| Back to Multiple platform build/check report for BioC 3.17: simplified long |
|
This page was generated on 2023-10-16 11:35:14 -0400 (Mon, 16 Oct 2023).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 22.04.2 LTS) | x86_64 | 4.3.1 (2023-06-16) -- "Beagle Scouts" | 4626 |
| palomino3 | Windows Server 2022 Datacenter | x64 | 4.3.1 (2023-06-16 ucrt) -- "Beagle Scouts" | 4379 |
| merida1 | macOS 12.6.4 Monterey | x86_64 | 4.3.1 (2023-06-16) -- "Beagle Scouts" | 4395 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 245/2230 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.64.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 22.04.2 LTS) / x86_64 | OK | OK | OK |  | ||||||||
| palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.6.4 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson2 | macOS 12.6.1 Monterey / arm64 | see weekly results here | ||||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.64.0 |
| Command: /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.17-bioc/R/site-library --timings BufferedMatrix_1.64.0.tar.gz |
| StartedAt: 2023-10-15 19:45:33 -0400 (Sun, 15 Oct 2023) |
| EndedAt: 2023-10-15 19:45:58 -0400 (Sun, 15 Oct 2023) |
| EllapsedTime: 25.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.17-bioc/R/site-library --timings BufferedMatrix_1.64.0.tar.gz
###
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* using log directory ‘/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.3.1 (2023-06-16)
* using platform: x86_64-pc-linux-gnu (64-bit)
* R was compiled by
gcc (Ubuntu 11.3.0-1ubuntu1~22.04.1) 11.3.0
GNU Fortran (Ubuntu 11.3.0-1ubuntu1~22.04.1) 11.3.0
* running under: Ubuntu 22.04.3 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.64.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... 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-3.17-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.17-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-3.17-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.17-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-3.17-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-3.17-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-3.17-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-3.17-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.17-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 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 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
0.263 0.036 0.288
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-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-3.17-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 457528 24.5 981822 52.5 650800 34.8
Vcells 842801 6.5 8388608 64.0 2062520 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] "Sun Oct 15 19:45:49 2023"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Sun Oct 15 19:45:49 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: 0x55fb857bc320>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Sun Oct 15 19:45:49 2023"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Sun Oct 15 19:45:49 2023"
>
> ColMode(tmp2)
<pointer: 0x55fb857bc320>
>
>
>
> ### 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,] 101.4210604 -1.7611091 1.12699233 1.0491806
[2,] -2.5988417 -1.5262708 0.74136169 0.3982037
[3,] 1.4034547 0.3984483 0.08853964 -0.6702742
[4,] -0.6068191 -0.4560960 0.24476243 -0.8665909
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.17-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,] 101.4210604 1.7611091 1.12699233 1.0491806
[2,] 2.5988417 1.5262708 0.74136169 0.3982037
[3,] 1.4034547 0.3984483 0.08853964 0.6702742
[4,] 0.6068191 0.4560960 0.24476243 0.8665909
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.17-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,] 10.0708024 1.3270679 1.0615989 1.0242952
[2,] 1.6120923 1.2354233 0.8610236 0.6310338
[3,] 1.1846749 0.6312276 0.2975561 0.8187028
[4,] 0.7789859 0.6753488 0.4947347 0.9309087
>
> 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-3.17-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,] 227.12908 40.03179 36.74298 36.29213
[2,] 43.71976 38.88050 34.35160 31.70854
[3,] 38.25020 31.71072 28.06410 33.85730
[4,] 33.39668 32.20958 30.19211 35.17568
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x55fb83b9a1d0>
> exp(tmp5)
<pointer: 0x55fb83b9a1d0>
> log(tmp5,2)
<pointer: 0x55fb83b9a1d0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 472.7394
> Min(tmp5)
[1] 53.65257
> mean(tmp5)
[1] 73.01688
> Sum(tmp5)
[1] 14603.38
> Var(tmp5)
[1] 869.1613
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.93410 72.54465 70.85725 70.04063 70.29458 73.97895 70.68711 69.07911
[9] 68.40331 72.34909
> rowSums(tmp5)
[1] 1838.682 1450.893 1417.145 1400.813 1405.892 1479.579 1413.742 1381.582
[9] 1368.066 1446.982
> rowVars(tmp5)
[1] 8077.30165 99.71966 67.43003 57.74199 59.52335 48.23248
[7] 66.01853 73.81054 64.39361 44.29895
> rowSd(tmp5)
[1] 89.873810 9.985973 8.211579 7.598815 7.715138 6.944961 8.125179
[8] 8.591306 8.024563 6.655745
> rowMax(tmp5)
[1] 472.73943 91.89115 88.29945 88.04994 81.38573 87.70743 88.13243
[8] 82.56720 85.23547 83.39683
> rowMin(tmp5)
[1] 60.38119 58.81706 56.93533 56.91898 55.81787 64.28776 57.60979 53.65257
[9] 55.00833 57.50487
>
> colMeans(tmp5)
[1] 112.78058 73.69357 69.82569 68.92439 71.32029 70.49340 73.12050
[8] 71.18477 71.16100 70.80991 72.58165 70.54517 69.90717 72.99511
[15] 73.62020 69.80197 64.73621 71.33720 70.93979 70.55899
> colSums(tmp5)
[1] 1127.8058 736.9357 698.2569 689.2439 713.2029 704.9340 731.2050
[8] 711.8477 711.6100 708.0991 725.8165 705.4517 699.0717 729.9511
[15] 736.2020 698.0197 647.3621 713.3720 709.3979 705.5899
> colVars(tmp5)
[1] 16078.42129 79.51150 48.89647 51.56902 61.77293 45.63098
[7] 25.52003 22.33867 58.59767 105.72272 84.38934 66.74678
[13] 75.93675 93.35100 27.72786 54.97526 24.54501 92.10527
[19] 114.14077 75.23778
> colSd(tmp5)
[1] 126.800715 8.916922 6.992601 7.181158 7.859576 6.755071
[7] 5.051735 4.726380 7.654912 10.282155 9.186367 8.169870
[13] 8.714170 9.661832 5.265725 7.414530 4.954292 9.597149
[19] 10.683668 8.673971
> colMax(tmp5)
[1] 472.73943 83.32092 80.34800 80.38364 84.36832 80.55504 78.36647
[8] 80.87439 85.23547 91.89115 88.29945 81.55530 79.80074 87.70743
[15] 79.68344 80.40189 71.91968 88.04994 86.56322 88.13243
> colMin(tmp5)
[1] 62.53633 57.60979 58.41175 53.65257 60.69636 59.47122 60.05678 64.31505
[9] 59.63542 55.22065 61.28517 57.50487 58.81706 57.50822 63.71781 56.91898
[17] 59.06851 55.00833 55.81787 58.64575
>
>
> ### 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] 91.93410 72.54465 70.85725 70.04063 NA 73.97895 70.68711 69.07911
[9] 68.40331 72.34909
> rowSums(tmp5)
[1] 1838.682 1450.893 1417.145 1400.813 NA 1479.579 1413.742 1381.582
[9] 1368.066 1446.982
> rowVars(tmp5)
[1] 8077.30165 99.71966 67.43003 57.74199 56.12353 48.23248
[7] 66.01853 73.81054 64.39361 44.29895
> rowSd(tmp5)
[1] 89.873810 9.985973 8.211579 7.598815 7.491564 6.944961 8.125179
[8] 8.591306 8.024563 6.655745
> rowMax(tmp5)
[1] 472.73943 91.89115 88.29945 88.04994 NA 87.70743 88.13243
[8] 82.56720 85.23547 83.39683
> rowMin(tmp5)
[1] 60.38119 58.81706 56.93533 56.91898 NA 64.28776 57.60979 53.65257
[9] 55.00833 57.50487
>
> colMeans(tmp5)
[1] 112.78058 73.69357 69.82569 68.92439 71.32029 70.49340 73.12050
[8] 71.18477 NA 70.80991 72.58165 70.54517 69.90717 72.99511
[15] 73.62020 69.80197 64.73621 71.33720 70.93979 70.55899
> colSums(tmp5)
[1] 1127.8058 736.9357 698.2569 689.2439 713.2029 704.9340 731.2050
[8] 711.8477 NA 708.0991 725.8165 705.4517 699.0717 729.9511
[15] 736.2020 698.0197 647.3621 713.3720 709.3979 705.5899
> colVars(tmp5)
[1] 16078.42129 79.51150 48.89647 51.56902 61.77293 45.63098
[7] 25.52003 22.33867 NA 105.72272 84.38934 66.74678
[13] 75.93675 93.35100 27.72786 54.97526 24.54501 92.10527
[19] 114.14077 75.23778
> colSd(tmp5)
[1] 126.800715 8.916922 6.992601 7.181158 7.859576 6.755071
[7] 5.051735 4.726380 NA 10.282155 9.186367 8.169870
[13] 8.714170 9.661832 5.265725 7.414530 4.954292 9.597149
[19] 10.683668 8.673971
> colMax(tmp5)
[1] 472.73943 83.32092 80.34800 80.38364 84.36832 80.55504 78.36647
[8] 80.87439 NA 91.89115 88.29945 81.55530 79.80074 87.70743
[15] 79.68344 80.40189 71.91968 88.04994 86.56322 88.13243
> colMin(tmp5)
[1] 62.53633 57.60979 58.41175 53.65257 60.69636 59.47122 60.05678 64.31505
[9] NA 55.22065 61.28517 57.50487 58.81706 57.50822 63.71781 56.91898
[17] 59.06851 55.00833 55.81787 58.64575
>
> Max(tmp5,na.rm=TRUE)
[1] 472.7394
> Min(tmp5,na.rm=TRUE)
[1] 53.65257
> mean(tmp5,na.rm=TRUE)
[1] 72.97674
> Sum(tmp5,na.rm=TRUE)
[1] 14522.37
> Var(tmp5,na.rm=TRUE)
[1] 873.2272
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.93410 72.54465 70.85725 70.04063 69.73095 73.97895 70.68711 69.07911
[9] 68.40331 72.34909
> rowSums(tmp5,na.rm=TRUE)
[1] 1838.682 1450.893 1417.145 1400.813 1324.888 1479.579 1413.742 1381.582
[9] 1368.066 1446.982
> rowVars(tmp5,na.rm=TRUE)
[1] 8077.30165 99.71966 67.43003 57.74199 56.12353 48.23248
[7] 66.01853 73.81054 64.39361 44.29895
> rowSd(tmp5,na.rm=TRUE)
[1] 89.873810 9.985973 8.211579 7.598815 7.491564 6.944961 8.125179
[8] 8.591306 8.024563 6.655745
> rowMax(tmp5,na.rm=TRUE)
[1] 472.73943 91.89115 88.29945 88.04994 81.38573 87.70743 88.13243
[8] 82.56720 85.23547 83.39683
> rowMin(tmp5,na.rm=TRUE)
[1] 60.38119 58.81706 56.93533 56.91898 55.81787 64.28776 57.60979 53.65257
[9] 55.00833 57.50487
>
> colMeans(tmp5,na.rm=TRUE)
[1] 112.78058 73.69357 69.82569 68.92439 71.32029 70.49340 73.12050
[8] 71.18477 70.06737 70.80991 72.58165 70.54517 69.90717 72.99511
[15] 73.62020 69.80197 64.73621 71.33720 70.93979 70.55899
> colSums(tmp5,na.rm=TRUE)
[1] 1127.8058 736.9357 698.2569 689.2439 713.2029 704.9340 731.2050
[8] 711.8477 630.6063 708.0991 725.8165 705.4517 699.0717 729.9511
[15] 736.2020 698.0197 647.3621 713.3720 709.3979 705.5899
> colVars(tmp5,na.rm=TRUE)
[1] 16078.42129 79.51150 48.89647 51.56902 61.77293 45.63098
[7] 25.52003 22.33867 52.46713 105.72272 84.38934 66.74678
[13] 75.93675 93.35100 27.72786 54.97526 24.54501 92.10527
[19] 114.14077 75.23778
> colSd(tmp5,na.rm=TRUE)
[1] 126.800715 8.916922 6.992601 7.181158 7.859576 6.755071
[7] 5.051735 4.726380 7.243420 10.282155 9.186367 8.169870
[13] 8.714170 9.661832 5.265725 7.414530 4.954292 9.597149
[19] 10.683668 8.673971
> colMax(tmp5,na.rm=TRUE)
[1] 472.73943 83.32092 80.34800 80.38364 84.36832 80.55504 78.36647
[8] 80.87439 85.23547 91.89115 88.29945 81.55530 79.80074 87.70743
[15] 79.68344 80.40189 71.91968 88.04994 86.56322 88.13243
> colMin(tmp5,na.rm=TRUE)
[1] 62.53633 57.60979 58.41175 53.65257 60.69636 59.47122 60.05678 64.31505
[9] 59.63542 55.22065 61.28517 57.50487 58.81706 57.50822 63.71781 56.91898
[17] 59.06851 55.00833 55.81787 58.64575
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.93410 72.54465 70.85725 70.04063 NaN 73.97895 70.68711 69.07911
[9] 68.40331 72.34909
> rowSums(tmp5,na.rm=TRUE)
[1] 1838.682 1450.893 1417.145 1400.813 0.000 1479.579 1413.742 1381.582
[9] 1368.066 1446.982
> rowVars(tmp5,na.rm=TRUE)
[1] 8077.30165 99.71966 67.43003 57.74199 NA 48.23248
[7] 66.01853 73.81054 64.39361 44.29895
> rowSd(tmp5,na.rm=TRUE)
[1] 89.873810 9.985973 8.211579 7.598815 NA 6.944961 8.125179
[8] 8.591306 8.024563 6.655745
> rowMax(tmp5,na.rm=TRUE)
[1] 472.73943 91.89115 88.29945 88.04994 NA 87.70743 88.13243
[8] 82.56720 85.23547 83.39683
> rowMin(tmp5,na.rm=TRUE)
[1] 60.38119 58.81706 56.93533 56.91898 NA 64.28776 57.60979 53.65257
[9] 55.00833 57.50487
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 118.31453 74.17128 70.05300 68.77264 70.84049 71.71808 74.57202
[8] 71.94808 NaN 70.11749 72.65773 70.27497 69.49701 72.06282
[15] 73.05863 69.62981 65.28107 71.14918 72.62001 69.58088
> colSums(tmp5,na.rm=TRUE)
[1] 1064.8308 667.5415 630.4770 618.9538 637.5644 645.4627 671.1482
[8] 647.5327 0.0000 631.0574 653.9196 632.4748 625.4731 648.5654
[15] 657.5277 626.6683 587.5296 640.3426 653.5801 626.2279
> colVars(tmp5,na.rm=TRUE)
[1] 17743.696676 86.883173 54.427264 57.756105 66.904734
[6] 34.461468 5.007169 18.576404 NA 113.544285
[11] 94.872883 74.268796 83.536265 95.241763 27.646091
[16] 61.513711 24.273318 103.220740 96.648282 73.879735
> colSd(tmp5,na.rm=TRUE)
[1] 133.205468 9.321114 7.377484 7.599744 8.179531 5.870389
[7] 2.237670 4.310035 NA 10.655716 9.740271 8.617935
[13] 9.139818 9.759189 5.257955 7.843068 4.926796 10.159761
[19] 9.830986 8.595332
> colMax(tmp5,na.rm=TRUE)
[1] 472.73943 83.32092 80.34800 80.38364 84.36832 80.55504 78.36647
[8] 80.87439 -Inf 91.89115 88.29945 81.55530 79.80074 87.70743
[15] 79.68344 80.40189 71.91968 88.04994 86.56322 88.13243
> colMin(tmp5,na.rm=TRUE)
[1] 62.53633 57.60979 58.41175 53.65257 60.69636 62.68662 71.59977 66.16122
[9] Inf 55.22065 61.28517 57.50487 58.81706 57.50822 63.71781 56.91898
[17] 59.06851 55.00833 56.93533 58.64575
>
>
>
>
> 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] 180.0959 136.4999 459.2311 203.6116 267.3199 128.1101 261.3169 251.5494
[9] 245.8539 257.9470
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 180.0959 136.4999 459.2311 203.6116 267.3199 128.1101 261.3169 251.5494
[9] 245.8539 257.9470
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -5.684342e-14 2.842171e-14 -1.136868e-13 -1.421085e-13 -2.273737e-13
[6] 8.526513e-14 5.684342e-14 5.684342e-14 0.000000e+00 -5.684342e-14
[11] -1.421085e-14 5.684342e-14 5.684342e-14 0.000000e+00 -2.273737e-13
[16] -9.947598e-14 1.136868e-13 0.000000e+00 -1.136868e-13 -8.526513e-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)
+ }
10 6
10 1
3 3
2 17
10 3
10 1
7 2
8 14
1 2
3 15
10 14
4 19
4 10
9 6
5 9
9 20
1 19
1 15
4 4
7 19
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] 2.281523
> Min(tmp)
[1] -2.513104
> mean(tmp)
[1] 0.06012704
> Sum(tmp)
[1] 6.012704
> Var(tmp)
[1] 0.9360641
>
> rowMeans(tmp)
[1] 0.06012704
> rowSums(tmp)
[1] 6.012704
> rowVars(tmp)
[1] 0.9360641
> rowSd(tmp)
[1] 0.9675041
> rowMax(tmp)
[1] 2.281523
> rowMin(tmp)
[1] -2.513104
>
> colMeans(tmp)
[1] 0.38163755 -1.89305710 -0.35956790 0.72302245 0.23330522 -1.95679314
[7] 0.23048188 1.93613091 -0.58544038 0.53400332 -0.05137971 1.21365228
[13] -1.50316250 0.34907020 2.02444155 0.67875424 -0.31990564 -1.68916677
[19] 0.19825226 0.47708980 0.68135238 -1.21333073 0.28710637 -1.00651469
[25] 0.96653415 0.41147567 0.73919727 0.36262847 0.73927107 1.82597156
[31] 0.06903952 1.07246753 -0.72462189 1.45085492 -0.33634578 0.63815319
[37] -0.44253756 -1.08089976 2.08238232 -0.47162202 -1.27647412 0.62274050
[43] 0.35342496 -0.79190309 0.87477479 -0.95298607 -0.50295808 0.19514874
[49] 0.08821131 0.30042913 -0.58252901 -0.20549733 -1.63469286 1.04866104
[55] 1.86031420 0.06864195 -0.91813312 0.98664288 0.47223098 0.20444977
[61] 0.37382007 -0.13063684 -1.19889254 -0.44431029 2.28152266 0.94980595
[67] 1.05983516 1.06272371 0.42279232 -0.37172931 -1.13072187 1.63087430
[73] -1.15653974 -0.78806532 1.00962004 -0.01616050 0.06252201 0.59512470
[79] 0.40605480 0.31313258 0.18761311 0.10969709 0.64935259 -0.11324161
[85] -1.09856944 -0.89445115 0.23679256 0.30023685 0.57988103 -0.82829408
[91] 0.31321584 -1.34989190 -1.18746280 0.55209694 0.33754931 -1.42681688
[97] -0.62703619 -0.06865092 1.04058824 -2.51310389
> colSums(tmp)
[1] 0.38163755 -1.89305710 -0.35956790 0.72302245 0.23330522 -1.95679314
[7] 0.23048188 1.93613091 -0.58544038 0.53400332 -0.05137971 1.21365228
[13] -1.50316250 0.34907020 2.02444155 0.67875424 -0.31990564 -1.68916677
[19] 0.19825226 0.47708980 0.68135238 -1.21333073 0.28710637 -1.00651469
[25] 0.96653415 0.41147567 0.73919727 0.36262847 0.73927107 1.82597156
[31] 0.06903952 1.07246753 -0.72462189 1.45085492 -0.33634578 0.63815319
[37] -0.44253756 -1.08089976 2.08238232 -0.47162202 -1.27647412 0.62274050
[43] 0.35342496 -0.79190309 0.87477479 -0.95298607 -0.50295808 0.19514874
[49] 0.08821131 0.30042913 -0.58252901 -0.20549733 -1.63469286 1.04866104
[55] 1.86031420 0.06864195 -0.91813312 0.98664288 0.47223098 0.20444977
[61] 0.37382007 -0.13063684 -1.19889254 -0.44431029 2.28152266 0.94980595
[67] 1.05983516 1.06272371 0.42279232 -0.37172931 -1.13072187 1.63087430
[73] -1.15653974 -0.78806532 1.00962004 -0.01616050 0.06252201 0.59512470
[79] 0.40605480 0.31313258 0.18761311 0.10969709 0.64935259 -0.11324161
[85] -1.09856944 -0.89445115 0.23679256 0.30023685 0.57988103 -0.82829408
[91] 0.31321584 -1.34989190 -1.18746280 0.55209694 0.33754931 -1.42681688
[97] -0.62703619 -0.06865092 1.04058824 -2.51310389
> 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] 0.38163755 -1.89305710 -0.35956790 0.72302245 0.23330522 -1.95679314
[7] 0.23048188 1.93613091 -0.58544038 0.53400332 -0.05137971 1.21365228
[13] -1.50316250 0.34907020 2.02444155 0.67875424 -0.31990564 -1.68916677
[19] 0.19825226 0.47708980 0.68135238 -1.21333073 0.28710637 -1.00651469
[25] 0.96653415 0.41147567 0.73919727 0.36262847 0.73927107 1.82597156
[31] 0.06903952 1.07246753 -0.72462189 1.45085492 -0.33634578 0.63815319
[37] -0.44253756 -1.08089976 2.08238232 -0.47162202 -1.27647412 0.62274050
[43] 0.35342496 -0.79190309 0.87477479 -0.95298607 -0.50295808 0.19514874
[49] 0.08821131 0.30042913 -0.58252901 -0.20549733 -1.63469286 1.04866104
[55] 1.86031420 0.06864195 -0.91813312 0.98664288 0.47223098 0.20444977
[61] 0.37382007 -0.13063684 -1.19889254 -0.44431029 2.28152266 0.94980595
[67] 1.05983516 1.06272371 0.42279232 -0.37172931 -1.13072187 1.63087430
[73] -1.15653974 -0.78806532 1.00962004 -0.01616050 0.06252201 0.59512470
[79] 0.40605480 0.31313258 0.18761311 0.10969709 0.64935259 -0.11324161
[85] -1.09856944 -0.89445115 0.23679256 0.30023685 0.57988103 -0.82829408
[91] 0.31321584 -1.34989190 -1.18746280 0.55209694 0.33754931 -1.42681688
[97] -0.62703619 -0.06865092 1.04058824 -2.51310389
> colMin(tmp)
[1] 0.38163755 -1.89305710 -0.35956790 0.72302245 0.23330522 -1.95679314
[7] 0.23048188 1.93613091 -0.58544038 0.53400332 -0.05137971 1.21365228
[13] -1.50316250 0.34907020 2.02444155 0.67875424 -0.31990564 -1.68916677
[19] 0.19825226 0.47708980 0.68135238 -1.21333073 0.28710637 -1.00651469
[25] 0.96653415 0.41147567 0.73919727 0.36262847 0.73927107 1.82597156
[31] 0.06903952 1.07246753 -0.72462189 1.45085492 -0.33634578 0.63815319
[37] -0.44253756 -1.08089976 2.08238232 -0.47162202 -1.27647412 0.62274050
[43] 0.35342496 -0.79190309 0.87477479 -0.95298607 -0.50295808 0.19514874
[49] 0.08821131 0.30042913 -0.58252901 -0.20549733 -1.63469286 1.04866104
[55] 1.86031420 0.06864195 -0.91813312 0.98664288 0.47223098 0.20444977
[61] 0.37382007 -0.13063684 -1.19889254 -0.44431029 2.28152266 0.94980595
[67] 1.05983516 1.06272371 0.42279232 -0.37172931 -1.13072187 1.63087430
[73] -1.15653974 -0.78806532 1.00962004 -0.01616050 0.06252201 0.59512470
[79] 0.40605480 0.31313258 0.18761311 0.10969709 0.64935259 -0.11324161
[85] -1.09856944 -0.89445115 0.23679256 0.30023685 0.57988103 -0.82829408
[91] 0.31321584 -1.34989190 -1.18746280 0.55209694 0.33754931 -1.42681688
[97] -0.62703619 -0.06865092 1.04058824 -2.51310389
> colMedians(tmp)
[1] 0.38163755 -1.89305710 -0.35956790 0.72302245 0.23330522 -1.95679314
[7] 0.23048188 1.93613091 -0.58544038 0.53400332 -0.05137971 1.21365228
[13] -1.50316250 0.34907020 2.02444155 0.67875424 -0.31990564 -1.68916677
[19] 0.19825226 0.47708980 0.68135238 -1.21333073 0.28710637 -1.00651469
[25] 0.96653415 0.41147567 0.73919727 0.36262847 0.73927107 1.82597156
[31] 0.06903952 1.07246753 -0.72462189 1.45085492 -0.33634578 0.63815319
[37] -0.44253756 -1.08089976 2.08238232 -0.47162202 -1.27647412 0.62274050
[43] 0.35342496 -0.79190309 0.87477479 -0.95298607 -0.50295808 0.19514874
[49] 0.08821131 0.30042913 -0.58252901 -0.20549733 -1.63469286 1.04866104
[55] 1.86031420 0.06864195 -0.91813312 0.98664288 0.47223098 0.20444977
[61] 0.37382007 -0.13063684 -1.19889254 -0.44431029 2.28152266 0.94980595
[67] 1.05983516 1.06272371 0.42279232 -0.37172931 -1.13072187 1.63087430
[73] -1.15653974 -0.78806532 1.00962004 -0.01616050 0.06252201 0.59512470
[79] 0.40605480 0.31313258 0.18761311 0.10969709 0.64935259 -0.11324161
[85] -1.09856944 -0.89445115 0.23679256 0.30023685 0.57988103 -0.82829408
[91] 0.31321584 -1.34989190 -1.18746280 0.55209694 0.33754931 -1.42681688
[97] -0.62703619 -0.06865092 1.04058824 -2.51310389
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.3816376 -1.893057 -0.3595679 0.7230225 0.2333052 -1.956793 0.2304819
[2,] 0.3816376 -1.893057 -0.3595679 0.7230225 0.2333052 -1.956793 0.2304819
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.936131 -0.5854404 0.5340033 -0.05137971 1.213652 -1.503162 0.3490702
[2,] 1.936131 -0.5854404 0.5340033 -0.05137971 1.213652 -1.503162 0.3490702
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 2.024442 0.6787542 -0.3199056 -1.689167 0.1982523 0.4770898 0.6813524
[2,] 2.024442 0.6787542 -0.3199056 -1.689167 0.1982523 0.4770898 0.6813524
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.213331 0.2871064 -1.006515 0.9665341 0.4114757 0.7391973 0.3626285
[2,] -1.213331 0.2871064 -1.006515 0.9665341 0.4114757 0.7391973 0.3626285
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.7392711 1.825972 0.06903952 1.072468 -0.7246219 1.450855 -0.3363458
[2,] 0.7392711 1.825972 0.06903952 1.072468 -0.7246219 1.450855 -0.3363458
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.6381532 -0.4425376 -1.0809 2.082382 -0.471622 -1.276474 0.6227405
[2,] 0.6381532 -0.4425376 -1.0809 2.082382 -0.471622 -1.276474 0.6227405
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.353425 -0.7919031 0.8747748 -0.9529861 -0.5029581 0.1951487 0.08821131
[2,] 0.353425 -0.7919031 0.8747748 -0.9529861 -0.5029581 0.1951487 0.08821131
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.3004291 -0.582529 -0.2054973 -1.634693 1.048661 1.860314 0.06864195
[2,] 0.3004291 -0.582529 -0.2054973 -1.634693 1.048661 1.860314 0.06864195
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.9181331 0.9866429 0.472231 0.2044498 0.3738201 -0.1306368 -1.198893
[2,] -0.9181331 0.9866429 0.472231 0.2044498 0.3738201 -0.1306368 -1.198893
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.4443103 2.281523 0.9498059 1.059835 1.062724 0.4227923 -0.3717293
[2,] -0.4443103 2.281523 0.9498059 1.059835 1.062724 0.4227923 -0.3717293
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -1.130722 1.630874 -1.15654 -0.7880653 1.00962 -0.0161605 0.06252201
[2,] -1.130722 1.630874 -1.15654 -0.7880653 1.00962 -0.0161605 0.06252201
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.5951247 0.4060548 0.3131326 0.1876131 0.1096971 0.6493526 -0.1132416
[2,] 0.5951247 0.4060548 0.3131326 0.1876131 0.1096971 0.6493526 -0.1132416
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -1.098569 -0.8944512 0.2367926 0.3002369 0.579881 -0.8282941 0.3132158
[2,] -1.098569 -0.8944512 0.2367926 0.3002369 0.579881 -0.8282941 0.3132158
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.349892 -1.187463 0.5520969 0.3375493 -1.426817 -0.6270362 -0.06865092
[2,] -1.349892 -1.187463 0.5520969 0.3375493 -1.426817 -0.6270362 -0.06865092
[,99] [,100]
[1,] 1.040588 -2.513104
[2,] 1.040588 -2.513104
>
>
> Max(tmp2)
[1] 1.784649
> Min(tmp2)
[1] -2.112094
> mean(tmp2)
[1] 0.06799504
> Sum(tmp2)
[1] 6.799504
> Var(tmp2)
[1] 0.691152
>
> rowMeans(tmp2)
[1] -0.28934558 -0.56219758 -0.37625511 -0.61213302 -0.44432441 0.66266733
[7] 0.04787504 -0.65477147 0.43994088 -2.11209415 0.38798405 -0.13869230
[13] -0.16967823 -0.46672395 1.10507141 -0.02904520 0.45716536 1.60607397
[19] -0.31396121 -0.27786876 -1.07337276 0.25031722 1.02837593 0.67195780
[25] -0.05756825 0.53465293 0.21416319 -0.64219293 -0.38531833 -1.68685393
[31] -1.41559104 -1.08481659 -1.12165879 -0.54596866 0.21788266 1.78464927
[37] 0.31148772 0.48221569 0.30117839 1.43073420 0.17175690 1.72017540
[43] -0.11566794 -1.43012362 1.64391474 -0.37138164 -0.56265097 -0.35240477
[49] 0.26429388 1.07164501 0.79841538 0.60134835 0.56715157 0.05647751
[55] -0.38008193 -0.42259844 1.01648779 0.75943358 -0.62634162 1.08005785
[61] -0.70562684 -0.12164344 -0.98681116 -0.01504689 -0.02057443 1.62863782
[67] 0.06312051 1.76501160 0.11654210 0.92657335 0.11645205 1.05011248
[73] -0.69624322 -1.25645847 0.44937067 0.38169445 -2.08349590 -0.64938809
[79] 0.11244870 -0.92745656 -0.21799631 0.94479965 1.12250900 0.65210040
[85] 0.70054281 0.75986604 -0.28504450 1.41937641 -0.42759055 -0.04544125
[91] 0.07178117 -0.09671957 0.09841293 0.77187221 -0.22405593 -0.82095297
[97] -1.03378623 0.68979361 0.16474168 0.44420918
> rowSums(tmp2)
[1] -0.28934558 -0.56219758 -0.37625511 -0.61213302 -0.44432441 0.66266733
[7] 0.04787504 -0.65477147 0.43994088 -2.11209415 0.38798405 -0.13869230
[13] -0.16967823 -0.46672395 1.10507141 -0.02904520 0.45716536 1.60607397
[19] -0.31396121 -0.27786876 -1.07337276 0.25031722 1.02837593 0.67195780
[25] -0.05756825 0.53465293 0.21416319 -0.64219293 -0.38531833 -1.68685393
[31] -1.41559104 -1.08481659 -1.12165879 -0.54596866 0.21788266 1.78464927
[37] 0.31148772 0.48221569 0.30117839 1.43073420 0.17175690 1.72017540
[43] -0.11566794 -1.43012362 1.64391474 -0.37138164 -0.56265097 -0.35240477
[49] 0.26429388 1.07164501 0.79841538 0.60134835 0.56715157 0.05647751
[55] -0.38008193 -0.42259844 1.01648779 0.75943358 -0.62634162 1.08005785
[61] -0.70562684 -0.12164344 -0.98681116 -0.01504689 -0.02057443 1.62863782
[67] 0.06312051 1.76501160 0.11654210 0.92657335 0.11645205 1.05011248
[73] -0.69624322 -1.25645847 0.44937067 0.38169445 -2.08349590 -0.64938809
[79] 0.11244870 -0.92745656 -0.21799631 0.94479965 1.12250900 0.65210040
[85] 0.70054281 0.75986604 -0.28504450 1.41937641 -0.42759055 -0.04544125
[91] 0.07178117 -0.09671957 0.09841293 0.77187221 -0.22405593 -0.82095297
[97] -1.03378623 0.68979361 0.16474168 0.44420918
> 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] -0.28934558 -0.56219758 -0.37625511 -0.61213302 -0.44432441 0.66266733
[7] 0.04787504 -0.65477147 0.43994088 -2.11209415 0.38798405 -0.13869230
[13] -0.16967823 -0.46672395 1.10507141 -0.02904520 0.45716536 1.60607397
[19] -0.31396121 -0.27786876 -1.07337276 0.25031722 1.02837593 0.67195780
[25] -0.05756825 0.53465293 0.21416319 -0.64219293 -0.38531833 -1.68685393
[31] -1.41559104 -1.08481659 -1.12165879 -0.54596866 0.21788266 1.78464927
[37] 0.31148772 0.48221569 0.30117839 1.43073420 0.17175690 1.72017540
[43] -0.11566794 -1.43012362 1.64391474 -0.37138164 -0.56265097 -0.35240477
[49] 0.26429388 1.07164501 0.79841538 0.60134835 0.56715157 0.05647751
[55] -0.38008193 -0.42259844 1.01648779 0.75943358 -0.62634162 1.08005785
[61] -0.70562684 -0.12164344 -0.98681116 -0.01504689 -0.02057443 1.62863782
[67] 0.06312051 1.76501160 0.11654210 0.92657335 0.11645205 1.05011248
[73] -0.69624322 -1.25645847 0.44937067 0.38169445 -2.08349590 -0.64938809
[79] 0.11244870 -0.92745656 -0.21799631 0.94479965 1.12250900 0.65210040
[85] 0.70054281 0.75986604 -0.28504450 1.41937641 -0.42759055 -0.04544125
[91] 0.07178117 -0.09671957 0.09841293 0.77187221 -0.22405593 -0.82095297
[97] -1.03378623 0.68979361 0.16474168 0.44420918
> rowMin(tmp2)
[1] -0.28934558 -0.56219758 -0.37625511 -0.61213302 -0.44432441 0.66266733
[7] 0.04787504 -0.65477147 0.43994088 -2.11209415 0.38798405 -0.13869230
[13] -0.16967823 -0.46672395 1.10507141 -0.02904520 0.45716536 1.60607397
[19] -0.31396121 -0.27786876 -1.07337276 0.25031722 1.02837593 0.67195780
[25] -0.05756825 0.53465293 0.21416319 -0.64219293 -0.38531833 -1.68685393
[31] -1.41559104 -1.08481659 -1.12165879 -0.54596866 0.21788266 1.78464927
[37] 0.31148772 0.48221569 0.30117839 1.43073420 0.17175690 1.72017540
[43] -0.11566794 -1.43012362 1.64391474 -0.37138164 -0.56265097 -0.35240477
[49] 0.26429388 1.07164501 0.79841538 0.60134835 0.56715157 0.05647751
[55] -0.38008193 -0.42259844 1.01648779 0.75943358 -0.62634162 1.08005785
[61] -0.70562684 -0.12164344 -0.98681116 -0.01504689 -0.02057443 1.62863782
[67] 0.06312051 1.76501160 0.11654210 0.92657335 0.11645205 1.05011248
[73] -0.69624322 -1.25645847 0.44937067 0.38169445 -2.08349590 -0.64938809
[79] 0.11244870 -0.92745656 -0.21799631 0.94479965 1.12250900 0.65210040
[85] 0.70054281 0.75986604 -0.28504450 1.41937641 -0.42759055 -0.04544125
[91] 0.07178117 -0.09671957 0.09841293 0.77187221 -0.22405593 -0.82095297
[97] -1.03378623 0.68979361 0.16474168 0.44420918
>
> colMeans(tmp2)
[1] 0.06799504
> colSums(tmp2)
[1] 6.799504
> colVars(tmp2)
[1] 0.691152
> colSd(tmp2)
[1] 0.8313555
> colMax(tmp2)
[1] 1.784649
> colMin(tmp2)
[1] -2.112094
> colMedians(tmp2)
[1] 0.05979901
> colRanges(tmp2)
[,1]
[1,] -2.112094
[2,] 1.784649
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.8151254 2.4529738 -4.0374779 -0.5527506 5.2024467 -0.6912827
[7] 4.2060368 -0.1808097 -3.9451174 5.3289717
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.254969501
[2,] -0.923838597
[3,] 0.004474975
[4,] 0.439364075
[5,] 1.303436675
>
> rowApply(tmp,sum)
[1] -1.8496992 1.5591725 0.2213933 2.7016786 4.0374460 -2.0237711
[7] -0.5351482 -4.6470570 4.3848801 3.1189704
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 6 4 5 8 8 2 1 4 1 7
[2,] 3 6 7 6 10 3 2 6 4 9
[3,] 9 3 8 5 9 1 4 1 7 1
[4,] 4 10 3 2 3 6 8 7 6 2
[5,] 5 8 6 10 4 8 6 8 5 8
[6,] 7 7 4 1 1 7 10 5 2 10
[7,] 10 5 10 7 2 10 3 3 10 4
[8,] 1 1 2 9 7 5 9 10 9 3
[9,] 2 2 1 4 6 4 5 2 3 6
[10,] 8 9 9 3 5 9 7 9 8 5
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.7239684 2.0745638 -3.4428708 1.5637966 -1.5426586 3.0986974
[7] -0.3267074 0.5639719 1.0692225 -0.9118338 -3.6558237 2.9728357
[13] -1.1786576 2.6106818 -1.2616367 -0.4159976 -0.7465305 2.5173863
[19] -1.4732479 0.1942102
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.7217820
[2,] -0.4952863
[3,] 0.2285506
[4,] 1.2959689
[5,] 1.4165171
>
> rowApply(tmp,sum)
[1] -9.088285 6.489794 3.208476 -3.741285 5.564671
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 20 4 10 1 19
[2,] 18 18 20 4 6
[3,] 12 8 3 2 7
[4,] 9 12 12 12 18
[5,] 11 5 15 8 2
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.4165171 0.3740812 -0.2883998 -0.65293633 -0.5241122 -0.7814729
[2,] -0.4952863 1.2562876 0.3078191 0.43350599 -0.2441207 0.3363411
[3,] 0.2285506 1.9678001 -1.5507445 0.46923519 0.8315480 1.6957607
[4,] -1.7217820 -1.2727210 -1.6655001 0.01891481 -0.6736950 0.8279540
[5,] 1.2959689 -0.2508840 -0.2460455 1.29507691 -0.9322788 1.0201145
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.2754312 -0.62479384 0.4440017 -1.0565185 -0.1490794 -0.2875128
[2,] 0.8902823 0.41625447 0.4728899 0.7608527 -1.1424459 1.4066666
[3,] -1.6688101 1.00167422 0.5254286 -0.5082265 0.3120210 -0.2046118
[4,] -0.1920376 -0.31175529 -0.9758261 0.2243776 -0.8725282 1.6375429
[5,] 0.9192892 0.08259235 0.6027284 -0.3323191 -1.8037912 0.4207507
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.67089043 -0.7239356 0.07358687 -1.6516028 -0.9213401 -1.0480546
[2,] -1.13606547 1.8108056 -0.14303862 0.8817020 -0.0746163 0.4165129
[3,] 0.72877627 0.2235431 -0.34229583 0.9414656 1.0032668 -0.2680094
[4,] 0.95951959 0.5994853 -0.48101592 -1.4185518 -1.0471541 1.4520375
[5,] -0.05999752 0.7007834 -0.36887316 0.8309893 0.2933131 1.9648998
[,19] [,20]
[1,] -0.9233739 0.1829824
[2,] 1.0363775 -0.7009310
[3,] -1.7859256 -0.3919710
[4,] 0.4780895 0.6933603
[5,] -0.2784154 0.4107695
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 652 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 564 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.7414691 -0.3657938 -0.2302828 1.100678 -1.41717 -0.08823351 0.776515
col8 col9 col10 col11 col12 col13 col14
row1 -0.9604654 -1.785666 1.148775 -0.5213503 -0.280173 -1.657487 -1.32356
col15 col16 col17 col18 col19 col20
row1 0.3246703 0.01819765 0.7177681 -0.8674265 -0.3022862 -0.6638837
> tmp[,"col10"]
col10
row1 1.14877487
row2 0.30475074
row3 -1.62862950
row4 -0.07097863
row5 -0.37763039
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.7414691 -0.3657938 -0.2302828 1.100678 -1.4171701 -0.08823351
row5 1.4310910 -1.0438559 -1.5963899 -1.476185 0.6449062 0.56738308
col7 col8 col9 col10 col11 col12
row1 0.7765150 -0.9604654 -1.785666 1.1487749 -0.5213503 -0.2801730
row5 -0.5550359 -1.1199685 1.069073 -0.3776304 2.1827612 -0.6993839
col13 col14 col15 col16 col17 col18
row1 -1.6574866 -1.323559902 0.32467033 0.01819765 0.7177681 -0.8674265
row5 -0.8375662 0.007600643 -0.03859187 0.81415265 -0.7411245 1.3938475
col19 col20
row1 -0.3022862 -0.6638837
row5 0.6419264 1.3414397
> tmp[,c("col6","col20")]
col6 col20
row1 -0.08823351 -0.6638837
row2 -0.77420678 0.1080168
row3 1.20565382 1.0064869
row4 1.44204865 -1.0216123
row5 0.56738308 1.3414397
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.08823351 -0.6638837
row5 0.56738308 1.3414397
>
>
>
>
> 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 50.24484 50.70382 48.97001 50.11648 50.60298 103.8971 51.05026 49.55828
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.07281 49.64633 48.71206 50.66906 50.07751 51.24194 48.7012 50.87712
col17 col18 col19 col20
row1 49.82139 50.56123 50.78529 104.1122
> tmp[,"col10"]
col10
row1 49.64633
row2 28.86488
row3 28.69857
row4 32.17390
row5 48.82963
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.24484 50.70382 48.97001 50.11648 50.60298 103.8971 51.05026 49.55828
row5 50.24964 50.86908 49.02581 49.64050 51.30443 104.7424 50.71863 51.08539
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.07281 49.64633 48.71206 50.66906 50.07751 51.24194 48.70120 50.87712
row5 49.05347 48.82963 49.35721 50.35671 50.25847 49.52959 50.03544 50.63642
col17 col18 col19 col20
row1 49.82139 50.56123 50.78529 104.1122
row5 52.28953 51.92547 49.28946 105.0072
> tmp[,c("col6","col20")]
col6 col20
row1 103.89713 104.11223
row2 75.73350 74.25359
row3 74.52082 73.60406
row4 74.92461 74.28833
row5 104.74242 105.00721
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 103.8971 104.1122
row5 104.7424 105.0072
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 103.8971 104.1122
row5 104.7424 105.0072
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.2987354
[2,] 1.4918104
[3,] -2.3612210
[4,] 0.5604242
[5,] -0.7375347
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.7491030 -0.41520193
[2,] -1.0887354 0.13029554
[3,] -1.2506092 0.03341121
[4,] -1.6668789 -0.97622740
[5,] -0.3920587 -0.26629006
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.001063621 -0.2790076
[2,] -0.807193809 -0.4344681
[3,] 0.603929380 1.3777450
[4,] 0.639142192 1.5576519
[5,] 0.551880358 -1.2630345
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.001063621
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.001063621
[2,] -0.807193809
>
>
>
> 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 -1.0061454 -0.2912972 0.4444438 -0.7801667 -0.6752512 0.1447177 -0.2602785
row1 -0.6746347 -0.1551517 0.9370214 -0.4742250 -1.1608996 0.7800360 0.5114938
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -0.7527318 -0.8196707 1.2962193 0.5146761 0.8625402 -0.2379729 0.2091979
row1 -2.5401220 -0.7004739 -0.6540136 1.6203306 0.2098835 -1.4040716 -0.1228161
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -1.881543 -0.5803100 0.3693078 1.499268 -0.3696925 -1.371220
row1 1.441305 0.4694894 0.6337575 1.259213 -0.7849072 -1.793417
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -2.020888 0.5915558 -0.6664236 1.343238 0.3826818 0.4198488 0.467582
[,8] [,9] [,10]
row2 0.463626 -2.679671 0.504501
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.2320461 0.2104604 -1.443834 -0.6423 -0.1311506 0.8913109 -0.4657504
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.3618019 1.13328 1.44776 0.2442518 0.1386196 0.05147564 1.519952
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.290434 0.7870306 0.4841558 0.9054032 0.7998726 1.154784
>
>
> 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: 0x55fb83535490>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM3db86918d0ce8d"
[2] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM3db869198a35b7"
[3] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM3db869480d67f"
[4] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM3db869ce9f122"
[5] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM3db869607bb041"
[6] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM3db86925551f7b"
[7] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM3db8695340ff48"
[8] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM3db86918ce9af"
[9] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM3db8693f83e6c2"
[10] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM3db8694ae0718"
[11] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM3db86913680cf0"
[12] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM3db86963a28eb3"
[13] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM3db8692705afad"
[14] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM3db8695b844a8e"
[15] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM3db8694a0d24ea"
>
>
> ### 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: 0x55fb841bb220>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x55fb841bb220>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x55fb841bb220>
> rowMedians(tmp)
[1] 0.383833691 -0.205867451 -0.048397838 0.044208029 -0.164468833
[6] -0.100357700 0.258536817 0.072768031 0.110674159 0.677768519
[11] -0.260401184 -0.296242972 0.079776102 0.466379015 -0.187572790
[16] -0.653546142 -0.495854981 0.357411302 -0.029040879 -0.256961893
[21] 0.345627529 0.722865877 -0.314010433 -0.399574510 0.475873389
[26] -0.044881364 -0.019547117 -0.002785882 -0.238251453 -0.058221012
[31] -0.483635176 -0.177880517 -0.570981498 -0.422102541 0.034683583
[36] -0.045998976 0.487482883 -0.017217783 0.494670000 0.578940276
[41] -0.270849702 0.168791073 -0.193599256 -0.185622228 0.315957544
[46] -0.271853561 -0.136393395 -0.307980620 0.409755790 0.101783775
[51] 0.176006667 0.314330067 -0.364801795 -0.221859356 0.050015336
[56] -0.513778750 -0.469276812 0.231056189 -0.188516407 0.593686441
[61] 0.173120126 0.134047724 -0.260338861 0.248805208 -0.111632170
[66] -0.658564639 0.092907564 0.036365475 -0.348265880 -0.220025957
[71] 0.468884185 0.383756909 -0.031921186 0.169002287 -0.368093172
[76] -0.301076583 0.152882621 -0.372186767 0.114938567 -0.304841780
[81] -0.627787799 -0.089005010 -0.612621735 0.185796770 0.246619093
[86] -0.135622317 0.375416675 -0.087829453 0.461869509 0.608497531
[91] 0.524066740 0.252955466 -0.367381877 -0.460825188 -0.051701630
[96] -0.431594290 -0.045156731 0.247346785 0.775464223 0.152260191
[101] 0.342671314 0.110551766 -0.076574273 0.478698527 -0.361945322
[106] 0.023859732 0.063797575 -0.267208281 0.270876203 -0.204779696
[111] -0.023530972 -0.056235540 -0.564190326 -0.325832256 0.393367729
[116] -0.083235444 0.156283660 -0.179051030 -0.167323625 -0.096513225
[121] -0.201397162 -0.935031883 -0.392115861 -0.133775172 0.186882066
[126] -0.445589881 -0.297180151 -0.001305476 -0.042327345 0.274208740
[131] -0.124109554 0.146431586 0.089981203 0.366601493 0.001899127
[136] -0.268586197 -0.066384862 0.414784991 0.060430908 0.088272646
[141] 0.061788792 -0.547103152 0.030570165 0.438688235 0.250239336
[146] -0.957776460 -0.289683793 0.157963589 -0.077981223 0.720721800
[151] -0.486253035 -0.493931338 0.323984484 0.309705906 0.501452872
[156] 0.053507519 0.159809914 0.005267675 -0.649927699 -0.637208248
[161] 0.440378488 0.689606340 -0.490017706 0.739530072 0.206961529
[166] -0.167919480 0.692287632 0.310409913 -0.183122140 -0.611487883
[171] -0.179419694 0.224436619 0.042390497 -0.170208366 -0.166718155
[176] -0.566027910 0.187859998 0.269730371 -0.173363019 -0.664787783
[181] 0.269419062 -0.029438492 -0.019805494 -0.253065054 0.222067568
[186] 0.013351950 0.066035430 0.312568919 0.179575406 -0.161081366
[191] -0.486813520 -0.386165110 0.189543004 0.216736809 0.212586825
[196] 0.481678977 0.149001542 -0.084207844 0.268389711 0.230044858
[201] -0.085126658 0.309516248 -0.104454596 -0.083728661 -0.234559099
[206] -0.187110590 -0.280518190 0.112288461 -0.025096759 -0.201831599
[211] 0.435166743 -0.109133556 0.153127039 -0.006279363 0.505144468
[216] -0.317030940 0.224982238 -0.255990367 0.159076123 0.167267295
[221] -0.093365316 0.189240874 0.081071376 -0.267178897 -0.196530110
[226] 0.306076878 0.443461926 -0.125357894 0.177770961 0.740603605
>
> proc.time()
user system elapsed
1.363 1.640 3.015
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-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: 0x5573624f0310>
> .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: 0x5573624f0310>
> .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: 0x5573624f0310>
> .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: 0x5573624f0310>
> 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: 0x557360a785c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x557360a785c0>
> .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: 0x557360a785c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x557360a785c0>
> .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: 0x557360a785c0>
> 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: 0x5573600b7a80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5573600b7a80>
> .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: 0x5573600b7a80>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5573600b7a80>
> .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: 0x5573600b7a80>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5573600b7a80>
> .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: 0x5573600b7a80>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5573600b7a80>
> .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: 0x5573600b7a80>
> 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: 0x557360cff230>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x557360cff230>
> .Call("R_bm_AddColumn",P)
<pointer: 0x557360cff230>
> .Call("R_bm_AddColumn",P)
<pointer: 0x557360cff230>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3dc72f697ab83d" "BufferedMatrixFile3dc72f7f55a184"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3dc72f697ab83d" "BufferedMatrixFile3dc72f7f55a184"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x557361b3d8f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x557361b3d8f0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x557361b3d8f0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x557361b3d8f0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x557361b3d8f0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x557361b3d8f0>
> .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: 0x5573608cd530>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5573608cd530>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5573608cd530>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5573608cd530>
> 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: 0x557360d4f8b0>
> .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: 0x557360d4f8b0>
> rm(P)
>
> proc.time()
user system elapsed
0.264 0.043 0.297
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.3.1 (2023-06-16) -- "Beagle Scouts"
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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
0.253 0.037 0.280