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This page was generated on 2024-03-04 11:38:56 -0500 (Mon, 04 Mar 2024).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 22.04.3 LTS)x86_64R Under development (unstable) (2024-01-16 r85808) -- "Unsuffered Consequences" 4676
palomino3Windows Server 2022 Datacenterx64R Under development (unstable) (2024-01-14 r85805 ucrt) -- "Unsuffered Consequences" 4414
merida1macOS 12.7.1 Montereyx86_64R Under development (unstable) (2024-01-16 r85808) -- "Unsuffered Consequences" 4441
kunpeng2Linux (openEuler 22.03 LTS-SP1)aarch64R Under development (unstable) (2024-01-16 r85812) -- "Unsuffered Consequences" 4417
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 246/2251HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
BufferedMatrix 1.67.0  (landing page)
Ben Bolstad
Snapshot Date: 2024-03-01 14:00:22 -0500 (Fri, 01 Mar 2024)
git_url: https://git.bioconductor.org/packages/BufferedMatrix
git_branch: devel
git_last_commit: 9250806
git_last_commit_date: 2023-10-24 09:37:50 -0500 (Tue, 24 Oct 2023)
nebbiolo1Linux (Ubuntu 22.04.3 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino3Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
merida1macOS 12.7.1 Monterey / x86_64  OK    OK    WARNINGS    OK  UNNEEDED, same version is already published
kunpeng2Linux (openEuler 22.03 LTS-SP1) / aarch64  OK    OK    OK  

CHECK results for BufferedMatrix on merida1


To the developers/maintainers of the BufferedMatrix package:
- Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information.
- Use the following Renviron settings to reproduce errors and warnings.
- 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.

raw results


Summary

Package: BufferedMatrix
Version: 1.67.0
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_1.67.0.tar.gz
StartedAt: 2024-03-02 01:07:00 -0500 (Sat, 02 Mar 2024)
EndedAt: 2024-03-02 01:08:18 -0500 (Sat, 02 Mar 2024)
EllapsedTime: 78.0 seconds
RetCode: 0
Status:   WARNINGS  
CheckDir: BufferedMatrix.Rcheck
Warnings: 1

Command output

##############################################################################
##############################################################################
###
### 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_1.67.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck’
* using R Under development (unstable) (2024-01-16 r85808)
* using platform: x86_64-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 Monterey 12.7.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.67.0’
* 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/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 ... 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/meat/BufferedMatrix.Rcheck/00check.log’
for details.



Installation output

BufferedMatrix.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-x86_64/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 x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/x86_64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/x86_64/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 x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/x86_64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/x86_64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c init_package.c -o init_package.o
clang -arch x86_64 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/x86_64/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-x86_64/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)

Tests output

BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout


R Under development (unstable) (2024-01-16 r85808) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-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 
  0.587   0.201   0.843 

BufferedMatrix.Rcheck/tests/objectTesting.Rout


R Under development (unstable) (2024-01-16 r85808) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-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/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 473445 25.3    1033281 55.2         NA   638837 34.2
Vcells 877115  6.7    8388608 64.0      65536  2074449 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] "Sat Mar  2 01:07:34 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] "Sat Mar  2 01:07:35 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: 0x6000011c4000>
> 
> 
> 
> 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] "Sat Mar  2 01:07:42 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] "Sat Mar  2 01:07:44 2024"
> 
> ColMode(tmp2)
<pointer: 0x6000011c4000>
> 
> 
> 
> ### 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,] 99.43287635  0.5753648  0.6141713 -0.644356294
[2,] -0.04169401  0.6370478  0.1347006  0.327916953
[3,]  0.69152828  0.7694964 -0.9608797 -0.405427930
[4,]  0.21831527 -0.3034190  0.7262757  0.007158516
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
            [,1]      [,2]      [,3]        [,4]
[1,] 99.43287635 0.5753648 0.6141713 0.644356294
[2,]  0.04169401 0.6370478 0.1347006 0.327916953
[3,]  0.69152828 0.7694964 0.9608797 0.405427930
[4,]  0.21831527 0.3034190 0.7262757 0.007158516
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]      [,2]      [,3]       [,4]
[1,] 9.9716035 0.7585281 0.7836908 0.80271807
[2,] 0.2041911 0.7981528 0.3670157 0.57264033
[3,] 0.8315818 0.8772094 0.9802447 0.63673223
[4,] 0.4672422 0.5508348 0.8522181 0.08460801
> 
> 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/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]     [,2]     [,3]     [,4]
[1,] 224.14891 33.16065 33.45108 33.67154
[2,]  27.08360 33.61858 28.80486 31.05432
[3,]  34.00735 34.54159 35.76333 31.77275
[4,]  29.89074 30.81177 34.24846 25.85324
> 
> 
> 
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000011c0000>
> exp(tmp5)
<pointer: 0x6000011c0000>
> log(tmp5,2)
<pointer: 0x6000011c0000>
> pow(tmp5,2)
> 
> 
> 
> 
> 
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.5366
> Min(tmp5)
[1] 53.81013
> mean(tmp5)
[1] 72.944
> Sum(tmp5)
[1] 14588.8
> Var(tmp5)
[1] 855.291
> 
> 
> ## testing functions applied to rows or columns
> 
> rowMeans(tmp5)
 [1] 91.32434 67.40045 73.59269 73.47786 68.88862 75.12386 70.18941 69.97771
 [9] 66.80619 72.65888
> rowSums(tmp5)
 [1] 1826.487 1348.009 1471.854 1469.557 1377.772 1502.477 1403.788 1399.554
 [9] 1336.124 1453.178
> rowVars(tmp5)
 [1] 7868.72487   77.00056   62.30232   68.60414   68.49157   67.76248
 [7]   94.31948   89.83727   28.78359   64.20923
> rowSd(tmp5)
 [1] 88.705833  8.774996  7.893182  8.282762  8.275963  8.231797  9.711822
 [8]  9.478253  5.365034  8.013066
> rowMax(tmp5)
 [1] 466.53659  84.45766  94.15413  89.63945  84.09276  87.00800  88.70769
 [8]  84.73782  75.11542  87.82724
> rowMin(tmp5)
 [1] 54.41540 55.27059 60.65479 53.81013 57.05038 59.71039 55.29901 55.60621
 [9] 57.98393 55.23337
> 
> colMeans(tmp5)
 [1] 107.14878  69.55127  68.14688  67.64191  70.11734  68.96988  69.14134
 [8]  72.97916  71.14066  71.66205  72.91632  68.60121  69.06428  75.37078
[15]  69.84991  70.80281  76.16655  70.94789  73.35049  75.31049
> colSums(tmp5)
 [1] 1071.4878  695.5127  681.4688  676.4191  701.1734  689.6988  691.4134
 [8]  729.7916  711.4066  716.6205  729.1632  686.0121  690.6428  753.7078
[15]  698.4991  708.0281  761.6655  709.4789  733.5049  753.1049
> colVars(tmp5)
 [1] 15994.92820    41.30486    50.37790    39.25805    90.00877    36.38038
 [7]    43.25179    44.40501   126.52238   136.94801   110.18995    86.26192
[13]    77.41667    48.99530    86.16195    75.32368   156.68383    28.15874
[19]    38.81361   100.22498
> colSd(tmp5)
 [1] 126.471057   6.426885   7.097739   6.265624   9.487295   6.031615
 [7]   6.576609   6.663708  11.248217  11.702479  10.497140   9.287730
[13]   8.798675   6.999664   9.282346   8.678922  12.517341   5.306481
[19]   6.230057  10.011242
> colMax(tmp5)
 [1] 466.53659  82.91523  80.87205  76.09950  86.46156  75.99795  77.04796
 [8]  84.02295  86.24110  89.63945  94.15413  81.74890  83.37078  88.70769
[15]  84.73782  82.40164  90.45871  80.40080  81.93003  85.70632
> colMin(tmp5)
 [1] 56.37098 57.98393 56.84940 53.81013 59.09057 57.94622 56.06745 62.61503
 [9] 55.23337 55.27059 59.71039 55.29901 54.41540 65.38584 57.34511 56.13617
[17] 56.78650 62.68037 61.73702 57.31737
> 
> 
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
> 
> 
> which.row <- sample(1:10,1,replace=TRUE)
> which.col  <- sample(1:20,1,replace=TRUE)
> 
> tmp5[which.row,which.col] <- NA
> 
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
> 
> rowMeans(tmp5)
 [1] 91.32434 67.40045 73.59269 73.47786 68.88862 75.12386 70.18941 69.97771
 [9] 66.80619       NA
> rowSums(tmp5)
 [1] 1826.487 1348.009 1471.854 1469.557 1377.772 1502.477 1403.788 1399.554
 [9] 1336.124       NA
> rowVars(tmp5)
 [1] 7868.72487   77.00056   62.30232   68.60414   68.49157   67.76248
 [7]   94.31948   89.83727   28.78359   66.96202
> rowSd(tmp5)
 [1] 88.705833  8.774996  7.893182  8.282762  8.275963  8.231797  9.711822
 [8]  9.478253  5.365034  8.183032
> rowMax(tmp5)
 [1] 466.53659  84.45766  94.15413  89.63945  84.09276  87.00800  88.70769
 [8]  84.73782  75.11542        NA
> rowMin(tmp5)
 [1] 54.41540 55.27059 60.65479 53.81013 57.05038 59.71039 55.29901 55.60621
 [9] 57.98393       NA
> 
> colMeans(tmp5)
 [1] 107.14878  69.55127  68.14688  67.64191  70.11734  68.96988  69.14134
 [8]  72.97916  71.14066        NA  72.91632  68.60121  69.06428  75.37078
[15]  69.84991  70.80281  76.16655  70.94789  73.35049  75.31049
> colSums(tmp5)
 [1] 1071.4878  695.5127  681.4688  676.4191  701.1734  689.6988  691.4134
 [8]  729.7916  711.4066        NA  729.1632  686.0121  690.6428  753.7078
[15]  698.4991  708.0281  761.6655  709.4789  733.5049  753.1049
> colVars(tmp5)
 [1] 15994.92820    41.30486    50.37790    39.25805    90.00877    36.38038
 [7]    43.25179    44.40501   126.52238          NA   110.18995    86.26192
[13]    77.41667    48.99530    86.16195    75.32368   156.68383    28.15874
[19]    38.81361   100.22498
> colSd(tmp5)
 [1] 126.471057   6.426885   7.097739   6.265624   9.487295   6.031615
 [7]   6.576609   6.663708  11.248217         NA  10.497140   9.287730
[13]   8.798675   6.999664   9.282346   8.678922  12.517341   5.306481
[19]   6.230057  10.011242
> colMax(tmp5)
 [1] 466.53659  82.91523  80.87205  76.09950  86.46156  75.99795  77.04796
 [8]  84.02295  86.24110        NA  94.15413  81.74890  83.37078  88.70769
[15]  84.73782  82.40164  90.45871  80.40080  81.93003  85.70632
> colMin(tmp5)
 [1] 56.37098 57.98393 56.84940 53.81013 59.09057 57.94622 56.06745 62.61503
 [9] 55.23337       NA 59.71039 55.29901 54.41540 65.38584 57.34511 56.13617
[17] 56.78650 62.68037 61.73702 57.31737
> 
> Max(tmp5,na.rm=TRUE)
[1] 466.5366
> Min(tmp5,na.rm=TRUE)
[1] 53.81013
> mean(tmp5,na.rm=TRUE)
[1] 72.92668
> Sum(tmp5,na.rm=TRUE)
[1] 14512.41
> Var(tmp5,na.rm=TRUE)
[1] 859.5504
> 
> rowMeans(tmp5,na.rm=TRUE)
 [1] 91.32434 67.40045 73.59269 73.47786 68.88862 75.12386 70.18941 69.97771
 [9] 66.80619 72.46247
> rowSums(tmp5,na.rm=TRUE)
 [1] 1826.487 1348.009 1471.854 1469.557 1377.772 1502.477 1403.788 1399.554
 [9] 1336.124 1376.787
> rowVars(tmp5,na.rm=TRUE)
 [1] 7868.72487   77.00056   62.30232   68.60414   68.49157   67.76248
 [7]   94.31948   89.83727   28.78359   66.96202
> rowSd(tmp5,na.rm=TRUE)
 [1] 88.705833  8.774996  7.893182  8.282762  8.275963  8.231797  9.711822
 [8]  9.478253  5.365034  8.183032
> rowMax(tmp5,na.rm=TRUE)
 [1] 466.53659  84.45766  94.15413  89.63945  84.09276  87.00800  88.70769
 [8]  84.73782  75.11542  87.82724
> rowMin(tmp5,na.rm=TRUE)
 [1] 54.41540 55.27059 60.65479 53.81013 57.05038 59.71039 55.29901 55.60621
 [9] 57.98393 55.23337
> 
> colMeans(tmp5,na.rm=TRUE)
 [1] 107.14878  69.55127  68.14688  67.64191  70.11734  68.96988  69.14134
 [8]  72.97916  71.14066  71.13665  72.91632  68.60121  69.06428  75.37078
[15]  69.84991  70.80281  76.16655  70.94789  73.35049  75.31049
> colSums(tmp5,na.rm=TRUE)
 [1] 1071.4878  695.5127  681.4688  676.4191  701.1734  689.6988  691.4134
 [8]  729.7916  711.4066  640.2299  729.1632  686.0121  690.6428  753.7078
[15]  698.4991  708.0281  761.6655  709.4789  733.5049  753.1049
> colVars(tmp5,na.rm=TRUE)
 [1] 15994.92820    41.30486    50.37790    39.25805    90.00877    36.38038
 [7]    43.25179    44.40501   126.52238   150.96101   110.18995    86.26192
[13]    77.41667    48.99530    86.16195    75.32368   156.68383    28.15874
[19]    38.81361   100.22498
> colSd(tmp5,na.rm=TRUE)
 [1] 126.471057   6.426885   7.097739   6.265624   9.487295   6.031615
 [7]   6.576609   6.663708  11.248217  12.286619  10.497140   9.287730
[13]   8.798675   6.999664   9.282346   8.678922  12.517341   5.306481
[19]   6.230057  10.011242
> colMax(tmp5,na.rm=TRUE)
 [1] 466.53659  82.91523  80.87205  76.09950  86.46156  75.99795  77.04796
 [8]  84.02295  86.24110  89.63945  94.15413  81.74890  83.37078  88.70769
[15]  84.73782  82.40164  90.45871  80.40080  81.93003  85.70632
> colMin(tmp5,na.rm=TRUE)
 [1] 56.37098 57.98393 56.84940 53.81013 59.09057 57.94622 56.06745 62.61503
 [9] 55.23337 55.27059 59.71039 55.29901 54.41540 65.38584 57.34511 56.13617
[17] 56.78650 62.68037 61.73702 57.31737
> 
> # now set an entire row to NA
> 
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
 [1] 91.32434 67.40045 73.59269 73.47786 68.88862 75.12386 70.18941 69.97771
 [9] 66.80619      NaN
> rowSums(tmp5,na.rm=TRUE)
 [1] 1826.487 1348.009 1471.854 1469.557 1377.772 1502.477 1403.788 1399.554
 [9] 1336.124    0.000
> rowVars(tmp5,na.rm=TRUE)
 [1] 7868.72487   77.00056   62.30232   68.60414   68.49157   67.76248
 [7]   94.31948   89.83727   28.78359         NA
> rowSd(tmp5,na.rm=TRUE)
 [1] 88.705833  8.774996  7.893182  8.282762  8.275963  8.231797  9.711822
 [8]  9.478253  5.365034        NA
> rowMax(tmp5,na.rm=TRUE)
 [1] 466.53659  84.45766  94.15413  89.63945  84.09276  87.00800  88.70769
 [8]  84.73782  75.11542        NA
> rowMin(tmp5,na.rm=TRUE)
 [1] 54.41540 55.27059 60.65479 53.81013 57.05038 59.71039 55.29901 55.60621
 [9] 57.98393       NA
> 
> 
> # now set an entire col to NA
> 
> 
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
 [1] 111.01763  69.74560  66.73298  67.00077  70.59187  68.69590  68.70222
 [8]  72.93281  72.90814       NaN  72.44948  68.88932  68.24634  74.74292
[15]  70.02331  72.43244  74.87092  70.53452  72.39721  75.46257
> colSums(tmp5,na.rm=TRUE)
 [1] 999.1587 627.7104 600.5968 603.0069 635.3268 618.2631 618.3200 656.3953
 [9] 656.1733   0.0000 652.0453 620.0038 614.2171 672.6863 630.2098 651.8919
[17] 673.8383 634.8107 651.5748 679.1631
> colVars(tmp5,na.rm=TRUE)
 [1] 17825.90393    46.04314    34.18488    39.54093    98.72658    40.08348
 [7]    46.48897    49.93146   107.19297          NA   121.51185    96.11087
[13]    79.56736    50.68492    96.59391    54.86270   157.38435    29.75626
[19]    33.44190   112.49292
> colSd(tmp5,na.rm=TRUE)
 [1] 133.513684   6.785510   5.846784   6.288158   9.936125   6.331152
 [7]   6.818282   7.066220  10.353404         NA  11.023241   9.803615
[13]   8.920054   7.119334   9.828220   7.406936  12.545292   5.454930
[19]   5.782897  10.606268
> colMax(tmp5,na.rm=TRUE)
 [1] 466.53659  82.91523  74.43668  76.09950  86.46156  75.99795  77.04796
 [8]  84.02295  86.24110      -Inf  94.15413  81.74890  83.37078  88.70769
[15]  84.73782  82.40164  90.45871  80.40080  79.31674  85.70632
> colMin(tmp5,na.rm=TRUE)
 [1] 56.37098 57.98393 56.84940 53.81013 59.09057 57.94622 56.06745 62.61503
 [9] 57.05038      Inf 59.71039 55.29901 54.41540 65.38584 57.34511 61.45934
[17] 56.78650 62.68037 61.73702 57.31737
> 
> 
> 
> 
> 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] 323.7676 328.2628 210.2415 166.6495 151.8955 252.0184 237.1729 156.6495
 [9] 245.4650 323.4996
> apply(copymatrix,1,var,na.rm=TRUE)
 [1] 323.7676 328.2628 210.2415 166.6495 151.8955 252.0184 237.1729 156.6495
 [9] 245.4650 323.4996
> 
> 
> 
> copymatrix <- matrix(rnorm(200,150,15),10,20)
> 
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col  <- 3
> cat(which.row," ",which.col,"\n")
1   3 
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
> 
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
 [1]  5.684342e-14  5.684342e-14 -5.684342e-14  1.705303e-13 -1.421085e-14
 [6]  2.273737e-13  1.136868e-13  0.000000e+00  0.000000e+00  5.684342e-14
[11] -1.705303e-13  1.136868e-13  1.421085e-14  2.842171e-14  0.000000e+00
[16]  5.684342e-14  1.705303e-13 -2.273737e-13 -2.842171e-14  5.684342e-14
> 
> 
> 
> 
> 
> 
> 
> 
> 
> 
> ## making sure these things agree
> ##
> ## first when there is no NA
> 
> 
> 
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+ 
+   if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+     stop("No agreement in Max")
+   }
+   
+ 
+   if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+     stop("No agreement in Min")
+   }
+ 
+ 
+   if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+ 
+     cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+     cat(sum(r.matrix,na.rm=TRUE),"\n")
+     cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+     
+     stop("No agreement in Sum")
+   }
+   
+   if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+     stop("No agreement in mean")
+   }
+   
+   
+   if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+     stop("No agreement in Var")
+   }
+   
+   
+ 
+   if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowMeans")
+   }
+   
+   
+   if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in colMeans")
+   }
+   
+   
+   if(any(abs(rowSums(buff.matrix,na.rm=TRUE)  -  apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in rowSums")
+   }
+   
+   
+   if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in colSums")
+   }
+   
+   ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when 
+   ### computing variance
+   my.Var <- function(x,na.rm=FALSE){
+    if (all(is.na(x))){
+      return(NA)
+    } else {
+      var(x,na.rm=na.rm)
+    }
+ 
+   }
+   
+   if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowVars")
+   }
+   
+   
+   if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowVars")
+   }
+ 
+ 
+   if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMax")
+   }
+   
+ 
+   if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMax")
+   }
+   
+   
+   
+   if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMin")
+   }
+   
+ 
+   if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMin")
+   }
+ 
+   if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMedian")
+   }
+ 
+   if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in colRanges")
+   }
+ 
+ 
+   
+ }
> 
> 
> 
> 
> 
> 
> 
> 
> 
> for (rep in 1:20){
+   copymatrix <- matrix(rnorm(200,150,15),10,20)
+   
+   tmp5[1:10,1:20] <- copymatrix
+ 
+ 
+   agree.checks(tmp5,copymatrix)
+   
+   ## now lets assign some NA values and check agreement
+ 
+   which.row <- sample(1:10,1,replace=TRUE)
+   which.col  <- sample(1:20,1,replace=TRUE)
+   
+   cat(which.row," ",which.col,"\n")
+   
+   tmp5[which.row,which.col] <- NA
+   copymatrix[which.row,which.col] <- NA
+   
+   agree.checks(tmp5,copymatrix)
+ 
+   ## make an entire row NA
+   tmp5[which.row,] <- NA
+   copymatrix[which.row,] <- NA
+ 
+ 
+   agree.checks(tmp5,copymatrix)
+   
+   ### also make an entire col NA
+   tmp5[,which.col] <- NA
+   copymatrix[,which.col] <- NA
+ 
+   agree.checks(tmp5,copymatrix)
+ 
+   ### now make 1 element non NA with NA in the rest of row and column
+ 
+   tmp5[which.row,which.col] <- rnorm(1,150,15)
+   copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+ 
+   agree.checks(tmp5,copymatrix)
+ }
2   14 
10   7 
6   3 
2   8 
1   3 
8   18 
1   1 
3   11 
3   18 
1   3 
3   15 
1   3 
9   10 
6   10 
7   14 
1   17 
4   8 
4   4 
6   3 
8   11 
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] 2.475116
> Min(tmp)
[1] -2.574081
> mean(tmp)
[1] -0.1395397
> Sum(tmp)
[1] -13.95397
> Var(tmp)
[1] 1.028677
> 
> rowMeans(tmp)
[1] -0.1395397
> rowSums(tmp)
[1] -13.95397
> rowVars(tmp)
[1] 1.028677
> rowSd(tmp)
[1] 1.014237
> rowMax(tmp)
[1] 2.475116
> rowMin(tmp)
[1] -2.574081
> 
> colMeans(tmp)
  [1] -0.99940087 -0.38240492 -0.08248278  1.29029579 -1.90410726  0.65289026
  [7] -0.90968953 -0.91716243  2.01666371  0.90256023 -0.66276936  0.77571512
 [13]  0.45011096  0.83480833  0.39654423 -0.84464366 -0.98893965 -1.38484852
 [19] -1.50335665 -0.86129245 -1.74430796 -1.82620026  0.32111846  0.76952834
 [25]  0.70653447 -0.31592461 -1.25224080 -1.45899903  1.29896013 -0.66092106
 [31]  0.49508039  0.51132941 -1.70881379 -0.89148810  0.28882119  1.58695404
 [37]  2.32040311  0.05982141  2.20284498 -1.44603396 -0.51390622  0.39980605
 [43] -0.72796823 -0.32569027 -0.74590685 -0.39777894  0.02944292  0.27926463
 [49]  0.29514141 -0.77564093  0.98006874 -0.18124801 -0.71029470 -1.12659933
 [55] -1.18620517  0.49489830  0.23573340  0.79609374  0.37617165  0.03852248
 [61] -1.15144226 -0.26476395  0.40625667 -2.57408150 -0.96607248 -1.81742301
 [67]  0.63376677 -0.44912940  0.92560092 -0.15049526 -0.66562413  0.76565568
 [73] -0.35051332  0.41694367  1.09868716 -0.29864700  0.17696818 -1.22854445
 [79]  1.17803685 -0.89763205 -0.19436286  0.02324336 -0.15077905  0.90440179
 [85] -0.49025052 -0.02920052 -1.06083735  0.80069185  0.35338067 -0.77397980
 [91] -1.45639743  1.70389596  2.47511631 -0.74125245  0.05264514  0.69454029
 [97] -0.98418849 -0.16652402 -2.04009277 -0.03042827
> colSums(tmp)
  [1] -0.99940087 -0.38240492 -0.08248278  1.29029579 -1.90410726  0.65289026
  [7] -0.90968953 -0.91716243  2.01666371  0.90256023 -0.66276936  0.77571512
 [13]  0.45011096  0.83480833  0.39654423 -0.84464366 -0.98893965 -1.38484852
 [19] -1.50335665 -0.86129245 -1.74430796 -1.82620026  0.32111846  0.76952834
 [25]  0.70653447 -0.31592461 -1.25224080 -1.45899903  1.29896013 -0.66092106
 [31]  0.49508039  0.51132941 -1.70881379 -0.89148810  0.28882119  1.58695404
 [37]  2.32040311  0.05982141  2.20284498 -1.44603396 -0.51390622  0.39980605
 [43] -0.72796823 -0.32569027 -0.74590685 -0.39777894  0.02944292  0.27926463
 [49]  0.29514141 -0.77564093  0.98006874 -0.18124801 -0.71029470 -1.12659933
 [55] -1.18620517  0.49489830  0.23573340  0.79609374  0.37617165  0.03852248
 [61] -1.15144226 -0.26476395  0.40625667 -2.57408150 -0.96607248 -1.81742301
 [67]  0.63376677 -0.44912940  0.92560092 -0.15049526 -0.66562413  0.76565568
 [73] -0.35051332  0.41694367  1.09868716 -0.29864700  0.17696818 -1.22854445
 [79]  1.17803685 -0.89763205 -0.19436286  0.02324336 -0.15077905  0.90440179
 [85] -0.49025052 -0.02920052 -1.06083735  0.80069185  0.35338067 -0.77397980
 [91] -1.45639743  1.70389596  2.47511631 -0.74125245  0.05264514  0.69454029
 [97] -0.98418849 -0.16652402 -2.04009277 -0.03042827
> 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] -0.99940087 -0.38240492 -0.08248278  1.29029579 -1.90410726  0.65289026
  [7] -0.90968953 -0.91716243  2.01666371  0.90256023 -0.66276936  0.77571512
 [13]  0.45011096  0.83480833  0.39654423 -0.84464366 -0.98893965 -1.38484852
 [19] -1.50335665 -0.86129245 -1.74430796 -1.82620026  0.32111846  0.76952834
 [25]  0.70653447 -0.31592461 -1.25224080 -1.45899903  1.29896013 -0.66092106
 [31]  0.49508039  0.51132941 -1.70881379 -0.89148810  0.28882119  1.58695404
 [37]  2.32040311  0.05982141  2.20284498 -1.44603396 -0.51390622  0.39980605
 [43] -0.72796823 -0.32569027 -0.74590685 -0.39777894  0.02944292  0.27926463
 [49]  0.29514141 -0.77564093  0.98006874 -0.18124801 -0.71029470 -1.12659933
 [55] -1.18620517  0.49489830  0.23573340  0.79609374  0.37617165  0.03852248
 [61] -1.15144226 -0.26476395  0.40625667 -2.57408150 -0.96607248 -1.81742301
 [67]  0.63376677 -0.44912940  0.92560092 -0.15049526 -0.66562413  0.76565568
 [73] -0.35051332  0.41694367  1.09868716 -0.29864700  0.17696818 -1.22854445
 [79]  1.17803685 -0.89763205 -0.19436286  0.02324336 -0.15077905  0.90440179
 [85] -0.49025052 -0.02920052 -1.06083735  0.80069185  0.35338067 -0.77397980
 [91] -1.45639743  1.70389596  2.47511631 -0.74125245  0.05264514  0.69454029
 [97] -0.98418849 -0.16652402 -2.04009277 -0.03042827
> colMin(tmp)
  [1] -0.99940087 -0.38240492 -0.08248278  1.29029579 -1.90410726  0.65289026
  [7] -0.90968953 -0.91716243  2.01666371  0.90256023 -0.66276936  0.77571512
 [13]  0.45011096  0.83480833  0.39654423 -0.84464366 -0.98893965 -1.38484852
 [19] -1.50335665 -0.86129245 -1.74430796 -1.82620026  0.32111846  0.76952834
 [25]  0.70653447 -0.31592461 -1.25224080 -1.45899903  1.29896013 -0.66092106
 [31]  0.49508039  0.51132941 -1.70881379 -0.89148810  0.28882119  1.58695404
 [37]  2.32040311  0.05982141  2.20284498 -1.44603396 -0.51390622  0.39980605
 [43] -0.72796823 -0.32569027 -0.74590685 -0.39777894  0.02944292  0.27926463
 [49]  0.29514141 -0.77564093  0.98006874 -0.18124801 -0.71029470 -1.12659933
 [55] -1.18620517  0.49489830  0.23573340  0.79609374  0.37617165  0.03852248
 [61] -1.15144226 -0.26476395  0.40625667 -2.57408150 -0.96607248 -1.81742301
 [67]  0.63376677 -0.44912940  0.92560092 -0.15049526 -0.66562413  0.76565568
 [73] -0.35051332  0.41694367  1.09868716 -0.29864700  0.17696818 -1.22854445
 [79]  1.17803685 -0.89763205 -0.19436286  0.02324336 -0.15077905  0.90440179
 [85] -0.49025052 -0.02920052 -1.06083735  0.80069185  0.35338067 -0.77397980
 [91] -1.45639743  1.70389596  2.47511631 -0.74125245  0.05264514  0.69454029
 [97] -0.98418849 -0.16652402 -2.04009277 -0.03042827
> colMedians(tmp)
  [1] -0.99940087 -0.38240492 -0.08248278  1.29029579 -1.90410726  0.65289026
  [7] -0.90968953 -0.91716243  2.01666371  0.90256023 -0.66276936  0.77571512
 [13]  0.45011096  0.83480833  0.39654423 -0.84464366 -0.98893965 -1.38484852
 [19] -1.50335665 -0.86129245 -1.74430796 -1.82620026  0.32111846  0.76952834
 [25]  0.70653447 -0.31592461 -1.25224080 -1.45899903  1.29896013 -0.66092106
 [31]  0.49508039  0.51132941 -1.70881379 -0.89148810  0.28882119  1.58695404
 [37]  2.32040311  0.05982141  2.20284498 -1.44603396 -0.51390622  0.39980605
 [43] -0.72796823 -0.32569027 -0.74590685 -0.39777894  0.02944292  0.27926463
 [49]  0.29514141 -0.77564093  0.98006874 -0.18124801 -0.71029470 -1.12659933
 [55] -1.18620517  0.49489830  0.23573340  0.79609374  0.37617165  0.03852248
 [61] -1.15144226 -0.26476395  0.40625667 -2.57408150 -0.96607248 -1.81742301
 [67]  0.63376677 -0.44912940  0.92560092 -0.15049526 -0.66562413  0.76565568
 [73] -0.35051332  0.41694367  1.09868716 -0.29864700  0.17696818 -1.22854445
 [79]  1.17803685 -0.89763205 -0.19436286  0.02324336 -0.15077905  0.90440179
 [85] -0.49025052 -0.02920052 -1.06083735  0.80069185  0.35338067 -0.77397980
 [91] -1.45639743  1.70389596  2.47511631 -0.74125245  0.05264514  0.69454029
 [97] -0.98418849 -0.16652402 -2.04009277 -0.03042827
> colRanges(tmp)
           [,1]       [,2]        [,3]     [,4]      [,5]      [,6]       [,7]
[1,] -0.9994009 -0.3824049 -0.08248278 1.290296 -1.904107 0.6528903 -0.9096895
[2,] -0.9994009 -0.3824049 -0.08248278 1.290296 -1.904107 0.6528903 -0.9096895
           [,8]     [,9]     [,10]      [,11]     [,12]    [,13]     [,14]
[1,] -0.9171624 2.016664 0.9025602 -0.6627694 0.7757151 0.450111 0.8348083
[2,] -0.9171624 2.016664 0.9025602 -0.6627694 0.7757151 0.450111 0.8348083
         [,15]      [,16]      [,17]     [,18]     [,19]      [,20]     [,21]
[1,] 0.3965442 -0.8446437 -0.9889397 -1.384849 -1.503357 -0.8612924 -1.744308
[2,] 0.3965442 -0.8446437 -0.9889397 -1.384849 -1.503357 -0.8612924 -1.744308
       [,22]     [,23]     [,24]     [,25]      [,26]     [,27]     [,28]
[1,] -1.8262 0.3211185 0.7695283 0.7065345 -0.3159246 -1.252241 -1.458999
[2,] -1.8262 0.3211185 0.7695283 0.7065345 -0.3159246 -1.252241 -1.458999
       [,29]      [,30]     [,31]     [,32]     [,33]      [,34]     [,35]
[1,] 1.29896 -0.6609211 0.4950804 0.5113294 -1.708814 -0.8914881 0.2888212
[2,] 1.29896 -0.6609211 0.4950804 0.5113294 -1.708814 -0.8914881 0.2888212
        [,36]    [,37]      [,38]    [,39]     [,40]      [,41]    [,42]
[1,] 1.586954 2.320403 0.05982141 2.202845 -1.446034 -0.5139062 0.399806
[2,] 1.586954 2.320403 0.05982141 2.202845 -1.446034 -0.5139062 0.399806
          [,43]      [,44]      [,45]      [,46]      [,47]     [,48]     [,49]
[1,] -0.7279682 -0.3256903 -0.7459068 -0.3977789 0.02944292 0.2792646 0.2951414
[2,] -0.7279682 -0.3256903 -0.7459068 -0.3977789 0.02944292 0.2792646 0.2951414
          [,50]     [,51]     [,52]      [,53]     [,54]     [,55]     [,56]
[1,] -0.7756409 0.9800687 -0.181248 -0.7102947 -1.126599 -1.186205 0.4948983
[2,] -0.7756409 0.9800687 -0.181248 -0.7102947 -1.126599 -1.186205 0.4948983
         [,57]     [,58]     [,59]      [,60]     [,61]      [,62]     [,63]
[1,] 0.2357334 0.7960937 0.3761717 0.03852248 -1.151442 -0.2647639 0.4062567
[2,] 0.2357334 0.7960937 0.3761717 0.03852248 -1.151442 -0.2647639 0.4062567
         [,64]      [,65]     [,66]     [,67]      [,68]     [,69]      [,70]
[1,] -2.574081 -0.9660725 -1.817423 0.6337668 -0.4491294 0.9256009 -0.1504953
[2,] -2.574081 -0.9660725 -1.817423 0.6337668 -0.4491294 0.9256009 -0.1504953
          [,71]     [,72]      [,73]     [,74]    [,75]     [,76]     [,77]
[1,] -0.6656241 0.7656557 -0.3505133 0.4169437 1.098687 -0.298647 0.1769682
[2,] -0.6656241 0.7656557 -0.3505133 0.4169437 1.098687 -0.298647 0.1769682
         [,78]    [,79]     [,80]      [,81]      [,82]      [,83]     [,84]
[1,] -1.228544 1.178037 -0.897632 -0.1943629 0.02324336 -0.1507791 0.9044018
[2,] -1.228544 1.178037 -0.897632 -0.1943629 0.02324336 -0.1507791 0.9044018
          [,85]       [,86]     [,87]     [,88]     [,89]      [,90]     [,91]
[1,] -0.4902505 -0.02920052 -1.060837 0.8006919 0.3533807 -0.7739798 -1.456397
[2,] -0.4902505 -0.02920052 -1.060837 0.8006919 0.3533807 -0.7739798 -1.456397
        [,92]    [,93]      [,94]      [,95]     [,96]      [,97]     [,98]
[1,] 1.703896 2.475116 -0.7412525 0.05264514 0.6945403 -0.9841885 -0.166524
[2,] 1.703896 2.475116 -0.7412525 0.05264514 0.6945403 -0.9841885 -0.166524
         [,99]      [,100]
[1,] -2.040093 -0.03042827
[2,] -2.040093 -0.03042827
> 
> 
> Max(tmp2)
[1] 2.713254
> Min(tmp2)
[1] -2.481848
> mean(tmp2)
[1] 0.009060189
> Sum(tmp2)
[1] 0.9060189
> Var(tmp2)
[1] 1.014519
> 
> rowMeans(tmp2)
  [1] -0.66445945  0.42564418 -0.10153881 -0.46669693 -0.46702990 -0.72281691
  [7]  1.30098214  0.93400199  2.19287415 -2.19351980 -0.48236484 -0.50502781
 [13] -0.60937422 -0.69391046  0.15059587 -1.03631955 -0.76985511  0.50030711
 [19]  1.09898828  1.17068437  0.26009837 -0.22979863  0.16121246  0.54016437
 [25]  0.78411783  0.41834015  1.19840360  0.84469365 -0.67644316  1.60325620
 [31]  0.27234995 -0.03278269  1.19545195  2.71325445  0.41338428  0.69779801
 [37]  0.39222052 -0.27584861  0.45341087  0.93918194  0.65972921 -0.07044250
 [43] -0.81499450 -1.38391648 -0.32737804  0.35528874 -0.23475986 -0.50079746
 [49] -0.76631029 -0.89082085  1.73179132 -1.69647614 -0.59720724  0.03849907
 [55] -2.04402439  0.44635242 -1.79421983 -0.10132004 -0.58166738  0.62641928
 [61]  0.68879986  1.85908431  0.85385782  0.54454973 -0.97858841  0.65516282
 [67]  0.12586524  2.37442076 -0.34528874  1.55638895 -0.02249873 -2.48184819
 [73] -0.39174384  0.42195996 -2.12614652  1.08251527 -0.26670212 -0.99857650
 [79] -1.34700800 -0.77787838 -1.47024760  0.61288512 -0.13864507 -1.81239423
 [85] -1.18521139  0.74207495  0.23584457 -0.57207372 -0.12698421 -0.95394863
 [91]  0.08043809  0.33110435  0.46315953 -0.47845217 -0.68451817  1.03074021
 [97]  1.01101813  0.32649388 -0.71861546  0.99965054
> rowSums(tmp2)
  [1] -0.66445945  0.42564418 -0.10153881 -0.46669693 -0.46702990 -0.72281691
  [7]  1.30098214  0.93400199  2.19287415 -2.19351980 -0.48236484 -0.50502781
 [13] -0.60937422 -0.69391046  0.15059587 -1.03631955 -0.76985511  0.50030711
 [19]  1.09898828  1.17068437  0.26009837 -0.22979863  0.16121246  0.54016437
 [25]  0.78411783  0.41834015  1.19840360  0.84469365 -0.67644316  1.60325620
 [31]  0.27234995 -0.03278269  1.19545195  2.71325445  0.41338428  0.69779801
 [37]  0.39222052 -0.27584861  0.45341087  0.93918194  0.65972921 -0.07044250
 [43] -0.81499450 -1.38391648 -0.32737804  0.35528874 -0.23475986 -0.50079746
 [49] -0.76631029 -0.89082085  1.73179132 -1.69647614 -0.59720724  0.03849907
 [55] -2.04402439  0.44635242 -1.79421983 -0.10132004 -0.58166738  0.62641928
 [61]  0.68879986  1.85908431  0.85385782  0.54454973 -0.97858841  0.65516282
 [67]  0.12586524  2.37442076 -0.34528874  1.55638895 -0.02249873 -2.48184819
 [73] -0.39174384  0.42195996 -2.12614652  1.08251527 -0.26670212 -0.99857650
 [79] -1.34700800 -0.77787838 -1.47024760  0.61288512 -0.13864507 -1.81239423
 [85] -1.18521139  0.74207495  0.23584457 -0.57207372 -0.12698421 -0.95394863
 [91]  0.08043809  0.33110435  0.46315953 -0.47845217 -0.68451817  1.03074021
 [97]  1.01101813  0.32649388 -0.71861546  0.99965054
> 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] -0.66445945  0.42564418 -0.10153881 -0.46669693 -0.46702990 -0.72281691
  [7]  1.30098214  0.93400199  2.19287415 -2.19351980 -0.48236484 -0.50502781
 [13] -0.60937422 -0.69391046  0.15059587 -1.03631955 -0.76985511  0.50030711
 [19]  1.09898828  1.17068437  0.26009837 -0.22979863  0.16121246  0.54016437
 [25]  0.78411783  0.41834015  1.19840360  0.84469365 -0.67644316  1.60325620
 [31]  0.27234995 -0.03278269  1.19545195  2.71325445  0.41338428  0.69779801
 [37]  0.39222052 -0.27584861  0.45341087  0.93918194  0.65972921 -0.07044250
 [43] -0.81499450 -1.38391648 -0.32737804  0.35528874 -0.23475986 -0.50079746
 [49] -0.76631029 -0.89082085  1.73179132 -1.69647614 -0.59720724  0.03849907
 [55] -2.04402439  0.44635242 -1.79421983 -0.10132004 -0.58166738  0.62641928
 [61]  0.68879986  1.85908431  0.85385782  0.54454973 -0.97858841  0.65516282
 [67]  0.12586524  2.37442076 -0.34528874  1.55638895 -0.02249873 -2.48184819
 [73] -0.39174384  0.42195996 -2.12614652  1.08251527 -0.26670212 -0.99857650
 [79] -1.34700800 -0.77787838 -1.47024760  0.61288512 -0.13864507 -1.81239423
 [85] -1.18521139  0.74207495  0.23584457 -0.57207372 -0.12698421 -0.95394863
 [91]  0.08043809  0.33110435  0.46315953 -0.47845217 -0.68451817  1.03074021
 [97]  1.01101813  0.32649388 -0.71861546  0.99965054
> rowMin(tmp2)
  [1] -0.66445945  0.42564418 -0.10153881 -0.46669693 -0.46702990 -0.72281691
  [7]  1.30098214  0.93400199  2.19287415 -2.19351980 -0.48236484 -0.50502781
 [13] -0.60937422 -0.69391046  0.15059587 -1.03631955 -0.76985511  0.50030711
 [19]  1.09898828  1.17068437  0.26009837 -0.22979863  0.16121246  0.54016437
 [25]  0.78411783  0.41834015  1.19840360  0.84469365 -0.67644316  1.60325620
 [31]  0.27234995 -0.03278269  1.19545195  2.71325445  0.41338428  0.69779801
 [37]  0.39222052 -0.27584861  0.45341087  0.93918194  0.65972921 -0.07044250
 [43] -0.81499450 -1.38391648 -0.32737804  0.35528874 -0.23475986 -0.50079746
 [49] -0.76631029 -0.89082085  1.73179132 -1.69647614 -0.59720724  0.03849907
 [55] -2.04402439  0.44635242 -1.79421983 -0.10132004 -0.58166738  0.62641928
 [61]  0.68879986  1.85908431  0.85385782  0.54454973 -0.97858841  0.65516282
 [67]  0.12586524  2.37442076 -0.34528874  1.55638895 -0.02249873 -2.48184819
 [73] -0.39174384  0.42195996 -2.12614652  1.08251527 -0.26670212 -0.99857650
 [79] -1.34700800 -0.77787838 -1.47024760  0.61288512 -0.13864507 -1.81239423
 [85] -1.18521139  0.74207495  0.23584457 -0.57207372 -0.12698421 -0.95394863
 [91]  0.08043809  0.33110435  0.46315953 -0.47845217 -0.68451817  1.03074021
 [97]  1.01101813  0.32649388 -0.71861546  0.99965054
> 
> colMeans(tmp2)
[1] 0.009060189
> colSums(tmp2)
[1] 0.9060189
> colVars(tmp2)
[1] 1.014519
> colSd(tmp2)
[1] 1.007233
> colMax(tmp2)
[1] 2.713254
> colMin(tmp2)
[1] -2.481848
> colMedians(tmp2)
[1] 0.00800017
> colRanges(tmp2)
          [,1]
[1,] -2.481848
[2,]  2.713254
> 
> 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]  2.10569671 -1.41875749 -3.27244934 -3.06473577 -0.07685308  0.49889904
 [7]  1.35864029  5.08418703 -0.78245694 -1.45152354
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -0.6595818
[2,] -0.2101381
[3,]  0.1304456
[4,]  0.5608820
[5,]  1.5015016
> 
> rowApply(tmp,sum)
 [1] -2.9400374  1.2225186 -1.3693586  5.5166234 -2.4763992  2.1299541
 [7] -2.7272492 -0.2355497 -0.5797518  0.4398968
> rowApply(tmp,rank)[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]   10    7    3    2    8    5    4   10    5     7
 [2,]    7    5    8    5    9    3    1    9    2     4
 [3,]    6    2    2    1    7    2    3    8    7     9
 [4,]    1    3    5    3    3   10    8    1    4     5
 [5,]    3    4    6    4    5    8   10    3   10     2
 [6,]    5    8    4    9    1    4    9    5    1    10
 [7,]    2   10    7    8   10    1    5    7    8     1
 [8,]    8    6    9   10    4    6    7    6    9     8
 [9,]    9    9    1    7    6    7    2    4    6     3
[10,]    4    1   10    6    2    9    6    2    3     6
> 
> tmp <- createBufferedMatrix(5,20)
> 
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
 [1] -0.15796686 -0.14063776 -5.13593687 -0.37087291  3.34530643 -3.10326826
 [7] -1.43553744  1.21323672 -0.37031887 -0.96012609  2.40340610 -0.58480266
[13] -2.62864100 -1.94144604 -0.01257848 -0.91555716 -3.23276763 -4.44830079
[19] -4.89090884  0.74422792
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -1.2414741
[2,] -1.2209848
[3,] -0.1836189
[4,]  0.6479218
[5,]  1.8401891
> 
> rowApply(tmp,sum)
[1] -5.360055 -5.233301 -6.016326 -7.034208  1.020399
> rowApply(tmp,rank)[1:5,]
     [,1] [,2] [,3] [,4] [,5]
[1,]    5    5   20   12   15
[2,]    8   13   17   20    5
[3,]    7    1    2    1   19
[4,]   13   19    9    8    6
[5,]   12   12   19    9   20
> 
> 
> as.matrix(tmp)
           [,1]       [,2]       [,3]        [,4]        [,5]        [,6]
[1,] -1.2209848 -0.8626167 -0.9654195 -0.08478108 -0.17456509 -2.44160200
[2,] -1.2414741  0.1559485 -2.3793403  1.44144670  0.08190447 -0.02899004
[3,]  1.8401891  0.5876191 -1.3952789 -0.82836556  1.41767422 -0.07791378
[4,] -0.1836189  1.3033743 -2.2174789 -0.52804980 -0.50308280 -0.31794656
[5,]  0.6479218 -1.3249629  1.8215808 -0.37112316  2.52337563 -0.23681588
           [,7]       [,8]       [,9]      [,10]       [,11]      [,12]
[1,] -1.7291045 -0.4308809  1.5298219 -0.3249451  0.89671918  0.4807229
[2,]  2.2332207  0.3631666 -0.1265312  0.3854775  0.61355046 -0.9464367
[3,] -1.0605809  0.3278004  0.3762076 -1.0947729 -0.53991361  0.2995125
[4,] -0.6108997  1.1267271 -0.4742601 -0.5532975  0.02202847 -1.3272799
[5,] -0.2681730 -0.1735765 -1.6755571  0.6274118  1.41102160  0.9086785
          [,13]      [,14]      [,15]      [,16]      [,17]      [,18]
[1,]  1.7671819 -2.5483186  1.5156122 -1.2388152 -0.3421774 -1.0556569
[2,] -1.0439565 -0.8432305 -1.2908540  0.4889161 -1.5570209 -1.1796760
[3,] -1.3855802  0.9243590  0.1604521 -1.0984177 -1.5963203 -1.3676339
[4,] -0.1004628  0.1551307 -2.0049891  0.7115013  0.2033919  0.7336992
[5,] -1.8658234  0.3706134  1.6072003  0.2212583  0.0593590 -1.5790332
          [,19]      [,20]
[1,]  0.5525277  1.3172264
[2,] -1.3889405  1.0295188
[3,] -1.3744869 -0.1308755
[4,] -1.3013812 -1.1673132
[5,] -1.3786279 -0.3043287
> 
> 
> 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/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  800  bytes.
> 
> 
> 
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size:  5 5 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  649  bytes.
Disk usage :  200  bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size:  5 4 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  563  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/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  480  bytes.
> 
> 
> rm(tmp)
> 
> 
> ###
> ### Testing colnames and rownames
> ###
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> 
> 
> colnames(tmp)
NULL
> rownames(tmp)
NULL
> 
> 
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> 
> colnames(tmp)
 [1] "col1"  "col2"  "col3"  "col4"  "col5"  "col6"  "col7"  "col8"  "col9" 
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
> 
> 
> tmp["row1",]
           col1      col2     col3        col4      col5        col6     col7
row1 -0.2129909 -1.538386 0.883643 -0.07811251 0.8401573 -0.08579522 1.393066
          col8     col9     col10   col11    col12     col13     col14
row1 -1.441978 1.122026 -1.202252 0.39134 1.633353 0.1717418 -1.280766
         col15      col16      col17     col18     col19     col20
row1 -2.078037 -0.5448039 -0.1115954 0.6312493 0.2303173 0.5318631
> tmp[,"col10"]
          col10
row1 -1.2022523
row2  1.1633947
row3  2.3024567
row4 -0.3966048
row5  0.1942420
> tmp[c("row1","row5"),]
           col1       col2      col3        col4      col5        col6
row1 -0.2129909 -1.5383861 0.8836430 -0.07811251 0.8401573 -0.08579522
row5  0.5443792 -0.8080539 0.7765278  0.03102178 0.7785924 -0.74593101
           col7       col8      col9     col10      col11     col12     col13
row1  1.3930657 -1.4419780  1.122026 -1.202252  0.3913400 1.6333534 0.1717418
row5 -0.2151411  0.9564085 -2.138784  0.194242 -0.8990519 0.5594276 2.4121207
         col14      col15       col16      col17       col18     col19
row1 -1.280766 -2.0780367 -0.54480388 -0.1115954  0.63124935 0.2303173
row5 -1.162110 -0.7557949 -0.03929401  0.2777472 -0.02162955 1.2557505
          col20
row1  0.5318631
row5 -0.7142257
> tmp[,c("col6","col20")]
            col6      col20
row1 -0.08579522  0.5318631
row2  2.29973736 -0.2685357
row3  0.23623558 -0.8052372
row4 -0.87745859  1.1890685
row5 -0.74593101 -0.7142257
> tmp[c("row1","row5"),c("col6","col20")]
            col6      col20
row1 -0.08579522  0.5318631
row5 -0.74593101 -0.7142257
> 
> 
> 
> 
> 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 49.43045 49.86247 49.13178 50.30206 48.38406 104.859 50.39239 50.70939
         col9    col10    col11    col12    col13    col14    col15    col16
row1 49.83129 50.63753 51.30087 50.68278 49.32085 50.48551 48.37885 49.39282
        col17    col18    col19    col20
row1 49.31023 50.76104 49.90923 104.4465
> tmp[,"col10"]
        col10
row1 50.63753
row2 30.07071
row3 29.42608
row4 29.35181
row5 49.61035
> tmp[c("row1","row5"),]
         col1     col2     col3     col4     col5    col6     col7     col8
row1 49.43045 49.86247 49.13178 50.30206 48.38406 104.859 50.39239 50.70939
row5 50.16859 48.25450 52.67745 50.49782 50.05750 105.360 50.12210 49.65956
         col9    col10    col11    col12    col13    col14    col15    col16
row1 49.83129 50.63753 51.30087 50.68278 49.32085 50.48551 48.37885 49.39282
row5 50.13082 49.61035 48.89578 50.53146 51.60218 50.38650 49.01033 49.07992
        col17    col18    col19    col20
row1 49.31023 50.76104 49.90923 104.4465
row5 48.91101 49.17077 49.63891 103.8894
> tmp[,c("col6","col20")]
          col6     col20
row1 104.85898 104.44650
row2  75.74102  76.39308
row3  74.45206  74.31707
row4  74.47526  75.40694
row5 105.36000 103.88938
> tmp[c("row1","row5"),c("col6","col20")]
        col6    col20
row1 104.859 104.4465
row5 105.360 103.8894
> 
> 
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
        col6    col20
row1 104.859 104.4465
row5 105.360 103.8894
> 
> 
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> 
> tmp[,"col13"]
           col13
[1,]  0.35278488
[2,] -0.35716710
[3,] -0.41038673
[4,] -1.46546772
[5,]  0.01676246
> tmp[,c("col17","col7")]
          col17       col7
[1,] -0.5726167 -0.8861414
[2,]  1.3041800 -1.4448500
[3,]  0.7645496  0.1547295
[4,] -0.1804821 -1.0740585
[5,] -0.8809667  2.5071522
> 
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
           col6      col20
[1,]  1.3286348  0.1873268
[2,] -0.7670321  2.1740339
[3,] -0.2149854  0.8580072
[4,] -1.4271411 -0.7484355
[5,]  0.9162317  0.1221138
> subBufferedMatrix(tmp,1,c("col6"))[,1]
         col1
[1,] 1.328635
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
           col6
[1,]  1.3286348
[2,] -0.7670321
> 
> 
> 
> 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  0.9547968 -0.1518111  0.7267268 1.0963836 0.247471768  0.2786178
row1 -0.4959588 -1.6158237 -1.7579434 0.1403902 0.005829339 -0.7381776
          [,7]       [,8]       [,9]      [,10]      [,11]       [,12]
row3 1.5630060 -1.4176570 -0.2343042  0.4426637 -0.3030738 -0.74137880
row1 0.4834254 -0.1091383  1.1362906 -0.3983239  1.3176666 -0.06503243
           [,13]      [,14]    [,15]     [,16]      [,17]     [,18]     [,19]
row3  0.62252121  0.3738310 2.471098  1.036794 -0.3512469  1.177644 0.8015782
row1 -0.09555372 -0.9104681 2.159371 -1.386950  1.3619229 -1.370971 0.3060681
          [,20]
row3 -0.1625648
row1  0.9043262
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
            [,1]       [,2]      [,3]        [,4]     [,5]     [,6]       [,7]
row2 -0.02911865 -0.9566149 0.5409379 0.002609536 1.907063 1.132289 -0.1632463
          [,8]       [,9]      [,10]
row2 -1.547108 -0.9935086 -0.1864415
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
           [,1]      [,2]     [,3]      [,4]       [,5]       [,6]     [,7]
row5 -0.2528949 0.4220061 1.029685 0.1055771 0.08170962 -0.8062829 1.397239
          [,8]     [,9]      [,10]     [,11]    [,12]    [,13]        [,14]
row5 0.5496579 1.030056 -0.4015256 -1.722462 0.466078 1.573517 -0.007405897
         [,15]     [,16]      [,17]     [,18]     [,19]      [,20]
row5 -1.090625 0.1415268 -0.4705039 0.6325884 -1.780406 0.09566731
> 
> 
> 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: 0x6000011c00c0>
> is.ReadOnlyMode(tmp)
[1] TRUE
> 
> filenames(tmp)
 [1] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbbb45a19fb14"
 [2] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbbb45fb30c42"
 [3] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbbb463e9f223"
 [4] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbbb414180b14"
 [5] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbbb4367f585a"
 [6] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbbb4628198a9"
 [7] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbbb42a4db1c5"
 [8] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbbb452d21235"
 [9] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbbb45da9800d"
[10] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbbb423160585"
[11] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbbb47ac470c1"
[12] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbbb476c6cdde"
[13] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbbb475f5e6bd"
[14] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbbb462ffbecb"
[15] "/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests/BMbbb44473434" 
> 
> 
> ### 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: 0x6000011dc060>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000011dc060>
Warning message:
In dir.create(new.directory) :
  '/Users/biocbuild/bbs-3.19-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
> 
> 
> RowMode(tmp)
<pointer: 0x6000011dc060>
> rowMedians(tmp)
  [1] -0.5419818308  0.4483621429 -0.4248065480 -0.2192632065 -0.2882717644
  [6] -0.4488021708  0.2799901596  0.3936543836  0.2520734718  0.0097220710
 [11] -0.4694126450 -0.6754462591  0.5614856538  0.4964602196  0.3507103523
 [16]  0.2574622622  0.0353274348 -0.5664388715  0.0482915921  0.5035333984
 [21] -0.4650308640  0.2333782889 -0.6058091408  0.0591789924 -0.1941642112
 [26]  0.4084946274 -0.0708939042 -0.4965401227  0.1010500444  0.0558588474
 [31] -0.3764727570  0.1879079988  0.1861845050  0.4532501270  0.4189735871
 [36]  0.3345296759  0.4322106381 -0.6520475405  0.3576420206 -0.2730554799
 [41]  0.2353696484  0.3052750000  0.2299874669 -0.1297009287  0.1743207308
 [46]  0.1174049061  0.1959949488 -0.2468201602  0.4220030604 -0.1251897259
 [51]  0.8072172615 -0.0515312585 -0.4099980267 -0.2088487765 -0.2105147823
 [56] -0.4133523587  0.4968796585  0.3068853617 -0.1339215110  0.0741848193
 [61]  0.4823751395 -0.2030298515  0.2889111288  0.0691210911 -0.3415974853
 [66]  0.5094489615 -0.5085090637  0.0147342544  0.5438184324  0.1141170974
 [71] -0.4552864983  0.2423041634 -0.3791101371 -0.2123688949  0.4318205067
 [76] -0.1204729729  0.3314047680  0.3931534765  0.6552389868 -0.2666098735
 [81]  0.2660080536 -0.5932530422  0.2136340916  0.1482242573 -0.0387503216
 [86] -0.3111999467 -0.6040381180 -0.3129873886 -0.8666458904  0.6184394085
 [91]  0.0352065293  0.2520743884  0.4986016046  0.0977218035  0.5363724225
 [96]  0.2395193900  0.0918475651 -0.4240318863  0.2428290201  0.2622103866
[101] -0.1255486791 -0.0846642280  0.1172421392 -0.4151203400 -0.2753327707
[106] -0.0412621219  0.1587272736 -0.3354839451 -0.3209424054  0.0295028572
[111] -0.1129953447 -0.0932262693  0.3200271966 -0.1720153801 -0.4797455212
[116]  0.0082054694  0.1402186349 -0.0350875591 -0.5179006162  0.0321656515
[121] -0.4852332682  0.1327646546  0.1925066359 -0.0770446554  0.4782290343
[126]  0.5688667749  0.2263425790 -0.5667548204  0.3210586435 -0.0119178138
[131] -0.1630794392 -0.0156214809 -0.5788403092 -0.3348637505  0.1507029335
[136] -0.3109938815  0.5869094433  0.2574405614  0.2326288473 -0.5186755713
[141] -0.1820800754 -0.1177827753  0.2705191712  0.6617944496  0.1542267024
[146]  0.1395608755  0.0348185497 -0.8117692491 -0.2564549947  0.2646730692
[151]  0.1772914300  0.3989267889 -0.0006459295  0.1583397347 -0.1289114731
[156] -0.0376900454  0.2269537833 -0.1409656065  0.3378417778  0.1928996776
[161] -0.1067804375 -0.1874182842  0.2110978578 -0.1483297062 -0.2188274556
[166]  0.3675977910 -0.2160206178  0.0572515670  0.0953990277  0.1346110048
[171] -0.0058439383  0.2969120012  0.1238190644  0.1055996669 -0.3769874530
[176] -0.1209174098  0.4191937318 -0.1196714992 -0.0795494330  0.2129335346
[181] -0.0584264260 -0.4160749514 -0.0525565054  0.0251304253  0.0477652549
[186]  0.4344279435 -0.3639824420  0.2687203627  0.0937171080 -0.1984057983
[191]  0.2146860306  0.1212423025  1.2366489517  0.0068021820  0.5605118137
[196]  0.4776154924 -0.3052055227 -0.2395241096 -0.7640154851 -0.0844087038
[201] -0.1554084310 -0.1882885430  0.2294387598  0.5593178894 -0.1858388976
[206] -0.3155234226 -0.2971331040  0.2286536364  0.0733112090 -0.2047135714
[211] -0.0446772638 -0.0854059614  0.2936851171 -0.0268922441 -0.3208243445
[216] -0.1868804577  0.0155516764 -0.5796789769  0.0760524738  0.0995081309
[221]  0.0507794010 -0.4993212630 -0.3511030585 -0.2677835369  0.4953655876
[226] -0.2702175719  0.4651889438 -0.1079095194  0.1806557899  0.2877488706
> 
> proc.time()
   user  system elapsed 
  5.030  17.761  29.292 

BufferedMatrix.Rcheck/tests/rawCalltesting.Rout


R Under development (unstable) (2024-01-16 r85808) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-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: 0x600000a800c0>
> .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: 0x600000a800c0>
> .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: 0x600000a800c0>
> .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: 0x600000a800c0>
> 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: 0x600000a94000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000a94000>
> .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: 0x600000a94000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000a94000>
> .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: 0x600000a94000>
> 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: 0x600000a84120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000a84120>
> .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: 0x600000a84120>
> 
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600000a84120>
> .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: 0x600000a84120>
> 
> .Call("R_bm_RowMode",P)
<pointer: 0x600000a84120>
> .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: 0x600000a84120>
> 
> .Call("R_bm_ColMode",P)
<pointer: 0x600000a84120>
> .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: 0x600000a84120>
> 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: 0x600000a90000>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600000a90000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000a90000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000a90000>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile10223746edc25" "BufferedMatrixFile10223debcf2e" 
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile10223746edc25" "BufferedMatrixFile10223debcf2e" 
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000ab8420>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000ab8420>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600000ab8420>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600000ab8420>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600000ab8420>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600000ab8420>
> .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: 0x600000aa0120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000aa0120>
> 
> .Call("R_bm_getSize",P)
[1] 10  2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600000aa0120>
> 
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600000aa0120>
> 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: 0x600000a94240>
> .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: 0x600000a94240>
> rm(P)
> 
> proc.time()
   user  system elapsed 
  0.584   0.213   0.855 

BufferedMatrix.Rcheck/tests/Rcodetesting.Rout


R Under development (unstable) (2024-01-16 r85808) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());

Attaching package: 'BufferedMatrix'

The following objects are masked from 'package:base':

    colMeans, colSums, rowMeans, rowSums

> 
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100   0
> buffer.dim(Temp)
[1] 1 1
> 
> 
> proc.time()
   user  system elapsed 
  0.583   0.140   0.762 

Example timings