| Back to Multiple platform build/check report for BioC 3.18: simplified long |
|
This page was generated on 2024-04-17 11:37:33 -0400 (Wed, 17 Apr 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.3.3 (2024-02-29) -- "Angel Food Cake" | 4676 |
| palomino4 | Windows Server 2022 Datacenter | x64 | 4.3.3 (2024-02-29 ucrt) -- "Angel Food Cake" | 4414 |
| merida1 | macOS 12.7.1 Monterey | x86_64 | 4.3.3 (2024-02-29) -- "Angel Food Cake" | 4437 |
| 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 246/2266 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.66.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK |  | ||||||||
| palomino4 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.1 Ventura / arm64 | see weekly results here | ||||||||||||
|
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: 1.66.0 |
| 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_1.66.0.tar.gz |
| StartedAt: 2024-04-16 00:11:03 -0400 (Tue, 16 Apr 2024) |
| EndedAt: 2024-04-16 00:12:17 -0400 (Tue, 16 Apr 2024) |
| EllapsedTime: 73.6 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_1.66.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.3.3 (2024-02-29)
* using platform: x86_64-apple-darwin20 (64-bit)
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.66.0’
* 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-3.18-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
* used SDK: ‘MacOSX11.3.sdk’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R 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
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 in ‘inst/doc’ ... 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-3.18-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/4.3-x86_64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
using SDK: ‘MacOSX11.3.sdk’
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch x86_64 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/x86_64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation
installing to /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)
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
0.583 0.202 0.779
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)
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-3.18-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 460384 24.6 992698 53.1 NA 645368 34.5
Vcells 848931 6.5 8388608 64.0 65536 2019930 15.5
>
>
>
>
> ##
> ## 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] "Tue Apr 16 00:11:38 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Apr 16 00:11:39 2024"
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
>
>
> RowMode(tmp2)
<pointer: 0x600003694180>
>
>
>
> 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] "Tue Apr 16 00:11:45 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Tue Apr 16 00:11:47 2024"
>
> ColMode(tmp2)
<pointer: 0x600003694180>
>
>
>
> ### 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,] 98.9729542 1.51349805 0.31234811 -0.2848055
[2,] -1.0790301 0.99524118 -0.91463592 0.5383451
[3,] -0.7964921 -0.86298765 0.09414639 1.7133622
[4,] 1.2998528 0.08051646 -0.19962358 2.0726390
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 98.9729542 1.51349805 0.31234811 0.2848055
[2,] 1.0790301 0.99524118 0.91463592 0.5383451
[3,] 0.7964921 0.86298765 0.09414639 1.7133622
[4,] 1.2998528 0.08051646 0.19962358 2.0726390
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.948515 1.2302431 0.5588811 0.5336717
[2,] 1.038764 0.9976178 0.9563660 0.7337200
[3,] 0.892464 0.9289713 0.3068328 1.3089546
[4,] 1.140111 0.2837542 0.4467925 1.4396663
>
> 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-3.18-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 223.45811 38.81593 30.90116 30.62152
[2,] 36.46667 35.97142 35.47830 32.87555
[3,] 34.72113 35.15270 28.16247 39.80291
[4,] 37.70096 27.91806 29.66755 41.46930
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000036b0000>
> exp(tmp5)
<pointer: 0x6000036b0000>
> log(tmp5,2)
<pointer: 0x6000036b0000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 465.0988
> Min(tmp5)
[1] 53.39687
> mean(tmp5)
[1] 72.68228
> Sum(tmp5)
[1] 14536.46
> Var(tmp5)
[1] 849.5202
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.91336 69.76437 68.88502 71.80204 71.93327 72.00626 68.72263 71.24230
[9] 69.29609 72.25751
> rowSums(tmp5)
[1] 1818.267 1395.287 1377.700 1436.041 1438.665 1440.125 1374.453 1424.846
[9] 1385.922 1445.150
> rowVars(tmp5)
[1] 7825.67071 63.61533 48.75495 83.20490 97.84106 77.27149
[7] 51.97209 67.35462 81.15059 93.93135
> rowSd(tmp5)
[1] 88.462821 7.975922 6.982474 9.121672 9.891464 8.790421 7.209167
[8] 8.206986 9.008362 9.691818
> rowMax(tmp5)
[1] 465.09877 83.44424 82.93325 86.31292 87.41926 89.91747 82.52465
[8] 90.89367 86.64067 87.76808
> rowMin(tmp5)
[1] 55.60863 56.92392 58.61650 58.10778 53.78716 59.10791 55.03979 60.82626
[9] 53.39687 56.22787
>
> colMeans(tmp5)
[1] 108.68763 69.13427 71.22747 72.17174 67.43126 65.07590 73.81246
[8] 67.56207 70.40017 74.29688 73.17188 72.35468 72.32621 72.42537
[15] 71.50056 72.27092 71.28460 70.12912 67.28800 71.09449
> colSums(tmp5)
[1] 1086.8763 691.3427 712.2747 721.7174 674.3126 650.7590 738.1246
[8] 675.6207 704.0017 742.9688 731.7188 723.5468 723.2621 724.2537
[15] 715.0056 722.7092 712.8460 701.2912 672.8800 710.9449
> colVars(tmp5)
[1] 15763.13051 113.99395 92.18406 64.14529 83.24656 104.39417
[7] 61.08771 35.76475 55.30133 97.76485 44.82916 45.48334
[13] 102.90725 63.38525 67.03900 67.93048 98.34782 52.12551
[19] 108.32822 24.35085
> colSd(tmp5)
[1] 125.551306 10.676795 9.601253 8.009076 9.123955 10.217347
[7] 7.815863 5.980363 7.436486 9.887611 6.695458 6.744134
[13] 10.144321 7.961486 8.187735 8.241995 9.917047 7.219800
[19] 10.408084 4.934659
> colMax(tmp5)
[1] 465.09877 89.91747 87.76808 86.31292 83.44424 82.86234 85.40436
[8] 82.52465 81.01053 85.92660 85.32795 80.44009 86.64067 87.41926
[15] 85.64971 84.19453 90.89367 79.56900 81.23478 80.93785
> colMin(tmp5)
[1] 53.78716 56.22787 58.61650 62.67120 57.48801 54.42230 61.29928 61.75015
[9] 58.15742 56.92392 60.82626 59.47652 55.03979 62.06302 65.30411 58.95147
[17] 57.28908 59.10791 53.39687 65.91271
>
>
> ### 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] 90.91336 69.76437 68.88502 71.80204 71.93327 72.00626 68.72263 71.24230
[9] 69.29609 NA
> rowSums(tmp5)
[1] 1818.267 1395.287 1377.700 1436.041 1438.665 1440.125 1374.453 1424.846
[9] 1385.922 NA
> rowVars(tmp5)
[1] 7825.67071 63.61533 48.75495 83.20490 97.84106 77.27149
[7] 51.97209 67.35462 81.15059 85.08087
> rowSd(tmp5)
[1] 88.462821 7.975922 6.982474 9.121672 9.891464 8.790421 7.209167
[8] 8.206986 9.008362 9.223929
> rowMax(tmp5)
[1] 465.09877 83.44424 82.93325 86.31292 87.41926 89.91747 82.52465
[8] 90.89367 86.64067 NA
> rowMin(tmp5)
[1] 55.60863 56.92392 58.61650 58.10778 53.78716 59.10791 55.03979 60.82626
[9] 53.39687 NA
>
> colMeans(tmp5)
[1] 108.68763 69.13427 NA 72.17174 67.43126 65.07590 73.81246
[8] 67.56207 70.40017 74.29688 73.17188 72.35468 72.32621 72.42537
[15] 71.50056 72.27092 71.28460 70.12912 67.28800 71.09449
> colSums(tmp5)
[1] 1086.8763 691.3427 NA 721.7174 674.3126 650.7590 738.1246
[8] 675.6207 704.0017 742.9688 731.7188 723.5468 723.2621 724.2537
[15] 715.0056 722.7092 712.8460 701.2912 672.8800 710.9449
> colVars(tmp5)
[1] 15763.13051 113.99395 NA 64.14529 83.24656 104.39417
[7] 61.08771 35.76475 55.30133 97.76485 44.82916 45.48334
[13] 102.90725 63.38525 67.03900 67.93048 98.34782 52.12551
[19] 108.32822 24.35085
> colSd(tmp5)
[1] 125.551306 10.676795 NA 8.009076 9.123955 10.217347
[7] 7.815863 5.980363 7.436486 9.887611 6.695458 6.744134
[13] 10.144321 7.961486 8.187735 8.241995 9.917047 7.219800
[19] 10.408084 4.934659
> colMax(tmp5)
[1] 465.09877 89.91747 NA 86.31292 83.44424 82.86234 85.40436
[8] 82.52465 81.01053 85.92660 85.32795 80.44009 86.64067 87.41926
[15] 85.64971 84.19453 90.89367 79.56900 81.23478 80.93785
> colMin(tmp5)
[1] 53.78716 56.22787 NA 62.67120 57.48801 54.42230 61.29928 61.75015
[9] 58.15742 56.92392 60.82626 59.47652 55.03979 62.06302 65.30411 58.95147
[17] 57.28908 59.10791 53.39687 65.91271
>
> Max(tmp5,na.rm=TRUE)
[1] 465.0988
> Min(tmp5,na.rm=TRUE)
[1] 53.39687
> mean(tmp5,na.rm=TRUE)
[1] 72.60648
> Sum(tmp5,na.rm=TRUE)
[1] 14448.69
> Var(tmp5,na.rm=TRUE)
[1] 852.6556
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.91336 69.76437 68.88502 71.80204 71.93327 72.00626 68.72263 71.24230
[9] 69.29609 71.44116
> rowSums(tmp5,na.rm=TRUE)
[1] 1818.267 1395.287 1377.700 1436.041 1438.665 1440.125 1374.453 1424.846
[9] 1385.922 1357.382
> rowVars(tmp5,na.rm=TRUE)
[1] 7825.67071 63.61533 48.75495 83.20490 97.84106 77.27149
[7] 51.97209 67.35462 81.15059 85.08087
> rowSd(tmp5,na.rm=TRUE)
[1] 88.462821 7.975922 6.982474 9.121672 9.891464 8.790421 7.209167
[8] 8.206986 9.008362 9.223929
> rowMax(tmp5,na.rm=TRUE)
[1] 465.09877 83.44424 82.93325 86.31292 87.41926 89.91747 82.52465
[8] 90.89367 86.64067 85.64971
> rowMin(tmp5,na.rm=TRUE)
[1] 55.60863 56.92392 58.61650 58.10778 53.78716 59.10791 55.03979 60.82626
[9] 53.39687 56.22787
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.68763 69.13427 69.38962 72.17174 67.43126 65.07590 73.81246
[8] 67.56207 70.40017 74.29688 73.17188 72.35468 72.32621 72.42537
[15] 71.50056 72.27092 71.28460 70.12912 67.28800 71.09449
> colSums(tmp5,na.rm=TRUE)
[1] 1086.8763 691.3427 624.5066 721.7174 674.3126 650.7590 738.1246
[8] 675.6207 704.0017 742.9688 731.7188 723.5468 723.2621 724.2537
[15] 715.0056 722.7092 712.8460 701.2912 672.8800 710.9449
> colVars(tmp5,na.rm=TRUE)
[1] 15763.13051 113.99395 65.70818 64.14529 83.24656 104.39417
[7] 61.08771 35.76475 55.30133 97.76485 44.82916 45.48334
[13] 102.90725 63.38525 67.03900 67.93048 98.34782 52.12551
[19] 108.32822 24.35085
> colSd(tmp5,na.rm=TRUE)
[1] 125.551306 10.676795 8.106058 8.009076 9.123955 10.217347
[7] 7.815863 5.980363 7.436486 9.887611 6.695458 6.744134
[13] 10.144321 7.961486 8.187735 8.241995 9.917047 7.219800
[19] 10.408084 4.934659
> colMax(tmp5,na.rm=TRUE)
[1] 465.09877 89.91747 78.93304 86.31292 83.44424 82.86234 85.40436
[8] 82.52465 81.01053 85.92660 85.32795 80.44009 86.64067 87.41926
[15] 85.64971 84.19453 90.89367 79.56900 81.23478 80.93785
> colMin(tmp5,na.rm=TRUE)
[1] 53.78716 56.22787 58.61650 62.67120 57.48801 54.42230 61.29928 61.75015
[9] 58.15742 56.92392 60.82626 59.47652 55.03979 62.06302 65.30411 58.95147
[17] 57.28908 59.10791 53.39687 65.91271
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.91336 69.76437 68.88502 71.80204 71.93327 72.00626 68.72263 71.24230
[9] 69.29609 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1818.267 1395.287 1377.700 1436.041 1438.665 1440.125 1374.453 1424.846
[9] 1385.922 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 7825.67071 63.61533 48.75495 83.20490 97.84106 77.27149
[7] 51.97209 67.35462 81.15059 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 88.462821 7.975922 6.982474 9.121672 9.891464 8.790421 7.209167
[8] 8.206986 9.008362 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 465.09877 83.44424 82.93325 86.31292 87.41926 89.91747 82.52465
[8] 90.89367 86.64067 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 55.60863 56.92392 58.61650 58.10778 53.78716 59.10791 55.03979 60.82626
[9] 53.39687 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.27790 70.56831 NaN 72.36524 66.26014 65.94374 73.15127
[8] 67.44173 71.76048 73.80189 72.57602 71.50618 73.05247 71.81071
[15] 69.92843 71.85766 70.66147 69.61642 67.95963 70.66031
> colSums(tmp5,na.rm=TRUE)
[1] 1028.5011 635.1148 0.0000 651.2872 596.3413 593.4937 658.3614
[8] 606.9755 645.8443 664.2170 653.1841 643.5556 657.4722 646.2964
[15] 629.3559 646.7190 635.9532 626.5478 611.6366 635.9428
> colVars(tmp5,na.rm=TRUE)
[1] 17381.94694 105.10775 NA 71.74220 78.22274 108.97051
[7] 63.80543 40.07241 41.39662 107.22903 46.43850 43.06935
[13] 109.83679 67.05801 47.61355 74.50050 106.27304 55.68398
[19] 116.79452 25.27392
> colSd(tmp5,na.rm=TRUE)
[1] 131.840612 10.252207 NA 8.470077 8.844362 10.438894
[7] 7.987830 6.330277 6.434021 10.355145 6.814580 6.562724
[13] 10.480305 8.188895 6.900257 8.631367 10.308881 7.462170
[19] 10.807151 5.027318
> colMax(tmp5,na.rm=TRUE)
[1] 465.09877 89.91747 -Inf 86.31292 83.44424 82.86234 85.40436
[8] 82.52465 81.01053 85.92660 85.32795 80.44009 86.64067 87.41926
[15] 81.92746 84.19453 90.89367 79.56900 81.23478 80.93785
> colMin(tmp5,na.rm=TRUE)
[1] 53.78716 58.10778 Inf 62.67120 57.48801 54.42230 61.29928 61.75015
[9] 62.68214 56.92392 60.82626 59.47652 55.03979 62.06302 65.30411 58.95147
[17] 57.28908 59.10791 53.39687 65.91271
>
>
>
>
> 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] 125.4062 214.5276 216.5727 203.1865 129.6395 229.3676 226.3242 354.7864
[9] 278.2089 398.6866
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 125.4062 214.5276 216.5727 203.1865 129.6395 229.3676 226.3242 354.7864
[9] 278.2089 398.6866
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -5.684342e-14 2.273737e-13 -5.684342e-14 5.684342e-14 -1.136868e-13
[6] 5.684342e-14 -1.136868e-13 -5.684342e-14 0.000000e+00 -5.684342e-14
[11] -1.136868e-13 5.684342e-14 0.000000e+00 1.421085e-13 2.842171e-14
[16] 0.000000e+00 5.684342e-14 5.684342e-14 -5.684342e-14 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
5 15
9 13
7 20
9 14
5 5
4 17
7 10
9 10
5 9
1 7
9 7
3 19
5 5
1 7
7 2
2 2
7 9
3 7
3 16
4 12
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] 2.294553
> Min(tmp)
[1] -2.817377
> mean(tmp)
[1] -0.1146256
> Sum(tmp)
[1] -11.46256
> Var(tmp)
[1] 1.067383
>
> rowMeans(tmp)
[1] -0.1146256
> rowSums(tmp)
[1] -11.46256
> rowVars(tmp)
[1] 1.067383
> rowSd(tmp)
[1] 1.033142
> rowMax(tmp)
[1] 2.294553
> rowMin(tmp)
[1] -2.817377
>
> colMeans(tmp)
[1] -0.19205704 -0.07485619 1.40599265 -0.78499789 -0.76388740 -0.40646427
[7] 0.04087847 -0.67098948 -0.52317895 1.61521300 0.35320423 -2.52479715
[13] -1.88486982 0.32220681 1.48925379 1.11124227 -0.34904393 0.71413358
[19] -0.41218935 -1.47799327 -2.81737702 1.19820019 1.89778301 -0.27262366
[25] -0.20830351 0.13506241 -0.38187904 -0.18426972 0.11593798 -0.77404447
[31] -0.58022265 -0.01995625 1.32454395 -1.39333875 1.09192574 -1.41238714
[37] -0.54142725 -0.02074870 -0.61899796 0.40540282 -0.76456202 1.64224160
[43] -0.64427230 1.32313780 0.86566253 0.02574758 -1.00595973 -1.32046976
[49] -0.91047136 0.08769237 -1.48896534 0.43678338 -0.63031640 0.55069026
[55] -0.07495078 0.25523001 0.53071505 2.29455333 -0.68481772 -0.49012014
[61] 1.06529328 0.85222188 -1.42089444 2.02717278 0.41296723 -0.87647741
[67] -0.63127463 -0.71865965 1.03291316 0.05116318 1.28049867 -0.63808338
[73] -0.94268775 -0.09614036 -0.02100296 0.08464245 -1.02373578 -0.33223307
[79] 1.27234872 0.60841509 -0.26701390 0.63250592 0.16101655 -0.30468121
[85] -0.10325031 -0.68258755 -0.25757843 -1.92213168 -1.86566209 0.15558927
[91] -1.94207419 -0.04848329 0.34900307 1.21834777 -1.37115201 0.47447115
[97] -2.31332602 -0.48205047 -0.69939192 1.89181819
> colSums(tmp)
[1] -0.19205704 -0.07485619 1.40599265 -0.78499789 -0.76388740 -0.40646427
[7] 0.04087847 -0.67098948 -0.52317895 1.61521300 0.35320423 -2.52479715
[13] -1.88486982 0.32220681 1.48925379 1.11124227 -0.34904393 0.71413358
[19] -0.41218935 -1.47799327 -2.81737702 1.19820019 1.89778301 -0.27262366
[25] -0.20830351 0.13506241 -0.38187904 -0.18426972 0.11593798 -0.77404447
[31] -0.58022265 -0.01995625 1.32454395 -1.39333875 1.09192574 -1.41238714
[37] -0.54142725 -0.02074870 -0.61899796 0.40540282 -0.76456202 1.64224160
[43] -0.64427230 1.32313780 0.86566253 0.02574758 -1.00595973 -1.32046976
[49] -0.91047136 0.08769237 -1.48896534 0.43678338 -0.63031640 0.55069026
[55] -0.07495078 0.25523001 0.53071505 2.29455333 -0.68481772 -0.49012014
[61] 1.06529328 0.85222188 -1.42089444 2.02717278 0.41296723 -0.87647741
[67] -0.63127463 -0.71865965 1.03291316 0.05116318 1.28049867 -0.63808338
[73] -0.94268775 -0.09614036 -0.02100296 0.08464245 -1.02373578 -0.33223307
[79] 1.27234872 0.60841509 -0.26701390 0.63250592 0.16101655 -0.30468121
[85] -0.10325031 -0.68258755 -0.25757843 -1.92213168 -1.86566209 0.15558927
[91] -1.94207419 -0.04848329 0.34900307 1.21834777 -1.37115201 0.47447115
[97] -2.31332602 -0.48205047 -0.69939192 1.89181819
> 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] -0.19205704 -0.07485619 1.40599265 -0.78499789 -0.76388740 -0.40646427
[7] 0.04087847 -0.67098948 -0.52317895 1.61521300 0.35320423 -2.52479715
[13] -1.88486982 0.32220681 1.48925379 1.11124227 -0.34904393 0.71413358
[19] -0.41218935 -1.47799327 -2.81737702 1.19820019 1.89778301 -0.27262366
[25] -0.20830351 0.13506241 -0.38187904 -0.18426972 0.11593798 -0.77404447
[31] -0.58022265 -0.01995625 1.32454395 -1.39333875 1.09192574 -1.41238714
[37] -0.54142725 -0.02074870 -0.61899796 0.40540282 -0.76456202 1.64224160
[43] -0.64427230 1.32313780 0.86566253 0.02574758 -1.00595973 -1.32046976
[49] -0.91047136 0.08769237 -1.48896534 0.43678338 -0.63031640 0.55069026
[55] -0.07495078 0.25523001 0.53071505 2.29455333 -0.68481772 -0.49012014
[61] 1.06529328 0.85222188 -1.42089444 2.02717278 0.41296723 -0.87647741
[67] -0.63127463 -0.71865965 1.03291316 0.05116318 1.28049867 -0.63808338
[73] -0.94268775 -0.09614036 -0.02100296 0.08464245 -1.02373578 -0.33223307
[79] 1.27234872 0.60841509 -0.26701390 0.63250592 0.16101655 -0.30468121
[85] -0.10325031 -0.68258755 -0.25757843 -1.92213168 -1.86566209 0.15558927
[91] -1.94207419 -0.04848329 0.34900307 1.21834777 -1.37115201 0.47447115
[97] -2.31332602 -0.48205047 -0.69939192 1.89181819
> colMin(tmp)
[1] -0.19205704 -0.07485619 1.40599265 -0.78499789 -0.76388740 -0.40646427
[7] 0.04087847 -0.67098948 -0.52317895 1.61521300 0.35320423 -2.52479715
[13] -1.88486982 0.32220681 1.48925379 1.11124227 -0.34904393 0.71413358
[19] -0.41218935 -1.47799327 -2.81737702 1.19820019 1.89778301 -0.27262366
[25] -0.20830351 0.13506241 -0.38187904 -0.18426972 0.11593798 -0.77404447
[31] -0.58022265 -0.01995625 1.32454395 -1.39333875 1.09192574 -1.41238714
[37] -0.54142725 -0.02074870 -0.61899796 0.40540282 -0.76456202 1.64224160
[43] -0.64427230 1.32313780 0.86566253 0.02574758 -1.00595973 -1.32046976
[49] -0.91047136 0.08769237 -1.48896534 0.43678338 -0.63031640 0.55069026
[55] -0.07495078 0.25523001 0.53071505 2.29455333 -0.68481772 -0.49012014
[61] 1.06529328 0.85222188 -1.42089444 2.02717278 0.41296723 -0.87647741
[67] -0.63127463 -0.71865965 1.03291316 0.05116318 1.28049867 -0.63808338
[73] -0.94268775 -0.09614036 -0.02100296 0.08464245 -1.02373578 -0.33223307
[79] 1.27234872 0.60841509 -0.26701390 0.63250592 0.16101655 -0.30468121
[85] -0.10325031 -0.68258755 -0.25757843 -1.92213168 -1.86566209 0.15558927
[91] -1.94207419 -0.04848329 0.34900307 1.21834777 -1.37115201 0.47447115
[97] -2.31332602 -0.48205047 -0.69939192 1.89181819
> colMedians(tmp)
[1] -0.19205704 -0.07485619 1.40599265 -0.78499789 -0.76388740 -0.40646427
[7] 0.04087847 -0.67098948 -0.52317895 1.61521300 0.35320423 -2.52479715
[13] -1.88486982 0.32220681 1.48925379 1.11124227 -0.34904393 0.71413358
[19] -0.41218935 -1.47799327 -2.81737702 1.19820019 1.89778301 -0.27262366
[25] -0.20830351 0.13506241 -0.38187904 -0.18426972 0.11593798 -0.77404447
[31] -0.58022265 -0.01995625 1.32454395 -1.39333875 1.09192574 -1.41238714
[37] -0.54142725 -0.02074870 -0.61899796 0.40540282 -0.76456202 1.64224160
[43] -0.64427230 1.32313780 0.86566253 0.02574758 -1.00595973 -1.32046976
[49] -0.91047136 0.08769237 -1.48896534 0.43678338 -0.63031640 0.55069026
[55] -0.07495078 0.25523001 0.53071505 2.29455333 -0.68481772 -0.49012014
[61] 1.06529328 0.85222188 -1.42089444 2.02717278 0.41296723 -0.87647741
[67] -0.63127463 -0.71865965 1.03291316 0.05116318 1.28049867 -0.63808338
[73] -0.94268775 -0.09614036 -0.02100296 0.08464245 -1.02373578 -0.33223307
[79] 1.27234872 0.60841509 -0.26701390 0.63250592 0.16101655 -0.30468121
[85] -0.10325031 -0.68258755 -0.25757843 -1.92213168 -1.86566209 0.15558927
[91] -1.94207419 -0.04848329 0.34900307 1.21834777 -1.37115201 0.47447115
[97] -2.31332602 -0.48205047 -0.69939192 1.89181819
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.192057 -0.07485619 1.405993 -0.7849979 -0.7638874 -0.4064643 0.04087847
[2,] -0.192057 -0.07485619 1.405993 -0.7849979 -0.7638874 -0.4064643 0.04087847
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.6709895 -0.523179 1.615213 0.3532042 -2.524797 -1.88487 0.3222068
[2,] -0.6709895 -0.523179 1.615213 0.3532042 -2.524797 -1.88487 0.3222068
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.489254 1.111242 -0.3490439 0.7141336 -0.4121894 -1.477993 -2.817377
[2,] 1.489254 1.111242 -0.3490439 0.7141336 -0.4121894 -1.477993 -2.817377
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.1982 1.897783 -0.2726237 -0.2083035 0.1350624 -0.381879 -0.1842697
[2,] 1.1982 1.897783 -0.2726237 -0.2083035 0.1350624 -0.381879 -0.1842697
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.115938 -0.7740445 -0.5802226 -0.01995625 1.324544 -1.393339 1.091926
[2,] 0.115938 -0.7740445 -0.5802226 -0.01995625 1.324544 -1.393339 1.091926
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.412387 -0.5414272 -0.0207487 -0.618998 0.4054028 -0.764562 1.642242
[2,] -1.412387 -0.5414272 -0.0207487 -0.618998 0.4054028 -0.764562 1.642242
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.6442723 1.323138 0.8656625 0.02574758 -1.00596 -1.32047 -0.9104714
[2,] -0.6442723 1.323138 0.8656625 0.02574758 -1.00596 -1.32047 -0.9104714
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.08769237 -1.488965 0.4367834 -0.6303164 0.5506903 -0.07495078 0.25523
[2,] 0.08769237 -1.488965 0.4367834 -0.6303164 0.5506903 -0.07495078 0.25523
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.5307151 2.294553 -0.6848177 -0.4901201 1.065293 0.8522219 -1.420894
[2,] 0.5307151 2.294553 -0.6848177 -0.4901201 1.065293 0.8522219 -1.420894
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 2.027173 0.4129672 -0.8764774 -0.6312746 -0.7186597 1.032913 0.05116318
[2,] 2.027173 0.4129672 -0.8764774 -0.6312746 -0.7186597 1.032913 0.05116318
[,71] [,72] [,73] [,74] [,75] [,76]
[1,] 1.280499 -0.6380834 -0.9426877 -0.09614036 -0.02100296 0.08464245
[2,] 1.280499 -0.6380834 -0.9426877 -0.09614036 -0.02100296 0.08464245
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -1.023736 -0.3322331 1.272349 0.6084151 -0.2670139 0.6325059 0.1610166
[2,] -1.023736 -0.3322331 1.272349 0.6084151 -0.2670139 0.6325059 0.1610166
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.3046812 -0.1032503 -0.6825875 -0.2575784 -1.922132 -1.865662 0.1555893
[2,] -0.3046812 -0.1032503 -0.6825875 -0.2575784 -1.922132 -1.865662 0.1555893
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -1.942074 -0.04848329 0.3490031 1.218348 -1.371152 0.4744711 -2.313326
[2,] -1.942074 -0.04848329 0.3490031 1.218348 -1.371152 0.4744711 -2.313326
[,98] [,99] [,100]
[1,] -0.4820505 -0.6993919 1.891818
[2,] -0.4820505 -0.6993919 1.891818
>
>
> Max(tmp2)
[1] 2.75338
> Min(tmp2)
[1] -3.240526
> mean(tmp2)
[1] 0.05081721
> Sum(tmp2)
[1] 5.081721
> Var(tmp2)
[1] 1.297804
>
> rowMeans(tmp2)
[1] 1.43396489 -1.23390123 -0.38642415 0.11921182 1.30549906 0.81042484
[7] -1.96571804 -0.27480458 -2.42145988 -1.89990314 0.03453279 0.48467553
[13] -2.21066146 0.52720852 0.39934552 0.64553217 0.67350647 -2.29610525
[19] -1.25699471 1.07048830 -1.70310901 0.52383151 0.45901939 -1.80895556
[25] -1.82538458 -0.44804928 1.24946310 0.09262725 0.54029958 -0.04965557
[31] -0.54357014 -0.66797740 2.44365346 0.52598303 0.73625061 1.06604544
[37] 0.83153320 1.01448447 -0.23832728 -0.16128241 1.35292894 -3.24052628
[43] -1.10132830 0.69116615 0.42969480 -0.01153292 -1.04899836 -0.33882175
[49] 1.29799606 0.37791504 2.75337952 -1.36617190 1.52254586 0.95732526
[55] 0.39557329 1.74078360 1.47936506 -0.87008695 1.30872308 0.44245988
[61] -1.15664130 1.21093595 0.89197477 -1.38695421 1.26489442 0.54244621
[67] -0.10544724 -0.56926754 1.45804753 -0.37450720 -0.43205058 0.91890809
[73] 1.20434499 -0.70440508 -0.42159074 -0.74735894 0.91021072 0.51176814
[79] 0.82730614 1.45184741 -0.36757528 -0.09065201 0.12891523 -0.47766734
[85] -0.25262663 1.77319500 0.23788852 0.79437550 1.18645344 -2.12141525
[91] 0.34081338 0.27062828 -1.98580053 -0.70266694 0.12134464 0.27737688
[97] -1.17778275 -0.05691094 -0.60381245 0.12549132
> rowSums(tmp2)
[1] 1.43396489 -1.23390123 -0.38642415 0.11921182 1.30549906 0.81042484
[7] -1.96571804 -0.27480458 -2.42145988 -1.89990314 0.03453279 0.48467553
[13] -2.21066146 0.52720852 0.39934552 0.64553217 0.67350647 -2.29610525
[19] -1.25699471 1.07048830 -1.70310901 0.52383151 0.45901939 -1.80895556
[25] -1.82538458 -0.44804928 1.24946310 0.09262725 0.54029958 -0.04965557
[31] -0.54357014 -0.66797740 2.44365346 0.52598303 0.73625061 1.06604544
[37] 0.83153320 1.01448447 -0.23832728 -0.16128241 1.35292894 -3.24052628
[43] -1.10132830 0.69116615 0.42969480 -0.01153292 -1.04899836 -0.33882175
[49] 1.29799606 0.37791504 2.75337952 -1.36617190 1.52254586 0.95732526
[55] 0.39557329 1.74078360 1.47936506 -0.87008695 1.30872308 0.44245988
[61] -1.15664130 1.21093595 0.89197477 -1.38695421 1.26489442 0.54244621
[67] -0.10544724 -0.56926754 1.45804753 -0.37450720 -0.43205058 0.91890809
[73] 1.20434499 -0.70440508 -0.42159074 -0.74735894 0.91021072 0.51176814
[79] 0.82730614 1.45184741 -0.36757528 -0.09065201 0.12891523 -0.47766734
[85] -0.25262663 1.77319500 0.23788852 0.79437550 1.18645344 -2.12141525
[91] 0.34081338 0.27062828 -1.98580053 -0.70266694 0.12134464 0.27737688
[97] -1.17778275 -0.05691094 -0.60381245 0.12549132
> 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] 1.43396489 -1.23390123 -0.38642415 0.11921182 1.30549906 0.81042484
[7] -1.96571804 -0.27480458 -2.42145988 -1.89990314 0.03453279 0.48467553
[13] -2.21066146 0.52720852 0.39934552 0.64553217 0.67350647 -2.29610525
[19] -1.25699471 1.07048830 -1.70310901 0.52383151 0.45901939 -1.80895556
[25] -1.82538458 -0.44804928 1.24946310 0.09262725 0.54029958 -0.04965557
[31] -0.54357014 -0.66797740 2.44365346 0.52598303 0.73625061 1.06604544
[37] 0.83153320 1.01448447 -0.23832728 -0.16128241 1.35292894 -3.24052628
[43] -1.10132830 0.69116615 0.42969480 -0.01153292 -1.04899836 -0.33882175
[49] 1.29799606 0.37791504 2.75337952 -1.36617190 1.52254586 0.95732526
[55] 0.39557329 1.74078360 1.47936506 -0.87008695 1.30872308 0.44245988
[61] -1.15664130 1.21093595 0.89197477 -1.38695421 1.26489442 0.54244621
[67] -0.10544724 -0.56926754 1.45804753 -0.37450720 -0.43205058 0.91890809
[73] 1.20434499 -0.70440508 -0.42159074 -0.74735894 0.91021072 0.51176814
[79] 0.82730614 1.45184741 -0.36757528 -0.09065201 0.12891523 -0.47766734
[85] -0.25262663 1.77319500 0.23788852 0.79437550 1.18645344 -2.12141525
[91] 0.34081338 0.27062828 -1.98580053 -0.70266694 0.12134464 0.27737688
[97] -1.17778275 -0.05691094 -0.60381245 0.12549132
> rowMin(tmp2)
[1] 1.43396489 -1.23390123 -0.38642415 0.11921182 1.30549906 0.81042484
[7] -1.96571804 -0.27480458 -2.42145988 -1.89990314 0.03453279 0.48467553
[13] -2.21066146 0.52720852 0.39934552 0.64553217 0.67350647 -2.29610525
[19] -1.25699471 1.07048830 -1.70310901 0.52383151 0.45901939 -1.80895556
[25] -1.82538458 -0.44804928 1.24946310 0.09262725 0.54029958 -0.04965557
[31] -0.54357014 -0.66797740 2.44365346 0.52598303 0.73625061 1.06604544
[37] 0.83153320 1.01448447 -0.23832728 -0.16128241 1.35292894 -3.24052628
[43] -1.10132830 0.69116615 0.42969480 -0.01153292 -1.04899836 -0.33882175
[49] 1.29799606 0.37791504 2.75337952 -1.36617190 1.52254586 0.95732526
[55] 0.39557329 1.74078360 1.47936506 -0.87008695 1.30872308 0.44245988
[61] -1.15664130 1.21093595 0.89197477 -1.38695421 1.26489442 0.54244621
[67] -0.10544724 -0.56926754 1.45804753 -0.37450720 -0.43205058 0.91890809
[73] 1.20434499 -0.70440508 -0.42159074 -0.74735894 0.91021072 0.51176814
[79] 0.82730614 1.45184741 -0.36757528 -0.09065201 0.12891523 -0.47766734
[85] -0.25262663 1.77319500 0.23788852 0.79437550 1.18645344 -2.12141525
[91] 0.34081338 0.27062828 -1.98580053 -0.70266694 0.12134464 0.27737688
[97] -1.17778275 -0.05691094 -0.60381245 0.12549132
>
> colMeans(tmp2)
[1] 0.05081721
> colSums(tmp2)
[1] 5.081721
> colVars(tmp2)
[1] 1.297804
> colSd(tmp2)
[1] 1.139212
> colMax(tmp2)
[1] 2.75338
> colMin(tmp2)
[1] -3.240526
> colMedians(tmp2)
[1] 0.1834019
> colRanges(tmp2)
[,1]
[1,] -3.240526
[2,] 2.753380
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.0273581 1.8368037 2.1862005 -1.1172659 -0.1303521 2.1592923
[7] -0.1491266 -2.8465085 2.5760267 -0.5625559
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.3758741
[2,] -1.0392845
[3,] -0.2536152
[4,] 1.0017522
[5,] 2.1041844
>
> rowApply(tmp,sum)
[1] 6.1490480 -0.3079103 2.7351760 1.7929515 -1.5435586 -0.6046294
[7] -0.8339846 2.3480088 0.4412934 -6.2512387
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 2 6 10 1 2 5 10 4 2
[2,] 4 9 7 7 5 7 3 3 6 7
[3,] 5 10 4 6 3 3 7 6 10 6
[4,] 7 7 8 5 4 8 1 5 2 1
[5,] 10 3 5 9 10 4 4 4 1 3
[6,] 6 8 3 4 8 10 8 2 3 10
[7,] 2 6 10 1 9 6 2 1 8 8
[8,] 1 1 1 2 7 9 9 7 7 5
[9,] 3 4 9 8 2 5 6 8 9 9
[10,] 9 5 2 3 6 1 10 9 5 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -4.0929512 -0.1299376 0.5683854 0.4021005 1.1925347 -0.6486457
[7] 6.1225078 -0.3524970 -1.4200011 0.8481767 -1.6759419 0.1204061
[13] 0.9344394 -1.9449755 -0.8427850 1.7215096 -2.0792841 -1.3549025
[19] 1.0479218 -0.2769775
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.4475593
[2,] -1.2411433
[3,] -0.8390210
[4,] -0.3658315
[5,] -0.1993962
>
> rowApply(tmp,sum)
[1] -5.609881 -3.901890 -5.587226 6.232878 7.005203
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 12 10 2 2 4
[2,] 16 2 6 17 9
[3,] 10 16 10 16 8
[4,] 20 14 11 6 5
[5,] 18 9 19 5 10
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.1993962 0.47124857 -0.5465925 1.75609035 1.42875656 -0.2358586
[2,] -0.3658315 -1.35123108 0.2016252 0.05141411 -0.60907541 1.5220111
[3,] -1.2411433 -0.78337072 -0.3395099 -0.30368158 0.77926382 -0.5368664
[4,] -1.4475593 1.56596538 1.4025181 -0.37882042 -0.38106991 -2.4364873
[5,] -0.8390210 -0.03254977 -0.1496555 -0.72290193 -0.02534038 1.0385555
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.23896137 -1.47871565 -1.4299935 -1.29867008 -1.0503499 -1.05258312
[2,] -0.03839626 -0.83608601 0.9857631 -0.03941048 -1.2654937 -0.97761854
[3,] 1.97990827 0.37311718 -0.8354218 -0.64633535 0.3088979 -0.01500411
[4,] 1.65413491 0.05537823 -1.3750976 1.06093998 0.6301110 0.43632525
[5,] 2.28789951 1.53380926 1.2347488 1.77165266 -0.2991073 1.72928664
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.1166177 -1.3850064 -1.2987439 0.04610421 1.2381210 -1.0914210
[2,] -0.9767384 -1.0412767 0.0212021 2.02059333 -2.0055922 -0.6563868
[3,] 0.2611682 -1.1744041 -1.1484759 -0.02948725 -0.1994681 0.1409396
[4,] 0.2951888 2.5481054 2.2709756 0.88068337 -0.2672262 -0.6146078
[5,] 1.2382032 -0.8923938 -0.6877429 -1.19638403 -0.8451185 0.8665735
[,19] [,20]
[1,] 1.5292613 -1.36771156
[2,] 0.1740111 1.28462672
[3,] -1.5033815 -0.67397133
[4,] 0.3991188 -0.06569882
[5,] 0.4489121 0.54577745
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.18-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-3.18-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 655 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 567 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.18-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 -0.6488192 1.71395 -0.8875412 -0.3610107 1.77937 -0.6577412 0.6886312
col8 col9 col10 col11 col12 col13 col14
row1 -0.2995948 0.9814229 -0.5454895 0.360555 0.03347744 1.437439 1.338648
col15 col16 col17 col18 col19 col20
row1 0.5002008 0.9096392 0.7446643 0.870833 0.05307386 -1.46765
> tmp[,"col10"]
col10
row1 -0.54548949
row2 0.52223859
row3 -0.37594461
row4 0.74109898
row5 0.05634309
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.6488192 1.7139495 -0.8875412 -0.3610107 1.7793703 -0.6577412 0.6886312
row5 -1.1594778 -0.4140679 0.3228548 -1.8177948 0.2274123 0.5131365 0.4293323
col8 col9 col10 col11 col12 col13
row1 -0.2995948 0.9814229 -0.54548949 0.3605550 0.03347744 1.4374389
row5 0.9638156 0.1303217 0.05634309 0.1951074 1.05438088 -0.9223217
col14 col15 col16 col17 col18 col19
row1 1.3386480 0.5002008 0.9096392 0.7446643 0.8708330 0.05307386
row5 -0.5073223 -1.0593503 0.4919426 -0.4446915 0.1832544 -1.88637380
col20
row1 -1.4676502
row5 0.5688816
> tmp[,c("col6","col20")]
col6 col20
row1 -0.65774116 -1.4676502
row2 -1.50932234 -0.7000391
row3 0.49099850 -0.2210199
row4 0.07947382 0.9818813
row5 0.51313649 0.5688816
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.6577412 -1.4676502
row5 0.5131365 0.5688816
>
>
>
>
> 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 47.90339 49.29694 50.89188 49.09256 50.37545 102.8696 50.73271 50.80035
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.52588 50.05237 49.93648 49.70397 49.4753 50.8234 50.26847 49.17536
col17 col18 col19 col20
row1 50.29758 48.95776 49.05725 105.4775
> tmp[,"col10"]
col10
row1 50.05237
row2 29.94677
row3 31.72975
row4 30.23947
row5 50.86980
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 47.90339 49.29694 50.89188 49.09256 50.37545 102.8696 50.73271 50.80035
row5 51.41394 50.69639 50.76665 49.41489 49.18747 104.7822 49.14636 51.31664
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.52588 50.05237 49.93648 49.70397 49.47530 50.82340 50.26847 49.17536
row5 50.22636 50.86980 50.30048 49.19235 50.15061 51.71732 49.88046 50.98311
col17 col18 col19 col20
row1 50.29758 48.95776 49.05725 105.4775
row5 49.50639 49.81616 51.05999 106.0679
> tmp[,c("col6","col20")]
col6 col20
row1 102.86959 105.47751
row2 75.94199 76.23362
row3 75.18181 74.47396
row4 75.19509 76.19034
row5 104.78216 106.06790
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 102.8696 105.4775
row5 104.7822 106.0679
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 102.8696 105.4775
row5 104.7822 106.0679
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 2.2488202
[2,] -0.3137606
[3,] 0.9188788
[4,] -2.0182743
[5,] -0.4986146
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.5100361 -0.6362928
[2,] 1.9576094 1.3733730
[3,] -0.4900161 -0.9700827
[4,] 2.3735494 0.3523671
[5,] -0.8507637 0.1760753
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.69089739 -0.8410935
[2,] 1.51827300 1.2204516
[3,] -0.04341543 0.5512339
[4,] 0.48130831 0.2706269
[5,] 0.83115270 -0.4568194
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.6908974
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.6908974
[2,] 1.5182730
>
>
>
> 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 -0.2345122 0.9742627 0.06405857 -0.6832829 1.131769 -1.3636340
row1 -1.9261635 -2.6178457 -0.53503074 2.3946548 -2.280947 0.4047736
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.8013691 0.007645097 0.3054592 0.02884295 -1.381871 -0.9697175 0.770685
row1 -0.5975489 1.351008683 0.7970257 -0.28147916 1.191715 -0.8982073 1.142580
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.1112061 0.6628991 0.8461462 0.725993 1.6689697 0.6529221 -0.8856435
row1 1.1913230 1.1523328 0.4097535 -1.242890 0.2699778 -1.1734286 -1.1547252
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.4376469 1.012365 0.7436925 -0.02127506 0.5336194 -1.798879 1.271177
[,8] [,9] [,10]
row2 -0.2843398 1.002058 -0.3360061
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.06336796 1.508774 -0.4021084 1.347945 0.1978693 -0.5678497 -0.7391043
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.2619837 -1.640861 0.5129514 1.49845 -0.379034 -0.9522804 1.696365
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.6017396 0.09272818 -0.8041554 0.9392286 -1.256194 -0.2343499
>
>
> 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: 0x600003694240>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM121cf7fe98f18"
[2] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM121cf3eb1b243"
[3] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM121cf42e6cdd"
[4] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM121cf3ed2350"
[5] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM121cf45a95b33"
[6] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM121cf71a294ff"
[7] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM121cf68e42ba1"
[8] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM121cf5bec8cd3"
[9] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM121cf7119fcb"
[10] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM121cf1611cc0d"
[11] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM121cf6a6b74cc"
[12] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM121cf34c133a9"
[13] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM121cf7826b74d"
[14] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM121cf35cc5ddb"
[15] "/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM121cf7c25f074"
>
>
> ### 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: 0x6000036ac300>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000036ac300>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6000036ac300>
> rowMedians(tmp)
[1] -0.237497962 0.146689130 -0.326123082 0.217754338 -0.739983519
[6] -0.100904631 0.413630998 -0.050420106 -0.261313542 0.096983521
[11] 0.120294955 0.457625791 -0.135607065 0.186460492 -0.342088882
[16] -0.410242711 0.332694137 0.194319580 0.050821365 0.114346675
[21] -0.430358738 -0.187626640 0.272518423 0.217352954 0.047579126
[26] 0.355620709 0.040822339 0.656908012 -0.232864176 0.262736853
[31] -0.468243612 -0.222825827 0.129453723 -0.042056590 -0.089469289
[36] 0.485817271 -0.122568405 0.133592037 0.039200547 -0.072703955
[41] 0.263981855 0.524422337 0.102012606 0.607844741 0.113985515
[46] -0.174519489 -0.300163802 0.294355310 0.032155397 0.104657855
[51] 0.049814285 0.157463581 -0.767711794 -0.407723880 -0.171042225
[56] 0.194323310 0.035080869 -0.264841454 0.249680171 -0.091631585
[61] -0.339887836 0.298187368 0.344826772 -0.113585082 0.111769754
[66] -0.357980627 0.232241813 0.169513058 0.374822219 -0.010597074
[71] 0.213944025 0.210246554 0.298492866 0.002251338 -0.041169830
[76] 0.425166972 -0.037968467 0.037644684 0.235514881 -0.157506515
[81] -0.360164687 -0.019342354 0.250303538 -0.413806776 0.078371729
[86] 0.449601418 -0.113282041 0.309303329 -0.246007721 0.148674391
[91] 0.578220732 0.174370620 -0.071202611 0.054633317 -0.239236663
[96] 0.163160862 -0.211513413 0.272135983 -0.292692469 0.159489268
[101] 0.362659325 -0.119890610 -0.563115686 -0.140686750 -0.235926836
[106] 0.183620279 -0.333558168 0.237651912 -0.153733631 0.139023333
[111] 0.406712598 -0.049375170 0.209992522 -0.792634186 0.419191278
[116] 0.327205928 -0.025055746 -0.624462556 -0.266276765 0.269603318
[121] -0.271010313 -0.320533330 0.001045296 0.365367607 -0.078054730
[126] 0.052675788 -0.094331973 -0.179927028 -0.138614535 0.099203646
[131] 0.197654913 0.212123467 0.575167545 -0.140284760 0.298014998
[136] -0.029258498 0.070261843 0.181160526 0.228423047 -0.058628275
[141] 0.192752696 0.151368007 -0.173922077 0.292767706 -0.086911770
[146] -0.604839134 0.028744524 -0.530637224 0.435190905 -0.114558758
[151] -0.237654898 0.013565517 -0.007451529 0.111393298 -0.098644896
[156] -0.321855610 0.153966823 0.021960183 -0.050534998 -0.162546159
[161] -0.421567820 -0.284032148 -0.216362369 0.020131577 0.428227908
[166] -0.252946690 0.742043991 -0.026608630 -0.696873166 0.088697279
[171] 0.107200356 0.608702091 0.499272591 -0.137020793 -0.541208235
[176] -0.066910650 0.175662980 -0.146816265 0.222230840 0.086287557
[181] -0.007836450 0.420264149 0.364613952 -0.201230041 0.460094535
[186] -0.068916748 0.345368717 -0.239349931 -0.419575837 0.558794466
[191] 0.163686581 -0.178654843 -0.250055885 0.025229449 -0.293988709
[196] 0.393113191 -0.529425795 0.011627386 -0.275584807 0.047492520
[201] -0.365347295 -0.204211398 -0.045889270 0.007033545 0.235153763
[206] -0.391351776 0.041499160 -0.068353233 -0.284508725 -0.109876802
[211] 0.115087609 -0.206591776 0.127782643 0.002723982 -0.066480733
[216] -0.193969143 -0.300526483 0.393087506 -0.237322448 0.313514758
[221] 0.300541554 0.398072870 0.100631689 0.099829387 -0.295896620
[226] -0.482743029 0.250480083 0.400578026 -0.236696515 0.197768074
>
> proc.time()
user system elapsed
4.939 17.747 25.671
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)
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: 0x600001338240>
> .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: 0x600001338240>
> .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: 0x600001338240>
> .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: 0x600001338240>
> 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: 0x600001300000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001300000>
> .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: 0x600001300000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001300000>
> .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: 0x600001300000>
> 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: 0x600001300180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001300180>
> .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: 0x600001300180>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600001300180>
> .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: 0x600001300180>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600001300180>
> .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: 0x600001300180>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600001300180>
> .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: 0x600001300180>
> 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: 0x6000013081e0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000013081e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000013081e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000013081e0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile138bb1e90afaa" "BufferedMatrixFile138bb2cfcd193"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile138bb1e90afaa" "BufferedMatrixFile138bb2cfcd193"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000131c240>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000131c240>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x60000131c240>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x60000131c240>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x60000131c240>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x60000131c240>
> .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: 0x60000131c420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000131c420>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x60000131c420>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x60000131c420>
> 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: 0x600001304000>
> .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: 0x600001304000>
> rm(P)
>
> proc.time()
user system elapsed
0.591 0.211 0.860
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)
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
0.577 0.134 0.681