| Back to Multiple platform build/check report for BioC 3.19: simplified long |
|
This page was generated on 2024-05-10 11:37:36 -0400 (Fri, 10 May 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4751 |
| palomino3 | Windows Server 2022 Datacenter | x64 | 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup" | 4485 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4515 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 249/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.68.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK |  | ||||||||
| palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.6.5 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: 1.68.0 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.68.0.tar.gz |
| StartedAt: 2024-05-09 19:30:37 -0400 (Thu, 09 May 2024) |
| EndedAt: 2024-05-09 19:31:32 -0400 (Thu, 09 May 2024) |
| EllapsedTime: 55.2 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.68.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.0 (2024-04-24)
* using platform: x86_64-apple-darwin20
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.68.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... WARNING
Found the following significant warnings:
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 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 code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 WARNING, 2 NOTEs
See
‘/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-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/4.4-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 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.356 0.155 0.513
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
Ncells 474174 25.4 1035461 55.3 NA 638642 34.2
Vcells 877658 6.7 8388608 64.0 98304 2071719 15.9
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu May 9 19:31:03 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu May 9 19:31:04 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: 0x600002c24000>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu May 9 19:31:08 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu May 9 19:31:10 2024"
>
> ColMode(tmp2)
<pointer: 0x600002c24000>
>
>
>
> ### 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,] 99.7786927 -0.9164091 1.1633446 -1.2568260
[2,] -0.2316318 -1.0737098 2.6592684 0.3740892
[3,] 0.7054800 -0.1217849 -1.9809419 0.6290023
[4,] 0.4903326 -0.8756645 0.4642764 -2.0748882
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.7786927 0.9164091 1.1633446 1.2568260
[2,] 0.2316318 1.0737098 2.6592684 0.3740892
[3,] 0.7054800 0.1217849 1.9809419 0.6290023
[4,] 0.4903326 0.8756645 0.4642764 2.0748882
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9889285 0.9572926 1.0785845 1.1210825
[2,] 0.4812814 1.0361997 1.6307263 0.6116283
[3,] 0.8399285 0.3489769 1.4074594 0.7930967
[4,] 0.7002375 0.9357695 0.6813783 1.4404472
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.66798 35.48933 36.94919 37.46765
[2,] 30.04445 36.43571 43.96653 31.49037
[3,] 34.10477 28.61155 41.05554 33.55997
[4,] 32.49271 35.23336 32.27806 41.47936
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600002c641e0>
> exp(tmp5)
<pointer: 0x600002c641e0>
> log(tmp5,2)
<pointer: 0x600002c641e0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.617
> Min(tmp5)
[1] 53.28379
> mean(tmp5)
[1] 72.09125
> Sum(tmp5)
[1] 14418.25
> Var(tmp5)
[1] 866.0326
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.24224 68.81782 73.29212 72.49985 68.99026 69.71259 71.29032 67.56768
[9] 67.67344 69.82622
> rowSums(tmp5)
[1] 1824.845 1376.356 1465.842 1449.997 1379.805 1394.252 1425.806 1351.354
[9] 1353.469 1396.524
> rowVars(tmp5)
[1] 7921.38361 99.56941 101.56833 71.67117 55.11688 67.86081
[7] 89.59765 58.97130 89.94095 51.59740
> rowSd(tmp5)
[1] 89.002155 9.978447 10.078112 8.465883 7.424074 8.237768 9.465603
[8] 7.679277 9.483720 7.183133
> rowMax(tmp5)
[1] 467.61696 91.51058 92.89400 87.16976 88.79220 82.13080 91.71293
[8] 82.50014 89.40322 82.01936
> rowMin(tmp5)
[1] 56.29201 54.98302 59.55120 58.63978 53.95601 55.09630 53.28379 58.73159
[9] 55.20057 54.86864
>
> colMeans(tmp5)
[1] 109.71541 70.23097 75.26009 73.92095 70.54227 70.47745 73.58605
[8] 76.15715 67.91707 72.05932 69.04467 68.09724 67.19127 64.21211
[15] 71.58973 65.78483 69.08476 67.69552 73.99429 65.26394
> colSums(tmp5)
[1] 1097.1541 702.3097 752.6009 739.2095 705.4227 704.7745 735.8605
[8] 761.5715 679.1707 720.5932 690.4467 680.9724 671.9127 642.1211
[15] 715.8973 657.8483 690.8476 676.9552 739.9429 652.6394
> colVars(tmp5)
[1] 15846.02399 41.20700 68.35823 121.32045 70.63142 36.98918
[7] 56.66477 109.34552 92.61914 69.47986 55.73005 108.79667
[13] 59.67572 53.58305 79.15547 86.29911 122.94468 101.52614
[19] 43.91221 31.83088
> colSd(tmp5)
[1] 125.880991 6.419268 8.267904 11.014556 8.404250 6.081873
[7] 7.527600 10.456841 9.623884 8.335458 7.465256 10.430564
[13] 7.725006 7.320044 8.896936 9.289732 11.088042 10.076018
[19] 6.626629 5.641886
> colMax(tmp5)
[1] 467.61696 80.73365 91.51058 89.40322 89.33307 78.59589 84.12260
[8] 92.89400 85.65389 84.41371 82.13080 91.71293 78.65614 81.34696
[15] 80.63554 81.46078 87.16976 85.95629 85.02551 74.16734
> colMin(tmp5)
[1] 62.53358 59.55120 66.08642 60.11489 60.88963 59.55848 64.62045 55.09630
[9] 53.95601 59.79649 59.55882 55.76608 54.98302 54.86864 55.52780 53.28379
[17] 55.20057 55.63309 65.62944 58.39557
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 91.24224 68.81782 73.29212 72.49985 68.99026 NA 71.29032 67.56768
[9] 67.67344 69.82622
> rowSums(tmp5)
[1] 1824.845 1376.356 1465.842 1449.997 1379.805 NA 1425.806 1351.354
[9] 1353.469 1396.524
> rowVars(tmp5)
[1] 7921.38361 99.56941 101.56833 71.67117 55.11688 70.22334
[7] 89.59765 58.97130 89.94095 51.59740
> rowSd(tmp5)
[1] 89.002155 9.978447 10.078112 8.465883 7.424074 8.379937 9.465603
[8] 7.679277 9.483720 7.183133
> rowMax(tmp5)
[1] 467.61696 91.51058 92.89400 87.16976 88.79220 NA 91.71293
[8] 82.50014 89.40322 82.01936
> rowMin(tmp5)
[1] 56.29201 54.98302 59.55120 58.63978 53.95601 NA 53.28379 58.73159
[9] 55.20057 54.86864
>
> colMeans(tmp5)
[1] 109.71541 70.23097 75.26009 73.92095 70.54227 70.47745 73.58605
[8] 76.15715 67.91707 72.05932 69.04467 68.09724 67.19127 64.21211
[15] 71.58973 65.78483 69.08476 67.69552 73.99429 NA
> colSums(tmp5)
[1] 1097.1541 702.3097 752.6009 739.2095 705.4227 704.7745 735.8605
[8] 761.5715 679.1707 720.5932 690.4467 680.9724 671.9127 642.1211
[15] 715.8973 657.8483 690.8476 676.9552 739.9429 NA
> colVars(tmp5)
[1] 15846.02399 41.20700 68.35823 121.32045 70.63142 36.98918
[7] 56.66477 109.34552 92.61914 69.47986 55.73005 108.79667
[13] 59.67572 53.58305 79.15547 86.29911 122.94468 101.52614
[19] 43.91221 NA
> colSd(tmp5)
[1] 125.880991 6.419268 8.267904 11.014556 8.404250 6.081873
[7] 7.527600 10.456841 9.623884 8.335458 7.465256 10.430564
[13] 7.725006 7.320044 8.896936 9.289732 11.088042 10.076018
[19] 6.626629 NA
> colMax(tmp5)
[1] 467.61696 80.73365 91.51058 89.40322 89.33307 78.59589 84.12260
[8] 92.89400 85.65389 84.41371 82.13080 91.71293 78.65614 81.34696
[15] 80.63554 81.46078 87.16976 85.95629 85.02551 NA
> colMin(tmp5)
[1] 62.53358 59.55120 66.08642 60.11489 60.88963 59.55848 64.62045 55.09630
[9] 53.95601 59.79649 59.55882 55.76608 54.98302 54.86864 55.52780 53.28379
[17] 55.20057 55.63309 65.62944 NA
>
> Max(tmp5,na.rm=TRUE)
[1] 467.617
> Min(tmp5,na.rm=TRUE)
[1] 53.28379
> mean(tmp5,na.rm=TRUE)
[1] 72.12786
> Sum(tmp5,na.rm=TRUE)
[1] 14353.44
> Var(tmp5,na.rm=TRUE)
[1] 870.1371
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.24224 68.81782 73.29212 72.49985 68.99026 69.97080 71.29032 67.56768
[9] 67.67344 69.82622
> rowSums(tmp5,na.rm=TRUE)
[1] 1824.845 1376.356 1465.842 1449.997 1379.805 1329.445 1425.806 1351.354
[9] 1353.469 1396.524
> rowVars(tmp5,na.rm=TRUE)
[1] 7921.38361 99.56941 101.56833 71.67117 55.11688 70.22334
[7] 89.59765 58.97130 89.94095 51.59740
> rowSd(tmp5,na.rm=TRUE)
[1] 89.002155 9.978447 10.078112 8.465883 7.424074 8.379937 9.465603
[8] 7.679277 9.483720 7.183133
> rowMax(tmp5,na.rm=TRUE)
[1] 467.61696 91.51058 92.89400 87.16976 88.79220 82.13080 91.71293
[8] 82.50014 89.40322 82.01936
> rowMin(tmp5,na.rm=TRUE)
[1] 56.29201 54.98302 59.55120 58.63978 53.95601 55.09630 53.28379 58.73159
[9] 55.20057 54.86864
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.71541 70.23097 75.26009 73.92095 70.54227 70.47745 73.58605
[8] 76.15715 67.91707 72.05932 69.04467 68.09724 67.19127 64.21211
[15] 71.58973 65.78483 69.08476 67.69552 73.99429 65.31475
> colSums(tmp5,na.rm=TRUE)
[1] 1097.1541 702.3097 752.6009 739.2095 705.4227 704.7745 735.8605
[8] 761.5715 679.1707 720.5932 690.4467 680.9724 671.9127 642.1211
[15] 715.8973 657.8483 690.8476 676.9552 739.9429 587.8328
> colVars(tmp5,na.rm=TRUE)
[1] 15846.02399 41.20700 68.35823 121.32045 70.63142 36.98918
[7] 56.66477 109.34552 92.61914 69.47986 55.73005 108.79667
[13] 59.67572 53.58305 79.15547 86.29911 122.94468 101.52614
[19] 43.91221 35.78069
> colSd(tmp5,na.rm=TRUE)
[1] 125.880991 6.419268 8.267904 11.014556 8.404250 6.081873
[7] 7.527600 10.456841 9.623884 8.335458 7.465256 10.430564
[13] 7.725006 7.320044 8.896936 9.289732 11.088042 10.076018
[19] 6.626629 5.981697
> colMax(tmp5,na.rm=TRUE)
[1] 467.61696 80.73365 91.51058 89.40322 89.33307 78.59589 84.12260
[8] 92.89400 85.65389 84.41371 82.13080 91.71293 78.65614 81.34696
[15] 80.63554 81.46078 87.16976 85.95629 85.02551 74.16734
> colMin(tmp5,na.rm=TRUE)
[1] 62.53358 59.55120 66.08642 60.11489 60.88963 59.55848 64.62045 55.09630
[9] 53.95601 59.79649 59.55882 55.76608 54.98302 54.86864 55.52780 53.28379
[17] 55.20057 55.63309 65.62944 58.39557
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.24224 68.81782 73.29212 72.49985 68.99026 NaN 71.29032 67.56768
[9] 67.67344 69.82622
> rowSums(tmp5,na.rm=TRUE)
[1] 1824.845 1376.356 1465.842 1449.997 1379.805 0.000 1425.806 1351.354
[9] 1353.469 1396.524
> rowVars(tmp5,na.rm=TRUE)
[1] 7921.38361 99.56941 101.56833 71.67117 55.11688 NA
[7] 89.59765 58.97130 89.94095 51.59740
> rowSd(tmp5,na.rm=TRUE)
[1] 89.002155 9.978447 10.078112 8.465883 7.424074 NA 9.465603
[8] 7.679277 9.483720 7.183133
> rowMax(tmp5,na.rm=TRUE)
[1] 467.61696 91.51058 92.89400 87.16976 88.79220 NA 91.71293
[8] 82.50014 89.40322 82.01936
> rowMin(tmp5,na.rm=TRUE)
[1] 56.29201 54.98302 59.55120 58.63978 53.95601 NA 53.28379 58.73159
[9] 55.20057 54.86864
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.52799 69.95106 74.94176 75.45496 70.49278 69.57541 73.22512
[8] 78.49724 67.20306 73.42186 67.59066 68.62132 67.00433 62.30824
[15] 71.30021 66.79267 68.66641 68.33611 73.88506 NaN
> colSums(tmp5,na.rm=TRUE)
[1] 1030.7519 629.5595 674.4758 679.0946 634.4350 626.1787 659.0261
[8] 706.4752 604.8275 660.7968 608.3159 617.5919 603.0390 560.7741
[15] 641.7019 601.1341 617.9977 615.0250 664.9655 0.0000
> colVars(tmp5,na.rm=TRUE)
[1] 17566.21677 45.47641 75.76297 110.01229 79.43279 32.45880
[7] 62.28233 61.40825 98.46124 57.27913 38.91205 119.30624
[13] 66.74206 19.50274 88.10692 85.65940 136.34389 109.60030
[19] 49.26700 NA
> colSd(tmp5,na.rm=TRUE)
[1] 132.537605 6.743620 8.704193 10.488674 8.912508 5.697263
[7] 7.891915 7.836341 9.922764 7.568298 6.237952 10.922739
[13] 8.169581 4.416190 9.386529 9.255237 11.676638 10.469016
[19] 7.019045 NA
> colMax(tmp5,na.rm=TRUE)
[1] 467.61696 80.73365 91.51058 89.40322 89.33307 75.51831 84.12260
[8] 92.89400 85.65389 84.41371 80.59284 91.71293 78.65614 67.89172
[15] 80.63554 81.46078 87.16976 85.95629 85.02551 -Inf
> colMin(tmp5,na.rm=TRUE)
[1] 62.53358 59.55120 66.08642 62.39314 60.88963 59.55848 64.62045 64.68655
[9] 53.95601 63.71037 59.55882 55.76608 54.98302 54.86864 55.52780 53.28379
[17] 55.20057 55.63309 65.62944 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] 83.58175 324.67553 205.27004 276.80910 189.61890 130.83152 279.22705
[8] 190.73812 286.80746 182.16541
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 83.58175 324.67553 205.27004 276.80910 189.61890 130.83152 279.22705
[8] 190.73812 286.80746 182.16541
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -1.136868e-13 -9.947598e-14 -8.526513e-14 -1.421085e-13 0.000000e+00
[6] -5.684342e-14 0.000000e+00 -5.684342e-14 1.705303e-13 -4.263256e-14
[11] 1.136868e-13 0.000000e+00 8.526513e-14 -2.842171e-14 5.684342e-14
[16] -1.421085e-13 1.989520e-13 -2.273737e-13 2.273737e-13 -5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
1 18
8 8
1 7
2 11
9 6
4 9
5 1
8 16
2 4
10 19
10 10
4 13
2 12
9 19
2 7
1 18
2 19
1 16
5 20
6 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] 3.141309
> Min(tmp)
[1] -2.909095
> mean(tmp)
[1] 0.1096039
> Sum(tmp)
[1] 10.96039
> Var(tmp)
[1] 1.223398
>
> rowMeans(tmp)
[1] 0.1096039
> rowSums(tmp)
[1] 10.96039
> rowVars(tmp)
[1] 1.223398
> rowSd(tmp)
[1] 1.106073
> rowMax(tmp)
[1] 3.141309
> rowMin(tmp)
[1] -2.909095
>
> colMeans(tmp)
[1] 0.40689847 3.14130910 0.37177278 0.40286302 -2.88494724 1.01096647
[7] 2.88372492 -0.03806166 -1.43085934 1.15090072 1.00585718 -0.09967717
[13] 1.89245355 1.43803706 -0.63336487 0.86692571 1.92400365 0.67485310
[19] 0.78877369 0.08896871 0.85994494 1.77657216 -0.34488670 0.44291040
[25] -0.02026313 0.38552475 0.46991006 1.61154722 -0.10408419 0.62007271
[31] 0.80989919 -1.55405363 0.31835491 0.35517210 -0.57310879 2.29331309
[37] -0.11535740 0.36694618 0.72306683 -0.40315416 -0.22942879 -0.89888377
[43] 1.48380708 -1.59176290 0.97138821 -0.19388787 0.35171021 -0.99889251
[49] 1.37291399 -0.18549150 -0.39439091 -0.44831073 0.37146180 0.73748020
[55] -1.53849619 -0.68539479 1.56568615 0.07389661 -1.35484292 0.90551941
[61] -0.42942941 -0.79086432 -0.39444144 0.31801490 0.71367187 0.95586420
[67] -1.24918128 -0.04700922 1.69807854 -0.66367796 0.35227497 -0.36746386
[73] 1.44551817 -1.49030512 0.73588567 -1.33028833 -0.95906062 0.20638389
[79] -0.99543385 -0.29518622 -0.34505517 -0.97312320 -0.22069612 -1.27226076
[85] -0.51440416 -0.09535646 -0.03058337 -1.29014905 -0.03541041 0.15736115
[91] 0.58971868 1.33622224 -0.01729363 -1.47113829 1.13744142 -2.90909497
[97] 1.18918308 0.98615083 -2.10114033 -0.76713942
> colSums(tmp)
[1] 0.40689847 3.14130910 0.37177278 0.40286302 -2.88494724 1.01096647
[7] 2.88372492 -0.03806166 -1.43085934 1.15090072 1.00585718 -0.09967717
[13] 1.89245355 1.43803706 -0.63336487 0.86692571 1.92400365 0.67485310
[19] 0.78877369 0.08896871 0.85994494 1.77657216 -0.34488670 0.44291040
[25] -0.02026313 0.38552475 0.46991006 1.61154722 -0.10408419 0.62007271
[31] 0.80989919 -1.55405363 0.31835491 0.35517210 -0.57310879 2.29331309
[37] -0.11535740 0.36694618 0.72306683 -0.40315416 -0.22942879 -0.89888377
[43] 1.48380708 -1.59176290 0.97138821 -0.19388787 0.35171021 -0.99889251
[49] 1.37291399 -0.18549150 -0.39439091 -0.44831073 0.37146180 0.73748020
[55] -1.53849619 -0.68539479 1.56568615 0.07389661 -1.35484292 0.90551941
[61] -0.42942941 -0.79086432 -0.39444144 0.31801490 0.71367187 0.95586420
[67] -1.24918128 -0.04700922 1.69807854 -0.66367796 0.35227497 -0.36746386
[73] 1.44551817 -1.49030512 0.73588567 -1.33028833 -0.95906062 0.20638389
[79] -0.99543385 -0.29518622 -0.34505517 -0.97312320 -0.22069612 -1.27226076
[85] -0.51440416 -0.09535646 -0.03058337 -1.29014905 -0.03541041 0.15736115
[91] 0.58971868 1.33622224 -0.01729363 -1.47113829 1.13744142 -2.90909497
[97] 1.18918308 0.98615083 -2.10114033 -0.76713942
> 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] 0.40689847 3.14130910 0.37177278 0.40286302 -2.88494724 1.01096647
[7] 2.88372492 -0.03806166 -1.43085934 1.15090072 1.00585718 -0.09967717
[13] 1.89245355 1.43803706 -0.63336487 0.86692571 1.92400365 0.67485310
[19] 0.78877369 0.08896871 0.85994494 1.77657216 -0.34488670 0.44291040
[25] -0.02026313 0.38552475 0.46991006 1.61154722 -0.10408419 0.62007271
[31] 0.80989919 -1.55405363 0.31835491 0.35517210 -0.57310879 2.29331309
[37] -0.11535740 0.36694618 0.72306683 -0.40315416 -0.22942879 -0.89888377
[43] 1.48380708 -1.59176290 0.97138821 -0.19388787 0.35171021 -0.99889251
[49] 1.37291399 -0.18549150 -0.39439091 -0.44831073 0.37146180 0.73748020
[55] -1.53849619 -0.68539479 1.56568615 0.07389661 -1.35484292 0.90551941
[61] -0.42942941 -0.79086432 -0.39444144 0.31801490 0.71367187 0.95586420
[67] -1.24918128 -0.04700922 1.69807854 -0.66367796 0.35227497 -0.36746386
[73] 1.44551817 -1.49030512 0.73588567 -1.33028833 -0.95906062 0.20638389
[79] -0.99543385 -0.29518622 -0.34505517 -0.97312320 -0.22069612 -1.27226076
[85] -0.51440416 -0.09535646 -0.03058337 -1.29014905 -0.03541041 0.15736115
[91] 0.58971868 1.33622224 -0.01729363 -1.47113829 1.13744142 -2.90909497
[97] 1.18918308 0.98615083 -2.10114033 -0.76713942
> colMin(tmp)
[1] 0.40689847 3.14130910 0.37177278 0.40286302 -2.88494724 1.01096647
[7] 2.88372492 -0.03806166 -1.43085934 1.15090072 1.00585718 -0.09967717
[13] 1.89245355 1.43803706 -0.63336487 0.86692571 1.92400365 0.67485310
[19] 0.78877369 0.08896871 0.85994494 1.77657216 -0.34488670 0.44291040
[25] -0.02026313 0.38552475 0.46991006 1.61154722 -0.10408419 0.62007271
[31] 0.80989919 -1.55405363 0.31835491 0.35517210 -0.57310879 2.29331309
[37] -0.11535740 0.36694618 0.72306683 -0.40315416 -0.22942879 -0.89888377
[43] 1.48380708 -1.59176290 0.97138821 -0.19388787 0.35171021 -0.99889251
[49] 1.37291399 -0.18549150 -0.39439091 -0.44831073 0.37146180 0.73748020
[55] -1.53849619 -0.68539479 1.56568615 0.07389661 -1.35484292 0.90551941
[61] -0.42942941 -0.79086432 -0.39444144 0.31801490 0.71367187 0.95586420
[67] -1.24918128 -0.04700922 1.69807854 -0.66367796 0.35227497 -0.36746386
[73] 1.44551817 -1.49030512 0.73588567 -1.33028833 -0.95906062 0.20638389
[79] -0.99543385 -0.29518622 -0.34505517 -0.97312320 -0.22069612 -1.27226076
[85] -0.51440416 -0.09535646 -0.03058337 -1.29014905 -0.03541041 0.15736115
[91] 0.58971868 1.33622224 -0.01729363 -1.47113829 1.13744142 -2.90909497
[97] 1.18918308 0.98615083 -2.10114033 -0.76713942
> colMedians(tmp)
[1] 0.40689847 3.14130910 0.37177278 0.40286302 -2.88494724 1.01096647
[7] 2.88372492 -0.03806166 -1.43085934 1.15090072 1.00585718 -0.09967717
[13] 1.89245355 1.43803706 -0.63336487 0.86692571 1.92400365 0.67485310
[19] 0.78877369 0.08896871 0.85994494 1.77657216 -0.34488670 0.44291040
[25] -0.02026313 0.38552475 0.46991006 1.61154722 -0.10408419 0.62007271
[31] 0.80989919 -1.55405363 0.31835491 0.35517210 -0.57310879 2.29331309
[37] -0.11535740 0.36694618 0.72306683 -0.40315416 -0.22942879 -0.89888377
[43] 1.48380708 -1.59176290 0.97138821 -0.19388787 0.35171021 -0.99889251
[49] 1.37291399 -0.18549150 -0.39439091 -0.44831073 0.37146180 0.73748020
[55] -1.53849619 -0.68539479 1.56568615 0.07389661 -1.35484292 0.90551941
[61] -0.42942941 -0.79086432 -0.39444144 0.31801490 0.71367187 0.95586420
[67] -1.24918128 -0.04700922 1.69807854 -0.66367796 0.35227497 -0.36746386
[73] 1.44551817 -1.49030512 0.73588567 -1.33028833 -0.95906062 0.20638389
[79] -0.99543385 -0.29518622 -0.34505517 -0.97312320 -0.22069612 -1.27226076
[85] -0.51440416 -0.09535646 -0.03058337 -1.29014905 -0.03541041 0.15736115
[91] 0.58971868 1.33622224 -0.01729363 -1.47113829 1.13744142 -2.90909497
[97] 1.18918308 0.98615083 -2.10114033 -0.76713942
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.4068985 3.141309 0.3717728 0.402863 -2.884947 1.010966 2.883725
[2,] 0.4068985 3.141309 0.3717728 0.402863 -2.884947 1.010966 2.883725
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.03806166 -1.430859 1.150901 1.005857 -0.09967717 1.892454 1.438037
[2,] -0.03806166 -1.430859 1.150901 1.005857 -0.09967717 1.892454 1.438037
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.6333649 0.8669257 1.924004 0.6748531 0.7887737 0.08896871 0.8599449
[2,] -0.6333649 0.8669257 1.924004 0.6748531 0.7887737 0.08896871 0.8599449
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.776572 -0.3448867 0.4429104 -0.02026313 0.3855248 0.4699101 1.611547
[2,] 1.776572 -0.3448867 0.4429104 -0.02026313 0.3855248 0.4699101 1.611547
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.1040842 0.6200727 0.8098992 -1.554054 0.3183549 0.3551721 -0.5731088
[2,] -0.1040842 0.6200727 0.8098992 -1.554054 0.3183549 0.3551721 -0.5731088
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 2.293313 -0.1153574 0.3669462 0.7230668 -0.4031542 -0.2294288 -0.8988838
[2,] 2.293313 -0.1153574 0.3669462 0.7230668 -0.4031542 -0.2294288 -0.8988838
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 1.483807 -1.591763 0.9713882 -0.1938879 0.3517102 -0.9988925 1.372914
[2,] 1.483807 -1.591763 0.9713882 -0.1938879 0.3517102 -0.9988925 1.372914
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.1854915 -0.3943909 -0.4483107 0.3714618 0.7374802 -1.538496 -0.6853948
[2,] -0.1854915 -0.3943909 -0.4483107 0.3714618 0.7374802 -1.538496 -0.6853948
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 1.565686 0.07389661 -1.354843 0.9055194 -0.4294294 -0.7908643 -0.3944414
[2,] 1.565686 0.07389661 -1.354843 0.9055194 -0.4294294 -0.7908643 -0.3944414
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.3180149 0.7136719 0.9558642 -1.249181 -0.04700922 1.698079 -0.663678
[2,] 0.3180149 0.7136719 0.9558642 -1.249181 -0.04700922 1.698079 -0.663678
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.352275 -0.3674639 1.445518 -1.490305 0.7358857 -1.330288 -0.9590606
[2,] 0.352275 -0.3674639 1.445518 -1.490305 0.7358857 -1.330288 -0.9590606
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.2063839 -0.9954338 -0.2951862 -0.3450552 -0.9731232 -0.2206961 -1.272261
[2,] 0.2063839 -0.9954338 -0.2951862 -0.3450552 -0.9731232 -0.2206961 -1.272261
[,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.5144042 -0.09535646 -0.03058337 -1.290149 -0.03541041 0.1573612
[2,] -0.5144042 -0.09535646 -0.03058337 -1.290149 -0.03541041 0.1573612
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 0.5897187 1.336222 -0.01729363 -1.471138 1.137441 -2.909095 1.189183
[2,] 0.5897187 1.336222 -0.01729363 -1.471138 1.137441 -2.909095 1.189183
[,98] [,99] [,100]
[1,] 0.9861508 -2.10114 -0.7671394
[2,] 0.9861508 -2.10114 -0.7671394
>
>
> Max(tmp2)
[1] 2.359761
> Min(tmp2)
[1] -2.743123
> mean(tmp2)
[1] 0.003968145
> Sum(tmp2)
[1] 0.3968145
> Var(tmp2)
[1] 0.9588095
>
> rowMeans(tmp2)
[1] -0.53448240 -2.74312330 -1.27089452 -0.54623810 0.36864555 -1.08888574
[7] 0.82121137 0.42899906 -0.53719301 0.62897778 -0.90525670 -0.23549201
[13] 1.08734827 0.67302062 1.11586801 -1.73188444 -0.77300508 -1.22061129
[19] -1.40583242 1.02237693 -0.48665579 -0.61083740 0.81057631 -0.31967085
[25] -1.27096358 -1.87908466 0.33802706 -1.16437112 -0.80957879 -0.74424124
[31] -0.39915935 1.28569794 -0.88054261 2.35976144 -1.05639921 0.24566596
[37] 0.20844185 0.73118544 0.57133587 1.02779413 0.88518707 1.02125361
[43] -0.14509804 -0.02814121 -1.07684982 0.96375589 -1.55291964 0.28647627
[49] -0.22588939 1.12168147 0.79655816 0.79655666 0.11806717 1.50597049
[55] -0.22661203 1.27561727 0.94827610 0.49410662 0.37685646 -0.31149404
[61] 0.51343727 1.15931624 -0.72148743 0.09375604 0.33098935 0.41535074
[67] -0.31328896 0.19847565 0.82303604 -0.82572160 -2.04101943 0.67547996
[73] 0.32574972 -1.24202097 -0.14694885 0.70161960 -1.36336903 -0.53837879
[79] -0.12836839 -0.02503965 -0.41927502 -0.56859402 1.61850875 1.11569397
[85] -0.54456212 -1.29232080 0.91672527 1.05538737 -0.85546343 -1.08205960
[91] -1.43259329 0.69671836 0.32366040 0.39094312 1.76718350 0.79387261
[97] 1.18356359 0.34372823 1.67118732 -1.31094628
> rowSums(tmp2)
[1] -0.53448240 -2.74312330 -1.27089452 -0.54623810 0.36864555 -1.08888574
[7] 0.82121137 0.42899906 -0.53719301 0.62897778 -0.90525670 -0.23549201
[13] 1.08734827 0.67302062 1.11586801 -1.73188444 -0.77300508 -1.22061129
[19] -1.40583242 1.02237693 -0.48665579 -0.61083740 0.81057631 -0.31967085
[25] -1.27096358 -1.87908466 0.33802706 -1.16437112 -0.80957879 -0.74424124
[31] -0.39915935 1.28569794 -0.88054261 2.35976144 -1.05639921 0.24566596
[37] 0.20844185 0.73118544 0.57133587 1.02779413 0.88518707 1.02125361
[43] -0.14509804 -0.02814121 -1.07684982 0.96375589 -1.55291964 0.28647627
[49] -0.22588939 1.12168147 0.79655816 0.79655666 0.11806717 1.50597049
[55] -0.22661203 1.27561727 0.94827610 0.49410662 0.37685646 -0.31149404
[61] 0.51343727 1.15931624 -0.72148743 0.09375604 0.33098935 0.41535074
[67] -0.31328896 0.19847565 0.82303604 -0.82572160 -2.04101943 0.67547996
[73] 0.32574972 -1.24202097 -0.14694885 0.70161960 -1.36336903 -0.53837879
[79] -0.12836839 -0.02503965 -0.41927502 -0.56859402 1.61850875 1.11569397
[85] -0.54456212 -1.29232080 0.91672527 1.05538737 -0.85546343 -1.08205960
[91] -1.43259329 0.69671836 0.32366040 0.39094312 1.76718350 0.79387261
[97] 1.18356359 0.34372823 1.67118732 -1.31094628
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] -0.53448240 -2.74312330 -1.27089452 -0.54623810 0.36864555 -1.08888574
[7] 0.82121137 0.42899906 -0.53719301 0.62897778 -0.90525670 -0.23549201
[13] 1.08734827 0.67302062 1.11586801 -1.73188444 -0.77300508 -1.22061129
[19] -1.40583242 1.02237693 -0.48665579 -0.61083740 0.81057631 -0.31967085
[25] -1.27096358 -1.87908466 0.33802706 -1.16437112 -0.80957879 -0.74424124
[31] -0.39915935 1.28569794 -0.88054261 2.35976144 -1.05639921 0.24566596
[37] 0.20844185 0.73118544 0.57133587 1.02779413 0.88518707 1.02125361
[43] -0.14509804 -0.02814121 -1.07684982 0.96375589 -1.55291964 0.28647627
[49] -0.22588939 1.12168147 0.79655816 0.79655666 0.11806717 1.50597049
[55] -0.22661203 1.27561727 0.94827610 0.49410662 0.37685646 -0.31149404
[61] 0.51343727 1.15931624 -0.72148743 0.09375604 0.33098935 0.41535074
[67] -0.31328896 0.19847565 0.82303604 -0.82572160 -2.04101943 0.67547996
[73] 0.32574972 -1.24202097 -0.14694885 0.70161960 -1.36336903 -0.53837879
[79] -0.12836839 -0.02503965 -0.41927502 -0.56859402 1.61850875 1.11569397
[85] -0.54456212 -1.29232080 0.91672527 1.05538737 -0.85546343 -1.08205960
[91] -1.43259329 0.69671836 0.32366040 0.39094312 1.76718350 0.79387261
[97] 1.18356359 0.34372823 1.67118732 -1.31094628
> rowMin(tmp2)
[1] -0.53448240 -2.74312330 -1.27089452 -0.54623810 0.36864555 -1.08888574
[7] 0.82121137 0.42899906 -0.53719301 0.62897778 -0.90525670 -0.23549201
[13] 1.08734827 0.67302062 1.11586801 -1.73188444 -0.77300508 -1.22061129
[19] -1.40583242 1.02237693 -0.48665579 -0.61083740 0.81057631 -0.31967085
[25] -1.27096358 -1.87908466 0.33802706 -1.16437112 -0.80957879 -0.74424124
[31] -0.39915935 1.28569794 -0.88054261 2.35976144 -1.05639921 0.24566596
[37] 0.20844185 0.73118544 0.57133587 1.02779413 0.88518707 1.02125361
[43] -0.14509804 -0.02814121 -1.07684982 0.96375589 -1.55291964 0.28647627
[49] -0.22588939 1.12168147 0.79655816 0.79655666 0.11806717 1.50597049
[55] -0.22661203 1.27561727 0.94827610 0.49410662 0.37685646 -0.31149404
[61] 0.51343727 1.15931624 -0.72148743 0.09375604 0.33098935 0.41535074
[67] -0.31328896 0.19847565 0.82303604 -0.82572160 -2.04101943 0.67547996
[73] 0.32574972 -1.24202097 -0.14694885 0.70161960 -1.36336903 -0.53837879
[79] -0.12836839 -0.02503965 -0.41927502 -0.56859402 1.61850875 1.11569397
[85] -0.54456212 -1.29232080 0.91672527 1.05538737 -0.85546343 -1.08205960
[91] -1.43259329 0.69671836 0.32366040 0.39094312 1.76718350 0.79387261
[97] 1.18356359 0.34372823 1.67118732 -1.31094628
>
> colMeans(tmp2)
[1] 0.003968145
> colSums(tmp2)
[1] 0.3968145
> colVars(tmp2)
[1] 0.9588095
> colSd(tmp2)
[1] 0.9791882
> colMax(tmp2)
[1] 2.359761
> colMin(tmp2)
[1] -2.743123
> colMedians(tmp2)
[1] 0.1582714
> colRanges(tmp2)
[,1]
[1,] -2.743123
[2,] 2.359761
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.038143036 2.161608160 -0.817783792 -0.996737635 2.138312239
[6] -5.929546901 -3.927887277 -0.136093299 0.001489514 1.925548005
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8783600
[2,] -0.8540888
[3,] -0.1429356
[4,] 0.6851394
[5,] 1.3414105
>
> rowApply(tmp,sum)
[1] 0.7311486 1.7977133 -1.3897499 -4.1465524 2.0451338 -7.1170069
[7] 3.6627986 -2.3264926 3.4398054 -4.3160318
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 10 7 3 2 5 6 9 7 1
[2,] 9 8 3 2 5 2 10 7 10 4
[3,] 7 1 2 9 6 9 5 4 6 10
[4,] 10 7 6 1 7 6 3 8 1 5
[5,] 2 6 10 5 8 3 9 1 9 6
[6,] 4 4 1 10 3 1 1 5 4 8
[7,] 8 2 5 7 1 7 2 2 2 9
[8,] 3 9 9 6 4 4 4 10 8 2
[9,] 5 3 8 4 9 8 8 6 3 3
[10,] 6 5 4 8 10 10 7 3 5 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.01375341 -2.03407945 -3.08390967 -4.21884682 0.39271919 -0.44275355
[7] 1.62653092 0.70974219 3.20220117 0.23537118 -1.00361615 -0.73275435
[13] 1.14228498 -0.50005568 -6.75144895 0.78132441 0.20576030 -0.32238008
[19] 0.75259137 2.22602037
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.15851804
[2,] -0.49723436
[3,] -0.34385002
[4,] 0.01999221
[5,] 1.99336362
>
> rowApply(tmp,sum)
[1] 7.3157041 -5.6007415 -5.7179356 0.9482491 -4.7468213
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 19 2 9 6 14
[2,] 6 4 4 11 9
[3,] 4 17 10 7 2
[4,] 13 20 2 1 7
[5,] 5 16 18 9 16
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.99336362 0.09993282 -0.9989919 0.6373741 -0.45235808 0.1406867
[2,] -1.15851804 -0.82165449 0.2979459 0.8119383 0.27029541 0.1510893
[3,] -0.34385002 -1.14184097 -0.2595696 -2.3983053 0.39658995 -0.1375246
[4,] -0.49723436 0.16326413 -0.4665397 -2.8895248 -0.08102237 -0.8620591
[5,] 0.01999221 -0.33378095 -1.6567544 -0.3803291 0.25921428 0.2650542
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.58928561 0.34573648 2.0184733 1.2355836 0.6058366 1.3889274
[2,] -0.28188776 -0.71946419 -0.6355012 -0.7053920 0.5775640 -1.3777841
[3,] -0.43143378 -0.62882966 -0.7850842 -0.1342459 -1.2200479 0.2927464
[4,] 1.78719391 1.79702702 1.6392974 0.1410784 0.2795518 -0.6290275
[5,] -0.03662707 -0.08472746 0.9650159 -0.3016529 -1.2465206 -0.4076166
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.6541298 -1.2838001 -1.7005363 0.48480376 0.7845461 -1.0242431
[2,] 0.1985294 0.4571766 -0.7776120 0.08247832 -0.8226617 -0.2323745
[3,] 0.2767239 1.1790086 -2.5485488 -0.19294115 -0.9294236 0.1818759
[4,] 0.3166795 -0.5169824 -0.9714813 0.95729714 -0.1047837 0.5337654
[5,] -0.3037776 -0.3354585 -0.7532705 -0.55031366 1.2780831 0.2185963
[,19] [,20]
[1,] 0.3971158 1.3998378
[2,] -0.7508901 -0.1640185
[3,] 0.1886844 2.9180807
[4,] 0.1684590 0.1832908
[5,] 0.7492223 -2.1111704
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 650 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 563 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.979714 1.973115 -0.7371795 -0.3282628 0.2607989 1.17419 1.087823
col8 col9 col10 col11 col12 col13 col14
row1 1.335119 -2.137027 0.3482812 -1.938213 1.485487 1.319329 0.09749017
col15 col16 col17 col18 col19 col20
row1 -0.3699238 -1.3512 -2.046831 -0.7357016 -0.9389319 0.6120565
> tmp[,"col10"]
col10
row1 0.3482812
row2 -0.9739796
row3 1.0277144
row4 -0.4286561
row5 -0.2992001
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.9797140 1.973115 -0.7371795 -0.32826281 0.2607989 1.17419 1.0878235
row5 0.6009639 -1.690591 -0.9910759 0.09794024 -0.1069211 1.05800 -0.7451568
col8 col9 col10 col11 col12 col13
row1 1.3351188 -2.1370274 0.3482812 -1.9382128 1.4854869 1.31932945
row5 -0.0379285 0.1734519 -0.2992001 0.5517953 -0.9333287 0.03319928
col14 col15 col16 col17 col18 col19
row1 0.09749017 -0.3699238 -1.3512003 -2.04683085 -0.7357016 -0.9389319
row5 0.17502872 0.3275003 0.6859483 0.01006674 -1.4857541 -1.0469115
col20
row1 0.6120565
row5 0.1177354
> tmp[,c("col6","col20")]
col6 col20
row1 1.1741899 0.6120565
row2 -0.2877931 -1.2638454
row3 2.0316783 0.2353746
row4 -1.4635415 0.7780192
row5 1.0579999 0.1177354
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.17419 0.6120565
row5 1.05800 0.1177354
>
>
>
>
> 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 48.9814 52.36711 50.26893 49.94581 50.99643 106.1677 51.08372 51.30958
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.57378 48.97241 50.80322 49.25809 49.21714 49.48074 52.05422 50.75067
col17 col18 col19 col20
row1 48.02748 49.81941 50.66643 106.2919
> tmp[,"col10"]
col10
row1 48.97241
row2 29.21559
row3 30.79496
row4 29.65719
row5 51.83076
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.98140 52.36711 50.26893 49.94581 50.99643 106.1677 51.08372 51.30958
row5 50.03095 50.44214 48.03592 52.19535 50.29021 106.2645 49.84543 51.41729
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.57378 48.97241 50.80322 49.25809 49.21714 49.48074 52.05422 50.75067
row5 50.45594 51.83076 49.02164 49.15850 48.52205 48.34297 50.21235 48.98133
col17 col18 col19 col20
row1 48.02748 49.81941 50.66643 106.2919
row5 48.30820 50.14147 51.22460 104.5908
> tmp[,c("col6","col20")]
col6 col20
row1 106.16772 106.29186
row2 74.40871 75.18579
row3 74.66469 75.37388
row4 77.12125 73.52647
row5 106.26447 104.59077
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.1677 106.2919
row5 106.2645 104.5908
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.1677 106.2919
row5 106.2645 104.5908
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.74244262
[2,] -0.65871528
[3,] 0.07540238
[4,] -1.53883117
[5,] 1.68791111
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.9193061 0.2893267
[2,] -0.6279261 0.5909574
[3,] 0.1288984 -0.1470679
[4,] 0.2878357 1.2746990
[5,] 1.4257696 0.3352009
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.0498677 0.6602365
[2,] 1.2219473 0.7269425
[3,] -0.3618195 0.2911228
[4,] 0.3390302 0.4956325
[5,] -0.1480620 -1.2805062
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.0498677
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.0498677
[2,] 1.2219473
>
>
>
> 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 0.3098337 2.5323301 0.5784456 -0.8061145 -1.170465 -0.4354838 -1.3793180
row1 -1.9183093 0.4947287 -1.2032003 1.4416927 -1.263639 -0.6198482 -0.3862111
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -1.5965776 -1.632826 0.9842295 0.05821965 -0.2936825 -0.8491813 1.57101544
row1 -0.4816127 -0.521626 0.6071731 0.94153718 0.9575735 0.6638517 0.09037622
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.4561473 -1.683320 1.3303420 0.4237737 -1.0755468 -0.276591
row1 -2.0388534 2.100311 -0.3151348 0.2466855 0.5332375 1.138681
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.1939987 0.2782809 -0.9486304 1.793609 0.6831086 0.3317293 -0.8197682
[,8] [,9] [,10]
row2 -0.1309485 1.750543 -0.08181413
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.3767914 -0.1506564 -0.6498068 -1.218852 1.224166 -0.1568856 -0.4890611
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.235136 0.08086852 -0.2452088 0.7595766 -0.8584444 0.1833478 -0.08789639
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.003812388 0.784022 1.354252 0.1750641 0.3803504 -0.449938
>
>
> 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: 0x600002c48060>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM15006b1c0374"
[2] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM15007c26eb9b"
[3] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM15005f364cca"
[4] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM150065eb929b"
[5] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM15004ce63263"
[6] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM15001cf62906"
[7] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM150064ff57c4"
[8] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM150037db38a9"
[9] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM15001964fbe5"
[10] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM150034d58469"
[11] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM15002de82498"
[12] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM150063ba8eb3"
[13] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM15006ceebceb"
[14] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM15002db5202c"
[15] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM15004e534025"
>
>
> ### 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: 0x600002cc8060>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600002cc8060>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600002cc8060>
> rowMedians(tmp)
[1] -0.235145362 -0.345760858 0.390279398 -0.053457202 0.028038936
[6] -0.191944706 -0.099564952 0.316895837 -0.619848571 0.081577064
[11] 0.604906113 -0.395413124 0.286570232 0.003380058 -0.275766738
[16] -0.121932003 -0.252299512 -0.442360646 0.066397429 0.087645178
[21] 0.269442777 0.246730984 0.350754406 -0.205144616 -0.034117906
[26] -0.048985123 -0.342491648 0.074440321 0.086890397 0.455620636
[31] -0.105510451 0.104541636 0.574730077 0.140992498 0.359709943
[36] -0.077518481 0.013420022 -0.326646159 -0.110323172 -0.101151497
[41] -0.474066217 0.115029260 0.086079871 -0.489167114 0.142438033
[46] -0.199024197 -0.072372220 -0.052776793 0.037624731 -0.624840691
[51] -0.241620527 -0.216705278 0.211637233 -0.651591396 -0.192220624
[56] 0.279727845 0.095211488 -0.231010832 -0.461478440 -0.474864036
[61] -0.039031519 -0.426739387 -0.454005145 0.376618219 -0.192694974
[66] -0.259842821 0.057601530 0.108120449 -0.300747016 -0.298531983
[71] -0.027643135 -0.543268966 -0.441836003 -0.049161733 -0.181528486
[76] -0.397531759 -0.645917329 0.179494367 -0.027469098 -0.075026814
[81] -0.106183325 0.477352495 -0.319672303 -0.173439051 -0.365183781
[86] -0.187570503 -0.537867566 0.407613479 0.275103468 0.661960585
[91] -0.361572185 0.015041652 -0.149365544 0.047466570 -0.130294384
[96] -0.561608575 -0.033400161 0.515023464 0.255063104 -0.206434372
[101] 0.722451798 -0.060260661 -0.339619642 -0.558945346 0.394536525
[106] 0.084683507 0.305601442 0.110515373 -0.238091311 -0.818069755
[111] -0.150591252 -0.348737473 0.084722545 -0.157296842 -0.554693605
[116] 0.630963516 0.757241579 0.062039352 0.333300139 -0.571484691
[121] -0.017717510 0.015756689 0.194078459 -0.296184456 0.196086221
[126] 0.615521450 -0.002636320 -0.296561556 0.040121310 0.097174619
[131] 0.519323728 -0.594616038 -0.580028420 -0.165933919 0.119816923
[136] 0.817962825 0.018409654 -0.436082296 0.091651888 0.020762553
[141] -0.808438873 -0.060065291 -0.413432148 -0.288336769 -0.252320402
[146] 0.287724021 0.494186378 -0.089113265 0.066894686 -0.183574494
[151] 0.805328511 -0.058199509 -0.110821956 0.002795709 0.257519543
[156] 0.121271553 0.124521952 0.133754731 0.576588841 0.551424099
[161] -0.205973186 0.683787923 -0.572910198 -0.482241040 0.214365104
[166] 0.125321677 -0.165864785 0.422739435 -0.477110942 0.303371823
[171] -0.120740065 -0.234295227 0.043015439 -0.422262621 0.500805792
[176] 0.125366302 0.117008360 0.307428896 -0.075713004 -0.280806213
[181] 0.288920790 -0.557798816 0.137413820 0.049764664 0.415589212
[186] -0.022369039 -0.025057276 -0.051106624 0.278460341 -0.058365348
[191] 0.282401347 -0.452247678 0.512863042 -0.186117500 0.170179607
[196] -0.071546788 -0.385093622 -0.611244954 0.308578958 -0.511793020
[201] -0.199976060 0.288454251 -0.576494135 -0.150752503 0.208601020
[206] -0.166129900 0.646647320 0.905396138 -0.144203140 0.376572415
[211] 0.471771257 -0.025691748 -0.365090616 -0.049954663 -0.194816395
[216] -0.172351766 0.070906433 0.235283525 0.349388874 0.043161041
[221] 0.383387008 0.003545751 0.780093238 -0.582146384 0.195205944
[226] -0.079625572 0.403832412 -0.043769905 -0.085213170 0.458583957
>
> proc.time()
user system elapsed
2.739 15.279 20.501
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x600001104180>
> .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: 0x600001104180>
> .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: 0x600001104180>
> .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: 0x600001104180>
> 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: 0x600001144000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001144000>
> .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: 0x600001144000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001144000>
> .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: 0x600001144000>
> 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: 0x600001140000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001140000>
> .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: 0x600001140000>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600001140000>
> .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: 0x600001140000>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600001140000>
> .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: 0x600001140000>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600001140000>
> .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: 0x600001140000>
> 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: 0x60000114c060>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x60000114c060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000114c060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000114c060>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1d3943d1c0f" "BufferedMatrixFile1d3947fd1ef5"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1d3943d1c0f" "BufferedMatrixFile1d3947fd1ef5"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000114c300>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000114c300>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x60000114c300>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x60000114c300>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x60000114c300>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x60000114c300>
> .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: 0x600001148000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001148000>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600001148000>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600001148000>
> 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: 0x600001150000>
> .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: 0x600001150000>
> rm(P)
>
> proc.time()
user system elapsed
0.334 0.149 0.508
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
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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
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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
0.362 0.102 0.471