Ben Bolstad
| Snapshot Date: 2024-10-16 14:00 -0400 (Wed, 16 Oct 2024) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_19 |
| git_last_commit: af6c73d |
| git_last_commit_date: 2024-04-30 10:16:21 -0400 (Tue, 30 Apr 2024) |
| Back to Multiple platform build/check report for BioC 3.19: simplified long |
|
This page was generated on 2024-10-18 20:41 -0400 (Fri, 18 Oct 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4763 |
| palomino7 | Windows Server 2022 Datacenter | x64 | 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life" | 4500 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4530 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.1 (2024-06-14) -- "Race for Your Life" | 4480 |
| 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 249/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.68.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
|
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: 1.68.0 |
| 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_1.68.0.tar.gz |
| StartedAt: 2024-10-17 14:39:57 -0400 (Thu, 17 Oct 2024) |
| EndedAt: 2024-10-17 14:40:43 -0400 (Thu, 17 Oct 2024) |
| EllapsedTime: 45.5 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_1.68.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.1 (2024-06-14)
* 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 ‘1.68.0’
* 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-3.19-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-3.19-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 4.4.1 (2024-06-14) -- "Race for Your Life"
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
0.361 0.125 0.523
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: 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-3.19-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 474153 25.4 1035428 55.3 NA 638588 34.2
Vcells 877591 6.7 8388608 64.0 65536 2072106 15.9
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu Oct 17 14:40:20 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu Oct 17 14:40:20 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: 0x6000020680c0>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu Oct 17 14:40:23 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu Oct 17 14:40:24 2024"
>
> ColMode(tmp2)
<pointer: 0x6000020680c0>
>
>
>
> ### 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,] 100.2324894 0.3034554 -0.4772048 1.2069532
[2,] 2.0363116 0.1384889 0.3511449 -0.7937053
[3,] -0.8993159 -0.9074649 -0.7382138 0.6442463
[4,] -1.3894777 0.1156486 0.8177855 0.3266826
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.2324894 0.3034554 0.4772048 1.2069532
[2,] 2.0363116 0.1384889 0.3511449 0.7937053
[3,] 0.8993159 0.9074649 0.7382138 0.6442463
[4,] 1.3894777 0.1156486 0.8177855 0.3266826
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0116177 0.5508679 0.6908001 1.0986142
[2,] 1.4269939 0.3721410 0.5925748 0.8909014
[3,] 0.9483227 0.9526095 0.8591937 0.8026496
[4,] 1.1787611 0.3400715 0.9043149 0.5715616
>
> 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-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.34867 30.81213 32.38521 37.19310
[2,] 41.30625 28.85990 31.27689 34.70272
[3,] 35.38254 35.43356 34.33015 33.67074
[4,] 38.17709 28.51636 34.86093 31.04230
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x60000206c7e0>
> exp(tmp5)
<pointer: 0x60000206c7e0>
> log(tmp5,2)
<pointer: 0x60000206c7e0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.0337
> Min(tmp5)
[1] 54.04427
> mean(tmp5)
[1] 72.87379
> Sum(tmp5)
[1] 14574.76
> Var(tmp5)
[1] 870.0687
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.99316 71.38906 75.37889 68.94396 70.75158 70.06056 71.60621 71.80274
[9] 69.03544 69.77626
> rowSums(tmp5)
[1] 1799.863 1427.781 1507.578 1378.879 1415.032 1401.211 1432.124 1436.055
[9] 1380.709 1395.525
> rowVars(tmp5)
[1] 8042.90965 77.15285 44.97954 57.61743 43.88705 105.45229
[7] 72.78593 75.32983 97.95154 119.49988
> rowSd(tmp5)
[1] 89.682271 8.783669 6.706679 7.590615 6.624730 10.268996 8.531467
[8] 8.679276 9.897047 10.931600
> rowMax(tmp5)
[1] 469.03372 85.97355 90.90038 81.54256 84.34986 95.47833 85.01566
[8] 87.18504 89.63773 91.39254
> rowMin(tmp5)
[1] 55.63462 58.31142 64.33843 57.08509 61.85236 55.35897 58.04426 56.95813
[9] 54.04427 54.15374
>
> colMeans(tmp5)
[1] 112.37696 73.03563 67.93404 67.52586 71.73846 74.07477 71.63508
[8] 68.77155 69.32221 71.07113 73.79574 72.30165 70.49102 74.21331
[15] 70.98094 70.30596 70.67568 72.37085 67.91875 66.93611
> colSums(tmp5)
[1] 1123.7696 730.3563 679.3404 675.2586 717.3846 740.7477 716.3508
[8] 687.7155 693.2221 710.7113 737.9574 723.0165 704.9102 742.1331
[15] 709.8094 703.0596 706.7568 723.7085 679.1875 669.3611
> colVars(tmp5)
[1] 15793.80927 141.86879 66.85697 50.51308 57.04009 115.65829
[7] 131.64038 70.29153 48.66105 98.71317 65.66159 71.97742
[13] 42.27373 82.95398 61.42905 84.93942 112.45027 79.58010
[19] 86.25031 48.72313
> colSd(tmp5)
[1] 125.673423 11.910869 8.176611 7.107255 7.552489 10.754454
[7] 11.473464 8.384005 6.975747 9.935450 8.103184 8.483951
[13] 6.501825 9.107908 7.837669 9.216259 10.604257 8.920768
[19] 9.287104 6.980195
> colMax(tmp5)
[1] 469.03372 91.39254 87.18504 77.41256 82.26168 89.63773 95.47833
[8] 81.43842 80.51368 85.90993 86.53264 87.09670 84.05269 85.01566
[15] 79.63502 82.62244 90.90038 84.78067 82.89429 77.39624
> colMin(tmp5)
[1] 61.06473 59.35307 58.88750 56.39560 54.15374 58.92019 57.28933 58.17265
[9] 56.95813 57.08509 63.20342 54.98240 64.30410 62.40215 55.63462 56.16687
[17] 57.70359 58.07452 54.04427 55.35897
>
>
> ### 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] 89.99316 71.38906 75.37889 68.94396 NA 70.06056 71.60621 71.80274
[9] 69.03544 69.77626
> rowSums(tmp5)
[1] 1799.863 1427.781 1507.578 1378.879 NA 1401.211 1432.124 1436.055
[9] 1380.709 1395.525
> rowVars(tmp5)
[1] 8042.90965 77.15285 44.97954 57.61743 46.27259 105.45229
[7] 72.78593 75.32983 97.95154 119.49988
> rowSd(tmp5)
[1] 89.682271 8.783669 6.706679 7.590615 6.802396 10.268996 8.531467
[8] 8.679276 9.897047 10.931600
> rowMax(tmp5)
[1] 469.03372 85.97355 90.90038 81.54256 NA 95.47833 85.01566
[8] 87.18504 89.63773 91.39254
> rowMin(tmp5)
[1] 55.63462 58.31142 64.33843 57.08509 NA 55.35897 58.04426 56.95813
[9] 54.04427 54.15374
>
> colMeans(tmp5)
[1] 112.37696 73.03563 67.93404 67.52586 71.73846 74.07477 71.63508
[8] 68.77155 69.32221 71.07113 NA 72.30165 70.49102 74.21331
[15] 70.98094 70.30596 70.67568 72.37085 67.91875 66.93611
> colSums(tmp5)
[1] 1123.7696 730.3563 679.3404 675.2586 717.3846 740.7477 716.3508
[8] 687.7155 693.2221 710.7113 NA 723.0165 704.9102 742.1331
[15] 709.8094 703.0596 706.7568 723.7085 679.1875 669.3611
> colVars(tmp5)
[1] 15793.80927 141.86879 66.85697 50.51308 57.04009 115.65829
[7] 131.64038 70.29153 48.66105 98.71317 NA 71.97742
[13] 42.27373 82.95398 61.42905 84.93942 112.45027 79.58010
[19] 86.25031 48.72313
> colSd(tmp5)
[1] 125.673423 11.910869 8.176611 7.107255 7.552489 10.754454
[7] 11.473464 8.384005 6.975747 9.935450 NA 8.483951
[13] 6.501825 9.107908 7.837669 9.216259 10.604257 8.920768
[19] 9.287104 6.980195
> colMax(tmp5)
[1] 469.03372 91.39254 87.18504 77.41256 82.26168 89.63773 95.47833
[8] 81.43842 80.51368 85.90993 NA 87.09670 84.05269 85.01566
[15] 79.63502 82.62244 90.90038 84.78067 82.89429 77.39624
> colMin(tmp5)
[1] 61.06473 59.35307 58.88750 56.39560 54.15374 58.92019 57.28933 58.17265
[9] 56.95813 57.08509 NA 54.98240 64.30410 62.40215 55.63462 56.16687
[17] 57.70359 58.07452 54.04427 55.35897
>
> Max(tmp5,na.rm=TRUE)
[1] 469.0337
> Min(tmp5,na.rm=TRUE)
[1] 54.04427
> mean(tmp5,na.rm=TRUE)
[1] 72.88922
> Sum(tmp5,na.rm=TRUE)
[1] 14504.95
> Var(tmp5,na.rm=TRUE)
[1] 874.4151
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.99316 71.38906 75.37889 68.94396 70.80151 70.06056 71.60621 71.80274
[9] 69.03544 69.77626
> rowSums(tmp5,na.rm=TRUE)
[1] 1799.863 1427.781 1507.578 1378.879 1345.229 1401.211 1432.124 1436.055
[9] 1380.709 1395.525
> rowVars(tmp5,na.rm=TRUE)
[1] 8042.90965 77.15285 44.97954 57.61743 46.27259 105.45229
[7] 72.78593 75.32983 97.95154 119.49988
> rowSd(tmp5,na.rm=TRUE)
[1] 89.682271 8.783669 6.706679 7.590615 6.802396 10.268996 8.531467
[8] 8.679276 9.897047 10.931600
> rowMax(tmp5,na.rm=TRUE)
[1] 469.03372 85.97355 90.90038 81.54256 84.34986 95.47833 85.01566
[8] 87.18504 89.63773 91.39254
> rowMin(tmp5,na.rm=TRUE)
[1] 55.63462 58.31142 64.33843 57.08509 61.85236 55.35897 58.04426 56.95813
[9] 54.04427 54.15374
>
> colMeans(tmp5,na.rm=TRUE)
[1] 112.37696 73.03563 67.93404 67.52586 71.73846 74.07477 71.63508
[8] 68.77155 69.32221 71.07113 74.23939 72.30165 70.49102 74.21331
[15] 70.98094 70.30596 70.67568 72.37085 67.91875 66.93611
> colSums(tmp5,na.rm=TRUE)
[1] 1123.7696 730.3563 679.3404 675.2586 717.3846 740.7477 716.3508
[8] 687.7155 693.2221 710.7113 668.1545 723.0165 704.9102 742.1331
[15] 709.8094 703.0596 706.7568 723.7085 679.1875 669.3611
> colVars(tmp5,na.rm=TRUE)
[1] 15793.80927 141.86879 66.85697 50.51308 57.04009 115.65829
[7] 131.64038 70.29153 48.66105 98.71317 71.65505 71.97742
[13] 42.27373 82.95398 61.42905 84.93942 112.45027 79.58010
[19] 86.25031 48.72313
> colSd(tmp5,na.rm=TRUE)
[1] 125.673423 11.910869 8.176611 7.107255 7.552489 10.754454
[7] 11.473464 8.384005 6.975747 9.935450 8.464931 8.483951
[13] 6.501825 9.107908 7.837669 9.216259 10.604257 8.920768
[19] 9.287104 6.980195
> colMax(tmp5,na.rm=TRUE)
[1] 469.03372 91.39254 87.18504 77.41256 82.26168 89.63773 95.47833
[8] 81.43842 80.51368 85.90993 86.53264 87.09670 84.05269 85.01566
[15] 79.63502 82.62244 90.90038 84.78067 82.89429 77.39624
> colMin(tmp5,na.rm=TRUE)
[1] 61.06473 59.35307 58.88750 56.39560 54.15374 58.92019 57.28933 58.17265
[9] 56.95813 57.08509 63.20342 54.98240 64.30410 62.40215 55.63462 56.16687
[17] 57.70359 58.07452 54.04427 55.35897
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.99316 71.38906 75.37889 68.94396 NaN 70.06056 71.60621 71.80274
[9] 69.03544 69.77626
> rowSums(tmp5,na.rm=TRUE)
[1] 1799.863 1427.781 1507.578 1378.879 0.000 1401.211 1432.124 1436.055
[9] 1380.709 1395.525
> rowVars(tmp5,na.rm=TRUE)
[1] 8042.90965 77.15285 44.97954 57.61743 NA 105.45229
[7] 72.78593 75.32983 97.95154 119.49988
> rowSd(tmp5,na.rm=TRUE)
[1] 89.682271 8.783669 6.706679 7.590615 NA 10.268996 8.531467
[8] 8.679276 9.897047 10.931600
> rowMax(tmp5,na.rm=TRUE)
[1] 469.03372 85.97355 90.90038 81.54256 NA 95.47833 85.01566
[8] 87.18504 89.63773 91.39254
> rowMin(tmp5,na.rm=TRUE)
[1] 55.63462 58.31142 64.33843 57.08509 NA 55.35897 58.04426 56.95813
[9] 54.04427 54.15374
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.16450 73.36075 68.60978 67.04788 71.36443 75.29261 71.60579
[8] 68.51964 69.65067 70.29346 NaN 71.17487 71.17846 75.20892
[15] 71.70146 71.05918 70.54384 71.03985 68.21201 65.92423
> colSums(tmp5,na.rm=TRUE)
[1] 1045.4805 660.2468 617.4880 603.4309 642.2799 677.6335 644.4521
[8] 616.6768 626.8560 632.6411 0.0000 640.5739 640.6061 676.8803
[15] 645.3132 639.5326 634.8946 639.3586 613.9081 593.3181
> colVars(tmp5,na.rm=TRUE)
[1] 17606.64890 158.41321 70.07704 54.25693 62.59625 113.43033
[7] 148.08577 78.36407 53.53001 104.24862 NA 66.69129
[13] 42.24156 82.17177 63.26719 89.17432 126.31103 69.59752
[19] 96.06411 43.29455
> colSd(tmp5,na.rm=TRUE)
[1] 132.690048 12.586231 8.371203 7.365931 7.911779 10.650367
[7] 12.169050 8.852348 7.316420 10.210221 NA 8.166474
[13] 6.499351 9.064864 7.954067 9.443216 11.238818 8.342513
[19] 9.801230 6.579859
> colMax(tmp5,na.rm=TRUE)
[1] 469.03372 91.39254 87.18504 77.41256 82.26168 89.63773 95.47833
[8] 81.43842 80.51368 85.90993 -Inf 87.09670 84.05269 85.01566
[15] 79.63502 82.62244 90.90038 84.78067 82.89429 77.39624
> colMin(tmp5,na.rm=TRUE)
[1] 61.06473 59.35307 58.88750 56.39560 54.15374 58.92019 57.28933 58.17265
[9] 56.95813 57.08509 Inf 54.98240 64.54002 62.40215 55.63462 56.16687
[17] 57.70359 58.07452 54.04427 55.35897
>
>
>
>
> 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] 191.22590 349.23734 140.85146 192.19619 233.31077 140.17855 220.30465
[8] 484.61502 307.30812 93.50804
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 191.22590 349.23734 140.85146 192.19619 233.31077 140.17855 220.30465
[8] 484.61502 307.30812 93.50804
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -1.421085e-13 -1.136868e-13 1.421085e-13 1.421085e-13 2.842171e-14
[6] 5.684342e-14 -5.684342e-14 1.136868e-13 9.947598e-14 1.136868e-13
[11] -5.684342e-14 5.684342e-14 1.421085e-13 -2.842171e-14 1.136868e-13
[16] 0.000000e+00 -2.842171e-14 -1.136868e-13 1.136868e-13 1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
5 4
1 10
5 9
4 14
7 13
4 16
2 6
7 6
8 15
3 15
2 2
4 5
9 10
7 5
9 13
1 4
9 16
7 5
3 8
3 17
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.413917
> Min(tmp)
[1] -2.58916
> mean(tmp)
[1] 0.1027062
> Sum(tmp)
[1] 10.27062
> Var(tmp)
[1] 0.9820057
>
> rowMeans(tmp)
[1] 0.1027062
> rowSums(tmp)
[1] 10.27062
> rowVars(tmp)
[1] 0.9820057
> rowSd(tmp)
[1] 0.990962
> rowMax(tmp)
[1] 2.413917
> rowMin(tmp)
[1] -2.58916
>
> colMeans(tmp)
[1] -0.77230658 -0.75125748 -0.18541607 -0.02322832 1.54200218 -0.49698357
[7] -1.38746494 -0.50183047 -0.02371466 0.18760665 -0.80637185 0.01579363
[13] -0.74618672 -2.58916000 -0.51564642 -0.14419381 0.82738463 -0.02315726
[19] -0.94736382 0.57331282 0.15996312 0.47978819 1.11144928 1.34326211
[25] 1.29930647 -2.47076686 -0.45140687 -0.61684257 -0.51973555 -0.87261147
[31] -0.05283985 2.41391653 -0.83645405 1.18842989 -1.43354456 0.48970552
[37] 0.95867748 0.57293307 -1.06745727 -0.58698136 -1.10742515 0.76131119
[43] 0.58667671 -0.11892055 -1.17064262 0.45417485 1.46562768 0.78382528
[49] 1.68964131 1.45823207 1.22100448 0.11961414 1.08551690 0.22149115
[55] 0.09533596 1.05050658 -0.97987463 1.18892007 -0.60310503 1.22355150
[61] -0.64148005 0.42012346 0.11308882 0.94653634 0.44517062 -1.29021925
[67] 1.56609677 0.50036867 -0.94801352 -1.02677579 0.96953061 -0.52711141
[73] -0.66445723 0.23860406 -0.02692245 -1.42088859 2.09689474 0.20439519
[79] 0.19192552 -1.10068360 0.88370456 0.90587034 -0.09356482 -0.35075801
[85] 0.79879271 -0.32459698 0.76699366 -1.71443170 0.42438475 2.27066632
[91] -1.52676397 0.30365230 0.87414119 1.36902054 1.41409217 0.80467832
[97] -0.32630193 -0.26277853 0.43876641 -0.19719849
> colSums(tmp)
[1] -0.77230658 -0.75125748 -0.18541607 -0.02322832 1.54200218 -0.49698357
[7] -1.38746494 -0.50183047 -0.02371466 0.18760665 -0.80637185 0.01579363
[13] -0.74618672 -2.58916000 -0.51564642 -0.14419381 0.82738463 -0.02315726
[19] -0.94736382 0.57331282 0.15996312 0.47978819 1.11144928 1.34326211
[25] 1.29930647 -2.47076686 -0.45140687 -0.61684257 -0.51973555 -0.87261147
[31] -0.05283985 2.41391653 -0.83645405 1.18842989 -1.43354456 0.48970552
[37] 0.95867748 0.57293307 -1.06745727 -0.58698136 -1.10742515 0.76131119
[43] 0.58667671 -0.11892055 -1.17064262 0.45417485 1.46562768 0.78382528
[49] 1.68964131 1.45823207 1.22100448 0.11961414 1.08551690 0.22149115
[55] 0.09533596 1.05050658 -0.97987463 1.18892007 -0.60310503 1.22355150
[61] -0.64148005 0.42012346 0.11308882 0.94653634 0.44517062 -1.29021925
[67] 1.56609677 0.50036867 -0.94801352 -1.02677579 0.96953061 -0.52711141
[73] -0.66445723 0.23860406 -0.02692245 -1.42088859 2.09689474 0.20439519
[79] 0.19192552 -1.10068360 0.88370456 0.90587034 -0.09356482 -0.35075801
[85] 0.79879271 -0.32459698 0.76699366 -1.71443170 0.42438475 2.27066632
[91] -1.52676397 0.30365230 0.87414119 1.36902054 1.41409217 0.80467832
[97] -0.32630193 -0.26277853 0.43876641 -0.19719849
> 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] -0.77230658 -0.75125748 -0.18541607 -0.02322832 1.54200218 -0.49698357
[7] -1.38746494 -0.50183047 -0.02371466 0.18760665 -0.80637185 0.01579363
[13] -0.74618672 -2.58916000 -0.51564642 -0.14419381 0.82738463 -0.02315726
[19] -0.94736382 0.57331282 0.15996312 0.47978819 1.11144928 1.34326211
[25] 1.29930647 -2.47076686 -0.45140687 -0.61684257 -0.51973555 -0.87261147
[31] -0.05283985 2.41391653 -0.83645405 1.18842989 -1.43354456 0.48970552
[37] 0.95867748 0.57293307 -1.06745727 -0.58698136 -1.10742515 0.76131119
[43] 0.58667671 -0.11892055 -1.17064262 0.45417485 1.46562768 0.78382528
[49] 1.68964131 1.45823207 1.22100448 0.11961414 1.08551690 0.22149115
[55] 0.09533596 1.05050658 -0.97987463 1.18892007 -0.60310503 1.22355150
[61] -0.64148005 0.42012346 0.11308882 0.94653634 0.44517062 -1.29021925
[67] 1.56609677 0.50036867 -0.94801352 -1.02677579 0.96953061 -0.52711141
[73] -0.66445723 0.23860406 -0.02692245 -1.42088859 2.09689474 0.20439519
[79] 0.19192552 -1.10068360 0.88370456 0.90587034 -0.09356482 -0.35075801
[85] 0.79879271 -0.32459698 0.76699366 -1.71443170 0.42438475 2.27066632
[91] -1.52676397 0.30365230 0.87414119 1.36902054 1.41409217 0.80467832
[97] -0.32630193 -0.26277853 0.43876641 -0.19719849
> colMin(tmp)
[1] -0.77230658 -0.75125748 -0.18541607 -0.02322832 1.54200218 -0.49698357
[7] -1.38746494 -0.50183047 -0.02371466 0.18760665 -0.80637185 0.01579363
[13] -0.74618672 -2.58916000 -0.51564642 -0.14419381 0.82738463 -0.02315726
[19] -0.94736382 0.57331282 0.15996312 0.47978819 1.11144928 1.34326211
[25] 1.29930647 -2.47076686 -0.45140687 -0.61684257 -0.51973555 -0.87261147
[31] -0.05283985 2.41391653 -0.83645405 1.18842989 -1.43354456 0.48970552
[37] 0.95867748 0.57293307 -1.06745727 -0.58698136 -1.10742515 0.76131119
[43] 0.58667671 -0.11892055 -1.17064262 0.45417485 1.46562768 0.78382528
[49] 1.68964131 1.45823207 1.22100448 0.11961414 1.08551690 0.22149115
[55] 0.09533596 1.05050658 -0.97987463 1.18892007 -0.60310503 1.22355150
[61] -0.64148005 0.42012346 0.11308882 0.94653634 0.44517062 -1.29021925
[67] 1.56609677 0.50036867 -0.94801352 -1.02677579 0.96953061 -0.52711141
[73] -0.66445723 0.23860406 -0.02692245 -1.42088859 2.09689474 0.20439519
[79] 0.19192552 -1.10068360 0.88370456 0.90587034 -0.09356482 -0.35075801
[85] 0.79879271 -0.32459698 0.76699366 -1.71443170 0.42438475 2.27066632
[91] -1.52676397 0.30365230 0.87414119 1.36902054 1.41409217 0.80467832
[97] -0.32630193 -0.26277853 0.43876641 -0.19719849
> colMedians(tmp)
[1] -0.77230658 -0.75125748 -0.18541607 -0.02322832 1.54200218 -0.49698357
[7] -1.38746494 -0.50183047 -0.02371466 0.18760665 -0.80637185 0.01579363
[13] -0.74618672 -2.58916000 -0.51564642 -0.14419381 0.82738463 -0.02315726
[19] -0.94736382 0.57331282 0.15996312 0.47978819 1.11144928 1.34326211
[25] 1.29930647 -2.47076686 -0.45140687 -0.61684257 -0.51973555 -0.87261147
[31] -0.05283985 2.41391653 -0.83645405 1.18842989 -1.43354456 0.48970552
[37] 0.95867748 0.57293307 -1.06745727 -0.58698136 -1.10742515 0.76131119
[43] 0.58667671 -0.11892055 -1.17064262 0.45417485 1.46562768 0.78382528
[49] 1.68964131 1.45823207 1.22100448 0.11961414 1.08551690 0.22149115
[55] 0.09533596 1.05050658 -0.97987463 1.18892007 -0.60310503 1.22355150
[61] -0.64148005 0.42012346 0.11308882 0.94653634 0.44517062 -1.29021925
[67] 1.56609677 0.50036867 -0.94801352 -1.02677579 0.96953061 -0.52711141
[73] -0.66445723 0.23860406 -0.02692245 -1.42088859 2.09689474 0.20439519
[79] 0.19192552 -1.10068360 0.88370456 0.90587034 -0.09356482 -0.35075801
[85] 0.79879271 -0.32459698 0.76699366 -1.71443170 0.42438475 2.27066632
[91] -1.52676397 0.30365230 0.87414119 1.36902054 1.41409217 0.80467832
[97] -0.32630193 -0.26277853 0.43876641 -0.19719849
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.7723066 -0.7512575 -0.1854161 -0.02322832 1.542002 -0.4969836 -1.387465
[2,] -0.7723066 -0.7512575 -0.1854161 -0.02322832 1.542002 -0.4969836 -1.387465
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.5018305 -0.02371466 0.1876066 -0.8063718 0.01579363 -0.7461867 -2.58916
[2,] -0.5018305 -0.02371466 0.1876066 -0.8063718 0.01579363 -0.7461867 -2.58916
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.5156464 -0.1441938 0.8273846 -0.02315726 -0.9473638 0.5733128 0.1599631
[2,] -0.5156464 -0.1441938 0.8273846 -0.02315726 -0.9473638 0.5733128 0.1599631
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.4797882 1.111449 1.343262 1.299306 -2.470767 -0.4514069 -0.6168426
[2,] 0.4797882 1.111449 1.343262 1.299306 -2.470767 -0.4514069 -0.6168426
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.5197355 -0.8726115 -0.05283985 2.413917 -0.8364541 1.18843 -1.433545
[2,] -0.5197355 -0.8726115 -0.05283985 2.413917 -0.8364541 1.18843 -1.433545
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.4897055 0.9586775 0.5729331 -1.067457 -0.5869814 -1.107425 0.7613112
[2,] 0.4897055 0.9586775 0.5729331 -1.067457 -0.5869814 -1.107425 0.7613112
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.5866767 -0.1189205 -1.170643 0.4541748 1.465628 0.7838253 1.689641
[2,] 0.5866767 -0.1189205 -1.170643 0.4541748 1.465628 0.7838253 1.689641
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 1.458232 1.221004 0.1196141 1.085517 0.2214912 0.09533596 1.050507
[2,] 1.458232 1.221004 0.1196141 1.085517 0.2214912 0.09533596 1.050507
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.9798746 1.18892 -0.603105 1.223552 -0.64148 0.4201235 0.1130888
[2,] -0.9798746 1.18892 -0.603105 1.223552 -0.64148 0.4201235 0.1130888
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.9465363 0.4451706 -1.290219 1.566097 0.5003687 -0.9480135 -1.026776
[2,] 0.9465363 0.4451706 -1.290219 1.566097 0.5003687 -0.9480135 -1.026776
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.9695306 -0.5271114 -0.6644572 0.2386041 -0.02692245 -1.420889 2.096895
[2,] 0.9695306 -0.5271114 -0.6644572 0.2386041 -0.02692245 -1.420889 2.096895
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.2043952 0.1919255 -1.100684 0.8837046 0.9058703 -0.09356482 -0.350758
[2,] 0.2043952 0.1919255 -1.100684 0.8837046 0.9058703 -0.09356482 -0.350758
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.7987927 -0.324597 0.7669937 -1.714432 0.4243848 2.270666 -1.526764
[2,] 0.7987927 -0.324597 0.7669937 -1.714432 0.4243848 2.270666 -1.526764
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.3036523 0.8741412 1.369021 1.414092 0.8046783 -0.3263019 -0.2627785
[2,] 0.3036523 0.8741412 1.369021 1.414092 0.8046783 -0.3263019 -0.2627785
[,99] [,100]
[1,] 0.4387664 -0.1971985
[2,] 0.4387664 -0.1971985
>
>
> Max(tmp2)
[1] 2.689517
> Min(tmp2)
[1] -2.008832
> mean(tmp2)
[1] 0.2143694
> Sum(tmp2)
[1] 21.43694
> Var(tmp2)
[1] 0.6737114
>
> rowMeans(tmp2)
[1] 0.007744053 -0.591952238 0.595340542 0.674818669 -0.260266790
[6] -0.023595295 -0.472873273 -1.021032675 0.929116923 1.243218891
[11] 1.303301237 0.480327215 0.401815207 0.073862888 0.713218978
[16] 1.115286345 1.340548292 -0.182964555 0.653633124 -0.031744117
[21] -0.248290336 0.635887580 -0.369157912 -0.713771067 1.071539124
[26] 0.615604850 0.433257001 2.689516741 -1.228958756 -0.683403563
[31] 0.138358487 -0.468139264 1.079766762 0.033392196 2.595320184
[36] 0.631952681 0.171107792 0.350246808 -1.201613600 1.419029857
[41] -0.859296327 -0.269961463 0.907923071 0.365210427 1.140924308
[46] -0.475785079 0.346300474 1.152535718 0.885977547 -0.944178243
[51] -0.119282267 -1.160580668 -0.130195153 0.125693435 -0.329433160
[56] -0.967112820 -0.885136953 -0.262128379 -0.019420321 -1.358597839
[61] 0.405858235 1.547198803 1.187412298 1.263652752 -1.496966262
[66] -0.551391222 -0.203957898 0.245610336 -0.491481814 1.150643758
[71] -0.065993029 -2.008831635 0.282659989 0.589320222 0.076164815
[76] 1.321522200 0.364249910 0.398401368 0.547207082 -0.449648903
[81] -0.623200999 0.636250651 -0.495665489 0.159428220 1.583174095
[86] 0.440494670 0.896020744 0.884903144 0.490282552 0.107043389
[91] -0.050426381 -0.233545376 -0.319839078 0.351521122 0.489191484
[96] 0.260751560 0.778554068 0.405757823 -0.307928614 0.829632633
> rowSums(tmp2)
[1] 0.007744053 -0.591952238 0.595340542 0.674818669 -0.260266790
[6] -0.023595295 -0.472873273 -1.021032675 0.929116923 1.243218891
[11] 1.303301237 0.480327215 0.401815207 0.073862888 0.713218978
[16] 1.115286345 1.340548292 -0.182964555 0.653633124 -0.031744117
[21] -0.248290336 0.635887580 -0.369157912 -0.713771067 1.071539124
[26] 0.615604850 0.433257001 2.689516741 -1.228958756 -0.683403563
[31] 0.138358487 -0.468139264 1.079766762 0.033392196 2.595320184
[36] 0.631952681 0.171107792 0.350246808 -1.201613600 1.419029857
[41] -0.859296327 -0.269961463 0.907923071 0.365210427 1.140924308
[46] -0.475785079 0.346300474 1.152535718 0.885977547 -0.944178243
[51] -0.119282267 -1.160580668 -0.130195153 0.125693435 -0.329433160
[56] -0.967112820 -0.885136953 -0.262128379 -0.019420321 -1.358597839
[61] 0.405858235 1.547198803 1.187412298 1.263652752 -1.496966262
[66] -0.551391222 -0.203957898 0.245610336 -0.491481814 1.150643758
[71] -0.065993029 -2.008831635 0.282659989 0.589320222 0.076164815
[76] 1.321522200 0.364249910 0.398401368 0.547207082 -0.449648903
[81] -0.623200999 0.636250651 -0.495665489 0.159428220 1.583174095
[86] 0.440494670 0.896020744 0.884903144 0.490282552 0.107043389
[91] -0.050426381 -0.233545376 -0.319839078 0.351521122 0.489191484
[96] 0.260751560 0.778554068 0.405757823 -0.307928614 0.829632633
> 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] 0.007744053 -0.591952238 0.595340542 0.674818669 -0.260266790
[6] -0.023595295 -0.472873273 -1.021032675 0.929116923 1.243218891
[11] 1.303301237 0.480327215 0.401815207 0.073862888 0.713218978
[16] 1.115286345 1.340548292 -0.182964555 0.653633124 -0.031744117
[21] -0.248290336 0.635887580 -0.369157912 -0.713771067 1.071539124
[26] 0.615604850 0.433257001 2.689516741 -1.228958756 -0.683403563
[31] 0.138358487 -0.468139264 1.079766762 0.033392196 2.595320184
[36] 0.631952681 0.171107792 0.350246808 -1.201613600 1.419029857
[41] -0.859296327 -0.269961463 0.907923071 0.365210427 1.140924308
[46] -0.475785079 0.346300474 1.152535718 0.885977547 -0.944178243
[51] -0.119282267 -1.160580668 -0.130195153 0.125693435 -0.329433160
[56] -0.967112820 -0.885136953 -0.262128379 -0.019420321 -1.358597839
[61] 0.405858235 1.547198803 1.187412298 1.263652752 -1.496966262
[66] -0.551391222 -0.203957898 0.245610336 -0.491481814 1.150643758
[71] -0.065993029 -2.008831635 0.282659989 0.589320222 0.076164815
[76] 1.321522200 0.364249910 0.398401368 0.547207082 -0.449648903
[81] -0.623200999 0.636250651 -0.495665489 0.159428220 1.583174095
[86] 0.440494670 0.896020744 0.884903144 0.490282552 0.107043389
[91] -0.050426381 -0.233545376 -0.319839078 0.351521122 0.489191484
[96] 0.260751560 0.778554068 0.405757823 -0.307928614 0.829632633
> rowMin(tmp2)
[1] 0.007744053 -0.591952238 0.595340542 0.674818669 -0.260266790
[6] -0.023595295 -0.472873273 -1.021032675 0.929116923 1.243218891
[11] 1.303301237 0.480327215 0.401815207 0.073862888 0.713218978
[16] 1.115286345 1.340548292 -0.182964555 0.653633124 -0.031744117
[21] -0.248290336 0.635887580 -0.369157912 -0.713771067 1.071539124
[26] 0.615604850 0.433257001 2.689516741 -1.228958756 -0.683403563
[31] 0.138358487 -0.468139264 1.079766762 0.033392196 2.595320184
[36] 0.631952681 0.171107792 0.350246808 -1.201613600 1.419029857
[41] -0.859296327 -0.269961463 0.907923071 0.365210427 1.140924308
[46] -0.475785079 0.346300474 1.152535718 0.885977547 -0.944178243
[51] -0.119282267 -1.160580668 -0.130195153 0.125693435 -0.329433160
[56] -0.967112820 -0.885136953 -0.262128379 -0.019420321 -1.358597839
[61] 0.405858235 1.547198803 1.187412298 1.263652752 -1.496966262
[66] -0.551391222 -0.203957898 0.245610336 -0.491481814 1.150643758
[71] -0.065993029 -2.008831635 0.282659989 0.589320222 0.076164815
[76] 1.321522200 0.364249910 0.398401368 0.547207082 -0.449648903
[81] -0.623200999 0.636250651 -0.495665489 0.159428220 1.583174095
[86] 0.440494670 0.896020744 0.884903144 0.490282552 0.107043389
[91] -0.050426381 -0.233545376 -0.319839078 0.351521122 0.489191484
[96] 0.260751560 0.778554068 0.405757823 -0.307928614 0.829632633
>
> colMeans(tmp2)
[1] 0.2143694
> colSums(tmp2)
[1] 21.43694
> colVars(tmp2)
[1] 0.6737114
> colSd(tmp2)
[1] 0.8207992
> colMax(tmp2)
[1] 2.689517
> colMin(tmp2)
[1] -2.008832
> colMedians(tmp2)
[1] 0.2531809
> colRanges(tmp2)
[,1]
[1,] -2.008832
[2,] 2.689517
>
> 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] -1.07071028 3.52609428 -0.03831111 1.56574342 2.98376591 5.60088783
[7] 0.25393573 -0.68722763 -3.16486150 -5.52770715
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.98953959
[2,] -0.67918172
[3,] -0.04065358
[4,] 0.40374731
[5,] 0.84870834
>
> rowApply(tmp,sum)
[1] 1.54984204 -5.94246307 1.35421357 2.56419549 2.81625712 0.91569372
[7] -0.51490867 0.04692501 1.48983742 -0.83798314
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 7 5 4 7 1 7 10 3 3
[2,] 7 9 10 2 6 5 9 3 9 8
[3,] 10 6 3 7 9 9 1 5 4 5
[4,] 9 2 4 9 4 6 5 9 5 9
[5,] 5 3 2 10 3 10 2 6 6 10
[6,] 2 10 9 8 8 4 8 4 10 7
[7,] 4 5 1 6 5 3 10 2 7 4
[8,] 6 4 8 3 10 7 6 8 2 2
[9,] 1 8 6 1 1 2 4 7 1 6
[10,] 3 1 7 5 2 8 3 1 8 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 4.606704e+00 -2.191438e+00 -3.366250e-01 -5.929937e-05 2.565252e+00
[6] 2.013765e-01 1.766818e+00 -3.299363e+00 -3.438975e+00 6.264983e-01
[11] 3.048710e+00 -3.122798e-01 -1.672171e+00 -2.629509e+00 -5.861959e+00
[16] 6.005086e-02 -1.239032e+00 1.747208e+00 -7.912324e-01 -1.393890e+00
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.1938667
[2,] 0.6969757
[3,] 1.0153944
[4,] 1.2207753
[5,] 1.8674259
>
> rowApply(tmp,sum)
[1] -0.3366117 -4.6443614 -2.1048302 0.6482734 -2.1063856
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 17 10 15 17 19
[2,] 8 1 10 15 10
[3,] 2 18 17 3 15
[4,] 12 11 16 10 8
[5,] 3 15 19 14 18
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.0153944 -0.5996495 -1.5876507 0.03117982 -1.0941493 -0.02026725
[2,] -0.1938667 -2.2229416 1.0630542 -0.12087473 0.4076336 -1.07981537
[3,] 0.6969757 -0.1983875 0.7793155 0.73409200 1.3817944 0.13227538
[4,] 1.2207753 1.0273387 -1.2209263 -0.09992455 0.6742150 1.79131377
[5,] 1.8674259 -0.1977979 0.6295823 -0.54453183 1.1957579 -0.62213005
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.04569931 1.1979981 -0.9195888 0.70991764 1.0134845 -0.6925137
[2,] 1.26810176 -1.6130139 -0.3028266 0.95343208 1.3113810 0.8415403
[3,] -1.09586006 -2.1932331 0.1259097 -0.29767237 -1.1207852 -0.5691463
[4,] 1.02833622 -1.0217416 -1.0026488 -0.83392401 2.8174545 -2.0276665
[5,] 0.61193976 0.3306277 -1.3398202 0.09474494 -0.9728247 2.1355064
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.2354663 1.2846192 -1.63705687 0.1892608 -0.002442166 -0.60015013
[2,] 0.3736412 -1.3894986 -1.26869720 -1.7156156 0.313536364 -0.40900346
[3,] 0.5662786 0.1471471 -1.53294733 -1.1201760 -0.690926747 2.08266034
[4,] -0.6580594 -0.9723636 -1.51531722 1.8701523 -0.068030439 0.01767057
[5,] -3.1894973 -1.6994134 0.09205944 0.8364293 -0.791169198 0.65603044
[,19] [,20]
[1,] 0.8029086 -0.61767330
[2,] -0.8862642 0.02573602
[3,] 0.8825800 -0.81472438
[4,] -0.6302090 0.25182857
[5,] -0.9602478 -0.23905721
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.19-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-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 650 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 563 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.19-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 0.3768937 1.638743 -1.215039 -0.6689996 0.5914061 -0.683199 1.028494
col8 col9 col10 col11 col12 col13 col14
row1 -0.1717831 -0.05018495 -0.3585846 1.590723 -1.013061 1.091576 0.5272803
col15 col16 col17 col18 col19 col20
row1 0.2156961 -0.7461668 0.223029 1.600489 -0.9801789 1.02791
> tmp[,"col10"]
col10
row1 -0.3585846
row2 0.6866988
row3 1.0939823
row4 -2.0287255
row5 -1.4475553
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.3768937 1.6387427 -1.215039 -0.6689996 0.5914061 -0.683199 1.02849414
row5 1.8595642 -0.2822902 1.325591 -0.1472374 1.3658404 -1.449963 -0.06200609
col8 col9 col10 col11 col12 col13
row1 -0.1717831 -0.05018495 -0.3585846 1.5907235 -1.013061 1.0915755
row5 -1.7869539 0.30094288 -1.4475553 -0.1259027 -2.166994 0.4127158
col14 col15 col16 col17 col18 col19
row1 0.5272803 0.2156961 -0.7461668 0.2230290 1.6004893 -0.9801789
row5 -0.0448244 1.1382228 -0.7589478 -0.3541132 -0.4923265 -0.1760045
col20
row1 1.02790980
row5 -0.04191003
> tmp[,c("col6","col20")]
col6 col20
row1 -0.6831990 1.02790980
row2 0.7270493 -0.45448138
row3 0.5067656 -0.51253339
row4 -0.4885695 -0.66979964
row5 -1.4499634 -0.04191003
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.683199 1.02790980
row5 -1.449963 -0.04191003
>
>
>
>
> 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 49.27662 50.85556 47.41074 50.15545 49.76515 105.768 49.01174 50.83474
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.87831 47.91808 48.70917 49.90001 50.02998 50.23448 49.33871 49.48325
col17 col18 col19 col20
row1 51.01047 48.19635 49.68456 106.1994
> tmp[,"col10"]
col10
row1 47.91808
row2 30.49493
row3 28.86661
row4 30.18776
row5 52.56305
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.27662 50.85556 47.41074 50.15545 49.76515 105.7680 49.01174 50.83474
row5 51.01299 51.23174 51.92168 48.73780 50.80572 104.6176 49.46173 50.63371
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.87831 47.91808 48.70917 49.90001 50.02998 50.23448 49.33871 49.48325
row5 51.46435 52.56305 50.82289 47.90560 48.18645 51.55539 49.60476 50.80650
col17 col18 col19 col20
row1 51.01047 48.19635 49.68456 106.1994
row5 50.09028 48.33087 47.58602 103.8291
> tmp[,c("col6","col20")]
col6 col20
row1 105.76798 106.19937
row2 76.14900 74.79493
row3 76.52228 74.34067
row4 74.58624 74.46920
row5 104.61760 103.82905
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.7680 106.1994
row5 104.6176 103.8291
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.7680 106.1994
row5 104.6176 103.8291
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.3930548
[2,] -0.5728722
[3,] -1.5188732
[4,] -0.2624557
[5,] -0.2052780
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.5125632 0.06756412
[2,] 1.1589388 -0.65654912
[3,] 1.1173230 -0.46205598
[4,] -0.6471841 0.03525412
[5,] -0.0522316 1.00133560
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.76983055 0.5034170
[2,] -0.41620757 0.5849640
[3,] 0.03344779 -0.7293052
[4,] -1.08569690 -1.4184855
[5,] 0.50533211 0.1962718
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.7698305
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.7698305
[2,] -0.4162076
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 0.1959864 -2.1713704 -0.3314154 -0.8226735 -1.2357549 0.9375554
row1 -0.5424274 -0.7032724 -0.9831599 -0.1203631 -0.2154912 -0.4512512
[,7] [,8] [,9] [,10] [,11] [,12]
row3 1.77754394 -0.98999439 -0.04404288 -0.2089625 0.3875419 0.6020302
row1 0.01637004 0.08307587 -0.86993921 0.4284599 2.0446504 -0.6818614
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 0.9568196 -0.1176856 0.3945884 0.01309039 -0.1912647 -2.149098 -0.5215430
row1 -1.2900184 -0.1785346 1.3423110 0.85336834 0.8965679 1.373967 0.6332313
[,20]
row3 -0.04449863
row1 -0.89135469
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.7780084 0.09201129 -0.1866156 -0.3814467 -1.326071 -2.43203 -0.07206164
[,8] [,9] [,10]
row2 -1.671375 1.258766 2.681048
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.278507 0.4627211 1.015857 0.5902035 -1.239517 1.034913 -1.046362
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.6084373 0.9318177 0.8878956 0.952094 0.26515 0.3814306 1.098239
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.7001606 -1.038518 -1.12344 -0.2322372 -0.9656001 -1.044714
>
>
> 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: 0x600002078600>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMe310237a6307"
[2] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMe31037fb72c3"
[3] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMe3105d2b7ceb"
[4] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMe31052165816"
[5] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMe31038f13674"
[6] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMe310642e16e0"
[7] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMe310ddfff82"
[8] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMe3106cffb6eb"
[9] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMe3108423635"
[10] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMe31032f4d5cf"
[11] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMe3106801232b"
[12] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMe31022ac1165"
[13] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMe3104eaa0fab"
[14] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMe3107eeacbe5"
[15] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMe31068f0687b"
>
>
> ### 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: 0x60000206ccc0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x60000206ccc0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x60000206ccc0>
> rowMedians(tmp)
[1] -0.2733306915 -0.2138925767 -0.1045233924 -0.1412274570 -0.1143872613
[6] -0.2301515190 -0.0674470038 -0.3561554327 0.4008261400 0.8532584498
[11] 0.1631114066 -0.5978157691 0.2007881217 0.7466431039 -0.4131473419
[16] 0.2328673813 0.2342781127 0.1811472607 -0.0346660260 0.0431174947
[21] 0.3115285115 -0.5932369728 -0.4251323947 0.0408162249 0.1562468664
[26] 0.0827660531 0.0797292415 -0.0138960230 -0.0712293550 -0.0731393605
[31] 0.3496295225 -0.1722092664 -0.1449187404 0.1404211668 0.2737139624
[36] 0.3217220483 0.2470668707 -0.1879118111 0.1311284469 -0.4618036494
[41] -0.3625557605 0.2014107764 -0.0862934249 0.8328051583 0.2865040575
[46] -0.3977542980 0.1302399518 -0.3938183972 0.1397931099 0.3359439644
[51] -0.2655876681 -0.3674094597 0.1545433290 0.1524117132 0.0441276757
[56] 0.1774113197 0.0006987812 0.1329564677 -0.2553916920 0.1901816937
[61] -0.1425156124 -0.2279600844 0.3015396265 -0.2895801705 0.9313424163
[66] 0.1473664491 0.3205299028 0.2565063894 0.0959350062 0.2704258837
[71] 0.1812922689 0.6288860390 0.1964333314 -0.3320428226 0.0946343897
[76] -0.3100640119 0.4412635159 0.1316360784 -0.2323612117 0.6680021998
[81] 0.3885410698 -0.6004237970 0.3357539632 0.1933498824 0.2381222106
[86] -0.2851351342 0.0291276586 0.2248595662 0.3109348735 0.1467220391
[91] -0.1296240425 -0.4617351036 -0.2351134394 0.2892941888 -0.6199566872
[96] -0.1617034502 0.2795352971 -0.4482335478 0.1609031589 0.3240401960
[101] -0.0989762945 0.1948059346 0.1838732279 0.6493108558 -0.1973777358
[106] -0.7923510507 0.1367344730 -0.3123009921 -0.1996064020 -0.1612087833
[111] -0.4171601795 0.0264098417 0.0066474893 -0.4011673329 -0.2847363590
[116] 0.2970950187 0.1488629173 -0.0974855123 -0.2837756572 0.0386510681
[121] 0.0121556993 -0.0092058000 -0.3279958358 0.0887992626 -0.4870070297
[126] 0.0916919792 0.0229328227 0.2642552123 0.0734812001 0.4025469665
[131] 0.3501549448 -0.0409504923 -0.0867321914 0.1599324486 -0.0948709105
[136] -0.2957193938 -0.4105792265 -0.4050002947 -0.1063761392 -0.3162387132
[141] 0.1888561738 -0.2923600906 -0.3272271036 -0.1613781302 0.2959514790
[146] -0.6609291221 0.3442197695 0.3167082554 0.6457883036 -0.2583185528
[151] 0.0102360417 0.3084175496 -0.2700520990 0.0245821733 0.1332653113
[156] -0.4786517440 -0.7222529492 -0.5092064248 -0.2150228201 0.1118044788
[161] -0.1463668622 0.5713977219 -0.1259742498 0.3327564786 -0.4685832410
[166] -0.3512949303 -0.0039355733 -0.0233510466 -0.1712480243 -0.1493946628
[171] -0.1849405644 0.6041040478 -0.0864164754 -0.1752744569 0.0522959718
[176] 0.3781931076 0.4997341464 0.2200462934 0.2266256493 0.2308185539
[181] 0.1412600871 0.1759331354 -0.1677302137 0.1699087112 0.7757051149
[186] -0.2097582405 0.0226111012 -0.6206132900 -0.2497657985 0.3284152082
[191] -0.1951449521 0.1653217077 0.0371469274 0.0316977111 -0.0526070202
[196] 0.2076119078 0.1007865908 0.1419647833 -0.0064361561 0.1149669992
[201] 0.2853467281 -0.1758755403 0.0255272379 -0.3067361458 0.0149848064
[206] 0.0010951164 0.0101170316 0.1366957657 -0.3243723094 0.0045565089
[211] -0.1117419113 0.0622967149 -0.4929578221 0.7486937581 -0.2044765066
[216] -0.2760136205 0.0003300573 -0.3238106500 -0.5275193478 0.6459060766
[221] 0.4481736076 -0.1466718008 0.2874629435 -0.3655956653 -0.3808281849
[226] -0.1843236953 -0.1198406379 -0.1680740260 -0.1233858096 0.2188915910
>
> proc.time()
user system elapsed
2.256 8.333 12.288
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: 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: 0x600002b441e0>
> .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: 0x600002b441e0>
> .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: 0x600002b441e0>
> .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: 0x600002b441e0>
> 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: 0x600002b642a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002b642a0>
> .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: 0x600002b642a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002b642a0>
> .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: 0x600002b642a0>
> 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: 0x600002b64480>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002b64480>
> .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: 0x600002b64480>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600002b64480>
> .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: 0x600002b64480>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600002b64480>
> .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: 0x600002b64480>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600002b64480>
> .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: 0x600002b64480>
> 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: 0x600002b64660>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600002b64660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002b64660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002b64660>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilee33f4ab2c0b5" "BufferedMatrixFilee33f5f60c726"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilee33f4ab2c0b5" "BufferedMatrixFilee33f5f60c726"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002b64900>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002b64900>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600002b64900>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600002b64900>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600002b64900>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600002b64900>
> .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: 0x600002b64ae0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002b64ae0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600002b64ae0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600002b64ae0>
> 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: 0x600002b64cc0>
> .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: 0x600002b64cc0>
> rm(P)
>
> proc.time()
user system elapsed
0.361 0.142 0.502
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: 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.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.358 0.087 0.459