.6996535 0.1161326 -3.3829771 -1.9903134
[13] -1.7257555 2.1178885 2.4257468 2.9242936 -0.3206013 1.8229455
[19] 1.9956308 3.1819969
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.5205538
[2,] -0.2575860
[3,] -0.1266586
[4,] 0.1860519
[5,] 0.2273336
>
> rowApply(tmp,sum)
[1] 2.044175 -3.344338 -2.721058 1.378263 -2.637258
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 9 8 14 8 11
[2,] 17 3 2 15 1
[3,] 11 4 9 13 14
[4,] 3 14 7 10 5
[5,] 10 6 6 4 7
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.1266586 1.0981019 0.1605121 -0.954497411 -0.07817861 -0.3405025
[2,] -0.5205538 -0.8173328 -0.7994248 -0.004037432 -0.62512089 -1.5450815
[3,] 0.1860519 -1.2111809 -0.3132140 -0.556387595 -0.83799467 -0.9476577
[4,] -0.2575860 0.6655643 0.5745088 -0.250570845 -0.67651897 0.6069073
[5,] 0.2273336 -2.8922871 0.4974696 -1.203345901 -0.91576689 0.5143682
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.6126378 1.7560881 0.18906466 -0.31832345 -2.26411255 1.3846149
[2,] -0.5170150 1.1093143 -0.17865383 1.69496156 -0.52329812 -1.2848704
[3,] -0.3193785 -0.1251063 -1.15539713 -0.08088128 0.08214849 -1.2653547
[4,] 1.4773038 -0.2564013 -0.06405674 0.20512684 -1.12776511 0.7401158
[5,] -1.8957573 -0.0188781 -0.49061049 -1.38475103 0.45005019 -1.5648191
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.3194958 0.4798777 1.5553692 0.64727351 1.08962890 -0.254534914
[2,] -0.3930216 -0.6825714 -0.5104084 0.07300249 1.09005482 -0.007032586
[3,] 1.3921758 -0.1489717 0.2344976 0.88349463 -1.10019029 0.509457593
[4,] -0.4625057 1.7525609 -0.3213702 0.86958601 -1.34413924 -0.602935401
[5,] -0.9429082 0.7169930 1.4676586 0.45093696 -0.05595547 2.177990758
[,19] [,20]
[1,] 0.7523053 -0.7997198
[2,] 0.2068743 0.8898766
[3,] 1.1399656 0.9128656
[4,] -0.9643168 0.8147557
[5,] 0.8608024 1.3642188
>
>
> 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 : 562 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 0.8459329 1.099106 -1.334399 1.674742 2.407365 0.8931176 0.5553847
col8 col9 col10 col11 col12 col13 col14
row1 0.07138166 -1.998853 -1.178667 1.015992 -0.1973721 -0.4910797 0.07880115
col15 col16 col17 col18 col19 col20
row1 0.6694418 0.3617548 -0.2510455 1.463382 0.7009127 0.03558656
> tmp[,"col10"]
col10
row1 -1.1786670
row2 0.1462230
row3 0.0678651
row4 -0.7906566
row5 -0.1453141
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.8459329 1.0991060 -1.3343987 1.6747420 2.407365 0.8931176 0.5553847
row5 -0.3509720 0.6247815 0.5278798 0.2273895 -2.177302 1.5386981 1.5822072
col8 col9 col10 col11 col12 col13 col14
row1 0.07138166 -1.998853 -1.1786670 1.015992 -0.1973721 -0.4910797 0.07880115
row5 0.93715717 1.968789 -0.1453141 -1.019106 0.6744614 1.8433719 0.58344081
col15 col16 col17 col18 col19 col20
row1 0.6694418 0.3617548 -0.25104546 1.463382 0.7009127 0.03558656
row5 0.2146033 -0.3787457 0.03061066 0.181197 -0.3078112 -0.92482353
> tmp[,c("col6","col20")]
col6 col20
row1 0.8931176 0.03558656
row2 -0.7614436 0.30340191
row3 -1.5771041 1.09859835
row4 0.1327524 -0.88702828
row5 1.5386981 -0.92482353
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.8931176 0.03558656
row5 1.5386981 -0.92482353
>
>
>
>
> 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 49.54059 51.51448 50.40439 51.66166 49.93272 105.607 50.4523 51.21755
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.61524 47.93174 49.62379 49.28595 50.14042 50.46349 49.49054 49.22604
col17 col18 col19 col20
row1 50.30586 48.15581 52.83316 106.9416
> tmp[,"col10"]
col10
row1 47.93174
row2 30.33653
row3 30.26902
row4 30.00123
row5 49.86975
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.54059 51.51448 50.40439 51.66166 49.93272 105.6070 50.45230 51.21755
row5 51.40134 50.81852 49.29338 51.21562 50.58743 103.2077 49.45517 49.11506
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.61524 47.93174 49.62379 49.28595 50.14042 50.46349 49.49054 49.22604
row5 49.94097 49.86975 47.97519 50.32452 49.11564 48.10166 49.79119 49.06258
col17 col18 col19 col20
row1 50.30586 48.15581 52.83316 106.9416
row5 49.98419 49.58571 51.04868 104.4113
> tmp[,c("col6","col20")]
col6 col20
row1 105.60700 106.94156
row2 74.04726 74.10025
row3 75.44566 76.17146
row4 76.58010 74.55287
row5 103.20772 104.41132
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.6070 106.9416
row5 103.2077 104.4113
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.6070 106.9416
row5 103.2077 104.4113
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.69726408
[2,] -1.39201571
[3,] 1.09483551
[4,] -0.07223249
[5,] -0.12597651
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.008963927 -1.301984940
[2,] 1.694800941 0.006059178
[3,] 0.861631285 -0.584117501
[4,] 1.171046122 -0.106852724
[5,] -0.141272518 -0.547335905
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.7871357 -0.2338427
[2,] -0.7371668 -1.0805332
[3,] -0.4082799 0.1853244
[4,] 1.6757528 0.6369590
[5,] -1.3490809 0.8654399
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.787136
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.7871357
[2,] -0.7371668
>
>
>
> 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 -0.2452743 1.772311 0.5544820 0.3139992 -1.2758868 1.3657771 0.4921861
row1 -0.9752452 2.476749 0.8664444 -0.7881304 -0.2017068 0.4115175 0.6551952
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -1.7097679 0.3587866 0.6305116 -1.3191059 -1.0381345 -1.820848 -0.2670037
row1 0.3550681 0.2476996 0.7550039 0.8884395 -0.4019518 2.194061 -1.1142287
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.8060375 -0.5884368 -0.4257041 0.2737428 0.1434370 0.575667
row1 0.4792600 -0.4464058 -0.7263199 -1.5643725 0.6158844 2.115345
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.07526807 -1.213921 -1.346949 -1.137139 -0.4462154 -0.7267388 -0.5600422
[,8] [,9] [,10]
row2 0.9788053 -0.2668515 -0.6402868
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.07158656 -2.079453 0.6581835 -1.223288 1.383188 2.043547 0.05632664
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.41669 -2.553959 -0.9293954 0.7434788 0.538901 -0.3649947 0.1927394
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.5798488 -0.8146802 0.9488029 -0.7661028 1.343867 1.005149
>
>
> 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: 0x6000036bc000>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e9969466569"
[2] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e99cac067e"
[3] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e9971de40b1"
[4] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e9936695ede"
[5] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e993fd35cba"
[6] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e994d6cd812"
[7] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e9924ddad74"
[8] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e9955a6ad94"
[9] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e9931cdfb7a"
[10] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e994a392021"
[11] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e996c6c7c98"
[12] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e99466816c4"
[13] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e995baec1f8"
[14] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e992e40afce"
[15] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM2e9918d6151b"
>
>
> ### 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: 0x6000036d4180>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000036d4180>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6000036d4180>
> rowMedians(tmp)
[1] -0.381807827 -0.295516148 -0.012023078 0.433452549 -0.170950569
[6] -0.623911262 0.357219656 0.084715343 -0.167918515 0.357131591
[11] -0.265499898 -0.517748581 0.376609615 0.001155300 -0.145176710
[16] -0.058901766 -0.382156205 -0.259066555 -0.386899779 0.199953912
[21] -1.016075997 -0.525225134 -0.015991619 -0.089737510 0.417689056
[26] -0.480212522 0.010585334 0.228958887 -0.060136131 0.489655497
[31] 0.297546065 -0.059943860 -0.832306360 -0.064616442 0.093809309
[36] 0.144106255 0.126262897 -0.078334189 -0.205397991 -0.430612526
[41] 0.081446038 -0.089963898 0.034550344 0.472296280 -0.018971341
[46] -0.043690077 -0.338726570 -0.671691038 0.107438560 -0.224487552
[51] -0.357408872 0.168114072 0.142254697 0.037615519 -0.262454891
[56] 0.475790398 0.622030573 -0.425292203 0.018489922 -0.192670568
[61] -0.231217793 -0.103293386 -0.394024056 -0.002242009 -0.405551955
[66] 0.135930026 -0.168145057 0.083512011 -0.087492809 0.132391845
[71] 0.229118469 -0.094071784 0.377245962 -0.106103073 0.400941742
[76] -0.003937339 -0.002912536 0.159075373 0.134622420 -0.023467047
[81] 0.355270538 0.161384769 0.738141753 -0.490520011 0.119145451
[86] -0.004659482 0.203737052 0.120634885 -0.454973606 -0.192332745
[91] -0.270654599 -0.624439280 0.500605137 0.110642466 -0.217435384
[96] -0.002685763 0.396014924 -0.422767021 0.028444959 0.130536535
[101] -0.182441851 0.391384923 0.510080946 0.136074998 0.003962278
[106] -0.234089834 0.284702977 0.552720437 -0.563168465 -0.101926328
[111] -0.133464459 -0.344470445 0.558088993 -0.325246066 0.184915920
[116] -0.331235367 0.032391588 -0.038976988 0.283036332 -1.018210219
[121] 0.160072517 -0.083063715 -0.178400887 -0.220074633 -0.106702536
[126] 0.100127488 -0.324804676 -0.399444462 0.024998766 0.162311533
[131] 0.070398728 -0.115212652 -0.798286907 -0.268458811 -0.227213968
[136] -0.602285022 -0.235370323 -0.126050663 -0.006442522 -0.096657694
[141] -0.430813953 -0.008850355 -0.079418768 -0.266355158 -0.540380983
[146] -0.519070371 -0.009125977 0.074391455 -0.024769317 0.426681553
[151] 0.235552813 0.258714440 -0.042810977 0.638409534 0.204579099
[156] -0.367257321 -0.027810433 -0.214300854 0.516560211 0.203854202
[161] 0.201609022 0.045547793 -0.201246196 -0.001705739 0.097611162
[166] -0.087385216 -0.735750342 -0.142474876 -0.059348580 -0.380782449
[171] 0.320567366 0.120212812 -0.028682156 0.326176799 0.437883432
[176] 0.057054758 -0.671407616 0.206073474 0.364431981 -0.008087774
[181] 0.074269818 -0.514277310 -0.136658124 0.962612672 -0.038867555
[186] -0.082200629 0.380430796 0.306576039 0.131795055 0.252661741
[191] -0.103219657 0.561481966 0.406091503 0.089264888 -0.001387507
[196] 0.063954268 0.047915937 -0.860846728 0.085063485 0.195941250
[201] 0.543917300 -0.561027749 -0.188821146 0.176247413 0.351965594
[206] 0.233690259 0.155793914 0.048695032 -0.036230588 -0.343611757
[211] 0.753530851 -0.396584943 0.281381442 0.088286847 -0.620266542
[216] 0.351889101 -0.033043547 -0.252167600 0.419536108 -0.273220686
[221] 0.077688375 0.329232278 -0.283358011 0.404697658 -0.169806999
[226] -0.010762231 0.175142054 -0.341274382 0.095683669 0.052409493
>
> proc.time()
user system elapsed
5.164 18.330 25.002
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup"
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: 0x600003398000>
> .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: 0x600003398000>
> .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: 0x600003398000>
> .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: 0x600003398000>
> 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: 0x600003384000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003384000>
> .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: 0x600003384000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003384000>
> .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: 0x600003384000>
> 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: 0x600003380000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003380000>
> .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: 0x600003380000>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003380000>
> .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: 0x600003380000>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600003380000>
> .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: 0x600003380000>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600003380000>
> .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: 0x600003380000>
> 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: 0x600003380180>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600003380180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003380180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003380180>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile354c7594f9a6" "BufferedMatrixFile354c7923d99"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile354c7594f9a6" "BufferedMatrixFile354c7923d99"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033a0120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033a0120>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000033a0120>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000033a0120>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000033a0120>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000033a0120>
> .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: 0x600003388060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003388060>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003388060>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600003388060>
> 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: 0x600003380420>
> .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: 0x600003380420>
> rm(P)
>
> proc.time()
user system elapsed
0.603 0.210 0.796
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup"
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
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.587 0.140 0.708