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 13:07:52 -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: /home/biocbuild/bbs-3.6-bioc/R/bin/R CMD check --no-vignettes --timings BufferedMatrix_1.42.0.tar.gz |
| StartedAt: 2018-04-11 21:55:54 -0400 (Wed, 11 Apr 2018) |
| EndedAt: 2018-04-11 21:56:20 -0400 (Wed, 11 Apr 2018) |
| EllapsedTime: 25.5 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.6-bioc/R/bin/R CMD check --no-vignettes --timings BufferedMatrix_1.42.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck’
* using R version 3.4.4 (2018-03-15)
* using platform: x86_64-pc-linux-gnu (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 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
‘/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
* installing *source* package ‘BufferedMatrix’ ...
** libs
gcc -I/home/biocbuild/bbs-3.6-bioc/R/include -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I/home/biocbuild/bbs-3.6-bioc/R/include -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘˜’ [-Wparentheses]
if (!(Matrix->readonly) & setting){
^
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
gcc -I/home/biocbuild/bbs-3.6-bioc/R/include -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I/home/biocbuild/bbs-3.6-bioc/R/include -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c init_package.c -o init_package.o
g++ -shared -L/home/biocbuild/bbs-3.6-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.6-bioc/R/lib -lR
installing to /home/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-pc-linux-gnu (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
0.292 0.008 0.296
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-pc-linux-gnu (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] "/home/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 397293 21.3 750400 40.1 592000 31.7
Vcells 714338 5.5 1308461 10.0 1023717 7.9
>
>
>
>
> ##
> ## 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] "Wed Apr 11 21:56:15 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] "Wed Apr 11 21:56:15 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: 0x1060270>
>
>
>
> 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] "Wed Apr 11 21:56:15 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] "Wed Apr 11 21:56:16 2018"
>
> ColMode(tmp2)
<pointer: 0x1060270>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 98.3901894 -0.8673140 0.6861522 0.6930709
[2,] -0.3404710 -1.0602325 -1.9453152 -1.4659976
[3,] -0.2058548 0.6866618 0.7173020 -0.1110814
[4,] -0.6744732 1.4670931 0.3944062 -0.2159552
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/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,] 98.3901894 0.8673140 0.6861522 0.6930709
[2,] 0.3404710 1.0602325 1.9453152 1.4659976
[3,] 0.2058548 0.6866618 0.7173020 0.1110814
[4,] 0.6744732 1.4670931 0.3944062 0.2159552
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/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,] 9.9191829 0.9312970 0.8283430 0.8325088
[2,] 0.5834989 1.0296759 1.3947456 1.2107839
[3,] 0.4537122 0.8286506 0.8469368 0.3332887
[4,] 0.8212632 1.2112362 0.6280177 0.4647098
>
> 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: /home/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,] 222.58202 35.18028 33.96958 34.01816
[2,] 31.17546 36.35699 40.89277 38.57384
[3,] 29.74298 33.97317 34.18667 28.44397
[4,] 33.88710 38.57945 31.67458 29.86305
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x2c55fc0>
> exp(tmp5)
<pointer: 0x2c55fc0>
> log(tmp5,2)
<pointer: 0x2c55fc0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 463.2753
> Min(tmp5)
[1] 53.66261
> mean(tmp5)
[1] 72.80922
> Sum(tmp5)
[1] 14561.84
> Var(tmp5)
[1] 837.2545
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.48311 71.30194 68.72428 69.11100 71.12676 70.94234 72.19222 72.29985
[9] 70.56119 70.34954
> rowSums(tmp5)
[1] 1829.662 1426.039 1374.486 1382.220 1422.535 1418.847 1443.844 1445.997
[9] 1411.224 1406.991
> rowVars(tmp5)
[1] 7713.68004 50.55391 48.31485 81.35216 66.16234 50.18899
[7] 83.87525 79.86579 107.96974 66.74553
> rowSd(tmp5)
[1] 87.827559 7.110127 6.950889 9.019543 8.134024 7.084419 9.158343
[8] 8.936766 10.390849 8.169794
> rowMax(tmp5)
[1] 463.27531 85.11295 80.14176 84.21550 94.61019 84.84383 87.38726
[8] 92.34483 93.48271 88.55355
> rowMin(tmp5)
[1] 58.85947 60.37758 55.43956 53.66261 59.78769 59.08577 54.32227 60.79265
[9] 55.11036 58.28744
>
> colMeans(tmp5)
[1] 107.54539 72.21486 73.18799 69.37434 71.29024 75.16442 70.27342
[8] 72.51186 72.88581 74.22694 69.06902 68.32285 68.23279 72.46759
[15] 69.26972 68.96274 67.38948 70.93814 72.56886 70.28800
> colSums(tmp5)
[1] 1075.4539 722.1486 731.8799 693.7434 712.9024 751.6442 702.7342
[8] 725.1186 728.8581 742.2694 690.6902 683.2285 682.3279 724.6759
[15] 692.6972 689.6274 673.8948 709.3814 725.6886 702.8800
> colVars(tmp5)
[1] 15653.30965 25.77971 67.26356 67.44785 104.64770 48.67056
[7] 107.46846 116.64863 58.58346 102.62347 89.78841 61.10497
[13] 50.24552 104.00248 89.51393 88.24426 33.88148 15.71305
[19] 55.99961 63.82965
> colSd(tmp5)
[1] 125.113187 5.077372 8.201436 8.212664 10.229746 6.976429
[7] 10.366700 10.800400 7.653983 10.130324 9.475675 7.816967
[13] 7.088408 10.198161 9.461180 9.393842 5.820780 3.963969
[19] 7.483289 7.989346
> colMax(tmp5)
[1] 463.27531 80.29808 85.11295 80.28639 88.55355 84.21550 91.34549
[8] 93.48271 86.23288 92.34483 87.38726 81.73156 77.68455 94.61019
[15] 86.12816 87.13890 76.03177 77.22462 85.43586 79.66923
> colMin(tmp5)
[1] 61.00287 62.40149 61.72897 55.11036 59.00803 59.78769 55.43956 59.60227
[9] 62.55371 60.37758 53.66261 58.85947 56.87325 55.23699 59.08577 54.32227
[17] 58.28744 66.03921 60.44820 59.40060
>
>
> ### 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] NA 71.30194 68.72428 69.11100 71.12676 70.94234 72.19222 72.29985
[9] 70.56119 70.34954
> rowSums(tmp5)
[1] NA 1426.039 1374.486 1382.220 1422.535 1418.847 1443.844 1445.997
[9] 1411.224 1406.991
> rowVars(tmp5)
[1] 8108.15422 50.55391 48.31485 81.35216 66.16234 50.18899
[7] 83.87525 79.86579 107.96974 66.74553
> rowSd(tmp5)
[1] 90.045290 7.110127 6.950889 9.019543 8.134024 7.084419 9.158343
[8] 8.936766 10.390849 8.169794
> rowMax(tmp5)
[1] NA 85.11295 80.14176 84.21550 94.61019 84.84383 87.38726 92.34483
[9] 93.48271 88.55355
> rowMin(tmp5)
[1] NA 60.37758 55.43956 53.66261 59.78769 59.08577 54.32227 60.79265
[9] 55.11036 58.28744
>
> colMeans(tmp5)
[1] 107.54539 72.21486 73.18799 69.37434 71.29024 75.16442 70.27342
[8] 72.51186 NA 74.22694 69.06902 68.32285 68.23279 72.46759
[15] 69.26972 68.96274 67.38948 70.93814 72.56886 70.28800
> colSums(tmp5)
[1] 1075.4539 722.1486 731.8799 693.7434 712.9024 751.6442 702.7342
[8] 725.1186 NA 742.2694 690.6902 683.2285 682.3279 724.6759
[15] 692.6972 689.6274 673.8948 709.3814 725.6886 702.8800
> colVars(tmp5)
[1] 15653.30965 25.77971 67.26356 67.44785 104.64770 48.67056
[7] 107.46846 116.64863 NA 102.62347 89.78841 61.10497
[13] 50.24552 104.00248 89.51393 88.24426 33.88148 15.71305
[19] 55.99961 63.82965
> colSd(tmp5)
[1] 125.113187 5.077372 8.201436 8.212664 10.229746 6.976429
[7] 10.366700 10.800400 NA 10.130324 9.475675 7.816967
[13] 7.088408 10.198161 9.461180 9.393842 5.820780 3.963969
[19] 7.483289 7.989346
> colMax(tmp5)
[1] 463.27531 80.29808 85.11295 80.28639 88.55355 84.21550 91.34549
[8] 93.48271 NA 92.34483 87.38726 81.73156 77.68455 94.61019
[15] 86.12816 87.13890 76.03177 77.22462 85.43586 79.66923
> colMin(tmp5)
[1] 61.00287 62.40149 61.72897 55.11036 59.00803 59.78769 55.43956 59.60227
[9] NA 60.37758 53.66261 58.85947 56.87325 55.23699 59.08577 54.32227
[17] 58.28744 66.03921 60.44820 59.40060
>
> Max(tmp5,na.rm=TRUE)
[1] 463.2753
> Min(tmp5,na.rm=TRUE)
[1] 53.66261
> mean(tmp5,na.rm=TRUE)
[1] 72.83667
> Sum(tmp5,na.rm=TRUE)
[1] 14494.5
> Var(tmp5,na.rm=TRUE)
[1] 841.3317
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.75336 71.30194 68.72428 69.11100 71.12676 70.94234 72.19222 72.29985
[9] 70.56119 70.34954
> rowSums(tmp5,na.rm=TRUE)
[1] 1762.314 1426.039 1374.486 1382.220 1422.535 1418.847 1443.844 1445.997
[9] 1411.224 1406.991
> rowVars(tmp5,na.rm=TRUE)
[1] 8108.15422 50.55391 48.31485 81.35216 66.16234 50.18899
[7] 83.87525 79.86579 107.96974 66.74553
> rowSd(tmp5,na.rm=TRUE)
[1] 90.045290 7.110127 6.950889 9.019543 8.134024 7.084419 9.158343
[8] 8.936766 10.390849 8.169794
> rowMax(tmp5,na.rm=TRUE)
[1] 463.27531 85.11295 80.14176 84.21550 94.61019 84.84383 87.38726
[8] 92.34483 93.48271 88.55355
> rowMin(tmp5,na.rm=TRUE)
[1] 58.85947 60.37758 55.43956 53.66261 59.78769 59.08577 54.32227 60.79265
[9] 55.11036 58.28744
>
> colMeans(tmp5,na.rm=TRUE)
[1] 107.54539 72.21486 73.18799 69.37434 71.29024 75.16442 70.27342
[8] 72.51186 73.50109 74.22694 69.06902 68.32285 68.23279 72.46759
[15] 69.26972 68.96274 67.38948 70.93814 72.56886 70.28800
> colSums(tmp5,na.rm=TRUE)
[1] 1075.4539 722.1486 731.8799 693.7434 712.9024 751.6442 702.7342
[8] 725.1186 661.5098 742.2694 690.6902 683.2285 682.3279 724.6759
[15] 692.6972 689.6274 673.8948 709.3814 725.6886 702.8800
> colVars(tmp5,na.rm=TRUE)
[1] 15653.30965 25.77971 67.26356 67.44785 104.64770 48.67056
[7] 107.46846 116.64863 61.64755 102.62347 89.78841 61.10497
[13] 50.24552 104.00248 89.51393 88.24426 33.88148 15.71305
[19] 55.99961 63.82965
> colSd(tmp5,na.rm=TRUE)
[1] 125.113187 5.077372 8.201436 8.212664 10.229746 6.976429
[7] 10.366700 10.800400 7.851595 10.130324 9.475675 7.816967
[13] 7.088408 10.198161 9.461180 9.393842 5.820780 3.963969
[19] 7.483289 7.989346
> colMax(tmp5,na.rm=TRUE)
[1] 463.27531 80.29808 85.11295 80.28639 88.55355 84.21550 91.34549
[8] 93.48271 86.23288 92.34483 87.38726 81.73156 77.68455 94.61019
[15] 86.12816 87.13890 76.03177 77.22462 85.43586 79.66923
> colMin(tmp5,na.rm=TRUE)
[1] 61.00287 62.40149 61.72897 55.11036 59.00803 59.78769 55.43956 59.60227
[9] 62.55371 60.37758 53.66261 58.85947 56.87325 55.23699 59.08577 54.32227
[17] 58.28744 66.03921 60.44820 59.40060
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 71.30194 68.72428 69.11100 71.12676 70.94234 72.19222 72.29985
[9] 70.56119 70.34954
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1426.039 1374.486 1382.220 1422.535 1418.847 1443.844 1445.997
[9] 1411.224 1406.991
> rowVars(tmp5,na.rm=TRUE)
[1] NA 50.55391 48.31485 81.35216 66.16234 50.18899 83.87525
[8] 79.86579 107.96974 66.74553
> rowSd(tmp5,na.rm=TRUE)
[1] NA 7.110127 6.950889 9.019543 8.134024 7.084419 9.158343
[8] 8.936766 10.390849 8.169794
> rowMax(tmp5,na.rm=TRUE)
[1] NA 85.11295 80.14176 84.21550 94.61019 84.84383 87.38726 92.34483
[9] 93.48271 88.55355
> rowMin(tmp5,na.rm=TRUE)
[1] NA 60.37758 55.43956 53.66261 59.78769 59.08577 54.32227 60.79265
[9] 55.11036 58.28744
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 68.01985 72.10282 73.46408 69.21545 72.39719 75.15758 69.86602 71.93666
[9] NaN 74.22538 67.89255 69.37433 68.14864 72.75227 67.39656 66.94317
[17] 67.39191 71.31924 73.91560 69.66657
> colSums(tmp5,na.rm=TRUE)
[1] 612.1786 648.9254 661.1767 622.9390 651.5747 676.4182 628.7942 647.4299
[9] 0.0000 668.0284 611.0330 624.3690 613.3378 654.7704 606.5690 602.4885
[17] 606.5272 641.8732 665.2404 626.9991
> colVars(tmp5,na.rm=TRUE)
[1] 34.44923 28.86097 74.81400 75.59482 103.94364 54.75385 119.03481
[8] 127.50749 NA 115.45138 85.44104 56.30483 56.44655 116.09105
[15] 61.22998 53.38968 38.11660 16.04329 42.59532 67.46378
> colSd(tmp5,na.rm=TRUE)
[1] 5.869347 5.372241 8.649508 8.694528 10.195275 7.399585 10.910308
[8] 11.291922 NA 10.744830 9.243433 7.503654 7.513092 10.774556
[15] 7.824959 7.306824 6.173864 4.005407 6.526509 8.213634
> colMax(tmp5,na.rm=TRUE)
[1] 79.94285 80.29808 85.11295 80.28639 88.55355 84.21550 91.34549 93.48271
[9] -Inf 92.34483 87.38726 81.73156 77.68455 94.61019 84.50477 80.14176
[17] 76.03177 77.22462 85.43586 79.66923
> colMin(tmp5,na.rm=TRUE)
[1] 61.00287 62.40149 61.72897 55.11036 59.00803 59.78769 55.43956 59.60227
[9] Inf 60.37758 53.66261 59.32226 56.87325 55.23699 59.08577 54.32227
[17] 58.28744 66.03921 65.84347 59.40060
>
>
>
>
> 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] 236.4923 366.0504 142.7587 231.3600 292.4623 119.3910 226.0731 225.5880
[9] 241.6129 239.0931
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 236.4923 366.0504 142.7587 231.3600 292.4623 119.3910 226.0731 225.5880
[9] 241.6129 239.0931
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -5.684342e-14 -2.842171e-14 -1.421085e-14 0.000000e+00 -1.705303e-13
[6] -1.421085e-14 -2.273737e-13 -5.684342e-14 -5.684342e-14 -4.263256e-14
[11] 0.000000e+00 5.684342e-14 0.000000e+00 -1.421085e-13 1.278977e-13
[16] -1.136868e-13 0.000000e+00 2.273737e-13 -1.705303e-13 1.705303e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
10 12
4 15
6 19
2 20
2 17
2 7
6 9
1 6
1 16
9 15
8 12
9 19
4 20
10 20
3 9
7 2
2 18
5 20
4 17
1 18
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] 2.115912
> Min(tmp)
[1] -2.695442
> mean(tmp)
[1] -0.04505655
> Sum(tmp)
[1] -4.505655
> Var(tmp)
[1] 1.076178
>
> rowMeans(tmp)
[1] -0.04505655
> rowSums(tmp)
[1] -4.505655
> rowVars(tmp)
[1] 1.076178
> rowSd(tmp)
[1] 1.03739
> rowMax(tmp)
[1] 2.115912
> rowMin(tmp)
[1] -2.695442
>
> colMeans(tmp)
[1] 0.006105224 -0.410861561 -0.474064741 1.204687283 1.084020258
[6] 0.035390405 -1.678425597 -1.858173076 1.038382854 -1.970812688
[11] 0.705194514 -0.204189475 -1.419653645 -1.119601548 0.649013854
[16] 0.761374479 0.079216070 -0.047076358 0.048005606 0.803706259
[21] 1.026936948 -0.982802991 -0.352876753 -0.151101677 1.139576574
[26] 0.566931603 -2.695441945 0.517515350 -0.569762390 0.301076289
[31] -1.378830934 -0.190647096 -0.949261756 0.690159337 -2.262553854
[36] -1.355433278 0.791192218 -1.578385241 -0.079269657 1.264299408
[41] -0.137181784 1.695853484 -0.179751765 0.099069447 1.743069839
[46] 0.352633463 -0.935614720 -0.314127479 0.066712722 0.286286679
[51] 1.838819801 1.084029487 1.057272617 -1.801963222 -0.660234620
[56] -0.296034428 0.801640949 -0.788716356 -0.770969964 0.703842784
[61] 1.502657651 -0.243458140 1.098965528 0.029309612 0.238192180
[66] -0.030169043 -1.179150814 -0.389364866 2.115912166 0.429672656
[71] -0.476540697 -0.269174577 0.209144055 -0.387414051 -0.401585135
[76] -0.776716977 1.178734530 1.870337398 -1.175044335 -0.165546674
[81] -0.182395645 0.489376482 -0.120802225 -0.265748883 1.923334256
[86] -0.547764518 -0.701806261 1.106601733 0.178339449 -0.488635291
[91] -0.026896825 -0.075688225 -1.837171829 -1.615462544 0.285272299
[96] 2.085230010 0.950516376 -1.082423211 -0.341966835 -2.244518679
> colSums(tmp)
[1] 0.006105224 -0.410861561 -0.474064741 1.204687283 1.084020258
[6] 0.035390405 -1.678425597 -1.858173076 1.038382854 -1.970812688
[11] 0.705194514 -0.204189475 -1.419653645 -1.119601548 0.649013854
[16] 0.761374479 0.079216070 -0.047076358 0.048005606 0.803706259
[21] 1.026936948 -0.982802991 -0.352876753 -0.151101677 1.139576574
[26] 0.566931603 -2.695441945 0.517515350 -0.569762390 0.301076289
[31] -1.378830934 -0.190647096 -0.949261756 0.690159337 -2.262553854
[36] -1.355433278 0.791192218 -1.578385241 -0.079269657 1.264299408
[41] -0.137181784 1.695853484 -0.179751765 0.099069447 1.743069839
[46] 0.352633463 -0.935614720 -0.314127479 0.066712722 0.286286679
[51] 1.838819801 1.084029487 1.057272617 -1.801963222 -0.660234620
[56] -0.296034428 0.801640949 -0.788716356 -0.770969964 0.703842784
[61] 1.502657651 -0.243458140 1.098965528 0.029309612 0.238192180
[66] -0.030169043 -1.179150814 -0.389364866 2.115912166 0.429672656
[71] -0.476540697 -0.269174577 0.209144055 -0.387414051 -0.401585135
[76] -0.776716977 1.178734530 1.870337398 -1.175044335 -0.165546674
[81] -0.182395645 0.489376482 -0.120802225 -0.265748883 1.923334256
[86] -0.547764518 -0.701806261 1.106601733 0.178339449 -0.488635291
[91] -0.026896825 -0.075688225 -1.837171829 -1.615462544 0.285272299
[96] 2.085230010 0.950516376 -1.082423211 -0.341966835 -2.244518679
> 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] 0.006105224 -0.410861561 -0.474064741 1.204687283 1.084020258
[6] 0.035390405 -1.678425597 -1.858173076 1.038382854 -1.970812688
[11] 0.705194514 -0.204189475 -1.419653645 -1.119601548 0.649013854
[16] 0.761374479 0.079216070 -0.047076358 0.048005606 0.803706259
[21] 1.026936948 -0.982802991 -0.352876753 -0.151101677 1.139576574
[26] 0.566931603 -2.695441945 0.517515350 -0.569762390 0.301076289
[31] -1.378830934 -0.190647096 -0.949261756 0.690159337 -2.262553854
[36] -1.355433278 0.791192218 -1.578385241 -0.079269657 1.264299408
[41] -0.137181784 1.695853484 -0.179751765 0.099069447 1.743069839
[46] 0.352633463 -0.935614720 -0.314127479 0.066712722 0.286286679
[51] 1.838819801 1.084029487 1.057272617 -1.801963222 -0.660234620
[56] -0.296034428 0.801640949 -0.788716356 -0.770969964 0.703842784
[61] 1.502657651 -0.243458140 1.098965528 0.029309612 0.238192180
[66] -0.030169043 -1.179150814 -0.389364866 2.115912166 0.429672656
[71] -0.476540697 -0.269174577 0.209144055 -0.387414051 -0.401585135
[76] -0.776716977 1.178734530 1.870337398 -1.175044335 -0.165546674
[81] -0.182395645 0.489376482 -0.120802225 -0.265748883 1.923334256
[86] -0.547764518 -0.701806261 1.106601733 0.178339449 -0.488635291
[91] -0.026896825 -0.075688225 -1.837171829 -1.615462544 0.285272299
[96] 2.085230010 0.950516376 -1.082423211 -0.341966835 -2.244518679
> colMin(tmp)
[1] 0.006105224 -0.410861561 -0.474064741 1.204687283 1.084020258
[6] 0.035390405 -1.678425597 -1.858173076 1.038382854 -1.970812688
[11] 0.705194514 -0.204189475 -1.419653645 -1.119601548 0.649013854
[16] 0.761374479 0.079216070 -0.047076358 0.048005606 0.803706259
[21] 1.026936948 -0.982802991 -0.352876753 -0.151101677 1.139576574
[26] 0.566931603 -2.695441945 0.517515350 -0.569762390 0.301076289
[31] -1.378830934 -0.190647096 -0.949261756 0.690159337 -2.262553854
[36] -1.355433278 0.791192218 -1.578385241 -0.079269657 1.264299408
[41] -0.137181784 1.695853484 -0.179751765 0.099069447 1.743069839
[46] 0.352633463 -0.935614720 -0.314127479 0.066712722 0.286286679
[51] 1.838819801 1.084029487 1.057272617 -1.801963222 -0.660234620
[56] -0.296034428 0.801640949 -0.788716356 -0.770969964 0.703842784
[61] 1.502657651 -0.243458140 1.098965528 0.029309612 0.238192180
[66] -0.030169043 -1.179150814 -0.389364866 2.115912166 0.429672656
[71] -0.476540697 -0.269174577 0.209144055 -0.387414051 -0.401585135
[76] -0.776716977 1.178734530 1.870337398 -1.175044335 -0.165546674
[81] -0.182395645 0.489376482 -0.120802225 -0.265748883 1.923334256
[86] -0.547764518 -0.701806261 1.106601733 0.178339449 -0.488635291
[91] -0.026896825 -0.075688225 -1.837171829 -1.615462544 0.285272299
[96] 2.085230010 0.950516376 -1.082423211 -0.341966835 -2.244518679
> colMedians(tmp)
[1] 0.006105224 -0.410861561 -0.474064741 1.204687283 1.084020258
[6] 0.035390405 -1.678425597 -1.858173076 1.038382854 -1.970812688
[11] 0.705194514 -0.204189475 -1.419653645 -1.119601548 0.649013854
[16] 0.761374479 0.079216070 -0.047076358 0.048005606 0.803706259
[21] 1.026936948 -0.982802991 -0.352876753 -0.151101677 1.139576574
[26] 0.566931603 -2.695441945 0.517515350 -0.569762390 0.301076289
[31] -1.378830934 -0.190647096 -0.949261756 0.690159337 -2.262553854
[36] -1.355433278 0.791192218 -1.578385241 -0.079269657 1.264299408
[41] -0.137181784 1.695853484 -0.179751765 0.099069447 1.743069839
[46] 0.352633463 -0.935614720 -0.314127479 0.066712722 0.286286679
[51] 1.838819801 1.084029487 1.057272617 -1.801963222 -0.660234620
[56] -0.296034428 0.801640949 -0.788716356 -0.770969964 0.703842784
[61] 1.502657651 -0.243458140 1.098965528 0.029309612 0.238192180
[66] -0.030169043 -1.179150814 -0.389364866 2.115912166 0.429672656
[71] -0.476540697 -0.269174577 0.209144055 -0.387414051 -0.401585135
[76] -0.776716977 1.178734530 1.870337398 -1.175044335 -0.165546674
[81] -0.182395645 0.489376482 -0.120802225 -0.265748883 1.923334256
[86] -0.547764518 -0.701806261 1.106601733 0.178339449 -0.488635291
[91] -0.026896825 -0.075688225 -1.837171829 -1.615462544 0.285272299
[96] 2.085230010 0.950516376 -1.082423211 -0.341966835 -2.244518679
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.006105224 -0.4108616 -0.4740647 1.204687 1.08402 0.0353904 -1.678426
[2,] 0.006105224 -0.4108616 -0.4740647 1.204687 1.08402 0.0353904 -1.678426
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.858173 1.038383 -1.970813 0.7051945 -0.2041895 -1.419654 -1.119602
[2,] -1.858173 1.038383 -1.970813 0.7051945 -0.2041895 -1.419654 -1.119602
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.6490139 0.7613745 0.07921607 -0.04707636 0.04800561 0.8037063 1.026937
[2,] 0.6490139 0.7613745 0.07921607 -0.04707636 0.04800561 0.8037063 1.026937
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.982803 -0.3528768 -0.1511017 1.139577 0.5669316 -2.695442 0.5175153
[2,] -0.982803 -0.3528768 -0.1511017 1.139577 0.5669316 -2.695442 0.5175153
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.5697624 0.3010763 -1.378831 -0.1906471 -0.9492618 0.6901593 -2.262554
[2,] -0.5697624 0.3010763 -1.378831 -0.1906471 -0.9492618 0.6901593 -2.262554
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.355433 0.7911922 -1.578385 -0.07926966 1.264299 -0.1371818 1.695853
[2,] -1.355433 0.7911922 -1.578385 -0.07926966 1.264299 -0.1371818 1.695853
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.1797518 0.09906945 1.74307 0.3526335 -0.9356147 -0.3141275 0.06671272
[2,] -0.1797518 0.09906945 1.74307 0.3526335 -0.9356147 -0.3141275 0.06671272
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.2862867 1.83882 1.084029 1.057273 -1.801963 -0.6602346 -0.2960344
[2,] 0.2862867 1.83882 1.084029 1.057273 -1.801963 -0.6602346 -0.2960344
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.8016409 -0.7887164 -0.77097 0.7038428 1.502658 -0.2434581 1.098966
[2,] 0.8016409 -0.7887164 -0.77097 0.7038428 1.502658 -0.2434581 1.098966
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.02930961 0.2381922 -0.03016904 -1.179151 -0.3893649 2.115912 0.4296727
[2,] 0.02930961 0.2381922 -0.03016904 -1.179151 -0.3893649 2.115912 0.4296727
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.4765407 -0.2691746 0.2091441 -0.3874141 -0.4015851 -0.776717 1.178735
[2,] -0.4765407 -0.2691746 0.2091441 -0.3874141 -0.4015851 -0.776717 1.178735
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.870337 -1.175044 -0.1655467 -0.1823956 0.4893765 -0.1208022 -0.2657489
[2,] 1.870337 -1.175044 -0.1655467 -0.1823956 0.4893765 -0.1208022 -0.2657489
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 1.923334 -0.5477645 -0.7018063 1.106602 0.1783394 -0.4886353 -0.02689682
[2,] 1.923334 -0.5477645 -0.7018063 1.106602 0.1783394 -0.4886353 -0.02689682
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.07568822 -1.837172 -1.615463 0.2852723 2.08523 0.9505164 -1.082423
[2,] -0.07568822 -1.837172 -1.615463 0.2852723 2.08523 0.9505164 -1.082423
[,99] [,100]
[1,] -0.3419668 -2.244519
[2,] -0.3419668 -2.244519
>
>
> Max(tmp2)
[1] 3.006057
> Min(tmp2)
[1] -3.035523
> mean(tmp2)
[1] 0.09661932
> Sum(tmp2)
[1] 9.661932
> Var(tmp2)
[1] 1.1839
>
> rowMeans(tmp2)
[1] -0.083820354 0.304315945 3.006057344 0.663928957 -0.552878786
[6] 1.313321101 -0.424690580 -0.655771359 1.561952618 -2.062165667
[11] -0.006638628 -0.835976004 1.413452604 1.375225073 -1.138345680
[16] -0.220404954 2.276900545 -3.035523456 0.734404135 0.828226486
[21] -0.664594153 -0.583562885 0.097049457 2.062795078 1.003397411
[26] -2.156132291 1.647789019 -0.810702664 -0.973247036 -0.448192343
[31] -1.170292032 1.354859974 0.327499458 -0.481743000 1.655611571
[36] -1.622133773 0.848739766 -1.279664900 0.749116049 -1.873379366
[41] 1.209309086 -1.025963193 0.433871753 0.499821010 0.719749453
[46] -0.579902902 -0.781268834 -0.148631435 1.469601422 1.189867824
[51] -0.905988703 0.728725652 1.019954842 0.224361245 1.867798618
[56] -0.184395181 -1.010948399 -0.181159023 -0.714901464 0.832243240
[61] 1.034981989 -0.452430059 -1.003677417 -0.423958334 0.797594936
[66] 0.758644856 -0.144751289 -0.822461549 0.507765068 -1.379370065
[71] -0.325303673 0.281892307 -0.551857438 0.068095215 -0.546354517
[76] 0.595857012 -0.467096711 0.820880037 -0.125821908 -0.379664730
[81] 1.471205287 -0.730110001 -1.171588897 -0.452767566 -1.473658317
[86] -0.548862440 -0.242748374 2.028245359 1.543142590 1.838161344
[91] -0.508410148 -0.807677248 1.099893054 1.135666073 -0.351262521
[96] 0.719297640 0.078985742 0.381347987 -0.428981730 1.032163205
> rowSums(tmp2)
[1] -0.083820354 0.304315945 3.006057344 0.663928957 -0.552878786
[6] 1.313321101 -0.424690580 -0.655771359 1.561952618 -2.062165667
[11] -0.006638628 -0.835976004 1.413452604 1.375225073 -1.138345680
[16] -0.220404954 2.276900545 -3.035523456 0.734404135 0.828226486
[21] -0.664594153 -0.583562885 0.097049457 2.062795078 1.003397411
[26] -2.156132291 1.647789019 -0.810702664 -0.973247036 -0.448192343
[31] -1.170292032 1.354859974 0.327499458 -0.481743000 1.655611571
[36] -1.622133773 0.848739766 -1.279664900 0.749116049 -1.873379366
[41] 1.209309086 -1.025963193 0.433871753 0.499821010 0.719749453
[46] -0.579902902 -0.781268834 -0.148631435 1.469601422 1.189867824
[51] -0.905988703 0.728725652 1.019954842 0.224361245 1.867798618
[56] -0.184395181 -1.010948399 -0.181159023 -0.714901464 0.832243240
[61] 1.034981989 -0.452430059 -1.003677417 -0.423958334 0.797594936
[66] 0.758644856 -0.144751289 -0.822461549 0.507765068 -1.379370065
[71] -0.325303673 0.281892307 -0.551857438 0.068095215 -0.546354517
[76] 0.595857012 -0.467096711 0.820880037 -0.125821908 -0.379664730
[81] 1.471205287 -0.730110001 -1.171588897 -0.452767566 -1.473658317
[86] -0.548862440 -0.242748374 2.028245359 1.543142590 1.838161344
[91] -0.508410148 -0.807677248 1.099893054 1.135666073 -0.351262521
[96] 0.719297640 0.078985742 0.381347987 -0.428981730 1.032163205
> 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] -0.083820354 0.304315945 3.006057344 0.663928957 -0.552878786
[6] 1.313321101 -0.424690580 -0.655771359 1.561952618 -2.062165667
[11] -0.006638628 -0.835976004 1.413452604 1.375225073 -1.138345680
[16] -0.220404954 2.276900545 -3.035523456 0.734404135 0.828226486
[21] -0.664594153 -0.583562885 0.097049457 2.062795078 1.003397411
[26] -2.156132291 1.647789019 -0.810702664 -0.973247036 -0.448192343
[31] -1.170292032 1.354859974 0.327499458 -0.481743000 1.655611571
[36] -1.622133773 0.848739766 -1.279664900 0.749116049 -1.873379366
[41] 1.209309086 -1.025963193 0.433871753 0.499821010 0.719749453
[46] -0.579902902 -0.781268834 -0.148631435 1.469601422 1.189867824
[51] -0.905988703 0.728725652 1.019954842 0.224361245 1.867798618
[56] -0.184395181 -1.010948399 -0.181159023 -0.714901464 0.832243240
[61] 1.034981989 -0.452430059 -1.003677417 -0.423958334 0.797594936
[66] 0.758644856 -0.144751289 -0.822461549 0.507765068 -1.379370065
[71] -0.325303673 0.281892307 -0.551857438 0.068095215 -0.546354517
[76] 0.595857012 -0.467096711 0.820880037 -0.125821908 -0.379664730
[81] 1.471205287 -0.730110001 -1.171588897 -0.452767566 -1.473658317
[86] -0.548862440 -0.242748374 2.028245359 1.543142590 1.838161344
[91] -0.508410148 -0.807677248 1.099893054 1.135666073 -0.351262521
[96] 0.719297640 0.078985742 0.381347987 -0.428981730 1.032163205
> rowMin(tmp2)
[1] -0.083820354 0.304315945 3.006057344 0.663928957 -0.552878786
[6] 1.313321101 -0.424690580 -0.655771359 1.561952618 -2.062165667
[11] -0.006638628 -0.835976004 1.413452604 1.375225073 -1.138345680
[16] -0.220404954 2.276900545 -3.035523456 0.734404135 0.828226486
[21] -0.664594153 -0.583562885 0.097049457 2.062795078 1.003397411
[26] -2.156132291 1.647789019 -0.810702664 -0.973247036 -0.448192343
[31] -1.170292032 1.354859974 0.327499458 -0.481743000 1.655611571
[36] -1.622133773 0.848739766 -1.279664900 0.749116049 -1.873379366
[41] 1.209309086 -1.025963193 0.433871753 0.499821010 0.719749453
[46] -0.579902902 -0.781268834 -0.148631435 1.469601422 1.189867824
[51] -0.905988703 0.728725652 1.019954842 0.224361245 1.867798618
[56] -0.184395181 -1.010948399 -0.181159023 -0.714901464 0.832243240
[61] 1.034981989 -0.452430059 -1.003677417 -0.423958334 0.797594936
[66] 0.758644856 -0.144751289 -0.822461549 0.507765068 -1.379370065
[71] -0.325303673 0.281892307 -0.551857438 0.068095215 -0.546354517
[76] 0.595857012 -0.467096711 0.820880037 -0.125821908 -0.379664730
[81] 1.471205287 -0.730110001 -1.171588897 -0.452767566 -1.473658317
[86] -0.548862440 -0.242748374 2.028245359 1.543142590 1.838161344
[91] -0.508410148 -0.807677248 1.099893054 1.135666073 -0.351262521
[96] 0.719297640 0.078985742 0.381347987 -0.428981730 1.032163205
>
> colMeans(tmp2)
[1] 0.09661932
> colSums(tmp2)
[1] 9.661932
> colVars(tmp2)
[1] 1.1839
> colSd(tmp2)
[1] 1.088072
> colMax(tmp2)
[1] 3.006057
> colMin(tmp2)
[1] -3.035523
> colMedians(tmp2)
[1] -0.1048211
> colRanges(tmp2)
[,1]
[1,] -3.035523
[2,] 3.006057
>
> 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] -5.197535 -1.179188 2.327021 -2.659806 2.923370 -1.892635 2.310058
[8] 2.131973 -2.379456 -2.253661
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.93881172
[2,] -0.97717809
[3,] -0.50174404
[4,] 0.08773703
[5,] 0.60366308
>
> rowApply(tmp,sum)
[1] 0.6017453 -1.6997138 2.8911185 -5.0524821 3.0638195 2.0773366
[7] -7.1539985 0.3480884 0.5335659 -1.4793409
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 4 8 2 8 3 1 1 6 3 1
[2,] 6 2 5 3 6 6 9 5 6 4
[3,] 1 9 1 4 5 10 10 9 5 7
[4,] 3 3 10 2 1 7 4 10 1 5
[5,] 5 6 9 10 10 9 6 7 2 2
[6,] 10 1 4 7 8 8 2 3 9 3
[7,] 2 10 8 6 7 3 7 8 7 9
[8,] 7 7 7 9 2 4 8 1 10 8
[9,] 8 5 6 5 9 2 3 4 8 6
[10,] 9 4 3 1 4 5 5 2 4 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -3.1334244 -1.6505952 1.1715536 -0.6246708 -3.5524208 1.9881549
[7] -2.5758342 2.1496583 2.1957308 2.1882210 -1.8386031 3.2901991
[13] -0.7692685 -3.0967969 2.6000557 -4.9770464 -0.4464758 -3.0004064
[19] 1.0170401 2.2241624
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8934173
[2,] -1.1467522
[3,] -1.0225285
[4,] 0.4056973
[5,] 0.5235764
>
> rowApply(tmp,sum)
[1] -7.985256 -6.401701 -4.185610 10.204370 1.527430
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 7 3 16 11 2
[2,] 8 6 7 6 13
[3,] 10 10 18 19 4
[4,] 6 2 13 18 19
[5,] 1 13 12 1 10
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.1467522 -0.9863097 -0.3242913 -1.32383596 -2.8240401877 0.73826616
[2,] -1.8934173 -0.7067302 -0.3389106 -1.92423635 0.1391693654 0.81143767
[3,] 0.4056973 -0.4308953 1.1885529 0.02680278 0.0002496161 -0.09848779
[4,] 0.5235764 0.2133980 1.3482128 1.30881113 -0.8828756900 0.16192203
[5,] -1.0225285 0.2599420 -0.7020102 1.28778763 0.0150760687 0.37501680
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.9682241 1.3315451 -0.69551007 0.8996349 0.08374199 -0.2656645
[2,] -1.8906485 0.3591614 -0.09590728 0.7745609 -2.49401045 0.6757115
[3,] -1.4469853 -0.3182502 1.67787960 -1.3939901 0.19031698 0.4311275
[4,] 0.6724360 0.8320546 0.37803791 1.4957190 0.45486724 -0.3666145
[5,] -0.8788605 -0.0548526 0.93123061 0.4122962 -0.07351889 2.8156391
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.6518725 -1.4398712 1.08245950 -2.0957024 0.2537136 -1.3650690
[2,] -0.3919360 -0.5111904 0.68423387 -0.8860603 0.9845784 -0.6914255
[3,] 0.3343268 -1.3442080 -0.19018028 -0.2361545 -2.7348274 -1.0381998
[4,] 0.1582254 0.7768766 1.06756286 0.4165605 0.9392616 -0.5309941
[5,] 0.7819879 -0.5784038 -0.04402021 -2.1756897 0.1107980 0.6252820
[,19] [,20]
[1,] -0.1423699 0.91844801
[2,] 0.1365712 0.85734738
[3,] 1.2405032 -0.44888772
[4,] 0.4377671 0.79956515
[5,] -0.6554315 0.09768954
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/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: /home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 638 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 553 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.8 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 -0.1120071 0.2491538 -0.3772114 -1.178938 0.6157469 -0.7821927 0.004687201
col8 col9 col10 col11 col12 col13 col14
row1 -0.6030268 0.04660236 1.889848 -0.9589836 0.2895034 0.3256659 -0.319793
col15 col16 col17 col18 col19 col20
row1 -1.169613 1.061976 -0.5581538 -0.2753477 -0.455979 0.1376503
> tmp[,"col10"]
col10
row1 1.88984813
row2 3.15941098
row3 0.05933375
row4 1.38391099
row5 -1.45090290
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.1120071 0.2491538 -0.3772114 -1.1789384 0.6157469 -0.7821927
row5 0.3019150 0.4252724 -0.9185938 0.1551437 -1.2178312 -0.1049755
col7 col8 col9 col10 col11 col12
row1 0.004687201 -0.6030268 0.046602358 1.889848 -0.9589836 0.2895034
row5 0.347146994 -0.2797253 0.001107999 -1.450903 -0.0599264 -0.1912365
col13 col14 col15 col16 col17 col18
row1 0.3256659 -0.3197930 -1.1696130 1.0619757 -0.5581538 -0.2753477
row5 -1.5333600 -0.7032757 0.7089121 -0.5640659 0.4006929 -0.5067187
col19 col20
row1 -0.455979 0.1376503
row5 -1.037014 -0.1995909
> tmp[,c("col6","col20")]
col6 col20
row1 -0.7821927 0.1376503
row2 1.3374497 -0.1856861
row3 -1.0617455 -1.2036574
row4 0.2799270 -0.9137427
row5 -0.1049755 -0.1995909
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.7821927 0.1376503
row5 -0.1049755 -0.1995909
>
>
>
>
> 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 49.42749 50.35359 50.6902 51.33625 49.70886 103.1446 49.14975 51.18142
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.92124 50.11302 50.42604 47.55546 49.17777 52.22079 50.05067 50.19457
col17 col18 col19 col20
row1 48.98332 50.70332 49.31776 103.812
> tmp[,"col10"]
col10
row1 50.11302
row2 29.81308
row3 31.85571
row4 30.17923
row5 49.97784
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.42749 50.35359 50.69020 51.33625 49.70886 103.1446 49.14975 51.18142
row5 50.32044 49.13804 50.11501 51.36642 48.82901 105.2964 48.60573 49.78482
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.92124 50.11302 50.42604 47.55546 49.17777 52.22079 50.05067 50.19457
row5 50.30496 49.97784 50.04944 50.06399 49.49849 50.46312 49.19002 50.14560
col17 col18 col19 col20
row1 48.98332 50.70332 49.31776 103.8120
row5 48.40827 51.21660 48.00310 105.8427
> tmp[,c("col6","col20")]
col6 col20
row1 103.14463 103.81200
row2 74.02284 74.54810
row3 77.11272 76.08649
row4 77.47604 75.77058
row5 105.29639 105.84274
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 103.1446 103.8120
row5 105.2964 105.8427
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 103.1446 103.8120
row5 105.2964 105.8427
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.1345526
[2,] 0.7328273
[3,] -0.3529183
[4,] -0.5327931
[5,] 0.8643351
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.01331204 -0.3801978
[2,] 1.61178119 0.3775634
[3,] 0.54439371 -1.4698984
[4,] 0.54503163 0.6542313
[5,] 0.55955754 -1.6592824
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.33559131 0.05312402
[2,] 0.19578484 -2.37289480
[3,] -0.13441651 -0.45144370
[4,] 0.42904848 0.25563616
[5,] -0.09276531 0.24042042
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.3355913
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.3355913
[2,] 0.1957848
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 0.3078124 -0.8719461 0.8104947 -2.715400 0.2175602 -0.26622421 0.9142003
row1 0.9141347 0.1703747 -0.5430919 -0.429049 2.1526251 -0.01998006 0.4924446
[,8] [,9] [,10] [,11] [,12] [,13]
row3 0.34168850 0.9045999 -1.023403 0.3521884 0.9171778 0.02106631
row1 -0.02406553 -0.3769560 0.417004 -0.1171901 -1.1171682 0.84722578
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.3835475 -0.2587168 0.084276785 1.679414919 -0.6170555 -1.100297
row1 0.3720597 2.0832350 0.001549922 0.008352935 0.6240564 0.215103
[,20]
row3 0.8694485
row1 -0.8575601
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.253794 1.288295 -0.1343655 -1.204064 2.159241 0.3454611 -0.6245427
[,8] [,9] [,10]
row2 0.196283 -0.6063349 -0.9033798
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.1932429 0.5830883 -0.1114945 1.221766 -0.5266395 1.535642 -2.389571
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.5526089 1.390894 -0.5274244 0.1007067 -0.2111941 -0.7288791 -1.12807
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.081855 0.805432 -0.5695603 2.122637 -0.6443446 1.95269
>
>
> 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: 0x3338f60>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BM696e662bc55a"
[2] "/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BM696e15023faa"
[3] "/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BM696e207df347"
[4] "/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BM696e3d49fba2"
[5] "/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BM696e3ee29541"
[6] "/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BM696e424b83d3"
[7] "/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BM696e678a681c"
[8] "/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BM696e65887f3b"
[9] "/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BM696e6aeff6e9"
[10] "/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BM696e36d65cdc"
[11] "/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BM696e2cf77592"
[12] "/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BM696ef17532a"
[13] "/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BM696e3fe630b9"
[14] "/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BM696e2c4cf57"
[15] "/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests/BM696e1b7df674"
>
>
> ### 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: 0x2c645e0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x2c645e0>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.6-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x2c645e0>
> rowMedians(tmp)
[1] -0.184506267 0.092679696 0.073479510 0.035683819 -0.475450843
[6] -0.353511666 -0.477463965 0.078832057 0.630428176 0.257241625
[11] -0.028299960 -0.064392327 -0.153399264 0.155008555 0.178231814
[16] -0.058464515 0.252375441 -0.662054212 -0.262494764 0.122517791
[21] -0.149221825 -0.404156746 -0.361460726 0.798536273 -0.093476423
[26] -0.176360253 0.468215967 0.082715319 -0.058447063 -0.363851218
[31] 0.189218901 -0.581237620 0.256274680 -0.278342473 0.190037827
[36] 0.284859642 0.247732194 -0.339956416 0.454093248 0.245285674
[41] 0.065838225 -0.196220711 0.199598005 -0.587951715 -0.200758767
[46] -0.268311363 0.858207350 -0.269530451 -0.479121764 -0.019890835
[51] -0.237190517 0.283468831 0.058356943 0.043989039 -0.214386690
[56] 0.273929370 -0.151731052 -0.009608394 -0.159806961 0.133862016
[61] 0.685937398 -0.413444689 -0.757378711 -0.233946410 -0.233773947
[66] -0.130116130 0.055497852 0.279438400 0.456876990 -0.010159853
[71] 0.125161005 0.294750415 -0.096106683 0.268904329 0.581258005
[76] 0.141204884 0.041198802 0.039813820 0.232705786 0.331728359
[81] -0.842460361 0.407665131 0.019049557 0.007786455 0.234581241
[86] 0.243488374 0.090130288 0.191203646 0.042967410 -0.418190260
[91] -0.360646538 0.136394128 0.143775550 0.497493316 -0.404972554
[96] -0.319099795 -0.635749325 -0.126161012 0.269294038 0.062928009
[101] 0.287727019 -0.160549141 -0.218746643 0.156576550 0.352408615
[106] 0.417773911 0.384323216 -0.042194538 0.129892163 -0.192801131
[111] -0.269017956 -0.106596145 0.458655732 -0.433277320 0.604819292
[116] -0.049003293 -0.097033459 0.274779608 0.577983305 -0.457432491
[121] 0.177739341 -0.071445746 -0.503313557 -0.019567169 -0.156676318
[126] 0.370488982 -0.132695325 -0.320519839 -0.062073380 -0.146924434
[131] -0.344696651 0.289261052 -0.065290545 0.287271552 0.208959281
[136] 0.440215061 0.476242346 0.361397632 0.388882185 0.270047922
[141] 0.158576847 0.094180750 0.099616530 0.180932317 0.096042746
[146] -0.125749276 -0.322204888 0.457546113 -0.282236392 0.648151141
[151] 0.185507850 -0.269918290 0.009040792 -0.051767080 -0.098652454
[156] -0.488393999 -0.194066205 0.320932878 0.126200898 0.028275889
[161] 0.047082377 0.322894896 0.224276301 0.385511895 -0.316814179
[166] 0.011892569 0.313901869 -0.664145631 -0.334495841 -0.460385060
[171] 0.026275806 -0.404972832 -0.281552493 0.228052941 0.027186654
[176] -0.011381094 -0.207205869 0.077180955 0.086483787 -0.004090017
[181] 0.242347322 -0.261295875 -0.115609264 0.076768413 0.190558660
[186] -0.264953961 0.364931214 -0.582135943 -0.179637422 -0.366631404
[191] 0.004936028 -0.315500734 -0.010720419 0.111433801 0.300161874
[196] 0.454249040 0.518862679 0.291109185 -0.328493894 -0.713699462
[201] 0.406990778 0.045700188 0.311759247 0.070610853 0.302323107
[206] -0.419715029 0.385306435 0.100042867 -0.225802575 0.096618730
[211] -0.262824997 0.190560852 -0.553092063 0.044066230 0.183774881
[216] 0.230900010 -0.289463380 -0.163713658 -0.254570576 -0.067334230
[221] 0.118435438 0.163313397 -0.227632441 -0.259630480 0.243327272
[226] -0.325158555 -0.068980988 -0.157048173 -0.370387994 -0.303432615
>
> proc.time()
user system elapsed
2.076 0.792 2.890
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-pc-linux-gnu (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: 0xa99270>
> .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: 0xa99270>
> .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: 0xa99270>
> .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: 0xa99270>
> 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: 0xbef530>
> .Call("R_bm_AddColumn",P)
<pointer: 0xbef530>
> .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: 0xbef530>
> .Call("R_bm_AddColumn",P)
<pointer: 0xbef530>
> .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: 0xbef530>
> 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: 0x1f11ae0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1f11ae0>
> .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: 0x1f11ae0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x1f11ae0>
> .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: 0x1f11ae0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x1f11ae0>
> .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: 0x1f11ae0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x1f11ae0>
> .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: 0x1f11ae0>
> 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: 0x1720740>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x1720740>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1720740>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1720740>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile6a443a247145" "BufferedMatrixFile6a443ff890ac"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile6a443a247145" "BufferedMatrixFile6a443ff890ac"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x1b93970>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1b93970>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x1b93970>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x1b93970>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x1b93970>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x1b93970>
> .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: 0x1637320>
> .Call("R_bm_AddColumn",P)
<pointer: 0x1637320>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x1637320>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x1637320>
> 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: 0xb9c3d0>
> .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: 0xb9c3d0>
> rm(P)
>
> proc.time()
user system elapsed
0.372 0.036 0.405
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-pc-linux-gnu (64-bit)
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.272 0.012 0.280