| Back to Mac ARM64 build report for BioC 3.19 |
|
This page was generated on 2024-05-07 11:32:30 -0400 (Tue, 07 May 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| kjohnson3 | macOS 13.6.5 Ventura | arm64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4461 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 249/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.68.0 (landing page) Ben Bolstad
| kjohnson3 | macOS 13.6.5 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: 1.68.0 |
| 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_1.68.0.tar.gz |
| StartedAt: 2024-05-06 20:05:54 -0400 (Mon, 06 May 2024) |
| EndedAt: 2024-05-06 20:06:09 -0400 (Mon, 06 May 2024) |
| EllapsedTime: 15.2 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_1.68.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck’
* using R version 4.4.0 (2024-04-24)
* 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 13.6.5
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.68.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... 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-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
* 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 ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
Running ‘Rcodetesting.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-3.19-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/4.4-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
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 (2024-04-24) -- "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
0.113 0.033 0.142
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: 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-3.19-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 474154 25.4 1035437 55.3 NA 638577 34.2
Vcells 877598 6.7 8388608 64.0 196608 2072866 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] "Mon May 6 20:06:03 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] "Mon May 6 20:06:03 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: 0x600003af0660>
>
>
>
> 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] "Mon May 6 20:06:04 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] "Mon May 6 20:06:04 2024"
>
> ColMode(tmp2)
<pointer: 0x600003af0660>
>
>
>
> ### 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,] 98.4229901 -0.7179900 0.4692752 -0.2789668
[2,] 0.5452138 -1.2953496 0.3572201 0.1475281
[3,] 0.6860532 0.4318072 -0.3908537 0.1211217
[4,] -0.4335475 1.6486702 0.5607235 1.5430302
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2.2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 98.4229901 0.7179900 0.4692752 0.2789668
[2,] 0.5452138 1.2953496 0.3572201 0.1475281
[3,] 0.6860532 0.4318072 0.3908537 0.1211217
[4,] 0.4335475 1.6486702 0.5607235 1.5430302
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2.2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9208362 0.8473429 0.6850367 0.5281730
[2,] 0.7383859 1.1381343 0.5976789 0.3840938
[3,] 0.8282833 0.6571204 0.6251830 0.3480255
[4,] 0.6584432 1.2840055 0.7488147 1.2421877
>
> 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-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2.2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 222.63135 34.19142 32.31964 30.56070
[2,] 32.92907 37.67669 31.33401 28.98847
[3,] 33.96889 32.00301 31.64268 28.60138
[4,] 32.01798 39.48873 33.04887 38.96491
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600003af8780>
> exp(tmp5)
<pointer: 0x600003af8780>
> log(tmp5,2)
<pointer: 0x600003af8780>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 463.378
> Min(tmp5)
[1] 53.1703
> mean(tmp5)
[1] 73.78958
> Sum(tmp5)
[1] 14757.92
> Var(tmp5)
[1] 835.683
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.11203 70.03213 71.09027 72.15939 70.43776 73.38730 68.85543 75.06141
[9] 73.00625 74.75386
> rowSums(tmp5)
[1] 1782.241 1400.643 1421.805 1443.188 1408.755 1467.746 1377.109 1501.228
[9] 1460.125 1495.077
> rowVars(tmp5)
[1] 7786.96330 100.37453 59.87681 49.26732 63.72913 96.62407
[7] 92.36180 51.62527 88.24867 50.19532
> rowSd(tmp5)
[1] 88.243772 10.018709 7.738011 7.019068 7.983053 9.829754 9.610505
[8] 7.185072 9.394076 7.084866
> rowMax(tmp5)
[1] 463.37799 93.72052 87.53247 82.19061 84.96564 91.02946 90.87415
[8] 88.36661 92.46983 85.14006
> rowMin(tmp5)
[1] 59.81193 59.05733 59.53002 53.17290 58.83691 53.17030 53.61625 58.34215
[9] 55.38610 62.11249
>
> colMeans(tmp5)
[1] 110.19706 72.79534 71.12838 70.00693 73.04580 72.42638 69.32480
[8] 72.77123 73.54907 69.49873 75.71313 74.56252 70.70508 65.32053
[15] 72.07752 76.81387 70.88168 74.02623 71.35664 69.59077
> colSums(tmp5)
[1] 1101.9706 727.9534 711.2838 700.0693 730.4580 724.2638 693.2480
[8] 727.7123 735.4907 694.9873 757.1313 745.6252 707.0508 653.2053
[15] 720.7752 768.1387 708.8168 740.2623 713.5664 695.9077
> colVars(tmp5)
[1] 15478.52887 51.84622 30.65161 68.92900 93.55465 21.52806
[7] 62.04032 139.07674 78.93475 37.67729 104.96156 81.50044
[13] 45.22967 83.51078 113.57650 28.25557 28.44979 143.95079
[19] 50.78902 46.65398
> colSd(tmp5)
[1] 124.412736 7.200432 5.536389 8.302349 9.672365 4.639834
[7] 7.876568 11.793080 8.884523 6.138183 10.245075 9.027759
[13] 6.725300 9.138423 10.657228 5.315597 5.333835 11.997949
[19] 7.126642 6.830372
> colMax(tmp5)
[1] 463.37799 82.19061 80.90391 82.01655 88.07549 78.80439 78.37026
[8] 92.46983 90.87415 79.57611 85.83123 93.72052 83.64824 82.13575
[15] 91.02946 87.53247 79.38058 85.51290 80.55211 76.76601
> colMin(tmp5)
[1] 53.17030 59.75069 65.21763 59.53002 59.77273 65.41921 58.82169 58.50998
[9] 62.13330 59.81193 57.51167 60.95602 62.91333 53.17290 58.83691 68.05680
[17] 62.11249 53.61625 59.05733 55.61830
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 89.11203 70.03213 71.09027 NA 70.43776 73.38730 68.85543 75.06141
[9] 73.00625 74.75386
> rowSums(tmp5)
[1] 1782.241 1400.643 1421.805 NA 1408.755 1467.746 1377.109 1501.228
[9] 1460.125 1495.077
> rowVars(tmp5)
[1] 7786.96330 100.37453 59.87681 51.99904 63.72913 96.62407
[7] 92.36180 51.62527 88.24867 50.19532
> rowSd(tmp5)
[1] 88.243772 10.018709 7.738011 7.211036 7.983053 9.829754 9.610505
[8] 7.185072 9.394076 7.084866
> rowMax(tmp5)
[1] 463.37799 93.72052 87.53247 NA 84.96564 91.02946 90.87415
[8] 88.36661 92.46983 85.14006
> rowMin(tmp5)
[1] 59.81193 59.05733 59.53002 NA 58.83691 53.17030 53.61625 58.34215
[9] 55.38610 62.11249
>
> colMeans(tmp5)
[1] 110.19706 72.79534 71.12838 70.00693 73.04580 72.42638 69.32480
[8] 72.77123 73.54907 69.49873 75.71313 74.56252 70.70508 65.32053
[15] 72.07752 76.81387 70.88168 74.02623 71.35664 NA
> colSums(tmp5)
[1] 1101.9706 727.9534 711.2838 700.0693 730.4580 724.2638 693.2480
[8] 727.7123 735.4907 694.9873 757.1313 745.6252 707.0508 653.2053
[15] 720.7752 768.1387 708.8168 740.2623 713.5664 NA
> colVars(tmp5)
[1] 15478.52887 51.84622 30.65161 68.92900 93.55465 21.52806
[7] 62.04032 139.07674 78.93475 37.67729 104.96156 81.50044
[13] 45.22967 83.51078 113.57650 28.25557 28.44979 143.95079
[19] 50.78902 NA
> colSd(tmp5)
[1] 124.412736 7.200432 5.536389 8.302349 9.672365 4.639834
[7] 7.876568 11.793080 8.884523 6.138183 10.245075 9.027759
[13] 6.725300 9.138423 10.657228 5.315597 5.333835 11.997949
[19] 7.126642 NA
> colMax(tmp5)
[1] 463.37799 82.19061 80.90391 82.01655 88.07549 78.80439 78.37026
[8] 92.46983 90.87415 79.57611 85.83123 93.72052 83.64824 82.13575
[15] 91.02946 87.53247 79.38058 85.51290 80.55211 NA
> colMin(tmp5)
[1] 53.17030 59.75069 65.21763 59.53002 59.77273 65.41921 58.82169 58.50998
[9] 62.13330 59.81193 57.51167 60.95602 62.91333 53.17290 58.83691 68.05680
[17] 62.11249 53.61625 59.05733 NA
>
> Max(tmp5,na.rm=TRUE)
[1] 463.378
> Min(tmp5,na.rm=TRUE)
[1] 53.1703
> mean(tmp5,na.rm=TRUE)
[1] 73.7993
> Sum(tmp5,na.rm=TRUE)
[1] 14686.06
> Var(tmp5,na.rm=TRUE)
[1] 839.8847
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.11203 70.03213 71.09027 72.17531 70.43776 73.38730 68.85543 75.06141
[9] 73.00625 74.75386
> rowSums(tmp5,na.rm=TRUE)
[1] 1782.241 1400.643 1421.805 1371.331 1408.755 1467.746 1377.109 1501.228
[9] 1460.125 1495.077
> rowVars(tmp5,na.rm=TRUE)
[1] 7786.96330 100.37453 59.87681 51.99904 63.72913 96.62407
[7] 92.36180 51.62527 88.24867 50.19532
> rowSd(tmp5,na.rm=TRUE)
[1] 88.243772 10.018709 7.738011 7.211036 7.983053 9.829754 9.610505
[8] 7.185072 9.394076 7.084866
> rowMax(tmp5,na.rm=TRUE)
[1] 463.37799 93.72052 87.53247 82.19061 84.96564 91.02946 90.87415
[8] 88.36661 92.46983 85.14006
> rowMin(tmp5,na.rm=TRUE)
[1] 59.81193 59.05733 59.53002 53.17290 58.83691 53.17030 53.61625 58.34215
[9] 55.38610 62.11249
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.19706 72.79534 71.12838 70.00693 73.04580 72.42638 69.32480
[8] 72.77123 73.54907 69.49873 75.71313 74.56252 70.70508 65.32053
[15] 72.07752 76.81387 70.88168 74.02623 71.35664 69.33896
> colSums(tmp5,na.rm=TRUE)
[1] 1101.9706 727.9534 711.2838 700.0693 730.4580 724.2638 693.2480
[8] 727.7123 735.4907 694.9873 757.1313 745.6252 707.0508 653.2053
[15] 720.7752 768.1387 708.8168 740.2623 713.5664 624.0507
> colVars(tmp5,na.rm=TRUE)
[1] 15478.52887 51.84622 30.65161 68.92900 93.55465 21.52806
[7] 62.04032 139.07674 78.93475 37.67729 104.96156 81.50044
[13] 45.22967 83.51078 113.57650 28.25557 28.44979 143.95079
[19] 50.78902 51.77243
> colSd(tmp5,na.rm=TRUE)
[1] 124.412736 7.200432 5.536389 8.302349 9.672365 4.639834
[7] 7.876568 11.793080 8.884523 6.138183 10.245075 9.027759
[13] 6.725300 9.138423 10.657228 5.315597 5.333835 11.997949
[19] 7.126642 7.195306
> colMax(tmp5,na.rm=TRUE)
[1] 463.37799 82.19061 80.90391 82.01655 88.07549 78.80439 78.37026
[8] 92.46983 90.87415 79.57611 85.83123 93.72052 83.64824 82.13575
[15] 91.02946 87.53247 79.38058 85.51290 80.55211 76.76601
> colMin(tmp5,na.rm=TRUE)
[1] 53.17030 59.75069 65.21763 59.53002 59.77273 65.41921 58.82169 58.50998
[9] 62.13330 59.81193 57.51167 60.95602 62.91333 53.17290 58.83691 68.05680
[17] 62.11249 53.61625 59.05733 55.61830
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.11203 70.03213 71.09027 NaN 70.43776 73.38730 68.85543 75.06141
[9] 73.00625 74.75386
> rowSums(tmp5,na.rm=TRUE)
[1] 1782.241 1400.643 1421.805 0.000 1408.755 1467.746 1377.109 1501.228
[9] 1460.125 1495.077
> rowVars(tmp5,na.rm=TRUE)
[1] 7786.96330 100.37453 59.87681 NA 63.72913 96.62407
[7] 92.36180 51.62527 88.24867 50.19532
> rowSd(tmp5,na.rm=TRUE)
[1] 88.243772 10.018709 7.738011 NA 7.983053 9.829754 9.610505
[8] 7.185072 9.394076 7.084866
> rowMax(tmp5,na.rm=TRUE)
[1] 463.37799 93.72052 87.53247 NA 84.96564 91.02946 90.87415
[8] 88.36661 92.46983 85.14006
> rowMin(tmp5,na.rm=TRUE)
[1] 59.81193 59.05733 59.53002 NA 58.83691 53.17030 53.61625 58.34215
[9] 55.38610 62.11249
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.03660 71.75142 71.38854 68.77433 73.75200 72.21830 68.56227
[8] 73.73817 73.30782 69.62062 75.41229 75.65983 70.71288 66.67026
[15] 71.16503 77.02921 70.34703 73.65855 71.27021 NaN
> colSums(tmp5,na.rm=TRUE)
[1] 1035.3294 645.7628 642.4969 618.9689 663.7680 649.9647 617.0604
[8] 663.6435 659.7704 626.5856 678.7106 680.9385 636.4160 600.0324
[15] 640.4852 693.2629 633.1233 662.9269 641.4319 0.0000
> colVars(tmp5,na.rm=TRUE)
[1] 17149.85738 46.06713 33.72160 60.45291 99.63845 23.73197
[7] 63.25396 145.94288 88.14681 42.21981 117.06362 78.14203
[13] 50.88269 73.45450 118.40638 31.26584 28.79025 160.42376
[19] 57.05360 NA
> colSd(tmp5,na.rm=TRUE)
[1] 130.957464 6.787277 5.807030 7.775147 9.981906 4.871547
[7] 7.953236 12.080682 9.388653 6.497677 10.819594 8.839798
[13] 7.133210 8.570560 10.881469 5.591587 5.365654 12.665850
[19] 7.553384 NA
> colMax(tmp5,na.rm=TRUE)
[1] 463.37799 80.18752 80.90391 82.01655 88.07549 78.80439 78.37026
[8] 92.46983 90.87415 79.57611 85.83123 93.72052 83.64824 82.13575
[15] 91.02946 87.53247 79.38058 85.51290 80.55211 -Inf
> colMin(tmp5,na.rm=TRUE)
[1] 53.17030 59.75069 65.21763 59.53002 59.77273 65.41921 58.82169 58.50998
[9] 62.13330 59.81193 57.51167 60.95602 62.91333 55.38610 58.83691 68.05680
[17] 62.11249 53.61625 59.05733 Inf
>
>
>
>
> 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] 225.5461 405.8657 193.3752 180.2943 125.1649 166.4227 264.9393 248.7579
[9] 177.1746 158.9296
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 225.5461 405.8657 193.3752 180.2943 125.1649 166.4227 264.9393 248.7579
[9] 177.1746 158.9296
>
>
>
> 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] -8.526513e-14 5.684342e-14 0.000000e+00 -8.526513e-14 0.000000e+00
[6] 2.842171e-13 -1.421085e-14 0.000000e+00 -5.684342e-14 0.000000e+00
[11] 2.842171e-14 2.273737e-13 1.136868e-13 1.705303e-13 7.105427e-14
[16] 4.263256e-14 -8.526513e-14 7.105427e-14 2.842171e-14 -8.526513e-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)
+ }
6 15
2 10
9 8
8 1
10 13
3 3
5 7
7 16
3 3
3 16
5 2
7 2
3 9
5 8
2 2
9 12
1 13
2 1
1 18
9 7
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] 2.206403
> Min(tmp)
[1] -2.451894
> mean(tmp)
[1] 0.01485967
> Sum(tmp)
[1] 1.485967
> Var(tmp)
[1] 0.9881573
>
> rowMeans(tmp)
[1] 0.01485967
> rowSums(tmp)
[1] 1.485967
> rowVars(tmp)
[1] 0.9881573
> rowSd(tmp)
[1] 0.994061
> rowMax(tmp)
[1] 2.206403
> rowMin(tmp)
[1] -2.451894
>
> colMeans(tmp)
[1] -1.169919549 -0.341340074 -0.492366920 1.022009275 -0.082380027
[6] -0.382840654 1.477847687 -0.318370071 1.014361168 0.045077646
[11] 1.165386867 1.406000266 0.276345268 -1.647247844 -0.215557239
[16] 0.005001830 -0.087594856 -0.064904272 -0.847981775 0.446806740
[21] -0.481982504 -0.048123889 0.621890367 1.359837818 -1.379645554
[26] 2.206403396 0.481740067 1.300702070 -0.191027725 -0.615345698
[31] 1.253859693 -0.264731381 0.349581410 -2.451894493 -0.115617572
[36] 0.570107995 1.406379044 0.757389600 2.126709826 -0.206405073
[41] -1.455348899 -1.439538588 -0.913928067 0.266968902 -1.548508700
[46] 1.172678799 1.308559147 -1.986344252 -0.832380281 -1.260202379
[51] -0.344877161 1.695641758 0.126235523 1.569986219 -1.211309128
[56] -0.197309332 0.772516644 -1.160297142 2.065460759 -1.456536681
[61] -0.888322588 1.125707674 -1.427048985 0.403438714 -1.373109421
[66] 0.415443947 -1.113659028 -1.197943142 -0.118976181 0.543606348
[71] -0.548607323 -0.225308206 0.305553130 -0.256367103 0.182897298
[76] -0.649619861 0.368932291 0.208916400 -0.201725263 -0.006629843
[81] 0.354122787 -0.997077504 1.003453955 0.599691973 -0.081075255
[86] 0.817218875 0.229528436 0.382308638 0.199607591 -0.721777808
[91] 0.186545452 1.157918305 0.400522575 -0.402557219 -0.669730066
[96] 0.755119385 1.858928895 0.180381081 -0.151572064 -2.222397890
> colSums(tmp)
[1] -1.169919549 -0.341340074 -0.492366920 1.022009275 -0.082380027
[6] -0.382840654 1.477847687 -0.318370071 1.014361168 0.045077646
[11] 1.165386867 1.406000266 0.276345268 -1.647247844 -0.215557239
[16] 0.005001830 -0.087594856 -0.064904272 -0.847981775 0.446806740
[21] -0.481982504 -0.048123889 0.621890367 1.359837818 -1.379645554
[26] 2.206403396 0.481740067 1.300702070 -0.191027725 -0.615345698
[31] 1.253859693 -0.264731381 0.349581410 -2.451894493 -0.115617572
[36] 0.570107995 1.406379044 0.757389600 2.126709826 -0.206405073
[41] -1.455348899 -1.439538588 -0.913928067 0.266968902 -1.548508700
[46] 1.172678799 1.308559147 -1.986344252 -0.832380281 -1.260202379
[51] -0.344877161 1.695641758 0.126235523 1.569986219 -1.211309128
[56] -0.197309332 0.772516644 -1.160297142 2.065460759 -1.456536681
[61] -0.888322588 1.125707674 -1.427048985 0.403438714 -1.373109421
[66] 0.415443947 -1.113659028 -1.197943142 -0.118976181 0.543606348
[71] -0.548607323 -0.225308206 0.305553130 -0.256367103 0.182897298
[76] -0.649619861 0.368932291 0.208916400 -0.201725263 -0.006629843
[81] 0.354122787 -0.997077504 1.003453955 0.599691973 -0.081075255
[86] 0.817218875 0.229528436 0.382308638 0.199607591 -0.721777808
[91] 0.186545452 1.157918305 0.400522575 -0.402557219 -0.669730066
[96] 0.755119385 1.858928895 0.180381081 -0.151572064 -2.222397890
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] -1.169919549 -0.341340074 -0.492366920 1.022009275 -0.082380027
[6] -0.382840654 1.477847687 -0.318370071 1.014361168 0.045077646
[11] 1.165386867 1.406000266 0.276345268 -1.647247844 -0.215557239
[16] 0.005001830 -0.087594856 -0.064904272 -0.847981775 0.446806740
[21] -0.481982504 -0.048123889 0.621890367 1.359837818 -1.379645554
[26] 2.206403396 0.481740067 1.300702070 -0.191027725 -0.615345698
[31] 1.253859693 -0.264731381 0.349581410 -2.451894493 -0.115617572
[36] 0.570107995 1.406379044 0.757389600 2.126709826 -0.206405073
[41] -1.455348899 -1.439538588 -0.913928067 0.266968902 -1.548508700
[46] 1.172678799 1.308559147 -1.986344252 -0.832380281 -1.260202379
[51] -0.344877161 1.695641758 0.126235523 1.569986219 -1.211309128
[56] -0.197309332 0.772516644 -1.160297142 2.065460759 -1.456536681
[61] -0.888322588 1.125707674 -1.427048985 0.403438714 -1.373109421
[66] 0.415443947 -1.113659028 -1.197943142 -0.118976181 0.543606348
[71] -0.548607323 -0.225308206 0.305553130 -0.256367103 0.182897298
[76] -0.649619861 0.368932291 0.208916400 -0.201725263 -0.006629843
[81] 0.354122787 -0.997077504 1.003453955 0.599691973 -0.081075255
[86] 0.817218875 0.229528436 0.382308638 0.199607591 -0.721777808
[91] 0.186545452 1.157918305 0.400522575 -0.402557219 -0.669730066
[96] 0.755119385 1.858928895 0.180381081 -0.151572064 -2.222397890
> colMin(tmp)
[1] -1.169919549 -0.341340074 -0.492366920 1.022009275 -0.082380027
[6] -0.382840654 1.477847687 -0.318370071 1.014361168 0.045077646
[11] 1.165386867 1.406000266 0.276345268 -1.647247844 -0.215557239
[16] 0.005001830 -0.087594856 -0.064904272 -0.847981775 0.446806740
[21] -0.481982504 -0.048123889 0.621890367 1.359837818 -1.379645554
[26] 2.206403396 0.481740067 1.300702070 -0.191027725 -0.615345698
[31] 1.253859693 -0.264731381 0.349581410 -2.451894493 -0.115617572
[36] 0.570107995 1.406379044 0.757389600 2.126709826 -0.206405073
[41] -1.455348899 -1.439538588 -0.913928067 0.266968902 -1.548508700
[46] 1.172678799 1.308559147 -1.986344252 -0.832380281 -1.260202379
[51] -0.344877161 1.695641758 0.126235523 1.569986219 -1.211309128
[56] -0.197309332 0.772516644 -1.160297142 2.065460759 -1.456536681
[61] -0.888322588 1.125707674 -1.427048985 0.403438714 -1.373109421
[66] 0.415443947 -1.113659028 -1.197943142 -0.118976181 0.543606348
[71] -0.548607323 -0.225308206 0.305553130 -0.256367103 0.182897298
[76] -0.649619861 0.368932291 0.208916400 -0.201725263 -0.006629843
[81] 0.354122787 -0.997077504 1.003453955 0.599691973 -0.081075255
[86] 0.817218875 0.229528436 0.382308638 0.199607591 -0.721777808
[91] 0.186545452 1.157918305 0.400522575 -0.402557219 -0.669730066
[96] 0.755119385 1.858928895 0.180381081 -0.151572064 -2.222397890
> colMedians(tmp)
[1] -1.169919549 -0.341340074 -0.492366920 1.022009275 -0.082380027
[6] -0.382840654 1.477847687 -0.318370071 1.014361168 0.045077646
[11] 1.165386867 1.406000266 0.276345268 -1.647247844 -0.215557239
[16] 0.005001830 -0.087594856 -0.064904272 -0.847981775 0.446806740
[21] -0.481982504 -0.048123889 0.621890367 1.359837818 -1.379645554
[26] 2.206403396 0.481740067 1.300702070 -0.191027725 -0.615345698
[31] 1.253859693 -0.264731381 0.349581410 -2.451894493 -0.115617572
[36] 0.570107995 1.406379044 0.757389600 2.126709826 -0.206405073
[41] -1.455348899 -1.439538588 -0.913928067 0.266968902 -1.548508700
[46] 1.172678799 1.308559147 -1.986344252 -0.832380281 -1.260202379
[51] -0.344877161 1.695641758 0.126235523 1.569986219 -1.211309128
[56] -0.197309332 0.772516644 -1.160297142 2.065460759 -1.456536681
[61] -0.888322588 1.125707674 -1.427048985 0.403438714 -1.373109421
[66] 0.415443947 -1.113659028 -1.197943142 -0.118976181 0.543606348
[71] -0.548607323 -0.225308206 0.305553130 -0.256367103 0.182897298
[76] -0.649619861 0.368932291 0.208916400 -0.201725263 -0.006629843
[81] 0.354122787 -0.997077504 1.003453955 0.599691973 -0.081075255
[86] 0.817218875 0.229528436 0.382308638 0.199607591 -0.721777808
[91] 0.186545452 1.157918305 0.400522575 -0.402557219 -0.669730066
[96] 0.755119385 1.858928895 0.180381081 -0.151572064 -2.222397890
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.16992 -0.3413401 -0.4923669 1.022009 -0.08238003 -0.3828407 1.477848
[2,] -1.16992 -0.3413401 -0.4923669 1.022009 -0.08238003 -0.3828407 1.477848
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.3183701 1.014361 0.04507765 1.165387 1.406 0.2763453 -1.647248
[2,] -0.3183701 1.014361 0.04507765 1.165387 1.406 0.2763453 -1.647248
[,15] [,16] [,17] [,18] [,19] [,20]
[1,] -0.2155572 0.00500183 -0.08759486 -0.06490427 -0.8479818 0.4468067
[2,] -0.2155572 0.00500183 -0.08759486 -0.06490427 -0.8479818 0.4468067
[,21] [,22] [,23] [,24] [,25] [,26] [,27]
[1,] -0.4819825 -0.04812389 0.6218904 1.359838 -1.379646 2.206403 0.4817401
[2,] -0.4819825 -0.04812389 0.6218904 1.359838 -1.379646 2.206403 0.4817401
[,28] [,29] [,30] [,31] [,32] [,33] [,34]
[1,] 1.300702 -0.1910277 -0.6153457 1.25386 -0.2647314 0.3495814 -2.451894
[2,] 1.300702 -0.1910277 -0.6153457 1.25386 -0.2647314 0.3495814 -2.451894
[,35] [,36] [,37] [,38] [,39] [,40] [,41]
[1,] -0.1156176 0.570108 1.406379 0.7573896 2.12671 -0.2064051 -1.455349
[2,] -0.1156176 0.570108 1.406379 0.7573896 2.12671 -0.2064051 -1.455349
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] -1.439539 -0.9139281 0.2669689 -1.548509 1.172679 1.308559 -1.986344
[2,] -1.439539 -0.9139281 0.2669689 -1.548509 1.172679 1.308559 -1.986344
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.8323803 -1.260202 -0.3448772 1.695642 0.1262355 1.569986 -1.211309
[2,] -0.8323803 -1.260202 -0.3448772 1.695642 0.1262355 1.569986 -1.211309
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.1973093 0.7725166 -1.160297 2.065461 -1.456537 -0.8883226 1.125708
[2,] -0.1973093 0.7725166 -1.160297 2.065461 -1.456537 -0.8883226 1.125708
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] -1.427049 0.4034387 -1.373109 0.4154439 -1.113659 -1.197943 -0.1189762
[2,] -1.427049 0.4034387 -1.373109 0.4154439 -1.113659 -1.197943 -0.1189762
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 0.5436063 -0.5486073 -0.2253082 0.3055531 -0.2563671 0.1828973 -0.6496199
[2,] 0.5436063 -0.5486073 -0.2253082 0.3055531 -0.2563671 0.1828973 -0.6496199
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] 0.3689323 0.2089164 -0.2017253 -0.006629843 0.3541228 -0.9970775 1.003454
[2,] 0.3689323 0.2089164 -0.2017253 -0.006629843 0.3541228 -0.9970775 1.003454
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 0.599692 -0.08107525 0.8172189 0.2295284 0.3823086 0.1996076 -0.7217778
[2,] 0.599692 -0.08107525 0.8172189 0.2295284 0.3823086 0.1996076 -0.7217778
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 0.1865455 1.157918 0.4005226 -0.4025572 -0.6697301 0.7551194 1.858929
[2,] 0.1865455 1.157918 0.4005226 -0.4025572 -0.6697301 0.7551194 1.858929
[,98] [,99] [,100]
[1,] 0.1803811 -0.1515721 -2.222398
[2,] 0.1803811 -0.1515721 -2.222398
>
>
> Max(tmp2)
[1] 2.385948
> Min(tmp2)
[1] -2.112772
> mean(tmp2)
[1] -0.1655998
> Sum(tmp2)
[1] -16.55998
> Var(tmp2)
[1] 0.9294322
>
> rowMeans(tmp2)
[1] -0.59794939 1.53955261 0.27800466 -0.28802585 2.34257821 0.62683097
[7] 1.24771997 -1.64459283 -1.91040724 0.20748999 0.12598907 -1.93823628
[13] -1.24491324 0.41647201 -1.08328746 -0.71548198 -0.88085899 -1.17059773
[19] -0.82386528 0.93684416 -0.55182937 -0.07842751 -0.71243778 -0.23308123
[25] 0.54845477 -1.86629183 -0.10820660 0.11072822 -0.01370104 -0.71677305
[31] -0.94686909 1.47233944 -1.17236483 -1.18337715 -0.08820305 0.32140085
[37] 1.14979992 -1.05646740 -0.07917257 0.40872605 -0.44892378 -1.29156152
[43] 1.76568393 -0.08045730 0.03163346 -0.99733702 -0.39193556 -0.19031628
[49] -1.34009849 -1.11844156 0.93146764 1.00545135 0.16766027 -0.49582931
[55] -0.05163235 -1.31626094 -0.79292033 0.89789285 1.42423660 -0.93004211
[61] -0.38208852 -0.59745515 0.62485995 -0.06640194 -1.58943490 -0.28356544
[67] -1.51244532 0.84343465 2.38594786 0.92294393 -1.97895302 -0.89978770
[73] 0.37556310 0.78292800 -2.11277226 0.13051901 -0.71692093 -0.17798267
[79] -1.03164732 0.36462023 -0.93972691 0.89499120 -0.44767413 0.04859949
[85] -1.09178703 0.10706784 -1.04046733 0.54718338 0.07332495 0.03143998
[91] -0.79706429 0.29420736 0.44915089 1.00027121 -0.23951566 -0.77804498
[97] 0.61421690 1.38628273 -0.44054130 1.28096561
> rowSums(tmp2)
[1] -0.59794939 1.53955261 0.27800466 -0.28802585 2.34257821 0.62683097
[7] 1.24771997 -1.64459283 -1.91040724 0.20748999 0.12598907 -1.93823628
[13] -1.24491324 0.41647201 -1.08328746 -0.71548198 -0.88085899 -1.17059773
[19] -0.82386528 0.93684416 -0.55182937 -0.07842751 -0.71243778 -0.23308123
[25] 0.54845477 -1.86629183 -0.10820660 0.11072822 -0.01370104 -0.71677305
[31] -0.94686909 1.47233944 -1.17236483 -1.18337715 -0.08820305 0.32140085
[37] 1.14979992 -1.05646740 -0.07917257 0.40872605 -0.44892378 -1.29156152
[43] 1.76568393 -0.08045730 0.03163346 -0.99733702 -0.39193556 -0.19031628
[49] -1.34009849 -1.11844156 0.93146764 1.00545135 0.16766027 -0.49582931
[55] -0.05163235 -1.31626094 -0.79292033 0.89789285 1.42423660 -0.93004211
[61] -0.38208852 -0.59745515 0.62485995 -0.06640194 -1.58943490 -0.28356544
[67] -1.51244532 0.84343465 2.38594786 0.92294393 -1.97895302 -0.89978770
[73] 0.37556310 0.78292800 -2.11277226 0.13051901 -0.71692093 -0.17798267
[79] -1.03164732 0.36462023 -0.93972691 0.89499120 -0.44767413 0.04859949
[85] -1.09178703 0.10706784 -1.04046733 0.54718338 0.07332495 0.03143998
[91] -0.79706429 0.29420736 0.44915089 1.00027121 -0.23951566 -0.77804498
[97] 0.61421690 1.38628273 -0.44054130 1.28096561
> 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] -0.59794939 1.53955261 0.27800466 -0.28802585 2.34257821 0.62683097
[7] 1.24771997 -1.64459283 -1.91040724 0.20748999 0.12598907 -1.93823628
[13] -1.24491324 0.41647201 -1.08328746 -0.71548198 -0.88085899 -1.17059773
[19] -0.82386528 0.93684416 -0.55182937 -0.07842751 -0.71243778 -0.23308123
[25] 0.54845477 -1.86629183 -0.10820660 0.11072822 -0.01370104 -0.71677305
[31] -0.94686909 1.47233944 -1.17236483 -1.18337715 -0.08820305 0.32140085
[37] 1.14979992 -1.05646740 -0.07917257 0.40872605 -0.44892378 -1.29156152
[43] 1.76568393 -0.08045730 0.03163346 -0.99733702 -0.39193556 -0.19031628
[49] -1.34009849 -1.11844156 0.93146764 1.00545135 0.16766027 -0.49582931
[55] -0.05163235 -1.31626094 -0.79292033 0.89789285 1.42423660 -0.93004211
[61] -0.38208852 -0.59745515 0.62485995 -0.06640194 -1.58943490 -0.28356544
[67] -1.51244532 0.84343465 2.38594786 0.92294393 -1.97895302 -0.89978770
[73] 0.37556310 0.78292800 -2.11277226 0.13051901 -0.71692093 -0.17798267
[79] -1.03164732 0.36462023 -0.93972691 0.89499120 -0.44767413 0.04859949
[85] -1.09178703 0.10706784 -1.04046733 0.54718338 0.07332495 0.03143998
[91] -0.79706429 0.29420736 0.44915089 1.00027121 -0.23951566 -0.77804498
[97] 0.61421690 1.38628273 -0.44054130 1.28096561
> rowMin(tmp2)
[1] -0.59794939 1.53955261 0.27800466 -0.28802585 2.34257821 0.62683097
[7] 1.24771997 -1.64459283 -1.91040724 0.20748999 0.12598907 -1.93823628
[13] -1.24491324 0.41647201 -1.08328746 -0.71548198 -0.88085899 -1.17059773
[19] -0.82386528 0.93684416 -0.55182937 -0.07842751 -0.71243778 -0.23308123
[25] 0.54845477 -1.86629183 -0.10820660 0.11072822 -0.01370104 -0.71677305
[31] -0.94686909 1.47233944 -1.17236483 -1.18337715 -0.08820305 0.32140085
[37] 1.14979992 -1.05646740 -0.07917257 0.40872605 -0.44892378 -1.29156152
[43] 1.76568393 -0.08045730 0.03163346 -0.99733702 -0.39193556 -0.19031628
[49] -1.34009849 -1.11844156 0.93146764 1.00545135 0.16766027 -0.49582931
[55] -0.05163235 -1.31626094 -0.79292033 0.89789285 1.42423660 -0.93004211
[61] -0.38208852 -0.59745515 0.62485995 -0.06640194 -1.58943490 -0.28356544
[67] -1.51244532 0.84343465 2.38594786 0.92294393 -1.97895302 -0.89978770
[73] 0.37556310 0.78292800 -2.11277226 0.13051901 -0.71692093 -0.17798267
[79] -1.03164732 0.36462023 -0.93972691 0.89499120 -0.44767413 0.04859949
[85] -1.09178703 0.10706784 -1.04046733 0.54718338 0.07332495 0.03143998
[91] -0.79706429 0.29420736 0.44915089 1.00027121 -0.23951566 -0.77804498
[97] 0.61421690 1.38628273 -0.44054130 1.28096561
>
> colMeans(tmp2)
[1] -0.1655998
> colSums(tmp2)
[1] -16.55998
> colVars(tmp2)
[1] 0.9294322
> colSd(tmp2)
[1] 0.9640707
> colMax(tmp2)
[1] 2.385948
> colMin(tmp2)
[1] -2.112772
> colMedians(tmp2)
[1] -0.1430946
> colRanges(tmp2)
[,1]
[1,] -2.112772
[2,] 2.385948
>
> 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] 4.6582200 -3.0734560 0.8213564 1.0309270 5.9505403 -0.9618034
[7] 0.6780877 2.6353436 -3.6087822 2.3620454
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.3770892
[2,] -0.2416668
[3,] 0.4389835
[4,] 1.5626658
[5,] 2.4405062
>
> rowApply(tmp,sum)
[1] 1.9169413 -1.9156911 4.3191585 5.0948223 1.1262070 -1.8638457
[7] 2.4359750 -0.9354202 4.4888933 -4.1745618
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 4 9 10 6 10 9 2 7 8
[2,] 8 6 4 1 3 4 6 6 6 5
[3,] 10 9 8 3 7 3 3 5 2 3
[4,] 2 7 1 8 1 9 7 7 8 10
[5,] 7 3 10 2 5 5 10 8 10 6
[6,] 5 5 2 6 2 8 1 9 5 4
[7,] 6 8 3 4 4 7 5 4 3 9
[8,] 9 2 7 9 10 2 8 3 4 7
[9,] 3 10 5 5 8 1 2 1 1 1
[10,] 4 1 6 7 9 6 4 10 9 2
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 3.20717197 -1.30192758 1.08032075 3.18780313 -3.12184395 1.67064379
[7] -0.54916666 1.04225624 -3.52404228 -1.48779868 -0.04328124 -0.95427222
[13] -3.80496584 -1.71778197 5.04377548 -2.81367604 3.63167025 -0.96046483
[19] -0.62236232 -2.03572497
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.01803677
[2,] 0.28955718
[3,] 0.48809724
[4,] 0.84334956
[5,] 1.60420476
>
> rowApply(tmp,sum)
[1] 2.0557076 4.2556187 -0.1359141 -6.2569718 -3.9921074
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 17 19 15 14 13
[2,] 7 16 7 7 3
[3,] 16 3 2 20 15
[4,] 19 6 14 18 16
[5,] 14 4 4 4 9
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.84334956 -0.1012484 0.6419776 1.2817558 0.4047143 1.27554311
[2,] 1.60420476 1.4385017 -0.8118483 -0.5546013 -0.6950151 1.48885042
[3,] 0.48809724 -0.5017333 -1.1733563 0.3920515 -0.7601767 0.08464321
[4,] 0.28955718 -1.0134826 1.8938010 1.4665463 -1.7044186 1.30236826
[5,] -0.01803677 -1.1239650 0.5297468 0.6020509 -0.3669478 -2.48076122
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.5824666 1.5506772 0.1706306 -0.6589263 0.14889808 -0.03565131
[2,] 0.7880884 -1.0029577 -0.9988331 -0.3063652 -0.14770131 -0.41537349
[3,] 1.0479237 0.3186264 -2.4715665 0.5044325 0.01235355 -0.47779707
[4,] -2.1687959 -0.4531702 0.3290240 -0.4118162 -1.78492100 -0.42671594
[5,] -0.7988494 0.6290805 -0.5532973 -0.6151235 1.72808944 0.40126559
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.2287952 -0.02538186 -0.02748165 -1.7076662 0.004402858 -0.3059508
[2,] 0.1999495 -0.61220665 2.04089501 -0.5035280 0.579243206 1.5979952
[3,] -1.0270037 1.08044893 1.66357449 -0.4072075 1.904107911 -0.5410546
[4,] -1.4494698 -2.93876117 0.58082465 0.2209833 1.509605939 -0.2514510
[5,] -0.2996465 0.77811878 0.78596298 -0.4162576 -0.365689669 -1.4600036
[,19] [,20]
[1,] -0.57097572 -0.1866306
[2,] 0.39030185 0.1760190
[3,] 0.36610346 -0.6383812
[4,] -0.02344321 -1.2232370
[5,] -0.78434870 -0.1634952
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.19-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-3.19-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-3.19-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-3.19-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 -0.4370343 -1.898285 0.1826253 -1.386301 -1.247755 1.06206 1.053516
col8 col9 col10 col11 col12 col13 col14
row1 -1.526789 0.01910348 2.873342 -0.6180586 0.6938238 -0.157587 -1.175463
col15 col16 col17 col18 col19 col20
row1 1.104128 0.7799782 0.1622106 0.009006303 0.4425133 -0.8292366
> tmp[,"col10"]
col10
row1 2.8733424
row2 -0.3970679
row3 -2.3776688
row4 0.1499388
row5 0.2898531
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.4370343 -1.898285 0.1826253 -1.3863010 -1.247755 1.06206 1.053516
row5 0.7852470 1.060454 0.2654473 -0.4486266 -1.563926 1.85349 -1.769620
col8 col9 col10 col11 col12 col13
row1 -1.5267888 0.01910348 2.8733424 -0.6180586 0.6938238 -0.1575870
row5 -0.6813992 -0.19329616 0.2898531 -0.2224912 0.6904898 -0.3856849
col14 col15 col16 col17 col18 col19
row1 -1.1754631 1.1041279 0.7799782 0.16221057 0.009006303 0.4425133
row5 0.0586333 0.3138147 -0.8662359 -0.03797018 -0.081854091 -0.9930434
col20
row1 -0.8292366
row5 -0.4666902
> tmp[,c("col6","col20")]
col6 col20
row1 1.0620597 -0.8292366
row2 0.1517996 2.1608600
row3 0.1286769 -0.7561271
row4 0.4737659 -1.0355725
row5 1.8534899 -0.4666902
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.06206 -0.8292366
row5 1.85349 -0.4666902
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.92574 51.54228 50.47893 50.44222 49.57576 107.626 50.55046 50.89434
col9 col10 col11 col12 col13 col14 col15 col16
row1 52.78416 48.66321 49.21742 50.59519 50.78542 50.69081 49.09691 49.74975
col17 col18 col19 col20
row1 50.97983 50.46156 49.47069 105.419
> tmp[,"col10"]
col10
row1 48.66321
row2 29.96677
row3 30.93988
row4 30.60727
row5 51.82700
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.92574 51.54228 50.47893 50.44222 49.57576 107.6260 50.55046 50.89434
row5 50.05363 50.63734 47.53169 48.15534 50.62953 105.9003 49.69409 49.46175
col9 col10 col11 col12 col13 col14 col15 col16
row1 52.78416 48.66321 49.21742 50.59519 50.78542 50.69081 49.09691 49.74975
row5 50.44408 51.82700 50.31481 50.33563 50.20971 50.84778 49.68222 50.59911
col17 col18 col19 col20
row1 50.97983 50.46156 49.47069 105.4190
row5 49.80117 49.36975 49.37038 106.2423
> tmp[,c("col6","col20")]
col6 col20
row1 107.62595 105.41896
row2 75.19137 75.10166
row3 75.62388 75.89875
row4 74.42448 76.50841
row5 105.90031 106.24234
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 107.6260 105.4190
row5 105.9003 106.2423
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 107.6260 105.4190
row5 105.9003 106.2423
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.5819391
[2,] 1.1824274
[3,] -1.1495611
[4,] -0.6229201
[5,] -0.4978991
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.74232819 0.2422719
[2,] -0.61974033 0.5633050
[3,] 1.58290117 -0.7960525
[4,] -0.02000313 0.9676056
[5,] 0.31144681 -0.3347164
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.45078544 -0.95514193
[2,] -0.32879470 0.39102423
[3,] 0.09815759 -0.07802455
[4,] 0.14109477 0.91171278
[5,] 0.58085323 -1.56256829
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.450785
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.4507854
[2,] -0.3287947
>
>
>
> 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 1.8131682 0.04853101 -0.6503088 0.2788511 0.68724867 -0.1480857
row1 -0.9071228 0.23342508 -0.3083675 -0.5441631 -0.08843278 -1.5527019
[,7] [,8] [,9] [,10] [,11] [,12]
row3 0.2362562 0.1690005 -2.5709156 -0.1068235 -0.8613681 1.2366956
row1 0.6804388 -0.8250977 0.3855747 0.1937885 1.4425332 -0.5979821
[,13] [,14] [,15] [,16] [,17] [,18]
row3 0.1337328 0.8494334 -1.0523348 -0.8062992 0.6006338 0.06405658
row1 -1.3669427 1.4110730 0.1280311 1.0983285 -0.9535008 -1.20290556
[,19] [,20]
row3 -2.8297559 0.5755643
row1 -0.2971016 -0.1866976
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.8333021 -0.07015597 -1.797444 -0.03798448 2.047034 -0.6253627 -1.609031
[,8] [,9] [,10]
row2 -0.647348 -0.5100416 0.8638067
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -1.830635 -2.145529 0.7282279 -0.1504023 0.8822051 0.8494639 -0.9740297
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.7651173 0.2100739 -0.03974964 -0.4820016 1.536457 1.502017 -1.35937
[,15] [,16] [,17] [,18] [,19] [,20]
row5 2.071295 -0.3794626 0.6264607 0.7577379 -0.4618007 1.946601
>
>
> 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: 0x600003ada100>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM83e1141b3d9f"
[2] "/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM83e186a9c09"
[3] "/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM83e1f2a1730"
[4] "/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM83e114585817"
[5] "/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM83e133ff5870"
[6] "/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM83e141073bbb"
[7] "/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM83e141e29357"
[8] "/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM83e1237568c"
[9] "/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM83e17f130276"
[10] "/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM83e13906d227"
[11] "/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM83e16ecf1bb0"
[12] "/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM83e15f22f8a5"
[13] "/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM83e170f2496e"
[14] "/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM83e132b30eb0"
[15] "/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests/BM83e19895ed1"
>
>
> ### 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: 0x600003ac8720>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600003ac8720>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600003ac8720>
> rowMedians(tmp)
[1] -0.411395433 0.072153975 -0.008155704 0.213410426 0.315482953
[6] -0.401733117 -0.115167274 -0.158903677 -0.137660916 -0.184300443
[11] -0.068286385 0.552280133 -0.013430630 0.011304412 -0.203666676
[16] -0.201976888 0.462335329 -0.703638815 -0.524844475 -0.536807783
[21] -0.276769270 0.515591691 -0.287636001 -0.276504406 0.043613736
[26] -0.758093813 -0.125963178 0.120219873 0.356098520 -0.319064738
[31] 0.221585049 0.363986039 -0.172085431 0.008823142 0.531209045
[36] 0.295134259 -0.021385870 0.100462232 0.441365996 -0.114410854
[41] -0.042603464 -0.005316359 -0.197776947 -0.310120435 0.265491821
[46] -0.539740633 -0.017953384 0.035009416 0.167403770 0.079759484
[51] -0.353371892 0.046756332 0.617938667 -0.045986769 0.239345384
[56] -0.048103579 0.262282899 0.285598769 -0.558104648 0.110826785
[61] -0.274706009 0.157490519 -0.205491375 0.216300097 0.349059524
[66] 0.276692267 0.442943552 0.443126187 0.486252054 0.592425306
[71] 0.456315111 0.484413081 0.018880851 -0.198311950 0.379592488
[76] -0.410410479 0.374190120 0.041803969 0.480767486 -0.058004538
[81] 0.052131588 0.310884453 0.115834534 -0.110582944 0.142047518
[86] -0.355408602 0.218094790 0.540466256 0.031128553 0.174929837
[91] -0.045950452 -0.459735463 -0.057900609 -0.153438834 0.493781715
[96] -0.439478068 0.212109618 0.401043941 0.035325947 0.050544766
[101] -0.805471000 0.331352885 0.395518165 -0.678231749 0.255824650
[106] 0.463311536 0.016260920 -0.276114821 0.002887415 0.279284321
[111] 0.023890835 0.097920231 -0.161947283 0.349412697 0.481316327
[116] 0.102800232 0.406297933 0.009794933 0.140863558 -0.237915465
[121] -0.160113661 -0.377619697 -0.197434608 -0.172428317 0.202572394
[126] -0.417470972 -0.194575985 -0.046501539 -0.100027391 -0.943144999
[131] -0.627325213 0.096228694 0.435651970 -0.274182830 0.453850403
[136] -0.005115961 -0.196267514 0.387147115 0.169731338 0.303322283
[141] 0.159602565 0.159401687 0.041007343 0.073240013 -0.436486126
[146] 0.626317261 0.203931973 0.094148406 0.009070218 -0.345607986
[151] 0.201744189 0.445484484 -0.213201477 0.043409790 0.261339092
[156] 0.046405151 -0.308583811 0.050599636 -0.056225121 -0.450510649
[161] 0.221036919 0.277669011 -0.651436891 0.527483421 -0.380360187
[166] 0.084531278 0.276943436 0.391309686 -0.148723063 -0.103340907
[171] -0.374212579 0.448405486 0.141448096 -0.024222020 0.006368959
[176] 0.475791751 0.391088203 -0.071542401 -0.492804143 -0.334413769
[181] -0.170842003 0.005739075 0.618814189 0.241213169 0.103298109
[186] 0.137691873 -0.465601755 0.308875363 -0.170647571 -0.019692516
[191] 0.584757209 0.670796308 -0.282511257 -0.145781907 -0.312871295
[196] 0.110506293 0.100395934 -0.145578210 -0.147551298 0.427334099
[201] 0.157238459 -0.167934451 -0.059083260 -0.288790493 -0.544889120
[206] 0.209453868 -0.055839337 -0.022845214 -0.343539940 -0.046261199
[211] 0.353036340 0.400893434 -0.230620946 -0.331067290 -0.105392045
[216] -0.638443800 -0.216426915 0.097391220 0.057629031 -0.171670193
[221] -0.457021416 -0.327077714 0.070434148 -0.539780713 0.141404246
[226] 0.037666256 -0.113328171 -0.084017255 -0.554920933 0.213077784
>
> proc.time()
user system elapsed
0.589 2.587 3.201
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: 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: 0x6000025f4000>
> .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: 0x6000025f4000>
> .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: 0x6000025f4000>
> .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: 0x6000025f4000>
> 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: 0x6000025f4780>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000025f4780>
> .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: 0x6000025f4780>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000025f4780>
> .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: 0x6000025f4780>
> 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: 0x6000025f4960>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000025f4960>
> .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: 0x6000025f4960>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000025f4960>
> .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: 0x6000025f4960>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000025f4960>
> .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: 0x6000025f4960>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000025f4960>
> .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: 0x6000025f4960>
> 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: 0x6000025f4b40>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000025f4b40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000025f4b40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000025f4b40>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile84523264d41" "BufferedMatrixFile84524799e804"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile84523264d41" "BufferedMatrixFile84524799e804"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000025f4c60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000025f4c60>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000025f4c60>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000025f4c60>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000025f4c60>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000025f4c60>
> .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: 0x6000025f4e40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000025f4e40>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000025f4e40>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000025f4e40>
> 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: 0x6000025f5020>
> .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: 0x6000025f5020>
> rm(P)
>
> proc.time()
user system elapsed
0.114 0.034 0.145
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
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Type 'demo()' for some demos, 'help()' for on-line help, or
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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
0.115 0.024 0.136