| Back to Build/check report for BioC 3.17 |
|
This page was generated on 2023-01-29 16:33:38 -0000 (Sun, 29 Jan 2023).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| kunpeng1 | Linux (Ubuntu 22.04.1 LTS) | aarch64 | R Under development (unstable) (2023-01-14 r83615) -- "Unsuffered Consequences" | 4021 |
| 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 227/2162 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.63.0 (landing page) Ben Bolstad
| kunpeng1 | Linux (Ubuntu 22.04.1 LTS) / aarch64 | OK | OK | WARNINGS | |||||||||
| Package: BufferedMatrix |
| Version: 1.63.0 |
| Command: /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.17-bioc/R/library --timings BufferedMatrix_1.63.0.tar.gz |
| StartedAt: 2023-01-28 18:50:58 -0000 (Sat, 28 Jan 2023) |
| EndedAt: 2023-01-28 18:51:29 -0000 (Sat, 28 Jan 2023) |
| EllapsedTime: 31.0 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.17-bioc/R/library --timings BufferedMatrix_1.63.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2023-01-14 r83615)
* using platform: aarch64-unknown-linux-gnu (64-bit)
* R was compiled by
gcc (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
GNU Fortran (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
* running under: Ubuntu 22.04.1 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.63.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘gcc (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0’
* checking 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 ... WARNING
Error in library(BufferedMatrix, lib.loc = "/home/biocbuild/bbs-3.17-bioc/R/library") :
there is no package called ‘BufferedMatrix’
Execution halted
It looks like this package has a loading problem when not on .libPaths:
see the messages for details.
* 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 ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... SKIPPED
* 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: 1 WARNING, 1 NOTE
See
‘/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.17-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0’
gcc -I"/home/biocbuild/bbs-3.17-bioc/R/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.17-bioc/R/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
gcc -I"/home/biocbuild/bbs-3.17-bioc/R/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"/home/biocbuild/bbs-3.17-bioc/R/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -c init_package.c -o init_package.o
gcc -shared -L/home/biocbuild/bbs-3.17-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.17-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.17-bioc/R/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R Under development (unstable) (2023-01-14 r83615) -- "Unsuffered Consequences"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-unknown-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
0.325 0.044 0.353
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R Under development (unstable) (2023-01-14 r83615) -- "Unsuffered Consequences"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 456959 24.5 979797 52.4 651600 34.8
Vcells 842287 6.5 8388608 64.0 2049159 15.7
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Sat Jan 28 18:51:17 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] "Sat Jan 28 18:51:17 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: 0xaaaaed5e0460>
>
>
>
> 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] "Sat Jan 28 18:51:18 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] "Sat Jan 28 18:51:18 2023"
>
> ColMode(tmp2)
<pointer: 0xaaaaed5e0460>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.834065378 -1.19702787 1.2345423 1.2442133
[2,] 0.232695834 0.01776452 -1.4785368 0.9943515
[3,] 0.007774307 -0.23350793 0.4737688 -0.4792685
[4,] -0.063733183 -1.11649963 -0.3339662 -1.1828581
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 1.008341e+02 1.19702787 1.2345423 1.2442133
[2,] 2.326958e-01 0.01776452 1.4785368 0.9943515
[3,] 7.774307e-03 0.23350793 0.4737688 0.4792685
[4,] 6.373318e-02 1.11649963 0.3339662 1.1828581
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.04161667 1.0940877 1.1110996 1.1154431
[2,] 0.48238557 0.1332836 1.2159510 0.9971718
[3,] 0.08817203 0.4832266 0.6883086 0.6922922
[4,] 0.25245432 1.0566455 0.5778981 1.0875928
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 226.25023 37.13790 37.34554 37.39864
[2,] 30.05655 26.35060 38.63805 35.96607
[3,] 25.88949 30.06577 32.35686 32.40219
[4,] 27.58828 36.68295 31.11295 37.05879
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0xaaaaecc29070>
> exp(tmp5)
<pointer: 0xaaaaecc29070>
> log(tmp5,2)
<pointer: 0xaaaaecc29070>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.9102
> Min(tmp5)
[1] 52.95941
> mean(tmp5)
[1] 72.10947
> Sum(tmp5)
[1] 14421.89
> Var(tmp5)
[1] 877.3105
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.12115 73.40651 65.57220 70.70451 69.91570 68.90494 71.82283 67.47957
[9] 70.87362 71.29369
> rowSums(tmp5)
[1] 1822.423 1468.130 1311.444 1414.090 1398.314 1378.099 1436.457 1349.591
[9] 1417.472 1425.874
> rowVars(tmp5)
[1] 8028.79133 115.47357 69.09723 47.52121 104.77611 78.69146
[7] 44.31863 63.25499 99.88673 66.72644
> rowSd(tmp5)
[1] 89.603523 10.745863 8.312474 6.893563 10.236020 8.870821 6.657224
[8] 7.953301 9.994335 8.168625
> rowMax(tmp5)
[1] 470.91022 93.73311 84.81194 81.66107 89.59159 83.45928 80.81822
[8] 90.51253 86.00594 82.89796
> rowMin(tmp5)
[1] 60.20270 54.84532 53.88559 57.42138 56.99524 52.95941 58.22765 56.36775
[9] 52.98968 58.23438
>
> colMeans(tmp5)
[1] 107.06697 69.98827 70.45057 72.26239 72.71781 70.64025 70.88572
[8] 69.33581 72.41215 70.30192 70.77418 69.45698 73.04003 70.77259
[15] 64.35486 64.93509 69.85523 72.53783 72.81972 67.58107
> colSums(tmp5)
[1] 1070.6697 699.8827 704.5057 722.6239 727.1781 706.4025 708.8572
[8] 693.3581 724.1215 703.0192 707.7418 694.5698 730.4003 707.7259
[15] 643.5486 649.3509 698.5523 725.3783 728.1972 675.8107
> colVars(tmp5)
[1] 16395.30284 78.67891 104.41347 47.63985 171.14844 66.20755
[7] 98.55520 38.02917 47.00763 100.91566 88.71562 50.30126
[13] 68.40097 85.62533 44.04191 20.25676 113.62713 72.33426
[19] 98.37568 60.14006
> colSd(tmp5)
[1] 128.044144 8.870113 10.218291 6.902163 13.082371 8.136802
[7] 9.927497 6.166780 6.856211 10.045679 9.418897 7.092338
[13] 8.270488 9.253395 6.636408 4.500752 10.659603 8.504955
[19] 9.918452 7.755002
> colMax(tmp5)
[1] 470.91022 79.80753 90.51253 81.87512 93.73311 79.58674 87.37663
[8] 78.96706 83.45928 85.87059 87.34676 81.23348 82.53581 90.03944
[15] 72.68502 73.78073 85.99094 87.66953 89.59159 78.42459
> colMin(tmp5)
[1] 53.88559 54.84532 52.95941 58.72653 55.12288 58.23438 59.75490 59.47848
[9] 61.16457 56.99524 60.88636 55.56762 57.65333 57.05061 54.75296 55.76342
[17] 52.98968 61.58973 59.16079 54.53896
>
>
> ### 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] 91.12115 73.40651 65.57220 70.70451 69.91570 68.90494 71.82283 67.47957
[9] 70.87362 NA
> rowSums(tmp5)
[1] 1822.423 1468.130 1311.444 1414.090 1398.314 1378.099 1436.457 1349.591
[9] 1417.472 NA
> rowVars(tmp5)
[1] 8028.79133 115.47357 69.09723 47.52121 104.77611 78.69146
[7] 44.31863 63.25499 99.88673 65.62602
> rowSd(tmp5)
[1] 89.603523 10.745863 8.312474 6.893563 10.236020 8.870821 6.657224
[8] 7.953301 9.994335 8.100989
> rowMax(tmp5)
[1] 470.91022 93.73311 84.81194 81.66107 89.59159 83.45928 80.81822
[8] 90.51253 86.00594 NA
> rowMin(tmp5)
[1] 60.20270 54.84532 53.88559 57.42138 56.99524 52.95941 58.22765 56.36775
[9] 52.98968 NA
>
> colMeans(tmp5)
[1] 107.06697 69.98827 70.45057 72.26239 72.71781 70.64025 70.88572
[8] 69.33581 72.41215 70.30192 70.77418 69.45698 73.04003 NA
[15] 64.35486 64.93509 69.85523 72.53783 72.81972 67.58107
> colSums(tmp5)
[1] 1070.6697 699.8827 704.5057 722.6239 727.1781 706.4025 708.8572
[8] 693.3581 724.1215 703.0192 707.7418 694.5698 730.4003 NA
[15] 643.5486 649.3509 698.5523 725.3783 728.1972 675.8107
> colVars(tmp5)
[1] 16395.30284 78.67891 104.41347 47.63985 171.14844 66.20755
[7] 98.55520 38.02917 47.00763 100.91566 88.71562 50.30126
[13] 68.40097 NA 44.04191 20.25676 113.62713 72.33426
[19] 98.37568 60.14006
> colSd(tmp5)
[1] 128.044144 8.870113 10.218291 6.902163 13.082371 8.136802
[7] 9.927497 6.166780 6.856211 10.045679 9.418897 7.092338
[13] 8.270488 NA 6.636408 4.500752 10.659603 8.504955
[19] 9.918452 7.755002
> colMax(tmp5)
[1] 470.91022 79.80753 90.51253 81.87512 93.73311 79.58674 87.37663
[8] 78.96706 83.45928 85.87059 87.34676 81.23348 82.53581 NA
[15] 72.68502 73.78073 85.99094 87.66953 89.59159 78.42459
> colMin(tmp5)
[1] 53.88559 54.84532 52.95941 58.72653 55.12288 58.23438 59.75490 59.47848
[9] 61.16457 56.99524 60.88636 55.56762 57.65333 NA 54.75296 55.76342
[17] 52.98968 61.58973 59.16079 54.53896
>
> Max(tmp5,na.rm=TRUE)
[1] 470.9102
> Min(tmp5,na.rm=TRUE)
[1] 52.95941
> mean(tmp5,na.rm=TRUE)
[1] 72.15913
> Sum(tmp5,na.rm=TRUE)
[1] 14359.67
> Var(tmp5,na.rm=TRUE)
[1] 881.2456
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.12115 73.40651 65.57220 70.70451 69.91570 68.90494 71.82283 67.47957
[9] 70.87362 71.77089
> rowSums(tmp5,na.rm=TRUE)
[1] 1822.423 1468.130 1311.444 1414.090 1398.314 1378.099 1436.457 1349.591
[9] 1417.472 1363.647
> rowVars(tmp5,na.rm=TRUE)
[1] 8028.79133 115.47357 69.09723 47.52121 104.77611 78.69146
[7] 44.31863 63.25499 99.88673 65.62602
> rowSd(tmp5,na.rm=TRUE)
[1] 89.603523 10.745863 8.312474 6.893563 10.236020 8.870821 6.657224
[8] 7.953301 9.994335 8.100989
> rowMax(tmp5,na.rm=TRUE)
[1] 470.91022 93.73311 84.81194 81.66107 89.59159 83.45928 80.81822
[8] 90.51253 86.00594 82.89796
> rowMin(tmp5,na.rm=TRUE)
[1] 60.20270 54.84532 53.88559 57.42138 56.99524 52.95941 58.22765 56.36775
[9] 52.98968 58.23438
>
> colMeans(tmp5,na.rm=TRUE)
[1] 107.06697 69.98827 70.45057 72.26239 72.71781 70.64025 70.88572
[8] 69.33581 72.41215 70.30192 70.77418 69.45698 73.04003 71.72211
[15] 64.35486 64.93509 69.85523 72.53783 72.81972 67.58107
> colSums(tmp5,na.rm=TRUE)
[1] 1070.6697 699.8827 704.5057 722.6239 727.1781 706.4025 708.8572
[8] 693.3581 724.1215 703.0192 707.7418 694.5698 730.4003 645.4990
[15] 643.5486 649.3509 698.5523 725.3783 728.1972 675.8107
> colVars(tmp5,na.rm=TRUE)
[1] 16395.30284 78.67891 104.41347 47.63985 171.14844 66.20755
[7] 98.55520 38.02917 47.00763 100.91566 88.71562 50.30126
[13] 68.40097 86.18551 44.04191 20.25676 113.62713 72.33426
[19] 98.37568 60.14006
> colSd(tmp5,na.rm=TRUE)
[1] 128.044144 8.870113 10.218291 6.902163 13.082371 8.136802
[7] 9.927497 6.166780 6.856211 10.045679 9.418897 7.092338
[13] 8.270488 9.283615 6.636408 4.500752 10.659603 8.504955
[19] 9.918452 7.755002
> colMax(tmp5,na.rm=TRUE)
[1] 470.91022 79.80753 90.51253 81.87512 93.73311 79.58674 87.37663
[8] 78.96706 83.45928 85.87059 87.34676 81.23348 82.53581 90.03944
[15] 72.68502 73.78073 85.99094 87.66953 89.59159 78.42459
> colMin(tmp5,na.rm=TRUE)
[1] 53.88559 54.84532 52.95941 58.72653 55.12288 58.23438 59.75490 59.47848
[9] 61.16457 56.99524 60.88636 55.56762 57.65333 57.05061 54.75296 55.76342
[17] 52.98968 61.58973 59.16079 54.53896
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.12115 73.40651 65.57220 70.70451 69.91570 68.90494 71.82283 67.47957
[9] 70.87362 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1822.423 1468.130 1311.444 1414.090 1398.314 1378.099 1436.457 1349.591
[9] 1417.472 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 8028.79133 115.47357 69.09723 47.52121 104.77611 78.69146
[7] 44.31863 63.25499 99.88673 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 89.603523 10.745863 8.312474 6.893563 10.236020 8.870821 6.657224
[8] 7.953301 9.994335 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 470.91022 93.73311 84.81194 81.66107 89.59159 83.45928 80.81822
[8] 90.51253 86.00594 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 60.20270 54.84532 53.88559 57.42138 56.99524 52.95941 58.22765 56.36775
[9] 52.98968 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 111.61656 68.89724 70.58318 71.19431 71.58669 72.01868 69.57744
[8] 70.43107 72.56736 71.23622 71.32620 68.69148 72.50997 NaN
[15] 63.50183 63.95224 70.65919 72.95759 71.76623 67.20669
> colSums(tmp5,na.rm=TRUE)
[1] 1004.5491 620.0751 635.2486 640.7488 644.2802 648.1681 626.1970
[8] 633.8797 653.1062 641.1260 641.9358 618.2233 652.5897 0.0000
[15] 571.5165 575.5701 635.9328 656.6183 645.8961 604.8603
> colVars(tmp5,na.rm=TRUE)
[1] 18211.85371 75.12239 117.26732 40.76086 178.14821 53.10771
[7] 91.61925 29.28740 52.61258 103.70976 96.37694 49.99648
[13] 73.79025 NA 41.36108 11.92145 120.55904 79.39378
[19] 98.18706 66.08077
> colSd(tmp5,na.rm=TRUE)
[1] 134.951301 8.667318 10.829004 6.384423 13.347217 7.287504
[7] 9.571795 5.411783 7.253453 10.183799 9.817176 7.070819
[13] 8.590125 NA 6.431258 3.452745 10.979938 8.910319
[19] 9.908938 8.129008
> colMax(tmp5,na.rm=TRUE)
[1] 470.91022 77.29768 90.51253 77.99818 93.73311 79.58674 87.37663
[8] 78.96706 83.45928 85.87059 87.34676 81.23348 82.53581 -Inf
[15] 72.68502 68.59106 85.99094 87.66953 89.59159 78.42459
> colMin(tmp5,na.rm=TRUE)
[1] 53.88559 54.84532 52.95941 58.72653 55.12288 59.14705 59.75490 60.20270
[9] 61.16457 56.99524 60.88636 55.56762 57.65333 Inf 54.75296 55.76342
[17] 52.98968 61.58973 59.16079 54.53896
>
>
>
>
> 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] 215.4204 204.8113 248.2262 313.2543 168.7596 174.8281 181.5588 305.0436
[9] 199.3378 197.6805
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 215.4204 204.8113 248.2262 313.2543 168.7596 174.8281 181.5588 305.0436
[9] 199.3378 197.6805
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 5.684342e-14 0.000000e+00 0.000000e+00 -5.684342e-14 0.000000e+00
[6] 1.563194e-13 2.273737e-13 0.000000e+00 -1.136868e-13 0.000000e+00
[11] 5.684342e-14 1.136868e-13 -1.421085e-13 -1.989520e-13 -5.684342e-14
[16] -2.842171e-14 5.684342e-14 -1.136868e-13 0.000000e+00 5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
4 2
6 19
2 19
7 2
6 20
2 15
2 11
3 20
3 13
3 2
2 16
4 18
2 14
1 2
8 1
9 8
3 2
4 2
1 5
7 9
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] 3.125351
> Min(tmp)
[1] -2.99953
> mean(tmp)
[1] 0.005394135
> Sum(tmp)
[1] 0.5394135
> Var(tmp)
[1] 1.311769
>
> rowMeans(tmp)
[1] 0.005394135
> rowSums(tmp)
[1] 0.5394135
> rowVars(tmp)
[1] 1.311769
> rowSd(tmp)
[1] 1.145325
> rowMax(tmp)
[1] 3.125351
> rowMin(tmp)
[1] -2.99953
>
> colMeans(tmp)
[1] 1.2605126381 1.2315983136 -0.4854926658 -1.6464915305 -0.2624161221
[6] -2.1765222141 -0.3417054705 0.1988193917 -1.6917826087 0.8577321188
[11] 0.2338299279 -1.2832085272 -1.2925261876 0.6922194577 -0.6309920413
[16] -0.8587907299 -1.7233481982 -1.1827233749 -0.1681828455 -0.8694776756
[21] 1.0089541123 -0.6032398324 -1.9914961315 -0.0763790536 -2.9995304980
[26] 1.4340909761 0.0934684339 0.6630983750 1.6638393813 0.3647611286
[31] -0.3710970537 -0.0167659499 3.1253510515 0.7051103294 -1.1475645996
[36] -2.7689666502 0.2606586265 1.5203765297 0.9919797930 0.4288143771
[41] 1.7542310815 1.1296595017 -0.2305422546 -0.4980751192 -1.0127850406
[46] 0.4146867727 -1.6888679809 1.7436967031 -0.2499685927 0.2107286288
[51] -0.1379608118 0.7577877625 0.0007496365 -0.6074168888 0.5900621164
[56] 0.8097252187 -0.9757314493 -0.5174113292 0.5168888665 0.2331795597
[61] 0.7361386089 -0.0625718879 -0.8428538180 0.2942797566 2.4356662450
[66] 1.1382984832 2.0407035731 -1.2891769073 -0.0487682314 -0.1972182924
[71] -0.5412995609 -1.0888682560 1.2787186339 1.1512179955 0.9099462807
[76] 0.8647503596 -0.2860699871 -0.2495407934 -0.5431577176 -0.6160725413
[81] -0.3855983887 1.6343483095 -0.5294571814 -0.3857188418 -0.3037353212
[86] 0.5232363045 1.9688247216 -0.2517709324 -1.9320692070 0.3767971826
[91] 0.5944615564 -0.0072096143 0.0724372636 2.0999392503 -1.7383635324
[96] -1.0003692489 -0.1816067902 -0.6085164724 2.0669880199 -0.9464769212
> colSums(tmp)
[1] 1.2605126381 1.2315983136 -0.4854926658 -1.6464915305 -0.2624161221
[6] -2.1765222141 -0.3417054705 0.1988193917 -1.6917826087 0.8577321188
[11] 0.2338299279 -1.2832085272 -1.2925261876 0.6922194577 -0.6309920413
[16] -0.8587907299 -1.7233481982 -1.1827233749 -0.1681828455 -0.8694776756
[21] 1.0089541123 -0.6032398324 -1.9914961315 -0.0763790536 -2.9995304980
[26] 1.4340909761 0.0934684339 0.6630983750 1.6638393813 0.3647611286
[31] -0.3710970537 -0.0167659499 3.1253510515 0.7051103294 -1.1475645996
[36] -2.7689666502 0.2606586265 1.5203765297 0.9919797930 0.4288143771
[41] 1.7542310815 1.1296595017 -0.2305422546 -0.4980751192 -1.0127850406
[46] 0.4146867727 -1.6888679809 1.7436967031 -0.2499685927 0.2107286288
[51] -0.1379608118 0.7577877625 0.0007496365 -0.6074168888 0.5900621164
[56] 0.8097252187 -0.9757314493 -0.5174113292 0.5168888665 0.2331795597
[61] 0.7361386089 -0.0625718879 -0.8428538180 0.2942797566 2.4356662450
[66] 1.1382984832 2.0407035731 -1.2891769073 -0.0487682314 -0.1972182924
[71] -0.5412995609 -1.0888682560 1.2787186339 1.1512179955 0.9099462807
[76] 0.8647503596 -0.2860699871 -0.2495407934 -0.5431577176 -0.6160725413
[81] -0.3855983887 1.6343483095 -0.5294571814 -0.3857188418 -0.3037353212
[86] 0.5232363045 1.9688247216 -0.2517709324 -1.9320692070 0.3767971826
[91] 0.5944615564 -0.0072096143 0.0724372636 2.0999392503 -1.7383635324
[96] -1.0003692489 -0.1816067902 -0.6085164724 2.0669880199 -0.9464769212
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] 1.2605126381 1.2315983136 -0.4854926658 -1.6464915305 -0.2624161221
[6] -2.1765222141 -0.3417054705 0.1988193917 -1.6917826087 0.8577321188
[11] 0.2338299279 -1.2832085272 -1.2925261876 0.6922194577 -0.6309920413
[16] -0.8587907299 -1.7233481982 -1.1827233749 -0.1681828455 -0.8694776756
[21] 1.0089541123 -0.6032398324 -1.9914961315 -0.0763790536 -2.9995304980
[26] 1.4340909761 0.0934684339 0.6630983750 1.6638393813 0.3647611286
[31] -0.3710970537 -0.0167659499 3.1253510515 0.7051103294 -1.1475645996
[36] -2.7689666502 0.2606586265 1.5203765297 0.9919797930 0.4288143771
[41] 1.7542310815 1.1296595017 -0.2305422546 -0.4980751192 -1.0127850406
[46] 0.4146867727 -1.6888679809 1.7436967031 -0.2499685927 0.2107286288
[51] -0.1379608118 0.7577877625 0.0007496365 -0.6074168888 0.5900621164
[56] 0.8097252187 -0.9757314493 -0.5174113292 0.5168888665 0.2331795597
[61] 0.7361386089 -0.0625718879 -0.8428538180 0.2942797566 2.4356662450
[66] 1.1382984832 2.0407035731 -1.2891769073 -0.0487682314 -0.1972182924
[71] -0.5412995609 -1.0888682560 1.2787186339 1.1512179955 0.9099462807
[76] 0.8647503596 -0.2860699871 -0.2495407934 -0.5431577176 -0.6160725413
[81] -0.3855983887 1.6343483095 -0.5294571814 -0.3857188418 -0.3037353212
[86] 0.5232363045 1.9688247216 -0.2517709324 -1.9320692070 0.3767971826
[91] 0.5944615564 -0.0072096143 0.0724372636 2.0999392503 -1.7383635324
[96] -1.0003692489 -0.1816067902 -0.6085164724 2.0669880199 -0.9464769212
> colMin(tmp)
[1] 1.2605126381 1.2315983136 -0.4854926658 -1.6464915305 -0.2624161221
[6] -2.1765222141 -0.3417054705 0.1988193917 -1.6917826087 0.8577321188
[11] 0.2338299279 -1.2832085272 -1.2925261876 0.6922194577 -0.6309920413
[16] -0.8587907299 -1.7233481982 -1.1827233749 -0.1681828455 -0.8694776756
[21] 1.0089541123 -0.6032398324 -1.9914961315 -0.0763790536 -2.9995304980
[26] 1.4340909761 0.0934684339 0.6630983750 1.6638393813 0.3647611286
[31] -0.3710970537 -0.0167659499 3.1253510515 0.7051103294 -1.1475645996
[36] -2.7689666502 0.2606586265 1.5203765297 0.9919797930 0.4288143771
[41] 1.7542310815 1.1296595017 -0.2305422546 -0.4980751192 -1.0127850406
[46] 0.4146867727 -1.6888679809 1.7436967031 -0.2499685927 0.2107286288
[51] -0.1379608118 0.7577877625 0.0007496365 -0.6074168888 0.5900621164
[56] 0.8097252187 -0.9757314493 -0.5174113292 0.5168888665 0.2331795597
[61] 0.7361386089 -0.0625718879 -0.8428538180 0.2942797566 2.4356662450
[66] 1.1382984832 2.0407035731 -1.2891769073 -0.0487682314 -0.1972182924
[71] -0.5412995609 -1.0888682560 1.2787186339 1.1512179955 0.9099462807
[76] 0.8647503596 -0.2860699871 -0.2495407934 -0.5431577176 -0.6160725413
[81] -0.3855983887 1.6343483095 -0.5294571814 -0.3857188418 -0.3037353212
[86] 0.5232363045 1.9688247216 -0.2517709324 -1.9320692070 0.3767971826
[91] 0.5944615564 -0.0072096143 0.0724372636 2.0999392503 -1.7383635324
[96] -1.0003692489 -0.1816067902 -0.6085164724 2.0669880199 -0.9464769212
> colMedians(tmp)
[1] 1.2605126381 1.2315983136 -0.4854926658 -1.6464915305 -0.2624161221
[6] -2.1765222141 -0.3417054705 0.1988193917 -1.6917826087 0.8577321188
[11] 0.2338299279 -1.2832085272 -1.2925261876 0.6922194577 -0.6309920413
[16] -0.8587907299 -1.7233481982 -1.1827233749 -0.1681828455 -0.8694776756
[21] 1.0089541123 -0.6032398324 -1.9914961315 -0.0763790536 -2.9995304980
[26] 1.4340909761 0.0934684339 0.6630983750 1.6638393813 0.3647611286
[31] -0.3710970537 -0.0167659499 3.1253510515 0.7051103294 -1.1475645996
[36] -2.7689666502 0.2606586265 1.5203765297 0.9919797930 0.4288143771
[41] 1.7542310815 1.1296595017 -0.2305422546 -0.4980751192 -1.0127850406
[46] 0.4146867727 -1.6888679809 1.7436967031 -0.2499685927 0.2107286288
[51] -0.1379608118 0.7577877625 0.0007496365 -0.6074168888 0.5900621164
[56] 0.8097252187 -0.9757314493 -0.5174113292 0.5168888665 0.2331795597
[61] 0.7361386089 -0.0625718879 -0.8428538180 0.2942797566 2.4356662450
[66] 1.1382984832 2.0407035731 -1.2891769073 -0.0487682314 -0.1972182924
[71] -0.5412995609 -1.0888682560 1.2787186339 1.1512179955 0.9099462807
[76] 0.8647503596 -0.2860699871 -0.2495407934 -0.5431577176 -0.6160725413
[81] -0.3855983887 1.6343483095 -0.5294571814 -0.3857188418 -0.3037353212
[86] 0.5232363045 1.9688247216 -0.2517709324 -1.9320692070 0.3767971826
[91] 0.5944615564 -0.0072096143 0.0724372636 2.0999392503 -1.7383635324
[96] -1.0003692489 -0.1816067902 -0.6085164724 2.0669880199 -0.9464769212
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.260513 1.231598 -0.4854927 -1.646492 -0.2624161 -2.176522 -0.3417055
[2,] 1.260513 1.231598 -0.4854927 -1.646492 -0.2624161 -2.176522 -0.3417055
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.1988194 -1.691783 0.8577321 0.2338299 -1.283209 -1.292526 0.6922195
[2,] 0.1988194 -1.691783 0.8577321 0.2338299 -1.283209 -1.292526 0.6922195
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.630992 -0.8587907 -1.723348 -1.182723 -0.1681828 -0.8694777 1.008954
[2,] -0.630992 -0.8587907 -1.723348 -1.182723 -0.1681828 -0.8694777 1.008954
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.6032398 -1.991496 -0.07637905 -2.99953 1.434091 0.09346843 0.6630984
[2,] -0.6032398 -1.991496 -0.07637905 -2.99953 1.434091 0.09346843 0.6630984
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.663839 0.3647611 -0.3710971 -0.01676595 3.125351 0.7051103 -1.147565
[2,] 1.663839 0.3647611 -0.3710971 -0.01676595 3.125351 0.7051103 -1.147565
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -2.768967 0.2606586 1.520377 0.9919798 0.4288144 1.754231 1.12966
[2,] -2.768967 0.2606586 1.520377 0.9919798 0.4288144 1.754231 1.12966
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.2305423 -0.4980751 -1.012785 0.4146868 -1.688868 1.743697 -0.2499686
[2,] -0.2305423 -0.4980751 -1.012785 0.4146868 -1.688868 1.743697 -0.2499686
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.2107286 -0.1379608 0.7577878 0.0007496365 -0.6074169 0.5900621 0.8097252
[2,] 0.2107286 -0.1379608 0.7577878 0.0007496365 -0.6074169 0.5900621 0.8097252
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.9757314 -0.5174113 0.5168889 0.2331796 0.7361386 -0.06257189 -0.8428538
[2,] -0.9757314 -0.5174113 0.5168889 0.2331796 0.7361386 -0.06257189 -0.8428538
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.2942798 2.435666 1.138298 2.040704 -1.289177 -0.04876823 -0.1972183
[2,] 0.2942798 2.435666 1.138298 2.040704 -1.289177 -0.04876823 -0.1972183
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.5412996 -1.088868 1.278719 1.151218 0.9099463 0.8647504 -0.28607
[2,] -0.5412996 -1.088868 1.278719 1.151218 0.9099463 0.8647504 -0.28607
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.2495408 -0.5431577 -0.6160725 -0.3855984 1.634348 -0.5294572 -0.3857188
[2,] -0.2495408 -0.5431577 -0.6160725 -0.3855984 1.634348 -0.5294572 -0.3857188
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.3037353 0.5232363 1.968825 -0.2517709 -1.932069 0.3767972 0.5944616
[2,] -0.3037353 0.5232363 1.968825 -0.2517709 -1.932069 0.3767972 0.5944616
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.007209614 0.07243726 2.099939 -1.738364 -1.000369 -0.1816068 -0.6085165
[2,] -0.007209614 0.07243726 2.099939 -1.738364 -1.000369 -0.1816068 -0.6085165
[,99] [,100]
[1,] 2.066988 -0.9464769
[2,] 2.066988 -0.9464769
>
>
> Max(tmp2)
[1] 2.770117
> Min(tmp2)
[1] -2.327912
> mean(tmp2)
[1] -0.004551597
> Sum(tmp2)
[1] -0.4551597
> Var(tmp2)
[1] 0.7331147
>
> rowMeans(tmp2)
[1] 0.35942867 -0.14963674 -0.34148521 -0.29658034 1.51753349 0.26936923
[7] -0.25973295 -0.22334076 -0.16544185 -0.21734079 -0.73786817 -0.35248179
[13] -0.17439955 1.09745963 -0.63381414 0.96324986 0.63408518 1.09994072
[19] 1.17001165 1.66569333 0.09105994 0.83419759 -0.78598179 0.26579824
[25] -0.41834086 -0.91121081 0.56594506 0.37883626 -0.61914395 -0.20361423
[31] -1.10935341 1.31344554 -0.34741886 -0.30162603 -0.58965206 -0.38380445
[37] -1.52907084 0.12302959 0.41462734 0.29540706 0.75110454 1.10476725
[43] 1.13477163 -0.19585037 0.20891968 -1.18611350 0.05781264 -1.07105863
[49] -0.53832520 -1.24584334 0.31319800 -0.10062504 0.62590049 -0.31196755
[55] 1.17369754 -0.10748903 -0.27056660 -1.53204963 -0.45539009 -0.15052500
[61] 0.71879279 0.21442005 -2.29749833 -1.18298745 0.20966935 0.53248941
[67] -1.26024153 2.77011653 -2.32791180 0.97974023 0.40001905 0.65460559
[73] -0.23891070 0.18807622 0.09401685 0.41938747 -1.12296735 -0.35022385
[79] 0.36196238 -0.25509899 1.04125833 0.40672464 -0.65689751 -0.51678355
[85] 0.80755188 0.46638172 -0.75442117 -0.48435288 1.34483174 -1.40195554
[91] 1.04034772 -0.57640703 1.22715175 -1.06554611 0.52196723 -0.37171865
[97] 0.77116389 -0.73476619 -0.51450271 -0.02478983
> rowSums(tmp2)
[1] 0.35942867 -0.14963674 -0.34148521 -0.29658034 1.51753349 0.26936923
[7] -0.25973295 -0.22334076 -0.16544185 -0.21734079 -0.73786817 -0.35248179
[13] -0.17439955 1.09745963 -0.63381414 0.96324986 0.63408518 1.09994072
[19] 1.17001165 1.66569333 0.09105994 0.83419759 -0.78598179 0.26579824
[25] -0.41834086 -0.91121081 0.56594506 0.37883626 -0.61914395 -0.20361423
[31] -1.10935341 1.31344554 -0.34741886 -0.30162603 -0.58965206 -0.38380445
[37] -1.52907084 0.12302959 0.41462734 0.29540706 0.75110454 1.10476725
[43] 1.13477163 -0.19585037 0.20891968 -1.18611350 0.05781264 -1.07105863
[49] -0.53832520 -1.24584334 0.31319800 -0.10062504 0.62590049 -0.31196755
[55] 1.17369754 -0.10748903 -0.27056660 -1.53204963 -0.45539009 -0.15052500
[61] 0.71879279 0.21442005 -2.29749833 -1.18298745 0.20966935 0.53248941
[67] -1.26024153 2.77011653 -2.32791180 0.97974023 0.40001905 0.65460559
[73] -0.23891070 0.18807622 0.09401685 0.41938747 -1.12296735 -0.35022385
[79] 0.36196238 -0.25509899 1.04125833 0.40672464 -0.65689751 -0.51678355
[85] 0.80755188 0.46638172 -0.75442117 -0.48435288 1.34483174 -1.40195554
[91] 1.04034772 -0.57640703 1.22715175 -1.06554611 0.52196723 -0.37171865
[97] 0.77116389 -0.73476619 -0.51450271 -0.02478983
> 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] 0.35942867 -0.14963674 -0.34148521 -0.29658034 1.51753349 0.26936923
[7] -0.25973295 -0.22334076 -0.16544185 -0.21734079 -0.73786817 -0.35248179
[13] -0.17439955 1.09745963 -0.63381414 0.96324986 0.63408518 1.09994072
[19] 1.17001165 1.66569333 0.09105994 0.83419759 -0.78598179 0.26579824
[25] -0.41834086 -0.91121081 0.56594506 0.37883626 -0.61914395 -0.20361423
[31] -1.10935341 1.31344554 -0.34741886 -0.30162603 -0.58965206 -0.38380445
[37] -1.52907084 0.12302959 0.41462734 0.29540706 0.75110454 1.10476725
[43] 1.13477163 -0.19585037 0.20891968 -1.18611350 0.05781264 -1.07105863
[49] -0.53832520 -1.24584334 0.31319800 -0.10062504 0.62590049 -0.31196755
[55] 1.17369754 -0.10748903 -0.27056660 -1.53204963 -0.45539009 -0.15052500
[61] 0.71879279 0.21442005 -2.29749833 -1.18298745 0.20966935 0.53248941
[67] -1.26024153 2.77011653 -2.32791180 0.97974023 0.40001905 0.65460559
[73] -0.23891070 0.18807622 0.09401685 0.41938747 -1.12296735 -0.35022385
[79] 0.36196238 -0.25509899 1.04125833 0.40672464 -0.65689751 -0.51678355
[85] 0.80755188 0.46638172 -0.75442117 -0.48435288 1.34483174 -1.40195554
[91] 1.04034772 -0.57640703 1.22715175 -1.06554611 0.52196723 -0.37171865
[97] 0.77116389 -0.73476619 -0.51450271 -0.02478983
> rowMin(tmp2)
[1] 0.35942867 -0.14963674 -0.34148521 -0.29658034 1.51753349 0.26936923
[7] -0.25973295 -0.22334076 -0.16544185 -0.21734079 -0.73786817 -0.35248179
[13] -0.17439955 1.09745963 -0.63381414 0.96324986 0.63408518 1.09994072
[19] 1.17001165 1.66569333 0.09105994 0.83419759 -0.78598179 0.26579824
[25] -0.41834086 -0.91121081 0.56594506 0.37883626 -0.61914395 -0.20361423
[31] -1.10935341 1.31344554 -0.34741886 -0.30162603 -0.58965206 -0.38380445
[37] -1.52907084 0.12302959 0.41462734 0.29540706 0.75110454 1.10476725
[43] 1.13477163 -0.19585037 0.20891968 -1.18611350 0.05781264 -1.07105863
[49] -0.53832520 -1.24584334 0.31319800 -0.10062504 0.62590049 -0.31196755
[55] 1.17369754 -0.10748903 -0.27056660 -1.53204963 -0.45539009 -0.15052500
[61] 0.71879279 0.21442005 -2.29749833 -1.18298745 0.20966935 0.53248941
[67] -1.26024153 2.77011653 -2.32791180 0.97974023 0.40001905 0.65460559
[73] -0.23891070 0.18807622 0.09401685 0.41938747 -1.12296735 -0.35022385
[79] 0.36196238 -0.25509899 1.04125833 0.40672464 -0.65689751 -0.51678355
[85] 0.80755188 0.46638172 -0.75442117 -0.48435288 1.34483174 -1.40195554
[91] 1.04034772 -0.57640703 1.22715175 -1.06554611 0.52196723 -0.37171865
[97] 0.77116389 -0.73476619 -0.51450271 -0.02478983
>
> colMeans(tmp2)
[1] -0.004551597
> colSums(tmp2)
[1] -0.4551597
> colVars(tmp2)
[1] 0.7331147
> colSd(tmp2)
[1] 0.8562212
> colMax(tmp2)
[1] 2.770117
> colMin(tmp2)
[1] -2.327912
> colMedians(tmp2)
[1] -0.1285629
> colRanges(tmp2)
[,1]
[1,] -2.327912
[2,] 2.770117
>
> 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] 5.5033592 -1.9318929 -4.8927639 -1.3283727 2.5461238 -3.7931654
[7] 1.3766452 -0.9351328 0.1664069 -1.9076070
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.0540651
[2,] 0.1122436
[3,] 0.3268143
[4,] 0.6051501
[5,] 4.0291500
>
> rowApply(tmp,sum)
[1] 0.2902238 -2.1359620 -4.9980319 -1.9114836 -0.5062689 6.0428976
[7] -2.9631872 -3.4278691 2.9523008 1.4609809
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 6 4 5 6 8 10 9 8 9 5
[2,] 9 8 2 9 9 2 3 5 3 2
[3,] 8 1 3 1 5 9 5 3 7 3
[4,] 2 3 6 3 3 6 8 9 10 6
[5,] 4 6 7 10 7 5 2 10 6 8
[6,] 5 5 9 2 6 4 1 4 2 7
[7,] 1 2 8 7 4 1 10 6 8 10
[8,] 10 10 1 4 1 7 4 2 1 9
[9,] 7 7 10 5 2 8 6 7 5 1
[10,] 3 9 4 8 10 3 7 1 4 4
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.8456378 2.0195861 3.2615209 -2.7648061 3.1125912 1.0677087
[7] -3.0082254 4.4164130 2.5150830 1.3064134 -1.8708264 -0.3856370
[13] 0.5118878 0.3393931 -1.6627308 -0.4504070 2.7872642 2.1466933
[19] 2.7022526 -2.1709026
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5881168
[2,] -0.3983785
[3,] -0.2120399
[4,] 0.2326821
[5,] 1.1202153
>
> rowApply(tmp,sum)
[1] -0.2182090 4.5201420 2.8603237 5.4980397 0.3673376
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 2 17 10 6 8
[2,] 16 14 4 4 19
[3,] 20 16 13 19 2
[4,] 11 3 3 11 6
[5,] 17 19 14 15 3
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.5881168 0.9253477 1.6622352 0.1391321 1.1433557 -1.0626251
[2,] 1.1202153 0.7146745 1.0443084 -1.4504131 1.9599620 1.6128429
[3,] 0.2326821 -0.8409743 0.3395658 -0.8997647 0.5272047 0.7790466
[4,] -0.2120399 -0.5131234 1.4602932 0.1597902 0.5840847 -0.8138064
[5,] -0.3983785 1.7336616 -1.2448818 -0.7135506 -1.1020160 0.5522507
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.04760433 -0.2050816 1.1481998 0.3407406 -2.17236730 0.8902651
[2,] -1.90042212 3.1194865 0.2698861 -0.4272436 -0.02063465 -0.5706187
[3,] -0.06464539 0.7814825 -0.5034870 1.5055537 -0.96292592 -0.5535011
[4,] -0.57081761 0.5217458 0.5193986 0.6973953 1.43704988 0.0635819
[5,] -0.51994458 0.1987796 1.0810856 -0.8100327 -0.15194837 -0.2153642
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.4908057 -0.8041799 -0.88402742 0.1753301 -0.111022776 0.4874824
[2,] 0.9032048 0.3151603 -1.46582553 -1.1352771 0.562732857 -0.1527586
[3,] 1.3980483 -1.3457901 -0.29624737 -0.4735987 0.272486480 0.5303317
[4,] -0.2291579 -0.7636669 0.88720623 0.1234730 2.070329688 -0.1809000
[5,] -1.0694017 2.9378697 0.09616329 0.8596656 -0.007262095 1.4625378
[,19] [,20]
[1,] 1.3671920 -1.22686753
[2,] 0.4141351 -0.39327330
[3,] 0.2479173 2.18693883
[4,] 0.1661833 0.09101995
[5,] 0.5068249 -2.82872050
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.9536858 0.0238902 0.123421 0.5981419 -1.544995 0.3487477 1.584368
col8 col9 col10 col11 col12 col13 col14
row1 1.32109 -0.05344108 1.327764 0.5767494 -0.2417424 -0.9900912 0.9838363
col15 col16 col17 col18 col19 col20
row1 0.3135916 -0.404486 -0.2641152 0.9871197 -1.908529 1.411169
> tmp[,"col10"]
col10
row1 1.3277641
row2 -0.1762196
row3 -0.2139421
row4 -1.0506476
row5 1.1426293
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.9536858 0.0238902 0.123421 0.5981419 -1.544995 0.3487477 1.584368
row5 0.2366101 -0.7832109 1.576635 0.8321049 -2.256566 -1.0406890 1.511734
col8 col9 col10 col11 col12 col13
row1 1.3210897 -0.05344108 1.327764 0.5767494 -0.2417424 -0.99009121
row5 -0.3028303 1.68461735 1.142629 0.1047262 -0.7624091 -0.05509119
col14 col15 col16 col17 col18 col19 col20
row1 0.9838363 0.31359159 -0.404486 -0.2641152 0.9871197 -1.9085292 1.411169
row5 -1.2841696 0.07602497 1.465710 -1.7502116 -2.3971334 -0.7168667 1.937374
> tmp[,c("col6","col20")]
col6 col20
row1 0.3487477 1.4111686
row2 0.2548203 0.9068413
row3 -1.0500270 -1.3505885
row4 0.1502925 -1.0074161
row5 -1.0406890 1.9373736
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.3487477 1.411169
row5 -1.0406890 1.937374
>
>
>
>
> 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 50.71988 49.6173 50.90334 49.27558 49.38879 104.6138 49.23694 50.29449
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.99184 50.36618 50.30548 51.02248 48.32623 48.88006 49.74232 50.5339
col17 col18 col19 col20
row1 48.94918 49.55261 49.30953 104.5877
> tmp[,"col10"]
col10
row1 50.36618
row2 28.18099
row3 31.42126
row4 29.21088
row5 50.13045
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.71988 49.61730 50.90334 49.27558 49.38879 104.6138 49.23694 50.29449
row5 49.93787 50.63074 49.71811 49.92475 49.89753 106.7987 50.90557 48.37149
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.99184 50.36618 50.30548 51.02248 48.32623 48.88006 49.74232 50.53390
row5 51.67332 50.13045 50.80746 48.62175 50.04061 49.98390 47.99357 49.79534
col17 col18 col19 col20
row1 48.94918 49.55261 49.30953 104.5877
row5 50.05148 50.20683 50.64163 104.6166
> tmp[,c("col6","col20")]
col6 col20
row1 104.61380 104.58765
row2 73.80030 75.92863
row3 73.42580 73.80218
row4 74.76739 74.51354
row5 106.79868 104.61659
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.6138 104.5877
row5 106.7987 104.6166
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.6138 104.5877
row5 106.7987 104.6166
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.01990791
[2,] -0.66863451
[3,] -1.07980171
[4,] -0.41633625
[5,] 0.01089184
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.62344699 0.5450700
[2,] 1.18063379 1.1341543
[3,] 2.53121795 0.1765248
[4,] 0.09398483 -2.5646066
[5,] 0.09504783 0.5621518
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.0521455 -1.65724288
[2,] -0.1873390 -0.35364168
[3,] -0.6372261 0.27601471
[4,] 0.1527238 0.01330035
[5,] -0.2041707 0.46429420
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.052145
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.052145
[2,] -0.187339
>
>
>
> 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 1.9928136 -0.0150163 0.003820296 0.20291470 1.1468525 -2.023620 0.9816317
row1 0.0413951 -0.4969490 0.367825881 0.07254466 -0.8148623 1.168647 0.5969427
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.6748637 1.44265174 -0.7476652 -0.5545853 0.3530565 0.2250282 -1.3651018
row1 0.2025854 0.02329938 1.2893097 -0.1271009 0.6132629 -1.9314657 -0.2290285
[,15] [,16] [,17] [,18] [,19] [,20]
row3 0.24033734 -0.2634527 1.9310353 0.08688315 -0.1389346 0.9439099
row1 -0.02705487 -2.1073232 0.4729903 0.38218888 -2.3699700 0.3563362
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.1293543 1.031859 -0.215424 1.328677 -1.067426 -0.8169535 -0.2888759
[,8] [,9] [,10]
row2 1.004379 -0.9736346 0.2626386
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.5945292 -0.8046378 -1.729373 -0.5072752 0.5930452 1.862048 -1.626965
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -1.326236 -0.1177188 0.7471929 1.175545 -1.137516 1.82065 -0.1552259
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.3320743 0.4646474 -2.279043 0.1466313 0.6619111 -0.5459419
>
>
> 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: 0xaaaaee0ccf90>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM277ead45ae24f2"
[2] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM277ead191c5819"
[3] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM277ead66d56352"
[4] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM277ead45bbe937"
[5] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM277ead77da26aa"
[6] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM277ead3f6ac4c8"
[7] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM277ead3f56f664"
[8] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM277ead1b26fe01"
[9] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM277ead15192976"
[10] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM277ead10dc1089"
[11] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM277ead4d24d3a2"
[12] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM277ead232c27d3"
[13] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM277ead7a052e0c"
[14] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM277ead4848dfa0"
[15] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM277ead59c34ce3"
>
>
> ### 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: 0xaaaaee9bedf0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0xaaaaee9bedf0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0xaaaaee9bedf0>
> rowMedians(tmp)
[1] 0.0484953643 -0.0817644196 0.3758660228 0.0352019605 0.0828020114
[6] -0.5161593438 -0.2752484977 0.5151313855 0.0094159722 0.0104160413
[11] 0.0979306542 0.0463873135 -0.3290247550 0.0269285114 -0.2683718022
[16] -0.4096195405 -0.2545746234 -0.0338801024 0.2457534504 0.5150784898
[21] 0.3627246076 -0.0432805435 0.7432113841 -0.2007378866 0.3467875530
[26] 0.1179062680 -0.0735802298 0.1441303441 0.3752681561 0.0113232373
[31] 0.2330930185 -0.2504512569 -0.1625636845 -0.6456823583 -0.1230045208
[36] -0.0722809297 0.1845263918 -0.3902395726 -0.0732142403 0.7741549899
[41] 0.0614286056 0.1766765600 0.7883518297 -0.3044206366 -0.0147189379
[46] -0.1662577344 0.5251647997 0.4351139752 0.1375564309 0.1408593795
[51] 0.4009885751 0.0004676534 0.2124033153 -0.0944972444 -0.5304837305
[56] -0.1992908317 0.0337412526 0.5700575949 -0.2685142360 0.0545594691
[61] -0.1338100601 0.2532610955 0.4047376184 -0.0021165990 0.2931158740
[66] -0.0701596352 -0.2678173961 0.0804675706 0.8070225749 -0.4642764352
[71] -0.2641153192 -0.0442740906 0.0766653664 0.4937584081 0.0580534624
[76] 0.5170336480 -0.1500020015 -0.2955161157 -0.1346006830 0.0710818436
[81] -0.0404130805 -0.1155147783 -0.3115267996 -0.2693077360 -0.1075887321
[86] -0.1518943571 0.2878331267 0.1368023711 -0.3994361842 0.1766137763
[91] -0.0075256366 0.0128233456 -0.2322721705 -0.3690504395 0.1529667144
[96] 0.1272677046 0.0536968115 0.4702528217 0.1952760589 0.1190721899
[101] -0.2995620514 0.8645613568 0.0192535559 -0.2363375385 -0.0632237169
[106] -0.3608654835 0.3785910447 -0.2522855866 0.2688059528 -0.0465379530
[111] -0.3568818786 -0.1552667536 -0.0586333205 -0.0417901354 -0.1167106047
[116] -0.0323572431 -0.1196328483 -0.2921380322 -0.6736075924 0.6406988098
[121] -0.2397151857 0.0760679837 0.1911674745 -0.0826856140 -0.1861187915
[126] -0.1526913537 0.2659023826 -0.4243573519 0.2860078905 -0.7262670965
[131] -0.3680023908 -0.4611438458 0.4812293358 0.0015093671 -0.3409401388
[136] -0.1669303096 0.1449430035 0.2499698390 -0.3529295604 -0.2138243044
[141] 0.4929971262 -0.1220809676 0.1428854840 0.0182172122 -0.7254619690
[146] -0.3748206208 -0.0358090497 -0.1918098158 -0.3417844603 -0.3288212380
[151] -0.5297907897 0.2077379323 -0.3696233976 0.4149560506 -0.0052369281
[156] 0.2982467162 -0.2296158350 0.2648075726 -0.1114415219 -0.0704090851
[161] -0.0084209226 0.8371754251 0.1124599413 0.4851862047 -0.0603339512
[166] -0.0134623280 -0.2712911512 -0.0671035369 -0.0156180825 0.1231387011
[171] 0.0741530833 0.1917022354 0.0605950954 -0.1772608435 0.3911694390
[176] 0.1657747363 -0.2560549140 0.0843957701 0.0786420233 0.1879508400
[181] -0.2766256667 0.3024776761 0.1393391945 -0.0036247031 0.1853919612
[186] 0.7554620931 0.1975546033 0.0735097012 -0.3675299587 -0.0254113312
[191] -0.5445701508 -0.2061308703 0.0508427418 0.0028398745 -0.1454024045
[196] 0.6282892079 0.0508206244 -0.1670530986 0.0678536298 -0.7356017955
[201] -0.1954069232 0.2383405288 0.2217572066 -0.2312973804 -0.0633479152
[206] -0.2641526602 -0.5512558396 0.3116559406 0.6419550539 0.2328517259
[211] 0.0928579342 0.1546019615 0.5196659908 0.5645918438 -0.1749733499
[216] 0.3795922673 0.2457157484 0.5610622822 -0.1399262377 0.0962567299
[221] 0.3424004567 -0.0991095312 -0.0219449696 0.0648948085 -0.4377408479
[226] -0.0331661230 -0.1914171106 0.2239550098 0.0163793668 -0.5331649179
>
> proc.time()
user system elapsed
2.045 1.202 3.292
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R Under development (unstable) (2023-01-14 r83615) -- "Unsuffered Consequences"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-unknown-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: 0xaaaab67c5460>
> .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: 0xaaaab67c5460>
> .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: 0xaaaab67c5460>
> .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: 0xaaaab67c5460>
> 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: 0xaaaab67b4dd0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaaab67b4dd0>
> .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: 0xaaaab67b4dd0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaaab67b4dd0>
> .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: 0xaaaab67b4dd0>
> 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: 0xaaaab5f3e4f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaaab5f3e4f0>
> .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: 0xaaaab5f3e4f0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0xaaaab5f3e4f0>
> .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: 0xaaaab5f3e4f0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0xaaaab5f3e4f0>
> .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: 0xaaaab5f3e4f0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0xaaaab5f3e4f0>
> .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: 0xaaaab5f3e4f0>
> 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: 0xaaaab71b2390>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0xaaaab71b2390>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaaab71b2390>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaaab71b2390>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile277ebf61572df1" "BufferedMatrixFile277ebf7bb5083d"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile277ebf61572df1" "BufferedMatrixFile277ebf7bb5083d"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaaab783dd20>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaaab783dd20>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0xaaaab783dd20>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0xaaaab783dd20>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0xaaaab783dd20>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0xaaaab783dd20>
> .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: 0xaaaab70d85a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaaab70d85a0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0xaaaab70d85a0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0xaaaab70d85a0>
> 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: 0xaaaab646dc00>
> .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: 0xaaaab646dc00>
> rm(P)
>
> proc.time()
user system elapsed
0.338 0.052 0.374
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2023-01-14 r83615) -- "Unsuffered Consequences"
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Platform: aarch64-unknown-linux-gnu (64-bit)
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.312 0.048 0.345