| Back to Multiple platform build/check report for BioC 3.17 |
|
This page was generated on 2023-04-12 10:55:22 -0400 (Wed, 12 Apr 2023).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 22.04.1 LTS) | x86_64 | 4.3.0 alpha (2023-04-03 r84154) | 4547 |
| nebbiolo2 | Linux (Ubuntu 20.04.5 LTS) | x86_64 | R Under development (unstable) (2023-02-14 r83833) -- "Unsuffered Consequences" | 4333 |
| 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 | ||||
|
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. Note: If "R CMD check" recently failed on the Linux builder over a missing dependency, add the missing dependency to "Suggests" in your DESCRIPTION file. See the Renviron.bioc for details. |
| Package 244/2207 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.63.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 22.04.1 LTS) / x86_64 | OK | OK | OK | |||||||||
| nebbiolo2 | Linux (Ubuntu 20.04.5 LTS) / x86_64 | OK | OK | OK | ||||||||||
| Package: BufferedMatrix |
| Version: 1.63.0 |
| 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_1.63.0.tar.gz |
| StartedAt: 2023-04-11 19:00:35 -0400 (Tue, 11 Apr 2023) |
| EndedAt: 2023-04-11 19:00:59 -0400 (Tue, 11 Apr 2023) |
| EllapsedTime: 24.3 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_1.63.0.tar.gz
###
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##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.3.0 alpha (2023-04-03 r84154)
* using platform: x86_64-pc-linux-gnu (64-bit)
* R was compiled by
gcc (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
GNU Fortran (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
* running under: Ubuntu 22.04.2 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.63.0’
* 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 11.3.0-1ubuntu1~22.04) 11.3.0’
* 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 11.3.0-1ubuntu1~22.04) 11.3.0’
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 4.3.0 alpha (2023-04-03 r84154)
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
0.236 0.078 0.303
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.3.0 alpha (2023-04-03 r84154)
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 457438 24.5 981480 52.5 650971 34.8
Vcells 842767 6.5 8388608 64.0 2064055 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] "Tue Apr 11 19:00:50 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] "Tue Apr 11 19:00:50 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: 0x5560d114cf50>
>
>
>
> 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] "Tue Apr 11 19:00:51 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] "Tue Apr 11 19:00:51 2023"
>
> ColMode(tmp2)
<pointer: 0x5560d114cf50>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.70787207 -1.1855258 -0.2127399 1.0386479
[2,] -0.00964319 -0.8451245 -2.5099201 0.4125944
[3,] 0.91671045 1.1841789 -1.1460604 1.3862741
[4,] 0.13959057 -0.1108675 1.0594453 -0.6045817
> 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,] 99.70787207 1.1855258 0.2127399 1.0386479
[2,] 0.00964319 0.8451245 2.5099201 0.4125944
[3,] 0.91671045 1.1841789 1.1460604 1.3862741
[4,] 0.13959057 0.1108675 1.0594453 0.6045817
> 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,] 9.98538292 1.0888185 0.4612374 1.0191408
[2,] 0.09819975 0.9193065 1.5842727 0.6423351
[3,] 0.95744997 1.0881998 1.0705421 1.1774014
[4,] 0.37361822 0.3329677 1.0292936 0.7775485
>
> 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,] 224.56170 37.07371 29.82511 36.23006
[2,] 25.99164 35.03819 43.35265 31.83595
[3,] 35.49121 37.06618 36.85148 38.16029
[4,] 28.87577 28.44054 36.35238 33.38007
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5560d0b3e160>
> exp(tmp5)
<pointer: 0x5560d0b3e160>
> log(tmp5,2)
<pointer: 0x5560d0b3e160>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.3958
> Min(tmp5)
[1] 54.09819
> mean(tmp5)
[1] 73.21703
> Sum(tmp5)
[1] 14643.41
> Var(tmp5)
[1] 846.5524
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.35985 70.65466 74.07761 70.68985 68.83934 72.97802 73.52163 72.36095
[9] 70.46942 68.21898
> rowSums(tmp5)
[1] 1807.197 1413.093 1481.552 1413.797 1376.787 1459.560 1470.433 1447.219
[9] 1409.388 1364.380
> rowVars(tmp5)
[1] 7940.05590 80.35704 28.03498 107.15613 40.62657 61.53290
[7] 37.42724 82.46514 46.84191 62.92403
> rowSd(tmp5)
[1] 89.106991 8.964209 5.294807 10.351625 6.373897 7.844291 6.117780
[8] 9.081032 6.844115 7.932467
> rowMax(tmp5)
[1] 467.39576 90.23286 82.03159 90.64828 85.23538 90.25740 83.49470
[8] 91.25572 82.12168 81.09880
> rowMin(tmp5)
[1] 56.53147 54.09819 62.21934 58.91629 60.05593 61.93981 64.93922 59.31204
[9] 54.69786 54.41569
>
> colMeans(tmp5)
[1] 110.08899 72.15717 72.01882 73.47378 64.11119 71.97216 70.49241
[8] 69.09729 70.99834 77.13748 72.16284 74.35516 69.88679 70.08443
[15] 70.44703 71.04836 70.04676 71.00578 71.51213 72.24372
> colSums(tmp5)
[1] 1100.8899 721.5717 720.1882 734.7378 641.1119 719.7216 704.9241
[8] 690.9729 709.9834 771.3748 721.6284 743.5516 698.8679 700.8443
[15] 704.4703 710.4836 700.4676 710.0578 715.1213 722.4372
> colVars(tmp5)
[1] 15825.16460 45.45916 82.94490 34.95374 37.24411 84.26765
[7] 64.36566 42.49717 69.49766 50.35644 86.23566 48.42834
[13] 56.74439 77.71106 51.80954 38.71684 87.28497 75.13603
[19] 67.07674 74.76290
> colSd(tmp5)
[1] 125.798110 6.742341 9.107409 5.912169 6.102795 9.179742
[7] 8.022821 6.518986 8.336525 7.096227 9.286316 6.959048
[13] 7.532887 8.815388 7.197884 6.222286 9.342642 8.668104
[19] 8.190039 8.646554
> colMax(tmp5)
[1] 467.39576 84.20282 90.23286 81.95847 73.12949 89.99577 90.25740
[8] 77.74719 90.64828 91.25572 84.13151 83.30479 82.87723 85.23538
[15] 82.12168 78.67137 81.95479 82.62963 82.26016 83.69180
> colMin(tmp5)
[1] 54.09819 59.19527 60.66230 64.17292 54.90333 63.06616 63.94346 56.53147
[9] 62.21934 67.29959 54.41569 60.56813 58.91629 59.82682 59.17976 59.31204
[17] 54.69786 58.13758 60.05593 61.03463
>
>
> ### 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] 90.35985 70.65466 74.07761 70.68985 68.83934 NA 73.52163 72.36095
[9] 70.46942 68.21898
> rowSums(tmp5)
[1] 1807.197 1413.093 1481.552 1413.797 1376.787 NA 1470.433 1447.219
[9] 1409.388 1364.380
> rowVars(tmp5)
[1] 7940.05590 80.35704 28.03498 107.15613 40.62657 59.01465
[7] 37.42724 82.46514 46.84191 62.92403
> rowSd(tmp5)
[1] 89.106991 8.964209 5.294807 10.351625 6.373897 7.682100 6.117780
[8] 9.081032 6.844115 7.932467
> rowMax(tmp5)
[1] 467.39576 90.23286 82.03159 90.64828 85.23538 NA 83.49470
[8] 91.25572 82.12168 81.09880
> rowMin(tmp5)
[1] 56.53147 54.09819 62.21934 58.91629 60.05593 NA 64.93922 59.31204
[9] 54.69786 54.41569
>
> colMeans(tmp5)
[1] 110.08899 72.15717 72.01882 73.47378 NA 71.97216 70.49241
[8] 69.09729 70.99834 77.13748 72.16284 74.35516 69.88679 70.08443
[15] 70.44703 71.04836 70.04676 71.00578 71.51213 72.24372
> colSums(tmp5)
[1] 1100.8899 721.5717 720.1882 734.7378 NA 719.7216 704.9241
[8] 690.9729 709.9834 771.3748 721.6284 743.5516 698.8679 700.8443
[15] 704.4703 710.4836 700.4676 710.0578 715.1213 722.4372
> colVars(tmp5)
[1] 15825.16460 45.45916 82.94490 34.95374 NA 84.26765
[7] 64.36566 42.49717 69.49766 50.35644 86.23566 48.42834
[13] 56.74439 77.71106 51.80954 38.71684 87.28497 75.13603
[19] 67.07674 74.76290
> colSd(tmp5)
[1] 125.798110 6.742341 9.107409 5.912169 NA 9.179742
[7] 8.022821 6.518986 8.336525 7.096227 9.286316 6.959048
[13] 7.532887 8.815388 7.197884 6.222286 9.342642 8.668104
[19] 8.190039 8.646554
> colMax(tmp5)
[1] 467.39576 84.20282 90.23286 81.95847 NA 89.99577 90.25740
[8] 77.74719 90.64828 91.25572 84.13151 83.30479 82.87723 85.23538
[15] 82.12168 78.67137 81.95479 82.62963 82.26016 83.69180
> colMin(tmp5)
[1] 54.09819 59.19527 60.66230 64.17292 NA 63.06616 63.94346 56.53147
[9] 62.21934 67.29959 54.41569 60.56813 58.91629 59.82682 59.17976 59.31204
[17] 54.69786 58.13758 60.05593 61.03463
>
> Max(tmp5,na.rm=TRUE)
[1] 467.3958
> Min(tmp5,na.rm=TRUE)
[1] 54.09819
> mean(tmp5,na.rm=TRUE)
[1] 73.26886
> Sum(tmp5,na.rm=TRUE)
[1] 14580.5
> Var(tmp5,na.rm=TRUE)
[1] 850.2879
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.35985 70.65466 74.07761 70.68985 68.83934 73.50832 73.52163 72.36095
[9] 70.46942 68.21898
> rowSums(tmp5,na.rm=TRUE)
[1] 1807.197 1413.093 1481.552 1413.797 1376.787 1396.658 1470.433 1447.219
[9] 1409.388 1364.380
> rowVars(tmp5,na.rm=TRUE)
[1] 7940.05590 80.35704 28.03498 107.15613 40.62657 59.01465
[7] 37.42724 82.46514 46.84191 62.92403
> rowSd(tmp5,na.rm=TRUE)
[1] 89.106991 8.964209 5.294807 10.351625 6.373897 7.682100 6.117780
[8] 9.081032 6.844115 7.932467
> rowMax(tmp5,na.rm=TRUE)
[1] 467.39576 90.23286 82.03159 90.64828 85.23538 90.25740 83.49470
[8] 91.25572 82.12168 81.09880
> rowMin(tmp5,na.rm=TRUE)
[1] 56.53147 54.09819 62.21934 58.91629 60.05593 61.93981 64.93922 59.31204
[9] 54.69786 54.41569
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.08899 72.15717 72.01882 73.47378 64.24550 71.97216 70.49241
[8] 69.09729 70.99834 77.13748 72.16284 74.35516 69.88679 70.08443
[15] 70.44703 71.04836 70.04676 71.00578 71.51213 72.24372
> colSums(tmp5,na.rm=TRUE)
[1] 1100.8899 721.5717 720.1882 734.7378 578.2095 719.7216 704.9241
[8] 690.9729 709.9834 771.3748 721.6284 743.5516 698.8679 700.8443
[15] 704.4703 710.4836 700.4676 710.0578 715.1213 722.4372
> colVars(tmp5,na.rm=TRUE)
[1] 15825.16460 45.45916 82.94490 34.95374 41.69668 84.26765
[7] 64.36566 42.49717 69.49766 50.35644 86.23566 48.42834
[13] 56.74439 77.71106 51.80954 38.71684 87.28497 75.13603
[19] 67.07674 74.76290
> colSd(tmp5,na.rm=TRUE)
[1] 125.798110 6.742341 9.107409 5.912169 6.457297 9.179742
[7] 8.022821 6.518986 8.336525 7.096227 9.286316 6.959048
[13] 7.532887 8.815388 7.197884 6.222286 9.342642 8.668104
[19] 8.190039 8.646554
> colMax(tmp5,na.rm=TRUE)
[1] 467.39576 84.20282 90.23286 81.95847 73.12949 89.99577 90.25740
[8] 77.74719 90.64828 91.25572 84.13151 83.30479 82.87723 85.23538
[15] 82.12168 78.67137 81.95479 82.62963 82.26016 83.69180
> colMin(tmp5,na.rm=TRUE)
[1] 54.09819 59.19527 60.66230 64.17292 54.90333 63.06616 63.94346 56.53147
[9] 62.21934 67.29959 54.41569 60.56813 58.91629 59.82682 59.17976 59.31204
[17] 54.69786 58.13758 60.05593 61.03463
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.35985 70.65466 74.07761 70.68985 68.83934 NaN 73.52163 72.36095
[9] 70.46942 68.21898
> rowSums(tmp5,na.rm=TRUE)
[1] 1807.197 1413.093 1481.552 1413.797 1376.787 0.000 1470.433 1447.219
[9] 1409.388 1364.380
> rowVars(tmp5,na.rm=TRUE)
[1] 7940.05590 80.35704 28.03498 107.15613 40.62657 NA
[7] 37.42724 82.46514 46.84191 62.92403
> rowSd(tmp5,na.rm=TRUE)
[1] 89.106991 8.964209 5.294807 10.351625 6.373897 NA 6.117780
[8] 9.081032 6.844115 7.932467
> rowMax(tmp5,na.rm=TRUE)
[1] 467.39576 90.23286 82.03159 90.64828 85.23538 NA 83.49470
[8] 91.25572 82.12168 81.09880
> rowMin(tmp5,na.rm=TRUE)
[1] 56.53147 54.09819 62.21934 58.91629 60.05593 NA 64.93922 59.31204
[9] 54.69786 54.41569
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.91248 70.81876 72.81640 73.34190 NaN 72.96172 68.29630
[8] 68.38200 71.63354 77.45443 72.31494 74.63219 69.64899 70.78106
[15] 69.84014 70.25261 68.78779 70.99561 72.57572 71.17963
> colSums(tmp5,na.rm=TRUE)
[1] 1025.2124 637.3689 655.3476 660.0771 0.0000 656.6555 614.6667
[8] 615.4380 644.7019 697.0899 650.8345 671.6897 626.8409 637.0295
[15] 628.5613 632.2735 619.0901 638.9605 653.1815 640.6167
> colVars(tmp5,na.rm=TRUE)
[1] 17638.84556 30.98911 86.15644 39.12731 NA 83.78487
[7] 18.15378 42.05349 73.64566 55.52085 96.75484 53.61847
[13] 63.20128 81.96545 54.14225 36.43278 80.36430 84.52687
[19] 62.73503 71.37013
> colSd(tmp5,na.rm=TRUE)
[1] 132.811316 5.566786 9.282049 6.255183 NA 9.153408
[7] 4.260726 6.484866 8.581705 7.451231 9.836404 7.322464
[13] 7.949923 9.053477 7.358142 6.035957 8.964614 9.193850
[19] 7.920545 8.448085
> colMax(tmp5,na.rm=TRUE)
[1] 467.39576 77.16407 90.23286 81.95847 -Inf 89.99577 76.85093
[8] 77.74719 90.64828 91.25572 84.13151 83.30479 82.87723 85.23538
[15] 82.12168 78.67137 81.95479 82.62963 82.26016 83.69180
> colMin(tmp5,na.rm=TRUE)
[1] 54.09819 59.19527 60.66230 64.17292 Inf 63.11694 63.94346 56.53147
[9] 62.21934 67.29959 54.41569 60.56813 58.91629 59.82682 59.17976 59.31204
[17] 54.69786 58.13758 60.05593 61.03463
>
>
>
>
> 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] 300.6284 272.1526 139.5076 346.7385 141.8787 313.8187 244.2605 148.3189
[9] 270.1720 219.4099
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 300.6284 272.1526 139.5076 346.7385 141.8787 313.8187 244.2605 148.3189
[9] 270.1720 219.4099
>
>
>
> 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 -2.842171e-14 -5.684342e-14 -2.842171e-14
[6] -1.421085e-13 4.263256e-14 -1.705303e-13 1.136868e-13 5.684342e-14
[11] 0.000000e+00 2.273737e-13 0.000000e+00 -2.842171e-14 -2.842171e-14
[16] 5.684342e-14 2.842171e-14 -1.136868e-13 2.842171e-14 1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## 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)
+ }
2 5
1 19
1 8
10 14
6 15
4 20
5 16
2 12
9 5
7 5
7 2
4 4
5 9
1 15
3 14
3 14
10 2
1 17
8 14
5 18
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] 2.873938
> Min(tmp)
[1] -2.715211
> mean(tmp)
[1] -0.1407467
> Sum(tmp)
[1] -14.07467
> Var(tmp)
[1] 1.277883
>
> rowMeans(tmp)
[1] -0.1407467
> rowSums(tmp)
[1] -14.07467
> rowVars(tmp)
[1] 1.277883
> rowSd(tmp)
[1] 1.130435
> rowMax(tmp)
[1] 2.873938
> rowMin(tmp)
[1] -2.715211
>
> colMeans(tmp)
[1] 0.08337627 -0.19680023 -0.43397779 -2.61514103 1.40840188 -0.78220811
[7] 1.16667541 -2.15671787 0.93614073 -0.04082392 -0.08869283 -1.19015470
[13] -0.26624963 -2.12708119 1.03026065 1.95110313 2.34017387 -0.23695277
[19] -0.40486678 0.05848853 -0.98589836 0.51745930 0.53585315 -0.67654436
[25] 1.76119390 -0.24689453 -1.30927565 -2.12335980 -1.06123725 -0.57753141
[31] 0.49615261 -0.66324252 -0.51125748 -0.14340492 -0.11887199 1.84714897
[37] 1.44785233 0.03640784 0.82185364 -2.10311411 -0.06588743 -0.65927058
[43] -0.33062806 -0.62121912 -1.21685301 -0.25537669 0.65166356 -1.56848475
[49] -2.04762841 0.65817854 0.99307052 0.89952243 0.03505215 -0.38583707
[55] -0.80106793 0.77507340 -1.10726634 1.18525352 -0.81732022 1.32200234
[61] 0.76466794 -0.67667941 1.45553704 -0.33991142 0.40864290 -2.71521148
[67] -0.14881490 -0.80329537 0.78759498 -1.73107164 -0.12274374 0.16879775
[73] 0.91519397 -0.32791892 0.50453196 0.09281214 1.38653627 0.03144121
[79] -2.01380855 0.10248020 -1.65016910 -0.50508217 -0.98373261 0.62526710
[85] -1.44755328 0.29010774 1.13026304 1.22144956 -1.99667791 -1.39847741
[91] -0.24304818 -1.36548015 0.02722734 -1.53165610 2.87393793 -0.63482400
[97] 0.29138720 -0.38165219 0.55782731 1.28621036
> colSums(tmp)
[1] 0.08337627 -0.19680023 -0.43397779 -2.61514103 1.40840188 -0.78220811
[7] 1.16667541 -2.15671787 0.93614073 -0.04082392 -0.08869283 -1.19015470
[13] -0.26624963 -2.12708119 1.03026065 1.95110313 2.34017387 -0.23695277
[19] -0.40486678 0.05848853 -0.98589836 0.51745930 0.53585315 -0.67654436
[25] 1.76119390 -0.24689453 -1.30927565 -2.12335980 -1.06123725 -0.57753141
[31] 0.49615261 -0.66324252 -0.51125748 -0.14340492 -0.11887199 1.84714897
[37] 1.44785233 0.03640784 0.82185364 -2.10311411 -0.06588743 -0.65927058
[43] -0.33062806 -0.62121912 -1.21685301 -0.25537669 0.65166356 -1.56848475
[49] -2.04762841 0.65817854 0.99307052 0.89952243 0.03505215 -0.38583707
[55] -0.80106793 0.77507340 -1.10726634 1.18525352 -0.81732022 1.32200234
[61] 0.76466794 -0.67667941 1.45553704 -0.33991142 0.40864290 -2.71521148
[67] -0.14881490 -0.80329537 0.78759498 -1.73107164 -0.12274374 0.16879775
[73] 0.91519397 -0.32791892 0.50453196 0.09281214 1.38653627 0.03144121
[79] -2.01380855 0.10248020 -1.65016910 -0.50508217 -0.98373261 0.62526710
[85] -1.44755328 0.29010774 1.13026304 1.22144956 -1.99667791 -1.39847741
[91] -0.24304818 -1.36548015 0.02722734 -1.53165610 2.87393793 -0.63482400
[97] 0.29138720 -0.38165219 0.55782731 1.28621036
> 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] 0.08337627 -0.19680023 -0.43397779 -2.61514103 1.40840188 -0.78220811
[7] 1.16667541 -2.15671787 0.93614073 -0.04082392 -0.08869283 -1.19015470
[13] -0.26624963 -2.12708119 1.03026065 1.95110313 2.34017387 -0.23695277
[19] -0.40486678 0.05848853 -0.98589836 0.51745930 0.53585315 -0.67654436
[25] 1.76119390 -0.24689453 -1.30927565 -2.12335980 -1.06123725 -0.57753141
[31] 0.49615261 -0.66324252 -0.51125748 -0.14340492 -0.11887199 1.84714897
[37] 1.44785233 0.03640784 0.82185364 -2.10311411 -0.06588743 -0.65927058
[43] -0.33062806 -0.62121912 -1.21685301 -0.25537669 0.65166356 -1.56848475
[49] -2.04762841 0.65817854 0.99307052 0.89952243 0.03505215 -0.38583707
[55] -0.80106793 0.77507340 -1.10726634 1.18525352 -0.81732022 1.32200234
[61] 0.76466794 -0.67667941 1.45553704 -0.33991142 0.40864290 -2.71521148
[67] -0.14881490 -0.80329537 0.78759498 -1.73107164 -0.12274374 0.16879775
[73] 0.91519397 -0.32791892 0.50453196 0.09281214 1.38653627 0.03144121
[79] -2.01380855 0.10248020 -1.65016910 -0.50508217 -0.98373261 0.62526710
[85] -1.44755328 0.29010774 1.13026304 1.22144956 -1.99667791 -1.39847741
[91] -0.24304818 -1.36548015 0.02722734 -1.53165610 2.87393793 -0.63482400
[97] 0.29138720 -0.38165219 0.55782731 1.28621036
> colMin(tmp)
[1] 0.08337627 -0.19680023 -0.43397779 -2.61514103 1.40840188 -0.78220811
[7] 1.16667541 -2.15671787 0.93614073 -0.04082392 -0.08869283 -1.19015470
[13] -0.26624963 -2.12708119 1.03026065 1.95110313 2.34017387 -0.23695277
[19] -0.40486678 0.05848853 -0.98589836 0.51745930 0.53585315 -0.67654436
[25] 1.76119390 -0.24689453 -1.30927565 -2.12335980 -1.06123725 -0.57753141
[31] 0.49615261 -0.66324252 -0.51125748 -0.14340492 -0.11887199 1.84714897
[37] 1.44785233 0.03640784 0.82185364 -2.10311411 -0.06588743 -0.65927058
[43] -0.33062806 -0.62121912 -1.21685301 -0.25537669 0.65166356 -1.56848475
[49] -2.04762841 0.65817854 0.99307052 0.89952243 0.03505215 -0.38583707
[55] -0.80106793 0.77507340 -1.10726634 1.18525352 -0.81732022 1.32200234
[61] 0.76466794 -0.67667941 1.45553704 -0.33991142 0.40864290 -2.71521148
[67] -0.14881490 -0.80329537 0.78759498 -1.73107164 -0.12274374 0.16879775
[73] 0.91519397 -0.32791892 0.50453196 0.09281214 1.38653627 0.03144121
[79] -2.01380855 0.10248020 -1.65016910 -0.50508217 -0.98373261 0.62526710
[85] -1.44755328 0.29010774 1.13026304 1.22144956 -1.99667791 -1.39847741
[91] -0.24304818 -1.36548015 0.02722734 -1.53165610 2.87393793 -0.63482400
[97] 0.29138720 -0.38165219 0.55782731 1.28621036
> colMedians(tmp)
[1] 0.08337627 -0.19680023 -0.43397779 -2.61514103 1.40840188 -0.78220811
[7] 1.16667541 -2.15671787 0.93614073 -0.04082392 -0.08869283 -1.19015470
[13] -0.26624963 -2.12708119 1.03026065 1.95110313 2.34017387 -0.23695277
[19] -0.40486678 0.05848853 -0.98589836 0.51745930 0.53585315 -0.67654436
[25] 1.76119390 -0.24689453 -1.30927565 -2.12335980 -1.06123725 -0.57753141
[31] 0.49615261 -0.66324252 -0.51125748 -0.14340492 -0.11887199 1.84714897
[37] 1.44785233 0.03640784 0.82185364 -2.10311411 -0.06588743 -0.65927058
[43] -0.33062806 -0.62121912 -1.21685301 -0.25537669 0.65166356 -1.56848475
[49] -2.04762841 0.65817854 0.99307052 0.89952243 0.03505215 -0.38583707
[55] -0.80106793 0.77507340 -1.10726634 1.18525352 -0.81732022 1.32200234
[61] 0.76466794 -0.67667941 1.45553704 -0.33991142 0.40864290 -2.71521148
[67] -0.14881490 -0.80329537 0.78759498 -1.73107164 -0.12274374 0.16879775
[73] 0.91519397 -0.32791892 0.50453196 0.09281214 1.38653627 0.03144121
[79] -2.01380855 0.10248020 -1.65016910 -0.50508217 -0.98373261 0.62526710
[85] -1.44755328 0.29010774 1.13026304 1.22144956 -1.99667791 -1.39847741
[91] -0.24304818 -1.36548015 0.02722734 -1.53165610 2.87393793 -0.63482400
[97] 0.29138720 -0.38165219 0.55782731 1.28621036
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.08337627 -0.1968002 -0.4339778 -2.615141 1.408402 -0.7822081 1.166675
[2,] 0.08337627 -0.1968002 -0.4339778 -2.615141 1.408402 -0.7822081 1.166675
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -2.156718 0.9361407 -0.04082392 -0.08869283 -1.190155 -0.2662496 -2.127081
[2,] -2.156718 0.9361407 -0.04082392 -0.08869283 -1.190155 -0.2662496 -2.127081
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.030261 1.951103 2.340174 -0.2369528 -0.4048668 0.05848853 -0.9858984
[2,] 1.030261 1.951103 2.340174 -0.2369528 -0.4048668 0.05848853 -0.9858984
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.5174593 0.5358531 -0.6765444 1.761194 -0.2468945 -1.309276 -2.12336
[2,] 0.5174593 0.5358531 -0.6765444 1.761194 -0.2468945 -1.309276 -2.12336
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -1.061237 -0.5775314 0.4961526 -0.6632425 -0.5112575 -0.1434049 -0.118872
[2,] -1.061237 -0.5775314 0.4961526 -0.6632425 -0.5112575 -0.1434049 -0.118872
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.847149 1.447852 0.03640784 0.8218536 -2.103114 -0.06588743 -0.6592706
[2,] 1.847149 1.447852 0.03640784 0.8218536 -2.103114 -0.06588743 -0.6592706
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.3306281 -0.6212191 -1.216853 -0.2553767 0.6516636 -1.568485 -2.047628
[2,] -0.3306281 -0.6212191 -1.216853 -0.2553767 0.6516636 -1.568485 -2.047628
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.6581785 0.9930705 0.8995224 0.03505215 -0.3858371 -0.8010679 0.7750734
[2,] 0.6581785 0.9930705 0.8995224 0.03505215 -0.3858371 -0.8010679 0.7750734
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -1.107266 1.185254 -0.8173202 1.322002 0.7646679 -0.6766794 1.455537
[2,] -1.107266 1.185254 -0.8173202 1.322002 0.7646679 -0.6766794 1.455537
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.3399114 0.4086429 -2.715211 -0.1488149 -0.8032954 0.787595 -1.731072
[2,] -0.3399114 0.4086429 -2.715211 -0.1488149 -0.8032954 0.787595 -1.731072
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.1227437 0.1687977 0.915194 -0.3279189 0.504532 0.09281214 1.386536
[2,] -0.1227437 0.1687977 0.915194 -0.3279189 0.504532 0.09281214 1.386536
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.03144121 -2.013809 0.1024802 -1.650169 -0.5050822 -0.9837326 0.6252671
[2,] 0.03144121 -2.013809 0.1024802 -1.650169 -0.5050822 -0.9837326 0.6252671
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -1.447553 0.2901077 1.130263 1.22145 -1.996678 -1.398477 -0.2430482
[2,] -1.447553 0.2901077 1.130263 1.22145 -1.996678 -1.398477 -0.2430482
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.36548 0.02722734 -1.531656 2.873938 -0.634824 0.2913872 -0.3816522
[2,] -1.36548 0.02722734 -1.531656 2.873938 -0.634824 0.2913872 -0.3816522
[,99] [,100]
[1,] 0.5578273 1.28621
[2,] 0.5578273 1.28621
>
>
> Max(tmp2)
[1] 3.04842
> Min(tmp2)
[1] -2.253619
> mean(tmp2)
[1] 0.05029617
> Sum(tmp2)
[1] 5.029617
> Var(tmp2)
[1] 0.8583649
>
> rowMeans(tmp2)
[1] -1.085493733 -1.422215355 -0.677505608 -0.917356326 0.774549966
[6] -0.145152954 0.896976829 0.570093507 -0.357898649 -0.097864761
[11] 0.636931744 -0.166748819 -0.414394811 0.433758290 -0.005898911
[16] 1.055400762 0.050165372 0.734852953 2.054075819 -2.253619359
[21] 1.079462817 0.779303078 -1.596107712 0.468785446 -0.297244395
[26] 0.186725952 1.785110914 -0.523073208 -0.517794258 0.232573876
[31] -2.012825316 0.155357416 -0.392011418 0.239665497 -0.438873028
[36] 0.358750584 -0.338551599 -0.083223221 0.392911435 -1.128254491
[41] -1.158814289 -1.007333997 -0.600485840 -0.177912042 -0.250366174
[46] -0.618934492 0.710035652 0.729860404 1.349964474 -0.472020072
[51] -0.100221011 -0.345685429 0.392386993 -0.063029878 3.048420125
[56] -0.811455348 -0.310173350 1.049564140 1.485877737 -1.420589999
[61] 0.154397553 0.308458041 -0.020399911 -1.077377706 0.961392072
[66] -1.067373748 1.050880804 1.118158248 -0.832182113 -1.235767014
[71] -0.915844605 1.087171935 0.466851472 -0.999131952 1.825422891
[76] 0.616391105 0.959377550 0.315534879 1.675129040 -0.170103907
[81] -0.330468550 -0.733320496 -1.141936293 1.363402602 0.738443165
[86] 0.182303846 0.079414807 0.298248152 0.005197932 1.136396292
[91] -0.486829344 -0.750701242 0.883682500 0.358706668 1.192120469
[96] -0.884593435 0.973099508 -0.064567293 -0.985313159 -0.467085316
> rowSums(tmp2)
[1] -1.085493733 -1.422215355 -0.677505608 -0.917356326 0.774549966
[6] -0.145152954 0.896976829 0.570093507 -0.357898649 -0.097864761
[11] 0.636931744 -0.166748819 -0.414394811 0.433758290 -0.005898911
[16] 1.055400762 0.050165372 0.734852953 2.054075819 -2.253619359
[21] 1.079462817 0.779303078 -1.596107712 0.468785446 -0.297244395
[26] 0.186725952 1.785110914 -0.523073208 -0.517794258 0.232573876
[31] -2.012825316 0.155357416 -0.392011418 0.239665497 -0.438873028
[36] 0.358750584 -0.338551599 -0.083223221 0.392911435 -1.128254491
[41] -1.158814289 -1.007333997 -0.600485840 -0.177912042 -0.250366174
[46] -0.618934492 0.710035652 0.729860404 1.349964474 -0.472020072
[51] -0.100221011 -0.345685429 0.392386993 -0.063029878 3.048420125
[56] -0.811455348 -0.310173350 1.049564140 1.485877737 -1.420589999
[61] 0.154397553 0.308458041 -0.020399911 -1.077377706 0.961392072
[66] -1.067373748 1.050880804 1.118158248 -0.832182113 -1.235767014
[71] -0.915844605 1.087171935 0.466851472 -0.999131952 1.825422891
[76] 0.616391105 0.959377550 0.315534879 1.675129040 -0.170103907
[81] -0.330468550 -0.733320496 -1.141936293 1.363402602 0.738443165
[86] 0.182303846 0.079414807 0.298248152 0.005197932 1.136396292
[91] -0.486829344 -0.750701242 0.883682500 0.358706668 1.192120469
[96] -0.884593435 0.973099508 -0.064567293 -0.985313159 -0.467085316
> 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] -1.085493733 -1.422215355 -0.677505608 -0.917356326 0.774549966
[6] -0.145152954 0.896976829 0.570093507 -0.357898649 -0.097864761
[11] 0.636931744 -0.166748819 -0.414394811 0.433758290 -0.005898911
[16] 1.055400762 0.050165372 0.734852953 2.054075819 -2.253619359
[21] 1.079462817 0.779303078 -1.596107712 0.468785446 -0.297244395
[26] 0.186725952 1.785110914 -0.523073208 -0.517794258 0.232573876
[31] -2.012825316 0.155357416 -0.392011418 0.239665497 -0.438873028
[36] 0.358750584 -0.338551599 -0.083223221 0.392911435 -1.128254491
[41] -1.158814289 -1.007333997 -0.600485840 -0.177912042 -0.250366174
[46] -0.618934492 0.710035652 0.729860404 1.349964474 -0.472020072
[51] -0.100221011 -0.345685429 0.392386993 -0.063029878 3.048420125
[56] -0.811455348 -0.310173350 1.049564140 1.485877737 -1.420589999
[61] 0.154397553 0.308458041 -0.020399911 -1.077377706 0.961392072
[66] -1.067373748 1.050880804 1.118158248 -0.832182113 -1.235767014
[71] -0.915844605 1.087171935 0.466851472 -0.999131952 1.825422891
[76] 0.616391105 0.959377550 0.315534879 1.675129040 -0.170103907
[81] -0.330468550 -0.733320496 -1.141936293 1.363402602 0.738443165
[86] 0.182303846 0.079414807 0.298248152 0.005197932 1.136396292
[91] -0.486829344 -0.750701242 0.883682500 0.358706668 1.192120469
[96] -0.884593435 0.973099508 -0.064567293 -0.985313159 -0.467085316
> rowMin(tmp2)
[1] -1.085493733 -1.422215355 -0.677505608 -0.917356326 0.774549966
[6] -0.145152954 0.896976829 0.570093507 -0.357898649 -0.097864761
[11] 0.636931744 -0.166748819 -0.414394811 0.433758290 -0.005898911
[16] 1.055400762 0.050165372 0.734852953 2.054075819 -2.253619359
[21] 1.079462817 0.779303078 -1.596107712 0.468785446 -0.297244395
[26] 0.186725952 1.785110914 -0.523073208 -0.517794258 0.232573876
[31] -2.012825316 0.155357416 -0.392011418 0.239665497 -0.438873028
[36] 0.358750584 -0.338551599 -0.083223221 0.392911435 -1.128254491
[41] -1.158814289 -1.007333997 -0.600485840 -0.177912042 -0.250366174
[46] -0.618934492 0.710035652 0.729860404 1.349964474 -0.472020072
[51] -0.100221011 -0.345685429 0.392386993 -0.063029878 3.048420125
[56] -0.811455348 -0.310173350 1.049564140 1.485877737 -1.420589999
[61] 0.154397553 0.308458041 -0.020399911 -1.077377706 0.961392072
[66] -1.067373748 1.050880804 1.118158248 -0.832182113 -1.235767014
[71] -0.915844605 1.087171935 0.466851472 -0.999131952 1.825422891
[76] 0.616391105 0.959377550 0.315534879 1.675129040 -0.170103907
[81] -0.330468550 -0.733320496 -1.141936293 1.363402602 0.738443165
[86] 0.182303846 0.079414807 0.298248152 0.005197932 1.136396292
[91] -0.486829344 -0.750701242 0.883682500 0.358706668 1.192120469
[96] -0.884593435 0.973099508 -0.064567293 -0.985313159 -0.467085316
>
> colMeans(tmp2)
[1] 0.05029617
> colSums(tmp2)
[1] 5.029617
> colVars(tmp2)
[1] 0.8583649
> colSd(tmp2)
[1] 0.9264798
> colMax(tmp2)
[1] 3.04842
> colMin(tmp2)
[1] -2.253619
> colMedians(tmp2)
[1] -0.01314941
> colRanges(tmp2)
[,1]
[1,] -2.253619
[2,] 3.048420
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] -2.7881733 -8.1222096 -0.3151333 -0.8694146 0.4707511 -3.0316958
[7] 1.2380829 -1.4375608 1.4736830 0.2101141
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.9112090
[2,] -1.3196254
[3,] -0.4314572
[4,] 1.0537247
[5,] 1.7361680
>
> rowApply(tmp,sum)
[1] -4.5612129 -0.3651335 2.5925236 3.0711968 -4.1286519 -6.3224357
[7] 0.9968458 -2.0197922 -1.7257096 -0.7091866
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 5 10 10 10 1 2 1 4 7
[2,] 3 3 7 1 1 6 4 2 2 2
[3,] 7 8 8 7 5 4 8 5 7 1
[4,] 9 7 3 6 6 2 3 8 9 5
[5,] 5 6 5 8 7 9 6 6 6 6
[6,] 8 9 2 3 9 3 5 4 5 3
[7,] 2 10 9 2 4 10 1 9 1 10
[8,] 4 1 4 4 8 5 9 10 3 8
[9,] 10 4 1 5 2 7 10 7 10 4
[10,] 6 2 6 9 3 8 7 3 8 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.3364676 -2.6487648 -0.1227105 2.1626577 -4.0963386 0.1638309
[7] -3.2929527 -1.0929622 -1.9449535 -3.6888787 1.5566071 2.3923051
[13] -0.1447604 -5.1679658 -2.8477436 2.2496781 -1.0057087 1.5805018
[19] -1.1333961 1.4950955
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1862764
[2,] -0.6656186
[3,] 0.4415963
[4,] 0.6475820
[5,] 1.0991843
>
> rowApply(tmp,sum)
[1] 5.283772 -6.321408 -8.438252 -4.120607 -1.653496
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 1 18 15 16 6
[2,] 12 10 7 8 7
[3,] 20 1 6 18 4
[4,] 5 20 20 6 19
[5,] 14 5 2 7 5
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.1862764 -0.09320149 2.5673115 -0.3977051 0.7511499 -0.3728292
[2,] 1.0991843 -0.36407694 -2.3540148 1.4927245 -1.0610012 -0.3984911
[3,] 0.4415963 -1.01320180 -1.0546165 1.2272627 -2.4014479 1.0182604
[4,] 0.6475820 -0.59413707 1.6089480 -1.3335790 -0.6485644 -0.4557689
[5,] -0.6656186 -0.58414750 -0.8903387 1.1739546 -0.7364750 0.3726596
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.2442756 -0.4722234 1.1921362 0.4269404 -0.6125059 -0.32762738
[2,] 0.6380349 0.1698058 0.3069975 -1.7084387 0.5111504 0.05909703
[3,] -2.7645766 0.6839267 -1.3621258 -0.4744796 1.0883615 0.17688726
[4,] -1.8611298 -1.3709727 -1.8836706 -0.1095314 -0.3933109 2.56939811
[5,] -0.5495567 -0.1034985 -0.1982908 -1.8233695 0.9629120 -0.08544995
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 2.12542748 -0.2186005 -0.2318021 0.92540442 -0.2054230 1.06033695
[2,] -2.10999103 -0.9847443 -1.8266352 1.12456752 -0.9489031 0.59745849
[3,] -0.81480550 -1.1455055 -1.7146538 -0.25695065 1.1652357 -0.65297980
[4,] 0.75054979 -1.3927566 -1.8036565 -0.02503542 0.3552243 0.59418093
[5,] -0.09594109 -1.4263590 2.7290039 0.48169227 -1.3718426 -0.01849472
[,19] [,20]
[1,] -0.6398212 -0.2511948
[2,] -0.7284770 0.1643444
[3,] 0.2674334 -0.8518724
[4,] -0.5398611 1.7654839
[5,] 0.5073298 0.6683343
>
>
> 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 : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 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 0.279127 1.364673 1.236662 2.479537 -0.4485195 -0.6921091 0.2233154
col8 col9 col10 col11 col12 col13 col14
row1 0.1269378 -0.3193101 -0.479723 -0.6037291 0.4935687 0.5103654 0.7011215
col15 col16 col17 col18 col19 col20
row1 -0.829062 0.2810254 0.1829834 1.903953 0.2929672 -2.425244
> tmp[,"col10"]
col10
row1 -0.4797230
row2 1.8184704
row3 -0.4402134
row4 -0.7839511
row5 -2.0392321
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.2791270 1.3646728 1.236662 2.4795369 -0.4485195 -0.69210910 0.2233154
row5 0.6920211 -0.4852819 -1.043491 0.9292921 -0.2184650 -0.06916423 1.6728947
col8 col9 col10 col11 col12 col13 col14
row1 0.1269378 -0.3193101 -0.479723 -0.6037291 0.4935687 0.5103654 0.7011215
row5 -0.2703533 0.3828394 -2.039232 0.5073475 -0.2975099 -1.6678552 0.1814546
col15 col16 col17 col18 col19 col20
row1 -0.8290620 0.2810254 0.1829834 1.9039527 0.29296716 -2.4252435
row5 0.7197822 1.1709165 0.1781464 0.2472329 -0.08746505 0.2709212
> tmp[,c("col6","col20")]
col6 col20
row1 -0.69210910 -2.4252435
row2 -0.89261600 1.1103957
row3 -1.02608378 0.2670051
row4 1.05923694 -0.2731038
row5 -0.06916423 0.2709212
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.69210910 -2.4252435
row5 -0.06916423 0.2709212
>
>
>
>
> 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 52.5559 49.2436 49.0975 49.7004 50.61089 104.5613 49.98432 50.00417
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.40098 53.06916 50.44435 49.98861 50.12452 49.22035 49.72365 49.75518
col17 col18 col19 col20
row1 48.51027 51.44649 50.03623 105.2746
> tmp[,"col10"]
col10
row1 53.06916
row2 30.67079
row3 30.38912
row4 30.74426
row5 49.63171
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 52.55590 49.24360 49.09750 49.70040 50.61089 104.5613 49.98432 50.00417
row5 48.83789 49.88838 49.62946 50.16563 50.24524 106.8056 49.66406 50.52442
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.40098 53.06916 50.44435 49.98861 50.12452 49.22035 49.72365 49.75518
row5 49.05070 49.63171 50.13556 48.81142 49.95406 50.64145 48.17525 50.82291
col17 col18 col19 col20
row1 48.51027 51.44649 50.03623 105.2746
row5 50.70309 49.23510 50.06120 105.3270
> tmp[,c("col6","col20")]
col6 col20
row1 104.56133 105.27462
row2 75.59372 75.24803
row3 76.12975 73.50013
row4 74.53765 75.18814
row5 106.80558 105.32703
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.5613 105.2746
row5 106.8056 105.3270
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.5613 105.2746
row5 106.8056 105.3270
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.4480748
[2,] 0.1716249
[3,] -0.2856069
[4,] 0.3525065
[5,] 2.6531057
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.9092845 1.4007410
[2,] 0.7046091 -0.3414969
[3,] -0.2851502 0.9964118
[4,] -1.7104268 -1.5211113
[5,] 1.1331780 0.4312711
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.20506907 -0.21529177
[2,] 0.85416168 0.69670499
[3,] -0.08445862 0.67230839
[4,] 1.02317792 -0.03123712
[5,] 1.10469813 0.28925775
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.2050691
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.2050691
[2,] 0.8541617
>
>
>
> 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 1.9219030 0.6211379 -0.5705971 -1.2093301 0.3462119 -0.03324183
row1 0.9003995 -0.8983126 -0.4188738 0.1190326 1.7186516 -0.21377164
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.07590217 2.4163238 -0.2337223 1.323922 0.8962505 -0.4204112
row1 -1.07770981 -0.1106625 1.1079420 -2.371469 -0.2007173 1.0750066
[,13] [,14] [,15] [,16] [,17] [,18]
row3 0.7903053 0.1519304 0.1631478 1.0322001 -0.3384904 -0.6143269
row1 -0.5631745 1.1474156 0.1166667 -0.7494738 -1.0543778 -1.8839454
[,19] [,20]
row3 2.271896215 -0.1173634
row1 -0.003787827 -0.4826192
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.200242 -0.3734695 -0.9887716 0.3020752 -0.7311229 0.4097139 -1.804484
[,8] [,9] [,10]
row2 -0.908063 -1.156784 0.8509532
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.5767735 -0.8751344 0.6678944 0.5972126 -0.3206129 -1.726779 -1.807424
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.8035656 -0.3035719 1.316324 -0.1793101 0.1502038 0.298832 -1.03588
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.5122353 -0.3460126 0.01480945 -1.038172 0.05759502 0.4728781
>
>
> 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: 0x5560d2488460>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM115c3153c54db2"
[2] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM115c3168e60bba"
[3] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM115c3117834fba"
[4] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM115c317263290c"
[5] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM115c316461d9f9"
[6] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM115c315bf2ef3c"
[7] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM115c311ce1a4f5"
[8] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM115c314da6646f"
[9] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM115c313b481494"
[10] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM115c314e4b1605"
[11] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM115c31769764c4"
[12] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM115c3119346878"
[13] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM115c31466d1f4f"
[14] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM115c313f3628c6"
[15] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM115c313095f199"
>
>
> ### 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: 0x5560d2e85860>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5560d2e85860>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x5560d2e85860>
> rowMedians(tmp)
[1] -0.218698686 0.053952237 0.097918110 -0.279459414 -0.204996297
[6] -0.560258865 0.152713465 0.641838536 -0.403902861 -0.080360119
[11] 0.069328498 -0.145270412 0.138030424 -0.077091880 0.096327360
[16] 0.237150181 0.146468973 0.314625257 0.201203694 -0.280312053
[21] -0.097334681 0.166241494 -0.031454719 -0.642431395 -0.757105766
[26] 0.009626492 -0.683631279 0.050088386 0.217362141 -0.429942287
[31] 0.296551528 0.032252301 0.116593877 0.027427878 0.044306310
[36] -0.523514800 0.084860911 0.069615969 -0.058194892 -0.004357898
[41] 0.228174647 0.166986770 -0.653756976 0.070890387 -0.394837656
[46] 0.225728473 0.495989633 0.280664157 -0.114465746 -0.405749387
[51] 0.375563739 -0.030596508 0.166114904 -0.104499774 -0.184404298
[56] 0.002451379 0.080273521 0.146304850 -0.109543385 0.128351154
[61] 0.259875211 0.275014763 -0.003207166 0.086505293 -0.301930979
[66] -0.177779610 0.100864052 -0.352203176 -0.096120006 0.525012730
[71] -0.060536209 0.458013413 0.128398746 -0.118034638 -0.141877405
[76] 0.093430043 0.483836496 -0.063338111 -0.372573471 0.557310724
[81] 0.043781488 0.148426337 0.565902819 0.529091539 -0.418973305
[86] -0.068879934 0.361289610 0.158584295 0.159483327 0.153482366
[91] -0.046811693 -0.079398711 0.044097294 0.093869614 0.271949640
[96] -0.405650820 -0.219003528 0.182512822 -0.067838461 -0.340865820
[101] -0.323538458 0.189088068 -0.026266771 0.028653087 -0.298451232
[106] -0.367892539 0.367650101 -0.072319036 -0.191057912 0.487191699
[111] -0.451723806 -0.098443018 0.093020407 0.030491965 0.283790596
[116] -0.626644123 -0.094381394 -0.359725855 0.108396282 0.137798263
[121] -0.565934220 0.666893028 0.183057827 -0.491920597 -0.303630976
[126] -0.334822976 -0.553194761 0.011530732 0.143566385 0.070118246
[131] 0.043690442 0.200763100 0.295064610 -0.364616606 0.117473187
[136] 0.352716661 0.455022113 0.128782530 0.060751303 -0.428731753
[141] -0.440492667 0.016463299 -0.087551519 -0.014164416 0.562633679
[146] -0.016169624 -0.349661633 -0.363837802 0.011415308 -0.207240036
[151] -0.619195734 0.233465371 0.422997401 -0.110594418 0.061421198
[156] -0.373064889 0.534095993 0.286282351 0.474038815 -0.209232117
[161] 0.032689318 0.083598506 -0.291251194 -0.163436105 -0.021849739
[166] 0.659270658 -0.680188906 0.683817889 -0.433380862 0.045472978
[171] 0.059856250 -0.417917891 -0.195662317 0.049915802 -0.264267520
[176] 0.025927264 0.211493547 0.010682253 -0.375900934 -0.473756355
[181] -0.003081995 -0.350482761 -0.059513324 0.075567537 -0.017417594
[186] 0.277345769 -0.453029486 -0.403424535 0.128919282 0.592505185
[191] 0.116703299 -0.280986618 -0.032516644 0.220664966 -0.803319352
[196] -0.143221726 0.216296073 0.465881609 -0.189642017 -0.419867763
[201] 0.195682839 -0.524356516 0.200474635 -0.029526171 -0.247503730
[206] -0.001085268 0.402062373 -0.266260280 -0.165926346 0.279264062
[211] 0.539459990 0.231826601 -0.198353202 -0.670378081 0.235206605
[216] -0.034625865 0.372708305 0.187232055 0.278927396 -0.100335267
[221] 0.156743653 0.077772174 -0.156455170 0.128083832 0.136675741
[226] 0.299355198 -0.738813631 0.269327885 0.112614470 -0.142598155
>
> proc.time()
user system elapsed
1.439 1.570 3.026
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.3.0 alpha (2023-04-03 r84154)
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: 0x555bad8c5110>
> .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: 0x555bad8c5110>
> .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: 0x555bad8c5110>
> .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: 0x555bad8c5110>
> 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: 0x555bad4c0330>
> .Call("R_bm_AddColumn",P)
<pointer: 0x555bad4c0330>
> .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: 0x555bad4c0330>
> .Call("R_bm_AddColumn",P)
<pointer: 0x555bad4c0330>
> .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: 0x555bad4c0330>
> 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: 0x555bae46c870>
> .Call("R_bm_AddColumn",P)
<pointer: 0x555bae46c870>
> .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: 0x555bae46c870>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x555bae46c870>
> .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: 0x555bae46c870>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x555bae46c870>
> .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: 0x555bae46c870>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x555bae46c870>
> .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: 0x555bae46c870>
> 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: 0x555bade97290>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x555bade97290>
> .Call("R_bm_AddColumn",P)
<pointer: 0x555bade97290>
> .Call("R_bm_AddColumn",P)
<pointer: 0x555bade97290>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1161ba432660f0" "BufferedMatrixFile1161ba6897f78a"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1161ba432660f0" "BufferedMatrixFile1161ba6897f78a"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x555bae3d0db0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x555bae3d0db0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x555bae3d0db0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x555bae3d0db0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x555bae3d0db0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x555bae3d0db0>
> .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: 0x555bad394bc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x555bad394bc0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x555bad394bc0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x555bad394bc0>
> 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: 0x555bad55db50>
> .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: 0x555bad55db50>
> rm(P)
>
> proc.time()
user system elapsed
0.257 0.058 0.301
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.3.0 alpha (2023-04-03 r84154)
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.259 0.034 0.280