| Back to Multiple platform build/check report for BioC 3.18: simplified long |
|
This page was generated on 2024-04-17 11:35:49 -0400 (Wed, 17 Apr 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.3.3 (2024-02-29) -- "Angel Food Cake" | 4676 |
| palomino4 | Windows Server 2022 Datacenter | x64 | 4.3.3 (2024-02-29 ucrt) -- "Angel Food Cake" | 4414 |
| merida1 | macOS 12.7.1 Monterey | x86_64 | 4.3.3 (2024-02-29) -- "Angel Food Cake" | 4437 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 246/2266 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.66.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK |  | ||||||||
| palomino4 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.1 Ventura / arm64 | see weekly results here | ||||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.66.0 |
| Command: /home/biocbuild/bbs-3.18-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.18-bioc/R/site-library --timings BufferedMatrix_1.66.0.tar.gz |
| StartedAt: 2024-04-15 20:46:23 -0400 (Mon, 15 Apr 2024) |
| EndedAt: 2024-04-15 20:46:45 -0400 (Mon, 15 Apr 2024) |
| EllapsedTime: 22.3 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.18-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.18-bioc/R/site-library --timings BufferedMatrix_1.66.0.tar.gz
###
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##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.3.3 (2024-02-29)
* using platform: x86_64-pc-linux-gnu (64-bit)
* R was compiled by
gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
* running under: Ubuntu 22.04.4 LTS
* using session charset: UTF-8
* 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 (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
* 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 ...
‘BufferedMatrix.Rnw’... OK
OK
* checking re-building of vignette outputs ... OK
* 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
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.18-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.18-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
gcc -I"/home/biocbuild/bbs-3.18-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.18-bioc/R/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/bbs-3.18-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"/home/biocbuild/bbs-3.18-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c init_package.c -o init_package.o
gcc -shared -L/home/biocbuild/bbs-3.18-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.18-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.18-bioc/R/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 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-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
0.231 0.054 0.275
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-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 457988 24.5 983265 52.6 650542 34.8
Vcells 843172 6.5 8388608 64.0 2057435 15.7
>
>
>
>
> ##
> ## 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] "Mon Apr 15 20:46:37 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] "Mon Apr 15 20:46:37 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: 0x55edc40f2010>
>
>
>
> 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] "Mon Apr 15 20:46:37 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] "Mon Apr 15 20:46:38 2024"
>
> ColMode(tmp2)
<pointer: 0x55edc40f2010>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.3461781 -0.2579965 -1.4087720 -0.20131962
[2,] 0.7084476 0.4685277 -0.1133205 1.11565570
[3,] -0.9791654 0.2520434 1.5342847 -1.86216941
[4,] 1.1482091 -0.2875651 0.5108231 0.02100524
> 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 : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.3461781 0.2579965 1.4087720 0.20131962
[2,] 0.7084476 0.4685277 0.1133205 1.11565570
[3,] 0.9791654 0.2520434 1.5342847 1.86216941
[4,] 1.1482091 0.2875651 0.5108231 0.02100524
> 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 : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0172940 0.5079336 1.1869170 0.4486865
[2,] 0.8416933 0.6844908 0.3366311 1.0562460
[3,] 0.9895278 0.5020393 1.2386625 1.3646133
[4,] 1.0715452 0.5362510 0.7147189 0.1449318
>
> 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 : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.51912 30.33733 38.27794 29.68819
[2,] 34.12538 32.31344 28.47963 36.67812
[3,] 35.87444 30.27244 38.92091 40.50830
[4,] 36.86366 30.65007 32.65801 26.47032
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x55edc44b86a0>
> exp(tmp5)
<pointer: 0x55edc44b86a0>
> log(tmp5,2)
<pointer: 0x55edc44b86a0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.3885
> Min(tmp5)
[1] 54.34079
> mean(tmp5)
[1] 73.79146
> Sum(tmp5)
[1] 14758.29
> Var(tmp5)
[1] 861.0765
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.85943 69.69978 72.44661 71.07608 72.41382 72.73607 72.89287 73.52546
[9] 72.38166 70.88285
> rowSums(tmp5)
[1] 1797.189 1393.996 1448.932 1421.522 1448.276 1454.721 1457.857 1470.509
[9] 1447.633 1417.657
> rowVars(tmp5)
[1] 8038.15207 65.32300 86.57727 75.78116 90.59520 46.74288
[7] 66.07367 51.02019 111.50633 72.72288
> rowSd(tmp5)
[1] 89.655742 8.082265 9.304691 8.705238 9.518151 6.836877 8.128571
[8] 7.142842 10.559656 8.527771
> rowMax(tmp5)
[1] 469.38850 86.74394 88.76230 84.87879 90.52905 86.65493 88.87357
[8] 88.96227 96.54761 83.47950
> rowMin(tmp5)
[1] 57.40275 56.68603 56.53034 55.09451 54.34079 59.91660 56.16933 60.88818
[9] 54.91377 55.54641
>
> colMeans(tmp5)
[1] 113.42699 68.95810 67.30675 70.28668 69.10275 73.26042 75.03478
[8] 68.39331 76.50259 70.51377 74.93785 71.56360 71.99496 73.53021
[15] 70.25026 66.90638 78.83590 70.16002 76.90458 67.95932
> colSums(tmp5)
[1] 1134.2699 689.5810 673.0675 702.8668 691.0275 732.6042 750.3478
[8] 683.9331 765.0259 705.1377 749.3785 715.6360 719.9496 735.3021
[15] 702.5026 669.0638 788.3590 701.6002 769.0458 679.5932
> colVars(tmp5)
[1] 15721.77320 98.75390 81.39763 100.24189 63.61073 63.89291
[7] 54.72634 66.88229 46.58234 30.95368 67.84664 52.77263
[13] 98.10200 67.64618 102.31458 43.23547 16.46674 77.19541
[19] 49.53041 55.90582
> colSd(tmp5)
[1] 125.386495 9.937500 9.022063 10.012087 7.975634 7.993304
[7] 7.397725 8.178159 6.825126 5.563603 8.236907 7.264478
[13] 9.904645 8.224730 10.115067 6.575369 4.057923 8.786092
[19] 7.037784 7.477020
> colMax(tmp5)
[1] 469.38850 88.96227 81.00877 84.31272 82.85941 85.80995 88.87357
[8] 81.58150 86.65493 83.47950 87.59103 86.74394 85.88405 84.87879
[15] 88.76230 76.13391 83.65305 90.52905 85.04879 79.32464
> colMin(tmp5)
[1] 63.34949 56.20740 54.91377 54.34079 58.09227 57.65115 64.44849 57.40275
[9] 67.65555 63.12080 62.48870 62.30805 56.16933 56.68603 57.44786 56.53034
[17] 71.03181 60.56204 63.91992 55.54641
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 89.85943 69.69978 NA 71.07608 72.41382 72.73607 72.89287 73.52546
[9] 72.38166 70.88285
> rowSums(tmp5)
[1] 1797.189 1393.996 NA 1421.522 1448.276 1454.721 1457.857 1470.509
[9] 1447.633 1417.657
> rowVars(tmp5)
[1] 8038.15207 65.32300 90.76578 75.78116 90.59520 46.74288
[7] 66.07367 51.02019 111.50633 72.72288
> rowSd(tmp5)
[1] 89.655742 8.082265 9.527108 8.705238 9.518151 6.836877 8.128571
[8] 7.142842 10.559656 8.527771
> rowMax(tmp5)
[1] 469.38850 86.74394 NA 84.87879 90.52905 86.65493 88.87357
[8] 88.96227 96.54761 83.47950
> rowMin(tmp5)
[1] 57.40275 56.68603 NA 55.09451 54.34079 59.91660 56.16933 60.88818
[9] 54.91377 55.54641
>
> colMeans(tmp5)
[1] 113.42699 68.95810 67.30675 70.28668 69.10275 NA 75.03478
[8] 68.39331 76.50259 70.51377 74.93785 71.56360 71.99496 73.53021
[15] 70.25026 66.90638 78.83590 70.16002 76.90458 67.95932
> colSums(tmp5)
[1] 1134.2699 689.5810 673.0675 702.8668 691.0275 NA 750.3478
[8] 683.9331 765.0259 705.1377 749.3785 715.6360 719.9496 735.3021
[15] 702.5026 669.0638 788.3590 701.6002 769.0458 679.5932
> colVars(tmp5)
[1] 15721.77320 98.75390 81.39763 100.24189 63.61073 NA
[7] 54.72634 66.88229 46.58234 30.95368 67.84664 52.77263
[13] 98.10200 67.64618 102.31458 43.23547 16.46674 77.19541
[19] 49.53041 55.90582
> colSd(tmp5)
[1] 125.386495 9.937500 9.022063 10.012087 7.975634 NA
[7] 7.397725 8.178159 6.825126 5.563603 8.236907 7.264478
[13] 9.904645 8.224730 10.115067 6.575369 4.057923 8.786092
[19] 7.037784 7.477020
> colMax(tmp5)
[1] 469.38850 88.96227 81.00877 84.31272 82.85941 NA 88.87357
[8] 81.58150 86.65493 83.47950 87.59103 86.74394 85.88405 84.87879
[15] 88.76230 76.13391 83.65305 90.52905 85.04879 79.32464
> colMin(tmp5)
[1] 63.34949 56.20740 54.91377 54.34079 58.09227 NA 64.44849 57.40275
[9] 67.65555 63.12080 62.48870 62.30805 56.16933 56.68603 57.44786 56.53034
[17] 71.03181 60.56204 63.91992 55.54641
>
> Max(tmp5,na.rm=TRUE)
[1] 469.3885
> Min(tmp5,na.rm=TRUE)
[1] 54.34079
> mean(tmp5,na.rm=TRUE)
[1] 73.8146
> Sum(tmp5,na.rm=TRUE)
[1] 14689.11
> Var(tmp5,na.rm=TRUE)
[1] 865.3177
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.85943 69.69978 72.61816 71.07608 72.41382 72.73607 72.89287 73.52546
[9] 72.38166 70.88285
> rowSums(tmp5,na.rm=TRUE)
[1] 1797.189 1393.996 1379.745 1421.522 1448.276 1454.721 1457.857 1470.509
[9] 1447.633 1417.657
> rowVars(tmp5,na.rm=TRUE)
[1] 8038.15207 65.32300 90.76578 75.78116 90.59520 46.74288
[7] 66.07367 51.02019 111.50633 72.72288
> rowSd(tmp5,na.rm=TRUE)
[1] 89.655742 8.082265 9.527108 8.705238 9.518151 6.836877 8.128571
[8] 7.142842 10.559656 8.527771
> rowMax(tmp5,na.rm=TRUE)
[1] 469.38850 86.74394 88.76230 84.87879 90.52905 86.65493 88.87357
[8] 88.96227 96.54761 83.47950
> rowMin(tmp5,na.rm=TRUE)
[1] 57.40275 56.68603 56.53034 55.09451 54.34079 59.91660 56.16933 60.88818
[9] 54.91377 55.54641
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.42699 68.95810 67.30675 70.28668 69.10275 73.71302 75.03478
[8] 68.39331 76.50259 70.51377 74.93785 71.56360 71.99496 73.53021
[15] 70.25026 66.90638 78.83590 70.16002 76.90458 67.95932
> colSums(tmp5,na.rm=TRUE)
[1] 1134.2699 689.5810 673.0675 702.8668 691.0275 663.4172 750.3478
[8] 683.9331 765.0259 705.1377 749.3785 715.6360 719.9496 735.3021
[15] 702.5026 669.0638 788.3590 701.6002 769.0458 679.5932
> colVars(tmp5,na.rm=TRUE)
[1] 15721.77320 98.75390 81.39763 100.24189 63.61073 69.57503
[7] 54.72634 66.88229 46.58234 30.95368 67.84664 52.77263
[13] 98.10200 67.64618 102.31458 43.23547 16.46674 77.19541
[19] 49.53041 55.90582
> colSd(tmp5,na.rm=TRUE)
[1] 125.386495 9.937500 9.022063 10.012087 7.975634 8.341165
[7] 7.397725 8.178159 6.825126 5.563603 8.236907 7.264478
[13] 9.904645 8.224730 10.115067 6.575369 4.057923 8.786092
[19] 7.037784 7.477020
> colMax(tmp5,na.rm=TRUE)
[1] 469.38850 88.96227 81.00877 84.31272 82.85941 85.80995 88.87357
[8] 81.58150 86.65493 83.47950 87.59103 86.74394 85.88405 84.87879
[15] 88.76230 76.13391 83.65305 90.52905 85.04879 79.32464
> colMin(tmp5,na.rm=TRUE)
[1] 63.34949 56.20740 54.91377 54.34079 58.09227 57.65115 64.44849 57.40275
[9] 67.65555 63.12080 62.48870 62.30805 56.16933 56.68603 57.44786 56.53034
[17] 71.03181 60.56204 63.91992 55.54641
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.85943 69.69978 NaN 71.07608 72.41382 72.73607 72.89287 73.52546
[9] 72.38166 70.88285
> rowSums(tmp5,na.rm=TRUE)
[1] 1797.189 1393.996 0.000 1421.522 1448.276 1454.721 1457.857 1470.509
[9] 1447.633 1417.657
> rowVars(tmp5,na.rm=TRUE)
[1] 8038.15207 65.32300 NA 75.78116 90.59520 46.74288
[7] 66.07367 51.02019 111.50633 72.72288
> rowSd(tmp5,na.rm=TRUE)
[1] 89.655742 8.082265 NA 8.705238 9.518151 6.836877 8.128571
[8] 7.142842 10.559656 8.527771
> rowMax(tmp5,na.rm=TRUE)
[1] 469.38850 86.74394 NA 84.87879 90.52905 86.65493 88.87357
[8] 88.96227 96.54761 83.47950
> rowMin(tmp5,na.rm=TRUE)
[1] 57.40275 56.68603 NA 55.09451 54.34079 59.91660 56.16933 60.88818
[9] 54.91377 55.54641
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 117.73355 69.61921 65.78430 68.72823 68.65907 NaN 74.68299
[8] 69.16767 75.91953 71.33522 74.01844 72.09677 72.62349 74.36251
[15] 68.19337 68.05927 78.93165 69.16425 77.11608 68.90917
> colSums(tmp5,na.rm=TRUE)
[1] 1059.6020 626.5729 592.0587 618.5541 617.9316 0.0000 672.1469
[8] 622.5090 683.2758 642.0169 666.1660 648.8709 653.6115 669.2626
[15] 613.7403 612.5335 710.3849 622.4783 694.0447 620.1826
> colVars(tmp5,na.rm=TRUE)
[1] 17478.34722 106.18114 65.49657 85.44853 69.34747 NA
[7] 60.17487 68.49685 48.58055 27.23176 66.81778 56.17117
[13] 105.92043 68.30881 67.50730 33.68682 18.42193 75.68985
[19] 55.21846 52.74397
> colSd(tmp5,na.rm=TRUE)
[1] 132.205700 10.304423 8.092995 9.243837 8.327513 NA
[7] 7.757246 8.276282 6.969975 5.218406 8.174215 7.494743
[13] 10.291765 8.264914 8.216283 5.804035 4.292078 8.699991
[19] 7.430912 7.262505
> colMax(tmp5,na.rm=TRUE)
[1] 469.38850 88.96227 79.67052 79.26275 82.85941 -Inf 88.87357
[8] 81.58150 86.65493 83.47950 87.59103 86.74394 85.88405 84.87879
[15] 76.94774 76.13391 83.65305 90.52905 85.04879 79.32464
> colMin(tmp5,na.rm=TRUE)
[1] 63.34949 56.20740 54.91377 54.34079 58.09227 Inf 64.44849 57.40275
[9] 67.65555 65.63301 62.48870 62.30805 56.16933 56.68603 57.44786 59.91660
[17] 71.03181 60.56204 63.91992 55.54641
>
>
>
>
> 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] 362.8318 454.1541 233.1669 283.9874 185.8858 289.4368 320.7182 124.1943
[9] 231.7858 251.9178
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 362.8318 454.1541 233.1669 283.9874 185.8858 289.4368 320.7182 124.1943
[9] 231.7858 251.9178
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 5.684342e-14 -1.136868e-13 -1.136868e-13 5.684342e-14 0.000000e+00
[6] -1.989520e-13 1.278977e-13 0.000000e+00 -5.684342e-14 8.526513e-14
[11] -1.136868e-13 0.000000e+00 0.000000e+00 5.684342e-14 8.526513e-14
[16] 1.421085e-14 5.684342e-14 -7.105427e-14 -7.105427e-14 -2.842171e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
3 16
7 16
1 18
7 20
10 8
8 13
6 20
5 3
5 7
10 8
7 9
2 4
5 2
1 3
7 19
7 2
7 13
1 13
5 10
1 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] 2.495052
> Min(tmp)
[1] -2.43404
> mean(tmp)
[1] 0.03875809
> Sum(tmp)
[1] 3.875809
> Var(tmp)
[1] 0.9822139
>
> rowMeans(tmp)
[1] 0.03875809
> rowSums(tmp)
[1] 3.875809
> rowVars(tmp)
[1] 0.9822139
> rowSd(tmp)
[1] 0.991067
> rowMax(tmp)
[1] 2.495052
> rowMin(tmp)
[1] -2.43404
>
> colMeans(tmp)
[1] -0.87026885 -0.53187245 -1.64394809 -0.76037477 0.46429842 -1.46613161
[7] 0.96082115 0.16645147 -0.76294893 0.20062451 1.46855531 -0.08338690
[13] 1.23755667 0.47398980 0.39188849 -0.33704788 0.92268133 -0.44256493
[19] -0.64759514 1.34144519 1.89835225 0.22026766 -0.26008122 -1.16325420
[25] 0.06712221 -0.54671103 -0.34252326 2.00024680 0.02944657 0.21145346
[31] 1.46176200 -0.33281578 -0.90253553 1.05721482 -0.18923887 -1.53637278
[37] -0.62525697 -0.02019847 1.07572302 0.03287294 0.29188158 0.25061969
[43] -2.43403976 -0.24173411 0.91591061 -0.60850148 -1.71561211 1.90279739
[49] -1.25652886 1.53934503 0.50612014 1.04302389 -0.34435765 1.10406561
[55] 0.18402334 0.19152214 1.77586140 -0.40426545 0.03593680 -1.03128727
[61] 1.00956250 -0.77647770 -0.29537489 -0.25623798 -2.12019609 0.32841630
[67] -1.65221116 -1.65767039 0.37807440 -0.55296802 0.28594554 -0.18587551
[73] 1.85491106 -0.15076244 -0.46367049 0.20536027 -0.33768072 0.62621065
[79] 0.09449402 -0.12385797 0.70558482 1.92603770 -0.28498859 1.65032242
[85] 1.73456023 -1.18692654 -0.97399383 -1.09696565 0.50055655 -0.22685057
[91] 0.03362763 -0.57141993 0.03968816 0.35140592 0.58049756 -0.66635286
[97] -0.34515575 -0.94344407 2.49505195 0.02215533
> colSums(tmp)
[1] -0.87026885 -0.53187245 -1.64394809 -0.76037477 0.46429842 -1.46613161
[7] 0.96082115 0.16645147 -0.76294893 0.20062451 1.46855531 -0.08338690
[13] 1.23755667 0.47398980 0.39188849 -0.33704788 0.92268133 -0.44256493
[19] -0.64759514 1.34144519 1.89835225 0.22026766 -0.26008122 -1.16325420
[25] 0.06712221 -0.54671103 -0.34252326 2.00024680 0.02944657 0.21145346
[31] 1.46176200 -0.33281578 -0.90253553 1.05721482 -0.18923887 -1.53637278
[37] -0.62525697 -0.02019847 1.07572302 0.03287294 0.29188158 0.25061969
[43] -2.43403976 -0.24173411 0.91591061 -0.60850148 -1.71561211 1.90279739
[49] -1.25652886 1.53934503 0.50612014 1.04302389 -0.34435765 1.10406561
[55] 0.18402334 0.19152214 1.77586140 -0.40426545 0.03593680 -1.03128727
[61] 1.00956250 -0.77647770 -0.29537489 -0.25623798 -2.12019609 0.32841630
[67] -1.65221116 -1.65767039 0.37807440 -0.55296802 0.28594554 -0.18587551
[73] 1.85491106 -0.15076244 -0.46367049 0.20536027 -0.33768072 0.62621065
[79] 0.09449402 -0.12385797 0.70558482 1.92603770 -0.28498859 1.65032242
[85] 1.73456023 -1.18692654 -0.97399383 -1.09696565 0.50055655 -0.22685057
[91] 0.03362763 -0.57141993 0.03968816 0.35140592 0.58049756 -0.66635286
[97] -0.34515575 -0.94344407 2.49505195 0.02215533
> 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] -0.87026885 -0.53187245 -1.64394809 -0.76037477 0.46429842 -1.46613161
[7] 0.96082115 0.16645147 -0.76294893 0.20062451 1.46855531 -0.08338690
[13] 1.23755667 0.47398980 0.39188849 -0.33704788 0.92268133 -0.44256493
[19] -0.64759514 1.34144519 1.89835225 0.22026766 -0.26008122 -1.16325420
[25] 0.06712221 -0.54671103 -0.34252326 2.00024680 0.02944657 0.21145346
[31] 1.46176200 -0.33281578 -0.90253553 1.05721482 -0.18923887 -1.53637278
[37] -0.62525697 -0.02019847 1.07572302 0.03287294 0.29188158 0.25061969
[43] -2.43403976 -0.24173411 0.91591061 -0.60850148 -1.71561211 1.90279739
[49] -1.25652886 1.53934503 0.50612014 1.04302389 -0.34435765 1.10406561
[55] 0.18402334 0.19152214 1.77586140 -0.40426545 0.03593680 -1.03128727
[61] 1.00956250 -0.77647770 -0.29537489 -0.25623798 -2.12019609 0.32841630
[67] -1.65221116 -1.65767039 0.37807440 -0.55296802 0.28594554 -0.18587551
[73] 1.85491106 -0.15076244 -0.46367049 0.20536027 -0.33768072 0.62621065
[79] 0.09449402 -0.12385797 0.70558482 1.92603770 -0.28498859 1.65032242
[85] 1.73456023 -1.18692654 -0.97399383 -1.09696565 0.50055655 -0.22685057
[91] 0.03362763 -0.57141993 0.03968816 0.35140592 0.58049756 -0.66635286
[97] -0.34515575 -0.94344407 2.49505195 0.02215533
> colMin(tmp)
[1] -0.87026885 -0.53187245 -1.64394809 -0.76037477 0.46429842 -1.46613161
[7] 0.96082115 0.16645147 -0.76294893 0.20062451 1.46855531 -0.08338690
[13] 1.23755667 0.47398980 0.39188849 -0.33704788 0.92268133 -0.44256493
[19] -0.64759514 1.34144519 1.89835225 0.22026766 -0.26008122 -1.16325420
[25] 0.06712221 -0.54671103 -0.34252326 2.00024680 0.02944657 0.21145346
[31] 1.46176200 -0.33281578 -0.90253553 1.05721482 -0.18923887 -1.53637278
[37] -0.62525697 -0.02019847 1.07572302 0.03287294 0.29188158 0.25061969
[43] -2.43403976 -0.24173411 0.91591061 -0.60850148 -1.71561211 1.90279739
[49] -1.25652886 1.53934503 0.50612014 1.04302389 -0.34435765 1.10406561
[55] 0.18402334 0.19152214 1.77586140 -0.40426545 0.03593680 -1.03128727
[61] 1.00956250 -0.77647770 -0.29537489 -0.25623798 -2.12019609 0.32841630
[67] -1.65221116 -1.65767039 0.37807440 -0.55296802 0.28594554 -0.18587551
[73] 1.85491106 -0.15076244 -0.46367049 0.20536027 -0.33768072 0.62621065
[79] 0.09449402 -0.12385797 0.70558482 1.92603770 -0.28498859 1.65032242
[85] 1.73456023 -1.18692654 -0.97399383 -1.09696565 0.50055655 -0.22685057
[91] 0.03362763 -0.57141993 0.03968816 0.35140592 0.58049756 -0.66635286
[97] -0.34515575 -0.94344407 2.49505195 0.02215533
> colMedians(tmp)
[1] -0.87026885 -0.53187245 -1.64394809 -0.76037477 0.46429842 -1.46613161
[7] 0.96082115 0.16645147 -0.76294893 0.20062451 1.46855531 -0.08338690
[13] 1.23755667 0.47398980 0.39188849 -0.33704788 0.92268133 -0.44256493
[19] -0.64759514 1.34144519 1.89835225 0.22026766 -0.26008122 -1.16325420
[25] 0.06712221 -0.54671103 -0.34252326 2.00024680 0.02944657 0.21145346
[31] 1.46176200 -0.33281578 -0.90253553 1.05721482 -0.18923887 -1.53637278
[37] -0.62525697 -0.02019847 1.07572302 0.03287294 0.29188158 0.25061969
[43] -2.43403976 -0.24173411 0.91591061 -0.60850148 -1.71561211 1.90279739
[49] -1.25652886 1.53934503 0.50612014 1.04302389 -0.34435765 1.10406561
[55] 0.18402334 0.19152214 1.77586140 -0.40426545 0.03593680 -1.03128727
[61] 1.00956250 -0.77647770 -0.29537489 -0.25623798 -2.12019609 0.32841630
[67] -1.65221116 -1.65767039 0.37807440 -0.55296802 0.28594554 -0.18587551
[73] 1.85491106 -0.15076244 -0.46367049 0.20536027 -0.33768072 0.62621065
[79] 0.09449402 -0.12385797 0.70558482 1.92603770 -0.28498859 1.65032242
[85] 1.73456023 -1.18692654 -0.97399383 -1.09696565 0.50055655 -0.22685057
[91] 0.03362763 -0.57141993 0.03968816 0.35140592 0.58049756 -0.66635286
[97] -0.34515575 -0.94344407 2.49505195 0.02215533
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.8702688 -0.5318724 -1.643948 -0.7603748 0.4642984 -1.466132 0.9608211
[2,] -0.8702688 -0.5318724 -1.643948 -0.7603748 0.4642984 -1.466132 0.9608211
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.1664515 -0.7629489 0.2006245 1.468555 -0.0833869 1.237557 0.4739898
[2,] 0.1664515 -0.7629489 0.2006245 1.468555 -0.0833869 1.237557 0.4739898
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.3918885 -0.3370479 0.9226813 -0.4425649 -0.6475951 1.341445 1.898352
[2,] 0.3918885 -0.3370479 0.9226813 -0.4425649 -0.6475951 1.341445 1.898352
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.2202677 -0.2600812 -1.163254 0.06712221 -0.546711 -0.3425233 2.000247
[2,] 0.2202677 -0.2600812 -1.163254 0.06712221 -0.546711 -0.3425233 2.000247
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.02944657 0.2114535 1.461762 -0.3328158 -0.9025355 1.057215 -0.1892389
[2,] 0.02944657 0.2114535 1.461762 -0.3328158 -0.9025355 1.057215 -0.1892389
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.536373 -0.625257 -0.02019847 1.075723 0.03287294 0.2918816 0.2506197
[2,] -1.536373 -0.625257 -0.02019847 1.075723 0.03287294 0.2918816 0.2506197
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -2.43404 -0.2417341 0.9159106 -0.6085015 -1.715612 1.902797 -1.256529
[2,] -2.43404 -0.2417341 0.9159106 -0.6085015 -1.715612 1.902797 -1.256529
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 1.539345 0.5061201 1.043024 -0.3443576 1.104066 0.1840233 0.1915221
[2,] 1.539345 0.5061201 1.043024 -0.3443576 1.104066 0.1840233 0.1915221
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 1.775861 -0.4042655 0.0359368 -1.031287 1.009563 -0.7764777 -0.2953749
[2,] 1.775861 -0.4042655 0.0359368 -1.031287 1.009563 -0.7764777 -0.2953749
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.256238 -2.120196 0.3284163 -1.652211 -1.65767 0.3780744 -0.552968
[2,] -0.256238 -2.120196 0.3284163 -1.652211 -1.65767 0.3780744 -0.552968
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.2859455 -0.1858755 1.854911 -0.1507624 -0.4636705 0.2053603 -0.3376807
[2,] 0.2859455 -0.1858755 1.854911 -0.1507624 -0.4636705 0.2053603 -0.3376807
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.6262106 0.09449402 -0.123858 0.7055848 1.926038 -0.2849886 1.650322
[2,] 0.6262106 0.09449402 -0.123858 0.7055848 1.926038 -0.2849886 1.650322
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 1.73456 -1.186927 -0.9739938 -1.096966 0.5005565 -0.2268506 0.03362763
[2,] 1.73456 -1.186927 -0.9739938 -1.096966 0.5005565 -0.2268506 0.03362763
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.5714199 0.03968816 0.3514059 0.5804976 -0.6663529 -0.3451558 -0.9434441
[2,] -0.5714199 0.03968816 0.3514059 0.5804976 -0.6663529 -0.3451558 -0.9434441
[,99] [,100]
[1,] 2.495052 0.02215533
[2,] 2.495052 0.02215533
>
>
> Max(tmp2)
[1] 2.1545
> Min(tmp2)
[1] -1.936139
> mean(tmp2)
[1] -0.073904
> Sum(tmp2)
[1] -7.3904
> Var(tmp2)
[1] 0.8131338
>
> rowMeans(tmp2)
[1] 0.05187960 -1.32990675 -1.21867354 -0.04347586 -1.52361124 -0.46379306
[7] -1.57258786 -1.10318683 -0.49898339 -0.98055708 0.52357316 0.24909781
[13] 1.33026553 0.64761495 0.37240897 0.23135985 -0.45804995 -0.23388070
[19] 0.79111230 -0.43234716 0.46266027 -0.71489904 0.53947478 -0.61812605
[25] 0.00856151 -0.30182872 0.88081157 -1.42361435 0.72551152 -0.54034569
[31] -0.50710224 0.08816186 -0.92961426 0.90418844 1.48808643 -1.64445128
[37] 1.30587900 -0.05048954 0.56592226 0.37443875 -0.74139363 1.30836857
[43] -0.42285743 -0.22028331 -0.04890839 0.36769859 -0.38101758 -0.22741143
[49] 1.35765864 0.87000105 -1.36971195 0.83428187 -0.47451946 -0.79709680
[55] 0.45270444 0.60055702 0.60705167 0.73799136 -0.75686048 1.48658973
[61] -1.37407109 0.68952435 -0.75516429 -0.09172925 1.86214993 0.85552659
[67] -0.49563051 1.37506369 -0.82273655 2.15450011 -0.62713395 0.38972976
[73] 1.22310610 0.10027311 -1.06514448 -1.09325234 0.72823443 -1.25355739
[79] -0.70756983 0.05922828 0.19586559 -0.35539320 0.45287143 1.56767437
[85] 0.16852735 -1.93613932 -1.93367718 -0.74293369 -0.66759044 -0.63241427
[91] -0.46089361 -0.56978008 -0.87840911 -0.41195297 1.48819034 0.22280599
[97] -1.15893822 -0.26692383 -0.89143830 0.13447566
> rowSums(tmp2)
[1] 0.05187960 -1.32990675 -1.21867354 -0.04347586 -1.52361124 -0.46379306
[7] -1.57258786 -1.10318683 -0.49898339 -0.98055708 0.52357316 0.24909781
[13] 1.33026553 0.64761495 0.37240897 0.23135985 -0.45804995 -0.23388070
[19] 0.79111230 -0.43234716 0.46266027 -0.71489904 0.53947478 -0.61812605
[25] 0.00856151 -0.30182872 0.88081157 -1.42361435 0.72551152 -0.54034569
[31] -0.50710224 0.08816186 -0.92961426 0.90418844 1.48808643 -1.64445128
[37] 1.30587900 -0.05048954 0.56592226 0.37443875 -0.74139363 1.30836857
[43] -0.42285743 -0.22028331 -0.04890839 0.36769859 -0.38101758 -0.22741143
[49] 1.35765864 0.87000105 -1.36971195 0.83428187 -0.47451946 -0.79709680
[55] 0.45270444 0.60055702 0.60705167 0.73799136 -0.75686048 1.48658973
[61] -1.37407109 0.68952435 -0.75516429 -0.09172925 1.86214993 0.85552659
[67] -0.49563051 1.37506369 -0.82273655 2.15450011 -0.62713395 0.38972976
[73] 1.22310610 0.10027311 -1.06514448 -1.09325234 0.72823443 -1.25355739
[79] -0.70756983 0.05922828 0.19586559 -0.35539320 0.45287143 1.56767437
[85] 0.16852735 -1.93613932 -1.93367718 -0.74293369 -0.66759044 -0.63241427
[91] -0.46089361 -0.56978008 -0.87840911 -0.41195297 1.48819034 0.22280599
[97] -1.15893822 -0.26692383 -0.89143830 0.13447566
> 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] 0.05187960 -1.32990675 -1.21867354 -0.04347586 -1.52361124 -0.46379306
[7] -1.57258786 -1.10318683 -0.49898339 -0.98055708 0.52357316 0.24909781
[13] 1.33026553 0.64761495 0.37240897 0.23135985 -0.45804995 -0.23388070
[19] 0.79111230 -0.43234716 0.46266027 -0.71489904 0.53947478 -0.61812605
[25] 0.00856151 -0.30182872 0.88081157 -1.42361435 0.72551152 -0.54034569
[31] -0.50710224 0.08816186 -0.92961426 0.90418844 1.48808643 -1.64445128
[37] 1.30587900 -0.05048954 0.56592226 0.37443875 -0.74139363 1.30836857
[43] -0.42285743 -0.22028331 -0.04890839 0.36769859 -0.38101758 -0.22741143
[49] 1.35765864 0.87000105 -1.36971195 0.83428187 -0.47451946 -0.79709680
[55] 0.45270444 0.60055702 0.60705167 0.73799136 -0.75686048 1.48658973
[61] -1.37407109 0.68952435 -0.75516429 -0.09172925 1.86214993 0.85552659
[67] -0.49563051 1.37506369 -0.82273655 2.15450011 -0.62713395 0.38972976
[73] 1.22310610 0.10027311 -1.06514448 -1.09325234 0.72823443 -1.25355739
[79] -0.70756983 0.05922828 0.19586559 -0.35539320 0.45287143 1.56767437
[85] 0.16852735 -1.93613932 -1.93367718 -0.74293369 -0.66759044 -0.63241427
[91] -0.46089361 -0.56978008 -0.87840911 -0.41195297 1.48819034 0.22280599
[97] -1.15893822 -0.26692383 -0.89143830 0.13447566
> rowMin(tmp2)
[1] 0.05187960 -1.32990675 -1.21867354 -0.04347586 -1.52361124 -0.46379306
[7] -1.57258786 -1.10318683 -0.49898339 -0.98055708 0.52357316 0.24909781
[13] 1.33026553 0.64761495 0.37240897 0.23135985 -0.45804995 -0.23388070
[19] 0.79111230 -0.43234716 0.46266027 -0.71489904 0.53947478 -0.61812605
[25] 0.00856151 -0.30182872 0.88081157 -1.42361435 0.72551152 -0.54034569
[31] -0.50710224 0.08816186 -0.92961426 0.90418844 1.48808643 -1.64445128
[37] 1.30587900 -0.05048954 0.56592226 0.37443875 -0.74139363 1.30836857
[43] -0.42285743 -0.22028331 -0.04890839 0.36769859 -0.38101758 -0.22741143
[49] 1.35765864 0.87000105 -1.36971195 0.83428187 -0.47451946 -0.79709680
[55] 0.45270444 0.60055702 0.60705167 0.73799136 -0.75686048 1.48658973
[61] -1.37407109 0.68952435 -0.75516429 -0.09172925 1.86214993 0.85552659
[67] -0.49563051 1.37506369 -0.82273655 2.15450011 -0.62713395 0.38972976
[73] 1.22310610 0.10027311 -1.06514448 -1.09325234 0.72823443 -1.25355739
[79] -0.70756983 0.05922828 0.19586559 -0.35539320 0.45287143 1.56767437
[85] 0.16852735 -1.93613932 -1.93367718 -0.74293369 -0.66759044 -0.63241427
[91] -0.46089361 -0.56978008 -0.87840911 -0.41195297 1.48819034 0.22280599
[97] -1.15893822 -0.26692383 -0.89143830 0.13447566
>
> colMeans(tmp2)
[1] -0.073904
> colSums(tmp2)
[1] -7.3904
> colVars(tmp2)
[1] 0.8131338
> colSd(tmp2)
[1] 0.9017393
> colMax(tmp2)
[1] 2.1545
> colMin(tmp2)
[1] -1.936139
> colMedians(tmp2)
[1] -0.1560063
> colRanges(tmp2)
[,1]
[1,] -1.936139
[2,] 2.154500
>
> 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] 4.2373250 4.1599818 1.0187081 0.1970061 -5.1844897 3.4574921
[7] -2.8794815 -0.7815305 -2.2779939 4.9484907
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.4871274
[2,] -0.3594472
[3,] 0.4049110
[4,] 1.2428725
[5,] 2.2343470
>
> rowApply(tmp,sum)
[1] -0.01312156 1.74552367 0.30944300 -1.44622955 1.00966584 5.19480207
[7] -4.56722667 -0.48817973 2.67958644 2.47124449
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 4 7 10 10 4 5 3 2 9 10
[2,] 5 8 4 5 5 2 9 8 8 9
[3,] 6 9 5 4 8 1 2 7 10 4
[4,] 7 4 2 3 3 7 8 4 7 8
[5,] 2 5 9 2 1 4 6 1 1 5
[6,] 9 3 1 9 10 9 5 6 5 6
[7,] 8 6 3 7 2 3 7 5 4 1
[8,] 3 1 6 6 7 10 10 3 3 2
[9,] 1 2 7 1 9 8 4 9 2 3
[10,] 10 10 8 8 6 6 1 10 6 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.7927628 1.1333692 -3.4819368 -5.8351292 -0.9335636 -1.8285011
[7] 1.5057874 1.1372740 1.7526882 1.0141457 5.7425175 -0.7448093
[13] 0.1126119 1.0425788 1.6274369 -0.7817657 -3.5832691 -0.2576606
[19] 2.7897653 1.5158707
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.9470354
[2,] -0.6487577
[3,] 0.5342497
[4,] 0.6930203
[5,] 1.1612857
>
> rowApply(tmp,sum)
[1] -7.864286 2.151018 8.661846 1.733271 -1.961677
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 8 14 14 17 5
[2,] 16 6 11 14 16
[3,] 17 10 3 2 2
[4,] 7 1 1 4 6
[5,] 10 7 12 3 18
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.6487577 0.3066219 0.37391725 -1.0047569 -0.3752337 -1.6157380
[2,] 0.6930203 -0.7745323 0.02444568 -1.7639011 -0.3352985 1.0354012
[3,] 0.5342497 0.4060084 -0.27794458 -1.1267373 0.4156794 -0.1528323
[4,] 1.1612857 0.6646866 -1.66255676 -1.1257777 -1.6338119 0.5215767
[5,] -0.9470354 0.5305845 -1.93979841 -0.8139562 0.9951010 -1.6169086
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.61798889 -1.2579011 -1.4152291 -1.1125708 0.8361134 -0.59073681
[2,] -1.33720500 0.7041045 2.1769258 0.4104791 -0.7918747 -1.54115847
[3,] -0.06243208 1.4263833 -0.6442422 1.9005727 3.0722021 0.05888299
[4,] 1.99672102 -0.6918143 0.1211543 -0.4687761 1.2146961 0.80896607
[5,] 0.29071456 0.9565015 1.5140795 0.2844408 1.4113806 0.51923689
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.05680678 0.18180796 0.97773480 -0.31925230 0.19858420 -2.1181863
[2,] 0.43283463 0.29550278 -0.30831642 1.47216120 -0.89760396 1.4610983
[3,] 0.96384798 0.35141101 -0.08664948 -0.04696865 -0.03692721 0.7203664
[4,] -0.18521928 0.18202146 0.93314092 -1.87385227 -0.48596567 -0.5982603
[5,] -1.15565818 0.03183562 0.11152704 -0.01385373 -2.36135648 0.2773213
[,19] [,20]
[1,] 0.225694925 -1.18119305
[2,] -0.268183232 1.46311783
[3,] 0.433332715 0.81364321
[4,] 2.404679206 0.45037741
[5,] -0.005758286 -0.03007469
>
>
> 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 : 654 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 : 565 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 0.8283981 1.313946 -0.2819822 -1.483308 -0.4627753 1.046628 1.149075
col8 col9 col10 col11 col12 col13 col14
row1 -1.828595 -0.7972727 -0.2845487 -0.2694148 -0.06301855 0.6436895 -1.760495
col15 col16 col17 col18 col19 col20
row1 -1.317129 0.8741899 -0.01873731 0.1871643 1.186937 1.121237
> tmp[,"col10"]
col10
row1 -0.2845487
row2 -0.3517277
row3 -0.4109703
row4 -1.5052516
row5 -0.2142395
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.8283981 1.3139462 -0.2819822 -1.483308 -0.4627753 1.0466283 1.1490749
row5 0.2182492 -0.7692544 -0.6474035 1.888591 -0.3438922 -0.6176382 -0.7388707
col8 col9 col10 col11 col12 col13
row1 -1.828595 -0.7972727 -0.2845487 -0.2694148 -0.06301855 0.6436895
row5 1.919966 0.9004562 -0.2142395 0.8743827 -1.17220140 0.2919370
col14 col15 col16 col17 col18 col19 col20
row1 -1.76049524 -1.3171295 0.8741899 -0.01873731 0.1871643 1.186937 1.121237
row5 -0.07793687 0.2590319 -0.1309118 -0.53901098 0.2470654 1.108010 -1.644345
> tmp[,c("col6","col20")]
col6 col20
row1 1.0466283 1.1212373
row2 -0.1887374 -1.9185567
row3 -0.1353483 -1.1754689
row4 -1.7205422 0.1249938
row5 -0.6176382 -1.6443452
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.0466283 1.121237
row5 -0.6176382 -1.644345
>
>
>
>
> 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 52.47462 49.62973 49.82642 48.42027 50.78443 104.86 50.90929 49.69124
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.50605 50.51518 49.93774 48.23236 48.20377 50.62164 49.73581 50.07681
col17 col18 col19 col20
row1 52.24496 49.81114 49.57543 105.1634
> tmp[,"col10"]
col10
row1 50.51518
row2 28.54235
row3 30.85175
row4 29.18763
row5 50.06648
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 52.47462 49.62973 49.82642 48.42027 50.78443 104.8600 50.90929 49.69124
row5 49.72600 48.90609 50.58459 50.28659 48.18166 104.8064 50.48116 51.36825
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.50605 50.51518 49.93774 48.23236 48.20377 50.62164 49.73581 50.07681
row5 50.30077 50.06648 50.80123 48.96738 49.36854 49.29003 50.26947 49.89678
col17 col18 col19 col20
row1 52.24496 49.81114 49.57543 105.1634
row5 48.97028 51.40390 51.08969 105.0236
> tmp[,c("col6","col20")]
col6 col20
row1 104.85998 105.16339
row2 74.74991 73.69739
row3 74.31567 77.85471
row4 74.93439 74.53709
row5 104.80638 105.02360
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.8600 105.1634
row5 104.8064 105.0236
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.8600 105.1634
row5 104.8064 105.0236
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 2.1891406
[2,] -1.1576426
[3,] 0.2218613
[4,] 0.9838115
[5,] -1.7749379
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.87334387 -0.14019918
[2,] -1.45768823 -0.36077109
[3,] 0.07059002 -0.02845363
[4,] 0.17954874 2.03490047
[5,] 1.32928969 1.51736515
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.367447280 -0.5452461
[2,] 0.004532309 -2.4316122
[3,] -0.082174520 -1.3821067
[4,] -0.862028007 -0.1629212
[5,] 0.181911201 1.0048503
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.3674473
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.367447280
[2,] 0.004532309
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 -1.3199607 0.456076 -0.2707662 0.7298219 0.008032333 -0.2689902
row1 -0.8515279 -1.251140 -0.8149424 -2.1725724 0.097756116 0.9515200
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.4219423 0.7818009 0.05225566 -0.6473065 0.4037991 0.8235632
row1 -0.4420061 -0.4235928 -0.48631887 -0.4717060 -0.8329338 -1.5567057
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 0.4949322 -1.112438 -0.08089107 0.698013 -0.4078098 -0.1800428 -0.6757478
row1 0.6076563 1.268473 0.14889337 -2.256058 0.9459686 0.2782430 0.1364585
[,20]
row3 0.1785968
row1 -0.9059002
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.760226 -1.806137 0.6235788 0.07249388 -1.705732 -1.206734 1.226458
[,8] [,9] [,10]
row2 0.1196487 -0.6058871 -0.4355586
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.395265 -0.5217258 -0.6084144 -2.07267 -0.3306047 1.05956 0.5444887
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.326054 1.006161 0.279859 -0.4293815 -0.5160042 0.2496768 1.020818
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.136433 -0.3067831 0.06986245 -1.253199 0.3120444 -0.7023519
>
>
> 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: 0x55edc34f9a90>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ad63f36358453"
[2] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ad63f77bbad65"
[3] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ad63f775309cc"
[4] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ad63f22a94a4c"
[5] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ad63f3a422837"
[6] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ad63f7256636a"
[7] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ad63f2b5665aa"
[8] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ad63f39c3ab6d"
[9] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ad63f408f0893"
[10] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ad63f44f696fc"
[11] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ad63f20157c18"
[12] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ad63f33a32c2e"
[13] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ad63f74682626"
[14] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ad63f37e6cc97"
[15] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BM2ad63f3acd41e7"
>
>
> ### 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: 0x55edc43173c0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x55edc43173c0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x55edc43173c0>
> rowMedians(tmp)
[1] -0.2195608720 -0.2564332886 -0.0126865822 0.1672510889 0.5509162824
[6] 0.0442110491 0.0977169743 -0.3422163297 -0.2004013640 -0.3657452646
[11] -0.2316222536 -0.1292094226 0.0469716090 0.0904495681 0.2325156699
[16] 0.3162808048 0.5846625426 -0.1108277406 0.0227621871 0.0868806095
[21] -0.5235975084 -0.3672691568 0.3036585007 -0.2034380854 0.0713707035
[26] 0.0475663782 0.0013433559 0.2664759541 -0.1259174626 -0.3748338811
[31] -0.3662357745 -0.5236962479 -0.3715541388 -0.4445952315 0.3190070327
[36] 0.1547969813 0.8524065144 -0.2670404356 0.1355928273 -0.2694010997
[41] 0.3333592665 -0.0373789729 -0.0076923318 -0.1275947414 -0.0025268764
[46] -0.2997429857 0.0478861221 -0.6702805293 0.4256407355 0.3229816877
[51] -0.3951212725 -0.0722907236 0.2113395201 0.0895962760 0.1278733788
[56] -0.1197457843 0.6249101690 0.1292392186 -0.0583432063 0.2233704067
[61] 0.1265555191 -0.1269454346 -0.3425629232 0.2550146264 0.3585110742
[66] 0.2318855640 -0.1919585849 -0.1267933318 -0.0177720671 -0.2741530740
[71] 0.3168638182 -0.5031653729 -0.4613251739 0.1682123238 -0.6172521238
[76] -0.2773897653 0.3020583272 -0.4330747890 0.2649480685 0.7207616809
[81] -0.4612224291 -0.1781114398 0.0145974758 0.1994981973 -0.2445790719
[86] -0.2351925363 0.3558882514 0.2105573033 -0.1247133596 -0.2854995440
[91] 0.4957738919 0.0329701583 0.0888228888 -0.2291244461 0.2991384264
[96] 0.0591858052 -0.2433273898 0.1301042516 -0.0064472926 0.0188374392
[101] -0.3080674683 0.3394863133 0.6408650466 0.2683189370 0.3228039726
[106] -0.1448574180 -0.1844749396 0.0552832766 -0.1551689284 -0.0313631799
[111] -0.5271895780 -0.5217890328 0.1277374232 -0.8230743870 -0.5697050613
[116] 0.0441438495 -0.9096147233 -0.5040228894 1.0227248155 -0.1092852232
[121] -0.4034792680 -0.1379273867 0.3567028353 0.5341709254 0.1900447951
[126] 0.0331066658 0.0271860729 0.2956146872 -0.3490668709 0.2965308471
[131] -0.5237894010 -0.1942237177 0.2278554252 0.3063464051 -0.6315212513
[136] 0.2068880952 -0.1329535974 -0.5536632138 -0.4416317132 0.6445666228
[141] -0.2758576607 -0.3169148305 -0.1345417385 -0.0007817262 0.1160625213
[146] 0.1117896455 0.5559332372 -0.4433698795 0.0067169195 0.0958235104
[151] -0.5290802824 -0.0459372283 0.3350491680 0.1141071311 -0.2781170166
[156] 0.3427391207 0.2599554472 0.7278607546 -0.1877864548 0.2775202048
[161] 0.1308714708 0.4960978122 -0.0033442870 -0.4050676483 0.1693863696
[166] -0.4644406526 0.1607446696 -0.1073497930 -0.2062441003 0.3168923848
[171] 0.2529105583 -0.2675672330 -0.4196016547 0.0213372380 0.1221255359
[176] -0.1996434554 0.3111077251 -0.4745088381 0.2040580933 0.2710251652
[181] 0.2959736265 -0.3535757989 -0.6447852645 -0.3242808717 -0.3694503756
[186] 0.3317236782 -0.0869290744 -0.4338370149 -0.4833666742 -0.1630313547
[191] 0.5932233503 -0.2805349078 -0.4919591759 -0.8659531296 0.1424956450
[196] -0.2211610589 0.1612683653 -0.0811139508 -0.2987869170 -0.2802425212
[201] -0.0101243281 0.0743370614 0.3174649354 0.0820709282 -0.1826452318
[206] 0.1285330784 0.4676667014 0.2159075679 -0.0509561449 0.3238500902
[211] -0.2644404174 0.2826380808 -0.4590444996 0.0097500617 -0.2468003139
[216] 0.2486410626 0.0498227770 -0.1523931674 -0.1056498889 -0.4252827413
[221] 0.1103401438 -0.2602561139 0.2033776424 0.0906689261 0.1967668813
[226] 0.3245975510 0.0632318862 -0.0178470270 -0.1595880767 0.0284838649
>
> proc.time()
user system elapsed
1.305 0.604 1.906
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-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: 0x55ad94be6010>
> .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: 0x55ad94be6010>
> .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: 0x55ad94be6010>
> .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: 0x55ad94be6010>
> 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: 0x55ad94fac6a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55ad94fac6a0>
> .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: 0x55ad94fac6a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55ad94fac6a0>
> .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: 0x55ad94fac6a0>
> 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: 0x55ad940ef1c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55ad940ef1c0>
> .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: 0x55ad940ef1c0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x55ad940ef1c0>
> .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: 0x55ad940ef1c0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x55ad940ef1c0>
> .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: 0x55ad940ef1c0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x55ad940ef1c0>
> .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: 0x55ad940ef1c0>
> 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: 0x55ad96a165e0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x55ad96a165e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55ad96a165e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55ad96a165e0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2ad6867670ef1d" "BufferedMatrixFile2ad686b8c8e1b"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2ad6867670ef1d" "BufferedMatrixFile2ad686b8c8e1b"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x55ad94e53280>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55ad94e53280>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x55ad94e53280>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x55ad94e53280>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x55ad94e53280>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x55ad94e53280>
> .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: 0x55ad960a5920>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55ad960a5920>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x55ad960a5920>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x55ad960a5920>
> 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: 0x55ad95383c00>
> .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: 0x55ad95383c00>
> rm(P)
>
> proc.time()
user system elapsed
0.265 0.036 0.290
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
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Platform: x86_64-pc-linux-gnu (64-bit)
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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
0.235 0.051 0.275