Back to Multiple platform build/check report for BioC 3.14 |
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This page was generated on 2022-04-13 12:05:41 -0400 (Wed, 13 Apr 2022).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo2 | Linux (Ubuntu 20.04.4 LTS) | x86_64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4324 |
tokay2 | Windows Server 2012 R2 Standard | x64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4077 |
machv2 | macOS 10.14.6 Mojave | x86_64 | 4.1.3 (2022-03-10) -- "One Push-Up" | 4137 |
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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? for more information. - Make sure to use the following settings in order to reproduce any error or warning you see on this page. |
Package 1289/2083 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
netresponse 1.54.0 (landing page) Leo Lahti
| nebbiolo2 | Linux (Ubuntu 20.04.4 LTS) / x86_64 | OK | OK | OK | |||||||||
tokay2 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK | |||||||||
machv2 | macOS 10.14.6 Mojave / x86_64 | OK | OK | OK | OK | |||||||||
Package: netresponse |
Version: 1.54.0 |
Command: /home/biocbuild/bbs-3.14-bioc/R/bin/R CMD check --install=check:netresponse.install-out.txt --library=/home/biocbuild/bbs-3.14-bioc/R/library --no-vignettes --timings netresponse_1.54.0.tar.gz |
StartedAt: 2022-04-12 08:28:29 -0400 (Tue, 12 Apr 2022) |
EndedAt: 2022-04-12 08:30:25 -0400 (Tue, 12 Apr 2022) |
EllapsedTime: 115.9 seconds |
RetCode: 0 |
Status: OK |
CheckDir: netresponse.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.14-bioc/R/bin/R CMD check --install=check:netresponse.install-out.txt --library=/home/biocbuild/bbs-3.14-bioc/R/library --no-vignettes --timings netresponse_1.54.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.14-bioc/meat/netresponse.Rcheck’ * using R version 4.1.3 (2022-03-10) * using platform: x86_64-pc-linux-gnu (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 ‘1.54.0’ * checking package namespace information ... OK * checking package dependencies ... NOTE Depends: includes the non-default packages: 'BiocStyle', 'Rgraphviz', 'rmarkdown', 'minet', 'mclust', 'reshape2' Adding so many packages to the search path is excessive and importing selectively is preferable. * 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 ... OK * 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 * 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 ‘/home/biocbuild/bbs-3.14-bioc/meat/netresponse.Rcheck/00check.log’ for details.
netresponse.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.14-bioc/R/bin/R CMD INSTALL netresponse ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.14-bioc/R/library’ * installing *source* package ‘netresponse’ ... ** using staged installation ** libs gcc -I"/home/biocbuild/bbs-3.14-bioc/R/include" -DNDEBUG -I/usr/local/include -fpic -g -O2 -Wall -c netresponse.c -o netresponse.o netresponse.c: In function ‘mHPpost’: netresponse.c:264:15: warning: unused variable ‘prior_fields’ [-Wunused-variable] 264 | const char *prior_fields[]={"Mumu","S2mu", | ^~~~~~~~~~~~ netresponse.c: In function ‘mLogLambda’: netresponse.c:713:3: warning: ‘U_p’ may be used uninitialized in this function [-Wmaybe-uninitialized] 713 | vdp_mk_log_lambda(Mumu, S2mu, Mubar, Mutilde, | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 714 | AlphaKsi, BetaKsi, KsiAlpha, KsiBeta, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 715 | post_gamma, log_lambda, prior_alpha, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 716 | U_p, U_hat, | ~~~~~~~~~~~ 717 | datalen, dim1, dim2, data1, data2, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 718 | Ns, ncentroids, implicitnoisevar); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ netresponse.c:713:3: warning: ‘KsiBeta’ may be used uninitialized in this function [-Wmaybe-uninitialized] netresponse.c:713:3: warning: ‘KsiAlpha’ may be used uninitialized in this function [-Wmaybe-uninitialized] netresponse.c:713:3: warning: ‘BetaKsi’ may be used uninitialized in this function [-Wmaybe-uninitialized] netresponse.c:713:3: warning: ‘AlphaKsi’ may be used uninitialized in this function [-Wmaybe-uninitialized] netresponse.c:713:3: warning: ‘Mutilde’ may be used uninitialized in this function [-Wmaybe-uninitialized] netresponse.c:713:3: warning: ‘Mubar’ may be used uninitialized in this function [-Wmaybe-uninitialized] netresponse.c:713:3: warning: ‘S2mu’ may be used uninitialized in this function [-Wmaybe-uninitialized] netresponse.c:713:3: warning: ‘Mumu’ may be used uninitialized in this function [-Wmaybe-uninitialized] gcc -shared -L/home/biocbuild/bbs-3.14-bioc/R/lib -L/usr/local/lib -o netresponse.so netresponse.o -L/home/biocbuild/bbs-3.14-bioc/R/lib -lR installing to /home/biocbuild/bbs-3.14-bioc/R/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 ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (netresponse)
netresponse.Rcheck/tests/bicmixture.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up" Copyright (C) 2022 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. > # 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: BiocStyle Loading required package: Rgraphviz Loading required package: graph Loading required package: BiocGenerics Attaching package: 'BiocGenerics' 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: rmarkdown Attaching package: 'rmarkdown' The following objects are masked from 'package:BiocStyle': html_document, md_document, pdf_document Loading required package: minet Loading required package: mclust Package 'mclust' version 5.4.9 Type 'citation("mclust")' for citing this R package in publications. Loading required package: reshape2 netresponse (C) 2008-2021 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 3.271 0.183 3.437
netresponse.Rcheck/tests/mixture.model.test.multimodal.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up" Copyright (C) 2022 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(netresponse) Loading required package: BiocStyle Loading required package: Rgraphviz Loading required package: graph Loading required package: BiocGenerics Attaching package: 'BiocGenerics' 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: rmarkdown Attaching package: 'rmarkdown' The following objects are masked from 'package:BiocStyle': html_document, md_document, pdf_document Loading required package: minet Loading required package: mclust Package 'mclust' version 5.4.9 Type 'citation("mclust")' for citing this R package in publications. Loading required package: reshape2 netresponse (C) 2008-2021 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 4.565 0.211 4.760
netresponse.Rcheck/tests/mixture.model.test.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up" Copyright (C) 2022 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. > # Validate mixture models > > # Generate random data from five Gaussians. > # Detect modes > # Plot data points and detected clusters > > library(netresponse) Loading required package: BiocStyle Loading required package: Rgraphviz Loading required package: graph Loading required package: BiocGenerics Attaching package: 'BiocGenerics' 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: rmarkdown Attaching package: 'rmarkdown' The following objects are masked from 'package:BiocStyle': html_document, md_document, pdf_document Loading required package: minet Loading required package: mclust Package 'mclust' version 5.4.9 Type 'citation("mclust")' for citing this R package in publications. Loading required package: reshape2 netresponse (C) 2008-2021 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 3.224 0.201 3.411
netresponse.Rcheck/tests/mixture.model.test.singlemode.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up" Copyright (C) 2022 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. > > 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: BiocStyle Loading required package: Rgraphviz Loading required package: graph Loading required package: BiocGenerics Attaching package: 'BiocGenerics' 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: rmarkdown Attaching package: 'rmarkdown' The following objects are masked from 'package:BiocStyle': html_document, md_document, pdf_document Loading required package: minet Loading required package: mclust Package 'mclust' version 5.4.9 Type 'citation("mclust")' for citing this R package in publications. Loading required package: reshape2 netresponse (C) 2008-2021 Leo Lahti et al. https://github.com/antagomir/netresponse > > proc.time() user system elapsed 3.469 0.216 3.668
netresponse.Rcheck/tests/timing.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up" Copyright (C) 2022 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. > > # 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 0.195 0.029 0.211
netresponse.Rcheck/tests/toydata2.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up" Copyright (C) 2022 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. > # 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 0.166 0.029 0.179
netresponse.Rcheck/tests/validate.netresponse.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up" Copyright (C) 2022 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. > > 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 0.182 0.015 0.180
netresponse.Rcheck/tests/validate.pca.basis.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up" Copyright (C) 2022 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. > > 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: BiocStyle Loading required package: Rgraphviz Loading required package: graph Loading required package: BiocGenerics Attaching package: 'BiocGenerics' 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: rmarkdown Attaching package: 'rmarkdown' The following objects are masked from 'package:BiocStyle': html_document, md_document, pdf_document Loading required package: minet Loading required package: mclust Package 'mclust' version 5.4.9 Type 'citation("mclust")' for citing this R package in publications. Loading required package: reshape2 netresponse (C) 2008-2021 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 16.916 0.424 17.325
netresponse.Rcheck/tests/vdpmixture.Rout
R version 4.1.3 (2022-03-10) -- "One Push-Up" Copyright (C) 2022 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. > > # 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: BiocStyle Loading required package: Rgraphviz Loading required package: graph Loading required package: BiocGenerics Attaching package: 'BiocGenerics' 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: rmarkdown Attaching package: 'rmarkdown' The following objects are masked from 'package:BiocStyle': html_document, md_document, pdf_document Loading required package: minet Loading required package: mclust Package 'mclust' version 5.4.9 Type 'citation("mclust")' for citing this R package in publications. Loading required package: reshape2 netresponse (C) 2008-2021 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 2.794 0.217 2.995
netresponse.Rcheck/netresponse-Ex.timings
name | user | system | elapsed | |
NetResponseModel-class | 0.001 | 0.001 | 0.001 | |
PlotMixture | 0 | 0 | 0 | |
PlotMixtureBivariate | 0 | 0 | 0 | |
PlotMixtureMultivariate | 0.000 | 0.000 | 0.001 | |
PlotMixtureUnivariate | 0 | 0 | 0 | |
centerData | 0.001 | 0.000 | 0.001 | |
check.matrix | 0 | 0 | 0 | |
check.network | 0 | 0 | 0 | |
continuous.responses | 0.000 | 0.000 | 0.001 | |
detect.responses | 0.003 | 0.000 | 0.003 | |
dna | 0.019 | 0.000 | 0.018 | |
enrichment.list.factor | 0 | 0 | 0 | |
enrichment.list.factor.minimal | 0.001 | 0.000 | 0.001 | |
factor.responses | 0.000 | 0.000 | 0.001 | |
factor.responses.minimal | 0 | 0 | 0 | |
filter.network | 0 | 0 | 0 | |
find.similar.features | 0.002 | 0.000 | 0.002 | |
generate.toydata | 0.002 | 0.000 | 0.002 | |
get.dat-NetResponseModel-method | 0 | 0 | 0 | |
get.model.parameters | 0.003 | 0.000 | 0.003 | |
get.subnets-NetResponseModel-method | 0 | 0 | 0 | |
getqofz-NetResponseModel-method | 0 | 0 | 0 | |
independent.models | 0 | 0 | 0 | |
list.responses.continuous.multi | 0 | 0 | 0 | |
list.responses.continuous.single | 0.000 | 0.000 | 0.001 | |
list.significant.responses | 0 | 0 | 0 | |
listify.groupings | 0 | 0 | 0 | |
mixture.model | 0 | 0 | 0 | |
model.stats | 0.002 | 0.000 | 0.002 | |
netresponse-package | 2.684 | 0.108 | 2.791 | |
order.responses | 0.001 | 0.000 | 0.000 | |
osmo | 0.034 | 0.003 | 0.039 | |
pick.model.pairs | 0 | 0 | 0 | |
pick.model.parameters | 0 | 0 | 0 | |
plotPCA | 0 | 0 | 0 | |
plot_associations | 0.001 | 0.000 | 0.000 | |
plot_data | 0 | 0 | 0 | |
plot_expression | 0 | 0 | 0 | |
plot_matrix | 0.005 | 0.003 | 0.008 | |
plot_response | 0 | 0 | 0 | |
plot_responses | 0 | 0 | 0 | |
plot_scale | 0 | 0 | 0 | |
plot_subnet | 0 | 0 | 0 | |
read.sif | 0 | 0 | 0 | |
remove.negative.edges | 0 | 0 | 0 | |
response.enrichment | 0 | 0 | 0 | |
response2sample | 0.003 | 0.000 | 0.004 | |
sample2response | 3.431 | 0.068 | 3.499 | |
set.breaks | 0.000 | 0.000 | 0.001 | |
toydata | 0.002 | 0.000 | 0.002 | |
update.model.pair | 0 | 0 | 0 | |
vdp.mixt | 0.03 | 0.00 | 0.03 | |
vectorize.groupings | 0 | 0 | 0 | |