Ben Bolstad
| Snapshot Date: 2025-01-23 13:00 -0500 (Thu, 23 Jan 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_20 |
| git_last_commit: 32b6f6a |
| git_last_commit_date: 2024-10-29 09:27:20 -0500 (Tue, 29 Oct 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2025-01-27 12:10 -0500 (Mon, 27 Jan 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4746 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves" | 4494 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4517 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4469 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4395 |
| 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 251/2289 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.70.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino8 | 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 | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.70.0 |
| 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_1.70.0.tar.gz |
| StartedAt: 2025-01-24 13:09:08 -0500 (Fri, 24 Jan 2025) |
| EndedAt: 2025-01-24 13:09:43 -0500 (Fri, 24 Jan 2025) |
| EllapsedTime: 34.7 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_1.70.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.2 (2024-10-31)
* 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 13.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.70.0’
* 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 4.4.2 (2024-10-31) -- "Pile of Leaves"
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
0.239 0.086 0.318
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
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 474168 25.4 1035467 55.3 NA 638597 34.2
Vcells 877630 6.7 8388608 64.0 65536 2072107 15.9
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Jan 24 13:09:25 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Jan 24 13:09:25 2025"
>
>
> 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: 0x600002e78180>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Jan 24 13:09:27 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Jan 24 13:09:28 2025"
>
> ColMode(tmp2)
<pointer: 0x600002e78180>
>
>
>
> ### 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,] 100.5234557 -0.03391968 1.3565872 -0.2941741
[2,] 0.5102901 0.94044139 0.1769854 -0.4876503
[3,] 0.3485093 -1.04899709 -0.3955687 -0.3386808
[4,] -0.1962084 -1.53845399 -0.2218492 -0.7642611
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.5234557 0.03391968 1.3565872 0.2941741
[2,] 0.5102901 0.94044139 0.1769854 0.4876503
[3,] 0.3485093 1.04899709 0.3955687 0.3386808
[4,] 0.1962084 1.53845399 0.2218492 0.7642611
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0261386 0.1841730 1.1647262 0.5423782
[2,] 0.7143459 0.9697636 0.4206963 0.6983196
[3,] 0.5903468 1.0242056 0.6289425 0.5819629
[4,] 0.4429542 1.2403443 0.4710087 0.8742203
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.78484 26.87565 38.00385 30.71796
[2,] 32.65375 35.63808 29.38395 32.47085
[3,] 31.25198 36.29105 31.68499 31.15831
[4,] 29.62575 38.94190 29.93194 34.50646
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600002e781e0>
> exp(tmp5)
<pointer: 0x600002e781e0>
> log(tmp5,2)
<pointer: 0x600002e781e0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.9416
> Min(tmp5)
[1] 53.7958
> mean(tmp5)
[1] 73.31275
> Sum(tmp5)
[1] 14662.55
> Var(tmp5)
[1] 868.6247
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.78895 72.93723 70.40453 73.97076 70.53005 71.36800 68.77761 72.34220
[9] 71.68287 69.32526
> rowSums(tmp5)
[1] 1835.779 1458.745 1408.091 1479.415 1410.601 1427.360 1375.552 1446.844
[9] 1433.657 1386.505
> rowVars(tmp5)
[1] 7992.77556 65.14337 77.54643 69.95615 108.53945 105.07134
[7] 55.29165 74.04580 79.51112 46.66962
> rowSd(tmp5)
[1] 89.402324 8.071144 8.806045 8.363980 10.418227 10.250431 7.435836
[8] 8.604987 8.916901 6.831517
> rowMax(tmp5)
[1] 469.94157 84.19279 85.76658 89.44734 92.69463 89.16907 86.39653
[8] 87.07559 95.85149 82.70810
> rowMin(tmp5)
[1] 55.93814 58.23829 58.04137 61.66212 54.93933 53.79580 57.65768 57.50967
[9] 60.47332 54.85549
>
> colMeans(tmp5)
[1] 111.92344 68.79367 68.25992 70.50285 70.78542 72.07461 73.26679
[8] 77.16855 75.68671 72.23063 70.27343 71.06167 67.01730 72.45441
[15] 70.51930 68.80936 69.21801 69.74026 71.99867 74.46993
> colSums(tmp5)
[1] 1119.2344 687.9367 682.5992 705.0285 707.8542 720.7461 732.6679
[8] 771.6855 756.8671 722.3063 702.7343 710.6167 670.1730 724.5441
[15] 705.1930 688.0936 692.1801 697.4026 719.9867 744.6993
> colVars(tmp5)
[1] 15880.99966 107.47974 47.00521 47.72259 57.31074 65.14624
[7] 128.53953 164.01361 62.28870 67.90392 93.06043 124.24392
[13] 75.76891 37.38912 37.89737 54.61979 57.66471 111.05235
[19] 50.42255 58.41326
> colSd(tmp5)
[1] 126.019838 10.367243 6.856035 6.908154 7.570386 8.071322
[7] 11.337527 12.806780 7.892319 8.240384 9.646783 11.146475
[13] 8.704534 6.114665 6.156084 7.390520 7.593728 10.538138
[19] 7.100884 7.642857
> colMax(tmp5)
[1] 469.94157 82.70810 79.97567 86.39653 84.83727 83.53625 89.44734
[8] 95.85149 87.69541 84.20521 82.83736 88.94205 84.99376 80.07656
[15] 78.40185 79.24305 82.17707 87.91752 83.11566 83.40197
> colMin(tmp5)
[1] 61.66212 55.93814 61.15884 63.25724 60.47332 58.84150 58.08567 58.39372
[9] 63.20810 54.85549 58.04137 57.65925 54.93933 61.37356 59.85585 53.79580
[17] 57.99203 57.66051 61.18323 60.63649
>
>
> ### 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] 91.78895 72.93723 70.40453 73.97076 70.53005 71.36800 68.77761 72.34220
[9] NA 69.32526
> rowSums(tmp5)
[1] 1835.779 1458.745 1408.091 1479.415 1410.601 1427.360 1375.552 1446.844
[9] NA 1386.505
> rowVars(tmp5)
[1] 7992.77556 65.14337 77.54643 69.95615 108.53945 105.07134
[7] 55.29165 74.04580 81.66270 46.66962
> rowSd(tmp5)
[1] 89.402324 8.071144 8.806045 8.363980 10.418227 10.250431 7.435836
[8] 8.604987 9.036742 6.831517
> rowMax(tmp5)
[1] 469.94157 84.19279 85.76658 89.44734 92.69463 89.16907 86.39653
[8] 87.07559 NA 82.70810
> rowMin(tmp5)
[1] 55.93814 58.23829 58.04137 61.66212 54.93933 53.79580 57.65768 57.50967
[9] NA 54.85549
>
> colMeans(tmp5)
[1] 111.92344 68.79367 68.25992 70.50285 70.78542 72.07461 73.26679
[8] 77.16855 75.68671 NA 70.27343 71.06167 67.01730 72.45441
[15] 70.51930 68.80936 69.21801 69.74026 71.99867 74.46993
> colSums(tmp5)
[1] 1119.2344 687.9367 682.5992 705.0285 707.8542 720.7461 732.6679
[8] 771.6855 756.8671 NA 702.7343 710.6167 670.1730 724.5441
[15] 705.1930 688.0936 692.1801 697.4026 719.9867 744.6993
> colVars(tmp5)
[1] 15880.99966 107.47974 47.00521 47.72259 57.31074 65.14624
[7] 128.53953 164.01361 62.28870 NA 93.06043 124.24392
[13] 75.76891 37.38912 37.89737 54.61979 57.66471 111.05235
[19] 50.42255 58.41326
> colSd(tmp5)
[1] 126.019838 10.367243 6.856035 6.908154 7.570386 8.071322
[7] 11.337527 12.806780 7.892319 NA 9.646783 11.146475
[13] 8.704534 6.114665 6.156084 7.390520 7.593728 10.538138
[19] 7.100884 7.642857
> colMax(tmp5)
[1] 469.94157 82.70810 79.97567 86.39653 84.83727 83.53625 89.44734
[8] 95.85149 87.69541 NA 82.83736 88.94205 84.99376 80.07656
[15] 78.40185 79.24305 82.17707 87.91752 83.11566 83.40197
> colMin(tmp5)
[1] 61.66212 55.93814 61.15884 63.25724 60.47332 58.84150 58.08567 58.39372
[9] 63.20810 NA 58.04137 57.65925 54.93933 61.37356 59.85585 53.79580
[17] 57.99203 57.66051 61.18323 60.63649
>
> Max(tmp5,na.rm=TRUE)
[1] 469.9416
> Min(tmp5,na.rm=TRUE)
[1] 53.7958
> mean(tmp5,na.rm=TRUE)
[1] 73.35221
> Sum(tmp5,na.rm=TRUE)
[1] 14597.09
> Var(tmp5,na.rm=TRUE)
[1] 872.6986
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.78895 72.93723 70.40453 73.97076 70.53005 71.36800 68.77761 72.34220
[9] 72.01048 69.32526
> rowSums(tmp5,na.rm=TRUE)
[1] 1835.779 1458.745 1408.091 1479.415 1410.601 1427.360 1375.552 1446.844
[9] 1368.199 1386.505
> rowVars(tmp5,na.rm=TRUE)
[1] 7992.77556 65.14337 77.54643 69.95615 108.53945 105.07134
[7] 55.29165 74.04580 81.66270 46.66962
> rowSd(tmp5,na.rm=TRUE)
[1] 89.402324 8.071144 8.806045 8.363980 10.418227 10.250431 7.435836
[8] 8.604987 9.036742 6.831517
> rowMax(tmp5,na.rm=TRUE)
[1] 469.94157 84.19279 85.76658 89.44734 92.69463 89.16907 86.39653
[8] 87.07559 95.85149 82.70810
> rowMin(tmp5,na.rm=TRUE)
[1] 55.93814 58.23829 58.04137 61.66212 54.93933 53.79580 57.65768 57.50967
[9] 60.47332 54.85549
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.92344 68.79367 68.25992 70.50285 70.78542 72.07461 73.26679
[8] 77.16855 75.68671 72.98310 70.27343 71.06167 67.01730 72.45441
[15] 70.51930 68.80936 69.21801 69.74026 71.99867 74.46993
> colSums(tmp5,na.rm=TRUE)
[1] 1119.2344 687.9367 682.5992 705.0285 707.8542 720.7461 732.6679
[8] 771.6855 756.8671 656.8479 702.7343 710.6167 670.1730 724.5441
[15] 705.1930 688.0936 692.1801 697.4026 719.9867 744.6993
> colVars(tmp5,na.rm=TRUE)
[1] 15880.99966 107.47974 47.00521 47.72259 57.31074 65.14624
[7] 128.53953 164.01361 62.28870 70.02212 93.06043 124.24392
[13] 75.76891 37.38912 37.89737 54.61979 57.66471 111.05235
[19] 50.42255 58.41326
> colSd(tmp5,na.rm=TRUE)
[1] 126.019838 10.367243 6.856035 6.908154 7.570386 8.071322
[7] 11.337527 12.806780 7.892319 8.367922 9.646783 11.146475
[13] 8.704534 6.114665 6.156084 7.390520 7.593728 10.538138
[19] 7.100884 7.642857
> colMax(tmp5,na.rm=TRUE)
[1] 469.94157 82.70810 79.97567 86.39653 84.83727 83.53625 89.44734
[8] 95.85149 87.69541 84.20521 82.83736 88.94205 84.99376 80.07656
[15] 78.40185 79.24305 82.17707 87.91752 83.11566 83.40197
> colMin(tmp5,na.rm=TRUE)
[1] 61.66212 55.93814 61.15884 63.25724 60.47332 58.84150 58.08567 58.39372
[9] 63.20810 54.85549 58.04137 57.65925 54.93933 61.37356 59.85585 53.79580
[17] 57.99203 57.66051 61.18323 60.63649
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.78895 72.93723 70.40453 73.97076 70.53005 71.36800 68.77761 72.34220
[9] NaN 69.32526
> rowSums(tmp5,na.rm=TRUE)
[1] 1835.779 1458.745 1408.091 1479.415 1410.601 1427.360 1375.552 1446.844
[9] 0.000 1386.505
> rowVars(tmp5,na.rm=TRUE)
[1] 7992.77556 65.14337 77.54643 69.95615 108.53945 105.07134
[7] 55.29165 74.04580 NA 46.66962
> rowSd(tmp5,na.rm=TRUE)
[1] 89.402324 8.071144 8.806045 8.363980 10.418227 10.250431 7.435836
[8] 8.604987 NA 6.831517
> rowMax(tmp5,na.rm=TRUE)
[1] 469.94157 84.19279 85.76658 89.44734 92.69463 89.16907 86.39653
[8] 87.07559 NA 82.70810
> rowMin(tmp5,na.rm=TRUE)
[1] 55.93814 58.23829 58.04137 61.66212 54.93933 53.79580 57.65768 57.50967
[9] NA 54.85549
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.94995 67.87398 68.86152 69.98396 71.93121 71.28986 72.84492
[8] 75.09266 76.29123 NaN 71.04558 72.19132 66.39469 73.15035
[15] 71.45596 69.10548 69.34398 68.61774 71.90376 73.56561
> colSums(tmp5,na.rm=TRUE)
[1] 1043.5495 610.8658 619.7536 629.8557 647.3809 641.6088 655.6043
[8] 675.8340 686.6210 0.0000 639.4102 649.7219 597.5522 658.3531
[15] 643.1036 621.9493 624.0958 617.5597 647.1339 662.0905
> colVars(tmp5,na.rm=TRUE)
[1] 17683.73128 111.39905 48.80930 50.65890 49.70520 66.36155
[7] 142.60478 136.03580 65.96353 NA 97.98562 125.41817
[13] 80.87907 36.61409 32.76458 60.46077 64.69430 110.75846
[19] 56.62404 56.51487
> colSd(tmp5,na.rm=TRUE)
[1] 132.980191 10.554575 6.986366 7.117507 7.050192 8.146260
[7] 11.941724 11.663438 8.121793 NA 9.898768 11.199025
[13] 8.993279 6.050958 5.724035 7.775652 8.043277 10.524185
[19] 7.524895 7.517637
> colMax(tmp5,na.rm=TRUE)
[1] 469.94157 82.70810 79.97567 86.39653 84.83727 83.53625 89.44734
[8] 92.69463 87.69541 -Inf 82.83736 88.94205 84.99376 80.07656
[15] 78.40185 79.24305 82.17707 87.91752 83.11566 83.40197
> colMin(tmp5,na.rm=TRUE)
[1] 61.66212 55.93814 61.15884 63.25724 63.34424 58.84150 58.08567 58.39372
[9] 63.20810 Inf 58.04137 57.65925 54.93933 61.37356 59.85585 53.79580
[17] 57.99203 57.66051 61.18323 60.63649
>
>
>
>
> 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] 194.84970 91.20252 281.47847 141.60754 207.89482 176.14066 317.63454
[8] 156.66390 347.91455 278.01623
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 194.84970 91.20252 281.47847 141.60754 207.89482 176.14066 317.63454
[8] 156.66390 347.91455 278.01623
>
>
>
> 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] 4.973799e-14 0.000000e+00 -2.842171e-14 -2.273737e-13 -5.684342e-14
[6] 5.684342e-14 1.136868e-13 -1.136868e-13 -1.989520e-13 0.000000e+00
[11] -1.136868e-13 4.263256e-14 8.526513e-14 -1.705303e-13 -5.684342e-14
[16] 4.547474e-13 0.000000e+00 1.136868e-13 5.684342e-14 1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
2 9
10 17
5 20
8 7
3 18
3 6
8 15
8 12
8 8
1 2
10 12
5 4
2 19
3 15
6 19
9 4
8 6
9 10
5 14
7 10
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] 1.768839
> Min(tmp)
[1] -2.000354
> mean(tmp)
[1] 0.1663512
> Sum(tmp)
[1] 16.63512
> Var(tmp)
[1] 0.7066136
>
> rowMeans(tmp)
[1] 0.1663512
> rowSums(tmp)
[1] 16.63512
> rowVars(tmp)
[1] 0.7066136
> rowSd(tmp)
[1] 0.8406031
> rowMax(tmp)
[1] 1.768839
> rowMin(tmp)
[1] -2.000354
>
> colMeans(tmp)
[1] -1.072781709 -0.012492691 1.240927920 0.543669933 0.652459148
[6] 0.788871914 -0.007631054 1.551959978 -0.153657032 1.131329490
[11] 1.017545517 0.643296200 0.598073191 1.320612404 0.086696929
[16] 1.511353597 -0.089927516 1.010879474 1.254798786 0.760256814
[21] -0.204516050 0.065938917 0.697637072 -0.186136119 -1.211232291
[26] -0.919320908 1.641384858 1.169176020 1.768838649 0.831427452
[31] 0.294555855 0.850983894 0.889357391 -1.842052209 0.848488617
[36] -0.758557912 -0.083689640 -0.157842867 0.515654266 0.811792637
[41] 1.182568577 1.306831873 1.549314710 0.254405319 1.188126659
[46] -0.149340845 -0.649335823 -2.000354055 -0.658799187 0.326313806
[51] 0.556466820 -0.045400969 1.480435117 0.083212070 -0.292180679
[56] -0.343485802 -0.569889495 -0.883588880 0.933419826 -1.102934853
[61] -0.238357239 -0.274553077 1.196688488 0.684573213 0.291364472
[66] 0.156463420 -0.530558780 -0.171622905 0.604445018 -1.601798780
[71] 0.288869124 -0.553040982 -0.661705836 -1.054847006 -0.940261150
[76] -0.412081520 -0.044702629 0.252727333 -0.556132825 1.153834467
[81] 0.239767771 0.683243396 0.440906583 -0.726826729 0.066188842
[86] -0.578013431 -1.076153695 -0.986037919 -0.604406785 1.159634525
[91] 0.181518261 -0.342770317 1.094762497 -0.111471455 -0.412480958
[96] 1.028519390 0.455292885 0.369411079 -0.854031292 -0.945152070
> colSums(tmp)
[1] -1.072781709 -0.012492691 1.240927920 0.543669933 0.652459148
[6] 0.788871914 -0.007631054 1.551959978 -0.153657032 1.131329490
[11] 1.017545517 0.643296200 0.598073191 1.320612404 0.086696929
[16] 1.511353597 -0.089927516 1.010879474 1.254798786 0.760256814
[21] -0.204516050 0.065938917 0.697637072 -0.186136119 -1.211232291
[26] -0.919320908 1.641384858 1.169176020 1.768838649 0.831427452
[31] 0.294555855 0.850983894 0.889357391 -1.842052209 0.848488617
[36] -0.758557912 -0.083689640 -0.157842867 0.515654266 0.811792637
[41] 1.182568577 1.306831873 1.549314710 0.254405319 1.188126659
[46] -0.149340845 -0.649335823 -2.000354055 -0.658799187 0.326313806
[51] 0.556466820 -0.045400969 1.480435117 0.083212070 -0.292180679
[56] -0.343485802 -0.569889495 -0.883588880 0.933419826 -1.102934853
[61] -0.238357239 -0.274553077 1.196688488 0.684573213 0.291364472
[66] 0.156463420 -0.530558780 -0.171622905 0.604445018 -1.601798780
[71] 0.288869124 -0.553040982 -0.661705836 -1.054847006 -0.940261150
[76] -0.412081520 -0.044702629 0.252727333 -0.556132825 1.153834467
[81] 0.239767771 0.683243396 0.440906583 -0.726826729 0.066188842
[86] -0.578013431 -1.076153695 -0.986037919 -0.604406785 1.159634525
[91] 0.181518261 -0.342770317 1.094762497 -0.111471455 -0.412480958
[96] 1.028519390 0.455292885 0.369411079 -0.854031292 -0.945152070
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] -1.072781709 -0.012492691 1.240927920 0.543669933 0.652459148
[6] 0.788871914 -0.007631054 1.551959978 -0.153657032 1.131329490
[11] 1.017545517 0.643296200 0.598073191 1.320612404 0.086696929
[16] 1.511353597 -0.089927516 1.010879474 1.254798786 0.760256814
[21] -0.204516050 0.065938917 0.697637072 -0.186136119 -1.211232291
[26] -0.919320908 1.641384858 1.169176020 1.768838649 0.831427452
[31] 0.294555855 0.850983894 0.889357391 -1.842052209 0.848488617
[36] -0.758557912 -0.083689640 -0.157842867 0.515654266 0.811792637
[41] 1.182568577 1.306831873 1.549314710 0.254405319 1.188126659
[46] -0.149340845 -0.649335823 -2.000354055 -0.658799187 0.326313806
[51] 0.556466820 -0.045400969 1.480435117 0.083212070 -0.292180679
[56] -0.343485802 -0.569889495 -0.883588880 0.933419826 -1.102934853
[61] -0.238357239 -0.274553077 1.196688488 0.684573213 0.291364472
[66] 0.156463420 -0.530558780 -0.171622905 0.604445018 -1.601798780
[71] 0.288869124 -0.553040982 -0.661705836 -1.054847006 -0.940261150
[76] -0.412081520 -0.044702629 0.252727333 -0.556132825 1.153834467
[81] 0.239767771 0.683243396 0.440906583 -0.726826729 0.066188842
[86] -0.578013431 -1.076153695 -0.986037919 -0.604406785 1.159634525
[91] 0.181518261 -0.342770317 1.094762497 -0.111471455 -0.412480958
[96] 1.028519390 0.455292885 0.369411079 -0.854031292 -0.945152070
> colMin(tmp)
[1] -1.072781709 -0.012492691 1.240927920 0.543669933 0.652459148
[6] 0.788871914 -0.007631054 1.551959978 -0.153657032 1.131329490
[11] 1.017545517 0.643296200 0.598073191 1.320612404 0.086696929
[16] 1.511353597 -0.089927516 1.010879474 1.254798786 0.760256814
[21] -0.204516050 0.065938917 0.697637072 -0.186136119 -1.211232291
[26] -0.919320908 1.641384858 1.169176020 1.768838649 0.831427452
[31] 0.294555855 0.850983894 0.889357391 -1.842052209 0.848488617
[36] -0.758557912 -0.083689640 -0.157842867 0.515654266 0.811792637
[41] 1.182568577 1.306831873 1.549314710 0.254405319 1.188126659
[46] -0.149340845 -0.649335823 -2.000354055 -0.658799187 0.326313806
[51] 0.556466820 -0.045400969 1.480435117 0.083212070 -0.292180679
[56] -0.343485802 -0.569889495 -0.883588880 0.933419826 -1.102934853
[61] -0.238357239 -0.274553077 1.196688488 0.684573213 0.291364472
[66] 0.156463420 -0.530558780 -0.171622905 0.604445018 -1.601798780
[71] 0.288869124 -0.553040982 -0.661705836 -1.054847006 -0.940261150
[76] -0.412081520 -0.044702629 0.252727333 -0.556132825 1.153834467
[81] 0.239767771 0.683243396 0.440906583 -0.726826729 0.066188842
[86] -0.578013431 -1.076153695 -0.986037919 -0.604406785 1.159634525
[91] 0.181518261 -0.342770317 1.094762497 -0.111471455 -0.412480958
[96] 1.028519390 0.455292885 0.369411079 -0.854031292 -0.945152070
> colMedians(tmp)
[1] -1.072781709 -0.012492691 1.240927920 0.543669933 0.652459148
[6] 0.788871914 -0.007631054 1.551959978 -0.153657032 1.131329490
[11] 1.017545517 0.643296200 0.598073191 1.320612404 0.086696929
[16] 1.511353597 -0.089927516 1.010879474 1.254798786 0.760256814
[21] -0.204516050 0.065938917 0.697637072 -0.186136119 -1.211232291
[26] -0.919320908 1.641384858 1.169176020 1.768838649 0.831427452
[31] 0.294555855 0.850983894 0.889357391 -1.842052209 0.848488617
[36] -0.758557912 -0.083689640 -0.157842867 0.515654266 0.811792637
[41] 1.182568577 1.306831873 1.549314710 0.254405319 1.188126659
[46] -0.149340845 -0.649335823 -2.000354055 -0.658799187 0.326313806
[51] 0.556466820 -0.045400969 1.480435117 0.083212070 -0.292180679
[56] -0.343485802 -0.569889495 -0.883588880 0.933419826 -1.102934853
[61] -0.238357239 -0.274553077 1.196688488 0.684573213 0.291364472
[66] 0.156463420 -0.530558780 -0.171622905 0.604445018 -1.601798780
[71] 0.288869124 -0.553040982 -0.661705836 -1.054847006 -0.940261150
[76] -0.412081520 -0.044702629 0.252727333 -0.556132825 1.153834467
[81] 0.239767771 0.683243396 0.440906583 -0.726826729 0.066188842
[86] -0.578013431 -1.076153695 -0.986037919 -0.604406785 1.159634525
[91] 0.181518261 -0.342770317 1.094762497 -0.111471455 -0.412480958
[96] 1.028519390 0.455292885 0.369411079 -0.854031292 -0.945152070
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.072782 -0.01249269 1.240928 0.5436699 0.6524591 0.7888719 -0.007631054
[2,] -1.072782 -0.01249269 1.240928 0.5436699 0.6524591 0.7888719 -0.007631054
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.55196 -0.153657 1.131329 1.017546 0.6432962 0.5980732 1.320612
[2,] 1.55196 -0.153657 1.131329 1.017546 0.6432962 0.5980732 1.320612
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.08669693 1.511354 -0.08992752 1.010879 1.254799 0.7602568 -0.204516
[2,] 0.08669693 1.511354 -0.08992752 1.010879 1.254799 0.7602568 -0.204516
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.06593892 0.6976371 -0.1861361 -1.211232 -0.9193209 1.641385 1.169176
[2,] 0.06593892 0.6976371 -0.1861361 -1.211232 -0.9193209 1.641385 1.169176
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.768839 0.8314275 0.2945559 0.8509839 0.8893574 -1.842052 0.8484886
[2,] 1.768839 0.8314275 0.2945559 0.8509839 0.8893574 -1.842052 0.8484886
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.7585579 -0.08368964 -0.1578429 0.5156543 0.8117926 1.182569 1.306832
[2,] -0.7585579 -0.08368964 -0.1578429 0.5156543 0.8117926 1.182569 1.306832
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 1.549315 0.2544053 1.188127 -0.1493408 -0.6493358 -2.000354 -0.6587992
[2,] 1.549315 0.2544053 1.188127 -0.1493408 -0.6493358 -2.000354 -0.6587992
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.3263138 0.5564668 -0.04540097 1.480435 0.08321207 -0.2921807 -0.3434858
[2,] 0.3263138 0.5564668 -0.04540097 1.480435 0.08321207 -0.2921807 -0.3434858
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.5698895 -0.8835889 0.9334198 -1.102935 -0.2383572 -0.2745531 1.196688
[2,] -0.5698895 -0.8835889 0.9334198 -1.102935 -0.2383572 -0.2745531 1.196688
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.6845732 0.2913645 0.1564634 -0.5305588 -0.1716229 0.604445 -1.601799
[2,] 0.6845732 0.2913645 0.1564634 -0.5305588 -0.1716229 0.604445 -1.601799
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.2888691 -0.553041 -0.6617058 -1.054847 -0.9402611 -0.4120815 -0.04470263
[2,] 0.2888691 -0.553041 -0.6617058 -1.054847 -0.9402611 -0.4120815 -0.04470263
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.2527273 -0.5561328 1.153834 0.2397678 0.6832434 0.4409066 -0.7268267
[2,] 0.2527273 -0.5561328 1.153834 0.2397678 0.6832434 0.4409066 -0.7268267
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.06618884 -0.5780134 -1.076154 -0.9860379 -0.6044068 1.159635 0.1815183
[2,] 0.06618884 -0.5780134 -1.076154 -0.9860379 -0.6044068 1.159635 0.1815183
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.3427703 1.094762 -0.1114715 -0.412481 1.028519 0.4552929 0.3694111
[2,] -0.3427703 1.094762 -0.1114715 -0.412481 1.028519 0.4552929 0.3694111
[,99] [,100]
[1,] -0.8540313 -0.9451521
[2,] -0.8540313 -0.9451521
>
>
> Max(tmp2)
[1] 2.921632
> Min(tmp2)
[1] -2.617534
> mean(tmp2)
[1] -0.1281769
> Sum(tmp2)
[1] -12.81769
> Var(tmp2)
[1] 1.020045
>
> rowMeans(tmp2)
[1] -1.201922442 -1.176519842 -0.653025849 -1.083823359 -0.752476067
[6] -0.585984979 -2.617534165 -1.668359381 -1.271996008 2.921632441
[11] -0.339167371 -0.431438821 -0.111573452 -1.169170665 0.572894721
[16] -1.412480412 0.800858897 1.361219398 0.569135084 0.072109090
[21] -0.838362512 -0.283128357 -0.004515673 0.414154642 0.452522337
[26] -0.291358769 -0.334203588 0.472457146 0.904194346 -0.204815847
[31] 1.070837159 0.548391873 1.110655361 -0.967426100 0.316425407
[36] -0.740947859 -0.012596841 0.217409596 1.118808450 -1.230937823
[41] -0.273397344 -0.397028143 -0.703515868 -0.616268331 0.709371117
[46] -1.397695905 -0.373670728 -1.756143417 -0.229315321 0.844639481
[51] 1.302773802 0.685994990 -1.144985314 -0.177750589 -0.008663391
[56] -0.613616602 -0.113513702 -2.091206560 -2.147490459 -0.330323871
[61] -0.219897379 -0.489877607 0.856414135 1.436099620 -0.149043045
[66] -0.049604893 -0.670259759 -0.515325785 0.628636301 1.334144795
[71] -0.246958448 -0.360922141 0.822276121 -1.618192992 0.747467843
[76] 1.812360953 -2.219704803 0.155080543 -1.076838870 1.278021453
[81] -1.244230025 0.800154384 0.176139315 1.220107219 0.669717566
[86] -1.006693900 0.371506822 0.887088907 -2.065801277 0.651942590
[91] 0.552770615 0.824026406 1.737548974 -0.100447288 0.224346221
[96] -0.476272580 -0.685340446 -1.738141867 0.796247685 -0.574367042
> rowSums(tmp2)
[1] -1.201922442 -1.176519842 -0.653025849 -1.083823359 -0.752476067
[6] -0.585984979 -2.617534165 -1.668359381 -1.271996008 2.921632441
[11] -0.339167371 -0.431438821 -0.111573452 -1.169170665 0.572894721
[16] -1.412480412 0.800858897 1.361219398 0.569135084 0.072109090
[21] -0.838362512 -0.283128357 -0.004515673 0.414154642 0.452522337
[26] -0.291358769 -0.334203588 0.472457146 0.904194346 -0.204815847
[31] 1.070837159 0.548391873 1.110655361 -0.967426100 0.316425407
[36] -0.740947859 -0.012596841 0.217409596 1.118808450 -1.230937823
[41] -0.273397344 -0.397028143 -0.703515868 -0.616268331 0.709371117
[46] -1.397695905 -0.373670728 -1.756143417 -0.229315321 0.844639481
[51] 1.302773802 0.685994990 -1.144985314 -0.177750589 -0.008663391
[56] -0.613616602 -0.113513702 -2.091206560 -2.147490459 -0.330323871
[61] -0.219897379 -0.489877607 0.856414135 1.436099620 -0.149043045
[66] -0.049604893 -0.670259759 -0.515325785 0.628636301 1.334144795
[71] -0.246958448 -0.360922141 0.822276121 -1.618192992 0.747467843
[76] 1.812360953 -2.219704803 0.155080543 -1.076838870 1.278021453
[81] -1.244230025 0.800154384 0.176139315 1.220107219 0.669717566
[86] -1.006693900 0.371506822 0.887088907 -2.065801277 0.651942590
[91] 0.552770615 0.824026406 1.737548974 -0.100447288 0.224346221
[96] -0.476272580 -0.685340446 -1.738141867 0.796247685 -0.574367042
> 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] -1.201922442 -1.176519842 -0.653025849 -1.083823359 -0.752476067
[6] -0.585984979 -2.617534165 -1.668359381 -1.271996008 2.921632441
[11] -0.339167371 -0.431438821 -0.111573452 -1.169170665 0.572894721
[16] -1.412480412 0.800858897 1.361219398 0.569135084 0.072109090
[21] -0.838362512 -0.283128357 -0.004515673 0.414154642 0.452522337
[26] -0.291358769 -0.334203588 0.472457146 0.904194346 -0.204815847
[31] 1.070837159 0.548391873 1.110655361 -0.967426100 0.316425407
[36] -0.740947859 -0.012596841 0.217409596 1.118808450 -1.230937823
[41] -0.273397344 -0.397028143 -0.703515868 -0.616268331 0.709371117
[46] -1.397695905 -0.373670728 -1.756143417 -0.229315321 0.844639481
[51] 1.302773802 0.685994990 -1.144985314 -0.177750589 -0.008663391
[56] -0.613616602 -0.113513702 -2.091206560 -2.147490459 -0.330323871
[61] -0.219897379 -0.489877607 0.856414135 1.436099620 -0.149043045
[66] -0.049604893 -0.670259759 -0.515325785 0.628636301 1.334144795
[71] -0.246958448 -0.360922141 0.822276121 -1.618192992 0.747467843
[76] 1.812360953 -2.219704803 0.155080543 -1.076838870 1.278021453
[81] -1.244230025 0.800154384 0.176139315 1.220107219 0.669717566
[86] -1.006693900 0.371506822 0.887088907 -2.065801277 0.651942590
[91] 0.552770615 0.824026406 1.737548974 -0.100447288 0.224346221
[96] -0.476272580 -0.685340446 -1.738141867 0.796247685 -0.574367042
> rowMin(tmp2)
[1] -1.201922442 -1.176519842 -0.653025849 -1.083823359 -0.752476067
[6] -0.585984979 -2.617534165 -1.668359381 -1.271996008 2.921632441
[11] -0.339167371 -0.431438821 -0.111573452 -1.169170665 0.572894721
[16] -1.412480412 0.800858897 1.361219398 0.569135084 0.072109090
[21] -0.838362512 -0.283128357 -0.004515673 0.414154642 0.452522337
[26] -0.291358769 -0.334203588 0.472457146 0.904194346 -0.204815847
[31] 1.070837159 0.548391873 1.110655361 -0.967426100 0.316425407
[36] -0.740947859 -0.012596841 0.217409596 1.118808450 -1.230937823
[41] -0.273397344 -0.397028143 -0.703515868 -0.616268331 0.709371117
[46] -1.397695905 -0.373670728 -1.756143417 -0.229315321 0.844639481
[51] 1.302773802 0.685994990 -1.144985314 -0.177750589 -0.008663391
[56] -0.613616602 -0.113513702 -2.091206560 -2.147490459 -0.330323871
[61] -0.219897379 -0.489877607 0.856414135 1.436099620 -0.149043045
[66] -0.049604893 -0.670259759 -0.515325785 0.628636301 1.334144795
[71] -0.246958448 -0.360922141 0.822276121 -1.618192992 0.747467843
[76] 1.812360953 -2.219704803 0.155080543 -1.076838870 1.278021453
[81] -1.244230025 0.800154384 0.176139315 1.220107219 0.669717566
[86] -1.006693900 0.371506822 0.887088907 -2.065801277 0.651942590
[91] 0.552770615 0.824026406 1.737548974 -0.100447288 0.224346221
[96] -0.476272580 -0.685340446 -1.738141867 0.796247685 -0.574367042
>
> colMeans(tmp2)
[1] -0.1281769
> colSums(tmp2)
[1] -12.81769
> colVars(tmp2)
[1] 1.020045
> colSd(tmp2)
[1] 1.009973
> colMax(tmp2)
[1] 2.921632
> colMin(tmp2)
[1] -2.617534
> colMedians(tmp2)
[1] -0.1912832
> colRanges(tmp2)
[,1]
[1,] -2.617534
[2,] 2.921632
>
> 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] 2.89560063 0.40519871 2.81239450 0.07653402 1.43031384 -5.20933726
[7] -3.82378298 -0.63228024 7.45983548 2.89084795
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1346722
[2,] -0.4279353
[3,] 0.3210154
[4,] 0.9055580
[5,] 2.1139875
>
> rowApply(tmp,sum)
[1] 5.3073511 -1.2543208 4.1806639 -5.3751242 -2.1875373 -3.4311708
[7] 0.5807133 4.5056378 3.4731565 2.5059551
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 4 8 7 5 3 5 4 7 8 10
[2,] 8 2 9 6 5 6 6 4 3 5
[3,] 9 4 2 8 9 3 10 9 5 4
[4,] 7 6 4 2 2 10 7 5 6 3
[5,] 6 7 3 4 1 1 2 10 10 7
[6,] 3 1 1 1 7 4 8 2 4 8
[7,] 2 3 6 9 4 2 1 8 2 2
[8,] 1 9 5 7 8 9 9 3 1 6
[9,] 10 10 8 3 10 8 5 6 9 1
[10,] 5 5 10 10 6 7 3 1 7 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.6211577 -2.1671373 -1.1015272 -2.6564139 -0.6378105 -4.4019030
[7] 3.2195695 -1.6700015 -1.8753703 0.7570075 -2.7306065 3.6621697
[13] -2.0809217 3.6179019 1.1302051 1.0009189 0.1607063 -1.9130359
[19] 2.4148191 3.3788742
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.96307943
[2,] -0.77638225
[3,] 0.08666535
[4,] 1.20588796
[5,] 2.06806603
>
> rowApply(tmp,sum)
[1] 0.09531662 3.11464059 1.04352422 -6.38914977 1.86427056
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 2 20 12 8 18
[2,] 5 3 2 7 20
[3,] 10 4 1 13 15
[4,] 13 18 7 2 4
[5,] 8 8 15 11 8
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.96307943 -0.6129234 -0.11274487 0.04289569 -0.31490441 -0.9511293
[2,] 2.06806603 -1.1808071 -0.52045882 0.93138220 -0.02003426 0.8887256
[3,] 0.08666535 -1.0285843 -1.45964654 -0.46045074 0.35026876 -0.8485972
[4,] -0.77638225 -0.9356755 0.01188311 -1.92292595 -0.23338277 -1.7823984
[5,] 1.20588796 1.5908531 0.97943996 -1.24731510 -0.41975784 -1.7085037
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.6749369 1.41015135 0.0408921 -0.3269597 -0.04757602 1.5861483
[2,] 0.6273586 0.03202834 0.3174650 -0.2140668 -1.22520371 -1.7223650
[3,] 0.1431335 -0.26031800 -0.2856104 -0.6717921 -0.87805813 1.6349771
[4,] 0.4552341 -1.93145299 -0.2928319 1.0191478 -1.02976447 0.9833365
[5,] 1.3189063 -0.92041016 -1.6552851 0.9506784 0.44999579 1.1800728
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.2673881 0.8774706 0.5302031 -0.94671302 -0.36054215 -1.7552076
[2,] -0.3379212 0.9719708 0.9024353 0.01617212 0.68176858 0.6083644
[3,] 0.5466150 1.3301383 0.2971936 1.00240999 -0.53984558 -0.2831591
[4,] -1.5166823 -0.3119383 -1.0083642 0.63598315 -0.01971958 0.9986639
[5,] -0.5055450 0.7502604 0.4087373 0.29306668 0.39904502 -1.4816976
[,19] [,20]
[1,] 0.22988497 1.3619017
[2,] 0.48693957 -0.1971791
[3,] 2.52731419 -0.1591295
[4,] 0.05895465 1.2091656
[5,] -0.88827425 1.1641155
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 650 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 562 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.1168581 1.534165 -0.4436884 -0.8551882 0.761899 0.2561965 1.375703
col8 col9 col10 col11 col12 col13 col14
row1 -0.7229257 -1.199653 -0.3604445 0.5050631 1.143332 -0.5335073 1.405059
col15 col16 col17 col18 col19 col20
row1 -0.6243758 -0.5342599 0.1964512 0.1975296 -0.2818713 0.4013881
> tmp[,"col10"]
col10
row1 -0.3604445
row2 2.5746819
row3 2.0893137
row4 2.1415729
row5 0.6191741
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.1168580824 1.53416468 -0.4436884 -0.8551882 0.7618990 0.2561965
row5 0.0006804365 0.01341857 1.0101328 2.9471303 -0.2482989 1.0303909
col7 col8 col9 col10 col11 col12 col13
row1 1.375703 -0.7229257 -1.1996530 -0.3604445 0.5050631 1.14333179 -0.5335073
row5 1.287305 -0.7019369 -0.8661621 0.6191741 1.4716842 -0.04806531 -0.1005679
col14 col15 col16 col17 col18 col19
row1 1.4050594 -0.6243758 -0.5342599 0.1964512 0.1975296 -0.2818713
row5 -0.9902784 0.4579765 -1.5154540 0.3235907 -1.6547154 -0.2507029
col20
row1 0.4013881
row5 -1.2356256
> tmp[,c("col6","col20")]
col6 col20
row1 0.2561965 0.4013881
row2 0.9648670 1.5605927
row3 0.4217514 -0.3138880
row4 -0.3633685 1.0160449
row5 1.0303909 -1.2356256
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.2561965 0.4013881
row5 1.0303909 -1.2356256
>
>
>
>
> 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 50.8164 49.95344 50.99862 48.57236 48.25725 104.7881 51.41038 49.37432
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.14472 49.56847 50.11706 50.28898 51.40333 51.62987 49.39677 51.38787
col17 col18 col19 col20
row1 50.96849 49.92687 50.28055 104.5472
> tmp[,"col10"]
col10
row1 49.56847
row2 30.14514
row3 30.47333
row4 29.24514
row5 49.15493
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.81640 49.95344 50.99862 48.57236 48.25725 104.7881 51.41038 49.37432
row5 49.28828 50.82742 49.34042 50.92492 49.33397 104.6066 51.29427 49.12701
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.14472 49.56847 50.11706 50.28898 51.40333 51.62987 49.39677 51.38787
row5 50.70462 49.15493 48.77353 49.79443 49.63932 49.23583 48.94464 48.63634
col17 col18 col19 col20
row1 50.96849 49.92687 50.28055 104.5472
row5 50.27827 49.61001 48.40138 104.4145
> tmp[,c("col6","col20")]
col6 col20
row1 104.78814 104.54722
row2 76.18339 73.94346
row3 73.36284 75.25167
row4 74.82751 76.01625
row5 104.60663 104.41446
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.7881 104.5472
row5 104.6066 104.4145
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.7881 104.5472
row5 104.6066 104.4145
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.4369035
[2,] 1.4476557
[3,] 0.5279273
[4,] -1.1109313
[5,] -0.5879859
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.4310329 1.58558529
[2,] -0.3142935 0.45086275
[3,] 0.3325681 0.06576871
[4,] -0.2962726 0.78074905
[5,] 1.5101874 -1.14214687
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.5349800 1.6436890
[2,] -1.5077962 -1.4715394
[3,] -0.4548141 0.5191896
[4,] -1.1822483 1.5472271
[5,] 0.3860064 -0.5251790
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.53498
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.534980
[2,] -1.507796
>
>
>
> 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 0.625442 -0.9174870 -0.7505062 0.2055999 -1.3129445 0.05313658
row1 1.233681 0.5197006 -0.5550617 -2.1408476 0.9976377 -0.31405108
[,7] [,8] [,9] [,10] [,11] [,12]
row3 0.7529534 -1.0703478 -0.35978690 -0.5006007 -0.7956781 -1.4997980
row1 -0.4365777 0.3300418 -0.03166908 1.0568507 -1.0252810 0.4070373
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 1.321630 -0.8106829 -2.554573 0.9250869 -0.6837359 0.69985361 -0.4624659
row1 2.835762 -1.5532583 -0.420711 -0.4040840 -1.5776011 -0.03947103 0.2761008
[,20]
row3 -1.20826185
row1 -0.01130237
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.540872 -0.4944898 1.841052 -0.7303397 -1.073393 0.4947813 0.3040073
[,8] [,9] [,10]
row2 -0.6315118 0.5247559 -1.514235
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.3784749 -0.2000407 -0.4929685 -0.2343863 -0.7200941 -0.3640275 0.897577
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.4264377 -1.695445 -0.03844919 -1.083538 2.171363 -1.595188 -0.06391628
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.6400225 -1.133952 -0.09329098 -0.5545595 0.9490479 -0.9135591
>
>
> 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: 0x600002e703c0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM69a24255cd35"
[2] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM69a2f137499"
[3] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM69a2464bf08a"
[4] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM69a2239d1814"
[5] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM69a21e97db50"
[6] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM69a23bf70e1"
[7] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM69a2d8bc5b3"
[8] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM69a2536071b7"
[9] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM69a260c9d024"
[10] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM69a261801d20"
[11] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM69a221f851e2"
[12] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM69a235c7ddda"
[13] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM69a254b62ecb"
[14] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM69a24ba3ce0"
[15] "/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests/BM69a25ef2988c"
>
>
> ### 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: 0x600002e71020>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600002e71020>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600002e71020>
> rowMedians(tmp)
[1] 0.026538336 -0.146476355 0.646422065 -0.175083172 -0.241485607
[6] -0.554325295 -0.223334559 -0.009885494 0.065513422 -0.625697374
[11] -0.232727470 0.126934677 0.570909454 0.148698201 0.183594945
[16] 0.071569822 -0.111878771 -0.179904905 -0.514052415 -0.112576776
[21] -0.240681699 -0.003960349 0.280694987 -0.178578781 0.110625352
[26] 0.023154168 0.247024809 0.181943265 0.091030092 0.067048536
[31] -0.194835667 -0.277041978 -0.111031117 0.126943857 -0.343221077
[36] 0.240342813 0.514804696 -0.555152054 0.540439358 0.181393273
[41] -0.395258436 -0.107715182 -0.030970796 0.087096352 0.156274652
[46] 0.264255515 -0.191698121 0.596411126 0.031351100 -0.207433142
[51] -0.384770889 0.617279285 -0.011851503 -0.043883022 0.352639325
[56] 0.263594121 0.167955717 -0.301264078 0.064513695 0.079235327
[61] -0.389132768 -0.221850986 0.225195549 0.087740840 0.308073039
[66] -0.433439586 -0.415046649 -0.347779412 -0.163267318 -0.338680863
[71] 0.787955130 0.056764925 0.139270679 -0.076294153 0.343723486
[76] 0.203895614 0.273713429 0.124283902 0.489585361 -0.157255303
[81] -0.323618145 0.340146114 -0.145842665 0.164926593 0.015114481
[86] 0.140399749 -0.028716621 -0.018788251 -0.132565215 -0.283979542
[91] -0.261326182 -0.013920192 0.169123706 0.108363365 -0.352153458
[96] 0.186041914 -0.066785054 -0.192052535 -0.254531936 -0.232040132
[101] -0.339457511 -0.094188732 -0.125185916 0.405690524 0.450460241
[106] 0.020402363 0.073397506 0.007511148 0.357723988 0.074157736
[111] -0.826116393 -0.498744325 0.391015422 0.121852261 -0.431902563
[116] -0.190815379 0.624272794 0.194143586 -0.182440378 -0.315722055
[121] -0.478033453 -0.427435558 0.443506021 0.045351664 -0.049624893
[126] 0.043721787 -0.405667192 0.118082391 1.126975588 -0.062302232
[131] -0.380265208 -0.266911096 -0.550244607 0.378872704 0.129998729
[136] 0.348131784 -0.119190876 0.407233185 0.239546590 0.021233960
[141] -0.064716415 0.278975384 -0.092739643 -0.228608108 -0.326571071
[146] 0.624995039 -0.422606976 0.132349527 0.137675905 0.034079744
[151] 0.412937316 -0.195275112 0.068146860 -0.253315217 -0.040977549
[156] -0.565514037 -0.844216023 0.221935712 0.041773170 -0.192722724
[161] 0.484454857 -0.356154577 -0.521999850 -0.353594759 -0.340821321
[166] 0.095372418 0.549251784 -0.169791398 -0.422042532 0.067773311
[171] 0.231169564 -0.210774889 0.521913983 0.396094447 0.385328124
[176] 0.320364205 -0.511729955 -0.108444947 0.090766250 -0.051476824
[181] 0.391487189 0.567742190 -0.227590500 0.010691551 0.811496391
[186] -0.389480459 -0.664701117 0.379752451 0.256661276 0.150578427
[191] 0.248540132 0.185025264 -0.077415436 0.332148124 -0.177394385
[196] 0.370979412 0.280672100 -0.520665516 -0.239288538 0.275248254
[201] 0.413771410 -0.019071015 -0.536220254 -0.217413106 -0.139553175
[206] -0.535785910 0.007300946 0.469391464 0.004176833 -0.022530587
[211] -0.101975568 -0.190660432 -0.046476411 -0.252935613 0.370798117
[216] -0.267528862 -0.185818850 -0.198803094 0.187253611 0.181776661
[221] 0.169930359 0.397429852 0.274220290 -0.557175313 -0.217070726
[226] -0.465028365 -0.325208267 0.154963381 -0.075061128 0.554396821
>
> proc.time()
user system elapsed
1.748 7.034 8.961
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
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: 0x6000028908a0>
> .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: 0x6000028908a0>
> .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: 0x6000028908a0>
> .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: 0x6000028908a0>
> 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: 0x60000288c2a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000288c2a0>
> .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: 0x60000288c2a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000288c2a0>
> .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: 0x60000288c2a0>
> 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: 0x60000288c480>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000288c480>
> .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: 0x60000288c480>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x60000288c480>
> .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: 0x60000288c480>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x60000288c480>
> .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: 0x60000288c480>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x60000288c480>
> .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: 0x60000288c480>
> 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: 0x60000288c660>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x60000288c660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000288c660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000288c660>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile69e26e96c496" "BufferedMatrixFile69e2bc9d07d"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile69e26e96c496" "BufferedMatrixFile69e2bc9d07d"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000288c900>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000288c900>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x60000288c900>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x60000288c900>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x60000288c900>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x60000288c900>
> .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: 0x600002890c60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002890c60>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600002890c60>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600002890c60>
> 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: 0x600002890e40>
> .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: 0x600002890e40>
> rm(P)
>
> proc.time()
user system elapsed
0.350 0.107 0.444
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
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
0.238 0.061 0.290