| Back to Multiple platform build/check report for BioC 3.16: simplified long |
|
This page was generated on 2023-04-12 11:04:59 -0400 (Wed, 12 Apr 2023).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 20.04.5 LTS) | x86_64 | 4.2.3 (2023-03-15) -- "Shortstop Beagle" | 4502 |
| palomino4 | Windows Server 2022 Datacenter | x64 | 4.2.3 (2023-03-15 ucrt) -- "Shortstop Beagle" | 4282 |
| lconway | macOS 12.5.1 Monterey | x86_64 | 4.2.3 (2023-03-15) -- "Shortstop Beagle" | 4310 |
| 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: - Please 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 How and When does the builder pull? When will my changes propagate? for more information. - Make sure to use the following settings in order to reproduce any error or warning you see on this page. |
| Package 232/2183 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.62.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 20.04.5 LTS) / x86_64 | OK | OK | OK |  | ||||||||
| palomino4 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.5.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| Package: BufferedMatrix |
| Version: 1.62.0 |
| Command: /home/biocbuild/bbs-3.16-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.16-bioc/R/site-library --timings BufferedMatrix_1.62.0.tar.gz |
| StartedAt: 2023-04-10 19:26:45 -0400 (Mon, 10 Apr 2023) |
| EndedAt: 2023-04-10 19:27:09 -0400 (Mon, 10 Apr 2023) |
| EllapsedTime: 24.3 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.16-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.16-bioc/R/site-library --timings BufferedMatrix_1.62.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck’ * using R version 4.2.3 (2023-03-15) * using platform: x86_64-pc-linux-gnu (64-bit) * using session charset: UTF-8 * checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK * this is package ‘BufferedMatrix’ version ‘1.62.0’ * 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 * 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-3.16-bioc/meat/BufferedMatrix.Rcheck/00check.log’ for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.16-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.16-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
gcc -I"/home/biocbuild/bbs-3.16-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.16-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-3.16-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-3.16-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-3.16-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-3.16-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.16-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 4.2.3 (2023-03-15) -- "Shortstop Beagle"
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
0.319 0.036 0.335
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.2.3 (2023-03-15) -- "Shortstop Beagle"
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-3.16-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 444084 23.8 953921 51 629780 33.7
Vcells 800801 6.2 8388608 64 1915324 14.7
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Mon Apr 10 19:27:02 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] "Mon Apr 10 19:27:02 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: 0x564e481a1400>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Mon Apr 10 19:27:02 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] "Mon Apr 10 19:27:02 2023"
>
> ColMode(tmp2)
<pointer: 0x564e481a1400>
>
>
>
> ### 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,] 102.34238851 0.39266984 -1.0902142 -0.65699931
[2,] -0.09241697 0.66563681 3.2209660 -0.05530266
[3,] -1.40964244 0.87096830 0.3794316 1.02324400
[4,] 0.05240489 -0.05420876 0.7757459 0.96744386
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.16-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,] 102.34238851 0.39266984 1.0902142 0.65699931
[2,] 0.09241697 0.66563681 3.2209660 0.05530266
[3,] 1.40964244 0.87096830 0.3794316 1.02324400
[4,] 0.05240489 0.05420876 0.7757459 0.96744386
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.1164415 0.6266337 1.0441332 0.8105549
[2,] 0.3040016 0.8158657 1.7947050 0.2351652
[3,] 1.1872836 0.9332568 0.6159802 1.0115552
[4,] 0.2289211 0.2328278 0.8807644 0.9835872
>
> 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-3.16-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,] 228.50680 31.65901 36.53155 33.76255
[2,] 28.13243 33.82429 46.16802 27.40695
[3,] 38.28248 35.20354 31.53923 36.13880
[4,] 27.34162 27.38249 34.58339 35.80332
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x564e46d477c0>
> exp(tmp5)
<pointer: 0x564e46d477c0>
> log(tmp5,2)
<pointer: 0x564e46d477c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 475.607
> Min(tmp5)
[1] 54.14436
> mean(tmp5)
[1] 73.04361
> Sum(tmp5)
[1] 14608.72
> Var(tmp5)
[1] 891.3772
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 96.05708 68.91291 71.55359 73.08465 70.00424 71.01810 69.80628 68.41152
[9] 69.77614 71.81159
> rowSums(tmp5)
[1] 1921.142 1378.258 1431.072 1461.693 1400.085 1420.362 1396.126 1368.230
[9] 1395.523 1436.232
> rowVars(tmp5)
[1] 8049.06376 90.90908 52.26326 100.35311 69.60019 65.46223
[7] 50.61610 80.73361 70.35263 68.35941
> rowSd(tmp5)
[1] 89.716575 9.534625 7.229333 10.017640 8.342673 8.090873 7.114499
[8] 8.985188 8.387647 8.267975
> rowMax(tmp5)
[1] 475.60697 96.09268 81.80336 91.40352 87.40378 82.53960 84.56582
[8] 82.52885 91.62200 83.45387
> rowMin(tmp5)
[1] 60.11236 54.46326 55.00838 56.90799 54.14436 56.18603 57.82729 56.66412
[9] 57.67233 54.75755
>
> colMeans(tmp5)
[1] 110.26534 68.43385 74.03066 72.63286 74.08390 71.49491 68.98630
[8] 65.24046 73.21602 68.04313 78.75573 71.84481 69.86337 69.01191
[15] 68.21810 68.65470 72.24793 71.78280 70.46441 73.60103
> colSums(tmp5)
[1] 1102.6534 684.3385 740.3066 726.3286 740.8390 714.9491 689.8630
[8] 652.4046 732.1602 680.4313 787.5573 718.4481 698.6337 690.1191
[15] 682.1810 686.5470 722.4793 717.8280 704.6441 736.0103
> colVars(tmp5)
[1] 16567.07879 58.89548 116.97090 58.30472 47.70836 47.17313
[7] 99.18152 70.34983 41.73258 55.29607 41.16173 38.53885
[13] 56.96172 106.46072 65.06712 49.00681 165.41790 91.19540
[19] 30.34145 95.95928
> colSd(tmp5)
[1] 128.713165 7.674339 10.815309 7.635753 6.907124 6.868269
[7] 9.958992 8.387480 6.460076 7.436133 6.415741 6.207967
[13] 7.547299 10.317980 8.066419 7.000486 12.861489 9.549628
[19] 5.508307 9.795881
> colMax(tmp5)
[1] 475.60697 82.52885 96.09268 81.32399 82.20168 82.39125 81.80336
[8] 81.04057 86.40051 77.97901 91.62200 82.26644 82.58008 87.63814
[15] 79.53144 83.45387 90.15843 91.40352 79.24691 87.51968
> colMin(tmp5)
[1] 56.90799 56.99306 59.99878 57.04398 64.25857 61.65072 56.18603 54.46326
[9] 64.15407 57.73227 69.49883 63.05183 56.66412 57.31425 54.14436 60.71365
[17] 55.00838 59.04918 63.47776 54.75755
>
>
> ### 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] 96.05708 68.91291 71.55359 73.08465 70.00424 71.01810 69.80628 68.41152
[9] 69.77614 NA
> rowSums(tmp5)
[1] 1921.142 1378.258 1431.072 1461.693 1400.085 1420.362 1396.126 1368.230
[9] 1395.523 NA
> rowVars(tmp5)
[1] 8049.06376 90.90908 52.26326 100.35311 69.60019 65.46223
[7] 50.61610 80.73361 70.35263 67.39942
> rowSd(tmp5)
[1] 89.716575 9.534625 7.229333 10.017640 8.342673 8.090873 7.114499
[8] 8.985188 8.387647 8.209715
> rowMax(tmp5)
[1] 475.60697 96.09268 81.80336 91.40352 87.40378 82.53960 84.56582
[8] 82.52885 91.62200 NA
> rowMin(tmp5)
[1] 60.11236 54.46326 55.00838 56.90799 54.14436 56.18603 57.82729 56.66412
[9] 57.67233 NA
>
> colMeans(tmp5)
[1] 110.26534 68.43385 74.03066 72.63286 74.08390 71.49491 68.98630
[8] 65.24046 73.21602 68.04313 78.75573 71.84481 69.86337 69.01191
[15] NA 68.65470 72.24793 71.78280 70.46441 73.60103
> colSums(tmp5)
[1] 1102.6534 684.3385 740.3066 726.3286 740.8390 714.9491 689.8630
[8] 652.4046 732.1602 680.4313 787.5573 718.4481 698.6337 690.1191
[15] NA 686.5470 722.4793 717.8280 704.6441 736.0103
> colVars(tmp5)
[1] 16567.07879 58.89548 116.97090 58.30472 47.70836 47.17313
[7] 99.18152 70.34983 41.73258 55.29607 41.16173 38.53885
[13] 56.96172 106.46072 NA 49.00681 165.41790 91.19540
[19] 30.34145 95.95928
> colSd(tmp5)
[1] 128.713165 7.674339 10.815309 7.635753 6.907124 6.868269
[7] 9.958992 8.387480 6.460076 7.436133 6.415741 6.207967
[13] 7.547299 10.317980 NA 7.000486 12.861489 9.549628
[19] 5.508307 9.795881
> colMax(tmp5)
[1] 475.60697 82.52885 96.09268 81.32399 82.20168 82.39125 81.80336
[8] 81.04057 86.40051 77.97901 91.62200 82.26644 82.58008 87.63814
[15] NA 83.45387 90.15843 91.40352 79.24691 87.51968
> colMin(tmp5)
[1] 56.90799 56.99306 59.99878 57.04398 64.25857 61.65072 56.18603 54.46326
[9] 64.15407 57.73227 69.49883 63.05183 56.66412 57.31425 NA 60.71365
[17] 55.00838 59.04918 63.47776 54.75755
>
> Max(tmp5,na.rm=TRUE)
[1] 475.607
> Min(tmp5,na.rm=TRUE)
[1] 54.14436
> mean(tmp5,na.rm=TRUE)
[1] 73.09513
> Sum(tmp5,na.rm=TRUE)
[1] 14545.93
> Var(tmp5,na.rm=TRUE)
[1] 895.3456
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 96.05708 68.91291 71.55359 73.08465 70.00424 71.01810 69.80628 68.41152
[9] 69.77614 72.28632
> rowSums(tmp5,na.rm=TRUE)
[1] 1921.142 1378.258 1431.072 1461.693 1400.085 1420.362 1396.126 1368.230
[9] 1395.523 1373.440
> rowVars(tmp5,na.rm=TRUE)
[1] 8049.06376 90.90908 52.26326 100.35311 69.60019 65.46223
[7] 50.61610 80.73361 70.35263 67.39942
> rowSd(tmp5,na.rm=TRUE)
[1] 89.716575 9.534625 7.229333 10.017640 8.342673 8.090873 7.114499
[8] 8.985188 8.387647 8.209715
> rowMax(tmp5,na.rm=TRUE)
[1] 475.60697 96.09268 81.80336 91.40352 87.40378 82.53960 84.56582
[8] 82.52885 91.62200 83.45387
> rowMin(tmp5,na.rm=TRUE)
[1] 60.11236 54.46326 55.00838 56.90799 54.14436 56.18603 57.82729 56.66412
[9] 57.67233 54.75755
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.26534 68.43385 74.03066 72.63286 74.08390 71.49491 68.98630
[8] 65.24046 73.21602 68.04313 78.75573 71.84481 69.86337 69.01191
[15] 68.82103 68.65470 72.24793 71.78280 70.46441 73.60103
> colSums(tmp5,na.rm=TRUE)
[1] 1102.6534 684.3385 740.3066 726.3286 740.8390 714.9491 689.8630
[8] 652.4046 732.1602 680.4313 787.5573 718.4481 698.6337 690.1191
[15] 619.3892 686.5470 722.4793 717.8280 704.6441 736.0103
> colVars(tmp5,na.rm=TRUE)
[1] 16567.07879 58.89548 116.97090 58.30472 47.70836 47.17313
[7] 99.18152 70.34983 41.73258 55.29607 41.16173 38.53885
[13] 56.96172 106.46072 69.11091 49.00681 165.41790 91.19540
[19] 30.34145 95.95928
> colSd(tmp5,na.rm=TRUE)
[1] 128.713165 7.674339 10.815309 7.635753 6.907124 6.868269
[7] 9.958992 8.387480 6.460076 7.436133 6.415741 6.207967
[13] 7.547299 10.317980 8.313297 7.000486 12.861489 9.549628
[19] 5.508307 9.795881
> colMax(tmp5,na.rm=TRUE)
[1] 475.60697 82.52885 96.09268 81.32399 82.20168 82.39125 81.80336
[8] 81.04057 86.40051 77.97901 91.62200 82.26644 82.58008 87.63814
[15] 79.53144 83.45387 90.15843 91.40352 79.24691 87.51968
> colMin(tmp5,na.rm=TRUE)
[1] 56.90799 56.99306 59.99878 57.04398 64.25857 61.65072 56.18603 54.46326
[9] 64.15407 57.73227 69.49883 63.05183 56.66412 57.31425 54.14436 60.71365
[17] 55.00838 59.04918 63.47776 54.75755
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 96.05708 68.91291 71.55359 73.08465 70.00424 71.01810 69.80628 68.41152
[9] 69.77614 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1921.142 1378.258 1431.072 1461.693 1400.085 1420.362 1396.126 1368.230
[9] 1395.523 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 8049.06376 90.90908 52.26326 100.35311 69.60019 65.46223
[7] 50.61610 80.73361 70.35263 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 89.716575 9.534625 7.229333 10.017640 8.342673 8.090873 7.114499
[8] 8.985188 8.387647 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 475.60697 96.09268 81.80336 91.40352 87.40378 82.53960 84.56582
[8] 82.52885 91.62200 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 60.11236 54.46326 55.00838 56.90799 54.14436 56.18603 57.82729 56.66412
[9] 57.67233 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.92203 67.72837 74.32507 71.97292 73.46970 71.17587 68.33556
[8] 64.45530 72.47708 68.90604 78.44330 72.82181 69.49344 67.59150
[15] NaN 67.01034 72.19179 72.40676 70.36736 75.69475
> colSums(tmp5,na.rm=TRUE)
[1] 1043.2983 609.5553 668.9257 647.7563 661.2273 640.5828 615.0201
[8] 580.0977 652.2937 620.1544 705.9897 655.3963 625.4410 608.3235
[15] 0.0000 603.0931 649.7261 651.6609 633.3062 681.2528
> colVars(tmp5,na.rm=TRUE)
[1] 18277.98467 60.65831 130.61711 60.69334 49.42802 51.92465
[7] 106.81537 72.20822 40.80626 53.83108 45.20880 32.61778
[13] 62.54239 97.07090 NA 24.71383 186.05967 98.21486
[19] 34.02815 58.63796
> colSd(tmp5,na.rm=TRUE)
[1] 135.196097 7.788345 11.428784 7.790593 7.030507 7.205876
[7] 10.335152 8.497542 6.387977 7.336967 6.723749 5.711198
[13] 7.908375 9.852457 NA 4.971301 13.640369 9.910341
[19] 5.833365 7.657543
> colMax(tmp5,na.rm=TRUE)
[1] 475.60697 82.52885 96.09268 81.32399 82.20168 82.39125 81.80336
[8] 81.04057 86.40051 77.97901 91.62200 82.26644 82.58008 87.63814
[15] -Inf 76.49016 90.15843 91.40352 79.24691 87.51968
> colMin(tmp5,na.rm=TRUE)
[1] 56.90799 56.99306 59.99878 57.04398 64.25857 61.65072 56.18603 54.46326
[9] 64.15407 57.73227 69.49883 64.83285 56.66412 57.31425 Inf 60.71365
[17] 55.00838 59.04918 63.47776 64.73252
>
>
>
>
> 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] 190.5262 150.9048 113.3545 190.5203 191.8663 197.4096 369.4204 328.7930
[9] 134.6383 262.3623
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 190.5262 150.9048 113.3545 190.5203 191.8663 197.4096 369.4204 328.7930
[9] 134.6383 262.3623
>
>
>
> 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] 2.842171e-14 7.105427e-14 8.526513e-14 -2.842171e-14 -2.842171e-14
[6] 1.421085e-13 2.842171e-14 -2.842171e-14 8.526513e-14 5.684342e-14
[11] -1.136868e-13 4.263256e-14 1.136868e-13 2.273737e-13 -8.526513e-14
[16] -7.105427e-14 2.842171e-14 5.684342e-14 2.842171e-14 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## 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)
+ }
4 13
8 4
6 5
2 5
9 15
4 19
9 11
1 20
6 14
3 7
5 19
2 4
5 7
9 12
2 5
7 3
6 20
4 12
8 7
9 15
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] 2.822056
> Min(tmp)
[1] -2.492887
> mean(tmp)
[1] 0.06613705
> Sum(tmp)
[1] 6.613705
> Var(tmp)
[1] 1.077604
>
> rowMeans(tmp)
[1] 0.06613705
> rowSums(tmp)
[1] 6.613705
> rowVars(tmp)
[1] 1.077604
> rowSd(tmp)
[1] 1.038077
> rowMax(tmp)
[1] 2.822056
> rowMin(tmp)
[1] -2.492887
>
> colMeans(tmp)
[1] -2.29398485 -0.06373387 0.72894134 -2.33987300 1.19112951 0.89499837
[7] 1.22088930 1.83133424 1.28148787 0.22043580 -2.49288699 0.98690150
[13] -2.12742756 -1.01147279 1.76839570 1.65411906 0.71849990 0.64966874
[19] 1.17489034 -0.46104850 -0.11667559 -0.92175118 -0.20028077 1.01404066
[25] -0.61770583 0.69218707 -0.44772472 1.34097627 0.01431211 0.77565744
[31] -0.08902253 -0.44444116 0.30390622 -0.87910274 0.36146985 -0.14077647
[37] -0.45355698 1.05492736 1.40383630 -0.46239206 0.27080016 -1.12923686
[43] 0.27804049 -0.78447979 -0.40910507 1.48655244 0.07249288 -0.89694986
[49] 0.46777219 -0.95489189 0.41534955 -0.10105137 1.78696462 -1.40706714
[55] 0.30466228 0.14510752 -0.76498496 -1.53493165 1.54477021 0.65396764
[61] 0.65436413 1.28755633 -0.48305014 1.15091021 -0.29081147 -1.22171620
[67] -0.55306686 0.56168949 -0.79330997 -0.47347168 0.08786368 -2.10859995
[73] 1.48144437 -0.04256233 -0.26462955 -0.20655692 0.54459956 1.10817386
[79] -0.33214474 0.44469112 0.59018516 -1.07999825 0.29966895 0.34884790
[85] 0.18383592 -0.43633674 1.41515192 0.53136820 -0.09134722 -1.45317036
[91] 2.82205564 -1.62129006 -0.00332294 -0.53181595 1.13159212 -0.14323970
[97] 1.21983828 -1.18511407 0.13723137 -1.23473672
> colSums(tmp)
[1] -2.29398485 -0.06373387 0.72894134 -2.33987300 1.19112951 0.89499837
[7] 1.22088930 1.83133424 1.28148787 0.22043580 -2.49288699 0.98690150
[13] -2.12742756 -1.01147279 1.76839570 1.65411906 0.71849990 0.64966874
[19] 1.17489034 -0.46104850 -0.11667559 -0.92175118 -0.20028077 1.01404066
[25] -0.61770583 0.69218707 -0.44772472 1.34097627 0.01431211 0.77565744
[31] -0.08902253 -0.44444116 0.30390622 -0.87910274 0.36146985 -0.14077647
[37] -0.45355698 1.05492736 1.40383630 -0.46239206 0.27080016 -1.12923686
[43] 0.27804049 -0.78447979 -0.40910507 1.48655244 0.07249288 -0.89694986
[49] 0.46777219 -0.95489189 0.41534955 -0.10105137 1.78696462 -1.40706714
[55] 0.30466228 0.14510752 -0.76498496 -1.53493165 1.54477021 0.65396764
[61] 0.65436413 1.28755633 -0.48305014 1.15091021 -0.29081147 -1.22171620
[67] -0.55306686 0.56168949 -0.79330997 -0.47347168 0.08786368 -2.10859995
[73] 1.48144437 -0.04256233 -0.26462955 -0.20655692 0.54459956 1.10817386
[79] -0.33214474 0.44469112 0.59018516 -1.07999825 0.29966895 0.34884790
[85] 0.18383592 -0.43633674 1.41515192 0.53136820 -0.09134722 -1.45317036
[91] 2.82205564 -1.62129006 -0.00332294 -0.53181595 1.13159212 -0.14323970
[97] 1.21983828 -1.18511407 0.13723137 -1.23473672
> 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] -2.29398485 -0.06373387 0.72894134 -2.33987300 1.19112951 0.89499837
[7] 1.22088930 1.83133424 1.28148787 0.22043580 -2.49288699 0.98690150
[13] -2.12742756 -1.01147279 1.76839570 1.65411906 0.71849990 0.64966874
[19] 1.17489034 -0.46104850 -0.11667559 -0.92175118 -0.20028077 1.01404066
[25] -0.61770583 0.69218707 -0.44772472 1.34097627 0.01431211 0.77565744
[31] -0.08902253 -0.44444116 0.30390622 -0.87910274 0.36146985 -0.14077647
[37] -0.45355698 1.05492736 1.40383630 -0.46239206 0.27080016 -1.12923686
[43] 0.27804049 -0.78447979 -0.40910507 1.48655244 0.07249288 -0.89694986
[49] 0.46777219 -0.95489189 0.41534955 -0.10105137 1.78696462 -1.40706714
[55] 0.30466228 0.14510752 -0.76498496 -1.53493165 1.54477021 0.65396764
[61] 0.65436413 1.28755633 -0.48305014 1.15091021 -0.29081147 -1.22171620
[67] -0.55306686 0.56168949 -0.79330997 -0.47347168 0.08786368 -2.10859995
[73] 1.48144437 -0.04256233 -0.26462955 -0.20655692 0.54459956 1.10817386
[79] -0.33214474 0.44469112 0.59018516 -1.07999825 0.29966895 0.34884790
[85] 0.18383592 -0.43633674 1.41515192 0.53136820 -0.09134722 -1.45317036
[91] 2.82205564 -1.62129006 -0.00332294 -0.53181595 1.13159212 -0.14323970
[97] 1.21983828 -1.18511407 0.13723137 -1.23473672
> colMin(tmp)
[1] -2.29398485 -0.06373387 0.72894134 -2.33987300 1.19112951 0.89499837
[7] 1.22088930 1.83133424 1.28148787 0.22043580 -2.49288699 0.98690150
[13] -2.12742756 -1.01147279 1.76839570 1.65411906 0.71849990 0.64966874
[19] 1.17489034 -0.46104850 -0.11667559 -0.92175118 -0.20028077 1.01404066
[25] -0.61770583 0.69218707 -0.44772472 1.34097627 0.01431211 0.77565744
[31] -0.08902253 -0.44444116 0.30390622 -0.87910274 0.36146985 -0.14077647
[37] -0.45355698 1.05492736 1.40383630 -0.46239206 0.27080016 -1.12923686
[43] 0.27804049 -0.78447979 -0.40910507 1.48655244 0.07249288 -0.89694986
[49] 0.46777219 -0.95489189 0.41534955 -0.10105137 1.78696462 -1.40706714
[55] 0.30466228 0.14510752 -0.76498496 -1.53493165 1.54477021 0.65396764
[61] 0.65436413 1.28755633 -0.48305014 1.15091021 -0.29081147 -1.22171620
[67] -0.55306686 0.56168949 -0.79330997 -0.47347168 0.08786368 -2.10859995
[73] 1.48144437 -0.04256233 -0.26462955 -0.20655692 0.54459956 1.10817386
[79] -0.33214474 0.44469112 0.59018516 -1.07999825 0.29966895 0.34884790
[85] 0.18383592 -0.43633674 1.41515192 0.53136820 -0.09134722 -1.45317036
[91] 2.82205564 -1.62129006 -0.00332294 -0.53181595 1.13159212 -0.14323970
[97] 1.21983828 -1.18511407 0.13723137 -1.23473672
> colMedians(tmp)
[1] -2.29398485 -0.06373387 0.72894134 -2.33987300 1.19112951 0.89499837
[7] 1.22088930 1.83133424 1.28148787 0.22043580 -2.49288699 0.98690150
[13] -2.12742756 -1.01147279 1.76839570 1.65411906 0.71849990 0.64966874
[19] 1.17489034 -0.46104850 -0.11667559 -0.92175118 -0.20028077 1.01404066
[25] -0.61770583 0.69218707 -0.44772472 1.34097627 0.01431211 0.77565744
[31] -0.08902253 -0.44444116 0.30390622 -0.87910274 0.36146985 -0.14077647
[37] -0.45355698 1.05492736 1.40383630 -0.46239206 0.27080016 -1.12923686
[43] 0.27804049 -0.78447979 -0.40910507 1.48655244 0.07249288 -0.89694986
[49] 0.46777219 -0.95489189 0.41534955 -0.10105137 1.78696462 -1.40706714
[55] 0.30466228 0.14510752 -0.76498496 -1.53493165 1.54477021 0.65396764
[61] 0.65436413 1.28755633 -0.48305014 1.15091021 -0.29081147 -1.22171620
[67] -0.55306686 0.56168949 -0.79330997 -0.47347168 0.08786368 -2.10859995
[73] 1.48144437 -0.04256233 -0.26462955 -0.20655692 0.54459956 1.10817386
[79] -0.33214474 0.44469112 0.59018516 -1.07999825 0.29966895 0.34884790
[85] 0.18383592 -0.43633674 1.41515192 0.53136820 -0.09134722 -1.45317036
[91] 2.82205564 -1.62129006 -0.00332294 -0.53181595 1.13159212 -0.14323970
[97] 1.21983828 -1.18511407 0.13723137 -1.23473672
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -2.293985 -0.06373387 0.7289413 -2.339873 1.19113 0.8949984 1.220889
[2,] -2.293985 -0.06373387 0.7289413 -2.339873 1.19113 0.8949984 1.220889
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.831334 1.281488 0.2204358 -2.492887 0.9869015 -2.127428 -1.011473
[2,] 1.831334 1.281488 0.2204358 -2.492887 0.9869015 -2.127428 -1.011473
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.768396 1.654119 0.7184999 0.6496687 1.17489 -0.4610485 -0.1166756
[2,] 1.768396 1.654119 0.7184999 0.6496687 1.17489 -0.4610485 -0.1166756
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.9217512 -0.2002808 1.014041 -0.6177058 0.6921871 -0.4477247 1.340976
[2,] -0.9217512 -0.2002808 1.014041 -0.6177058 0.6921871 -0.4477247 1.340976
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.01431211 0.7756574 -0.08902253 -0.4444412 0.3039062 -0.8791027 0.3614698
[2,] 0.01431211 0.7756574 -0.08902253 -0.4444412 0.3039062 -0.8791027 0.3614698
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.1407765 -0.453557 1.054927 1.403836 -0.4623921 0.2708002 -1.129237
[2,] -0.1407765 -0.453557 1.054927 1.403836 -0.4623921 0.2708002 -1.129237
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.2780405 -0.7844798 -0.4091051 1.486552 0.07249288 -0.8969499 0.4677722
[2,] 0.2780405 -0.7844798 -0.4091051 1.486552 0.07249288 -0.8969499 0.4677722
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.9548919 0.4153496 -0.1010514 1.786965 -1.407067 0.3046623 0.1451075
[2,] -0.9548919 0.4153496 -0.1010514 1.786965 -1.407067 0.3046623 0.1451075
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.764985 -1.534932 1.54477 0.6539676 0.6543641 1.287556 -0.4830501
[2,] -0.764985 -1.534932 1.54477 0.6539676 0.6543641 1.287556 -0.4830501
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 1.15091 -0.2908115 -1.221716 -0.5530669 0.5616895 -0.79331 -0.4734717
[2,] 1.15091 -0.2908115 -1.221716 -0.5530669 0.5616895 -0.79331 -0.4734717
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.08786368 -2.1086 1.481444 -0.04256233 -0.2646295 -0.2065569 0.5445996
[2,] 0.08786368 -2.1086 1.481444 -0.04256233 -0.2646295 -0.2065569 0.5445996
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.108174 -0.3321447 0.4446911 0.5901852 -1.079998 0.2996689 0.3488479
[2,] 1.108174 -0.3321447 0.4446911 0.5901852 -1.079998 0.2996689 0.3488479
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.1838359 -0.4363367 1.415152 0.5313682 -0.09134722 -1.45317 2.822056
[2,] 0.1838359 -0.4363367 1.415152 0.5313682 -0.09134722 -1.45317 2.822056
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.62129 -0.00332294 -0.5318159 1.131592 -0.1432397 1.219838 -1.185114
[2,] -1.62129 -0.00332294 -0.5318159 1.131592 -0.1432397 1.219838 -1.185114
[,99] [,100]
[1,] 0.1372314 -1.234737
[2,] 0.1372314 -1.234737
>
>
> Max(tmp2)
[1] 2.086103
> Min(tmp2)
[1] -3.076678
> mean(tmp2)
[1] -0.1418059
> Sum(tmp2)
[1] -14.18059
> Var(tmp2)
[1] 0.8802007
>
> rowMeans(tmp2)
[1] -0.28501868 0.47948137 0.87857595 0.34128777 -2.44225906 1.24409457
[7] 0.84015111 1.08312635 -1.71945479 -0.28609324 0.37051113 -0.68576434
[13] 0.54413531 -1.11291539 -0.39990723 -1.03453365 -0.07029947 -0.77922803
[19] -0.09815984 0.25008948 -0.85961031 1.58986738 0.35645388 0.54407725
[25] -0.21496416 0.17765613 1.76985399 0.12236409 0.45578388 -0.60797467
[31] 0.98916850 -1.28644157 0.31615665 -0.10729415 2.00749978 -1.95200982
[37] -0.10880713 0.16623252 -0.81184936 -0.97374070 0.41751630 -2.40125091
[43] -0.45943705 -0.48829812 0.34155481 -0.70671506 0.31196112 -1.22348169
[49] 0.24614907 -0.30308651 1.22904090 -0.01754509 -0.46072526 -0.75210353
[55] -0.47823288 -2.02910257 -0.79765999 0.92409306 -1.13831068 2.08610282
[61] -0.07171931 -1.00674581 -0.83766042 0.09494260 -0.42508328 -0.85537589
[67] 0.62802618 -0.98554142 -0.89002271 1.76736479 -1.39142839 -0.11515637
[73] 0.23313597 -0.03019055 0.48112453 -3.07667793 -0.12511011 1.36739413
[79] -0.82833151 -0.49932274 -0.01095936 0.43260076 -0.16860069 0.85303512
[85] -0.42725268 -0.34051922 -0.65142410 1.42585933 -0.08851861 -0.08026622
[91] 0.55083288 0.07069194 0.36357626 -0.86473650 -0.31997654 0.45261900
[97] -0.48025020 -0.40665059 -1.06804872 0.15306646
> rowSums(tmp2)
[1] -0.28501868 0.47948137 0.87857595 0.34128777 -2.44225906 1.24409457
[7] 0.84015111 1.08312635 -1.71945479 -0.28609324 0.37051113 -0.68576434
[13] 0.54413531 -1.11291539 -0.39990723 -1.03453365 -0.07029947 -0.77922803
[19] -0.09815984 0.25008948 -0.85961031 1.58986738 0.35645388 0.54407725
[25] -0.21496416 0.17765613 1.76985399 0.12236409 0.45578388 -0.60797467
[31] 0.98916850 -1.28644157 0.31615665 -0.10729415 2.00749978 -1.95200982
[37] -0.10880713 0.16623252 -0.81184936 -0.97374070 0.41751630 -2.40125091
[43] -0.45943705 -0.48829812 0.34155481 -0.70671506 0.31196112 -1.22348169
[49] 0.24614907 -0.30308651 1.22904090 -0.01754509 -0.46072526 -0.75210353
[55] -0.47823288 -2.02910257 -0.79765999 0.92409306 -1.13831068 2.08610282
[61] -0.07171931 -1.00674581 -0.83766042 0.09494260 -0.42508328 -0.85537589
[67] 0.62802618 -0.98554142 -0.89002271 1.76736479 -1.39142839 -0.11515637
[73] 0.23313597 -0.03019055 0.48112453 -3.07667793 -0.12511011 1.36739413
[79] -0.82833151 -0.49932274 -0.01095936 0.43260076 -0.16860069 0.85303512
[85] -0.42725268 -0.34051922 -0.65142410 1.42585933 -0.08851861 -0.08026622
[91] 0.55083288 0.07069194 0.36357626 -0.86473650 -0.31997654 0.45261900
[97] -0.48025020 -0.40665059 -1.06804872 0.15306646
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] -0.28501868 0.47948137 0.87857595 0.34128777 -2.44225906 1.24409457
[7] 0.84015111 1.08312635 -1.71945479 -0.28609324 0.37051113 -0.68576434
[13] 0.54413531 -1.11291539 -0.39990723 -1.03453365 -0.07029947 -0.77922803
[19] -0.09815984 0.25008948 -0.85961031 1.58986738 0.35645388 0.54407725
[25] -0.21496416 0.17765613 1.76985399 0.12236409 0.45578388 -0.60797467
[31] 0.98916850 -1.28644157 0.31615665 -0.10729415 2.00749978 -1.95200982
[37] -0.10880713 0.16623252 -0.81184936 -0.97374070 0.41751630 -2.40125091
[43] -0.45943705 -0.48829812 0.34155481 -0.70671506 0.31196112 -1.22348169
[49] 0.24614907 -0.30308651 1.22904090 -0.01754509 -0.46072526 -0.75210353
[55] -0.47823288 -2.02910257 -0.79765999 0.92409306 -1.13831068 2.08610282
[61] -0.07171931 -1.00674581 -0.83766042 0.09494260 -0.42508328 -0.85537589
[67] 0.62802618 -0.98554142 -0.89002271 1.76736479 -1.39142839 -0.11515637
[73] 0.23313597 -0.03019055 0.48112453 -3.07667793 -0.12511011 1.36739413
[79] -0.82833151 -0.49932274 -0.01095936 0.43260076 -0.16860069 0.85303512
[85] -0.42725268 -0.34051922 -0.65142410 1.42585933 -0.08851861 -0.08026622
[91] 0.55083288 0.07069194 0.36357626 -0.86473650 -0.31997654 0.45261900
[97] -0.48025020 -0.40665059 -1.06804872 0.15306646
> rowMin(tmp2)
[1] -0.28501868 0.47948137 0.87857595 0.34128777 -2.44225906 1.24409457
[7] 0.84015111 1.08312635 -1.71945479 -0.28609324 0.37051113 -0.68576434
[13] 0.54413531 -1.11291539 -0.39990723 -1.03453365 -0.07029947 -0.77922803
[19] -0.09815984 0.25008948 -0.85961031 1.58986738 0.35645388 0.54407725
[25] -0.21496416 0.17765613 1.76985399 0.12236409 0.45578388 -0.60797467
[31] 0.98916850 -1.28644157 0.31615665 -0.10729415 2.00749978 -1.95200982
[37] -0.10880713 0.16623252 -0.81184936 -0.97374070 0.41751630 -2.40125091
[43] -0.45943705 -0.48829812 0.34155481 -0.70671506 0.31196112 -1.22348169
[49] 0.24614907 -0.30308651 1.22904090 -0.01754509 -0.46072526 -0.75210353
[55] -0.47823288 -2.02910257 -0.79765999 0.92409306 -1.13831068 2.08610282
[61] -0.07171931 -1.00674581 -0.83766042 0.09494260 -0.42508328 -0.85537589
[67] 0.62802618 -0.98554142 -0.89002271 1.76736479 -1.39142839 -0.11515637
[73] 0.23313597 -0.03019055 0.48112453 -3.07667793 -0.12511011 1.36739413
[79] -0.82833151 -0.49932274 -0.01095936 0.43260076 -0.16860069 0.85303512
[85] -0.42725268 -0.34051922 -0.65142410 1.42585933 -0.08851861 -0.08026622
[91] 0.55083288 0.07069194 0.36357626 -0.86473650 -0.31997654 0.45261900
[97] -0.48025020 -0.40665059 -1.06804872 0.15306646
>
> colMeans(tmp2)
[1] -0.1418059
> colSums(tmp2)
[1] -14.18059
> colVars(tmp2)
[1] 0.8802007
> colSd(tmp2)
[1] 0.9381901
> colMax(tmp2)
[1] 2.086103
> colMin(tmp2)
[1] -3.076678
> colMedians(tmp2)
[1] -0.1080506
> colRanges(tmp2)
[,1]
[1,] -3.076678
[2,] 2.086103
>
> 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] -1.64574178 2.70448759 -4.86894579 0.07977272 -3.13376018 -2.86387218
[7] 1.81682061 1.35303405 -1.80175798 -0.92572307
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8775338
[2,] -0.2018005
[3,] -0.1049020
[4,] 0.4748409
[5,] 0.6764634
>
> rowApply(tmp,sum)
[1] -2.4213855 -3.9489520 -0.7148956 -1.7276734 2.7946215 -1.7708809
[7] -0.2868639 -1.1473023 0.3909943 -0.4533482
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 4 5 9 3 9 7 7 1 5
[2,] 6 8 10 2 9 2 10 2 8 10
[3,] 7 1 9 7 6 5 1 1 2 2
[4,] 10 9 7 1 1 10 8 3 4 7
[5,] 3 7 8 4 2 7 9 4 3 4
[6,] 2 3 4 5 8 6 5 6 5 1
[7,] 8 5 2 6 7 4 2 10 9 9
[8,] 1 10 1 10 5 8 4 9 6 8
[9,] 4 6 6 8 10 1 6 5 7 6
[10,] 9 2 3 3 4 3 3 8 10 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.3323767729 -0.5165027153 2.5227593258 0.3618066576 -0.8711142105
[6] -2.6271665575 -1.4903903137 -3.3839428841 -1.7674616238 -2.2231027349
[11] -1.8030546493 -1.4423946269 1.1193023750 -0.0004215632 0.5501104335
[16] 1.9174617273 -0.4048783861 2.7622284931 -3.4543438177 -3.3960720221
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1119460
[2,] -0.5968085
[3,] -0.1061362
[4,] 0.4896730
[5,] 1.6575944
>
> rowApply(tmp,sum)
[1] -2.912188 4.748206 -4.851297 -1.919930 -8.879591
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 20 4 16 12 3
[2,] 12 12 8 5 17
[3,] 14 8 20 16 16
[4,] 6 16 7 20 6
[5,] 9 9 15 13 2
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.6575944 -0.08724728 0.07185386 -0.4359326 -0.3166426 -1.6550448
[2,] -0.5968085 0.49059650 0.06706589 0.9730622 0.1051912 1.1239403
[3,] 0.4896730 -0.55546456 1.83091126 -0.6810176 0.3399156 -1.3797245
[4,] -0.1061362 -0.66721857 0.57278048 1.4852803 0.3370772 -0.1840960
[5,] -1.1119460 0.30283119 -0.01985217 -0.9795856 -1.3366556 -0.5322417
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.41971446 -1.6218300 0.7588185 -0.34241498 -0.5495918 0.3357793
[2,] -0.56354998 -0.0430211 -1.2351195 1.28556666 0.1495986 -0.7767074
[3,] 0.05574648 -0.7843174 -1.6787051 -0.01566368 -0.2036884 -0.3680527
[4,] 0.52375416 -0.3202681 1.4101689 -2.52940240 -0.3896766 -1.1524838
[5,] -0.08662652 -0.6145063 -1.0226244 -0.62118833 -0.8096964 0.5190700
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.5271972 0.66590305 0.7094489 -0.1824590 -0.4106173 0.6942046
[2,] 0.6822764 -0.73377076 0.5718252 1.9504409 -0.5146252 1.0187064
[3,] -1.3100088 -0.07485145 0.6414289 0.9597237 -0.4139375 0.8711795
[4,] 1.1683768 1.04383211 -0.3180157 -0.2543818 -0.2484997 0.4131763
[5,] 1.1058552 -0.90153451 -1.0545769 -0.5558621 1.1828014 -0.2350383
[,19] [,20]
[1,] -0.0274530 -0.2296455
[2,] 0.5612958 0.2322428
[3,] -0.7573582 -1.8170859
[4,] -1.6393431 -1.0648545
[5,] -1.5914853 -0.5167290
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.16-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-3.16-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-3.16-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-3.16-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 0.5275382 0.7963622 -0.3636468 0.7871186 -0.1362482 -0.3804809 0.02695642
col8 col9 col10 col11 col12 col13 col14
row1 0.4957004 -0.1213287 -0.1534587 0.1345878 1.368665 0.5201636 -0.8606943
col15 col16 col17 col18 col19 col20
row1 -0.6624096 1.401834 -0.03446318 -2.22575 1.120212 0.4527283
> tmp[,"col10"]
col10
row1 -0.1534587
row2 0.9871983
row3 0.1468037
row4 -1.1720923
row5 0.4154686
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.52753820 0.7963622 -0.3636468 0.7871186 -0.1362482 -0.3804809
row5 -0.07745503 -1.8991005 -0.5309208 1.0024419 -0.3968450 0.7607392
col7 col8 col9 col10 col11 col12 col13
row1 0.02695642 0.4957004 -0.1213287 -0.1534587 0.1345878 1.368665 0.5201636
row5 0.35993367 1.8176391 0.8771015 0.4154686 -1.1252005 -1.845296 -0.8597593
col14 col15 col16 col17 col18 col19
row1 -0.8606943 -0.6624096 1.4018339 -0.03446318 -2.225750 1.12021231
row5 0.7642779 -0.8249638 0.2677119 -0.61648145 -2.176733 0.05938362
col20
row1 0.4527283
row5 -0.2525177
> tmp[,c("col6","col20")]
col6 col20
row1 -0.380480877 0.4527283
row2 0.003943092 -1.2015461
row3 -1.591938014 0.9041334
row4 -0.452415236 -0.5539976
row5 0.760739195 -0.2525177
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.3804809 0.4527283
row5 0.7607392 -0.2525177
>
>
>
>
> 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 48.63492 50.91937 49.77884 51.31591 50.5719 105.9148 49.27295 49.90226
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.30547 51.29037 49.63152 48.1664 51.75081 50.29604 49.39017 50.15189
col17 col18 col19 col20
row1 49.27989 48.44918 50.68361 105.8797
> tmp[,"col10"]
col10
row1 51.29037
row2 29.25341
row3 29.59805
row4 30.47362
row5 50.74549
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.63492 50.91937 49.77884 51.31591 50.57190 105.9148 49.27295 49.90226
row5 48.79222 50.08647 50.46709 50.32070 49.48974 104.6730 47.70184 51.00178
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.30547 51.29037 49.63152 48.16640 51.75081 50.29604 49.39017 50.15189
row5 51.39168 50.74549 50.66247 50.63554 49.61625 51.06199 50.74084 50.21975
col17 col18 col19 col20
row1 49.27989 48.44918 50.68361 105.8797
row5 51.43661 49.31311 51.58061 104.7694
> tmp[,c("col6","col20")]
col6 col20
row1 105.91481 105.87968
row2 75.33252 75.57750
row3 73.26407 75.11375
row4 73.32577 74.79257
row5 104.67297 104.76941
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.9148 105.8797
row5 104.6730 104.7694
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.9148 105.8797
row5 104.6730 104.7694
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.72727774
[2,] -2.14467417
[3,] -1.22597861
[4,] -0.34128684
[5,] 0.08924229
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.8520689 0.6162731
[2,] -0.9034236 1.0370901
[3,] -0.8300349 -0.2404026
[4,] 0.1759477 -1.0082700
[5,] 1.0019575 -0.7219563
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.0611959 -1.69923709
[2,] 0.7792572 0.04253195
[3,] 0.2461811 -0.75571257
[4,] -0.5689546 2.01420536
[5,] -0.3379242 0.25913816
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.061196
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.0611959
[2,] 0.7792572
>
>
>
> 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 -0.2662524 0.04368194 0.7469249 0.15773539 -0.4097168 -1.055098 -1.129942
row1 -2.0213311 0.14354567 1.4843671 0.08191703 0.7605243 1.083542 1.078775
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -1.429739 0.04213796 -0.5951278 0.01945607 1.6753192 0.1598279
row1 1.011421 -0.10561773 0.3284162 -0.14184385 0.1119739 -1.1258848
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 0.9522855 0.4111701 -1.7535457 -0.2089844 0.9920628 -1.882661 0.3598216
row1 0.2620410 -0.5814269 0.7482123 -0.9546981 -1.0844419 3.017733 0.1899054
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.137074 0.8584987 0.3480136 -0.9000065 0.2240043 -2.043939 0.9463576
[,8] [,9] [,10]
row2 0.8275182 -0.1573261 0.9952898
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.09474 -0.7245323 -0.1109607 -1.02987 0.2896883 0.4215385 -0.1490782
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.5823595 1.036447 -0.5058636 -0.3636589 0.7763065 0.5427279 1.932613
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.6740161 0.7687233 -0.4348615 0.3165725 -0.4693568 -0.9033428
>
>
> 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: 0x564e4734ccf0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM25894d13e29266"
[2] "/home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM25894d7b05e293"
[3] "/home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM25894d4319d27b"
[4] "/home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM25894d598351e9"
[5] "/home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM25894d28dc7451"
[6] "/home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM25894d3be034dc"
[7] "/home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM25894d1fc6a6a7"
[8] "/home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM25894d7be7f425"
[9] "/home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM25894d10cc2932"
[10] "/home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM25894d3951d15e"
[11] "/home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM25894d5a33e172"
[12] "/home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM25894d63b1acc3"
[13] "/home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM25894d25e53677"
[14] "/home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM25894d387b64ab"
[15] "/home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests/BM25894d19564c5e"
>
>
> ### 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: 0x564e47faa800>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x564e47faa800>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.16-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x564e47faa800>
> rowMedians(tmp)
[1] 0.047663843 -0.276205796 0.371263016 0.575084195 -0.196516838
[6] -0.704484536 -0.431982415 0.169267243 0.479658609 0.160188435
[11] -0.340145765 0.017065836 -0.446150355 -0.019544778 -0.072819769
[16] -0.006114917 0.286125180 -0.043521382 0.058788538 -0.104481769
[21] 0.297910664 0.106259837 -0.071137655 0.028430873 -0.057150978
[26] -0.008262095 -0.116887605 0.423476736 -0.398850812 0.582360818
[31] 0.237660075 0.098949535 -0.094140439 0.320259918 0.010355863
[36] -0.419732927 0.054254277 -0.202867982 -0.630991643 0.066956339
[41] 0.481913310 0.014528535 0.255289297 -0.027805936 0.243199067
[46] -0.095947727 -0.015036939 -0.079324659 0.170894277 0.329242566
[51] 0.344680027 -0.599671108 0.493837336 0.079276468 0.506833522
[56] -0.589115138 0.285901980 -0.525106858 -0.529745485 0.337231263
[61] -0.016397120 0.035766425 0.271189444 -0.687745079 -0.146396385
[66] -0.018646115 0.297085562 0.515881385 0.544989638 -0.412661950
[71] -0.467620016 0.008206551 -0.166331879 -0.389533910 -0.773127790
[76] 0.024255996 0.028043346 -0.064542804 0.098187055 -0.320390963
[81] -0.082053352 0.301811169 0.231471490 0.120250061 0.107884074
[86] -0.275309755 -0.388371308 0.210566882 -0.708204669 0.251249936
[91] -0.058697391 -0.017428487 -0.082321298 0.161074169 -0.292227110
[96] 0.183423539 0.193212776 0.742654679 -0.256349379 0.542063089
[101] -0.284526841 0.720094213 -0.001308810 -0.258688566 0.061478565
[106] -0.019702245 -0.292751378 0.435616466 -0.060891835 0.250441071
[111] -0.329646279 -0.402229157 -0.291377318 -0.314442361 -0.395321584
[116] 0.040867250 0.048546353 -0.599685757 -0.384159014 -0.173478292
[121] -0.044734488 0.334670513 -0.336520907 -0.031222791 -0.231799322
[126] -0.103845724 -0.129156360 -0.093785189 0.357867907 -0.427011732
[131] -0.579990012 0.033499319 -0.110541834 -0.223604860 -0.116303587
[136] -0.319148798 -0.404232890 0.238165516 0.145041876 0.558143657
[141] 0.036375373 0.645108500 -0.382747566 0.508784660 -0.430237366
[146] 0.464658844 0.349881537 0.145965366 0.069607176 0.168427735
[151] -0.281389359 -0.289449254 0.117814788 -0.085008531 -0.233080529
[156] 0.548959876 -0.452591456 -0.687605123 0.326861589 0.171226960
[161] -0.300457595 0.147719320 -0.430174394 0.091439981 -0.430793250
[166] 0.041187532 -0.242927064 -0.258484973 -0.160083295 0.385625712
[171] 0.257661607 -0.401210751 0.143819166 0.240798853 0.135034538
[176] 0.023045419 0.342666561 -0.333573848 0.132669349 -0.132432376
[181] 0.430073631 0.219562138 0.233529542 -0.316463648 -0.651681083
[186] -0.196524091 -0.252034029 0.218298468 -0.276160780 -0.013209619
[191] 0.176543642 -0.248234331 -0.075823501 0.263135722 0.645007862
[196] -0.243320262 -0.170923746 -0.093744793 0.364668180 0.263738515
[201] 0.604826031 -0.224700519 -0.319669663 0.280494072 0.163965621
[206] -0.265831202 -0.273663349 0.034428784 -0.067112090 0.188762984
[211] -0.274624031 -0.072900328 0.381968021 0.139748207 0.687904861
[216] -0.142700476 -0.029768046 -0.084222246 -0.372916278 -0.117170259
[221] -0.002649165 -0.444231597 -0.105282266 0.379337599 0.099503920
[226] -0.298011613 -0.194955589 -0.270919203 0.239829793 0.140173115
>
> proc.time()
user system elapsed
1.471 0.578 2.039
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.2.3 (2023-03-15) -- "Shortstop Beagle"
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: 0x563aad3a6400>
> .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: 0x563aad3a6400>
> .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: 0x563aad3a6400>
> .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: 0x563aad3a6400>
> 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: 0x563aad3f19d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x563aad3f19d0>
> .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: 0x563aad3f19d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x563aad3f19d0>
> .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: 0x563aad3f19d0>
> 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: 0x563aac22b450>
> .Call("R_bm_AddColumn",P)
<pointer: 0x563aac22b450>
> .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: 0x563aac22b450>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x563aac22b450>
> .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: 0x563aac22b450>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x563aac22b450>
> .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: 0x563aac22b450>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x563aac22b450>
> .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: 0x563aac22b450>
> 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: 0x563aabbd0dc0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x563aabbd0dc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x563aabbd0dc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x563aabbd0dc0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile258c433b800083" "BufferedMatrixFile258c435930cb37"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile258c433b800083" "BufferedMatrixFile258c435930cb37"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x563aad0cede0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x563aad0cede0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x563aad0cede0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x563aad0cede0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x563aad0cede0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x563aad0cede0>
> .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: 0x563aab4092c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x563aab4092c0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x563aab4092c0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x563aab4092c0>
> 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: 0x563aab408920>
> .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: 0x563aab408920>
> rm(P)
>
> proc.time()
user system elapsed
0.313 0.048 0.345
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.2.3 (2023-03-15) -- "Shortstop Beagle"
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
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.290 0.038 0.311