Ben Bolstad
| Snapshot Date: 2024-05-11 09:00:03 -0400 (Sat, 11 May 2024) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: d422a05 |
| git_last_commit_date: 2024-04-30 10:16:21 -0400 (Tue, 30 Apr 2024) |
| Back to Mac ARM64 build report for BioC 3.20 |
|
This page was generated on 2024-05-13 11:32:01 -0400 (Mon, 13 May 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup" | 4378 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 244/2230 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.69.0 (landing page) Ben Bolstad
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | WARNINGS | OK | | |||||||
|
To the developers/maintainers of the BufferedMatrix package: - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.69.0 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.69.0.tar.gz |
| StartedAt: 2024-05-12 07:19:20 -0400 (Sun, 12 May 2024) |
| EndedAt: 2024-05-12 07:20:01 -0400 (Sun, 12 May 2024) |
| EllapsedTime: 41.1 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
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###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.69.0.tar.gz
###
##############################################################################
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* using log directory ‘/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck’
* using R version 4.4.0 Patched (2024-04-24 r86482)
* using platform: aarch64-apple-darwin20
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.6.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.69.0’
* 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 ... WARNING
Found the following significant warnings:
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 15.0.0 (clang-1500.0.40.1)’
* used SDK: ‘MacOSX11.3.sdk’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 WARNING, 2 NOTEs
See
‘/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
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###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
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##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.0.40.1)’
using SDK: ‘MacOSX11.3.sdk’
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch arm64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch arm64 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/arm64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation
installing to /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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
0.341 0.113 0.439
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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] "/Users/biocbuild/bbs-3.20-bioc-mac-arm64/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) limit (Mb) max used (Mb)
Ncells 474155 25.4 1035431 55.3 NA 638594 34.2
Vcells 877595 6.7 8388608 64.0 65536 2072093 15.9
>
>
>
>
> ##
> ## 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] "Sun May 12 07:19:41 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Sun May 12 07:19:42 2024"
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
>
>
> RowMode(tmp2)
<pointer: 0x600000924de0>
>
>
>
> 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] "Sun May 12 07:19:44 2024"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Sun May 12 07:19:45 2024"
>
> ColMode(tmp2)
<pointer: 0x600000924de0>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.7638653 0.2322128 -0.6683061 0.7087083
[2,] -0.2850386 -1.5763104 -1.2433750 -0.5564015
[3,] 0.3524517 -0.7220167 -0.2886663 -0.3412316
[4,] 0.5423588 -0.2217446 -1.2243379 -0.3443694
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2.1 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 99.7638653 0.2322128 0.6683061 0.7087083
[2,] 0.2850386 1.5763104 1.2433750 0.5564015
[3,] 0.3524517 0.7220167 0.2886663 0.3412316
[4,] 0.5423588 0.2217446 1.2243379 0.3443694
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2.1 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9881863 0.4818846 0.8174999 0.8418481
[2,] 0.5338901 1.2555120 1.1150672 0.7459232
[3,] 0.5936765 0.8497156 0.5372768 0.5841503
[4,] 0.7364501 0.4708976 1.1064980 0.5868300
>
> 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: /Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2.1 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 224.64573 30.05106 33.84330 34.12719
[2,] 30.62394 39.13143 37.39405 33.01563
[3,] 31.28922 34.21917 30.66143 31.18273
[4,] 32.90686 29.93072 37.28932 31.21267
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600000920300>
> exp(tmp5)
<pointer: 0x600000920300>
> log(tmp5,2)
<pointer: 0x600000920300>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.5707
> Min(tmp5)
[1] 53.53179
> mean(tmp5)
[1] 72.55531
> Sum(tmp5)
[1] 14511.06
> Var(tmp5)
[1] 855.0762
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 88.40894 71.63433 67.19086 71.37072 68.42241 71.31171 70.98499 69.47739
[9] 74.18422 72.56757
> rowSums(tmp5)
[1] 1768.179 1432.687 1343.817 1427.414 1368.448 1426.234 1419.700 1389.548
[9] 1483.684 1451.351
> rowVars(tmp5)
[1] 8034.51921 67.10586 85.08150 60.25418 72.41790 51.01589
[7] 47.61123 60.82011 80.78291 63.99326
> rowSd(tmp5)
[1] 89.635480 8.191816 9.223963 7.762357 8.509871 7.142541 6.900089
[8] 7.798725 8.987931 7.999578
> rowMax(tmp5)
[1] 467.57065 82.83071 83.25876 84.69741 83.71307 80.57102 82.91133
[8] 81.78271 97.52831 87.86672
> rowMin(tmp5)
[1] 57.76671 55.61954 53.53179 55.13362 55.62775 55.17357 60.28841 53.83625
[9] 59.28661 56.44761
>
> colMeans(tmp5)
[1] 108.66067 69.29462 72.68968 69.91772 70.54663 67.18249 71.29359
[8] 71.38099 69.95386 66.29194 73.07098 69.88401 68.99978 68.20355
[15] 68.89237 73.42061 74.75432 70.98456 72.99933 72.68460
> colSums(tmp5)
[1] 1086.6067 692.9462 726.8968 699.1772 705.4663 671.8249 712.9359
[8] 713.8099 699.5386 662.9194 730.7098 698.8401 689.9978 682.0355
[15] 688.9237 734.2061 747.5432 709.8456 729.9933 726.8460
> colVars(tmp5)
[1] 15954.08002 64.83610 54.88486 21.72031 79.73307 91.23174
[7] 62.46943 52.22303 71.54814 94.95494 104.41967 40.58651
[13] 53.39065 70.55667 56.75991 87.42264 154.26094 76.65369
[19] 28.28331 60.29460
> colSd(tmp5)
[1] 126.309461 8.052087 7.408431 4.660505 8.929338 9.551531
[7] 7.903761 7.226550 8.458613 9.744483 10.218594 6.370754
[13] 7.306890 8.399802 7.533917 9.350008 12.420183 8.755209
[19] 5.318205 7.764960
> colMax(tmp5)
[1] 467.57065 81.44695 87.86672 78.58688 82.91133 83.25876 82.83071
[8] 81.28834 80.57102 80.12242 88.70271 77.30901 80.50335 81.89004
[15] 83.71307 86.45137 97.52831 81.07871 80.27076 81.24549
> colMin(tmp5)
[1] 59.03543 53.83625 63.81776 64.90278 57.84205 55.13362 57.76671 58.21532
[9] 57.46436 55.35693 61.74853 57.31316 59.74253 55.07389 56.44761 54.99593
[17] 57.22623 55.17357 63.14727 53.53179
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 88.40894 71.63433 67.19086 71.37072 68.42241 71.31171 70.98499 69.47739
[9] NA 72.56757
> rowSums(tmp5)
[1] 1768.179 1432.687 1343.817 1427.414 1368.448 1426.234 1419.700 1389.548
[9] NA 1451.351
> rowVars(tmp5)
[1] 8034.51921 67.10586 85.08150 60.25418 72.41790 51.01589
[7] 47.61123 60.82011 84.54638 63.99326
> rowSd(tmp5)
[1] 89.635480 8.191816 9.223963 7.762357 8.509871 7.142541 6.900089
[8] 7.798725 9.194910 7.999578
> rowMax(tmp5)
[1] 467.57065 82.83071 83.25876 84.69741 83.71307 80.57102 82.91133
[8] 81.78271 NA 87.86672
> rowMin(tmp5)
[1] 57.76671 55.61954 53.53179 55.13362 55.62775 55.17357 60.28841 53.83625
[9] NA 56.44761
>
> colMeans(tmp5)
[1] 108.66067 69.29462 72.68968 69.91772 70.54663 67.18249 71.29359
[8] 71.38099 69.95386 66.29194 73.07098 NA 68.99978 68.20355
[15] 68.89237 73.42061 74.75432 70.98456 72.99933 72.68460
> colSums(tmp5)
[1] 1086.6067 692.9462 726.8968 699.1772 705.4663 671.8249 712.9359
[8] 713.8099 699.5386 662.9194 730.7098 NA 689.9978 682.0355
[15] 688.9237 734.2061 747.5432 709.8456 729.9933 726.8460
> colVars(tmp5)
[1] 15954.08002 64.83610 54.88486 21.72031 79.73307 91.23174
[7] 62.46943 52.22303 71.54814 94.95494 104.41967 NA
[13] 53.39065 70.55667 56.75991 87.42264 154.26094 76.65369
[19] 28.28331 60.29460
> colSd(tmp5)
[1] 126.309461 8.052087 7.408431 4.660505 8.929338 9.551531
[7] 7.903761 7.226550 8.458613 9.744483 10.218594 NA
[13] 7.306890 8.399802 7.533917 9.350008 12.420183 8.755209
[19] 5.318205 7.764960
> colMax(tmp5)
[1] 467.57065 81.44695 87.86672 78.58688 82.91133 83.25876 82.83071
[8] 81.28834 80.57102 80.12242 88.70271 NA 80.50335 81.89004
[15] 83.71307 86.45137 97.52831 81.07871 80.27076 81.24549
> colMin(tmp5)
[1] 59.03543 53.83625 63.81776 64.90278 57.84205 55.13362 57.76671 58.21532
[9] 57.46436 55.35693 61.74853 NA 59.74253 55.07389 56.44761 54.99593
[17] 57.22623 55.17357 63.14727 53.53179
>
> Max(tmp5,na.rm=TRUE)
[1] 467.5707
> Min(tmp5,na.rm=TRUE)
[1] 53.53179
> mean(tmp5,na.rm=TRUE)
[1] 72.56482
> Sum(tmp5,na.rm=TRUE)
[1] 14440.4
> Var(tmp5,na.rm=TRUE)
[1] 859.3767
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.40894 71.63433 67.19086 71.37072 68.42241 71.31171 70.98499 69.47739
[9] 74.36947 72.56757
> rowSums(tmp5,na.rm=TRUE)
[1] 1768.179 1432.687 1343.817 1427.414 1368.448 1426.234 1419.700 1389.548
[9] 1413.020 1451.351
> rowVars(tmp5,na.rm=TRUE)
[1] 8034.51921 67.10586 85.08150 60.25418 72.41790 51.01589
[7] 47.61123 60.82011 84.54638 63.99326
> rowSd(tmp5,na.rm=TRUE)
[1] 89.635480 8.191816 9.223963 7.762357 8.509871 7.142541 6.900089
[8] 7.798725 9.194910 7.999578
> rowMax(tmp5,na.rm=TRUE)
[1] 467.57065 82.83071 83.25876 84.69741 83.71307 80.57102 82.91133
[8] 81.78271 97.52831 87.86672
> rowMin(tmp5,na.rm=TRUE)
[1] 57.76671 55.61954 53.53179 55.13362 55.62775 55.17357 60.28841 53.83625
[9] 59.28661 56.44761
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.66067 69.29462 72.68968 69.91772 70.54663 67.18249 71.29359
[8] 71.38099 69.95386 66.29194 73.07098 69.79729 68.99978 68.20355
[15] 68.89237 73.42061 74.75432 70.98456 72.99933 72.68460
> colSums(tmp5,na.rm=TRUE)
[1] 1086.6067 692.9462 726.8968 699.1772 705.4663 671.8249 712.9359
[8] 713.8099 699.5386 662.9194 730.7098 628.1756 689.9978 682.0355
[15] 688.9237 734.2061 747.5432 709.8456 729.9933 726.8460
> colVars(tmp5,na.rm=TRUE)
[1] 15954.08002 64.83610 54.88486 21.72031 79.73307 91.23174
[7] 62.46943 52.22303 71.54814 94.95494 104.41967 45.57522
[13] 53.39065 70.55667 56.75991 87.42264 154.26094 76.65369
[19] 28.28331 60.29460
> colSd(tmp5,na.rm=TRUE)
[1] 126.309461 8.052087 7.408431 4.660505 8.929338 9.551531
[7] 7.903761 7.226550 8.458613 9.744483 10.218594 6.750942
[13] 7.306890 8.399802 7.533917 9.350008 12.420183 8.755209
[19] 5.318205 7.764960
> colMax(tmp5,na.rm=TRUE)
[1] 467.57065 81.44695 87.86672 78.58688 82.91133 83.25876 82.83071
[8] 81.28834 80.57102 80.12242 88.70271 77.30901 80.50335 81.89004
[15] 83.71307 86.45137 97.52831 81.07871 80.27076 81.24549
> colMin(tmp5,na.rm=TRUE)
[1] 59.03543 53.83625 63.81776 64.90278 57.84205 55.13362 57.76671 58.21532
[9] 57.46436 55.35693 61.74853 57.31316 59.74253 55.07389 56.44761 54.99593
[17] 57.22623 55.17357 63.14727 53.53179
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 88.40894 71.63433 67.19086 71.37072 68.42241 71.31171 70.98499 69.47739
[9] NaN 72.56757
> rowSums(tmp5,na.rm=TRUE)
[1] 1768.179 1432.687 1343.817 1427.414 1368.448 1426.234 1419.700 1389.548
[9] 0.000 1451.351
> rowVars(tmp5,na.rm=TRUE)
[1] 8034.51921 67.10586 85.08150 60.25418 72.41790 51.01589
[7] 47.61123 60.82011 NA 63.99326
> rowSd(tmp5,na.rm=TRUE)
[1] 89.635480 8.191816 9.223963 7.762357 8.509871 7.142541 6.900089
[8] 7.798725 NA 7.999578
> rowMax(tmp5,na.rm=TRUE)
[1] 467.57065 82.83071 83.25876 84.69741 83.71307 80.57102 82.91133
[8] 81.78271 NA 87.86672
> rowMin(tmp5,na.rm=TRUE)
[1] 57.76671 55.61954 53.53179 55.13362 55.62775 55.17357 60.28841 53.83625
[9] NA 56.44761
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 112.86639 68.40130 72.72852 70.21046 70.40141 65.96813 71.64249
[8] 70.67875 70.60095 67.07031 71.33412 NaN 69.94222 66.68283
[15] 68.14091 73.81649 72.22388 70.21483 72.73781 72.02742
> colSums(tmp5,na.rm=TRUE)
[1] 1015.7975 615.6117 654.5567 631.8941 633.6127 593.7132 644.7824
[8] 636.1088 635.4086 603.6328 642.0071 0.0000 629.4800 600.1455
[15] 613.2682 664.3484 650.0149 631.9335 654.6403 648.2468
> colVars(tmp5,na.rm=TRUE)
[1] 17749.34849 63.96292 61.72849 23.47130 89.46246 86.04561
[7] 68.90860 53.20312 75.78091 100.00838 83.53449 NA
[13] 50.07234 53.35958 57.50202 96.58733 101.50818 79.56989
[19] 31.04930 62.97270
> colSd(tmp5,na.rm=TRUE)
[1] 133.226681 7.997682 7.856748 4.844719 9.458460 9.276077
[7] 8.301120 7.294047 8.705223 10.000419 9.139720 NA
[13] 7.076181 7.304764 7.583009 9.827885 10.075127 8.920196
[19] 5.572190 7.935534
> colMax(tmp5,na.rm=TRUE)
[1] 467.57065 81.44695 87.86672 78.58688 82.91133 83.25876 82.83071
[8] 81.28834 80.57102 80.12242 85.51994 -Inf 80.50335 76.96240
[15] 83.71307 86.45137 84.69741 81.07871 80.27076 81.24549
> colMin(tmp5,na.rm=TRUE)
[1] 59.03543 53.83625 63.81776 64.90278 57.84205 55.13362 57.76671 58.21532
[9] 57.46436 55.35693 61.74853 Inf 59.74253 55.07389 56.44761 54.99593
[17] 57.22623 55.17357 63.14727 53.53179
>
>
>
>
> 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] 249.8154 348.1567 292.7165 236.7767 163.5545 259.6255 225.3899 200.2870
[9] 273.7990 219.0467
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 249.8154 348.1567 292.7165 236.7767 163.5545 259.6255 225.3899 200.2870
[9] 273.7990 219.0467
>
>
>
> 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 2.842171e-14 -2.273737e-13 -2.273737e-13 -8.526513e-14
[6] 0.000000e+00 -2.273737e-13 1.421085e-13 -1.421085e-14 -8.526513e-14
[11] 0.000000e+00 5.684342e-14 -5.684342e-14 -2.842171e-14 -2.273737e-13
[16] 0.000000e+00 0.000000e+00 7.105427e-14 0.000000e+00 5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
10 2
5 9
9 11
3 19
3 14
2 15
4 10
1 18
9 12
3 8
3 1
6 12
2 15
6 6
4 11
6 6
4 6
3 5
10 8
3 17
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] 2.807802
> Min(tmp)
[1] -2.556584
> mean(tmp)
[1] -0.03283804
> Sum(tmp)
[1] -3.283804
> Var(tmp)
[1] 0.9904742
>
> rowMeans(tmp)
[1] -0.03283804
> rowSums(tmp)
[1] -3.283804
> rowVars(tmp)
[1] 0.9904742
> rowSd(tmp)
[1] 0.9952257
> rowMax(tmp)
[1] 2.807802
> rowMin(tmp)
[1] -2.556584
>
> colMeans(tmp)
[1] 0.034209836 -0.026947381 -1.674826783 0.782501137 -1.012765763
[6] 1.139400240 1.748005666 -0.298918678 -0.682935312 0.707682478
[11] 0.636792825 -1.169740323 -0.881330320 -0.154920406 -0.075581804
[16] -1.605471700 1.480898130 -1.210604267 0.449220000 0.696027570
[21] -0.694824586 -0.513590008 -0.170011797 2.807801987 -0.831235819
[26] 0.718420475 -1.032201065 0.340100030 0.287824626 -1.123872091
[31] -0.834021804 0.231094953 1.533131962 0.620095164 0.482682516
[36] 1.306266306 1.419670684 -0.859495287 0.513178766 -0.313460805
[41] 0.473443279 0.311442594 -0.949503327 0.421015936 0.913440647
[46] -0.469407936 -0.461046034 0.312890026 -0.658316623 0.008941458
[51] -0.806778602 -0.318705867 0.671732535 1.312480845 -1.387111149
[56] 0.990427057 0.923540008 -0.147057185 0.911851962 0.196367766
[61] 0.558894552 0.028925825 -0.073426149 1.100871092 0.968678955
[66] 0.593355754 -0.020767563 1.080245973 1.165984060 -0.675650817
[71] -1.857680224 0.134581902 -2.048055574 0.929615791 0.141771827
[76] -1.112535305 0.707581684 0.641189189 -0.797502322 -1.139520014
[81] -1.508948525 1.030736749 0.901351771 -0.081110494 0.954460151
[86] 0.238744584 -0.847182904 -0.283584323 -0.367298997 -0.015540629
[91] -2.527668709 -1.810129486 -1.067554766 -1.101391198 0.933573373
[96] 0.861409867 -2.556583624 -1.471268313 0.410384194 -0.320658585
> colSums(tmp)
[1] 0.034209836 -0.026947381 -1.674826783 0.782501137 -1.012765763
[6] 1.139400240 1.748005666 -0.298918678 -0.682935312 0.707682478
[11] 0.636792825 -1.169740323 -0.881330320 -0.154920406 -0.075581804
[16] -1.605471700 1.480898130 -1.210604267 0.449220000 0.696027570
[21] -0.694824586 -0.513590008 -0.170011797 2.807801987 -0.831235819
[26] 0.718420475 -1.032201065 0.340100030 0.287824626 -1.123872091
[31] -0.834021804 0.231094953 1.533131962 0.620095164 0.482682516
[36] 1.306266306 1.419670684 -0.859495287 0.513178766 -0.313460805
[41] 0.473443279 0.311442594 -0.949503327 0.421015936 0.913440647
[46] -0.469407936 -0.461046034 0.312890026 -0.658316623 0.008941458
[51] -0.806778602 -0.318705867 0.671732535 1.312480845 -1.387111149
[56] 0.990427057 0.923540008 -0.147057185 0.911851962 0.196367766
[61] 0.558894552 0.028925825 -0.073426149 1.100871092 0.968678955
[66] 0.593355754 -0.020767563 1.080245973 1.165984060 -0.675650817
[71] -1.857680224 0.134581902 -2.048055574 0.929615791 0.141771827
[76] -1.112535305 0.707581684 0.641189189 -0.797502322 -1.139520014
[81] -1.508948525 1.030736749 0.901351771 -0.081110494 0.954460151
[86] 0.238744584 -0.847182904 -0.283584323 -0.367298997 -0.015540629
[91] -2.527668709 -1.810129486 -1.067554766 -1.101391198 0.933573373
[96] 0.861409867 -2.556583624 -1.471268313 0.410384194 -0.320658585
> 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] 0.034209836 -0.026947381 -1.674826783 0.782501137 -1.012765763
[6] 1.139400240 1.748005666 -0.298918678 -0.682935312 0.707682478
[11] 0.636792825 -1.169740323 -0.881330320 -0.154920406 -0.075581804
[16] -1.605471700 1.480898130 -1.210604267 0.449220000 0.696027570
[21] -0.694824586 -0.513590008 -0.170011797 2.807801987 -0.831235819
[26] 0.718420475 -1.032201065 0.340100030 0.287824626 -1.123872091
[31] -0.834021804 0.231094953 1.533131962 0.620095164 0.482682516
[36] 1.306266306 1.419670684 -0.859495287 0.513178766 -0.313460805
[41] 0.473443279 0.311442594 -0.949503327 0.421015936 0.913440647
[46] -0.469407936 -0.461046034 0.312890026 -0.658316623 0.008941458
[51] -0.806778602 -0.318705867 0.671732535 1.312480845 -1.387111149
[56] 0.990427057 0.923540008 -0.147057185 0.911851962 0.196367766
[61] 0.558894552 0.028925825 -0.073426149 1.100871092 0.968678955
[66] 0.593355754 -0.020767563 1.080245973 1.165984060 -0.675650817
[71] -1.857680224 0.134581902 -2.048055574 0.929615791 0.141771827
[76] -1.112535305 0.707581684 0.641189189 -0.797502322 -1.139520014
[81] -1.508948525 1.030736749 0.901351771 -0.081110494 0.954460151
[86] 0.238744584 -0.847182904 -0.283584323 -0.367298997 -0.015540629
[91] -2.527668709 -1.810129486 -1.067554766 -1.101391198 0.933573373
[96] 0.861409867 -2.556583624 -1.471268313 0.410384194 -0.320658585
> colMin(tmp)
[1] 0.034209836 -0.026947381 -1.674826783 0.782501137 -1.012765763
[6] 1.139400240 1.748005666 -0.298918678 -0.682935312 0.707682478
[11] 0.636792825 -1.169740323 -0.881330320 -0.154920406 -0.075581804
[16] -1.605471700 1.480898130 -1.210604267 0.449220000 0.696027570
[21] -0.694824586 -0.513590008 -0.170011797 2.807801987 -0.831235819
[26] 0.718420475 -1.032201065 0.340100030 0.287824626 -1.123872091
[31] -0.834021804 0.231094953 1.533131962 0.620095164 0.482682516
[36] 1.306266306 1.419670684 -0.859495287 0.513178766 -0.313460805
[41] 0.473443279 0.311442594 -0.949503327 0.421015936 0.913440647
[46] -0.469407936 -0.461046034 0.312890026 -0.658316623 0.008941458
[51] -0.806778602 -0.318705867 0.671732535 1.312480845 -1.387111149
[56] 0.990427057 0.923540008 -0.147057185 0.911851962 0.196367766
[61] 0.558894552 0.028925825 -0.073426149 1.100871092 0.968678955
[66] 0.593355754 -0.020767563 1.080245973 1.165984060 -0.675650817
[71] -1.857680224 0.134581902 -2.048055574 0.929615791 0.141771827
[76] -1.112535305 0.707581684 0.641189189 -0.797502322 -1.139520014
[81] -1.508948525 1.030736749 0.901351771 -0.081110494 0.954460151
[86] 0.238744584 -0.847182904 -0.283584323 -0.367298997 -0.015540629
[91] -2.527668709 -1.810129486 -1.067554766 -1.101391198 0.933573373
[96] 0.861409867 -2.556583624 -1.471268313 0.410384194 -0.320658585
> colMedians(tmp)
[1] 0.034209836 -0.026947381 -1.674826783 0.782501137 -1.012765763
[6] 1.139400240 1.748005666 -0.298918678 -0.682935312 0.707682478
[11] 0.636792825 -1.169740323 -0.881330320 -0.154920406 -0.075581804
[16] -1.605471700 1.480898130 -1.210604267 0.449220000 0.696027570
[21] -0.694824586 -0.513590008 -0.170011797 2.807801987 -0.831235819
[26] 0.718420475 -1.032201065 0.340100030 0.287824626 -1.123872091
[31] -0.834021804 0.231094953 1.533131962 0.620095164 0.482682516
[36] 1.306266306 1.419670684 -0.859495287 0.513178766 -0.313460805
[41] 0.473443279 0.311442594 -0.949503327 0.421015936 0.913440647
[46] -0.469407936 -0.461046034 0.312890026 -0.658316623 0.008941458
[51] -0.806778602 -0.318705867 0.671732535 1.312480845 -1.387111149
[56] 0.990427057 0.923540008 -0.147057185 0.911851962 0.196367766
[61] 0.558894552 0.028925825 -0.073426149 1.100871092 0.968678955
[66] 0.593355754 -0.020767563 1.080245973 1.165984060 -0.675650817
[71] -1.857680224 0.134581902 -2.048055574 0.929615791 0.141771827
[76] -1.112535305 0.707581684 0.641189189 -0.797502322 -1.139520014
[81] -1.508948525 1.030736749 0.901351771 -0.081110494 0.954460151
[86] 0.238744584 -0.847182904 -0.283584323 -0.367298997 -0.015540629
[91] -2.527668709 -1.810129486 -1.067554766 -1.101391198 0.933573373
[96] 0.861409867 -2.556583624 -1.471268313 0.410384194 -0.320658585
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.03420984 -0.02694738 -1.674827 0.7825011 -1.012766 1.1394 1.748006
[2,] 0.03420984 -0.02694738 -1.674827 0.7825011 -1.012766 1.1394 1.748006
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.2989187 -0.6829353 0.7076825 0.6367928 -1.16974 -0.8813303 -0.1549204
[2,] -0.2989187 -0.6829353 0.7076825 0.6367928 -1.16974 -0.8813303 -0.1549204
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.0755818 -1.605472 1.480898 -1.210604 0.44922 0.6960276 -0.6948246
[2,] -0.0755818 -1.605472 1.480898 -1.210604 0.44922 0.6960276 -0.6948246
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.51359 -0.1700118 2.807802 -0.8312358 0.7184205 -1.032201 0.3401
[2,] -0.51359 -0.1700118 2.807802 -0.8312358 0.7184205 -1.032201 0.3401
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.2878246 -1.123872 -0.8340218 0.231095 1.533132 0.6200952 0.4826825
[2,] 0.2878246 -1.123872 -0.8340218 0.231095 1.533132 0.6200952 0.4826825
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.306266 1.419671 -0.8594953 0.5131788 -0.3134608 0.4734433 0.3114426
[2,] 1.306266 1.419671 -0.8594953 0.5131788 -0.3134608 0.4734433 0.3114426
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.9495033 0.4210159 0.9134406 -0.4694079 -0.461046 0.31289 -0.6583166
[2,] -0.9495033 0.4210159 0.9134406 -0.4694079 -0.461046 0.31289 -0.6583166
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.008941458 -0.8067786 -0.3187059 0.6717325 1.312481 -1.387111 0.9904271
[2,] 0.008941458 -0.8067786 -0.3187059 0.6717325 1.312481 -1.387111 0.9904271
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.92354 -0.1470572 0.911852 0.1963678 0.5588946 0.02892582 -0.07342615
[2,] 0.92354 -0.1470572 0.911852 0.1963678 0.5588946 0.02892582 -0.07342615
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 1.100871 0.968679 0.5933558 -0.02076756 1.080246 1.165984 -0.6756508
[2,] 1.100871 0.968679 0.5933558 -0.02076756 1.080246 1.165984 -0.6756508
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -1.85768 0.1345819 -2.048056 0.9296158 0.1417718 -1.112535 0.7075817
[2,] -1.85768 0.1345819 -2.048056 0.9296158 0.1417718 -1.112535 0.7075817
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.6411892 -0.7975023 -1.13952 -1.508949 1.030737 0.9013518 -0.08111049
[2,] 0.6411892 -0.7975023 -1.13952 -1.508949 1.030737 0.9013518 -0.08111049
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 0.9544602 0.2387446 -0.8471829 -0.2835843 -0.367299 -0.01554063 -2.527669
[2,] 0.9544602 0.2387446 -0.8471829 -0.2835843 -0.367299 -0.01554063 -2.527669
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.810129 -1.067555 -1.101391 0.9335734 0.8614099 -2.556584 -1.471268
[2,] -1.810129 -1.067555 -1.101391 0.9335734 0.8614099 -2.556584 -1.471268
[,99] [,100]
[1,] 0.4103842 -0.3206586
[2,] 0.4103842 -0.3206586
>
>
> Max(tmp2)
[1] 2.568589
> Min(tmp2)
[1] -2.26245
> mean(tmp2)
[1] 0.1220458
> Sum(tmp2)
[1] 12.20458
> Var(tmp2)
[1] 0.9989833
>
> rowMeans(tmp2)
[1] 1.02012002 0.84144956 1.01875811 -0.96226523 0.95003026 -0.45235479
[7] 0.38408829 -1.71827939 0.93809951 -0.47182604 1.10666068 -0.71951497
[13] -0.75517918 0.05661202 -1.27241363 1.29555556 -0.48425626 -0.85521660
[19] 0.50307469 1.51522640 1.47303951 0.16591786 0.79418843 0.47933441
[25] -0.16084447 -0.89040399 1.04588966 1.66973197 0.02538948 -0.20269458
[31] -0.91317487 0.29057520 -0.52575065 0.40136031 -1.42120783 0.17838799
[37] 2.19567919 0.44481482 0.69160407 -0.49732849 -0.47303519 -2.26244978
[43] 0.59160642 0.30378573 0.53530272 0.83136170 0.82121237 -0.68642145
[49] -0.85596954 0.24416014 1.24868958 -0.09054983 0.44141444 -2.16337431
[55] 0.11998201 -1.38418686 1.00010190 0.25487448 0.16597793 -0.94851279
[61] 2.56858871 -0.77021859 0.60274784 -1.57079829 -0.02173159 0.03979238
[67] -0.26871203 -0.69984154 2.22833131 0.20480811 -1.06401925 1.77952655
[73] -0.87315536 -0.72904149 -1.30929201 0.48929220 1.19427258 -0.69313249
[79] 0.34138882 0.29485347 -1.87249604 1.07056587 0.50831196 -0.53982388
[85] -0.11432551 0.51365478 1.12365933 0.26635061 -0.08233200 0.97752737
[91] 0.43075079 1.11262237 -0.90466743 1.99179037 -0.36428687 0.09254600
[97] -1.70887306 0.41053757 1.64078403 1.03178089
> rowSums(tmp2)
[1] 1.02012002 0.84144956 1.01875811 -0.96226523 0.95003026 -0.45235479
[7] 0.38408829 -1.71827939 0.93809951 -0.47182604 1.10666068 -0.71951497
[13] -0.75517918 0.05661202 -1.27241363 1.29555556 -0.48425626 -0.85521660
[19] 0.50307469 1.51522640 1.47303951 0.16591786 0.79418843 0.47933441
[25] -0.16084447 -0.89040399 1.04588966 1.66973197 0.02538948 -0.20269458
[31] -0.91317487 0.29057520 -0.52575065 0.40136031 -1.42120783 0.17838799
[37] 2.19567919 0.44481482 0.69160407 -0.49732849 -0.47303519 -2.26244978
[43] 0.59160642 0.30378573 0.53530272 0.83136170 0.82121237 -0.68642145
[49] -0.85596954 0.24416014 1.24868958 -0.09054983 0.44141444 -2.16337431
[55] 0.11998201 -1.38418686 1.00010190 0.25487448 0.16597793 -0.94851279
[61] 2.56858871 -0.77021859 0.60274784 -1.57079829 -0.02173159 0.03979238
[67] -0.26871203 -0.69984154 2.22833131 0.20480811 -1.06401925 1.77952655
[73] -0.87315536 -0.72904149 -1.30929201 0.48929220 1.19427258 -0.69313249
[79] 0.34138882 0.29485347 -1.87249604 1.07056587 0.50831196 -0.53982388
[85] -0.11432551 0.51365478 1.12365933 0.26635061 -0.08233200 0.97752737
[91] 0.43075079 1.11262237 -0.90466743 1.99179037 -0.36428687 0.09254600
[97] -1.70887306 0.41053757 1.64078403 1.03178089
> 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] 1.02012002 0.84144956 1.01875811 -0.96226523 0.95003026 -0.45235479
[7] 0.38408829 -1.71827939 0.93809951 -0.47182604 1.10666068 -0.71951497
[13] -0.75517918 0.05661202 -1.27241363 1.29555556 -0.48425626 -0.85521660
[19] 0.50307469 1.51522640 1.47303951 0.16591786 0.79418843 0.47933441
[25] -0.16084447 -0.89040399 1.04588966 1.66973197 0.02538948 -0.20269458
[31] -0.91317487 0.29057520 -0.52575065 0.40136031 -1.42120783 0.17838799
[37] 2.19567919 0.44481482 0.69160407 -0.49732849 -0.47303519 -2.26244978
[43] 0.59160642 0.30378573 0.53530272 0.83136170 0.82121237 -0.68642145
[49] -0.85596954 0.24416014 1.24868958 -0.09054983 0.44141444 -2.16337431
[55] 0.11998201 -1.38418686 1.00010190 0.25487448 0.16597793 -0.94851279
[61] 2.56858871 -0.77021859 0.60274784 -1.57079829 -0.02173159 0.03979238
[67] -0.26871203 -0.69984154 2.22833131 0.20480811 -1.06401925 1.77952655
[73] -0.87315536 -0.72904149 -1.30929201 0.48929220 1.19427258 -0.69313249
[79] 0.34138882 0.29485347 -1.87249604 1.07056587 0.50831196 -0.53982388
[85] -0.11432551 0.51365478 1.12365933 0.26635061 -0.08233200 0.97752737
[91] 0.43075079 1.11262237 -0.90466743 1.99179037 -0.36428687 0.09254600
[97] -1.70887306 0.41053757 1.64078403 1.03178089
> rowMin(tmp2)
[1] 1.02012002 0.84144956 1.01875811 -0.96226523 0.95003026 -0.45235479
[7] 0.38408829 -1.71827939 0.93809951 -0.47182604 1.10666068 -0.71951497
[13] -0.75517918 0.05661202 -1.27241363 1.29555556 -0.48425626 -0.85521660
[19] 0.50307469 1.51522640 1.47303951 0.16591786 0.79418843 0.47933441
[25] -0.16084447 -0.89040399 1.04588966 1.66973197 0.02538948 -0.20269458
[31] -0.91317487 0.29057520 -0.52575065 0.40136031 -1.42120783 0.17838799
[37] 2.19567919 0.44481482 0.69160407 -0.49732849 -0.47303519 -2.26244978
[43] 0.59160642 0.30378573 0.53530272 0.83136170 0.82121237 -0.68642145
[49] -0.85596954 0.24416014 1.24868958 -0.09054983 0.44141444 -2.16337431
[55] 0.11998201 -1.38418686 1.00010190 0.25487448 0.16597793 -0.94851279
[61] 2.56858871 -0.77021859 0.60274784 -1.57079829 -0.02173159 0.03979238
[67] -0.26871203 -0.69984154 2.22833131 0.20480811 -1.06401925 1.77952655
[73] -0.87315536 -0.72904149 -1.30929201 0.48929220 1.19427258 -0.69313249
[79] 0.34138882 0.29485347 -1.87249604 1.07056587 0.50831196 -0.53982388
[85] -0.11432551 0.51365478 1.12365933 0.26635061 -0.08233200 0.97752737
[91] 0.43075079 1.11262237 -0.90466743 1.99179037 -0.36428687 0.09254600
[97] -1.70887306 0.41053757 1.64078403 1.03178089
>
> colMeans(tmp2)
[1] 0.1220458
> colSums(tmp2)
[1] 12.20458
> colVars(tmp2)
[1] 0.9989833
> colSd(tmp2)
[1] 0.9994915
> colMax(tmp2)
[1] 2.568589
> colMin(tmp2)
[1] -2.26245
> colMedians(tmp2)
[1] 0.2244841
> colRanges(tmp2)
[,1]
[1,] -2.262450
[2,] 2.568589
>
> 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] -0.2462453 0.5949949 -1.1918942 -1.9411495 1.8291540 -2.7238645
[7] -1.8129289 -0.7271838 0.6729978 -2.4485504
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.1337190
[2,] -0.3882468
[3,] -0.0261979
[4,] 0.2144925
[5,] 1.0083019
>
> rowApply(tmp,sum)
[1] -2.2131674 1.3407178 -5.9734802 -4.1548023 3.2244263 1.2965857
[7] -0.2808193 1.6845106 -2.5989107 -0.3197307
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 4 2 5 8 6 7 7 4 5
[2,] 3 5 8 9 10 8 8 2 9 1
[3,] 6 7 10 4 1 7 3 4 6 7
[4,] 9 1 3 2 9 1 4 5 7 10
[5,] 10 9 6 6 3 9 1 9 3 4
[6,] 5 2 4 10 2 3 5 6 1 6
[7,] 1 6 7 1 4 10 9 8 8 9
[8,] 7 10 5 8 6 2 6 3 2 3
[9,] 4 8 9 7 5 4 2 1 10 8
[10,] 2 3 1 3 7 5 10 10 5 2
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.59691544 1.20094075 -0.02084515 0.45713092 -0.08668239 -1.39809924
[7] -1.39289177 -3.48709475 -2.35675317 2.69936996 1.42190272 -0.18923138
[13] -0.47471727 -3.25878782 1.25043752 0.05277150 0.15971551 -0.65387265
[19] -3.06703586 -1.24402525
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.9287145
[2,] -0.7211822
[3,] -0.5810911
[4,] 0.1177199
[5,] 2.7101834
>
> rowApply(tmp,sum)
[1] 8.117802 -8.185604 -3.780300 2.808491 -8.751242
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 5 10 11 20 7
[2,] 13 8 15 10 16
[3,] 14 15 5 13 12
[4,] 19 5 8 17 5
[5,] 18 4 19 12 3
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.7211822 1.00392711 1.2017403 2.0669337 1.8309530 1.4436206
[2,] -0.5810911 -0.76253215 -0.2237347 -1.3000842 -1.3929124 -0.5493365
[3,] 0.1177199 0.56150040 -1.2105817 -0.8505471 1.1845616 -0.8831117
[4,] 2.7101834 -0.01897544 0.4347460 1.4987699 0.1047781 0.9052099
[5,] -0.9287145 0.41702083 -0.2230150 -0.9579415 -1.8140627 -2.3144816
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.2369640 -1.0621389 0.5775443 2.1277657 1.7092952 -0.3140310
[2,] -1.0591107 0.9031899 -0.6657684 -0.3667164 -1.4292615 -0.5519116
[3,] -1.7529981 -1.2222925 1.7175240 0.3396161 0.9258709 -0.1937836
[4,] -0.2946911 -1.6286179 -1.3163606 0.7065721 1.5758186 1.2765605
[5,] 1.4769440 -0.4772354 -2.6696924 -0.1078676 -1.3598204 -0.4060656
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.9180312 -1.2822872875 0.38158049 -0.21985547 0.1858144 -0.01915371
[2,] -2.4437757 -1.4744582887 0.67233912 -0.51553655 2.2355905 2.05856000
[3,] 0.7902458 0.4651408862 0.74916976 0.19962600 -1.6254965 -2.00295459
[4,] 2.2428737 -0.9677470469 -0.63266116 0.05214654 -0.3857344 -1.41859246
[5,] 0.8539702 0.0005639197 0.08000931 0.53639099 -0.2504585 0.72826811
[,19] [,20]
[1,] -0.77970829 1.6680512
[2,] -0.86789046 0.1288373
[3,] -0.02410935 -1.0653998
[4,] -0.44453747 -1.5912498
[5,] -0.95079028 -0.3842641
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2.1 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 709 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 612 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2.1 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -0.716722 -1.30316 1.053594 0.7572719 1.026279 0.1323876 -0.4567174
col8 col9 col10 col11 col12 col13 col14
row1 -1.296453 -0.01351783 0.3566349 1.539827 -0.7434787 0.1656571 -1.096747
col15 col16 col17 col18 col19 col20
row1 0.121345 -0.3948321 -0.6913879 0.5604511 -0.235933 -1.164078
> tmp[,"col10"]
col10
row1 0.3566349
row2 -0.9667087
row3 0.2051693
row4 0.9498496
row5 -0.6135425
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.7167220 -1.3031597 1.0535944 0.7572719 1.0262787 0.13238763
row5 0.8257113 -0.4693191 0.5358238 -0.4834039 -0.5853529 0.03275386
col7 col8 col9 col10 col11 col12
row1 -0.4567174 -1.2964530 -0.013517829 0.3566349 1.5398266 -0.7434787
row5 0.8117078 0.3308204 0.007417853 -0.6135425 0.8964061 -0.2735904
col13 col14 col15 col16 col17 col18
row1 0.16565711 -1.0967472 0.12134502 -0.3948321 -0.6913879 0.5604511
row5 -0.03918778 -0.1268874 -0.03337106 1.1398485 0.3496817 -1.0422250
col19 col20
row1 -0.235933 -1.1640784
row5 1.944262 -0.2011537
> tmp[,c("col6","col20")]
col6 col20
row1 0.13238763 -1.1640784
row2 0.55155271 0.9251589
row3 -0.79592981 0.1273273
row4 -0.27425068 1.1078685
row5 0.03275386 -0.2011537
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.13238763 -1.1640784
row5 0.03275386 -0.2011537
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.60568 50.26419 51.9871 50.07697 49.452 105.4716 49.63118 49.05612
col9 col10 col11 col12 col13 col14 col15 col16
row1 47.83349 52.00757 51.56958 51.27363 51.91831 50.92316 48.62715 50.86394
col17 col18 col19 col20
row1 52.48893 50.19237 49.7922 104.6903
> tmp[,"col10"]
col10
row1 52.00757
row2 30.34634
row3 30.75747
row4 30.85350
row5 50.00208
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.60568 50.26419 51.9871 50.07697 49.4520 105.4716 49.63118 49.05612
row5 49.04947 50.86922 50.2369 50.77116 49.8403 105.9147 50.62110 50.19903
col9 col10 col11 col12 col13 col14 col15 col16
row1 47.83349 52.00757 51.56958 51.27363 51.91831 50.92316 48.62715 50.86394
row5 48.01878 50.00208 49.40959 50.41646 50.13943 50.11559 49.48037 50.01155
col17 col18 col19 col20
row1 52.48893 50.19237 49.79220 104.6903
row5 50.22002 49.64247 49.98254 104.0451
> tmp[,c("col6","col20")]
col6 col20
row1 105.47157 104.69029
row2 74.57831 75.89767
row3 74.07161 73.11407
row4 75.16953 74.16278
row5 105.91467 104.04505
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.4716 104.6903
row5 105.9147 104.0451
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.4716 104.6903
row5 105.9147 104.0451
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.39380790
[2,] 0.56159748
[3,] -1.21199631
[4,] 0.01496781
[5,] 0.15432447
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.37058963 0.2372698
[2,] -0.17961795 -1.5194309
[3,] -0.03931635 -0.4042894
[4,] 0.74737255 -0.7231795
[5,] -0.44281520 1.7928479
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.32645066 1.46598452
[2,] 2.57118083 0.71247642
[3,] -0.96958843 -0.58785210
[4,] 0.06401927 -0.02135518
[5,] -0.09843649 1.19014846
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.326451
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.326451
[2,] 2.571181
>
>
>
> 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 1.491329762 -0.2382582 0.7305842 -0.6956596 -0.2641467 -0.5342373
row1 0.004118821 -0.2258438 0.4429730 -0.9392904 -0.6659541 0.4189731
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.46036882 -0.2143406 0.9597042 2.107312 -0.5000897 -0.4277051
row1 0.07361399 -0.2048213 -0.1432138 0.281099 0.8843305 0.6190764
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.8375463 0.234313 1.0047737 1.6690724 -1.631106 -0.9357441 0.007558982
row1 0.1217077 -1.204613 0.7773982 0.3674076 -1.059131 0.4550830 -2.196040765
[,20]
row3 0.2133991
row1 -0.9142445
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.9633099 -0.04957365 -1.294236 1.063991 -0.6825468 0.3570931 -0.8068611
[,8] [,9] [,10]
row2 -0.3875245 0.1535623 -0.1961543
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.9246352 0.9979964 -0.345417 -0.8815326 -0.2893989 -2.051409 -0.6427358
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.138719 -0.08250406 2.145373 -0.4345786 0.4298385 1.559776 -1.158758
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.1211452 0.1642037 -2.023803 -0.1541524 -0.98531 1.656117
>
>
> 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: 0x600000922160>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM92ad44bc44a7"
[2] "/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM92ad243f5332"
[3] "/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM92ad396f0a35"
[4] "/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM92ad29073b08"
[5] "/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM92ad19b49f43"
[6] "/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM92ad2143f4e4"
[7] "/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM92ad7482b5cb"
[8] "/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM92ad316d5e2f"
[9] "/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM92ad3427903"
[10] "/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM92ad116b5a1"
[11] "/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM92ad79ee5d95"
[12] "/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM92ad10421fbd"
[13] "/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM92ad6531b9a1"
[14] "/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM92ad23922cee"
[15] "/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM92ad51c3cf80"
>
>
> ### 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: 0x60000090d200>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x60000090d200>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.20-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x60000090d200>
> rowMedians(tmp)
[1] 0.007766754 -0.077252692 0.289680838 -0.188351679 -0.006536585
[6] -0.470218610 0.194638088 0.150334765 -0.314104879 0.061579239
[11] -0.429984084 -0.121635721 -0.124568966 0.149306074 -0.170051400
[16] 0.545841472 0.301417679 -0.324986437 0.179619490 -0.294857141
[21] 0.185411367 -0.481219912 0.407920663 0.031500515 0.461496927
[26] 0.350717633 -0.039638962 0.343246503 0.052156071 0.091875278
[31] -0.007379989 -0.155919624 -0.159304855 0.491703142 0.062971024
[36] 0.240308562 0.195431022 -0.332770970 -0.246062482 -0.014400844
[41] -0.534367661 -0.851846683 0.142090307 0.413343176 0.420712482
[46] 0.047880044 0.254699746 0.254036410 -0.195668724 0.168723843
[51] 0.515598177 -0.397527990 -0.091960850 -0.088589675 -0.207458239
[56] -0.259755728 -0.257012158 -0.273802331 -0.032338997 -0.019070655
[61] -0.556022297 0.538926232 0.009111053 -0.519059368 -0.471340211
[66] 0.107562569 0.076614069 -0.419932516 0.026597066 0.636820695
[71] -0.241467552 -0.361378736 0.042963241 -0.403881683 -0.121766950
[76] 0.201593697 0.232243510 -0.031643294 0.124018289 -0.530023157
[81] -0.080597448 0.092765574 -0.128040956 -0.209078634 0.127903236
[86] 0.158807819 -0.330682176 -0.302033502 -0.087189926 -0.352834824
[91] 0.202212604 -0.302445965 0.441212707 0.097103034 -0.285002390
[96] 0.166148747 -0.279340373 -0.455037310 -0.351003027 0.160530406
[101] -0.315948323 -0.042385220 -0.077784562 -0.262171450 -0.227710565
[106] -0.247450501 0.766982794 -0.215115734 -0.037361338 0.668256514
[111] 0.068506816 0.191922943 0.283560247 -0.130383863 -0.317837668
[116] -0.033284899 -0.088741994 0.334264762 -0.049245761 0.057614351
[121] -0.241408044 0.207386265 0.329451804 0.220588534 0.195892328
[126] -0.017776179 0.033017931 -0.531262468 -0.318983889 0.114542810
[131] -0.462627028 -0.392448468 -0.388229015 0.223043231 0.448455587
[136] -0.434823105 -0.107661157 0.191281327 0.052437100 -0.359644656
[141] -0.049640870 -0.212434071 -0.171989045 0.219842657 -0.112105854
[146] 0.296284772 -0.013371699 0.452016386 0.104649558 0.761450323
[151] 0.331360163 -0.374342630 -0.021458520 -0.256500015 -0.333346145
[156] -0.127356508 0.321854071 0.028821969 -0.146977613 0.437161022
[161] -0.461911550 -0.111172230 -0.099179832 -0.228708456 -0.333507552
[166] 0.194081681 -0.239566926 -0.381747870 0.100693217 -0.090099767
[171] 0.004142586 -0.023783307 0.321233210 -0.168984289 0.179094707
[176] 0.125074662 0.130776677 0.292939310 0.323783168 0.305610356
[181] -0.144172472 -0.180615962 0.045135503 -0.207165237 -0.144389335
[186] -0.166609268 0.218893660 0.187696375 -0.216922188 -0.231433079
[191] 0.249067495 0.485086659 0.381630903 -0.087556708 0.108867196
[196] 0.244805588 0.037039839 0.174177020 -0.272466592 0.312761474
[201] -0.067446156 0.164339663 -0.370882564 -0.142391347 0.218959023
[206] -0.228846188 -0.203038324 0.186361536 -0.110270005 0.230376073
[211] 0.102486120 0.038877707 0.061278107 0.032827375 0.304996999
[216] -0.183333696 0.131151892 0.065881671 0.227446391 -0.094794984
[221] 0.677206189 0.364677150 0.027859587 0.218663633 0.311900527
[226] 0.527079760 0.079319128 -0.072404391 0.121069953 0.171051111
>
> proc.time()
user system elapsed
1.954 8.173 10.455
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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: 0x600001330000>
> .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: 0x600001330000>
> .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: 0x600001330000>
> .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: 0x600001330000>
> 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: 0x600001324900>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001324900>
> .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: 0x600001324900>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001324900>
> .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: 0x600001324900>
> 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: 0x600001324ae0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001324ae0>
> .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: 0x600001324ae0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600001324ae0>
> .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: 0x600001324ae0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600001324ae0>
> .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: 0x600001324ae0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600001324ae0>
> .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: 0x600001324ae0>
> 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: 0x600001324cc0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600001324cc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001324cc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001324cc0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile92f73aa03176" "BufferedMatrixFile92f76b0f580b"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile92f73aa03176" "BufferedMatrixFile92f76b0f580b"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001324de0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001324de0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600001324de0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600001324de0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600001324de0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600001324de0>
> .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: 0x600001324fc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600001324fc0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600001324fc0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600001324fc0>
> 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: 0x6000013251a0>
> .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: 0x6000013251a0>
> rm(P)
>
> proc.time()
user system elapsed
0.345 0.109 0.443
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.0 Patched (2024-04-24 r86482) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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
0.340 0.070 0.395