Ben Bolstad
| Snapshot Date: 2025-03-16 13:40 -0400 (Sun, 16 Mar 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 824836d |
| git_last_commit_date: 2024-12-14 17:47:34 -0400 (Sat, 14 Dec 2024) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-03-17 11:39 -0400 (Mon, 17 Mar 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| palomino7 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2025-03-01 r87860 ucrt) -- "Unsuffered Consequences" | 4545 |
| lconway | macOS 12.7.1 Monterey | x86_64 | R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences" | 4576 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences" | 4528 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4459 |
| 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 249/2313 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.71.1 (landing page) Ben Bolstad
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | |||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.1 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| kunpeng2 | 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: 1.71.1 |
| 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_1.71.1.tar.gz |
| StartedAt: 2025-03-16 18:26:28 -0400 (Sun, 16 Mar 2025) |
| EndedAt: 2025-03-16 18:26:45 -0400 (Sun, 16 Mar 2025) |
| EllapsedTime: 17.2 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.71.1.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2025-03-02 r87868)
* using platform: aarch64-apple-darwin20
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 14.2.0
* 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 ‘1.71.1’
* 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-3.21-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
* 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-3.21-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/4.5-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.71.1’
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
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/4.5-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 Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences"
Copyright (C) 2025 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
0.111 0.041 0.148
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences"
Copyright (C) 2025 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-3.21-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 480271 25.7 1055041 56.4 NA 634322 33.9
Vcells 890108 6.8 8388608 64.0 196608 2109036 16.1
>
>
>
>
> ##
> ## 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] "Sun Mar 16 18:26:38 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] "Sun Mar 16 18:26:38 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: 0x6000011c4000>
>
>
>
> 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] "Sun Mar 16 18:26:39 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] "Sun Mar 16 18:26:39 2025"
>
> ColMode(tmp2)
<pointer: 0x6000011c4000>
>
>
>
> ### 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,] 100.9578583 -1.2843778 0.0900955 0.9091096
[2,] -1.6977468 1.0134237 0.4596458 -0.6832384
[3,] 0.7192806 0.6496045 1.0980168 0.6055721
[4,] -0.7877016 1.7160507 -1.5645345 -2.1669722
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-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,] 100.9578583 1.2843778 0.0900955 0.9091096
[2,] 1.6977468 1.0134237 0.4596458 0.6832384
[3,] 0.7192806 0.6496045 1.0980168 0.6055721
[4,] 0.7877016 1.7160507 1.5645345 2.1669722
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-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,] 10.0477788 1.1333039 0.3001591 0.9534724
[2,] 1.3029761 1.0066895 0.6779719 0.8265824
[3,] 0.8481041 0.8059805 1.0478629 0.7781851
[4,] 0.8875256 1.3099812 1.2508135 1.4720639
>
> 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-3.21-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,] 226.43565 37.61742 28.09169 35.44383
[2,] 39.72751 36.08032 32.23936 33.94906
[3,] 34.20032 33.70941 36.57665 33.38742
[4,] 34.66296 39.81586 39.07267 41.88761
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000011c0000>
> exp(tmp5)
<pointer: 0x6000011c0000>
> log(tmp5,2)
<pointer: 0x6000011c0000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.2961
> Min(tmp5)
[1] 54.20809
> mean(tmp5)
[1] 73.19068
> Sum(tmp5)
[1] 14638.14
> Var(tmp5)
[1] 876.0149
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.65376 69.60237 71.60517 72.49224 70.59563 68.17145 71.08255 73.83562
[9] 74.71920 70.14878
> rowSums(tmp5)
[1] 1793.075 1392.047 1432.103 1449.845 1411.913 1363.429 1421.651 1476.712
[9] 1494.384 1402.976
> rowVars(tmp5)
[1] 8174.27892 51.39181 63.77048 60.03013 141.16993 34.20816
[7] 85.62899 89.04451 52.80683 69.83917
> rowSd(tmp5)
[1] 90.411719 7.168808 7.985642 7.747912 11.881495 5.848774 9.253593
[8] 9.436340 7.266831 8.356984
> rowMax(tmp5)
[1] 471.29613 82.68760 85.11581 87.18358 93.95197 80.56191 97.57058
[8] 89.98598 90.10024 90.91486
> rowMin(tmp5)
[1] 54.20809 56.06956 55.44218 59.74766 54.95726 59.74499 56.50711 57.14161
[9] 61.67974 55.72254
>
> colMeans(tmp5)
[1] 113.92438 73.31902 71.45273 76.14903 71.36569 71.44658 68.65295
[8] 67.02441 70.04925 70.84614 69.28732 73.67539 74.06717 74.19344
[15] 72.20746 68.31159 66.22624 70.80276 69.00125 71.81076
> colSums(tmp5)
[1] 1139.2438 733.1902 714.5273 761.4903 713.6569 714.4658 686.5295
[8] 670.2441 700.4925 708.4614 692.8732 736.7539 740.6717 741.9344
[15] 722.0746 683.1159 662.2624 708.0276 690.0125 718.1076
> colVars(tmp5)
[1] 15801.59536 114.76103 138.35208 46.18028 47.65026 115.32240
[7] 42.27079 57.83182 41.51487 127.30045 60.19828 120.25919
[13] 72.68514 60.89496 87.73003 28.01661 73.97779 97.29193
[19] 86.64157 74.68334
> colSd(tmp5)
[1] 125.704397 10.712658 11.762316 6.795607 6.902917 10.738827
[7] 6.501599 7.604724 6.443204 11.282750 7.758755 10.966275
[13] 8.525558 7.803523 9.366431 5.293072 8.601034 9.863667
[19] 9.308146 8.641952
> colMax(tmp5)
[1] 471.29613 90.91486 90.10024 87.18358 82.89313 92.27725 78.97651
[8] 77.48095 77.05778 85.11581 82.09797 97.57058 93.95197 89.98598
[15] 85.18103 74.86559 79.58674 83.41484 84.92884 84.98487
> colMin(tmp5)
[1] 65.91637 56.50711 57.09893 67.58848 58.58504 58.23324 56.13525 58.08617
[9] 55.44218 54.20809 57.93562 59.74766 65.95368 63.11101 60.99079 57.15758
[17] 54.95726 57.29043 55.72254 59.20860
>
>
> ### 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] 89.65376 69.60237 71.60517 72.49224 NA 68.17145 71.08255 73.83562
[9] 74.71920 70.14878
> rowSums(tmp5)
[1] 1793.075 1392.047 1432.103 1449.845 NA 1363.429 1421.651 1476.712
[9] 1494.384 1402.976
> rowVars(tmp5)
[1] 8174.27892 51.39181 63.77048 60.03013 136.57213 34.20816
[7] 85.62899 89.04451 52.80683 69.83917
> rowSd(tmp5)
[1] 90.411719 7.168808 7.985642 7.747912 11.686408 5.848774 9.253593
[8] 9.436340 7.266831 8.356984
> rowMax(tmp5)
[1] 471.29613 82.68760 85.11581 87.18358 NA 80.56191 97.57058
[8] 89.98598 90.10024 90.91486
> rowMin(tmp5)
[1] 54.20809 56.06956 55.44218 59.74766 NA 59.74499 56.50711 57.14161
[9] 61.67974 55.72254
>
> colMeans(tmp5)
[1] 113.92438 73.31902 71.45273 76.14903 71.36569 71.44658 68.65295
[8] 67.02441 70.04925 70.84614 69.28732 73.67539 74.06717 74.19344
[15] NA 68.31159 66.22624 70.80276 69.00125 71.81076
> colSums(tmp5)
[1] 1139.2438 733.1902 714.5273 761.4903 713.6569 714.4658 686.5295
[8] 670.2441 700.4925 708.4614 692.8732 736.7539 740.6717 741.9344
[15] NA 683.1159 662.2624 708.0276 690.0125 718.1076
> colVars(tmp5)
[1] 15801.59536 114.76103 138.35208 46.18028 47.65026 115.32240
[7] 42.27079 57.83182 41.51487 127.30045 60.19828 120.25919
[13] 72.68514 60.89496 NA 28.01661 73.97779 97.29193
[19] 86.64157 74.68334
> colSd(tmp5)
[1] 125.704397 10.712658 11.762316 6.795607 6.902917 10.738827
[7] 6.501599 7.604724 6.443204 11.282750 7.758755 10.966275
[13] 8.525558 7.803523 NA 5.293072 8.601034 9.863667
[19] 9.308146 8.641952
> colMax(tmp5)
[1] 471.29613 90.91486 90.10024 87.18358 82.89313 92.27725 78.97651
[8] 77.48095 77.05778 85.11581 82.09797 97.57058 93.95197 89.98598
[15] NA 74.86559 79.58674 83.41484 84.92884 84.98487
> colMin(tmp5)
[1] 65.91637 56.50711 57.09893 67.58848 58.58504 58.23324 56.13525 58.08617
[9] 55.44218 54.20809 57.93562 59.74766 65.95368 63.11101 NA 57.15758
[17] 54.95726 57.29043 55.72254 59.20860
>
> Max(tmp5,na.rm=TRUE)
[1] 471.2961
> Min(tmp5,na.rm=TRUE)
[1] 54.20809
> mean(tmp5,na.rm=TRUE)
[1] 73.13042
> Sum(tmp5,na.rm=TRUE)
[1] 14552.95
> Var(tmp5,na.rm=TRUE)
[1] 879.7094
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.65376 69.60237 71.60517 72.49224 69.82798 68.17145 71.08255 73.83562
[9] 74.71920 70.14878
> rowSums(tmp5,na.rm=TRUE)
[1] 1793.075 1392.047 1432.103 1449.845 1326.732 1363.429 1421.651 1476.712
[9] 1494.384 1402.976
> rowVars(tmp5,na.rm=TRUE)
[1] 8174.27892 51.39181 63.77048 60.03013 136.57213 34.20816
[7] 85.62899 89.04451 52.80683 69.83917
> rowSd(tmp5,na.rm=TRUE)
[1] 90.411719 7.168808 7.985642 7.747912 11.686408 5.848774 9.253593
[8] 9.436340 7.266831 8.356984
> rowMax(tmp5,na.rm=TRUE)
[1] 471.29613 82.68760 85.11581 87.18358 93.95197 80.56191 97.57058
[8] 89.98598 90.10024 90.91486
> rowMin(tmp5,na.rm=TRUE)
[1] 54.20809 56.06956 55.44218 59.74766 54.95726 59.74499 56.50711 57.14161
[9] 61.67974 55.72254
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.92438 73.31902 71.45273 76.14903 71.36569 71.44658 68.65295
[8] 67.02441 70.04925 70.84614 69.28732 73.67539 74.06717 74.19344
[15] 70.76595 68.31159 66.22624 70.80276 69.00125 71.81076
> colSums(tmp5,na.rm=TRUE)
[1] 1139.2438 733.1902 714.5273 761.4903 713.6569 714.4658 686.5295
[8] 670.2441 700.4925 708.4614 692.8732 736.7539 740.6717 741.9344
[15] 636.8935 683.1159 662.2624 708.0276 690.0125 718.1076
> colVars(tmp5,na.rm=TRUE)
[1] 15801.59536 114.76103 138.35208 46.18028 47.65026 115.32240
[7] 42.27079 57.83182 41.51487 127.30045 60.19828 120.25919
[13] 72.68514 60.89496 75.31940 28.01661 73.97779 97.29193
[19] 86.64157 74.68334
> colSd(tmp5,na.rm=TRUE)
[1] 125.704397 10.712658 11.762316 6.795607 6.902917 10.738827
[7] 6.501599 7.604724 6.443204 11.282750 7.758755 10.966275
[13] 8.525558 7.803523 8.678675 5.293072 8.601034 9.863667
[19] 9.308146 8.641952
> colMax(tmp5,na.rm=TRUE)
[1] 471.29613 90.91486 90.10024 87.18358 82.89313 92.27725 78.97651
[8] 77.48095 77.05778 85.11581 82.09797 97.57058 93.95197 89.98598
[15] 84.62495 74.86559 79.58674 83.41484 84.92884 84.98487
> colMin(tmp5,na.rm=TRUE)
[1] 65.91637 56.50711 57.09893 67.58848 58.58504 58.23324 56.13525 58.08617
[9] 55.44218 54.20809 57.93562 59.74766 65.95368 63.11101 60.99079 57.15758
[17] 54.95726 57.29043 55.72254 59.20860
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.65376 69.60237 71.60517 72.49224 NaN 68.17145 71.08255 73.83562
[9] 74.71920 70.14878
> rowSums(tmp5,na.rm=TRUE)
[1] 1793.075 1392.047 1432.103 1449.845 0.000 1363.429 1421.651 1476.712
[9] 1494.384 1402.976
> rowVars(tmp5,na.rm=TRUE)
[1] 8174.27892 51.39181 63.77048 60.03013 NA 34.20816
[7] 85.62899 89.04451 52.80683 69.83917
> rowSd(tmp5,na.rm=TRUE)
[1] 90.411719 7.168808 7.985642 7.747912 NA 5.848774 9.253593
[8] 9.436340 7.266831 8.356984
> rowMax(tmp5,na.rm=TRUE)
[1] 471.29613 82.68760 85.11581 87.18358 NA 80.56191 97.57058
[8] 89.98598 90.10024 90.91486
> rowMin(tmp5,na.rm=TRUE)
[1] 54.20809 56.06956 55.44218 59.74766 NA 59.74499 56.50711 57.14161
[9] 61.67974 55.72254
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 119.25860 74.70382 70.29287 75.22872 72.78576 69.74733 68.92586
[8] 65.86257 70.06839 71.89948 67.86392 74.56281 71.85774 75.42482
[15] NaN 69.55092 67.47835 72.02698 68.06441 73.21100
> colSums(tmp5,na.rm=TRUE)
[1] 1073.3274 672.3344 632.6358 677.0585 655.0718 627.7260 620.3328
[8] 592.7631 630.6155 647.0954 610.7753 671.0653 646.7197 678.8233
[15] 0.0000 625.9583 607.3051 648.2429 612.5797 658.8990
> colVars(tmp5,na.rm=TRUE)
[1] 17456.68798 107.53245 140.51167 42.42436 30.91976 97.25379
[7] 46.71670 49.87480 46.70011 130.73071 44.92964 126.43196
[13] 26.85336 51.44848 NA 14.23927 65.58753 92.59270
[19] 87.59800 61.96120
> colSd(tmp5,na.rm=TRUE)
[1] 132.123760 10.369785 11.853762 6.513399 5.560554 9.861733
[7] 6.834961 7.062209 6.833748 11.433753 6.702958 11.244197
[13] 5.182023 7.172760 NA 3.773495 8.098613 9.622510
[19] 9.359381 7.871544
> colMax(tmp5,na.rm=TRUE)
[1] 471.29613 90.91486 90.10024 87.18358 82.89313 92.27725 78.97651
[8] 77.36040 77.05778 85.11581 78.50810 97.57058 81.16587 89.98598
[15] -Inf 74.86559 79.58674 83.41484 84.92884 84.98487
> colMin(tmp5,na.rm=TRUE)
[1] 69.67365 56.50711 57.09893 67.58848 66.45843 58.23324 56.13525 58.08617
[9] 55.44218 54.20809 57.93562 59.74766 65.95368 65.37059 Inf 63.81158
[17] 59.30055 57.29043 55.72254 59.74499
>
>
>
>
> 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] 254.4538 385.1740 170.0564 168.1752 262.3748 149.5780 387.1602 158.4448
[9] 109.2809 244.6575
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 254.4538 385.1740 170.0564 168.1752 262.3748 149.5780 387.1602 158.4448
[9] 109.2809 244.6575
>
>
>
> 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] 4.263256e-14 1.136868e-13 5.684342e-14 0.000000e+00 0.000000e+00
[6] 0.000000e+00 0.000000e+00 -5.684342e-14 -1.705303e-13 -5.684342e-14
[11] 1.136868e-13 -2.842171e-14 5.684342e-14 1.705303e-13 2.273737e-13
[16] 0.000000e+00 2.842171e-13 5.684342e-14 0.000000e+00 -2.842171e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
1 19
10 14
8 17
8 4
8 20
1 11
9 17
7 9
5 12
4 8
2 2
5 4
6 7
8 14
3 17
2 11
5 16
10 20
7 8
7 9
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] 2.192359
> Min(tmp)
[1] -2.091027
> mean(tmp)
[1] -0.03759271
> Sum(tmp)
[1] -3.759271
> Var(tmp)
[1] 0.8916395
>
> rowMeans(tmp)
[1] -0.03759271
> rowSums(tmp)
[1] -3.759271
> rowVars(tmp)
[1] 0.8916395
> rowSd(tmp)
[1] 0.9442666
> rowMax(tmp)
[1] 2.192359
> rowMin(tmp)
[1] -2.091027
>
> colMeans(tmp)
[1] -0.412440004 -0.246282262 -0.680963307 1.176745776 -0.775457513
[6] -1.049595857 0.750360140 -0.973207910 -0.087846573 0.988829160
[11] -0.166588072 0.667114146 0.995690213 0.004791148 -0.634900673
[16] 1.328905605 1.305764620 -0.467727825 -0.305707863 -1.434934767
[21] 1.215105990 -0.673478167 -0.031590157 0.951860211 0.410747581
[26] 0.989296609 1.030140210 0.367441738 -1.619055041 -0.605444129
[31] -0.339518037 -0.487935437 0.691696222 1.058446734 -0.777706447
[36] 0.488032846 1.315696264 0.163985572 0.288745522 -1.424835035
[41] -0.140798521 -0.827973552 -0.397315622 0.187559307 -1.823297885
[46] 1.718010906 -0.402643998 -1.688547579 0.016173691 -0.819519695
[51] -0.180020397 1.009843484 2.192358904 0.050488493 1.155435474
[56] 0.424424570 -0.014557221 -0.012893764 0.628845075 -1.234195578
[61] -0.739853820 -0.661470234 1.010654187 1.557224550 -1.043326733
[66] 1.161819806 -2.091026636 1.119644509 -0.678412095 -0.860765930
[71] 0.454652836 -0.641276582 1.268722014 0.452445156 -1.702276142
[76] -1.106935327 0.397345599 -0.344036382 0.366606285 0.476177827
[81] -0.723492900 -0.579819313 1.691471314 0.191889731 1.290829832
[86] -1.862261370 -0.523548769 0.069687564 1.378605409 -1.577913740
[91] -1.492519714 -0.616078236 0.190561209 -0.034633757 -0.749649597
[96] -0.354774502 -1.275607565 0.095376875 -0.127271177 0.018407730
> colSums(tmp)
[1] -0.412440004 -0.246282262 -0.680963307 1.176745776 -0.775457513
[6] -1.049595857 0.750360140 -0.973207910 -0.087846573 0.988829160
[11] -0.166588072 0.667114146 0.995690213 0.004791148 -0.634900673
[16] 1.328905605 1.305764620 -0.467727825 -0.305707863 -1.434934767
[21] 1.215105990 -0.673478167 -0.031590157 0.951860211 0.410747581
[26] 0.989296609 1.030140210 0.367441738 -1.619055041 -0.605444129
[31] -0.339518037 -0.487935437 0.691696222 1.058446734 -0.777706447
[36] 0.488032846 1.315696264 0.163985572 0.288745522 -1.424835035
[41] -0.140798521 -0.827973552 -0.397315622 0.187559307 -1.823297885
[46] 1.718010906 -0.402643998 -1.688547579 0.016173691 -0.819519695
[51] -0.180020397 1.009843484 2.192358904 0.050488493 1.155435474
[56] 0.424424570 -0.014557221 -0.012893764 0.628845075 -1.234195578
[61] -0.739853820 -0.661470234 1.010654187 1.557224550 -1.043326733
[66] 1.161819806 -2.091026636 1.119644509 -0.678412095 -0.860765930
[71] 0.454652836 -0.641276582 1.268722014 0.452445156 -1.702276142
[76] -1.106935327 0.397345599 -0.344036382 0.366606285 0.476177827
[81] -0.723492900 -0.579819313 1.691471314 0.191889731 1.290829832
[86] -1.862261370 -0.523548769 0.069687564 1.378605409 -1.577913740
[91] -1.492519714 -0.616078236 0.190561209 -0.034633757 -0.749649597
[96] -0.354774502 -1.275607565 0.095376875 -0.127271177 0.018407730
> 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] -0.412440004 -0.246282262 -0.680963307 1.176745776 -0.775457513
[6] -1.049595857 0.750360140 -0.973207910 -0.087846573 0.988829160
[11] -0.166588072 0.667114146 0.995690213 0.004791148 -0.634900673
[16] 1.328905605 1.305764620 -0.467727825 -0.305707863 -1.434934767
[21] 1.215105990 -0.673478167 -0.031590157 0.951860211 0.410747581
[26] 0.989296609 1.030140210 0.367441738 -1.619055041 -0.605444129
[31] -0.339518037 -0.487935437 0.691696222 1.058446734 -0.777706447
[36] 0.488032846 1.315696264 0.163985572 0.288745522 -1.424835035
[41] -0.140798521 -0.827973552 -0.397315622 0.187559307 -1.823297885
[46] 1.718010906 -0.402643998 -1.688547579 0.016173691 -0.819519695
[51] -0.180020397 1.009843484 2.192358904 0.050488493 1.155435474
[56] 0.424424570 -0.014557221 -0.012893764 0.628845075 -1.234195578
[61] -0.739853820 -0.661470234 1.010654187 1.557224550 -1.043326733
[66] 1.161819806 -2.091026636 1.119644509 -0.678412095 -0.860765930
[71] 0.454652836 -0.641276582 1.268722014 0.452445156 -1.702276142
[76] -1.106935327 0.397345599 -0.344036382 0.366606285 0.476177827
[81] -0.723492900 -0.579819313 1.691471314 0.191889731 1.290829832
[86] -1.862261370 -0.523548769 0.069687564 1.378605409 -1.577913740
[91] -1.492519714 -0.616078236 0.190561209 -0.034633757 -0.749649597
[96] -0.354774502 -1.275607565 0.095376875 -0.127271177 0.018407730
> colMin(tmp)
[1] -0.412440004 -0.246282262 -0.680963307 1.176745776 -0.775457513
[6] -1.049595857 0.750360140 -0.973207910 -0.087846573 0.988829160
[11] -0.166588072 0.667114146 0.995690213 0.004791148 -0.634900673
[16] 1.328905605 1.305764620 -0.467727825 -0.305707863 -1.434934767
[21] 1.215105990 -0.673478167 -0.031590157 0.951860211 0.410747581
[26] 0.989296609 1.030140210 0.367441738 -1.619055041 -0.605444129
[31] -0.339518037 -0.487935437 0.691696222 1.058446734 -0.777706447
[36] 0.488032846 1.315696264 0.163985572 0.288745522 -1.424835035
[41] -0.140798521 -0.827973552 -0.397315622 0.187559307 -1.823297885
[46] 1.718010906 -0.402643998 -1.688547579 0.016173691 -0.819519695
[51] -0.180020397 1.009843484 2.192358904 0.050488493 1.155435474
[56] 0.424424570 -0.014557221 -0.012893764 0.628845075 -1.234195578
[61] -0.739853820 -0.661470234 1.010654187 1.557224550 -1.043326733
[66] 1.161819806 -2.091026636 1.119644509 -0.678412095 -0.860765930
[71] 0.454652836 -0.641276582 1.268722014 0.452445156 -1.702276142
[76] -1.106935327 0.397345599 -0.344036382 0.366606285 0.476177827
[81] -0.723492900 -0.579819313 1.691471314 0.191889731 1.290829832
[86] -1.862261370 -0.523548769 0.069687564 1.378605409 -1.577913740
[91] -1.492519714 -0.616078236 0.190561209 -0.034633757 -0.749649597
[96] -0.354774502 -1.275607565 0.095376875 -0.127271177 0.018407730
> colMedians(tmp)
[1] -0.412440004 -0.246282262 -0.680963307 1.176745776 -0.775457513
[6] -1.049595857 0.750360140 -0.973207910 -0.087846573 0.988829160
[11] -0.166588072 0.667114146 0.995690213 0.004791148 -0.634900673
[16] 1.328905605 1.305764620 -0.467727825 -0.305707863 -1.434934767
[21] 1.215105990 -0.673478167 -0.031590157 0.951860211 0.410747581
[26] 0.989296609 1.030140210 0.367441738 -1.619055041 -0.605444129
[31] -0.339518037 -0.487935437 0.691696222 1.058446734 -0.777706447
[36] 0.488032846 1.315696264 0.163985572 0.288745522 -1.424835035
[41] -0.140798521 -0.827973552 -0.397315622 0.187559307 -1.823297885
[46] 1.718010906 -0.402643998 -1.688547579 0.016173691 -0.819519695
[51] -0.180020397 1.009843484 2.192358904 0.050488493 1.155435474
[56] 0.424424570 -0.014557221 -0.012893764 0.628845075 -1.234195578
[61] -0.739853820 -0.661470234 1.010654187 1.557224550 -1.043326733
[66] 1.161819806 -2.091026636 1.119644509 -0.678412095 -0.860765930
[71] 0.454652836 -0.641276582 1.268722014 0.452445156 -1.702276142
[76] -1.106935327 0.397345599 -0.344036382 0.366606285 0.476177827
[81] -0.723492900 -0.579819313 1.691471314 0.191889731 1.290829832
[86] -1.862261370 -0.523548769 0.069687564 1.378605409 -1.577913740
[91] -1.492519714 -0.616078236 0.190561209 -0.034633757 -0.749649597
[96] -0.354774502 -1.275607565 0.095376875 -0.127271177 0.018407730
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.41244 -0.2462823 -0.6809633 1.176746 -0.7754575 -1.049596 0.7503601
[2,] -0.41244 -0.2462823 -0.6809633 1.176746 -0.7754575 -1.049596 0.7503601
[,8] [,9] [,10] [,11] [,12] [,13]
[1,] -0.9732079 -0.08784657 0.9888292 -0.1665881 0.6671141 0.9956902
[2,] -0.9732079 -0.08784657 0.9888292 -0.1665881 0.6671141 0.9956902
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0.004791148 -0.6349007 1.328906 1.305765 -0.4677278 -0.3057079 -1.434935
[2,] 0.004791148 -0.6349007 1.328906 1.305765 -0.4677278 -0.3057079 -1.434935
[,21] [,22] [,23] [,24] [,25] [,26] [,27]
[1,] 1.215106 -0.6734782 -0.03159016 0.9518602 0.4107476 0.9892966 1.03014
[2,] 1.215106 -0.6734782 -0.03159016 0.9518602 0.4107476 0.9892966 1.03014
[,28] [,29] [,30] [,31] [,32] [,33] [,34]
[1,] 0.3674417 -1.619055 -0.6054441 -0.339518 -0.4879354 0.6916962 1.058447
[2,] 0.3674417 -1.619055 -0.6054441 -0.339518 -0.4879354 0.6916962 1.058447
[,35] [,36] [,37] [,38] [,39] [,40] [,41]
[1,] -0.7777064 0.4880328 1.315696 0.1639856 0.2887455 -1.424835 -0.1407985
[2,] -0.7777064 0.4880328 1.315696 0.1639856 0.2887455 -1.424835 -0.1407985
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] -0.8279736 -0.3973156 0.1875593 -1.823298 1.718011 -0.402644 -1.688548
[2,] -0.8279736 -0.3973156 0.1875593 -1.823298 1.718011 -0.402644 -1.688548
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] 0.01617369 -0.8195197 -0.1800204 1.009843 2.192359 0.05048849 1.155435
[2,] 0.01617369 -0.8195197 -0.1800204 1.009843 2.192359 0.05048849 1.155435
[,56] [,57] [,58] [,59] [,60] [,61]
[1,] 0.4244246 -0.01455722 -0.01289376 0.6288451 -1.234196 -0.7398538
[2,] 0.4244246 -0.01455722 -0.01289376 0.6288451 -1.234196 -0.7398538
[,62] [,63] [,64] [,65] [,66] [,67] [,68]
[1,] -0.6614702 1.010654 1.557225 -1.043327 1.16182 -2.091027 1.119645
[2,] -0.6614702 1.010654 1.557225 -1.043327 1.16182 -2.091027 1.119645
[,69] [,70] [,71] [,72] [,73] [,74] [,75]
[1,] -0.6784121 -0.8607659 0.4546528 -0.6412766 1.268722 0.4524452 -1.702276
[2,] -0.6784121 -0.8607659 0.4546528 -0.6412766 1.268722 0.4524452 -1.702276
[,76] [,77] [,78] [,79] [,80] [,81] [,82]
[1,] -1.106935 0.3973456 -0.3440364 0.3666063 0.4761778 -0.7234929 -0.5798193
[2,] -1.106935 0.3973456 -0.3440364 0.3666063 0.4761778 -0.7234929 -0.5798193
[,83] [,84] [,85] [,86] [,87] [,88] [,89]
[1,] 1.691471 0.1918897 1.29083 -1.862261 -0.5235488 0.06968756 1.378605
[2,] 1.691471 0.1918897 1.29083 -1.862261 -0.5235488 0.06968756 1.378605
[,90] [,91] [,92] [,93] [,94] [,95] [,96]
[1,] -1.577914 -1.49252 -0.6160782 0.1905612 -0.03463376 -0.7496496 -0.3547745
[2,] -1.577914 -1.49252 -0.6160782 0.1905612 -0.03463376 -0.7496496 -0.3547745
[,97] [,98] [,99] [,100]
[1,] -1.275608 0.09537687 -0.1272712 0.01840773
[2,] -1.275608 0.09537687 -0.1272712 0.01840773
>
>
> Max(tmp2)
[1] 2.351822
> Min(tmp2)
[1] -2.387472
> mean(tmp2)
[1] 0.0224396
> Sum(tmp2)
[1] 2.24396
> Var(tmp2)
[1] 0.8969815
>
> rowMeans(tmp2)
[1] 0.872098994 -0.821537060 -0.461319073 -0.439759105 0.686214177
[6] 2.351822141 1.012581601 -0.877943216 -0.609052785 0.049438231
[11] 0.133123666 1.914475935 0.020550039 -0.383139834 -0.602095162
[16] 1.681819790 -0.744693641 -0.454320657 0.947941429 1.192741957
[21] -0.562361964 -0.728637051 0.700478763 -0.499180688 -0.446730913
[26] -0.218057174 1.832041395 0.450448500 -0.350465414 0.997409509
[31] -0.012120179 0.838798587 -1.228987886 0.326200374 0.030540189
[36] -0.647842545 0.846898584 0.426154941 -1.588718033 -0.118078913
[41] -0.003235685 0.725457597 0.099546574 -1.731735418 0.462450274
[46] -1.388989978 0.534025455 -0.810344421 1.611995416 -0.012645703
[51] -0.405789186 -1.953053630 0.910512850 -0.147409592 1.359325571
[56] 0.349631755 -0.177165055 0.266623769 1.200729350 0.146348198
[61] 1.255829527 -0.074748003 0.250859615 0.831363140 0.314287335
[66] 0.524024806 -2.128130756 0.193199954 -1.160839585 0.989656917
[71] -0.686350448 0.888118410 -0.383542369 -2.387471906 1.147657875
[76] -0.836119927 1.579667271 0.742660340 1.345130895 -0.053884822
[81] -1.540738762 -0.816143043 -1.888123006 1.693726563 -1.051738334
[86] 0.001166260 0.217041849 -0.225535062 0.035565134 -0.389339828
[91] -0.131705843 -0.026775165 0.357648355 -0.114677902 0.971889293
[96] -0.638665878 -0.697882674 -0.547663928 -0.957215311 -0.911256952
> rowSums(tmp2)
[1] 0.872098994 -0.821537060 -0.461319073 -0.439759105 0.686214177
[6] 2.351822141 1.012581601 -0.877943216 -0.609052785 0.049438231
[11] 0.133123666 1.914475935 0.020550039 -0.383139834 -0.602095162
[16] 1.681819790 -0.744693641 -0.454320657 0.947941429 1.192741957
[21] -0.562361964 -0.728637051 0.700478763 -0.499180688 -0.446730913
[26] -0.218057174 1.832041395 0.450448500 -0.350465414 0.997409509
[31] -0.012120179 0.838798587 -1.228987886 0.326200374 0.030540189
[36] -0.647842545 0.846898584 0.426154941 -1.588718033 -0.118078913
[41] -0.003235685 0.725457597 0.099546574 -1.731735418 0.462450274
[46] -1.388989978 0.534025455 -0.810344421 1.611995416 -0.012645703
[51] -0.405789186 -1.953053630 0.910512850 -0.147409592 1.359325571
[56] 0.349631755 -0.177165055 0.266623769 1.200729350 0.146348198
[61] 1.255829527 -0.074748003 0.250859615 0.831363140 0.314287335
[66] 0.524024806 -2.128130756 0.193199954 -1.160839585 0.989656917
[71] -0.686350448 0.888118410 -0.383542369 -2.387471906 1.147657875
[76] -0.836119927 1.579667271 0.742660340 1.345130895 -0.053884822
[81] -1.540738762 -0.816143043 -1.888123006 1.693726563 -1.051738334
[86] 0.001166260 0.217041849 -0.225535062 0.035565134 -0.389339828
[91] -0.131705843 -0.026775165 0.357648355 -0.114677902 0.971889293
[96] -0.638665878 -0.697882674 -0.547663928 -0.957215311 -0.911256952
> 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] 0.872098994 -0.821537060 -0.461319073 -0.439759105 0.686214177
[6] 2.351822141 1.012581601 -0.877943216 -0.609052785 0.049438231
[11] 0.133123666 1.914475935 0.020550039 -0.383139834 -0.602095162
[16] 1.681819790 -0.744693641 -0.454320657 0.947941429 1.192741957
[21] -0.562361964 -0.728637051 0.700478763 -0.499180688 -0.446730913
[26] -0.218057174 1.832041395 0.450448500 -0.350465414 0.997409509
[31] -0.012120179 0.838798587 -1.228987886 0.326200374 0.030540189
[36] -0.647842545 0.846898584 0.426154941 -1.588718033 -0.118078913
[41] -0.003235685 0.725457597 0.099546574 -1.731735418 0.462450274
[46] -1.388989978 0.534025455 -0.810344421 1.611995416 -0.012645703
[51] -0.405789186 -1.953053630 0.910512850 -0.147409592 1.359325571
[56] 0.349631755 -0.177165055 0.266623769 1.200729350 0.146348198
[61] 1.255829527 -0.074748003 0.250859615 0.831363140 0.314287335
[66] 0.524024806 -2.128130756 0.193199954 -1.160839585 0.989656917
[71] -0.686350448 0.888118410 -0.383542369 -2.387471906 1.147657875
[76] -0.836119927 1.579667271 0.742660340 1.345130895 -0.053884822
[81] -1.540738762 -0.816143043 -1.888123006 1.693726563 -1.051738334
[86] 0.001166260 0.217041849 -0.225535062 0.035565134 -0.389339828
[91] -0.131705843 -0.026775165 0.357648355 -0.114677902 0.971889293
[96] -0.638665878 -0.697882674 -0.547663928 -0.957215311 -0.911256952
> rowMin(tmp2)
[1] 0.872098994 -0.821537060 -0.461319073 -0.439759105 0.686214177
[6] 2.351822141 1.012581601 -0.877943216 -0.609052785 0.049438231
[11] 0.133123666 1.914475935 0.020550039 -0.383139834 -0.602095162
[16] 1.681819790 -0.744693641 -0.454320657 0.947941429 1.192741957
[21] -0.562361964 -0.728637051 0.700478763 -0.499180688 -0.446730913
[26] -0.218057174 1.832041395 0.450448500 -0.350465414 0.997409509
[31] -0.012120179 0.838798587 -1.228987886 0.326200374 0.030540189
[36] -0.647842545 0.846898584 0.426154941 -1.588718033 -0.118078913
[41] -0.003235685 0.725457597 0.099546574 -1.731735418 0.462450274
[46] -1.388989978 0.534025455 -0.810344421 1.611995416 -0.012645703
[51] -0.405789186 -1.953053630 0.910512850 -0.147409592 1.359325571
[56] 0.349631755 -0.177165055 0.266623769 1.200729350 0.146348198
[61] 1.255829527 -0.074748003 0.250859615 0.831363140 0.314287335
[66] 0.524024806 -2.128130756 0.193199954 -1.160839585 0.989656917
[71] -0.686350448 0.888118410 -0.383542369 -2.387471906 1.147657875
[76] -0.836119927 1.579667271 0.742660340 1.345130895 -0.053884822
[81] -1.540738762 -0.816143043 -1.888123006 1.693726563 -1.051738334
[86] 0.001166260 0.217041849 -0.225535062 0.035565134 -0.389339828
[91] -0.131705843 -0.026775165 0.357648355 -0.114677902 0.971889293
[96] -0.638665878 -0.697882674 -0.547663928 -0.957215311 -0.911256952
>
> colMeans(tmp2)
[1] 0.0224396
> colSums(tmp2)
[1] 2.24396
> colVars(tmp2)
[1] 0.8969815
> colSd(tmp2)
[1] 0.9470911
> colMax(tmp2)
[1] 2.351822
> colMin(tmp2)
[1] -2.387472
> colMedians(tmp2)
[1] -0.007677932
> colRanges(tmp2)
[,1]
[1,] -2.387472
[2,] 2.351822
>
> 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] -2.6003090 2.5309132 -5.3682921 -1.4150207 4.1094588 0.9102203
[7] -2.3734795 4.8594262 -2.0581577 -1.0217426
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1464809
[2,] -0.7695897
[3,] -0.2791085
[4,] 0.1854990
[5,] 0.7618937
>
> rowApply(tmp,sum)
[1] -1.1676949 0.2606878 -4.3069375 3.3624182 -0.8663087 -3.3092213
[7] 2.0539623 0.4859533 -0.9161196 1.9762772
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 4 5 10 5 3 1 5 6 2 6
[2,] 8 9 8 4 7 7 1 10 9 4
[3,] 5 1 4 10 1 4 9 4 4 2
[4,] 6 10 1 1 5 8 4 9 3 3
[5,] 9 3 9 9 8 5 2 5 8 9
[6,] 3 6 2 7 9 6 10 2 5 10
[7,] 1 2 5 2 4 9 6 8 10 5
[8,] 10 8 7 3 6 10 3 7 7 7
[9,] 7 4 6 6 2 2 8 3 1 8
[10,] 2 7 3 8 10 3 7 1 6 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.63686144 -1.22703807 -0.92749515 1.00832254 -1.91934498 1.11166999
[7] -0.07551814 2.76129491 1.13526505 -0.28518916 5.65974902 3.38914204
[13] 2.00119796 -2.90430564 -1.37857134 2.33446139 -1.42610850 0.43503769
[19] -1.18222347 1.15561341
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5058304
[2,] -0.5537243
[3,] -0.2985445
[4,] -0.1956548
[5,] 0.9168926
>
> rowApply(tmp,sum)
[1] 2.062383 2.085829 -5.036359 2.078520 6.838726
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 4 8 18 3 6
[2,] 18 7 4 4 9
[3,] 1 9 8 11 15
[4,] 16 17 2 6 16
[5,] 12 3 13 2 12
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.5537243 1.176746719 -1.3664512 0.8682327 0.03528044 -0.1405869
[2,] -0.2985445 -0.473014617 -0.2978228 1.3834633 -1.11309895 1.4012303
[3,] 0.9168926 -1.192094555 -0.5802110 -2.1439357 -0.01946305 -0.2352079
[4,] -1.5058304 -0.747170731 0.2616495 -0.1679731 -1.51579081 -0.5827625
[5,] -0.1956548 0.008495116 1.0553403 1.0685354 0.69372738 0.6689969
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.24795565 1.0270920 0.5026929 1.4951368 1.4801562 0.1445225
[2,] -1.51821307 -0.1885751 -0.8239058 -1.0359307 1.8964945 2.2107339
[3,] 1.31539146 -0.6454809 -0.3389760 -2.1629565 0.6656896 0.5953446
[4,] 0.46363576 0.8003755 0.6842774 0.4659939 -0.1317760 0.2553849
[5,] -0.08837665 1.7678833 1.1111765 0.9525674 1.7491846 0.1831562
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.1463332 -0.6414246 -0.5101419 -0.43107114 0.8375045 -0.36238015
[2,] 0.9712352 0.7493856 -1.7930742 -0.04087074 -0.6624755 -0.08484913
[3,] -0.1856424 -0.6142913 0.6623525 0.99241723 -1.6199781 -0.70105170
[4,] 2.6154975 -1.7741505 0.7290242 0.70107118 0.1374500 0.56624988
[5,] -1.2535592 -0.6238249 -0.4667319 1.11291485 -0.1186093 1.01706878
[,19] [,20]
[1,] -1.1151974 0.01028474
[2,] 0.8103079 0.99335334
[3,] -0.3006629 0.55550491
[4,] -0.1340229 0.95738671
[5,] -0.4426482 -1.36091629
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-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-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 649 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-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-3.21-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 -0.4604991 -1.248786 -0.5178177 -1.276851 0.1780917 0.5129452 -1.620301
col8 col9 col10 col11 col12 col13 col14
row1 0.4101992 -0.6073337 -0.3094485 0.3365768 0.3043903 -0.06248499 1.877395
col15 col16 col17 col18 col19 col20
row1 -0.3664288 0.3302158 -0.6287118 1.515556 1.273757 -0.3666041
> tmp[,"col10"]
col10
row1 -0.3094485
row2 -1.3976914
row3 0.5155544
row4 0.5288460
row5 -0.4191572
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.4604991 -1.2487862 -0.5178177 -1.276851 0.1780917 0.5129452 -1.620301
row5 1.8664188 0.9584107 -0.7718082 1.251206 -0.7794445 0.2367778 -2.233968
col8 col9 col10 col11 col12 col13
row1 0.4101992 -0.6073337 -0.3094485 0.3365768 0.3043903 -0.06248499
row5 -1.0152785 0.7015303 -0.4191572 1.2685140 0.9454655 -1.09096607
col14 col15 col16 col17 col18 col19
row1 1.8773949 -0.3664288 0.3302158 -0.6287118 1.5155565 1.2737570
row5 -0.8783661 0.9383748 0.2469391 0.1524019 0.8329353 -0.5198323
col20
row1 -0.36660408
row5 -0.05753876
> tmp[,c("col6","col20")]
col6 col20
row1 0.5129452 -0.36660408
row2 0.4271091 1.92645938
row3 -1.5941717 1.11737628
row4 0.7569471 2.02430926
row5 0.2367778 -0.05753876
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.5129452 -0.36660408
row5 0.2367778 -0.05753876
>
>
>
>
> 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 49.57173 51.50194 50.72979 49.13074 51.36844 105.0607 50.12713 49.76975
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.03205 49.98324 50.23229 48.74013 51.99815 50.40187 49.26081 50.38243
col17 col18 col19 col20
row1 51.0409 49.51828 49.97054 105.7419
> tmp[,"col10"]
col10
row1 49.98324
row2 28.09336
row3 30.95104
row4 30.85955
row5 49.84851
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.57173 51.50194 50.72979 49.13074 51.36844 105.0607 50.12713 49.76975
row5 50.38722 50.32144 49.17699 49.79747 48.68727 105.5376 51.08525 49.03228
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.03205 49.98324 50.23229 48.74013 51.99815 50.40187 49.26081 50.38243
row5 48.72302 49.84851 50.94891 50.60311 50.87458 50.25106 49.41731 50.86717
col17 col18 col19 col20
row1 51.04090 49.51828 49.97054 105.7419
row5 50.81106 48.48186 48.63514 105.4614
> tmp[,c("col6","col20")]
col6 col20
row1 105.06066 105.74185
row2 75.02409 75.94511
row3 75.84379 74.75370
row4 74.39067 76.22020
row5 105.53760 105.46136
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.0607 105.7419
row5 105.5376 105.4614
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.0607 105.7419
row5 105.5376 105.4614
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.2036100
[2,] -0.4831599
[3,] -0.8623952
[4,] 1.5451152
[5,] 1.2557244
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.5904688 0.8847998
[2,] 0.2013838 0.1110622
[3,] -0.7722339 2.3120806
[4,] 0.3973044 0.1518357
[5,] 0.6937618 -0.9366233
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.2808279 0.9682893
[2,] -1.1065338 -1.5249796
[3,] 0.9911783 0.5589894
[4,] 1.8363649 1.5810691
[5,] 1.4798939 -1.6218598
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.2808279
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.2808279
[2,] -1.1065338
>
>
>
> 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 0.2537090 0.08618019 -0.3119902 0.4154712 0.08329386 -0.2671878
row1 0.6427571 0.16628341 0.7549231 -0.2424674 0.82514791 -1.3000766
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.8214937 -0.05079295 1.0270800 -0.8700395 -0.9923527 0.3153013
row1 -1.4684491 0.27800001 -0.6661987 -1.2428837 1.1482125 -1.2435246
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.8040854 -0.5096831 0.7413222 -0.8305697 0.7454832 -2.0596472 1.5345393
row1 -0.3059939 -0.9273286 0.8089935 -1.0766175 1.0218895 0.6779049 0.4407201
[,20]
row3 1.858272
row1 1.433495
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.941775 -0.4367697 1.512234 0.7473534 -1.555866 0.423518 -0.8481515
[,8] [,9] [,10]
row2 -1.032215 -0.6427955 0.04265501
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.06154212 1.167638 0.3484968 1.699715 -1.147287 1.106283 -0.4996393
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.3978697 1.017604 0.6131531 1.440184 -2.779549 0.7069475 0.3865234
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.270247 -0.6415321 -0.781403 0.7555753 0.9592276 -1.682933
>
>
> 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: 0x6000011f80c0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM7cde63aaca73"
[2] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM7cde61d17723"
[3] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM7cde7ee4cd00"
[4] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM7cde5f4efc15"
[5] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM7cde3a87f795"
[6] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM7cde348f7538"
[7] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM7cde3658ca7d"
[8] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM7cde7f55f06a"
[9] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM7cde631b0075"
[10] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM7cde1bb3428"
[11] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM7cde295d2efb"
[12] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM7cde24b775f4"
[13] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM7cde8a0f901"
[14] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM7cde3bb514"
[15] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM7cde4fed342a"
>
>
> ### 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: 0x6000011e4420>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000011e4420>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6000011e4420>
> rowMedians(tmp)
[1] -0.2499183386 -0.1350138407 0.0507113795 -0.4042207923 0.0825521007
[6] 0.0209204707 0.8219259430 0.0925691400 0.1114912151 -0.1430201295
[11] 0.3485278965 0.0931202615 -0.3814940221 0.5079699900 -0.0946381085
[16] -0.3148447270 0.2098982880 -0.2183760952 0.3006756251 0.1475081024
[21] 0.3308979136 -0.4600746585 -0.3906742464 -0.0239675803 0.2643526211
[26] 0.1317859945 0.2103119028 -0.0411079030 -0.1984102780 0.1078244869
[31] -0.2518170240 0.0936231502 -0.3065461165 0.3568488062 0.3551010575
[36] 0.1259486055 -0.2638605307 0.2659052468 -0.7653352550 0.1212468928
[41] 0.3062285000 -0.1576047125 0.4485001601 0.0533077053 0.0528035169
[46] 0.5296368198 -0.1837199169 -0.2838636544 -0.0323891318 0.0816172999
[51] -0.0621805761 0.1549315420 -0.1038372609 0.3016874842 -0.1018866201
[56] 0.0015605641 -0.0159776270 1.0302162455 -0.0698691849 -0.1904050251
[61] 0.0299327933 0.2409278430 -0.0008711806 0.4072966478 0.1542470703
[66] -0.3324201832 -0.1363061846 0.0435422858 0.3929697769 -0.3839811405
[71] 0.0804957150 -0.5336478828 -0.2905942823 -0.1998382455 -0.3254733945
[76] -0.2853771152 0.5471047993 0.1941088614 0.2083174890 0.0143912259
[81] 0.3374907488 -0.5060073572 0.1253524498 0.1161133403 0.3039649328
[86] -0.2071904297 -0.0491320288 0.3747432656 -0.2252432870 -0.1458947089
[91] -0.0531516691 0.2180540623 -0.3392818926 0.2564584573 -0.4725295767
[96] -0.6204021136 -0.2603391274 -0.3909504826 0.0427864671 -0.0794787072
[101] 0.3416213142 0.1811605552 0.0519574020 -0.1508185707 -0.1837281046
[106] -0.1692580719 0.5042811040 0.2551015174 0.2356451107 -0.4180647754
[111] 0.0016271917 -0.6538927727 0.1857610475 0.0474921998 0.0435423228
[116] -0.0786928546 -0.0312255393 0.4014592621 -0.4221400827 -0.1590640859
[121] 0.4933093011 0.0728071592 0.1132914868 -0.0845187500 -0.0652679681
[126] 0.2246293557 0.0029795418 -0.1782221948 0.1162730919 -0.5524860598
[131] -0.0045013753 -0.3909926222 0.2838350037 0.5143353821 -0.2200241723
[136] 0.1573800575 0.1342842134 -1.1599202727 -0.4605998544 0.1238194948
[141] 0.4085896873 -0.1734106408 0.3816088471 -0.0330642447 -0.2983883750
[146] -0.3515616261 0.4877559541 -0.2701180963 0.0829927199 -0.3651784252
[151] 0.6887514966 0.1496459758 -0.0853898432 0.2130415153 -0.2507632826
[156] 0.3871520232 -0.5208489904 -0.3265350874 0.4798179946 0.0599354110
[161] -0.3843594655 -0.3247564891 -0.1231283686 0.2121359405 -0.4653763805
[166] 0.4617376946 -0.0369738814 -0.1085703186 0.5464073317 0.4278007633
[171] -0.3370065758 -0.0455956203 -0.2662665511 -0.2069481205 0.0417471588
[176] 0.2040315838 0.2209874916 -0.0374015381 0.5705958286 0.4019347197
[181] 0.2481860587 -0.4217286174 0.4974814605 0.1586764512 -0.1577077474
[186] 0.3868050577 0.4159159289 0.1448308313 -0.0422889426 -0.0389469686
[191] -0.2145186228 0.3428332217 0.2713837843 -0.1400351209 -0.1720205279
[196] -0.1070786870 0.9175123441 0.0176225528 0.8424551875 0.0174685014
[201] 0.0922589073 0.0368502950 -0.4307243428 -0.0737388319 0.0800620698
[206] 0.0530919794 -0.0064854173 -0.0266877711 -0.3640493996 -0.4680784241
[211] -0.3465778294 -0.0260212557 -0.4903609069 0.5040160495 0.1473310586
[216] 0.2345855854 0.0460994860 -0.3743425915 0.0428504670 -0.4206558482
[221] -0.2696142176 -0.2421263591 -0.1753712821 -0.2241880561 -0.1906060562
[226] 0.0766232216 -0.0207066112 0.2306718717 -0.0107985859 -0.2235883630
>
> proc.time()
user system elapsed
0.639 3.171 3.978
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences"
Copyright (C) 2025 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: 0x600003e98000>
> .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: 0x600003e98000>
> .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: 0x600003e98000>
> .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: 0x600003e98000>
> 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: 0x600003e953e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003e953e0>
> .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: 0x600003e953e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003e953e0>
> .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: 0x600003e953e0>
> 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: 0x600003e955c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003e955c0>
> .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: 0x600003e955c0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003e955c0>
> .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: 0x600003e955c0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600003e955c0>
> .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: 0x600003e955c0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600003e955c0>
> .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: 0x600003e955c0>
> 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: 0x600003e957a0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600003e957a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003e957a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003e957a0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile7d283e680f23" "BufferedMatrixFile7d28e7f292c"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile7d283e680f23" "BufferedMatrixFile7d28e7f292c"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003e9c240>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003e9c240>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003e9c240>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003e9c240>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600003e9c240>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600003e9c240>
> .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: 0x600003e9c420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003e9c420>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003e9c420>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600003e9c420>
> 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: 0x600003e9c600>
> .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: 0x600003e9c600>
> rm(P)
>
> proc.time()
user system elapsed
0.113 0.043 0.153
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences"
Copyright (C) 2025 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
0.112 0.032 0.136