| Back to Multiple platform build/check report for BioC 3.17 |
|
This page was generated on 2023-04-12 10:55:34 -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: 2023-04-12 05:04:13 -0400 (Wed, 12 Apr 2023) |
| EndedAt: 2023-04-12 05:04:37 -0400 (Wed, 12 Apr 2023) |
| EllapsedTime: 24.1 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
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2023-02-14 r83833)
* using platform: x86_64-pc-linux-gnu (64-bit)
* R was compiled by
gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
GNU Fortran (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
* running under: Ubuntu 20.04.6 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 9.4.0-1ubuntu1~20.04.1) 9.4.0’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ...
‘BufferedMatrix.Rnw’... OK
OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.17-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0’
gcc -I"/home/biocbuild/bbs-3.17-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.17-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
gcc -I"/home/biocbuild/bbs-3.17-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"/home/biocbuild/bbs-3.17-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c init_package.c -o init_package.o
gcc -shared -L/home/biocbuild/bbs-3.17-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.17-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.17-bioc/R/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R Under development (unstable) (2023-02-14 r83833) -- "Unsuffered Consequences"
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
0.273 0.043 0.300
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2023-02-14 r83833) -- "Unsuffered Consequences"
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 457293 24.5 980737 52.4 651628 34.9
Vcells 842606 6.5 8388608 64.0 2045623 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 Apr 12 05:04:29 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] "Wed Apr 12 05:04:29 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: 0x561d1f5b1880>
>
>
>
> 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 Apr 12 05:04:29 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] "Wed Apr 12 05:04:29 2023"
>
> ColMode(tmp2)
<pointer: 0x561d1f5b1880>
>
>
>
> ### 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,] 99.7374793 -0.07161363 -1.1488624 -0.14529234
[2,] -0.4532767 -1.77889036 0.7463050 2.19155751
[3,] -0.3411601 -0.84162679 -1.1390014 -0.08146317
[4,] 0.5002311 -0.76200456 -0.8906446 0.12538671
> 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,] 99.7374793 0.07161363 1.1488624 0.14529234
[2,] 0.4532767 1.77889036 0.7463050 2.19155751
[3,] 0.3411601 0.84162679 1.1390014 0.08146317
[4,] 0.5002311 0.76200456 0.8906446 0.12538671
> 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,] 9.9868653 0.2676072 1.0718500 0.3811723
[2,] 0.6732583 1.3337505 0.8638895 1.4803910
[3,] 0.5840891 0.9174022 1.0672401 0.2854175
[4,] 0.7072702 0.8729287 0.9437397 0.3540999
>
> 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,] 224.60613 27.74769 36.86736 28.95702
[2,] 32.18586 40.11640 34.38520 41.99547
[3,] 31.18205 35.01565 36.81140 27.93564
[4,] 32.57293 34.49129 35.32804 28.66639
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x561d1d9e03a0>
> exp(tmp5)
<pointer: 0x561d1d9e03a0>
> log(tmp5,2)
<pointer: 0x561d1d9e03a0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.4882
> Min(tmp5)
[1] 52.85728
> mean(tmp5)
[1] 73.52567
> Sum(tmp5)
[1] 14705.13
> Var(tmp5)
[1] 858.8118
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 88.49944 72.53693 70.11251 73.04583 71.69762 73.73889 69.59039 72.81183
[9] 71.07211 72.15113
> rowSums(tmp5)
[1] 1769.989 1450.739 1402.250 1460.917 1433.952 1474.778 1391.808 1456.237
[9] 1421.442 1443.023
> rowVars(tmp5)
[1] 8020.73621 53.65181 64.76250 67.47473 72.29581 94.04044
[7] 81.11224 70.43885 100.02570 92.10791
> rowSd(tmp5)
[1] 89.558563 7.324740 8.047515 8.214301 8.502694 9.697445 9.006233
[8] 8.392786 10.001285 9.597287
> rowMax(tmp5)
[1] 467.48824 87.40806 84.03098 86.21482 87.85226 90.37819 83.10318
[8] 88.14667 83.75637 89.06885
> rowMin(tmp5)
[1] 56.26920 60.45296 58.14437 57.95304 56.72632 58.12104 55.08766 58.12970
[9] 52.85728 55.33076
>
> colMeans(tmp5)
[1] 109.82342 75.12913 72.01313 67.36109 72.81578 72.53821 74.89934
[8] 69.44174 71.68096 70.15518 73.01227 73.39150 72.66029 73.47965
[15] 72.67800 69.24890 67.73173 67.87119 69.05405 75.52779
> colSums(tmp5)
[1] 1098.2342 751.2913 720.1313 673.6109 728.1578 725.3821 748.9934
[8] 694.4174 716.8096 701.5518 730.1227 733.9150 726.6029 734.7965
[15] 726.7800 692.4890 677.3173 678.7119 690.5405 755.2779
> colVars(tmp5)
[1] 15841.96770 138.60562 36.73965 99.50488 90.92999 51.46735
[7] 96.44932 66.85964 100.00688 48.20568 48.61299 24.87376
[13] 97.21867 92.24004 67.93792 120.34498 101.68189 78.03488
[19] 81.41419 34.20586
> colSd(tmp5)
[1] 125.864879 11.773089 6.061324 9.975213 9.535722 7.174075
[7] 9.820861 8.176774 10.000344 6.943031 6.972302 4.987360
[13] 9.859953 9.604168 8.242446 10.970186 10.083744 8.833735
[19] 9.022981 5.848577
> colMax(tmp5)
[1] 467.48824 90.37819 78.91496 87.40806 85.82517 84.03098 86.43764
[8] 82.26440 82.29448 81.23274 83.52620 81.48709 87.85226 88.14667
[15] 80.60569 89.06885 85.48025 79.71187 83.59866 86.21482
> colMin(tmp5)
[1] 60.47552 57.75317 59.77976 55.15480 58.12970 61.93596 62.35414 56.92809
[9] 52.85728 59.55827 60.06254 65.93303 61.19225 55.64550 57.66855 55.40926
[17] 55.08766 57.95304 58.20614 67.70486
>
>
> ### 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] 88.49944 72.53693 70.11251 NA 71.69762 73.73889 69.59039 72.81183
[9] 71.07211 72.15113
> rowSums(tmp5)
[1] 1769.989 1450.739 1402.250 NA 1433.952 1474.778 1391.808 1456.237
[9] 1421.442 1443.023
> rowVars(tmp5)
[1] 8020.73621 53.65181 64.76250 71.13097 72.29581 94.04044
[7] 81.11224 70.43885 100.02570 92.10791
> rowSd(tmp5)
[1] 89.558563 7.324740 8.047515 8.433918 8.502694 9.697445 9.006233
[8] 8.392786 10.001285 9.597287
> rowMax(tmp5)
[1] 467.48824 87.40806 84.03098 NA 87.85226 90.37819 83.10318
[8] 88.14667 83.75637 89.06885
> rowMin(tmp5)
[1] 56.26920 60.45296 58.14437 NA 56.72632 58.12104 55.08766 58.12970
[9] 52.85728 55.33076
>
> colMeans(tmp5)
[1] 109.82342 NA 72.01313 67.36109 72.81578 72.53821 74.89934
[8] 69.44174 71.68096 70.15518 73.01227 73.39150 72.66029 73.47965
[15] 72.67800 69.24890 67.73173 67.87119 69.05405 75.52779
> colSums(tmp5)
[1] 1098.2342 NA 720.1313 673.6109 728.1578 725.3821 748.9934
[8] 694.4174 716.8096 701.5518 730.1227 733.9150 726.6029 734.7965
[15] 726.7800 692.4890 677.3173 678.7119 690.5405 755.2779
> colVars(tmp5)
[1] 15841.96770 NA 36.73965 99.50488 90.92999 51.46735
[7] 96.44932 66.85964 100.00688 48.20568 48.61299 24.87376
[13] 97.21867 92.24004 67.93792 120.34498 101.68189 78.03488
[19] 81.41419 34.20586
> colSd(tmp5)
[1] 125.864879 NA 6.061324 9.975213 9.535722 7.174075
[7] 9.820861 8.176774 10.000344 6.943031 6.972302 4.987360
[13] 9.859953 9.604168 8.242446 10.970186 10.083744 8.833735
[19] 9.022981 5.848577
> colMax(tmp5)
[1] 467.48824 NA 78.91496 87.40806 85.82517 84.03098 86.43764
[8] 82.26440 82.29448 81.23274 83.52620 81.48709 87.85226 88.14667
[15] 80.60569 89.06885 85.48025 79.71187 83.59866 86.21482
> colMin(tmp5)
[1] 60.47552 NA 59.77976 55.15480 58.12970 61.93596 62.35414 56.92809
[9] 52.85728 59.55827 60.06254 65.93303 61.19225 55.64550 57.66855 55.40926
[17] 55.08766 57.95304 58.20614 67.70486
>
> Max(tmp5,na.rm=TRUE)
[1] 467.4882
> Min(tmp5,na.rm=TRUE)
[1] 52.85728
> mean(tmp5,na.rm=TRUE)
[1] 73.53439
> Sum(tmp5,na.rm=TRUE)
[1] 14633.34
> Var(tmp5,na.rm=TRUE)
[1] 863.134
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.49944 72.53693 70.11251 73.11198 71.69762 73.73889 69.59039 72.81183
[9] 71.07211 72.15113
> rowSums(tmp5,na.rm=TRUE)
[1] 1769.989 1450.739 1402.250 1389.128 1433.952 1474.778 1391.808 1456.237
[9] 1421.442 1443.023
> rowVars(tmp5,na.rm=TRUE)
[1] 8020.73621 53.65181 64.76250 71.13097 72.29581 94.04044
[7] 81.11224 70.43885 100.02570 92.10791
> rowSd(tmp5,na.rm=TRUE)
[1] 89.558563 7.324740 8.047515 8.433918 8.502694 9.697445 9.006233
[8] 8.392786 10.001285 9.597287
> rowMax(tmp5,na.rm=TRUE)
[1] 467.48824 87.40806 84.03098 86.21482 87.85226 90.37819 83.10318
[8] 88.14667 83.75637 89.06885
> rowMin(tmp5,na.rm=TRUE)
[1] 56.26920 60.45296 58.14437 57.95304 56.72632 58.12104 55.08766 58.12970
[9] 52.85728 55.33076
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.82342 75.50024 72.01313 67.36109 72.81578 72.53821 74.89934
[8] 69.44174 71.68096 70.15518 73.01227 73.39150 72.66029 73.47965
[15] 72.67800 69.24890 67.73173 67.87119 69.05405 75.52779
> colSums(tmp5,na.rm=TRUE)
[1] 1098.2342 679.5022 720.1313 673.6109 728.1578 725.3821 748.9934
[8] 694.4174 716.8096 701.5518 730.1227 733.9150 726.6029 734.7965
[15] 726.7800 692.4890 677.3173 678.7119 690.5405 755.2779
> colVars(tmp5,na.rm=TRUE)
[1] 15841.96770 154.38191 36.73965 99.50488 90.92999 51.46735
[7] 96.44932 66.85964 100.00688 48.20568 48.61299 24.87376
[13] 97.21867 92.24004 67.93792 120.34498 101.68189 78.03488
[19] 81.41419 34.20586
> colSd(tmp5,na.rm=TRUE)
[1] 125.864879 12.425052 6.061324 9.975213 9.535722 7.174075
[7] 9.820861 8.176774 10.000344 6.943031 6.972302 4.987360
[13] 9.859953 9.604168 8.242446 10.970186 10.083744 8.833735
[19] 9.022981 5.848577
> colMax(tmp5,na.rm=TRUE)
[1] 467.48824 90.37819 78.91496 87.40806 85.82517 84.03098 86.43764
[8] 82.26440 82.29448 81.23274 83.52620 81.48709 87.85226 88.14667
[15] 80.60569 89.06885 85.48025 79.71187 83.59866 86.21482
> colMin(tmp5,na.rm=TRUE)
[1] 60.47552 57.75317 59.77976 55.15480 58.12970 61.93596 62.35414 56.92809
[9] 52.85728 59.55827 60.06254 65.93303 61.19225 55.64550 57.66855 55.40926
[17] 55.08766 57.95304 58.20614 67.70486
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.49944 72.53693 70.11251 NaN 71.69762 73.73889 69.59039 72.81183
[9] 71.07211 72.15113
> rowSums(tmp5,na.rm=TRUE)
[1] 1769.989 1450.739 1402.250 0.000 1433.952 1474.778 1391.808 1456.237
[9] 1421.442 1443.023
> rowVars(tmp5,na.rm=TRUE)
[1] 8020.73621 53.65181 64.76250 NA 72.29581 94.04044
[7] 81.11224 70.43885 100.02570 92.10791
> rowSd(tmp5,na.rm=TRUE)
[1] 89.558563 7.324740 8.047515 NA 8.502694 9.697445 9.006233
[8] 8.392786 10.001285 9.597287
> rowMax(tmp5,na.rm=TRUE)
[1] 467.48824 87.40806 84.03098 NA 87.85226 90.37819 83.10318
[8] 88.14667 83.75637 89.06885
> rowMin(tmp5,na.rm=TRUE)
[1] 56.26920 60.45296 58.14437 NA 56.72632 58.12104 55.08766 58.12970
[9] 52.85728 55.33076
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.49310 NaN 71.84451 68.21618 71.56983 71.84352 75.86387
[8] 69.04660 70.94133 69.06064 72.34065 74.22022 73.47769 73.71031
[15] 72.10532 69.74497 65.75967 68.97321 68.52745 74.34034
> colSums(tmp5,na.rm=TRUE)
[1] 1030.4379 0.0000 646.6006 613.9456 644.1285 646.5917 682.7748
[8] 621.4194 638.4720 621.5458 651.0659 667.9820 661.2992 663.3928
[15] 648.9479 627.7048 591.8370 620.7589 616.7470 669.0631
> colVars(tmp5,na.rm=TRUE)
[1] 17576.89704 NA 41.01225 103.71732 84.83191 52.47168
[7] 98.03934 73.46055 106.35342 40.75370 49.61505 20.25674
[13] 101.85448 103.17152 72.74055 132.61961 70.64072 74.12678
[19] 88.47117 22.61871
> colSd(tmp5,na.rm=TRUE)
[1] 132.577890 NA 6.404081 10.184170 9.210424 7.243734
[7] 9.901482 8.570913 10.312779 6.383862 7.043795 4.500749
[13] 10.092298 10.157338 8.528807 11.516059 8.404804 8.609691
[19] 9.405911 4.755914
> colMax(tmp5,na.rm=TRUE)
[1] 467.48824 -Inf 78.91496 87.40806 85.82517 84.03098 86.43764
[8] 82.26440 82.29448 81.23274 83.52620 81.48709 87.85226 88.14667
[15] 80.60569 89.06885 81.01779 79.71187 83.59866 80.64668
> colMin(tmp5,na.rm=TRUE)
[1] 60.47552 Inf 59.77976 55.15480 58.12970 61.93596 62.35414 56.92809
[9] 52.85728 59.55827 60.06254 67.19368 61.19225 55.64550 57.66855 55.40926
[17] 55.08766 58.12104 58.20614 67.70486
>
>
>
>
> 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] 453.3067 257.1329 183.9046 114.0317 236.8666 245.5217 165.4758 175.7394
[9] 137.5179 262.1105
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 453.3067 257.1329 183.9046 114.0317 236.8666 245.5217 165.4758 175.7394
[9] 137.5179 262.1105
>
>
>
> 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 0.000000e+00 8.526513e-14 8.526513e-14 2.842171e-14
[6] 0.000000e+00 -8.526513e-14 5.684342e-14 8.526513e-14 -9.947598e-14
[11] 3.126388e-13 -5.684342e-14 8.526513e-14 8.526513e-14 -2.842171e-14
[16] -2.842171e-14 -2.842171e-14 0.000000e+00 -2.842171e-14 5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
2 12
10 3
4 16
10 15
10 15
2 5
3 19
3 9
9 20
5 20
8 20
1 15
10 6
3 17
3 13
1 8
2 15
6 11
8 12
5 17
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] 2.781252
> Min(tmp)
[1] -2.133833
> mean(tmp)
[1] 0.003786894
> Sum(tmp)
[1] 0.3786894
> Var(tmp)
[1] 0.911379
>
> rowMeans(tmp)
[1] 0.003786894
> rowSums(tmp)
[1] 0.3786894
> rowVars(tmp)
[1] 0.911379
> rowSd(tmp)
[1] 0.9546617
> rowMax(tmp)
[1] 2.781252
> rowMin(tmp)
[1] -2.133833
>
> colMeans(tmp)
[1] 1.105706289 -0.148350851 -1.341915112 2.199985818 -0.173379148
[6] -0.027788553 -0.449748352 -0.142840336 1.184991923 -0.032298196
[11] 1.470979330 0.090724414 1.067726760 -0.040739571 -0.636851201
[16] 0.884643748 1.356068250 -0.578057158 -1.430800297 0.778742689
[21] -0.240862303 -2.133833115 -1.441945494 -0.981008150 0.348614527
[26] 0.249099220 0.052264252 0.537495922 -0.434539924 -0.062122045
[31] -0.661105819 -0.123873785 -0.664375623 -0.536020597 -0.093565083
[36] 1.460520717 -0.534493324 -1.115186989 1.543084228 1.629716959
[41] 0.765184781 0.164585914 0.745613960 2.395467268 -0.859795891
[46] 1.427017831 0.972462689 1.685933741 -0.004467749 0.170594784
[51] -1.500742615 0.491407967 -0.410589722 -1.097760322 -0.161054062
[56] -0.312386406 0.359159907 0.650032089 -0.833251595 0.965469255
[61] -0.890421150 -1.251817495 0.584758431 -0.447493535 2.781252154
[66] -1.651023873 -0.259473459 0.135979884 -0.796211555 -0.409120672
[71] -0.242959829 1.041931084 -0.601591707 0.720674299 0.909534308
[76] 0.521926057 0.205253627 -1.408373341 -0.461074063 1.004756162
[81] -0.295059770 -0.451907946 0.839331282 -1.126268826 -0.019881382
[86] 0.079810632 -0.727167884 1.495161351 -1.242226140 0.524652032
[91] -0.494165412 -0.389166257 -1.473715215 0.210747929 -1.227294430
[96] 0.031621431 -0.512115225 -0.111595673 -1.034288861 -0.731833375
> colSums(tmp)
[1] 1.105706289 -0.148350851 -1.341915112 2.199985818 -0.173379148
[6] -0.027788553 -0.449748352 -0.142840336 1.184991923 -0.032298196
[11] 1.470979330 0.090724414 1.067726760 -0.040739571 -0.636851201
[16] 0.884643748 1.356068250 -0.578057158 -1.430800297 0.778742689
[21] -0.240862303 -2.133833115 -1.441945494 -0.981008150 0.348614527
[26] 0.249099220 0.052264252 0.537495922 -0.434539924 -0.062122045
[31] -0.661105819 -0.123873785 -0.664375623 -0.536020597 -0.093565083
[36] 1.460520717 -0.534493324 -1.115186989 1.543084228 1.629716959
[41] 0.765184781 0.164585914 0.745613960 2.395467268 -0.859795891
[46] 1.427017831 0.972462689 1.685933741 -0.004467749 0.170594784
[51] -1.500742615 0.491407967 -0.410589722 -1.097760322 -0.161054062
[56] -0.312386406 0.359159907 0.650032089 -0.833251595 0.965469255
[61] -0.890421150 -1.251817495 0.584758431 -0.447493535 2.781252154
[66] -1.651023873 -0.259473459 0.135979884 -0.796211555 -0.409120672
[71] -0.242959829 1.041931084 -0.601591707 0.720674299 0.909534308
[76] 0.521926057 0.205253627 -1.408373341 -0.461074063 1.004756162
[81] -0.295059770 -0.451907946 0.839331282 -1.126268826 -0.019881382
[86] 0.079810632 -0.727167884 1.495161351 -1.242226140 0.524652032
[91] -0.494165412 -0.389166257 -1.473715215 0.210747929 -1.227294430
[96] 0.031621431 -0.512115225 -0.111595673 -1.034288861 -0.731833375
> 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] 1.105706289 -0.148350851 -1.341915112 2.199985818 -0.173379148
[6] -0.027788553 -0.449748352 -0.142840336 1.184991923 -0.032298196
[11] 1.470979330 0.090724414 1.067726760 -0.040739571 -0.636851201
[16] 0.884643748 1.356068250 -0.578057158 -1.430800297 0.778742689
[21] -0.240862303 -2.133833115 -1.441945494 -0.981008150 0.348614527
[26] 0.249099220 0.052264252 0.537495922 -0.434539924 -0.062122045
[31] -0.661105819 -0.123873785 -0.664375623 -0.536020597 -0.093565083
[36] 1.460520717 -0.534493324 -1.115186989 1.543084228 1.629716959
[41] 0.765184781 0.164585914 0.745613960 2.395467268 -0.859795891
[46] 1.427017831 0.972462689 1.685933741 -0.004467749 0.170594784
[51] -1.500742615 0.491407967 -0.410589722 -1.097760322 -0.161054062
[56] -0.312386406 0.359159907 0.650032089 -0.833251595 0.965469255
[61] -0.890421150 -1.251817495 0.584758431 -0.447493535 2.781252154
[66] -1.651023873 -0.259473459 0.135979884 -0.796211555 -0.409120672
[71] -0.242959829 1.041931084 -0.601591707 0.720674299 0.909534308
[76] 0.521926057 0.205253627 -1.408373341 -0.461074063 1.004756162
[81] -0.295059770 -0.451907946 0.839331282 -1.126268826 -0.019881382
[86] 0.079810632 -0.727167884 1.495161351 -1.242226140 0.524652032
[91] -0.494165412 -0.389166257 -1.473715215 0.210747929 -1.227294430
[96] 0.031621431 -0.512115225 -0.111595673 -1.034288861 -0.731833375
> colMin(tmp)
[1] 1.105706289 -0.148350851 -1.341915112 2.199985818 -0.173379148
[6] -0.027788553 -0.449748352 -0.142840336 1.184991923 -0.032298196
[11] 1.470979330 0.090724414 1.067726760 -0.040739571 -0.636851201
[16] 0.884643748 1.356068250 -0.578057158 -1.430800297 0.778742689
[21] -0.240862303 -2.133833115 -1.441945494 -0.981008150 0.348614527
[26] 0.249099220 0.052264252 0.537495922 -0.434539924 -0.062122045
[31] -0.661105819 -0.123873785 -0.664375623 -0.536020597 -0.093565083
[36] 1.460520717 -0.534493324 -1.115186989 1.543084228 1.629716959
[41] 0.765184781 0.164585914 0.745613960 2.395467268 -0.859795891
[46] 1.427017831 0.972462689 1.685933741 -0.004467749 0.170594784
[51] -1.500742615 0.491407967 -0.410589722 -1.097760322 -0.161054062
[56] -0.312386406 0.359159907 0.650032089 -0.833251595 0.965469255
[61] -0.890421150 -1.251817495 0.584758431 -0.447493535 2.781252154
[66] -1.651023873 -0.259473459 0.135979884 -0.796211555 -0.409120672
[71] -0.242959829 1.041931084 -0.601591707 0.720674299 0.909534308
[76] 0.521926057 0.205253627 -1.408373341 -0.461074063 1.004756162
[81] -0.295059770 -0.451907946 0.839331282 -1.126268826 -0.019881382
[86] 0.079810632 -0.727167884 1.495161351 -1.242226140 0.524652032
[91] -0.494165412 -0.389166257 -1.473715215 0.210747929 -1.227294430
[96] 0.031621431 -0.512115225 -0.111595673 -1.034288861 -0.731833375
> colMedians(tmp)
[1] 1.105706289 -0.148350851 -1.341915112 2.199985818 -0.173379148
[6] -0.027788553 -0.449748352 -0.142840336 1.184991923 -0.032298196
[11] 1.470979330 0.090724414 1.067726760 -0.040739571 -0.636851201
[16] 0.884643748 1.356068250 -0.578057158 -1.430800297 0.778742689
[21] -0.240862303 -2.133833115 -1.441945494 -0.981008150 0.348614527
[26] 0.249099220 0.052264252 0.537495922 -0.434539924 -0.062122045
[31] -0.661105819 -0.123873785 -0.664375623 -0.536020597 -0.093565083
[36] 1.460520717 -0.534493324 -1.115186989 1.543084228 1.629716959
[41] 0.765184781 0.164585914 0.745613960 2.395467268 -0.859795891
[46] 1.427017831 0.972462689 1.685933741 -0.004467749 0.170594784
[51] -1.500742615 0.491407967 -0.410589722 -1.097760322 -0.161054062
[56] -0.312386406 0.359159907 0.650032089 -0.833251595 0.965469255
[61] -0.890421150 -1.251817495 0.584758431 -0.447493535 2.781252154
[66] -1.651023873 -0.259473459 0.135979884 -0.796211555 -0.409120672
[71] -0.242959829 1.041931084 -0.601591707 0.720674299 0.909534308
[76] 0.521926057 0.205253627 -1.408373341 -0.461074063 1.004756162
[81] -0.295059770 -0.451907946 0.839331282 -1.126268826 -0.019881382
[86] 0.079810632 -0.727167884 1.495161351 -1.242226140 0.524652032
[91] -0.494165412 -0.389166257 -1.473715215 0.210747929 -1.227294430
[96] 0.031621431 -0.512115225 -0.111595673 -1.034288861 -0.731833375
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.105706 -0.1483509 -1.341915 2.199986 -0.1733791 -0.02778855 -0.4497484
[2,] 1.105706 -0.1483509 -1.341915 2.199986 -0.1733791 -0.02778855 -0.4497484
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.1428403 1.184992 -0.0322982 1.470979 0.09072441 1.067727 -0.04073957
[2,] -0.1428403 1.184992 -0.0322982 1.470979 0.09072441 1.067727 -0.04073957
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.6368512 0.8846437 1.356068 -0.5780572 -1.4308 0.7787427 -0.2408623
[2,] -0.6368512 0.8846437 1.356068 -0.5780572 -1.4308 0.7787427 -0.2408623
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -2.133833 -1.441945 -0.9810082 0.3486145 0.2490992 0.05226425 0.5374959
[2,] -2.133833 -1.441945 -0.9810082 0.3486145 0.2490992 0.05226425 0.5374959
[,29] [,30] [,31] [,32] [,33] [,34]
[1,] -0.4345399 -0.06212205 -0.6611058 -0.1238738 -0.6643756 -0.5360206
[2,] -0.4345399 -0.06212205 -0.6611058 -0.1238738 -0.6643756 -0.5360206
[,35] [,36] [,37] [,38] [,39] [,40] [,41]
[1,] -0.09356508 1.460521 -0.5344933 -1.115187 1.543084 1.629717 0.7651848
[2,] -0.09356508 1.460521 -0.5344933 -1.115187 1.543084 1.629717 0.7651848
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] 0.1645859 0.745614 2.395467 -0.8597959 1.427018 0.9724627 1.685934
[2,] 0.1645859 0.745614 2.395467 -0.8597959 1.427018 0.9724627 1.685934
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.004467749 0.1705948 -1.500743 0.491408 -0.4105897 -1.09776 -0.1610541
[2,] -0.004467749 0.1705948 -1.500743 0.491408 -0.4105897 -1.09776 -0.1610541
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.3123864 0.3591599 0.6500321 -0.8332516 0.9654693 -0.8904212 -1.251817
[2,] -0.3123864 0.3591599 0.6500321 -0.8332516 0.9654693 -0.8904212 -1.251817
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 0.5847584 -0.4474935 2.781252 -1.651024 -0.2594735 0.1359799 -0.7962116
[2,] 0.5847584 -0.4474935 2.781252 -1.651024 -0.2594735 0.1359799 -0.7962116
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] -0.4091207 -0.2429598 1.041931 -0.6015917 0.7206743 0.9095343 0.5219261
[2,] -0.4091207 -0.2429598 1.041931 -0.6015917 0.7206743 0.9095343 0.5219261
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] 0.2052536 -1.408373 -0.4610741 1.004756 -0.2950598 -0.4519079 0.8393313
[2,] 0.2052536 -1.408373 -0.4610741 1.004756 -0.2950598 -0.4519079 0.8393313
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -1.126269 -0.01988138 0.07981063 -0.7271679 1.495161 -1.242226 0.524652
[2,] -1.126269 -0.01988138 0.07981063 -0.7271679 1.495161 -1.242226 0.524652
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -0.4941654 -0.3891663 -1.473715 0.2107479 -1.227294 0.03162143 -0.5121152
[2,] -0.4941654 -0.3891663 -1.473715 0.2107479 -1.227294 0.03162143 -0.5121152
[,98] [,99] [,100]
[1,] -0.1115957 -1.034289 -0.7318334
[2,] -0.1115957 -1.034289 -0.7318334
>
>
> Max(tmp2)
[1] 3.244247
> Min(tmp2)
[1] -3.076514
> mean(tmp2)
[1] -0.0474132
> Sum(tmp2)
[1] -4.74132
> Var(tmp2)
[1] 1.055154
>
> rowMeans(tmp2)
[1] 1.205427655 -0.457390839 0.328280841 -1.539021933 1.154740428
[6] -0.152173348 -0.567860502 -1.489376942 -0.262564278 -0.261542549
[11] 0.707336339 -0.365889306 -0.703421578 -1.031977626 0.875619197
[16] -0.406808773 -0.284944218 -1.062181451 -1.072610401 0.157607819
[21] 1.234571731 -0.648025985 -0.165524160 0.002908584 -1.571257701
[26] 0.720840604 0.599908534 0.124183935 0.903786466 0.980190745
[31] -1.047959841 0.277428878 -1.767471680 -1.871015898 0.818190022
[36] -0.364575565 0.212698999 1.470242439 -0.321388546 -0.299626545
[41] -0.518456148 -1.712943211 2.289785692 -0.176566869 -0.596498064
[46] -0.265553296 0.539158622 -0.204329525 -0.567536609 1.698434888
[51] -0.694747579 0.173902330 -1.290392045 1.192423752 0.283156791
[56] 0.350964459 -0.561298162 0.187495400 0.177118511 1.429789409
[61] 0.943068139 -0.229251340 1.204059672 -0.173258442 0.683522246
[66] 2.103328525 0.904204660 -1.452847037 -0.785898427 -0.258938989
[71] 0.629348947 0.593905585 -0.220888838 -3.076513744 -0.013963524
[76] -0.365913523 -0.917170188 0.396785364 1.310603731 0.256112531
[81] 0.520439400 -0.721994798 -2.217568536 -0.947879649 0.158963184
[86] -0.145299729 -1.264331461 0.630106569 -2.274484199 0.203904396
[91] -0.756575613 0.484602915 -0.678943882 0.956302221 -1.192129996
[96] 0.269085798 1.355816125 0.435062356 3.244246605 -0.124199243
> rowSums(tmp2)
[1] 1.205427655 -0.457390839 0.328280841 -1.539021933 1.154740428
[6] -0.152173348 -0.567860502 -1.489376942 -0.262564278 -0.261542549
[11] 0.707336339 -0.365889306 -0.703421578 -1.031977626 0.875619197
[16] -0.406808773 -0.284944218 -1.062181451 -1.072610401 0.157607819
[21] 1.234571731 -0.648025985 -0.165524160 0.002908584 -1.571257701
[26] 0.720840604 0.599908534 0.124183935 0.903786466 0.980190745
[31] -1.047959841 0.277428878 -1.767471680 -1.871015898 0.818190022
[36] -0.364575565 0.212698999 1.470242439 -0.321388546 -0.299626545
[41] -0.518456148 -1.712943211 2.289785692 -0.176566869 -0.596498064
[46] -0.265553296 0.539158622 -0.204329525 -0.567536609 1.698434888
[51] -0.694747579 0.173902330 -1.290392045 1.192423752 0.283156791
[56] 0.350964459 -0.561298162 0.187495400 0.177118511 1.429789409
[61] 0.943068139 -0.229251340 1.204059672 -0.173258442 0.683522246
[66] 2.103328525 0.904204660 -1.452847037 -0.785898427 -0.258938989
[71] 0.629348947 0.593905585 -0.220888838 -3.076513744 -0.013963524
[76] -0.365913523 -0.917170188 0.396785364 1.310603731 0.256112531
[81] 0.520439400 -0.721994798 -2.217568536 -0.947879649 0.158963184
[86] -0.145299729 -1.264331461 0.630106569 -2.274484199 0.203904396
[91] -0.756575613 0.484602915 -0.678943882 0.956302221 -1.192129996
[96] 0.269085798 1.355816125 0.435062356 3.244246605 -0.124199243
> 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] 1.205427655 -0.457390839 0.328280841 -1.539021933 1.154740428
[6] -0.152173348 -0.567860502 -1.489376942 -0.262564278 -0.261542549
[11] 0.707336339 -0.365889306 -0.703421578 -1.031977626 0.875619197
[16] -0.406808773 -0.284944218 -1.062181451 -1.072610401 0.157607819
[21] 1.234571731 -0.648025985 -0.165524160 0.002908584 -1.571257701
[26] 0.720840604 0.599908534 0.124183935 0.903786466 0.980190745
[31] -1.047959841 0.277428878 -1.767471680 -1.871015898 0.818190022
[36] -0.364575565 0.212698999 1.470242439 -0.321388546 -0.299626545
[41] -0.518456148 -1.712943211 2.289785692 -0.176566869 -0.596498064
[46] -0.265553296 0.539158622 -0.204329525 -0.567536609 1.698434888
[51] -0.694747579 0.173902330 -1.290392045 1.192423752 0.283156791
[56] 0.350964459 -0.561298162 0.187495400 0.177118511 1.429789409
[61] 0.943068139 -0.229251340 1.204059672 -0.173258442 0.683522246
[66] 2.103328525 0.904204660 -1.452847037 -0.785898427 -0.258938989
[71] 0.629348947 0.593905585 -0.220888838 -3.076513744 -0.013963524
[76] -0.365913523 -0.917170188 0.396785364 1.310603731 0.256112531
[81] 0.520439400 -0.721994798 -2.217568536 -0.947879649 0.158963184
[86] -0.145299729 -1.264331461 0.630106569 -2.274484199 0.203904396
[91] -0.756575613 0.484602915 -0.678943882 0.956302221 -1.192129996
[96] 0.269085798 1.355816125 0.435062356 3.244246605 -0.124199243
> rowMin(tmp2)
[1] 1.205427655 -0.457390839 0.328280841 -1.539021933 1.154740428
[6] -0.152173348 -0.567860502 -1.489376942 -0.262564278 -0.261542549
[11] 0.707336339 -0.365889306 -0.703421578 -1.031977626 0.875619197
[16] -0.406808773 -0.284944218 -1.062181451 -1.072610401 0.157607819
[21] 1.234571731 -0.648025985 -0.165524160 0.002908584 -1.571257701
[26] 0.720840604 0.599908534 0.124183935 0.903786466 0.980190745
[31] -1.047959841 0.277428878 -1.767471680 -1.871015898 0.818190022
[36] -0.364575565 0.212698999 1.470242439 -0.321388546 -0.299626545
[41] -0.518456148 -1.712943211 2.289785692 -0.176566869 -0.596498064
[46] -0.265553296 0.539158622 -0.204329525 -0.567536609 1.698434888
[51] -0.694747579 0.173902330 -1.290392045 1.192423752 0.283156791
[56] 0.350964459 -0.561298162 0.187495400 0.177118511 1.429789409
[61] 0.943068139 -0.229251340 1.204059672 -0.173258442 0.683522246
[66] 2.103328525 0.904204660 -1.452847037 -0.785898427 -0.258938989
[71] 0.629348947 0.593905585 -0.220888838 -3.076513744 -0.013963524
[76] -0.365913523 -0.917170188 0.396785364 1.310603731 0.256112531
[81] 0.520439400 -0.721994798 -2.217568536 -0.947879649 0.158963184
[86] -0.145299729 -1.264331461 0.630106569 -2.274484199 0.203904396
[91] -0.756575613 0.484602915 -0.678943882 0.956302221 -1.192129996
[96] 0.269085798 1.355816125 0.435062356 3.244246605 -0.124199243
>
> colMeans(tmp2)
[1] -0.0474132
> colSums(tmp2)
[1] -4.74132
> colVars(tmp2)
[1] 1.055154
> colSd(tmp2)
[1] 1.027207
> colMax(tmp2)
[1] 3.244247
> colMin(tmp2)
[1] -3.076514
> colMedians(tmp2)
[1] -0.1487365
> colRanges(tmp2)
[,1]
[1,] -3.076514
[2,] 3.244247
>
> 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] 1.9820844 -3.9101074 -1.2073149 2.6761063 -1.9950903 -0.2532113
[7] 5.7936542 -1.8462114 -4.5923013 4.3528763
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5358330
[2,] -0.1168098
[3,] 0.2584932
[4,] 0.7971450
[5,] 1.2657024
>
> rowApply(tmp,sum)
[1] -1.1491012 4.0347322 2.7144346 0.8285878 -0.4943322 -5.0539162
[7] 1.5459491 3.7915341 -0.4599451 -4.7574584
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 8 4 2 6 10 9 6 7 1
[2,] 2 6 7 3 1 9 5 8 2 3
[3,] 4 7 2 5 7 7 6 5 4 5
[4,] 3 5 10 4 5 2 4 3 8 10
[5,] 10 2 1 9 2 4 2 7 6 7
[6,] 1 4 9 6 4 8 8 1 5 4
[7,] 9 9 5 7 9 5 7 9 9 9
[8,] 7 3 3 10 10 3 1 10 3 8
[9,] 8 1 6 1 3 1 10 2 1 2
[10,] 6 10 8 8 8 6 3 4 10 6
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 3.18299748 -2.49280969 -2.52710214 -0.64421877 1.10959616 -2.14558995
[7] 1.55317615 0.04512242 -3.99142762 1.23227163 -1.34333254 1.23675681
[13] 2.11355122 0.40774576 0.99406549 4.13756828 -2.42275269 -0.12848672
[19] 0.69769688 -1.47830080
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8055477
[2,] -0.2726038
[3,] 0.9812235
[4,] 1.5512812
[5,] 1.7286442
>
> rowApply(tmp,sum)
[1] -3.818081 -3.387610 5.857276 2.867131 -1.982188
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 8 17 19 20
[2,] 5 12 7 2 11
[3,] 4 3 11 17 1
[4,] 9 7 14 3 15
[5,] 20 2 12 7 19
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.8055477 -1.05155385 -1.078372 -0.4914937 1.4339433 -0.5894654
[2,] -0.2726038 0.21460725 -1.745776 -0.4440643 -1.8370973 -1.8803689
[3,] 0.9812235 0.05293184 0.341002 0.9572427 0.4455143 -0.1432363
[4,] 1.7286442 -1.58243499 1.223581 -1.2957710 -0.1187756 1.5859173
[5,] 1.5512812 -0.12635994 -1.267537 0.6298676 1.1860114 -1.1184366
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.7252927 1.1133228 -3.2266231 -0.3606952 1.05201358 0.2347720
[2,] -0.1978496 1.9257658 -1.4919075 0.3954980 0.68121453 0.7256410
[3,] 1.3226907 -1.1369285 -0.1791647 0.2976375 -2.07808858 -0.2635128
[4,] 0.4714212 -0.8870772 0.1066370 0.5940975 0.02937377 0.7146902
[5,] -0.7683787 -0.9699604 0.7996306 0.3057338 -1.02784583 -0.1748336
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.7741243 0.6604124 -1.1291490 0.6340102 -1.5548909 0.3832863
[2,] 0.4427914 -0.1243058 0.6008724 0.9898195 -1.5885565 -0.8141257
[3,] 0.9757169 0.3390115 1.4005043 1.4227408 0.2965446 0.9585861
[4,] 0.3912606 0.3396464 -0.3578290 1.8570770 -0.1123460 0.5301359
[5,] 1.0779066 -0.8070188 0.4796668 -0.7660793 0.5364961 -1.1863692
[,19] [,20]
[1,] 0.06633954 0.9404411
[2,] 0.91645527 0.1163800
[3,] 0.67234838 -0.8054882
[4,] -1.88391747 -0.4671993
[5,] 0.92647116 -1.2624345
>
>
> 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 : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.17-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 0.05235542 -1.20462 -0.9656507 -1.090947 0.840571 0.09357325 -0.535268
col8 col9 col10 col11 col12 col13 col14
row1 0.8840218 0.4736145 0.335435 1.989209 -0.402684 -1.258364 0.7630695
col15 col16 col17 col18 col19 col20
row1 -0.01063844 0.760407 0.8548113 -0.5797787 1.38549 -0.006105789
> tmp[,"col10"]
col10
row1 0.3354350
row2 1.1998839
row3 0.3048637
row4 0.6602830
row5 0.5043884
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.05235542 -1.2046204 -0.9656507 -1.0909468 0.8405710 0.09357325
row5 0.93533164 0.2367815 0.6928933 -0.5606234 -0.3016924 2.00081318
col7 col8 col9 col10 col11 col12 col13
row1 -0.535268 0.8840218 0.4736145 0.3354350 1.989209 -0.402684 -1.258364
row5 2.112524 -0.7314354 -0.1078632 0.5043884 0.768892 -1.002206 -1.231196
col14 col15 col16 col17 col18 col19
row1 0.7630695 -0.01063844 0.760407 0.8548113 -0.5797787 1.3854902
row5 0.6889428 0.32028961 -0.399712 0.8149038 -1.0724496 -0.5348033
col20
row1 -0.006105789
row5 0.776305937
> tmp[,c("col6","col20")]
col6 col20
row1 0.09357325 -0.006105789
row2 -0.28156469 -0.443277041
row3 1.30750218 1.213512413
row4 -1.28583343 0.669086045
row5 2.00081318 0.776305937
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.09357325 -0.006105789
row5 2.00081318 0.776305937
>
>
>
>
> 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 50.42361 50.64519 49.88638 48.12533 51.08461 105.9231 49.23198 50.3299
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.81616 47.33353 50.05274 50.5834 49.13327 49.83474 50.80847 51.46156
col17 col18 col19 col20
row1 50.45386 50.30609 48.56487 104.2848
> tmp[,"col10"]
col10
row1 47.33353
row2 31.49672
row3 30.80802
row4 28.42879
row5 50.03586
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.42361 50.64519 49.88638 48.12533 51.08461 105.9231 49.23198 50.32990
row5 50.74609 50.26107 49.64672 50.09223 49.65722 103.4518 50.15938 49.53285
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.81616 47.33353 50.05274 50.58340 49.13327 49.83474 50.80847 51.46156
row5 49.01725 50.03586 49.73632 50.00594 49.87342 49.46039 50.59400 51.22846
col17 col18 col19 col20
row1 50.45386 50.30609 48.56487 104.2848
row5 48.82692 49.78267 50.06632 105.5888
> tmp[,c("col6","col20")]
col6 col20
row1 105.92315 104.28479
row2 74.53614 74.62126
row3 74.79249 75.97816
row4 75.55508 74.05790
row5 103.45178 105.58879
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.9231 104.2848
row5 103.4518 105.5888
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.9231 104.2848
row5 103.4518 105.5888
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.4439909
[2,] -0.4642162
[3,] 0.1706559
[4,] -0.2120447
[5,] 1.4354746
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.9971753 0.68025451
[2,] -1.5154798 -0.32460178
[3,] 1.1211297 3.01257546
[4,] 1.6063282 0.35029739
[5,] -0.1858421 0.05123272
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.51845002 -0.4261582
[2,] -1.00028038 -0.4818241
[3,] 0.09412242 2.4058847
[4,] -1.75538644 -1.5384433
[5,] 0.64970540 -0.7402479
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.51845
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.51845
[2,] -1.00028
>
>
>
> 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 -0.2390798 0.3865937 0.6933823 0.8617728 1.0838351 0.3483824
row1 -0.9571761 -2.4138213 -0.5956025 -0.3994133 0.5422996 -1.1230703
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.61254970 -0.697848 0.3970973 -0.3352101 1.220627 0.7441411 0.2697051
row1 -0.06830471 -1.493222 -1.4856209 0.4794322 1.797827 0.8393974 -1.4483837
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -1.514035 1.854812 0.71678579 -0.8311669 0.06797271 0.5704959 0.9101099
row1 -1.747439 2.848005 -0.07740968 -0.5284791 -0.50336313 0.9175124 1.5359176
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.333985 0.0296909 -1.045474 1.023356 -3.432362 -0.4269969 -1.101885
[,8] [,9] [,10]
row2 0.8857883 1.115738 0.1114478
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.08856461 -0.7858026 0.732044 0.7581299 -0.5565398 0.4200934 -0.08746156
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.5482436 0.3637481 0.5994703 0.3816235 1.048535 0.6237659 -1.014636
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.280052 -1.068402 -3.003649 -0.874382 0.466016 -0.2293498
>
>
> 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: 0x561d1cf68e90>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM15020aae67202"
[2] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM15020a51f9bf42"
[3] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM15020a11c60a02"
[4] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM15020a93ca8ce"
[5] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM15020a6a3c1f5"
[6] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM15020a249c0159"
[7] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM15020a17fd3c55"
[8] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM15020a78e14dca"
[9] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM15020a2e92049f"
[10] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM15020a72c4785e"
[11] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM15020a4f11584"
[12] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM15020a74d184f4"
[13] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM15020a215ae8a9"
[14] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM15020a63ffd42c"
[15] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM15020a5f129ad6"
>
>
> ### 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: 0x561d2079f840>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x561d2079f840>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x561d2079f840>
> rowMedians(tmp)
[1] -0.638369472 0.432647489 0.174856407 -0.201667453 0.001912438
[6] 0.269526575 0.393254033 0.068933670 -0.534968186 0.453443612
[11] -0.370777623 0.201955603 -0.359645101 -0.236231922 -0.019842906
[16] 0.100813479 -0.013810847 -0.049950668 0.504903556 0.196941869
[21] -0.452408613 -0.058938431 -0.211656938 0.156496275 0.076008695
[26] 0.295573337 -0.104822761 -0.123321793 0.273550253 0.190863030
[31] 0.043943039 0.006042233 0.062762060 0.269600519 -0.323879814
[36] -0.567855943 -0.581722141 0.148098328 -0.958151087 0.066626377
[41] -0.243200416 0.025564808 0.004000812 -0.129188930 0.496189748
[46] 0.040203998 0.020344000 0.252306013 0.340934209 -0.083957288
[51] 0.216575210 -0.277007169 0.237091082 -0.692992185 -0.005379424
[56] -0.717554494 0.007186337 0.168116247 -0.191862561 -0.298418849
[61] 0.232969914 -0.184681502 0.258795566 -0.303824333 0.003154686
[66] 0.246712992 0.098207924 -0.076113440 0.015185545 -0.947504235
[71] -0.060341789 -0.074596406 -0.154954941 -0.133167386 0.014215322
[76] 0.081215354 -0.387681880 0.003067599 -0.245640759 -0.074937097
[81] 0.050222578 -0.141492873 -0.082444478 -0.194398692 0.227620368
[86] -0.241183342 0.256458358 -0.371276903 -0.108045467 0.035706841
[91] -0.030290675 -0.231758979 0.341218270 0.003476616 -0.044429529
[96] 0.023840570 0.170048331 -0.678113599 0.005566498 0.174269909
[101] 0.037290876 0.063231900 0.092437808 -0.124983254 0.389290053
[106] 0.043018425 -0.484109103 0.011065840 -0.395551873 -0.230065099
[111] 0.286712450 0.370633851 -0.494218531 0.335292990 0.481387515
[116] 0.044730852 0.140993463 0.157607820 -0.329659900 0.070675066
[121] 0.134698199 -0.170042102 0.022570565 0.087303953 -0.570717466
[126] -0.195732451 0.011732601 0.059899398 -0.404680324 0.230693079
[131] -0.073286305 0.242470187 0.063712359 0.073382521 0.342958444
[136] 0.471033117 0.556020556 -0.506427837 -0.000559178 -0.183703293
[141] 0.190739026 0.032829346 -0.234562251 0.901367506 -0.220254318
[146] 0.147940817 -0.174652453 -0.659135987 -0.029611334 -0.124240122
[151] -0.185548612 0.823347552 0.226455526 -0.087572858 -0.119105115
[156] -0.139055113 0.260353695 -0.317683014 -0.694050489 0.016291491
[161] -0.025024660 0.029840873 -0.213610829 0.248434379 -0.361335416
[166] 0.030778619 0.037689743 0.510087908 -0.169592800 0.157852947
[171] -0.153214630 0.232356318 -0.135898696 0.248876907 -0.330201876
[176] -0.332974384 -0.059269190 -0.261091602 -0.108810573 0.423444772
[181] 0.602814515 0.346913837 0.290358544 0.433567755 0.977400717
[186] 0.530114055 -0.651185654 0.946017263 0.256788288 0.054464708
[191] 0.217580269 -0.045285727 0.091394979 -0.319308406 0.189193012
[196] 0.189697426 -0.189769634 -0.412964168 0.153953388 0.016960229
[201] 0.314360488 -0.316121272 0.006496640 0.146170501 -0.249577039
[206] -0.046366995 0.710263383 0.490662099 -0.048391405 -0.447409486
[211] 0.426998207 -0.171968605 -0.026121783 0.157164717 0.235989464
[216] -0.316267052 -0.459815454 -0.316934716 0.127289651 -0.411106181
[221] -0.260797033 -0.544218632 0.220457386 0.100593386 0.476825479
[226] -0.127606904 0.748515689 0.023702494 0.006243927 0.101278140
>
> proc.time()
user system elapsed
1.322 0.610 1.918
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2023-02-14 r83833) -- "Unsuffered Consequences"
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: 0x55f9363fe880>
> .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: 0x55f9363fe880>
> .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: 0x55f9363fe880>
> .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: 0x55f9363fe880>
> 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: 0x55f9363432a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55f9363432a0>
> .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: 0x55f9363432a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55f9363432a0>
> .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: 0x55f9363432a0>
> 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: 0x55f934098860>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55f934098860>
> .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: 0x55f934098860>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x55f934098860>
> .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: 0x55f934098860>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x55f934098860>
> .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: 0x55f934098860>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x55f934098860>
> .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: 0x55f934098860>
> 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: 0x55f934a56630>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x55f934a56630>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55f934a56630>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55f934a56630>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1504d516c578" "BufferedMatrixFile1504d53058f6b6"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1504d516c578" "BufferedMatrixFile1504d53058f6b6"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x55f934aeba30>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55f934aeba30>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x55f934aeba30>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x55f934aeba30>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x55f934aeba30>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x55f934aeba30>
> .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: 0x55f9345f8900>
> .Call("R_bm_AddColumn",P)
<pointer: 0x55f9345f8900>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x55f9345f8900>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x55f9345f8900>
> 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: 0x55f935b1d4e0>
> .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: 0x55f935b1d4e0>
> rm(P)
>
> proc.time()
user system elapsed
0.258 0.052 0.294
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2023-02-14 r83833) -- "Unsuffered Consequences"
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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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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
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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
0.308 0.044 0.337