| Back to Multiple platform build/check report for BioC 3.17: simplified long |
|
This page was generated on 2023-10-16 11:36:53 -0400 (Mon, 16 Oct 2023).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 22.04.2 LTS) | x86_64 | 4.3.1 (2023-06-16) -- "Beagle Scouts" | 4626 |
| palomino3 | Windows Server 2022 Datacenter | x64 | 4.3.1 (2023-06-16 ucrt) -- "Beagle Scouts" | 4379 |
| merida1 | macOS 12.6.4 Monterey | x86_64 | 4.3.1 (2023-06-16) -- "Beagle Scouts" | 4395 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 245/2230 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.64.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 22.04.2 LTS) / x86_64 | OK | OK | OK |  | ||||||||
| palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.6.4 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson2 | macOS 12.6.1 Monterey / 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: 1.64.0 |
| 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_1.64.0.tar.gz |
| StartedAt: 2023-10-15 23:18:58 -0400 (Sun, 15 Oct 2023) |
| EndedAt: 2023-10-15 23:20:23 -0400 (Sun, 15 Oct 2023) |
| EllapsedTime: 85.7 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.64.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.3.1 (2023-06-16)
* using platform: x86_64-apple-darwin20 (64-bit)
* R was compiled by
Apple clang version 14.0.3 (clang-1403.0.22.14.1)
GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.6.4
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.64.0’
* 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-3.17-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-3.17-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 -single_module -multiply_defined suppress -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 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 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
0.595 0.212 0.983
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 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-3.17-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 459924 24.6 991237 53 NA 645662 34.5
Vcells 848560 6.5 8388608 64 65536 2024450 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] "Sun Oct 15 23:19:34 2023"
> 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 Oct 15 23:19:35 2023"
>
>
> 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: 0x6000010682a0>
>
>
>
> 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 Oct 15 23:19:42 2023"
> 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 Oct 15 23:19:45 2023"
>
> ColMode(tmp2)
<pointer: 0x6000010682a0>
>
>
>
> ### 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,] 100.601029 -0.94372370 0.1898417 -0.6471091
[2,] -1.427904 -0.03603975 0.4984971 0.5649766
[3,] 1.372227 -0.55098927 0.4411361 -0.8525790
[4,] 1.523013 -0.19051469 -0.1721450 -0.5214332
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.17-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,] 100.601029 0.94372370 0.1898417 0.6471091
[2,] 1.427904 0.03603975 0.4984971 0.5649766
[3,] 1.372227 0.55098927 0.4411361 0.8525790
[4,] 1.523013 0.19051469 0.1721450 0.5214332
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.17-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,] 10.030006 0.9714544 0.4357083 0.8044309
[2,] 1.194949 0.1898414 0.7060433 0.7516492
[3,] 1.171421 0.7422865 0.6641808 0.9233521
[4,] 1.234104 0.4364799 0.4149036 0.7221033
>
> 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-3.17-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.90109 35.65827 29.54692 33.69142
[2,] 38.37740 26.93445 32.55893 33.08147
[3,] 38.08643 32.97385 32.08294 35.08610
[4,] 38.86405 29.55531 29.32118 32.74247
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600001048000>
> exp(tmp5)
<pointer: 0x600001048000>
> log(tmp5,2)
<pointer: 0x600001048000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.1835
> Min(tmp5)
[1] 53.09352
> mean(tmp5)
[1] 72.87706
> Sum(tmp5)
[1] 14575.41
> Var(tmp5)
[1] 870.3618
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 86.84471 71.95545 72.25030 72.35022 71.82569 71.25088 70.63273 71.98123
[9] 69.61268 70.06667
> rowSums(tmp5)
[1] 1736.894 1439.109 1445.006 1447.004 1436.514 1425.018 1412.655 1439.625
[9] 1392.254 1401.333
> rowVars(tmp5)
[1] 8198.13881 83.23542 41.91627 93.77669 59.24035 116.58367
[7] 67.32706 108.08653 49.63057 61.37126
> rowSd(tmp5)
[1] 90.543574 9.123345 6.474278 9.683836 7.696775 10.797392 8.205307
[8] 10.396467 7.044897 7.833981
> rowMax(tmp5)
[1] 470.18353 88.15037 83.44858 86.40151 83.42893 91.10883 85.26911
[8] 89.77102 81.83454 85.53684
> rowMin(tmp5)
[1] 53.09352 55.10823 58.72420 55.08909 54.71957 55.05620 58.03674 55.77882
[9] 54.48590 57.20729
>
> colMeans(tmp5)
[1] 111.47620 66.04078 67.04742 66.69428 68.48547 72.70652 76.55205
[8] 73.21699 74.75246 70.11095 75.32182 66.91464 69.41671 69.80223
[15] 72.80118 70.73289 69.05883 75.83409 71.05165 69.52397
> colSums(tmp5)
[1] 1114.7620 660.4078 670.4742 666.9428 684.8547 727.0652 765.5205
[8] 732.1699 747.5246 701.1095 753.2182 669.1464 694.1671 698.0223
[15] 728.0118 707.3289 690.5883 758.3409 710.5165 695.2397
> colVars(tmp5)
[1] 15934.18500 43.42952 58.55074 32.00512 119.60577 38.23988
[7] 72.01167 87.65384 59.38297 77.58823 94.53536 50.05198
[13] 41.57443 83.55853 78.17138 88.99670 63.95961 145.90089
[19] 45.94679 75.53874
> colSd(tmp5)
[1] 126.230682 6.590108 7.651845 5.657307 10.936442 6.183840
[7] 8.485969 9.362363 7.706034 8.808418 9.722930 7.074742
[13] 6.447823 9.141035 8.841458 9.433806 7.997475 12.078944
[19] 6.778406 8.691302
> colMax(tmp5)
[1] 470.18353 74.41678 81.77915 76.87514 83.93246 80.23481 91.10883
[8] 88.72398 86.52941 84.40261 88.15037 79.93520 81.48794 83.81527
[15] 83.42893 89.77102 77.26440 87.94366 80.53821 83.44858
> colMin(tmp5)
[1] 62.45674 56.06054 55.05620 59.84850 53.09352 59.72425 65.46068 54.48590
[9] 62.49675 58.11594 55.11057 59.09586 62.47582 55.08909 55.10823 58.35821
[17] 56.40505 56.11257 62.82175 55.77882
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] NA 71.95545 72.25030 72.35022 71.82569 71.25088 70.63273 71.98123
[9] 69.61268 70.06667
> rowSums(tmp5)
[1] NA 1439.109 1445.006 1447.004 1436.514 1425.018 1412.655 1439.625
[9] 1392.254 1401.333
> rowVars(tmp5)
[1] 8637.71457 83.23542 41.91627 93.77669 59.24035 116.58367
[7] 67.32706 108.08653 49.63057 61.37126
> rowSd(tmp5)
[1] 92.939306 9.123345 6.474278 9.683836 7.696775 10.797392 8.205307
[8] 10.396467 7.044897 7.833981
> rowMax(tmp5)
[1] NA 88.15037 83.44858 86.40151 83.42893 91.10883 85.26911 89.77102
[9] 81.83454 85.53684
> rowMin(tmp5)
[1] NA 55.10823 58.72420 55.08909 54.71957 55.05620 58.03674 55.77882
[9] 54.48590 57.20729
>
> colMeans(tmp5)
[1] 111.47620 66.04078 67.04742 66.69428 68.48547 72.70652 76.55205
[8] 73.21699 74.75246 70.11095 75.32182 66.91464 69.41671 69.80223
[15] 72.80118 70.73289 69.05883 75.83409 71.05165 NA
> colSums(tmp5)
[1] 1114.7620 660.4078 670.4742 666.9428 684.8547 727.0652 765.5205
[8] 732.1699 747.5246 701.1095 753.2182 669.1464 694.1671 698.0223
[15] 728.0118 707.3289 690.5883 758.3409 710.5165 NA
> colVars(tmp5)
[1] 15934.18500 43.42952 58.55074 32.00512 119.60577 38.23988
[7] 72.01167 87.65384 59.38297 77.58823 94.53536 50.05198
[13] 41.57443 83.55853 78.17138 88.99670 63.95961 145.90089
[19] 45.94679 NA
> colSd(tmp5)
[1] 126.230682 6.590108 7.651845 5.657307 10.936442 6.183840
[7] 8.485969 9.362363 7.706034 8.808418 9.722930 7.074742
[13] 6.447823 9.141035 8.841458 9.433806 7.997475 12.078944
[19] 6.778406 NA
> colMax(tmp5)
[1] 470.18353 74.41678 81.77915 76.87514 83.93246 80.23481 91.10883
[8] 88.72398 86.52941 84.40261 88.15037 79.93520 81.48794 83.81527
[15] 83.42893 89.77102 77.26440 87.94366 80.53821 NA
> colMin(tmp5)
[1] 62.45674 56.06054 55.05620 59.84850 53.09352 59.72425 65.46068 54.48590
[9] 62.49675 58.11594 55.11057 59.09586 62.47582 55.08909 55.10823 58.35821
[17] 56.40505 56.11257 62.82175 NA
>
> Max(tmp5,na.rm=TRUE)
[1] 470.1835
> Min(tmp5,na.rm=TRUE)
[1] 53.09352
> mean(tmp5,na.rm=TRUE)
[1] 72.88967
> Sum(tmp5,na.rm=TRUE)
[1] 14505.04
> Var(tmp5,na.rm=TRUE)
[1] 874.7256
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 87.71191 71.95545 72.25030 72.35022 71.82569 71.25088 70.63273 71.98123
[9] 69.61268 70.06667
> rowSums(tmp5,na.rm=TRUE)
[1] 1666.526 1439.109 1445.006 1447.004 1436.514 1425.018 1412.655 1439.625
[9] 1392.254 1401.333
> rowVars(tmp5,na.rm=TRUE)
[1] 8637.71457 83.23542 41.91627 93.77669 59.24035 116.58367
[7] 67.32706 108.08653 49.63057 61.37126
> rowSd(tmp5,na.rm=TRUE)
[1] 92.939306 9.123345 6.474278 9.683836 7.696775 10.797392 8.205307
[8] 10.396467 7.044897 7.833981
> rowMax(tmp5,na.rm=TRUE)
[1] 470.18353 88.15037 83.44858 86.40151 83.42893 91.10883 85.26911
[8] 89.77102 81.83454 85.53684
> rowMin(tmp5,na.rm=TRUE)
[1] 53.09352 55.10823 58.72420 55.08909 54.71957 55.05620 58.03674 55.77882
[9] 54.48590 57.20729
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.47620 66.04078 67.04742 66.69428 68.48547 72.70652 76.55205
[8] 73.21699 74.75246 70.11095 75.32182 66.91464 69.41671 69.80223
[15] 72.80118 70.73289 69.05883 75.83409 71.05165 69.43020
> colSums(tmp5,na.rm=TRUE)
[1] 1114.7620 660.4078 670.4742 666.9428 684.8547 727.0652 765.5205
[8] 732.1699 747.5246 701.1095 753.2182 669.1464 694.1671 698.0223
[15] 728.0118 707.3289 690.5883 758.3409 710.5165 624.8718
> colVars(tmp5,na.rm=TRUE)
[1] 15934.18500 43.42952 58.55074 32.00512 119.60577 38.23988
[7] 72.01167 87.65384 59.38297 77.58823 94.53536 50.05198
[13] 41.57443 83.55853 78.17138 88.99670 63.95961 145.90089
[19] 45.94679 84.88217
> colSd(tmp5,na.rm=TRUE)
[1] 126.230682 6.590108 7.651845 5.657307 10.936442 6.183840
[7] 8.485969 9.362363 7.706034 8.808418 9.722930 7.074742
[13] 6.447823 9.141035 8.841458 9.433806 7.997475 12.078944
[19] 6.778406 9.213152
> colMax(tmp5,na.rm=TRUE)
[1] 470.18353 74.41678 81.77915 76.87514 83.93246 80.23481 91.10883
[8] 88.72398 86.52941 84.40261 88.15037 79.93520 81.48794 83.81527
[15] 83.42893 89.77102 77.26440 87.94366 80.53821 83.44858
> colMin(tmp5,na.rm=TRUE)
[1] 62.45674 56.06054 55.05620 59.84850 53.09352 59.72425 65.46068 54.48590
[9] 62.49675 58.11594 55.11057 59.09586 62.47582 55.08909 55.10823 58.35821
[17] 56.40505 56.11257 62.82175 55.77882
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 71.95545 72.25030 72.35022 71.82569 71.25088 70.63273 71.98123
[9] 69.61268 70.06667
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1439.109 1445.006 1447.004 1436.514 1425.018 1412.655 1439.625
[9] 1392.254 1401.333
> rowVars(tmp5,na.rm=TRUE)
[1] NA 83.23542 41.91627 93.77669 59.24035 116.58367 67.32706
[8] 108.08653 49.63057 61.37126
> rowSd(tmp5,na.rm=TRUE)
[1] NA 9.123345 6.474278 9.683836 7.696775 10.797392 8.205307
[8] 10.396467 7.044897 7.833981
> rowMax(tmp5,na.rm=TRUE)
[1] NA 88.15037 83.44858 86.40151 83.42893 91.10883 85.26911 89.77102
[9] 81.83454 85.53684
> rowMin(tmp5,na.rm=TRUE)
[1] NA 55.10823 58.72420 55.08909 54.71957 55.05620 58.03674 55.77882
[9] 54.48590 57.20729
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 71.61983 65.13220 67.66402 66.31317 70.19569 72.68843 76.14209 74.08000
[9] 76.11421 71.44373 75.44235 67.78339 69.14265 71.07761 72.56844 71.47330
[17] 68.38523 78.02537 71.78000 NaN
> colSums(tmp5,na.rm=TRUE)
[1] 644.5784 586.1898 608.9761 596.8186 631.7612 654.1959 685.2788 666.7200
[9] 685.0279 642.9935 678.9812 610.0505 622.2838 639.6985 653.1160 643.2597
[17] 615.4671 702.2283 646.0200 0.0000
> colVars(tmp5,na.rm=TRUE)
[1] 54.99272 39.57111 61.59243 34.37176 101.65202 43.01618 79.12234
[8] 90.23188 45.94439 67.30338 106.18883 47.81775 45.92625 75.70413
[15] 87.33340 93.95394 66.85012 110.11929 45.72212 NA
> colSd(tmp5,na.rm=TRUE)
[1] 7.415707 6.290557 7.848084 5.862743 10.082263 6.558672 8.895074
[8] 9.499046 6.778229 8.203864 10.304797 6.915038 6.776891 8.700812
[15] 9.345234 9.692984 8.176192 10.493774 6.761813 NA
> colMax(tmp5,na.rm=TRUE)
[1] 80.89044 74.41678 81.77915 76.87514 83.93246 80.23481 91.10883 88.72398
[9] 86.52941 84.40261 88.15037 79.93520 81.48794 83.81527 83.42893 89.77102
[17] 77.26440 87.94366 80.53821 -Inf
> colMin(tmp5,na.rm=TRUE)
[1] 62.45674 56.06054 55.05620 59.84850 54.71957 59.72425 65.46068 54.48590
[9] 65.79630 58.41217 55.11057 62.35227 62.47582 55.08909 55.10823 58.35821
[17] 56.40505 58.72420 62.82175 Inf
>
>
>
>
> 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] 185.8977 108.1493 153.3088 315.3969 309.6534 253.8226 152.8007 209.4610
[9] 282.1370 196.2791
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 185.8977 108.1493 153.3088 315.3969 309.6534 253.8226 152.8007 209.4610
[9] 282.1370 196.2791
>
>
>
> 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] 8.526513e-14 -8.526513e-14 0.000000e+00 -7.105427e-14 0.000000e+00
[6] 8.526513e-14 -5.684342e-14 0.000000e+00 -2.273737e-13 0.000000e+00
[11] 5.684342e-14 0.000000e+00 5.684342e-14 5.684342e-14 -5.684342e-14
[16] 1.705303e-13 1.421085e-13 1.136868e-13 9.947598e-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)
+ }
1 4
2 16
9 2
3 17
2 5
7 3
4 10
5 4
2 2
9 1
10 9
9 3
7 2
2 3
10 6
7 1
6 5
4 6
4 19
9 8
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] 2.83637
> Min(tmp)
[1] -2.845304
> mean(tmp)
[1] -0.2496734
> Sum(tmp)
[1] -24.96734
> Var(tmp)
[1] 1.011674
>
> rowMeans(tmp)
[1] -0.2496734
> rowSums(tmp)
[1] -24.96734
> rowVars(tmp)
[1] 1.011674
> rowSd(tmp)
[1] 1.00582
> rowMax(tmp)
[1] 2.83637
> rowMin(tmp)
[1] -2.845304
>
> colMeans(tmp)
[1] 0.902595852 0.312045357 -1.105760679 0.012683502 0.215492799
[6] -0.952389863 -0.044559607 0.208320623 -1.121959004 -1.200266796
[11] 0.755804801 1.874695170 -1.697684840 -0.453601405 -0.783258167
[16] -0.732650869 -0.963082959 0.198788511 -0.471523737 2.836369685
[21] 0.863530970 -1.107430185 0.721015197 -1.119862583 -1.296405241
[26] -1.423497953 2.088143680 -0.008532296 -0.151070418 -0.507540785
[31] -0.264586367 0.744827969 -1.667673059 0.334868539 -0.899345523
[36] 0.231208485 0.377085099 0.028486661 0.823662770 -1.733456288
[41] -1.309686190 0.039884296 -0.316281422 0.224563807 -1.250588320
[46] -0.833029217 1.205298832 -2.845303937 -0.408727937 -2.419165711
[51] -1.162676832 0.431455245 -0.152556385 -1.716070187 0.239812967
[56] -0.183206814 -0.933871228 -1.297188429 -0.745454689 -0.212445742
[61] -1.888502327 0.724791343 0.512276887 -0.551451355 -0.745052186
[66] -0.337120788 -0.057405489 -0.947031633 -0.253351923 -1.302164290
[71] 0.502313926 0.849938042 0.514256441 2.104826620 0.139433059
[76] 0.601967271 0.966127936 -0.281517412 1.224654773 -0.492251364
[81] -0.035639938 -2.248841766 -0.986412218 -1.113931008 0.853487182
[86] 0.106453035 0.298855546 -2.035027229 0.614665953 0.004702153
[91] -1.121951971 0.770759178 0.788621513 -1.226298477 0.084582812
[96] 0.750141282 -0.251329972 -0.297459550 -0.990792500 -0.394912367
> colSums(tmp)
[1] 0.902595852 0.312045357 -1.105760679 0.012683502 0.215492799
[6] -0.952389863 -0.044559607 0.208320623 -1.121959004 -1.200266796
[11] 0.755804801 1.874695170 -1.697684840 -0.453601405 -0.783258167
[16] -0.732650869 -0.963082959 0.198788511 -0.471523737 2.836369685
[21] 0.863530970 -1.107430185 0.721015197 -1.119862583 -1.296405241
[26] -1.423497953 2.088143680 -0.008532296 -0.151070418 -0.507540785
[31] -0.264586367 0.744827969 -1.667673059 0.334868539 -0.899345523
[36] 0.231208485 0.377085099 0.028486661 0.823662770 -1.733456288
[41] -1.309686190 0.039884296 -0.316281422 0.224563807 -1.250588320
[46] -0.833029217 1.205298832 -2.845303937 -0.408727937 -2.419165711
[51] -1.162676832 0.431455245 -0.152556385 -1.716070187 0.239812967
[56] -0.183206814 -0.933871228 -1.297188429 -0.745454689 -0.212445742
[61] -1.888502327 0.724791343 0.512276887 -0.551451355 -0.745052186
[66] -0.337120788 -0.057405489 -0.947031633 -0.253351923 -1.302164290
[71] 0.502313926 0.849938042 0.514256441 2.104826620 0.139433059
[76] 0.601967271 0.966127936 -0.281517412 1.224654773 -0.492251364
[81] -0.035639938 -2.248841766 -0.986412218 -1.113931008 0.853487182
[86] 0.106453035 0.298855546 -2.035027229 0.614665953 0.004702153
[91] -1.121951971 0.770759178 0.788621513 -1.226298477 0.084582812
[96] 0.750141282 -0.251329972 -0.297459550 -0.990792500 -0.394912367
> 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] 0.902595852 0.312045357 -1.105760679 0.012683502 0.215492799
[6] -0.952389863 -0.044559607 0.208320623 -1.121959004 -1.200266796
[11] 0.755804801 1.874695170 -1.697684840 -0.453601405 -0.783258167
[16] -0.732650869 -0.963082959 0.198788511 -0.471523737 2.836369685
[21] 0.863530970 -1.107430185 0.721015197 -1.119862583 -1.296405241
[26] -1.423497953 2.088143680 -0.008532296 -0.151070418 -0.507540785
[31] -0.264586367 0.744827969 -1.667673059 0.334868539 -0.899345523
[36] 0.231208485 0.377085099 0.028486661 0.823662770 -1.733456288
[41] -1.309686190 0.039884296 -0.316281422 0.224563807 -1.250588320
[46] -0.833029217 1.205298832 -2.845303937 -0.408727937 -2.419165711
[51] -1.162676832 0.431455245 -0.152556385 -1.716070187 0.239812967
[56] -0.183206814 -0.933871228 -1.297188429 -0.745454689 -0.212445742
[61] -1.888502327 0.724791343 0.512276887 -0.551451355 -0.745052186
[66] -0.337120788 -0.057405489 -0.947031633 -0.253351923 -1.302164290
[71] 0.502313926 0.849938042 0.514256441 2.104826620 0.139433059
[76] 0.601967271 0.966127936 -0.281517412 1.224654773 -0.492251364
[81] -0.035639938 -2.248841766 -0.986412218 -1.113931008 0.853487182
[86] 0.106453035 0.298855546 -2.035027229 0.614665953 0.004702153
[91] -1.121951971 0.770759178 0.788621513 -1.226298477 0.084582812
[96] 0.750141282 -0.251329972 -0.297459550 -0.990792500 -0.394912367
> colMin(tmp)
[1] 0.902595852 0.312045357 -1.105760679 0.012683502 0.215492799
[6] -0.952389863 -0.044559607 0.208320623 -1.121959004 -1.200266796
[11] 0.755804801 1.874695170 -1.697684840 -0.453601405 -0.783258167
[16] -0.732650869 -0.963082959 0.198788511 -0.471523737 2.836369685
[21] 0.863530970 -1.107430185 0.721015197 -1.119862583 -1.296405241
[26] -1.423497953 2.088143680 -0.008532296 -0.151070418 -0.507540785
[31] -0.264586367 0.744827969 -1.667673059 0.334868539 -0.899345523
[36] 0.231208485 0.377085099 0.028486661 0.823662770 -1.733456288
[41] -1.309686190 0.039884296 -0.316281422 0.224563807 -1.250588320
[46] -0.833029217 1.205298832 -2.845303937 -0.408727937 -2.419165711
[51] -1.162676832 0.431455245 -0.152556385 -1.716070187 0.239812967
[56] -0.183206814 -0.933871228 -1.297188429 -0.745454689 -0.212445742
[61] -1.888502327 0.724791343 0.512276887 -0.551451355 -0.745052186
[66] -0.337120788 -0.057405489 -0.947031633 -0.253351923 -1.302164290
[71] 0.502313926 0.849938042 0.514256441 2.104826620 0.139433059
[76] 0.601967271 0.966127936 -0.281517412 1.224654773 -0.492251364
[81] -0.035639938 -2.248841766 -0.986412218 -1.113931008 0.853487182
[86] 0.106453035 0.298855546 -2.035027229 0.614665953 0.004702153
[91] -1.121951971 0.770759178 0.788621513 -1.226298477 0.084582812
[96] 0.750141282 -0.251329972 -0.297459550 -0.990792500 -0.394912367
> colMedians(tmp)
[1] 0.902595852 0.312045357 -1.105760679 0.012683502 0.215492799
[6] -0.952389863 -0.044559607 0.208320623 -1.121959004 -1.200266796
[11] 0.755804801 1.874695170 -1.697684840 -0.453601405 -0.783258167
[16] -0.732650869 -0.963082959 0.198788511 -0.471523737 2.836369685
[21] 0.863530970 -1.107430185 0.721015197 -1.119862583 -1.296405241
[26] -1.423497953 2.088143680 -0.008532296 -0.151070418 -0.507540785
[31] -0.264586367 0.744827969 -1.667673059 0.334868539 -0.899345523
[36] 0.231208485 0.377085099 0.028486661 0.823662770 -1.733456288
[41] -1.309686190 0.039884296 -0.316281422 0.224563807 -1.250588320
[46] -0.833029217 1.205298832 -2.845303937 -0.408727937 -2.419165711
[51] -1.162676832 0.431455245 -0.152556385 -1.716070187 0.239812967
[56] -0.183206814 -0.933871228 -1.297188429 -0.745454689 -0.212445742
[61] -1.888502327 0.724791343 0.512276887 -0.551451355 -0.745052186
[66] -0.337120788 -0.057405489 -0.947031633 -0.253351923 -1.302164290
[71] 0.502313926 0.849938042 0.514256441 2.104826620 0.139433059
[76] 0.601967271 0.966127936 -0.281517412 1.224654773 -0.492251364
[81] -0.035639938 -2.248841766 -0.986412218 -1.113931008 0.853487182
[86] 0.106453035 0.298855546 -2.035027229 0.614665953 0.004702153
[91] -1.121951971 0.770759178 0.788621513 -1.226298477 0.084582812
[96] 0.750141282 -0.251329972 -0.297459550 -0.990792500 -0.394912367
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.9025959 0.3120454 -1.105761 0.0126835 0.2154928 -0.9523899 -0.04455961
[2,] 0.9025959 0.3120454 -1.105761 0.0126835 0.2154928 -0.9523899 -0.04455961
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.2083206 -1.121959 -1.200267 0.7558048 1.874695 -1.697685 -0.4536014
[2,] 0.2083206 -1.121959 -1.200267 0.7558048 1.874695 -1.697685 -0.4536014
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.7832582 -0.7326509 -0.963083 0.1987885 -0.4715237 2.83637 0.863531
[2,] -0.7832582 -0.7326509 -0.963083 0.1987885 -0.4715237 2.83637 0.863531
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.10743 0.7210152 -1.119863 -1.296405 -1.423498 2.088144 -0.008532296
[2,] -1.10743 0.7210152 -1.119863 -1.296405 -1.423498 2.088144 -0.008532296
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.1510704 -0.5075408 -0.2645864 0.744828 -1.667673 0.3348685 -0.8993455
[2,] -0.1510704 -0.5075408 -0.2645864 0.744828 -1.667673 0.3348685 -0.8993455
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.2312085 0.3770851 0.02848666 0.8236628 -1.733456 -1.309686 0.0398843
[2,] 0.2312085 0.3770851 0.02848666 0.8236628 -1.733456 -1.309686 0.0398843
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.3162814 0.2245638 -1.250588 -0.8330292 1.205299 -2.845304 -0.4087279
[2,] -0.3162814 0.2245638 -1.250588 -0.8330292 1.205299 -2.845304 -0.4087279
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -2.419166 -1.162677 0.4314552 -0.1525564 -1.71607 0.239813 -0.1832068
[2,] -2.419166 -1.162677 0.4314552 -0.1525564 -1.71607 0.239813 -0.1832068
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.9338712 -1.297188 -0.7454547 -0.2124457 -1.888502 0.7247913 0.5122769
[2,] -0.9338712 -1.297188 -0.7454547 -0.2124457 -1.888502 0.7247913 0.5122769
[,64] [,65] [,66] [,67] [,68] [,69]
[1,] -0.5514514 -0.7450522 -0.3371208 -0.05740549 -0.9470316 -0.2533519
[2,] -0.5514514 -0.7450522 -0.3371208 -0.05740549 -0.9470316 -0.2533519
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] -1.302164 0.5023139 0.849938 0.5142564 2.104827 0.1394331 0.6019673
[2,] -1.302164 0.5023139 0.849938 0.5142564 2.104827 0.1394331 0.6019673
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] 0.9661279 -0.2815174 1.224655 -0.4922514 -0.03563994 -2.248842 -0.9864122
[2,] 0.9661279 -0.2815174 1.224655 -0.4922514 -0.03563994 -2.248842 -0.9864122
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -1.113931 0.8534872 0.106453 0.2988555 -2.035027 0.614666 0.004702153
[2,] -1.113931 0.8534872 0.106453 0.2988555 -2.035027 0.614666 0.004702153
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -1.121952 0.7707592 0.7886215 -1.226298 0.08458281 0.7501413 -0.25133
[2,] -1.121952 0.7707592 0.7886215 -1.226298 0.08458281 0.7501413 -0.25133
[,98] [,99] [,100]
[1,] -0.2974596 -0.9907925 -0.3949124
[2,] -0.2974596 -0.9907925 -0.3949124
>
>
> Max(tmp2)
[1] 2.239488
> Min(tmp2)
[1] -2.326432
> mean(tmp2)
[1] 0.09202154
> Sum(tmp2)
[1] 9.202154
> Var(tmp2)
[1] 1.123875
>
> rowMeans(tmp2)
[1] -2.22801809 0.26270042 0.53408382 1.37574462 1.32505483 2.22599717
[7] 0.56176873 1.05797040 -0.33777665 -0.68576619 1.53414508 1.71575314
[13] -0.24667991 0.45135662 0.88703201 -1.81112606 2.10699324 0.47480133
[19] 0.21018355 -0.51745537 0.56049331 0.18830516 0.11476247 -0.13681920
[25] -1.24327766 -1.18628707 -1.57510874 0.74961077 1.57320791 0.28959406
[31] 0.33013928 -0.64395422 -0.55627739 -1.23080462 -1.32698022 -0.39953547
[37] 0.84994189 1.47891975 -0.25357546 -2.08745001 -0.75647098 -0.12698755
[43] -0.24492387 -0.62418704 -2.32643174 -0.44958413 -1.37729696 -1.54461423
[49] -0.59983349 1.01075161 0.94665799 1.74492719 0.55588046 -1.81691040
[55] 0.23909855 1.20891289 0.01474613 -0.44022180 1.06321822 -0.11260046
[61] -1.00963435 0.34668608 0.78934101 0.79775894 0.69291326 0.32376310
[67] 0.41462324 0.38863162 -0.41826312 0.42910868 1.69234585 1.67312959
[73] -1.33116923 -0.11704143 0.72051246 -0.64344223 0.67029296 -1.06933736
[79] -0.97800226 1.49521650 0.99441044 -0.43483096 -0.41982017 0.27621990
[85] 1.09558123 1.51901908 0.12512644 -0.07713700 0.76550314 0.65438459
[91] -0.34801149 0.41341430 -1.33624194 0.93015362 -0.98589132 1.31573493
[97] -0.59138147 -2.05855661 2.23948837 -0.49824167
> rowSums(tmp2)
[1] -2.22801809 0.26270042 0.53408382 1.37574462 1.32505483 2.22599717
[7] 0.56176873 1.05797040 -0.33777665 -0.68576619 1.53414508 1.71575314
[13] -0.24667991 0.45135662 0.88703201 -1.81112606 2.10699324 0.47480133
[19] 0.21018355 -0.51745537 0.56049331 0.18830516 0.11476247 -0.13681920
[25] -1.24327766 -1.18628707 -1.57510874 0.74961077 1.57320791 0.28959406
[31] 0.33013928 -0.64395422 -0.55627739 -1.23080462 -1.32698022 -0.39953547
[37] 0.84994189 1.47891975 -0.25357546 -2.08745001 -0.75647098 -0.12698755
[43] -0.24492387 -0.62418704 -2.32643174 -0.44958413 -1.37729696 -1.54461423
[49] -0.59983349 1.01075161 0.94665799 1.74492719 0.55588046 -1.81691040
[55] 0.23909855 1.20891289 0.01474613 -0.44022180 1.06321822 -0.11260046
[61] -1.00963435 0.34668608 0.78934101 0.79775894 0.69291326 0.32376310
[67] 0.41462324 0.38863162 -0.41826312 0.42910868 1.69234585 1.67312959
[73] -1.33116923 -0.11704143 0.72051246 -0.64344223 0.67029296 -1.06933736
[79] -0.97800226 1.49521650 0.99441044 -0.43483096 -0.41982017 0.27621990
[85] 1.09558123 1.51901908 0.12512644 -0.07713700 0.76550314 0.65438459
[91] -0.34801149 0.41341430 -1.33624194 0.93015362 -0.98589132 1.31573493
[97] -0.59138147 -2.05855661 2.23948837 -0.49824167
> 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] -2.22801809 0.26270042 0.53408382 1.37574462 1.32505483 2.22599717
[7] 0.56176873 1.05797040 -0.33777665 -0.68576619 1.53414508 1.71575314
[13] -0.24667991 0.45135662 0.88703201 -1.81112606 2.10699324 0.47480133
[19] 0.21018355 -0.51745537 0.56049331 0.18830516 0.11476247 -0.13681920
[25] -1.24327766 -1.18628707 -1.57510874 0.74961077 1.57320791 0.28959406
[31] 0.33013928 -0.64395422 -0.55627739 -1.23080462 -1.32698022 -0.39953547
[37] 0.84994189 1.47891975 -0.25357546 -2.08745001 -0.75647098 -0.12698755
[43] -0.24492387 -0.62418704 -2.32643174 -0.44958413 -1.37729696 -1.54461423
[49] -0.59983349 1.01075161 0.94665799 1.74492719 0.55588046 -1.81691040
[55] 0.23909855 1.20891289 0.01474613 -0.44022180 1.06321822 -0.11260046
[61] -1.00963435 0.34668608 0.78934101 0.79775894 0.69291326 0.32376310
[67] 0.41462324 0.38863162 -0.41826312 0.42910868 1.69234585 1.67312959
[73] -1.33116923 -0.11704143 0.72051246 -0.64344223 0.67029296 -1.06933736
[79] -0.97800226 1.49521650 0.99441044 -0.43483096 -0.41982017 0.27621990
[85] 1.09558123 1.51901908 0.12512644 -0.07713700 0.76550314 0.65438459
[91] -0.34801149 0.41341430 -1.33624194 0.93015362 -0.98589132 1.31573493
[97] -0.59138147 -2.05855661 2.23948837 -0.49824167
> rowMin(tmp2)
[1] -2.22801809 0.26270042 0.53408382 1.37574462 1.32505483 2.22599717
[7] 0.56176873 1.05797040 -0.33777665 -0.68576619 1.53414508 1.71575314
[13] -0.24667991 0.45135662 0.88703201 -1.81112606 2.10699324 0.47480133
[19] 0.21018355 -0.51745537 0.56049331 0.18830516 0.11476247 -0.13681920
[25] -1.24327766 -1.18628707 -1.57510874 0.74961077 1.57320791 0.28959406
[31] 0.33013928 -0.64395422 -0.55627739 -1.23080462 -1.32698022 -0.39953547
[37] 0.84994189 1.47891975 -0.25357546 -2.08745001 -0.75647098 -0.12698755
[43] -0.24492387 -0.62418704 -2.32643174 -0.44958413 -1.37729696 -1.54461423
[49] -0.59983349 1.01075161 0.94665799 1.74492719 0.55588046 -1.81691040
[55] 0.23909855 1.20891289 0.01474613 -0.44022180 1.06321822 -0.11260046
[61] -1.00963435 0.34668608 0.78934101 0.79775894 0.69291326 0.32376310
[67] 0.41462324 0.38863162 -0.41826312 0.42910868 1.69234585 1.67312959
[73] -1.33116923 -0.11704143 0.72051246 -0.64344223 0.67029296 -1.06933736
[79] -0.97800226 1.49521650 0.99441044 -0.43483096 -0.41982017 0.27621990
[85] 1.09558123 1.51901908 0.12512644 -0.07713700 0.76550314 0.65438459
[91] -0.34801149 0.41341430 -1.33624194 0.93015362 -0.98589132 1.31573493
[97] -0.59138147 -2.05855661 2.23948837 -0.49824167
>
> colMeans(tmp2)
[1] 0.09202154
> colSums(tmp2)
[1] 9.202154
> colVars(tmp2)
[1] 1.123875
> colSd(tmp2)
[1] 1.06013
> colMax(tmp2)
[1] 2.239488
> colMin(tmp2)
[1] -2.326432
> colMedians(tmp2)
[1] 0.224641
> colRanges(tmp2)
[,1]
[1,] -2.326432
[2,] 2.239488
>
> 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] -0.3805275 -1.7170950 -0.4292745 0.5684295 -5.1980466 0.4745567
[7] -2.5092948 -2.4291070 -1.2688545 -2.5086635
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.3837646
[2,] -0.3651519
[3,] -0.1821899
[4,] 0.6398632
[5,] 1.1160945
>
> rowApply(tmp,sum)
[1] 0.8349328456 -5.5593754841 1.7922000778 -2.6712917300 1.5217338405
[6] -9.0734365491 3.3895484970 -2.7505819788 0.0008459178 -2.8824524775
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 6 4 9 9 4 5 3 6 5 9
[2,] 1 5 1 4 8 9 8 10 8 3
[3,] 10 1 10 10 3 8 2 1 10 5
[4,] 2 7 4 8 2 10 10 5 7 1
[5,] 5 2 5 2 5 1 5 9 4 4
[6,] 4 6 2 6 1 6 9 8 9 10
[7,] 3 9 6 5 10 2 4 4 6 6
[8,] 7 8 7 3 9 7 1 7 3 2
[9,] 8 10 3 1 6 3 6 2 2 7
[10,] 9 3 8 7 7 4 7 3 1 8
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.6195535 -0.6082952 -2.8964191 4.4672255 -0.9789187 2.2817771
[7] 0.8017633 0.1924899 -3.6017172 0.2546197 -1.6489433 0.9905621
[13] 0.2121546 0.6816875 0.1108645 2.5227153 -3.4189795 -0.8922380
[19] -1.9675843 1.8902378
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.6441333
[2,] -0.6240457
[3,] 0.0880273
[4,] 0.5010321
[5,] 1.2986730
>
> rowApply(tmp,sum)
[1] 2.919948 -7.875461 3.141817 2.974988 -2.148737
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 9 7 14 4 20
[2,] 11 12 8 10 11
[3,] 1 17 10 12 6
[4,] 19 16 19 17 5
[5,] 6 15 9 16 2
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.0880273 0.25846710 -2.6483618 1.4123746 -0.19953254 0.9900746
[2,] -0.6441333 -0.25302090 0.4100068 0.2827659 0.09210945 -0.6379965
[3,] 0.5010321 -0.60721702 -0.3266584 2.2105435 -0.60412041 0.9803305
[4,] -0.6240457 0.06375950 0.3081082 1.2154664 0.98236822 1.4399018
[5,] 1.2986730 -0.07028383 -0.6395139 -0.6539250 -1.24974345 -0.4905334
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.4390032 0.0621957 -1.59075423 1.2872217 1.0439705 0.04507405
[2,] -0.1734554 -0.8451450 -1.18674923 -0.5081276 -1.6612301 -0.07981396
[3,] 0.3606763 1.6145686 -0.93773498 -1.1284455 -1.1791967 2.04065516
[4,] 0.5018540 0.1399467 0.02998588 0.3313535 -0.1645299 -2.01591642
[5,] -0.3263149 -0.7790761 0.08353539 0.2726178 0.3120430 1.00056330
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.2987365 0.2542947 -1.01229614 2.4650685 -0.3837113 0.5713195
[2,] 0.4943935 -0.5031028 0.61065484 -1.8630389 -0.5716290 -0.8777702
[3,] -0.1018694 -0.7799655 2.36163537 1.9816435 -1.6061603 -0.6715445
[4,] -0.8155313 1.2382012 -0.07835869 0.6394466 -0.2788129 -0.4613520
[5,] 0.3364254 0.4722600 -1.77077089 -0.7004045 -0.5786660 0.5471092
[,19] [,20]
[1,] -1.2897621 0.8285381
[2,] -0.8580850 0.8979068
[3,] -0.2853917 -0.6809639
[4,] -0.7032482 1.2263914
[5,] 1.1689026 -0.3816346
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.17-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-3.17-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 648 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 563 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.17-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 -0.3999785 -2.295268 -0.3793909 1.162007 0.2006257 1.49419 0.2207599
col8 col9 col10 col11 col12 col13 col14
row1 0.4965725 0.1169585 -0.7620862 0.0871046 0.7977335 0.66565 -0.3381749
col15 col16 col17 col18 col19 col20
row1 -1.002994 1.588895 0.3838827 0.02578519 0.8043706 0.8135919
> tmp[,"col10"]
col10
row1 -0.7620862
row2 1.4248475
row3 0.6922815
row4 -1.6945312
row5 -1.9979671
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.3999785 -2.295268 -0.3793909 1.1620066 0.2006257 1.494190 0.2207599
row5 -1.8996750 -1.550389 -0.2183484 0.6586788 -0.4016761 1.065901 0.5795352
col8 col9 col10 col11 col12 col13 col14
row1 0.4965725 0.1169585 -0.7620862 0.0871046 0.7977335 0.665650 -0.3381749
row5 1.1538941 -1.0941794 -1.9979671 -1.1340480 0.2089424 -1.494384 1.3450312
col15 col16 col17 col18 col19 col20
row1 -1.0029937 1.5888947 0.3838827 0.02578519 0.8043706 0.8135919
row5 0.1659908 0.5672621 -1.5231179 0.83034131 -0.1481995 1.1100720
> tmp[,c("col6","col20")]
col6 col20
row1 1.4941897 0.8135919
row2 0.8547575 -0.7554406
row3 -1.1287511 1.0654681
row4 1.0873596 1.2916798
row5 1.0659010 1.1100720
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.494190 0.8135919
row5 1.065901 1.1100720
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.8002 49.2549 50.55316 49.32264 49.89921 104.1605 50.5639 48.9171
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.52389 49.36702 48.75442 50.91929 50.5103 51.3318 49.64689 49.78555
col17 col18 col19 col20
row1 49.56367 49.69714 49.79977 105.1917
> tmp[,"col10"]
col10
row1 49.36702
row2 30.85640
row3 29.27305
row4 30.48581
row5 48.53789
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.80020 49.2549 50.55316 49.32264 49.89921 104.1605 50.56390 48.91710
row5 50.06625 49.3237 50.39650 49.08168 51.34892 103.7110 49.65838 50.04574
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.52389 49.36702 48.75442 50.91929 50.51030 51.33180 49.64689 49.78555
row5 49.99241 48.53789 50.51785 48.88606 49.19241 49.80839 50.16792 51.14049
col17 col18 col19 col20
row1 49.56367 49.69714 49.79977 105.1917
row5 50.21649 51.49873 49.96883 105.0893
> tmp[,c("col6","col20")]
col6 col20
row1 104.16054 105.19166
row2 73.57655 74.89360
row3 75.98793 74.94577
row4 75.46477 76.18283
row5 103.71103 105.08932
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.1605 105.1917
row5 103.7110 105.0893
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.1605 105.1917
row5 103.7110 105.0893
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.56713834
[2,] -0.57971031
[3,] -1.72214270
[4,] -0.04302318
[5,] -1.28629686
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.3790892 -0.3695637
[2,] 0.4725150 1.3854508
[3,] -0.5880581 -0.6948054
[4,] 0.6000128 2.0218090
[5,] -0.6770146 -0.7558638
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.66049988 0.3424555
[2,] 0.05008343 -1.4945853
[3,] 0.43496437 0.7512407
[4,] -0.68062681 0.5454488
[5,] 0.68861365 1.2128176
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.6604999
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.66049988
[2,] 0.05008343
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 0.2431479 -0.8813634 -0.5603831 -0.9611727 0.6048705 1.254999 0.01879252
row1 -2.1511355 2.1929996 -0.6478940 -1.0767716 0.9382414 -2.082143 0.38609148
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.8419983 0.3598046 1.2212049 1.02439918 1.016470 -0.5126742 -0.2141441
row1 -0.9444276 0.9167608 -0.1927731 0.04938933 -1.340118 0.2626719 0.6789819
[,15] [,16] [,17] [,18] [,19] [,20]
row3 1.7472899 0.3010771 1.576032 -1.2473651 0.2135824 0.3534124
row1 0.1741844 -1.5582201 1.500649 0.7303798 -0.6650982 1.4013548
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.3262764 2.035822 1.387042 -0.1098174 -0.009924486 -1.270464 -0.9397294
[,8] [,9] [,10]
row2 0.4221788 -0.462463 -1.83597
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -1.383045 -0.4281763 0.4026961 -1.423726 -1.072864 0.4623933 -1.556051
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.353298 1.369124 -0.6971461 0.764428 0.6775675 -0.7276669 -0.1773289
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.6276515 0.01575386 0.3834161 -0.193582 -0.8502929 -0.3872001
>
>
> 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: 0x600001058000>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BMebf679e60e74"
[2] "/Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BMebf66ebf2031"
[3] "/Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BMebf645daa9c4"
[4] "/Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BMebf616bfa6b0"
[5] "/Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BMebf658787b"
[6] "/Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BMebf6304dd36a"
[7] "/Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BMebf64572ecec"
[8] "/Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BMebf67c209d92"
[9] "/Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BMebf641491be8"
[10] "/Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BMebf626c73dd4"
[11] "/Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BMebf662ac3d2f"
[12] "/Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BMebf619e50b45"
[13] "/Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BMebf6c46ec4b"
[14] "/Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BMebf64433639"
[15] "/Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BMebf6589cda5e"
>
>
> ### 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: 0x600001044180>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600001044180>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600001044180>
> rowMedians(tmp)
[1] 0.1815582262 -0.4607500721 -0.1438077239 0.0058808979 0.0231738327
[6] 0.0975983618 -0.2545721190 0.4107281358 -0.0095282969 0.2127163886
[11] 0.3336462204 0.6748124753 0.0791940888 -0.0537539351 -0.5443611918
[16] -0.1529840739 -0.2193791671 -0.2830185281 0.6025641155 -0.1279945638
[21] -0.4515086380 -0.3767510576 0.1611721495 0.1547794845 0.3959514883
[26] 0.2891836905 -0.3035708767 0.1079373596 0.2445685092 0.5554558173
[31] 0.4866715322 0.0496587427 -0.0076616622 0.3633049988 0.4144597713
[36] -0.0041955390 -0.2489111320 0.2286102794 0.6271732877 0.3202100868
[41] 0.6956240977 0.1252417119 0.1479903114 0.2003886598 -0.0976220120
[46] -0.1846411374 -0.0967204467 -0.0780496260 0.3194617912 -0.8046816114
[51] -0.2330778321 0.1362347661 0.0148142341 0.3619923757 -0.6946713565
[56] 0.4053611871 0.1664501191 0.1242721913 0.3638452303 -0.1919140236
[61] -0.1421693947 -0.0175516224 -0.2729631225 -0.1222953005 -0.2059309576
[66] -0.3200700961 0.7510097868 0.1779078843 -0.0571217178 0.0517057900
[71] 0.0308695670 0.5024091282 -0.3716135018 0.0282855613 -0.1084954785
[76] -0.0082824223 0.4342778940 -0.2277213534 0.2602670359 -0.1417226058
[81] 0.0014241945 0.0939402874 0.0994373953 -0.0793169781 -0.0567798873
[86] -0.9207747603 0.4794015869 -0.0019230476 -0.4552595340 0.0229367559
[91] -0.4170616714 0.1795631191 -0.3160360061 0.1236170464 0.5914205778
[96] -0.1577808648 -0.0577011474 0.0950864013 -0.2050456835 -0.0841861330
[101] -0.0808083892 -0.1065564209 -0.2802825216 0.3126711730 -0.0409637793
[106] -0.6114210851 -0.0379468934 -0.0626803696 0.1379232932 -0.2558036948
[111] -0.0066194330 0.4364030289 -0.0693983408 0.3337765449 0.1233955773
[116] 0.0261005032 0.2628727375 0.4799148710 0.1495757546 0.0671713442
[121] 0.5984128628 -0.0004760885 -0.2042120889 -0.1319792652 0.1672039008
[126] 0.3616559764 0.3319425895 0.1310039043 -0.0987015538 -0.0569733747
[131] 0.2635439543 -0.5087053053 0.4711803785 -0.2756051234 0.1981981679
[136] -0.2100000958 0.0038845244 -0.4533200596 0.0132643682 0.6849589407
[141] 0.3996812774 -0.5197586986 0.1937789659 -0.4537166538 0.0292998894
[146] -0.3810028274 -0.0397677668 -0.1094777682 0.0298218847 0.0624181605
[151] 0.4989755355 -0.6422519449 0.1964132983 0.2420673811 0.0100947499
[156] 0.1652564957 0.7937569270 -0.2227670910 -0.2958454086 -0.2093937288
[161] -0.2893484266 0.5422681584 0.0186072657 -0.1156779378 0.1907129756
[166] 0.2882934691 -0.2557507529 -0.1341211359 0.0054909793 -0.1211731250
[171] 0.1471791535 -0.3435463435 0.0016605763 0.2570585696 -0.2156315667
[176] -0.0709033695 -0.3197894662 0.2576030954 -0.3131703102 0.2217081913
[181] 0.0755048792 -0.5874744528 0.3056153291 -0.5117281036 -0.3124372593
[186] 0.0614807446 0.1988829188 0.5638455114 0.0099924029 -0.1415815709
[191] 0.0485691883 -0.1356170184 0.2816370277 0.0703471190 0.0222005891
[196] -0.0657550194 -0.1584654903 0.5840831790 0.0386149756 0.5772696305
[201] 0.1396613674 0.1202168616 0.2746299474 0.0476442679 0.3560732495
[206] 0.7279894874 0.2953427982 -0.0530126749 0.0170069740 -0.0071356679
[211] -0.1164901465 0.0201371132 0.0018157727 -0.0469393959 0.3211400294
[216] -0.0716467544 -0.1303678300 -0.6058699372 -0.1474434664 0.4637727758
[221] -0.0195816011 0.2532048449 0.3507908762 -0.8316205939 -0.3705297011
[226] 0.3392895248 0.2114365396 -0.0497028583 -0.0264861359 -0.2889298782
>
> proc.time()
user system elapsed
5.062 18.337 31.762
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 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: 0x600000150120>
> .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: 0x600000150120>
> .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: 0x600000150120>
> .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: 0x600000150120>
> 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: 0x6000001582a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000001582a0>
> .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: 0x6000001582a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000001582a0>
> .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: 0x6000001582a0>
> 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: 0x600000158420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000158420>
> .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: 0x600000158420>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600000158420>
> .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: 0x600000158420>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600000158420>
> .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: 0x600000158420>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600000158420>
> .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: 0x600000158420>
> 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: 0x600000170000>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600000170000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000170000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000170000>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilef04543d585dd" "BufferedMatrixFilef045478c2cdd"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilef04543d585dd" "BufferedMatrixFilef045478c2cdd"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000178060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000178060>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600000178060>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600000178060>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600000178060>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600000178060>
> .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: 0x60000016c060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000016c060>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x60000016c060>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x60000016c060>
> 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: 0x60000016c240>
> .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: 0x60000016c240>
> rm(P)
>
> proc.time()
user system elapsed
0.593 0.218 0.898
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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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
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.589 0.139 0.805