| Back to Multiple platform build/check report for BioC 3.19: simplified long |
|
This page was generated on 2024-06-07 20:24 -0400 (Fri, 07 Jun 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4755 |
| palomino3 | Windows Server 2022 Datacenter | x64 | 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup" | 4489 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4520 |
| kjohnson3 | macOS 13.6.5 Ventura | arm64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4466 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 249/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.68.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK |  | ||||||||
| palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.6.5 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.68.0 |
| Command: /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings BufferedMatrix_1.68.0.tar.gz |
| StartedAt: 2024-06-05 21:11:10 -0400 (Wed, 05 Jun 2024) |
| EndedAt: 2024-06-05 21:11:34 -0400 (Wed, 05 Jun 2024) |
| EllapsedTime: 24.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings BufferedMatrix_1.68.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.0 (2024-04-24)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
* running under: Ubuntu 22.04.4 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.68.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... 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 code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking 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
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.19-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-3.19-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.19-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-3.19-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-3.19-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-3.19-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-3.19-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.19-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 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
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
0.254 0.050 0.293
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
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-3.19-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 471778 25.2 1026221 54.9 643431 34.4
Vcells 871899 6.7 8388608 64.0 2046580 15.7
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Wed Jun 5 21:11:26 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed Jun 5 21:11:26 2024"
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
>
>
> RowMode(tmp2)
<pointer: 0x55633a849440>
>
>
>
> 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] "Wed Jun 5 21:11:26 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Wed Jun 5 21:11:26 2024"
>
> ColMode(tmp2)
<pointer: 0x55633a849440>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.2178634 -0.3268447 0.2194538 -0.1043740
[2,] -0.9811115 0.0337887 -1.4449222 -0.6213913
[3,] 0.4362262 0.8112260 0.5340964 1.5469756
[4,] -2.4126687 1.0792537 2.0051480 1.1111074
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.2178634 0.3268447 0.2194538 0.1043740
[2,] 0.9811115 0.0337887 1.4449222 0.6213913
[3,] 0.4362262 0.8112260 0.5340964 1.5469756
[4,] 2.4126687 1.0792537 2.0051480 1.1111074
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0108872 0.5717034 0.468459 0.3230696
[2,] 0.9905108 0.1838170 1.202049 0.7882838
[3,] 0.6604742 0.9006809 0.730819 1.2437747
[4,] 1.5532768 1.0388714 1.416032 1.0540908
>
> 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-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.32674 31.04388 29.90404 28.33507
[2,] 35.88622 26.87196 38.46541 33.50423
[3,] 32.04097 34.81803 32.84229 38.98472
[4,] 42.94544 36.46797 41.16547 36.65202
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x55633a3bb3b0>
> exp(tmp5)
<pointer: 0x55633a3bb3b0>
> log(tmp5,2)
<pointer: 0x55633a3bb3b0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.9881
> Min(tmp5)
[1] 52.45139
> mean(tmp5)
[1] 72.26512
> Sum(tmp5)
[1] 14453.02
> Var(tmp5)
[1] 876.8655
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.28130 67.84948 69.58337 76.75346 68.63480 71.08124 70.77988 70.78016
[9] 67.75831 70.14916
> rowSums(tmp5)
[1] 1785.626 1356.990 1391.667 1535.069 1372.696 1421.625 1415.598 1415.603
[9] 1355.166 1402.983
> rowVars(tmp5)
[1] 8067.28811 57.26995 73.06396 107.64245 84.82183 68.07258
[7] 92.73632 48.89741 64.65522 119.39005
> rowSd(tmp5)
[1] 89.818083 7.567691 8.547746 10.375088 9.209877 8.250611 9.629970
[8] 6.992668 8.040847 10.926575
> rowMax(tmp5)
[1] 468.98808 80.06072 91.54176 99.61094 85.01793 84.67457 95.44125
[8] 80.96641 80.60139 90.92814
> rowMin(tmp5)
[1] 52.45139 55.15245 54.01841 61.56884 56.18443 53.12924 58.12387 58.47575
[9] 54.58244 54.87939
>
> colMeans(tmp5)
[1] 108.26101 67.29007 70.40980 70.81319 69.32448 70.18324 71.47765
[8] 74.58547 71.08780 71.28606 67.51364 67.39337 69.56101 71.91252
[15] 73.11210 68.76639 67.01572 68.49767 77.09837 69.71275
> colSums(tmp5)
[1] 1082.6101 672.9007 704.0980 708.1319 693.2448 701.8324 714.7765
[8] 745.8547 710.8780 712.8606 675.1364 673.9337 695.6101 719.1252
[15] 731.1210 687.6639 670.1572 684.9767 770.9837 697.1275
> colVars(tmp5)
[1] 16161.22358 55.33406 109.86068 59.57190 100.87622 136.32110
[7] 18.98605 72.63286 76.21995 49.91363 29.32163 72.57908
[13] 48.99004 129.12824 118.49156 119.15220 56.23155 154.57768
[19] 62.25351 106.06492
> colSd(tmp5)
[1] 127.126801 7.438687 10.481445 7.718284 10.043715 11.675663
[7] 4.357298 8.522491 8.730404 7.064958 5.414945 8.519336
[13] 6.999289 11.363461 10.885383 10.915686 7.498770 12.432927
[19] 7.890089 10.298783
> colMax(tmp5)
[1] 468.98808 77.76801 85.68054 81.14159 85.53531 91.54176 78.26090
[8] 85.00836 85.20471 82.98161 74.44292 80.69389 81.69851 88.92457
[15] 92.46355 95.44125 76.27917 99.61094 90.92814 84.68441
> colMin(tmp5)
[1] 53.12924 55.93046 54.87939 56.18443 52.45139 58.12387 63.90824 58.06729
[9] 63.94390 56.65692 60.24726 56.03569 56.95480 54.58244 57.02624 58.66273
[17] 55.15245 59.18704 62.76466 54.01841
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 89.28130 67.84948 NA 76.75346 68.63480 71.08124 70.77988 70.78016
[9] 67.75831 70.14916
> rowSums(tmp5)
[1] 1785.626 1356.990 NA 1535.069 1372.696 1421.625 1415.598 1415.603
[9] 1355.166 1402.983
> rowVars(tmp5)
[1] 8067.28811 57.26995 76.98247 107.64245 84.82183 68.07258
[7] 92.73632 48.89741 64.65522 119.39005
> rowSd(tmp5)
[1] 89.818083 7.567691 8.773965 10.375088 9.209877 8.250611 9.629970
[8] 6.992668 8.040847 10.926575
> rowMax(tmp5)
[1] 468.98808 80.06072 NA 99.61094 85.01793 84.67457 95.44125
[8] 80.96641 80.60139 90.92814
> rowMin(tmp5)
[1] 52.45139 55.15245 NA 61.56884 56.18443 53.12924 58.12387 58.47575
[9] 54.58244 54.87939
>
> colMeans(tmp5)
[1] 108.26101 67.29007 70.40980 70.81319 69.32448 70.18324 71.47765
[8] 74.58547 71.08780 71.28606 67.51364 67.39337 NA 71.91252
[15] 73.11210 68.76639 67.01572 68.49767 77.09837 69.71275
> colSums(tmp5)
[1] 1082.6101 672.9007 704.0980 708.1319 693.2448 701.8324 714.7765
[8] 745.8547 710.8780 712.8606 675.1364 673.9337 NA 719.1252
[15] 731.1210 687.6639 670.1572 684.9767 770.9837 697.1275
> colVars(tmp5)
[1] 16161.22358 55.33406 109.86068 59.57190 100.87622 136.32110
[7] 18.98605 72.63286 76.21995 49.91363 29.32163 72.57908
[13] NA 129.12824 118.49156 119.15220 56.23155 154.57768
[19] 62.25351 106.06492
> colSd(tmp5)
[1] 127.126801 7.438687 10.481445 7.718284 10.043715 11.675663
[7] 4.357298 8.522491 8.730404 7.064958 5.414945 8.519336
[13] NA 11.363461 10.885383 10.915686 7.498770 12.432927
[19] 7.890089 10.298783
> colMax(tmp5)
[1] 468.98808 77.76801 85.68054 81.14159 85.53531 91.54176 78.26090
[8] 85.00836 85.20471 82.98161 74.44292 80.69389 NA 88.92457
[15] 92.46355 95.44125 76.27917 99.61094 90.92814 84.68441
> colMin(tmp5)
[1] 53.12924 55.93046 54.87939 56.18443 52.45139 58.12387 63.90824 58.06729
[9] 63.94390 56.65692 60.24726 56.03569 NA 54.58244 57.02624 58.66273
[17] 55.15245 59.18704 62.76466 54.01841
>
> Max(tmp5,na.rm=TRUE)
[1] 468.9881
> Min(tmp5,na.rm=TRUE)
[1] 52.45139
> mean(tmp5,na.rm=TRUE)
[1] 72.2708
> Sum(tmp5,na.rm=TRUE)
[1] 14381.89
> Var(tmp5,na.rm=TRUE)
[1] 881.2876
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.28130 67.84948 69.50177 76.75346 68.63480 71.08124 70.77988 70.78016
[9] 67.75831 70.14916
> rowSums(tmp5,na.rm=TRUE)
[1] 1785.626 1356.990 1320.534 1535.069 1372.696 1421.625 1415.598 1415.603
[9] 1355.166 1402.983
> rowVars(tmp5,na.rm=TRUE)
[1] 8067.28811 57.26995 76.98247 107.64245 84.82183 68.07258
[7] 92.73632 48.89741 64.65522 119.39005
> rowSd(tmp5,na.rm=TRUE)
[1] 89.818083 7.567691 8.773965 10.375088 9.209877 8.250611 9.629970
[8] 6.992668 8.040847 10.926575
> rowMax(tmp5,na.rm=TRUE)
[1] 468.98808 80.06072 91.54176 99.61094 85.01793 84.67457 95.44125
[8] 80.96641 80.60139 90.92814
> rowMin(tmp5,na.rm=TRUE)
[1] 52.45139 55.15245 54.01841 61.56884 56.18443 53.12924 58.12387 58.47575
[9] 54.58244 54.87939
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.26101 67.29007 70.40980 70.81319 69.32448 70.18324 71.47765
[8] 74.58547 71.08780 71.28606 67.51364 67.39337 69.38624 71.91252
[15] 73.11210 68.76639 67.01572 68.49767 77.09837 69.71275
> colSums(tmp5,na.rm=TRUE)
[1] 1082.6101 672.9007 704.0980 708.1319 693.2448 701.8324 714.7765
[8] 745.8547 710.8780 712.8606 675.1364 673.9337 624.4762 719.1252
[15] 731.1210 687.6639 670.1572 684.9767 770.9837 697.1275
> colVars(tmp5,na.rm=TRUE)
[1] 16161.22358 55.33406 109.86068 59.57190 100.87622 136.32110
[7] 18.98605 72.63286 76.21995 49.91363 29.32163 72.57908
[13] 54.77017 129.12824 118.49156 119.15220 56.23155 154.57768
[19] 62.25351 106.06492
> colSd(tmp5,na.rm=TRUE)
[1] 127.126801 7.438687 10.481445 7.718284 10.043715 11.675663
[7] 4.357298 8.522491 8.730404 7.064958 5.414945 8.519336
[13] 7.400687 11.363461 10.885383 10.915686 7.498770 12.432927
[19] 7.890089 10.298783
> colMax(tmp5,na.rm=TRUE)
[1] 468.98808 77.76801 85.68054 81.14159 85.53531 91.54176 78.26090
[8] 85.00836 85.20471 82.98161 74.44292 80.69389 81.69851 88.92457
[15] 92.46355 95.44125 76.27917 99.61094 90.92814 84.68441
> colMin(tmp5,na.rm=TRUE)
[1] 53.12924 55.93046 54.87939 56.18443 52.45139 58.12387 63.90824 58.06729
[9] 63.94390 56.65692 60.24726 56.03569 56.95480 54.58244 57.02624 58.66273
[17] 55.15245 59.18704 62.76466 54.01841
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.28130 67.84948 NaN 76.75346 68.63480 71.08124 70.77988 70.78016
[9] 67.75831 70.14916
> rowSums(tmp5,na.rm=TRUE)
[1] 1785.626 1356.990 0.000 1535.069 1372.696 1421.625 1415.598 1415.603
[9] 1355.166 1402.983
> rowVars(tmp5,na.rm=TRUE)
[1] 8067.28811 57.26995 NA 107.64245 84.82183 68.07258
[7] 92.73632 48.89741 64.65522 119.39005
> rowSd(tmp5,na.rm=TRUE)
[1] 89.818083 7.567691 NA 10.375088 9.209877 8.250611 9.629970
[8] 6.992668 8.040847 10.926575
> rowMax(tmp5,na.rm=TRUE)
[1] 468.98808 80.06072 NA 99.61094 85.01793 84.67457 95.44125
[8] 80.96641 80.60139 90.92814
> rowMin(tmp5,na.rm=TRUE)
[1] 52.45139 55.15245 NA 61.56884 56.18443 53.12924 58.12387 58.47575
[9] 54.58244 54.87939
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 112.88011 66.71461 70.63790 69.66559 70.13498 67.81007 72.31870
[8] 74.50022 71.80060 71.15925 67.39204 67.98584 NaN 72.94461
[15] 72.24190 69.59206 65.98645 68.66385 77.99015 71.45656
> colSums(tmp5,na.rm=TRUE)
[1] 1015.9210 600.4315 635.7411 626.9903 631.2148 610.2906 650.8683
[8] 670.5020 646.2054 640.4333 606.5283 611.8725 0.0000 656.5015
[15] 650.1771 626.3285 593.8781 617.9746 701.9113 643.1091
> colVars(tmp5,na.rm=TRUE)
[1] 17941.34520 58.52538 123.00794 52.20228 106.09559 90.00201
[7] 13.40152 81.63020 80.03143 55.97194 32.82049 77.70257
[13] NA 133.28549 124.78400 126.37678 51.34224 173.58920
[19] 61.08847 85.11302
> colSd(tmp5,na.rm=TRUE)
[1] 133.945307 7.650188 11.090895 7.225115 10.300271 9.486939
[7] 3.660809 9.034943 8.946028 7.481440 5.728917 8.814906
[13] NA 11.544933 11.170676 11.241743 7.165350 13.175326
[19] 7.815911 9.225672
> colMax(tmp5,na.rm=TRUE)
[1] 468.98808 77.76801 85.68054 76.42821 85.53531 87.11732 78.26090
[8] 85.00836 85.20471 82.98161 74.44292 80.69389 -Inf 88.92457
[15] 92.46355 95.44125 76.11388 99.61094 90.92814 84.68441
> colMin(tmp5,na.rm=TRUE)
[1] 53.12924 55.93046 54.87939 56.18443 52.45139 58.12387 65.23151 58.06729
[9] 63.94390 56.65692 60.24726 56.03569 Inf 54.58244 57.02624 58.66273
[17] 55.15245 59.18704 62.76466 59.88055
>
>
>
>
> 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] 135.3574 144.5133 125.6562 387.1852 271.3956 242.4365 245.1594 233.7619
[9] 305.7130 237.2662
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 135.3574 144.5133 125.6562 387.1852 271.3956 242.4365 245.1594 233.7619
[9] 305.7130 237.2662
>
>
>
> 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] 2.273737e-13 5.684342e-14 -8.526513e-14 0.000000e+00 -2.842171e-14
[6] 5.684342e-14 1.421085e-14 4.263256e-14 -1.136868e-13 8.526513e-14
[11] -2.273737e-13 -8.526513e-14 5.684342e-14 -2.842171e-14 5.684342e-14
[16] -5.684342e-14 8.526513e-14 -2.842171e-14 -2.842171e-14 -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)
+ }
8 10
4 19
1 18
7 4
4 17
7 15
7 4
2 4
2 14
6 13
7 1
2 18
9 9
9 1
6 17
2 11
8 15
4 2
5 4
1 20
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] 2.685686
> Min(tmp)
[1] -2.434939
> mean(tmp)
[1] -0.05807649
> Sum(tmp)
[1] -5.807649
> Var(tmp)
[1] 1.087019
>
> rowMeans(tmp)
[1] -0.05807649
> rowSums(tmp)
[1] -5.807649
> rowVars(tmp)
[1] 1.087019
> rowSd(tmp)
[1] 1.042602
> rowMax(tmp)
[1] 2.685686
> rowMin(tmp)
[1] -2.434939
>
> colMeans(tmp)
[1] -0.11555630 0.67379644 -0.61749520 -0.72111077 -1.33191524 0.07524809
[7] -0.10865056 -2.35754210 0.28286594 0.09483582 -0.07809666 1.03857845
[13] -0.99398625 0.15485237 -0.39679989 0.78474260 -0.44247463 0.80675494
[19] 0.37715687 1.90884389 0.81610813 -0.78155804 -1.29313706 0.63953293
[25] 0.05173363 0.69519687 0.32858828 -0.86935222 -0.61760184 0.34778060
[31] -1.44583307 0.82273895 0.26776798 0.69948461 0.17192093 0.74733731
[37] 0.92140793 -1.08111071 0.20161032 -0.36497841 0.30479290 -2.43493878
[43] -0.62416048 -0.10342430 -0.66453948 0.54684155 0.07425754 -0.02067601
[49] -0.87962646 2.63218698 -1.73983165 1.04454421 1.17578354 -0.05395172
[55] 1.55953036 0.91074945 -1.56197988 -0.07406391 -2.16089168 -1.30116981
[61] -0.68869796 0.70552342 -0.17656314 -1.46798273 -0.48068115 -2.17750202
[67] -0.11545614 1.54094394 -0.47458508 -2.11612431 -0.00694896 -0.41204518
[73] -0.12531377 -0.35823909 -0.97180463 0.97025604 -1.30465139 0.33241240
[79] -0.84122832 0.50353122 -0.84176155 2.68568617 -1.50436750 1.37297435
[85] -1.48842968 1.32984174 1.40038728 -1.44007099 -0.84169863 0.41470721
[91] 0.89384012 -0.08954248 -0.39633946 0.43463218 -0.28738456 2.03600365
[97] 0.69591224 0.60268444 0.36153165 0.59778413
> colSums(tmp)
[1] -0.11555630 0.67379644 -0.61749520 -0.72111077 -1.33191524 0.07524809
[7] -0.10865056 -2.35754210 0.28286594 0.09483582 -0.07809666 1.03857845
[13] -0.99398625 0.15485237 -0.39679989 0.78474260 -0.44247463 0.80675494
[19] 0.37715687 1.90884389 0.81610813 -0.78155804 -1.29313706 0.63953293
[25] 0.05173363 0.69519687 0.32858828 -0.86935222 -0.61760184 0.34778060
[31] -1.44583307 0.82273895 0.26776798 0.69948461 0.17192093 0.74733731
[37] 0.92140793 -1.08111071 0.20161032 -0.36497841 0.30479290 -2.43493878
[43] -0.62416048 -0.10342430 -0.66453948 0.54684155 0.07425754 -0.02067601
[49] -0.87962646 2.63218698 -1.73983165 1.04454421 1.17578354 -0.05395172
[55] 1.55953036 0.91074945 -1.56197988 -0.07406391 -2.16089168 -1.30116981
[61] -0.68869796 0.70552342 -0.17656314 -1.46798273 -0.48068115 -2.17750202
[67] -0.11545614 1.54094394 -0.47458508 -2.11612431 -0.00694896 -0.41204518
[73] -0.12531377 -0.35823909 -0.97180463 0.97025604 -1.30465139 0.33241240
[79] -0.84122832 0.50353122 -0.84176155 2.68568617 -1.50436750 1.37297435
[85] -1.48842968 1.32984174 1.40038728 -1.44007099 -0.84169863 0.41470721
[91] 0.89384012 -0.08954248 -0.39633946 0.43463218 -0.28738456 2.03600365
[97] 0.69591224 0.60268444 0.36153165 0.59778413
> 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] -0.11555630 0.67379644 -0.61749520 -0.72111077 -1.33191524 0.07524809
[7] -0.10865056 -2.35754210 0.28286594 0.09483582 -0.07809666 1.03857845
[13] -0.99398625 0.15485237 -0.39679989 0.78474260 -0.44247463 0.80675494
[19] 0.37715687 1.90884389 0.81610813 -0.78155804 -1.29313706 0.63953293
[25] 0.05173363 0.69519687 0.32858828 -0.86935222 -0.61760184 0.34778060
[31] -1.44583307 0.82273895 0.26776798 0.69948461 0.17192093 0.74733731
[37] 0.92140793 -1.08111071 0.20161032 -0.36497841 0.30479290 -2.43493878
[43] -0.62416048 -0.10342430 -0.66453948 0.54684155 0.07425754 -0.02067601
[49] -0.87962646 2.63218698 -1.73983165 1.04454421 1.17578354 -0.05395172
[55] 1.55953036 0.91074945 -1.56197988 -0.07406391 -2.16089168 -1.30116981
[61] -0.68869796 0.70552342 -0.17656314 -1.46798273 -0.48068115 -2.17750202
[67] -0.11545614 1.54094394 -0.47458508 -2.11612431 -0.00694896 -0.41204518
[73] -0.12531377 -0.35823909 -0.97180463 0.97025604 -1.30465139 0.33241240
[79] -0.84122832 0.50353122 -0.84176155 2.68568617 -1.50436750 1.37297435
[85] -1.48842968 1.32984174 1.40038728 -1.44007099 -0.84169863 0.41470721
[91] 0.89384012 -0.08954248 -0.39633946 0.43463218 -0.28738456 2.03600365
[97] 0.69591224 0.60268444 0.36153165 0.59778413
> colMin(tmp)
[1] -0.11555630 0.67379644 -0.61749520 -0.72111077 -1.33191524 0.07524809
[7] -0.10865056 -2.35754210 0.28286594 0.09483582 -0.07809666 1.03857845
[13] -0.99398625 0.15485237 -0.39679989 0.78474260 -0.44247463 0.80675494
[19] 0.37715687 1.90884389 0.81610813 -0.78155804 -1.29313706 0.63953293
[25] 0.05173363 0.69519687 0.32858828 -0.86935222 -0.61760184 0.34778060
[31] -1.44583307 0.82273895 0.26776798 0.69948461 0.17192093 0.74733731
[37] 0.92140793 -1.08111071 0.20161032 -0.36497841 0.30479290 -2.43493878
[43] -0.62416048 -0.10342430 -0.66453948 0.54684155 0.07425754 -0.02067601
[49] -0.87962646 2.63218698 -1.73983165 1.04454421 1.17578354 -0.05395172
[55] 1.55953036 0.91074945 -1.56197988 -0.07406391 -2.16089168 -1.30116981
[61] -0.68869796 0.70552342 -0.17656314 -1.46798273 -0.48068115 -2.17750202
[67] -0.11545614 1.54094394 -0.47458508 -2.11612431 -0.00694896 -0.41204518
[73] -0.12531377 -0.35823909 -0.97180463 0.97025604 -1.30465139 0.33241240
[79] -0.84122832 0.50353122 -0.84176155 2.68568617 -1.50436750 1.37297435
[85] -1.48842968 1.32984174 1.40038728 -1.44007099 -0.84169863 0.41470721
[91] 0.89384012 -0.08954248 -0.39633946 0.43463218 -0.28738456 2.03600365
[97] 0.69591224 0.60268444 0.36153165 0.59778413
> colMedians(tmp)
[1] -0.11555630 0.67379644 -0.61749520 -0.72111077 -1.33191524 0.07524809
[7] -0.10865056 -2.35754210 0.28286594 0.09483582 -0.07809666 1.03857845
[13] -0.99398625 0.15485237 -0.39679989 0.78474260 -0.44247463 0.80675494
[19] 0.37715687 1.90884389 0.81610813 -0.78155804 -1.29313706 0.63953293
[25] 0.05173363 0.69519687 0.32858828 -0.86935222 -0.61760184 0.34778060
[31] -1.44583307 0.82273895 0.26776798 0.69948461 0.17192093 0.74733731
[37] 0.92140793 -1.08111071 0.20161032 -0.36497841 0.30479290 -2.43493878
[43] -0.62416048 -0.10342430 -0.66453948 0.54684155 0.07425754 -0.02067601
[49] -0.87962646 2.63218698 -1.73983165 1.04454421 1.17578354 -0.05395172
[55] 1.55953036 0.91074945 -1.56197988 -0.07406391 -2.16089168 -1.30116981
[61] -0.68869796 0.70552342 -0.17656314 -1.46798273 -0.48068115 -2.17750202
[67] -0.11545614 1.54094394 -0.47458508 -2.11612431 -0.00694896 -0.41204518
[73] -0.12531377 -0.35823909 -0.97180463 0.97025604 -1.30465139 0.33241240
[79] -0.84122832 0.50353122 -0.84176155 2.68568617 -1.50436750 1.37297435
[85] -1.48842968 1.32984174 1.40038728 -1.44007099 -0.84169863 0.41470721
[91] 0.89384012 -0.08954248 -0.39633946 0.43463218 -0.28738456 2.03600365
[97] 0.69591224 0.60268444 0.36153165 0.59778413
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.1155563 0.6737964 -0.6174952 -0.7211108 -1.331915 0.07524809 -0.1086506
[2,] -0.1155563 0.6737964 -0.6174952 -0.7211108 -1.331915 0.07524809 -0.1086506
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -2.357542 0.2828659 0.09483582 -0.07809666 1.038578 -0.9939863 0.1548524
[2,] -2.357542 0.2828659 0.09483582 -0.07809666 1.038578 -0.9939863 0.1548524
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.3967999 0.7847426 -0.4424746 0.8067549 0.3771569 1.908844 0.8161081
[2,] -0.3967999 0.7847426 -0.4424746 0.8067549 0.3771569 1.908844 0.8161081
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.781558 -1.293137 0.6395329 0.05173363 0.6951969 0.3285883 -0.8693522
[2,] -0.781558 -1.293137 0.6395329 0.05173363 0.6951969 0.3285883 -0.8693522
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.6176018 0.3477806 -1.445833 0.8227389 0.267768 0.6994846 0.1719209
[2,] -0.6176018 0.3477806 -1.445833 0.8227389 0.267768 0.6994846 0.1719209
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.7473373 0.9214079 -1.081111 0.2016103 -0.3649784 0.3047929 -2.434939
[2,] 0.7473373 0.9214079 -1.081111 0.2016103 -0.3649784 0.3047929 -2.434939
[,43] [,44] [,45] [,46] [,47] [,48]
[1,] -0.6241605 -0.1034243 -0.6645395 0.5468416 0.07425754 -0.02067601
[2,] -0.6241605 -0.1034243 -0.6645395 0.5468416 0.07425754 -0.02067601
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.8796265 2.632187 -1.739832 1.044544 1.175784 -0.05395172 1.55953
[2,] -0.8796265 2.632187 -1.739832 1.044544 1.175784 -0.05395172 1.55953
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] 0.9107495 -1.56198 -0.07406391 -2.160892 -1.30117 -0.688698 0.7055234
[2,] 0.9107495 -1.56198 -0.07406391 -2.160892 -1.30117 -0.688698 0.7055234
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] -0.1765631 -1.467983 -0.4806812 -2.177502 -0.1154561 1.540944 -0.4745851
[2,] -0.1765631 -1.467983 -0.4806812 -2.177502 -0.1154561 1.540944 -0.4745851
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] -2.116124 -0.00694896 -0.4120452 -0.1253138 -0.3582391 -0.9718046 0.970256
[2,] -2.116124 -0.00694896 -0.4120452 -0.1253138 -0.3582391 -0.9718046 0.970256
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -1.304651 0.3324124 -0.8412283 0.5035312 -0.8417615 2.685686 -1.504367
[2,] -1.304651 0.3324124 -0.8412283 0.5035312 -0.8417615 2.685686 -1.504367
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 1.372974 -1.48843 1.329842 1.400387 -1.440071 -0.8416986 0.4147072
[2,] 1.372974 -1.48843 1.329842 1.400387 -1.440071 -0.8416986 0.4147072
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 0.8938401 -0.08954248 -0.3963395 0.4346322 -0.2873846 2.036004 0.6959122
[2,] 0.8938401 -0.08954248 -0.3963395 0.4346322 -0.2873846 2.036004 0.6959122
[,98] [,99] [,100]
[1,] 0.6026844 0.3615316 0.5977841
[2,] 0.6026844 0.3615316 0.5977841
>
>
> Max(tmp2)
[1] 2.25775
> Min(tmp2)
[1] -2.724296
> mean(tmp2)
[1] -0.02999068
> Sum(tmp2)
[1] -2.999068
> Var(tmp2)
[1] 1.014232
>
> rowMeans(tmp2)
[1] -1.712053853 -0.624915448 0.116028325 1.808513903 -0.403047101
[6] -1.119850566 -0.966094494 0.590718950 1.456402124 0.831493376
[11] 0.332042833 -0.591433998 -0.954806930 -0.728453916 0.625976965
[16] 0.980920196 -0.596028671 0.139377785 -0.183355429 -1.053635053
[21] 0.088933801 2.257749798 0.819801591 -2.724295791 -0.243872749
[26] -0.858023256 -0.569615895 0.007915375 -0.888615750 0.700371506
[31] -2.346164803 -0.186134830 -1.013197537 -0.017232699 0.378763930
[36] -0.469535278 1.017072194 -1.866076601 -0.266812482 -0.038979082
[41] 0.170761805 -0.309976396 2.184453007 1.732035128 0.386868011
[46] 1.788268382 1.286041000 -1.052875264 -0.038220052 -0.818046086
[51] -0.761360468 0.535352323 0.692963396 -1.320934242 -0.203899555
[56] 0.222736142 -0.537600266 0.439339725 -0.563752192 0.431913157
[61] 1.358103787 0.051627163 0.387828858 -0.042165471 -0.024267286
[66] -1.457852712 1.293008525 0.125546723 -0.058975562 -1.752611423
[71] 0.474236027 -1.366518532 -0.950838969 -1.481517900 -0.635803107
[76] -0.414715167 1.007898762 0.804137610 -0.968847849 -0.422779258
[81] 0.955699460 0.095244280 -0.059251435 0.504438942 -1.547097495
[86] 0.914899606 0.534303644 -0.238271175 -1.448815302 0.164764998
[91] 1.122306035 -0.798701374 -0.600821862 1.434486555 1.157092500
[96] -0.847636758 2.186306098 -0.230640884 0.376827857 1.406385799
> rowSums(tmp2)
[1] -1.712053853 -0.624915448 0.116028325 1.808513903 -0.403047101
[6] -1.119850566 -0.966094494 0.590718950 1.456402124 0.831493376
[11] 0.332042833 -0.591433998 -0.954806930 -0.728453916 0.625976965
[16] 0.980920196 -0.596028671 0.139377785 -0.183355429 -1.053635053
[21] 0.088933801 2.257749798 0.819801591 -2.724295791 -0.243872749
[26] -0.858023256 -0.569615895 0.007915375 -0.888615750 0.700371506
[31] -2.346164803 -0.186134830 -1.013197537 -0.017232699 0.378763930
[36] -0.469535278 1.017072194 -1.866076601 -0.266812482 -0.038979082
[41] 0.170761805 -0.309976396 2.184453007 1.732035128 0.386868011
[46] 1.788268382 1.286041000 -1.052875264 -0.038220052 -0.818046086
[51] -0.761360468 0.535352323 0.692963396 -1.320934242 -0.203899555
[56] 0.222736142 -0.537600266 0.439339725 -0.563752192 0.431913157
[61] 1.358103787 0.051627163 0.387828858 -0.042165471 -0.024267286
[66] -1.457852712 1.293008525 0.125546723 -0.058975562 -1.752611423
[71] 0.474236027 -1.366518532 -0.950838969 -1.481517900 -0.635803107
[76] -0.414715167 1.007898762 0.804137610 -0.968847849 -0.422779258
[81] 0.955699460 0.095244280 -0.059251435 0.504438942 -1.547097495
[86] 0.914899606 0.534303644 -0.238271175 -1.448815302 0.164764998
[91] 1.122306035 -0.798701374 -0.600821862 1.434486555 1.157092500
[96] -0.847636758 2.186306098 -0.230640884 0.376827857 1.406385799
> 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] -1.712053853 -0.624915448 0.116028325 1.808513903 -0.403047101
[6] -1.119850566 -0.966094494 0.590718950 1.456402124 0.831493376
[11] 0.332042833 -0.591433998 -0.954806930 -0.728453916 0.625976965
[16] 0.980920196 -0.596028671 0.139377785 -0.183355429 -1.053635053
[21] 0.088933801 2.257749798 0.819801591 -2.724295791 -0.243872749
[26] -0.858023256 -0.569615895 0.007915375 -0.888615750 0.700371506
[31] -2.346164803 -0.186134830 -1.013197537 -0.017232699 0.378763930
[36] -0.469535278 1.017072194 -1.866076601 -0.266812482 -0.038979082
[41] 0.170761805 -0.309976396 2.184453007 1.732035128 0.386868011
[46] 1.788268382 1.286041000 -1.052875264 -0.038220052 -0.818046086
[51] -0.761360468 0.535352323 0.692963396 -1.320934242 -0.203899555
[56] 0.222736142 -0.537600266 0.439339725 -0.563752192 0.431913157
[61] 1.358103787 0.051627163 0.387828858 -0.042165471 -0.024267286
[66] -1.457852712 1.293008525 0.125546723 -0.058975562 -1.752611423
[71] 0.474236027 -1.366518532 -0.950838969 -1.481517900 -0.635803107
[76] -0.414715167 1.007898762 0.804137610 -0.968847849 -0.422779258
[81] 0.955699460 0.095244280 -0.059251435 0.504438942 -1.547097495
[86] 0.914899606 0.534303644 -0.238271175 -1.448815302 0.164764998
[91] 1.122306035 -0.798701374 -0.600821862 1.434486555 1.157092500
[96] -0.847636758 2.186306098 -0.230640884 0.376827857 1.406385799
> rowMin(tmp2)
[1] -1.712053853 -0.624915448 0.116028325 1.808513903 -0.403047101
[6] -1.119850566 -0.966094494 0.590718950 1.456402124 0.831493376
[11] 0.332042833 -0.591433998 -0.954806930 -0.728453916 0.625976965
[16] 0.980920196 -0.596028671 0.139377785 -0.183355429 -1.053635053
[21] 0.088933801 2.257749798 0.819801591 -2.724295791 -0.243872749
[26] -0.858023256 -0.569615895 0.007915375 -0.888615750 0.700371506
[31] -2.346164803 -0.186134830 -1.013197537 -0.017232699 0.378763930
[36] -0.469535278 1.017072194 -1.866076601 -0.266812482 -0.038979082
[41] 0.170761805 -0.309976396 2.184453007 1.732035128 0.386868011
[46] 1.788268382 1.286041000 -1.052875264 -0.038220052 -0.818046086
[51] -0.761360468 0.535352323 0.692963396 -1.320934242 -0.203899555
[56] 0.222736142 -0.537600266 0.439339725 -0.563752192 0.431913157
[61] 1.358103787 0.051627163 0.387828858 -0.042165471 -0.024267286
[66] -1.457852712 1.293008525 0.125546723 -0.058975562 -1.752611423
[71] 0.474236027 -1.366518532 -0.950838969 -1.481517900 -0.635803107
[76] -0.414715167 1.007898762 0.804137610 -0.968847849 -0.422779258
[81] 0.955699460 0.095244280 -0.059251435 0.504438942 -1.547097495
[86] 0.914899606 0.534303644 -0.238271175 -1.448815302 0.164764998
[91] 1.122306035 -0.798701374 -0.600821862 1.434486555 1.157092500
[96] -0.847636758 2.186306098 -0.230640884 0.376827857 1.406385799
>
> colMeans(tmp2)
[1] -0.02999068
> colSums(tmp2)
[1] -2.999068
> colVars(tmp2)
[1] 1.014232
> colSd(tmp2)
[1] 1.007091
> colMax(tmp2)
[1] 2.25775
> colMin(tmp2)
[1] -2.724296
> colMedians(tmp2)
[1] -0.03859957
> colRanges(tmp2)
[,1]
[1,] -2.724296
[2,] 2.257750
>
> 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] -0.5333683 1.9495824 5.5905780 -1.6559529 1.2288060 1.0648037
[7] 1.6420272 -4.4924846 -2.4513739 5.0921295
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.9170560
[2,] -0.3578661
[3,] -0.1816542
[4,] 0.1353290
[5,] 1.3223675
>
> rowApply(tmp,sum)
[1] 1.0472506 3.2026585 8.6221308 -1.4263987 3.4363895 0.7940592
[7] -3.0788782 0.5870259 -3.2017884 -2.5477020
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 4 2 1 9 7 4 5 8 3 7
[2,] 9 1 8 8 9 2 3 2 6 10
[3,] 8 5 10 10 6 5 4 9 9 1
[4,] 3 10 5 6 1 1 9 3 7 2
[5,] 7 7 6 5 3 9 8 6 4 5
[6,] 2 6 7 2 10 7 2 1 10 6
[7,] 1 3 2 4 4 8 10 10 8 9
[8,] 6 9 4 1 5 3 1 4 5 3
[9,] 10 8 3 3 2 6 6 7 1 4
[10,] 5 4 9 7 8 10 7 5 2 8
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.2472875 2.5151388 -1.4723673 0.9737350 -0.8475556 -1.9613959
[7] -1.0756255 -3.0488851 2.5111675 1.2005275 1.8752516 0.2634763
[13] -1.7078991 -2.8373965 0.3138169 -1.4270688 0.3157886 0.3767359
[19] 2.3301307 -1.7263816
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.61317638
[2,] -0.13929652
[3,] -0.05765423
[4,] -0.03699366
[5,] 0.59983325
>
> rowApply(tmp,sum)
[1] 1.830949 -13.110815 3.950622 -1.342899 3.996048
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 4 6 13 15
[2,] 10 20 18 9 12
[3,] 13 8 7 1 16
[4,] 3 18 11 16 10
[5,] 20 11 5 4 8
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.13929652 0.07396239 0.2513453 -0.6264369 1.2330605 -0.09311089
[2,] -1.61317638 0.94974570 -0.9023494 0.5292611 -0.6333364 -0.83160330
[3,] -0.05765423 1.44522959 -0.0566018 0.5573906 -0.9274184 0.38719047
[4,] -0.03699366 -0.39119800 -1.4620344 0.2512224 -0.6384322 -0.07973498
[5,] 0.59983325 0.43739911 0.6972730 0.2622977 0.1185710 -1.34413717
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.06210835 -1.34648265 0.3679583 -0.4143777 -0.12984882 0.6574486
[2,] -0.51940164 -0.90696949 -0.3782216 -0.6277029 -0.15561926 -0.8886322
[3,] 0.72535014 -1.23946247 0.6076495 0.5676237 0.82636848 0.6896887
[4,] 0.11757371 -0.04339942 0.8330054 2.2392489 -0.07891215 -0.5066307
[5,] -1.33703939 0.48742892 1.0807760 -0.5642645 1.41326333 0.3116019
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.48812826 0.6393076 0.60203652 0.1894457 1.0635337 -0.8179722
[2,] -1.17446090 -1.8856387 -0.05718256 0.6979578 -1.7817482 0.4112198
[3,] 0.32665013 -1.2689297 -0.93303712 -2.4284866 2.0170753 0.1509508
[4,] 0.02771706 -0.7912836 -0.45437113 0.2853356 -0.4180646 -0.3938445
[5,] -0.39967717 0.4691479 1.15637122 -0.1713213 -0.5650075 1.0263821
[,19] [,20]
[1,] 0.7535304 0.1170826
[2,] -1.1610545 -2.1819021
[3,] 1.5435252 1.0175202
[4,] 0.9576065 -0.7597087
[5,] 0.2365231 0.0806264
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 644 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 562 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 0.3042102 0.03380082 0.283129 2.307689 1.915638 -1.300643 0.6364027
col8 col9 col10 col11 col12 col13 col14 col15
row1 -1.4197 0.3479598 1.636185 -0.6147785 0.5309488 1.747187 1.31944 0.375534
col16 col17 col18 col19 col20
row1 -0.2520696 0.9543232 -1.595232 -0.5221602 -1.861379
> tmp[,"col10"]
col10
row1 1.6361850
row2 1.2705425
row3 1.3429971
row4 0.6420492
row5 -1.0674284
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.3042102 0.03380082 0.283129 2.307689 1.915638 -1.300643 0.6364027
row5 0.8414195 0.69858868 -1.224771 -1.621612 -1.718020 -1.909352 0.9438082
col8 col9 col10 col11 col12 col13 col14
row1 -1.419700 0.3479598 1.636185 -0.6147785 0.5309488 1.7471875 1.319440
row5 1.463971 0.4705869 -1.067428 -0.8920360 1.0996871 0.1963202 -1.448473
col15 col16 col17 col18 col19 col20
row1 0.3755340 -0.2520696 0.9543232 -1.5952317 -0.5221602 -1.8613793
row5 -0.2852591 0.7261688 -0.3400636 -0.4765768 1.0934675 0.2288516
> tmp[,c("col6","col20")]
col6 col20
row1 -1.3006435 -1.8613793
row2 -2.4080061 0.5349793
row3 3.1755337 2.6134365
row4 -0.9182905 -1.6030076
row5 -1.9093524 0.2288516
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.300643 -1.8613793
row5 -1.909352 0.2288516
>
>
>
>
> 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 50.44297 48.90839 48.42376 49.56827 49.56765 103.3965 52.0023 49.71598
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.39565 50.09516 48.04754 50.92698 50.11839 50.55422 50.6741 49.94073
col17 col18 col19 col20
row1 49.96166 47.61019 49.33053 105.6534
> tmp[,"col10"]
col10
row1 50.09516
row2 30.49081
row3 29.46232
row4 28.25989
row5 48.94105
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.44297 48.90839 48.42376 49.56827 49.56765 103.3965 52.00230 49.71598
row5 51.58420 48.98854 49.87702 48.86293 48.89728 104.4836 52.53198 49.90035
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.39565 50.09516 48.04754 50.92698 50.11839 50.55422 50.67410 49.94073
row5 49.58956 48.94105 49.31949 49.53685 49.85966 51.70489 49.46902 49.89288
col17 col18 col19 col20
row1 49.96166 47.61019 49.33053 105.6534
row5 50.84978 50.09963 51.11618 104.0239
> tmp[,c("col6","col20")]
col6 col20
row1 103.39654 105.65335
row2 74.10038 75.70813
row3 74.85359 74.91010
row4 75.64856 74.61166
row5 104.48364 104.02387
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 103.3965 105.6534
row5 104.4836 104.0239
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 103.3965 105.6534
row5 104.4836 104.0239
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.26017240
[2,] 0.43189284
[3,] 1.03159374
[4,] 1.41739565
[5,] -0.08328064
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.5013891 1.4034557
[2,] 0.3535986 0.6343811
[3,] 0.6007301 -0.7032471
[4,] -0.3448235 -0.1514491
[5,] 0.6069600 0.1522176
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.5650995 -0.1945559
[2,] -2.2494411 -0.5952126
[3,] -0.7970577 -0.4930617
[4,] -0.4795459 -2.2805411
[5,] 0.4795271 0.3736762
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.5650995
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.5650995
[2,] -2.2494411
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 -0.116540 -1.1646584 1.682768 -0.7073249 -0.1463693 -0.1500886 0.5139702
row1 -1.513292 -0.4814543 -2.495022 -0.6023165 1.2386459 -1.1016600 1.2325293
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 1.4241615 -1.359081 1.972014 -0.8891318 -0.1938842 1.8566998 0.5547853
row1 -0.4332207 -1.207277 1.197258 0.4011264 0.2574840 0.1236656 -0.8638794
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.6382571 0.2516431 0.2335248 -0.4671640 -0.2979834 0.2311978
row1 0.1996776 0.5128405 0.6784090 -0.4823052 -0.6345610 1.5506993
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.6394509 -0.8931439 -0.568851 -0.2557265 1.213242 0.2036723 -0.4181541
[,8] [,9] [,10]
row2 1.056599 0.694154 -0.01769401
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.3960511 -1.455011 0.02185965 -2.093485 0.2303758 0.06779888 1.019669
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.030726 -0.968707 -0.8213531 -2.12462 0.1859841 0.8812366 0.08230739
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.9208021 0.6624538 -2.38479 -0.3763229 -0.3028949 -0.6598878
>
>
> 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: 0x55633bc18020>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM841bb38c41f2e"
[2] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM841bb84e6998"
[3] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM841bb5a90b75a"
[4] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM841bb46f40461"
[5] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM841bb3989105e"
[6] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM841bbc3e69e9"
[7] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM841bb796c5c93"
[8] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM841bb5b4658bf"
[9] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM841bb18f57e2d"
[10] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM841bb429bc25e"
[11] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM841bb5ccdc6e8"
[12] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM841bb287eb818"
[13] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM841bb63d05254"
[14] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM841bb27fa78a1"
[15] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM841bb44c2d65c"
>
>
> ### 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: 0x55633a8eb7a0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x55633a8eb7a0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x55633a8eb7a0>
> rowMedians(tmp)
[1] -0.0897431796 -0.0074096244 -0.4615275751 0.5240099748 0.6238447027
[6] -0.3307206160 -0.1669259957 0.5469336474 0.5122529319 -0.3007235216
[11] 0.1940002696 0.6515117975 0.3858286406 0.3360616706 -0.1161530770
[16] 0.2559652884 -0.4456317276 -0.2085011461 -0.0717674782 0.1322469990
[21] -0.1913257312 -0.1757678407 0.5702030926 -0.0697031378 0.0219915325
[26] -0.3010790773 -0.2051167329 -0.1137911677 -0.2575981015 0.4746684649
[31] 0.3170478036 -0.0147382424 -0.2381128770 0.0170850695 -0.2300250963
[36] -0.0326674354 0.0486643176 -0.2095127708 -0.0044832989 0.0837041514
[41] 0.2015843145 0.3237163833 -0.2707865909 0.1933855871 -0.3246070974
[46] 0.1672911239 0.3846671732 0.0398616831 0.4362839843 -0.3816966993
[51] 0.1010967320 -0.2098529339 -0.1273789472 0.1264398837 0.2568666727
[56] 0.3970513469 -0.3233179820 0.4242804086 0.1571671206 -0.5077571661
[61] -0.0067952370 0.1273522718 -0.1598302331 0.5542622570 -0.0004425680
[66] 0.2856419155 -0.0374082522 -0.0304287666 -0.3454632783 -0.3999690793
[71] 0.2661451143 0.2199231667 -0.2086433762 -0.3513316840 0.7785635489
[76] 0.2219992291 -0.2834573580 -0.3913367684 0.2380960337 0.0402656420
[81] 0.0897107234 -0.3425969059 -0.2519190922 0.0649027045 -0.1104828716
[86] -0.0653771930 0.2197518468 -0.0637321149 0.2869178015 0.4576287381
[91] -0.1335789474 0.0971937079 0.3051930903 -0.8282665784 0.0532013826
[96] 0.1721498702 0.2395829266 -0.2530494982 0.1507547696 -0.1215543235
[101] -0.0228127319 -0.3443400905 0.2260489031 0.1674140251 -0.2950218278
[106] -0.5351429404 -0.0424205241 0.0796849997 0.4591024917 -0.5666630090
[111] 0.4462872924 -0.1366298803 -0.4308183300 -0.1881089507 -0.3626386748
[116] -0.5407651355 -0.1880000120 -0.0052898330 0.2838375413 0.0143211691
[121] -0.3149473868 -0.4571494587 0.4534030161 0.1673709999 -0.2723194861
[126] -0.1531508389 0.0291395750 0.0037106954 -0.2454877656 0.3452301356
[131] 0.5048601024 -0.3302760489 -0.3146723832 0.0630479365 -0.0737439085
[136] 0.0575237166 -0.1115672373 -0.1510674064 0.3113278344 0.0491217071
[141] -0.0001234148 -0.0084881371 0.5230379707 0.2199352436 0.3681484841
[146] 0.1448363353 0.2014445726 0.0807680470 0.3788976888 0.2254135989
[151] -0.6222379172 0.2602859200 0.3089240755 0.3220458484 0.1116353364
[156] -0.0448288851 -0.1737717325 -0.1446219456 -0.0389080668 -0.0014995862
[161] -0.2033259767 -0.0084367504 -0.0252957912 -0.1511121778 0.5247792228
[166] -0.2969542130 -0.2047066034 0.2418779337 0.1935782506 -0.3986353802
[171] -0.1801464961 0.0031790938 -0.1390825188 -0.0716254736 0.1218770247
[176] -0.1746858306 0.2396271741 -0.0053267355 -0.2768940453 0.0978072831
[181] 0.4391439390 0.3152618795 0.0286447739 0.1814603308 0.1095336383
[186] 0.1681590873 0.3863626864 0.2048109834 0.3772357485 0.4706635482
[191] -0.6849339585 -0.0293762788 -0.2080626565 0.1679422130 -0.0720761113
[196] 0.8752896380 -0.3347680223 -0.0768180146 -0.5879220594 -0.0506001363
[201] 0.0577555564 0.4729293082 0.3429690077 -0.3182897271 -0.0139313908
[206] -0.3721528551 0.1263282958 -0.1576993458 0.3878310874 -0.7297713267
[211] -0.5034453171 -0.8503515667 -0.0073353408 0.3261027395 0.3702247025
[216] 0.0886725818 -0.1674326180 -0.0388529166 -0.5426807825 0.4204121354
[221] -0.0412003591 -0.1491062159 -0.1968893310 0.4655794072 0.0056913382
[226] -0.2733571098 0.0805103788 0.3750509876 -0.3955215901 0.2897122935
>
> proc.time()
user system elapsed
1.411 1.649 3.083
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
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: 0x5599076f6b80>
> .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: 0x5599076f6b80>
> .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: 0x5599076f6b80>
> .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: 0x5599076f6b80>
> 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: 0x559906d6c290>
> .Call("R_bm_AddColumn",P)
<pointer: 0x559906d6c290>
> .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: 0x559906d6c290>
> .Call("R_bm_AddColumn",P)
<pointer: 0x559906d6c290>
> .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: 0x559906d6c290>
> 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: 0x559907b2b1a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x559907b2b1a0>
> .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: 0x559907b2b1a0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x559907b2b1a0>
> .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: 0x559907b2b1a0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x559907b2b1a0>
> .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: 0x559907b2b1a0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x559907b2b1a0>
> .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: 0x559907b2b1a0>
> 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: 0x559907501440>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x559907501440>
> .Call("R_bm_AddColumn",P)
<pointer: 0x559907501440>
> .Call("R_bm_AddColumn",P)
<pointer: 0x559907501440>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile847f3618c9c38" "BufferedMatrixFile847f3e16dd03"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile847f3618c9c38" "BufferedMatrixFile847f3e16dd03"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x559907932aa0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x559907932aa0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x559907932aa0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x559907932aa0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x559907932aa0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x559907932aa0>
> .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: 0x559907c09fc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x559907c09fc0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x559907c09fc0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x559907c09fc0>
> 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: 0x559908876770>
> .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: 0x559908876770>
> rm(P)
>
> proc.time()
user system elapsed
0.267 0.044 0.300
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
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> 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
0.254 0.042 0.285