| Back to Build/check report for BioC 3.18: simplified long |
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This page was generated on 2023-05-31 05:44:30 -0000 (Wed, 31 May 2023).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| kunpeng1 | Linux (Ubuntu 22.04.1 LTS) | aarch64 | 4.3.0 (2023-04-21) -- "Already Tomorrow" | 4219 |
| 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 | ||||
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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. Note: If "R CMD check" recently failed on the Linux builder over a missing dependency, add the missing dependency to "Suggests" in your DESCRIPTION file. See the Renviron.bioc for details. |
| Package 241/2197 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.65.0 (landing page) Ben Bolstad
| kunpeng1 | Linux (Ubuntu 22.04.1 LTS) / aarch64 | OK | OK | OK | |||||||||
| Package: BufferedMatrix |
| Version: 1.65.0 |
| Command: /home/biocbuild/R/R-4.3.0/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R-4.3.0/site-library --timings BufferedMatrix_1.65.0.tar.gz |
| StartedAt: 2023-05-30 02:19:31 -0000 (Tue, 30 May 2023) |
| EndedAt: 2023-05-30 02:19:57 -0000 (Tue, 30 May 2023) |
| EllapsedTime: 26.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/R/R-4.3.0/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R-4.3.0/site-library --timings BufferedMatrix_1.65.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.3.0 (2023-04-21)
* 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 22.04.2 LTS
* using session charset: UTF-8
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.65.0’
* 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 11.3.0-1ubuntu1~22.04.1) 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 loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ...
‘BufferedMatrix.Rnw’... OK
OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/R/R-4.3.0/bin/R CMD INSTALL BufferedMatrix ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/R/R-4.3.0/site-library’ * installing *source* package ‘BufferedMatrix’ ... ** using staged installation ** libs using C compiler: ‘gcc (Ubuntu 11.3.0-1ubuntu1~22.04.1) 11.3.0’ gcc -I"/home/biocbuild/R/R-4.3.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o gcc -I"/home/biocbuild/R/R-4.3.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o gcc -I"/home/biocbuild/R/R-4.3.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o gcc -I"/home/biocbuild/R/R-4.3.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -c init_package.c -o init_package.o gcc -shared -L/home/biocbuild/R/R-4.3.0/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/R/R-4.3.0/lib -lR installing to /home/biocbuild/R/R-4.3.0/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 4.3.0 (2023-04-21) -- "Already Tomorrow"
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
0.333 0.039 0.355
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.3.0 (2023-04-21) -- "Already Tomorrow"
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-3.18-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 457491 24.5 981592 52.5 651048 34.8
Vcells 842681 6.5 8388608 64.0 2063992 15.8
>
>
>
>
> ##
> ## 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] "Tue May 30 02:19:47 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] "Tue May 30 02:19:47 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: 0xaaaac80533f0>
>
>
>
> 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] "Tue May 30 02:19:47 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] "Tue May 30 02:19:47 2023"
>
> ColMode(tmp2)
<pointer: 0xaaaac80533f0>
>
>
>
> ### 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,] 101.4814612 0.3112575 2.2168902 0.9601311
[2,] -0.2700225 -0.2283436 -0.6060944 0.7714475
[3,] 2.5966166 -0.3961275 1.3520555 0.5855681
[4,] -0.7742962 -1.4164393 -3.0951051 -0.1687762
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.18-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,] 101.4814612 0.3112575 2.2168902 0.9601311
[2,] 0.2700225 0.2283436 0.6060944 0.7714475
[3,] 2.5966166 0.3961275 1.3520555 0.5855681
[4,] 0.7742962 1.4164393 3.0951051 0.1687762
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.18-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,] 10.0738007 0.5579046 1.4889225 0.9798628
[2,] 0.5196369 0.4778531 0.7785206 0.8783209
[3,] 1.6114021 0.6293866 1.1627792 0.7652242
[4,] 0.8799410 1.1901425 1.7592911 0.4108238
>
> 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-3.18-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,] 227.21947 30.89030 42.10611 35.75876
[2,] 30.46639 30.00687 33.39130 34.55466
[3,] 43.71064 31.68999 37.97985 33.23781
[4,] 34.57371 38.31786 45.68802 29.27701
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0xaaaac7843960>
> exp(tmp5)
<pointer: 0xaaaac7843960>
> log(tmp5,2)
<pointer: 0xaaaac7843960>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 472.9276
> Min(tmp5)
[1] 52.77588
> mean(tmp5)
[1] 74.22859
> Sum(tmp5)
[1] 14845.72
> Var(tmp5)
[1] 873.9202
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.72931 71.26672 72.31099 70.58389 73.38841 71.89433 71.90645 71.42653
[9] 73.35837 74.42092
> rowSums(tmp5)
[1] 1834.586 1425.334 1446.220 1411.678 1467.768 1437.887 1438.129 1428.531
[9] 1467.167 1488.418
> rowVars(tmp5)
[1] 8130.55286 70.77070 79.40680 109.56206 74.01879 62.77154
[7] 94.32995 52.80084 34.02879 74.18350
> rowSd(tmp5)
[1] 90.169578 8.412532 8.911049 10.467190 8.603417 7.922850 9.712361
[8] 7.266419 5.833420 8.612985
> rowMax(tmp5)
[1] 472.92755 86.25078 90.97796 95.09362 87.11403 83.50374 94.52515
[8] 84.94989 84.04851 89.21254
> rowMin(tmp5)
[1] 58.85763 54.80503 58.30741 54.19647 53.87808 52.77588 56.17701 55.71792
[9] 59.28644 53.68866
>
> colMeans(tmp5)
[1] 112.64748 68.90085 74.57701 70.16699 67.49585 72.95482 73.42239
[8] 70.27845 76.29331 71.49286 73.92371 74.79572 69.18947 73.37874
[15] 74.02285 68.38820 71.70636 72.81456 74.94048 73.18173
> colSums(tmp5)
[1] 1126.4748 689.0085 745.7701 701.6699 674.9585 729.5482 734.2239
[8] 702.7845 762.9331 714.9286 739.2371 747.9572 691.8947 733.7874
[15] 740.2285 683.8820 717.0636 728.1456 749.4048 731.8173
> colVars(tmp5)
[1] 16111.27447 75.82816 107.48504 61.34285 26.31008 89.45899
[7] 52.06362 121.90671 34.48508 11.59195 104.45203 53.11480
[13] 29.09721 117.09950 75.68193 50.47213 94.23034 61.00736
[19] 116.04954 78.60356
> colSd(tmp5)
[1] 126.930195 8.707937 10.367499 7.832167 5.129336 9.458276
[7] 7.215512 11.041137 5.872400 3.404695 10.220178 7.287990
[13] 5.394183 10.821252 8.699536 7.104374 9.707231 7.810721
[19] 10.772629 8.865865
> colMax(tmp5)
[1] 472.92755 80.31034 95.09362 84.94989 74.03182 87.07251 82.76257
[8] 87.39910 82.73978 75.22067 89.21254 86.78945 76.79039 89.44218
[15] 89.31833 81.09224 89.83849 87.11403 94.52515 83.32930
> colMin(tmp5)
[1] 59.28644 53.68866 61.61918 56.17701 58.88794 62.08329 62.45481 54.80503
[9] 64.11079 63.44911 52.77588 65.20221 59.04127 53.87808 63.67437 59.03772
[17] 55.92468 55.71792 61.58850 54.19647
>
>
> ### 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] 91.72931 71.26672 72.31099 70.58389 73.38841 71.89433 71.90645 NA
[9] 73.35837 74.42092
> rowSums(tmp5)
[1] 1834.586 1425.334 1446.220 1411.678 1467.768 1437.887 1438.129 NA
[9] 1467.167 1488.418
> rowVars(tmp5)
[1] 8130.55286 70.77070 79.40680 109.56206 74.01879 62.77154
[7] 94.32995 53.36562 34.02879 74.18350
> rowSd(tmp5)
[1] 90.169578 8.412532 8.911049 10.467190 8.603417 7.922850 9.712361
[8] 7.305177 5.833420 8.612985
> rowMax(tmp5)
[1] 472.92755 86.25078 90.97796 95.09362 87.11403 83.50374 94.52515
[8] NA 84.04851 89.21254
> rowMin(tmp5)
[1] 58.85763 54.80503 58.30741 54.19647 53.87808 52.77588 56.17701 NA
[9] 59.28644 53.68866
>
> colMeans(tmp5)
[1] 112.64748 68.90085 74.57701 70.16699 67.49585 72.95482 NA
[8] 70.27845 76.29331 71.49286 73.92371 74.79572 69.18947 73.37874
[15] 74.02285 68.38820 71.70636 72.81456 74.94048 73.18173
> colSums(tmp5)
[1] 1126.4748 689.0085 745.7701 701.6699 674.9585 729.5482 NA
[8] 702.7845 762.9331 714.9286 739.2371 747.9572 691.8947 733.7874
[15] 740.2285 683.8820 717.0636 728.1456 749.4048 731.8173
> colVars(tmp5)
[1] 16111.27447 75.82816 107.48504 61.34285 26.31008 89.45899
[7] NA 121.90671 34.48508 11.59195 104.45203 53.11480
[13] 29.09721 117.09950 75.68193 50.47213 94.23034 61.00736
[19] 116.04954 78.60356
> colSd(tmp5)
[1] 126.930195 8.707937 10.367499 7.832167 5.129336 9.458276
[7] NA 11.041137 5.872400 3.404695 10.220178 7.287990
[13] 5.394183 10.821252 8.699536 7.104374 9.707231 7.810721
[19] 10.772629 8.865865
> colMax(tmp5)
[1] 472.92755 80.31034 95.09362 84.94989 74.03182 87.07251 NA
[8] 87.39910 82.73978 75.22067 89.21254 86.78945 76.79039 89.44218
[15] 89.31833 81.09224 89.83849 87.11403 94.52515 83.32930
> colMin(tmp5)
[1] 59.28644 53.68866 61.61918 56.17701 58.88794 62.08329 NA 54.80503
[9] 64.11079 63.44911 52.77588 65.20221 59.04127 53.87808 63.67437 59.03772
[17] 55.92468 55.71792 61.58850 54.19647
>
> Max(tmp5,na.rm=TRUE)
[1] 472.9276
> Min(tmp5,na.rm=TRUE)
[1] 52.77588
> mean(tmp5,na.rm=TRUE)
[1] 74.27465
> Sum(tmp5,na.rm=TRUE)
[1] 14780.66
> Var(tmp5,na.rm=TRUE)
[1] 877.9075
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.72931 71.26672 72.31099 70.58389 73.38841 71.89433 71.90645 71.76149
[9] 73.35837 74.42092
> rowSums(tmp5,na.rm=TRUE)
[1] 1834.586 1425.334 1446.220 1411.678 1467.768 1437.887 1438.129 1363.468
[9] 1467.167 1488.418
> rowVars(tmp5,na.rm=TRUE)
[1] 8130.55286 70.77070 79.40680 109.56206 74.01879 62.77154
[7] 94.32995 53.36562 34.02879 74.18350
> rowSd(tmp5,na.rm=TRUE)
[1] 90.169578 8.412532 8.911049 10.467190 8.603417 7.922850 9.712361
[8] 7.305177 5.833420 8.612985
> rowMax(tmp5,na.rm=TRUE)
[1] 472.92755 86.25078 90.97796 95.09362 87.11403 83.50374 94.52515
[8] 84.94989 84.04851 89.21254
> rowMin(tmp5,na.rm=TRUE)
[1] 58.85763 54.80503 58.30741 54.19647 53.87808 52.77588 56.17701 55.71792
[9] 59.28644 53.68866
>
> colMeans(tmp5,na.rm=TRUE)
[1] 112.64748 68.90085 74.57701 70.16699 67.49585 72.95482 74.35129
[8] 70.27845 76.29331 71.49286 73.92371 74.79572 69.18947 73.37874
[15] 74.02285 68.38820 71.70636 72.81456 74.94048 73.18173
> colSums(tmp5,na.rm=TRUE)
[1] 1126.4748 689.0085 745.7701 701.6699 674.9585 729.5482 669.1616
[8] 702.7845 762.9331 714.9286 739.2371 747.9572 691.8947 733.7874
[15] 740.2285 683.8820 717.0636 728.1456 749.4048 731.8173
> colVars(tmp5,na.rm=TRUE)
[1] 16111.27447 75.82816 107.48504 61.34285 26.31008 89.45899
[7] 48.86451 121.90671 34.48508 11.59195 104.45203 53.11480
[13] 29.09721 117.09950 75.68193 50.47213 94.23034 61.00736
[19] 116.04954 78.60356
> colSd(tmp5,na.rm=TRUE)
[1] 126.930195 8.707937 10.367499 7.832167 5.129336 9.458276
[7] 6.990316 11.041137 5.872400 3.404695 10.220178 7.287990
[13] 5.394183 10.821252 8.699536 7.104374 9.707231 7.810721
[19] 10.772629 8.865865
> colMax(tmp5,na.rm=TRUE)
[1] 472.92755 80.31034 95.09362 84.94989 74.03182 87.07251 82.76257
[8] 87.39910 82.73978 75.22067 89.21254 86.78945 76.79039 89.44218
[15] 89.31833 81.09224 89.83849 87.11403 94.52515 83.32930
> colMin(tmp5,na.rm=TRUE)
[1] 59.28644 53.68866 61.61918 56.17701 58.88794 62.08329 62.45481 54.80503
[9] 64.11079 63.44911 52.77588 65.20221 59.04127 53.87808 63.67437 59.03772
[17] 55.92468 55.71792 61.58850 54.19647
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.72931 71.26672 72.31099 70.58389 73.38841 71.89433 71.90645 NaN
[9] 73.35837 74.42092
> rowSums(tmp5,na.rm=TRUE)
[1] 1834.586 1425.334 1446.220 1411.678 1467.768 1437.887 1438.129 0.000
[9] 1467.167 1488.418
> rowVars(tmp5,na.rm=TRUE)
[1] 8130.55286 70.77070 79.40680 109.56206 74.01879 62.77154
[7] 94.32995 NA 34.02879 74.18350
> rowSd(tmp5,na.rm=TRUE)
[1] 90.169578 8.412532 8.911049 10.467190 8.603417 7.922850 9.712361
[8] NA 5.833420 8.612985
> rowMax(tmp5,na.rm=TRUE)
[1] 472.92755 86.25078 90.97796 95.09362 87.11403 83.50374 94.52515
[8] NA 84.04851 89.21254
> rowMin(tmp5,na.rm=TRUE)
[1] 58.85763 54.80503 58.30741 54.19647 53.87808 52.77588 56.17701 NA
[9] 59.28644 53.68866
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.76076 68.24692 74.83137 68.52445 67.26096 73.70593 NaN
[8] 69.60649 76.51866 71.07866 73.15856 74.53652 68.86199 74.18705
[15] 74.85662 69.17951 71.28881 74.71419 76.42403 72.70586
> colSums(tmp5,na.rm=TRUE)
[1] 1050.8469 614.2222 673.4823 616.7200 605.3486 663.3534 0.0000
[8] 626.4584 688.6680 639.7079 658.4270 670.8287 619.7579 667.6835
[15] 673.7096 622.6156 641.5993 672.4277 687.8163 654.3527
> colVars(tmp5,na.rm=TRUE)
[1] 17934.84394 80.49580 120.19283 38.65873 28.97813 94.29446
[7] NA 132.06526 38.22441 11.11086 110.92223 58.99838
[13] 31.52783 124.38652 77.32146 49.73660 104.04780 28.03672
[19] 105.79526 85.88135
> colSd(tmp5,na.rm=TRUE)
[1] 133.921036 8.971945 10.963249 6.217614 5.383134 9.710534
[7] NA 11.491965 6.182589 3.333296 10.531962 7.681040
[13] 5.614965 11.152871 8.793262 7.052418 10.200382 5.294971
[19] 10.285682 9.267219
> colMax(tmp5,na.rm=TRUE)
[1] 472.92755 80.31034 95.09362 74.42717 74.03182 87.07251 -Inf
[8] 87.39910 82.73978 74.18827 89.21254 86.78945 76.79039 89.44218
[15] 89.31833 81.09224 89.83849 87.11403 94.52515 83.32930
> colMin(tmp5,na.rm=TRUE)
[1] 59.28644 53.68866 61.61918 56.17701 58.88794 62.08329 Inf 54.80503
[9] 64.11079 63.44911 52.77588 65.20221 59.04127 53.87808 63.67437 59.03772
[17] 55.92468 68.16570 61.85078 54.19647
>
>
>
>
> 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] 160.1360 217.6100 163.9205 307.7580 198.3562 193.8130 167.5171 220.2981
[9] 355.9141 292.5971
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 160.1360 217.6100 163.9205 307.7580 198.3562 193.8130 167.5171 220.2981
[9] 355.9141 292.5971
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -2.842171e-14 -3.410605e-13 0.000000e+00 1.705303e-13 -1.136868e-13
[6] 5.684342e-14 2.557954e-13 2.842171e-14 2.842171e-14 0.000000e+00
[11] 5.684342e-14 2.273737e-13 0.000000e+00 0.000000e+00 -2.842171e-13
[16] -5.684342e-14 1.136868e-13 -3.979039e-13 -1.136868e-13 -5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
1 8
7 8
10 19
9 14
10 19
6 4
1 7
5 5
10 20
6 1
7 20
4 4
6 1
10 9
7 18
4 8
6 8
7 17
9 2
4 10
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] 2.016698
> Min(tmp)
[1] -2.957161
> mean(tmp)
[1] 0.167914
> Sum(tmp)
[1] 16.7914
> Var(tmp)
[1] 1.024334
>
> rowMeans(tmp)
[1] 0.167914
> rowSums(tmp)
[1] 16.7914
> rowVars(tmp)
[1] 1.024334
> rowSd(tmp)
[1] 1.012094
> rowMax(tmp)
[1] 2.016698
> rowMin(tmp)
[1] -2.957161
>
> colMeans(tmp)
[1] -0.46186375 1.62579786 0.27715582 0.25910262 1.10696854 0.29994584
[7] -0.95426805 0.89079072 0.26357454 0.08427752 0.01614744 -0.15749850
[13] -0.42353467 -0.32063188 -0.98365939 1.81720031 1.01558939 -0.36973281
[19] 1.34533333 1.16003367 1.17293649 1.68939390 1.31765990 0.34565140
[25] -1.93812182 0.28399529 -0.20923849 0.83476953 -0.11097442 -1.12501453
[31] 0.59294883 -0.74333004 1.31394386 0.62423466 1.34502302 -1.84938684
[37] 1.09394998 -0.25194562 -1.17608493 -0.01374789 0.68406218 0.63619574
[43] 1.14568422 1.60403864 0.02916164 0.23032414 0.67931551 -0.33268871
[49] 1.61036340 1.33931307 0.97624287 0.24106010 -1.66717133 0.85978398
[55] -1.32840279 -0.14543082 1.67685871 -0.55893176 0.14338522 1.77388630
[61] -0.25565409 0.70866835 1.93858490 -0.18399449 -0.30552277 -0.64388788
[67] 0.28252544 0.86454162 0.77511473 -0.21657044 -1.05448287 -0.37635830
[73] 1.50078802 0.53181978 0.77954888 1.17162616 -0.96223453 0.04241109
[79] -0.98021040 -0.74760612 -0.43507032 0.62302867 -2.22037143 -0.42795274
[85] -1.00773635 0.48884294 -1.37256646 0.74322397 -1.79119082 0.27720710
[91] 0.20465858 0.16438387 2.01669769 0.55437915 -0.53310401 0.85871844
[97] -1.34009070 -2.95716053 0.88267705 -0.09072545
> colSums(tmp)
[1] -0.46186375 1.62579786 0.27715582 0.25910262 1.10696854 0.29994584
[7] -0.95426805 0.89079072 0.26357454 0.08427752 0.01614744 -0.15749850
[13] -0.42353467 -0.32063188 -0.98365939 1.81720031 1.01558939 -0.36973281
[19] 1.34533333 1.16003367 1.17293649 1.68939390 1.31765990 0.34565140
[25] -1.93812182 0.28399529 -0.20923849 0.83476953 -0.11097442 -1.12501453
[31] 0.59294883 -0.74333004 1.31394386 0.62423466 1.34502302 -1.84938684
[37] 1.09394998 -0.25194562 -1.17608493 -0.01374789 0.68406218 0.63619574
[43] 1.14568422 1.60403864 0.02916164 0.23032414 0.67931551 -0.33268871
[49] 1.61036340 1.33931307 0.97624287 0.24106010 -1.66717133 0.85978398
[55] -1.32840279 -0.14543082 1.67685871 -0.55893176 0.14338522 1.77388630
[61] -0.25565409 0.70866835 1.93858490 -0.18399449 -0.30552277 -0.64388788
[67] 0.28252544 0.86454162 0.77511473 -0.21657044 -1.05448287 -0.37635830
[73] 1.50078802 0.53181978 0.77954888 1.17162616 -0.96223453 0.04241109
[79] -0.98021040 -0.74760612 -0.43507032 0.62302867 -2.22037143 -0.42795274
[85] -1.00773635 0.48884294 -1.37256646 0.74322397 -1.79119082 0.27720710
[91] 0.20465858 0.16438387 2.01669769 0.55437915 -0.53310401 0.85871844
[97] -1.34009070 -2.95716053 0.88267705 -0.09072545
> 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] -0.46186375 1.62579786 0.27715582 0.25910262 1.10696854 0.29994584
[7] -0.95426805 0.89079072 0.26357454 0.08427752 0.01614744 -0.15749850
[13] -0.42353467 -0.32063188 -0.98365939 1.81720031 1.01558939 -0.36973281
[19] 1.34533333 1.16003367 1.17293649 1.68939390 1.31765990 0.34565140
[25] -1.93812182 0.28399529 -0.20923849 0.83476953 -0.11097442 -1.12501453
[31] 0.59294883 -0.74333004 1.31394386 0.62423466 1.34502302 -1.84938684
[37] 1.09394998 -0.25194562 -1.17608493 -0.01374789 0.68406218 0.63619574
[43] 1.14568422 1.60403864 0.02916164 0.23032414 0.67931551 -0.33268871
[49] 1.61036340 1.33931307 0.97624287 0.24106010 -1.66717133 0.85978398
[55] -1.32840279 -0.14543082 1.67685871 -0.55893176 0.14338522 1.77388630
[61] -0.25565409 0.70866835 1.93858490 -0.18399449 -0.30552277 -0.64388788
[67] 0.28252544 0.86454162 0.77511473 -0.21657044 -1.05448287 -0.37635830
[73] 1.50078802 0.53181978 0.77954888 1.17162616 -0.96223453 0.04241109
[79] -0.98021040 -0.74760612 -0.43507032 0.62302867 -2.22037143 -0.42795274
[85] -1.00773635 0.48884294 -1.37256646 0.74322397 -1.79119082 0.27720710
[91] 0.20465858 0.16438387 2.01669769 0.55437915 -0.53310401 0.85871844
[97] -1.34009070 -2.95716053 0.88267705 -0.09072545
> colMin(tmp)
[1] -0.46186375 1.62579786 0.27715582 0.25910262 1.10696854 0.29994584
[7] -0.95426805 0.89079072 0.26357454 0.08427752 0.01614744 -0.15749850
[13] -0.42353467 -0.32063188 -0.98365939 1.81720031 1.01558939 -0.36973281
[19] 1.34533333 1.16003367 1.17293649 1.68939390 1.31765990 0.34565140
[25] -1.93812182 0.28399529 -0.20923849 0.83476953 -0.11097442 -1.12501453
[31] 0.59294883 -0.74333004 1.31394386 0.62423466 1.34502302 -1.84938684
[37] 1.09394998 -0.25194562 -1.17608493 -0.01374789 0.68406218 0.63619574
[43] 1.14568422 1.60403864 0.02916164 0.23032414 0.67931551 -0.33268871
[49] 1.61036340 1.33931307 0.97624287 0.24106010 -1.66717133 0.85978398
[55] -1.32840279 -0.14543082 1.67685871 -0.55893176 0.14338522 1.77388630
[61] -0.25565409 0.70866835 1.93858490 -0.18399449 -0.30552277 -0.64388788
[67] 0.28252544 0.86454162 0.77511473 -0.21657044 -1.05448287 -0.37635830
[73] 1.50078802 0.53181978 0.77954888 1.17162616 -0.96223453 0.04241109
[79] -0.98021040 -0.74760612 -0.43507032 0.62302867 -2.22037143 -0.42795274
[85] -1.00773635 0.48884294 -1.37256646 0.74322397 -1.79119082 0.27720710
[91] 0.20465858 0.16438387 2.01669769 0.55437915 -0.53310401 0.85871844
[97] -1.34009070 -2.95716053 0.88267705 -0.09072545
> colMedians(tmp)
[1] -0.46186375 1.62579786 0.27715582 0.25910262 1.10696854 0.29994584
[7] -0.95426805 0.89079072 0.26357454 0.08427752 0.01614744 -0.15749850
[13] -0.42353467 -0.32063188 -0.98365939 1.81720031 1.01558939 -0.36973281
[19] 1.34533333 1.16003367 1.17293649 1.68939390 1.31765990 0.34565140
[25] -1.93812182 0.28399529 -0.20923849 0.83476953 -0.11097442 -1.12501453
[31] 0.59294883 -0.74333004 1.31394386 0.62423466 1.34502302 -1.84938684
[37] 1.09394998 -0.25194562 -1.17608493 -0.01374789 0.68406218 0.63619574
[43] 1.14568422 1.60403864 0.02916164 0.23032414 0.67931551 -0.33268871
[49] 1.61036340 1.33931307 0.97624287 0.24106010 -1.66717133 0.85978398
[55] -1.32840279 -0.14543082 1.67685871 -0.55893176 0.14338522 1.77388630
[61] -0.25565409 0.70866835 1.93858490 -0.18399449 -0.30552277 -0.64388788
[67] 0.28252544 0.86454162 0.77511473 -0.21657044 -1.05448287 -0.37635830
[73] 1.50078802 0.53181978 0.77954888 1.17162616 -0.96223453 0.04241109
[79] -0.98021040 -0.74760612 -0.43507032 0.62302867 -2.22037143 -0.42795274
[85] -1.00773635 0.48884294 -1.37256646 0.74322397 -1.79119082 0.27720710
[91] 0.20465858 0.16438387 2.01669769 0.55437915 -0.53310401 0.85871844
[97] -1.34009070 -2.95716053 0.88267705 -0.09072545
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.4618638 1.625798 0.2771558 0.2591026 1.106969 0.2999458 -0.954268
[2,] -0.4618638 1.625798 0.2771558 0.2591026 1.106969 0.2999458 -0.954268
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.8907907 0.2635745 0.08427752 0.01614744 -0.1574985 -0.4235347 -0.3206319
[2,] 0.8907907 0.2635745 0.08427752 0.01614744 -0.1574985 -0.4235347 -0.3206319
[,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22]
[1,] -0.9836594 1.8172 1.015589 -0.3697328 1.345333 1.160034 1.172936 1.689394
[2,] -0.9836594 1.8172 1.015589 -0.3697328 1.345333 1.160034 1.172936 1.689394
[,23] [,24] [,25] [,26] [,27] [,28] [,29]
[1,] 1.31766 0.3456514 -1.938122 0.2839953 -0.2092385 0.8347695 -0.1109744
[2,] 1.31766 0.3456514 -1.938122 0.2839953 -0.2092385 0.8347695 -0.1109744
[,30] [,31] [,32] [,33] [,34] [,35] [,36] [,37]
[1,] -1.125015 0.5929488 -0.74333 1.313944 0.6242347 1.345023 -1.849387 1.09395
[2,] -1.125015 0.5929488 -0.74333 1.313944 0.6242347 1.345023 -1.849387 1.09395
[,38] [,39] [,40] [,41] [,42] [,43] [,44]
[1,] -0.2519456 -1.176085 -0.01374789 0.6840622 0.6361957 1.145684 1.604039
[2,] -0.2519456 -1.176085 -0.01374789 0.6840622 0.6361957 1.145684 1.604039
[,45] [,46] [,47] [,48] [,49] [,50] [,51]
[1,] 0.02916164 0.2303241 0.6793155 -0.3326887 1.610363 1.339313 0.9762429
[2,] 0.02916164 0.2303241 0.6793155 -0.3326887 1.610363 1.339313 0.9762429
[,52] [,53] [,54] [,55] [,56] [,57] [,58]
[1,] 0.2410601 -1.667171 0.859784 -1.328403 -0.1454308 1.676859 -0.5589318
[2,] 0.2410601 -1.667171 0.859784 -1.328403 -0.1454308 1.676859 -0.5589318
[,59] [,60] [,61] [,62] [,63] [,64] [,65]
[1,] 0.1433852 1.773886 -0.2556541 0.7086684 1.938585 -0.1839945 -0.3055228
[2,] 0.1433852 1.773886 -0.2556541 0.7086684 1.938585 -0.1839945 -0.3055228
[,66] [,67] [,68] [,69] [,70] [,71] [,72]
[1,] -0.6438879 0.2825254 0.8645416 0.7751147 -0.2165704 -1.054483 -0.3763583
[2,] -0.6438879 0.2825254 0.8645416 0.7751147 -0.2165704 -1.054483 -0.3763583
[,73] [,74] [,75] [,76] [,77] [,78] [,79]
[1,] 1.500788 0.5318198 0.7795489 1.171626 -0.9622345 0.04241109 -0.9802104
[2,] 1.500788 0.5318198 0.7795489 1.171626 -0.9622345 0.04241109 -0.9802104
[,80] [,81] [,82] [,83] [,84] [,85] [,86]
[1,] -0.7476061 -0.4350703 0.6230287 -2.220371 -0.4279527 -1.007736 0.4888429
[2,] -0.7476061 -0.4350703 0.6230287 -2.220371 -0.4279527 -1.007736 0.4888429
[,87] [,88] [,89] [,90] [,91] [,92] [,93]
[1,] -1.372566 0.743224 -1.791191 0.2772071 0.2046586 0.1643839 2.016698
[2,] -1.372566 0.743224 -1.791191 0.2772071 0.2046586 0.1643839 2.016698
[,94] [,95] [,96] [,97] [,98] [,99] [,100]
[1,] 0.5543791 -0.533104 0.8587184 -1.340091 -2.957161 0.882677 -0.09072545
[2,] 0.5543791 -0.533104 0.8587184 -1.340091 -2.957161 0.882677 -0.09072545
>
>
> Max(tmp2)
[1] 2.929547
> Min(tmp2)
[1] -1.826108
> mean(tmp2)
[1] 0.1943672
> Sum(tmp2)
[1] 19.43672
> Var(tmp2)
[1] 0.8711067
>
> rowMeans(tmp2)
[1] 0.273088911 -0.321783630 0.211043443 0.437030155 1.232369040
[6] -0.628819832 -0.306798613 0.636021220 1.827427995 -0.779706981
[11] 0.405308776 -0.231695420 0.656329923 -0.340332050 -0.081072657
[16] 1.824197692 1.304227346 0.290043951 -0.843602534 1.371697404
[21] 0.897549820 1.748288733 0.579619952 0.049805082 -0.406995004
[26] 0.377928053 -0.004018630 2.929546959 0.902687855 -0.894077894
[31] 0.779327287 -0.343313420 1.866423204 -0.087931722 -0.071257742
[36] 1.159030169 -1.780139131 0.117314692 -0.150827407 -1.547682056
[41] -0.249848961 -0.311291374 -0.262037723 0.828392408 -0.225129005
[46] -0.408074999 -0.518517652 0.390409309 0.093135048 -0.351863061
[51] 0.081302822 -1.826108136 -0.278366587 -0.627443323 -0.170748572
[56] -0.585602361 -0.096168687 -0.703190414 0.037341347 0.617435283
[61] -0.635370612 -0.795256749 -0.666604324 1.615963340 -0.056800830
[66] 0.614561700 -0.744640161 2.240926332 0.244102696 -0.004906882
[71] 0.089010612 1.559717226 1.445201305 -1.659585989 -0.900462409
[76] 2.643799583 0.283720465 -0.164781744 0.991383676 -0.210823036
[81] -0.656401431 1.871322134 0.529837010 0.218266046 0.424972967
[86] 0.037855550 -0.199394093 1.605210429 -1.170345723 1.289494803
[91] 0.160812622 1.518149202 0.118339226 -0.664491398 -0.512094581
[96] -0.480913026 0.577360851 0.044664801 1.183701045 -0.838662232
> rowSums(tmp2)
[1] 0.273088911 -0.321783630 0.211043443 0.437030155 1.232369040
[6] -0.628819832 -0.306798613 0.636021220 1.827427995 -0.779706981
[11] 0.405308776 -0.231695420 0.656329923 -0.340332050 -0.081072657
[16] 1.824197692 1.304227346 0.290043951 -0.843602534 1.371697404
[21] 0.897549820 1.748288733 0.579619952 0.049805082 -0.406995004
[26] 0.377928053 -0.004018630 2.929546959 0.902687855 -0.894077894
[31] 0.779327287 -0.343313420 1.866423204 -0.087931722 -0.071257742
[36] 1.159030169 -1.780139131 0.117314692 -0.150827407 -1.547682056
[41] -0.249848961 -0.311291374 -0.262037723 0.828392408 -0.225129005
[46] -0.408074999 -0.518517652 0.390409309 0.093135048 -0.351863061
[51] 0.081302822 -1.826108136 -0.278366587 -0.627443323 -0.170748572
[56] -0.585602361 -0.096168687 -0.703190414 0.037341347 0.617435283
[61] -0.635370612 -0.795256749 -0.666604324 1.615963340 -0.056800830
[66] 0.614561700 -0.744640161 2.240926332 0.244102696 -0.004906882
[71] 0.089010612 1.559717226 1.445201305 -1.659585989 -0.900462409
[76] 2.643799583 0.283720465 -0.164781744 0.991383676 -0.210823036
[81] -0.656401431 1.871322134 0.529837010 0.218266046 0.424972967
[86] 0.037855550 -0.199394093 1.605210429 -1.170345723 1.289494803
[91] 0.160812622 1.518149202 0.118339226 -0.664491398 -0.512094581
[96] -0.480913026 0.577360851 0.044664801 1.183701045 -0.838662232
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] 0.273088911 -0.321783630 0.211043443 0.437030155 1.232369040
[6] -0.628819832 -0.306798613 0.636021220 1.827427995 -0.779706981
[11] 0.405308776 -0.231695420 0.656329923 -0.340332050 -0.081072657
[16] 1.824197692 1.304227346 0.290043951 -0.843602534 1.371697404
[21] 0.897549820 1.748288733 0.579619952 0.049805082 -0.406995004
[26] 0.377928053 -0.004018630 2.929546959 0.902687855 -0.894077894
[31] 0.779327287 -0.343313420 1.866423204 -0.087931722 -0.071257742
[36] 1.159030169 -1.780139131 0.117314692 -0.150827407 -1.547682056
[41] -0.249848961 -0.311291374 -0.262037723 0.828392408 -0.225129005
[46] -0.408074999 -0.518517652 0.390409309 0.093135048 -0.351863061
[51] 0.081302822 -1.826108136 -0.278366587 -0.627443323 -0.170748572
[56] -0.585602361 -0.096168687 -0.703190414 0.037341347 0.617435283
[61] -0.635370612 -0.795256749 -0.666604324 1.615963340 -0.056800830
[66] 0.614561700 -0.744640161 2.240926332 0.244102696 -0.004906882
[71] 0.089010612 1.559717226 1.445201305 -1.659585989 -0.900462409
[76] 2.643799583 0.283720465 -0.164781744 0.991383676 -0.210823036
[81] -0.656401431 1.871322134 0.529837010 0.218266046 0.424972967
[86] 0.037855550 -0.199394093 1.605210429 -1.170345723 1.289494803
[91] 0.160812622 1.518149202 0.118339226 -0.664491398 -0.512094581
[96] -0.480913026 0.577360851 0.044664801 1.183701045 -0.838662232
> rowMin(tmp2)
[1] 0.273088911 -0.321783630 0.211043443 0.437030155 1.232369040
[6] -0.628819832 -0.306798613 0.636021220 1.827427995 -0.779706981
[11] 0.405308776 -0.231695420 0.656329923 -0.340332050 -0.081072657
[16] 1.824197692 1.304227346 0.290043951 -0.843602534 1.371697404
[21] 0.897549820 1.748288733 0.579619952 0.049805082 -0.406995004
[26] 0.377928053 -0.004018630 2.929546959 0.902687855 -0.894077894
[31] 0.779327287 -0.343313420 1.866423204 -0.087931722 -0.071257742
[36] 1.159030169 -1.780139131 0.117314692 -0.150827407 -1.547682056
[41] -0.249848961 -0.311291374 -0.262037723 0.828392408 -0.225129005
[46] -0.408074999 -0.518517652 0.390409309 0.093135048 -0.351863061
[51] 0.081302822 -1.826108136 -0.278366587 -0.627443323 -0.170748572
[56] -0.585602361 -0.096168687 -0.703190414 0.037341347 0.617435283
[61] -0.635370612 -0.795256749 -0.666604324 1.615963340 -0.056800830
[66] 0.614561700 -0.744640161 2.240926332 0.244102696 -0.004906882
[71] 0.089010612 1.559717226 1.445201305 -1.659585989 -0.900462409
[76] 2.643799583 0.283720465 -0.164781744 0.991383676 -0.210823036
[81] -0.656401431 1.871322134 0.529837010 0.218266046 0.424972967
[86] 0.037855550 -0.199394093 1.605210429 -1.170345723 1.289494803
[91] 0.160812622 1.518149202 0.118339226 -0.664491398 -0.512094581
[96] -0.480913026 0.577360851 0.044664801 1.183701045 -0.838662232
>
> colMeans(tmp2)
[1] 0.1943672
> colSums(tmp2)
[1] 19.43672
> colVars(tmp2)
[1] 0.8711067
> colSd(tmp2)
[1] 0.933331
> colMax(tmp2)
[1] 2.929547
> colMin(tmp2)
[1] -1.826108
> colMedians(tmp2)
[1] 0.04126018
> colRanges(tmp2)
[,1]
[1,] -1.826108
[2,] 2.929547
>
> 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] -0.5178228 -3.7222119 -4.8833539 -0.6173750 0.3636737 0.5494144
[7] 0.2616500 -3.6072028 1.5977632 -2.0138490
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8319404
[2,] -0.3611272
[3,] -0.2348113
[4,] 0.4079760
[5,] 1.5931607
>
> rowApply(tmp,sum)
[1] -1.7384473 -3.8939835 -2.5702261 1.3339211 1.3046653 1.6779486
[7] -5.5139662 -2.3679984 -0.6974587 -0.1237688
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 2 9 2 9 9 4 6 7 8 6
[2,] 10 3 1 3 10 10 4 1 4 1
[3,] 6 8 4 4 2 3 3 6 2 2
[4,] 1 7 7 2 1 8 9 10 9 3
[5,] 9 5 5 8 5 5 10 3 6 5
[6,] 7 6 8 5 6 2 1 8 10 8
[7,] 5 4 9 7 7 6 2 5 7 7
[8,] 8 1 10 6 8 1 5 4 3 4
[9,] 3 10 6 1 4 9 8 9 1 10
[10,] 4 2 3 10 3 7 7 2 5 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 4.77641132 0.97973999 -0.26516262 0.87302348 -1.28528979 -0.02248327
[7] 0.69913013 0.98873681 0.56248780 -0.93750214 -0.51950450 0.40647317
[13] 1.64514879 0.47920256 1.79071803 -0.36500348 0.32010358 0.12124671
[19] -0.22444024 3.35675587
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.3190162
[2,] 0.1772891
[3,] 1.1290590
[4,] 1.4787540
[5,] 2.3103255
>
> rowApply(tmp,sum)
[1] 1.916948 2.443626 1.888124 -2.799326 9.930421
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 17 20 9 9 19
[2,] 9 5 19 18 2
[3,] 1 11 20 11 5
[4,] 19 13 1 17 8
[5,] 8 3 10 6 12
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.1290590 -0.3067811 -1.24894809 1.43875136 -0.3097969 -0.7712341
[2,] 2.3103255 -0.7660234 0.06785877 0.34851566 -0.9518911 0.2021641
[3,] 0.1772891 1.2685057 1.35825084 -1.69958699 0.1952002 -0.6470247
[4,] -0.3190162 1.3117539 -0.25932756 0.86591190 -0.8630820 -0.1882526
[5,] 1.4787540 -0.5277151 -0.18299658 -0.08056845 0.6442800 1.3818640
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.5138231 0.01150572 0.4691759 -0.3583488 -0.1597467 -0.5787177
[2,] 0.8424520 0.05036404 1.0364042 -0.9821340 -1.1765203 1.4282129
[3,] 0.2236531 -0.67329644 0.8622644 -0.4436757 -0.6828375 1.0974135
[4,] -2.0360800 1.73301795 -1.4195573 0.3058060 0.5520006 -1.3609719
[5,] 1.1552819 -0.13285447 -0.3857993 0.5408504 0.9475994 -0.1794636
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.5943386 -0.4078430 -0.6800070 -0.5783955 1.6298649 0.2098331
[2,] -0.9250474 -0.5356466 -0.4831068 -0.2507839 0.6237915 -0.1317550
[3,] -0.6834440 1.1157365 0.5637174 0.3811761 -1.2216898 0.4878271
[4,] -0.6782019 0.6631245 1.6852534 0.7779309 -1.3896550 -0.5974582
[5,] 3.3375035 -0.3561689 0.7048610 -0.6949310 0.6777919 0.1527998
[,19] [,20]
[1,] 0.1614926 1.15892233
[2,] 0.4100031 1.32644274
[3,] -0.8917523 1.10039730
[4,] -1.3124080 -0.27011463
[5,] 1.4082243 0.04110814
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.18-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-3.18-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 649 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 562 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.18-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 1.005379 -0.2042533 0.7097084 2.045623 -0.3415709 -0.1324054 0.3074825
col8 col9 col10 col11 col12 col13 col14
row1 -0.526375 1.215263 1.134155 1.289732 0.9353714 1.853403 0.520565
col15 col16 col17 col18 col19 col20
row1 -0.4794122 1.288559 0.108167 -0.1835524 -0.3445053 -1.577546
> tmp[,"col10"]
col10
row1 1.1341546
row2 1.9005757
row3 -1.9547009
row4 -1.1191810
row5 0.3041576
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.005379 -0.2042533 0.7097084 2.045623 -0.3415709 -0.1324054 0.30748250
row5 1.076345 0.1102592 1.6810072 1.519685 1.4554054 -0.5867209 -0.07153151
col8 col9 col10 col11 col12 col13 col14
row1 -0.5263750 1.2152626 1.1341546 1.2897319 0.9353714 1.853403 0.5205650
row5 0.1633553 0.4797779 0.3041576 -0.2106924 -1.1572572 1.755638 0.4857409
col15 col16 col17 col18 col19 col20
row1 -0.4794122 1.288559 0.108167 -0.1835524 -0.3445053 -1.577546
row5 0.2290894 -1.116783 -1.484556 -1.1813066 2.3971055 -1.069496
> tmp[,c("col6","col20")]
col6 col20
row1 -0.13240538 -1.5775456
row2 -1.10186418 -0.2991780
row3 0.01833878 0.5771291
row4 -1.12065052 0.1018358
row5 -0.58672086 -1.0694956
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.1324054 -1.577546
row5 -0.5867209 -1.069496
>
>
>
>
> 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 49.92675 49.63039 50.7997 50.50506 49.04638 104.9878 50.22144 48.04494
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.00351 49.48425 52.29507 48.19113 51.31837 49.50561 50.21805 48.7634
col17 col18 col19 col20
row1 49.03603 48.00586 50.81193 104.8613
> tmp[,"col10"]
col10
row1 49.48425
row2 28.82292
row3 29.78738
row4 29.73867
row5 51.53127
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.92675 49.63039 50.79970 50.50506 49.04638 104.9878 50.22144 48.04494
row5 48.10783 48.05477 50.15778 49.95507 49.66872 105.2857 50.95232 51.19262
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.00351 49.48425 52.29507 48.19113 51.31837 49.50561 50.21805 48.76340
row5 50.10113 51.53127 49.53471 49.59349 48.34932 49.73586 49.97572 48.77806
col17 col18 col19 col20
row1 49.03603 48.00586 50.81193 104.8613
row5 50.23681 48.88365 51.05819 105.4551
> tmp[,c("col6","col20")]
col6 col20
row1 104.98779 104.86134
row2 75.66821 76.33891
row3 75.69475 75.23098
row4 73.98907 74.73063
row5 105.28572 105.45506
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.9878 104.8613
row5 105.2857 105.4551
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.9878 104.8613
row5 105.2857 105.4551
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.2443024
[2,] 0.1049565
[3,] 0.1305160
[4,] -0.2838849
[5,] 0.1884513
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.0964277 -0.40228386
[2,] 1.0362728 0.89698057
[3,] -0.4829333 0.23391101
[4,] -0.1795308 -0.01962683
[5,] 2.1156559 -0.11062186
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.43330862 0.07873309
[2,] -0.25306408 1.53552325
[3,] -0.07652937 -0.42457002
[4,] 2.55869356 0.33209994
[5,] -0.09588774 1.28653853
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.433309
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.4333086
[2,] -0.2530641
>
>
>
> 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 -1.644539 0.6710735 0.04839734 0.7547574 0.40447840 1.26272429
row1 2.647725 1.0436212 -0.07705641 0.3413155 -0.02125259 0.09373461
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.5646136 -0.05203307 -0.2353559 1.3312788 0.8391532 1.0039243
row1 -0.9738245 -0.65731485 -0.3241807 0.9853953 -0.9822006 -0.8151814
[,13] [,14] [,15] [,16] [,17] [,18]
row3 0.6823594 -1.2779551 -1.1663540 -0.7626421 -0.9186413 -0.4861206
row1 -0.6304507 -0.2882094 0.3836131 0.6346589 1.3182967 -0.5823038
[,19] [,20]
row3 0.4686420 0.2741502
row1 0.5865292 0.3963665
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.027775 0.2926552 -0.8570404 -1.949886 -0.6837991 -0.8407367 1.972252
[,8] [,9] [,10]
row2 0.2280788 0.1261193 -0.8889439
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.4554009 -0.4218949 0.52749 -0.8485476 -1.161193 -0.9208157 0.7738527
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.4609239 0.1102681 -0.6381406 0.07193092 1.488408 -0.4363016 -0.4063259
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.515909 -0.3217054 -1.511975 -0.8606614 -1.202496 1.268418
>
>
> 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: 0xaaaac892a9b0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BMdc8834045c340"
[2] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BMdc8832d562dc2"
[3] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BMdc883760eeae1"
[4] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BMdc883638e3fa"
[5] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BMdc8831945c881"
[6] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BMdc8834d8382d1"
[7] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BMdc88350801251"
[8] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BMdc88360e05c3f"
[9] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BMdc8836f901aea"
[10] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BMdc88366ec0e2f"
[11] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BMdc88366afa898"
[12] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BMdc8833919f3e3"
[13] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BMdc883d6f48e3"
[14] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BMdc8835d988ef6"
[15] "/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests/BMdc88322497625"
>
>
> ### 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: 0xaaaac71da2c0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0xaaaac71da2c0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.18-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0xaaaac71da2c0>
> rowMedians(tmp)
[1] 0.105007837 0.113665611 0.227586181 0.491819139 0.430557113
[6] -0.325649108 0.657702881 -0.111787831 -0.259901554 0.386972882
[11] -0.277350097 -0.002885932 0.312177865 0.322822462 0.204487250
[16] 0.674594609 0.234608316 -0.242115709 -0.519541704 -0.123682056
[21] 0.301784916 -0.235994791 0.058208508 0.170030044 -0.147522775
[26] -0.481552605 0.066282055 -0.105953805 0.284524474 -0.056281193
[31] -0.101640936 -0.314814399 0.270487874 -0.269740946 0.084624101
[36] 0.247111490 0.155766969 0.256739233 -0.248414906 -0.116436410
[41] 0.150973759 -0.103010438 0.048625691 -0.119082185 0.553416237
[46] -0.415724538 0.102048496 -0.586093199 0.084671911 0.199580917
[51] 0.276202244 0.176973205 -0.438556759 -0.308385808 -0.062155271
[56] 0.067230196 0.343903935 0.153951219 0.482759436 -0.241581053
[61] 0.414363567 -0.228042195 0.195047055 0.064156677 0.374012984
[66] -0.434051787 0.631104673 0.053523856 -0.193707703 0.090922787
[71] 0.134857818 -0.490102394 0.028044901 0.019078376 0.256802107
[76] -0.220171330 -0.415018307 -0.434867060 -0.700945586 0.468026423
[81] -0.162205326 -0.524914411 -0.217774275 0.114268418 0.203078533
[86] -0.613834687 -0.361094677 0.276571237 0.099818964 0.203238230
[91] 0.076571446 -0.328341262 -0.138953595 0.434020748 -0.078850204
[96] -0.166510245 0.364147998 -0.079046607 0.022042798 0.159721480
[101] -0.504860009 -0.196949570 0.190249661 0.158556293 0.066722693
[106] 0.086411733 0.175982559 -0.126478254 0.276207772 -0.193877367
[111] -0.092279849 0.603634572 -0.103882339 -0.139027164 -0.365923729
[116] -0.541395868 0.101919532 -0.284140196 0.018479742 0.305095603
[121] 0.010968978 -0.067516417 -0.069179095 0.598316434 -0.196869813
[126] -0.048020624 -0.116605512 0.088188066 0.175802842 0.025402099
[131] 0.079968247 -0.138740544 -0.395904646 1.016568624 -0.127830971
[136] 0.050260237 -0.181184111 0.478771806 -0.577549467 0.209650377
[141] 0.351073625 -0.303285740 0.163863845 0.262336194 -0.293683164
[146] 0.015060334 0.035005236 0.281479749 -0.131938542 -0.149178232
[151] -0.406333237 0.237184697 -0.588087862 -0.343258827 0.592697212
[156] 0.552386609 -0.306148566 0.323914190 -0.337023813 -0.156139969
[161] 0.410821734 0.205440260 -0.264204489 -0.149451096 0.097600722
[166] 0.267649857 -0.170845199 -0.142052853 0.151612770 0.036073597
[171] 0.334705205 0.240006748 -0.201485002 -0.059766092 -0.685249085
[176] 0.182218957 -0.156094802 0.242196301 -1.284144189 -0.299851686
[181] 0.234588517 -0.224159370 -0.163989618 -0.830162604 -0.120117905
[186] -0.172971550 -0.320068995 -0.265848672 -0.697901704 -0.721103116
[191] -0.105933232 -0.366484228 0.377546467 -0.159464196 0.349659068
[196] 0.411261909 0.432277931 0.581189184 -0.288936756 0.081367152
[201] 0.539089250 -0.323365227 0.653673295 0.214729797 0.115514172
[206] -0.007377515 -0.075642626 -0.263400074 0.464239161 -0.068207061
[211] -0.674448109 -0.440752776 0.500049157 -0.412531621 0.477166018
[216] -0.372996208 -0.084545706 -0.268933544 0.398600768 -0.103415398
[221] -0.070288817 0.363689806 0.318123665 0.428189455 0.527901697
[226] -0.207749435 0.089061270 -0.116409002 0.473045362 0.411617650
>
> proc.time()
user system elapsed
1.883 1.380 3.284
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.3.0 (2023-04-21) -- "Already Tomorrow"
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: 0xaaab2336a3f0>
> .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: 0xaaab2336a3f0>
> .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: 0xaaab2336a3f0>
> .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: 0xaaab2336a3f0>
> 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: 0xaaab21b24e60>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaab21b24e60>
> .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: 0xaaab21b24e60>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaab21b24e60>
> .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: 0xaaab21b24e60>
> 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: 0xaaab22bf87f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaab22bf87f0>
> .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: 0xaaab22bf87f0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0xaaab22bf87f0>
> .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: 0xaaab22bf87f0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0xaaab22bf87f0>
> .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: 0xaaab22bf87f0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0xaaab22bf87f0>
> .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: 0xaaab22bf87f0>
> 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: 0xaaab21c72830>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0xaaab21c72830>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaab21c72830>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaab21c72830>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFiledc89c57a4ff1d" "BufferedMatrixFiledc89c7c55aaa"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFiledc89c57a4ff1d" "BufferedMatrixFiledc89c7c55aaa"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaab22119380>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaab22119380>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0xaaab22119380>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0xaaab22119380>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0xaaab22119380>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0xaaab22119380>
> .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: 0xaaab21921d40>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaaab21921d40>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0xaaab21921d40>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0xaaab21921d40>
> 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: 0xaaab2252ccb0>
> .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: 0xaaab2252ccb0>
> rm(P)
>
> proc.time()
user system elapsed
0.336 0.047 0.366
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.3.0 (2023-04-21) -- "Already Tomorrow"
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
0.330 0.038 0.351