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 15:42 -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 13:39:09 -0400 (Mon, 10 Jun 2024) |
| EndedAt: 2024-06-10 13:39:47 -0400 (Mon, 10 Jun 2024) |
| EllapsedTime: 38.2 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: aarch64-apple-darwin20
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.6.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.69.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... WARNING
Found the following significant warnings:
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 15.0.0 (clang-1500.0.40.1)’
* used SDK: ‘MacOSX11.3.sdk’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 WARNING, 2 NOTEs
See
‘/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.0.40.1)’
using SDK: ‘MacOSX11.3.sdk’
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch arm64 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/arm64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation
installing to /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.360 0.108 0.453
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: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
Ncells 474155 25.4 1035432 55.3 NA 638591 34.2
Vcells 877595 6.7 8388608 64.0 65536 2072089 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 13:39:28 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Mon Jun 10 13:39:28 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: 0x6000017c0000>
>
>
>
> 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 13:39:30 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Mon Jun 10 13:39:31 2024"
>
> ColMode(tmp2)
<pointer: 0x6000017c0000>
>
>
>
> ### 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,] 100.9281717 -1.4336718 -0.7031740 0.4290184
[2,] -0.4475094 -0.2298727 0.5108909 -0.7269646
[3,] 1.0080085 0.6285377 3.3889046 -0.6904979
[4,] 0.6245586 0.3476215 -0.8568128 0.8422756
> 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,] 100.9281717 1.4336718 0.7031740 0.4290184
[2,] 0.4475094 0.2298727 0.5108909 0.7269646
[3,] 1.0080085 0.6285377 3.3889046 0.6904979
[4,] 0.6245586 0.3476215 0.8568128 0.8422756
> 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,] 10.0463014 1.1973604 0.8385547 0.6549950
[2,] 0.6689615 0.4794504 0.7147664 0.8526222
[3,] 1.0039962 0.7928037 1.8408978 0.8309620
[4,] 0.7902902 0.5895944 0.9256418 0.9177557
>
> 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,] 226.39119 38.40728 34.08872 31.97897
[2,] 32.13712 30.02438 32.65855 34.25319
[3,] 36.04797 33.55657 46.79788 34.00012
[4,] 33.52746 31.24357 35.11323 35.01983
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000017c81e0>
> exp(tmp5)
<pointer: 0x6000017c81e0>
> log(tmp5,2)
<pointer: 0x6000017c81e0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.2036
> Min(tmp5)
[1] 52.96717
> mean(tmp5)
[1] 72.72674
> Sum(tmp5)
[1] 14545.35
> Var(tmp5)
[1] 870.6166
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.33360 69.94285 71.26886 73.65681 72.68186 70.08995 70.20192 71.93232
[9] 67.74953 68.40972
> rowSums(tmp5)
[1] 1826.672 1398.857 1425.377 1473.136 1453.637 1401.799 1404.038 1438.646
[9] 1354.991 1368.194
> rowVars(tmp5)
[1] 8063.84863 48.94341 97.06426 54.05406 108.96405 48.51297
[7] 24.74274 57.67971 97.38463 81.23715
> rowSd(tmp5)
[1] 89.798934 6.995957 9.852120 7.352146 10.438585 6.965125 4.974208
[8] 7.594716 9.868365 9.013165
> rowMax(tmp5)
[1] 471.20359 82.38296 97.40366 87.16822 89.69399 82.93927 78.43736
[8] 85.29049 82.82868 87.95263
> rowMin(tmp5)
[1] 57.30904 57.98651 55.50377 58.59602 55.74648 53.86765 60.55442 61.76061
[9] 52.96717 56.58373
>
> colMeans(tmp5)
[1] 114.79181 67.18074 72.98091 69.39802 69.98480 71.32940 71.51893
[8] 74.38675 70.30609 67.93943 72.93004 69.96076 73.32608 72.14852
[15] 69.50740 71.31295 68.40394 67.21915 69.12604 70.78308
> colSums(tmp5)
[1] 1147.9181 671.8074 729.8091 693.9802 699.8480 713.2940 715.1893
[8] 743.8675 703.0609 679.3943 729.3004 699.6076 733.2608 721.4852
[15] 695.0740 713.1295 684.0394 672.1915 691.2604 707.8308
> colVars(tmp5)
[1] 15740.57388 57.90525 91.36418 24.29977 79.13499 83.13981
[7] 108.34483 51.63536 37.11488 54.06516 101.87352 30.41295
[13] 118.90081 70.91102 101.63938 60.95682 78.77515 79.63475
[19] 57.59380 66.08298
> colSd(tmp5)
[1] 125.461444 7.609550 9.558461 4.929480 8.895785 9.118103
[7] 10.408882 7.185775 6.092198 7.352902 10.093242 5.514794
[13] 10.904165 8.420868 10.081636 7.807485 8.875537 8.923830
[19] 7.589058 8.129144
> colMax(tmp5)
[1] 471.20359 79.93971 97.40366 77.42823 85.53596 86.14130 83.39943
[8] 85.29049 80.62684 78.43736 87.95263 83.73510 87.16822 85.59601
[15] 89.69399 86.27525 82.88256 76.87678 82.82868 82.54772
> colMin(tmp5)
[1] 66.88921 53.85970 61.76061 58.49029 57.59736 55.50377 55.74648 63.99304
[9] 59.33896 59.10009 57.30904 64.85719 58.02332 57.98651 52.96717 62.44532
[17] 55.65044 53.86765 56.58373 57.97552
>
>
> ### 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 69.94285 71.26886 73.65681 72.68186 70.08995 70.20192 71.93232
[9] 67.74953 68.40972
> rowSums(tmp5)
[1] NA 1398.857 1425.377 1473.136 1453.637 1401.799 1404.038 1438.646
[9] 1354.991 1368.194
> rowVars(tmp5)
[1] 8470.41547 48.94341 97.06426 54.05406 108.96405 48.51297
[7] 24.74274 57.67971 97.38463 81.23715
> rowSd(tmp5)
[1] 92.034860 6.995957 9.852120 7.352146 10.438585 6.965125 4.974208
[8] 7.594716 9.868365 9.013165
> rowMax(tmp5)
[1] NA 82.38296 97.40366 87.16822 89.69399 82.93927 78.43736 85.29049
[9] 82.82868 87.95263
> rowMin(tmp5)
[1] NA 57.98651 55.50377 58.59602 55.74648 53.86765 60.55442 61.76061
[9] 52.96717 56.58373
>
> colMeans(tmp5)
[1] 114.79181 67.18074 72.98091 69.39802 69.98480 71.32940 71.51893
[8] 74.38675 70.30609 67.93943 72.93004 69.96076 73.32608 72.14852
[15] 69.50740 NA 68.40394 67.21915 69.12604 70.78308
> colSums(tmp5)
[1] 1147.9181 671.8074 729.8091 693.9802 699.8480 713.2940 715.1893
[8] 743.8675 703.0609 679.3943 729.3004 699.6076 733.2608 721.4852
[15] 695.0740 NA 684.0394 672.1915 691.2604 707.8308
> colVars(tmp5)
[1] 15740.57388 57.90525 91.36418 24.29977 79.13499 83.13981
[7] 108.34483 51.63536 37.11488 54.06516 101.87352 30.41295
[13] 118.90081 70.91102 101.63938 NA 78.77515 79.63475
[19] 57.59380 66.08298
> colSd(tmp5)
[1] 125.461444 7.609550 9.558461 4.929480 8.895785 9.118103
[7] 10.408882 7.185775 6.092198 7.352902 10.093242 5.514794
[13] 10.904165 8.420868 10.081636 NA 8.875537 8.923830
[19] 7.589058 8.129144
> colMax(tmp5)
[1] 471.20359 79.93971 97.40366 77.42823 85.53596 86.14130 83.39943
[8] 85.29049 80.62684 78.43736 87.95263 83.73510 87.16822 85.59601
[15] 89.69399 NA 82.88256 76.87678 82.82868 82.54772
> colMin(tmp5)
[1] 66.88921 53.85970 61.76061 58.49029 57.59736 55.50377 55.74648 63.99304
[9] 59.33896 59.10009 57.30904 64.85719 58.02332 57.98651 52.96717 NA
[17] 55.65044 53.86765 56.58373 57.97552
>
> Max(tmp5,na.rm=TRUE)
[1] 471.2036
> Min(tmp5,na.rm=TRUE)
[1] 52.96717
> mean(tmp5,na.rm=TRUE)
[1] 72.76699
> Sum(tmp5,na.rm=TRUE)
[1] 14480.63
> Var(tmp5,na.rm=TRUE)
[1] 874.6882
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.73440 69.94285 71.26886 73.65681 72.68186 70.08995 70.20192 71.93232
[9] 67.74953 68.40972
> rowSums(tmp5,na.rm=TRUE)
[1] 1761.954 1398.857 1425.377 1473.136 1453.637 1401.799 1404.038 1438.646
[9] 1354.991 1368.194
> rowVars(tmp5,na.rm=TRUE)
[1] 8470.41547 48.94341 97.06426 54.05406 108.96405 48.51297
[7] 24.74274 57.67971 97.38463 81.23715
> rowSd(tmp5,na.rm=TRUE)
[1] 92.034860 6.995957 9.852120 7.352146 10.438585 6.965125 4.974208
[8] 7.594716 9.868365 9.013165
> rowMax(tmp5,na.rm=TRUE)
[1] 471.20359 82.38296 97.40366 87.16822 89.69399 82.93927 78.43736
[8] 85.29049 82.82868 87.95263
> rowMin(tmp5,na.rm=TRUE)
[1] 57.30904 57.98651 55.50377 58.59602 55.74648 53.86765 60.55442 61.76061
[9] 52.96717 56.58373
>
> colMeans(tmp5,na.rm=TRUE)
[1] 114.79181 67.18074 72.98091 69.39802 69.98480 71.32940 71.51893
[8] 74.38675 70.30609 67.93943 72.93004 69.96076 73.32608 72.14852
[15] 69.50740 72.04567 68.40394 67.21915 69.12604 70.78308
> colSums(tmp5,na.rm=TRUE)
[1] 1147.9181 671.8074 729.8091 693.9802 699.8480 713.2940 715.1893
[8] 743.8675 703.0609 679.3943 729.3004 699.6076 733.2608 721.4852
[15] 695.0740 648.4110 684.0394 672.1915 691.2604 707.8308
> colVars(tmp5,na.rm=TRUE)
[1] 15740.57388 57.90525 91.36418 24.29977 79.13499 83.13981
[7] 108.34483 51.63536 37.11488 54.06516 101.87352 30.41295
[13] 118.90081 70.91102 101.63938 62.53659 78.77515 79.63475
[19] 57.59380 66.08298
> colSd(tmp5,na.rm=TRUE)
[1] 125.461444 7.609550 9.558461 4.929480 8.895785 9.118103
[7] 10.408882 7.185775 6.092198 7.352902 10.093242 5.514794
[13] 10.904165 8.420868 10.081636 7.908008 8.875537 8.923830
[19] 7.589058 8.129144
> colMax(tmp5,na.rm=TRUE)
[1] 471.20359 79.93971 97.40366 77.42823 85.53596 86.14130 83.39943
[8] 85.29049 80.62684 78.43736 87.95263 83.73510 87.16822 85.59601
[15] 89.69399 86.27525 82.88256 76.87678 82.82868 82.54772
> colMin(tmp5,na.rm=TRUE)
[1] 66.88921 53.85970 61.76061 58.49029 57.59736 55.50377 55.74648 63.99304
[9] 59.33896 59.10009 57.30904 64.85719 58.02332 57.98651 52.96717 62.44532
[17] 55.65044 53.86765 56.58373 57.97552
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 69.94285 71.26886 73.65681 72.68186 70.08995 70.20192 71.93232
[9] 67.74953 68.40972
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1398.857 1425.377 1473.136 1453.637 1401.799 1404.038 1438.646
[9] 1354.991 1368.194
> rowVars(tmp5,na.rm=TRUE)
[1] NA 48.94341 97.06426 54.05406 108.96405 48.51297 24.74274
[8] 57.67971 97.38463 81.23715
> rowSd(tmp5,na.rm=TRUE)
[1] NA 6.995957 9.852120 7.352146 10.438585 6.965125 4.974208
[8] 7.594716 9.868365 9.013165
> rowMax(tmp5,na.rm=TRUE)
[1] NA 82.38296 97.40366 87.16822 89.69399 82.93927 78.43736 85.29049
[9] 82.82868 87.95263
> rowMin(tmp5,na.rm=TRUE)
[1] NA 57.98651 55.50377 58.59602 55.74648 53.86765 60.55442 61.76061
[9] 52.96717 56.58373
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 75.19050 65.76307 73.20644 69.71335 71.36119 71.22695 70.70161 74.54334
[9] 71.52467 68.92158 74.66570 68.43028 73.54505 71.29183 68.41069 NaN
[17] 68.32724 66.14607 68.57403 69.59704
> colSums(tmp5,na.rm=TRUE)
[1] 676.7145 591.8677 658.8579 627.4201 642.2507 641.0425 636.3145 670.8901
[9] 643.7220 620.2942 671.9913 615.8725 661.9054 641.6265 615.6962 0.0000
[17] 614.9451 595.3147 617.1663 626.3733
> colVars(tmp5,na.rm=TRUE)
[1] 65.17929 42.53349 102.21252 26.21861 67.71453 93.41419 114.37275
[8] 57.81393 25.04896 49.97137 80.71667 7.86285 133.22399 71.51822
[15] 100.81312 NA 88.55584 76.63493 61.36502 58.51790
> colSd(tmp5,na.rm=TRUE)
[1] 8.073369 6.521771 10.110021 5.120411 8.228884 9.665102 10.694520
[8] 7.603547 5.004894 7.069043 8.984246 2.804077 11.542270 8.456845
[15] 10.040574 NA 9.410411 8.754138 7.833583 7.649700
> colMax(tmp5,na.rm=TRUE)
[1] 88.46814 74.58418 97.40366 77.42823 85.53596 86.14130 83.39943 85.29049
[9] 80.62684 78.43736 87.95263 73.98953 87.16822 85.59601 89.69399 -Inf
[17] 82.88256 75.83571 82.82868 82.54772
> colMin(tmp5,na.rm=TRUE)
[1] 66.88921 53.85970 61.76061 58.49029 59.14124 55.50377 55.74648 63.99304
[9] 64.67697 62.16300 58.85637 64.85719 58.02332 57.98651 52.96717 Inf
[17] 55.65044 53.86765 56.58373 57.97552
>
>
>
>
> 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] 187.9594 210.5986 228.3530 346.8650 215.2424 237.6190 118.4976 208.6655
[9] 233.1144 270.0433
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 187.9594 210.5986 228.3530 346.8650 215.2424 237.6190 118.4976 208.6655
[9] 233.1144 270.0433
>
>
>
> 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] -5.684342e-14 0.000000e+00 5.684342e-14 1.989520e-13 -1.421085e-13
[6] -8.526513e-14 -2.842171e-14 2.842171e-14 1.705303e-13 0.000000e+00
[11] 5.684342e-14 7.105427e-14 0.000000e+00 1.705303e-13 0.000000e+00
[16] 5.684342e-14 1.136868e-13 5.684342e-14 -3.979039e-13 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## 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)
+ }
1 7
8 13
2 4
7 13
7 8
1 13
10 17
3 20
3 13
8 11
3 5
2 8
8 17
2 7
2 11
1 14
7 1
5 9
9 16
1 19
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] 2.151908
> Min(tmp)
[1] -1.754398
> mean(tmp)
[1] 0.1649764
> Sum(tmp)
[1] 16.49764
> Var(tmp)
[1] 0.6255368
>
> rowMeans(tmp)
[1] 0.1649764
> rowSums(tmp)
[1] 16.49764
> rowVars(tmp)
[1] 0.6255368
> rowSd(tmp)
[1] 0.7909088
> rowMax(tmp)
[1] 2.151908
> rowMin(tmp)
[1] -1.754398
>
> colMeans(tmp)
[1] -0.65334785 -0.08316170 -0.18470911 1.36546339 -0.06978303 0.63587212
[7] 1.53681608 0.27516413 -0.30467471 -0.35859201 -0.47145719 -0.41450284
[13] -0.09755148 0.72381179 -0.01201085 -0.05628744 0.18941915 0.25621866
[19] 0.04106911 -0.05503954 -0.23494769 0.10845604 0.47367313 1.54871461
[25] 1.31354337 0.16299332 -0.67858299 0.22641617 1.53130477 1.22662427
[31] -0.58164284 -0.24467104 0.08667236 0.41792979 -0.29872487 -0.61862659
[37] 0.54078337 -0.91849313 -0.69872090 -0.47641687 0.22477419 -1.06923168
[43] -1.16057928 0.94100189 0.48698944 0.28274049 -0.11672031 0.42686452
[49] -0.94491644 0.01566600 0.75357878 0.18742993 -0.90619726 0.82025362
[55] 0.91486348 -0.37369313 -0.42016974 -0.36483784 1.82288960 -0.84905711
[61] 1.09603187 0.45487797 -0.18566292 0.22836956 -0.56098788 -0.01036481
[67] -0.43041930 0.37557325 1.14095774 0.06140091 0.39871450 0.58274685
[73] -0.02740646 -1.55443945 -0.14714270 1.55195974 0.05003337 0.42678531
[79] 1.25897398 -0.13580337 0.16445401 -0.06340975 0.58102204 0.02840782
[85] 1.82170356 0.50851585 0.37827262 -0.29078851 1.50029134 -1.75439820
[91] 1.81556904 1.44085821 0.06512903 -0.55065129 -0.75835824 -1.55579586
[97] 0.70459224 2.15190776 -0.46748019 0.38294778
> colSums(tmp)
[1] -0.65334785 -0.08316170 -0.18470911 1.36546339 -0.06978303 0.63587212
[7] 1.53681608 0.27516413 -0.30467471 -0.35859201 -0.47145719 -0.41450284
[13] -0.09755148 0.72381179 -0.01201085 -0.05628744 0.18941915 0.25621866
[19] 0.04106911 -0.05503954 -0.23494769 0.10845604 0.47367313 1.54871461
[25] 1.31354337 0.16299332 -0.67858299 0.22641617 1.53130477 1.22662427
[31] -0.58164284 -0.24467104 0.08667236 0.41792979 -0.29872487 -0.61862659
[37] 0.54078337 -0.91849313 -0.69872090 -0.47641687 0.22477419 -1.06923168
[43] -1.16057928 0.94100189 0.48698944 0.28274049 -0.11672031 0.42686452
[49] -0.94491644 0.01566600 0.75357878 0.18742993 -0.90619726 0.82025362
[55] 0.91486348 -0.37369313 -0.42016974 -0.36483784 1.82288960 -0.84905711
[61] 1.09603187 0.45487797 -0.18566292 0.22836956 -0.56098788 -0.01036481
[67] -0.43041930 0.37557325 1.14095774 0.06140091 0.39871450 0.58274685
[73] -0.02740646 -1.55443945 -0.14714270 1.55195974 0.05003337 0.42678531
[79] 1.25897398 -0.13580337 0.16445401 -0.06340975 0.58102204 0.02840782
[85] 1.82170356 0.50851585 0.37827262 -0.29078851 1.50029134 -1.75439820
[91] 1.81556904 1.44085821 0.06512903 -0.55065129 -0.75835824 -1.55579586
[97] 0.70459224 2.15190776 -0.46748019 0.38294778
> 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] -0.65334785 -0.08316170 -0.18470911 1.36546339 -0.06978303 0.63587212
[7] 1.53681608 0.27516413 -0.30467471 -0.35859201 -0.47145719 -0.41450284
[13] -0.09755148 0.72381179 -0.01201085 -0.05628744 0.18941915 0.25621866
[19] 0.04106911 -0.05503954 -0.23494769 0.10845604 0.47367313 1.54871461
[25] 1.31354337 0.16299332 -0.67858299 0.22641617 1.53130477 1.22662427
[31] -0.58164284 -0.24467104 0.08667236 0.41792979 -0.29872487 -0.61862659
[37] 0.54078337 -0.91849313 -0.69872090 -0.47641687 0.22477419 -1.06923168
[43] -1.16057928 0.94100189 0.48698944 0.28274049 -0.11672031 0.42686452
[49] -0.94491644 0.01566600 0.75357878 0.18742993 -0.90619726 0.82025362
[55] 0.91486348 -0.37369313 -0.42016974 -0.36483784 1.82288960 -0.84905711
[61] 1.09603187 0.45487797 -0.18566292 0.22836956 -0.56098788 -0.01036481
[67] -0.43041930 0.37557325 1.14095774 0.06140091 0.39871450 0.58274685
[73] -0.02740646 -1.55443945 -0.14714270 1.55195974 0.05003337 0.42678531
[79] 1.25897398 -0.13580337 0.16445401 -0.06340975 0.58102204 0.02840782
[85] 1.82170356 0.50851585 0.37827262 -0.29078851 1.50029134 -1.75439820
[91] 1.81556904 1.44085821 0.06512903 -0.55065129 -0.75835824 -1.55579586
[97] 0.70459224 2.15190776 -0.46748019 0.38294778
> colMin(tmp)
[1] -0.65334785 -0.08316170 -0.18470911 1.36546339 -0.06978303 0.63587212
[7] 1.53681608 0.27516413 -0.30467471 -0.35859201 -0.47145719 -0.41450284
[13] -0.09755148 0.72381179 -0.01201085 -0.05628744 0.18941915 0.25621866
[19] 0.04106911 -0.05503954 -0.23494769 0.10845604 0.47367313 1.54871461
[25] 1.31354337 0.16299332 -0.67858299 0.22641617 1.53130477 1.22662427
[31] -0.58164284 -0.24467104 0.08667236 0.41792979 -0.29872487 -0.61862659
[37] 0.54078337 -0.91849313 -0.69872090 -0.47641687 0.22477419 -1.06923168
[43] -1.16057928 0.94100189 0.48698944 0.28274049 -0.11672031 0.42686452
[49] -0.94491644 0.01566600 0.75357878 0.18742993 -0.90619726 0.82025362
[55] 0.91486348 -0.37369313 -0.42016974 -0.36483784 1.82288960 -0.84905711
[61] 1.09603187 0.45487797 -0.18566292 0.22836956 -0.56098788 -0.01036481
[67] -0.43041930 0.37557325 1.14095774 0.06140091 0.39871450 0.58274685
[73] -0.02740646 -1.55443945 -0.14714270 1.55195974 0.05003337 0.42678531
[79] 1.25897398 -0.13580337 0.16445401 -0.06340975 0.58102204 0.02840782
[85] 1.82170356 0.50851585 0.37827262 -0.29078851 1.50029134 -1.75439820
[91] 1.81556904 1.44085821 0.06512903 -0.55065129 -0.75835824 -1.55579586
[97] 0.70459224 2.15190776 -0.46748019 0.38294778
> colMedians(tmp)
[1] -0.65334785 -0.08316170 -0.18470911 1.36546339 -0.06978303 0.63587212
[7] 1.53681608 0.27516413 -0.30467471 -0.35859201 -0.47145719 -0.41450284
[13] -0.09755148 0.72381179 -0.01201085 -0.05628744 0.18941915 0.25621866
[19] 0.04106911 -0.05503954 -0.23494769 0.10845604 0.47367313 1.54871461
[25] 1.31354337 0.16299332 -0.67858299 0.22641617 1.53130477 1.22662427
[31] -0.58164284 -0.24467104 0.08667236 0.41792979 -0.29872487 -0.61862659
[37] 0.54078337 -0.91849313 -0.69872090 -0.47641687 0.22477419 -1.06923168
[43] -1.16057928 0.94100189 0.48698944 0.28274049 -0.11672031 0.42686452
[49] -0.94491644 0.01566600 0.75357878 0.18742993 -0.90619726 0.82025362
[55] 0.91486348 -0.37369313 -0.42016974 -0.36483784 1.82288960 -0.84905711
[61] 1.09603187 0.45487797 -0.18566292 0.22836956 -0.56098788 -0.01036481
[67] -0.43041930 0.37557325 1.14095774 0.06140091 0.39871450 0.58274685
[73] -0.02740646 -1.55443945 -0.14714270 1.55195974 0.05003337 0.42678531
[79] 1.25897398 -0.13580337 0.16445401 -0.06340975 0.58102204 0.02840782
[85] 1.82170356 0.50851585 0.37827262 -0.29078851 1.50029134 -1.75439820
[91] 1.81556904 1.44085821 0.06512903 -0.55065129 -0.75835824 -1.55579586
[97] 0.70459224 2.15190776 -0.46748019 0.38294778
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.6533478 -0.0831617 -0.1847091 1.365463 -0.06978303 0.6358721 1.536816
[2,] -0.6533478 -0.0831617 -0.1847091 1.365463 -0.06978303 0.6358721 1.536816
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.2751641 -0.3046747 -0.358592 -0.4714572 -0.4145028 -0.09755148 0.7238118
[2,] 0.2751641 -0.3046747 -0.358592 -0.4714572 -0.4145028 -0.09755148 0.7238118
[,15] [,16] [,17] [,18] [,19] [,20]
[1,] -0.01201085 -0.05628744 0.1894191 0.2562187 0.04106911 -0.05503954
[2,] -0.01201085 -0.05628744 0.1894191 0.2562187 0.04106911 -0.05503954
[,21] [,22] [,23] [,24] [,25] [,26] [,27]
[1,] -0.2349477 0.108456 0.4736731 1.548715 1.313543 0.1629933 -0.678583
[2,] -0.2349477 0.108456 0.4736731 1.548715 1.313543 0.1629933 -0.678583
[,28] [,29] [,30] [,31] [,32] [,33] [,34]
[1,] 0.2264162 1.531305 1.226624 -0.5816428 -0.244671 0.08667236 0.4179298
[2,] 0.2264162 1.531305 1.226624 -0.5816428 -0.244671 0.08667236 0.4179298
[,35] [,36] [,37] [,38] [,39] [,40] [,41]
[1,] -0.2987249 -0.6186266 0.5407834 -0.9184931 -0.6987209 -0.4764169 0.2247742
[2,] -0.2987249 -0.6186266 0.5407834 -0.9184931 -0.6987209 -0.4764169 0.2247742
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] -1.069232 -1.160579 0.9410019 0.4869894 0.2827405 -0.1167203 0.4268645
[2,] -1.069232 -1.160579 0.9410019 0.4869894 0.2827405 -0.1167203 0.4268645
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.9449164 0.015666 0.7535788 0.1874299 -0.9061973 0.8202536 0.9148635
[2,] -0.9449164 0.015666 0.7535788 0.1874299 -0.9061973 0.8202536 0.9148635
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.3736931 -0.4201697 -0.3648378 1.82289 -0.8490571 1.096032 0.454878
[2,] -0.3736931 -0.4201697 -0.3648378 1.82289 -0.8490571 1.096032 0.454878
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] -0.1856629 0.2283696 -0.5609879 -0.01036481 -0.4304193 0.3755733 1.140958
[2,] -0.1856629 0.2283696 -0.5609879 -0.01036481 -0.4304193 0.3755733 1.140958
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 0.06140091 0.3987145 0.5827469 -0.02740646 -1.554439 -0.1471427 1.55196
[2,] 0.06140091 0.3987145 0.5827469 -0.02740646 -1.554439 -0.1471427 1.55196
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] 0.05003337 0.4267853 1.258974 -0.1358034 0.164454 -0.06340975 0.581022
[2,] 0.05003337 0.4267853 1.258974 -0.1358034 0.164454 -0.06340975 0.581022
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 0.02840782 1.821704 0.5085159 0.3782726 -0.2907885 1.500291 -1.754398
[2,] 0.02840782 1.821704 0.5085159 0.3782726 -0.2907885 1.500291 -1.754398
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 1.815569 1.440858 0.06512903 -0.5506513 -0.7583582 -1.555796 0.7045922
[2,] 1.815569 1.440858 0.06512903 -0.5506513 -0.7583582 -1.555796 0.7045922
[,98] [,99] [,100]
[1,] 2.151908 -0.4674802 0.3829478
[2,] 2.151908 -0.4674802 0.3829478
>
>
> Max(tmp2)
[1] 2.318794
> Min(tmp2)
[1] -2.047052
> mean(tmp2)
[1] -0.01209662
> Sum(tmp2)
[1] -1.209662
> Var(tmp2)
[1] 0.8806227
>
> rowMeans(tmp2)
[1] -0.45588214 0.61396360 0.59856907 0.83671546 0.75209380 -1.81836797
[7] -0.96502766 -0.07787725 -0.38136195 -0.61533919 -0.67006001 -0.39464000
[13] -0.15076950 -0.90692881 1.30891552 -1.14401569 -1.15481407 0.19344077
[19] 0.53409785 1.32548487 0.67690838 -1.07199507 -0.88889986 -1.01113869
[25] -0.43744685 -1.27502114 -0.21563579 -0.76135018 0.93550472 -0.47055265
[31] -0.33900216 -0.80524595 -0.56656861 -0.99679640 0.48108710 -1.18452576
[37] -0.12870958 0.32530657 -1.38531933 -0.17341845 -0.04127873 -1.26198122
[43] 1.51785903 -0.98475503 -0.47944516 0.55921915 -0.81746175 -1.77300027
[49] 1.10779150 0.41176998 1.45599791 1.18495574 -0.16289449 0.85505398
[55] 0.85544025 1.23143162 1.19945963 -0.62041916 0.28490119 0.77187214
[61] 0.94737695 0.26739091 0.89557367 2.31879446 -0.69026378 1.28104246
[67] 0.15714850 -0.59544229 0.89657477 0.03459471 -0.87281001 -0.18310347
[73] -1.09741213 0.07490991 -1.27133046 -0.04485575 1.17078573 0.99898636
[79] -0.63649675 -1.13355674 -0.09028662 1.62546746 1.73592008 1.12507754
[85] -0.01961378 -0.36559814 1.42282180 0.82177588 -0.93983634 0.05883269
[91] -0.04115922 -2.04705168 0.17800560 -0.25281426 -1.85876158 0.97384352
[97] 0.10076402 1.40274167 -0.45905209 -0.52853845
> rowSums(tmp2)
[1] -0.45588214 0.61396360 0.59856907 0.83671546 0.75209380 -1.81836797
[7] -0.96502766 -0.07787725 -0.38136195 -0.61533919 -0.67006001 -0.39464000
[13] -0.15076950 -0.90692881 1.30891552 -1.14401569 -1.15481407 0.19344077
[19] 0.53409785 1.32548487 0.67690838 -1.07199507 -0.88889986 -1.01113869
[25] -0.43744685 -1.27502114 -0.21563579 -0.76135018 0.93550472 -0.47055265
[31] -0.33900216 -0.80524595 -0.56656861 -0.99679640 0.48108710 -1.18452576
[37] -0.12870958 0.32530657 -1.38531933 -0.17341845 -0.04127873 -1.26198122
[43] 1.51785903 -0.98475503 -0.47944516 0.55921915 -0.81746175 -1.77300027
[49] 1.10779150 0.41176998 1.45599791 1.18495574 -0.16289449 0.85505398
[55] 0.85544025 1.23143162 1.19945963 -0.62041916 0.28490119 0.77187214
[61] 0.94737695 0.26739091 0.89557367 2.31879446 -0.69026378 1.28104246
[67] 0.15714850 -0.59544229 0.89657477 0.03459471 -0.87281001 -0.18310347
[73] -1.09741213 0.07490991 -1.27133046 -0.04485575 1.17078573 0.99898636
[79] -0.63649675 -1.13355674 -0.09028662 1.62546746 1.73592008 1.12507754
[85] -0.01961378 -0.36559814 1.42282180 0.82177588 -0.93983634 0.05883269
[91] -0.04115922 -2.04705168 0.17800560 -0.25281426 -1.85876158 0.97384352
[97] 0.10076402 1.40274167 -0.45905209 -0.52853845
> 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] -0.45588214 0.61396360 0.59856907 0.83671546 0.75209380 -1.81836797
[7] -0.96502766 -0.07787725 -0.38136195 -0.61533919 -0.67006001 -0.39464000
[13] -0.15076950 -0.90692881 1.30891552 -1.14401569 -1.15481407 0.19344077
[19] 0.53409785 1.32548487 0.67690838 -1.07199507 -0.88889986 -1.01113869
[25] -0.43744685 -1.27502114 -0.21563579 -0.76135018 0.93550472 -0.47055265
[31] -0.33900216 -0.80524595 -0.56656861 -0.99679640 0.48108710 -1.18452576
[37] -0.12870958 0.32530657 -1.38531933 -0.17341845 -0.04127873 -1.26198122
[43] 1.51785903 -0.98475503 -0.47944516 0.55921915 -0.81746175 -1.77300027
[49] 1.10779150 0.41176998 1.45599791 1.18495574 -0.16289449 0.85505398
[55] 0.85544025 1.23143162 1.19945963 -0.62041916 0.28490119 0.77187214
[61] 0.94737695 0.26739091 0.89557367 2.31879446 -0.69026378 1.28104246
[67] 0.15714850 -0.59544229 0.89657477 0.03459471 -0.87281001 -0.18310347
[73] -1.09741213 0.07490991 -1.27133046 -0.04485575 1.17078573 0.99898636
[79] -0.63649675 -1.13355674 -0.09028662 1.62546746 1.73592008 1.12507754
[85] -0.01961378 -0.36559814 1.42282180 0.82177588 -0.93983634 0.05883269
[91] -0.04115922 -2.04705168 0.17800560 -0.25281426 -1.85876158 0.97384352
[97] 0.10076402 1.40274167 -0.45905209 -0.52853845
> rowMin(tmp2)
[1] -0.45588214 0.61396360 0.59856907 0.83671546 0.75209380 -1.81836797
[7] -0.96502766 -0.07787725 -0.38136195 -0.61533919 -0.67006001 -0.39464000
[13] -0.15076950 -0.90692881 1.30891552 -1.14401569 -1.15481407 0.19344077
[19] 0.53409785 1.32548487 0.67690838 -1.07199507 -0.88889986 -1.01113869
[25] -0.43744685 -1.27502114 -0.21563579 -0.76135018 0.93550472 -0.47055265
[31] -0.33900216 -0.80524595 -0.56656861 -0.99679640 0.48108710 -1.18452576
[37] -0.12870958 0.32530657 -1.38531933 -0.17341845 -0.04127873 -1.26198122
[43] 1.51785903 -0.98475503 -0.47944516 0.55921915 -0.81746175 -1.77300027
[49] 1.10779150 0.41176998 1.45599791 1.18495574 -0.16289449 0.85505398
[55] 0.85544025 1.23143162 1.19945963 -0.62041916 0.28490119 0.77187214
[61] 0.94737695 0.26739091 0.89557367 2.31879446 -0.69026378 1.28104246
[67] 0.15714850 -0.59544229 0.89657477 0.03459471 -0.87281001 -0.18310347
[73] -1.09741213 0.07490991 -1.27133046 -0.04485575 1.17078573 0.99898636
[79] -0.63649675 -1.13355674 -0.09028662 1.62546746 1.73592008 1.12507754
[85] -0.01961378 -0.36559814 1.42282180 0.82177588 -0.93983634 0.05883269
[91] -0.04115922 -2.04705168 0.17800560 -0.25281426 -1.85876158 0.97384352
[97] 0.10076402 1.40274167 -0.45905209 -0.52853845
>
> colMeans(tmp2)
[1] -0.01209662
> colSums(tmp2)
[1] -1.209662
> colVars(tmp2)
[1] 0.8806227
> colSd(tmp2)
[1] 0.938415
> colMax(tmp2)
[1] 2.318794
> colMin(tmp2)
[1] -2.047052
> colMedians(tmp2)
[1] -0.08408193
> colRanges(tmp2)
[,1]
[1,] -2.047052
[2,] 2.318794
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.7321637 -5.1893727 -1.5396772 -0.3270164 0.2808195 1.3205782
[7] 3.0947024 0.8244909 2.3715154 1.7456839
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.9950391
[2,] -0.5438738
[3,] -0.2124595
[4,] 0.1034241
[5,] 0.8589680
>
> rowApply(tmp,sum)
[1] -0.8294798 -4.8031309 -4.2396929 7.4073324 0.7309883 -0.6069422
[7] 0.5883155 3.1643104 1.4929700 -2.0551106
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 5 9 1 5 4 7 5 3 8
[2,] 1 9 1 4 3 8 2 2 5 6
[3,] 10 1 4 2 9 2 3 7 7 2
[4,] 4 10 7 10 4 1 1 4 2 9
[5,] 7 6 3 8 1 10 9 3 9 1
[6,] 2 4 10 6 2 3 8 9 8 3
[7,] 6 2 6 9 10 7 4 6 10 4
[8,] 5 7 5 3 8 9 5 10 1 7
[9,] 9 8 8 5 6 6 6 1 6 10
[10,] 8 3 2 7 7 5 10 8 4 5
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 3.2142945 -1.0029195 0.3254314 1.2742018 2.3382441 -0.7141094
[7] -1.0670086 3.1555425 -0.5994773 -1.5296273 -0.2868230 -1.3808801
[13] 2.7789311 1.8895163 2.1428850 2.2157591 0.1835684 -0.3398984
[19] 1.2416324 -1.0257085
> colApply(tmp,quantile)[,1]
[,1]
[1,] 0.09176426
[2,] 0.39642350
[3,] 0.52825094
[4,] 0.96157058
[5,] 1.23628524
>
> rowApply(tmp,sum)
[1] 6.998857 11.980671 -1.998171 -4.821954 0.654150
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 13 15 12 17 18
[2,] 5 1 20 2 4
[3,] 4 17 8 7 14
[4,] 16 4 14 11 10
[5,] 3 19 18 4 19
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.52825094 -0.1067839 -0.2060002 0.824922601 -0.6000073 -0.04975866
[2,] 0.96157058 -0.6791350 1.1141171 -0.004518028 1.5640145 -0.39318878
[3,] 0.09176426 1.8488690 -0.3589936 0.418911290 1.2163564 -0.45651653
[4,] 0.39642350 -1.5555901 -0.6638108 0.014422560 -1.1039544 0.46236024
[5,] 1.23628524 -0.5102795 0.4401190 0.020463418 1.2618348 -0.27700569
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.33452175 0.73152542 0.05981781 1.4006772 1.62360272 -1.2822218
[2,] 0.05186548 0.86570141 0.90267110 -0.4467370 0.85577682 1.3758651
[3,] 1.05512826 0.45347658 0.07234348 -1.8789119 -2.42912015 -0.2078450
[4,] -0.81209818 0.07899515 -0.52204786 -0.3311339 0.05274361 -1.5119562
[5,] -1.69642591 1.02584389 -1.11226186 -0.2735216 -0.38982601 0.2452777
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 2.0272102 0.5040768 0.7326463 0.04906949 0.4675551 -1.4380502
[2,] 1.0459454 0.2184739 0.2835731 0.45895266 2.4421084 0.5779716
[3,] -1.1718399 0.4004173 -0.7628321 -0.55182394 -0.3398957 1.4638775
[4,] 1.2122376 0.2211286 -0.3038026 2.24471989 0.2718995 -1.0781364
[5,] -0.3346222 0.5454197 2.1933002 0.01484097 -2.6580988 0.1344391
[,19] [,20]
[1,] 0.40939740 0.9884059
[2,] 0.02696606 0.7586769
[3,] 0.50645440 -1.3679904
[4,] 0.22224418 -2.1165979
[5,] 0.07657037 0.7117971
>
>
> 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 : 652 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 -0.7341533 -0.07256032 0.1918689 0.7628883 -1.099243 -0.03478558 -1.076104
col8 col9 col10 col11 col12 col13 col14
row1 0.969736 0.2106718 -0.878668 0.5865651 0.4217166 -1.058527 -0.05348667
col15 col16 col17 col18 col19 col20
row1 1.133259 0.3711717 -1.482785 -0.5234423 1.138474 1.527559
> tmp[,"col10"]
col10
row1 -0.8786680
row2 -0.3397641
row3 1.8273690
row4 -0.7145421
row5 1.4630323
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.7341533 -0.07256032 0.1918689 0.7628883 -1.0992426 -0.03478558
row5 0.5666702 -1.25104663 -0.0480539 0.3612306 -0.2198469 0.40651314
col7 col8 col9 col10 col11 col12 col13
row1 -1.07610363 0.9697360 0.2106718 -0.878668 0.5865651 0.4217166 -1.058527
row5 -0.09649551 0.9415224 -0.7907173 1.463032 2.2622305 -0.6663641 1.128855
col14 col15 col16 col17 col18 col19 col20
row1 -0.05348667 1.133259 0.3711717 -1.482785 -0.5234423 1.138474 1.527559
row5 -1.36266402 1.004225 -0.6161237 1.618689 -0.3984148 1.806051 -1.511667
> tmp[,c("col6","col20")]
col6 col20
row1 -0.03478558 1.5275585
row2 1.16853886 -0.8944563
row3 0.90057226 0.7897045
row4 -0.57014173 -0.3362400
row5 0.40651314 -1.5116673
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.03478558 1.527559
row5 0.40651314 -1.511667
>
>
>
>
> 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 48.3801 50.33325 50.24632 49.10133 50.51529 106.6041 50.23676 49.40341
col9 col10 col11 col12 col13 col14 col15 col16
row1 47.73638 50.86792 49.83226 49.83059 49.51137 49.14694 49.67748 50.42676
col17 col18 col19 col20
row1 49.59522 49.83001 50.17513 105.4051
> tmp[,"col10"]
col10
row1 50.86792
row2 29.57455
row3 29.85673
row4 29.08692
row5 52.63998
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.38010 50.33325 50.24632 49.10133 50.51529 106.6041 50.23676 49.40341
row5 52.88863 48.61795 50.40533 48.60688 49.57069 105.6909 48.70962 51.24200
col9 col10 col11 col12 col13 col14 col15 col16
row1 47.73638 50.86792 49.83226 49.83059 49.51137 49.14694 49.67748 50.42676
row5 50.58645 52.63998 51.40264 47.90223 50.67185 51.57741 48.87313 49.40687
col17 col18 col19 col20
row1 49.59522 49.83001 50.17513 105.4051
row5 50.16143 50.10706 49.69561 105.0177
> tmp[,c("col6","col20")]
col6 col20
row1 106.60408 105.40514
row2 74.43343 75.88574
row3 75.39995 74.47815
row4 75.88805 74.44874
row5 105.69093 105.01772
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.6041 105.4051
row5 105.6909 105.0177
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.6041 105.4051
row5 105.6909 105.0177
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.3730927
[2,] -0.3504112
[3,] 0.2236120
[4,] -2.4299193
[5,] 1.7628022
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.2695441 1.179087
[2,] -0.2439515 -1.069078
[3,] 0.1490119 2.051483
[4,] 0.1294783 1.463591
[5,] -1.1261058 1.569953
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.20248545 0.89209419
[2,] 0.57510685 0.09541211
[3,] -1.81529066 1.69541038
[4,] -1.15646150 -1.18387213
[5,] 0.09498518 -1.52932993
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.202485
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.2024855
[2,] 0.5751068
>
>
>
> 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 -1.0463038 -1.6529103 2.138667 0.3186581 -0.01186829 0.3557278 0.8318121
row1 0.2809419 -0.4294261 -1.261360 0.5752168 -1.60589913 1.7114232 2.1825639
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -1.2789610 -2.032424 -0.6654304 0.2673333 -0.58605924 -0.8045788
row1 -0.1760772 -1.221894 -0.4361736 0.8401069 -0.07928626 -0.3702096
[,14] [,15] [,16] [,17] [,18] [,19]
row3 0.5843203 1.54335088 0.05418989 0.349527 -0.6478500 -0.9821894
row1 -2.7911369 -0.04643385 -0.37053773 0.559298 -0.9016693 0.9128510
[,20]
row3 -1.8115585
row1 0.4681358
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.8612707 -0.1814688 0.06931986 -0.158759 -0.2218857 1.131735 0.1908652
[,8] [,9] [,10]
row2 -0.1582589 -1.563304 -0.4447653
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.6938719 1.851345 -1.647598 0.07634349 -1.244108 0.3433949 1.243464
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.629354 -0.41386 0.4802507 -2.065872 -0.4127954 -0.8607028 0.1767225
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.8066816 -0.2209001 -0.07185821 -1.309204 -0.9921826 -0.9541709
>
>
> 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: 0x6000017c87e0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM14f311f45f818"
[2] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM14f312aa2ffb2"
[3] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM14f31334114fc"
[4] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM14f3175c8c6ad"
[5] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM14f31506bc444"
[6] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM14f315322759b"
[7] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM14f317b573dc0"
[8] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM14f311c974783"
[9] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM14f31fd7f81f"
[10] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM14f312be2c359"
[11] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM14f3134871e91"
[12] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM14f3112e7dc88"
[13] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM14f31343f6e6a"
[14] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM14f31306a0bf2"
[15] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM14f3123655b3"
>
>
> ### 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: 0x6000017c93e0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000017c93e0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6000017c93e0>
> rowMedians(tmp)
[1] -0.1979199282 -0.3946858001 -0.1659242270 -0.7056063314 0.0950210325
[6] 0.1665910043 -0.0793674832 -0.3914579590 -0.0876993399 0.1372015562
[11] -0.0362797164 -0.0387925004 0.5449602914 0.1795146157 -0.0950318445
[16] -0.7354787399 0.5061656992 -0.4564405895 -0.0003101371 0.0911597687
[21] -0.1591309258 -0.1586543732 -0.0282036948 -0.1850509270 -0.1777178266
[26] -0.1774828704 0.6192429356 0.5106149268 -0.5516180308 0.4129166516
[31] -0.0515626619 0.4728203489 0.1750227954 0.0646731086 -0.2280305788
[36] 0.3556353750 0.7077951156 -0.3777228380 -0.2539346893 0.3755256232
[41] 0.3798398319 0.0474280410 -0.2134174678 -0.1945346596 -0.0168246672
[46] 0.1270978807 0.0190387176 -0.4214558809 0.2137435386 0.1021690093
[51] -0.1635992731 0.0549079020 -0.1046701141 -0.5758376005 -0.2776190882
[56] 0.0193223237 -0.3102533918 0.0073214605 -0.6730552153 -0.1058637754
[61] -0.4421196728 0.4761006577 -0.0190425418 -0.5964131943 -0.3196966606
[66] -0.8235556012 0.5906798887 0.1869807799 -0.0688377239 -0.0234690605
[71] 0.0654175921 -0.2405797515 -0.0777807820 0.0827406931 0.0341833958
[76] 0.0904696321 0.6032390646 0.0438628746 0.0542354544 -0.2485787181
[81] -0.2259845014 0.2120295535 -0.0938086045 0.2314399349 0.2506000772
[86] -0.3096511260 0.1384983215 -0.4757622477 -0.2270230713 0.0106459449
[91] 0.2393281132 0.0838611539 -0.4846702587 0.0783653509 -0.2342661465
[96] 0.0232645318 -0.4369179834 0.2142563536 -0.2414133151 0.3588121778
[101] -0.0654455622 -0.1968866661 0.2604449437 0.3571000795 0.3461238388
[106] 0.0052954083 -0.4423607544 0.0394643468 0.1830279271 -0.2980698643
[111] -0.2525812587 -0.5114904249 -0.3686203400 0.5291930785 -0.1260244485
[116] -0.0639333054 -0.2164482146 -0.1789293121 -0.0076545545 -0.0679328234
[121] 0.0308966565 0.1244269611 0.0642243797 0.0627972145 0.0585036368
[126] 0.5239020955 -0.3517736457 -0.1585519783 0.4808537404 -0.0763695691
[131] -0.2896999498 -0.0084939603 0.1372871006 -0.3480373643 -0.7633688933
[136] 0.1692926987 0.2252022193 -0.2792763326 -0.1160208905 -0.1281297248
[141] 0.3350748987 -0.3502034326 0.3806185282 0.0184951234 -0.2419267697
[146] 0.4023707430 0.1439128152 0.0735070854 -0.4097075736 -0.2670538456
[151] -0.0460761340 0.1341436894 -0.1695659193 0.5695983887 -0.1960107734
[156] 0.0235834586 0.2532393087 -0.2029721345 -0.0842670915 0.2384321399
[161] 0.4612555695 -0.0700183316 0.6566161479 0.3470988759 0.1018110407
[166] 0.3500555045 0.6165678976 -0.1872498986 -0.1587479492 -0.6686328282
[171] 0.6717577223 -0.3757374832 -0.5190386803 0.2779542355 0.1732607183
[176] -0.1479794637 -0.5933613573 -0.6811608148 0.1186058042 -0.3880764838
[181] 0.2205409891 -0.6386084375 -0.0478218530 -0.5167481073 0.0916448265
[186] -0.0514383306 -0.5564245550 0.0151279589 0.4747191439 0.0779391921
[191] 0.2539756689 -0.5836713420 0.7184651773 -0.3162030475 0.3295053271
[196] 0.5333194371 0.3628700802 -0.0708238451 0.0632693797 -0.2077931710
[201] -0.0726811028 -0.0419971293 0.4444761293 0.5582020110 0.1718496649
[206] -0.0405154021 0.0975324150 -0.0519503393 0.3076898134 0.1781230988
[211] 0.3850264306 -0.0880549071 -0.1277536045 0.4034490655 0.2580279900
[216] -0.1792044056 0.1801352156 0.1044716974 0.3456705893 -0.7206568646
[221] 0.0956803297 0.0145630745 -0.0662852682 0.3501187447 0.0844960358
[226] 0.5514006311 -0.0564533544 -0.0750292345 -0.1627554020 -0.0040741581
>
> proc.time()
user system elapsed
2.002 8.265 10.439
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: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x6000017104e0>
> .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: 0x6000017104e0>
> .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: 0x6000017104e0>
> .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: 0x6000017104e0>
> 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: 0x60000170c000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000170c000>
> .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: 0x60000170c000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000170c000>
> .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: 0x60000170c000>
> 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: 0x60000170c180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000170c180>
> .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: 0x60000170c180>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x60000170c180>
> .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: 0x60000170c180>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x60000170c180>
> .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: 0x60000170c180>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x60000170c180>
> .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: 0x60000170c180>
> 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: 0x60000170c360>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x60000170c360>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000170c360>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000170c360>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile14f5f16323c2" "BufferedMatrixFile14f5f34c53de7"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile14f5f16323c2" "BufferedMatrixFile14f5f34c53de7"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000170c600>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000170c600>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x60000170c600>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x60000170c600>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x60000170c600>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x60000170c600>
> .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: 0x60000170c7e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000170c7e0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x60000170c7e0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x60000170c7e0>
> 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: 0x60000170c9c0>
> .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: 0x60000170c9c0>
> rm(P)
>
> proc.time()
user system elapsed
0.358 0.110 0.452
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: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.340 0.072 0.398