| Back to Mac ARM64 build report for BioC 3.17 |
|
This page was generated on 2023-10-20 09:37:59 -0400 (Fri, 20 Oct 2023).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| kjohnson2 | macOS 12.6.1 Monterey | arm64 | 4.3.1 (2023-06-16) -- "Beagle Scouts" | 4347 |
| 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 245/2230 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.64.0 (landing page) Ben Bolstad
| kjohnson2 | macOS 12.6.1 Monterey / 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: 1.64.0 |
| 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_1.64.0.tar.gz |
| StartedAt: 2023-10-17 06:56:04 -0400 (Tue, 17 Oct 2023) |
| EndedAt: 2023-10-17 06:57:20 -0400 (Tue, 17 Oct 2023) |
| EllapsedTime: 75.2 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_1.64.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck’
* using R version 4.3.1 (2023-06-16)
* using platform: aarch64-apple-darwin20 (64-bit)
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.6.7
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.64.0’
* 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-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
* 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 R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking 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 in ‘inst/doc’ ... 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-3.17-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
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
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 -single_module -multiply_defined suppress -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/4.3-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 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20 (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
0.352 0.114 0.750
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20 (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] "/Users/biocbuild/bbs-3.17-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 459904 24.6 991195 53 NA 645631 34.5
Vcells 848492 6.5 8388608 64 16384 2024378 15.5
>
>
>
>
> ##
> ## 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 Oct 17 06:56:43 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 Oct 17 06:56:44 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: 0x6000029ac420>
>
>
>
> 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 Oct 17 06:56:48 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 Oct 17 06:56:50 2023"
>
> ColMode(tmp2)
<pointer: 0x6000029ac420>
>
>
>
> ### 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,] 99.4170117 -0.08029004 -0.4264962 -1.4637480
[2,] 0.4178291 2.07927878 1.4225125 -3.8411860
[3,] 2.9067727 0.31570541 -0.4937036 -1.1282164
[4,] 0.4451296 -1.06039735 -0.7369338 0.8012403
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.17-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,] 99.4170117 0.08029004 0.4264962 1.4637480
[2,] 0.4178291 2.07927878 1.4225125 3.8411860
[3,] 2.9067727 0.31570541 0.4937036 1.1282164
[4,] 0.4451296 1.06039735 0.7369338 0.8012403
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.17-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,] 9.9708080 0.2833550 0.6530668 1.2098545
[2,] 0.6463970 1.4419705 1.1926913 1.9598944
[3,] 1.7049260 0.5618767 0.7026405 1.0621753
[4,] 0.6671804 1.0297560 0.8584485 0.8951203
>
> 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-3.17-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,] 224.12509 27.91384 31.95716 38.56229
[2,] 31.88180 41.49898 38.34943 48.44013
[3,] 44.95603 30.93447 32.52011 36.74997
[4,] 32.11693 36.35796 34.32142 34.75244
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000029a0fc0>
> exp(tmp5)
<pointer: 0x6000029a0fc0>
> log(tmp5,2)
<pointer: 0x6000029a0fc0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.487
> Min(tmp5)
[1] 54.64119
> mean(tmp5)
[1] 74.07806
> Sum(tmp5)
[1] 14815.61
> Var(tmp5)
[1] 863.864
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.98925 75.21129 71.95781 75.87991 71.60095 72.08657 73.18521 70.98547
[9] 67.70831 71.17586
> rowSums(tmp5)
[1] 1819.785 1504.226 1439.156 1517.598 1432.019 1441.731 1463.704 1419.709
[9] 1354.166 1423.517
> rowVars(tmp5)
[1] 7899.88989 123.52070 98.45051 87.08219 79.65358 42.63846
[7] 44.77525 91.76350 50.99613 145.41171
> rowSd(tmp5)
[1] 88.881325 11.113986 9.922223 9.331784 8.924886 6.529813 6.691431
[8] 9.579327 7.141157 12.058678
> rowMax(tmp5)
[1] 466.48701 100.82178 93.57009 94.86354 90.04269 86.00109 87.95009
[8] 89.00202 83.96464 93.31726
> rowMin(tmp5)
[1] 58.09900 56.19802 54.64119 58.73275 55.61955 57.13170 62.55514 55.49728
[9] 58.71694 56.64705
>
> colMeans(tmp5)
[1] 113.89843 72.11378 72.08295 71.65642 70.89151 70.05488 80.50577
[8] 71.58481 73.09323 68.79528 78.69644 70.28264 70.56683 72.45361
[15] 66.02590 71.52011 75.87241 73.53414 68.61044 69.32166
> colSums(tmp5)
[1] 1138.9843 721.1378 720.8295 716.5642 708.9151 700.5488 805.0577
[8] 715.8481 730.9323 687.9528 786.9644 702.8264 705.6683 724.5361
[15] 660.2590 715.2011 758.7241 735.3414 686.1044 693.2166
> colVars(tmp5)
[1] 15483.69835 81.19411 86.87997 161.98673 56.15336 75.05016
[7] 74.15944 32.56627 161.08392 168.77610 78.26153 66.01703
[13] 83.23561 60.17199 20.29787 69.15878 66.91422 72.02660
[19] 43.37221 70.84426
> colSd(tmp5)
[1] 124.433510 9.010778 9.320943 12.727401 7.493555 8.663149
[7] 8.611587 5.706686 12.691884 12.991386 8.846554 8.125086
[13] 9.123355 7.757061 4.505316 8.316176 8.180111 8.486849
[19] 6.585758 8.416903
> colMax(tmp5)
[1] 466.48701 86.37470 90.93114 100.82178 78.78348 81.96821 93.31726
[8] 79.71995 94.86354 97.58901 90.04269 84.87149 84.73798 84.00203
[15] 75.77950 84.29381 89.94874 91.14270 77.85886 84.54097
> colMin(tmp5)
[1] 58.52622 58.09900 58.36353 58.71694 56.64705 56.19802 67.01062 62.38125
[9] 55.49728 56.51925 68.35495 55.61955 55.84078 58.28617 60.85047 57.24391
[17] 63.10380 63.26743 54.64119 58.52776
>
>
> ### 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] 90.98925 75.21129 71.95781 NA 71.60095 72.08657 73.18521 70.98547
[9] 67.70831 71.17586
> rowSums(tmp5)
[1] 1819.785 1504.226 1439.156 NA 1432.019 1441.731 1463.704 1419.709
[9] 1354.166 1423.517
> rowVars(tmp5)
[1] 7899.88989 123.52070 98.45051 80.23100 79.65358 42.63846
[7] 44.77525 91.76350 50.99613 145.41171
> rowSd(tmp5)
[1] 88.881325 11.113986 9.922223 8.957176 8.924886 6.529813 6.691431
[8] 9.579327 7.141157 12.058678
> rowMax(tmp5)
[1] 466.48701 100.82178 93.57009 NA 90.04269 86.00109 87.95009
[8] 89.00202 83.96464 93.31726
> rowMin(tmp5)
[1] 58.09900 56.19802 54.64119 NA 55.61955 57.13170 62.55514 55.49728
[9] 58.71694 56.64705
>
> colMeans(tmp5)
[1] 113.89843 72.11378 72.08295 71.65642 70.89151 70.05488 NA
[8] 71.58481 73.09323 68.79528 78.69644 70.28264 70.56683 72.45361
[15] 66.02590 71.52011 75.87241 73.53414 68.61044 69.32166
> colSums(tmp5)
[1] 1138.9843 721.1378 720.8295 716.5642 708.9151 700.5488 NA
[8] 715.8481 730.9323 687.9528 786.9644 702.8264 705.6683 724.5361
[15] 660.2590 715.2011 758.7241 735.3414 686.1044 693.2166
> colVars(tmp5)
[1] 15483.69835 81.19411 86.87997 161.98673 56.15336 75.05016
[7] NA 32.56627 161.08392 168.77610 78.26153 66.01703
[13] 83.23561 60.17199 20.29787 69.15878 66.91422 72.02660
[19] 43.37221 70.84426
> colSd(tmp5)
[1] 124.433510 9.010778 9.320943 12.727401 7.493555 8.663149
[7] NA 5.706686 12.691884 12.991386 8.846554 8.125086
[13] 9.123355 7.757061 4.505316 8.316176 8.180111 8.486849
[19] 6.585758 8.416903
> colMax(tmp5)
[1] 466.48701 86.37470 90.93114 100.82178 78.78348 81.96821 NA
[8] 79.71995 94.86354 97.58901 90.04269 84.87149 84.73798 84.00203
[15] 75.77950 84.29381 89.94874 91.14270 77.85886 84.54097
> colMin(tmp5)
[1] 58.52622 58.09900 58.36353 58.71694 56.64705 56.19802 NA 62.38125
[9] 55.49728 56.51925 68.35495 55.61955 55.84078 58.28617 60.85047 57.24391
[17] 63.10380 63.26743 54.64119 58.52776
>
> Max(tmp5,na.rm=TRUE)
[1] 466.487
> Min(tmp5,na.rm=TRUE)
[1] 54.64119
> mean(tmp5,na.rm=TRUE)
[1] 73.99796
> Sum(tmp5,na.rm=TRUE)
[1] 14725.59
> Var(tmp5,na.rm=TRUE)
[1] 866.9373
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.98925 75.21129 71.95781 75.13580 71.60095 72.08657 73.18521 70.98547
[9] 67.70831 71.17586
> rowSums(tmp5,na.rm=TRUE)
[1] 1819.785 1504.226 1439.156 1427.580 1432.019 1441.731 1463.704 1419.709
[9] 1354.166 1423.517
> rowVars(tmp5,na.rm=TRUE)
[1] 7899.88989 123.52070 98.45051 80.23100 79.65358 42.63846
[7] 44.77525 91.76350 50.99613 145.41171
> rowSd(tmp5,na.rm=TRUE)
[1] 88.881325 11.113986 9.922223 8.957176 8.924886 6.529813 6.691431
[8] 9.579327 7.141157 12.058678
> rowMax(tmp5,na.rm=TRUE)
[1] 466.48701 100.82178 93.57009 94.86354 90.04269 86.00109 87.95009
[8] 89.00202 83.96464 93.31726
> rowMin(tmp5,na.rm=TRUE)
[1] 58.09900 56.19802 54.64119 58.73275 55.61955 57.13170 62.55514 55.49728
[9] 58.71694 56.64705
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.89843 72.11378 72.08295 71.65642 70.89151 70.05488 79.44886
[8] 71.58481 73.09323 68.79528 78.69644 70.28264 70.56683 72.45361
[15] 66.02590 71.52011 75.87241 73.53414 68.61044 69.32166
> colSums(tmp5,na.rm=TRUE)
[1] 1138.9843 721.1378 720.8295 716.5642 708.9151 700.5488 715.0398
[8] 715.8481 730.9323 687.9528 786.9644 702.8264 705.6683 724.5361
[15] 660.2590 715.2011 758.7241 735.3414 686.1044 693.2166
> colVars(tmp5,na.rm=TRUE)
[1] 15483.69835 81.19411 86.87997 161.98673 56.15336 75.05016
[7] 70.86256 32.56627 161.08392 168.77610 78.26153 66.01703
[13] 83.23561 60.17199 20.29787 69.15878 66.91422 72.02660
[19] 43.37221 70.84426
> colSd(tmp5,na.rm=TRUE)
[1] 124.433510 9.010778 9.320943 12.727401 7.493555 8.663149
[7] 8.417990 5.706686 12.691884 12.991386 8.846554 8.125086
[13] 9.123355 7.757061 4.505316 8.316176 8.180111 8.486849
[19] 6.585758 8.416903
> colMax(tmp5,na.rm=TRUE)
[1] 466.48701 86.37470 90.93114 100.82178 78.78348 81.96821 93.31726
[8] 79.71995 94.86354 97.58901 90.04269 84.87149 84.73798 84.00203
[15] 75.77950 84.29381 89.94874 91.14270 77.85886 84.54097
> colMin(tmp5,na.rm=TRUE)
[1] 58.52622 58.09900 58.36353 58.71694 56.64705 56.19802 67.01062 62.38125
[9] 55.49728 56.51925 68.35495 55.61955 55.84078 58.28617 60.85047 57.24391
[17] 63.10380 63.26743 54.64119 58.52776
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.98925 75.21129 71.95781 NaN 71.60095 72.08657 73.18521 70.98547
[9] 67.70831 71.17586
> rowSums(tmp5,na.rm=TRUE)
[1] 1819.785 1504.226 1439.156 0.000 1432.019 1441.731 1463.704 1419.709
[9] 1354.166 1423.517
> rowVars(tmp5,na.rm=TRUE)
[1] 7899.88989 123.52070 98.45051 NA 79.65358 42.63846
[7] 44.77525 91.76350 50.99613 145.41171
> rowSd(tmp5,na.rm=TRUE)
[1] 88.881325 11.113986 9.922223 NA 8.924886 6.529813 6.691431
[8] 9.579327 7.141157 12.058678
> rowMax(tmp5,na.rm=TRUE)
[1] 466.48701 100.82178 93.57009 NA 90.04269 86.00109 87.95009
[8] 89.00202 83.96464 93.31726
> rowMin(tmp5,na.rm=TRUE)
[1] 58.09900 56.19802 54.64119 NA 55.61955 57.13170 62.55514 55.49728
[9] 58.71694 56.64705
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 119.12635 71.71816 72.15488 71.58128 70.51910 70.59967 NaN
[8] 70.68091 70.67431 69.91334 79.06035 69.80166 68.99226 71.76218
[15] 66.60095 70.10082 74.89298 72.52902 68.49230 68.90777
> colSums(tmp5,na.rm=TRUE)
[1] 1072.1371 645.4635 649.3939 644.2315 634.6719 635.3970 0.0000
[8] 636.1282 636.0688 629.2201 711.5431 628.2149 620.9303 645.8596
[15] 599.4086 630.9073 674.0368 652.7612 616.4307 620.1700
> colVars(tmp5,na.rm=TRUE)
[1] 17111.68574 89.58262 97.68176 182.17156 61.61233 81.09254
[7] NA 27.44533 115.39357 175.80998 86.55440 71.66662
[13] 65.74819 62.31506 19.11495 55.14152 64.48670 69.66442
[19] 48.63671 77.77266
> colSd(tmp5,na.rm=TRUE)
[1] 130.811642 9.464809 9.883408 13.497094 7.849352 9.005139
[7] NA 5.238829 10.742140 13.259336 9.303462 8.465614
[13] 8.108525 7.893989 4.372065 7.425733 8.030361 8.346521
[19] 6.974002 8.818881
> colMax(tmp5,na.rm=TRUE)
[1] 466.48701 86.37470 90.93114 100.82178 78.78348 81.96821 -Inf
[8] 77.17414 87.81363 97.58901 90.04269 84.87149 77.94437 84.00203
[15] 75.77950 83.31769 89.94874 91.14270 77.85886 84.54097
> colMin(tmp5,na.rm=TRUE)
[1] 58.52622 58.09900 58.36353 58.71694 56.64705 56.19802 Inf 62.38125
[9] 55.49728 56.51925 68.35495 55.61955 55.84078 58.28617 62.19121 57.24391
[17] 63.10380 63.26743 54.64119 58.52776
>
>
>
>
> 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] 196.8395 138.0618 195.1697 158.4822 270.4117 205.5616 175.0262 105.5279
[9] 151.0430 160.5624
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 196.8395 138.0618 195.1697 158.4822 270.4117 205.5616 175.0262 105.5279
[9] 151.0430 160.5624
>
>
>
> 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 0.000000e+00 2.842171e-14 -2.842171e-14 1.136868e-13
[6] 0.000000e+00 8.526513e-14 1.421085e-13 0.000000e+00 5.684342e-14
[11] -1.136868e-13 -2.842171e-14 2.842171e-14 -8.526513e-14 -1.136868e-13
[16] 0.000000e+00 0.000000e+00 -5.684342e-14 -2.842171e-14 2.131628e-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)
+ }
8 17
8 14
8 19
3 3
3 20
4 18
8 1
5 1
9 10
10 20
9 20
8 9
7 11
2 10
1 1
5 16
8 7
6 5
8 11
5 13
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] 2.055903
> Min(tmp)
[1] -2.469559
> mean(tmp)
[1] -0.008690042
> Sum(tmp)
[1] -0.8690042
> Var(tmp)
[1] 0.8051534
>
> rowMeans(tmp)
[1] -0.008690042
> rowSums(tmp)
[1] -0.8690042
> rowVars(tmp)
[1] 0.8051534
> rowSd(tmp)
[1] 0.8973034
> rowMax(tmp)
[1] 2.055903
> rowMin(tmp)
[1] -2.469559
>
> colMeans(tmp)
[1] -0.890571940 1.707442121 -0.135929427 -0.860582342 0.049222299
[6] 1.006116159 0.105337259 -0.402462675 0.118274881 -0.482955310
[11] 1.244589860 -1.137442155 0.512483673 0.556952465 0.063256713
[16] 2.049081927 -0.515493077 -0.419903733 -0.507122201 0.079062852
[21] 0.509227832 -0.507949881 0.714441805 -0.651967478 -0.365207221
[26] -0.190061320 -1.171459199 0.379994523 -0.640680594 0.878201756
[31] -1.263854242 0.526671888 1.569915444 0.555341027 0.211244917
[36] 0.471973724 0.400748650 0.745838824 0.815176197 -0.633901661
[41] 1.755515228 -1.227810010 -1.990664926 -0.885319973 -0.567885317
[46] 0.630063765 -0.530953020 -0.503839564 0.282512632 -0.226770573
[51] 2.055903421 -0.158628605 -0.842316557 -0.001423204 -0.271457737
[56] -0.996674773 -0.501805420 -1.658855407 0.716785199 -0.231150106
[61] 0.993457834 0.246257223 0.976530628 0.635947815 0.428417225
[66] 0.391530745 -1.304949200 -0.430408562 0.208036207 0.871720480
[71] -0.520032146 0.755854234 0.042001917 0.863336003 0.273064314
[76] -0.080226982 -2.469558654 -0.047322515 -0.300936088 0.979420567
[81] -1.482674272 -1.205971364 0.697467002 1.238301997 -0.701416967
[86] -2.428232928 0.397206831 0.938948250 -0.454465635 -0.326552668
[91] 0.519411595 -0.829447458 -1.295070912 0.154858667 -0.942611100
[96] 1.322574760 0.790523535 -0.021755085 0.183541993 0.725941113
> colSums(tmp)
[1] -0.890571940 1.707442121 -0.135929427 -0.860582342 0.049222299
[6] 1.006116159 0.105337259 -0.402462675 0.118274881 -0.482955310
[11] 1.244589860 -1.137442155 0.512483673 0.556952465 0.063256713
[16] 2.049081927 -0.515493077 -0.419903733 -0.507122201 0.079062852
[21] 0.509227832 -0.507949881 0.714441805 -0.651967478 -0.365207221
[26] -0.190061320 -1.171459199 0.379994523 -0.640680594 0.878201756
[31] -1.263854242 0.526671888 1.569915444 0.555341027 0.211244917
[36] 0.471973724 0.400748650 0.745838824 0.815176197 -0.633901661
[41] 1.755515228 -1.227810010 -1.990664926 -0.885319973 -0.567885317
[46] 0.630063765 -0.530953020 -0.503839564 0.282512632 -0.226770573
[51] 2.055903421 -0.158628605 -0.842316557 -0.001423204 -0.271457737
[56] -0.996674773 -0.501805420 -1.658855407 0.716785199 -0.231150106
[61] 0.993457834 0.246257223 0.976530628 0.635947815 0.428417225
[66] 0.391530745 -1.304949200 -0.430408562 0.208036207 0.871720480
[71] -0.520032146 0.755854234 0.042001917 0.863336003 0.273064314
[76] -0.080226982 -2.469558654 -0.047322515 -0.300936088 0.979420567
[81] -1.482674272 -1.205971364 0.697467002 1.238301997 -0.701416967
[86] -2.428232928 0.397206831 0.938948250 -0.454465635 -0.326552668
[91] 0.519411595 -0.829447458 -1.295070912 0.154858667 -0.942611100
[96] 1.322574760 0.790523535 -0.021755085 0.183541993 0.725941113
> 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] -0.890571940 1.707442121 -0.135929427 -0.860582342 0.049222299
[6] 1.006116159 0.105337259 -0.402462675 0.118274881 -0.482955310
[11] 1.244589860 -1.137442155 0.512483673 0.556952465 0.063256713
[16] 2.049081927 -0.515493077 -0.419903733 -0.507122201 0.079062852
[21] 0.509227832 -0.507949881 0.714441805 -0.651967478 -0.365207221
[26] -0.190061320 -1.171459199 0.379994523 -0.640680594 0.878201756
[31] -1.263854242 0.526671888 1.569915444 0.555341027 0.211244917
[36] 0.471973724 0.400748650 0.745838824 0.815176197 -0.633901661
[41] 1.755515228 -1.227810010 -1.990664926 -0.885319973 -0.567885317
[46] 0.630063765 -0.530953020 -0.503839564 0.282512632 -0.226770573
[51] 2.055903421 -0.158628605 -0.842316557 -0.001423204 -0.271457737
[56] -0.996674773 -0.501805420 -1.658855407 0.716785199 -0.231150106
[61] 0.993457834 0.246257223 0.976530628 0.635947815 0.428417225
[66] 0.391530745 -1.304949200 -0.430408562 0.208036207 0.871720480
[71] -0.520032146 0.755854234 0.042001917 0.863336003 0.273064314
[76] -0.080226982 -2.469558654 -0.047322515 -0.300936088 0.979420567
[81] -1.482674272 -1.205971364 0.697467002 1.238301997 -0.701416967
[86] -2.428232928 0.397206831 0.938948250 -0.454465635 -0.326552668
[91] 0.519411595 -0.829447458 -1.295070912 0.154858667 -0.942611100
[96] 1.322574760 0.790523535 -0.021755085 0.183541993 0.725941113
> colMin(tmp)
[1] -0.890571940 1.707442121 -0.135929427 -0.860582342 0.049222299
[6] 1.006116159 0.105337259 -0.402462675 0.118274881 -0.482955310
[11] 1.244589860 -1.137442155 0.512483673 0.556952465 0.063256713
[16] 2.049081927 -0.515493077 -0.419903733 -0.507122201 0.079062852
[21] 0.509227832 -0.507949881 0.714441805 -0.651967478 -0.365207221
[26] -0.190061320 -1.171459199 0.379994523 -0.640680594 0.878201756
[31] -1.263854242 0.526671888 1.569915444 0.555341027 0.211244917
[36] 0.471973724 0.400748650 0.745838824 0.815176197 -0.633901661
[41] 1.755515228 -1.227810010 -1.990664926 -0.885319973 -0.567885317
[46] 0.630063765 -0.530953020 -0.503839564 0.282512632 -0.226770573
[51] 2.055903421 -0.158628605 -0.842316557 -0.001423204 -0.271457737
[56] -0.996674773 -0.501805420 -1.658855407 0.716785199 -0.231150106
[61] 0.993457834 0.246257223 0.976530628 0.635947815 0.428417225
[66] 0.391530745 -1.304949200 -0.430408562 0.208036207 0.871720480
[71] -0.520032146 0.755854234 0.042001917 0.863336003 0.273064314
[76] -0.080226982 -2.469558654 -0.047322515 -0.300936088 0.979420567
[81] -1.482674272 -1.205971364 0.697467002 1.238301997 -0.701416967
[86] -2.428232928 0.397206831 0.938948250 -0.454465635 -0.326552668
[91] 0.519411595 -0.829447458 -1.295070912 0.154858667 -0.942611100
[96] 1.322574760 0.790523535 -0.021755085 0.183541993 0.725941113
> colMedians(tmp)
[1] -0.890571940 1.707442121 -0.135929427 -0.860582342 0.049222299
[6] 1.006116159 0.105337259 -0.402462675 0.118274881 -0.482955310
[11] 1.244589860 -1.137442155 0.512483673 0.556952465 0.063256713
[16] 2.049081927 -0.515493077 -0.419903733 -0.507122201 0.079062852
[21] 0.509227832 -0.507949881 0.714441805 -0.651967478 -0.365207221
[26] -0.190061320 -1.171459199 0.379994523 -0.640680594 0.878201756
[31] -1.263854242 0.526671888 1.569915444 0.555341027 0.211244917
[36] 0.471973724 0.400748650 0.745838824 0.815176197 -0.633901661
[41] 1.755515228 -1.227810010 -1.990664926 -0.885319973 -0.567885317
[46] 0.630063765 -0.530953020 -0.503839564 0.282512632 -0.226770573
[51] 2.055903421 -0.158628605 -0.842316557 -0.001423204 -0.271457737
[56] -0.996674773 -0.501805420 -1.658855407 0.716785199 -0.231150106
[61] 0.993457834 0.246257223 0.976530628 0.635947815 0.428417225
[66] 0.391530745 -1.304949200 -0.430408562 0.208036207 0.871720480
[71] -0.520032146 0.755854234 0.042001917 0.863336003 0.273064314
[76] -0.080226982 -2.469558654 -0.047322515 -0.300936088 0.979420567
[81] -1.482674272 -1.205971364 0.697467002 1.238301997 -0.701416967
[86] -2.428232928 0.397206831 0.938948250 -0.454465635 -0.326552668
[91] 0.519411595 -0.829447458 -1.295070912 0.154858667 -0.942611100
[96] 1.322574760 0.790523535 -0.021755085 0.183541993 0.725941113
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.8905719 1.707442 -0.1359294 -0.8605823 0.0492223 1.006116 0.1053373
[2,] -0.8905719 1.707442 -0.1359294 -0.8605823 0.0492223 1.006116 0.1053373
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.4024627 0.1182749 -0.4829553 1.24459 -1.137442 0.5124837 0.5569525
[2,] -0.4024627 0.1182749 -0.4829553 1.24459 -1.137442 0.5124837 0.5569525
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.06325671 2.049082 -0.5154931 -0.4199037 -0.5071222 0.07906285 0.5092278
[2,] 0.06325671 2.049082 -0.5154931 -0.4199037 -0.5071222 0.07906285 0.5092278
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.5079499 0.7144418 -0.6519675 -0.3652072 -0.1900613 -1.171459 0.3799945
[2,] -0.5079499 0.7144418 -0.6519675 -0.3652072 -0.1900613 -1.171459 0.3799945
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.6406806 0.8782018 -1.263854 0.5266719 1.569915 0.555341 0.2112449
[2,] -0.6406806 0.8782018 -1.263854 0.5266719 1.569915 0.555341 0.2112449
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.4719737 0.4007486 0.7458388 0.8151762 -0.6339017 1.755515 -1.22781
[2,] 0.4719737 0.4007486 0.7458388 0.8151762 -0.6339017 1.755515 -1.22781
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -1.990665 -0.88532 -0.5678853 0.6300638 -0.530953 -0.5038396 0.2825126
[2,] -1.990665 -0.88532 -0.5678853 0.6300638 -0.530953 -0.5038396 0.2825126
[,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.2267706 2.055903 -0.1586286 -0.8423166 -0.001423204 -0.2714577
[2,] -0.2267706 2.055903 -0.1586286 -0.8423166 -0.001423204 -0.2714577
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.9966748 -0.5018054 -1.658855 0.7167852 -0.2311501 0.9934578 0.2462572
[2,] -0.9966748 -0.5018054 -1.658855 0.7167852 -0.2311501 0.9934578 0.2462572
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 0.9765306 0.6359478 0.4284172 0.3915307 -1.304949 -0.4304086 0.2080362
[2,] 0.9765306 0.6359478 0.4284172 0.3915307 -1.304949 -0.4304086 0.2080362
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 0.8717205 -0.5200321 0.7558542 0.04200192 0.863336 0.2730643 -0.08022698
[2,] 0.8717205 -0.5200321 0.7558542 0.04200192 0.863336 0.2730643 -0.08022698
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -2.469559 -0.04732252 -0.3009361 0.9794206 -1.482674 -1.205971 0.697467
[2,] -2.469559 -0.04732252 -0.3009361 0.9794206 -1.482674 -1.205971 0.697467
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 1.238302 -0.701417 -2.428233 0.3972068 0.9389482 -0.4544656 -0.3265527
[2,] 1.238302 -0.701417 -2.428233 0.3972068 0.9389482 -0.4544656 -0.3265527
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 0.5194116 -0.8294475 -1.295071 0.1548587 -0.9426111 1.322575 0.7905235
[2,] 0.5194116 -0.8294475 -1.295071 0.1548587 -0.9426111 1.322575 0.7905235
[,98] [,99] [,100]
[1,] -0.02175508 0.183542 0.7259411
[2,] -0.02175508 0.183542 0.7259411
>
>
> Max(tmp2)
[1] 2.428367
> Min(tmp2)
[1] -2.330207
> mean(tmp2)
[1] -0.2394029
> Sum(tmp2)
[1] -23.94029
> Var(tmp2)
[1] 0.9858359
>
> rowMeans(tmp2)
[1] -0.941513193 -0.096129349 0.193798531 0.335341038 -0.669731478
[6] 0.020260445 0.942674055 1.762630997 0.908456197 0.371717597
[11] 0.448412580 -0.126290274 -1.317246740 -1.151012471 -0.789488628
[16] -0.349411005 1.644940998 1.321447850 -0.255007703 0.373646861
[21] 0.676517002 -1.836736706 0.459297887 0.202176073 -1.924716104
[26] 0.275168471 -0.704520201 0.620801657 -0.546400230 -0.098962647
[31] -1.990098943 1.458419741 -0.590893272 0.585802695 0.008394127
[36] -0.271437435 -1.427902683 -1.409466674 -0.532908549 1.339680963
[41] -0.037808821 -1.359541608 1.912298713 -0.560557229 0.985997076
[46] -1.384156988 -0.009357322 0.909245423 -0.306545571 -0.197141549
[51] -1.370653371 -0.721353263 -0.483620366 -1.844359032 0.965192661
[56] 0.550561119 -0.380728319 -1.655895207 -0.458478517 -1.261866393
[61] -0.104521105 0.824239698 -1.249067015 -0.116477833 0.265505246
[66] 0.248510739 0.764506159 0.205386119 -0.656104054 -0.261064993
[71] -0.532172896 0.018368109 -1.829693359 -1.348746842 -0.837444743
[76] 0.835033256 -0.775680734 0.837094192 0.385128861 -2.330206601
[81] -0.177339854 1.505381867 -1.901192580 -0.637298150 -0.959124734
[86] -0.878539590 2.428366898 -0.937972931 -1.280834773 -0.523312117
[91] 1.072569190 -0.066641789 0.834337461 -0.766932263 -0.109629893
[96] -0.501442052 -1.527237961 -1.325366328 -1.537427155 -1.204190346
> rowSums(tmp2)
[1] -0.941513193 -0.096129349 0.193798531 0.335341038 -0.669731478
[6] 0.020260445 0.942674055 1.762630997 0.908456197 0.371717597
[11] 0.448412580 -0.126290274 -1.317246740 -1.151012471 -0.789488628
[16] -0.349411005 1.644940998 1.321447850 -0.255007703 0.373646861
[21] 0.676517002 -1.836736706 0.459297887 0.202176073 -1.924716104
[26] 0.275168471 -0.704520201 0.620801657 -0.546400230 -0.098962647
[31] -1.990098943 1.458419741 -0.590893272 0.585802695 0.008394127
[36] -0.271437435 -1.427902683 -1.409466674 -0.532908549 1.339680963
[41] -0.037808821 -1.359541608 1.912298713 -0.560557229 0.985997076
[46] -1.384156988 -0.009357322 0.909245423 -0.306545571 -0.197141549
[51] -1.370653371 -0.721353263 -0.483620366 -1.844359032 0.965192661
[56] 0.550561119 -0.380728319 -1.655895207 -0.458478517 -1.261866393
[61] -0.104521105 0.824239698 -1.249067015 -0.116477833 0.265505246
[66] 0.248510739 0.764506159 0.205386119 -0.656104054 -0.261064993
[71] -0.532172896 0.018368109 -1.829693359 -1.348746842 -0.837444743
[76] 0.835033256 -0.775680734 0.837094192 0.385128861 -2.330206601
[81] -0.177339854 1.505381867 -1.901192580 -0.637298150 -0.959124734
[86] -0.878539590 2.428366898 -0.937972931 -1.280834773 -0.523312117
[91] 1.072569190 -0.066641789 0.834337461 -0.766932263 -0.109629893
[96] -0.501442052 -1.527237961 -1.325366328 -1.537427155 -1.204190346
> 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] -0.941513193 -0.096129349 0.193798531 0.335341038 -0.669731478
[6] 0.020260445 0.942674055 1.762630997 0.908456197 0.371717597
[11] 0.448412580 -0.126290274 -1.317246740 -1.151012471 -0.789488628
[16] -0.349411005 1.644940998 1.321447850 -0.255007703 0.373646861
[21] 0.676517002 -1.836736706 0.459297887 0.202176073 -1.924716104
[26] 0.275168471 -0.704520201 0.620801657 -0.546400230 -0.098962647
[31] -1.990098943 1.458419741 -0.590893272 0.585802695 0.008394127
[36] -0.271437435 -1.427902683 -1.409466674 -0.532908549 1.339680963
[41] -0.037808821 -1.359541608 1.912298713 -0.560557229 0.985997076
[46] -1.384156988 -0.009357322 0.909245423 -0.306545571 -0.197141549
[51] -1.370653371 -0.721353263 -0.483620366 -1.844359032 0.965192661
[56] 0.550561119 -0.380728319 -1.655895207 -0.458478517 -1.261866393
[61] -0.104521105 0.824239698 -1.249067015 -0.116477833 0.265505246
[66] 0.248510739 0.764506159 0.205386119 -0.656104054 -0.261064993
[71] -0.532172896 0.018368109 -1.829693359 -1.348746842 -0.837444743
[76] 0.835033256 -0.775680734 0.837094192 0.385128861 -2.330206601
[81] -0.177339854 1.505381867 -1.901192580 -0.637298150 -0.959124734
[86] -0.878539590 2.428366898 -0.937972931 -1.280834773 -0.523312117
[91] 1.072569190 -0.066641789 0.834337461 -0.766932263 -0.109629893
[96] -0.501442052 -1.527237961 -1.325366328 -1.537427155 -1.204190346
> rowMin(tmp2)
[1] -0.941513193 -0.096129349 0.193798531 0.335341038 -0.669731478
[6] 0.020260445 0.942674055 1.762630997 0.908456197 0.371717597
[11] 0.448412580 -0.126290274 -1.317246740 -1.151012471 -0.789488628
[16] -0.349411005 1.644940998 1.321447850 -0.255007703 0.373646861
[21] 0.676517002 -1.836736706 0.459297887 0.202176073 -1.924716104
[26] 0.275168471 -0.704520201 0.620801657 -0.546400230 -0.098962647
[31] -1.990098943 1.458419741 -0.590893272 0.585802695 0.008394127
[36] -0.271437435 -1.427902683 -1.409466674 -0.532908549 1.339680963
[41] -0.037808821 -1.359541608 1.912298713 -0.560557229 0.985997076
[46] -1.384156988 -0.009357322 0.909245423 -0.306545571 -0.197141549
[51] -1.370653371 -0.721353263 -0.483620366 -1.844359032 0.965192661
[56] 0.550561119 -0.380728319 -1.655895207 -0.458478517 -1.261866393
[61] -0.104521105 0.824239698 -1.249067015 -0.116477833 0.265505246
[66] 0.248510739 0.764506159 0.205386119 -0.656104054 -0.261064993
[71] -0.532172896 0.018368109 -1.829693359 -1.348746842 -0.837444743
[76] 0.835033256 -0.775680734 0.837094192 0.385128861 -2.330206601
[81] -0.177339854 1.505381867 -1.901192580 -0.637298150 -0.959124734
[86] -0.878539590 2.428366898 -0.937972931 -1.280834773 -0.523312117
[91] 1.072569190 -0.066641789 0.834337461 -0.766932263 -0.109629893
[96] -0.501442052 -1.527237961 -1.325366328 -1.537427155 -1.204190346
>
> colMeans(tmp2)
[1] -0.2394029
> colSums(tmp2)
[1] -23.94029
> colVars(tmp2)
[1] 0.9858359
> colSd(tmp2)
[1] 0.9928927
> colMax(tmp2)
[1] 2.428367
> colMin(tmp2)
[1] -2.330207
> colMedians(tmp2)
[1] -0.2580363
> colRanges(tmp2)
[,1]
[1,] -2.330207
[2,] 2.428367
>
> 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] -4.9720995 -2.1990541 -2.8065983 -1.8202434 1.1984866 -2.3061289
[7] -0.6799602 5.3108711 4.3898145 3.1342137
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.1763952
[2,] -0.7695761
[3,] -0.5420147
[4,] -0.3539015
[5,] 1.5909281
>
> rowApply(tmp,sum)
[1] -2.8748051 -2.1298411 -1.7793315 -2.5738528 2.9776926 0.8014295
[7] -4.8693185 0.6580190 5.8444305 3.1948789
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 3 4 4 1 6 7 1 9 1
[2,] 8 1 7 2 9 7 9 4 2 3
[3,] 1 2 3 5 3 8 8 2 5 6
[4,] 7 4 6 3 2 1 5 5 7 8
[5,] 9 6 2 7 4 10 2 10 3 4
[6,] 4 8 9 6 5 5 1 9 1 2
[7,] 2 10 10 1 7 4 4 3 4 10
[8,] 10 7 5 9 8 2 6 8 10 9
[9,] 5 5 1 10 10 3 10 7 6 5
[10,] 6 9 8 8 6 9 3 6 8 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.5762418 -0.9678961 0.2075174 0.9887812 0.3772691 0.4541604
[7] -2.8343377 -0.2328239 -1.5255687 -2.0439036 0.6948342 3.8125891
[13] -3.1425601 1.2330121 3.3694903 -0.1112748 6.9142515 1.5691364
[19] 2.9143291 1.0870855
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.5654034
[2,] 0.4616635
[3,] 0.4747406
[4,] 0.9539809
[5,] 1.2512602
>
> rowApply(tmp,sum)
[1] 4.7943435 -2.0871133 0.5282240 9.7144837 0.3903954
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 13 19 15 1 18
[2,] 9 9 9 8 5
[3,] 2 2 18 18 11
[4,] 10 13 7 9 15
[5,] 4 5 8 15 13
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.4616635 0.21546542 -1.42999985 0.2794717 -0.2007421 1.1688353
[2,] 1.2512602 -0.52407467 -1.37776697 0.2976042 -1.1266855 -1.4511802
[3,] 0.4747406 0.04505533 0.97406343 -0.4264618 -0.3029741 0.5906349
[4,] -2.5654034 0.07986825 1.96859523 0.2660538 1.4971784 -0.4158536
[5,] 0.9539809 -0.78421042 0.07262555 0.5721134 0.5104923 0.5617240
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -1.5110280 0.6779371 0.9378502 0.7894007 -0.1860412 0.0554043
[2,] 0.5364908 1.2464306 -1.0214782 -1.1472460 -0.2928834 0.1370108
[3,] -1.5521683 -0.7548538 0.3705068 -0.9776392 0.4543135 0.1262998
[4,] 0.9811959 -0.6240363 -0.9236753 -1.4862969 0.9204542 1.7268323
[5,] -1.2888281 -0.7783015 -0.8887722 0.7778778 -0.2010089 1.7670419
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.94305007 -0.07263144 1.47743506 -0.9209848 1.4385864 0.4335194
[2,] -1.34235398 0.14376477 1.28769190 -0.8551980 1.2285015 -0.7081255
[3,] -0.98450479 1.12558571 0.12759924 0.8820757 0.3396272 -0.4914940
[4,] -0.05284359 -0.57915062 0.46590727 1.7819930 2.6268400 2.1561305
[5,] -1.70590780 0.61544368 0.01085681 -0.9991606 1.2806965 0.1791061
[,19] [,20]
[1,] 0.3426436 -0.10549177
[2,] 0.9134001 0.71772428
[3,] 1.2495409 -0.74172326
[4,] 0.5817158 1.30897887
[5,] -0.1729713 -0.09240264
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.17-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-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 710 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.17-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-3.17-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 -0.2371397 -0.1907472 -0.4806215 0.1203408 0.2032009 0.2738994 -0.6477989
col8 col9 col10 col11 col12 col13 col14
row1 -0.4407325 -1.998742 -0.2821482 0.773777 1.022356 0.9225898 -0.3145842
col15 col16 col17 col18 col19 col20
row1 1.054912 0.818159 0.7660573 0.03538286 -0.6221022 -0.8458386
> tmp[,"col10"]
col10
row1 -0.2821482
row2 -0.9101689
row3 -0.5106064
row4 -0.4103436
row5 -0.9141395
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.2371397 -0.1907472 -0.4806215 0.1203408 0.2032009 0.2738994 -0.6477989
row5 2.1540241 -0.4527049 -0.5338700 1.4139374 0.6702825 0.7890267 0.3779201
col8 col9 col10 col11 col12 col13 col14
row1 -0.4407325 -1.9987418 -0.2821482 0.7737770 1.022356 0.9225898 -0.3145842
row5 -0.2120497 -0.7729827 -0.9141395 0.5894538 1.095317 0.1280187 -0.9237675
col15 col16 col17 col18 col19 col20
row1 1.0549123 0.8181590 0.76605735 0.03538286 -0.6221022 -0.8458386
row5 -0.8939897 0.1504841 0.04382111 -0.73955296 0.3543816 -0.8275517
> tmp[,c("col6","col20")]
col6 col20
row1 0.2738994 -0.8458386
row2 -0.4884005 0.1319816
row3 0.4845263 2.4004958
row4 -2.0181504 0.9171046
row5 0.7890267 -0.8275517
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.2738994 -0.8458386
row5 0.7890267 -0.8275517
>
>
>
>
> 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 47.47983 49.48446 51.59686 49.65203 50.26651 105.1205 50.17219 51.65087
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.5173 49.97279 50.35043 48.11641 49.36618 49.27869 51.22058 48.47149
col17 col18 col19 col20
row1 51.06553 49.39188 50.65406 104.773
> tmp[,"col10"]
col10
row1 49.97279
row2 28.51778
row3 31.22179
row4 30.09371
row5 48.82565
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 47.47983 49.48446 51.59686 49.65203 50.26651 105.1205 50.17219 51.65087
row5 50.77837 51.22115 47.84324 50.04389 50.07067 105.9167 47.45591 51.27778
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.51730 49.97279 50.35043 48.11641 49.36618 49.27869 51.22058 48.47149
row5 52.10735 48.82565 49.54083 49.64073 50.56507 50.84913 49.91664 52.41684
col17 col18 col19 col20
row1 51.06553 49.39188 50.65406 104.7730
row5 49.52998 51.31660 49.29665 104.2837
> tmp[,c("col6","col20")]
col6 col20
row1 105.12046 104.77305
row2 74.93053 74.91496
row3 74.38162 71.99706
row4 75.10584 73.97128
row5 105.91667 104.28366
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.1205 104.7730
row5 105.9167 104.2837
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.1205 104.7730
row5 105.9167 104.2837
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.1354418
[2,] 0.2007980
[3,] 1.6107218
[4,] -0.5896155
[5,] -0.6546034
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.7325208 0.09384546
[2,] 0.3291883 0.08124812
[3,] 1.0075261 1.86628144
[4,] 1.4541759 0.31485746
[5,] -1.4427908 -0.40579327
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.06558208 1.0813650
[2,] -0.35550227 -1.3655486
[3,] -0.05471552 -1.8823430
[4,] 0.06324094 1.9484447
[5,] -0.30822630 0.2653773
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.06558208
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.06558208
[2,] -0.35550227
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 0.7803706 -0.4856637 1.6410568 2.287453 1.898435 -1.364925 -1.4280472
row1 -0.2576403 1.2978485 0.3625786 1.048954 -0.129934 1.205617 0.3855539
[,8] [,9] [,10] [,11] [,12] [,13]
row3 1.0422280 -1.35720330 -0.3159257 -0.3786494 -0.9256798 -0.8626671
row1 0.5401539 0.04561126 -0.4921011 -0.1054021 0.5104126 -0.8455296
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.2390940 0.85878028 -0.6784978 -0.2870969 0.6579135 -0.5127142 0.3152839
row1 -0.8805598 0.07730108 2.0665201 0.4740497 1.4775209 1.7812348 0.4424580
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.5335491 0.7296335 0.7624575 -0.00218895 0.1486318 1.575085 1.388113
[,8] [,9] [,10]
row2 -0.05456278 -1.180319 -0.6020453
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.4561631 -0.4230532 -0.2011505 0.04248554 -2.50907 -1.394998 0.6477708
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.9849313 -0.2637437 -0.7204982 -0.3670872 -2.407482 0.2812346 1.174259
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.3662353 -0.7706154 -1.467039 0.1054096 -1.424562 -1.147942
>
>
> 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: 0x6000029ab4e0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BMdf1e6e999e2e"
[2] "/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BMdf1e276016bc"
[3] "/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BMdf1e1574a4d6"
[4] "/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BMdf1e1cf1e89b"
[5] "/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BMdf1e4dde26f5"
[6] "/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BMdf1e33cfc6c3"
[7] "/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BMdf1ee0246c8"
[8] "/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BMdf1e3774fba7"
[9] "/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BMdf1e6135ad62"
[10] "/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BMdf1eb0a2eca"
[11] "/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BMdf1e4985d56f"
[12] "/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BMdf1e717f901e"
[13] "/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BMdf1e6dcedbc8"
[14] "/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BMdf1e27bf5fca"
[15] "/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BMdf1e529db29"
>
>
> ### 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: 0x6000029b6f40>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000029b6f40>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.17-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6000029b6f40>
> rowMedians(tmp)
[1] -0.270442637 0.457203743 0.167549560 0.207388402 -0.393620335
[6] -0.127701880 -0.005239197 -0.279583759 -0.517933769 -0.093383290
[11] -0.379359780 -0.329832165 0.168109341 0.035254282 0.154989483
[16] 0.773532004 -0.429436901 0.030876618 0.462550828 0.289860928
[21] -0.306504705 0.248139092 0.085911198 -0.135239759 0.423954176
[26] -0.164949218 -0.092341033 -0.126405225 -0.029303169 -0.045627102
[31] -0.106151853 -0.304479918 0.031313420 -0.243465474 -0.143221724
[36] -0.490159688 0.119753811 0.264476864 -0.445405595 -0.048798730
[41] 0.846661292 0.016671280 -0.223972191 0.222786151 0.432562117
[46] 0.481967314 -0.440093476 0.058901740 0.346458816 0.118047265
[51] -0.015919914 0.330236483 -0.311086384 0.488673519 0.117798536
[56] 0.276834929 1.054646634 -0.379709358 -0.006897930 -0.182116112
[61] -0.398375713 0.072853718 0.220468137 -0.130363483 -0.221072681
[66] 0.152157921 -0.185032789 -0.073549818 0.131228019 -0.346913882
[71] -0.671995204 -0.335347963 0.007943850 0.258812398 -0.157072440
[76] -0.376124553 0.554985967 0.383569539 -0.254695146 -0.137208768
[81] -0.512837716 -0.506933786 0.460449778 -0.678361207 0.013973149
[86] -0.185834639 -0.291151881 -0.138386018 -0.104925239 -0.048424324
[91] -0.227973540 0.023800597 -0.741702666 -0.054285898 0.386052501
[96] -0.491152207 -0.085834979 0.653597114 0.019690683 -0.097115525
[101] 0.578522022 -0.156746333 -0.047512094 -0.153121161 0.686620823
[106] 0.279816133 -0.209654529 -0.184039682 0.246241893 0.339790962
[111] -0.104247727 0.242970201 -0.544564098 -0.361383528 0.036512347
[116] -0.050229761 -0.572325401 0.254283011 0.042912149 -0.092551617
[121] 0.398379918 -0.142273910 -0.018075508 -0.327677654 0.317906939
[126] 0.175374338 0.134297453 0.198121058 -0.061263949 0.195459060
[131] 0.206874612 0.197672181 0.561868609 -0.170399668 0.268629014
[136] -0.532053137 -0.033167645 0.690740639 -0.216966413 0.325554614
[141] -0.183812445 0.042064171 0.358125252 -0.459290345 0.505909205
[146] 0.256795149 0.363376857 0.694229246 -0.072428977 -0.129608921
[151] -0.089497577 -0.282090214 0.028265343 0.146419570 0.335813208
[156] -0.516141276 -0.081190603 -0.267956930 -0.329616948 0.115357411
[161] 0.619933152 -0.252864522 0.683951004 -0.364068443 -0.258859670
[166] 0.084768459 0.492415892 0.262946917 -0.337204407 0.254626500
[171] 0.064699550 -0.072978751 0.029769300 0.194776065 -0.034107905
[176] 0.037309861 -0.492557983 0.602133707 0.198669079 0.062081474
[181] -0.170205206 0.199232505 -0.084101412 0.020721427 0.156389276
[186] -0.059723512 0.425323928 0.633827452 -0.235843278 0.277345224
[191] -0.094994895 -0.205368115 -0.622683846 0.300426106 0.079905449
[196] -0.410703105 -0.017350868 -0.106335215 0.554891914 0.205010736
[201] 0.268380812 -0.050871733 0.263238124 -0.157795263 0.253228875
[206] 0.207512297 0.002156626 0.494329105 -0.166638425 -0.279464513
[211] -0.085580537 -0.193131071 -0.179886535 0.039523821 0.073048835
[216] -0.069299737 0.359952966 -0.306137691 0.436621701 -0.015967851
[221] -0.165581871 0.173302172 0.008968405 -0.420831540 -0.324528795
[226] 0.016725688 -0.678883931 -0.617296141 -0.330677877 0.110461486
>
> proc.time()
user system elapsed
2.414 8.859 19.311
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20 (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: 0x600002074720>
> .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: 0x600002074720>
> .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: 0x600002074720>
> .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: 0x600002074720>
> 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: 0x6000020709c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000020709c0>
> .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: 0x6000020709c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000020709c0>
> .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: 0x6000020709c0>
> 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: 0x60000207c360>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000207c360>
> .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: 0x60000207c360>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x60000207c360>
> .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: 0x60000207c360>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x60000207c360>
> .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: 0x60000207c360>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x60000207c360>
> .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: 0x60000207c360>
> 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: 0x600002074960>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600002074960>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002074960>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002074960>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilee05b3327e0f5" "BufferedMatrixFilee05b7f220f0f"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilee05b3327e0f5" "BufferedMatrixFilee05b7f220f0f"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002070ba0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002070ba0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600002070ba0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600002070ba0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600002070ba0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600002070ba0>
> .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: 0x600002070d80>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002070d80>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600002070d80>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600002070d80>
> 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: 0x600002070f60>
> .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: 0x600002070f60>
> rm(P)
>
> proc.time()
user system elapsed
0.350 0.109 0.720
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20 (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.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.342 0.078 0.669