Ben Bolstad
| Snapshot Date: 2024-06-09 14:00 -0400 (Sun, 09 Jun 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 2024-06-11 15:41 -0400 (Tue, 11 Jun 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" | 4679 |
| palomino4 | Windows Server 2022 Datacenter | x64 | 4.4.0 RC (2024-04-16 r86468 ucrt) -- "Puppy Cup" | 4414 |
| merida1 | macOS 12.7.4 Monterey | x86_64 | 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup" | 4441 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup" | 4394 |
| 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 245/2239 | 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: 2024-06-10 00:45:08 -0400 (Mon, 10 Jun 2024) |
| EndedAt: 2024-06-10 00:46:41 -0400 (Mon, 10 Jun 2024) |
| EllapsedTime: 93.5 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
0.618 0.225 0.937
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 1035477 55.4 NA 638617 34.2
Vcells 877663 6.7 8388608 64.0 65536 2072283 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] "Mon Jun 10 00:45:55 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] "Mon Jun 10 00:45:56 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: 0x6000024f8180>
>
>
>
> 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] "Mon Jun 10 00:46:04 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] "Mon Jun 10 00:46:07 2024"
>
> ColMode(tmp2)
<pointer: 0x6000024f8180>
>
>
>
> ### 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,] 100.8389333 1.3049467 -0.9034481 0.5966279
[2,] -0.2744652 0.9477663 -0.3631620 0.6250013
[3,] -1.6498557 -0.5888024 -1.1076183 0.4452843
[4,] -1.6113882 1.6138503 -0.1049336 -0.2896765
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.8389333 1.3049467 0.9034481 0.5966279
[2,] 0.2744652 0.9477663 0.3631620 0.6250013
[3,] 1.6498557 0.5888024 1.1076183 0.4452843
[4,] 1.6113882 1.6138503 0.1049336 0.2896765
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0418591 1.1423426 0.9504989 0.7724169
[2,] 0.5238943 0.9735329 0.6026292 0.7905702
[3,] 1.2844671 0.7673346 1.0524345 0.6672963
[4,] 1.2694047 1.2703741 0.3239346 0.5382160
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 226.25752 37.72837 35.40844 33.32080
[2,] 30.51341 35.68310 31.38945 33.53070
[3,] 39.49453 33.26215 36.63196 32.11825
[4,] 39.30543 39.31759 28.34428 30.67184
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600002494000>
> exp(tmp5)
<pointer: 0x600002494000>
> log(tmp5,2)
<pointer: 0x600002494000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.9254
> Min(tmp5)
[1] 52.86995
> mean(tmp5)
[1] 72.77393
> Sum(tmp5)
[1] 14554.79
> Var(tmp5)
[1] 871.8694
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.61135 70.79319 72.36947 68.22078 69.74876 71.47307 70.08483 71.23021
[9] 72.53635 71.67129
> rowSums(tmp5)
[1] 1792.227 1415.864 1447.389 1364.416 1394.975 1429.461 1401.697 1424.604
[9] 1450.727 1433.426
> rowVars(tmp5)
[1] 8121.67592 36.97131 79.43938 62.81673 86.92286 69.83287
[7] 44.09916 70.67517 134.47321 77.36007
> rowSd(tmp5)
[1] 90.120341 6.080404 8.912877 7.925701 9.323243 8.356607 6.640720
[8] 8.406853 11.596258 8.795458
> rowMax(tmp5)
[1] 470.92539 78.60770 93.01273 81.83441 89.58111 86.09332 87.31986
[8] 83.73548 91.42694 88.27881
> rowMin(tmp5)
[1] 53.60563 57.03390 57.63341 54.01424 54.74301 56.77983 58.83917 56.86274
[9] 55.75503 52.86995
>
> colMeans(tmp5)
[1] 112.43660 75.17583 71.04324 71.50684 69.89356 68.97004 68.53615
[8] 71.89190 70.01973 69.63063 65.78817 73.04290 69.73853 69.73040
[15] 75.57717 72.89384 70.30939 69.04252 72.20268 68.04845
> colSums(tmp5)
[1] 1124.3660 751.7583 710.4324 715.0684 698.9356 689.7004 685.3615
[8] 718.9190 700.1973 696.3063 657.8817 730.4290 697.3853 697.3040
[15] 755.7717 728.9384 703.0939 690.4252 722.0268 680.4845
> colVars(tmp5)
[1] 15963.55490 49.83340 108.26432 60.87217 92.13356 17.97898
[7] 61.79927 70.27805 55.69559 71.59291 17.87594 107.40852
[13] 48.60102 125.14953 71.25246 34.11180 105.11430 137.28976
[19] 57.51575 65.74313
> colSd(tmp5)
[1] 126.346962 7.059277 10.405014 7.802062 9.598623 4.240162
[7] 7.861251 8.383201 7.462948 8.461259 4.227995 10.363808
[13] 6.971443 11.187025 8.441117 5.840531 10.252527 11.717071
[19] 7.583914 8.108214
> colMax(tmp5)
[1] 470.92539 88.27881 89.58111 86.09332 86.12388 77.88241 78.25333
[8] 82.90538 82.19372 85.62365 73.23550 93.01273 80.34598 87.31986
[15] 85.83353 83.25945 83.59716 91.42694 80.66967 79.21827
> colMin(tmp5)
[1] 58.61670 64.61385 56.86274 62.52741 53.60563 63.12568 57.03390 59.31824
[9] 58.77993 56.77983 59.16173 55.75503 59.79338 54.01424 62.49413 64.02135
[17] 54.86671 52.86995 58.83917 56.91132
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 89.61135 70.79319 72.36947 68.22078 69.74876 71.47307 NA 71.23021
[9] 72.53635 71.67129
> rowSums(tmp5)
[1] 1792.227 1415.864 1447.389 1364.416 1394.975 1429.461 NA 1424.604
[9] 1450.727 1433.426
> rowVars(tmp5)
[1] 8121.67592 36.97131 79.43938 62.81673 86.92286 69.83287
[7] 39.15351 70.67517 134.47321 77.36007
> rowSd(tmp5)
[1] 90.120341 6.080404 8.912877 7.925701 9.323243 8.356607 6.257277
[8] 8.406853 11.596258 8.795458
> rowMax(tmp5)
[1] 470.92539 78.60770 93.01273 81.83441 89.58111 86.09332 NA
[8] 83.73548 91.42694 88.27881
> rowMin(tmp5)
[1] 53.60563 57.03390 57.63341 54.01424 54.74301 56.77983 NA 56.86274
[9] 55.75503 52.86995
>
> colMeans(tmp5)
[1] 112.43660 75.17583 71.04324 71.50684 69.89356 68.97004 68.53615
[8] 71.89190 70.01973 69.63063 65.78817 73.04290 69.73853 69.73040
[15] 75.57717 72.89384 70.30939 69.04252 NA 68.04845
> colSums(tmp5)
[1] 1124.3660 751.7583 710.4324 715.0684 698.9356 689.7004 685.3615
[8] 718.9190 700.1973 696.3063 657.8817 730.4290 697.3853 697.3040
[15] 755.7717 728.9384 703.0939 690.4252 NA 680.4845
> colVars(tmp5)
[1] 15963.55490 49.83340 108.26432 60.87217 92.13356 17.97898
[7] 61.79927 70.27805 55.69559 71.59291 17.87594 107.40852
[13] 48.60102 125.14953 71.25246 34.11180 105.11430 137.28976
[19] NA 65.74313
> colSd(tmp5)
[1] 126.346962 7.059277 10.405014 7.802062 9.598623 4.240162
[7] 7.861251 8.383201 7.462948 8.461259 4.227995 10.363808
[13] 6.971443 11.187025 8.441117 5.840531 10.252527 11.717071
[19] NA 8.108214
> colMax(tmp5)
[1] 470.92539 88.27881 89.58111 86.09332 86.12388 77.88241 78.25333
[8] 82.90538 82.19372 85.62365 73.23550 93.01273 80.34598 87.31986
[15] 85.83353 83.25945 83.59716 91.42694 NA 79.21827
> colMin(tmp5)
[1] 58.61670 64.61385 56.86274 62.52741 53.60563 63.12568 57.03390 59.31824
[9] 58.77993 56.77983 59.16173 55.75503 59.79338 54.01424 62.49413 64.02135
[17] 54.86671 52.86995 NA 56.91132
>
> Max(tmp5,na.rm=TRUE)
[1] 470.9254
> Min(tmp5,na.rm=TRUE)
[1] 52.86995
> mean(tmp5,na.rm=TRUE)
[1] 72.84395
> Sum(tmp5,na.rm=TRUE)
[1] 14495.95
> Var(tmp5,na.rm=TRUE)
[1] 875.2872
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.61135 70.79319 72.36947 68.22078 69.74876 71.47307 70.67670 71.23021
[9] 72.53635 71.67129
> rowSums(tmp5,na.rm=TRUE)
[1] 1792.227 1415.864 1447.389 1364.416 1394.975 1429.461 1342.857 1424.604
[9] 1450.727 1433.426
> rowVars(tmp5,na.rm=TRUE)
[1] 8121.67592 36.97131 79.43938 62.81673 86.92286 69.83287
[7] 39.15351 70.67517 134.47321 77.36007
> rowSd(tmp5,na.rm=TRUE)
[1] 90.120341 6.080404 8.912877 7.925701 9.323243 8.356607 6.257277
[8] 8.406853 11.596258 8.795458
> rowMax(tmp5,na.rm=TRUE)
[1] 470.92539 78.60770 93.01273 81.83441 89.58111 86.09332 87.31986
[8] 83.73548 91.42694 88.27881
> rowMin(tmp5,na.rm=TRUE)
[1] 53.60563 57.03390 57.63341 54.01424 54.74301 56.77983 63.12568 56.86274
[9] 55.75503 52.86995
>
> colMeans(tmp5,na.rm=TRUE)
[1] 112.43660 75.17583 71.04324 71.50684 69.89356 68.97004 68.53615
[8] 71.89190 70.01973 69.63063 65.78817 73.04290 69.73853 69.73040
[15] 75.57717 72.89384 70.30939 69.04252 73.68751 68.04845
> colSums(tmp5,na.rm=TRUE)
[1] 1124.3660 751.7583 710.4324 715.0684 698.9356 689.7004 685.3615
[8] 718.9190 700.1973 696.3063 657.8817 730.4290 697.3853 697.3040
[15] 755.7717 728.9384 703.0939 690.4252 663.1876 680.4845
> colVars(tmp5,na.rm=TRUE)
[1] 15963.55490 49.83340 108.26432 60.87217 92.13356 17.97898
[7] 61.79927 70.27805 55.69559 71.59291 17.87594 107.40852
[13] 48.60102 125.14953 71.25246 34.11180 105.11430 137.28976
[19] 39.90199 65.74313
> colSd(tmp5,na.rm=TRUE)
[1] 126.346962 7.059277 10.405014 7.802062 9.598623 4.240162
[7] 7.861251 8.383201 7.462948 8.461259 4.227995 10.363808
[13] 6.971443 11.187025 8.441117 5.840531 10.252527 11.717071
[19] 6.316802 8.108214
> colMax(tmp5,na.rm=TRUE)
[1] 470.92539 88.27881 89.58111 86.09332 86.12388 77.88241 78.25333
[8] 82.90538 82.19372 85.62365 73.23550 93.01273 80.34598 87.31986
[15] 85.83353 83.25945 83.59716 91.42694 80.66967 79.21827
> colMin(tmp5,na.rm=TRUE)
[1] 58.61670 64.61385 56.86274 62.52741 53.60563 63.12568 57.03390 59.31824
[9] 58.77993 56.77983 59.16173 55.75503 59.79338 54.01424 62.49413 64.02135
[17] 54.86671 52.86995 65.21048 56.91132
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.61135 70.79319 72.36947 68.22078 69.74876 71.47307 NaN 71.23021
[9] 72.53635 71.67129
> rowSums(tmp5,na.rm=TRUE)
[1] 1792.227 1415.864 1447.389 1364.416 1394.975 1429.461 0.000 1424.604
[9] 1450.727 1433.426
> rowVars(tmp5,na.rm=TRUE)
[1] 8121.67592 36.97131 79.43938 62.81673 86.92286 69.83287
[7] NA 70.67517 134.47321 77.36007
> rowSd(tmp5,na.rm=TRUE)
[1] 90.120341 6.080404 8.912877 7.925701 9.323243 8.356607 NA
[8] 8.406853 11.596258 8.795458
> rowMax(tmp5,na.rm=TRUE)
[1] 470.92539 78.60770 93.01273 81.83441 89.58111 86.09332 NA
[8] 83.73548 91.42694 88.27881
> rowMin(tmp5,na.rm=TRUE)
[1] 53.60563 57.03390 57.63341 54.01424 54.74301 56.77983 NA 56.86274
[9] 55.75503 52.86995
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.16954 76.04443 70.47985 70.61527 70.01919 69.61942 68.31157
[8] 72.13859 70.48018 69.98583 65.71506 73.20017 69.82180 67.77602
[15] 76.91275 73.63164 70.22734 69.40202 NaN 67.21618
> colSums(tmp5,na.rm=TRUE)
[1] 1045.5258 684.3999 634.3187 635.5374 630.1727 626.5747 614.8041
[8] 649.2473 634.3217 629.8725 591.4355 658.8015 628.3962 609.9842
[15] 692.2147 662.6847 632.0461 624.6182 0.0000 604.9456
> colVars(tmp5,na.rm=TRUE)
[1] 17802.23281 47.57473 118.22654 59.53844 103.47269 15.48238
[7] 68.95673 78.37818 60.27238 79.12260 20.05029 120.55632
[13] 54.59815 97.82254 60.09148 32.25187 118.17786 152.99695
[19] NA 66.16844
> colSd(tmp5,na.rm=TRUE)
[1] 133.425008 6.897444 10.873203 7.716115 10.172153 3.934766
[7] 8.304019 8.853145 7.763529 8.895089 4.477755 10.979814
[13] 7.389056 9.890528 7.751869 5.679073 10.870964 12.369194
[19] NA 8.134398
> colMax(tmp5,na.rm=TRUE)
[1] 470.92539 88.27881 89.58111 86.09332 86.12388 77.88241 78.25333
[8] 82.90538 82.19372 85.62365 73.23550 93.01273 80.34598 86.67700
[15] 85.83353 83.25945 83.59716 91.42694 -Inf 79.21827
> colMin(tmp5,na.rm=TRUE)
[1] 58.61670 64.61385 56.86274 62.52741 53.60563 65.67537 57.03390 59.31824
[9] 58.77993 56.77983 59.16173 55.75503 59.79338 54.01424 62.49413 64.02135
[17] 54.86671 52.86995 Inf 56.91132
>
>
>
>
> 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] 188.9792 236.4156 390.4972 237.0070 184.0545 150.8797 201.6562 336.4334
[9] 224.1374 148.3446
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 188.9792 236.4156 390.4972 237.0070 184.0545 150.8797 201.6562 336.4334
[9] 224.1374 148.3446
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 1.136868e-13 2.842171e-14 5.684342e-14 -1.136868e-13 1.136868e-13
[6] 5.684342e-14 9.947598e-14 5.684342e-14 8.526513e-14 2.273737e-13
[11] -5.684342e-14 -1.136868e-13 -1.136868e-13 -5.684342e-14 -7.105427e-14
[16] 0.000000e+00 0.000000e+00 2.842171e-14 -1.705303e-13 8.526513e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
5 9
2 7
2 5
10 10
1 19
7 11
9 8
2 7
6 18
8 7
1 16
7 1
9 2
4 16
9 15
3 10
5 18
3 8
10 4
8 3
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] 2.456419
> Min(tmp)
[1] -3.228956
> mean(tmp)
[1] -0.1236539
> Sum(tmp)
[1] -12.36539
> Var(tmp)
[1] 0.9219144
>
> rowMeans(tmp)
[1] -0.1236539
> rowSums(tmp)
[1] -12.36539
> rowVars(tmp)
[1] 0.9219144
> rowSd(tmp)
[1] 0.9601638
> rowMax(tmp)
[1] 2.456419
> rowMin(tmp)
[1] -3.228956
>
> colMeans(tmp)
[1] -0.507588239 -0.288838419 -3.228955657 -0.930353685 -0.452217616
[6] 0.012961617 0.666183408 0.200173602 1.079068983 1.224883954
[11] -0.166368572 0.301602791 -1.361028296 2.456419066 0.732853043
[16] 0.050396311 -1.071983814 0.133173910 -0.479531772 -0.280303618
[21] 0.805798186 -2.482558093 0.238658957 -0.283521339 -0.493792804
[26] 1.104718732 -0.088190257 -1.047780570 -0.776710072 1.381429203
[31] -2.128846034 -1.311448332 -0.414717670 0.393828167 -1.045702282
[36] 0.185723123 0.356984784 -0.569623500 0.690896769 1.950015606
[41] -0.707953463 0.821564208 1.168373338 -1.371937597 -0.550824043
[46] 0.406354891 -0.893079488 -1.325358362 -0.892517134 -0.397758065
[51] 1.128217618 -0.307908604 -0.646382430 -0.935756121 -0.037616140
[56] 0.442166004 -0.405242798 -1.076753495 -0.885966287 1.048421696
[61] 0.127238393 -0.240280742 -0.662424857 2.118486915 0.261519848
[66] 0.717485377 -2.443781358 0.748256099 -0.245967898 -0.770091367
[71] 0.059816174 -0.295956442 0.459315701 1.509303405 0.304331219
[76] -0.257455788 0.847137007 -0.429461437 -0.462862299 0.486354351
[81] -0.470057010 1.175643928 -1.487838077 0.311997928 1.019913970
[86] 0.191292445 -0.689405214 0.553139669 0.514756987 -0.358958793
[91] 0.009209783 -1.570617415 0.399675568 0.310983806 -1.075252538
[96] -0.294298322 -0.196018086 -0.241100574 -1.324149811 -0.111027016
> colSums(tmp)
[1] -0.507588239 -0.288838419 -3.228955657 -0.930353685 -0.452217616
[6] 0.012961617 0.666183408 0.200173602 1.079068983 1.224883954
[11] -0.166368572 0.301602791 -1.361028296 2.456419066 0.732853043
[16] 0.050396311 -1.071983814 0.133173910 -0.479531772 -0.280303618
[21] 0.805798186 -2.482558093 0.238658957 -0.283521339 -0.493792804
[26] 1.104718732 -0.088190257 -1.047780570 -0.776710072 1.381429203
[31] -2.128846034 -1.311448332 -0.414717670 0.393828167 -1.045702282
[36] 0.185723123 0.356984784 -0.569623500 0.690896769 1.950015606
[41] -0.707953463 0.821564208 1.168373338 -1.371937597 -0.550824043
[46] 0.406354891 -0.893079488 -1.325358362 -0.892517134 -0.397758065
[51] 1.128217618 -0.307908604 -0.646382430 -0.935756121 -0.037616140
[56] 0.442166004 -0.405242798 -1.076753495 -0.885966287 1.048421696
[61] 0.127238393 -0.240280742 -0.662424857 2.118486915 0.261519848
[66] 0.717485377 -2.443781358 0.748256099 -0.245967898 -0.770091367
[71] 0.059816174 -0.295956442 0.459315701 1.509303405 0.304331219
[76] -0.257455788 0.847137007 -0.429461437 -0.462862299 0.486354351
[81] -0.470057010 1.175643928 -1.487838077 0.311997928 1.019913970
[86] 0.191292445 -0.689405214 0.553139669 0.514756987 -0.358958793
[91] 0.009209783 -1.570617415 0.399675568 0.310983806 -1.075252538
[96] -0.294298322 -0.196018086 -0.241100574 -1.324149811 -0.111027016
> 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] -0.507588239 -0.288838419 -3.228955657 -0.930353685 -0.452217616
[6] 0.012961617 0.666183408 0.200173602 1.079068983 1.224883954
[11] -0.166368572 0.301602791 -1.361028296 2.456419066 0.732853043
[16] 0.050396311 -1.071983814 0.133173910 -0.479531772 -0.280303618
[21] 0.805798186 -2.482558093 0.238658957 -0.283521339 -0.493792804
[26] 1.104718732 -0.088190257 -1.047780570 -0.776710072 1.381429203
[31] -2.128846034 -1.311448332 -0.414717670 0.393828167 -1.045702282
[36] 0.185723123 0.356984784 -0.569623500 0.690896769 1.950015606
[41] -0.707953463 0.821564208 1.168373338 -1.371937597 -0.550824043
[46] 0.406354891 -0.893079488 -1.325358362 -0.892517134 -0.397758065
[51] 1.128217618 -0.307908604 -0.646382430 -0.935756121 -0.037616140
[56] 0.442166004 -0.405242798 -1.076753495 -0.885966287 1.048421696
[61] 0.127238393 -0.240280742 -0.662424857 2.118486915 0.261519848
[66] 0.717485377 -2.443781358 0.748256099 -0.245967898 -0.770091367
[71] 0.059816174 -0.295956442 0.459315701 1.509303405 0.304331219
[76] -0.257455788 0.847137007 -0.429461437 -0.462862299 0.486354351
[81] -0.470057010 1.175643928 -1.487838077 0.311997928 1.019913970
[86] 0.191292445 -0.689405214 0.553139669 0.514756987 -0.358958793
[91] 0.009209783 -1.570617415 0.399675568 0.310983806 -1.075252538
[96] -0.294298322 -0.196018086 -0.241100574 -1.324149811 -0.111027016
> colMin(tmp)
[1] -0.507588239 -0.288838419 -3.228955657 -0.930353685 -0.452217616
[6] 0.012961617 0.666183408 0.200173602 1.079068983 1.224883954
[11] -0.166368572 0.301602791 -1.361028296 2.456419066 0.732853043
[16] 0.050396311 -1.071983814 0.133173910 -0.479531772 -0.280303618
[21] 0.805798186 -2.482558093 0.238658957 -0.283521339 -0.493792804
[26] 1.104718732 -0.088190257 -1.047780570 -0.776710072 1.381429203
[31] -2.128846034 -1.311448332 -0.414717670 0.393828167 -1.045702282
[36] 0.185723123 0.356984784 -0.569623500 0.690896769 1.950015606
[41] -0.707953463 0.821564208 1.168373338 -1.371937597 -0.550824043
[46] 0.406354891 -0.893079488 -1.325358362 -0.892517134 -0.397758065
[51] 1.128217618 -0.307908604 -0.646382430 -0.935756121 -0.037616140
[56] 0.442166004 -0.405242798 -1.076753495 -0.885966287 1.048421696
[61] 0.127238393 -0.240280742 -0.662424857 2.118486915 0.261519848
[66] 0.717485377 -2.443781358 0.748256099 -0.245967898 -0.770091367
[71] 0.059816174 -0.295956442 0.459315701 1.509303405 0.304331219
[76] -0.257455788 0.847137007 -0.429461437 -0.462862299 0.486354351
[81] -0.470057010 1.175643928 -1.487838077 0.311997928 1.019913970
[86] 0.191292445 -0.689405214 0.553139669 0.514756987 -0.358958793
[91] 0.009209783 -1.570617415 0.399675568 0.310983806 -1.075252538
[96] -0.294298322 -0.196018086 -0.241100574 -1.324149811 -0.111027016
> colMedians(tmp)
[1] -0.507588239 -0.288838419 -3.228955657 -0.930353685 -0.452217616
[6] 0.012961617 0.666183408 0.200173602 1.079068983 1.224883954
[11] -0.166368572 0.301602791 -1.361028296 2.456419066 0.732853043
[16] 0.050396311 -1.071983814 0.133173910 -0.479531772 -0.280303618
[21] 0.805798186 -2.482558093 0.238658957 -0.283521339 -0.493792804
[26] 1.104718732 -0.088190257 -1.047780570 -0.776710072 1.381429203
[31] -2.128846034 -1.311448332 -0.414717670 0.393828167 -1.045702282
[36] 0.185723123 0.356984784 -0.569623500 0.690896769 1.950015606
[41] -0.707953463 0.821564208 1.168373338 -1.371937597 -0.550824043
[46] 0.406354891 -0.893079488 -1.325358362 -0.892517134 -0.397758065
[51] 1.128217618 -0.307908604 -0.646382430 -0.935756121 -0.037616140
[56] 0.442166004 -0.405242798 -1.076753495 -0.885966287 1.048421696
[61] 0.127238393 -0.240280742 -0.662424857 2.118486915 0.261519848
[66] 0.717485377 -2.443781358 0.748256099 -0.245967898 -0.770091367
[71] 0.059816174 -0.295956442 0.459315701 1.509303405 0.304331219
[76] -0.257455788 0.847137007 -0.429461437 -0.462862299 0.486354351
[81] -0.470057010 1.175643928 -1.487838077 0.311997928 1.019913970
[86] 0.191292445 -0.689405214 0.553139669 0.514756987 -0.358958793
[91] 0.009209783 -1.570617415 0.399675568 0.310983806 -1.075252538
[96] -0.294298322 -0.196018086 -0.241100574 -1.324149811 -0.111027016
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.5075882 -0.2888384 -3.228956 -0.9303537 -0.4522176 0.01296162 0.6661834
[2,] -0.5075882 -0.2888384 -3.228956 -0.9303537 -0.4522176 0.01296162 0.6661834
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.2001736 1.079069 1.224884 -0.1663686 0.3016028 -1.361028 2.456419
[2,] 0.2001736 1.079069 1.224884 -0.1663686 0.3016028 -1.361028 2.456419
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.732853 0.05039631 -1.071984 0.1331739 -0.4795318 -0.2803036 0.8057982
[2,] 0.732853 0.05039631 -1.071984 0.1331739 -0.4795318 -0.2803036 0.8057982
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -2.482558 0.238659 -0.2835213 -0.4937928 1.104719 -0.08819026 -1.047781
[2,] -2.482558 0.238659 -0.2835213 -0.4937928 1.104719 -0.08819026 -1.047781
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.7767101 1.381429 -2.128846 -1.311448 -0.4147177 0.3938282 -1.045702
[2,] -0.7767101 1.381429 -2.128846 -1.311448 -0.4147177 0.3938282 -1.045702
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.1857231 0.3569848 -0.5696235 0.6908968 1.950016 -0.7079535 0.8215642
[2,] 0.1857231 0.3569848 -0.5696235 0.6908968 1.950016 -0.7079535 0.8215642
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 1.168373 -1.371938 -0.550824 0.4063549 -0.8930795 -1.325358 -0.8925171
[2,] 1.168373 -1.371938 -0.550824 0.4063549 -0.8930795 -1.325358 -0.8925171
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.3977581 1.128218 -0.3079086 -0.6463824 -0.9357561 -0.03761614 0.442166
[2,] -0.3977581 1.128218 -0.3079086 -0.6463824 -0.9357561 -0.03761614 0.442166
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.4052428 -1.076753 -0.8859663 1.048422 0.1272384 -0.2402807 -0.6624249
[2,] -0.4052428 -1.076753 -0.8859663 1.048422 0.1272384 -0.2402807 -0.6624249
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 2.118487 0.2615198 0.7174854 -2.443781 0.7482561 -0.2459679 -0.7700914
[2,] 2.118487 0.2615198 0.7174854 -2.443781 0.7482561 -0.2459679 -0.7700914
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.05981617 -0.2959564 0.4593157 1.509303 0.3043312 -0.2574558 0.847137
[2,] 0.05981617 -0.2959564 0.4593157 1.509303 0.3043312 -0.2574558 0.847137
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.4294614 -0.4628623 0.4863544 -0.470057 1.175644 -1.487838 0.3119979
[2,] -0.4294614 -0.4628623 0.4863544 -0.470057 1.175644 -1.487838 0.3119979
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 1.019914 0.1912924 -0.6894052 0.5531397 0.514757 -0.3589588 0.009209783
[2,] 1.019914 0.1912924 -0.6894052 0.5531397 0.514757 -0.3589588 0.009209783
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.570617 0.3996756 0.3109838 -1.075253 -0.2942983 -0.1960181 -0.2411006
[2,] -1.570617 0.3996756 0.3109838 -1.075253 -0.2942983 -0.1960181 -0.2411006
[,99] [,100]
[1,] -1.32415 -0.111027
[2,] -1.32415 -0.111027
>
>
> Max(tmp2)
[1] 4.492871
> Min(tmp2)
[1] -2.194535
> mean(tmp2)
[1] 0.1870774
> Sum(tmp2)
[1] 18.70774
> Var(tmp2)
[1] 1.170312
>
> rowMeans(tmp2)
[1] -0.092293025 0.128239418 0.691212866 -0.053015124 -0.024509395
[6] 0.136977561 -0.514473444 -2.194535055 0.115601499 1.531682876
[11] 1.305718089 2.115115663 1.433286643 0.169154581 0.845492508
[16] -0.149526990 0.578251442 -0.669542648 -0.093871941 1.123829389
[21] -0.343492309 -1.535230243 -1.390171509 0.802044241 -0.015361032
[26] 0.694589014 -1.660028796 -1.442937086 0.478832999 -0.231353328
[31] -0.493735088 0.490456864 1.131238938 0.756922710 1.152184292
[36] 1.084214568 0.433335799 0.371413668 -1.548175962 -0.875809657
[41] 1.063315153 0.333019851 0.128988315 -1.954522760 0.821222461
[46] 4.492870833 1.328906303 0.033589347 -1.535395817 0.811210894
[51] 0.825027557 -0.630728788 1.790218449 1.114649952 -0.512288675
[56] 0.728780918 0.104052488 -0.760516031 1.371657717 -0.042366465
[61] 1.516069468 0.210667269 0.120889728 1.110238819 -0.494869060
[66] 0.426013173 1.835652061 1.544963358 0.309786218 -1.032118933
[71] -0.825912272 -0.655285728 -0.437501341 1.102919649 0.001897305
[76] 0.267719004 -0.377319421 0.075288683 0.216733377 -1.581475423
[81] -1.242873930 1.231845296 -0.539674052 1.529034559 -1.852051456
[86] 0.429435877 1.537411638 0.347557038 -1.451791925 -0.421280978
[91] 0.637593950 -0.085121068 -1.505210563 -0.335589897 1.921490629
[96] 0.987927325 1.107008767 0.287734561 -1.557919260 0.594435162
> rowSums(tmp2)
[1] -0.092293025 0.128239418 0.691212866 -0.053015124 -0.024509395
[6] 0.136977561 -0.514473444 -2.194535055 0.115601499 1.531682876
[11] 1.305718089 2.115115663 1.433286643 0.169154581 0.845492508
[16] -0.149526990 0.578251442 -0.669542648 -0.093871941 1.123829389
[21] -0.343492309 -1.535230243 -1.390171509 0.802044241 -0.015361032
[26] 0.694589014 -1.660028796 -1.442937086 0.478832999 -0.231353328
[31] -0.493735088 0.490456864 1.131238938 0.756922710 1.152184292
[36] 1.084214568 0.433335799 0.371413668 -1.548175962 -0.875809657
[41] 1.063315153 0.333019851 0.128988315 -1.954522760 0.821222461
[46] 4.492870833 1.328906303 0.033589347 -1.535395817 0.811210894
[51] 0.825027557 -0.630728788 1.790218449 1.114649952 -0.512288675
[56] 0.728780918 0.104052488 -0.760516031 1.371657717 -0.042366465
[61] 1.516069468 0.210667269 0.120889728 1.110238819 -0.494869060
[66] 0.426013173 1.835652061 1.544963358 0.309786218 -1.032118933
[71] -0.825912272 -0.655285728 -0.437501341 1.102919649 0.001897305
[76] 0.267719004 -0.377319421 0.075288683 0.216733377 -1.581475423
[81] -1.242873930 1.231845296 -0.539674052 1.529034559 -1.852051456
[86] 0.429435877 1.537411638 0.347557038 -1.451791925 -0.421280978
[91] 0.637593950 -0.085121068 -1.505210563 -0.335589897 1.921490629
[96] 0.987927325 1.107008767 0.287734561 -1.557919260 0.594435162
> 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] -0.092293025 0.128239418 0.691212866 -0.053015124 -0.024509395
[6] 0.136977561 -0.514473444 -2.194535055 0.115601499 1.531682876
[11] 1.305718089 2.115115663 1.433286643 0.169154581 0.845492508
[16] -0.149526990 0.578251442 -0.669542648 -0.093871941 1.123829389
[21] -0.343492309 -1.535230243 -1.390171509 0.802044241 -0.015361032
[26] 0.694589014 -1.660028796 -1.442937086 0.478832999 -0.231353328
[31] -0.493735088 0.490456864 1.131238938 0.756922710 1.152184292
[36] 1.084214568 0.433335799 0.371413668 -1.548175962 -0.875809657
[41] 1.063315153 0.333019851 0.128988315 -1.954522760 0.821222461
[46] 4.492870833 1.328906303 0.033589347 -1.535395817 0.811210894
[51] 0.825027557 -0.630728788 1.790218449 1.114649952 -0.512288675
[56] 0.728780918 0.104052488 -0.760516031 1.371657717 -0.042366465
[61] 1.516069468 0.210667269 0.120889728 1.110238819 -0.494869060
[66] 0.426013173 1.835652061 1.544963358 0.309786218 -1.032118933
[71] -0.825912272 -0.655285728 -0.437501341 1.102919649 0.001897305
[76] 0.267719004 -0.377319421 0.075288683 0.216733377 -1.581475423
[81] -1.242873930 1.231845296 -0.539674052 1.529034559 -1.852051456
[86] 0.429435877 1.537411638 0.347557038 -1.451791925 -0.421280978
[91] 0.637593950 -0.085121068 -1.505210563 -0.335589897 1.921490629
[96] 0.987927325 1.107008767 0.287734561 -1.557919260 0.594435162
> rowMin(tmp2)
[1] -0.092293025 0.128239418 0.691212866 -0.053015124 -0.024509395
[6] 0.136977561 -0.514473444 -2.194535055 0.115601499 1.531682876
[11] 1.305718089 2.115115663 1.433286643 0.169154581 0.845492508
[16] -0.149526990 0.578251442 -0.669542648 -0.093871941 1.123829389
[21] -0.343492309 -1.535230243 -1.390171509 0.802044241 -0.015361032
[26] 0.694589014 -1.660028796 -1.442937086 0.478832999 -0.231353328
[31] -0.493735088 0.490456864 1.131238938 0.756922710 1.152184292
[36] 1.084214568 0.433335799 0.371413668 -1.548175962 -0.875809657
[41] 1.063315153 0.333019851 0.128988315 -1.954522760 0.821222461
[46] 4.492870833 1.328906303 0.033589347 -1.535395817 0.811210894
[51] 0.825027557 -0.630728788 1.790218449 1.114649952 -0.512288675
[56] 0.728780918 0.104052488 -0.760516031 1.371657717 -0.042366465
[61] 1.516069468 0.210667269 0.120889728 1.110238819 -0.494869060
[66] 0.426013173 1.835652061 1.544963358 0.309786218 -1.032118933
[71] -0.825912272 -0.655285728 -0.437501341 1.102919649 0.001897305
[76] 0.267719004 -0.377319421 0.075288683 0.216733377 -1.581475423
[81] -1.242873930 1.231845296 -0.539674052 1.529034559 -1.852051456
[86] 0.429435877 1.537411638 0.347557038 -1.451791925 -0.421280978
[91] 0.637593950 -0.085121068 -1.505210563 -0.335589897 1.921490629
[96] 0.987927325 1.107008767 0.287734561 -1.557919260 0.594435162
>
> colMeans(tmp2)
[1] 0.1870774
> colSums(tmp2)
[1] 18.70774
> colVars(tmp2)
[1] 1.170312
> colSd(tmp2)
[1] 1.08181
> colMax(tmp2)
[1] 4.492871
> colMin(tmp2)
[1] -2.194535
> colMedians(tmp2)
[1] 0.1899109
> colRanges(tmp2)
[,1]
[1,] -2.194535
[2,] 4.492871
>
> 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] -0.07499978 5.82461605 -3.92035153 -3.97328048 -3.52318947 -4.66028007
[7] 3.99151023 2.86630967 -3.09396024 -6.21614226
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.03208994
[2,] -0.89977131
[3,] 0.04740239
[4,] 0.73728778
[5,] 2.16778135
>
> rowApply(tmp,sum)
[1] 1.1920776 -4.5682964 -0.5967463 0.3021278 1.1859903 -6.6994050
[7] -4.1423062 -2.2999179 1.7977633 1.0489448
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 10 2 8 9 3 4 9 1 2
[2,] 5 9 9 10 6 10 10 8 9 3
[3,] 7 4 7 2 2 2 8 4 10 1
[4,] 4 5 5 4 4 8 1 2 5 7
[5,] 2 8 4 1 7 1 2 10 7 6
[6,] 1 2 6 5 10 4 6 1 3 8
[7,] 6 7 8 6 8 6 7 6 8 10
[8,] 10 6 10 3 5 9 9 5 6 5
[9,] 3 3 1 9 3 7 5 7 4 4
[10,] 8 1 3 7 1 5 3 3 2 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.6522943 2.0983631 1.3468109 -0.9793098 -3.8369410 3.2469190
[7] -0.7330187 -2.3861512 4.5796451 1.4031167 0.8059347 2.9370017
[13] 1.9263049 -1.4942443 -0.0315664 -1.3766364 -3.2889812 3.1007454
[19] 1.0540556 -2.0479304
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.57430219
[2,] -0.55646687
[3,] -0.03322193
[4,] 0.97607164
[5,] 1.84021365
>
> rowApply(tmp,sum)
[1] -1.0876431 7.4951750 8.1543746 -5.6186598 -0.9668349
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 9 18 18 10 7
[2,] 10 20 8 8 4
[3,] 6 9 14 19 10
[4,] 7 5 1 20 9
[5,] 16 11 3 1 1
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.03322193 -0.03287847 -0.50122283 -0.38067986 0.7093501 1.1263134
[2,] 1.84021365 3.25836552 -0.06480701 -0.47145647 0.1695789 0.9797692
[3,] 0.97607164 0.32190096 0.70873287 -1.43929859 -0.7083994 0.9238198
[4,] -0.55646687 -0.59132104 1.04173588 1.41052190 -2.1891715 0.8908412
[5,] -0.57430219 -0.85770383 0.16237197 -0.09839684 -1.8182992 -0.6738247
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.5364411 -1.6189157 0.3623235 1.32662840 -0.7401573 1.0029477
[2,] -0.5198349 -0.8228595 0.7418512 1.11709808 1.3641109 1.4037560
[3,] 0.7876259 0.7722081 1.3598902 0.42981448 -0.1491212 0.6134469
[4,] -1.0360552 -1.7642037 0.8740215 -0.03961187 -0.6152726 0.6325445
[5,] 0.5716867 1.0476195 1.2415586 -1.43081236 0.9463749 -0.7156934
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.8786711 -1.4971813 -0.37103056 0.1754770 0.001232263 0.7540453
[2,] 1.6209372 -0.2483376 0.08437898 -0.2303474 -0.446380062 1.8789640
[3,] 0.2769996 0.2975231 0.51410628 -0.8301721 0.197028968 0.6478250
[4,] 0.2534521 -0.2274224 -0.96624172 -0.2620077 -1.297753284 -0.6744458
[5,] 0.6535871 0.1811739 0.70722062 -0.2295863 -1.743109123 0.4943569
[,19] [,20]
[1,] -0.01791301 0.06235227
[2,] -1.54860965 -2.61121619
[3,] 1.77337406 0.68099793
[4,] 0.05856969 -0.56037286
[5,] 0.78863455 0.38030842
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 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 -0.4896183 -0.8790605 -1.175628 1.397034 -0.4202635 0.1545347 0.5199965
col8 col9 col10 col11 col12 col13 col14
row1 0.02091985 -0.2223859 0.7749574 0.6007197 1.658832 0.5744327 0.07259025
col15 col16 col17 col18 col19 col20
row1 -0.4015349 0.005970227 -0.617502 0.6340031 -0.5300854 -0.527721
> tmp[,"col10"]
col10
row1 0.7749574
row2 0.7724405
row3 -1.3416773
row4 0.9315019
row5 1.2876967
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.4896183 -0.8790605 -1.175628 1.3970342 -0.4202635 0.1545347 0.51999646
row5 -0.6464672 -1.1493919 -1.247759 0.6626056 -1.4247196 0.8708481 -0.03092428
col8 col9 col10 col11 col12 col13
row1 0.02091985 -0.2223859 0.7749574 0.6007197 1.6588317 0.5744327
row5 1.59213505 0.8883351 1.2876967 0.2141658 -0.5230476 -0.1304721
col14 col15 col16 col17 col18 col19
row1 0.07259025 -0.4015349 0.005970227 -0.617502 0.6340031 -0.5300854
row5 -0.84318976 -0.7226069 -0.171898909 -1.813177 -1.3327122 0.4917142
col20
row1 -0.5277210
row5 -0.7976807
> tmp[,c("col6","col20")]
col6 col20
row1 0.1545347 -0.52772095
row2 -0.1679961 -0.50711623
row3 -0.7540551 0.03875428
row4 -0.6873689 -1.05900019
row5 0.8708481 -0.79768070
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.1545347 -0.5277210
row5 0.8708481 -0.7976807
>
>
>
>
> 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 49.57945 50.0309 49.02187 50.13943 50.45445 104.9846 50.14307 50.90717
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.86163 50.00742 51.24086 50.51035 49.21194 48.38952 49.66837 51.43317
col17 col18 col19 col20
row1 49.4486 49.45771 48.16456 104.7498
> tmp[,"col10"]
col10
row1 50.00742
row2 30.10462
row3 30.40488
row4 29.50904
row5 50.48022
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.57945 50.03090 49.02187 50.13943 50.45445 104.9846 50.14307 50.90717
row5 49.06868 48.70585 50.80811 52.24120 51.39484 105.1085 49.95010 49.55147
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.86163 50.00742 51.24086 50.51035 49.21194 48.38952 49.66837 51.43317
row5 50.48565 50.48022 49.84222 48.75945 50.06876 49.93002 49.23744 50.70717
col17 col18 col19 col20
row1 49.44860 49.45771 48.16456 104.7498
row5 49.69479 50.09185 49.97142 102.5641
> tmp[,c("col6","col20")]
col6 col20
row1 104.98456 104.74983
row2 75.64947 73.59366
row3 76.41617 75.07800
row4 74.50698 76.17133
row5 105.10847 102.56413
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.9846 104.7498
row5 105.1085 102.5641
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.9846 104.7498
row5 105.1085 102.5641
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.46994208
[2,] 1.41938575
[3,] 0.36521380
[4,] 0.02635691
[5,] -0.83835888
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.8005866 -2.58164736
[2,] 0.8578732 -0.40742867
[3,] -0.8026626 -0.25583121
[4,] -0.6353352 0.31397076
[5,] -0.4005046 -0.09908679
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.4415422 -0.599930225
[2,] 0.6358822 1.125162601
[3,] 1.0819324 -0.747886906
[4,] -1.3109301 0.986941178
[5,] -1.7027489 -0.003815541
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.441542
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.4415422
[2,] 0.6358822
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 -1.2028081 -0.004136363 -0.6036437 1.455534 0.4320841 0.9932337
row1 -0.6683476 1.980351670 1.8029987 2.024618 -1.0819853 1.5645170
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.8704241 -0.08541919 0.2494105 0.5879719 -0.9683351 -1.3564508
row1 -0.7553837 -0.30998943 0.7535870 -0.6336666 -0.1852523 0.2646976
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 -1.285506 -1.1560618 -3.0455501 1.520393 -1.507528 -0.3937335 0.5406261
row1 1.279155 0.7812496 -0.5466089 -1.726810 -1.427093 -1.0882556 -0.5430778
[,20]
row3 0.09852863
row1 0.70691149
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.07735406 -0.5203523 1.476035 -0.957634 -0.8549367 2.031207 0.04219464
[,8] [,9] [,10]
row2 0.9540507 -2.610441 0.082648
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.457369 -0.2476614 -0.8130784 1.135079 -1.424499 1.334388 1.31321
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.407533 -1.056235 -0.6638857 -0.494914 0.4508127 -1.835634 -1.819729
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.1095696 0.7152352 -1.700031 1.084577 -1.457387 -0.7808814
>
>
> 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: 0x600002494120>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM135285e629995"
[2] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM135281b51359c"
[3] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM135287096a2c6"
[4] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM135283198aee9"
[5] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM135281f035c6f"
[6] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1352815a98b51"
[7] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM135282df97df3"
[8] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1352856bbf419"
[9] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM135284d96c1cb"
[10] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM13528648d1e38"
[11] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM135286cbb221a"
[12] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1352871bc10ba"
[13] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM1352871ee5dab"
[14] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM135285847bffc"
[15] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM135284e8d66ab"
>
>
> ### 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: 0x6000024f00c0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000024f00c0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6000024f00c0>
> rowMedians(tmp)
[1] -0.1987916193 -0.1610744336 -0.1798621048 0.3401475664 0.8019427026
[6] 0.3489249292 0.0973029961 0.1054400879 -0.1655929886 -0.2162701200
[11] 0.3400543891 0.2210471072 0.1958981977 -0.6637849583 -0.0315903466
[16] 0.0950307256 -0.1072603945 -0.0399060672 0.2158864991 -0.1596296588
[21] -0.2011196640 0.2204181850 -0.1800751754 0.5283635630 0.0149484066
[26] 0.2848907732 0.0073420373 0.3761240865 -0.1419637713 -0.0352568762
[31] 0.0360392338 -0.1585797503 0.0151039814 0.4169102471 0.0170541439
[36] 0.3362619108 -0.0599033908 -0.2841662653 -0.2520999217 -0.5290731632
[41] -0.4649313319 -0.1725893142 -0.0958697574 0.0429134620 -0.1223644036
[46] 0.3899362731 0.2875092738 -0.1478575274 0.3317641999 0.2289077144
[51] 0.3631023120 -0.4706374626 0.3217141169 -0.2792999979 0.3325939052
[56] -0.1982853371 -0.0600942209 0.0084338676 0.2000147822 -0.4450351414
[61] 0.3894797686 0.2396504890 -0.1003027916 0.1773354446 0.0586909482
[66] -0.6743460047 -0.3657389538 0.1095988130 0.0394347615 -0.4906570754
[71] 0.3687152474 -0.7246171376 0.3115217455 0.0667530840 0.1863064879
[76] 0.2489671934 -0.0606963144 -0.1997268491 -0.0322812257 -0.6266190496
[81] -0.1713131387 -0.2948370572 -0.3136841036 0.1184018978 -0.0148150304
[86] 0.1522899582 0.1268885892 -0.1440887570 0.1613965824 0.1517696620
[91] 0.5117342696 -0.3951125514 -0.2985980601 0.1049672765 0.3328070068
[96] -0.7560885209 0.0388152357 -0.0002601968 -1.1449450862 0.0835316691
[101] 0.2580552618 -0.5403055919 0.1052157696 -0.8806860074 0.5001968328
[106] -0.0775854271 0.4065583356 0.0056273662 -0.0686534156 0.1287661577
[111] 0.1312753163 -0.7525331449 -0.1869801568 0.5461999894 0.2546610924
[116] -0.0368326694 0.1611705966 0.2669514740 -0.3102567469 -0.0142766388
[121] -0.2561786179 -0.1881793292 0.8170739291 0.2301318809 -0.1070734472
[126] -0.0133015948 0.1078852959 0.5261501287 -0.0338964423 0.0586699670
[131] -0.1113046702 0.0096877919 -0.0064943719 -0.3378705815 0.2533516607
[136] -0.8448179304 -0.2178558345 -0.5857236383 -0.0618146883 0.0024021174
[141] 0.4758708494 0.1731114042 -0.2066404856 0.1311412886 0.0988818517
[146] 0.3190752452 0.2227705217 -0.3914034134 0.1334556244 -0.1975064484
[151] 0.4566607288 0.0481896287 0.0821897502 -0.5397789673 0.2418881294
[156] 0.2299537381 -0.1208250749 -0.0944771756 0.0326642316 0.5425099013
[161] -0.6518501378 0.2133381475 -0.2410527304 0.4565163091 0.3834426354
[166] 0.2076294734 0.2099155909 0.3905053746 -0.3522336009 0.1079507198
[171] -0.4062552664 0.0833810991 -0.3910765472 0.1781408613 0.1640806772
[176] -0.8524695194 -0.2825212276 0.2140161669 -0.3310140178 0.7242424849
[181] -0.3740269064 -0.2668382656 -0.1931737328 0.1484837533 0.0742662028
[186] -0.0470199761 -0.2608931151 0.3390076345 -0.3549947161 0.1446376217
[191] 0.0673954670 -0.3126730178 -0.3220399435 -0.2510880326 -0.0763546727
[196] -0.2657461964 -0.3754211761 -0.2085463454 -0.2321180246 -0.1468455172
[201] 0.3853469895 0.5204008603 0.3218728508 0.3626769100 0.2551386784
[206] 0.0996501026 0.0911166779 0.3049827359 -0.0246695712 0.2671582411
[211] 0.0803567557 -0.4073228103 -0.2537723057 -0.0569128368 0.3004954423
[216] 0.3867824557 -0.1575035358 -0.1716650335 -0.2263194056 0.1527793677
[221] -0.0703647383 0.0696206870 0.8518439360 -0.3097340558 -0.1184098942
[226] 0.7134756843 0.1999818701 -0.3181662204 -0.0307124441 -0.2194067113
>
> proc.time()
user system elapsed
5.261 19.310 32.920
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: 0x600003850300>
> .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: 0x600003850300>
> .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: 0x600003850300>
> .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: 0x600003850300>
> 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: 0x6000038781e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000038781e0>
> .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: 0x6000038781e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000038781e0>
> .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: 0x6000038781e0>
> 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: 0x6000038783c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000038783c0>
> .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: 0x6000038783c0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000038783c0>
> .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: 0x6000038783c0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000038783c0>
> .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: 0x6000038783c0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000038783c0>
> .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: 0x6000038783c0>
> 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: 0x600003864000>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600003864000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003864000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003864000>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1488239933884" "BufferedMatrixFile1488270637fa3"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1488239933884" "BufferedMatrixFile1488270637fa3"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003864240>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003864240>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003864240>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003864240>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600003864240>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600003864240>
> .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: 0x600003848000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003848000>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003848000>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600003848000>
> 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: 0x600003860000>
> .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: 0x600003860000>
> rm(P)
>
> proc.time()
user system elapsed
0.611 0.224 0.898
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
0.614 0.151 0.877