| Back to Multiple platform build/check report for BioC 3.18: simplified long |
|
This page was generated on 2023-11-02 11:40:29 -0400 (Thu, 02 Nov 2023).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 22.04.2 LTS) | x86_64 | 4.3.1 (2023-06-16) -- "Beagle Scouts" | 4729 |
| palomino4 | Windows Server 2022 Datacenter | x64 | 4.3.1 (2023-06-16 ucrt) -- "Beagle Scouts" | 4463 |
| lconway | macOS 12.6.5 Monterey | x86_64 | 4.3.1 Patched (2023-06-17 r84564) -- "Beagle Scouts" | 4478 |
| kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | 4.3.1 (2023-06-16) -- "Beagle Scouts" | 4464 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 246/2266 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.66.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 22.04.2 LTS) / x86_64 | OK | OK | OK |  | ||||||||
| palomino4 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.6.5 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.1 Ventura / arm64 | see weekly results here | ||||||||||||
| kunpeng2 | Linux (openEuler 22.03 LTS-SP1) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. - See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host. |
| Package: BufferedMatrix |
| Version: 1.66.0 |
| Command: /home/biocbuild/R/R-4.3.1/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R-4.3.1/site-library --no-vignettes --timings BufferedMatrix_1.66.0.tar.gz |
| StartedAt: 2023-11-02 08:55:12 -0000 (Thu, 02 Nov 2023) |
| EndedAt: 2023-11-02 08:55:38 -0000 (Thu, 02 Nov 2023) |
| EllapsedTime: 25.9 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/R/R-4.3.1/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R-4.3.1/site-library --no-vignettes --timings BufferedMatrix_1.66.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.3.1 (2023-06-16)
* using platform: aarch64-unknown-linux-gnu (64-bit)
* R was compiled by
gcc (GCC) 10.3.1
GNU Fortran (GCC) 10.3.1
* running under: openEuler 22.03 (LTS-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.66.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘gcc (GCC) 10.3.1’
* 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 loading without being on the library search path ... 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 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: 2 NOTEs
See
‘/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/R/R-4.3.1/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/R/R-4.3.1/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘gcc (GCC) 10.3.1’
gcc -I"/home/biocbuild/R/R-4.3.1/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/R/R-4.3.1/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
gcc -I"/home/biocbuild/R/R-4.3.1/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"/home/biocbuild/R/R-4.3.1/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -c init_package.c -o init_package.o
gcc -shared -L/home/biocbuild/R/R-4.3.1/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/R/R-4.3.1/lib -lR
installing to /home/biocbuild/R/R-4.3.1/site-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: aarch64-unknown-linux-gnu (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
0.282 0.062 0.333
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: aarch64-unknown-linux-gnu (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] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 457529 24.5 981817 52.5 650817 34.8
Vcells 842781 6.5 8388608 64.0 2061648 15.8
>
>
>
>
> ##
> ## 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 Nov 2 08:55:33 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] "Thu Nov 2 08:55:33 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: 0x281ca990>
>
>
>
> 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 Nov 2 08:55:33 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] "Thu Nov 2 08:55:33 2023"
>
> ColMode(tmp2)
<pointer: 0x281ca990>
>
>
>
> ### 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,] 101.28790601 -0.6259419 0.9414516 -1.542804227
[2,] -1.22279566 -0.9313893 -0.1228438 -0.004749671
[3,] -0.97163912 0.1679657 -0.2808444 -1.994270518
[4,] -0.02047474 0.3248567 1.1847121 0.877797487
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.18-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,] 101.28790601 0.6259419 0.9414516 1.542804227
[2,] 1.22279566 0.9313893 0.1228438 0.004749671
[3,] 0.97163912 0.1679657 0.2808444 1.994270518
[4,] 0.02047474 0.3248567 1.1847121 0.877797487
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.18-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,] 10.0641893 0.7911649 0.9702843 1.24209671
[2,] 1.1058009 0.9650851 0.3504908 0.06891786
[3,] 0.9857176 0.4098362 0.5299476 1.41218643
[4,] 0.1430900 0.5699620 1.0884448 0.93690847
>
> 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: /home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 226.92980 33.53759 35.64429 38.96377
[2,] 37.28080 35.58224 28.62775 25.69393
[3,] 35.82881 29.26633 30.58032 41.11613
[4,] 26.45137 31.02448 37.06916 35.24688
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x2a5403b0>
> exp(tmp5)
<pointer: 0x2a5403b0>
> log(tmp5,2)
<pointer: 0x2a5403b0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 472.3246
> Min(tmp5)
[1] 53.07172
> mean(tmp5)
[1] 73.55093
> Sum(tmp5)
[1] 14710.19
> Var(tmp5)
[1] 882.4255
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.70104 70.26383 76.62032 70.02487 70.82077 70.99349 72.36721 70.12646
[9] 72.48297 70.10841
> rowSums(tmp5)
[1] 1834.021 1405.277 1532.406 1400.497 1416.415 1419.870 1447.344 1402.529
[9] 1449.659 1402.168
> rowVars(tmp5)
[1] 8112.07353 76.96892 100.81379 51.96296 61.49492 89.27246
[7] 82.86310 91.61933 64.95643 86.85219
> rowSd(tmp5)
[1] 90.067050 8.773193 10.040607 7.208534 7.841870 9.448411 9.102917
[8] 9.571799 8.059555 9.319452
> rowMax(tmp5)
[1] 472.32464 85.37343 93.10113 81.64525 94.52360 88.83559 89.95394
[8] 88.43887 86.56070 87.84751
> rowMin(tmp5)
[1] 53.63005 53.47855 57.99862 55.05507 59.38956 56.91226 57.12964 54.85703
[9] 60.17866 53.07172
>
> colMeans(tmp5)
[1] 110.07265 73.19591 71.52273 71.21972 73.46592 76.00074 72.13008
[8] 70.10991 69.10310 69.84416 72.22815 69.91670 71.53843 73.51444
[15] 71.05644 73.99607 72.21088 69.96939 67.91296 72.01031
> colSums(tmp5)
[1] 1100.7265 731.9591 715.2273 712.1972 734.6592 760.0074 721.3008
[8] 701.0991 691.0310 698.4416 722.2815 699.1670 715.3843 735.1444
[15] 710.5644 739.9607 722.1088 699.6939 679.1296 720.1031
> colVars(tmp5)
[1] 16272.00669 81.05939 86.08537 86.71638 85.94960 142.80051
[7] 103.39881 35.46751 84.74250 61.40759 78.59812 121.60880
[13] 38.56198 38.22649 67.72474 122.31525 58.25356 148.53325
[19] 60.54350 102.83610
> colSd(tmp5)
[1] 127.561776 9.003299 9.278220 9.312163 9.270901 11.949917
[7] 10.168520 5.955461 9.205569 7.836300 8.865558 11.027638
[13] 6.209829 6.182757 8.229504 11.059622 7.632402 12.187422
[19] 7.780970 10.140813
> colMax(tmp5)
[1] 472.32464 88.83559 89.95394 85.57785 86.56070 94.52360 93.10113
[8] 82.87379 80.25222 81.54388 85.95477 88.43887 82.58936 81.64525
[15] 80.23980 88.92625 84.18710 91.30518 79.15743 90.23761
> colMin(tmp5)
[1] 55.05507 60.91403 59.58491 53.47855 61.75872 57.12964 60.30322 64.58518
[9] 53.56938 56.91226 57.99862 53.07172 61.63352 61.45013 55.84547 54.85703
[17] 60.67851 53.63005 56.40549 56.50085
>
>
> ### 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] 91.70104 70.26383 76.62032 70.02487 70.82077 70.99349 72.36721 70.12646
[9] NA 70.10841
> rowSums(tmp5)
[1] 1834.021 1405.277 1532.406 1400.497 1416.415 1419.870 1447.344 1402.529
[9] NA 1402.168
> rowVars(tmp5)
[1] 8112.07353 76.96892 100.81379 51.96296 61.49492 89.27246
[7] 82.86310 91.61933 59.91816 86.85219
> rowSd(tmp5)
[1] 90.067050 8.773193 10.040607 7.208534 7.841870 9.448411 9.102917
[8] 9.571799 7.740682 9.319452
> rowMax(tmp5)
[1] 472.32464 85.37343 93.10113 81.64525 94.52360 88.83559 89.95394
[8] 88.43887 NA 87.84751
> rowMin(tmp5)
[1] 53.63005 53.47855 57.99862 55.05507 59.38956 56.91226 57.12964 54.85703
[9] NA 53.07172
>
> colMeans(tmp5)
[1] 110.07265 73.19591 71.52273 71.21972 73.46592 76.00074 72.13008
[8] 70.10991 69.10310 69.84416 72.22815 69.91670 71.53843 73.51444
[15] 71.05644 73.99607 72.21088 NA 67.91296 72.01031
> colSums(tmp5)
[1] 1100.7265 731.9591 715.2273 712.1972 734.6592 760.0074 721.3008
[8] 701.0991 691.0310 698.4416 722.2815 699.1670 715.3843 735.1444
[15] 710.5644 739.9607 722.1088 NA 679.1296 720.1031
> colVars(tmp5)
[1] 16272.00669 81.05939 86.08537 86.71638 85.94960 142.80051
[7] 103.39881 35.46751 84.74250 61.40759 78.59812 121.60880
[13] 38.56198 38.22649 67.72474 122.31525 58.25356 NA
[19] 60.54350 102.83610
> colSd(tmp5)
[1] 127.561776 9.003299 9.278220 9.312163 9.270901 11.949917
[7] 10.168520 5.955461 9.205569 7.836300 8.865558 11.027638
[13] 6.209829 6.182757 8.229504 11.059622 7.632402 NA
[19] 7.780970 10.140813
> colMax(tmp5)
[1] 472.32464 88.83559 89.95394 85.57785 86.56070 94.52360 93.10113
[8] 82.87379 80.25222 81.54388 85.95477 88.43887 82.58936 81.64525
[15] 80.23980 88.92625 84.18710 NA 79.15743 90.23761
> colMin(tmp5)
[1] 55.05507 60.91403 59.58491 53.47855 61.75872 57.12964 60.30322 64.58518
[9] 53.56938 56.91226 57.99862 53.07172 61.63352 61.45013 55.84547 54.85703
[17] 60.67851 NA 56.40549 56.50085
>
> Max(tmp5,na.rm=TRUE)
[1] 472.3246
> Min(tmp5,na.rm=TRUE)
[1] 53.07172
> mean(tmp5,na.rm=TRUE)
[1] 73.61741
> Sum(tmp5,na.rm=TRUE)
[1] 14649.86
> Var(tmp5,na.rm=TRUE)
[1] 885.994
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.70104 70.26383 76.62032 70.02487 70.82077 70.99349 72.36721 70.12646
[9] 73.12296 70.10841
> rowSums(tmp5,na.rm=TRUE)
[1] 1834.021 1405.277 1532.406 1400.497 1416.415 1419.870 1447.344 1402.529
[9] 1389.336 1402.168
> rowVars(tmp5,na.rm=TRUE)
[1] 8112.07353 76.96892 100.81379 51.96296 61.49492 89.27246
[7] 82.86310 91.61933 59.91816 86.85219
> rowSd(tmp5,na.rm=TRUE)
[1] 90.067050 8.773193 10.040607 7.208534 7.841870 9.448411 9.102917
[8] 9.571799 7.740682 9.319452
> rowMax(tmp5,na.rm=TRUE)
[1] 472.32464 85.37343 93.10113 81.64525 94.52360 88.83559 89.95394
[8] 88.43887 86.56070 87.84751
> rowMin(tmp5,na.rm=TRUE)
[1] 53.63005 53.47855 57.99862 55.05507 59.38956 56.91226 57.12964 54.85703
[9] 60.17866 53.07172
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.07265 73.19591 71.52273 71.21972 73.46592 76.00074 72.13008
[8] 70.10991 69.10310 69.84416 72.22815 69.91670 71.53843 73.51444
[15] 71.05644 73.99607 72.21088 71.04120 67.91296 72.01031
> colSums(tmp5,na.rm=TRUE)
[1] 1100.7265 731.9591 715.2273 712.1972 734.6592 760.0074 721.3008
[8] 701.0991 691.0310 698.4416 722.2815 699.1670 715.3843 735.1444
[15] 710.5644 739.9607 722.1088 639.3708 679.1296 720.1031
> colVars(tmp5,na.rm=TRUE)
[1] 16272.00669 81.05939 86.08537 86.71638 85.94960 142.80051
[7] 103.39881 35.46751 84.74250 61.40759 78.59812 121.60880
[13] 38.56198 38.22649 67.72474 122.31525 58.25356 154.17611
[19] 60.54350 102.83610
> colSd(tmp5,na.rm=TRUE)
[1] 127.561776 9.003299 9.278220 9.312163 9.270901 11.949917
[7] 10.168520 5.955461 9.205569 7.836300 8.865558 11.027638
[13] 6.209829 6.182757 8.229504 11.059622 7.632402 12.416767
[19] 7.780970 10.140813
> colMax(tmp5,na.rm=TRUE)
[1] 472.32464 88.83559 89.95394 85.57785 86.56070 94.52360 93.10113
[8] 82.87379 80.25222 81.54388 85.95477 88.43887 82.58936 81.64525
[15] 80.23980 88.92625 84.18710 91.30518 79.15743 90.23761
> colMin(tmp5,na.rm=TRUE)
[1] 55.05507 60.91403 59.58491 53.47855 61.75872 57.12964 60.30322 64.58518
[9] 53.56938 56.91226 57.99862 53.07172 61.63352 61.45013 55.84547 54.85703
[17] 60.67851 53.63005 56.40549 56.50085
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.70104 70.26383 76.62032 70.02487 70.82077 70.99349 72.36721 70.12646
[9] NaN 70.10841
> rowSums(tmp5,na.rm=TRUE)
[1] 1834.021 1405.277 1532.406 1400.497 1416.415 1419.870 1447.344 1402.529
[9] 0.000 1402.168
> rowVars(tmp5,na.rm=TRUE)
[1] 8112.07353 76.96892 100.81379 51.96296 61.49492 89.27246
[7] 82.86310 91.61933 NA 86.85219
> rowSd(tmp5,na.rm=TRUE)
[1] 90.067050 8.773193 10.040607 7.208534 7.841870 9.448411 9.102917
[8] 9.571799 NA 9.319452
> rowMax(tmp5,na.rm=TRUE)
[1] 472.32464 85.37343 93.10113 81.64525 94.52360 88.83559 89.95394
[8] 88.43887 NA 87.84751
> rowMin(tmp5,na.rm=TRUE)
[1] 53.63005 53.47855 57.99862 55.05507 59.38956 56.91226 57.12964 54.85703
[9] NA 53.07172
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.02829 73.18827 72.34851 72.06460 72.01094 76.99872 72.95177
[8] 69.48184 68.47975 70.91810 73.29535 68.99316 70.31055 73.68425
[15] 70.03607 73.05551 71.15705 NaN 67.35699 71.99104
> colSums(tmp5,na.rm=TRUE)
[1] 1026.2546 658.6944 651.1366 648.5814 648.0985 692.9885 656.5659
[8] 625.3365 616.3178 638.2629 659.6581 620.9385 632.7950 663.1583
[15] 630.3246 657.4996 640.4134 0.0000 606.2129 647.9194
> colVars(tmp5,na.rm=TRUE)
[1] 18129.97829 91.19116 89.17453 89.52548 72.87757 149.44593
[7] 108.72799 35.46312 90.96393 56.10830 75.61009 127.21450
[13] 26.42070 42.68039 64.47727 127.65223 53.04134 NA
[19] 64.63405 115.68644
> colSd(tmp5,na.rm=TRUE)
[1] 134.647608 9.549406 9.443227 9.461790 8.536836 12.224808
[7] 10.427271 5.955092 9.537501 7.490548 8.695406 11.278941
[13] 5.140107 6.533023 8.029774 11.298329 7.282948 NA
[19] 8.039531 10.755763
> colMax(tmp5,na.rm=TRUE)
[1] 472.32464 88.83559 89.95394 85.57785 85.37343 94.52360 93.10113
[8] 82.87379 80.25222 81.54388 85.95477 88.43887 79.24474 81.64525
[15] 79.77029 88.92625 84.18710 -Inf 79.15743 90.23761
> colMin(tmp5,na.rm=TRUE)
[1] 55.05507 60.91403 59.58491 53.47855 61.75872 57.12964 60.30322 64.58518
[9] 53.56938 56.91226 57.99862 53.07172 61.63352 61.45013 55.84547 54.85703
[17] 60.67851 Inf 56.40549 56.50085
>
>
>
>
> 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] 260.1337 179.9195 190.6077 171.1772 209.5510 359.5484 157.6151 315.7714
[9] 202.1509 304.8451
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 260.1337 179.9195 190.6077 171.1772 209.5510 359.5484 157.6151 315.7714
[9] 202.1509 304.8451
>
>
>
> 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] 0.000000e+00 -2.273737e-13 5.684342e-14 5.684342e-14 -5.684342e-14
[6] -1.421085e-14 2.842171e-14 8.526513e-14 5.684342e-14 -5.684342e-14
[11] -2.842171e-14 5.684342e-14 0.000000e+00 2.842171e-14 0.000000e+00
[16] 1.136868e-13 1.136868e-13 1.136868e-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)
+ }
8 3
10 14
10 16
3 13
8 17
4 15
6 17
9 6
4 7
10 2
3 18
4 2
2 15
9 14
9 7
3 17
3 20
6 4
4 10
2 14
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] 2.16193
> Min(tmp)
[1] -2.303883
> mean(tmp)
[1] 0.02748082
> Sum(tmp)
[1] 2.748082
> Var(tmp)
[1] 0.8469492
>
> rowMeans(tmp)
[1] 0.02748082
> rowSums(tmp)
[1] 2.748082
> rowVars(tmp)
[1] 0.8469492
> rowSd(tmp)
[1] 0.9202984
> rowMax(tmp)
[1] 2.16193
> rowMin(tmp)
[1] -2.303883
>
> colMeans(tmp)
[1] 0.44182961 -0.03476540 -0.58678839 -1.25015885 0.77923065 -0.97027371
[7] 0.05278601 -1.01565077 0.42382434 0.69347218 -0.83851422 -1.91923076
[13] -0.23156080 0.49260956 0.28379907 -0.09112402 -0.74729251 0.40891712
[19] 1.91389244 0.31414593 -0.03578916 1.57739245 -0.27875906 1.53996472
[25] -0.37246972 -0.60604168 0.89147073 0.36413514 0.50125947 1.81816781
[31] 0.42973042 1.16210103 -1.48731087 1.49869295 0.08517462 -0.18659299
[37] -0.06642323 -0.67508626 -1.79595102 -1.28246794 0.07134563 -0.86412190
[43] 0.16377002 0.48734710 1.45210962 -0.40965184 -0.71206594 -0.02553298
[49] -0.89094402 0.80226213 0.16514238 2.16192987 -1.62348766 0.14340935
[55] 0.50073246 1.56930262 -1.05248120 1.17596715 1.17986145 -0.14910411
[61] 0.18146874 -1.46416785 -0.14857276 -0.64270566 -0.31629621 -1.00305979
[67] 0.70053990 -1.43509019 1.69665435 -0.97255638 0.08476879 0.77790220
[73] -2.30388336 0.01335980 0.77614917 0.62439755 0.07250802 -0.68316334
[79] 1.32504893 -0.80195913 -0.76870310 -0.65813671 0.01858989 -0.03561010
[85] -0.45155724 0.02639805 0.96932154 0.96117539 0.59194361 0.45605975
[91] -0.65174178 1.47331430 -0.30867336 0.11986197 -0.62677620 -0.56624110
[97] 1.24373963 -0.27330112 -0.47444593 -0.12461310
> colSums(tmp)
[1] 0.44182961 -0.03476540 -0.58678839 -1.25015885 0.77923065 -0.97027371
[7] 0.05278601 -1.01565077 0.42382434 0.69347218 -0.83851422 -1.91923076
[13] -0.23156080 0.49260956 0.28379907 -0.09112402 -0.74729251 0.40891712
[19] 1.91389244 0.31414593 -0.03578916 1.57739245 -0.27875906 1.53996472
[25] -0.37246972 -0.60604168 0.89147073 0.36413514 0.50125947 1.81816781
[31] 0.42973042 1.16210103 -1.48731087 1.49869295 0.08517462 -0.18659299
[37] -0.06642323 -0.67508626 -1.79595102 -1.28246794 0.07134563 -0.86412190
[43] 0.16377002 0.48734710 1.45210962 -0.40965184 -0.71206594 -0.02553298
[49] -0.89094402 0.80226213 0.16514238 2.16192987 -1.62348766 0.14340935
[55] 0.50073246 1.56930262 -1.05248120 1.17596715 1.17986145 -0.14910411
[61] 0.18146874 -1.46416785 -0.14857276 -0.64270566 -0.31629621 -1.00305979
[67] 0.70053990 -1.43509019 1.69665435 -0.97255638 0.08476879 0.77790220
[73] -2.30388336 0.01335980 0.77614917 0.62439755 0.07250802 -0.68316334
[79] 1.32504893 -0.80195913 -0.76870310 -0.65813671 0.01858989 -0.03561010
[85] -0.45155724 0.02639805 0.96932154 0.96117539 0.59194361 0.45605975
[91] -0.65174178 1.47331430 -0.30867336 0.11986197 -0.62677620 -0.56624110
[97] 1.24373963 -0.27330112 -0.47444593 -0.12461310
> 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] 0.44182961 -0.03476540 -0.58678839 -1.25015885 0.77923065 -0.97027371
[7] 0.05278601 -1.01565077 0.42382434 0.69347218 -0.83851422 -1.91923076
[13] -0.23156080 0.49260956 0.28379907 -0.09112402 -0.74729251 0.40891712
[19] 1.91389244 0.31414593 -0.03578916 1.57739245 -0.27875906 1.53996472
[25] -0.37246972 -0.60604168 0.89147073 0.36413514 0.50125947 1.81816781
[31] 0.42973042 1.16210103 -1.48731087 1.49869295 0.08517462 -0.18659299
[37] -0.06642323 -0.67508626 -1.79595102 -1.28246794 0.07134563 -0.86412190
[43] 0.16377002 0.48734710 1.45210962 -0.40965184 -0.71206594 -0.02553298
[49] -0.89094402 0.80226213 0.16514238 2.16192987 -1.62348766 0.14340935
[55] 0.50073246 1.56930262 -1.05248120 1.17596715 1.17986145 -0.14910411
[61] 0.18146874 -1.46416785 -0.14857276 -0.64270566 -0.31629621 -1.00305979
[67] 0.70053990 -1.43509019 1.69665435 -0.97255638 0.08476879 0.77790220
[73] -2.30388336 0.01335980 0.77614917 0.62439755 0.07250802 -0.68316334
[79] 1.32504893 -0.80195913 -0.76870310 -0.65813671 0.01858989 -0.03561010
[85] -0.45155724 0.02639805 0.96932154 0.96117539 0.59194361 0.45605975
[91] -0.65174178 1.47331430 -0.30867336 0.11986197 -0.62677620 -0.56624110
[97] 1.24373963 -0.27330112 -0.47444593 -0.12461310
> colMin(tmp)
[1] 0.44182961 -0.03476540 -0.58678839 -1.25015885 0.77923065 -0.97027371
[7] 0.05278601 -1.01565077 0.42382434 0.69347218 -0.83851422 -1.91923076
[13] -0.23156080 0.49260956 0.28379907 -0.09112402 -0.74729251 0.40891712
[19] 1.91389244 0.31414593 -0.03578916 1.57739245 -0.27875906 1.53996472
[25] -0.37246972 -0.60604168 0.89147073 0.36413514 0.50125947 1.81816781
[31] 0.42973042 1.16210103 -1.48731087 1.49869295 0.08517462 -0.18659299
[37] -0.06642323 -0.67508626 -1.79595102 -1.28246794 0.07134563 -0.86412190
[43] 0.16377002 0.48734710 1.45210962 -0.40965184 -0.71206594 -0.02553298
[49] -0.89094402 0.80226213 0.16514238 2.16192987 -1.62348766 0.14340935
[55] 0.50073246 1.56930262 -1.05248120 1.17596715 1.17986145 -0.14910411
[61] 0.18146874 -1.46416785 -0.14857276 -0.64270566 -0.31629621 -1.00305979
[67] 0.70053990 -1.43509019 1.69665435 -0.97255638 0.08476879 0.77790220
[73] -2.30388336 0.01335980 0.77614917 0.62439755 0.07250802 -0.68316334
[79] 1.32504893 -0.80195913 -0.76870310 -0.65813671 0.01858989 -0.03561010
[85] -0.45155724 0.02639805 0.96932154 0.96117539 0.59194361 0.45605975
[91] -0.65174178 1.47331430 -0.30867336 0.11986197 -0.62677620 -0.56624110
[97] 1.24373963 -0.27330112 -0.47444593 -0.12461310
> colMedians(tmp)
[1] 0.44182961 -0.03476540 -0.58678839 -1.25015885 0.77923065 -0.97027371
[7] 0.05278601 -1.01565077 0.42382434 0.69347218 -0.83851422 -1.91923076
[13] -0.23156080 0.49260956 0.28379907 -0.09112402 -0.74729251 0.40891712
[19] 1.91389244 0.31414593 -0.03578916 1.57739245 -0.27875906 1.53996472
[25] -0.37246972 -0.60604168 0.89147073 0.36413514 0.50125947 1.81816781
[31] 0.42973042 1.16210103 -1.48731087 1.49869295 0.08517462 -0.18659299
[37] -0.06642323 -0.67508626 -1.79595102 -1.28246794 0.07134563 -0.86412190
[43] 0.16377002 0.48734710 1.45210962 -0.40965184 -0.71206594 -0.02553298
[49] -0.89094402 0.80226213 0.16514238 2.16192987 -1.62348766 0.14340935
[55] 0.50073246 1.56930262 -1.05248120 1.17596715 1.17986145 -0.14910411
[61] 0.18146874 -1.46416785 -0.14857276 -0.64270566 -0.31629621 -1.00305979
[67] 0.70053990 -1.43509019 1.69665435 -0.97255638 0.08476879 0.77790220
[73] -2.30388336 0.01335980 0.77614917 0.62439755 0.07250802 -0.68316334
[79] 1.32504893 -0.80195913 -0.76870310 -0.65813671 0.01858989 -0.03561010
[85] -0.45155724 0.02639805 0.96932154 0.96117539 0.59194361 0.45605975
[91] -0.65174178 1.47331430 -0.30867336 0.11986197 -0.62677620 -0.56624110
[97] 1.24373963 -0.27330112 -0.47444593 -0.12461310
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.4418296 -0.0347654 -0.5867884 -1.250159 0.7792306 -0.9702737 0.05278601
[2,] 0.4418296 -0.0347654 -0.5867884 -1.250159 0.7792306 -0.9702737 0.05278601
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.015651 0.4238243 0.6934722 -0.8385142 -1.919231 -0.2315608 0.4926096
[2,] -1.015651 0.4238243 0.6934722 -0.8385142 -1.919231 -0.2315608 0.4926096
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.2837991 -0.09112402 -0.7472925 0.4089171 1.913892 0.3141459 -0.03578916
[2,] 0.2837991 -0.09112402 -0.7472925 0.4089171 1.913892 0.3141459 -0.03578916
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.577392 -0.2787591 1.539965 -0.3724697 -0.6060417 0.8914707 0.3641351
[2,] 1.577392 -0.2787591 1.539965 -0.3724697 -0.6060417 0.8914707 0.3641351
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.5012595 1.818168 0.4297304 1.162101 -1.487311 1.498693 0.08517462
[2,] 0.5012595 1.818168 0.4297304 1.162101 -1.487311 1.498693 0.08517462
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.186593 -0.06642323 -0.6750863 -1.795951 -1.282468 0.07134563 -0.8641219
[2,] -0.186593 -0.06642323 -0.6750863 -1.795951 -1.282468 0.07134563 -0.8641219
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.16377 0.4873471 1.45211 -0.4096518 -0.7120659 -0.02553298 -0.890944
[2,] 0.16377 0.4873471 1.45211 -0.4096518 -0.7120659 -0.02553298 -0.890944
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.8022621 0.1651424 2.16193 -1.623488 0.1434094 0.5007325 1.569303
[2,] 0.8022621 0.1651424 2.16193 -1.623488 0.1434094 0.5007325 1.569303
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -1.052481 1.175967 1.179861 -0.1491041 0.1814687 -1.464168 -0.1485728
[2,] -1.052481 1.175967 1.179861 -0.1491041 0.1814687 -1.464168 -0.1485728
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.6427057 -0.3162962 -1.00306 0.7005399 -1.43509 1.696654 -0.9725564
[2,] -0.6427057 -0.3162962 -1.00306 0.7005399 -1.43509 1.696654 -0.9725564
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.08476879 0.7779022 -2.303883 0.0133598 0.7761492 0.6243976 0.07250802
[2,] 0.08476879 0.7779022 -2.303883 0.0133598 0.7761492 0.6243976 0.07250802
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.6831633 1.325049 -0.8019591 -0.7687031 -0.6581367 0.01858989 -0.0356101
[2,] -0.6831633 1.325049 -0.8019591 -0.7687031 -0.6581367 0.01858989 -0.0356101
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.4515572 0.02639805 0.9693215 0.9611754 0.5919436 0.4560597 -0.6517418
[2,] -0.4515572 0.02639805 0.9693215 0.9611754 0.5919436 0.4560597 -0.6517418
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 1.473314 -0.3086734 0.119862 -0.6267762 -0.5662411 1.24374 -0.2733011
[2,] 1.473314 -0.3086734 0.119862 -0.6267762 -0.5662411 1.24374 -0.2733011
[,99] [,100]
[1,] -0.4744459 -0.1246131
[2,] -0.4744459 -0.1246131
>
>
> Max(tmp2)
[1] 2.252792
> Min(tmp2)
[1] -2.874687
> mean(tmp2)
[1] 0.01465905
> Sum(tmp2)
[1] 1.465905
> Var(tmp2)
[1] 1.05169
>
> rowMeans(tmp2)
[1] 0.398004360 1.320620002 0.933229030 -1.260658883 0.160508261
[6] -1.242638272 1.687854960 2.252792069 1.053093753 0.945673212
[11] -0.232203164 -2.874686840 -2.538616850 -1.351657374 0.457179922
[16] -0.503687222 -0.227706098 -0.713333057 -2.371142898 1.106949228
[21] -0.236999139 1.079018592 1.221367175 -0.425297822 0.112644958
[26] -1.196887328 -0.687248156 -0.007729514 -0.078368740 -0.855425815
[31] 0.750429485 -0.233610215 1.205741336 -1.398630665 -0.998394185
[36] 0.606506367 -0.188881570 -1.212429564 -0.171547617 0.959764121
[41] 0.629266925 0.942940875 -1.169350721 0.144390719 -0.395863383
[46] -0.576565631 0.781862114 0.375202182 0.250527122 -0.407878821
[51] 0.083171156 -0.466122634 0.129974171 0.216672585 -0.766685788
[56] 0.293768979 0.676902541 0.417044729 0.938793074 -0.655945861
[61] -0.502832988 -0.704360992 0.143178469 -0.651551177 1.048518889
[66] -2.403372660 0.038346331 1.460434776 0.414576097 -1.205628741
[71] 0.900222736 -0.439322055 -0.114977853 0.302804237 1.482216211
[76] 0.391002960 -0.386774473 -1.255433041 0.015624176 1.423772362
[81] 0.545580299 0.394590449 1.124755999 -0.096013713 1.463296446
[86] -0.945524308 -1.371355771 -1.763899852 1.788391974 2.214993606
[91] -0.484899270 0.882150581 0.072108213 -0.130648621 1.652567438
[96] -1.481062439 0.462585716 -0.207590563 0.411873884 0.291861088
> rowSums(tmp2)
[1] 0.398004360 1.320620002 0.933229030 -1.260658883 0.160508261
[6] -1.242638272 1.687854960 2.252792069 1.053093753 0.945673212
[11] -0.232203164 -2.874686840 -2.538616850 -1.351657374 0.457179922
[16] -0.503687222 -0.227706098 -0.713333057 -2.371142898 1.106949228
[21] -0.236999139 1.079018592 1.221367175 -0.425297822 0.112644958
[26] -1.196887328 -0.687248156 -0.007729514 -0.078368740 -0.855425815
[31] 0.750429485 -0.233610215 1.205741336 -1.398630665 -0.998394185
[36] 0.606506367 -0.188881570 -1.212429564 -0.171547617 0.959764121
[41] 0.629266925 0.942940875 -1.169350721 0.144390719 -0.395863383
[46] -0.576565631 0.781862114 0.375202182 0.250527122 -0.407878821
[51] 0.083171156 -0.466122634 0.129974171 0.216672585 -0.766685788
[56] 0.293768979 0.676902541 0.417044729 0.938793074 -0.655945861
[61] -0.502832988 -0.704360992 0.143178469 -0.651551177 1.048518889
[66] -2.403372660 0.038346331 1.460434776 0.414576097 -1.205628741
[71] 0.900222736 -0.439322055 -0.114977853 0.302804237 1.482216211
[76] 0.391002960 -0.386774473 -1.255433041 0.015624176 1.423772362
[81] 0.545580299 0.394590449 1.124755999 -0.096013713 1.463296446
[86] -0.945524308 -1.371355771 -1.763899852 1.788391974 2.214993606
[91] -0.484899270 0.882150581 0.072108213 -0.130648621 1.652567438
[96] -1.481062439 0.462585716 -0.207590563 0.411873884 0.291861088
> 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] 0.398004360 1.320620002 0.933229030 -1.260658883 0.160508261
[6] -1.242638272 1.687854960 2.252792069 1.053093753 0.945673212
[11] -0.232203164 -2.874686840 -2.538616850 -1.351657374 0.457179922
[16] -0.503687222 -0.227706098 -0.713333057 -2.371142898 1.106949228
[21] -0.236999139 1.079018592 1.221367175 -0.425297822 0.112644958
[26] -1.196887328 -0.687248156 -0.007729514 -0.078368740 -0.855425815
[31] 0.750429485 -0.233610215 1.205741336 -1.398630665 -0.998394185
[36] 0.606506367 -0.188881570 -1.212429564 -0.171547617 0.959764121
[41] 0.629266925 0.942940875 -1.169350721 0.144390719 -0.395863383
[46] -0.576565631 0.781862114 0.375202182 0.250527122 -0.407878821
[51] 0.083171156 -0.466122634 0.129974171 0.216672585 -0.766685788
[56] 0.293768979 0.676902541 0.417044729 0.938793074 -0.655945861
[61] -0.502832988 -0.704360992 0.143178469 -0.651551177 1.048518889
[66] -2.403372660 0.038346331 1.460434776 0.414576097 -1.205628741
[71] 0.900222736 -0.439322055 -0.114977853 0.302804237 1.482216211
[76] 0.391002960 -0.386774473 -1.255433041 0.015624176 1.423772362
[81] 0.545580299 0.394590449 1.124755999 -0.096013713 1.463296446
[86] -0.945524308 -1.371355771 -1.763899852 1.788391974 2.214993606
[91] -0.484899270 0.882150581 0.072108213 -0.130648621 1.652567438
[96] -1.481062439 0.462585716 -0.207590563 0.411873884 0.291861088
> rowMin(tmp2)
[1] 0.398004360 1.320620002 0.933229030 -1.260658883 0.160508261
[6] -1.242638272 1.687854960 2.252792069 1.053093753 0.945673212
[11] -0.232203164 -2.874686840 -2.538616850 -1.351657374 0.457179922
[16] -0.503687222 -0.227706098 -0.713333057 -2.371142898 1.106949228
[21] -0.236999139 1.079018592 1.221367175 -0.425297822 0.112644958
[26] -1.196887328 -0.687248156 -0.007729514 -0.078368740 -0.855425815
[31] 0.750429485 -0.233610215 1.205741336 -1.398630665 -0.998394185
[36] 0.606506367 -0.188881570 -1.212429564 -0.171547617 0.959764121
[41] 0.629266925 0.942940875 -1.169350721 0.144390719 -0.395863383
[46] -0.576565631 0.781862114 0.375202182 0.250527122 -0.407878821
[51] 0.083171156 -0.466122634 0.129974171 0.216672585 -0.766685788
[56] 0.293768979 0.676902541 0.417044729 0.938793074 -0.655945861
[61] -0.502832988 -0.704360992 0.143178469 -0.651551177 1.048518889
[66] -2.403372660 0.038346331 1.460434776 0.414576097 -1.205628741
[71] 0.900222736 -0.439322055 -0.114977853 0.302804237 1.482216211
[76] 0.391002960 -0.386774473 -1.255433041 0.015624176 1.423772362
[81] 0.545580299 0.394590449 1.124755999 -0.096013713 1.463296446
[86] -0.945524308 -1.371355771 -1.763899852 1.788391974 2.214993606
[91] -0.484899270 0.882150581 0.072108213 -0.130648621 1.652567438
[96] -1.481062439 0.462585716 -0.207590563 0.411873884 0.291861088
>
> colMeans(tmp2)
[1] 0.01465905
> colSums(tmp2)
[1] 1.465905
> colVars(tmp2)
[1] 1.05169
> colSd(tmp2)
[1] 1.025519
> colMax(tmp2)
[1] 2.252792
> colMin(tmp2)
[1] -2.874687
> colMedians(tmp2)
[1] 0.07763968
> colRanges(tmp2)
[,1]
[1,] -2.874687
[2,] 2.252792
>
> 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] 2.7969252 -4.4749928 -0.4602618 3.2457381 2.0500060 3.4186623
[7] 2.2258465 0.9235435 2.0539604 1.6380040
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8991891
[2,] -0.2816147
[3,] 0.2226968
[4,] 0.7525109
[5,] 1.9685742
>
> rowApply(tmp,sum)
[1] 0.4404119 -4.8306307 6.7096396 2.0329161 2.4727886 -0.6415718
[7] -1.9582586 -0.9348853 2.2528948 7.8741268
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 7 3 8 6 8 10 7 4 1
[2,] 5 2 1 9 7 2 5 1 2 4
[3,] 10 8 2 3 1 6 6 3 6 5
[4,] 7 4 4 10 3 9 1 6 10 7
[5,] 1 1 10 7 5 10 2 5 7 6
[6,] 2 10 7 2 8 5 9 8 1 9
[7,] 6 5 8 6 2 3 8 10 3 8
[8,] 4 9 5 1 10 1 4 9 8 3
[9,] 8 6 6 5 4 4 7 2 9 10
[10,] 9 3 9 4 9 7 3 4 5 2
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.3216001 1.0590150 5.1024386 -0.8076979 1.8872386 2.5908136
[7] -2.9918656 -0.5173536 0.3366415 -0.4992355 -5.5854796 1.1358168
[13] 1.6187084 -2.8233262 -2.6023202 -3.8064341 1.0913510 -1.7708385
[19] 3.7864763 0.6616542
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.26479097
[2,] -0.51945430
[3,] -0.13561879
[4,] 0.09105647
[5,] 0.50720750
>
> rowApply(tmp,sum)
[1] -1.7518468 4.2255258 -1.4849043 -0.5268185 -4.9179535
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 2 10 11 9 17
[2,] 10 7 16 16 18
[3,] 17 18 7 20 9
[4,] 16 15 5 2 7
[5,] 9 17 18 11 12
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -2.26479097 -0.1420170 0.85284521 0.4925267 -0.2398470 -0.85088701
[2,] -0.13561879 -0.3041349 1.75411436 0.9750438 1.3359008 2.37471605
[3,] 0.09105647 0.4882519 -0.44118776 -0.5950256 0.9070083 1.13393626
[4,] -0.51945430 0.3892587 3.02752686 -1.3096035 -0.2865206 0.08933745
[5,] 0.50720750 0.6276563 -0.09086004 -0.3706393 0.1706971 -0.15628914
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.9957353 0.2815007 0.05642135 2.0013678 -0.9557921 0.06487237
[2,] -0.5793103 -0.9690910 0.27079142 -0.6178745 -1.0916585 0.85395853
[3,] -0.7931808 0.4337482 0.12186153 -0.1686653 -1.3930034 0.13052404
[4,] -1.1834036 -0.5239787 -0.91054707 -0.6402208 -1.3555514 -0.54889373
[5,] -2.4317062 0.2604672 0.79811426 -1.0738427 -0.7894743 0.63535561
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.62043366 -2.5478951 2.2775967 -1.06552036 0.2342986 -0.88683342
[2,] -0.03066796 1.2252481 -1.7337124 -0.29626115 0.6127505 -1.08149687
[3,] 1.26312278 -1.8932458 -1.0472512 0.07258953 -0.3186798 0.61564003
[4,] 0.55070044 0.1456240 -0.9852637 -0.26045968 0.1317545 -0.45246241
[5,] 0.45598676 0.2469425 -1.1136896 -2.25678248 0.4312273 0.03431417
[,19] [,20]
[1,] 0.1203228 -0.55531764
[2,] 1.9289822 -0.26615342
[3,] 0.3586321 -0.45103591
[4,] 2.2078576 1.90748137
[5,] -0.8293184 0.02667985
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.18-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: /home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 562 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.4889718 -1.003536 -1.280695 0.1812963 0.8993539 1.935454 -0.1255411
col8 col9 col10 col11 col12 col13 col14
row1 -1.065111 0.3978782 2.323195 -0.2147036 1.086833 0.3968196 0.9962809
col15 col16 col17 col18 col19 col20
row1 0.4914252 1.319078 1.877677 -0.2527656 -0.9461138 1.82861
> tmp[,"col10"]
col10
row1 2.323194814
row2 -0.007595023
row3 -0.226716378
row4 0.091737476
row5 2.762596407
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.4889718 -1.0035363 -1.280695 0.1812963 0.8993539 1.9354545 -0.1255411
row5 0.7663837 -0.1819082 0.238164 1.2131628 -0.4389573 0.5751858 0.1773631
col8 col9 col10 col11 col12 col13 col14
row1 -1.065111 0.3978782 2.323195 -0.21470360 1.086833 0.3968196 0.9962809
row5 -1.789330 1.5443068 2.762596 -0.08965097 0.625061 1.8901827 -0.4763358
col15 col16 col17 col18 col19 col20
row1 0.4914252 1.3190784 1.8776773 -0.2527656 -0.9461138 1.828610
row5 0.8680934 0.6342231 0.2473076 -0.3226033 -0.2633529 -1.467251
> tmp[,c("col6","col20")]
col6 col20
row1 1.9354545 1.828610
row2 0.8730803 2.064117
row3 -0.8034094 -1.194325
row4 1.7006833 1.264998
row5 0.5751858 -1.467251
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.9354545 1.828610
row5 0.5751858 -1.467251
>
>
>
>
> 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 50.168 48.87267 49.60903 50.98213 48.42543 104.4121 50.96938 48.81316
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.13495 49.17107 50.84391 48.86398 49.38691 50.35565 49.97112 49.9041
col17 col18 col19 col20
row1 50.2552 50.5517 48.4672 105.2507
> tmp[,"col10"]
col10
row1 49.17107
row2 30.37276
row3 28.32526
row4 29.40581
row5 49.31278
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.16800 48.87267 49.60903 50.98213 48.42543 104.4121 50.96938 48.81316
row5 50.51999 48.39866 50.63949 50.55971 49.46429 104.0085 51.93519 51.06191
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.13495 49.17107 50.84391 48.86398 49.38691 50.35565 49.97112 49.90410
row5 50.02607 49.31278 50.54132 52.17242 50.52082 49.49069 51.41368 50.43635
col17 col18 col19 col20
row1 50.25520 50.55170 48.46720 105.2507
row5 49.63995 49.30577 49.46085 106.2511
> tmp[,c("col6","col20")]
col6 col20
row1 104.41207 105.25069
row2 74.42828 74.10028
row3 75.87572 74.46711
row4 74.19275 72.47563
row5 104.00853 106.25106
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.4121 105.2507
row5 104.0085 106.2511
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.4121 105.2507
row5 104.0085 106.2511
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.826857964
[2,] -0.312209860
[3,] 0.007996488
[4,] 0.500086696
[5,] 1.127956620
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.39350059 0.4387078
[2,] -0.67381618 -0.2161369
[3,] -0.06168884 -0.2271525
[4,] -0.23736963 0.4698814
[5,] -0.16899843 0.4675848
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.0052317 0.07013231
[2,] -0.2661973 0.15895310
[3,] -0.8226139 0.84866919
[4,] 1.9175413 0.28044074
[5,] 0.5502551 -0.16756169
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.005232
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.0052317
[2,] -0.2661973
>
>
>
> 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 0.1086093 2.1474190 0.1968104 -1.2537746 0.1012310 -1.509782 1.341511
row1 -1.2298063 0.5503504 -0.2200106 -0.1829441 0.9688412 -1.576549 -1.554668
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 1.5144625 0.1324446 0.9050938 0.2009485 0.3070879 -1.04618807 -0.5154507
row1 0.8628731 0.4170821 -0.4684021 -1.4692257 0.1663628 -0.04329888 -0.4641255
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.5191451 0.03703779 -0.4857522 0.0988101 -1.246316 0.3314848
row1 -0.8689121 -1.69250595 -0.4202528 -0.5971086 2.260781 -0.5496871
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.072818 -3.072418 -0.7967002 0.7799494 1.539017 -0.4457664 1.918577
[,8] [,9] [,10]
row2 -1.158964 -1.909605 1.629145
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.5384444 -1.071038 0.3588673 1.266238 -0.232476 -1.583568 0.1092354
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.421512 1.282231 -1.7397 0.3882904 -0.3320347 -0.440799 1.411381
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.1432103 1.484817 1.622342 0.68272 -1.425494 1.82835
>
>
> 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: 0x28e10240>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM6d2da129375dd"
[2] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM6d2daa0e5841"
[3] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM6d2da29bacfe7"
[4] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM6d2da3e232c6f"
[5] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM6d2da15afdfda"
[6] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM6d2da63c25b7f"
[7] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM6d2da486a1381"
[8] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM6d2da8c6bdd4"
[9] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM6d2da5b5f47ac"
[10] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM6d2dabdaa885"
[11] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM6d2da578a53a6"
[12] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM6d2da7e4b1aa6"
[13] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM6d2da353e0961"
[14] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM6d2da3eaff2f9"
[15] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM6d2da7ed9b740"
>
>
> ### 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: 0x285613b0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x285613b0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x285613b0>
> rowMedians(tmp)
[1] 0.1315268948 0.3943010024 -0.0362354136 0.5190065736 0.4819924059
[6] -0.4737170637 -0.0951971405 -0.3474014278 -0.1704928795 -0.7866171116
[11] -0.3420929775 -0.5628138601 -0.0746268636 0.0248133489 -0.5611366332
[16] -0.0978306419 -0.3546830876 0.4229927935 0.0112641197 -0.0588866488
[21] 0.0096375528 -0.0071208248 -0.1223998643 -0.0850247275 -0.4536215867
[26] -0.6267057320 -0.1999488640 -0.3170196458 0.0021187755 0.0288399309
[31] 0.0178184224 0.1641254165 0.0292658330 0.1086145997 -0.3988763735
[36] 0.1250437541 -0.0374668229 -0.7480877143 0.1359026109 0.4211896792
[41] -0.1460826228 -0.0080849454 -0.4506007631 -0.1382832718 0.1392556521
[46] -0.3293919667 0.1473927204 0.1956023827 -0.2285454986 -0.0188658324
[51] 0.2056641608 0.0421399467 0.0300585388 -0.2736672671 -0.5737389735
[56] 0.9043893713 -0.1250111581 -0.5515343281 -0.0787657245 -0.0007756854
[61] 0.0516571327 -0.0272237358 0.4776124161 0.3035941003 0.0650635102
[66] 0.4782139558 -0.0326003572 -0.0233177094 -0.1461053513 -0.1057357392
[71] 0.3535122641 -0.2943494479 -0.4368080311 -0.3062240588 -0.3922191405
[76] -0.4890564659 -0.3459209304 0.2373455544 0.2170235283 0.4501190777
[81] -0.1466498381 -0.0978475615 -0.5982709275 0.0148884885 -0.0385753720
[86] 0.1383231617 0.0682983822 0.0367998318 0.1829461023 -0.0157024969
[91] -0.0288824115 -0.1900776550 -0.2353305485 -0.0128765605 0.0248813307
[96] -0.2564001116 -0.1569702999 0.0350321543 -0.3898115504 0.5491358445
[101] -0.0546987838 -0.3462618244 -0.2077082732 -0.3192862223 -0.2417612543
[106] -0.2458071960 0.0448125406 0.1492830397 0.1255170682 -0.3021632426
[111] 0.2460485880 -0.0417641409 0.7008708883 -0.6854812267 0.6776845795
[116] -0.4087368949 -0.4207396394 -0.3987628120 0.1972431732 0.1062826806
[121] -0.4665129018 0.3857419209 -0.7257273090 0.1112961901 0.2755059691
[126] 0.3112226354 0.2456645007 0.0726830071 -0.1641611677 -0.2965326578
[131] 0.0407363115 -0.0864225071 -0.0325665142 -0.5549030922 0.0111833404
[136] -0.2552875995 0.2481332092 0.0205703144 0.5101722412 -0.2196208641
[141] 0.2608850627 -0.4486970813 -0.2658602691 0.2541791269 0.0899630900
[146] -0.2816713403 -0.0552727975 0.0994980326 0.3964881254 -0.1382496131
[151] -0.3086270176 -0.0799700021 -0.2450312950 -0.5253870170 -0.3015731848
[156] 0.3651084909 -0.0185867184 -0.0379360419 0.1822323537 0.4068564818
[161] -0.5193823335 0.0813270637 -0.0514321295 0.0627031643 0.3383716274
[166] -0.2616861826 -0.1137881165 0.5780458599 -0.0043737704 -0.2783273450
[171] -0.0545551145 -0.0573651547 -0.1710523051 0.4675994714 0.2314813358
[176] -0.2558093649 -0.5063751765 -0.7161643615 0.1616653017 0.2880022565
[181] -0.1271161360 -0.4575025394 -0.2986094771 -0.1342087128 0.0742528774
[186] -0.0981849738 0.0850867505 -0.6898292584 0.4137346668 -0.0417149331
[191] -0.1581043577 -0.3469072920 0.1244493469 0.3197363419 0.1916174510
[196] 0.4178441026 -0.0499300767 0.2955207676 0.2633664578 -0.2118892819
[201] -0.0520942398 -0.0044753904 0.0620512551 0.5153409981 0.1277956329
[206] -0.3167784423 -0.0718262755 -0.6641729491 0.0377919069 -0.0278705731
[211] -0.1363252213 -0.0239033303 -0.4877648298 0.3542310095 -0.0188543240
[216] 0.0484488071 0.0420078578 -0.1128893498 -0.7026089495 0.3902027025
[221] 0.1184454714 -0.0225950484 -0.3439206272 -0.0221601551 -0.3192787245
[226] -0.0306462694 -0.2430061332 -0.1943775348 -0.2978017085 0.3078946590
>
> proc.time()
user system elapsed
1.822 1.001 2.845
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: aarch64-unknown-linux-gnu (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: 0x1f54c990>
> .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: 0x1f54c990>
> .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: 0x1f54c990>
> .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: 0x1f54c990>
> 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: 0x1faaae70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1faaae70>
> .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: 0x1faaae70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1faaae70>
> .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: 0x1faaae70>
> 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: 0x1f51b640>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1f51b640>
> .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: 0x1f51b640>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x1f51b640>
> .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: 0x1f51b640>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x1f51b640>
> .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: 0x1f51b640>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x1f51b640>
> .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: 0x1f51b640>
> 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: 0x204d5820>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x204d5820>
> .Call("R_bm_AddColumn",P)
<pointer: 0x204d5820>
> .Call("R_bm_AddColumn",P)
<pointer: 0x204d5820>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile6d35a2fd0a7cc" "BufferedMatrixFile6d35a73760c37"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile6d35a2fd0a7cc" "BufferedMatrixFile6d35a73760c37"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x1ff093e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1ff093e0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x1ff093e0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x1ff093e0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x1ff093e0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x1ff093e0>
> .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: 0x210416e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x210416e0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x210416e0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x210416e0>
> 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: 0x21076ee0>
> .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: 0x21076ee0>
> rm(P)
>
> proc.time()
user system elapsed
0.329 0.040 0.358
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: aarch64-unknown-linux-gnu (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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> 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
0.313 0.032 0.333