| Back to Build/check report for BioC 3.17: simplified long |
|
This page was generated on 2023-02-27 02:34:30 -0000 (Mon, 27 Feb 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" | 4259 |
| 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 228/2169 | 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 | OK | |||||||||
| Package: BufferedMatrix |
| Version: 1.63.0 |
| Command: /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.17-bioc/R/library --timings BufferedMatrix_1.63.0.tar.gz |
| StartedAt: 2023-02-24 08:11:13 -0000 (Fri, 24 Feb 2023) |
| EndedAt: 2023-02-24 08:11:48 -0000 (Fri, 24 Feb 2023) |
| EllapsedTime: 35.1 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.17-bioc/R/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 installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ...
‘BufferedMatrix.Rnw’... OK
OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.17-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/bbs-3.17-bioc/R/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/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
0.331 0.064 0.380
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 456993 24.5 979984 52.4 651420 34.8
Vcells 842364 6.5 8388608 64.0 2047783 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 Feb 24 08:11:33 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] "Fri Feb 24 08:11:33 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: 0xaaab1cea7910>
>
>
>
> 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 Feb 24 08:11:33 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] "Fri Feb 24 08:11:33 2023"
>
> ColMode(tmp2)
<pointer: 0xaaab1cea7910>
>
>
>
> ### 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,] 100.2595668 -0.1589055 1.611628 0.2625203
[2,] 1.1856836 0.4252815 -1.916579 -1.1262262
[3,] -0.2585755 1.0257944 1.495150 -1.1573463
[4,] 0.7437231 -0.3810803 2.556633 -0.4282077
> 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,] 100.2595668 0.1589055 1.611628 0.2625203
[2,] 1.1856836 0.4252815 1.916579 1.1262262
[3,] 0.2585755 1.0257944 1.495150 1.1573463
[4,] 0.7437231 0.3810803 2.556633 0.4282077
> 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,] 10.0129699 0.3986295 1.269499 0.5123673
[2,] 1.0888910 0.6521361 1.384406 1.0612381
[3,] 0.5085032 1.0128151 1.222763 1.0758003
[4,] 0.8623938 0.6173170 1.598947 0.6543758
>
> 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,] 225.38927 29.14520 39.30662 30.38619
[2,] 37.07459 31.94664 40.76064 36.73861
[3,] 30.34361 36.15395 38.72278 36.91535
[4,] 34.36766 31.55425 43.54611 31.97197
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0xaaab1c626470>
> exp(tmp5)
<pointer: 0xaaab1c626470>
> log(tmp5,2)
<pointer: 0xaaab1c626470>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.1182
> Min(tmp5)
[1] 55.28219
> mean(tmp5)
[1] 73.40595
> Sum(tmp5)
[1] 14681.19
> Var(tmp5)
[1] 852.1027
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.73326 72.26012 71.17121 69.28110 70.89375 72.32696 74.96421 69.69279
[9] 71.04480 72.69127
> rowSums(tmp5)
[1] 1794.665 1445.202 1423.424 1385.622 1417.875 1446.539 1499.284 1393.856
[9] 1420.896 1453.825
> rowVars(tmp5)
[1] 8069.57108 66.90386 67.02677 58.03981 52.60736 66.85815
[7] 42.16218 21.91113 48.93400 94.13527
> rowSd(tmp5)
[1] 89.830791 8.179478 8.186988 7.618386 7.253093 8.176683 6.493241
[8] 4.680932 6.995284 9.702333
> rowMax(tmp5)
[1] 469.11823 87.71707 87.18016 90.63551 88.41088 87.75929 87.58849
[8] 78.86324 87.47546 92.10785
> rowMin(tmp5)
[1] 55.28219 56.09955 56.13541 56.59591 57.55937 56.85017 62.41352 61.46430
[9] 59.76577 60.45770
>
> colMeans(tmp5)
[1] 111.69852 69.19721 78.00105 72.54220 70.79490 72.66650 68.60633
[8] 72.29317 67.25244 73.06701 71.82605 68.98919 69.81432 73.09453
[15] 72.60086 69.60669 66.89889 71.75471 74.02565 73.38874
> colSums(tmp5)
[1] 1116.9852 691.9721 780.0105 725.4220 707.9490 726.6650 686.0633
[8] 722.9317 672.5244 730.6701 718.2605 689.8919 698.1432 730.9453
[15] 726.0086 696.0669 668.9889 717.5471 740.2565 733.8874
> colVars(tmp5)
[1] 15856.44875 44.20363 73.58102 38.01539 58.10724 62.81929
[7] 66.20005 69.43729 23.74277 50.75008 68.81719 87.52739
[13] 80.12049 36.62579 60.10513 67.65868 58.41733 36.46856
[19] 50.13242 95.03454
> colSd(tmp5)
[1] 125.922392 6.648581 8.577938 6.165662 7.622810 7.925862
[7] 8.136341 8.332904 4.872655 7.123909 8.295613 9.355607
[13] 8.951005 6.051925 7.752750 8.225490 7.643123 6.038920
[19] 7.080425 9.748566
> colMax(tmp5)
[1] 469.11823 77.97521 90.63551 84.48165 81.85310 87.18016 77.82651
[8] 87.47546 75.02052 86.46882 87.58849 81.97076 89.46810 84.30296
[15] 87.71707 79.00181 77.33614 78.53875 88.41088 87.75929
> colMin(tmp5)
[1] 59.76577 60.45770 62.13828 63.24488 63.08620 61.94177 56.85017 60.33417
[9] 56.79904 62.62613 61.53147 56.09955 59.88043 64.06193 63.06553 55.28219
[17] 56.13541 60.70396 64.04682 61.46430
>
>
> ### 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] 89.73326 72.26012 71.17121 69.28110 70.89375 72.32696 74.96421 69.69279
[9] 71.04480 NA
> rowSums(tmp5)
[1] 1794.665 1445.202 1423.424 1385.622 1417.875 1446.539 1499.284 1393.856
[9] 1420.896 NA
> rowVars(tmp5)
[1] 8069.57108 66.90386 67.02677 58.03981 52.60736 66.85815
[7] 42.16218 21.91113 48.93400 92.35025
> rowSd(tmp5)
[1] 89.830791 8.179478 8.186988 7.618386 7.253093 8.176683 6.493241
[8] 4.680932 6.995284 9.609904
> rowMax(tmp5)
[1] 469.11823 87.71707 87.18016 90.63551 88.41088 87.75929 87.58849
[8] 78.86324 87.47546 NA
> rowMin(tmp5)
[1] 55.28219 56.09955 56.13541 56.59591 57.55937 56.85017 62.41352 61.46430
[9] 59.76577 NA
>
> colMeans(tmp5)
[1] 111.69852 69.19721 78.00105 72.54220 70.79490 72.66650 68.60633
[8] 72.29317 67.25244 73.06701 71.82605 68.98919 69.81432 73.09453
[15] 72.60086 69.60669 NA 71.75471 74.02565 73.38874
> colSums(tmp5)
[1] 1116.9852 691.9721 780.0105 725.4220 707.9490 726.6650 686.0633
[8] 722.9317 672.5244 730.6701 718.2605 689.8919 698.1432 730.9453
[15] 726.0086 696.0669 NA 717.5471 740.2565 733.8874
> colVars(tmp5)
[1] 15856.44875 44.20363 73.58102 38.01539 58.10724 62.81929
[7] 66.20005 69.43729 23.74277 50.75008 68.81719 87.52739
[13] 80.12049 36.62579 60.10513 67.65868 NA 36.46856
[19] 50.13242 95.03454
> colSd(tmp5)
[1] 125.922392 6.648581 8.577938 6.165662 7.622810 7.925862
[7] 8.136341 8.332904 4.872655 7.123909 8.295613 9.355607
[13] 8.951005 6.051925 7.752750 8.225490 NA 6.038920
[19] 7.080425 9.748566
> colMax(tmp5)
[1] 469.11823 77.97521 90.63551 84.48165 81.85310 87.18016 77.82651
[8] 87.47546 75.02052 86.46882 87.58849 81.97076 89.46810 84.30296
[15] 87.71707 79.00181 NA 78.53875 88.41088 87.75929
> colMin(tmp5)
[1] 59.76577 60.45770 62.13828 63.24488 63.08620 61.94177 56.85017 60.33417
[9] 56.79904 62.62613 61.53147 56.09955 59.88043 64.06193 63.06553 55.28219
[17] NA 60.70396 64.04682 61.46430
>
> Max(tmp5,na.rm=TRUE)
[1] 469.1182
> Min(tmp5,na.rm=TRUE)
[1] 55.28219
> mean(tmp5,na.rm=TRUE)
[1] 73.46458
> Sum(tmp5,na.rm=TRUE)
[1] 14619.45
> Var(tmp5,na.rm=TRUE)
[1] 855.7153
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.73326 72.26012 71.17121 69.28110 70.89375 72.32696 74.96421 69.69279
[9] 71.04480 73.26771
> rowSums(tmp5,na.rm=TRUE)
[1] 1794.665 1445.202 1423.424 1385.622 1417.875 1446.539 1499.284 1393.856
[9] 1420.896 1392.086
> rowVars(tmp5,na.rm=TRUE)
[1] 8069.57108 66.90386 67.02677 58.03981 52.60736 66.85815
[7] 42.16218 21.91113 48.93400 92.35025
> rowSd(tmp5,na.rm=TRUE)
[1] 89.830791 8.179478 8.186988 7.618386 7.253093 8.176683 6.493241
[8] 4.680932 6.995284 9.609904
> rowMax(tmp5,na.rm=TRUE)
[1] 469.11823 87.71707 87.18016 90.63551 88.41088 87.75929 87.58849
[8] 78.86324 87.47546 92.10785
> rowMin(tmp5,na.rm=TRUE)
[1] 55.28219 56.09955 56.13541 56.59591 57.55937 56.85017 62.41352 61.46430
[9] 59.76577 60.45770
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.69852 69.19721 78.00105 72.54220 70.79490 72.66650 68.60633
[8] 72.29317 67.25244 73.06701 71.82605 68.98919 69.81432 73.09453
[15] 72.60086 69.60669 67.47221 71.75471 74.02565 73.38874
> colSums(tmp5,na.rm=TRUE)
[1] 1116.9852 691.9721 780.0105 725.4220 707.9490 726.6650 686.0633
[8] 722.9317 672.5244 730.6701 718.2605 689.8919 698.1432 730.9453
[15] 726.0086 696.0669 607.2499 717.5471 740.2565 733.8874
> colVars(tmp5,na.rm=TRUE)
[1] 15856.44875 44.20363 73.58102 38.01539 58.10724 62.81929
[7] 66.20005 69.43729 23.74277 50.75008 68.81719 87.52739
[13] 80.12049 36.62579 60.10513 67.65868 62.02165 36.46856
[19] 50.13242 95.03454
> colSd(tmp5,na.rm=TRUE)
[1] 125.922392 6.648581 8.577938 6.165662 7.622810 7.925862
[7] 8.136341 8.332904 4.872655 7.123909 8.295613 9.355607
[13] 8.951005 6.051925 7.752750 8.225490 7.875383 6.038920
[19] 7.080425 9.748566
> colMax(tmp5,na.rm=TRUE)
[1] 469.11823 77.97521 90.63551 84.48165 81.85310 87.18016 77.82651
[8] 87.47546 75.02052 86.46882 87.58849 81.97076 89.46810 84.30296
[15] 87.71707 79.00181 77.33614 78.53875 88.41088 87.75929
> colMin(tmp5,na.rm=TRUE)
[1] 59.76577 60.45770 62.13828 63.24488 63.08620 61.94177 56.85017 60.33417
[9] 56.79904 62.62613 61.53147 56.09955 59.88043 64.06193 63.06553 55.28219
[17] 56.13541 60.70396 64.04682 61.46430
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.73326 72.26012 71.17121 69.28110 70.89375 72.32696 74.96421 69.69279
[9] 71.04480 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1794.665 1445.202 1423.424 1385.622 1417.875 1446.539 1499.284 1393.856
[9] 1420.896 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 8069.57108 66.90386 67.02677 58.03981 52.60736 66.85815
[7] 42.16218 21.91113 48.93400 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 89.830791 8.179478 8.186988 7.618386 7.253093 8.176683 6.493241
[8] 4.680932 6.995284 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 469.11823 87.71707 87.18016 90.63551 88.41088 87.75929 87.58849
[8] 78.86324 87.47546 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 55.28219 56.09955 56.13541 56.59591 57.55937 56.85017 62.41352 61.46430
[9] 59.76577 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.87527 70.16827 78.62273 72.91448 71.58682 71.97213 67.76953
[8] 71.62875 67.55449 71.57791 72.96989 69.80166 67.63057 73.83783
[15] 72.27065 69.83037 NaN 71.44143 74.42791 72.35424
> colSums(tmp5,na.rm=TRUE)
[1] 1024.8774 631.5144 707.6045 656.2303 644.2814 647.7492 609.9258
[8] 644.6587 607.9904 644.2012 656.7290 628.2150 608.6751 664.5404
[15] 650.4358 628.4733 0.0000 642.9728 669.8512 651.1882
> colVars(tmp5,na.rm=TRUE)
[1] 17785.20007 39.12086 78.43078 41.20816 58.31519 65.24747
[7] 66.59736 73.15061 25.68419 32.14821 62.70013 91.04209
[13] 36.48683 34.98848 66.39157 75.55316 NA 39.92301
[19] 54.57862 94.87419
> colSd(tmp5,na.rm=TRUE)
[1] 133.361164 6.254667 8.856115 6.419358 7.636438 8.077591
[7] 8.160721 8.552813 5.067957 5.669939 7.918342 9.541598
[13] 6.040433 5.915106 8.148102 8.692132 NA 6.318466
[19] 7.387734 9.740339
> colMax(tmp5,na.rm=TRUE)
[1] 469.11823 77.97521 90.63551 84.48165 81.85310 87.18016 77.82651
[8] 87.47546 75.02052 77.86518 87.58849 81.97076 78.19493 84.30296
[15] 87.71707 79.00181 -Inf 78.53875 88.41088 87.75929
> colMin(tmp5,na.rm=TRUE)
[1] 59.76577 60.66192 62.13828 63.24488 63.08620 61.94177 56.85017 60.33417
[9] 56.79904 62.62613 63.48990 56.09955 59.88043 64.06193 63.06553 55.28219
[17] Inf 60.70396 64.04682 61.46430
>
>
>
>
> 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] 201.8649 166.3454 244.1035 229.0218 132.6894 165.5294 377.3763 190.5012
[9] 119.1664 202.9056
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 201.8649 166.3454 244.1035 229.0218 132.6894 165.5294 377.3763 190.5012
[9] 119.1664 202.9056
>
>
>
> 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 -8.526513e-14 1.705303e-13 4.547474e-13 -1.989520e-13
[6] 0.000000e+00 -1.989520e-13 -2.842171e-13 1.705303e-13 0.000000e+00
[11] -5.684342e-14 -2.842171e-14 5.684342e-14 2.842171e-14 -1.136868e-13
[16] -1.705303e-13 2.842171e-14 -1.136868e-13 1.136868e-13 -1.705303e-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)
+ }
4 13
9 15
8 6
8 11
2 18
2 20
5 10
7 15
7 3
4 19
10 20
8 5
4 9
8 8
7 13
10 14
8 11
5 16
4 18
5 14
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] 3.093933
> Min(tmp)
[1] -2.184655
> mean(tmp)
[1] 0.06783318
> Sum(tmp)
[1] 6.783318
> Var(tmp)
[1] 1.214117
>
> rowMeans(tmp)
[1] 0.06783318
> rowSums(tmp)
[1] 6.783318
> rowVars(tmp)
[1] 1.214117
> rowSd(tmp)
[1] 1.10187
> rowMax(tmp)
[1] 3.093933
> rowMin(tmp)
[1] -2.184655
>
> colMeans(tmp)
[1] -0.21029769 -0.64473525 1.76967570 -0.48343749 -2.18465549 -1.11853703
[7] 0.43046268 0.37679891 0.25778777 -0.88668358 -0.53255066 -0.85465069
[13] 0.51675428 0.57625694 1.09476982 1.23151397 1.90242282 -0.88034564
[19] -0.40525392 -0.89923823 1.14680732 0.94674576 -1.42799356 -0.30010057
[25] 1.21100434 2.32577779 0.22778536 -0.06964000 -0.20539732 0.61884491
[31] -0.06952551 3.09393296 1.65884755 0.45679419 -0.90643250 1.60994795
[37] 0.08706516 0.93710048 0.24147166 -0.76448379 1.94170275 -0.51015957
[43] -1.83835837 -0.32801857 1.82154450 -0.21088785 -0.19583383 -0.64309025
[49] -0.88546901 2.61692910 0.84530207 0.93350108 -1.34176972 -0.97767453
[55] -1.13305316 0.95346085 -0.18641897 -1.96160678 3.00726829 0.25824473
[61] 0.28387277 -0.97976188 -0.21830409 -1.00506067 -0.68206520 0.33307330
[67] -0.04667323 -1.39530849 -0.79561770 0.53130834 1.91774301 -1.19190036
[73] 1.40415058 -0.76149371 -0.89445549 -1.10960885 0.17442632 -0.55433788
[79] -0.89135535 0.23013984 0.26560614 -1.59431335 0.97131684 0.49563176
[85] -0.29435426 0.88578440 0.85750736 -0.67679857 -0.10970941 0.63138183
[91] 0.28026494 -0.05219247 0.11342993 -2.10762949 -0.59874540 0.39574672
[97] -0.62887307 -0.77765520 0.53805204 1.79987409
> colSums(tmp)
[1] -0.21029769 -0.64473525 1.76967570 -0.48343749 -2.18465549 -1.11853703
[7] 0.43046268 0.37679891 0.25778777 -0.88668358 -0.53255066 -0.85465069
[13] 0.51675428 0.57625694 1.09476982 1.23151397 1.90242282 -0.88034564
[19] -0.40525392 -0.89923823 1.14680732 0.94674576 -1.42799356 -0.30010057
[25] 1.21100434 2.32577779 0.22778536 -0.06964000 -0.20539732 0.61884491
[31] -0.06952551 3.09393296 1.65884755 0.45679419 -0.90643250 1.60994795
[37] 0.08706516 0.93710048 0.24147166 -0.76448379 1.94170275 -0.51015957
[43] -1.83835837 -0.32801857 1.82154450 -0.21088785 -0.19583383 -0.64309025
[49] -0.88546901 2.61692910 0.84530207 0.93350108 -1.34176972 -0.97767453
[55] -1.13305316 0.95346085 -0.18641897 -1.96160678 3.00726829 0.25824473
[61] 0.28387277 -0.97976188 -0.21830409 -1.00506067 -0.68206520 0.33307330
[67] -0.04667323 -1.39530849 -0.79561770 0.53130834 1.91774301 -1.19190036
[73] 1.40415058 -0.76149371 -0.89445549 -1.10960885 0.17442632 -0.55433788
[79] -0.89135535 0.23013984 0.26560614 -1.59431335 0.97131684 0.49563176
[85] -0.29435426 0.88578440 0.85750736 -0.67679857 -0.10970941 0.63138183
[91] 0.28026494 -0.05219247 0.11342993 -2.10762949 -0.59874540 0.39574672
[97] -0.62887307 -0.77765520 0.53805204 1.79987409
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] -0.21029769 -0.64473525 1.76967570 -0.48343749 -2.18465549 -1.11853703
[7] 0.43046268 0.37679891 0.25778777 -0.88668358 -0.53255066 -0.85465069
[13] 0.51675428 0.57625694 1.09476982 1.23151397 1.90242282 -0.88034564
[19] -0.40525392 -0.89923823 1.14680732 0.94674576 -1.42799356 -0.30010057
[25] 1.21100434 2.32577779 0.22778536 -0.06964000 -0.20539732 0.61884491
[31] -0.06952551 3.09393296 1.65884755 0.45679419 -0.90643250 1.60994795
[37] 0.08706516 0.93710048 0.24147166 -0.76448379 1.94170275 -0.51015957
[43] -1.83835837 -0.32801857 1.82154450 -0.21088785 -0.19583383 -0.64309025
[49] -0.88546901 2.61692910 0.84530207 0.93350108 -1.34176972 -0.97767453
[55] -1.13305316 0.95346085 -0.18641897 -1.96160678 3.00726829 0.25824473
[61] 0.28387277 -0.97976188 -0.21830409 -1.00506067 -0.68206520 0.33307330
[67] -0.04667323 -1.39530849 -0.79561770 0.53130834 1.91774301 -1.19190036
[73] 1.40415058 -0.76149371 -0.89445549 -1.10960885 0.17442632 -0.55433788
[79] -0.89135535 0.23013984 0.26560614 -1.59431335 0.97131684 0.49563176
[85] -0.29435426 0.88578440 0.85750736 -0.67679857 -0.10970941 0.63138183
[91] 0.28026494 -0.05219247 0.11342993 -2.10762949 -0.59874540 0.39574672
[97] -0.62887307 -0.77765520 0.53805204 1.79987409
> colMin(tmp)
[1] -0.21029769 -0.64473525 1.76967570 -0.48343749 -2.18465549 -1.11853703
[7] 0.43046268 0.37679891 0.25778777 -0.88668358 -0.53255066 -0.85465069
[13] 0.51675428 0.57625694 1.09476982 1.23151397 1.90242282 -0.88034564
[19] -0.40525392 -0.89923823 1.14680732 0.94674576 -1.42799356 -0.30010057
[25] 1.21100434 2.32577779 0.22778536 -0.06964000 -0.20539732 0.61884491
[31] -0.06952551 3.09393296 1.65884755 0.45679419 -0.90643250 1.60994795
[37] 0.08706516 0.93710048 0.24147166 -0.76448379 1.94170275 -0.51015957
[43] -1.83835837 -0.32801857 1.82154450 -0.21088785 -0.19583383 -0.64309025
[49] -0.88546901 2.61692910 0.84530207 0.93350108 -1.34176972 -0.97767453
[55] -1.13305316 0.95346085 -0.18641897 -1.96160678 3.00726829 0.25824473
[61] 0.28387277 -0.97976188 -0.21830409 -1.00506067 -0.68206520 0.33307330
[67] -0.04667323 -1.39530849 -0.79561770 0.53130834 1.91774301 -1.19190036
[73] 1.40415058 -0.76149371 -0.89445549 -1.10960885 0.17442632 -0.55433788
[79] -0.89135535 0.23013984 0.26560614 -1.59431335 0.97131684 0.49563176
[85] -0.29435426 0.88578440 0.85750736 -0.67679857 -0.10970941 0.63138183
[91] 0.28026494 -0.05219247 0.11342993 -2.10762949 -0.59874540 0.39574672
[97] -0.62887307 -0.77765520 0.53805204 1.79987409
> colMedians(tmp)
[1] -0.21029769 -0.64473525 1.76967570 -0.48343749 -2.18465549 -1.11853703
[7] 0.43046268 0.37679891 0.25778777 -0.88668358 -0.53255066 -0.85465069
[13] 0.51675428 0.57625694 1.09476982 1.23151397 1.90242282 -0.88034564
[19] -0.40525392 -0.89923823 1.14680732 0.94674576 -1.42799356 -0.30010057
[25] 1.21100434 2.32577779 0.22778536 -0.06964000 -0.20539732 0.61884491
[31] -0.06952551 3.09393296 1.65884755 0.45679419 -0.90643250 1.60994795
[37] 0.08706516 0.93710048 0.24147166 -0.76448379 1.94170275 -0.51015957
[43] -1.83835837 -0.32801857 1.82154450 -0.21088785 -0.19583383 -0.64309025
[49] -0.88546901 2.61692910 0.84530207 0.93350108 -1.34176972 -0.97767453
[55] -1.13305316 0.95346085 -0.18641897 -1.96160678 3.00726829 0.25824473
[61] 0.28387277 -0.97976188 -0.21830409 -1.00506067 -0.68206520 0.33307330
[67] -0.04667323 -1.39530849 -0.79561770 0.53130834 1.91774301 -1.19190036
[73] 1.40415058 -0.76149371 -0.89445549 -1.10960885 0.17442632 -0.55433788
[79] -0.89135535 0.23013984 0.26560614 -1.59431335 0.97131684 0.49563176
[85] -0.29435426 0.88578440 0.85750736 -0.67679857 -0.10970941 0.63138183
[91] 0.28026494 -0.05219247 0.11342993 -2.10762949 -0.59874540 0.39574672
[97] -0.62887307 -0.77765520 0.53805204 1.79987409
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.2102977 -0.6447352 1.769676 -0.4834375 -2.184655 -1.118537 0.4304627
[2,] -0.2102977 -0.6447352 1.769676 -0.4834375 -2.184655 -1.118537 0.4304627
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.3767989 0.2577878 -0.8866836 -0.5325507 -0.8546507 0.5167543 0.5762569
[2,] 0.3767989 0.2577878 -0.8866836 -0.5325507 -0.8546507 0.5167543 0.5762569
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.09477 1.231514 1.902423 -0.8803456 -0.4052539 -0.8992382 1.146807
[2,] 1.09477 1.231514 1.902423 -0.8803456 -0.4052539 -0.8992382 1.146807
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.9467458 -1.427994 -0.3001006 1.211004 2.325778 0.2277854 -0.06964
[2,] 0.9467458 -1.427994 -0.3001006 1.211004 2.325778 0.2277854 -0.06964
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.2053973 0.6188449 -0.06952551 3.093933 1.658848 0.4567942 -0.9064325
[2,] -0.2053973 0.6188449 -0.06952551 3.093933 1.658848 0.4567942 -0.9064325
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.609948 0.08706516 0.9371005 0.2414717 -0.7644838 1.941703 -0.5101596
[2,] 1.609948 0.08706516 0.9371005 0.2414717 -0.7644838 1.941703 -0.5101596
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.838358 -0.3280186 1.821545 -0.2108879 -0.1958338 -0.6430902 -0.885469
[2,] -1.838358 -0.3280186 1.821545 -0.2108879 -0.1958338 -0.6430902 -0.885469
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 2.616929 0.8453021 0.9335011 -1.34177 -0.9776745 -1.133053 0.9534608
[2,] 2.616929 0.8453021 0.9335011 -1.34177 -0.9776745 -1.133053 0.9534608
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.186419 -1.961607 3.007268 0.2582447 0.2838728 -0.9797619 -0.2183041
[2,] -0.186419 -1.961607 3.007268 0.2582447 0.2838728 -0.9797619 -0.2183041
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.005061 -0.6820652 0.3330733 -0.04667323 -1.395308 -0.7956177 0.5313083
[2,] -1.005061 -0.6820652 0.3330733 -0.04667323 -1.395308 -0.7956177 0.5313083
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 1.917743 -1.1919 1.404151 -0.7614937 -0.8944555 -1.109609 0.1744263
[2,] 1.917743 -1.1919 1.404151 -0.7614937 -0.8944555 -1.109609 0.1744263
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.5543379 -0.8913554 0.2301398 0.2656061 -1.594313 0.9713168 0.4956318
[2,] -0.5543379 -0.8913554 0.2301398 0.2656061 -1.594313 0.9713168 0.4956318
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.2943543 0.8857844 0.8575074 -0.6767986 -0.1097094 0.6313818 0.2802649
[2,] -0.2943543 0.8857844 0.8575074 -0.6767986 -0.1097094 0.6313818 0.2802649
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.05219247 0.1134299 -2.107629 -0.5987454 0.3957467 -0.6288731 -0.7776552
[2,] -0.05219247 0.1134299 -2.107629 -0.5987454 0.3957467 -0.6288731 -0.7776552
[,99] [,100]
[1,] 0.538052 1.799874
[2,] 0.538052 1.799874
>
>
> Max(tmp2)
[1] 2.482794
> Min(tmp2)
[1] -3.467938
> mean(tmp2)
[1] -0.04932791
> Sum(tmp2)
[1] -4.932791
> Var(tmp2)
[1] 1.026057
>
> rowMeans(tmp2)
[1] -1.21023388 0.60589722 -0.62480801 -1.41975039 -0.99432880 -0.44351798
[7] 1.41218988 -0.47752839 -1.38039187 0.54251731 -1.38087931 0.57535954
[13] 1.36802999 2.48279417 0.55231978 1.14988074 -1.01885013 1.24496605
[19] 1.14045618 -0.38219375 1.52123554 0.95629609 -0.84840395 0.46126271
[25] 2.03834349 -0.61177842 0.35191873 -0.10573409 0.12063577 0.58160754
[31] 0.46612393 0.52689227 0.15013675 0.45035437 -0.04285073 -1.33903218
[37] -2.03843088 0.23047645 0.51868103 -0.44668094 -3.46793791 -0.59936507
[43] -1.29819729 0.16087531 -1.46442653 -0.52573063 0.84216412 -0.95285040
[49] -0.86578062 -0.29535152 0.87120188 0.11196467 -1.32840429 0.01758171
[55] 0.34256170 -0.49163599 -0.81660436 -0.47161586 0.40797656 1.03556090
[61] -0.18990964 -1.10661623 -0.67936920 -0.30244269 0.03166153 -0.26307781
[67] 0.77677946 0.85858262 -0.68275420 0.97831835 -0.64454561 -1.00836876
[73] 1.89335566 0.23976342 0.97434403 1.18395936 0.29244791 0.16664024
[79] 1.56017993 0.22880378 -0.88484284 -0.96308577 0.26243336 0.23407381
[85] 0.58346237 -1.78360736 -1.42321259 0.04519700 -0.72692981 0.13352933
[91] 1.61396010 0.63007023 -2.27960811 -0.70156317 0.37903500 1.13789205
[97] -0.09895157 -0.20141331 -1.61783078 0.52588065
> rowSums(tmp2)
[1] -1.21023388 0.60589722 -0.62480801 -1.41975039 -0.99432880 -0.44351798
[7] 1.41218988 -0.47752839 -1.38039187 0.54251731 -1.38087931 0.57535954
[13] 1.36802999 2.48279417 0.55231978 1.14988074 -1.01885013 1.24496605
[19] 1.14045618 -0.38219375 1.52123554 0.95629609 -0.84840395 0.46126271
[25] 2.03834349 -0.61177842 0.35191873 -0.10573409 0.12063577 0.58160754
[31] 0.46612393 0.52689227 0.15013675 0.45035437 -0.04285073 -1.33903218
[37] -2.03843088 0.23047645 0.51868103 -0.44668094 -3.46793791 -0.59936507
[43] -1.29819729 0.16087531 -1.46442653 -0.52573063 0.84216412 -0.95285040
[49] -0.86578062 -0.29535152 0.87120188 0.11196467 -1.32840429 0.01758171
[55] 0.34256170 -0.49163599 -0.81660436 -0.47161586 0.40797656 1.03556090
[61] -0.18990964 -1.10661623 -0.67936920 -0.30244269 0.03166153 -0.26307781
[67] 0.77677946 0.85858262 -0.68275420 0.97831835 -0.64454561 -1.00836876
[73] 1.89335566 0.23976342 0.97434403 1.18395936 0.29244791 0.16664024
[79] 1.56017993 0.22880378 -0.88484284 -0.96308577 0.26243336 0.23407381
[85] 0.58346237 -1.78360736 -1.42321259 0.04519700 -0.72692981 0.13352933
[91] 1.61396010 0.63007023 -2.27960811 -0.70156317 0.37903500 1.13789205
[97] -0.09895157 -0.20141331 -1.61783078 0.52588065
> 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] -1.21023388 0.60589722 -0.62480801 -1.41975039 -0.99432880 -0.44351798
[7] 1.41218988 -0.47752839 -1.38039187 0.54251731 -1.38087931 0.57535954
[13] 1.36802999 2.48279417 0.55231978 1.14988074 -1.01885013 1.24496605
[19] 1.14045618 -0.38219375 1.52123554 0.95629609 -0.84840395 0.46126271
[25] 2.03834349 -0.61177842 0.35191873 -0.10573409 0.12063577 0.58160754
[31] 0.46612393 0.52689227 0.15013675 0.45035437 -0.04285073 -1.33903218
[37] -2.03843088 0.23047645 0.51868103 -0.44668094 -3.46793791 -0.59936507
[43] -1.29819729 0.16087531 -1.46442653 -0.52573063 0.84216412 -0.95285040
[49] -0.86578062 -0.29535152 0.87120188 0.11196467 -1.32840429 0.01758171
[55] 0.34256170 -0.49163599 -0.81660436 -0.47161586 0.40797656 1.03556090
[61] -0.18990964 -1.10661623 -0.67936920 -0.30244269 0.03166153 -0.26307781
[67] 0.77677946 0.85858262 -0.68275420 0.97831835 -0.64454561 -1.00836876
[73] 1.89335566 0.23976342 0.97434403 1.18395936 0.29244791 0.16664024
[79] 1.56017993 0.22880378 -0.88484284 -0.96308577 0.26243336 0.23407381
[85] 0.58346237 -1.78360736 -1.42321259 0.04519700 -0.72692981 0.13352933
[91] 1.61396010 0.63007023 -2.27960811 -0.70156317 0.37903500 1.13789205
[97] -0.09895157 -0.20141331 -1.61783078 0.52588065
> rowMin(tmp2)
[1] -1.21023388 0.60589722 -0.62480801 -1.41975039 -0.99432880 -0.44351798
[7] 1.41218988 -0.47752839 -1.38039187 0.54251731 -1.38087931 0.57535954
[13] 1.36802999 2.48279417 0.55231978 1.14988074 -1.01885013 1.24496605
[19] 1.14045618 -0.38219375 1.52123554 0.95629609 -0.84840395 0.46126271
[25] 2.03834349 -0.61177842 0.35191873 -0.10573409 0.12063577 0.58160754
[31] 0.46612393 0.52689227 0.15013675 0.45035437 -0.04285073 -1.33903218
[37] -2.03843088 0.23047645 0.51868103 -0.44668094 -3.46793791 -0.59936507
[43] -1.29819729 0.16087531 -1.46442653 -0.52573063 0.84216412 -0.95285040
[49] -0.86578062 -0.29535152 0.87120188 0.11196467 -1.32840429 0.01758171
[55] 0.34256170 -0.49163599 -0.81660436 -0.47161586 0.40797656 1.03556090
[61] -0.18990964 -1.10661623 -0.67936920 -0.30244269 0.03166153 -0.26307781
[67] 0.77677946 0.85858262 -0.68275420 0.97831835 -0.64454561 -1.00836876
[73] 1.89335566 0.23976342 0.97434403 1.18395936 0.29244791 0.16664024
[79] 1.56017993 0.22880378 -0.88484284 -0.96308577 0.26243336 0.23407381
[85] 0.58346237 -1.78360736 -1.42321259 0.04519700 -0.72692981 0.13352933
[91] 1.61396010 0.63007023 -2.27960811 -0.70156317 0.37903500 1.13789205
[97] -0.09895157 -0.20141331 -1.61783078 0.52588065
>
> colMeans(tmp2)
[1] -0.04932791
> colSums(tmp2)
[1] -4.932791
> colVars(tmp2)
[1] 1.026057
> colSd(tmp2)
[1] 1.012945
> colMax(tmp2)
[1] 2.482794
> colMin(tmp2)
[1] -3.467938
> colMedians(tmp2)
[1] 0.07858084
> colRanges(tmp2)
[,1]
[1,] -3.467938
[2,] 2.482794
>
> 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] 0.02384615 -2.57267716 1.26438626 0.72478742 1.58595991 -9.76710443
[7] -1.10087706 -2.07651509 -0.29355638 4.34915571
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.00157041
[2,] -0.28497356
[3,] 0.03318193
[4,] 0.10819998
[5,] 2.41814838
>
> rowApply(tmp,sum)
[1] -5.3134126 3.0336315 -0.6963553 -2.4983643 1.2247786 3.3719330
[7] -4.9665604 -2.3950852 0.8862742 -0.5094344
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 5 5 5 4 10 6 6 4 8
[2,] 7 1 1 4 8 5 8 2 10 1
[3,] 6 7 9 10 6 3 7 3 9 9
[4,] 9 3 8 7 2 4 9 5 2 6
[5,] 10 8 7 2 10 1 2 9 8 3
[6,] 2 6 3 6 1 8 1 1 1 7
[7,] 5 4 4 9 7 2 5 7 5 5
[8,] 3 9 2 1 5 6 4 10 7 4
[9,] 8 2 10 3 9 9 3 4 3 2
[10,] 4 10 6 8 3 7 10 8 6 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.4352556 -1.6909735 -1.4317232 3.7604393 0.3520055 1.3476592
[7] 3.3980285 -1.4648248 -1.6788502 2.4263544 1.3635616 0.6490619
[13] -2.0731145 -1.8705541 -5.2705371 0.8315160 0.6137943 -0.9801708
[19] -0.2461183 -0.5042770
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.0060934
[2,] -0.5898705
[3,] 0.8548803
[4,] 0.8666598
[5,] 1.3096794
>
> rowApply(tmp,sum)
[1] 9.323484 -5.378999 -8.904625 1.914710 2.011962
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 14 10 19 3 19
[2,] 1 16 14 7 4
[3,] 3 3 18 8 7
[4,] 18 14 20 15 10
[5,] 16 19 8 10 2
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.8666598 -0.8661957 -0.1262431 1.2578491 1.01382279 0.0423251
[2,] -0.5898705 0.5110599 -1.5578165 0.2508813 1.35359966 0.7872294
[3,] 0.8548803 -0.1606349 0.7241909 1.7182414 -0.69239474 -1.1145482
[4,] -1.0060934 -0.1852225 -0.1521912 0.6596890 0.07492085 1.1655109
[5,] 1.3096794 -0.9899803 -0.3196634 -0.1262214 -1.39794301 0.4671420
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.0384498 0.9073171 -0.09905745 1.3701420 0.08065723 0.50579183
[2,] 0.3939041 -0.7366793 -0.06489320 -1.1182303 -0.67871480 1.73833523
[3,] -0.4568685 -1.3629090 -0.20977252 0.5962965 -0.23467166 -1.37121469
[4,] 0.1129649 1.2027035 -1.39007752 0.4434381 0.90549878 -0.03530703
[5,] 2.3095782 -1.4752570 0.08495052 1.1347082 1.29079207 -0.18854344
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.4821015 0.4585083 0.7458277 1.3576550 0.4783620 -0.05246812
[2,] -0.6315455 -0.8363827 -2.4365947 1.1773034 -0.8227340 -1.88639679
[3,] -2.1701949 -0.4492302 -2.3015564 -0.7512455 -0.1273301 -0.51177212
[4,] 1.3884812 -0.7156201 -1.2601216 -0.5367721 0.8701836 0.20097486
[5,] -0.1777538 -0.3278294 -0.0180921 -0.4154247 0.2153128 1.26949141
[,19] [,20]
[1,] 0.48469589 0.3414868
[2,] -0.05356389 -0.1778895
[3,] 0.10516046 -0.9890508
[4,] 0.52219780 -0.3504476
[5,] -1.30460852 0.6716241
>
>
> 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 : 566 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.17-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 1.211433 -0.6519422 1.055763 0.7168975 -0.7493754 0.4174491 -0.07871524
col8 col9 col10 col11 col12 col13 col14
row1 0.7332413 0.674242 -0.5016965 -1.395564 0.7919441 -0.7790658 -0.1927717
col15 col16 col17 col18 col19 col20
row1 -1.223846 -1.576528 0.6776459 1.244797 0.4501776 -2.300911
> tmp[,"col10"]
col10
row1 -0.5016965
row2 -1.2927741
row3 -1.7508908
row4 -1.2346402
row5 0.3676499
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 1.2114332 -0.65194216 1.05576334 0.7168975 -0.7493754 0.4174491
row5 0.3467963 0.04882948 0.01631738 1.3507221 0.5356489 -0.2850436
col7 col8 col9 col10 col11 col12 col13
row1 -0.07871524 0.7332413 0.6742420 -0.5016965 -1.395564 0.79194414 -0.7790658
row5 0.19098830 1.0620415 0.1285413 0.3676499 1.134773 0.06864253 0.6311019
col14 col15 col16 col17 col18 col19 col20
row1 -0.1927717 -1.2238459 -1.5765282 0.6776459 1.244797 0.4501776 -2.3009109
row5 0.4789930 -0.3212982 -0.7885172 -0.3559707 1.063778 -2.1930544 -0.6063485
> tmp[,c("col6","col20")]
col6 col20
row1 0.41744912 -2.3009109
row2 -0.01023848 -1.8860427
row3 1.29449460 -1.3307380
row4 1.51327349 -0.6205449
row5 -0.28504358 -0.6063485
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.4174491 -2.3009109
row5 -0.2850436 -0.6063485
>
>
>
>
> 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 51.25718 49.68477 49.22072 48.51188 50.24936 105.7492 50.86572 50.53983
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.71109 50.74005 48.82645 51.567 48.41413 48.72116 50.33281 51.61008
col17 col18 col19 col20
row1 50.37839 49.28071 49.72559 103.3606
> tmp[,"col10"]
col10
row1 50.74005
row2 28.30550
row3 30.33144
row4 28.75352
row5 51.19734
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.25718 49.68477 49.22072 48.51188 50.24936 105.7492 50.86572 50.53983
row5 49.39253 50.19338 51.27816 50.45850 49.89229 103.9327 50.56178 49.53590
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.71109 50.74005 48.82645 51.56700 48.41413 48.72116 50.33281 51.61008
row5 50.21499 51.19734 49.66447 49.28518 50.33594 49.73005 50.19048 51.88293
col17 col18 col19 col20
row1 50.37839 49.28071 49.72559 103.3606
row5 49.23075 49.94392 50.14622 103.9427
> tmp[,c("col6","col20")]
col6 col20
row1 105.74918 103.36055
row2 76.77449 75.67961
row3 76.26030 74.35518
row4 75.33436 75.76635
row5 103.93274 103.94266
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.7492 103.3606
row5 103.9327 103.9427
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.7492 103.3606
row5 103.9327 103.9427
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.54466570
[2,] -1.92556799
[3,] 0.34633598
[4,] -0.30225849
[5,] -0.05731927
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.4552930 1.0163123
[2,] -1.5061210 0.1057241
[3,] 2.0516713 0.4617977
[4,] -1.3789652 -0.2823507
[5,] -0.5185199 -0.6655292
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.32859885 0.8706774
[2,] -0.07350854 1.5158652
[3,] -1.84915702 -0.3943190
[4,] 0.83021722 0.9040473
[5,] 0.43052428 -1.5752265
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.3285988
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.32859885
[2,] -0.07350854
>
>
>
> 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 1.6016757 0.3222501 0.1347314 1.031443 -0.4117513 -1.434496043
row1 0.4914814 -0.9941600 -1.2180375 -1.465915 0.3097731 -0.003097359
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.1771900 -1.551916 -1.597790 -0.9925248 0.4045346 0.03094472 0.9196098
row1 0.2232065 0.695837 -1.663329 -0.5468029 -1.1786131 1.30818988 -1.0713582
[,14] [,15] [,16] [,17] [,18] [,19]
row3 0.7673875 -0.7439819 0.7769879 -0.1092605 1.1708956 1.020351
row1 -0.6955491 -0.3774686 -0.1172052 -0.3711686 -0.1528833 -1.097124
[,20]
row3 0.825575842
row1 0.005172927
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.2042054 -0.5322041 0.1295967 0.06500065 1.37047 0.4673684 -0.07611888
[,8] [,9] [,10]
row2 -0.3712524 0.09965826 -0.5429038
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.0591445 -0.1995165 0.1742892 0.3534153 0.3272675 1.126597 1.976564
[,8] [,9] [,10] [,11] [,12] [,13]
row5 -0.4373231 0.3162267 -0.7786957 0.4108388 -0.8397869 -0.02475916
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.3534782 0.6602275 0.4488391 0.007857584 -1.426013 0.9882005 0.3255809
>
>
> 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: 0xaaab1f06dc60>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM24311358d3889"
[2] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM24311324876521"
[3] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM2431133f65d439"
[4] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM24311362b8ce8e"
[5] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM243113a58421b"
[6] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM24311323863f37"
[7] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM2431132526a58b"
[8] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM2431136a684a2e"
[9] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM24311376a20458"
[10] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM2431132e25ee8d"
[11] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM2431134cb81546"
[12] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM2431133e5d00db"
[13] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM2431135ff3b174"
[14] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM243113231c1300"
[15] "/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests/BM24311335a64513"
>
>
> ### 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: 0xaaab200ffeb0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0xaaab200ffeb0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.17-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0xaaab200ffeb0>
> rowMedians(tmp)
[1] -0.062797595 0.314495888 -0.857407909 -0.218972514 0.005572621
[6] -0.332681526 0.202624439 0.457621755 0.095451775 -0.042688020
[11] 0.016777184 0.563512173 0.099894585 0.022907687 0.264931184
[16] 0.439764863 -0.193590728 0.356405777 0.266291448 -0.345399754
[21] 0.073591694 -0.340408232 0.096419041 -0.400429139 -0.006094065
[26] -0.319218077 -0.417176062 -0.652913996 -0.267368551 0.215391396
[31] -0.370974157 0.048795481 -0.062037152 -0.119028467 0.082560080
[36] 0.413489008 -0.321329852 -0.561004806 0.130404807 -0.327966077
[41] -0.223423409 0.327807657 0.057307413 -0.787772057 0.274221985
[46] -0.126775600 0.522159246 0.041157741 -0.259939398 0.112261823
[51] 0.065108814 -0.084882682 0.063783936 -0.487337236 -0.501020329
[56] 0.099595568 0.110904690 -0.057405217 -0.250337395 -0.286216550
[61] 0.284456180 -0.346396292 0.124142952 -0.057588349 -0.477111551
[66] -0.134566228 0.368907802 0.089140080 0.238856664 -0.182867095
[71] 0.311587267 -0.112016591 0.170959417 -0.096145674 -0.515457171
[76] 0.435418304 -0.152618888 -0.325761354 0.437597106 0.412662676
[81] 0.246036633 -0.253994006 -0.971332105 -0.065637830 0.303503625
[86] 0.299652843 0.213544450 0.219158061 -0.025183356 0.210555529
[91] 0.529629915 0.695554331 -0.207969627 -0.237609412 -0.336245373
[96] 0.053418808 -0.302858467 -0.218823358 -0.731448599 -0.081009518
[101] 0.117753611 -0.462001484 -0.156633186 0.228137785 0.738030362
[106] -0.015209474 -0.349793534 -0.075499928 0.272909999 0.409999354
[111] -0.536075544 0.089305287 0.010196149 -0.239347315 -0.526920286
[116] 0.555783597 -0.175456751 0.108173342 0.095576893 -0.087471626
[121] 0.413793153 0.177482082 0.191250806 0.913289267 -0.074712539
[126] -0.361830581 0.093221903 0.150976184 -0.311563531 0.070353441
[131] 0.023017216 0.328874075 -0.235160130 0.213927626 -0.176533046
[136] 0.282049859 0.529424903 0.391510775 0.001063209 -0.248990703
[141] 0.351264106 -0.091471504 0.156198118 0.198496388 -0.278282058
[146] 0.166336798 -0.240242866 -0.430346955 -0.029670613 0.045067327
[151] 0.243775455 -0.180483358 0.065417330 0.026283186 0.211509848
[156] -0.075349588 0.164203880 -0.024589740 -0.145968486 -0.390726371
[161] 0.210678605 -0.311553414 -0.387963982 0.147734471 -0.126418611
[166] 0.334454350 0.242684145 -0.340912830 -0.371504840 -0.187898295
[171] 0.427093790 0.453140050 -0.407404550 0.362982674 0.011430238
[176] 0.022820964 -0.173899765 0.275698508 -0.069071645 -0.407609724
[181] 0.182400473 -0.242174581 0.299217685 0.743777612 0.204566072
[186] -0.236113414 0.352130033 0.054959629 0.325239329 0.217041580
[191] -0.015558823 0.082177356 0.295845875 -0.394032137 0.280783635
[196] 0.160277208 0.194370718 -0.275000745 -0.194439350 0.181268472
[201] 0.242356696 -0.412482129 -0.188584770 0.505495367 0.064860970
[206] -0.388372533 -0.304798861 0.269098120 -0.263011616 0.231820124
[211] -0.297152325 0.361895403 0.043043713 -0.368506369 1.106355391
[216] 0.014230636 -0.192836341 0.116783040 0.501532889 -0.111572973
[221] 0.381670525 -0.040971792 -0.645713576 0.187362963 -0.275115541
[226] -0.220436460 -0.619737813 0.111433823 -0.024838895 -0.090206913
>
> proc.time()
user system elapsed
2.134 1.187 3.310
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: 0xaaaac460b910>
> .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: 0xaaaac460b910>
> .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: 0xaaaac460b910>
> .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: 0xaaaac460b910>
> 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: 0xaaaac4dcc2a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaaac4dcc2a0>
> .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: 0xaaaac4dcc2a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaaac4dcc2a0>
> .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: 0xaaaac4dcc2a0>
> 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: 0xaaaac45b9df0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaaac45b9df0>
> .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: 0xaaaac45b9df0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0xaaaac45b9df0>
> .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: 0xaaaac45b9df0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0xaaaac45b9df0>
> .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: 0xaaaac45b9df0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0xaaaac45b9df0>
> .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: 0xaaaac45b9df0>
> 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: 0xaaaac4e373a0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0xaaaac4e373a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaaac4e373a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaaac4e373a0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2431a83418ebbe" "BufferedMatrixFile2431a8e85ce79"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile2431a83418ebbe" "BufferedMatrixFile2431a8e85ce79"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaaac67709b0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaaac67709b0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0xaaaac67709b0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0xaaaac67709b0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0xaaaac67709b0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0xaaaac67709b0>
> .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: 0xaaaac6247010>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaaac6247010>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0xaaaac6247010>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0xaaaac6247010>
> 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: 0xaaaac677c530>
> .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: 0xaaaac677c530>
> rm(P)
>
> proc.time()
user system elapsed
0.325 0.059 0.368
BufferedMatrix.Rcheck/tests/Rcodetesting.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
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.342 0.050 0.378