| Back to Multiple platform build/check report for BioC 3.19: simplified long |
|
This page was generated on 2024-05-31 17:02:51 -0400 (Fri, 31 May 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4753 |
| kjohnson3 | macOS 13.6.5 Ventura | arm64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4464 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 249/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.68.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK |  | ||||||||
| kjohnson3 | macOS 13.6.5 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.68.0 |
| Command: /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings BufferedMatrix_1.68.0.tar.gz |
| StartedAt: 2024-05-31 01:51:33 -0400 (Fri, 31 May 2024) |
| EndedAt: 2024-05-31 01:51:58 -0400 (Fri, 31 May 2024) |
| EllapsedTime: 24.1 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings BufferedMatrix_1.68.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.4.0 (2024-04-24)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
* running under: Ubuntu 22.04.4 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.68.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.19-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
gcc -I"/home/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"/home/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
gcc -I"/home/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"/home/biocbuild/bbs-3.19-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c init_package.c -o init_package.o
gcc -shared -L/home/biocbuild/bbs-3.19-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.19-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.19-bioc/R/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.263 0.045 0.297
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 471778 25.2 1026221 54.9 643431 34.4
Vcells 871899 6.7 8388608 64.0 2046580 15.7
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri May 31 01:51:49 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri May 31 01:51:49 2024"
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
>
>
> RowMode(tmp2)
<pointer: 0x55b343c73210>
>
>
>
> 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] "Fri May 31 01:51:50 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri May 31 01:51:50 2024"
>
> ColMode(tmp2)
<pointer: 0x55b343c73210>
>
>
>
> ### 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,] 99.3470469 1.1464719 2.4196793 0.05387797
[2,] -0.2557478 0.6902386 0.1607653 -0.10353112
[3,] -0.5311733 0.6384974 -0.8700559 -0.10563874
[4,] 1.1869947 -1.9023386 0.5314897 -0.24382303
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.3470469 1.1464719 2.4196793 0.05387797
[2,] 0.2557478 0.6902386 0.1607653 0.10353112
[3,] 0.5311733 0.6384974 0.8700559 0.10563874
[4,] 1.1869947 1.9023386 0.5314897 0.24382303
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9672989 1.0707343 1.5555318 0.2321163
[2,] 0.5057151 0.8308060 0.4009555 0.3217625
[3,] 0.7288164 0.7990603 0.9327679 0.3250211
[4,] 1.0894929 1.3792529 0.7290334 0.4937844
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.02004 36.85381 42.97500 27.37504
[2,] 30.31290 33.99830 29.17032 28.32116
[3,] 32.81934 33.62910 35.19773 28.35585
[4,] 37.08192 40.69487 32.82182 30.18167
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x55b3431e1350>
> exp(tmp5)
<pointer: 0x55b3431e1350>
> log(tmp5,2)
<pointer: 0x55b3431e1350>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.2684
> Min(tmp5)
[1] 53.46313
> mean(tmp5)
[1] 73.45867
> Sum(tmp5)
[1] 14691.73
> Var(tmp5)
[1] 851.384
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.01838 69.85421 69.09276 69.64417 73.80120 72.56890 72.46938 70.41246
[9] 73.03001 72.69519
> rowSums(tmp5)
[1] 1820.368 1397.084 1381.855 1392.883 1476.024 1451.378 1449.388 1408.249
[9] 1460.600 1453.904
> rowVars(tmp5)
[1] 7883.02971 64.07940 90.37037 53.81104 75.13097 68.42142
[7] 39.14144 54.19272 120.10046 82.65878
> rowSd(tmp5)
[1] 88.786427 8.004961 9.506333 7.335601 8.667812 8.271724 6.256312
[8] 7.361571 10.959036 9.091688
> rowMax(tmp5)
[1] 466.26835 83.90197 83.54917 84.70104 87.16612 84.00794 85.65827
[8] 83.89023 93.21701 97.79473
> rowMin(tmp5)
[1] 56.97756 58.94678 54.61155 60.03457 57.50159 53.46313 64.86567 54.96779
[9] 55.08039 55.45155
>
> colMeans(tmp5)
[1] 113.19992 75.09226 74.05872 70.75533 73.77088 69.16623 72.62261
[8] 69.04969 72.33099 69.76935 65.95853 73.10397 75.03251 66.14934
[15] 72.34969 71.26536 68.60981 67.46926 78.54557 70.87335
> colSums(tmp5)
[1] 1131.9992 750.9226 740.5872 707.5533 737.7088 691.6623 726.2261
[8] 690.4969 723.3099 697.6935 659.5853 731.0397 750.3251 661.4934
[15] 723.4969 712.6536 686.0981 674.6926 785.4557 708.7335
> colVars(tmp5)
[1] 15439.60589 28.05284 103.11891 174.41629 67.86424 28.45831
[7] 110.45095 103.06873 74.43536 34.79744 100.14307 30.66873
[13] 42.68562 70.52654 16.48578 47.20947 77.76341 69.01181
[19] 73.22340 73.59913
> colSd(tmp5)
[1] 124.256211 5.296493 10.154748 13.206676 8.237976 5.334633
[7] 10.509565 10.152277 8.627593 5.898935 10.007151 5.537936
[13] 6.533423 8.398008 4.060269 6.870915 8.818356 8.307334
[19] 8.557067 8.578993
> colMax(tmp5)
[1] 466.26835 84.70104 90.59960 93.21701 82.32518 76.58687 85.65827
[8] 86.30382 83.59022 79.52417 83.90197 83.03834 83.24729 79.81750
[15] 79.90257 81.62387 81.58894 85.29741 97.79473 82.80501
> colMin(tmp5)
[1] 63.09233 69.99457 60.18463 56.97756 59.44431 60.90670 54.61155 53.46313
[9] 57.37762 61.03084 54.96779 64.94540 61.30007 55.08039 65.93149 59.84889
[17] 55.45155 57.39781 66.18754 59.17937
>
>
> ### 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] 91.01838 NA 69.09276 69.64417 73.80120 72.56890 72.46938 70.41246
[9] 73.03001 72.69519
> rowSums(tmp5)
[1] 1820.368 NA 1381.855 1392.883 1476.024 1451.378 1449.388 1408.249
[9] 1460.600 1453.904
> rowVars(tmp5)
[1] 7883.02971 67.59107 90.37037 53.81104 75.13097 68.42142
[7] 39.14144 54.19272 120.10046 82.65878
> rowSd(tmp5)
[1] 88.786427 8.221379 9.506333 7.335601 8.667812 8.271724 6.256312
[8] 7.361571 10.959036 9.091688
> rowMax(tmp5)
[1] 466.26835 NA 83.54917 84.70104 87.16612 84.00794 85.65827
[8] 83.89023 93.21701 97.79473
> rowMin(tmp5)
[1] 56.97756 NA 54.61155 60.03457 57.50159 53.46313 64.86567 54.96779
[9] 55.08039 55.45155
>
> colMeans(tmp5)
[1] 113.19992 NA 74.05872 70.75533 73.77088 69.16623 72.62261
[8] 69.04969 72.33099 69.76935 65.95853 73.10397 75.03251 66.14934
[15] 72.34969 71.26536 68.60981 67.46926 78.54557 70.87335
> colSums(tmp5)
[1] 1131.9992 NA 740.5872 707.5533 737.7088 691.6623 726.2261
[8] 690.4969 723.3099 697.6935 659.5853 731.0397 750.3251 661.4934
[15] 723.4969 712.6536 686.0981 674.6926 785.4557 708.7335
> colVars(tmp5)
[1] 15439.60589 NA 103.11891 174.41629 67.86424 28.45831
[7] 110.45095 103.06873 74.43536 34.79744 100.14307 30.66873
[13] 42.68562 70.52654 16.48578 47.20947 77.76341 69.01181
[19] 73.22340 73.59913
> colSd(tmp5)
[1] 124.256211 NA 10.154748 13.206676 8.237976 5.334633
[7] 10.509565 10.152277 8.627593 5.898935 10.007151 5.537936
[13] 6.533423 8.398008 4.060269 6.870915 8.818356 8.307334
[19] 8.557067 8.578993
> colMax(tmp5)
[1] 466.26835 NA 90.59960 93.21701 82.32518 76.58687 85.65827
[8] 86.30382 83.59022 79.52417 83.90197 83.03834 83.24729 79.81750
[15] 79.90257 81.62387 81.58894 85.29741 97.79473 82.80501
> colMin(tmp5)
[1] 63.09233 NA 60.18463 56.97756 59.44431 60.90670 54.61155 53.46313
[9] 57.37762 61.03084 54.96779 64.94540 61.30007 55.08039 65.93149 59.84889
[17] 55.45155 57.39781 66.18754 59.17937
>
> Max(tmp5,na.rm=TRUE)
[1] 466.2684
> Min(tmp5,na.rm=TRUE)
[1] 53.46313
> mean(tmp5,na.rm=TRUE)
[1] 73.47221
> Sum(tmp5,na.rm=TRUE)
[1] 14620.97
> Var(tmp5,na.rm=TRUE)
[1] 855.647
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.01838 69.80638 69.09276 69.64417 73.80120 72.56890 72.46938 70.41246
[9] 73.03001 72.69519
> rowSums(tmp5,na.rm=TRUE)
[1] 1820.368 1326.321 1381.855 1392.883 1476.024 1451.378 1449.388 1408.249
[9] 1460.600 1453.904
> rowVars(tmp5,na.rm=TRUE)
[1] 7883.02971 67.59107 90.37037 53.81104 75.13097 68.42142
[7] 39.14144 54.19272 120.10046 82.65878
> rowSd(tmp5,na.rm=TRUE)
[1] 88.786427 8.221379 9.506333 7.335601 8.667812 8.271724 6.256312
[8] 7.361571 10.959036 9.091688
> rowMax(tmp5,na.rm=TRUE)
[1] 466.26835 83.90197 83.54917 84.70104 87.16612 84.00794 85.65827
[8] 83.89023 93.21701 97.79473
> rowMin(tmp5,na.rm=TRUE)
[1] 56.97756 58.94678 54.61155 60.03457 57.50159 53.46313 64.86567 54.96779
[9] 55.08039 55.45155
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.19992 75.57329 74.05872 70.75533 73.77088 69.16623 72.62261
[8] 69.04969 72.33099 69.76935 65.95853 73.10397 75.03251 66.14934
[15] 72.34969 71.26536 68.60981 67.46926 78.54557 70.87335
> colSums(tmp5,na.rm=TRUE)
[1] 1131.9992 680.1596 740.5872 707.5533 737.7088 691.6623 726.2261
[8] 690.4969 723.3099 697.6935 659.5853 731.0397 750.3251 661.4934
[15] 723.4969 712.6536 686.0981 674.6926 785.4557 708.7335
> colVars(tmp5,na.rm=TRUE)
[1] 15439.60589 28.95633 103.11891 174.41629 67.86424 28.45831
[7] 110.45095 103.06873 74.43536 34.79744 100.14307 30.66873
[13] 42.68562 70.52654 16.48578 47.20947 77.76341 69.01181
[19] 73.22340 73.59913
> colSd(tmp5,na.rm=TRUE)
[1] 124.256211 5.381108 10.154748 13.206676 8.237976 5.334633
[7] 10.509565 10.152277 8.627593 5.898935 10.007151 5.537936
[13] 6.533423 8.398008 4.060269 6.870915 8.818356 8.307334
[19] 8.557067 8.578993
> colMax(tmp5,na.rm=TRUE)
[1] 466.26835 84.70104 90.59960 93.21701 82.32518 76.58687 85.65827
[8] 86.30382 83.59022 79.52417 83.90197 83.03834 83.24729 79.81750
[15] 79.90257 81.62387 81.58894 85.29741 97.79473 82.80501
> colMin(tmp5,na.rm=TRUE)
[1] 63.09233 69.99457 60.18463 56.97756 59.44431 60.90670 54.61155 53.46313
[9] 57.37762 61.03084 54.96779 64.94540 61.30007 55.08039 65.93149 59.84889
[17] 55.45155 57.39781 66.18754 59.17937
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.01838 NaN 69.09276 69.64417 73.80120 72.56890 72.46938 70.41246
[9] 73.03001 72.69519
> rowSums(tmp5,na.rm=TRUE)
[1] 1820.368 0.000 1381.855 1392.883 1476.024 1451.378 1449.388 1408.249
[9] 1460.600 1453.904
> rowVars(tmp5,na.rm=TRUE)
[1] 7883.02971 NA 90.37037 53.81104 75.13097 68.42142
[7] 39.14144 54.19272 120.10046 82.65878
> rowSd(tmp5,na.rm=TRUE)
[1] 88.786427 NA 9.506333 7.335601 8.667812 8.271724 6.256312
[8] 7.361571 10.959036 9.091688
> rowMax(tmp5,na.rm=TRUE)
[1] 466.26835 NA 83.54917 84.70104 87.16612 84.00794 85.65827
[8] 83.89023 93.21701 97.79473
> rowMin(tmp5,na.rm=TRUE)
[1] 56.97756 NA 54.61155 60.03457 57.50159 53.46313 64.86567 54.96779
[9] 55.08039 55.45155
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 118.76743 NaN 75.54144 72.06739 72.82040 69.61521 71.49185
[8] 70.03467 72.56835 70.55091 63.96481 73.77849 74.68766 66.36557
[15] 72.30187 72.21159 67.94892 67.63312 78.59044 70.66983
> colSums(tmp5,na.rm=TRUE)
[1] 1068.9069 0.0000 679.8730 648.6065 655.3836 626.5369 643.4267
[8] 630.3121 653.1152 634.9582 575.6833 664.0064 672.1889 597.2901
[15] 650.7168 649.9043 611.5403 608.6980 707.3140 636.0284
> colVars(tmp5,na.rm=TRUE)
[1] 17020.83845 NA 91.27598 176.85140 66.18393 29.74779
[7] 109.87303 105.03757 83.10593 32.27519 67.94326 29.38384
[13] 46.68346 78.81639 18.52078 43.03790 82.57023 77.33624
[19] 82.35368 82.33304
> colSd(tmp5,na.rm=TRUE)
[1] 130.463935 NA 9.553846 13.298549 8.135351 5.454153
[7] 10.482033 10.248784 9.116245 5.681126 8.242770 5.420686
[13] 6.832529 8.877860 4.303578 6.560328 9.086816 8.794102
[19] 9.074893 9.073755
> colMax(tmp5,na.rm=TRUE)
[1] 466.26835 -Inf 90.59960 93.21701 82.02568 76.58687 85.65827
[8] 86.30382 83.59022 79.52417 79.92556 83.03834 83.24729 79.81750
[15] 79.90257 81.62387 81.58894 85.29741 97.79473 82.80501
> colMin(tmp5,na.rm=TRUE)
[1] 68.04558 Inf 60.18463 56.97756 59.44431 60.90670 54.61155 53.46313
[9] 57.37762 61.03084 54.96779 64.94540 61.30007 55.08039 65.93149 59.84889
[17] 55.45155 57.39781 66.18754 59.17937
>
>
>
>
> 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] 132.2298 261.8379 186.9958 499.8591 358.1450 335.7775 205.6439 226.4381
[9] 142.4934 233.6725
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 132.2298 261.8379 186.9958 499.8591 358.1450 335.7775 205.6439 226.4381
[9] 142.4934 233.6725
>
>
>
> 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 -2.842171e-14 -1.421085e-14 -8.526513e-14
[6] 5.684342e-14 -3.197442e-14 1.705303e-13 4.263256e-14 8.526513e-14
[11] -1.421085e-13 -2.842171e-14 0.000000e+00 -1.705303e-13 8.526513e-14
[16] 0.000000e+00 -8.526513e-14 1.136868e-13 -2.842171e-14 -1.421085e-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)
+ }
9 5
1 1
5 7
9 20
3 12
3 20
5 1
2 8
2 7
5 7
8 14
8 1
2 19
8 17
5 5
2 10
1 8
7 12
5 3
8 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] 2.394164
> Min(tmp)
[1] -1.926865
> mean(tmp)
[1] 0.04644184
> Sum(tmp)
[1] 4.644184
> Var(tmp)
[1] 0.7799264
>
> rowMeans(tmp)
[1] 0.04644184
> rowSums(tmp)
[1] 4.644184
> rowVars(tmp)
[1] 0.7799264
> rowSd(tmp)
[1] 0.8831344
> rowMax(tmp)
[1] 2.394164
> rowMin(tmp)
[1] -1.926865
>
> colMeans(tmp)
[1] -1.56359827 0.05491150 -0.55202524 -0.02361119 -1.03728783 -0.23704382
[7] 1.70425364 0.77166750 0.50547432 -0.93695100 0.72266682 0.59584563
[13] -0.57231756 -0.61462880 -0.30399246 0.48396819 0.14187552 -0.08087577
[19] -0.18527367 -0.57782313 0.25060956 -0.77882972 -0.17228990 -0.95369271
[25] -0.47877250 -0.37811051 1.31643218 -0.35220667 0.39219384 0.51854917
[31] 0.10774675 -0.33719182 -0.89220818 1.03245973 0.93058265 1.30223766
[37] -1.32244586 -0.68484639 1.48616832 0.70521693 -0.11028946 -1.78428703
[43] -0.63052661 1.13893307 -1.05359198 1.05772636 0.93508936 1.30456232
[49] 0.23003682 0.36222945 -0.23728682 0.68905417 0.16538713 -0.73441071
[55] 1.43068300 -1.92686510 0.80563494 1.05758107 2.15559975 -0.61737769
[61] -1.02896095 0.22574572 -0.55269918 -0.31264609 -0.90449877 -1.44492956
[67] 0.87958836 0.14838054 0.11278551 0.59257933 0.85950591 0.31603500
[73] 0.51973387 -0.18870006 -0.29118658 -0.78834078 -0.83456382 -1.35864680
[79] 0.43022649 1.19745548 -0.81039533 0.54513400 -0.32286212 -0.50422629
[85] -0.25563343 -1.10869119 2.39416353 -0.46837911 -0.89311766 2.09392467
[91] 0.66032079 0.67732389 0.55984504 -1.10145428 0.64317799 -0.19299131
[97] -0.10489223 -0.09622737 0.07380417 1.05377810
> colSums(tmp)
[1] -1.56359827 0.05491150 -0.55202524 -0.02361119 -1.03728783 -0.23704382
[7] 1.70425364 0.77166750 0.50547432 -0.93695100 0.72266682 0.59584563
[13] -0.57231756 -0.61462880 -0.30399246 0.48396819 0.14187552 -0.08087577
[19] -0.18527367 -0.57782313 0.25060956 -0.77882972 -0.17228990 -0.95369271
[25] -0.47877250 -0.37811051 1.31643218 -0.35220667 0.39219384 0.51854917
[31] 0.10774675 -0.33719182 -0.89220818 1.03245973 0.93058265 1.30223766
[37] -1.32244586 -0.68484639 1.48616832 0.70521693 -0.11028946 -1.78428703
[43] -0.63052661 1.13893307 -1.05359198 1.05772636 0.93508936 1.30456232
[49] 0.23003682 0.36222945 -0.23728682 0.68905417 0.16538713 -0.73441071
[55] 1.43068300 -1.92686510 0.80563494 1.05758107 2.15559975 -0.61737769
[61] -1.02896095 0.22574572 -0.55269918 -0.31264609 -0.90449877 -1.44492956
[67] 0.87958836 0.14838054 0.11278551 0.59257933 0.85950591 0.31603500
[73] 0.51973387 -0.18870006 -0.29118658 -0.78834078 -0.83456382 -1.35864680
[79] 0.43022649 1.19745548 -0.81039533 0.54513400 -0.32286212 -0.50422629
[85] -0.25563343 -1.10869119 2.39416353 -0.46837911 -0.89311766 2.09392467
[91] 0.66032079 0.67732389 0.55984504 -1.10145428 0.64317799 -0.19299131
[97] -0.10489223 -0.09622737 0.07380417 1.05377810
> 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] -1.56359827 0.05491150 -0.55202524 -0.02361119 -1.03728783 -0.23704382
[7] 1.70425364 0.77166750 0.50547432 -0.93695100 0.72266682 0.59584563
[13] -0.57231756 -0.61462880 -0.30399246 0.48396819 0.14187552 -0.08087577
[19] -0.18527367 -0.57782313 0.25060956 -0.77882972 -0.17228990 -0.95369271
[25] -0.47877250 -0.37811051 1.31643218 -0.35220667 0.39219384 0.51854917
[31] 0.10774675 -0.33719182 -0.89220818 1.03245973 0.93058265 1.30223766
[37] -1.32244586 -0.68484639 1.48616832 0.70521693 -0.11028946 -1.78428703
[43] -0.63052661 1.13893307 -1.05359198 1.05772636 0.93508936 1.30456232
[49] 0.23003682 0.36222945 -0.23728682 0.68905417 0.16538713 -0.73441071
[55] 1.43068300 -1.92686510 0.80563494 1.05758107 2.15559975 -0.61737769
[61] -1.02896095 0.22574572 -0.55269918 -0.31264609 -0.90449877 -1.44492956
[67] 0.87958836 0.14838054 0.11278551 0.59257933 0.85950591 0.31603500
[73] 0.51973387 -0.18870006 -0.29118658 -0.78834078 -0.83456382 -1.35864680
[79] 0.43022649 1.19745548 -0.81039533 0.54513400 -0.32286212 -0.50422629
[85] -0.25563343 -1.10869119 2.39416353 -0.46837911 -0.89311766 2.09392467
[91] 0.66032079 0.67732389 0.55984504 -1.10145428 0.64317799 -0.19299131
[97] -0.10489223 -0.09622737 0.07380417 1.05377810
> colMin(tmp)
[1] -1.56359827 0.05491150 -0.55202524 -0.02361119 -1.03728783 -0.23704382
[7] 1.70425364 0.77166750 0.50547432 -0.93695100 0.72266682 0.59584563
[13] -0.57231756 -0.61462880 -0.30399246 0.48396819 0.14187552 -0.08087577
[19] -0.18527367 -0.57782313 0.25060956 -0.77882972 -0.17228990 -0.95369271
[25] -0.47877250 -0.37811051 1.31643218 -0.35220667 0.39219384 0.51854917
[31] 0.10774675 -0.33719182 -0.89220818 1.03245973 0.93058265 1.30223766
[37] -1.32244586 -0.68484639 1.48616832 0.70521693 -0.11028946 -1.78428703
[43] -0.63052661 1.13893307 -1.05359198 1.05772636 0.93508936 1.30456232
[49] 0.23003682 0.36222945 -0.23728682 0.68905417 0.16538713 -0.73441071
[55] 1.43068300 -1.92686510 0.80563494 1.05758107 2.15559975 -0.61737769
[61] -1.02896095 0.22574572 -0.55269918 -0.31264609 -0.90449877 -1.44492956
[67] 0.87958836 0.14838054 0.11278551 0.59257933 0.85950591 0.31603500
[73] 0.51973387 -0.18870006 -0.29118658 -0.78834078 -0.83456382 -1.35864680
[79] 0.43022649 1.19745548 -0.81039533 0.54513400 -0.32286212 -0.50422629
[85] -0.25563343 -1.10869119 2.39416353 -0.46837911 -0.89311766 2.09392467
[91] 0.66032079 0.67732389 0.55984504 -1.10145428 0.64317799 -0.19299131
[97] -0.10489223 -0.09622737 0.07380417 1.05377810
> colMedians(tmp)
[1] -1.56359827 0.05491150 -0.55202524 -0.02361119 -1.03728783 -0.23704382
[7] 1.70425364 0.77166750 0.50547432 -0.93695100 0.72266682 0.59584563
[13] -0.57231756 -0.61462880 -0.30399246 0.48396819 0.14187552 -0.08087577
[19] -0.18527367 -0.57782313 0.25060956 -0.77882972 -0.17228990 -0.95369271
[25] -0.47877250 -0.37811051 1.31643218 -0.35220667 0.39219384 0.51854917
[31] 0.10774675 -0.33719182 -0.89220818 1.03245973 0.93058265 1.30223766
[37] -1.32244586 -0.68484639 1.48616832 0.70521693 -0.11028946 -1.78428703
[43] -0.63052661 1.13893307 -1.05359198 1.05772636 0.93508936 1.30456232
[49] 0.23003682 0.36222945 -0.23728682 0.68905417 0.16538713 -0.73441071
[55] 1.43068300 -1.92686510 0.80563494 1.05758107 2.15559975 -0.61737769
[61] -1.02896095 0.22574572 -0.55269918 -0.31264609 -0.90449877 -1.44492956
[67] 0.87958836 0.14838054 0.11278551 0.59257933 0.85950591 0.31603500
[73] 0.51973387 -0.18870006 -0.29118658 -0.78834078 -0.83456382 -1.35864680
[79] 0.43022649 1.19745548 -0.81039533 0.54513400 -0.32286212 -0.50422629
[85] -0.25563343 -1.10869119 2.39416353 -0.46837911 -0.89311766 2.09392467
[91] 0.66032079 0.67732389 0.55984504 -1.10145428 0.64317799 -0.19299131
[97] -0.10489223 -0.09622737 0.07380417 1.05377810
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.563598 0.0549115 -0.5520252 -0.02361119 -1.037288 -0.2370438 1.704254
[2,] -1.563598 0.0549115 -0.5520252 -0.02361119 -1.037288 -0.2370438 1.704254
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.7716675 0.5054743 -0.936951 0.7226668 0.5958456 -0.5723176 -0.6146288
[2,] 0.7716675 0.5054743 -0.936951 0.7226668 0.5958456 -0.5723176 -0.6146288
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.3039925 0.4839682 0.1418755 -0.08087577 -0.1852737 -0.5778231 0.2506096
[2,] -0.3039925 0.4839682 0.1418755 -0.08087577 -0.1852737 -0.5778231 0.2506096
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.7788297 -0.1722899 -0.9536927 -0.4787725 -0.3781105 1.316432 -0.3522067
[2,] -0.7788297 -0.1722899 -0.9536927 -0.4787725 -0.3781105 1.316432 -0.3522067
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.3921938 0.5185492 0.1077467 -0.3371918 -0.8922082 1.03246 0.9305827
[2,] 0.3921938 0.5185492 0.1077467 -0.3371918 -0.8922082 1.03246 0.9305827
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.302238 -1.322446 -0.6848464 1.486168 0.7052169 -0.1102895 -1.784287
[2,] 1.302238 -1.322446 -0.6848464 1.486168 0.7052169 -0.1102895 -1.784287
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.6305266 1.138933 -1.053592 1.057726 0.9350894 1.304562 0.2300368
[2,] -0.6305266 1.138933 -1.053592 1.057726 0.9350894 1.304562 0.2300368
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.3622295 -0.2372868 0.6890542 0.1653871 -0.7344107 1.430683 -1.926865
[2,] 0.3622295 -0.2372868 0.6890542 0.1653871 -0.7344107 1.430683 -1.926865
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.8056349 1.057581 2.1556 -0.6173777 -1.028961 0.2257457 -0.5526992
[2,] 0.8056349 1.057581 2.1556 -0.6173777 -1.028961 0.2257457 -0.5526992
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.3126461 -0.9044988 -1.44493 0.8795884 0.1483805 0.1127855 0.5925793
[2,] -0.3126461 -0.9044988 -1.44493 0.8795884 0.1483805 0.1127855 0.5925793
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.8595059 0.316035 0.5197339 -0.1887001 -0.2911866 -0.7883408 -0.8345638
[2,] 0.8595059 0.316035 0.5197339 -0.1887001 -0.2911866 -0.7883408 -0.8345638
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -1.358647 0.4302265 1.197455 -0.8103953 0.545134 -0.3228621 -0.5042263
[2,] -1.358647 0.4302265 1.197455 -0.8103953 0.545134 -0.3228621 -0.5042263
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.2556334 -1.108691 2.394164 -0.4683791 -0.8931177 2.093925 0.6603208
[2,] -0.2556334 -1.108691 2.394164 -0.4683791 -0.8931177 2.093925 0.6603208
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.6773239 0.559845 -1.101454 0.643178 -0.1929913 -0.1048922 -0.09622737
[2,] 0.6773239 0.559845 -1.101454 0.643178 -0.1929913 -0.1048922 -0.09622737
[,99] [,100]
[1,] 0.07380417 1.053778
[2,] 0.07380417 1.053778
>
>
> Max(tmp2)
[1] 2.730212
> Min(tmp2)
[1] -2.466818
> mean(tmp2)
[1] 0.008134281
> Sum(tmp2)
[1] 0.8134281
> Var(tmp2)
[1] 0.9721496
>
> rowMeans(tmp2)
[1] -1.01111850 -0.55697320 -0.15552885 -1.93918387 -0.19059300 -0.33791147
[7] -0.72658681 -0.06678857 0.17463856 1.04662535 -0.07299987 0.12551146
[13] 1.01821369 0.01713461 -0.45072595 0.77795841 1.19765240 1.18381617
[19] 0.18730259 -2.46681814 -1.39360509 1.62363754 0.06505744 -0.08433185
[25] 0.50029571 -1.99596891 0.79348809 1.29085229 -0.22588779 0.51784148
[31] 0.29023549 0.02880819 -0.98945595 0.04781142 -0.42429347 1.01277128
[37] 0.55156764 -0.61731827 -0.41112305 -1.85650233 -0.42691079 -0.20274932
[43] 0.42205351 -1.09437743 -0.06649912 -0.31487434 1.25616533 1.15645284
[49] 0.39633498 -1.13589143 -0.69795091 -0.28125907 -0.32098924 -0.88012538
[55] -2.07588099 0.69001327 -0.28321150 -0.75059213 -0.11362526 1.03200846
[61] 0.43445337 0.45030876 -0.65791231 1.21610595 1.63641621 -0.02352070
[67] 0.76219157 0.69777907 -0.08665161 2.73021193 -1.00773446 1.09183054
[73] 0.74999842 -0.04669692 0.25232234 -0.50829266 2.54722767 -0.99342542
[79] 0.61200509 -0.68966603 0.86943529 -1.61681695 0.49473186 0.22304660
[85] -1.44619171 1.16696926 -0.08148290 -0.15047317 -1.34602958 0.03509051
[91] 0.62750536 -1.62351610 1.84503497 0.96064259 -1.39652431 0.76670477
[97] 0.67017626 -0.52185214 0.63454887 -1.25011855
> rowSums(tmp2)
[1] -1.01111850 -0.55697320 -0.15552885 -1.93918387 -0.19059300 -0.33791147
[7] -0.72658681 -0.06678857 0.17463856 1.04662535 -0.07299987 0.12551146
[13] 1.01821369 0.01713461 -0.45072595 0.77795841 1.19765240 1.18381617
[19] 0.18730259 -2.46681814 -1.39360509 1.62363754 0.06505744 -0.08433185
[25] 0.50029571 -1.99596891 0.79348809 1.29085229 -0.22588779 0.51784148
[31] 0.29023549 0.02880819 -0.98945595 0.04781142 -0.42429347 1.01277128
[37] 0.55156764 -0.61731827 -0.41112305 -1.85650233 -0.42691079 -0.20274932
[43] 0.42205351 -1.09437743 -0.06649912 -0.31487434 1.25616533 1.15645284
[49] 0.39633498 -1.13589143 -0.69795091 -0.28125907 -0.32098924 -0.88012538
[55] -2.07588099 0.69001327 -0.28321150 -0.75059213 -0.11362526 1.03200846
[61] 0.43445337 0.45030876 -0.65791231 1.21610595 1.63641621 -0.02352070
[67] 0.76219157 0.69777907 -0.08665161 2.73021193 -1.00773446 1.09183054
[73] 0.74999842 -0.04669692 0.25232234 -0.50829266 2.54722767 -0.99342542
[79] 0.61200509 -0.68966603 0.86943529 -1.61681695 0.49473186 0.22304660
[85] -1.44619171 1.16696926 -0.08148290 -0.15047317 -1.34602958 0.03509051
[91] 0.62750536 -1.62351610 1.84503497 0.96064259 -1.39652431 0.76670477
[97] 0.67017626 -0.52185214 0.63454887 -1.25011855
> 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] -1.01111850 -0.55697320 -0.15552885 -1.93918387 -0.19059300 -0.33791147
[7] -0.72658681 -0.06678857 0.17463856 1.04662535 -0.07299987 0.12551146
[13] 1.01821369 0.01713461 -0.45072595 0.77795841 1.19765240 1.18381617
[19] 0.18730259 -2.46681814 -1.39360509 1.62363754 0.06505744 -0.08433185
[25] 0.50029571 -1.99596891 0.79348809 1.29085229 -0.22588779 0.51784148
[31] 0.29023549 0.02880819 -0.98945595 0.04781142 -0.42429347 1.01277128
[37] 0.55156764 -0.61731827 -0.41112305 -1.85650233 -0.42691079 -0.20274932
[43] 0.42205351 -1.09437743 -0.06649912 -0.31487434 1.25616533 1.15645284
[49] 0.39633498 -1.13589143 -0.69795091 -0.28125907 -0.32098924 -0.88012538
[55] -2.07588099 0.69001327 -0.28321150 -0.75059213 -0.11362526 1.03200846
[61] 0.43445337 0.45030876 -0.65791231 1.21610595 1.63641621 -0.02352070
[67] 0.76219157 0.69777907 -0.08665161 2.73021193 -1.00773446 1.09183054
[73] 0.74999842 -0.04669692 0.25232234 -0.50829266 2.54722767 -0.99342542
[79] 0.61200509 -0.68966603 0.86943529 -1.61681695 0.49473186 0.22304660
[85] -1.44619171 1.16696926 -0.08148290 -0.15047317 -1.34602958 0.03509051
[91] 0.62750536 -1.62351610 1.84503497 0.96064259 -1.39652431 0.76670477
[97] 0.67017626 -0.52185214 0.63454887 -1.25011855
> rowMin(tmp2)
[1] -1.01111850 -0.55697320 -0.15552885 -1.93918387 -0.19059300 -0.33791147
[7] -0.72658681 -0.06678857 0.17463856 1.04662535 -0.07299987 0.12551146
[13] 1.01821369 0.01713461 -0.45072595 0.77795841 1.19765240 1.18381617
[19] 0.18730259 -2.46681814 -1.39360509 1.62363754 0.06505744 -0.08433185
[25] 0.50029571 -1.99596891 0.79348809 1.29085229 -0.22588779 0.51784148
[31] 0.29023549 0.02880819 -0.98945595 0.04781142 -0.42429347 1.01277128
[37] 0.55156764 -0.61731827 -0.41112305 -1.85650233 -0.42691079 -0.20274932
[43] 0.42205351 -1.09437743 -0.06649912 -0.31487434 1.25616533 1.15645284
[49] 0.39633498 -1.13589143 -0.69795091 -0.28125907 -0.32098924 -0.88012538
[55] -2.07588099 0.69001327 -0.28321150 -0.75059213 -0.11362526 1.03200846
[61] 0.43445337 0.45030876 -0.65791231 1.21610595 1.63641621 -0.02352070
[67] 0.76219157 0.69777907 -0.08665161 2.73021193 -1.00773446 1.09183054
[73] 0.74999842 -0.04669692 0.25232234 -0.50829266 2.54722767 -0.99342542
[79] 0.61200509 -0.68966603 0.86943529 -1.61681695 0.49473186 0.22304660
[85] -1.44619171 1.16696926 -0.08148290 -0.15047317 -1.34602958 0.03509051
[91] 0.62750536 -1.62351610 1.84503497 0.96064259 -1.39652431 0.76670477
[97] 0.67017626 -0.52185214 0.63454887 -1.25011855
>
> colMeans(tmp2)
[1] 0.008134281
> colSums(tmp2)
[1] 0.8134281
> colVars(tmp2)
[1] 0.9721496
> colSd(tmp2)
[1] 0.9859765
> colMax(tmp2)
[1] 2.730212
> colMin(tmp2)
[1] -2.466818
> colMedians(tmp2)
[1] -0.03510881
> colRanges(tmp2)
[,1]
[1,] -2.466818
[2,] 2.730212
>
> 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] -2.3210549 4.0166164 0.1267087 -0.4750805 -4.3492604 0.3705803
[7] -6.4458902 1.2207390 2.9124530 0.4921429
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.1213103
[2,] -1.0494689
[3,] -0.3961251
[4,] 0.1607948
[5,] 2.0973977
>
> rowApply(tmp,sum)
[1] -0.365557 1.210785 3.814417 2.409198 -3.024447 -6.538181 -1.085294
[8] -1.669896 0.311345 0.485585
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 1 10 9 2 9 3 4 1 4
[2,] 9 7 9 1 10 7 5 8 5 5
[3,] 10 5 3 5 8 8 10 3 4 7
[4,] 8 8 1 8 4 1 6 5 8 6
[5,] 1 3 5 4 5 2 4 6 9 3
[6,] 5 4 6 6 7 4 8 10 3 8
[7,] 3 2 2 10 3 5 1 1 2 2
[8,] 2 9 7 2 9 6 7 2 7 9
[9,] 4 6 4 7 6 3 9 7 10 10
[10,] 6 10 8 3 1 10 2 9 6 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.3545756 -2.2848959 1.1831662 2.3633473 -0.8965437 1.1073550
[7] 2.3127740 2.4185936 0.3778802 -0.2502381 -2.1243083 2.3701803
[13] -4.1665925 0.4217876 -0.5674651 1.2080392 -2.2405897 -2.9819135
[19] 3.6042417 -0.8951412
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1224066
[2,] -0.5261097
[3,] -0.1568176
[4,] 0.7219035
[5,] 1.4380061
>
> rowApply(tmp,sum)
[1] -2.2508943 -0.6758540 -0.2571857 3.4482949 1.0498919
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 20 3 11 16 4
[2,] 1 8 19 2 7
[3,] 18 13 12 10 3
[4,] 17 18 18 5 6
[5,] 11 1 15 3 18
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.4380061 -2.19400981 1.1978403 0.6080102 0.03898809 0.28100805
[2,] -1.1224066 -0.32052535 0.2372580 1.1125570 -1.74204120 1.71811130
[3,] -0.1568176 1.26981199 0.1156315 1.1201902 0.80670085 -1.44995984
[4,] 0.7219035 -1.00592336 0.3644238 -0.3031553 -0.80571108 0.57129704
[5,] -0.5261097 -0.03424933 -0.7319874 -0.1742548 0.80551967 -0.01310156
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.2264420 1.2563437 0.1843303 -1.82736119 -1.4916568 -0.4140968
[2,] 0.8412537 -0.1514789 0.1431835 -0.02158902 -1.0161070 1.8944151
[3,] 0.2159423 0.9302620 -0.8984960 1.06361668 -0.5841813 -0.4256348
[4,] 0.9134608 -0.1896045 -0.2184719 0.33577877 0.7546098 0.6493339
[5,] 0.1156752 0.5730713 1.1673344 0.19931663 0.2130270 0.6661630
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.9731780 0.02752846 -0.5550476 0.22080119 0.02926961 -0.3426811
[2,] -1.7183649 0.23739323 -0.4760009 -0.05312031 -0.66496257 0.5785672
[3,] -0.4829662 -0.67705778 -0.6524465 -0.67419194 0.47530092 -1.5198790
[4,] -1.9292999 0.70586487 0.4215184 1.47402654 -0.62602482 -0.2085128
[5,] 0.9372165 0.12805887 0.6945116 0.24052369 -1.45417284 -1.4894078
[,19] [,20]
[1,] -0.02896569 0.06753474
[2,] 0.56712636 -0.71912275
[3,] 1.68738659 -0.42039761
[4,] 1.14338383 0.67939746
[5,] 0.23531062 -0.50255302
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 645 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 559 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 1.711948 -0.959949 -0.4264526 -0.08548261 -1.246337 0.759464 -0.5756586
col8 col9 col10 col11 col12 col13 col14
row1 -0.9543638 -0.8520401 -0.4905851 1.281778 -0.4232354 1.262 -0.2820225
col15 col16 col17 col18 col19 col20
row1 0.7404247 -0.9981066 0.4974124 0.392093 1.400905 -1.719788
> tmp[,"col10"]
col10
row1 -0.4905851
row2 0.4331531
row3 -1.5452509
row4 -1.1713477
row5 -0.3028487
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 1.7119484 -0.959948992 -0.4264526 -0.08548261 -1.2463373 0.7594640
row5 0.9930151 0.003394664 -1.7359099 -0.32618221 0.3325111 -0.4367148
col7 col8 col9 col10 col11 col12
row1 -0.5756586 -0.9543638 -0.8520401 -0.4905851 1.28177835 -0.4232354
row5 -0.8416358 1.9982251 1.2879911 -0.3028487 -0.03957866 -1.0943504
col13 col14 col15 col16 col17 col18 col19
row1 1.262000 -0.2820225 0.7404247 -0.9981066 0.4974124 0.3920930 1.4009051
row5 2.249778 -1.0413108 -0.4362416 -0.1690046 0.4791213 -0.5444236 -0.8961575
col20
row1 -1.7197881
row5 0.2153449
> tmp[,c("col6","col20")]
col6 col20
row1 0.7594640 -1.719788078
row2 0.5119852 -0.582527926
row3 0.5626579 0.003900029
row4 0.2850949 0.204122709
row5 -0.4367148 0.215344895
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.7594640 -1.7197881
row5 -0.4367148 0.2153449
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.52784 49.87883 50.29584 50.49232 48.57438 105.1959 48.51612 49.75043
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.11055 50.10316 50.36262 49.19778 49.7971 50.00539 50.34326 49.40939
col17 col18 col19 col20
row1 49.44578 50.08295 49.57835 105.9673
> tmp[,"col10"]
col10
row1 50.10316
row2 31.85884
row3 30.53592
row4 31.88655
row5 50.04863
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.52784 49.87883 50.29584 50.49232 48.57438 105.1959 48.51612 49.75043
row5 49.81626 49.40687 51.32752 50.23772 51.98614 103.4672 51.84969 49.35608
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.11055 50.10316 50.36262 49.19778 49.79710 50.00539 50.34326 49.40939
row5 49.55005 50.04863 48.97053 51.64753 50.92492 52.51087 49.89216 49.70921
col17 col18 col19 col20
row1 49.44578 50.08295 49.57835 105.9673
row5 49.86270 50.06246 49.68483 105.3301
> tmp[,c("col6","col20")]
col6 col20
row1 105.19586 105.96734
row2 75.01846 75.19418
row3 74.01405 75.41170
row4 74.51947 74.31630
row5 103.46722 105.33007
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.1959 105.9673
row5 103.4672 105.3301
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.1959 105.9673
row5 103.4672 105.3301
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.7792765
[2,] 1.3457156
[3,] 0.2752048
[4,] -0.4798530
[5,] -0.6040869
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.1564493 1.36443115
[2,] -0.5813661 -0.04014445
[3,] -0.5362591 -0.16634969
[4,] 1.2525729 1.09277923
[5,] 0.6488432 -1.18549956
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.2099377 1.8005400
[2,] 1.4002461 -1.3108956
[3,] 1.4823887 -0.8237070
[4,] -0.6754015 0.2398302
[5,] 0.9182802 -0.1361080
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.209938
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.209938
[2,] 1.400246
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 1.051917 1.6177428 -0.8813233 0.08314417 -0.04693943 0.06668868
row1 1.475749 -0.8569985 -0.3630112 0.37424166 -2.15180500 0.95822472
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -1.9163555 2.3933078 -0.4388965 0.2665989 1.4355042 0.8298994 1.99761581
row1 0.7960961 0.3321575 0.8514749 0.6302310 -0.2212047 0.3280170 0.09833081
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 0.2318782 0.4137170 -1.8133675 -1.4336345 -0.2985351 1.487952 0.08530958
row1 -1.4994081 -0.8484571 0.2359821 0.8945034 -0.7625974 1.176100 0.29130053
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
row2 1.20875 -2.195828 2.271064 1.2572 1.146364 -1.043267 -0.7277871 -0.2600524
[,9] [,10]
row2 0.8039734 -0.3825327
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -1.58687 -0.5654451 1.563343 -0.7741684 2.367736 1.241679 -0.3779457
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.5516336 -0.1273606 0.4388466 1.238965 1.262067 -1.714848 -2.65744
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.9455962 1.367341 0.9261052 -2.755254 -1.167124 0.07595868
>
>
> 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: 0x55b3452ec9f0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM4566e4664ca86"
[2] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM4566e7624ec95"
[3] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM4566e446c413b"
[4] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM4566e288e601a"
[5] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM4566e7df0b75b"
[6] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM4566e563e49e2"
[7] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM4566e7e08a7f3"
[8] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM4566e5176eb40"
[9] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM4566e583a3a6a"
[10] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM4566e5bb26b79"
[11] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM4566e1682c3d5"
[12] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM4566e68dab593"
[13] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM4566e2330cc07"
[14] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM4566e2fe942db"
[15] "/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BM4566e7d0c1781"
>
>
> ### 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: 0x55b34382c890>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x55b34382c890>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x55b34382c890>
> rowMedians(tmp)
[1] 0.0205249616 0.3036630990 -0.3360361771 0.0115479170 0.0951042251
[6] -0.0271463518 -0.2229319175 0.2072970377 -0.0848920264 0.0324263345
[11] 0.4178059390 0.1424150562 -0.4515634182 -0.0646724065 0.0902211693
[16] 0.3190189435 0.1785496788 0.2528944628 0.3048280772 -0.4606571334
[21] 0.4037819128 -1.0240122064 0.2533087957 0.3399603819 0.5995838176
[26] 0.2760221363 0.1843841536 -0.1967655040 0.0908400586 0.2099043268
[31] -0.5039168129 -0.3673553336 -0.1760523386 -0.6904055425 -0.3564349192
[36] 0.1766703166 -0.0928378910 -0.0533858870 0.3445008511 -0.2456061441
[41] 0.5513879394 -0.5101457926 0.6681628666 0.2357599377 -0.2359198573
[46] -0.1787785615 0.1285331684 0.4483387944 -0.3233111716 -0.1320394579
[51] -0.2623130234 -0.2605880604 0.2446028545 0.3146520325 -0.1880559637
[56] 0.0453360208 -0.1441176674 0.5994202962 0.2747912790 -0.3342798239
[61] -0.0937620745 -0.0329325341 -0.1011991516 -0.2370335205 0.4457304726
[66] -0.2448547467 -0.6126553827 0.0368250604 -0.5876387939 -0.0451845398
[71] -0.0911740040 0.0156398934 0.1469920846 -0.2749174921 -0.1460397289
[76] -0.0042092666 0.4892412464 0.1458127435 -0.5218256862 -0.4094880605
[81] 0.1145717549 -0.0250423573 0.6799663631 -0.1827186516 0.1037621600
[86] -0.0299995164 -0.2723789429 0.0006108964 0.1742667634 0.0058062955
[91] -0.0656828511 -1.2441543095 -0.2733558298 -0.2906877011 -0.1808444874
[96] 0.0723349968 -0.0576561254 -0.3949840888 -0.0400777581 -0.1391241153
[101] -0.5689611977 -0.0264133629 -0.9827460681 -0.0214298202 -0.1870611138
[106] -0.0191542839 0.5240394298 0.4306413650 -0.0085759010 0.2160428037
[111] -0.2964852047 -0.5849509344 -0.3191868309 -0.1241122226 -0.0632938969
[116] -0.8287146913 0.5627527181 0.0154564013 0.2245338396 0.4252129390
[121] 0.0087767698 0.2550589369 0.1249207202 0.4590112609 0.0219875598
[126] -0.3565894288 -0.1644273304 0.2658687596 0.1743346416 0.2834354029
[131] 0.3033410139 -0.1601587791 0.6604413963 -0.3100230190 -0.0920628827
[136] 0.0226469364 -0.1455967602 -0.0555520920 -0.0765118340 -0.1454120929
[141] -0.5043724149 0.0773777175 0.0523278876 0.0515366525 0.0141925107
[146] 0.0354644715 0.2324165290 -0.5406679790 0.2337435320 -0.3156065081
[151] -0.2441028647 0.1563042664 -0.2144368073 0.1096567490 -0.0068120685
[156] -0.4739100381 0.0948271999 -0.0455378655 0.7624817834 0.0603221690
[161] 0.0281306745 0.5099855792 0.0399362937 -0.1125321264 0.2940794108
[166] 0.1171271270 0.4121053319 0.5028934952 -0.3373542586 -0.0491978162
[171] 0.0789001403 -0.1936670628 -0.4886489316 0.1412306720 0.1783777176
[176] 0.0930050149 -0.1344002219 0.1416174092 -0.3284059947 0.0166410742
[181] 0.2087677239 -0.5084407902 0.0350618385 -0.0111009902 -0.3191879772
[186] 0.1721239021 -0.3486944267 -0.0420358706 -0.5570358463 0.2194373293
[191] 0.1290865848 -0.5075456008 0.3494662526 0.1849394788 0.0339136273
[196] -0.4415853570 -0.0619158323 0.3457566044 -0.0222381460 0.2954301683
[201] 0.1364984892 -0.4804104313 0.1742687150 0.2136699110 0.7323547043
[206] -0.4342195917 0.0406723218 0.2044610724 0.0329435174 -0.1282635391
[211] -0.2052727924 0.4138209791 0.1183834892 0.0884612070 -0.1366950813
[216] 0.0649359592 0.6403483432 -0.0355809296 -0.4060745266 0.1494400190
[221] 0.0268452326 0.3774152709 -0.9678441219 -0.7406947786 -0.0738225694
[226] -0.2288181549 0.1320735906 -0.0366308514 0.2223732889 0.2045846812
>
> proc.time()
user system elapsed
1.502 1.575 3.088
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x5609e69314b0>
> .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: 0x5609e69314b0>
> .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: 0x5609e69314b0>
> .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: 0x5609e69314b0>
> 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: 0x5609e6d6b6e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5609e6d6b6e0>
> .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: 0x5609e6d6b6e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5609e6d6b6e0>
> .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: 0x5609e6d6b6e0>
> 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: 0x5609e8418d70>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5609e8418d70>
> .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: 0x5609e8418d70>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5609e8418d70>
> .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: 0x5609e8418d70>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x5609e8418d70>
> .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: 0x5609e8418d70>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x5609e8418d70>
> .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: 0x5609e8418d70>
> 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: 0x5609e8464120>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5609e8464120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5609e8464120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5609e8464120>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile4574f274c9695" "BufferedMatrixFile4574f7b8c57ff"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile4574f274c9695" "BufferedMatrixFile4574f7b8c57ff"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5609e7cbc010>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5609e7cbc010>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5609e7cbc010>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5609e7cbc010>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5609e7cbc010>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5609e7cbc010>
> .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: 0x5609e7cc3a40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5609e7cc3a40>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5609e7cc3a40>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5609e7cc3a40>
> 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: 0x5609e7cc8c90>
> .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: 0x5609e7cc8c90>
> rm(P)
>
> proc.time()
user system elapsed
0.264 0.047 0.301
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
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Platform: x86_64-pc-linux-gnu
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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
0.263 0.040 0.291