| Back to Multiple platform build/check report for BioC 3.13 |
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This page was generated on 2021-10-15 15:05:36 -0400 (Fri, 15 Oct 2021).
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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? here for more information. - Make sure to use the following settings in order to reproduce any error or warning you see on this page. |
| Package 220/2041 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.56.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 20.04.2 LTS) / x86_64 | OK | OK | OK |  | ||||||||
| tokay2 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||||
| machv2 | macOS 10.14.6 Mojave / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| Package: BufferedMatrix |
| Version: 1.56.0 |
| Command: /home/biocbuild/bbs-3.13-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.13-bioc/R/library --no-vignettes --timings BufferedMatrix_1.56.0.tar.gz |
| StartedAt: 2021-10-14 09:06:27 -0400 (Thu, 14 Oct 2021) |
| EndedAt: 2021-10-14 09:06:48 -0400 (Thu, 14 Oct 2021) |
| EllapsedTime: 21.2 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.13-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.13-bioc/R/library --no-vignettes --timings BufferedMatrix_1.56.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck’ * using R version 4.1.1 (2021-08-10) * using platform: x86_64-pc-linux-gnu (64-bit) * using session charset: UTF-8 * using option ‘--no-vignettes’ * checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK * this is package ‘BufferedMatrix’ version ‘1.56.0’ * 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 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 ... SKIPPED * checking re-building of vignette outputs ... SKIPPED * checking PDF version of manual ... OK * DONE Status: 2 NOTEs See ‘/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/00check.log’ for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.13-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.13-bioc/R/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
gcc -I"/home/biocbuild/bbs-3.13-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.13-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-3.13-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-3.13-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-3.13-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-3.13-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.13-bioc/R/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 4.1.1 (2021-08-10) -- "Kick Things"
Copyright (C) 2021 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
0.301 0.049 0.335
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.1.1 (2021-08-10) -- "Kick Things"
Copyright (C) 2021 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-3.13-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 440595 23.6 931294 49.8 655097 35.0
Vcells 793405 6.1 8388608 64.0 2013076 15.4
>
>
>
>
> ##
> ## 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] "Thu Oct 14 09:06:43 2021"
> 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] "Thu Oct 14 09:06:43 2021"
>
>
> 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: 0x55d103cb7e40>
>
>
>
> 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] "Thu Oct 14 09:06:43 2021"
> 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] "Thu Oct 14 09:06:43 2021"
>
> ColMode(tmp2)
<pointer: 0x55d103cb7e40>
>
>
>
> ### 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,] 99.43739012 -0.9044897 0.7601256 0.4686092
[2,] 2.43657911 0.1635811 0.3447145 -0.3715492
[3,] 0.61521453 -0.6123723 0.8329995 0.7072454
[4,] -0.03330469 -1.7402938 -0.1635472 -0.5268385
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.13-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,] 99.43739012 0.9044897 0.7601256 0.4686092
[2,] 2.43657911 0.1635811 0.3447145 0.3715492
[3,] 0.61521453 0.6123723 0.8329995 0.7072454
[4,] 0.03330469 1.7402938 0.1635472 0.5268385
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.13-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,] 9.9718298 0.9510467 0.8718518 0.6845504
[2,] 1.5609546 0.4044516 0.5871239 0.6095484
[3,] 0.7843561 0.7825422 0.9126881 0.8409788
[4,] 0.1824957 1.3192019 0.4044097 0.7258364
>
> 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-3.13-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,] 224.15569 35.41496 34.47864 32.31411
[2,] 43.04612 29.20810 31.21595 31.46703
[3,] 33.45878 33.43779 34.95988 34.11703
[4,] 26.85826 39.93231 29.20764 32.78520
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x55d103ae26c0>
> exp(tmp5)
<pointer: 0x55d103ae26c0>
> log(tmp5,2)
<pointer: 0x55d103ae26c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.5507
> Min(tmp5)
[1] 53.20633
> mean(tmp5)
[1] 72.51536
> Sum(tmp5)
[1] 14503.07
> Var(tmp5)
[1] 852.1671
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 88.36519 70.04716 72.47162 68.82515 70.08721 74.10720 71.49521 69.72570
[9] 70.58348 69.44564
> rowSums(tmp5)
[1] 1767.304 1400.943 1449.432 1376.503 1401.744 1482.144 1429.904 1394.514
[9] 1411.670 1388.913
> rowVars(tmp5)
[1] 7941.53776 66.31001 120.22386 91.71570 97.90684 67.27634
[7] 52.60509 63.26214 42.20003 65.09449
> rowSd(tmp5)
[1] 89.115306 8.143096 10.964664 9.576832 9.894788 8.202215 7.252937
[8] 7.953750 6.496155 8.068116
> rowMax(tmp5)
[1] 466.55070 89.59487 94.17639 90.28322 90.45060 86.79382 84.54782
[8] 81.65888 79.28092 81.23311
> rowMin(tmp5)
[1] 57.98376 59.21162 53.20633 55.90195 53.83445 59.34405 58.41608 53.29001
[9] 58.56120 55.20532
>
> colMeans(tmp5)
[1] 111.81794 69.23337 71.22219 69.04613 67.25820 71.21062 71.70555
[8] 66.14220 69.77010 72.87527 68.43763 71.69380 70.80322 72.55569
[15] 68.25656 73.96470 70.93454 68.53534 71.24800 73.59608
> colSums(tmp5)
[1] 1118.1794 692.3337 712.2219 690.4613 672.5820 712.1062 717.0555
[8] 661.4220 697.7010 728.7527 684.3763 716.9380 708.0322 725.5569
[15] 682.5656 739.6470 709.3454 685.3534 712.4800 735.9608
> colVars(tmp5)
[1] 15635.43907 95.76294 103.58491 37.81610 84.18409 37.28136
[7] 37.55127 81.78272 48.56178 41.57290 43.80562 119.76228
[13] 24.85968 79.71518 38.18518 53.16697 73.78438 80.67097
[19] 79.13369 146.80775
> colSd(tmp5)
[1] 125.041749 9.785854 10.177667 6.149480 9.175189 6.105847
[7] 6.127909 9.043380 6.968628 6.447705 6.618581 10.943596
[13] 4.985948 8.928336 6.179416 7.291569 8.589784 8.981702
[19] 8.895712 12.116425
> colMax(tmp5)
[1] 466.55070 83.11388 84.42789 79.47249 86.79382 78.40277 82.02174
[8] 79.88899 80.60967 84.54782 84.03036 91.99264 79.53532 90.28322
[15] 78.72760 90.45060 86.50331 81.01130 90.30506 94.17639
> colMin(tmp5)
[1] 55.90195 53.83445 54.61834 57.52990 55.20532 58.84592 64.33219 53.29001
[9] 57.98376 64.35505 61.22054 55.47569 65.13363 61.33062 58.70340 65.02846
[17] 57.57988 53.20633 57.63737 56.89412
>
>
> ### 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] 88.36519 70.04716 72.47162 68.82515 70.08721 74.10720 71.49521 NA
[9] 70.58348 69.44564
> rowSums(tmp5)
[1] 1767.304 1400.943 1449.432 1376.503 1401.744 1482.144 1429.904 NA
[9] 1411.670 1388.913
> rowVars(tmp5)
[1] 7941.53776 66.31001 120.22386 91.71570 97.90684 67.27634
[7] 52.60509 65.03895 42.20003 65.09449
> rowSd(tmp5)
[1] 89.115306 8.143096 10.964664 9.576832 9.894788 8.202215 7.252937
[8] 8.064673 6.496155 8.068116
> rowMax(tmp5)
[1] 466.55070 89.59487 94.17639 90.28322 90.45060 86.79382 84.54782
[8] NA 79.28092 81.23311
> rowMin(tmp5)
[1] 57.98376 59.21162 53.20633 55.90195 53.83445 59.34405 58.41608 NA
[9] 58.56120 55.20532
>
> colMeans(tmp5)
[1] 111.81794 69.23337 71.22219 69.04613 NA 71.21062 71.70555
[8] 66.14220 69.77010 72.87527 68.43763 71.69380 70.80322 72.55569
[15] 68.25656 73.96470 70.93454 68.53534 71.24800 73.59608
> colSums(tmp5)
[1] 1118.1794 692.3337 712.2219 690.4613 NA 712.1062 717.0555
[8] 661.4220 697.7010 728.7527 684.3763 716.9380 708.0322 725.5569
[15] 682.5656 739.6470 709.3454 685.3534 712.4800 735.9608
> colVars(tmp5)
[1] 15635.43907 95.76294 103.58491 37.81610 NA 37.28136
[7] 37.55127 81.78272 48.56178 41.57290 43.80562 119.76228
[13] 24.85968 79.71518 38.18518 53.16697 73.78438 80.67097
[19] 79.13369 146.80775
> colSd(tmp5)
[1] 125.041749 9.785854 10.177667 6.149480 NA 6.105847
[7] 6.127909 9.043380 6.968628 6.447705 6.618581 10.943596
[13] 4.985948 8.928336 6.179416 7.291569 8.589784 8.981702
[19] 8.895712 12.116425
> colMax(tmp5)
[1] 466.55070 83.11388 84.42789 79.47249 NA 78.40277 82.02174
[8] 79.88899 80.60967 84.54782 84.03036 91.99264 79.53532 90.28322
[15] 78.72760 90.45060 86.50331 81.01130 90.30506 94.17639
> colMin(tmp5)
[1] 55.90195 53.83445 54.61834 57.52990 NA 58.84592 64.33219 53.29001
[9] 57.98376 64.35505 61.22054 55.47569 65.13363 61.33062 58.70340 65.02846
[17] 57.57988 53.20633 57.63737 56.89412
>
> Max(tmp5,na.rm=TRUE)
[1] 466.5507
> Min(tmp5,na.rm=TRUE)
[1] 53.20633
> mean(tmp5,na.rm=TRUE)
[1] 72.55677
> Sum(tmp5,na.rm=TRUE)
[1] 14438.8
> Var(tmp5,na.rm=TRUE)
[1] 856.1262
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.36519 70.04716 72.47162 68.82515 70.08721 74.10720 71.49521 70.01260
[9] 70.58348 69.44564
> rowSums(tmp5,na.rm=TRUE)
[1] 1767.304 1400.943 1449.432 1376.503 1401.744 1482.144 1429.904 1330.239
[9] 1411.670 1388.913
> rowVars(tmp5,na.rm=TRUE)
[1] 7941.53776 66.31001 120.22386 91.71570 97.90684 67.27634
[7] 52.60509 65.03895 42.20003 65.09449
> rowSd(tmp5,na.rm=TRUE)
[1] 89.115306 8.143096 10.964664 9.576832 9.894788 8.202215 7.252937
[8] 8.064673 6.496155 8.068116
> rowMax(tmp5,na.rm=TRUE)
[1] 466.55070 89.59487 94.17639 90.28322 90.45060 86.79382 84.54782
[8] 81.65888 79.28092 81.23311
> rowMin(tmp5,na.rm=TRUE)
[1] 57.98376 59.21162 53.20633 55.90195 53.83445 59.34405 58.41608 53.29001
[9] 58.56120 55.20532
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.81794 69.23337 71.22219 69.04613 67.58972 71.21062 71.70555
[8] 66.14220 69.77010 72.87527 68.43763 71.69380 70.80322 72.55569
[15] 68.25656 73.96470 70.93454 68.53534 71.24800 73.59608
> colSums(tmp5,na.rm=TRUE)
[1] 1118.1794 692.3337 712.2219 690.4613 608.3075 712.1062 717.0555
[8] 661.4220 697.7010 728.7527 684.3763 716.9380 708.0322 725.5569
[15] 682.5656 739.6470 709.3454 685.3534 712.4800 735.9608
> colVars(tmp5,na.rm=TRUE)
[1] 15635.43907 95.76294 103.58491 37.81610 93.47064 37.28136
[7] 37.55127 81.78272 48.56178 41.57290 43.80562 119.76228
[13] 24.85968 79.71518 38.18518 53.16697 73.78438 80.67097
[19] 79.13369 146.80775
> colSd(tmp5,na.rm=TRUE)
[1] 125.041749 9.785854 10.177667 6.149480 9.668021 6.105847
[7] 6.127909 9.043380 6.968628 6.447705 6.618581 10.943596
[13] 4.985948 8.928336 6.179416 7.291569 8.589784 8.981702
[19] 8.895712 12.116425
> colMax(tmp5,na.rm=TRUE)
[1] 466.55070 83.11388 84.42789 79.47249 86.79382 78.40277 82.02174
[8] 79.88899 80.60967 84.54782 84.03036 91.99264 79.53532 90.28322
[15] 78.72760 90.45060 86.50331 81.01130 90.30506 94.17639
> colMin(tmp5,na.rm=TRUE)
[1] 55.90195 53.83445 54.61834 57.52990 55.20532 58.84592 64.33219 53.29001
[9] 57.98376 64.35505 61.22054 55.47569 65.13363 61.33062 58.70340 65.02846
[17] 57.57988 53.20633 57.63737 56.89412
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.36519 70.04716 72.47162 68.82515 70.08721 74.10720 71.49521 NaN
[9] 70.58348 69.44564
> rowSums(tmp5,na.rm=TRUE)
[1] 1767.304 1400.943 1449.432 1376.503 1401.744 1482.144 1429.904 0.000
[9] 1411.670 1388.913
> rowVars(tmp5,na.rm=TRUE)
[1] 7941.53776 66.31001 120.22386 91.71570 97.90684 67.27634
[7] 52.60509 NA 42.20003 65.09449
> rowSd(tmp5,na.rm=TRUE)
[1] 89.115306 8.143096 10.964664 9.576832 9.894788 8.202215 7.252937
[8] NA 6.496155 8.068116
> rowMax(tmp5,na.rm=TRUE)
[1] 466.55070 89.59487 94.17639 90.28322 90.45060 86.79382 84.54782
[8] NA 79.28092 81.23311
> rowMin(tmp5,na.rm=TRUE)
[1] 57.98376 59.21162 53.20633 55.90195 53.83445 59.34405 58.41608 NA
[9] 58.56120 55.20532
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.60568 67.85276 73.06706 68.81524 NaN 71.07794 71.93335
[8] 67.57022 68.56570 73.82196 68.86667 71.20738 71.31133 71.96553
[15] 68.30965 74.95761 71.70169 68.00546 71.33285 72.94856
> colSums(tmp5,na.rm=TRUE)
[1] 1040.4511 610.6748 657.6036 619.3372 0.0000 639.7014 647.4002
[8] 608.1319 617.0913 664.3976 619.8001 640.8664 641.8020 647.6897
[15] 614.7869 674.6185 645.3152 612.0492 641.9957 656.5371
> colVars(tmp5,na.rm=TRUE)
[1] 17428.46586 86.28980 78.24304 41.94339 NA 41.74349
[7] 41.66139 69.06409 38.31306 36.68699 47.21045 132.07075
[13] 25.06271 85.76127 42.92661 48.72167 76.38665 87.59614
[19] 88.94440 160.44185
> colSd(tmp5,na.rm=TRUE)
[1] 132.016915 9.289230 8.845510 6.476371 NA 6.460920
[7] 6.454563 8.310481 6.189755 6.056979 6.870986 11.492204
[13] 5.006267 9.260738 6.551841 6.980091 8.739946 9.359281
[19] 9.431034 12.666564
> colMax(tmp5,na.rm=TRUE)
[1] 466.55070 83.11388 84.42789 79.47249 -Inf 78.40277 82.02174
[8] 79.88899 77.53926 84.54782 84.03036 91.99264 79.53532 90.28322
[15] 78.72760 90.45060 86.50331 81.01130 90.30506 94.17639
> colMin(tmp5,na.rm=TRUE)
[1] 55.90195 53.83445 60.79188 57.52990 Inf 58.84592 64.33219 56.47534
[9] 57.98376 65.75810 61.22054 55.47569 65.13363 61.33062 58.70340 69.03547
[17] 57.57988 53.20633 57.63737 56.89412
>
>
>
>
> 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] 132.2004 164.7700 270.1511 218.9274 160.3203 333.7520 231.8513 317.4320
[9] 208.6443 135.7260
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 132.2004 164.7700 270.1511 218.9274 160.3203 333.7520 231.8513 317.4320
[9] 208.6443 135.7260
>
>
>
> 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] 0.000000e+00 2.842171e-14 1.989520e-13 -8.526513e-14 -8.526513e-14
[6] -2.842171e-14 0.000000e+00 7.105427e-14 2.842171e-14 1.136868e-13
[11] -2.842171e-14 0.000000e+00 1.421085e-13 5.684342e-14 5.684342e-14
[16] 0.000000e+00 -2.842171e-14 -8.526513e-14 -1.136868e-13 -1.136868e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
2 1
5 11
3 17
5 16
6 8
6 18
8 13
7 13
6 10
4 5
1 1
4 18
10 19
9 14
3 15
9 16
1 19
9 1
8 7
10 7
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] 2.572171
> Min(tmp)
[1] -2.809493
> mean(tmp)
[1] -0.04838313
> Sum(tmp)
[1] -4.838313
> Var(tmp)
[1] 0.9511432
>
> rowMeans(tmp)
[1] -0.04838313
> rowSums(tmp)
[1] -4.838313
> rowVars(tmp)
[1] 0.9511432
> rowSd(tmp)
[1] 0.9752657
> rowMax(tmp)
[1] 2.572171
> rowMin(tmp)
[1] -2.809493
>
> colMeans(tmp)
[1] 0.15109533 0.33899709 -0.63118516 0.45498771 -0.94225028 -0.53659682
[7] -0.55224161 -0.11038090 -0.10278041 -0.49158193 -0.02851368 0.27899845
[13] -0.31710652 0.41718080 -1.21143310 -0.04265048 -1.42533188 0.08619243
[19] 0.20954010 -0.36876224 -0.38752280 -0.51507749 -0.27332055 -1.33837861
[25] 1.58615435 1.04291718 0.30885884 0.37763977 -1.53169739 -0.28491994
[31] 0.19543538 0.52505444 0.68611977 -1.46509791 -0.45454515 1.97785687
[37] 1.43376772 -0.27314116 -0.03794893 -2.15790528 0.45527049 0.63853125
[43] -0.11762081 0.48073833 0.61022647 0.26758837 -0.59843505 -0.53368330
[49] -0.22031275 -1.02701236 -0.56654000 0.38703112 -0.28422517 0.63597677
[55] 1.02266285 0.94226880 0.46832407 0.78761370 -1.43826195 -1.50503176
[61] -2.13082641 -0.06560649 2.10672184 -0.89355564 -1.18374123 -2.80949292
[67] 0.39172904 -0.03057422 0.39077463 -0.29823891 -1.05670238 0.31232724
[73] 2.57217130 0.42575493 1.47333531 -0.55330915 0.57445383 -1.21385632
[79] 1.61587807 -0.20751716 1.33033102 0.68325467 0.05705096 0.55701380
[85] 1.00901901 -0.54789991 2.01003089 -0.39496969 -0.79798954 -0.03989009
[91] -0.37109453 -0.43248034 -2.23320322 -0.88029243 -0.26907411 -1.66504354
[97] 0.21907935 0.94865451 0.51508676 1.04884335
> colSums(tmp)
[1] 0.15109533 0.33899709 -0.63118516 0.45498771 -0.94225028 -0.53659682
[7] -0.55224161 -0.11038090 -0.10278041 -0.49158193 -0.02851368 0.27899845
[13] -0.31710652 0.41718080 -1.21143310 -0.04265048 -1.42533188 0.08619243
[19] 0.20954010 -0.36876224 -0.38752280 -0.51507749 -0.27332055 -1.33837861
[25] 1.58615435 1.04291718 0.30885884 0.37763977 -1.53169739 -0.28491994
[31] 0.19543538 0.52505444 0.68611977 -1.46509791 -0.45454515 1.97785687
[37] 1.43376772 -0.27314116 -0.03794893 -2.15790528 0.45527049 0.63853125
[43] -0.11762081 0.48073833 0.61022647 0.26758837 -0.59843505 -0.53368330
[49] -0.22031275 -1.02701236 -0.56654000 0.38703112 -0.28422517 0.63597677
[55] 1.02266285 0.94226880 0.46832407 0.78761370 -1.43826195 -1.50503176
[61] -2.13082641 -0.06560649 2.10672184 -0.89355564 -1.18374123 -2.80949292
[67] 0.39172904 -0.03057422 0.39077463 -0.29823891 -1.05670238 0.31232724
[73] 2.57217130 0.42575493 1.47333531 -0.55330915 0.57445383 -1.21385632
[79] 1.61587807 -0.20751716 1.33033102 0.68325467 0.05705096 0.55701380
[85] 1.00901901 -0.54789991 2.01003089 -0.39496969 -0.79798954 -0.03989009
[91] -0.37109453 -0.43248034 -2.23320322 -0.88029243 -0.26907411 -1.66504354
[97] 0.21907935 0.94865451 0.51508676 1.04884335
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] 0.15109533 0.33899709 -0.63118516 0.45498771 -0.94225028 -0.53659682
[7] -0.55224161 -0.11038090 -0.10278041 -0.49158193 -0.02851368 0.27899845
[13] -0.31710652 0.41718080 -1.21143310 -0.04265048 -1.42533188 0.08619243
[19] 0.20954010 -0.36876224 -0.38752280 -0.51507749 -0.27332055 -1.33837861
[25] 1.58615435 1.04291718 0.30885884 0.37763977 -1.53169739 -0.28491994
[31] 0.19543538 0.52505444 0.68611977 -1.46509791 -0.45454515 1.97785687
[37] 1.43376772 -0.27314116 -0.03794893 -2.15790528 0.45527049 0.63853125
[43] -0.11762081 0.48073833 0.61022647 0.26758837 -0.59843505 -0.53368330
[49] -0.22031275 -1.02701236 -0.56654000 0.38703112 -0.28422517 0.63597677
[55] 1.02266285 0.94226880 0.46832407 0.78761370 -1.43826195 -1.50503176
[61] -2.13082641 -0.06560649 2.10672184 -0.89355564 -1.18374123 -2.80949292
[67] 0.39172904 -0.03057422 0.39077463 -0.29823891 -1.05670238 0.31232724
[73] 2.57217130 0.42575493 1.47333531 -0.55330915 0.57445383 -1.21385632
[79] 1.61587807 -0.20751716 1.33033102 0.68325467 0.05705096 0.55701380
[85] 1.00901901 -0.54789991 2.01003089 -0.39496969 -0.79798954 -0.03989009
[91] -0.37109453 -0.43248034 -2.23320322 -0.88029243 -0.26907411 -1.66504354
[97] 0.21907935 0.94865451 0.51508676 1.04884335
> colMin(tmp)
[1] 0.15109533 0.33899709 -0.63118516 0.45498771 -0.94225028 -0.53659682
[7] -0.55224161 -0.11038090 -0.10278041 -0.49158193 -0.02851368 0.27899845
[13] -0.31710652 0.41718080 -1.21143310 -0.04265048 -1.42533188 0.08619243
[19] 0.20954010 -0.36876224 -0.38752280 -0.51507749 -0.27332055 -1.33837861
[25] 1.58615435 1.04291718 0.30885884 0.37763977 -1.53169739 -0.28491994
[31] 0.19543538 0.52505444 0.68611977 -1.46509791 -0.45454515 1.97785687
[37] 1.43376772 -0.27314116 -0.03794893 -2.15790528 0.45527049 0.63853125
[43] -0.11762081 0.48073833 0.61022647 0.26758837 -0.59843505 -0.53368330
[49] -0.22031275 -1.02701236 -0.56654000 0.38703112 -0.28422517 0.63597677
[55] 1.02266285 0.94226880 0.46832407 0.78761370 -1.43826195 -1.50503176
[61] -2.13082641 -0.06560649 2.10672184 -0.89355564 -1.18374123 -2.80949292
[67] 0.39172904 -0.03057422 0.39077463 -0.29823891 -1.05670238 0.31232724
[73] 2.57217130 0.42575493 1.47333531 -0.55330915 0.57445383 -1.21385632
[79] 1.61587807 -0.20751716 1.33033102 0.68325467 0.05705096 0.55701380
[85] 1.00901901 -0.54789991 2.01003089 -0.39496969 -0.79798954 -0.03989009
[91] -0.37109453 -0.43248034 -2.23320322 -0.88029243 -0.26907411 -1.66504354
[97] 0.21907935 0.94865451 0.51508676 1.04884335
> colMedians(tmp)
[1] 0.15109533 0.33899709 -0.63118516 0.45498771 -0.94225028 -0.53659682
[7] -0.55224161 -0.11038090 -0.10278041 -0.49158193 -0.02851368 0.27899845
[13] -0.31710652 0.41718080 -1.21143310 -0.04265048 -1.42533188 0.08619243
[19] 0.20954010 -0.36876224 -0.38752280 -0.51507749 -0.27332055 -1.33837861
[25] 1.58615435 1.04291718 0.30885884 0.37763977 -1.53169739 -0.28491994
[31] 0.19543538 0.52505444 0.68611977 -1.46509791 -0.45454515 1.97785687
[37] 1.43376772 -0.27314116 -0.03794893 -2.15790528 0.45527049 0.63853125
[43] -0.11762081 0.48073833 0.61022647 0.26758837 -0.59843505 -0.53368330
[49] -0.22031275 -1.02701236 -0.56654000 0.38703112 -0.28422517 0.63597677
[55] 1.02266285 0.94226880 0.46832407 0.78761370 -1.43826195 -1.50503176
[61] -2.13082641 -0.06560649 2.10672184 -0.89355564 -1.18374123 -2.80949292
[67] 0.39172904 -0.03057422 0.39077463 -0.29823891 -1.05670238 0.31232724
[73] 2.57217130 0.42575493 1.47333531 -0.55330915 0.57445383 -1.21385632
[79] 1.61587807 -0.20751716 1.33033102 0.68325467 0.05705096 0.55701380
[85] 1.00901901 -0.54789991 2.01003089 -0.39496969 -0.79798954 -0.03989009
[91] -0.37109453 -0.43248034 -2.23320322 -0.88029243 -0.26907411 -1.66504354
[97] 0.21907935 0.94865451 0.51508676 1.04884335
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.1510953 0.3389971 -0.6311852 0.4549877 -0.9422503 -0.5365968 -0.5522416
[2,] 0.1510953 0.3389971 -0.6311852 0.4549877 -0.9422503 -0.5365968 -0.5522416
[,8] [,9] [,10] [,11] [,12] [,13]
[1,] -0.1103809 -0.1027804 -0.4915819 -0.02851368 0.2789985 -0.3171065
[2,] -0.1103809 -0.1027804 -0.4915819 -0.02851368 0.2789985 -0.3171065
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0.4171808 -1.211433 -0.04265048 -1.425332 0.08619243 0.2095401 -0.3687622
[2,] 0.4171808 -1.211433 -0.04265048 -1.425332 0.08619243 0.2095401 -0.3687622
[,21] [,22] [,23] [,24] [,25] [,26] [,27]
[1,] -0.3875228 -0.5150775 -0.2733206 -1.338379 1.586154 1.042917 0.3088588
[2,] -0.3875228 -0.5150775 -0.2733206 -1.338379 1.586154 1.042917 0.3088588
[,28] [,29] [,30] [,31] [,32] [,33] [,34]
[1,] 0.3776398 -1.531697 -0.2849199 0.1954354 0.5250544 0.6861198 -1.465098
[2,] 0.3776398 -1.531697 -0.2849199 0.1954354 0.5250544 0.6861198 -1.465098
[,35] [,36] [,37] [,38] [,39] [,40] [,41]
[1,] -0.4545452 1.977857 1.433768 -0.2731412 -0.03794893 -2.157905 0.4552705
[2,] -0.4545452 1.977857 1.433768 -0.2731412 -0.03794893 -2.157905 0.4552705
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] 0.6385313 -0.1176208 0.4807383 0.6102265 0.2675884 -0.598435 -0.5336833
[2,] 0.6385313 -0.1176208 0.4807383 0.6102265 0.2675884 -0.598435 -0.5336833
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.2203128 -1.027012 -0.56654 0.3870311 -0.2842252 0.6359768 1.022663
[2,] -0.2203128 -1.027012 -0.56654 0.3870311 -0.2842252 0.6359768 1.022663
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] 0.9422688 0.4683241 0.7876137 -1.438262 -1.505032 -2.130826 -0.06560649
[2,] 0.9422688 0.4683241 0.7876137 -1.438262 -1.505032 -2.130826 -0.06560649
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 2.106722 -0.8935556 -1.183741 -2.809493 0.391729 -0.03057422 0.3907746
[2,] 2.106722 -0.8935556 -1.183741 -2.809493 0.391729 -0.03057422 0.3907746
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] -0.2982389 -1.056702 0.3123272 2.572171 0.4257549 1.473335 -0.5533092
[2,] -0.2982389 -1.056702 0.3123272 2.572171 0.4257549 1.473335 -0.5533092
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] 0.5744538 -1.213856 1.615878 -0.2075172 1.330331 0.6832547 0.05705096
[2,] 0.5744538 -1.213856 1.615878 -0.2075172 1.330331 0.6832547 0.05705096
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 0.5570138 1.009019 -0.5478999 2.010031 -0.3949697 -0.7979895 -0.03989009
[2,] 0.5570138 1.009019 -0.5478999 2.010031 -0.3949697 -0.7979895 -0.03989009
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -0.3710945 -0.4324803 -2.233203 -0.8802924 -0.2690741 -1.665044 0.2190793
[2,] -0.3710945 -0.4324803 -2.233203 -0.8802924 -0.2690741 -1.665044 0.2190793
[,98] [,99] [,100]
[1,] 0.9486545 0.5150868 1.048843
[2,] 0.9486545 0.5150868 1.048843
>
>
> Max(tmp2)
[1] 2.178027
> Min(tmp2)
[1] -2.646211
> mean(tmp2)
[1] -0.1805399
> Sum(tmp2)
[1] -18.05399
> Var(tmp2)
[1] 1.321197
>
> rowMeans(tmp2)
[1] -1.74699331 -2.48532783 -0.32307932 0.61959967 0.20324381 1.09115700
[7] -0.75759565 1.25282577 0.12294908 1.67414094 0.15510905 -2.43832199
[13] -0.32568304 -2.27162319 1.29591222 -1.13962239 1.98322369 0.03793058
[19] 1.67051976 0.65151082 -0.09146585 -0.67981015 -1.07879053 -0.59813314
[25] -0.41392073 -0.13749059 -1.04591181 -1.72221591 0.70651324 -0.28636172
[31] 0.52427445 -1.02211774 -0.48819197 -1.20448101 1.17739799 -1.07317799
[37] -0.84478208 0.24955314 -0.79019429 -1.87195669 1.29080028 -2.64621105
[43] 0.37078792 0.87790405 1.18758234 -1.02430015 0.47044986 -0.63172888
[49] 1.78781967 -0.62107983 0.50553906 -0.03757047 -0.10160285 1.57946644
[55] -0.54454706 0.42559387 0.09569717 1.07999791 -2.30352909 1.25142381
[61] 0.93260456 -1.91752465 0.32701738 -1.19392626 -0.59507836 -1.62018585
[67] 2.17041543 -0.90929568 -0.34661478 -1.81383140 0.42267344 -0.69535807
[73] -0.26692183 -0.96864914 -1.11738928 1.41351672 -0.27502382 -0.10206817
[79] -0.77243412 0.76053149 -0.91941510 -1.87375205 -1.56848019 -0.06435102
[85] 0.26405817 1.24748249 -2.49298866 1.00123946 -0.68441680 -0.34985123
[91] 2.17802681 0.53365372 -0.16328533 0.13950282 -1.01212977 -0.77309890
[97] 0.20168230 -0.70319862 -0.11151646 2.07328914
> rowSums(tmp2)
[1] -1.74699331 -2.48532783 -0.32307932 0.61959967 0.20324381 1.09115700
[7] -0.75759565 1.25282577 0.12294908 1.67414094 0.15510905 -2.43832199
[13] -0.32568304 -2.27162319 1.29591222 -1.13962239 1.98322369 0.03793058
[19] 1.67051976 0.65151082 -0.09146585 -0.67981015 -1.07879053 -0.59813314
[25] -0.41392073 -0.13749059 -1.04591181 -1.72221591 0.70651324 -0.28636172
[31] 0.52427445 -1.02211774 -0.48819197 -1.20448101 1.17739799 -1.07317799
[37] -0.84478208 0.24955314 -0.79019429 -1.87195669 1.29080028 -2.64621105
[43] 0.37078792 0.87790405 1.18758234 -1.02430015 0.47044986 -0.63172888
[49] 1.78781967 -0.62107983 0.50553906 -0.03757047 -0.10160285 1.57946644
[55] -0.54454706 0.42559387 0.09569717 1.07999791 -2.30352909 1.25142381
[61] 0.93260456 -1.91752465 0.32701738 -1.19392626 -0.59507836 -1.62018585
[67] 2.17041543 -0.90929568 -0.34661478 -1.81383140 0.42267344 -0.69535807
[73] -0.26692183 -0.96864914 -1.11738928 1.41351672 -0.27502382 -0.10206817
[79] -0.77243412 0.76053149 -0.91941510 -1.87375205 -1.56848019 -0.06435102
[85] 0.26405817 1.24748249 -2.49298866 1.00123946 -0.68441680 -0.34985123
[91] 2.17802681 0.53365372 -0.16328533 0.13950282 -1.01212977 -0.77309890
[97] 0.20168230 -0.70319862 -0.11151646 2.07328914
> 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] -1.74699331 -2.48532783 -0.32307932 0.61959967 0.20324381 1.09115700
[7] -0.75759565 1.25282577 0.12294908 1.67414094 0.15510905 -2.43832199
[13] -0.32568304 -2.27162319 1.29591222 -1.13962239 1.98322369 0.03793058
[19] 1.67051976 0.65151082 -0.09146585 -0.67981015 -1.07879053 -0.59813314
[25] -0.41392073 -0.13749059 -1.04591181 -1.72221591 0.70651324 -0.28636172
[31] 0.52427445 -1.02211774 -0.48819197 -1.20448101 1.17739799 -1.07317799
[37] -0.84478208 0.24955314 -0.79019429 -1.87195669 1.29080028 -2.64621105
[43] 0.37078792 0.87790405 1.18758234 -1.02430015 0.47044986 -0.63172888
[49] 1.78781967 -0.62107983 0.50553906 -0.03757047 -0.10160285 1.57946644
[55] -0.54454706 0.42559387 0.09569717 1.07999791 -2.30352909 1.25142381
[61] 0.93260456 -1.91752465 0.32701738 -1.19392626 -0.59507836 -1.62018585
[67] 2.17041543 -0.90929568 -0.34661478 -1.81383140 0.42267344 -0.69535807
[73] -0.26692183 -0.96864914 -1.11738928 1.41351672 -0.27502382 -0.10206817
[79] -0.77243412 0.76053149 -0.91941510 -1.87375205 -1.56848019 -0.06435102
[85] 0.26405817 1.24748249 -2.49298866 1.00123946 -0.68441680 -0.34985123
[91] 2.17802681 0.53365372 -0.16328533 0.13950282 -1.01212977 -0.77309890
[97] 0.20168230 -0.70319862 -0.11151646 2.07328914
> rowMin(tmp2)
[1] -1.74699331 -2.48532783 -0.32307932 0.61959967 0.20324381 1.09115700
[7] -0.75759565 1.25282577 0.12294908 1.67414094 0.15510905 -2.43832199
[13] -0.32568304 -2.27162319 1.29591222 -1.13962239 1.98322369 0.03793058
[19] 1.67051976 0.65151082 -0.09146585 -0.67981015 -1.07879053 -0.59813314
[25] -0.41392073 -0.13749059 -1.04591181 -1.72221591 0.70651324 -0.28636172
[31] 0.52427445 -1.02211774 -0.48819197 -1.20448101 1.17739799 -1.07317799
[37] -0.84478208 0.24955314 -0.79019429 -1.87195669 1.29080028 -2.64621105
[43] 0.37078792 0.87790405 1.18758234 -1.02430015 0.47044986 -0.63172888
[49] 1.78781967 -0.62107983 0.50553906 -0.03757047 -0.10160285 1.57946644
[55] -0.54454706 0.42559387 0.09569717 1.07999791 -2.30352909 1.25142381
[61] 0.93260456 -1.91752465 0.32701738 -1.19392626 -0.59507836 -1.62018585
[67] 2.17041543 -0.90929568 -0.34661478 -1.81383140 0.42267344 -0.69535807
[73] -0.26692183 -0.96864914 -1.11738928 1.41351672 -0.27502382 -0.10206817
[79] -0.77243412 0.76053149 -0.91941510 -1.87375205 -1.56848019 -0.06435102
[85] 0.26405817 1.24748249 -2.49298866 1.00123946 -0.68441680 -0.34985123
[91] 2.17802681 0.53365372 -0.16328533 0.13950282 -1.01212977 -0.77309890
[97] 0.20168230 -0.70319862 -0.11151646 2.07328914
>
> colMeans(tmp2)
[1] -0.1805399
> colSums(tmp2)
[1] -18.05399
> colVars(tmp2)
[1] 1.321197
> colSd(tmp2)
[1] 1.149434
> colMax(tmp2)
[1] 2.178027
> colMin(tmp2)
[1] -2.646211
> colMedians(tmp2)
[1] -0.2151036
> colRanges(tmp2)
[,1]
[1,] -2.646211
[2,] 2.178027
>
> 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] 3.55009380 0.06034151 3.73709499 -4.87464818 2.42486548 2.65253503
[7] -0.03343562 3.25754348 4.57155243 -2.20057440
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.8888735
[2,] -0.3873603
[3,] 0.7299207
[4,] 1.4435291
[5,] 1.6941795
>
> rowApply(tmp,sum)
[1] 6.4319560 3.3738621 -0.6638741 -2.5947762 3.2793064 0.4501089
[7] 1.7881958 -0.4576040 0.9219704 0.6162233
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 9 7 1 9 9 3 2 10 6
[2,] 8 7 8 2 6 7 6 4 1 3
[3,] 3 6 3 5 8 8 1 8 8 9
[4,] 1 1 5 7 1 1 8 9 5 5
[5,] 7 4 6 8 5 6 5 6 6 4
[6,] 6 2 9 6 3 3 9 10 3 7
[7,] 9 3 2 10 10 4 2 3 4 1
[8,] 2 10 4 3 2 10 10 7 2 8
[9,] 4 8 10 4 4 5 7 5 9 10
[10,] 5 5 1 9 7 2 4 1 7 2
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.5017653 -3.4987488 3.9259644 1.1976719 0.8679631 -3.3206523
[7] -5.3537464 0.4842716 2.7961839 -1.6313869 -2.8066977 -1.4113236
[13] -0.5007665 0.7772251 -1.7623329 -1.1121870 -1.4215954 -1.9155872
[19] -0.2891241 4.1426915
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.9613094
[2,] -0.4385818
[3,] -0.2117638
[4,] 0.6144217
[5,] 1.4989987
>
> rowApply(tmp,sum)
[1] -2.510517 -3.139431 -3.073669 -6.812793 5.205998
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 18 8 15 11 3
[2,] 1 3 3 17 11
[3,] 19 14 17 12 13
[4,] 20 16 9 7 9
[5,] 16 7 11 10 15
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.4989987 -1.7346724 2.0044807 2.2013402 1.1228641 -1.55588176
[2,] -0.4385818 -0.9317799 0.1677095 0.2848347 -0.6372476 0.07106812
[3,] 0.6144217 -1.6591730 1.3156280 -0.7120721 -0.2725655 0.35765378
[4,] -0.2117638 0.3431779 -0.2095057 -0.8388319 -0.2989205 -0.13064682
[5,] -0.9613094 0.4836985 0.6476519 0.2624010 0.9538326 -2.06284565
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.2232730 -0.46229073 0.3279891 -0.4147486 -0.06859623 -0.61964384
[2,] -0.1575605 0.75421009 0.2655082 1.2889239 -0.88542946 -0.01112071
[3,] -2.0618673 -0.92580983 0.3248913 -1.3123435 -1.27351589 -0.36733133
[4,] -1.6782199 -0.01623222 0.8004919 -0.9962428 -1.20578196 -0.53422950
[5,] -0.2328256 1.13439429 1.0773034 -0.1969759 0.62662581 0.12100174
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.1868745 -0.98548201 -1.1146073 -0.8265976 -0.5713149 0.1783142
[2,] -2.3054710 -0.34522411 -1.8715908 -0.8421177 -0.1554023 -0.9111503
[3,] 2.0793405 0.60208871 -2.0348403 1.1170264 -0.7896132 1.3721685
[4,] -0.6136818 -0.09476112 2.4243079 0.7851042 -1.0640775 -1.7755751
[5,] -0.8478286 1.60060364 0.8343976 -1.3456023 1.1588125 -0.7793446
[,19] [,20]
[1,] -0.4802414 -0.9740291
[2,] 2.4436812 1.0773094
[3,] -1.0516643 1.6039086
[4,] -1.6204557 0.1230510
[5,] 0.4195561 2.3124517
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.13-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-3.13-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 653 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.13-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 1.803059 -0.0002182497 0.3519268 -0.3817751 1.441945 0.1073764 0.5453452
col8 col9 col10 col11 col12 col13 col14
row1 1.772046 1.649568 0.5626254 0.05454181 -0.006534198 1.170828 -0.02145208
col15 col16 col17 col18 col19 col20
row1 -0.9837916 1.887737 1.749948 -0.3300696 -1.302355 1.821243
> tmp[,"col10"]
col10
row1 0.56262544
row2 0.02810039
row3 -0.27014737
row4 -1.29809995
row5 1.05577174
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 1.803059 -0.0002182497 0.3519268 -0.38177509 1.4419454 0.1073764
row5 -1.338748 -1.4277300813 -0.1466625 -0.08849856 -0.7550111 0.5504584
col7 col8 col9 col10 col11 col12
row1 0.5453452 1.77204613 1.649568 0.5626254 0.05454181 -0.006534198
row5 -0.3094840 -0.02123464 -1.988322 1.0557717 1.04332212 -1.000653122
col13 col14 col15 col16 col17 col18 col19
row1 1.170828 -0.02145208 -0.9837916 1.8877374 1.7499483 -0.3300696 -1.3023546
row5 1.362583 1.20128119 1.2526583 0.2143699 -0.5025682 -0.4928046 -0.4292016
col20
row1 1.821243
row5 1.000986
> tmp[,c("col6","col20")]
col6 col20
row1 0.1073764 1.8212427
row2 0.8120002 1.1297221
row3 0.7481949 -0.2166020
row4 -0.4413924 0.5302178
row5 0.5504584 1.0009857
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.1073764 1.821243
row5 0.5504584 1.000986
>
>
>
>
> 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 50.04287 50.00645 50.62493 50.32496 51.32943 103.6374 50.59731 49.6091
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.19235 51.02158 48.85125 48.13308 50.47962 48.93378 49.99649 50.46873
col17 col18 col19 col20
row1 50.57401 49.88866 49.57867 104.175
> tmp[,"col10"]
col10
row1 51.02158
row2 32.01850
row3 29.66177
row4 28.99920
row5 48.66793
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.04287 50.00645 50.62493 50.32496 51.32943 103.6374 50.59731 49.60910
row5 48.81994 49.06958 51.28219 49.23796 48.93545 103.0914 48.98176 49.36936
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.19235 51.02158 48.85125 48.13308 50.47962 48.93378 49.99649 50.46873
row5 49.26770 48.66793 49.38705 49.28428 50.94930 49.84772 49.65276 51.07143
col17 col18 col19 col20
row1 50.57401 49.88866 49.57867 104.1750
row5 49.72156 48.01020 49.27346 103.7676
> tmp[,c("col6","col20")]
col6 col20
row1 103.63740 104.17496
row2 76.53713 74.08900
row3 74.84017 74.42741
row4 75.87154 76.77789
row5 103.09137 103.76759
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 103.6374 104.1750
row5 103.0914 103.7676
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 103.6374 104.1750
row5 103.0914 103.7676
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.2640322
[2,] 1.2765782
[3,] -0.5956504
[4,] -0.5958342
[5,] 2.9976408
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.70086127 -2.3325123
[2,] 2.30147601 0.2697307
[3,] 0.73507137 0.5486491
[4,] 0.05371092 1.2215007
[5,] 0.34294429 2.0567096
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.1781597 1.12387516
[2,] -0.8922881 -0.69436043
[3,] 1.6590296 -0.37688758
[4,] -0.5581464 0.01203421
[5,] -1.4647174 -0.87226025
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.1781597
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.1781597
[2,] -0.8922881
>
>
>
> 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 0.8377024 0.7744824 0.5560146 -0.05392819 0.2898703 -0.5405862 1.1145955
row1 0.2948882 -1.1344609 0.2342711 0.43545964 -1.2810809 1.0062168 0.1386291
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -1.7029216 0.9553084 -1.394688 0.4431662 -0.5092678 -1.420270 -2.170254
row1 0.7587867 1.2113758 -0.767509 -0.8247597 -0.6300664 1.153906 -1.267485
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.780165 0.05098667 -0.4286775 -0.7503945 -1.537570 -0.2929728
row1 -0.408044 0.64427636 0.7615676 -0.7785921 1.572407 0.1455138
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.46306 -0.2242697 0.0575739 -0.5721491 -1.579408 -0.1227466 -0.6204317
[,8] [,9] [,10]
row2 0.09751625 1.535582 -2.273497
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.2600587 -2.609028 -0.5824154 -1.333154 -0.6121733 0.5086133 0.1890482
[,8] [,9] [,10] [,11] [,12] [,13]
row5 0.397118 -0.5298924 -0.8755338 -0.9529571 -0.3308074 -0.009359541
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.1408245 0.6250395 1.285174 -0.4929864 -0.6018477 -1.651811 0.4938605
>
>
> 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: 0x55d105aba220>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e9b9ae674052"
[2] "/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e9b9a251d7ae4"
[3] "/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e9b9a2f744f64"
[4] "/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e9b9a65984ef5"
[5] "/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e9b9a4e826aa"
[6] "/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e9b9a21b9ee2c"
[7] "/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e9b9a4d2450aa"
[8] "/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e9b9a5384c2e7"
[9] "/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e9b9a360de8cd"
[10] "/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e9b9a5d53fc85"
[11] "/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e9b9a5954770c"
[12] "/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e9b9a330d4d51"
[13] "/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e9b9a6ac931da"
[14] "/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e9b9a36089cb5"
[15] "/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/tests/BM3e9b9a7b2761d"
>
>
> ### 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: 0x55d104d9db00>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x55d104d9db00>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.13-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x55d104d9db00>
> rowMedians(tmp)
[1] -0.3387767546 -0.1713215025 -0.0273328275 0.0629806578 -0.4022025471
[6] 0.3525325383 -0.5357303204 0.2884563680 0.2916892071 0.6088161783
[11] -0.1827934064 0.2289751882 -0.4182576340 0.2854839510 0.3340785862
[16] -0.4537113299 -0.1853921224 0.4890452720 0.1478243180 -0.2902885204
[21] -0.2572134202 0.1419401815 0.4593125167 0.1435721910 0.0246922434
[26] 0.0399487057 0.2071452517 -0.5004855803 0.2491803506 0.4320341506
[31] 0.5531430825 0.0280194765 0.4587878947 0.3790151861 -0.5963074697
[36] 0.5413481068 -0.7829876004 0.0070572580 0.3981240264 -0.1428414172
[41] 0.2867870268 0.1810970271 -0.0817980813 0.1375552721 0.0453476752
[46] -0.0413280690 -0.4560663121 -0.6470041529 -0.3307176269 0.0431922347
[51] -0.9314597217 0.1292300018 0.0629415084 0.3827950719 -0.1099259188
[56] 0.3152645625 0.0590740037 -0.1651794365 0.0994117717 0.2386906239
[61] 0.1734282104 -0.4222089471 0.2846925555 0.4391037377 0.3394173747
[66] 0.1272110530 0.4519679314 0.3492896730 -0.3514465534 0.1471611033
[71] 0.1457377772 0.1773297956 0.2326060051 -0.3271101146 0.0446163107
[76] -0.1891153865 0.1223949174 0.2090372146 0.0142231176 -0.0511110952
[81] -0.2890905258 -0.0836691706 -0.1320974438 0.0549497775 -0.6532343755
[86] -0.2578311058 0.4232924459 -0.1126635260 -0.1347416149 0.6240440771
[91] 0.0793341017 0.2208189974 0.2870489109 -0.0878763497 -0.2629386272
[96] 0.2877576072 0.2003644611 -0.1429520413 -0.1145656590 0.1304409413
[101] 0.0936571679 -0.3480319159 0.3857016020 -0.0861990022 -0.0789184233
[106] -0.6256291521 -0.0797066588 -0.0524181870 -0.6860521515 -0.1367752776
[111] 0.4936325676 -0.1409579213 0.4194288705 0.2713453778 0.3159122153
[116] 0.1644407880 -0.1363571984 0.4003696189 0.3211506074 0.4414971452
[121] -0.0455429327 0.1387061622 0.1728517490 0.0744549194 -0.0761755530
[126] 0.6053521837 0.3455790322 0.0439959203 0.1148763985 -0.2059716024
[131] 0.6018492369 0.3502853099 -0.1960579951 -0.0134914315 -0.1589238207
[136] 0.2931563514 -0.1164444693 0.0418945193 -0.3336867364 -0.0822215701
[141] 0.0429557675 -0.0008392129 -0.1787193343 -0.1901792447 -0.2393462882
[146] -0.0066371521 -0.4644376233 -0.1295291023 0.2279466326 0.0153728717
[151] -0.0770281308 0.3790019015 -0.0345285197 0.2381195572 -0.6883067690
[156] 0.3134793218 0.7669346448 -0.6213759449 -0.0601207513 -0.0194798699
[161] 0.7315443653 -0.0340770631 -0.1203804157 -0.4200314336 -0.3380396479
[166] 0.4668553471 -0.0314907116 0.3895299012 -0.0759059282 0.3105271608
[171] -0.2647703314 0.5736193119 0.6800978213 0.4702604370 0.6759610667
[176] -0.0195601875 0.1356343452 0.5455930778 -0.5597913878 -0.0679073023
[181] 0.1552441372 -0.0391471735 0.1729700497 0.2460358031 -0.3086644578
[186] -0.3425855910 -0.4006167468 -0.6895584369 0.0616115218 -0.3593096849
[191] -0.1417067165 0.4035418117 0.4032716891 0.0474891847 -0.0109062174
[196] 0.3079553066 0.1044216879 -0.0850971671 0.3845666781 0.2438628221
[201] -0.0222608761 0.1848244732 0.2398864865 0.4557328680 0.2501488969
[206] -0.2254985135 -0.6048809997 0.0385542907 0.3848040745 -0.2497428339
[211] -0.6474824658 0.2425970034 0.2238213798 0.0009628953 -0.0858203117
[216] -0.0895703298 -0.0372654999 0.1260416387 -0.2553788717 0.2911820924
[221] 0.0202497620 -0.5689270373 -0.0028407812 0.1665705990 -0.2218101470
[226] 0.3127399652 0.2568994860 -0.0293464772 -0.1788848857 -0.0167900481
>
> proc.time()
user system elapsed
1.402 1.626 3.034
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.1.1 (2021-08-10) -- "Kick Things"
Copyright (C) 2021 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: 0x5629bc99fa10>
> .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: 0x5629bc99fa10>
> .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: 0x5629bc99fa10>
> .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: 0x5629bc99fa10>
> 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: 0x5629bbfc2140>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5629bbfc2140>
> .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: 0x5629bbfc2140>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5629bbfc2140>
> .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: 0x5629bbfc2140>
> 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: 0x5629bc551850>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5629bc551850>
> .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: 0x5629bc551850>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5629bc551850>
> .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: 0x5629bc551850>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5629bc551850>
> .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: 0x5629bc551850>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5629bc551850>
> .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: 0x5629bc551850>
> 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: 0x5629bbea8520>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5629bbea8520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5629bbea8520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5629bbea8520>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3e9e91216d193e" "BufferedMatrixFile3e9e912d25108c"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3e9e91216d193e" "BufferedMatrixFile3e9e912d25108c"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5629bb9bbbb0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5629bb9bbbb0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5629bb9bbbb0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5629bb9bbbb0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5629bb9bbbb0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5629bb9bbbb0>
> .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: 0x5629bbc86e40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5629bbc86e40>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5629bbc86e40>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5629bbc86e40>
> 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: 0x5629bbd747c0>
> .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: 0x5629bbd747c0>
> rm(P)
>
> proc.time()
user system elapsed
0.284 0.031 0.303
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.1.1 (2021-08-10) -- "Kick Things"
Copyright (C) 2021 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
0.281 0.051 0.318