Ben Bolstad
| Snapshot Date: 2018-04-11 16:45:18 -0400 (Wed, 11 Apr 2018) |
| URL: https://git.bioconductor.org/packages/BufferedMatrix |
| Branch: RELEASE_3_6 |
| Last Commit: 4631078 |
| Last Changed Date: 2017-10-30 12:39:19 -0400 (Mon, 30 Oct 2017) |
| Back to Multiple platform build/check report for BioC 3.6 |
|
This page was generated on 2018-04-12 13:32:17 -0400 (Thu, 12 Apr 2018).
| Package 165/1472 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||
| BufferedMatrix 1.42.0 Ben Bolstad
| malbec1 | Linux (Ubuntu 16.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||
| tokay1 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | | ||||||
| veracruz1 | OS X 10.11.6 El Capitan / x86_64 | OK | OK | [ OK ] | OK | |
| Package: BufferedMatrix |
| Version: 1.42.0 |
| Command: /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --no-vignettes --timings BufferedMatrix_1.42.0.tar.gz |
| StartedAt: 2018-04-12 01:10:06 -0400 (Thu, 12 Apr 2018) |
| EndedAt: 2018-04-12 01:10:39 -0400 (Thu, 12 Apr 2018) |
| EllapsedTime: 33.3 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --no-vignettes --timings BufferedMatrix_1.42.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck’
* using R version 3.4.4 (2018-03-15)
* using platform: x86_64-apple-darwin15.6.0 (64-bit)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.42.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... OK
* 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 ... NOTE
Warning: no function found corresponding to methods exports from ‘BufferedMatrix’ for: ‘coerce’, ‘show’
A namespace must be able to be loaded with just the base namespace
loaded: otherwise if the namespace gets loaded by a saved object, the
session will be unable to start.
Probably some imports need to be declared in the NAMESPACE file.
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... NOTE
Package in Depends field not imported from: ‘methods’
These packages need to be imported from (in the NAMESPACE file)
for when this namespace is loaded but not attached.
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... NOTE
NB: .First.lib is obsolete and will not be used in R >= 3.0.0
as.BufferedMatrix: warning in createBufferedMatrix(rows = dim(x)[1],
cols = dim(x)[2], bufferrows = bufferrows, buffercols = buffercols,
director = directory): partial argument match of 'director' to
'directory'
createBufferedMatrix: no visible global function definition for ‘new’
colApply,BufferedMatrix: no visible global function definition for
‘new’
duplicate,BufferedMatrix: no visible global function definition for
‘new’
rowApply,BufferedMatrix: no visible global function definition for
‘new’
subBufferedMatrix,BufferedMatrix: no visible global function definition
for ‘new’
Undefined global functions or variables:
new
Consider adding
importFrom("methods", "new")
to your NAMESPACE file (and ensure that your DESCRIPTION Imports field
contains 'methods').
* 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 ... OK
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking installed files from ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 4 NOTEs
See
‘/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
* installing *source* package ‘BufferedMatrix’ ...
** libs
clang -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -I/usr/local/include -fPIC -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -I/usr/local/include -fPIC -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 -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -I/usr/local/include -fPIC -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -I/usr/local/include -fPIC -Wall -g -O2 -c init_package.c -o init_package.o
clang++ -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -single_module -multiply_defined suppress -L/Library/Frameworks/R.framework/Resources/lib -L/usr/local/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 /Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/BufferedMatrix/libs
** R
** inst
** preparing 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
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 3.4.4 (2018-03-15) -- "Someone to Lean On"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin15.6.0 (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.331 0.060 0.379
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 3.4.4 (2018-03-15) -- "Someone to Lean On"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin15.6.0 (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 400646 21.4 750400 40.1 592000 31.7
Vcells 722398 5.6 1308461 10.0 1002163 7.7
>
>
>
>
> ##
> ## 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] "Thu Apr 12 01:10:28 2018"
> 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] "Thu Apr 12 01:10:28 2018"
>
>
> 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: 0x7f8dbcb0ea20>
>
>
>
> 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] "Thu Apr 12 01:10:30 2018"
> 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] "Thu Apr 12 01:10:30 2018"
>
> ColMode(tmp2)
<pointer: 0x7f8dbcb0ea20>
>
>
>
> ### 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,] 97.7812159 -1.8783312 -0.6692386 -0.5683364
[2,] 0.3658068 -1.1242566 0.6628609 0.1320353
[3,] -0.7770437 -0.2441641 -2.1696744 -0.4972014
[4,] -1.4399090 -0.2386567 -1.5064557 -0.5744913
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.6-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,] 97.7812159 1.8783312 0.6692386 0.5683364
[2,] 0.3658068 1.1242566 0.6628609 0.1320353
[3,] 0.7770437 0.2441641 2.1696744 0.4972014
[4,] 1.4399090 0.2386567 1.5064557 0.5744913
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.6-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,] 9.8884385 1.3705222 0.8180700 0.7538809
[2,] 0.6048197 1.0603096 0.8141627 0.3633666
[3,] 0.8815008 0.4941297 1.4729815 0.7051251
[4,] 1.1999621 0.4885250 1.2273776 0.7579520
>
> 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-3.6-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,] 221.66560 40.58355 33.84994 33.10715
[2,] 31.41400 36.72735 33.80449 28.76570
[3,] 34.59205 30.18546 41.89949 32.54845
[4,] 38.43953 30.12391 38.78023 33.15401
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x7f8db9d06830>
> exp(tmp5)
<pointer: 0x7f8db9d06830>
> log(tmp5,2)
<pointer: 0x7f8db9d06830>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 461.3679
> Min(tmp5)
[1] 53.35388
> mean(tmp5)
[1] 72.36306
> Sum(tmp5)
[1] 14472.61
> Var(tmp5)
[1] 832.7582
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.10424 69.09386 71.38286 69.31186 71.06670 72.29756 68.47820 72.12836
[9] 68.69619 69.07076
> rowSums(tmp5)
[1] 1842.085 1381.877 1427.657 1386.237 1421.334 1445.951 1369.564 1442.567
[9] 1373.924 1381.415
> rowVars(tmp5)
[1] 7609.66552 69.08663 78.34799 75.75831 70.54550 82.56488
[7] 66.35231 78.52614 67.15086 48.48087
> rowSd(tmp5)
[1] 87.233397 8.311837 8.851440 8.703925 8.399137 9.086522 8.145692
[8] 8.861498 8.194563 6.962821
> rowMax(tmp5)
[1] 461.36791 90.29501 87.20830 91.93601 86.20213 86.47303 84.63153
[8] 91.48393 80.32889 81.66150
> rowMin(tmp5)
[1] 61.33792 55.67578 56.69988 58.38060 58.87520 54.38896 56.53119 57.98046
[9] 53.35388 55.25531
>
> colMeans(tmp5)
[1] 111.11127 70.72807 68.88678 72.20015 70.79783 72.91566 65.15197
[8] 72.00118 72.12403 73.09370 67.01434 68.90989 66.93235 71.08283
[15] 68.46275 71.84894 71.21059 74.43492 68.75623 69.59769
> colSums(tmp5)
[1] 1111.1127 707.2807 688.8678 722.0015 707.9783 729.1566 651.5197
[8] 720.0118 721.2403 730.9370 670.1434 689.0989 669.3235 710.8283
[15] 684.6275 718.4894 712.1059 744.3492 687.5623 695.9769
> colVars(tmp5)
[1] 15225.47104 58.77428 91.17554 61.29768 109.75907 37.55701
[7] 27.59868 102.50241 28.49217 31.37683 44.35431 61.96822
[13] 42.98303 133.14118 67.34958 40.15404 79.23323 40.26331
[19] 81.95742 175.46357
> colSd(tmp5)
[1] 123.391536 7.666439 9.548588 7.829284 10.476596 6.128377
[7] 5.253445 10.124347 5.337806 5.601502 6.659903 7.871989
[13] 6.556145 11.538682 8.206679 6.336722 8.901305 6.345338
[19] 9.053034 13.246266
> colMax(tmp5)
[1] 461.36791 84.46935 87.20830 82.32739 91.93601 80.43263 72.63211
[8] 91.48393 78.17607 79.82877 79.88704 86.19246 75.84274 86.20213
[15] 79.48068 80.58707 86.23155 84.77267 81.14743 90.29501
> colMin(tmp5)
[1] 56.02156 62.69896 58.67529 59.87204 57.57836 61.11016 58.38060 55.25531
[9] 60.71498 63.78554 56.69988 57.98046 54.38896 56.33868 56.53119 63.50212
[17] 59.28237 66.11656 55.67578 53.35388
>
>
> ### 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] 92.10424 69.09386 71.38286 69.31186 71.06670 NA 68.47820 72.12836
[9] 68.69619 69.07076
> rowSums(tmp5)
[1] 1842.085 1381.877 1427.657 1386.237 1421.334 NA 1369.564 1442.567
[9] 1373.924 1381.415
> rowVars(tmp5)
[1] 7609.66552 69.08663 78.34799 75.75831 70.54550 81.23870
[7] 66.35231 78.52614 67.15086 48.48087
> rowSd(tmp5)
[1] 87.233397 8.311837 8.851440 8.703925 8.399137 9.013251 8.145692
[8] 8.861498 8.194563 6.962821
> rowMax(tmp5)
[1] 461.36791 90.29501 87.20830 91.93601 86.20213 NA 84.63153
[8] 91.48393 80.32889 81.66150
> rowMin(tmp5)
[1] 61.33792 55.67578 56.69988 58.38060 58.87520 NA 56.53119 57.98046
[9] 53.35388 55.25531
>
> colMeans(tmp5)
[1] 111.11127 70.72807 68.88678 72.20015 70.79783 72.91566 65.15197
[8] 72.00118 72.12403 73.09370 NA 68.90989 66.93235 71.08283
[15] 68.46275 71.84894 71.21059 74.43492 68.75623 69.59769
> colSums(tmp5)
[1] 1111.1127 707.2807 688.8678 722.0015 707.9783 729.1566 651.5197
[8] 720.0118 721.2403 730.9370 NA 689.0989 669.3235 710.8283
[15] 684.6275 718.4894 712.1059 744.3492 687.5623 695.9769
> colVars(tmp5)
[1] 15225.47104 58.77428 91.17554 61.29768 109.75907 37.55701
[7] 27.59868 102.50241 28.49217 31.37683 NA 61.96822
[13] 42.98303 133.14118 67.34958 40.15404 79.23323 40.26331
[19] 81.95742 175.46357
> colSd(tmp5)
[1] 123.391536 7.666439 9.548588 7.829284 10.476596 6.128377
[7] 5.253445 10.124347 5.337806 5.601502 NA 7.871989
[13] 6.556145 11.538682 8.206679 6.336722 8.901305 6.345338
[19] 9.053034 13.246266
> colMax(tmp5)
[1] 461.36791 84.46935 87.20830 82.32739 91.93601 80.43263 72.63211
[8] 91.48393 78.17607 79.82877 NA 86.19246 75.84274 86.20213
[15] 79.48068 80.58707 86.23155 84.77267 81.14743 90.29501
> colMin(tmp5)
[1] 56.02156 62.69896 58.67529 59.87204 57.57836 61.11016 58.38060 55.25531
[9] 60.71498 63.78554 NA 57.98046 54.38896 56.33868 56.53119 63.50212
[17] 59.28237 66.11656 55.67578 53.35388
>
> Max(tmp5,na.rm=TRUE)
[1] 461.3679
> Min(tmp5,na.rm=TRUE)
[1] 53.35388
> mean(tmp5,na.rm=TRUE)
[1] 72.41392
> Sum(tmp5,na.rm=TRUE)
[1] 14410.37
> Var(tmp5,na.rm=TRUE)
[1] 836.4441
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.10424 69.09386 71.38286 69.31186 71.06670 72.82680 68.47820 72.12836
[9] 68.69619 69.07076
> rowSums(tmp5,na.rm=TRUE)
[1] 1842.085 1381.877 1427.657 1386.237 1421.334 1383.709 1369.564 1442.567
[9] 1373.924 1381.415
> rowVars(tmp5,na.rm=TRUE)
[1] 7609.66552 69.08663 78.34799 75.75831 70.54550 81.23870
[7] 66.35231 78.52614 67.15086 48.48087
> rowSd(tmp5,na.rm=TRUE)
[1] 87.233397 8.311837 8.851440 8.703925 8.399137 9.013251 8.145692
[8] 8.861498 8.194563 6.962821
> rowMax(tmp5,na.rm=TRUE)
[1] 461.36791 90.29501 87.20830 91.93601 86.20213 86.47303 84.63153
[8] 91.48393 80.32889 81.66150
> rowMin(tmp5,na.rm=TRUE)
[1] 61.33792 55.67578 56.69988 58.38060 58.87520 54.38896 56.53119 57.98046
[9] 53.35388 55.25531
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.11127 70.72807 68.88678 72.20015 70.79783 72.91566 65.15197
[8] 72.00118 72.12403 73.09370 67.54460 68.90989 66.93235 71.08283
[15] 68.46275 71.84894 71.21059 74.43492 68.75623 69.59769
> colSums(tmp5,na.rm=TRUE)
[1] 1111.1127 707.2807 688.8678 722.0015 707.9783 729.1566 651.5197
[8] 720.0118 721.2403 730.9370 607.9014 689.0989 669.3235 710.8283
[15] 684.6275 718.4894 712.1059 744.3492 687.5623 695.9769
> colVars(tmp5,na.rm=TRUE)
[1] 15225.47104 58.77428 91.17554 61.29768 109.75907 37.55701
[7] 27.59868 102.50241 28.49217 31.37683 46.73537 61.96822
[13] 42.98303 133.14118 67.34958 40.15404 79.23323 40.26331
[19] 81.95742 175.46357
> colSd(tmp5,na.rm=TRUE)
[1] 123.391536 7.666439 9.548588 7.829284 10.476596 6.128377
[7] 5.253445 10.124347 5.337806 5.601502 6.836327 7.871989
[13] 6.556145 11.538682 8.206679 6.336722 8.901305 6.345338
[19] 9.053034 13.246266
> colMax(tmp5,na.rm=TRUE)
[1] 461.36791 84.46935 87.20830 82.32739 91.93601 80.43263 72.63211
[8] 91.48393 78.17607 79.82877 79.88704 86.19246 75.84274 86.20213
[15] 79.48068 80.58707 86.23155 84.77267 81.14743 90.29501
> colMin(tmp5,na.rm=TRUE)
[1] 56.02156 62.69896 58.67529 59.87204 57.57836 61.11016 58.38060 55.25531
[9] 60.71498 63.78554 56.69988 57.98046 54.38896 56.33868 56.53119 63.50212
[17] 59.28237 66.11656 55.67578 53.35388
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.10424 69.09386 71.38286 69.31186 71.06670 NaN 68.47820 72.12836
[9] 68.69619 69.07076
> rowSums(tmp5,na.rm=TRUE)
[1] 1842.085 1381.877 1427.657 1386.237 1421.334 0.000 1369.564 1442.567
[9] 1373.924 1381.415
> rowVars(tmp5,na.rm=TRUE)
[1] 7609.66552 69.08663 78.34799 75.75831 70.54550 NA
[7] 66.35231 78.52614 67.15086 48.48087
> rowSd(tmp5,na.rm=TRUE)
[1] 87.233397 8.311837 8.851440 8.703925 8.399137 NA 8.145692
[8] 8.861498 8.194563 6.962821
> rowMax(tmp5,na.rm=TRUE)
[1] 461.36791 90.29501 87.20830 91.93601 86.20213 NA 84.63153
[8] 91.48393 80.32889 81.66150
> rowMin(tmp5,na.rm=TRUE)
[1] 61.33792 55.67578 56.69988 58.38060 58.87520 NA 56.53119 57.98046
[9] 53.35388 55.25531
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.84885 69.88660 68.39807 71.07490 70.45854 73.37655 64.32085
[8] 72.66903 71.89874 72.34536 NaN 69.08483 68.32606 70.24846
[15] 69.58144 71.36764 69.54160 74.85888 67.73771 70.83803
> colSums(tmp5,na.rm=TRUE)
[1] 1024.6397 628.9794 615.5827 639.6741 634.1268 660.3890 578.8876
[8] 654.0213 647.0887 651.1082 0.0000 621.7635 614.9346 632.2361
[15] 626.2330 642.3087 625.8744 673.7299 609.6394 637.5423
> colVars(tmp5,na.rm=TRUE)
[1] 17044.34341 58.15524 99.88566 54.71531 122.18384 39.86195
[7] 23.27735 110.29745 31.48270 28.99877 NA 69.36995
[13] 26.50361 141.95181 61.68912 42.56717 57.79999 43.27413
[19] 80.53167 180.08903
> colSd(tmp5,na.rm=TRUE)
[1] 130.553987 7.625959 9.994281 7.396980 11.053680 6.313632
[7] 4.824660 10.502259 5.610944 5.385051 NA 8.328862
[13] 5.148166 11.914353 7.854242 6.524352 7.602631 6.578307
[19] 8.973944 13.419725
> colMax(tmp5,na.rm=TRUE)
[1] 461.36791 84.46935 87.20830 81.66150 91.93601 80.43263 70.85920
[8] 91.48393 78.17607 78.56815 -Inf 86.19246 75.84274 86.20213
[15] 79.48068 80.58707 82.44117 84.77267 81.14743 90.29501
> colMin(tmp5,na.rm=TRUE)
[1] 56.02156 62.69896 58.67529 59.87204 57.57836 61.11016 58.38060 55.25531
[9] 60.71498 63.78554 Inf 57.98046 61.03500 56.33868 56.53119 63.50212
[17] 59.28237 66.11656 55.67578 53.35388
>
>
>
>
> 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] 159.0335 236.4528 146.4398 335.8111 194.0143 261.1082 352.1552 170.1634
[9] 209.6251 173.4408
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 159.0335 236.4528 146.4398 335.8111 194.0143 261.1082 352.1552 170.1634
[9] 209.6251 173.4408
>
>
>
> 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] 0.000000e+00 2.842171e-14 0.000000e+00 0.000000e+00 -5.684342e-14
[6] -1.705303e-13 0.000000e+00 -1.136868e-13 5.684342e-14 -8.526513e-14
[11] -1.705303e-13 2.273737e-13 8.526513e-14 0.000000e+00 0.000000e+00
[16] 2.557954e-13 0.000000e+00 2.842171e-14 1.136868e-13 8.526513e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
3 2
5 6
9 10
4 3
2 15
9 2
10 8
8 12
9 7
10 11
1 9
10 20
2 6
5 19
5 1
8 3
2 9
2 12
2 5
3 1
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] 2.590037
> Min(tmp)
[1] -1.966184
> mean(tmp)
[1] 0.03919081
> Sum(tmp)
[1] 3.919081
> Var(tmp)
[1] 0.6955838
>
> rowMeans(tmp)
[1] 0.03919081
> rowSums(tmp)
[1] 3.919081
> rowVars(tmp)
[1] 0.6955838
> rowSd(tmp)
[1] 0.8340167
> rowMax(tmp)
[1] 2.590037
> rowMin(tmp)
[1] -1.966184
>
> colMeans(tmp)
[1] 0.896048775 1.712847441 -1.853282038 1.027119791 0.409829150
[6] 0.212010263 0.412780401 0.408802813 -0.037605871 0.524423770
[11] -0.041436951 0.144455256 -1.756946668 0.681600963 -0.099394492
[16] 0.360305468 -1.347206355 1.101638196 -0.034133578 0.512450148
[21] -0.844776351 -0.266365289 0.559200969 -0.062126011 -0.428158342
[26] 2.590037474 0.477946368 1.505726868 -0.416905616 0.550727328
[31] -0.872776847 0.164194227 -0.238244931 0.184348190 0.941443838
[36] 0.974196460 -1.966183526 0.798583993 1.093344409 0.003524626
[41] -0.153658189 1.355079225 -0.336923403 -0.378318248 -0.473499422
[46] -0.647786044 -1.560182829 -1.234849251 -1.419694160 -0.490687548
[51] -0.669991686 -0.821782983 -0.926514620 -0.548902661 -0.076001460
[56] 0.987609921 -0.724925244 0.308843311 1.155445592 -0.190938931
[61] 0.148917719 0.328385173 0.609247236 0.674773432 0.050797804
[66] -0.085293431 0.604843351 0.224816821 -0.177030831 1.878996409
[71] -0.512229946 0.095891202 0.560740939 -1.478236279 0.524306978
[76] -0.098487693 -0.385948380 0.610094022 -0.810308068 -0.268481769
[81] -0.096698096 0.732751595 0.374009577 1.313377143 -0.265295915
[86] -0.955305965 -1.278401204 0.593845697 -1.106082802 -0.230498681
[91] -0.205467206 0.068662669 0.510933475 0.848359754 -0.227727830
[96] 0.064220935 -0.242674538 1.275193036 -0.070040198 -0.814240716
> colSums(tmp)
[1] 0.896048775 1.712847441 -1.853282038 1.027119791 0.409829150
[6] 0.212010263 0.412780401 0.408802813 -0.037605871 0.524423770
[11] -0.041436951 0.144455256 -1.756946668 0.681600963 -0.099394492
[16] 0.360305468 -1.347206355 1.101638196 -0.034133578 0.512450148
[21] -0.844776351 -0.266365289 0.559200969 -0.062126011 -0.428158342
[26] 2.590037474 0.477946368 1.505726868 -0.416905616 0.550727328
[31] -0.872776847 0.164194227 -0.238244931 0.184348190 0.941443838
[36] 0.974196460 -1.966183526 0.798583993 1.093344409 0.003524626
[41] -0.153658189 1.355079225 -0.336923403 -0.378318248 -0.473499422
[46] -0.647786044 -1.560182829 -1.234849251 -1.419694160 -0.490687548
[51] -0.669991686 -0.821782983 -0.926514620 -0.548902661 -0.076001460
[56] 0.987609921 -0.724925244 0.308843311 1.155445592 -0.190938931
[61] 0.148917719 0.328385173 0.609247236 0.674773432 0.050797804
[66] -0.085293431 0.604843351 0.224816821 -0.177030831 1.878996409
[71] -0.512229946 0.095891202 0.560740939 -1.478236279 0.524306978
[76] -0.098487693 -0.385948380 0.610094022 -0.810308068 -0.268481769
[81] -0.096698096 0.732751595 0.374009577 1.313377143 -0.265295915
[86] -0.955305965 -1.278401204 0.593845697 -1.106082802 -0.230498681
[91] -0.205467206 0.068662669 0.510933475 0.848359754 -0.227727830
[96] 0.064220935 -0.242674538 1.275193036 -0.070040198 -0.814240716
> 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] 0.896048775 1.712847441 -1.853282038 1.027119791 0.409829150
[6] 0.212010263 0.412780401 0.408802813 -0.037605871 0.524423770
[11] -0.041436951 0.144455256 -1.756946668 0.681600963 -0.099394492
[16] 0.360305468 -1.347206355 1.101638196 -0.034133578 0.512450148
[21] -0.844776351 -0.266365289 0.559200969 -0.062126011 -0.428158342
[26] 2.590037474 0.477946368 1.505726868 -0.416905616 0.550727328
[31] -0.872776847 0.164194227 -0.238244931 0.184348190 0.941443838
[36] 0.974196460 -1.966183526 0.798583993 1.093344409 0.003524626
[41] -0.153658189 1.355079225 -0.336923403 -0.378318248 -0.473499422
[46] -0.647786044 -1.560182829 -1.234849251 -1.419694160 -0.490687548
[51] -0.669991686 -0.821782983 -0.926514620 -0.548902661 -0.076001460
[56] 0.987609921 -0.724925244 0.308843311 1.155445592 -0.190938931
[61] 0.148917719 0.328385173 0.609247236 0.674773432 0.050797804
[66] -0.085293431 0.604843351 0.224816821 -0.177030831 1.878996409
[71] -0.512229946 0.095891202 0.560740939 -1.478236279 0.524306978
[76] -0.098487693 -0.385948380 0.610094022 -0.810308068 -0.268481769
[81] -0.096698096 0.732751595 0.374009577 1.313377143 -0.265295915
[86] -0.955305965 -1.278401204 0.593845697 -1.106082802 -0.230498681
[91] -0.205467206 0.068662669 0.510933475 0.848359754 -0.227727830
[96] 0.064220935 -0.242674538 1.275193036 -0.070040198 -0.814240716
> colMin(tmp)
[1] 0.896048775 1.712847441 -1.853282038 1.027119791 0.409829150
[6] 0.212010263 0.412780401 0.408802813 -0.037605871 0.524423770
[11] -0.041436951 0.144455256 -1.756946668 0.681600963 -0.099394492
[16] 0.360305468 -1.347206355 1.101638196 -0.034133578 0.512450148
[21] -0.844776351 -0.266365289 0.559200969 -0.062126011 -0.428158342
[26] 2.590037474 0.477946368 1.505726868 -0.416905616 0.550727328
[31] -0.872776847 0.164194227 -0.238244931 0.184348190 0.941443838
[36] 0.974196460 -1.966183526 0.798583993 1.093344409 0.003524626
[41] -0.153658189 1.355079225 -0.336923403 -0.378318248 -0.473499422
[46] -0.647786044 -1.560182829 -1.234849251 -1.419694160 -0.490687548
[51] -0.669991686 -0.821782983 -0.926514620 -0.548902661 -0.076001460
[56] 0.987609921 -0.724925244 0.308843311 1.155445592 -0.190938931
[61] 0.148917719 0.328385173 0.609247236 0.674773432 0.050797804
[66] -0.085293431 0.604843351 0.224816821 -0.177030831 1.878996409
[71] -0.512229946 0.095891202 0.560740939 -1.478236279 0.524306978
[76] -0.098487693 -0.385948380 0.610094022 -0.810308068 -0.268481769
[81] -0.096698096 0.732751595 0.374009577 1.313377143 -0.265295915
[86] -0.955305965 -1.278401204 0.593845697 -1.106082802 -0.230498681
[91] -0.205467206 0.068662669 0.510933475 0.848359754 -0.227727830
[96] 0.064220935 -0.242674538 1.275193036 -0.070040198 -0.814240716
> colMedians(tmp)
[1] 0.896048775 1.712847441 -1.853282038 1.027119791 0.409829150
[6] 0.212010263 0.412780401 0.408802813 -0.037605871 0.524423770
[11] -0.041436951 0.144455256 -1.756946668 0.681600963 -0.099394492
[16] 0.360305468 -1.347206355 1.101638196 -0.034133578 0.512450148
[21] -0.844776351 -0.266365289 0.559200969 -0.062126011 -0.428158342
[26] 2.590037474 0.477946368 1.505726868 -0.416905616 0.550727328
[31] -0.872776847 0.164194227 -0.238244931 0.184348190 0.941443838
[36] 0.974196460 -1.966183526 0.798583993 1.093344409 0.003524626
[41] -0.153658189 1.355079225 -0.336923403 -0.378318248 -0.473499422
[46] -0.647786044 -1.560182829 -1.234849251 -1.419694160 -0.490687548
[51] -0.669991686 -0.821782983 -0.926514620 -0.548902661 -0.076001460
[56] 0.987609921 -0.724925244 0.308843311 1.155445592 -0.190938931
[61] 0.148917719 0.328385173 0.609247236 0.674773432 0.050797804
[66] -0.085293431 0.604843351 0.224816821 -0.177030831 1.878996409
[71] -0.512229946 0.095891202 0.560740939 -1.478236279 0.524306978
[76] -0.098487693 -0.385948380 0.610094022 -0.810308068 -0.268481769
[81] -0.096698096 0.732751595 0.374009577 1.313377143 -0.265295915
[86] -0.955305965 -1.278401204 0.593845697 -1.106082802 -0.230498681
[91] -0.205467206 0.068662669 0.510933475 0.848359754 -0.227727830
[96] 0.064220935 -0.242674538 1.275193036 -0.070040198 -0.814240716
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.8960488 1.712847 -1.853282 1.02712 0.4098291 0.2120103 0.4127804
[2,] 0.8960488 1.712847 -1.853282 1.02712 0.4098291 0.2120103 0.4127804
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.4088028 -0.03760587 0.5244238 -0.04143695 0.1444553 -1.756947 0.681601
[2,] 0.4088028 -0.03760587 0.5244238 -0.04143695 0.1444553 -1.756947 0.681601
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.09939449 0.3603055 -1.347206 1.101638 -0.03413358 0.5124501 -0.8447764
[2,] -0.09939449 0.3603055 -1.347206 1.101638 -0.03413358 0.5124501 -0.8447764
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.2663653 0.559201 -0.06212601 -0.4281583 2.590037 0.4779464 1.505727
[2,] -0.2663653 0.559201 -0.06212601 -0.4281583 2.590037 0.4779464 1.505727
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.4169056 0.5507273 -0.8727768 0.1641942 -0.2382449 0.1843482 0.9414438
[2,] -0.4169056 0.5507273 -0.8727768 0.1641942 -0.2382449 0.1843482 0.9414438
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.9741965 -1.966184 0.798584 1.093344 0.003524626 -0.1536582 1.355079
[2,] 0.9741965 -1.966184 0.798584 1.093344 0.003524626 -0.1536582 1.355079
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.3369234 -0.3783182 -0.4734994 -0.647786 -1.560183 -1.234849 -1.419694
[2,] -0.3369234 -0.3783182 -0.4734994 -0.647786 -1.560183 -1.234849 -1.419694
[,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.4906875 -0.6699917 -0.821783 -0.9265146 -0.5489027 -0.07600146
[2,] -0.4906875 -0.6699917 -0.821783 -0.9265146 -0.5489027 -0.07600146
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] 0.9876099 -0.7249252 0.3088433 1.155446 -0.1909389 0.1489177 0.3283852
[2,] 0.9876099 -0.7249252 0.3088433 1.155446 -0.1909389 0.1489177 0.3283852
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 0.6092472 0.6747734 0.0507978 -0.08529343 0.6048434 0.2248168 -0.1770308
[2,] 0.6092472 0.6747734 0.0507978 -0.08529343 0.6048434 0.2248168 -0.1770308
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 1.878996 -0.5122299 0.0958912 0.5607409 -1.478236 0.524307 -0.09848769
[2,] 1.878996 -0.5122299 0.0958912 0.5607409 -1.478236 0.524307 -0.09848769
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -0.3859484 0.610094 -0.8103081 -0.2684818 -0.0966981 0.7327516 0.3740096
[2,] -0.3859484 0.610094 -0.8103081 -0.2684818 -0.0966981 0.7327516 0.3740096
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 1.313377 -0.2652959 -0.955306 -1.278401 0.5938457 -1.106083 -0.2304987
[2,] 1.313377 -0.2652959 -0.955306 -1.278401 0.5938457 -1.106083 -0.2304987
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -0.2054672 0.06866267 0.5109335 0.8483598 -0.2277278 0.06422094 -0.2426745
[2,] -0.2054672 0.06866267 0.5109335 0.8483598 -0.2277278 0.06422094 -0.2426745
[,98] [,99] [,100]
[1,] 1.275193 -0.0700402 -0.8142407
[2,] 1.275193 -0.0700402 -0.8142407
>
>
> Max(tmp2)
[1] 2.535566
> Min(tmp2)
[1] -2.795231
> mean(tmp2)
[1] -0.04046953
> Sum(tmp2)
[1] -4.046953
> Var(tmp2)
[1] 0.962633
>
> rowMeans(tmp2)
[1] 0.838359258 -0.144687815 -1.247660630 -0.492959520 -0.107116293
[6] 0.249806239 -0.573593522 0.779443748 -0.462952541 1.379609063
[11] 0.841958575 0.308875322 -0.678213519 -0.071832051 -0.687506960
[16] -0.613647830 0.026767860 -0.644844065 0.318815544 0.799892595
[21] -0.367854066 1.991197399 -1.272177265 0.013753982 0.659169287
[26] 0.800642553 -0.919840092 -0.009428884 -1.008109953 0.149673006
[31] 2.535566410 -0.766342324 -0.439022510 -0.239899713 -0.350577960
[36] -0.667965206 -0.895248996 -0.702213474 -2.408846306 0.506890784
[41] 2.129149893 1.171321388 1.326099305 -0.449075477 -2.795230885
[46] -0.294050194 -0.365957128 -0.103774257 0.774591392 1.819722961
[51] 0.419283242 -0.502072225 0.326888789 -1.098263292 -0.433813908
[56] 0.567958237 1.203556337 0.598756403 -0.171101461 0.208530866
[61] 0.351375846 1.693766689 -1.330352167 1.238818266 -0.335547574
[66] -0.136900412 1.584790023 0.236031160 -0.755785839 -0.039200565
[71] -0.810142568 -0.254293892 -0.211062456 0.370775301 -1.168936518
[76] -2.639610920 0.276821390 0.702566826 -0.020375694 0.480995487
[81] 1.622395770 0.301117085 -0.100438509 0.110079089 -2.139376005
[86] 0.827497808 0.087319461 -0.518310078 -0.513827129 -0.002051534
[91] -0.586164165 -2.240091770 0.078559655 -0.312529112 1.164570404
[96] -1.297082959 -0.898952978 -0.567697110 0.961976735 -0.018080128
> rowSums(tmp2)
[1] 0.838359258 -0.144687815 -1.247660630 -0.492959520 -0.107116293
[6] 0.249806239 -0.573593522 0.779443748 -0.462952541 1.379609063
[11] 0.841958575 0.308875322 -0.678213519 -0.071832051 -0.687506960
[16] -0.613647830 0.026767860 -0.644844065 0.318815544 0.799892595
[21] -0.367854066 1.991197399 -1.272177265 0.013753982 0.659169287
[26] 0.800642553 -0.919840092 -0.009428884 -1.008109953 0.149673006
[31] 2.535566410 -0.766342324 -0.439022510 -0.239899713 -0.350577960
[36] -0.667965206 -0.895248996 -0.702213474 -2.408846306 0.506890784
[41] 2.129149893 1.171321388 1.326099305 -0.449075477 -2.795230885
[46] -0.294050194 -0.365957128 -0.103774257 0.774591392 1.819722961
[51] 0.419283242 -0.502072225 0.326888789 -1.098263292 -0.433813908
[56] 0.567958237 1.203556337 0.598756403 -0.171101461 0.208530866
[61] 0.351375846 1.693766689 -1.330352167 1.238818266 -0.335547574
[66] -0.136900412 1.584790023 0.236031160 -0.755785839 -0.039200565
[71] -0.810142568 -0.254293892 -0.211062456 0.370775301 -1.168936518
[76] -2.639610920 0.276821390 0.702566826 -0.020375694 0.480995487
[81] 1.622395770 0.301117085 -0.100438509 0.110079089 -2.139376005
[86] 0.827497808 0.087319461 -0.518310078 -0.513827129 -0.002051534
[91] -0.586164165 -2.240091770 0.078559655 -0.312529112 1.164570404
[96] -1.297082959 -0.898952978 -0.567697110 0.961976735 -0.018080128
> 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] 0.838359258 -0.144687815 -1.247660630 -0.492959520 -0.107116293
[6] 0.249806239 -0.573593522 0.779443748 -0.462952541 1.379609063
[11] 0.841958575 0.308875322 -0.678213519 -0.071832051 -0.687506960
[16] -0.613647830 0.026767860 -0.644844065 0.318815544 0.799892595
[21] -0.367854066 1.991197399 -1.272177265 0.013753982 0.659169287
[26] 0.800642553 -0.919840092 -0.009428884 -1.008109953 0.149673006
[31] 2.535566410 -0.766342324 -0.439022510 -0.239899713 -0.350577960
[36] -0.667965206 -0.895248996 -0.702213474 -2.408846306 0.506890784
[41] 2.129149893 1.171321388 1.326099305 -0.449075477 -2.795230885
[46] -0.294050194 -0.365957128 -0.103774257 0.774591392 1.819722961
[51] 0.419283242 -0.502072225 0.326888789 -1.098263292 -0.433813908
[56] 0.567958237 1.203556337 0.598756403 -0.171101461 0.208530866
[61] 0.351375846 1.693766689 -1.330352167 1.238818266 -0.335547574
[66] -0.136900412 1.584790023 0.236031160 -0.755785839 -0.039200565
[71] -0.810142568 -0.254293892 -0.211062456 0.370775301 -1.168936518
[76] -2.639610920 0.276821390 0.702566826 -0.020375694 0.480995487
[81] 1.622395770 0.301117085 -0.100438509 0.110079089 -2.139376005
[86] 0.827497808 0.087319461 -0.518310078 -0.513827129 -0.002051534
[91] -0.586164165 -2.240091770 0.078559655 -0.312529112 1.164570404
[96] -1.297082959 -0.898952978 -0.567697110 0.961976735 -0.018080128
> rowMin(tmp2)
[1] 0.838359258 -0.144687815 -1.247660630 -0.492959520 -0.107116293
[6] 0.249806239 -0.573593522 0.779443748 -0.462952541 1.379609063
[11] 0.841958575 0.308875322 -0.678213519 -0.071832051 -0.687506960
[16] -0.613647830 0.026767860 -0.644844065 0.318815544 0.799892595
[21] -0.367854066 1.991197399 -1.272177265 0.013753982 0.659169287
[26] 0.800642553 -0.919840092 -0.009428884 -1.008109953 0.149673006
[31] 2.535566410 -0.766342324 -0.439022510 -0.239899713 -0.350577960
[36] -0.667965206 -0.895248996 -0.702213474 -2.408846306 0.506890784
[41] 2.129149893 1.171321388 1.326099305 -0.449075477 -2.795230885
[46] -0.294050194 -0.365957128 -0.103774257 0.774591392 1.819722961
[51] 0.419283242 -0.502072225 0.326888789 -1.098263292 -0.433813908
[56] 0.567958237 1.203556337 0.598756403 -0.171101461 0.208530866
[61] 0.351375846 1.693766689 -1.330352167 1.238818266 -0.335547574
[66] -0.136900412 1.584790023 0.236031160 -0.755785839 -0.039200565
[71] -0.810142568 -0.254293892 -0.211062456 0.370775301 -1.168936518
[76] -2.639610920 0.276821390 0.702566826 -0.020375694 0.480995487
[81] 1.622395770 0.301117085 -0.100438509 0.110079089 -2.139376005
[86] 0.827497808 0.087319461 -0.518310078 -0.513827129 -0.002051534
[91] -0.586164165 -2.240091770 0.078559655 -0.312529112 1.164570404
[96] -1.297082959 -0.898952978 -0.567697110 0.961976735 -0.018080128
>
> colMeans(tmp2)
[1] -0.04046953
> colSums(tmp2)
[1] -4.046953
> colVars(tmp2)
[1] 0.962633
> colSd(tmp2)
[1] 0.9811386
> colMax(tmp2)
[1] 2.535566
> colMin(tmp2)
[1] -2.795231
> colMedians(tmp2)
[1] -0.08613528
> colRanges(tmp2)
[,1]
[1,] -2.795231
[2,] 2.535566
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.7361696 2.0187598 -2.0329841 -1.3529840 -11.7396184 -4.4762796
[7] 0.7446427 -3.6750511 -2.4056705 -0.5686555
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.85853215
[2,] -0.43631114
[3,] 0.01014676
[4,] 0.37222170
[5,] 1.37084999
>
> rowApply(tmp,sum)
[1] -2.3781317 -0.4736017 -8.4368473 -2.9462401 -3.8739694 0.2616084
[7] -1.9992801 2.1864692 -4.6422300 -0.4494486
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 6 4 4 4 10 9 7 5 6 6
[2,] 5 9 10 5 3 6 3 4 10 10
[3,] 10 8 1 10 6 7 6 6 7 1
[4,] 3 1 7 8 9 10 5 9 3 2
[5,] 2 3 9 1 2 1 8 1 2 3
[6,] 7 7 3 2 8 3 4 7 1 4
[7,] 4 10 2 7 4 5 9 8 9 7
[8,] 8 2 6 9 1 4 2 3 4 8
[9,] 9 6 8 3 7 8 1 2 8 5
[10,] 1 5 5 6 5 2 10 10 5 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.1085212 0.5155605 0.7063328 0.7050758 -1.4217747 1.3362469
[7] 2.1442587 0.9917600 -0.2679717 0.2308818 0.5431408 -1.4628295
[13] -1.4384834 -0.6204181 3.7982459 3.8269809 4.5360838 -0.3622376
[19] -3.4995537 -1.2217891
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.3654361
[2,] -0.8705091
[3,] -0.0985044
[4,] 1.5604543
[5,] 2.8825165
>
> rowApply(tmp,sum)
[1] -1.201464 -3.796849 7.127649 6.000855 3.017840
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 3 13 17 20 1
[2,] 18 5 1 15 11
[3,] 12 11 16 11 4
[4,] 15 18 15 3 10
[5,] 2 9 10 9 12
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.8705091 0.9970749 0.1423792 0.4516297 -0.88850402 -0.3620050
[2,] -0.0985044 -0.6753532 -0.1175945 0.7492905 -0.52138413 -0.5520356
[3,] 1.5604543 -0.8323111 1.0706973 0.6480950 -0.08892457 -0.5053202
[4,] 2.8825165 0.8388327 0.4550766 -1.2397159 -0.13022970 1.3674915
[5,] -1.3654361 0.1873173 -0.8442259 0.0957764 0.20726769 1.3881162
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.6077365 0.1849255 -0.8117871 -0.4441524 -0.1789406 -0.1611566
[2,] 0.1093953 -1.0653182 -0.6162324 -0.1030120 0.5448070 -1.1075685
[3,] 2.2197979 0.3762247 -0.3447608 0.5441378 0.4622804 -0.4634893
[4,] -0.6864014 -0.3897952 2.6768226 -0.6127979 -1.5446734 0.6003938
[5,] -0.1062696 1.8857231 -1.1720139 0.8467063 1.2596674 -0.3310090
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.3555260 1.2605271 0.3290676 -0.510260694 0.76783119 -0.69527287
[2,] -0.7505804 -0.3197530 0.8419878 0.006949206 0.95687265 0.49960572
[3,] -0.7868118 -0.1273291 0.5232555 1.600482949 3.05151014 -0.58933519
[4,] -1.7746730 -0.5971992 1.6881751 1.281762712 -0.20843813 0.04834923
[5,] 0.5180558 -0.8366639 0.4157599 1.448046712 -0.03169204 0.37441555
[,19] [,20]
[1,] -1.8065044 -0.56906838
[2,] -0.5511195 -1.02730151
[3,] -0.8006354 -0.39036946
[4,] 0.5069149 0.83844346
[5,] -0.8482094 -0.07349322
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.6-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-3.6-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 644 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 558 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.6-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 -0.1698641 2.25908 1.700553 0.1764344 -1.46221 0.2955077 0.7108774
col8 col9 col10 col11 col12 col13 col14
row1 0.5457724 -1.002212 -1.826702 -0.4728517 -1.905608 -0.3525888 -0.545446
col15 col16 col17 col18 col19 col20
row1 -0.8464497 -1.624757 -0.3784619 -1.035745 0.5350151 0.4068957
> tmp[,"col10"]
col10
row1 -1.826701862
row2 0.004998823
row3 -0.263799396
row4 -0.110357333
row5 0.098792408
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.1698641 2.2590800 1.7005533 0.1764344 -1.462210 0.2955077 0.7108774
row5 -1.2189511 -0.6417032 0.9081926 -0.7359549 2.195868 -1.4707095 -0.6152910
col8 col9 col10 col11 col12 col13
row1 0.5457724 -1.0022120 -1.82670186 -0.4728517 -1.905608 -0.3525888
row5 -1.4139787 0.6058675 0.09879241 -1.2274960 1.337708 -0.1526020
col14 col15 col16 col17 col18 col19 col20
row1 -0.545446 -0.8464497 -1.6247567 -0.3784619 -1.0357450 0.5350151 0.4068957
row5 -1.263972 0.2450051 0.3461861 2.5928330 0.9582051 0.8304592 0.9450485
> tmp[,c("col6","col20")]
col6 col20
row1 0.29550767 0.40689575
row2 0.65957014 -1.32371057
row3 0.63285311 -0.61437963
row4 0.05021991 -0.01743781
row5 -1.47070950 0.94504846
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.2955077 0.4068957
row5 -1.4707095 0.9450485
>
>
>
>
> 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 48.76343 50.8156 50.56734 50.01987 51.59103 106.2159 48.63481 49.72179
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.6131 50.60781 50.96616 52.71379 51.25875 49.91762 49.61067 50.50402
col17 col18 col19 col20
row1 49.63249 51.01247 49.74683 105.4333
> tmp[,"col10"]
col10
row1 50.60781
row2 30.70664
row3 29.20898
row4 30.03078
row5 50.46528
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.76343 50.81560 50.56734 50.01987 51.59103 106.2159 48.63481 49.72179
row5 49.47363 50.75543 49.53279 49.78808 49.87917 105.2233 50.05650 49.81294
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.61310 50.60781 50.96616 52.71379 51.25875 49.91762 49.61067 50.50402
row5 51.35043 50.46528 50.00566 49.13526 49.70929 50.08563 49.99763 48.18047
col17 col18 col19 col20
row1 49.63249 51.01247 49.74683 105.4333
row5 49.74003 49.79043 50.56751 105.8619
> tmp[,c("col6","col20")]
col6 col20
row1 106.21594 105.43328
row2 75.15332 73.67189
row3 72.71943 75.48872
row4 75.62774 75.66506
row5 105.22327 105.86189
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.2159 105.4333
row5 105.2233 105.8619
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.2159 105.4333
row5 105.2233 105.8619
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.9584331
[2,] 1.2162461
[3,] -0.6263415
[4,] 0.9990860
[5,] 0.5500561
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.5203118 -0.2986721
[2,] 0.9722900 0.5322498
[3,] -0.1675745 1.1930267
[4,] -0.9954921 -0.5814914
[5,] -1.7963077 -0.2643167
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.3406079 -0.5989864
[2,] 1.3699477 -0.0535281
[3,] -0.6295580 0.2312536
[4,] -1.2973703 -1.5599605
[5,] -0.6594747 1.7261684
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.3406079
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.3406079
[2,] 1.3699477
>
>
>
> 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 -0.1375269 -0.9907649 -1.0548778 -0.931438 -0.2584585 0.3112933
row1 0.4171530 -0.6568405 -0.1455673 1.105656 -0.9749489 -0.6634518
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.05054088 1.2189305 1.5160184 -0.4610972 0.5367708 0.7594679
row1 -1.03171867 0.2706551 0.5986037 0.4845208 -1.2712864 -1.2568203
[,13] [,14] [,15] [,16] [,17] [,18]
row3 -2.1860285 0.3174410 -0.6174318 0.828377 -1.4855702 -0.8883978
row1 -0.3348751 -0.1384401 1.3240166 1.451058 -0.5307702 0.3595560
[,19] [,20]
row3 -0.07524667 -0.157345
row1 0.14238430 -1.001296
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6]
row2 -0.7230813 -0.1617093 -0.4702508 0.01713954 -0.5164873 -0.5141303
[,7] [,8] [,9] [,10]
row2 0.1251291 0.5749143 0.03523805 -1.068626
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.8402937 -0.2795535 -0.5424386 -2.020344 -0.7628825 -1.177353 -0.2260681
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.9980972 0.1184532 0.1664307 -1.201399 -0.7392467 1.104942 0.1754503
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.5007124 0.1899512 0.4623083 0.429871 1.723687 -1.21218
>
>
> 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: 0x7f8dbca48320>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BMb4ef1285772f"
[2] "/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BMb4ef7853b828"
[3] "/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BMb4ef405f87cf"
[4] "/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BMb4ef3fcd480d"
[5] "/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BMb4ef3e356e34"
[6] "/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BMb4ef25d637d4"
[7] "/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BMb4ef12eb52b4"
[8] "/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BMb4ef1782b120"
[9] "/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BMb4ef53ab7ef"
[10] "/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BMb4ef5201ae97"
[11] "/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BMb4ef6c6d6590"
[12] "/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BMb4ef227088d"
[13] "/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BMb4ef50a26215"
[14] "/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BMb4ef54d57a0e"
[15] "/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BMb4efb4058a5"
>
>
> ### 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: 0x7f8db9c37510>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x7f8db9c37510>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x7f8db9c37510>
> rowMedians(tmp)
[1] 0.608261897 0.531784012 0.277849336 0.062282056 0.023944173
[6] -0.336121008 -0.034042223 -0.056480061 -0.128460797 -0.242443902
[11] 0.102298205 -0.349883696 0.441319196 0.425682030 0.448024577
[16] -0.186801346 0.070343824 -0.309555993 -0.195102843 0.239392475
[21] -0.483110409 -0.254160304 -0.079886115 0.222685824 0.055451584
[26] 0.065091371 -0.295404284 0.301257955 -0.211090313 0.068311148
[31] -0.183280776 0.361212943 0.442355659 -0.216482294 0.140341771
[36] -0.462577061 -0.310538173 0.637044385 0.609471069 0.565187478
[41] -0.399742910 0.314283908 -0.274241342 -0.395500931 0.017522885
[46] -0.014460527 0.038094844 -0.107399231 -0.201947973 0.070785229
[51] -0.235487861 0.105118626 -0.121544793 -0.011072109 -0.075015946
[56] 0.372118704 0.157188971 0.509641773 0.057917299 0.216706459
[61] 0.008754496 0.232946339 -0.275609038 0.273341169 0.151003230
[66] -0.317023523 0.145360284 0.069432658 -0.354919174 -0.492113051
[71] 0.022281091 -0.453801138 0.006101679 -0.386864123 0.305684391
[76] 0.156024260 0.309654998 -0.439551630 -0.090911030 0.181671320
[81] -0.128179642 -0.013186776 0.321388302 0.174801493 0.091884109
[86] 0.348019404 0.200380173 -0.225489930 0.014670195 0.242086092
[91] 0.227928646 0.291351968 -0.009759798 0.244678062 -0.619983262
[96] 0.191346023 0.317609929 0.698845825 -0.140618961 0.022262424
[101] -0.219437955 0.187355486 0.344642401 1.120464155 0.008456351
[106] 0.039270827 -0.164387522 -0.319285001 -0.115759598 -0.201517101
[111] -0.206841567 -0.333283360 -0.820272194 -0.346025239 -0.085179936
[116] 0.082077811 -0.065377079 -0.079185654 -0.043563016 -0.337634822
[121] 0.228077196 0.252277931 -0.027541718 -0.068129137 -0.108134248
[126] 0.497270845 -0.336541304 0.668613011 -0.411705499 -0.292398866
[131] 0.665218266 0.440421783 0.208007498 0.046505111 0.411190859
[136] -0.174823803 0.209757249 -0.140372753 -0.085082524 0.001508235
[141] 0.108992471 -0.180890006 -0.153948009 -0.102243121 -0.405627047
[146] -0.366193837 -0.891669627 -0.355069355 0.205127336 -0.121279397
[151] -0.011608061 -0.776260921 -0.572953912 -0.055187190 0.621867161
[156] 0.092717780 -0.287243844 -0.076686898 0.069840953 0.389830478
[161] -0.329996118 0.200569954 -0.163793796 0.751332690 0.295892445
[166] 0.554903349 0.409107744 -0.225885800 -0.233586542 0.277663831
[171] 0.174212337 -0.028571589 0.096513533 0.219025429 0.017519747
[176] -0.348952581 0.258357998 -0.186671077 0.041115161 0.012832365
[181] -0.460343660 -0.416263118 -0.128054416 -0.793233643 -0.226283638
[186] -0.481582491 -0.066140456 -0.065124591 0.463494052 0.041772270
[191] 0.068332028 -0.203134054 0.126775236 -0.631755647 -0.605948388
[196] 0.110980497 -0.831452914 0.708760848 0.169655387 -0.341800285
[201] -0.108576657 0.637259783 0.045110085 0.045147482 0.057774600
[206] -0.143541272 -0.147367812 -0.126171585 -0.334507613 0.557376197
[211] 0.521944770 -0.036652249 -0.124388556 -0.427136470 -0.427668474
[216] 0.432034222 -0.196399168 -0.043816881 0.300253165 -0.106206723
[221] 0.395694875 0.075439187 -0.490719826 0.110356465 0.189219153
[226] 0.271787517 -0.434441797 0.101276169 0.409711494 0.126198701
>
> proc.time()
user system elapsed
3.314 4.694 8.171
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 3.4.4 (2018-03-15) -- "Someone to Lean On"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin15.6.0 (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x7fd5dda4bb40>
> .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: 0x7fd5dda4bb40>
> .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: 0x7fd5dda4bb40>
> .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: 0x7fd5dda4bb40>
> 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: 0x7fd5ddb4b930>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fd5ddb4b930>
> .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: 0x7fd5ddb4b930>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fd5ddb4b930>
> .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: 0x7fd5ddb4b930>
> 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: 0x7fd5ddb16260>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fd5ddb16260>
> .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: 0x7fd5ddb16260>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x7fd5ddb16260>
> .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: 0x7fd5ddb16260>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x7fd5ddb16260>
> .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: 0x7fd5ddb16260>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x7fd5ddb16260>
> .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: 0x7fd5ddb16260>
> 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: 0x7fd5dda24810>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x7fd5dda24810>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fd5dda24810>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fd5dda24810>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFileb51c32b2f1c0" "BufferedMatrixFileb51c777732f6"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFileb51c32b2f1c0" "BufferedMatrixFileb51c777732f6"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fd5dae01eb0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fd5dae01eb0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x7fd5dae01eb0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x7fd5dae01eb0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x7fd5dae01eb0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x7fd5dae01eb0>
> .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: 0x7fd5ddb1ce90>
> .Call("R_bm_AddColumn",P)
<pointer: 0x7fd5ddb1ce90>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x7fd5ddb1ce90>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x7fd5ddb1ce90>
> 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: 0x7fd5dac16860>
> .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: 0x7fd5dac16860>
> rm(P)
>
> proc.time()
user system elapsed
0.362 0.067 0.411
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 3.4.4 (2018-03-15) -- "Someone to Lean On"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin15.6.0 (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.333 0.044 0.362