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CHECK results for netresponse on machv2

This page was generated on 2021-06-11 14:06:41 -0400 (Fri, 11 Jun 2021).

Package 1267/2041HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
netresponse 1.52.0  (landing page)
Leo Lahti
Snapshot Date: 2021-06-10 06:50:12 -0400 (Thu, 10 Jun 2021)
URL: https://git.bioconductor.org/packages/netresponse
Branch: RELEASE_3_13
Last Commit: 1ecd688
Last Changed Date: 2021-05-19 11:46:24 -0400 (Wed, 19 May 2021)
nebbiolo1Linux (Ubuntu 20.04.2 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
tokay2Windows Server 2012 R2 Standard / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
machv2macOS 10.14.6 Mojave / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published
To the developers/maintainers of the netresponse package:
- Please allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/netresponse.git to
reflect on this report. See How and When does the builder pull? When will my changes propagate? here for more information.
- Make sure to use the following settings in order to reproduce any error or warning you see on this page.

Summary

Package: netresponse
Version: 1.52.0
Command: /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --install=check:netresponse.install-out.txt --library=/Library/Frameworks/R.framework/Versions/Current/Resources/library --no-vignettes --timings netresponse_1.52.0.tar.gz
StartedAt: 2021-06-10 21:33:18 -0400 (Thu, 10 Jun 2021)
EndedAt: 2021-06-10 21:36:10 -0400 (Thu, 10 Jun 2021)
EllapsedTime: 172.2 seconds
RetCode: 0
Status:   OK  
CheckDir: netresponse.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --install=check:netresponse.install-out.txt --library=/Library/Frameworks/R.framework/Versions/Current/Resources/library --no-vignettes --timings netresponse_1.52.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.13-bioc/meat/netresponse.Rcheck’
* using R version 4.1.0 (2021-05-18)
* using platform: x86_64-apple-darwin17.0 (64-bit)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘netresponse/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘netresponse’ version ‘1.52.0’
* 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 ‘netresponse’ 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 ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... NOTE
plotPCA: no visible binding for global variable ‘npoints’
Undefined global functions or variables:
  npoints
* checking Rd files ... OK
* 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 contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking line endings in Makefiles ... OK
* checking compilation flags in Makevars ... OK
* checking for GNU extensions in Makefiles ... OK
* checking for portable use of $(BLAS_LIBS) and $(LAPACK_LIBS) ... OK
* checking use of PKG_*FLAGS in Makefiles ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                 user system elapsed
sample2response 5.158  0.059   5.219
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘bicmixture.R’
  Running ‘mixture.model.test.R’
  Running ‘mixture.model.test.multimodal.R’
  Running ‘mixture.model.test.singlemode.R’
  Running ‘timing.R’
  Running ‘toydata2.R’
  Running ‘validate.netresponse.R’
  Running ‘validate.pca.basis.R’
  Running ‘vdpmixture.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: 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.13-bioc/meat/netresponse.Rcheck/00check.log’
for details.



Installation output

netresponse.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD INSTALL netresponse
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.1/Resources/library’
* installing *source* package ‘netresponse’ ...
** using staged installation
** libs
clang -mmacosx-version-min=10.13 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/usr/local/include   -fPIC  -Wall -g -O2  -c netresponse.c -o netresponse.o
netresponse.c:264:15: warning: unused variable 'prior_fields' [-Wunused-variable]
  const char *prior_fields[]={"Mumu","S2mu",
              ^
netresponse.c:686:6: warning: variable 'Mumu' is used uninitialized whenever 'if' condition is false [-Wsometimes-uninitialized]
  if(dim1) {
     ^~~~
netresponse.c:713:21: note: uninitialized use occurs here
  vdp_mk_log_lambda(Mumu, S2mu, Mubar, Mutilde, 
                    ^~~~
netresponse.c:686:3: note: remove the 'if' if its condition is always true
  if(dim1) {
  ^~~~~~~~~
netresponse.c:655:15: note: initialize the variable 'Mumu' to silence this warning
  double *Mumu, *S2mu, *Mubar, *Mutilde, 
              ^
               = NULL
netresponse.c:686:6: warning: variable 'S2mu' is used uninitialized whenever 'if' condition is false [-Wsometimes-uninitialized]
  if(dim1) {
     ^~~~
netresponse.c:713:27: note: uninitialized use occurs here
  vdp_mk_log_lambda(Mumu, S2mu, Mubar, Mutilde, 
                          ^~~~
netresponse.c:686:3: note: remove the 'if' if its condition is always true
  if(dim1) {
  ^~~~~~~~~
netresponse.c:655:22: note: initialize the variable 'S2mu' to silence this warning
  double *Mumu, *S2mu, *Mubar, *Mutilde, 
                     ^
                      = NULL
netresponse.c:686:6: warning: variable 'Mubar' is used uninitialized whenever 'if' condition is false [-Wsometimes-uninitialized]
  if(dim1) {
     ^~~~
netresponse.c:713:33: note: uninitialized use occurs here
  vdp_mk_log_lambda(Mumu, S2mu, Mubar, Mutilde, 
                                ^~~~~
netresponse.c:686:3: note: remove the 'if' if its condition is always true
  if(dim1) {
  ^~~~~~~~~
netresponse.c:655:30: note: initialize the variable 'Mubar' to silence this warning
  double *Mumu, *S2mu, *Mubar, *Mutilde, 
                             ^
                              = NULL
netresponse.c:686:6: warning: variable 'Mutilde' is used uninitialized whenever 'if' condition is false [-Wsometimes-uninitialized]
  if(dim1) {
     ^~~~
netresponse.c:713:40: note: uninitialized use occurs here
  vdp_mk_log_lambda(Mumu, S2mu, Mubar, Mutilde, 
                                       ^~~~~~~
netresponse.c:686:3: note: remove the 'if' if its condition is always true
  if(dim1) {
  ^~~~~~~~~
netresponse.c:655:40: note: initialize the variable 'Mutilde' to silence this warning
  double *Mumu, *S2mu, *Mubar, *Mutilde, 
                                       ^
                                        = NULL
netresponse.c:686:6: warning: variable 'AlphaKsi' is used uninitialized whenever 'if' condition is false [-Wsometimes-uninitialized]
  if(dim1) {
     ^~~~
netresponse.c:714:7: note: uninitialized use occurs here
                    AlphaKsi, BetaKsi, KsiAlpha, KsiBeta, 
                    ^~~~~~~~
netresponse.c:686:3: note: remove the 'if' if its condition is always true
  if(dim1) {
  ^~~~~~~~~
netresponse.c:656:14: note: initialize the variable 'AlphaKsi' to silence this warning
    *AlphaKsi, *BetaKsi, *KsiAlpha, *KsiBeta, *U_p, *prior_alpha,
             ^
              = NULL
netresponse.c:686:6: warning: variable 'BetaKsi' is used uninitialized whenever 'if' condition is false [-Wsometimes-uninitialized]
  if(dim1) {
     ^~~~
netresponse.c:714:17: note: uninitialized use occurs here
                    AlphaKsi, BetaKsi, KsiAlpha, KsiBeta, 
                              ^~~~~~~
netresponse.c:686:3: note: remove the 'if' if its condition is always true
  if(dim1) {
  ^~~~~~~~~
netresponse.c:656:24: note: initialize the variable 'BetaKsi' to silence this warning
    *AlphaKsi, *BetaKsi, *KsiAlpha, *KsiBeta, *U_p, *prior_alpha,
                       ^
                        = NULL
netresponse.c:686:6: warning: variable 'KsiAlpha' is used uninitialized whenever 'if' condition is false [-Wsometimes-uninitialized]
  if(dim1) {
     ^~~~
netresponse.c:714:26: note: uninitialized use occurs here
                    AlphaKsi, BetaKsi, KsiAlpha, KsiBeta, 
                                       ^~~~~~~~
netresponse.c:686:3: note: remove the 'if' if its condition is always true
  if(dim1) {
  ^~~~~~~~~
netresponse.c:656:35: note: initialize the variable 'KsiAlpha' to silence this warning
    *AlphaKsi, *BetaKsi, *KsiAlpha, *KsiBeta, *U_p, *prior_alpha,
                                  ^
                                   = NULL
netresponse.c:686:6: warning: variable 'KsiBeta' is used uninitialized whenever 'if' condition is false [-Wsometimes-uninitialized]
  if(dim1) {
     ^~~~
netresponse.c:714:36: note: uninitialized use occurs here
                    AlphaKsi, BetaKsi, KsiAlpha, KsiBeta, 
                                                 ^~~~~~~
netresponse.c:686:3: note: remove the 'if' if its condition is always true
  if(dim1) {
  ^~~~~~~~~
netresponse.c:656:45: note: initialize the variable 'KsiBeta' to silence this warning
    *AlphaKsi, *BetaKsi, *KsiAlpha, *KsiBeta, *U_p, *prior_alpha,
                                            ^
                                             = NULL
netresponse.c:696:6: warning: variable 'U_p' is used uninitialized whenever 'if' condition is false [-Wsometimes-uninitialized]
  if(dim2) {
     ^~~~
netresponse.c:716:7: note: uninitialized use occurs here
                    U_p, U_hat,
                    ^~~
netresponse.c:696:3: note: remove the 'if' if its condition is always true
  if(dim2) {
  ^~~~~~~~~
netresponse.c:656:51: note: initialize the variable 'U_p' to silence this warning
    *AlphaKsi, *BetaKsi, *KsiAlpha, *KsiBeta, *U_p, *prior_alpha,
                                                  ^
                                                   = NULL
netresponse.c:696:6: warning: variable 'U_hat' is used uninitialized whenever 'if' condition is false [-Wsometimes-uninitialized]
  if(dim2) {
     ^~~~
netresponse.c:716:12: note: uninitialized use occurs here
                    U_p, U_hat,
                         ^~~~~
netresponse.c:696:3: note: remove the 'if' if its condition is always true
  if(dim2) {
  ^~~~~~~~~
netresponse.c:661:14: note: initialize the variable 'U_hat' to silence this warning
  SEXP* U_hat;
             ^
              = NULL
11 warnings generated.
clang -mmacosx-version-min=10.13 -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 netresponse.so netresponse.o -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation
installing to /Library/Frameworks/R.framework/Versions/4.1/Resources/library/00LOCK-netresponse/00new/netresponse/libs
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
llvm-objdump: '/Library/Frameworks/R.framework/Versions/4.1/Resources/library/00LOCK-netresponse/00new/netresponse/extras/netresponse.so': Object is not a Mach-O file type.
llvm-objdump: '/Library/Frameworks/R.framework/Versions/4.1/Resources/library/00LOCK-netresponse/00new/netresponse/extras/netresponse.so': Object is not a Mach-O file type.
llvm-objdump: '/Library/Frameworks/R.framework/Versions/4.1/Resources/library/00LOCK-netresponse/00new/netresponse/extras/netresponse.so': Object is not a Mach-O file type.
llvm-objdump: '/Library/Frameworks/R.framework/Versions/4.1/Resources/library/00LOCK-netresponse/00new/netresponse/extras/netresponse.so': Object is not a Mach-O file type.
llvm-objdump: '/Library/Frameworks/R.framework/Versions/4.1/Resources/library/00LOCK-netresponse/00new/netresponse/extras/netresponse.so': Object is not a Mach-O file type.
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (netresponse)

Tests output

netresponse.Rcheck/tests/bicmixture.Rout


R version 4.1.0 (2021-05-18) -- "Camp Pontanezen"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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.

> # 1. vdp.mixt: moodien loytyminen eri dimensiolla, naytemaarilla ja komponenteilla
> #   -> ainakin nopea check
> 
> #######################################################################
> 
> # Generate random data from five Gaussians. 
> # Detect modes with vdp-gm. 
> # Plot data points and detected clusters with variance ellipses
> 
> #######################################################################
> 
> library(netresponse)
Loading required package: Rgraphviz
Loading required package: graph
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

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

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

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

    IQR, mad, sd, var, xtabs

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

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
    pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
    tapply, union, unique, unsplit, which.max, which.min

Loading required package: grid
Loading required package: minet
Loading required package: mclust
Package 'mclust' version 5.4.7
Type 'citation("mclust")' for citing this R package in publications.
Loading required package: reshape2

netresponse (C) 2008-2020 Leo Lahti et al.

https://github.com/antagomir/netresponse
> #source("~/Rpackages/netresponse/netresponse/R/detect.responses.R")
> #source("~/Rpackages/netresponse/netresponse/R/internals.R")
> #source("~/Rpackages/netresponse/netresponse/R/vdp.mixt.R")
> #dyn.load("/home/tuli/Rpackages/netresponse/netresponse/src/netresponse.so")
> 
> #########  Generate DATA #############################################
> 
> # Generate Nc components from normal-inverseGamma prior
> 
> set.seed(12346)
> 
> dd <- 3   # Dimensionality of data
> Nc <- 5   # Number of components
> Ns <- 200 # Number of data points
> sd0 <- 3  # component spread
> rgam.shape = 2 # parameters for Gamma distribution 
> rgam.scale = 2 # parameters for Gamma distribution to define precisions
> 
> 
> # Generate means and variances (covariance diagonals) for the components 
> component.means <- matrix(rnorm(Nc*dd, mean = 0, sd = sd0), nrow = Nc, ncol = dd)
> component.vars <- matrix(1/rgamma(Nc*dd, shape = rgam.shape, scale = rgam.scale), 
+ 	                 nrow = Nc, ncol = dd)
> component.sds <- sqrt(component.vars)
> 
> 
> # Size for each component -> sample randomly for each data point from uniform distr.
> # i.e. cluster assignments
> sample2comp <- sample.int(Nc, Ns, replace = TRUE)
> 
> D <- array(NA, dim = c(Ns, dd))
> for (i in 1:Ns)  {
+     # component identity of this sample
+     ci <- sample2comp[[i]]
+     cm <- component.means[ci,]
+     csd <- component.sds[ci,]
+     D[i,] <- rnorm(dd, mean = cm, sd = csd)
+ }
> 
> 
> ######################################################################
> 
> # Fit mixture model
> out <- mixture.model(D, mixture.method = "bic")
> 
> # FIXME rowmeans(qofz) is constant but not 1
> #qofz <- P.r.s(t(D), list(mu = out$mu, sd = out$sd, w = out$w), log = FALSE)
> 
> ############################################################
> 
> # Compare input data and results
> 
> ord.out <- order(out$mu[,1])
> ord.in <- order(component.means[,1])
> 
> means.out <- out$mu[ord.out,]
> means.in <- component.means[ord.in,]
> 
> # Cluster stds and variances
> sds.out <- out$sd[ord.out,]
> sds.in  <- sqrt(component.vars[ord.in,])
> 
> # -----------------------------------------------------------
> 
> vars.out <- sds.out^2
> vars.in <- sds.in^2
> 
> # Check correspondence between input and output
> if (length(means.in) == length(means.out)) {
+    cm <- cor(as.vector(means.in), as.vector(means.out))
+    csd <- cor(as.vector(sds.in), as.vector(sds.out))
+ }
> 
> # Plot results (assuming 2D)
> 
> ran <- range(c(as.vector(means.in - 2*vars.in), 
+                as.vector(means.in + 2*vars.in), 
+ 	       as.vector(means.out + 2*vars.out), 
+ 	       as.vector(means.out - 2*vars.out)))
> 
> plot(D, pch = 20, main = paste("Cor.means:", round(cm,3), "/ Cor.sds:", round(csd,3)), xlim = ran, ylim = ran) 
> #for (ci in 1:nrow(means.out))  { add.ellipse(centroid = means.out[ci,], covmat = diag(vars.out[ci,]), col = "red") }
> #for (ci in 1:nrow(means.in))  { add.ellipse(centroid = means.in[ci,], covmat = diag(vars.in[ci,]), col = "blue") }
> 
> ######################################################
> 
> #for (ci in 1:nrow(means.out))  {
> #    points(means.out[ci,1], means.out[ci,2], col = "red", pch = 19)
> #    el <- ellipse(matrix(c(vars.out[ci,1],0,0,vars.out[ci,2]),2), centre = means.out[ci,])
> #    lines(el, col = "red") 						  
> #}
> 
> #for (ci in 1:nrow(means.in))  {
> #    points(means.in[ci,1], means.in[ci,2], col = "blue", pch = 19)
> #    el <- ellipse(matrix(c(vars.in[ci,1],0,0,vars.in[ci,2]),2), centre = means.in[ci,])
> #    lines(el, col = "blue") 						  
> #}
> 
> 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
  4.314   0.274   4.564 

netresponse.Rcheck/tests/mixture.model.test.multimodal.Rout


R version 4.1.0 (2021-05-18) -- "Camp Pontanezen"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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(netresponse)
Loading required package: Rgraphviz
Loading required package: graph
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

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

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

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

    IQR, mad, sd, var, xtabs

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

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
    pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
    tapply, union, unique, unsplit, which.max, which.min

Loading required package: grid
Loading required package: minet
Loading required package: mclust
Package 'mclust' version 5.4.7
Type 'citation("mclust")' for citing this R package in publications.
Loading required package: reshape2

netresponse (C) 2008-2020 Leo Lahti et al.

https://github.com/antagomir/netresponse
> 
> # Three MODES
> 
> # set.seed(34884)
> set.seed(3488400)
> 
> Ns <- 200
> Nd <- 2
> 
> D3 <- rbind(matrix(rnorm(Ns*Nd, mean = 0), ncol = Nd), 
+       	    matrix(rnorm(Ns*Nd, mean = 3), ncol = Nd),
+       	    cbind(rnorm(Ns, mean = -3), rnorm(Ns, mean = 3))
+ 	    )
> 
> #X11()
> par(mfrow = c(2,2))
> for (mm in c("vdp", "bic")) {
+   for (pp in c(FALSE, TRUE)) {
+ 
+     # Fit nonparametric Gaussian mixture model
+     out <- mixture.model(D3, mixture.method = mm, pca.basis = pp)
+     plot(D3, col = apply(out$qofz, 1, which.max), main = paste(mm, "/ pca:",  pp)) 
+ 
+   }
+ }
> 
> # VDP is less sensitive than BIC in detecting Gaussian modes (more
> # separation between the clusters needed)
> 
> # pca.basis option is less important for sensitive detection but
> # it will help to avoid overfitting to unimodal features that
> # are not parallel to the axes (unimodal distribution often becomes
> # splitted in two or more clusters in these cases)
> 
> 
> proc.time()
   user  system elapsed 
  6.225   0.334   6.536 

netresponse.Rcheck/tests/mixture.model.test.Rout


R version 4.1.0 (2021-05-18) -- "Camp Pontanezen"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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.

> # Validate mixture models
> 
> # Generate random data from five Gaussians. 
> # Detect modes 
> # Plot data points and detected clusters 
> 
> library(netresponse)
Loading required package: Rgraphviz
Loading required package: graph
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

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

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

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

    IQR, mad, sd, var, xtabs

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

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
    pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
    tapply, union, unique, unsplit, which.max, which.min

Loading required package: grid
Loading required package: minet
Loading required package: mclust
Package 'mclust' version 5.4.7
Type 'citation("mclust")' for citing this R package in publications.
Loading required package: reshape2

netresponse (C) 2008-2020 Leo Lahti et al.

https://github.com/antagomir/netresponse
> 
> #fs <- list.files("~/Rpackages/netresponse/netresponse/R/", full.names = TRUE); for (f in fs) {source(f)}; dyn.load("/home/tuli/Rpackages/netresponse/netresponse/src/netresponse.so")
> 
> #########  Generate DATA #######################
> 
> res <- generate.toydata()
> D <- res$data
> component.means <- res$means
> component.sds   <- res$sds
> sample2comp     <- res$sample2comp
> 
> ######################################################################
> 
> par(mfrow = c(2,1))
> 
> for (mm in c("vdp", "bic")) {
+ 
+   # Fit nonparametric Gaussian mixture model
+   #source("~/Rpackages/netresponse/netresponse/R/vdp.mixt.R")
+   out <- mixture.model(D, mixture.method = mm, max.responses = 10, pca.basis = FALSE)
+ 
+   ############################################################
+ 
+   # Compare input data and results
+ 
+   ord.out <- order(out$mu[,1])
+   ord.in <- order(component.means[,1])
+ 
+   means.out <- out$mu[ord.out,]
+   means.in <- component.means[ord.in,]
+ 
+   # Cluster stds and variances
+   sds.out <- out$sd[ord.out,]
+   vars.out <- sds.out^2
+ 
+   sds.in  <- component.sds[ord.in,]
+   vars.in <- sds.in^2
+ 
+   # Check correspondence between input and output
+   if (length(means.in) == length(means.out)) {
+     cm <- cor(as.vector(means.in), as.vector(means.out))
+     csd <- cor(as.vector(sds.in), as.vector(sds.out))
+   }
+ 
+   # Plot results (assuming 2D)
+   ran <- range(c(as.vector(means.in - 2*vars.in), 
+                as.vector(means.in + 2*vars.in), 
+ 	       as.vector(means.out + 2*vars.out), 
+ 	       as.vector(means.out - 2*vars.out)))
+ 
+   real.modes <- sample2comp
+   obs.modes <- apply(out$qofz, 1, which.max)
+ 
+   # plot(D, pch = 20, main = paste(mm, "/ cor.means:", round(cm,6), "/ Cor.sds:", round(csd,6)), xlim = ran, ylim = ran)
+   
+   # plot(D, pch = real.modes, col = obs.modes, main = paste(mm, "/ cor.means:", round(cm,6), "/ Cor.sds:", round(csd,6)), xlim = ran, ylim = ran)
+   
+   # for (ci in 1:nrow(means.out))  { add.ellipse(centroid = means.out[ci,], covmat = diag(vars.out[ci,]), col = "red") }
+   # for (ci in 1:nrow(means.in))  { add.ellipse(centroid = means.in[ci,], covmat = diag(vars.in[ci,]), col = "blue") }
+ 
+ }
> 
> 
> proc.time()
   user  system elapsed 
  4.662   0.293   4.935 

netresponse.Rcheck/tests/mixture.model.test.singlemode.Rout


R version 4.1.0 (2021-05-18) -- "Camp Pontanezen"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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.

> 
> skip <- FALSE
> 
> if (!skip) {
+ 
+ library(netresponse)
+ 
+ # SINGLE MODE
+ 
+ # Produce test data that has full covariance
+ # It is expected that
+ # pca.basis = FALSE splits Gaussian with full covariance into two modes
+ # pca.basis = TRUE should detect just a single mode
+ 
+ Ns <- 200
+ Nd <- 2
+ k <- 1.5
+ 
+ D2 <- matrix(rnorm(Ns*Nd), ncol = Nd) %*% rbind(c(1,k), c(k,1))
+ 
+ par(mfrow = c(2,2))
+ for (mm in c("vdp", "bic")) {
+   for (pp in c(FALSE, TRUE)) {
+ 
+     # Fit nonparametric Gaussian mixture model
+     out <- mixture.model(D2, mixture.method = mm, pca.basis = pp)
+     plot(D2, col = apply(out$qofz, 1, which.max), main = paste("mm:" , mm, "/ pp:",  pp)) 
+ 
+   }
+ }
+ 
+ }
Loading required package: Rgraphviz
Loading required package: graph
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

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

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

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

    IQR, mad, sd, var, xtabs

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

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
    pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
    tapply, union, unique, unsplit, which.max, which.min

Loading required package: grid
Loading required package: minet
Loading required package: mclust
Package 'mclust' version 5.4.7
Type 'citation("mclust")' for citing this R package in publications.
Loading required package: reshape2

netresponse (C) 2008-2020 Leo Lahti et al.

https://github.com/antagomir/netresponse
> 
> proc.time()
   user  system elapsed 
  4.594   0.296   4.872 

netresponse.Rcheck/tests/timing.Rout


R version 4.1.0 (2021-05-18) -- "Camp Pontanezen"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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.

> 
> # Play with different options and check their effect on  running times for bic and vdp 
> 
> skip <- TRUE
> 
> if (!skip) {
+ 
+   Ns <- 100
+   Nd <- 2
+ 
+   set.seed(3488400)
+ 
+   D <- cbind(
+ 
+      	rbind(matrix(rnorm(Ns*Nd, mean = 0), ncol = Nd), 
+        	      matrix(rnorm(Ns*Nd, mean = 2), ncol = Nd),
+       	      cbind(rnorm(Ns, mean = -1), rnorm(Ns, mean = 3))
+  	    ), 
+ 
+      	rbind(matrix(rnorm(Ns*Nd, mean = 0), ncol = Nd), 
+        	      matrix(rnorm(Ns*Nd, mean = 2), ncol = Nd),
+       	      cbind(rnorm(Ns, mean = -1), rnorm(Ns, mean = 3))
+  	    )
+ 	    )
+ 
+   rownames(D) <- paste("R", 1:nrow(D), sep = "-")
+   colnames(D) <- paste("C", 1:ncol(D), sep = "-")
+ 
+   ts <- c()
+   for (mm in c("bic", "vdp")) {
+ 
+ 
+     # NOTE: no PCA basis needed with mixture.method = "bic"
+     tt <- system.time(detect.responses(D, verbose = TRUE, max.responses = 5, 
+ 	   		       mixture.method = mm, information.criterion = "BIC", 
+ 			       merging.threshold = 0, bic.threshold = 0, pca.basis = TRUE))
+ 
+     print(paste(mm, ":", round(tt[["elapsed"]], 3)))
+     ts[[mm]] <- tt[["elapsed"]]
+   }
+ 
+    print(paste(names(ts)[[1]], "/", names(ts)[[2]], ": ", round(ts[[1]]/ts[[2]], 3)))
+ 
+ }
> 
> # -> VDP is much faster when sample sizes increase 
> # 1000 samples -> 25-fold speedup with VDP
> 
> 
> 
> proc.time()
   user  system elapsed 
  0.288   0.068   0.334 

netresponse.Rcheck/tests/toydata2.Rout


R version 4.1.0 (2021-05-18) -- "Camp Pontanezen"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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.

> # Generate Nc components from normal-inverseGamma prior
> 
> set.seed(12346)
> 
> Ns <- 300
> Nd <- 2
> 
> # Isotropic cloud
> D1 <- matrix(rnorm(Ns*Nd), ncol = Nd) 
> 
> # Single diagonal mode
> D2 <- matrix(rnorm(Ns*Nd), ncol = Nd) %*% rbind(c(1,2), c(2,1)) 
> 
> # Two isotropic modes
> D3 <- rbind(matrix(rnorm(Ns/2*Nd), ncol = Nd), matrix(rnorm(Ns/2*Nd, mean = 3), ncol = Nd))
> D <- cbind(D1, D2, D3)
> 
> colnames(D) <- paste("Feature-",  1:ncol(D), sep = "")
> rownames(D) <- paste("Sample-", 1:nrow(D), sep = "")
> 
> 
> proc.time()
   user  system elapsed 
  0.260   0.065   0.301 

netresponse.Rcheck/tests/validate.netresponse.Rout


R version 4.1.0 (2021-05-18) -- "Camp Pontanezen"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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.

> 
> skip <- TRUE
> 
> if (!skip) {
+ 
+ # 2. netresponse test
+ # test later with varying parameters
+ 
+ # Load the package
+ library(netresponse)
+ #load("../data/toydata.rda")
+ fs <- list.files("../R/", full.names = TRUE); for (f in fs) {source(f)};
+ 
+ data(toydata)
+ 
+ D <- toydata$emat
+ netw <- toydata$netw
+ 
+ # The toy data is random data with 10 features (genes). 
+ # The features 
+ rf <- c(4, 5, 6)
+ #form a subnetwork with coherent responses
+ # with means 
+ r1 <- c(0, 3, 0)
+ r2 <- c(-5, 0, 2)
+ r3 <- c(5, -3, -3)
+ mu.real <- rbind(r1, r2, r3)
+ # real weights
+ w.real <- c(70, 70, 60)/200
+ # and unit variances
+ rv <- 1
+ 
+ # Fit the model
+ #res <- detect.responses(D, netw, verbose = TRUE, mc.cores = 2)
+ #res <- detect.responses(D, netw, verbose = TRUE, max.responses = 4)
+ 
+ res <- detect.responses(D, netw, verbose = TRUE, max.responses = 3, mixture.method = "bic", information.criterion = "BIC", merging.threshold = 1, bic.threshold = 10, pca.basis = FALSE)
+ 
+ print("OK")
+ 
+ # Subnets (each is a list of nodes)
+ subnets <- get.subnets(res)
+ 
+ # the correct subnet is retrieved in subnet number 2:
+ #> subnet[[2]]
+ #[1] "feat4" "feat5" "feat6"
+ 
+ # how about responses
+ # Retrieve model for the subnetwork with lowest cost function value
+ # means, standard devations and weights for the components
+ if (!is.null(subnets)) {
+ m <- get.model.parameters(res, subnet.id = "Subnet-2")
+ 
+ # order retrieved and real response means by the first feature 
+ # (to ensure responses are listed in the same order)
+ # and compare deviation from correct solution
+ ord.obs <- order(m$mu[,1])
+ ord.real <- order(mu.real[,1])
+ 
+ print(paste("Correlation between real and observed responses:", cor(as.vector(m$mu[ord.obs,]), as.vector(mu.real[ord.real,]))))
+ 
+ # all real variances are 1, compare to observed ones
+ print(paste("Maximum deviation from real variances: ", max(abs(rv - range(m$sd))/rv)))
+ 
+ # weights deviate somewhat, this is likely due to relatively small sample size
+ #print("Maximum deviation from real weights: ")
+ #print( (w.real[ord.real] - m$w[ord.obs])/w.real[ord.real])
+ 
+ print("estimated and real mean matrices")
+ print(m$mu[ord.obs,])
+ print(mu.real[ord.real,])
+ 
+ }
+ 
+ }
> 
> proc.time()
   user  system elapsed 
  0.248   0.060   0.284 

netresponse.Rcheck/tests/validate.pca.basis.Rout


R version 4.1.0 (2021-05-18) -- "Camp Pontanezen"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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.

> 
> skip <- FALSE
> 
> if (!skip) {
+ # Visualization
+ 
+ library(netresponse)
+ 
+ #fs <- list.files("~/Rpackages/netresponse/netresponse/R/", full.names = T); for (f in fs) {source(f)}
+ 
+ source("toydata2.R")
+ 
+ # --------------------------------------------------------------------
+ 
+ set.seed(4243)
+ mixture.method <- "bic"
+ 
+ # --------------------------------------------------------------------
+ 
+ res <- detect.responses(D, verbose = TRUE, max.responses = 10, 
+ 	   		       mixture.method = mixture.method, information.criterion = "BIC", 
+ 			       merging.threshold = 1, bic.threshold = 10, pca.basis = FALSE)
+ 
+ res.pca <- detect.responses(D, verbose = TRUE, max.responses = 10, mixture.method = mixture.method, information.criterion = "BIC", merging.threshold = 1, bic.threshold = 10, pca.basis = TRUE)
+ 
+ # --------------------------------------------------------------------
+ 
+ k <- 1
+ 
+ # Incorrect VDP: two modes detected
+ # Correct BIC: single mode detected
+ subnet.id <- names(get.subnets(res))[[k]]
+ 
+ # Correct: single mode detected (VDP & BIC)
+ subnet.id.pca <- names(get.subnets(res.pca))[[k]]
+ 
+ # --------------------------------------------------------------------------------------------------
+ 
+ vis1 <- plot_responses(res, subnet.id, plot_mode = "pca", main = paste("NoPCA; NoDM"))
+ vis2 <- plot_responses(res, subnet.id, plot_mode = "pca", datamatrix = D, main = "NoPCA, DM")
+ vis3 <- plot_responses(res.pca, subnet.id.pca, plot_mode = "pca", main = "PCA, NoDM")
+ vis4 <- plot_responses(res.pca, subnet.id.pca, plot_mode = "pca", datamatrix = D, main = "PCA, DM")
+ 
+ # With original data: VDP overlearns; BIC works; with full covariance data 
+ # With PCA basis: modes detected ok with both VDP and BIC.
+ 
+ # ------------------------------------------------------------------------
+ 
+ # TODO
+ # pca.plot(res, subnet.id)
+ # plot_subnet(res, subnet.id) 
+ }
Loading required package: Rgraphviz
Loading required package: graph
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

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

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

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

    IQR, mad, sd, var, xtabs

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

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
    pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
    tapply, union, unique, unsplit, which.max, which.min

Loading required package: grid
Loading required package: minet
Loading required package: mclust
Package 'mclust' version 5.4.7
Type 'citation("mclust")' for citing this R package in publications.
Loading required package: reshape2

netresponse (C) 2008-2020 Leo Lahti et al.

https://github.com/antagomir/netresponse
No network provided in function call: assuming fully connected nodes.
convert the network into edge matrix
removing self-links
matching the features between network and datamatrix
Filter the network to only keep the edges with highest mutual information
1 / 5
2 / 5
3 / 5
4 / 5
5 / 5
Compute cost for each variable
Computing model for node 1 / 6
Computing model for node 2 / 6
Computing model for node 3 / 6
Computing model for node 4 / 6
Computing model for node 5 / 6
Computing model for node 6 / 6
independent models done
Computing delta values for edge  1 / 15 

Computing delta values for edge  2 / 15 

Computing delta values for edge  3 / 15 

Computing delta values for edge  4 / 15 

Computing delta values for edge  5 / 15 

Computing delta values for edge  6 / 15 

Computing delta values for edge  7 / 15 

Computing delta values for edge  8 / 15 

Computing delta values for edge  9 / 15 

Computing delta values for edge  10 / 15 

Computing delta values for edge  11 / 15 

Computing delta values for edge  12 / 15 

Computing delta values for edge  13 / 15 

Computing delta values for edge  14 / 15 

Computing delta values for edge  15 / 15 

Combining groups,  6  group(s) left...

Combining groups,  5  group(s) left...

Combining groups,  4  group(s) left...

Combining groups,  3  group(s) left...

No network provided in function call: assuming fully connected nodes.
convert the network into edge matrix
removing self-links
matching the features between network and datamatrix
Filter the network to only keep the edges with highest mutual information
1 / 5
2 / 5
3 / 5
4 / 5
5 / 5
Compute cost for each variable
Computing model for node 1 / 6
Computing model for node 2 / 6
Computing model for node 3 / 6
Computing model for node 4 / 6
Computing model for node 5 / 6
Computing model for node 6 / 6
independent models done
Computing delta values for edge  1 / 15 

Computing delta values for edge  2 / 15 

Computing delta values for edge  3 / 15 

Computing delta values for edge  4 / 15 

Computing delta values for edge  5 / 15 

Computing delta values for edge  6 / 15 

Computing delta values for edge  7 / 15 

Computing delta values for edge  8 / 15 

Computing delta values for edge  9 / 15 

Computing delta values for edge  10 / 15 

Computing delta values for edge  11 / 15 

Computing delta values for edge  12 / 15 

Computing delta values for edge  13 / 15 

Computing delta values for edge  14 / 15 

Computing delta values for edge  15 / 15 

Combining groups,  6  group(s) left...

Combining groups,  5  group(s) left...

Combining groups,  4  group(s) left...

Combining groups,  3  group(s) left...

Warning messages:
1: In xtfrm.data.frame(x) : cannot xtfrm data frames
2: In xtfrm.data.frame(x) : cannot xtfrm data frames
3: In xtfrm.data.frame(x) : cannot xtfrm data frames
4: In xtfrm.data.frame(x) : cannot xtfrm data frames
5: In xtfrm.data.frame(x) : cannot xtfrm data frames
6: In xtfrm.data.frame(x) : cannot xtfrm data frames
7: In xtfrm.data.frame(x) : cannot xtfrm data frames
8: In xtfrm.data.frame(x) : cannot xtfrm data frames
9: In xtfrm.data.frame(x) : cannot xtfrm data frames
10: In xtfrm.data.frame(x) : cannot xtfrm data frames
> 
> proc.time()
   user  system elapsed 
 25.370   0.430  25.801 

netresponse.Rcheck/tests/vdpmixture.Rout


R version 4.1.0 (2021-05-18) -- "Camp Pontanezen"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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.

> 
> # 1. vdp.mixt: moodien loytyminen eri dimensiolla, naytemaarilla ja komponenteilla
> #   -> ainakin nopea check
> 
> #######################################################################
> 
> # Generate random data from five Gaussians. 
> # Detect modes with vdp-gm. 
> # Plot data points and detected clusters with variance ellipses
> 
> #######################################################################
> 
> library(netresponse)
Loading required package: Rgraphviz
Loading required package: graph
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

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

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

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

    IQR, mad, sd, var, xtabs

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

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
    pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
    tapply, union, unique, unsplit, which.max, which.min

Loading required package: grid
Loading required package: minet
Loading required package: mclust
Package 'mclust' version 5.4.7
Type 'citation("mclust")' for citing this R package in publications.
Loading required package: reshape2

netresponse (C) 2008-2020 Leo Lahti et al.

https://github.com/antagomir/netresponse
> #source("~/Rpackages/netresponse/netresponse/R/detect.responses.R")
> #source("~/Rpackages/netresponse/netresponse/R/internals.R")
> #source("~/Rpackages/netresponse/netresponse/R/vdp.mixt.R")
> #dyn.load("/home/tuli/Rpackages/netresponse/netresponse/src/netresponse.so")
> 
> 
> #########  Generate DATA #############################################
> 
> res <- generate.toydata()
> D <- res$data
> component.means <- res$means
> component.sds   <- res$sds
> sample2comp     <- res$sample2comp
> 
> ######################################################################
> 
> # Fit nonparametric Gaussian mixture model
> out <- vdp.mixt(D)
> # out <- vdp.mixt(D, c.max = 3) # try with limited number of components -> OK
> 
> ############################################################
> 
> # Compare input data and results
> 
> ord.out <- order(out$posterior$centroids[,1])
> ord.in <- order(component.means[,1])
> 
> means.out <- out$posterior$centroids[ord.out,]
> means.in <- component.means[ord.in,]
> 
> # Cluster stds and variances
> sds.out <- out$posterior$sds[ord.out,]
> sds.in  <- component.sds[ord.in,]
> vars.out <- sds.out^2
> vars.in <- sds.in^2
> 
> # Check correspondence between input and output
> if (length(means.in) == length(means.out)) {
+    cm <- cor(as.vector(means.in), as.vector(means.out))
+    csd <- cor(as.vector(sds.in), as.vector(sds.out))
+ }
> 
> # Plot results (assuming 2D)
> 
> ran <- range(c(as.vector(means.in - 2*vars.in), 
+                as.vector(means.in + 2*vars.in), 
+ 	       as.vector(means.out + 2*vars.out), 
+ 	       as.vector(means.out - 2*vars.out)))
> 
> #plot(D, pch = 20, main = paste("Cor.means:", round(cm,3), "/ Cor.sds:", round(csd,3)), xlim = ran, ylim = ran) 
> #for (ci in 1:nrow(means.out))  { add.ellipse(centroid = means.out[ci,], covmat = diag(vars.out[ci,]), col = "red") }
> #for (ci in 1:nrow(means.in))  { add.ellipse(centroid = means.in[ci,], covmat = diag(vars.in[ci,]), col = "blue") }
> 
> 
> 
> proc.time()
   user  system elapsed 
  3.884   0.241   4.106 

Example timings

netresponse.Rcheck/netresponse-Ex.timings

nameusersystemelapsed
NetResponseModel-class0.0010.0000.002
PlotMixture0.0000.0010.001
PlotMixtureBivariate0.0000.0000.001
PlotMixtureMultivariate0.0000.0000.001
PlotMixtureUnivariate000
centerData0.0020.0010.004
check.matrix000
check.network000
continuous.responses0.0000.0010.001
detect.responses0.0050.0030.008
dna0.0290.0030.032
enrichment.list.factor000
enrichment.list.factor.minimal0.0000.0000.001
factor.responses0.0010.0000.000
factor.responses.minimal0.0010.0000.001
filter.network0.0000.0010.000
find.similar.features0.0030.0030.006
generate.toydata0.0040.0010.005
get.dat-NetResponseModel-method000
get.model.parameters0.0030.0040.007
get.subnets-NetResponseModel-method0.0010.0000.001
getqofz-NetResponseModel-method0.0000.0000.001
independent.models0.0000.0010.000
list.responses.continuous.multi000
list.responses.continuous.single0.0010.0010.001
list.significant.responses000
listify.groupings0.0000.0010.000
mixture.model000
model.stats0.0030.0020.006
netresponse-package4.1370.1354.281
order.responses0.0000.0010.001
osmo0.0460.0030.051
pick.model.pairs000
pick.model.parameters000
plotPCA0.0000.0010.000
plot_associations000
plot_data000
plot_expression000
plot_matrix0.0080.0010.008
plot_response000
plot_responses000
plot_scale000
plot_subnet000
read.sif0.0010.0000.000
remove.negative.edges000
response.enrichment0.0000.0010.000
response2sample0.0040.0030.007
sample2response5.1580.0595.219
set.breaks0.0010.0000.001
toydata0.0020.0020.003
update.model.pair000
vdp.mixt0.0370.0020.040
vectorize.groupings000